Abstract 472: Large-Scale Single-Cell RNA-Seq Identifies Heterogeneous Populations of Human Primary and Induced Pluripotent Stem Cell-Derived Endothelial Cells

Rationale: Human induced pluripotent stem cell-derived endothelial cells (iPSC-ECs) have risen as a useful tool in cardiovascular research, offering a wide gamut of translational and clinical applications. However, inefficiency of the currently available iPSC-EC differentiation protocol and underlying heterogeneity of derived iPSC-ECs remain as major limitations of iPSC-EC technology. Objective: Here we performed droplet-based single-cell RNA-sequencing (scRNA-seq) of the human iPSCs following iPSC-EC differentiation and of primary endothelial cells isolated from human coronary arteries. Droplet-based scRNA-seq enables analysis of thousands of cells in parallel, allowing comprehensive analysis of transcriptional heterogeneity. Methods and Results: Bona fide iPSC-EC cluster was identified by scRNA-seq, which expressed high levels of endothelial-specific genes. iPSC-ECs sorted by CD144 antibody-conjugated magnetic sorting exhibited standard endothelial morphology and function including tube formation, response to inflammatory signals, and production of nitric oxide. Non-endothelial cell populations resulting from the differentiation protocol were identified, which included immature and atrial-like cardiomyocytes, hepatic-like cells, and vascular smooth muscle cells. Furthermore, scRNA-seq analysis of purified iPSC-ECs revealed transcriptional heterogeneity with four major subpopulations, marked by robust enrichment of CLDN5, APLNR, GJA5, and ESM1 genes respectively. These findings were then cross-analyzed with the primary EC data. Conclusions: Massively parallel scRNA-seq allowed analysis of thousands of human iPSCs subjected to EC differentiation. Results showed inefficiency of the differentiation technique, which can be improved with further studies based on identification of molecular signatures that inhibit expansion of non-endothelial cell types. Subtypes of bona fide human iPSC-ECs were also identified, allowing us to sort for iPSC-ECs with specific biological function and identity. Cross-analysis with scRNA-seq data of human coronary artery ECs reveals transcriptional similarities and dissimilarities of iPSC-ECs to the primary ECs that will be addressed in subsequent studies.