Bayesian modeling to infer mechanisms of GWAS hypertension genes in rats

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 DESCRIPTION (provided by applicant): Hypertension is a major risk factor for heart disease and stroke that affects millions of Americans. Genome- wide association studies (GWAS) have nominated a large number of genes as important in human hypertension. Many of these genes are largely unknown, complicating study of their effects even in cell and animal model systems. We propose a novel approach whereby the function of these genes may be determined by placing them into the context of gene-gene interactions in a sensitized rodent system, the Dahl salt- sensitive (SS) rat, a well-established rodent model of hypertension. We will reduce complexity by defining the molecular network of a single cell type known to be of functional importance in salt-sensitive forms of hypertension, the epithelial Na+ transporting cells of the medullary thick ascending limb (mTAL) of the renal outer medulla. We will expose SS-derived primary cultured mTAL cells to a panel of nine stimuli to induce transcriptional changes. Samples will be collected at regular intervals after exposure and their transcriptomes will be measured. These time-course data will be analyzed using a novel Bayesian graphical approach which will create a time-dependent gene-gene interaction network. This network will be used to make predictions about the effect of knockouts from the SS genome. These predications will be tested using primary cultured mTALs from four GWAS-nominated knockout rats on the SS background. The effects of the knockouts on the networks will be used to predict phenotypes for the knockout rats, which will be tested in these animal models. The network generated by our method will provide context for GWAS-nominated genes and will greatly improve the conversion of GWAS-nominated loci into testable and useful animal models, thereby advancing the study of the genetics of salt-sensitive hypertension.