Crossover Interference: Shedding Light on the Evolution of Recombination.

Through recombination, genes are freed to evolve more independently of one another, unleashing genetic variance hidden in the linkage disequilibrium that accumulates through selection combined with drift. Yet crossover numbers are evolutionarily constrained, with at least one and not many more than one crossover per bivalent in most taxa. Crossover interference, whereby a crossover reduces the probability of a neighboring crossover, contributes to this homogeneity. The mechanisms by which interference is achieved and crossovers are regulated are a major current subject of inquiry, facilitated by novel methods to visualize crossovers and to pinpoint recombination events. Here, we review patterns of crossover interference and the models built to describe this process. We then discuss the selective forces that have likely shaped interference and the regulation of crossover numbers.

Recommendations for improving statistical inference in population genomics.

The field of population genomics has grown rapidly in response to the recent advent of affordable, large-scale sequencing technologies. As opposed to the situation during the majority of the 20th century, in which the development of theoretical and statistical population genetic insights outpaced the generation of data to which they could be applied, genomic data are now being produced at a far greater rate than they can be meaningfully analyzed and interpreted. With this wealth of data has come a tendency to focus on fitting specific (and often rather idiosyncratic) models to data, at the expense of a careful exploration of the range of possible underlying evolutionary processes. For example, the approach of directly investigating models of adaptive evolution in each newly sequenced population or species often neglects the fact that a thorough characterization of ubiquitous nonadaptive processes is a prerequisite for accurate inference. We here describe the perils of these tendencies, present our consensus views on current best practices in population genomic data analysis, and highlight areas of statistical inference and theory that are in need of further attention. Thereby, we argue for the importance of defining a biologically relevant baseline model tuned to the details of each new analysis, of skepticism and scrutiny in interpreting model fitting results, and of carefully defining addressable hypotheses and underlying uncertainties.

Genetics of behavioural evolution in giant mice from Gough Island.

The evolution of behaviour on islands is a pervasive phenomenon that contributed to Darwin's theory of natural selection. Island populations frequently show increased boldness and exploration compared with their mainland counterparts. Despite the generality of this pattern, the genetic basis of island-associated behaviours remains a mystery. To address this gap in knowledge, we genetically dissected behaviour in 613 F2s generated by crossing inbred mouse strains from Gough Island (where they live without predators or human commensals) and a mainland conspecific. We used open field and light/dark box tests to measure seven behaviours related to boldness and exploration in juveniles and adults. Across all assays, we identified a total of 41 quantitative trait loci (QTL) influencing boldness and exploration. QTL have moderate effects and are often unique to specific behaviours or ages. Function-valued trait mapping revealed changes in estimated effects of QTL during assays, providing a rare dynamic window into the genetics of behaviour often missed by standard approaches. The genomic locations of QTL are distinct from those found in laboratory strains of mice, indicating different genetic paths to the evolution of similar behaviours. We combine our mapping results with extensive phenotypic and genetic information available for laboratory mice to nominate candidate genes for the evolution of behaviour on islands.

Finding Hybrid Incompatibilities Using Genome Sequences from Hybrid Populations.

Natural hybrid zones offer a powerful framework for understanding the genetic basis of speciation in progress because ongoing hybridization continually creates unfavorable gene combinations. Evidence indicates that postzygotic reproductive isolation is often caused by epistatic interactions between mutations in different genes that evolved independently of one another (hybrid incompatibilities). We examined the potential to detect epistatic selection against incompatibilities from genome sequence data using the site frequency spectrum (SFS) of polymorphisms by conducting individual-based simulations in SLiM. We found that the genome-wide SFS in hybrid populations assumes a diagnostic shape, with the continual input of fixed differences between source populations via migration inducing a mass at intermediate allele frequency. Epistatic selection locally distorts the SFS as non-incompatibility alleles rise in frequency in a manner analogous to a selective sweep. Building on these results, we present a statistical method to identify genomic regions containing incompatibility loci that locates departures in the local SFS compared with the genome-wide SFS. Cross-validation studies demonstrate that our method detects recessive and codominant incompatibilities across a range of scenarios varying in the strength of epistatic selection, migration rate, and hybrid zone age. Our approach takes advantage of whole genome sequence data, does not require knowledge of demographic history, and can be applied to any pair of nascent species that forms a hybrid zone.

Genomic Targets of Positive Selection in Giant Mice from Gough Island.

A key challenge in understanding how organisms adapt to their environments is to identify the mutations and genes that make it possible. By comparing patterns of sequence variation to neutral predictions across genomes, the targets of positive selection can be located. We applied this logic to house mice that invaded Gough Island (GI), an unusual population that shows phenotypic and ecological hallmarks of selection. We used massively parallel short-read sequencing to survey the genomes of 14 GI mice. We computed a set of summary statistics to capture diverse aspects of variation across these genome sequences, used approximate Bayesian computation to reconstruct a null demographic model, and then applied machine learning to estimate the posterior probability of positive selection in each region of the genome. Using a conservative threshold, 1,463 5-kb windows show strong evidence for positive selection in GI mice but not in a mainland reference population of German mice. Disproportionate shares of these selection windows contain genes that harbor derived nonsynonymous mutations with large frequency differences. Over-represented gene ontologies in selection windows emphasize neurological themes. Inspection of genomic regions harboring many selection windows with high posterior probabilities pointed to genes with known effects on exploratory behavior and body size as potential targets. Some genes in these regions contain candidate adaptive variants, including missense mutations and/or putative regulatory mutations. Our results provide a genomic portrait of adaptation to island conditions and position GI mice as a powerful system for understanding the genetic component of natural selection.

Background selection under evolving recombination rates.

Background selection (BGS), the effect that purifying selection exerts on sites linked to deleterious alleles, is expected to be ubiquitous across eukaryotic genomes. The effects of BGS reflect the interplay of the rates and fitness effects of deleterious mutations with recombination. A fundamental assumption of BGS models is that recombination rates are invariant over time. However, in some lineages, recombination rates evolve rapidly, violating this central assumption. Here, we investigate how recombination rate evolution affects genetic variation under BGS. We show that recombination rate evolution modifies the effects of BGS in a manner similar to a localized change in the effective population size, potentially leading to underestimation or overestimation of the genome-wide effects of selection. Furthermore, we find evidence that recombination rate evolution in the ancestors of modern house mice may have impacted inferences of the genome-wide effects of selection in that species.

A first genetic portrait of synaptonemal complex variation.

The synaptonemal complex (SC) is a proteinaceous scaffold required for synapsis and recombination between homologous chromosomes during meiosis. Although the SC has been linked to differences in genome-wide crossover rates, the genetic basis of standing variation in SC structure remains unknown. To investigate the possibility that recombination evolves through changes to the SC, we characterized the genetic architecture of SC divergence on two evolutionary timescales. Applying a novel digital image analysis technique to spermatocyte spreads, we measured total SC length in 9,532 spermatocytes from recombinant offspring of wild-derived mouse strains with differences in this fundamental meiotic trait. Using this large dataset, we identified the first known genomic regions involved in the evolution of SC length. Distinct loci affect total SC length divergence between and within subspecies, with the X chromosome contributing to both. Joint genetic analysis of MLH1 foci-immunofluorescent markers of crossovers-from the same spermatocytes revealed that two of the identified loci also confer differences in the genome-wide recombination rate. Causal mediation analysis suggested that one pleiotropic locus acts early in meiosis to designate crossovers prior to SC assembly, whereas a second locus primarily shapes crossover number through its effect on SC length. One genomic interval shapes the relationship between SC length and recombination rate, likely modulating the strength of crossover interference. Our findings pinpoint SC formation as a key step in the evolution of recombination and demonstrate the power of genetic mapping on standing variation in the context of the recombination pathway.

Disrupted Gene Networks in Subfertile Hybrid House Mice.

The Dobzhansky-Muller (DM) model provides a widely accepted mechanism for the evolution of reproductive isolation: incompatible substitutions disrupt interactions between genes. To date, few candidate incompatibility genes have been identified, leaving the genes driving speciation mostly uncharacterized. The importance of interactions in the DM model suggests that gene coexpression networks provide a powerful framework to understand disrupted pathways associated with postzygotic isolation. Here, we perform weighted gene coexpression network analysis to infer gene interactions in hybrids of two recently diverged European house mouse subspecies, Mus mus domesticus and M. m. musculus, which commonly show hybrid male sterility or subfertility. We use genome-wide testis expression data from 467 hybrid mice from two mapping populations: F2s from a laboratory cross between wild-derived pure subspecies strains and offspring of natural hybrids captured in the Central Europe hybrid zone. This large data set enabled us to build a robust consensus network using hybrid males with fertile phenotypes. We identify several expression modules, or groups of coexpressed genes, that are disrupted in subfertile hybrids, including modules functionally enriched for spermatogenesis, cilium and sperm flagellum organization, chromosome organization, and DNA repair, and including genes expressed in spermatogonia, spermatocytes, and spermatids. Our network-based approach enabled us to hone in on specific hub genes likely to be influencing module-wide gene expression and hence potentially driving large-effect DM incompatibilities. A disproportionate number of hub genes lie within sterility loci identified previously in the hybrid zone mapping population and represent promising candidate barrier genes and targets for future functional analysis.

Higher Intercellular Variation in Genome-Wide Recombination Rate in Female Mice.

Meiotic recombination affects fertility, shuffles genomes, and modulates the effectiveness of natural selection. Despite conservation of the recombination pathway, the rate of recombination varies among individuals and along chromosomes. Recombination rate also differs among cells from the same organism, but this form of variation has received less attention. To identify patterns that characterize intercellular variation in the genome-wide recombination rate, we counted foci of the MLH1 recombination-associated protein in oocytes and spermatocytes from a panel of wild-derived inbred strains of house mice. Females show higher intercellular variation in MLH1 focus count than males from the same inbred strains. This pattern is consistent across strains from multiple subspecies, including 2 strains in which the average MLH1 focus count is higher in males. The sex difference in genome-wide recombination rate we report suggests that selection targeting recombination rate will be more efficient in males than in females.

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 Power of Natural Variation for Model Organism Biology.

Genetic background effects have long been recognized and, in some cases studied, but they are often viewed as a nuisance by molecular biologists. We suggest that genetic variation currently represents a critical frontier for molecular studies. Human genetics has seen a surge of interest in genetic variation and its contributions to disease, but insights into disease mechanisms are difficult since information about gene function is lacking. By contrast, model organism genetics has excelled at revealing molecular mechanisms of cellular processes, but often de-emphasizes genetic variation and its functional consequences. We argue that model organism biology would benefit from incorporating natural variation, both to capture how well laboratory lines exemplify the species they represent and to inform on molecular processes and their variability. Such a synthesis would also greatly expand the relevance of model systems for studies of complex trait variation, including disease.

Conservation of the genome-wide recombination rate in white-footed mice.

Despite being linked to the fundamental processes of chromosome segregation and offspring diversification, meiotic recombination rates vary within and between species. Recent years have seen progress in quantifying recombination rate evolution across multiple temporal and genomic scales. Nevertheless, the level of variation in recombination rate within wild populations-a key determinant of evolution in this trait-remains poorly documented on the genomic scale. To address this notable gap, we used immunofluorescent cytology to quantify genome-wide recombination rates in males from a wild population of the white-footed mouse, Peromyscus leucopus. For comparison, we measured recombination rates in a second population of male P. leucopus raised in the laboratory and in male deer mice from the subspecies Peromyscus maniculatus bairdii. Although we found differences between individuals in the genome-wide recombination rate, levels of variation were low-within populations, between populations, and between species. Quantification of synaptonemal complex length and crossover positions along chromosome 1 using a novel automated approach also revealed conservation in broad-scale crossover patterning, including strong crossover interference. We propose stabilizing selection targeting recombination or correlated processes as the explanation for these patterns.

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

Population genetics theory supplies powerful predictions about how natural selection interacts with genetic linkage to sculpt the genomic landscape of nucleotide polymorphism. Both the spread of beneficial mutations and the removal of deleterious mutations act to depress polymorphism levels, especially in low-recombination regions. However, empiricists have documented extreme disparities among species. Here we characterize the dominant features that could drive differences in linked selection among species--including roles for selective sweeps being 'hard' or 'soft'--and the concealing effects of demography and confounding genomic variables. We advocate targeted studies of closely related species to unify our understanding of how selection and linkage interact to shape genome evolution.

Recombination rate variation in mice from an isolated island.

Recombination rate is a heritable trait that varies among individuals. Despite the major impact of recombination rate on patterns of genetic diversity and the efficacy of selection, natural variation in this phenotype remains poorly characterized. We present a comparison of genetic maps, sampling 1212 meioses, from a unique population of wild house mice (Mus musculus domesticus) that recently colonized remote Gough Island. Crosses to a mainland reference strain (WSB/EiJ) reveal pervasive variation in recombination rate among Gough Island mice, including subchromosomal intervals spanning up to 28% of the genome. In spite of this high level of polymorphism, the genomewide recombination rate does not significantly vary. In general, we find that recombination rate varies more when measured in smaller genomic intervals. Using the current standard genetic map of the laboratory mouse to polarize intervals with divergent recombination rates, we infer that the majority of evolutionary change occurred in one of the two tested lines of Gough Island mice. Our results confirm that natural populations harbour a high level of recombination rate polymorphism and highlight the disparities in recombination rate evolution across genomic scales.

Mouse genomic variation and its effect on phenotypes and gene regulation.

We report genome sequences of 17 inbred strains of laboratory mice and identify almost ten times more variants than previously known. We use these genomes to explore the phylogenetic history of the laboratory mouse and to examine the functional consequences of allele-specific variation on transcript abundance, revealing that at least 12% of transcripts show a significant tissue-specific expression bias. By identifying candidate functional variants at 718 quantitative trait loci we show that the molecular nature of functional variants and their position relative to genes vary according to the effect size of the locus. These sequences provide a starting point for a new era in the functional analysis of a key model organism.

Genomic networks of hybrid sterility.

Hybrid dysfunction, a common feature of reproductive barriers between species, is often caused by negative epistasis between loci ("Dobzhansky-Muller incompatibilities"). The nature and complexity of hybrid incompatibilities remain poorly understood because identifying interacting loci that affect complex phenotypes is difficult. With subspecies in the early stages of speciation, an array of genetic tools, and detailed knowledge of reproductive biology, house mice (Mus musculus) provide a model system for dissecting hybrid incompatibilities. Male hybrids between M. musculus subspecies often show reduced fertility. Previous studies identified loci and several X chromosome-autosome interactions that contribute to sterility. To characterize the genetic basis of hybrid sterility in detail, we used a systems genetics approach, integrating mapping of gene expression traits with sterility phenotypes and QTL. We measured genome-wide testis expression in 305 male F2s from a cross between wild-derived inbred strains of M. musculus musculus and M. m. domesticus. We identified several thousand cis- and trans-acting QTL contributing to expression variation (eQTL). Many trans eQTL cluster into eleven 'hotspots,' seven of which co-localize with QTL for sterility phenotypes identified in the cross. The number and clustering of trans eQTL-but not cis eQTL-were substantially lower when mapping was restricted to a 'fertile' subset of mice, providing evidence that trans eQTL hotspots are related to sterility. Functional annotation of transcripts with eQTL provides insights into the biological processes disrupted by sterility loci and guides prioritization of candidate genes. Using a conditional mapping approach, we identified eQTL dependent on interactions between loci, revealing a complex system of epistasis. Our results illuminate established patterns, including the role of the X chromosome in hybrid sterility. The integrated mapping approach we employed is applicable in a broad range of organisms and we advocate for widespread adoption of a network-centered approach in speciation genetics.

A genomic perspective on hybridization and speciation.

Hybridization among diverging lineages is common in nature. Genomic data provide a special opportunity to characterize the history of hybridization and the genetic basis of speciation. We review existing methods and empirical studies to identify recent advances in the genomics of hybridization, as well as issues that need to be addressed. Notable progress has been made in the development of methods for detecting hybridization and inferring individual ancestries. However, few approaches reconstruct the magnitude and timing of gene flow, estimate the fitness of hybrids or incorporate knowledge of recombination rate. Empirical studies indicate that the genomic consequences of hybridization are complex, including a highly heterogeneous landscape of differentiation. Inferred characteristics of hybridization differ substantially among species groups. Loci showing unusual patterns - which may contribute to reproductive barriers - are usually scattered throughout the genome, with potential enrichment in sex chromosomes and regions of reduced recombination. We caution against the growing trend of interpreting genomic variation in summary statistics across genomes as evidence of differential gene flow. We argue that converting genomic patterns into useful inferences about hybridization will ultimately require models and methods that directly incorporate key ingredients of speciation, including the dynamic nature of gene flow, selection acting in hybrid populations and recombination rate variation.

Fifteen years of genomewide scans for selection: trends, lessons and unaddressed genetic sources of complication.

Genomewide scans for natural selection (GWSS) have become increasingly common over the last 15 years due to increased availability of genome-scale genetic data. Here, we report a representative survey of GWSS from 1999 to present and find that (i) between 1999 and 2009, 35 of 49 (71%) GWSS focused on human, while from 2010 to present, only 38 of 83 (46%) of GWSS focused on human, indicating increased focus on nonmodel organisms; (ii) the large majority of GWSS incorporate interpopulation or interspecific comparisons using, for example F(ST), cross-population extended haplotype homozygosity or the ratio of nonsynonymous to synonymous substitutions; (iii) most GWSS focus on detection of directional selection rather than other modes such as balancing selection; and (iv) in human GWSS, there is a clear shift after 2004 from microsatellite markers to dense SNP data. A survey of GWSS meant to identify loci positively selected in response to severe hypoxic conditions support an approach to GWSS in which a list of a priori candidate genes based on potential selective pressures are used to filter the list of significant hits a posteriori. We also discuss four frequently ignored determinants of genomic heterogeneity that complicate GWSS: mutation, recombination, selection and the genetic architecture of adaptive traits. We recommend that GWSS methodology should better incorporate aspects of genomewide heterogeneity using empirical estimates of relevant parameters and/or realistic, whole-chromosome simulations to improve interpretation of GWSS results. Finally, we argue that knowledge of potential selective agents improves interpretation of GWSS results and that new methods focused on correlations between environmental variables and genetic variation can help automate this approach.

Microsatellites as targets of natural selection.

The ability to survey polymorphism on a genomic scale has enabled genome-wide scans for the targets of natural selection. Theory that connects patterns of genetic variation to evidence of natural selection most often assumes a diallelic locus and no recurrent mutation. Although these assumptions are suitable to selection that targets single nucleotide variants, fundamentally different types of mutation generate abundant polymorphism in genomes. Moreover, recent empirical results suggest that mutationally complex, multiallelic loci including microsatellites and copy number variants are sometimes targeted by natural selection. Given their abundance, the lack of inference methods tailored to the mutational peculiarities of these types of loci represents a notable gap in our ability to interrogate genomes for signatures of natural selection. Previous theoretical investigations of mutation-selection balance at multiallelic loci include assumptions that limit their application to inference from empirical data. Focusing on microsatellites, we assess the dynamics and population-level consequences of selection targeting mutationally complex variants. We develop general models of a multiallelic fitness surface, a realistic model of microsatellite mutation, and an efficient simulation algorithm. Using these tools, we explore mutation-selection-drift equilibrium at microsatellites and investigate the mutational history and selective regime of the microsatellite that causes Friedreich's ataxia. We characterize microsatellite selective events by their duration and cost, note similarities to sweeps from standing point variation, and conclude that it is premature to label microsatellites as ubiquitous agents of efficient adaptive change. Together, our models and simulation algorithm provide a powerful framework for statistical inference, which can be used to test the neutrality of microsatellites and other multiallelic variants.

Extensive recombination rate variation in the house mouse species complex inferred from genetic linkage maps.

The rate of recombination is a key genomic parameter that displays considerable variation among taxa. Species comparisons have demonstrated that the rate of evolution in recombination rate is strongly dependent on the physical scale of measurement. Individual recombination hotspots are poorly conserved among closely related taxa, whereas genomic-scale recombination rate variation bears a strong signature of phylogenetic history. In contrast, the mode and tempo of evolution in recombination rates measured on intermediate physical scales is poorly understood. Here, we conduct a detailed statistical comparison between two whole-genome F2 genetic linkage maps constructed from experimental intercrosses between closely related house mouse subspecies (Mus musculus). Our two maps profile a common wild-derived inbred strain of M. m. domesticus crossed to distinct wild-derived inbred strains representative of two other house mouse subspecies, M. m. castaneus and M. m. musculus. We identify numerous orthologous genomic regions with significant map length differences between these two crosses. Because the genomes of these recently diverged house mice are highly collinear, observed differences in map length (centimorgans) are suggestive of variation in broadscale recombination rate (centimorgans per megabase) within M. musculus. Collectively, these divergent intervals span 19% of the house mouse genome, disproportionately aggregating on the X chromosome. In addition, we uncover strong statistical evidence for a large effect, sex-linked, site-specific modifier of recombination rate segregating within M. musculus. Our findings reveal considerable variation in the megabase-scale recombination landscape among recently diverged taxa and underscore the continued importance of genetic linkage maps in the post-genome era.