Choice of target in the genomes of prototypic strains to recognize subgenus of coronaviruses
Matematičeskaâ biologiâ i bioinformatika, Tome 18 (2023) no. 2, pp. 267-281.

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Targeted approach to recognition of coronavirus subgenus on the base of codon frequency distribution in the N-gene of nucleocapsid protein was proposed in the work. Deviation of codon frequency distribution in the N-gene of coronavirus genome analyzed from the same distributions for the 67 prototypic strains, which characterize the 23 subgenera in the four coronavirus genera, is calculated on the base of statistics in the approach proposed. The smallest value of such a deviation from certain prototypic strain points at subgenus to which this strain belongs. The approach proposed appeared to be effective and supports significance for recognizing coronavirus subgenus at least 99%. Populations of the 38 and 7 codons providing for needed efficiency level were selected out of all codons of the genetic code in accordance with their frequency distribution. The codons from the populations outlined fix taxonomic structure of coronavirus subgenus.
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M. B. Chaley; V. A. Kutyrkin. Choice of target in the genomes of prototypic strains to recognize subgenus of coronaviruses. Matematičeskaâ biologiâ i bioinformatika, Tome 18 (2023) no. 2, pp. 267-281. http://geodesic.mathdoc.fr/item/MBB_2023_18_2_a1/

[1] M. V. Sprindzhuk, V. I. Bernik, N. I. Kalosha, B. Batgerel, “Avtomatizatsiya i matematicheskii apparat analiza bioinformatsionnykh dannykh genomnoi prirody”, Sistemnyi analiz i upravlenie v biomeditsinskikh sistemakh, 21:4 (2022), 129–139 | DOI

[2] GISAID, (accessed 14.06.2023) https://gisaid.org

[3] GenBank, (accessed 14.06.2023) https://www.ncbi.nlm.nih.gov/genbank

[4] ENA, (accessed 14.06.2023) https://www.ebi.ac.uk/ena/browser/home

[5] CNGBdb, (accessed 14.06.2023) https://db.cngb.org

[6] B. Liu, K. Liu, H. Zhang, L. Zhang, Y. Bian, Huang L. CoV-Seq, “a new tool for SARS CoV-2 genome analysis and visualization: development and usability study”, J. Med. Internet Res., 22:10 (2020) | DOI | MR

[7] S. Cleemput, W. Dumon, V. Fonseca, W. Abdool Karim, M. Giovanetti, L. C. Alcantara, K. Deforche, T. de Oliveira, “Genome detective coronavirus typing tool for rapid identification and characterization of novel coronavirus genomes”, Bioinformatics, 36:11 (2020), 3552–3555 | DOI | MR

[8] D. Y. Seong, J. Park, K. Yi, D. Hong, “Systematic guidelines for effective utilization of COVID-19 databases in genomic, epidemiologic, and clinical research”, Viruses, 15:3 (2023), 692 | DOI

[9] R. C. Taylor J. Edgar, V. Lin, T. Altman, P. Barbera, D. Meleshko, D. Lohr, G. Novakovsky, B. Buchfink, B. Al-Shayeb et al, “Petabase-scale sequence alignment catalyses viral discovery”, Nature, 602 (2022), 142–147 | DOI

[10] A. E. Gorbalenya, S. G. Siddell, “Recognizing species as a new focus of virus research”, PLoS Pathog, 17:3 (2021), e1009318 | DOI

[11] D. Hoper, C. Wylezich, M. Beer, “Loeffler 4.0: diagnostic metagenomics”, Adv. Virus Res., 99 (2017), 17–37 | DOI

[12] A. L. Greninger, “A decade of RNA virus metagenomics is (not) enough”, Virus Res, 244 (2018), 218–229 | DOI

[13] Y. Z. Zhang, M. Shi, E. C. Holmes, “Using metagenomics to characterize an expanding virosphere”, Cell, 172:6 (2018), 1168–1172 | DOI

[14] M. J. Adams, E. J. Lefkowitz, A. M.Q. King, B. Harrach, R. L. Harrison, N. J. Knowles, A. M. Kropinski, M. Krupovic, J. H. Kuhn, A. R. Mushegian et al, “50 years of the International Committee on Taxonomy of Viruses: progress and prospects”, Arch. Virol., 162 (2017), 1441–1446 | DOI

[15] S. G. Siddell, P. J. Walker, E. J. Lefkowitz, A. R. Mushegian, M. J. Adams, B. E. Dutilh, A. E. Gorbalenya, B. Harrach, R. L. Harrison, S. Junglen et al, “Additional changes to taxonomy ratified in a special vote by the International Committee on Taxonomy of Viruses (October 2018)”, Arch. Virol., 164 (2019), 943–946 | DOI

[16] W. J.M. Spaan, D. Brian, D. Cavanagh, R. J. de Groot, L. Enjuanes, A. E. Gorbalenya, K. V. Holmes, P. Masters, P. Rottier, F. Taguchi, et al., “Coronaviridae”, Virus taxonomy, Eighth report of the International Committee on Taxonomy of Viruses, eds. C. M. Fauquet et al., Elsevier, Academic Press, 2005, 947–964 | DOI

[17] A. E. Gorbalenya, M. Krupovic, A. Mushegian, A. M. Kropinski, S. G. Siddell, A. Varsani, M. J. Adams, A. J. Davison, B. E. Dutilh, B. Harrach et al, “The new scope of virus taxonomy: partitioning the virosphere into 15 hierarchical ranks”, Nat. Microbiol, 5:5 (2020), 668–674 | DOI

[18] P. J. Walker, S. G. Siddell, E. J. Lefkowitz, A. R. Mushegian, E. M. Adriaenssens, P. Alfenas-Zerbini, A. J. Davison, D. M. Dempsey, B. E. Dutilh, M. L. Garcia et al, “Changes to virus taxonomy and to the international code of virus classification and nomenclature ratified by the International Committee on Taxonomy of Viruses (2021)”, Arch. Virol, 166:9 (2021), 2633–2648 | DOI

[19] J. Felsenstein, “Evolutionary trees from DNA sequences: a maximum likelihood approach”, J. Mol. Evol, 17 (1981), 368–376 | DOI

[20] Felsenstein J., Inferring Phylogenies, Sinauer Associates, Sunderland, MA, 2003, 664 pp.

[21] L. T. Nguyen, H. A. Schmidt, A. von Haeseler, B. Q. Minh, “IQ-TREE: a fast and effective stochastic algorithm for estimating maximum likelihood phylogenies”, Mol. Biol. Evol, 32:1 (2015), 268–274 | DOI

[22] K. Katoh, J. Rozewicki, K. D. Yamada, “MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization”, Brief. Bioinform., 20:4 (2019), 1160–1166 | DOI

[23] E. V. Mavrodiev, M. L. Tursky, N. E. Mavrodiev, L. Schroder, A. P. Laktionov, M. C. Ebach, D. M. Williams, “On classification and taxonomy of coronaviruses (Riboviria, Nidovirales, Coronaviridae) with special focus on severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2)”, Math. Biol. Bioinf., 17:2 (2022), 289–311 | DOI | MR

[24] I. J. Kitching, P. Forey, P. L. Forey, C. Humphries, D. M. Williams, Cladistics, the Theory and Practice of Parsimony Analysis, Oxford University Press, Oxford–New York, 1998, 228 pp.

[25] G. Nelson, N. Platnick, Three-taxon statements, a more precise use of parsimony?, Cladistics, 7:4 (1991), 351–366 | DOI

[26] C. J. Creevey, J. O. McInerney, “Trees from trees: construction of phylogenetic supertrees using Clann”, Bioinformatics for DNA sequence analysis, ed. Posada D., Springer Humana Press, New York, 2009, 139–161 | DOI

[27] M. B. Chalei, V. A. Kutyrkin, “Raspoznavanie roda koronavirusa na osnove prototipnykh shtammov”, Mat. Biol. Bioinf., 17:1 (2022), 10–27 | DOI

[28] M. Yu. Schelkanov, A. Yu. Popova, V. G. Dedkov, V. G. Akimkin, V. V. Maleev, “Istoriya izucheniya i sovremennaya klassifikatsiya koronavirusov (Nidovirales: Coronaviridae)”, Infektsiya i immunitet, 10:2 (2020), 221–246 | DOI

[29] N. I. Borisova, I. A. Kotov, A. A. Kolesnikov, V. V. Kaptelova, A. S. Speranskaya, L. Yu. Kondrasheva, E. V. Tivanova, K. F. Khafizov, V. G. Akimkin, “Monitoring rasprostraneniya variantov SARS-CoV-2 (Coronaviridae: Coronavirinae: Betacoronavirus; Sarbecovirus) na territorii Moskovskogo regiona s pomoschyu targetnogo vysokoproizvoditelnogo sekvenirovaniya”, Voprosy virusologii, 66:4 (2021), 269–278 | DOI | MR

[30] A. N. Vlasova, L. J. Saif, “Bovine coronavirus and the associated diseases”, Front. Vet. Sci, 8 (2021), 643220 | DOI

[31] A. G. Glotov, A. V. Nefedchenko, A. G. Yuzhakov, S. V. Koteneva, T. I. Glotova, A. K. Komina, N. Yu. Krasnikov, “Geneticheskii polimorfizm sibirskikh izolyatov koronavirusa krupnogo rogatogo skota (Coronaviridae: Betacoronavirus: Betacoronavirus-1)”, Voprosy virusologii, 67:5 (2022), 465–474 | DOI

[32] E. W. Sayers, M. Cavanaugh, K. Clark, J. Ostell, K. D. Pruitt, I. Karsch-Mizrachi, “GenBank”, Nucleic Acids Res, 47:D1 (2019), D94–D99 | DOI

[33] E. W. Sayers, J. Beck, E. E. Bolton, D. Bourexis, J. R. Brister, K. Canese, D. C. Comeau, K. Funk, S. Kim, W. Klimke et al, “Database resources of the National Center for Biotechnology Information”, Nucleic Acids Res., 49:D1 (2021), D10–D17 | DOI