Molecular Signatures and Networks of Cardiomyocyte Differentiation in Humans and Mice

Yumei Wang, Na Yi, Yi Hu, Xianxiao Zhou, Hanyu Jiang, Qin Lin, Rou Chen, Huan Liu, Yanqiong Gu, Chang Tong, Min Lu, Junfang Zhang, Bin Zhang, Luying Peng, Li Li

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


Cardiomyocyte differentiation derived from embryonic stem cells (ESCs) is a complex process involving molecular regulation of multiple levels. In this study, we first identify and compare differentially expressed gene (DEG) signatures of ESC-derived cardiomyocyte differentiation (ESCDCD) in humans and mice. Then, the multiscale embedded gene co-expression network analysis (MEGENA) of the human ESCDCD dataset is performed to identify 212 significantly co-expressed gene modules, which capture well the regulatory information of cardiomyocyte differentiation. Three modules respectively involved in the regulation of stem cell pluripotency, Wnt, and calcium pathways are enriched in the DEG signatures of the differentiation phase transition in the two species. Three human-specific cardiomyocyte differentiation phase transition modules are identified. Moreover, the potential regulation mechanisms of transcription factors during cardiomyocyte differentiation are also illustrated. Finally, several novel key drivers of ESCDCD are identified with the evidence of their expression during mouse embryonic cardiomyocyte differentiation. Using an integrative network analysis, the core molecular signatures and gene subnetworks (modules) underlying cardiomyocyte lineage commitment are identified in both humans and mice. Our findings provide a global picture of gene-gene co-regulation and identify key regulators during ESCDCD.

Original languageEnglish
Pages (from-to)696-711
Number of pages16
JournalMolecular Therapy Nucleic Acids
StatePublished - 4 Sep 2020


  • cardiomyocyte differentiation
  • differentially expressed gene
  • embryonic stem cell
  • gene co-expression network
  • module
  • transcription factor


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