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TitleBoth simulation and sequencing data reveal coinfections with multiple SARS-CoV-2 variants in the COVID-19 pandemic
Creator
Date Issued2022
Source PublicationComputational and Structural Biotechnology Journal
ISSN2001-0370
Volume20Pages:1389-1401
Abstract

SARS-CoV-2 is a single-stranded RNA betacoronavirus with a high mutation rate. The rapidly emerging SARS-CoV-2 variants could increase transmissibility and diminish vaccine protection. However, whether coinfection with multiple SARS-CoV-2 variants exists remains controversial. This study collected 12,986 and 4,113 SARS-CoV-2 genomes from the GISAID database on May 11, 2020 (GISAID20May11), and Apr 1, 2021 (GISAID21Apr1), respectively. With single-nucleotide variant (SNV) and network clique analyses, we constructed single-nucleotide polymorphism (SNP) coexistence networks and discovered maximal SNP cliques of sizes 16 and 34 in the GISAID20May11 and GISAID21Apr1 datasets, respectively. Simulating the transmission routes and SNV accumulations, we discovered a linear relationship between the size of the maximal clique and the number of coinfected variants. We deduced that the COVID-19 cases in GISAID20May11 and GISAID21Apr1 were coinfections with 3.20 and 3.42 variants on average, respectively. Additionally, we performed Nanopore sequencing on 42 COVID-19 patients and discovered recurrent heterozygous SNPs in twenty of the patients, including loci 8,782 and 28,144, which were crucial for SARS-CoV-2 lineage divergence. In conclusion, our findings reported SARS-CoV-2 variants coinfection in COVID-19 patients and demonstrated the increasing number of coinfected variants.

KeywordCoinfection index Heterozygous single-nucleotide polymorphisms SARS-CoV-2 variant coinfection Viral transmission simulation
DOI10.1016/j.csbj.2022.03.011
URLView source
Indexed BySCIE
Language英语English
WOS Research AreaBiochemistry & Molecular Biology ; Biotechnology & Applied Microbiology
WOS SubjectBiochemistry & Molecular Biology ; Biotechnology & Applied Microbiology
WOS IDWOS:000791774200012
Scopus ID2-s2.0-85126687132
Citation statistics
Cited Times:6[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/9040
CollectionResearch outside affiliated institution
Corresponding AuthorYe, Feng
Affiliation
1.Institutes for Systems Genetics,Frontiers Science Center for Disease-related Molecular Network,West China Hospital,Sichuan University,Chengdu,610212,China
2.Department of Computer Science,City University of Hong Kong,Hong Kong,999077,Hong Kong
3.State Key Laboratory of Respiratory Disease,National Clinical Research Center for Respiratory Disease,Guangzhou Institute of Respiratory Health,the First Affiliated Hospital of Guangzhou Medical University,Guangzhou,510120,China
4.Department of Computer Science,Hong Kong Baptist University,Hong Kong,999077,Hong Kong
5.Kotai Biotechnologies,Inc.,Osaka,565-0871,Japan
Recommended Citation
GB/T 7714
Li, Yinhu,Jiang, Yiqi,Li, Zhengtuet al. Both simulation and sequencing data reveal coinfections with multiple SARS-CoV-2 variants in the COVID-19 pandemic[J]. Computational and Structural Biotechnology Journal, 2022, 20: 1389-1401.
APA Li, Yinhu., Jiang, Yiqi., Li, Zhengtu., Yu, Yonghan., Chen, Jiaxing., .. & Shen, Bairong. (2022). Both simulation and sequencing data reveal coinfections with multiple SARS-CoV-2 variants in the COVID-19 pandemic. Computational and Structural Biotechnology Journal, 20, 1389-1401.
MLA Li, Yinhu,et al."Both simulation and sequencing data reveal coinfections with multiple SARS-CoV-2 variants in the COVID-19 pandemic". Computational and Structural Biotechnology Journal 20(2022): 1389-1401.
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