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ABSTRACT Hybrid zones, where genetically distinct groups of organisms meet and interbreed, offer valuable insights into the nature of species and speciation. Here, we present a new R package,bgchm, for population genomic analyses of hybrid zones. This R package extends and updates the existingbgcsoftware and combines Bayesian analyses of hierarchical genomic clines with Bayesian methods for estimating hybrid indexes, interpopulation ancestry proportions, and geographic clines. Compared to existing software,bgchmoffers enhanced efficiency through Hamiltonian Monte Carlo sampling and the ability to work with genotype likelihoods combined with a hierarchical Bayesian approach, enabling inference for diverse types of genetic data sets. The package also facilitates the quantification of introgression patterns across genomes, which is crucial for understanding reproductive isolation and speciation genetics. We first describe the models underlyingbgchmand then provide an overview of the R package and illustrate its use through the analysis of simulated and empirical data sets. We show thatbgchmgenerates accurate estimates of model parameters under a variety of conditions, especially when the genetic loci analyzed are highly ancestry informative. This includes relatively robust estimates of genome‐wide variability in clines, which has not been the focus of previous models and methods. We also illustrate how both selection and genetic drift contribute to variability in introgression among loci and how additional information can be used to help distinguish these contributions. We conclude by describing the promises and limitations ofbgchm, comparingbgchmto other software for genomic cline analyses, and identifying areas for fruitful future development. 

Abstract Understanding the processes that underlie the development of population genetic structure is central to the study of evolution. Patterns of genetic structure, in turn, can reveal signatures of isolation by distance (IBD), barriers to gene flow, or even the genesis of speciation. However, it is unclear how severe range restriction might impact the processes that dominate the development of genetic structure. In narrow endemic species, is population structure likely to be adaptive in nature, or rather the result of genetic drift? In this study, we investigated patterns of genetic diversity and structure in the narrow endemic Hayden's ringlet butterfly. Specifically, we asked to what degree genetic structure in the Hayden's ringlet can be explained by IBD, isolation by resistance (IBR) (in the form of geographic or ecological barriers to migration between populations), and isolation by environment (in the form of differences in host plant availability and preference). We employed a genotyping‐by‐sequencing (GBS) approach coupled with host preference assays, Bayesian modelling, and population genomic analyses to answer these questions. Our results suggest that despite their restricted range, levels of genetic diversity in the Hayden's ringlet are comparable to those seen in more widespread butterfly species. Hayden's ringlets showed a strong preference for feeding on grasses relative to sedges, but neither larval preference nor potential host availability at sampling sites correlated with genetic structure. We conclude that geography, in the form of IBR and simple IBD, was the major driver of contemporary patterns of differentiation in this narrow endemic species. 

Abstract Structural variants (SVs) can promote speciation by directly causing reproductive isolation or by suppressing recombination across large genomic regions. Whereas examples of each mechanism have been documented, systematic tests of the role of SVs in speciation are lacking. Here, we take advantage of long‐read (Oxford nanopore) whole‐genome sequencing and a hybrid zone between twoLycaeidesbutterfly taxa (L.melissaand Jackson HoleLycaeides) to comprehensively evaluate genome‐wide patterns of introgression for SVs and relate these patterns to hypotheses about speciation. We found >100,000 SVs segregating within or between the two hybridizing species. SVs and SNPs exhibited similar levels of genetic differentiation between species, with the exception of inversions, which were more differentiated. We detected credible variation in patterns of introgression among SV loci in the hybrid zone, with 562 of 1419 ancestry‐informative SVs exhibiting genomic clines that deviated from null expectations based on genome‐average ancestry. Overall, hybrids exhibited a directional shift towards Jackson HoleLycaeidesancestry at SV loci, consistent with the hypothesis that these loci experienced more selection on average than SNP loci. Surprisingly, we found that deletions, rather than inversions, showed the highest skew towards excess ancestry from Jackson HoleLycaeides. Excess Jackson HoleLycaeidesancestry in hybrids was also especially pronounced for Z‐linked SVs and inversions containing many genes. In conclusion, our results show that SVs are ubiquitous and suggest that SVs in general, but especially deletions, might disproportionately affect hybrid fitness and thus contribute to reproductive isolation. 

Abstract Understanding selection's impact on the genome is a major theme in biology. Functionally neutral genetic regions can be affected indirectly by natural selection, via their statistical association with genes under direct selection. The genomic extent of such indirect selection, particularly across loci not physically linked to those under direct selection, remains poorly understood, as does the time scale at which indirect selection occurs. Here, we use field experiments and genomic data in stick insects, deer mice and stickleback fish to show that widespread statistical associations with genes known to affect fitness cause many genetic loci across the genome to be impacted indirectly by selection. This includes regions physically distant from those directly under selection. Then, focusing on the stick insect system, we show that statistical associations between SNPs and other unknown, causal variants result in additional indirect selection in general and specifically within genomic regions of physically linked loci. This widespread indirect selection necessarily makes aspects of evolution more predictable. Thus, natural selection combines with chance genetic associations to affect genome‐wide evolution across linked and unlinked loci and even in modest‐sized populations. This process has implications for the application of evolutionary principles in basic and applied science. 

Abstract Effective population size affects the efficacy of selection, rate of evolution by drift and neutral diversity levels. When species are subdivided into multiple populations connected by gene flow, evolutionary processes can depend on global or local effective population sizes. Theory predicts that high levels of diversity might be maintained by gene flow, even very low levels of gene flow, consistent with species long‐term effective population size, but tests of this idea are mostly lacking. Here, we show thatLycaeidesbutterfly populations maintain low contemporary (variance) effective population sizes (e.g. ~200 individuals) and thus evolve rapidly by genetic drift. However, populations harboured high levels of genetic diversity consistent with an effective population size several orders of magnitude larger. We hypothesized that the differences in the magnitude and variability of contemporary versus long‐term effective population sizes were caused by gene flow of sufficient magnitude to maintain diversity but only subtly affect evolution on generational timescales. Consistent with this hypothesis, we detected low but nontrivial gene flow among populations. Furthermore, using short‐term population‐genomic time‐series data, we documented patterns consistent with predictions from this hypothesis, including a weak but detectable excess of evolutionary change in the direction of the mean (migrant gene pool) allele frequencies across populations and consistency in the direction of allele frequency change over time. The documented decoupling of diversity levels and short‐term change by drift inLycaeideshas implications for our understanding of contemporary evolution and the maintenance of genetic variation in the wild. 

Abstract Strong selection can cause rapid evolutionary change, but temporal fluctuations in the form, direction and intensity of selection can limit net evolutionary change over longer time periods. Fluctuating selection could affect molecular diversity levels and the evolution of plasticity and ecological specialization. Nonetheless, this phenomenon remains understudied, in part because of analytical limitations and the general difficulty of detecting selection that does not occur in a consistent manner. Herein, I fill this analytical gap by presenting an approximate Bayesian computation (ABC) method to detect and quantify fluctuating selection on polygenic traits from population genomic time‐series data. I propose a model for environment‐dependent phenotypic selection. The evolutionary genetic consequences of selection are then modelled based on a genotype–phenotype map. Using simulations, I show that the proposed method generates accurate and precise estimates of selection when the generative model for the data is similar to the model assumed by the method. The performance of the method when applied to an evolve‐and‐resequence study of host adaptation in the cowpea seed beetle (Callosobruchus maculatus) was more idiosyncratic and depended on specific analytical choices. Despite some limitations, these results suggest the proposed method provides a powerful approach to connect the causes of (variable) selection to traits and genome‐wide patterns of evolution. Documentation and open‐source computer software (fsabc) implementing this method are available fromgithub(https://github.com/zgompert/fsabc.git). 

Structural elements are widespread across genomes, but their complexity and role in repeatedly driving local adaptation remain unclear. In this work, we use phased genome assemblies to show that adaptive divergence in cryptic color pattern in a stick insect is repeatedly underlain by structural variation, but not a simple chromosomal inversion. We found that color pattern in populations of stick insects on two mountains is associated with translocations that have also been inverted. These translocations differ in size and origin on each mountain, but they overlap partially and involve some of the same gene regions. Moreover, this structural variation is subject to divergent selection and arose without introgression between species. Our results show how the origin of structural variation provides a mechanism for repeated bouts of adaptation. 

Despite the well-known effects of sexual selection on phenotypes, links between this evolutionary process and reproductive isolation, genomic divergence, and speciation have been difficult to establish. We unravel the genetic basis of sexually selected plumage traits to investigate their effects on reproductive isolation in barn swallows. The genetic architecture of sexual traits is characterized by 12 loci on two autosomes and the Z chromosome. Sexual trait loci exhibit signatures of divergent selection in geographic isolation and barriers to gene flow in secondary contact. Linkage disequilibrium between these genes has been maintained by selection in hybrid zones beyond what would be expected under admixture alone. Our findings reveal that selection on coupled sexual trait loci promotes reproductive isolation, providing key empirical evidence for the role of sexual selection in speciation. 

The extent to which evolution is repeatable remains debated. Here, we study changes over time in the frequency of cryptic color-pattern morphs in 10 replicate long-term field studies of a stick insect, each spanning at least a decade (across 30 years of total data). We find predictable “up-and-down” fluctuations in stripe frequency in all populations, representing repeatable evolutionary dynamics based on standing genetic variation. A field experiment demonstrates that these fluctuations involve negative frequency-dependent natural selection (NFDS). These fluctuations rely on demographic and selective variability that pushes populations away from equilibrium, such that they can reliably move back toward it via NFDS. Last, we show that the origin of new cryptic forms is associated with multiple structural genomic variants such that which mutations arise affects evolution at larger temporal scales. Thus, evolution from existing variation is predictable and repeatable, but mutation adds complexity even for traits evolving deterministically under natural selection. 

In hybrid zones, whether barrier loci experience selection mostly independently or as a unit depends on the ratio of selection to recombination as captured by the coupling coefficient. Theory predicts a sharper transition between an uncoupled and coupled system when more loci affect hybrid fitness. However, the extent of coupling in hybrid zones has rarely been quantified. Here, we use simulations to characterize the relationship between the coupling coefficient and variance in clines across genetic loci. We then re-analyze 25 hybrid zone data sets and find that cline variances and estimated coupling coefficients form a smooth continuum from high variance and weak coupling to low variance and strong coupling. Our results are consistent with low rates of hybridization and a strong genome-wide barrier to gene flow when the coupling coefficient is much greater than 1, but also suggest that this boundary might be approached gradually and at a near constant rate over time.