The rate of recombination impacts on rates of protein evolution for at least two reasons: it affects the efficacy of selection due to linkage and influences sequence evolution through the process of GC-biased gene conversion (gBGC). We studied how recombination, via gBGC, affects inferences of selection in gene sequences using comparative genomic and population genomic data from the collared flycatcher (Ficedula albicollis). We separately analyzed different mutation categories ("strong"-to-"weak" "weak-to-strong," and GC-conservative changes) and found that gBGC impacts on the distribution of fitness effects of new mutations, and leads to that the rate of adaptive evolution and the proportion of adaptive mutations among nonsynonymous substitutions are underestimated by 22-33%. It also biases inferences of demographic history based on the site frequency spectrum. In light of this impact, we suggest that inferences of selection (and demography) in lineages with pronounced gBGC should be based on GC-conservative changes only. Doing so, we estimate that 10% of nonsynonymous mutations are effectively neutral and that 27% of nonsynonymous substitutions have been fixed by positive selection in the flycatcher lineage. We also find that gene expression level, sex-bias in expression, and the number of protein-protein interactions, but not Hill-Robertson interference (HRI), are strong determinants of selective constraint and rate of adaptation of collared flycatcher genes. This study therefore illustrates the importance of disentangling the effects of different evolutionary forces and genetic factors in interpretation of sequence data, and from that infer the role of natural selection in DNA sequence evolution.

Spatially varying selection with gene flow can favour the evolution of inversions that bind locally adapted alleles together, facilitate local adaptation and ultimately drive genomic divergence between species. Several studies have shown that the rates of spread and establishment of new inversions capturing locally adaptive alleles depend on a suite of evolutionary factors, including the strength of selection for local adaptation, rates of gene flow and recombination, and the deleterious mutation load carried by inversions. Because the balance of these factors is expected to differ between X (or Z) chromosomes and autosomes, opportunities for inversion evolution are likely to systematically differ between these genomic regions, though such scenarios have not been formally modelled. Here, we consider the evolutionary dynamics of X-linked and autosomal inversions in populations evolving at a balance between migration and local selection. We identify three factors that lead to asymmetric rates of X-linked and autosome inversion establishment: (1) sex-biased migration, (2) dominance of locally adapted alleles and (3) chromosome-specific deleterious mutation loads. This theory predicts an elevated rate of fixation, and depressed opportunities for polymorphism, for X-linked inversions. Our survey of data on the genomic distribution of polymorphic and fixed inversions supports both theoretical predictions. This article is part of the theme issue 'Linking local adaptation with the evolution of sex differences'.

Theoretical work suggests that sexual conflict should promote the maintenance of genetic diversity by the opposing directions of selection on sexually antagonistic mutations in males and females. This prediction, so far not been empirically tested on a genome-wide scale, could potentially contribute towards genomic heterogeneity in levels of genetic diversity. We used large-scale population genomic and transcriptomic data from the collared flycatcher (Ficedula albicollis) to analyse how sex-biased gene expression – one outcome of sexual conflict – relates to genetic variability. Here, we demonstrate that the extent of sex-biased gene expression of both male-biased and female-biased genes is significantly correlated with levels of nucleotide diversity in gene sequences and that this correlation extends to the overall levels of genomic diversity. We find evidence for balancing selection in sex-biased genes, suggesting that sex-biased gene expression could be seen as a component counteracting the diversity-reducing effects of linked positive and purifying selection. The observation of significant genetic differentiation between males and females for male-biased genes indicates ongoing sexual conflict and sex-specific viability selection, potentially driven by sexual selection. Our results thus provide a new perspective on the long-standing question in evolutionary biology of how genomes can remain so genetically variable in face of strong natural and sexual selection.

Closely related species may show similar levels of genetic diversity in homologous regions of the genome owing to shared ancestral variation still segregating in the extant species. However, after completion of lineage sorting, such covariation is not necessarily expected. On the other hand, if the processes that govern genetic diversity are conserved, diversity may potentially covary even among distantly related species. We mapped regions of conserved synteny between the genomes of two divergent bird speciescollared flycatcher and hooded crow-and identified more than 600 Mb of homologous regions (66% of the genome). From analyses of whole-genome resequencing data in large population samples of both species we found nucleotide diversity in 200 kb windows to be well correlated (Spearman's rho = 0.407). The correlation remained highly similar after excluding coding sequences. To explain this covariation, we suggest that a stable avian karyotype and a conserved landscape of recombination rate variation render the diversity-reducing effects of linked selection similar in divergent bird lineages. Principal component regression analysis of several potential explanatory variables driving heterogeneity in flycatcher diversity levels revealed the strongest effects from recombination rate variation and density of coding sequence targets for selection, consistent with linked selection. It is also possible that a stable karyotype is associated with a conserved genomic mutation environment contributing to covariation in diversity levels between lineages. Our observations imply that genetic diversity is to some extent predictable.

Individuals vary from each other in their genetic content. Genetic diversity is at the core of the evolutionary theory. Rooted in a solid theoretical framework developed as early as the 1930s, current empirical observations of genomic diversity became possible due to technological advances. These measurements, originally based on a few gene sequences from several individuals, are becoming possible at the genome scale for entire populations. We can now explore how evolutionary forces shape diversity levels along different parts of the genome. In this thesis, I focus on the variation in levels of diversity within genomes using avian systems and in particular that of the collared flycatcher (Ficedula albicollis). First, I describe the variation in genetic diversity along the genome of the collared flycatcher and compare it to the amount of variation in diversity across individuals within the population. I provide guidelines on how a small number of makers can capture the extent of variability in a population. Second, I investigate the stability of the local levels of diversity in the genome across evolutionary time scales by comparing collared flycatcher to the hooded crow (Corvus (corone) corone). Third, I study how selection can maintain variation through pervasive evolutionary conflict between sexes. Lastly, I explore how shifts in genome-wide variant frequencies across few generations can be utilised to estimate the effective size of population.

Properly estimating genetic diversity in populations of nonmodel species requires a basic understanding of how diversity is distributed across the genome and among individuals. To this end, we analysed whole-genome resequencing data from 20 collared flycatchers (genome size approximate to 1.1 Gb; 10.13 million single nucleotide polymorphisms detected). Genomewide nucleotide diversity was almost identical among individuals (mean = 0.00394, range = 0.00384-0.00401), but diversity levels varied extensively across the genome (95% confidence interval for 200-kb windows = 0.0013-0.0053). Diversity was related to selective constraint such that in comparison with intergenic DNA, diversity at fourfold degenerate sites was reduced to 85%, 3' UTRs to 82%, 5' UTRs to 70% and nondegenerate sites to 12%. There was a strong positive correlation between diversity and chromosome size, probably driven by a higher density of targets for selection on smaller chromosomes increasing the diversity-reducing effect of linked selection. Simulations exploring the ability of sequence data from a small number of genetic markers to capture the observed diversity clearly demonstrated that diversity estimation from finite sampling of such data is bound to be associated with large confidence intervals. Nevertheless, we show that precision in diversity estimation in large out-bred population benefits from increasing the number of loci rather than the number of individuals. Simulations mimicking RAD sequencing showed that this approach gives accurate estimates of genomewide diversity. Based on the patterns of observed diversity and the performed simulations, we provide broad recommendations for how genetic diversity should be estimated in natural populations.

Relatively little is known about the character of gene expression evolution as species diverge. It is for instance unclear if gene expression generally evolves in a clock-like manner (by stabilizing selection or neutral evolution) or if there are frequent episodes of directional selection. To gain insights into the evolutionary divergence of gene expression, we sequenced and compared the transcriptomes of multiple organs from population samples of collared (Ficedula albicollis) and pied flycatchers (F. hypoleuca), two species which diverged less than one million years ago. Ordination analysis separated samples by organ rather than by species. Organs differed in their degrees of expression variance within species and expression divergence between species. Variance was negatively correlated with expression breadth and protein interactivity, suggesting that pleiotropic constraints reduce gene expression variance within species. Variance was correlated with between-species divergence, consistent with a pattern expected from stabilizing selection and neutral evolution. Using an expression PST approach, we identified genes differentially expressed between species and found 16 genes uniquely expressed in one of the species. For one of these, DPP7, uniquely expressed in collared flycatcher, the absence of expression in pied flycatcher could be associated with a ≈ 20 kb deletion including 11 out of 13 exons. This study of a young vertebrate speciation model system expands our knowledge of how gene expression evolves as natural populations become reproductively isolated.

Parasite population structure is often thought to be largely shaped by that of its host. In the case of a parasite with a complex life cycle, two host species, each with their own patterns of demography and migration, spread the parasite. However, the population structure of the parasite is predicted to resemble only that of the most vagile host species. In this study, we tested this prediction in the context of a vector-transmitted parasite. We sampled the haemosporidian parasite Polychromophilus melanipherus across its European range, together with its bat fly vector Nycteribia schmidlii and its host, the bent-winged bat Miniopterus schreibersii. Based on microsatellite analyses, the wingless vector, and not the bat host, was identified as the least structured population and should therefore be considered the most vagile host. Genetic distance matrices were compared for all three species based on a mitochondrial DNA fragment. Both host and vector populations followed an isolation-by-distance pattern across the Mediterranean, but not the parasite. Mantel tests found no correlation between the parasite and either the host or vector populations. We therefore found no support for our hypothesis; the parasite population structure matched neither vector nor host. Instead, we propose a model where the parasite's gene flow is represented by the added effects of host and vector dispersal patterns.

Speciation is a continuous process during which genetic changes gradually accumulate in the genomes of diverging species. Recent studies have documented highly heterogeneous differentiation landscapes, with distinct regions of elevated differentiation ("differentiation islands") widespread across genomes. However, it remains unclear which processes drive the evolution of differentiation islands; how the differentiation landscape evolves as speciation advances; and ultimately, how differentiation islands are related to speciation. Here, we addressed these questions based on population genetic analyses of 200 resequenced genomes from 10 populations of four Ficedula flycatcher sister species. We show that a heterogeneous differentiation landscape starts emerging among populations within species, and differentiation islands evolve recurrently in the very same genomic regions among independent lineages. Contrary to expectations from models that interpret differentiation islands as genomic regions involved in reproductive isolation that are shielded from gene flow, patterns of sequence divergence (d(XY) relative node depth) do not support a major role of gene flow in the evolution of the differentiation landscape in these species. Instead, as predicted by models of linked selection, genome-wide variation in diversity and differentiation can be explained by variation in recombination rate and the density of targets for selection. We thus conclude that the heterogeneous landscape of differentiation in Ficedula flycatchers evolves mainly as the result of background selection and selective sweeps in genomic regions of low recombination. Our results emphasize the necessity of incorporating linked selection as a null model to identify genome regions involved in adaptation and speciation.