Comparative analysis of primer-probe sets for the laboratory confirmation of SARS-CoV-2

  1. Yu Jin Jung
  2. Gun-Soo Park
  3. Jun Hye Moon
  4. Keunbon Ku
  5. Seung-Hwa Beak
  6. Seil Kim
  7. Edmond Changkyun Park
  8. Daeui Park
  9. Jong-Hwan Lee
  10. Cheol Woo Byeon
  11. Joong Jin Lee
  12. Jin-Soo Maeng
  13. Seong Jun Kim
  14. Seung Il Kim
  15. Bum-Tae Kim
  16. Min Jun Lee
  17. Hong Gi Kim

Reviewed by

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

Log in to save this article

Abstract

Coronavirus disease 2019 (COVID-19) is newly emerging human infectious diseases, which is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2, also previously known as 2019-nCoV). Within two months of the outbreak, more than 80,000 cases of COVID-19 have been confirmed worldwide. Since the human to human transmission occurred easily and the human infection is rapidly increasing, the sensitive and early diagnosis is essential to prevent the global outbreak. Recently, World Health Organization (WHO) announced various primer and probe sets for SARS-CoV-2 previously developed in China, Germany, Hong Kong, Japan, Thailand, and USA. In this study, we compared the ability to detect SARS-CoV-2 RNA among the seven primer-probe sets for N gene and the three primer-probe sets for Orf1 gene. The result of the comparative analysis represented that the ‘2019-nCoV_N2, N3’ of USA and the ‘ORF1ab’ of China are the most sensitive primer-probe sets for N and Orf1 genes, respectively. Therefore, the appropriate combination from ORF1ab (China), 2019-nCoV_N2, N3 (USA), and NIID_2019-nCOV_N (Japan) sets should be selected for the sensitive and reliable laboratory confirmation of SARS-CoV-2.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.02.25.964775: (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
    African green monkey kidney Vero cells (ATCC CCL-81) were infected with a clinical isolate SARS-CoV-2 (BetaCoV/Korea/KCDC03/2020 provided from Korea CDC).
    Vero
    suggested: None
    Software and Algorithms
    SentencesResources
    South Korea) and T7 terminator primer (5’ – GCTAGTTATTGCTCAGCGG – 3’, Macrogen) with AccuPower® PCR PreMix (-dye) kit (Bioneer Inc., South Korea).
    Macrogen
    suggested: (Macrogen, RRID:SCR_014454)
    PCR product was then used as in vitro transcription template using MEGAscript™ T7 Transcription Kit (Invitrogen Inc., CA, USA).
    MEGAscript™
    suggested: None

    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:
    • No conflict of interest statement was detected. If there are no conflicts, we encourage authors to explicit state so.
    • 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.

  2. Version published to 10.1101/2020.02.25.964775 on bioRxiv