The abundance of deleterious polymorphisms in humans

Mitochondrial DNA Genomes Reveal Relaxed Purifying Selection During Human Population Expansion after the Last Glacial Maximum

Modern humans have experienced explosive population growth in the past thousand years. We hypothesized that recent human populations have inhabited environments with relaxation of selective constraints, possibly due to the more abundant food supply after the Last Glacial Maximum. The ratio of nonsynonymous to synonymous mutations (N/S ratio) is a useful and common statistic for measuring selective constraints. In this study, we reconstructed a high-resolution phylogenetic tree using a total of 26,419 East Eurasian mitochondrial DNA genomes, which were further classified into expansion and nonexpansion groups on the basis of the frequencies of their founder lineages. We observed a much higher N/S ratio in the expansion group, especially for nonsynonymous mutations with moderately deleterious effects, indicating a weaker effect of purifying selection in the expanded clades. However, this observation on N/S ratio was unlikely in computer simulations where all individuals were under the same selective constraints. Thus, we argue that the expanded populations were subjected to weaker selective constraints than the nonexpanded populations were. The mildly deleterious mutations were retained during population expansion, which could have a profound impact on present-day disease patterns.

Severity of effect considerations regarding the use of mutation as a toxicological endpoint for risk assessment: A report from the 8th International Workshop on Genotoxicity Testing (IWGT)

Exposure levels without appreciable human health risk may be determined by dividing a point of departure on a dose-response curve (e.g., benchmark dose) by a composite adjustment factor (AF). An "effect severity" AF (ESAF) is employed in some regulatory contexts. An ESAF of 10 may be incorporated in the derivation of a health-based guidance value (HBGV) when a "severe" toxicological endpoint, such as teratogenicity, irreversible reproductive effects, neurotoxicity, or cancer was observed in the reference study. Although mutation data have been used historically for hazard identification, this endpoint is suitable for quantitative dose-response modeling and risk assessment. As part of the 8th International Workshops on Genotoxicity Testing, a sub-group of the Quantitative Analysis Work Group (WG) explored how the concept of effect severity could be applied to mutation. To approach this question, the WG reviewed the prevailing regulatory guidance on how an ESAF is incorporated into risk assessments, evaluated current knowledge of associations between germline or somatic mutation and severe disease risk, and mined available data on the fraction of human germline mutations expected to cause severe disease. Based on this review and given that mutations are irreversible and some cause severe human disease, in regulatory settings where an ESAF is used, a majority of the WG recommends applying an ESAF value between 2 and 10 when deriving a HBGV from mutation data. This recommendation may need to be revisited in the future if direct measurement of disease-causing mutations by error-corrected next generation sequencing clarifies selection of ESAF values.

The Extent of Edgetic Perturbations in the Human Interactome Caused by Population-Specific Mutations

Until recently, efforts in population genetics have been focused primarily on people of European ancestry. To attenuate this bias, global population studies, such as the 1000 Genomes Project, have revealed differences in genetic variation across ethnic groups. How many of these differences can be attributed to population-specific traits? To answer this question, the mutation data must be linked with functional outcomes. A new "edgotype" concept has been proposed, which emphasizes the interaction-specific, "edgetic", perturbations caused by mutations in the interacting proteins. In this work, we performed systematic in silico edgetic profiling of ~50,000 non-synonymous SNVs (nsSNVs) from the 1000 Genomes Project by leveraging our semi-supervised learning approach SNP-IN tool on a comprehensive set of over 10,000 protein interaction complexes. We interrogated the functional roles of the variants and their impact on the human interactome and compared the results with the pathogenic variants disrupting PPIs in the same interactome. Our results demonstrated that a considerable number of nsSNVs from healthy populations could rewire the interactome. We also showed that the proteins enriched with interaction-disrupting mutations were associated with diverse functions and had implications in a broad spectrum of diseases. Further analysis indicated that distinct gene edgetic profiles among major populations could shed light on the molecular mechanisms behind the population phenotypic variances. Finally, the network analysis revealed that the disease-associated modules surprisingly harbored a higher density of interaction-disrupting mutations from healthy populations. The variation in the cumulative network damage within these modules could potentially account for the observed disparities in disease susceptibility, which are distinctly specific to certain populations. Our work demonstrates the feasibility of a large-scale in silico edgetic study, and reveals insights into the orchestrated play of population-specific mutations in the human interactome.

Harmful mutation load in the mitochondrial genomes of cattle breeds

Objective

Domestication of wild animals results in a reduction in the effective population size, and this could affect the deleterious mutation load of domesticated breeds. Furthermore, artificial selection will also contribute to the accumulation of deleterious mutations due to the increased rate of inbreeding among these animals. The process of domestication, founder population size, and artificial selection differ between cattle breeds, which could lead to a variation in their deleterious mutation loads. We investigated this using mitochondrial genome data from 364 animals belonging to 18 cattle breeds of the world.

Results

Our analysis revealed more than a fivefold difference in the deleterious mutation load among cattle breeds. We also observed a negative correlation between the breed age and the proportion of deleterious amino acid-changing polymorphisms. This suggests a proportionally higher deleterious SNPs in young breeds compared to older breeds. Our results highlight the magnitude of difference in the deleterious mutations present in the mitochondrial genomes of various breeds. The results of this study could be useful in predicting the rate of incidence of genetic diseases in different breeds.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13104-021-05664-y.

Abundance of clinical variants in exons included in multiple transcripts

Previous studies showed that the magnitude of selection pressure in constitutive exons is higher than that in alternatively spliced exons. The intensity of selection was also shown to be depended on the inclusion level of exons: the number of transcripts that include an exon. Here, we examined how the difference in selection pressure influences the patterns of clinical variants in human exons. Our analysis revealed a positive relationship between exon inclusion level and the abundance of pathogenic variants. The proportion of pathogenic variants in the exons that are included in > 10 transcripts was 6.8 times higher than those in the exons included in only one transcript. This suggests that the mutations occurring in the exons included in multiple transcripts are more deleterious than those present in the exons included in one transcript. The findings of this study highlight that the exon inclusion level could be used to predict the mutations associated with diseases.

A Temporal Perspective on the Interplay of Demography and Selection on Deleterious Variation in Humans

When mutations have small effects on fitness, population size plays an important role in determining the amount and nature of deleterious genetic variation. The extent to which recent population size changes have impacted deleterious variation in humans has been a question of considerable interest and debate. An emerging consensus is that the Out-of-Africa bottleneck and subsequent growth events have been too short to cause meaningful differences in genetic load between populations; though changes in the number and average frequencies of deleterious variants have taken place. To provide more support for this view and to offer additional insight into the divergent evolution of deleterious variation across populations, we numerically solve time-inhomogeneous diffusion equations and study the temporal dynamics of the frequency spectra in models of population size change for modern humans. We observe how the response to demographic change differs by the strength of selection, and we then assess whether similar patterns are observed in exome sequence data from 33,370 and 5203 individuals of non-Finnish European and West African ancestry, respectively. Our theoretical results highlight how even simple summaries of the frequency spectrum can have complex responses to demographic change. These results support the finding that some apparent discrepancies between previous results have been driven by the behaviors of the precise summaries of deleterious variation. Further, our empirical results make clear the difficulty of inferring slight differences in frequency spectra using recent next-generation sequence data.

The effects of sample size on population genomic analyses--implications for the tests of neutrality

BACKGROUND

One of the fundamental measures of molecular genetic variation is the Watterson's estimator (θ), which is based on the number of segregating sites. The estimation of θ is unbiased only under neutrality and constant population growth. It is well known that the estimation of θ is biased when these assumptions are violated. However, the effects of sample size in modulating the bias was not well appreciated.

RESULTS

We examined this issue in detail based on large-scale exome data and robust simulations. Our investigation revealed that sample size appreciably influences θ estimation and this effect was much higher for constrained genomic regions than that of neutral regions. For instance, θ estimated for synonymous sites using 512 human exomes was 1.9 times higher than that obtained using 16 exomes. However, this difference was 2.5 times for the nonsynonymous sites of the same data. We observed a positive correlation between the rate of increase in θ estimates (with respect to the sample size) and the magnitude of selection pressure. For example, θ estimated for the nonsynonymous sites of highly constrained genes (dN/dS < 0.1) using 512 exomes was 3.6 times higher than that estimated using 16 exomes. In contrast this difference was only 2 times for the less constrained genes (dN/dS > 0.9).

CONCLUSIONS

The results of this study reveal the extent of underestimation owing to small sample sizes and thus emphasize the importance of sample size in estimating a number of population genomic parameters. Our results have serious implications for neutrality tests such as Tajima D, Fu-Li D and those based on the McDonald and Kreitman test: Neutrality Index and the fraction of adaptive substitutions. For instance, use of 16 exomes produced 2.4 times higher proportion of adaptive substitutions compared to that obtained using 512 exomes (24% vs 10 %).

The distribution of deleterious genetic variation in human populations

Population genetic studies suggest that most amino-acid changing mutations are deleterious. Such mutations are of tremendous interest in human population genetics as they are important for the evolutionary process and may contribute risk to common disease. Genomic studies over the past 5 years have documented differences across populations in the number of heterozygous deleterious genotypes, number of homozygous derived deleterious genotypes, number of deleterious segregating sites and proportion of sites that are potentially deleterious. These differences have been attributed to population history affecting the ability of natural selection to remove deleterious variants from the population. However, recent studies have suggested that the genetic load is the same across populations and that the efficacy of natural selection has not differed across human populations. Here I show that these observations are not incompatible with each other and that the apparent differences are due to examining different features of the genetic data and differing definitions of terms.

Inference of Evolutionary Forces Acting on Human Biological Pathways

Because natural selection is likely to act on multiple genes underlying a given phenotypic trait, we study here the potential effect of ongoing and past selection on the genetic diversity of human biological pathways. We first show that genes included in gene sets are generally under stronger selective constraints than other genes and that their evolutionary response is correlated. We then introduce a new procedure to detect selection at the pathway level based on a decomposition of the classical McDonald-Kreitman test extended to multiple genes. This new test, called 2DNS, detects outlier gene sets and takes into account past demographic effects and evolutionary constraints specific to gene sets. Selective forces acting on gene sets can be easily identified by a mere visual inspection of the position of the gene sets relative to their two-dimensional null distribution. We thus find several outlier gene sets that show signals of positive, balancing, or purifying selection but also others showing an ancient relaxation of selective constraints. The principle of the 2DNS test can also be applied to other genomic contrasts. For instance, the comparison of patterns of polymorphisms private to African and non-African populations reveals that most pathways show a higher proportion of nonsynonymous mutations in non-Africans than in Africans, potentially due to different demographic histories and selective pressures.

Using the plurality of codon positions to identify deleterious variants in human exomes

MOTIVATION

A codon position could perform different or multiple roles in alternative transcripts of a gene. For instance, a non-synonymous position in one transcript could be a synonymous site in another. Alternatively, a position could remain as non-synonymous in multiple transcripts. Here we examined the impact of codon position plurality on the frequency of deleterious single-nucleotide variations (SNVs) using data from 6500 human exomes.

RESULTS

Our results showed that the proportion of deleterious SNVs was more than 2-fold higher in positions that remain non-synonymous in multiple transcripts compared with that observed in positions that are non-synonymous in one or some transcript(s) and synonymous or intronic in other(s). Furthermore, we observed a positive relationship between the fraction of deleterious non-synonymous SNVs and the number of proteins (alternative splice variants) affected. These results demonstrate that the plurality of codon positions is an important attribute, which could be useful in identifying mutations associated with diseases.

CONTACT

s.subramanian@griffith.edu.au

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Characteristics of neutral and deleterious protein-coding variation among individuals and populations

Whole-genome and exome data sets continue to be produced at a frenetic pace, resulting in massively large catalogs of human genomic variation. However, a clear picture of the characteristics and patterns of neutral and deleterious variation within and between populations has yet to emerge, given that recent large-scale sequencing studies have often emphasized different aspects of the data and sometimes appear to have conflicting conclusions. Here, we comprehensively studied characteristics of protein-coding variation in high-coverage exome sequence data from 6,515 European American (EA) and African American (AA) individuals. We developed an unbiased approach to identify putatively deleterious variants and investigated patterns of neutral and deleterious single-nucleotide variants and alleles between individuals and populations. We show that there are substantial differences in the composition of genotypes between EA and AA populations and that small but statistically significant differences exist in the average number of deleterious alleles carried by EA and AA individuals. Furthermore, we performed extensive simulations to delineate the temporal dynamics of deleterious alleles for a broad range of demographic models and use these data to inform the interpretation of empirical patterns of deleterious variation. Finally, we illustrate that the effects of demographic perturbations, such as bottlenecks and expansions, often manifest in opposing patterns of neutral and deleterious variation depending on whether the focus is on populations or individuals. Our results clarify seemingly disparate empirical characteristics of protein-coding variation and provide substantial insights into how natural selection and demographic history have patterned neutral and deleterious variation within and between populations.

Design and development of exome capture sequencing for the domestic pig (Sus scrofa)

Background

The domestic pig (Sus scrofa) is both an important livestock species and a model for biomedical research. Exome sequencing has accelerated identification of protein-coding variants underlying phenotypic traits in human and mouse. We aimed to develop and validate a similar resource for the pig.

Results

We developed probe sets to capture pig exonic sequences based upon the current Ensembl pig gene annotation supplemented with mapped expressed sequence tags (ESTs) and demonstrated proof-of-principle capture and sequencing of the pig exome in 96 pigs, encompassing 24 capture experiments. For most of the samples at least 10x sequence coverage was achieved for more than 90% of the target bases. Bioinformatic analysis of the data revealed over 236,000 high confidence predicted SNPs and over 28,000 predicted indels.

Conclusions

We have achieved coverage statistics similar to those seen with commercially available human and mouse exome kits. Exome capture in pigs provides a tool to identify coding region variation associated with production traits, including loss of function mutations which may explain embryonic and neonatal losses, and to improve genomic assemblies in the vicinity of protein coding genes in the pig.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-550) contains supplementary material, which is available to authorized users.

Genetic diversity in the interference selection limit

Pervasive natural selection can strongly influence observed patterns of genetic variation, but these effects remain poorly understood when multiple selected variants segregate in nearby regions of the genome. Classical population genetics fails to account for interference between linked mutations, which grows increasingly severe as the density of selected polymorphisms increases. Here, we describe a simple limit that emerges when interference is common, in which the fitness effects of individual mutations play a relatively minor role. Instead, similar to models of quantitative genetics, molecular evolution is determined by the variance in fitness within the population, defined over an effectively asexual segment of the genome (a "linkage block"). We exploit this insensitivity in a new "coarse-grained" coalescent framework, which approximates the effects of many weakly selected mutations with a smaller number of strongly selected mutations that create the same variance in fitness. This approximation generates accurate and efficient predictions for silent site variability when interference is common. However, these results suggest that there is reduced power to resolve individual selection pressures when interference is sufficiently widespread, since a broad range of parameters possess nearly identical patterns of silent site variability.

On the accumulation of deleterious mutations during range expansions

We investigate the effect of spatial range expansions on the evolution of fitness when beneficial and deleterious mutations cosegregate. We perform individual-based simulations of 1D and 2D range expansions and complement them with analytical approximations for the evolution of mean fitness at the edge of the expansion. We find that deleterious mutations accumulate steadily on the wave front during range expansions, thus creating an expansion load. Reduced fitness due to the expansion load is not restricted to the wave front, but occurs over a large proportion of newly colonized habitats. The expansion load can persist and represent a major fraction of the total mutation load for thousands of generations after the expansion. The phenomenon of expansion load may explain growing evidence that populations that have recently expanded, including humans, show an excess of deleterious mutations. To test the predictions of our model, we analyse functional genetic diversity in humans and find patterns that are consistent with our model.

Selective constraints determine the time dependency of molecular rates for human nuclear genomes

In contrast to molecular rates for neutral mitochondrial sequences, rates for constrained sites (including nonsynonymous sites, D-loop, and RNA) in the mitochondrial genome are known to vary with the time frame used for their estimation. Here, we examined this issue for the nuclear genomes using single-nucleotide polymorphisms (SNPs) from six complete human genomes of individuals belonging to different populations. We observed a strong time-dependent distribution of nonsynonymous SNPs (nSNPs) in highly constrained genes. Typically, the proportion of young nSNPs specific to a single population was found to be up to three times higher than that of the ancient nSNPs shared between diverse human populations. In contrast, this trend disappeared, and a uniform distribution of young and old nSNPs was observed in genes under relaxed selective constraints. This suggests that because mutations in constrained genes are highly deleterious, they are removed over time, resulting in a relative overabundance of young nSNPs. In contrast, mutations in genes under relaxed constraints are nearly neutral, which leads to similar proportions of young and old SNPs. These results could be useful to researchers aiming to select appropriate genes or genomic regions for estimating evolutionary rates and species or population divergence times.

Weak selection and protein evolution

The "nearly neutral" theory of molecular evolution proposes that many features of genomes arise from the interaction of three weak evolutionary forces: mutation, genetic drift, and natural selection acting at its limit of efficacy. Such forces generally have little impact on allele frequencies within populations from generation to generation but can have substantial effects on long-term evolution. The evolutionary dynamics of weakly selected mutations are highly sensitive to population size, and near neutrality was initially proposed as an adjustment to the neutral theory to account for general patterns in available protein and DNA variation data. Here, we review the motivation for the nearly neutral theory, discuss the structure of the model and its predictions, and evaluate current empirical support for interactions among weak evolutionary forces in protein evolution. Near neutrality may be a prevalent mode of evolution across a range of functional categories of mutations and taxa. However, multiple evolutionary mechanisms (including adaptive evolution, linked selection, changes in fitness-effect distributions, and weak selection) can often explain the same patterns of genome variation. Strong parameter sensitivity remains a limitation of the nearly neutral model, and we discuss concave fitness functions as a plausible underlying basis for weak selection.