Study on Pathological Mechanism of Pneumonia Infected by Coronavirus Based on Time-Series Gene Co-expression Network Analysis

Abstract

Recently, the epidemic of COVID-19 infection broke out in Wuhan, China. To explore the pathological mechanism of pneumonia infected by coronavirus, we built a bioinformatics pipeline based on time-series gene co-expression network analysis to analyze the gene expression profile of lung cells in mice infected by SARS-Cov (GSE19137). In this study, Pearson correlation analysis was performed to construct a gene co-expression network. Time-ordered gene network modules were digged out by BFS algorithm. PageRank algorithm was used to explore HUB genes related to pneumonia infected by coronavirus. Based on the information we got, we think that cell lines infected by coronavirus might go through 5 stages, and 10 HUB genes(AKT1, CD68, CTSS, FCGR3A, HSPA8, PTPRC, UBC, VCP, PRPF31, ITPKB) might play a key role in coronavirus infection. This might provide some hints for coronavirus related research.