Data from: Population genetic inferences using immune gene SNPs mirror patterns inferred by microsatellites

Single nucleotide polymorphisms (SNPs) are replacing microsatellites for population genetic analyses, but it is not apparent how many SNPs are needed or how well SNPs correlate with microsatellites. We used data from the gopher tortoise, Gopherus polyphemus – a species with small populations, to compare SNPs and microsatellites to estimate population genetic parameters. Specifically, we compared one SNP dataset (16 tortoises from 4 populations sequenced at 17,901 SNPs) to two microsatellite datasets, a full dataset of 101 tortoises and a partial dataset of 16 tortoises previously genotyped at 10 microsatellites. For the full microsatellite dataset, observed heterozygosity, expected heterozygosity, and FST were correlated between SNPs and microsatellites; however, allelic richness was not. The same was true for the partial microsatellite dataset, except that allelic richness, but not observed heterozygosity, was correlated. The number of clusters estimated by Structure differed for each dataset (SNPs = 2; partial microsatellite = 3; full microsatellite = 4). PCA showed four clusters for all datasets. More than 800 SNPs were needed to correlate with allelic richness, observed heterozygosity, and expected heterozygosity, but only 100 were needed for FST. The number of SNPs typically obtained from NGS far exceeds the number needed to correlate with microsatellite parameter estimates. Our study illustrates that diversity, FST, and PCA results from microsatellites can mirror those obtained with SNPs. These results may be generally applicable to small populations, a defining feature of endangered and threatened species, because theory predicts that genetic drift will tend to outweigh selection in small populations.单核苷酸多态性（SNPs）正逐步取代微卫星（microsatellites）成为群体遗传分析的主流分子标记，但目前仍不明确所需SNP标记的数量，以及SNP与微卫星之间的关联程度究竟如何。本研究以小型种群为典型特征的哥法地鼠龟（Gopherus polyphemus）为研究对象，利用其相关数据开展SNP与微卫星的对比分析，以估算群体遗传参数。具体而言，本研究将1组SNP数据集（采自4个种群的16只个体，共检测到17901个SNP位点）与2组微卫星数据集进行对比：其一为包含101只个体的完整微卫星数据集，其二为先前已对16只个体进行10个微卫星位点基因分型的部分微卫星数据集。针对完整微卫星数据集，SNP与微卫星在观测杂合度、期望杂合度以及种群遗传分化系数（Fixation Index, FST）这三个参数上均呈现显著相关性，但等位基因丰富度除外。对于部分微卫星数据集，结果呈现出相似的趋势，唯一的差异在于：此时等位基因丰富度与SNP结果存在相关性，而观测杂合度则不然。通过Structure软件估算的种群聚类组数在各组数据集间存在差异：SNP数据集为2组，部分微卫星数据集为3组，完整微卫星数据集为4组。主成分分析（Principal Component Analysis, PCA）则在所有数据集下均识别出4个聚类组。若要使SNP数据与等位基因丰富度、观测杂合度及期望杂合度三者的结果形成有效关联，所需的SNP位点数量需超过800个；而针对FST参数，仅需100个SNP位点即可满足要求。下一代测序（Next-Generation Sequencing, NGS）技术通常所能获取的SNP位点数量，远高于与微卫星遗传参数估算结果建立关联所需的阈值。本研究表明，基于微卫星得到的遗传多样性、FST以及PCA分析结果，可与SNP分析得到的结果高度吻合。鉴于濒危与受威胁物种的典型特征即为小型种群，且理论预测小型种群中遗传漂变的作用通常强于自然选择，因此本研究结果或可推广至其他小型种群研究场景。