Identification of Transcription Factor Cooperativity via Stochastic System Model

　

Yu-Hsiang Chang^†, Yu-Chao Wang^†, and Bor-Sen Chen*

　

Lab of Control and Systems Biology,

Department of Electrical Engineering, National Tsing Hua University,

Hsinchu, 300, Taiwan.

　

*To whom correspondence should be addressed.

^†These authors contributed equally to this work.

Abstract

Motivation: Transcription factor binding sites are known to co-occur in the same gene due 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, for example, 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.

Keywords: TF cooperativity, dynamic model, gene regulatory network, cell cycle.

Contact: bschen@ee.nthu.edu.tw