Epigenomic and Transcriptomic Dynamics During Human Heart Organogenesis

Abstract

Rationale: There is growing evidence that common variants and rare sequence alterations in regulatory sequences can result in birth defects or predisposition to disease. Congenital heart defects are the most common birth defect and have a clear genetic component, yet only a third of cases can be attributed to structural variation in the genome or a mutation in a gene. The remaining unknown cases could be caused by alterations in regulatory sequences. Objective: Identify regulatory sequences and gene expression networks that are active during organogenesis of the human heart. Determine whether these sites and networks are enriched for disease-relevant genes and associated genetic variation. Methods and Results: We characterized ChromHMM (chromatin state) and gene expression dynamics during human heart organogenesis. We profiled 7 histone modifications in embryonic hearts from each of 9 distinct Carnegie stages (13–14, 16–21, and 23), annotated chromatin states, and compared these maps to over 100 human tissues and cell types. We also generated RNA-sequencing data, performed differential expression, and constructed weighted gene coexpression networks. We identified 177 412 heart enhancers; 12 395 had not been previously annotated as strong enhancers. We identified 92% of all functionally validated heart-positive enhancers (n=281; 7.5× enrichment; P <2.2×10 −16 ). Integration of these data demonstrated novel heart enhancers are enriched near genes expressed more strongly in cardiac tissue and are enriched for variants associated with ECG measures and atrial fibrillation. Our gene expression network analysis identified gene modules strongly enriched for heart-related functions, regulatory control by heart-specific enhancers, and putative disease genes. Conclusions: Well-connected hub genes with heart-specific expression targeted by embryonic heart-specific enhancers are likely disease candidates. Our functional annotations will allow for better interpretation of whole genome sequencing data in the large number of patients affected by congenital heart defects.