Computational Reconstruction of Transcriptional Relationships from ChIP-Chip Data
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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Post-translational modifications (PTMs) of his tone proteins play critical roles in establishing functionally separated domains on chromatin and regulating important biological processes, such as transcription. These modifications often act in cooperative manner, forming complicated "histone codes". Elucidation of functional relationships among them will, therefore, significantly increase our understanding of cell differentiation, development, and cancer pathogenesis. Biological evidence has shown that nucleosome positioning can provide invaluable information about interactive effects of PTMs. However, to our knowledge, none of previous works has exploited this information in the reconstruction of his tone modification networks. We propose a computational approach based on Bayesian network to reconstruct a network representing functional relationships of his tone modifications. Our approach employed the search-and-score method to infer the network structure using interactive information of his tone modifications, which is measured by the correlation between each modification with nucleosome positioning. When applied on human CD4+ T cell ChIP-Seq dataset, containing 38 different his tone modifications and binding information of three other proteins, H2A.Z, PolII and CTCF, our method not only outperformed previous approaches in recovering known relationships but also suggested many new ones, confirming its validity and efficiency. Our unbiased method for inferring the network structure can also be applied to reconstruct interaction networks of other epigenetic factors.