Cited by 2,731Forensic and Genetic ResearchGenetic diversity and population structureGenetic Associations and Epidemiology

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Inference of Population Splits and Mixtures from Genome-Wide Allele Frequency Data

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Pickrell, Joseph K., Pritchard, Jonathan K.·2012·PLoS Genetics

DOI 10.1371/journal.pgen.1002967PMC PMC3499260

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Abstract

Many aspects of the historical relationships between populations in a species are reflected in genetic data. Inferring these relationships from genetic data, however, remains a challenging task. In this paper, we present a statistical model for inferring the patterns of population splits and mixtures in multiple populations. In our model, the sampled populations in a species are related to their common ancestor through a graph of ancestral populations. Using genome-wide allele frequency data and a Gaussian approximation to genetic drift, we infer the structure of this graph. We applied this method to a set of 55 human populations and a set of 82 dog breeds and wild canids. In both species, we show that a simple bifurcating tree does not fully describe the data; in contrast, we infer many migration events. While some of the migration events that we find have been detected previously, many have not. For example, in the human data, we infer that Cambodians trace approximately 16% of their ancestry to a population ancestral to other extant East Asian populations. In the dog data, we infer that both the boxer and basenji trace a considerable fraction of their ancestry (9% and 25%, respectively) to wolves subsequent to domestication and that East Asian toy breeds (the Shih Tzu and the Pekingese) result from admixture between modern toy breeds and "ancient" Asian breeds. Software implementing the model described here, called TreeMix, is available at http://treemix.googlecode.com.

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Authors: Pickrell, J. K., & Pritchard, J. K.
Affiliations: University of Chicago (US)
Howard Hughes Medical Institute (US)
Corresponding author: Pickrell, Joseph K.
Pritchard, Jonathan K.
ORCID: Pritchard, Jonathan K.
Venue: PLoS Genetics
Publisher: Public Library of Science (PLoS)
Published: 2012-11-15
Volume: 8
Issue: 11
Pages: e1002967
ISSN: 1553-7390 (ISSN-L)
1553-7404
DOI: 10.1371/journal.pgen.1002967
PMC: PMC3499260
OpenAlex: W2093044565
Cited by: 2,731
References: 79
Citations by year: 2026: 223 · 2025: 260 · 2024: 362 · 2023: 271 · 2022: 277 · 2021: 346 · 2020: 222 · 2019: 175 · 2018: 180 · 2017: 117 · 2016: 120 · 2015: 80 · 2014: 65 · 2013: 22 · 2012: 7
FWCI: 33.43
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (unspecified)
Locations: PLoS Genetics (publishedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
arXiv (Cornell University) (submittedVersion)
Figshare (submittedVersion, cc-by)
Knowledge@UChicago (University of Chicago) (submittedVersion, cc-by-nc-nd)
RePEc: Research Papers in Economics (submittedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Nature Precedings (submittedVersion)
arXiv (Cornell University)
University of Chicago (cc-by)
Funders: Howard Hughes Medical Institute
National Institutes of Health
National Institute of Mental Health (R01MH084703, MH084703)
National Institute of General Medical Sciences (F32GM103098)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Forensic and Genetic Research
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic diversity and population structure
Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Keywords: population admixture, population structure inference, migration events, dog breeds, wild canids, genetic drift, TreeMix, dog domestication, Shih Tzu, Pekingese
MeSH terms: Algorithms, Animals, Breeding, Dogs, Gene Frequency, Humans, Models, Genetic, Population, Wolves, Polymorphism, Single Nucleotide, Genetic Drift, Genome-Wide Association Study

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Inference of Population Splits and Mixtures from Genome-Wide Allele Frequency Data

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