StructureQTL : novel QTL to associate SNPs and neighborhood regulatory structure

Abstract

Due to the effects they convey on the expression levels of certain genes, noncoding genetic regions are thought to play an integral part in the process of gene regulation and consequently the onset of several diseases. Numerous previous studies have demonstrated associations between single-nucleotide genetic changes (SNPs) and the regulatory activity of these noncoding regions. However, these studies have largely focused on single noncoding loci rather than the overall regulatory structure in a certain area, which could provide significant novel insight. We present two complementary approaches for this problem, which both involve studying the histone acetylation peak correlation matrix for a particular neighborhood. The first involves permutations and the Kolmogorov-Smirnov test, and the second relies heavily on community detection. We then demonstrate promising preliminary results on simulated and experimental data, and we identify a set of SNPs that may be attractive candidates for future study. We believe these methods, when applied on a large scale, will improve current knowledge regarding the mechanisms behind gene regulation and the causes of several important human diseases.