Department of Mathematics, Statistics, and Computer Science, The University of Illinois at Chicago, Chicago, IL 60607-7045, USA.
J Theor Biol. 2021 Apr 21;515:110604. doi: 10.1016/j.jtbi.2021.110604. Epub 2021 Jan 26.
The ongoing global pandemic of infection disease COVID-19 caused by the 2019 novel coronavirus (SARS-COV-2, formerly 2019-nCoV) presents critical threats to public health and the economy. The genome of SARS-CoV-2 had been sequenced and structurally annotated, yet little is known of the intrinsic organization and evolution of the genome. To this end, we present a mathematical method for the genomic spectrum, a kind of barcode, of SARS-CoV-2 and common human coronaviruses. The genomic spectrum is constructed according to the periodic distributions of nucleotides and therefore reflects the unique characteristics of the genome. The results demonstrate that coronavirus SARS-CoV-2 exhibits predominant latent periodicity-2 regions of non-structural proteins 3, 4, 5, and 6. Further analysis of the latent periodicity-2 regions suggests that the dinucleotide imbalances are increased during evolution and may confer the evolutionary fitness of the virus. Especially, SARS-CoV-2 isolates have increased latent periodicity-2 and periodicity-3 during COVID-19 pandemic. The special strong periodicity-2 regions and the intensity of periodicity-2 in the SARS-CoV-2 whole genome may become diagnostic and pharmaceutical targets in monitoring and curing the COVID-19 disease.
由 2019 年新型冠状病毒(SARS-CoV-2,以前称为 2019-nCoV)引起的持续全球传染病大流行 COVID-19 对公共卫生和经济构成了重大威胁。SARS-CoV-2 的基因组已经被测序并进行了结构注释,但对其内在组织和进化知之甚少。为此,我们提出了一种用于 SARS-CoV-2 和常见人类冠状病毒基因组的基因组谱(一种条码)的数学方法。基因组谱是根据核苷酸的周期性分布构建的,因此反映了基因组的独特特征。结果表明,冠状病毒 SARS-CoV-2 表现出主要的潜伏周期性-2 区域,分别是非结构蛋白 3、4、5 和 6。对潜伏周期性-2 区域的进一步分析表明,在进化过程中,二核苷酸不平衡增加,这可能赋予了病毒的进化适应性。特别是,在 COVID-19 大流行期间,SARS-CoV-2 分离株的潜伏周期性-2 和周期性-3 增加。SARS-CoV-2 全基因组中的特殊强周期性-2 区域和周期性-2 强度可能成为监测和治疗 COVID-19 疾病的诊断和药物靶点。