Prediction and testing of novel transcriptional networks regulating embryonic stem cell self-renewal and commitment

Cell Stem Cell. 2007 Jun 7;1(1):71-86. doi: 10.1016/j.stem.2007.04.002.


Stem cell fate is governed by the integration of intrinsic and extrinsic positive and negative signals upon inherent transcriptional networks. To identify novel embryonic stem cell (ESC) regulators and assemble transcriptional networks controlling ESC fate, we performed temporal expression microarray analyses of ESCs after the initiation of commitment and integrated these data with known genome-wide transcription factor binding. Effects of forced under- or overexpression of predicted novel regulators, defined as differentially expressed genes with potential binding sites for known regulators of pluripotency, demonstrated greater than 90% correspondence with predicted function, as assessed by functional and high-content assays of self-renewal. We next assembled 43 theoretical transcriptional networks in ESCs, 82% (23 out of 28 tested) of which were supported by analysis of genome-wide expression in Oct4 knockdown cells. By using this integrative approach, we have formulated novel networks describing gene repression of key developmental regulators in undifferentiated ESCs and successfully predicted the outcomes of genetic manipulation of these networks.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cell Lineage
  • DNA-Binding Proteins / genetics
  • Electroporation
  • Embryonic Stem Cells / cytology*
  • HMGB Proteins / genetics
  • Humans
  • Octamer Transcription Factor-3 / genetics
  • Pluripotent Stem Cells / cytology
  • Polymerase Chain Reaction
  • RNA, Small Interfering
  • SOXB1 Transcription Factors
  • Transcription Factors / genetics
  • Transcription, Genetic*


  • DNA-Binding Proteins
  • HMGB Proteins
  • Octamer Transcription Factor-3
  • Pou5f1 protein, mouse
  • RNA, Small Interfering
  • SOX2 protein, human
  • SOXB1 Transcription Factors
  • Sox2 protein, mouse
  • Transcription Factors

Associated data

  • GEO/GSE7506
  • GEO/GSE7520