Covid-19 genomic analysis reveals clusters of emerging sublineages within the delta variant

  1. Evans K. Rono

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

The emerging SARS-CoV-2 variants may potentially have enhanced transmissibility and virulence of the virus, and impacts on performance of diagnostic tools and efficacy of vaccines. Genomic surveillance provides an opportunity to detect and characterize new mutations early enough for effective deployment of control strategies. Here, genomic data from Germany and United Kingdom were examined for genetic diversity by assessing gene mutations and inferring phylogeny, and simplifying genomic data workflow for faster visualization and interpretation. Delta variant sublineages were grouped into seven distinct clusters of spike mutations located in N-terminal domain of S1 region (T95I, D138H, *D142G, Y145H and A222V) and S2 region (T719I and *N950D). The most predominant cluster was T95I mutation, with the highest frequencies (71.1% - 83.9%) in Wales, England and Scotland, and the least frequencies (8.9% - 12.1%) in Germany. Two mutations, *D142G and *N950D here described as *reverse mutations and T719I mutation, were largely unique to Germany. In a month, frequencies of D142G had increased from 55.6% to 67.8 % in Germany. Additionally, a cluster of D142G+T719I/T mutation went up from 27.7% to 34.1%, while a T95I+ D142G+N950D/N cluster rose from 19.2% to 26.2%. Although, two distinct clusters of T95I+D138H (2.6% - 3.8%) and T95I+Y145H+A222V (2.5% - 8.5%) mutations were present in all the countries, they were most predominant in Wales and Scotland respectively. Results suggest divergent evolutionary trajectories between the clusters of T95I mutation and those of D142G mutation. These findings provide insights into underlying dynamics of evolution of the delta variant. Future studies may evaluate the epidemiological and biological implications of these sublineages.

Article activity feed

  1. Version published to 10.1101/2021.10.08.463334v2 on bioRxiv
  2. ScreenIT

    SciScore for 10.1101/2021.10.08.463334: (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.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    No key resources detected.

    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: 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.

    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 10.1101/2021.10.08.463334v1 on bioRxiv