PLoS ONEGenomicsPeer-reviewed journal article
Profiling of the most reliable mutations from sequenced SARS-CoV-2 genomes scattered in Uzbekistan
Ayubov Mirzakamol SobitjonovichiD, Zabardast Tadjiboevich BurieviD, Mukhammadjon K. MirzakhmedoviD, Abdurakhmon N. Yusupov, Dilshod E. UsmanoviD, Shukhrat E. ShermatoviD, Khurshida Abdullaevna UbaydullaevaiD, Ibrokhim Yulchievich AbdurakhmonoviD
Abstract
Due to rapid mutations in the coronavirus genome over time and re-emergence of multiple novel variants of concerns (VOC), there is a continuous need for a periodic genome sequencing of SARS-CoV-2 genotypes of particular region. This is for on-time development of diagnostics, monitoring and therapeutic tools against virus in the global pandemics condition. Toward this goal, we have generated 18 high-quality whole-genome sequence data from 32 SARS-CoV-2 genotypes of PCR-positive COVID-19 patients, sampled from the Tashkent region of Uzbekistan. The nucleotide polymorphisms in the sequenced sample genomes were determined, including nonsynonymous (missense) and synonymous mutations in coding regions of coronavirus genome. Phylogenetic analysis grouped fourteen whole genome sample sequences (1, 2, 4, 5, 8, 10-15, 17, 32) into the G clade (or GR sub-clade) and four whole genome sample sequences (3, 6, 25, 27) into the S clade. A total of 128 mutations were identified, consisting of 45 shared and 83 unique mutations. Collectively, nucleotide changes represented one unique frameshift mutation, four upstream region mutations, six downstream region mutations, 50 synonymous mutations, and 67 missense mutations. The sequence data, presented herein, is the first coronavirus genomic sequence data from the Republic of Uzbekistan, which should contribute to enrich the global coronavirus sequence database, helping in future comparative studies. More importantly, the sequenced genomic data of coronavirus genotypes of this study should be useful for comparisons, diagnostics, monitoring, and therapeutics of COVID-19 disease in local and regional levels.
- organism: virus
- assay: whole-genome sequencing
- research focus: database / resource
- approach: statistical model
- Citations
- 13
- FWCI
- 1.46
- Field percentile
- top 17%
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