RNA Secondary Structure Analysis Using The RNAshapes Package
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- Abstract
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- Literature Cited
Abstract
This unit shows how to use the RNAshapes package for the prediction of the secondary structure of a single RNA sequence using either minimum free energy methods or weighted ensemble information. It also includes a protocol for the consensus prediction of a set of related sequences. Curr. Protoc. Bioinform. 26:12.8.1?12.8.17. © 2009 by John Wiley & Sons, Inc.
Keywords: RNA secondary structure; minimum free energy; Boltzmann weighted ensemble; consensus structure; software package; suboptimal folding space; graphical user interface
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PDF or HTML at Wiley Online LibraryTable of Contents
- Introduction
- Basic Explanations
- Basic Protocol 1: Minimum Free Energy Prediction of Shape Representative Structures
- Basic Protocol 2: Probabilistic Shape Analysis
- Basic Protocol 3: Comparative Shapes Analysis
- Support Protocol 1: Installation of the RNAshapes Package
- Commentary
- Literature Cited
- Figures
- Tables
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-
Figure 12.8.1 Graphical illustration of shape abstraction. Features having the same color in the plot as well as the dot‐bracket and the shape notation mark up corresponding substructures. View Image -
Figure 12.8.2 Sample session of RNAshapes with a 5S rRNA sequence. (A ) Command‐line output of RNAshapes for the example sequence. (B to D ) Shreps of the best three predicted shape classes. View Image -
Figure 12.8.3 (A ) Probabilistic shape analysis of the Vibrio vulnificus add A riboswitch (Rieder et al., ) sequence. The non‐adenine‐binding structure with the stable terminator is formed in the shrep of shape 1 ([][][]) holding 60% of the total Boltzmann probability mass (B ). The adenine‐binding structure with the multiloop is formed in shape 2 ([[][]][]) with 32% (C ). For reason of space, the option ‐S was used to split sequence and structures after 60 nucleotides. Also, the output shown here is truncated to the first five predicted shapes. View Image -
Figure 12.8.4 Output of the probability sampling procedure for the same sequence in Figure , for reason of space also truncated after the first five shapes. The highly probable shapes are estimated accurately. View Image -
Figure 12.8.5 Sample session of consensus shape prediction with a set of five 5S rRNA sequence. (A ) Output of the consensus mode of RNAshapes . Only the highest ranking shape is displayed above. Many other, lower ranking shapes are not shown. (B ) Consensus structure alignment produced by RNAforester . The less conserved a base pair is, the lighter it is drawn. View Image -
Figure 12.8.6 A screenshot of the dedicated Windows graphical user interface of RNAshapes . View Image
Videos
Literature Cited
| Berezikov, E., van Tetering, G., Verheul, M., van de Belt, J., van Laake, L., Vos, J., Verloop, R., van de Wetering, M., Guryev, V., Takada, S., van Zonneveld, A.J., Mano, H., Plasterk, R., and Cuppen, E. 2006. Many novel mammalian microRNA candidates identified by extensive cloning and RAKE analysis. Genome Res. 16:1289‐1298. | |
| Ding, Y. and Lawrence, C.E. 2003. A statistical sampling algorithm for RNA secondary structure prediction. Nucleic Acids Res. 31:7280‐7301. | |
| Doshi, K., Cannone, J., Cobaugh, C., and Gutell, R. 2004. Evaluation of the suitability of free‐energy minimization using nearest‐neighbor energy parameters for RNA secondary structure prediction. BMC Bioinformatics 5:105 | |
| Flamm, C., Hofacker, I.L., Stadler, P.F., and Wolfinger, M.T. 2002. Barrier trees of degenerate landscapes. Z. Phys. Chem. 216:1‐19. | |
| Gardner, P.P. and Giegerich, R. 2004. A comprehensive comparison of comparative RNA structure prediction approaches. BMC Bioinformatics 5:140. | |
| Giegerich, R., Haase, D., and Rehmsmeier, M. 1999. Prediction and visualization of structural switches in RNA. In Proceedings of the 1999 Pacific Symposium on Biocomputing 4:126‐137. World Scientific Publishing, Singapore. | |
| Giegerich, R., Voss, B., and Rehmsmeier, M. 2004. Abstract shapes of RNA. Nucleic Acids Res. 32:4843‐4851. | |
| Höchsmann, M., Voss, B., and Giegerich, R. 2004. Pure multiple RNA secondary structure alignments: A progressive profile approach. IEEE/ACM Trans. Comput. Biol. Bioinform. 1:53‐62. | |
| Hofacker, I.L. 2004. RNA secondary structure analysis using the Vienna RNA package. Curr. Protoc. Bioinform. 4:12.2.1‐12.2.12 | |
| Hofacker, I.L., Fekete, M., and Stadler, P.F. 2002. Secondary structure prediction for aligned RNA sequences. J. Mol. Biol. 319:1059‐1066. | |
| Hofacker, I.L., Fontana, W., Stadler, P.F., Bonhoeffer, S., Tacker, M., and Schuster, P. 1994. Fast folding and comparison of RNA secondary structures. Monatsh. Chem. 125:167‐188. | |
| Janssen, S., Reeder, J., and Giegerich, R. 2008. Shape based indexing for faster search of RNA family databases. BMC Bioinformatics 9:131. | |
| Lu, J., Shen, Y., Wu, Q., Kumar, S., He, B., Shi, S., Carthew, R.W., Wang, S.M., and Wu, C.‐I. 2008. The birth and death of microRNA genes in Drosophila. Nat. Genet. 40:351‐355. | |
| Mathews, D.H. 2006. RNA secondary structure analysis using RNAstructure. Curr. Protoc. Bioinform. 13:12.6.1‐12.6.14. | |
| Mathews, D.H., Sabina, J., Zuker, M. and Turner, D.H. 1999. Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure. J. Mol. Biol. 288:911‐940. | |
| McCaskill, J.S. 1990. The equilibrium partition function and base pair binding probabilities for RNA secondary structure. Biopolymers 29:1105‐1119. | |
| Meyer, I.M. and Miklós, I. 2004. Co‐transcriptional folding is encoded within RNA genes. BMC Mol. Biol. 5:10. | |
| Reeder, J. and Giegerich, R. 2005. Consensus shapes: An alternative to the Sankoff algorithm for RNA consensus structure prediction. Bioinformatics 21:3516‐3523. | |
| Rieder, R., Lang, K., Graber, D. and Micura, R. 2007. Ligand‐induced folding of the adenosine deaminase A‐riboswitch and implications on riboswitch translational control. Chembiochem 8:896‐902. | |
| Stein, P.R. and Waterman, M.S. 1978. On some new sequences generalizing the Catalan and Motzkin numbers. Discr. Math. 26:261‐272. | |
| Torarinsson, E., Havgaard, J.H., and Gorodkin, J. 2007. Multiple structural alignment and clustering of RNA sequences. Bioinformatics 23:926‐932. | |
| Voss, B., Giegerich, R., and Rehmsmeier, M. 2006. Complete probabilistic analysis of RNA shapes. BMC Biol. 4:5. | |
| Voss, B., Meyer, C., and Giegerich, R. 2004. Evaluating the predictability of conformational switching in RNA. Bioinformatics 20:1573‐1582. | |
| Will, S., Reiche, K., Hofacker, I.L., Stadler, P.F., and Backofen, R. 2007. Inferring non‐coding RNA families and classes by means of genome‐scale structure‐based clustering. PLoS Comput. Biol. 3:e65 | |
| Wuchty, S., Fontana, W., Hofacker, I.L., and Schuster, P. 1999. Complete suboptimal folding of RNA and the stability of secondary structures. Biopolymers 49:145‐165. | |
| Yao, Z., Weinberg, Z., and Ruzzo, W.L. 2006. CMfinder: A covariance model based RNA motif finding algorithm. Bioinformatics 22:445‐452. | |
| Zuker, M. 1989. On finding all suboptimal foldings of an RNA molecule. Science 244:48‐52. | |
| Zuker, M. 2003. Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res. 31:3406‐3415. | |
| Zuker, M. and Stiegler, P. 1981. Optimal computer folding of large RNA sequences using thermodynamic and auxiliary information. Nucleic Acids Res. 9:133‐148. | |
| Key References | |
| Giegerich et al., 2004. See above. | |
| Introduces the abstract shape technique into minimum free energy prediction. | |
| Reeder and Giegerich, 2005. See above. | |
| Comparative structure prediction employing abstract shapes. | |
| Voss et al., 2006. See above. | |
| Extends the shapes approach to a complete probabilistic analysis. | |
| Internet Resources | |
| http://bibiserv.techfak.uni‐bielefeld.de/rnashapes | |
| The project's home page where the latest distribution can be downloaded and also be used online. | |
| http://bibiserv.techfak.uni‐bielefeld.de/bibi/Tools_RNA_Studio.html | |
| Collection of several RNA‐related tools, mostly for online use via Web interface and also for download. |
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