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Archive for the ‘Male Genetics’ Category

Genetic basis for male baldness identified in large-scale study – Medical News Today

Although common, male baldness can have negative psychological effects and some studies have even linked it to a handful of serious illnesses. New research identifies the genetic variants involved in the condition, which could eventually enable researchers to predict a person’s chances of hair loss.

Male baldness – also referred to as androgenetic alopecia or male pattern baldness (MPB) – affects a significant number of people in the United States, as the condition accounts for over 95 percent of all hair loss in men.

According to the American Hair Loss Association, two thirds of U.S. adults will be affected by MPB to a certain degree by the age of 35, and around 85 percent of men will have experienced significant hair loss by the age of 50.

A lot of these men are seriously affected by the condition, which can have a negative effect on a person’s self-image, as well as on their interpersonal relationships.

Additionally, some genetic studies have even associated MPB with negative clinical outcomes such as prostate cancer and cardiovascular disease.

A new study – led by Saskia Hagenaars and David Hill of the University of Edinburgh in the United Kingdom – explores the genetic basis for the condition. The findings were published in the journal PLOS Genetics.

Scientists analyzed the genomic and health data of more than 52,000 men enrolled in the UK Biobank – an international health resource offering health information on more than 500,000 individuals.

The team located more than 250 independent genetic regions linked to severe hair loss.

The researchers split the 52,000 participants into two groups: a so-called discovery sample of 40,000 people and a target sample of 12,000 individuals. Based on the genetic variants that separated those with no hair loss from those with severe hair loss, the team designed an algorithm aimed to predict who would develop MPB.

The algorithmic baldness predictor is based on a genetic score, and although accurate predictions are still a long way off, the results of this study might soon enable researchers to identify subgroups of the population that are particularly prone to hair loss.

In the present study, researchers found that 14 percent of the participants with a submedian genetic score had severe MPB, and 39 percent had no hair loss. By contrast, 58 percent of those scoring in the top 10 percent on the polygenic score had moderate to severe MPB.

Co-lead author Saskia Hagenaars – a Ph.D. student at the University of Edinburgh’s Centre for Cognitive Aging and Cognitive Epidemiology – comments on the findings:

“We identified hundreds of new genetic signals,” Hagenaars says. “It was interesting to find that many of the genetics signals for male pattern baldness came from the X chromosome, which men inherit from their mothers.”

The study’s other lead author, Dr. David Hill, notes that the study did not collect data on the age of baldness onset, but only on hair loss pattern. However, he adds that, “we would expect to see an even stronger genetic signal if we were able to identify those with early-onset hair loss.”

To the authors’ knowledge, this is the largest genetic study of MPB to date.

The study’s principal investigator, Dr. Riccardo Marioni, from the University of Edinburgh’s Centre for Genomic and Experimental Medicine, explains the significance of the findings:

“We are still a long way from making an accurate prediction for an individual’s hair loss pattern. However, these results take us one step closer. The findings pave the way for an improved understanding of the genetic causes of hair loss.”

Learn how a drug promises robust new hair growth.

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Genetic basis for male baldness identified in large-scale study – Medical News Today

Genetic data show mainly men migrated from the Pontic steppe to Europe 5000 years ago – Phys.Org

February 21, 2017

A new study, looking at the sex-specifically inherited X chromosome of prehistoric human remains, shows that hardly any women took part in the extensive migration from the Pontic-Caspian Steppe approximately 5,000 years ago. The great migration that brought farming practices to Europe 4,000 years earlier, on the other hand, consisted of both women and men. The difference in sex bias suggests that different social and cultural processes drove the two migrations.

Genetic data suggest that modern European ancestry represents a mosaic of ancestral contributions from multiple waves of prehistoric migration events. Recent studies of genomic variation in prehistoric human remains have demonstrated that two mass migration events are particularly important to understanding European prehistory: the Neolithic spread of agriculture from Anatolia starting around 9,000 years ago, and migration from the Pontic-Caspian Steppe around 5,000 years ago. These migrations are coincident with large social, cultural, and linguistic changes, and each has been inferred to have replaced more than half of the contemporaneous gene pool of resident Central Europeans.

Dramatic events in human prehistory can be investigated using patterns of genetic variation among the people that lived in those times. In particular, studies of differing female and male demographic histories on the basis of ancient genomes can provide information about complexities of social structures and cultural interactions in prehistoric populations.

Researchers from Uppsala and Stanford University investigated the genetic ancestry on the sex-specifically inherited X chromosome and the autosomes in 20 early Neolithic and 16 Late Neolithic/Bronze Age human remains. Contrary to previous hypotheses suggesting patrilocality (social system in which a family resides near the man’s parents) of many agricultural populations, they found no evidence of sex-biased admixture during the migration that spread farming across Europe during the early Neolithic.

For later migrations from the Pontic steppe during the early Bronze Age, however, we find a dramatic male bias. There are simply too few X-chromosomes from the migrants, which points to around ten migrating males for every migrating female, says Mattias Jakobsson, professor of Genetics at the Department of Organismal Biology, Uppsala University.

The research group found evidence of ongoing, primarily male, migration from the steppe to central Europe over a period of multiple generations, with a level of sex bias that excludes a pulse migration during a single generation.

The contrasting patterns of sex-specific migration during these two migrations suggest a view of differing cultural histories in which the Neolithic transition was driven by mass migration of both males and females in roughly equal numbersperhaps whole familieswhereas the later Bronze Age migration and cultural shift were instead driven by male migration.

Explore further: Baltic hunter-gatherers began farming without influence of migration, ancient DNA suggests

More information: “Ancient X chromosomes reveal contrasting sex bias in Neolithic and Bronze Age Eurasian migrations,” PNAS, DOI: 10.1073/pnas.1616392114 ,

New research indicates that Baltic hunter-gatherers were not swamped by migrations of early agriculturalists from the Middle East, as was the case for the rest of central and western Europe. Instead, these people probably …

( team of researchers at Ancestry, the people behind, has used genotype data gathered from user kit samples and family tree information to create maps of post-colonial North American migration patterns. …

A new research project, ‘1,000 Ancient Genomes’, seeks to map the genetic variation among 1,000 prehistoric individuals who lived in Europe and Asia between 1,000 and 50,000 years ago. This data will help researchers give …

This week, an international research team led by paleogeneticists of Johannes Gutenberg University Mainz publishes a study in the journal Proceedings of the National Academy of Sciences of the United States of America showing …

Analysis of oxygen isotopes in fossil teeth from red deer near the Adriatic Sea suggest that they migrated seasonally, which may have driven the movements of the Paleolithic hunter-gatherers that ate them, according a study …

A team of geneticists from Trinity College Dublin and archaeologists from Queen’s University Belfast has sequenced the first genomes from ancient Irish humans, and the information buried within is already answering pivotal …

A new study, looking at the sex-specifically inherited X chromosome of prehistoric human remains, shows that hardly any women took part in the extensive migration from the Pontic-Caspian Steppe approximately 5,000 years ago. …

Discovering who was a leader, or even if leaders existed, from the ruins of archaeological sites is difficult, but now a team of archaeologists and biological anthropologists, using a powerful combination of radiocarbon dating …

A previously undiscovered species of an extinct primordial giant worm with terrifying snapping jaws has been identified by an international team of scientists.

A longtime Cal Poly Pomona anthropology professor who studies violence among prehistoric people in California has been published in a prestigious journal.

Last year, headlines in The New York Times, The Atlantic, Scientific American and other outlets declared that a decades-old paleontological mystery had been solved. The “Tully monster,” an ancient animal that had long defied …

A project exploring the role of East Africa in the evolution of modern humans has amassed the largest and most diverse collection of prehistoric bone harpoons ever assembled from the area.The collection offers clues about …

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Genetic data show mainly men migrated from the Pontic steppe to Europe 5000 years ago – Phys.Org

Men inherit male pattern baldness from their mum’s side of the family … – Metro

It all comes from your X chromosome (Picture: Getty)

Getting a bit smooth up top? Judging on how you feel about it, your mum is the one you should be blaming /thanking.

Researchers at the University of Edinburgh have found that men inherit most of their baldness genes from their mums side of the family.

For what is the largest ever analysis of hair loss, scientists looked at the DNA of 52,000 men.

They identified almost 300 genes that could contribute to male pattern baldness most of which come from the X chromosome.

Saskia Hagenaars, who jointly led the research, said: We identified hundreds of new genetic signals.

It was interesting to find that many of the genetics signals for male pattern baldness came from the X chromosome, which men inherit from their mothers.

Before this research, published in PLOS Genetics, scientists had only identified a handful of genes related to baldness.

The studys principle investigator, Dr Riccardo Marioni, added: We are still a long way from making an accurate prediction for an individuals hair loss pattern.

However, these results take us one step closer.

The findings pave the way for an improved understanding of the genetic causes of hair loss.

More here:
Men inherit male pattern baldness from their mum’s side of the family … – Metro

Experts Are One Step Closer To Predicting A Man’s Risk For Hair Loss – Huffington Post

More than 200 new genetic markers linked with male pattern baldness have been identified, according to a new study from the United Kingdom.

The findings greatly increase the number of known genetic markers linked with baldness in men; a previous large study identified just eight such markers.

The researchers in the new study were also able to use their set of genetic markers to predict mens chances of severe hair loss, although the scientists noted that their results apply more to large populations of people than to any given individual.

We are still a long way from making an accurate prediction for an individuals hair-loss pattern. However, these results take us one step closer, study co-author Riccardo Marioni, of the University of Edinburghs Centre for Genomic and Experimental Medicine, said in a statement. The findings pave the way for an improved understanding of the genetic causes of hair loss, Marioni said. [5 Myths About the Male Body]

In the study, the researchers analyzed information from more than 52,000 men ages 40 to 69 years in the United Kingdom. Of these men, about 32 percent said they had no hair loss, 23 percent said they had slight hair loss, 27 percent said they had moderate hair loss and 18 percent said they had severe hair loss

The researchers then analyzed participants genomes, looking for genetic variations, known as single-nucleotide polymorphisms, or SNPs, that were linked with severe hair loss. That search revealed 287 genetic variations, located on more than 100 genes, that were linked with severe hair loss.

Many of the genetic variations were located on or near genes that have previously been linked with hair growth, hair graying or the biological structures involved in making hair, the researchers said.

Forty of the genetic variations were located on the X chromosome, which men inherit from their mothers, the researchers said. One of the genes on the X chromosome the gene for the androgen receptor, which binds to the hormone testosterone was strongly linked with severe hair loss. Previous studies have also pinpointed this gene as tied to male pattern baldness.

The researchers then created a formula, which resulted in a genetic risk score, to try to predict the chances of severe hair loss in the men. Among those men with a below-average score, 39 percent had no hair loss and 14 percent had severe hair loss. In contrast, among those with a high score that put them in the top 10 percent of those in the study, 58 percent had moderate-to-severe hair loss.

The researchers noted that in the study, they did not collect information on the age at which the men started losing their hair. The scientists said they would expect to see even stronger genetic associations with hair loss if they were able to include information about which men experienced early onset hair loss.

As more information from these participants becomes available, the researchers may be able to further refine their predictions, they said.

The study was published today (Feb. 14) in the journal PLOS Genetics.

Original article on Live Science.

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Experts Are One Step Closer To Predicting A Man’s Risk For Hair Loss – Huffington Post

Baldness linked to over 280 genes – BioNews

A new study has found over 280 genes associated with male-pattern baldness.

These genes could be used to predict a man’s chance of hair loss or possibly provide targets for drug development in the future.

The research, published in PLOS Genetics, is the largest genomic study of baldness to date. Researchers studied the DNA of more than 52,000 men aged between 4069 years old enrolled in the UK Biobank, looking for genes associated with baldness.

‘We identified hundreds of new genetic signals,’ Saskia Hagenaars, a PhD student at the University of Edinburgh and co-lead author, said. ‘It was interesting to find that many of the genetics signals for male-pattern baldness came from the X chromosome, which men inherit from their mothers.’

Many of the 287 genes linked with hair loss were related to hair growth and development. The researchers used these genes to try to predict the chance that a man will go bald, and found that almost 60 percent of those with the most number of hair loss genes showed signs of moderate to serious balding. However, the authors state that predictions for individuals are still ‘relatively crude’.

‘Data were collected on hair-loss pattern but not age of onset; we would expect to see an even stronger genetic signal if we were able to identify those with early-onset hair loss,’ said Dr David Hill, University of Edinburgh, who co-led the research.

Male-pattern baldness affects around half of all men by the age of 50. The condition is hereditary and thought to be linked to levels of a certain male sex hormone. Previous genetic studies have also associated male-pattern baldness with prostate cancer and heart disease.

The study’s principal investigator, Dr Riccardo Marioniof theUniversity of Edinburgh, said: ‘We are still a long way from making an accurate prediction for an individual’s hair-loss pattern. However, these results take us one step closer. The findings pave the way for an improved understanding of the genetic causes of hair loss.’

The study was based on information from the first release of data from the UK Biobank in 2015. The authors say that the release of data from the full cohort will enable them to further refine their predictions of male-pattern baldness and investigate its genetic basis.

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Baldness linked to over 280 genes – BioNews

More Than 200 Baldness-Linked Genetic Markers Found – Yahoo News

More than 200 new genetic markers linked with male pattern baldness have been identified, according to a new study from the United Kingdom.

The findings greatly increase the number of known genetic markers linked with baldness in men; a previous large study identified just eight such markers.

The researchers in the new study were also able to use their set of genetic markers to predict men’s chances of severe hair loss, although the scientists noted that their results apply more to large populations of people than to any given individual.

“We are still a long way from making an accurate prediction for an individual’s hair-loss pattern. However, these results take us one step closer,” study co-author Riccardo Marioni, of the University of Edinburgh’s Centre for Genomic and Experimental Medicine, said in a statement. “The findings pave the way for an improved understanding of the genetic causes of hair loss,” Marioni said. [5 Myths About the Male Body]

In the study, the researchers analyzed information from more than 52,000 men ages 40 to 69 years in the United Kingdom. Of these men, about 32 percent said they had no hair loss, 23 percent said they had slight hair loss, 27 percent said they had moderate hair loss and 18 percent said they had severe hair loss

The researchers then analyzed participants’ genomes, looking for genetic variations, known as single-nucleotide polymorphisms, or SNPs, that were linked with severe hair loss. That search revealed 287 genetic variations, located on more than 100 genes, that were linked with severe hair loss.

Many of the genetic variations were located on or near genes that have previously been linked with hair growth, hair graying or the biological structures involved in making hair, the researchers said.

Forty of the genetic variations were located on the X chromosome, which men inherit from their mothers, the researchers said. One of the genes on the X chromosome the gene for the androgen receptor, which binds to the hormone testosterone was strongly linked with severe hair loss. Previous studies have also pinpointed this gene as tied to male pattern baldness.

The researchers then created a formula, which resulted in a genetic “risk score,” to try to predict the chances of severe hair loss in the men. Among those men with a below-average score, 39 percent had no hair loss and 14 percent had severe hair loss. In contrast, among those with a high score that put them in the top 10 percent of those in the study, 58 percent had moderate-to-severe hair loss.

The researchers noted that in the study, they did not collect information on the age at which the men started losing their hair. The scientists said they would expect to see even stronger genetic associations with hair loss if they were able to include information about which men experienced early onset hair loss.

As more information from these participants becomes available, the researchers may be able to further refine their predictions, they said.

The study was published today (Feb. 14) in the journal PLOS Genetics.

Original article on Live Science.

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More Than 200 Baldness-Linked Genetic Markers Found – Yahoo News

Can Your Anxiety Impact How Long You Last In Bed? – Men’s Health

Men’s Health
Can Your Anxiety Impact How Long You Last In Bed?
Men’s Health
To rule out the influence of genetics, the researchers only studied male twins and brothers of twins. After analyzing their responses, the researchers found no link between anxiety symptoms reported in 2006 with later reports of premature ejaculation

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Can Your Anxiety Impact How Long You Last In Bed? – Men’s Health

Male Contraceptives Have A Messy History And A Bright Future – Yahoo News


Why is contraception the burden of women? Male contraception would seem to be a much easier way of having sex for fun and not sticking a woman with the baby, but its rarely been on the minds of scientists in the past. That may be about to change, especially with the recent success of Vasalgel in a clinical trial. But why did it take so long, and why is it going so slowly?

Currently contraception takes three forms when it comes to men: Withdrawal, vascetomy, or condoms. Pulling out requires experience and control, making it less than ideal for an act all about losing control. Vasectomy works, but is, well, a rather permanent solution most people dont want to resort to. And condoms generally work, and have the bonus of helping prevent STIs.

That said, contraceptive options for women tend to be riskier, healthwise. Hormonal birth control may, depending on your genetics, increase your risk of stroke, and other side effects of the pill, especially the psychological ones, had been downplayed or even covered up for years or decades. Tubal ligation is more dangerous than vasectomy, albeit only by a small margin, and also a permanent solution where one may not be wanted. And IUDs have rare, but potentially serious, risks. Simply put, biology makes it much easier for men to use contraceptives, but historically, its been the womans job.

The main issue is that where women produce one cell a month, men crank out literally over a thousand sperm per second. That makes male birth control inherently more hit-or-miss since, despite making millions of them, you only need one to get pregnant. And, it has to be said, theres also the social aspect: Men dont get pregnant, and its easier to simply stick the woman with the responsibility and walk away. The history of birth control is littered with ugly incidents where sex without babies was seen as more important than womens health.

That doesnt mean, however, that men havent been trying, and even succeeding to some degree. The ancient Greeks mixed hemp seeds and rue in alcohol to lower sperm count, a method which worked in rat studies conducted thousands of years later. Gossypol, a polymer found in cottonseed oil used for cooking, turned out to be effective, but had a high risk of permanent infertility. And recently, the folklore that papaya seeds reduce fertility turned out to be accurate.

The problem is that the fields had several high profile failures. For example, a few months ago, Facebook had a good giggle at the idea of fragile men unable to handle the side effects of an experimental set of hormonal birth control shots. But that ignored that as the study has scaled up, it had gotten more and more reports of excessively increased libido from more than a third of study participants and 20% reporting mood disorders. That meant one of two things: The drug was riskier than previously thought, or something in the trial had gone wrong.


There are, however, a host of other options. Calcium channel blockers, encouraging the immune system to attack sperm, and even an alpha blocker that simply prevents ejaculation are all out there and being tested. And noninvasive surgical options, like the aforementioned Vasalgel, which is already in human trials in India, and a treatment blasting the testicles with ultrasound to kill sperm, are also showing promise.

So whats the issue? Why is research so slow? In a word? Trust. Women have repeatedly expressed a discomfort in trusting men to be in charge of their reproductive destiny. In fact, it can even be a form of domestic violence: In 2010, 10% of men and 9% of women report theyve been the targets of reproductive coercion, in which someone is forced into a pregnancy by means of sabotaging their birth control, or being impregnated without their consent. And only recently have the courts viewed removing a condom during sex as a serious crime.

That, combined with the fears of some men that male birth control will make them less of a man, can be a difficult hurdle for some to jump. That said, men should be allowed to take more control of their reproductive destiny. And medical science finally seems ready to give them just that.

Excerpt from:
Male Contraceptives Have A Messy History And A Bright Future – Yahoo News

The impact of RABL2B gene (rs144944885) on human male infertility in patients with oligoasthenoteratozoospermia … – UroToday

Male infertility is a multifactorial disorder with impressively genetic basis; besides, sperm abnormalities are the cause of numerous cases of male infertility. In this study, we evaluated the genetic variants in exons 4 and 5 and their intron-exon boundaries in RABL2B gene in infertile men with oligoasthenoteratozoospermia (OAT) and immotile short tail sperm (ISTS) defects to define if there is any association between these variants and human male infertility.

To this purpose, DNA was extracted from peripheral blood and after PCR reaction and sequencing, the results of sequenced segments were analyzed. In the present study, 30 infertile men with ISTS defect and 30 oligoasthenoteratozoospermic infertile men were recruited. All men were of Iranian origin and it took 3years to collect patient’s samples with ISTS defect.

As a result, the 50776482 delC intronic variant (rs144944885) was identified in five patients with oligoasthenoteratozoospermia defect and one patient with ISTS defect in heterozygote form. This variant was not identified in controls. The allelic frequency of the 50776482 delC variant was significantly statistically higher in oligoasthenoteratozoospermic infertile men (p

According to the present study, 50776482 delC allele in the RABL2B gene could be a risk factor in Iranian infertile men with oligoasthenoteratozoospermia defect, but more genetic studies are required to understand the accurate role of this variant in pathogenesis of human male infertility.

Journal of assisted reproduction and genetics. 2017 Jan 30 [Epub ahead of print]

Seyedeh Hanieh Hosseini, Mohammad Ali Sadighi Gilani, Anahita Mohseni Meybodi, Marjan Sabbaghian

Department of Andrology, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, ACECR, Tehran, Iran., Department of Genetics, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, ACECR, Tehran, Iran., Department of Andrology, Reproductive Biomedicine Research Center, Royan Institute for Reproductive Biomedicine, ACECR, Tehran, Iran. .


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The impact of RABL2B gene (rs144944885) on human male infertility in patients with oligoasthenoteratozoospermia … – UroToday

Women in Data Science conference highlights female participation in male-dominated field – Daily Free Press (subscription)

Daily Free Press (subscription)
Women in Data Science conference highlights female participation in male-dominated field
Daily Free Press (subscription)
Later in the day, Caroline Uhler, a professor at MIT's Institute for Data, Systems, and Society, shared her research on weather forecasting models and her work with genetics. Audience members listened, taking notes on Uhler's data-driven research and

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Women in Data Science conference highlights female participation in male-dominated field – Daily Free Press (subscription)

Entrepreneurship Is Genetic, And South Africa Is The Ideal Environment For Young Entrepreneurs To Thrive – Huffington Post South Africa (blog)

Knowing the real South Africa is to know, and be familiar with, the ambitious entrepreneurial spirit that runs through its tributaries and flows like a river into the heart of a nation. South Africans have always been opportunistic, from J.B.M Hertzog who founded Naspers, which is now Africa’s largest company and globally the 7th largest internet company, to MTN and Discovery, both of which can now be found all over the world. We can even highlight the contributions of one of the world’s most foremost thinkers and innovators, Elon Musk, the driving force behind SpaceX.

Recently, Ventureburn did an article on the Top Entrepreneurs Under 40 in South Africa, highlighting how this spirit continues to grow and is a far cry from fading anytime soon. But what differentiates the men and women who started these companies from those of us ‘normal’ people who would not regard ourselves as entrepreneurs?

Entrepreneurs are a rare breed of humans who choose to innovate and forge their ideas into successful business from the ground up. They’re fearless and believe that what they are creating is going to change the world forever. And guess what, research shows that this could be genetic.

A recent study at Kings College in London, headed up by Scott Shane, identified that 37 to 48 per cent of the tendency to be an entrepreneur is genetic, and that the tendency to identify new business opportunities is in your genes. If you take this study as anything to go by, then this is remarkable as genetics account for almost half of what is a determining factor in becoming an entrepreneur.

What we know about genetics is that in some cases almost half of who we are is genetic, or how we are made, and the rest is down to environmental factors (in other words, what we do and how we live). This presents us all with an incredible opportunity to take control of our environment to use our genetic strengths to reach our goal. For some, and I would encourage any young South African with ambition to consider this path, that goal is entrepreneurship.

Take the environment in South Africa, for instance. South Africa is still a young country that is constantly growing, discovering who it is, and where its place in the world will be. This is what makes it the ideal environment for those predisposed, by either genetics, environment or desire, to entrepreneurship to thrive. It’s not all dependent on your genotype, but a large proportion of it could be, according to this study, and this could be what drives certain people to tackle new, exciting business ventures that other people may be dissuaded from due to fear of failure and the unknown.

This isn’t the only study that associates entrepreneurship with being genetics.

Nicos Nicolaou is a researcher who has been heading up these new discoveries that attempt to link genetics to entrepreneurship. Although they still require more research, which will come as the science around the human genome develops, their findings are interesting. They explain that there is a “single nucleotide polymorphism (rs1486011) of the DRD3 gene on chromosome 3 to be significantly associated with the tendency to be an entrepreneur. This result is the first evidence of the association of a specific gene with entrepreneurship.”

Wouldn’t you like to know if you had this gene, especially if you can already be considered an entrepreneur? I know I would, as it would be interesting to discover if my genes influenced me to start DNAFit, or any of my other business ventures.

I would also like to know if this gene is related to not requiring as much sleep as the average person – entrepreneurs never rest while there is opportunity to innovate and expand our ideas!

Going even deeper, Zhang did twin studies to find out if personality and gender play a role in the development of entrepreneurship as well. Their study can be regarded as verging on epigenetic as it uses the environmental impact, as well as genes.

It is based on “1285 pairs of identical twins (449 male and 836 female pairs) and 849 pairs of same-sex fraternal twins (283 male and 566 female pairs), we found that females have a strong genetic influence and zero shared-environmental influences on their tendency to become entrepreneurs. In contrast, males show zero genetic influence, but a large shared-environmental influence… such individuals appear to be ‘both born and made’.”

The difference in gender also make clear the notion that genes influence females and males differently, but they still eventually reach the same conclusion on their journey. As with everything, we still do not know enough about our genes to get conclusive, definite answers, and, even then, never forget environmental effects could re-direct people in a variety of ways.

How much start-up capital are you able to attain? How dedicated is your work force to your vision so that make it a success? How well-received are you not only by the market but by the influential people who rely on to believe in your brand as well?

And those are just a few factors…

Studies like the ones above do show how genetics are becoming more important than ever before when it comes to our understanding of the world. It’s not only about predisposition to disease, ancestry, and race.

We are becoming more and more capable of harnessing the power of genetics and applying it to our daily lives, and there is an opportunity to make South Africa the best environment for entrepreneurship in the world. Take the example of other great startup cities, such as Lisbon. In Lisbon, they went to great lengths to provide great access to capital, human resource, and cut red-tape for new businesses. Now, Lisbon is one of the top startup cities in the world – nominated European Capital of Entrepreneurship in 2015.

In South Africa, we have the ability to follow Lisbon, and go even further. With a talented, ambitious, and abundant workforce, great access to high quality office space and a low cost of living, we have everything the country needs to be the next Silicon Valley. Coupled with our incredible quality of life (and weather!), it seems to me that for all South Africans, this a time where nothing should be holding you back.

It’s inspirational to think that our entrepreneurial fire has only been started, and we as a country should do everything we can to foster an environment supportive of entrepreneurship and startup culture for everybody no matter how or where they were born. With this approach, we can make South Africa a world leader in both our genetic talent pool, and our fostering environment for entrepreneurship.

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Entrepreneurship Is Genetic, And South Africa Is The Ideal Environment For Young Entrepreneurs To Thrive – Huffington Post South Africa (blog)

Tortoiseshell cat – Wikipedia

Tortoiseshell is a cat coat coloring named for its similarity to tortoiseshell material. Tortoiseshell cats are almost exclusively female.[1][2][3] Male tortoiseshells are rare and are usually sterile.[4][a]

Also called torties for short, tortoiseshell cats combine two colors other than white, either closely mixed or in larger patches.[2] The colors are often described as red and black, but the “red” patches can instead be orange, yellow, or cream,[2] and the “black” can instead be chocolate, grey, tabby, or blue.[2] Tortoiseshell cats with the tabby pattern as one of their colors are sometimes referred to as a torbie.[6]

“Tortoiseshell” is typically reserved for particolored cats with relatively small or no white markings. Those that are largely white with tortoiseshell patches are described as tricolor,[2] tortoiseshell-and-white (in the United Kingdom), or calico (in Canada and the United States).[7]

Tortoiseshell markings appear in many different breeds, as well as in non-purebred domestic cats.[7] This pattern is especially preferred in the Japanese Bobtail breed,[8] and exists in the Cornish Rex group.[9]

Tortoiseshell cats have particolored coats with patches of various shades of red and black, and sometimes white. A tortoiseshell can also have splotches of orange or gold, but these colors are rarer on the breed.[4] The size of the patches can vary from a fine speckled pattern to large areas of color. Typically, the more white a cat has, the more solid the patches of color. Dilution genes may modify the coloring, lightening the fur to a mix of cream and blue, lilac or fawn; and the markings on tortoiseshell cats are usually asymmetrical.[10]

Occasionally tabby patterns of black and brown (eumelanistic) and red (phaeomelanistic) colors are also seen. These patched tabbies are often called a tortie-tabby, torbie or, with large white areas, a caliby.[10] Not uncommonly there will be a “split face” pattern with black on one side of the face and orange on the other, with a dividing line running down the bridge of the nose. Tortoiseshell coloring can also be expressed in the point pattern, referred to as a “tortie point”.[10]

Tortoiseshell and calico coats result from an interaction between genetic and developmental factors. The primary gene for coat color (B) for the colors brown, chocolate, cinnamon, etc., can be masked by the co-dominant gene for the orange color (O) which is on the X Chromosome and has two alleles, the orange (XO) and not-orange (Xo), that produce orange phaeomelanin and black eumelanin pigments, respectively. (NOTE: Typically, the X for the chromosome is assumed from context and the alleles are referred to by just the uppercase O for the orange, or lower case o for the not-orange.) The tortoiseshell and calico cats are indicated: Oo to indicate they are heterozygous on the O gene. The (B) and (O) genes can be further modified by a recessive dilute gene (dd) which softens the colors. Orange becomes cream, black becomes gray, etc. Various terms are used for specific colors, for example, gray is also called blue, orange is also called ginger. Therefore, a tortoiseshell cat may be a chocolate tortoiseshell or a blue/cream tortoiseshell or the like, based on the alleles for the (B) and (D) genes.

The cells of female cats, which like other mammalian females have two X chromosomes (XX), undergo the phenomenon of X-inactivation,[11][12] in which one or the other of the X-chromosomes is turned off at random in each cell in very early development. The inactivated X becomes a Barr body. Cells in which the chromosome carrying the orange (O) allele is inactivated express the alternative non-orange (o) allele, determined by the (B) gene. Cells in which the non-orange (o) allele is inactivated express the orange (O) allele. Pigment genes are expressed in melanocytes that migrate to the skin surface later in development. In bi-colored tortoiseshell cats, the melanocytes arrive relatively early, and the two cell types become intermingled, producing the characteristic brindled appearance consisting of an intimate mixture of orange and black cells, with occasional small diffuse spots of orange and black.

In tri-colored calico cats, a separate gene interacts developmentally with the coat color gene. This spotting gene produces white, unpigmented patches by delaying the migration of the melanocytes to the skin surface. There are a number of alleles of this gene that produce greater or lesser delays. The amount of white is artificially divided into mitted, bicolor, harlequin, and van, going from almost no white to almost completely white. In the extreme case, no melanocytes make it to the skin and the cat is entirely white (but not an albino). In intermediate cases, melanocyte migration is slowed, so that the pigment cells arrive late in development and have less time to intermingle. Observation of tri-color cats will show that, with a little white color, the orange and black patches become more defined, and with still more white, the patches become completely distinct. Each patch represents a clone of cells derived from one original cell in the early embryo.[13]

A male cat, like males of other therian mammals, has only one X and one Y chromosome (XY). That X chromosome does not undergo X-inactivation, and coat color is determined by which allele is present on the X. Accordingly, the cat’s coat will be either entirely orange or non-orange. Very rarely (approximately 1 in 3,000[14]) a male tortoiseshell or calico is born. These animals typically have an extra X chromosome (XXY), a condition known in humans as Klinefelter syndrome, and their cells undergo an X-inactivation process like that in females. As in humans, these cats often are sterile because of the imbalance in sex chromosomes. Some male calico or tortoiseshell cats may be chimeras, which result from the fusion in early development of two (fraternal twin) embryos with different color genotypes. Others are mosaics, in which the XXY condition arises after conception and the cat is a mixture of cells with different numbers of X chromosomes.

In the folklore of many cultures, cats of the tortoiseshell coloration are believed to bring good luck.[15] Dating back to Celtic times, tortoiseshell cats have been perceived to bring good fortune into their homes. Even today, the Irish and Scottish believe stray tortoiseshell cats bring them luck.[16] In the United States, tortoiseshells are sometimes referred to as money cats.[17]

One study found that tortoiseshell owners frequently believe their cats have increased attitude (“tortitude”);[18] however, little scientific evidence supports this.[19] According to celebrity cat expert Jackson Galaxy, tortoiseshell cats tend to have a much more distinct personality.[20]

See the rest here:
Tortoiseshell cat – Wikipedia

Binary thought suppresses identity – The Daily Evergreen

WSU forms ask non-inclusive race and gender questions, even though these answers are not important to the evaluation of the form.

While our country has become increasingly more accepting of individuality, there are still many instances where our society is failing to adequately represent minorities.

For example, the WSU Junior Writing Portfolios (JWP) cover sheet asks students to specify their gender as either male or female, giving no option for individuals who do not identify as one or the other.

Freshman mechanical engineering major Nicklaus McHendry said that they have had difficulties with how to identify themself for others.

Ive been out as a non-binary person for many years, McHendry said. At this point (it is exhausting to see) a question with a binary male or female box on a form that I dont particularly feel I need to be asked that on.

So, why is WSU asking questions such as these on forms where specifying something such as gender or race isnt necessary? For the JWP, WSU just wants a representation of a students writing ability.

I dont feel that my gender or anyone elses should be specified on a form that doesnt have anything to do with it, McHendry said.

The director of writing assessments, Xyanthe Neider, wrote in an email that students can mark the gender that they feel most adequately represents them or they can leave the question blank.

We understand that gender is much more fluid beyond the binary male/female designators and we revisit this regularly, Neider wrote.

However, there is no indication on the form to suggest that specifying ones gender is optional.

Consequently, attempting to answer this question has left many students confused and frustrated while they ponder which of the two boxes most correctly identifies them.

Its hard not to be upset, McHendry said. In order to get through the day and not spend every waking moment of my life being bothered, angry and upset … I try to focus on things that are more important.

If they want to ask about gender, they should add the option to write it in on the JWP form, which would make certain minority students feel more accepted.

In addition to the JWP, the WSU online application for admission requires students to report their gender as either male or female. The application also asks students to report their race.

Many universities across the country consider ethnicity and gender in the admission process, which unfairly puts some students at a disadvantage and gives others the upper hand.

According to, Washington is one of eight states that currently bans public universities from considering race in admissions, a policy known as Affirmative Action.

WSU does not discriminate on the basis of race, sex, sexual orientation, gender identity/expression (or) religion, the Office for Equal Opportunity states on its website.

It is completely inappropriate to ask students to specify certain personal demographics when those responses have absolutely nothing to do with the reason the form is completed.

So, if WSU is not allowed to consider race during the application process, then why are they asking students to specify it on their application?

Emily Hogan is a freshman genetics and cell biology major from Harrington, Delaware. She can be contacted at 335-2290 or The opinions expressed in this column are not necessarily those of the staff of The Daily Evergreen or those of The Office of Student Media.

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Binary thought suppresses identity – The Daily Evergreen

The 44 Chromosome Man | Understanding Genetics

In a recent article, a doctor in China has identified a man who has 44 chromosomes instead of the usual 46. Except for his different number of chromosomes, this man is perfectly normal in every measurable way.

His chromosomes are arranged in a stable way that could be passed on if he met a nice girl who had 44 chromosomes too. And this would certainly be possible in the future given his family history.

But why doesn’t he have any problems? A loss of one let alone two chromosomes is almost always fatal because so many essential genes are lost.

In this case, he has fewer chromosomes but is actually missing very few genes. Instead, he has two chromosomes stuck to two other chromosomes. More specifically, both his chromosome 14’s are stuck to his chromosome 15’s.

So he has almost all the same genes as any other person. He just has them packaged a bit differently.

This is an important finding because it tells us about a key genetic event in human prehistory. All the evidence points to humans, like their relatives the chimpanzees, having 48 chromosomes a million or so years ago. Nowadays most humans have 46.

What happened to this 44 chromosome man shows one way that the first step in this sort of change might have happened in our past. Scientists could certainly predict something like this. But now there is proof that it can actually happen.

Note added in Proof: Here are some older papers that I missed that have very similar findings:

And the current one:

Case Report: Potential Speciation in Humans Involving Robertsonian Translocations.

His Story

So how did this man end up with 44 chromosomes? It is a story of close relatives having children together. And a chromosomal rearrangement called a balanced translocation.

A balanced translocation is when one chromosome sticks to another. Because no genes are lost in this process, it usually doesn’t have any effect. Until these folks try to have kids that is.

Usually around 2/3 of pregnancies involving one person with a balanced translocation will end in miscarriage. This has to do with how chromosomes separate when eggs and sperm are made. This process is called meiosis.

Remember, humans (and most other living things) have two copies of each chromosome. So they have two copies of chromosome 1, two copies of chromosome 2, etc. Only one chromosome from each pair gets put into any one sperm or egg. That way, when the sperm fertilizes the egg, the fetus has the right number of chromosomes.

This is where the problem starts for people with a balanced translocation. They have one unpaired chromosome and a pair with an extra chromosome. Here is what can happen in this situation:

The top row represents two potential parents. The parent on the right has a balanced translocation. There are two possible ways for the fused chromosome to line up.

In the figure, only two chromosomes are shown. Numbers 14 and 15 were chosen because these are the two that are fused in the 44 chromosome man.

The parent with the balanced translocation can make 4 different kinds of sperm or egg (the second row). As the figure shows, when the eggs and sperm combine, 1/2 of the time the fetus ends up with an extra or missing chromosome. Unless this chromosome is the X, Y or number 21, the usual result is miscarriage or being born with severe problems.

In this case it would almost certainly result in miscarriage. In fact, the 44 chromosome man’s family has a long history of miscarriages and spontaneous abortions.

To get two of the same balanced translocations, both parents need to have the same balanced translocation. This is incredibly rare. Except when the parents are related.

In this case, both parents are first cousins and they share the same translocation. When these parents try to have kids, they run into the same kinds of problems that can happen with one balanced translocation. Except that the problems are doubled. This makes for the many possibilities outlined below:

This very complicated table shows the 36 possible outcomes when two parents with the same balanced translocation attempt to have a child.

In this representation, the father’s possible sperm are shown on the top and the mother’s eggs on the side. Each pregnancy has only an 8 in 36 chance for success. And 1 out of 36 would have two of the same balanced translocation (the circled possibility).

Theoretically the 44 chromosome man should have fewer problems having children than his parents did. As this figure shows, there are no unpaired chromosomes when he and a woman with 46 chromosomes have children. But all of their kids would have a balanced translocation:

So this is how he came to have 44 chromosomes. This might also be how humans started on the road to 46 chromosomes a million or so years ago.

See the article here:
The 44 Chromosome Man | Understanding Genetics

Sex – Wikipedia

Organisms of many species are specialized into male and female varieties, each known as a sex,[1] with some falling in between being intersex. Sexual reproduction involves the combining and mixing of genetic traits: specialized cells known as gametes combine to form offspring that inherit traits from each parent. Gametes can be identical in form and function (known as isogamy), but in many cases an asymmetry has evolved such that two sex-specific types of gametes (heterogametes) exist (known as anisogamy).

Among humans and other mammals, males typically carry XY chromosomes, whereas females typically carry XX chromosomes, which are a part of the XY sex-determination system. Other animals have a sex-determination system as well, such as the ZW sex-determination system in birds, and the X0 sex-determination system in insects.

The gametes produced by an organism are determined by its sex: males produce male gametes (spermatozoa, or sperm, in animals; pollen in plants) while females produce female gametes (ova, or egg cells); individual organisms which produce both male and female gametes are termed hermaphroditic. Frequently, physical differences are associated with the different sexes of an organism; these sexual dimorphisms can reflect the different reproductive pressures the sexes experience. For instance, mate choice and sexual selection can accelerate the evolution of physical differences between the sexes.











One of the basic properties of life is reproduction, the capacity to generate new individuals, and sex is an aspect of this process. Life has evolved from simple stages to more complex ones, and so have the reproduction mechanisms. Initially the reproduction was a replicating process that consists in producing new individuals that contain the same genetic information as the original or parent individual. This mode of reproduction is called asexual, and it is still used by many species, particularly unicellular, but it is also very common in multicellular organisms.[2] In sexual reproduction, the genetic material of the offspring comes from two different individuals. As sexual reproduction developed by way of a long process of evolution, intermediates exist. Bacteria, for instance, reproduce asexually, but undergo a process by which a part of the genetic material of an individual (donor) is transferred to an other (recipient).[3]

Disregarding intermediates, the basic distinction between asexual and sexual reproduction is the way in which the genetic material is processed. Typically, prior to an asexual division, a cell duplicates its genetic information content, and then divides. This process of cell division is called mitosis. In sexual reproduction, there are special kinds of cells that divide without prior duplication of its genetic material, in a process named meiosis. The resulting cells are called gametes, and contain only half the genetic material of the parent cells. These gametes are the cells that are prepared for the sexual reproduction of the organism.[4] Sex comprises the arrangements that enable sexual reproduction, and has evolved alongside the reproduction system, starting with similar gametes (isogamy) and progressing to systems that have different gamete types, such as those involving a large female gamete (ovum) and a small male gamete (sperm).[5]

In complex organisms, the sex organs are the parts that are involved in the production and exchange of gametes in sexual reproduction. Many species, particularly animals, have sexual specialization, and their populations are divided into male and female individuals. Conversely, there are also species in which there is no sexual specialization, and the same individuals both contain masculine and feminine reproductive organs, and they are called hermaphrodites. This is very frequent in plants.[6]

Sexual reproduction first probably evolved about a billion years ago within ancestral single-celled eukaryotes.[7] The reason for the evolution of sex, and the reason(s) it has survived to the present, are still matters of debate. Some of the many plausible theories include: that sex creates variation among offspring, sex helps in the spread of advantageous traits, that sex helps in the removal of disadvantageous traits, and that sex facilitates repair of germ-line DNA.

Sexual reproduction is a process specific to eukaryotes, organisms whose cells contain a nucleus and mitochondria. In addition to animals, plants, and fungi, other eukaryotes (e.g. the malaria parasite) also engage in sexual reproduction. Some bacteria use conjugation to transfer genetic material between cells; while not the same as sexual reproduction, this also results in the mixture of genetic traits.

The defining characteristic of sexual reproduction in eukaryotes is the difference between the gametes and the binary nature of fertilization. Multiplicity of gamete types within a species would still be considered a form of sexual reproduction. However, no third gamete is known in multicellular animals.[8][9][10]

While the evolution of sex dates to the prokaryote or early eukaryote stage,[11] the origin of chromosomal sex determination may have been fairly early in eukaryotes (see Evolution of anisogamy). The ZW sex-determination system is shared by birds, some fish and some crustaceans. XY sex determination is used by most mammals,[12] but also some insects,[13] and plants (Silene latifolia).[14]X0 sex-determination is found in certain insects.

No genes are shared between the avian ZW and mammal XY chromosomes,[15] and from a comparison between chicken and human, the Z chromosome appeared similar to the autosomal chromosome 9 in human, rather than X or Y, suggesting that the ZW and XY sex-determination systems do not share an origin, but that the sex chromosomes are derived from autosomal chromosomes of the common ancestor of birds and mammals. A paper from 2004 compared the chicken Z chromosome with platypus X chromosomes and suggested that the two systems are related.[16]

Sexual reproduction in eukaryotes is a process whereby organisms form offspring that combine genetic traits from both parents. Chromosomes are passed on from one generation to the next in this process. Each cell in the offspring has half the chromosomes of the mother and half of the father.[17] Genetic traits are contained within the deoxyribonucleic acid (DNA) of chromosomesby combining one of each type of chromosomes from each parent, an organism is formed containing a doubled set of chromosomes. This double-chromosome stage is called “diploid”, while the single-chromosome stage is “haploid”. Diploid organisms can, in turn, form haploid cells (gametes) that randomly contain one of each of the chromosome pairs, via meiosis.[18] Meiosis also involves a stage of chromosomal crossover, in which regions of DNA are exchanged between matched types of chromosomes, to form a new pair of mixed chromosomes. Crossing over and fertilization (the recombining of single sets of chromosomes to make a new diploid) result in the new organism containing a different set of genetic traits from either parent.

In many organisms, the haploid stage has been reduced to just gametes specialized to recombine and form a new diploid organism; in others, the gametes are capable of undergoing cell division to produce multicellular haploid organisms. In either case, gametes may be externally similar, particularly in size (isogamy), or may have evolved an asymmetry such that the gametes are different in size and other aspects (anisogamy).[19] By convention, the larger gamete (called an ovum, or egg cell) is considered female, while the smaller gamete (called a spermatozoon, or sperm cell) is considered male. An individual that produces exclusively large gametes is female, and one that produces exclusively small gametes is male. An individual that produces both types of gametes is a hermaphrodite; in some cases hermaphrodites are able to self-fertilize and produce offspring on their own, without a second organism.[20]

Most sexually reproducing animals spend their lives as diploid organisms, with the haploid stage reduced to single cell gametes.[21] The gametes of animals have male and female formsspermatozoa and egg cells. These gametes combine to form embryos which develop into a new organism.

The male gamete, a spermatozoon (produced within a testicle), is a small cell containing a single long flagellum which propels it.[22] Spermatozoa are extremely reduced cells, lacking many cellular components that would be necessary for embryonic development. They are specialized for motility, seeking out an egg cell and fusing with it in a process called fertilization.

Female gametes are egg cells (produced within ovaries), large immobile cells that contain the nutrients and cellular components necessary for a developing embryo.[23] Egg cells are often associated with other cells which support the development of the embryo, forming an egg. In mammals, the fertilized embryo instead develops within the female, receiving nutrition directly from its mother.

Animals are usually mobile and seek out a partner of the opposite sex for mating. Animals which live in the water can mate using external fertilization, where the eggs and sperm are released into and combine within the surrounding water.[24] Most animals that live outside of water, however, must transfer sperm from male to female to achieve internal fertilization.

In most birds, both excretion and reproduction is done through a single posterior opening, called the cloacamale and female birds touch cloaca to transfer sperm, a process called “cloacal kissing”.[25] In many other terrestrial animals, males use specialized sex organs to assist the transport of spermthese male sex organs are called intromittent organs. In humans and other mammals this male organ is the penis, which enters the female reproductive tract (called the vagina) to achieve inseminationa process called sexual intercourse. The penis contains a tube through which semen (a fluid containing sperm) travels. In female mammals the vagina connects with the uterus, an organ which directly supports the development of a fertilized embryo within (a process called gestation).

Because of their motility, animal sexual behavior can involve coercive sex. Traumatic insemination, for example, is used by some insect species to inseminate females through a wound in the abdominal cavitya process detrimental to the female’s health.

Like animals, plants have developed specialized male and female gametes.[26] Within seed plants, male gametes are contained within hard coats, forming pollen. The female gametes of plants are contained within ovules; once fertilized by pollen these form seeds which, like eggs, contain the nutrients necessary for the development of the embryonic plant.

Female (left) and male (right) cones are the sex organs of pines and other conifers.

Many plants have flowers and these are the sexual organs of those plants. Flowers are usually hermaphroditic, producing both male and female gametes. The female parts, in the center of a flower, are the pistils, each unit consisting of a carpel, a style and a stigma. One or more of these reproductive units may be merged to form a single compound pistil. Within the carpels are ovules which develop into seeds after fertilization. The male parts of the flower are the stamens: these consist of long filaments arranged between the pistil and the petals that produce pollen in anthers at their tips. When a pollen grain lands upon the stigma on top of a carpel’s style, it germinates to produce a pollen tube that grows down through the tissues of the style into the carpel, where it delivers male gamete nuclei to fertilize an ovule that eventually develops into a seed.

In pines and other conifers the sex organs are conifer cones and have male and female forms. The more familiar female cones are typically more durable, containing ovules within them. Male cones are smaller and produce pollen which is transported by wind to land in female cones. As with flowers, seeds form within the female cone after pollination.

Because plants are immobile, they depend upon passive methods for transporting pollen grains to other plants. Many plants, including conifers and grasses, produce lightweight pollen which is carried by wind to neighboring plants. Other plants have heavier, sticky pollen that is specialized for transportation by insects. The plants attract these insects or larger animals such as humming birds and bats with nectar-containing flowers. These animals transport the pollen as they move to other flowers, which also contain female reproductive organs, resulting in pollination.

Most fungi reproduce sexually, having both a haploid and diploid stage in their life cycles. These fungi are typically isogamous, lacking male and female specialization: haploid fungi grow into contact with each other and then fuse their cells. In some of these cases the fusion is asymmetric, and the cell which donates only a nucleus (and not accompanying cellular material) could arguably be considered “male”.[27]

Some fungi, including baker’s yeast, have mating types that create a duality similar to male and female roles. Yeast with the same mating type will not fuse with each other to form diploid cells, only with yeast carrying the other mating type.[28]

Fungi produce mushrooms as part of their sexual reproduction. Within the mushroom diploid cells are formed, later dividing into haploid sporesthe height of the mushroom aids the dispersal of these sexually produced offspring.

The most basic sexual system is one in which all organisms are hermaphrodites, producing both male and female gametes[citation needed] this is true of some animals (e.g. snails) and the majority of flowering plants.[29] In many cases, however, specialization of sex has evolved such that some organisms produce only male or only female gametes. The biological cause for an organism developing into one sex or the other is called sex determination.

In the majority of species with sex specialization, organisms are either male (producing only male gametes) or female (producing only female gametes). Exceptions are commonfor example, the roundworm C. elegans has an hermaphrodite and a male sex (a system called androdioecy).

Sometimes an organism’s development is intermediate between male and female, a condition called intersex. Sometimes intersex individuals are called “hermaphrodite”; but, unlike biological hermaphrodites, intersex individuals are unusual cases and are not typically fertile in both male and female aspects.

In genetic sex-determination systems, an organism’s sex is determined by the genome it inherits. Genetic sex-determination usually depends on asymmetrically inherited sex chromosomes which carry genetic features that influence development; sex may be determined either by the presence of a sex chromosome or by how many the organism has. Genetic sex-determination, because it is determined by chromosome assortment, usually results in a 1:1 ratio of male and female offspring.

Humans and other mammals have an XY sex-determination system: the Y chromosome carries factors responsible for triggering male development. The “default sex,” in the absence of a Y chromosome, is female-like. Thus, XX mammals are female and XY are male. In humans, biological sex is determined by five factors present at birth: the presence or absence of a Y chromosome (which alone determines the individual’s genetic sex), the type of gonads, the sex hormones, the internal reproductive anatomy (such as the uterus in females), and the external genitalia.[30]

XY sex determination is found in other organisms, including the common fruit fly and some plants.[29] In some cases, including in the fruit fly, it is the number of X chromosomes that determines sex rather than the presence of a Y chromosome (see below).

In birds, which have a ZW sex-determination system, the opposite is true: the W chromosome carries factors responsible for female development, and default development is male.[31] In this case ZZ individuals are male and ZW are female. The majority of butterflies and moths also have a ZW sex-determination system. In both XY and ZW sex determination systems, the sex chromosome carrying the critical factors is often significantly smaller, carrying little more than the genes necessary for triggering the development of a given sex.[32]

Many insects use a sex determination system based on the number of sex chromosomes. This is called X0 sex-determinationthe 0 indicates the absence of the sex chromosome. All other chromosomes in these organisms are diploid, but organisms may inherit one or two X chromosomes. In field crickets, for example, insects with a single X chromosome develop as male, while those with two develop as female.[33] In the nematode C. elegans most worms are self-fertilizing XX hermaphrodites, but occasionally abnormalities in chromosome inheritance regularly give rise to individuals with only one X chromosomethese X0 individuals are fertile males (and half their offspring are male).[34]

Other insects, including honey bees and ants, use a haplodiploid sex-determination system.[35] In this case diploid individuals are generally female, and haploid individuals (which develop from unfertilized eggs) are male. This sex-determination system results in highly biased sex ratios, as the sex of offspring is determined by fertilization rather than the assortment of chromosomes during meiosis.

For many species, sex is not determined by inherited traits, but instead by environmental factors experienced during development or later in life. Many reptiles have temperature-dependent sex determination: the temperature embryos experience during their development determines the sex of the organism. In some turtles, for example, males are produced at lower incubation temperatures than females; this difference in critical temperatures can be as little as 12C.

Many fish change sex over the course of their lifespan, a phenomenon called sequential hermaphroditism. In clownfish, smaller fish are male, and the dominant and largest fish in a group becomes female. In many wrasses the opposite is truemost fish are initially female and become male when they reach a certain size. Sequential hermaphrodites may produce both types of gametes over the course of their lifetime, but at any given point they are either female or male.

In some ferns the default sex is hermaphrodite, but ferns which grow in soil that has previously supported hermaphrodites are influenced by residual hormones to instead develop as male.[36]

Many animals and some plants have differences between the male and female sexes in size and appearance, a phenomenon called sexual dimorphism. Sex differences in humans include, generally, a larger size and more body hair in men; women have breasts, wider hips, and a higher body fat percentage. In other species, the differences may be more extreme, such as differences in coloration or bodyweight.

Sexual dimorphisms in animals are often associated with sexual selection the competition between individuals of one sex to mate with the opposite sex.[37] Antlers in male deer, for example, are used in combat between males to win reproductive access to female deer. In many cases the male of a species is larger than the female. Mammal species with extreme sexual size dimorphism tend to have highly polygynous mating systemspresumably due to selection for success in competition with other malessuch as the elephant seals. Other examples demonstrate that it is the preference of females that drive sexual dimorphism, such as in the case of the stalk-eyed fly.[38]

Other animals, including most insects and many fish, have larger females. This may be associated with the cost of producing egg cells, which requires more nutrition than producing spermlarger females are able to produce more eggs.[39] For example, female southern black widow spiders are typically twice as long as the males.[40] Occasionally this dimorphism is extreme, with males reduced to living as parasites dependent on the female, such as in the anglerfish. Some plant species also exhibit dimorphism in which the females are significantly larger than the males, such as in the moss Dicranum[41] and the liverwort Sphaerocarpos.[42] There is some evidence that, in these genera, the dimorphism may be tied to a sex chromosome,[42][43] or to chemical signalling from females.[44]

In birds, males often have a more colourful appearance and may have features (like the long tail of male peacocks) that would seem to put the organism at a disadvantage (e.g. bright colors would seem to make a bird more visible to predators). One proposed explanation for this is the handicap principle.[45] This hypothesis says that, by demonstrating he can survive with such handicaps, the male is advertising his genetic fitness to femalestraits that will benefit daughters as well, who will not be encumbered with such handicaps.

Read more:
Sex – Wikipedia

Breast CancerPatient Version – National Cancer Institute

The breast is made up of glands called lobules that can make milk and thin tubes called ducts that carry the milk from the lobules to the nipple. Breast tissue also contains fat and connective tissue, lymph nodes, and blood vessels.

The most common type of breast cancer is ductal carcinoma, which begins in the cells of the ducts. Breast cancer can also begin in the cells of the lobules and in other tissues in the breast. Ductal carcinoma in situ is a condition in which abnormal cells are found in the lining of the ducts but they haven’t spread outside the duct. Breast cancer that has spread from where it began in the ducts or lobules to surrounding tissue is called invasive breast cancer. In inflammatory breast cancer, the breast looks red and swollen and feels warm because the cancer cells block the lymph vessels in the skin.

In the U.S., breast cancer is the second most common cancer in women after skin cancer. It can occur in both men and women, but it is rare in men. Each year there are about 100 times more new cases of breast cancer in women than in men.

Key statistics about breast cancer from the SEER Cancer Statistics Review, 1975-2010.

Excerpt from:
Breast CancerPatient Version – National Cancer Institute

Drosophila melanogaster – Wikipedia

Drosophila melanogaster is a species of fly (the taxonomic order Diptera) in the family Drosophilidae. The species is known generally as the common fruit fly or vinegar fly. Starting with Charles W. Woodworth’s proposal of the use of this species as a model organism, D. melanogaster continues to be widely used for biological research in studies of genetics, physiology, microbial pathogenesis, and life history evolution. It is typically used because it is an animal species that is easy to care for, has four pairs of chromosomes, breeds quickly, and lays many eggs.[2]D. melanogaster is a common pest in homes, restaurants, and other occupied places where food is served.[3]

Flies belonging to the family Tephritidae are also called “fruit flies”. This can cause confusion, especially in Australia and South Africa, where the Mediterranean fruit fly Ceratitis capitata is an economic pest.

Wildtype fruit flies are yellow-brown, with brick-red eyes and transverse black rings across the abdomen. They exhibit sexual dimorphism: females are about 2.5 millimeters (0.098in) long; males are slightly smaller with darker backs. Males are easily distinguished from females based on colour differences, with a distinct black patch at the abdomen, less noticeable in recently emerged flies (see fig.), and the sexcombs (a row of dark bristles on the tarsus of the first leg). Furthermore, males have a cluster of spiky hairs (claspers) surrounding the reproducing parts used to attach to the female during mating. There are extensive images at FlyBase.[4]

Egg of D. melanogaster

The D. melanogaster lifespan is about 30 days at 29C (84F).

The developmental period for D. melanogaster varies with temperature, as with many ectothermic species. The shortest development time (egg to adult), 7 days, is achieved at 28C (82F).[5][6] Development times increase at higher temperatures (11 days at 30C or 86F) due to heat stress. Under ideal conditions, the development time at 25C (77F) is 8.5 days,[5][6][7] at 18C (64F) it takes 19 days[5][6] and at 12C (54F) it takes over 50 days.[5][6] Under crowded conditions, development time increases,[8] while the emerging flies are smaller.[8][9] Females lay some 400 eggs (embryos), about five at a time, into rotting fruit or other suitable material such as decaying mushrooms and sap fluxes. The eggs, which are about 0.5mm long, hatch after 1215 hours (at 25C or 77F).[5][6] The resulting larvae grow for about 4 days (at 25C) while molting twice (into second- and third-instar larvae), at about 24 and 48 h after hatching.[5][6] During this time, they feed on the microorganisms that decompose the fruit, as well as on the sugar of the fruit itself. The mother puts feces on the egg sacs to establish the same microbial composition in the larvae’s guts which has worked positively for herself.[10] Then the larvae encapsulate in the puparium and undergo a four-day-long metamorphosis (at 25C), after which the adults eclose (emerge).[5][6]

Females become receptive to courting males at about 812 hours after emergence.[11] Specific neuron groups in females have been found to affect copulation behavior and mate choice. One such group in the abdominal nerve cord allows the female fly to pause her body movements to copulate.[12] Activation of these neurons induces the female to cease movement and orient herself towards the male to allow for mounting. If the group is inactivated, the female remains in motion and does not copulate. Various chemical signals such as male pheromones often are able to activate the group.[12]

The female fruit fly prefers a shorter duration when it comes to sex. Males, on the other hand, prefer it to last longer.[13] Males perform a sequence of five behavioral patterns to court females. First, males orient themselves while playing a courtship song by horizontally extending and vibrating their wings. Soon after, the male positions itself at the rear of the female’s abdomen in a low posture to tap and lick the female genitalia. Finally, the male curls its abdomen and attempts copulation. Females can reject males by moving away, kicking, and extruding their ovipositor.[14] Copulation lasts around 1520 minutes,[15] during which males transfer a few hundred, very long (1.76mm) sperm cells in seminal fluid to the female.[16] Females store the sperm in a tubular receptacle and in two mushroom-shaped spermathecae; sperm from multiple matings compete for fertilization. A last male precedence is believed to exist in which the last male to mate with a female sires about 80% of her offspring. This precedence was found to occur through both displacement and incapacitation.[17] The displacement is attributed to sperm handling by the female fly as multiple matings are conducted and is most significant during the first 12 days after copulation. Displacement from the seminal receptacle is more significant than displacement from the spermathecae.[17] Incapacitation of first male sperm by second male sperm becomes significant 27 days after copulation. The seminal fluid of the second male is believed to be responsible for this incapacitation mechanism (without removal of first male sperm) which takes effect before fertilization occurs.[17] The delay in effectiveness of the incapacitation mechanism is believed to be a protective mechanism that prevents a male fly from incapacitating its own sperm should it mate with the same female fly repetitively. Sensory neurons in the uterus of female D. melanogaster respond to a male protein, sex peptide, which is found in sperm.[12] This protein makes the female reluctant to copulate for about 10 days after insemination. The signal pathway leading to this change in behavior has been determined. The signal is sent to a brain region that is a homolog of the hypothalamus and the hypothalamus then controls sexual behavior and desire[12]

D. melanogaster is often used for life extension studies, such as to identify genes purported to increase lifespan when mutated.[18]

D. melanogaster females exhibit mate choice copying. When virgin females are shown other females copulating with a certain type of male, they tend to copulate more with this type of male afterwards than naive females (which have not observed the copulation of others). This behavior is sensitive to environmental conditions, and females copy less in bad weather conditions.[19]

D. melanogaster males exhibit a strong reproductive learning curve. That is, with sexual experience, these flies tend to modify their future mating behavior in multiple ways. These changes include increased selectivity for courting only intraspecifically, as well as decreased courtship times.

Sexually nave D. melanogaster males are known to spend significant time courting interspecifically, such as with D. simulans flies. Nave D. melanogaster will also attempt to court females that are not yet sexually mature, and other males. D. melanogaster males show little to no preference for D. melanogaster females over females of other species or even other male flies. However, after D. simulans or other flies incapable of copulation have rejected the males advances, D. melanogaster males are much less likely to spend time courting nonspecifically in the future. This apparent learned behavior modification seems to be evolutionarily significant, as it allows the males to avoid investing energy into futile sexual encounters.[20]

In addition, males with previous sexual experience will modify their courtship dance when attempting to mate with new females the experienced males spend less time courting and therefore have lower mating latencies, meaning that they are able to reproduce more quickly. This decreased mating latency leads to a greater mating efficiency for experienced males over nave males.[21] This modification also appears to have obvious evolutionary advantages, as increased mating efficiency is extremely important in the eyes of natural selection.

Both male and female D. melanogaster act polygamously (having multiple sexual partners at the same time).[22] In both males and females, polygamy results in a decrease in evening activity compared to virgin flies, more so in males than females.[22] Evening activity consists of the activities that the flies participate in other than mating and finding partners, such as finding food.[23] The reproductive success of males and females varies, due to the fact that a female only needs to mate once to reach maximum fertility.[23] Mating with multiple partners provides no advantage over mating with one partner, and therefore females exhibit no difference in evening activity between polygamous and monogamous individuals.[23] For males, however, mating with multiple partners increases their reproductive success by increasing the genetic diversity of their offspring.[23] This benefit of genetic diversity is an evolutionary advantage because it increases the chance that some of the offspring will have traits that increase their fitness in their environment.

The difference in evening activity between polygamous and monogamous male flies can be explained with courtship. For polygamous flies, their reproductive success increases by having offspring with multiple partners, and therefore they spend more time and energy on courting multiple females.[23] On the other hand, monogamous flies only court one female, and expend less energy doing so.[23] While it requires more energy for male flies to court multiple females, the overall reproductive benefits it produces has kept polygamy as the preferred sexual choice.[23]

It has been shown that the mechanism that affects courtship behavior in Drosophila is controlled by the oscillator neurons DN1s and LNDs.[24] Oscillation of the DN1 neurons was found to be effected by socio-sexual interactions, and is connected to mating-related decrease of evening activity.[24]

D. melanogaster was among the first organisms used for genetic analysis, and today it is one of the most widely used and genetically best-known of all eukaryotic organisms. All organisms use common genetic systems; therefore, comprehending processes such as transcription and replication in fruit flies helps in understanding these processes in other eukaryotes, including humans.[25]

Thomas Hunt Morgan began using fruit flies in experimental studies of heredity at Columbia University in 1910 in a laboratory known as the Fly Room. The Fly Room was cramped with eight desks, each occupied by students and their experiments. They started off experiments using milk bottles to rear the fruit flies and handheld lenses for observing their traits. The lenses were later replaced by microscopes, which enhanced their observations. Morgan and his students eventually elucidated many basic principles of heredity, including sex-linked inheritance, epistasis, multiple alleles, and gene mapping.[25]

D. melanogaster is one of the most studied organisms in biological research, particularly in genetics and developmental biology. The several reasons include:

Genetic markers are commonly used in Drosophila research, for example within balancer chromosomes or P-element inserts, and most phenotypes are easily identifiable either with the naked eye or under a microscope. In the list of example common markers below, the allele symbol is followed by the name of the gene affected and a description of its phenotype. (Note: Recessive alleles are in lower case, while dominant alleles are capitalised.)

Drosophila genes are traditionally named after the phenotype they cause when mutated. For example, the absence of a particular gene in Drosophila will result in a mutant embryo that does not develop a heart. Scientists have thus called this gene tinman, named after the Oz character of the same name.[27] This system of nomenclature results in a wider range of gene names than in other organisms.

The genome of D. melanogaster (sequenced in 2000, and curated at the FlyBase database[26]) contains four pairs of chromosomes: an X/Y pair, and three autosomes labeled 2, 3, and 4. The fourth chromosome is so tiny, it is often ignored, aside from its important eyeless gene. The D. melanogaster sequenced genome of 139.5 million base pairs has been annotated[28] and contains around 15,682 genes according to Ensemble release 73. More than 60% of the genome appears to be functional non-protein-coding DNA[29] involved in gene expression control. Determination of sex in Drosophila occurs by the X:A ratio of X chromosomes to autosomes, not because of the presence of a Y chromosome as in human sex determination. Although the Y chromosome is entirely heterochromatic, it contains at least 16 genes, many of which are thought to have male-related functions.[30]

A March 2000 study by National Human Genome Research Institute comparing the fruit fly and human genome estimated that about 60% of genes are conserved between the two species.[31] About 75% of known human disease genes have a recognizable match in the genome of fruit flies,[32] and 50% of fly protein sequences have mammalian homologs. An online database called Homophila is available to search for human disease gene homologues in flies and vice versa.[33]Drosophila is being used as a genetic model for several human diseases including the neurodegenerative disorders Parkinson’s, Huntington’s, spinocerebellar ataxia and Alzheimer’s disease. The fly is also being used to study mechanisms underlying aging and oxidative stress, immunity, diabetes, and cancer, as well as drug abuse.

Embryogenesis in Drosophila has been extensively studied, as its small size, short generation time, and large brood size makes it ideal for genetic studies. It is also unique among model organisms in that cleavage occurs in a syncytium.

During oogenesis, cytoplasmic bridges called “ring canals” connect the forming oocyte to nurse cells. Nutrients and developmental control molecules move from the nurse cells into the oocyte. In the figure to the left, the forming oocyte can be seen to be covered by follicular support cells.

After fertilization of the oocyte, the early embryo (or syncytial embryo) undergoes rapid DNA replication and 13 nuclear divisions until about 5000 to 6000 nuclei accumulate in the unseparated cytoplasm of the embryo. By the end of the eighth division, most nuclei have migrated to the surface, surrounding the yolk sac (leaving behind only a few nuclei, which will become the yolk nuclei). After the 10th division, the pole cells form at the posterior end of the embryo, segregating the germ line from the syncytium. Finally, after the 13th division, cell membranes slowly invaginate, dividing the syncytium into individual somatic cells. Once this process is completed, gastrulation starts.[34]

Nuclear division in the early Drosophila embryo happens so quickly, no proper checkpoints exist, so mistakes may be made in division of the DNA. To get around this problem, the nuclei that have made a mistake detach from their centrosomes and fall into the centre of the embryo (yolk sac), which will not form part of the fly.

The gene network (transcriptional and protein interactions) governing the early development of the fruit fly embryo is one of the best understood gene networks to date, especially the patterning along the anteroposterior (AP) and dorsoventral (DV) axes (See under morphogenesis).[34]

The embryo undergoes well-characterized morphogenetic movements during gastrulation and early development, including germ-band extension, formation of several furrows, ventral invagination of the mesoderm, and posterior and anterior invagination of endoderm (gut), as well as extensive body segmentation until finally hatching from the surrounding cuticle into a first-instar larva.

During larval development, tissues known as imaginal discs grow inside the larva. Imaginal discs develop to form most structures of the adult body, such as the head, legs, wings, thorax, and genitalia. Cells of the imaginal disks are set aside during embryogenesis and continue to grow and divide during the larval stagesunlike most other cells of the larva, which have differentiated to perform specialized functions and grow without further cell division. At metamorphosis, the larva forms a pupa, inside which the larval tissues are reabsorbed and the imaginal tissues undergo extensive morphogenetic movements to form adult structures.

Drosophila flies have both X and Y chromosomes, as well as autosomes. Unlike humans, the Y chromosome does not confer maleness; rather, it encodes genes necessary for making sperm. Sex is instead determined by the ratio of X chromosomes to autosomes. Furthermore, each cell “decides” whether to be male or female independently of the rest of the organism, resulting in the occasional occurrence of gynandromorphs.

Three major genes are involved in determination of Drosophila sex. These are sex-lethal, sisterless, and deadpan. Deadpan is an autosomal gene which inhibits sex-lethal, while sisterless is carried on the X chromosome and inhibits the action of deadpan. An AAX cell has twice as much deadpan as sisterless, so sex-lethal will be inhibited, creating a male. However, an AAXX cell will produce enough sisterless to inhibit the action of deadpan, allowing the sex-lethal gene to be transcribed to create a female.

Later, control by deadpan and sisterless disappears and what becomes important is the form of the sex-lethal gene. A secondary promoter causes transcription in both males and females. Analysis of the cDNA has shown that different forms are expressed in males and females. Sex-lethal has been shown to affect the splicing of its own mRNA. In males, the third exon is included which encodes a stop codon, causing a truncated form to be produced. In the female version, the presence of sex-lethal causes this exon to be missed out; the other seven amino acids are produced as a full peptide chain, again giving a difference between males and females.[35]

Presence or absence of functional sex-lethal proteins now go on to affect the transcription of another protein known as doublesex. In the absence of sex-lethal, doublesex will have the fourth exon removed and be translated up to and including exon 6 (DSX-M[ale]), while in its presence the fourth exon which encodes a stop codon will produce a truncated version of the protein (DSX-F[emale]). DSX-F causes transcription of Yolk proteins 1 and 2 in somatic cells, which will be pumped into the oocyte on its production.

Unlike mammals, Drosophila flies only have innate immunity and lack an adaptive immune response. The D. melanogaster immune system can be divided into two responses: humoral and cell-mediated. The former is a systemic response mediated through the Toll and imd pathways, which are parallel systems for detecting microbes. The Toll pathway in Drosophila is known as the homologue of Toll-like pathways in mammals. Spatzle, a known ligand for the Toll pathway in flies, is produced in response to Gram-positive bacteria, parasites, and fungal infection. Upon infection, pro-Spatzle will be cleaved by protease SPE (Spatzle processing enzyme) to become active Spatzle, which then binds to the Toll receptor located on the cell surface (Fat body, hemocytes) and dimerise for activation of downstream NF-B signaling pathways. The imd pathway, though, is triggered by Gram-negative bacteria through soluble and surface receptors (PGRP-LE and LC, respectively). D. melanogaster has a “fat body”, which is thought to be homologous to the human liver. It is the primary secretory organ and produces antimicrobial peptides. These peptides are secreted into the hemolymph and bind infectious bacteria, killing them by forming pores in their cell walls. Years ago[when?] many drug companies wanted to purify these peptides and use them as antibiotics. Other than the fat body, hemocytes, the blood cells in Drosophila, are known as the homologue of mammalian monocyte/macrophages, possessing a significant role in immune responses. It is known from the literature that in response to immune challenge, hemocytes are able to secrete cytokines, for example Spatzle, to activate downstream signaling pathways in the fat body. However, the mechanism still remains unclear.

In 1971, Ron Konopka and Seymour Benzer published “Clock mutants of Drosophila melanogaster”, a paper describing the first mutations that affected an animal’s behavior. Wild-type flies show an activity rhythm with a frequency of about a day (24 hours). They found mutants with faster and slower rhythms, as well as broken rhythmsflies that move and rest in random spurts. Work over the following 30 years has shown that these mutations (and others like them) affect a group of genes and their products that comprise a biochemical or biological clock. This clock is found in a wide range of fly cells, but the clock-bearing cells that control activity are several dozen neurons in the fly’s central brain.

Since then, Benzer and others have used behavioral screens to isolate genes involved in vision, olfaction, audition, learning/memory, courtship, pain, and other processes, such as longevity.

The first learning and memory mutants (dunce, rutabaga, etc.) were isolated by William “Chip” Quinn while in Benzer’s lab, and were eventually shown to encode components of an intracellular signaling pathway involving cyclic AMP, protein kinase A, and a transcription factor known as CREB. These molecules were shown to be also involved in synaptic plasticity in Aplysia and mammals.[citation needed]

Male flies sing to the females during courtship using their wings to generate sound, and some of the genetics of sexual behavior have been characterized. In particular, the fruitless gene has several different splice forms, and male flies expressing female splice forms have female-like behavior and vice versa. The TRP channels nompC, nanchung, and inactive are expressed in sound-sensitive Johnston’s organ neurons and participate in the transduction of sound.[36][37]

Furthermore, Drosophila has been used in neuropharmacological research, including studies of cocaine and alcohol consumption. Models for Parkinson’s disease also exist for flies.[38]

Stereo images of the fly eye

The compound eye of the fruit fly contains 760 unit eyes or ommatidia, and are one of the most advanced among insects. Each ommatidium contains eight photoreceptor cells (R1-8), support cells, pigment cells, and a cornea. Wild-type flies have reddish pigment cells, which serve to absorb excess blue light so the fly is not blinded by ambient light.

Each photoreceptor cell consists of two main sections, the cell body and the rhabdomere. The cell body contains the nucleus, while the 100-m-long rhabdomere is made up of toothbrush-like stacks of membrane called microvilli. Each microvillus is 12 m in length and about 60 nm in diameter.[39] The membrane of the rhabdomere is packed with about 100 million rhodopsin molecules, the visual protein that absorbs light. The rest of the visual proteins are also tightly packed into the microvillar space, leaving little room for cytoplasm.

The photoreceptors in Drosophila express a variety of rhodopsin isoforms. The R1-R6 photoreceptor cells express rhodopsin1 (Rh1), which absorbs blue light (480nm). The R7 and R8 cells express a combination of either Rh3 or Rh4, which absorb UV light (345nm and 375nm), and Rh5 or Rh6, which absorb blue (437nm) and green (508nm) light, respectively. Each rhodopsin molecule consists of an opsin protein covalently linked to a carotenoid chromophore, 11-cis-3-hydroxyretinal.[40]

As in vertebrate vision, visual transduction in invertebrates occurs via a G protein-coupled pathway. However, in vertebrates, the G protein is transducin, while the G protein in invertebrates is Gq (dgq in Drosophila). When rhodopsin (Rh) absorbs a photon of light its chromophore, 11-cis-3-hydroxyretinal, is isomerized to all-trans-3-hydroxyretinal. Rh undergoes a conformational change into its active form, metarhodopsin. Metarhodopsin activates Gq, which in turn activates a phospholipase C (PLC) known as NorpA.[41]

PLC hydrolyzes phosphatidylinositol (4,5)-bisphosphate (PIP2), a phospholipid found in the cell membrane, into soluble inositol triphosphate (IP3) and diacylglycerol (DAG), which stays in the cell membrane. DAG or a derivative of DAG causes a calcium-selective ion channel known as transient receptor potential (TRP) to open and calcium and sodium flows into the cell. IP3 is thought to bind to IP3 receptors in the subrhabdomeric cisternae, an extension of the endoplasmic reticulum, and cause release of calcium, but this process does not seem to be essential for normal vision.[41]

Calcium binds to proteins such as calmodulin (CaM) and an eye-specific protein kinase C (PKC) known as InaC. These proteins interact with other proteins and have been shown to be necessary for shut off of the light response. In addition, proteins called arrestins bind metarhodopsin and prevent it from activating more Gq. A sodium-calcium exchanger known as CalX pumps the calcium out of the cell. It uses the inward sodium gradient to export calcium at a stoichiometry of 3 Na+/ 1 Ca++.[42]

TRP, InaC, and PLC form a signaling complex by binding a scaffolding protein called InaD. InaD contains five binding domains called PDZ domain proteins, which specifically bind the C termini of target proteins. Disruption of the complex by mutations in either the PDZ domains or the target proteins reduces the efficiency of signaling. For example, disruption of the interaction between InaC, the protein kinase C, and InaD results in a delay in inactivation of the light response.

Unlike vertebrate metarhodopsin, invertebrate metarhodopsin can be converted back into rhodopsin by absorbing a photon of orange light (580nm).

About two-thirds of the Drosophila brain is dedicated to visual processing.[43] Although the spatial resolution of their vision is significantly worse than that of humans, their temporal resolution is around 10 times better.

The wings of a fly are capable of beating up to 220 times per second.[citation needed] Flies fly via straight sequences of movement interspersed by rapid turns called saccades.[44] During these turns, a fly is able to rotate 90 in less than 50 milliseconds.[44]

Characteristics of Drosophila flight may be dominated by the viscosity of the air, rather than the inertia of the fly body, but the opposite case with inertia as the dominant force may occur.[44] However, subsequent work showed that while the viscous effects on the insect body during flight may be negligible, the aerodynamic forces on the wings themselves actually cause fruit flies’ turns to be damped viscously.[45]

Drosophila is commonly considered a pest due to its tendency to infest habitations and establishments where fruit is found; the flies may collect in homes, restaurants, stores, and other locations.[3] Removal of an infestation can be difficult, as larvae may continue to hatch in nearby fruit even as the adult population is eliminated.

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Drosophila melanogaster – Wikipedia

Quantitative genetics – Wikipedia

Quantitative genetics is a branch of population genetics that deals with phenotypes that vary continuously (in characters such as height or mass)as opposed to discretely identifiable phenotypes and gene-products (such as eye-colour, or the presence of a particular biochemical).

Both branches use the frequencies of different alleles of a gene in breeding populations (gamodemes), and combine them with concepts from simple Mendelian inheritance to analyze inheritance patterns across generations and descendant lines. While population genetics can focus on particular genes and their subsequent metabolic products, quantitative genetics focuses more on the outward phenotypes, and makes summaries only of the underlying genetics.

Due to the continuous distribution of phenotypic values, quantitative genetics must employ many other statistical methods (such as the effect size, the mean and the variance) to link phenotypes (attributes) to genotypes. Some phenotypes may be analyzed either as discrete categories or as continuous phenotypes, depending on the definition of cut-off points, or on the metric used to quantify them.[1]:2769 Mendel himself had to discuss this matter in his famous paper,[2] especially with respect to his peas attribute tall/dwarf, which actually was “length of stem”.[3][4] Analysis of quantitative trait loci, or QTL,[5][6][7] is a more recent addition to quantitative genetics, linking it more directly to molecular genetics.

In diploid organisms, the average genotypic “value” (locus value) may be defined by the allele “effect” together with a dominance effect, and also by how genes interact with genes at other loci (epistasis). The founder of quantitative genetics – Sir Ronald Fisher – perceived much of this when he proposed the first mathematics of this branch of genetics.[8]

Being a statistician, he defined the gene effects as deviations from a central valueenabling the use of statistical concepts such as mean and variance, which use this idea.[9] The central value he chose for the gene was the midpoint between the two opposing homozygotes at the one locus. The deviation from there to the “greater” homozygous genotype can be named “+a”; and therefore it is “-a” from that same midpoint to the “lesser” homozygote genotype. This is the “allele” effect mentioned above. The heterozygote deviation from the same midpoint can be named “d”, this being the “dominance” effect referred to above.[10] The diagram depicts the idea. However, in reality we measure phenotypes, and the figure also shows how observed phenotypes relate to the gene effects. Formal definitions of these effects recognize this phenotypic focus.[11][12] Epistasis has been approached statistically as interaction (i.e., inconsistencies),[13] but epigenetics suggests a new approach may be needed.

If 0a was known as “over-dominance”.[14]

Mendel’s pea attribute “length of stem” provides us with a good example.[3] Mendel stated that the tall true-breeding parents ranged from 67 feet in stem length (183 213cm), giving a median of 198cm (= P1). The short parents ranged from 0.75 – 1.25 feet in stem length (23 46cm), with a rounded median of 34cm (= P2). Their hybrid ranged from 67.5 feet in length (183229cm), with a median of 206cm (= F1). The mean of P1 and P2 is 116cm, this being the phenotypic value of the homozygotes midpoint (mp). The allele affect (a) is [P1-mp] = 82cm = -[P2-mp]. The dominance effect (d) is [F1-mp] = 90cm.[15] This historical example illustrates clearly how phenotype values and gene effects are linked.

To obtain means, variances and other statistics, both quantities and their occurrences are required. The gene effects (above) provide the framework for quantities: and the frequencies of the contrasting alleles in the fertilization gamete-pool provide the information on occurrences.

Commonly, the frequency of the allele causing “more” in the phenotype (including dominance) is given the symbol p, while the frequency of the contrasting allele is q. An initial assumption made when establishing the algebra was that the parental population was infinite and random mating, which was made simply to facilitate the derivation. The subsequent mathematical development also implied that the frequency distribution within the effective gamete-pool was uniform: there were no local perturbations where p and q varied. Looking at the diagrammatic analysis of sexual reproduction, this is the same as declaring that pP = pg = p; and similarly for q.[14] This mating system, dependent upon these assumptions, became known as “panmixia”.

Panmixia rarely actually occurs in nature,[16]:152180[17] as gamete distribution may be limited, for example by dispersal restrictions or by behaviour, or by chance sampling (those local perturbations mentioned above). It is well-known that there is a huge wastage of gametes in Nature, which is why the diagram depicts a potential gamete-pool separately to the actual gamete-pool. Only the latter sets the definitive frequencies for the zygotes: this is the true “gamodeme” (“gamo” refers to the gametes, and “deme” derives from Greek for “population”). But, under Fisher’s assumptions, the gamodeme can be effectively extended back to the potential gamete-pool, and even back to the parental base-population (the “source” population). The random sampling arising when small “actual” gamete-pools are sampled from a large “potential” gamete-pool is known as genetic drift, and is considered subsequently.

While panmixia may not be widely extant, the potential for it does occur, although it may be only ephemeral because of those local perturbations. It has been shown, for example, that the F2 derived from random fertilization of F1 individuals (an allogamous F2), following hybridization, is an origin of a new potentially panmictic population.[18][19] It has also been shown that if panmictic random fertilization occurred continually, it would maintain the same allele and genotype frequencies across each successive panmictic sexual generationthis being the Hardy Weinberg equilibrium.[13]:3439[20][21][22][23] However, as soon as genetic drift was initiated by local random sampling of gametes, the equilibrium would cease.

Male and female gametes within the actual fertilizing pool are considered usually to have the same frequencies for their corresponding alleles. (Exceptions have been considered.) This means that when p male gametes carrying the A allele randomly fertilize p female gametes carrying that same allele, the resulting zygote has genotype AA, and, under random fertilization, the combination occurs with a frequency of p x p (= p2). Similarly, the zygote aa occurs with a frequency of q2. Heterozygotes (Aa) can arise in two ways: when p male (A allele) randomly fertilize q female (a allele) gametes, and vice versa. The resulting frequency for the heterozygous zygotes is thus 2pq.[13]:32 Notice that such a population is never more than half heterozygous, this maximum occurring when p=q= 0.5.

In summary then, under random fertilization, the zygote (genotype) frequencies are the quadratic expansion of the gametic (allelic) frequencies: ( p + q ) 2 = p 2 + 2 p q + q 2 = 1 {textstyle (p+q)^{2}=p^{2}+2pq+q^{2}=1} . (The “=1” states that the frequencies are in fraction form, not percentages; and that there are no omissions within the framework proposed.)

Notice that “random fertilization” and “panmixia” are not synonyms.

Mendel’s pea experiments were constructed by establishing true-breeding parents with “opposite” phenotypes for each attribute.[3] This meant that each opposite parent was homozygous for its respective allele only. In our example, “tall vs dwarf”, the tall parent would be genotype TT with p = 1 (and q = 0); while the dwarf parent would be genotype tt with q = 1 (and p = 0). After controlled crossing, their hybrid is Tt, with p = q = . However, the frequency of this heterozygote = 1, because this is the F1 of an artificial cross: it has not arisen through random fertilization.[24] The F2 generation was produced by natural self-pollination of the F1 (with monitoring against insect contamination), resulting in p = q = being maintained. Such an F2 is said to be “autogamous”. However, the genotype frequencies (0.25 TT, 0.5 Tt, 0.25 tt) have arisen through a mating system very different from random fertilization, and therefore the use of the quadratic expansion has been avoided. The numerical values obtained were the same as those for random fertilization only because this is the special case of having originally crossed homozygous opposite parents.[25] We can notice that, because of the dominance of T- [frequency (0.25 + 0.5)] over tt [frequency 0.25], the 3:1 ratio is still obtained.

A cross such as Mendel’s, where true-breeding (largely homozygous) opposite parents are crossed in a controlled way to produce an F1, is a special case of hybrid structure. The F1 is often regarded as “entirely heterozygous” for the gene under consideration. However, this is an over-simplification and does not apply generallyfor example when individual parents are not homozygous, or when populations inter-hybridise to form hybrid swarms.[24] The general properties of intra-species hybrids (F1) and F2 (both “autogamous” and “allogamous”) are considered in a later section.

Having noticed that the pea is naturally self-pollinated, we cannot continue to use it as an example for illustrating random fertilization properties. Self-fertilization (“selfing”) is a major alternative to random fertilization, especially within Plants. Most of the Earth’s cereals are naturally self-pollinated (rice, wheat, barley, for example), as well as the pulses. Considering the millions of individuals of each of these on Earth at any time, it’s obvious that self-fertilization is at least as significant as random fertilization. Self-fertilization is the most intensive form of inbreeding, which arises whenever there is restricted independence in the genetical origins of gametes. Such reduction in independence arises if parents are already related, and/or from genetic drift or other spatial restrictions on gamete dispersal. Path analysis demonstrates that these are tantamount to the same thing.[26][27] Arising from this background, the inbreeding coefficient (often symbolized as F or f) quantifies the effect of inbreeding from whatever cause. There are several formal definitions of f, and some of these are considered in later sections. For the present, note that for a long-term self-fertilized species f = 1. Natural self-fertilized populations are not single ” pure lines “, however, but mixtures of such lines. This becomes particularly obvious when considering more than one gene at a time. Therefore, allele frequencies (p and q) other than 1 or 0 are still relevant in these cases (refer back to the Mendel Cross section). The genotype frequencies take a different form, however.

In general, the genotype frequencies become [ p 2 ( 1 f ) + p f ] {textstyle [p^{2}(1-f)+pf]} for AA and 2 p q ( 1 f ) {textstyle 2pq(1-f)} for Aa and [ q 2 ( 1 f ) + q f ] {textstyle [q^{2}(1-f)+qf]} for aa.[13]:65

Notice that the frequency of the heterozygote declines in proportion to f. When f = 1, these three frequencies become respectively p, 0 and q Conversely, when f = 0, they reduce to the random-fertilization quadratic expansion shown previously.

The population mean shifts the central reference point from the homozygote midpoint (mp) to the mean of a sexually reproduced population. This is important not only to relocate the focus into the natural world, but also to use a measure of central tendency used by Statistics/Biometrics. In particular, the square of this mean is the Correction Factor, which is used to obtain the genotypic variances later.[9]

For each genotype in turn, its allele effect is multiplied by its genotype frequency; and the products are accumulated across all genotypes in the model. Some algebraic simplification usually follows to reach a succinct result.

The contribution of AA is p 2 ( + ) a {textstyle p^{2}(+)a} , that of Aa is 2 p q d {textstyle 2pqd} , and that of aa is q 2 ( ) a {textstyle q^{2}(-)a} . Gathering together the two a terms and accumulating over all, the result is: a ( p 2 q 2 ) + 2 p q d {textstyle a(p^{2}-q^{2})+2pqd} . Simplification is achieved by noting that ( p 2 q 2 ) = ( p q ) ( p + q ) {textstyle (p^{2}-q^{2})=(p-q)(p+q)} , and by recalling that ( p + q ) = 1 {textstyle (p+q)=1} , thereby reducing the right-hand term to ( p q ) {textstyle (p-q)} .

The succinct result is therefore G = a ( p q ) + 2 p q d {textstyle G=a(p-q)+2pqd} .[14]:110

This defines the population mean as an “offset” from the homozygote midpoint (recall a and d are defined as deviations from that midpoint). The Figure depicts G across all values of p for several values of d, including one case of slight over-dominance. Notice that G is often negative, thereby emphasizing that it is itself a deviation (from mp).

Finally, to obtain the actual Population Mean in “phenotypic space”, the midpoint value is added to this offset: P = G + m p {textstyle P=G+mp} .

An example arises from data on ear length in maize.[28]:103 Assuming for now that one gene only is represented, a = 5.45cm, d = 0.12cm [virtually “0”, really], mp = 12.05cm. Further assuming that p = 0.6 and q = 0.4 in this example population, then:

G = 5.45 (0.6 – 0.4) + (0.48)0.12 = 1.15cm (rounded); and

P = 1.15 + 12.05 = 13.20cm (rounded).

The contribution of AA is p ( + a ) {textstyle p(+a)} , while that of aa is q ( a ) {textstyle q(-a)} . [See above for the frequencies.] Gathering these two a terms together leads to an immediately very simple final result:

G ( f = 1 ) = a ( p q ) {textstyle G_{(f=1)}=a(p-q)} . As before, P = G + m p {textstyle P=G+mp} .

Often, “G(f=1)” is abbreviated to “G1”.

Mendel’s peas can provide us with the allele effects and midpoint (see previously); and a mixed self-pollinated population with p = 0.6 and q = 0.4 provides example frequencies. Thus:

G(f=1) = 82 (0.6 – .04) = 59.6cm (rounded); and

P(f=1) = 59.6 + 116 = 175.6cm (rounded).

A general formula incorporates the inbreeding coefficient f, and can then accommodate any situation. The procedure is exactly the same as before, using the weighted genotype frequencies given earlier. After translation into our symbols, and further rearrangement:[13]:7778

G f = a ( q p ) + [ 2 p q d f ( 2 p q d ) ] = a ( p q ) + ( 1 f ) 2 p q d = G 0 f 2 p q d {displaystyle {begin{aligned}G_{f}&=a(q-p)+[2pqd-f(2pqd)]\&=a(p-q)+(1-f)2pqd\&=G_{0}-f 2pqdend{aligned}}}

Supposing that the maize example [given earlier] had been constrained on a holme (a narrow riparian meadow), and had partial inbreeding to the extent of f = 0.25, then, using the third version (above) of Gf:

G0.25 = 1.15 – 0.25 (0.48) 0.12 = 1.136 cm (rounded), with P0.25 = 13.194 cm (rounded).

There is hardly any effect from inbreeding in this example, which arises because there was virtually no dominance in this attribute (d 0). Examination of all three versions of Gf reveals that this would lead to trivial change in the Population mean. Where dominance was notable, however, there would be considerable change.

Genetic drift was introduced when discussing the likelihood of panmixia being widely extant as a natural fertilization pattern. [See section on Allele and Genotype frequencies.] Here the sampling of gametes from the potential gamodeme is discussed in more detail. The sampling involves random fertilization between pairs of random gametes, each of which may contain either an A or an a allele. The sampling is therefore binomial sampling.[13]:382395[14]:4963[29]:35[30]:55 Each sampling “packet” involves 2N alleles, and produces N zygotes (a “progeny” or a “line”) as a result. During the course of the reproductive period, this sampling is repeated over and over, so that the final result is a mixture of sample progenies. The result is dispersed random fertilization ( ) {displaystyle left(bigodot right)} These events, and the overall end-result, are examined here with an illustrative example.

The “base” allele frequencies of the example are those of the potential gamodeme: the frequency of A is pg = 0.75, while the frequency of a is qg = 0.25. [White label “1” in the diagram.] Five example actual gamodemes are binomially sampled out of this base (s = the number of samples = 5), and each sample is designated with an “index” k: with k = 1 …. s sequentially. (These are the sampling “packets” referred to in the previous paragraph.) The number of gametes involved in fertilization varies from sample to sample, and is given as 2Nk [at white label “2” in the diagram]. The total () number of gametes sampled overall is 52 [white label “3” in the diagram]. Because each sample has its own size, weights are needed to obtain averages (and other statistics) when obtaining the overall results. These are k = 2 N k / ( k s 2 N k ) {textstyle omega _{k}=2N_{k}/(sum _{k}^{s}2N_{k})} , and are given at white label “4” in the diagram.

Following completion of these five binomial sampling events, the resultant actual gamodemes each contained different allele frequencies(pk and qk). [These are given at white label “5” in the diagram.] This outcome is actually the genetic drift itself. Notice that two samples (k = 1 and 5) happen to have the same frequencies as the base (potential) gamodeme. Another (k = 3) happens to have the p and q “reversed”. Sample (k = 2) happens to be an “extreme” case, with pk = 0.9 and qk = 0.1; while the remaining sample (k = 4) is “middle of the range” in its allele frequencies. All of these results have arisen only by “chance”, through binomial sampling. Having occurred, however, they set in place all the downstream properties of the progenies.

Because sampling involves chance, the probabilities ( k ) of obtaining each of these samples become of interest. These binomial probabilities depend on the starting frequencies (pg and qg) and the sample size (2Nk). They are tedious to obtain,[13]:382395[30]:55 but are of considerable interest. [See white label “6” in the diagram.] The two samples (k = 1, 5), with the allele frequencies the same as in the potential gamodeme, had higher “chances” of occurring than the other samples. Their binomial probabilities did differ, however, because of their different sample sizes (2Nk). The “reversal” sample (k = 3) had a very low Probability of occurring, confirming perhaps what might be expected. The “extreme” allele frequency gamodeme (k = 2) was not “rare”, however; and the “middle of the range” sample (k=4) was rare. These same Probabilities apply also to the progeny of these fertilizations.

Here, some summarizing can begin. The overall allele frequencies in the progenies bulk are supplied by weighted averages of the appropriate frequencies of the individual samples. That is: p = k s k p k {textstyle p_{centerdot }=sum _{k}^{s}omega _{k} p_{k}} and q = k s k q k {textstyle q_{centerdot }=sum _{k}^{s}omega _{k} q_{k}} . (Notice that k is replaced by for the overall result – a common practice.)[9] The results for the example are p = 0.631 and q = 0.369 [black label “5” in the diagram]. These values are quite different to the starting ones (pg and qg) [white label “1”]. The sample allele frequencies also have variance as well as an average. This has been obtained using the sum of squares (SS) method [31] [See to the right of black label “5” in the diagram]. [Further discussion on this variance occurs in the section below on Extensive genetic drift.]

The genotype frequencies of the five sample progenies are obtained from the usual quadratic expansion of their respective allele frequencies (random fertilization). The results are given at the diagram’s white label “7” for the homozygotes, and at white label “8” for the heterozygotes. Re-arrangement in this manner prepares the way for monitoring inbreeding levels. This can be done either by examining the level of total homozygosis [(p2k + q2k) = (1 – 2pkqk)] , or by examining the level of heterozygosis (2pkqk), as they are complementary.[32] Notice that samples k= 1, 3, 5 all had the same level of heterozygosis, despite one being the “mirror image” of the others with respect to allele frequencies. The “extreme” allele-frequency case (k= 2) had the most homozygosis (least heterozygosis) of any sample. The “middle of the range” case (k= 4) had the least homozygosity (most heterozygosity): they were each equal at 0.50, in fact.

The overall summary can continue by obtaining the weighted average of the respective genotype frequencies for the progeny bulk. Thus, for AA, it is p 2 = k s k p k 2 {textstyle p_{centerdot }^{2}=sum _{k}^{s}omega _{k} p_{k}^{2}} , for Aa , it is 2 p q = k s k 2 p k q k {textstyle 2p_{centerdot }q_{centerdot }=sum _{k}^{s}omega _{k} 2p_{k}q_{k}} and for aa, it is q 2 = k s k q k 2 {textstyle q_{centerdot }^{2}=sum _{k}^{s}omega _{k} q_{k}^{2}} . The example results are given at black label “7” for the homozygotes, and at black label “8” for the heterozygote. Note that the heterozygosity mean is 0.3588, which the next section uses to examine inbreeding resulting from this genetic drift.

The next focus of interest is the dispersion itself, which refers to the “spreading apart” of the progenies’ population means. These are obtained as G k = a ( p k q k ) + 2 p k q k d {textstyle G_{k}=a(p_{k}-q_{k})+2p_{k}q_{k}d} [see section on the Population mean], for each sample progeny in turn, using the example gene effects given at white label “9” in the diagram. Then, each P k = G k + m p {textstyle P_{k}=G_{k}+mp} is obtained also [at white label “10” in the diagram]. Notice that the “best” line (k = 2) had the highest allele frequency for the “more” allele (A) (it also had the highest level of homozygosity). The worst progeny (k = 3) had the highest frequency for the “less” allele (a), which accounted for its poor performance. This “poor” line was less homozygous than the “best” line; and it shared the same level of homozygosity, in fact, as the two second-best lines (k = 1, 5). The progeny line with both the “more” and the “less” alleles present in equal frequency (k = 4) had a mean below the overall average (see next paragraph), and had the lowest level of homozygosity. These results reveal the fact that the alleles most prevalent in the “gene-pool” (also called the “germplasm”) determine performance, not the level of homozygosity per se. Binomial sampling alone effects this dispersion.

The overall summary can now be concluded by obtaining G = k s k G k {textstyle G_{centerdot }=sum _{k}^{s}omega _{k} G_{k}} and P = k s k P k {textstyle P_{centerdot }=sum _{k}^{s}omega _{k} P_{k}} . The example result for P is 36.94 (black label “10” in the diagram). This later is used to quantify inbreeding depression overall, from the gamete sampling. [See the next section.] However, recall that some “non-depressed” progeny means have been identified already (k = 1, 2, 5). This is an enigma of inbreeding – while there may be “depression” overall, there are usually superior lines among the gamodeme samplings.

Included in the overall summary were the averaqe allele frequencies in the mixture of progeny lines (p and q). These can now be used to construct a hypothetical panmictic equivalent.[13]:382395[14]:4963[29]:35 This can be regarded as a “reference” to assess the changes wrought by the gamete sampling. The example appends such a panmictic to the right of the Diagram. The frequency of AA is therefore (p)2 = 0.3979. This is less than that found in the dispersed bulk (0.4513 at black label “7”). Similarly, for aa, (q)2 = 0.1303 – again less than the equivalent in the progenies bulk (0.1898). Clearly, genetic drift has increased the overall level of homozygosis by the amount (0.6411 – 0.5342) = 0.1069. In a complementary approach, the heterozygosity could be used instead. The panmictic equivalent for Aa is 2 p q = 0.4658, which is higher than that in the sampled bulk (0.3588) [black label “8”]. The sampling has caused the heterozygosity to decrease by 0.1070, which differs trivially from the earlier estimate because of rounding errors.

The inbreeding coefficient (f) was introduced in the early section on Self Fertilization. Here, a formal definition of it is considered: f is the probability that two “same” alleles (that is A and A, or a and a), which fertilize together are of common ancestral origin – or (more formally) f is the probability that two homologous alleles are autozygous.[14][27] Consider any random gamete in the potential gamodeme that has its syngamy partner restricted by binomial sampling. The probability that that second gamete is homologous autozygous to the first is 1/(2N), the reciprocal of the gamodeme size. For the five example progenies, these quantities are 0.1, 0.0833, 0.1, 0.0833 and 0.125 respectively, and their weighted average is 0.0961. This is the inbreeding coefficient of the example progenies bulk, provided it is unbiased with respect to the full binomial distribution. An example based upon s = 5 is likely to be biased, however, when compared to an appropriate entire binomial distribution based upon the sample number (s) approaching infinity (s ). Another derived definition of f for the full Distribution is that f also equals the rise in homozygosity, which equals the fall in heterozygosity.[33] For the example, these frequency changes are 0.1069 and 0.1070, respectively. This result is different to the above, indicating that bias with respect to the full underlying distribution is present in the example. For the example itself, these latter values are the better ones to use, namely f = 0.10695.

The population mean of the equivalent panmictic is found as [a (p-q) + 2 pq d] + mp. Using the example gene effects (white label “9” in the diagram), this mean is P = {textstyle P_{centerdot }=} 37.87. The equivalent mean in the dispersed bulk is 36.94 (black label “10”), which is depressed by the amount 0.93. This is the inbreeding depression from this Genetic Drift. However, as noted previously, three progenies were not depressed (k = 1, 2, 5), and had means even greater than that of the panmictic equivalent. These are the lines a plant breeder looks for in a line selection programme.[34]

If the number of binomial samples is large (s ), then p pg and q qg. It might be queried whether panmixia would effectively re-appear under these circumstances. However, the sampling of allele frequencies has still occurred, with the result that 2p, q 0.[35] In fact, as s , the p , q 2 p g q g 2 N {textstyle sigma _{p, q}^{2}to {tfrac {p_{g}q_{g}}{2N}}} , which is the variance of the whole binomial distribution.[13]:382395[14]:4963 Furthermore, the “Wahlund equations” show that the progeny-bulk homozygote frequencies can be obtained as the sums of their respective average values (p2 or q2) plus 2p, q.[13]:382395 Likewise, the bulk heterozygote frequency is (2 p q) minus twice the 2p, q. The variance arising from the binomial sampling is conspicuously present. Thus, even when s , the progeny-bulk genotype frequencies still reveal increased homozygosis, and decreased heterozygosis, there is still dispersion of progeny means, and still inbreeding and inbreeding depression. That is, panmixia is not re-attained once lost because of genetic drift (binomial sampling). However, a new potential panmixia can be initiated via an allogamous F2 following hybridization.[36]

Previous discussion on genetic drift examined just one cycle (generation) of the process. When the sampling continues over successive generations, conspicuous changes occur in 2p, q and f. Furthermore, another “index” is needed to keep track of “time”: t = 1 …. y where y = the number of “years” (generations) considered. The methodology often is to add the current binomial increment ( = “de novo”) to what has occurred previously.[13] The entire Binomial Distribution is examined here. [There is no further benefit to be had from an abbreviated example.]

Earlier this variance ( 2p,q[35]) was seen to be:-

p , q 2 = p g q g / 2 N = p g q g ( 1 2 N ) = p g q g f = p g q g f when used in recursive equations {displaystyle {begin{aligned}sigma _{p,q}^{2}&=p_{g}q_{g} / 2N\&=p_{g}q_{g}left({frac {1}{2N}}right)\&=p_{g}q_{g} f\&=p_{g}q_{g} Delta f scriptstyle {text{when used in recursive equations}}end{aligned}}}

With the extension over time, this is also the result of the first cycle, and so is 1 2 {textstyle sigma _{1}^{2}} (for brevity). At cycle 2, this variance is generated yet again – this time becoming the de novo variance ( 2 {textstyle Delta sigma ^{2}} ) – and accumulates to what was present already – the “carry-over” variance. The second cycle variance ( 2 2 {textstyle sigma _{2}^{2}} ) is the weighted sum of these two components, the weights being 1 {textstyle 1} for the de novo and ( 1 1 2 N ) {textstyle left(1-{tfrac {1}{2N}}right)} = ( 1 f ) {textstyle left(1-Delta fright)} for the”carry-over”.


2 2 = ( 1 ) 2 + ( 1 f ) 1 2 {displaystyle sigma _{2}^{2}=left(1right) Delta sigma ^{2}+left(1-Delta fright)sigma _{1}^{2}}

( 1)

The extension to generalize to any time t , after considerable simplification, becomes:[13]:328-

t 2 = p g q g [ 1 ( 1 f ) t ] {displaystyle sigma _{t}^{2}=p_{g}q_{g}left[1-left(1-Delta fright)^{t}right]}

( 2)

Because it was this variation in allele frequencies that caused the “spreading apart” of the progenies’ means (dispersion), the change in 2t over the generations indicates the change in the level of the dispersion.

The method for examining the inbreeding coefficient is similar to that used for 2p,q. The same weights as before are used respectively for de novo f ( f ) [recall this is 1/(2N) ] and carry-over f. Therefore, f 2 = ( 1 ) f + ( 1 f ) f 1 {textstyle f_{2}=left(1right)Delta f+left(1-Delta fright)f_{1}} , which is similar to Equation (1) in the previous sub-section.

In general, after rearrangement,[13]

f t = f + ( 1 f ) f t 1 = f ( 1 f t 1 ) + f t 1 {displaystyle {begin{aligned}f_{t}&=Delta f+left(1-Delta fright)f_{t-1}\&=Delta fleft(1-f_{t-1}right)+f_{t-1}end{aligned}}}

Still further rearrangements of this general equation reveal some interesting relationships.

(A) After some simplification,[13] ( f t f t 1 ) = f ( 1 f t 1 ) = f t {textstyle left(f_{t}-f_{t-1}right)=Delta fleft(1-f_{t-1}right)=delta f_{t}} . The left-hand side is the difference between the current and previous levels of inbreeding: the change in inbreeding (ft). Notice, that this change in inbreeding (ft) is equal to the de novo inbreeding (f) only for the first cycle – when ft-1 is zero.

(B) An item of note is the (1-ft-1), which is an “index of non-inbreeding”. It is known as the panmictic index.[13][14] P t 1 = ( 1 f t 1 ) {textstyle P_{t-1}=left(1-f_{t-1}right)} .

(C) Further useful relationships emerge involving the panmictic index.[13][14]

f = f t P t 1 = 1 P t P t 1 {displaystyle {begin{aligned}Delta f&={frac {delta f_{t}}{P_{t-1}}}\&=1-{frac {P_{t}}{P_{t-1}}}end{aligned}}}

f t = 1 ( 1 1 f ) t ( 1 f 0 ) {displaystyle {begin{aligned}f_{t}&=1-left(1-1Delta fright)^{t}left(1-f_{0}right)end{aligned}}}

It is easy to overlook that random fertilization includes self-fertilization. Sewall Wright showed that a proportion 1/N of random fertilizations is actually self fertilization ( ) {displaystyle left(bigotimes right)} , with the remainder (N-1)/N being cross fertilization ( X ) {displaystyle left({mathsf {X}}right)} . Following path analysis and simplification, the new view random fertilization inbreeding was found to be: f t = f ( 1 + f t 1 ) + N 1 N f t 1 {textstyle f_{t}=Delta fleft(1+f_{t-1}right)+{tfrac {N-1}{N}}f_{t-1}} .[27][37] Upon further rearrangement, the earlier results from the binomial sampling were confirmed, along with some new arrangements. Two of these were potentially very useful, namely: (A) f t = f [ 1 + f t 1 ( 2 N 1 ) ] {textstyle f_{t}=Delta fleft[1+f_{t-1}left(2N-1right)right]} ; and (B) f t = f ( 1 f t 1 ) + f t 1 {textstyle f_{t}=Delta fleft(1-f_{t-1}right)+f_{t-1}} .

The recognition that selfing may intrinsically be a part of random fertilization leads to some issues about the use of the previous random fertilization ‘inbreeding coefficient’. Clearly, then, it is inappropriate for any species incapable of self fertilization, which includes plants with self-incompatibility mechanisms, dioecious plants, and bisexual animals. The equation of Wright was modified later to provide a version of random fertilization that involved only cross fertilization with no self fertilization. The proportion 1/N formerly due to selfing now defined the carry-over gene-drift inbreeding arising from the previous cycle. The new version is:[13]:166

f X t = f t 1 + f ( 1 + f t 2 2 f t 1 ) {displaystyle f_{{mathsf {X}}_{t}}=f_{t-1}+Delta fleft(1+f_{t-2}-2f_{t-1}right)}

The graphs to the right depict the differences between standard random fertilization RF, and random fertilization adjusted for “cross fertilization alone” CF. As can be seen, the issue is non-trivial for small gamodeme sample sizes.

It now is necessary to note that not only is “panmixia” not a synonym for “random fertilization”, but also that “random fertilization” is not a synonym for “cross fertilization”.

In the sub-section on the “The sample gamodemes – Genetic drift”, a series of gamete samplings was followed, an outcome of which was an increase in homozygosity at the expense of heterozygosity. From this viewpoint, the rise in homozygosity was due to the gamete samplings. Levels of homozygosity can be viewed also according to whether homozygotes arose allozygously or autozygously. Recall that autozygous alleles have the same allelic origin, the likelihood (frequency) of which is the inbreeding coefficient (f) by definition. The proportion arising allozygously is therefore (1-f). For the A-bearing gametes, which are present with a general frequency of p, the overall frequency of those that are autozygous is therefore (f p). Similarly, for a-bearing gametes, the autozygous frequency is (f q).[38] These two viewpoints regarding genotype frequencies must be connected to establish consistency.

Following firstly the auto/allo viewpoint, consider the allozygous component. This occurs with the frequency of (1-f), and the alleles unite according to the random fertilization quadratic expansion. Thus:

( 1 f ) [ p 0 + q 0 ] 2 = ( 1 f ) [ p 0 2 + q 0 2 ] + ( 1 f ) [ 2 p 0 q 0 ] {displaystyle left(1-fright)left[p_{0}+q_{0}right]^{2}=left(1-fright)left[p_{0}^{2}+q_{0}^{2}right]+left(1-fright)left[2p_{0}q_{0}right]}

Secondly, the sampling viewpoint is re-examined. Previously, it was noted that the decline in heterozygotes was f ( 2 p 0 q 0 ) {textstyle fleft(2p_{0}q_{0}right)} . This decline is distributed equally towards each homozygote; and is added to their basic random fertilization expectations. Therefore, the genotype frequencies are: ( p 0 2 + f p 0 q 0 ) {textstyle left(p_{0}^{2}+fp_{0}q_{0}right)} for the “AA” homozygote; ( q 0 2 + f p 0 q 0 ) {textstyle left(q_{0}^{2}+fp_{0}q_{0}right)} for the “aa” homozygote; and 2 p 0 q 0 f ( 2 p 0 q 0 ) {textstyle 2p_{0}q_{0}-fleft(2p_{0}q_{0}right)} for the heterozygote.

Thirdly, the consistency between the two previous viewpoints needs establishing. It is apparent at once [from the corresponding equations above] that the heterozygote frequency is the same in both viewpoints. However, such a straightforward result is not immediately apparent for the homozygotes. Begin by considering the AA homozygote’s final equation in the auto/allo paragraph above:- [ ( 1 f ) p 0 2 + f p 0 ] {textstyle left[left(1-fright)p_{0}^{2}+fp_{0}right]} . Expand the brackets, and follow by re-gathering [within the resultant] the two new terms with the common-factor f in them. The result is: p 0 2 f ( p 0 2 p 0 ) {textstyle p_{0}^{2}-fleft(p_{0}^{2}-p_{0}right)} . Next, for the parenthesized ” p20 “, a (1-q) is substituted for a p, the result becoming p 0 2 f [ p 0 ( 1 q 0 ) p 0 ] {textstyle p_{0}^{2}-fleft[p_{0}left(1-q_{0}right)-p_{0}right]} . Following that substitution, it is a straightforward matter of multiplying-out, simplifying and watching signs. The end result is p 0 2 + f p 0 q 0 {textstyle p_{0}^{2}+fp_{0}q_{0}} , which is exactly the result for AA in the sampling paragraph. The two viewpoints are therefore consistent for the AA homozygote. In a like manner, the consistency of the aa viewpoints can also be shown. The two viewpoints are consistent for all classes of genotypes.

In previous sections, dispersive random fertilization (genetic drift) has been considered comprehensively, and self-fertilization and hybridizing have been examined to varying degrees. The diagram to the left depicts the first two of these, along with another “spatially based” pattern: islands. This is a pattern of random fertilization featuring dispersed gamodemes, with the addition of “overlaps” in which non-dispersive random fertilization occurs. With the islands pattern, individual gamodeme sizes (2N) are observable, and overlaps (m) are minimal. This is one of Sewall Wright’s array of possibilities.[37] In addition to “spatially” based patterns of fertilization, there are others based on either “phenotypic” or “relationship” criteria. The phenotypic bases include assortative fertilization (between similar phenotypes) and disassortative fertilization (between opposite phenotypes). The relationship patterns include sib crossing, cousin crossing and backcrossingand are considered in a separate section. Self fertilization may be considered both from a spatial or relationship point of view.

The breeding population consists of s small dispersed random fertilization gamodemes of sample size 2 N k {textstyle 2N_{k}} ( k = 1 … s ) with ” overlaps ” of proportion m k {textstyle m_{k}} in which non-dispersive random fertilization occurs. The dispersive proportion is thus ( 1 m k ) {textstyle left(1-m_{k}right)} . The bulk population consists of weighted averages of sample sizes, allele and genotype frequencies and progeny means, as was done for genetic drift in an earlier section. However, each gamete sample size is reduced to allow for the overlaps, thus finding a 2 N k {textstyle 2N_{k}} effective for ( 1 m k ) {textstyle left(1-m_{k}right)} .

For brevity, the argument is followed further with the subscripts omitted. Recall that 1 2 N {textstyle {tfrac {1}{2N}}} is f {textstyle Delta f} in general. [Here, and following, the 2N refers to the previously defined sample size, not to any “islands adjusted” version.]

After simplification,[37]

i s l a n d s f = ( 1 m ) 2 2 N m 2 ( 2 N 1 ) {displaystyle ^{mathsf {islands}}Delta f={frac {left(1-mright)^{2}}{2N-m^{2}left(2N-1right)}}}

This f is also substituted into the previous inbreeding coefficient to obtain [37]

i s l a n d s f t = i s l a n d s f t + ( 1 i s l a n d s f t ) i s l a n d s f t 1 {displaystyle {^{mathsf {islands}}f_{t}}= {^{mathsf {islands}}Delta f_{t}}+left(1- {^{mathsf {islands}}Delta f_{t}}right) {^{mathsf {islands}}f_{t-1}}}

The effective overlap proportion can be obtained also,[37] as

m t = 1 [ 2 N i s l a n d s f t ( 2 N 1 ) i s l a n d s f t + 1 ] 1 2 {displaystyle m_{t}=1-left[{frac {2N {^{mathsf {islands}}Delta f_{t}}}{left(2N-1right) {^{mathsf {islands}}Delta f_{t}+1}}}right]^{tfrac {1}{2}}}

The graphs to the right show the inbreeding for a gamodeme size of 2N = 50 for ordinary dispersed random fertilization (RF) (m=0), and for four overlap levels ( m = 0.0625, 0.125, 0.25, 0.5 ) of islands random fertilization. There has indeed been reduction in the inbreeding resulting from the non-dispersed random fertilization in the overlaps. It is particularly notable as m 0.50. Sewall Wright suggested that this value should be the limit for the use of this approach.[37]

The gene-model examines the heredity pathway from the point of view of “inputs” (alleles/gametes) and “outputs” (genotypes/zygotes), with fertilization being the “process” converting one to the other. An alternative viewpoint concentrates on the “process” itself, and considers the zygote genotypes as arising from allele shuffling. In particular, it regards the results as if one allele had “substituted” for the other during the shuffle, together with a residual that deviates from this view. This formed an integral part of Fisher’s method,[8] in addition to his use of frequencies and effects to generate his genetical statistics.[14] A discursive derivation of the allele substitution alternative follows.[14]:113

Suppose that the usual random fertilization of gametes in a “base” gamodeme – consisting of p gametes (A) and q gametes (a) – is replaced by fertilization with a “flood” of gametes all containing a single allele (A or a, but not both). The zygotic results can be interpreted in terms of the “flood” allele having “substituted for” the alternative allele in the underlying “base” gamodeme. The diagram assists in following this viewpoint: the upper part pictures an A substitution, while the lower part shows an a substitution. (The diagram’s “RF allele” is the allele in the “base” gamodeme.)

Consider the upper part firstly. Because base A is present with a frequency of p, the substitute A fertilizes it with a frequency of p resulting in a zygote AA with an allele effect of a. Its contribution to the outcome, therefore, is the product ( p a ) {textstyle left(p aright)} . Similarly, when the substitute fertilizes base a (resulting in Aa with a frequency of q and heterozygote effect of d), the contribution is ( q d ) {textstyle left(q dright)} . The overall result of substitution by A is, therefore, ( p a + q d ) {textstyle left(p a+q dright)} . This is now oriented towards the population mean [see earlier section] by expressing it as a deviate from that mean: ( p a + q d ) G {textstyle left(p a+q dright)-G}

After some algebraic simplification, this becomes

A = q [ a + ( q p ) d ] {displaystyle beta _{A}=q left[a+left(q-pright)dright]}

A parallel reasoning can be applied to the lower part of the diagram, taking care with the differences in frequencies and gene effects. The result is the substitution effect of a, which is

a = p [ a + ( q p ) d ] {displaystyle beta _{a}=- pleft[a+left(q-pright)dright]}

= a + ( q p ) d {displaystyle beta =a+left(q-pright)d}

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Quantitative genetics – Wikipedia

Beefalo – Wikipedia

Beefalo, also referred to as cattalo or the American hybrid, are a fertile hybrid offspring of domestic cattle (Bos taurus), usually a male in managed breeding programs, and the American bison (Bison bison), usually a female in managed breeding programs.[1][2] The breed was created to combine the characteristics of both animals for beef production.

Beefalo are primarily cattle in genetics and appearance, with the breed association defining a full Beefalo as one with three-eighths (37.5%) bison genetics, while animals with higher percentages of bison genetics are called “bison hybrids”.

Accidental crosses were noticed as long ago as 1749 in the southern English colonies of North America. Beef and bison were first intentionally crossbred during the mid-19th century.

The first deliberate attempts to cross breed bison with cattle was made by Colonel Samuel Bedson, warden of Stoney Mountain Penitentiary, Winnipeg, in 1880. Bedson bought eight bison from a captive herd of James McKay and inter-bred them with Durham cattle. The hybrids raised by Bedson were described by naturalist Ernest Thompson Seton:[3]

The hybrid animal is [claimed] to be a great improvement on both of its progenitors, as it is more docile and a better milker than the Buffalo, but retains its hardihood, while the robe is finer, darker and more even, and the general shape of the animal is improved by the reduction of the hump and increased proportion of the hind-quarters.

After seeing thousands of cattle die in a Kansas blizzard in 1886, Charles “Buffalo” Jones, a co-founder of Garden City, Kansas, also worked to cross bison and cattle at a ranch near the future Grand Canyon National Park, with the hope the animals could survive the harsh winters.[4] He called the result “cattalo” in 1888.[5]Mossom Boyd of Bobcaygeon, Ontario first started the practice in Canada, publishing about some of his outcomes in the Journal of Heredity.[6] After his death in 1914, the Canadian government continued experiments in crossbreeding up to 1964, with little success. For example, in 1936 the Canadian government had successfully cross-bred only 30 cattalos.[7] Lawrence Boyd continues the crossbreeding work of his grandfather on a farm in Alberta.[citation needed]

It was found early on that crossing a male bison with a domestic cow would produce few offspring, but that crossing a domestic bull with a bison cow apparently solved the problem. The female offspring proved fertile, but rarely so for the males. Although the cattalo performed well, the mating problems meant the breeder had to maintain a herd of wild and difficult-to-handle bison cows.[citation needed]

In 1965, Jim Burnett of Montana produced a hybrid bull that was fertile. Soon after, Cory Skowronek of California formed the World Beefalo Association and began marketing the hybrids as a new breed. The new name, Beefalo, was meant to separate this hybrid from the problems associated with the old cattalo hybrids. The breed was eventually set at being genetically at least five-eighths Bos taurus and at most three-eighths Bison bison.

A United States Department of Agriculture study[citation needed] found Beefalo meat, like bison meat, to be lower in fat and cholesterol than standard beef cattle. The American Beefalo Association states that Beefalo are better able to tolerate cold and need less assistance calving than cattle, while retaining domestic cattle’s docile nature and fast growth rate. They damage rangeland less than cattle.[8] They also state that Beefalo meat contains 4 to 6% more protein and is more tender, flavorful, and nutritious than a standard steer.[8] Beefalo has significantly less calories, fat, and cholesterol, than beef cattle, chicken, and cod.[9]

The American Beefalo Association states that the “crossbreeds are hardier, are more economical (and less care-intensive) to nurture, and produce meat that’s superior to that of the common cow.”[8]

In 1983, the three main Beefalo registration groups reorganized under the American Beefalo World Registry. Until November 2008, there were two Beefalo associations, the American Beefalo World Registry[10] and American Beefalo International. These organizations jointly formed the American Beefalo Association, Inc., which currently operates as the registering body for Beefalo in the United States.[11]

Most current bison herds are genetically polluted or partly crossbred with cattle.[12][13][14][15] There are only four genetically unmixed American bison herds left, and only two that are also free of brucellosis, the Wind Cave bison herd that roams Wind Cave National Park, South Dakota; and the Henry Mountains herd in the Henry Mountains of Utah.[16] A herd on Catalina island, California is not genetically pure or self-sustaining.

Dr. Dirk Van Vuren, formerly of the University of Kansas, however, points out that “The bison today that carry cattle DNA look exactly like bison, function exactly like bison and in fact are bison. For conservation groups, the interest is that they are not totally pure.”[17]

The term “cattalo” is defined by United States law as a cross of bison and cattle which have a bison appearance;[18] in Canada, however, the term is used for hybrids of all degrees and appearance. In the U.S., cattalo are regulated as “exotic animals”, along with pure bison and deer.

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Beefalo – Wikipedia

Genetics – Wikipedia

This article is about the general scientific term. For the scientific journal, see Genetics (journal).

Genetics is the study of genes, genetic variation, and heredity in living organisms.[1][2] It is generally considered a field of biology, but it intersects frequently with many of the life sciences and is strongly linked with the study of information systems.

The father of genetics is Gregor Mendel, a late 19th-century scientist and Augustinian friar. Mendel studied “trait inheritance,” patterns in the way traits are handed down from parents to offspring. He observed that organisms (pea plants) inherit traits by way of discrete “units of inheritance.” This term, still used today, is a somewhat ambiguous definition of what is referred to as a gene.

Trait inheritance and molecular inheritance mechanisms of genes are still primary principles of genetics in the 21st century, but modern genetics has expanded beyond inheritance to studying the function and behavior of genes. Gene structure and function, variation, and distribution are studied within the context of the cell, the organism (e.g. dominance), and within the context of a population. Genetics has given rise to a number of sub-fields, including epigenetics and population genetics. Organisms studied within the broad field span the domain of life, including bacteria, plants, animals, and humans.

Genetic processes work in combination with an organism’s environment and experiences to influence development and behavior, often referred to as nature versus nurture. The intra- or extra-cellular environment of a cell or organism may switch gene transcription on or off. A classic example is two seeds of genetically identical corn, one placed in a temperate climate and one in an arid climate. While the average height of the two corn stalks may be genetically determined to be equal, the one in the arid climate only grows to half the height of the one in the temperate climate due to lack of water and nutrients in its environment.

The word genetics stems from the Ancient Greek genetikos meaning “genitive”/”generative”, which in turn derives from genesis meaning “origin”.[3][4][5]

The observation that living things inherit traits from their parents has been used since prehistoric times to improve crop plants and animals through selective breeding.[6] The modern science of genetics, seeking to understand this process, began with the work of Gregor Mendel in the mid-19th century.[7]

Prior to Mendel, Imre Festetics, a Hungarian noble, who lived in Kszeg before Mendel, was the first who used the word “genetics.” He described several rules of genetic inheritance in his work The genetic law of the Nature (Die genetische Gestze der Natur, 1819). His second law is the same as what Mendel published. In his third law, he developed the basic principles of mutation (he can be considered a forerunner of Hugo de Vries.)[8]

Other theories of inheritance preceded his work. A popular theory during Mendel’s time was the concept of blending inheritance: the idea that individuals inherit a smooth blend of traits from their parents.[9] Mendel’s work provided examples where traits were definitely not blended after hybridization, showing that traits are produced by combinations of distinct genes rather than a continuous blend. Blending of traits in the progeny is now explained by the action of multiple genes with quantitative effects. Another theory that had some support at that time was the inheritance of acquired characteristics: the belief that individuals inherit traits strengthened by their parents. This theory (commonly associated with Jean-Baptiste Lamarck) is now known to be wrongthe experiences of individuals do not affect the genes they pass to their children,[10] although evidence in the field of epigenetics has revived some aspects of Lamarck’s theory.[11] Other theories included the pangenesis of Charles Darwin (which had both acquired and inherited aspects) and Francis Galton’s reformulation of pangenesis as both particulate and inherited.[12]

Modern genetics started with Gregor Johann Mendel, a scientist and Augustinian friar who studied the nature of inheritance in plants. In his paper “Versuche ber Pflanzenhybriden” (“Experiments on Plant Hybridization”), presented in 1865 to the Naturforschender Verein (Society for Research in Nature) in Brnn, Mendel traced the inheritance patterns of certain traits in pea plants and described them mathematically.[13] Although this pattern of inheritance could only be observed for a few traits, Mendel’s work suggested that heredity was particulate, not acquired, and that the inheritance patterns of many traits could be explained through simple rules and ratios.

The importance of Mendel’s work did not gain wide understanding until the 1890s, after his death, when other scientists working on similar problems re-discovered his research. William Bateson, a proponent of Mendel’s work, coined the word genetics in 1905.[14][15] (The adjective genetic, derived from the Greek word genesis, “origin”, predates the noun and was first used in a biological sense in 1860.)[16] Bateson both acted as a mentor and was aided significantly by the work of female scientists from Newnham College at Cambridge, specifically the work of Becky Saunders, Nora Darwin Barlow, and Muriel Wheldale Onslow.[17] Bateson popularized the usage of the word genetics to describe the study of inheritance in his inaugural address to the Third International Conference on Plant Hybridization in London, England, in 1906.[18]

After the rediscovery of Mendel’s work, scientists tried to determine which molecules in the cell were responsible for inheritance. In 1911, Thomas Hunt Morgan argued that genes are on chromosomes, based on observations of a sex-linked white eye mutation in fruit flies.[19] In 1913, his student Alfred Sturtevant used the phenomenon of genetic linkage to show that genes are arranged linearly on the chromosome.[20]

Although genes were known to exist on chromosomes, chromosomes are composed of both protein and DNA, and scientists did not know which of the two is responsible for inheritance. In 1928, Frederick Griffith discovered the phenomenon of transformation (see Griffith’s experiment): dead bacteria could transfer genetic material to “transform” other still-living bacteria. Sixteen years later, in 1944, the AveryMacLeodMcCarty experiment identified DNA as the molecule responsible for transformation.[21] The role of the nucleus as the repository of genetic information in eukaryotes had been established by Hmmerling in 1943 in his work on the single celled alga Acetabularia.[22] The HersheyChase experiment in 1952 confirmed that DNA (rather than protein) is the genetic material of the viruses that infect bacteria, providing further evidence that DNA is the molecule responsible for inheritance.[23]

James Watson and Francis Crick determined the structure of DNA in 1953, using the X-ray crystallography work of Rosalind Franklin and Maurice Wilkins that indicated DNA has a helical structure (i.e., shaped like a corkscrew).[24][25] Their double-helix model had two strands of DNA with the nucleotides pointing inward, each matching a complementary nucleotide on the other strand to form what look like rungs on a twisted ladder.[26] This structure showed that genetic information exists in the sequence of nucleotides on each strand of DNA. The structure also suggested a simple method for replication: if the strands are separated, new partner strands can be reconstructed for each based on the sequence of the old strand. This property is what gives DNA its semi-conservative nature where one strand of new DNA is from an original parent strand.[27]

Although the structure of DNA showed how inheritance works, it was still not known how DNA influences the behavior of cells. In the following years, scientists tried to understand how DNA controls the process of protein production.[28] It was discovered that the cell uses DNA as a template to create matching messenger RNA, molecules with nucleotides very similar to DNA. The nucleotide sequence of a messenger RNA is used to create an amino acid sequence in protein; this translation between nucleotide sequences and amino acid sequences is known as the genetic code.[29]

With the newfound molecular understanding of inheritance came an explosion of research.[30] A notable theory arose from Tomoko Ohta in 1973 with her amendment to the neutral theory of molecular evolution through publishing the nearly neutral theory of molecular evolution. In this theory, Ohta stressed the importance of natural selection and the environment to the rate at which genetic evolution occurs.[31] One important development was chain-termination DNA sequencing in 1977 by Frederick Sanger. This technology allows scientists to read the nucleotide sequence of a DNA molecule.[32] In 1983, Kary Banks Mullis developed the polymerase chain reaction, providing a quick way to isolate and amplify a specific section of DNA from a mixture.[33] The efforts of the Human Genome Project, Department of Energy, NIH, and parallel private efforts by Celera Genomics led to the sequencing of the human genome in 2003.[34][35]

At its most fundamental level, inheritance in organisms occurs by passing discrete heritable units, called genes, from parents to offspring.[36] This property was first observed by Gregor Mendel, who studied the segregation of heritable traits in pea plants.[13][37] In his experiments studying the trait for flower color, Mendel observed that the flowers of each pea plant were either purple or whitebut never an intermediate between the two colors. These different, discrete versions of the same gene are called alleles.

In the case of the pea, which is a diploid species, each individual plant has two copies of each gene, one copy inherited from each parent.[38] Many species, including humans, have this pattern of inheritance. Diploid organisms with two copies of the same allele of a given gene are called homozygous at that gene locus, while organisms with two different alleles of a given gene are called heterozygous.

The set of alleles for a given organism is called its genotype, while the observable traits of the organism are called its phenotype. When organisms are heterozygous at a gene, often one allele is called dominant as its qualities dominate the phenotype of the organism, while the other allele is called recessive as its qualities recede and are not observed. Some alleles do not have complete dominance and instead have incomplete dominance by expressing an intermediate phenotype, or codominance by expressing both alleles at once.[39]

When a pair of organisms reproduce sexually, their offspring randomly inherit one of the two alleles from each parent. These observations of discrete inheritance and the segregation of alleles are collectively known as Mendel’s first law or the Law of Segregation.

Geneticists use diagrams and symbols to describe inheritance. A gene is represented by one or a few letters. Often a “+” symbol is used to mark the usual, non-mutant allele for a gene.[40]

In fertilization and breeding experiments (and especially when discussing Mendel’s laws) the parents are referred to as the “P” generation and the offspring as the “F1” (first filial) generation. When the F1 offspring mate with each other, the offspring are called the “F2” (second filial) generation. One of the common diagrams used to predict the result of cross-breeding is the Punnett square.

When studying human genetic diseases, geneticists often use pedigree charts to represent the inheritance of traits.[41] These charts map the inheritance of a trait in a family tree.

Organisms have thousands of genes, and in sexually reproducing organisms these genes generally assort independently of each other. This means that the inheritance of an allele for yellow or green pea color is unrelated to the inheritance of alleles for white or purple flowers. This phenomenon, known as “Mendel’s second law” or the “law of independent assortment,” means that the alleles of different genes get shuffled between parents to form offspring with many different combinations. (Some genes do not assort independently, demonstrating genetic linkage, a topic discussed later in this article.)

Often different genes can interact in a way that influences the same trait. In the Blue-eyed Mary (Omphalodes verna), for example, there exists a gene with alleles that determine the color of flowers: blue or magenta. Another gene, however, controls whether the flowers have color at all or are white. When a plant has two copies of this white allele, its flowers are whiteregardless of whether the first gene has blue or magenta alleles. This interaction between genes is called epistasis, with the second gene epistatic to the first.[42]

Many traits are not discrete features (e.g. purple or white flowers) but are instead continuous features (e.g. human height and skin color). These complex traits are products of many genes.[43] The influence of these genes is mediated, to varying degrees, by the environment an organism has experienced. The degree to which an organism’s genes contribute to a complex trait is called heritability.[44] Measurement of the heritability of a trait is relativein a more variable environment, the environment has a bigger influence on the total variation of the trait. For example, human height is a trait with complex causes. It has a heritability of 89% in the United States. In Nigeria, however, where people experience a more variable access to good nutrition and health care, height has a heritability of only 62%.[45]

The molecular basis for genes is deoxyribonucleic acid (DNA). DNA is composed of a chain of nucleotides, of which there are four types: adenine (A), cytosine (C), guanine (G), and thymine (T). Genetic information exists in the sequence of these nucleotides, and genes exist as stretches of sequence along the DNA chain.[46]Viruses are the only exception to this rulesometimes viruses use the very similar molecule RNA instead of DNA as their genetic material.[47] Viruses cannot reproduce without a host and are unaffected by many genetic processes, so tend not to be considered living organisms.

DNA normally exists as a double-stranded molecule, coiled into the shape of a double helix. Each nucleotide in DNA preferentially pairs with its partner nucleotide on the opposite strand: A pairs with T, and C pairs with G. Thus, in its two-stranded form, each strand effectively contains all necessary information, redundant with its partner strand. This structure of DNA is the physical basis for inheritance: DNA replication duplicates the genetic information by splitting the strands and using each strand as a template for synthesis of a new partner strand.[48]

Genes are arranged linearly along long chains of DNA base-pair sequences. In bacteria, each cell usually contains a single circular genophore, while eukaryotic organisms (such as plants and animals) have their DNA arranged in multiple linear chromosomes. These DNA strands are often extremely long; the largest human chromosome, for example, is about 247 million base pairs in length.[49] The DNA of a chromosome is associated with structural proteins that organize, compact, and control access to the DNA, forming a material called chromatin; in eukaryotes, chromatin is usually composed of nucleosomes, segments of DNA wound around cores of histone proteins.[50] The full set of hereditary material in an organism (usually the combined DNA sequences of all chromosomes) is called the genome.

While haploid organisms have only one copy of each chromosome, most animals and many plants are diploid, containing two of each chromosome and thus two copies of every gene.[38] The two alleles for a gene are located on identical loci of the two homologous chromosomes, each allele inherited from a different parent.

Many species have so-called sex chromosomes that determine the gender of each organism.[51] In humans and many other animals, the Y chromosome contains the gene that triggers the development of the specifically male characteristics. In evolution, this chromosome has lost most of its content and also most of its genes, while the X chromosome is similar to the other chromosomes and contains many genes. The X and Y chromosomes form a strongly heterogeneous pair.

When cells divide, their full genome is copied and each daughter cell inherits one copy. This process, called mitosis, is the simplest form of reproduction and is the basis for asexual reproduction. Asexual reproduction can also occur in multicellular organisms, producing offspring that inherit their genome from a single parent. Offspring that are genetically identical to their parents are called clones.

Eukaryotic organisms often use sexual reproduction to generate offspring that contain a mixture of genetic material inherited from two different parents. The process of sexual reproduction alternates between forms that contain single copies of the genome (haploid) and double copies (diploid).[38] Haploid cells fuse and combine genetic material to create a diploid cell with paired chromosomes. Diploid organisms form haploids by dividing, without replicating their DNA, to create daughter cells that randomly inherit one of each pair of chromosomes. Most animals and many plants are diploid for most of their lifespan, with the haploid form reduced to single cell gametes such as sperm or eggs.

Although they do not use the haploid/diploid method of sexual reproduction, bacteria have many methods of acquiring new genetic information. Some bacteria can undergo conjugation, transferring a small circular piece of DNA to another bacterium.[52] Bacteria can also take up raw DNA fragments found in the environment and integrate them into their genomes, a phenomenon known as transformation.[53] These processes result in horizontal gene transfer, transmitting fragments of genetic information between organisms that would be otherwise unrelated.

The diploid nature of chromosomes allows for genes on different chromosomes to assort independently or be separated from their homologous pair during sexual reproduction wherein haploid gametes are formed. In this way new combinations of genes can occur in the offspring of a mating pair. Genes on the same chromosome would theoretically never recombine. However, they do, via the cellular process of chromosomal crossover. During crossover, chromosomes exchange stretches of DNA, effectively shuffling the gene alleles between the chromosomes.[54] This process of chromosomal crossover generally occurs during meiosis, a series of cell divisions that creates haploid cells.

The first cytological demonstration of crossing over was performed by Harriet Creighton and Barbara McClintock in 1931. Their research and experiments on corn provided cytological evidence for the genetic theory that linked genes on paired chromosomes do in fact exchange places from one homolog to the other.[55]

The probability of chromosomal crossover occurring between two given points on the chromosome is related to the distance between the points. For an arbitrarily long distance, the probability of crossover is high enough that the inheritance of the genes is effectively uncorrelated.[56] For genes that are closer together, however, the lower probability of crossover means that the genes demonstrate genetic linkage; alleles for the two genes tend to be inherited together. The amounts of linkage between a series of genes can be combined to form a linear linkage map that roughly describes the arrangement of the genes along the chromosome.[57]

Genes generally express their functional effect through the production of proteins, which are complex molecules responsible for most functions in the cell. Proteins are made up of one or more polypeptide chains, each of which is composed of a sequence of amino acids, and the DNA sequence of a gene (through an RNA intermediate) is used to produce a specific amino acid sequence. This process begins with the production of an RNA molecule with a sequence matching the gene’s DNA sequence, a process called transcription.

This messenger RNA molecule is then used to produce a corresponding amino acid sequence through a process called translation. Each group of three nucleotides in the sequence, called a codon, corresponds either to one of the twenty possible amino acids in a protein or an instruction to end the amino acid sequence; this correspondence is called the genetic code.[58] The flow of information is unidirectional: information is transferred from nucleotide sequences into the amino acid sequence of proteins, but it never transfers from protein back into the sequence of DNAa phenomenon Francis Crick called the central dogma of molecular biology.[59]

The specific sequence of amino acids results in a unique three-dimensional structure for that protein, and the three-dimensional structures of proteins are related to their functions.[60][61] Some are simple structural molecules, like the fibers formed by the protein collagen. Proteins can bind to other proteins and simple molecules, sometimes acting as enzymes by facilitating chemical reactions within the bound molecules (without changing the structure of the protein itself). Protein structure is dynamic; the protein hemoglobin bends into slightly different forms as it facilitates the capture, transport, and release of oxygen molecules within mammalian blood.

A single nucleotide difference within DNA can cause a change in the amino acid sequence of a protein. Because protein structures are the result of their amino acid sequences, some changes can dramatically change the properties of a protein by destabilizing the structure or changing the surface of the protein in a way that changes its interaction with other proteins and molecules. For example, sickle-cell anemia is a human genetic disease that results from a single base difference within the coding region for the -globin section of hemoglobin, causing a single amino acid change that changes hemoglobin’s physical properties.[62] Sickle-cell versions of hemoglobin stick to themselves, stacking to form fibers that distort the shape of red blood cells carrying the protein. These sickle-shaped cells no longer flow smoothly through blood vessels, having a tendency to clog or degrade, causing the medical problems associated with this disease.

Some DNA sequences are transcribed into RNA but are not translated into protein productssuch RNA molecules are called non-coding RNA. In some cases, these products fold into structures which are involved in critical cell functions (e.g. ribosomal RNA and transfer RNA). RNA can also have regulatory effects through hybridization interactions with other RNA molecules (e.g. microRNA).

Although genes contain all the information an organism uses to function, the environment plays an important role in determining the ultimate phenotypes an organism displays. This is the complementary relationship often referred to as “nature and nurture.” The phenotype of an organism depends on the interaction of genes and the environment. An interesting example is the coat coloration of the Siamese cat. In this case, the body temperature of the cat plays the role of the environment. The cat’s genes code for dark hair, thus the hair-producing cells in the cat make cellular proteins resulting in dark hair. But these dark hair-producing proteins are sensitive to temperature (i.e. have a mutation causing temperature-sensitivity) and denature in higher-temperature environments, failing to produce dark-hair pigment in areas where the cat has a higher body temperature. In a low-temperature environment, however, the protein’s structure is stable and produces dark-hair pigment normally. The protein remains functional in areas of skin that are coldersuch as its legs, ears, tail and faceso the cat has dark-hair at its extremities.[63]

Environment plays a major role in effects of the human genetic disease phenylketonuria.[64] The mutation that causes phenylketonuria disrupts the ability of the body to break down the amino acid phenylalanine, causing a toxic build-up of an intermediate molecule that, in turn, causes severe symptoms of progressive intellectual disability and seizures. However, if someone with the phenylketonuria mutation follows a strict diet that avoids this amino acid, they remain normal and healthy.

A popular method for determining how genes and environment (“nature and nurture”) contribute to a phenotype involves studying identical and fraternal twins, or other siblings of multiple births.[65] Because identical siblings come from the same zygote, they are genetically the same. Fraternal twins are as genetically different from one another as normal siblings. By comparing how often a certain disorder occurs in a pair of identical twins to how often it occurs in a pair of fraternal twins, scientists can determine whether that disorder is caused by genetic or postnatal environmental factors whether it has “nature” or “nurture” causes. One famous example is the multiple birth study of the Genain quadruplets, who were identical quadruplets all diagnosed with schizophrenia.[66] However such tests cannot separate genetic factors from environmental factors affecting fetal development.

The genome of a given organism contains thousands of genes, but not all these genes need to be active at any given moment. A gene is expressed when it is being transcribed into mRNA and there exist many cellular methods of controlling the expression of genes such that proteins are produced only when needed by the cell. Transcription factors are regulatory proteins that bind to DNA, either promoting or inhibiting the transcription of a gene.[67] Within the genome of Escherichia coli bacteria, for example, there exists a series of genes necessary for the synthesis of the amino acid tryptophan. However, when tryptophan is already available to the cell, these genes for tryptophan synthesis are no longer needed. The presence of tryptophan directly affects the activity of the genestryptophan molecules bind to the tryptophan repressor (a transcription factor), changing the repressor’s structure such that the repressor binds to the genes. The tryptophan repressor blocks the transcription and expression of the genes, thereby creating negative feedback regulation of the tryptophan synthesis process.[68]

Differences in gene expression are especially clear within multicellular organisms, where cells all contain the same genome but have very different structures and behaviors due to the expression of different sets of genes. All the cells in a multicellular organism derive from a single cell, differentiating into variant cell types in response to external and intercellular signals and gradually establishing different patterns of gene expression to create different behaviors. As no single gene is responsible for the development of structures within multicellular organisms, these patterns arise from the complex interactions between many cells.

Within eukaryotes, there exist structural features of chromatin that influence the transcription of genes, often in the form of modifications to DNA and chromatin that are stably inherited by daughter cells.[69] These features are called “epigenetic” because they exist “on top” of the DNA sequence and retain inheritance from one cell generation to the next. Because of epigenetic features, different cell types grown within the same medium can retain very different properties. Although epigenetic features are generally dynamic over the course of development, some, like the phenomenon of paramutation, have multigenerational inheritance and exist as rare exceptions to the general rule of DNA as the basis for inheritance.[70]

During the process of DNA replication, errors occasionally occur in the polymerization of the second strand. These errors, called mutations, can affect the phenotype of an organism, especially if they occur within the protein coding sequence of a gene. Error rates are usually very low1 error in every 10100million basesdue to the “proofreading” ability of DNA polymerases.[71][72] Processes that increase the rate of changes in DNA are called mutagenic: mutagenic chemicals promote errors in DNA replication, often by interfering with the structure of base-pairing, while UV radiation induces mutations by causing damage to the DNA structure.[73] Chemical damage to DNA occurs naturally as well and cells use DNA repair mechanisms to repair mismatches and breaks. The repair does not, however, always restore the original sequence.

In organisms that use chromosomal crossover to exchange DNA and recombine genes, errors in alignment during meiosis can also cause mutations.[74] Errors in crossover are especially likely when similar sequences cause partner chromosomes to adopt a mistaken alignment; this makes some regions in genomes more prone to mutating in this way. These errors create large structural changes in DNA sequence duplications, inversions, deletions of entire regions or the accidental exchange of whole parts of sequences between different chromosomes (chromosomal translocation).

Mutations alter an organism’s genotype and occasionally this causes different phenotypes to appear. Most mutations have little effect on an organism’s phenotype, health, or reproductive fitness.[75] Mutations that do have an effect are usually detrimental, but occasionally some can be beneficial.[76] Studies in the fly Drosophila melanogaster suggest that if a mutation changes a protein produced by a gene, about 70 percent of these mutations will be harmful with the remainder being either neutral or weakly beneficial.[77]

Population genetics studies the distribution of genetic differences within populations and how these distributions change over time.[78] Changes in the frequency of an allele in a population are mainly influenced by natural selection, where a given allele provides a selective or reproductive advantage to the organism,[79] as well as other factors such as mutation, genetic drift, genetic draft,[80]artificial selection and migration.[81]

Over many generations, the genomes of organisms can change significantly, resulting in evolution. In the process called adaptation, selection for beneficial mutations can cause a species to evolve into forms better able to survive in their environment.[82] New species are formed through the process of speciation, often caused by geographical separations that prevent populations from exchanging genes with each other.[83] The application of genetic principles to the study of population biology and evolution is known as the “modern evolutionary synthesis.”

By comparing the homology between different species’ genomes, it is possible to calculate the evolutionary distance between them and when they may have diverged. Genetic comparisons are generally considered a more accurate method of characterizing the relatedness between species than the comparison of phenotypic characteristics. The evolutionary distances between species can be used to form evolutionary trees; these trees represent the common descent and divergence of species over time, although they do not show the transfer of genetic material between unrelated species (known as horizontal gene transfer and most common in bacteria).[84]

Although geneticists originally studied inheritance in a wide range of organisms, researchers began to specialize in studying the genetics of a particular subset of organisms. The fact that significant research already existed for a given organism would encourage new researchers to choose it for further study, and so eventually a few model organisms became the basis for most genetics research.[85] Common research topics in model organism genetics include the study of gene regulation and the involvement of genes in development and cancer.

Organisms were chosen, in part, for convenienceshort generation times and easy genetic manipulation made some organisms popular genetics research tools. Widely used model organisms include the gut bacterium Escherichia coli, the plant Arabidopsis thaliana, baker’s yeast (Saccharomyces cerevisiae), the nematode Caenorhabditis elegans, the common fruit fly (Drosophila melanogaster), and the common house mouse (Mus musculus).

Medical genetics seeks to understand how genetic variation relates to human health and disease.[86] When searching for an unknown gene that may be involved in a disease, researchers commonly use genetic linkage and genetic pedigree charts to find the location on the genome associated with the disease. At the population level, researchers take advantage of Mendelian randomization to look for locations in the genome that are associated with diseases, a method especially useful for multigenic traits not clearly defined by a single gene.[87] Once a candidate gene is found, further research is often done on the corresponding (or homologous) genes of model organisms. In addition to studying genetic diseases, the increased availability of genotyping methods has led to the field of pharmacogenetics: the study of how genotype can affect drug responses.[88]

Individuals differ in their inherited tendency to develop cancer,[89] and cancer is a genetic disease.[90] The process of cancer development in the body is a combination of events. Mutations occasionally occur within cells in the body as they divide. Although these mutations will not be inherited by any offspring, they can affect the behavior of cells, sometimes causing them to grow and divide more frequently. There are biological mechanisms that attempt to stop this process; signals are given to inappropriately dividing cells that should trigger cell death, but sometimes additional mutations occur that cause cells to ignore these messages. An internal process of natural selection occurs within the body and eventually mutations accumulate within cells to promote their own growth, creating a cancerous tumor that grows and invades various tissues of the body.

Normally, a cell divides only in response to signals called growth factors and stops growing once in contact with surrounding cells and in response to growth-inhibitory signals. It usually then divides a limited number of times and dies, staying within the epithelium where it is unable to migrate to other organs. To become a cancer cell, a cell has to accumulate mutations in a number of genes (three to seven) that allow it to bypass this regulation: it no longer needs growth factors to divide, continues growing when making contact to neighbor cells, ignores inhibitory signals, keeps growing indefinitely and is immortal, escapes from the epithelium and ultimately may be able to escape from the primary tumor, cross the endothelium of a blood vessel, be transported by the bloodstream and colonize a new organ, forming deadly metastasis. Although there are some genetic predispositions in a small fraction of cancers, the major fraction is due to a set of new genetic mutations that originally appear and accumulate in one or a small number of cells that will divide to form the tumor and are not transmitted to the progeny (somatic mutations). The most frequent mutations are a loss of function of p53 protein, a tumor suppressor, or in the p53 pathway, and gain of function mutations in the Ras proteins, or in other oncogenes.

DNA can be manipulated in the laboratory. Restriction enzymes are commonly used enzymes that cut DNA at specific sequences, producing predictable fragments of DNA.[91] DNA fragments can be visualized through use of gel electrophoresis, which separates fragments according to their length.

The use of ligation enzymes allows DNA fragments to be connected. By binding (“ligating”) fragments of DNA together from different sources, researchers can create recombinant DNA, the DNA often associated with genetically modified organisms. Recombinant DNA is commonly used in the context of plasmids: short circular DNA molecules with a few genes on them. In the process known as molecular cloning, researchers can amplify the DNA fragments by inserting plasmids into bacteria and then culturing them on plates of agar (to isolate clones of bacteria cells). (“Cloning” can also refer to the various means of creating cloned (“clonal”) organisms.)

DNA can also be amplified using a procedure called the polymerase chain reaction (PCR).[92] By using specific short sequences of DNA, PCR can isolate and exponentially amplify a targeted region of DNA. Because it can amplify from extremely small amounts of DNA, PCR is also often used to detect the presence of specific DNA sequences.

DNA sequencing, one of the most fundamental technologies developed to study genetics, allows researchers to determine the sequence of nucleotides in DNA fragments. The technique of chain-termination sequencing, developed in 1977 by a team led by Frederick Sanger, is still routinely used to sequence DNA fragments.[93] Using this technology, researchers have been able to study the molecular sequences associated with many human diseases.

As sequencing has become less expensive, researchers have sequenced the genomes of many organisms using a process called genome assembly, which utilizes computational tools to stitch together sequences from many different fragments.[94] These technologies were used to sequence the human genome in the Human Genome Project completed in 2003.[34] New high-throughput sequencing technologies are dramatically lowering the cost of DNA sequencing, with many researchers hoping to bring the cost of resequencing a human genome down to a thousand dollars.[95]

Next-generation sequencing (or high-throughput sequencing) came about due to the ever-increasing demand for low-cost sequencing. These sequencing technologies allow the production of potentially millions of sequences concurrently.[96][97] The large amount of sequence data available has created the field of genomics, research that uses computational tools to search for and analyze patterns in the full genomes of organisms. Genomics can also be considered a subfield of bioinformatics, which uses computational approaches to analyze large sets of biological data. A common problem to these fields of research is how to manage and share data that deals with human subject and personally identifiable information. See also genomics data sharing.

On 19 March 2015, a leading group of biologists urged a worldwide ban on clinical use of methods, particularly the use of CRISPR and zinc finger, to edit the human genome in a way that can be inherited.[98][99][100][101] In April 2015, Chinese researchers reported results of basic research to edit the DNA of non-viable human embryos using CRISPR.[102][103]

The rest is here:
Genetics – Wikipedia

Human – Wikipedia

Human[1] Temporal range: 0.1950Ma Middle Pleistocene Recent An adult human male (left) and female (right) in Northern Thailand. Scientific classification Kingdom: Animalia Phylum: Chordata Class: Mammalia Order: Primates Suborder: Haplorhini Family: Hominidae Genus: Homo Species: H.sapiens Binomial name Homo sapiens Linnaeus, 1758 Subspecies

Homo sapiens idaltu White et al., 2003 Homo sapiens sapiens

Modern humans (Homo sapiens, primarily ssp. Homo sapiens sapiens) are the only extant members of Hominina clade (or human clade), a branch of the taxonomical tribe Hominini belonging to the family of great apes. They are characterized by erect posture and bipedal locomotion; manual dexterity and increased tool use, compared to other animals; and a general trend toward larger, more complex brains and societies.[3][4]

Early homininsparticularly the australopithecines, whose brains and anatomy are in many ways more similar to ancestral non-human apesare less often referred to as “human” than hominins of the genus Homo.[5] Several of these hominins used fire, occupied much of Eurasia, and gave rise to anatomically modern Homo sapiens in Africa about 200,000 years ago.[6][7] They began to exhibit evidence of behavioral modernity around 50,000 years ago. In several waves of migration, anatomically modern humans ventured out of Africa and populated most of the world.[8]

The spread of humans and their large and increasing population has had a profound impact on large areas of the environment and millions of native species worldwide. Advantages that explain this evolutionary success include a relatively larger brain with a particularly well-developed neocortex, prefrontal cortex and temporal lobes, which enable high levels of abstract reasoning, language, problem solving, sociality, and culture through social learning. Humans use tools to a much higher degree than any other animal, are the only extant species known to build fires and cook their food, and are the only extant species to clothe themselves and create and use numerous other technologies and arts.

Humans are uniquely adept at utilizing systems of symbolic communication (such as language and art) for self-expression and the exchange of ideas, and for organizing themselves into purposeful groups. Humans create complex social structures composed of many cooperating and competing groups, from families and kinship networks to political states. Social interactions between humans have established an extremely wide variety of values,[9]social norms, and rituals, which together form the basis of human society. Curiosity and the human desire to understand and influence the environment and to explain and manipulate phenomena (or events) has provided the foundation for developing science, philosophy, mythology, religion, anthropology, and numerous other fields of knowledge.

Though most of human existence has been sustained by hunting and gathering in band societies,[10] increasing numbers of human societies began to practice sedentary agriculture approximately some 10,000 years ago,[11] domesticating plants and animals, thus allowing for the growth of civilization. These human societies subsequently expanded in size, establishing various forms of government, religion, and culture around the world, unifying people within regions to form states and empires. The rapid advancement of scientific and medical understanding in the 19th and 20th centuries led to the development of fuel-driven technologies and increased lifespans, causing the human population to rise exponentially. By February 2016, the global human population had exceeded 7.3 billion.[12]






















In common usage, the word “human” generally refers to the only extant species of the genus Homo anatomically and behaviorally modern Homo sapiens.

In scientific terms, the meanings of “hominid” and “hominin” have changed during the recent decades with advances in the discovery and study of the fossil ancestors of modern humans. The previously clear boundary between humans and apes has blurred, resulting in now acknowledging the hominids as encompassing multiple species, and Homo and close relatives since the split from chimpanzees as the only hominins. There is also a distinction between anatomically modern humans and Archaic Homo sapiens, the earliest fossil members of the species.

The English adjective human is a Middle English loanword from Old French humain, ultimately from Latin hmnus, the adjective form of hom “man.” The word’s use as a noun (with a plural: humans) dates to the 16th century.[13] The native English term man can refer to the species generally (a synonym for humanity), and could formerly refer to specific individuals of either sex, though this latter use is now obsolete.[14]

The species binomial Homo sapiens was coined by Carl Linnaeus in his 18th century work Systema Naturae.[15] The generic name Homo is a learned 18th century derivation from Latin hom “man,” ultimately “earthly being” (Old Latin hem a cognate to Old English guma “man,” from PIE demon-, meaning “earth” or “ground”).[16] The species-name sapiens means “wise” or “sapient.” Note that the Latin word homo refers to humans of either gender, and that sapiens is the singular form (while there is no such word as sapien).[17]

The genus Homo evolved and diverged from other hominins in Africa, after the human clade split from the chimpanzee lineage of the hominids (great apes) branch of the primates. Modern humans, defined as the species Homo sapiens or specifically to the single extant subspecies Homo sapiens sapiens, proceeded to colonize all the continents and larger islands, arriving in Eurasia 125,00060,000 years ago,[18][19]Australia around 40,000 years ago, the Americas around 15,000 years ago, and remote islands such as Hawaii, Easter Island, Madagascar, and New Zealand between the years 300 and 1280.[20][21]

The closest living relatives of humans are chimpanzees (genus Pan) and gorillas (genus Gorilla).[22] With the sequencing of both the human and chimpanzee genome, current estimates of similarity between human and chimpanzee DNA sequences range between 95% and 99%.[22][23][24] By using the technique called a molecular clock which estimates the time required for the number of divergent mutations to accumulate between two lineages, the approximate date for the split between lineages can be calculated. The gibbons (Hylobatidae) and orangutans (genus Pongo) were the first groups to split from the line leading to the humans, then gorillas (genus Gorilla) followed by the chimpanzees (genus Pan). The splitting date between human and chimpanzee lineages is placed around 48 million years ago during the late Miocene epoch.[25][26] During this split, chromosome 2 was formed from two other chromosomes, leaving humans with only 23 pairs of chromosomes, compared to 24 for the other apes.[27][28]

There is little fossil evidence for the divergence of the gorilla, chimpanzee and hominin lineages.[29][30] The earliest fossils that have been proposed as members of the hominin lineage are Sahelanthropus tchadensis dating from 7 million years ago, Orrorin tugenensis dating from 5.7 million years ago, and Ardipithecus kadabba dating to 5.6 million years ago. Each of these species has been argued to be a bipedal ancestor of later hominins, but all such claims are contested. It is also possible that any one of the three is an ancestor of another branch of African apes, or is an ancestor shared between hominins and other African Hominoidea (apes). The question of the relation between these early fossil species and the hominin lineage is still to be resolved. From these early species the australopithecines arose around 4 million years ago diverged into robust (also called Paranthropus) and gracile branches, possibly one of which (such as A. garhi, dating to 2.5 million years ago) is a direct ancestor of the genus Homo.[citation needed]

The earliest members of the genus Homo are Homo habilis which evolved around 2.8 million years ago.[31]Homo habilis has been considered the first species for which there is clear evidence of the use of stone tools. More recently, however, in 2015, stone tools, perhaps predating Homo habilis, have been discovered in northwestern Kenya that have been dated to 3.3 million years old.[32] Nonetheless, the brains of Homo habilis were about the same size as that of a chimpanzee, and their main adaptation was bipedalism as an adaptation to terrestrial living. During the next million years a process of encephalization began, and with the arrival of Homo erectus in the fossil record, cranial capacity had doubled. Homo erectus were the first of the hominina to leave Africa, and these species spread through Africa, Asia, and Europe between 1.3to1.8 million years ago. One population of H. erectus, also sometimes classified as a separate species Homo ergaster, stayed in Africa and evolved into Homo sapiens. It is believed that these species were the first to use fire and complex tools. The earliest transitional fossils between H. ergaster/erectus and archaic humans are from Africa such as Homo rhodesiensis, but seemingly transitional forms are also found at Dmanisi, Georgia. These descendants of African H. erectus spread through Eurasia from ca. 500,000 years ago evolving into H. antecessor, H. heidelbergensis and H. neanderthalensis. The earliest fossils of anatomically modern humans are from the Middle Paleolithic, about 200,000 years ago such as the Omo remains of Ethiopia and the fossils of Herto sometimes classified as Homo sapiens idaltu.[33] Later fossils of archaic Homo sapiens from Skhul in Israel and Southern Europe begin around 90,000 years ago.[34]

Human evolution is characterized by a number of morphological, developmental, physiological, and behavioral changes that have taken place since the split between the last common ancestor of humans and chimpanzees. The most significant of these adaptations are 1. bipedalism, 2. increased brain size, 3. lengthened ontogeny (gestation and infancy), 4. decreased sexual dimorphism (neoteny). The relationship between all these changes is the subject of ongoing debate.[35] Other significant morphological changes included the evolution of a power and precision grip, a change first occurring in H. erectus.[36]

Bipedalism is the basic adaption of the hominin line, and it is considered the main cause behind a suite of skeletal changes shared by all bipedal hominins. The earliest bipedal hominin is considered to be either Sahelanthropus[37] or Orrorin, with Ardipithecus, a full bipedal, coming somewhat later.[citation needed] The knuckle walkers, the gorilla and chimpanzee, diverged around the same time, and either Sahelanthropus or Orrorin may be humans’ last shared ancestor with those animals.[citation needed] The early bipedals eventually evolved into the australopithecines and later the genus Homo.[citation needed] There are several theories of the adaptational value of bipedalism. It is possible that bipedalism was favored because it freed up the hands for reaching and carrying food, because it saved energy during locomotion, because it enabled long distance running and hunting, or as a strategy for avoiding hyperthermia by reducing the surface exposed to direct sun.[citation needed]

The human species developed a much larger brain than that of other primates typically 1,330 cm3 in modern humans, over twice the size of that of a chimpanzee or gorilla.[38] The pattern of encephalization started with Homo habilis which at approximately 600cm3 had a brain slightly larger than chimpanzees, and continued with Homo erectus (8001100cm3), and reached a maximum in Neanderthals with an average size of 12001900cm3, larger even than Homo sapiens (but less encephalized).[39] The pattern of human postnatal brain growth differs from that of other apes (heterochrony), and allows for extended periods of social learning and language acquisition in juvenile humans. However, the differences between the structure of human brains and those of other apes may be even more significant than differences in size.[40][41][42][43] The increase in volume over time has affected different areas within the brain unequally the temporal lobes, which contain centers for language processing have increased disproportionately, as has the prefrontal cortex which has been related to complex decision making and moderating social behavior.[38] Encephalization has been tied to an increasing emphasis on meat in the diet,[44][45] or with the development of cooking,[46] and it has been proposed [47] that intelligence increased as a response to an increased necessity for solving social problems as human society became more complex.

The reduced degree of sexual dimorphism is primarily visible in the reduction of the male canine tooth relative to other ape species (except gibbons). Another important physiological change related to sexuality in humans was the evolution of hidden estrus. Humans are the only ape in which the female is fertile year round, and in which no special signals of fertility are produced by the body (such as genital swelling during estrus). Nonetheless humans retain a degree of sexual dimorphism in the distribution of body hair and subcutaneous fat, and in the overall size, males being around 25% larger than females. These changes taken together have been interpreted as a result of an increased emphasis on pair bonding as a possible solution to the requirement for increased parental investment due to the prolonged infancy of offspring.[citation needed]

By the beginning of the Upper Paleolithic period (50,000 BP), full behavioral modernity, including language, music and other cultural universals had developed.[48][49] As modern humans spread out from Africa they encountered other hominids such as Homo neanderthalensis and the so-called Denisovans. The nature of interaction between early humans and these sister species has been a long-standing source of controversy, the question being whether humans replaced these earlier species or whether they were in fact similar enough to interbreed, in which case these earlier populations may have contributed genetic material to modern humans.[50] Recent studies of the human and Neanderthal genomes suggest gene flow between archaic Homo sapiens and Neanderthals and Denisovans.[51][52][53] In March 2016, studies were published that suggest that modern humans bred with hominins, including Denisovans and Neanderthals, on multiple occasions.[54]

This dispersal out of Africa is estimated to have begun about 70,000 years BP from Northeast Africa. Current evidence suggests that there was only one such dispersal and that it only involved a few hundred individuals. The vast majority of humans stayed in Africa and adapted to a diverse array of environments.[55] Modern humans subsequently spread globally, replacing earlier hominins (either through competition or hybridization). They inhabited Eurasia and Oceania by 40,000 years BP, and the Americas at least 14,500 years BP.[56][57]

Until about 10,000 years ago, humans lived as hunter-gatherers. They gradually gained domination over much of the natural environment. They generally lived in small nomadic groups known as band societies, often in caves. The advent of agriculture prompted the Neolithic Revolution, when access to food surplus led to the formation of permanent human settlements, the domestication of animals and the use of metal tools for the first time in history. Agriculture encouraged trade and cooperation, and led to complex society.[citation needed]

The early civilizations of Mesopotamia, Egypt, India, China, Maya, Greece and Rome were some of the cradles of civilization.[58][59][60] The Late Middle Ages and the Early Modern Period saw the rise of revolutionary ideas and technologies. Over the next 500 years, exploration and European colonialism brought great parts of the world under European control, leading to later struggles for independence. The concept of the modern world as distinct from an ancient world is based on a rapid change progress in a brief period of time in many areas.[citation needed] Advances in all areas of human activity prompted new theories such as evolution and psychoanalysis, which changed humanity’s views of itself.[citation needed] The Scientific Revolution, Technological Revolution and the Industrial Revolution up until the 19th century resulted in independent discoveries such as imaging technology, major innovations in transport, such as the airplane and automobile; energy development, such as coal and electricity.[61] This correlates with population growth (especially in America)[62] and higher life expectancy, the World population rapidly increased numerous times in the 19th and 20th centuries as nearly 10% of the 100 billion people lived in the past century.[63]

With the advent of the Information Age at the end of the 20th century, modern humans live in a world that has become increasingly globalized and interconnected. As of 2010, almost 2billion humans are able to communicate with each other via the Internet,[64] and 3.3 billion by mobile phone subscriptions.[65] Although interconnection between humans has encouraged the growth of science, art, discussion, and technology, it has also led to culture clashes and the development and use of weapons of mass destruction.[citation needed] Human civilization has led to environmental destruction and pollution significantly contributing to the ongoing mass extinction of other forms of life called the Holocene extinction event,[66] which may be further accelerated by global warming in the future.[67]

Early human settlements were dependent on proximity to water and, depending on the lifestyle, other natural resources used for subsistence, such as populations of animal prey for hunting and arable land for growing crops and grazing livestock. But humans have a great capacity for altering their habitats by means of technology, through irrigation, urban planning, construction, transport, manufacturing goods, deforestation and desertification. Deliberate habitat alteration is often done with the goals of increasing material wealth, increasing thermal comfort, improving the amount of food available, improving aesthetics, or improving ease of access to resources or other human settlements. With the advent of large-scale trade and transport infrastructure, proximity to these resources has become unnecessary, and in many places, these factors are no longer a driving force behind the growth and decline of a population. Nonetheless, the manner in which a habitat is altered is often a major determinant in population change.[citation needed]

Technology has allowed humans to colonize all of the continents and adapt to virtually all climates. Within the last century, humans have explored Antarctica, the ocean depths, and outer space, although large-scale colonization of these environments is not yet feasible. With a population of over seven billion, humans are among the most numerous of the large mammals. Most humans (61%) live in Asia. The remainder live in the Americas (14%), Africa (14%), Europe (11%), and Oceania (0.5%).[68]

Human habitation within closed ecological systems in hostile environments, such as Antarctica and outer space, is expensive, typically limited in duration, and restricted to scientific, military, or industrial expeditions. Life in space has been very sporadic, with no more than thirteen humans in space at any given time.[69] Between 1969 and 1972, two humans at a time spent brief intervals on the Moon. As of November 2016, no other celestial body has been visited by humans, although there has been a continuous human presence in space since the launch of the initial crew to inhabit the International Space Station on October 31, 2000.[70] However, other celestial bodies have been visited by human-made objects.[71][72][73]

Since 1800, the human population has increased from one billion[74] to over seven billion,[75] In 2004, some 2.5 billion out of 6.3 billion people (39.7%) lived in urban areas. In February 2008, the U.N. estimated that half the world’s population would live in urban areas by the end of the year.[76] Problems for humans living in cities include various forms of pollution and crime,[77] especially in inner city and suburban slums. Both overall population numbers and the proportion residing in cities are expected to increase significantly in the coming decades.[78]

Humans have had a dramatic effect on the environment. Humans are apex predators, being rarely preyed upon by other species.[79] Currently, through land development, combustion of fossil fuels, and pollution, humans are thought to be the main contributor to global climate change.[80] If this continues at its current rate it is predicted that climate change will wipe out half of all plant and animal species over the next century.[81][82]

Most aspects of human physiology are closely homologous to corresponding aspects of animal physiology. The human body consists of the legs, the torso, the arms, the neck, and the head. An adult human body consists of about 100 trillion (1014) cells. The most commonly defined body systems in humans are the nervous, the cardiovascular, the circulatory, the digestive, the endocrine, the immune, the integumentary, the lymphatic, the muscoskeletal, the reproductive, the respiratory, and the urinary system.[83][84]

Humans, like most of the other apes, lack external tails, have several blood type systems, have opposable thumbs, and are sexually dimorphic. The comparatively minor anatomical differences between humans and chimpanzees are a result of human bipedalism. One difference is that humans have a far faster and more accurate throw than other animals. Humans are also among the best long-distance runners in the animal kingdom, but slower over short distances.[85][86] Humans’ thinner body hair and more productive sweat glands help avoid heat exhaustion while running for long distances.[87]

As a consequence of bipedalism, human females have narrower birth canals. The construction of the human pelvis differs from other primates, as do the toes. A trade-off for these advantages of the modern human pelvis is that childbirth is more difficult and dangerous than in most mammals, especially given the larger head size of human babies compared to other primates. This means that human babies must turn around as they pass through the birth canal, which other primates do not do, and it makes humans the only species where females require help from their conspecifics[clarification needed] to reduce the risks of birthing. As a partial evolutionary solution, human fetuses are born less developed and more vulnerable. Chimpanzee babies are cognitively more developed than human babies until the age of six months, when the rapid development of human brains surpasses chimpanzees. Another difference between women and chimpanzee females is that women go through the menopause and become unfertile decades before the end of their lives. All species of non-human apes are capable of giving birth until death. Menopause probably developed as it has provided an evolutionary advantage (more caring time) to young relatives.[86]

Apart from bipedalism, humans differ from chimpanzees mostly in smelling, hearing, digesting proteins, brain size, and the ability of language. Humans’ brains are about three times bigger than in chimpanzees. More importantly, the brain to body ratio is much higher in humans than in chimpanzees, and humans have a significantly more developed cerebral cortex, with a larger number of neurons. The mental abilities of humans are remarkable compared to other apes. Humans’ ability of speech is unique among primates. Humans are able to create new and complex ideas, and to develop technology, which is unprecedented among other organisms on Earth.[86]

It is estimated that the worldwide average height for an adult human male is about 172cm (5ft 712in),[citation needed] while the worldwide average height for adult human females is about 158cm (5ft 2in).[citation needed] Shrinkage of stature may begin in middle age in some individuals, but tends to be typical in the extremely aged.[88] Through history human populations have universally become taller, probably as a consequence of better nutrition, healthcare, and living conditions.[89] The average mass of an adult human is 5464kg (120140lb) for females and 7683kg (168183lb) for males.[90] Like many other conditions, body weight and body type is influenced by both genetic susceptibility and environment and varies greatly among individuals. (see obesity)[91][92]

Although humans appear hairless compared to other primates, with notable hair growth occurring chiefly on the top of the head, underarms and pubic area, the average human has more hair follicles on his or her body than the average chimpanzee. The main distinction is that human hairs are shorter, finer, and less heavily pigmented than the average chimpanzee’s, thus making them harder to see.[93] Humans have about 2 million sweat glands spread over their entire bodies, many more than chimpanzees, whose sweat glands are scarce and are mainly located on the palm of the hand and on the soles of the feet.[94]

The dental formula of humans is: Humans have proportionately shorter palates and much smaller teeth than other primates. They are the only primates to have short, relatively flush canine teeth. Humans have characteristically crowded teeth, with gaps from lost teeth usually closing up quickly in young individuals. Humans are gradually losing their wisdom teeth, with some individuals having them congenitally absent.[95]

Like all mammals, humans are a diploid eukaryotic species. Each somatic cell has two sets of 23 chromosomes, each set received from one parent; gametes have only one set of chromosomes, which is a mixture of the two parental sets. Among the 23 pairs of chromosomes there are 22 pairs of autosomes and one pair of sex chromosomes. Like other mammals, humans have an XY sex-determination system, so that females have the sex chromosomes XX and males have XY.[96]

One human genome was sequenced in full in 2003, and currently efforts are being made to achieve a sample of the genetic diversity of the species (see International HapMap Project). By present estimates, humans have approximately 22,000 genes.[97] The variation in human DNA is very small compared to other species, possibly suggesting a population bottleneck during the Late Pleistocene (around 100,000 years ago), in which the human population was reduced to a small number of breeding pairs.[98][99]Nucleotide diversity is based on single mutations called single nucleotide polymorphisms (SNPs). The nucleotide diversity between humans is about 0.1%, i.e. 1 difference per 1,000 base pairs.[100][101] A difference of 1 in 1,000 nucleotides between two humans chosen at random amounts to about 3 million nucleotide differences, since the human genome has about 3 billion nucleotides. Most of these single nucleotide polymorphisms (SNPs) are neutral but some (about 3 to 5%) are functional and influence phenotypic differences between humans through alleles.[citation needed]

By comparing the parts of the genome that are not under natural selection and which therefore accumulate mutations at a fairly steady rate, it is possible to reconstruct a genetic tree incorporating the entire human species since the last shared ancestor. Each time a certain mutation (SNP) appears in an individual and is passed on to his or her descendants, a haplogroup is formed including all of the descendants of the individual who will also carry that mutation. By comparing mitochondrial DNA, which is inherited only from the mother, geneticists have concluded that the last female common ancestor whose genetic marker is found in all modern humans, the so-called mitochondrial Eve, must have lived around 90,000 to 200,000 years ago.[102][103][104]

Human accelerated regions, first described in August 2006,[105][106] are a set of 49 segments of the human genome that are conserved throughout vertebrate evolution but are strikingly different in humans. They are named according to their degree of difference between humans and their nearest animal relative (chimpanzees) (HAR1 showing the largest degree of human-chimpanzee differences). Found by scanning through genomic databases of multiple species, some of these highly mutated areas may contribute to human-specific traits.[citation needed]

The forces of natural selection have continued to operate on human populations, with evidence that certain regions of the genome display directional selection in the past 15,000 years.[107]

As with other mammals, human reproduction takes place as internal fertilization by sexual intercourse. During this process, the male inserts his erect penis into the female’s vagina and ejaculates semen, which contains sperm. The sperm travels through the vagina and cervix into the uterus or Fallopian tubes for fertilization of the ovum. Upon fertilization and implantation, gestation then occurs within the female’s uterus.

The zygote divides inside the female’s uterus to become an embryo, which over a period of 38 weeks (9 months) of gestation becomes a fetus. After this span of time, the fully grown fetus is birthed from the woman’s body and breathes independently as an infant for the first time. At this point, most modern cultures recognize the baby as a person entitled to the full protection of the law, though some jurisdictions extend various levels of personhood earlier to human fetuses while they remain in the uterus.

Compared with other species, human childbirth is dangerous. Painful labors lasting 24 hours or more are not uncommon and sometimes lead to the death of the mother, the child or both.[108] This is because of both the relatively large fetal head circumference and the mother’s relatively narrow pelvis.[109][110] The chances of a successful labor increased significantly during the 20th century in wealthier countries with the advent of new medical technologies. In contrast, pregnancy and natural childbirth remain hazardous ordeals in developing regions of the world, with maternal death rates approximately 100 times greater than in developed countries.[111]

In developed countries, infants are typically 34kg (69pounds) in weight and 5060cm (2024inches) in height at birth.[112][not in citation given] However, low birth weight is common in developing countries, and contributes to the high levels of infant mortality in these regions.[113] Helpless at birth, humans continue to grow for some years, typically reaching sexual maturity at 12 to 15years of age. Females continue to develop physically until around the age of 18, whereas male development continues until around age 21. The human life span can be split into a number of stages: infancy, childhood, adolescence, young adulthood, adulthood and old age. The lengths of these stages, however, have varied across cultures and time periods. Compared to other primates, humans experience an unusually rapid growth spurt during adolescence, where the body grows 25% in size. Chimpanzees, for example, grow only 14%, with no pronounced spurt.[114] The presence of the growth spurt is probably necessary to keep children physically small until they are psychologically mature. Humans are one of the few species in which females undergo menopause. It has been proposed that menopause increases a woman’s overall reproductive success by allowing her to invest more time and resources in her existing offspring, and in turn their children (the grandmother hypothesis), rather than by continuing to bear children into old age.[115][116]

For various reasons, including biological/genetic causes,[117] women live on average about four years longer than menas of 2013 the global average life expectancy at birth of a girl is estimated at 70.2 years compared to 66.1 for a boy.[118] There are significant geographical variations in human life expectancy, mostly correlated with economic developmentfor example life expectancy at birth in Hong Kong is 84.8years for girls and 78.9 for boys, while in Swaziland, primarily because of AIDS, it is 31.3years for both sexes.[119] The developed world is generally aging, with the median age around 40years. In the developing world the median age is between 15 and 20years. While one in five Europeans is 60years of age or older, only one in twenty Africans is 60years of age or older.[120] The number of centenarians (humans of age 100years or older) in the world was estimated by the United Nations at 210,000 in 2002.[121] At least one person, Jeanne Calment, is known to have reached the age of 122years;[122] higher ages have been claimed but they are not well substantiated.

Humans are omnivorous, capable of consuming a wide variety of plant and animal material.[123][124] Varying with available food sources in regions of habitation, and also varying with cultural and religious norms, human groups have adopted a range of diets, from purely vegetarian to primarily carnivorous. In some cases, dietary restrictions in humans can lead to deficiency diseases; however, stable human groups have adapted to many dietary patterns through both genetic specialization and cultural conventions to use nutritionally balanced food sources.[125] The human diet is prominently reflected in human culture, and has led to the development of food science.

Until the development of agriculture approximately 10,000 years ago, Homo sapiens employed a hunter-gatherer method as their sole means of food collection. This involved combining stationary food sources (such as fruits, grains, tubers, and mushrooms, insect larvae and aquatic mollusks) with wild game, which must be hunted and killed in order to be consumed.[126] It has been proposed that humans have used fire to prepare and cook food since the time of Homo erectus.[127] Around ten thousand years ago, humans developed agriculture,[128] which substantially altered their diet. This change in diet may also have altered human biology; with the spread of dairy farming providing a new and rich source of food, leading to the evolution of the ability to digest lactose in some adults.[129][130] Agriculture led to increased populations, the development of cities, and because of increased population density, the wider spread of infectious diseases. The types of food consumed, and the way in which they are prepared, have varied widely by time, location, and culture.

In general, humans can survive for two to eight weeks without food, depending on stored body fat. Survival without water is usually limited to three or four days. About 36 million humans die every year from causes directly or indirectly related to starvation.[131] Childhood malnutrition is also common and contributes to the global burden of disease.[132] However global food distribution is not even, and obesity among some human populations has increased rapidly, leading to health complications and increased mortality in some developed, and a few developing countries. Worldwide over one billion people are obese,[133] while in the United States 35% of people are obese, leading to this being described as an “obesity epidemic.”[134] Obesity is caused by consuming more calories than are expended, so excessive weight gain is usually caused by an energy-dense diet.[133]

No two humansnot even monozygotic twinsare genetically identical. Genes and environment influence human biological variation from visible characteristics to physiology to disease susceptibly to mental abilities. The exact influence of genes and environment on certain traits is not well understood.[135][136]

Most current genetic and archaeological evidence supports a recent single origin of modern humans in East Africa,[137] with first migrations placed at 60,000 years ago. Compared to the great apes, human gene sequenceseven among African populationsare remarkably homogeneous.[138] On average, genetic similarity between any two humans is 99.9%.[139][140] There is about 23 times more genetic diversity within the wild chimpanzee population, than in the entire human gene pool.[141][142][143]

The human body’s ability to adapt to different environmental stresses is remarkable, allowing humans to acclimatize to a wide variety of temperatures, humidity, and altitudes. As a result, humans are a cosmopolitan species found in almost all regions of the world, including tropical rainforests, arid desert, extremely cold arctic regions, and heavily polluted cities. Most other species are confined to a few geographical areas by their limited adaptability.[144]

There is biological variation in the human specieswith traits such as blood type, cranial features, eye color, hair color and type, height and build, and skin color varying across the globe. Human body types vary substantially. The typical height of an adult human is between 1.4m and 1.9m (4ft 7 in and 6ft 3 in), although this varies significantly depending, among other things, on sex and ethnic origin.[145][146] Body size is partly determined by genes and is also significantly influenced by environmental factors such as diet, exercise, and sleep patterns, especially as an influence in childhood. Adult height for each sex in a particular ethnic group approximately follows a normal distribution. Those aspects of genetic variation that give clues to human evolutionary history, or are relevant to medical research, have received particular attention. For example, the genes that allow adult humans to digest lactose are present in high frequencies in populations that have long histories of cattle domestication, suggesting natural selection having favored that gene in populations that depend on cow milk. Some hereditary diseases such as sickle cell anemia are frequent in populations where malaria has been endemic throughout historyit is believed that the same gene gives increased resistance to malaria among those who are unaffected carriers of the gene. Similarly, populations that have for a long time inhabited specific climates, such as arctic or tropical regions or high altitudes, tend to have developed specific phenotypes that are beneficial for conserving energy in those environmentsshort stature and stocky build in cold regions, tall and lanky in hot regions, and with high lung capacities at high altitudes. Similarly, skin color varies clinally with darker skin around the equatorwhere the added protection from the sun’s ultraviolet radiation is thought to give an evolutionary advantageand lighter skin tones closer to the poles.[147][148][149][150]

The hue of human skin and hair is determined by the presence of pigments called melanins. Human skin color can range from darkest brown to lightest peach, or even nearly white or colorless in cases of albinism.[143] Human hair ranges in color from white to red to blond to brown to black, which is most frequent.[151] Hair color depends on the amount of melanin (an effective sun blocking pigment) in the skin and hair, with hair melanin concentrations in hair fading with increased age, leading to grey or even white hair. Most researchers believe that skin darkening is an adaptation that evolved as protection against ultraviolet solar radiation, which also helps balancing folate, which is destroyed by ultraviolet radiation. Light skin pigmentation protects against depletion of vitamin D, which requires sunlight to make.[152] Skin pigmentation of contemporary humans is clinally distributed across the planet, and in general correlates with the level of ultraviolet radiation in a particular geographic area. Human skin also has a capacity to darken (tan) in response to exposure to ultraviolet radiation.[153][154][155]

Within the human species, the greatest degree of genetic variation exists between males and females. While the nucleotide genetic variation of individuals of the same sex across global populations is no greater than 0.1%, the genetic difference between males and females is between 1% and 2%. Although different in nature[clarification needed], this approaches the genetic differentiation between men and male chimpanzees or women and female chimpanzees. The genetic difference between sexes contributes to anatomical, hormonal, neural, and physiological differences between men and women, although the exact degree and nature of social and environmental influences on sexes are not completely understood. Males on average are 15% heavier and 15cm taller than females. There is a difference between body types, body organs and systems, hormonal levels, sensory systems, and muscle mass between sexes. On average, there is a difference of about 4050% in upper body strength and 2030% in lower body strength between men and women. Women generally have a higher body fat percentage than men. Women have lighter skin than men of the same population; this has been explained by a higher need for vitamin D (which is synthesized by sunlight) in females during pregnancy and lactation. As there are chromosomal differences between females and males, some X and Y chromosome related conditions and disorders only affect either men or women. Other conditional differences between males and females are not related to sex chromosomes. Even after allowing for body weight and volume, the male voice is usually an octave deeper than the female voice. Women have a longer life span in almost every population around the world.[157][158][159][160][161][162][163][164][165]

Males typically have larger tracheae and branching bronchi, with about 30% greater lung volume per unit body mass. They have larger hearts, 10% higher red blood cell count, and higher hemoglobin, hence greater oxygen-carrying capacity. They also have higher circulating clotting factors (vitamin K, prothrombin and platelets). These differences lead to faster healing of wounds and higher peripheral pain tolerance.[166] Females typically have more white blood cells (stored and circulating), more granulocytes and B and T lymphocytes. Additionally, they produce more antibodies at a faster rate than males. Hence they develop fewer infectious diseases and these continue for shorter periods.[166]Ethologists argue that females, interacting with other females and multiple offspring in social groups, have experienced such traits as a selective advantage.[167][168][169][170][171] According to Daly and Wilson, “The sexes differ more in human beings than in monogamous mammals, but much less than in extremely polygamous mammals.”[172] But given that sexual dimorphism in the closest relatives of humans is much greater than among humans, the human clade must be considered to be characterized by decreasing sexual dimorphism, probably due to less competitive mating patterns. One proposed explanation is that human sexuality has developed more in common with its close relative the bonobo, which exhibits similar sexual dimorphism, is polygynandrous and uses recreational sex to reinforce social bonds and reduce aggression.[173]

Humans of the same sex are 99.9% genetically identical. There is extremely little variation between human geographical populations, and most of the variation that does occur is at the personal level within local areas, and not between populations.[143][174][175] Of the 0.1% of human genetic differentiation, 85% exists within any randomly chosen local population, be they Italians, Koreans, or Kurds. Two randomly chosen Koreans may be genetically as different as a Korean and an Italian. Any ethnic group contains 85% of the human genetic diversity of the world. Genetic data shows that no matter how population groups are defined, two people from the same population group are about as different from each other as two people from any two different population groups.[143][176][177][178]

Current genetic research has demonstrated that humans on the African continent are the most genetically diverse.[179] There is more human genetic diversity in Africa than anywhere else on Earth. The genetic structure of Africans was traced to 14 ancestral population clusters. Human genetic diversity decreases in native populations with migratory distance from Africa and this is thought to be the result of bottlenecks during human migration.[180][181] Humans have lived in Africa for the longest time, which has allowed accumulation of a higher diversity of genetic mutations in these populations. Only part of Africa’s population migrated out of the continent, bringing just part of the original African genetic variety with them. African populations harbor genetic alleles that are not found in other places of the world. All the common alleles found in populations outside of Africa are found on the African continent.[143]

Geographical distribution of human variation is complex and constantly shifts through time which reflects complicated human evolutionary history. Most human biological variation is clinally distributed and blends gradually from one area to the next. Groups of people around the world have different frequencies of polymorphic genes. Furthermore, different traits are non-concordant and each have different clinal distribution. Adaptability varies both from person to person and from population to population. The most efficient adaptive responses are found in geographical populations where the environmental stimuli are the strongest (e.g. Tibetans are highly adapted to high altitudes). The clinal geographic genetic variation is further complicated by the migration and mixing between human populations which has been occurring since prehistoric times.[143][182][183][184][185][186]

Human – Wikipedia

Evolution – Wikipedia

Evolution is change in the heritable characteristics of biological populations over successive generations.[1][2] Evolutionary processes give rise to biodiversity at every level of biological organisation, including the levels of species, individual organisms, and molecules.[3]

All life on Earth shares a common ancestor known as the last universal common ancestor (LUCA),[4][5][6] which lived approximately 3.53.8 billion years ago,[7] although a study in 2015 found “remains of biotic life” from 4.1 billion years ago in ancient rocks in Western Australia.[8][9] In July 2016, scientists reported identifying a set of 355 genes from the LUCA of all organisms living on Earth.[10]

Repeated formation of new species (speciation), change within species (anagenesis), and loss of species (extinction) throughout the evolutionary history of life on Earth are demonstrated by shared sets of morphological and biochemical traits, including shared DNA sequences.[11] These shared traits are more similar among species that share a more recent common ancestor, and can be used to reconstruct a biological “tree of life” based on evolutionary relationships (phylogenetics), using both existing species and fossils. The fossil record includes a progression from early biogenic graphite,[12] to microbial mat fossils,[13][14][15] to fossilized multicellular organisms. Existing patterns of biodiversity have been shaped both by speciation and by extinction.[16] More than 99 percent of all species that ever lived on Earth are estimated to be extinct.[17][18] Estimates of Earth’s current species range from 10 to 14 million,[19] of which about 1.2 million have been documented.[20] More recently, in May 2016, scientists reported that 1 trillion species are estimated to be on Earth currently with only one-thousandth of one percent described.[21]

In the mid-19th century, Charles Darwin formulated the scientific theory of evolution by natural selection, published in his book On the Origin of Species (1859). Evolution by natural selection is a process demonstrated by the observation that more offspring are produced than can possibly survive, along with three facts about populations: 1) traits vary among individuals with respect to morphology, physiology, and behaviour (phenotypic variation), 2) different traits confer different rates of survival and reproduction (differential fitness), and 3) traits can be passed from generation to generation (heritability of fitness).[22] Thus, in successive generations members of a population are replaced by progeny of parents better adapted to survive and reproduce in the biophysical environment in which natural selection takes place. This teleonomy is the quality whereby the process of natural selection creates and preserves traits that are seemingly fitted for the functional roles they perform.[23] Natural selection, including sexual selection, is the only known cause of adaptation but not the only known cause of evolution. Other, nonadaptive evolutionary processes include mutation, genetic drift and gene migration.[24]

In the early 20th century the modern evolutionary synthesis integrated classical genetics with Darwin’s theory of evolution by natural selection through the discipline of population genetics. The importance of natural selection as a cause of evolution was accepted into other branches of biology. Moreover, previously held notions about evolution, such as orthogenesis, evolutionism, and other beliefs about innate “progress” within the largest-scale trends in evolution, became obsolete scientific theories.[25] Scientists continue to study various aspects of evolutionary biology by forming and testing hypotheses, constructing mathematical models of theoretical biology and biological theories, using observational data, and performing experiments in both the field and the laboratory.

In terms of practical application, an understanding of evolution has been instrumental to developments in numerous scientific and industrial fields, including agriculture, human and veterinary medicine, and the life sciences in general.[26][27][28] Discoveries in evolutionary biology have made a significant impact not just in the traditional branches of biology but also in other academic disciplines, including biological anthropology, and evolutionary psychology.[29][30]Evolutionary computation, a sub-field of artificial intelligence, involves the application of Darwinian principles to problems in computer science.

The proposal that one type of organism could descend from another type goes back to some of the first pre-Socratic Greek philosophers, such as Anaximander and Empedocles.[32] Such proposals survived into Roman times. The poet and philosopher Lucretius followed Empedocles in his masterwork De rerum natura (On the Nature of Things).[33][34] In contrast to these materialistic views, Aristotle considered all natural things, not only living things, as being imperfect actualisations of different fixed natural possibilities, known as “forms,” “ideas,” or (in Latin translations) “species.”[35][36] This was part of his teleological understanding of nature in which all things have an intended role to play in a divine cosmic order. Variations of this idea became the standard understanding of the Middle Ages and were integrated into Christian learning, but Aristotle did not demand that real types of organisms always correspond one-for-one with exact metaphysical forms and specifically gave examples of how new types of living things could come to be.[37]

In the 17th century, the new method of modern science rejected Aristotle’s approach. It sought explanations of natural phenomena in terms of physical laws that were the same for all visible things and that did not require the existence of any fixed natural categories or divine cosmic order. However, this new approach was slow to take root in the biological sciences, the last bastion of the concept of fixed natural types. John Ray applied one of the previously more general terms for fixed natural types, “species,” to plant and animal types, but he strictly identified each type of living thing as a species and proposed that each species could be defined by the features that perpetuated themselves generation after generation.[38] The biological classification introduced by Carl Linnaeus in 1735 explicitly recognized the hierarchical nature of species relationships, but still viewed species as fixed according to a divine plan.[39]

Other naturalists of this time speculated on the evolutionary change of species over time according to natural laws. In 1751, Pierre Louis Maupertuis wrote of natural modifications occurring during reproduction and accumulating over many generations to produce new species.[40]Georges-Louis Leclerc, Comte de Buffon suggested that species could degenerate into different organisms, and Erasmus Darwin proposed that all warm-blooded animals could have descended from a single microorganism (or “filament”).[41] The first full-fledged evolutionary scheme was Jean-Baptiste Lamarck’s “transmutation” theory of 1809,[42] which envisaged spontaneous generation continually producing simple forms of life that developed greater complexity in parallel lineages with an inherent progressive tendency, and postulated that on a local level these lineages adapted to the environment by inheriting changes caused by their use or disuse in parents.[43][44] (The latter process was later called Lamarckism.)[43][45][46][47] These ideas were condemned by established naturalists as speculation lacking empirical support. In particular, Georges Cuvier insisted that species were unrelated and fixed, their similarities reflecting divine design for functional needs. In the meantime, Ray’s ideas of benevolent design had been developed by William Paley into the Natural Theology or Evidences of the Existence and Attributes of the Deity (1802), which proposed complex adaptations as evidence of divine design and which was admired by Charles Darwin.[48][49][50]

The crucial break from the concept of constant typological classes or types in biology came with the theory of evolution through natural selection, which was formulated by Charles Darwin in terms of variable populations. Partly influenced by An Essay on the Principle of Population (1798) by Thomas Robert Malthus, Darwin noted that population growth would lead to a “struggle for existence” in which favorable variations prevailed as others perished. In each generation, many offspring fail to survive to an age of reproduction because of limited resources. This could explain the diversity of plants and animals from a common ancestry through the working of natural laws in the same way for all types of organism.[51][52][53][54] Darwin developed his theory of “natural selection” from 1838 onwards and was writing up his “big book” on the subject when Alfred Russel Wallace sent him a version of virtually the same theory in 1858. Their separate papers were presented together at a 1858 meeting of the Linnean Society of London.[55] At the end of 1859, Darwin’s publication of his “abstract” as On the Origin of Species explained natural selection in detail and in a way that led to an increasingly wide acceptance of concepts of evolution. Thomas Henry Huxley applied Darwin’s ideas to humans, using paleontology and comparative anatomy to provide strong evidence that humans and apes shared a common ancestry. Some were disturbed by this since it implied that humans did not have a special place in the universe.[56]

Precise mechanisms of reproductive heritability and the origin of new traits remained a mystery. Towards this end, Darwin developed his provisional theory of pangenesis.[57] In 1865, Gregor Mendel reported that traits were inherited in a predictable manner through the independent assortment and segregation of elements (later known as genes). Mendel’s laws of inheritance eventually supplanted most of Darwin’s pangenesis theory.[58]August Weismann made the important distinction between germ cells that give rise to gametes (such as sperm and egg cells) and the somatic cells of the body, demonstrating that heredity passes through the germ line only. Hugo de Vries connected Darwin’s pangenesis theory to Weismann’s germ/soma cell distinction and proposed that Darwin’s pangenes were concentrated in the cell nucleus and when expressed they could move into the cytoplasm to change the cells structure. De Vries was also one of the researchers who made Mendel’s work well-known, believing that Mendelian traits corresponded to the transfer of heritable variations along the germline.[59] To explain how new variants originate, de Vries developed a mutation theory that led to a temporary rift between those who accepted Darwinian evolution and biometricians who allied with de Vries.[44][60][61] In the 1930s, pioneers in the field of population genetics, such as Ronald Fisher, Sewall Wright and J. B. S. Haldane set the foundations of evolution onto a robust statistical philosophy. The false contradiction between Darwin’s theory, genetic mutations, and Mendelian inheritance was thus reconciled.[62]

In the 1920s and 1930s a modern evolutionary synthesis connected natural selection, mutation theory, and Mendelian inheritance into a unified theory that applied generally to any branch of biology. The modern synthesis was able to explain patterns observed across species in populations, through fossil transitions in palaeontology, and even complex cellular mechanisms in developmental biology.[44][63] The publication of the structure of DNA by James Watson and Francis Crick in 1953 demonstrated a physical mechanism for inheritance.[64]Molecular biology improved our understanding of the relationship between genotype and phenotype. Advancements were also made in phylogenetic systematics, mapping the transition of traits into a comparative and testable framework through the publication and use of evolutionary trees.[65][66] In 1973, evolutionary biologist Theodosius Dobzhansky penned that “nothing in biology makes sense except in the light of evolution,” because it has brought to light the relations of what first seemed disjointed facts in natural history into a coherent explanatory body of knowledge that describes and predicts many observable facts about life on this planet.[67]

Since then, the modern synthesis has been further extended to explain biological phenomena across the full and integrative scale of the biological hierarchy, from genes to species. This extension, known as evolutionary developmental biology and informally called “evo-devo,” emphasises how changes between generations (evolution) acts on patterns of change within individual organisms (development).[68][69][70]

Evolution in organisms occurs through changes in heritable traitsthe inherited characteristics of an organism. In humans, for example, eye colour is an inherited characteristic and an individual might inherit the “brown-eye trait” from one of their parents.[71] Inherited traits are controlled by genes and the complete set of genes within an organism’s genome (genetic material) is called its genotype.[72]

The complete set of observable traits that make up the structure and behaviour of an organism is called its phenotype. These traits come from the interaction of its genotype with the environment.[73] As a result, many aspects of an organism’s phenotype are not inherited. For example, suntanned skin comes from the interaction between a person’s genotype and sunlight; thus, suntans are not passed on to people’s children. However, some people tan more easily than others, due to differences in genotypic variation; a striking example are people with the inherited trait of albinism, who do not tan at all and are very sensitive to sunburn.[74]

Heritable traits are passed from one generation to the next via DNA, a molecule that encodes genetic information.[72] DNA is a long biopolymer composed of four types of bases. The sequence of bases along a particular DNA molecule specify the genetic information, in a manner similar to a sequence of letters spelling out a sentence. Before a cell divides, the DNA is copied, so that each of the resulting two cells will inherit the DNA sequence. Portions of a DNA molecule that specify a single functional unit are called genes; different genes have different sequences of bases. Within cells, the long strands of DNA form condensed structures called chromosomes. The specific location of a DNA sequence within a chromosome is known as a locus. If the DNA sequence at a locus varies between individuals, the different forms of this sequence are called alleles. DNA sequences can change through mutations, producing new alleles. If a mutation occurs within a gene, the new allele may affect the trait that the gene controls, altering the phenotype of the organism.[75] However, while this simple correspondence between an allele and a trait works in some cases, most traits are more complex and are controlled by quantitative trait loci (multiple interacting genes).[76][77]

Recent findings have confirmed important examples of heritable changes that cannot be explained by changes to the sequence of nucleotides in the DNA. These phenomena are classed as epigenetic inheritance systems.[78]DNA methylation marking chromatin, self-sustaining metabolic loops, gene silencing by RNA interference and the three-dimensional conformation of proteins (such as prions) are areas where epigenetic inheritance systems have been discovered at the organismic level.[79][80] Developmental biologists suggest that complex interactions in genetic networks and communication among cells can lead to heritable variations that may underlay some of the mechanics in developmental plasticity and canalisation.[81] Heritability may also occur at even larger scales. For example, ecological inheritance through the process of niche construction is defined by the regular and repeated activities of organisms in their environment. This generates a legacy of effects that modify and feed back into the selection regime of subsequent generations. Descendants inherit genes plus environmental characteristics generated by the ecological actions of ancestors.[82] Other examples of heritability in evolution that are not under the direct control of genes include the inheritance of cultural traits and symbiogenesis.[83][84]

An individual organism’s phenotype results from both its genotype and the influence from the environment it has lived in. A substantial part of the phenotypic variation in a population is caused by genotypic variation.[77] The modern evolutionary synthesis defines evolution as the change over time in this genetic variation. The frequency of one particular allele will become more or less prevalent relative to other forms of that gene. Variation disappears when a new allele reaches the point of fixationwhen it either disappears from the population or replaces the ancestral allele entirely.[85]

Natural selection will only cause evolution if there is enough genetic variation in a population. Before the discovery of Mendelian genetics, one common hypothesis was blending inheritance. But with blending inheritance, genetic variance would be rapidly lost, making evolution by natural selection implausible. The HardyWeinberg principle provides the solution to how variation is maintained in a population with Mendelian inheritance. The frequencies of alleles (variations in a gene) will remain constant in the absence of selection, mutation, migration and genetic drift.[86]

Variation comes from mutations in the genome, reshuffling of genes through sexual reproduction and migration between populations (gene flow). Despite the constant introduction of new variation through mutation and gene flow, most of the genome of a species is identical in all individuals of that species.[87] However, even relatively small differences in genotype can lead to dramatic differences in phenotype: for example, chimpanzees and humans differ in only about 5% of their genomes.[88]

Mutations are changes in the DNA sequence of a cell’s genome. When mutations occur, they may alter the product of a gene, or prevent the gene from functioning, or have no effect. Based on studies in the fly Drosophila melanogaster, it has been suggested that if a mutation changes a protein produced by a gene, this will probably be harmful, with about 70% of these mutations having damaging effects, and the remainder being either neutral or weakly beneficial.[89]

Mutations can involve large sections of a chromosome becoming duplicated (usually by genetic recombination), which can introduce extra copies of a gene into a genome.[90] Extra copies of genes are a major source of the raw material needed for new genes to evolve.[91] This is important because most new genes evolve within gene families from pre-existing genes that share common ancestors.[92] For example, the human eye uses four genes to make structures that sense light: three for colour vision and one for night vision; all four are descended from a single ancestral gene.[93]

New genes can be generated from an ancestral gene when a duplicate copy mutates and acquires a new function. This process is easier once a gene has been duplicated because it increases the redundancy of the system; one gene in the pair can acquire a new function while the other copy continues to perform its original function.[94][95] Other types of mutations can even generate entirely new genes from previously noncoding DNA.[96][97]

The generation of new genes can also involve small parts of several genes being duplicated, with these fragments then recombining to form new combinations with new functions.[98][99] When new genes are assembled from shuffling pre-existing parts, domains act as modules with simple independent functions, which can be mixed together to produce new combinations with new and complex functions.[100] For example, polyketide synthases are large enzymes that make antibiotics; they contain up to one hundred independent domains that each catalyse one step in the overall process, like a step in an assembly line.[101]

In asexual organisms, genes are inherited together, or linked, as they cannot mix with genes of other organisms during reproduction. In contrast, the offspring of sexual organisms contain random mixtures of their parents’ chromosomes that are produced through independent assortment. In a related process called homologous recombination, sexual organisms exchange DNA between two matching chromosomes.[102] Recombination and reassortment do not alter allele frequencies, but instead change which alleles are associated with each other, producing offspring with new combinations of alleles.[103] Sex usually increases genetic variation and may increase the rate of evolution.[104][105]

The two-fold cost of sex was first described by John Maynard Smith.[106] The first cost is that in sexually dimorphic species only one of the two sexes can bear young. (This cost does not apply to hermaphroditic species, like most plants and many invertebrates.) The second cost is that any individual who reproduces sexually can only pass on 50% of its genes to any individual offspring, with even less passed on as each new generation passes.[107] Yet sexual reproduction is the more common means of reproduction among eukaryotes and multicellular organisms. The Red Queen hypothesis has been used to explain the significance of sexual reproduction as a means to enable continual evolution and adaptation in response to coevolution with other species in an ever-changing environment.[107][108][109][110]

Gene flow is the exchange of genes between populations and between species.[111] It can therefore be a source of variation that is new to a population or to a species. Gene flow can be caused by the movement of individuals between separate populations of organisms, as might be caused by the movement of mice between inland and coastal populations, or the movement of pollen between heavy metal tolerant and heavy metal sensitive populations of grasses.

Gene transfer between species includes the formation of hybrid organisms and horizontal gene transfer. Horizontal gene transfer is the transfer of genetic material from one organism to another organism that is not its offspring; this is most common among bacteria.[112] In medicine, this contributes to the spread of antibiotic resistance, as when one bacteria acquires resistance genes it can rapidly transfer them to other species.[113] Horizontal transfer of genes from bacteria to eukaryotes such as the yeast Saccharomyces cerevisiae and the adzuki bean weevil Callosobruchus chinensis has occurred.[114][115] An example of larger-scale transfers are the eukaryotic bdelloid rotifers, which have received a range of genes from bacteria, fungi and plants.[116]Viruses can also carry DNA between organisms, allowing transfer of genes even across biological domains.[117]

Large-scale gene transfer has also occurred between the ancestors of eukaryotic cells and bacteria, during the acquisition of chloroplasts and mitochondria. It is possible that eukaryotes themselves originated from horizontal gene transfers between bacteria and archaea.[118]

From a Neo-Darwinian perspective, evolution occurs when there are changes in the frequencies of alleles within a population of interbreeding organisms.[86] For example, the allele for black colour in a population of moths becoming more common. Mechanisms that can lead to changes in allele frequencies include natural selection, genetic drift, genetic hitchhiking, mutation and gene flow.

Evolution by means of natural selection is the process by which traits that enhance survival and reproduction become more common in successive generations of a population. It has often been called a “self-evident” mechanism because it necessarily follows from three simple facts:[22]

More offspring are produced than can possibly survive, and these conditions produce competition between organisms for survival and reproduction. Consequently, organisms with traits that give them an advantage over their competitors are more likely to pass on their traits to the next generation than those with traits that do not confer an advantage.[119]

The central concept of natural selection is the evolutionary fitness of an organism.[120] Fitness is measured by an organism’s ability to survive and reproduce, which determines the size of its genetic contribution to the next generation.[120] However, fitness is not the same as the total number of offspring: instead fitness is indicated by the proportion of subsequent generations that carry an organism’s genes.[121] For example, if an organism could survive well and reproduce rapidly, but its offspring were all too small and weak to survive, this organism would make little genetic contribution to future generations and would thus have low fitness.[120]

If an allele increases fitness more than the other alleles of that gene, then with each generation this allele will become more common within the population. These traits are said to be “selected for.” Examples of traits that can increase fitness are enhanced survival and increased fecundity. Conversely, the lower fitness caused by having a less beneficial or deleterious allele results in this allele becoming rarerthey are “selected against.”[122] Importantly, the fitness of an allele is not a fixed characteristic; if the environment changes, previously neutral or harmful traits may become beneficial and previously beneficial traits become harmful.[75] However, even if the direction of selection does reverse in this way, traits that were lost in the past may not re-evolve in an identical form (see Dollo’s law).[123][124]

Natural selection within a population for a trait that can vary across a range of values, such as height, can be categorised into three different types. The first is directional selection, which is a shift in the average value of a trait over timefor example, organisms slowly getting taller.[125] Secondly, disruptive selection is selection for extreme trait values and often results in two different values becoming most common, with selection against the average value. This would be when either short or tall organisms had an advantage, but not those of medium height. Finally, in stabilising selection there is selection against extreme trait values on both ends, which causes a decrease in variance around the average value and less diversity.[119][126] This would, for example, cause organisms to slowly become all the same height.

A special case of natural selection is sexual selection, which is selection for any trait that increases mating success by increasing the attractiveness of an organism to potential mates.[127] Traits that evolved through sexual selection are particularly prominent among males of several animal species. Although sexually favoured, traits such as cumbersome antlers, mating calls, large body size and bright colours often attract predation, which compromises the survival of individual males.[128][129] This survival disadvantage is balanced by higher reproductive success in males that show these hard-to-fake, sexually selected traits.[130]

Natural selection most generally makes nature the measure against which individuals and individual traits, are more or less likely to survive. “Nature” in this sense refers to an ecosystem, that is, a system in which organisms interact with every other element, physical as well as biological, in their local environment. Eugene Odum, a founder of ecology, defined an ecosystem as: “Any unit that includes all of the organisms…in a given area interacting with the physical environment so that a flow of energy leads to clearly defined trophic structure, biotic diversity and material cycles (ie: exchange of materials between living and nonliving parts) within the system.”[131] Each population within an ecosystem occupies a distinct niche, or position, with distinct relationships to other parts of the system. These relationships involve the life history of the organism, its position in the food chain and its geographic range. This broad understanding of nature enables scientists to delineate specific forces which, together, comprise natural selection.

Natural selection can act at different levels of organisation, such as genes, cells, individual organisms, groups of organisms and species.[132][133][134] Selection can act at multiple levels simultaneously.[135] An example of selection occurring below the level of the individual organism are genes called transposons, which can replicate and spread throughout a genome.[136] Selection at a level above the individual, such as group selection, may allow the evolution of cooperation, as discussed below.[137]

In addition to being a major source of variation, mutation may also function as a mechanism of evolution when there are different probabilities at the molecular level for different mutations to occur, a process known as mutation bias.[138] If two genotypes, for example one with the nucleotide G and another with the nucleotide A in the same position, have the same fitness, but mutation from G to A happens more often than mutation from A to G, then genotypes with A will tend to evolve.[139] Different insertion vs. deletion mutation biases in different taxa can lead to the evolution of different genome sizes.[140][141] Developmental or mutational biases have also been observed in morphological evolution.[142][143] For example, according to the phenotype-first theory of evolution, mutations can eventually cause the genetic assimilation of traits that were previously induced by the environment.[144][145]

Mutation bias effects are superimposed on other processes. If selection would favor either one out of two mutations, but there is no extra advantage to having both, then the mutation that occurs the most frequently is the one that is most likely to become fixed in a population.[146][147] Mutations leading to the loss of function of a gene are much more common than mutations that produce a new, fully functional gene. Most loss of function mutations are selected against. But when selection is weak, mutation bias towards loss of function can affect evolution.[148] For example, pigments are no longer useful when animals live in the darkness of caves, and tend to be lost.[149] This kind of loss of function can occur because of mutation bias, and/or because the function had a cost, and once the benefit of the function disappeared, natural selection leads to the loss. Loss of sporulation ability in Bacillus subtilis during laboratory evolution appears to have been caused by mutation bias, rather than natural selection against the cost of maintaining sporulation ability.[150] When there is no selection for loss of function, the speed at which loss evolves depends more on the mutation rate than it does on the effective population size,[151] indicating that it is driven more by mutation bias than by genetic drift. In parasitic organisms, mutation bias leads to selection pressures as seen in Ehrlichia. Mutations are biased towards antigenic variants in outer-membrane proteins.

Genetic drift is the change in allele frequency from one generation to the next that occurs because alleles are subject to sampling error.[152] As a result, when selective forces are absent or relatively weak, allele frequencies tend to “drift” upward or downward randomly (in a random walk). This drift halts when an allele eventually becomes fixed, either by disappearing from the population, or replacing the other alleles entirely. Genetic drift may therefore eliminate some alleles from a population due to chance alone. Even in the absence of selective forces, genetic drift can cause two separate populations that began with the same genetic structure to drift apart into two divergent populations with different sets of alleles.[153]

It is usually difficult to measure the relative importance of selection and neutral processes, including drift.[154] The comparative importance of adaptive and non-adaptive forces in driving evolutionary change is an area of current research.[155]

The neutral theory of molecular evolution proposed that most evolutionary changes are the result of the fixation of neutral mutations by genetic drift.[156] Hence, in this model, most genetic changes in a population are the result of constant mutation pressure and genetic drift.[157] This form of the neutral theory is now largely abandoned, since it does not seem to fit the genetic variation seen in nature.[158][159] However, a more recent and better-supported version of this model is the nearly neutral theory, where a mutation that would be effectively neutral in a small population is not necessarily neutral in a large population.[119] Other alternative theories propose that genetic drift is dwarfed by other stochastic forces in evolution, such as genetic hitchhiking, also known as genetic draft.[152][160][161]

The time for a neutral allele to become fixed by genetic drift depends on population size, with fixation occurring more rapidly in smaller populations.[162] The number of individuals in a population is not critical, but instead a measure known as the effective population size.[163] The effective population is usually smaller than the total population since it takes into account factors such as the level of inbreeding and the stage of the lifecycle in which the population is the smallest.[163] The effective population size may not be the same for every gene in the same population.[164]

Recombination allows alleles on the same strand of DNA to become separated. However, the rate of recombination is low (approximately two events per chromosome per generation). As a result, genes close together on a chromosome may not always be shuffled away from each other and genes that are close together tend to be inherited together, a phenomenon known as linkage.[165] This tendency is measured by finding how often two alleles occur together on a single chromosome compared to expectations, which is called their linkage disequilibrium. A set of alleles that is usually inherited in a group is called a haplotype. This can be important when one allele in a particular haplotype is strongly beneficial: natural selection can drive a selective sweep that will also cause the other alleles in the haplotype to become more common in the population; this effect is called genetic hitchhiking or genetic draft.[166] Genetic draft caused by the fact that some neutral genes are genetically linked to others that are under selection can be partially captured by an appropriate effective population size.[160]

Gene flow involves the exchange of genes between populations and between species.[111] The presence or absence of gene flow fundamentally changes the course of evolution. Due to the complexity of organisms, any two completely isolated populations will eventually evolve genetic incompatibilities through neutral processes, as in the Bateson-Dobzhansky-Muller model, even if both populations remain essentially identical in terms of their adaptation to the environment.

If genetic differentiation between populations develops, gene flow between populations can introduce traits or alleles which are disadvantageous in the local population and this may lead to organisms within these populations evolving mechanisms that prevent mating with genetically distant populations, eventually resulting in the appearance of new species. Thus, exchange of genetic information between individuals is fundamentally important for the development of the biological species concept.

During the development of the modern synthesis, Sewall Wright developed his shifting balance theory, which regarded gene flow between partially isolated populations as an important aspect of adaptive evolution.[167] However, recently there has been substantial criticism of the importance of the shifting balance theory.[168]

Evolution influences every aspect of the form and behaviour of organisms. Most prominent are the specific behavioural and physical adaptations that are the outcome of natural selection. These adaptations increase fitness by aiding activities such as finding food, avoiding predators or attracting mates. Organisms can also respond to selection by cooperating with each other, usually by aiding their relatives or engaging in mutually beneficial symbiosis. In the longer term, evolution produces new species through splitting ancestral populations of organisms into new groups that cannot or will not interbreed.

These outcomes of evolution are distinguished based on time scale as macroevolution versus microevolution. Macroevolution refers to evolution that occurs at or above the level of species, in particular speciation and extinction; whereas microevolution refers to smaller evolutionary changes within a species or population, in particular shifts in gene frequency and adaptation.[170] In general, macroevolution is regarded as the outcome of long periods of microevolution.[171] Thus, the distinction between micro- and macroevolution is not a fundamental onethe difference is simply the time involved.[172] However, in macroevolution, the traits of the entire species may be important. For instance, a large amount of variation among individuals allows a species to rapidly adapt to new habitats, lessening the chance of it going extinct, while a wide geographic range increases the chance of speciation, by making it more likely that part of the population will become isolated. In this sense, microevolution and macroevolution might involve selection at different levelswith microevolution acting on genes and organisms, versus macroevolutionary processes such as species selection acting on entire species and affecting their rates of speciation and extinction.[174][175]

A common misconception is that evolution has goals, long-term plans, or an innate tendency for “progress,” as expressed in beliefs such as orthogenesis and evolutionism; realistically however, evolution has no long-term goal and does not necessarily produce greater complexity.[176][177][178] Although complex species have evolved, they occur as a side effect of the overall number of organisms increasing and simple forms of life still remain more common in the biosphere.[179] For example, the overwhelming majority of species are microscopic prokaryotes, which form about half the world’s biomass despite their small size,[180] and constitute the vast majority of Earth’s biodiversity.[181] Simple organisms have therefore been the dominant form of life on Earth throughout its history and continue to be the main form of life up to the present day, with complex life only appearing more diverse because it is more noticeable.[182] Indeed, the evolution of microorganisms is particularly important to modern evolutionary research, since their rapid reproduction allows the study of experimental evolution and the observation of evolution and adaptation in real time.[183][184]

Adaptation is the process that makes organisms better suited to their habitat.[185][186] Also, the term adaptation may refer to a trait that is important for an organism’s survival. For example, the adaptation of horses’ teeth to the grinding of grass. By using the term adaptation for the evolutionary process and adaptive trait for the product (the bodily part or function), the two senses of the word may be distinguished. Adaptations are produced by natural selection.[187] The following definitions are due to Theodosius Dobzhansky:

Adaptation may cause either the gain of a new feature, or the loss of an ancestral feature. An example that shows both types of change is bacterial adaptation to antibiotic selection, with genetic changes causing antibiotic resistance by both modifying the target of the drug, or increasing the activity of transporters that pump the drug out of the cell.[191] Other striking examples are the bacteria Escherichia coli evolving the ability to use citric acid as a nutrient in a long-term laboratory experiment,[192]Flavobacterium evolving a novel enzyme that allows these bacteria to grow on the by-products of nylon manufacturing,[193][194] and the soil bacterium Sphingobium evolving an entirely new metabolic pathway that degrades the synthetic pesticide pentachlorophenol.[195][196] An interesting but still controversial idea is that some adaptations might increase the ability of organisms to generate genetic diversity and adapt by natural selection (increasing organisms’ evolvability).[197][198][199][200][201]

Adaptation occurs through the gradual modification of existing structures. Consequently, structures with similar internal organisation may have different functions in related organisms. This is the result of a single ancestral structure being adapted to function in different ways. The bones within bat wings, for example, are very similar to those in mice feet and primate hands, due to the descent of all these structures from a common mammalian ancestor.[203] However, since all living organisms are related to some extent,[204] even organs that appear to have little or no structural similarity, such as arthropod, squid and vertebrate eyes, or the limbs and wings of arthropods and vertebrates, can depend on a common set of homologous genes that control their assembly and function; this is called deep homology.[205][206]

During evolution, some structures may lose their original function and become vestigial structures.[207] Such structures may have little or no function in a current species, yet have a clear function in ancestral species, or other closely related species. Examples include pseudogenes,[208] the non-functional remains of eyes in blind cave-dwelling fish,[209] wings in flightless birds,[210] the presence of hip bones in whales and snakes,[202] and sexual traits in organisms that reproduce via asexual reproduction.[211] Examples of vestigial structures in humans include wisdom teeth,[212] the coccyx,[207] the vermiform appendix,[207] and other behavioural vestiges such as goose bumps[213][214] and primitive reflexes.[215][216][217]

However, many traits that appear to be simple adaptations are in fact exaptations: structures originally adapted for one function, but which coincidentally became somewhat useful for some other function in the process. One example is the African lizard Holaspis guentheri, which developed an extremely flat head for hiding in crevices, as can be seen by looking at its near relatives. However, in this species, the head has become so flattened that it assists in gliding from tree to treean exaptation. Within cells, molecular machines such as the bacterial flagella[219] and protein sorting machinery[220] evolved by the recruitment of several pre-existing proteins that previously had different functions.[170] Another example is the recruitment of enzymes from glycolysis and xenobiotic metabolism to serve as structural proteins called crystallins within the lenses of organisms’ eyes.[221][222]

An area of current investigation in evolutionary developmental biology is the developmental basis of adaptations and exaptations.[223] This research addresses the origin and evolution of embryonic development and how modifications of development and developmental processes produce novel features.[224] These studies have shown that evolution can alter development to produce new structures, such as embryonic bone structures that develop into the jaw in other animals instead forming part of the middle ear in mammals.[225] It is also possible for structures that have been lost in evolution to reappear due to changes in developmental genes, such as a mutation in chickens causing embryos to grow teeth similar to those of crocodiles.[226] It is now becoming clear that most alterations in the form of organisms are due to changes in a small set of conserved genes.[227]

Interactions between organisms can produce both conflict and cooperation. When the interaction is between pairs of species, such as a pathogen and a host, or a predator and its prey, these species can develop matched sets of adaptations. Here, the evolution of one species causes adaptations in a second species. These changes in the second species then, in turn, cause new adaptations in the first species. This cycle of selection and response is called coevolution.[228] An example is the production of tetrodotoxin in the rough-skinned newt and the evolution of tetrodotoxin resistance in its predator, the common garter snake. In this predator-prey pair, an evolutionary arms race has produced high levels of toxin in the newt and correspondingly high levels of toxin resistance in the snake.[229]

Not all co-evolved interactions between species involve conflict.[230] Many cases of mutually beneficial interactions have evolved. For instance, an extreme cooperation exists between plants and the mycorrhizal fungi that grow on their roots and aid the plant in absorbing nutrients from the soil.[231] This is a reciprocal relationship as the plants provide the fungi with sugars from photosynthesis. Here, the fungi actually grow inside plant cells, allowing them to exchange nutrients with their hosts, while sending signals that suppress the plant immune system.[232]

Coalitions between organisms of the same species have also evolved. An extreme case is the eusociality found in social insects, such as bees, termites and ants, where sterile insects feed and guard the small number of organisms in a colony that are able to reproduce. On an even smaller scale, the somatic cells that make up the body of an animal limit their reproduction so they can maintain a stable organism, which then supports a small number of the animal’s germ cells to produce offspring. Here, somatic cells respond to specific signals that instruct them whether to grow, remain as they are, or die. If cells ignore these signals and multiply inappropriately, their uncontrolled growth causes cancer.[233]

Such cooperation within species may have evolved through the process of kin selection, which is where one organism acts to help raise a relative’s offspring.[234] This activity is selected for because if the helping individual contains alleles which promote the helping activity, it is likely that its kin will also contain these alleles and thus those alleles will be passed on.[235] Other processes that may promote cooperation include group selection, where cooperation provides benefits to a group of organisms.[236]

Speciation is the process where a species diverges into two or more descendant species.[237]

There are multiple ways to define the concept of “species.” The choice of definition is dependent on the particularities of the species concerned.[238] For example, some species concepts apply more readily toward sexually reproducing organisms while others lend themselves better toward asexual organisms. Despite the diversity of various species concepts, these various concepts can be placed into one of three broad philosophical approaches: interbreeding, ecological and phylogenetic.[239] The Biological Species Concept (BSC) is a classic example of the interbreeding approach. Defined by Ernst Mayr in 1942, the BSC states that “species are groups of actually or potentially interbreeding natural populations, which are reproductively isolated from other such groups.”[240] Despite its wide and long-term use, the BSC like others is not without controversy, for example because these concepts cannot be applied to prokaryotes,[241] and this is called the species problem.[238] Some researchers have attempted a unifying monistic definition of species, while others adopt a pluralistic approach and suggest that there may be different ways to logically interpret the definition of a species.[238][239]

Barriers to reproduction between two diverging sexual populations are required for the populations to become new species. Gene flow may slow this process by spreading the new genetic variants also to the other populations. Depending on how far two species have diverged since their most recent common ancestor, it may still be possible for them to produce offspring, as with horses and donkeys mating to produce mules.[242] Such hybrids are generally infertile. In this case, closely related species may regularly interbreed, but hybrids will be selected against and the species will remain distinct. However, viable hybrids are occasionally formed and these new species can either have properties intermediate between their parent species, or possess a totally new phenotype.[243] The importance of hybridisation in producing new species of animals is unclear, although cases have been seen in many types of animals,[244] with the gray tree frog being a particularly well-studied example.[245]

Speciation has been observed multiple times under both controlled laboratory conditions and in nature.[246] In sexually reproducing organisms, speciation results from reproductive isolation followed by genealogical divergence. There are four mechanisms for speciation. The most common in animals is allopatric speciation, which occurs in populations initially isolated geographically, such as by habitat fragmentation or migration. Selection under these conditions can produce very rapid changes in the appearance and behaviour of organisms.[247][248] As selection and drift act independently on populations isolated from the rest of their species, separation may eventually produce organisms that cannot interbreed.[249]

The second mechanism of speciation is peripatric speciation, which occurs when small populations of organisms become isolated in a new environment. This differs from allopatric speciation in that the isolated populations are numerically much smaller than the parental population. Here, the founder effect causes rapid speciation after an increase in inbreeding increases selection on homozygotes, leading to rapid genetic change.[250]

The third mechanism of speciation is parapatric speciation. This is similar to peripatric speciation in that a small population enters a new habitat, but differs in that there is no physical separation between these two populations. Instead, speciation results from the evolution of mechanisms that reduce gene flow between the two populations.[237] Generally this occurs when there has been a drastic change in the environment within the parental species’ habitat. One example is the grass Anthoxanthum odoratum, which can undergo parapatric speciation in response to localised metal pollution from mines.[251] Here, plants evolve that have resistance to high levels of metals in the soil. Selection against interbreeding with the metal-sensitive parental population produced a gradual change in the flowering time of the metal-resistant plants, which eventually produced complete reproductive isolation. Selection against hybrids between the two populations may cause reinforcement, which is the evolution of traits that promote mating within a species, as well as character displacement, which is when two species become more distinct in appearance.[252]

Finally, in sympatric speciation species diverge without geographic isolation or changes in habitat. This form is rare since even a small amount of gene flow may remove genetic differences between parts of a population.[253] Generally, sympatric speciation in animals requires the evolution of both genetic differences and non-random mating, to allow reproductive isolation to evolve.[254]

One type of sympatric speciation involves crossbreeding of two related species to produce a new hybrid species. This is not common in animals as animal hybrids are usually sterile. This is because during meiosis the homologous chromosomes from each parent are from different species and cannot successfully pair. However, it is more common in plants because plants often double their number of chromosomes, to form polyploids.[255] This allows the chromosomes from each parental species to form matching pairs during meiosis, since each parent’s chromosomes are represented by a pair already.[256] An example of such a speciation event is when the plant species Arabidopsis thaliana and Arabidopsis arenosa crossbred to give the new species Arabidopsis suecica.[257] This happened about 20,000 years ago,[258] and the speciation process has been repeated in the laboratory, which allows the study of the genetic mechanisms involved in this process.[259] Indeed, chromosome doubling within a species may be a common cause of reproductive isolation, as half the doubled chromosomes will be unmatched when breeding with undoubled organisms.[260]

Speciation events are important in the theory of punctuated equilibrium, which accounts for the pattern in the fossil record of short “bursts” of evolution interspersed with relatively long periods of stasis, where species remain relatively unchanged.[261] In this theory, speciation and rapid evolution are linked, with natural selection and genetic drift acting most strongly on organisms undergoing speciation in novel habitats or small populations. As a result, the periods of stasis in the fossil record correspond to the parental population and the organisms undergoing speciation and rapid evolution are found in small populations or geographically restricted habitats and therefore rarely being preserved as fossils.[174]

Extinction is the disappearance of an entire species. Extinction is not an unusual event, as species regularly appear through speciation and disappear through extinction.[262] Nearly all animal and plant species that have lived on Earth are now extinct,[263] and extinction appears to be the ultimate fate of all species.[264] These extinctions have happened continuously throughout the history of life, although the rate of extinction spikes in occasional mass extinction events.[265] The CretaceousPaleogene extinction event, during which the non-avian dinosaurs became extinct, is the most well-known, but the earlier PermianTriassic extinction event was even more severe, with approximately 96% of all marine species driven to extinction.[265] The Holocene extinction event is an ongoing mass extinction associated with humanity’s expansion across the globe over the past few thousand years. Present-day extinction rates are 1001000 times greater than the background rate and up to 30% of current species may be extinct by the mid 21st century.[266] Human activities are now the primary cause of the ongoing extinction event;[267]global warming may further accelerate it in the future.[268]

The role of extinction in evolution is not very well understood and may depend on which type of extinction is considered.[265] The causes of the continuous “low-level” extinction events, which form the majority of extinctions, may be the result of competition between species for limited resources (the competitive exclusion principle).[68] If one species can out-compete another, this could produce species selection, with the fitter species surviving and the other species being driven to extinction.[133] The intermittent mass extinctions are also important, but instead of acting as a selective force, they drastically reduce diversity in a nonspecific manner and promote bursts of rapid evolution and speciation in survivors.[269]
















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Genetics of Breast and Gynecologic Cancers (PDQ)Health …

Executive Summary

This executive summary provides an overview of the genetics of breast and gynecologic cancer topics covered in this PDQ summary. Click on the hyperlinks within the executive summary to go to the section of the summary where the evidence surrounding each of these topics is covered in detail.

Breast and ovarian cancer are present in several autosomal dominant cancer syndromes, although they are most strongly associated with highly penetrant germline mutations in BRCA1 and BRCA2. Other genes, such as PALB2, TP53 (associated with Li-Fraumeni syndrome), PTEN (associated with Cowden syndrome), CDH1 (associated with diffuse gastric and lobular breast cancer syndrome), and STK11 (associated with Peutz-Jeghers syndrome), confer a risk to either or both of these cancers with relatively high penetrance.

Inherited endometrial cancer is most commonly associated with LS, a condition caused by inherited mutations in the highly penetrant mismatch repair genes MLH1, MSH2, MSH6, PMS2, and EPCAM. Colorectal cancer (and, to a lesser extent, ovarian cancer and stomach cancer) is also associated with LS.

Additional genes, such as CHEK2, BRIP1, RAD51, and ATM, are associated with breast and/or gynecologic cancers with moderate penetrance. Genome-wide searches are showing promise in identifying common, low-penetrance susceptibility alleles for many complex diseases, including breast and gynecologic cancers, but the clinical utility of these findings remains uncertain.

Breast cancer screening strategies, including breast magnetic resonance imaging and mammography, are commonly performed in BRCA mutation carriers and in individuals at increased risk of breast cancer. Initiation of screening is generally recommended at earlier ages and at more frequent intervals in individuals with an increased risk due to genetics and family history than in the general population. There is evidence to demonstrate that these strategies have utility in early detection of cancer. In contrast, there is currently no evidence to demonstrate that gynecologic cancer screening using cancer antigen 125 testing and transvaginal ultrasound leads to early detection of cancer.

Risk-reducing surgeries, including risk-reducing mastectomy (RRM) and risk-reducing salpingo-oophorectomy (RRSO), have been shown to significantly reduce the risk of developing breast and/or ovarian cancer and improve overall survival in BRCA1 and BRCA2 mutation carriers. Chemoprevention strategies, including the use of tamoxifen and oral contraceptives, have also been examined in this population. Tamoxifen use has been shown to reduce the risk of contralateral breast cancer among BRCA1 and BRCA2 mutation carriers after treatment for breast cancer, but there are limited data in the primary cancer prevention setting to suggest that it reduces the risk of breast cancer among healthy female BRCA2 mutation carriers. The use of oral contraceptives has been associated with a protective effect on the risk of developing ovarian cancer, including in BRCA1 and BRCA2 mutation carriers, with no association of increased risk of breast cancer when using formulations developed after 1975.

Psychosocial factors influence decisions about genetic testing for inherited cancer risk and risk-management strategies. Uptake of genetic testing varies widely across studies. Psychological factors that have been associated with testing uptake include cancer-specific distress and perceived risk of developing breast or ovarian cancer. Studies have shown low levels of distress after genetic testing for both carriers and noncarriers, particularly in the longer term. Uptake of RRM and RRSO also varies across studies, and may be influenced by factors such as cancer history, age, family history, recommendations of the health care provider, and pretreatment genetic education and counseling. Patients’ communication with their family members about an inherited risk of breast and gynecologic cancer is complex; gender, age, and the degree of relatedness are some elements that affect disclosure of this information. Research is ongoing to better understand and address psychosocial and behavioral issues in high-risk families.

[Note: Many of the medical and scientific terms used in this summary are found in the NCI Dictionary of Genetics Terms. When a linked term is clicked, the definition will appear in a separate window.]

[Note: Many of the genes and conditions described in this summary are found in the Online Mendelian Inheritance in Man (OMIM) database. When OMIM appears after a gene name or the name of a condition, click on OMIM for a link to more information.]

Among women, breast cancer is the most commonly diagnosed cancer after nonmelanoma skin cancer, and it is the second leading cause of cancer deaths after lung cancer. In 2016, an estimated 249,260 new cases will be diagnosed, and 40,890 deaths from breast cancer will occur.[1] The incidence of breast cancer, particularly for estrogen receptorpositive cancers occurring after age 50 years, is declining and has declined at a faster rate since 2003; this may be temporally related to a decrease in hormone replacement therapy (HRT) after early reports from the Womens Health Initiative (WHI).[2] An estimated 22,280 new cases of ovarian cancer are expected in 2016, with an estimated 14,240 deaths. Ovarian cancer is the fifth most deadly cancer in women.[1] An estimated 60,050 new cases of endometrial cancer are expected in 2016, with an estimated 10,470 deaths.[1] (Refer to the PDQ summaries on Breast Cancer Treatment; Ovarian Epithelial, Fallopian Tube, and Primary Peritoneal Cancer Treatment; and Endometrial Cancer Treatment for more information about breast, ovarian, and endometrial cancer rates, diagnosis, and management.)

A possible genetic contribution to both breast and ovarian cancer risk is indicated by the increased incidence of these cancers among women with a family history (refer to the Risk Factors for Breast Cancer, Risk Factors for Ovarian Cancer, and Risk Factors for Endometrial Cancer sections below for more information), and by the observation of some families in which multiple family members are affected with breast and/or ovarian cancer, in a pattern compatible with an inheritance of autosomal dominant cancer susceptibility. Formal studies of families (linkage analysis) have subsequently proven the existence of autosomal dominant predispositions to breast and ovarian cancer and have led to the identification of several highly penetrant genes as the cause of inherited cancer risk in many families. (Refer to the PDQ summary Cancer Genetics Overview for more information about linkage analysis.) Mutations in these genes are rare in the general population and are estimated to account for no more than 5% to 10% of breast and ovarian cancer cases overall. It is likely that other genetic factors contribute to the etiology of some of these cancers.

Refer to the PDQ summary on Breast Cancer Prevention for information about risk factors for breast cancer in the general population.

In cross-sectional studies of adult populations, 5% to 10% of women have a mother or sister with breast cancer, and about twice as many have either a first-degree relative (FDR) or a second-degree relative with breast cancer.[3-6] The risk conferred by a family history of breast cancer has been assessed in case-control and cohort studies, using volunteer and population-based samples, with generally consistent results.[7] In a pooled analysis of 38 studies, the relative risk (RR) of breast cancer conferred by an FDR with breast cancer was 2.1 (95% confidence interval [CI], 2.02.2).[7] Risk increases with the number of affected relatives, age at diagnosis, the occurrence of bilateral or multiple ipsilateral breast cancers in a family member, and the number of affected male relatives.[4,5,7-9] A large population-based study from the Swedish Family Cancer Database confirmed the finding of a significantly increased risk of breast cancer in women who had a mother or a sister with breast cancer. The hazard ratio (HR) for women with a single breast cancer in the family was 1.8 (95% CI, 1.81.9) and was 2.7 (95% CI, 2.62.9) for women with a family history of multiple breast cancers. For women who had multiple breast cancers in the family, with one occurring before age 40 years, the HR was 3.8 (95% CI, 3.14.8). However, the study also found a significant increase in breast cancer risk if the relative was aged 60 years or older, suggesting that breast cancer at any age in the family carries some increase in risk.[9] (Refer to the Penetrance of BRCA mutations section of this summary for a discussion of familial risk in women from families with BRCA1/BRCA2 mutations who themselves test negative for the family mutation.)

Cumulative risk of breast cancer increases with age, with most breast cancers occurring after age 50 years.[10] In women with a genetic susceptibility, breast cancer, and to a lesser degree, ovarian cancer, tends to occur at an earlier age than in sporadic cases.

In general, breast cancer risk increases with early menarche and late menopause and is reduced by early first full-term pregnancy. There may be an increased risk of breast cancer in BRCA1 and BRCA2 mutation carriers with pregnancy at a younger age (before age 30 years), with a more significant effect seen for BRCA1 mutation carriers.[11-13] Likewise, breast feeding can reduce breast cancer risk in BRCA1 (but not BRCA2) mutation carriers.[14] Regarding the effect of pregnancy on breast cancer outcomes, neither diagnosis of breast cancer during pregnancy nor pregnancy after breast cancer seems to be associated with adverse survival outcomes in women who carry a BRCA1 or BRCA2 mutation.[15] Parity appears to be protective for BRCA1 and BRCA2 mutation carriers, with an additional protective effect for live birth before age 40 years.[16]

Reproductive history can also affect the risk of ovarian cancer and endometrial cancer. (Refer to the Reproductive History sections in the Risk Factors for Ovarian Cancer and Risk Factors for Endometrial Cancer sections of this summary for more information.)

Oral contraceptives (OCs) may produce a slight increase in breast cancer risk among long-term users, but this appears to be a short-term effect. In a meta-analysis of data from 54 studies, the risk of breast cancer associated with OC use did not vary in relationship to a family history of breast cancer.[17]

OCs are sometimes recommended for ovarian cancer prevention in BRCA1 and BRCA2 mutation carriers. (Refer to the Oral Contraceptives section in the Risk Factors for Ovarian Cancer section of this summary for more information.) Although the data are not entirely consistent, a meta-analysis concluded that there was no significant increased risk of breast cancer with OC use in BRCA1/BRCA2 mutation carriers.[18] However, use of OCs formulated before 1975 was associated with an increased risk of breast cancer (summary relative risk [SRR], 1.47; 95% CI, 1.062.04).[18] (Refer to the Reproductive factors section in the Clinical Management of BRCA Mutation Carriers section of this summary for more information.)

Data exist from both observational and randomized clinical trials regarding the association between postmenopausal HRT and breast cancer. A meta-analysis of data from 51 observational studies indicated a RR of breast cancer of 1.35 (95% CI, 1.211.49) for women who had used HRT for 5 or more years after menopause.[19] The WHI (NCT00000611), a randomized controlled trial of about 160,000 postmenopausal women, investigated the risks and benefits of HRT. The estrogen-plus-progestin arm of the study, in which more than 16,000 women were randomly assigned to receive combined HRT or placebo, was halted early because health risks exceeded benefits.[20,21] Adverse outcomes prompting closure included significant increase in both total (245 vs. 185 cases) and invasive (199 vs. 150 cases) breast cancers (RR, 1.24; 95% CI, 1.021.5, P

The association between HRT and breast cancer risk among women with a family history of breast cancer has not been consistent; some studies suggest risk is particularly elevated among women with a family history, while others have not found evidence for an interaction between these factors.[24-28,19] The increased risk of breast cancer associated with HRT use in the large meta-analysis did not differ significantly between subjects with and without a family history.[28] The WHI study has not reported analyses stratified on breast cancer family history, and subjects have not been systematically tested for BRCA1/BRCA2 mutations.[21] Short-term use of hormones for treatment of menopausal symptoms appears to confer little or no breast cancer risk.[19,29] The effect of HRT on breast cancer risk among carriers of BRCA1 or BRCA2 mutations has been studied only in the context of bilateral risk-reducing oophorectomy, in which short-term replacement does not appear to reduce the protective effect of oophorectomy on breast cancer risk.[30] (Refer to the Hormone replacement therapy in BRCA1/BRCA2 mutation carriers section of this summary for more information.)

Hormone use can also affect the risk of developing endometrial cancer. (Refer to the Hormones section in the Risk Factors for Endometrial Cancer section of this summary for more information.)

Observations in survivors of the atomic bombings of Hiroshima and Nagasaki and in women who have received therapeutic radiation treatments to the chest and upper body document increased breast cancer risk as a result of radiation exposure. The significance of this risk factor in women with a genetic susceptibility to breast cancer is unclear.

Preliminary data suggest that increased sensitivity to radiation could be a cause of cancer susceptibility in carriers of BRCA1 or BRCA2 mutations,[31-34] and in association with germline ATM and TP53 mutations.[35,36]

The possibility that genetic susceptibility to breast cancer occurs via a mechanism of radiation sensitivity raises questions about radiation exposure. It is possible that diagnostic radiation exposure, including mammography, poses more risk in genetically susceptible women than in women of average risk. Therapeutic radiation could also pose carcinogenic risk. A cohort study of BRCA1 and BRCA2 mutation carriers treated with breast-conserving therapy, however, showed no evidence of increased radiation sensitivity or sequelae in the breast, lung, or bone marrow of mutation carriers.[37] Conversely, radiation sensitivity could make tumors in women with genetic susceptibility to breast cancer more responsive to radiation treatment. Studies examining the impact of radiation exposure, including, but not limited to, mammography, in BRCA1 and BRCA2 mutation carriers have had conflicting results.[38-43] A large European study showed a dose-response relationship of increased risk with total radiation exposure, but this was primarily driven by nonmammographic radiation exposure before age 20 years.[42] Subsequently, no significant association was observed between prior mammography exposure and breast cancer risk in a prospective study of 1,844 BRCA1 carriers and 502 BRCA2 carriers without a breast cancer diagnosis at time of study entry; average follow-up time was 5.3 years.[43] (Refer to the Mammography section in the Clinical Management of BRCA Mutation Carriers section of this summary for more information about radiation.)

The risk of breast cancer increases by approximately 10% for each 10 g of daily alcohol intake (approximately one drink or less) in the general population.[44,45] Prior studies of BRCA1/BRCA2 mutation carriers have found no increased risk associated with alcohol consumption.[46,47]

Weight gain and being overweight are commonly recognized risk factors for breast cancer. In general, overweight women are most commonly observed to be at increased risk of postmenopausal breast cancer and at reduced risk of premenopausal breast cancer. Sedentary lifestyle may also be a risk factor.[48] These factors have not been systematically evaluated in women with a positive family history of breast cancer or in carriers of cancer-predisposing mutations, but one study suggested a reduced risk of cancer associated with exercise among BRCA1 and BRCA2 mutation carriers.[49]

Benign breast disease (BBD) is a risk factor for breast cancer, independent of the effects of other major risk factors for breast cancer (age, age at menarche, age at first live birth, and family history of breast cancer).[50] There may also be an association between BBD and family history of breast cancer.[51]

An increased risk of breast cancer has also been demonstrated for women who have increased density of breast tissue as assessed by mammogram,[50,52,53] and breast density is likely to have a genetic component in its etiology.[54-56]

Other risk factors, including those that are only weakly associated with breast cancer and those that have been inconsistently associated with the disease in epidemiologic studies (e.g., cigarette smoking), may be important in women who are in specific genotypically defined subgroups. One study [57] found a reduced risk of breast cancer among BRCA1/BRCA2 mutation carriers who smoked, but an expanded follow-up study failed to find an association.[58]

Refer to the PDQ summary on Ovarian, Fallopian Tube, and Primary Peritoneal Cancer Prevention for information about risk factors for ovarian cancer in the general population.

Although reproductive, demographic, and lifestyle factors affect risk of ovarian cancer, the single greatest ovarian cancer risk factor is a family history of the disease. A large meta-analysis of 15 published studies estimated an odds ratio of 3.1 for the risk of ovarian cancer associated with at least one FDR with ovarian cancer.[59]

Ovarian cancer incidence rises in a linear fashion from age 30 years to age 50 years and continues to increase, though at a slower rate, thereafter. Before age 30 years, the risk of developing epithelial ovarian cancer is remote, even in hereditary cancer families.[60]

Nulliparity is consistently associated with an increased risk of ovarian cancer, including among BRCA1/BRCA2 mutation carriers, yet a meta-analysis could only identify risk-reduction in women with four or more live births.[13] Risk may also be increased among women who have used fertility drugs, especially those who remain nulligravid.[61,62] Several studies have reported a risk reduction in ovarian cancer after OC pill use in BRCA1/BRCA2 mutation carriers;[63-65] a risk reduction has also been shown after tubal ligation in BRCA1 carriers, with a statistically significant decreased risk of 22% to 80% after the procedure.[65,66] On the other hand, evidence is growing that the use of menopausal HRT is associated with an increased risk of ovarian cancer, particularly in long-time users and users of sequential estrogen-progesterone schedules.[67-70]

Bilateral tubal ligation and hysterectomy are associated with reduced ovarian cancer risk,[61,71,72] including in BRCA1/BRCA2 mutation carriers.[73] Ovarian cancer risk is reduced more than 90% in women with documented BRCA1 or BRCA2 mutations who chose risk-reducing salpingo-oophorectomy. In this same population, risk-reducing oophorectomy also resulted in a nearly 50% reduction in the risk of subsequent breast cancer.[74,75] (Refer to the Risk-reducing salpingo-oophorectomy section of this summary for more information about these studies.)

Use of OCs for 4 or more years is associated with an approximately 50% reduction in ovarian cancer risk in the general population.[61,76] A majority of, but not all, studies also support OCs being protective among BRCA1/ BRCA2 mutation carriers.[66,77-80] A meta-analysis of 18 studies including 13,627 BRCA mutation carriers reported a significantly reduced risk of ovarian cancer (SRR, 0.50; 95% CI, 0.330.75) associated with OC use.[18] (Refer to the Oral contraceptives section in the Chemoprevention section of this summary for more information.)

Refer to the PDQ summary on Endometrial Cancer Prevention for information about risk factors for endometrial cancer in the general population.

Although the hyperestrogenic state is the most common predisposing factor for endometrial cancer, family history also plays a significant role in a womans risk for disease. Approximately 3% to 5% of uterine cancer cases are attributable to a hereditary cause,[81] with the main hereditary endometrial cancer syndrome being Lynch syndrome (LS), an autosomal dominant genetic condition with a population prevalence of 1 in 300 to 1 in 1,000 individuals.[82,83] (Refer to the LS section in the PDQ summary on Genetics of Colorectal Cancer for more information.)

Age is an important risk factor for endometrial cancer. Most women with endometrial cancer are diagnosed after menopause. Only 15% of women are diagnosed with endometrial cancer before age 50 years, and fewer than 5% are diagnosed before age 40 years.[84] Women with LS tend to develop endometrial cancer at an earlier age, with the median age at diagnosis of 48 years.[85]

Reproductive factors such as multiparity, late menarche, and early menopause decrease the risk of endometrial cancer because of the lower cumulative exposure to estrogen and the higher relative exposure to progesterone.[86,87]

Hormonal factors that increase the risk of type I endometrial cancer are better understood. All endometrial cancers share a predominance of estrogen relative to progesterone. Prolonged exposure to estrogen or unopposed estrogen increases the risk of endometrial cancer. Endogenous exposure to estrogen can result from obesity, polycystic ovary syndrome (PCOS), and nulliparity, while exogenous estrogen can result from taking unopposed estrogen or tamoxifen. Unopposed estrogen increases the risk of developing endometrial cancer by twofold to twentyfold, proportional to the duration of use.[88,89] Tamoxifen, a selective estrogen receptor modulator, acts as an estrogen agonist on the endometrium while acting as an estrogen antagonist in breast tissue, and increases the risk of endometrial cancer.[90] In contrast, oral contraceptives, the levonorgestrel-releasing intrauterine system, and combination estrogen-progesterone hormone replacement therapy all reduce the risk of endometrial cancer through the antiproliferative effect of progesterone acting on the endometrium.[91-94]

Autosomal dominant inheritance of breast and gynecologic cancers is characterized by transmission of cancer predisposition from generation to generation, through either the mothers or the fathers side of the family, with the following characteristics:

Breast and ovarian cancer are components of several autosomal dominant cancer syndromes. The syndromes most strongly associated with both cancers are the BRCA1 or BRCA2 mutation syndromes. Breast cancer is also a common feature of Li-Fraumeni syndrome due to TP53 mutations and of Cowden syndrome due to PTEN mutations.[95] Other genetic syndromes that may include breast cancer as an associated feature include heterozygous carriers of the ataxia telangiectasia gene and Peutz-Jeghers syndrome. Ovarian cancer has also been associated with LS, basal cell nevus (Gorlin) syndrome (OMIM), and multiple endocrine neoplasia type 1 (OMIM).[95] LS is mainly associated with colorectal cancer and endometrial cancer, although several studies have demonstrated that patients with LS are also at risk of developing transitional cell carcinoma of the ureters and renal pelvis; cancers of the stomach, small intestine, liver and biliary tract, brain, breast, prostate, and adrenal cortex; and sebaceous skin tumors (Muir-Torre syndrome).[96-102]

Germline mutations in the genes responsible for these autosomal dominant cancer syndromes produce different clinical phenotypes of characteristic malignancies and, in some instances, associated nonmalignant abnormalities.

The family characteristics that suggest hereditary cancer predisposition include the following:

Figure 1 and Figure 2 depict some of the classic inheritance features of a deleterious BRCA1 and BRCA2 mutation, respectively. Figure 3 depicts a classic family with LS. (Refer to the Standard Pedigree Nomenclature figure in the PDQ summary on Cancer Genetics Risk Assessment and Counseling for definitions of the standard symbols used in these pedigrees.)

Figure 1. BRCA1 pedigree. This pedigree shows some of the classic features of a family with a deleterious BRCA1 mutation across three generations, including affected family members with breast cancer or ovarian cancer and a young age at onset. BRCA1 families may exhibit some or all of these features. As an autosomal dominant syndrome, a deleterious BRCA1 mutation can be transmitted through maternal or paternal lineages, as depicted in the figure.

Figure 2. BRCA2 pedigree. This pedigree shows some of the classic features of a family with a deleterious BRCA2 mutation across three generations, including affected family members with breast (including male breast cancer), ovarian, pancreatic, or prostate cancers and a relatively young age at onset. BRCA2 families may exhibit some or all of these features. As an autosomal dominant syndrome, a deleterious BRCA2 mutation can be transmitted through maternal or paternal lineages, as depicted in the figure.

Figure 3. Lynch syndrome pedigree. This pedigree shows some of the classic features of a family with Lynch syndrome, including affected family members with colon cancer or endometrial cancer and a younger age at onset in some individuals. Lynch syndrome families may exhibit some or all of these features. Lynch syndrome families may also include individuals with other gastrointestinal, gynecologic, and genitourinary cancers, or other extracolonic cancers. As an autosomal dominant syndrome, Lynch syndrome can be transmitted through maternal or paternal lineages, as depicted in the figure.

There are no pathognomonic features distinguishing breast and ovarian cancers occurring in BRCA1 or BRCA2 mutation carriers from those occurring in noncarriers. Breast cancers occurring in BRCA1 mutation carriers are more likely to be ER-negative, progesterone receptornegative, HER2/neu receptornegative (i.e., triple-negative breast cancers), and have a basal phenotype. BRCA1-associated ovarian cancers are more likely to be high-grade and of serous histopathology. (Refer to the Pathology of breast cancer and Pathology of ovarian cancer sections of this summary for more information.)

Some pathologic features distinguish LS mutation carriers from noncarriers. The hallmark feature of endometrial cancers occurring in LS is mismatch repair (MMR) defects, including the presence of microsatellite instability (MSI), and the absence of specific MMR proteins. In addition to these molecular changes, there are also histologic changes including tumor-infiltrating lymphocytes, peritumoral lymphocytes, undifferentiated tumor histology, lower uterine segment origin, and synchronous tumors.

The accuracy and completeness of family histories must be taken into account when they are used to assess risk. A reported family history may be erroneous, or a person may be unaware of relatives affected with cancer. In addition, small family sizes and premature deaths may limit the information obtained from a family history. Breast or ovarian cancer on the paternal side of the family usually involves more distant relatives than does breast or ovarian cancer on the maternal side, so information may be more difficult to obtain. When self-reported information is compared with independently verified cases, the sensitivity of a history of breast cancer is relatively high, at 83% to 97%, but lower for ovarian cancer, at 60%.[103,104] Additional limitations of relying on family histories include adoption; families with a small number of women; limited access to family history information; and incidental removal of the uterus, ovaries, and/or fallopian tubes for noncancer indications. Family histories will evolve, therefore it is important to update family histories from both parents over time. (Refer to the Accuracy of the family history section in the PDQ summary on Cancer Genetics Risk Assessment and Counseling for more information.)

Models to predict an individuals lifetime risk of developing breast and/or gynecologic cancer are available.[105-108] In addition, models exist to predict an individuals likelihood of having a mutation in BRCA1, BRCA2, or one of the MMR genes associated with LS. (Refer to the Models for prediction of the likelihood of a BRCA1 or BRCA2 mutation section of this summary for more information about some of these models.) Not all models can be appropriately applied to all patients. Each model is appropriate only when the patients characteristics and family history are similar to those of the study population on which the model was based. Different models may provide widely varying risk estimates for the same clinical scenario, and the validation of these estimates has not been performed for many models.[106,109,110]

In general, breast cancer risk assessment models are designed for two types of populations: 1) women without a predisposing mutation or strong family history of breast or ovarian cancer; and 2) women at higher risk because of a personal or family history of breast cancer or ovarian cancer.[110] Models designed for women of the first type (e.g., the Gail model, which is the basis for the Breast Cancer Risk Assessment Tool [BCRAT]) [111], and the Colditz and Rosner model [112]) require only limited information about family history (e.g., number of first-degree relatives with breast cancer). Models designed for women at higher risk require more detailed information about personal and family cancer history of breast and ovarian cancers, including ages at onset of cancer and/or carrier status of specific breast cancer-susceptibility alleles. The genetic factors used by the latter models differ, with some assuming one risk locus (e.g., the Claus model [113]), others assuming two loci (e.g., the International Breast Cancer Intervention Study [IBIS] model [114] and the BRCAPRO model [115]), and still others assuming an additional polygenic component in addition to multiple loci (e.g., the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm [BOADICEA] model [116-118]). The models also differ in whether they include information about nongenetic risk factors. Three models (Gail/BCRAT, Pfeiffer,[108] and IBIS) include nongenetic risk factors but differ in the risk factors they include (e.g., the Pfeiffer model includes alcohol consumption, whereas the Gail/BCRAT does not). These models have limited ability to discriminate between individuals who are affected and those who are unaffected with cancer; a model with high discrimination would be close to 1, and a model with little discrimination would be close to 0.5; the discrimination of the models currently ranges between 0.56 and 0.63).[119] The existing models generally are more accurate in prospective studies that have assessed how well they predict future cancers.[110,120-122]

In the United States, BRCAPRO, the Claus model,[113,123] and the Gail/BCRAT [111] are widely used in clinical counseling. Risk estimates derived from the models differ for an individual patient. Several other models that include more detailed family history information are also in use and are discussed below.

The Gail model is the basis for the BCRAT, a computer program available from the National Cancer Institute (NCI) by calling the Cancer Information Service at 1-800-4-CANCER (1-800-422-6237). This version of the Gail model estimates only the risk of invasive breast cancer. The Gail/BCRAT model has been found to be reasonably accurate at predicting breast cancer risk in large groups of white women who undergo annual screening mammography; however, reliability varies depending on the cohort studied.[124-129] Risk can be overestimated in the following populations:

The Gail/BCRAT model is valid for women aged 35 years and older. The model was primarily developed for white women.[128] Extensions of the Gail model for African American women have been subsequently developed to calibrate risk estimates using data from more than 1,600 African American women with invasive breast cancer and more than 1,600 controls.[130] Additionally, extensions of the Gail model have incorporated high-risk single nucleotide polymorphisms and mutations; however, no software exists to calculate risk in these extended models.[131,132] Other risk assessment models incorporating breast density have been developed but are not ready for clinical use.[133,134]

Generally, the Gail/BCRAT model should not be the sole model used for families with one or more of the following characteristics:

Commonly used models that incorporate family history include the IBIS, BOADICEA, and BRCAPRO models. The IBIS/Tyrer-Cuzick model incorporates both genetic and nongenetic factors.[114] A three-generation pedigree is used to estimate the likelihood that an individual carries either a BRCA1/BRCA2 mutation or a hypothetical low-penetrance gene. In addition, the model incorporates personal risk factors such as parity, body mass index (BMI); height; and age at menarche, first live birth, menopause, and HRT use. Both genetic and nongenetic factors are combined to develop a risk estimate. The BOADICEA model examines family history to estimate breast cancer risk and also incorporates both BRCA1/BRCA2 and non-BRCA1/BRCA2 genetic risk factors.[117] The most important difference between BOADICEA and the other models using information on BRCA1/BRCA2 is that BOADICEA assumes an additional polygenic component in addition to multiple loci,[116-118] which is more in line with what is known about the underlying genetics of breast cancer. However, the discrimination and calibration for these models differ significantly when compared in independent samples;[120] the IBIS and BOADICEA models are more comparable when estimating risk over a shorter fixed time horizon (e.g., 10 years),[120] than when estimating remaining lifetime risk. As all risk assessment models for cancers are typically validated over a shorter time horizon (e.g., 5 or 10 years), fixed time horizon estimates rather than remaining lifetime risk may be more accurate and useful measures to convey in a clinical setting.

In addition, readily available models that provide information about an individual womans risk in relation to the population-level risk depending on her risk factors may be useful in a clinical setting (e.g., Your Disease Risk). Although this tool was developed using information about average-risk women and does not calculate absolute risk estimates, it still may be useful when counseling women about prevention. Risk assessment models are being developed and validated in large cohorts to integrate genetic and nongenetic data, breast density, and other biomarkers.

Two risk predictions models have been developed for ovarian cancer.[107,108] The Rosner model [107] included age at menopause, age at menarche, oral contraception use, and tubal ligation; the concordance statistic was 0.60 (0.570.62). The Pfeiffer model [108] included oral contraceptive use, menopausal hormone therapy use, and family history of breast cancer or ovarian cancer, with a similar discriminatory power of 0.59 (0.560.62). Although both models were well calibrated, their modest discriminatory power limited their screening potential.

The Pfeiffer model has been used to predict endometrial cancer risk in the general population.[108] For endometrial cancer, the relative risk model included BMI, menopausal hormone therapy use, menopausal status, age at menopause, smoking status, and oral contraceptive pill use. The discriminatory power of the model was 0.68 (0.660.70); it overestimated observed endometrial cancers in most subgroups but underestimated disease in women with the highest BMI category, in premenopausal women, and in women taking menopausal hormone therapy for 10 years or more.

In contrast, MMRpredict, PREMM1,2,6, and MMRpro are three quantitative predictive models used to identify individuals who may potentially have LS.[135-137] MMRpredict incorporates only colorectal cancer patients but does include MSI and immunohistochemistry (IHC) tumor testing results. PREMM1,2,6 accounts for other LS-associated tumors but does not include tumor testing results. MMRpro incorporates tumor testing and germline testing results, but is more time intensive because it includes affected and unaffected individuals in the risk-quantification process. All three predictive models are comparable to the traditional Amsterdam and Bethesda criteria in identifying individuals with colorectal cancer who carry MMR mutations.[138] However, because these models were developed and validated in colorectal cancer patients, the discriminative abilities of these models to identify LS are lower among individuals with endometrial cancer than among those with colon cancer.[139] In fact, the sensitivity and specificity of MSI and IHC in identifying mutation carriers are considerably higher than the prediction models and support the use of molecular tumor testing to screen for LS in women with endometrial cancer.

Table 1 summarizes salient aspects of breast and gynecologic cancer risk assessment models that are commonly used in the clinical setting. These models differ by the extent of family history included, whether nongenetic risk factors are included, and whether carrier status and polygenic risk are included (inputs to the models). The models also differ in the type of risk estimates that are generated (outputs of the models). These factors may be relevant in choosing the model that best applies to a particular individual.

The proportion of individuals carrying a mutation who will manifest a certain disease is referred to as penetrance. In general, common genetic variants that are associated with cancer susceptibility have a lower penetrance than rare genetic variants. This is depicted in Figure 4. For adult-onset diseases, penetrance is usually described by the individual carrier’s age, sex, and organ site. For example, the penetrance for breast cancer in female BRCA1 mutation carriers is often quoted by age 50 years and by age 70 years. Of the numerous methods for estimating penetrance, none are without potential biases, and determining an individual mutation carrier’s risk of cancer involves some level of imprecision.

Figure 4. Genetic architecture of cancer risk. This graph depicts the general finding of a low relative risk associated with common, low-penetrance genetic variants, such as single-nucleotide polymorphisms identified in genome-wide association studies, and a higher relative risk associated with rare, high-penetrance genetic variants, such as mutations in the BRCA1/BRCA2 genes associated with hereditary breast and ovarian cancer and the mismatch repair genes associated with Lynch syndrome.

Throughout this summary, we discuss studies that report on relative and absolute risks. These are two important but different concepts. Relative risk (RR) refers to an estimate of risk relative to another group (e.g., risk of an outcome like breast cancer for women who are exposed to a risk factor RELATIVE to the risk of breast cancer for women who are unexposed to the same risk factor). RR measures that are greater than 1 mean that the risk for those captured in the numerator (i.e., the exposed) is higher than the risk for those captured in the denominator (i.e., the unexposed). RR measures that are less than 1 mean that the risk for those captured in the numerator (i.e., the exposed) is lower than the risk for those captured in the denominator (i.e., the unexposed). Measures with similar relative interpretations include the odds ratio (OR), hazard ratio (HR), and risk ratio.

Absolute risk measures take into account the number of people who have a particular outcome, the number of people in a population who could have the outcome, and person-time (the period of time during which an individual was at risk of having the outcome), and reflect the absolute burden of an outcome in a population. Absolute measures include risks and rates and can be expressed over a specific time frame (e.g., 1 year, 5 years) or overall lifetime. Cumulative risk is a measure of risk that occurs over a defined time period. For example, overall lifetime risk is a type of cumulative risk that is usually calculated on the basis of a given life expectancy (e.g., 80 or 90 years). Cumulative risk can also be presented over other time frames (e.g., up to age 50 years).

Large relative risk measures do not mean that there will be large effects in the actual number of individuals at a population level because the disease outcome may be quite rare. For example, the relative risk for smoking is much higher for lung cancer than for heart disease, but the absolute difference between smokers and nonsmokers is greater for heart disease, the more-common outcome, than for lung cancer, the more-rare outcome.

Therefore, in evaluating the effect of exposures and biological markers on disease prevention across the continuum, it is important to recognize the differences between relative and absolute effects in weighing the overall impact of a given risk factor. For example, the magnitude is in the range of 30% (e.g., ORs or RRs of 1.3) for many breast cancer risk factors, which means that women with a risk factor (e.g., alcohol consumption, late age at first birth, oral contraceptive use, postmenopausal body size) have a 30% relative increase in breast cancer in comparison with what they would have if they did not have that risk factor. But the absolute increase in risk is based on the underlying absolute risk of disease. Figure 5 and Table 2 show the impact of a relative risk factor in the range of 1.3 on absolute risk. (Refer to the Standard Pedigree Nomenclature figure in the PDQ summary on Cancer Genetics Risk Assessment and Counseling for definitions of the standard symbols used in these pedigrees.) As shown, women with a family history of breast cancer have a much higher benefit from risk factor reduction on an absolute scale.[1]

Figure 5. These five pedigrees depict probands with varying degrees of family history. Table 2 accompanies this figure.

Since the availability of next-generation sequencing and the Supreme Court of the United States ruling that human genes cannot be patented, several clinical laboratories now offer genetic testing through multigene panels at a cost comparable to single-gene testing. Even testing for BRCA1 and BRCA2 is a limited panel test of two genes. Looking beyond BRCA1 and BRCA2, some authors have suggested that one-quarter of heritable ovarian/tubal/peritoneal cancers may be attributed to other genes, many associated with the Fanconi anemia pathway or otherwise involved with homologous recombination.[1] In a population of patients who test negative for BRCA1 and BRCA2 mutations, multigene panel testing can reveal actionable pathologic mutations.[2,3] A caveat is the possible finding of a variant of uncertain significance, where the clinical significance remains unknown. Many centers now offer a multigene panel test instead of just BRCA1 and BRCA2 testing if there is a concerning family history of syndromes other than hereditary breast and ovarian cancer, or more importantly, to gain as much genetic information as possible with one test, particularly if there may be insurance limitations.

(Refer to the Multigene [panel] testing section in the PDQ summary on Cancer Genetics Risk Assessment and Counseling for more information about multigene testing, including genetic education and counseling considerations and research examining the use of multigene testing.)

Epidemiologic studies have clearly established the role of family history as an important risk factor for both breast and ovarian cancer. After gender and age, a positive family history is the strongest known predictive risk factor for breast cancer. However, it has long been recognized that in some families, there is hereditary breast cancer, which is characterized by an early age of onset, bilaterality, and the presence of breast cancer in multiple generations in an apparent autosomal dominant pattern of transmission (through either the maternal or the paternal lineage), sometimes including tumors of other organs, particularly the ovary and prostate gland.[1,2] It is now known that some of these cancer families can be explained by specific mutations in single cancer susceptibility genes. The isolation of several of these genes, which when mutated are associated with a significantly increased risk of breast/ovarian cancer, makes it possible to identify individuals at risk. Although such cancer susceptibility genes are very important, highly penetrant germline mutations are estimated to account for only 5% to 10% of breast cancers overall.

A 1988 study reported the first quantitative evidence that breast cancer segregated as an autosomal dominant trait in some families.[3] The search for genes associated with hereditary susceptibility to breast cancer has been facilitated by studies of large kindreds with multiple affected individuals and has led to the identification of several susceptibility genes, including BRCA1, BRCA2, TP53, PTEN/MMAC1, and STK11. Other genes, such as the mismatch repair genes MLH1, MSH2, MSH6, and PMS2, have been associated with an increased risk of ovarian cancer, but have not been consistently associated with breast cancer.

In 1990, a susceptibility gene for breast cancer was mapped by genetic linkage to the long arm of chromosome 17, in the interval 17q12-21.[4] The linkage between breast cancer and genetic markers on chromosome 17q was soon confirmed by others, and evidence for the coincident transmission of both breast and ovarian cancer susceptibility in linked families was observed.[5] The BRCA1 gene (OMIM) was subsequently identified by positional cloning methods and has been found to contain 24 exons that encode a protein of 1,863 amino acids. Germline mutations in BRCA1 are associated with early-onset breast cancer, ovarian cancer, and fallopian tube cancer. (Refer to the Penetrance of BRCA mutations section of this summary for more information.) Male breast cancer, pancreatic cancer, testicular cancer, and early-onset prostate cancer may also be associated with mutations in BRCA1;[6-9] however, male breast cancer, pancreatic cancer, and prostate cancer are more strongly associated with mutations in BRCA2.

A second breast cancer susceptibility gene, BRCA2, was localized to the long arm of chromosome 13 through linkage studies of 15 families with multiple cases of breast cancer that were not linked to BRCA1. Mutations in BRCA2 (OMIM) are associated with multiple cases of breast cancer in families, and are also associated with male breast cancer, ovarian cancer, prostate cancer, melanoma, and pancreatic cancer.[8-14] (Refer to the Penetrance of BRCA mutations section of this summary for more information.) BRCA2 is a large gene with 27 exons that encode a protein of 3,418 amino acids.[15] While not homologous genes, both BRCA1 and BRCA2 have an unusually large exon 11 and translational start sites in exon 2. Like BRCA1, BRCA2 appears to behave like a tumor suppressor gene. In tumors associated with both BRCA1 and BRCA2 mutations, there is often loss of the wild-type (nonmutated) allele.

Mutations in BRCA1 and BRCA2 appear to be responsible for disease in 45% of families with multiple cases of breast cancer only and in up to 90% of families with both breast and ovarian cancer.[16]

Most BRCA1 and BRCA2 mutations are predicted to produce a truncated protein product, and thus loss of protein function, although some missense mutations cause loss of function without truncation. Because inherited breast/ovarian cancer is an autosomal dominant condition, persons with a BRCA1 or BRCA2 mutation on one copy of chromosome 17 or 13 also carry a normal allele on the other paired chromosome. In most breast and ovarian cancers that have been studied from mutation carriers, deletion of the normal allele results in loss of all function, leading to the classification of BRCA1 and BRCA2 as tumor suppressor genes. In addition to, and as part of, their roles as tumor suppressor genes, BRCA1 and BRCA2 are involved in myriad functions within cells, including homologous DNA repair, genomic stability, transcriptional regulation, protein ubiquitination, chromatin remodeling, and cell cycle control.[17,18]

Nearly 2,000 distinct mutations and sequence variations in BRCA1 and BRCA2 have already been described.[19] Approximately 1 in 400 to 800 individuals in the general population may carry a pathogenic germline mutation in BRCA1 or BRCA2.[20,21] The mutations that have been associated with increased risk of cancer result in missing or nonfunctional proteins, supporting the hypothesis that BRCA1 and BRCA2 are tumor suppressor genes. While a small number of these mutations have been found repeatedly in unrelated families, most have not been reported in more than a few families.

Mutation-screening methods vary in their sensitivity. Methods widely used in research laboratories, such as single-stranded conformational polymorphism analysis and conformation-sensitive gel electrophoresis, miss nearly a third of the mutations that are detected by DNA sequencing.[22] In addition, large genomic alterations such as translocations, inversions, or large deletions or insertions are missed by most of the techniques, including direct DNA sequencing, but testing for these is commercially available. Such rearrangements are believed to be responsible for 12% to 18% of BRCA1 inactivating mutations but are less frequently seen in BRCA2 and in individuals of Ashkenazi Jewish (AJ) descent.[23-29] Furthermore, studies have suggested that these rearrangements may be more frequently seen in Hispanic and Caribbean populations.[27,29,30]

Germline deleterious mutations in the BRCA1/BRCA2 genes are associated with an approximately 60% lifetime risk of breast cancer and a 15% to 40% lifetime risk of ovarian cancer. There are no definitive functional tests for BRCA1 or BRCA2; therefore, the classification of nucleotide changes to predict their functional impact as deleterious or benign relies on imperfect data. The majority of accepted deleterious mutations result in protein truncation and/or loss of important functional domains. However, 10% to 15% of all individuals undergoing genetic testing with full sequencing of BRCA1 and BRCA2 will not have a clearly deleterious mutation detected but will have a variant of uncertain (or unknown) significance (VUS). VUS may cause substantial challenges in counseling, particularly in terms of cancer risk estimates and risk management. Clinical management of such patients needs to be highly individualized and must take into consideration factors such as the patients personal and family cancer history, in addition to sources of information to help characterize the VUS as benign or deleterious. Thus an improved classification and reporting system may be of clinical utility.[31]

A comprehensive analysis of 7,461 consecutive full gene sequence analyses performed by Myriad Genetic Laboratories, Inc., described the frequency of VUS over a 3-year period.[32] Among subjects who had no clearly deleterious mutation, 13% had VUS defined as missense mutations and mutations that occur in analyzed intronic regions whose clinical significance has not yet been determined, chain-terminating mutations that truncate BRCA1 and BRCA2 distal to amino acid positions 1853 and 3308, respectively, and mutations that eliminate the normal stop codons for these proteins. The classification of a sequence variant as a VUS is a moving target. An additional 6.8% of subjects with no clear deleterious mutations had sequence alterations that were once considered VUS but were reclassified as a polymorphism, or occasionally as a deleterious mutation.

The frequency of VUS varies by ethnicity within the U.S. population. African Americans appear to have the highest rate of VUS.[33] In a 2009 study of data from Myriad, 16.5% of individuals of African ancestry had VUS, the highest rate among all ethnicities. The frequency of VUS in Asian, Middle Eastern, and Hispanic populations clusters between 10% and 14%, although these numbers are based on limited sample sizes. Over time, the rate of changes classified as VUS has decreased in all ethnicities, largely the result of improved mutation classification algorithms.[34] VUS continue to be reclassified as additional information is curated and interpreted.[35,36] Such information may impact the continuing care of affected individuals.

A number of methods for discriminating deleterious from neutral VUS exist and others are in development [37-40] including integrated methods (see below).[41] Interpretation of VUS is greatly aided by efforts to track VUS in the family to determine if there is cosegregation of the VUS with the cancer in the family. In general, a VUS observed in individuals who also have a deleterious mutation, especially when the same VUS has been identified in conjunction with different deleterious mutations, is less likely to be in itself deleterious, although there are rare exceptions. As an adjunct to the clinical information, models to interpret VUS have been developed, based on sequence conservation, biochemical properties of amino acid changes,[37,42-46] incorporation of information on pathologic characteristics of BRCA1- and BRCA2-related tumors (e.g., BRCA1-related breast cancers are usually estrogen receptor [ER]negative),[47] and functional studies to measure the influence of specific sequence variations on the activity of BRCA1 or BRCA2 proteins.[48,49] When attempting to interpret a VUS, all available information should be examined.

Statistics regarding the percentage of individuals found to be BRCA mutation carriers among samples of women and men with a variety of personal cancer histories regardless of family history are provided below. These data can help determine who might best benefit from a referral for cancer genetic counseling and consideration of genetic testing but cannot replace a personalized risk assessment, which might indicate a higher or lower mutation likelihood based on additional personal and family history characteristics.

In some cases, the same mutation has been found in multiple apparently unrelated families. This observation is consistent with a founder effect, wherein a mutation identified in a contemporary population can be traced to a small group of founders isolated by geographic, cultural, or other factors. Most notably, two specific BRCA1 mutations (185delAG and 5382insC) and a BRCA2 mutation (6174delT) have been reported to be common in AJs. However, other founder mutations have been identified in African Americans and Hispanics.[30,50,51] The presence of these founder mutations has practical implications for genetic testing. Many laboratories offer directed testing specifically for ethnic-specific alleles. This greatly simplifies the technical aspects of the test but is not without limitations. For example, it is estimated that up to 15% of BRCA1 and BRCA2 mutations that occur among Ashkenazim are nonfounder mutations.[32]

Among the general population, the likelihood of having any BRCA mutation is as follows:

Among AJ individuals, the likelihood of having any BRCA mutation is as follows:

Two large U.S. population-based studies of breast cancer patients younger than age 65 years examined the prevalence of BRCA1 [55,70] and BRCA2 [55] mutations in various ethnic groups. The prevalence of BRCA1 mutations in breast cancer patients by ethnic group was 3.5% in Hispanics, 1.3% to 1.4% in African Americans, 0.5% in Asian Americans, 2.2% to 2.9% in non-Ashkenazi whites, and 8.3% to 10.2% in Ashkenazi Jewish individuals.[55,70] The prevalence of BRCA2 mutations by ethnic group was 2.6% in African Americans and 2.1% in whites.[55]

A study of Hispanic patients with a personal or family history of breast cancer and/or ovarian cancer, who were enrolled through multiple clinics in the southwestern United States, examined the prevalence of BRCA1 and BRCA2 mutations. Deleterious BRCA mutations were identified in 189 of 746 patients (25%) (124 BRCA1, 65 BRCA2);[71] 21 of the 189 (11%) deleterious BRCA mutations identified were large rearrangements, of which 13 (62%) were the BRCA1 exon 912 deletion. An unselected cohort of 810 women of Mexican ancestry with breast cancer were tested; 4.3% had a BRCA mutation. Eight of the 35 mutations identified also were the BRCA1 exon 912 deletion.[72] In another population-based cohort of 492 Hispanic women with breast cancer, the BRCA1 exon 912 deletion was found in three patients, suggesting that this mutation may be a Mexican founder mutation and may represent 10% to 12% of all BRCA1 mutations in similar clinic- and population-based cohorts in the United States. Within the clinic-based cohort, there were nine recurrent mutations, which accounted for 53% of all mutations observed in this cohort, suggesting the existence of additional founder mutations in this population.

A retrospective review of 29 AJ patients with primary fallopian tube tumors identified germline BRCA mutations in 17%.[69] Another study of 108 women with fallopian tube cancer identified mutations in 55.6% of the Jewish women and 26.4% of non-Jewish women (30.6% overall).[73] Estimates of the frequency of fallopian tube cancer in BRCA mutation carriers are limited by the lack of precision in the assignment of site of origin for high-grade, metastatic, serous carcinomas at initial presentation.[6,69,73,74]

Several studies have assessed the frequency of BRCA1 or BRCA2 mutations in women with breast or ovarian cancer.[55,56,70,75-83] Personal characteristics associated with an increased likelihood of a BRCA1 and/or BRCA2 mutation include the following:

Family history characteristics associated with an increased likelihood of carrying a BRCA1 and/or BRCA2 mutation include the following:

Several professional organizations and expert panels, including the American Society of Clinical Oncology,[88] the National Comprehensive Cancer Network (NCCN),[89] the American Society of Human Genetics,[90] the American College of Medical Genetics and Genomics,[91] the National Society of Genetic Counselors,[91] the U.S. Preventive Services Task Force,[92] and the Society of Gynecologic Oncologists,[93] have developed clinical criteria and practice guidelines that can be helpful to health care providers in identifying individuals who may have a BRCA1 or BRCA2 mutation.

Many models have been developed to predict the probability of identifying germline BRCA1/BRCA2 mutations in individuals or families. These models include those using logistic regression,[32,75,76,78,81,94,95] genetic models using Bayesian analysis (BRCAPRO and Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm [BOADICEA]),[81,96] and empiric observations,[52,55,58,97-99] including the Myriad prevalence tables.

In addition to BOADICEA, BRCAPRO is commonly used for genetic counseling in the clinical setting. BRCAPRO and BOADICEA predict the probability of being a carrier and produce estimates of breast cancer risk (see Table 3). The discrimination and accuracy (factors used to evaluate the performance of prediction models) of these models are much higher for these models’ ability to report on carrier status than for their ability to predict fixed or remaining lifetime risk.

More recently, a polygenetic model (BOADICEA) using complex segregation analysis to examine both breast cancer risk and the probability of having a BRCA1 or BRCA2 mutation has been published.[96] Even among experienced providers, the use of prediction models has been shown to increase the power to discriminate which patients are most likely to be BRCA1/BRCA2 mutation carriers.[100,101] Most models do not include other cancers seen in the BRCA1 and BRCA2 spectrum, such as pancreatic cancer and prostate cancer. Interventions that decrease the likelihood that an individual will develop cancer (such as oophorectomy and mastectomy) may influence the ability to predict BRCA1 and BRCA2 mutation status.[102] One study has shown that the prediction models for genetic risk are sensitive to the amount of family history data available and do not perform as well with limited family information.[103]

The performance of the models can vary in specific ethnic groups. The BRCAPRO model appeared to best fit a series of French Canadian families.[104] There have been variable results in the performance of the BRCAPRO model among Hispanics,[105,106] and both the BRCAPRO model and Myriad tables underestimated the proportion of mutation carriers in an Asian American population.[107] BOADICEA was developed and validated in British women. Thus, the major models used for both overall risk (Table 1) and genetic risk (Table 3) have not been developed or validated in large populations of racially and ethnically diverse women. Of the commonly used clinical models for assessing genetic risk, only the Tyrer-Cuzick model contains nongenetic risk factors.

The power of several of the models has been compared in different studies.[108-111] Four breast cancer genetic-risk models, BOADICEA, BRCAPRO, IBIS, and eCLAUS, were evaluated for their diagnostic accuracy in predicting BRCA1/2 mutations in a cohort of 7,352 German families.[112] The family member with the highest likelihood of carrying a mutation from each family was screened for BRCA1/2 mutations. Carrier probabilities from each model were calculated and compared with the actual mutations detected. BRCAPRO and BOADICEA had significantly higher diagnostic accuracy than IBIS or eCLAUS. Accuracy for the BOADICEA model was further improved when information on the tumor markers ER, progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2/neu) were included in the model. The inclusion of these biomarkers has been shown to improve the performance of BRCAPRO.[113,114]

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[Note: Many of the medical and scientific terms used in this summary are found in the NCI Dictionary of Genetics Terms. When a linked term is clicked, the definition will appear in a separate window.]

[Note: Many of the genes described in this summary are found in the Online Mendelian Inheritance in Man (OMIM) database. When OMIM appears after a gene name or the name of a condition, click on OMIM for a link to more information.]

The public health burden of prostate cancer is substantial. A total of 180,890 new cases of prostate cancer and 26,120 deaths from the disease are anticipated in the United States in 2016, making it the most frequent nondermatologic cancer among U.S. males.[1] A mans lifetime risk of prostate cancer is one in seven. Prostate cancer is the second leading cause of cancer death in men, exceeded only by lung cancer.[1]

Some men with prostate cancer remain asymptomatic and die from unrelated causes rather than as a result of the cancer itself. This may be due to the advanced age of many men at the time of diagnosis, slow tumor growth, or response to therapy.[2] The estimated number of men with latent prostate carcinoma (i.e., prostate cancer that is present in the prostate gland but never detected or diagnosed during a patients life) is greater than the number of men with clinically detected disease. A better understanding is needed of the genetic and biologic mechanisms that determine why some prostate carcinomas remain clinically silent, while others cause serious, even life-threatening illness.[2]

Prostate cancer exhibits tremendous differences in incidence among populations worldwide; the ratio of countries with high and low rates of prostate cancer ranges from 60-fold to 100-fold.[3] Asian men typically have a very low incidence of prostate cancer, with age-adjusted incidence rates ranging from 2 to 10 cases per 100,000 men. Higher incidence rates are generally observed in northern European countries. African American men, however, have the highest incidence of prostate cancer in the world; within the United States, African American men have a 60% higher incidence rate than white men.[4] African American men have been reported to have more than twice the rate of prostate cancerspecific death compared with non-Hispanic white men.[1] Differences in race-specific prostate cancer survival estimates may be narrowing over time.[5]

These differences may be due to the interplay of genetic, environmental, and social influences (such as access to health care), which may affect the development and progression of the disease.[6] Differences in screening practices have also had a substantial influence on prostate cancer incidence, by permitting prostate cancer to be diagnosed in some patients before symptoms develop or before abnormalities on physical examination are detectable. An analysis of population-based data from Sweden suggested that a diagnosis of prostate cancer in one brother leads to an early diagnosis in a second brother using prostate-specific antigen (PSA) screening.[7] This may account for an increase in prostate cancer diagnosed in younger men that was evident in nationwide incidence data. A genetic contribution to prostate cancer risk has been documented, and there is increasing knowledge of the molecular genetics of the disease, although much of what is known is not yet clinically actionable. Malignant transformation of prostate epithelial cells and progression of prostate carcinoma are likely to result from a complex series of initiation and promotional events under both genetic and environmental influences.[8]

The three most important recognized risk factors for prostate cancer in the United States are:

Age is an important risk factor for prostate cancer. Prostate cancer is rarely seen in men younger than 40 years; the incidence rises rapidly with each decade thereafter. For example, the probability of being diagnosed with prostate cancer is 1 in 325 for men 49 years or younger, 1 in 48 for men aged 50 through 59 years, 1 in 17 for men aged 60 through 69 years, and 1 in 10 for men aged 70 years and older, with an overall lifetime risk of developing prostate cancer of 1 in 7.[1]

Approximately 10% of prostate cancer cases are diagnosed in men younger than 56 years and represent early-onset prostate cancer. Data from the Surveillance, Epidemiology, and End Results (SEER) Program show that early-onset prostate cancer is increasing, and there is evidence that some cases may be more aggressive.[9] Because early-onset cancers may result from germline mutations, young men with prostate cancer are being extensively studied with the goal of identifying prostate cancer susceptibility genes.

The risk of developing and dying from prostate cancer is dramatically higher among blacks, is of intermediate levels among whites, and is lowest among native Japanese.[10,11] Conflicting data have been published regarding the etiology of these outcomes, but some evidence is available that access to health care may play a role in disease outcomes.[12]

Prostate cancer is highly heritable; the inherited risk of prostate cancer has been estimated to be as high as 60%.[13] As with breast and colon cancer, familial clustering of prostate cancer has been reported frequently.[14-18] From 5% to 10% of prostate cancer cases are believed to be primarily caused by high-risk inherited genetic factors or prostate cancer susceptibility genes. Results from several large case-control studies and cohort studies representing various populations suggest that family history is a major risk factor in prostate cancer.[15,19,20] A family history of a brother or father with prostate cancer increases the risk of prostate cancer, and the risk is inversely related to the age of the affected relative.[16-20] However, at least some familial aggregation is due to increased prostate cancer screening in families thought to be at high risk.[21]

Although some of the prostate cancer studies examining risks associated with family history have used hospital-based series, several studies described population-based series.[22-24] The latter are thought to provide information that is more generalizable. A meta-analysis of 33 epidemiologic case-control and cohort-based studies has provided more detailed information regarding risk ratios related to family history of prostate cancer. Risk appeared to be greater for men with affected brothers than for men with affected fathers in this meta-analysis. Although the reason for this difference in risk is unknown, possible hypotheses have included X-linked or recessive inheritance. In addition, risk increased with increasing numbers of affected close relatives. Risk also increased when a first-degree relative (FDR) was diagnosed with prostate cancer before age 65 years. (See Table 1 for a summary of the relative risks [RRs] related to a family history of prostate cancer.)[25]

Among the many data sources included in this meta-analysis, those from the Swedish population-based Family-Cancer Database warrant special comment. These data were derived from a resource that contained more than 11.8 million individuals, among whom there were 26,651 men with medically verified prostate cancer, of which 5,623 were familial cases.[26] The size of this data set, with its nearly complete ascertainment of the entire Swedish population and objective verification of cancer diagnoses, should yield risk estimates that are both accurate and free of bias. When the familial age-specific hazard ratios (HRs) for prostate cancer diagnosis and mortality were computed, as expected, the HR for prostate cancer diagnosis increased with more family history. Specifically, HRs for prostate cancer were 2.12 (95% CI, 2.052.20) with an affected father only, 2.96 (95% CI, 2.803.13) with an affected brother only, and 8.51 (95% CI, 6.1311.80) with a father and two brothers affected. The highest HR, 17.74 (95% CI, 12.2625.67), was seen in men with three brothers diagnosed with prostate cancer. The HRs were even higher when the affected relative was diagnosed with prostate cancer before age 55 years.

A separate analysis of this Swedish database reported that the cumulative (absolute) risks of prostate cancer among men in families with two or more affected cases were 5% by age 60 years, 15% by age 70 years, and 30% by age 80 years, compared with 0.45%, 3%, and 10%, respectively, by the same ages in the general population. The risks were even higher when the affected father was diagnosed before age 70 years.[27] The corresponding familial population attributable fractions (PAFs) were 8.9%, 1.8%, and 1.0% for the same three age groups, respectively, yielding a total PAF of 11.6% (i.e., approximately 11.6% of all prostate cancers in Sweden can be accounted for on the basis of familial history of the disease).

The risk of prostate cancer may also increase in men who have a family history of breast cancer. Approximately 9.6% of the Iowa cohort had a family history of breast and/or ovarian cancer in a mother or sister at baseline, and this was positively associated with prostate cancer risk (age-adjusted RR, 1.7; 95% CI, 1.03.0; multivariate RR, 1.7; 95% CI, 0.93.2). Men with a family history of both prostate and breast/ovarian cancer were also at increased risk of prostate cancer (RR, 5.8; 95% CI, 2.414.0).[22] Analysis of data from the Women’s Health Initiative also showed that a family history of prostate cancer was associated with an increase in the risk of postmenopausal breast cancer (adjusted HR, 1.14; 95% CI, 1.021.26).[28] Further analyses showed that breast cancer risk was associated with a family history of both breast and prostate cancers; the risk was higher in black women than in white women. Other studies, however, did not find an association between family history of female breast cancer and risk of prostate cancer.[22,29] A family history of prostate cancer also increases the risk of breast cancer among female relatives.[30] The association between prostate cancer and breast cancer in the same family may be explained, in part, by the increased risk of prostate cancer among men with BRCA1/BRCA2 mutations in the setting of hereditary breast/ovarian cancer or early-onset prostate cancer.[31-34] (Refer to the BRCA1 and BRCA2 section of this summary for more information.)

Prostate cancer clusters with particular intensity in some families. Highly penetrant genetic variants are thought to be associated with prostate cancer risk in these families. (Refer to the Linkage Analyses section of this summary for more information.) Members of such families may benefit from genetic counseling. Emerging recommendations and guidelines for genetic counseling referrals are based on prostate cancer age at diagnosis and specific family cancer history patterns.[35,36] Individuals meeting the following criteria may warrant referral for genetic consultation:[35-38]

Family history has been shown to be a risk factor for men of different races and ethnicities. In a population-based case-control study of prostate cancer among African Americans, whites, and Asian Americans in the United States (Los Angeles, San Francisco, and Hawaii) and Canada (Vancouver and Toronto),[39] 5% of controls and 13% of all cases reported a father, brother, or son with prostate cancer. These prevalence estimates were somewhat lower among Asian Americans than among African Americans or whites. A positive family history was associated with a twofold to threefold increase in RR in each of the three ethnic groups. The overall odds ratio associated with a family history of prostate cancer was 2.5 (95% CI, 1.93.3) with adjustment for age and ethnicity.[39]

Endogenous hormones, including both androgens and estrogens, likely influence prostate carcinogenesis. It has been widely reported that eunuchs and other individuals with castrate levels of testosterone before puberty do not develop prostate cancer.[40] Some investigators have considered the potential role of genetic variation in androgen biosynthesis and metabolism in prostate cancer risk,[41] including the potential role of the androgen receptor (AR) CAG repeat length in exon 1. This modulates AR activity, which may influence prostate cancer risk.[42] For example, a meta-analysis reported that AR CAG repeat length greater than or equal to 20 repeats conferred a protective effect for prostate cancer in subsets of men.[43]

(Refer to the PDQ summary on Prostate Cancer Prevention for more information about nongenetic modifiers of prostate cancer risk in the general population.)

The SEER Cancer Registries assessed the risk of developing a second primary cancer in 292,029 men diagnosed with prostate cancer between 1973 and 2000. Excluding subsequent prostate cancer and adjusting for the risk of death from other causes, the cumulative incidence of a second primary cancer among all patients was 15.2% at 25 years (95% CI, 5.015.4). There was a significant risk of new malignancies (all cancers combined) among men diagnosed before age 50 years, no excess or deficit in cancer risk in men aged 50 to 59 years, and a deficit in cancer risk in all older age groups. The authors suggested that this deficit may be attributable to decreased cancer surveillance in an elderly population. Excess risks of second primary cancers included cancers of the small intestine, soft tissue, bladder, thyroid, and thymus; and melanoma. Prostate cancer diagnosed in patients aged 50 years or younger was associated with an excess risk of pancreatic cancer.[44]

A review of more than 441,000 men diagnosed with prostate cancer between 1992 and 2010 demonstrated similar findings, with an overall reduction in the risk of being diagnosed with a second primary cancer. This study also examined the risk of second primary cancers in 44,310 men (10%) by treatment modality for localized cancer. The study suggested that men who received radiation therapy had increases in bladder (standardized incidence ratio [SIR], 1.42) and rectal cancer risk (SIR, 1.70) compared with those who did not receive radiation therapy (SIRbladder, 0.76; SIRrectal, 0.74).[45]

The underlying etiology of developing a second primary cancer after prostate cancer may be related to various factors, including treatment modality. More than 50% of the small intestine tumors were carcinoid malignancies, suggesting possible hormonal influences. The excess of pancreatic cancer may be due to mutations in BRCA2, which predisposes to both. The risk of melanoma was most pronounced in the first year of follow-up after diagnosis, raising the possibility that this is the result of increased screening and surveillance.[44]

One Swedish study using the nationwide Swedish Family Cancer Database assessed the role of family history in the risk of a second primary cancer after prostate cancer. Of 18,207 men with prostate cancer, 560 developed a second primary malignancy. Of those, the RR was increased for colorectal, kidney, bladder, and squamous cell skin cancers. Having a paternal family history of prostate cancer was associated with an increased risk of bladder cancer, myeloma, and squamous cell skin cancer. Among prostate cancer probands, those with a family history of colorectal cancer, bladder cancer, or chronic lymphoid leukemia were at increased risk of that specific cancer as a second primary cancer.[46]

Several reports have suggested an elevated risk of various other cancers among relatives within multiple-case prostate cancer families, but none of these associations have been established definitively.[47-49]

In a population-based Finnish study of 202 multiple-case prostate cancer families, no excess risk of all cancers combined (other than prostate cancer) was detected in 5,523 family members. Female family members had a marginal excess of gastric cancer (SIR, 1.9; 95% CI, 1.03.2). No difference in familial cancer risk was observed when families affected by clinically aggressive prostate cancers were compared with those having nonaggressive prostate cancer. These data suggest that familial prostate cancer is a cancer sitespecific disorder.[50]

Many types of epidemiologic studies (case-control, cohort, twin, family) strongly suggest that prostate cancer susceptibility genes exist in the population. Analysis of longer follow-up of the monozygotic (MZ) and dizygotic (DZ) twin pairs in Scandinavia concluded that 58% (95% CI, 5263) of prostate cancer risk may be accounted for by heritable factors.[13] Additionally, among affected MZ and DZ pairs, the time to diagnosis in the second twin was shortest in MZ twins (mean, 3.8 years in MZ twins vs. 6.5 years in DZ twins). This is in agreement with a previous U.S. study that showed a concordance of 7.1% between DZ twin pairs and a 27% concordance between MZ twin pairs.[51] The first segregation analysis was performed in 1992 using families from 740 consecutive probands who had radical prostatectomies between 1982 and 1989. The study results suggested that familial clustering of disease among men with early-onset prostate cancer was best explained by the presence of a rare (frequency of 0.003) autosomal dominant, highly penetrant allele(s).[15] Hereditary prostate cancer susceptibility genes were predicted to account for almost half of early-onset disease (age 55 years or younger). In addition, early-onset disease has been further supported to have a strong genetic component from the study of common variants associated with disease onset before age 55 years.[52]

Subsequent segregation analyses generally agreed with the conclusions but differed in the details regarding frequency, penetrance, and mode of inheritance.[53-55] A study of 4,288 men who underwent radical prostatectomy between 1966 and 1995 found that the best fitting genetic model of inheritance was the presence of a rare, autosomal dominant susceptibility gene (frequency of 0.06). In this study, the lifetime risk in carriers was estimated to be 89% by age 85 years and 3.9% for noncarriers.[51] This study also suggested the presence of genetic heterogeneity, as the model did not reliably predict prostate cancer risk in FDRs of probands who were diagnosed at age 70 years or older. More recent segregation analyses have concluded that there are multiple genes associated with prostate cancer [56-59] in a pattern similar to other adult-onset hereditary cancer syndromes, such as those involving the breast, ovary, colorectum, kidney, and melanoma. In addition, a segregation analysis of 1,546 families from Finland found evidence for Mendelian recessive inheritance. Results showed that individuals carrying the risk allele were diagnosed with prostate cancer at younger ages (

Various research methods have been employed to uncover the landscape of genetic variation associated with prostate cancer. Specific methodologies inform of unique phenotypes or inheritance patterns. The sections below describe prostate cancer research utilizing various methods to highlight their role in uncovering the genetic basis of prostate cancer. In an effort to identify disease susceptibility genes, linkage studies are typically performed on high-risk extended families in which multiple cases of a particular disease have occurred. Typically, gene mutations identified through linkage analyses are rare in the population, are moderately to highly penetrant in families, and have large (e.g., relative risk >2.0) effect sizes. The clinical role of mutations that are identified in linkage studies is a clearer one, establishing precedent for genetic testing for cancer with genes such as BRCA1 and BRCA2. (Refer to the BRCA1 and BRCA2 section in the Genes With Potential Clinical Relevance in Prostate Cancer Risk section of this summary for more information about these genes.) Genome-wide association studies (GWAS) are another methodology used to identify candidate loci associated with prostate cancer. Genetic variants identified from GWAS typically are common in the population and have low to modest effect sizes for prostate cancer risk. The clinical role of markers identified from GWAS is an active area of investigation. Case-control studies are useful in validating the findings of linkage studies and GWAS as well as for studying candidate gene alterations for association with prostate cancer risk, although the clinical role of findings from case-control studies needs to be further defined.

The recognition that prostate cancer clusters within families has led many investigators to collect multiple-case families with the goal of localizing prostate cancer susceptibility genes through linkage studies.

Linkage studies are typically performed on high-risk kindreds in whom multiple cases of a particular disease have occurred in an effort to identify disease susceptibility genes. Linkage analysis statistically compares the genotypes between affected and unaffected individuals and looks for evidence that known genetic markers are inherited along with the disease trait. If such evidence is found (linkage), it provides statistical data that the chromosomal region near the marker also harbors a disease susceptibility gene. Once a genomic region of interest has been identified through linkage analysis, additional studies are required to prove that there truly is a susceptibility gene at that position. Linkage analysis is affected by the following:

Furthermore, because a standard definition of hereditary prostate cancer has not been accepted, prostate cancer linkage studies have not used consistent criteria for enrollment.[1] One criterion that has been proposed is the Hopkins Criteria, which provides a working definition of hereditary prostate cancer families.[2] Using the Hopkins Criteria, kindreds with prostate cancer need to fulfill only one of following criteria to be considered to have hereditary prostate cancer:

Using these criteria, surgical series have reported that approximately 3% to 5% of men will be from a family with hereditary prostate cancer.[2,3]

An additional issue in linkage studies is the high background rate of sporadic prostate cancer in the context of family studies. Because a mans lifetime risk of prostate cancer is one in seven,[4] it is possible that families under study have men with both inherited and sporadic prostate cancer. Thus, men who do not inherit the prostate cancer susceptibility gene that is segregating in their family may still develop prostate cancer. There are no clinical or pathological features of prostate cancer that will allow differentiation between inherited and sporadic forms of the disease, although current advances in the understanding of molecular phenotypes of prostate cancer may be informative in identifying inherited prostate cancer. Similarly, there are limited data regarding the clinical phenotype or natural history of prostate cancer associated with specific candidate loci. Measurement of the serum prostate-specific antigen (PSA) has been used inconsistently in evaluating families used in linkage analysis studies of prostate cancer. In linkage studies, the definition of an affected man can be biased by the use of serum PSA screening as the rates of prostate cancer in families will differ between screened and unscreened families.

One way to address inconsistencies between linkage studies is to require inclusion criteria that define clinically significant disease (e.g., Gleason score 7, PSA 20 ng/mL) in an affected man.[5-7] This approach attempts to define a homogeneous set of cases/families to increase the likelihood of identifying a linkage signal. It also prevents the inclusion of cases that may be considered clinically insignificant that were identified by screening in families.

Investigators have also incorporated clinical parameters into linkage analyses with the goal of identifying genes that may influence disease severity.[8,9] This type of approach, however, has not yet led to the identification of consistent linkage signals across datasets.[10,11]

Table 2 summarizes the proposed prostate cancer susceptibility loci identified in families with multiple prostate canceraffected individuals. Conflicting evidence exists regarding the linkage to some of the loci described above. Data on the proposed phenotype associated with each locus are also limited, and the strength of repeated studies is needed to firmly establish these associations. Evidence suggests that many of these prostate cancer loci account for disease in a small subset of families, which is consistent with the concept that prostate cancer exhibits locus heterogeneity.

Genome-wide linkage studies of families with prostate cancer have identified several other loci that may harbor prostate cancer susceptibility genes, emphasizing the underlying complexity and genetic heterogeneity of this cancer. The following chromosomal regions have been found to be associated with prostate cancer in more than one study or clinical cohort with a statistically significant (2) logarithm of the odds (LOD) score, heterogeneity LOD (HLOD) score, or summary LOD score:

The chromosomal region 19q has also been found to be associated with prostate cancer, although specific LOD scores have not been described.[8,11,95]

Linkage studies have also been performed in specific populations or with specific clinical parameters to identify population-specific susceptibility genes or genes influencing disease phenotypes.

The African American Hereditary Prostate Cancer study conducted a genome-wide linkage study of 77 families with four or more affected men. Multipoint HLOD scores of 1.3 to less than 2.0 were observed using markers that map to 11q22, 17p11, and Xq21. Analysis of the 16 families with more than six men with prostate cancer provided evidence for two additional loci: 2p21 (multipoint HLOD score = 1.08) and 22q12 (multipoint HLOD score = 0.91).[92,99] A smaller linkage study that included 15 African American hereditary prostate cancer families from the southeastern and southcentral Louisiana region identified suggestive linkage for prostate cancer at 2p16 (HLOD = 1.97) and 12q24 (HLOD = 2.21) using a 6,000 single nucleotide polymorphism (SNP) platform.[111] Further study including a larger number of African American families is needed to confirm these findings.

In an effort to identify loci contributing to prostate cancer aggressiveness, linkage analysis was performed in families with one or more of the following: Gleason grade 7 or higher, PSA of 20 ng/mL or higher, regional or distant cancer stage at diagnosis, or death from metastatic prostate cancer before age 65 years. One hundred twenty-three families with two or more affected family members with aggressive prostate cancer were studied. Suggestive linkage was found at chromosome 22q11 (HLOD score = 2.18) and 22q12.3-q13.1 (HLOD score = 1.90).[5] These findings suggest that using a clinically defined phenotype may facilitate finding prostate cancer susceptibility genes. A fine-mapping study of 14 extended high-risk prostate cancer families has subsequently narrowed the genomic region of interest to an 880-kb region at 22q12.3.[107] An analysis of high-risk pedigrees from Utah provides an overview of this strategy.[112] A linkage analysis utilizing a higher resolution marker set of 6,000 SNPs was performed among 348 families from the International Consortium for Prostate Cancer Genetics with aggressive prostate cancer.[44] Aggressive disease was defined as Gleason score 7 or higher, invasion into seminal vesicles or extracapsular extension, pretreatment PSA level of 20 ng/mL or higher, or death from prostate cancer. The region with strongest evidence of linkage among aggressive prostate cancer families was 8q24 with LOD scores of 3.093.17. Additional regions of linkage included with LOD scores of 2 or higher included 1q43, 2q35, and 12q24.31. No candidate genes have been identified.

In light of the multiple prostate cancer susceptibility loci and disease heterogeneity, another approach has been to stratify families based on other cancers, given that many cancer susceptibility genes are pleiotropic.[113] A genome-wide linkage study was conducted to identify a susceptibility locus that may account for both prostate cancer and kidney cancer in families. Analysis of 15 families with evidence of hereditary prostate cancer and one or more cases of kidney cancer (pathologically confirmed) in a man with prostate cancer or in a first-degree relative of a man with prostate cancer revealed suggestive linkage with markers that mapped to an 8 cM region of chromosome 11p11.2-q12.2.[114] This observation awaits confirmation. Another genome-wide linkage study was conducted in 96 hereditary prostate cancer families with one or more first-degree relatives with colon cancer. Evidence for linkage in all families was found in several regions, including 11q25, 15q14, and 18q21. In families with two or more cases of colon cancer, linkage was also observed at 1q31, 11q14, and 15q11-14.[113]

Linkage to chromosome 17q21-22 and subsequent fine-mapping and targeted sequencing have identified recurrent mutations in the HOXB13 gene that account for a fraction of hereditary prostate cancer, particularly early-onset prostate cancer. Multiple studies have confirmed the association between the G84E mutation in HOXB13 and prostate cancer risk. (Refer to the HOXB13 section of this summary for more information.) The clinical utility of testing for HOXB13 mutations has not yet been defined, but studies are ongoing to define the clinical role. For example, a study evaluated 948 unselected men scheduled for prostate biopsy. The G84E mutation was found in three men (0.3%) who had prostate cancer detected on biopsy, although none of the 301 men who had a family history of prostate cancer carried the mutation.[115] Furthermore, many linkage studies have mapped several prostate cancer susceptibility loci (Table 2), although the genetic alterations contributing to hereditary prostate cancer from these loci have not been consistently reproduced. With the evolution of high-throughput sequencing technologies, there will likely be additional moderately to highly penetrant genetic mutations identified to account for subsets of hereditary prostate cancer families.[116]

A case-control study involves evaluating factors of interest for association to a condition. The design involves investigation of cases with a condition of interest, such as a specific disease or gene mutation, compared with a control sample without that condition, but often with other similar characteristics (i.e., age, gender, and ethnicity). Limitations of case-control design with regard to identifying genetic factors include the following:[117,118]

Additionally, identified associations may not always be valid, but they could represent a random association and, therefore, warrant validation studies.[117,118]

Androgen receptor (AR) gene variants have been examined in relation to both prostate cancer risk and disease progression. The AR is expressed during all stages of prostate carcinogenesis.[120] One study demonstrated that men with hereditary prostate cancer who underwent radical prostatectomy had a higher percentage of prostate cancer cells exhibiting expression of the AR and a lower percentage of cancer cells expressing estrogen receptor alpha than did men with sporadic prostate cancer. The authors suggest that a specific pattern of hormone receptor expression may be associated with hereditary predisposition to prostate cancer.[121]

Altered activity of the AR caused by inherited variants of the AR gene may influence risk of prostate cancer. The length of the polymorphic trinucleotide CAG and GGN microsatellite repeats in exon 1 of the AR gene (located on the X chromosome) have been associated with the risk of prostate cancer.[122,123] Some studies have suggested an inverse association between CAG repeat length and prostate cancer risk, and a direct association between GGN repeat length and risk of prostate cancer; however, the evidence is inconsistent.[120,122-132] A meta-analysis of 19 case-control studies demonstrated a statistically significant association between both short CAG length (odds ratio [OR], 1.2; 95% confidence interval [CI], 1.11.3) and short GGN length (OR, 1.3; 95% CI, 1.11.6) and prostate cancer; however, the absolute difference in number of repeats between cases and controls is less than one, leading the investigators to question whether these small, statistically significant differences are biologically meaningful.[133] Subsequently, the large multiethnic cohort study of 2,036 incident prostate cancer cases and 2,160 ethnically matched controls failed to confirm a statistically significant association (OR, 1.02; P = .11) between CAG repeat size and prostate cancer.[134] A study of 1,461 Swedish men with prostate cancer and 796 control men reported an association between AR alleles, with more than 22 CAG repeats and prostate cancer (OR, 1.35; 95% CI, 1.081.69; P = .03).[135]

An analysis of AR gene CAG and CGN repeat length polymorphisms targeted African American men from the Flint Mens Health Study in an effort to identify a genetic modifier that might help explain the increased risk of prostate cancer in black versus white males in the United States.[136] This population-based study of 131 African American prostate cancer patients and 340 screened-negative African American controls showed no evidence of an association between shorter AR repeat length and prostate cancer risk. These results, together with data from three prior, smaller studies,[134,137,138] indicate that short AR repeat variants do not contribute significantly to the risk of prostate cancer in African American men.

Germline mutations in the AR gene (located on the X chromosome) have been rarely reported. The R726L mutation has been identified as a possible contributor to about 2% of both sporadic and familial prostate cancer in Finland.[139] This mutation, which alters the transactivational specificity of the AR protein, was found in 8 of 418 (1.91%) consecutive sporadic prostate cancer cases, 2 of 106 (1.89%) familial cases, and 3 of 900 (0.33%) normal blood donors, yielding a significantly increased prostate cancer OR of 5.8 for both case groups. A subsequent Finnish study of 38 early-onset prostate cancer cases and 36 multiple-case prostate cancer families with no evidence of male-to-male transmission revealed one additional R726L mutation in one of the familial cases and no new germline mutations in the AR gene.[140] These investigators concluded that germline AR mutations explain only a small fraction of familial and early-onset cases in Finland.

A study of genomic DNA from 60 multiple-case African American (n = 30) and white (n = 30) families identified a novel missense germline AR mutation, T559S, in three affected members of a black sibship and none in the white families. No functional data were presented to indicate that this mutation was clearly deleterious. This was reported as a suggestive finding, in need of additional data.[141]

Molecular epidemiology studies have also examined genetic polymorphisms of the steroid 5-alpha-reductase 2 gene, which is also involved in the androgen metabolism cascade. Two isozymes of 5-alpha-reductase exist. The gene that codes for 5-alpha-reductase type II (SRD5A2) is located on chromosome 2. It is expressed in the prostate, where testosterone is converted irreversibly to dihydrotestosterone (DHT) by 5-alpha-reductase type II.[142] Evidence suggests that 5-alpha-reductase type II activity is reduced in populations at lower risk of prostate cancer, including Chinese and Japanese men.[143,144]

A polymorphism in the untranslated region of the SRD5A2 gene may also be associated with prostate cancer risk.[145] Ten alleles fall into three families that differ in the number of TA dinucleotide repeats.[142,146] Although no clinical significance for these polymorphisms has yet been determined, some TA repeat alleles may promote an elevation of enzyme activity, which may in turn increase the level of DHT in the prostate.[120,142] A subsequent meta-analysis failed to detect a statistically significant association between prostate cancer risk and the TA repeat polymorphism, although a relationship could not be definitively excluded.[147] This meta-analysis also examined the potential roles of two coding variants: A49T and V89L. An association with V89L was excluded, and the role for A49T was found to have at most a modest effect on prostate cancer susceptibility. Bias or chance could account for the latter observation. A study of 1,461 Swedish men with prostate cancer and 796 control men reported an association between two variants in SRD5A2 and prostate cancer risk (OR, 1.45; 95% CI, 1.012.08; OR, 1.49; 95% CI, 1.032.15).[135] Another meta-analysis of 25 case-control studies, including 8,615 cases and 9,089 controls, found no overall association between the V89L polymorphism and prostate cancer risk. In a subgroup analysis, men younger than 65 years (323 cases and 677 controls) who carried the LL genotype had a modest association with prostate cancer (LL vs. VV, OR, 1.70; 95% CI, 1.092.66 and LL vs. VV+VL, OR, 1.75; 95% CI, 1.142.68).[148] A subsequent systematic review and meta-analysis including 27 nonfamilial case-control studies found no statistically significant association between either the V89L or A49T polymorphisms and prostate cancer risk.[149]

Polymorphisms in several genes involved in the biosynthesis, activation, metabolism, and degradation of androgens (CYP17, CYP3A4, CYP19A1, and SRD5A2) and the stimulation of mitogenic and antiapoptotic activities (IGF-1 and IGFBP-3) of normal prostate cells were examined for association with prostate cancer in 131 African American cases and 342 controls. While allele frequencies did not differ between cases and controls regarding three SNPs in the CYP17 gene (rs6163, rs6162, and rs743572), heterozygous genotypes of these SNPs were found to be associated with a reduced risk (OR, 0.56; 95% CI, 0.350.88; OR, 0.57; 95% CI, 0.360.90; OR, 0.55; 95% CI, 0.350.88, respectively). Evidence suggestive of an association between SNP rs5742657 in intron 2 of IGF-1 was also found (OR, 1.57; 95% CI, 0.942.63).[150] Additional studies are needed to confirm these findings.

Other investigators have explored the potential contribution of the variation in genes involved in the estrogen pathway. A Swedish population study of 1,415 prostate cancer cases and 801 age-matched controls examined the association of SNPs in the estrogen receptor-beta (ER-beta) gene and prostate cancer. One SNP in the promoter region of ER-beta, rs2987983, was associated with an overall prostate cancer risk of 1.23 and 1.35 for localized disease.[151] This study awaits replication.

Germline mutations in the tumor suppressor gene E-cadherin (also called CDH1) cause a hereditary form of gastric carcinoma. A SNP designated -160A, located in the promoter region of E-cadherin, has been found to alter the transcriptional activity of this gene.[152] Because somatic mutations in E-cadherin have been implicated in the development of invasive malignancies in a number of different cancers,[153] investigators have searched for evidence that this functionally significant promoter might be a modifier of cancer risk. A meta-analysis of 47 case-control studies in 16 cancer types included ten prostate cancer cohorts (3,570 cases and 3,304 controls). The OR of developing prostate cancer among risk allele carriers was 1.33 (95% CI, 1.111.60). However, the authors of the study noted that there are sources of bias in the dataset, stemming mostly from the small sample sizes of individual cohorts.[154] Additional studies are required to determine whether this finding is reproducible and biologically and clinically important.

There is a great deal of interest in the possibility that chronic inflammation may represent an important risk factor in prostate carcinogenesis.[155] The family of toll-like receptors has been recognized as a critical component of the intrinsic immune system,[156] one which recognizes ligands from exogenous microbes and a variety of endogenous substrates. This family of genes has been studied most extensively in the context of autoimmune disease, but there also have been a series of studies that have analyzed genetic variants in various members of this pathway as potential prostate cancer risk modifiers.[157-161] The results have been inconsistent, ranging from decreased risk, to null association, to increased risk.

One study was based upon 1,414 incident prostate cancer cases and 1,414 age-matched controls from the American Cancer Society Cancer Prevention Study II Nutrition Cohort.[162] These investigators genotyped 28 SNPs in a region on chromosome 4p14 that includes TLR-10, TLR-1, and TLR-6, three members of the toll-like receptor gene cluster. Two TLR-10 SNPs and four TLR-1 SNPs were associated with significant reductions in prostate cancer risk, ranging from 29% to 38% for the homozygous variant genotype. A more detailed analysis demonstrated these six SNPs were not independent in their effect, but rather represented a single strong association with reduced risk (OR, 0.55; 95% CI, 0.330.90). There were no significant differences in this association when covariates such as Gleason score, history of benign prostatic hypertrophy, use of nonsteroidal anti-inflammatory drugs, and body mass index were taken into account. This is the largest study undertaken to date and included the most comprehensive panel of SNPs evaluated in the 4p14 region. While these observations provide a basis for further investigation of the toll-like receptor genes in prostate cancer etiology, inconsistencies with the prior studies and lack of information regarding what the biological basis of these associations might be warrant caution in interpreting the findings.

SNPs in genes involved in the steroid hormone pathway have previously been studied in sporadic and familial prostate cancer using a sample of individuals with primarily Caucasian ancestry.[163] Another study evaluated 116 tagging SNPs located in 12 genes in the steroid hormone pathway for risk of prostate cancer in 886 cases and 1,566 controls encompassing non-Hispanic white men, Hispanic white men, and African American men.[164] The genes included CYP17, HSD17B3, ESR1, SRD5A2, HSD3B1, HSD3B2, CYP19, CYP1A1, CYP1B1, CYP3A4, CYP27B1, and CYP24A1. Several SNPs in CYP19 were associated with prostate cancer risk in all three populations. Analysis of SNP-SNP interactions involving SNPs in multiple genes revealed a seven-SNP interaction involving HSD17B3, CYP19, and CYP24A1 in Hispanic whites (P = .001). In non-Hispanic whites, an interaction of four SNPs in HSD3B2, HSD17B3, and CYP19 was found (P

A meta-analysis of the relationship between eight polymorphisms in six genes (MTHFR, MTR, MTHFD1, SLC19A1, SHMT1, and FOLH1) from the folate pathway was conducted by pooling data from eight case-control studies, four GWAS, and a nested case-control study named Prostate Testing for Cancer and Treatment in the United Kingdom. Numbers of tested subjects varied among these polymorphisms, with up to 10,743 cases and 35,821 controls analyzed. The report concluded that known common folate-pathway SNPs do not have significant effects on prostate cancer susceptibility in white men.[165]

Four SNPs in the p53 pathway (three in genes regulating p53 function including MDM2, MDM4, and HAUSP and one in p53) were evaluated for association with aggressive prostate cancer in a hospital-based prostate cancer cohort of men with Caucasian ethnicity (N = 4,073).[166] However, a subsequent meta-analysis of case-control studies that focused on MDM2 (T309G) and prostate cancer risk revealed no association.[167] Therefore, the biologic basis of the various associations identified requires further study.

Table 3 summarizes additional case-control studies that have assessed genes that are potentially associated with prostate cancer susceptibility.

Case-control studies assessed site-specific prostate cancer susceptibility in the following genes: EMSY, KLF6, AMACR, NBS1, CHEK2, AR, SRD5A2, ER-beta, E-cadherin, and the toll-like receptor genes. These studies have been complicated by the later-onset nature of the disease and the high background rate of prostate cancer in the general population. In addition, there is likely to be real, extensive locus heterogeneity for hereditary prostate cancer, as suggested by both segregation and linkage studies. In this respect, hereditary prostate cancer resembles a number of the other major adult-onset hereditary cancer syndromes, in which more than one gene can produce the same or very similar clinical phenotype (e.g., hereditary breast/ovarian cancer, Lynch syndrome, hereditary melanoma, and hereditary renal cancer). The clinical validity and utility of genetic testing for any of these genes based solely on evidence for hereditary prostate cancer susceptibility has not been established.

Admixture mapping is a method used to identify genetic variants associated with traits and/or diseases in individuals with mixed ancestry.[178] This approach is most effective when applied to individuals whose admixture was recent and consists of two populations who had previously been separated for thousands of years. The genomes of such individuals are a mosaic, comprised of large blocks from each ancestral locale. The technique takes advantage of a difference in disease incidence in one ancestral group compared with another. Genetic risk loci are presumed to reside in regions enriched for the ancestral group with higher incidence. Successful mapping depends on the availability of population-specific genetic markers associated with ancestry, and on the number of generations since admixture.[179,180]

Admixture mapping is a particularly attractive method for identifying genetic loci associated with increased prostate cancer risk among African Americans. African American men are at higher risk of developing prostate cancer than are men of European ancestry, and the genomes of African American men are mosaics of regions from Africa and regions from Europe. It is therefore hypothesized that inherited variants accounting for the difference in incidence between the two groups must reside in regions enriched for African ancestry. In prostate cancer admixture studies, genetic markers for ancestry were genotyped genome-wide in African American cases and controls in a search for areas enriched for African ancestry in the men with prostate cancer. Admixture studies have identified the following chromosomal regions associated with prostate cancer:

An advantage of this approach is that recent admixtures result in long stretches of linkage disequilibrium (up to hundreds of thousands of base pairs) of one particular ancestry.[182] As a result, fewer markers are needed to search for genetic variants associated with specific diseases, such as prostate cancer, than the number of markers needed for successful GWAS.[179] (Refer to the GWAS section of this summary for more information.)

Genome-wide searches have successfully identified susceptibility alleles for many complex diseases,[183] including prostate cancer. This approach can be contrasted with linkage analysis, which searches for genetic risk variants co-segregating within families that have a high prevalence of disease. Linkage analyses are designed to uncover rare, highly penetrant variants that segregate in predictable heritance patterns (e.g., autosomal dominant, autosomal recessive, X-linked, and mitochondrial). GWAS, on the other hand, are best suited to identify multiple, common, low-penetrance genetic polymorphisms. GWAS are conducted under the assumption that the genetic underpinnings of complex phenotypes, such as prostate cancer, are governed by many alleles, each conferring modest risk. Most genetic polymorphisms genotyped in GWAS are common, with minor allele frequencies greater than 1% to 5% within a given ancestral population (e.g., men of European ancestry). GWAS survey all common inherited variants across the genome, searching for alleles that are associated with incidence of a given disease or phenotype.[184,185] The strong correlation between many alleles located close to one another on a given chromosome (called linkage disequilibrium) allows one to scan the genome without having to test all tens of millions of known SNPs. GWAS can test approximately 1 million to 5 million SNPs and ascertain almost all common inherited variants in the genome.

In a GWAS, allele frequency is compared for each SNP between cases and controls. Promising signalsin which allele frequencies deviate significantly in case compared to control populationsare validated in replication cohorts. In order to have adequate statistical power to identify variants associated with a phenotype, large numbers of cases and controls, typically thousands of each, are studied. Because 1 million SNPs are typically evaluated in a GWAS, false-positive findings are expected to occur frequently when standard statistical thresholds are used. Therefore, stringent statistical rules are used to declare a positive finding, usually using a threshold of P

To date, approximately 100 variants associated with prostate cancer have been identified by well-powered GWAS and validated in independent cohorts (see Table 4).[189] These studies have revealed convincing associations between specific inherited variants and prostate cancer risk. However, the findings should be qualified with a few important considerations:

The implications of these points are discussed in greater detail below. Additional detail can be found elsewhere.[192]

In 2006, two genome-wide studies seeking associations with prostate cancer risk converged on the same chromosomal locus, 8q24. Using a technique called admixture mapping, a 3.8 megabase (Mb) region emerged as significantly involved with risk in African American men.[69] In another study, linkage analysis of 323 Icelandic prostate cancer cases also revealed an 8q24 risk locus.[68] Detailed genotyping of this region and an association study for prostate cancer risk in three case-control populations in Sweden, Iceland, and the United States revealed specific 8q24 risk markers: a SNP, rs1447295, and a microsatellite polymorphism, allele-8 at marker DG8S737.[68] The population-attributable risk of prostate cancer from these alleles was 8%. The results were replicated in an African American case-control population, and the population attributable risk was 16%.[68] These results were confirmed in several large, independent cohorts.[70-73,80-83,193] Subsequent GWAS independently converged on another risk variant at 8q24, rs6983267.[73-75] Fine mapping, genotyping a large number of variants densely packed within a region of interest in many cases and controls, was performed across 8q24 targeting the variants most significantly associated with prostate cancer risk. Across multiple ethnic populations, three distinct 8q24 risk loci were described: region 1 (containing rs1447295) at 128.54128.62 Mb, region 2 at 128.14128.28 Mb, and region 3 (containing rs6983267) at 128.47128.54 Mb.[75] Variants within each of these three regions independently confer disease risk with ORs ranging from 1.11 to 1.66. In 2009, two separate GWAS uncovered two additional risk regions at 8q24. In all, approximately nine genetic polymorphisms, all independently associated with disease, reside within five distinct 8q24 risk regions.[86,87]

Since the discovery of prostate cancer risk loci at 8q24, other chromosomal risk loci similarly have been identified by multistage GWAS comprised of thousands of cases and controls and validated in independent cohorts. The most convincing associations reported to date for men of European ancestry are included in Table 4. The association between risk and allele status for each variant listed in Table 4 reached genome-wide statistical significance in more than one independent cohort.

Most prostate cancer GWAS data generated to date have been derived from populations of European descent. This shortcoming is profound, considering that linkage disequilibrium structure, SNP frequencies, and incidence of disease differ across ancestral groups. To provide meaningful genetic data to all patients, well-designed, adequately powered GWAS must be aimed at specific ethnic groups.[206] Most work in this regard has focused on African American, Chinese, and Japanese men. The most convincing associations reported to date for men of non-European ancestry are included in Table 5. The association between risk and allele status for each variant listed in Table 5 reached genome-wide statistical significance in more than one independent cohort.

The African American population is of particular interest because American men with African ancestry are at higher risk of prostate cancer than any other group. In addition, inherited variation at the 8q24 risk locus appears to contribute to differences in African American and European American incidence of disease.[69] A handful of studies have sought to determine whether GWAS findings in men of European ancestry are applicable to men of African ancestry. One study interrogated 28 known prostate cancer risk loci via fine mapping in 3,425 African American cases and 3,290 African American controls.[208] On average, risk allele frequencies were 0.05 greater in African Americans than in European Americans. Of the 37 known risk SNPs analyzed, 18 replicated in the African American population were significantly associated with prostate cancer at P .05 (the study was underpowered to properly assess nine of the remaining 19 SNPs). For seven risk regions (2p24, 2p15, 3q21, 6q22, 8q21, 11q13, and 19q13), fine mapping identified SNPs in the African American population more strongly associated with risk than the index SNPs reported in the original European-based GWAS. Fine mapping of the 8q24 region revealed four SNPs associated with disease that are substantially more common in African Americans. The SNP most strongly correlated with disease among African Americans (rs6987409) is not strongly correlated with a European risk allele and may account for a portion of increased risk in the African American population. In all, the risk SNPs identified in this study are estimated to represent 11% of total inherited risk.

Some of the risk variants identified in Table 5 have also been found to confer risk in men of European ancestry. These include rs16901979, rs6983267, and rs1447295 at 8q24 in African Americans and rs13254738 in Japanese populations. Additionally, the Japanese rs4430796 at 17q12 and rs2660753 at 3p12 have also been observed in men of European ancestry. However, the vast majority of the variants identified in these studies reveal novel variants that are unique to that specific ethnic population. These results confirm the importance of evaluating SNP associations in different ethnic populations. Considerable effort is still needed to fully annotate genetic risk in these and other populations.

Because the variants discovered by GWAS are markers of risk, there has been great interest in using genotype as a screening tool to predict the development of prostate cancer. In an attempt to determine the potential clinical value of risk SNP genotype, cases of prostate cancer (n = 2,893) were identified from four cancer registries in Sweden. Controls (n = 1,781) were randomly selected from the Swedish Population Registry and were matched to cases by age and geographic region.[78] Known risk SNPs from 8q24, 17q12, and 17q24.3 were analyzed (rs4430796 at 17q12, rs1859962 at 17q24.3, rs16901979 at 8q24 [region 2], rs6983267 at 8q24 [region 3], and rs1447295 at 8q24 [region 1]). ORs for prostate cancer for men carrying any combination of one, two, three, or four or more genotypes associated with prostate cancer were estimated by comparing them with men carrying none of the associated genotypes using logistic regression analysis. Men who carried one to five risk alleles had an increasing likelihood of having prostate cancer compared with men carrying none of the alleles (P = 6.75 10-27). After controlling for age, geographic location, and family history of prostate cancer, men carrying four or more of these alleles had a significant elevation in risk of prostate cancer (OR, 4.47; 95% CI, 2.936.80; P = 1.20 10-13). When family history was added as a risk factor, men with five or more factors (five SNPs plus family history) had an even stronger risk of prostate cancer (OR, 9.46; 95% CI, 3.6224.72; P = 1.29 10-8). The population-attributable risks (PARs) for these five SNPs were estimated to account for 4% to 21% of prostate cancer cases in Sweden, and the joint PAR for prostate cancer of the five SNPs plus family history was 46%.

A second study assessed prostate cancer risk associated with a family history of prostate cancer in combination with various numbers of 27 risk alleles identified through four prior GWAS. Two case-control populations were studied, the Prostate, Lung, Colon, and Ovarian Cancer Screening Trial (PLCO) in the United States (1,172 cases and 1,157 controls) and the Cancer of the Prostate in Sweden (CAPS) study (2,899 cases and 1,722 controls). The highest risk of prostate cancer from the CAPS population was observed in men with a positive family history and greater than 14 risk alleles (OR, 4.92; 95% CI, 3.646.64). Repeating this analysis in the PLCO population revealed similar findings (OR, 3.88; 95% CI, 2.835.33).[214]

However, the proportion of men carrying large numbers of the risk alleles was low. While ORs were impressively high for this subset, they do not reflect the utility of genotyping the overall population. Receiver operating characteristic curves were constructed in these studies to measure the sensitivity and specificity of certain risk profiles. The area under the curve (AUC) was 0.61 when age, geographic region, and family history were used to assess risk. When genotype of the five risk SNPs at chromosomes 8 and 17 were introduced, a very modest AUC improvement to 0.63 was detected.[78] The addition of more recently discovered SNPs to the model has not appreciably improved these results.[215] While genotype may inform risk status for the small minority of men carrying multiple risk alleles, testing of the known panel of prostate cancer SNPs is currently of questionable clinical utility.[216]

Another study incorporated 10,501 prostate cancer cases and 10,831 controls from multiple cohorts (including PLCO) and genotyped each individual for 25 prostate cancer risk SNPs. Age and family history data were available for all subjects. Genotype data helped discriminate those who developed prostate cancer from those who did not. However, similar to the series above, discriminative ability was modest and only compelling at the extremes of risk allele distribution in a relatively small subset population; younger subjects (men aged 50 to 59 years) with a family history of disease who were in 90th percentile for risk allele status had an absolute 10-year risk of 6.7% compared with an absolute 10-year risk of 1.6% in men in the 10th percentile for risk allele status.[217]

In another study, 49 risk SNPs were genotyped in 2,696 Swedish men, and a polygenic risk score was calculated. On the basis of their genetic risk scores, 172 men aged 50 to 69 years with PSA levels of 1 to 3 ng/mL underwent biopsy. Prostate cancer was diagnosed in 27% of these individuals, and 6% had Gleason 7 or higher disease.[218] The utility of this strategy for identifying who should undergo prostate biopsy is yet to be determined.

In July 2012, the Agency for Healthcare Research and Quality (AHRQ) published a report that sought to address the clinical utility of germline genotyping of prostate cancer risk markers discovered by GWAS.[216] Largely on the basis of the evidence from the studies described above, AHRQ concluded that established prostate cancer risk SNPs have poor discriminative ability to identify individuals at risk of developing the disease. Similarly, the authors of another study estimated that the contribution of GWAS polymorphisms in determining the risk of developing prostate cancer will be modest, even as meta-analyses or larger studies uncover additional common risk alleles (alleles carried by >1%5% of individuals within the population).[219]

GWAS findings to date account for only a fraction of heritable risk of disease. Research is ongoing to uncover the remaining portion of genetic risk. This includes the discovery of rarer alleles with higher ORs for risk. For example, a consortium led by deCODE genetics in Iceland performed whole-genome sequencing of 2,500 Icelanders and identified approximately 32.5 million variants, including millions of rare variants (carried by

In addition, other genetic polymorphisms, such as copy number variants, are becoming increasingly amenable to testing. As the full picture of inherited prostate cancer risk becomes more complete, it is hoped that germline information will become clinically useful.

Notably, almost all reported prostate cancer risk alleles reside in nonprotein coding regions of the genome, and the underlying biological mechanism of disease susceptibility remains unclear. Hypotheses explaining the mechanism of inherited risk include the following:

The 8q24 risk locus, which contains multiple prostate cancer risk alleles and risk alleles for other cancers, has been the focus of intense study. c-MYC, a known oncogene, is the closest known gene to the 8q24 risk regions, although it is located hundreds of kb away. Given this significant distance, SNPs within c-MYC are not in linkage disequilibrium with the 8q24 prostate cancer risk variants. One study examined whether 8q24 prostate cancer risk SNPs are in fact located in areas of previously unannotated transcription, and no transcriptional activity was uncovered at the risk loci.[222] Attention turned to the idea of distal gene regulation. Interrogation of the epigenetic landscape at the 8q24 risk loci revealed that the risk variants are located in areas that bear the marks of genetic enhancers, elements that influence gene activity from a distance.[223-225] To identify a prostate cancer risk gene, germline DNA from 280 men undergoing prostatectomy for prostate cancer was genotyped for all known 8q24 risk SNPs. Genotypes were tested for association with the normal prostate and prostate tumor RNA expression levels of genes located within one Mb of the risk SNPs. No association was detected between expression of any of the genes, including c-MYC, and risk allele status in either normal epithelium or tumor tissue. Another study, using normal prostate tissue from 59 patients, detected an association between an 8q24 risk allele and the gene PVT1, downstream from c-MYC.[226] Nonetheless, c-MYC, with its substantial involvement in many cancers, remains a prime candidate. A series of experiments in prostate cancer cell lines demonstrated that chromatin is configured in such a way that the 8q24 risk variants lie in close proximity to c-MYC, even though they are quite distant in linear space. These data implicate c-MYC despite the absence of expression data.[224,226] Further work at 8q24 and similar analyses at other prostate cancer risk loci are ongoing.

Additional insights are emerging regarding the potential interaction between SNPs identified from GWAS and prostate cancer susceptibility gene regulation. One study found that a SNP at 6q22 lies within a binding region for HOXB13. Through multiple functional approaches, the T allele of this SNP (rs339331) was found to enhance binding of HOXB13, leading to allele-specific upregulation of RFX6, which correlates with prostate cancer progression and severity.[227] Thus, this study supports the hypothesis that risk alleles identified from GWAS may play a role in regulating or modifying gene expression and therefore impact prostate cancer risk.

A 2012 study used a novel approach to identify polymorphisms associated with risk.[228] On the basis of the well-established principle that the AR plays a prominent role in prostate tumorigenesis, the investigators targeted SNPs that reside at sites where the AR binds to DNA. They leveraged data from previous studies that mapped thousands of AR binding sites genome-wide in prostate cancer cell lines to select SNPs to genotype in the Johns Hopkins Hospital cohort of 1,964 cases and 3,172 controls and the Cancer Genetic Markers of Susceptibility cohort of 1,172 cases and 1,157 controls. This modified GWAS revealed a SNP (rs4919743) located at the KRT8 locus at 12q13.13a locus previously implicated in cancer developmentassociated with prostate cancer risk, with an OR of 1.22 (95% CI, 1.131.32). The study is notable for its use of a reasonable hypothesis and prior data to guide a genome-wide search for risk variants.

Although the statistical evidence for an association between genetic variation at these loci and prostate cancer risk is overwhelming, the clinical relevance of the variants and the mechanism(s) by which they lead to increased risk are unclear and will require further characterization. Additionally, these loci are associated with very modest risk estimates and explain only a fraction of overall inherited risk. Further work will include genome-wide analysis of rarer alleles catalogued via sequencing efforts, such as the 1000 Genomes Project.[229] Disease-associated alleles with frequencies of less than 1% in the population may prove to be more highly penetrant and clinically useful. In addition, further work is needed to describe the landscape of genetic risk in non-European populations. Finally, until the individual and collective influences of genetic risk alleles are evaluated prospectively, their clinical utility will remain difficult to fully assess.

Prostate cancer is clinically heterogeneous. Many cases are indolent and are successfully managed with observation alone. Other cases are quite aggressive and prove deadly. Several variables are used to determine prostate cancer aggressiveness at the time of diagnosis, such as Gleason score and PSA, but these are imperfect. Additional markers are needed, as sound treatment decisions depend on accurate prognostic information. Germline genetic variants are attractive markers since they are present, easily detectable, and static throughout life. Several studies have interrogated inherited variants that may distinguish indolent and aggressive prostate cancer. Several of these studies identified polymorphisms associated with aggressiveness, after adjusting for commonly used clinical variables, and are reviewed in the Table 6.

Findings to date regarding inherited risk of aggressive disease are considered preliminary. Further work is needed to validate findings and assess prospectively.

Like studies of the genetics of prostate cancer risk, initial studies of inherited risk of aggressive prostate cancer focused on polymorphisms in candidate genes. Next, as GWAS revealed prostate cancer risk SNPs, several research teams sought to determine whether certain risk SNPs were also associated with aggressiveness (see table below). There has been great interest in launching more unbiased, genome-wide searches for inherited variants associated with indolent versus aggressive prostate cancer. While GWAS designed explicitly for disease aggressiveness have been initiated, most genome-wide analyses to date have relied on datasets previously generated to evaluate prostate cancer risk. The cases from these case-control cohorts were divided into aggressive and nonaggressive subgroups then compared with each other and/or with the control (nonprostate cancer) subjects. Several associations between germline markers and prostate cancer aggressiveness have been reported. However, there remains no accepted set of germline markers that clearly provides prognostic information beyond that provided by more traditional variables at the time of diagnosis.

In independent retrospective series (see Table 6) the prostate cancer risk allele at rs2735839 (G) was associated with less aggressive disease. This risk allele has also been associated with higher PSA levels.[198,238] A hypothesis explaining the association between the nonrisk allele (A) and more aggressive disease is that those carrying the A allele generally have lower PSA levels and are sent for prostate biopsy less often. They subsequently may be diagnosed later in the natural history of the disease, resulting in poorer outcomes.

To definitively identify the inherited variants associated with prostate cancer aggressiveness, GWAS focusing on prostate cancer subjects with poor disease-related outcomes are needed. Notably, in a genome-wide analysis in which two of the largest international prostate cancer genotyped cohorts were combined for analysis (24,023 prostate cancer cases, including 3,513 disease-specific deaths), no SNP was associated with prostate cancerspecific survival.[239] The authors concluded that any SNP associated with prostate cancer outcome must be fairly rare in the general population (minor allele frequency below 1%). As more data regarding rarer variants are generated and validated, the value of inherited variants for therapeutic decision making may be determined.

While genetic testing for prostate cancer is not yet standard clinical practice, research from selected cohorts has reported that prostate cancer risk is elevated in men with mutations in BRCA1, BRCA2, and on a smaller scale, in mismatch repair (MMR) genes. Since clinical genetic testing is available for these genes, information about risk of prostate cancer based on alterations in these genes is included in this section. In addition, mutations in HOXB13 were reported to account for a proportion of hereditary prostate cancer. Although clinical testing is not yet available for HOXB13 alterations, it is expected that this gene will have clinical relevance in the future and therefore it is also included in this section. The genetic alterations described in this section require further study and are not to be used in routine clinical practice at this time.

Studies of male BRCA1 [1] and BRCA2 mutation carriers demonstrate that these individuals have a higher risk of prostate cancer and other cancers.[2] Prostate cancer in particular has been observed at higher rates in male BRCA2 mutations carriers than in the general population.[3]

The risk of prostate cancer in BRCA mutation carriers has been studied in various settings.

In an effort to clarify the relationship between BRCA mutations and prostate cancer risk, findings from several case series are summarized in Table 7.

Estimates derived from the Breast Cancer Linkage Consortium may be overestimated because these data are generated from a highly select population of families ascertained for significant evidence of risk of breast cancer and ovarian cancer and suitability for linkage analysis. However, a review of the relationship between germline mutations in BRCA2 and prostate cancer risk supports the view that this gene confers a significant increase in risk among male members of hereditary breast and ovarian cancer families but that it likely plays only a small role, if any, in site-specific, multiple-case prostate cancer families.[6] In addition, the clinical validity and utility of BRCA testing solely on the basis of evidence for hereditary prostate cancer susceptibility has not been established.

Several studies in Israel and in North America have analyzed the frequency of BRCA founder mutations among Ashkenazi Jewish (AJ) men with prostate cancer.[7-9] Two specific BRCA1 mutations (185delAG and 5382insC) and one BRCA2 mutation (6174delT) are common in individuals of AJ ancestry. Carrier frequencies for these mutations in the general Jewish population are 0.9% (95% CI, 0.71.1) for the 185delAG mutation, 0.3% (95% confidence interval [CI], 0.20.4) for the 5382insC mutation, and 1.3% (95% CI, 1.01.5) for the BRCA2 6174delT mutation.[10-13] (Refer to the High-Penetrance Breast and/or Gynecologic Cancer Susceptibility Genes section in the PDQ summary on Genetics of Breast and Gynecologic Cancers for more information about BRCA1 and BRCA2 genes.) In these studies, the relative risks (RRs) were commonly greater than 1, but only a few have been statistically significant. Many of these studies were not sufficiently powered to rule out a lower, but clinically significant, risk of prostate cancer in carriers of Ashkenazi BRCA founder mutations.

In the Washington Ashkenazi Study (WAS), a kin-cohort analytic approach was used to estimate the cumulative risk of prostate cancer among more than 5,000 American AJ male volunteers from the Washington, District of Columbia, area who carried one of the BRCA Ashkenazi founder mutations. The cumulative risk to age 70 years was estimated to be 16% (95% CI, 430) among carriers and 3.8% among noncarriers (95% CI, 3.34.4).[13] This fourfold increase in prostate cancer risk was equal (in absolute terms) to the cumulative risk of ovarian cancer among female mutation carriers at the same age (16% by age 70 years; 95% CI, 628). The risk of prostate cancer in male mutation carriers in the WAS cohort was elevated by age 50 years, was statistically significantly elevated by age 67 years, and increased thereafter with age, suggesting both an overall excess in prostate cancer risk and an earlier age at diagnosis among carriers of Ashkenazi founder mutations. Prostate cancer risk differed depending on the gene, with BRCA1 mutations associated with increasing risk after age 55 to 60 years, reaching 25% by age 70 years and 41% by age 80 years. In contrast, prostate cancer risk associated with the BRCA2 mutation began to rise at later ages, reaching 5% by age 70 years and 36% by age 80 years (numeric values were provided by the author [written communication, April 2005]).

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Genetics of Prostate Cancer (PDQ)Health Professional …

Genetics of Skin Cancer (PDQ)Health Professional Version


[Note: Many of the medical and scientific terms used in this summary are found in the NCI Dictionary of Genetics Terms. When a linked term is clicked, the definition will appear in a separate window.]

[Note: Many of the genes described in this summary are found in the Online Mendelian Inheritance in Man (OMIM) database. When OMIM appears after a gene name or the name of a condition, click on OMIM for a link to more information.]

The genetics of skin cancer is an extremely broad topic. There are more than 100 types of tumors that are clinically apparent on the skin; many of these are known to have familial components, either in isolation or as part of a syndrome with other features. This is, in part, because the skin itself is a complex organ made up of multiple cell types. Furthermore, many of these cell types can undergo malignant transformation at various points in their differentiation, leading to tumors with distinct histology and dramatically different biological behaviors, such as squamous cell carcinoma (SCC) and basal cell cancer (BCC). These have been called nonmelanoma skin cancers or keratinocyte cancers.

Figure 1 is a simple diagram of normal skin structure. It also indicates the major cell types that are normally found in each compartment. Broadly speaking, there are two large compartmentsthe avascular epidermis and the vascular dermiswith many cell types distributed in a largely acellular matrix.[1]

Figure 1. Schematic representation of normal skin. The relatively avascular epidermis houses basal cell keratinocytes and squamous epithelial keratinocytes, the source cells for BCC and SCC, respectively. Melanocytes are also present in normal skin and serve as the source cell for melanoma. The separation between epidermis and dermis occurs at the basement membrane zone, located just inferior to the basal cell keratinocytes.

The outer layer or epidermis is made primarily of keratinocytes but has several other minor cell populations. The bottom layer is formed of basal keratinocytes abutting the basement membrane. The basement membrane is formed from products of keratinocytes and dermal fibroblasts, such as collagen and laminin, and is an important anatomical and functional structure. Basal keratinocytes lose contact with the basement membrane as they divide. As basal keratinocytes migrate toward the skin surface, they progressively differentiate to form the spinous cell layer; the granular cell layer; and the keratinized outer layer, or stratum corneum.

The true cytologic origin of BCC remains in question. BCC and basal cell keratinocytes share many histologic similarities, as is reflected in the name. Alternatively, the outer root sheath cells of the hair follicle have also been proposed as the cell of origin for BCC.[2] This is suggested by the fact that BCCs occur predominantly on hair-bearing skin. BCCs rarely metastasize but can invade tissue locally or regionally, sometimes following along nerves. A tendency for superficial necrosis has resulted in the name “rodent ulcer.”[3]

Some debate remains about the origin of SCC; however, these cancers are likely derived from epidermal stem cells associated with the hair follicle.[4] A variety of tissues, such as lung and uterine cervix, can give rise to SCC, and this cancer has somewhat differing behavior depending on its source. Even in cancer derived from the skin, SCC from different anatomic locations can have moderately differing aggressiveness; for example, SCC from glabrous (smooth, hairless) skin has a lower metastatic rate than SCC arising from the vermillion border of the lip or from scars.[3]

Additionally, in the epidermal compartment, melanocytes distribute singly along the basement membrane and can undergo malignant transformation into melanoma. Melanocytes are derived from neural crest cells and migrate to the epidermal compartment near the eighth week of gestational age. Langerhans cells, or dendritic cells, are another cell type in the epidermis and have a primary function of antigen presentation. These cells reside in the skin for an extended time and respond to different stimuli, such as ultraviolet radiation or topical steroids, which cause them to migrate out of the skin.[5]

The dermis is largely composed of an extracellular matrix. Prominent cell types in this compartment are fibroblasts, endothelial cells, and transient immune system cells. When transformed, fibroblasts form fibrosarcomas and endothelial cells form angiosarcomas, Kaposi sarcoma, and other vascular tumors. There are a number of immune cell types that move in and out of the skin to blood vessels and lymphatics; these include mast cells, lymphocytes, mononuclear cells, histiocytes, and granulocytes. These cells can increase in number in inflammatory diseases and can form tumors within the skin. For example, urticaria pigmentosa is a condition that arises from mast cells and is occasionally associated with mast cell leukemia; cutaneous T-cell lymphoma is often confined to the skin throughout its course. Overall, 10% of leukemias and lymphomas have prominent expression in the skin.[6]

Epidermal appendages are also found in the dermal compartment. These are derivatives of the epidermal keratinocytes, such as hair follicles, sweat glands, and the sebaceous glands associated with the hair follicles. These structures are generally formed in the first and second trimesters of fetal development. These can form a large variety of benign or malignant tumors with diverse biological behaviors. Several of these tumors are associated with familial syndromes. Overall, there are dozens of different histological subtypes of these tumors associated with individual components of the adnexal structures.[7]

Finally, the subcutis is a layer that extends below the dermis with varying depth, depending on the anatomic location. This deeper boundary can include muscle, fascia, bone, or cartilage. The subcutis can be affected by inflammatory conditions such as panniculitis and malignancies such as liposarcoma.[8]

These compartments give rise to their own malignancies but are also the region of immediate adjacent spread of localized skin cancers from other compartments. The boundaries of each skin compartment are used to define the staging of skin cancers. For example, an in situ melanoma is confined to the epidermis. Once the cancer crosses the basement membrane into the dermis, it is invasive. Internal malignancies also commonly metastasize to the skin. The dermis and subcutis are the most common locations, but the epidermis can also be involved in conditions such as Pagetoid breast cancer.

The skin has a wide variety of functions. First, the skin is an important barrier preventing extensive water and temperature loss and providing protection against minor abrasions. These functions can be aberrantly regulated in cancer. For example, in the erythroderma (reddening of the skin) associated with advanced cutaneous T-cell lymphoma, alterations in the regulations of body temperature can result in profound heat loss. Second, the skin has important adaptive and innate immunity functions. In adaptive immunity, antigen-presenting cells engender T-cell responses consisting of increased levels of TH1, TH2, or TH17 cells.[9] In innate immunity, the immune system produces numerous peptides with antibacterial and antifungal capacity. Consequently, even small breaks in the skin can lead to infection. The skin-associated lymphoid tissue is one of the largest arms of the immune system. It may also be important in immune surveillance against cancer. Immunosuppression, which occurs during organ transplant, is a significant risk factor for skin cancer. The skin is significant for communication through facial expression and hand movements. Unfortunately, areas of specialized function, such as the area around the eyes and ears, are common places for cancer to occur. Even small cancers in these areas can lead to reconstructive challenges and have significant cosmetic and social ramifications.[1]

While the appearance of any one skin cancer can vary, there are general physical presentations that can be used in screening. BCCs most commonly have a pearly rim or can appear somewhat eczematous (see Figure 2 and Figure 3). They often ulcerate (see Figure 2). SCCs frequently have a thick keratin top layer (see Figure 4). Both BCCs and SCCs are associated with a history of sun-damaged skin. Melanomas are characterized by asymmetry, border irregularity, color variation, a diameter of more than 6 mm, and evolution (ABCDE criteria). (Refer to What Does Melanoma Look Like? on NCI’s website for more information about the ABCDE criteria.) Photographs representing typical clinical presentations of these cancers are shown below.


Figure 2. Ulcerated basal cell carcinoma (left panel) and ulcerated basal cell carcinoma with characteristic pearly rim (right panel).

Figure 3. Superficial basal cell carcinoma (left panel) and nodular basal cell carcinoma (right panel).


Figure 4. Squamous cell carcinoma on the face with thick keratin top layer (left panel) and squamous cell carcinoma on the leg (right panel).


Figure 5. Melanomas with characteristic asymmetry, border irregularity, color variation, and large diameter.

Basal cell carcinoma (BCC) is the most common malignancy in people of European descent, with an associated lifetime risk of 30%.[1] While exposure to ultraviolet (UV) radiation is the risk factor most closely linked to the development of BCC, other environmental factors (such as ionizing radiation, chronic arsenic ingestion, and immunosuppression) and genetic factors (such as family history, skin type, and genetic syndromes) also potentially contribute to carcinogenesis. In contrast to melanoma, metastatic spread of BCC is very rare and typically arises from large tumors that have evaded medical treatment for extended periods of time. BCCs can invade tissue locally or regionally, sometimes following along nerves. A tendency for superficial necrosis has resulted in the name “rodent ulcer.” With early detection, the prognosis for BCC is excellent.

Sun exposure is the major known environmental factor associated with the development of skin cancer of all types. There are different patterns of sun exposure associated with each major type of skin cancer (BCC, squamous cell carcinoma [SCC], and melanoma). (Refer to the PDQ summary on Skin Cancer Prevention for more information about risk factors for skin cancer in the general population.)

The high-risk phenotype consists of individuals with the following physical characteristics:

Specifically, people with more highly pigmented skin demonstrate lower incidence of BCC than do people with lighter pigmented skin. Individuals with Fitzpatrick Type I or II skin were shown to have a twofold increased risk of BCC in a small case-control study.[2] (Refer to the Pigmentary characteristics section in the Melanoma section of this summary for a more detailed discussion of skin phenotypes based upon pigmentation.) Blond or red hair color was associated with increased risk of BCC in two large cohorts: the Nurses Health Study and the Health Professionals Follow-Up Study.[3]

Individuals with BCCs and/or SCCs report a higher frequency of these cancers in their family members than do controls. The importance of this finding is unclear. Apart from defined genetic disorders with an increased risk of BCC, a positive family history of any skin cancer is a strong predictor of the development of BCC.

A study on the heritability of cancer among 80,309 monozygotic and 123,382 dizygotic twins showed that nonmelanoma skin cancers (NMSCs) have a heritability of 43% (95% confidence interval [CI], 26%59%), suggesting that almost half of the risk of NMSC is caused by inherited factors.[4] Additionally, the cumulative risk of NMSC was 1.9-fold higher for monozygotic than for dizygotic twins (95% CI, 1.82.0).[4]

A personal history of BCC or SCC is strongly associated with subsequent BCC or SCC. There is an approximate 20% increased risk of a subsequent lesion within the first year after a skin cancer has been diagnosed. The mean age of occurrence for these NMSCs is the mid-60s.[5-10] In addition, several studies have found that individuals with a history of skin cancer have an increased risk of a subsequent diagnosis of a noncutaneous cancer;[11-14] however, other studies have contradicted this finding.[15-18] In the absence of other risk factors or evidence of a defined cancer susceptibility syndrome, as discussed below, skin cancer patients are encouraged to follow screening recommendations for the general population for sites other than the skin.

Mutations in the gene coding for the transmembrane receptor protein PTCH1, or PTCH, are associated with basal cell nevus syndrome (BCNS) and sporadic cutaneous BCCs. (Refer to the BCNS section of this summary for more information.) PTCH1, the human homolog of the Drosophila segment polarity gene patched (ptc), is an integral component of the hedgehog signaling pathway, which serves many developmental (appendage development, embryonic segmentation, neural tube differentiation) and regulatory (maintenance of stem cells) roles.

In the resting state, the transmembrane receptor protein PTCH1 acts catalytically to suppress the seven-transmembrane protein Smoothened (Smo), preventing further downstream signal transduction.[19] Binding of the hedgehog ligand to PTCH1 releases inhibition of Smo, with resultant activation of transcription factors (GLI1, GLI2), cell proliferation genes (cyclin D, cyclin E, myc), and regulators of angiogenesis.[20,21] Thus, the balance of PTCH1 (inhibition) and Smo (activation) manages the essential regulatory downstream hedgehog signal transduction pathway. Loss-of-function mutations of PTCH1 or gain-of-function mutations of Smo tip this balance toward activation, a key event in potential neoplastic transformation.

Demonstration of allelic loss on chromosome 9q22 in both sporadic and familial BCCs suggested the potential presence of an associated tumor suppressor gene.[22,23] Further investigation identified a mutation in PTCH1 that localized to the area of allelic loss.[24] Up to 30% of sporadic BCCs demonstrate PTCH1 mutations.[25] In addition to BCC, medulloblastoma and rhabdomyosarcoma, along with other tumors, have been associated with PTCH1 mutations. All three malignancies are associated with BCNS, and most people with clinical features of BCNS demonstrate PTCH1 mutations, predominantly truncation in type.[26]

Truncating mutations in PTCH2, a homolog of PTCH1 mapping to chromosome 1p32.1-32.3, have been demonstrated in both BCC and medulloblastoma.[27,28] PTCH2 displays 57% homology to PTCH1.[29] While the exact role of PTCH2 remains unclear, there is evidence to support its involvement in the hedgehog signaling pathway.[27,30]

BCNS, also known as Gorlin Syndrome, Gorlin-Goltz syndrome, and nevoid BCC syndrome, is an autosomal dominant disorder with an estimated prevalence of 1 in 57,000 individuals.[31] The syndrome is notable for complete penetrance and high levels of variable expressivity, as evidenced by evaluation of individuals with identical genotypes but widely varying phenotypes.[26,32] The clinical features of BCNS differ more among families than within families.[33] BCNS is primarily associated with germline mutations in PTCH1, but families with this phenotype have also been associated with alterations in PTCH2 and SUFU.[34-36]

As detailed above, PTCH1 provides both developmental and regulatory guidance; spontaneous or inherited germline mutations of PTCH1 in BCNS may result in a wide spectrum of potentially diagnostic physical findings. The BCNS mutation has been localized to chromosome 9q22.3-q31, with a maximum logarithm of the odd (LOD) score of 3.597 and 6.457 at markers D9S12 and D9S53.[31] The resulting haploinsufficiency of PTCH1 in BCNS has been associated with structural anomalies such as odontogenic keratocysts, with evaluation of the cyst lining revealing heterozygosity for PTCH1.[37] The development of BCC and other BCNS-associated malignancies is thought to arise from the classic two-hit suppressor gene model: baseline heterozygosity secondary to germline PTCH1 mutation as the first hit, with the second hit due to mutagen exposure such as UV or ionizing radiation.[38-42] However, haploinsufficiency or dominant negative isoforms have also been implicated for the inactivation of PTCH1.[43]

The diagnosis of BCNS is typically based upon characteristic clinical and radiologic examination findings. Several sets of clinical diagnostic criteria for BCNS are in use (refer to Table 1 for a comparison of these criteria).[44-47] Although each set of criteria has advantages and disadvantages, none of the sets have a clearly superior balance of sensitivity and specificity for identifying mutation carriers. The BCNS Colloquium Group proposed criteria in 2011 that required 1 major criterion with molecular diagnosis, two major criteria without molecular diagnosis, or one major and two minor criteria without molecular diagnosis.[47] PTCH1 mutations are found in 60% to 85% of patients who meet clinical criteria.[48,49] Most notably, BCNS is associated with the formation of both benign and malignant neoplasms. The strongest benign neoplasm association is with ovarian fibromas, diagnosed in 14% to 24% of females affected by BCNS.[41,45,50] BCNS-associated ovarian fibromas are more likely to be bilateral and calcified than sporadic ovarian fibromas.[51] Ameloblastomas, aggressive tumors of the odontogenic epithelium, have also been proposed as a diagnostic criterion for BCNS, but most groups do not include it at this time.[52]

Other associated benign neoplasms include gastric hamartomatous polyps,[53] congenital pulmonary cysts,[54] cardiac fibromas,[55] meningiomas,[56-58] craniopharyngiomas,[59] fetal rhabdomyomas,[60] leiomyomas,[61] mesenchymomas,[62] and nasal dermoid tumors. Development of meningiomas and ependymomas occurring postradiation therapy has been documented in the general pediatric population; radiation therapy for syndrome-associated intracranial processes may be partially responsible for a subset of these benign tumors in individuals with BCNS.[63-65] In addition, radiation therapy of malignant medulloblastomas in the BCNS population may result in many cutaneous BCCs in the radiation ports. Similarly, treatment of BCC of the skin with radiation therapy may result in induction of large numbers of additional BCCs.[40,41,61]

The diagnostic criteria for BCNS are described in Table 1 below.

Of greatest concern with BCNS are associated malignant neoplasms, the most common of which is BCC. BCC in individuals with BCNS may appear during childhood as small acrochordon -like lesions, while larger lesions demonstrate more classic cutaneous features.[66] Nonpigmented BCCs are more common than pigmented lesions.[67] The age at first BCC diagnosis associated with BCNS ranges from 3 to 53 years, with a mean age of 21.4 years; the vast majority of individuals are diagnosed with their first BCC before age 20 years.[45,50] Most BCCs are located on sun-exposed sites, but individuals with greater than 100 BCCs have a more uniform distribution of BCCs over the body.[67] Case series have suggested that up to 1 in 200 individuals with BCC demonstrate findings supportive of a diagnosis of BCNS.[31] BCNS has rarely been reported in individuals with darker skin pigmentation; however, significantly fewer BCCs are found in individuals of African or Mediterranean ancestry.[45,68,69] Despite the rarity of BCC in this population, reported cases document full expression of the noncutaneous manifestations of BCNS.[69] However, in individuals of African ancestry who have received radiation therapy, significant basal cell tumor burden has been reported within the radiation port distribution.[45,61] Thus, cutaneous pigmentation may protect against the mutagenic effects of UV but not against ionizing radiation.

Variants associated with an increased risk of BCC in the general population appear to modify the age of BCC onset in individuals with BCNS. A study of 125 individuals with BCNS found that a variant in MC1R (Arg151Cys) was associated with an early median age of onset of 27 years (95% CI, 2034), compared with individuals who did not carry the risk allele and had a median age of BCC of 34 years (95% CI, 3040) (hazard ratio [HR], 1.64; 95% CI, 1.042.58, P = .034). A variant in the TERT-CLPTM1L gene showed a similar effect, with individuals with the risk allele having a median age of BCC of 31 years (95% CI, 2837) relative to a median onset of 41 years (95% CI, 3248) in individuals who did not carry a risk allele (HR, 1.44; 95% CI, 1.081.93, P = .014).[70]

Many other malignancies have been associated with BCNS. Medulloblastoma carries the strongest association with BCNS and is diagnosed in 1% to 5% of BCNS cases. While BCNS-associated medulloblastoma is typically diagnosed between ages 2 and 3 years, sporadic medulloblastoma is usually diagnosed later in childhood, between the ages of 6 and 10 years.[41,45,50,71] A desmoplastic phenotype occurring around age 2 years is very strongly associated with BCNS and carries a more favorable prognosis than sporadic classic medulloblastoma.[72,73] Up to three times more males than females with BCNS are diagnosed with medulloblastoma.[74] As with other malignancies, treatment of medulloblastoma with ionizing radiation has resulted in numerous BCCs within the radiation field.[41,56] Other reported malignancies include ovarian carcinoma,[75] ovarian fibrosarcoma,[76,77] astrocytoma,[78] melanoma,[79] Hodgkin disease,[80,81] rhabdomyosarcoma,[82] and undifferentiated sinonasal carcinoma.[83]

Odontogenic keratocystsor keratocystic odontogenic tumors (KCOTs), as renamed by the World Health Organization working groupare one of the major features of BCNS.[84] Demonstration of clonal loss of heterozygosity (LOH) of common tumor suppressor genes, including PTCH1, supports the transition of terminology to reflect a neoplastic process.[37] Less than one-half of KCOTs from individuals with BCNS show LOH of PTCH1.[43,85] The tumors are lined with a thin squamous epithelium and a thin corrugated layer of parakeratin. Increased mitotic activity in the tumor epithelium and potential budding of the basal layer with formation of daughter cysts within the tumor wall may be responsible for the high rates of recurrence post simple enucleation.[84,86] In a recent case series of 183 consecutively excised KCOTs, 6% of individuals demonstrated an association with BCNS.[84] A study that analyzed the rate of PTCH1 mutations in BCNS-associated KCOTs found that 11 of 17 individuals carried a germline PTCH1 mutation and an additional 3 individuals had somatic mutations in this gene.[87] Individuals with germline PTCH1 mutations had an early age of KCOT presentation. KCOTs occur in 65% to 100% of individuals with BCNS,[45,88] with higher rates of occurrence in young females.[89]

Palmoplantar pits are another major finding in BCC and occur in 70% to 80% of individuals with BCNS.[50] When these pits occur together with early-onset BCC and/or KCOTs, they are considered diagnostic for BCNS.[90]

Several characteristic radiologic findings have been associated with BCNS, including lamellar calcification of falx cerebri;[91,92] fused, splayed or bifid ribs;[93] and flame-shaped lucencies or pseudocystic bone lesions of the phalanges, carpal, tarsal, long bones, pelvis, and calvaria.[49] Imaging for rib abnormalities may be useful in establishing the diagnosis in younger children, who may have not yet fully manifested a diagnostic array on physical examination.

Table 2 summarizes the frequency and median age of onset of nonmalignant findings associated with BCNS.

Individuals with PTCH2 mutations may have a milder phenotype of BCNS than those with PTCH1 mutations. Characteristic features such as palmar/plantar pits, macrocephaly, falx calcification, hypertelorism, and coarse face may be absent in these individuals.[94]

A 9p22.3 microdeletion syndrome that includes the PTCH1 locus has been described in ten children.[95] All patients had facial features typical of BCNS, including a broad forehead, but they had other features variably including craniosynostosis, hydrocephalus, macrosomia, and developmental delay. At the time of the report, none had basal cell skin cancer. On the basis of their hemizygosity of the PTCH1 gene, these patients are presumably at an increased risk of basal cell skin cancer.

Germline mutations in SUFU, a major negative regulator of the hedgehog pathway, have been identified in a small number of individuals with a clinical phenotype resembling that of BCNS.[35,36] These mutations were first identified in individuals with childhood medulloblastoma,[96] and the incidence of medulloblastoma appears to be much higher in individuals with BCNS associated with SUFU mutations than in those with PTCH1 mutations.[35] SUFU mutations may also be associated with an increased predisposition to meningioma.[58,97] Conversely, odontogenic jaw keratocysts appear less frequently in this population. Some clinical laboratories offer genetic testing for SUFU mutations for individuals with BCNS who do not have an identifiable PTCH1 mutation.

Rombo syndrome, a very rare probably autosomal dominant genetic disorder associated with BCC, has been outlined in three case series in the literature.[98-100] The cutaneous examination is within normal limits until age 7 to 10 years, with the development of distinctive cyanotic erythema of the lips, hands, and feet and early atrophoderma vermiculatum of the cheeks, with variable involvement of the elbows and dorsal hands and feet.[98] Development of BCC occurs in the fourth decade.[98] A distinctive grainy texture to the skin, secondary to interspersed small, yellowish, follicular-based papules and follicular atrophy, has been described.[98,100] Missing, irregularly distributed and/or misdirected eyelashes and eyebrows are another associated finding.[98,99] The genetic basis of Rombo syndrome is not known.

Bazex-Dupr-Christol syndrome, another rare genodermatosis associated with development of BCC, has more thorough documentation in the literature than Rombo syndrome. Inheritance is accomplished in an X-linked dominant fashion, with no reported male-to-male transmission.[101-103] Regional assignment of the locus of interest to chromosome Xq24-q27 is associated with a maximum LOD score of 5.26 with the DXS1192 locus.[104] Further work has narrowed the potential location to an 11.4-Mb interval on chromosome Xq25-27; however, the causative gene remains unknown.[105]

Characteristic physical findings include hypotrichosis, hypohidrosis, milia, follicular atrophoderma of the cheeks, and multiple BCC, which manifest in the late second decade to early third decade.[101] Documented hair changes with Bazex-Dupr-Christol syndrome include reduced density of scalp and body hair, decreased melanization,[106] a twisted/flattened appearance of the hair shaft on electron microscopy,[107] and increased hair shaft diameter on polarizing light microscopy.[103] The milia, which may be quite distinctive in childhood, have been reported to regress or diminish substantially at puberty.[103] Other reported findings in association with this syndrome include trichoepitheliomas; hidradenitis suppurativa; hypoplastic alae; and a prominent columella, the fleshy terminal portion of the nasal septum.[108,109]

A rare subtype of epidermolysis bullosa simplex (EBS), Dowling-Meara (EBS-DM), is primarily inherited in an autosomal dominant fashion and is associated with mutations in either keratin-5 (KRT5) or keratin-14 (KRT14).[110] EBS-DM is one of the most severe types of EBS and occasionally results in mortality in early childhood.[111] One report cites an incidence of BCC of 44% by age 55 years in this population.[112] Individuals who inherit two EBS mutations may present with a more severe phenotype.[113] Other less phenotypically severe subtypes of EBS can also be caused by mutations in either KRT5 or KRT14.[110] Approximately 75% of individuals with a clinical diagnosis of EBS (regardless of subtype) have KRT5 or KRT14 mutations.[114]

Characteristics of hereditary syndromes associated with a predisposition to BCC are described in Table 3 below.

(Refer to the Brooke-Spiegler Syndrome, Multiple Familial Trichoepithelioma, and Familial Cylindromatosis section in the Rare Skin Cancer Syndromes section of this summary for more information about Brooke-Spiegler syndrome.)

As detailed further below, the U.S. Preventive Services Task Force does not recommend regular screening for the early detection of any cutaneous malignancies, including BCC. However, once BCC is detected, the National Comprehensive Cancer Network guidelines of care for NMSCs recommends complete skin examinations every 6 to 12 months for life.[125]

The BCNS Colloquium Group has proposed guidelines for the surveillance of individuals with BCNS (see Table 4).

Level of evidence: 5

Avoidance of excessive cumulative and sporadic sun exposure is important in reducing the risk of BCC, along with other cutaneous malignancies. Scheduling activities outside of the peak hours of UV radiation, utilizing sun-protective clothing and hats, using sunscreen liberally, and strictly avoiding tanning beds are all reasonable steps towards minimizing future risk of skin cancer.[126] For patients with particular genetic susceptibility (such as BCNS), avoidance or minimization of ionizing radiation is essential to reducing future tumor burden.

Level of evidence: 2aii

The role of various systemic retinoids, including isotretinoin and acitretin, has been explored in the chemoprevention and treatment of multiple BCCs, particularly in BCNS patients. In one study of isotretinoin use in 12 patients with multiple BCCs, including 5 patients with BCNS, tumor regression was noted, with decreasing efficacy as the tumor diameter increased.[127] However, the results were insufficient to recommend use of systemic retinoids for treatment of BCC. Three additional patients, including one with BCNS, were followed long-term for evaluation of chemoprevention with isotretinoin, demonstrating significant decrease in the number of tumors per year during treatment.[127] Although the rate of tumor development tends to increase sharply upon discontinuation of systemic retinoid therapy, in some patients the rate remains lower than their pretreatment rate, allowing better management and control of their cutaneous malignancies.[127-129] In summary, the use of systemic retinoids for chemoprevention of BCC is reasonable in high-risk patients, including patients with xeroderma pigmentosum, as discussed in the Squamous Cell Carcinoma section of this summary.

A patients cumulative and evolving tumor load should be evaluated carefully in light of the potential long-term use of a medication class with cumulative and idiosyncratic side effects. Given the possible side-effect profile, systemic retinoid use is best managed by a practitioner with particular expertise and comfort with the medication class. However, for all potentially childbearing women, strict avoidance of pregnancy during the systemic retinoid courseand for 1 month after completion of isotretinoin and 3 years after completion of acitretinis essential to avoid potentially fatal and devastating fetal malformations.

Level of evidence (retinoids): 2aii

In a phase II study of 41 patients with BCNS, vismodegib (an inhibitor of the hedgehog pathway) has been shown to reduce the per-patient annual rate of new BCCs requiring surgery.[130] Existing BCCs also regressed for these patients during daily treatment with 150 mg of oral vismodegib. While patients treated had visible regression of their tumors, biopsy demonstrated residual microscopic malignancies at the site, and tumors progressed after the discontinuation of the therapy. Adverse effects included taste disturbance, muscle cramps, hair loss, and weight loss and led to discontinuation of the medication in 54% of subjects. Based on the side-effect profile and rate of disease recurrence after discontinuation of the medication, additional study regarding optimal dosing of vismodegib is ongoing.

Level of evidence (vismodegib): 1aii

A phase III, double-blind, placebo-controlled clinical trial evaluated the effects of oral nicotinamide (vitamin B3) in 386 individuals with a history of at least two NMSCs within 5 years before study enrollment.[131] After 12 months of treatment, those taking nicotinamide 500 mg twice daily had a 20% reduction in the incidence of new BCCs (95% CI, 6%39%; P = .12). The rate of new NMSCs was 23% lower in the nicotinamide group (95% CI, 438; P =.02) than in the placebo group. No clinically significant differences in adverse events were observed between the two groups, and there was no evidence of benefit after discontinuation of nicotinamide. Of note, this study was not conducted in a population with an identified genetic predisposition to BCC.

Level of evidence (nicotinamide): 1aii

Treatment of individual BCCs in BCNS is generally the same as for sporadic basal cell cancers. Due to the large number of lesions on some patients, this can present a surgical challenge. Field therapy with imiquimod or photodynamic therapy are attractive options, as they can treat multiple tumors simultaneously.[132,133] However, given the radiosensitivity of patients with BCNS, radiation as a therapeutic option for large tumors should be avoided.[45] There are no randomized trials, but the isolated case reports suggest that field therapy has similar results as in sporadic basal cell cancer, with higher success rates for superficial cancers than for nodular cancers.[132,133]

Consensus guidelines for the use of methylaminolevulinate photodynamic therapy in BCNS recommend that this modality may best be used for superficial BCC of all sizes and for nodular BCC less than 2 mm thick.[134] Monthly therapy with photodynamic therapy may be considered for these patients as clinically indicated.

Level of evidence (imiquimod and photodynamic therapy): 4

Topical treatment with LDE225, a Smoothened agonist, has also been investigated for the treatment of BCC in a small number of patients with BCNS with promising results;[135] however, this medication is not approved in this formulation by the U.S. Food and Drug Administration.

Level of evidence (LDE225): 1

In addition to its effects on the prevention of BCCs in patients with BCNS, vismodegib may also have a palliative effect on KCOTs found in this population. An initial report indicated that the use of GDC-0449, the hedgehog pathway inhibitor now known as vismodegib, resulted in resolution of KCOTs in one patient with BCNS.[136] Another small study found that four of six patients who took 150 mg of vismodegib daily had a reduction in the size of KCOTs.[137] None of the six patients in this study had new KCOTs or an increase in the size of existing KCOTs while being treated, and one patient had a sustained response that lasted 9 months after treatment was discontinued.

Level of evidence (vismodegib): 3diii

Squamous cell carcinoma (SCC) is the second most common type of skin cancer and accounts for approximately 20% of cutaneous malignancies. Although most cancer registries do not include information on the incidence of nonmelanoma skin cancer (NMSC), annual incidence estimates range from 1 million to 5.4 million cases in the United States.[1,2]

Mortality is rare from this cancer; however, the morbidity and costs associated with its treatment are considerable.

Sun exposure is the major known environmental factor associated with the development of skin cancer of all types; however, different patterns of sun exposure are associated with each major type of skin cancer.

Unlike basal cell carcinoma (BCC), SCC is associated with chronic exposure, rather than intermittent intense exposure to ultraviolet (UV) radiation. Occupational exposure is the characteristic pattern of sun exposure linked with SCC.[3] A case-control study in southern Europe showed increased risk of SCC when lifetime sun exposure exceeded 70,000 hours. People whose lifetime sun exposure equaled or exceeded 200,000 hours had an odds ratio (OR) 8 to 9 times that of the reference group.[4] A Canadian case-control study did not find an association between cumulative lifetime sun exposure and SCC; however, sun exposure in the 10 years before diagnosis and occupational exposure were found to be risk factors.[5]

In addition to environmental radiation, exposure to therapeutic radiation is another risk factor for SCC. Individuals with skin disorders treated with psoralen and ultraviolet-A radiation (PUVA) had a threefold to sixfold increase in SCC.[6] This effect appears to be dose-dependent, as only 7% of individuals who underwent fewer than 200 treatments had SCC, compared with more than 50% of those who underwent more than 400 treatments.[7] Therapeutic use of ultraviolet-B (UVB) radiation has also been shown to cause a mild increase in SCC (adjusted incidence rate ratio, 1.37).[8] Devices such as tanning beds also emit UV radiation and have been associated with increased SCC risk, with a reported OR of 2.5 (95% confidence interval [CI], 1.73.8).[9]

Investigation into the effect of ionizing radiation on SCC carcinogenesis has yielded conflicting results. One population-based case-control study found that patients who had undergone therapeutic radiation therapy had an increased risk of SCC at the site of previous radiation (OR, 2.94), compared with individuals who had not undergone radiation treatments.[10] Cohort studies of radiology technicians, atomic-bomb survivors, and survivors of childhood cancers have not shown an increased risk of SCC, although the incidence of BCC was increased in all of these populations.[11-13] For those who develop SCC at previously radiated sites that are not sun-exposed, the latent period appears to be quite long; these cancers may be diagnosed years or even decades after the radiation exposure.[14]

The effect of other types of radiation, such as cosmic radiation, is also controversial. Pilots and flight attendants have a reported incidence of SCC that ranges between 2.1 and 9.9 times what would be expected; however, the overall cancer incidence is not consistently elevated. Some attribute the high rate of NMSCs in airline flight personnel to cosmic radiation, while others suspect lifestyle factors.[15-20]

Like BCCs, SCCs appear to be associated with exposure to arsenic in drinking water and combustion products.[21,22] However, this association may hold true only for the highest levels of arsenic exposure. Individuals who had toenail concentrations of arsenic above the 97th percentile were found to have an approximately twofold increase in SCC risk.[23] For arsenic, the latency period can be lengthy; invasive SCC has been found to develop at an average of 20 years after exposure.[24]

Current or previous cigarette smoking has been associated with a 1.5-fold to 2-fold increase in SCC risk,[25-27] although one large study showed no change in risk.[28] Available evidence suggests that the effect of smoking on cancer risk seems to be greater for SCC than for BCC.

Additional reports have suggested weak associations between SCC and exposure to insecticides, herbicides, or fungicides.[29]

Like melanoma and BCC, SCC occurs more frequently in individuals with lighter skin than in those with darker skin.[3,30] A case-control study of 415 cases and 415 controls showed similar findings; relative to Fitzpatrick Type I skin, individuals with increasingly darker skin had decreased risks of skin cancer (ORs, 0.6, 0.3, and 0.1, for Fitzpatrick Types II, III, and IV, respectively).[31] (Refer to the Pigmentary characteristics section in the Melanoma section of this summary for a more detailed discussion of skin phenotypes based upon pigmentation.) The same study found that blue eyes and blond/red hair were also associated with increased risks of SCC, with crude ORs of 1.7 (95% CI, 1.22.3) for blue eyes, 1.5 (95% CI, 1.12.1) for blond hair, and 2.2 (95% CI, 1.53.3) for red hair.

However, SCC can also occur in individuals with darker skin. An Asian registry based in Singapore reported an increase in skin cancer in that geographic area, with an incidence rate of 8.9 per 100,000 person-years. Incidence of SCC, however, was shown to be on the decline.[30] SCC is the most common form of skin cancer in black individuals in the United States and in certain parts of Africa; the mortality rate for this disease is relatively high in these populations.[32,33] Epidemiologic characteristics of, and prevention strategies for, SCC in those individuals with darker skin remain areas of investigation.

Freckling of the skin and reaction of the skin to sun exposure have been identified as other risk factors for SCC.[34] Individuals with heavy freckling on the forearm were found to have a 14-fold increase in SCC risk if freckling was present in adulthood, and an almost threefold risk if freckling was present in childhood.[34,35] The degree of SCC risk corresponded to the amount of freckling. In this study, the inability of the skin to tan and its propensity to burn were also significantly associated with risk of SCC (OR of 2.9 for severe burn and 3.5 for no tan).

The presence of scars on the skin can also increase the risk of SCC, although the process of carcinogenesis in this setting may take years or even decades. SCCs arising in chronic wounds are referred to as Marjolins ulcers. The mean time for development of carcinoma in these wounds is estimated at 26 years.[36] One case report documents the occurrence of cancer in a wound that was incurred 59 years earlier.[37]

Immunosuppression also contributes to the formation of NMSCs. Among solid-organ transplant recipients, the risk of SCC is 65 to 250 times higher, and the risk of BCC is 10 times higher than that observed in the general population, although the risks vary with transplant type.[38-41] NMSCs in high-risk patients (solid-organ transplant recipients and chronic lymphocytic leukemia patients) occur at a younger age, are more common and more aggressive, and have a higher risk of recurrence and metastatic spread than these cancers do in the general population.[42,43] Additionally, there is a high risk of second SCCs.[44,45] In one study, over 65% of kidney transplant recipients developed subsequent SCCs after their first diagnosis.[44] Among patients with an intact immune system, BCCs outnumber SCCs by a 4:1 ratio; in transplant patients, SCCs outnumber BCCs by a 2:1 ratio.

This increased risk has been linked to an interaction between the level of immunosuppression and UV radiation exposure. As the duration and dosage of immunosuppressive agents increase, so does the risk of cutaneous malignancy; this effect is reversed with decreasing the dosage of, or taking a break from, immunosuppressive agents. Heart transplant recipients, requiring the highest rates of immunosuppression, are at much higher risk of cutaneous malignancy than liver transplant recipients, in whom much lower levels of immunosuppression are needed to avoid rejection.[38,46,47] The risk appears to be highest in geographic areas with high UV exposure.[47] When comparing Australian and Dutch organ transplant populations, the Australian patients carried a fourfold increased risk of developing SCC and a fivefold increased risk of developing BCC.[48] This finding underlines the importance of rigorous sun avoidance, particularly among high-risk immunosuppressed individuals.

Certain immunosuppressive agents have been associated with increased risk of SCC. Kidney transplant patients who received cyclosporine in addition to azathioprine and prednisolone had a 2.8-fold increase in risk of SCC over those kidney transplant patients on azathioprine and prednisolone alone.[38] In cardiac transplant patients, increased incidence of SCC was seen in individuals who had received OKT3 (muromonab-CD3), a murine monoclonal antibody against the CD3 receptor.[49]

A personal history of BCC or SCC is strongly associated with subsequent SCC. A study from Ireland showed that individuals with a history of BCC had a 14% higher incidence of subsequent SCC; for men with a history of BCC, the subsequent SCC risk was 27% higher.[50] In the same report, individuals with melanoma were also 2.5 times more likely to report a subsequent SCC. There is an approximate 20% increased risk of a subsequent lesion within the first year after a skin cancer has been diagnosed. The mean age of occurrence for these NMSCs is the middle of the sixth decade of life.[26,51-55]

A Swedish study of 224 melanoma index cases and 944 of their first-degree relatives (FDRs) from 154 CDKN2A wild-type families and 11,680 matched controls showed that personal and family histories of melanoma increased the risk of SCC, with relative risks (RRs) of 9.1 (95% CI, 6.013.7) for personal history and 3.4 (95% CI, 2.25.2) for family history.[56]

Although the literature is scant on this subject, a family history of SCC may increase the risk of SCC in FDRs. In an independent survey-based study of 415 SCC cases and 415 controls, SCC risk was increased in individuals with a family history of SCC (adjusted OR, 3.4; 95% CI, 1.011.6), even after adjustment for skin type, hair color, and eye color.[31] This risk was elevated to an OR of 5.6 in those with a family history of melanoma (95% CI, 1.619.7), 9.8 in those with a family history of BCC (95% CI, 2.636.8), and 10.5 in those with a family history of multiple types of skin cancer (95% CI, 2.729.6). Review of the Swedish Family Center Database showed that individuals with at least one sibling or parent affected with SCC, in situ SCC (Bowen disease), or actinic keratosis had a twofold to threefold increased risk of invasive and in situ SCC relative to the general population.[57,58] Increased number of tumors in parents was associated with increased risk to the offspring. Of note, diagnosis of the proband at an earlier age was not consistently associated with a trend of increased incidence of SCC in the FDR, as would be expected in most hereditary syndromes because of germline mutations. Further analysis of the Swedish population-based data estimates genetic risk effects of 8% and familial shared-environmental effects of 18%.[59] Thus, shared environmental and behavioral factors likely account for some of the observed familial clustering of SCC.

A study on the heritability of cancer among 80,309 monozygotic and 123,382 dizygotic twins showed that NMSCs have a heritability of 43% (95% CI, 26%59%), suggesting that almost half of the risk of NMSC is caused by inherited factors.[60] Additionally, the cumulative risk of NMSC was 1.9-fold higher for monozygotic than for dizygotic twins (95% CI, 1.82.0).[60]

Major genes have been defined elsewhere in this summary as genes that are necessary and sufficient for disease, with important mutations of the gene as causal. The disorders resulting from single-gene mutations within families lead to a very high risk of disease and are relatively rare. The influence of the environment on the development of disease in individuals with these single-gene disorders is often very difficult to determine because of the rarity of the genetic mutation.

Identification of a strong environmental risk factorchronic exposure to UV radiationmakes it difficult to apply genetic causation for SCC of the skin. Although the risk of UV exposure is well known, quantifying its attributable risk to cancer development has proven challenging. In addition, ascertainment of cases of SCC of the skin is not always straightforward. Many registries and other epidemiologic studies do not fully assess the incidence of SCC of the skin owing to: (1) the common practice of treating lesions suspicious for SCC without a diagnostic biopsy, and (2) the relatively low potential for metastasis. Moreover, NMSC is routinely excluded from the major cancer registries such as the Surveillance, Epidemiology, and End Results registry.

With these considerations in mind, the discussion below will address genes associated with disorders that have an increased incidence of skin cancer.

Characteristics of the major hereditary syndromes associated with a predisposition to SCC are described in Table 5 below.

Xeroderma pigmentosum (XP) is a hereditary disorder of nucleotide excision repair that results in cutaneous malignancies in the first decade of life. Affected individuals have an increased sensitivity to sunlight, resulting in a markedly increased risk of SCCs, BCCs, and melanomas. One report found that NMSC was increased 150-fold in individuals with XP; for those younger than 20 years, the prevalence was almost 5,000 times what would be expected in the general population.[61]

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