Genome-wide fine-scale recombination rate variation in Drosophila melanogaster

Genomic architecture and introgression shape a butterfly radiation

We used 20 de novo genome assemblies to probe the speciation history and architecture of gene flow in rapidly radiating Heliconius butterflies. Our tests to distinguish incomplete lineage sorting from introgression indicate that gene flow has obscured several ancient phylogenetic relationships in this group over large swathes of the genome. Introgressed loci are underrepresented in low-recombination and gene-rich regions, consistent with the purging of foreign alleles more tightly linked to incompatibility loci. Here, we identify a hitherto unknown inversion that traps a color pattern switch locus. We infer that this inversion was transferred between lineages by introgression and is convergent with a similar rearrangement in another part of the genus. These multiple de novo genome sequences enable improved understanding of the importance of introgression and selective processes in adaptive radiation.

Inference of recombination maps from a single pair of genomes and its application to ancient samples

Understanding the causes and consequences of recombination landscape evolution is a fundamental goal in genetics that requires recombination maps from across the tree of life. Such maps can be obtained from population genomic datasets, but require large sample sizes. Alternative methods are therefore necessary to research organisms where such datasets cannot be generated easily, such as non-model or ancient species. Here we extend the sequentially Markovian coalescent model to jointly infer demography and the spatial variation in recombination rate. Using extensive simulations and sequence data from humans, fruit-flies and a fungal pathogen, we demonstrate that iSMC accurately infers recombination maps under a wide range of scenarios-remarkably, even from a single pair of unphased genomes. We exploit this possibility and reconstruct the recombination maps of ancient hominins. We report that the ancient and modern maps are correlated in a manner that reflects the established phylogeny of Neanderthals, Denisovans, and modern human populations.

Inference and analysis of population-specific fine-scale recombination maps across 26 diverse human populations

Fine-scale rates of meiotic recombination vary by orders of magnitude across the genome and differ between species and even populations. Studying cross-population differences has been stymied by the confounding effects of demographic history. To address this problem, we developed a demography-aware method to infer fine-scale recombination rates and applied it to 26 diverse human populations, inferring population-specific recombination maps. These maps recapitulate many aspects of the history of these populations including signatures of the trans-Atlantic slave trade and the Iberian colonization of the Americas. We also investigated modulators of the local recombination rate, finding further evidence that Polycomb group proteins and the trimethylation of H3K27 elevate recombination rates. Further differences in the recombination landscape across the genome and between populations are driven by variation in the gene that encodes the DNA binding protein PRDM9, and we quantify the weak effect of meiotic drive acting to remove its binding sites.

Dissecting the Effects of Selection and Mutation on Genetic Diversity in Three Wood White (Leptidea) Butterfly Species

The relative role of natural selection and genetic drift in evolution is a major topic of debate in evolutionary biology. Most knowledge spring from a small group of organisms and originate from before it was possible to generate genome-wide data on genetic variation. Hence, it is necessary to extend to a larger number of taxonomic groups, descriptive and hypothesis-based research aiming at understanding the proximate and ultimate mechanisms underlying both levels of genetic polymorphism and the efficiency of natural selection. In this study, we used data from 60 whole-genome resequenced individuals of three cryptic butterfly species (Leptidea sp.), together with novel gene annotation information and population recombination data. We characterized the overall prevalence of natural selection and investigated the effects of mutation and linked selection on regional variation in nucleotide diversity. Our analyses showed that genome-wide diversity and rate of adaptive substitutions were comparatively low, whereas nonsynonymous to synonymous polymorphism and substitution levels were comparatively high in Leptidea, suggesting small long-term effective population sizes. Still, negative selection on linked sites (background selection) has resulted in reduced nucleotide diversity in regions with relatively high gene density and low recombination rate. We also found a significant effect of mutation rate variation on levels of polymorphism. Finally, there were considerable population differences in levels of genetic diversity and pervasiveness of selection against slightly deleterious alleles, in line with expectations from differences in estimated effective population sizes.

Balancing Selection Drives the Maintenance of Genetic Variation in Drosophila Antimicrobial Peptides

Genes involved in immune defense against pathogens provide some of the most well-known examples of both directional and balancing selection. Antimicrobial peptides (AMPs) are innate immune effector genes, playing a key role in pathogen clearance in many species, including Drosophila. Conflicting lines of evidence have suggested that AMPs may be under directional, balancing, or purifying selection. Here, we use both a linear model and control-gene-based approach to show that balancing selection is an important force shaping AMP diversity in Drosophila. In Drosophila melanogaster, this is most clearly observed in ancestral African populations. Furthermore, the signature of balancing selection is even more striking once background selection has been accounted for. Balancing selection also acts on AMPs in Drosophila mauritiana, an isolated island endemic separated from D. melanogaster by about 4 Myr of evolution. This suggests that balancing selection may be broadly acting to maintain adaptive diversity in Drosophila AMPs, as has been found in other taxa.

DNA Motifs Are Not General Predictors of Recombination in Two Drosophila Sister Species

Meiotic recombination is crucial for chromosomal segregation and facilitates the spread of beneficial and removal of deleterious mutations. Recombination rates frequently vary along chromosomes and Drosophila melanogaster exhibits a remarkable pattern. Recombination rates gradually decrease toward centromeres and telomeres, with a dramatic impact on levels of variation in natural populations. Two close sister species, Drosophila simulans and Drosophila mauritiana do not only have higher recombination rates but also exhibit a much more homogeneous recombination rate that only drops sharply very close to centromeres and telomeres. Because certain sequence motifs are associated with recombination rate variation in D. melanogaster, we tested whether the difference in recombination landscape between D. melanogaster and D. simulans can be explained by the genomic distribution of recombination rate–associated sequence motifs. We constructed the first high-resolution recombination map for D. simulans based on 189 haplotypes from a natural D. simulans population and searched for short sequence motifs linked with higher than average recombination in both sister species. We identified five consensus motifs significantly associated with higher than average chromosome-wide recombination rates in at least one species and present in both. Testing fine resolution associations between motif density and recombination, we found strong and positive associations genome-wide over a range of scales in D. melanogaster, while the results were equivocal in D. simulans. Despite the strong association in D. melanogaster, we did not find a decreasing density of these short-repeat motifs toward centromeres and telomeres. We conclude that the density of recombination-associated repeat motifs cannot explain the large-scale recombination landscape in D. melanogaster, nor the differences to D. simulans. The strong association seen for the sequence motifs in D. melanogaster likely reflects their impact influencing local differences in recombination rates along the genome.

What can be learned by scanning the genome for molecular convergence in wild populations?

Convergent evolution, where independent lineages evolve similar phenotypes in response to similar challenges, can provide valuable insight into how selection operates and the limitations it encounters. However, it has only recently become possible to explore how convergent evolution is reflected at the genomic level. The overlapping outlier approach (OOA), where genome scans of multiple independent lineages are used to find outliers that overlap and therefore identify convergently evolving loci, is becoming popular. Here, we present a quantitative analysis of 34 studies that used this approach across many sampling designs, taxa, and sampling intensities. We found that OOA studies with increased biological sampling power within replicates have increased likelihood of finding overlapping, "convergent" signals of adaptation between them. When identifying convergent loci as overlapping outliers, it is tempting to assume that any false-positive outliers derived from individual scans will fail to overlap across replicates, but this cannot be guaranteed. We highlight how population demographics and genomic context can contribute toward both true convergence and false positives in OOA studies. We finish with an exploration of emerging methods that couple genome scans with phenotype and environmental measures, leveraging added information from genome data to more directly test hypotheses of the likelihood of convergent evolution.

Ancient polymorphisms contribute to genome-wide variation by long-term balancing selection and divergent sorting in Boechera stricta

BACKGROUND

Genomic variation is widespread, and both neutral and selective processes can generate similar patterns in the genome. These processes are not mutually exclusive, so it is difficult to infer the evolutionary mechanisms that govern population and species divergence. Boechera stricta is a perennial relative of Arabidopsis thaliana native to largely undisturbed habitats with two geographic and ecologically divergent subspecies. Here, we delineate the evolutionary processes driving the genetic diversity and population differentiation in this species.

RESULTS

Using whole-genome re-sequencing data from 517 B. stricta accessions, we identify four genetic groups that diverged around 30-180 thousand years ago, with long-term small effective population sizes and recent population expansion after the Last Glacial Maximum. We find three genomic regions with elevated nucleotide diversity, totaling about 10% of the genome. These three regions of elevated nucleotide diversity show excess of intermediate-frequency alleles, higher absolute divergence (dXY), and lower relative divergence (FST) than genomic background, and significant enrichment in immune-related genes, reflecting long-term balancing selection. Scattered across the genome, we also find regions with both high FST and dXY among the groups, termed FST-islands. Population genetic signatures indicate that FST-islands with elevated divergence, which have experienced directional selection, are derived from divergent sorting of ancient polymorphisms.

CONCLUSIONS

Our results suggest that long-term balancing selection on disease resistance genes may have maintained ancestral haplotypes across different geographical lineages, and unequal sorting of balanced polymorphisms may have generated genomic regions with elevated divergence. This study highlights the importance of ancestral balanced polymorphisms as crucial components of genome-wide variation.

Divergent Fine-Scale Recombination Landscapes between a Freshwater and Marine Population of Threespine Stickleback Fish

Meiotic recombination is a highly conserved process that has profound effects on genome evolution. At a fine-scale, recombination rates can vary drastically across genomes, often localized into small recombination "hotspots" with highly elevated rates, surrounded by regions with little recombination. In most species studied, the location of hotspots within genomes is highly conserved across broad evolutionary timescales. The main exception to this pattern is in mammals, where hotspot location can evolve rapidly among closely related species and even among populations within a species. Hotspot position in mammals is controlled by the gene, Prdm9, whereas in species with conserved hotspots, a functional Prdm9 is typically absent. Due to a limited number of species where recombination rates have been estimated at a fine-scale, it remains unclear whether hotspot conservation is always associated with the absence of a functional Prdm9. Threespine stickleback fish (Gasterosteus aculeatus) are an excellent model to examine the evolution of recombination over short evolutionary timescales. Using a linkage disequilibrium-based approach, we found recombination rates indeed varied at a fine-scale across the genome, with many regions organized into narrow hotspots. Hotspots had highly divergent landscapes between stickleback populations, where only ∼15% of these hotspots were shared. Our results indicate that fine-scale recombination rates may be diverging between closely related populations of threespine stickleback fish. Interestingly, we found only a weak association of a PRDM9 binding motif within hotspots, which suggests that threespine stickleback fish may possess a novel mechanism for targeting recombination hotspots at a fine-scale.

Models of archaic admixture and recent history from two-locus statistics

We learn about population history and underlying evolutionary biology through patterns of genetic polymorphism. Many approaches to reconstruct evolutionary histories focus on a limited number of informative statistics describing distributions of allele frequencies or patterns of linkage disequilibrium. We show that many commonly used statistics are part of a broad family of two-locus moments whose expectation can be computed jointly and rapidly under a wide range of scenarios, including complex multi-population demographies with continuous migration and admixture events. A full inspection of these statistics reveals that widely used models of human history fail to predict simple patterns of linkage disequilibrium. To jointly capture the information contained in classical and novel statistics, we implemented a tractable likelihood-based inference framework for demographic history. Using this approach, we show that human evolutionary models that include archaic admixture in Africa, Asia, and Europe provide a much better description of patterns of genetic diversity across the human genome. We estimate that an unidentified, deeply diverged population admixed with modern humans within Africa both before and after the split of African and Eurasian populations, contributing 4 - 8% genetic ancestry to individuals in world-wide populations.

LDJump: Estimating variable recombination rates from population genetic data

As recombination plays an important role in evolution, its estimation and the identification of hotspot positions is of considerable interest. We propose a novel approach for estimating population recombination rates based on genotyping or sequence data that involves a sequential multiscale change point estimator. Our method also permits demography to be taken into account. It uses several summary statistics within a regression model fitted on suitable scenarios. Our proposed method is accurate, computationally fast, and provides a parsimonious solution by ensuring a type I error control against too many changes in the recombination rate. An application to human genome data suggests a good congruence between our estimated and experimentally identified hotspots. Our method is implemented in the R-package LDJump, which is freely available at https://github.com/PhHermann/LDJump.

Colocalization analyses of genomic elements: approaches, recommendations and challenges

MOTIVATION

Many high-throughput methods produce sets of genomic regions as one of their main outputs. Scientists often use genomic colocalization analysis to interpret such region sets, for example to identify interesting enrichments and to understand the interplay between the underlying biological processes. Although widely used, there is little standardization in how these analyses are performed. Different practices can substantially affect the conclusions of colocalization analyses.

RESULTS

Here, we describe the different approaches and provide recommendations for performing genomic colocalization analysis, while also discussing common methodological challenges that may influence the conclusions. As illustrated by concrete example cases, careful attention to analysis details is needed in order to meet these challenges and to obtain a robust and biologically meaningful interpretation of genomic region set data.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Analysis of 100 high-coverage genomes from a pedigreed captive baboon colony

Baboons (genus Papio) are broadly studied in the wild and in captivity. They are widely used as a nonhuman primate model for biomedical studies, and the Southwest National Primate Research Center (SNPRC) at Texas Biomedical Research Institute has maintained a large captive baboon colony for more than 50 yr. Unlike other model organisms, however, the genomic resources for baboons are severely lacking. This has hindered the progress of studies using baboons as a model for basic biology or human disease. Here, we describe a data set of 100 high-coverage whole-genome sequences obtained from the mixed colony of olive (P. anubis) and yellow (P. cynocephalus) baboons housed at the SNPRC. These data provide a comprehensive catalog of common genetic variation in baboons, as well as a fine-scale genetic map. We show how the data can be used to learn about ancestry and admixture and to correct errors in the colony records. Finally, we investigated the consequences of inbreeding within the SNPRC colony and found clear evidence for increased rates of infant mortality and increased homozygosity of putatively deleterious alleles in inbred individuals.

Pleiotropy Modulates the Efficacy of Selection in Drosophila melanogaster

Pleiotropy is the well-established idea that a single mutation affects multiple phenotypes. If a mutation has opposite effects on fitness when expressed in different contexts, then genetic conflict arises. Pleiotropic conflict is expected to reduce the efficacy of selection by limiting the fixation of beneficial mutations through adaptation, and the removal of deleterious mutations through purifying selection. Although this has been widely discussed, in particular in the context of a putative "gender load," it has yet to be systematically quantified. In this work, we empirically estimate to which extent different pleiotropic regimes impede the efficacy of selection in Drosophila melanogaster. We use whole-genome polymorphism data from a single African population and divergence data from D. simulans to estimate the fraction of adaptive fixations (α), the rate of adaptation (ωA), and the direction of selection (DoS). After controlling for confounding covariates, we find that the different pleiotropic regimes have a relatively small, but significant, effect on selection efficacy. Specifically, our results suggest that pleiotropic sexual antagonism may restrict the efficacy of selection, but that this conflict can be resolved by limiting the expression of genes to the sex where they are beneficial. Intermediate levels of pleiotropy across tissues and life stages can also lead to maladaptation in D. melanogaster, due to inefficient purifying selection combined with low frequency of mutations that confer a selective advantage. Thus, our study highlights the need to consider the efficacy of selection in the context of antagonistic pleiotropy, and of genetic conflict in general.

Fast Estimation of Recombination Rates Using Topological Data Analysis

Accurate estimation of recombination rates is critical for studying the origins and maintenance of genetic diversity. Because the inference of recombination rates under a full evolutionary model is computationally expensive, we developed an alternative approach using topological data analysis (TDA) on genome sequences. We find that this method can analyze datasets larger than what can be handled by any existing recombination inference software, and has accuracy comparable to commonly used model-based methods with significantly less processing time. Previous TDA methods used information contained solely in the first Betti number ([Formula: see text]) of a set of genomes, which aims to capture the number of loops that can be detected within a genealogy. These explorations have proven difficult to connect to the theory of the underlying biological process of recombination, and, consequently, have unpredictable behavior under perturbations of the data. We introduce a new topological feature, which we call ψ, with a natural connection to coalescent models, and present novel arguments relating [Formula: see text] to population genetic models. Using simulations, we show that ψ and [Formula: see text] are differentially affected by missing data, and package our approach as TREE (Topological Recombination Estimator). TREE's efficiency and accuracy make it well suited as a first-pass estimator of recombination rate heterogeneity or hotspots throughout the genome. Our work empirically and theoretically justifies the use of topological statistics as summaries of genome sequences and describes a new, unintuitive relationship between topological features of the distribution of sequence data and the footprint of recombination on genomes.

Recombination rate variation shapes barriers to introgression across butterfly genomes

Hybridisation and introgression can dramatically alter the relationships among groups of species, leading to phylogenetic discordance across the genome and between populations. Introgression can also erode species differences over time, but selection against introgression at certain loci acts to maintain postmating species barriers. Theory predicts that species barriers made up of many loci throughout the genome should lead to a broad correlation between introgression and recombination rate, which determines the extent to which selection on deleterious foreign alleles will affect neutral alleles at physically linked loci. Here, we describe the variation in genealogical relationships across the genome among three species of Heliconius butterflies: H. melpomene (mel), H. cydno (cyd), and H. timareta (tim), using whole genomes of 92 individuals, and ask whether this variation can be explained by heterogeneous barriers to introgression. We find that species relationships vary predictably at the chromosomal scale. By quantifying recombination rate and admixture proportions, we then show that rates of introgression are predicted by variation in recombination rate. This implies that species barriers are highly polygenic, with selection acting against introgressed alleles across most of the genome. In addition, long chromosomes, which have lower recombination rates, produce stronger barriers on average than short chromosomes. Finally, we find a consistent difference between two species pairs on either side of the Andes, which suggests differences in the architecture of the species barriers. Our findings illustrate how the combined effects of hybridisation, recombination, and natural selection, acting at multitudes of loci over long periods, can dramatically sculpt the phylogenetic relationships among species.

Parental legacy, demography, and admixture influenced the evolution of the two subgenomes of the tetraploid Capsella bursa-pastoris (Brassicaceae)

Allopolyploidy is generally perceived as a major source of evolutionary novelties and as an instantaneous way to create isolation barriers. However, we do not have a clear understanding of how two subgenomes evolve and interact once they have fused in an allopolyploid species nor how isolated they are from their relatives. Here, we address these questions by analyzing genomic and transcriptomic data of allotetraploid Capsella bursa-pastoris in three differentiated populations, Asia, Europe, and the Middle East. We phased the two subgenomes, one descended from the outcrossing and highly diverse Capsella grandiflora (CbpCg) and the other one from the selfing and genetically depauperate Capsella orientalis (CbpCo). For each subgenome, we assessed its relationship with the diploid relatives, temporal changes of effective population size (Ne), signatures of positive and negative selection, and gene expression patterns. In all three regions, Ne of the two subgenomes decreased gradually over time and the CbpCo subgenome accumulated more deleterious changes than CbpCg. There were signs of widespread admixture between C. bursa-pastoris and its diploid relatives. The two subgenomes were impacted differentially depending on geographic region suggesting either strong interploidy gene flow or multiple origins of C. bursa-pastoris. Selective sweeps were more common on the CbpCg subgenome in Europe and the Middle East, and on the CbpCo subgenome in Asia. In contrast, differences in expression were limited with the CbpCg subgenome slightly more expressed than CbpCo in Europe and the Middle-East. In summary, after more than 100,000 generations of co-existence, the two subgenomes of C. bursa-pastoris still retained a strong signature of parental legacy but their evolutionary trajectory strongly varied across geographic regions.

The Unreasonable Effectiveness of Convolutional Neural Networks in Population Genetic Inference

Population-scale genomic data sets have given researchers incredible amounts of information from which to infer evolutionary histories. Concomitant with this flood of data, theoretical and methodological advances have sought to extract information from genomic sequences to infer demographic events such as population size changes and gene flow among closely related populations/species, construct recombination maps, and uncover loci underlying recent adaptation. To date, most methods make use of only one or a few summaries of the input sequences and therefore ignore potentially useful information encoded in the data. The most sophisticated of these approaches involve likelihood calculations, which require theoretical advances for each new problem, and often focus on a single aspect of the data (e.g., only allele frequency information) in the interest of mathematical and computational tractability. Directly interrogating the entirety of the input sequence data in a likelihood-free manner would thus offer a fruitful alternative. Here, we accomplish this by representing DNA sequence alignments as images and using a class of deep learning methods called convolutional neural networks (CNNs) to make population genetic inferences from these images. We apply CNNs to a number of evolutionary questions and find that they frequently match or exceed the accuracy of current methods. Importantly, we show that CNNs perform accurate evolutionary model selection and parameter estimation, even on problems that have not received detailed theoretical treatments. Thus, when applied to population genetic alignments, CNNs are capable of outperforming expert-derived statistical methods and offer a new path forward in cases where no likelihood approach exists.

Female Meiosis: Synapsis, Recombination, and Segregation in Drosophila melanogaster

A century of genetic studies of the meiotic process in Drosophila melanogaster females has been greatly augmented by both modern molecular biology and major advances in cytology. These approaches, and the findings they have allowed, are the subject of this review. Specifically, these efforts have revealed that meiotic pairing in Drosophila females is not an extension of somatic pairing, but rather occurs by a poorly understood process during premeiotic mitoses. This process of meiotic pairing requires the function of several components of the synaptonemal complex (SC). When fully assembled, the SC also plays a critical role in maintaining homolog synapsis and in facilitating the maturation of double-strand breaks (DSBs) into mature crossover (CO) events. Considerable progress has been made in elucidating not only the structure, function, and assembly of the SC, but also the proteins that facilitate the formation and repair of DSBs into both COs and noncrossovers (NCOs). The events that control the decision to mature a DSB as either a CO or an NCO, as well as determining which of the two CO pathways (class I or class II) might be employed, are also being characterized by genetic and genomic approaches. These advances allow a reconsideration of meiotic phenomena such as interference and the centromere effect, which were previously described only by genetic studies. In delineating the mechanisms by which the oocyte controls the number and position of COs, it becomes possible to understand the role of CO position in ensuring the proper orientation of homologs on the first meiotic spindle. Studies of bivalent orientation have occurred in the context of numerous investigations into the assembly, structure, and function of the first meiotic spindle. Additionally, studies have examined the mechanisms ensuring the segregation of chromosomes that have failed to undergo crossing over.

Connecting theory and data to understand recombination rate evolution

Meiotic recombination is necessary for successful gametogenesis in most sexually reproducing organisms and is a fundamental genomic parameter, influencing the efficacy of selection and the fate of new mutations. The molecular and evolutionary functions of recombination should impose strong selective constraints on the range of recombination rates. Yet, variation in recombination rate is observed on a variety of genomic and evolutionary scales. In the past decade, empirical studies have described variation in recombination rate within genomes, between individuals, between sexes, between populations and between species. At the same time, theoretical work has provided an increasingly detailed picture of the evolutionary advantages to recombination. Perhaps surprisingly, the causes of natural variation in recombination rate remain poorly understood. We argue that empirical and theoretical approaches to understand the evolution of recombination have proceeded largely independently of each other. Most models that address the evolution of recombination rate were created to explain the evolutionary advantage of recombination rather than quantitative differences in rate among individuals. Conversely, most empirical studies aim to describe variation in recombination rate, rather than to test evolutionary hypotheses. In this Perspective, we argue that efforts to integrate the rich bodies of empirical and theoretical work on recombination rate are crucial to moving this field forward. We provide new directions for the development of theory and the production of data that will jointly close this gap.This article is part of the themed issue 'Evolutionary causes and consequences of recombination rate variation in sexual organisms'.

Variation in recombination frequency and distribution across eukaryotes: patterns and processes

Recombination, the exchange of DNA between maternal and paternal chromosomes during meiosis, is an essential feature of sexual reproduction in nearly all multicellular organisms. While the role of recombination in the evolution of sex has received theoretical and empirical attention, less is known about how recombination rate itself evolves and what influence this has on evolutionary processes within sexually reproducing organisms. Here, we explore the patterns of, and processes governing recombination in eukaryotes. We summarize patterns of variation, integrating current knowledge with an analysis of linkage map data in 353 organisms. We then discuss proximate and ultimate processes governing recombination rate variation and consider how these influence evolutionary processes. Genome-wide recombination rates (cM/Mb) can vary more than tenfold across eukaryotes, and there is large variation in the distribution of recombination events across closely related taxa, populations and individuals. We discuss how variation in rate and distribution relates to genome architecture, genetic and epigenetic mechanisms, sex, environmental perturbations and variable selective pressures. There has been great progress in determining the molecular mechanisms governing recombination, and with the continued development of new modelling and empirical approaches, there is now also great opportunity to further our understanding of how and why recombination rate varies.This article is part of the themed issue 'Evolutionary causes and consequences of recombination rate variation in sexual organisms'.

Sex Differences in Recombination in Sticklebacks

Recombination often differs markedly between males and females. Here we present the first analysis of sex-specific recombination in Gasterosteus sticklebacks. Using whole-genome sequencing of 15 crosses between G. aculeatus and G. nipponicus, we localized 698 crossovers with a median resolution of 2.3 kb. We also used a bioinformatic approach to infer historical sex-averaged recombination patterns for both species. Recombination is greater in females than males on all chromosomes, and overall map length is 1.64 times longer in females. The locations of crossovers differ strikingly between sexes. Crossovers cluster toward chromosome ends in males, but are distributed more evenly across chromosomes in females. Suppression of recombination near the centromeres in males causes crossovers to cluster at the ends of long arms in acrocentric chromosomes, and greatly reduces crossing over on short arms. The effect of centromeres on recombination is much weaker in females. Genomic differentiation between G. aculeatus and G. nipponicus is strongly correlated with recombination rate, and patterns of differentiation along chromosomes are strongly influenced by male-specific telomere and centromere effects. We found no evidence for fine-scale correlations between recombination and local gene content in either sex. We discuss hypotheses for the origin of sexual dimorphism in recombination and its consequences for sexually antagonistic selection and sex chromosome evolution.

Background selection as null hypothesis in population genomics: insights and challenges from Drosophila studies

The consequences of selection at linked sites are multiple and widespread across the genomes of most species. Here, I first review the main concepts behind models of selection and linkage in recombining genomes, present the difficulty in parametrizing these models simply as a reduction in effective population size (N_e) and discuss the predicted impact of recombination rates on levels of diversity across genomes. Arguments are then put forward in favour of using a model of selection and linkage with neutral and deleterious mutations (i.e. the background selection model, BGS) as a sensible null hypothesis for investigating the presence of other forms of selection, such as balancing or positive. I also describe and compare two studies that have generated high-resolution landscapes of the predicted consequences of selection at linked sites in Drosophila melanogaster. Both studies show that BGS can explain a very large fraction of the observed variation in diversity across the whole genome, thus supporting its use as null model. Finally, I identify and discuss a number of caveats and challenges in studies of genetic hitchhiking that have been often overlooked, with several of them sharing a potential bias towards overestimating the evidence supporting recent selective sweeps to the detriment of a BGS explanation. One potential source of bias is the analysis of non-equilibrium populations: it is precisely because models of selection and linkage predict variation in N_e across chromosomes that demographic dynamics are not expected to be equivalent chromosome- or genome-wide. Other challenges include the use of incomplete genome annotations, the assumption of temporally stable recombination landscapes, the presence of genes under balancing selection and the consequences of ignoring non-crossover (gene conversion) recombination events.

This article is part of the themed issue ‘Evolutionary causes and consequences of recombination rate variation in sexual organisms’.

Natural selection interacts with recombination to shape the evolution of hybrid genomes

To investigate the consequences of hybridization between species, we studied three replicate hybrid populations that formed naturally between two swordtail fish species, estimating their fine-scale genetic map and inferring ancestry along the genomes of 690 individuals. In all three populations, ancestry from the "minor" parental species is more common in regions of high recombination and where there is linkage to fewer putative targets of selection. The same patterns are apparent in a reanalysis of human and archaic admixture. These results support models in which ancestry from the minor parental species is more likely to persist when rapidly uncoupled from alleles that are deleterious in hybrids. Our analyses further indicate that selection on swordtail hybrids stems predominantly from deleterious combinations of epistatically interacting alleles.

Supervised machine learning reveals introgressed loci in the genomes of Drosophila simulans and D. sechellia

Hybridization and gene flow between species appears to be common. Even though it is clear that hybridization is widespread across all surveyed taxonomic groups, the magnitude and consequences of introgression are still largely unknown. Thus it is crucial to develop the statistical machinery required to uncover which genomic regions have recently acquired haplotypes via introgression from a sister population. We developed a novel machine learning framework, called FILET (Finding Introgressed Loci via Extra-Trees) capable of revealing genomic introgression with far greater power than competing methods. FILET works by combining information from a number of population genetic summary statistics, including several new statistics that we introduce, that capture patterns of variation across two populations. We show that FILET is able to identify loci that have experienced gene flow between related species with high accuracy, and in most situations can correctly infer which population was the donor and which was the recipient. Here we describe a data set of outbred diploid Drosophila sechellia genomes, and combine them with data from D. simulans to examine recent introgression between these species using FILET. Although we find that these populations may have split more recently than previously appreciated, FILET confirms that there has indeed been appreciable recent introgression (some of which might have been adaptive) between these species, and reveals that this gene flow is primarily in the direction of D. simulans to D. sechellia.

PopFly: the Drosophila population genomics browser

Summary

The recent compilation of over 1100 worldwide wild-derived Drosophila melanogaster genome sequences reassembled using a standardized pipeline provides a unique resource for population genomic studies (Drosophila Genome Nexus, DGN). A visual display of the estimated metrics describing genome-wide variation and selection patterns would allow gaining a global view and understanding of the evolutionary forces shaping genome variation.

Availability and implementation

Here, we present PopFly, a population genomics-oriented genome browser, based on JBrowse software, that contains a complete inventory of population genomic parameters estimated from DGN data. This browser is designed for the automatic analysis and display of genetic variation data within and between populations along the D. melanogaster genome. PopFly allows the visualization and retrieval of functional annotations, estimates of nucleotide diversity metrics, linkage disequilibrium statistics, recombination rates, a battery of neutrality tests, and population differentiation parameters at different window sizes through the euchromatic chromosomes. PopFly is open and freely available at site http://popfly.uab.cat .

Contact

sergi.hervas@uab.cat or antonio.barbadilla@uab.cat.

Multiple Modes of Positive Selection Shaping the Patterns of Incomplete Selective Sweeps over African Populations of Drosophila melanogaster

It remains a challenge in evolutionary genetics to elucidate how beneficial mutations arise and propagate in a population and how selective pressures on mutant alleles are structured over space and time. By identifying "sweeping haplotypes (SHs)" that putatively carry beneficial alleles and are increasing (or have increased) rapidly in frequency, and surveying the geographic distribution of SH frequencies, we can indirectly infer how selective sweeps unfold in time and thus which modes of positive selection underlie those sweeps. Using population genomic data from African Drosophila melanogaster, we identified SHs from 37 candidate loci under selection. At more than half of loci, we identify single SHs. However, many other loci harbor multiple independent SHs, namely soft selective sweeps, either due to parallel evolution across space or a high beneficial mutation rate. At about a quarter of the loci, intermediate SH frequencies are found across multiple populations, which cannot be explained unless a certain form of frequency-dependent positive selection, such as heterozygote advantage, is invoked given the reasonable range of migration rates between African populations. At one locus, many independent SHs are observed over multiple populations but always together with ancestral haplotypes. This complex pattern is compatible with a large number of mutational targets in a gene and frequency-dependent selection on new variants. We conclude that very diverse modes of positive selection are operating at different sets of loci in D. melanogaster populations.

Fine-Scale Recombination Maps of Fungal Plant Pathogens Reveal Dynamic Recombination Landscapes and Intragenic Hotspots

Meiotic recombination is an important driver of evolution. Variability in the intensity of recombination across chromosomes can affect sequence composition, nucleotide variation, and rates of adaptation. In many organisms, recombination events are concentrated within short segments termed recombination hotspots. The variation in recombination rate and positions of recombination hotspot can be studied using population genomics data and statistical methods. In this study, we conducted population genomics analyses to address the evolution of recombination in two closely related fungal plant pathogens: the prominent wheat pathogen Zymoseptoria tritici and a sister species infecting wild grasses Z. ardabiliae We specifically addressed whether recombination landscapes, including hotspot positions, are conserved in the two recently diverged species and if recombination contributes to rapid evolution of pathogenicity traits. We conducted a detailed simulation analysis to assess the performance of methods of recombination rate estimation based on patterns of linkage disequilibrium, in particular in the context of high nucleotide diversity. Our analyses reveal overall high recombination rates, a lack of suppressed recombination in centromeres, and significantly lower recombination rates on chromosomes that are known to be accessory. The comparison of the recombination landscapes of the two species reveals a strong correlation of recombination rate at the megabase scale, but little correlation at smaller scales. The recombination landscapes in both pathogen species are dominated by frequent recombination hotspots across the genome including coding regions, suggesting a strong impact of recombination on gene evolution. A significant but small fraction of these hotspots colocalize between the two species, suggesting that hotspot dynamics contribute to the overall pattern of fast evolving recombination in these species.

A Genome Resequencing-Based Genetic Map Reveals the Recombination Landscape of an Outbred Parasitic Nematode in the Presence of Polyploidy and Polyandry

The parasitic nematode Haemonchus contortus is an economically and clinically important pathogen of small ruminants, and a model system for understanding the mechanisms and evolution of traits such as anthelmintic resistance. Anthelmintic resistance is widespread and is a major threat to the sustainability of livestock agriculture globally; however, little is known about the genome architecture and parameters such as recombination that will ultimately influence the rate at which resistance may evolve and spread. Here, we performed a genetic cross between two divergent strains of H. contortus, and subsequently used whole-genome resequencing of a female worm and her brood to identify the distribution of genome-wide variation that characterizes these strains. Using a novel bioinformatic approach to identify variants that segregate as expected in a pseudotestcross, we characterized linkage groups and estimated genetic distances between markers to generate a chromosome-scale F1 genetic map. We exploited this map to reveal the recombination landscape, the first for any helminth species, demonstrating extensive variation in recombination rate within and between chromosomes. Analyses of these data also revealed the extent of polyandry, whereby at least eight males were found to have contributed to the genetic variation of the progeny analyzed. Triploid offspring were also identified, which we hypothesize are the result of nondisjunction during female meiosis or polyspermy. These results expand our knowledge of the genetics of parasitic helminths and the unusual life-history of H. contortus, and enhance ongoing efforts to understand the genetic basis of resistance to the drugs used to control these worms and for related species that infect livestock and humans throughout the world. This study also demonstrates the feasibility of using whole-genome resequencing data to directly construct a genetic map in a single generation cross from a noninbred nonmodel organism with a complex lifecycle.

Effects of Demographic History on the Detection of Recombination Hotspots from Linkage Disequilibrium

In some species, meiotic recombination is concentrated in small genomic regions. These "recombination hotspots" leave signatures in fine-scale patterns of linkage disequilibrium, raising the prospect that the genomic landscape of hotspots can be characterized from sequence variation. This approach has led to the inference that hotspots evolve rapidly in some species, but are conserved in others. Historic demographic events, such as population bottlenecks, are known to affect patterns of linkage disequilibrium across the genome, violating population genetic assumptions of this approach. Although such events are prevalent, demographic history is generally ignored when making inferences about the evolution of recombination hotspots. To determine the effect of demography on the detection of recombination hotspots, we use the coalescent to simulate haplotypes with a known recombination landscape. We measure the ability of popular linkage disequilibrium-based programs to detect hotspots across a range of demographic histories, including population bottlenecks, hidden population structure, population expansions, and population contractions. We find that demographic events have the potential to greatly reduce the power and increase the false positive rate of hotspot discovery. Neither the power nor the false positive rate of hotspot detection can be predicted without also knowing the demographic history of the sample. Our results suggest that ignoring demographic history likely overestimates the power to detect hotspots and therefore underestimates the degree of hotspot sharing between species. We suggest strategies for incorporating demographic history into population genetic inferences about recombination hotspots.

The consequences of sequence erosion in the evolution of recombination hotspots

Meiosis is initiated by a double-strand break (DSB) introduced in the DNA by a highly controlled process that is repaired by recombination. In many organisms, recombination occurs at specific and narrow regions of the genome, known as recombination hotspots, which overlap with regions enriched for DSBs. In recent years, it has been demonstrated that conversions and mutations resulting from the repair of DSBs lead to a rapid sequence evolution at recombination hotspots eroding target sites for DSBs. We still do not fully understand the effect of this erosion in the recombination activity, but evidence has shown that the binding of trans-acting factors like PRDM9 is affected. PRDM9 is a meiosis-specific, multi-domain protein that recognizes DNA target motifs by its zinc finger domain and directs DSBs to these target sites. Here we discuss the changes in affinity of PRDM9 to eroded recognition sequences, and explain how these changes in affinity of PRDM9 can affect recombination, leading sometimes to sterility in the context of hybrid crosses. We also present experimental data showing that DNA methylation reduces PRDM9 binding in vitro Finally, we discuss PRDM9-independent hotspots, posing the question how these hotspots evolve and change with sequence erosion.This article is part of the themed issue 'Evolutionary causes and consequences of recombination rate variation in sexual organisms'.

Recombination rate plasticity: revealing mechanisms by design

For over a century, scientists have known that meiotic recombination rates can vary considerably among individuals, and that environmental conditions can modify recombination rates relative to the background. A variety of external and intrinsic factors such as temperature, age, sex and starvation can elicit 'plastic' responses in recombination rate. The influence of recombination rate plasticity on genetic diversity of the next generation has interesting and important implications for how populations evolve. Further, many questions remain regarding the mechanisms and molecular processes that contribute to recombination rate plasticity. Here, we review 100 years of experimental work on recombination rate plasticity conducted in Drosophila melanogaster We categorize this work into four major classes of experimental designs, which we describe via classic studies in D. melanogaster Based on these studies, we highlight molecular mechanisms that are supported by experimental results and relate these findings to studies in other systems. We synthesize lessons learned from this model system into experimental guidelines for using recent advances in genotyping technologies, to study recombination rate plasticity in non-model organisms. Specifically, we recommend (1) using fine-scale genome-wide markers, (2) collecting time-course data, (3) including crossover distribution measurements, and (4) using mixed effects models to analyse results. To illustrate this approach, we present an application adhering to these guidelines from empirical work we conducted in Drosophila pseudoobscuraThis article is part of the themed issue 'Evolutionary causes and consequences of recombination rate variation in sexual organisms'.

Variation in Recombination Rate and Its Genetic Determinism in Sheep Populations

Recombination is a complex biological process that results from a cascade of multiple events during meiosis. Understanding the genetic determinism of recombination can help to understand if and how these events are interacting. To tackle this question, we studied the patterns of recombination in sheep, using multiple approaches and data sets. We constructed male recombination maps in a dairy breed from the south of France (the Lacaune breed) at a fine scale by combining meiotic recombination rates from a large pedigree genotyped with a 50K SNP array and historical recombination rates from a sample of unrelated individuals genotyped with a 600K SNP array. This analysis revealed recombination patterns in sheep similar to other mammals but also genome regions that have likely been affected by directional and diversifying selection. We estimated the average recombination rate of Lacaune sheep at 1.5 cM/Mb, identified ∼50,000 crossover hotspots on the genome, and found a high correlation between historical and meiotic recombination rate estimates. A genome-wide association study revealed two major loci affecting interindividual variation in recombination rate in Lacaune, including the RNF212 and HEI10 genes and possibly two other loci of smaller effects including the KCNJ15 and FSHR genes. The comparison of these new results to those obtained previously in a distantly related population of domestic sheep (the Soay) revealed that Soay and Lacaune males have a very similar distribution of recombination along the genome. The two data sets were thus combined to create more precise male meiotic recombination maps in Sheep. However, despite their similar recombination maps, Soay and Lacaune males were found to exhibit different heritabilities and QTL effects for interindividual variation in genome-wide recombination rates. This highlights the robustness of recombination patterns to underlying variation in their genetic determinism.

Mutation and recombination in pathogen evolution: Relevance, methods and controversies

Mutation and recombination drive the evolution of most pathogens by generating the genetic variants upon which selection operates. Those variants can, for example, confer resistance to host immune systems and drug therapies or lead to epidemic outbreaks. Given their importance, diverse evolutionary studies have investigated the abundance and consequences of mutation and recombination in pathogen populations. However, some controversies persist regarding the contribution of each evolutionary force to the development of particular phenotypic observations (e.g., drug resistance). In this study, we revise the importance of mutation and recombination in the evolution of pathogens at both intra-host and inter-host levels. We also describe state-of-the-art analytical methodologies to detect and quantify these two evolutionary forces, including biases that are often ignored in evolutionary studies. Finally, we present some of our former studies involving pathogenic taxa where mutation and recombination played crucial roles in the recovery of pathogenic fitness, the generation of interspecific genetic diversity, or the design of centralized vaccines. This review also illustrates several common controversies and pitfalls in the analysis and in the evaluation and interpretation of mutation and recombination outcomes.

The Recombination Landscape in Wild House Mice Inferred Using Population Genomic Data

Characterizing variation in the rate of recombination across the genome is important for understanding several evolutionary processes. Previous analysis of the recombination landscape in laboratory mice has revealed that the different subspecies have different suites of recombination hotspots. It is unknown, however, whether hotspots identified in laboratory strains reflect the hotspot diversity of natural populations or whether broad-scale variation in the rate of recombination is conserved between subspecies. In this study, we constructed fine-scale recombination rate maps for a natural population of the Eastern house mouse, Mus musculus castaneus We performed simulations to assess the accuracy of recombination rate inference in the presence of phase errors, and we used a novel approach to quantify phase error. The spatial distribution of recombination events is strongly positively correlated between our castaneus map, and a map constructed using inbred lines derived predominantly from M. m. domesticus Recombination hotspots in wild castaneus show little overlap, however, with the locations of double-strand breaks in wild-derived house mouse strains. Finally, we also find that genetic diversity in M. m. castaneus is positively correlated with the rate of recombination, consistent with pervasive natural selection operating in the genome. Our study suggests that recombination rate variation is conserved at broad scales between house mouse subspecies, but it is not strongly conserved at fine scales.

A High-Density Linkage Map Reveals Sexual Dimorphism in Recombination Landscapes in Red Deer (Cervus elaphus)

High-density linkage maps are an important tool to gain insight into the genetic architecture of traits of evolutionary and economic interest, and provide a resource to characterize variation in recombination landscapes. Here, we used information from the cattle genome and the 50 K Cervine Illumina BeadChip to inform and refine a high-density linkage map in a wild population of red deer (Cervus elaphus). We constructed a predicted linkage map of 38,038 SNPs and a skeleton map of 10,835 SNPs across 34 linkage groups. We identified several chromosomal rearrangements in the deer lineage relative to sheep and cattle, including six chromosome fissions, one fusion, and two large inversions. Otherwise, our findings showed strong concordance with map orders in the cattle genome. The sex-averaged linkage map length was 2739.7 cM and the genome-wide autosomal recombination rate was 1.04 cM/Mb. The female autosomal map length was 1.21 longer than that of males (2767.4 cM vs. 2280.8 cM, respectively). Sex differences in map length were driven by high female recombination rates in peri-centromeric regions, a pattern that is unusual relative to other mammal species. This effect was more pronounced in fission chromosomes that would have had to produce new centromeres. We propose two hypotheses to explain this effect: (1) that this mechanism may have evolved to counteract centromeric drive associated with meiotic asymmetry in oocyte production; and/or (2) that sequence and structural characteristics suppressing recombination in close proximity to the centromere may not have evolved at neo-centromeres. Our study provides insight into how recombination landscapes vary and evolve in mammals, and will provide a valuable resource for studies of evolution, genetic improvement, and population management in red deer and related species.

Genomewide patterns of variation in genetic diversity are shared among populations, species and higher-order taxa

Genomewide screens of genetic variation within and between populations can reveal signatures of selection implicated in adaptation and speciation. Genomic regions with low genetic diversity and elevated differentiation reflective of locally reduced effective population sizes (N_e ) are candidates for barrier loci contributing to population divergence. Yet, such candidate genomic regions need not arise as a result of selection promoting adaptation or advancing reproductive isolation. Linked selection unrelated to lineage-specific adaptation or population divergence can generate comparable signatures. It is challenging to distinguish between these processes, particularly when diverging populations share ancestral genetic variation. In this study, we took a comparative approach using population assemblages from distant clades assessing genomic parallelism of variation in N_e . Utilizing population-level polymorphism data from 444 resequenced genomes of three avian clades spanning 50 million years of evolution, we tested whether population genetic summary statistics reflecting genomewide variation in N_e would covary among populations within clades, and importantly, also among clades where lineage sorting has been completed. All statistics including population-scaled recombination rate (ρ), nucleotide diversity (π) and measures of genetic differentiation between populations (F_ST , PBS, d_xy ) were significantly correlated across all phylogenetic distances. Moreover, genomic regions with elevated levels of genetic differentiation were associated with inferred pericentromeric and subtelomeric regions. The phylogenetic stability of diversity landscapes and stable association with genomic features support a role of linked selection not necessarily associated with adaptation and speciation in shaping patterns of genomewide heterogeneity in genetic diversity.

Repeated losses of PRDM9-directed recombination despite the conservation of PRDM9 across vertebrates

Studies of highly diverged species have revealed two mechanisms by which meiotic recombination is directed to the genome-through PRDM9 binding or by targeting promoter-like features-that lead to dramatically different evolutionary dynamics of hotspots. Here, we identify PRDM9 orthologs from genome and transcriptome data in 225 species. We find the complete PRDM9 ortholog across distantly related vertebrates but, despite this broad conservation, infer a minimum of six partial and three complete losses. Strikingly, taxa carrying the complete ortholog of PRDM9 are precisely those with rapid evolution of its predicted binding affinity, suggesting that all domains are necessary for directing recombination. Indeed, as we show, swordtail fish carrying only a partial but conserved ortholog share recombination properties with PRDM9 knock-outs.

Inferring Demographic History Using Two-Locus Statistics

Population demographic history may be learned from contemporary genetic variation data. Methods based on aggregating the statistics of many single loci into an allele frequency spectrum (AFS) have proven powerful, but such methods ignore potentially informative patterns of linkage disequilibrium (LD) between neighboring loci. To leverage such patterns, we developed a composite-likelihood framework for inferring demographic history from aggregated statistics of pairs of loci. Using this framework, we show that two-locus statistics are more sensitive to demographic history than single-locus statistics such as the AFS. In particular, two-locus statistics escape the notorious confounding of depth and duration of a bottleneck, and they provide a means to estimate effective population size based on the recombination rather than mutation rate. We applied our approach to a Zambian population of Drosophila melanogaster Notably, using both single- and two-locus statistics, we inferred a substantially lower ancestral effective population size than previous works and did not infer a bottleneck history. Together, our results demonstrate the broad potential for two-locus statistics to enable powerful population genetic inference.

Molecular Population Genetics

Molecular population genetics aims to explain genetic variation and molecular evolution from population genetics principles. The field was born 50 years ago with the first measures of genetic variation in allozyme loci, continued with the nucleotide sequencing era, and is currently in the era of population genomics. During this period, molecular population genetics has been revolutionized by progress in data acquisition and theoretical developments. The conceptual elegance of the neutral theory of molecular evolution or the footprint carved by natural selection on the patterns of genetic variation are two examples of the vast number of inspiring findings of population genetics research. Since the inception of the field, Drosophila has been the prominent model species: molecular variation in populations was first described in Drosophila and most of the population genetics hypotheses were tested in Drosophila species. In this review, we describe the main concepts, methods, and landmarks of molecular population genetics, using the Drosophila model as a reference. We describe the different genetic data sets made available by advances in molecular technologies, and the theoretical developments fostered by these data. Finally, we review the results and new insights provided by the population genomics approach, and conclude by enumerating challenges and new lines of inquiry posed by increasingly large population scale sequence data.

Combination of short-read, long-read, and optical mapping assemblies reveals large-scale tandem repeat arrays with population genetic implications

Accurate and contiguous genome assembly is key to a comprehensive understanding of the processes shaping genomic diversity and evolution. Yet, it is frequently constrained by constitutive heterochromatin, usually characterized by highly repetitive DNA. As a key feature of genome architecture associated with centromeric and subtelomeric regions, it locally influences meiotic recombination. In this study, we assess the impact of large tandem repeat arrays on the recombination rate landscape in an avian speciation model, the Eurasian crow. We assembled two high-quality genome references using single-molecule real-time sequencing (long-read assembly [LR]) and single-molecule optical maps (optical map assembly [OM]). A three-way comparison including the published short-read assembly (SR) constructed for the same individual allowed assessing assembly properties and pinpointing misassemblies. By combining information from all three assemblies, we characterized 36 previously unidentified large repetitive regions in the proximity of sequence assembly breakpoints, the majority of which contained complex arrays of a 14-kb satellite repeat or its 1.2-kb subunit. Using whole-genome population resequencing data, we estimated the population-scaled recombination rate (ρ) and found it to be significantly reduced in these regions. These findings are consistent with an effect of low recombination in regions adjacent to centromeric or subtelomeric heterochromatin and add to our understanding of the processes generating widespread heterogeneity in genetic diversity and differentiation along the genome. By combining three different technologies, our results highlight the importance of adding a layer of information on genome structure that is inaccessible to each approach independently.

Gene flow, ancient polymorphism, and ecological adaptation shape the genomic landscape of divergence among Darwin's finches

Genomic comparisons of closely related species have identified “islands” of locally elevated sequence divergence. Genomic islands may contain functional variants involved in local adaptation or reproductive isolation and may therefore play an important role in the speciation process. However, genomic islands can also arise through evolutionary processes unrelated to speciation, and examination of their properties can illuminate how new species evolve. Here, we performed scans for regions of high relative divergence (F_ST) in 12 species pairs of Darwin's finches at different genetic distances. In each pair, we identify genomic islands that are, on average, elevated in both relative divergence (F_ST) and absolute divergence (d_XY). This signal indicates that haplotypes within these genomic regions became isolated from each other earlier than the rest of the genome. Interestingly, similar numbers of genomic islands of elevated d_XY are observed in sympatric and allopatric species pairs, suggesting that recent gene flow is not a major factor in their formation. We find that two of the most pronounced genomic islands contain the ALX1 and HMGA2 loci, which are associated with variation in beak shape and size, respectively, suggesting that they are involved in ecological adaptation. A subset of genomic island regions, including these loci, appears to represent anciently diverged haplotypes that evolved early during the radiation of Darwin's finches. Comparative genomics data indicate that these loci, and genomic islands in general, have exceptionally low recombination rates, which may play a role in their establishment.

Population structure and local selection yield high genomic variation in Mimulus guttatus

Across western North America, Mimulus guttatus exists as many local populations adapted to site-specific environmental challenges. Gene flow between locally adapted populations will affect genetic diversity both within demes and across the larger metapopulation. Here, we analyse 34 whole-genome sequences from the intensively studied Iron Mountain population (IM) in conjunction with sequences from 22 Mimulus individuals sampled from across western North America. Three striking features of these data address hypotheses about migration and selection in a locally adapted population. First, we find very high levels of intrapopulation polymorphism (synonymous π = 0.033). Variation outside of genes is likely even higher but difficult to estimate because excessive divergence reduces the efficiency of read mapping. Second, IM exhibits a significantly positive genomewide average for Tajima's D. This indicates allele frequencies are typically more intermediate than expected from neutrality, opposite the pattern observed in many other species. Third, IM exhibits a distinctive haplotype structure with a genomewide excess of positive associations between rarer alleles at linked loci. This suggests an important effect of gene flow from other Mimulus populations, although a residual effect of population founding might also contribute. The combination of multiple analyses, including a novel tree-based analytic method, illustrates how the balance of local selection, limited dispersal and metapopulation dynamics manifests across the genome. The overall genomic pattern of sequence diversity suggests successful gene flow of divergent immigrant genotypes into IM. However, many loci show patterns indicative of local adaptation, particularly at SNPs associated with chromosomal inversions.

Evolution of heterogeneous genome differentiation across multiple contact zones in a crow species complex

Uncovering the genetic basis of species diversification is a central goal in evolutionary biology. Yet, the link between the accumulation of genomic changes during population divergence and the evolutionary forces promoting reproductive isolation is poorly understood. Here, we analysed 124 genomes of crow populations with various degrees of genome-wide differentiation, with parallelism of a sexually selected plumage phenotype, and ongoing hybridization. Overall, heterogeneity in genetic differentiation along the genome was best explained by linked selection exposed on a shared genome architecture. Superimposed on this common background, we identified genomic regions with signatures of selection specific to independent phenotypic contact zones. Candidate pigmentation genes with evidence for divergent selection were only partly shared, suggesting context-dependent selection on a multigenic trait architecture and parallelism by pathway rather than by repeated single-gene effects. This study provides insight into how various forms of selection shape genome-wide patterns of genomic differentiation as populations diverge.

A high-density genetic map reveals variation in recombination rate across the genome of Daphnia magna

BACKGROUND

Recombination rate is an essential parameter for many genetic analyses. Recombination rates are highly variable across species, populations, individuals and different genomic regions. Due to the profound influence that recombination can have on intraspecific diversity and interspecific divergence, characterization of recombination rate variation emerges as a key resource for population genomic studies and emphasises the importance of high-density genetic maps as tools for studying genome biology. Here we present such a high-density genetic map for Daphnia magna, and analyse patterns of recombination rate across the genome.

RESULTS

A F2 intercross panel was genotyped by Restriction-site Associated DNA sequencing to construct the third-generation linkage map of D. magna. The resulting high-density map included 4037 markers covering 813 scaffolds and contigs that sum up to 77 % of the currently available genome draft sequence (v2.4) and 55 % of the estimated genome size (238 Mb). Total genetic length of the map presented here is 1614.5 cM and the genome-wide recombination rate is estimated to 6.78 cM/Mb. Merging genetic and physical information we consistently found that recombination rate estimates are high towards the peripheral parts of the chromosomes, while chromosome centres, harbouring centromeres in D. magna, show very low recombination rate estimates.

CONCLUSIONS

Due to its high-density, the third-generation linkage map for D. magna can be coupled with the draft genome assembly, providing an essential tool for genome investigation in this model organism. Thus, our linkage map can be used for the on-going improvements of the genome assembly, but more importantly, it has enabled us to characterize variation in recombination rate across the genome of D. magna for the first time. These new insights can provide a valuable assistance in future studies of the genome evolution, mapping of quantitative traits and population genetic studies.

Predictive Models of Recombination Rate Variation across the Drosophila melanogaster Genome

In all eukaryotic species examined, meiotic recombination, and crossovers in particular, occur non‐randomly along chromosomes. The cause for this non-random distribution remains poorly understood but some specific DNA sequence motifs have been shown to be enriched near crossover hotspots in a number of species. We present analyses using machine learning algorithms to investigate whether DNA motif distribution across the genome can be used to predict crossover variation in Drosophila melanogaster, a species without hotspots. Our study exposes a combinatorial non-linear influence of motif presence able to account for a significant fraction of the genome-wide variation in crossover rates at all genomic scales investigated, from 20% at 5-kb to almost 70% at 2,500-kb scale. The models are particularly predictive for regions with the highest and lowest crossover rates and remain highly informative after removing sub-telomeric and -centromeric regions known to have strongly reduced crossover rates. Transcriptional activity during early meiosis and differences in motif use between autosomes and the X chromosome add to the predictive power of the models. Moreover, we show that population-specific differences in crossover rates can be partly explained by differences in motif presence. Our results suggest that crossover distribution in Drosophila is influenced by both meiosis-specific chromatin dynamics and very local constitutive open chromatin associated with DNA motifs that prevent nucleosome stabilization. These findings provide new information on the genetic factors influencing variation in recombination rates and a baseline to study epigenetic mechanisms responsible for plastic recombination as response to different biotic and abiotic conditions and stresses.

Estimating the Effective Population Size from Temporal Allele Frequency Changes in Experimental Evolution

The effective population size (Ne) is a major factor determining allele frequency changes in natural and experimental populations. Temporal methods provide a powerful and simple approach to estimate short-term Ne. They use allele frequency shifts between temporal samples to calculate the standardized variance, which is directly related to Ne. Here we focus on experimental evolution studies that often rely on repeated sequencing of samples in pools (Pool-seq). Pool-seq is cost-effective and often outperforms individual-based sequencing in estimating allele frequencies, but it is associated with atypical sampling properties: Additional to sampling individuals, sequencing DNA in pools leads to a second round of sampling, which increases the variance of allele frequency estimates. We propose a new estimator of Ne, which relies on allele frequency changes in temporal data and corrects for the variance in both sampling steps. In simulations, we obtain accurate Ne estimates, as long as the drift variance is not too small compared to the sampling and sequencing variance. In addition to genome-wide Ne estimates, we extend our method using a recursive partitioning approach to estimate Ne locally along the chromosome. Since the type I error is controlled, our method permits the identification of genomic regions that differ significantly in their Ne estimates. We present an application to Pool-seq data from experimental evolution with Drosophila and provide recommendations for whole-genome data. The estimator is computationally efficient and available as an R package at https://github.com/ThomasTaus/Nest.