Bayesian Inference of Recent Migration Rates Using Multilocus Genotypes

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.

Molecular Characterization of the Common Snook, Centropomus undecimalis (Bloch, 1792) in the Usumacinta Basin

“…We estimated gene flow based on recent migration rates (m) among the genetic clusters obtained with STRUCTURE software (K = 2 and K = 3) and DAPC (K = 3) using an assignment test in BayesASS 3.0.3 [54]. First, we ran BayesASS 3.0.3 for 10,000,000 iterations with a burn-in of 1,000,000 to adjust the mixing parameters, in order to have acceptance rates for the proposed changes in the parameters between 20% and 60%, according to the BayesASS user manual [54]. The delta values used for allele frequency (a), migration rate (m) and the inbreeding (f ) coefficient were 0.4, 0.2 and 0.55, respectively.…”

Context‐dependent dispersal determines relatedness and genetic structure in a patchy amphibian population

“…Effective dispersal rates (i.e., migration rates) between the two genetic clusters identified by the structure analysis within the SSP (see Section 3) were estimated using the programs bimr (Faubet & Gaggiotti, 2008) and bayesass (Wilson & Rannala, 2003).…”

Taxonomy based on limited genomic markers may underestimate species diversity of rockhopper penguins and threaten their conservation

“…In the light of previous studies suggesting the existence of contemporary gene flow among rockhopper penguins (Mays et al, 2019), we used BAYESASS V. 3.0.4 (Wilson & Rannala, 2003) to test for recent migration between the three taxa using an unlinked dataset (Table S3). BAYESASS uses a Bayesian approach with MCMC to estimate migrant ancestries of each individual based on an assignment method and infers migration rates based on the frequency of individuals exhibiting migrant ancestry.…”