Properties and rates of germline mutations in humans
2013; Elsevier BV; Volume: 29; Issue: 10 Linguagem: Inglês
10.1016/j.tig.2013.04.005
ISSN1362-4555
AutoresCatarina D. Campbell, Evan E. Eichler,
Tópico(s)Genomics and Chromatin Dynamics
Resumo•We describe insights into mutation rate from high-throughput genome sequencing of families.•A paternal bias and agebeffect in mutation has been quantified at the genome-wide level.•Copy number variants arise less frequently than do point mutations, but affect more bases.•Future research will yield insights into the mutation rate of other forms of variation. All genetic variation arises via new mutations; therefore, determining the rate and biases for different classes of mutation is essential for understanding the genetics of human disease and evolution. Decades of mutation rate analyses have focused on a relatively small number of loci because of technical limitations. However, advances in sequencing technology have allowed for empirical assessments of genome-wide rates of mutation. Recent studies have shown that 76% of new mutations originate in the paternal lineage and provide unequivocal evidence for an increase in mutation with paternal age. Although most analyses have focused on single nucleotide variants (SNVs), studies have begun to provide insight into the mutation rate for other classes of variation, including copy number variants (CNVs), microsatellites, and mobile element insertions (MEIs). Here, we review the genome-wide analyses for the mutation rate of several types of variants and suggest areas for future research. All genetic variation arises via new mutations; therefore, determining the rate and biases for different classes of mutation is essential for understanding the genetics of human disease and evolution. Decades of mutation rate analyses have focused on a relatively small number of loci because of technical limitations. However, advances in sequencing technology have allowed for empirical assessments of genome-wide rates of mutation. Recent studies have shown that 76% of new mutations originate in the paternal lineage and provide unequivocal evidence for an increase in mutation with paternal age. Although most analyses have focused on single nucleotide variants (SNVs), studies have begun to provide insight into the mutation rate for other classes of variation, including copy number variants (CNVs), microsatellites, and mobile element insertions (MEIs). Here, we review the genome-wide analyses for the mutation rate of several types of variants and suggest areas for future research. The replication of the genome before cell division is a remarkably precise process. Nevertheless, there are some errors during DNA replication that lead to new mutations. If these errors occur in the germ cell lineage (i.e., the sperm and egg), then these mutations can be transmitted to offspring. Some of these new genetic variants will be deleterious to the organism, and a select few will be advantageous and serve as substrates for selection. Therefore, knowledge about the rate at which new mutations appear and the properties of new mutations is critical in the study of human genetics from evolution to disease. The study of the mutation rate in humans dates back further than the discovery of the structure of DNA or the determination of DNA as the genetic material. In seminal work performed during the 1930s and 1940s, J.B.S. Haldane studied hemophilia with the assumption of a mutation–selection balance to estimate mutation rate at that locus and determined that most new mutations arose in the paternal germline [1Haldane J.B.S. The rate of spontaneous mutation of a human gene.J. Genet. 1935; 31: 317-326Crossref Scopus (142) Google Scholar, 2Haldane J.B. The mutation rate of the gene for haemophilia, and its segregation ratios in males and females.Ann. Eugen. 1947; 13: 262-271Crossref PubMed Google Scholar]. Until recently, most mutation rate analyses were similar to this initial work in that they extrapolated rates and properties from a handful of loci (often linked to dominant genetic disorders; for example, see [3Kondrashov A.S. Direct estimates of human per nucleotide mutation rates at 20 loci causing Mendelian diseases.Hum. Mutat. 2003; 21: 12-27Crossref PubMed Scopus (169) Google Scholar]). Over the past few years, it has become feasible to generate large amounts of sequence data (including the genomes of parents and their offspring), and it is now possible to calculate empirically a genome-wide mutation rate. In addition, much interest has focused on understanding the role of de novo mutations in human disease. Therefore, in this review, we synthesize the recent analyses of mutation rate for multiple forms of genetic variation and discuss their implications with respect to human disease and evolution. It is now feasible to perform whole-genome sequencing on all individuals from a nuclear family; from these data, one can identify de novo mutations that ‘disobey’ Mendelian inheritance (Box 1, Figure I). The first two papers to apply this approach were limited in scope to three families [4Roach J.C. et al.Analysis of genetic inheritance in a family quartet by whole-genome sequencing.Science. 2010; 328: 636-639Crossref PubMed Scopus (366) Google Scholar, 5Conrad D.F. et al.Variation in genome-wide mutation rates within and between human families.Nat. Genet. 2011; 43: 712-714Crossref PubMed Scopus (105) Google Scholar], thus restricting the total number of de novo SNVs observed. Even with this limitation, these two analyses reported similar overall mutation rates of approximately 1 × 10−8 SNV mutation per base pair per generation, although there was considerable variation in families [4Roach J.C. et al.Analysis of genetic inheritance in a family quartet by whole-genome sequencing.Science. 2010; 328: 636-639Crossref PubMed Scopus (366) Google Scholar, 5Conrad D.F. et al.Variation in genome-wide mutation rates within and between human families.Nat. Genet. 2011; 43: 712-714Crossref PubMed Scopus (105) Google Scholar]. A more recent study using whole-sequence data from 78 Icelandic parent–offspring trios suggested a higher rate of 1.2 × 10−8 SNVs per generation from de novo mutations [6Kong A. et al.Rate of de novo mutations and the importance of father's age to disease risk.Nature. 2012; 488: 471-475Crossref PubMed Scopus (131) Google Scholar]. Another study used autozygous segments (see Glossary) in the genomes of Hutterite trios, who were descended from a 13-generation pedigree with 64 founders, to calculate independently the same SNV mutation rate of 1.2 × 10−8 [7Campbell C.D. et al.Estimating the human mutation rate using autozygosity in a founder population.Nat. Genet. 2012; 44: 1277-1281Crossref PubMed Scopus (16) Google Scholar]. A study of ten additional families of individuals affected with autism reported a rate of 1 × 10−8 [8Michaelson Jacob J. et al.Whole-genome sequencing in autism identifies hot spots for de novo germline mutation.Cell. 2012; 151: 1431-1442Abstract Full Text Full Text PDF PubMed Scopus (23) Google Scholar].Box 1Methods for discovering new mutations and estimating mutation rateMost of the methods developed for estimating mutation rate were developed for SNV data, but can be applied more broadly to other forms of variation. The most common approach for estimating mutation rate is to use families to look for mutations carried by a child but not by either of his or her parents (Figure I). This approach has been carried out on selected loci up to whole genomes. However, it is important to note that this method can be confounded by false positives for which putative de novo variants are enriched [5Conrad D.F. et al.Variation in genome-wide mutation rates within and between human families.Nat. Genet. 2011; 43: 712-714Crossref PubMed Scopus (105) Google Scholar]. In addition, somatic mutations in offspring of the sequenced families cannot be distinguished from germline de novo variants.The other classical approach for estimating mutation rates is to look at fixed differences between species [9Li W.H. Tanimura M. The molecular clock runs more slowly in man than in apes and monkeys.Nature. 1987; 326: 93-96Crossref PubMed Google Scholar, 10Nachman M.W. Crowell S.L. Estimate of the mutation rate per nucleotide in humans.Genetics. 2000; 156: 297-304PubMed Google Scholar]. The mutation rate can then be calculated based on the estimated divergence time between the species (Figure I). Although this approach is not confounded by false positives or somatic mutations, there is uncertainty in the divergence time between humans and chimpanzees, the average generation time, and effective population sizes.Recently, other approaches for determining mutation rate have been described. One group constructed a model of microsatellite evolution and applied this model to estimate the time to the most recent common ancestor (MRCA) for microsatellite alleles [12Sun J.X. et al.A direct characterization of human mutation based on microsatellites.Nat. Genet. 2012; 44: 1161-1165Crossref PubMed Scopus (21) Google Scholar]. Because SNVs near the microsatellite have the same ancestry as the microsatellite, the mutation rate for SNVs could be calculated using the SNV differences between haplotypes and the time to the MRCA [12Sun J.X. et al.A direct characterization of human mutation based on microsatellites.Nat. Genet. 2012; 44: 1161-1165Crossref PubMed Scopus (21) Google Scholar]. Another approach to estimating mutation rate involves the identification of heterozygous mutations in large regions of homozygosity by recent descent (autozygosity) [7Campbell C.D. et al.Estimating the human mutation rate using autozygosity in a founder population.Nat. Genet. 2012; 44: 1277-1281Crossref PubMed Scopus (16) Google Scholar, 120Alkuraya F.S. Autozygome decoded.Genet. Med. 2010; 12: 765-771Abstract Full Text Full Text PDF PubMed Scopus (24) Google Scholar] (Figure I). Such regions are particularly abundant among founder populations, providing a means for estimating mutation rate from a recent common ancestor in populations such as the Hutterites, the Amish, and the Icelandic population. Although different in many ways, these two approaches have some important similarities. Both are less susceptible to false positive and somatic mutations than are analyses of de novo mutations in trios. In addition, both approaches estimate the time to the MRCA for segments of the genome in different ways, but benefit by studying haplotypes with a more recent coalescent time than humans and chimpanzees. Most of the methods developed for estimating mutation rate were developed for SNV data, but can be applied more broadly to other forms of variation. The most common approach for estimating mutation rate is to use families to look for mutations carried by a child but not by either of his or her parents (Figure I). This approach has been carried out on selected loci up to whole genomes. However, it is important to note that this method can be confounded by false positives for which putative de novo variants are enriched [5Conrad D.F. et al.Variation in genome-wide mutation rates within and between human families.Nat. Genet. 2011; 43: 712-714Crossref PubMed Scopus (105) Google Scholar]. In addition, somatic mutations in offspring of the sequenced families cannot be distinguished from germline de novo variants. The other classical approach for estimating mutation rates is to look at fixed differences between species [9Li W.H. Tanimura M. The molecular clock runs more slowly in man than in apes and monkeys.Nature. 1987; 326: 93-96Crossref PubMed Google Scholar, 10Nachman M.W. Crowell S.L. Estimate of the mutation rate per nucleotide in humans.Genetics. 2000; 156: 297-304PubMed Google Scholar]. The mutation rate can then be calculated based on the estimated divergence time between the species (Figure I). Although this approach is not confounded by false positives or somatic mutations, there is uncertainty in the divergence time between humans and chimpanzees, the average generation time, and effective population sizes. Recently, other approaches for determining mutation rate have been described. One group constructed a model of microsatellite evolution and applied this model to estimate the time to the most recent common ancestor (MRCA) for microsatellite alleles [12Sun J.X. et al.A direct characterization of human mutation based on microsatellites.Nat. Genet. 2012; 44: 1161-1165Crossref PubMed Scopus (21) Google Scholar]. Because SNVs near the microsatellite have the same ancestry as the microsatellite, the mutation rate for SNVs could be calculated using the SNV differences between haplotypes and the time to the MRCA [12Sun J.X. et al.A direct characterization of human mutation based on microsatellites.Nat. Genet. 2012; 44: 1161-1165Crossref PubMed Scopus (21) Google Scholar]. Another approach to estimating mutation rate involves the identification of heterozygous mutations in large regions of homozygosity by recent descent (autozygosity) [7Campbell C.D. et al.Estimating the human mutation rate using autozygosity in a founder population.Nat. Genet. 2012; 44: 1277-1281Crossref PubMed Scopus (16) Google Scholar, 120Alkuraya F.S. Autozygome decoded.Genet. Med. 2010; 12: 765-771Abstract Full Text Full Text PDF PubMed Scopus (24) Google Scholar] (Figure I). Such regions are particularly abundant among founder populations, providing a means for estimating mutation rate from a recent common ancestor in populations such as the Hutterites, the Amish, and the Icelandic population. Although different in many ways, these two approaches have some important similarities. Both are less susceptible to false positive and somatic mutations than are analyses of de novo mutations in trios. In addition, both approaches estimate the time to the MRCA for segments of the genome in different ways, but benefit by studying haplotypes with a more recent coalescent time than humans and chimpanzees. In addition to the direct approaches in families, earlier studies used more indirect approaches to estimate mutation rate. Using fixed differences between the human and chimpanzee genomes (Box 1) yielded a mutation rate for SNVs of approximately 2.5 × 10−8 in pseudogenes, where selection is not a confounding factor [9Li W.H. Tanimura M. The molecular clock runs more slowly in man than in apes and monkeys.Nature. 1987; 326: 93-96Crossref PubMed Google Scholar, 10Nachman M.W. Crowell S.L. Estimate of the mutation rate per nucleotide in humans.Genetics. 2000; 156: 297-304PubMed Google Scholar]; this is over twofold higher than the rates estimated from direct approaches. However, more recent comparisons of the human, chimpanzee, and gorilla genomes bring the mutation rate estimates in line with what is observed in family-based analyses [11Scally A. et al.Insights into hominid evolution from the gorilla genome sequence.Nature. 2012; 483: 169-175Crossref PubMed Scopus (72) Google Scholar]. Another indirect approach estimated the mutation rate for SNVs to be 1.82 × 10−8 using inferred ancestry of nearby microsatellites [12Sun J.X. et al.A direct characterization of human mutation based on microsatellites.Nat. Genet. 2012; 44: 1161-1165Crossref PubMed Scopus (21) Google Scholar] (Box 1, Figure I). The difference between this mutation rate and those calculated with family information may be due to differences in filtering applied for SNVs or in sequencing methodology. Recent genome-wide studies of the SNV mutation rate in humans have started to converge (Table 1). Studies based on whole-genome sequencing and direct estimates of de novo mutations give an average SNV mutation rate of 1.16 × 10−8 mutations per base pair per generation [95% confidence interval (CI) of the mean: 1.11–1.22] in 96 total families [4Roach J.C. et al.Analysis of genetic inheritance in a family quartet by whole-genome sequencing.Science. 2010; 328: 636-639Crossref PubMed Scopus (366) Google Scholar, 5Conrad D.F. et al.Variation in genome-wide mutation rates within and between human families.Nat. Genet. 2011; 43: 712-714Crossref PubMed Scopus (105) Google Scholar, 6Kong A. et al.Rate of de novo mutations and the importance of father's age to disease risk.Nature. 2012; 488: 471-475Crossref PubMed Scopus (131) Google Scholar, 7Campbell C.D. et al.Estimating the human mutation rate using autozygosity in a founder population.Nat. Genet. 2012; 44: 1277-1281Crossref PubMed Scopus (16) Google Scholar, 8Michaelson Jacob J. et al.Whole-genome sequencing in autism identifies hot spots for de novo germline mutation.Cell. 2012; 151: 1431-1442Abstract Full Text Full Text PDF PubMed Scopus (23) Google Scholar] (Table 1). However, it is important to note that all of these studies involve substantial filtering of de novo variants to remove false positives and often exclude highly repetitive regions of the genome. Given the relevance of variants in protein-coding sequence to disease, it is also important to understand the mutation rate in exonic regions. Studies from targeted sequencing of exomes or other regions have reported higher mutation rates (1.31–2.17 × 10−8 mutations per base pair per generation) [13Awadalla P. et al.Direct measure of the de novo mutation rate in autism and schizophrenia cohorts.Am. J. Hum. Genet. 2010; 87: 316-324Abstract Full Text Full Text PDF PubMed Scopus (79) Google Scholar, 14Neale B.M. et al.Patterns and rates of exonic de novo mutations in autism spectrum disorders.Nature. 2012; 485: 242-245Crossref PubMed Scopus (199) Google Scholar, 15O’Roak B.J. et al.Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations.Nature. 2012; 485: 246-250Crossref PubMed Scopus (229) Google Scholar, 16Sanders S.J. et al.De novo mutations revealed by whole-exome sequencing are strongly associated with autism.Nature. 2012; 485: 237-241Crossref PubMed Scopus (206) Google Scholar]; this apparent increase may be due to several factors, as discussed below.Table 1Genome-wide estimates of SNV mutation rateTypeNumber of familiesμ(× 10−8)95% CI% PaternalRefsWhole genome11.100.68–1.704Roach J.C. et al.Analysis of genetic inheritance in a family quartet by whole-genome sequencing.Science. 2010; 328: 636-639Crossref PubMed Scopus (366) Google Scholar11.170.88–1.6292%5Conrad D.F. et al.Variation in genome-wide mutation rates within and between human families.Nat. Genet. 2011; 43: 712-714Crossref PubMed Scopus (105) Google Scholar10.970.67–1.3436%5Conrad D.F. et al.Variation in genome-wide mutation rates within and between human families.Nat. Genet. 2011; 43: 712-714Crossref PubMed Scopus (105) Google Scholar781.2076%6Kong A. et al.Rate of de novo mutations and the importance of father's age to disease risk.Nature. 2012; 488: 471-475Crossref PubMed Scopus (131) Google Scholar50.960.82–1.0985%7Campbell C.D. et al.Estimating the human mutation rate using autozygosity in a founder population.Nat. Genet. 2012; 44: 1277-1281Crossref PubMed Scopus (16) Google Scholar10aFamilies of monozygotic twins with autism.1.0074%8Michaelson Jacob J. et al.Whole-genome sequencing in autism identifies hot spots for de novo germline mutation.Cell. 2012; 151: 1431-1442Abstract Full Text Full Text PDF PubMed Scopus (23) Google ScholarTargeted resequencing of 430 Mbp570bHalf of these families have probands with autism or schizophrenia. Mutation rate is based on ‘neutral’ sites.1.360.34–2.7013Awadalla P. et al.Direct measure of the de novo mutation rate in autism and schizophrenia cohorts.Am. J. Hum. Genet. 2010; 87: 316-324Abstract Full Text Full Text PDF PubMed Scopus (79) Google ScholarWhole exome209cProbands are affected with autism.2.1781%15O’Roak B.J. et al.Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations.Nature. 2012; 485: 246-250Crossref PubMed Scopus (229) Google Scholar238dFamilies comprise proband with autism, unaffected sibling, and parents. Mutation rate for unaffected siblings is reported here.1.3116Sanders S.J. et al.De novo mutations revealed by whole-exome sequencing are strongly associated with autism.Nature. 2012; 485: 237-241Crossref PubMed Scopus (206) Google Scholar175cProbands are affected with autism.1.5014Neale B.M. et al.Patterns and rates of exonic de novo mutations in autism spectrum disorders.Nature. 2012; 485: 242-245Crossref PubMed Scopus (199) Google ScholarIndirect from microsatellites23eNumber of unrelated individuals.1.821.40–2.2812Sun J.X. et al.A direct characterization of human mutation based on microsatellites.Nat. Genet. 2012; 44: 1161-1165Crossref PubMed Scopus (21) Google Scholar512 Mbp of autozygosity51.200.89–1.437Campbell C.D. et al.Estimating the human mutation rate using autozygosity in a founder population.Nat. Genet. 2012; 44: 1277-1281Crossref PubMed Scopus (16) Google Scholara Families of monozygotic twins with autism.b Half of these families have probands with autism or schizophrenia. Mutation rate is based on ‘neutral’ sites.c Probands are affected with autism.d Families comprise proband with autism, unaffected sibling, and parents. Mutation rate for unaffected siblings is reported here.e Number of unrelated individuals. Open table in a new tab In addition to SNVs, there has been considerable effort in estimating the rates of formation of CNVs. Although CNVs are operationally defined as deletions and duplications of 50 bp or more [17Scherer S.W. et al.Challenges and standards in integrating surveys of structural variation.Nat. Genet. 2007; 39: S7-S15Crossref PubMed Scopus (171) Google Scholar], most studies have assessed de novo events only in the multi-kilobase pair range. As with SNVs, initial studies in this area focused on only a few loci. These analyses found that the locus mutation rate was higher for CNVs (2.5 × 10−6–1 × 10−4 mutations per locus per generation) compared with SNVs and that the rate varied by more than an order of magnitude between loci [18Lupski J.R. Genomic rearrangements and sporadic disease.Nat. Genet. 2007; 39: S43-S47Crossref PubMed Scopus (211) Google Scholar, 19Turner D.J. et al.Germline rates of de novo meiotic deletions and duplications causing several genomic disorders.Nat. Genet. 2008; 40: 90-95Crossref PubMed Scopus (141) Google Scholar]; data from mice suggest that the difference in rates between loci are even larger [20Egan C.M. et al.Recurrent DNA copy number variation in the laboratory mouse.Nat. Genet. 2007; 39: 1384-1389Crossref PubMed Scopus (79) Google Scholar]. A genome-wide analysis of large CNVs (>100 kbp) revealed a mutation rate of 1.2 × 10−2 CNVs per generation based on approximately 400 parent–offspring trios [21Itsara A. et al.De novo rates and selection of large copy number variation.Genome Res. 2010; 20: 1469-1481Crossref PubMed Scopus (85) Google Scholar]. A significantly higher mutation rate of 3.6 × 10−2 mutations per generation was observed for individuals with intellectual disability, probably because some of these de novo CNVs were influencing the development of the disorders observed in these individuals [22Hehir-Kwa J.Y. et al.De novo copy number variants associated with intellectual disability have a paternal origin and age bias.J. Med. Genet. 2011; 48: 776-778Crossref PubMed Scopus (18) Google Scholar]. Using high-density microarrays and population genetic approaches, the rate of CNV formation was estimated to be 3 × 10−2 for variants >500 bp [23Conrad D.F. et al.Origins and functional impact of copy number variation in the human genome.Nature. 2010; 464: 704-712Crossref PubMed Scopus (585) Google Scholar]. However, this rate is likely a lower boundary because selection will remove deleterious mutations from the population and most large CNVs are estimated to be deleterious [21Itsara A. et al.De novo rates and selection of large copy number variation.Genome Res. 2010; 20: 1469-1481Crossref PubMed Scopus (85) Google Scholar, 23Conrad D.F. et al.Origins and functional impact of copy number variation in the human genome.Nature. 2010; 464: 704-712Crossref PubMed Scopus (585) Google Scholar]. Notably, when considering the total number of mutated base pairs between SNVs and CNVs, CNVs account for the vast majority. New large CNVs (>100 kbp) are relatively rare compared with SNVs: one new large CNV per 42 births (95% Poisson CI: 23–97) [21Itsara A. et al.De novo rates and selection of large copy number variation.Genome Res. 2010; 20: 1469-1481Crossref PubMed Scopus (85) Google Scholar] compared with an average 61 new SNVs per birth (95% CI of the mean: 58–64) [5Conrad D.F. et al.Variation in genome-wide mutation rates within and between human families.Nat. Genet. 2011; 43: 712-714Crossref PubMed Scopus (105) Google Scholar, 6Kong A. et al.Rate of de novo mutations and the importance of father's age to disease risk.Nature. 2012; 488: 471-475Crossref PubMed Scopus (131) Google Scholar, 7Campbell C.D. et al.Estimating the human mutation rate using autozygosity in a founder population.Nat. Genet. 2012; 44: 1277-1281Crossref PubMed Scopus (16) Google Scholar, 8Michaelson Jacob J. et al.Whole-genome sequencing in autism identifies hot spots for de novo germline mutation.Cell. 2012; 151: 1431-1442Abstract Full Text Full Text PDF PubMed Scopus (23) Google Scholar] (Figure 1). The average number of base pairs affected by large CNVs is 8–25 kbp per gamete (16–50 kbp per birth) [21Itsara A. et al.De novo rates and selection of large copy number variation.Genome Res. 2010; 20: 1469-1481Crossref PubMed Scopus (85) Google Scholar], which is larger than the average of 30.5 bp per gamete observed for SNVs (61 bp per birth; Figure 1). It is important to note that the estimates for CNVs are based on microarray data that could not be used reliably to detect smaller CNVs (<100 kbp); therefore, the mutational properties and rates of formation of these smaller variants remain unknown. Comparisons between the human and chimpanzee genomes also revealed that insertions and deletions account for close to three times the number of bases that are different compared with SNVs (3% versus 1.23%) [24Chimpanzee Sequencing and Analysis ConsortiumInitial sequence of the chimpanzee genome and comparison with the human genome.Nature. 2005; 437: 69-87Crossref PubMed Scopus (974) Google Scholar]. Although caution must be exercised in the estimate of the de novo rate of CNVs, the data suggest a more than 100-fold differential between the number of base pairs affected (on average) per generation, yet only a threefold difference after 12 million years of evolution based on chimpanzee and human genome comparisons. This may reflect significant differences in the action of selection or radical rate changes since divergence for these different classes of mutation [25Marques-Bonet T. et al.A burst of segmental duplications in the genome of the African great ape ancestor.Nature. 2009; 457: 877-881Crossref PubMed Scopus (77) Google Scholar]. In addition to CNVs and SNVs, there are many other forms of genetic variation that arise by completely different mutational processes and, consequently, have distinct biases. The largest, of course, are aneuploidies (the duplication or deletion of an entire chromosome). Due to the severity of these mutations (the most well-studied aneuploidy is Down syndrome), most aneuploidies are lethal in utero. Studies of spontaneous abortions and embryos created with in vitro fertilization suggest that 30–60% of embryos and 0.3% of newborns have a chromosomal aneuploidy (reviewed in [26Nagaoka S.I. et al.Human aneuploidy: mechanisms and new insights into an age-old problem.Nat. Rev. Genet. 2012; 13: 493-504Crossref PubMed Scopus (37) Google Scholar]; Figure 1). Interestingly, there are substantial differences between chromosomes in the incidence of aneuploidy; trisomies of chromosomes 16, 18, 21, and the sex chromosomes are most prevalent [27Hassold T. Hunt P. To err (meiotically) is human: the genesis of human aneuploidy.Nat. Rev. Genet. 2001; 2: 280-291Crossref PubMed Scopus (831) Google Scholar]. Chromosomal aneuploidies are thought to primarily arise during meiosis I through several mechanisms. Most simply, homologous chromosomes can fail to pair or stay paired in meiosis, potentially due to lack of recombination events [28Henderson S.A. Edwards R.G. Chiasma frequency and maternal age in mammals.Nature. 1968; 218: 22-28Crossref PubMed Scopus (118) Google Scholar]. However, trisomies can also arise if sister chromatids improperly segregate during meiosis I [29Angell R.R. Predivision in human oocytes at meiosis I: a mechanism for trisomy formation in man.Hum. Genet. 1991; 86: 383-387Crossref PubMed Google Scholar] (Figure 1), and it appears as though different chromosomes may be primarily affected by different mechanisms [26Nagaoka S.I. et al.Human aneuploidy: mechanisms and new insights into an age-old problem.Nat. Rev. Genet. 2012; 13: 493-504Crossref PubMed Scopus (37) Google Scholar]. Other forms of genetic variation have been less well characterized, often due to methodological biases in their discovery leading to reduced sensitivity. The rate of small insertions and deletions or ‘indels’ has been reported as approximately 0.20 × 10−9 per site per generation for insertions and 0.53 × 10−9–0.58 × 10−9 per site per generation for deletions; this corresponds to approximately 6% of the SNV mutation rate [3Kondrashov A.S. Direct estimates of human per nucleotide mutation rates at 20 loci causing Mendelian diseases.Hum. Mutat. 2003; 21: 12-27Crossref PubMed Scopus (169) Google Scholar, 30Lynch M. Rate, molecular spectrum, and consequences of human mutation.Proc. Natl. Acad. Sci. U.S.A. 2010; 107: 961-968Crossref PubMed Scopus (123) Google Scholar] (Figure 1). Whole-genome sequence data from the 1000 Genomes Project suggested that each individual carries approximately one-tenth the number of indels compared with SNVs [31The 1000 Genomes Project ConsortiumAn integrated map of genetic variation from 1,092 human genomes.Nature. 2012; 491: 56-65Crossref PubMed Scopus (230) Google Scholar], but comparison of two Sanger-sequenced human genomes suggested a ratio closer
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