New methods employing multilocus genotypes to select or exclude populations as origins of individuals

A new method for assigning individuals of unknown origin to populations, ba sed on the genetic distance between individuals and populations, was compar ed to two existing methods based on the likelihood of multilocus genotypes. The distribution of the assignment criterion (genetic distance or genotype likelihood) for individuals of a given population was used to define the p robability that an individual belongs to the population. Using this definit ion, it becomes possible to exclude a population as the origin of an indivi dual, a useful extension of the currently available assignment methods. Usi ng simulated data based on the coalescent process, the different methods we re evaluated, varying the time of divergence of populations, the mutation m odel, the sample size, and the number of loci. Likelihood-based methods (es pecially the Bayesian method) always performed better than distance methods . Other things being equal, genetic markers were always more efficient when evolving under the infinite allele model than under the stepwise mutation model, even for equal values of the differentiation parameter F-st. Using t he Bayesian method, a 100% correct assignment rate can be achieved by scori ng ca. 10 microsatellite loci (H approximate to 0.6) on 30-50 individuals f rom each of 10 populations when the F-st is near 0.1.