Genomic Diversity of the SARS-CoV-2 in Turkey and the Impact of Virus Genome Mutations on Clinical Outcomes

  1. Ilker Karacan
  2. Tugba Kizilboga Akgun
  3. Nihat Bugra Agaoglu
  4. Payam Zolfagharian
  5. Mehtap Aydin
  6. Gizem Alkurt
  7. Jale Yildiz
  8. Betsi Kose
  9. Nisan Denizce Can
  10. Ayse Serra Ozel
  11. Nilsun Altunal
  12. Arzu Irvem
  13. Yasemin Kendir Demirkol
  14. Ozlem Akgun Dogan
  15. Levent Doganay
  16. Gizem Dinler Doganay

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Abstract

COVID-19 is a viral respiratory disease caused by SARS-CoV-2 infection. Global efforts of genomic surveillance of the virus give chance to track the spread of the pandemic. Global emergence of some viral mutations called attention and various studies have been suggested about increased infectivity of the virus. Herein, we sequenced viral genomes isolated from 184 patients in Istanbul and analyzed clinical metadata for the investigation of any viral mutation which affects the disease course of the host. We did not detect any viral mutations affecting the disease outcome in our cohort. Besides, we observed intra-host mutations in 76% of the isolates. Insertion/deletion and stop-gain mutations are also significantly less common among intra-host variants compared to consensus viral genome mutations. Longitudinal genomic surveillance is essential for timely detection of any lineages that might affect clinical outcome, the performance of diagnostic assays, or even the immunological escape of the virus.

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  1. ScreenIT

    SciScore for 10.1101/2020.12.25.20248851: (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

    Software and Algorithms
    SentencesResources
    Raw sequencing data were first demultiplexed and quality assessment was performed using the FASTQC program (Andrews, 2010).
    FASTQC
    suggested: (FastQC, RRID:SCR_014583)
    Primers were pruned using TrimPrimers script within the fgbio tool (http://fulcrumgenomics.github.io/fgbio/).
    TrimPrimers
    suggested: None
    Variant calling and consensus sequence generation were performed using Samtools (Li et al., 2009) and iVAR (Grubaugh et al., 2019).
    Samtools
    suggested: (SAMTOOLS, RRID:SCR_002105)
    Variant files for each isolate were converted to vcf files, which was further processed with BCFtools (Li, 2011) and annotated using ANNOVAR (Wang et al., 2010).
    ANNOVAR
    suggested: (ANNOVAR, RRID:SCR_012821)
    Consensus genome sequences of isolates were aligned using MAFFT (Katoh et al., 2019).
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    The neighbor[joining method was used to estimate phylogenies using aligned sequences and the tree was visualized using FigTree v1.4.4.
    FigTree
    suggested: (FigTree, RRID:SCR_008515)

    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.

  2. Version published to 10.1101/2020.12.25.20248851v1 on medRxiv