Evaluation of a single nucleotide polymorphism baseline for genetic stock identification of Chinook Salmon (Oncorhynchus tshawytscha) in the California Current large marine ecosystem

Abstract

Abstract-Chinook Salmon (Oncorhynchus tshawytscha) is an economically and ecologically important species, and populations from the west coast of North America are a major component of fisheries in the North Pacific Ocean. The anadromous life history strategy of this species generates populations (or stocks) that typically are differentiated from neighboring populations. In many cases, it is desirable to discern the stock of origin of an individual fish or the stock composition of a mixed sample to monitor the stock-specific effects of anthropogenic impacts and alter management strategies accordingly. Genetic stock identification (GSI) provides such discrimination, and we describe here a novel GSI baseline composed of genotypes from more than 8000 individual fish from 69 distinct populations at 96 single nucleotide polymorphism (SNP) loci. The populations included in this baseline represent the likely sources for more than 99% of the salmon encountered in ocean fisheries of California and Oregon. This new genetic baseline permits GSI with the use of rapid and cost-effective SNP genotyping, and power analyses indicate that it provides very accurate identification of important stocks of Chinook Salmon. In an ocean fishery sample, GSI assignments of more than 1000 fish, with our baseline, were highly concordant (98.95%) at the reporting unit level with information from the physical tags recovered from the same fish. This SNP baseline represents an important advance in the technologies available to managers and researchers of this species.

Identification of multiple genetically distinct populations of Chinook salmon (Oncorhynchus tshawytscha) in a small coastal watershed

“…Five independent runs were performed for each value of k (2-6), using 50,000 burn-in and 150,000 retained iterations. An additional STRUCTURE run to assess the association of SISP and SIFA to the Central Oregon Coast reporting unit was conducted using published data provided in (Clemento et al 2014). Five independent runs were also performed for values of k = 4-10, using the same burn-in and iterations as above.…”

“…A panel of 96 SNPs specific for Chinook salmon (Clemento et al 2014) were genotyped on 96.96 Dynamic Arrays with an EP1 System (Fluidigm Corp., South San Francisco, CA), and genotypes were called with Fluidigm Genotyping Analysis software v2.1.1. These SNPs have been used previously to construct a GSI Bbaseline^database that is comprised of genotypes from more than 69 populations, including fall-run from the Siletz River.…”

“…As genetic techniques have improved, they have been used increasingly to enable better management (Clemento et al 2014;Shafer et al 2015). Salmonid fishes were among the first groups of organisms to be studied with molecular techniques, when the available methods were limited to the evaluation of genetically determined variation in a handful of proteins that could be reliably stained for detection (Utter and Hodgins 1972).…”

“…Previous studies that examined salmon populations from the Siletz River using data from neutral genetic variation included only samples from the fall-run, and were part of large-scale efforts to characterize genetic structure in the species and provide methods for identification of fish of unknown origin (Seeb et al 2007;Moran et al 2013;Clemento et al 2014). We studied salmon of different life-history types and used data from three types of molecular marker to: i) identify patterns of neutral genetic variation within the watershed, ii) evaluate whether temporal patterns of life-history variation are correlated with variation at genetic markers known to be associated with run-timing, and iii) determine phylogeographic patterns within the river and compare them to other coastal basins in the North Oregon Coast region.…”

“…One important application of molecular techniques has been genetic stock identification (GSI), which uses a Bbaseline^ref-erence dataset of genotypes from individuals of known origin to identify the most likely provenance of individuals of unknown origin on the basis of their genotype (Milner et al 1985). A North America-wide baseline dataset has been developed for Chinook salmon that includes 42 major reporting units (Seeb et al 2007) and, more recently, baseline datasets using single nucleotide polymorphisms (SNPs) have been developed for regional applications, including in the California Current ecosystem (Clemento et al 2014).…”