G3: Genes, Genomes, Genetics (Nov 2018)

Estimating Asian Contribution to the Brazilian Population: A New Application of a Validated Set of 61 Ancestry Informative Markers

  • Roberta B. Andrade,
  • Marcos A. T. Amador,
  • Giovanna C. Cavalcante,
  • Luciana P. C. Leitão,
  • Marianne R. Fernandes,
  • Antônio A. C. Modesto,
  • Fabiano C. Moreira,
  • André S. Khayat,
  • Paulo P. Assumpção,
  • Ândrea Ribeiro-dos-Santos,
  • Sidney Santos,
  • Ney P. C. Santos

DOI
https://doi.org/10.1534/g3.118.200650
Journal volume & issue
Vol. 8, no. 11
pp. 3577 – 3582

Abstract

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Estimates of different ancestral proportions in admixed populations are very important in population genetics studies, especially for the detection of population substructure effects in studies of case-control associations. Brazil is one of the most heterogeneous countries in the world, both from a socio-cultural and a genetic point of view. In this work, we investigated a previously developed set of 61 ancestry informative markers (AIM), aiming to estimate the proportions of four different ancestral groups (African, European, Native American and Asian) in Brazilian populations. To the best of our knowledge, this is the first study to use a set of AIM to investigate the genetic contribution of all four main parental populations to the Brazilian population, including Asian contribution. All selected markers were genotyped through multiplex PCR and capillary electrophoresis. The set was able to successfully differentiate the four ancestral populations (represented by 939 individuals) and identify their genetic contributions to the Brazilian population. In addition, it was used to estimate individual interethnic admixture of 1050 individuals from the Southeast region of Brazil and it showed that these individuals present a higher European ancestry contribution, followed by African, Asian and Native American ancestry contributions. Therefore, the 61 AIM set has proved to be a valuable tool to estimate individual and global ancestry proportions in populations mainly formed by these four groups. Our findings highlight the importance of using sets of AIM to evaluate population substructure in studies carried in admixed populations, in order to avoid misinterpretation of results.

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