Genetic Basis of Adult Migration-timing Within a Population of Steelhead (Oncorhynchus mykiss)
Abstract
Migration traits are presumed to be complex and to involve interaction among multiple genes of minor effect, therefore univariate analyses may lack the power to detect associations. Further, analyses of species that lack a wealth of genomic resources (e.g. whole genome sequence, high density linkage maps, or >100 k markers for genotyping) may present difficulties in elucidating the key genomic regions underpinning particular traits. Therefore we employed both univariate analyses as well as a random-forest (RF) machine learning algorithm to conduct association mapping of ~15k single nucleotide polymorphisms (SNPs) for adult migration-timing phenotype in steelhead (Oncorhynchus mykiss). Steelhead is an anadromous salmonid species which exhibits two divergent freshwater migration-timing life histories, winter- and summer-run. Our study focused on a tributary of the Columbia River, the Klickitat River, where population divergence between summer and winter run types appears minimal and this rare condition is beneficial to a study of the genetic basis of this trait. A univariate mixed linear model found 3 SNPs to be significantly associated with migration-timing. The same 3 SNPs were ranked high in importance values based on RF and explained 46% of trait variation (7% residual). However, RF identified 18 minor SNPs were required to reach a maximum ~70% explained trait variation (44% residual). These candidate SNPs may provide the ability to predict the adult migration-timing of steelhead and facilitate conservation management of this species. This study also demonstrates how beneficial a RF approach may be for identifying SNPs in minor effect genes of complex traits that may otherwise escape detection in univariate association analyses.
Authors
Citation
Hess, J.E., J.S. Zendt, A.R. Matala, and S.R. Narum. 2015. Genetic basis of adult migration-timing within a population of steelhead (Oncorhynchus mykiss). American Fisheries Society Annual Conference, August 16-20, 2015. Portland, OR.