通过随机系统模型鉴定转录因子协同作用
Identification of transcription factor cooperativity via stochastic system model.
作者信息
Chang Yu-Hsiang, Wang Yu-Chao, Chen Bor-Sen
机构信息
Laboratory of Control and Systems Biology, Department of Electrical Engineering National Tsing Hua University, Hsinchu 300, Taiwan.
出版信息
Bioinformatics. 2006 Sep 15;22(18):2276-82. doi: 10.1093/bioinformatics/btl380. Epub 2006 Jul 14.
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
SUPPLEMENTARY INFORMATION
动机
由于与转录因子结合位点（TFBS）结合的转录因子（TF）之间存在协同作用，已知这些位点会在同一基因中共现。全基因组定位数据有助于我们了解单个TF如何调控其靶基因。然而，TF如何协同调控其靶基因仍需进一步研究。在本研究中，整合全基因组定位数据和表达谱，从随机系统的角度揭示TF如何协同调控其靶基因。
结果
基于随机动态模型，根据协同TF对的调控能力及其出现次数，开发了一种新的TF协同性测量方法。我们的方法应用于酵母细胞周期，成功揭示了许多先前实验证实的协同TF对，例如G1/S期的Swi4-Swi6和G2/M期的Ndd1-Fkh2。我们结果中提到的其他具有潜在协同性的TF对可为未来实验提供新方向。最后，从显著的协同TF对构建了细胞周期的协同TF网络。
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