Genome-phenotype-environment associations identify signatures of selection in a panmictic population of threespine stickleback
Cite this dataset
Strickland, Kasha et al. (2023). Genome-phenotype-environment associations identify signatures of selection in a panmictic population of threespine stickleback [Dataset]. Dryad. https://doi.org/10.5061/dryad.mkkwh7147
Abstract
Adaptive genetic divergence occurs when selection imposed by the environment causes the genomic component of the phenotype to differentiate. However, genomic signatures of natural selection are usually identified without information on which trait is responding to selection by which selective agent(s). Here we integrate whole-genome-sequencing with phenomics and measures of putative selective agents to assess the extent of adaptive divergence in threespine stickleback occupying the highly heterogeneous lake Mývatn, NE Iceland. We find negligible genome-wide divergence, yet multiple traits (body size, gill raker structure and defence traits) were divergent along known ecological gradients (temperature, predatory bird densities and water depth). SNP-based heritability of all measured traits was high (h2 = 0.42 – 0.65), indicating adaptive potential for all traits. Whilst environment-association analyses identified thousands of loci putatively involved in selection, related to genes linked to neuron development and protein phosphorylation, only loci linked to pelvic spine length were concurrently linked to environmental variation (water depth) – supporting the conclusion that divergence in pelvic spine length occurred in face of gene flow. Our results suggest that whilst there is substantial genetic variation in the traits measured, phenotypic divergence of Mývatn stickleback is mostly weakly associated with environmental gradients, potentially as a result of substantial gene flow. Our study illustrates the value of integrative studies that combine genomic assays of multivariate trait variation with landscape genomics.
Funding
The Icelandic Centre for Research