Epigenetic state network approach for describing cell phenotypic transitions

Ping Wang, Chaoming Song, Hang Zhang, Zhanghan Wu, Xiao Jun Tian, Jianhua Xing

Research output: Contribution to journalArticlepeer-review

42 Scopus citations


Recent breakthroughs of cell phenotype reprogramming impose theoretical challenges on unravelling the complexity of large circuits maintaining cell phenotypes coupled at many different epigenetic and gene regulation levels, and quantitatively describing the phenotypic transition dynamics.Apopular picture proposed by Waddington views cell differentiation as a ball sliding down a landscape with valleys corresponding to different cell types separated by ridges. Based on theories of dynamical systems, we establish a novel 'epigenetic state network' framework that captures the global architecture of cell pheno-types, which allows us to translate the metaphorical low-dimensional Waddington epigenetic landscape concept into a simple-yet-predictive rigorous mathematical frameworkofcell phenotypic transitions. Specifically,we simplify a high-dimensional epigenetic landscape into a collection of discrete states corresponding to stable cell phenotypes connected by optimal transition pathways among them.Wethen apply theapproachtothe phenotypic transition processes among fibroblasts (FBs), pluripotent stem cells (PSCs) and cardiomyocytes (CMs). The epigenetic state network for this case predicts three major transition pathways connecting FBs and CMs. One goes by way of PSCs. The other two pathways involve transdifferentiation either indirectly through cardiac progenitor cells or directly from FB to CM. The predicted pathways and multiple intermediate states are supported by existing microarray data and other experiments. Our approach provides a theoretical framework for studying cell phenotypic transitions. Future studies at single-cell levels can directly test the model predictions.

Original languageEnglish (US)
JournalInterface Focus
Issue number3
StatePublished - 2014
Externally publishedYes


  • Gene regulatory network
  • Non-equilibrium steady state
  • Nonlinear dynamics

ASJC Scopus subject areas

  • Biotechnology
  • Biophysics
  • Bioengineering
  • Biochemistry
  • Biomaterials
  • Biomedical Engineering


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