DNA damage can cause an error when the DNA is replicated, and this error of replication can cause a gene mutation that, in turn, could cause a genetic disorder. DNA damages are repaired by the DNA repair system of the cell. Each cell has a number of pathways through which enzymes recognize and repair damages in DNA. Because DNA can be damaged in many ways, the process of DNA repair is an important way in which the body protects itself from disease. Once DNA damage has given rise to a mutation, the mutation cannot be repaired.


On the other hand, a mutation may occur in a somatic cell of an organism. Such mutations will be present in all descendants of this cell within the same organism. The accumulation of certain mutations over generations of somatic cells is part of cause of  malignant transformation , from normal cell to cancer cell. [ 112 ]


Cells with heterozygous loss-of-function mutations (one good copy of gene and one mutated copy) may function normally with the unmutated copy until the good copy has been spontaneously somatically mutated. This kind of mutation happens often in living organisms, but it is difficult to measure the rate. Measuring this rate is important in predicting the rate at which people may develop cancer. [ 113 ]


Point mutations may arise from spontaneous mutations that occur during DNA replication. The rate of mutation may be increased by mutagens. Mutagens can be physical, such as radiation from  UV rays ,  X-rays  or extreme heat, or chemical (molecules that misplace base pairs or disrupt the helical shape of DNA). Mutagens associated with cancers are often studied to learn about cancer and its prevention.


Although mutations that cause changes in protein sequences can be harmful to an organism, on occasions the effect may be positive in a given environment. In this case, the mutation may enable the mutant organism to withstand particular environmental stresses better than wild-type organisms, or reproduce more quickly. In these cases a mutation will tend to become more common in a population through natural selection. That said, the same mutation can be beneficial in one condition and disadvantageous in another condition. Examples include the following:


HIV resistance : a specific 32 base pair deletion in human  CCR5  ( CCR5-Δ32 ) confers  HIV  resistance to  homozygotes  and delays  AIDS  onset in heterozygotes. [ 114 ]  One possible explanation of the  etiology  of the relatively high frequency of CCR5-Δ32 in the  European  population is that it conferred resistance to the  bubonic plague  in mid-14th century  Europe . People with this mutation were more likely to survive infection; thus its frequency in the population increased. [ 115 ]  This theory could explain why this mutation is not found in  Southern Africa , which remained untouched by bubonic plague. A newer theory suggests that the  selective pressure  on the CCR5 Delta 32 mutation was caused by  smallpox  instead of the bubonic plague. [ 116 ]


Malaria resistance : An example of a harmful mutation is  sickle-cell disease , a blood disorder in which the body produces an abnormal type of the oxygen-carrying substance  haemoglobin  in the  red blood cells . One-third of all  indigenous  inhabitants of  Sub-Saharan Africa  carry the allele, because, in areas where  malaria  is common, there is a  survival value  in carrying only a single sickle-cell allele ( sickle cell trait ). [ 117 ]  Those with only one of the two alleles of the sickle-cell disease are more resistant to malaria, since the infestation of the malaria  Plasmodium  is halted by the sickling of the cells that it infests.


Antibiotic resistance : Practically all bacteria develop antibiotic resistance when exposed to antibiotics. In fact, bacterial populations already have such mutations that get selected under antibiotic selection. [ 118 ]  Obviously, such mutations are only beneficial for the bacteria but not for those infected.


Lactase persistence . A mutation allowed humans to express the enzyme  lactase  after they are naturally weaned from breast milk, allowing adults to digest  lactose , which is likely one of the most beneficial mutations in recent  human evolution . [ 119 ]


By introducing novel genetic qualities to a population of organisms, de novo mutations play a critical role in the combined forces of evolutionary change. However, the weight of genetic diversity generated by mutational change is often considered a generally "weak" evolutionary force. [ 103 ]  Although the random emergence of mutations alone provides the basis for genetic variation across all organic life, this force must be taken in consideration alongside all evolutionary forces at play. Spontaneous de novo mutations as cataclysmic events of speciation depend on factors introduced by  natural selection , genetic flow, and  genetic drift . For example, smaller populations with heavy mutational input (high rates of mutation) are prone to increases of genetic variation which lead to speciation in future generations. In contrast, larger populations tend to see lesser effects of newly introduced mutated traits. In these conditions, selective forces diminish the frequency of mutated alleles, which are most often deleterious, over time. [ 120 ]


Compensated pathogenic deviations refer to amino acid residues in a protein sequence that are pathogenic in one species but are wild type residues in the functionally equivalent protein in another species. Although the amino acid residue is pathogenic in the first species, it is not so in the second species because its pathogenicity is compensated by one or more amino acid substitutions in the second species. The compensatory mutation can occur in the same protein or in another protein with which it interacts. [ 121 ]


It is critical to understand the effects of compensatory mutations in the context of fixed deleterious mutations due to the population fitness decreasing because of fixation. [ 122 ]  Effective population size refers to a population that is reproducing. [ 123 ]  An increase in this population size has been correlated with a decreased rate of genetic diversity. [ 123 ]  The position of a population relative to the critical effect population size is essential to determine the effect deleterious alleles will have on fitness. [ 122 ]  If the population is below the critical effective size fitness will decrease drastically, however if the population is above the critical effect size, fitness can increase regardless of deleterious mutations due to compensatory alleles. [ 122 ]


As the function of a RNA molecule is dependent on its structure, [ 124 ]  the structure of RNA molecules is evolutionarily conserved. Therefore, any mutation that alters the stable structure of RNA molecules must be compensated by other compensatory mutations. In the context of RNA, the sequence of the RNA can be considered as ' genotype' and the structure of the RNA can be considered as its 'phenotype'. Since RNAs have relatively simpler composition than proteins, the structure of RNA molecules can be computationally predicted with high degree of accuracy. Because of this convenience, compensatory mutations have been studied in computational simulations using RNA folding algorithms. [ 125 ] [ 126 ]


Compensatory mutations can be explained by the genetic phenomenon epistasis whereby the phenotypic effect of one mutation is dependent upon mutation(s) at other loci. While epistasis was originally conceived in the context of interaction between different genes, intragenic epistasis has also been studied recently. [ 127 ]  Existence of compensated pathogenic deviations can be explained by 'sign epistasis', in which the effects of a deleterious mutation can be compensated by the presence of an epistatic mutation in another loci. For a given protein, a deleterious mutation (D) and a compensatory mutation (C) can be considered, where C can be in the same protein as D or in a different interacting protein depending on the context. The fitness effect of C itself could be neutral or somewhat deleterious such that it can still exist in the population, and the effect of D is deleterious to the extent that it cannot exist in the population. However, when C and D co-occur together, the combined fitness effect becomes neutral or positive. [ 121 ]  Thus, compensatory mutations can bring novelty to proteins by forging new pathways of protein evolution : it allows individuals to travel from one fitness peak to another through the valleys of lower fitness. [ 127 ]


DePristo et al. 2005 outlined two models to explain the dynamics of compensatory pathogenic deviations (CPD). [ 128 ]  In the first hypothesis P is a pathogenic amino acid mutation that and C is a neutral compensatory mutation. [ 128 ]  Under these conditions, if the pathogenic mutation arises after a compensatory mutation, then P can become fixed in the population. [ 128 ]  The second model of CPDs states that P and C are both deleterious mutations resulting in fitness valleys when mutations occur simultaneously. [ 128 ]  Using publicly available, Ferrer-Costa et al. 2007 obtained compensatory mutations and human pathogenic mutation datasets that were characterized to determine what causes CPDs. [ 129 ]  Results indicate that the structural constraints and the location in protein structure determine whether compensated mutations will occur. [ 129 ]


Lunzer et al. [ 130 ]  tested the outcome of swapping divergent amino acids between two orthologous proteins of isopropymalate dehydrogenase (IMDH). They substituted 168 amino acids in  Escherichia coli  IMDH that are wild type residues in IMDH  Pseudomonas aeruginosa . They found that over one third of these substitutions compromised IMDH enzymatic activity in the  Escherichia coli  genetic background. This demonstrated that identical amino acid states can result in different phenotypic states depending on the genetic background. Corrigan et al. 2011 demonstrated how  Staphylococcus aureus  was able to grow normally without the presence of lipoteichoic acid due to compensatory mutations. [ 131 ]  Whole genome sequencing results revealed that when Cyclic-di-AMP phosphodiesterase (GdpP) was disrupted in this bacterium, it compensated for the disappearance of the cell wall polymer, resulting in normal cell growth. [ 131 ]


Research has shown that bacteria can gain drug resistance through compensatory mutations that do not impede or having little effect on fitness. [ 132 ]  Previous research from Gagneux et al. 2006 has found that laboratory grown  Mycobacterium tuberculosis  strains with rifampicin resistance have reduced fitness, however drug resistant clinical strains of this pathogenic bacteria do not have reduced fitness. [ 133 ]  Comas et al. 2012 used whole genome comparisons between clinical strains and lab derived mutants to determine the role and contribution of compensatory mutations in drug resistance to rifampicin. [ 132 ]  Genome analysis reveal rifampicin resistant strains have a mutation in rpoA and rpoC. [ 132 ]  A similar study investigated the bacterial fitness associated with compensatory mutations in rifampin resistant  Escherichia coli . [ 134 ]  Results obtained from this study demonstrate that drug resistance is linked to bacterial fitness as higher fitness costs are linked to greater transcription errors. [ 134 ]


Gong et al. [ 135 ]  collected obtained genotype data of influenza nucleoprotein from different timelines and temporally ordered them according to their time of origin. Then they isolated 39 amino acid substitutions that occurred in different timelines and substituted them in a genetic background that approximated the ancestral genotype. They found that 3 of the 39 substitutions significantly reduced the fitness of the ancestral background. Compensatory mutations are new mutations that arise and have a positive or neutral impact on a populations fitness. [ 136 ]  Previous research has shown that populations have can compensate detrimental mutations. [ 121 ] [ 136 ] [ 137 ]  Burch and Chao tested  Fisher's geometric model  of adaptive evolution by testing whether bacteriophage φ6 evolves by small steps. [ 138 ]  Their results showed that  bacteriophage  φ6 fitness declined rapidly and recovered in small steps . [ 138 ]  Viral nucleoproteins have been shown to avoid cytotoxic T lymphocytes (CTLs) through arginine-to glycine substitutions. [ 139 ]  This substitution mutations impacts the fitness of viral nucleoproteins, however compensatory co-mutations impede fitness declines and aid the virus to avoid recognition from CTLs. [ 139 ]  Mutations can have three different effects; mutations can have deleterious effects, some increase fitness through compensatory mutations, and lastly mutations can be counterbalancing resulting in compensatory neutral mutations. [ 140 ] [ 134 ] [ 133 ]


In the human genome, the frequency and characteristics of de novo mutations have been studied as important contextual factors to our evolution. Compared to the human reference genome, a typical human genome varies at approximately 4.1 to 5.0 million loci, and the majority of this genetic diversity is shared by nearly 0.5% of the population. [ 141 ]  The typical human genome also contains 40,000 to 200,000 rare variants observed in less than 0.5% of the population that can only have occurred from at least one de novo germline mutation in the history of human evolution. [ 142 ]  De novo mutations have also been researched as playing a crucial role in the persistence of genetic disease in humans. With recents advancements in  next-generation sequencing  (NGS), all types of de novo mutations within the genome can be directly studied, the detection of which provides a magnitude of insight toward the causes of both rare and common genetic disorders. Currently, the best estimate of the average human germline SNV mutation rate is 1.18 x 10^-8, with an approximate ~78 novel mutations per generation. The ability to conduct whole genome sequencing of parents and offspring allows for the comparison of mutation rates between generations, narrowing down the origin possibilities of certain genetic disorders. [ 143 ]


Hermann J. Muller  (1890–1967), who was a 1946 Nobel Prize winner, coined the terms  amorph, hypomorph, hypermorph, antimorph  and  neomorph  to classify mutations based on their behaviour in various  genetic  situations, as well as  gene interaction  between themselves. [ 1 ]  These classifications are still widely used in  Drosophila  genetics to describe mutations. For a more general description of mutations, see  mutation , and for a discussion of  allele  interactions, see  dominance relationship .


Key: In the following sections, alleles are referred to as +=wildtype, m=mutant, Df=gene deletion, Dp=gene duplication. Phenotypes are compared with '>', meaning 'phenotype is more severe than'


Amorphic  describes a mutation that causes complete loss of  gene  function. [ 1 ]  Amorph is sometimes used interchangeably with "genetic  null ". An amorphic mutation might cause complete loss of protein function by disrupting translation ("protein null") and/or preventing transcription ("RNA null").


An amorphic allele elicits the same phenotype when  homozygous  and when  heterozygous  to a  chromosomal deletion  or deficiency that disrupts the same gene. [ 2 ]  This relationship can be represented as follows:


m/m = m/Df


An amorphic allele is commonly  recessive  to its wildtype counterpart. It is possible for an amorph to be  dominant  if the gene in question is required in two copies to elicit a normal phenotype (i.e.  haploinsufficient ).


Hypomorphic  describes a mutation that causes a partial loss of  gene  function. [ 1 ]  A hypomorph is a reduction in gene function through reduced (protein, RNA) expression or reduced functional performance, but not a complete loss.


The phenotype of a hypomorph is more severe in  trans  to a deletion allele than when homozygous. [ 2 ]


m/DF > m/m


Hypomorphs are usually recessive, but occasional alleles are dominant due to  haploinsufficiency .


A  hypermorphic  mutation causes an increase in normal  gene  function. [ 1 ]  Hypermorphic alleles are gain of function alleles. A hypermorph can result from an increase in gene dose (a gene duplication), from increased  mRNA  or  protein  expression, or constitutive protein activity.


The phenotype of a hypermorph is worsened by increasing the wildtype gene dose, and is reduced by lowering wildtype gene dose. [ 2 ]


m/Dp > m/+ > m/Df


Antimorph s are  dominant  mutations that act in opposition to normal  gene  activity. [ 1 ]  Antimorphs are also called  dominant negative  mutations.


Increasing wildtype gene function reduces the phenotypic severity of an antimorph, so the phenotype of an antimorph is worse when heterozygous than when in  trans  to a  gene duplication . [ 2 ]


m/m > m/Df > m/+ >>> +/Df > +/+  [ 3 ]


An antimorphic mutation might affect the function of a protein that acts as a  dimer  so that a dimer consisting of one normal and one mutated protein is no longer functional.


A  neomorphic  mutation causes a dominant gain of  gene  function that is different from the normal function. [ 1 ]  A neomorphic mutation can cause ectopic  mRNA  or  protein  expression, or new protein functions from altered protein structure.


Changing wildtype gene dose has no effect on the phenotype of a neomorph. [ 2 ]


m/Df = m/+ = m/Dp


After Muller's classification of  gene mutation , an  isomorph  was described as a  silent   point mutant  with identical  gene expression  as the original  allele . [ 4 ] [ 5 ]


m/Df = m/Dp


Therefore, with respect to the relationship between the original and mutated genes, one cannot talk about the effects of  dominance  and/or  recessiveness . [ 4 ] [ 5 ] [ 6 ]


Somatic recombination , as opposed to the  genetic recombination  that occurs in  meiosis , is an alteration of the DNA of a  somatic cell  that is inherited by its daughter cells. The term is usually reserved for large-scale alterations of DNA such as  chromosomal translocations  and  deletions  and not applied to  point mutations . Somatic recombination occurs physiologically in the assembly of the  B cell receptor  and  T-cell receptor  genes ( V(D)J recombination ), [ 1 ]  as well as in the  class switching  of  immunoglobulins . [ 2 ]  Somatic recombination is also important in the process of  carcinogenesis . [ 3 ]


In neurons of the human  brain , somatic recombination occurs in the gene that encodes the  amyloid precursor protein  APP. [ 4 ]   Neurons  from individuals with sporadic  Alzheimer's disease  show greater APP gene diversity due to somatic recombination than neurons from healthy individuals. [ 4 ]


Intrachromosomal  homologous recombination  in  Arabidopsis thaliana  plants was found to occur in all organs examined from the seed stage to the flowering stage of somatic plant development. [ 5 ]   Recombination frequencies were typically in the range of 10 −6   to 10 −7  events per  genome . [ 5 ]   A. thaliana   mutants  selected for hypersensitivity to  X-irradiation  also proved to be simultaneously hypersensitive to the DNA damaging agents  mitomycin C  and/or  methyl methanesulfonate . [ 6 ]   The mutants were also deficient in somatic homologous recombination. [ 6 ]   These findings suggest that repair of some types of  DNA damage  requires a recombinational process that was defective in the mutants studied.  In nature, plants are continuously exposed to  UV-B  (280–320 nm) radiation, a component of sunlight that damages the DNA of somatic cells. [ 7 ]   Cyclobutane  pyrimidine dimers  (CPD) are a type of damage induced by UV-B.  In  A. thaliana , homologous recombination appears to be directly involved in repairing CPD damage. [ 7 ]


A  suppressor mutation  is a second  mutation  that alleviates or reverts the  phenotypic  effects of an already existing mutation in a process defined  synthetic rescue .  Genetic suppression therefore restores the phenotype seen prior to the original background mutation. [ 1 ]   Suppressor mutations are useful for identifying new genetic sites which affect a biological process of interest.  They also provide evidence between functionally interacting molecules and intersecting  biological pathways . [ 2 ]


Intragenic suppression  results from suppressor mutations that occur in the same  gene  as the original mutation.  In a classic study,  Francis Crick  (et al.) used intragenic suppression to study the fundamental nature of the  genetic code .  From this study it was shown that genes are expressed as non-overlapping  triplets ( codons ). [ 1 ]


Researchers showed that mutations caused by either a single  base insertion  (+) or a single  base deletion  (-) could be "suppressed" or restored by a second mutation of the opposite sign, as long as the two mutations occurred in the same vicinity of the gene.  This led to the conclusion that genes needed to be read in a specific " reading frame " and a single base insertion or deletion would shift the reading frame ( frameshift mutation ) in such a way that the remaining DNA would code for a different polypeptide than the one intended.  Therefore, researchers concluded that the second mutation of opposite sign suppresses the original mutation by restoring the reading frame, as long as the portion between the two mutations is not critical for protein function. [ 1 ]


In addition to the reading frame, Crick also used suppressor mutations to determine codon size.  It was found that while one and two base insertions/deletions of the same sign resulted in a mutant phenotype, deleting or inserting three bases could give a  wild type  phenotype.  From these results it was concluded that an inserted or deleted triplet does not disturb the reading frame and the genetic code is in fact a triplet. [ 1 ]


Intergenic  (also known as  extragenic )  suppression  relieves the effects of a mutation in one gene by a mutation somewhere else within the  genome . The second mutation is not on the same gene as the original mutation. [ 2 ]   Intergenic suppression is useful for identifying and studying interactions between molecules, such as  proteins .  For example, a mutation which disrupts the complementary interaction between protein molecules may be compensated for by a second mutation elsewhere in the genome that restores or provides a suitable alternative interaction between those molecules.  Several proteins of biochemical,  signal transduction , and  gene expression  pathways have been identified using this approach.  Examples of such pathways include  receptor-ligand  interactions as well as the interaction of components involved in  DNA replication ,  transcription , and  translation . [ 1 ]


These Intergenic suppressions are also likely to persist in the population. When these compensatory mutations are established in organisms like E. coli making it resistant to the drug due to the presence of a drug, and the drug usage is halted, the resistant strains are not easily able to evolve back into strains that can then once again be sensitive to the drug they had incurred resistance to. [ 3 ]  These strains are likely not subject to losing these compensatory mutations and which would greatly decrease the fitness in the strain resulting in the intermediate strains. These intermediate strains are subjected to bottlenecking and thus making it difficult for the alleles to be reverted prior to Intergenic suppressions. Consequently, when drugs are halted it can be seen that these mutations are likely to persist in the population.


Suppressor mutations also occur in genes that code for virus structural proteins.  To create a viable  phage T4 virus  (see image), a balance of structural components is required.  An amber mutant of phage T4 contains a mutation that changes a codon for an amino acid in a protein to the nonsense stop codon TAG (see  stop codon  and  nonsense mutation ).  If, upon infection, an amber mutant defective in a gene encoding a needed structural component of phage T4 is weakly suppressed (in an  E. coli  host containing a specific altered  tRNA  – see  nonsense suppressor ), it will produce a reduced number of the needed structural component.  As a consequence few if any viable phage are formed.  However, it was found that viable phage could sometimes be produced in the host with the weak nonsense suppressor if a second amber mutation in a gene that encodes another structural protein is also present in the phage genome. [ 4 ]   It was found that the reason the second amber mutation could suppress the first one is that the two numerically reduced structural proteins would now be in balance.  For instance, if the first amber mutation caused a reduction of tail fibers to one tenth the normal level, most phage particles produced would have insufficient tail fibers to be infective.  However, if a second amber mutation is defective in a base plate component and causes one tenth the number of base plates to be made, this may restore the balance of tail fibers and base plates, and thus allow infective phage to be produced. [ 4 ]


In  microbial genetics , a  revertant  is a  mutant  that has reverted to its former  genotype  or to the original  phenotype  by means of a suppressor mutation, or else by compensatory mutation somewhere in the gene (second site reversion).


A8V  is point mutation on  Troponin C  (cTNC) that leads to a  hypertrophic cardiomyopathy . The coordinated cardiac muscle contraction is regulated by the troponin complex on thin filament (troponin C which is calcium binding,  troponin T  that plays the role with  tropomyosin , and  troponin I  which has an inhibitory action  annulating  the S1 ATPase activity in the presence of tropomyosin and troponin and absence of Ca 2+ ). [ 1 ] [ 2 ]  This mutation is determined by the change of Alanine to Valine at nucleotide 23 from C to T. [ 3 ]  Patients with this type of mutation shows thickness on the left ventricle wall of around 18 mm, compared to the normal this thickness would be 12 mm. [ 3 ] [ 4 ]  Also, A8V affects the Ca 2+  binding affinity compared to normal genotype and increased sensitivity on force development. [ 4 ]


Adaptive evolution  results from the propagation of advantageous  mutations  through  positive selection . This is the modern synthesis of the process which  Darwin  and  Wallace  originally identified as the mechanism of evolution. However, in the last half century, there has been considerable debate as to whether evolutionary changes at the molecular level are largely driven by natural selection or random genetic drift. Unsurprisingly, the forces which drive evolutionary changes in our own species’ lineage have been of particular interest. Quantifying  adaptive evolution in the human genome  gives insights into our own evolutionary history and helps to resolve this  neutralist-selectionist debate . Identifying specific regions of the human genome that show evidence of adaptive evolution helps us find functionally significant  genes , including genes important for human health, such as those associated with diseases.


The methods used to identify adaptive evolution are generally devised to test the null hypothesis of  neutral evolution , which, if rejected, provides evidence of adaptive evolution. These tests can be broadly divided into two categories.


Firstly, there are methods that use a comparative approach to search for evidence of function-altering mutations. The  dN/dS  rates-ratio test estimates ω, the rates at which  nonsynonymous  ('dN') and  synonymous  ('dS')  nucleotide substitutions  occur ('synonymous' nucleotide substitutions do not lead to a change in the coding amino acid, while 'nonsynonymous' ones do). In this model,  neutral evolution  is considered the  null hypothesis , in which dN and dS approximately balance so that ω ≈ 1. The two  alternative hypotheses  are a  relative absence  of nonsynonymous substitutions (dN < dS; ω < 1), suggesting the effect on  fitness  ('fitness effect', or ' selection pressure ') of such mutations is negative ( purifying selection  has operated over time); or a  relative excess  of nonsynonymous substitutions (dN > dS; ω > 1), indicating positive effect on fitness, i.e.  diversifying selection  (Yang and Bielawski 2000).


The  McDonald-Kreitman (MK) test  quantifies the amount of adaptive evolution occurring by estimating the proportion of nonsynonymous substitutions which are adaptive, referred to as  α  (McDonald and  Kreitman  1991,  Eyre-Walker  2006). α is calculated as: α = 1-(dspn/dnps), where dn and ds are as above, and pn and ps are the number of nonsynonymous (fitness effect assumed neutral or deleterious) and synonymous (fitness effect assumed neutral) polymorphisms respectively  (Eyre-Walker 2006).


Note, both these tests are presented here in basic forms, and these tests are normally modified considerably to account for other factors, such as the effect of slightly deleterious mutations.


The other methods for detecting adaptive evolution use genome wide approaches, often to look for evidence of selective sweeps. Evidence of complete selective sweeps is shown by a decrease in genetic diversity, and can be inferred from comparing the patterns of the Site Frequency Spectrum (SFS, i.e. the allele frequency distribution) obtained with the SFS expected under a neutral model (Willamson et al. 2007). Partial selective sweeps provide evidence of the most recent adaptive evolution, and the methods identify adaptive evolution by searching for regions with a high proportion of derived alleles (Sabeti et al. 2006).


Examining patterns of Linkage Disequilibrium (LD) can locate signatures of adaptive evolution (Hawks et al. 2007, Voight et al. 2006). LD tests work on the basic principle that, assuming equal recombination rates, LD will rise with increasing  natural selection . These genomic methods can also be applied to search for adaptive evolution in non-coding DNA, where putatively neutral sites are hard to identify (Ponting and Lunter 2006).


Another recent method used to detect selection in non-coding sequences examines  insertions  and  deletions  (indels), rather than point mutations (Lunter et al. 2006), although the method has only been applied to examine patterns of negative selection.


Many different studies have attempted to quantify the amount of adaptive evolution in the  human genome , the vast majority using the comparative approaches outlined above. Although there are discrepancies between studies, generally there is relatively little evidence of adaptive evolution in protein  coding DNA , with estimates of adaptive evolution often near 0% (see Table 1). The most obvious exception to this is the 35% estimate of α (Fay et al. 2001). This comparatively early study used relatively few  loci  (fewer than 200) for their estimate, and the  polymorphism  and divergence data used was obtained from different genes, both of which may have led to an overestimate of α. The next highest estimate is the 20% value of α (Zhang and Li 2005). However, the MK test used in this study was sufficiently weak that the authors state that this value of α is not statistically significantly different from 0%. Nielsen et al. (2005a)’s estimate that 9.8% of genes have undergone adaptive evolution also has a large margin of error associated with it, and their estimate shrinks dramatically to 0.4% when they stipulate that the degree of certainty that there has been adaptive evolution must be 95% or more.


This raises an important issue, which is that many of these tests for adaptive evolution are very weak. Therefore, the fact that many estimates are at (or very near to) 0% does not rule out the occurrence of any adaptive evolution in the human genome, but simply shows that positive selection is not frequent enough to be detected by the tests. In fact, the most recent study mentioned states that confounding variables, such as demographic changes, mean that the true value of α may be as high as 40% (Eyre-Walker and Keightley 2009). Another recent study, which uses a relatively robust methodology, estimates α at 10-20%  Boyko et al. (2008). Clearly, the debate over the amount of adaptive evolution occurring in human coding DNA is not yet resolved.


Even if low estimates of α are accurate, a small proportion of substitutions evolving adaptively can still equate to a considerable amount of coding DNA. Many authors, whose studies have small estimates of the amount of adaptive evolution in coding DNA, nevertheless accept that there has been some adaptive evolution in this DNA, because these studies identify specific regions within the human genome which have been evolving adaptively (e.g. Bakewell et al. (2007)). More genes underwent positive selection in chimpanzee evolution than in human.


The generally low estimates of adaptive evolution in human coding DNA can be contrasted with other species. Bakewell et al. (2007) found more evidence of adaptive evolution in chimpanzees than humans, with 1.7% of chimpanzee genes showing evidence of adaptive evolution (compared with the 1.1% estimate for humans; see Table 1). Comparing humans with more distantly related animals, an early estimate for α in  Drosophila  species was 45% (Smith and Eyre-Walker 2002), and later estimates largely agree with this (Eyre-Walker 2006). Bacteria and viruses generally show even more evidence of adaptive evolution; research shows values of α in a range of 50-85%, depending on the species examined (Eyre-Walker 2006). Generally, there does appear to be a positive correlation between (effective)  population size  of the species, and amount of adaptive evolution occurring in the coding DNA regions. This may be because random  genetic drift  becomes less powerful at altering  allele frequencies , compared to natural selection, as population size increases.


Estimates of the amount of adaptive evolution in  non-coding DNA  are generally very low, although fewer studies have been done on non-coding DNA. As with the coding DNA however, the methods currently used are relatively weak. Ponting and Lunter (2006) speculate that underestimates may be even more severe in non-coding DNA, because non-coding DNA may undergo periods of functionality (and adaptive evolution), followed by periods of neutrality. If this is true, current methods for detecting adaptive evolution are inadequate to account for such patterns. Additionally, even if low estimates of the amount of adaptive evolution are correct, this can still equate to a large amount of adaptively evolving non-coding DNA, since non-coding DNA makes up approximately 98% of the DNA in the human genome. For example, Ponting and Lunter (2006) detect a modest 0.03% of non-coding DNA showing evidence of adaptive evolution, but this still equates to approximately 1 Mb of adaptively evolving DNA. Where there is evidence of adaptive evolution (which implies functionality) in non-coding DNA, these regions are generally thought to be involved in the regulation of protein coding sequences.


As with humans, fewer studies have searched for adaptive evolution in non-coding regions of other organisms. However, where research has been done on Drosophila, there appears to be large amounts of adaptively evolving non-coding DNA. Andolfatto (2005) estimated that adaptive evolution has occurred in 60% of untranslated mature portions of mRNAs, and in 20% of intronic and intergenic regions. If this is true, this would imply that much non-coding DNA could be of more functional importance than coding DNA, dramatically altering the consensus view. However, this would still leave unanswered what function all this non-coding DNA performs, as the regulatory activity observed thus far is in just a tiny proportion of the total amount of non-coding DNA. Ultimately, significantly more evidence needs to be gathered to substantiate this viewpoint.


Several recent studies have compared the amounts of adaptive evolution occurring between different populations within the human species. Williamson et al. (2007) found more evidence of adaptive evolution in European and Asian populations than African American populations. Assuming African Americans are representative of Africans, these results makes sense intuitively, because humans spread out of Africa approximately 50,000 years ago  (according to the consensus Out-of-Africa hypothesis of human origins (Klein 2009)), and these humans would have adapted to the new environments they encountered. By contrast, African populations remained in a similar environment for the following tens of thousands of years, and were therefore probably nearer their adaptive peak for the environment. However, Voight et al. (2006) found evidence of more adaptive evolution in Africans, than in Non-Africans (East Asian and European populations examined), and Boyko et al. (2008) found no significant difference in the amount of adaptive evolution occurring between different human populations. Therefore, the evidence obtained so far is inconclusive as to what extent different human populations have undergone different amounts of adaptive evolution.


The rate of adaptive evolution in the human genome has often been assumed to be constant over time. For example, the 35% estimate for α calculated by Fay et al. (2001) led them to conclude that there was one adaptive substitution in the human lineage every 200 years since human divergence from  old-world monkeys . However, even if the original value of α is accurate for a particular time period, this extrapolation is still invalid. This is because there has been a large acceleration in the amount of positive selection in the human lineage over the last 40,000 years, in terms of the number of genes that have undergone adaptive evolution (Hawks et al. 2007). This agrees with simple theoretical predictions, because the human population size has expanded dramatically in the last 40,000 years, and with more people, there should be more adaptive substitutions. Hawks et al. (2007) argue that demographic changes (particularly population expansion) may greatly facilitate adaptive evolution, an argument that somewhat corroborates the positive correlation inferred between population size and amount of adaptive evolution occurring mentioned previously.


It has been suggested that cultural evolution may have replaced genetic evolution, and hence slowed the rate of adaptive evolution over the past 10,000 years. However, it is possible that cultural evolution could actually increase genetic adaptation. Cultural evolution has vastly increased communication and contact between different populations, and this provides much greater opportunities for genetic admixture between the different populations (Hawks et al. 2007). However, recent cultural phenomena, such as modern medicine and the smaller variation in modern family sizes, may reduce genetic adaptation as natural selection is relaxed, overriding the increased potential for adaptation due to greater genetic admixture.


Studies generally do not attempt to quantify the average strength of selection propagating advantageous mutations in the human genome. Many models make assumptions about how strong selection is, and some of the discrepancies between the estimates of the amounts of adaptive evolution occurring have been attributed to the use of such differing assumptions (Eyre-Walker 2006). The way to accurately estimate the average strength of positive selection acting on the human genome is by inferring the distribution of fitness effects (DFE) of new advantageous mutations in the human genome, but this DFE is difficult to infer because new advantageous mutations are very rare (Boyko et al. 2008). The DFE may be exponential shaped in an adapted population (Eyre-Walker and Keightley 2007). However, more research is required to produce more accurate estimates of the average strength of positive selection in humans, which will in turn improve the estimates of the amount of adaptive evolution occurring in the human genome (Boyko et al. 2008).


A considerable number of studies have used genomic methods to identify specific human genes that show evidence of adaptive evolution. Table 2 gives selected examples of such genes for each gene type discussed, but provides nowhere near an exhaustive list of the human genes showing evidence of adaptive evolution. Below are listed some of the types of gene which show strong evidence of adaptive evolution in the human genome.


Bakewell et al. (2007) found that a relatively large proportion (9.7%) of positively selected genes were associated with diseases. This may be because diseases can be adaptive in some contexts. For example, schizophrenia has been linked with increased creativity (Crespi et al. 2007), perhaps a useful trait for obtaining food or attracting mates in  Palaeolithic  times. Alternatively, the adaptive mutations may be the ones which reduce the chance of disease arising due to other mutations. However, this second explanation seems unlikely, because the mutation rate in the human genome is fairly low, so selection would be relatively weak.


417 genes involved in the immune system showed strong evidence of adaptive evolution in the study of Nielsen et al. (2005a). This is probably because the immune genes may become involved in an  evolutionary arms race  with bacteria and viruses (Daugherty and Malik 2012; Van der Lee et al. 2017). These pathogens evolve very rapidly, so selection pressures change quickly, giving more opportunity for adaptive evolution.


247 genes in the testes showed evidence of adaptive evolution in the study of Nielsen et al. (2005a). This could be partially due to sexual antagonism. Male-female competition could facilitate an arms race of adaptive evolution. However, in this situation you would expect to find evidence of adaptive evolution in the female sexual organs also, but there is less evidence of this.  Sperm competition  is another possible explanation. Sperm competition is strong, and sperm can improve their chances of fertilising the female egg in a variety of ways, including increasing their speed, stamina or response to chemoattractants (Swanson and Vacquier 2002).


Genes involved in detecting smell show strong evidence of adaptive evolution (Voight et al. 2006), probably due to the fact that the smells encountered by humans have changed recently in their evolutionary history (Williamson et al. 2007). Humans’ sense of smell has played an important role in determining the safety of food sources.


Genes involved in lactose metabolism show particularly strong evidence of adaptive evolution amongst the genes involved in nutrition. A mutation linked to  lactase persistence  shows very strong evidence of adaptive evolution in European and American populations (Williamson et al. 2007), populations where pastoral farming for milk has been historically important.


Pigmentation genes show particularly strong evidence of adaptive evolution in non-African populations (Williamson et al. 2007). This is likely to be because those humans that left Africa approximately 50,000 years ago, entered less sunny climates, and so were under new selection pressures to obtain enough Vitamin D from the weakened sunlight.


There is some evidence of adaptive evolution in genes linked to brain development, but some of these genes are often associated with diseases, e.g. microcephaly (see Table 2). However, there is a particular interest in the search for adaptive evolution in brain genes, despite the ethical issues surrounding such research. If more adaptive evolution was discovered in brain genes in one human population than another, then this information could be interpreted as showing greater intelligence in the more adaptively evolved population.


Other gene types showing considerable evidence of adaptive evolution (but generally less evidence than the types discussed) include: genes on the  X chromosome , nervous system genes, genes involved in  apoptosis , genes coding for skeletal traits, and possibly genes associated with speech (Nielsen et al. 2005a, Williamson et al. 2007, Voight et al. 2006, Krause et al. 2007).


As noted previously, many of the tests used to detect adaptive evolution have very large degrees of uncertainty surrounding their estimates. While there are many different modifications applied to individual tests to overcome the associated problems, two types of confounding variables are particularly important in hindering the accurate detection of adaptive evolution: demographic changes and biased gene conversion.


Demographic changes are particularly problematic and may severely bias estimates of adaptive evolution. The human lineage has undergone both rapid population size contractions and expansions over its evolutionary history, and these events will change many of the signatures thought to be characteristic of adaptive evolution (Nielsen et al. 2007). Some genomic methods have been shown through simulations to be relatively robust to demographic changes (e.g. Willamson et al. 2007). However, no tests are completely robust to demographic changes, and new genetic phenomena linked to demographic changes have recently been discovered. This includes the concept of “surfing mutations”, where new mutations can be propagated with a population expansion (Klopfstein et al. 2006).


A phenomenon which could severely alter the way we look for signatures of adaptive evolution is  biased gene conversion  (BGC) (Galtier and Duret 2007). Meiotic recombination between  homologous chromosomes  that are heterozygous at a particular locus can produce a DNA mismatch.  DNA repair  mechanisms are biased towards repairing a mismatch to the CG base pair. This will lead allele frequencies to change, leaving a signature of non-neutral evolution (Galtier et al. 2001). The excess of AT to GC mutations in human genomic regions with high substitution rates (human accelerated regions, HARs) implies that BGC has occurred frequently in the human genome (Pollard et al. 2006, Galtier and Duret 2007). Initially, it was postulated that BGC could have been adaptive (Galtier et al. 2001), but more recent observations have made this seem unlikely. Firstly, some HARs show no substantial signs of selective sweeps around them. Secondly, HARs tend to be present in regions with high recombination rates (Pollard et al. 2006). In fact, BGC could lead to HARs containing a high frequency of deleterious mutations (Galtier and Duret 2007). However, it is unlikely that HARs are generally maladaptive, because DNA repair mechanisms themselves would be subject to strong selection if they propagated deleterious mutations. Either way, BGC should be further investigated, because it may force radical alteration of the methods which test for the presence of adaptive evolution.


(format of table and some data displayed as in Table 1 of Eyre-Walker (2006))


Adaptive mutation , also called  directed mutation  or  directed mutagenesis  is a controversial evolutionary theory.  It posits that  mutations , or genetic changes, are much less random and more purposeful than traditional  evolution , implying that organisms can respond to environmental stresses by directing mutations to certain  genes  or areas of the  genome . There have been a wide variety of experiments trying to support (or disprove) the idea of adaptive mutation, at least in  microorganisms .


The most widely accepted theory of  evolution  states that organisms are modified by natural selection where changes caused by mutations improve their chance of reproductive success. Adaptive mutation states that rather than mutations and evolution being random, they are in response to specific stresses. In other words, the mutations that occur are more beneficial and specific to the given stress, instead of random and not a response to anything in particular. The term stress refers to any change in the environment, such as temperature, nutrients, population size, etc. Tests with microorganisms have found that for adaptive mutation, more of the mutations observed after a given stress were more effective at dealing with the stress than chance alone would suggest is possible. [ 1 ] [ 2 ]  This theory of adaptive mutation was first brought to academic attention in the 1980s by  John Cairns . [ 3 ]


Adaptive mutation is a controversial claim leading to a series of experiments designed to test the idea. Three major experiments are the SOS response, [ 4 ]  responses to starvation in  Escherichia coli , [ 5 ]  and testing for revertants of a  tryptophan   auxotroph  in  Saccharomyces cerevisiae  (yeast). [ 1 ]


The  E. coli  strain FC40 has a high rate of mutation, and so is useful for studies, such as for adaptive mutation. Due to a  frameshift mutation , a change in the sequence that causes the DNA to code for something different, FC40 is unable to process lactose. When placed in a lactose-rich medium, it has been found that 20% of the cells mutated from Lac- (could not process lactose) to Lac+, meaning they could now utilize the lactose in their environment. The responses to stress are not in current DNA, but the change is made during DNA replication through recombination and the replication process itself, meaning that the adaptive mutation occurs in the current bacteria and will be inherited by the next generations because the mutation becomes part of the genetic code in the bacteria. [ 5 ]  This is particularly obvious in a study by Cairns, which demonstrated that even after moving  E. coli  back to a medium with minimal levels of lactose, Lac+ mutants continued to be produced as a response to the previous environment. [ 1 ]  This would not be possible if adaptive mutation was not at work because natural selection would not favor this mutation in the new environment. Although there are many genes involved in adaptive mutation, RecG, a protein, was found to have an effect on adaptive mutation. By itself, RecG was found to not necessarily lead to a mutational phenotype. However, it was found to inhibit the appearance of revertants (cells that appeared normally, as opposed to those with the mutations being studied) in  wild type  cells. On the other hand, RecG mutants were key to the expression of RecA-dependent mutations, which were a major portion of study in the SOS response experiments, such as the ability to utilize lactose. [ 6 ]


Adaptive mutation was re-proposed in 1988 [ 7 ]  by  John Cairns  who was studying  Escherichia coli  that lacked the ability to  metabolize   lactose .  He grew these bacteria in  media  in which lactose was the only source of  energy .  In doing so, he found that the rate at which the bacteria  evolved  the ability to metabolize lactose was many  orders of magnitude  higher than would be expected if the  mutations  were truly  random .  This inspired him to propose that the mutations that had occurred had been  directed  at those genes involved in lactose utilization. [ 8 ]


Later support for this hypothesis came from Susan Rosenberg, then at the  University of Alberta , who found that an enzyme involved in  DNA recombinational repair ,  recBCD , was necessary for the directed mutagenesis observed by Cairns and colleagues in 1989. The directed mutagenesis hypothesis was challenged in 2002, by work showing that the phenomenon was due to general  hypermutability  due to selected gene amplification, followed by natural selection, and was thus a standard  Darwinian  process. [ 9 ] [ 10 ]  Later research from 2007 however, concluded that amplification could not account for the adaptive mutation and that "mutants that appear during the first few days of lactose selection are true revertants that arise in a single step". [ 11 ]


This experiment is different from the others in one small way: this experiment is concerned with the pathways leading to an adaptive mutation while the others tested the changing environment microorganisms were exposed to. The  SOS response  in  E. coli  is a response to DNA damage that must be repaired. The normal  cell cycle  is put on hold and  mutagenesis  may begin.  This means that mutations will occur to try to fix the damage. This  hypermutation , or increased rate of change, response has to have some regulatory process, and some key molecules in this process are  RecA , and  LexA . These are proteins and act as stoplights for this and other processes. They also appear to be the main contributors to adaptive mutation in  E. coli . Changes in presence of one or the other was shown to affect the SOS response, which in turn affected how the cells were able to process  lactose , which should not be confused with the lactose starvation experiment. The key point to understand here is that LexA and RecA both were required for adaptive mutation to occur, and without the SOS response adaptive mutation would not be possible. [ 1 ]


von Borstel, in the 1970s, conducted experiments similar to the Lactose Starvation experiment with yeast, specifically  Saccharomyces cerevisiae . He tested for tryptophan  auxotroph  revertants. A tryptophan auxotroph cannot make tryptophan for itself, but wild-type cells can and so a revertant will revert to the normal state of being able to produce tryptophan. He found that when yeast colonies were moved from a tryptophan-rich medium to a minimal one, revertants continued to appear for several days. The degree to which revertants were observed in yeast was not as high as with bacteria. Other scientists have conducted similar experiments, such as Hall who tested  histidine  revertants, or Steele and Jinks-Robertson who tested  lysine .  These experiments demonstrate how  recombination  and  DNA replication  are necessary for adaptive mutation. However, in lysine-tested cells, recombination continued to occur even without selection for it. Steele and Jinks-Robertson concluded that recombination occurred in all circumstances, adaptive or otherwise, while mutations were present only when they were beneficial and adaptive. [ 1 ]


Although the production of mutations during selection was not as vigorous as observed with bacteria, these studies are convincing. As mentioned above, a subsequent study adds even more weight to the results with  lys2 . Steele and Jinks-Robertson [ 12 ]  found that LYS prototrophs due to interchromosomal recombination events also continue to arise in nondividing cells, but in this case, the production of recombinants continued whether there was selection for them or not. Thus, mutation occurred in stationary phase only when it was adaptive, but recombination occurred whether it was adaptive or not.


Delayed appearance of mutants has also been reported for  Candida albicans . [ 13 ]  With long exposure to sublethal concentrations of heavy metals, colonies of resistant cells began to appear after 5–10 days and continued to appear for 1–2 weeks thereafter. These resistances could have resulted from gene amplification, although the phenotypes were stable during a short period of nonselective growth. However, revertants of two auxotrophies also appeared with similar kinetics. None of these events in  Candida albicans  have, as yet, been shown to be specific to the selection imposed.


Allele age  (or  mutation age ) is the amount of time elapsed since an  allele  first appeared due to  mutation . Estimating the time at which a certain allele appeared allows researchers to infer patterns of human migration, disease, and  natural selection . Allele age can be estimated based on (1) the frequency of the allele in a population and (2) the genetic variation that occurs within different copies of the allele, also known as intra-allelic variation. While either of these methods can be used to estimate allele age, the use of both increases the accuracy of the estimation and can sometimes offer additional information regarding the presence of selection.


Estimating allele age based on the allele’s frequency is based on the fact that alleles in high frequency are older than alleles in low frequency (assuming the absence of selection). Of course, many alleles of interest are under some type of selection. Because alleles that are under positive selection can rise to high frequency very quickly, it is important to understand the mechanisms that underlie allele frequency change, such as natural selection,  gene flow ,  genetic drift , and mutation.


Estimating allele age based on intra-allelic variation is based on the fact that with every generation, linkage with other alleles ( linkage disequilibrium ) is disrupted by recombination and new variation in linkage is created via new mutations. The analysis of intra-allelic variation to assess allele age depends on coalescent theory. There are two different approaches that can be used to analyze allele age based on intra-allelic variation. First, a phylogenetics approach extrapolates an allele’s age by reconstructing a gene tree and dating the root of the tree. This approach is best when analyzing ancient, as opposed to recent, mutations. Second, a population genetics approach estimates allele age by using mutation, recombination, and demography models instead of a gene tree. This type of approach is best for analyzing recent mutations.


Recently, Albers and McVean (2018) proposed a non-parametric method to estimate the age of an allele, using probabilistic, coalescent-based models of mutation and recombination. [ 1 ]  Specifically, their method infers the time to the most recent common ancestor ( TMRCA ) between hundreds or thousands of chromosomal sequence ( haplotype ) pairs. This information is then combined using a  composite likelihood  approach to obtain an estimate of the time of mutation at a single locus. This methodology was applied to more than 16 million variants in the human genome, using data from the  1000 Genomes Project  and the  Simons Genome Diversity Project , to generate the  atlas of variant age . [ 2 ]


Population geneticists,  Motoo Kimura  and  Tomoko Ohta , were the first to analyze the association between an allele’s frequency and its age in the 1970s. [ 3 ] [ 4 ]  They showed that the age of a neutral allele can be estimated (assuming a large, randomly mating population) by


E
 (

 t

 1

 )
 =
 (
 −
 2
 p
 )

 /

 (
 1
 −
 p
 )
 ln

 (
 p
 )

 {\displaystyle E(t_{1})=(-2p)/(1-p)\ln(p)}


Where

 p

 {\displaystyle p}

  represents the allele frequency and

 t

 1

 {\displaystyle t_{1}}

  is the expected age, measured in units of 2N generations. [ 3 ] [ 4 ]


More recent studies, however, have focused on the analysis of intra-allelic variation. In 1990, Jean-Louis Serre and his team were the first to assess allele age by analyzing intra-allelic variation. Using a sample of 240 French families, they surveyed two restriction fragment length polymorphisms (RFLP) sites (E1 and E2) that are closely linked to an allele (ΔF508) at the cystic fibrosis locus (CFTR). Recombination theory allows for the calculation of x(t), the expected frequency of E2 in association with the allele ΔF508 in generation t, and y, the frequency of E2 on chromosomes without the ΔF508 allele. The recombination rate, c, is assumed to be known, and so the allele age can be calculated as an estimate of t. [ 4 ] [ 5 ]


t
 =

 1

 ln

 (
 1
 −
 c
 )

 ln

 x
 (
 t
 )
 −
 y

 1
 −
 y

 {\displaystyle t={1 \over \ln(1-c)}\ln {x(t)-y \over 1-y}}


Although Serre et al. (1990) were the first to employ this method, it became increasingly popular after the Risch et al. study in 1995, which analyzed alleles in an Ashkenazi Jewish population. [ 4 ] [ 6 ]


Many intra-allelic variation studies suggest that disease-causing alleles arose rather recently in human history. [ 7 ]


The Serre et al. (1990) study estimated that an allele causing  cystic fibrosis  arose approximately 181.4 generations ago. Therefore, they estimated that the allele age to be between 3,000 and 6,000 years ago. [ 4 ] [ 5 ]  However, other studies have obtained drastically different estimates. Morral et al. (1994) suggested a minimum age of 52,000 years ago. A reanalysis of the Morral et al. (1994) data by Slatkin and Rannala (2000) estimated an allele age of approximately 3,000 years, which is consistent with the Serre et al. (1990) results. [ 4 ]


A 32 base pair deletion at the CCR5 locus results in resistance to the  HIV  infection, which causes AIDS. Individuals who are homozygous for the mutation experience complete resistance to the infection, while heterozygotes only experience partial resistance to the infection, resulting in a delayed onset of AIDS. [ 4 ] [ 8 ]  A study by Stephens et al. in 1998 suggested that this allele originated approximately 27.5 generations, or 688 years ago. These results were obtained using intra-allelic variation analysis. This same study also used the allele frequency and the Kimura-Ohta model to estimate allele age. This method provided very different results, suggesting that the allele appeared more than 100,000 years ago. Stephens et al. (1996) argue that the discrepancy between these age estimates strongly suggest recent positive selection for the CCR5 mutation. [ 4 ] [ 9 ]  Because the CCR5 mutation also offers resistance to smallpox, these results are consistent with the idea that the CCR5 mutation first rose to higher frequency due to positive selection during smallpox outbreaks in European history before being positively selected for due to its role in HIV resistance. [ 10 ]


Many adults are lactose intolerant because their bodies cease production of the enzyme lactase post childhood. However, mutations in the promoter region of the lactase gene (LCT) result in the continued production of lactase throughout adulthood in certain African populations, a condition known as  lactase persistence . A study conducted by Sarah Tishkoff and her team shows that the mutation for lactase persistence has been under positive selection since its recent appearance approximately 3,000 to 7,000 years ago. These dates are consistent with the rise of cattle domestication and pastoralist lifestyles in these regions, making the lactase persistence mutation a strong example of gene-culture co-evolution. [ 11 ]


Allelic heterogeneity  is the phenomenon in which different  mutations  at the same  locus  lead to the same or very similar  phenotypes . These allelic variations can arise as a result of  natural selection  processes, as a result of  exogenous   mutagens ,  genetic drift , or  genetic migration . Many of these mutations take the form of  single nucleotide polymorphisms  in which a single nucleotide base is altered compared to a  consensus sequence . They can also exist as  copy number variants  (CNV) in which the copies of a gene or DNA sequence is different from the population. [ 1 ]


Mutated alleles expressing allelic heterogeneity can be classified as adaptive or disadaptive. These mutations can occur in the  germ line  cells,  somatic cells , or in the  mitochondrial . Mutations in germ line cells can be inherited as well as mitochondrial allelic mutations. The mitochondrial allelic mutations are inherited maternally. Typically in the human genome a small amount of allele variants account for ~75% of the mutations found at a particular locus within a population. Other variants found are considered to be rare or exclusive to a single  pedigree . The  Online Mendelian Inheritance of Man  has a record of over 1000 genes and their associated allelic variants. These genes display allelic heterogeneity at their loci and are responsible for distinct disease  phenotypes . Some of these diseases include  alkaptonuria ,  albinism ,  achondroplasia , and  phenylketonuria . [ 2 ] [ 3 ]  For example,  β-thalassemia  may be caused by several different mutations in the  β-globin  gene. Allelic heterogeneity should not be confused with  locus heterogeneity  in which a mutation at a different gene causes a similar phenotype. Nor should it be confused with  phenotypic heterogeneity  in which a mutation within the same gene causes a different phenotype. Other major diseases displaying allelic heterogeneity are allelic mutations in the dystrophin gene which cause Duchenne dystrophy and mutations in the CFTR gene that are known to causes cystic fibrosis. [ 4 ]


The human gene for the  HGD  nucleotide sequence shows a number of AKU-causing allelic mutations. Approximately 40 different allelic variants have been documented. Most of these variants do not have an effect on the enzyme catalysis function. A few known alleles have an indirect effect on protein function by causing misfolding and disrupt the proper assembly of the enzyme complex. Alkaptunoria is considered to be a classic example of allelic heterogeneity showing a single variant in the human phenotype. [ 5 ]


In  genetics , the  Bateman–Mukai method , sometimes referred to as the Bateman–Mukai technique, is a traditional method used for describing the  mutation rates  for  genes  through the observation of physical traits ( phenotype ) of a living  organism . The method involves the maintenance of many mutation accumulation lineages of the organism studied, and it is therefore labor intensive.


The foundational papers from which this method gets its name were conducted by geneticists A. J. Bateman in 1959 [ 1 ]  and T. Mukai in 1964. [ 2 ]  Bateman used an early form of this method to understand how  radiation  affects the survival of  chromosomes  due to radiation induced  mutations . Mukai's experimental design largely followed the design of Bateman's study, but rather than inducing mutations via any external factor, the study aimed to describe the spontaneous naturally occurring  deleterious mutation  rate of the common fruit fly.


The method requires the establishment of many mutation accumulation lineages using within line breeding of  diploid  organisms. These lines are maintained in a favorable environment for deleterious mutations to accumulate so that they are not to be purged by  natural selection : excess food and other resources are kept available to eliminate  competition , and the parents of the next generation are chosen at random without any regards to  fitness . Importantly, in this way, mutation accumulation experiments attempt to describe the true mutation rates that would be observed in the absence of natural selection.


Asexually reproducing  organisms can simply have a single parent selected as the parent for the next generation of each line. In  sexually reproducing  organisms, measures must be taken such that researchers can be sure that mutations are  inherited  in by future generations of the mutation accumulation lines. The use of a  balancer gene  can be implemented towards this end. In the Mukai experiment, male flies  homozygous  for the wild type chromosome 2 were always mated with female  heterozygotes  for the Pm/Cy balancer gene that produces an observable phenotype in the wings, with homozygous Pm/Cy being lethal. This ensures that researches can select for organisms that do not exhibit the phenotypic trait of the balancer gene, which in turn means that only wild type chromosomes will be passed down to the next generation. In this way, in sexually reproducing organisms, any spontaneously occurring mutations that occur in the mutation accumulation line should have a random chance, due to the  independent assortment , of being fixed in the next generation of line.


The main measurements that are derived from results of a Bateman–Mukai method are: the deleterious mutation rate,

 U

 {\displaystyle U}

 , and the average selection coefficient,

 E
 (
 a
 )

 {\displaystyle E(a)}

 , although these must be derived from phenotype observation. [ 3 ]

 U

 {\displaystyle U}

 , which is specifically the mutation rate for a single copy of a gene is derived from the assumption that deleterious mutations are randomly fixed and from the nature of the diploid organisms, which have two copies of each gene. So the mutation rate from both copies,

 2
 U

 {\displaystyle 2U}

 , multiplied by the population of the line,

 p

 {\displaystyle p}

 , with the assumption of random fixation gives that the deleterious mutation rate,

 U
 =
 (
 p
 2
 U

 /

 p
 2
 )

 {\displaystyle U=(p2U/p2)}

 , such that each mutation per line per generation directly counts towards the mutation rate. By tracking the quantitative deleterious change in a trait delta M (ie. number of offspring), the mutation rate can be defined within one line as:

 Δ
 M
 =
 U
 E
 (
 a
 )

 {\displaystyle \Delta M=UE(a)}

 .


A  behaviour mutation  is a genetic  mutation  that alters genes that control the way in which an organism behaves, causing their behavioural patterns to change.


A mutation is a change or error in the  genomic  sequence of a cell. [ 1 ]  It can occur during  meiosis  or  replication  of  DNA , as well as due to  ionizing  or  UV radiation ,  transposons ,  mutagenic chemicals ,  viruses  and a number of other factors. [ 2 ] [ 3 ] [ 4 ]  Mutations usually (but not always) result in a change in an organism's  fitness . These changes are largely deleterious, having a negative effect on fitness; however, they can also be neutral and even advantageous. [ 1 ] [ 5 ]


It is theorized that these mutations, along with  genetic recombination , are the raw material upon which  natural selection  can act to form evolutionary processes. [ 6 ]  This is due to selection's tendency to "pick and choose" mutations which are advantageous and pass them on to an organism's offspring, while discarding deleterious mutations. In  asexual  lineages, these mutations will always be passed on, causing them to become a crucial factor in whether the lineage will survive or go extinct. [ 1 ]


One way that mutations manifest themselves is behaviour mutation. Some examples of this could be variations in mating patterns, [ 7 ]  increasingly aggressive or passive demeanor, [ 8 ]  how an individual learns and the way an individual interacts and coordinates with others. [ 9 ]


Behaviour mutations have important implications on the nature of the evolution of animal behaviour. They can help us understand how different forms of behaviour evolve, especially behaviour which can seem strange or out of place. In other cases, they can help us understand how important patterns of behaviour were able to arise – on the back of a simple gene mutation. [ 10 ] [ 11 ]  Finally, they can help provide key insight on the nature of speciation events which can occur when a behaviour mutation changes the courtship methods and manner of mating in sexually reproducing species. [ 12 ]


Ethology , the study of animal behaviour, has been a topic of interest since the 1930s. The pioneers of the field include Dutch biologist  Nikolaas Tinbergen  and Austrian biologists  Karl von Frisch  and  Konrad Lorenz [ 13 ] [ 14 ] [ 15 ]  (the three won the Nobel Prize in Physiology or Medicine in 1973 for their discoveries concerning organization and elicitation of individual and social behaviour patterns). [ 16 ]  However, the first published demonstration of how a mutation in a single gene could change an organism's behaviour was carried out by  Margaret Bastock  in 1956, while she was a Ph.D. student working under Tinbergen at Oxford University. [ 15 ]


Bastock investigated the yellow mutant of  Drosophila melanogaster , the common fruit fly. Upon comparison of courtship rituals in 19 yellow mutants and 19 wild types, wild types were noted to court 92% of the time, while yellow ones courted only 83% of the time. In addition, when the yellow mutants courted it took them noticeably longer than the wild types. Even after significant generations of crossing, the flies homozygous for the "yellow" allele were less successful in mating with wild type females than their heterozygous brothers. These results led Bastock to conclude that the origin of this deficient mating behaviour was the very same mutant gene that caused yellow discolouration. [ 12 ]


Bastock's work directly and indirectly influenced a new way of observing behaviour patterns and analyzing them, as well as changed the way we look at the evolution of these behavioural patterns in animals. [ 10 ] [ 11 ]  However, it was not until much later that her work was fully recognized and accredited in further studies on genes influencing animal behaviour. [ 15 ]   Seymour Benzer  worked further on  D. melanogaster  in the 1960s, focusing on different novel  phenotypes  such as  phototaxis  and  circadian rhythms . [ 17 ]  In 1978, J.C. Hall returned to a similar focus on courtship while investigating different mutations. [ 18 ]  Bastock's work had important consequences for the field of  neuroscience  as well, spurring the emergence of  neurogenetics  and a new understanding of how our brains work. [ 19 ] [ 20 ]


Behaviour mutations have been studied in a variety of animals, but most commonly in  Drosophila melanogaster  due to being able to produce large numbers with short generation time as well as a rich diversity of behaviours. Many tests have been used in drosophila by specifying behavioural mutations to further understand the  nervous system . [ 17 ]  In order to understand how behaviour is controlled by the nervous system, it is key to identify the neuronal substrates important for the specific activity studied, as well as to explain how they are incorporated into a functional circuit. Most tests used allowed researchers to directly observe the mutation, such as altering  phototaxis  or flight-reduction. It was also shown in some experiments that certain mutations affect experience-based behaviour. Behavioural mutation has also been extensively tested in mice.


In one test involving  Drosophila , a temperature-sensitive allele of shibire is overexpressed in neuronal subsets using the  GAL4/UAS system . [ 21 ]  The shi gene is used for  synaptic vesicle  recycling, and a change in the temperature would cause an accelerated and reversible effect on the synaptic transmission of shi expressing neurons. When shi was tested to cholinergic neurons, the flies showed a quick response to the temperature and were paralyzed within two minutes at 30 degrees, which was reversible. When shi was expressed in  photoreceptor cell , fly larva showed temporary temperature-dependent blindness. This experiment shows that shi can be expressed in specific neurons to cause temperature-dependent alterations in behaviours. This research will further be helpful in studying the neuronal subsets in the behaviour of intact animals due to the reversible and controlled manner it is performed in.


In more recent studies the  Zebrafish  ennui mutation was identified from mutagenesis identification for defects in early behaviour. [ 22 ]  Homozygous ennui embryo swam more slowly than the wild-type but gained normal swimming as it aged. When tested, the motor output of the  central nervous system  following mechano-sensory stimulation was normal in ennui, which means that the reaction-time and reaction-style were normal to the wild-types and the  motoneuron  were not affected. The synaptic current at the neuromuscular junction was significantly reduced in ennui which means that the  neuromuscular junction  was affected. The  acetylcholine receptor  was significantly reduced in the adult ennui in size as well as localization at the  myotome  segment borders of fast-twitch muscles.  Genetic mosaic  analysis revealed that ennui is necessary cell autonomously in muscle fibers for normal synaptic localization of acetylcholine receptors. Also, ennui is very important for  agrin  function. Ennui is very important in nerve-dependent acetylcholine clustering and the stability of axon growth.


In mice, chemical mutagenesis is a phenotype-driven approach to map the mouse mutant catalogue. [ 23 ]  The usage of mice in behavioural mutation tests allows scientists to increase our understanding of the genetic basis of mammalian behaviour as well as applying this information to human  neurological disorders  and  psychiatric disorders .  SHIRPA  is a hierarchal screening protocol that efficiently searches for mutations in muscle and lower  motor neuron function ,  Spinocerebellar ,  sensory neuron  function,  neuropsychiatry  function, and  autonomic nervous system function . The mice are then further tested for defects in parameters that are associated with human psychiatric disorders by using two well-known behaviour tests. The mice are tested for  locomotor activity  (LMA) as well as  prepulse inhibition  (PPI). For LMA, mice are placed in cages with beam-splitting monitors that will measure the activity of the mice as well as calculate their habituation to that environment. LMA is recorded in 35-minute time spans in bins of a 5-minute duration. The PPI measures the acoustic startle response, which is an exaggerated response to an unexpected stimulus. The acoustic startle is measured over a range of frequencies and amplitudes to calculate the average response. These tests allow us to detect abnormal behaviours and document them.


In each generation, the  genetic variation  within a population increases due to accumulation of  mutations  and decreases in response to  natural selection  and  genetic drift . Mutation accumulation occurs when mutations of small effect accumulate at certain  loci , yielding a large phenotypic effect in the aggregate. Multiple genes may simultaneously affect behavioural traits.  Spontaneous mutations  arise from sources including errors in  DNA replication , spontaneous lesions, and  transposable genetic elements  in the absence of  mutagens . Spontaneous mutations play a central role in the maintenance of genetic variation and persistence of natural population of many organisms. [ 24 ] [ 25 ]


Evolutionary biologists have used mutation accumulation experiments, in which mutations are allowed to drift to fixation in  inbred lines , to study the effect of spontaneous mutations on  phenotype  character. Phenotypic assays significantly determine whether and how quickly population with accumulated deleterious mutational loads can result in degradation of behavioural responses over time. [ 1 ]


Based on laboratory experimental evolution with long-term mutation accumulation (MA) lines of the nematode  Caenorhabditis elegans , a team of researchers at the  University of Oregon  investigated that mutation accumulation of behaviour is capable of generating significant levels of individual variation in ecologically relevant behavioural traits within populations. This variation will be dependent largely on the  genetic structure  and demographic characteristics of individuals. As a result, small or isolated populations are at high risk of experiencing behavioural degradation. For instance, the rate of mutation for behavioural traits has more effects for behavioural mutation within  captive populations  and some  endangered species . The study of two closely related behavioural traits of the free-living soil nematode  C. elegans ,  chemotaxis  and  locomotion , indicates that behavioural degradation is a direct source of competitive  fitness  loss under genomic mutation accumulation. [ 26 ]


Raymond B. Huey  and his colleagues used the same MA lines method, suggesting that mutation accumulation in  Drosophila melanogaster  significantly depresses only some behavioural traits. There are several explanations for this. It is possible that traits are influenced only by few  loci  so that their mutational target is small. Alternatively, the values of the behavioural traits are not maximized by  directional selection , but rather are under the influence of  stabilizing selection . Since behavioural traits are highly variable, mutation accumulation does not negatively affect all traits equivalently. [ 27 ]


The study of  sex allocation  has provided some of the most convincing tests of adaptive behaviour. Theory predicts that organisms can adjust the allocation of resources to male and female offspring in response to environmental conditions.  Sex ratio  behaviour is the sex ratio response of a female in various conditions. Mutation accumulation is important because it is one evolutionary cause that increases variation between individuals in sex-ratio behaviour. For example, female wasps can adjust their offspring sex ratios by choosing whether to fertilize an egg because they are  haplodiploid . In particular, female  Nasonia vitripennis  produce less males when laying eggs alone, and more males when laying eggs on a patch with other females. If female parasitoid wasps produce too few male offspring, then some of the female offspring will remain unmated. On the other hand, if too many sons are produced, then resources are wasted that could have been used to produce more daughters. Females of other strains show no similar conditional sex ratio behaviours. Researchers find that these behaviours are indeed subject to genetic variation. However, genetic variation in natural population is low and it has low  heritability  as for other fitness-related traits. The observation of this type of behavioural mutation has been argued to pose a problem for sex-ratio theory because the mutations are likely to have decreased fitness. [ 28 ] [ 29 ]


Aggression  is a survival trait that can be favoured by  natural selection  in nearly any species. Aggressive individuals can be better able to compete for resources including food, territory and mates, as well as more successful in protecting themselves and their progeny from predators. It can also be energetically costly, and extreme or out of context aggression can be disadvantageous or deleterious, especially in social organisms. [ 30 ]  Aggression is a complex trait that is regulated by many interacting genes and  gene expression  is highly variable depending on environment ( phenotypic plasticity ). Mutations in genes that influence aggressive behaviours can potentially increase aggression or  passivity .


Neurotransmitters ,  dopamine  and  serotonin  in particular, play an important role in the regulation of aggressive behaviours. Many studies are focused on genes that change the way neurotransmitters interact with receptors within the organism. For example, when individuals suffer from a mutation that causes them to have low levels of serotonin, there is an observed increase in impulsivity and depression [ 8 ]  With neurotransmitters playing a central role in the development of aggressive behaviour, it follows that many of the gene mutations that have been implicated with aggressive behaviours are involved in the breakdown and/or receipt of neurotransmitters.


Alexis Edwards and her team identified 59 mutations in 57 genes that affected aggressive behaviour in  Drosophila melanogaster . [ 31 ]  The results of their research showed that 32 of the mutants displayed increased aggression and 27 of the mutants displayed less aggression than the control group. Several of the genes examined were found to affect  nervous system  development and function. Aggression was assessed in this experiment by depriving  mutant  Drosophila flies from food and then allowing them to defend a limited food source. The number of contest competitions between flies was recorded and compared to non-mutant flies to assess whether the mutants were more or less aggressive than the  wild type . Examples of mutations that increase aggression are mutations in the  fruitless  or  dissatisfaction  genes which result in observable increases in male-male aggression. [ 31 ]


Mutations involving  amines  have been shown to be a prevalent source of changes in behaviour. A  point mutation  in the structural gene for  Monoamine Oxidase A , also known as MAO-A, is responsible for the breakdown of neurotransmitters. [ 8 ]  This mutation is  X-linked , affecting only males, and eliminates the production of MAO-A. Males afflicted with this mutation are prone to mild mental retardation as well as violent and  antisocial behaviour . Another amine affecting aggression is  β-alanine  which is a bioamine neurotransmitter that has been implicated in Drosophila aggression. A mutation known as the  black  mutation causes reduced levels of β-alanine and results in less reactive flies than the wild type.


In nearly all species, there is an obvious disequilibrium between frequency and severity of aggression in males versus females. [ 32 ]  Males are almost always the more aggressive sex and there are genetic differences that back up this observation. A common explanation for this phenomenon is the higher  testosterone  levels in males. Testosterone levels have a direct effect on neurotransmitter functioning contributing to physical aggression. Mutations affecting neurotransmitters, as stated above, are the dominant cause of changes in aggressive behaviour. Another contributor to the unequal male-female aggression ratio are the sex-linked gene mutations that affect only male behaviour, such as MAO-A mentioned above. These mutations could be the reason why males are nearly always more aggressive than females, although, testosterone levels are a much more feasible explanation.


Other evolutionary and genetic explanations of violent behaviour include: dopamine receptors mutations,  DRD2  and  DRD4 , [ 8 ]  that, when mutate simultaneously, are hypothesized to cause  personality disorders , low serotonin levels increasing irritability and gloom [ 30 ]  and the effects of testosterone [ 32 ]  on neurotransmitter functioning to explain the increased occurrence of aggression in males.


Behavioural mutations play a detrimental part towards the  genomes  of many species, however, they can greatly affect the outcome of  mating ; affecting the success of fitness, how many offspring will arise and the likelihood that the male will actually procreate. When  mutations  affect the mating habits of species, different traits that would otherwise benefit the species procreating are compromised.


A couple chemicals that are altered from mutation and have a great impact on mating, are  dopamine  and  serotonin . Each of these chemicals either has a reaction to how the animal acts, or how the species body is formed to benefit their mating success. An example of a mutation in serotonin was found in a species of  Nematodes . The serotonin caused their tails to curl during mating, when the mutation occurred the tails did not curl. Without the curling of the tail the nematode was unlikely to find the hermaphrodites sex organs to procreate, and results in less of that nematodes sperm being spread to other offspring. [ 33 ]  Another example is when the  D1 dopamine receptor  has a mutation on it; the arousal of a  Drosophila melanogaster  is increased, which also increases the courtship of the animal. [ 34 ] [ self-published source? ]


One example of a study was found in the 'yellow'  D.melanogaster , the mating of these males was only beneficial when it was dark outside, or when they were in a dark environment. The mutation is not yet known why it occurs this way, but studies have mentioned that the females of this fly species may be turned off by the certain colour of the mutated fly, and therefore in the dark the female is less likely to tell what colour this fly is. [ 34 ] [ 35 ]


A beneficial component of a mutation in the behaviour of a mating  D. melanogaster , was when the mutation caused the male to have a longer courtship time period. The flies that had a longer courtship had a tendency to have a higher probability of procreating. This means that the fly that took longer to actually initiate the courtship with the female fly, was more likely to be successful with the female successfully accepting the male. [ 35 ]


A  BRCA  mutation  is a  mutation  in either of the  BRCA1  and  BRCA2   genes , which are  tumour suppressor genes . Hundreds of different types of mutations in these genes have been identified, some of which have been determined to be harmful, while others have no proven impact. Harmful mutations in these genes may produce a  hereditary breast–ovarian cancer syndrome  in affected persons. Only 5–10% of  breast cancer  cases in women are attributed to  BRCA1  and  BRCA2  mutations (with  BRCA1  mutations being slightly more common than  BRCA2  mutations), but the impact on women with the gene mutation is more profound. [ 2 ]  Women with harmful mutations in either  BRCA1  or  BRCA2  have a risk of breast cancer that is about five times the normal risk, and a risk of ovarian cancer that is about ten to thirty times normal. [ 3 ]  The risk of breast and ovarian cancer is higher for women with a high-risk  BRCA1  mutation than with a  BRCA2  mutation. Having a high-risk mutation does not guarantee that the woman will develop any type of cancer, or imply that any cancer that appears was actually caused by the mutation, rather than some other factor.


High-risk mutations, which disable an important error-free DNA repair process ( homology directed repair ), significantly increase the person's risk of developing  breast cancer ,  ovarian cancer  and certain other cancers. Why  BRCA1  and  BRCA2  mutations lead preferentially to cancers of the breast and ovary is not known, but lack of  BRCA1  function seems to lead to non-functional  X-chromosome inactivation . Not all mutations are high-risk; some appear to be harmless variations.  The cancer risk associated with any given mutation varies significantly and depends on the exact type and location of the mutation and possibly other individual factors.


Mutations can be inherited from either parent and may be passed on to both sons and daughters. Each child of a  genetic carrier , regardless of sex, has a 50% chance of inheriting the mutated gene from the parent who carries the mutation. As a result, half of the people with  BRCA  gene mutations are male, who would then pass the mutation on to 50% of their offspring, male or female. The risk of  BRCA -related breast cancers for men with the mutation is higher than for other men, but still low. [ 4 ]  However,  BRCA  mutations can increase the risk of other cancers, such as  colon cancer ,  pancreatic cancer , and  prostate cancer .


Methods to diagnose the likelihood of a patient with mutations in  BRCA1  and  BRCA2  getting cancer were covered by  patents  owned or controlled by  Myriad Genetics . [ 5 ] [ 6 ]  Myriad's business model of exclusively offering the diagnostic test led to Myriad growing from being a startup in 1994 to being a publicly traded company with 1200 employees and about $500 million in annual revenue in 2012; [ 7 ]  it also led to controversy over high prices and the inability to get second opinions from other diagnostic labs, which in turn led to the landmark  Association for Molecular Pathology v. Myriad Genetics  lawsuit. [ 8 ]


Biallelic and homozygous inheritance of a BRCA gene leads to a severe form of  Fanconi anemia , and is embryonically lethal in the majority of the cases.


Women with deleterious mutations in either the  BRCA1  or  BRCA2  genes have a high risk of developing  breast  and/or  ovarian cancer .  Because different studies look at different populations, and because different types of mutations have somewhat different risks, the risk is best expressed as a range, rather than a single number. [ 9 ] : 89–111


Approximately 50% to 65% of women born with a deleterious mutation in  BRCA1  will develop breast cancer by age 70, and 35% to 46% will develop ovarian cancer by age 70.  Approximately 40% to 57% of women with a deleterious mutation in  BRCA2  will develop breast cancer by age 70, and 13% to 23% will develop ovarian cancer by age 70. [ 9 ] : 89–111  [ 10 ]


Women with a breast cancer associated with a  BRCA  mutation have up to a 40% probability of developing a new primary breast cancer within 10 years following initial diagnosis if they did not receive  tamoxifen  treatment or have an  oophorectomy . [ 4 ]  The woman's ten-year risk for ovarian cancer is also increased by 6-12% under these conditions. [ 4 ]


Statistics for  BRCA -related ovarian cancer typically encompass not only cancer of the  ovaries  themselves, but also  peritoneal cancer  and the very rare, but somewhat easier to detect, cancer of the  fallopian tubes .  Women with a  BRCA  mutation have more than 100 times the normal rate of fallopian tube cancer. [ 9 ] : 275–302    These three types of these cancers can be difficult to distinguish in their advanced stages.


BRCA -related breast cancer appears at an earlier age than sporadic breast cancer. [ 9 ] : 89–111    It has been asserted that  BRCA -related breast cancer is more aggressive than normal breast cancer, however most studies in specific populations suggest little or no difference in survival rates despite seemingly worse prognostic factors. [ 11 ] [ 12 ] [ 13 ]


BRCA -related ovarian and fallopian tube cancer is more treatable than average because it is unusually susceptible to platinum-based chemotherapy like  cisplatin . [ 9 ] : 275–302   There are also FDA-approved maintenance therapies available in the form of  PARP inhibitors . [ 14 ]   BRCA1 -related ovarian cancer appears at younger ages, but the risk for women with  BRCA2  climbs markedly at or shortly after menopause. [ 9 ] : 275–302


A 25-year-old woman with no mutation in her  BRCA  genes has an 84% probability to reach at least the age of 70. [ 15 ]  Of those not surviving, 11% die from either breast or ovarian cancer, and 89% from other causes.


Compared to that, a woman with a high-risk  BRCA1  mutation, if she had  breast cancer screening  but no prophylactic medical or surgical intervention, would have only 59% chance to reach age 70, twenty-five percentage points lower than normal. Of those women not surviving, 26% would die of breast cancer, 46% ovarian cancer, and 28% other causes. [ 15 ]


Women with high-risk  BRCA2  mutations, with screening but with no prophylactic medical or surgical intervention, would have only 71% chance to reach age 70, thirteen percentage points lower than normal. Of those not surviving, 21% would die of breast cancer, 25% ovarian cancer and 54% other causes. [ 15 ]


The likelihood of surviving to at least age 70 can be improved by several medical interventions, notably prophylactic mastectomy and oophorectomy. [ 15 ]


Men with a  BRCA  mutation have a dramatically elevated  relative risk  of developing breast cancer, but because the overall incidence of breast cancer in men is so low, the  absolute risk  is equal to or lower than the risk for women without a  BRCA  mutation. [ 9 ] : Ch8    Approximately 1% to 2% of men with a  BRCA1  mutation will develop breast cancer by age 70.  Approximately 6% of men with a  BRCA2  mutation will develop breast cancer by age 70, which is approximately equal to the risk for women without a  BRCA  mutation.  Very few men, with or without a predisposing mutation, develop breast cancer before age 50. [ 9 ] : Ch8


Approximately half of men who develop breast cancer have a mutation in a  BRCA  gene or in one of the other genes associated with  hereditary breast–ovarian cancer syndromes .


Breast cancer in men can be treated as successfully as breast cancer in women, but men often ignore the signs and symptoms of cancer, such as a painful area or an unusual swelling, which may be no bigger than a grain of  rice , until it has reached a late stage. [ 9 ] : Ch8


Unlike other men, men with a  BRCA  mutation, especially a  BRCA2  mutation, may benefit from professional and self  breast exams .  Medical imaging is not usually recommended, but because male  BRCA2  carriers have a risk of breast cancer that is very similar to the general female population, the standard annual  mammogram  program can be adapted to these high-risk men. [ 9 ] : Ch8


Mutations have been associated with increased risk of developing any kind of invasive cancer, including  stomach cancer ,  pancreatic cancer , prostate cancer, and  colon cancer . [ 16 ]  Carriers have the normal risks of developing cancer (and other diseases) associated with increased age, smoking, alcohol consumption, poor diet, lack of exercise, and other known risk factors, plus the additional risk from the genetic mutations and an increased susceptibility to damage from ionizing radiation, including natural  background radiation . [ 9 ] : 39–50


Men with  BRCA  mutations cannot get ovarian cancer, but they may be twice as likely as non-carriers to develop  prostate cancer  at a younger age. [ 9 ] : Ch8     The risk is smaller and disputed for  BRCA1  carriers; up to one-third of  BRCA2  mutation carriers are expected to develop prostate cancer before age 65.  Prostate cancer in  BRCA  mutation carriers tends to appear a decade earlier than normal, and it tends to be more aggressive than normal.  As a result, annual prostate screening, including a  digital rectal examination , is appropriate at age 40 among known carriers, rather than age 50. [ 9 ] : Ch8


Cancer of the  pancreas  tends to run in families, even among  BRCA  families. [ 9 ] : Ch8     A  BRCA1  mutation approximately doubles or triples the lifetime risk of developing pancreatic cancer; a  BRCA2  mutation triples to quintuples it.  Between 4% and 7% of people with pancreatic cancer have a  BRCA  mutation. [ 16 ]  However, since pancreatic cancer is relatively rare, people with a  BRCA2  mutation probably face an absolute risk of about 5%.  Like ovarian cancer, it tends not to produce symptoms in the early, treatable stages.  Like prostate cancer, pancreatic cancer associated with a  BRCA  mutation tends to appear about a decade earlier than non-hereditary cases. [ 16 ]  Asymptomatic screening is  invasive  and may be recommended only to  BRCA2  carriers who also have a family history of pancreatic cancer. [ 9 ] : Ch8


Melanoma  is the most deadly skin cancer, although it is easily cured in the early stages.  The normal likelihood of developing melanoma depends on race, the number of  moles  the person has, family history, age, sex, and how much the person has been exposed to UV radiation.  BRCA2  mutation carriers have approximately double or triple the risk that they would normally have, including a higher than average risk of  melanoma of the eye . [ 9 ] : Ch8  [ 16 ]


Cancer of the  colon  is approximately as common in both men and women in the developed world as breast cancer is among average-risk women, with about 6% of people being diagnosed with it, usually over the age of 50. [ 9 ] : Ch8     Like sporadic prostate cancer, it is a multifactorial disease, and is affected by age, diet, and similar factors.   BRCA  mutation carriers have a higher than average risk of this common cancer, but the risk is not as high as in some other  hereditary cancers .  The risk might be as high as four times normal in some  BRCA1  families, and double the normal risk among  BRCA2  carriers.  Like pancreatic cancer, it may be that only some  BRCA  mutations or some  BRCA  families have the extra risk; unlike other  BRCA -caused cancers, it does not appear at an earlier age than usual. [ 9 ] : Ch8     Normal colon cancer screening is usually recommended to  BRCA  mutation carriers.


Mutations in  BRCA1  and  BRCA2  are strongly implicated in some  hematological malignancies .   BRCA1  mutations are associated  acute myelogenous leukemia  and  chronic myelogenous leukemia . [ 17 ]  Mutations of  BRCA2  are also found in many  T-cell lymphomas  and  chronic lymphocytic leukemias . [ 17 ]