Mega-study on Mexican admixture

There have been other studies on Mexican admixture patterns before, but this one breaks new ground, by determining the more specific origin of the three major components of the Mexican population. From the paper:

In addition to the HapMap CEU, who are mostly of Northern European ancestry, we used individuals recruited from Dublin, (Ireland), Warsaw (Poland), Rome (Italy) and Porto (Portugal) to provide references for different areas within Europe. The first two PCs provide good separation of these reference populations, and correspond roughly to North-South and West-East gradients (Figure 3A). Both the MEX1EUR and MEX2EUR virtual genomes are most closely related to intact genomes from Porto, which we interpret as a surrogate for populations from the Iberian Peninsula, [3], consistent with the historical record that the first European migrants to Mexico were Spaniards.

The paper is also methodologically interesting:

Continental-level admixture proportions were estimated two ways: (1) a model-based clustering algorithm implemented in frappe [35], and (2) average locus-specific ancestries across all markers. Locus-specific ancestry was estimated with SABER+, an extension of a previously described approach, SABER, that uses a Markov-Hidden Markov Model [12]. SABER+ differs from SABER in implementation of a new algorithm, an Autoregressive Hidden Markov Model (ARHMM), in which haplotype structure within the ancestral populations is adaptively constructed using a binary decision tree based on as many as 15 markers, and which therefore does not require a priori knowledge of genome-wide ancestry proportions (Johnson et al., in preparation). In simulation studies, the ARHMM achieves accuracy comparable to HapMix [36] but is more flexible in modeling the three-way admixture in the Mexican population and does not require information about the recombination rate.

PLoS Genet 7(12): e1002410. doi:10.1371/journal.pgen.1002410

Ancestral Components of Admixed Genomes in a Mexican Cohort

Nicholas A. Johnson et al.

For most of the world, human genome structure at a population level is shaped by interplay between ancient geographic isolation and more recent demographic shifts, factors that are captured by the concepts of biogeographic ancestry and admixture, respectively. The ancestry of non-admixed individuals can often be traced to a specific population in a precise region, but current approaches for studying admixed individuals generally yield coarse information in which genome ancestry proportions are identified according to continent of origin. Here we introduce a new analytic strategy for this problem that allows fine-grained characterization of admixed individuals with respect to both geographic and genomic coordinates. Ancestry segments from different continents, identified with a probabilistic model, are used to construct and study “virtual genomes” of admixed individuals. We apply this approach to a cohort of 492 parent–offspring trios from Mexico City. The relative contributions from the three continental-level ancestral populations—Africa, Europe, and America—vary substantially between individuals, and the distribution of haplotype block length suggests an admixing time of 10–15 generations. The European and Indigenous American virtual genomes of each Mexican individual can be traced to precise regions within each continent, and they reveal a gradient of Amerindian ancestry between indigenous people of southwestern Mexico and Mayans of the Yucatan Peninsula. This contrasts sharply with the African roots of African Americans, which have been characterized by a uniform mixing of multiple West African populations. We also use the virtual European and Indigenous American genomes to search for the signatures of selection in the ancestral populations, and we identify previously known targets of selection in other populations, as well as new candidate loci. The ability to infer precise ancestral components of admixed genomes will facilitate studies of disease-related phenotypes and will allow new insight into the adaptive and demographic history of indigenous people.

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