BMC Ecology and Evolution (Apr 2021)

Growth genes are implicated in the evolutionary divergence of sympatric piscivorous and insectivorous rainbow trout (Oncorhynchus mykiss)

  • Jared A. Grummer,
  • Michael C. Whitlock,
  • Patricia M. Schulte,
  • Eric B. Taylor

DOI
https://doi.org/10.1186/s12862-021-01795-9
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 13

Abstract

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Abstract Background Identifying ecologically significant phenotypic traits and the genomic mechanisms that underly them are crucial steps in understanding traits associated with population divergence. We used genome-wide data to identify genomic regions associated with key traits that distinguish two ecomorphs of rainbow trout (Oncorhynchus mykiss)—insectivores and piscivores—that coexist for the non-breeding portion of the year in Kootenay Lake, southeastern British Columbia. “Gerrards” are large-bodied, rapidly growing piscivores with high metabolic rates that spawn north of Kootenay Lake in the Lardeau River, in contrast to the insectivorous populations that are on average smaller in body size, with lower growth and metabolic rates, mainly forage on aquatic insects, and spawn in tributaries immediately surrounding Kootenay Lake. We used pool-seq data representing ~ 60% of the genome and 80 fish per population to assess the level of genomic divergence between ecomorphs and to identify and interrogate loci that may play functional or selective roles in their divergence. Results Genomic divergence was high between sympatric insectivores and piscivores ( $$F_{\text{ST}}$$ F ST = 0.188), and in fact higher than between insectivorous populations from Kootenay Lake and the Blackwater River ( $$F_{\text{ST}}$$ F ST = 0.159) that are > 500 km apart. A window-based $$F_{\text{ST}}$$ F ST analysis did not reveal “islands” of genomic differentiation; however, the window with highest $$F_{\text{ST}}$$ F ST estimate did include a gene associated with insulin secretion. Although we explored the use of the “Local score” approach to identify genomic outlier regions, this method was ultimately not used because simulations revealed a high false discovery rate (~ 20%). Gene ontology (GO) analysis identified several growth processes as enriched in genes occurring in the ~ 200 most divergent genomic windows, indicating many loci of small effect involved in growth and growth-related metabolic processes are associated with the divergence of these ecomorphs. Conclusion Our results reveal a high degree of genomic differentiation between piscivorous and insectivorous populations and indicate that the large body piscivorous phenotype is likely not due to one or a few loci of large effect. Rather, the piscivore phenotype may be controlled by several loci of small effect, thus highlighting the power of whole-genome resequencing in identifying genomic regions underlying population-level phenotypic divergences.

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