We propose an integrative experimental system to identify and functionally characterize noncoding genetic variants associated with cardiac conduction traits and susceptibility to arrhythmias. Conduction system diseases are among the most prevalent heart diseases, with sudden cardiac death alone responding for over 325,000 deaths in the US per year. This major public health issue has spurred intensive efforts to identify genetic factors underlying increased risk to conduction system diseases. Most genetic variants identified are noncoding in nature, making the determination of their impact on gene function and conduction system biology difficult to ascertain. Added to this difficulty, there is a generalized lack of proper experimental platforms to study cardiac system biology, such as cardiac conduction system myocytes in culture. Our proposal directly addresses these deficiencies. Capitalizing on the complementary expertise of the PIs, a genomicist that was a PI in the ENCODE project and a cardiac conduction system pathologist, we propose to create a multi-tiered experimental platform to identify causal SNPs from LD blocks associated with conduction system phenotypes from GWAS, and to systematically test for the impact of these SNPs on their putative transcriptional enhancer functions in cardiac conduction myocytes and in vivo, in transgenic mice. For the R21 phase of this project, we propose to generate a mini-ENCODE of the human heart, mapping genome-wide the coordinates of putative functional noncoding sequences in the human heart. We will overlay this information with a 3-D map of distant chromatin interactions in 50 loci containing noncoding SNPs associated with conduction system traits. Together, these data will point to the location of putative conduction system enhancers harboring SNPs associated with conduction system traits. In the R33 phase, we will utilize a multi-tiered platform to functionally interrogate the impact of these SNPs. We will initilly test candidate enhancers emerging from the R21 component. Toward that end, we developed a strategy to derive conduction system cardiomyocytes from induced pluripotent stem cells (iPSC). These cells are ideally suited for functional experiments involving conduction system biology. We will test candidate enhancers harboring disease-associated SNPs in these cells, establishing both their enhancer properties as well as allele-specific enhancer effects. A subset of conduction system enhancers will be further tested using state-of-the art mouse transgenics, to demonstrate their regulatory properties in vivo. Together, our proposed plan describes a logical, step-wise approach to identify causal SNPs within LD blocks associated with cardiac conduction system parameters and develops a novel and integrated experimental platform to functionally ascertain these disease-associated noncoding SNPs.
We propose to tackle the molecular mechanisms underlying genetic association to arrhythmias and cardiac conduction system diseases. These diseases represent a particularly intractable experimental problem due to the lack of appropriate molecular, genetic and live reagents for experimentation. (End of Abstract)
| Montefiori, Lindsey E; Sobreira, Debora R; Sakabe, Noboru J et al. (2018) A promoter interaction map for cardiovascular disease genetics. Elife 7: |
| Yang, Xinan H; Nadadur, Rangarajan D; Hilvering, Catharina Re et al. (2017) Transcription-factor-dependent enhancer transcription defines a gene regulatory network for cardiac rhythm. Elife 6: |
| Bailey, Kathleen A; Savic, Daniel; Zielinski, Mark et al. (2015) Evidence of non-pancreatic beta cell-dependent roles of Tcf7l2 in the regulation of glucose metabolism in mice. Hum Mol Genet 24:1646-54 |
