The Application of Microsatellites for Stock Identification of Yukon River Chinook Salmon

Abstract

In a cooperative project among three agencies, variation at 30 microsatellite loci was surveyed for 19 populations of Chinook salmon Oncorhynchus tshawytscha from the Yukon River. The observed number of alleles per locus ranged from 2 to 63. Loci with a greater number of alleles displayed lower genetic differentiation index (F ST ) values, but loci with lower F ST values also tended to provide more-accurate estimates of stock composition. The observed number of alleles was related to the power of the locus for providing accurate estimates of stock composition of simulated single-population samples. Mean estimated stock compositions for these mixtures ranged from 38.9% for simulations of single loci with fewer than 10 alleles to 85.5% for simulated loci with more than 60 alleles. Reliable population-specific estimation of stock composition was obtained with a minimum of five loci. Comparison of microsatellite stock identification power with an existing nine-locus single-nucleotide polymorphism (SNP) baseline indicated that nine SNPs or a single microsatellite locus can provide accurate and reasonably precise estimates of stock composition to country of origin. In comparisons of population-specific estimation, the nine-SNP baseline was approximately equivalent to a single microsatellite locus with 17-22 alleles. Mixed-stock analysis applying the microsatellite baseline outlined in this study can accurately and precisely allocate Chinook salmon to units useful for management, such as region or major drainage, providing managers with a powerful tool for assessing and regulating fisheries.

A Comparison of Stock and Individual Identification for Chinook Salmon in British Columbia Provided by Microsatellites and Single‐Nucleotide Polymorphisms

“…Microsatellites with larger numbers of alleles provided more accurate and precise estimates than did microsatellites with few alleles. Similar empirical results have previously been reported for Chinook salmon in the Yukon River drainage (Beacham et al 2008b) and on a Pacific Rim basis (Beacham et al 2006a). Of the top 10 microsatellites surveyed in the current study, 5 were also in the top 10 evaluated in the Yukon River; 2 of the remaining loci were not surveyed in the previous study and 3 were of lesser value.…”

“…In 2002, this was precisely the Subject editor: Timothy King, U.S. Geological Survey, Leetown Science Center, Kearneysville, West Virginia *Corresponding author: terry.beacham@dfo-mpo.gc.ca Received January 10, 2011; accepted August 22, 2011 dilemma confronting Canadian fishery managers in the management of the Chinook salmon O. tshawytscha fisheries off the Queen Charlotte Islands in northern British Columbia and the west coast of Vancouver Island in southern British Columbia, as only a small portion of the quota available to Canadian fishermen from 1995 to 2001 was harvested due to conservation concerns about specific Chinook salmon stocks. Microsatellite variation had been surveyed previously for stocks likely to be present in these two fisheries (Beacham et al 2003(Beacham et al , 2006. Beginning in 2002, with managers' knowledge of the timing and locations 1 2 BEACHAM ET AL.…”

“…The set of microsatellites used by Beacham et al (2006a) for previous stock composition estimation became known as the DFO loci; four of the loci in the DFO suite were also in the GAPS suite. Other than the comparison outlined by Beacham et al (2008b) for 19 populations of Yukon River Chinook salmon, there has been no formal comparison of the relative power of the microsatellites in the GAPS and DFO baselines, nor has there been any comparison of the power of adding microsatellites currently not in either baseline.While the GAPS microsatellite baseline was being developed, single-nucleotide polymorphisms (SNPs) were also being developed and promoted by some fishery management agencies as an alternative to microsatellites for salmon stock identification. The benefits of using SNPs were suggested to be ease of data standardization among laboratories, high throughput, high among-population diversity, lower genotyping errors, and lower cost of analysis per individual (Smith et al 2005b(Smith et al , 2005d.…”

“…The focus of any evaluation for Chinook salmon would be the resolution of the stock composition and individual identification estimates provided by the two techniques and the cost per individual required to obtain the observed resolution. An initial comparison of stock identification resolution was conducted for 19 Yukon River populations incorporating 30 microsatellites and 9 SNPs (Beacham et al 2008b). In comparisons of population-specific estimates, a 9-SNP baseline was approximately equivalent to a single microsatellite locus with 17-22 alleles.…”

A new tool in the toolbox for large-scale, high-throughput fisheries mark-recapture studies using genetic identification

“…Genetic profiling, or gene tagging, has been considered a potential fishery-independent alternative to conventional tagging for many years; however, the high set-up and ongoing costs of gene tagging have meant that there has not been widespread development of this approach for fisheries assessment (Nguyen et al 2006), except in a few high value and unusual applications (Graves and McDowell 2003;Beacham et al 2008). Although costs in the past have been prohibitively high, recent developments in robotics and genotyping procedures have substantially reduced the costs associated with gene tagging (Bert et al 2002;Ogden et al 2009;Eggen 2012).…”