Elbers Jean P, Clostio Rachel W, Taylor Sabrina S
School of Renewable Natural Resources, Louisiana State University and AgCenter, 227 RNR Bldg., Baton Rouge, LA, 70803, USA.
Department of Biology, University of Louisiana at Lafayette, 300 E. Street Mary Blvd., Lafayette, LA, 70503, USA.
Mol Ecol Resour. 2017 May;17(3):481-491. doi: 10.1111/1755-0998.12591. Epub 2016 Aug 29.
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 data set (16 tortoises from four populations sequenced at 17 901 SNPs) to two microsatellite data sets, a full data set of 101 tortoises and a partial data set of 16 tortoises previously genotyped at 10 microsatellites. For the full microsatellite data set, observed heterozygosity, expected heterozygosity and F were correlated between SNPs and microsatellites; however, allelic richness was not. The same was true for the partial microsatellite data set, except that allelic richness, but not observed heterozygosity, was correlated. The number of clusters estimated by structure differed for each data set (SNPs = 2; partial microsatellite = 3; full microsatellite = 4). Principle component analyses (PCA) showed four clusters for all data sets. More than 800 SNPs were needed to correlate with allelic richness, observed heterozygosity and expected heterozygosity, but only 100 were needed for F . The number of SNPs typically obtained from next-generation sequencing (NGS) far exceeds the number needed to correlate with microsatellite parameter estimates. Our study illustrates that diversity, F 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）正取代微卫星用于群体遗传学分析，但尚不清楚需要多少个SNPs，以及SNPs与微卫星的相关性如何。我们利用来自穴小鳄龟（Gopherus polyphemus）的数据——一种种群数量较少的物种——来比较SNPs和微卫星，以估计群体遗传参数。具体而言，我们将一个SNP数据集（来自四个种群的16只乌龟，对17901个SNPs进行了测序）与两个微卫星数据集进行了比较，一个是包含101只乌龟的完整数据集，另一个是之前对10个微卫星进行基因分型的16只乌龟的部分数据集。对于完整的微卫星数据集，观察到的杂合度、预期杂合度和F值在SNPs和微卫星之间具有相关性；然而，等位基因丰富度却没有。部分微卫星数据集也是如此，只是等位基因丰富度具有相关性，而观察到的杂合度没有。通过结构分析估计的聚类数量在每个数据集之间有所不同（SNPs = 2；部分微卫星 = 3；完整微卫星 = 4）。主成分分析（PCA）显示所有数据集均有四个聚类。要使等位基因丰富度、观察到的杂合度和预期杂合度具有相关性，需要超过800个SNPs，但对于F值，仅需要100个。从下一代测序（NGS）通常获得的SNPs数量远远超过与微卫星参数估计具有相关性所需的数量。我们的研究表明，微卫星的多样性、F值和PCA结果可以反映通过SNPs获得的结果。这些结果可能普遍适用于小种群，这是濒危和受威胁物种的一个决定性特征，因为理论预测在小种群中遗传漂变往往会超过选择作用。
