Project Summary/Abstract The mechanisms for induction of autoimmunity remain enigmatic, in part due to the unconfirmed activity of many autoimmune-associated noncoding common genetic variants. To dissect the specific mechanisms of how all common and disease-associated noncoding variation modulates gene expression, I propose to employ scalable assays in three cell types that will assess 2708 noncoding common variants for gene-modulatory function in an important autoimmune-associated locus containing the negative regulatory gene TNFAIP3/A20. One assay will test ~2700 variants for their effects on reporter expression pre- and post-stimulation. A second assay will evaluate ~43,000 systematic locus-wide deletions in the genome to determine regulatory regions (and potentially active variants within) in cell types. I will then map the active disease-associated variants from these assays to the open chromatin of autoimmune patient cell types to create a ranked list of those that putatively operate in disease. I will then determine the mechanism of action for these active, open chromatin localized variants through genetically engineering risk and non-risk alleles using CRISPR-Cas9 homology directed repair and performing biochemical assays. This method is scalable to study many loci in future work, which will contribute to our knowledge of disease gene networks, accurate animal disease models, and more efficacious therapeutics.

Project Narrative Autoimmune diseases likely arise through a combination of human genetic and epigenetic variation. The goal of this work is to incorporate methods for studying the function of thousands of genetic variants in an important autoimmune locus containing the TNFAIP3 gene. These studies, which will be scaled to the study of many disease loci in future studies, will be carried out in disease associated cell types and related to patient epigenetic information, with important implications for the study of complex disease inheritance, creation of genetically relevant murine disease models, and the formation of disease gene networks.