Vienna RNA Package Research Articles

A39 DEVELOPMENTALLY REGULATED CECAL CONTENT MICRO-RNAS CORRELATE WITH MATURING MICROBIOTA GENES AND FUNCTIONS IN JUVENILE MICE

Abstract Background The gut microbiome establishment in early life is critical to life-long health and influenced by the maternal gut ecosystem. MicroRNAs (miRNAs) have emerged as a new player in host-microbiota interaction due to their regulatory effect on bacterial genes. We previously found that maternal supplementation with a probiotic mix of Lacticaseibacillus rhamnosus R0011 and Lactobacillus helveticus R0052 supported the maturation of microbial metabolic activity and altered the cecal content miRNA profile in juvenile mice. Aims To investigate the relationship between cecal content miRNAs and inferred microbiota genes and functions in early life and identify potential miRNA-bacterial gene targets. Methods We generated 16S rRNA gene sequencing and NanoString nCounter® data from the cecal content of 14, 21, and 36-days-old C57BL/6 mice born to dams receiving or not probiotic-supplemented water since preconception. Taxa contributions to bacterial enzyme-encoding genes and pathways were inferred with PICRUSt2. Time or group-altered genes, pathways, and miRNAs were identified with DESeq2. Spearman correlations were performed between miRNAs and bacterial genes or pathways (n= 3-5 male offspring/PND/group) and significant correlations (q ampersand:003C 0.05) were visualized with NAViGaTOR. Potential miRNA binding sites on bacterial genes were investigated using the ViennaRNA Package. Results Time-associated miR-433 positively correlated with two time-altered genes involved in the TCA and glyoxylate cycles. Group-associated miR-691 was positively correlated with genes related to tRNA charging pathway, pyruvate fermentation to acetate and lactate, and amino acids biosynthesis. Additionally, miR-691 was negatively correlated with six group-altered genes involved in myo-inositol degradation. We identified potential miRNA binding sites (total free energy of binding ampersand:003C -10 kcal/mol) for miR-691 with genes involved in pyruvate fermentation, lysine biosynthesis, and myo-inositol degradation, and for miR-433 with genes annotated to the TCA and glyoxylate cycles. Conclusions Host miRNAs correlate with bacterial pathways and genes maturing during the weaning transition, highlighting their potential to regulate microbial metabolic activity. Maternal probiotics supplementation may accelerate the development of microbial metabolic pathways through epigenetic mechanisms, independently of weaning dietary shift. Correlations identified include energy production pathways and may become clinical targets in infants with delayed maturation of the intestinal ecosystem. Funding Agencies NSERC

Abstract 16901: A Computational Framework to Estimate the Consequences of Cardiac RNA Editing Events at Single-Cell Resolution

Introduction: RNA is a highly dynamic molecule subject to various epigenetic modifications. One such process is RNA editing, a tightly regulated mechanism that introduces alterations to RNA nucleotides without affecting the DNA template. RNA editing serves as a mechanism for expanding and diversifying the functional repertoire of proteins. In the context of the heart, the RNA editors assume crucial roles in preserving cardiac function. Despite the importance of RNA editing, there are no framework to evaluate consequence of synonymous RNA editing events. Synonymous RNA editing events can affect mRNA stability, translation efficiency, protein folding, and even protein-protein interactions. These subtle changes in the coding region can influence gene expression, protein synthesis, and ultimately, cellular function. Research question: What are the functional consequences of RNA editing events in different types of cardiac cells? Methods: To estimate the RNA structural metrics, we employed the Vienna RNA package software. This comprehensive package provides a range of metrics for quantifying RNA secondary structures. Results: We have developed a framework to profile RNA editing and analyse synonymous events using new and existing single-cell datasets. Our framework enables users to explore the distribution of RNA editing events across different cell types and states, as well as analyse the functional consequences of these events. Here, to demonstrate its efficacy, we have applied our framework on healthy hearts. We identified highly edited cell types such as cardiomyocytes, fibroblasts, endothelial cells, macrophages, and pericytes, with over 1,000 edited sites. Interestingly, more than 50% of these edited sites enhanced secondary RNA structures, while 25% of the events destabilized the secondary structure. Conclusions: We have developed a comprehensive framework to estimate consequence of RNA editing events at single-cell resolution. Our results demonstrate the power of our framework in elucidating the impact of RNA editing on cellular processes. Synonymous RNA editing expands our understanding of the complexity of genetic regulation and its implications for cellular processes and disease.

Modified RNAs and predictions with the ViennaRNA Package.

In living organisms, many RNA molecules are modified post-transcriptionally. This turns the widely known four-letter RNA alphabet ACGU into a much larger one with currently more than 300 known distinct modified bases. The roles for the majority of modified bases remain uncertain, but many are already well-known for their ability to influence the preferred structures that an RNA may adopt. In fact, tRNAs sometimes require certain modifications to fold into their cloverleaf shaped structure. However, predicting the structure of RNAs with base modifications is still difficult due to the lack of efficient algorithms that can deal with the extended sequence alphabet, as well as missing parameter sets that account for the changes in stability induced by the modified bases. We present an approach to include sparse energy parameter data for modified bases into the ViennaRNA Package. Our method does not require any changes to the underlying efficient algorithms but instead uses a set of plug-in constraints that adapt the predictions in terms of loop evaluation at runtime. These adaptations are efficient in the sense that they are only performed for loops where additional parameters are actually available for. In addition, our approach also facilitates the inclusion of more modified bases as soon as further parameters become available. Source code and documentation are available at https://www.tbi.univie.ac.at/RNA.

Mono-valent salt corrections for RNA secondary structures in the ViennaRNA package

BackgroundRNA features a highly negatively charged phosphate backbone that attracts a cloud of counter-ions that reduce the electrostatic repulsion in a concentration dependent manner. Ion concentrations thus have a large influence on folding and stability of RNA structures. Despite their well-documented effects, salt effects are not handled consistently by currently available secondary structure prediction algorithms. Combining Debye-Hückel potentials for line charges and Manning’s counter-ion condensation theory, Einert et al. (Biophys J 100: 2745-2753, 2011) modeled the energetic contributions of monovalent cations on loops and helices.ResultsThe model of Einert et al. is adapted to match the structure of the dynamic programming recursion of RNA secondary structure prediction algorithms. An empirical term describing the salt dependence of the duplex initiation energy is added to improve co-folding predictions for two or more RNA strands. The slightly modified model is implemented in the ViennaRNA package in such way that only the energy parameters but not the algorithmic structure is affected. A comparison with data from the literature show that predicted free energies and melting temperatures are in reasonable agreement with experiments.ConclusionThe new feature in the ViennaRNA package makes it possible to study effects of salt concentrations on RNA folding in a systematic manner. Strictly speaking, the model pertains only to mono-valent cations, and thus covers the most important parameter, i.e., the NaCl concentration. It remains a question for future research to what extent unspecific effects of bi- and tri-valent cations can be approximated in a similar manner.AvailabilityCorrections for the concentration of monovalent cations are available in the ViennaRNA package starting from version 2.6.0.

Local RNA folding revisited.

Most of the functional RNA elements located within large transcripts are local. Local folding therefore serves a practically useful approximation to global structure prediction. Due to the sensitivity of RNA secondary structure prediction to the exact definition of sequence ends, accuracy can be increased by averaging local structure predictions over multiple, overlapping sequence windows. These averages can be computed efficiently by dynamic programming. Here we revisit the local folding problem, present a concise mathematical formalization that generalizes previous approaches and show that correct Boltzmann samples can be obtained by local stochastic backtracing in McCaskill's algorithms but not from local folding recursions. Corresponding new features are implemented in the ViennaRNA package to improve the support of local folding. Applications include the computation of maximum expected accuracy structures from RNAplfold data and a mutual information measure to quantify the sensitivity of individual sequence positions.

Identification and Validation of Mirnas and their Targets that Regulate the Resistance Genes against Fusarium Wilt in Tomato

MicroRNAs (miRNAs) are a specialized group of small RNAs (sRNAs) that regulate gene expression in plants at both transcriptional and post-transcriptional levels. Numerous families of miRNA target genes are involved in regulating plant immunity. In this study, we studied the role of miRNAs in the defensive response against a fungal pathogen, Fusarium oxysporum f. sp. lycopersici, which causes wilt disease in tomatoes. Furthermore, the expression patterns of two novel miRNAs and their targets were validated by qRT-PCR. Moreover, two new miRNAs (miR30 and miR33) were further sequenced by Applied Biosystems, using gene-specific primers. The results showed that four miRNAs, two novel (miR30 and miR33), and two known miRNAs (miR46 and miR49) and their target genes were differentially expressed during the infection with the pathogen. On the other hand, two targets (P4) and (β-1,3-glucanase) showed an inverse correlation in expression with their corresponding (miR46), and (miR33, and miR49), respectively. Our results showed that tomato cv. Pusa Early Dwarf is moderately susceptible to the fungus because its resistance is not well-expressed enough to be attributed to miRNAs. Sequences analysis showed that miR30 and miR33 are highly conserved and are found in different plant species. We predicted the secondary structures of miR30 and miR33 by minimum free energy (MFE). The total free energy of miRNA30 and miR33 was -1.2 and -0.4 kcal/mol respectively, predicted by the Vienna RNA package program V.1.7. The result of this study could improve our comprehension of the role that miRNAs play in tomato resistance to F. oxysporum f. sp. lycopersici. In addition, it will provide novel gene sources to develop resistant breeds.

An Algorithm for the Selection of Probes for Specific Detection of Human Disease Pathogens Using the DNA Microarray Technology.

The aim of the study was to develop an algorithm for the selection of discriminating probes to identify a wide range of causative agents of human infectious diseases.Materials and MethodsThe algorithm for selecting the probes was implemented in the form of the disprose (DIScrimination PRObe SElection) computer program written in the R language. Additionally, third-party software was used: the BLAST+ and ViennaRNA Package programs. The developed algorithm was tested by selecting specific probes for detecting Chlamydophila (Chlamydia) pneumoniae — an atypical bacterial pathogen causing community-acquired pneumonia (CAP). Nucleotide sequences for analysis were downloaded from the NCBI databank.ResultsAn algorithm for the selection of specific probes capable of detecting human infectious pathogens has been developed. The algorithm is implemented in the form of the disprose modular program, which allows for performing all stages of the probe selection process: loading the nucleotide sequences and their metadata from available databanks, creating local databases, forming a pool of probes, calculating their physicochemical parameters, aligning the probes and sequences contained in local databases, processing and evaluating the alignment results. The algorithm was successfully tested and its performance was confirmed by selecting a set of probes for the specific detection of Chlamydophila pneumoniae. The specificity of the selected probes calculated in silico indicated a low risk of their nonspecific binding and a high potential of using them as molecular genetic diagnostic tools (DNA microarrays, PCR).ConclusionAn algorithm for the selection of specific probes detecting a wide range of human pathogens in clinical biomaterial has been developed and implemented in the form of the disprose modular program. The probes selected using this program can serve as the functional basis of DNA-oriented microarrays able to identify causative agents of polyetiological diseases, such as CAP. Due to the flexibility and openness of the program, the scope of its application can be expanded.

The Structural Annotations of The Mir-122 Non-Coding RNA from The Tilapia Fish (Oreochromis niloticus)

Tilapia (Oreochromis niloticus) is an important fisheries commodity. Scientific efforts have been done to increase its quality. One of them is staging a premium diet such as a fat-enriched diet. The transcriptomics approach is able to provide the signatures of the diet outcomes by observing the micro(mi)RNA signature in transcriptional regulation. Hence, it was found that the availability of mir-122 is essential in the regulation of a high-fat diet in tilapia. However, this transcriptomics signature is lacking structural annotations and the complete interaction annotations with its silencing(si)RNA. RNAcentral website was navigated for the latest annotation of mir-122 from tilapia and other species as a comparison. MEGA X was employed to comprehend the miRNA evolutionary repertoire. The RNA secondary structure prediction tools from the Vienna RNA package and the RNA tertiary structure prediction tools from simRNA and modeRNA are secured with default parameters. The HNADOCK tools were leveraged to observe the interaction between mir-122 and its siRNA. The post-processing was conducted with the Chimera visualization tool. The secondary and tertiary structure of the mir-122 and its siRNA could be elucidated, docked, and visualized. In this end, further effort to develop a comprehensive molecular breeding tool could be secured with the structural annotation information.

Design the RNA aptamer of PCA3 long non-coding ribonucleic acid by the coarse-grained molecular mechanics

The stochastic tunneling-basin hopping-discrete molecular dynamics (STUN-BH-DMD) method was applied to predict the tertiary structure of the prostate cancer marker PCA3 using two respective secondary structures predicted by the Vienna RNA package and Mathews lab package. The RNA CG force field with the geometrical restraints for maintaining PCA3 secondary structures is used. For each secondary structure, 5000 PCA3 structures were predicted by using 5000 independent initial structures. These structures were then evaluated by a scoring function, considering the contributions from the radius of gyration, contact energy, and surface fraction of complementary nucleotides to ASO683 and ASO735 used in the related experiment. For each secondary structure, the PCA3 structures with the highest three scores were selected for aptamer design and further adsorption simulation. The ASOs complementary to PCA3 surface segments possessing relatively higher RMSF values are selected to be the potential PCA3 aptamers. After the adsorption simulation, the adsorption energies of ASO961, ASO3181, ASO3533, and ASO3595 are higher than or comparable to those of ASO683 and ASO735 used in the experiment. The NEB method was used to obtain MEPs for the adsorption process of all predicted ASOs onto PCA3. The adsorption barriers range between 29 ∼ 39 kcal/mol, while the desorption barriers range between 112 ∼ 352 kcal/mol, indicating these aptamer/PCA3 complexes are very stable. Using PCA3 surface segments with relatively higher RMSF values, longer ASOs can be also obtained and most longer ASOs possess lower binding energy, ranging between −486.1 and −618.2 kcal/mol. Communicated by Ramaswamy H. Sarma

DsRBPBind: modeling the effect of RNA secondary structure on double-stranded RNA-protein binding.

RNA-binding proteins are fundamental to many cellular processes. Double-stranded RNA-binding proteins (dsRBPs) in particular are crucial for RNA interference, mRNA elongation, A-to-I editing, host defense, splicing and a multitude of other important mechanisms. Since dsRBPs require double-stranded RNA to bind, their binding affinity depends on the competition among all possible secondary structures of the target RNA molecule. Here, we introduce a quantitative model that allows calculation of the effective affinity of dsRBPs to any RNA given a principal affinity and the sequence of the RNA, while fully taking into account the entire secondary structure ensemble of the RNA. We implement our model within the ViennaRNA folding package while maintaining its O(N3) time complexity. We validate our quantitative model by comparing with experimentally determined binding affinities and stoichiometries for transactivation response element RNA-binding protein (TRBP). We also find that the change in dsRBP binding affinity purely due to the presence of alternative RNA structures can be many orders of magnitude and that the predicted affinity of TRBP for pre-miRNA-like constructs correlates with experimentally measured processing rates. Our modified version of the ViennaRNA package is available for download at http://bioserv.mps.ohio-state.edu/dsRBPBind, is free to use for research and educational purposes, and utilizes simple get/set methods for footprint size, concentration, cooperativity, principal dissociation constant and overlap.

RNA Secondary Structures with Limited Base Pair Span: Exact Backtracking and an Application.

The accuracy of RNA secondary structure prediction decreases with the span of a base pair, i.e., the number of nucleotides that it encloses. The dynamic programming algorithms for RNA folding can be easily specialized in order to consider only base pairs with a limited span L, reducing the memory requirements to , and further to by interleaving backtracking. However, the latter is an approximation that precludes the retrieval of the globally optimal structure. So far, the ViennaRNA package therefore does not provide a tool for computing optimal, span-restricted minimum energy structure. Here, we report on an efficient backtracking algorithm that reconstructs the globally optimal structure from the locally optimal fragments that are produced by the interleaved backtracking implemented in RNALfold. An implementation is integrated into the ViennaRNA package. The forward and the backtracking recursions of RNALfold are both easily constrained to structural components with a sufficiently negative z-scores. This provides a convenient method in order to identify hyper-stable structural elements. A screen of the C. elegans genome shows that such features are more abundant in real genomic sequences when compared to a di-nucleotide shuffled background model.

Chemistry Teachers’ Awareness, Understanding, and Confidence toward Computational Tools for Molecular Visualization

Recent advances in cheminformatics and bioinformatics research have generated software and computational tools for molecular modeling and visualization that can be incorporated to improve chemistry teaching and learning in high school. Nevertheless, there have never been any study simultaneously reporting chemistry teachers’ awareness, understanding, and confidence toward contemporary computer-aided molecular modeling and visualization tools. This study examined 32 high school chemistry teachers’ knowledge, understanding and confidence toward nine new computational programs on molecular modeling and visualization namely ChemDraw, HyperChem, UCSF Chimera, Marvin Sketch, PsiPred, MBC (PS2), Rampage, Vienna RNA Package and Mode RNA following two days of professional workshop-based training. After completing the training and assessments, the teachers showed an enhancement in awareness, understanding, and confidence toward those nine computational programs. Intensive activities consisting of theoretical lectures, hands-on practices, assignments, and case study presentations seem to provide valuable resources to the increase in teachers’ knowledge, understanding, and skill that incorporates computational technology. Hence, the impact of this research pointed toward the value of teachers’ professional development that creates a platform to reduce the barriers of access, resources, knowledge, and skills. This study is expected to help improving teachers’ awareness, understanding, and confidence necessarily required for further implementation of available technology for instructional purposes.Â

Determination of secondary and tertiary structures of cervical cancer lncRNA diagnostic and siRNA therapeutic biomarkers

Cervical cancer is one of the primary causes of mortality in women due to human papilloma virus (HPV) infection. The fingerprint of an HPV infection could be detected using a long non-coding RNA (lncRNA) biomarker, enabling it to be utilized in molecular diagnostics. The primary structure or sequences of RNA should be annotated within conventional bioinformatics tools. Therefore, this study aimed to determine the fine-grained 2D and 3D structures of lncRNA PVT1 and its respective siRNA inhibitors. lncRNA PVT1 sequences from Homo sapiens, Mus musculus, and Rattus norvegicus were retrieved from Genbank (NCBI). Prediction of the 2D structure and analysis of the interactions of the lncRNA and siRNA were performed using the Vienna RNA package. The 3D structure of the RNA was computed using the SimRNA and ModeRNA software programs. The results showed that lncRNA PVT1 from H. sapiens and M. musculus had a conserved region. However, the lncRNA from both H. sapiens and M. musculus showed a low conserved region, and the 2D structure could not be determined; thus, the annotation and 2D model focused only on H. sapiens. Both of their lncRNA PVT1 also had a short half-life in the cell. Based on the 3D modeling pipeline, the 3D model of lncRNA PVT1 showed the stability and possible function as molecules, while the PVT1 siRNA-lncRNA interaction analysis revealed that the molecules could bind well. Based on these findings, the structures of both lncRNA PVT1 and its siRNA have the potential to be utilized as biomarkers.

The Construction of Two and Three Dimensional Molecular Models for the miR-31 and Its Silencer as the Triple Negative Breast Cancer Biomarkers

The Triple Negative Breast Cancer (TNBC) is considered as the most difficult Breast Cancer type to be medicated. So far, the acceptable medication and diagnostics measure are based upon the proteomics-world view, especially with utilizing the natural products and their derivatives as drug candidates. However, as the transcriptomics-studies are getting more advanced, the research on non-coding (nc)RNA is being considered as a more feasible approach to deal with the TNBC. The miR-31, as the ncRNA that play part in the molecular mechanism of the TNBC, is extensively studied mainly for providing the biomarker and drug candidate. However, the molecular interaction and structures are mainly unknown and it is subject of investigation of this research. This research is utilizing the interplay of pipelines that consist of the Vienna RNA package for 2D RNA structure prediction and the simRNA/modeRNA packages for 3D RNA structure prediction. The result is a blueprint that satifactionary illustrates the RNA structure in a fine-grained manner. The miR-31 and its respective silencing (si)RNA are indeed could be useful to be biomarkers and blue-print for the drug design of the TNBC.

Ribosome Biogenesis Controls Erythroid Differentiation Via a p53-Dependent Transcriptional Checkpoint and Its Limitation By RPS14 Haploinsufficiency Results in Selective Defects in Translation

Haploinsufficiency in genes encoding ribosomal proteins (RP) or ribosome-associated proteins either by mutation or deletion leads to a predominant erythroid phenotype. In acquired 5q- myelodysplasic syndrome (MDS), the macrocytic anemia has been linked to the monoallelic deletion of RPS14 gene which results in altered ribosome biogenesis. Because of the defective maturation of the small 40S ribosome subunit, the RPL5/RPL11/5SrARN complex, normally involved in the assembly of the large 60S subunit assembly, accumulates and inhibits E3-ligase-HDM2 leading to the stabilization and activation of p53 resultig in cell cycle arrest, increased apoptosis and defective differentiation of maturing erythroblasts. In the present work, we hypothesized that p53 could play a key role in the control of normal erythroid differentiation by ribosome biogenesis and we further investigated the involvement of the decreased pool of ribosome on erythroid defects in the 5q- syndrome.To investigate the first hypothesis, we studied the kinetics of ribosome biogenesis in human primary erythroblasts by mass spectrometry after pulse-SILAC. We noted that ribosome renewal collapses begining at the polychromatophilic erythroblast stage. We subsequently used the pharmacological agent CX-5461 to inhibit RNA polymerase I. When ribosome biogenesis in proerythroblasts is blocked by CX-5461, p53 is activated and proerythroblasts enter the terminal differentiation by expressing GATA1-erythroid target genes without apoptosis. By ChIP-seq in primary erythroblasts, we demonstrated that p53 binds to 1289 genes including 263 genes specifically activated by CX-5461, 6 of them being upregulated during CX-5461-induced erythroid differentiation and 3 of them being known GATA1 targets. We further used an shRNA strategy to demonstrate that one of these genes is required to permit entry into terminal erythroid differentiation when ribosome biogenesis is abrogated. We thus showed that normal erythroid differentiation is controlled by ribosome biogenesis through a p53-dependent checkpoint.In 5q- syndrome, ribosome biogenesis is continuously decreased along all stages of erythropoiesis and in contrast to the normal conditions, erythroid differentiation is defective with an excess of apoptosis affecting mature erythroblasts. We previously reported that GATA1 is targeted by a caspase-dependent cleavage since GATA1 is not protected by its chaperone HSP70 in the nucleus of MDS erythroblasts. We confirmed that GATA1 protein is decreased in 5q- primary erythroblasts and in RPS14 shRNA-expressing normal erythroblasts. To obtain further insights into the defective erythroid maturation of RPS14-deleted erythroblasts, we developed an inducible shRNA to RPS14 in the UT7/Epo cell line. Polysome profiling confirmed the decrease of 40S subunit and absolute quantification of RP by deep proteomics demonstrated a 50% decrease of RPS in conjunction with 50% reduction of ribosome content in these cells. GATA1 expression was decreased and was only partially rescued by treatment with either caspase inhibitor qVD or proteasome inhibitor, bortezomib. We then tested the hypothesis of a decrease in GATA1 translation, as previously shown in a shRNA RPS19 Diamond-Blackfan model, by analyzing and comparing the global transcriptome and the translatome corresponding to transcripts present in high molecular weight polysomes using Affymetrix HTA 2.0 microarrays. We observed a decoupling between transcriptome and translatome suggesting a selectivity of translational defects. Thermodynamic characteristics i.e. the fold energy, energy per base and length of the 3'UTR and the energy per base of the 5'UTR (Vienna RNA Package, UCSC genome browser) were the determinants of transcript selection on the polysome. The shortest transcripts with a highly structured 3'UTR including GATA1 were the transcripts which were less effectively translated. Consistently, the diminution of GATA1 protein was associated with a decrease of its target genes. Our results suggest that GATA1 is a potentially interesting therapeutic target.In summary, our results show that ribosome biogenesis controls erythroid differentiation via a p53-dependent transcriptional regulation and that a reduction of the ribosome pool leads to a selective translation at the expense of erythroid master gene GATA1. DisclosuresFontenay:Celgene: Research Funding.

Sparse RNA folding revisited: space-efficient minimum free energy structure prediction

BackgroundRNA secondary structure prediction by energy minimization is the central computational tool for the analysis of structural non-coding RNAs and their interactions. Sparsification has been successfully applied to improve the time efficiency of various structure prediction algorithms while guaranteeing the same result; however, for many such folding problems, space efficiency is of even greater concern, particularly for long RNA sequences. So far, space-efficient sparsified RNA folding with fold reconstruction was solved only for simple base-pair-based pseudo-energy models.ResultsHere, we revisit the problem of space-efficient free energy minimization. Whereas the space-efficient minimization of the free energy has been sketched before, the reconstruction of the optimum structure has not even been discussed. We show that this reconstruction is not possible in trivial extension of the method for simple energy models. Then, we present the time- and space-efficient sparsified free energy minimization algorithm SparseMFEFold that guarantees MFE structure prediction. In particular, this novel algorithm provides efficient fold reconstruction based on dynamically garbage-collected trace arrows. The complexity of our algorithm depends on two parameters, the number of candidates Z and the number of trace arrows T; both are bounded by n^2, but are typically much smaller. The time complexity of RNA folding is reduced from O(n^3) to O(n^2+nZ); the space complexity, from O(n^2) to O(n + T + Z). Our empirical results show more than 80 % space savings over RNAfold [Vienna RNA package] on the long RNAs from the RNA STRAND database (≥2500 bases).ConclusionsThe presented technique is intentionally generalizable to complex prediction algorithms; due to their high space demands, algorithms like pseudoknot prediction and RNA–RNA-interaction prediction are expected to profit even stronger than “standard” MFE folding. SparseMFEFold is free software, available at http://www.bioinf.uni-leipzig.de/~will/Software/SparseMFEFold.

RNA folding with hard and soft constraints.

BackgroundA large class of RNA secondary structure prediction programs uses an elaborate energy model grounded in extensive thermodynamic measurements and exact dynamic programming algorithms. External experimental evidence can be in principle be incorporated by means of hard constraints that restrict the search space or by means of soft constraints that distort the energy model. In particular recent advances in coupling chemical and enzymatic probing with sequencing techniques but also comparative approaches provide an increasing amount of experimental data to be combined with secondary structure prediction.ResultsResponding to the increasing needs for a versatile and user-friendly inclusion of external evidence into diverse flavors of RNA secondary structure prediction tools we implemented a generic layer of constraint handling into the ViennaRNA Package. It makes explicit use of the conceptual separation of the “folding grammar” defining the search space and the actual energy evaluation, which allows constraints to be interleaved in a natural way between recursion steps and evaluation of the standard energy function.ConclusionsThe extension of the ViennaRNA Package provides a generic way to include diverse types of constraints into RNA folding algorithms. The computational overhead incurred is negligible in practice. A wide variety of application scenarios can be accommodated by the new framework, including the incorporation of structure probing data, non-standard base pairs and chemical modifications, as well as structure-dependent ligand binding.Electronic supplementary materialThe online version of this article (doi:10.1186/s13015-016-0070-z) contains supplementary material, which is available to authorized users.

SHAPE directed RNA folding.

Summary: Chemical mapping experiments allow for nucleotide resolution assessment of RNA structure. We demonstrate that different strategies of integrating probing data with thermodynamics-based RNA secondary structure prediction algorithms can be implemented by means of soft constraints. This amounts to incorporating suitable pseudo-energies into the standard energy model for RNA secondary structures. As a showcase application for this new feature of the ViennaRNA Package we compare three distinct, previously published strategies to utilize SHAPE reactivities for structure prediction. The new tool is benchmarked on a set of RNAs with known reference structure.Availability and implementation: The capability for SHAPE directed RNA folding is part of the upcoming release of the ViennaRNA Package 2.2, for which a preliminary release is already freely available at http://www.tbi.univie.ac.at/RNA.Contact: michael.wolfinger@univie.ac.atSupplementary information: Supplementary data are available at Bioinformatics online.

Sequence-controlled RNA self-processing: computational design, biochemical analysis, and visualization by AFM.

Reversible chemistry allowing for assembly and disassembly of molecular entities is important for biological self-organization. Thus, ribozymes that support both cleavage and formation of phosphodiester bonds may have contributed to the emergence of functional diversity and increasing complexity of regulatory RNAs in early life. We have previously engineered a variant of the hairpin ribozyme that shows how ribozymes may have circularized or extended their own length by forming concatemers. Using the Vienna RNA package, we now optimized this hairpin ribozyme variant and selected four different RNA sequences that were expected to circularize more efficiently or form longer concatemers upon transcription. (Two-dimensional) PAGE analysis confirms that (i) all four selected ribozymes are catalytically active and (ii) high yields of cyclic species are obtained. AFM imaging in combination with RNA structure prediction enabled us to calculate the distributions of monomers and self-concatenated dimers and trimers. Our results show that computationally optimized molecules do form reasonable amounts of trimers, which has not been observed for the original system so far, and we demonstrate that the combination of theoretical prediction, biochemical and physical analysis is a promising approach toward accurate prediction of ribozyme behavior and design of ribozymes with predefined functions.

StructureFold: genome-wide RNA secondary structure mapping and reconstruction in vivo.

RNAs fold into complex structures that are integral to the diverse mechanisms underlying RNA regulation of gene expression. Recent development of transcriptome-wide RNA structure profiling through the application of structure-probing enzymes or chemicals combined with high-throughput sequencing has opened a new field that greatly expands the amount of in vitro and in vivo RNA structural information available. The resultant datasets provide the opportunity to investigate RNA structural information on a global scale. However, the analysis of high-throughput RNA structure profiling data requires considerable computational effort and expertise. We present a new platform, StructureFold, that provides an integrated computational solution designed specifically for large-scale RNA structure mapping and reconstruction across any transcriptome. StructureFold automates the processing and analysis of raw high-throughput RNA structure profiling data, allowing the seamless incorporation of wet-bench structural information from chemical probes and/or ribonucleases to restrain RNA secondary structure prediction via the RNAstructure and ViennaRNA package algorithms. StructureFold performs reads mapping and alignment, normalization and reactivity derivation, and RNA structure prediction in a single user-friendly web interface or via local installation. The variation in transcript abundance and length that prevails in living cells and consequently causes variation in the counts of structure-probing events between transcripts is accounted for. Accordingly, StructureFold is applicable to RNA structural profiling data obtained in vivo as well as to in vitro or in silico datasets. StructureFold is deployed via the Galaxy platform. StructureFold is freely available as a component of Galaxy available at: https://usegalaxy.org/. yxt148@psu.edu or sma3@psu.edu Supplementary data are available at Bioinformatics online.