Variant analysis of SARS-CoV-2 strains with phylogenetic analysis and the Coronavirus Antiviral and Resistance Database
No Thumbnail Available
Date
2021-01-01
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
FUTURE MEDICINE LTD
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.
Description
Keywords
bioinformatics, COVID-19, next-generation sequencing, phylogenetic analyses, SARS-CoV-2 variants