Research of Dioxins Toxicogenomics with Biological Network Analysis

• Main Authors: Guo-Xin Wang, 王國信
• Other Authors: Sher Singh
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/22137002803353127472

碩士 === 國立臺灣師範大學 === 生命科學研究所 === 101 === To investigate the important genes/receptors, we were analyzing toxicogenomics data of 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) in human and visualizing biological networks to calculate the nodal centrality (including: betweenness centrality, closenness centrality and degree centrality) describing the network topology. More than 70 chemicals have been found in dioxin family, and TCDD is the chemical compound that has the greatest number of gene-interactions. Retrieving TCDD toxicogenomics data from Comparative Toxicogenomics Database (CTD). Using Gene Set Enrichment Analysis (GSEA) method to analyze gene sets by pathways, GeneOntology (GO) and networks. To analyze array data of TCDD effect of human using Affymetrix GeneChip Human Genome U133 Plus 2.0 platform (HG-U133_Plus_2), we use CLC genomics workbench software to execute statistical analysis. After mining feature ids at false discovery rate (FDR) p-value less than 0.05, we add annotations of their gene symbols. The visualization software Cytoscape could construct biological network with gene list, and its plugin CentiScaPe can compute specific nodal centrality parameters in the biological networks analyze. The curated interactions between TCDD and genes/interactions were obtained from CTD, and 2234 unique human genes/proteins were found. The GO and pathways of these 2234 genes/proteins were fully analyzed. The top 20 genes/proteins may serve as molecular biomarkers of TCDD toxicity. The top 10 diseases included pathologic processes, female urogenital, stomach, skin, adnexal and ovarian disease. The high nodal centrality nodes, HDAC1, E2F1 and SP1 are retrieved by CentiScaPe from TCDD related toxicogenomics data(E-MEXP-2817, E-MEXP-2574, E-MEXP-2458 and E-GEOD-35034). Someday, these results could be biomarks using in biosensor system to detect chemicals in human body.