Bioinformatic Study Of Genetic Regulation Based On The Integration Of Multi-omics Data

In the post-genomic era, different kinds of omics data provide new view of life system. The flow of genetic information from genome to proteome follows the central dogma, but some complex regulatory mechanisms cannot be fully explained by the central dogma, such as post-translational modification. Therefore, it is necessary to reveal regulatory mechanisms of biosystem which contains various molecules and biological processes by the comparison and integration analysis of multi-omics data. However, studies about multi-omics data integration are lacking, especially the study about the regulatory mechanism based on association analysis between different types of omics data. This thesis aims to uncover the genetic regulation between different layers of biosystem, based on the tools of visualization and analysis of multi-omics data.First, a chromosome-assembled proteome browser (CAPER) was developed for multi-omics data restoration, visualization and analysis. CAPER 1.0 adopts the proteome visualization strategy based on chromosome, which can be used to annotate genome by proteomic data. As an extension of CAPER 1.0, the update version of CAPER (CAPER 2.0) was developed for omics data analysis based on Galaxy workflow system. CAPER system provides a convenient and user-friendly web service for understanding and utilization of multi-omics data.Second, an investigation of transcriptional hierarchy about tissue specificity was performed. DNA methylation and external signal were found to result in TF’s tissue specific expression and activation according to different hierarchies of transcriptional network. For detailed, the strong tissue specific expression pattern of TFs in the top hierarchy level may be a consequence of TF coding genes tissue specific DNA methylation of promoter and enhancer. And tissue specific signals in tissue microenvironment tended to activate TFs in the middle and bottom levels. All the above results showed that signals of tissue specific DNA methylation and signals in organ microenvironment were received by different transcriptional hierarchies. The architecture of transcriptional network may be designed to accept, integrate and transmit tissue specific signals from epigenome and environment.Third, the relevance between gene function and genes chromosomal locations was discussed. In this work, we found that functional related genes were clustered on genome and chromosomal 3D structure, including non-coding genes. Moreover, this phenomenon is evolutionary conserved, and gives a new perspective to understand gene organization on chromosome.Finally, I developed the first online bioinformatic analysis tool specially designed for the research of molecular mechanism of Traditional Chinese Medicine (TCM)-BATMAN-TCM (a Bioinformatic Analysis Tool of Molecular mechANism of Traditional Chinese Medicine), which was primarily based on TCM ingredients’ target prediction and subsequent network pharmacology analyses, aiming to provide clues for the following experimental validation. This online web service fills the blank of multi-constituents medicines therapeutic mechanism research based on network pharmacology.