The clock-like accumulation of germline and somatic mutations can arise from the interplay of DNA damage and repair.

The rates at which mutations accumulate across human cell types vary. To identify causes of this variation, mutations are often decomposed into a combination of the single-base substitution (SBS) "signatures" observed in germline, soma, and tumors, with the idea that each signature corresponds to one or a small number of underlying mutagenic processes. Two such signatures turn out to be ubiquitous across cell types: SBS signature 1, which consists primarily of transitions at methylated CpG sites thought to be caused by spontaneous deamination, and the more diffuse SBS signature 5, which is of unknown etiology. In cancers, the number of mutations attributed to these 2 signatures accumulates linearly with age of diagnosis, and thus the signatures have been termed "clock-like." To better understand this clock-like behavior, we develop a mathematical model that includes DNA replication errors, unrepaired damage, and damage repaired incorrectly. We show that mutational signatures can exhibit clock-like behavior because cell divisions occur at a constant rate and/or because damage rates remain constant over time, and that these distinct sources can be teased apart by comparing cell lineages that divide at different rates. With this goal in mind, we analyze the rate of accumulation of mutations in multiple cell types, including soma as well as male and female germline. We find no detectable increase in SBS signature 1 mutations in neurons and only a very weak increase in mutations assigned to the female germline, but a significant increase with time in rapidly dividing cells, suggesting that SBS signature 1 is driven by rounds of DNA replication occurring at a relatively fixed rate. In contrast, SBS signature 5 increases with time in all cell types, including postmitotic ones, indicating that it accumulates independently of cell divisions; this observation points to errors in DNA repair as the key underlying mechanism. Thus, the two "clock-like" signatures observed across cell types likely have distinct origins, one set by rates of cell division, the other by damage rates.

Causal interpretations of family GWAS in the presence of heterogeneous effects.

Family-based genome-wide association studies (GWASs) are often claimed to provide an unbiased estimate of the average causal effects (or average treatment effects; ATEs) of alleles, on the basis of an analogy between the random transmission of alleles from parents to children and a randomized controlled trial. We show that this claim does not hold in general. Because Mendelian segregation only randomizes alleles among children of heterozygotes, the effects of alleles in the children of homozygotes are not observable. This feature will matter if an allele has different average effects in the children of homozygotes and heterozygotes, as can arise in the presence of gene-by-environment interactions, gene-by-gene interactions, or differences in linkage disequilibrium patterns. At a single locus, family-based GWAS can be thought of as providing an unbiased estimate of the average effect in the children of heterozygotes (i.e., a local average treatment effect; LATE). This interpretation does not extend to polygenic scores (PGSs), however, because different sets of SNPs are heterozygous in each family. Therefore, other than under specific conditions, the within-family regression slope of a PGS cannot be assumed to provide an unbiased estimate of the LATE for any subset or weighted average of families. In practice, the potential biases of a family-based GWAS are likely smaller than those that can arise from confounding in a standard, population-based GWAS, and so family studies remain important for the dissection of genetic contributions to phenotypic variation. Nonetheless, their causal interpretation is less straightforward than has been widely appreciated.

PRDM9 losses in vertebrates are coupled to those of paralogs ZCWPW1 and ZCWPW2.

In most mammals and likely throughout vertebrates, the gene PRDM9 specifies the locations of meiotic double strand breaks; in mice and humans at least, it also aids in their repair. For both roles, many of the molecular partners remain unknown. Here, we take a phylogenetic approach to identify genes that may be interacting with PRDM9 by leveraging the fact that PRDM9 arose before the origin of vertebrates but was lost many times, either partially or entirely-and with it, its role in recombination. As a first step, we characterize PRDM9 domain composition across 446 vertebrate species, inferring at least 13 independent losses. We then use the interdigitation of PRDM9 orthologs across vertebrates to test whether it coevolved with any of 241 candidate genes coexpressed with PRDM9 in mice or associated with recombination phenotypes in mammals. Accounting for the phylogenetic relationship among a subsample of 189 species, we find two genes whose presence and absence is unexpectedly coincident with that of PRDM9: ZCWPW1, which was recently shown to facilitate double strand break repair, and its paralog ZCWPW2, as well as, more tentatively, TEX15 and FBXO47ZCWPW2 is expected to be recruited to sites of PRDM9 binding; its tight coevolution with PRDM9 across vertebrates suggests that it is a key interactor within mammals and beyond, with a role either in recruiting the recombination machinery or in double strand break repair.

The evolution of group differences in changing environments.

The selection pressures that have shaped the evolution of complex traits in humans remain largely unknown, and in some contexts highly contentious, perhaps above all where they concern mean trait differences among groups. To date, the discussion has focused on whether such group differences have any genetic basis, and if so, whether they are without fitness consequences and arose via random genetic drift, or whether they were driven by selection for different trait optima in different environments. Here, we highlight a plausible alternative: that many complex traits evolve under stabilizing selection in the face of shifting environmental effects. Under this scenario, there will be rapid evolution at the loci that contribute to trait variation, even when the trait optimum remains the same. These considerations underscore the strong assumptions about environmental effects that are required in ascribing trait differences among groups to genetic differences.

A comparison of humans and baboons suggests germline mutation rates do not track cell divisions.

In humans, most germline mutations are inherited from the father. This observation has been widely interpreted as reflecting the replication errors that accrue during spermatogenesis. If so, the male bias in mutation should be substantially lower in a closely related species with similar rates of spermatogonial stem cell divisions but a shorter mean age of reproduction. To test this hypothesis, we resequenced two 3-4 generation nuclear families (totaling 29 individuals) of olive baboons (Papio anubis), who reproduce at approximately 10 years of age on average, and analyzed the data in parallel with three 3-generation human pedigrees (26 individuals). We estimated a mutation rate per generation in baboons of 0.57×10-8 per base pair, approximately half that of humans. Strikingly, however, the degree of male bias in germline mutations is approximately 4:1, similar to that of humans-indeed, a similar male bias is seen across mammals that reproduce months, years, or decades after birth. These results mirror the finding in humans that the male mutation bias is stable with parental ages and cast further doubt on the assumption that germline mutations track cell divisions. Our mutation rate estimates for baboons raise a further puzzle, suggesting a divergence time between apes and Old World monkeys of 65 million years, too old to be consistent with the fossil record; reconciling them now requires not only a slowdown of the mutation rate per generation in humans but also in baboons.

Signatures of replication timing, recombination, and sex in the spectrum of rare variants on the human X chromosome and autosomes.

The sources of human germline mutations are poorly understood. Part of the difficulty is that mutations occur very rarely, and so direct pedigree-based approaches remain limited in the numbers that they can examine. To address this problem, we consider the spectrum of low-frequency variants in a dataset (Genome Aggregation Database, gnomAD) of 13,860 human X chromosomes and autosomes. X-autosome differences are reflective of germline sex differences and have been used extensively to learn about male versus female mutational processes; what is less appreciated is that they also reflect chromosome-level biochemical features that differ between the X and autosomes. We tease these components apart by comparing the mutation spectrum in multiple genomic compartments on the autosomes and between the X and autosomes. In so doing, we are able to ascribe specific mutation patterns to replication timing and recombination and to identify differences in the types of mutations that accrue in males and females. In particular, we identify C > G as a mutagenic signature of male meiotic double-strand breaks on the X, which may result from late repair. Our results show how biochemical processes of damage and repair in the germline interact with sex-specific life history traits to shape mutation patterns on both the X chromosome and autosomes.

Overlooked roles of DNA damage and maternal age in generating human germline mutations.

The textbook view that most germline mutations in mammals arise from replication errors is indirectly supported by the fact that there are both more mutations and more cell divisions in the male than in the female germline. When analyzing large de novo mutation datasets in humans, we find multiple lines of evidence that call that view into question. Notably, despite the drastic increase in the ratio of male to female germ cell divisions after the onset of spermatogenesis, even young fathers contribute three times more mutations than young mothers, and this ratio barely increases with parental age. This surprising finding points to a substantial contribution of damage-induced mutations. Indeed, C-to-G transversions and CpG transitions, which together constitute over one-fourth of all base substitution mutations, show genomic distributions and sex-specific age dependencies indicative of double-strand break repair and methylation-associated damage, respectively. Moreover, we find evidence that maternal age at conception influences the mutation rate both because of the accumulation of damage in oocytes and potentially through an influence on the number of postzygotic mutations in the embryo. These findings reveal underappreciated roles of DNA damage and maternal age in the genesis of human germline mutations.

Correction: The population genetics of human disease: The case of recessive, lethal mutations.

[This corrects the article DOI: 10.1371/journal.pgen.1006915.].

Identifying genetic variants that affect viability in large cohorts.

A number of open questions in human evolutionary genetics would become tractable if we were able to directly measure evolutionary fitness. As a step towards this goal, we developed a method to examine whether individual genetic variants, or sets of genetic variants, currently influence viability. The approach consists in testing whether the frequency of an allele varies across ages, accounting for variation in ancestry. We applied it to the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort and to the parents of participants in the UK Biobank. Across the genome, we found only a few common variants with large effects on age-specific mortality: tagging the APOE ε4 allele and near CHRNA3. These results suggest that when large, even late-onset effects are kept at low frequency by purifying selection. Testing viability effects of sets of genetic variants that jointly influence 1 of 42 traits, we detected a number of strong signals. In participants of the UK Biobank of British ancestry, we found that variants that delay puberty timing are associated with a longer parental life span (P~6.2 × 10-6 for fathers and P~2.0 × 10-3 for mothers), consistent with epidemiological studies. Similarly, variants associated with later age at first birth are associated with a longer maternal life span (P~1.4 × 10-3). Signals are also observed for variants influencing cholesterol levels, risk of coronary artery disease (CAD), body mass index, as well as risk of asthma. These signals exhibit consistent effects in the GERA cohort and among participants of the UK Biobank of non-British ancestry. We also found marked differences between males and females, most notably at the CHRNA3 locus, and variants associated with risk of CAD and cholesterol levels. Beyond our findings, the analysis serves as a proof of principle for how upcoming biomedical data sets can be used to learn about selection effects in contemporary humans.

The population genetics of human disease: The case of recessive, lethal mutations.

Do the frequencies of disease mutations in human populations reflect a simple balance between mutation and purifying selection? What other factors shape the prevalence of disease mutations? To begin to answer these questions, we focused on one of the simplest cases: recessive mutations that alone cause lethal diseases or complete sterility. To this end, we generated a hand-curated set of 417 Mendelian mutations in 32 genes reported to cause a recessive, lethal Mendelian disease. We then considered analytic models of mutation-selection balance in infinite and finite populations of constant sizes and simulations of purifying selection in a more realistic demographic setting, and tested how well these models fit allele frequencies estimated from 33,370 individuals of European ancestry. In doing so, we distinguished between CpG transitions, which occur at a substantially elevated rate, and three other mutation types. Intriguingly, the observed frequency for CpG transitions is slightly higher than expectation but close, whereas the frequencies observed for the three other mutation types are an order of magnitude higher than expected, with a bigger deviation from expectation seen for less mutable types. This discrepancy is even larger when subtle fitness effects in heterozygotes or lethal compound heterozygotes are taken into account. In principle, higher than expected frequencies of disease mutations could be due to widespread errors in reporting causal variants, compensation by other mutations, or balancing selection. It is unclear why these factors would have a greater impact on disease mutations that occur at lower rates, however. We argue instead that the unexpectedly high frequency of disease mutations and the relationship to the mutation rate likely reflect an ascertainment bias: of all the mutations that cause recessive lethal diseases, those that by chance have reached higher frequencies are more likely to have been identified and thus to have been included in this study. Beyond the specific application, this study highlights the parameters likely to be important in shaping the frequencies of Mendelian disease alleles.

Human Germline Mutation and the Erratic Evolutionary Clock.

Our understanding of the chronology of human evolution relies on the "molecular clock" provided by the steady accumulation of substitutions on an evolutionary lineage. Recent analyses of human pedigrees have called this understanding into question by revealing unexpectedly low germline mutation rates, which imply that substitutions accrue more slowly than previously believed. Translating mutation rates estimated from pedigrees into substitution rates is not as straightforward as it may seem, however. We dissect the steps involved, emphasizing that dating evolutionary events requires not "a mutation rate" but a precise characterization of how mutations accumulate in development in males and females-knowledge that remains elusive.

Interpreting the Dependence of Mutation Rates on Age and Time.

Mutations can originate from the chance misincorporation of nucleotides during DNA replication or from DNA lesions that arise between replication cycles and are not repaired correctly. We introduce a model that relates the source of mutations to their accumulation with cell divisions, providing a framework for understanding how mutation rates depend on sex, age, and cell division rate. We show that the accrual of mutations should track cell divisions not only when mutations are replicative in origin but also when they are non-replicative and repaired efficiently. One implication is that observations from diverse fields that to date have been interpreted as pointing to a replicative origin of most mutations could instead reflect the accumulation of mutations arising from endogenous reactions or exogenous mutagens. We further find that only mutations that arise from inefficiently repaired lesions will accrue according to absolute time; thus, unless life history traits co-vary, the phylogenetic "molecular clock" should not be expected to run steadily across species.

Variation in the molecular clock of primates.

Events in primate evolution are often dated by assuming a constant rate of substitution per unit time, but the validity of this assumption remains unclear. Among mammals, it is well known that there exists substantial variation in yearly substitution rates. Such variation is to be expected from differences in life history traits, suggesting it should also be found among primates. Motivated by these considerations, we analyze whole genomes from 10 primate species, including Old World Monkeys (OWMs), New World Monkeys (NWMs), and apes, focusing on putatively neutral autosomal sites and controlling for possible effects of biased gene conversion and methylation at CpG sites. We find that substitution rates are up to 64% higher in lineages leading from the hominoid-NWM ancestor to NWMs than to apes. Within apes, rates are ∼2% higher in chimpanzees and ∼7% higher in the gorilla than in humans. Substitution types subject to biased gene conversion show no more variation among species than those not subject to it. Not all mutation types behave similarly, however; in particular, transitions at CpG sites exhibit a more clocklike behavior than do other types, presumably because of their nonreplicative origin. Thus, not only the total rate, but also the mutational spectrum, varies among primates. This finding suggests that events in primate evolution are most reliably dated using CpG transitions. Taking this approach, we estimate the human and chimpanzee divergence time is 12.1 million years,​ and the human and gorilla divergence time is 15.1 million years​.

A genetic method for dating ancient genomes provides a direct estimate of human generation interval in the last 45,000 years.

The study of human evolution has been revolutionized by inferences from ancient DNA analyses. Key to these studies is the reliable estimation of the age of ancient specimens. High-resolution age estimates can often be obtained using radiocarbon dating, and, while precise and powerful, this method has some biases, making it of interest to directly use genetic data to infer a date for samples that have been sequenced. Here, we report a genetic method that uses the recombination clock. The idea is that an ancient genome has evolved less than the genomes of present-day individuals and thus has experienced fewer recombination events since the common ancestor. To implement this idea, we take advantage of the insight that all non-Africans have a common heritage of Neanderthal gene flow into their ancestors. Thus, we can estimate the date since Neanderthal admixture for present-day and ancient samples simultaneously and use the difference as a direct estimate of the ancient specimen's age. We apply our method to date five Upper Paleolithic Eurasian genomes with radiocarbon dates between 12,000 and 45,000 y ago and show an excellent correlation of the genetic and (14)C dates. By considering the slope of the correlation between the genetic dates, which are in units of generations, and the (14)C dates, which are in units of years, we infer that the mean generation interval in humans over this period has been 26-30 y. Extensions of this methodology that use older shared events may be applicable for dating beyond the radiocarbon frontier.

Variation in Rural African Gut Microbiota Is Strongly Correlated with Colonization by Entamoeba and Subsistence.

The human gut microbiota is impacted by host nutrition and health status and therefore represents a potentially adaptive phenotype influenced by metabolic and immune constraints. Previous studies contrasting rural populations in developing countries to urban industrialized ones have shown that industrialization is strongly correlated with patterns in human gut microbiota; however, we know little about the relative contribution of factors such as climate, diet, medicine, hygiene practices, host genetics, and parasitism. Here, we focus on fine-scale comparisons of African rural populations in order to (i) contrast the gut microbiota of populations inhabiting similar environments but having different traditional subsistence modes and either shared or distinct genetic ancestry, and (ii) examine the relationship between gut parasites and bacterial communities. Characterizing the fecal microbiota of Pygmy hunter-gatherers as well as Bantu individuals from both farming and fishing populations in Southwest Cameroon, we found that the gut parasite Entamoeba is significantly correlated with microbiome composition and diversity. We show that across populations, colonization by this protozoa can be predicted with 79% accuracy based on the composition of an individual's gut microbiota, and that several of the taxa most important for distinguishing Entamoeba absence or presence are signature taxa for autoimmune disorders. We also found gut communities to vary significantly with subsistence mode, notably with some taxa previously shown to be enriched in other hunter-gatherers groups (in Tanzania and Peru) also discriminating hunter-gatherers from neighboring farming or fishing populations in Cameroon.

Determinants of mutation rate variation in the human germline.

Because germline mutations are the source of all evolutionary adaptations and heritable diseases, characterizing their properties and the rate at which they arise across individuals is of fundamental importance for human genetics. After decades during which estimates were based on indirect approaches, notably on inferences from evolutionary patterns, it is now feasible to count de novo mutations in transmissions from parents to offspring. Surprisingly, this direct approach yields a mutation rate that is twofold lower than previous estimates, calling into question our understanding of the chronology of human evolution and raising the possibility that mutation rates have evolved relatively rapidly. Here, we bring together insights from studies of human genetics and molecular evolution, focusing on where they conflict and what the discrepancies tell us about important open questions. We begin by outlining various methods for studying the properties of mutations in humans. We review what we have learned from their applications about genomic factors that influence mutation rates and the effects of sex, age, and other sources of interindividual variation. We then consider the mutation rate as a product of evolution and discuss how and why it may have changed over time in primates.

Different selective pressures shape the evolution of Toll-like receptors in human and African great ape populations.

The study of the genetic and selective landscape of immunity genes across primates can provide insight into the existing differences in susceptibility to infection observed between human and non-human primates. Here, we explored how selection has driven the evolution of a key family of innate immunity receptors, the Toll-like receptors (TLRs), in African great ape species. We sequenced the 10 TLRs in various populations of chimpanzees and gorillas, and analysed these data jointly with a human data set. We found that purifying selection has been more pervasive in great apes than in humans. Furthermore, in chimpanzees and gorillas, purifying selection has targeted TLRs irrespectively of whether they are endosomal or cell surface, in contrast to humans where strong selective constraints are restricted to endosomal TLRs. These observations suggest important differences in the relative importance of TLR-mediated pathogen sensing, such as that of recognition of flagellated bacteria by TLR5, between humans and great apes. Lastly, we used a population genetics-phylogenetics method that jointly analyses polymorphism and divergence data to detect fine-scale variation in selection pressures at specific codons within TLR genes. We identified different codons at different TLRs as being under positive selection in each species, highlighting that functional variation at these genes has conferred a selective advantage in immunity to infection to specific primate species. Overall, this study showed that the degree of selection driving the evolution of TLRs has largely differed between human and non-human primates, increasing our knowledge on their respective biological contribution to host defence in the natural setting.

TroX: a new method to learn about the genesis of aneuploidy from trisomic products of conception.

MOTIVATION: An estimated 10-30% of clinically recognized conceptions are aneuploid, leading to spontaneous miscarriages, in vitro fertilization failures and, when viable, severe developmental disabilities. With the ongoing reduction in the cost of genotyping and DNA sequencing, the use of high-density single nucleotide polymorphism (SNP) markers for clinical diagnosis of aneuploidy and biomedical research into its causes is becoming common practice. A reliable, flexible and computationally feasible method for inferring the sources of aneuploidy is thus crucial. RESULTS: We propose a new method, TroX, for analyzing human trisomy data using high density SNP markers from a trisomic individual or product of conception and one parent. Using a hidden Markov model, we infer the stage of the meiotic error (I or II) and the individual in which non-disjunction event occurred, as well as the crossover locations on the trisomic chromosome. A novel and important feature of the method is its reliance on data from the proband and only one parent, reducing the experimental cost by a third and enabling a larger set of data to be used. We evaluate our method by applying it to simulated trio data as well as to genotype data for 282 trios that include a child trisomic for chromosome 21. The analyses show the method to be highly reliable even when data from only one parent are available. With the increasing availability of DNA samples from mother and fetus, application of approaches such as ours should yield unprecedented insights into the genetic risk factors for aneuploidy. AVAILABILITY AND IMPLEMENTATION: An R package implementing TroX is available for download at http://przeworski.uchicago.edu/.

Evolutionary history inferred from the de novo assembly of a nonmodel organism, the blue-eyed black lemur.

Lemurs, the living primates most distantly related to humans, demonstrate incredible diversity in behaviour, life history patterns and adaptive traits. Although many lemur species are endangered within their native Madagascar, there is no high-quality genome assembly from this taxon, limiting population and conservation genetic studies. One critically endangered lemur is the blue-eyed black lemur Eulemur flavifrons. This species is fixed for blue irises, a convergent trait that evolved at least four times in primates and was subject to positive selection in humans, where 5' regulatory variation of OCA2 explains most of the brown/blue eye colour differences. We built a de novo genome assembly for E. flavifrons, providing the most complete lemur genome to date, and a high confidence consensus sequence for close sister species E. macaco, the (brown-eyed) black lemur. From diversity and divergence patterns across the genomes, we estimated a recent split time of the two species (160 Kya) and temporal fluctuations in effective population sizes that accord with known environmental changes. By looking for regions of unusually low diversity, we identified potential signals of directional selection in E. flavifrons at MITF, a melanocyte development gene that regulates OCA2 and has previously been associated with variation in human iris colour, as well as at several other genes involved in melanin biosynthesis in mammals. Our study thus illustrates how whole-genome sequencing of a few individuals can illuminate the demographic and selection history of nonmodel species.

Revisiting an old riddle: what determines genetic diversity levels within species?

Understanding why some species have more genetic diversity than others is central to the study of ecology and evolution, and carries potentially important implications for conservation biology. Yet not only does this question remain unresolved, it has largely fallen into disregard. With the rapid decrease in sequencing costs, we argue that it is time to revive it.