Genome‐wide single‐generation signatures of local selection in the panmictic European eel

Next‐generation sequencing and the collection of genome‐wide data allow identifying adaptive variation and footprints of directional selection. Using a large SNP data set from 259 RAD‐sequenced European eel individuals (glass eels) from eight locations between 34 and 64^oN, we examined the patterns of genome‐wide genetic diversity across locations. We tested for local selection by searching for increased population differentiation using F_ST‐based outlier tests and by testing for significant associations between allele frequencies and environmental variables. The overall low genetic differentiation found (F_ST = 0.0007) indicates that most of the genome is homogenized by gene flow, providing further evidence for genomic panmixia in the European eel. The lack of genetic substructuring was consistent at both nuclear and mitochondrial SNPs. Using an extensive number of diagnostic SNPs, results showed a low occurrence of hybrids between European and American eel, mainly limited to Iceland (5.9%), although individuals with signatures of introgression several generations back in time were found in mainland Europe. Despite panmixia, a small set of SNPs showed high genetic differentiation consistent with single‐generation signatures of spatially varying selection acting on glass eels. After screening 50 354 SNPs, a total of 754 potentially locally selected SNPs were identified. Candidate genes for local selection constituted a wide array of functions, including calcium signalling, neuroactive ligand–receptor interaction and circadian rhythm. Remarkably, one of the candidate genes identified is PERIOD, possibly related to differences in local photoperiod associated with the >30° difference in latitude between locations. Genes under selection were spread across the genome, and there were no large regions of increased differentiation as expected when selection occurs within just a single generation due to panmixia. This supports the conclusion that most of the genome is homogenized by gene flow that removes any effects of diversifying selection from each new generation.     

Genome-Wide Association Analysis of Adaptation Using Environmentally Predicted Traits

Current methods for studying the genetic basis of adaptation evaluate genetic associations with ecologically relevant traits or single environmental variables, under the implicit assumption that natural selection imposes correlations between phenotypes, environments and genotypes. In practice, observed trait and environmental data are manifestations of unknown selective forces and are only indirectly associated with adaptive genetic variation. In theory, improved estimation of these forces could enable more powerful detection of loci under selection. Here we present an approach in which we approximate adaptive variation by modeling phenotypes as a function of the environment and using the predicted trait in multivariate and univariate genome-wide association analysis (GWAS). Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate GWAS and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables. Our results provide an example of the use of environmental data to obtain independent and meaningful information on adaptive genetic variation.     

A quantitative genetics model for viability selection

Viability selection will change gene frequencies of loci controlling fitness. Consequently, the frequencies of marker loci linked to the viability loci will also change. In genetic mapping, the change of marker allelic frequencies is reflected by the departure from Mendelian segregation ratio. The non-Mendelian segregation of markers has been used to map viability loci along the genome. However, current methods have not been able to detect the amount of selection (s) and the degree of dominance (h) simultaneously. We developed a method to detect both s and h using an F2 mating design under the classical fitness model. We also developed a quantitative genetics model for viability selection by proposing a continuous liability controlling the viability of individuals. With the liability model, mapping viability loci has been formulated as mapping quantitative trait loci. As a result, nongenetic systematic environmental effects can be easily incorporated into the model and subsequently separated from the genetic effects of the viability loci. The quantitative genetic model has been verified with a series of Monte Carlo simulation experiments.     

Regional environmental pressure influences population differentiation in turbot (Scophthalmus maximus)

Unravelling the factors shaping the genetic structure of mobile marine species is challenging due to the high potential for gene flow. However, genetic inference can be greatly enhanced by increasing the genomic, geographical or environmental resolution of population genetic studies. Here, we investigated the population structure of turbot (Scophthalmus maximus) by screening 17 random and gene‐linked markers in 999 individuals at 290 geographical locations throughout the northeast Atlantic Ocean. A seascape genetics approach with the inclusion of high‐resolution oceanographical data was used to quantify the association of genetic variation with spatial, temporal and environmental parameters. Neutral loci identified three subgroups: an Atlantic group, a Baltic Sea group and one on the Irish Shelf. The inclusion of loci putatively under selection suggested an additional break in the North Sea, subdividing southern from northern Atlantic individuals. Environmental and spatial seascape variables correlated marginally with neutral genetic variation, but explained significant proportions (respectively, 8.7% and 10.3%) of adaptive genetic variation. Environmental variables associated with outlier allele frequencies included salinity, temperature, bottom shear stress, dissolved oxygen concentration and depth of the pycnocline. Furthermore, levels of explained adaptive genetic variation differed markedly between basins (3% vs. 12% in the North and Baltic Sea, respectively). We suggest that stable environmental selection pressure contributes to relatively strong local adaptation in the Baltic Sea. Our seascape genetic approach using a large number of sampling locations and associated oceanographical data proved useful for the identification of population units as the basis of management decisions.     

Natural selection influences AFLP intraspecific genetic variability and introgression patterns in Atlantic eels

Investigating patterns of genetic variation in hybridizing species provides an opportunity to understand the impact of natural selection on intraspecific genetic variability and interspecific gene exchange. The Atlantic eels Anguilla rostrata and A. anguilla each occupy a large heterogeneous habitat upon which natural selection could differentially shape genetic variation. They also produce viable hybrids only found in Iceland. However, the possible footprint of natural selection on patterns of genetic variation within species and introgressive hybridization in Icelandic eels has never been assessed. We revisited amplified fragment length polymorphism data collected previously using population genomics and admixture analyses to test if (i) genetic variation could be influenced by non-neutral mechanisms at both the intra- and interspecific levels, and if (ii) selection could shape the spatio-temporal distribution of Icelandic hybrids. We first found candidate loci for directional selection within both species. Spatial distributions of allelic frequencies displayed by some of these loci were possibly related with the geographical patterns of life-history traits in A. rostrata , and could have been shaped by natural selection associated with an environmental gradient along European coasts in A. anguilla . Second, we identified outlier loci at the interspecific level. Non-neutral introgression was strongly suggested for some of these loci. We detected a locus at which typical A. rostrata allele hardly crossed the species genetic barrier, whereas three other loci showed accelerated patterns of introgression into A. anguilla in Iceland. Moreover, the level of introgression at these three loci increased from the glass eel to the yellow eel stage, supporting the hypothesis that differential survival of admixed genotypes partly explains the spatio-temporal pattern of hybrid abundance previously documented in Iceland.     

Emergence of long‐term balanced polymorphism under cyclic selection of spatially variable magnitude

A fundamental question in evolutionary biology is what promotes genetic variation at nonneutral loci, a major precursor to adaptation in changing environments. In particular, balanced polymorphism under realistic evolutionary models of temporally varying environments in finite natural populations remains to be demonstrated. Here, we propose a novel mechanism of balancing selection under temporally varying fitnesses. Using forward‐in‐time computer simulations and mathematical analysis, we show that cyclic selection that spatially varies in magnitude, such as along an environmental gradient, can lead to elevated levels of nonneutral genetic polymorphism in finite populations. Balanced polymorphism is more likely with an increase in gene flow, magnitude and period of fitness oscillations, and spatial heterogeneity. This polymorphism‐promoting effect is robust to small systematic fitness differences between competing alleles or to random environmental perturbation. Furthermore, we demonstrate analytically that protected polymorphism arises as spatially heterogeneous cyclic fitness oscillations generate a type of storage effect that leads to negative frequency dependent selection. Our findings imply that spatially variable cyclic environments can promote elevated levels of nonneutral genetic variation in natural populations.     

INTEGRATING LANDSCAPE GENOMICS AND SPATIALLY EXPLICIT APPROACHES TO DETECT LOCI UNDER SELECTION IN CLINAL POPULATIONS

Uncovering the genetic basis of adaptation hinges on the ability to detect loci under selection. However, population genomics outlier approaches to detect selected loci may be inappropriate for clinal populations or those with unclear population structure because they require that individuals be clustered into populations. An alternate approach, landscape genomics, uses individual‐based approaches to detect loci under selection and reveal potential environmental drivers of selection. We tested four landscape genomics methods on a simulated clinal population to determine their effectiveness at identifying a locus under varying selection strengths along an environmental gradient. We found all methods produced very low type I error rates across all selection strengths, but elevated type II error rates under “weak” selection. We then applied these methods to an AFLP genome scan of an alpine plant, Campanula barbata, and identified five highly supported candidate loci associated with precipitation variables. These loci also showed spatial autocorrelation and cline patterns indicative of selection along a precipitation gradient. Our results suggest that landscape genomics in combination with other spatial analyses provides a powerful approach for identifying loci potentially under selection and explaining spatially complex interactions between species and their environment.     

Identifying genetic signatures of selection in a non-model species, alpine gentian (Gentiana nivalis L.), using a landscape genetic approach

It is generally accepted that most plant populations are locally adapted. Yet, understanding how environmental forces give rise to adaptive genetic variation is a challenge in conservation genetics and crucial to the preservation of species under rapidly changing climatic conditions. Environmental variation, phylogeographic history, and population demographic processes all contribute to spatially structured genetic variation, however few current models attempt to separate these confounding effects. To illustrate the benefits of using a spatially-explicit model for identifying potentially adaptive loci, we compared outlier locus detection methods with a recently-developed landscape genetic approach. We analyzed 157 loci from samples of the alpine herb Gentiana nivalis collected across the European Alps. Principle coordinates of neighbor matrices (PCNM), eigenvectors that quantify multi-scale spatial variation present in a data set, were incorporated into a landscape genetic approach relating AFLP frequencies with 23 environmental variables. Four major findings emerged. 1) Fifteen loci were significantly correlated with at least one predictor variable (R _adj ²  > 0.5). 2) Models including PCNM variables identified eight more potentially adaptive loci than models run without spatial variables. 3) When compared to outlier detection methods, the landscape genetic approach detected four of the same loci plus 11 additional loci. 4) Temperature, precipitation, and solar radiation were the three major environmental factors driving potentially adaptive genetic variation in G. nivalis. Techniques presented in this paper offer an efficient method for identifying potentially adaptive genetic variation and associated environmental forces of selection, providing an important step forward for the conservation of non-model species under global change.     

Controlling for P‐value inflation in allele frequency change in experimental evolution and artificial selection experiments

Experimental evolution studies can be used to explore genomic response to artificial and natural selection. In such studies, loci that display larger allele frequency change than expected by genetic drift alone are assumed to be directly or indirectly associated with traits under selection. However, such studies report surprisingly many loci under selection, suggesting that current tests for allele frequency change may be subject to P‐value inflation and hence be anticonservative. One factor known from genomewide association (GWA) studies to cause P‐value inflation is population stratification, such as relatedness among individuals. Here, we suggest that by treating presence of an individual in a population after selection as a binary response variable, existing GWA methods can be used to account for relatedness when estimating allele frequency change. We show that accounting for relatedness like this effectively reduces false‐positives in tests for allele frequency change in simulated data with varying levels of population structure. However, once relatedness has been accounted for, the power to detect causal loci under selection is low. Finally, we demonstrate the presence of P‐value inflation in allele frequency change in empirical data spanning multiple generations from an artificial selection experiment on tarsus length in two free‐living populations of house sparrow and correct for this using genomic control. Our results indicate that since allele frequencies in large parts of the genome may change when selection acts on a heritable trait, such selection is likely to have considerable and immediate consequences for the eco‐evolutionary dynamics of the affected populations.     

Maintenance of clinal variation for shell colour phenotype in the flat periwinkle Littorina obtusata

Clines can signal spatially varying selection and therefore have long been used to investigate the role of environmental heterogeneity in maintaining genetic variation. However, clinal patterns alone are not sufficient to reject neutrality or to establish the mechanism of selection. Indirect, inferential methods can be used to address neutrality and mechanism, but fully understanding the adaptive significance of clinal variation ultimately requires a direct approach. Ecological model systems such as the rocky intertidal provide a useful context for direct experimentation and can serve as a complement to studies in more traditional genetic model systems. In this study, we use indirect and direct approaches to investigate the role of environmental heterogeneity in the maintenance of shell colour polymorphism in the flat periwinkle snail, Littorina obtusata. We document replicated clines in shell colour morph frequencies over thermal gradients at two spatial scales, contrasting with patterns at previously reported microsatellite loci. In addition, experimental results demonstrate that that shell colour has predictable effects on shell temperature and that these differences in temperature, in turn, coincide with patterns of survivorship under episodic thermal stress. Direct manipulation of shell colour revealed that shell colour, and not a correlated character, was the target of selection. Our study provides evidence that spatially varying selection via thermal regime contributes to the maintenance of shell colour phenotype variation in L. obtusata in the sampled areas of the Gulf of Maine.     

Adaptations to new environments in humans: the role of subtle allele frequency shifts

Humans show tremendous phenotypic diversity across geographically distributed populations, and much of this diversity undoubtedly results from genetic adaptations to different environmental pressures. The availability of genome-wide genetic variation data from densely sampled populations offers unprecedented opportunities for identifying the loci responsible for these adaptations and for elucidating the genetic architecture of human adaptive traits. Several approaches have been used to detect signals of selection in human populations, and these approaches differ in the assumptions they make about the underlying mode of selection. We contrast the results of approaches based on haplotype structure and differentiation of allele frequencies to those from a method for identifying single nucleotide polymorphisms strongly correlated with environmental variables. Although the first group of approaches tends to detect new beneficial alleles that were driven to high frequencies by selection, the environmental correlation approach has power to identify alleles that experienced small shifts in frequency owing to selection. We suggest that the first group of approaches tends to identify only variants with relatively strong phenotypic effects, whereas the environmental correlation methods can detect variants that make smaller contributions to an adaptive trait.     

Temporal and Microgeographic Variation in Allozyme Frequencies in a Natural Population of DROSOPHILA BUZZATII

Temporal variation in allozyme frequencies at six loci was studied by making monthly collections over 4 yr in one population of the cactophilic species Drosophila buzzatii. Ten sites were defined within the study locality, and for all temporal samples, separate collections were made at each of these sites. Population structure over microgeographic space and changes in population structure over time were analyzed using F-statistic estimators, and multivariate analyses of allele and genotype frequencies with environmental variables were carried out. Allele frequencies showed significant variation over time, although there were no clear cyclical or seasonal patterns. A biplot analysis of allele frequencies over seasons within years and over years showed clear discrimination among years by alleles at four loci. During the 4 yr, three alleles showed directional changes which were associated with directional changes in environmental variables. Significant associations with one or more environmental variables were found for allele frequencies at every locus and for both expected and observed heterozygosities (except those for Est-1 and Est-2). Thus, variation in allele frequencies over time cannot be attributed solely to drift. Significant linkage disequilibria were detected among three loci (Est-2, Hex and Aldox), but there was no evidence for spatial or temporal patterns. The F-statistic analyses showed significant differentiation among months within years for all loci, but the statistic used (coancestry) was heterogeneous among loci. Estimates of F (inbreeding) for all loci were significantly different from zero, with the loci in four groups, Adh-1 (negative), Pgm(small positive), Est-2 and Hex (intermediate) and Est-1 and Aldox (high positive). The correlation of genes within individuals within populations (f) for each locus in each month by site sample differed among loci, as did the (f) for each locus in each month by site sample differed among loci, as did the patterns of change in f over time (seasons). Heterogeneity in the F-statistic estimates indicates that natural selection is directly or indirectly affecting allele and genotype frequencies at some loci. However, the F-statistic analyses showed essentially no microgeographic structure (i.e., among sites), although there was significant heterogeneity in allele frequencies among flies emerging from individual rots. Thus, microspatial heterogeneity probably is most important at the level of individual rots, and coupled with habitat selection, it could be a major factor promoting diversifying selection and the maintenance of polymorphism.(ABSTRACT TRUNCATED AT 400 WORDS)     

Signatures of natural selection between life cycle stages separated by metamorphosis in European eel

Background

Species showing complex life cycles provide excellent opportunities to study the genetic associations between life cycle stages, as selective pressures may differ before and after metamorphosis. The European eel presents a complex life cycle with two metamorphoses, a first metamorphosis from larvae into glass eels (juvenile stage) and a second metamorphosis into silver eels (adult stage). We tested the hypothesis that different genes and gene pathways will be under selection at different life stages when comparing the genetic associations between glass eels and silver eels.

Results

We used two sets of markers to test for selection: first, we genotyped individuals using a panel of 80 coding-gene single nucleotide polymorphisms (SNPs) developed in American eel; second, we investigated selection at the genome level using a total of 153,423 RAD-sequencing generated SNPs widely distributed across the genome. Using the RAD approach, outlier tests identified a total of 2413 (1.57 %) potentially selected SNPs. Functional annotation analysis identified signal transduction pathways as the most over-represented group of genes, including MAPK/Erk signalling, calcium signalling and GnRH (gonadotropin-releasing hormone) signalling. Many of the over-represented pathways were related to growth, while others could result from the different conditions that eels inhabit during their life cycle.

Conclusions

The observation of different genes and gene pathways under selection when comparing glass eels vs. silver eels supports the adaptive decoupling hypothesis for the benefits of metamorphosis. Partitioning the life cycle into discrete morphological phases may be overall beneficial since it allows the different life stages to respond independently to their unique selection pressures. This might translate into a more effective use of food and niche resources and/or performance of phase-specific tasks (e.g. feeding in the case of glass eels, migrating and reproducing in the case of silver eels).

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1754-3) contains supplementary material, which is available to authorized users.     

Neutral and adaptive drivers of genomic change in introduced brook trout (Salvelinus fontinalis) populations revealed by pooled sequencing

Understanding the drivers of successful species invasions is important for conserving native biodiversity and for mitigating the economic impacts of introduced species. However, whole‐genome resolution investigations of the underlying contributions of neutral and adaptive genetic variation in successful introductions are rare. Increased propagule pressure should result in greater neutral genetic variation, while environmental differences should elicit selective pressures on introduced populations, leading to adaptive differentiation. We investigated neutral and adaptive variation among nine introduced brook trout (Salvelinus fontinalis) populations using whole‐genome pooled sequencing. The populations inhabit isolated alpine lakes in western Canada and descend from a common source, with an average of ~19 (range of 7–41) generations since introduction. We found some evidence of bottlenecks without recovery, no strong evidence of purifying selection, and little support that varying propagule pressure or differences in local environments shaped observed neutral genetic variation differences. Putative adaptive loci analysis revealed nonconvergent patterns of adaptive differentiation among lakes with minimal putatively adaptive loci (0.001%–0.15%) that did not correspond with tested environmental variables. Our results suggest that (i) introduction success is not always strongly influenced by genetic load; (ii) observed differentiation among introduced populations can be idiosyncratic, population‐specific, or stochastic; and (iii) conservatively, in some introduced species, colonization barriers may be overcome by support through one aspect of propagule pressure or benign environmental conditions.     

Correlations of allele frequencies with physical and environmental variables for populations of largemouth bass, Micropterus salmoides (Lacepede)

Differences in the biochemical genetic structure of each of 90 populations of largemouth bass, Micropterus salmoides (Lacepede), were detected by vertical starch gel electrophoresis. The allele frequencies at each of 28 enzyme loci were tested for correlation with 24 physical and environmental variables determined for each body of water from which the populations were sampled. The allele frequencies at several loci (malate dehydrogenase-B, isocitrate dehydrogenase-B, superoxide dismutase-A, and aspartate aminotransferase-B) were highly significantly correlated ( P ≤0.000l) with several physical and environmental variables (latitude, heating degree-days, cooling degree-days, and the length of the growing season). These correlations are consistent with the hypothesis that allelic differences at specific enzyme loci can confer different degrees of fitness in different thermal environments. Additional laboratory and field studies will be required to determine the extent to which allelic variants at a given enzyme locus contribute to thermal tolerance and thermal preference of largemouth bass.     

A spatial analysis method (SAM) to detect candidate loci for selection: towards a landscape genomics approach to adaptation

The detection of adaptive loci in the genome is essential as it gives the possibility of understanding what proportion of a genome or which genes are being shaped by natural selection. Several statistical methods have been developed which make use of molecular data to reveal genomic regions under selection. In this paper, we propose an approach to address this issue from the environmental angle, in order to complement results obtained by population genetics. We introduce a new method to detect signatures of natural selection based on the application of spatial analysis, with the contribution of geographical information systems (GIS), environmental variables and molecular data. Multiple univariate logistic regressions were carried out to test for association between allelic frequencies at marker loci and environmental variables. This spatial analysis method (SAM) is similar to current population genomics approaches since it is designed to scan hundreds of markers to assess a putative association with hundreds of environmental variables. Here, by application to studies of pine weevils and breeds of sheep we demonstrate a strong correspondence between SAM results and those obtained using population genetics approaches. Statistical signals were found that associate loci with environmental parameters, and these loci behave atypically in comparison with the theoretical distribution for neutral loci. The contribution of this new tool is not only to permit the identification of loci under selection but also to establish hypotheses about ecological factors that could exert the selection pressure responsible. In the future, such an approach may accelerate the process of hunting for functional genes at the population level.     

Genetic variability in white-tailed deer (Odocoileus virginianus) and its relationship to environmental parameters and herd origin (Cervidae)

Allozyme variation was examined in 1571 white-tailed deer (Odocoileus virginianus) from 29 localities in Tennessee by starch gel electrophoresis. For 11 polymorphic loci, sex-related, age-related and temporal differences were minimal. However, significant spatial hererogeneity was evident in genotypes (contingency table results), allele frequencies (F _ST=0.057) and heterozygosity. Heterozygosity ranged from 16.9% to 26.8% with a mean of 22.9%. The spatial pattern of allele frequencies determined from Rogers' coefficients of genetic similarity indicated associations based on geographic proximity and stocking history. In hierarchial analyses, physiographic regions accounted for more of the total gene diversity than herd origin groups (populations of similar origin) but less than individual populations. For five loci, physiographic regions accounted for more of the gene diversity than populations, suggesting a selection role in the observed genetic variability. Bivariate and canonical correlation analyses revealed significant associations between environmental and genetic variables. Temperature variables and allele frequencies for three loci (alcohol dehydrogenase, alpha-glycerophosphate dehydrogenase, sorbitol dehydrogenase) had the prominent roles in the multivariate association between environmental and genetic variables. Herd origin, gene flow and selection appear to be involved in the gene diversity in deer from Tennesee.     

Simulating the evolution of a clonal trait in plants with sexual and vegetative reproduction

Aims Phenotypic optimality models neglect genetics. However, especially when heterozygous genotypes are fittest, evolving allele, genotype and phenotype frequencies may not correspond to predicted optima. This was not previously addressed for organisms with complex life histories.Methods Therefore, we modelled the evolution of a fitness-relevant trait of clonal plants, stolon internode length. We explored the likely case of an asymmetric unimodal fitness profile with three model types. In constant selection models (CSMs), which are gametic, but not spatially explicit, evolving allele frequencies in the one-locus and five-loci cases did not correspond to optimum stolon internode length predicted by the spatially explicit, but not gametic, phenotypic model. This deviation was due to the asymmetry of the fitness profile. Gametic, spatially explicit individual-based (SEIB) modeling allowed us relaxing the CSM assumptions of constant selection with exclusively sexual reproduction.Important findings For entirely vegetative or sexual reproduction, predictions of the gametic SEIB model were close to the ones of spatially explicit non-gametic phenotypic models, but for mixed modes of reproduction they approximated those of gametic, not spatially explicit CSMs. Thus, in contrast to gametic SEIB models, phenotypic models and, especially for few loci, also CSMs can be very misleading. We conclude that the evolution of traits governed by few quantitative trait loci appears hardly predictable by simple models, that genetic algorithms aiming at technical optimization may actually miss the optimum and that selection may lead to loci with smaller effects in derived compared with ancestral lines.     

Finding needles in a genomic haystack: targeted capture identifies clear signatures of selection in a nonmodel plant species

Teasing apart neutral and adaptive genomic processes and identifying loci that are targets of selection can be difficult, particularly for nonmodel species that lack a reference genome. However, identifying such loci and the factors driving selection have the potential to greatly assist conservation and restoration practices, especially for the management of species in the face of contemporary and future climate change. Here, we focus on assessing adaptive genomic variation within a nonmodel plant species, the narrow‐leaf hopbush (Dodonaea viscosa ssp. angustissima), commonly used for restoration in Australia. We used a hybrid‐capture target enrichment approach to selectively sequence 970 genes across 17 populations along a latitudinal gradient from 30°S to 36°S. We analysed 8462 single‐nucleotide polymorphisms (SNPs) for F_ST outliers as well as associations with environmental variables. Using three different methods, we found 55 SNPs with significant correlations to temperature and water availability, and 38 SNPs to elevation. Genes containing SNPs identified as under environmental selection were diverse, including aquaporin and abscisic acid genes, as well as genes with ontologies relating to responses to environmental stressors such as water deprivation and salt stress. Redundancy analysis demonstrated that only a small proportion of the total genetic variance was explained by environmental variables. We demonstrate that selection has led to clines in allele frequencies in a number of functional genes, including those linked to leaf shape and stomatal variation, which have been previously observed to vary along the sampled environmental cline. Using our approach, gene regions subject to environmental selection can be readily identified for nonmodel organisms.     

Riverscape genomics of a threatened fish across a hydroclimatically heterogeneous river basin

Understanding how natural selection generates and maintains adaptive genetic diversity in heterogeneous environments is key to predicting the evolutionary response of populations to rapid environmental change. Detecting selection in complex spatial environments remains challenging, especially for threatened species where the effects of strong genetic drift may overwhelm signatures of selection. We carried out a basinwide riverscape genomic analysis in the threatened southern pygmy perch (Nannoperca australis), an ecological specialist with low dispersal potential. High‐resolution environmental data and 5162 high‐quality filtered SNPs were used to clarify spatial population structure and to assess footprints of selection associated with a steep hydroclimatic gradient and with human disturbance across the naturally and anthropogenically fragmented Murray–Darling Basin (Australia). Our approach included F_ST outlier tests to define neutral loci, and a combination of spatially explicit genotype–environment association analyses to identify candidate adaptive loci while controlling for the effects of landscape structure and shared population history. We found low levels of genetic diversity and strong neutral population structure consistent with expectations based on spatial stream hierarchy and life history. In contrast, variables related to precipitation and temperature appeared as the most important environmental surrogates for putatively adaptive genetic variation at both regional and local scales. Human disturbance also influenced the variation in candidate loci for adaptation, but only at a local scale. Our study contributes to understanding of adaptive evolution along naturally and anthropogenically fragmented ecosystems. It also offers a tangible example of the potential contributions of landscape genomics for informing in situ and ex situ conservation management of biodiversity.