Signatures of positive selection: from selective sweeps at individual loci to subtle allele frequency changes in polygenic adaptation

Evolution of parasites in the Anthropocene: new pressures, new adaptive directions

The Anthropocene is seeing the human footprint rapidly spreading to all of Earth's ecosystems. The fast-changing biotic and abiotic conditions experienced by all organisms are exerting new and strong selective pressures, and there is a growing list of examples of human-induced evolution in response to anthropogenic impacts. No organism is exempt from these novel selective pressures. Here, we synthesise current knowledge on human-induced evolution in eukaryotic parasites of animals, and present a multidisciplinary framework for its study and monitoring. Parasites generally have short generation times and huge fecundity, features that predispose them for rapid evolution. We begin by reviewing evidence that parasites often have substantial standing genetic variation, and examples of their rapid evolution both under conditions of livestock production and in serial passage experiments. We then present a two-step conceptual overview of the causal chain linking anthropogenic impacts to parasite evolution. First, we review the major anthropogenic factors impacting parasites, and identify the selective pressures they exert on parasites through increased mortality of either infective stages or adult parasites, or through changes in host density, quality or immunity. Second, we discuss what new phenotypic traits are likely to be favoured by the new selective pressures resulting from altered parasite mortality or host changes; we focus mostly on parasite virulence and basic life-history traits, as these most directly influence the transmission success of parasites and the pathology they induce. To illustrate the kinds of evolutionary changes in parasites anticipated in the Anthropocene, we present a few scenarios, either already documented or hypothetical but plausible, involving parasite taxa in livestock, aquaculture and natural systems. Finally, we offer several approaches for investigations and real-time monitoring of rapid, human-induced evolution in parasites, ranging from controlled experiments to the use of state-of-the-art genomic tools. The implications of fast-evolving parasites in the Anthropocene for disease emergence and the dynamics of infections in domestic animals and wildlife are concerning. Broader recognition that it is not only the conditions for parasite transmission that are changing, but the parasites themselves, is needed to meet better the challenges ahead.

Large changes in detected selection signatures after a selection limit in mice bred for voluntary wheel-running behavior

In various organisms, sequencing of selectively bred lines at apparent selection limits has demonstrated that genetic variation can remain at many loci, implying that evolution at the genetic level may continue even if the population mean phenotype remains constant. We compared selection signatures at generations 22 and 61 of the "High Runner" mouse experiment, which includes 4 replicate lines bred for voluntary wheel-running behavior (HR) and 4 non-selected control (C) lines. Previously, we reported multiple regions of differentiation between the HR and C lines, based on whole-genome sequence data for 10 mice from each line at generation 61, which was >31 generations after selection limits had been reached in all HR lines. Here, we analyzed pooled sequencing data from ~20 mice for each of the 8 lines at generation 22, around when HR lines were reaching limits. Differentiation analyses of allele frequencies at ~4.4 million SNP loci used the regularized T-test and detected 258 differentiated regions with FDR = 0.01. Comparable analyses involving pooling generation 61 individual mouse genotypes into allele frequencies by line produced only 11 such regions, with almost no overlap among the largest and most statistically significant peaks between the two generations. These results implicate a sort of "genetic churn" that continues at loci relevant for running. Simulations indicate that loss of statistical power due to random genetic drift and sampling error are insufficient to explain the differences in selection signatures. The 13 differentiated regions at generation 22 with strict culling measures include 79 genes related to a wide variety of functions. Gene ontology identified pathways related to olfaction and vomeronasal pathways as being overrepresented, consistent with generation 61 analyses, despite those specific regions differing between generations. Genes Dspp and Rbm24 are also identified as potentially explaining known bone and skeletal muscle differences, respectively, between the linetypes.

Genome-wide relaxation of selection and the evolution of the island syndrome in Orkney voles

Island populations often experience different ecological and demographic conditions than their counterparts on the continent, resulting in divergent evolutionary forces affecting their genomes. Random genetic drift and selection both may leave their imprints on island populations, although the relative impact depends strongly on the specific conditions. Here we address their contributions to the island syndrome in a rodent with an unusually clear history of isolation. Common voles (Microtus arvalis) were introduced by humans on the Orkney archipelago north of Scotland >5000 years ago and rapidly evolved to exceptionally large size. Our analyses show that the genomes of Orkney voles were dominated by genetic drift, with extremely low diversity, variable Tajima's D, and very high divergence from continental conspecifics. Increased d N/d S ratios over a wide range of genes in Orkney voles indicated genome-wide relaxation of purifying selection. We found evidence of hard sweeps on key genes of the lipid metabolism pathway only in continental voles. The marked increase of body size in Orkney-a typical phenomenon of the island syndrome-may thus be associated to the relaxation of positive selection on genes related to this pathway. On the other hand, a hard sweep on immune genes of Orkney voles likely reflects the divergent ecological conditions and possibly the history of human introduction. The long-term isolated Orkney voles show that adaptive changes may still impact the evolutionary trajectories of such populations despite the pervasive consequences of genetic drift at the genome level.

Shared xerophytic genes and their re-use in local adaptation to aridity in the desert plant Gymnocarpos przewalskii

In order to thrive and survive, plant species need to combine stability in the long term and rapid response to environmental challenges in the short term. The former would be reflected by parallel or convergent adaptation across species, and the latter by pronounced local adaptation among populations of the same species. In the present study, we generated a high-quality genome and re-sequenced 177 individuals for Gymnocarpos przewalskii, an important desert plant species from North-West China, to detect local adaptation. We first focus on ancient adaptation to aridity at the molecular level by comparing the genomic data of 15 species that vary in their ability to withstand aridity. We found that a total of 118 genes were shared across xerophytic species but absent from non-xerophytic species. Of the 65 found in G. przewalskii, 63 were under purifying selection and two under positive selection. We then focused on local adaptation. Up to 20% of the G. przewalskii genome showed signatures of local adaptation to aridity during population divergence. Thirteen of the selected shared xerophytic genes were reused in local adaptation after population differentiation. Hence, only about 20% of the genes shared and specific to xerophytic species and associated with adaptation to aridity were later recruited for local adaptation in G. przewalskii.

Determinants of rapid adaptation in species with large variance in offspring production

The speed of population adaptation to changing biotic and abiotic environments is determined by the interaction between genetic drift, positive selection and linkage effects. Many marine species (fish, crustaceans), invertebrates and pathogens of humans and crops, exhibit sweepstakes reproduction characterized by the production of a very large amount of offspring (fecundity phase) from which only a small fraction may survive to the next generation (viability phase). Using stochastic simulations, we investigate whether the occurrence of sweepstakes reproduction affects the efficiency of a positively selected unlinked locus, and thus, the speed of adaptation since fecundity and/or viability have distinguishable consequences on mutation rate, probability and fixation time of advantageous alleles. We observe that the mean number of mutations at the next generation is always the function of the population size, but the variance increases with stronger sweepstakes reproduction when mutations occur in the parents. On the one hand, stronger sweepstakes reproduction magnifies the effect of genetic drift thus increasing the probability of fixation of neutral allele and decreasing that of selected alleles. On the other hand, the time to fixation of advantageous (as well as neutral) alleles is shortened by stronger sweepstakes reproduction. Importantly, fecundity and viability selection exhibit different probabilities and times to fixation of advantageous alleles under intermediate and weak sweepstakes reproduction. Finally, alleles under both strong fecundity and viability selection display a synergistic efficiency of selection. We conclude that measuring and modelling accurately fecundity and/or viability selection are crucial to predict the adaptive potential of species with sweepstakes reproduction.

Sweepstakes reproduction facilitates rapid adaptation in highly fecund populations

Adaptation enables natural populations to survive in a changing environment. Understanding the mechanics of adaptation is therefore crucial for learning about the evolution and ecology of natural populations. We focus on the impact of random sweepstakes on selection in highly fecund haploid and diploid populations partitioned into two genetic types, with one type conferring selective advantage. For the diploid populations, we incorporate various dominance mechanisms. We assume that the populations may experience recurrent bottlenecks. In random sweepstakes, the distribution of individual recruitment success is highly skewed, resulting in a huge variance in the number of offspring contributed by the individuals present in any given generation. Using computer simulations, we investigate the joint effects of random sweepstakes, recurrent bottlenecks and dominance mechanisms on selection. In our framework, bottlenecks allow random sweepstakes to have an effect on the time to fixation, and in diploid populations, the effect of random sweepstakes depends on the dominance mechanism. We describe selective sweepstakes that are approximated by recurrent sweeps of strongly beneficial allelic types arising by mutation. We demonstrate that both types of sweepstakes reproduction may facilitate rapid adaptation (as defined based on the average time to fixation of a type conferring selective advantage conditioned on fixation of the type). However, whether random sweepstakes cause rapid adaptation depends also on their interactions with bottlenecks and dominance mechanisms. Finally, we review a case study in which a model of recurrent sweeps is shown to essentially explain population genomic data from Atlantic cod.

Genetic depletion does not prevent rapid evolution in island-introduced lizards

Experimental introductions of species have provided some of the most tractable examples of rapid phenotypic changes, which may reflect plasticity, the impact of stochastic processes, or the action of natural selection. Yet to date, very few studies have investigated the neutral and potentially adaptive genetic impacts of experimental introductions. We dissect the role of these processes in shaping the population differentiation of wall lizards in three Croatian islands (Sušac, Pod Kopište, and Pod Mrčaru), including the islet of Pod Mrčaru, where experimentally introduced lizards underwent rapid (~30 generations) phenotypic changes associated with a shift from an insectivorous to a plant-based diet. Using a genomic approach (~82,000 ddRAD loci), we confirmed a founder effect during introduction and very low neutral genetic differentiation between the introduced population and its source. However, genetic depletion did not prevent rapid population growth, as the introduced lizards exhibited population genetic signals of expansion and are known to have reached a high density. Our genome-scan analysis identified just a handful of loci showing large allelic shifts between ecologically divergent populations. This low overall signal of selection suggests that the extreme phenotypic differences observed among populations are determined by a small number of large-effect loci and/or that phenotypic plasticity plays a major role in phenotypic changes. Nonetheless, functional annotation of the outlier loci revealed some candidate genes relevant to diet-induced adaptation, in agreement with the hypothesis of directional selection. Our study provides important insights on the evolutionary potential of bottlenecked populations in response to new selective pressures on short ecological timescales.

Detecting parallel polygenic adaptation to novel evolutionary pressure in wild populations: a case study in Atlantic cod (Gadus morhua)

Populations can adapt to novel selection pressures through dramatic frequency changes in a few genes of large effect or subtle shifts in many genes of small effect. The latter (polygenic adaptation) is expected to be the primary mode of evolution for many life-history traits but tends to be more difficult to detect than changes in genes of large effect. Atlantic cod (Gadus morhua) were subjected to intense fishing pressure over the twentieth century, leading to abundance crashes and a phenotypic shift toward earlier maturation across many populations. Here, we use spatially replicated temporal genomic data to test for a shared polygenic adaptive response to fishing using methods previously applied to evolve-and-resequence experiments. Cod populations on either side of the Atlantic show covariance in allele frequency change across the genome that are characteristic of recent polygenic adaptation. Using simulations, we demonstrate that the degree of covariance in allele frequency change observed in cod is unlikely to be explained by neutral processes or background selection. As human pressures on wild populations continue to increase, understanding and attributing modes of adaptation using methods similar to those demonstrated here will be important in identifying the capacity for adaptive responses and evolutionary rescue. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

This population does not exist: learning the distribution of evolutionary histories with generative adversarial networks

Numerous studies over the last decade have demonstrated the utility of machine learning methods when applied to population genetic tasks. More recent studies show the potential of deep-learning methods in particular, which allow researchers to approach problems without making prior assumptions about how the data should be summarized or manipulated, instead learning their own internal representation of the data in an attempt to maximize inferential accuracy. One type of deep neural network, called Generative Adversarial Networks (GANs), can even be used to generate new data, and this approach has been used to create individual artificial human genomes free from privacy concerns. In this study, we further explore the application of GANs in population genetics by designing and training a network to learn the statistical distribution of population genetic alignments (i.e. data sets consisting of sequences from an entire population sample) under several diverse evolutionary histories-the first GAN capable of performing this task. After testing multiple different neural network architectures, we report the results of a fully differentiable Deep-Convolutional Wasserstein GAN with gradient penalty that is capable of generating artificial examples of population genetic alignments that successfully mimic key aspects of the training data, including the site-frequency spectrum, differentiation between populations, and patterns of linkage disequilibrium. We demonstrate consistent training success across various evolutionary models, including models of panmictic and subdivided populations, populations at equilibrium and experiencing changes in size, and populations experiencing either no selection or positive selection of various strengths, all without the need for extensive hyperparameter tuning. Overall, our findings highlight the ability of GANs to learn and mimic population genetic data and suggest future areas where this work can be applied in population genetics research that we discuss herein.

The role of genomic signatures of directional selection and demographic history in the population structure of a marine teleost with high gene flow

Recent studies have uncovered patterns of genomic divergence in marine teleosts where panmixia due to high gene flow has been the general paradigm. These signatures of divergent selection are often impacted by structural variants, acting as "supergenes" facilitating local adaptation. The highly dispersing European plaice (Pleuronectes platessa)-in which putative structural variants (i.e., inversions) have been identified-has successfully colonized the brackish water ecosystem of the Baltic Sea. Thus, the species represents an ideal opportunity to investigate how the interplay of gene flow, structural variants, natural selection, past demographic history, and gene flow impacts on population (sub)structuring in marine systems. Here, we report on the generation of an annotated draft plaice genome assembly in combination with population sequencing data-following the salinity gradient from the Baltic Sea into the North Sea together with samples from Icelandic waters-to illuminate genome-wide patterns of divergence. Neutral markers pointed at large-scale panmixia across the European continental shelf associated with high gene flow and a common postglacial colonization history of shelf populations. However, based on genome-wide outlier loci, we uncovered signatures of population substructuring among the European continental shelf populations, i.e., suggesting signs of ongoing selection. Genome-wide selection analyses (xp-EHH) and the identification of genes within genomic regions of recent selective sweeps-overlapping with the outlier loci-suggest that these represent the signs of divergent selection. Our findings provide support for genomic divergence driven by local adaptation in the face of high gene flow and elucidate the relative importance of demographic history versus adaptive divergence in shaping the contemporary population genetic structure of a marine teleost. The role of the putative inversion(s) in the substructuring-and potentially ongoing adaptation-was seemingly not substantial.

Prospects for genomic surveillance for selection in schistosome parasites

Schistosomiasis is a neglected tropical disease caused by multiple parasitic Schistosoma species, and which impacts over 200 million people globally, mainly in low- and middle-income countries. Genomic surveillance to detect evidence for natural selection in schistosome populations represents an emerging and promising approach to identify and interpret schistosome responses to ongoing control efforts or other environmental factors. Here we review how genomic variation is used to detect selection, how these approaches have been applied to schistosomes, and how future studies to detect selection may be improved. We discuss the theory of genomic analyses to detect selection, identify experimental designs for such analyses, and review studies that have applied these approaches to schistosomes. We then consider the biological characteristics of schistosomes that are expected to respond to selection, particularly those that may be impacted by control programs. Examples include drug resistance, host specificity, and life history traits, and we review our current understanding of specific genes that underlie them in schistosomes. We also discuss how inherent features of schistosome reproduction and demography pose substantial challenges for effective identification of these traits and their genomic bases. We conclude by discussing how genomic surveillance for selection should be designed to improve understanding of schistosome biology, and how the parasite changes in response to selection.

Uncovering signals of positive selection in Peruvian populations from three ecological regions

Perú hosts extremely diverse ecosystems which can be broadly classified into three major ecoregions: the Pacific desert coast, the Andean highlands, and the Amazon rainforest. Since its initial peopling approximately 12,000 years ago, the populations inhabiting such ecoregions might have differentially adapted to their contrasting environmental pressures. Previous studies have described several candidate genes underlying adaptation to hypobaric hypoxia among Andean highlanders. However, the adaptive genetic diversity of coastal and rainforest populations has been less studied. Here, we gathered genome-wide SNP-array data from 286 Peruvians living across the three ecoregions and analysed signals of recent positive selection through population differentiation and haplotype-based selection scans. Among highland populations, we identify candidate genes related to cardiovascular function (TLL1, DUSP27, TBX5, PLXNA4, SGCD), to the Hypoxia-Inducible Factor pathway (TGFA, APIP), to skin pigmentation (MITF), as well as to glucose (GLIS3) and glycogen metabolism (PPP1R3C, GANC). In contrast, most signatures of adaptation in coastal and rainforest populations comprise candidate genes related to the immune system (including SIGLEC8, TRIM21, CD44 and ICAM1 in the coast; CBLB and PRDM1 in rainforest and the BRD2- HLA-DOA- HLA-DPA1 region in both), possibly as a result of strong pathogen-driven selection. This study identifies candidate genes related to human adaptation to the diverse environments of South America.

How Can We Resolve Lewontin's Paradox?

We discuss the genetic, demographic, and selective forces that are likely to be at play in restricting observed levels of DNA sequence variation in natural populations to a much smaller range of values than would be expected from the distribution of census population sizes alone-Lewontin's Paradox. While several processes that have previously been strongly emphasized must be involved, including the effects of direct selection and genetic hitchhiking, it seems unlikely that they are sufficient to explain this observation without contributions from other factors. We highlight a potentially important role for the less-appreciated contribution of population size change; specifically, the likelihood that many species and populations may be quite far from reaching the relatively high equilibrium diversity values that would be expected given their current census sizes.

Machine-Learning Prospects for Detecting Selection Signatures Using Population Genomics Data

Natural selection has been given a lot of attention because it relates to the adaptation of populations to their environments, both biotic and abiotic. An allele is selected when it is favored by natural selection. Consequently, the favored allele increases in frequency in the population and neighboring linked variation diminishes, causing so-called selective sweeps. A high-throughput genomic sequence allows one to disentangle the evolutionary forces at play in populations. With the development of high-throughput genome sequencing technologies, it has become easier to detect these selective sweeps/selection signatures. Various methods can be used to detect selective sweeps, from simple implementations using summary statistics to complex statistical approaches. One of the important problems of these statistical models is the potential to provide inaccurate results when their assumptions are violated. The use of machine learning (ML) in population genetics has been introduced as an alternative method of detecting selection by treating the problem of detecting selection signatures as a classification problem. Since the availability of population genomics data is increasing, researchers may incorporate ML into these statistical models to infer signatures of selection with higher predictive accuracy and better resolution. This article describes how ML can be used to aid in detecting and studying natural selection patterns using population genomic data.

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.

Identification of important genomic footprints using eight different selection signature statistics in domestic cattle breeds

In the present study, the population genomic data of different cattle breeds were explored to decipher the genomic regions affected due to selective events and reflected in the productive, reproductive, thermo-tolerance, and health-related traits. To find out these genomic deviations due to selective sweeps, we used eight different statistical tools (Tajima's D, Fu & Li's D*, CLR, ROH, iHS, F_ST, FLK, and hapFLK) on seven indigenous and five exotic cattle breeds. We further performed composite analysis by comparing their covariance matrix. Several candidate genes were found to be related to milk production (ADARB, WDR70, and CA8), reproductive (PARN, FAM134B2, and ZBTB20), and health-related traits (SP110, CXCL2, CLXCL3, CXCL5, IRF8, and MYOM1). The outcome of this investigation provides a basis for detecting selective sweeps that explain the genetic variation of traits. They may possess functional importance for multiple cattle breeds in different subcontinents. However, further studies are required to improve the findings using high-density arrays or whole-genome sequencing with higher resolution and greater sample sizes.

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.

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 resequencing reveals rapid, repeated evolution in the Colorado potato beetle

Insecticide resistance and rapid pest evolution threatens food security and the development of sustainable agricultural practices, yet the evolutionary mechanisms that allow pests to rapidly adapt to control tactics remains unclear. Here we examine how a global super-pest, the Colorado potato beetle (CPB), Leptinotarsa decemlineata, rapidly evolves resistance to insecticides. Using whole genome resequencing and transcriptomic data focused on its ancestral and pest range in North America, we assess evidence for three, non-mutually exclusive models of rapid evolution: pervasive selection on novel mutations, rapid regulatory evolution, and repeated selection on standing genetic variation. Population genomic analysis demonstrates that CPB is geographically structured, even among recently established pest populations. Pest populations exhibit similar levels of nucleotide diversity, relative to non-pest populations, and show evidence of recent expansion. Genome scans provide clear signatures of repeated adaptation across CPB populations, with especially strong evidence of selection on insecticide resistance genes in different populations. Analyses of gene expression show that constitutive upregulation of candidate insecticide resistance genes drives distinctive population patterns. CPB evolves insecticide resistance repeatedly across agricultural regions, leveraging similar genetic pathways but different genes, demonstrating a polygenic trait architecture for insecticide resistance that can evolve from standing genetic variation. Despite expectations, we do not find support for strong selection on novel mutations, or rapid evolution from selection on regulatory genes. These results suggest that integrated pest management practices must mitigate the evolution of polygenic resistance phenotypes among local pest populations, in order to maintain the efficacy and sustainability of novel control techniques.

Detecting selection using extended haplotype homozygosity (EHH)-based statistics in unphased or unpolarized data

Analysis of population genetic data often includes a search for genomic regions with signs of recent positive selection. One of such approaches involves the concept of extended haplotype homozygosity (EHH) and its associated statistics. These statistics typically require phased haplotypes, and some of them necessitate polarized variants. Here, we unify and extend previously proposed modifications to loosen these requirements. We compare the modified versions with the original ones by measuring the false discovery rate in simulated whole-genome scans and by quantifying the overlap of inferred candidate regions in empirical data. We find that phasing information is indispensable for accurate estimation of within-population statistics (for all but very large samples) and of cross-population statistics for small samples. Ancestry information, in contrast, is of lesser importance for both types of statistic. Our publicly available R package rehh incorporates the modified statistics presented here.

Contrasting gene-level signatures of selection with reproductive fitness

Selection leaves signatures in the DNA sequence of genes, with many test statistics devised to detect its action. While these statistics are frequently used to support hypotheses about the adaptive significance of particular genes, the effect these genes have on reproductive fitness is rarely quantified experimentally. Consequently, it is unclear how gene-level signatures of selection are associated with empirical estimates of gene effect on fitness. Eukaryotic datasets that permit this comparison are very limited. Using the model plant Arabidopsis thaliana, for which these resources are available, we calculated seven gene-level substitution and polymorphism-based statistics commonly used to infer selection (dN/dS, NI, DOS, Tajima's D, Fu and Li's D*, Fay and Wu's H, and Zeng's E) and, using knockout lines, compared these to gene-level estimates of effect on fitness. We found that consistent with expectations, essential genes were more likely to be classified as negatively selected. By contrast, using 379 Arabidopsis genes for which data was available, we found no evidence that genes predicted to be positively selected had a significantly different effect on fitness than genes evolving more neutrally. We discuss these results in the context of the analytic challenges posed by Arabidopsis, one of the only systems in which this study could be conducted, and advocate for examination in additional systems. These results are relevant to the evaluation of genome-wide studies across species where experimental fitness data is unavailable, as well as highlighting an increasing need for the latter.

Sporadic occurrence of recent selective sweeps from standing variation in humans as revealed by an approximate Bayesian computation approach

During their dispersals over the last 100,000 years, modern humans have been exposed to a large variety of environments, resulting in genetic adaptation. While genome-wide scans for the footprints of positive Darwinian selection have increased knowledge of genes and functions potentially involved in human local adaptation, they have globally produced evidence of a limited contribution of selective sweeps in humans. Conversely, studies based on machine learning algorithms suggest that recent sweeps from standing variation are widespread in humans, an observation that has been recently questioned. Here, we sought to formally quantify the number of recent selective sweeps in humans, by leveraging approximate Bayesian computation and whole-genome sequence data. Our computer simulations revealed suitable ABC estimations, regardless of the frequency of the selected alleles at the onset of selection and the completion of sweeps. Under a model of recent selection from standing variation, we inferred that an average of 68 (from 56 to 79) and 140 (from 94 to 198) sweeps occurred over the last 100,000 years of human history, in African and Eurasian populations, respectively. The former estimation is compatible with human adaptation rates estimated since divergence with chimps, and reveals numbers of sweeps per generation per site in the range of values estimated in Drosophila. Our results confirm the rarity of selective sweeps in humans and show a low contribution of sweeps from standing variation to recent human adaptation.

Drosophila Evolution over Space and Time (DEST): A New Population Genomics Resource

Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome data sets from natural populations of this species have been published over the last years. A major challenge is the integration of disparate data sets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 previously published and unpublished population samples from over 100 locations in >20 countries on four continents. Several of these locations have been sampled at different seasons across multiple years. This data set, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental metadata. A web-based genome browser and web portal provide easy access to the SNP data set. We further provide guidelines on how to use Pool-Seq data for model-based demographic inference. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan data set. Our resource will enable population geneticists to analyze spatiotemporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.

Using singleton densities to detect recent selection in Bos taurus

Many quantitative traits are subject to polygenic selection, where several genomic regions undergo small, simultaneous changes in allele frequency that collectively alter a phenotype. The widespread availability of genome data, along with novel statistical techniques, has made it easier to detect these changes. We apply one such method, the "Singleton Density Score" (SDS), to the Holstein breed of Bos taurus to detect recent selection (arising up to around 740 years ago). We identify several genes as candidates for targets of recent selection, including some relating to cell regulation, catabolic processes, neural-cell adhesion and immunity. We do not find strong evidence that three traits that are important to humans-milk protein content, milk fat content, and stature-have been subject to directional selection. Simulations demonstrate that because B. taurus recently experienced a population bottleneck, singletons are depleted so the power of SDS methods is reduced. These results inform on which genes underlie recent genetic change in B. taurus, while providing information on how polygenic selection can be best investigated in future studies.

Time to fixation in changing environments

Although many experimental and theoretical studies on natural selection have been carried out in a constant environment, as natural environments typically vary in time, it is important to ask if and how the results of these investigations are affected by a changing environment. Here, we study the properties of the conditional fixation time defined as the time to fixation of a new mutant that is destined to fix in a finite, randomly mating diploid population with intermediate dominance that is evolving in a periodically changing environment. It is known that in a static environment, the conditional mean fixation time of a co-dominant beneficial mutant is equal to that of a deleterious mutant with the same magnitude of selection coefficient. We find that this symmetry is not preserved, even when the environment is changing slowly. More generally, we find that the conditional mean fixation time of an initially beneficial mutant in a slowly changing environment depends weakly on the dominance coefficient and remains close to the corresponding result in the static environment. However, for an initially deleterious mutant under moderate and slowly varying selection, the fixation time differs substantially from that in a constant environment when the mutant is recessive. As fixation times are intimately related to the levels and patterns of genetic diversity, our results suggest that for beneficial sweeps, these quantities are only mildly affected by temporal variation in environment. In contrast, environmental change is likely to impact the patterns due to recessive deleterious sweeps strongly.

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.

Genomic Signatures of Domestication Selection in the Australasian Snapper (Chrysophrys auratus)

Domestication of teleost fish is a recent development, and in most cases started less than 50 years ago. Shedding light on the genomic changes in key economic traits during the domestication process can provide crucial insights into the evolutionary processes involved and help inform selective breeding programmes. Here we report on the recent domestication of a native marine teleost species in New Zealand, the Australasian snapper (Chrysophrys auratus). Specifically, we use genome-wide data from a three-generation pedigree of this species to uncover genetic signatures of domestication selection for growth. Genotyping-By-Sequencing (GBS) was used to generate genome-wide SNP data from a three-generation pedigree to calculate generation-wide averages of FST between every generation pair. The level of differentiation between generations was further investigated using ADMIXTURE analysis and Principal Component Analysis (PCA). After that, genome scans using Bayescan, LFMM and XP-EHH were applied to identify SNP variants under putative selection following selection for growth. Finally, genes near candidate SNP variants were annotated to gain functional insights. Analysis showed that between generations FST values slightly increased as generational time increased. The extent of these changes was small, and both ADMIXTURE analysis and PCA were unable to form clear clusters. Genome scans revealed a number of SNP outliers, indicative of selection, of which a small number overlapped across analyses methods and populations. Genes of interest within proximity of putative selective SNPs were related to biological functions, and revealed an association with growth, immunity, neural development and behaviour, and tumour repression. Even though few genes overlapped between outlier SNP methods, gene functionalities showed greater overlap between methods. While the genetic changes observed were small in most cases, a number of outlier SNPs could be identified, of which some were found by more than one method. Multiple outlier SNPs appeared to be predominately linked to gene functionalities that modulate growth and survival. Ultimately, the results help to shed light on the genomic changes occurring during the early stages of domestication selection in teleost fish species such as snapper, and will provide useful candidates for the ongoing selective breeding in the future of this and related species.

Selection on growth rate and local adaptation drive genomic adaptation during experimental range expansions in the protist Tetrahymena thermophila

Populations that expand their range can undergo rapid evolutionary adaptation of life‐history traits, dispersal behaviour and adaptation to the local environment. Such adaptation may be aided or hindered by sexual reproduction, depending on the context.

However, few empirical and experimental studies have investigated the genetic basis of adaptive evolution during range expansions. Even less attention has been given to the question how sexual reproduction may modulate such adaptive evolution during range expansions.

We here studied genomic adaptation during experimental range expansions of the protist Tetrahymena thermophila in landscapes with a uniform environment or a pH gradient. Specifically, we investigated two aspects of genomic adaptation during range expansion. First, we investigated adaptive genetic change in terms of the underlying numbers of allele frequency changes from standing genetic variation and de novo variants. We focused on how sexual reproduction may alter this adaptive genetic change. Second, we identified genes subject to selection caused by the expanding range itself, and directional selection due to the presence or absence of the pH gradient. We focused this analysis on alleles with large frequency changes that occurred in parallel in more than one population to identify the most likely candidate targets of selection.

We found that sexual reproduction altered adaptive genetic change both in terms of de novo variants and standing genetic variation. However, sexual reproduction affected allele frequency changes in standing genetic variation only in the absence of long‐distance gene flow. Adaptation to the range expansion affected genes involved in cell divisions and DNA repair, whereas adaptation to the pH gradient additionally affected genes involved in ion balance and oxidoreductase reactions. These genetic changes may result from selection on growth and adaptation to low pH.

In the absence of gene flow, sexual reproduction may have aided genetic adaptation. Gene flow may have swamped expanding populations with maladapted alleles, thus reducing the extent of evolutionary adaptation during range expansion. Sexual reproduction also altered the genetic basis of adaptation in our evolving populations via de novo variants, possibly by purging deleterious mutations or by revealing fitness benefits of rare genetic variants.

Rapid Evolutionary Adaptation in Response to Selection on Quantitative Traits

Evolutionary adaptation after sudden environmental changes can occur very rapidly. The mechanisms facilitating rapid adaptation range from strong positive directional selection leading to large shifts in the allele frequencies at a few loci (selective sweeps) to polygenic selection causing small changes in allele frequencies at many loci. In addition, combinations of these two extreme mechanisms may also result in fast evolution. In recent years, following reports of new case studies of rapid adaptation, population genetic models have been proposed to explain these observations. In these models, the role of the major selective forces (positive directional and stabilizing selection) is highlighted as well as the genetic architecture of quantitative traits. Furthermore, the factors limiting the speed of adaptation are analyzed, in particular, the effects of random genetic drift and demography due to finite population size.

Maintenance of Adaptive Dynamics and No Detectable Load in a Range-Edge Outcrossing Plant Population

During range expansion, edge populations are expected to face increased genetic drift, which in turn can alter and potentially compromise adaptive dynamics, preventing the removal of deleterious mutations and slowing down adaptation. Here, we contrast populations of the European subspecies Arabidopsis lyrata ssp. petraea, which expanded its Northern range after the last glaciation. We document a sharp decline in effective population size in the range-edge population and observe that nonsynonymous variants segregate at higher frequencies. We detect a 4.9% excess of derived nonsynonymous variants per individual in the range-edge population, suggesting an increase of the genomic burden of deleterious mutations. Inference of the fitness effects of mutations and modeling of allele frequencies under the explicit demographic history of each population predicts a depletion of rare deleterious variants in the range-edge population, but an enrichment for fixed ones, consistent with the bottleneck effect. However, the demographic history of the range-edge population predicts a small net decrease in per-individual fitness. Consistent with this prediction, the range-edge population is not impaired in its growth and survival measured in a common garden experiment. We further observe that the allelic diversity at the self-incompatibility locus, which ensures strict outcrossing and evolves under negative frequency-dependent selection, has remained unchanged. Genomic footprints indicative of selective sweeps are broader in the Northern population but not less frequent. We conclude that the outcrossing species A. lyrata ssp. petraea shows a strong resilience to the effect of range expansion.

Genomic stability through time despite decades of exploitation in cod on both sides of the Atlantic

The mode and extent of rapid evolution and genomic change in response to human harvesting are key conservation issues. Although experiments and models have shown a high potential for both genetic and phenotypic change in response to fishing, empirical examples of genetic responses in wild populations are rare. Here, we compare whole-genome sequence data of Atlantic cod (Gadus morhua) that were collected before (early 20th century) and after (early 21st century) periods of intensive exploitation and rapid decline in the age of maturation from two geographically distinct populations in Newfoundland, Canada, and the northeast Arctic, Norway. Our temporal, genome-wide analyses of 346,290 loci show no substantial loss of genetic diversity and high effective population sizes. Moreover, we do not find distinct signals of strong selective sweeps anywhere in the genome, although we cannot rule out the possibility of highly polygenic evolution. Our observations suggest that phenotypic change in these populations is not constrained by irreversible loss of genomic variation and thus imply that former traits could be reestablished with demographic recovery.

Labelling Selective Sweeps Used in Durum Wheat Breeding from a Diverse and Structured Panel of Landraces and Cultivars

Simple Summary

Evaluation of the genetic diversity of a crop species is a critical step for breeding. Landraces are essential to avoid genetic erosion, and Mediterranean landraces are an important group of genetic resources due to their high genetic variability, adaptation to local conditions in rainfed environments, and their resilience to pests and pathogens. This study uses a genome-wide association approach employing eigenvectors to identify selective sweeps among Mediterranean durum wheat landraces and a world panel of modern cultivars.

Abstract

A panel of 387 durum wheat genotypes including Mediterranean landraces and modern cultivars was characterized with 46,161 diversity arrays technology (DArTseq) markers. Analysis of population structure uncovered the existence of five subpopulations (SP) related to the pattern of migration of durum wheat from the domestication area to the west of the Mediterranean basin (SPs 1, 2, and 3) and further improved germplasm (SPs 4 and 5). The total genetic diversity (H_T) was 0.40 with a genetic differentiation (G_ST) of 0.08 and a mean gene flow among SPs of 6.02. The lowest gene flow was detected between SP 1 (presumably the ancient genetic pool of the panel) and SPs 4 and 5. However, gene flow from SP 2 to modern cultivars was much higher. The highest gene flow was detected between SP 3 (western Mediterranean germplasm) and SP 5 (North American and European cultivars). A genome wide association study (GWAS) approach using the top ten eigenvectors as phenotypic data revealed the presence of 89 selective sweeps, represented as quantitative trait loci (QTL) hotspots, widely distributed across the durum wheat genome. A principal component analysis (PCoA) using 147 markers with −log₁₀p > 5 identified three regions located on chromosomes 2A, 2B and 3A as the main drivers for differentiation of Mediterranean landraces. Gene flow between SPs offers clues regarding the putative use of Mediterranean old durum germplasm by the breeding programs represented in the structure analysis. EigenGWAS identified selective sweeps among landraces and modern cultivars. The analysis of the corresponding genomic regions in the ‘Zavitan’, ‘Svevo’ and ‘Chinese Spring’ genomes discovered the presence of important functional genes including Ppd, Vrn, Rht, and gene models involved in important biological processes including LRR-RLK, MADS-box, NAC, and F-box.

Inference with selection, varying population size, and evolving population structure: application of ABC to a forward-backward coalescent process with interactions

Genetic data are often used to infer demographic history and changes or detect genes under selection. Inferential methods are commonly based on models making various strong assumptions: demography and population structures are supposed a priori known, the evolution of the genetic composition of a population does not affect demography nor population structure, and there is no selection nor interaction between and within genetic strains. In this paper, we present a stochastic birth-death model with competitive interactions and asexual reproduction. We develop an inferential procedure for ecological, demographic, and genetic parameters. We first show how genetic diversity and genealogies are related to birth and death rates, and to how individuals compete within and between strains. This leads us to propose an original model of phylogenies, with trait structure and interactions, that allows multiple merging. Second, we develop an Approximate Bayesian Computation framework to use our model for analyzing genetic data. We apply our procedure to simulated data from a toy model, and to real data by analyzing the genetic diversity of microsatellites on Y-chromosomes sampled from Central Asia human populations in order to test whether different social organizations show significantly different fertilities.

A genome-wide investigation of adaptive signatures in protein-coding genes related to tool behaviour in New Caledonian and Hawaiian crows

Very few animals habitually manufacture and use tools. It has been suggested that advanced tool behaviour co-evolves with a suite of behavioural, morphological and life history traits. In fact, there are indications for such an adaptive complex in tool-using crows (genus Corvus species). Here, we sequenced the genomes of two habitually tool-using and ten non-tool-using crow species to search for genomic signatures associated with a tool-using lifestyle. Using comparative genomic and population genetic approaches, we screened for signals of selection in protein-coding genes in the tool-using New Caledonian and Hawaiian crows. While we detected signals of recent selection in New Caledonian crows near genes associated with bill morphology, our data indicate that genetic changes in these two lineages are surprisingly subtle, with little evidence at present for convergence. We explore the biological explanations for these findings, such as the relative roles of gene regulation and protein-coding changes, as well as the possibility that statistical power to detect selection in recently diverged lineages may have been insufficient. Our study contributes to a growing body of literature aiming to decipher the genetic basis of recently evolved complex behaviour.

Extensive haplotypes are associated with population differentiation and environmental adaptability in Upland cotton (Gossypium hirsutum)

Three extensive eco-haplotypes associated with population differentiation and environmental adaptability in Upland cotton were identified, with A06_85658585, A08_43734499 and A06_113104285 considered the eco-loci for environmental adaptability. Population divergence is suggested to be the primary force driving the evolution of environmental adaptability in various species. Chromosome inversion increases reproductive isolation between subspecies and accelerates population divergence to adapt to new environments. Although modern cultivated Upland cotton (Gossypium hirsutum L.) has spread worldwide, the noticeable phenotypic differences still existed among cultivars grown in different areas. In recent years, the long-distance migration of cotton cultivation areas throughout China has demanded that breeders better understand the genetic basis of environmental adaptability in Upland cotton. Here, we integrated the genotypes of 419 diverse accessions, long-term environment-associated variables (EAVs) and environment-associated traits (EATs) to evaluate subgroup differentiation and identify adaptive loci in Upland cotton. Two highly divergent genomic regions were found on chromosomes A06 and A08, which likely caused by extensive chromosome inversions. The subgroups could be geographically classified based on distinct haplotypes in the divergent regions. A genome-wide association study (GWAS) also confirmed that loci located in these regions were significantly associated with environmental adaptability in Upland cotton. Our study first revealed the cause of population divergence in Upland cotton, as well as the consequences of variation in its environmental adaptability. These findings provide new insights into the genetic basis of environmental adaptability in Upland cotton, which could accelerate the development of molecular markers for adaptation to climate change in future cotton breeding.

Gene flow as a simple cause for an excess of high-frequency-derived alleles

Most human populations exhibit an excess of high-frequency variants, leading to a U-shaped site-frequency spectrum (uSFS). This pattern has been generally interpreted as a signature of ongoing episodes of positive selection, or as evidence for a mis-assignment of ancestral/derived allelic states, but uSFS has also been observed in populations receiving gene flow from a ghost population, in structured populations, or after range expansions. In order to better explain the prevalence of high-frequency variants in humans and other populations, we describe here which patterns of gene flow and population demography can lead to uSFS by using extensive coalescent simulations. We find that uSFS can often be observed in a population if gene flow brings a few ancestral alleles from a well-differentiated population. Gene flow can either consist in single pulses of admixture or continuous immigration, but different demographic conditions are necessary to observe uSFS in these two scenarios. Indeed, an extremely low and recent gene flow is required in the case of single admixture events, while with continuous immigration, uSFS occurs only if gene flow started recently at a high rate or if it lasted for a long time at a low rate. Overall, we find that a neutral uSFS occurs under more restrictive conditions in populations having received single pulses of gene flow than in populations exposed to continuous gene flow. We also show that the uSFS observed in human populations from the 1000 Genomes Project can easily be explained by gene flow from surrounding populations without requiring past episodes of positive selection. These results imply that uSFS should be common in non-isolated populations, such as most wild or domesticated plants and animals.

Predicting Thermal Adaptation by Looking Into Populations' Genomic Past

Molecular evolution offers an insightful theory to interpret the genomic consequences of thermal adaptation to previous events of climate change beyond range shifts. However, disentangling often mixed footprints of selective and demographic processes from those due to lineage sorting, recombination rate variation, and genomic constrains is not trivial. Therefore, here we condense current and historical population genomic tools to study thermal adaptation and outline key developments (genomic prediction, machine learning) that might assist their utilization for improving forecasts of populations' responses to thermal variation. We start by summarizing how recent thermal-driven selective and demographic responses can be inferred by coalescent methods and in turn how quantitative genetic theory offers suitable multi-trait predictions over a few generations via the breeder's equation. We later assume that enough generations have passed as to display genomic signatures of divergent selection to thermal variation and describe how these footprints can be reconstructed using genome-wide association and selection scans or, alternatively, may be used for forward prediction over multiple generations under an infinitesimal genomic prediction model. Finally, we move deeper in time to comprehend the genomic consequences of thermal shifts at an evolutionary time scale by relying on phylogeographic approaches that allow for reticulate evolution and ecological parapatric speciation, and end by envisioning the potential of modern machine learning techniques to better inform long-term predictions. We conclude that foreseeing future thermal adaptive responses requires bridging the multiple spatial scales of historical and predictive environmental change research under modern cohesive approaches such as genomic prediction and machine learning frameworks.

Genomic insight into the developmental history of southern highbush blueberry populations

Interspecific hybridization is a common breeding approach for introducing novel traits and genetic diversity to breeding populations. Southern highbush blueberry (SHB) is a blueberry cultivar group that has been intensively bred over the last 60 years. Specifically, it was developed by multiple interspecific crosses between northern highbush blueberry [NHB, Vaccinium corymbosum L. (2n = 4x = 48)] and low-chill Vaccinium species to expand the geographic limits of highbush blueberry production. In this study, we genotyped polyploid blueberries, including 105 SHB, 17 NHB, and 10 rabbiteye blueberry (RE) (Vaccinium virgatum Aiton), from the accessions planted at Poplarville, Mississippi, and accessions distributed in Japan, based on the double-digest restriction site-associated DNA sequencing. The genome-wide SNP data clearly indicated that RE cultivars were genetically distinct from SHB and NHB cultivars, whereas NHB and SHB were genetically indistinguishable. The population structure results appeared to reflect the differences in the allele selection strategies that breeders used for developing germplasm adapted to local climates. The genotype data implied that there are no or very few genomic segments that were commonly introgressed from low-chill Vaccinium species to the SHB genome. Principal component analysis-based outlier detection analysis found a few loci associated with a variable that could partially differentiate NHB and SHB. These SNP loci were detected in Mb-scale haplotype blocks and may be close to the functional genes related to SHB development. Collectively, the data generated in this study suggest a polygenic adaptation of SHB to the southern climate, and may be relevant for future population-scale genome-wide analyses of blueberry.

Polygenic Adaptation in a Population of Finite Size

Polygenic adaptation in response to selection on quantitative traits has become an important topic in evolutionary biology. Here we review the recent literature on models of polygenic adaptation. In particular, we focus on a model that includes mutation and both directional and stabilizing selection on a highly polygenic trait in a population of finite size (thus experiencing random genetic drift). Assuming that a sudden environmental shift of the fitness optimum occurs while the population is in a stochastic equilibrium, we analyze the adaptation of the trait to the new optimum. When the shift is not too large relative to the equilibrium genetic variance and this variance is determined by loci with mostly small effects, the approach of the mean phenotype to the optimum can be approximated by a rapid exponential process (whose rate is proportional to the genetic variance). During this rapid phase the underlying changes to allele frequencies, however, may depend strongly on genetic drift. While trait-increasing alleles with intermediate equilibrium frequencies are dominated by selection and contribute positively to changes of the trait mean (i.e., are aligned with the direction of the optimum shift), alleles with low or high equilibrium frequencies show more of a random dynamics, which is expected when drift is dominating. A strong effect of drift is also predicted for population size bottlenecks. Our simulations show that the presence of a bottleneck results in a larger deviation of the population mean of the trait from the fitness optimum, which suggests that more loci experience the influence of drift.

Consequences of Single-Locus and Tightly Linked Genomic Architectures for Evolutionary Responses to Environmental Change

Genetic and genomic architectures of traits under selection are key factors influencing evolutionary responses. Yet, knowledge of their impacts has been limited by a widespread assumption that most traits are controlled by unlinked polygenic architectures. Recent advances in genome sequencing and eco-evolutionary modeling are unlocking the potential for integrating genomic information into predictions of population responses to environmental change. Using eco-evolutionary simulations, we demonstrate that hypothetical single-locus control of a life history trait produces highly variable and unpredictable harvesting-induced evolution relative to the classically applied multilocus model. Single-locus control of complex traits is thought to be uncommon, yet blocks of linked genes, such as those associated with some types of structural genomic variation, have emerged as taxonomically widespread phenomena. Inheritance of linked architectures resembles that of single loci, thus enabling single-locus-like modeling of polygenic adaptation. Yet, the number of loci, their effect sizes, and the degree of linkage among them all occur along a continuum. We review how linked architectures are often associated, directly or indirectly, with traits expected to be under selection from anthropogenic stressors and are likely to play a large role in adaptation to environmental disturbance. We suggest using single-locus models to explore evolutionary extremes and uncertainties when the trait architecture is unknown, refining parameters as genomic information becomes available, and explicitly incorporating linkage among loci when possible. By overestimating the complexity (e.g., number of independent loci) of the genomic architecture of traits under selection, we risk underestimating the complexity (e.g., nonlinearity) of their evolutionary dynamics.

Rapid evolution in plant-microbe interactions - an evolutionary genomics perspective

Access to greater genomic resolution through new sequencing technologies is transforming the field of plant pathology. As scientists embrace these new methods, some overarching patterns and observations come into focus. Evolutionary genomic studies are used to determine not only the origins of pathogen lineages and geographic patterns of genetic diversity, but also to discern how natural selection structures genetic variation across the genome. With greater and greater resolution, we can now pinpoint the targets of selection on a large scale. At multiple levels, crypsis and convergent evolution are evident. Host jumps and shifts may be more pervasive than once believed, and hybridization and horizontal gene transfer (HGT) likely play important roles in the emergence of genetic novelty.

Comparative genomics approach to evolutionary process connectivity

The influence of species life history traits and historical demography on contemporary connectivity is still poorly understood. However, these factors partly determine the evolutionary responses of species to anthropogenic landscape alterations. Genetic connectivity and its evolutionary outcomes depend on a variety of spatially dependent evolutionary processes, such as population structure, local adaptation, genetic admixture, and speciation. Over the last years, population genomic studies have been interrogating these processes with increasing resolution, revealing a large diversity of species responses to spatially structured landscapes. In parallel, multispecies meta-analyses usually based on low-genome coverage data have provided fundamental insights into the ecological determinants of genetic connectivity, such as the influence of key life history traits on population structure. However, comparative studies still lack a thorough integration of macro- and micro-evolutionary scales to fully realize their potential. Here, I present how a comparative genomics framework may provide a deeper understanding of evolutionary process connectivity. This framework relies on coupling the inference of long-term demographic and selective history with an assessment of the contemporary consequences of genetic connectivity. Standardizing this approach across several species occupying the same landscape should help understand how spatial environmental heterogeneity has shaped the diversity of historical and contemporary connectivity patterns in different taxa with contrasted life history traits. I will argue that a reasonable amount of genome sequence data can be sufficient to resolve and connect complex macro- and micro-evolutionary histories. Ultimately, implementing this framework in varied taxonomic groups is expected to improve scientific guidelines for conservation and management policies.

Inference of past demography, dormancy and self-fertilization rates from whole genome sequence data

Several methods based on the Sequential Markovian coalescence (SMC) have been developed that make use of genome sequence data to uncover population demographic history, which is of interest in its own right and is a key requirement to generate a null model for selection tests. While these methods can be applied to all possible kind of species, the underlying assumptions are sexual reproduction in each generation and non-overlapping generations. However, in many plants, invertebrates, fungi and other taxa, those assumptions are often violated due to different ecological and life history traits, such as self-fertilization or long term dormant structures (seed or egg-banking). We develop a novel SMC-based method to infer 1) the rates/parameters of dormancy and of self-fertilization, and 2) the populations' past demographic history. Using simulated data sets, we demonstrate the accuracy of our method for a wide range of demographic scenarios and for sequence lengths from one to 30 Mb using four sampled genomes. Finally, we apply our method to a Swedish and a German population of Arabidopsis thaliana demonstrating a selfing rate of ca. 0.87 and the absence of any detectable seed-bank. In contrast, we show that the water flea Daphnia pulex exhibits a long lived egg-bank of three to 18 generations. In conclusion, we here present a novel method to infer accurate demographies and life-history traits for species with selfing and/or seed/egg-banks. Finally, we provide recommendations for the use of SMC-based methods for non-model organisms, highlighting the importance of the per site and the effective ratios of recombination over mutation.

Genetic susceptibility to severe childhood asthma and rhinovirus-C maintained by balancing selection in humans for 150 000 years

Selective pressures imposed by pathogens have varied among human populations throughout their evolution, leading to marked inter-population differences at some genes mediating susceptibility to infectious and immune-related diseases. Here, we investigated the evolutionary history of a common polymorphism resulting in a Y529 versus C529 change in the cadherin related family member 3 (CDHR3) receptor which underlies variable susceptibility to rhinovirus-C infection and is associated with severe childhood asthma. The protective variant is the derived allele and is found at high frequency worldwide (69-95%). We detected genome-wide significant signatures of natural selection consistent with a rapid increase of the haplotypes carrying the allele, suggesting that non-neutral processes have acted on this locus across all human populations. However, the allele has not fixed in any population despite multiple lines of evidence suggesting that the mutation predates human migrations out of Africa. Using an approximate Bayesian computation method, we estimate the age of the mutation while explicitly accounting for past demography and positive or frequency-dependent balancing selection. Our analyses indicate a single emergence of the mutation in anatomically modern humans ~150 000 years ago and indicate that balancing selection has maintained the beneficial allele at high equilibrium frequencies worldwide. Apart from the well-known cases of the MHC and ABO genes, this study provides the first evidence that negative frequency-dependent selection plausibly acted on a human disease susceptibility locus, a form of balancing selection compatible with typical transmission dynamics of communicable respiratory viruses that might exploit CDHR3.

Selective Sweeps Under Dominance and Inbreeding

A major research goal in evolutionary genetics is to uncover loci experiencing positive selection. One approach involves finding 'selective sweeps' patterns, which can either be 'hard sweeps' formed by de novo mutation, or 'soft sweeps' arising from recurrent mutation or existing standing variation. Existing theory generally assumes outcrossing populations, and it is unclear how dominance affects soft sweeps. We consider how arbitrary dominance and inbreeding via self-fertilization affect hard and soft sweep signatures. With increased self-fertilization, they are maintained over longer map distances due to reduced effective recombination and faster beneficial allele fixation times. Dominance can affect sweep patterns in outcrossers if the derived variant originates from either a single novel allele, or from recurrent mutation. These models highlight the challenges in distinguishing hard and soft sweeps, and propose methods to differentiate between scenarios.