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Analyses of S Protein Homology Using the Genomes of SARS-CoV-2 Specimens Unveil Missing Links in the Temporal Order of Mutations in Its Variants

(1) Background: Since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the evolutionary traits of its variants have been revealed. However, the temporal order of the majority of mutations harbored by variants after the closest ancestors (or precursors), as “missing link...

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Detalles Bibliográficos
Autores principales: Kitayama, Ruri, Ogata, Yoshiyuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10675617/
https://www.ncbi.nlm.nih.gov/pubmed/38005860
http://dx.doi.org/10.3390/v15112182
Descripción
Sumario:(1) Background: Since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the evolutionary traits of its variants have been revealed. However, the temporal order of the majority of mutations harbored by variants after the closest ancestors (or precursors), as “missing links”, remains unclear. In this study, we aimed to unveil such missing links based on analyses of S protein homology by focusing on specimens with incomplete sets of S protein mutations in a variant. (2) Methods: Prevariant and postvariant mutations were defined as those before and after the variant’s development, respectively. A total of 6,758,926 and 14,519,521 genomes were obtained from the National Center for Biotechnology Information and the GISAID initiative, respectively, and S protein mutations were detected based on BLASTN analyses. (3) Results: The temporal order of prevariant mutations harbored by 12 variants was deduced. In particular, the D950N mutation in the Mu variant shows V-shaped mutation transitions, in which multiple routes of evolution were combined and resulted in the formation of a V-shaped transition, indicating recombination. (4) Conclusions: Many genome data for SARS-CoV-2 unveiled the candidate precursors of Mu variant based on a data-driven approach to its prevariant mutations in each nation.