Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Orozco-terWengel P

PROVIDER: S-EPMC3084510 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature

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

Orozco-terWengel Pablo P Corander Jukka J Schlötterer Christian C

Molecular ecology 20110118 6

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 pr ...[more]

PMID: 21244537

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Project description:The demographic history of a population drives the pattern of genetic variation and is encoded in the gene-genealogical trees of the sampled alleles. However, existing methods to infer demographic history from genetic data tend to use relatively low-dimensional summaries of the genealogy, such as allele frequency spectra. As a step toward capturing more of the information encoded in the genome-wide sequence of genealogical trees, here we propose a novel framework called the genealogical likelihood (gLike), which derives the full likelihood of a genealogical tree under any hypothesized demographic history. Employing a graph-based structure, gLike summarizes across independent trees the relationships among all lineages in a tree with all possible trajectories of population memberships through time and efficiently computes the exact marginal probability under a parameterized demographic model. Through extensive simulations and empirical applications on populations that have experienced multiple admixtures, we showed that gLike can accurately estimate dozens of demographic parameters when the true genealogy is known, including ancestral population sizes, admixture timing, and admixture proportions. Moreover, when using genealogical trees inferred from genetic data, we showed that gLike outperformed conventional demographic inference methods that leverage only the allele-frequency spectrum and yielded parameter estimates that align with established historical knowledge of the past demographic histories for populations like Latino Americans and Native Hawaiians. Furthermore, our framework can trace ancestral histories by analyzing a sample from the admixed population without proxies for its source populations, removing the need to sample ancestral populations that may no longer exist. Taken together, our proposed gLike framework harnesses underutilized genealogical information to offer exceptional sensitivity and accuracy in inferring complex demographies for humans and other species, particularly as estimation of genome-wide genealogies improves.

Dataset Information

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

Publications

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

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