Exploring genomic variation associated with drought stress in Picea mariana populations

Predicted increases in drought and heat stress will likely induce shifts in species bioclimatic envelopes. Genetic variants adapted to water limitation may prove pivotal for species response under scenarios of increasing drought. In this study, we aimed to explore this hypothesis by investigating genetic variation in 16 populations of black spruce (Picea mariana) in relation to climate variables in Alaska. A total of 520 single nucleotide polymorphisms (SNPs) were genotyped for 158 trees sampled from areas of contrasting climate regimes. We used multivariate and univariate genotype‐by‐environment approaches along with available gene annotations to investigate the relationship between climate and genetic variation among sampled populations. Nine SNPs were identified as having a significant association with climate, of which five were related to drought stress response. Outlier SNPs with respect to the overall environment were significantly overrepresented for several biological functions relevant for coping with variable hydric regimes, including osmotic stress response. This genomic imprint is consistent with local adaptation of black spruce to drought stress. These results suggest that natural selection acting on standing variation prompts local adaptation in forest stands facing water limitation. Improved understanding of possible adaptive responses could inform our projections about future forest dynamics and help prioritize populations that harbor valuable genetic diversity for conservation.     

Characterizing genomic variation of Arabidopsis thaliana: the roles of geography and climate

Arabidopsis thaliana inhabits diverse climates and exhibits varied phenology across its range. Although A. thaliana is an extremely well‐studied model species, the relationship between geography, growing season climate and its genetic variation is poorly characterized. We used redundancy analysis (RDA) to quantify the association of genomic variation [214 051 single nucleotide polymorphisms (SNPs)] with geography and climate among 1003 accessions collected from 447 locations in Eurasia. We identified climate variables most correlated with genomic variation, which may be important selective gradients related to local adaptation across the species range. Climate variation among sites of origin explained slightly more genomic variation than geographical distance. Large‐scale spatial gradients and early spring temperatures explained the most genomic variation, while growing season and summer conditions explained the most after controlling for spatial structure. SNP variation in Scandinavia showed the greatest climate structure among regions, possibly because of relatively consistent phenology and life history of populations in this region. Climate variation explained more variation among nonsynonymous SNPs than expected by chance, suggesting that much of the climatic structure of SNP correlations is due to changes in coding sequence that may underlie local adaptation.     

Comparing methods for detecting multilocus adaptation with multivariate genotype–environment associations

Identifying adaptive loci can provide insight into the mechanisms underlying local adaptation. Genotype–environment association (GEA) methods, which identify these loci based on correlations between genetic and environmental data, are particularly promising. Univariate methods have dominated GEA, despite the high dimensional nature of genotype and environment. Multivariate methods, which analyse many loci simultaneously, may be better suited to these data as they consider how sets of markers covary in response to environment. These methods may also be more effective at detecting adaptive processes that result in weak, multilocus signatures. Here, we evaluate four multivariate methods and five univariate and differentiation‐based approaches, using published simulations of multilocus selection. We found that Random Forest performed poorly for GEA. Univariate GEAs performed better, but had low detection rates for loci under weak selection. Constrained ordinations, particularly redundancy analysis (RDA), showed a superior combination of low false‐positive and high true‐positive rates across all levels of selection. These results were robust across the demographic histories, sampling designs, sample sizes and weak population structure tested here. The value of combining detections from different methods was variable and depended on the study goals and knowledge of the drivers of selection. Re‐analysis of genomic data from grey wolves highlighted the unique, covarying sets of adaptive loci that could be identified using RDA. Although additional testing is needed, this study indicates that RDA is an effective means of detecting adaptation, including signatures of weak, multilocus selection, providing a powerful tool for investigating the genetic basis of 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.     

Regional differences in the abiotic environment contribute to genomic divergence within a wild tomato species

The wild currant tomato Solanum pimpinellifolium inhabits a wide range of abiotic habitats across its native range of Ecuador and Peru. Although it has served as a key genetic resource for the improvement of domestic cultivars, little is known about the genetic basis of traits underlying local adaptation in this species, nor what abiotic variables are most important for driving differentiation. Here we use redundancy analysis (RDA) and other multivariate statistical methods (structural equation modelling [SEM] and generalized dissimilarity modelling [GDM]) to quantify the relationship of genomic variation (6,830 single nucleotide polymorphisms [SNPs]) with climate and geography, among 140 wild accessions. RDA, SEM and GDM each identified environment as explaining more genomic variation than geography, suggesting that local adaptation to heterogeneous abiotic habitats may be an important source of genetic diversity in this species. Environmental factors describing temporal variation in precipitation and evaporative demand explained the most SNP variation among accessions, indicating that these forces may represent key selective agents. Lastly, by studying how SNP–environment associations vary throughout the genome (44,064 SNPs), we mapped the location and investigated the functions of loci putatively contributing to climatic adaptations. Together, our findings indicate an important role for selection imposed by the abiotic environment in driving genomic differentiation between populations.     

The genomic footprint of climate adaptation in Chironomus riparius

The gradual heterogeneity of climatic factors poses varying selection pressures across geographic distances that leave signatures of clinal variation in the genome. Separating signatures of clinal adaptation from signatures of other evolutionary forces, such as demographic processes, genetic drift and adaptation, to nonclinal conditions of the immediate local environment is a major challenge. Here, we examine climate adaptation in five natural populations of the harlequin fly Chironomus riparius sampled along a climatic gradient across Europe. Our study integrates experimental data, individual genome resequencing, Pool‐Seq data and population genetic modelling. Common‐garden experiments revealed significantly different population growth rates at test temperatures corresponding to the population origin along the climate gradient, suggesting thermal adaptation on the phenotypic level. Based on a population genomic analysis, we derived empirical estimates of historical demography and migration. We used an F_ST outlier approach to infer positive selection across the climate gradient, in combination with an environmental association analysis. In total, we identified 162 candidate genes as genomic basis of climate adaptation. Enriched functions among these candidate genes involved the apoptotic process and molecular response to heat, as well as functions identified in studies of climate adaptation in other insects. Our results show that local climate conditions impose strong selection pressures and lead to genomic adaptation despite strong gene flow. Moreover, these results imply that selection to different climatic conditions seems to converge on a functional level, at least between different insect species.     

Landscape genomics and a common garden trial reveal adaptive differentiation to temperature across Europe in the tree species Alnus glutinosa

The adaptive potential of tree species to cope with climate change has important ecological and economic implications. Many temperate tree species experience a wide range of environmental conditions, suggesting high adaptability to new environmental conditions. We investigated adaptation to regional climate in the drought‐sensitive tree species Alnus glutinosa (Black alder), using a complementary approach that integrates genomic, phenotypic and landscape data. A total of 24 European populations were studied in a common garden and through landscape genomic approaches. Genotyping‐by‐sequencing was used to identify SNPs across the genome, resulting in 1990 SNPs. Although a relatively low percentage of putative adaptive SNPs was detected (2.86% outlier SNPs), we observed clear associations among outlier allele frequencies, temperature and plant traits. In line with the typical drought avoiding nature of A. glutinosa, leaf size varied according to a temperature gradient and significant associations with multiple outlier loci were observed, corroborating the ecological relevance of the observed outlier SNPs. Moreover, the lack of isolation by distance, the very low genetic differentiation among populations and the high intrapopulation genetic variation all support the notion that high gene exchange combined with strong environmental selection promotes adaptation to environmental cues.     

Evidence of genomic adaptation to climate in Eucalyptus microcarpa: Implications for adaptive potential to projected climate change

Understanding whether populations can adapt in situ or whether interventions are required is of key importance for biodiversity management under climate change. Landscape genomics is becoming an increasingly important and powerful tool for rapid assessments of climate adaptation, especially in long‐lived species such as trees. We investigated climate adaptation in Eucalyptus microcarpa using the DArTseq genomic approach. A combination of F_ST outlier and environmental association analyses were performed using >4200 genomewide single nucleotide polymorphisms (SNPs) from 26 populations spanning climate gradients in southeastern Australia. Eighty‐one SNPs were identified as putatively adaptive, based on significance in F_ST outlier tests and significant associations with one or more climate variables related to temperature (70/81), aridity (37/81) or precipitation (35/81). Adaptive SNPs were located on all 11 chromosomes, with no particular region associated with individual climate variables. Climate adaptation appeared to be characterized by subtle shifts in allele frequencies, with no consistent fixed differences identified. Based on these associations, we predict adaptation under projected changes in climate will include a suite of shifts in allele frequencies. Whether this can occur sufficiently rapidly through natural selection within populations, or would benefit from assisted gene migration, requires further evaluation. In some populations, the absence or predicted increases to near fixation of particular adaptive alleles hint at potential limits to adaptive capacity. Together, these results reinforce the importance of standing genetic variation at the geographic level for maintaining species’ evolutionary potential.     

Adaptive population divergence and directional gene flow across steep elevational gradients in a climate‐sensitive mammal

The ecological effects of climate change have been shown in most major taxonomic groups; however, the evolutionary consequences are less well‐documented. Adaptation to new climatic conditions offers a potential long‐term mechanism for species to maintain viability in rapidly changing environments, but mammalian examples remain scarce. The American pika (Ochotona princeps) has been impacted by recent climate‐associated extirpations and range‐wide reductions in population sizes, establishing it as a sentinel mammalian species for climate change. To investigate evidence for local adaptation and reconstruct patterns of genomic diversity and gene flow across rapidly changing environments, we used a space‐for‐time design and restriction site‐associated DNA sequencing to genotype American pikas along two steep elevational gradients at 30,966 SNPs and employed independent outlier detection methods that scanned for genotype‐environment associations. We identified 338 outlier SNPs detected by two separate analyses and/or replicated in both transects, several of which were annotated to genes involved in metabolic function and oxygen transport. Additionally, we found evidence of directional gene flow primarily downslope from high‐elevation populations, along with reduced gene flow at outlier loci. If this trend continues, elevational range contractions in American pikas will likely be from local extirpation rather than upward movement of low‐elevation individuals; this, in turn, could limit the potential for adaptation within this landscape. These findings are of particular relevance for future conservation and management of American pikas and other elevationally restricted, thermally sensitive species.     

Whole‐genome resequencing uncovers molecular signatures of natural and sexual selection in wild bighorn sheep

The identification of genes influencing fitness is central to our understanding of the genetic basis of adaptation and how it shapes phenotypic variation in wild populations. Here, we used whole‐genome resequencing of wild Rocky Mountain bighorn sheep (Ovis canadensis) to >50‐fold coverage to identify 2.8 million single nucleotide polymorphisms (SNPs) and genomic regions bearing signatures of directional selection (i.e. selective sweeps). A comparison of SNP diversity between the X chromosome and the autosomes indicated that bighorn males had a dramatically reduced long‐term effective population size compared to females. This probably reflects a long history of intense sexual selection mediated by male–male competition for mates. Selective sweep scans based on heterozygosity and nucleotide diversity revealed evidence for a selective sweep shared across multiple populations at RXFP2, a gene that strongly affects horn size in domestic ungulates. The massive horns carried by bighorn rams appear to have evolved in part via strong positive selection at RXFP2. We identified evidence for selection within individual populations at genes affecting early body growth and cellular response to hypoxia; however, these must be interpreted more cautiously as genetic drift is strong within local populations and may have caused false positives. These results represent a rare example of strong genomic signatures of selection identified at genes with known function in wild populations of a nonmodel species. Our results also showcase the value of reference genome assemblies from agricultural or model species for studies of the genomic basis of adaptation in closely related wild taxa.     

Water availability drives signatures of local adaptation in whitebark pine (Pinus albicaulis Engelm.) across fine spatial scales of the Lake Tahoe Basin,USA

Patterns of local adaptation at fine spatial scales are central to understanding how evolution proceeds, and are essential to the effective management of economically and ecologically important forest tree species. Here, we employ single and multilocus analyses of genetic data (n = 116 231 SNPs) to describe signatures of fine‐scale adaptation within eight whitebark pine (Pinus albicaulis Engelm.) populations across the local extent of the environmentally heterogeneous Lake Tahoe Basin, USA. We show that despite highly shared genetic variation (F_ST = 0.0069), there is strong evidence for adaptation to the rain shadow experienced across the eastern Sierra Nevada. Specifically, we build upon evidence from a common garden study and find that allele frequencies of loci associated with four phenotypes (mean = 236 SNPs), 18 environmental variables (mean = 99 SNPs), and those detected through genetic differentiation (n = 110 SNPs) exhibit significantly higher signals of selection (covariance of allele frequencies) than could be expected to arise, given the data. We also provide evidence that this covariance tracks environmental measures related to soil water availability through subtle allele frequency shifts across populations. Our results replicate empirical support for theoretical expectations of local adaptation for populations exhibiting strong gene flow and high selective pressures and suggest that ongoing adaptation of many P. albicaulis populations within the Lake Tahoe Basin will not be constrained by the lack of genetic variation. Even so, some populations exhibit low levels of heritability for the traits presumed to be related to fitness. These instances could be used to prioritize management to maintain adaptive potential. Overall, we suggest that established practices regarding whitebark pine conservation be maintained, with the additional context of fine‐scale adaptation.     

On the roles of landscape heterogeneity and environmental variation in determining population genomic structure in a dendritic system

Dispersal and natural selection are key evolutionary processes shaping the distribution of phenotypic and genetic diversity. For species inhabiting complex spatial environments however, it is unclear how the balance between gene flow and selection may be influenced by landscape heterogeneity and environmental variation. Here, we evaluated the effects of dendritic landscape structure and the selective forces of hydroclimatic variation on population genomic parameters for the Murray River rainbowfish, Melanotaenia fluviatilis across the Murray–Darling Basin, Australia. We genotyped 249 rainbowfish at 17,503 high‐quality SNP loci and integrated these with models of network connectivity and high‐resolution environmental data within a riverscape genomics framework. We tested competing models of gene flow before using multivariate genotype–environment association (GEA) analysis to test for signals of adaptive divergence associated with hydroclimatic variation. Patterns of neutral genetic variation were consistent with expectations based on the stream hierarchy model and M. fluviatilis’ moderate dispersal ability. Models incorporating dendritic network structure suggested that landscape heterogeneity is a more important factor determining connectivity and gene flow than waterway distance. Extending these results, we also introduce a novel approach to controlling for the unique effects of dendritic network structure in GEA analyses of populations of aquatic species. We identified 146 candidate loci potentially underlying a polygenic adaptive response to seasonal fluctuations in stream flow and variation in the relative timing of temperature and precipitation extremes. Our findings underscore an emerging predominant role for seasonal variation in hydroclimatic conditions driving local adaptation and are relevant for informing proactive conservation management.     

Local adaptation across a complex bioclimatic landscape in two montane bumble bee species

Understanding evolutionary responses to variation in temperature and precipitation across species ranges is of fundamental interest given ongoing climate change. The importance of temperature and precipitation for multiple aspects of bumble bee (Bombus) biology, combined with large geographic ranges that expose populations to diverse environmental pressures, make these insects well‐suited for studying local adaptation. Here, we analyzed genome‐wide sequence data from two widespread bumble bees, Bombus vosnesenskii and Bombus vancouverensis, using multiple environmental association analysis methods to investigate climate adaptation across latitude and altitude. The strongest signatures of selection were observed in B. vancouverensis, but despite unique responses between species for most loci, we detected several shared responses. Genes relating to neural and neuromuscular function and ion transport were especially evident with respect to temperature variables, while genes relating to cuticle formation, tracheal and respiratory system development, and homeostasis were associated with precipitation variables. Our data thus suggest that adaptive responses for tolerating abiotic variation are likely to be complex, but that several parallels among species can emerge even for these complex traits and landscapes. Results provide the framework for future work into mechanisms of thermal and desiccation tolerance in bumble bees and a set of genomic targets that might be monitored for future conservation efforts.     

The challenge of separating signatures of local adaptation from those of isolation by distance and colonization history: The case of two white pines

Accurately detecting signatures of local adaptation using genetic‐environment associations (GEAs) requires controlling for neutral patterns of population structure to reduce the risk of false positives. However, a high degree of collinearity between climatic gradients and neutral population structure can greatly reduce power, and the performance of GEA methods in such case is rarely evaluated in empirical studies. In this study, we attempted to disentangle the effects of local adaptation and isolation by environment (IBE) from those of isolation by distance (IBD) and isolation by colonization from glacial refugia (IBC) using range‐wide samples in two white pine species. For this, SNPs from 168 genes, including 52 candidate genes for growth and phenology, were genotyped in 133 and 61 populations of Pinus strobus and P. monticola, respectively. For P. strobus and using all 153 SNPs, climate (IBE) did not significantly explained among‐population variation when controlling for IBD and IBC in redundancy analyses (RDAs). However, 26 SNPs were significantly associated with climate in single‐locus GEA analyses (Bayenv2 and LFMM), suggesting that local adaptation took place in the presence of high gene flow. For P. monticola, we found no evidence of IBE using RDAs and weaker signatures of local adaptation using GEA and F_ST outlier tests, consistent with adaptation via phenotypic plasticity. In both species, the majority of the explained among‐population variation (69 to 96%) could not be partitioned between the effects of IBE, IBD, and IBC. GEA methods can account differently for this confounded variation, and this could explain the small overlap of SNPs detected between Bayenv2 and LFMM. Our study illustrates the inherent difficulty of taking into account neutral structure in natural populations and the importance of sampling designs that maximize climatic variation, while minimizing collinearity between climatic gradients and neutral structure.     

Evolutionary genomics of gypsy moth populations sampled along a latitudinal gradient

The European gypsy moth (Lymantria dispar L.) was first introduced to Massachusetts in 1869 and within 150 years has spread throughout eastern North America. This large‐scale invasion across a heterogeneous landscape allows examination of the genetic signatures of adaptation potentially associated with rapid geographical spread. We tested the hypothesis that spatially divergent natural selection has driven observed changes in three developmental traits that were measured in a common garden for 165 adult moths sampled from six populations across a latitudinal gradient covering the entirety of the range. We generated genotype data for 91,468 single nucleotide polymorphisms based on double digest restriction‐site associated DNA sequencing and used these data to discover genome‐wide associations for each trait, as well as to test for signatures of selection on the discovered architectures. Genetic structure across the introduced range of gypsy moth was low in magnitude (F_ST = 0.069), with signatures of bottlenecks and spatial expansion apparent in the rare portion of the allele frequency spectrum. Results from applications of Bayesian sparse linear mixed models were consistent with the presumed polygenic architectures of each trait. Further analyses indicated spatially divergent natural selection acting on larval development time and pupal mass, with the linkage disequilibrium component of this test acting as the main driver of observed patterns. The populations most important for these signals were two range‐edge populations established less than 30 generations ago. We discuss the importance of rapid polygenic adaptation to the ability of non‐native species to invade novel environments.     

Subspecies delineation amid phenotypic,geographic and genetic discordance in a songbird

Understanding the processes that drive divergence within and among species is a long‐standing goal in evolutionary biology. Traditional approaches to assessing differentiation rely on phenotypes to identify intra‐ and interspecific variation, but many species express subtle morphological gradients in which boundaries among forms are unclear. This intraspecific variation may be driven by differential adaptation to local conditions and may thereby reflect the evolutionary potential within a species. Here, we combine genetic and morphological data to evaluate intraspecific variation within the Nelson's (Ammodramus nelsoni) and salt marsh (Ammodramus caudacutus) sparrow complex, a group with populations that span considerable geographic distributions and a habitat gradient. We evaluated genetic structure among and within five putative subspecies of A. nelsoni and A. caudacutus using a reduced‐representation sequencing approach to generate a panel of 1929 SNPs among 69 individuals. Although we detected morphological differences among some groups, individuals sorted along a continuous phenotypic gradient. In contrast, the genetic data identified three distinct clusters corresponding to populations that inhabit coastal salt marsh, interior freshwater marsh and coastal brackish–water marsh habitats. These patterns support the current species‐level recognition but do not match the subspecies‐level taxonomy within each species—a finding which may have important conservation implications. We identified loci exhibiting patterns of elevated divergence among and within these species, indicating a role for local selective pressures in driving patterns of differentiation across the complex. We conclude that this evidence for adaptive variation among subspecies warrants the consideration of evolutionary potential and genetic novelty when identifying conservation units for this group.     

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.     

Conserving marine biodiversity: insights from life-history trait candidate genes in Atlantic cod (Gadus morhua)

Recent technological developments have facilitated an increased focus on identifying genomic regions underlying adaptive trait variation in natural populations, and it has been advocated that this information should be important for designating population units for conservation. In marine fishes, phenotypic studies have suggested adaptation through divergence of life-history traits among natural populations, but the distribution of adaptive genetic variation in these species is still relatively poorly known. In this study, we extract information about the geographical distribution of genetic variation for 33 single nucleotide polymorphisms (SNPs) associated with life-history trait candidate genes, and compare this to variation in 70 putatively neutral SNPs in Atlantic cod (Gadus morhua). We analyse samples covering the major population complexes in the eastern Atlantic and find strong evidence for non-neutral levels and patterns of population structuring for several of the candidate gene-associated markers, including two SNPs in the growth hormone 1 gene. Thus, this study aligns with findings from phenotypic studies, providing molecular data strongly suggesting that these or closely linked genes are under selection in natural populations of Atlantic cod. Furthermore, we find that patterns of variation in outlier markers do not align with those observed at selectively neutral markers, and that outlier markers identify conservation units on finer geographical scales than those revealed when analysing only neutral markers. Accordingly, results also suggest that information about adaptive genetic variation will be useful for targeted conservation and management in this and other marine species.     

Genome scans for the contemporary response to selection in quantitative traits

Genome scans have been an important approach for discovering historical signatures of selection in both model and nonmodel species. An exciting new experimental design for genome scans is to measure the change in allele frequency before and after contemporary selection within a generation, from a single population. The most widely‐used methods, however, have two major limitations: they are based on testing one locus at a time, and they only have power to uncover loci that have evolved under relatively strong selection. On the other hand, complex quantitative traits are common in nature and are caused by several loci of small effect. Selection on a quantitative trait at the phenotypic level is predicted to be accompanied by subtle allele frequency changes in many loci that covary (a polygenic soft sweep), rather than a large, single‐effect allele (a selective sweep). In this issue of Molecular Ecology, Bourret et al. (2014) measure the contemporary response to natural selection across the genome in multiple cohorts of Atlantic salmon during their first year at sea. They introduce a multilocus framework based on groups of markers that covary in their genotypic distribution. While the traditional, single‐locus approach did not find evidence for repeated patterns of selection, the multivariate approach found that a group of covarying SNPs was selected for in different cohorts at one site. Their multilocus framework has potential to be a more fruitful approach for uncovering the genomic basis of adaptation in quantitative traits, although caution should be applied as the framework has yet to be validated with simulated data.