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Genealogical lineage sorting leads to significant, but incorrect Bayesian multilocus inference of population structure

Orozco-terWengel, Pablo ORCID:, Corander, J. and Schlotterer, C. 2011. Genealogical lineage sorting leads to significant, but incorrect Bayesian multilocus inference of population structure. Molecular Ecology 20 (6) , pp. 1108-1121. 10.1111/j.1365-294X.2010.04990.x

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Over the past decades, the use of molecular markers has revolutionized biology and led to the foundation of a new research discipline—phylogeography. Of particular interest has been the inference of population structure and biogeography. While initial studies focused on mtDNA as a molecular marker, it has become apparent that selection and genealogical lineage sorting could lead to erroneous inferences. As it is not clear to what extent these forces affect a given marker, it has become common practice to use the combined evidence from a set of molecular markers as an attempt to recover the signals that approximate the true underlying demography. Typically, the number of markers used is determined by either budget constraints or by statistical power required to recognize significant population differentiation. Using microsatellite markers from Drosophila and humans, we show that even large numbers of loci (>50) can frequently result in statistically well-supported, but incorrect inference of population structure using the software baps. Most importantly, genomic features, such as chromosomal location, variability of the markers, or recombination rate, cannot explain this observation. Instead, it can be attributed to sampling variation among loci with different realizations of the stochastic lineage sorting. This phenomenon is particularly pronounced for low levels of population differentiation. Our results have important implications for ongoing studies of population differentiation, as we unambiguously demonstrate that statistical significance of population structure inferred from a random set of genetic markers cannot necessarily be taken as evidence for a reliable demographic inference.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Biosciences
Publisher: Blackwell Publishing
ISSN: 0962-1083
Last Modified: 27 Oct 2022 08:44

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