sgDI-tector: defective interfering viral genome bioinformatics for detection of coronavirus subgenomic RNAs

  1. Andrea Di Gioacchino
  2. Rachel Legendre
  3. Yannis Rahou
  4. Valérie Najburg
  5. Pierre Charneau
  6. Benjamin D. Greenbaum
  7. Frédéric Tangy
  8. Sylvie van der Werf
  9. Simona Cocco
  10. Anastassia V. Komarova

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Abstract

Coronavirus RNA-dependent RNA polymerases produce subgenomic RNAs (sgRNAs) that encode viral structural and accessory proteins. User-friendly bioinformatic tools to detect and quantify sgRNA production are urgently needed to study the growing number of next-generation sequencing (NGS) data of SARS-CoV-2. We introduced sgDI-tector to identify and quantify sgRNA in SARS-CoV-2 NGS data. sgDI-tector allowed detection of sgRNA without initial knowledge of the transcription-regulatory sequences. We produced NGS data and successfully detected the nested set of sgRNAs with the ranking M > ORF3a > N>ORF6 > ORF7a > ORF8 > S > E>ORF7b. We also compared the level of sgRNA production with other types of viral RNA products such as defective interfering viral genomes.

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  1. Version published to 10.1261/rna.078969.121
  2. ScreenIT

    SciScore for 10.1101/2021.11.30.470527: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    RandomizationTherefore, we used a different approach: firstly, sgDI-tector computes the probability of a random sub-sequence of the viral genome to have a sub-sequence of length L (putative TRS) which appears also in the final part of the leader sequence.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line AuthenticationContamination: The absence of mycoplasma was regularly checked by RT-PCR in all cell lines.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    The efficiency of virus amplification was evaluated by titrating the supernatant on Vero-E6 cells, in a standard plaque assay adapted from Matrosovich et al. [Matrosovich et al., 2006].
    Vero-E6
    suggested: None
    For SARS-CoV-2 infection ST-CHACE-2 cells were seeded into polylysine-coated (SIGMA) T150 flasks 1 day before infection (20×106 cells/flask).
    ST-CHACE-2
    suggested: None
    Software and Algorithms
    SentencesResources
    Quality control was performed on an Agilent Bioanalyzer.
    Agilent Bioanalyzer
    suggested: None
    Bowtie version 2.1.0, with default parameters, was used for alignment on the reference genome (hCoV-19/France/GES-1973/2020, GI-SAID accession Id: EPI ISL 414631).
    Bowtie
    suggested: (Bowtie, RRID:SCR_005476)
    SARS-CoV-2 genome coverages were computed with bedtools genomecov for each strand.
    bedtools
    suggested: (BEDTools, RRID:SCR_006646)
    Reactions were performed in a final volume of 20 µL in the presence of 60 nM U3dc4-specific forward (5’-CCTTCCCAGGTAACAAAC) and reverse (5’-GTCTCAGTCCAACATTTTG) primers; or N-specific forward (5’-TAAAGGTTTATACCTTCCCA) or reverse (5’-CGTTCTCCATTCTG-GTTA) primers; or GAPDH forward (5’-CACATGGCCTCCAAGGAG-TAA) and reverse (5’-TGAGGGTCTCTCTCTTCCTCTTGT) primers. sgDI-tector pipeline: from NGS data to sgRNA detection: When sgDI-tector is run, it firstly calls DI-tector [Beauclair et al., 2018] (here used in version 0.6) with default parameters (using bwa v0.7.17, bed-tools v2.17.0 and samtools v1.9) to detect SARS-CoV-2 DVGs.
    DI-tector
    suggested: None
    samtools
    suggested: (SAMTOOLS, RRID:SCR_002105)
    The data collected and used for this work have been deposited in NCBI’s Gene Expression Omnibus [Edgar et al., 2002] and are accessible through GEO Series accession number GSE180632, at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE180632.
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)

    Results from OddPub: Thank you for sharing your code and 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.
    • 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.

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

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  3. Version published to 10.1101/2021.11.30.470527v1 on bioRxiv