Computational Reconstruction of Transcriptional Relationships from ChIP-Chip Data

• Published in: IEEE/ACM Transactions on Computational Biology and Bioinformatics Vol. 10; no. 2; pp. 300 - 307
• Main Authors: Le, Ngoc Tu, Ho, Tu Bao, Ho, Bich Hai
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.03.2013; Institute of Electrical and Electronics Engineers (IEEE); The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Bayes Theorem; Bayesian methods; Bayesian network; Bioinformatics; ChIP-Chip data; Chromatin; Chromatin Assembly and Disassembly; Chromatin Assembly and Disassembly - genetics; Chromatin Immunoprecipitation; chromatin remodeling complex; Computational Biology; Computational Biology - methods; Data models; Gene Regulatory Networks; Genes; Genomics; histone modification; Histones; Histones - chemistry; Histones - genetics; Histones - metabolism; Machinery; Models, Genetic; nucleosome positioning; Oligonucleotide Array Sequence Analysis; Proteins; Saccharomyces cerevisiae; Saccharomyces cerevisiae - genetics; Saccharomyces cerevisiae Proteins; Saccharomyces cerevisiae Proteins - genetics; Stability analysis; Transcription Factors; Transcription Factors - genetics; Transcription, Genetic; Transcriptional relationship
• ISSN: 1545-5963; 1557-9964; 1557-9964
• DOI: 10.1109/TCBB.2012.102

Eukaryotic gene transcription is a complex process, which requires the orchestrated recruitment of a large number of proteins, such as sequence-specific DNA binding factors, chromatin remodelers and modifiers, and general transcription machinery, to regulatory regions. Previous works have shown that these regulatory proteins favor specific organizational theme along promoters. Details about how they cooperatively regulate transcriptional process, however, remain unclear. We developed a method to reconstruct a Bayesian network (BN) model representing functional relationships among various transcriptional components. The positive/negative influence between these components was measured from protein binding and nucleosome occupancy data and embedded into the model. Application on S.cerevisiae ChIP-Chip data showed that the proposed method can recover confirmed relationships, such as Isw1-Pol II, TFIIH-Pol II, TFIIB-TBP, Pol II-H3K36Me3, H3K4Me3-H3K14Ac, etc. Moreover, it can distinguish colocating components from functionally related ones. Novel relationships, e.g., ones between Mediator and chromatin remodeling complexes (CRCs), and the combinatorial regulation of Pol II recruitment and activity by CRCs and general transcription factors (GTFs), were also suggested. Conclusion: protein binding events during transcription positively influence each other. Among contributing components, GTFs and CRCs play pivotal roles in transcriptional regulation. These findings provide insights into the regulatory mechanism.