A minimum set of ancestry informative markers for determining admixture proportions in a mixed American population: the Brazilian set

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art_SANTOS_A_minimum_set_of_ancestry_informative_markers_for_2016.PDF (1.01 MB)
Citações na Scopus
34
Tipo de produção
article
Data de publicação
2016
Editora
NATURE PUBLISHING GROUP
DOI
Indexadores
Scopus
Web of Science
PubMed
Título da Revista
ISSN da Revista
Título do Volume
Autores
TARAZONA-SANTOS, Eduardo
RODRIGUES-SOARES, Fernanda
BARRETO, Mauricio L.
HORTA, Bernardo L.
LIMA-COSTA, Maria F.
GOUVEIA, Mateus H.
MACHADO, Moara
SILVA, Thiago M.
Autor de Grupo de pesquisa
Brazilian EPIGEN Project
Editores
Coordenadores
Organizadores
Citação
EUROPEAN JOURNAL OF HUMAN GENETICS, v.24, n.5, p.725-731, 2016
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
The Brazilian population is considered to be highly admixed. The main contributing ancestral populations were European and African, with Amerindians contributing to a lesser extent. The aims of this study were to provide a resource for determining and quantifying individual continental ancestry using the smallest number of SNPs possible, thus allowing for a cost-and time-efficient strategy for genomic ancestry determination. We identified and validated a minimum set of 192 ancestry informative markers (AIMs) for the genetic ancestry determination of Brazilian populations. These markers were selected on the basis of their distribution throughout the human genome, and their capacity of being genotyped on widely available commercial platforms. We analyzed genotyping data from 6487 individuals belonging to three Brazilian cohorts. Estimates of individual admixture using this 192 AIM panels were highly correlated with estimates using similar to 370 000 genome-wide SNPs: 91%, 92%, and 74% of, respectively, African, European, and Native American ancestry components. Besides that, 192 AIMs are well distributed among populations from these ancestral continents, allowing greater freedom in future studies with this panel regarding the choice of reference populations. We also observed that genetic ancestry inferred by AIMs provides similar association results to the one obtained using ancestry inferred by genomic data (370 K SNPs) in a simple regression model with rs1426654, related to skin pigmentation, genotypes as dependent variable. In conclusion, these markers can be used to identify and accurately quantify ancestry of Latin Americans or US Hispanics/Latino individuals, in particular in the context of fine-mapping strategies that require the quantification of continental ancestry in thousands of individuals.
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URI
https://observatorio.fm.usp.br/handle/OPI/14541
Referências
  1. Cooper RS, 2008, HUM MOL GENET, V17, pR151, DOI 10.1093/hmg/ddn263
  2. Rosenberg NA, 2003, AM J HUM GENET, V73, P1402, DOI 10.1086/380416
  3. Yang N, 2005, HUM GENET, V118, P382, DOI 10.1007/s00439-005-0012-1
  4. Price AL, 2006, NAT GENET, V38, P904, DOI 10.1038/ng1847
  5. Victora CG, 2006, INT J EPIDEMIOL, V35, P237, DOI 10.1093/ije/dyi290
  6. Lima-Costa MF, 2011, INT J EPIDEMIOL, V40, P862, DOI 10.1093/ije/dyq143
  7. Purcell S, 2007, AM J HUM GENET, V81, P559, DOI 10.1086/519795
  8. Phillips C, 2013, ELECTROPHORESIS, V34, P1151, DOI 10.1002/elps.201200621
  9. Lamason RL, 2005, SCIENCE, V310, P1782, DOI 10.1126/science.1116238
  10. Giolo SR, 2012, EUR J HUM GENET, V20, P111, DOI 10.1038/ejhg.2011.144
  11. Alexander DH, 2009, GENOME RES, V19, P1655, DOI 10.1101/gr.094052.109
  12. Goncalves VF, 2008, HUM HERED, V65, P23, DOI 10.1159/000106059
  13. Kosoy R, 2009, HUM MUTAT, V30, P69, DOI 10.1002/humu.20822
  14. Santos NPC, 2010, HUM MUTAT, V31, P184, DOI 10.1002/humu.21159
  15. Barreto Mauricio L, 2006, BMC Pulm Med, V6, P15, DOI 10.1186/1471-2466-6-15
  16. Beleza S, 2013, PLOS GENET, V9, DOI 10.1371/journal.pgen.1003372
  17. Galanter JM, 2012, PLOS GENET, V8, DOI 10.1371/journal.pgen.1002554
  18. Holsinger KE, 2009, NAT REV GENET, V10, P639, DOI 10.1038/nrg2611
  19. Kuhn PC, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0042702
  20. Manichaikul A, 2012, PLOS GENET, V8, P285, DOI 10.1371/journal.pgen.1002640
  21. Pena SDJ, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0017063
  22. Price AL, 2008, PLOS GENET, V4, DOI 10.1371/journal.pgen.0030236
  23. Manta FSD, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0075145
  24. Shriver Mark D., 2004, Human Genomics, V1, P274
  25. Shtir CJ, 2009, BMC GENET, V10, DOI 10.1186/1471-2156-10-71
  26. Tayo BO, 2011, PLOS ONE, V6, DOI 10.1371/journal.pone.0019166
  27. Tian C, 2008, PLOS GENET, V4, DOI 10.1371/journal.pgen.0040004
  28. Wang ZM, 2010, PLOS ONE, V5, DOI 10.1371/journal.pone.0013336

Coleções
Artigos e Materiais de Revistas Científicas - HC/InCor
Artigos e Materiais de Revistas Científicas - LIM/13