Abstract
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.
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