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G3 (Bethesda). 2014 Nov 3;4(12):2505-18. doi: 10.1534/g3.114.014274.

Spatial localization of recent ancestors for admixed individuals.

Author information

1
Department of Computer Science, University of California, Los Angeles, California 90095.
2
Department of Ecology and Evolutionary Biology, University of California, Los Angeles, California 90095.
3
Department of Computer Science, University of California, Los Angeles, California 90095 Interdepartmental Program in Bioinformatics, University of California, Los Angeles, California 90095 Department of Human Genetics, University of California, Los Angeles, California 90095.
4
Department of Human Genetics, University of Chicago, Chicago, Illinois 60637.
5
Interdepartmental Program in Bioinformatics, University of California, Los Angeles, California 90095 Department of Human Genetics, University of California, Los Angeles, California 90095 Department of Pathology and Laboratory Medicine, Geffen School of Medicine at University of California, Los Angeles, California 90095 bpasaniuc@mednet.ucla.edu.

Abstract

Ancestry analysis from genetic data plays a critical role in studies of human disease and evolution. Recent work has introduced explicit models for the geographic distribution of genetic variation and has shown that such explicit models yield superior accuracy in ancestry inference over nonmodel-based methods. Here we extend such work to introduce a method that models admixture between ancestors from multiple sources across a geographic continuum. We devise efficient algorithms based on hidden Markov models to localize on a map the recent ancestors (e.g., grandparents) of admixed individuals, joint with assigning ancestry at each locus in the genome. We validate our methods by using empirical data from individuals with mixed European ancestry from the Population Reference Sample study and show that our approach is able to localize their recent ancestors within an average of 470 km of the reported locations of their grandparents. Furthermore, simulations from real Population Reference Sample genotype data show that our method attains high accuracy in localizing recent ancestors of admixed individuals in Europe (an average of 550 km from their true location for localization of two ancestries in Europe, four generations ago). We explore the limits of ancestry localization under our approach and find that performance decreases as the number of distinct ancestries and generations since admixture increases. Finally, we build a map of expected localization accuracy across admixed individuals according to the location of origin within Europe of their ancestors.

KEYWORDS:

admixture; ancestry inference; genetic continuum; genetic variation; localization

PMID:
25371484
PMCID:
PMC4267945
DOI:
10.1534/g3.114.014274
[Indexed for MEDLINE]
Free PMC Article

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