Mapping Molecular Gene Signatures Among Respiratory Viruses Based on Large-Scale and Genome-wide Transcriptomics Analysis

  1. Thomas Smith
  2. Mohammed A. Rohaim
  3. Muhammad Munir

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Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging RNA virus causing COVID-19 disease across the globe. SARS-CoV-2 infected patients exhibit acute respiratory distress syndrome which can be compounded by endemic respiratory viruses and thus highlighting the need to understand the genetic bases of clinical outcome under multiple respiratory infections. In this study, 42 individual datasets and a multi-parametric based selected list of over 12,000 genes against five medically important respiratory viruses (SARS-CoV-2, SARS-CoV-1, influenza A, respiratory syncytial virus (RSV) and rhinovirus were collected and analysed in an attempt to understand differentially regulated gene patterns and to cast genetic markers of individual and multiple co-infections. While a certain cohort of virus-specific genes were regulated (negatively and positively), notably results revealed a greatest correlation among gene regulation by SARS-CoV-2 and RSV. Furthermore, out of analysed genes, the MAP2K5 and NFKBIL1 were specifically and highly upregulated in SARS-CoV-2 infection in vivo or in vitro. In contrast, several genes including GPBAR1 and SC5DL were specifically downregulated in SARS-CoV-2 datasets. Additionally, we catalogued a set of genes that were conserved or differentially regulated across all the respiratory viruses. These finding provide foundational and genome-wide data to gauge the markers of respiratory viral infections individually and under co-infection.

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    SciScore for 10.1101/2021.10.17.464720: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Gene Expression Omnibus (GEO) and PubMed datasets were used to search for literature that contained data relating to upregulated and downregulated genes in response to infection with respiratory viruses (SARS-CoV-2, influenza, SARS-CoV-1, RSV and rhinovirus).
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    On GEO, the terms “(“Severe acute respiratory syndrome coronavirus 2“[Organism] OR SARS-CoV-2[All Fields]) AND “Homo sapiens“” were used whereas when searching on PubMed, the terms “(SARS-CoV-AND (Transcriptome)” were used.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Included Datasets and Data Synchronisation: The collected datasets from various sources were compiled into one set of data using Microsoft Excel program.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    Using the GraphPad Prism 9.0.0 software, a scatter bar graph was generated using the overall ranking score for each gene of each virus.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • No funding statement was detected.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  2. Version published to 10.1101/2021.10.17.464720 on bioRxiv