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Abstract: Detecting genetic variants under selection using FST outlier analysis (OA) and environmental association analyses (EAAs) are popular approaches that provide insight into the genetic basis of local adaptation. Despite the frequent use of OA and EAA approaches and their increasing attractiveness for detecting signatures of selection, their application to field‐based empirical data have not been synthesized. Here, we review 66 empirical studies that use Single Nucleotide Polymorphisms (SNPs) in OA and EAA. We report trends and biases across biological systems, sequencing methods, approaches, parameters, environmental variables and their influence on detecting signatures of selection. We found striking variability in both the use and reporting of environmental data and statistical parameters. For example, linkage disequilibrium among SNPs and numbers of unique SNP associations identified with EAA were rarely reported. The proportion of putatively adaptive SNPs detected varied widely among studies, and decreased with the number of SNPs analysed. We found that genomic sampling effort had a greater impact than biological sampling effort on the proportion of identified SNPs under selection. OA identified a higher proportion of outliers when more individuals were sampled, but this was not the case for EAA. To facilitate repeatability, interpretation and synthesis of studies detecting selection, we recommend that future studies consistently report geographical coordinates, environmental data, model parameters, linkage disequilibrium, and measures of genetic structure. Identifying standards for how OA and EAA studies are designed and reported will aid future transparency and comparability of SNP‐based selection studies and help to progress landscape and evolutionary genomics. [ABSTRACT FROM AUTHOR]

Identifying the genetic basis of phenotypic variation and its relationship with the environment is key to understanding how local adaptations evolve. Such patterns are especially interesting among populations distributed across habitat gradients, where genetic structure can be driven by isolation by distance ( IBD) and/or isolation by environment ( IBE). Here, we used variation in ~1,600 high-quality SNPs derived from paired-end sequencing of double-digest restriction site-associated DNA (dd RAD-Seq) to test hypotheses related to IBD and IBE in the Yucatan jay ( Cyanocorax yucatanicus), a tropical bird endemic to the Yucatán Peninsula. This peninsula is characterized by a precipitation and vegetation gradient-from dry to evergreen tropical forests-that is associated with morphological variation in this species. We found a moderate level of nucleotide diversity (π = .008) and little evidence for genetic differentiation among vegetation types. Analyses of neutral and putatively adaptive SNPs (identified by complementary genome-scan approaches) indicate that IBD is the most reliable explanation to account for frequency distribution of the former, while IBE has to be invoked to explain those of the later. These results suggest that selective factors acting along a vegetation gradient can promote local adaptation in the presence of gene flow in a vagile, nonmigratory and geographically restricted species. The putative candidate SNPs identified here are located within or linked to a variety of genes that represent ideal targets for future genomic surveys. [ABSTRACT FROM AUTHOR]

Landscape genomics is an emerging research field that aims to identify the environmental factors that shape adaptive genetic variation and the gene variants that drive local adaptation. Its development has been facilitated by next-generation sequencing, which allows for screening thousands to millions of single nucleotide polymorphisms in many individuals and populations at reasonable costs. In parallel, data sets describing environmental factors have greatly improved and increasingly become publicly accessible. Accordingly, numerous analytical methods for environmental association studies have been developed. Environmental association analysis identifies genetic variants associated with particular environmental factors and has the potential to uncover adaptive patterns that are not discovered by traditional tests for the detection of outlier loci based on population genetic differentiation. We review methods for conducting environmental association analysis including categorical tests, logistic regressions, matrix correlations, general linear models and mixed effects models. We discuss the advantages and disadvantages of different approaches, provide a list of dedicated software packages and their specific properties, and stress the importance of incorporating neutral genetic structure in the analysis. We also touch on additional important aspects such as sampling design, environmental data preparation, pooled and reduced-representation sequencing, candidate-gene approaches, linearity of allele-environment associations and the combination of environmental association analyses with traditional outlier detection tests. We conclude by summarizing expected future directions in the field, such as the extension of statistical approaches, environmental association analysis for ecological gene annotation, and the need for replication and post hoc validation studies. [ABSTRACT FROM AUTHOR]

Understanding landscape processes driving patterns of population genetic differentiation and diversity has been a long-standing focus of ecology and evolutionary biology. Gene flow may be reduced by historical, ecological or geographic factors, resulting in patterns of isolation by distance ( IBD) or isolation by environment ( IBE). Although IBE has been found in many natural systems, most studies investigating patterns of IBD and IBE in nature have used anonymous neutral genetic markers, precluding inference of selection mechanisms or identification of genes potentially under selection. Using landscape genomics, the simultaneous study of genomic and ecological landscapes, we investigated the processes driving population genetic patterns of White-breasted Nuthatches ( Sitta carolinensis) in sky islands (montane forest habitat islands) of the Madrean Archipelago. Using more than 4000 single nucleotide polymorphisms and multiple tests to investigate the relationship between genetic differentiation and geographic or ecological distance, we identified IBE, and a lack of IBD, among sky island populations of S. carolinensis. Using three tests to identify selection, we found 79 loci putatively under selection; of these, seven matched CDS regions in the Zebra Finch. The loci under selection were highly associated with climate extremes (maximum temperature of warmest month and minimum precipitation of driest month). These results provide evidence for IBE - disentangled from IBD - in sky island vertebrates and identify potential adaptive genetic variation. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Understanding the genetic basis of adaptation in response to environmental variation is fundamental as adaptation plays a key role in the extension of ecological niches to marginal habitats and in ecological speciation. Based on the assumption that some genomic markers are correlated to environmental variables, we aimed to detect loci of ecological relevance in the alpine plant Arabis alpina L. sampled in two regions, the French (99 locations) and the Swiss (109 locations) Alps. We used an unusually large genome scan [825 amplified fragment length polymorphism loci (AFLPs)] and four environmental variables related to temperature, precipitation and topography. We detected linkage disequilibrium among only 3.5% of the considered AFLP loci. A population structure analysis identified no admixture in the study regions, and the French and Swiss Alps were differentiated and therefore could be considered as two independent regions. We applied generalized estimating equations (GEE) to detect ecologically relevant loci separately in the French and Swiss Alps. We identified 78 loci of ecological relevance (9%), which were mainly related to mean annual minimum temperature. Only four of these loci were common across the French and Swiss Alps. Finally, we discuss that the genomic characterization of these ecologically relevant loci, as identified in this study, opens up new perspectives for studying functional ecology in A. alpina, its relatives and other alpine plant species. [ABSTRACT FROM AUTHOR]

Predicting likely species responses to an alteration of their local environment is key to decision-making in resource management, ecosystem restoration and biodiversity conservation practice in the face of global human-induced habitat disturbance. This is especially true for forest trees which are a dominant life form on Earth and play a central role in supporting diverse communities and structuring a wide range of ecosystems. In Europe, it is expected that most forest tree species will not be able to migrate North fast enough to follow the estimated temperature isocline shift given current predictions for rapid climate warming. In this context, a topical question for forest genetics research is to quantify the ability for tree species to adapt locally to strongly altered environmental conditions (Kremer et al. ). Identifying environmental factors driving local adaptation is, however, a major challenge for evolutionary biology and ecology in general but is particularly difficult in trees given their large individual and population size and long generation time. Empirical evaluation of local adaptation in trees has traditionally relied on fastidious long-term common garden experiments (provenance trials) now supplemented by reference genome sequence analysis for a handful of economically valuable species. However, such resources have been lacking for most tree species despite their ecological importance in supporting whole ecosystems. In this issue of Molecular Ecology, De Kort et al. () provide original and convincing empirical evidence of local adaptation to temperature in black alder, Alnus glutinosa L. Gaertn, a surprisingly understudied keystone species supporting riparian ecosystems. Here, De Kort et al. () use an innovative empirical approach complementing state-of-the-art landscape genomics analysis of A. glutinosa populations sampled in natura across a regional climate gradient with phenotypic trait assessment in a common garden experiment (Fig. [Diagram ad]). By combining the two methods, De Kort et al. () were able to detect unequivocal association between temperature and phenotypic traits such as leaf size as well as with genetic loci putatively under divergent selection for temperature. The research by De Kort et al. () provides valuable insight into adaptive response to temperature variation for an ecologically important species and demonstrates the usefulness of an integrated approach for empirical evaluation of local adaptation in nonmodel species (Sork et al. ). [ABSTRACT FROM AUTHOR]