Abstract 15806: Decoding Gene Regulatory Networks Governing Differentiation of Human Induced Pluripotent Stem Cell to Cardiovascular Lineages by Single Cell RNA-seq
Background: Human induced pluripotent stem cells (hiPSCs) offer a unique platform to investigate the regulation of human genes implicated in congenital heart diseases. However, due the heterogeneity of the differentiation process, it is difficult to identify the molecular markers for subpopulations of cardiac progenitor cells (CPC), differentiated and mature cardiomyocytes (CM). Moreover, decoding gene regulatory networks (GRN) that control the CM differentiation remains a challenging task.
Results: The RNA-seq analysis at the single cell level emerges as a powerful tool to study the complex transcriptional dynamics of cell differentiation. In this study, we differentiated hiPSCs into CMs, and performed the RNA sequencing of 315 single cells from differentiation days 0, 6, 10, 30 and 60. To cluster the cells and reconstruct the lineage hierarchies, we developed a Bayesian statistical framework called time series topographic cell map (tsTCM). tsTCM has demonstrated significantly better performance of reconstructing lineage hierarchies from temporal single cell RNA-seq than other methods such as SCUBA, Monocle and Wishbone on synthetic and published datasets. With this novel computational tool, we identified 10 distinct cell clusters corresponding to multiple stages of mesodermal progenitors, CPCs and CMs, as well as two major differentiation paths leading toward mature CMs and cardiac fibroblasts, respectively, branching around day 10. We discovered and verified molecular markers that are specifically expressed in CPCs and mature CMs such as APLNR, LRP2, HOPX, GABRA4 and FAM198B. Moreover, tsTCM allowed us to infer the dynamic GRNs controlling the CM differentiation.
Conclusion: In this study, we presented a set of novel methods to cluster cells, reconstruct lineage hierarchies, and infer the GRNs for single cell RNA-seq data. On applying these methods to single cell RNA-seq data of hiPSC-CM differentiation, we identified novel markers for distinct cell populations and pathways controlling differentiation.
Author Disclosures: W. Gong: None. N. Koyano-Nakagawa: None. W. Pan: None. D.J. Garry: None.
- © 2016 by American Heart Association, Inc.