Polygenic adaptation: From sweeps to subtle frequency shifts

Polygenic dynamics underlying the response of quantitative traits to directional selection

We study the response of a quantitative trait to exponential directional selection in a finite haploid population, both at the genetic and the phenotypic level. We assume an infinite sites model, in which the number of new mutations per generation in the population follows a Poisson distribution (with mean Θ) and each mutation occurs at a new, previously monomorphic site. Mutation effects are beneficial and drawn from a distribution. Sites are unlinked and contribute additively to the trait. Assuming that selection is stronger than random genetic drift, we model the initial phase of the dynamics by a supercritical Galton-Watson process. This enables us to obtain time-dependent results. We show that the copy-number distribution of the mutant in generation n, conditioned on non-extinction until n, is described accurately by the deterministic increase from an initial distribution with mean 1. This distribution is related to the absolutely continuous part W+ of the random variable, typically denoted W, that characterizes the stochasticity accumulating during the mutant's sweep. A suitable transformation yields the approximate dynamics of the mutant frequency distribution in a Wright-Fisher population of size N. Our expression provides a very accurate approximation except when mutant frequencies are close to 1. On this basis, we derive explicitly the (approximate) time dependence of the expected mean and variance of the trait and of the expected number of segregating sites. Unexpectedly, we obtain highly accurate approximations for all times, even for the quasi-stationary phase when the expected per-generation response and the trait variance have equilibrated. The latter refine classical results. In addition, we find that Θ is the main determinant of the pattern of adaptation at the genetic level, i.e., whether the initial allele-frequency dynamics are best described by sweep-like patterns at few loci or small allele-frequency shifts at many. The number of segregating sites is an appropriate indicator for these patterns. The selection strength determines primarily the rate of adaptation. The accuracy of our results is tested by comprehensive simulations in a Wright-Fisher framework. We argue that our results apply to more complex forms of directional selection.

Integrating very high resolution environmental proxies in genotype-environment association studies

Landscape genomic analyses associating genetic variation with environmental variables are powerful tools for studying molecular signatures of species' local adaptation and for detecting candidate genes under selection. The development of landscape genomics over the past decade has been spurred by improvements in resolutions of genomic and environmental datasets, allegedly increasing the power to identify putative genes underlying local adaptation in non-model organisms. Although these associations have been successfully applied to numerous species across a diverse array of taxa, the spatial scale of environmental predictor variables has been largely overlooked, potentially limiting conclusions to be reached with these methods. To address this knowledge gap, we systematically evaluated performances of genotype-environment association (GEA) models using predictor variables at multiple spatial resolutions. Specifically, we used multivariate redundancy analyses to associate whole-genome sequence data from the plant Arabis alpina L. collected across four neighboring valleys in the western Swiss Alps, with very high-resolution topographic variables derived from digital elevation models of grain sizes between 0.5 m and 16 m. These comparisons highlight the sensitivity of landscape genomic models to spatial resolution, where the optimal grain sizes were specific to variable type, terrain characteristics, and study extent. To assist in selecting variables at appropriate spatial resolutions, we demonstrate a practical approach to produce, select, and integrate multiscale variables into GEA models. After generalizing fine-grained variables to multiple spatial resolutions, a forward selection procedure is applied to retain only the most relevant variables for a particular context. Depending on the spatial resolution, the relevance for topographic variables in GEA studies calls for integrating multiple spatial scales into landscape genomic models. By carefully considering spatial resolutions, candidate genes under selection by a more realistic range of pressures can be detected for downstream analyses, with important applied implications for experimental research and conservation management of natural populations.

Polygenic selection to a changing optimum under self-fertilisation

Many traits are polygenic, affected by multiple genetic variants throughout the genome. Selection acting on these traits involves co-ordinated allele-frequency changes at these underlying variants, and this process has been extensively studied in random-mating populations. Yet many species self-fertilise to some degree, which incurs changes to genetic diversity, recombination and genome segregation. These factors cumulatively influence how polygenic selection is realised in nature. Here, we use analytical modelling and stochastic simulations to investigate to what extent self-fertilisation affects polygenic adaptation to a new environment. Our analytical solutions show that while selfing can increase adaptation to an optimum, it incurs linkage disequilibrium that can slow down the initial spread of favoured mutations due to selection interference, and favours the fixation of alleles with opposing trait effects. Simulations show that while selection interference is present, high levels of selfing (at least 90%) aids adaptation to a new optimum, showing a higher long-term fitness. If mutations are pleiotropic then only a few major-effect variants fix along with many neutral hitchhikers, with a transient increase in linkage disequilibrium. These results show potential advantages to self-fertilisation when adapting to a new environment, and how the mating system affects the genetic composition of polygenic selection.

A Path Integral Approach for Allele Frequency Dynamics Under Polygenic Selection

Many phenotypic traits have a polygenic genetic basis, making it challenging to learn their genetic architectures and predict individual phenotypes. One promising avenue to resolve the genetic basis of complex traits is through evolve-and-resequence experiments, in which laboratory populations are exposed to some selective pressure and trait-contributing loci are identified by extreme frequency changes over the course of the experiment. However, small laboratory populations will experience substantial random genetic drift, and it is difficult to determine whether selection played a roll in a given allele frequency change. Predicting how much allele frequencies change under drift and selection had remained an open problem well into the 21st century, even those contributing to simple, monogenic traits. Recently, there have been efforts to apply the path integral, a method borrowed from physics, to solve this problem. So far, this approach has been limited to genic selection, and is therefore inadequate to capture the complexity of quantitative, highly polygenic traits that are commonly studied. Here we extend one of these path integral methods, the perturbation approximation, to selection scenarios that are of interest to quantitative genetics. In particular, we derive analytic expressions for the transition probability (i.e., the probability that an allele will change in frequency from x , to y in time t ) of an allele contributing to a trait subject to stabilizing selection, as well as that of an allele contributing to a trait rapidly adapting to a new phenotypic optimum. We use these expressions to characterize the use of allele frequency change to test for selection, as well as explore optimal design choices for evolve-and-resequence experiments to uncover the genetic architecture of polygenic traits under selection.

Predicting species invasiveness with genomic data: Is genomic offset related to establishment probability?

Predicting the risk of establishment and spread of populations outside their native range represents a major challenge in evolutionary biology. Various methods have recently been developed to estimate population (mal)adaptation to a new environment with genomic data via so-called Genomic Offset (GO) statistics. These approaches are particularly promising for studying invasive species but have still rarely been used in this context. Here, we evaluated the relationship between GO and the establishment probability of a population in a new environment using both in silico and empirical data. First, we designed invasion simulations to evaluate the ability to predict establishment probability of two GO computation methods (Geometric GO and Gradient Forest) under several conditions. Additionally, we aimed to evaluate the interpretability of absolute Geometric GO values, which theoretically represent the adaptive genetic distance between populations from distinct environments. Second, utilizing public empirical data from the crop pest species Bactrocera tryoni, a fruit fly native from Northern Australia, we computed GO between "source" populations and a diverse range of locations within invaded areas. This practical application of GO within the context of a biological invasion underscores its potential in providing insights and guiding recommendations for future invasion risk assessment. Overall, our results suggest that GO statistics represent good predictors of the establishment probability and may thus inform invasion risk, although the influence of several factors on prediction performance (e.g., propagule pressure or admixture) will need further investigation.

Rapid evolutionary change, constraints and the maintenance of polymorphism in natural populations of Drosophila melanogaster

Allele frequencies can shift rapidly within natural populations. Under certain conditions, repeated rapid allele frequency shifts can lead to the long-term maintenance of polymorphism. In recent years, studies of the model insect Drosophila melanogaster have suggested that this phenomenon is more common than previously believed and is often driven by some form of balancing selection, such as temporally fluctuating or sexually antagonistic selection. Here we discuss some of the general insights into rapid evolutionary change revealed by large-scale population genomic studies, as well as the functional and mechanistic causes of rapid adaptation uncovered by single-gene studies. As an example of the latter, we consider a regulatory polymorphism of the D. melanogaster fezzik gene. Polymorphism at this site has been maintained at intermediate frequency over an extended period of time. Regular observations from a single population over a period of 7 years revealed significant differences in the frequency of the derived allele and its variance across collections between the sexes. These patterns are highly unlikely to arise from genetic drift alone or from the action of sexually antagonistic or temporally fluctuating selection individually. Instead, the joint action of sexually antagonistic and temporally fluctuating selection can best explain the observed rapid and repeated allele frequency shifts. Temporal studies such as those reviewed here further our understanding of how rapid changes in selection can lead to the long-term maintenance of polymorphism as well as improve our knowledge of the forces driving and limiting adaptation in nature.

Common signatures of selection reveal target loci for breeding across soybean populations

Understanding the underlying genetic bases of yield-related selection and distinguishing these changes from genetic drift are critical for both improved understanding and future success of plant breeding. Soybean [Glycine max (L.) Merr.] is a key species for world food security, yet knowledge of the mechanism of selective breeding in soybean, such as the century-long program of artificial selection in U.S. soybean germplasm, is currently limited to certain genes and loci. Here, we identify genome-wide signatures of selection in separate populations of soybean subjected to artificial selection for increased yield by multiple breeding programs in the United States. We compared the alternative soybean breeding population (AGP) created by USDA-ARS to the conventional public soybean lines (CGP) developed at three different stages of breeding (ancestral, intermediate, and elite) to identify shared signatures of selection and differentiate these from drift. The results showed a strong selection for specific haplotypes identified by single site frequency and haplotype homozygosity methods. A set of common selection signatures was identified in both AGP and CGP that supports the hypothesis that separate breeding programs within similar environments coalesce on the fixation of the same key haplotypes. Signatures unique to each breeding program were observed. These results raise the possibility that selection analysis can allow the identification of favorable alleles to enhance directed breeding approaches.

Repeatability of adaptation in sunflowers reveals that genomic regions harbouring inversions also drive adaptation in species lacking an inversion

Local adaptation commonly involves alleles of large effect, which experience fitness advantages when in positive linkage disequilibrium (LD). Because segregating inversions suppress recombination and facilitate the maintenance of LD between locally adapted loci, they are also commonly found to be associated with adaptive divergence. However, it is unclear what fraction of an adaptive response can be attributed to inversions and alleles of large effect, and whether the loci within an inversion could still drive adaptation in the absence of its recombination-suppressing effect. Here, we use genome-wide association studies to explore patterns of local adaptation in three species of sunflower: Helianthus annuus, Helianthus argophyllus, and Helianthus petiolaris, which each harbour a large number of species-specific inversions. We find evidence of significant genome-wide repeatability in signatures of association to phenotypes and environments, which are particularly enriched within regions of the genome harbouring an inversion in one species. This shows that while inversions may facilitate local adaptation, at least some of the loci can still harbour mutations that make substantial contributions without the benefit of recombination suppression in species lacking a segregating inversion. While a large number of genomic regions show evidence of repeated adaptation, most of the strongest signatures of association still tend to be species-specific, indicating substantial genotypic redundancy for local adaptation in these species.

Unraveling the Molecular Basis of Stabilizing Selection by Experimental Evolution

Stabilizing selection provides a challenge to molecular population genetics. Although stabilizing selection is ubiquitous, its genomic signature is difficult to distinguish from demographic signals. Experimental evolution provides a promising approach to characterize genomic regions exposed to stabilizing selection. A recent experimental evolution study of Aedes aegypti populations evolving either with or without sexual selection found a pattern of genetic differentiation suggestive of relaxed stabilizing selection. I argue that this study could not have detected the signal of relaxed stabilizing selection. I highlight why incorrect statistical methods resulted in a high number of false positive candidate single nucleotide polymorphism (SNPs) and discuss the fallacy of functional validation of candidate SNPs for polygenic traits by RNA-mediated knockdown.

Genome architecture underlying salinity adaptation in the invasive copepod Eurytemora affinis species complex: A review

With climate change, habitat salinity is shifting rapidly throughout the globe. In addition, many destructive freshwater invaders are recent immigrants from saline habitats. Recently, populations of the copepod Eurytemora affinis species complex have invaded freshwater habitats multiple times independently from saline estuaries on three continents. This review discusses features of this species complex that could enhance their evolutionary potential during rapid environmental change. Remarkably, across independent freshwater invasions, natural selection has repeatedly favored the same alleles far more than expected. This high degree of parallelism is surprising, given the expectation of nonparallel evolution for polygenic adaptation. Factors such as population structure and the genome architecture underlying critical traits under selection might help drive rapid adaptation and parallel evolution. Given the preponderance of saline-to-freshwater invasions and climate-induced salinity change, the principles found here could provide invaluable insights into mechanisms operating in other systems and the potential for adaptation in a changing planet.

A theory of oligogenic adaptation of a quantitative trait

Rapid phenotypic adaptation is widespread in nature, but the underlying genetic dynamics remain controversial. Whereas population genetics envisages sequential beneficial substitutions, quantitative genetics assumes a collective response through subtle shifts in allele frequencies. This dichotomy of a monogenic and a highly polygenic view of adaptation raises the question of a middle ground, as well as the factors controlling the transition. Here, we consider an additive quantitative trait with equal locus effects under Gaussian stabilizing selection that adapts to a new trait optimum after an environmental change. We present an analytical framework based on Yule branching processes to describe how phenotypic adaptation is achieved by collective changes in allele frequencies at the underlying loci. In particular, we derive an approximation for the joint allele-frequency distribution conditioned on the trait mean as a comprehensive descriptor of the adaptive architecture. Depending on the model parameters, this architecture reproduces the well-known patterns of sequential, monogenic sweeps, or of subtle, polygenic frequency shifts. Between these endpoints, we observe oligogenic architecture types that exhibit characteristic patterns of partial sweeps. We find that a single compound parameter, the population-scaled background mutation rate Θbg, is the most important predictor of the type of adaptation, while selection strength, the number of loci in the genetic basis, and linkage only play a minor role.

Analysis of polygenic selection in purebred and crossbred pig genomes using generation proxy selection mapping

BACKGROUND

Artificial selection on quantitative traits using breeding values and selection indices in commercial livestock breeding populations causes changes in allele frequency over time at hundreds or thousands of causal loci and the surrounding genomic regions. In population genetics, this type of selection is called polygenic selection. Researchers and managers of pig breeding programs are motivated to understand the genetic basis of phenotypic diversity across genetic lines, breeds, and populations using selection mapping analyses. Here, we applied generation proxy selection mapping (GPSM), a genome-wide association analysis of single nucleotide polymorphism (SNP) genotypes (38,294-46,458 markers) of birth date, in four pig populations (15,457, 15,772, 16,595 and 8447 pigs per population) to identify loci responding to artificial selection over a period of five to ten years. Gene-drop simulation analyses were conducted to provide context for the GPSM results. Selected loci within and across each population of pigs were compared in the context of swine breeding objectives.

RESULTS

The GPSM identified 49 to 854 loci as under selection (Q-values less than 0.10) across 15 subsets of pigs based on combinations of populations. The number of significant associations increased when data were pooled across populations. In addition, several significant associations were identified in more than one population. These results indicate concurrent selection objectives, similar genetic architectures, and shared causal variants responding to selection across these pig populations. Negligible error rates (less than or equal to 0.02%) of false-positive associations were found when testing GPSM on gene-drop simulated genotypes, suggesting that GPSM distinguishes selection from random genetic drift in actual pig populations.

CONCLUSIONS

This work confirms the efficacy and the negligible error rates of the GPSM method in detecting selected loci in commercial pig populations. Our results suggest shared selection objectives and genetic architectures across swine populations. The identified polygenic selection highlights loci that are important to swine production.

The final frontier: ecological and evolutionary dynamics of a global parasite invasion

Studying rapid biological changes accompanying the introduction of alien organisms into native ecosystems can provide insights into fundamental ecological and evolutionary theory. While powerful, this quasi-experimental approach is difficult to implement because the timing of invasions and their consequences are hard to predict, meaning that baseline pre-invasion data are often missing. Exceptionally, the eventual arrival of Varroa destructor (hereafter Varroa) in Australia has been predicted for decades. Varroa is a major driver of honeybee declines worldwide, particularly as vectors of diverse RNA viruses. The detection of Varroa in 2022 at over a hundred sites poses a risk of further spread across the continent. At the same time, careful study of Varroa's spread, if it does become established, can provide a wealth of information that can fill knowledge gaps about its effects worldwide. This includes how Varroa affects honeybee populations and pollination. Even more generally, Varroa invasion can serve as a model for evolution, virology and ecological interactions between the parasite, the host and other organisms.

Polygenic routes lead to parallel altitudinal adaptation in Heliosperma pusillum (Caryophyllaceae)

Understanding how organisms adapt to the environment is a major goal of modern biology. Parallel evolution-the independent evolution of similar phenotypes in different populations-provides a powerful framework to investigate the evolutionary potential of populations, the constraints of evolution, its repeatability and therefore its predictability. Here, we quantified the degree of gene expression and functional parallelism across replicated ecotype formation in Heliosperma pusillum (Caryophyllaceae), and gained insights into the architecture of adaptive traits. Population structure analyses and demographic modelling support a previously formulated hypothesis of parallel polytopic divergence of montane and alpine ecotypes. We detect a large proportion of differentially expressed genes (DEGs) underlying divergence within each replicate ecotype pair, with a strikingly low number of shared DEGs across pairs. Functional enrichment of DEGs reveals that the traits affected by significant expression divergence are largely consistent across ecotype pairs, in strong contrast to the nonshared genetic basis. The remarkable redundancy of differential gene expression indicates a polygenic architecture for the diverged adaptive traits. We conclude that polygenic traits appear key to opening multiple routes for adaptation, widening the adaptive potential of organisms.

Nonparallel genome changes within subpopulations over time contributed to genetic diversity within the US Holstein population

Maintaining genetic variation in a population is important for long-term genetic gain. The existence of subpopulations within a breed helps maintain genetic variation and diversity. The 20,990 genotyped animals, representing the breeding animals in the year 2014, were identified as the sires of animals born after 2010 with at least 25 progenies, and females measured for type traits within the last 2 yr of data. K-means clustering with 5 clusters (C1, C2, C3, C4, and C5) was applied to the genomic relationship matrix based on 58,990 SNP markers to stratify the selected candidates into subpopulations. The general higher inbreeding resulting from within-cluster mating than across-cluster mating suggests the successful stratification into genetically different groups. The largest cluster (C4) contained animals that were less related to each animal within and across clusters. The average fixation index was 0.03, indicating that the populations were differentiated, and allele differences across the subpopulations were not due to drift alone. Starting with the selected candidates within each cluster, a family unit was identified by tracing back through the pedigree, identifying the genotyped ancestors, and assigning them to a pseudogeneration. Each of the 5 families (F1, F2, F3, F4, and F5) was traced back for 10 generations, allowing for changes in frequency of individual SNPs over time to be observed, which we call allele frequencies change. Alternative procedures were used to identify SNPs changing in a parallel or nonparallel way across families. For example, markers that have changed the most in the whole population, markers that have changed differently across families, and genes previously identified as those that have changed in allele frequency. The genomic trajectory taken by each family involves selective sweeps, polygenic changes, hitchhiking, and epistasis. The replicate frequency spectrum was used to measure the similarity of change across families and showed that populations have changed differently. The proportion of markers that reversed direction in allele frequency change varied from 0.00 to 0.02 if the rate of change was greater than 0.02 per generation, or from 0.14 to 0.24 if the rate of change was greater than 0.005 per generation within each family. Cluster-specific SNP effects for stature were estimated using only females and applied to obtain indirect genomic predictions for males. Reranking occurs depending on SNP effects used. Additive genetic correlations between clusters show possible differences in populations. Further research is required to determine how this knowledge can be applied to maintain diversity and optimize selection decisions in the future.

Long-distance migration is a major factor driving local adaptation at continental scale in Coho salmon

Inferring the genomic basis of local adaptation is a long-standing goal of evolutionary biology. Beyond its fundamental evolutionary implications, such knowledge can guide conservation decisions for populations of conservation and management concern. Here, we investigated the genomic basis of local adaptation in the Coho salmon (Oncorhynchus kisutch) across its entire North American range. We hypothesized that extensive spatial variation in environmental conditions and the species' homing behaviour may promote the establishment of local adaptation. We genotyped 7829 individuals representing 217 sampling locations at more than 100,000 high-quality RADseq loci to investigate how recombination might affect the detection of loci putatively under selection and took advantage of the precise description of the demographic history of the species from our previous work to draw accurate population genomic inferences about local adaptation. The results indicated that genetic differentiation scans and genetic-environment association analyses were both significantly affected by variation in recombination rate as low recombination regions displayed an increased number of outliers. By taking these confounding factors into consideration, we revealed that migration distance was the primary selective factor driving local adaptation and partial parallel divergence among distant populations. Moreover, we identified several candidate single nucleotide polymorphisms associated with long-distance migration and altitude including a gene known to be involved in adaptation to altitude in other species. The evolutionary implications of our findings are discussed along with conservation applications.

Polygenic adaptation dynamics in large, finite populations

Although many phenotypic traits are determined by a large number of genetic variants, how a polygenic trait adapts in response to a change in the environment is not completely understood. In the framework of diffusion theory, we study the steady state and the adaptation dynamics of a large but finite population evolving under stabilizing selection and symmetric mutations when selection and mutation are moderately large. We find that in the stationary state, the allele frequency distribution at a locus is unimodal if its effect size is below a threshold effect and bimodal otherwise; these results are the stochastic analog of the deterministic ones where the stable allele frequency becomes bistable when the effect size exceeds a threshold. It is known that following a sudden shift in the phenotypic optimum, in an infinitely large population, selective sweeps at a large-effect locus are prevented and adaptation proceeds exclusively via subtle changes in the allele frequency; in contrast, we find that the chance of sweep is substantially enhanced in large, finite populations and the allele frequency at a large-effect locus can reach a high frequency at short times even for small shifts in the phenotypic optimum.

Genomic vulnerability to climate change in Quercus acutissima, a dominant tree species in East Asian deciduous forests

Understanding the evolutionary processes that shape the landscape of genetic variation and influence the response of species to future climate change is critical for biodiversity conservation. Here, we sampled 27 populations across the distribution range of a dominant forest tree, Quercus acutissima, in East Asia, and applied genome-wide analyses to track the evolutionary history and predict the fate of populations under future climate. We found two genetic groups (East and West) in Q. acutissima that diverged during Pliocene. We also found a heterogeneous landscape of genomic variation in this species, which may have been shaped by population demography and linked selections. Using genotype-environment association analyses, we identified climate-associated SNPs in a diverse set of genes and functional categories, indicating a model of polygenic adaptation in Q. acutissima. We further estimated three genetic offset metrics to quantify genomic vulnerability of this species to climate change due to the complex interplay between local adaptation and migration. We found that marginal populations are under higher risk of local extinction because of future climate change, and may not be able to track suitable habitats to maintain the gene-environment relationships observed under the current climate. We also detected higher reverse genetic offsets in northern China, indicating that genetic variation currently present in the whole range of Q. acutissima may not adapt to future climate conditions in this area. Overall, this study illustrates how evolutionary processes have shaped the landscape of genomic variation, and provides a comprehensive genome-wide view of climate maladaptation in Q. acutissima.

Common microgeographical selection patterns revealed in four European conifers

Microgeographical adaptation occurs when the effects of directional selection persist despite gene flow. Traits and genetic loci under selection can then show adaptive divergence, against the backdrop of little differentiation at other traits or loci. How common such events are and how strong the selection is that underlies them remain open questions. Here, we discovered and analysed microgeographical patterns of genomic divergence in four European and Mediterranean conifers with widely differing life-history traits and ecological requirements (Abies alba MIll., Cedrus atlantica [Endl.] Manetti, Pinus halepensis Mill. and Pinus pinaster Aiton) by screening pairs from geographically close forest stands sampled along steep ecological gradients. We inferred patterns of genomic divergence by applying a combination of divergence outlier detection methods, demographic modelling, Approximate Bayesian Computation inferences and genomic annotation to genomic data. Surprisingly for such small geographical scales, we showed that selection is strong in all species but generally affects different loci in each. A clear signature of selection was systematically detected on a fraction of the genome, of the order of 0.1%-1% of the loci depending on the species. The novel modelling method we designed for estimating selection coefficients showed that the microgeographical selection coefficient scaled by population size (Ns) was 2-30. Our results convincingly suggest that selection maintains within-population diversity at microgeographical scales in spatially heterogeneous environments. Such genetic diversity is likely to be a major reservoir of adaptive potential, helping populations to adapt under fluctuating environmental conditions.

Museum Genomics of an Agricultural Super-Pest, the Colorado Potato Beetle, Leptinotarsa decemlineata (Chrysomelidae), Provides Evidence of Adaptation from Standing Variation

Despite extensive research on agricultural pests, our knowledge about their evolutionary history is often limited. A mechanistic understanding of the demographic changes and modes of adaptation remains an important goal, as it improves our understanding of organismal responses to environmental change and our ability to sustainably manage pest populations. Emerging genomic datasets now allow for characterization of demographic and adaptive processes, but face limits when they are drawn from contemporary samples, especially in the context of strong demographic change, repeated selection, or adaptation involving modest shifts in allele frequency at many loci. Temporal sampling, however, can improve our ability to reconstruct evolutionary events. Here, we leverage museum samples to examine whether population genomic diversity and structure has changed over time, and to identify genomic regions that appear to be under selection. We focus on the Colorado potato beetle (CPB), Leptinotarsa decemlineata (Say 1824; Coleoptera: Chrysomelidae), which is widely regarded as a super-pest due to its rapid, and repeated, evolution to insecticides. By combining whole genome resequencing data from 78 museum samples with modern sampling, we demonstrate that CPB expanded rapidly in the 19th century, leading to a reduction in diversity and limited genetic structure from the Midwest to Northeast United States. Temporal genome scans provide extensive evidence for selection acting in resistant field populations in Wisconsin and New York, including numerous known insecticide resistance genes. We also validate these results by showing that known selective sweeps in modern populations are identified by our genome scan. Perhaps most importantly, temporal analysis indicates selection on standing genetic variation, as we find evidence for parallel evolution in the two geographical regions. Parallel evolution involves a range of phenotypic traits not previously identified as under selection in CPB, such as reproductive and morphological functional pathways that might be important for adaptation to agricultural habitats.

Admixture has obscured signals of historical hard sweeps in humans

The role of natural selection in shaping biological diversity is an area of intense interest in modern biology. To date, studies of positive selection have primarily relied on genomic datasets from contemporary populations, which are susceptible to confounding factors associated with complex and often unknown aspects of population history. In particular, admixture between diverged populations can distort or hide prior selection events in modern genomes, though this process is not explicitly accounted for in most selection studies despite its apparent ubiquity in humans and other species. Through analyses of ancient and modern human genomes, we show that previously reported Holocene-era admixture has masked more than 50 historic hard sweeps in modern European genomes. Our results imply that this canonical mode of selection has probably been underappreciated in the evolutionary history of humans and suggest that our current understanding of the tempo and mode of selection in natural populations may be inaccurate.

Genomic insights into local adaptation and future climate-induced vulnerability of a keystone forest tree in East Asia

Rapid global climate change is posing a substantial threat to biodiversity. The assessment of population vulnerability and adaptive capacity under climate change is crucial for informing conservation and mitigation strategies. Here we generate a chromosome-scale genome assembly and re-sequence genomes of 230 individuals collected from 24 populations for Populus koreana, a pioneer and keystone tree species in temperate forests of East Asia. We integrate population genomics and environmental variables to reveal a set of climate-associated single-nucleotide polymorphisms, insertion/deletions and structural variations, especially numerous adaptive non-coding variants distributed across the genome. We incorporate these variants into an environmental modeling scheme to predict a highly spatiotemporal shift of this species in response to future climate change. We further identify the most vulnerable populations that need conservation priority and many candidate genes and variants that may be useful for forest tree breeding with special aims. Our findings highlight the importance of integrating genomic and environmental data to predict adaptive capacity of a key forest to rapid climate change in the future.

A possible genomic footprint of polygenic adaptation on population divergence in seed beetles?

Efforts to unravel the genomic basis of incipient speciation are hampered by a mismatch between our toolkit and our understanding of the ecology and genetics of adaptation. While the former is focused on detecting selective sweeps involving few independently acting or linked speciation genes, the latter states that divergence typically occurs in polygenic traits under stabilizing selection. Here, we ask whether a role of stabilizing selection on polygenic traits in population divergence may be unveiled by using a phenotypically informed integrative approach, based on genome‐wide variation segregating in divergent populations. We compare three divergent populations of seed beetles (Callosobruchus maculatus) where previous work has demonstrated a prominent role for stabilizing selection on, and population divergence in, key life history traits that reflect rate‐dependent metabolic processes. We derive and assess predictions regarding the expected pattern of covariation between genetic variation segregating within populations and genetic differentiation between populations. Population differentiation was considerable (mean F_ST = 0.23–0.26) and was primarily built by genes showing high selective constraints and an imbalance in inferred selection in different populations (positive Tajima's D_NS in one and negative in one), and this set of genes was enriched with genes with a metabolic function. Repeatability of relative population differentiation was low at the level of individual genes but higher at the level of broad functional classes, again spotlighting metabolic genes. Absolute differentiation (d_XY) showed a very different general pattern at this scale of divergence, more consistent with an important role for genetic drift. Although our exploration is consistent with stabilizing selection on polygenic metabolic phenotypes as an important engine of genome‐wide relative population divergence and incipient speciation in our study system, we note that it is exceedingly difficult to firmly exclude other scenarios.

Genome-wide selection signatures reveal widespread synergistic effects of two different stressors in Drosophila melanogaster

Experimental evolution combined with whole-genome sequencing (evolve and resequence (E&R)) is a powerful approach to study the adaptive architecture of selected traits. Nevertheless, so far the focus has been on the selective response triggered by a single stressor. Building on the highly parallel selection response of founder populations with reduced variation, we evaluated how the presence of a second stressor affects the genomic selection response. After 20 generations of adaptation to laboratory conditions at either 18°C or 29°C, strong genome-wide selection signatures were observed. Only 38% of the selection signatures can be attributed to laboratory adaptation (no difference between temperature regimes). The remaining selection responses are either caused by temperature-specific effects, or reflect the joint effects of temperature and laboratory adaptation (same direction, but the magnitude differs between temperatures). The allele frequency changes resulting from the combined effects of temperature and laboratory adaptation were more extreme in the hot environment for 83% of the affected genomic regions-indicating widespread synergistic effects of the two stressors. We conclude that E&R with reduced genetic variation is a powerful approach to study genome-wide fitness consequences driven by the combined effects of multiple environmental factors.

Genomic basis and phenotypic manifestation of (non-)parallel serpentine adaptation in Arabidopsis arenosa

Parallel evolution is common in nature and provides one of the most compelling examples of rapid environmental adaptation. In contrast to the recent burst of studies addressing genomic basis of parallel evolution, integrative studies linking genomic and phenotypic parallelism are scarce. Edaphic islands of toxic serpentine soils provide ideal systems for studying rapid parallel adaptation in plants, imposing strong, spatially replicated selection on recently diverged populations. We leveraged threefold independent serpentine adaptation of Arabidopsis arenosa and combined reciprocal transplants, ion uptake phenotyping, and available genome-wide polymorphisms to test if parallelism is manifested to a similar extent at both genomic and phenotypic levels. We found pervasive phenotypic parallelism in functional traits yet with varying magnitude of fitness differences that was congruent with neutral genetic differentiation between populations. Limited costs of serpentine adaptation suggest absence of soil-driven trade-offs. On the other hand, the genomic parallelism at the gene level was significant, although relatively minor. Therefore, the similarly modified phenotypes, for example, of ion uptake arose possibly by selection on different loci in similar functional pathways. In summary, we bring evidence for the important role of genetic redundancy in rapid adaptation involving traits with polygenic architecture.

Experimental evolution reveals the synergistic genomic mechanisms of adaptation to ocean warming and acidification in a marine copepod

Metazoan adaptation to global change relies on selection of standing genetic variation. Determining the extent to which this variation exists in natural populations, particularly for responses to simultaneous stressors, is essential to make accurate predictions for persistence in future conditions. Here, we identified the genetic variation enabling the copepod Acartia tonsa to adapt to experimental ocean warming, acidification, and combined ocean warming and acidification (OWA) over 25 generations of continual selection. Replicate populations showed a consistent polygenic response to each condition, targeting an array of adaptive mechanisms including cellular homeostasis, development, and stress response. We used a genome-wide covariance approach to partition the allelic changes into three categories: selection, drift and replicate-specific selection, and laboratory adaptation responses. The majority of allele frequency change in warming (57%) and OWA (63%) was driven by shared selection pressures across replicates, but this effect was weaker under acidification alone (20%). OWA and warming shared 37% of their response to selection but OWA and acidification shared just 1%, indicating that warming is the dominant driver of selection in OWA. Despite the dominance of warming, the interaction with acidification was still critical as the OWA selection response was highly synergistic with 47% of the allelic selection response unique from either individual treatment. These results disentangle how genomic targets of selection differ between single and multiple stressors and demonstrate the complexity that nonadditive multiple stressors will contribute to predictions of adaptation to complex environmental shifts caused by global change.

1,000 ancient genomes uncover 10,000 years of natural selection in Europe

Ancient DNA has revolutionized our understanding of human population history. However, its potential to examine how rapid cultural evolution to new lifestyles may have driven biological adaptation has not been met, largely due to limited sample sizes. We assembled genome-wide data from 1,291 individuals from Europe over 10,000 years, providing a dataset that is large enough to resolve the timing of selection into the Neolithic, Bronze Age, and Historical periods. We identified 25 genetic loci with rapid changes in frequency during these periods, a majority of which were previously undetected. Signals specific to the Neolithic transition are associated with body weight, diet, and lipid metabolism-related phenotypes. They also include immune phenotypes, most notably a locus that confers immunity to Salmonella infection at a time when ancient Salmonella genomes have been shown to adapt to human hosts, thus providing a possible example of human-pathogen co-evolution. In the Bronze Age, selection signals are enriched near genes involved in pigmentation and immune-related traits, including at a key human protein interactor of SARS-CoV-2. Only in the Historical period do the selection candidates we detect largely mirror previously-reported signals, highlighting how the statistical power of previous studies was limited to the last few millennia. The Historical period also has multiple signals associated with vitamin D binding, providing evidence that lactase persistence may have been part of an oligogenic adaptation for efficient calcium uptake and challenging the theory that its adaptive value lies only in facilitating caloric supplementation during times of scarcity. Finally, we detect selection on complex traits in all three periods, including selection favoring variants that reduce body weight in the Neolithic. In the Historical period, we detect selection favoring variants that increase risk for cardiovascular disease plausibly reflecting selection for a more active inflammatory response that would have been adaptive in the face of increased infectious disease exposure. Our results provide an evolutionary rationale for the high prevalence of these deadly diseases in modern societies today and highlight the unique power of ancient DNA in elucidating biological change that accompanied the profound cultural transformations of recent human history.

Challenges and potential solutions for studying the genetic and phenotypic architecture of adaptation in microbes

All organisms are defined by the makeup of their DNA. Over billions of years, the structure and information contained in that DNA, often referred to as genetic architecture, have been honed by a multitude of evolutionary processes. Mutations that cause genetic elements to change in a way that results in beneficial phenotypic change are more likely to survive and propagate through the population in a process known as adaptation. Recent work reveals that the genetic targets of adaptation are varied and can change with genetic background. Further, seemingly similar adaptive mutations, even within the same gene, can have diverse and unpredictable effects on phenotype. These challenges represent major obstacles in predicting adaptation and evolution. In this review, we cover these concepts in detail and identify three emerging synergistic solutions: higher-throughput evolution experiments combined with updated genotype-phenotype mapping strategies and physiological models. Our review largely focuses on recent literature in yeast, and the field seems to be on the cusp of a new era with regard to studying the predictability of evolution.

The "New Synthesis"

When Mendel’s work was rediscovered in 1900, and extended to establish classical genetics, it was initially seen in opposition to Darwin’s theory of evolution by natural selection on continuous variation, as represented by the biometric research program that was the foundation of quantitative genetics. As Fisher, Haldane, and Wright established a century ago, Mendelian inheritance is exactly what is needed for natural selection to work efficiently. Yet, the synthesis remains unfinished. We do not understand why sexual reproduction and a fair meiosis predominate in eukaryotes, or how far these are responsible for their diversity and complexity. Moreover, although quantitative geneticists have long known that adaptive variation is highly polygenic, and that this is essential for efficient selection, this is only now becoming appreciated by molecular biologists—and we still do not have a good framework for understanding polygenic variation or diffuse function.

Genome-wide signatures of synergistic epistasis during parallel adaptation in a Baltic Sea copepod

The role of epistasis in driving adaptation has remained an unresolved problem dating back to the Evolutionary Synthesis. In particular, whether epistatic interactions among genes could promote parallel evolution remains unexplored. To address this problem, we employ an Evolve and Resequence (E&R) experiment, using the copepod Eurytemora affinis, to elucidate the evolutionary genomic response to rapid salinity decline. Rapid declines in coastal salinity at high latitudes are a predicted consequence of global climate change. Based on time-resolved pooled whole-genome sequencing, we uncover a remarkably parallel, polygenic response across ten replicate selection lines, with 79.4% of selected alleles shared between lines by the tenth generation of natural selection. Using extensive computer simulations of our experiment conditions, we find that this polygenic parallelism is consistent with positive synergistic epistasis among alleles, far more so than other mechanisms tested. Our study provides experimental and theoretical support for a novel mechanism promoting repeatable polygenic adaptation, a phenomenon that may be common for selection on complex physiological traits.

Using time-series whole-genome sequencing data from a laboratory evolution experiment, along with extensive computer simulations, the authors show that synergistic epistasis could drive rapid parallel freshwater adaptation in a saline copepod.

Inferring Signatures of Positive Selection in Whole-Genome Sequencing Data: An Overview of Haplotype-Based Methods

Signatures of positive selection in the genome are a characteristic mark of adaptation that can reveal an ongoing, recent, or ancient response to environmental change throughout the evolution of a population. New sources of food, climate conditions, and exposure to pathogens are only some of the possible sources of selective pressure, and the rise of advantageous genetic variants is a crucial determinant of survival and reproduction. In this context, the ability to detect these signatures of selection may pinpoint genetic variants that are responsible for a significant change in gene regulation, gene expression, or protein synthesis, structure, and function. This review focuses on statistical methods that take advantage of linkage disequilibrium and haplotype determination to reveal signatures of positive selection in whole-genome sequencing data, showing that they emerge from different descriptions of the same underlying event. Moreover, considerations are provided around the application of these statistics to different species, their suitability for ancient DNA, and the usefulness of discovering variants under selection for biomedicine and public health in an evolutionary medicine framework.

Negotiating mutualism: A locus for exploitation by rhizobia has a broad effect size distribution and context-dependent effects on legume hosts

In mutualisms, variation at genes determining partner fitness provides the raw material upon which coevolutionary selection acts, setting the dynamics and pace of coevolution. However, we know little about variation in the effects of genes that underlie symbiotic fitness in natural mutualist populations. In some species of legumes that form root nodule symbioses with nitrogen‐fixing rhizobial bacteria, hosts secrete nodule‐specific cysteine‐rich (NCR) peptides that cause rhizobia to differentiate in the nodule environment. However, rhizobia can cleave NCR peptides through the expression of genes like the plasmid‐borne Host range restriction peptidase (hrrP), whose product degrades specific NCR peptides. Although hrrP activity can confer host exploitation by depressing host fitness and enhancing symbiont fitness, the effects of hrrP on symbiosis phenotypes depend strongly on the genotypes of the interacting partners. However, the effects of hrrP have yet to be characterised in a natural population context, so its contribution to variation in wild mutualist populations is unknown. To understand the distribution of effects of hrrP in wild rhizobia, we measured mutualism phenotypes conferred by hrrP in 12 wild Ensifer medicae strains. To evaluate context dependency of hrrP effects, we compared hrrP effects across two Medicago polymorpha host genotypes and across two experimental years for five E. medicae strains. We show for the first time in a natural population context that hrrP has a wide distribution of effect sizes for many mutualism traits, ranging from strongly positive to strongly negative. Furthermore, we show that hrrP effect size varies across host genotypes and experiment years, suggesting that researchers should be cautious about extrapolating the role of genes in natural populations from controlled laboratory studies of single genetic variants.

Parallel reduction in flowering time from de novo mutations enable evolutionary rescue in colonizing lineages

Understanding how populations adapt to abrupt environmental change is necessary to predict responses to future challenges, but identifying specific adaptive variants, quantifying their responses to selection and reconstructing their detailed histories is challenging in natural populations. Here, we use Arabidopsis from the Cape Verde Islands as a model to investigate the mechanisms of adaptation after a sudden shift to a more arid climate. We find genome-wide evidence of adaptation after a multivariate change in selection pressures. In particular, time to flowering is reduced in parallel across islands, substantially increasing fitness. This change is mediated by convergent de novo loss of function of two core flowering time genes: FRI on one island and FLC on the other. Evolutionary reconstructions reveal a case where expansion of the new populations coincided with the emergence and proliferation of these variants, consistent with models of rapid adaptation and evolutionary rescue.

Detailing how populations adapted to environmental change is needed to predict future responses, but identifying adaptive variants and detailing their fitness effects is rare. Here, the authors show that parallel loss of FRI and FLC function reduces time to flowering and drives adaptation in a drought prone environment.

The evolution of larger size in high-altitude Drosophila melanogaster has a variable genetic architecture

Important uncertainties persist regarding the genetic architecture of adaptive trait evolution in natural populations, including the number of genetic variants involved, whether they are drawn from standing genetic variation, and whether directional selection drives them to complete fixation. Here, we take advantage of a unique natural population of Drosophila melanogaster from the Ethiopian highlands, which has evolved larger body size than any other known population of this species. We apply a bulk segregant quantitative trait locus mapping approach to 4 unique crosses between highland Ethiopian and lowland Zambian populations for both thorax length and wing length. Results indicated a persistently variable genetic basis for these evolved traits (with largely distinct sets of quantitative trait loci for each cross), and at least a moderately polygenic architecture with relatively strong effects present. We complemented these mapping experiments with population genetic analyses of quantitative trait locus regions and gene ontology enrichment analysis, generating strong hypotheses for specific genes and functional processes that may have contributed to these adaptive trait changes. Finally, we find that the genetic architectures indicated by our quantitative trait locus mapping results for size traits mirror those from similar experiments on other recently evolved traits in this species. Collectively, these studies suggest a recurring pattern of polygenic adaptation in this species, in which causative variants do not approach fixation and moderately strong effect loci are present.

Evolution in small steps and giant leaps

The first Editor of Evolution was Ernst Mayr. His foreword to the first issue of Evolution published in 1947 framed evolution as a "problem of interaction" that was just beginning to be studied in this broad context. First, I explore progress and prospects on understanding the subsidiary interactions identified by Mayr, including interactions between parts of organisms, between individuals and populations, between species, and between the organism and its abiotic environment. Mayr's overall "problem of interaction" framework is examined in the context of coevolution within and among levels of biological organization. This leads to a comparison in the relative roles of biotic versus abiotic agents of selection and fluctuating versus directional selection, followed by stabilizing selection in shaping the genomic architecture of adaptation. Oligogenic architectures may be typical for traits shaped more by fluctuating selection and biotic selection. Conversely, polygenic architectures may be typical for traits shaped more by directional followed by stabilizing selection and abiotic selection. The distribution of effect sizes and turnover dynamics of adaptive alleles in these scenarios deserves further study. Second, I review two case studies on the evolution of acquired toxicity in animals, one involving cardiac glycosides obtained from plants and one involving bacterial virulence factors horizontally transferred to animals. The approaches used in these studies and the results gained directly flow from Mayr's vision of an evolutionary biology that revolves around the "problem of interaction."

Polygenic adaptation and negative selection across traits, years and environments in a long-lived plant species (Pinus pinaster Ait., Pinaceae)

A decade of genetic association studies in multiple organisms suggests that most complex traits are polygenic, i.e., they have a genetic architecture determined by numerous loci each with small effect-size. Thus, determining the degree of polygenicity and its variation across traits, environments and time is crucial to understand the genetic basis of phenotypic variation. We applied multilocus approaches to estimate the degree of polygenicity of fitness-related traits in a long-lived plant (Pinus pinaster Ait., maritime pine) and to analyze this variation across environments and years. We evaluated five categories of fitness-related traits (survival, height, phenology, functional, and biotic-stress response traits) in a clonal common-garden network, planted in contrasted environments (over 12,500 trees). Most of the analyzed traits showed evidence of local adaptation based on Q_st -F_st comparisons. We further observed a remarkably stable degree of polygenicity, averaging 6% (range of 0-27%), across traits, environments and years. We detected evidence of negative selection, which could explain, at least partially, the high degree of polygenicity. Because polygenic adaptation can occur rapidly, our results suggest that current predictions on the capacity of natural forest tree populations to adapt to new environments should be revised, especially in the current context of climate change.

Genome-wide evolutionary response of European oaks during the Anthropocene

The pace of tree microevolution during Anthropocene warming is largely unknown. We used a retrospective approach to monitor genomic changes in oak trees since the Little Ice Age (LIA). Allelic frequency changes were assessed from whole-genome pooled sequences for four age-structured cohorts of sessile oak (Quercus petraea) dating back to 1680, in each of three different oak forests in France. The genetic covariances of allelic frequency changes increased between successive time periods, highlighting genome-wide effects of linked selection. We found imprints of parallel linked selection in the three forests during the late LIA, and a shift of selection during more recent time periods of the Anthropocene. The changes in allelic covariances within and between forests mirrored the documented changes in the occurrence of extreme events (droughts and frosts) over the last 300 years. The genomic regions with the highest covariances were enriched in genes involved in plant responses to pathogens and abiotic stresses (temperature and drought). These responses are consistent with the reported sequence of frost (or drought) and disease damage ultimately leading to the oak dieback after extreme events. They provide support for adaptive evolution of long-lived species during recent climatic changes. Although we acknowledge that other sources (e.g., gene flow, generation overlap) may have contributed to temporal covariances of allelic frequency changes, the consistent and correlated response across the three forests lends support to the existence of a systematic driving force such as natural selection.

Evolution of polygenic traits under global vs local adaptation

Observations about the number, frequency, effect size, and genomic distribution of alleles associated with complex traits must be interpreted in light of evolutionary process. These characteristics, which constitute a trait's genetic architecture, can dramatically affect evolutionary outcomes in applications from agriculture to medicine, and can provide a window into how evolution works. Here, I review theoretical predictions about the evolution of genetic architecture under spatially homogeneous, global adaptation as compared with spatially heterogeneous, local adaptation. Due to the tension between divergent selection and migration, local adaptation can favor "concentrated" genetic architectures that are enriched for alleles of larger effect, clustered in a smaller number of genomic regions, relative to expectations under global adaptation. However, the evolution of such architectures may be limited by many factors, including the genotypic redundancy of the trait, mutation rate, and temporal variability of environment. I review the circumstances in which predictions differ for global vs local adaptation and discuss where progress can be made in testing hypotheses using data from natural populations and lab experiments. As the field of comparative population genomics expands in scope, differences in architecture among traits and species will provide insights into how evolution works, and such differences must be interpreted in light of which kind of selection has been operating.

Genomic basis of fishing-associated selection varies with population density

Fisheries-associated selection is recognized as one of the strongest potential human drivers of contemporary evolution in natural populations. The results of this study show that while simulated commercial fishing techniques consistently remove fish with traits associated with growth, metabolism, and social behavior, the specific genes under fishing selection differ depending on the density of the targeted population. This finding suggests that different fish populations of varying sizes will respond differently to fishing selection at the genetic level. Furthermore, as a population is fished over time, the genes under selection may change as the population diminishes. This could have repercussions on population resilience. This study highlights the importance of selection but also environmental and density effects on harvested fish populations.

Fisheries induce one of the strongest anthropogenic selective pressures on natural populations, but the genetic effects of fishing remain unclear. Crucially, we lack knowledge of how capture-associated selection and its interaction with reductions in population density caused by fishing can potentially shift which genes are under selection. Using experimental fish reared at two densities and repeatedly harvested by simulated trawling, we show consistent phenotypic selection on growth, metabolism, and social behavior regardless of density. However, the specific genes under selection—mainly related to brain function and neurogenesis—varied with the population density. This interaction between direct fishing selection and density could fundamentally alter the genomic responses to harvest. The evolutionary consequences of fishing are therefore likely context dependent, possibly varying as exploited populations decline. These results highlight the need to consider environmental factors when predicting effects of human-induced selection and evolution.

Populations, Traits, and Their Spatial Structure in Humans

The spatial distribution of genetic variants is jointly determined by geography, past demographic processes, natural selection, and its interplay with environmental variation. A fraction of these genetic variants are "causal alleles" that affect the manifestation of a complex trait. The effect exerted by these causal alleles on complex traits can be independent or dependent on the environment. Understanding the evolutionary processes that shape the spatial structure of causal alleles is key to comprehend the spatial distribution of complex traits. Natural selection, past population size changes, range expansions, consanguinity, assortative mating, archaic introgression, admixture, and the environment can alter the frequencies, effect sizes, and heterozygosities of causal alleles. This provides a genetic axis along which complex traits can vary. However, complex traits also vary along biogeographical and sociocultural axes which are often correlated with genetic axes in complex ways. The purpose of this review is to consider these genetic and environmental axes in concert and examine the ways they can help us decipher the variation in complex traits that is visible in humans today. This initiative necessarily implies a discussion of populations, traits, the ability to infer and interpret "genetic" components of complex traits, and how these have been impacted by adaptive events. In this review, we provide a history-aware discussion on these topics using both the recent and more distant past of our academic discipline and its relevant contexts.

Complex adaptive architecture underlies adaptation to quantitative host resistance in a fungal plant pathogen

Plant pathogens often adapt to plant genetic resistance so characterization of the architecture underlying such an adaptation is required to understand the adaptive potential of pathogen populations. Erosion of banana quantitative resistance to a major leaf disease caused by polygenic adaptation of the causal agent, the fungus Pseudocercospora fijiensis, was recently identified in the northern Caribbean region. Genome scan and quantitative genetics approaches were combined to investigate the adaptive architecture underlying this adaptation. Thirty-two genomic regions showing host selection footprints were identified by pool sequencing of isolates collected from seven plantation pairs of two cultivars with different levels of quantitative resistance. Individual sequencing and phenotyping of isolates from one pair revealed significant and variable levels of correlation between haplotypes in 17 of these regions with a quantitative trait of pathogenicity (the diseased leaf area). The multilocus pattern of haplotypes detected in the 17 regions was found to be highly variable across all the population pairs studied. These results suggest complex adaptive architecture underlying plant pathogen adaptation to quantitative resistance with a polygenic basis, redundancy, and a low level of parallel evolution between pathogen populations. Candidate genes involved in quantitative pathogenicity and host adaptation of P. fijiensis were identified in genomic regions by combining annotation analysis with available biological data.

Highly Parallel Genomic Selection Response in Replicated Drosophila melanogaster Populations with Reduced Genetic Variation

Many adaptive traits are polygenic and frequently more loci contributing to the phenotype are segregating than needed to express the phenotypic optimum. Experimental evolution with replicated populations adapting to a new controlled environment provides a powerful approach to study polygenic adaptation. Because genetic redundancy often results in nonparallel selection responses among replicates, we propose a modified evolve and resequence (E&R) design that maximizes the similarity among replicates. Rather than starting from many founders, we only use two inbred Drosophila melanogaster strains and expose them to a very extreme, hot temperature environment (29 °C). After 20 generations, we detect many genomic regions with a strong, highly parallel selection response in 10 evolved replicates. The X chromosome has a more pronounced selection response than the autosomes, which may be attributed to dominance effects. Furthermore, we find that the median selection coefficient for all chromosomes is higher in our two-genotype experiment than in classic E&R studies. Because two random genomes harbor sufficient variation for adaptive responses, we propose that this approach is particularly well-suited for the analysis of polygenic adaptation.

Ethanol resistance in Drosophila melanogaster has increased in parallel cold-adapted populations and shows a variable genetic architecture within and between populations

Understanding the genetic properties of adaptive trait evolution is a fundamental crux of biological inquiry that links molecular processes to biological diversity. Important uncertainties persist regarding the genetic predictability of adaptive trait change, the role of standing variation, and whether adaptation tends to result in the fixation of favored variants. Here, we use the recurrent evolution of enhanced ethanol resistance in Drosophila melanogaster during this species' worldwide expansion as a promising system to add to our understanding of the genetics of adaptation. We find that elevated ethanol resistance has evolved at least three times in different cooler regions of the species' modern range-not only at high latitude but also in two African high-altitude regions. Applying a bulk segregant mapping framework, we find that the genetic architecture of ethanol resistance evolution differs substantially not only between our three resistant populations, but also between two crosses involving the same European population. We then apply population genetic scans for local adaptation within our quantitative trait locus regions, and we find potential contributions of genes with annotated roles in spindle localization, membrane composition, sterol and alcohol metabolism, and other processes. We also apply simulation-based analyses that confirm the variable genetic basis of ethanol resistance and hint at a moderately polygenic architecture. However, these simulations indicate that larger-scale studies will be needed to more clearly quantify the genetic architecture of adaptive evolution and to firmly connect trait evolution to specific causative loci.

Chromosome X-wide Analysis of Positive Selection in Human Populations: Common and Private Signals of Selection and its Impact on Inactivated Genes and Enhancers

The ability of detecting adaptive (positive) selection in the genome has opened the possibility of understanding the genetic basis of population-specific adaptations genome-wide. Here, we present the analysis of recent selective sweeps, specifically in the X chromosome, in human populations from the third phase of the 1,000 Genomes Project using three different haplotype-based statistics. We describe instances of recent positive selection that fit the criteria of hard or soft sweeps, and detect a higher number of events among sub-Saharan Africans than non-Africans (Europe and East Asia). A global enrichment of neural-related processes is observed and numerous genes related to fertility appear among the top candidates, reflecting the importance of reproduction in human evolution. Commonalities with previously reported genes under positive selection are found, while particularly strong new signals are reported in specific populations or shared across different continental groups. We report an enrichment of signals in genes that escape X chromosome inactivation, which may contribute to the differentiation between sexes. We also provide evidence of a widespread presence of soft-sweep-like signatures across the chromosome and a global enrichment of highly scoring regions that overlap potential regulatory elements. Among these, enhancers-like signatures seem to present putative signals of positive selection which might be in concordance with selection in their target genes. Also, particularly strong signals appear in regulatory regions that show differential activities, which might point to population-specific regulatory adaptations.

Interplay between extreme drift and selection intensities favors the fixation of beneficial mutations in selfing maize populations

Population and quantitative genetic models provide useful approximations to predict long-term selection responses sustaining phenotypic shifts, and underlying multilocus adaptive dynamics. Valid across a broad range of parameters, their use for understanding the adaptive dynamics of small selfing populations undergoing strong selection intensity (thereafter High Drift-High selection regime, HDHS) remains to be explored. Saclay Divergent Selection Experiments (DSEs) on maize flowering time provide an interesting example of populations evolving under HDHS, with significant selection responses over 20 generations in two directions. We combined experimental data from Saclay DSEs, forward individual-based simulations, and theoretical predictions to dissect the evolutionary mechanisms at play in the observed selection responses. We asked two main questions: How do mutations arise, spread, and reach fixation in populations evolving under HDHS? How does the interplay between drift and selection influence observed phenotypic shifts? We showed that the long-lasting response to selection in small populations is due to the rapid fixation of mutations occurring during the generations of selection. Among fixed mutations, we also found a clear signal of enrichment for beneficial mutations revealing a limited cost of selection. Both environmental stochasticity and variation in selection coefficients likely contributed to exacerbate mutational effects, thereby facilitating selection grasp and fixation of small-effect mutations. Together our results highlight that despite a small number of polymorphic loci expected under HDHS, adaptive variation is continuously fueled by a vast mutational target. We discuss our results in the context of breeding and long-term survival of small selfing populations.

Allele frequency divergence reveals ubiquitous influence of positive selection in Drosophila

Resolving the role of natural selection is a basic objective of evolutionary biology. It is generally difficult to detect the influence of selection because ubiquitous non-selective stochastic change in allele frequencies (genetic drift) degrades evidence of selection. As a result, selection scans typically only identify genomic regions that have undergone episodes of intense selection. Yet it seems likely such episodes are the exception; the norm is more likely to involve subtle, concurrent selective changes at a large number of loci. We develop a new theoretical approach that uncovers a previously undocumented genome-wide signature of selection in the collective divergence of allele frequencies over time. Applying our approach to temporally resolved allele frequency measurements from laboratory and wild Drosophila populations, we quantify the selective contribution to allele frequency divergence and find that selection has substantial effects on much of the genome. We further quantify the magnitude of the total selection coefficient (a measure of the combined effects of direct and linked selection) at a typical polymorphic locus, and find this to be large (of order 1%) even though most mutations are not directly under selection. We find that selective allele frequency divergence is substantially elevated at intermediate allele frequencies, which we argue is most parsimoniously explained by positive-not negative-selection. Thus, in these populations most mutations are far from evolving neutrally in the short term (tens of generations), including mutations with neutral fitness effects, and the result cannot be explained simply as an ongoing purging of deleterious mutations.