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Gene flow influences the genomic architecture of local adaptation in six riverine fish species

January 1, 2023

Understanding how gene flow influences adaptive divergence is important for predicting adaptive responses. Theoretical studies suggest that when gene flow is high, clustering of adaptive genes in fewer genomic regions would protect adaptive alleles from recombination and thus be selected for, but few studies have tested it with empirical data. Here, we used restriction site-associated sequencing to generate genomic data for six fish species with contrasting life histories from six reaches of the Upper Mississippi River System, USA. We used four differentiation-based outlier tests and three genotype–environment association analyses to define neutral single nucleotide polymorphisms (SNPs) and outlier SNPs that were putatively under selection. We then examined the distribution of outlier SNPs along the genome and investigated whether these SNPs were found in genomic islands of differentiation and inversions. We found that gene flow varied among species, and outlier SNPs were clustered more tightly in species with higher gene flow. The two species with the highest overall FST (0.0303–0.0720) and therefore lowest gene flow showed little evidence of clusters of outlier SNPs, with outlier SNPs in these species spreading uniformly across the genome. In contrast, nearly all outlier SNPs in the species with the lowest FST (0.0003) were found in a single large putative inversion. Two other species with intermediate gene flow (FST ~ 0.0025–0.0050) also showed clustered genomic architectures, with most islands of differentiation clustered on a few chromosomes. Our results provide important empirical evidence to support the hypothesis that increasingly clustered architecture of local adaptation is associated with high gene flow.

Publication Year 2023
Title Gene flow influences the genomic architecture of local adaptation in six riverine fish species
DOI 10.1111/mec.16317
Authors Yue Shi, Kristen L. Bouska, Garrett J. McKinney, William Dokai, Andrew Bartels, Megan V. McPhee, Wesley Larson
Publication Type Article
Publication Subtype Journal Article
Series Title Molecular Ecology
Index ID 70231550
Record Source USGS Publications Warehouse
USGS Organization Coop Res Unit Leetown; Upper Midwest Environmental Sciences Center