Article: Phyloevolutionary analysis of SARS-CoV-2 in Nigeria.
New microbes and new infections
2020 Volume 36, Page(s) 100717
Abstract: Phyloepidemiological approaches have provided specific insight into understanding the emergence and evolution of infection. Knowledge on the outbreak and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Nigeria would assist in ... ...
Abstract | Phyloepidemiological approaches have provided specific insight into understanding the emergence and evolution of infection. Knowledge on the outbreak and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Nigeria would assist in provision of preventive measures to reduce transmission among populations at risk. This study aimed to investigate the evolution of SARS-CoV-2 in Nigeria. A total of 39 complete genomes of SARS-CoV-2 were retrieved from the GISAID EpiFlu™ database on 29 March 2020 to investigate its evolution in Nigeria. Sequences were selected based on the travel history of the individual and the collection date. Other sequences were not selected because they were short, contained artefacts, were not from an original source or had insufficient information. Evolutionary history was inferred using the maximum likelihood method based on the general time reversible model. A phylogenetic tree was constructed to determine the common ancestor of each strain. The phylogenetic analysis showed that the strain in Nigeria clustered in a monophyletic clade with a Wuhan sublineage. Nucleotide alignment also showed a 100% similarity indicating a common origin of evolution. Comparative analysis showed 27 972 (93.6%) identical sites and 97.6% pairwise identity with the consensus. The study evidently showed the entire outbreak of SARS-CoV-2 infection in Nigeria stemmed from a single introduction sharing consensus similarity with the reference SARS-CoV-2 human genome from Wuhan. Preventive measures that can limit the spread of the infection among populations at risk should be implemented. |
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Keywords | covid19 |
Language | English |
Publishing date | 2020-06-14 |
Publishing country | England |
Document type | Journal Article |
ZDB-ID | 2750179-6 |
ISSN | 2052-2975 |
ISSN | 2052-2975 |
DOI | 10.1016/j.nmni.2020.100717 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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