Polygenic adaptation: a unifying framework to understand positive selection

Scots pine - panmixia and the elusive signal of genetic adaptation

Scots pine is the foundation species of diverse forested ecosystems across Eurasia and displays remarkable ecological breadth, occurring in environments ranging from temperate rainforests to arid tundra margins. Such expansive distributions can be favored by various demographic and adaptive processes and the interactions between them. To understand the impact of neutral and selective forces on genetic structure in Scots pine, we conducted range-wide population genetic analyses on 2321 trees from 202 populations using genotyping-by-sequencing, reconstructed the recent demography of the species and examined signals of genetic adaptation. We found a high and uniform genetic diversity across the entire range (global FST 0.048), no increased genetic load in expanding populations and minor impact of the last glacial maximum on historical population sizes. Genetic-environmental associations identified only a handful of single-nucleotide polymorphisms significantly linked to environmental gradients. The results suggest that extensive gene flow is predominantly responsible for the observed genetic patterns in Scots pine. The apparent missing signal of genetic adaptation is likely attributed to the intricate genetic architecture controlling adaptation to multi-dimensional environments. The panmixia metapopulation of Scots pine offers a good study system for further exploration into how genetic adaptation and plasticity evolve under gene flow and changing environment.

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.

Polygenic adaptation of a cosmopolitan pest to a novel thermal environment

The fluctuation in temperature poses a significant challenge for poikilothermic organisms, notably insects, particularly in the context of changing climatic conditions. In insects, temperature adaptation has been driven by polygenes. In addition to genes that directly affect traits (core genes), other genes (peripheral genes) may also play a role in insect temperature adaptation. This study focuses on two peripheral genes, the GRIP and coiled-coil domain containing 2 (GCC2) and karyopherin subunit beta 1 (KPNB1). These genes are differentially expressed at different temperatures in the cosmopolitan pest, Plutella xylostella. GCC2 and KPNB1 in P. xylostella were cloned, and their relative expression patterns were identified. Reduced capacity for thermal adaptation (development, reproduction and response to temperature extremes) in the GCC2-deficient and KPNB1-deficient P. xylostella strains, which were constructed by CRISPR/Cas9 technique. Deletion of the PxGCC2 or PxKPNB1 genes in P. xylostella also had a differential effect on gene expression for many traits including stress resistance, resistance to pesticides, involved in immunity, trehalose metabolism, fatty acid metabolism and so forth. The ability of the moth to adapt to temperature via different pathways is likely to be key to its ability to remain an important pest species under predicted climate change conditions.

Alternative splicing in parallel evolution and the evolutionary potential in sticklebacks

Repeatability of adaptation to similar environments provides opportunity to evaluate the predictability of natural selection. While many studies have investigated gene expression differences between populations adapted to contrasting environments, the role of post-transcriptional processes such as alternative splicing has rarely been evaluated in the context of parallel adaptation. To address the aforementioned knowledge gap, we reanalysed transcriptomic data from three pairs of threespine stickleback (Gasterosteus aculeatus) ecotypes adapted to marine or freshwater environment. First, we identified genes with repeated expression or splicing divergence across ecotype pairs, and compared the genetic architecture and biological processes between parallelly expressed and parallelly spliced loci. Second, we analysed the extent to which parallel adaptation was reflected at gene expression and alternative splicing levels. Finally, we tested how the two axes of transcriptional variation differed in their potential for evolutionary change. Although both repeated differential splicing and differential expression across ecotype pairs showed tendency for parallel divergence, the degree of parallelism was lower for splicing than expression. Furthermore, parallel divergences in splicing and expression were likely to be associated with distinct cis-regulatory genetic variants and functionally unique set of genes. Finally, we found that parallelly spliced genes showed higher nucleotide diversity than parallelly expressed genes, indicating splicing is less susceptible to genetic variation erosion during parallel adaptation. Our results provide novel insight into the role of splicing in parallel adaptation, and underscore the contribution of splicing to the evolutionary potential of wild populations under environmental change.

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.

Analysis of Evolutionary Conservation, Expression Level, and Genetic Association at a Genome-wide Scale Reveals Heterogeneity Across Polygenic Phenotypes

Understanding the expression level and evolutionary rate of associated genes with human polygenic diseases provides crucial insights into their disease-contributing roles. In this work, we leveraged genome-wide association studies (GWASs) to investigate the relationship between the genetic association and both the evolutionary rate (dN/dS) and expression level of human genes associated with the two polygenic diseases of schizophrenia and coronary artery disease. Our findings highlight a distinct variation in these relationships between the two diseases. Genes associated with both diseases exhibit a significantly greater variance in evolutionary rate compared to those implicated in monogenic diseases. Expanding our analyses to 4,756 complex traits in the GWAS atlas database, we unraveled distinct trait categories with a unique interplay among the evolutionary rate, expression level, and genetic association of human genes. In most polygenic traits, highly expressed genes were more associated with the polygenic phenotypes compared to lowly expressed genes. About 69% of polygenic traits displayed a negative correlation between genetic association and evolutionary rate, while approximately 30% of these traits showed a positive correlation between genetic association and evolutionary rate. Our results demonstrate the presence of a spectrum among complex traits, shaped by natural selection. Notably, at opposite ends of this spectrum, we find metabolic traits being more likely influenced by purifying selection, and immunological traits that are more likely shaped by positive selection. We further established the polygenic evolution portal (evopolygen.de) as a resource for investigating relationships and generating hypotheses in the field of human polygenic trait evolution.

Across two continents: The genomic basis of environmental adaptation in house mice (Mus musculus domesticus) from the Americas

Replicated clines across environmental gradients can be strong evidence of adaptation. House mice (Mus musculus domesticus) were introduced to the Americas by European colonizers and are now widely distributed from Tierra del Fuego to Alaska. Multiple aspects of climate, such as temperature, vary predictably across latitude in the Americas. Past studies of North American populations across latitudinal gradients provided evidence of environmental adaptation in traits related to body size, metabolism, and behavior and identified candidate genes using selection scans. Here, we investigate genomic signals of environmental adaptation on a second continent, South America, and ask whether there is evidence of parallel adaptation across multiple latitudinal transects in the Americas. We first identified loci across the genome showing signatures of selection related to climatic variation in mice sampled across a latitudinal transect in South America, accounting for neutral population structure. Consistent with previous results, most candidate SNPs were in putatively regulatory regions. Genes that contained the most extreme outliers relate to traits such as body weight or size, metabolism, immunity, fat, eye function, and the cardiovascular system. We then compared these results with the results of analyses of published data from two transects in North America. While most candidate genes were unique to individual transects, we found significant overlap among candidate genes identified independently in the three transects. These genes are diverse, with functions relating to metabolism, immunity, cardiac function, and circadian rhythm, among others. We also found parallel shifts in allele frequency in candidate genes across latitudinal gradients. Finally, combining data from all three transects, we identified several genes associated with variation in body weight. Overall, our results provide strong evidence of shared responses to selection and identify genes that likely underlie recent environmental adaptation in house mice across North and South America.

Heritability of complex traits in sub-populations experiencing bottlenecks and growth

Populations that have experienced a bottleneck are regularly used in Genome Wide Association Studies (GWAS) to investigate variants associated with complex traits. It is generally understood that these isolated sub-populations may experience high frequency of otherwise rare variants with large effect size, and therefore provide a unique opportunity to study said trait. However, the demographic history of the population under investigation affects all SNPs that determine the complex trait genome-wide, changing its heritability and genetic architecture. We use a simulation based approach to identify the impact of the demographic processes of drift, expansion, and migration on the heritability of complex trait. We show that demography has considerable impact on complex traits. We then investigate the power to resolve heritability of complex traits in GWAS studies subjected to demographic effects. We find that demography is an important component for interpreting inference of complex traits and has a nuanced impact on the power of GWAS. We conclude that demographic histories need to be explicitly modelled to properly quantify the history of selection on a complex trait.

Evolutionary ecology of denitrifying methanotrophic NC10 bacteria in the deep-sea biosphere

The NC10 phylum links anaerobic methane oxidation to nitrite denitrification through a unique O2-producing intra-aerobic methanotrophic pathway. Although numerous amplicon-based studies revealed the distribution of this phylum, comprehensive genomic insights and niche characterization in deep-sea environments were still largely unknown. In this study, we extensively surveyed the NC10 bacteria across diverse deep-sea environments, including waters, sediments, cold seeps, biofilms, rocky substrates, and subseafloor aquifers. We then reconstructed and analysed 38 metagenome-assembled genomes (MAGs), and revealed the extensive distribution of NC10 bacteria and their intense selective pressure in these harsh environments. Isotopic analyses combined with gene expression profiling confirmed that active nitrite-dependent anaerobic methane oxidation (n-DAMO) occurs within deep-sea sediments. In addition, the identification of the Wood-Ljungdahl (WL) and 3-hydroxypropionate/4-hydroxybutyrat (3HB/4HP) pathways in these MAGs suggests their capability for carbon fixation as chemoautotrophs in these deep-sea environments. Indeed, we found that for their survival in the oligotrophic deep-sea biosphere, NC10 bacteria encode two branches of the WL pathway, utilizing acetyl-CoA from the carbonyl branch for citric acid cycle-based energy production and methane from the methyl branch for n-DAMO. The observed low ratios of non-synonymous substitutions to synonymous substitutions (pN/pS) in n-DAMO-related genes across these habitats suggest a pronounced purifying selection that is critical for the survival of NC10 bacteria in oligotrophic deep-sea environments. These findings not only advance our understanding of the evolutionary adaptations of NC10 bacteria but also underscore the intricate coupling between the carbon and nitrogen cycles within deep-sea ecosystems, driven by this bacterial phylum.

Limited evidence for genetic differentiation or adaptation in two amphibian species across replicated rural-urban gradients

Urbanization leads to complex environmental changes and poses multiple challenges to organisms. Amphibians are highly susceptible to the effects of urbanization, with land use conversion, habitat destruction, and degradation ranked as the most significant threats. Consequently, amphibians are declining in urban areas, in both population numbers and abundance, however, the effect of urbanization on population genetic parameters remains unclear. Here, we studied the genomic response to urbanization in two widespread European species, the common toad Bufo bufo (26 localities, 480 individuals), and the smooth newt Lissotriton vulgaris (30 localities, 516 individuals) in three geographic regions: southern and northern Poland and southern Norway. We assessed genome-wide SNP variation using RADseq (ca. 42 and 552 thousand SNPs in toads and newts, respectively) and adaptively relevant major histocompatibility complex (MHC) class I and II genes. The results linked most of the genetic differentiation in both marker types to regional (latitudinal) effects, which also correspond to historical biogeography. Further, we did not find any association between genetic differentiation and level of urbanization at local scales for either species. However, urban smooth newts, but not toads, have lower levels of within-population genome-wide diversity, suggesting higher susceptibility to the negative effects of urbanization. A decreasing level of genetic diversity linked to increasing urbanization was also found for MHC II in smooth newts, while the relationship between MHC class I diversity and urbanization differed between geographic regions. We did not find any effects of urbanization on MHC diversity in the toad populations. Although two genetic environment association analyses of genome-wide data, LFMM and BayPass, revealed numerous (219 in B. bufo and 7040 in L. vulgaris) SNPs statistically associated with urbanization, we found a marked lack of repeatability between geographic regions, suggesting a complex and multifaceted response to natural selection elicited by life in the city.

Study on the detection rate, genetic polymorphism, viral load, persistent infection capacity, and pathogenicity of human papillomavirus type 81

Human papillomavirus (HPV) type 81 has recently become one of the most common low-risk HPV types; however, literature focusing on it is limited. This study aimed to analyze the reasons for the increased detection rate of HPV81 and investigate its evolving pathogenicity. We analyzed the detection rates and trends of HPV81 in 229 061 exfoliated cervical cell samples collected from 2014 to 2023; collected samples of HPV81 single infections from two different time periods; and analyzed the allele frequencies, positive selection, viral load, persistent infection capacity, and pathogenicity of E6 and E7 genotypes. We found that the detection rate of HPV81 ranked first among the low-risk types in exfoliated cervical cells and exhibited a significantly increasing trend (p < 0.001). The frequency of the E6 prototype allele of HPV81 (n = 317) was significantly increased (p = 0.018) and demonstrated the strongest adaptive capacity. The viral load and persistent infection capacity of the E6 prototype were significantly higher than those of the mutants, thus serving as key drivers for increasing the detection rate of HPV81 and enhancing its pathogenicity. The viral load was positively correlated with persistent infection capacity and pathogenicity. Persistent infection was a crucial factor in the pathogenicity of HPV81. Successful adaptive evolution of HPV81 is accompanied by enhanced pathogenicity.

Reproductive isolation arises during laboratory adaptation to a novel hot environment

BACKGROUND

Reproductive isolation can result from adaptive processes (e.g., ecological speciation and mutation-order speciation) or stochastic processes such as "system drift" model. Ecological speciation predicts barriers to gene flow between populations from different environments, but not among replicate populations from the same environment. In contrast, reproductive isolation among populations independently adapted to the same/similar environment can arise from both mutation-order speciation or system drift.

RESULTS

In experimentally evolved populations adapting to a hot environment for over 100 generations, we find evidence for pre- and postmating reproductive isolation. On one hand, an altered lipid metabolism and cuticular hydrocarbon composition pointed to possible premating barriers between the ancestral and replicate evolved populations. On the other hand, the pronounced gene expression differences in male reproductive genes may underlie the postmating isolation among replicate evolved populations adapting to the same environment with the same standing genetic variation.

CONCLUSION

Our study confirms that replicated evolution experiments provide valuable insights into the mechanisms of speciation. The rapid emergence of the premating reproductive isolation during temperature adaptation showcases incipient ecological speciation. The potential evidence of postmating reproductive isolation among replicates gave rise to two hypotheses: (1) mutation-order speciation through a common selection on early fecundity leading to an inherent inter-locus sexual conflict; (2) system drift with genetic drift along the neutral ridges.

Abiotic Stress Tolerance Boosted by Genetic Diversity in Plants

Plant breeding [...].

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.

Leveraging functional genomic annotations and genome coverage to improve polygenic prediction of complex traits within and between ancestries

We develop a method, SBayesRC, that integrates genome-wide association study (GWAS) summary statistics with functional genomic annotations to improve polygenic prediction of complex traits. Our method is scalable to whole-genome variant analysis and refines signals from functional annotations by allowing them to affect both causal variant probability and causal effect distribution. We analyze 50 complex traits and diseases using ∼7 million common single-nucleotide polymorphisms (SNPs) and 96 annotations. SBayesRC improves prediction accuracy by 14% in European ancestry and up to 34% in cross-ancestry prediction compared to the baseline method SBayesR, which does not use annotations, and outperforms other methods, including LDpred2, LDpred-funct, MegaPRS, PolyPred-S and PRS-CSx. Investigation of factors affecting prediction accuracy identifies a significant interaction between SNP density and annotation information, suggesting whole-genome sequence variants with annotations may further improve prediction. Functional partitioning analysis highlights a major contribution of evolutionary constrained regions to prediction accuracy and the largest per-SNP contribution from nonsynonymous SNPs.

The distribution of fitness effects during adaptive walks using a simple genetic network

The tempo and mode of adaptation depends on the availability of beneficial alleles. Genetic interactions arising from gene networks can restrict this availability. However, the extent to which networks affect adaptation remains largely unknown. Current models of evolution consider additive genotype-phenotype relationships while often ignoring the contribution of gene interactions to phenotypic variance. In this study, we model a quantitative trait as the product of a simple gene regulatory network, the negative autoregulation motif. Using forward-time genetic simulations, we measure adaptive walks towards a phenotypic optimum in both additive and network models. A key expectation from adaptive walk theory is that the distribution of fitness effects of new beneficial mutations is exponential. We found that both models instead harbored distributions with fewer large-effect beneficial alleles than expected. The network model also had a complex and bimodal distribution of fitness effects among all mutations, with a considerable density at deleterious selection coefficients. This behavior is reminiscent of the cost of complexity, where correlations among traits constrain adaptation. Our results suggest that the interactions emerging from genetic networks can generate complex and multimodal distributions of fitness effects.

Evolution of Phenotypic Variance Provides Insights into the Genetic Basis of Adaptation

Most traits are polygenic, and the contributing loci can be identified by genome-wide association studies. The genetic basis of adaptation (adaptive architecture) is, however, difficult to characterize. Here, we propose to study the adaptive architecture of traits by monitoring the evolution of their phenotypic variance during adaptation to a new environment in well-defined laboratory conditions. Extensive computer simulations show that the evolution of phenotypic variance in a replicated experimental evolution setting can distinguish between oligogenic and polygenic adaptive architectures. We compared gene expression variance in male Drosophila simulans before and after 100 generations of adaptation to a novel hot environment. The variance change in gene expression was indistinguishable for genes with and without a significant change in mean expression after 100 generations of evolution. We suggest that the majority of adaptive gene expression evolution can be explained by a polygenic architecture. We propose that tracking the evolution of phenotypic variance across generations can provide an approach to characterize the adaptive architecture.

Genomic insights into Yak (Bos grunniens) adaptations for nutrient assimilation in high-altitudes

High-altitude environments present formidable challenges for survival and reproduction, with organisms facing limited oxygen availability and scarce nutrient resources. The yak (Bos grunniens), indigenous to the Tibetan Plateau, has notably adapted to these extreme conditions. This study delves into the genomic basis of the yak's adaptation, focusing on the positive selection acting on genes involved in nutrient assimilation pathways. Employing techniques in comparative genomics and molecular evolutionary analyses, we selected genes in the yak that show signs of positive selection associated with nutrient metabolism, absorption, and transport. Our findings reveal specific genetic adaptations related to nutrient metabolism in harsh climatic conditions. Notably, genes involved in energy metabolism, oxygen transport, and thermoregulation exhibited signs of positive selection, suggesting their crucial role in the yak's successful colonization of high-altitude regions. The study also sheds light on the yak's immune system adaptations, emphasizing genes involved in response to various stresses prevalent at elevated altitudes. Insights into the yak's genomic makeup provide valuable information for understanding the broader implications of high-altitude adaptations in mammalian evolution. They may contribute to efforts in enhancing livestock resilience to environmental challenges.

Rapid and Repeated Climate Adaptation Involving Chromosome Inversions following Invasion of an Insect

Following invasion, insects can become adapted to conditions experienced in their invasive range, but there are few studies on the speed of adaptation and its genomic basis. Here, we examine a small insect pest, Thrips palmi, following its contemporary range expansion across a sharp climate gradient from the subtropics to temperate areas. We first found a geographically associated population genetic structure and inferred a stepping-stone dispersal pattern in this pest from the open fields of southern China to greenhouse environments of northern regions, with limited gene flow after colonization. In common garden experiments, both the field and greenhouse groups exhibited clinal patterns in thermal tolerance as measured by critical thermal maximum (CTmax) closely linked with latitude and temperature variables. A selection experiment reinforced the evolutionary potential of CTmax with an estimated h2 of 6.8% for the trait. We identified 3 inversions in the genome that were closely associated with CTmax, accounting for 49.9%, 19.6%, and 8.6% of the variance in CTmax among populations. Other genomic variations in CTmax outside the inversion region were specific to certain populations but functionally conserved. These findings highlight rapid adaptation to CTmax in both open field and greenhouse populations and reiterate the importance of inversions behaving as large-effect alleles in climate adaptation.

Dissecting the genetic architecture of quantitative traits using genome-wide identity-by-descent sharing

Additive and dominance genetic variances underlying the expression of quantitative traits are important quantities for predicting short-term responses to selection, but they are notoriously challenging to estimate in most non-model wild populations. Specifically, large-sized or panmictic populations may be characterized by low variance in genetic relatedness among individuals which, in turn, can prevent accurate estimation of quantitative genetic parameters. We used estimates of genome-wide identity-by-descent (IBD) sharing from autosomal SNP loci to estimate quantitative genetic parameters for ecologically important traits in nine-spined sticklebacks (Pungitius pungitius) from a large, outbred population. Using empirical and simulated datasets, with varying sample sizes and pedigree complexity, we assessed the performance of different crossing schemes in estimating additive genetic variance and heritability for all traits. We found that low variance in relatedness characteristic of wild outbred populations with high migration rate can impair the estimation of quantitative genetic parameters and bias heritability estimates downwards. On the other hand, the use of a half-sib/full-sib design allowed precise estimation of genetic variance components and revealed significant additive variance and heritability for all measured traits, with negligible dominance contributions. Genome-partitioning and QTL mapping analyses revealed that most traits had a polygenic basis and were controlled by genes at multiple chromosomes. Furthermore, different QTL contributed to variation in the same traits in different populations suggesting heterogeneous underpinnings of parallel evolution at the phenotypic level. Our results provide important guidelines for future studies aimed at estimating adaptive potential in the wild, particularly for those conducted in outbred large-sized populations.

Genomic architecture controls multivariate adaptation to climate change

As climate change advances, environmental gradients may decouple, generating novel multivariate environments that stress wild populations. A commonly invoked mechanism of evolutionary rescue is adaptive gene flow tracking climate shifts, but gene flow from populations inhabiting similar conditions on one environmental axis could cause maladaptive introgression when populations are adapted to different environmental variables that do not shift together. Genomic architecture can play an important role in determining the effectiveness and relative magnitudes of adaptive gene flow and in situ adaptation. This may have direct consequences for how species respond to climate change but is often overlooked. Here, we simulated microevolutionary responses to environmental change under scenarios defined by variation in the polygenicity, linkage, and genetic redundancy of two independent traits, one of which is adapted to a gradient that shifts under climate change. We used these simulations to examine how genomic architecture influences evolutionary outcomes under climate change. We found that climate-tracking (up-gradient) gene flow, though present in all scenarios, was strongly constrained under scenarios of lower linkage and higher polygenicity and redundancy, suggesting in situ adaptation as the predominant mechanism of evolutionary rescue under these conditions. We also found that high polygenicity caused increased maladaptation and demographic decline, a concerning result given that many climate-adapted traits may be polygenic. Finally, in scenarios with high redundancy, we observed increased adaptive capacity. This finding adds to the growing recognition of the importance of redundancy in mediating in situ adaptive capacity and suggests opportunities for better understanding the climatic vulnerability of real populations.

Genetics and the Evolution of Prezygotic Isolation

The significance of prezygotic isolation for speciation has been recognized at least since the Modern Synthesis. However, fundamental questions remain. For example, how are genetic associations between traits that contribute to prezygotic isolation maintained? What is the source of genetic variation underlying the evolution of these traits? And how do prezygotic barriers affect patterns of gene flow? We address these questions by reviewing genetic features shared across plants and animals that influence prezygotic isolation. Emerging technologies increasingly enable the identification and functional characterization of the genes involved, allowing us to test established theoretical expectations. Embedding these genes in their developmental context will allow further predictions about what constrains the evolution of prezygotic isolation. Ongoing improvements in statistical and computational tools will reveal how pre- and postzygotic isolation may differ in how they influence gene flow across the genome. Finally, we highlight opportunities for progress by combining theory with appropriate data.

Rapid genomic evolution in Brassica rapa with bumblebee selection in experimental evolution

BACKGROUND

Insect pollinators shape rapid phenotypic evolution of traits related to floral attractiveness and plant reproductive success. However, the underlying genomic changes remain largely unknown despite their importance in predicting adaptive responses to natural or to artificial selection. Based on a nine-generation experimental evolution study with fast cycling Brassica rapa plants adapting to bumblebees, we investigate the genomic evolution associated with the previously observed parallel phenotypic evolution. In this current evolve and resequencing (E&R) study, we conduct a genomic scan of the allele frequency changes along the genome in bumblebee-pollinated and hand-pollinated plants and perform a genomic principal component analysis (PCA).

RESULTS

We highlight rapid genomic evolution associated with the observed phenotypic evolution mediated by bumblebees. Controlling for genetic drift, we observe significant changes in allelic frequencies at multiple loci. However, this pattern differs according to the replicate of bumblebee-pollinated plants, suggesting putative non-parallel genomic evolution. Finally, our study underlines an increase in genomic variance implying the putative involvement of multiple loci in short-term pollinator adaptation.

CONCLUSIONS

Overall, our study enhances our understanding of the complex interactions between pollinator and plants, providing a stepping stone towards unravelling the genetic basis of plant genomic adaptation to biotic factors in the environment.

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.

Across two continents: the genomic basis of environmental adaptation in house mice (Mus musculus domesticus) from the Americas

Parallel clines across environmental gradients can be strong evidence of adaptation. House mice (Mus musculus domesticus) were introduced to the Americas by European colonizers and are now widely distributed from Tierra del Fuego to Alaska. Multiple aspects of climate, such as temperature, vary predictably across latitude in the Americas. Past studies of North American populations across latitudinal gradients provided evidence of environmental adaptation in traits related to body size, metabolism, and behavior and identified candidate genes using selection scans. Here, we investigate genomic signals of environmental adaptation on a second continent, South America, and ask whether there is evidence of parallel adaptation across multiple latitudinal transects in the Americas. We first identified loci across the genome showing signatures of selection related to climatic variation in mice sampled across a latitudinal transect in South America, accounting for neutral population structure. Consistent with previous results, most candidate SNPs were in regulatory regions. Genes containing the most extreme outliers relate to traits such as body weight or size, metabolism, immunity, fat, and development or function of the eye as well as traits associated with the cardiovascular and renal systems. We then combined these results with published results from two transects in North America. While most candidate genes were unique to individual transects, we found significant overlap among candidate genes identified independently in the three transects, providing strong evidence of parallel adaptation and identifying genes that likely underlie recent environmental adaptation in house mice across North and South America.

The genomic response to urbanization in the damselfly Ischnura elegans

The complex and rapid environmental changes brought about by urbanization pose significant challenges to organisms. The multifaceted effects of urbanization often make it difficult to define and pinpoint the very nature of adaptive urban phenotypes. In such situations, scanning genomes for regions differentiated between urban and non-urban populations may be an attractive approach. Here, we investigated the genomic signatures of adaptation to urbanization in the damselfly Ischnura elegans sampled from 31 rural and urban localities in three geographic regions: southern and northern Poland, and southern Sweden. Genome-wide variation was assessed using more than 370,000 single nucleotide polymorphisms (SNPs) genotyped by ddRADseq. Associations between SNPs and the level of urbanization were tested using two genetic environment association methods: Latent Factors Mixed Models and BayPass. While we found numerous candidate SNPs and a highly significant overlap between candidates identified by the two methods within the geographic regions, there was a distinctive lack of repeatability between the geographic regions both at the level of individual SNPs and of genomic regions. However, we found "synapse organization" at the top of the functional categories enriched among the genes located in the proximity of the candidate urbanization SNPs. Interestingly, the overall significance of "synapse organization" was built up by the accretion of different genes associated with candidate SNPs in different geographic regions. This finding is consistent with the highly polygenic nature of adaptation, where the response may be achieved through a subtle adjustment of allele frequencies in different genes that contribute to adaptive phenotypes. Taken together, our results point to a polygenic adaptive response in the nervous system, specifically implicating genes involved in synapse organization, which mirrors the findings from several genomic and behavioral studies of adaptation to urbanization in other taxa.

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.

Uncovering the genetic architecture of parallel evolution

Identifying the genetic architecture underlying adaptive traits is exceptionally challenging in natural populations. This is because associations between traits not only mask the targets of selection but also create correlated patterns of genomic divergence that hinder our ability to isolate causal genetic effects. Here, we examine the repeated evolution of components of the auxin pathway that have contributed to the replicated loss of gravitropism (i.e. the ability of a plant to bend in response to gravity) in multiple populations of the Senecio lautus species complex in Australia. We use a powerful approach which combines parallel population genomics with association mapping in a Multiparent Advanced Generation Inter-Cross (MAGIC) population to break down genetic and trait correlations to reveal how adaptive traits evolve during replicated evolution. We sequenced auxin and shoot gravitropism-related gene regions in 80 individuals from six natural populations (three parallel divergence events) and 133 individuals from a MAGIC population derived from two of the recently diverged natural populations. We show that artificial tail selection on gravitropism in the MAGIC population recreates patterns of parallel divergence in the auxin pathway in the natural populations. We reveal a set of 55 auxin gene regions that have evolved repeatedly during the evolution of the species, of which 50 are directly associated with gravitropism divergence in the MAGIC population. Our work creates a strong link between patterns of genomic divergence and trait variation contributing to replicated evolution by natural selection, paving the way to understand the origin and maintenance of adaptations in natural populations.

Revisiting the Role of Genetic Variation in Adaptation

AbstractEvolutionary biologists have thought about the role of genetic variation during adaptation for a very long time-before we understood the organization of the genetic code, the provenance of genetic variation, and how such variation influenced the phenotypes on which natural selection acts. Half a century after the discovery of the structure of DNA and the unraveling of the genetic code, we have a rich understanding of these problems and the means to both delve deeper and widen our perspective across organisms and natural populations. The 2022 Vice Presidential Symposium of the American Society of Naturalists highlighted examples of recent insights into the role of genetic variation in adaptive processes, which are compiled in this special section. The work was conducted in different parts of the world, included theoretical and empirical studies with diverse organisms, and addressed distinct aspects of how genetic variation influences adaptation. In our introductory article to the special section, we discuss some important recent insights about the generation and maintenance of genetic variation, its impacts on phenotype and fitness, its fate in natural populations, and its role in driving adaptation. By placing the special section articles in the broader context of recent developments, we hope that this overview will also serve as a useful introduction to the field.

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 Genomic Basis of Adaptation to High Elevations in Africanized Honey Bees

A range of different genetic architectures underpin local adaptation in nature. Honey bees (Apis mellifera) in the Eastern African Mountains harbor high frequencies of two chromosomal inversions that likely govern adaptation to this high-elevation habitat. In the Americas, honey bees are hybrids of European and African ancestries and adaptation to latitudinal variation in climate correlates with the proportion of these ancestries across the genome. It is unknown which, if either, of these forms of genetic variation governs adaptation in honey bees living at high elevations in the Americas. Here, we performed whole-genome sequencing of 29 honey bees from both high- and low-elevation populations in Colombia. Analysis of genetic ancestry indicated that both populations were predominantly of African ancestry, but the East African inversions were not detected. However, individuals in the higher elevation population had significantly higher proportions of European ancestry, likely reflecting local adaptation. Several genomic regions exhibited particularly high differentiation between highland and lowland bees, containing candidate loci for local adaptation. Genes that were highly differentiated between highland and lowland populations were enriched for functions related to reproduction and sperm competition. Furthermore, variation in levels of European ancestry across the genome was correlated between populations of honey bees in the highland population and populations at higher latitudes in South America. The results are consistent with the hypothesis that adaptation to both latitude and elevation in these hybrid honey bees are mediated by variation in ancestry at many loci across the genome.

Selection and the direction of phenotypic evolution

Predicting adaptive phenotypic evolution depends on invariable selection gradients and on the stability of the genetic covariances between the component traits of the multivariate phenotype. We describe the evolution of six traits of locomotion behavior and body size in the nematode Caenorhabditis elegans for 50 generations of adaptation to a novel environment. We show that the direction of adaptive multivariate phenotypic evolution can be predicted from the ancestral selection differentials, particularly when the traits were measured in the new environment. Interestingly, the evolution of individual traits does not always occur in the direction of selection, nor are trait responses to selection always homogeneous among replicate populations. These observations are explained because the phenotypic dimension with most of the ancestral standing genetic variation only partially aligns with the phenotypic dimension under directional selection. These findings validate selection theory and suggest that the direction of multivariate adaptive phenotypic evolution is predictable for tens of generations.

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'.

Embracing Complexity: Yeast Evolution Experiments Featuring Standing Genetic Variation

The yeast Saccharomyces cerevisiae has a long and esteemed history as a model system for laboratory selection experiments. The majority of yeast evolution experiments begin with an isogenic ancestor, impose selection as cells divide asexually, and track mutations that arise and accumulate over time. Within the last decade, the popularity of S. cerevisiae as a model system for exploring the evolution of standing genetic variation has grown considerably. As a facultatively sexual microbe, it is possible to initiate experiments with populations that harbor diversity and also to maintain that diversity by promoting sexual recombination as the experiment progresses. These experimental choices expand the scope of evolutionary hypotheses that can be tested with yeast. And, in this review, I argue that yeast is one of the best model systems for testing such hypotheses relevant to eukaryotic species. Here, I compile a list of yeast evolution experiments that involve standing genetic variation, initially and/or by implementing protocols that induce sexual recombination in evolving populations. I also provide an overview of experimental methods required to set up such an experiment and discuss the unique challenges that arise in this type of research. Throughout the article, I emphasize the best practices emerging from this small but growing niche of the literature.

A revised central dogma for the 21st century:all biology is cognitive information processing

Crick's Central Dogma has been a foundational aspect of 20th century biology, describing an implicit relationship governing the flow of information in biological systems in biomolecular terms. Accumulating scientific discoveries support the need for a revised Central Dogma to buttress evolutionary biology's still-fledgling migration from a Neodarwinian canon. A reformulated Central Dogma to meet contemporary biology is proposed: all biology is cognitive information processing. Central to this contention is the recognition that life is the self-referential state, instantiated within the cellular form. Self-referential cells act to sustain themselves and to do so, cells must be in consistent harmony with their environment. That consonance is achieved by the continuous assimilation of environmental cues and stresses as information to self-referential observers. All received cellular information must be analyzed to be deployed as cellular problem-solving to maintain homeorhetic equipoise. However, the effective implementation of information is definitively a function of orderly information management. Consequently, effective cellular problem-solving is information processing and management. The epicenter of that cellular information processing is its self-referential internal measurement. All further biological self-organization initiates from this obligate activity. As the internal measurement by cells of information is self-referential by definition, self-reference is biological self-organization, underpinning 21st century Cognition-Based Biology.

How predictable is adaptation from standing genetic variation? Experimental evolution in Drosophila highlights the central role of redundancy and linkage disequilibrium

Experimental evolution is well-suited to test the predictability of evolution without the confounding effects of inaccurate forecasts about future environments. Most of the literature about parallel (and thus predictable) evolution has been carried out in asexual microorganisms, which adapt by de novo mutations. Nevertheless, parallel evolution has also been studied in sexual species at the genomic level. Here, I review the evidence for parallel evolution in Drosophila, the best-studied obligatory outcrossing model for adaptation from standing genetic variation in the laboratory. Similar to asexual microorganisms, evidence for parallel evolution varies between the focal hierarchical levels. Selected phenotypes consistently respond in a very predicable way, but the underlying allele frequency changes are much less predictable. The most important insight is that the predictability of the genomic selection response for polygenic traits depends highly on the founder population and to a much lesser extent on the selection regime. This implies that predicting adaptive genomic response is challenging and requires a good understanding of the adaptive architecture (including linkage disequilibrium) in the ancestral populations. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

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.

Genetic architecture of human brain evolution

Comparative studies of hominids have long sought to identify mutational events that shaped the evolution of the human nervous system. However, functional genetic differences are outnumbered by millions of nearly neutral mutations, and the developmental mechanisms underlying human nervous system specializations are difficult to model and incompletely understood. Candidate-gene studies have attempted to map select human-specific genetic differences to neurodevelopmental functions, but it remains unclear how to contextualize the relative effects of genes that are investigated independently. Considering these limitations, we discuss scalable approaches for probing the functional contributions of human-specific genetic differences. We propose that a systems-level view will enable a more quantitative and integrative understanding of the genetic, molecular and cellular underpinnings of human nervous system evolution.

Selective sweeps linked to the colonization of novel habitats and climatic changes in a wild tomato species

Positive selection is the driving force underpinning local adaptation and leaves footprints of selective sweeps on the underlying major genes. Quantifying the timing of selection and revealing the genetic bases of adaptation in plant species occurring in steep and varying environmental gradients are crucial to predict a species' ability to colonize new niches. We use whole-genome sequence data from six populations across three different habitats of the wild tomato species Solanum chilense to infer the past demographic history and search for genes under strong positive selection. We then correlate current and past climatic projections with the demographic history, allele frequencies, the age of selection events and distribution shifts. Several selective sweeps occur at regulatory networks involved in root-hair development in low altitude and response to photoperiod and vernalization in high-altitude populations. These sweeps appear to occur in a concerted fashion in a given regulatory gene network at particular periods of substantial climatic change. Using a unique combination of genome scans and modelling of past climatic data, we quantify the timing of selection at genes likely underpinning local adaptation to semiarid habitats.

Polygenic adaptation from standing genetic variation allows rapid ecotype formation

Adaptive ecotype formation can be the first step to speciation, but the genetic underpinnings of this process are poorly understood. Marine midges of the genus Clunio (Diptera) have recolonized Northern European shore areas after the last glaciation. In response to local tide conditions they have formed different ecotypes with respect to timing of adult emergence, oviposition behavior and larval habitat. Genomic analysis confirms the recent establishment of these ecotypes, reflected in massive haplotype sharing between ecotypes, irrespective of whether there is ongoing gene flow or geographic isolation. QTL mapping and genome screens reveal patterns of polygenic adaptation from standing genetic variation. Ecotype-associated loci prominently include circadian clock genes, as well as genes affecting sensory perception and nervous system development, hinting to a central role of these processes in ecotype formation. Our data show that adaptive ecotype formation can occur rapidly, with ongoing gene flow and largely based on a re-assortment of existing alleles.

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.

Repeated genetic divergence plays a minor role in repeated phenotypic divergence of lake-stream stickleback

Recent studies have shown that the repeated evolution of similar phenotypes in response to similar ecological conditions (here "parallel evolution") often occurs through mutations in the same genes. However, many previous studies have focused on known candidate genes in a limited number of systems. Thus, the question of how often parallel phenotypic evolution is due to parallel genetic changes remains open. Here, we used quantitative trait locus (QTL) mapping in F2 intercrosses between lake and stream threespine stickleback (Gasterosteus aculeatus) from four independent watersheds on Vancouver Island, Canada to determine whether the same QTL underlie divergence in the same phenotypes across, between, and within watersheds. We find few parallel QTL, even in independent crosses from the same watershed or for phenotypes that have diverged in parallel. These findings suggest that different mutations can lead to similar phenotypes. The low genetic repeatability observed in these lake-stream systems contrasts with the higher genetic repeatability observed in other stickleback systems. We speculate that differences in evolutionary history, gene flow, and/or the strength and direction of selection might explain these differences in genetic parallelism and emphasize that more work is needed to move beyond documenting genetic parallelism to identifying the underlying causes.