Monitoring Stock-Specific Abundance, Run Timing, and Straying of Chinook Salmon in the Columbia River Using Genetic Stock Identification (GSI)

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.

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Stock composition and ocean spatial distribution inference from California recreational Chinook salmon fisheries using genetic stock identification

Fisheries Research ◽

10.1016/j.fishres.2015.06.001 ◽

2015 ◽

Vol 170 ◽

pp. 166-178 ◽

Cited By ~ 17

Author(s):

William H. Satterthwaite ◽

Javier Ciancio ◽

Eric Crandall ◽

Melodie L. Palmer-Zwahlen ◽

Allen M. Grover ◽

...

Keyword(s):

Spatial Distribution ◽

Chinook Salmon ◽

Stock Identification ◽

Genetic Stock ◽

Genetic Stock Identification ◽

Salmon Fisheries

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Population and individual identification of Chinook salmon in British Columbia through parentage-based tagging and genetic stock identification with single nucleotide polymorphisms

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/cjfas-2017-0168 ◽

2018 ◽

Vol 75 (7) ◽

pp. 1096-1105 ◽

Cited By ~ 11

Author(s):

Terry D. Beacham ◽

Colin Wallace ◽

Cathy MacConnachie ◽

Kim Jonsen ◽

Brenda McIntosh ◽

...

Keyword(s):

British Columbia ◽

Single Nucleotide Polymorphisms ◽

Chinook Salmon ◽

Individual Identification ◽

Parental Genotype ◽

Stock Identification ◽

Nucleotide Polymorphisms ◽

Genetic Stock ◽

Single Nucleotide ◽

Genetic Stock Identification

A study was undertaken to evaluate whether a parentage-based tagging (PBT) and genetic stock identification (GSI) program has the potential to emulate the results from an existing coded-wire tag (CWT) assessment program in British Columbia. A PBT–GSI approach was used to identify Chinook salmon (Oncorhynchus tshawytscha) to specific populations and brood years where 36 241 individuals from 45 populations were genotyped at 321 single nucleotide polymorphisms (SNPs). Known-origin and known-age age 1 juveniles from seven test populations were assigned via PBT (two parental genotypes required, 538 of 656 juveniles assigned; one parental genotype required, 636 of 656 juveniles assigned) with a minimum accuracy of 99.9%. Assignment accuracy via PBT of 1026 ages 1, 2, or 3 Chinook salmon returning to nine populations in 2015 or 2016 (two parental genotypes required, 556 of 1026 individuals assigned; one parental genotype required, 898 of 1026 individuals assigned) was a minimum of 99.8%. A PBT–GSI or PBT system of identification may provide an alternate cost-effective method of identification in the assessment and conservation of Canadian-origin Chinook salmon relative to the existing CWT program, thereby providing very high resolution of mixed-stock fishery samples containing both hatchery-origin (adipose fin clipped) and wild-origin (unclipped) populations.

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Single-nucleotide polymorphisms (SNPs) identified through genotyping-by-sequencing improve genetic stock identification of Chinook salmon (Oncorhynchus tshawytscha) from western Alaska

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/cjfas-2013-0502 ◽

2014 ◽

Vol 71 (5) ◽

pp. 698-708 ◽

Cited By ~ 52

Author(s):

Wesley A. Larson ◽

James E. Seeb ◽

Carita E. Pascal ◽

William D. Templin ◽

Lisa W. Seeb

Keyword(s):

Single Nucleotide Polymorphisms ◽

Chinook Salmon ◽

Oncorhynchus Tshawytscha ◽

Sequence Data ◽

Genotyping By Sequencing ◽

Stock Identification ◽

Nucleotide Polymorphisms ◽

Genetic Stock ◽

Single Nucleotide ◽

Genetic Stock Identification

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.

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