Journal Article

Bayesian inference of admixture graphs on Native American and Arctic populations

Landis, Michael J., Mailund, Thomas, Nielsen, Svend V., Nielsen, Rasmus, Vaughn, Andrew H., Leppälä, Kalle

2023

Overview

Admixture graphs are mathematical structures that describe the ancestry of populations in terms of divergence and merging (admixing) of ancestral populations as a graph. An admixture graph consists of a graph topology, branch lengths, and admixture proportions. The branch lengths and admixture proportions can be estimated using numerous numerical optimization methods, but inferring the topology involves a combinatorial search for which no polynomial algorithm is known. In this paper, we present a reversible jump MCMC algorithm for sampling high-probability admixture graphs and show that this approach works well both as a heuristic search for a single best-fitting graph and for summarizing shared features extracted from posterior samples of graphs. We apply the method to 11 Native American and Siberian populations and exploit the shared structure of high-probability graphs to characterize the relationship between Saqqaq, Inuit, Koryaks, and Athabascans. Our analyses show that the Saqqaq is not a good proxy for the previously identified gene flow from Arctic people into the Na-Dene speaking Athabascans.

• Publisher: Public Library of Science,Public Library of Science (PLoS)
• Subject: Admixture mapping / Algorithms / American Indian or Alaska Native - genetics / Analysis / Bayes Theorem / Bayesian analysis / Biology and Life Sciences / Computer and Information Sciences / Gene Flow / Genetic aspects / Genetic screening / Genetics, Population / Graphs / Health aspects / Humans / Markov analysis / Methods / Minority & ethnic groups / Native Americans / People and places / Phylogenetics / Physical Sciences / Population / Research and Analysis Methods