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Genomic diversity analysis of SARS-CoV-2 genomes in Rwanda
Nzungize Lambert; Ndishimye Pacifique; Fathiah Zakham.
Affiliation
  • Nzungize Lambert; Synthetic Biology Rwanda
  • Ndishimye Pacifique; Rwanda Joint Task Force COVID-19, Rwanda Biomedical Center, Ministry of Health, Kigali, Rwanda.
  • Fathiah Zakham; Laboratory of Virology, University of Helsinki, Helsinki 00014, Finland.
Preprint in English | bioRxiv | ID: ppbiorxiv-422793
ABSTRACT
COVID-19 (Coronavirus disease 2019) is an emerging pneumonia-like respiratory disease of humans and is recently spreading across the globe. ObjectiveTo analyze the genome sequence of SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2) isolated from Rwanda with other viral strains from African countries. MethodsWe downloaded 75 genomes sequences of clinical SARS-CoV-2 from the GISAID (global initiative on sharing all influenza data) database and we comprehensively analyzed these SARS-CoV-2 genomes sequences alongside with Wuhan SARS-CoV-2 sequences as the reference strains. ResultsWe analyzed 75 genomes sequences of SARS-CoV-2 isolated in different African countries including 10 samples of SARS-CoV-2 isolated in Rwanda between July and August 2020. The phylogenetic analysis of the genome sequence of SARS-CoV-2 revealed a strong identity with reference strains between 90-95%. We identified a missense mutation in four proteins including orf1ab polyprotein, NSP2, 2-O-ribose methyltransferase and orf1a polyprotein. The most common changes in the base are C > T. We also found that all clinically SARS-CoV-2 isolated from Rwanda had genomes belonging to clade G and lineage B.1. ConclusionsTracking the genetic evolution of SARS-CoV-2 over time is important to understand viral evolution pathogenesis. These findings may help to implement public health measures in curbing COVID-19 in Rwanda.
License
cc_by_nc
Full text: Available Collection: Preprints Database: bioRxiv Type of study: Prognostic study Language: English Year: 2020 Document type: Preprint
Full text: Available Collection: Preprints Database: bioRxiv Type of study: Prognostic study Language: English Year: 2020 Document type: Preprint
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