tetano
Editor, Senior Moderator
J Comp Eff Res
. 2022 Jan 11.
doi: 10.2217/cer-2021-0208. Online ahead of print.
Variant analysis of SARS-CoV-2 strains with phylogenetic analysis and the Coronavirus Antiviral and Resistance Database
Murat Sayan[SUP] 1 2 [/SUP], Ayse Arikan[SUP] 2 3 [/SUP], Murat Isbilen[SUP] 4 [/SUP]
Affiliations
Abstract
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.
Keywords: COVID-19; SARS-CoV-2 variants; bioinformatics; next-generation sequencing; phylogenetic analyses.
. 2022 Jan 11.
doi: 10.2217/cer-2021-0208. Online ahead of print.
Variant analysis of SARS-CoV-2 strains with phylogenetic analysis and the Coronavirus Antiviral and Resistance Database
Murat Sayan[SUP] 1 2 [/SUP], Ayse Arikan[SUP] 2 3 [/SUP], Murat Isbilen[SUP] 4 [/SUP]
Affiliations
- PMID: 35014556
- DOI: 10.2217/cer-2021-0208
Abstract
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.
Keywords: COVID-19; SARS-CoV-2 variants; bioinformatics; next-generation sequencing; phylogenetic analyses.