Dataset Information

Determining ancestry proportions in complex admixture scenarios in South Africa using a novel proxy ancestry selection method.

ABSTRACT: Admixed populations can make an important contribution to the discovery of disease susceptibility genes if the parental populations exhibit substantial variation in susceptibility. Admixture mapping has been used successfully, but is not designed to cope with populations that have more than two or three ancestral populations. The inference of admixture proportions and local ancestry and the imputation of missing genotypes in admixed populations are crucial in both understanding variation in disease and identifying novel disease loci. These inferences make use of reference populations, and accuracy depends on the choice of ancestral populations. Using an insufficient or inaccurate ancestral panel can result in erroneously inferred ancestry and affect the detection power of GWAS and meta-analysis when using imputation. Current algorithms are inadequate for multi-way admixed populations. To address these challenges we developed PROXYANC, an approach to select the best proxy ancestral populations. From the simulation of a multi-way admixed population we demonstrate the capability and accuracy of PROXYANC and illustrate the importance of the choice of ancestry in both estimating admixture proportions and imputing missing genotypes. We applied this approach to a complex, uniquely admixed South African population. Using genome-wide SNP data from over 764 individuals, we accurately estimate the genetic contributions from the best ancestral populations: isiXhosa [Formula: see text], ‡Khomani SAN [Formula: see text], European [Formula: see text], Indian [Formula: see text], and Chinese [Formula: see text]. We also demonstrate that the ancestral allele frequency differences correlate with increased linkage disequilibrium in the South African population, which originates from admixture events rather than population bottlenecks.The collective term for people of mixed ancestry in southern Africa is "Coloured," and this is officially recognized in South Africa as a census term, and for self-classification. Whilst we acknowledge that some cultures may use this term in a derogatory manner, these connotations are not present in South Africa, and are certainly not intended here.

SUBMITTER: Chimusa ER

PROVIDER: S-EPMC3774743 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Determining ancestry proportions in complex admixture scenarios in South Africa using a novel proxy ancestry selection method.

Chimusa Emile R ER Daya Michelle M Möller Marlo M Ramesar Raj R Henn Brenna M BM van Helden Paul D PD Mulder Nicola J NJ Hoal Eileen G EG

PloS one 20130916 9

Admixed populations can make an important contribution to the discovery of disease susceptibility genes if the parental populations exhibit substantial variation in susceptibility. Admixture mapping has been used successfully, but is not designed to cope with populations that have more than two or three ancestral populations. The inference of admixture proportions and local ancestry and the imputation of missing genotypes in admixed populations are crucial in both understanding variation in dise ...[more]

PMID: 24066090

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Project description:BACKGROUND:Accurate determination of genetic ancestry is of high interest for many areas such as biomedical research, personal genomics and forensics. It remains an important topic in genetic association studies, as it has been shown that population stratification, if not appropriately considered, can lead to false-positive and -negative results. While large association studies typically extract ancestry information from available genome-wide SNP genotypes, many important clinical data sets on rare phenotypes and historical collections assembled before the GWAS area are in need of a feasible method (i.e., ease of genotyping, small number of markers) to infer the geographic origin and potential admixture of the study subjects. Here we report on the development, application and limitations of a small, multiplexable ancestry informative marker (AIM) panel of SNPs (or AISNP) developed specifically for this purpose. RESULTS:Based on worldwide populations from the HGDP, a 41-AIM AISNP panel for multiplex application with the ABI SNPlex and a subset with 31 AIMs for the Sequenome iPLEX system were selected and found to be highly informative for inferring ancestry among the seven continental regions Africa, the Middle East, Europe, Central/South Asia, East Asia, the Americas and Oceania. The panel was found to be least informative for Eurasian populations, and additional AIMs for a higher resolution are suggested. A large reference set including over 4,000 subjects collected from 120 global populations was assembled to facilitate accurate ancestry determination. We show practical applications of this AIM panel, discuss its limitations for admixed individuals and suggest ways to incorporate ancestry information into genetic association studies. CONCLUSION:We demonstrated the utility of a small AISNP panel specifically developed to discern global ancestry. We believe that it will find wide application because of its feasibility and potential for a wide range of applications.

Dataset Information

Determining ancestry proportions in complex admixture scenarios in South Africa using a novel proxy ancestry selection method.

Publications

Determining ancestry proportions in complex admixture scenarios in South Africa using a novel proxy ancestry selection method.

Similar Datasets

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