Unravelling the hidden ancestry of American admixed populations

Abstract

The movement of people into the Americas has brought different populations into contact, and contemporary American genomes are the product of a range of complex admixture events. Here we apply a haplotype-based ancestry identification approach to a large set of genome-wide SNP data from a variety of American, European and African populations to determine the contributions of different ancestral populations to the Americas. Our results provide a fine-scale characterization of the source populations, identify a series of novel, previously unreported contributions from Africa and Europe and highlight geohistorical structure in the ancestry of American admixed populations.

The Genetic Diversity of the Americas

“…A simple explanation for this observation was that of a genetic continuity between local pre-and post-Columbian populations (i.e., that the native population could have become amalgamated into the growing admixed population from that region). Subsequent autosomal marker surveys [including high-density singlenucleotide polymorphism (SNP) haplotype analyses] in populations from Central and South America have consistently shown that the native ancestry of these populations relates most closely to natives living in proximity (3,61,62,106). These observations suggest that, despite an increased migration across Ibero-America in recent decades, this has not been extensive enough to erase the signature of pre-Columbian native population structure.…”

“…With regard to the European ancestry of American populations, a broad genetic pattern (consistent with the colonial history of the continent) is the detection, through highdensity SNP data, of relatively high levels of northern European ancestry in US European Americans and of Iberian ancestry in Spanish America and Brazil (19,48,61). These high-density SNP data have also revealed finer-grained geographic patterns.…”

Latin Americans show wide-spread Converso ancestry and the imprint of local Native ancestry on physical appearance

“…This approach differs from the mixture model procedure described in 3,5,[32][33][34] in that it assumes that ݈ is multinomial distributed and solves for ߚ using a Bayesian approach rather than a nonnegative least squares optimization. The model is similar to the one described in 35 , but introduces new improvements in the way that λ is estimated and in the MCMC proposal procedure.…”

Population inference from contemporary American craniometrics

“…Reduced datasets include Black and White (n 5 1,666) and Black, White and Hispanic samples (n 5 2,005); while an expanded dataset (n 5 2,222) incorporates a majority sampling (n 5 144) of the Asian individuals (n % 170) in the FDB. These Asian cases were not included as part of this project's primary analysis given concerns over this sample's ability to sufficiently address the variation present in any one of the many biogeographic populations inhabiting Asia or in those U.S. groups which are of Asian descent (Zhang et al, 2007;Hanihara et al, 2008;Hanihara and Ishida, 2009;Hugo Pan-Asian SNP Consortium, 2009;Lao et al, 2010;Stoneking and Delfin, 2010;Montinaro et al, 2015). Inferential potential is limited by the sampling of largely Asian born males, sourced in small numbers from only a few countries-Japan, China, and Vietnam (Dudzik 2015).…”

“…The resulting history of settlement, coupled with periods of recent admixture among these groups, has led to a landscape of variation in the United States that is highly structured and so exhibits complex patterns of biological relationship (Paschou et al, 2008;Halder et al, 2009;Bryc et al, 2010a,b;Lao et al, 2010;Bryc et al, 2015;Montinaro et al, 2015). In recent years, focus in human genetics has shifted accordingly towards large-scale genomic analyses that allow for the identification of such admixture events and the understanding of ancestry at unprecedented levels of resolution for these challenging samples who often represent especially underserved populations in the Americas (Kosoy et al, 2009;Galanter et al, 2012;Kidd et al, 2012;Gravel et al, 2013;Moreno-Estrada et al, 2013Skoglund et al, 2015).…”