基于原型病毒变体的冠状病毒属识别

Q3 Mathematics
M. Chaley, V. Kutyrkin
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引用次数: 4

摘要

本文提出了基于病毒ORF1ab密码子分布频率和结构蛋白(S、M、N)基因的变异识别冠状病毒属的方法。该方法采用改进的统计量,其有效性已在早期的黄病毒种类识别中得到证实。为了识别冠状病毒属,变异方法既考虑了几种冠状病毒结构基因的不同组合,也考虑了单个结构基因的不同组合。最后,根据所考虑的所有变异的分析结果确定冠状病毒属。该方法是通过学习甲型冠状病毒、乙型冠状病毒、德尔塔冠状病毒和伽玛冠状病毒属的原型病毒变体样本而开发的。变异方法在冠状病毒属识别中的应用表明,该方法的准确率高达95%。在联合分析的所有变异中,如果使用ORF1ab的密码子频率,识别属的可靠性最高(98%)。变异方法揭示了冠状病毒基因组中的镶嵌结构现象,即少数基因的属识别结果与冠状病毒属的最终结论存在差异。这一现象似乎反映了不同冠状病毒物种之间基因的同源重组及其基因组在进化过程中的可塑性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coronavirus Genus Recognition Based on Prototype Virus Variants
Method named as variant approach to recognizing genus of coronavirus that is based on frequency of codon distribution in viral ORF1ab and genes of structural proteins (S, M and N) was proposed in the work. This method uses modified statistics whose efficiency was demonstrated earlier for flavivirus species recognition. To recognize genus of coronavirus the variant approach considers both various combinations of several structural coronavirus genes and individual structural genes. Finally, coronavirus genus is determined in the result of analysis of all variants considered. The method proposed was developed with the help of learning sample from prototype viral variants of Alphacoronavirus, Betacoronavirus, Deltacoronavirus and Gammacoronavirus genus. Application of the variant approach to recognizing genus of coronavirus has demonstrated the approach high assurance at level of 95 %. Among all variants of joint analysis, the most reliability (98 %) in recognizing genus has been achieved if codon frequency of the ORF1ab was used. Variant approach has revealed a phenomenon of mosaic structure in coronavirus genomes, i.e., when the results of genus recognition for a few genes differ from final conclusion about coronavirus genus. It seems that such phenomenon reflects homologous recombinations of the genes between various species of the coronaviruses and plasticity of their genomes in evolutionary processes.
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来源期刊
Mathematical Biology and Bioinformatics
Mathematical Biology and Bioinformatics Mathematics-Applied Mathematics
CiteScore
1.10
自引率
0.00%
发文量
13
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