Browsing by Author "Arikan, Ayse"

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    Circulating Dynamics of SARS-CoV-2 Variants between April 2021 and February 2022 in Turkey
    (HINDAWI LTD, 2022-01-01) Sayan, Murat; Arikan, Ayse; Isbilen, Murat
    The diagnosis of new variants and monitoring their potential effects on diagnosis, therapeutics, and vaccines by genomic sequencing is essential to manage global public crises. In the current study, spike-genome next-generation sequencing was generated from 492 SARS-CoV-2 isolates to evaluate the mutations in Turkey from April 2021 to February 2022. The variant analysis was performed using (Coronavirus Antiviral and Resistance Database (CoV-RDB) by Stanford University). We revealed that the lineages Alpha (B.1.1.7), Beta (B.1.351), Delta (B.1.617.2), Eta (B.1.525), variant of interest (VOI), lota (B.1.526), Zeta (P.2), Omicron (B.1.1.529), and Omicron BA.1 (B.1.1.529.1) were in the circulation in Turkey during the given period. The most common lineages were B.1.1.7, B.1.617.2, B.1.1.529, and B.1.1.529.1 SARS-CoV-2 variant circulation in Turkey seems highly heterogenetic
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    Variant analysis of SARS-CoV-2 strains with phylogenetic analysis and the Coronavirus Antiviral and Resistance Database
    (FUTURE MEDICINE LTD, 2021-01-01) Sayan, Murat; Arikan, Ayse; Isbilen, Murat
    Aims: This study determined SARS-CoV-2 variations by phylogenetic and virtual phenotyping analyses. Materials \& methods: Strains isolated from 143 COVID-19 cases in Turkey in April 2021 were assessed. Illumina NexteraXT library preparation kits were processed for next-generation ]sequencing. Phylogenetic (neighbor-joining method) and virtual phenotyping analyses (Coronavirus Antiviral and Resistance Database {[}CoV-RDB] by Stanford University) were used for variant analysis. Results: B.1.1.7-1/2 (n = 103, 72\%), B.1.351 (n = 5, 3\%) and B.1.525 (n = 1, 1\%) were identified among 109 SARS-CoV-2 variations by phylogenetic analysis and B.1.1.7 (n = 95, 66\%), B.1.351 (n = 5, 4\%), B.1.617 (n = 4, 3\%), B.1.525 (n = 2, 1.4\%), B.1.526-1 (n = 1, 0.6\%) and missense mutations (n = 15, 10\%) were reported by CoV-RDB. The two methods were 85\% compatible and B.1.1.7 (alpha) was the most frequent SARS-CoV-2 variation in Turkey in April 2021. Conclusion: The Stanford CoV-RDB analysis method appears useful for SARS-CoV-2 lineage surveillance.