Genomic signatures of selection at linked sites: unifying the disparity among species

The recombination landscape of the barn owl, from families to populations

Homologous recombination is a meiotic process that generates diversity along the genome and interacts with all evolutionary forces. Despite its importance, studies of recombination landscapes are lacking due to methodological limitations and limited data. Frequently used approaches include linkage mapping based on familial data that provides sex-specific broad-scale estimates of realized recombination and inferences based on population linkage disequilibrium that reveal a more fine-scale resolution of the recombination landscape, albeit dependent on the effective population size and the selective forces acting on the population. In this study, we use a combination of these 2 methods to elucidate the recombination landscape for the Afro-European barn owl (Tyto alba). We find subtle differences in crossover placement between sexes that lead to differential effective shuffling of alleles. Linkage disequilibrium-based estimates of recombination are concordant with family-based estimates and identify large variation in recombination rates within and among linkage groups. Larger chromosomes show variation in recombination rates, while smaller chromosomes have a universally high rate that shapes the diversity landscape. We find that recombination rates are correlated with gene content, genetic diversity, and GC content. We find no conclusive differences in the recombination landscapes between populations. Overall, this comprehensive analysis enhances our understanding of recombination dynamics, genomic architecture, and sex-specific variation in the barn owl, contributing valuable insights to the broader field of avian genomics.

Selection Can Favor a Recombination Landscape That Limits Polygenic Adaptation

Modifiers of recombination rates have been described but the selective pressures acting on them and their effect on adaptation to novel environments remain unclear. We performed experimental evolution in the nematode Caenorhabditis elegans using alternative rec-1 alleles modifying the position of meiotic crossovers along chromosomes without detectable direct fitness effects. We show that adaptation to a novel environment is impaired by the allele that decreases recombination rates in the genomic regions containing fitness variation. However, the allele that impairs adaptation is indirectly favored by selection, because it increases recombination rates and reduces the associations among beneficial and deleterious variation located in its chromosomal vicinity. These results validate theoretical expectations about the evolution of recombination but suggest that genome-wide polygenic adaptation is of little consequence to indirect selection on recombination rate modifiers.

Thrushes in Love: Extensive Gene Flow, With Differential Resistance and Selection, Obscures and Reveals the Evolutionary History of a Songbird Clade

The application of high-throughput sequencing to phylogenetic analyses is allowing authors to reconstruct the true evolutionary history of species. This work can illuminate specific mechanisms underlying divergence when combined with analyses of gene flow, recombination and selection. We conducted a phylogenomic analysis of Catharus, a songbird genus with considerable potential for gene flow, variation in migratory behaviour and genomic resources. We documented discordance among trees constructed for mitochondrial, autosomal and sex (Z) chromosome partitions. Two trees were recovered on the Z. Both trees differed from the autosomes, one matched the mitochondria, and the other was unique to the Z. Gene flow with one species likely generated much of this discordance; substantial admixture between ustulatus and the remaining species was documented and linked to at least two historic events. The tree unique to the Z likely reflects the true history of Catharus; local genomic analyses recovered the same tree in autosomal regions with reduced admixture and recombination. Genes previously connected to migration were enriched in these regions suggesting transitions between migratory and non-migratory states helped generate divergence. Migratory (vs. nonmigratory) Catharus formed a monophyletic clade in a subset of genomic regions. Gene flow was elevated in some of these regions suggesting adaptive introgression may have occurred, but the dominant pattern was of balancing selection maintaining ancestral polymorphisms important for olfaction and perhaps, by extension, adaptation to temperate climates. This work illuminates the evolutionary history of an important model in speciation and demonstrates how differential resistance to gene flow can affect local genomic patterns.

The Genetic Architecture of Local Adaptation and Reproductive Character Displacement in Scutiger boulengeri Complex (Anura: Megophryidae)

Speciation is a continuous process driven by barriers to gene flow. Based on genome-wide SNPs (single nucleotide polymorphisms) of 190 toads from 31 sampling sites of Scutiger boulengeri complex, we found evidence for monophyly which represented a continuous speciation process of at least six lineages in S. boulengeri, which radiated and exhibited varying degrees of divergence and gene flow. The SNP-based phylogenetic tree was largely discordant with the multilocus mitochondrial tree (i.e., S. mammatus and S. glandulatus nested in the lineages of S. boulengeri) published before. The Min Mountains (MM) and Qinghai-Tibet Plateau (QTP) lineages differ fundamentally in habitat (i.e., elevation) and morphology (i.e., SVL), we detected signatures of potential high-altitude and cold adaptation genes in QTP (vs. MM). We found the evidence of reproductive trait disparity (i.e., SVL and nuptial pads) is key to promoting sympatric rather than allopatric species pairs. In addition, we identified selection signals for genes related to sympatric character displacement, genes linked to obesity-related traits, nuptial spines morphology and enlarged chest nuptial pads in S. mammatus (vs. QTP group of S. boulengeri). Our study provided new insight and paradigm for a varied speciation pattern from local adaptation of allopatry to sympatric character displacement in the S. boulengeri complex.

The F204S mutation in adrenodoxin oxidoreductase drives salinomycin resistance in Eimeria tenella

Salinomycin is a polyether ionophore widely used for the treatment of coccidiosis in poultry. However, the emergence of coccidia strains resistant to salinomycin presents challenges for control efforts, and the mechanisms underlying this resistance in Eimeria remain inadequately understood. In this study, 78 stable salinomycin-resistant strains were generated through experimental evolution approaches. Whole-genome sequencing of salinomycin-resistant Eimeria tenella isolates revealed single nucleotide polymorphisms (SNPs), with 12 candidate genes harboring nonsynonymous mutations identified. To confirm the candidate gene responsible for conferring salinomycin resistance, we leveraged reverse genetic strategies and identified a key amino acid substitution (F204S) in adrenodoxin oxidoreductase (EtADR), which markedly reduced susceptibility to salinomycin. Our results elucidate the complex interactions among salinomycin resistance, parasite fitness, point mutations, and the structure of EtADR, laying the foundation for future studies on drug resistance in Eimeria and contributing to the development of targeted control strategies.

Digital Image Processing to Detect Adaptive Evolution

In recent years, advances in image processing and machine learning have fueled a paradigm shift in detecting genomic regions under natural selection. Early machine learning techniques employed population-genetic summary statistics as features, which focus on specific genomic patterns expected by adaptive and neutral processes. Though such engineered features are important when training data are limited, the ease at which simulated data can now be generated has led to the recent development of approaches that take in image representations of haplotype alignments and automatically extract important features using convolutional neural networks. Digital image processing methods termed α-molecules are a class of techniques for multiscale representation of objects that can extract a diverse set of features from images. One such α-molecule method, termed wavelet decomposition, lends greater control over high-frequency components of images. Another α-molecule method, termed curvelet decomposition, is an extension of the wavelet concept that considers events occurring along curves within images. We show that application of these α-molecule techniques to extract features from image representations of haplotype alignments yield high true positive rate and accuracy to detect hard and soft selective sweep signatures from genomic data with both linear and nonlinear machine learning classifiers. Moreover, we find that such models are easy to visualize and interpret, with performance rivaling those of contemporary deep learning approaches for detecting sweeps.

FST and genetic diversity in an island model with background selection

Background selection, by which selection on deleterious alleles reduces diversity at linked neutral sites, influences patterns of total neutral diversity, πT, and genetic differentiation, FST, in structured populations. The theory of background selection may be split into two regimes: the background selection regime, where selection pressures are strong and mutation rates are sufficiently low such that deleterious alleles are at a deterministic mutation-selection balance, and the interference selection regime, where selection pressures are weak and mutation rates are sufficiently high that deleterious alleles accumulate and interfere with another, leading to selective interference. Previous work has quantified the effects of background selection on πT and FST only for deleterious alleles in the background selection regime. Furthermore, there is evidence to suggest that migration reduces the effects of background selection on FST, but this has not been fully explained. Here, we derive novel theory to predict the effects of migration on background selection experienced by a subpopulation and extend previous theory from the interference selection regime to make predictions in an island model. Using simulations, we show that this theory best predicts FST and πT. Moreover, we demonstrate that background selection may generate minimal increases in FST under sufficiently high migration rates, because migration reduces correlated effects on fitness over generations within subpopulations. However, we show that background selection may still cause substantial reductions in πT, particularly for metapopulations with a larger effective population size. Our work further extends the theory of background selection into structured populations, and suggests that background selection will minimally confound locus-to-locus FST scans.

Mating systems and recombination landscape strongly shape genetic diversity and selection in wheat relatives

How and why genetic diversity varies among species is a long-standing question in evolutionary biology. Life history traits have been shown to explain a large part of observed diversity. Among them, mating systems have one of the strongest impacts on genetic diversity, with selfing species usually exhibiting much lower diversity than outcrossing relatives. Theory predicts that a high rate of selfing amplifies selection at linked sites, reducing genetic diversity genome-wide, but frequent bottlenecks and rapid population turn-over could also explain low genetic diversity in selfers. However, how linked selection varies with mating systems and whether it is sufficient to explain the observed difference between selfers and outcrossers has never been tested. Here, we used the Aegilops/Triticum grass species, a group characterized by contrasted mating systems (from obligate outcrossing to high selfing) and marked recombination rate variation across the genome, to quantify the effects of mating system and linked selection on patterns of neutral and selected polymorphism. By analyzing phenotypic and transcriptomic data of 13 species, we show that selfing strongly affects genetic diversity and the efficacy of selection by amplifying the intensity of linked selection genome-wide. In particular, signatures of adaptation were only found in the highly recombining regions in outcrossing species. These results bear implications for the evolution of mating systems and, more generally, for our understanding of the fundamental drivers of genetic diversity.

Inferring demographic and selective histories from population genomic data using a two-step approach in species with coding-sparse genomes: an application to human data

The demographic history of a population, and the distribution of fitness effects (DFE) of newly arising mutations in functional genomic regions, are fundamental factors dictating both genetic variation and evolutionary trajectories. Although both demographic and DFE inference has been performed extensively in humans, these approaches have generally either been limited to simple demographic models involving a single population, or, where a complex population history has been inferred, without accounting for the potentially confounding effects of selection at linked sites. Taking advantage of the coding-sparse nature of the genome, we propose a 2-step approach in which coalescent simulations are first used to infer a complex multi-population demographic model, utilizing large non-functional regions that are likely free from the effects of background selection. We then use forward-in-time simulations to perform DFE inference in functional regions, conditional on the complex demography inferred and utilizing expected background selection effects in the estimation procedure. Throughout, recombination and mutation rate maps were used to account for the underlying empirical rate heterogeneity across the human genome. Importantly, within this framework it is possible to utilize and fit multiple aspects of the data, and this inference scheme represents a generalized approach for such large-scale inference in species with coding-sparse genomes.

Whole Genomes Reveal Evolutionary Relationships and Mechanisms Underlying Gene-Tree Discordance in Neodiprion Sawflies

Rapidly evolving taxa are excellent models for understanding the mechanisms that give rise to biodiversity. However, developing an accurate historical framework for comparative analysis of such lineages remains a challenge due to ubiquitous incomplete lineage sorting (ILS) and introgression. Here, we use a whole-genome alignment, multiple locus-sampling strategies, and summary-tree and single nucleotide polymorphism-based species-tree methods to infer a species tree for eastern North American Neodiprion species, a clade of pine-feeding sawflies (Order: Hymenopteran; Family: Diprionidae). We recovered a well-supported species tree that-except for three uncertain relationships-was robust to different strategies for analyzing whole-genome data. Nevertheless, underlying gene-tree discordance was high. To understand this genealogical variation, we used multiple linear regression to model site concordance factors estimated in 50-kb windows as a function of several genomic predictor variables. We found that site concordance factors tended to be higher in regions of the genome with more parsimony-informative sites, fewer singletons, less missing data, lower GC content, more genes, lower recombination rates, and lower D-statistics (less introgression). Together, these results suggest that ILS, introgression, and genotyping error all shape the genomic landscape of gene-tree discordance in Neodiprion. More generally, our findings demonstrate how combining phylogenomic analysis with knowledge of local genomic features can reveal mechanisms that produce topological heterogeneity across genomes.

Characterising the Genomic Landscape of Differentiation Between Annual and Perennial Rye

Annuality and perenniality represent two different life-history strategies in plants, and an analysis of genomic differentiation between closely related species of different life histories bears the potential to identify the underlying targets of selection. Additionally, understanding the interactions between patterns of recombination and signatures of natural selection is a central aim in evolutionary biology, because patterns of recombination shape the evolution of genomes by affecting the efficacy of selection. Here, our aim was to characterise the landscape of genomic differentiation between weedy annual rye (Secale cereale L.) and wild perennial rye (Secale strictum C. Presl), and explore the extent to which signatures of selection are influenced by recombination rate variation. We used population-level sequence data of annual and perennial rye to analyse population structure and their demographic history. Based on our analyses, annual and perennial rye diverged approximately 26,500 years ago (ya) from an ancestral population size of ~85,000 individuals. We analysed patterns of genetic diversity and genetic differentiation, and found highly differentiated regions located in low-recombination regions, indicative of linked selection. Although all highly differentiated regions, as revealed by F ST-outlier scans, were located in low-recombining regions, not all chromosomes showed this tendency. We therefore performed a gene ontology enrichment analysis, which showed that highly differentiated regions comprise genes involved in photosynthesis. This enrichment was confirmed when F ST outlier scans were performed separately in low- and intermediate-recombining regions, but not in high-recombining regions, suggesting that local recombination rate variation in rye affects outlier scans. Cultivated rye is an annual crop, but the introduction of perenniality may be advantageous in regions with poor soil quality or under low-input farming. Although the resolution of our analysis is limited to a broad-scale, knowledge about the evolutionary divergence between annual and perennial rye might support breeding efforts towards perennial rye cultivation.

Recurrent selection shapes the genomic landscape of differentiation between a pair of host-specialized haplodiploids that diverged with gene flow

Understanding the genetics of adaptation and speciation is critical for a complete picture of how biodiversity is generated and maintained. Heterogeneous genomic differentiation between diverging taxa is commonly documented, with genomic regions of high differentiation interpreted as resulting from differential gene flow, linked selection and reduced recombination rates. Disentangling the roles of each of these non-exclusive processes in shaping genome-wide patterns of divergence is challenging but will enhance our knowledge of the repeatability of genomic landscapes across taxa. Here, we combine whole-genome resequencing and genome feature data to investigate the processes shaping the genomic landscape of differentiation for a sister-species pair of haplodiploid pine sawflies, Neodiprion lecontei and Neodiprion pinetum. We find genome-wide correlations between genome features and summary statistics are consistent with pervasive linked selection, with patterns of diversity and divergence more consistently predicted by exon density and recombination rate than the neutral mutation rate (approximated by dS). We also find that both global and local patterns of FST, dXY and π provide strong support for recurrent selection as the primary selective process shaping variation across pine sawfly genomes, with some contribution from balancing selection and lineage-specific linked selection. Because inheritance patterns for haplodiploid genomes are analogous to those of sex chromosomes, we hypothesize that haplodiploids may be especially prone to recurrent selection, even if gene flow occurred throughout divergence. Overall, our study helps fill an important taxonomic gap in the genomic landscape literature and contributes to our understanding of the processes that shape genome-wide patterns of genetic variation.

Selection leads to false inferences of introgression using popular methods

Detecting introgression between closely related populations or species is a fundamental objective in evolutionary biology. Existing methods for detecting migration and inferring migration rates from population genetic data often assume a neutral model of evolution. Growing evidence of the pervasive impact of selection on large portions of the genome across diverse taxa suggests that this assumption is unrealistic in most empirical systems. Further, ignoring selection has previously been shown to negatively impact demographic inferences (e.g. of population size histories). However, the impacts of biologically realistic selection on inferences of migration remain poorly explored. Here, we simulate data under models of background selection, selective sweeps, balancing selection, and adaptive introgression. We show that ignoring selection sometimes leads to false inferences of migration in popularly used methods that rely on the site frequency spectrum. Specifically, balancing selection and some models of background selection result in the rejection of isolation-only models in favor of isolation-with-migration models and lead to elevated estimates of migration rates. BPP, a method that analyzes sequence data directly, showed false positives for all conditions at recent divergence times, but balancing selection also led to false positives at medium-divergence times. Our results suggest that such methods may be unreliable in some empirical systems, such that new methods that are robust to selection need to be developed.

Linked Selection and Gene Density Shape Genome-Wide Patterns of Diversification in Peatmosses

Genome evolution under speciation is poorly understood in nonmodel and nonvascular plants, such as bryophytes-the largest group of nonvascular land plants. Their genomes are structurally different from angiosperms and likely subjected to stronger linked selection pressure, which may have profound consequences on genome evolution in diversifying lineages, even more so when their genome architecture is conserved. We use the highly diverse, rapidly radiated group of peatmosses (Sphagnum) to characterize the processes affecting genome diversification in bryophytes. Using whole-genome sequencing data from populations of 12 species sampled at different phylogenetic and geographical scales, we describe high correlation of the genomic landscapes of differentiation, divergence, and diversity in Sphagnum. Coupled with evidence from the patterns of covariation among different measures of genetic diversity, phylogenetic discordance, and gene density, this provides strong support that peatmoss genome evolution has been shaped by the long-term effects of linked selection, constrained by distribution of selection targets in the genome. Thus, peatmosses join the growing number of animal and plant groups where functional features of the genome, such as gene density, and linked selection drive genome evolution along predetermined and highly similar routes in different species. Our findings demonstrate the great potential of bryophytes for studying the genomics of speciation and highlight the urgent need to expand the genomic resources in this remarkable group of plants.

Genetic diversity of United States Rambouillet, Katahdin and Dorper sheep

BACKGROUND

Managing genetic diversity is critically important for maintaining species fitness. Excessive homozygosity caused by the loss of genetic diversity can have detrimental effects on the reproduction and production performance of a breed. Analysis of genetic diversity can facilitate the identification of signatures of selection which may contribute to the specific characteristics regarding the health, production and physical appearance of a breed or population. In this study, breeds with well-characterized traits such as fine wool production (Rambouillet, N = 745), parasite resistance (Katahdin, N = 581) and environmental hardiness (Dorper, N = 265) were evaluated for inbreeding, effective population size (Ne), runs of homozygosity (ROH) and Wright's fixation index (FST) outlier approach to identify differential signatures of selection at 36,113 autosomal single nucleotide polymorphisms (SNPs).

RESULTS

Katahdin sheep had the largest current Ne at the most recent generation estimated with both the GONe and NeEstimator software. The most highly conserved ROH Island was identified in Rambouillet with a signature of selection on chromosome 6 containing 202 SNPs called in an ROH in 50 to 94% of the individuals. This region contained the DCAF16, LCORL and NCAPG genes that have been previously reported to be under selection and have biological roles related to milk production and growth traits. The outlier regions identified through the FST comparisons of Katahdin with Rambouillet and Dorper contained genes with known roles in milk production and mastitis resistance or susceptibility, and the FST comparisons of Rambouillet with Katahdin and Dorper identified genes related to wool growth, suggesting these traits have been under natural or artificial selection pressure in these populations. Genes involved in the cytokine-cytokine receptor interaction pathways were identified in all FST breed comparisons, which indicates the presence of allelic diversity between these breeds in genomic regions controlling cytokine signaling mechanisms.

CONCLUSIONS

In this paper, we describe signatures of selection within diverse and economically important U.S. sheep breeds. The genes contained within these signatures are proposed for further study to understand their relevance to biological traits and improve understanding of breed diversity.

Causes and consequences of a complex recombinational landscape in the ant Cardiocondyla obscurior

Eusocial Hymenoptera have the highest recombination rates among all multicellular animals studied so far, but it is unclear why this is and how this affects the biology of individual species. A high-resolution linkage map for the ant Cardiocondyla obscurior corroborates genome-wide high recombination rates reported for ants (8.1 cM/Mb). However, recombination is locally suppressed in regions that are enriched with TEs, that have strong haplotype divergence, or that show signatures of epistatic selection in C. obscurior The results do not support the hypotheses that high recombination rates are linked to phenotypic plasticity or to modulating selection efficiency. Instead, genetic diversity and the frequency of structural variants correlate positively with local recombination rates, potentially compensating for the low levels of genetic variation expected in haplodiploid social Hymenoptera with low effective population size. Ultimately, the data show that recombination contributes to within-population polymorphism and to the divergence of the lineages within C. obscurior.

Drivers of genomic differentiation landscapes in populations of disparate ecological and geographical settings within mainland Apis cerana

Elucidating the evolutionary processes that drive population divergence can enhance our understanding of the early stages of speciation and inform conservation management decisions. The honeybee Apis cerana displays extensive population divergence, providing an informative natural system for exploring these processes. The mainland lineage A. cerana includes several peripheral subspecies with disparate ecological and geographical settings radiated from a central ancestor. Under this evolutionary framework, we can explore the patterns of genome differentiation and the evolutionary models that explain them. We can also elucidate the contribution of non-genomic spatiotemporal mechanisms (extrinsic features) and genomic mechanisms (intrinsic features) that influence these genomic differentiation landscapes. Based on 293 whole genomes, a small part of the genome is highly differentiated between central-peripheral subspecies pairs, while low and partial parallelism partly reflects idiosyncratic responses to environmental differences. Combined elements of recurrent selection and speciation-with-gene-flow models generate the heterogeneous genome landscapes. These elements weight differently between central-island and other central-peripheral subspecies pairs, influenced by glacial cycles superimposed on different geomorphologies. Although local recombination rates exert a significant influence on patterns of genomic differentiation, it is unlikely that low-recombination rates regions were generated by structural variation. In conclusion, complex factors including geographical isolation, divergent ecological selection and non-uniform genome features have acted concertedly in the evolution of reproductive barriers that could reduce gene flow in part of the genome and facilitate the persistence of distinct populations within mainland lineage of A. cerana.

Comparative population genomics reveals convergent and divergent selection in the apricot-peach-plum-mei complex

The economically significant genus Prunus includes fruit and nut crops that have been domesticated for shared and specific agronomic traits; however, the genomic signals of convergent and divergent selection have not been elucidated. In this study, we aimed to detect genomic signatures of convergent and divergent selection by conducting comparative population genomic analyses of the apricot-peach-plum-mei (APPM) complex, utilizing a haplotype-resolved telomere-to-telomere (T2T) genome assembly and population resequencing data. The haplotype-resolved T2T reference genome for the plum cultivar was assembled through HiFi and Hi-C reads, resulting in two haplotypes 251.25 and 251.29 Mb in size, respectively. Comparative genomics reveals a chromosomal translocation of ~1.17 Mb in the apricot genomes compared with peach, plum, and mei. Notably, the translocation involves the D locus, significantly impacting titratable acidity (TA), pH, and sugar content. Population genetic analysis detected substantial gene flow between plum and apricot, with introgression regions enriched in post-embryonic development and pollen germination processes. Comparative population genetic analyses revealed convergent selection for stress tolerance, flower development, and fruit ripening, along with divergent selection shaping specific crop, such as somatic embryogenesis in plum, pollen germination in mei, and hormone regulation in peach. Notably, selective sweeps on chromosome 7 coincide with a chromosomal collinearity from the comparative genomics, impacting key fruit-softening genes such as PG, regulated by ERF and RMA1H1. Overall, this study provides insights into the genetic diversity, evolutionary history, and domestication of the APPM complex, offering valuable implications for genetic studies and breeding programs of Prunus crops.

rec-1 loss of function increases recombination in the central gene clusters at the expense of autosomal pairing centers

Meiotic control of crossover (CO) number and position is critical for homologous chromosome segregation and organismal fertility, recombination of parental genotypes, and the generation of novel genetic combinations. We here characterize the recombination rate landscape of a rec-1 loss of function modifier of CO position in Caenorhabditis elegans, one of the first ever modifiers discovered. By averaging CO position across hermaphrodite and male meioses and by genotyping 203 single-nucleotide variants covering about 95% of the genome, we find that the characteristic chromosomal arm-center recombination rate domain structure is lost in the loss of function rec-1 mutant. The rec-1 loss of function mutant smooths the recombination rate landscape but is insufficient to eliminate the nonuniform position of CO. Lower recombination rates in the rec-1 mutant are particularly found in the autosomal arm domains containing the pairing centers. We further find that the rec-1 mutant is of little consequence for organismal fertility and egg viability and thus for rates of autosomal nondisjunction. It nonetheless increases X chromosome nondisjunction rates and thus male appearance. Our findings question the maintenance of recombination rate heritability and genetic diversity among C. elegans natural populations, and they further suggest that manipulating genetic modifiers of CO position will help find quantitative trait loci located in low-recombining genomic regions normally refractory to discovery.

Background Selection From Unlinked Sites Causes Nonindependent Evolution of Deleterious Mutations

Background selection describes the reduction in neutral diversity caused by selection against deleterious alleles at other loci. It is typically assumed that the purging of deleterious alleles affects linked neutral variants, and indeed simulations typically only treat a genomic window. However, background selection at unlinked loci also depresses neutral diversity. In agreement with previous analytical approximations, in our simulations of a human-like genome with a realistically high genome-wide deleterious mutation rate, the effects of unlinked background selection exceed those of linked background selection. Background selection reduces neutral genetic diversity by a factor that is independent of census population size. Outside of genic regions, the strength of background selection increases with the mean selection coefficient, contradicting the linked theory but in agreement with the unlinked theory. Neutral diversity within genic regions is fairly independent of the strength of selection. Deleterious genetic load among haploid individuals is underdispersed, indicating nonindependent evolution of deleterious mutations. Empirical evidence for underdispersion was previously interpreted as evidence for global epistasis, but we recover it from a non-epistatic model.

The impact of non-neutral synonymous mutations when inferring selection on non-synonymous mutations

The distribution of fitness effects (DFE) describes the proportions of new mutations that have different effects on reproductive fitness. Accurate measurements of the DFE are important because the DFE is a fundamental parameter in evolutionary genetics and has implications for our understanding of other phenomena like complex disease or inbreeding depression. Current computational methods to infer the DFE for nonsynonymous mutations from natural variation first estimate demographic parameters from synonymous variants to control for the effects of demography and background selection. Then, conditional on these parameters, the DFE is then inferred for nonsynonymous mutations. This approach relies on the assumption that synonymous variants are neutrally evolving. However, some evidence points toward synonymous mutations having measurable effects on fitness. To test whether selection on synonymous mutations affects inference of the DFE of nonsynonymous mutations, we simulated several possible models of selection on synonymous mutations using SLiM and attempted to recover the DFE of nonsynonymous mutations using Fit∂a∂i, a common method for DFE inference. Our results show that the presence of selection on synonymous variants leads to incorrect inferences of recent population growth. Furthermore, under certain parameter combinations, inferences of the DFE can have an inflated proportion of highly deleterious nonsynonymous mutations. However, this bias can be eliminated if the correct demographic parameters are used for DFE inference instead of the biased ones inferred from synonymous variants. Our work demonstrates how unmodeled selection on synonymous mutations may affect downstream inferences of the DFE.

The Effects of Mutation and Recombination Rate Heterogeneity on the Inference of Demography and the Distribution of Fitness Effects

Disentangling the effects of demography and selection has remained a focal point of population genetic analysis. Knowledge about mutation and recombination is essential in this endeavor; however, despite clear evidence that both mutation and recombination rates vary across genomes, it is common practice to model both rates as fixed. In this study, we quantify how this unaccounted for rate heterogeneity may impact inference using common approaches for inferring selection (DFE-alpha, Grapes, and polyDFE) and/or demography (fastsimcoal2 and δaδi). We demonstrate that, if not properly modeled, this heterogeneity can increase uncertainty in the estimation of demographic and selective parameters and in some scenarios may result in mis-leading inference. These results highlight the importance of quantifying the fundamental evolutionary parameters of mutation and recombination before utilizing population genomic data to quantify the effects of genetic drift (i.e. as modulated by demographic history) and selection; or, at the least, that the effects of uncertainty in these parameters can and should be directly modeled in downstream inference.

Moderating the neutralist-selectionist debate: exactly which propositions are we debating, and which arguments are valid?

Half a century after its foundation, the neutral theory of molecular evolution continues to attract controversy. The debate has been hampered by the coexistence of different interpretations of the core proposition of the neutral theory, the 'neutral mutation-random drift' hypothesis. In this review, we trace the origins of these ambiguities and suggest potential solutions. We highlight the difference between the original, the revised and the nearly neutral hypothesis, and re-emphasise that none of them equates to the null hypothesis of strict neutrality. We distinguish the neutral hypothesis of protein evolution, the main focus of the ongoing debate, from the neutral hypotheses of genomic and functional DNA evolution, which for many species are generally accepted. We advocate a further distinction between a narrow and an extended neutral hypothesis (of which the latter posits that random non-conservative amino acid substitutions can cause non-ecological phenotypic divergence), and we discuss the implications for evolutionary biology beyond the domain of molecular evolution. We furthermore point out that the debate has widened from its initial focus on point mutations, and also concerns the fitness effects of large-scale mutations, which can alter the dosage of genes and regulatory sequences. We evaluate the validity of neutralist and selectionist arguments and find that the tested predictions, apart from being sensitive to violation of underlying assumptions, are often derived from the null hypothesis of strict neutrality, or equally consistent with the opposing selectionist hypothesis, except when assuming molecular panselectionism. Our review aims to facilitate a constructive neutralist-selectionist debate, and thereby to contribute to answering a key question of evolutionary biology: what proportions of amino acid and nucleotide substitutions and polymorphisms are adaptive?

The role of recombination dynamics in shaping signatures of direct and indirect selection across the Ficedula flycatcher genome†

Recombination is a central evolutionary process that reshuffles combinations of alleles along chromosomes, and consequently is expected to influence the efficacy of direct selection via Hill-Robertson interference. Additionally, the indirect effects of selection on neutral genetic diversity are expected to show a negative relationship with recombination rate, as background selection and genetic hitchhiking are stronger when recombination rate is low. However, owing to the limited availability of recombination rate estimates across divergent species, the impact of evolutionary changes in recombination rate on genomic signatures of selection remains largely unexplored. To address this question, we estimate recombination rate in two Ficedula flycatcher species, the taiga flycatcher (Ficedula albicilla) and collared flycatcher (Ficedula albicollis). We show that recombination rate is strongly correlated with signatures of indirect selection, and that evolutionary changes in recombination rate between species have observable impacts on this relationship. Conversely, signatures of direct selection on coding sequences show little to no relationship with recombination rate, even when restricted to genes where recombination rate is conserved between species. Thus, using measures of indirect and direct selection that bridge micro- and macro-evolutionary timescales, we demonstrate that the role of recombination rate and its dynamics varies for different signatures of selection.

Accurate inference of population history in the presence of background selection

All published methods for learning about demographic history make the simplifying assumption that the genome evolves neutrally, and do not seek to account for the effects of natural selection on patterns of variation. This is a major concern, as ample work has demonstrated the pervasive effects of natural selection and in particular background selection (BGS) on patterns of genetic variation in diverse species. Simulations and theoretical work have shown that methods to infer changes in effective population size over time (Ne(t)) become increasingly inaccurate as the strength of linked selection increases. Here, we introduce an extension to the Pairwise Sequentially Markovian Coalescent (PSMC) algorithm, PSMC+, which explicitly co-models demographic history and natural selection. We benchmark our method using forward-in-time simulations with BGS and find that our approach improves the accuracy of effective population size inference. Leveraging a high resolution map of BGS in humans, we infer considerable changes in the magnitude of inferred effective population size relative to previous reports. Finally, we separately infer Ne(t) on the X chromosome and on the autosomes in diverse great apes without making a correction for selection, and find that the inferred ratio fluctuates substantially through time in a way that differs across species, showing that uncorrected selection may be an important driver of signals of genetic difference on the X chromosome and autosomes.

Mechanisms of Rapid Karyotype Evolution in Mammals

Chromosome reshuffling events are often a foundational mechanism by which speciation can occur, giving rise to highly derivative karyotypes even amongst closely related species. Yet, the features that distinguish lineages prone to such rapid chromosome evolution from those that maintain stable karyotypes across evolutionary time are still to be defined. In this review, we summarize lineages prone to rapid karyotypic evolution in the context of Simpson's rates of evolution-tachytelic, horotelic, and bradytelic-and outline the mechanisms proposed to contribute to chromosome rearrangements, their fixation, and their potential impact on speciation events. Furthermore, we discuss relevant genomic features that underpin chromosome variation, including patterns of fusions/fissions, centromere positioning, and epigenetic marks such as DNA methylation. Finally, in the era of telomere-to-telomere genomics, we discuss the value of gapless genome resources to the future of research focused on the plasticity of highly rearranged karyotypes.

Complex Evolutionary History With Extensive Ancestral Gene Flow in an African Primate Radiation

Understanding the drivers of speciation is fundamental in evolutionary biology, and recent studies highlight hybridization as an important evolutionary force. Using whole-genome sequencing data from 22 species of guenons (tribe Cercopithecini), one of the world's largest primate radiations, we show that rampant gene flow characterizes their evolutionary history and identify ancient hybridization across deeply divergent lineages that differ in ecology, morphology, and karyotypes. Some hybridization events resulted in mitochondrial introgression between distant lineages, likely facilitated by cointrogression of coadapted nuclear variants. Although the genomic landscapes of introgression were largely lineage specific, we found that genes with immune functions were overrepresented in introgressing regions, in line with adaptive introgression, whereas genes involved in pigmentation and morphology may contribute to reproductive isolation. In line with reports from other systems that hybridization might facilitate diversification, we find that some of the most species-rich guenon clades are of admixed origin. This study provides important insights into the prevalence, role, and outcomes of ancestral hybridization in a large mammalian radiation.

Landmarks in the history of selective sweeps

Half a century ago, a seminal article on the hitchhiking effect by Smith and Haigh inaugurated the concept of the selection signature. Selective sweeps are characterised by the rapid spread of an advantageous genetic variant through a population and hence play an important role in shaping evolution and research on genetic diversity. The process by which a beneficial allele arises and becomes fixed in a population, leading to a increase in the frequency of other linked alleles, is known as genetic hitchhiking or genetic draft. Kimura's neutral theory and hitchhiking theory are complementary, with Kimura's neutral evolution as the 'null model' and positive selection as the 'signal'. Both are widely accepted in evolution, especially with genomics enabling precise measurements. Significant advances in genomic technologies, such as next-generation sequencing, high-density SNP arrays and powerful bioinformatics tools, have made it possible to systematically investigate selection signatures in a variety of species. Although the history of selection signatures is relatively recent, progress has been made in the last two decades, owing to the increasing availability of large-scale genomic data and the development of computational methods. In this review, we embark on a journey through the history of research on selective sweeps, ranging from early theoretical work to recent empirical studies that utilise genomic data.

The effects of mutation and recombination rate heterogeneity on the inference of demography and the distribution of fitness effects

Disentangling the effects of demography and selection has remained a focal point of population genetic analysis. Knowledge about mutation and recombination is essential in this endeavour; however, despite clear evidence that both mutation and recombination rates vary across genomes, it is common practice to model both rates as fixed. In this study, we quantify how this unaccounted for rate heterogeneity may impact inference using common approaches for inferring selection (DFE-alpha, Grapes, and polyDFE) and/or demography (fastsimcoal2 and δaδi). We demonstrate that, if not properly modelled, this heterogeneity can increase uncertainty in the estimation of demographic and selective parameters and in some scenarios may result in mis-leading inference. These results highlight the importance of quantifying the fundamental evolutionary parameters of mutation and recombination prior to utilizing population genomic data to quantify the effects of genetic drift (i.e., as modulated by demographic history) and selection; or, at the least, that the effects of uncertainty in these parameters can and should be directly modelled in downstream inference.

Tensor Decomposition-based Feature Extraction and Classification to Detect Natural Selection from Genomic Data

Inferences of adaptive events are important for learning about traits, such as human digestion of lactose after infancy and the rapid spread of viral variants. Early efforts toward identifying footprints of natural selection from genomic data involved development of summary statistic and likelihood methods. However, such techniques are grounded in simple patterns or theoretical models that limit the complexity of settings they can explore. Due to the renaissance in artificial intelligence, machine learning methods have taken center stage in recent efforts to detect natural selection, with strategies such as convolutional neural networks applied to images of haplotypes. Yet, limitations of such techniques include estimation of large numbers of model parameters under nonconvex settings and feature identification without regard to location within an image. An alternative approach is to use tensor decomposition to extract features from multidimensional data although preserving the latent structure of the data, and to feed these features to machine learning models. Here, we adopt this framework and present a novel approach termed T-REx, which extracts features from images of haplotypes across sampled individuals using tensor decomposition, and then makes predictions from these features using classical machine learning methods. As a proof of concept, we explore the performance of T-REx on simulated neutral and selective sweep scenarios and find that it has high power and accuracy to discriminate sweeps from neutrality, robustness to common technical hurdles, and easy visualization of feature importance. Therefore, T-REx is a powerful addition to the toolkit for detecting adaptive processes from genomic data.

Evaluating power to detect recurrent selective sweeps under increasingly realistic evolutionary null models

The detection of selective sweeps from population genomic data often relies on the premise that the beneficial mutations in question have fixed very near the sampling time. As it has been previously shown that the power to detect a selective sweep is strongly dependent on the time since fixation as well as the strength of selection, it is naturally the case that strong, recent sweeps leave the strongest signatures. However, the biological reality is that beneficial mutations enter populations at a rate, one that partially determines the mean wait time between sweep events and hence their age distribution. An important question thus remains about the power to detect recurrent selective sweeps when they are modeled by a realistic mutation rate and as part of a realistic distribution of fitness effects, as opposed to a single, recent, isolated event on a purely neutral background as is more commonly modeled. Here we use forward-in-time simulations to study the performance of commonly used sweep statistics, within the context of more realistic evolutionary baseline models incorporating purifying and background selection, population size change, and mutation and recombination rate heterogeneity. Results demonstrate the important interplay of these processes, necessitating caution when interpreting selection scans; specifically, false-positive rates are in excess of true-positive across much of the evaluated parameter space, and selective sweeps are often undetectable unless the strength of selection is exceptionally strong.

Quantifying adaptive evolution and the effects of natural selection across the Norway spruce genome

Detecting natural selection is one of the major goals of evolutionary genomics. Here, we sequenced the whole genome of 25 Picea abies individuals and quantified the amount of selection across the genome. Using an estimate of the distribution of fitness effects, we showed that both negative selection and the rate of positively selected substitutions are very limited in coding regions. We found a positive correlation between the rate of adaptive substitutions and recombination rate and a negative correlation between the rate of adaptive substitutions and gene density, suggesting a widespread influence from Hill-Robertson interference on the efficiency of protein adaptation in P. abies. Finally, the distinct population statistics between genomic regions under either positive or balancing selection with that under neutral regions indicated the impact of natural selection on the genomic architecture of Norway spruce. Further gene ontology enrichment analysis for genes located in regions identified as undergoing either positive or long-term balancing selection also highlighted the specific molecular functions and biological processes that appear to be targets of selection in Norway spruce.

Effect of recombination on genetic diversity of Caenorhabditis elegans

Greater molecular divergence and genetic diversity are present in regions of high recombination in many species. Studies describing the correlation between variant abundance and recombination rate have long focused on recombination in the context of linked selection models, whereby interference between linked sites under positive or negative selection reduces genetic diversity in regions of low recombination. Here, we show that indels, especially those of intermediate sizes, are enriched relative to single nucleotide polymorphisms in regions of high recombination in C. elegans. To explain this phenomenon, we reintroduce an alternative model that emphasizes the mutagenic effect of recombination. To extend the analysis, we examine the variants with a phylogenetic context and discuss how different models could be examined together. The number of variants generated by recombination in natural populations could be substantial including possibly the majority of some indel subtypes. Our work highlights the potential importance of a mutagenic effect of recombination, which could have a significant role in the shaping of natural genetic diversity.

A few essential genetic loci distinguish Penstemon species with flowers adapted to pollination by bees or hummingbirds

In the formation of species, adaptation by natural selection generates distinct combinations of traits that function well together. The maintenance of adaptive trait combinations in the face of gene flow depends on the strength and nature of selection acting on the underlying genetic loci. Floral pollination syndromes exemplify the evolution of trait combinations adaptive for particular pollinators. The North American wildflower genus Penstemon displays remarkable floral syndrome convergence, with at least 20 separate lineages that have evolved from ancestral bee pollination syndrome (wide blue-purple flowers that present a landing platform for bees and small amounts of nectar) to hummingbird pollination syndrome (bright red narrowly tubular flowers offering copious nectar). Related taxa that differ in floral syndrome offer an attractive opportunity to examine the genomic basis of complex trait divergence. In this study, we characterized genomic divergence among 229 individuals from a Penstemon species complex that includes both bee and hummingbird floral syndromes. Field plants are easily classified into species based on phenotypic differences and hybrids displaying intermediate floral syndromes are rare. Despite unambiguous phenotypic differences, genome-wide differentiation between species is minimal. Hummingbird-adapted populations are more genetically similar to nearby bee-adapted populations than to geographically distant hummingbird-adapted populations, in terms of genome-wide dXY. However, a small number of genetic loci are strongly differentiated between species. These approximately 20 "species-diagnostic loci," which appear to have nearly fixed differences between pollination syndromes, are sprinkled throughout the genome in high recombination regions. Several map closely to previously established floral trait quantitative trait loci (QTLs). The striking difference between the diagnostic loci and the genome as whole suggests strong selection to maintain distinct combinations of traits, but with sufficient gene flow to homogenize the genomic background. A surprisingly small number of alleles confer phenotypic differences that form the basis of species identity in this species complex.

Genetic architecture and polygenic risk score prediction of degenerative suspensory ligament desmitis (DSLD) in the Peruvian Horse

Introduction: Spontaneous rupture of tendons and ligaments is common in several species including humans. In horses, degenerative suspensory ligament desmitis (DSLD) is an important acquired idiopathic disease of a major energy-storing tendon-like structure. DSLD risk is increased in several breeds, including the Peruvian Horse. Affected horses have often been used for breeding before the disease is apparent. Breed predisposition suggests a substantial genetic contribution, but heritability and genetic architecture of DSLD have not been determined. Methods: To identify genomic regions associated with DSLD, we recruited a reference population of 183 Peruvian Horses, phenotyped as DSLD cases or controls, and undertook a genome-wide association study (GWAS), a regional window variance analysis using local genomic partitioning, a signatures of selection (SOS) analysis, and polygenic risk score (PRS) prediction of DSLD risk. We also estimated trait heritability from pedigrees. Results: Heritability was estimated in a population of 1,927 Peruvian horses at 0.22 ± 0.08. After establishing a permutation-based threshold for genome-wide significance, 151 DSLD risk single nucleotide polymorphisms (SNPs) were identified by GWAS. Multiple regions of enriched local heritability were identified across the genome, with strong enrichment signals on chromosomes 1, 2, 6, 10, 13, 16, 18, 22, and the X chromosome. With SOS analysis, there were 66 genes with a selection signature in DSLD cases that was not present in the control group that included the TGFB3 gene. Pathways enriched in DSLD cases included proteoglycan metabolism, extracellular matrix homeostasis, and signal transduction pathways that included the hedgehog signaling pathway. The best PRS predictive performance was obtained when we fitted 1% of top SNPs using a Bayesian Ridge Regression model which achieved the highest mean of R2 on both the probit and logit liability scales, indicating a strong predictive performance. Discussion: We conclude that within-breed GWAS of DSLD in the Peruvian Horse has further confirmed that moderate heritability and a polygenic architecture underlies the trait and identified multiple DSLD SNP associations in novel tendinopathy candidate genes influencing disease risk. Pathways enriched with DSLD risk variants include ones that influence glycosaminoglycan metabolism, extracellular matrix homeostasis, signal transduction pathways.

Nascent evolution of recombination rate differences as a consequence of chromosomal rearrangements

Reshuffling of genetic variation occurs both by independent assortment of chromosomes and by homologous recombination. Such reshuffling can generate novel allele combinations and break linkage between advantageous and deleterious variants which increases both the potential and the efficacy of natural selection. Here we used high-density linkage maps to characterize global and regional recombination rate variation in two populations of the wood white butterfly (Leptidea sinapis) that differ considerably in their karyotype as a consequence of at least 27 chromosome fissions and fusions. The recombination data were compared to estimates of genetic diversity and measures of selection to assess the relationship between chromosomal rearrangements, crossing over, maintenance of genetic diversity and adaptation. Our data show that the recombination rate is influenced by both chromosome size and number, but that the difference in the number of crossovers between karyotypes is reduced as a consequence of a higher frequency of double crossovers in larger chromosomes. As expected from effects of selection on linked sites, we observed an overall positive association between recombination rate and genetic diversity in both populations. Our results also revealed a significant effect of chromosomal rearrangements on the rate of intergenic diversity change between populations, but limited effects on polymorphisms in coding sequence. We conclude that chromosomal rearrangements can have considerable effects on the recombination landscape and consequently influence both maintenance of genetic diversity and efficiency of selection in natural populations.

Genomic diversity landscapes in outcrossing and selfing Caenorhabditis nematodes

Caenorhabditis nematodes form an excellent model for studying how the mode of reproduction affects genetic diversity, as some species reproduce via outcrossing whereas others can self-fertilize. Currently, chromosome-level patterns of diversity and recombination are only available for self-reproducing Caenorhabditis, making the generality of genomic patterns across the genus unclear given the profound potential influence of reproductive mode. Here we present a whole-genome diversity landscape, coupled with a new genetic map, for the outcrossing nematode C. remanei. We demonstrate that the genomic distribution of recombination in C. remanei, like the model nematode C. elegans, shows high recombination rates on chromosome arms and low rates toward the central regions. Patterns of genetic variation across the genome are also similar between these species, but differ dramatically in scale, being tenfold greater for C. remanei. Historical reconstructions of variation in effective population size over the past million generations echo this difference in polymorphism. Evolutionary simulations demonstrate how selection, recombination, mutation, and selfing shape variation along the genome, and that multiple drivers can produce patterns similar to those observed in natural populations. The results illustrate how genome organization and selection play a crucial role in shaping the genomic pattern of diversity whereas demographic processes scale the level of diversity across the genome as a whole.

Detecting parallel polygenic adaptation to novel evolutionary pressure in wild populations: a case study in Atlantic cod (Gadus morhua)

Populations can adapt to novel selection pressures through dramatic frequency changes in a few genes of large effect or subtle shifts in many genes of small effect. The latter (polygenic adaptation) is expected to be the primary mode of evolution for many life-history traits but tends to be more difficult to detect than changes in genes of large effect. Atlantic cod (Gadus morhua) were subjected to intense fishing pressure over the twentieth century, leading to abundance crashes and a phenotypic shift toward earlier maturation across many populations. Here, we use spatially replicated temporal genomic data to test for a shared polygenic adaptive response to fishing using methods previously applied to evolve-and-resequence experiments. Cod populations on either side of the Atlantic show covariance in allele frequency change across the genome that are characteristic of recent polygenic adaptation. Using simulations, we demonstrate that the degree of covariance in allele frequency change observed in cod is unlikely to be explained by neutral processes or background selection. As human pressures on wild populations continue to increase, understanding and attributing modes of adaptation using methods similar to those demonstrated here will be important in identifying the capacity for adaptive responses and evolutionary rescue. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

The role of recombination landscape in species hybridisation and speciation

It is now well recognised that closely related species can hybridize and exchange genetic material, which may promote or oppose adaptation and speciation. In some cases, interspecific hybridisation is very common, making it surprising that species identity is preserved despite active gene exchange. The genomes of most eukaryotic species are highly heterogeneous with regard to gene density, abundance of repetitive DNA, chromatin compactisation etc, which can make certain genomic regions more prone or more resistant to introgression of genetic material from other species. Heterogeneity in local recombination rate underpins many of the observed patterns across the genome (e.g. actively recombining regions are typically gene rich and depleted for repetitive DNA) and it can strongly affect the permeability of genomic regions to interspecific introgression. The larger the region lacking recombination, the higher the chance for the presence of species incompatibility gene(s) in that region, making the entire non- or rarely recombining block impermeable to interspecific introgression. Large plant genomes tend to have highly heterogeneous recombination landscape, with recombination frequently occurring at the ends of the chromosomes and central regions lacking recombination. In this paper we review the relationship between recombination and introgression in plants and argue that large rarely recombining regions likely play a major role in preserving species identity in actively hybridising plant species.

Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations

Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic datasets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than threefold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed the best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.

Evaluating power to detect recurrent selective sweeps under increasingly realistic evolutionary null models

The detection of selective sweeps from population genomic data often relies on the premise that the beneficial mutations in question have fixed very near the sampling time. As it has been previously shown that the power to detect a selective sweep is strongly dependent on the time since fixation as well as the strength of selection, it is naturally the case that strong, recent sweeps leave the strongest signatures. However, the biological reality is that beneficial mutations enter populations at a rate, one that partially determines the mean wait time between sweep events and hence their age distribution. An important question thus remains about the power to detect recurrent selective sweeps when they are modelled by a realistic mutation rate and as part of a realistic distribution of fitness effects (DFE), as opposed to a single, recent, isolated event on a purely neutral background as is more commonly modelled. Here we use forward-in-time simulations to study the performance of commonly used sweep statistics, within the context of more realistic evolutionary baseline models incorporating purifying and background selection, population size change, and mutation and recombination rate heterogeneity. Results demonstrate the important interplay of these processes, necessitating caution when interpreting selection scans; specifically, false positive rates are in excess of true positive across much of the evaluated parameter space, and selective sweeps are often undetectable unless the strength of selection is exceptionally strong.

Teaser Text

Outlier-based genomic scans have proven a popular approach for identifying loci that have potentially experienced recent positive selection. However, it has previously been shown that an evolutionarily appropriate baseline model that incorporates non-equilibrium population histories, purifying and background selection, and variation in mutation and recombination rates is necessary to reduce often extreme false positive rates when performing genomic scans. Here we evaluate the power to detect recurrent selective sweeps using common SFS-based and haplotype-based methods under these increasingly realistic models. We find that while these appropriate evolutionary baselines are essential to reduce false positive rates, the power to accurately detect recurrent selective sweeps is generally low across much of the biologically relevant parameter space.

Reconstructing the colonization history of Indo-Pacific bottlenose dolphins (Tursiops aduncus) in Northwestern Australia

Bottlenose dolphins (Tursiops spp.) are found in waters around Australia, with T. truncatus typically occupying deeper, more oceanic habitat, while T. aduncus occur in shallower, coastal waters. Little is known about the colonization history of T. aduncus along the Western Australian coastline; however, it has been hypothesized that extant populations are the result of an expansion along the coastline originating from a source in the north of Australia. To investigate the history of coastal T. aduncus populations in the area, we generated a genomic SNP dataset using a double-digest restriction-site-associated DNA (ddRAD) sequencing approach. The resulting dataset consisted of 103,201 biallelic SNPs for 112 individuals which were sampled from eleven coastal and two offshore sites between Shark Bay and Cygnet Bay, Western Australia. Our population genomic analyses showed a pattern consistent with the proposed source in the north with significant isolation by distance along the coastline, as well as a reduction in genomic diversity measures along the coastline with Shark Bay showing the most pronounced reduction. Our demographic analysis indicated that the expansion of T. aduncus along the coastline began around the last glacial maximum and progressed southwards with the Shark Bay population being founded only 13 kya. Our results are in line with coastal colonization histories inferred for Tursiops globally, highlighting the ability of delphinids to rapidly colonize novel coastal niches as habitat is released during glacial cycle-related global sea level and temperature changes.

The fine-scale recombination rate variation and associations with genomic features in a butterfly

Recombination is a key molecular mechanism that has profound implications on both micro- and macroevolutionary processes. However, the determinants of recombination rate variation in holocentric organisms are poorly understood, in particular in Lepidoptera (moths and butterflies). The wood white butterfly (Leptidea sinapis) shows considerable intraspecific variation in chromosome numbers and is a suitable system for studying regional recombination rate variation and its potential molecular underpinnings. Here, we developed a large whole-genome resequencing data set from a population of wood whites to obtain high-resolution recombination maps using linkage disequilibrium information. The analyses revealed that larger chromosomes had a bimodal recombination landscape, potentially caused by interference between simultaneous chiasmata. The recombination rate was significantly lower in subtelomeric regions, with exceptions associated with segregating chromosome rearrangements, showing that fissions and fusions can have considerable effects on the recombination landscape. There was no association between the inferred recombination rate and base composition, supporting a limited influence of GC-biased gene conversion in butterflies. We found significant but variable associations between the recombination rate and the density of different classes of transposable elements, most notably a significant enrichment of short interspersed nucleotide elements in genomic regions with higher recombination rate. Finally, the analyses unveiled significant enrichment of genes involved in farnesyltranstransferase activity in recombination coldspots, potentially indicating that expression of transferases can inhibit formation of chiasmata during meiotic division. Our results provide novel information about recombination rate variation in holocentric organisms and have particular implications for forthcoming research in population genetics, molecular/genome evolution, and speciation.

Fine mapping of meiotic crossovers in Brassica oleracea reveals patterns and variations depending on direction and combination of crosses

Meiotic recombination is crucial for assuring proper segregation of parental chromosomes and generation of novel allelic combinations. As this process is tightly regulated, identifying factors influencing rate, and distribution of meiotic crossovers (COs) is of major importance, notably for plant breeding programs. However, high-resolution recombination maps are sparse in most crops including the Brassica genus and knowledge about intraspecific variation and sex differences is lacking. Here, we report fine-scale resolution recombination landscapes for 10 female and 10 male crosses in Brassica oleracea, by analyzing progenies of five large four-way-cross populations from two reciprocally crossed F1s per population. Parents are highly diverse inbred lines representing major crops, including broccoli, cauliflower, cabbage, kohlrabi, and kale. We produced approximately 4.56T Illumina data from 1248 progenies and identified 15 353 CO across the 10 reciprocal crosses, 51.13% of which being mapped to <10 kb. We revealed fairly similar Mb-scale recombination landscapes among all cross combinations and between the sexes, and provided evidence that these landscapes are largely independent of sequence divergence. We evidenced strong influence of gene density and large structural variations on CO formation in B. oleracea. Moreover, we found extensive variations in CO number depending on the direction and combination of the initial parents crossed with, for the first time, a striking interdependency between these factors. These data improve our current knowledge on meiotic recombination and are important for Brassica breeders.

Demography and linked selection interact to shape the genomic landscape of codistributed woodpeckers during the Ice Age

The influence of genetic drift on population dynamics during Pleistocene glacial cycles is well understood, but the role of selection in shaping patterns of genomic variation during these events is less explored. We resequenced whole genomes to investigate how demography and natural selection interact to generate the genomic landscapes of Downy and Hairy Woodpecker, species codistributed in previously glaciated North America. First, we explored the spatial and temporal patterns of genomic diversity produced by neutral evolution. Next, we tested (i) whether levels of nucleotide diversity along the genome are correlated with intrinsic genomic properties, such as recombination rate and gene density, and (ii) whether different demographic trajectories impacted the efficacy of selection. Our results revealed cycles of bottleneck and expansion, and genetic structure associated with glacial refugia. Nucleotide diversity varied widely along the genome, but this variation was highly correlated between the species, suggesting the presence of conserved genomic features. In both taxa, nucleotide diversity was positively correlated with recombination rate and negatively correlated with gene density, suggesting that linked selection played a role in reducing diversity. Despite strong fluctuations in effective population size, the maintenance of relatively large populations during glaciations may have facilitated selection. Under these conditions, we found evidence that the individual demographic trajectory of populations modulated linked selection, with purifying selection being more efficient in removing deleterious alleles in large populations. These results highlight that while genome-wide variation reflects the expected signature of demographic change during climatic perturbations, the interaction of multiple processes produces a predictable and highly heterogeneous genomic landscape.

The effect of DNA polymorphisms and natural variation on crossover hotspot activity in Arabidopsis hybrids

In hybrid organisms, genetically divergent homologous chromosomes pair and recombine during meiosis; however, the effect of specific types of polymorphisms on crossover is poorly understood. Here, to analyze this in Arabidopsis, we develop the seed-typing method that enables the massively parallel fine-mapping of crossovers by sequencing. We show that structural variants, observed in one of the generated intervals, do not change crossover frequency unless they are located directly within crossover hotspots. Both natural and Cas9-induced deletions result in lower hotspot activity but are not compensated by increases in immediately adjacent hotspots. To examine the effect of single nucleotide polymorphisms on crossover formation, we analyze hotspot activity in mismatch detection-deficient msh2 mutants. Surprisingly, polymorphic hotspots show reduced activity in msh2. In lines where only the hotspot-containing interval is heterozygous, crossover numbers increase above those in the inbred (homozygous). We conclude that MSH2 shapes crossover distribution by stimulating hotspot activity at polymorphic regions.

High heterogeneity in genomic differentiation between phenotypically divergent songbirds: a test of mitonuclear co-introgression

Comparisons of genomic variation among closely related species often show more differentiation in mitochondrial DNA (mtDNA) and sex chromosomes than in autosomes, a pattern expected due to the differing effective population sizes and evolutionary dynamics of these genomic components. Yet, introgression can cause species pairs to deviate dramatically from general differentiation trends. The yellowhammer (Emberiza citrinella) and pine bunting (E. leucocephalos) are hybridizing avian sister species that differ greatly in appearance and moderately in nuclear DNA, but that show no mtDNA differentiation. This discordance is best explained by adaptive mtDNA introgression-a process that can select for co-introgression at nuclear genes with mitochondrial functions (mitonuclear genes). To better understand these discordant differentiation patterns and characterize nuclear differentiation in this system, we investigated genome-wide differentiation between allopatric yellowhammers and pine buntings and compared it to what was seen previously in mtDNA. We found significant nuclear differentiation that was highly heterogeneous across the genome, with a particularly wide differentiation peak on the sex chromosome Z. We further investigated mitonuclear gene co-introgression between yellowhammers and pine buntings and found support for this process in the direction of pine buntings into yellowhammers. Genomic signals indicative of co-introgression were common in mitonuclear genes coding for subunits of the mitoribosome and electron transport chain complexes. Such introgression of mitochondrial DNA and mitonuclear genes provides a possible explanation for the patterns of high genomic heterogeneity in genomic differentiation seen among some species groups.

The genomic scale of fluctuating selection in a natural plant population

This study characterizes evolution at ≈1.86 million Single Nucleotide Polymorphisms (SNPs) within a natural population of yellow monkeyflower (Mimulus guttatus). Most SNPs exhibit minimal change over a span of 23 generations (less than 1% per year), consistent with neutral evolution in a large population. However, several thousand SNPs display strong fluctuations in frequency. Multiple lines of evidence indicate that these 'Fluctuating SNPs' are driven by temporally varying selection. Unlinked loci exhibit synchronous changes with the same allele increasing consistently in certain time intervals but declining in others. This synchrony is sufficiently pronounced that we can roughly classify intervals into two categories, "green" and "yellow," corresponding to conflicting selection regimes. Alleles increasing in green intervals are associated with early life investment in vegetative tissue and delayed flowering. The alternative alleles that increase in yellow intervals are associated with rapid progression to flowering. Selection on the Fluctuating SNPs produces a strong ripple effect on variation across the genome. Accounting for estimation error, we estimate the distribution of allele frequency change per generation in this population. While change is minimal for most SNPs, diffuse hitchhiking effects generated by selected loci may be driving neutral SNPs to a much greater extent than classic genetic drift.

Evidence that genomic incompatibilities and other multilocus processes impact hybrid fitness in a rattlesnake hybrid zone

Hybrid zones provide valuable opportunities to understand the genomic mechanisms that promote speciation by providing insight into factors involved in intermediate stages of speciation. Here, we investigate introgression in a hybrid zone between two rattlesnake species (Crotalus viridis and Crotalus oreganus concolor) that have undergone historical allopatric divergence and recent range expansion and secondary contact. We use Bayesian genomic cline models to characterize genomic patterns of introgression between these lineages and identify loci potentially subject to selection in hybrids. We find evidence for a large number of genomic regions with biased ancestry that deviate from the genomic background in hybrids (i.e., excess ancestry loci), which tend to be associated with genomic regions with higher recombination rates. We also identify suites of excess ancestry loci that show highly correlated allele frequencies (including conspecific and heterospecific combinations) across physically unlinked genomic regions in hybrids. Our findings provide evidence for multiple multilocus evolutionary processes impacting hybrid fitness in this system.

A butterfly pan-genome reveals that a large amount of structural variation underlies the evolution of chromatin accessibility

Despite insertions and deletions being the most common structural variants (SVs) found across genomes, not much is known about how much these SVs vary within populations and between closely related species, nor their significance in evolution. To address these questions, we characterized the evolution of indel SVs using genome assemblies of three closely related Heliconius butterfly species. Over the relatively short evolutionary timescales investigated, up to 18.0% of the genome was composed of indels between two haplotypes of an individual Heliconius charithonia butterfly and up to 62.7% included lineage-specific SVs between the genomes of the most distant species (11 Mya). Lineage-specific sequences were mostly characterized as transposable elements (TEs) inserted at random throughout the genome and their overall distribution was similarly affected by linked selection as single nucleotide substitutions. Using chromatin accessibility profiles (i.e., ATAC-seq) of head tissue in caterpillars to identify sequences with potential cis-regulatory function, we found that out of the 31,066 identified differences in chromatin accessibility between species, 30.4% were within lineage-specific SVs and 9.4% were characterized as TE insertions. These TE insertions were localized closer to gene transcription start sites than expected at random and were enriched for sites with significant resemblance to several transcription factor binding sites with known function in neuron development in Drosophila We also identified 24 TE insertions with head-specific chromatin accessibility. Our results show high rates of structural genome evolution that were previously overlooked in comparative genomic studies and suggest a high potential for structural variation to serve as raw material for adaptive evolution.