Identification of key genes in SARS-CoV-2 patients on bioinformatics analysis

Abstract

The COVID-19 pandemic has infected millions of people and overwhelmed many health systems globally. Our study is to identify differentially expressed genes (DEGs) and associated biological processes of COVID-19 using a bioinformatics approach to elucidate their potential pathogenesis. The gene expression profiles of the GSE152075 datasets were originally produced by using the high-throughput Illumina NextSeq 500. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed to identify functional categories and biochemical pathways. GO and KEGG results suggested that several biological pathways such as Fatty acid metabolism and Cilium morphogenesis are mostly involved in the development of COVID-19. Moreover, several genes are critical for virus invasion and adhesion including FLOC, DYNLL1, FBXL3, and FBXW11 and show significant differences in COVID-19 patients. Thus, our study provides further insights into the underlying pathogenesis of COVID-19.

Identification of key genes and pathways in the hPSC-derived lungs infected by the SARS-CoV-2

“…COVID-19, a huge threaten caused by SARS-CoV-2, has affected a large number of people and the death toll has reached hundreds of thousands worldwide 15,17,18 . The trachea which connects the upper airway to the lung becomes a high virus contact zone.…”

“…The raw microarray data between SARS-CoV-2 positive samples and negative controls were subsequently conducted by R script as previously described [15][16][17] . We set a classical t test to identify DEGs with P<.01 and fold change ≥1.5 as being statistically signi cant.…”

Identification of biomarkers and candidate inhibitors for multiple myeloma

“…The dataset GSE153626 containing WT samples and VQ mice samples was analyzed and conducted by R script as described previously 12, 13 . We used a classical t test to identify DEGs with P<.01 and fold change ≥1.5 as being statistically significant.…”

Identification of the difference of neutrophils in different locations in RA patients

“…The dataset GSE154474 that includes Neutrophils from paired peripheral blood and synovial uid was analyzed and conducted by R script 12,13 . We performed a classical t test to identify DEGs with P < .01 and fold change ≥ 1.5 as being statistically signi cant.…”

“…To further identify the biological roles and potential mechanisms of the DEGs of neutrophils from blood and synovial uid, we performed KEGG pathway and GO categories enrichment analysis (Supplemental Table S1) 12 . The KEGG pathway (http://www.genome.jp/kegg/) includes curated sets of genes that are to understand the molecular interaction, reaction and relation networks.…”