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

By Joseph K. Pickrell, J. K. Pritchard. PLoS Genetics, 2012

2,606 citations recorded by the source corpus.

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.

Subfields: Ecology, Genetics

View Paper: https://www.semanticscholar.org/paper/2e3416e64571a4e04497ca06bfbce1c9513b5841

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Citations in the corpus

Robust Identification of Local Adaptation from Allele Frequencies (2012, methodology): “The similar level of power of the two tests is perhaps not unsurprising, as the history of the worldwide HGDP populations can be well represented by a tree-like relationship (with a small number of migration events, Pickrell and Pritchard, 2012).”
High-Dimensional Asymptotics of Prediction: Ridge Regression and Classification (2015, methodology): “Consider the following examples: First, Σ has eigenvalues corresponding to evenly-spaced quantiles of the standard Exponential distribution; Second, Σ has a depth-d BinaryTree covariance structure that has been used in population genetics to model the correlations between populations whose evolution”
Wild Mouse Gut Microbiota Promotes Host Fitness and Improves Disease Resistance (2017, positive): “12 Pickrell and Pritchard, 2012 https://bitbucket.org/nygcresearch/ treemix (Continued on next page) Cell 171, 1015–1028.e1–e6, November 16, 2017 e1”
OptM: estimating the optimal number of migration edges on population trees using Treemix (2021, methodology): “The population graph without any migration events was identical to that in Pickrell and Pritchard [2] (Supplementary Fig.”
Ancient Admixture in Human History (2012, methodology): “Admixture graph fitting has some similarities to the TreeMix method of Pickrell and Pritchard (2012) but differs in that TreeMix allows users to automatically explore the space of possible models and to find the one that best fits the data (our method does not), while our method provides a rigorous…”
PhyloNetworks: A Package for Phylogenetic Networks (2017, methodology): “Other software packages can estimate phylogenetic networks (notably PhyloNet [Than et al. 2008], BEAST2 [Zhang et al. 2017], and TreeMix [Pickrell and Pritchard 2012]) or plot rooted networks (Dendroscope, Huson and Scornavacca, 2012).”
Inferring Phylogenetic Networks Using PhyloNet (2017, methodology): “TreeMix (Pickrell and Pritchard, 2012) is a very popular tool in the population genetics community.”
Visualizing spatial population structure with estimated effective migration surfaces (2014, methodology): “For example, PCA [17] and TreeMix [56] both work with the genetic covariance matrix.”
The Utility of Single Nucleotide Polymorphism (SNP) Data in Phylogenetics (2017, background): “Allele frequency methods can help identify directions of gene flow among populations (Pickrell & Pritchard 2012), but the analytical machinery necessary for estimating a species tree with gene flow under a coalescent model has yet to be developed for multiple loci and species (De Maio et al. 2015b).”
Genomic and Chemical Diversity in Cannabis (2015, methodology): “for reticulation within the trees and admixture between populations were performed in TreeMix 457 (81) FST estimates were calculated with vcftools (78).”
Dsuite - fast D-statistics and related admixture evidence from VCF files (2020, methodology): “The treemix method (Pickrell & Pritchard, 2012), on the other hand, can fit a complex historical graph model of a tree with migration edges for a data set of many populations, but does not provide a rigorous test for whether any proposed migration edges are correct (Patterson et al., 2012; Pickrell…”
fastSTRUCTURE: Variational Inference of Population Structure in Large SNP Data Sets (2014, background): “A natural extension of this hierarchical prior would be to allow for a full locus-independent variance – covariance matrix (Pickrell and Pritchard 2012).”
ipyrad: Interactive assembly and analysis of RADseq datasets (2020, methodology): “, 2000) and admixture (TreeMix; Pickrell and Pritchard, 2012), among many others.”