PROJECT SUMMARY A substantial fraction of SNPs associated with human traits and diseases through genome-wide association studies (GWAS) are likely regulatory variants as they tend to be located within enhancers and associated with differential gene expression. Thus, as a key step in implementing personalized medicine, it is important to identify regulatory variants in the human genome, and characterize their underlying molecular mechanisms. However, identifying and elucidating the functions of regulatory variants is currently challenging as these variants show similar associations with many other neutral variants due to linkage disequilibrium, can be quite far from the gene(s) they regulate, and often have cell type-specific effects. To overcome these challenges, the Frazer laboratory has established an experimental platform that enables the simultaneous interrogation of multiple processes involved in gene regulation, including the colocalization of distant regions of the genome through chromatin looping, the binding of many regulatory proteins to DNA, and the alteration of DNA methylation. This experimental platform, consisting of a biobank of 231 iPSC lines (from 214 individuals) and 140 iPSC-derived cardiomyocytes (from 130 individuals), enables the generation and analysis of molecular phenotype data across hundreds of samples from different individuals. All individuals in the resource have 50X whole genome sequencing (WGS) data, and the lab is currently molecularly characterizing the iPSCs and iPSC-derived cardiomyocytes via RNA-seq, ATAC-seq, H3K27ac ChIP-seq, and DNA-methylation arrays, as well as Hi-C data for both cell types from seven individuals in a three-generational family. These datasets, combined with analytic frameworks that integrate the effects of genetics on each of these phenotypes, provide a powerful experimental approach for systematically identifying and functionally characterizing regulatory variation genome-wide. In Aim 1, I quantify the extent to which genetic variants influence 3D chromatin structure, and identify genetic variants that affect gene expression by modulating chromatin architecture. In Aim 2, I will identify genetic variation affecting chromatin accessibility, use a quantitative framework to characterize whether this variation is systematically associated with functional regions of the genome, and determine the extent to which these enrichments vary by minor allele frequency and cell type-specificity. In Aim 3, I will integrate genetic associations across multiple molecular phenotypes to prioritize likely functional regulatory variants, and for each prioritized variant, propose likely underlying molecular mechanisms based on its patterns of association. Overall, the proposed project will establish an experimental and computational framework using multiple types of molecular phenotypes in iPSC and iPSC-derived cardiomyocytes to interrogate the molecular function of human regulatory variation. Insights gained from this approach will improve our understanding of the molecular impact of regulatory variation on complex disease and may enable better integration of regulatory variation into personalized medicine.