Literature DB >> 28243843

Dynamic gene expression analysis in a H1N1 influenza virus mouse pneumonia model.

Yanyan Bao1, Yingjie Gao1, Yujing Shi1, Xiaolan Cui2.   

Abstract

H1N1, a major pathogenic subtype of influenza A virus, causes a respiratory infection in humans and livestock that can range from a mild infection to more severe pneumonia associated with acute respiratory distress syndrome. Understanding the dynamic changes in the genome and the related functional changes induced by H1N1 influenza virus infection is essential to elucidating the pathogenesis of this virus and thereby determining strategies to prevent future outbreaks. In this study, we filtered the significantly expressed genes in mouse pneumonia using mRNA microarray analysis. Using STC analysis, seven significant gene clusters were revealed, and using STC-GO analysis, we explored the significant functions of these seven gene clusters. The results revealed GOs related to H1N1 virus-induced inflammatory and immune functions, including innate immune response, inflammatory response, specific immune response, and cellular response to interferon-beta. Furthermore, the dynamic regulation relationships of the key genes in mouse pneumonia were revealed by dynamic gene network analysis, and the most important genes were filtered, including Dhx58, Cxcl10, Cxcl11, Zbp1, Ifit1, Ifih1, Trim25, Mx2, Oas2, Cd274, Irgm1, and Irf7. These results suggested that during mouse pneumonia, changes in the expression of gene clusters and the complex interactions among genes lead to significant changes in function. Dynamic gene expression analysis revealed key genes that performed important functions. These results are a prelude to advancements in mouse H1N1 influenza virus infection biology, as well as the use of mice as a model organism for human H1N1 influenza virus infection studies.

Entities:  

Keywords:  Bioinformatics; H1N1; Influenza A virus; Pneumonia; STC analysis

Mesh:

Substances:

Year:  2017        PMID: 28243843     DOI: 10.1007/s11262-017-1438-y

Source DB:  PubMed          Journal:  Virus Genes        ISSN: 0920-8569            Impact factor:   2.332


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