Yakama Nation Fisheries Program

Toppenish, WA, United States

Yakama Nation Fisheries Program

Toppenish, WA, United States
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Hess J.E.,Columbia River Inter Tribal Fish Commission | Matala A.P.,Columbia River Inter Tribal Fish Commission | Zendt J.S.,Yakama Nation Fisheries Program | Frederiksen C.R.,Yakama Nation Fisheries Program | And 2 more authors.
Canadian Journal of Fisheries and Aquatic Sciences | Year: 2011

Major lineages of anadromous salmonids show resilience to natural introgressive hybridization; however, Klickitat River spring-run Chinook salmon (KRSC, Oncorhynchus tshawytscha) have an enigmatic origin because of their intermediate genetic and geographic relationship among Columbia River Chinook salmon lineages. We used computer simulations to evaluate four anthropogenic and natural processes as likely causes of the apparent introgressed genetic composition of KRSC: recent admixture (~5 generations), historical admixture (>200 generations), isolation-by-distance gene flow, and natural selection. We also genotyped 2413 fish (32 collections) across 96 single nucleotide polymorphism loci to clarify the relationship of KRSC among the three major Columbia River lineages (Lower Columbia and interior ocean- and streamtypes) and to quantify introgression among collections. Between 1980 and 2000, we observed a decline of pure interior stream-type individuals in the KRSC collections. This temporal shift in genetic composition was coincident with relevant changes in hatchery practices. Based on results from the simulations and time-series samples, a recent and anthropogenically caused admixture was most likely responsible for introgression of KRSC. Potential long-term negative effects of introgression may require some form of mitigation.


PubMed | Columbia River Inter Tribal Fish Commission and Yakama Nation Fisheries Program
Type: Journal Article | Journal: Proceedings. Biological sciences | Year: 2016

Migration traits are presumed to be complex and to involve interaction among multiple genes. We used both univariate analyses and a multivariate random forest (RF) machine learning algorithm to conduct association mapping of 15 239 single nucleotide polymorphisms (SNPs) for adult migration-timing phenotype in steelhead (Oncorhynchus mykiss). Our study focused on a model natural population of steelhead that exhibits two distinct migration-timing life histories with high levels of admixture in nature. Neutral divergence was limited between fish exhibiting summer- and winter-run migration owing to high levels of interbreeding, but a univariate mixed linear model found three SNPs from a major effect gene to be significantly associated with migration timing (p < 0.000005) that explained 46% of trait variation. Alignment to the annotated Salmo salar genome provided evidence that all three SNPs localize within a 46 kb region overlapping GREB1-like (an oestrogen target gene) on chromosome Ssa03. Additionally, multivariate analyses with RF identified that these three SNPs plus 15 additional SNPs explained up to 60% of trait variation. These candidate SNPs may provide the ability to predict adult migration timing of steelhead to facilitate conservation management of this species, and this study demonstrates the benefit of multivariate analyses for association studies.

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