【作者】
唐小鹿；
应若晨；
姚欣敏；
李广浩；
吴长城；
汤易雨立；
李志达；
邝碧姗；
伍锋；
池昌盛；
杜晓满；
覃依；
高胜寒；
胡松年；
马俊才；
刘天罡；
庞星火；
王建伟；
赵国屏；
谭文杰；
张亚平；
吕雪梅；
陆剑；
【Author】
Xiaolu Tang;Ruochen Ying;Xinmin Yao;Guanghao Li;Changcheng Wu;Yiyuli Tang;Zhida Li;Bishan Kuang;Feng Wu;Changsheng Chi;Xiaoman Du;Yi Qin;Shenghan Gao;Songnian Hu;Juncai Ma;Tiangang Liu;Xinghuo Pang;Jianwei Wang;Guoping Zhao;Wenjie Tan;Yaping Zhang;Xuemei Lu;Jian Lu;State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences, Peking University;State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences;Beijing Institute of Genomics, Chinese Academy of Sciences;Yuxi Rongjian Information Technology Co., Ltd.;State Key Laboratory of Microbial Resources (SKLMR), The Institute of Microbiology, Chinese Academy of Sciences;The Microresource and Big Data Center, The Institute of Microbiology, Chinese Academy of Sciences;Key Laboratory of Combinatorial Biosynthesis and Drug Discovery, Ministry of Education and Wuhan University School of Pharmaceutical Sciences;Beijing Center for Disease Prevention and Control (CDC) & Research Center for Preventive Medicine of Beijing;NHC Key Laboratory of Systems Biology of Pathogens and Christophe Mérieux Laboratory, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College;Key Laboratory of Respiratory Disease Pathogenomics, Chinese Academy of Medical Sciences and Peking Union Medical College;Key Laboratory of Synthetic Biology, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences;NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention;
【通讯作者】
谭文杰;张亚平;吕雪梅;陆剑;
【机构】
State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences, Peking University；
State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences；
Beijing Institute of Genomics, Chinese Academy of Sciences；
Yuxi Rongjian Information Technology Co., Ltd.；
State Key Laboratory of Microbial Resources (SKLMR), The Institute of Microbiology, Chinese Academy of Sciences；
The Microresource and Big Data Center, The Institute of Microbiology, Chinese Academy of Sciences；
Key Laboratory of Combinatorial Biosynthesis and Drug Discovery, Ministry of Education and Wuhan University School of Pharmaceutical Sciences；
Beijing Center for Disease Prevention and Control (CDC) & Research Center for Preventive Medicine of Beijing；
NHC Key Laboratory of Systems Biology of Pathogens and Christophe Mérieux Laboratory, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College；
Key Laboratory of Respiratory Disease Pathogenomics, Chinese Academy of Medical Sciences and Peking Union Medical College；
Key Laboratory of Synthetic Biology, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences；
NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention；
【摘要】 新型冠状病毒肺炎(COVID-19,新冠病毒)的流行严重影响了世界经济和人类健康.随着新冠病毒基因组序列的迅速积累,国际上已经检测和发表了成千上万的基因组变异.为了更好地追踪新冠病毒基因组进化轨迹,并实时解析疫情发展进程中的病毒基因组特征,本研究分析了121618个高质量的病毒基因组.基于参考基因组第8782和28144位点上的单核苷酸变异(SNV),首先将这些病毒基因组划分为L和S两个主要谱系;根据第3037、14408和23403位点上的SNV,进一步将L谱系划分为L1和L2两个主要亚谱系.在此基础上,根据另外201个基因组变异位点,逐级划分出了130个亚谱系(S中37个, L1中35个, L2中58个).该谱系/亚谱系划分系统具有层次结构,反映了主要谱系中的亚谱系之间的亲缘关系.本研究同时建立了一个配套网站(www.covid19evolution.net),不仅方便用户查看亚谱系信息,而且提供了谱系划分工具,用户可以通过上传新冠病毒基因组序列,做谱系类型鉴定.最后,本研究讨论了代偿突变和自然选择在新冠病毒进化过程中可能起到的作用.本研究将增进对新冠病毒基因组时空动态进化的理解.更多还原
【Abstract】 The pandemic due to the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2), the etiological agent of coronavirus disease 2019(COVID-19), has caused immense global disruption. With the rapid accumulation of SARS-CoV-2 genome sequences, however, thousands of genomic variants of SARS-CoV-2 are now publicly available. To improve the tracing of the viral genomes’ evolution during the development of the pandemic, we analyzed single nucleotide variants(SNVs) in 121,618 high-quality SARS-CoV-2 genomes. We divided these viral genomes into two major lineages(L and S) based on variants at sites 8782 and 28144, and further divided the L lineage into two major sublineages(L1 and L2)using SNVs at sites 3037, 14408, and 23403. Subsequently, we categorized them into 130 sublineages(37 in S, 35 in L1, and 58 in L2) based on marker SNVs at 201 additional genomic sites. This lineage/sublineage designation system has a hierarchical structure and reflects the relatedness among the subclades of the major lineages. We also provide a companion website(www.covid19evolution.net) that allows users to visualize sublineage information and upload their own SARS-CoV-2 genomes for sublineage classification. Finally, we discussed the possible roles of compensatory mutations and natural selection during SARS-CoV-2’s evolution. These efforts will improve our understanding of the temporal and spatial dynamics of SARS-CoV-2’s genome evolution.更多还原
【基金】 supported by the National Natural Science Foundation of China (91731301 and U1902201);the Ministry of Science and Technology of the People’s Republic of China (2020YFC0847000);the Light of West China Program of the Chinese Academy of Sciences
