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

Background  

Alignment of RNA secondary structures is important in studying functional RNA motifs. In recent years, much progress has been made in RNA motif finding and structure alignment. However, existing tools either require a large number of prealigned structures or suffer from high time complexities. This makes it difficult for the tools to process RNAs whose prealigned structures are unavailable or process very large RNA structure databases.     

Inverse folding of RNA pseudoknot structures

Background  

RNA exhibits a variety of structural configurations. Here we consider a structure to be tantamount to the noncrossing Watson-Crick and G-U-base pairings (secondary structure) and additional cross-serial base pairs. These interactions are called pseudoknots and are observed across the whole spectrum of RNA functionalities. In the context of studying natural RNA structures, searching for new ribozymes and designing artificial RNA, it is of interest to find RNA sequences folding into a specific structure and to analyze their induced neutral networks. Since the established inverse folding algorithms, RNAinverse, RNA-SSD as well as INFO-RNA are limited to RNA secondary structures, we present in this paper the inverse folding algorithm Inv which can deal with 3-noncrossing, canonical pseudoknot structures.     

RNAmute: RNA secondary structure mutation analysis tool

Background  

RNAMute is an interactive Java application that calculates the secondary structure of all single point mutations, given an RNA sequence, and organizes them into categories according to their similarity with respect to the wild type predicted structure. The secondary structure predictions are performed using the Vienna RNA package. Several alternatives are used for the categorization of single point mutations: Vienna's RNAdistance based on dot-bracket representation, as well as tree edit distance and second eigenvalue of the Laplacian matrix based on Shapiro's coarse grain tree graph representation.     

Evaluation of sequence alignments and oligonucleotide probes with respect to three-dimensional structure of ribosomal RNA using ARB software package

Background  

Availability of high-resolution RNA crystal structures for the 30S and 50S ribosomal subunits and the subsequent validation of comparative secondary structure models have prompted the biologists to use three-dimensional structure of ribosomal RNA (rRNA) for evaluating sequence alignments of rRNA genes. Furthermore, the secondary and tertiary structural features of rRNA are highly useful and successfully employed in designing rRNA targeted oligonucleotide probes intended for in situ hybridization experiments. RNA3D, a program to combine sequence alignment information with three-dimensional structure of rRNA was developed. Integration into ARB software package, which is used extensively by the scientific community for phylogenetic analysis and molecular probe designing, has substantially extended the functionality of ARB software suite with 3D environment.     

Accelerated probabilistic inference of RNA structure evolution

Background  

Pairwise stochastic context-free grammars (Pair SCFGs) are powerful tools for evolutionary analysis of RNA, including simultaneous RNA sequence alignment and secondary structure prediction, but the associated algorithms are intensive in both CPU and memory usage. The same problem is faced by other RNA alignment-and-folding algorithms based on Sankoff's 1985 algorithm. It is therefore desirable to constrain such algorithms, by pre-processing the sequences and using this first pass to limit the range of structures and/or alignments that can be considered.     

RNA STRAND: The RNA Secondary Structure and Statistical Analysis Database

Background  

The ability to access, search and analyse secondary structures of a large set of known RNA molecules is very important for deriving improved RNA energy models, for evaluating computational predictions of RNA secondary structures and for a better understanding of RNA folding. Currently there is no database that can easily provide these capabilities for almost all RNA molecules with known secondary structures.     

Computational RNA secondary structure design: empirical complexity and improved methods

Background  

We investigate the empirical complexity of the RNA secondary structure design problem, that is, the scaling of the typical difficulty of the design task for various classes of RNA structures as the size of the target structure is increased. The purpose of this work is to understand better the factors that make RNA structures hard to design for existing, high-performance algorithms. Such understanding provides the basis for improving the performance of one of the best algorithms for this problem, RNA-SSD, and for characterising its limitations.     

4SALE – A tool for synchronous RNA sequence and secondary structure alignment and editing

Background  

In sequence analysis the multiple alignment builds the fundament of all proceeding analyses. Errors in an alignment could strongly influence all succeeding analyses and therefore could lead to wrong predictions. Hand-crafted and hand-improved alignments are necessary and meanwhile good common practice. For RNA sequences often the primary sequence as well as a secondary structure consensus is well known, e.g., the cloverleaf structure of the t-RNA. Recently, some alignment editors are proposed that are able to include and model both kinds of information. However, with the advent of a large amount of reliable RNA sequences together with their solved secondary structures (available from e.g. the ITS2 Database), we are faced with the problem to handle sequences and their associated secondary structures synchronously.     

Enhancement of accuracy and efficiency for RNA secondary structure prediction by sequence segmentation and MapReduce

Background

Ribonucleic acid (RNA) molecules play important roles in many biological processes including gene expression and regulation. Their secondary structures are crucial for the RNA functionality, and the prediction of the secondary structures is widely studied. Our previous research shows that cutting long sequences into shorter chunks, predicting secondary structures of the chunks independently using thermodynamic methods, and reconstructing the entire secondary structure from the predicted chunk structures can yield better accuracy than predicting the secondary structure using the RNA sequence as a whole. The chunking, prediction, and reconstruction processes can use different methods and parameters, some of which produce more accurate predictions than others. In this paper, we study the prediction accuracy and efficiency of three different chunking methods using seven popular secondary structure prediction programs that apply to two datasets of RNA with known secondary structures, which include both pseudoknotted and non-pseudoknotted sequences, as well as a family of viral genome RNAs whose structures have not been predicted before. Our modularized MapReduce framework based on Hadoop allows us to study the problem in a parallel and robust environment.

Results

On average, the maximum accuracy retention values are larger than one for our chunking methods and the seven prediction programs over 50 non-pseudoknotted sequences, meaning that the secondary structure predicted using chunking is more similar to the real structure than the secondary structure predicted by using the whole sequence. We observe similar results for the 23 pseudoknotted sequences, except for the NUPACK program using the centered chunking method. The performance analysis for 14 long RNA sequences from the Nodaviridae virus family outlines how the coarse-grained mapping of chunking and predictions in the MapReduce framework exhibits shorter turnaround times for short RNA sequences. However, as the lengths of the RNA sequences increase, the fine-grained mapping can surpass the coarse-grained mapping in performance.

Conclusions

By using our MapReduce framework together with statistical analysis on the accuracy retention results, we observe how the inversion-based chunking methods can outperform predictions using the whole sequence. Our chunk-based approach also enables us to predict secondary structures for very long RNA sequences, which is not feasible with traditional methods alone.

     

Fine-tuning structural RNA alignments in the twilight zone

Background  

A 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.     

An image processing approach to computing distances between RNA secondary structures dot plots

Background  

Computing the distance between two RNA secondary structures can contribute in understanding the functional relationship between them. When used repeatedly, such a procedure may lead to finding a query RNA structure of interest in a database of structures. Several methods are available for computing distances between RNAs represented as strings or graphs, but none utilize the RNA representation with dot plots. Since dot plots are essentially digital images, there is a clear motivation to devise an algorithm for computing the distance between dot plots based on image processing methods.     

Phenotypic effect of mutations in evolving populations of RNA molecules

Background  

The secondary structure of folded RNA sequences is a good model to map phenotype onto genotype, as represented by the RNA sequence. Computational studies of the evolution of ensembles of RNA molecules towards target secondary structures yield valuable clues to the mechanisms behind adaptation of complex populations. The relationship between the space of sequences and structures, the organization of RNA ensembles at mutation-selection equilibrium, the time of adaptation as a function of the population parameters, the presence of collective effects in quasispecies, or the optimal mutation rates to promote adaptation all are issues that can be explored within this framework.     

RNA FRABASE 2.0: an advanced web-accessible database with the capacity to search the three-dimensional fragments within RNA structures

Background  

Recent discoveries concerning novel functions of RNA, such as RNA interference, have contributed towards the growing importance of the field. In this respect, a deeper knowledge of complex three-dimensional RNA structures is essential to understand their new biological functions. A number of bioinformatic tools have been proposed to explore two major structural databases (PDB, NDB) in order to analyze various aspects of RNA tertiary structures. One of these tools is RNA FRABASE 1.0, the first web-accessible database with an engine for automatic search of 3D fragments within PDB-derived RNA structures. This search is based upon the user-defined RNA secondary structure pattern. In this paper, we present and discuss RNA FRABASE 2.0. This second version of the system represents a major extension of this tool in terms of providing new data and a wide spectrum of novel functionalities. An intuitionally operated web server platform enables very fast user-tailored search of three-dimensional RNA fragments, their multi-parameter conformational analysis and visualization.     

Phylogenetic reconstruction using secondary structures of Internal Transcribed Spacer 2 (ITS2, rDNA): finding the molecular and morphological gap in Caribbean gorgonian corals

Background  

Most phylogenetic studies using current methods have focused on primary DNA sequence information. However, RNA secondary structures are particularly useful in systematics because they include characteristics, not found in the primary sequence, that give "morphological" information. Despite the number of recent molecular studies on octocorals, there is no consensus opinion about a region that carries enough phylogenetic resolution to solve intrageneric or close species relationships. Moreover, intrageneric morphological information by itself does not always produce accurate phylogenies; intra-species comparisons can reveal greater differences than intra-generic ones. The search for new phylogenetic approaches, such as by RNA secondary structure analysis, is therefore a priority in octocoral research.     

Thioredoxin 1 as a serum marker for breast cancer and its use in combination with CEA or CA15-3 for improving the sensitivity of breast cancer diagnoses

Background

Influenza B and C are single-stranded RNA viruses that cause yearly epidemics and infections. Knowledge of RNA secondary structure generated by influenza B and C will be helpful in further understanding the role of RNA structure in the progression of influenza infection.

Findings

All available protein-coding sequences for influenza B and C were analyzed for regions with high potential for functional RNA secondary structure. On the basis of conserved RNA secondary structure with predicted high thermodynamic stability, putative structures were identified that contain splice sites in segment 8 of influenza B and segments 6 and 7 of influenza C. The sequence in segment 6 also contains three unused AUG start codon sites that are sequestered within a hairpin structure.

Conclusions

When added to previous studies on influenza A, the results suggest that influenza splicing may share common structural strategies for regulation of splicing. In particular, influenza 3′ splice sites are predicted to form secondary structures that can switch conformation to regulate splicing. Thus, these RNA structures present attractive targets for therapeutics aimed at targeting one or the other conformation.     

Correlation between nucleotide composition and folding energy of coding sequences with special attention to wobble bases

Background  

The secondary structure and complexity of mRNA influences its accessibility to regulatory molecules (proteins, micro-RNAs), its stability and its level of expression. The mobile elements of the RNA sequence, the wobble bases, are expected to regulate the formation of structures encompassing coding sequences.     

An efficient method for the prediction of deleterious multiple-point mutations in the secondary structure of RNAs using suboptimal folding solutions

Background  

RNAmute is an interactive Java application which, given an RNA sequence, calculates the secondary structure of all single point mutations and organizes them into categories according to their similarity to the predicted structure of the wild type. The secondary structure predictions are performed using the Vienna RNA package. A more efficient implementation of RNAmute is needed, however, to extend from the case of single point mutations to the general case of multiple point mutations, which may often be desired for computational predictions alongside mutagenesis experiments. But analyzing multiple point mutations, a process that requires traversing all possible mutations, becomes highly expensive since the running time is O(n ^m ) for a sequence of length n with m-point mutations. Using Vienna's RNAsubopt, we present a method that selects only those mutations, based on stability considerations, which are likely to be conformational rearranging. The approach is best examined using the dot plot representation for RNA secondary structure.     

RNACompress: Grammar-based compression and informational complexity measurement of RNA secondary structure

Background  

With the rapid emergence of RNA databases and newly identified non-coding RNAs, an efficient compression algorithm for RNA sequence and structural information is needed for the storage and analysis of such data. Although several algorithms for compressing DNA sequences have been proposed, none of them are suitable for the compression of RNA sequences with their secondary structures simultaneously. This kind of compression not only facilitates the maintenance of RNA data, but also supplies a novel way to measure the informational complexity of RNA structural data, raising the possibility of studying the relationship between the functional activities of RNA structures and their complexities, as well as various structural properties of RNA based on compression.     

RNAstructure: software for RNA secondary structure prediction and analysis

Background  

To understand an RNA sequence's mechanism of action, the structure must be known. Furthermore, target RNA structure is an important consideration in the design of small interfering RNAs and antisense DNA oligonucleotides. RNA secondary structure prediction, using thermodynamics, can be used to develop hypotheses about the structure of an RNA sequence.     

Effective ambiguity checking in biosequence analysis

Background  

Ambiguity is a problem in biosequence analysis that arises in various analysis tasks solved via dynamic programming, and in particular, in the modeling of families of RNA secondary structures with stochastic context free grammars. Several types of analysis are invalidated by the presence of ambiguity. As this problem inherits undecidability (as we show here) from the namely problem for context free languages, there is no complete algorithmic solution to the problem of ambiguity checking.