Ethnic-Difference Markers for Use in Mapping by Admixture Linkage Disequilibrium

Abstract

Mapping by admixture linkage disequilibrium (MALD) is a potentially powerful technique for the mapping of complex genetic diseases. The practical requirements of this method include (a) a set of markers spanning the genome that have large allele-frequency differences between the parental ethnicities contributing to the admixed population and (b) an understanding of the extent of admixture in the study population. To this end, a DNA-pooling technique was used to screen microsatellite and diallelic insertion/deletion markers for allele-frequency differences between putative representatives of the parental populations of the admixed Mexican American (MA) and African American (AA) populations. Markers with promising pooled differences were then confirmed by individual genotyping in both the parental and admixed populations. For the MA population, screening of >600 markers identified 151 ethnic-difference markers (EDMs) with delta>0.30 (where delta is the absolute value of each allele-frequency difference between two populations, summed over all marker alleles and divided by two) that are likely to be useful for MALD analysis. For the AA population, analysis of >400 markers identified 97 EDMs. In addition, individual genotyping of these markers in Pima Amerindians, Yavapai Amerindians, European American (EA) individuals, Africans from Zimbabwe, MA individuals, and AA individuals, as well as comparison to the CEPH genotyping set, suggests that the differences between subpopulations of an ethnicity are small for many markers with large interethnic differences. Estimates of admixture that are based on individual genotyping of these markers are consistent with a 60% EA:40% Amerindian contribution to MA populations and with a 20% EA:80% African contribution to AA populations. Taken together, these data suggest that EDMs with large interpopulation and small intrapopulation differences can be readily identified for MALD studies in both AA and MA populations.

Interethnic variability and admixture in Latin America - social implications

“…Early in these studies it was realized that the best ethnicity estimators are those with large allele frequency differences between the parental groups, and Shriver et al (1997) provided a list of such alleles; they and McKeighe et al (2000) also devised a Bayesian log-likelihood analysis for individual and population ethnic-affiliation estimation that was afterwards applied by Parra et al (2003) to Brazilian data. Parra et al (1998) and Collins-Schramm et al (2002) also used alleles with wide allele differences between parental groups (labeled by them as "population-specific" or "ethnic-difference markers") in their analyses. Relethford (2002) remarked that since the apportionment of genetic diversity in skin color is atypical (only 9% of within-population differences, against the 93%-95% cited above for other markers) it could not be used for purposes of classification.…”

Admixture analysis of South Asian cattle

“…Several studies have been carried out to examine the amount and pattern of admixture in selected human populations (Parra et al, 1998;Wilson and Goldstein, 2000;Pfaff et al, 2001;Collins-Schramm et al, 2002). A serious obstacle to these studies is the genetic similarity of all human groups and the potential difficulty in finding private or population-specific alleles (McKeigue, 1997;Shriver et al, 1997).…”

Admixture Mapping Using Interval Transmission/Disequilibrium Tests

“…In fact, computer simulation completed in this study demonstrates its good performance under conditions where the admixture process occurred over many generations and the individuals in the admixed populations had considerable variation in admixture proportion. The required information regarding the marker allele frequencies in the founding populations can be obtained through population surveys, or more conveniently be abstracted from existing sources (Kaplan et al 1998;Parra et al 1998;Goddard et al 2000;Lautenberger et al 2000;Pfaff et al 2001;Smith et al 2001;Collins-Schramm et al 2002).…”