Application of Bayesian phylogenetic inference modelling for evolutionary genetic analysis and dynamic changes in 2019-nCoV

Application of Bayesian phylogenetic inference modelling for evolutionary genetic analysis and dynamic changes in 2019-nCoV
复制标题

应用贝叶斯系统发育推理模型进行2019-nCoV进化遗传分析和动态变化

DOI:
10.1093/bib/bbaa154
复制
发表时间:
2020-07
影响因子:
9.5
通讯作者:
Guoqing Wang
Guoqing Wang
中科院分区:
生物学2区
文献类型:
--
作者:
Tong Shao;Wenfang Wang;Meiyu Duan;Jiahui Pan;Zhuoyuan Xin;Baoyue Liu;Fengfeng Zhou;Guoqing Wang

文献摘要

参考文献

相似文献

摘要新型冠状病毒(2019-nCoV)最近在中国和世界范围内引起了大规模的病毒性肺炎疫情。在这项研究中,我们从公共基因库获得了截至2020年2月29日的777株新型冠状病毒毒株的全基因组序列。对这些毒株的生物信息学分析表明,目前这些新型冠状病毒的突变率并不高,与严重急性呼吸综合征(SARS)病毒的突变率相似。2019-nCoV与SARS病毒的相似性表明,S和ORF 6蛋白的相似性较低,而E蛋白的相似性较高。2019-nCoV序列在表面蛋白和ORF 1ab多聚蛋白上具有与SARS病毒相似的潜在磷酸化位点和糖基化位点;但中国毒株与部分美国毒株在潜在修饰位点上存在差异。同时,我们提出了2019-nCoV的两个可能的重组位点。根据天际线的结果,我们推测2019-nCoV的基因群体的活性可能在2019年底之前。随着2019-nCoV感染范围的进一步扩大,它可能会因环境的不同而产生不同的适应性进化。最后,进化遗传分析可以成为研究2019-nCoV传播和毒力的有用资源,这是预防和精准医学的重要方面。
Abstract The novel coronavirus (2019-nCoV) has recently caused a large-scale outbreak of viral pneumonia both in China and worldwide. In this study, we obtained the entire genome sequence of 777 new coronavirus strains as of 29 February 2020 from a public gene bank. Bioinformatics analysis of these strains indicated that the mutation rate of these new coronaviruses is not high at present, similar to the mutation rate of the severe acute respiratory syndrome (SARS) virus. The similarities of 2019-nCoV and SARS virus suggested that the S and ORF6 proteins shared a low similarity, while the E protein shared the higher similarity. The 2019-nCoV sequence has similar potential phosphorylation sites and glycosylation sites on the surface protein and the ORF1ab polyprotein as the SARS virus; however, there are differences in potential modification sites between the Chinese strain and some American strains. At the same time, we proposed two possible recombination sites for 2019-nCoV. Based on the results of the skyline, we speculate that the activity of the gene population of 2019-nCoV may be before the end of 2019. As the scope of the 2019-nCoV infection further expands, it may produce different adaptive evolutions due to different environments. Finally, evolutionary genetic analysis can be a useful resource for studying the spread and virulence of 2019-nCoV, which are essential aspects of preventive and precise medicine.
DOI: 10.3760/cma.j.cn112338-20200427-00659
发表时间: 2020-12
影响因子: --
作者:
Chaolin Huang;Ye-ming Wang;Xing-wang Li;L. Ren;Jianping Zhao;Y. Hu;Li Zhang;Guohui Fan;
通讯作者: Chaolin Huang;Ye-ming Wang;Xing-wang Li;L. Ren;Jianping Zhao;Y. Hu;Li Zhang;Guohui Fan;
DOI: 10.1093/nar/gkv1276
发表时间: 2016-01-04
影响因子: 14.9
作者:
Clark K;Karsch-Mizrachi I;Lipman DJ;Ostell J;Sayers EW
通讯作者: Sayers EW
DOI: 10.1016/bs.aivir.2018.01.001
发表时间: 2018
影响因子: --
作者:
Corman VM;Muth D;Niemeyer D;Drosten C
通讯作者: Drosten C
基于人工蜂群和梯度提升决策树的特征选择
DOI: 10.1016/j.asoc.2018.10.036
发表时间: 2019-01-01
影响因子: 8.7
作者:
Rao, Haidi;Shi, Xianzhang;Gu, Lichuan
通讯作者: Gu, Lichuan
DOI: 10.1038/sj.emboj.7600640
发表时间: 2005-04-20
期刊: EMBO JOURNAL
影响因子: 11.4
作者:
Li, WH;Zhang, CS;Sui, JH;Kuhn, JH;Moore, MJ;Luo, SW;Wong, SK;Huang, IC;Xu, KM;Vasilieva, N;Murakami, A;He, YQ;Marasco, WA;Guan, Y;Choe, HY;Farzan, M
通讯作者: Farzan, M