A method for aligning RNA secondary structures and its application to RNA motif detection

DIAL (dihedral alignment) is a web server that provides public access to a new dynamic programming algorithm for pairwise 3D structural alignment of RNA. DIAL achieves quadratic time by performing an alignment that accounts for (i) pseudo-dihedral and/or dihedral angle similarity, (ii) nucleotide sequence similarity and (iii) nucleotide base-pairing similarity.DIAL provides access to three alignment algorithms: global (Needleman–Wunsch), local (Smith–Waterman) and semiglobal (modified to yield motif search). Suboptimal alignments are optionally returned, and also Boltzmann pair probabilities Pr(ai,bj) for aligned positions ai , bj from the optimal alignment. If a non-zero suboptimal alignment score ratio is entered, then the semiglobal alignment algorithm may be used to detect structurally similar occurrences of a user-specified 3D motif. The query motif may be contiguous in the linear chain or fragmented in a number of noncontiguous regions.The DIAL web server provides graphical output which allows the user to view, rotate and enlarge the 3D superposition for the optimal (and suboptimal) alignment of query to target. Although graphical output is available for all three algorithms, the semiglobal motif search may be of most interest in attempts to identify RNA motifs. DIAL is available at http://bioinformatics.bc.edu/clotelab/DIAL.

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“…Liu et al . (28) present a quadratic time algorithm RSmatch for RNA secondary structure alignment and motif detection. Dalli et al .…”

Section: Introductionmentioning

confidence: 99%

DIAL: a web server for the pairwise alignment of two RNA three-dimensional structures using nucleotide, dihedral angle and base-pairing similarities

Ferré

Ponty

Lorenz

et al. 2007

Nucleic Acids Research

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“…The RSmatch algorithm (16) on which RADAR is based is built upon the premise that MFE (minimum free energy) structure prediction for a single sequence is accurate. However, this may not always be true (5, 21), which may impact the accuracy of our method.…”

Section: Discussionmentioning

confidence: 99%

“…RADAR employs the RSmatch algorithm (16) for computing the alignment of two RNA secondary structures. Briefly, it decomposes each RNA secondary structure into a set of basic structure components that are further organized by a tree model.…”

Section: Methodsmentioning

confidence: 99%

“…Pairwise structure alignment involves the alignment of a query structure with each of the subject structures in a set. Multiple structure alignment uses the same alignment algorithm along with a position specific scoring matrix to build up an alignment by including one structure at a time until no appropriate structure can be included in the alignment (16). Database search is done by aligning a query structure one by one with the consensus structures of the non-coding RNA families stored in the release 8.0 of Rfam (17) to find the consensus structures similar to the query structure.…”

Section: Methodsmentioning

confidence: 99%

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RADAR: a web server for RNA data analysis and research

Khaladkar

Bellofatto

Wang

et al. 2007

Nucleic Acids Research

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RADAR is a web server that provides a multitude of functionality for RNA data analysis and research. It can align structure-annotated RNA sequences so that both sequence and structure information are taken into consideration during the alignment process. This server is capable of performing pairwise structure alignment, multiple structure alignment, database search and clustering. In addition, RADAR provides two salient features: (i) constrained alignment of RNA secondary structures, and (ii) prediction of the consensus structure for a set of RNA sequences. RADAR will be able to assist scientists in performing many important RNA mining operations, including the understanding of the functionality of RNA sequences, the detection of RNA structural motifs and the clustering of RNA molecules, among others. The web server together with a software package for download is freely accessible at http://datalab.njit.edu/biodata/rna/RSmatch/server.htm and http://www.ccrnp.ncifcrf.gov/~bshapiro/

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“…There are several previous models for representing a pseudoknot-free RNA secondary structure (example in Figure 9a) as an ordered, rooted tree [3,9,10,13,45-48]. For example, [45] represented the RNA structure as a tree, where nodes correspond to loop elements of the secondary structure (hairpin loops, bulges, internal loops or multi-loops) and the edges correspond to base-paired (stem) regions.…”

Section: Implementation Detailsmentioning

confidence: 99%

Unrooted unordered homeomorphic subtree alignment of RNA trees

Milo

Zakov

Katzenelson

et al. 2013

Algorithms Mol Biol

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We generalize some current approaches for RNA tree alignment, which are traditionally confined to ordered rooted mappings, to also consider unordered unrooted mappings. We define the Homeomorphic Subtree Alignment problem (HSA), and present a new algorithm which applies to several modes, combining global or local, ordered or unordered, and rooted or unrooted tree alignments. Our algorithm generalizes previous algorithms that either solved the problem in an asymmetric manner, or were restricted to the rooted and/or ordered cases. Focusing here on the most general unrooted unordered case, we show that for input trees T and S, our algorithm has an O(nTnS + min(dT,dS)LTLS) time complexity, where nT,LT and dT are the number of nodes, the number of leaves, and the maximum node degree in T, respectively (satisfying dT ≤ LT ≤ nT), and similarly for nS,LS and dS with respect to the tree S. This improves the time complexity of previous algorithms for less general variants of the problem.In order to obtain this time bound for HSA, we developed new algorithms for a generalized variant of the Min-Cost Bipartite Matching problem (MCM), as well as to two derivatives of this problem, entitled All-Cavity-MCM and All-Pairs-Cavity-MCM. For two input sets of size n and m, where n ≤ m, MCM and both its cavity derivatives are solved in O(n3 + nm) time, without the usage of priority queues (e.g. Fibonacci heaps) or other complex data structures. This gives the first cubic time algorithm for All-Pairs-Cavity-MCM, and improves the running times of MCM and All-Cavity-MCM problems in the unbalanced case where n ≪ m.We implemented the algorithm (in all modes mentioned above) as a graphical software tool which computes and displays similarities between secondary structures of RNA given as input, and employed it to a preliminary experiment in which we ran all-against-all inter-family pairwise alignments of RNAse P and Hammerhead RNA family members, exposing new similarities which could not be detected by the traditional rooted ordered alignment approaches. The results demonstrate that our approach can be used to expose structural similarity between some RNAs with higher sensitivity than the traditional rooted ordered alignment approaches. Source code and web-interface for our tool can be found in http://www.cs.bgu.ac.il/\~negevcb/FRUUT.

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A method for aligning RNA secondary structures and its application to RNA motif detection

Cited by 45 publications

References 43 publications

DIAL: a web server for the pairwise alignment of two RNA three-dimensional structures using nucleotide, dihedral angle and base-pairing similarities

DIAL: a web server for the pairwise alignment of two RNA three-dimensional structures using nucleotide, dihedral angle and base-pairing similarities

RADAR: a web server for RNA data analysis and research

Unrooted unordered homeomorphic subtree alignment of RNA trees

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