Rank and Order: Evaluating the Performance of SNPs for Individual Assignment in a Non-Model Organism |
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Authors: | Caroline G. Storer Carita E. Pascal Steven B. Roberts William D. Templin Lisa W. Seeb James E. Seeb |
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Affiliation: | 1. School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington, United States of America.; 2. Gene Conservation Laboratory, Alaska Department of Fish and Game, Anchorage, Alaska, United States of America.; University of Jaén, Spain, |
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Abstract: | Single nucleotide polymorphisms (SNPs) are valuable tools for ecological and evolutionary studies. In non-model species, the use of SNPs has been limited by the number of markers available. However, new technologies and decreasing technology costs have facilitated the discovery of a constantly increasing number of SNPs. With hundreds or thousands of SNPs potentially available, there is interest in comparing and developing methods for evaluating SNPs to create panels of high-throughput assays that are customized for performance, research questions, and resources. Here we use five different methods to rank 43 new SNPs and 71 previously published SNPs for sockeye salmon: FST, informativeness (In), average contribution to principal components (LC), and the locus-ranking programs BELS and WHICHLOCI. We then tested the performance of these different ranking methods by creating 48- and 96-SNP panels of the top-ranked loci for each method and used empirical and simulated data to obtain the probability of assigning individuals to the correct population using each panel. All 96-SNP panels performed similarly and better than the 48-SNP panels except for the 96-SNP BELS panel. Among the 48-SNP panels, panels created from FST, In, and LC ranks performed better than panels formed using the top-ranked loci from the programs BELS and WHICHLOCI. The application of ranking methods to optimize panel performance will become more important as more high-throughput assays become available. |
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