EloE: Web application for estimation of gene translation elongation efficiency

  • V. S. Sokolov
  • B. S. Zuraev
  • S. A. Lashin
  • Yu. G. Matushkin
Article
  • 14 Downloads

Abstract

Many modern investigations study important gene characteristic such as the efficiency of its expression. As is known, it is determined at the levels of transcription, translation, posttranslational modification, etc. The EloE (Elongation Efficiency) program, which sorts the organism genes in order of decreasing their supposed translation elongation rate based on the analysis of their nucleotide sequences, is presented in the work. The obtained theoretical data are significantly correlated to the available experimental data on gene expression in different organisms (for example, S. cerevisiae and H. pylori). The program also detects preferential codons in the organism genome and constructs the distribution of the stability of potential secondary structures near the mRNA 5′- and 3′-ends. The program can be used for preliminarily estimating the level of gene expression in the studied organism (for which the experimental data are not available yet). The results of EloE can be transferred in third-party program instruments that model artificial genetic constructions for genetically engineered experiments.

Keywords

elongation efficiency index web application translation efficiency secondary structures 

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References

  1. Bennetzen, J.L. and Hall, B.D., Codon selection in yeast, J. Biol. Chem., 1982, vol. 257, no. 6, pp. 3026–3031.PubMedGoogle Scholar
  2. Eck, S. and Stephan, W., Determining the relationship of gene expression and global mRNA stability in Drosophila melanogaster and Escherichia coli using linear models, Gene, 2008, vol. 1, no. 1, pp. 102–107.CrossRefGoogle Scholar
  3. Hofacker, I.L., Vienna RNA secondary structure server, Nucleic Acids Res., 2003, vol. 31, no. 13, pp. 3429–3431.PubMedCentralCrossRefPubMedGoogle Scholar
  4. Ikemura, T., Correlation between the abundance of Escherichia coli transfer RNAs and the occurrence of the respective codons in its protein genes: a proposal for a synonymous codon choice that is optimal for the E. coli system, J. Mol. Biol., 1981, vol. 151, no. 3, pp. 389–409.CrossRefPubMedGoogle Scholar
  5. Likhoshvai, V.A. and Matushkin, Yu.G., Nucleotide composition-based prediction of gene expression efficacy, Mol. Biol. (Moscow), 2000, vol. 34, no. 3, pp. 345–350.CrossRefGoogle Scholar
  6. Likhoshvai, V.A. and Matushkin, Y.G., Differentiation of single cell organisms according to elongation stages crucial for gene expression efficacy, FEBS Lett., 2002, vol. 1, no. 1, pp. 87–92.CrossRefGoogle Scholar
  7. Lopinski, J.D., Dinman, J.D., and Bruenn, J.A., Kinetics of ribosomal pausing during programmed-1 translational frame shifting, Mol. Cell. Biol., 2000, vol. 20, no. 4, pp. 1095–1103.PubMedCentralCrossRefPubMedGoogle Scholar
  8. Matushkin, Yu.G., et al., Efficacy of elongation yeast genes is correlated with the nucleosome packing density in the 5′-untranslated region, Matem. Biol. Bioinform., 2013, vol. 8, no. 1, pp. 248–257.CrossRefGoogle Scholar
  9. McLachlan, A.D., Staden, R., and Boswell, D.R., A method for measuring the non-random bias of a codon usage table, Nucleic Acids Res., 1984, vol. 12, no. 24, pp. 9567–9575.PubMedCentralCrossRefPubMedGoogle Scholar
  10. Sharp, P.M. and Li, W.H., An evolutionary perspective on synonymous codon usage in unicellular organisms, J. Mol. Evol., 1986, vol. 24, nos. 1–2, pp. 28–38.CrossRefPubMedGoogle Scholar
  11. Sokolov, V.S., Likhoshvai, V.A., and Matushkin, Y.G., Gene expression and secondary mRNA structures in different mycoplasma species, Russ. J. Genet. Appl. Res., 2014, vol. 4, no. 3, pp. 208–217.CrossRefGoogle Scholar
  12. Takyar, S., Hickerson, R.P., and Noller, H.F., mRNA helicase activity of the ribosome, Cell, 2005, vol. 120, no. 1, pp. 49–58.CrossRefPubMedGoogle Scholar
  13. Thanaraj, T.A. and Argos, P., Ribosome-mediated translational pause and protein domain organization, Protein Sci., 1996, vol. 5, no. 8, pp. 1594–1612.PubMedCentralCrossRefPubMedGoogle Scholar
  14. Vladimirov, N.V., Likhoshvai, V.A., and Matushkin, Y.G., Correlation of codon biases and potential secondary structures with mRNA translation efficiency in unicellular organisms, Mol. Biol., 2007, vol. 41, no. 5, pp. 843–850.CrossRefGoogle Scholar
  15. Zuker, M., Mfold web server for nucleic acid folding and hybridization prediction, Nucleic Acids Res., 2003, vol. 31, no. 13, pp. 3406–3415.PubMedCentralCrossRefPubMedGoogle Scholar
  16. Zuker, M., Mathews, D.H., and Turner, D.H., Algorithms and thermodynamics for rna secondary structure prediction: a practical guide, in RNA Biochemistry and Biotechnology, Netherlands: Springer, 1999, pp. 11–43.CrossRefGoogle Scholar

Copyright information

© Pleiades Publishing, Ltd. 2015

Authors and Affiliations

  • V. S. Sokolov
    • 1
  • B. S. Zuraev
    • 1
    • 2
  • S. A. Lashin
    • 1
    • 2
  • Yu. G. Matushkin
    • 1
    • 2
  1. 1.Institute of Cytology and Genetics, Siberian BranchRussian Academy of SciencesNovosibirskRussia
  2. 2.Novosibirsk National Research State UniversityNovosibirskRussia

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