Human Genetics

, Volume 128, Issue 2, pp 145–153

Genome-wide analysis of the structure of the South African Coloured Population in the Western Cape

  • Erika de Wit
  • Wayne Delport
  • Chimusa E. Rugamika
  • Ayton Meintjes
  • Marlo Möller
  • Paul D. van Helden
  • Cathal Seoighe
  • Eileen G. Hoal
Original Investigation

DOI: 10.1007/s00439-010-0836-1

Cite this article as:
de Wit, E., Delport, W., Rugamika, C.E. et al. Hum Genet (2010) 128: 145. doi:10.1007/s00439-010-0836-1

Abstract

Admixed populations present unique opportunities to discover the genetic factors underlying many multifactorial diseases. The geographical position and complex history of South Africa has led to the establishment of the unique admixed population known as the South African Coloured. Not much is known about the genetic make-up of this population, and the historical record is patchy. We genotyped 959 individuals from the Western Cape area, self-identified as belonging to this population, using the Affymetrix 500k genotyping platform. This resulted in nearly 75,000 autosomal SNPs that could be compared with populations represented in the International HapMap Project and the Human Genome Diversity Project. Analysis by means of both the admixture and linkage models in STRUCTURE revealed that the major ancestral components of this population are predominantly Khoesan (32–43%), Bantu-speaking Africans (20–36%), European (21–28%) and a smaller Asian contribution (9–11%), depending on the model used. This is consistent with historical data. While of great historical and genealogical interest, this information is also essential for future admixture mapping of disease genes in this population.

Supplementary material

439_2010_836_MOESM1_ESM.tif (6 kb)
Figure S1 Estimates of the number of ancestral populations (K) for the SAC and combined HapMap and HGDP samples under an admixture model using the STRUCTURE software. The estimated probability of the data given the model is plotted against increasing K for each of the subsets of SNP data used (see Methods) (TIFF 6 kb)
439_2010_836_MOESM2_ESM.tif (601 kb)
Figure S2 Proportion of each individual’s ancestry for the number of ancestral populations from k = 2 to the estimated number of ancestral populations with greatest probability (Fig S1). Plots shown are for random linked SNPs (TIFF 600 kb)
439_2010_836_MOESM3_ESM.tif (256 kb)
Figure S3 Proportion of each individual’s ancestry for the number of ancestral populations from k = 2 to the estimated number of ancestral populations with greatest probability (Fig S1). Plots shown are for unlinked random SNPs (TIFF 256 kb)
439_2010_836_MOESM4_ESM.tif (357 kb)
Figure S4 Proportion of each individual’s ancestry for the number of ancestral populations from k = 2 to the estimated number of ancestral populations with greatest probability (Fig S1). Plots shown are for linked Ancestry Informative Markers (TIFF 356 kb)
439_2010_836_MOESM5_ESM.tif (102 kb)
Figure S5: Proportion of each individual’s ancestry derived using the linkage model in STRUCTURE for the optimal number of ancestral populations (K = 4) (TIFF 102 kb)
439_2010_836_MOESM6_ESM.pdf (23 kb)
Supplementary Tables (PDF 23 kb)

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Erika de Wit
    • 1
  • Wayne Delport
    • 2
    • 3
  • Chimusa E. Rugamika
    • 3
  • Ayton Meintjes
    • 3
  • Marlo Möller
    • 1
  • Paul D. van Helden
    • 1
  • Cathal Seoighe
    • 4
  • Eileen G. Hoal
    • 1
  1. 1.Molecular Biology and Human Genetics, MRC Centre for Molecular and Cellular Biology, DST/NRF Centre of Excellence for Biomedical TB Research, Faculty of Health SciencesStellenbosch UniversityTygerbergSouth Africa
  2. 2.Department of Pathology, Antiviral Research CenterUniversity of CaliforniaSan DiegoUSA
  3. 3.Institute of Infectious Disease and Molecular MedicineUniversity of Cape TownCape TownSouth Africa
  4. 4.School of Mathematics, Statistics and Applied MathematicsNational University of IrelandGalwayIreland