Gene ontology tree analysis integrated with tendency cluster for deep sequencing database to interpret the mechanism of classical swine fe-ver virus infection
Conference: BIBE 2018 - International Conference on Biological Information and Biomedical Engineering
06/06/2018 - 06/08/2018 at Shanghai, China
Proceedings: BIBE 2018
Pages: 4Language: englishTyp: PDF
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Authors:
Gong, Xiaocheng; Hu, Aoxue; Li, Xuepeng; Wu, Zhongxing; He, Jun (School of Life Science and Technology, Xidian University, Xi’an, Shaanxi 710071, China)
Ning, Pengbo (School of Life Science and Technology, Xidian University, Xi’an, Shaanxi 710071, China & Engineering Research Center of Molecular and Neuro Imaging Ministry of Education, Xi’an, Shaanxi 710071, China)
Abstract:
Classical swine fever (CSF), inducing significant economic losses to the global pig breeding industry, is caused by classical swine cause fever virus (CSFV). Macrophage is one of main targets of CSFV infection. To well understand the key gene responses of macrophages to CSFV Shimen, gene ontology tree analysis integrated with tendency cluster was carried out to investigate database on macrophage transcripts. By using tendency cluster analysis, up- and down-regulated genes in macrophages induced by CSFV Shimen were obtained by comparing CSFV Shimen group with CSFV C and the control group. Gene ontology (GO) and pathway analysis showed that regulation of cell proliferation, cell cycle arrest, inflammatory response, etc., were identified as key GO terms, and TGF-β pathway, PI3K-Akt pathway, p53 signaling pathway, etc., were highlighted as significantly signalling pathway during CSFV Shimen infection. GO tree analysis as a power tool displayed detailed similarities and differences of responding process on macrophages to meet CSFV Shimen and CSFV C infection. Our systematic analysis provides valuable information for better understanding host's molecular pathogenesis of CSFV infection.