The vast majority of single nucleotide polymorphisms (SNPs) associated with complex human traits, including blood pressure (BP), are located in noncoding regions of DNA. These noncoding SNPs, especially the ones located in haplotype regions far from protein-coding genes, most likely influence BP by regulating gene expression. Expression quantitative trait locus (eQTL) studies are beginning to enable the identification of associations between noncoding SNPs and gene expression. However, very few studies have gone beyond associations to examine the functional effect of BP- associated noncoding SNPs on gene expression. Such studies would have to overcome substantial challenges. First, BP-associated noncoding SNPs could regulate the expression of distant protein-coding genes through chromatin folding or noncoding RNA, which means one cannot assume that the protein-coding genes that the SNPs regulate are the ones that are sequentially closest to the SNPs. Second, results from eQTL and other studies indicate the effect of noncoding SNPs on gene expression is often cell type-specific. In Project 1 of this PPG, we have developed several approaches and methods to overcome these challenges and to test the overall hypothesis that BP-associated noncoding SNPs regulate the expression of genes that are physiologically important to BP regulation. All three aims in Project 1 share the goal of identifying the effect of BP-associated noncoding SNPs on gene expression in BP-relevant cell types.
Each aim will focus on a group of LD (linkage disequilibrium) regions located far from any protein-coding gene and a specific hypothesis. The mechanistic aspect of each hypothesis will be tested in Projects 2 and 3 of this PPG. The feasibility of Project 1 is supported by an extensive series of preparatory and preliminary studies. The overall goal of this PPG proposal is to identify genes regulated by human BP-associated noncoding SNPs, examining the underlying mechanisms, and investigating their influence on BP. Project 1 focuses on the first part of the overall goal and will contribute to the goal of the program through extensive integration with Projects 2 and 3. Project 1 will rely on Core B for extensive RNA-seq analysis.
