Integrated multi-omics analysis identifies features that predict human pluripotent stem cell-derived progenitor differentiation to cardiomyocytes [RNA-Seq]

Human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) are advancing cardiovascular development and disease modeling, drug testing, and regenerative therapies. However, hPSC-CM production is hindered by significant variability in the differentiation process. Establishment of early quality markers to monitor lineage progression and predict terminal differentiation outcomes would address this robustness and reproducibility roadblock in hPSC-CM production. We performed an integrated transcriptomic and epigenomic analysis to assess how attributes of the cardiac progenitor cell (CPC) affect CM differentiation outcome. Our analysis identified predictive markers of CPCs that give rise to high purity CM batches, including TTN, TRIM55, DUSP5, DUSP6, GIPR, RHOBTB3, CRIP2, SLC7A11, MAB21L2, and CALD1. We also gained insight into mechanisms of batch failure and dominant non-CM cell types generated in failed batches. This study demonstrates how integrated multi-omic analysis of progenitor cells can identify quality attributes of that progenitor and predict differentiation outcomes, thereby improving differentiation protocols and increasing process robustness. We sought to identify molecular markers at the CPC stage of differentiation of hIPSCs which are predictive of (or correlate with) high terminal purity of cardiomyoytes (i.e. markers at the CPC stage which are enriched in CPCs which have been validate to result in high CM purity batches vs low purity ones). To this end, we performed multi-omic analyses (in this submission, RNA-seq and ATAC-seq) on high efficiency CPCs (those resulting in high CM purity outcomes) and low efficiency CPCs (those resulting in low CM purity outcomes)