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.
【저자키워드】 COVID-19, bioinformatics, SARS-CoV-2 variants, Next-generation sequencing, phylogenetic analyses, 【초록키워드】 SARS-CoV-2, coronavirus, B.1.351, Variation, variant, Turkey, Phylogenetic analysis, Surveillance, B.1.1.7, resistance, B.1.617, Missense mutation, Alpha, B.1.526, Illumina, Strains, Analysis, Missense mutations, strain, Phylogenetic, (alpha, COVID-19 case, material, B.1.525, SARS-CoV-2 variations, Stanford University, SARS-CoV-2 lineage, reported, appear, were used, analysis, analyses, processed, SARS-CoV-2 variation, 【제목키워드】 resistance, Analysis, SARS-CoV-2 strain,