A Genome Epidemiological Study of SARS-CoV-2 Introduction into Japan

  1. Tsuyoshi Sekizuka
  2. Kentaro Itokawa
  3. Masanori Hashino
  4. Tetsuro Kawano-Sugaya
  5. Rina Tanaka
  6. Koji Yatsu
  7. Asami Ohnishi
  8. Keiko Goto
  9. Hiroyuki Tsukagoshi
  10. Hayato Ehara
  11. Kenji Sadamasu
  12. Masakatsu Taira
  13. Shinichiro Shibata
  14. Ryohei Nomoto
  15. Satoshi Hiroi
  16. Miho Toho
  17. Tomoe Shimada
  18. Tamano Matsui
  19. Tomimasa Sunagawa
  20. Hajime Kamiya
  21. Yuichiro Yahata
  22. Takuya Yamagishi
  23. Motoi Suzuki
  24. Takaji Wakita
  25. Makoto Kuroda

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Abstract

This study aimed to evaluate the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome sequences from COVID-19 cases and to characterize their genealogical networks to demonstrate possible routes of spread in Japan. We found that there were at least two distinct SARS-CoV-2 introductions into Japan, initially from China and subsequently from other countries, including Europe. Our findings can help understand how SARS-CoV-2 entered Japan and contribute to increased knowledge of SARS-CoV-2 in Asia and its association with implemented stay-at-home/shelter-in-place/self-restraint/lockdown measures. This study suggested that it is necessary to formulate a more efficient containment strategy using real-time genome surveillance to support epidemiological field investigations in order to highlight potential infection linkages and mitigate the next wave of COVID-19 in Japan.

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  1. Version published to 10.1128/msphere.00786-20
  2. ScreenIT

    SciScore for 10.1101/2020.07.01.20143958: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Ethical approval and consent to participate: The study protocol was approved by the National Institute of Infectious Diseases in Japan (Approval No. 1091).
    IACUC: The ethical committee waived the need for written consent since the study involved the viral genome sequencing.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    These mapped reads of SARS-CoV-2 sequences were assembled using A5-miseq v.
    A5-miseq
    suggested: (A5-miseq, RRID:SCR_012148)
    Comparative genome sequence and SNV analyses: The nearly full-length genome sequence (≥ 29 kb) of SARS-CoV-2 was retrieved from the GISAID EpiCoV database in 28 April 2020, followed by multiple alignment using MAFFT v7.222 19.
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    Network graph visualization: We had applied various visualization software for network graph visualization such as Network, PopART, TCS, and Cytoscape.
    Cytoscape
    suggested: (Cytoscape, RRID:SCR_003032)
    Thus, we developed Haplotype Explorer software to visualise the spatiotemporal pattern of SARS-CoV-2 infections based on network graphs (https://github.com/TKSjp/HaplotypeExplorer).
    Haplotype Explorer
    suggested: (Genetic Analysis Software, RRID:SCR_013155)

    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: Please consider improving the rainbow (“jet”) colormap(s) used on pages 14 and 15. 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 10.1101/2020.07.01.20143958v1 on medRxiv