Utilizing linkage disequilibrium information from Indian Genome Variation Database for mapping mutations: SCA12 case study.

Stratification in heterogeneous populations poses an enormous challenge in linkage disequilibrium (LD) based identification of causal loci using surrogate markers. In this study, we demonstrate the enormous potential of endogamous Indian populations for mapping mutations in candidate genes using minimal SNPs, mainly due to larger regions of LD. We show this by a case study of the PPP2R2B gene (approximately 400 kb) that harbours a CAG repeat, expansion of which has been implicated in spinocerebellar ataxia type 12 (SCA12). Using LD information derived from Indian Genome Variation database (IGVdb) on populations which share similar ethnic and linguistic backgrounds as the SCA12 study population, we could map the causal loci using a minimal set of three SNPs, without the generation of additional basal data from the ethnically matched population. We could also demonstrate transferability of tagSNPs from a related HapMap population for mapping the mutation.