Unravelling codon usage patterns in the coding sequences of Bat RNA virus genomes of Rhabdoviridae family

Deepika Sharma Yengkhom Sophiarani Supriyo Chakraborty   

Open Access   

Published:  May 03, 2024

DOI: 10.7324/JABB.2024.187892
Abstract

Bats have a wide range of viral species in their bodies. RNA viruses of the Rhabdoviridae family have been found in arthropods, which might act as biological vectors for disease transmission to other plants or animals. The choice of one synonymous codon over another for the same amino acid is referred to as codon usage bias (CUB). It is primarily influenced by the forces of evolution, protein characteristics, compositional properties, and gene expression. In this study, we analyzed the composition of CUB and its distribution among 15 different Rhabdoviridae viral genomes found in bats. The genomes of all 15 viruses were found to be AT-rich and weak CUB. The pattern of codon utilization was investigated using parameters such as neutrality plot, parity plot, translational selection, nucleotide skewness, and relative synonymous codon usage (RSCU) values. Natural selection and mutational pressure both influenced the CUB of the 15 Rhabdoviridae viruses. RSCU analysis identified overrepresented and underrepresented codons. The neutrality plot study revealed that natural selection dominated in shaping the CUB. The results of our study revealed the pattern of codon usage in Rhabdoviridae genomes and set the groundwork for important evolutionary research on them.


Keyword:     Codon usage bias Mutational pressure Natural selection Rhabdoviridae


Citation:

Sharma D, Sophiarani Y, Chakraborty S. Unraveling codon usage patterns in the coding sequences of Bat RNA virus genomes of Rhabdoviridae family. J App Biol Biotech. 2024. Online First. http://doi.org/10.7324/JABB.2024.187892

Copyright: Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike license.

HTML Full Text
Reference

1. Olival KJ, Hayman DT. Filoviruses in bats: Current knowledge and future directions. Viruses 2014;6:1759-88. https://doi.org/10.3390/v6041759

2. Memish ZA, Mishra N, Olival KJ, Fagbo SF, Kapoor V, Epstein JH, et al. Middle East respiratory syndrome coronavirus in bats, Saudi Arabia. Emerg Infect Dis 2013;19:1819-23. https://doi.org/10.3201/eid1911.131172

3. Leroy EM, Kumulungui B, Pourrut X, Rouquet P, Hassanin A, Yaba P, et al. Fruit bats as reservoirs of Ebola virus. Nature 2005;438:575-6. https://doi.org/10.1038/438575a

4. Amman BR, Albariño CG, Bird BH, Nyakarahuka L, Sealy TK, Balinandi S, et al. A recently discovered pathogenic Paramyxovirus, Sosuga virus, is present in Rousettus aegyptiacus fruit bats at multiple locations in Uganda. J Wildl Dis 2015;51:774-9. https://doi.org/10.7589/2015-02-044

5. Mollentze N, Streicker DG. Viral zoonotic risk is homogenous among taxonomic orders of mammalian and avian reservoir hosts. Proc Natl Acad Sci U S A 2020;117:9423-30. https://doi.org/10.1073/pnas.1919176117

6. Olival KJ, Hosseini PR, Zambrana-Torrelio C, Ross N, Bogich TL, Daszak P. Host and viral traits predict zoonotic spillover from mammals. Nature 2017;546:646-50. https://doi.org/10.1038/nature22975

7. Kuzmin IV, Novella IS, Dietzgen RG, Padhi A, Rupprecht CE. The rhabdoviruses: Biodiversity, phylogenetics, and evolution. Infect Genet Evol 2009;9:541-53. https://doi.org/10.1016/j.meegid.2009.02.005

8. Walker PJ, Dietzgen RG, Joubert DA, Blasdell KR. Rhabdovirus accessory genes. Virus Res 2011;162:110-25. https://doi.org/10.1016/j.virusres.2011.09.004

9. Lozano R, Naghavi M, Foreman K, Lim S, Shibuya K, Aboyans V, et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012;380:2095-128. https://doi.org/10.1016/S0140-6736(12)61728-0

10. Wellehan JF Jr., Pessier AP, Archer LL, Childress AL, Jacobson ER, Tesh RB. Initial sequence characterization of the rhabdoviruses of squamate reptiles, including a novel rhabdovirus from a caiman lizard (Dracaena guianensis). Vet Microbiol 2012;158:274-9. https://doi.org/10.1016/j.vetmic.2012.02.020

11. Wang Y, Walker PJ. Adelaide river rhabdovirus expresses consecutive glycoprotein genes as polycistronic mRNAs: New evidence of gene duplication as an evolutionary process. Virology 1993;195:719-31. https://doi.org/10.1006/viro.1993.1423

12. Allison AB, Mead DG, Palacios GF, Tesh RB, Holmes EC. Gene duplication and phylogeography of North American members of the Hart Park serogroup of avian rhabdoviruses. Virology 2014;448:284-92. https://doi.org/10.1016/j.virol.2013.10.024

13. Simon-Loriere E, Holmes EC. Gene duplication is infrequent in the recent evolutionary history of RNA viruses. Mol Biol Evol 2013;30:1263-9. https://doi.org/10.1093/molbev/mst044

14. Walker PJ, Byrne KA, Riding GA, Cowley JA, Wang Y, McWilliam S. The genome of bovine ephemeral fever rhabdovirus contains two related glycoprotein genes. Virology 1992;191:49-61. https://doi.org/10.1016/0042-6822(92)90165-L

15. Jenkins GM, Holmes EC. The extent of codon usage bias in human RNA viruses and its evolutionary origin. Virus Res 2003;92:1-7. https://doi.org/10.1016/S0168-1702(02)00309-X

16. Wong EH, Smith DK, Rabadan R, Peiris M, Poon LL. Codon usage bias and the evolution of influenza A viruses. Codon usage biases of influenza virus. BMC Evol Biol 2010;10:253. https://doi.org/10.1186/1471-2148-10-253

17. Ma QP, Li C, Wang J, Wang Y, Ding ZT. Analysis of synonymous codon usage in FAD7 genes from different plant species. Genet Mol Res 2015;14:1414-22. https://doi.org/10.4238/2015.February.13.20

18. Liu Y. A code within the genetic code: Codon usage regulates co-translational protein folding. Cell Commun Signal 2020;18:145. https://doi.org/10.1186/s12964-020-00642-6

19. Hooper SD, Berg OG. Gradients in nucleotide and codon usage along Escherichia coli genes. Nucleic Acids Res 2000;28:3517-23. https://doi.org/10.1093/nar/28.18.3517

20. Plotkin JB, Kudla G. Synonymous but not the same: The causes and consequences of codon bias. Nat Rev Genet 2011;12:32-42. https://doi.org/10.1038/nrg2899

21. Ingvarsson PK. Molecular evolution of synonymous codon usage in Populus. BMC Evol Biol 2008;8:307. https://doi.org/10.1186/1471-2148-8-307

22. Liu Q. Mutational bias and translational selection shaping the codon usage pattern of tissue-specific genes in rice. PLoS One 2012;7:e48295. https://doi.org/10.1371/journal.pone.0048295

23. Mazumdar P, Binti Othman R, Mebus K, Ramakrishnan N, Ann Harikrishna J. Codon usage and codon pair patterns in non-grass monocot genomes. Ann Bot 2017;120:893-909. https://doi.org/10.1093/aob/mcx112

24. Quax TE, Claassens NJ, Söll D, Van der Oost J. Codon bias as a means to fine-tune gene expression. Mol Cell 2015;59:149-61. https://doi.org/10.1016/j.molcel.2015.05.035

25. Athey J, Alexaki A, Osipova E, Rostovtsev A, Santana-Quintero LV, Katneni U, et al. A new and updated resource for codon usage tables. BMC Bioinformatics 2017;18:391. https://doi.org/10.1186/s12859-017-1793-7

26. Zhou Z, Dang Y, Zhou M, Li L, Yu CH, Fu J, et al. Codon usage is an important determinant of gene expression levels largely through its effects on transcription. Proc Natl Acad Sci U S A 2016;113:E6117-25. https://doi.org/10.1073/pnas.1606724113

27. Gupta SK, Ghosh TC. Gene expressivity is the main factor in dictating the codon usage variation among the genes in Pseudomonas aeruginosa. Gene 2001;273:63-70. https://doi.org/10.1016/S0378-1119(01)00576-5

28. Zhou JH, Zhang J, Sun DJ, Ma Q, Chen HT, Ma LN, et al. The distribution of synonymous codon choice in the translation initiation region of dengue virus. PLoS One 2013;8:e77239. https://doi.org/10.1371/journal.pone.0077239

29. Wright F. The 'effective number of codons' used in a gene. Gene 1990;87:23-9. https://doi.org/10.1016/0378-1119(90)90491-9

30. Sueoka N. Intrastrand parity rules of DNA base composition and usage biases of synonymous codons. J Mol Evol 1995;40:318-25. https://doi.org/10.1007/BF00163236

31. Shields DC, Sharp PM. Synonymous codon usage in Bacillus subtilis reflects both translational selection and mutational biases. Nucleic Acids Res 1987;15:8023-40. https://doi.org/10.1093/nar/15.19.8023

32. Sueoka N. Directional mutation pressure and neutral molecular evolution. Proc Natl Acad Sci U S A 1988;85:2653-7. https://doi.org/10.1073/pnas.85.8.2653

33. Gouy M, Gautier C. Codon usage in bacteria: Correlation with gene expressivity. Nucleic Acids Res 1982;10:7055-74. https://doi.org/10.1093/nar/10.22.7055

34. Gatherer D, McEwan NR. Small regions of preferential codon usage and their effect on overall codon bias--the case of the plp gene. Biochem Mol Biol Int 1997;43:107-14. https://doi.org/10.1080/15216549700203871

35. Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol 2018;35:1547-9. https://doi.org/10.1093/molbev/msy096

36. Tamura K, Nei M. Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees. Mol Biol Evol 1993;10:512-26.

37. Hammer Ø, Harper DA, Ryan PD. PAST: Paleontological statistics software package for education and data analysis. Palaeontol Electron 2001;4:9.

38. Kosakovsky Pond SL, Frost SD. Not so different after all: A comparison of methods for detecting amino acid sites under selection. Mol Biol Evol 2005;22:1208-22. https://doi.org/10.1093/molbev/msi105

39. Kumar S, Stecher G, Tamura K. MEGA7: Molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol 2016;33:1870-4. https://doi.org/10.1093/molbev/msw054

40. Nie X, Deng P, Feng K, Liu P, Du X, You FM, et al. Comparative analysis of codon usage patterns in chloroplast genomes of the Asteraceae family. Plant Mol Biol Rep 2014;32:828-40. https://doi.org/10.1007/s11105-013-0691-z

41. Van Hemert F, Van der Kuyl AC, Berkhout B. Impact of the biased

nucleotide composition of viral RNA genomes on RNA structure and codon usage. J Gen Virol 2016;97:2608-19. https://doi.org/10.1099/jgv.0.000579

42. Deb B, Uddin A, Chakraborty S. Codon usage pattern and its influencing factors in different genomes of hepadnaviruses. Arch Virol 2020;165:557-70. https://doi.org/10.1007/s00705-020-04533-6

43. Rajewska M, Wegrzyn K, Konieczny I. AT-rich region and repeated sequences-the essential elements of replication origins of bacterial replicons. FEMS Microbiol Rev 2012;36:408-34. https://doi.org/10.1111/j.1574-6976.2011.00300.x

44. Wan XF, Xu D, Kleinhofs A, Zhou J. Quantitative relationship between synonymous codon usage bias and GC composition across unicellular genomes. BMC Evol Biol 2004;4:19. https://doi.org/10.1186/1471-2148-4-19

45. Huang X, Xu J, Chen L, Wang Y, Gu X, Peng X, et al. Analysis of transcriptome data reveals multifactor constraint on codon usage in Taenia multiceps. BMC Genomics 2017;18:308. https://doi.org/10.1186/s12864-017-3704-8

46. Dutta R, Buragohain L, Borah P. Analysis of codon usage of severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) and its adaptability in dog. Virus Res 2020;288:198113. https://doi.org/10.1016/j.virusres.2020.198113

47. Wang L, Xing H, Yuan Y, Wang X, Saeed M, Tao J, et al. Genome-wide analysis of codon usage bias in four sequenced cotton species. PLoS One 2018;13:e0194372. https://doi.org/10.1371/journal.pone.0194372

48. Zhou T, Gu W, Ma J, Sun X, Lu Z. Analysis of synonymous codon usage in H5N1 virus and other influenza A viruses. Biosystems 2005;81:77-86. https://doi.org/10.1016/j.biosystems.2005.03.002

49. Chakraborty S, Deb B, Barbhuiya PA, Uddin A. Analysis of codon usage patterns and influencing factors in Nipah virus. Virus Res 2019;263:129-38. https://doi.org/10.1016/j.virusres.2019.01.011

50. Kumar N, Bera BC, Greenbaum BD, Bhatia S, Sood R, Selvaraj P, et al. Revelation of influencing factors in overall codon usage bias of equine influenza viruses. PLoS One 2016;11:e0154376. https://doi.org/10.1371/journal.pone.0154376

51. Wang H, Liu S, Zhang B, Wei W. Analysis of synonymous codon usage bias of Zika virus and its adaption to the hosts. PLoS One 2016;11:e0166260. https://doi.org/10.1371/journal.pone.0166260

52. Gu W, Zhou T, Ma J, Sun X, Lu Z. Analysis of synonymous codon usage in SARS Coronavirus and other viruses in the nidovirales. Virus Res 2004;101:155-61. https://doi.org/10.1016/j.virusres.2004.01.006

53. Sueoka N. Correlation between base composition of deoxyribonucleic acid and amino acid composition of protein. Proc Natl Acad Sci U S A 1961;47:1141-9. https://doi.org/10.1073/pnas.47.8.1141

54. Cheng X, Virk N, Chen W, Ji S, Ji S, Sun Y, et al. CpG usage in RNA viruses: Data and hypotheses. PLoS One 2013;8:e74109. https://doi.org/10.1371/journal.pone.0074109

55. Vicario S, Moriyama EN, Powell JR. Codon usage in twelve species of Drosophila. BMC Evol Biol 2007;7:226. https://doi.org/10.1186/1471-2148-7-226

56. Liu Q. Analysis of codon usage pattern in the radioresistant bacterium Deinococcus radiodurans. Biosystems 2006;85:99-106. https://doi.org/10.1016/j.biosystems.2005.12.003

57. Anisimova M, Liberles DA. The quest for natural selection in the age of comparative genomics. Heredity (Edinb) 2007;99:567-79. https://doi.org/10.1038/sj.hdy.6801052

58. Mazumder TH, Uddin A, Chakraborty S. Transcription factor gene GATA2: Association of leukemia and nonsynonymous to the synonymous substitution rate across five mammals. Genomics 2016;107:155-61. https://doi.org/10.1016/j.ygeno.2016.02.001

59. Arai YT, Kuzmin IV, Kameoka Y, Botvinkin AD. New Lyssavirus genotype from the lesser mouse-eared bat (Myotis blythii), Kyrghyzstan. Emerg Infect Dis 2003;9:333-7. https://doi.org/10.3201/eid0903.020252

60. Kuzmin IV, Orciari LA, Arai YT, Smith JS, Hanlon CA, Kameoka Y, et al. Bat Lyssaviruses (Aravan and Khujand) from Central Asia: Phylogenetic relationships according to N, P and G gene sequences. Virus Res 2003;97:65-79. https://doi.org/10.1016/S0168-1702(03)00217-X

61. Hyeon JY, Risatti GR, Helal ZH, McGinnis H, Sims M, Hunt A, et al. Whole genome sequencing and phylogenetic analysis of rabies viruses from bats in Connecticut, USA, 2018-2019. Viruses 2021;13:2500. https://doi.org/10.3390/v13122500

62. Bourhy H, Cowley JA, Larrous F, Holmes EC, Walker PJ. Phylogenetic relationships among rhabdoviruses inferred using the L polymerase gene. J Gen Virol 2005;86:2849-58. https://doi.org/10.1099/vir.0.81128-0

63. Guyatt KJ, Twin J, Davis P, Holmes EC, Smith GA, Smith IL, et al. A molecular epidemiological study of Australian bat Lyssavirus. J Gen Virol 2003;84:485-96. https://doi.org/10.1099/vir.0.18652-0

64. Holmes EC, Woelk CH, Kassis R, Bourhy H. Genetic constraints and the adaptive evolution of rabies virus in nature. Virology 2002;292:247-57. https://doi.org/10.1006/viro.2001.1271

Article Metrics
38 Views 14 Downloads 52 Total

Year

Month

Related Search

By author names

Similar Articles