Most variants implicated in common human disease by Genome-Wide Association Studies (GWAS) lie in non-coding sequence intervals. Despite the suggestion that regulatory element disruption represents a common theme, identifying causal risk variants within indicted genomic regions remains a significant challenge. Here we present a novel sequence-based computational method to predict the effect of regulatory variation, using a classifier (gkm-SVM) which encodes cell-specific regulatory sequence vocabularies. The induced change in the gkm-SVM score, deltaSVM, quantifies the effect of variants. We show that deltaSVM accurately predicts the impact of SNPs on DNase I sensitivity in their native genomic context, and accurately predicts the results of dense mutagenesis of several enhancers in reporter assays. Previously validated GWAS SNPs yield large deltaSVM scores, and we predict novel risk SNPs for several autoimmune diseases. Thus, deltaSVM provides a powerful computational approach for systematically identifying functional regulatory variants.

The identification of common variants that contribute to the genesis of human inherited disorders remains a significant challenge. Hirschsprung disease (HSCR) is a multifactorial, non-mendelian disorder in which rare high-penetrance coding sequence mutations in the receptor tyrosine kinase RET contribute to risk in combination with mutations at other genes. We have used family-based association studies to identify a disease interval, and integrated this with comparative and functional genomic analysis to prioritize conserved and functional elements within which mutations can be sought. We now show that a common non-coding RET variant within a conserved enhancer-like sequence in intron 1 is significantly associated with HSCR susceptibility and makes a 20-fold greater contribution to risk than rare alleles do. This mutation reduces in vitro enhancer activity markedly, has low penetrance, has different genetic effects in males and females, and explains several features of the complex inheritance pattern of HSCR. Thus, common low-penetrance variants, identified by association studies, can underlie both common and rare diseases.

Evolutionary sequence conservation is an accepted criterion to identify noncoding regulatory sequences. We have used a transposon-based transgenic assay in zebrafish to evaluate noncoding sequences at the zebrafish ret locus, conserved among teleosts, and at the human RET locus, conserved among mammals. Most teleost sequences directed ret-specific reporter gene expression, with many displaying overlapping regulatory control. The majority of human RET noncoding sequences also directed ret-specific expression in zebrafish. Thus, vast amounts of functional sequence information may exist that would not be detected by sequence similarity approaches.