RNA Secondary Structure Models Research Articles

RNA Folding, Mutation, and Detection.

The structure of RNA molecules is absolutely critical to their functions in a biological system. RNA structure is dynamic and changes in response to cellular needs. Within the last few decades, there has been an increased interest in studying the structure of RNA molecules and how they change to support the needs of the cell in different conditions. Selective 2'-hydroxyl acylation-based mutational profiling using high-throughput sequencing is a powerful method to predict the secondary structure of RNA molecules both in vivo and in immunopurified samples. Selective 2'-hydroxyl acylation-based mutational profiling using high-throughput sequencing works by adding bulky groups onto accessible "flexible" bases in an RNA molecule that are not involved in any base-pairing or RNA-protein interactions. When the RNA is reverse transcribed into cDNA, the bulky groups are incorporated as base mutations, which can be compared to an unmodified control to identify the locations of flexible bases. The comparison ofsequence data between modified and unmodified samples allows the computer software program (developed to generate reactivity profiles) to generate RNA secondary structure models. These models can be compared in a variety of conditions to determine how specific stimuli influence RNA secondary structures.

Complex and simple translational readthrough signals in pea enation mosaic virus 1 and potato leafroll virus, respectively.

Different essential viral proteins are translated via programmed stop codon readthrough. Pea enation mosaic virus 1 (PEMV1) and potato leafroll virus (PLRV) are related positive-sense RNA plant viruses in the family Solemoviridae, and are type members of the Enamovirus and Polerovirus genera, respectively. Both use translational readthrough to express a C-terminally extended minor capsid protein (CP), termed CP-readthrough domain (CP-RTD), from a viral subgenomic mRNA that is transcribed during infections. Limited incorporation of CP-RTD subunits into virus particles is essential for aphid transmission, however the functional readthrough structures that mediate CP-RTD translation have not yet been defined. Through RNA solution structure probing, RNA secondary structure modeling, site-directed mutagenesis, and functional in vitro and in vivo analyses, we have investigated in detail the readthrough elements and complex structure involved in expression of CP-RTD in PEMV1, and assessed and deduced a comparatively simpler readthrough structure for PLRV. Collectively, this study has (i) generated the first higher-order RNA structural models for readthrough elements in an enamovirus and a polerovirus, (ii) revealed a stark contrast in the complexity of readthrough structures in these two related viruses, (iii) provided compelling experimental evidence for the strict requirement for long-distance RNA-RNA interactions in generating the active readthrough signals, (iv) uncovered what could be considered the most complex readthrough structure reported to date, that for PEMV1, and (v) proposed plausible assembly pathways for the formation of the elaborate PEMV1 and simple PLRV readthrough structures. These findings notably advance our understanding of this essential mode of gene expression in these agriculturally important plant viruses.

Trans-Activator Binding Site Context in RCNMV Modulates Subgenomic mRNA Transcription.

Many positive-sense RNA viruses transcribe subgenomic (sg) mRNAs during infections that template the translation of a subset of viral proteins. Red clover necrotic mosaic virus (RCNMV) expresses its capsid protein through the transcription of a sg mRNA from RNA1 genome segment. This transcription event is activated by an RNA structure formed by base pairing between a trans-activator (TA) in RNA2 and a trans-activator binding site (TABS) in RNA1. In this study, the impact of the structural context of the TABS in RNA1 on the TA–TABS interaction and sg mRNA transcription was investigated using in vitro and in vivo approaches. The results (i) generated RNA secondary structure models for the TA and TABS, (ii) revealed that the TABS is partially base paired with proximal upstream sequences, which limits TA access, (iii) demonstrated that the aforementioned intra-RNA1 base pairing involving the TABS modulates the TA–TABS interaction in vitro and sg mRNA levels during infections, and (iv) revealed that the TABS in RNA1 can be modified to mediate sg mRNA transcription in a TA-independent manner. These findings advance our understanding of transcriptional regulation in RCNMV and provide novel insights into the origin of the TA–TABS interaction.

3′UTR SL-IV and DB1 Regions Contribute to Japanese Encephalitis Virus Replication and Pathogenicity

Japanese encephalitis virus (JEV), a mosquito-borne flavivirus that causes fatal neurological disease in humans, is one of the most important emerging pathogens of public health significance. JEV is maintained in an enzootic cycle and causes reproductive failure in pigs. Notably, the shift in JEV genotypes is not fully protected by existing vaccines, so the development of a candidate vaccine is urgently needed. In this study, we compared pathogenicity between Japanese encephalitis virus SA14 and BJB (isolated from humans in the 1970s) strains. We found that the BJB strain was attenuated in mice and that there was no case fatality rate. The growth rate of BJB was higher than SA14 virus in BHK-21 cells. Based on the sequence alignment of the viral genome between the SA14 and BJB virus strains, some mutations at sites 248, 254, 258, and 307 were observed in the 3′ untranslated region (3′UTR). The 3′UTR of JEV plays a very important role in the viral life cycle. Furthermore, using a reverse genetic system, we conducted and rescued the parental JEV strain SA14 (T248, A254, and A258) and the mutant virus rSA14-3′UTRmut (T248C, A254G, A258G, and 307G). Through an analysis of the RNA secondary structure model of the 3′UTR, we discovered that the mutations of T248C, A254G, and A258G reduced the apiculus ring and increased the lateral ring significantly in the stem-loop structures IV (SL-IV) structure region of 3′UTR. Moreover, the insertion of 307G added a ring to the dumbbell structure 1 (DB1) structure region. Strikingly, these RNA secondary structure changes in 3′UTR of rSA14-3′UTRmut increased viral negative chain RNA production and enhanced the replication ability of the virus in BHK-21 cells. However, in vivo mouse experiments illustrated that the rSA14-3′UTRmut virus significantly decreased the neurovirulence of JEV. These results affirmed that the JEV SL-IV and DB1 regions play an important role in viral proliferation and pathogenicity. Taken together, we complement the study of RNA element function in the 3′UTR region of JEV by providing a new target for the rational design of live attenuated candidate vaccines and the increase of virus production.

In vivo structure of the Ty1 retrotransposon RNA genome.

Long terminal repeat (LTR)-retrotransposons constitute a significant part of eukaryotic genomes and influence their function and evolution. Like other RNA viruses, LTR-retrotransposons efficiently utilize their RNA genome to interact with host cell machinery during replication. Here, we provide the first genome-wide RNA secondary structure model for a LTR-retrotransposon in living cells. Using SHAPE probing, we explore the secondary structure of the yeast Ty1 retrotransposon RNA genome in its native in vivo state and under defined in vitro conditions. Comparative analyses reveal the strong impact of the cellular environment on folding of Ty1 RNA. In vivo, Ty1 genome RNA is significantly less structured and more dynamic but retains specific well-structured regions harboring functional cis-acting sequences. Ribosomes participate in the unfolding and remodeling of Ty1 RNA, and inhibition of translation initiation stabilizes Ty1 RNA structure. Together, our findings support the dual role of Ty1 genomic RNA as a template for protein synthesis and reverse transcription. This study also contributes to understanding how a complex multifunctional RNA genome folds in vivo, and strengthens the need for studying RNA structure in its natural cellular context.

Relative Information Gain: Shannon entropy-based measure of the relative structural conservation in RNA alignments.

Structural characterization of RNAs is a dynamic field, offering many modelling possibilities. RNA secondary structure models are usually characterized by an encoding that depicts structural information of the molecule through string representations or graphs. In this work, we provide a generalization of the BEAR encoding (a context-aware structural encoding we previously developed) by expanding the set of alignments used for the construction of substitution matrices and then applying it to secondary structure encodings ranging from fine-grained to more coarse-grained representations. We also introduce a re-interpretation of the Shannon Information applied on RNA alignments, proposing a new scoring metric, the Relative Information Gain (RIG). The RIG score is available for any position in an alignment, showing how different levels of detail encoded in the RNA representation can contribute differently to convey structural information. The approaches presented in this study can be used alongside state-of-the-art tools to synergistically gain insights into the structural elements that RNAs and RNA families are composed of. This additional information could potentially contribute to their improvement or increase the degree of confidence in the secondary structure of families and any set of aligned RNAs.

Classifying Conserved RNA Secondary Structures With Pseudoknots by Vector-Edit Distance

Secondary structures have been proved to relate with the great functional diversity of RNA. There have been many studies to predict and compare the RNA secondary structures. However, fast and accurate comparison of RNA secondary structures with arbitrary pseudoknots is a challenging issue due to the hidden but important structural properties, such as the distribution of stems and branches. In this paper, we construct a novel RNA secondary structure model called modified adjoining grammars binary tree ( $\mathrm {BTMG_{CSP}}$ ). It can not only represent the complex RNA secondary structure including arbitrary pseudoknots intuitively, but also reserve RNA secondary structure properties. Further, we propose vector-edit distance to measure the structure similarity between $\mathrm {BTMG_{CSP}}$ trees converted from RNA sequences and their secondary structures for classifying conserved stem pattern. The experimental results show that our method substantially reduces the memory and time consumption in contrast to previous algorithms, such as $O((n/k)^{2}) $ and $O(n/k) $ for time and space complexity, respectively. In particular, the AUC value of our method achieves 0.949 in PseudoBase.

IRIS: A method for predicting in vivo RNA secondary structures using PARIS data

BackgroundRNA secondary structures play a pivotal role in posttranscriptional regulation and the functions of non‐coding RNAs, yet in vivo RNA secondary structures remain enigmatic. PARIS (Psoralen Analysis of RNA Interactions and Structures) is a recently developed high‐throughput sequencing‐based approach that enables direct capture of RNA duplex structures in vivo. However, the existence of incompatible, fuzzy pairing information obstructs the integration of PARIS data with the existing tools for reconstructing RNA secondary structure models at the single‐base resolution.MethodsWe introduce IRIS, a method for predicting RNA secondary structure ensembles based on PARIS data. IRIS generates a large set of candidate RNA secondary structure models under the guidance of redistributed PARIS reads and then uses a Bayesian model to identify the optimal ensemble, according to both thermodynamic principles and PARIS data.ResultsThe predicted RNA structure ensembles by IRIS have been verified based on evolutionary conservation information and consistency with other experimental RNA structural data. IRIS is implemented in Python and freely available at http://iris.zhanglab.net.ConclusionIRIS capitalizes upon PARIS data to improve the prediction of in vivo RNA secondary structure ensembles. We expect that IRIS will enhance the application of the PARIS technology and shed more insight on in vivo RNA secondary structures.

Modeling Loop Composition and Ion Concentration Effects in RNA Hairpin Folding Stability

The ability to accurately predict RNA hairpin structure and stability for different loop sequences and salt conditions is important for understanding, modeling, and designing larger RNA folds. However, traditional RNA secondary structure models cannot treat loop-sequence and ionic effects on RNA hairpin folding. Here, we describe a general, three-dimensional (3D) conformation-based computational method for modeling salt concentration-dependent conformational distributions and the detailed 3D structures for a set of three RNA hairpins that contain a variable, 15-nucleotide loop sequence. For a given RNA sequence, the new, to our knowledge, method integrates a Vfold2D two-dimensional structure folding model with IsRNA coarse-grained molecular dynamics 3D folding simulations and Monte Carlo tightly bound ion estimations of ion-mediated electrostatic interactions. The model predicts free-energy landscapes for the different RNA hairpin-forming sequences with variable salt conditions. The theoretically predicted results agree with the experimental fluorescence measurements, validating the strategy. Furthermore, the theoretical model goes beyond the experimental results by enabling in-depth 3D structural analysis, revealing energetic mechanisms for the sequence- and salt-dependent folding stability. Although the computational framework presented here is developed for RNA hairpin systems, the general method may be applied to investigate other RNA systems, such as multiway junctions or pseudoknots in mixed metal ion solutions.

Design of Artificial Riboswitches as Biosensors.

RNA aptamers readily recognize small organic molecules, polypeptides, as well as other nucleic acids in a highly specific manner. Many such aptamers have evolved as parts of regulatory systems in nature. Experimental selection techniques such as SELEX have been very successful in finding artificial aptamers for a wide variety of natural and synthetic ligands. Changes in structure and/or stability of aptamers upon ligand binding can propagate through larger RNA constructs and cause specific structural changes at distal positions. In turn, these may affect transcription, translation, splicing, or binding events. The RNA secondary structure model realistically describes both thermodynamic and kinetic aspects of RNA structure formation and refolding at a single, consistent level of modelling. Thus, this framework allows studying the function of natural riboswitches in silico. Moreover, it enables rationally designing artificial switches, combining essentially arbitrary sensors with a broad choice of read-out systems. Eventually, this approach sets the stage for constructing versatile biosensors.

Chemogenomics driven discovery of endogenous polyketide anti-infective compounds from endosymbiotic Emericella variecolor CLB38 and their RNA secondary structure analysis.

In the postgenomic era, a new strategy for chemical dereplication of polyketide anti-infective drugs requires novel genomics and chromatographic strategies. An endosymbiotic fungal strain CLB38 was isolated from the root tissue of Combretum latifolium Blume (Combretaceae) which was collected from the Western Ghats of India. The isolate CLB38 was then identified as Emericella variecolor by its characteristic stellate ascospores culture morphology and molecular analysis of ITS nuclear rDNA and intervening 5.8S rRNA gene sequence. ITS2 RNA secondary structure modeling clearly distinguished fungal endosymbiont E. variecolor CLB38 with other lifestyles in the same monophyletic clade. Ethyl acetate fraction of CLB38 explored a broad spectrum of antimicrobial activity against multidrug resistant pathogens. Biosynthetic PKS type-I gene and chromatographic approach afford two polyketide antimicrobial compounds which identified as evariquinone and isoindolones derivative emerimidine A. MIC of purified compounds against test microorganisms ranged between 3.12 μg/ml and 12.5 μg/ml. This research highlights the utility of E. variecolor CLB38 as an anticipate source for anti-infective polyketide metabolites evariquinone and emerimidine A to combat multidrug resistant microorganisms. Here we demonstrates a chemogenomics strategy via the feasibility of PKS type-I gene and chromatographic approach as a proficient method for the rapid prediction and discovery of new polyketides compounds from fungal endosymbionts.

Probing Xist RNA Structure in Cells Using Targeted Structure-Seq.

The long non-coding RNA (lncRNA) Xist is a master regulator of X-chromosome inactivation in mammalian cells. Models for how Xist and other lncRNAs function depend on thermodynamically stable secondary and higher-order structures that RNAs can form in the context of a cell. Probing accessible RNA bases can provide data to build models of RNA conformation that provide insight into RNA function, molecular evolution, and modularity. To study the structure of Xist in cells, we built upon recent advances in RNA secondary structure mapping and modeling to develop Targeted Structure-Seq, which combines chemical probing of RNA structure in cells with target-specific massively parallel sequencing. By enriching for signals from the RNA of interest, Targeted Structure-Seq achieves high coverage of the target RNA with relatively few sequencing reads, thus providing a targeted and scalable approach to analyze RNA conformation in cells. We use this approach to probe the full-length Xist lncRNA to develop new models for functional elements within Xist, including the repeat A element in the 5’-end of Xist. This analysis also identified new structural elements in Xist that are evolutionarily conserved, including a new element proximal to the C repeats that is important for Xist function.

Full-length RNA structure prediction of the HIV-1 genome reveals a conserved core domain.

A distance constrained secondary structural model of the ≈10 kb RNA genome of the HIV-1 has been predicted but higher-order structures, involving long distance interactions, are currently unknown. We present the first global RNA secondary structure model for the HIV-1 genome, which integrates both comparative structure analysis and information from experimental data in a full-length prediction without distance constraints. Besides recovering known structural elements, we predict several novel structural elements that are conserved in HIV-1 evolution. Our results also indicate that the structure of the HIV-1 genome is highly variable in most regions, with a limited number of stable and conserved RNA secondary structures. Most interesting, a set of long distance interactions form a core organizing structure (COS) that organize the genome into three major structural domains. Despite overlapping protein-coding regions the COS is supported by a particular high frequency of compensatory base changes, suggesting functional importance for this element. This new structural element potentially organizes the whole genome into three major domains protruding from a conserved core structure with potential roles in replication and evolution for the virus.

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.

Combinatorics of RNA Secondary Structures with Base Triples.

The structure of RNA has been the subject of intense research over the last decades due to its importance for the correct functioning of RNA molecules in biological processes. Hence, a large number of models for RNA folding and corresponding algorithms for structure prediction have been developed. However, previous models often only consider base pairs, although every base is capable of up to three edge-to-edge interactions with other bases. Recently, Höner zu Siederdissen et al. presented an extended model of RNA secondary structure, including base triples together with a folding algorithm-the first thermodynamics-based algorithm that allows the prediction of secondary structures with base triples. In this article, we investigate the search space processed by this new algorithm, that is, the combinatorics of extended RNA secondary structures with base triples. We present generalized definitions for structural motifs like hairpins, stems, bulges, or interior loops occurring in structures with base triples. Furthermore, we prove precise asymptotic results for the number of different structures (size of search space) and expectations for various parameters associated with structural motifs (typical shape of folding). Our analysis shows that the asymptotic number of secondary structures of size n increases exponentially to [Formula: see text] compared to the classic model by Stein and Waterman for which [Formula: see text] structures exist. A comparison with the classic model reveals large deviations in the expected structural appearance, too. The inclusion of base triples constitutes a significant refinement of the combinatorial model of RNA secondary structure, which, by our findings, is quantitatively characterized. Our results are of special theoretical interest, because a closer look at the numbers involved suggests that extended RNA secondary structures constitute a new combinatorial class not bijective with any other combinatorial objects studied so far.

RNA secondary structure modeling at consistent high accuracy using differential SHAPE.

RNA secondary structure modeling is a challenging problem, and recent successes have raised the standards for accuracy, consistency, and tractability. Large increases in accuracy have been achieved by including data on reactivity toward chemical probes: Incorporation of 1M7 SHAPE reactivity data into an mfold-class algorithm results in median accuracies for base pair prediction that exceed 90%. However, a few RNA structures are modeled with significantly lower accuracy. Here, we show that incorporating differential reactivities from the NMIA and 1M6 reagents--which detect noncanonical and tertiary interactions--into prediction algorithms results in highly accurate secondary structure models for RNAs that were previously shown to be difficult to model. For these RNAs, 93% of accepted canonical base pairs were recovered in SHAPE-directed models. Discrepancies between accepted and modeled structures were small and appear to reflect genuine structural differences. Three-reagent SHAPE-directed modeling scales concisely to structurally complex RNAs to resolve the in-solution secondary structure analysis problem for many classes of RNA.

RNA secondary structure modeling at consistent high accuracy using differential SHAPE

RNA secondary structure modeling at consistent high accuracy using differential SHAPE

On the role of four small hairpins in the HIV-1 RNA genome

An RNA secondary structure model for the complete HIV-1 genome has recently been published based on SHAPE technology. Several well-known RNA motifs such as TAR and RRE were confirmed and numerous new structured motifs were described that may play important roles in virus replication. The 9 kb viral RNA genome is densely packed with many RNA hairpin motifs and the collective fold may play an important role in HIV-1 biology. We initially focused on 16 RNA hairpin motifs scattered along the viral genome. We considered conservation of these structures, despite sequence variation among virus isolates, as a first indication for a significant function. Four relatively small hairpins exhibited considerable structural conservation and were selected for experimental validation in virus replication assays. Mutations were introduced into the HIV-1 RNA genome to destabilize individual RNA structures without affecting the protein-coding properties (silent codon changes). No major virus replication defects were scored, suggesting that these four hairpin structures do not play essential roles in HIV-1 replication.

Accurate SHAPE-directed RNA secondary structure modeling, including pseudoknots

A pseudoknot forms in an RNA when nucleotides in a loop pair with a region outside the helices that close the loop. Pseudoknots occur relatively rarely in RNA but are highly overrepresented in functionally critical motifs in large catalytic RNAs, in riboswitches, and in regulatory elements of viruses. Pseudoknots are usually excluded from RNA structure prediction algorithms. When included, these pairings are difficult to model accurately, especially in large RNAs, because allowing this structure dramatically increases the number of possible incorrect folds and because it is difficult to search the fold space for an optimal structure. We have developed a concise secondary structure modeling approach that combines SHAPE (selective 2'-hydroxyl acylation analyzed by primer extension) experimental chemical probing information and a simple, but robust, energy model for the entropic cost of single pseudoknot formation. Structures are predicted with iterative refinement, using a dynamic programming algorithm. This melded experimental and thermodynamic energy function predicted the secondary structures and the pseudoknots for a set of 21 challenging RNAs of known structure ranging in size from 34 to 530 nt. On average, 93% of known base pairs were predicted, and all pseudoknots in well-folded RNAs were identified.

Evaluation of the authenticity of a highly novel environmental sequence from boreal forest soil using ribosomal RNA secondary structure modeling

The number of sequences from both formally described taxa and uncultured environmental DNA deposited in the International Nucleotide Sequence Databases has increased substantially over the last two decades. Although the majority of these sequences represent authentic gene copies, there is evidence of DNA artifacts in these databases as well. These include lab artifacts, such as PCR chimeras, and biological artifacts such as pseudogenes or other paralogous sequences. Sequences that fall in basal positions in phylogenetic trees and appear distant from known sequences are particularly suspect. Phylogenetic analyses suggest that a novel sequence type (NS1) found in two boreal forest soil clone libraries belongs to the fungal kingdom but does not fall unambiguously within any known phylum. We have evaluated this sequence type using an array of secondary-structure analyses. To our knowledge, such analyses have never been used on environmental ribosomal sequences. Ribosomal secondary structure was modeled for four rRNA loci (ITS1, 5.8S, ITS2, 5′ LSU). These models were analyzed for the presence of conserved domains, conserved nucleotide motifs, and compensatory base changes. Minimal free energy (MFE) foldings and GC contents of sequences representing the major fungal clades, as well as NS1, were also compared. NS1 displays secondary rRNA structures consistent with other fungi and many, but not all, conserved nucleotide motifs found across eukaryotes. However, our analyses show that many other authentic sequences from basal fungi lack more of these conserved motifs than does NS1. Together our findings suggest that NS1 represents an authentic gene copy. The methods described here can be used on any rRNA-coding sequence, not just environmental fungal sequences. As new-generation sequencing methods that yield shorter sequences become more widely implemented, methods that evaluate sequence authenticity should also be more widely implemented. For fungi, the adjacent 5.8S and ITS2 loci should be prioritized. This region is not only suited to distinguishing between closely related species, but it is also more informative in terms of expected secondary structure.