Tracking the circulating SARS-CoV-2 variants in Turkey: Complete genome sequencing and molecular characterization of 1000 SARS-CoV-2 samples

  1. Faruk Berat Akçeşme
  2. Tuğba Kul Köprülü
  3. Burçin Erkal
  4. Şeyma İş
  5. Birsen Cevher Keskin
  6. Betül Akçeşme
  7. Kürşad Nuri Baydili
  8. Bahar Gezer
  9. Jülide Balkan
  10. Bihter Uçar
  11. Osman Gürsoy
  12. Mehmet Taha Yıldız
  13. Halil Kurt
  14. Nevzat Ünal
  15. Mustafa Altındiş
  16. Celalettin Korkmaz
  17. Hasan Türkez
  18. Özlem Bayraktar
  19. Barış Demirkol
  20. Yasemin Çağ
  21. Melih Akay Arslan
  22. Hilal Abakay
  23. Şükran Köse
  24. Abdülkadir Özel
  25. Neslihan Mutluay
  26. Şaban Tekin

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Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible coronavirus and has caused a pandemic of acute respiratory disease, named ‘coronavirus disease 2019’ (COVID-19). COVID-19 has a deep impact on public health as one of the most serious pandemics in the last century. Tracking SARS-CoV-2 is important for monitoring and assessing its evolution. This is only possible by detecting all mutations in the viral genome through genomic sequencing. Moreover, accurate detection of SARS-CoV-2 and tracking its mutations is also required for its correct diagnosis. Potential effects of mutations on the prognosis of the disease can be observed. Assignment of epidemiological lineages in an emerging pandemic requires efforts. To address this, we collected 1000 SARS-CoV-2 samples from different geographical regions in Turkey and analyze their genome comprehensively. To track the virus across Turkey we focus on 10 distinct cities in different geographic regions. Each SARS-CoV-2 genome was analyzed and named according to the nomenclature system of Nextclade and Pangolin Lineage. Furthermore, the frequency of the variations observed in 10 months was also determined by region. In this way, we have observed how the virus mutations and what kind of transmission mechanism it has. The effects of age and disease severity on lineage distribution were other considered parameters. The temporal rates of SARS-CoV-2 variants by time in Turkey were close to the global trend. This study is one of the most comprehensive whole genome analyses of SARS-CoV-2 that represents a general picture of the distribution of SARS-CoV-2 variations in Turkey in 2021.

Author Summary

Since the outbreak of the COVID-19 pandemic in 2019, the viral genome of SARS-CoV-2 was analysed intensively all over the world both to detect its zoonotic origin and the emerging variants worldwide together with the variants’ effect on the prognosis and treatment, respectively, of the infection. Remarkable COVID-19 studies were also made in Turkey as it was in the rest of the world. To date, indeed, almost all studies on COVID-19 in Turkey either sequenced only a small number of the viral genome or analysed the viral genome which was obtained from online databases. In respect thereof, our study constitutes a milestone regarding both the huge sample size consisting of 1000 viral genomes and the widespread geographic origin of the viral genome samples. Our study provides new insights both into the SARS-CoV-2 landscape of Turkey and the transmission of the emerging viral pathogen and its interaction with its vertebrate host.

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  1. ScreenIT

    SciScore for 10.1101/2022.04.19.488722: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Sample Collection: Nasopharyngeal swab samples obtained from patients diagnosed with SARS-CoV-2 infection by performing a RT-PCR (Coronex, Bio-Speedy and Diagno5plex NS) in hospitals between March 2021 and December 2021 were included in the study (the approval for this research was obtained from the ethics committee of University of Health Sciences).
    Field Sample Permit: Viral RNA Extraction: All collected samples were transferred to Genetic Engineering and Biotechnology Institute of the Scientific and Technological Research Institution of Turkey TÜBİTAK for viral RNA (vRNA).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot 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:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • No funding statement was detected.
    • 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.

  2. Version published to 10.1101/2022.04.19.488722v1 on bioRxiv