The rate of molecular adaptation in a changing environment

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

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

Independently evolved pollution resistance in four killifish populations is largely explained by few variants of large effect

The genetic architecture of phenotypic traits can affect the mode and tempo of trait evolution. Human-altered environments can impose strong natural selection, where successful evolutionary adaptation requires swift and large phenotypic shifts. In these scenarios, theory predicts that adaptation is due to a few adaptive variants of large effect, but empirical studies that have revealed the genetic architecture of rapidly evolved phenotypes are rare, especially for populations inhabiting polluted environments. Fundulus killifish have repeatedly evolved adaptive resistance to extreme pollution in urban estuaries. Prior studies, including genome scans for signatures of natural selection, have revealed some of the genes and pathways important for evolved pollution resistance, and provide context for the genotype-phenotype association studies reported here. We created multiple quantitative trait locus (QTL) mapping families using progenitors from four different resistant populations, and using RAD-seq genetically mapped variation in sensitivity (developmental perturbations) following embryonic exposure to a model toxicant PCB-126. We found that one to two large-effect QTL loci accounted for resistance to PCB-mediated developmental toxicity. QTLs harbored candidate genes that govern the regulation of aryl hydrocarbon receptor (AHR) signaling. One QTL locus was shared across all populations and another was shared across three populations. One QTL locus showed strong signatures of recent natural selection in the corresponding wild population but another QTL locus did not. Some candidate genes for PCB resistance inferred from genome scans in wild populations were identified as QTL, but some key candidate genes were not. We conclude that rapidly evolved resistance to the developmental defects normally caused by PCB-126 is governed by few genes of large effect. However, other aspects of resistance beyond developmental phenotypes may be governed by additional loci, such that comprehensive resistance to PCB-126, and to the mixtures of chemicals that distinguish urban estuaries more broadly, may be more genetically complex.

Comparative Population Transcriptomics Provide New Insight into the Evolutionary History and Adaptive Potential of World Ocean Krill

Genetic variation is instrumental for adaptation to changing environments but it is unclear how it is structured and contributes to adaptation in pelagic species lacking clear barriers to gene flow. Here, we applied comparative genomics to extensive transcriptome datasets from 20 krill species collected across the Atlantic, Indian, Pacific, and Southern Oceans. We compared genetic variation both within and between species to elucidate their evolutionary history and genomic bases of adaptation. We resolved phylogenetic interrelationships and uncovered genomic evidence to elevate the cryptic Euphausia similis var. armata into species. Levels of genetic variation and rates of adaptive protein evolution vary widely. Species endemic to the cold Southern Ocean, such as the Antarctic krill Euphausia superba, showed less genetic variation and lower evolutionary rates than other species. This could suggest a low adaptive potential to rapid climate change. We uncovered hundreds of candidate genes with signatures of adaptive evolution among Antarctic Euphausia but did not observe strong evidence of adaptive convergence with the predominantly Arctic Thysanoessa. We instead identified candidates for cold-adaptation that have also been detected in Antarctic fish, including genes that govern thermal reception such as TrpA1. Our results suggest parallel genetic responses to similar selection pressures across Antarctic taxa and provide new insights into the adaptive potential of important zooplankton already affected by climate change.

Independently evolved pollution resistance in four killifish populations is largely explained by few variants of large effect

The genetic architecture of phenotypic traits can affect the mode and tempo of trait evolution. Human-altered environments can impose strong natural selection, where successful evolutionary adaptation requires swift and large phenotypic shifts. In these scenarios, theory predicts the influence of few adaptive variants of large effect, but empirical studies that have revealed the genetic architecture of rapidly evolved phenotypes are rare, especially for populations inhabiting polluted environments. Fundulus killifish have repeatedly evolved adaptive resistance to extreme pollution in urban estuaries. Prior studies, including genome scans for signatures of natural selection, have revealed some of the genes and pathways important for evolved pollution resistance, and provide context for the genotype-phenotype association studies reported here. We created multiple quantitative trait locus (QTL) mapping families using progenitors from four different resistant populations, and genetically mapped variation in sensitivity (developmental perturbations) following embryonic exposure to a model toxicant PCB-126. We found that a few large-effect QTL loci accounted for resistance to PCB-mediated developmental toxicity. QTLs harbored candidate genes that govern the regulation of aryl hydrocarbon receptor (AHR) signaling, where some (but not all) of these QTL loci were shared across all populations, and some (but not all) of these loci showed signatures of recent natural selection in the corresponding wild population. Some strong candidate genes for PCB resistance inferred from genome scans in wild populations were identified as QTL, but some key candidate genes were not. We conclude that rapidly evolved resistance to the developmental defects normally caused by PCB-126 is governed by few genes of large effect. However, other aspects of resistance beyond developmental phenotypes may be governed by additional loci, such that comprehensive resistance to PCB-126, and to the mixtures of chemicals that distinguish urban estuaries more broadly, may be more genetically complex.

Population-genomic analysis identifies a low rate of global adaptive fixation in the proteins of the cyclical parthenogen Daphnia magna

Daphnia are well-established ecological and evolutionary models, and the interaction between D. magna and its microparasites is widely considered a paragon of the host-parasite coevolutionary process. Like other well-studied arthropods such as Drosophila melanogaster and Anopheles gambiae, D. magna is a small, widespread, and abundant species that is therefore expected to display a large long-term population size and high rates of adaptive protein evolution. However, unlike these other species, D. magna is cyclically asexual and lives in a highly structured environment (ponds and lakes) with moderate levels of dispersal, both of which are predicted to impact upon long-term effective population size and adaptive protein evolution. To investigate patterns of adaptive protein fixation, we produced the complete coding genomes of 36 D. magna clones sampled from across the European range (Western Palaearctic), along with draft sequences for the close relatives D. similis and D. lumholtzi, used as outgroups. We analyzed genome-wide patterns of adaptive fixation, with a particular focus on genes that have an a priori expectation of high rates, such as those likely to mediate immune responses, RNA interference against viruses and transposable elements, and those with a strongly male-biased expression pattern. We find that, as expected, D. magna displays high levels of diversity and that this is highly structured among populations. However, compared with Drosophila, we find that D. magna proteins appear to have a high proportion of weakly deleterious variants and do not show evidence of pervasive adaptive fixation across its entire range. This is true of the genome as a whole, and also of putative ‘arms race’ genes that often show elevated levels of adaptive substitution in other species. In addition to the likely impact of extensive, and previously documented, local adaptation, we speculate that these findings may reflect reduced efficacy of selection associated with cyclical asexual reproduction.

OUP accepted manuscript

It is known that methods to estimate the rate of adaptive evolution, which are based on the McDonald–Kreitman test, can be biased by changes in effective population size. Here, we demonstrate theoretically that changes in population size can also generate an artifactual correlation between the rate of adaptive evolution and any factor that is correlated to the strength of selection acting against deleterious mutations. In this context, we have investigated whether several site-level factors influence the rate of adaptive evolution in the divergence of humans and chimpanzees, two species that have been inferred to have undergone population size contraction since they diverged. We find that the rate of adaptive evolution, relative to the rate of mutation, is higher for more exposed amino acids, lower for amino acid pairs that are more dissimilar in terms of their polarity, volume, and lower for amino acid pairs that are subject to stronger purifying selection, as measured by the ratio of the numbers of nonsynonymous to synonymous polymorphisms (p_N/p_S). All of these correlations are opposite to the artifactual correlations expected under contracting population size. We therefore conclude that these correlations are genuine.

Allen Orr and the genetics of adaptation

Over most of the 20th century, evolutionary biologists predominantly subscribed to a strong form of "micro-mutationism," in which adaptive phenotypic divergence arises from allele frequency changes at many loci, each with a small effect on the phenotype. To be sure, there were well-known examples of large-effect alleles contributing to adaptation, yet such cases were generally regarded as atypical and unrepresentative of evolutionary change in general. In 1998, Allen Orr published a landmark theoretical paper in Evolution, which showed that both small- and large-effect mutations are likely to contribute to "adaptive walks" of a population to an optimum. Coupled with a growing set of empirical examples of large-effect alleles contributing to divergence (e.g., from QTL studies), Orr's paper provided a mathematical formalism that converted many evolutionary biologists from micro-mutationism to a more pluralistic perspective on the genetic basis of evolutionary change. We revisit the theoretical insights emerging from Orr's paper within the historical context leading up to 1998, and track the influence of this paper on the field of evolutionary biology through an examination of its citations over the last two decades and an analysis of the extensive body of theoretical and empirical research that Orr's pioneering paper inspired.

Quantifying the impact of changes in effective population size and expression level on the rate of coding sequence evolution

Molecular sequences are shaped by selection, where the strength of selection relative to drift is determined by effective population size (N_e). Populations with high N_e are expected to undergo stronger purifying selection, and consequently to show a lower substitution rate for selected mutations relative to the substitution rate for neutral mutations (ω). However, computational models based on biophysics of protein stability have suggested that ω can also be independent of N_e. Together, the response of ω to changes in N_e depends on the specific mapping from sequence to fitness. Importantly, an increase in protein expression level has been found empirically to result in decrease of ω, an observation predicted by theoretical models assuming selection for protein stability. Here, we derive a theoretical approximation for the response of ω to changes in N_e and expression level, under an explicit genotype-phenotype-fitness map. The method is generally valid for additive traits and log-concave fitness functions. We applied these results to protein undergoing selection for their conformational stability and corroborate out findings with simulations under more complex models. We predict a weak response of ω to changes in either N_e or expression level, which are interchangeable. Based on empirical data, we propose that fitness based on the conformational stability may not be a sufficient mechanism to explain the empirically observed variation in ω across species. Other aspects of protein biophysics might be explored, such as protein-protein interactions, which can lead to a stronger response of ω to changes in N_e.

Speciation in marine environments: Diving under the surface

Marine environments are inhabited by a broad representation of the tree of life, yet our understanding of speciation in marine ecosystems is extremely limited compared with terrestrial and freshwater environments. Developing a more comprehensive picture of speciation in marine environments requires that we 'dive under the surface' by studying a wider range of taxa and ecosystems is necessary for a more comprehensive picture of speciation. Although studying marine evolutionary processes is often challenging, recent technological advances in different fields, from maritime engineering to genomics, are making it increasingly possible to study speciation of marine life forms across diverse ecosystems and taxa. Motivated by recent research in the field, including the 14 contributions in this issue, we highlight and discuss six axes of research that we think will deepen our understanding of speciation in the marine realm: (a) study a broader range of marine environments and organisms; (b) identify the reproductive barriers driving speciation between marine taxa; (c) understand the role of different genomic architectures underlying reproductive isolation; (d) infer the evolutionary history of divergence using model-based approaches; (e) study patterns of hybridization and introgression between marine taxa; and (f) implement highly interdisciplinary, collaborative research programmes. In outlining these goals, we hope to inspire researchers to continue filling this critical knowledge gap surrounding the origins of marine biodiversity.

Greater strength of selection and higher proportion of beneficial amino acid changing mutations in humans compared with mice and Drosophila melanogaster

Quantifying and comparing the amount of adaptive evolution among different species is key to understanding how evolution works. Previous studies have shown differences in adaptive evolution across species; however, their specific causes remain elusive. Here, we use improved modeling of weakly deleterious mutations and the demographic history of the outgroup species and ancestral population and estimate that at least 20% of nonsynonymous substitutions between humans and an outgroup species were fixed by positive selection. This estimate is much higher than previous estimates, which did not correct for the sizes of the outgroup species and ancestral population. Next, we jointly estimate the proportion and selection coefficient (p⁺ and s⁺, respectively) of newly arising beneficial nonsynonymous mutations in humans, mice, and Drosophila melanogaster by examining patterns of polymorphism and divergence. We develop a novel composite likelihood framework to test whether these parameters differ across species. Overall, we reject a model with the same p⁺ and s⁺ of beneficial mutations across species and estimate that humans have a higher p⁺s⁺ compared with that of D. melanogaster and mice. We show that this result cannot be caused by biased gene conversion or hypermutable CpG sites. We discuss possible biological explanations that could generate the observed differences in the amount of adaptive evolution across species.

Why is cancer not more common? A changing microenvironment may help to explain why, and suggests strategies for anti-cancer therapy

One of the great unsolved puzzles in cancer biology is not why cancers occur, but rather explaining why so few cancers occur compared with the theoretical number that could occur, given the number of progenitor cells in the body and the normal mutation rate. We hypothesized that a contributory explanation is that the tumour microenvironment (TME) is not fixed due to factors such as immune cell infiltration, and that this could impair the ability of neoplastic cells to retain a high enough fitness to become a cancer. The TME has implicitly been assumed to be static in most cancer evolution models, and we therefore developed a mathematical model of spatial cancer evolution assuming that the TME, and thus the optimum cancer phenotype, changes over time. Based on simulations, we show how cancer cell populations adapt to diverse changing TME conditions and fitness landscapes. Compared with static TMEs, which generate neutral dynamics, changing TMEs lead to complex adaptations with characteristic spatio-temporal heterogeneity involving variable fitness effects of driver mutations, subclonal mixing, subclonal competition and phylogeny patterns. In many cases, cancer cell populations fail to grow or undergo spontaneous regression, and even extinction. Our analyses predict that cancer evolution in a changing TME is challenging, and can help to explain why cancer is neither inevitable nor as common as expected. Should cancer driver mutations with effects dependent of the TME exist, they are likely to be selected. Anti-cancer prevention and treatment strategies based on changing the TME are feasible and potentially effective.

Is adaptation limited by mutation? A timescale-dependent effect of genetic diversity on the adaptive substitution rate in animals

Whether adaptation is limited by the beneficial mutation supply is a long-standing question of evolutionary genetics, which is more generally related to the determination of the adaptive substitution rate and its relationship with species effective population size (Ne) and genetic diversity. Empirical evidence reported so far is equivocal, with some but not all studies supporting a higher adaptive substitution rate in large-Ne than in small-Ne species. We gathered coding sequence polymorphism data and estimated the adaptive amino-acid substitution rate ωa, in 50 species from ten distant groups of animals with markedly different population mutation rate θ. We reveal the existence of a complex, timescale dependent relationship between species adaptive substitution rate and genetic diversity. We find a positive relationship between ωa and θ among closely related species, indicating that adaptation is indeed limited by the mutation supply, but this was only true in relatively low-θ taxa. In contrast, we uncover no significant correlation between ωa and θ at a larger taxonomic scale, suggesting that the proportion of beneficial mutations scales negatively with species' long-term Ne.

Variation of the adaptive substitution rate between species and within genomes

The importance of adaptive mutations in molecular evolution is extensively debated. Recent developments in population genomics allow inferring rates of adaptive mutations by fitting a distribution of fitness effects to the observed patterns of polymorphism and divergence at sites under selection and sites assumed to evolve neutrally. Here, we summarize the current state-of-the-art of these methods and review the factors that affect the molecular rate of adaptation. Several studies have reported extensive cross-species variation in the proportion of adaptive amino-acid substitutions (α) and predicted that species with larger effective population sizes undergo less genetic drift and higher rates of adaptation. Disentangling the rates of positive and negative selection, however, revealed that mutations with deleterious effects are the main driver of this population size effect and that adaptive substitution rates vary comparatively little across species. Conversely, rates of adaptive substitution have been documented to vary substantially within genomes. On a genome-wide scale, gene density, recombination and mutation rate were observed to play a role in shaping molecular rates of adaptation, as predicted under models of linked selection. At the gene level, it has been reported that the gene functional category and the macromolecular structure substantially impact the rate of adaptive mutations. Here, we deliver a comprehensive review of methods used to infer the molecular adaptive rate, the potential drivers of adaptive evolution and how positive selection shapes molecular evolution within genes, across genes within species and between species.

Comparison of the Full Distribution of Fitness Effects of New Amino Acid Mutations Across Great Apes

The distribution of fitness effects (DFE) is central to many questions in evolutionary biology. However, little is known about the differences in DFE between closely related species. We use >9000 coding genes orthologous one-to-one across great apes, gibbons, and macaques to assess the stability of the DFE across great apes. We use the unfolded site frequency spectrum of polymorphic mutations (n = 8 haploid chromosomes per population) to estimate the DFE. We find that the shape of the deleterious DFE is strikingly similar across great apes. We confirm that effective population size (Ne ) is a strong predictor of the strength of negative selection, consistent with the nearly neutral theory. However, we also find that the strength of negative selection varies more than expected given the differences in Ne between species. Across species, mean fitness effects of new deleterious mutations covaries with Ne , consistent with positive epistasis among deleterious mutations. We find that the strength of negative selection for the smallest populations, bonobos and western chimpanzees, is higher than expected given their Ne This may result from a more efficient purging of strongly deleterious recessive variants in these populations. Forward simulations confirm that these findings are not artifacts of the way we are inferring Ne and DFE parameters. All findings are replicated using only GC-conservative mutations, thereby confirming that GC-biased gene conversion is not affecting our conclusions.

Tipping the Scales: The Migration-Selection Balance Leans toward Selection in Snake Venoms

The migration-selection interaction is the strongest determinant of whether a beneficial allele increases in frequency within a population. Results of empirical studies examining the role of gene flow in an adaptive context, however, have largely been equivocal, with examples of opposing outcomes being repeatedly documented (e.g., local adaptation with high levels of gene flow vs. gene swamping). We compared neutral genomic and venom expression divergence for three sympatric pit vipers with differing ecologies to determine if and how migration-selection disequilibria result in local adaptation. We specifically tested whether neutral differentiation predicted phenotypic differentiation within an isolation-by-distance framework. The decoupling of neutral and phenotypic differentiation would indicate selection led to adaptive divergence irrespective of migration, whereas a significant relationship between neutral and venom expression differentiation would provide evidence in favor of the constraining force of gene flow. Neutral differentiation and geographic distance predicted phenotypic differentiation only in the generalist species, indicating that selection was the predominant mechanism in the migration-selection balance underlying adaptive venom evolution in both specialists. Dispersal is thought to be a stronger influence on genetic differentiation than specialization, but our results suggest the opposite. Greater specialization may lead to greater diversification rates, and extreme spatial and temporal variation in selective pressures can favor generalist phenotypes evolving under strong stabilizing selection. Our results are consistent with these expectations, suggesting that the equivocal findings of studies examining the role of gene flow in an adaptive context may be explained by ecological specialization theory.

Biased Inference of Selection Due to GC-Biased Gene Conversion and the Rate of Protein Evolution in Flycatchers When Accounting for It

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.

Determinants of the Efficacy of Natural Selection on Coding and Noncoding Variability in Two Passerine Species

Population genetic theory predicts that selection should be more effective when the effective population size (N_e) is larger, and that the efficacy of selection should correlate positively with recombination rate. Here, we analyzed the genomes of ten great tits and ten zebra finches. Nucleotide diversity at 4-fold degenerate sites indicates that zebra finches have a 2.83-fold larger N_e. We obtained clear evidence that purifying selection is more effective in zebra finches. The proportion of substitutions at 0-fold degenerate sites fixed by positive selection (α) is high in both species (great tit 48%; zebra finch 64%) and is significantly higher in zebra finches. When α was estimated on GC-conservative changes (i.e., between A and T and between G and C), the estimates reduced in both species (great tit 22%; zebra finch 53%). A theoretical model presented herein suggests that failing to control for the effects of GC-biased gene conversion (gBGC) is potentially a contributor to the overestimation of α, and that this effect cannot be alleviated by first fitting a demographic model to neutral variants. We present the first estimates in birds for α in the untranslated regions, and found evidence for substantial adaptive changes. Finally, although purifying selection is stronger in high-recombination regions, we obtained mixed evidence for α increasing with recombination rate, especially after accounting for gBGC. These results highlight that it is important to consider the potential confounding effects of gBGC when quantifying selection and that our understanding of what determines the efficacy of selection is incomplete.

Evolutionary and food supply implications of ongoing maize domestication by Mexican campesinos

Maize evolution under domestication is a process that continues today. Case studies suggest that Mexican smallholder family farmers, known as campesinos, contribute importantly to this, but their significance has not been explicitly quantified and analysed as a whole. Here, we examine the evolutionary and food security implications of the scale and scope under which campesinos produce maize. We gathered official municipal-level data on maize production under rainfed conditions and identified campesino agriculture as occurring in municipalities with average yields of less than or equal to 3 t ha^-1 Environmental conditions vary widely in those municipalities and are associated with a great diversity of maize races, representing 85.3% of native maize samples collected in the country. We estimate that in those municipalities, around 1.38 × 10¹¹ genetically different individual plants are subjected to evolution under domestication each season. This implies that 5.24 × 10⁸ mother plants contribute to the next generation with their standing genetic diversity and rare alleles. Such a large breeding population size also increases the total number of adaptive mutations that may appear and be selected for. We also estimate that campesino agriculture could potentially feed around 54.7 million people in Mexico. These analyses provide insights about the contributions of smallholder agriculture around the world.

High rate of adaptive evolution in two widespread European pines

Comparing related organisms with differing ecological requirements and evolutionary histories can shed light on the mechanisms and drivers underlying genetic adaptation. Here, by examining a common set of hundreds of loci, we compare patterns of nucleotide diversity and molecular adaptation of two European conifers (Scots pine and maritime pine) living in contrasted environments and characterized by distinct population genetic structure (low and clinal in Scots pine, high and ecotypic in maritime pine) and demographic histories. We found higher nucleotide diversity in Scots pine than in maritime pine, whereas rates of new adaptive substitutions (ω_a ), as estimated from the distribution of fitness effects, were similar across species and among the highest found in plants. Sample size and population genetic structure did not appear to have resulted in significant bias in estimates of ω_a . Moreover, population contraction-expansion dynamics for each species did not affect differentially the rate of adaptive substitution in these two pines. Several methodological and biological factors may underlie the unusually high rate of adaptive evolution of Scots pine and maritime pine. By providing two new case studies with contrasting evolutionary histories, we contribute to disentangling the multiple factors potentially affecting adaptive evolution in natural plant populations.

Effect of Population Size and Mutation Rate on the Evolution of RNA Sequences on an Adaptive Landscape Determined by RNA Folding

The dynamics of populations evolving on an adaptive landscape depends on multiple factors, including the structure of the landscape, the rate of mutations, and effective population size. Existing theoretical work often makes ad hoc and simplifying assumptions about landscape structure, whereas experimental work can vary important parameters only to a limited extent. We here overcome some of these limitations by simulating the adaptive evolution of RNA molecules, whose fitness is determined by the thermodynamics of RNA secondary structure folding. We study the influence of mutation rates and population sizes on final mean population fitness, on the substitution rates of mutations, and on population diversity. We show that evolutionary dynamics cannot be understood as a function of mutation rate µ, population size N, or population mutation rate Nµ alone. For example, at a given mutation rate, clonal interference prevents the fixation of beneficial mutations as population size increases, but larger populations still arrive at a higher mean fitness. In addition, at the highest population mutation rates we study, mean final fitness increases with population size, because small populations are driven to low fitness by the relatively higher incidence of mutations they experience. Our observations show that mutation rate and population size can interact in complex ways to influence the adaptive dynamics of a population on a biophysically motivated fitness landscape.

Determining the factors driving selective effects of new nonsynonymous mutations

The distribution of fitness effects (DFE) of new mutations plays a fundamental role in evolutionary genetics. However, the extent to which the DFE differs across species has yet to be systematically investigated. Furthermore, the biological mechanisms determining the DFE in natural populations remain unclear. Here, we show that theoretical models emphasizing different biological factors at determining the DFE, such as protein stability, back-mutations, species complexity, and mutational robustness make distinct predictions about how the DFE will differ between species. Analyzing amino acid-changing variants from natural populations in a comparative population genomic framework, we find that humans have a higher proportion of strongly deleterious mutations than Drosophila melanogaster. Furthermore, when comparing the DFE across yeast, Drosophila, mice, and humans, the average selection coefficient becomes more deleterious with increasing species complexity. Last, pleiotropic genes have a DFE that is less variable than that of nonpleiotropic genes. Comparing four categories of theoretical models, only Fisher's geometrical model (FGM) is consistent with our findings. FGM assumes that multiple phenotypes are under stabilizing selection, with the number of phenotypes defining the complexity of the organism. Our results suggest that long-term population size and cost of complexity drive the evolution of the DFE, with many implications for evolutionary and medical genomics.

Evidence that the rate of strong selective sweeps increases with population size in the great apes

Quantifying the number of selective sweeps and their combined effects on genomic diversity in humans and other great apes is notoriously difficult. Here we address the question using a comparative approach to contrast diversity patterns according to the distance from genes in all great ape taxa. The extent of diversity reduction near genes compared with the rest of intergenic sequences is greater in a species with larger effective population size. Also, the maximum distance from genes at which the diversity reduction is observed is larger in species with large effective population size. In Sumatran orangutans, the overall genomic diversity is ∼30% smaller than diversity levels far from genes, whereas this reduction is only 9% in humans. We show by simulation that selection against deleterious mutations in the form of background selection is not expected to cause these differences in diversity among species. Instead, selective sweeps caused by positive selection can reduce diversity level more severely in a large population if there is a higher number of selective sweeps per unit time. We discuss what can cause such a correlation, including the possibility that more frequent sweeps in larger populations are due to a shorter waiting time for the right mutations to arise.

Does long term low impact stress cause population extinction?

This study assessed and monitored 40 consecutive reproduction tests - multigenerational (MG) - of continuous exposure to Cd (at 2 reproduction Effect Concentrations (EC): EC10 and EC50) using the standard soil invertebrate Folsomia candida, in total 3.5 years of data were collected. Endpoints included survival, reproduction, size and metallothionein (MTc) gene expression. Further, to investigate adaptation to the toxicant, additional standard toxicity experiments were performed with the MG organisms of F₆, F₁₀, F₂₆, F₃₄ and F₄₀ generations of exposure. Exposure to Cd EC10 caused population extinction after one year, whereas populations survived exposure to Cd EC50. Cd induced the up-regulation of the MTc gene, this being higher for the higher Cd concentration, which may have promoted the increased tolerance at the EC50. Moreover, EC10 induced a shift towards organisms of smaller size (positive skew), whereas EC50 induced a shift towards larger size (negative skew). Size distribution shifts could be an effect predictor. Sensitivity increased up to F₁₀, but this was reverted to values similar to F₀ in the next generations. The maximum Cd tolerance limits of F. candida increased for Cd EC50 MG. The consequences for risk assessment are discussed.

Antiviral drug resistance as an adaptive process

Antiviral drug resistance is a matter of great clinical importance that, historically, has been investigated mostly from a virological perspective. Although the proximate mechanisms of resistance can be readily uncovered using these methods, larger evolutionary trends often remain elusive. Recent interest by population geneticists in studies of antiviral resistance has spurred new metrics for evaluating mutation and recombination rates, demographic histories of transmission and compartmentalization, and selective forces incurred during viral adaptation to antiviral drug treatment. We present up-to-date summaries on antiviral resistance for a range of drugs and viral types, and review recent advances for studying their evolutionary histories. We conclude that information imparted by demographic and selective histories, as revealed through population genomic inference, is integral to assessing the evolution of antiviral resistance as it pertains to human health.

Adaptive Protein Evolution in Animals and the Effective Population Size Hypothesis

The rate at which genomes adapt to environmental changes and the prevalence of adaptive processes in molecular evolution are two controversial issues in current evolutionary genetics. Previous attempts to quantify the genome-wide rate of adaptation through amino-acid substitution have revealed a surprising diversity of patterns, with some species (e.g. Drosophila) experiencing a very high adaptive rate, while other (e.g. humans) are dominated by nearly-neutral processes. It has been suggested that this discrepancy reflects between-species differences in effective population size. Published studies, however, were mainly focused on model organisms, and relied on disparate data sets and methodologies, so that an overview of the prevalence of adaptive protein evolution in nature is currently lacking. Here we extend existing estimators of the amino-acid adaptive rate by explicitly modelling the effect of favourable mutations on non-synonymous polymorphism patterns, and we apply these methods to a newly-built, homogeneous data set of 44 non-model animal species pairs. Data analysis uncovers a major contribution of adaptive evolution to the amino-acid substitution process across all major metazoan phyla—with the notable exception of humans and primates. The proportion of adaptive amino-acid substitution is found to be positively correlated to species effective population size. This relationship, however, appears to be primarily driven by a decreased rate of nearly-neutral amino-acid substitution because of more efficient purifying selection in large populations. Our results reveal that adaptive processes dominate the evolution of proteins in most animal species, but do not corroborate the hypothesis that adaptive substitutions accumulate at a faster rate in large populations. Implications regarding the factors influencing the rate of adaptive evolution and positive selection detection in humans vs. other organisms are discussed.

The rate at which species adapt to environmental changes is a controversial topic. The theory predicts that adaptation is easier in large than in small populations, and the genomic studies of model organisms have revealed a much higher adaptive rate in large population-sized flies than in small population-sized humans and apes. Here we build and analyse a large data set of protein-coding sequences made of thousands of genes in 44 pairs of species from various groups of animals including insects, molluscs, annelids, echinoderms, reptiles, birds, and mammals. Extending and improving existing data analysis methods, we show that adaptation is a major process in protein evolution across all phyla of animals: the proportion of amino-acid substitutions that occurred adaptively is above 50% in a majority of species, and reaches up to 90%. Our analysis does not confirm that population size, here approached through species genetic diversity and ecological traits, does influence the rate of adaptive molecular evolution, but points to human and apes as a special case, compared to other animals, in terms of adaptive genomic processes.

Kr/Kc but not dN/dS correlates positively with body mass in birds, raising implications for inferring lineage-specific selection

Background

The ratio of the rates of non-synonymous and synonymous substitution (d_N/d_S) is commonly used to estimate selection in coding sequences. It is often suggested that, all else being equal, d_N/d_S should be lower in populations with large effective size (N_e) due to increased efficacy of purifying selection. As N_e is difficult to measure directly, life history traits such as body mass, which is typically negatively associated with population size, have commonly been used as proxies in empirical tests of this hypothesis. However, evidence of whether the expected positive correlation between body mass and d_N/d_S is consistently observed is conflicting.

Results

Employing whole genome sequence data from 48 avian species, we assess the relationship between rates of molecular evolution and life history in birds. We find a negative correlation between d_N/d_S and body mass, contrary to nearly neutral expectation. This raises the question whether the correlation might be a method artefact. We therefore in turn consider non-stationary base composition, divergence time and saturation as possible explanations, but find no clear patterns. However, in striking contrast to d_N/d_S, the ratio of radical to conservative amino acid substitutions (K_r/K_c) correlates positively with body mass.

Conclusions

Our results in principle accord with the notion that non-synonymous substitutions causing radical amino acid changes are more efficiently removed by selection in large populations, consistent with nearly neutral theory. These findings have implications for the use of d_N/d_S and suggest that caution is warranted when drawing conclusions about lineage-specific modes of protein evolution using this metric.

Electronic supplementary material

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Genomic tools to assist breeding for drought tolerance

Water deficit or drought stress is a major limitation to crop production globally. Plant breeders have used a wide range of technologies to successfully breed varieties that perform well under the growth conditions for their target environments but they are always seeking new opportunities to enhance rates of genetic gain. Under drought, yield is determined by the integration of variable levels of water deficit across the developmental life of the crop. Genomics technologies were seen as a path to understand the genetic and environmental complexity of drought stress. To be relevant to breeding programs, genomic studies must consider the nature of drought stress in the target environment and use plant material and phenotyping techniques that relate to field conditions.

Mining the pig genome to investigate the domestication process

Pig domestication began around 9000 YBP in the Fertile Crescent and Far East, involving marked morphological and genetic changes that occurred in a relatively short window of time. Identifying the alleles that drove the behavioural and physiological transformation of wild boars into pigs through artificial selection constitutes a formidable challenge that can only be faced from an interdisciplinary perspective. Indeed, although basic facts regarding the demography of pig domestication and dispersal have been uncovered, the biological substrate of these processes remains enigmatic. Considerable hope has been placed on new approaches, based on next-generation sequencing, which allow whole-genome variation to be analyzed at the population level. In this review, we provide an outline of the current knowledge on pig domestication by considering both archaeological and genetic data. Moreover, we discuss several potential scenarios of genome evolution under the complex mixture of demography and selection forces at play during domestication. Finally, we highlight several technical and methodological approaches that may represent significant advances in resolving the conundrum of livestock domestication.

The Utility of Fisher's Geometric Model in Evolutionary Genetics

The accumulation of data on the genomic bases of adaptation has triggered renewed interest in theoretical models of adaptation. Among these models, Fisher Geometric Model (FGM) has received a lot of attention over the last two decades. FGM is based on a continuous multidimensional phenotypic landscape, but it is for the emerging properties of individual mutation effects that it is mostly used. Despite an apparent simplicity and a limited number of parameters, FGM integrates a full model of mutation and epistatic interactions that allows the study of both beneficial and deleterious mutations, and subsequently the fate of evolving populations. In this review, I present the different properties of FGM and the qualitative and quantitative support they have received from experimental evolution data. I later discuss how to estimate the different parameters of the model and outline some future directions to connect FGM and the molecular determinants of adaptation.

High prevalence of non-synonymous substitutions in mtDNA of cichlid fishes from Lake Victoria

When a population size is reduced, genetic drift may fix slightly deleterious mutations, and an increase in nonsynonymous substitution is expected. It has been suggested that past aridity has seriously affected and decreased the populations of cichlid fishes in Lake Victoria, while geographical studies have shown that the water levels in Lake Tanganyika and Lake Malawi have remained fairly constant. The comparably stable environments in the latter two lakes might have kept the populations of cichlid fishes large enough to remove slightly deleterious mutations. The difference in the stability of cichlid fish population sizes between Lake Victoria and the Lakes Tanganyika and Malawi is expected to have caused differences in the nonsynonymous/synonymous ratio, ω (=dN/dS), of the evolutionary rate. Here, we estimated ω and compared it between the cichlids of the three lakes for 13 mitochondrial protein-coding genes using maximum likelihood methods. We found that the lineages of the cichlids in Lake Victoria had a significantly higher ω for several mitochondrial loci. Moreover, positive selection was indicated for several codons in the mtDNA of the Lake Victoria cichlid lineage. Our results indicate that both adaptive and slightly deleterious molecular evolution has taken place in the Lake Victoria cichlids' mtDNA genes, whose nonsynonymous sites are generally conserved.

Fisher's geometric model with a moving optimum

Fisher's geometric model has been widely used to study the effects of pleiotropy and organismic complexity on phenotypic adaptation. Here, we study a version of Fisher's model in which a population adapts to a gradually moving optimum. Key parameters are the rate of environmental change, the dimensionality of phenotype space, and the patterns of mutational and selectional correlations. We focus on the distribution of adaptive substitutions, that is, the multivariate distribution of the phenotypic effects of fixed beneficial mutations. Our main results are based on an “adaptive-walk approximation,” which is checked against individual-based simulations. We find that (1) the distribution of adaptive substitutions is strongly affected by the ecological dynamics and largely depends on a single composite parameter γ, which scales the rate of environmental change by the “adaptive potential” of the population; (2) the distribution of adaptive substitution reflects the shape of the fitness landscape if the environment changes slowly, whereas it mirrors the distribution of new mutations if the environment changes fast; (3) in contrast to classical models of adaptation assuming a constant optimum, with a moving optimum, more complex organisms evolve via larger adaptive steps.

Genetic signatures of natural selection in response to air pollution in red spruce (Picea rubens, Pinaceae)

One of the most important drivers of local adaptation for forest trees is climate. Coupled to these patterns, however, are human-induced disturbances through habitat modification and pollution. The confounded effects of climate and disturbance have rarely been investigated with regard to selective pressure on forest trees. Here, we have developed and used a population genetic approach to search for signals of selection within a set of 36 candidate genes chosen for their putative effects on adaptation to climate and human-induced air pollution within five populations of red spruce (Picea rubens Sarg.), distributed across its natural range and air pollution gradient in eastern North America. Specifically, we used FST outlier and environmental correlation analyses to highlight a set of seven single nucleotide polymorphisms (SNPs) that were overly correlated with climate and levels of sulphate pollution after correcting for the confounding effects of population history. Use of three age cohorts within each population allowed the effects of climate and pollution to be separated temporally, as climate-related SNPs (n = 7) showed the strongest signals in the oldest cohort, while pollution-related SNPs (n = 3) showed the strongest signals in the youngest cohorts. These results highlight the usefulness of population genetic scans for the identification of putatively nonneutral evolution within genomes of nonmodel forest tree species, but also highlight the need for the development and application of robust methodologies to deal with the inherent multivariate nature of the genetic and ecological data used in these types of analyses.

Population size and the rate of evolution

Does evolution proceed faster in larger or smaller populations? The relationship between effective population size (Ne) and the rate of evolution has consequences for our ability to understand and interpret genomic variation, and is central to many aspects of evolution and ecology. Many factors affect the relationship between Ne and the rate of evolution, and recent theoretical and empirical studies have shown some surprising and sometimes counterintuitive results. Some mechanisms tend to make the relationship positive, others negative, and they can act simultaneously. The relationship also depends on whether one is interested in the rate of neutral, adaptive, or deleterious evolution. Here, we synthesize theoretical and empirical approaches to understanding the relationship and highlight areas that remain poorly understood.

Pollen-specific, but not sperm-specific, genes show stronger purifying selection and higher rates of positive selection than sporophytic genes in Capsella grandiflora

Selection on the gametophyte can be a major force shaping plant genomes as 7-11% of genes are expressed only in that phase and 60% of genes are expressed in both the gametophytic and sporophytic phases. The efficacy of selection on gametophytic tissues is likely to be influenced by sexual selection acting on male and female functions of hermaphroditic plants. Moreover, the haploid nature of the gametophytic phase allows selection to be efficient in removing recessive deleterious mutations and fixing recessive beneficial mutations. To assess the importance of gametophytic selection, we compared the strength of purifying selection and extent of positive selection on gametophyte- and sporophyte-specific genes in the highly outcrossing plant Capsella grandiflora. We found that pollen-exclusive genes had a larger fraction of sites under strong purifying selection, a greater proportion of adaptive substitutions, and faster protein evolution compared with seedling-exclusive genes. In contrast, sperm cell-exclusive genes had a smaller fraction of sites under strong purifying selection, a lower proportion of adaptive substitutions, and slower protein evolution compared with seedling-exclusive genes. Observations of strong selection acting on pollen-expressed genes are likely explained by sexual selection resulting from pollen competition aided by the haploid nature of that tissue. The relaxation of selection in sperm might be due to the reduced influence of intrasexual competition, but reduced gene expression may also be playing an important role.