Allelic expression profiling to dissect genome-wide association study signals

Abstract

Genome-wide association studies are providing exciting new insight into the genetics of complex disease, but oftentimes, the genomic regions associated with the trait of interest are large enough to contain several equally plausible candidate genes. Commonly, no obvious, putatively functional, polymorphisms are found to segregate. In most cases, therefore, functional evaluation of possible regulatory mechanisms is necessary to narrow the list of potential candidates. One approach to functional characterization of such variants is allelic expression (AE) profiling, which provides an assessment of transcriptional differences between two homologous transcripts. In AE, a heterozygous, transcribed single nucleotide polymorphism is used to quantify the relative transcript abundance between two gene copies. A ratio that differs significantly from 1:1 suggests that the sample may be heterozygous for a cis-acting regulatory allele. The pattern of observed cis-regulatory variation in the profiled candidate genes can thus narrow the list of candidates under an association signal substantially. In addition, AE is also an accessible and economical strategy, as it relies heavily upon standard techniques and equipment likely to be present in any disease-mapping laboratory.