Bayesian Inference of Recent Migration Rates Using Multilocus Genotypes

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ID: 291125
2003
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Abstract
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.
Reference Key
openalex_W1835981228 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Gregory Wilson, Bruce Rannala
Journal current genetics
Year 2003
DOI
10.1093/genetics/163.3.1177
URL
https://doi.org/10.1093/genetics/163.3.1177
Keywords Keywords not found

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