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[Preprint]. 2022 Jul 19:2022.07.18.500565.
doi: 10.1101/2022.07.18.500565.

The First Geographic Identification by Country of Sustainable Mutations of SARS-COV2 Sequence Samples: Worldwide Natural Selection Trends

Mohammadamin Mahmanzar  1 , Seyed Taleb Houseini  2 , Karim Rahimian  3 , Arsham Mikaeili Namini  4 , Amir Gholamzad  5 , Samaneh Tokhanbigli  6 , Mahsa Mollapour Sisakht  7 , Amin Farhadi  8 , Donna Lee Kuehu  1 , Youping Deng  1
Affiliations

The First Geographic Identification by Country of Sustainable Mutations of SARS-COV2 Sequence Samples: Worldwide Natural Selection Trends

Mohammadamin Mahmanzar et al. bioRxiv. .

Abstract

The high mutation rates of RNA viruses, coupled with short generation times and large population sizes, allow viruses to evolve rapidly and adapt to the host environment. The rapidity of viral mutation also causes problems in developing successful vaccines and antiviral drugs. With the spread of SARS-CoV-2 worldwide, thousands of mutations have been identified, some of which have relatively high incidences, but their potential impacts on virus characteristics remain unknown. The present study analyzed mutation patterns, SARS-CoV-2 AASs retrieved from the GISAID database containing 10,500,000 samples. Python 3.8.0 programming language was utilized to pre-process FASTA data, align to the reference sequence, and analyze the sequences. Upon completion, all mutations discovered were categorized based on geographical regions and dates. The most stable mutations were found in nsp1(8% S135R), nsp12(99.3% P323L), nsp16 (1.2% R216C), envelope (30.6% T9I), spike (97.6% D614G), and Orf8 (3.5% S24L), and were identified in the United States on April 3, 2020, and England, Gibraltar, and, New Zealand, on January 1, 2020, respectively. The study of mutations is the key to improving understanding of the function of the SARS-CoV-2, and recent information on mutations helps provide strategic planning for the prevention and treatment of this disease. Viral mutation studies could improve the development of vaccines, antiviral drugs, and diagnostic assays designed with high accuracy, specifically useful during pandemics. This knowledge helps to be one step ahead of new emergence variants.

Keywords: Amino Acid; Epidemiology; Mutation; Natural selection; SARS-CoV2; region.

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Conflict of interest statement

Declaration of competing interest The authors declare that they have no conflicts of interest that might be relevant to the contents of this manuscript, and the research was carried out regardless of commercial or financial relationships that may cause any conflict of interest.

Figures

Figure 1.
Figure 1.
The first country reported sustainable mutation in each gene. From left to right, gene name, country name, Amino acid substitutions and positions, the Mutation frequency of all mutations occurring in that gene, and date of the first sample include mentioned mutation.
Figure 2A:
Figure 2A:
First stable mutations in SARS-CoV-2, including nsp1-nsp7
Figure 2B:
Figure 2B:
First stable mutations in SARS-CoV-2, including nsp8-nsp16
Figure 3A:
Figure 3A:
First stable mutations in SARS-CoV-2 including ORF3a, ORF6, ORF7a, ORF8
Figure 3B:
Figure 3B:
First stable mutations in SARS-CoV-2 including (ORF7b, ORF9b, ORF9c)
Figure 4.
Figure 4.
First stable mutation in sars-cov2 including Envelope, Membrane, Nucleoprotein, and Spike.
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See this image and copyright information in PMC

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