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Virology journal2013; 10; 356; doi: 10.1186/1743-422X-10-356

Comprehensive analysis of the overall codon usage patterns in equine infectious anemia virus.

Abstract: Equine infectious anemia virus (EIAV) is an important animal model for understanding the relationship between viral persistence and the host immune response during lentiviral infections. Comparison and analysis of the codon usage model between EIAV and its hosts is important for the comprehension of viral evolution. In our study, the codon usage pattern of EIAV was analyzed from the available 29 full-length EIAV genomes through multivariate statistical methods. Results: Effective number of codons (ENC) suggests that the codon usage among EIAV strains is slightly biased. The ENC-plot analysis demonstrates that mutation pressure plays a substantial role in the codon usage pattern of EIAV, whereas other factors such as geographic distribution and host translation selection also take part in the process of EIAV evolution. Comparative analysis of codon adaptation index (CAI) values among EIAV and its hosts suggests that EIAV utilize the translational resources of horse more efficiently than that of donkey. Conclusions: The codon usage bias in EIAV is slight and mutation pressure is the main factor that affects codon usage variation in EIAV. These results suggest that EIAV genomic biases are the result of the co-evolution of genome composition and the ability to evade the host's immune response.
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Publication Date: 2013-12-20 PubMed ID: 24359511PubMed Central: PMC3878193DOI: 10.1186/1743-422X-10-356Google Scholar: Lookup
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  • Non-U.S. Gov't

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The research paper studies the patterning of codon usage within the Equine Infectious Anemia Virus (EIAV). This is done by comparing the virus’s codon usage pattern with those of its hosts and asserting that slight bias, mutation pressure, and other factors contribute to EIAV’s evolutionary process.

Codon Usage Analysis

  • The paper uses 29 full-length EIAV genomes and employs multivariate statistical methods to carry out a comprehensive analysis of EIAV’s codon usage.
  • The Effective Number of Codons (ENC) revealed a slight codon usage bias among different EIAV strains.

Role of Mutation Pressure

  • ENC-plot analysis showed that mutation pressure plays a significant role in the codon usage pattern of EIAV.
  • The authors found that EIAV’s codon bias and its genomic biases are heavily influenced by mutation pressure, which subsequently plays a role in viral evolution.

Other Factors Influencing Codon Usage

  • Apart from mutation pressure, other factors including geographic distribution and translation selections by the host organism also influence EIAV’s viral evolution.
  • The study notes that these elements participate in altering the codon usage pattern, impacting the path of EIAV’s evolution.

Comparison with Hosts

  • Comparative analysis was conducted between the Codon Adaptation Index (CAI) values of EIAV and its hosts.
  • The results indicated that EIAV employs the translational resources of horses more efficiently than those of donkeys.
  • This usage of host resources contributes to the slight codon usage bias seen in EIAV.

Important Conclusions

  • The paper concludes that codon usage bias in EIAV is slight but pivotal.
  • In addition to mutation pressure, the study highlights the role of co-evolution of the viral genome and the ability to dodge the host’s immune response in shaping codon usage bias.

Cite This Article

APA
Yin X, Lin Y, Cai W, Wei P, Wang X. (2013). Comprehensive analysis of the overall codon usage patterns in equine infectious anemia virus. Virol J, 10, 356. https://doi.org/10.1186/1743-422X-10-356

Publication

Virology journal
ISSN: 1743-422X
NlmUniqueID: 101231645
Country: England
Language: English
Volume: 10
Pages: 356

Researcher Affiliations

Yin, Xin
    Lin, Yuezhi
      Cai, Weigang
        Wei, Ping
        • Division of Livestock Infectious Diseases, State Key Laboratory of Veterinary Biotechnology, Harbin Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Harbin 150001, PR China. weiiping@yahoo.com.cn.
        Wang, Xiaojun

          MeSH Terms

          • Codon / analysis
          • Computational Biology
          • Host-Pathogen Interactions
          • Infectious Anemia Virus, Equine / genetics
          • Selection, Genetic
          • Sequence Analysis, DNA

          References

          This article includes 25 references
          1. Leroux C, Cadoré JL, Montelaro RC. Equine Infectious Anemia Virus (EIAV): what has HIV's country cousin got to tell us?. Vet Res 2004 Jul-Aug;35(4):485-512.
            doi: 10.1051/vetres:2004020pubmed: 15236678google scholar: lookup
          2. Craigo JK, Montelaro RC. EIAV envelope diversity: shaping viral persistence and encumbering vaccine efficacy.. Curr HIV Res 2010 Jan;8(1):81-6.
            doi: 10.2174/157016210790416398pubmed: 20210783google scholar: lookup
          3. Cook SJ, Cook RF, Montelaro RC, Issel CJ. Differential responses of Equus caballus and Equus asinus to infection with two pathogenic strains of equine infectious anemia virus.. Vet Microbiol 2001 Mar 20;79(2):93-109.
            doi: 10.1016/S0378-1135(00)00348-5pubmed: 11230932google scholar: lookup
          4. Hershberg R, Petrov DA. Selection on codon bias.. Annu Rev Genet 2008;42:287-99.
            doi: 10.1146/annurev.genet.42.110807.091442pubmed: 18983258google scholar: lookup
          5. Karlin S, Mrázek J. What drives codon choices in human genes?. J Mol Biol 1996 Oct 4;262(4):459-72.
            doi: 10.1006/jmbi.1996.0528pubmed: 8893856google scholar: lookup
          6. Shackelton LA, Holmes EC. The evolution of large DNA viruses: combining genomic information of viruses and their hosts.. Trends Microbiol 2004 Oct;12(10):458-65.
            doi: 10.1016/j.tim.2004.08.005pubmed: 15381195google scholar: lookup
          7. Ma XX, Feng YP, Chen L, Zhao YQ, Liu JL, Guo JZ, Guo PH, Yang JT, Lu JX, Chen SE, Ma ZR. Mapping codon usage in sequence regions flanking cleavage positions in the hepatitis A virus polyprotein.. Genet Mol Res 2013 Jul 8;12(3):2306-19.
            doi: 10.4238/2013.July.8.11pubmed: 23884773google scholar: lookup
          8. Zhang Y, Liu Y, Liu W, Zhou J, Chen H, Wang Y, Ma L, Ding Y, Zhang J. Analysis of synonymous codon usage in hepatitis A virus.. Virol J 2011 Apr 16;8:174.
            doi: 10.1186/1743-422X-8-174pmc: PMC3087699pubmed: 21496278google scholar: lookup
          9. Moratorio G, Iriarte A, Moreno P, Musto H, Cristina J. A detailed comparative analysis on the overall codon usage patterns in West Nile virus.. Infect Genet Evol 2013 Mar;14:396-400.
            pubmed: 23333335doi: 10.1016/j.meegid.2013.01.001google scholar: lookup
          10. Zhou JH, You YN, Chen HT, Zhang J, Ma LN, Ding YZ, Pejsak Z, Liu YS. The effects of the synonymous codon usage and tRNA abundance on protein folding of the 3C protease of foot-and-mouth disease virus.. Infect Genet Evol 2013 Jun;16:270-4.
            pubmed: 23499709doi: 10.1016/j.meegid.2013.02.017google scholar: lookup
          11. Goñi N, Iriarte A, Comas V, Soñora M, Moreno P, Moratorio G, Musto H, Cristina J. Pandemic influenza A virus codon usage revisited: biases, adaptation and implications for vaccine strain development.. Virol J 2012 Nov 8;9:263.
            doi: 10.1186/1743-422X-9-263pmc: PMC3543350pubmed: 23134595google scholar: lookup
          12. van der Kuyl AC, Berkhout B. The biased nucleotide composition of the HIV genome: a constant factor in a highly variable virus.. Retrovirology 2012 Nov 6;9:92.
            doi: 10.1186/1742-4690-9-92pmc: PMC3511177pubmed: 23131071google scholar: lookup
          13. Pandit A, Sinha S. Differential trends in the codon usage patterns in HIV-1 genes.. PLoS One 2011;6(12):e28889.
            doi: 10.1371/journal.pone.0028889pmc: PMC3245234pubmed: 22216135google scholar: lookup
          14. Kypr J, Mrázek J. Unusual codon usage of HIV.. Nature 1987 May 7-13;327(6117):20.
            pubmed: 3646480doi: 10.1038/327020a0google scholar: lookup
          15. van Hemert FJ, Berkhout B. The tendency of lentiviral open reading frames to become A-rich: constraints imposed by viral genome organization and cellular tRNA availability.. J Mol Evol 1995 Aug;41(2):132-40.
            pubmed: 7666442doi: 10.1007/BF00170664google scholar: lookup
          16. Sharp PM, Li WH. An evolutionary perspective on synonymous codon usage in unicellular organisms.. J Mol Evol 1986;24(1-2):28-38.
            doi: 10.1007/BF02099948pubmed: 3104616google scholar: lookup
          17. Comeron JM, Aguadé M. An evaluation of measures of synonymous codon usage bias.. J Mol Evol 1998 Sep;47(3):268-74.
            doi: 10.1007/PL00006384pubmed: 9732453google scholar: lookup
          18. Puigbò P, Bravo IG, Garcia-Vallvé S. E-CAI: a novel server to estimate an expected value of Codon Adaptation Index (eCAI).. BMC Bioinformatics 2008 Jan 29;9:65.
            doi: 10.1186/1471-2105-9-65pmc: PMC2246156pubmed: 18230160google scholar: lookup
          19. Tao P, Dai L, Luo M, Tang F, Tien P, Pan Z. Analysis of synonymous codon usage in classical swine fever virus.. Virus Genes 2009 Feb;38(1):104-12.
            doi: 10.1007/s11262-008-0296-zpmc: PMC7089228pubmed: 18958611google scholar: lookup
          20. Zielonka J, Bravo IG, Marino D, Conrad E, Perković M, Battenberg M, Cichutek K, Münk C. Restriction of equine infectious anemia virus by equine APOBEC3 cytidine deaminases.. J Virol 2009 Aug;83(15):7547-59.
            doi: 10.1128/JVI.00015-09pmc: PMC2708611pubmed: 19458006google scholar: lookup
          21. Bogerd HP, Tallmadge RL, Oaks JL, Carpenter S, Cullen BR. Equine infectious anemia virus resists the antiretroviral activity of equine APOBEC3 proteins through a packaging-independent mechanism.. J Virol 2008 Dec;82(23):11889-901.
            doi: 10.1128/JVI.01537-08pmc: PMC2583693pubmed: 18818324google scholar: lookup
          22. Capomaccio S, Cappelli K, Cook RF, Nardi F, Gifford R, Marenzoni ML, Passamonti F. Geographic structuring of global EIAV isolates: a single origin for New World strains?. Virus Res 2012 Feb;163(2):656-9.
            doi: 10.1016/j.virusres.2011.11.011pubmed: 22119901google scholar: lookup
          23. Zheng YH, Sentsui H, Kono Y, Ikuta K. Mutations occurring during serial passage of Japanese equine infectious anemia virus in primary horse macrophages.. Virus Res 2000 Jun;68(1):93-8.
            doi: 10.1016/S0168-1702(00)00147-7pubmed: 10930666google scholar: lookup
          24. Dong JB, Zhu W, Cook FR, Goto Y, Horii Y, Haga T. Identification of a novel equine infectious anemia virus field strain isolated from feral horses in southern Japan.. J Gen Virol 2013 Feb;94(Pt 2):360-365.
            doi: 10.1099/vir.0.047498-0pubmed: 23100364google scholar: lookup
          25. Puigbò P, Bravo IG, Garcia-Vallve S. CAIcal: a combined set of tools to assess codon usage adaptation.. Biol Direct 2008 Sep 16;3:38.
            doi: 10.1186/1745-6150-3-38pmc: PMC2553769pubmed: 18796141google scholar: lookup

          Citations

          This article has been cited 6 times.
          1. Câmara RJF, Bueno BL, Resende CF, Balasuriya UBR, Sakamoto SM, Reis JKPD. Viral Diseases that Affect Donkeys and Mules.. Animals (Basel) 2020 Nov 25;10(12).
            doi: 10.3390/ani10122203pubmed: 33255568google scholar: lookup
          2. He W, Wang N, Tan J, Wang R, Yang Y, Li G, Guan H, Zheng Y, Shi X, Ye R, Su S, Zhou J. Comprehensive codon usage analysis of porcine deltacoronavirus.. Mol Phylogenet Evol 2019 Dec;141:106618.
            doi: 10.1016/j.ympev.2019.106618pubmed: 31536759google scholar: lookup
          3. Zhang X, Cai Y, Zhai X, Liu J, Zhao W, Ji S, Su S, Zhou J. Comprehensive Analysis of Codon Usage on Rabies Virus and Other Lyssaviruses.. Int J Mol Sci 2018 Aug 14;19(8).
            doi: 10.3390/ijms19082397pubmed: 30110957google scholar: lookup
          4. Chen Y, Xu Q, Yuan X, Li X, Zhu T, Ma Y, Chen JL. Analysis of the codon usage pattern in Middle East Respiratory Syndrome Coronavirus.. Oncotarget 2017 Dec 15;8(66):110337-110349.
            doi: 10.18632/oncotarget.22738pubmed: 29299151google scholar: lookup
          5. Bera BC, Virmani N, Kumar N, Anand T, Pavulraj S, Rash A, Elton D, Rash N, Bhatia S, Sood R, Singh RK, Tripathi BN. Genetic and codon usage bias analyses of polymerase genes of equine influenza virus and its relation to evolution.. BMC Genomics 2017 Aug 23;18(1):652.
            doi: 10.1186/s12864-017-4063-1pubmed: 28830350google scholar: lookup
          6. Kumar N, Bera BC, Greenbaum BD, Bhatia S, Sood R, Selvaraj P, Anand T, Tripathi BN, Virmani N. Revelation of Influencing Factors in Overall Codon Usage Bias of Equine Influenza Viruses.. PLoS One 2016;11(4):e0154376.
            doi: 10.1371/journal.pone.0154376pubmed: 27119730google scholar: lookup
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