Variant analysis of SARS-CoV-2 strains with phylogenetic analysis and the Coronavirus Antiviral and Resistance Database

dc.contributor.authorSayan, Murat
dc.contributor.authorArikan, Ayse
dc.contributor.authorIsbilen, Murat
dc.date.accessioned2023-02-21T12:34:37Z
dc.date.available2023-02-21T12:34:37Z
dc.date.issued2021-01-01
dc.description.abstractAims: 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.
dc.description.issue3
dc.description.issueNOV
dc.description.pages157-167
dc.description.volume11
dc.identifier.doi10.2217/cer-2021-0208
dc.identifier.urihttps://hdl.handle.net/11443/1779
dc.identifier.urihttp://dx.doi.org/10.2217/cer-2021-0208
dc.identifier.wosWOS:000741015300001
dc.publisherFUTURE MEDICINE LTD
dc.relation.ispartofJOURNAL OF COMPARATIVE EFFECTIVENESS RESEARCH
dc.subjectbioinformatics
dc.subjectCOVID-19
dc.subjectnext-generation sequencing
dc.subjectphylogenetic analyses
dc.subjectSARS-CoV-2 variants
dc.titleVariant analysis of SARS-CoV-2 strains with phylogenetic analysis and the Coronavirus Antiviral and Resistance Database
dc.typeArticle

Files

Collections