Portability of Tag SNPs Across Isolated Population Groups: An Example from India

Abstract

SummaryIsolated population groups are useful in conducting association studies of complex diseases to avoid various pitfalls, including those arising from population stratification. Since DNA resequencing is expensive, it is recommended that genotyping be carried out at tagSNP (tSNP) loci. For this, tSNPs identified in one isolated population need to be used in another. Unless tSNPs are highly portable across populations this strategy may result in loss of information in association studies. We examined the issue of tSNP portability by sampling individuals from 10 isolated ethnic groups from India. We generated DNA resequencing data pertaining to 3 genomic regions and identified tSNPs in each population. We defined an index of tSNP portability and showed that portability is low across isolated Indian ethnic groups. The extent of portability did not significantly correlate with genetic similarity among the populations studied here. We also analyzed our data with sequence data from individuals of African and European descent. Our results indicated that it may be necessary to carry out resequencing in a small number of individuals to discover SNPs and identify tSNPs in the specific isolated population in which a disease association study is to be conducted.

Using Population Mixtures to Optimize the Utility of Genomic Databases: Linkage Disequilibrium and Association Study Design in India

“…One of these groups is sub‐Saharan African populations, who have considerably lower levels of LD than other populations (Reich et al 2001; Gabriel et al 2002; Tishkoff & Kidd, 2004; Hinds et al 2005; The International HapMap Consortium, 2005; Sawyer et al 2005; Conrad et al 2006) and who therefore require more tag SNPs to attain the same genomic coverage as can be obtained elsewhere. The other group consists of intermediate‐LD non‐African populations who are genetically distant from populations in the HapMap (Conrad et al 2006; Johansson et al 2007; Roy et al 2008). Such populations – found mainly in parts of Eurasia far from HapMap locations – do not benefit either from the relative ease of identifying tag SNPs in high‐LD populations using almost any low‐ or intermediate‐LD donor sample, or from the boost in tag performance supplied by a close genetic relationship to a HapMap population.…”

“…These linguistically defined groups were chosen from a larger survey of Indian genetic variation (Rosenberg et al 2006) to represent parts of India distant from other places in which haplotype variation has previously been more extensively studied. India has been largely omitted from genomic LD studies, and as a result of its intermediate location between Europe and East Asia, SNP variation in Indian groups is expected to be imperfectly captured by any single HapMap sample (Roy et al 2008). Thus, use of mixtures may have some potential for improving the prospects for genetic association studies in Indian populations.…”

Linkage Effects and Analysis of Finite Sample Errors in the HapMap

“…We let x = p AB , y = p H B , and z = p H A and rewrite the formula for the correlation coefficient in terms of x, y, z. (13) We compute the gradient of f:…”

“…Second, the estimates of r 2 are very inaccurate which leads to inaccurate estimates of the power of association studies. Several groups have previously pointed out this limitation [10] and have performed empirical studies exploring this and the related issue of the transferability of tag SNPs to different populations [11][12][13] . Finally, the linkage structure is used by imputation methods to estimate frequencies of untyped SNPs in association studies.…”

An approach to incorporate linkage disequilibrium structure into genomic association analysis

“…However, identification of tag SNPs may vary with the method of haplotype construction (Niu, 2004). Further, tag SNPs selected from one population may not apply to other populations (Liu et al, 2004;Roy et al, 2007).…”