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Identification and classification of differentially expressed genes reveal potential molecular signature associated with SARS-CoV-2 infection in lung adenocarcinomal cells.


ABSTRACT: Genomic techniques such as next-generation sequencing and microarrays have facilitated the identification and classification of molecular signatures inherent in cells upon viral infection, for possible therapeutic targets. Therefore, in this study, we performed a differential gene expression analysis, pathway enrichment analysis, and gene ontology on RNAseq data obtained from SARS-CoV-2 infected A549 cells. Differential expression analysis revealed that 753 genes were up-regulated while 746 down-regulated. SNORA81, OAS2, SYCP2, LOC100506985, and SNORD35B are the top 5 upregulated genes upon SARS-Cov-2 infection. Expectedly, these genes have been implicated in the immune response to viral assaults. In the Ontology of protein classification, a high percentage of the genes are classified as Gene-specific transcriptional regulator, metabolite interconversion enzyme, and Protein modifying enzymes. Twenty pathways with P-value lower than 0.05 were enriched in the up-regulated genes while 18 pathways are enriched in the down-regulated DEGs. The toll-like receptor signalling pathway is one of the major pathways enriched. This pathway plays an important role in the innate immune system by identifying the pathogen-associated molecular signature emanating from various microorganisms. Taken together, our results present a novel understanding of genes and corresponding pathways upon SARS-Cov-2 infection, and could facilitate the identification of novel therapeutic targets and biomarkers in the treatment of COVID-19.

SUBMITTER: Soremekun OS 

PROVIDER: S-EPMC7308782 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identification and classification of differentially expressed genes reveal potential molecular signature associated with SARS-CoV-2 infection in lung adenocarcinomal cells.

Soremekun Opeyemi S OS   Omolabi Kehinde F KF   Soliman Mahmoud E S MES  

Informatics in medicine unlocked 20200623


Genomic techniques such as next-generation sequencing and microarrays have facilitated the identification and classification of molecular signatures inherent in cells upon viral infection, for possible therapeutic targets. Therefore, in this study, we performed a differential gene expression analysis, pathway enrichment analysis, and gene ontology on RNAseq data obtained from SARS-CoV-2 infected A549 cells. Differential expression analysis revealed that 753 genes were up-regulated while 746 down  ...[more]