ABSTRACT
BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new emerging coronavirus that causes coronavirus disease 2019 (COVID-19). Whole-genome tracking of the SARS-CoV-2 enhanced our understanding of the mechanism of disease, control, and prevent COVID-19 infections. Materials and MethodsIn the current study, we investigated 1221 SARS-CoV-2 protein sequences of Iranian SARS-CoV-2 in the public database of the GISAID from January 2019 to April 2022. Prepare a list of suitable samples and preprocess performed by python programming language. To compare and identify mutation patterns SARS-CoV-2 genome was aligned to the Wuhan-Hu-1 as a reference sequence. ResultsOur investigation revealed that spike-P323L, ORF9c-G50N, NSP14-I42V, spike-D614G, NSP4-T492I, nucleocapsid-R203K, nucleocapsid-G204R, membrane-A63T, membrane-Q19E, NSP5-P132H, envelope-T9I, NSP3-G489S, ORF3a-T24I, membrane-D3G, spike-S477N, Spike-D478K, nucleocapsid-S235F, spike-N501Y, nucleocapsid-D3L, and spike-P861H as the most frequent mutations among the Iranian SARS-COV-2 sequences. Furthermore, it was observed that more than 95 % of the SARS-CoV-2 genome, including NSP7, NSP8, NSP9, NSP10, NSP11, and ORF8, had no mutation when compared to the Wuhan-Hu-1. Finally, our data indicated the ORF3a-T24I, NSP3-G489S, NSP5-P132H, NSP14-I42V, envelope-T9I, nucleocapsid-D3L, membrane-Q19E, and membrane-A63T mutations might be one of the responsible factors for the surge in the SARS-CoV-2 omicron variant wave in Iran. DiscussionOur results highlight the value of real-time genomic surveillance that help to identify novel SARS-CoV-2 variants and could be applied to update SARS-CoV-2 diagnostic tools, vaccine design, and understanding of the mechanisms of adaptation to a new host environment.
