TY - JOUR
T1 - Examination of ancestry and ethnic affiliation using highly informative diallelic DNA markers
T2 - Application to diverse and admixed populations and implications for clinical epidemiology and forensic medicine
AU - Yang, Nan
AU - Li, Hongzhe
AU - Criswell, Lindsey A.
AU - Gregersen, Peter K.
AU - Alarcon-Riquelme, Marta E.
AU - Kittles, Rick
AU - Shigeta, Russell
AU - Silva, Gabriel
AU - Patel, Pragna I.
AU - Belmont, John W.
AU - Seldin, Michael F.
N1 - Funding Information:
Acknowledgments Support for this research was provided by National Institute of Health grants U01-DK57249, AR44804, AR50267 and AR20684.
PY - 2005/12
Y1 - 2005/12
N2 - We and others have identified several hundred ancestry informative markers (AIMs) with large allele frequency differences between different major ancestral groups. For this study, a panel of 199 widely distributed AIMs was used to examine a diverse set of 796 DNA samples including self-identified European Americans, West Africans, East Asians, Amerindians, African Americans, Mexicans, Mexican Americans, Puerto Ricans and South Asians. Analysis using a Bayesian clustering algorithm (STRUCTURE) showed grouping of individuals with similar ethnic identity without any identifier other than the AIMs genotyping and showed admixture proportions that clearly distinguished different individuals of mixed ancestry. Additional analyses showed that, for the majority of samples, the predicted ethnic identity corresponded with the self-identified ethnicity at high probability (P > 0.99). Overall, the study demonstrates that AIMs can provide a useful adjunct to forensic medicine, pharmacogenomics and disease studies in which major ancestry or ethnic affiliation might be linked to specific outcomes.
AB - We and others have identified several hundred ancestry informative markers (AIMs) with large allele frequency differences between different major ancestral groups. For this study, a panel of 199 widely distributed AIMs was used to examine a diverse set of 796 DNA samples including self-identified European Americans, West Africans, East Asians, Amerindians, African Americans, Mexicans, Mexican Americans, Puerto Ricans and South Asians. Analysis using a Bayesian clustering algorithm (STRUCTURE) showed grouping of individuals with similar ethnic identity without any identifier other than the AIMs genotyping and showed admixture proportions that clearly distinguished different individuals of mixed ancestry. Additional analyses showed that, for the majority of samples, the predicted ethnic identity corresponded with the self-identified ethnicity at high probability (P > 0.99). Overall, the study demonstrates that AIMs can provide a useful adjunct to forensic medicine, pharmacogenomics and disease studies in which major ancestry or ethnic affiliation might be linked to specific outcomes.
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U2 - 10.1007/s00439-005-0012-1
DO - 10.1007/s00439-005-0012-1
M3 - Article
C2 - 16193326
AN - SCOPUS:30844438710
SN - 0340-6717
VL - 118
SP - 382
EP - 392
JO - Human Genetics
JF - Human Genetics
IS - 3-4
ER -