Structural RNA Alignment Research Articles

RNAscClust: clustering RNA sequences using structure conservation and graph based motifs.

MotivationClustering RNA sequences with common secondary structure is an essential step towards studying RNA function. Whereas structural RNA alignment strategies typically identify common structure for orthologous structured RNAs, clustering seeks to group paralogous RNAs based on structural similarities. However, existing approaches for clustering paralogous RNAs, do not take the compensatory base pair changes obtained from structure conservation in orthologous sequences into account.ResultsHere, we present RNAscClust, the implementation of a new algorithm to cluster a set of structured RNAs taking their respective structural conservation into account. For a set of multiple structural alignments of RNA sequences, each containing a paralog sequence included in a structural alignment of its orthologs, RNAscClust computes minimum free-energy structures for each sequence using conserved base pairs as prior information for the folding. The paralogs are then clustered using a graph kernel-based strategy, which identifies common structural features. We show that the clustering accuracy clearly benefits from an increasing degree of compensatory base pair changes in the alignments.Availability and Implementation RNAscClust is available at http://www.bioinf.uni-freiburg.de/Software/RNAscClust.Supplementary information Supplementary data are available at Bioinformatics online.

Structural RNA alignment by multi-objective optimization

The calculation of reliable alignments for structured RNA is still considered as an open problem. One approach is the incorporation of secondary structure information into the optimization criteria by using a weighted sum of sequence and structure components as an objective function. As it is not clear how to choose the weighting parameters, we use multi-objective optimization to calculate a set of Pareto-optimal RNA sequence-structure alignments. The solutions in this set then represent all possible trade-offs between the different objectives, independent of any previous weighting. We present a practical multi-objective dynamic programming algorithm, which is a new method for the calculation of the set of Pareto-optimal solutions to the pairwise RNA sequence-structure alignment problem. In selected examples, we show the usefulness of this approach, and its advantages over state-of-the-art single-objective algorithms. The source code of our software (ISO C++11) is freely available at http://sysbio.uni-ulm.de/?Software and is licensed under the GNU GPLv3. Supplementary data are available at Bioinformatics online.

Structural Alignment of RNA with Triple Helix Structure

Structural alignment is useful in identifying members of ncRNAs. Existing tools are all based on the secondary structures of the molecules. There is evidence showing that tertiary interactions (the interaction between a single-stranded nucleotide and a base-pair) in triple helix structures are critical in some functions of ncRNAs. In this article, we address the problem of structural alignment of RNAs with the triple helix. We provide a formal definition to capture a simplified model of a triple helix structure, then develop an algorithm of O(mn(3)) time to align a query sequence (of length m) with known triple helix structure with a target sequence (of length n) with an unknown structure. The resulting algorithm is shown to be useful in identifying ncRNA members in a simulated genome.

RNASAlign: RNA Structural Alignment System

Structural alignment of RNA is found to be a useful computational technique for idenitfying non-coding RNAs (ncRNAs). However, existing tools do not handle structures with pseudoknots. Although algorithms exist that can handle structural alignment for different types of pseudoknots, no software tools are available and users have to determine the type of pseudoknots to select the appropriate algoirthm to use which limits the usage of structural alignment in identifying novel ncRNAs. We implemented the first web server, RNASAlign, which can automatically identify the pseudoknot type of a secondary structure and perform structural alignment of a folded RNA with every region of a target DNA/RNA sequence. Regions with high similarity scores and low e-values, together with the detailed alignments will be reported to the user. Experiments on more than 350 ncRNA families show that RNASAlign is effective. http://www.bio8.cs.hku.hk/RNASAlign.

Local structural alignment of RNA with affine gap model

BackgroundPredicting new non-coding RNAs (ncRNAs) of a family can be done by aligning the potential candidate with a member of the family with known sequence and secondary structure. Existing tools either only consider the sequence similarity or cannot handle local alignment with gaps.ResultsIn this paper, we consider the problem of finding the optimal local structural alignment between a query RNA sequence (with known secondary structure) and a target sequence (with unknown secondary structure) with the affine gap penalty model. We provide the algorithm to solve the problem.ConclusionsBased on an experiment, we show that there are ncRNA families in which considering local structural alignment with gap penalty model can identify real hits more effectively than using global alignment or local alignment without gap penalty model.

Structural Alignment of RNA with Complex Pseudoknot Structure

The secondary structure of an ncRNA molecule is known to play an important role in its biological functions. Aligning a known ncRNA to a target candidate to determine the sequence and structural similarity helps in identifying de novo ncRNA molecules that are in the same family of the known ncRNA. However, existing algorithms cannot handle complex pseudoknot structures which are found in nature. In this article, we propose algorithms to handle two types of complex pseudoknots: simple non-standard pseudoknots and recursive pseudoknots. Although our methods are not designed for general pseudoknots, it already covers all known ncRNAs in both Rfam and PseudoBase databases. An evaluation of our algorithms shows that it is useful to identify ncRNA molecules in other species which are in the same family of a known ncRNA.

Fine-tuning structural RNA alignments in the twilight zone

BackgroundA widely used method to find conserved secondary structure in RNA is to first construct a multiple sequence alignment, and then fold the alignment, optimizing a score based on thermodynamics and covariance. This method works best around 75% sequence similarity. However, in a "twilight zone" below 55% similarity, the sequence alignment tends to obscure the covariance signal used in the second phase. Therefore, while the overall shape of the consensus structure may still be found, the degree of conservation cannot be estimated reliably.ResultsBased on a combination of available methods, we present a method named planACstar for improving structure conservation in structural alignments in the twilight zone. After constructing a consensus structure by alignment folding, planACstar abandons the original sequence alignment, refolds the sequences individually, but consistent with the consensus, aligns the structures, irrespective of sequence, by a pure structure alignment method, and derives an improved sequence alignment from the alignment of structures, to be re-submitted to alignment folding, etc.. This circle may be iterated as long as structural conservation improves, but normally, one step suffices.ConclusionsEmploying the tools ClustalW, RNAalifold, and RNAforester, we find that for sequences with 30-55% sequence identity, structural conservation can be improved by 10% on average, with a large variation, measured in terms of RNAalifold's own criterion, the structure conservation index.

Local RNA structure alignment with incomplete sequence

Motivation: Accuracy of automated structural RNA alignment is improved by using models that consider not only primary sequence but also secondary structure information. However, current RNA structural alignment approaches tend to perform poorly on incomplete sequence fragments, such as single reads from metagenomic environmental surveys, because nucleotides that are expected to be base paired are missing.Results: We present a local RNA structural alignment algorithm, trCYK, for aligning and scoring incomplete sequences under a model using primary sequence conservation and secondary structure information when possible. The trCYK algorithm improves alignment accuracy and coverage of sequence fragments of structural RNAs in simulated metagenomic shotgun datasets.Availability: The source code for Infernal 1.0, which includes trCYK, is available at http://infernal.janelia.orgContact: kolbed@janelia.hhmi.org; eddys@janelia.hhmi.orgSupplementary information: Supplementary data are available at Bioinformatics online.

Structural Alignment of Pseudoknotted RNA

In this paper, we address the problem of discovering novel non-coding RNA (ncRNA) using primary sequence, and secondary structure conservation, focusing on ncRNA families with pseudoknotted structures. Our main technical result is an efficient algorithm for computing an optimum structural alignment of an RNA sequence against a genomic substring. This algorithm has two applications. First, by scanning a genome, we can identify novel (homologous) pseudoknotted ncRNA, and second, we can infer the secondary structure of the target aligned sequence. We test an implementation of our algorithm (PAL) and show that it has near-perfect behavior for predicting the structure of many known pseudoknots. Additionally, it can detect the true homologs with high sensitivity and specificity in controlled tests. We also use PAL to search entire viral genome and mouse genome for novel homologs of some viral and eukaryotic pseudoknots, respectively. In each case, we have found strong support for novel homologs.

RNALogo: a new approach to display structural RNA alignment

Regulatory RNAs play essential roles in many essential biological processes, ranging from gene regulation to protein synthesis. This work presents a web-based tool, RNALogo, to create a new graphical representation of the patterns in a multiple RNA sequence alignment with a consensus structure. The RNALogo graph can indicate significant features within an RNA sequence alignment and its consensus RNA secondary structure. RNALogo extends Sequence logos, and specifically incorporates RNA secondary structures and mutual information of base-paired regions into the graphical representation. Each RNALogo graph is composed of stacks of letters, with one stack for each position in the consensus RNA secondary structure. RNALogo provides a convenient and high configurable logo generator. An RNALogo graph is generated for each RNA family in Rfam, and these generated logos are accumulated into a gallery of RNALogo. Users can search or browse RNALogo graphs in this gallery to receive additional perspectives of known RNA families. RNALogo is now available at: http://rnalogo.mbc.nctu.edu.tw/.

The Vienna RNA Websuite

The Vienna RNA Websuite is a comprehensive collection of tools for folding, design and analysis of RNA sequences. It provides a web interface to the most commonly used programs of the Vienna RNA package. Among them, we find folding of single and aligned sequences, prediction of RNA–RNA interactions, and design of sequences with a given structure. Additionally, we provide analysis of folding landscapes using the barriers program and structural RNA alignments using LocARNA. The web server together with software packages for download is freely accessible at http://rna.tbi.univie.ac.at/.

Fast Pairwise Structural RNA Alignments by Pruning of the Dynamical Programming Matrix

It has become clear that noncoding RNAs (ncRNA) play important roles in cells, and emerging studies indicate that there might be a large number of unknown ncRNAs in mammalian genomes. There exist computational methods that can be used to search for ncRNAs by comparing sequences from different genomes. One main problem with these methods is their computational complexity, and heuristics are therefore employed. Two heuristics are currently very popular: pre-folding and pre-aligning. However, these heuristics are not ideal, as pre-aligning is dependent on sequence similarity that may not be present and pre-folding ignores the comparative information. Here, pruning of the dynamical programming matrix is presented as an alternative novel heuristic constraint. All subalignments that do not exceed a length-dependent minimum score are discarded as the matrix is filled out, thus giving the advantage of providing the constraints dynamically. This has been included in a new implementation of the FOLDALIGN algorithm for pairwise local or global structural alignment of RNA sequences. It is shown that time and memory requirements are dramatically lowered while overall performance is maintained. Furthermore, a new divide and conquer method is introduced to limit the memory requirement during global alignment and backtrack of local alignment. All branch points in the computed RNA structure are found and used to divide the structure into smaller unbranched segments. Each segment is then realigned and backtracked in a normal fashion. Finally, the FOLDALIGN algorithm has also been updated with a better memory implementation and an improved energy model. With these improvements in the algorithm, the FOLDALIGN software package provides the molecular biologist with an efficient and user-friendly tool for searching for new ncRNAs. The software package is available for download at http://foldalign.ku.dk.

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

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.

Fast Pairwise Structural RNA Alignments by Pruning of the Dynamical Programming Matrix

Fast Pairwise Structural RNA Alignments by Pruning of the Dynamical Programming Matrix

Semi-automated update and cleanup of structural RNA alignment databases.

We have developed a series of programs which assist in maintenance of structural RNA databases. A main program BLASTs the RNA database against GenBank and automatically extends and realigns the sequences to include the entire range of the RNA query sequences. After manual update of the database, other programs can examine base pair consistency and phylogenetic support. The output can be applied iteratively to refine the structural alignment of the RNA database. Using these tools, the number of potential misannotations per sequence was reduced from 20 to 3 in the Signal Recognition Particle RNA database. A quick-server and programs are available at http://www.bioinf.au.dk/rnadbtool/

Displaying the in formation contents of structural RNA alignments: the structure logos

We extend the standard 'Sequence Logo' method of Schneider and Stevens (Nucleic Acids Res., 18, 6097-6100, 1990) to incorporate prior frequencies on the bases, allow for gaps in the alignments, and indicate the mutual information of base-paired regions in RNA. Given an alignment of RNA sequences with the base pairings indicated, the program will calculate the information at each position, including the mutual information of the base pairs, and display the results in a 'Structure Logo'. Alignments without base pairing can also be displayed in a 'Sequence Logo', but still allowing gaps and incorporating prior frequencies if desired. The code is available from, and an Internet server can be used to run the program at, http://www.cbs.dtu.dk/gorodkin/appl/slogo. html.