RESUMO
Congenital heart disease (CHD) is present in 1% of live births, yet identification of causal mutations remains challenging. We hypothesized that genetic determinants for CHDs may lie in the protein interactomes of transcription factors whose mutations cause CHDs. Defining the interactomes of two transcription factors haplo-insufficient in CHD, GATA4 and TBX5, within human cardiac progenitors, and integrating the results with nearly 9,000 exomes from proband-parent trios revealed an enrichment of de novo missense variants associated with CHD within the interactomes. Scoring variants of interactome members based on residue, gene, and proband features identified likely CHD-causing genes, including the epigenetic reader GLYR1. GLYR1 and GATA4 widely co-occupied and co-activated cardiac developmental genes, and the identified GLYR1 missense variant disrupted interaction with GATA4, impairing in vitro and in vivo function in mice. This integrative proteomic and genetic approach provides a framework for prioritizing and interrogating genetic variants in heart disease.
Assuntos
Fator de Transcrição GATA4/metabolismo , Cardiopatias Congênitas , Proteínas Nucleares/metabolismo , Oxirredutases/metabolismo , Fatores de Transcrição , Animais , Cardiopatias Congênitas/genética , Camundongos , Mutação , Proteômica , Proteínas com Domínio T/genética , Fatores de Transcrição/genéticaRESUMO
Congenital heart disease often arises from perturbations of transcription factors (TFs) that guide cardiac development. ISLET1 (ISL1) is a TF that influences early cardiac cell fate, as well as differentiation of other cell types including motor neuron progenitors (MNPs) and pancreatic islet cells. While lineage specificity of ISL1 function is likely achieved through combinatorial interactions, its essential cardiac interacting partners are unknown. By assaying ISL1 genomic occupancy in human induced pluripotent stem cell-derived cardiac progenitors (CPs) or MNPs and leveraging the deep learning approach BPNet, we identified motifs of other TFs that predicted ISL1 occupancy in each lineage, with NKX2.5 and GATA motifs being most closely associated to ISL1 in CPs. Experimentally, nearly two-thirds of ISL1-bound loci were co-occupied by NKX2.5 and/or GATA4. Removal of NKX2.5 from CPs led to widespread ISL1 redistribution, and overexpression of NKX2.5 in MNPs led to ISL1 occupancy of CP-specific loci. These results reveal how ISL1 guides lineage choices through a combinatorial code that dictates genomic occupancy and transcription.