RNA Secondary Structure Prediction Research Articles

Characterization of a novel insect-specific flavivirus from Brazil: potential for inhibition of infection of arthropod cells with medically important flaviviruses.

In the past decade, there has been an upsurge in the number of newly described insect-specific flaviviruses isolated pan-globally. We recently described the isolation of a novel flavivirus (tentatively designated 'Nhumirim virus'; NHUV) that represents an example of a unique subset of apparently insect-specific viruses that phylogenetically affiliate with dual-host mosquito-borne flaviviruses despite appearing to be limited to replication in mosquito cells. We characterized the in vitro growth potential and 3' untranslated region (UTR) sequence homology with alternative flaviviruses, and evaluated the virus's capacity to suppress replication of representative Culex spp.-vectored pathogenic flaviviruses in mosquito cells. Only mosquito cell lines were found to support NHUV replication, further reinforcing the insect-specific phenotype of this virus. Analysis of the sequence and predicted RNA secondary structures of the 3' UTR indicated NHUV to be most similar to viruses within the yellow fever serogroup and Japanese encephalitis serogroup, and viruses in the tick-borne flavivirus clade. NHUV was found to share the fewest conserved sequence elements when compared with traditional insect-specific flaviviruses. This suggests that, despite apparently being insect specific, this virus probably diverged from an ancestral mosquito-borne flavivirus. Co-infection experiments indicated that prior or concurrent infection of mosquito cells with NHUV resulted in a significant reduction in virus production of West Nile virus (WNV), St Louis encephalitis virus (SLEV) and Japanese encephalitis virus. The inhibitory effect was most effective against WNV and SLEV with over a 10(6)-fold and 10(4)-fold reduction in peak titres, respectively.

SP-fold Speculative Parallelization for Parallel Algorithm of RNA Secondary Structure Prediction on Multicore

is faced with accelerating increase of data set sizes originating from powerful high-throughput measuring devices. Extensive computational power is the basic requirement for solving problems in bioinformatics. One of the key solutions to time-efficient data processing is the proper implementation of computational intensive tasks using parallel technology. A large number of cores is combined into a single chip to improve the overall performance of the multi- core processors. This depicts the current trends in processor architecture. This paper proposes a new software-only speculative parallelization scheme for implementing RNA Secondary Structure Prediction algorithm in parallel. The scheme is developed after a systematic evaluation of the design options available. It is also shown to be efficient, robust and to outperform previously proposed schemes used for parallel implementation of RNA Secondary Structure Prediction.

MiRPlant: an integrated tool for identification of plant miRNA from RNA sequencing data.

BackgroundSmall RNA sequencing is commonly used to identify novel miRNAs and to determine their expression levels in plants. There are several miRNA identification tools for animals such as miRDeep, miRDeep2 and miRDeep*. miRDeep-P was developed to identify plant miRNA using miRDeep’s probabilistic model of miRNA biogenesis, but it depends on several third party tools and lacks a user-friendly interface. The objective of our miRPlant program is to predict novel plant miRNA, while providing a user-friendly interface with improved accuracy of prediction.ResultWe have developed a user-friendly plant miRNA prediction tool called miRPlant. We show using 16 plant miRNA datasets from four different plant species that miRPlant has at least a 10% improvement in accuracy compared to miRDeep-P, which is the most popular plant miRNA prediction tool. Furthermore, miRPlant uses a Graphical User Interface for data input and output, and identified miRNA are shown with all RNAseq reads in a hairpin diagram.ConclusionsWe have developed miRPlant which extends miRDeep* to various plant species by adopting suitable strategies to identify hairpin excision regions and hairpin structure filtering for plants. miRPlant does not require any third party tools such as mapping or RNA secondary structure prediction tools. miRPlant is also the first plant miRNA prediction tool that dynamically plots miRNA hairpin structure with small reads for identified novel miRNAs. This feature will enable biologists to visualize novel pre-miRNA structure and the location of small RNA reads relative to the hairpin. Moreover, miRPlant can be easily used by biologists with limited bioinformatics skills.miRPlant and its manual are freely available at http://www.australianprostatecentre.org/research/software/mirplant or http://sourceforge.net/projects/mirplant/.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2105-15-275) contains supplementary material, which is available to authorized users.

RNA Secondary Structure Analysis Using RNAstructure.

RNAstructure is a user-friendly program for the prediction and analysis of RNA secondary structure. It is available as a Web server, as a program with a graphical user interface, or as a set of command-line tools. The programs are available for Microsoft Windows, Macintosh OS X, or Linux. This unit provides protocols for RNA secondary structure prediction (using the Web server or the graphical user interface) and prediction of high-affinity oligonucleotide biding sites to a structured RNA target (using the graphical user interface).

Fine-grained parallelism accelerating for RNA secondary structure prediction with pseudoknots based on FPGA.

PKNOTS is a most famous benchmark program and has been widely used to predict RNA secondary structure including pseudoknots. It adopts the standard four-dimensional (4D) dynamic programming (DP) method and is the basis of many variants and improved algorithms. Unfortunately, the O(N(6)) computing requirements and complicated data dependency greatly limits the usefulness of PKNOTS package with the explosion in gene database size. In this paper, we present a fine-grained parallel PKNOTS package and prototype system for accelerating RNA folding application based on FPGA chip. We adopted a series of storage optimization strategies to resolve the "Memory Wall" problem. We aggressively exploit parallel computing strategies to improve computational efficiency. We also propose several methods that collectively reduce the storage requirements for FPGA on-chip memory. To the best of our knowledge, our design is the first FPGA implementation for accelerating 4D DP problem for RNA folding application including pseudoknots. The experimental results show a factor of more than 50x average speedup over the PKNOTS-1.08 software running on a PC platform with Intel Core2 Q9400 Quad CPU for input RNA sequences. However, the power consumption of our FPGA accelerator is only about 50% of the general-purpose micro-processors.

Improved model to predict the free energy contribution of trinucleotide bulges to RNA duplex stability.

Trinucleotide bulges in RNA commonly occur in nature. Yet, little data exists concerning the thermodynamic parameters of this motif. Algorithms that predict RNA secondary structure from sequence currently attribute a constant free energy value of 3.2 kcal/mol to all trinucleotide bulges, regardless of bulge sequence. To test the accuracy of this model, RNA duplexes that contain frequent naturally occurring trinucleotide bulges were optically melted, and their thermodynamic parameters—enthalpy, entropy, free energy, and melting temperature—were determined. The thermodynamic data were used to derive a new model to predict the free energy contribution of trinucleotide bulges to RNA duplex stability: ΔG°37, trint bulge = ΔG°37, bulge + ΔG°37, AU + ΔG°37, GU. The parameter ΔG°37, bulge is variable depending upon the purine and pyrimidine composition of the bulge, ΔG°37, AU is a 0.49 kcal/mol penalty for an A-U closing pair, and ΔG° 37, GU is a −0.56 kcal/mol bonus for a G-U closing pair. With both closing pair and bulge sequence taken into account, this new model predicts free energy values within 0.30 kcal/mol of the experimental value. The new model can be used by algorithms that predict RNA free energies as well as algorithms that use free energy minimization to predict RNA secondary structure from sequence.

A fast and robust iterative algorithm for prediction of RNA pseudoknotted secondary structures.

BackgroundImproving accuracy and efficiency of computational methods that predict pseudoknotted RNA secondary structures is an ongoing challenge. Existing methods based on free energy minimization tend to be very slow and are limited in the types of pseudoknots that they can predict. Incorporating known structural information can improve prediction accuracy; however, there are not many methods for prediction of pseudoknotted structures that can incorporate structural information as input. There is even less understanding of the relative robustness of these methods with respect to partial information.ResultsWe present a new method, Iterative HFold, for pseudoknotted RNA secondary structure prediction. Iterative HFold takes as input a pseudoknot-free structure, and produces a possibly pseudoknotted structure whose energy is at least as low as that of any (density-2) pseudoknotted structure containing the input structure. Iterative HFold leverages strengths of earlier methods, namely the fast running time of HFold, a method that is based on the hierarchical folding hypothesis, and the energy parameters of HotKnots V2.0.Our experimental evaluation on a large data set shows that Iterative HFold is robust with respect to partial information, with average accuracy on pseudoknotted structures steadily increasing from roughly 54% to 79% as the user provides up to 40% of the input structure.Iterative HFold is much faster than HotKnots V2.0, while having comparable accuracy. Iterative HFold also has significantly better accuracy than IPknot on our HK-PK and IP-pk168 data sets.ConclusionsIterative HFold is a robust method for prediction of pseudoknotted RNA secondary structures, whose accuracy with more than 5% information about true pseudoknot-free structures is better than that of IPknot, and with about 35% information about true pseudoknot-free structures compares well with that of HotKnots V2.0 while being significantly faster. Iterative HFold and all data used in this work are freely available at http://www.cs.ubc.ca/~hjabbari/software.php.

Computational analysis of conserved RNA secondary structure in transcriptomes and genomes.

Transcriptomics experiments and computational predictions both enable systematic discovery of new functional RNAs. However, many putative noncoding transcripts arise instead from artifacts and biological noise, and current computational prediction methods have high false positive rates. I discuss prospects for improving computational methods for analyzing and identifying functional RNAs, with a focus on detecting signatures of conserved RNA secondary structure. An interesting new front is the application of chemical and enzymatic experiments that probe RNA structure on a transcriptome-wide scale. I review several proposed approaches for incorporating structure probing data into the computational prediction of RNA secondary structure. Using probabilistic inference formalisms, I show how all these approaches can be unified in a well-principled framework, which in turn allows RNA probing data to be easily integrated into a wide range of analyses that depend on RNA secondary structure inference. Such analyses include homology search and genome-wide detection of new structural RNAs.

ReadXplorer--visualization and analysis of mapped sequences.

Motivation: Fast algorithms and well-arranged visualizations are required for the comprehensive analysis of the ever-growing size of genomic and transcriptomic next-generation sequencing data.Results: ReadXplorer is a software offering straightforward visualization and extensive analysis functions for genomic and transcriptomic DNA sequences mapped on a reference. A unique specialty of ReadXplorer is the quality classification of the read mappings. It is incorporated in all analysis functions and displayed in ReadXplorer's various synchronized data viewers for (i) the reference sequence, its base coverage as (ii) normalizable plot and (iii) histogram, (iv) read alignments and (v) read pairs. ReadXplorer's analysis capability covers RNA secondary structure prediction, single nucleotide polymorphism and deletion–insertion polymorphism detection, genomic feature and general coverage analysis. Especially for RNA-Seq data, it offers differential gene expression analysis, transcription start site and operon detection as well as RPKM value and read count calculations. Furthermore, ReadXplorer can combine or superimpose coverage of different datasets.Availability and implementation: ReadXplorer is available as open-source software at http://www.readxplorer.org along with a detailed manual.Contact: rhilker@mikrobio.med.uni-giessen.deSupplementary information: Supplementary data are available at Bioinformatics online.

Mixed Triple: Allied Viruses in Unique Recent Isolates of Highly Virulent Type 2 Bovine Viral Diarrhea Virus Detected by Deep Sequencing

In February 2013, very severe acute clinical symptoms were observed in calves, heifers, and dairy cattle in several farms in North Rhine Westphalia and Lower Saxony, Germany. Deep sequencing revealed the coexistence of three distinct genome variants within recent highly virulent bovine viral diarrhea virus type 2 (BVDV-2) isolates. While the major portion (ca. 95%) of the population harbored a duplication of a 222-nucleotide (nt) segment within the p7-NS2-encoding region, the minority reflected the standard structure of a BVDV-2 genome. Additionally, unusual mutations were found in both variants, within the highly conserved p7 protein and close to the p7-NS2 cleavage site. Using a reverse genetic system with a BVDV-2a strain harboring a similar duplication, it could be demonstrated that during replication, genomes without duplication are generated de novo from genomes with duplication. The major variant with duplication is compulsorily escorted by the minor variant without duplication. RNA secondary structure prediction allowed the analysis of the unique but stable mixture of three BVDV variants and also provided the explanation for their generation. Finally, our results suggest that the variant with duplication plays the major role in the highly virulent phenotype. This study emphasizes the importance of full-genome deep sequencing in combination with manual in-depth data analysis for the investigation of viruses in basic research and diagnostics. Here we investigated recent highly virulent bovine viral diarrhea virus isolates from a 2013 series of outbreaks. We discovered a unique special feature of the viral genome, an unstable duplication of 222 nucleotides which is eventually deleted by viral polymerase activity, leading to an unexpectedly mixed population of viral genomes for all investigated isolates. Our study is of high importance to the field because we demonstrate that these insertion/deletion events allow another level of genome plasticity of plus-strand RNA viruses, in addition to the well-known polymerase-induced single nucleotide variations which are generally considered the main basis for viral adaptation and evolution.

Helix Capping in RNA Structure

Helices are an essential element in defining the three-dimensional architecture of structured RNAs. While internal basepairs in a canonical helix stack on both sides, the ends of the helix stack on only one side and are exposed to the loop side, thus susceptible to fraying unless they are protected. While coaxial stacking has long been known to stabilize helix ends by directly stacking two canonical helices coaxially, based on analysis of helix-loop junctions in RNA crystal structures, herein we describe helix capping, topological stacking of a helix end with a basepair or an unpaired nucleotide from the loop side, which in turn protects helix ends. Beyond the topological protection of helix ends against fraying, helix capping should confer greater stability onto the resulting composite helices. Our analysis also reveals that this general motif is associated with the formation of tertiary structure interactions. Greater knowledge about the dynamics at the helix-junctions in the secondary structure should enhance the prediction of RNA secondary structure with a richer set of energetic rules and help better understand the folding of a secondary structure into its three-dimensional structure. These together suggest that helix capping likely play a fundamental role in driving RNA folding.

CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction

CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction

FINE-GRAINED PARALLEL APPLICATION SPECIFIC COMPUTING FOR RNA SECONDARY STRUCTURE PREDICTION ON FPGA

RNA secondary structure prediction is one of the important research areas in modern bioinformatics and computational biology. PKNOTS is the most famous benchmark program and has been widely used to predict RNA secondary structure including pseudoknots. It adopts the standard 4D dynamic programming method and is the basis of many variants and improved algorithms. Unfortunately, the O(N6) computing requirements and complicated data dependency greatly limits the usefulness of PKNOTS package with the explosion in gene database size. In this paper, we present a fine-grained parallel PKNOTS algorithm and prototype system for accelerating RNA folding application on field programmable gate-array (FPGA) platform. We improved data locality by converting cycle nested relationship and reorganizing computing order of the elements in source code. We aggressively exploit data reuse, data dependency elimination and memory access scheduling strategies to minimize the need for loading data from external memory. To the best of our knowledge, our design is the first FPGA implementation for accelerating 4D dynamic programming problem for RNA folding application including pseudoknots. The experimental results show a factor of more than 11 × average speedup over the PKNOTS-1.05 software running on a PC platform with AMD Phenom 9650 Quad CPU for input RNA sequences. However, the power consumption of our FPGA accelerator is only about 50% of the general-purpose micro-processors.

Reconfiguring the Bioinformatics Computational Spectrum: Challenges and Opportunities of FPGA-Based Bioinformatics Acceleration Platforms

This paper conducts a detailed survey on the use of FPGA-based reconfigurable computing platforms for a wide range of sequence and structural bioinformatics applications, with emphasis on performance and energy savings of the underlying architectures. Applications considered include sequence comparison, multiple sequence alignment, RNA and protein secondary structure prediction, gene prediction, and phylogenetic tree computation.

Kassiopeia: a database and web application for the analysis of mutually exclusive exomes of eukaryotes

BackgroundAlternative splicing is an important process in higher eukaryotes that allows obtaining several transcripts from one gene. A specific case of alternative splicing is mutually exclusive splicing, in which exactly one exon out of a cluster of neighbouring exons is spliced into the mature transcript. Recently, a new algorithm for the prediction of these exons has been developed based on the preconditions that the exons of the cluster have similar lengths, sequence homology, and conserved splice sites, and that they are translated in the same reading frame.DescriptionIn this contribution we introduce Kassiopeia, a database and web application for the generation, storage, and presentation of genome-wide analyses of mutually exclusive exomes. Currently, Kassiopeia provides access to the mutually exclusive exomes of twelve Drosophila species, the thale cress Arabidopsis thaliana, the flatworm Caenorhabditis elegans, and human. Mutually exclusive spliced exons (MXEs) were predicted based on gene reconstructions from Scipio. Based on the standard prediction values, with which 83.5% of the annotated MXEs of Drosophila melanogaster were reconstructed, the exomes contain surprisingly more MXEs than previously supposed and identified. The user can search Kassiopeia using BLAST or browse the genes of each species optionally adjusting the parameters used for the prediction to reveal more divergent or only very similar exon candidates.ConclusionsWe developed a pipeline to predict MXEs in the genomes of several model organisms and a web interface, Kassiopeia, for their visualization. For each gene Kassiopeia provides a comprehensive gene structure scheme, the sequences and predicted secondary structures of the MXEs, and, if available, further evidence for MXE candidates from cDNA/EST data, predictions of MXEs in homologous genes of closely related species, and RNA secondary structure predictions. Kassiopeia can be accessed at http://www.motorprotein.de/kassiopeia.

A classifier system for predicting RNA secondary structure.

Finding the secondary structures of ribonucleic acid sequences is a very important task. The secondary structure helps determine their functionalities which in turn plays a role in the proteins production. Manual laboratory methods use X-ray diffraction to predict secondary structures but it is complex, slow and expensive. Therefore, different computational approaches are used to predict RNA secondary structure in order to reduce the time and cost associated with the manual process. We propose a system called IsRNA to predict a single element, internal loop, of the RNA secondary structure. IsRNA experiments with different classifiers such as SVM, KNN, Naive Bayes and Simple K means to find the most accurate classifier. We present a through experimental evaluation of 24 features, classified into five groups, to determine the most relevant feature groups. The system is evaluated using Rfam sequences and achieves an overall sensitivity, selectivity, and accuracy of 96.1%, 98%, and 96.1%, respectively.

Solvent Kinetic Isotope Effects on 2'-Hydroxyl Acylation of RNA

RNA can fold into complex tertiary structures, much like proteins, and exhibits significant conformational dynamics that are a central facet of its functions. Two limiting types of RNA motions occur: equilibrium fluctuations and induced conformational changes. Equilibrium fluctuations are spontaneous transitions between conformers along the RNA free energy landscape and conformational transitions occur when the free energy landscape is perturbed to generate new minima and change the energy barriers between minima. Surprisingly, little experimental data are available for equilibrium fluctuations for even simple RNA, and even less is known about the driving forces for conformational transitions in large RNAs. In part this is due to limiting technologies. One technology, SHAPE, has overcome many of the limitations for studying large RNAs. SHAPE, for selective 2′-hydroxyl acylation analyzed by primer extension, has revolutionized RNA secondary structure prediction and provides a transformative experimental approach to investigate nucleotide specific equilibrium fluctuations and conformations. SHAPE reactivity is governed primarily by nucleotide flexibility, which in turn is governed by secondary and tertiary structure constraints. In practice, SHAPE provides nucleotide level resolution of RNA structure and dynamics in RNA of any size. We hypothesize that the solvent isotope effect on SHAPE chemistry will allow insights into the roles of hydrogen bonding and solvation on RNA structure and dynamics. Here, we describe the initial experiments and theoretic basis for interpreting this solvent isotope effect.

Viral IRES Prediction System - a Web Server for Prediction of the IRES Secondary Structure In Silico

The internal ribosomal entry site (IRES) functions as cap-independent translation initiation sites in eukaryotic cells. IRES elements have been applied as useful tools for bi-cistronic expression vectors. Current RNA structure prediction programs are unable to predict precisely the potential IRES element. We have designed a viral IRES prediction system (VIPS) to perform the IRES secondary structure prediction. In order to obtain better results for the IRES prediction, the VIPS can evaluate and predict for all four different groups of IRESs with a higher accuracy. RNA secondary structure prediction, comparison, and pseudoknot prediction programs were implemented to form the three-stage procedure for the VIPS. The backbone of VIPS includes: the RNAL fold program, aimed to predict local RNA secondary structures by minimum free energy method; the RNA Align program, intended to compare predicted structures; and pknotsRG program, used to calculate the pseudoknot structure. VIPS was evaluated by using UTR database, IRES database and Virus database, and the accuracy rate of VIPS was assessed as 98.53%, 90.80%, 82.36% and 80.41% for IRES groups 1, 2, 3, and 4, respectively. This advance useful search approach for IRES structures will facilitate IRES related studies. The VIPS on-line website service is available at http://140.135.61.250/vips/.

SHAPE analysis of the 5′ end of the Mason-Pfizer monkey virus (MPMV) genomic RNA reveals structural elements required for genome dimerization

Earlier genetic and structural prediction analyses revealed that the packaging determinants of Mason Pfizer monkey virus (MPMV) include two discontinuous core regions at the 5' end of its genomic RNA. RNA secondary structure predictions suggested that these packaging determinants fold into several stem-loops (SLs). To experimentally validate this structural model, we employed selective 2' hydroxyl acylation analyzed by primer extension (SHAPE), which examines the flexibility of the RNA backbone at each nucleotide position. Our SHAPE data validated several predicted structural motifs, including U5/Gag long-range interactions (LRIs), a stretch of single-stranded purine (ssPurine)-rich region, and a distinctive G-C-rich palindromic (pal) SL. Minimum free-energy structure predictions, phylogenetic, and in silico modeling analyses of different MPMV strains revealed that the U5 and gag sequences involved in the LRIs differ minimally within strains and maintain a very high degree of complementarity. Since the pal SL forms a helix loop containing a canonical "GC" dyad, it may act as a RNA dimerization initiation site (DIS), enabling the virus to package two copies of its genome. Analyses of wild-type and pal mutant RNAs revealed that disruption of pal sequence strongly affected RNA dimerization. However, when in vitro transcribed trans-complementary pal mutants were incubated together showed RNA dimerization was restored authenticating that the pal loop (5'-CGGCCG-3') functions as DIS.

RNA-SSPT: RNA Secondary Structure Prediction Tools.

The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes.