SARS-CoV-2 Receptors and Entry Genes Are Expressed in the Human Olfactory Neuroepithelium and Brain

  1. Leon Fodoulian
  2. Joël Tuberosa
  3. Daniel Rossier
  4. Madlaina Boillat
  5. Chenda Kan
  6. Véronique Pauli
  7. Kristof Egervari
  8. Johannes A. Lobrinus
  9. Basile N. Landis
  10. Alan Carleton
  11. Ivan Rodriguez

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  1. Version published to 10.1016/j.isci.2020.101839
  2. ScreenIT

    SciScore for 10.1101/2020.03.31.013268: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableFor whole tissue RNA-seq, samples of 4 individuals (3 males and 1 females) were resected during nasal cavity surgeries under general anesthesia.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    For RNA extraction, tissues were placed in RLT Buffer (Qiagen) with beta-mercaptoethanol and lysed with stainless steel balls (5mm diameter, Schieritz and Huenstein AG) using a homogenizer (Big Prep, MB Biomedicals).
    MB Biomedicals
    suggested: None
    Bulk RNA sequencing data analysis: RNA-seq reads were mapped onto the GRCh38 human genome assembly with STAR58 version 2.7.0a using the Ensembl v99 gene annotation file (GTF).
    STAR58
    suggested: None
    Note that this annotation was absent from and did not affect the single-cell RNA-sequencing datasets as it first appeared in the GENCODE release 30 and the Ensembl release 96 of the GRCh38 GTF files.
    GENCODE
    suggested: (GENCODE, RRID:SCR_014966)
    Ensembl
    suggested: (Ensembl, RRID:SCR_002344)
    Differential gene expression analysis between main olfactory epithelial (MOE) biopsies and respiratory epithelial (RE) biopsies was performed using the DESeq260 Bioconductor package version 1.22.2 in R version 3.5.0.
    DESeq260
    suggested: None
    The Approximate Posterior Estimation for GLM coefficients (an adaptive Bayesian shrinkage estimator) implemented in the apeglm62 Bioconductor package version 1.4.2 was used to shrink log2 fold changes.
    apeglm62
    suggested: None
    Single-cell RNA sequencing data analysis of human olfactory epithelial cells: Droplet-based single-nucleus RNA sequencing data analysis of human brain cells: SMART-Seq v4 single-nucleus RNA sequencing data analysis of human brain cells: Data visualization and programming tools: All plots in Figures 1, 2 and 6, as well as in Supplementary Figure 4, were generated using ggplot2 version 3.3.0.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    Other R and Bioconductor packages used for data analysis and plotting include rtracklayer69 version 1.46.0, Matrix version 1.2.18, reshape2 version 1.4.3, data.table version 1.12.8, dplyr version 0.8.5, stringr version 1.4.0, ggrepel version 0.9.0, lemon version 0.4.4, extrafont version 0.17, viridis version 0.5.1, RColorBrewer version 1.1.2, patchwork version 1.0.0 and grid version 3.5.0.
    Bioconductor
    suggested: (Bioconductor, RRID:SCR_006442)
    RColorBrewer
    suggested: (RColorBrewer, RRID:SCR_016697)
    Mouse brain cell database mining: For mouse brain single-cell transcriptomes, the datasets of Zeisel et al.41 (Figure 5A and B) and Sauders et al.42 (Figure 5C) were analyzed from their respective websites: http://mousebrain.org/ and http://dropviz.org/.
    http://mousebrain.org/
    suggested: (Linnarsson lab Mouse Brain Atlas, RRID:SCR_016999)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    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: Please consider improving the rainbow (“jet”) colormap(s) used on pages 9, 11 and 30. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

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

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.03.31.013268v2 on bioRxiv
  4. Version published to 10.1101/2020.03.31.013268v1 on bioRxiv