Stock identification of chinook salmon (Oncorhynchus tshawytscha) using minisatellite DNA variation

1996 ◽  
Vol 53 (2) ◽  
pp. 380-394 ◽  
Author(s):  
Terry D Beacham ◽  
Ruth E Withler ◽  
Tracy A Stevens



2010 ◽  
Vol 67 (1) ◽  
pp. 202-205 ◽  
Author(s):  
Terry D. Beacham ◽  
Ruth E. Withler

Temporally stable genetic structure among salmonid populations has been reported in many studies, although the time span evaluated in most studies is limited to 10 years or less. This result has important implications in conservation and management of Pacific salmon ( Oncorhynchus spp.) and ramifications for the construction and application of genetic databases for stock identification of fish sampled from mixed-stock fisheries. Walter et al. (2009. Can. J. Fish. Aquat. Sci. 66: 167–176) failed to consider recent studies providing evidence that their conclusion “the overall magnitude of temporal within-population variation exceeding that of among-population variation” for the populations under study may be invalid for Fraser River Chinook salmon ( Oncorhynchus tshawytscha ) populations. Their estimation of rates and patterns of migration among Chinook salmon populations also provided results that are difficult to reconcile with published information. Evaluation of the experimental designed employed by Walter et al. (2009) indicates that their sample sizes were too small to estimate reliably genetic variation among or within populations. Extrapolation of their conclusions relating temporal instability of population structure to other Chinook salmon populations or indeed other salmonid species is unwarranted.



1996 ◽  
Vol 53 (1) ◽  
pp. 181-195 ◽  
Author(s):  
Kristina M Miller ◽  
Ruth E Withler ◽  
Terry D Beacham


1993 ◽  
Vol 50 (4) ◽  
pp. 708-715 ◽  
Author(s):  
Matthew A. Cronin ◽  
William J. Spearman ◽  
Richard L. Wilmot ◽  
John C. Patton ◽  
John W. Bickham

We analyzed intraspecific mitochondrial DNA variation in chinook salmon (Oncorhynchus tshawytscha) from drainages in the Yukon River (Alaska and Yukon Territory), the Kenai River (Alaska), and Oregon and California rivers; and chum salmon (O. keta) from the Yukon River and Vancouver Island, and Washington rivers. For each species, three different portions of the mtDNA molecule were amplified separately using the polymerase chain reaction and then digested with at least 19 restriction enzymes. Intraspecific sequence divergences between haplotypes were less than 0.01 base substitution per nucleotide. Nine chum salmon haplotypes were identified. Yukon River chum salmon stocks displayed more haplotypes (eight) than the stocks of Vancouver Island and Washington (two). The most common chum salmon haplotype occurred in all areas. Seven chinook salmon haplotypes were identified. Four haplotypes occurred in the Yukon and Kenai rivers and four occurred in Oregon/California, with only one haplotype shared between the regions. Sample sizes were too small to quantify the degree of stock separation among drainages, but the patterns of variation that we observed suggest utility of the technique in genetic stock identification.



1996 ◽  
Vol 49 (3) ◽  
pp. 411-429 ◽  
Author(s):  
T. D. Beacham ◽  
K. M. Miller ◽  
R. E. Withler


2008 ◽  
Vol 65 (7) ◽  
pp. 1475-1486 ◽  
Author(s):  
Eric C. Anderson ◽  
Robin S. Waples ◽  
Steven T. Kalinowski

Estimating the accuracy of genetic stock identification (GSI) that can be expected given a previously collected baseline requires simulation. The conventional method involves repeatedly simulating mixtures by resampling from the baseline, simulating new baselines by resampling from the baseline, and analyzing the simulated mixtures with the simulated baselines. We show that this overestimates the predicted accuracy of GSI. The bias is profound for closely related populations and increases as more genetic data (loci and (or) alleles) are added to the analysis. We develop a new method based on leave-one-out cross validation and show that it yields essentially unbiased estimates of GSI accuracy. Applying both our method and the conventional method to a coastwide baseline of 166 Chinook salmon ( Oncorhynchus tshawytscha ) populations shows that the conventional method provides severely biased predictions of accuracy for some individual populations. The bias for reporting units (aggregations of closely related populations) is moderate, but still present.



2014 ◽  
Vol 71 (5) ◽  
pp. 698-708 ◽  
Author(s):  
Wesley A. Larson ◽  
James E. Seeb ◽  
Carita E. Pascal ◽  
William D. Templin ◽  
Lisa W. Seeb

Genetic stock identification (GSI), an important tool for fisheries management that relies upon the ability to differentiate stocks of interest, can be difficult when populations are closely related. Here we genotyped 11 850 single-nucleotide polymorphisms (SNPs) from existing DNA sequence data available in five closely related populations of Chinook salmon (Oncorhynchus tshawytscha) from western Alaska. We then converted a subset of 96 of these SNPs displaying high differentiation into high-throughput genotyping assays. These 96 SNPs (RAD96) and 191 SNPs developed previously (CTC191) were screened in 28 populations from western Alaska. Regional assignment power was evaluated for five different SNP panels, including a panel containing the 96 SNPs with the highest FST across the CTC191 and RAD96 panels (FST96). Assignment tests indicated that SNPs in the RAD96 were more useful for GSI than those in the CTC191 and that increasing the number of reporting groups in western Alaska from one to three was feasible with the FST96. Our approach represents an efficient way to discover SNPs for GSI and should be applicable to other populations and species.



1992 ◽  
Vol 14 ◽  
pp. 81-89 ◽  
Author(s):  
ML Kent ◽  
J Ellis ◽  
JW Fournie ◽  
SC Dawe ◽  
JW Bagshaw ◽  
...  




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