On the origin and continuing evolution of SARS-CoV-2
On the origin and continuing evolution of SARS-CoV-2
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DOI：
10.1093/nsr/nwaa036
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发表时间：
2020-06-01
影响因子：
20.6
通讯作者：
Lu, Jian
中科院分区：
文献类型：
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作者：
Tang, Xiaolu;Wu, Changcheng;Lu, Jian
SARS-CoV-2疫情于2019年12月下旬在中国武汉开始，此后影响了中国的大部分地区，并引起了全球的重大关注。在此，我们研究了SARS-CoV-2和其他相关冠状病毒之间的分子差异程度。虽然我们发现SARS-CoV-2和蝙蝠SARS相关冠状病毒（SARS-CoV; RaTG 13）之间的基因组核苷酸只有4%的变异性，但中性位点的差异为17%，这表明两种病毒之间的差异比以前估计的要大得多。我们的研究结果表明，在SARS-CoV-2和穿山甲SARS-CoV病毒中看到的刺突的受体结合结构域（RBD）中功能位点的新变化的发展可能是由自然选择引起的，除了重组。对103个SARS-CoV-2基因组的群体遗传分析表明，这些病毒有两个主要谱系（命名为L和S），这两个谱系由两个不同的SNP很好地定义，这两个SNP显示出迄今为止测序的病毒株之间几乎完全的连锁。我们发现，在我们检查的有限患者样本中，L谱系比S谱系更普遍。这些进化变化对疾病病因的影响仍不清楚。这些发现强烈强调了进一步全面研究的迫切需要，这些研究将联合收割机病毒基因组数据与2019冠状病毒病（COVID-19）的流行病学研究相结合。
The SARS-CoV-2 epidemic started in late December 2019 in Wuhan, China, and has since impacted a large portion of China and raised major global concern. Herein, we investigated the extent of molecular divergence between SARS-CoV-2 and other related coronaviruses. Although we found only 4% variability in genomic nucleotides between SARS-CoV-2 and a bat SARS-related coronavirus (SARSr-CoV; RaTG13), the difference at neutral sites was 17%, suggesting the divergence between the two viruses is much larger than previously estimated. Our results suggest that the development of new variations in functional sites in the receptor-binding domain (RBD) of the spike seen in SARS-CoV-2 and viruses from pangolin SARSr-CoVs are likely caused by natural selection besides recombination. Population genetic analyses of 103 SARS-CoV-2 genomes indicated that these viruses had two major lineages (designated L and S), that are well defined by two different SNPs that show nearly complete linkage across the viral strains sequenced to date. We found that L lineage was more prevalent than the S lineage within the limited patient samples we examined. The implication of these evolutionary changes on disease etiology remains unclear. These findings strongly underscores the urgent need for further comprehensive studies that combine viral genomic data, with epidemiological studies of coronavirus disease 2019 (COVID-19).