{"title":"Coronavirus Genus Recognition Based on Prototype Virus Variants","authors":"M. Chaley, V. Kutyrkin","doi":"10.17537/2022.17.10","DOIUrl":null,"url":null,"abstract":"\nMethod 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.\n","PeriodicalId":53525,"journal":{"name":"Mathematical Biology and Bioinformatics","volume":"29 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical Biology and Bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17537/2022.17.10","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 4
Abstract
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.