COV2Var, a function annotation database of SARS-CoV-2 genetic variation

Author:

Feng Yuzhou12,Yi Jiahao3,Yang Lin4,Wang Yanfei5,Wen Jianguo5,Zhao Weiling5,Kim Pora5ORCID,Zhou Xiaobo567ORCID

Affiliation:

1. Department of Laboratory Medicine and West China Biomedical Big Data Center, West China Hospital, Sichuan University , Chengdu  610041 , China

2. Med-X Center for Informatics, Sichuan University , Chengdu  610041 , China

3. School of Big Health, Guizhou Medical University , Guiyang  550025 , China

4. Department of Cardiology and Laboratory of Gene Therapy for Heart Diseases, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University and Collaborative Innovation Center for Biotherapy , Chengdu  610041 , China

5. Center for Computational Systems Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston , Houston , TX  77030 , USA

6. McGovern Medical School, The University of Texas Health Science Center at Houston , Houston , TX  77030 , USA

7. School of Dentistry, The University of Texas Health Science Center at Houston , Houston , TX  77030 , USA

Abstract

Abstract The COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, has resulted in the loss of millions of lives and severe global economic consequences. Every time SARS-CoV-2 replicates, the viruses acquire new mutations in their genomes. Mutations in SARS-CoV-2 genomes led to increased transmissibility, severe disease outcomes, evasion of the immune response, changes in clinical manifestations and reducing the efficacy of vaccines or treatments. To date, the multiple resources provide lists of detected mutations without key functional annotations. There is a lack of research examining the relationship between mutations and various factors such as disease severity, pathogenicity, patient age, patient gender, cross-species transmission, viral immune escape, immune response level, viral transmission capability, viral evolution, host adaptability, viral protein structure, viral protein function, viral protein stability and concurrent mutations. Deep understanding the relationship between mutation sites and these factors is crucial for advancing our knowledge of SARS-CoV-2 and for developing effective responses. To fill this gap, we built COV2Var, a function annotation database of SARS-CoV-2 genetic variation, available at http://biomedbdc.wchscu.cn/COV2Var/. COV2Var aims to identify common mutations in SARS-CoV-2 variants and assess their effects, providing a valuable resource for intensive functional annotations of common mutations among SARS-CoV-2 variants.

Funder

Center of Excellence-International Collaboration Initiative

West China Hospital, Sichuan University

NIH

NSF

Publisher

Oxford University Press (OUP)

Subject

Genetics

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