The study of local adaptation in the presence of ongoing gene flow is the study of natural selection in action, revealing the functional genetic diversity most relevant to contemporary pressures. In addition to individual genes, genome-wide architecture can itself evolve to enable adaptation. Distributed across a steep thermal gradient along the east coast of North America, Atlantic silversides (Menidia menidia) exhibit an extraordinary degree of local adaptation in a suite of traits, and the capacity for rapid adaptation from standing genetic variation, but we know little about the patterns of genomic variation across the species range that enable this remarkable adaptability. Here, we use low-coverage, whole-transcriptome sequencing of Atlantic silversides sampled along an environmental cline to show marked signatures of divergent selection across a gradient of neutral differentiation. Atlantic silversides sampled across 1371 km of the southern section of its distribution have very low genome-wide differentiation (median FST = 0.006 across 1.9 million variants), consistent with historical connectivity and observations of recent migrants. Yet almost 14,000 single nucleotide polymorphisms (SNPs) are nearly fixed (FST > 0.95) for alternate alleles. Highly differentiated SNPs cluster into four tight linkage disequilibrium (LD) blocks that span hundreds of genes and several megabases. Variants in these LD blocks are disproportionately nonsynonymous and concentrated in genes enriched for multiple functions related to known adaptations in silversides, including variation in lipid storage, metabolic rate, and spawning behavior. Elevated levels of absolute divergence and demographic modeling suggest selection maintaining divergence across these blocks under gene flow. These findings represent an extreme case of heterogeneity in levels of differentiation across the genome, and highlight how gene flow shapes genomic architecture in continuous populations. Locally adapted alleles may be common features of populations distributed along environmental gradients, and will likely be key to conserving variation to enable future responses to environmental change.
Maximum SNP FST Outperforms Full-Window Statistics for Detecting Soft Sweeps in Local Adaptation
Abstract Local adaptation can lead to elevated genetic differentiation at the targeted genetic variant and nearby sites. Selective sweeps come in different forms, and depending on the initial and final frequencies of a favored variant, very different patterns of genetic variation may be produced. If local selection favors an existing variant that had already recombined onto multiple genetic backgrounds, then the width of elevated genetic differentiation (high FST) may be too narrow to detect using a typical windowed genome scan, even if the targeted variant becomes highly differentiated. We, therefore, used a simulation approach to investigate the power of SNP-level FST (specifically, the maximum SNP FST value within a window, or FST_MaxSNP) to detect diverse scenarios of local adaptation, and compared it against whole-window FST and the Comparative Haplotype Identity statistic. We found that FST_MaxSNP had superior power to detect complete or mostly complete soft sweeps, but lesser power than full-window statistics to detect partial hard sweeps. Nonetheless, the power of FST_MaxSNP depended highly on sample size, and confident outliers depend on robust precautions and quality control. To investigate the relative enrichment of FST_MaxSNP outliers from real data, we applied the two FST statistics to a panel of Drosophila melanogaster populations. We found that FST_MaxSNP had a genome-wide enrichment of outliers compared with demographic expectations, and though it yielded a lesser enrichment than window FST, it detected mostly unique outlier genes and functional categories. Our results suggest that FST_MaxSNP is highly complementary to typical window-based approaches for detecting local adaptation, and merits inclusion in future genome scans and methodologies.
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- Award ID(s):
- 1754745
- PAR ID:
- 10465411
- Editor(s):
- Betancourt, Andrea
- Date Published:
- Journal Name:
- Genome Biology and Evolution
- Volume:
- 14
- Issue:
- 10
- ISSN:
- 1759-6653
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Ware, Jessica (Ed.)Abstract Broadly distributed species experience divergent abiotic conditions across their ranges that may drive local adaptation. Montane systems where populations are distributed across both latitudinal and elevational gradients are especially likely to produce local adaptation due to spatial variation in multiple abiotic factors, including temperature, oxygen availability, and air density. We use whole-genome resequencing to evaluate the landscape genomics of Bombus vancouverensis Cresson (Hymenoptera: Apidae), a common montane bumble bee that is distributed throughout the western part of North America. Combined statistical approaches revealed several large windows of outlier SNPs with unusual levels of differentiation across the region and indicated that isothermality and elevation were the environmental features most strongly associated with these variants. Genes found within these regions had diverse biological functions, but included neuromuscular function, ion homeostasis, oxidative stress, and hypoxia that could be associated with tolerance of temperature, desiccation, or high elevation conditions. The whole-genome sequencing approach revealed outliers occurred in genome regions with elevated linkage disequilibrium, elevated mean FST, and low intrapopulation nucleotide diversity. Other kinds of structural variations were not widely associated with environmental predictors but did broadly match geographic separation. Results are consistent with other studies suggesting that regions of low recombination may harbor adaptive variation in bumble bees within as well as between species and refine our understanding of candidate genes that could be further investigated as possible targets of selection across the B. vancouverensis range.more » « less
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Chapman, Mark (Ed.)Abstract Populations along steep environmental gradients are subject to differentiating selection that can result in local adaptation, despite countervailing gene flow, and genetic drift. In montane systems, where species are often restricted to narrow ranges of elevation, it is unclear whether the selection is strong enough to influence functional differentiation of subpopulations differing by a few hundred meters in elevation. We used targeted capture of 12 501 exons from across the genome, including 271 genes previously implicated in altitude adaptation, to test for adaptation to local elevations for 2 highland hummingbird species, Coeligena violifer (n = 62) and Colibri coruscans (n = 101). For each species, we described population genetic structure across the complex geography of the Peruvian Andes and, while accounting for this structure, we tested whether elevational allele frequency clines in single nucleotide polymorphisms (SNPs) showed evidence for local adaptation to elevation. Although the 2 species exhibited contrasting population genetic structures, we found signatures of clinal genetic variation with shifts in elevation in both. The genes with SNP-elevation associations included candidate genes previously discovered for high-elevation adaptation as well as others not previously identified, with cellular functions related to hypoxia response, energy metabolism, and immune function, among others. Despite the homogenizing effects of gene flow and genetic drift, natural selection on parts of the genome evidently optimizes elevation-specific cellular function even within elevation range-restricted montane populations. Consequently, our results suggest local adaptation occurring in narrow elevation bands in tropical mountains, such as the Andes, may effectively make them “taller” biogeographic barriers.more » « less
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Hernandez, R (Ed.)Abstract Gene expression links genotypes to phenotypes, so identifying genes whose expression is shaped by selection will be important for understanding the traits and processes underlying local adaptation. However, detecting local adaptation for gene expression will require distinguishing between divergence due to selection and divergence due to genetic drift. Here, we adapt a QST−FST framework to detect local adaptation for transcriptome-wide gene expression levels in a population of diverse maize genotypes. We compare the number and types of selected genes across a wide range of maize populations and tissues, as well as selection on cold-response genes, drought-response genes, and coexpression clusters. We identify a number of genes whose expression levels are consistent with local adaptation and show that genes involved in stress response show enrichment for selection. Due to its history of intense selective breeding and domestication, maize evolution has long been of interest to researchers, and our study provides insight into the genes and processes important for in local adaptation of maize.more » « less
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Abstract Deciphering processes that contribute to genetic differentiation and divergent selection of natural populations is useful for evaluating the adaptive potential and resilience of organisms faced with various anthropogenic stressors. Insect pollinator species, including wild bees, provide critical ecosystem services but are highly susceptible to biodiversity declines. Here, we use population genomics to infer the genetic structure and test for evidence of local adaptation in an economically important native pollinator, the small carpenter bee (
Ceratina calcarata ). Using genome‐wide SNP data (n = 8302), collected from specimens across the species' entire distribution, we evaluated population differentiation and genetic diversity and identified putative signatures of selection in the context of geographic and environmental variation. Results of the analyses of principal component and Bayesian clustering were concordant with the presence of two to three genetic clusters, associated with landscape features and inferred phylogeography of the species. All populations examined in our study demonstrated a heterozygote deficit, along with significant levels of inbreeding. We identified 250 robust outlier SNPs, corresponding to 85 annotated genes with known functional relevance to thermoregulation, photoperiod, and responses to various abiotic and biotic stressors. Taken together, these data provide evidence for local adaptation in a wild bee and highlight genetic responses of native pollinators to landscape and climate features.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1093/gbe/evac143
