Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have become a powerful tool for human disease modeling and therapeutic testing. However, their use remains limited by their immaturity and heterogeneity. To characterize the source of this heterogeneity, we applied complementary single-cell RNA-seq and bulk RNA-seq technologies over time during hiPSC cardiac differentiation and in the adult heart. Using integrated transcriptomic and splicing analysis, more than half a dozen distinct single-cell populations were observed, several of which were coincident at a single time-point, day 30 of differentiation. To dissect the role of distinct cardiac transcriptional regulators associated with each cell population, we systematically tested the effect of a gain or loss of three transcription factors (NR2F2, TBX5, and HEY2), using CRISPR genome editing and ChIP-seq, in conjunction with patch clamp, calcium imaging, and CyTOF analysis. These targets, data, and integrative genomics analysis methods provide a powerful platform for understanding in vitro cellular heterogeneity.

Induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) capture patient-specific genotype-phenotype relationships, as well as cell-to-cell variability of cardiac electrical activity r Computational modelling and simulation provide a high throughput approach to reconcile multiple datasets describing physiological variability, and also identify vulnerable parameter regimes r We have developed a whole-cell model of iPSC-CMs, composed of single exponential voltage-dependent gating variable rate constants, parameterized to fit experimental iPSC-CM outputs r We have utilized experimental data across multiple laboratories to model experimental variability and investigate subcellular phenotypic mechanisms in iPSC-CMs r This framework links molecular mechanisms to cellular-level outputs by revealing unique subsets of model parameters linked to known iPSC-CM phenotypes Abstract There is a profound need to develop a strategy for predicting patient-to-patient vulnerability in the emergence of cardiac arrhythmia. A promising in vitro method to address patient-specific proclivity to cardiac disease utilizes induced pluripotent stem cell-derived Divya Kernik is currently a PhD candidate in Biomedical Engineering at the University of California, Davis. She obtained a BS in Biomedical Engineering from Johns Hopkins University. The focus of her PhD work has been the development of computational methods that help to understand human-derived cardiac cells, as reported in the present study. In the future, she aims to continue to use computational modelling to address questions in cardiac physiology and pharmacology, with the underlying goal of incorporating human diversity throughout these efforts.