BMC Evolutionary Biology (Sep 2018)

Selection at a genomic region of major effect is responsible for evolution of complex life histories in anadromous steelhead

  • Steven J. Micheletti,
  • Jon E. Hess,
  • Joseph S. Zendt,
  • Shawn R. Narum

DOI
https://doi.org/10.1186/s12862-018-1255-5
Journal volume & issue
Vol. 18, no. 1
pp. 1 – 11

Abstract

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Abstract Background Disparity in the timing of biological events occurs across a variety of systems, yet the understanding of genetic basis underlying diverse phenologies remains limited. Variation in maturation timing occurs in steelhead trout, which has been associated with greb1L, an oestrogen target gene. Previous techniques that identified this gene only accounted for about 0.5–2.0% of the genome and solely investigated coastal populations, leaving uncertainty on the genetic basis of this trait and its prevalence across a larger geographic scale. Results We used a three-tiered approach to interrogate the genomic basis of complex phenology in anadromous steelhead. First, fine scale mapping with 5.3 million SNPs from resequencing data covering 68% of the genome confirmed a 309-kb region consisting of four genes on chromosome 28, including greb1L, to be the genomic region of major effect for maturation timing. Second, broad-scale characterization of candidate greb1L genotypes across 59 populations revealed unexpected patterns in maturation phenology for inland fish migrating long distances relative to those in coastal streams. Finally, genotypes from 890 PIT-tag tracked steelhead determined associations with early versus late arrival to spawning grounds that were previously unknown. Conclusions This study clarifies the genetic bases for disparity in phenology observed in steelhead, determining an unanticipated trait association with premature versus mature arrival to spawning grounds and identifying multiple candidate genes potentially contributing to this variation from a single genomic region of major effect. This illustrates how dense genome mapping and detailed phenotypic characterization can clarify genotype to phenotype associations across geographic ranges of species.

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