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 (CHDs) 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 if these sites and networks are enriched for disease relevant genes and associated genetic variation. Methods and Results: We characterized chromatin state and gene expression dynamics during human heart organogenesis. We profiled seven histone modifications in embryonic hearts from each of nine distinct Carnegie stages (CS13-14, CS16-21, and CS23), annotated chromatin states, and compared these maps to over 100 human tissues and cell types. We also generated RNA-seq data, performed differential expression, and constructed weighted gene co-expression 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, 7.5x enrichment, p<2.2x10 -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 electrocardiogram 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 CHDs.

Craniofacial disorders are among the most common of all congenital defects. A majority of craniofacial development occurs early in pregnancy and to fully understand how craniofacial defects arise, it is essential to observe gene expression during this critical time period. To address this we performed bulk and single-cell RNA-seq on human craniofacial tissue from embryonic development 4 to 8 weeks post conception. This data comprises the most comprehensive profiling of the transcriptome in the early developing human face to date. We identified 239 genes that were specifically expressed in craniofacial tissues relative to dozens of other human tissues and stages. We found that craniofacial specific enhancers are enriched within 400kb of these genes establishing putative regulatory interactions. To further understand how genes are organized in this program we constructed coexpression networks. Strong disease candidates are likely genes that are coexpressed with many other genes, serving as regulatory hubs within these networks. We leveraged large functional genomics databases including GTEx and GnomAD to reveal hub genes that are specifically expressed in craniofacial tissue and genes which are resistant to mutation in the normal healthy population. Our unbiased method revealed dozens of novel disease candidate genes that warrant further study.

Craniofacial disorders arise in early pregnancy and are one of the most common congenital defects. To fully understand how craniofacial disorders arise, it is essential to characterize gene expression during the patterning of the craniofacial region. To address this, we performed bulk and single-cell RNA-seq on human craniofacial tissue from 4-8 weeks post conception. Comparisons to dozens of other human tissues revealed 239 genes most strongly expressed during craniofacial development. Craniofacial-biased developmental enhancers were enriched +/− 400 kb surrounding these craniofacial-biased genes. Gene co-expression analysis revealed that regulatory hubs are enriched for known disease causing genes and are resistant to mutation in the normal healthy population. Combining transcriptomic and epigenomic data we identified 539 genes likely to contribute to craniofacial disorders. While most have not been previously implicated in craniofacial disorders, we demonstrate this set of genes has increased levels of de novo mutations in orofacial clefting patients warranting further study.