Genome-wide association studies (GWAS) have emerged as a robust unbiased approach to identify single nucleotide polymorphisms (SNPs) associated with incidence of a particular phenotype or disease (Manolio, 2010). Only a small fraction of GWAS lead variants lie within coding sequence and thus directly implicate a functional gene at a locus; the vast majority of lead SNPs fall in noncoding sequence. Moreover, most of these SNPs are not themselves functional but exist in linkage disequilibrium (LD) with the true functional variants. Because many human disease-associated variants are believed to regulate gene expression, expression quantitative trait locus (eQTL) and allele-specific expression (ASE) studies may illuminate potential downstream targets of functional variants. These regulated genes then become candidates for experimental manipulation to ascertain their relevance to the phenotype of interest. However, functional studies elucidating the mechanisms of identified variants have remained a challenge due to the need for laborious experiments and the lack of suitable model systems for noncoding sequence studies.
