Identification of transcription factor cooperativity via stochastic system model

Bioinformatics. 2006 Sep 15;22(18):2276-82. doi: 10.1093/bioinformatics/btl380. Epub 2006 Jul 14.

Abstract

Motivation: Transcription factor binding sites are known to co-occur in the same gene owing to cooperativity of the transcription factors (TFs) that bind to them. Genome-wide location data can help us understand how an individual TF regulates its target gene. Nevertheless, how TFs cooperate to regulate their target genes still needs further study. In this study, genome-wide location data and expression profiles are integrated to reveal how TFs cooperate to regulate their target genes from the stochastic system perspective.

Results: Based on a stochastic dynamic model, a new measurement of TF cooperativity is developed according to the regulatory abilities of cooperative TF pairs and the number of their occurrences. Our method is employed to the yeast cell cycle and reveals successfully many cooperative TF pairs confirmed by previous experiments, e.g. Swi4-Swi6 in G1/S phase and Ndd1-Fkh2 in G2/M phase. Other TF pairs with potential cooperativity mentioned in our results can provide new directions for future experiments. Finally, a cooperative TF network of cell cycle is constructed from significant cooperative TF pairs.

Contact: bschen@ee.nthu.edu.tw

Supplementary information: http://www.ee.nthu.edu.tw/~bschen/cooperativity/

MeSH terms

  • Binding Sites
  • Cell Cycle Proteins / physiology
  • Computer Simulation
  • Gene Expression Regulation / physiology*
  • Models, Genetic*
  • Models, Statistical
  • Protein Binding
  • Regulatory Elements, Transcriptional / physiology*
  • Saccharomyces cerevisiae / physiology*
  • Saccharomyces cerevisiae Proteins / metabolism*
  • Signal Transduction / physiology*
  • Transcription Factors / physiology*

Substances

  • Cell Cycle Proteins
  • Saccharomyces cerevisiae Proteins
  • Transcription Factors