Whole-genome sequencing and de novo assembly of a 2019 novel coronavirus (SARS-CoV-2) strain isolated in Vietnam

  1. Le Tung Lam
  2. Nguyen Trung Hieu
  3. Nguyen Hong Trang
  4. Ho Thi Thuong
  5. Tran Huyen Linh
  6. Luu Thuy Tien
  7. Nguyen Thi Ngoc Thao
  8. Huynh Thi Kim Loan
  9. Pham Duy Quang
  10. Luong Chan Quang
  11. Cao Minh Thang
  12. Nguyen Vu Thuong
  13. Hoang Ha
  14. Chu Hoang Ha
  15. Phan Trong Lan
  16. Truong Nam Hai

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Abstract

The pandemic COVID-19 caused by the virus SARS-CoV-2 has devastated countries worldwide, infecting more than 4.5 million people and leading to more than 300,000 deaths as of May 16th, 2020. Whole-genome sequencing (WGS) is an effective tool to monitor emerging strains and provide information for intervention, thus help to inform outbreak control decisions. Here, we reported the first effort to sequence and de novo assemble the whole genome of SARS-CoV-2 using PacBio’s SMRT sequencing technology in Vietnam. We also presented the annotation results and a brief analysis of the variants found in our SARS-CoV-2 strain, which was isolated from a Vietnamese patient. The sequencing was successfully completed and de novo assembled in less than 30 hours, resulting in one contig with no gap and a length of 29,766 bp. All detected variants as compared to the NCBI reference were highly accurate, as confirmed by Sanger sequencing. The results have shown the potential of long read sequencing to provide high quality WGS data to support public health responses and advance understanding of this and future pandemics.

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  1. Version published to 10.15625/1811-4989/18/2/15082
  2. ScreenIT

    SciScore for 10.1101/2020.06.12.149377: (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 variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Virus cultivation: The Vero E6 cell lines were investigated for their susceptibility to SARS-CoV-2 and used for virus isolation in this study.
    Vero E6
    suggested: RRID:CVCL_XD71)
    Software and Algorithms
    SentencesResources
    High quality sequence data was proofread and generated by PacBio’s circular consensus sequencing (CCS), then de novo assembled using Canu software v2.0 (Koren et al., 2017), and the quality of the assembly was checked by using Quast software v5.0.2 (Gurevich et al., 2013).
    Canu
    suggested: (Canu, RRID:SCR_015880)
    Quast
    suggested: (QUAST, RRID:SCR_001228)
    Then, the sequenced was aligned with multiple sequences retrieved from GISAID and the reference sequence MN908947v3 from NCBI (Wu et al., 2020) using Clustal Omega v.
    Clustal Omega
    suggested: (Clustal Omega, RRID:SCR_001591)
    The variants were visualized by using Geneious program v2020.1.2 (Biomatters, Auckland, New Zealand) and listed out manually.
    Geneious
    suggested: (Geneious, RRID:SCR_010519)

    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: 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.

    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 10.1101/2020.06.12.149377v1 on bioRxiv