Abstract
We present biRNA, a novel algorithm for prediction of binding sites between two RNAs based on minimization of binding free energy. Similar to RNAup approach [30], we assume the binding free energy is the sum of accessibility and the interaction free energies. Our algorithm maintains tractability and speed and also has two important advantages over previous similar approaches: (1) biRNA is able to predict multiple simultaneous binding sites and (2) it computes a more accurate interaction free energy by considering both intramolecular and intermolecular base pairing. Moreover, biRNA can handle crossing interactions as well as hairpins interacting in a zigzag fashion. To deal with simultaneous accessibility of binding sites, our algorithm models their joint probability of being unpaired. Since computing the exact joint probability distribution is intractable, we approximate the joint probability by a polynomially representable graphical model namely a Chow-Liu tree-structured Markov Random Field. Experimental results show that biRNA outperforms RNAup and also support the accuracy of our approach. Our proposed Bayesian approximation of the Boltzmann joint probability distribution provides a powerful, novel framework that can also be utilized in other applications.
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References
Alkan, C., Karakoc, E., Nadeau, J.H., Cenk Sahinalp, S., Zhang, K.: RNA-RNA interaction prediction and antisense RNA target search. Journal of Computational Biology 13(2), 267–282 (2006)
Andronescu, M., Zhang, Z.C., Condon, A.: Secondary structure prediction of interacting RNA molecules. J. Mol. Biol. 345, 987–1001 (2005)
Argaman, L., Altuvia, S.: fhlA repression by OxyS RNA: kissing complex formation at two sites results in a stable antisense-target RNA complex. J. Mol. Biol. 300, 1101–1112 (2000)
Asano, K., Mizobuchi, K.: Structural analysis of late intermediate complex formed between plasmid ColIb-P9 Inc RNA and its target RNA. How does a single antisense RNA repress translation of two genes at different rates? J. Biol. Chem. 275, 1269–1274 (2000)
Bossi, L., Figueroa-Bossi, N.: A small RNA downregulates LamB maltoporin in Salmonella. Mol. Microbiol. 65, 799–810 (2007)
Busch, A., Richter, A.S., Backofen, R.: IntaRNA: Efficient prediction of bacterial sRNA targets incorporating target site accessibility and seed regions. Bioinformatics 24(24), 2849–2856 (2008)
Chazelle, B.: A minimum spanning tree algorithm with inverse-Ackermann type complexity. J. ACM 47(6), 1028–1047 (2000)
Chen, S., Zhang, A., Blyn, L.B., Storz, G.: MicC, a second small-RNA regulator of Omp protein expression in Escherichia coli. J. Bacteriol. 186, 6689–6697 (2004)
Chitsaz, H., Salari, R., Sahinalp, S.C., Backofen, R.: A partition function algorithm for interacting nucleic acid strands. Bioinformatics 25(12), i365–i373 (2009)
Chow, C., Liu, C.: Approximating discrete probability distributions with dependence trees. IEEE Transactions on Information Theory 14(3), 462–467 (1968)
Cooper, G.F.: The computational complexity of probabilistic inference using bayesian belief networks (research note). Artif. Intell. 42(2-3), 393–405 (1990)
Dimitrov, R.A., Zuker, M.: Prediction of hybridization and melting for double-stranded nucleic acids. Biophysical Journal 87, 215–226 (2004)
Dirks, R.M., Bois, J.S., Schaeffer, J.M., Winfree, E., Pierce, N.A.: Thermodynamic analysis of interacting nucleic acid strands. SIAM Review 49(1), 65–88 (2007)
Dirks, R.M., Pierce, N.A.: A partition function algorithm for nucleic acid secondary structure including pseudoknots. Journal of Computational Chemistry 24(13), 1664–1677 (2003)
Geissmann, T.A., Touati, D.: Hfq, a new chaperoning role: binding to messenger RNA determines access for small RNA regulator. EMBO J. 23, 396–405 (2004)
Gottesman, S.: Micros for microbes: non-coding regulatory RNAs in bacteria. Trends in Genetics 21(7), 399–404 (2005)
Jordan, M.I., Weiss, Y.: Graphical models: probabilistic inference. In: Arbib, M. (ed.) Handbook of Neural Networks and Brain Theory. MIT Press, Cambridge (2002)
Kato, Y., Akutsu, T., Seki, H.: A grammatical approach to RNA-RNA interaction prediction. Pattern Recognition 42(4), 531–538 (2009)
Kawamoto, H., Koide, Y., Morita, T., Aiba, H.: Base-pairing requirement for RNA silencing by a bacterial small RNA and acceleration of duplex formation by Hfq. Mol. Microbiol. 61, 1013–1022 (2006)
Kolb, F.A., Engdahl, H.M., Slagter-Jger, J.G., Ehresmann, B., Ehresmann, C., Westhof, E., Wagner, E.G., Romby, P.: Progression of a loop-loop complex to a four-way junction is crucial for the activity of a regulatory antisense RNA. EMBO J. 19, 5905–5915 (2000)
Kolb, F.A., Malmgren, C., Westhof, E., Ehresmann, C., Ehresmann, B., Wagner, E.G., Romby, P.: An unusual structure formed by antisense-target RNA binding involves an extended kissing complex with a four-way junction and a side-by-side helical alignment. RNA 6, 311–324 (2000)
Lu, Z.J., Mathews, D.H.: Efficient siRNA selection using hybridization thermodynamics. Nucleic Acids Res. 36, 640–647 (2008)
Majdalani, N., Hernandez, D., Gottesman, S.: Regulation and mode of action of the second small RNA activator of RpoS translation, RprA. Mol. Microbiol. 46, 813–826 (2002)
Markham, N.R., Zuker, M.: UNAFold: software for nucleic acid folding and hybridization. Methods Mol. Biol. 453, 3–31 (2008)
Massé, E., Gottesman, S.: A small RNA regulates the expression of genes involved in iron metabolism in Escherichia coli. Proc. Natl. Acad. Sci. U.S.A. 99, 4620–4625 (2002)
Mathews, D.H., Sabina, J., Zuker, M., Turner, D.H.: Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure. J. Mol. Biol. 288, 911–940 (1999)
McCaskill, J.S.: The equilibrium partition function and base pair binding probabilities for RNA secondary structure. Biopolymers 29, 1105–1119 (1990)
Mneimneh, S.: On the approximation of optimal structures for RNA-RNA interaction. IEEE/ACM Transactions on Computational Biology and Bioinformatics (to appear)
Møller, T., Franch, T., Udesen, C., Gerdes, K., Valentin-Hansen, P.: Spot 42 RNA mediates discoordinate expression of the E. coli galactose operon. Genes Dev. 16, 1696–1706 (2002)
Mückstein, U., Tafer, H., Bernhart, S.H., Hernandez-Rosales, M., Vogel, J., Stadler, P.F., Hofacker, I.L.: Translational control by RNA-RNA interaction: Improved computation of RNA-RNA binding thermodynamics. In: Elloumi, M., Küng, J., Linial, M., Murphy, R.F., Schneider, K., Toma, C. (eds.) BIRD. Communications in Computer and Information Science, vol. 13, pp. 114–127. Springer, Heidelberg (2008)
Nussinov, R., Piecznik, G., Grigg, J.R., Kleitman, D.J.: Algorithms for loop matchings. SIAM Journal on Applied Mathematics 35, 68–82 (1978)
Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, San Francisco (1988)
Pervouchine, D.D.: IRIS: intermolecular RNA interaction search. Genome Inform. 15, 92–101 (2004)
Rasmussen, A.A., Eriksen, M., Gilany, K., Udesen, C., Franch, T., Petersen, C., Valentin-Hansen, P.: Regulation of ompA mRNA stability: the role of a small regulatory RNA in growth phase-dependent control. Mol. Microbiol. 58, 1421–1429 (2005)
Rehmsmeier, M., Steffen, P., Hochsmann, M., Giegerich, R.: Fast and effective prediction of microRNA/target duplexes. RNA 10, 1507–1517 (2004)
Repoila, F., Majdalani, N., Gottesman, S.: Small non-coding RNAs, co-ordinators of adaptation processes in Escherichia coli: the RpoS paradigm. Mol. Microbiol. 48, 855–861 (2003)
Rivas, E., Eddy, S.R.: A dynamic programming algorithm for RNA structure prediction including pseudoknots. J. Mol. Biol. 285, 2053–2068 (1999)
Schmidt, M., Zheng, P., Delihas, N.: Secondary structures of Escherichia coli antisense micF RNA, the 5’-end of the target ompF mRNA, and the RNA/RNA duplex. Biochemistry 34, 3621–3631 (1995)
Sharma, C.M., Darfeuille, F., Plantinga, T.H., Vogel, J.: A small RNA regulates multiple ABC transporter mRNAs by targeting C/A-rich elements inside and upstream of ribosome-binding sites. Genes Dev. 21, 2804–2817 (2007)
Storz, G.: An expanding universe of noncoding RNAs. Science 296(5571), 1260–1263 (2002)
Tafer, H., Ameres, S.L., Obernosterer, G., Gebeshuber, C.A., Schroeder, R., Martinez, J., Hofacker, I.L.: The impact of target site accessibility on the design of effective siRNAs. Nat. Biotechnol. 26, 578–583 (2008)
Tafer, H., Hofacker, I.L.: RNAplex: a fast tool for RNA-RNA interaction search. Bioinformatics 24(22), 2657–2663 (2008)
Tinoco, I., Uhlenbeck, O.C., Levine, M.D.: Estimation of secondary structure in ribonucleic acids. Nature 230, 362–367 (1971)
Vogel, J., Argaman, L., Wagner, E.G., Altuvia, S.: The small RNA IstR inhibits synthesis of an SOS-induced toxic peptide. Curr. Biol. 14, 2271–2276 (2004)
Walton, S.P., Stephanopoulos, G.N., Yarmush, M.L., Roth, C.M.: Thermodynamic and kinetic characterization of antisense oligodeoxynucleotide binding to a structured mRNA. Biophys. J. 82, 366–377 (2002)
Waterman, M.S., Smith, T.F.: RNA secondary structure: A complete mathematical analysis. Math. Biosc. 42, 257–266 (1978)
Zuker, M., Stiegler, P.: Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information. Nucleic Acids Research 9(1), 133–148 (1981)
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Chitsaz, H., Backofen, R., Sahinalp, S.C. (2009). biRNA: Fast RNA-RNA Binding Sites Prediction. In: Salzberg, S.L., Warnow, T. (eds) Algorithms in Bioinformatics. WABI 2009. Lecture Notes in Computer Science(), vol 5724. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04241-6_3
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DOI: https://doi.org/10.1007/978-3-642-04241-6_3
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