Summary Congenital heart defects, the most common birth disorders, are the clinical manifestation of anomalies in fetal heart development - a complex process involving dynamic spatiotemporal coordination among various precursor cell lineages. This complexity underlies the incomplete understanding of the genetic architecture of congenital heart diseases (CHDs). To define the multi-cellular epigenomic and transcriptional landscape of cardiac cellular development, we generated single-cell chromatin accessibility maps of human fetal heart tissues. We identified eight major differentiation trajectories involving primary cardiac cell types, each associated with dynamic transcription factor (TF) activity signatures. We identified similarities and differences of regulatory landscapes of iPSC-derived cardiac cell types and their in vivo counterparts. We interpreted deep learning models that predict cell-type resolved, base-resolution chromatin accessibility profiles from DNA sequence to decipher underlying TF motif lexicons and infer the regulatory impact of non-coding variants. De novo mutations predicted to affect chromatin accessibility in arterial endothelium were enriched in CHD cases versus controls. We used CRISPR-based perturbations to validate an enhancer harboring a nominated regulatory CHD mutation, linking it to effects on the expression of a known CHD gene JARID2 . Together, this work defines the cell-type resolved cis-regulatory sequence determinants of heart development and identifies disruption of cell type-specific regulatory elements as a component of the genetic etiology of CHD.

Integrative single-cell analysis of cardiogenesis identifies developmental trajectories and non-coding mutations in congenital heart disease