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Designing RNA Secondary Structures in Coding Regions

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Bioinformatics Research and Applications (ISBRA 2012)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 7292))

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Abstract

Sophisticated regulatory structures appear within highly-constrained coding regions of genes. We study the extent to which such structures can be constructed. Can such stem loops appear essentially anywhere within coding regions, or is the potential restricted to rare amino acid sequences? While predicting secondary structures of an RNA sequence is an extensively studied problem in computational biology, the inverse problem, designing sequences based on a known structure is also important. We work on a particular version of the inverse RNA folding problem, where our goal is to achieve a targeted energy level. For a particular RNA structure, we design sequences with the maximum and minimum folding energy while maintaining desired codon distribution. Our major contributions in work is to optimize RNA secondary structure under codon constraints via fast estimation of folding energies following local modification.

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References

  1. Zuker, M., Mathews, D.H., Turner, D.H.: Algorithms and thermodynamics for rna secondary structure prediction (1999)

    Google Scholar 

  2. Jaeger, J., Turner, D.H., Zuker, M.: Improved predictions of secondary structures for rna. Proc. Natl. Acad. Sci. USA 86, 7706–7710 (1989)

    Article  Google Scholar 

  3. Tinoco, I.J., Borer, P., Dengler, B., Levin, M., Uhlenbeck, O., Crothers, D., Bralla, J.: Improved estimation of secondary structure in ribonucleic acids. Nat. New Biol. 246, 40–41 (1973)

    Google Scholar 

  4. Hofacker, I.L., Fontana, W., Stadler, P.F., Bonhoeffer, L.S.: Fast folding and comparison of rna secondary structures. Monatshefte fur Chemie 125, 167–188 (1994)

    Article  Google Scholar 

  5. Cohen, B., Skiena, S.: Natural selection and algorithmic design of mRNA. J. Computational Biology 10, 419–432 (2003)

    Article  Google Scholar 

  6. Cohen, B., Skiena, S.: Optimizing rna secondary structure over all possible encodings of a given protein. In: RECOMB (2000)

    Google Scholar 

  7. Kudla, G., Murray, A., Tollervey, D., Plotkin, J.: Coding-sequence determinants of gene expression in escherichia coli. Science 324, 255–258 (2009)

    Article  Google Scholar 

  8. Plotkin, J., Kudla, G.: Synonymous but not the same: the causes and consequences of codon bias. Nature Reviews Genetics 12, 32–42 (2011)

    Article  Google Scholar 

  9. Tuller, T., Waldman, Y.Y., Kupiec, M., Ruppin, E.: Translation efficiency is determined by both codon bias and folding energy. Natl. Acad. Sci. USA

    Google Scholar 

  10. Sitaraman, V., Hearing, P., Ward, C., Gnatenko, D., Wimmer, E., Mueller, S., Skiena, S., Bahou, W.: Computationally designed adeno-associated virus (aav) rep 78 is efficiently maintained within an adenovirus vector. Proc. National Academy of Sciences 108, 14294–14299 (2011)

    Article  Google Scholar 

  11. Mueller, S., Coleman, R., Papamichail, D., Ward, C., Nimnual, A., Futcher, B., Skiena, S., Wimmer, E.: Live attenuated influenza vaccines by computer-aided rational design. Nature Biotechnology 28 (2010)

    Google Scholar 

  12. Coleman, J., Papamichial, D., Futcher, B., Skiena, S., Mueller, S., Wimmer, E.: Virus attenuation by genome-scale changes in codon-pair bias. Science 320, 1784–1787 (2008)

    Article  Google Scholar 

  13. Zuker, M.: Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res. 31, 3406–3415 (2003)

    Article  Google Scholar 

  14. Mathews, D., Sabina, J., Zuker, M., Turner, D.: Expanded sequence dependence of thermodynamic parameters improves prediction of rna secondary structure. J. Mol. Biol. 288, 911–940 (1999)

    Article  Google Scholar 

  15. Zuker, M., Stiegler, P.: Optimal computer folding of large rna sequences using thermodynamics and auxiliary information. Nucleic Acids Res., 133–148 (1981)

    Google Scholar 

  16. McCaskill, J.: The equilibrium partition function and base pair binding probabilities for rna secondary structure. Biopolymers 29, 1105–1119 (1990)

    Article  Google Scholar 

  17. Wuchty, S., Fontana, W., L.H. I., Schuster, P.: Complete suboptimal folding of rna and the stability of secondary structures. Biopolymers 49, 145–165 (1999)

    Article  Google Scholar 

  18. Shapiro, B.A., Zhang, K.: Comparing multiple rna secondary structures using tree comparisons. Comput. Appl. Biosci. 6, 309–318 (1990)

    Google Scholar 

  19. Hofacker, I.L.: The rules of the evolutionary game for rna: A statistical characterization of the sequence to structure mapping in rna. PhD thesis

    Google Scholar 

  20. Dromi, N., Avihoo, A., Barash, D.: Reconstruction of natural rna sequences from rna shape, thermodynamic stability, mutational robustness, and linguistic complexity by evolutionary computation. Biomol. Struct. Dyn. 26, 147–162 (2008)

    Google Scholar 

  21. Dehiyat, B.I., Mayo, S.L.: De novo protein design: Fully automated sequence selection. Science 278, 82–87 (1997)

    Article  Google Scholar 

  22. Busch, A., Backofen, R.: Info-rna: a server for fast inverse rna folding satisfying sequence constraints. Nucleic Acids Res. (2007)

    Google Scholar 

  23. Avihoo, A., Churkin, A., Barash, D.: Rnaexinv: An extended inverse rna folding from shape and physical attributes to sequences. BMC Bioinformatics

    Google Scholar 

  24. Durbin, R., Eddy, S., Krogh, A., Mitchison, G.: Biological sequence analysis: Probabilistic models of proteins and nucleic acids. Cambridge University Press (1998)

    Google Scholar 

  25. Knudsen, B., Hein, J.: Rna secondary structure prediction using stochastic context-free grammars and evolutionary history. Bioinformatics 15, 446–454 (1999)

    Article  Google Scholar 

  26. Dowell, R., Eddy, S.: Evaluation of several lightweight stochastic context-free grammars for rna secondary structure prediction. BMC Bioinformatics 5 (2004)

    Google Scholar 

  27. Do, C.B., Woods, D.A., Batzoglou, S.: Contrafold: Rna secondary structure prediction without physics-based models. Bioinformatics 22, 90–98 (2006)

    Article  Google Scholar 

  28. Andronescu, M., Condon, A., Hoos, H.H., Mathews, D.H., Murphy, K.P.: Efficient parameter estimation for rna secondary structure prediction. Bioinformatics 23 (2007)

    Google Scholar 

  29. Andronescu, M.: Computational approaches for rna energy parameter estimation. PhD thesis, University of British Columbia, Vancouver, Canada

    Google Scholar 

  30. Zakov, S., Goldberg, Y., Elhadad, M., Ziv-Ukelson, M.: Rich Parameterization Improves RNA Structure Prediction. In: Bafna, V., Sahinalp, S.C. (eds.) RECOMB 2011. LNCS, vol. 6577, pp. 546–562. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  31. Doshi, K.J., Cannone, J.J., Cobaugh, C.W., Gutell, R.R.: Evaluation of the suitability of free-energy minimization using nearest-neighbor energy parameters for rna secondary structure prediction. BMC Bioinformatics 5, 105 (2004)

    Article  Google Scholar 

  32. Metropolis, N., Rosenbluth, A.W., Rosenbluth, M.N., Teller, A.H., Teller, E.: Equation of state by fast computing machines. The Journal of Chemical Physics 21, 1087–1092 (1953)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science, Stony Brook University, Stony Brook, NY, 11794-4400, USA

    Rukhsana Yeasmin & Steven Skiena

Authors
  1. Rukhsana Yeasmin
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  2. Steven Skiena
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Editor information

Editors and Affiliations

  1. Departments of Bioengineering and Electrical Engineering, University of Texas at Dallas, 75080, Richardson, TX, USA

    Leonidas Bleris

  2. Department of Computer Science and Engineering, University of Connecticut, 06269, Storrs, CT, USA

    Ion Măndoiu

  3. Department of Biological Sciences, Carnegie Mellon University, 15213, Pittsburgh, PA, USA

    Russell Schwartz

  4. School of Information Science and Engineering, Central South University, 410083, Changsha, China

    Jianxin Wang

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© 2012 Springer-Verlag Berlin Heidelberg

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Yeasmin, R., Skiena, S. (2012). Designing RNA Secondary Structures in Coding Regions. In: Bleris, L., Măndoiu, I., Schwartz, R., Wang, J. (eds) Bioinformatics Research and Applications. ISBRA 2012. Lecture Notes in Computer Science(), vol 7292. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30191-9_28

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  • DOI: https://doi.org/10.1007/978-3-642-30191-9_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30190-2

  • Online ISBN: 978-3-642-30191-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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