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Uncovering the genetic and evolutionary basis of local adaptation is a major focus of evolutionary biology. The recent development of cost-effective methods for obtaining high-quality genome-scale data makes it possible to identify some of the loci responsible for adaptive differences among populations. Two basic approaches for identifying putatively locally adaptive loci have been developed and are broadly used: one that identifies loci with unusually high genetic differentiation among populations (differentiation outlier methods) and one that searches for correlations between local population allele frequencies and local environments (genetic-environment association methods). Here, we review the promises and challenges of these genome scan methods, including correcting for the confounding influence of a species’ demographic history, biases caused by missing aspects of the genome, matching scales of environmental data with population structure, and other statistical considerations. In each case, we make suggestions for best practices for maximizing the accuracy and efficiency of genome scans to detect the underlying genetic basis of local adaptation. With attention to their current limitations, genome scan methods can be an important tool in finding the genetic basis of adaptive evolutionary change.

• Self-fertilisation has consequences for variation across the genome as it reduces effective population size, effect recombination rates and pollen flow, with implications for local adaptation. • We conducted simulations of divergent stabilising selection on a quantitative trait with drift, pollen flow, mutation, recombination and different outcrossing rates. We quantified trait divergence and the genetic architecture of adaptation. We conducted an FST outlier analysis to identify candidate loci and quantified the impact of mating system on detectability. • Selfing promoted trait divergence mainly through reductions in pollen flow. Moreover, trait architecture became more diffuse with selfing. Average effect size of trait loci was lower, while the number of loci, and their clustering distance increased. The genetic architecture of selfers was also more diffuse than outcrossers for equivalent migration rates. However, when deleterious alleles were included, architectures became more concentrated in selfers, likely to be because of reductions in population size caused by mutational meltdown and impacts of background selection on Nₑ. • Our simulations demonstrate that mating system has important impacts on adaptive divergence of traits and the genetic landscape underlying that divergence. Selfing has a significant effect on detectability of regions of the genome important for adaptation because of neutral divergence and diffuse trait architecture.

Understanding the genetics of adaptation is a central focus in evolutionary biology. Here, we use a population genomics approach to examine striking parallel morphological divergences of parapatric stream–lake ecotypes of threespine stickleback fish in three watersheds on the Haida Gwaii archipelago, western Canada. Genome-wide variation at greater than 1000 single nucleotide polymorphism loci indicate separate origin of giant lake and small-bodied stream fish within each watershed (mean FST between watersheds = 0.244 and within = 0.114). Genome scans within watersheds identified a total of 21 genomic regions that are highly differentiated between ecotypes and are probably subject to directional selection. Most outliers were watershed-specific, but genomic regions undergoing parallel genetic changes in multiple watersheds were also identified. Interestingly, several of the stream–lake outlier regions match those previously identified in marine–freshwater and benthic–limnetic genome scans, indicating reuse of the same genetic loci in different adaptive scenarios. We also identified multiple new outlier loci, which may contribute to unique aspects of differentiation in stream–lake environments. Overall, our data emphasize the important role of ecological boundaries in driving both local and broadly occurring parallel genetic changes during adaptation.

Populus trichocarpa is an ecologically important tree across western North America. We used a large population sample of 498 accessions over a wide geographical area genotyped with a 34K Populus SNP array to quantify geographical patterns of genetic variation in this species (landscape genomics). We present evidence that three processes contribute to the observed patterns: (1) introgression from the sister species P. balsamifera, (2) isolation by distance (IBD), and (3) natural selection. Introgression was detected only at the margins of the species' distribution. IBD was significant across the sampled area as a whole, but no evidence of restricted gene flow was detected in a core of drainages from southern British Columbia (BC). We identified a large number of FST outliers. Gene Ontology analyses revealed that FST outliers are overrepresented in genes involved in circadian rhythm and response to red/far-red light when the entire dataset is considered, whereas in southern BC heat response genes are overrepresented. We also identified strong correlations between geoclimate variables and allele frequencies at FST outlier loci that provide clues regarding the selective pressures acting at these loci.

Spatially varying selection promotes variance in allele frequencies, increasing genetic differentiation between the demes of a metapopulation. For that reason, outliers in the genome‐wide distribution of summary statistics measuring genetic differentiation, such as FST, are often interpreted as evidence for alleles that contribute to local adaptation. However, theoretical studies have shown that in spatially structured populations the spread of beneficial mutations with spatially uniform fitness effects can also induce transient genetic differentiation. In recent years, numerous empirical studies have suggested that such species‐wide, or global, adaptation makes a substantial contribution to molecular evolution. In this perspective, we discuss how commonly such global adaptation may influence the genome‐wide distribution of FST and generate genetic differentiation patterns, which could be mistaken for local adaptation. To illustrate this, we use forward‐in‐time population genetic simulations assuming parameters for the rate and strength of beneficial mutations consistent with estimates from natural populations. We demonstrate that the spread of globally beneficial mutations in parapatric populations may frequently generate FST outliers, which could be misinterpreted as evidence for local adaptation. The spread of beneficial mutations causes selective sweeps at flanking sites, so in some cases, the effects of global versus local adaptation may be distinguished by examining patterns of nucleotide diversity within and between populations in addition to FST. However, when local adaptation has been only recently established, it may be much more difficult to distinguish from global adaptation, due to less accumulation of linkage disequilibrium at flanking sites. Through our discussion, we conclude that a large fraction of FST outliers that are presumed to arise from local adaptation may instead be due to global adaptation.

Chilean mussel populations have been thought to be panmictic with limited genetic structure. Genotyping‐by‐sequencing approaches have enabled investigation of genomewide variation that may better distinguish populations that have evolved in different environments. We investigated neutral and adaptive genetic variation in Mytilus from six locations in southern Chile with 1240 SNPs obtained with RAD‐seq. Differentiation among locations with 891 neutral SNPs was low (FST = 0.005). Higher differentiation was obtained with a panel of 58 putative outlier SNPs (FST = 0.114) indicating the potential for local adaptation. This panel identified clusters of genetically related individuals and demonstrated that much of the differentiation (~92%) could be attributed to the three major regions and environments: extreme conditions in Patagonia, inner bay influenced by aquaculture (Reloncaví), and outer bay (Chiloé Island). Patagonia samples were most distinct, but additional analysis carried out excluding this collection also revealed adaptive divergence between inner and outer bay samples. The four locations within Reloncaví area were most similar with all panels of markers, likely due to similar environments, high gene flow by aquaculture practices, and low geographical distance. Our results and the SNP markers developed will be a powerful tool supporting management and programs of this harvested species. The current study aimed to evaluate the potential of SNP outlier loci to addresses the fine‐scale population structure in Chilean mussel. The SNP marker panels developed here increased assignment of individual to their origin populations and they could be applied for traceability purposes in management and conservation programs.

PREMISE OF THE STUDY: The Cape Floristic Region (CFR) of South Africa is renowned for its botanical diversity, but the evolutionary origins of this diversity remain controversial. Both neutral and adaptive processes have been implicated in driving diversification, but population‐level studies of plants in the CFR are rare. Here, we investigate the limits to gene flow and potential environmental drivers of selection in Protea repens L. (Proteaceae L.), a widespread CFR species. METHODS: We sampled 19 populations across the range of P. repens and used genotyping by sequencing to identify 2066 polymorphic loci in 663 individuals. We used a Bayesian FST outlier analysis to identify single‐nucleotide polymorphisms (SNPs) marking genomic regions that may be under selection; we used those SNPs to identify potential drivers of selection and excluded them from analyses of gene flow and genetic structure. RESULTS: A pattern of isolation by distance suggested limited gene flow between nearby populations. The populations of P. repens fell naturally into two or three groupings, which corresponded to an east‐west split. Differences in rainfall seasonality contributed to diversification in highly divergent loci, as do barriers to gene flow that have been identified in other species. CONCLUSIONS: The strong pattern of isolation by distance is in contrast to the findings in the only other widespread species in the CFR that has been similarly studied, while the effects of rainfall seasonality are consistent with well‐known patterns. Assessing the generality of these results will require investigations of other CFR species.

In the Southern United States, the widely distributed loblolly pine contributes greatly to lumber and pulp production, as well as providing many important ecosystem services. Climate change may affect the productivity and range of loblolly pine. Nevertheless, we have insufficient knowledge of the adaptive potential and the genetics underlying the adaptability of loblolly pine. To address this, we tested the association of 2.8 million whole exome‐based single nucleotide polymorphisms (SNPs) with climate and geographic variables, including temperature, precipitation, latitude, longitude, and elevation data. Using an integrative landscape genomics approach by combining multiple environmental association and outlier detection analyses, we identified 611 SNPs associated with 56 climate and geographic variables. Longitude, maximum temperature of the warm months and monthly precipitation associated with most SNPs, indicating their importance and complexity in shaping the genetic variation in loblolly pine. Functions of candidate genes related to terpenoid synthesis, pathogen defense, transcription factors, and abiotic stress response. We provided evidence that environment‐associated SNPs also composed the genetic structure of adaptive phenotypic traits including height, diameter, metabolite levels, and gene transcript abundance. Our study promotes understanding of the genetic basis of local adaptation in loblolly pine and provides promising tools for selecting genotypes adapted to local environments in a changing climate. We tested the association of 2.8 million whole exome‐based single nucleotide polymorphisms (SNPs) with climate and geographic variables, including temperature, precipitation, latitude, longitude, and elevation data. Using an integrative landscape genomics approach by combining multiple environmental association and outlier detection analyses, we identified 611 SNPs associated with 56 climate and geographic variables. Our study promotes understanding of the genetic basis of local adaptation in loblolly pine and provides promising tools for selecting genotypes adapted to local environments in a changing climate.

Background Genes underlying signal production and reception are expected to evolve to maximize signal detection in specific environments. Fireflies vary in their light signal color both within and between species, and thus provide an excellent system in which to study signal production and reception in the context of signaling environments. Differences in signal color have been hypothesized to be due to variation in the sequence of luciferase, the enzyme that catalyzes the light reaction. Similarly, differences in visual sensitivity, which are expected to match signal color, have been hypothesized to be due to variation in the sequence of opsins, the protein component of visual pigments. Here we investigated (1) whether sequence variation in luciferase correlates with variation in signal color and (2) whether sequence variation in opsins correlates with inferred matching visual sensitivity across populations of a widespread North American firefly species, Photinus pyralis . We further tested (3) whether selection has acted on these loci by examining their population-level differentiation relative to the distribution of differentiation derived from a genome-wide sample of loci generated by double-digest RADseq. Results We found virtually no coding variation in luciferase or opsins. However, there was extreme divergence in non-coding variation in luciferase across populations relative to a panel of random genomic loci. Conclusions The absence of protein variation at both loci challenges the paradigm that variation in signal color and visual sensitivity in fireflies is exclusively due to coding variation in luciferase and opsin genes. Instead, flash color variation within species must involve other mechanisms, such as abdominal pigmentation or regulation of light organ physiology. Evidence for selection at non-coding variation in luciferase suggests that selection is targeting luciferase regulation and may favor differ expression levels across populations.

To study effects from natural selection acting on brown trout in a natural stream habitat compared with a hatchery environment, 3,781 single nucleotide polymorphism (SNP) markers were analyzed in three closely related groups of brown trout (Salmo trutta L.). Autumn (W/0+, n = 48) and consecutive spring (W/1+, n = 47) samples of brown trout individuals belonging to the same cohort and stream were retrieved using electrofishing. A third group (H/1+, n = 48) comprised hatchery‐reared individuals, bred from a mixture of wild parents of the strain of the two former groups and from a neighboring stream. Pairwise analysis of FST outliers and analysis under a hierarchical model by means of ARLEQUIN software detected 421 (10.8%) candidates of selection, before multitest correction. BAYESCAN software detected 10 candidate loci, all of which were included among the ARLEQUIN candidate loci. Body length was significantly different across genotypes at 10 candidate loci in the W/0+, at 34 candidate loci in the W/1+ and at 21 candidate loci in the H/1+ group. The W/1+ sample was tested for genotype‐specific body length at all loci, and significant differences were found in 10.6% of all loci, and of these, 14.2% had higher frequency of the largest genotype in the W/1+ sample than in W/0+. The corresponding proportion among the candidate loci of W/1+ was 22.7% with genotype‐specific body length, and 88.2% of these had increased frequency of the largest genotype from W/0+ to W/1+, indicating a linkage between these loci and traits affecting growth and survival under this stream's environmental conditions. Bayesian structuring of all loci, and of the noncandidate loci suggested two (K = 2), alternatively four clusters (K = 4). This differed from the candidate SNPs, which suggested only two clusters. In both cases, the hatchery fish dominated one cluster, and body length of W/1+ fish was positively correlated with membership of one cluster both from the K = 2 and the K = 4 structure. Our analysis demonstrates profound genetic differentiation that can be linked to differential selection on a fitness‐related trait (individual growth) in brown trout living under natural vs. hatchery conditions. Candidate SNP loci linked to genes affecting individual growth were identified and provide important inputs into future mapping of the genetic basis of brown trout body size selection. The study compares Bayesian clustering and selection‐based microsatellites and single nucleotide polymorphism of brown trout. The latter revealed size differences between genotypes.