Wilson Gregory A, Rannala Bruce
Department of Medical Genetics, University of Alberta, Edmonton, Alberta T6G 2H7, Canada.
Genetics. 2003 Mar;163(3):1177-91. doi: 10.1093/genetics/163.3.1177.
A new Bayesian method that uses individual multilocus genotypes to estimate rates of recent immigration (over the last several generations) among populations is presented. The method also estimates the posterior probability distributions of individual immigrant ancestries, population allele frequencies, population inbreeding coefficients, and other parameters of potential interest. The method is implemented in a computer program that relies on Markov chain Monte Carlo techniques to carry out the estimation of posterior probabilities. The program can be used with allozyme, microsatellite, RFLP, SNP, and other kinds of genotype data. We relax several assumptions of early methods for detecting recent immigrants, using genotype data; most significantly, we allow genotype frequencies to deviate from Hardy-Weinberg equilibrium proportions within populations. The program is demonstrated by applying it to two recently published microsatellite data sets for populations of the plant species Centaurea corymbosa and the gray wolf species Canis lupus. A computer simulation study suggests that the program can provide highly accurate estimates of migration rates and individual migrant ancestries, given sufficient genetic differentiation among populations and sufficient numbers of marker loci.
本文提出了一种新的贝叶斯方法，该方法利用个体多位点基因型来估计种群间近期（过去几代）的移民率。该方法还能估计个体移民祖先、种群等位基因频率、种群近亲繁殖系数以及其他潜在感兴趣参数的后验概率分布。该方法通过一个计算机程序实现，该程序依靠马尔可夫链蒙特卡罗技术来进行后验概率的估计。该程序可用于等位酶、微卫星、限制性片段长度多态性、单核苷酸多态性以及其他类型的基因型数据。我们放宽了早期利用基因型数据检测近期移民方法的几个假设；最重要的是，我们允许基因型频率在种群内偏离哈迪 - 温伯格平衡比例。通过将该程序应用于最近发表的关于植物物种矢车菊（Centaurea corymbosa）和灰狼物种（Canis lupus）种群的两个微卫星数据集来进行演示。一项计算机模拟研究表明，在种群间有足够的遗传分化和足够数量的标记位点的情况下，该程序能够提供高度准确的移民率和个体移民祖先估计值。
