The 2019-new coronavirus epidemic: evidence for virus evolution

This article has been Reviewed by the following groups

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Abstract

There is concern about a new coronavirus, the 2019-nCoV, as a global public health threat. In this article, we provide a preliminary evolutionary and molecular epidemiological analysis of this new virus. A phylogenetic tree has been built using the 15 available whole genome sequence of 2019-nCoV and 12 whole genome sequences highly similar sequences available in gene bank (5 from SARS, 2 from MERS and 5 from Bat SARS-like Coronavirus). FUBAR analysis shows that the Nucleocapsid and the Spike Glycoprotein has some sites under positive pressure while homology modelling helped to explain some molecular and structural differences between the viruses. The phylogenetic tree showed that 2019.nCoV significantly clustered with Bat SARS-like Coronavirus sequence isolated in 2015, whereas structural analysis revealed mutation in S and nucleocapsid proteins. From these results, 2019nCoV could be considered a coronavirus distinct from SARS virus, probably transmitted from bats or another host where mutations conferred upon it the ability to infect humans.

Article activity feed

  1. SciScore for 10.1101/2020.01.24.915157: (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.

    Table 2: Resources

    No key resources detected.


    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.
    • No funding statement was detected.
    • 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.