沈林琥Sher Singh王國信Guo-Xin Wang2019-09-052018-8-222019-09-052013http://etds.lib.ntnu.edu.tw/cgi-bin/gs32/gsweb.cgi?o=dstdcdr&s=id=%22GN060043055S%22.&%22.id.&amp;http://rportal.lib.ntnu.edu.tw:80/handle/20.500.12235/104061戴奧辛類(Dioxins)的相關化合物目前已知共有76個，其中以四氯戴奧辛(2,3,7,8-Tetrachlorodibenzo-p-dioxin, TCDD)是最常用來作為研究戴奧辛毒性的化學物質，同時也有最多相關的基因-反應數。為了探討重要的基因/受體(Receptor)，需要分析TCDD相關的各項研究數據，尤其是毒理基因體方面的資料，再輔以視覺化生物網絡及統計數據的計算；本篇研究以Gene Set Enrichment Analysis (GSEA)分析TCDD相關的毒理基因體學數據，包含有基因本體論(GeneOntology, GO)及相關途徑的分析，另一方面搜集相關微陣列晶片(microarray)的資料，其後篩選出FDR p-value< 0.05的基因列表，並利用cytoscape視覺化生物網絡(Biological Networks)及搭配統計中間度指標(包含：連接中間度指標、近距中間度指標、參與中間度指標)計算加以分析。 完成上述分析後，我們從毒理基因體資料分析中了解TCDD的毒理基因體相關機轉，得到TCDD影響人類的2234個不重複基因，進一步找出TCDD對於人類生理上影響的廣泛性及最有可能影響的基因及疾病；在微陣列晶片資料的分析中，藉著視覺化及統計數據的分析，由統計數據的不同得以確切的比較出對於不同基因或受體的作用差異，找出了像是HDAC1、E2F1、SP1這些與過往文獻中不盡相同的結果，這些研究結果再經由進一步的分析比對後，也可能在之後的相關毒理及病理研究上，作為可用的生物標的。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.戴奧辛生物網絡中間度指標近距中間度指標連接中間度指標參與中間度指標DioxinsBiological NetworksNodal CentralityClosenness CentralityDegree CentralityBetweenness Centrality