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Bioinformatics analysis of high-throughput sequencing to identify key genes and signaling pathways in vero E6 cells infected by SARS-CoV-2
Respirology ; 26(SUPPL 3):18-19, 2021.
Article in English | EMBASE | ID: covidwho-1583447
ABSTRACT

Background:

In 2020, the coronavirus disease 2019 began spreading widely across the world. We aim to study the biological changes of SARS-CoV-2 infected Vero cells using high-throughput sequencing data, which will be helpful for vaccine development and drug screening.

Methods:

The data GSE153940 was obtained from the Gene Expression Omnibus database. R software was used to screen out differentially expressed genes and perform Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. The protein-protein interaction network was built by STRING. Cytoscape 3.7.2 was applied for the visualization of the protein-protein interaction network and the identification of the hub genes. GraphPad Prism 8.4.3 was used to perform the statistical analysis to verify the obtained central genes.

Results:

A total of 3640 differentially expressed genes were obtained. The most significant enrichment items of Gene Ontology in the biological process, cellular component, and molecular function were the regulation of mRNA metabolic process, organelle inner membrane, and cadherin binding respectively. Ten enrichment pathways were identified by the Kyoto Encyclopedia of Genes and Genomes analyses. A protein-protein interaction network with 328 nodes and 498 edges was established. Six hub genes were screened out, among which four genes (MRPS7, DAP3, CHCHD1 and MRPL3) were confirmed to be statistically significant.

Conclusions:

Our results suggest that mitochondrial activity has a significant role in the process of SARS-CoV-2 infecting Vero E6 cells. Further experimental studies are needed to obtain abundant data to verify the predicted results of the bioinformatics analysis.
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Full text: Available Collection: Databases of international organizations Database: EMBASE Language: English Journal: Respirology Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: EMBASE Language: English Journal: Respirology Year: 2021 Document Type: Article