Functional dissection of human cardiac enhancers and non-coding de novo variants in congenital heart disease

About 45% of congenital heart disease (CHD) is caused by rare gene mutations. Non-coding mutations that perturb cis-regulatory elements (CREs) likely contribute to CHD among the remaining cases without clear etiology. However, identifying CHD-causing non-coding variants has been problematic. We combined human induced pluripotent stem cell-derived cardiomyocyte (iPSC-CM) differentiation and a lentivirus-mediated massively parallel reporter assay (lentiMPRA) to create a high-throughput platform to measure human cardiac enhancer activity. We tested 2451 candidate human cardiac enhancers, identified 1185 with measurable activity, and functionally dissected 123 of these by systematic tiling mutagenesis. We functionally evaluated 6761 non-coding de novo variants (ncDNVs) prioritized from the whole genome sequencing (WGS) of 749 CHD trios. 397 ncDNVs significantly affected cardiac CRE activity. Remarkably, 53% of these ncDNVs increased enhancer activity, often at regions with undetectable enhancer activity in the reference sequence. We introduced 10 of these DNVs associated with CHD genes into iPSCs and found that 4 altered expression of neighboring genes. Moreover, these 4 DNVs also altered cardiomyocyte differentiation, as assessed by single nucleus RNA sequencing. Using the MPRA data, we developed a regression model to prioritize future DNVs for functional testing and demonstrate that this model finds enrichment of DNVs in a second, independent WGS cohort. Taken together, we developed a scalable system to measure the impact of non-coding DNVs on CRE activity and deployed this platform to systematically assess the contribution of non-coding DNVs to CHD. Overall design: Control and the mutant hiPSC cells were differentiated into cardiomyocytes and frozen. Frozen cell pellets were individually barcoded with the CellPlex Kit from 10X Genomics. Nuclei from the barcoded cells were extracted and then pooled at equal amount. Single Nuclei RNAsequencing library was generated using 10X Genomics platform. Nuclei were demulitplexed using reads mapping to the barcodes.