Background selection and biased gene conversion affect more than 95% of the human genome and bias demographic inferences

The Effects of GC-Biased Gene Conversion on Patterns of Genetic Diversity among and across Butterfly Genomes

Recombination reshuffles the alleles of a population through crossover and gene conversion. These mechanisms have considerable consequences on the evolution and maintenance of genetic diversity. Crossover, for example, can increase genetic diversity by breaking the linkage between selected and nearby neutral variants. Bias in favor of G or C alleles during gene conversion may instead promote the fixation of one allele over the other, thus decreasing diversity. Mutation bias from G or C to A and T opposes GC-biased gene conversion (gBGC). Less recognized is that these two processes may-when balanced-promote genetic diversity. Here, we investigate how gBGC and mutation bias shape genetic diversity patterns in wood white butterflies (Leptidea sp.). This constitutes the first in-depth investigation of gBGC in butterflies. Using 60 resequenced genomes from six populations of three species, we find substantial variation in the strength of gBGC across lineages. When modeling the balance of gBGC and mutation bias and comparing analytical results with empirical data, we reject gBGC as the main determinant of genetic diversity in these butterfly species. As alternatives, we consider linked selection and GC content. We find evidence that high values of both reduce diversity. We also show that the joint effects of gBGC and mutation bias can give rise to a diversity pattern which resembles the signature of linked selection. Consequently, gBGC should be considered when interpreting the effects of linked selection on levels of genetic diversity.

Inferring number of populations and changes in connectivity under the n-island model

Inferring the demographic history of species is one of the greatest challenges in populations genetics. This history is often represented as a history of size changes, ignoring population structure. Alternatively, when structure is assumed, it is defined a priori as a population tree and not inferred. Here we propose a framework based on the IICR (Inverse Instantaneous Coalescence Rate). The IICR can be estimated for a single diploid individual using the PSMC method of Li and Durbin (2011). For an isolated panmictic population, the IICR matches the population size history, and this is how the PSMC outputs are generally interpreted. However, it is increasingly acknowledged that the IICR is a function of the demographic model and sampling scheme with limited connection to population size changes. Our method fits observed IICR curves of diploid individuals with IICR curves obtained under piecewise stationary symmetrical island models. In our models we assume a fixed number of time periods during which gene flow is constant, but gene flow is allowed to change between time periods. We infer the number of islands, their sizes, the periods at which connectivity changes and the corresponding rates of connectivity. Validation with simulated data showed that the method can accurately recover most of the scenario parameters. Our application to a set of five human PSMCs yielded demographic histories that are in agreement with previous studies using similar methods and with recent research suggesting ancient human structure. They are in contrast with the view of human evolution consisting of one ancestral population branching into three large continental and panmictic populations with varying degrees of connectivity and no population structure within each continent.

Biases in Demographic Modeling Affect Our Understanding of Recent Divergence

Testing among competing demographic models of divergence has become an important component of evolutionary research in model and non-model organisms. However, the effect of unaccounted demographic events on model choice and parameter estimation remains largely unexplored. Using extensive simulations, we demonstrate that under realistic divergence scenarios, failure to account for population size (N_e) changes in daughter and ancestral populations leads to strong biases in divergence time estimates as well as model choice. We illustrate these issues reconstructing the recent demographic history of North Sea and Baltic Sea turbots (Scophthalmus maximus) by testing 16 isolation with migration (IM) and 16 secondary contact (SC) scenarios, modeling changes in N_e as well as the effects of linked selection and barrier loci. Failure to account for changes in N_e resulted in selecting SC models with long periods of strict isolation and divergence times preceding the formation of the Baltic Sea. In contrast, models accounting for N_e changes suggest recent (<6 kya) divergence with constant gene flow. We further show how interpreting genomic landscapes of differentiation can help discerning among competing models. For example, in the turbot data, islands of differentiation show signatures of recent selective sweeps, rather than old divergence resisting secondary introgression. The results have broad implications for the study of population divergence by highlighting the potential effects of unmodeled changes in N_e on demographic inference. Tested models should aim at representing realistic divergence scenarios for the target taxa, and extreme caution should always be exercised when interpreting results of demographic modeling.

The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects

Current procedures for inferring population history generally assume complete neutrality—that is, they neglect both direct selection and the effects of selection on linked sites. We here examine how the presence of direct purifying selection and background selection may bias demographic inference by evaluating two commonly-used methods (MSMC and fastsimcoal2), specifically studying how the underlying shape of the distribution of fitness effects and the fraction of directly selected sites interact with demographic parameter estimation. The results show that, even after masking functional genomic regions, background selection may cause the mis-inference of population growth under models of both constant population size and decline. This effect is amplified as the strength of purifying selection and the density of directly selected sites increases, as indicated by the distortion of the site frequency spectrum and levels of nucleotide diversity at linked neutral sites. We also show how simulated changes in background selection effects caused by population size changes can be predicted analytically. We propose a potential method for correcting for the mis-inference of population growth caused by selection. By treating the distribution of fitness effect as a nuisance parameter and averaging across all potential realizations, we demonstrate that even directly selected sites can be used to infer demographic histories with reasonable accuracy.

Genetic history of Calabrian Greeks reveals ancient events and long term isolation in the Aspromonte area of Southern Italy

Calabrian Greeks are an enigmatic population that have preserved and evolved a unique variety of language, Greco, survived in the isolated Aspromonte mountain area of Southern Italy. To understand their genetic ancestry and explore possible effects of geographic and cultural isolation, we genome-wide genotyped a large set of South Italian samples including both communities that still speak Greco nowadays and those that lost the use of this language earlier in time. Comparisons with modern and ancient populations highlighted ancient, long-lasting genetic links with Eastern Mediterranean and Caucasian/Near-Eastern groups as ancestral sources of Southern Italians. Our results suggest that the Aspromonte communities might be interpreted as genetically drifted remnants that departed from such ancient genetic background as a consequence of long-term isolation. Specific patterns of population structuring and higher levels of genetic drift were indeed observed in these populations, reflecting geographic isolation amplified by cultural differences in the groups that still conserve the Greco language. Isolation and drift also affected the current genetic differentiation at specific gene pathways, prompting for future genome-wide association studies aimed at exploring trait-related loci that have drifted up in frequency in these isolated groups.

The impact of purifying and background selection on the inference of population history: problems and prospects

Current procedures for inferring population history generally assume complete neutrality - that is, they neglect both direct selection and the effects of selection on linked sites. We here examine how the presence of direct purifying selection and background selection may bias demographic inference by evaluating two commonly-used methods (MSMC and fastsimcoal2), specifically studying how the underlying shape of the distribution of fitness effects (DFE) and the fraction of directly selected sites interact with demographic parameter estimation. The results show that, even after masking functional genomic regions, background selection may cause the mis-inference of population growth under models of both constant population size and decline. This effect is amplified as the strength of purifying selection and the density of directly selected sites increases, as indicated by the distortion of the site frequency spectrum and levels of nucleotide diversity at linked neutral sites. We also show how simulated changes in background selection effects caused by population size changes can be predicted analytically. We propose a potential method for correcting for the mis-inference of population growth caused by selection. By treating the DFE as a nuisance parameter and averaging across all potential realizations, we demonstrate that even directly selected sites can be used to infer demographic histories with reasonable accuracy.

Genomic inference of complex domestication histories in three Solanaceae species

Domestication is a human-induced selection process that imprints the genomes of domesticated populations over a short evolutionary time scale and that occurs in a given demographic context. Reconstructing historical gene flow, effective population size changes and their timing is therefore of fundamental interest to understand how plant demography and human selection jointly shape genomic divergence during domestication. Yet, the comparison under a single statistical framework of independent domestication histories across different crop species has been little evaluated so far. Thus, it is unclear whether domestication leads to convergent demographic changes that similarly affect crop genomes. To address this question, we used existing and new transcriptome data on three crop species of Solanaceae (eggplant, pepper and tomato), together with their close wild relatives. We fitted twelve demographic models of increasing complexity on the unfolded joint allele frequency spectrum for each wild/crop pair, and we found evidence for both shared and species-specific demographic processes between species. A convergent history of domestication with gene flow was inferred for all three species, along with evidence of strong reduction in the effective population size during the cultivation stage of tomato and pepper. The absence of any reduction in size of the crop in eggplant stands out from the classical view of the domestication process; as does the existence of a "protracted period" of management before cultivation. Our results also suggest divergent management strategies of modern cultivars among species as their current demography substantially differs. Finally, the timing of domestication is species-specific and supported by the few historical records available.

Gene flow as a simple cause for an excess of high-frequency-derived alleles

Most human populations exhibit an excess of high-frequency variants, leading to a U-shaped site-frequency spectrum (uSFS). This pattern has been generally interpreted as a signature of ongoing episodes of positive selection, or as evidence for a mis-assignment of ancestral/derived allelic states, but uSFS has also been observed in populations receiving gene flow from a ghost population, in structured populations, or after range expansions. In order to better explain the prevalence of high-frequency variants in humans and other populations, we describe here which patterns of gene flow and population demography can lead to uSFS by using extensive coalescent simulations. We find that uSFS can often be observed in a population if gene flow brings a few ancestral alleles from a well-differentiated population. Gene flow can either consist in single pulses of admixture or continuous immigration, but different demographic conditions are necessary to observe uSFS in these two scenarios. Indeed, an extremely low and recent gene flow is required in the case of single admixture events, while with continuous immigration, uSFS occurs only if gene flow started recently at a high rate or if it lasted for a long time at a low rate. Overall, we find that a neutral uSFS occurs under more restrictive conditions in populations having received single pulses of gene flow than in populations exposed to continuous gene flow. We also show that the uSFS observed in human populations from the 1000 Genomes Project can easily be explained by gene flow from surrounding populations without requiring past episodes of positive selection. These results imply that uSFS should be common in non-isolated populations, such as most wild or domesticated plants and animals.

Whole-exome sequencing reveals a long-term decline in effective population size of red spruce (Picea rubens)

Understanding the factors influencing the current distribution of genetic diversity across a species range is one of the main questions of evolutionary biology, especially given the increasing threat to biodiversity posed by climate change. Historical demographic processes such as population expansion or bottlenecks and decline are known to exert a predominant influence on past and current levels of genetic diversity, and revealing this demo-genetic history can have immediate conservation implications. We used a whole-exome capture sequencing approach to analyze polymorphism across the gene space of red spruce (Picea rubens Sarg.), an endemic and emblematic tree species of eastern North America high-elevation forests that are facing the combined threat of global warming and increasing human activities. We sampled a total of 340 individuals, including populations from the current core of the range in northeastern USA and southeastern Canada and from the southern portions of its range along the Appalachian Mountains, where populations occur as highly fragmented mountaintop "sky islands." Exome capture baits were designed from the closely relative white spruce (P. glauca Voss) transcriptome, and sequencing successfully captured most regions on or near our target genes, resulting in the generation of a new and expansive genomic resource for studying standing genetic variation in red spruce applicable to its conservation. Our results, based on over 2 million exome-derived variants, indicate that red spruce is structured into three distinct ancestry groups that occupy different geographic regions of its highly fragmented range. Moreover, these groups show small Ne , with a temporal history of sustained population decline that has been ongoing for thousands (or even hundreds of thousands) of years. These results demonstrate the broad potential of genomic studies for revealing details of the demographic history that can inform management and conservation efforts of nonmodel species with active restoration programs, such as red spruce.

Demographic history shaped geographical patterns of deleterious mutation load in a broadly distributed Pacific Salmon

A thorough reconstruction of historical processes is essential for a comprehensive understanding of the mechanisms shaping patterns of genetic diversity. Indeed, past and current conditions influencing effective population size have important evolutionary implications for the efficacy of selection, increased accumulation of deleterious mutations, and loss of adaptive potential. Here, we gather extensive genome-wide data that represent the extant diversity of the Coho salmon (Oncorhynchus kisutch) to address two objectives. We demonstrate that a single glacial refugium is the source of most of the present-day genetic diversity, with detectable inputs from a putative secondary micro-refugium. We found statistical support for a scenario whereby ancestral populations located south of the ice sheets expanded recently, swamping out most of the diversity from other putative micro-refugia. Demographic inferences revealed that genetic diversity was also affected by linked selection in large parts of the genome. Moreover, we demonstrate that the recent demographic history of this species generated regional differences in the load of deleterious mutations among populations, a finding that mirrors recent results from human populations and provides increased support for models of expansion load. We propose that insights from these historical inferences should be better integrated in conservation planning of wild organisms, which currently focuses largely on neutral genetic diversity and local adaptation, with the role of potentially maladaptive variation being generally ignored.

Reconstruction of a species’ past demographic history from genetic data can highlight historical factors that have shaped the distribution of genetic diversity along its genome and its geographic range. Here, we combine genotyping-by-sequencing with demographic modelling to address these issues in the Coho salmon, a Pacific salmon of conservation concern in some parts of its range, notably in the south. Our demographic reconstructions reveal a linear decrease in genetic diversity toward the north of the species range, supporting the hypothesis of a northern route of postglacial recolonization from a single major southern refugium. As predicted by theory, we also observed a higher proportion of deleterious mutations in the most distant populations from this refugium. Beyond this general pattern, among-site variation in the proportion of deleterious mutations is consistent with different local trends in effective population sizes. Our results highlight the potential importance of understanding historical factors that have shaped geographic patterns of the distribution of deleterious mutations in order to implement effective management programs for the conservation of wild populations. Such fundamental knowledge of human historical demography is now having major impacts on health sciences, and we argue it is time to integrate such approaches in conservation science as well.

Inferring evolutionary dynamics of mutation rates through the lens of mutation spectrum variation

There are many possible failure points in the transmission of genetic information that can produce heritable germline mutations. Once a mutation has been passed from parents to offspring for several generations, it can be difficult or impossible to identify its root cause; however, sometimes the nature of the ancestral and derived DNA sequences can provide mechanistic clues about a genetic change that happened hundreds or thousands of generations ago. Here, we review evidence that the sequence context 'spectrum' of germline mutagenesis has been evolving surprisingly rapidly over the history of humans and other species. We go on to discuss possible causal factors that might underlie rapid mutation spectrum evolution.

Facilitating Complex Trait Analysis via Reduced Complexity Crosses

Genetically diverse inbred strains are frequently used in quantitative trait mapping to identify sequence variants underlying trait variation. Poor locus resolution and high genetic complexity impede variant discovery. As a solution, we explore reduced complexity crosses (RCCs) between phenotypically divergent, yet genetically similar, rodent substrains. RCCs accelerate functional variant discovery via decreasing the number of segregating variants by orders of magnitude. The simplified genetic architecture of RCCs often permit immediate identification of causal variants or rapid fine-mapping of broad loci to smaller intervals. Whole-genome sequences of substrains make RCCs possible by supporting the development of array- and targeted sequencing-based genotyping platforms, coupled with rapid genome editing for variant validation. In summary, RCCs enhance discovery-based genetics of complex traits.

Inference of natural selection from ancient DNA

Evolutionary processes, including selection, can be indirectly inferred based on patterns of genomic variation among contemporary populations or species. However, this often requires unrealistic assumptions of ancestral demography and selective regimes. Sequencing ancient DNA from temporally spaced samples can inform about past selection processes, as time series data allow direct quantification of population parameters collected before, during, and after genetic changes driven by selection. In this Comment and Opinion, we advocate for the inclusion of temporal sampling and the generation of paleogenomic datasets in evolutionary biology, and highlight some of the recent advances that have yet to be broadly applied by evolutionary biologists. In doing so, we consider the expected signatures of balancing, purifying, and positive selection in time series data, and detail how this can advance our understanding of the chronology and tempo of genomic change driven by selection. However, we also recognize the limitations of such data, which can suffer from postmortem damage, fragmentation, low coverage, and typically low sample size. We therefore highlight the many assumptions and considerations associated with analyzing paleogenomic data and the assumptions associated with analytical methods.

The Temporal Dynamics of Background Selection in Nonequilibrium Populations

Neutral genetic diversity across the genome is determined by the complex interplay of mutation, demographic history, and natural selection. While the direct action of natural selection is limited to functional loci across the genome, its impact can have effects on nearby neutral loci due to genetic linkage. These effects of selection at linked sites, referred to as genetic hitchhiking and background selection (BGS), are pervasive across natural populations. However, only recently has there been a focus on the joint consequences of demography and selection at linked sites, and some empirical studies have come to apparently contradictory conclusions as to their combined effects. To understand the relationship between demography and selection at linked sites, we conducted an extensive forward simulation study of BGS under a range of demographic models. We found that the relative levels of diversity in BGS and neutral regions vary over time and that the initial dynamics after a population size change are often in the opposite direction of the long-term expected trajectory. Our detailed observations of the temporal dynamics of neutral diversity in the context of selection at linked sites in nonequilibrium populations provide new intuition about why patterns of diversity under BGS vary through time in natural populations and help reconcile previously contradictory observations. Most notably, our results highlight that classical models of BGS are poorly suited for predicting diversity in nonequilibrium populations.

Transition from Background Selection to Associative Overdominance Promotes Diversity in Regions of Low Recombination

Linked selection is a major driver of genetic diversity. Selection against deleterious mutations removes linked neutral diversity (background selection [BGS]) [1], creating a positive correlation between recombination rates and genetic diversity. Purifying selection against recessive variants, however, can also lead to associative overdominance (AOD) [2, 3], due to an apparent heterozygote advantage at linked neutral loci that opposes the loss of neutral diversity by BGS. Zhao and Charlesworth [3] identified the conditions under which AOD should dominate over BGS in a single-locus model and suggested that the effect of AOD could become stronger if multiple linked deleterious variants co-segregate. We present a model describing how and under which conditions multi-locus dynamics can amplify the effects of AOD. We derive the conditions for a transition from BGS to AOD due to pseudo-overdominance [4], i.e., a form of balancing selection that maintains complementary deleterious haplotypes that mask the effect of recessive deleterious mutations. Simulations confirm these findings and show that multi-locus AOD can increase diversity in low-recombination regions much more strongly than previously appreciated. While BGS is known to drive genome-wide diversity in humans [5], the observation of a resurgence of genetic diversity in regions of very low recombination is indicative of AOD. We identify 22 such regions in the human genome consistent with multi-locus AOD. Our results demonstrate that AOD may play an important role in the evolution of low-recombination regions of many species.

Patterns of Genetic Variability in Genomic Regions with Low Rates of Recombination

The amount of DNA sequence variability in a genomic region is often positively correlated with its rate of crossing over (CO) [1-3]. This pattern is caused by selection acting on linked sites, which reduces genetic variability and biases the frequency distribution of segregating variants toward more rare variants than are expected without selection (skew). These effects may involve the spread of beneficial mutations (selective sweeps [SSWs]), the elimination of deleterious mutations (background selection [BGS]), or both, and are expected to be stronger with lower CO rates [1-3]. However, in a recent study of human populations, the skew was reduced in the lowest CO regions compared with regions with somewhat higher CO rates [4]. A low skew in very low CO regions, compared with theoretical predictions, is seen in the population genomic studies of Drosophila simulans described here and in other Drosophila species. Here, we propose an explanation for lower than expected skew in low CO regions, and validate it using computer simulations; explanations for higher skew with higher CO rates, as in D. simulans, will be explored elsewhere. Partially recessive, linked deleterious mutations can increase neutral variability when the product of the effective population size (N_e) and the selection coefficient against homozygous carriers of mutations (s) is ≤1, i.e., there is associative overdominance (AOD) rather than BGS [5]. AOD can operate in low CO regions, producing a lower skew than in its absence. This opens up a new perspective on how selection affects patterns of variability at linked sites.

Comparison of the Full Distribution of Fitness Effects of New Amino Acid Mutations Across Great Apes

The distribution of fitness effects (DFE) is central to many questions in evolutionary biology. However, little is known about the differences in DFE between closely related species. We use >9000 coding genes orthologous one-to-one across great apes, gibbons, and macaques to assess the stability of the DFE across great apes. We use the unfolded site frequency spectrum of polymorphic mutations (n = 8 haploid chromosomes per population) to estimate the DFE. We find that the shape of the deleterious DFE is strikingly similar across great apes. We confirm that effective population size (Ne ) is a strong predictor of the strength of negative selection, consistent with the nearly neutral theory. However, we also find that the strength of negative selection varies more than expected given the differences in Ne between species. Across species, mean fitness effects of new deleterious mutations covaries with Ne , consistent with positive epistasis among deleterious mutations. We find that the strength of negative selection for the smallest populations, bonobos and western chimpanzees, is higher than expected given their Ne This may result from a more efficient purging of strongly deleterious recessive variants in these populations. Forward simulations confirm that these findings are not artifacts of the way we are inferring Ne and DFE parameters. All findings are replicated using only GC-conservative mutations, thereby confirming that GC-biased gene conversion is not affecting our conclusions.

Admixture between old lineages facilitated contemporary ecological speciation in Lake Constance stickleback

Ecological speciation can sometimes rapidly generate reproductively isolated populations coexisting in sympatry, but the origin of genetic variation permitting this is rarely known. We previously explored the genomics of very recent ecological speciation into lake and stream ecotypes in stickleback from Lake Constance. Here, we reconstruct the origin of alleles underlying ecological speciation by combining demographic modelling on genome-wide single nucleotide polymorphisms, phenotypic data and mitochondrial sequence data in the wider European biogeographical context. We find that parallel differentiation between lake and stream ecotypes across replicate lake-stream ecotones resulted from recent secondary contact and admixture between old East and West European lineages. Unexpectedly, West European alleles that introgressed across the hybrid zone at the western end of the lake, were recruited to genomic islands of differentiation between ecotypes at the eastern end of the lake. Our results highlight an overlooked outcome of secondary contact: ecological speciation facilitated by admixture variation.

Ecological speciation can proceed rapidly, but the origin of genetic variation facilitating it has remained elusive. Here, the authors show that secondary contact and introgression between deeply diverged lineages of stickleback fish facilitated rapid ecological speciation into lake and stream ecotypes in Lake Constance.

Impact of demography on linked selection in two outcrossing Brassicaceae species

Genetic diversity is shaped by mutation, genetic drift, gene flow, recombination, and selection. The dynamics and interactions of these forces shape genetic diversity across different parts of the genome, between populations and species. Here, we have studied the effects of linked selection on nucleotide diversity in outcrossing populations of two Brassicaceae species, Arabidopsis lyrata and Capsella grandiflora, with contrasting demographic history. In agreement with previous estimates, we found evidence for a modest population size expansion thousands of generations ago, as well as efficient purifying selection in C. grandiflora. In contrast, the A. lyrata population exhibited evidence for very recent strong population size decline and weaker efficacy of purifying selection. Using multiple regression analyses with recombination rate and other genomic covariates as explanatory variables, we can explain 47% of the variance in neutral diversity in the C. grandiflora population, while in the A. lyrata population, only 11% of the variance was explained by the model. Recombination rate had a significant positive effect on neutral diversity in both species, suggesting that selection at linked sites has an effect on patterns of neutral variation. In line with this finding, we also found reduced neutral diversity in the vicinity of genes in the C. grandiflora population. However, in A. lyrata no such reduction in diversity was evident, a finding that is consistent with expectations of the impact of a recent bottleneck on patterns of neutral diversity near genes. This study thus empirically demonstrates how differences in demographic history modulate the impact of selection at linked sites in natural populations.

A high-resolution map of non-crossover events reveals impacts of genetic diversity on mammalian meiotic recombination

During meiotic recombination, homologue-templated repair of programmed DNA double-strand breaks (DSBs) produces relatively few crossovers and many difficult-to-detect non-crossovers. By intercrossing two diverged mouse subspecies over five generations and deep-sequencing 119 offspring, we detect thousands of crossover and non-crossover events genome-wide with unprecedented power and spatial resolution. We find that both crossovers and non-crossovers are strongly depleted at DSB hotspots where the DSB-positioning protein PRDM9 fails to bind to the unbroken homologous chromosome, revealing that PRDM9 also functions to promote homologue-templated repair. Our results show that complex non-crossovers are much rarer in mice than humans, consistent with complex events arising from accumulated non-programmed DNA damage. Unexpectedly, we also find that GC-biased gene conversion is restricted to non-crossover tracts containing only one mismatch. These results demonstrate that local genetic diversity profoundly alters meiotic repair pathway decisions via at least two distinct mechanisms, impacting genome evolution and Prdm9-related hybrid infertility.

During meiotic recombination, genetic information is transferred or exchanged between parental chromosome copies. Using a large hybrid mouse pedigree, the authors generated high-resolution maps of these transfer/exchange events and discovered new properties governing their processing and resolution.

Quantifying GC-Biased Gene Conversion in Great Ape Genomes Using Polymorphism-Aware Models

As multi-individual population-scale data become available, more complex modeling strategies are needed to quantify genome-wide patterns of nucleotide usage and associated mechanisms of evolution. Recently, the multivariate neutral Moran model was proposed. However, it was shown insufficient to explain the distribution of alleles in great apes. Here, we propose a new model that includes allelic selection. Our theoretical results constitute the basis of a new Bayesian framework to estimate mutation rates and selection coefficients from population data. We apply the new framework to a great ape dataset, where we found patterns of allelic selection that match those of genome-wide GC-biased gene conversion (gBGC). In particular, we show that great apes have patterns of allelic selection that vary in intensity-a feature that we correlated with great apes' distinct demographies. We also demonstrate that the AT/GC toggling effect decreases the probability of a substitution, promoting more polymorphisms in the base composition of great ape genomes. We further assess the impact of GC-bias in molecular analysis, and find that mutation rates and genetic distances are estimated under bias when gBGC is not properly accounted for. Our results contribute to the discussion on the tempo and mode of gBGC evolution, while stressing the need for gBGC-aware models in population genetics and phylogenetics.

Recent Secondary Contacts, Linked Selection, and Variable Recombination Rates Shape Genomic Diversity in the Model Species Anolis carolinensis

Gaining a better understanding on how selection and neutral processes affect genomic diversity is essential to gain better insights into the mechanisms driving adaptation and speciation. However, the evolutionary processes affecting variation at a genomic scale have not been investigated in most vertebrate lineages. Here, we present the first population genomics survey using whole genome resequencing in the green anole (Anolis carolinensis). Anoles have been intensively studied to understand mechanisms underlying adaptation and speciation. The green anole in particular is an important model to study genome evolution. We quantified how demography, recombination, and selection have led to the current genetic diversity of the green anole by using whole-genome resequencing of five genetic clusters covering the entire species range. The differentiation of green anole's populations is consistent with a northward expansion from South Florida followed by genetic isolation and subsequent gene flow among adjacent genetic clusters. Dispersal out-of-Florida was accompanied by a drastic population bottleneck followed by a rapid population expansion. This event was accompanied by male-biased dispersal and/or selective sweeps on the X chromosome. We show that the interaction between linked selection and recombination is the main contributor to the genomic landscape of differentiation in the anole genome.

The genomic determinants of adaptive evolution in a fungal pathogen

Unravelling the strength, frequency, and distribution of selective variants along the genome as well as the underlying factors shaping this distribution are fundamental goals of evolutionary biology. Antagonistic host-pathogen coevolution is thought to be a major driver of genome evolution between interacting species. While rapid evolution of pathogens has been documented in several model organisms, the genetic mechanisms of their adaptation are still poorly understood and debated, particularly the role of sexual reproduction. Here, we apply a population genomic approach to infer genome-wide patterns of selection among 13 isolates of Zymoseptoria tritici, a fungal pathogen characterized by extremely high genetic diversity, gene density, and recombination rates. We report that the genome of Z. tritici undergoes a high rate of adaptive substitutions, with 44% of nonsynonymous substitutions being adaptive on average. This fraction reaches 68% in so-called effector genes encoding determinants of pathogenicity, and the distribution of fitness effects differs in this class of genes as they undergo adaptive mutations with stronger positive fitness effects, but also more slightly deleterious mutations. Besides the globally high rate of adaptive substitutions, we report a negative relationship between pN/pS and the fine-scale recombination rate and a strong positive correlation between the rate of adaptive nonsynonymous substitutions (ωa) and recombination rate. This result suggests a pervasive role of both background selection and Hill-Robertson interference even in a species with an exceptionally high recombination rate (60 cM/Mb on average). While transposable elements (TEs) have been suggested to contribute to adaptation by creating compartments of fast-evolving genomic regions, we do not find a significant effect of TEs on the rate of adaptive mutations. Overall our study suggests that sexual recombination is a significant driver of genome evolution, even in rapidly evolving organisms subject to recurrent mutations with large positive effects.

Evolutionary Modeling in SLiM 3 for Beginners

The SLiM forward genetic simulation framework has proved to be a powerful and flexible tool for population genetic modeling. However, as a complex piece of software with many features that allow simulating a diverse assortment of evolutionary models, its initial learning curve can be difficult. Here we provide a step-by-step demonstration of how to build a simple evolutionary model in SLiM 3, to help new users get started. We will begin with a panmictic neutral model, and build up to a model of the evolution of a polygenic quantitative trait under selection for an environmental phenotypic optimum.

Fine-Scale Characterization of Genomic Structural Variation in the Human Genome Reveals Adaptive and Biomedically Relevant Hotspots

Genomic structural variants (SVs) are distributed nonrandomly across the human genome. The "hotspots" of SVs have been implicated in evolutionary innovations, as well as medical conditions. However, the evolutionary and biomedical features of these hotspots remain incompletely understood. Here, we analyzed data from 2,504 genomes to construct a refined map of 1,148 SV hotspots in human genomes. We confirmed that segmental duplication-related nonallelic homologous recombination is an important mechanistic driver of SV hotspot formation. However, to our surprise, we also found that a majority of SVs in hotspots do not form through such recombination-based mechanisms, suggesting diverse mechanistic and selective forces shaping hotspots. Indeed, our evolutionary analyses showed that the majority of SV hotspots are within gene-poor regions and evolve under relaxed negative selection or neutrality. However, we still found a small subset of SV hotspots harboring genes that are enriched for anthropologically crucial functions and evolve under geography-specific and balancing adaptive forces. These include two independent hotspots on different chromosomes affecting alpha and beta hemoglobin gene clusters. Biomedically, we found that the SV hotspots coincide with breakpoints of clinically relevant, large de novo SVs, significantly more often than genome-wide expectations. For example, we showed that the breakpoints of multiple large SVs, which lead to idiopathic short stature, coincide with SV hotspots. Therefore, the mutational instability in SV hotpots likely enables chromosomal breaks that lead to pathogenic structural variation formations. Overall, our study contributes to a better understanding of the mutational and adaptive landscape of the genome.

The importance of the Neutral Theory in 1968 and 50 years on: A response to Kern and Hahn 2018

A recent article reassessing the Neutral Theory of Molecular Evolution claims that it is no longer as important as is widely believed. The authors argue that "the neutral theory was supported by unreliable theoretical and empirical evidence from the beginning, and that in light of modern, genome-scale data, we can firmly reject its universality." Claiming that "the neutral theory has been overwhelmingly rejected," they propose instead that natural selection is the major force shaping both between-species divergence and within-species variation. Although this is probably a minority view, it is important to evaluate such claims carefully in the context of current knowledge, as inaccuracies can sometimes morph into an accepted narrative for those not familiar with the underlying science. We here critically examine and ultimately reject Kern and Hahn's arguments and assessment, and instead propose that it is now abundantly clear that the foundational ideas presented five decades ago by Kimura and Ohta are indeed correct.

The natural selection that shapes our genomes

Most of the variation in the human genome (∼95%) is constrained, directly or indirectly, by purifying selection and GC-biased gene conversion, according to a recent article by Pouyet et al. (2018). The use of 'non-neutral' variation to infer human demographies can lead to undesirable biases; for example, in estimation of the time of the most recent common ancestor. Further examination of 'neutral' variation in entire human genomes from The 1000 Genomes Project reveals that ∼99% of this variation lacks exonic function, but ∼35% of it falls in introns. In addition, estimates of biogeographical ancestry using 'non-neutral' SNPs differ very marginally from inferences obtained from 'neutral' variation. Additional investigations should be carried out before establishing the roadmap for future human population and forensic genetic studies.

The randomness that shapes our DNA

Just 5% of the human genome is subject to neutral evolution, but this process remains central to understanding the history of human migration across the Earth.