COVID-19 Transcriptomic Atlas: A Comprehensive Analysis of COVID-19 Related Transcriptomics Datasets

Abstract

Background: To develop anti-viral drugs and vaccines, it is crucial to understand the molecular basis and pathology of COVID-19. An increase in research output is required to generate data and results at a faster rate, therefore bioinformatics plays a crucial role in COVID-19 research. There is an abundance of transcriptomic data from studies carried out on COVID-19, however, their use is limited by the confounding factors pertaining to each study. The reanalysis of all these datasets in a unified approach should help in understanding the molecular basis of COVID-19. This should allow for the identification of COVID-19 biomarkers expressed in patients and the presence of markers specific to disease severity and condition.Aim: In this study, we aim to use the multiple publicly available transcriptomic datasets retrieved from the Gene Expression Omnibus (GEO) database to identify consistently differential expressed genes in different tissues and clinical settings.Materials and Methods: A list of datasets was generated from NCBI’s GEO using the GEOmetadb package through R software. Search keywords included SARS-COV-2 and COVID-19. Datasets in human tissues containing more than ten samples were selected for this study. Differentially expressed genes (DEGs) in each dataset were identified. Then the common DEGs between different datasets, conditions, tissues and clinical settings were shortlisted.Results: Using a unified approach, we were able to identify common DEGs based on the disease conditions, samples source and clinical settings. For each indication, a different set of genes have been identified, revealing that a multitude of factors play a role in the level of gene expression.Conclusion: Unified reanalysis of publically available transcriptomic data showed promising potential in identifying core targets that can explain the molecular pathology and be used as biomarkers for COVID-19.

Severe COVID-19 Shares a Common Neutrophil Activation Signature with Other Acute Inflammatory States

“…The present study represents a follow-up of a recent report from our group [ 21 ] in which we performed an integrative analysis of transcriptional alterations in respiratory airways and peripheral blood leukocytes. This approach successfully developed by our and other groups [ 22 , 23 , 24 ] demonstrated multi-tissue systemic effects of SARS-CoV-2 infection, providing insightful mechanisms of SARS-CoV-2 pathology and cellular targets for therapy [ 23 ].…”

Impact of SARS-CoV-2 on Host Factors Involved in Mental Disorders

“…We previously noted that increased TLR3 signaling leads to reduced DISC1 expression and aberrant neurogenesis. A recent transcriptomics study of publicly available datasets demonstrated that DISC1 is downregulated by COVID-19 ( Alqutami et al, 2021 ). Though the exact role that DISC1 plays in complex mental disorders is unclear, DISC1 is an important component in the formation of the immune synapse.…”

“…DISC1 and the DISC1 pathway genes like PDE4B and NRXN1 are implicated in several mental health disorders ( Millar et al, 2007 ; Korth, 2009 ; Hu et al, 2019 ). PDE4B is found in the DISC1 interactome, and differential expression of PDE4B has also been noted in relation to COVID-19 infection ( Alqutami et al, 2021 ). PDE4B has been shown to regulate cytokine signaling pathways ( Lugnier et al, 2021 ; Moolamalla et al, 2021 ).…”

Systematic analysis of alternative splicing in time course data using Spycone

“…A previous study found that knock down of MAP3K9 reduced SARS-CoV-2 virus replication [38]. DCLK2 is differentially expressed in SARS-CoV-2 patients [39]. AURKC would be an interesting candidate to investigate for its role in SARS-CoV-2 infection.…”