Data from: Comparison of SNPs and microsatellites for fine-scale application of genetic stock identification of Chinook salmon in the Columbia River Basin

Genetic stock identification (GSI) is an important tool in fisheries management. Microsatellites (µSATs) have been the dominant genetic marker for GSI, however increasing availability and numerous advantages of single nucleotide polymorphism (SNP) markers make them an appealing alternative. We tested performance of 13 µSAT versus 92 SNP loci in a fine-scale application of GSI, using a new baseline for Chinook salmon consisting of 49 collections (n=4014) distributed across the Columbia River Basin. In GSI, baseline genotypes for both marker sets were used independently to analyze a real fishery mixture (n=2731) representing the total run of Chinook salmon passing Bonneville Dam in the Columbia River. Marker sets were evaluated using three criteria: 1) ability to differentiate reporting groups, 2) proportion of correct assignment in mixture simulation tests and baseline leave-one-out analyses, and 3) individual assignment and confidence intervals around estimated stock proportions of a real fishery mixture. The µSATs outperformed the SNPs in resolving fine-scale relationships, but all 105 markers combined provided greatest power for GSI. SNPs were ranked by relative information content based on both an iterative procedure that optimized correct assignment to the baseline and ranking by minor allele frequency. For both methods, we identified a subset of the top 50 ranked loci, which were similar in assignment accuracy, and both reached maximum available power of the total 92 SNP loci (correct assignment=73%). Our estimates indicate that between 100-200 highly informative SNP loci are required to meet management standards (correct assignment>90%) for resolving stocks in finer-scale GSI applications.遗传种群识别（Genetic stock identification, GSI）是渔业管理中的重要工具，微卫星标记（Microsatellites, µSATs）曾是GSI研究中占主导地位的遗传标记，但单核苷酸多态性（single nucleotide polymorphism, SNP）标记的可获取性不断提升且具备诸多优势，使其成为极具吸引力的替代方案。本研究针对奇努克鲑（Chinook salmon）的GSI精细尺度应用，对比了13个微卫星位点与92个SNP位点的性能，所用的新基线数据集包含分布于哥伦比亚河流域（Columbia River Basin）的49个采集群体（n=4014）；在GSI分析中，我们分别使用两种标记体系的基线基因型，对代表通过哥伦比亚河邦纳维尔水坝（Bonneville Dam）的奇努克鲑总洄游群体的真实渔业混合样本（n=2731）开展分析。研究通过三项标准对两种标记体系进行性能评估：其一为区分报告群体的能力，其二为混合样本模拟测试与基线留一法分析中的正确分配比例，其三为真实渔业混合样本的个体分配结果及估算种群比例对应的置信区间。实验结果显示，微卫星标记在解析精细尺度种群关系方面的表现优于SNP标记，但将全部105个标记整合使用时，GSI的分辨效力达到最强。本研究通过两种方式对SNP标记进行排序：一是采用迭代程序优化基线样本的正确分配率，二是依据次要等位基因频率进行排序，两种方法均筛选出排名前50的位点子集，该子集的分配准确率相近，且二者均实现了全部92个SNP位点可达到的最大分辨效力（正确分配率=73%）。本研究的估算结果表明，若要在精细尺度GSI应用中满足管理标准（正确分配率>90%），需要100~200个高信息含量的SNP位点。