Local adaptation (mostly) remains local: reassessing environmental associations of climate-related candidate SNPs in Arabidopsis halleri

Space-for-time substitutions in climate change ecology and evolution

In an epoch of rapid environmental change, understanding and predicting how biodiversity will respond to a changing climate is an urgent challenge. Since we seldom have sufficient long-term biological data to use the past to anticipate the future, spatial climate-biotic relationships are often used as a proxy for predicting biotic responses to climate change over time. These 'space-for-time substitutions' (SFTS) have become near ubiquitous in global change biology, but with different subfields largely developing methods in isolation. We review how climate-focussed SFTS are used in four subfields of ecology and evolution, each focussed on a different type of biotic variable - population phenotypes, population genotypes, species' distributions, and ecological communities. We then examine the similarities and differences between subfields in terms of methods, limitations and opportunities. While SFTS are used for a wide range of applications, two main approaches are applied across the four subfields: spatial in situ gradient methods and transplant experiments. We find that SFTS methods share common limitations relating to (i) the causality of identified spatial climate-biotic relationships and (ii) the transferability of these relationships, i.e. whether climate-biotic relationships observed over space are equivalent to those occurring over time. Moreover, despite widespread application of SFTS in climate change research, key assumptions remain largely untested. We highlight opportunities to enhance the robustness of SFTS by addressing key assumptions and limitations, with a particular emphasis on where approaches could be shared between the four subfields.

Tropical forest loss and geographic location drive the functional genomic diversity of an endangered palm tree

Human activity has diminished forests in different terrestrial ecosystems. This is well illustrated in the Brazilian Atlantic Forest, which still hosts high levels of species richness and endemism, even with only 28% of its original extent remaining. The consequences of such forest loss in remaining populations can be investigated with several approaches, including the genomic perspective, which allows a broader understanding of how human disturbance influences the genetic variability in natural populations. In this context, our study investigated the genomic responses of Euterpe edulis Martius, an endangered palm tree, in forest remnants located in landscapes presenting different forest cover amount and composed by distinct bird assemblage that disperse its seeds. We sampled 22 areas of the Brazilian Atlantic Forest in four regions using SNP markers inserted into transcribed regions of the genome of E. edulis, distinguishing neutral loci from those putatively under natural selection (outlier). We demonstrate that populations show patterns of structure and genetic variability that differ between regions, as a possible reflection of deforestation and biogeographic histories. Deforested landscapes still maintain high neutral genetic diversity due to gene flow over short distances. Overall, we not only support previous evidence with microsatellite markers, but also show that deforestation can influence the genetic variability outlier, in the scenario of selective pressures imposed by these stressful environments. Based on our findings, we suggest that, to protect genetic diversity in the long term, it is necessary to reforest and enrich deforested areas, using seeds from populations in the same management target region.

Population transcriptomics uncover the relative roles of positive selection and differential expression in Batrachium bungei adaptation to the Qinghai-Tibetan plateau

KEY MESSAGE

Positive selection genes are related to metabolism, while differentially expressed genes are related to photosynthesis, suggesting that genetic adaptation and expression regulation may play independent roles in different gene classes. Genome-wide investigation of the molecular mechanisms for high-altitude adaptation is an intriguing topic in evolutionary biology. The Qinghai-Tibet Plateau (QTP) with its extremely variable environments is an ideal site for studying high-altitude adaptation. Here, we used transcriptome data of 100 individuals from 20 populations collected from various altitudes on the QTP to investigate the adaptive mechanisms of the aquatic plant Batrachium bungei at both the genetic and transcriptional level. To explore genes and biological pathways that may contribute to QTP adaptation, we employed a two-step approach, in which we identified positively selected genes and differentially expressed genes using the landscape genomic and differential expression approaches. The positive selection analysis showed that genes involved in metabolic regulation played a crucial role in B. bungei adaptation to the extreme environments of the QTP, especially intense ultraviolet radiation. Altitude-based differential expression analysis suggested that B. bungei could increase the rate of energy dissipation or reduce the efficiency of light energy absorption by down regulating the expression of photosynthesis-related genes to adapt to the strong ultraviolet radiation. Weighted gene co-expression network analysis identified ribosomal genes as hubs of altitude adaptation in B. bungei. Only a small part of genes (about 10%) overlapped between positively selected genes and differentially expressed genes in B. bungei, suggesting that genetic adaptation and gene expression regulation might play relatively independent roles in different categories of functional genes. Taken together, this study enriches our understanding of the high-altitude adaptation mechanism of B. bungei on the QTP.

The genomic and epigenetic footprint of local adaptation to variable climates in kiwifruit

A full understanding of adaptive genetic variation at the genomic level will help address questions of how organisms adapt to diverse climates. Actinidia eriantha is a shade-tolerant species, widely distributed in the southern tropical region of China, occurring in spatially heterogeneous environments. In the present study we combined population genomic, epigenomic, and environmental association analyses to infer population genetic structure and positive selection across a climatic gradient, and to assess genomic offset to climatic change for A. eriantha. The population structure is strongly shaped by geography and influenced by restricted gene flow resulting from isolation by distance due to habitat fragmentation. In total, we identified 102 outlier loci and annotated 455 candidate genes associated with the genomic basis of climate adaptation, which were enriched in functional categories related to development processes and stress response; both temperature and precipitation are important factors driving adaptive variation. In addition to single-nucleotide polymorphisms (SNPs), a total of 27 single-methylation variants (SMVs) had significant correlation with at least one of four climatic variables and 16 SMVs were located in or adjacent to genes, several of which were predicted to be involved in plant response to abiotic or biotic stress. Gradient forest analysis indicated that the central/east populations were predicted to be at higher risk of future population maladaptation under climate change. Our results demonstrate that local climate factors impose strong selection pressures and lead to local adaptation. Such information adds to our understanding of adaptive mechanisms to variable climates revealed by both population genome and epigenome analysis.

Polymorphisms in alternative oxidase genes from ecotypes of Arabidopsis and rice revealed an environment-induced linkage to altitude and rainfall

We investigated SNPs in alternative oxidase (AOX) genes and their connection to ecotype origins (climate, altitude, and rainfall) by using genomic data sets of Arabidopsis and rice populations from 1190 and 90 ecotypes, respectively. Parameters were defined to detect non-synonymous SNPs in the AOX ORF, which revealed amino acid (AA) changes in AOX1c, AOX1d, and AOX2 from Arabidopsis and AOX1c from rice in comparison to AOX references from Columbia-0 and Japonica ecotypes, respectively. Among these AA changes, Arabidopsis AOX1c_A161E&G165R and AOX1c_R242S revealed a link to high rainfall and high altitude, respectively, while all other changes in Arabidopsis and rice AOX was connected to high altitude and rainfall. Comparative 3D modeling showed that all mutant AOX presented structural differences in relation to the respective references. Molecular docking analysis uncovered lower binding affinity values between AOX and the substrate ubiquinol for most of the identified structures compared to their reference, indicating better enzyme-substrate binding affinities. Thus, our in silico data suggest that the majority of the AA changes found in the available ecotypes will confer better enzyme-subtract interactions and thus indicate environment-related, more efficient AOX activity.

Genetic basis of growth reaction to drought stress differs in contrasting high-latitude treeline ecotones of a widespread conifer

Climate change is increasing the frequency and intensity of drought events in many boreal forests. Trees are sessile organisms with a long generation time, which makes them vulnerable to fast climate change and hinders fast adaptations. Therefore, it is important to know how forests cope with drought stress and to explore the genetic basis of these reactions. We investigated three natural populations of white spruce (Picea glauca) in Alaska, located at one drought-limited and two cold-limited treelines with a paired plot design of one forest and one treeline plot. We obtained individual increment cores from 458 trees and climate data to assess dendrophenotypes, in particular the growth reaction to drought stress. To explore the genetic basis of these dendrophenotypes, we genotyped the individual trees at 3000 single nucleotide polymorphisms in candidate genes and performed genotype-phenotype association analysis using linear mixed models and Bayesian sparse linear mixed models. Growth reaction to drought stress differed in contrasting treeline populations. Therefore, the populations are likely to be unevenly affected by climate change. We identified 40 genes associated with dendrophenotypic traits that differed among the treeline populations. Most genes were identified in the drought-limited site, indicating comparatively strong selection pressure of drought-tolerant phenotypes. Contrasting patterns of drought-associated genes among sampled sites and in comparison to Canadian populations in a previous study suggest that drought adaptation acts on a local scale. Our results highlight genes that are associated with wood traits which in turn are critical for the establishment and persistence of future forests under climate change.

European common frog (Rana temporaria) recolonized Switzerland from multiple glacial refugia in northern Italy via trans- and circum-Alpine routes

The high mountain ranges of Western Europe had a profound effect on the biotic recolonization of Europe from glacial refugia. The Alps present a particularly interesting case because they form an absolute barrier to dispersal for most taxa, obstructing recolonization from multiple refugia in northern Italy. Here, we investigate the effect of the European Alps on the phylogeographic history of the European common frog Rana temporaria. Based on partial cytochrome b and COXI sequences from Switzerland, we find two mitochondrial lineages roughly north and south of the Alpine ridge, with contact zones between them in eastern and western Switzerland. The northern haplogroup falls within the previously identified Western European haplogroup, while the southern haplogroup is unique to Switzerland. We find that the lineages diverged ~110 kya, at approximately the onset of the last glacial glaciation; this indicates that they are from different glacial refugia. Phylogenetic analyses suggest that the northern and southern haplogroups colonized Switzerland via trans- and circum-Alpine routes from at least two separate refugia in northern Italy. Our results illustrate how a complex recolonization history of the central European Alps can arise from the semi-permeable barrier created by high mountains.

Arabis alpina: A perennial model plant for ecological genomics and life-history evolution

Many model organisms were chosen and achieved prominence because of an advantageous combination of their life‐history characteristics, genetic properties and also practical considerations. Discoveries made in Arabidopsis thaliana, the most renowned noncrop plant model species, have markedly stimulated studies in other species with different biology. Within the family Brassicaceae, the arctic–alpine Arabis alpina has become a model complementary to Arabidopsis thaliana to study the evolution of life‐history traits, such as perenniality, and ecological genomics in harsh environments. In this review, we provide an overview of the properties that facilitated the rapid emergence of A. alpina as a plant model. We summarize the evolutionary history of A. alpina, including genomic aspects, the diversification of its mating system and demographic properties, and we discuss recent progress in the molecular dissection of developmental traits that are related to its perennial life history and environmental adaptation. From this published knowledge, we derive open questions that might inspire future research in A. alpina, other Brassicaceae species or more distantly related plant families.

Genome-environment association methods comparison supports omnigenic adaptation to ecological niche in malaria vector mosquitoes

The concept of a fundamental ecological niche is central to questions of geographic distribution, population demography, species conservation, and evolutionary potential. However, robust inference of genomic regions associated with evolutionary adaptation to particular environmental conditions remains difficult due to the myriad of potential confounding processes that can generate heterogeneous patterns of variation across the genome. Here, we interrogate the potential role of genome environment association (GEA) testing as an initial step in building an understanding of the genetic basis of ecological niche. We leverage publicly available genomic data from the Anopheles gambiae 1000 Genomes (Ag1000g) Consortium to test the ability of multiple analytically unique GEA methods to handle confounding patterns of genetic variation, control false positive rates, and discern associations with broadly relevant climate variables from random allele frequency patterns throughout the genome. We found evidence supporting the ability of commonly implemented GEA methods to account for confounding patterns of spatial and genetic variation, and control false positive rates. However, we fail to find evidence supporting the ability of GEA tests to reject signals of adaptation to randomly simulated environmental variables, indicating that discerning between true signals of genome environment adaptation and genome environment correlations resulting from alternative evolutionary processes, remains challenging. Because signals of environmental adaptation are so diffuse and confounded throughout the genome, we argue that genomic adaptation to ecological niche is likely best understood under an omnigenic model wherein highly interconnected, genome-wide gene regulatory networks shape genomic adaptation to key environmental conditions.

Adaptive divergence despite low effective population size in a peripherally isolated population of the pygmy rabbit, Brachylagus idahoensis

Local adaptation can occur when spatially separated populations are subjected to contrasting environmental conditions. Historically, understanding the genetic basis of adaptation has been difficult, but increased availability of genome-wide markers facilitates studies of local adaptation in non-model organisms of conservation concern. The pygmy rabbit (Brachylagus idahoensis) is an imperiled lagomorph that relies on sagebrush for forage and cover. This reliance has led to widespread population declines following reductions in the distribution of sagebrush, leading to geographic separation between populations. In this study, we used >20,000 single nucleotide polymorphisms, genotype-environment association methods, and demographic modeling to examine neutral genetic variation and local adaptation in the pygmy rabbit in Nevada and California. We identified 308 loci as outliers, many of which had functional annotations related to metabolism of plant secondary compounds. Likewise, patterns of spatial variation in outlier loci were correlated with landscape and climatic variables including proximity to streams, sagebrush cover, and precipitation. We found that populations in the Mono Basin of California probably diverged from other Great Basin populations during late Pleistocene climate oscillations, and that this region is adaptively differentiated from other regions in the southern Great Basin despite limited gene flow and low effective population size. Our results demonstrate that peripherally isolated populations can maintain adaptive divergence.

Prospects and limitations of genomic offset in conservation management

In nature conservation, there is keen interest in predicting how populations will respond to environmental changes such as climate change. These predictions can help determine whether a population can be self-sustaining under future alterations of its habitat or whether it may require human intervention such as protection, restoration, or assisted migration. An increasingly popular approach in this respect is the concept of genomic offset, which combines genomic and environmental data from different time points and/or locations to assess the degree of possible maladaptation to new environmental conditions. Here, we argue that the concept of genomic offset holds great potential, but an exploration of its risks and limitations is needed to use it for recommendations in conservation or assisted migration. After briefly describing the concept, we list important issues to consider (e.g., statistical frameworks, population genetic structure, migration, independent evidence) when using genomic offset or developing these methods further. We conclude that genomic offset is an area of development that still lacks some important features and should be used in combination with other approaches to inform conservation measures.

Environment and pathogens shape local and regional adaptations to climate change in the chocolate tree, Theobroma cacao L

Predicting the potential fate of a species in the face of climate change requires knowing the distribution of molecular adaptations across the geographic range of the species. In this work, we analysed 79 genomes of Theobroma cacao, an Amazonian tree known for the fruit from which chocolate is produced, to evaluate how local and regional molecular signatures of adaptation are distributed across the natural range of the species. We implemented novel techniques that incorporate summary statistics from multiple selection scans to infer selective sweeps. The majority of the molecular adaptations in the genome are not shared among populations. We show that ~71.5% of genes under selection also show significant associations with changes in environmental variables. Our results support the interpretation that these genes contribute to local adaptation of the populations in response to abiotic factors. We also found strong patterns of molecular adaptation in a diverse array of disease resistance genes (6.5% of selective sweeps), suggesting that differential adaptation to pathogens also contributes significantly to local adaptations. Our results are consistent with the interpretation that local selective pressures are more important than regional selective pressures in explaining adaptation across the range of a species.

Landscape genomics of Quercus lobata reveals genes involved in local climate adaptation at multiple spatial scales

Understanding how the environment shapes genetic variation provides critical insight about the evolution of local adaptation in natural populations. At multiple spatial scales and multiple geographic contexts within a single species, such information could address a number of fundamental questions about the scale of local adaptation and whether or not the same loci are involved at different spatial scales or geographic contexts. We used landscape genomic approaches from three local elevational transects and rangewide sampling to (a) identify genetic variation underlying local adaptation to environmental gradients in the California endemic oak, Quercus lobata; (b) examine whether putatively adaptive SNPs show signatures of selection at multiple spatial scales; and (c) map putatively adaptive variation to assess the scale and pattern of local adaptation. Of over 10 k single-nucleotide polymorphisms (SNPs) generated with genotyping-by-sequencing, we found signatures of natural selection by climate or local environment at over 600 SNPs (536 loci), some at multiple spatial scales across multiple analyses. Candidate SNPs identified with gene-environment tests (LFMM) at the rangewide scale also showed elevated associations with climate variables compared to the background at both rangewide and elevational transect scales with gradient forest analysis. Some loci overlap with those detected in other oak species, raising the question of whether the same loci might be involved in local climate adaptation in different congeneric species that inhabit different geographic contexts. Mapping landscape patterns of adaptive versus background genetic variation identified regions of marked local adaptation and suggests nonlinear association of candidate SNPs and environmental variables. Taken together, our results offer robust evidence for novel candidate genes for local climate adaptation at multiple spatial scales.

Genomic signatures of convergent adaptation to Alpine environments in three Brassicaceae species

It has long been discussed to what extent related species develop similar genetic mechanisms to adapt to similar environments. Most studies documenting such convergence have either used different lineages within species or surveyed only a limited portion of the genome. Here, we investigated whether similar or different sets of orthologous genes were involved in genetic adaptation of natural populations of three related plant species to similar environmental gradients in the Alps. We used whole-genome pooled population sequencing to study genome-wide SNP variation in 18 natural populations of three Brassicaceae (Arabis alpina, Arabidopsis halleri, and Cardamine resedifolia) from the Swiss Alps. We first de novo assembled draft reference genomes for all three species. We then ran population and landscape genomic analyses with ~3 million SNPs per species to look for shared genomic signatures of selection and adaptation in response to similar environmental gradients acting on these species. Genes with a signature of convergent adaptation were found at significantly higher numbers than expected by chance. The most closely related species pair showed the highest relative over-representation of shared adaptation signatures. Moreover, the identified genes of convergent adaptation were enriched for nonsynonymous mutations, suggesting functional relevance of these genes, even though many of the identified candidate genes have hitherto unknown or poorly described functions based on comparison with Arabidopsis thaliana. We conclude that adaptation to heterogeneous Alpine environments in related species is partly driven by convergent evolution, but that most of the genomic signatures of adaptation remain species-specific.

Disentangling the effects of geographic peripherality and habitat suitability on neutral and adaptive genetic variation in Swiss stone pine

It is generally accepted that the spatial distribution of neutral genetic diversity within a species' native range mostly depends on effective population size, demographic history, and geographic position. However, it is unclear how genetic diversity at adaptive loci correlates with geographic peripherality or with habitat suitability within the ecological niche. Using exome-wide genomic data and distribution maps of the Alpine range, we first tested whether geographic peripherality correlates with four measures of population genetic diversity at > 17,000 SNP loci in 24 Alpine populations (480 individuals) of Swiss stone pine (Pinus cembra) from Switzerland. To distinguish between neutral and adaptive SNP sets, we used four approaches (two gene diversity estimates, F_ST outlier test, and environmental association analysis) that search for signatures of selection. Second, we established ecological niche models for P. cembra in the study range and investigated how habitat suitability correlates with genetic diversity at neutral and adaptive loci. All estimates of neutral genetic diversity decreased with geographic peripherality, but were uncorrelated with habitat suitability. However, heterozygosity (H_e ) at adaptive loci based on Tajima's D declined significantly with increasingly suitable conditions. No other diversity estimates at adaptive loci were correlated with habitat suitability. Our findings suggest that populations at the edge of a species' geographic distribution harbour limited neutral genetic diversity due to demographic properties. Moreover, we argue that populations from suitable habitats went through strong selection processes, are thus well adapted to local conditions, and therefore exhibit reduced genetic diversity at adaptive loci compared to populations at niche margins.

Genetic structure among morphotypes of the endangered Brazilian palm Euterpe edulis Mart (Arecaceae)

Euterpe edulis (Arecaceae) Mart has high ecological and economic importance providing food resources for more than 58 species of birds and 20 species of mammals, including humans. E. edulis is the second most exploited nontimber product from Brazilian Atlantic Forest. Due to overexploitation and destruction of habitats, E. edulis is threatened by extinction. Euterpe edulis populations have large morphological variations, with individuals having green, red, or yellow leaf sheath. However, no study has related phenotypic distinctions between populations and their levels of genetic structure. Thus, this study aimed to evaluate the diversity and genetic structure of different E. edulis morphotypes. We sampled 250 adult individuals in eight populations with the different morphotypes. Using 14 microsatellite markers, we access genetic diversity through population genetic parameters calculated in the GenAlex program and the diveRsity package in R. We used the Wilcoxon test to verify population bottlenecks and the genetic distance of Nei and Bayesian analysis for genetic clusters. The eight populations showed low allele richness, low observed heterozygosity, and high inbreeding values (f). In addition, six of the eight populations experienced genetic bottlenecks, which would partly explain the low genetic diversity in populations. Cluster analysis identified two clusters (K = 2), with green morphotype genetically distinguishing from yellow and red morphotypes. Thus, we show, for the first time, a strong genetic structure among E. edulis morphotypes even for geographically close populations.

Knowledge status and sampling strategies to maximize cost-benefit ratio of studies in landscape genomics of wild plants

To avoid local extinction due to the changes in their natural ecosystems, introduced by anthropogenic activities, species undergo local adaptation. Landscape genomics approach, through genome–environment association studies, has helped evaluate the local adaptation in natural populations. Landscape genomics, is still a developing discipline, requiring refinement of guidelines in sampling design, especially for studies conducted in the backdrop of stark socioeconomic realities of the rainforest ecologies, which are global biodiversity hotspots. In this study we aimed to devise strategies to improve the cost-benefit ratio of landscape genomics studies by surveying sampling designs and genome sequencing strategies used in existing studies. We conducted meta-analyses to evaluate the importance of sampling designs, in terms of (i) number of populations sampled, (ii) number of individuals sampled per population, (iii) total number of individuals sampled, and (iv) number of SNPs used in different studies, in discerning the molecular mechanisms underlying local adaptation of wild plant species. Using the linear mixed effects model, we demonstrated that the total number of individuals sampled and the number of SNPs used, significantly influenced the detection of loci underlying the local adaptation. Thus, based on our findings, in order to optimize the cost-benefit ratio of landscape genomics studies, we suggest focusing on increasing the total number of individuals sampled and using a targeted (e.g. sequencing capture) Pool-Seq approach and/or a random (e.g. RAD-Seq) Pool-Seq approach to detect SNPs and identify SNPs under selection for a given environmental cline. We also found that the existing molecular evidences are inadequate in predicting the local adaptations to climate change in tropical forest ecosystems.

In the presence of population structure: From genomics to candidate genes underlying local adaptation

Understanding the genomic signatures, genes, and traits underlying local adaptation of organisms to heterogeneous environments is of central importance to the field evolutionary biology. To identify loci underlying local adaptation, models that combine allelic and environmental variation while controlling for the effects of population structure have emerged as the method of choice. Despite being evaluated in simulation studies, there has not been a thorough investigation of empirical evidence supporting local adaptation across these alleles. To evaluate these methods, we use 875 Arabidopsis thaliana Eurasian accessions and two mixed models (GEMMA and LFMM) to identify candidate SNPs underlying local adaptation to climate. Subsequently, to assess evidence of local adaptation and function among significant SNPs, we examine allele frequency differentiation and recent selection across Eurasian populations, in addition to their distribution along quantitative trait loci (QTL) explaining fitness variation between Italy and Sweden populations and cis-regulatory/nonsynonymous sites showing significant selective constraint. Our results indicate that significant LFMM/GEMMA SNPs show low allele frequency differentiation and linkage disequilibrium across locally adapted Italy and Sweden populations, in addition to a poor association with fitness QTL peaks (highest logarithm of odds score). Furthermore, when examining derived allele frequencies across the Eurasian range, we find that these SNPs are enriched in low-frequency variants that show very large climatic differentiation but low levels of linkage disequilibrium. These results suggest that their enrichment along putative functional sites most likely represents deleterious variation that is independent of local adaptation. Among all the genomic signatures examined, only SNPs showing high absolute allele frequency differentiation (AFD) and linkage disequilibrium (LD) between Italy and Sweden populations showed a strong association with fitness QTL peaks and were enriched along selectively constrained cis-regulatory/nonsynonymous sites. Using these SNPs, we find strong evidence linking flowering time, freezing tolerance, and the abscisic-acid pathway to local adaptation.

In the presence of population structure: From genomics to candidate genes underlying local adaptation

Understanding the genomic signatures, genes, and traits underlying local adaptation of organisms to heterogeneous environments is of central importance to the field evolutionary biology. To identify loci underlying local adaptation, models that combine allelic and environmental variation while controlling for the effects of population structure have emerged as the method of choice. Despite being evaluated in simulation studies, there has not been a thorough investigation of empirical evidence supporting local adaptation across these alleles. To evaluate these methods, we use 875 Arabidopsis thaliana Eurasian accessions and two mixed models (GEMMA and LFMM) to identify candidate SNPs underlying local adaptation to climate. Subsequently, to assess evidence of local adaptation and function among significant SNPs, we examine allele frequency differentiation and recent selection across Eurasian populations, in addition to their distribution along quantitative trait loci (QTL) explaining fitness variation between Italy and Sweden populations and cis-regulatory/nonsynonymous sites showing significant selective constraint. Our results indicate that significant LFMM/GEMMA SNPs show low allele frequency differentiation and linkage disequilibrium across locally adapted Italy and Sweden populations, in addition to a poor association with fitness QTL peaks (highest logarithm of odds score). Furthermore, when examining derived allele frequencies across the Eurasian range, we find that these SNPs are enriched in low-frequency variants that show very large climatic differentiation but low levels of linkage disequilibrium. These results suggest that their enrichment along putative functional sites most likely represents deleterious variation that is independent of local adaptation. Among all the genomic signatures examined, only SNPs showing high absolute allele frequency differentiation (AFD) and linkage disequilibrium (LD) between Italy and Sweden populations showed a strong association with fitness QTL peaks and were enriched along selectively constrained cis-regulatory/nonsynonymous sites. Using these SNPs, we find strong evidence linking flowering time, freezing tolerance, and the abscisic-acid pathway to local adaptation.

Anthropogenic pressures negatively impact genomic diversity of the vulnerable seagrass Zostera capensis

Zostera capensis is a keystone species providing essential ecosystem services to southern African coastal systems. Like most seagrasses globally, Z. capensis is declining and under threat from anthropogenic pressures, and indicators of seagrass health and resilience may be of interest in preventing further declines. As intraspecific diversity is an important component of resilience, we used a pooled RADseq approach to generate genome-wide measures of variation across the entire South African distribution of Z. capensis. Using nucleotide diversity, heterozygosity and allelic richness we tested for associations with fine-scale anthropogenic pressure data compiled by the South African National Biodiversity Assessment using generalised linear models. Increased fishing effort, habitat loss, sand mining and a change in estuary flow dynamics were found to play an important role in decreasing nucleotide diversity and expected heterozygosity, most likely due to the loss of less resilient genotypes as a result of direct physical damage or indirect consequences. As the building block for adaptation, nucleotide diversity is particularly important for resilience. Because of this, as well as the fact that nucleotide diversity displayed the most distinct difference between the west and east coast, and responded most strongly to anthropogenic pressures, we suggest that this may be a useful measure for monitoring genetic or genomic variation. As genomic diversity influences resilience and resistance to disturbances, the remaining diversity in South African seagrass beds urgently needs to be conserved through restoration efforts and careful management of pressures.

Evolutionary genomics can improve prediction of species' responses to climate change

Global climate change (GCC) increasingly threatens biodiversity through the loss of species, and the transformation of entire ecosystems. Many species are challenged by the pace of GCC because they might not be able to respond fast enough to changing biotic and abiotic conditions. Species can respond either by shifting their range, or by persisting in their local habitat. If populations persist, they can tolerate climatic changes through phenotypic plasticity, or genetically adapt to changing conditions depending on their genetic variability and census population size to allow for de novo mutations. Otherwise, populations will experience demographic collapses and species may go extinct. Current approaches to predicting species responses to GCC begin to combine ecological and evolutionary information for species distribution modelling. Including an evolutionary dimension will substantially improve species distribution projections which have not accounted for key processes such as dispersal, adaptive genetic change, demography, or species interactions. However, eco‐evolutionary models require new data and methods for the estimation of a species' adaptive potential, which have so far only been available for a small number of model species. To represent global biodiversity, we need to devise large‐scale data collection strategies to define the ecology and evolutionary potential of a broad range of species, especially of keystone species of ecosystems. We also need standardized and replicable modelling approaches that integrate these new data to account for eco‐evolutionary processes when predicting the impact of GCC on species' survival. Here, we discuss different genomic approaches that can be used to investigate and predict species responses to GCC. This can serve as guidance for researchers looking for the appropriate experimental setup for their particular system. We furthermore highlight future directions for moving forward in the field and allocating available resources more effectively, to implement mitigation measures before species go extinct and ecosystems lose important functions.

Arabidopsis halleri: a perennial model system for studying population differentiation and local adaptation

Local adaptation is assumed to occur when populations differ in a phenotypic trait or a set of traits, and such variation has a genetic basis. Here, we introduce Arabidopsis halleri and its life history as a perennial model system to study population differentiation and local adaptation. Studies on altitudinal adaptation have been conducted in two regions: Mt. Ibuki in Japan and the European Alps. Several studies have demonstrated altitudinal adaptation in ultraviolet-B (UV-B) tolerance, leaf water repellency against spring frost and anti-herbivore defences. Studies on population differentiation in A. halleri have also focused on metal hyperaccumulation and tolerance to heavy metal contamination. In these study systems, genome scans to identify candidate genes under selection have been applied. Lastly, we briefly discuss how RNA-Seq can broaden phenotypic space and serve as a link to underlying mechanisms. In conclusion, A. halleri provides us with opportunities to study population differentiation and local adaptation, and relate these to the genetic systems underlying target functional traits.

Divergence in Glucosinolate Profiles between High- and Low-Elevation Populations of Arabidopsis halleri Correspond to Variation in Field Herbivory and Herbivore Behavioral Preferences

Variation in local herbivore pressure along elevation gradients is predicted to drive variation in plant defense traits. Yet, the extent of intraspecific variation in defense investment along elevation gradients, and its effects on both herbivore preference and performance, remain relatively unexplored. Using populations of Arabidopsis halleri (Brassicaceae) occurring at different elevations in the Alps, we tested for associations between elevation, herbivore damage in the field, and constitutive chemical defense traits (glucosinolates) assayed under common-garden conditions. Additionally, we examined the feeding preferences and performance of a specialist herbivore, the butterfly Pieris brassicae, on plants from different elevations in the Alps. Although we found no effect of elevation on the overall levels of constitutive glucosinolates in leaves, relative amounts of indole glucosinolates increased significantly with elevation and were negatively correlated with herbivore damage in the field. In oviposition preference assays, P. brassicae females laid fewer eggs on plants from high-elevation populations, although larval performance was similar on populations from different elevations. Taken together, these results support the prediction that species distributed along elevation gradients exhibit genetic variation in chemical defenses, which can have consequences for interactions with herbivores in the field.

Diverse paths to hybrid incompatibility in Arabidopsis

One of the most essential questions of biology is to understand how different species have evolved. Hybrid incompatibility, a phenomenon in which hybrids show reduced fitness in comparison with their parents, can result in reproductive isolation and speciation. Therefore, studying hybrid incompatibility provides an entry point in understanding speciation. Hybrid incompatibilities are known throughout taxa, and the underlying mechanisms have mystified scientists since the theory of evolution by means of natural selection was introduced. In plants, it is only in recent years that the high-throughput genetic and molecular tools have become available for the Arabidopsis genus, thus helping to shed light on the different genes and molecular and evolutionary mechanisms that underlie hybrid incompatibilities. In this review, we highlight the current knowledge of diverse mechanisms that are known to contribute to hybrid incompatibility.

Strong impact of thermal environment on the quantitative genetic basis of a key stress tolerance trait

Most organisms experience variable and sometimes suboptimal environments in their lifetime. While stressful environmental conditions are normally viewed as a strong selective force, they can also impact directly on the genetic basis of traits such as through environment-dependent gene action. Here, we used the Drosophila melanogaster Genetic Reference Panel to investigate the impact of developmental temperature on variance components and evolutionary potential of cold tolerance. We reared 166 lines at five temperatures and assessed cold tolerance of adult male flies from each line and environment. We show (1) that the expression of genetic variation for cold tolerance is highly dependent on developmental temperature, (2) that the genetic correlation of cold tolerance between environments decreases as developmental temperatures become more distinct, (3) that the correlation between cold tolerance at individual developmental temperatures and plasticity for cold tolerance differs across developmental temperatures, and even switches sign across the thermal developmental gradient, and (4) that evolvability decrease with increasing developmental temperatures. Our results show that the quantitative genetic basis of low temperature tolerance is environment specific. This conclusion is important for the understanding of evolution in variable thermal environments and for designing experiments aimed at pinpointing candidate genes and performing functional analyses of thermal resistance.

Evolutionary dynamics of quantitative variation in an adaptive trait at the regional scale: The case of zinc hyperaccumulation in Arabidopsis halleri

Metal hyperaccumulation in plants is an ecological trait whose biological significance remains debated, in particular because the selective pressures that govern its evolutionary dynamics are complex. One of the possible causes of quantitative variation in hyperaccumulation may be local adaptation to metalliferous soils. Here, we explored the population genetic structure of Arabidopsis halleri at fourteen metalliferous and nonmetalliferous sampling sites in southern Poland. The results were integrated with a quantitative assessment of variation in zinc hyperaccumulation to trace local adaptation. We identified a clear hierarchical structure with two distinct genetic groups at the upper level of clustering. Interestingly, these groups corresponded to different geographic subregions, rather than to ecological types (i.e., metallicolous vs. nonmetallicolous). Also, approximate Bayesian computation analyses suggested that the current distribution of A. halleri in southern Poland could be relictual as a result of habitat fragmentation caused by climatic shifts during the Holocene, rather than due to recent colonization of industrially polluted sites. In addition, we find evidence that some nonmetallicolous lowland populations may have actually derived from metallicolous populations. Meanwhile, the distribution of quantitative variation in zinc hyperaccumulation did separate metallicolous and nonmetallicolous accessions, indicating more recent adaptive evolution and diversifying selection between metalliferous and nonmetalliferous habitats. This suggests that zinc hyperaccumulation evolves both ways-towards higher levels at nonmetalliferous sites and lower levels at metalliferous sites. Our results open a new perspective on possible evolutionary relationships between A. halleri edaphic types that may inspire future genetic studies of quantitative variation in metal hyperaccumulation.

Invoking adaptation to decipher the genetic legacy of past climate change

Persistence of natural populations during periods of climate change is likely to depend on migration (range shifts) or adaptation. These responses were traditionally considered discrete processes and conceptually divided into the realms of ecology and evolution. In a milestone paper, Davis and Shaw (2001) Science 292:673 argued that the interplay of adaptation and migration was central to biotic responses to Quaternary climate, but since then there has been no synthesis of efforts made to set up this research program. Here we review some of the salient findings from molecular genetic studies assessing ecological and evolutionary responses to Quaternary climate change. These studies have revolutionized our understanding of population processes associated with past species migration. However, knowledge remains limited about the role of natural selection for local adaptation of populations to Quaternary environmental fluctuations and associated range shifts, and for the footprints this might have left on extant populations. Next-generation sequencing technologies, high-resolution paleoclimate analyses, and advances in population genetic theory offer an unprecedented opportunity to test hypotheses about adaptation through time. Recent population genomics studies have greatly improved our understanding of the role of contemporary adaptation to local environments in shaping spatial patterns of genetic diversity across modern-day landscapes. Advances in this burgeoning field provide important conceptual and methodological bases to decipher the historical role of natural selection and assess adaptation to past environmental variation. We suggest that a process called "temporal conditional neutrality" has taken place: some alleles favored in glacial environments become selectively neutral in modern-day conditions, whereas some alleles that had been neutral during glacial periods become under selection in modern environments. Building on this view, we present a new integrative framework for addressing the interplay of demographic and adaptive evolutionary responses to Quaternary climate dynamics, the research agenda initially envisioned by Davis and Shaw (2001) Science 292:673.

Signatures of positive selection and local adaptation to urbanization in white-footed mice (Peromyscus leucopus)

Urbanization significantly alters natural ecosystems and has accelerated globally. Urban wildlife populations are often highly fragmented by human infrastructure, and isolated populations may adapt in response to local urban pressures. However, relatively few studies have identified genomic signatures of adaptation in urban animals. We used a landscape genomic approach to examine signatures of selection in urban populations of white-footed mice (Peromyscus leucopus) in New York City. We analysed 154,770 SNPs identified from transcriptome data from 48 P. leucopus individuals from three urban and three rural populations and used outlier tests to identify evidence of urban adaptation. We accounted for demography by simulating a neutral SNP data set under an inferred demographic history as a null model for outlier analysis. We also tested whether candidate genes were associated with environmental variables related to urbanization. In total, we detected 381 outlier loci and after stringent filtering, identified and annotated 19 candidate loci. Many of the candidate genes were involved in metabolic processes and have well-established roles in metabolizing lipids and carbohydrates. Our results indicate that white-footed mice in New York City are adapting at the biomolecular level to local selective pressures in urban habitats. Annotation of outlier loci suggests selection is acting on metabolic pathways in urban populations, likely related to novel diets in cities that differ from diets in less disturbed areas.