Department of Laboratory Medicine and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, China.
Med-X Center for Informatics, Sichuan University, Chengdu 610041, China.
Nucleic Acids Res. 2024 Jan 5;52(D1):D701-D713. doi: 10.1093/nar/gkad958.
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.
由冠状病毒 SARS-CoV-2 引起的 COVID-19 大流行导致数百万人丧生和全球严重的经济后果。每次 SARS-CoV-2 复制时,其基因组都会获得新的突变。SARS-CoV-2 基因组中的突变导致了传染性的增加、严重的疾病结果、免疫反应的逃避、临床表现的变化以及疫苗或治疗效果的降低。迄今为止,多种资源提供了已检测突变的列表,但没有关键的功能注释。缺乏研究来检查突变与疾病严重程度、致病性、患者年龄、患者性别、种间传播、病毒免疫逃逸、免疫反应水平、病毒传播能力、病毒进化、宿主适应性、病毒蛋白结构、病毒蛋白功能、病毒蛋白稳定性和并发突变等各种因素之间的关系。深入了解突变位点与这些因素之间的关系对于推进我们对 SARS-CoV-2 的认识以及开发有效的应对措施至关重要。为了填补这一空白,我们构建了 COV2Var,这是一个 SARS-CoV-2 遗传变异的功能注释数据库,可在 http://biomedbdc.wchscu.cn/COV2Var/ 上获得。COV2Var 的目标是识别 SARS-CoV-2 变异株中的常见突变并评估其影响,为 SARS-CoV-2 变异株中常见突变的密集功能注释提供了有价值的资源。