Large RNA Structures Research Articles

Predicting Small Molecule Binding Nucleotides in RNA Structures Using RNA Surface Topography.

RNA small molecule interactions play a crucial role in drug discovery and inhibitor design. Identifying RNA small molecule binding nucleotides is essential and requires methods that exhibit a high predictive ability to facilitate drug discovery and inhibitor design. Existing methods can predict the binding nucleotides of simple RNA structures, but it is hard to predict binding nucleotides in complex RNA structures with junctions. To address this limitation, we developed a new deep learning model based on spatial correlation, ZHmolReSTasite, which can accurately predict binding nucleotides of small and large RNA with junctions. We utilize RNA surface topography to consider the spatial correlation, characterizing nucleotides from sequence and tertiary structures to learn a high-level representation. Our method outperforms existing methods for benchmark test sets composed of simple RNA structures, achieving precision values of 72.9% on TE18 and 76.7% on RB9 test sets. For a challenging test set composed of RNA structures with junctions, our method outperforms the second best method by 11.6% in precision. Moreover, ZHmolReSTasite demonstrates robustness regarding the predicted RNA structures. In summary, ZHmolReSTasite successfully incorporates spatial correlation, outperforms previous methods on small and large RNA structures using RNA surface topography, and can provide valuable insights into RNA small molecule prediction and accelerate RNA inhibitor design.

Prediction of 3D RNA Structures from Sequence Using Energy Landscapes of RNA Dimers: Application to RNA Tetraloops.

Access to the three-dimensional structure of RNA enables an ability to gain a more profound understanding of its biological mechanisms, as well as the ability to design RNA-targeting drugs, which can take advantage of the unique chemical environment imposed by a folded RNA structure. Due to the dynamic and structurally complex properties of RNA, both experimental and traditional computational methods have difficulty in determining RNA's 3D structure. Herein, we introduce TAPERSS (Theoretical Analyses, Prediction, and Evaluation of RNA Structures from Sequence), a physics-based fragment assembly method for predicting 3D RNA structures from sequence. Using a fragment library created using discrete path sampling calculations of RNA dinucleoside monophosphates, TAPERSS can sample the physics-based energy landscapes of any RNA sequence with relatively low computational complexity. We have benchmarked TAPERSS on 21 RNA tetraloops, using a combinatorial algorithm as a proof-of-concept. We show that TAPERSS was successfully able to predict the apo-state structures of all 21 RNA hairpins, with 16 of those structures also having low predicted energies as well. We demonstrate that TAPERSS performs most accurately on GNRA-like tetraloops with mostly stacked loop-nucleotides, while having limited success with more dynamic UNCG and CUYG tetraloops, most likely due to the influence of the RNA force field used to create the fragment library. Moreover, we show that TAPERSS can successfully predict the majority of the experimental non-apo states, highlighting its potential in anticipating biologically significant yet unobserved states. This holds great promise for future applications in drug design and related studies. With discussed improvements and implementation of more efficient sampling algorithms, we believe TAPERSS may serve as a useful tool for a physics-based conformational sampling of large RNA structures.

High-Resolution Atomic Force Microscopy Imaging of RNA Molecules in Solution.

Atomic force microscopy (AFM) is an important and versatile technique to investigate the structures and dynamics of biomolecules under physiologically relevant conditions at the single-molecule level. Recent progresses in high-resolution AFM imaging of nucleic acids have expanded this technique from simple characterization of double-stranded DNA or RNA to detailed analyses of the structure and dynamics of large functional RNAs with complex folds. Several technical developments, such as sharper probes and more stable instruments with novel imaging modes, AFM is capable of directly visualizing RNA conformational heterogeneity in solution in real time. Here, we introduce a comprehensive method for recording high-resolution images of RNA molecules, including sample preparation, instrument setup, data acquisition, and image processing.

The Potential Role of RNA Structure in Crop Molecular Breeding.

The continually growing human population creates a concomitantly increasing demand for nutritious crops with high yields. Advances in high throughput sequencing technologies have revealed the genetic architecture of major crops. This includes extensive information enabling comprehensive genetic markers for breeding selection, new gene discoveries, and novel gene regulatory strategies for crop editing. RNA structure is an important type of genetic feature, essential for post-transcriptional regulation of gene expression. Here, we summarize recent advances in genome-wide RNA structure studies in crops and review the associated RNA structure-mediated regulation of gene expression. We also discuss the functional importance of those single nucleotide variations that induce large RNA structure disparities. Lastly, we discuss the potential role of RNA structure in crop molecular breeding.

Wheat in vivo RNA structure landscape reveals a prevalent role of RNA structure in modulating translational subgenome expression asymmetry

BackgroundPolyploidy, especially allopolyploidy, which entails merging divergent genomes via hybridization and whole-genome duplication (WGD), is a major route to speciation in plants. The duplication among the parental genomes (subgenomes) often leads to one subgenome becoming dominant over the other(s), resulting in subgenome asymmetry in gene content and expression. Polyploid wheats are allopolyploids with most genes present in two (tetraploid) or three (hexaploid) functional copies, which commonly show subgenome expression asymmetry. It is unknown whether a similar subgenome asymmetry exists during translation. We aim to address this key biological question and explore the major contributing factors to subgenome translation asymmetry.ResultsHere, we obtain the first tetraploid wheat translatome and reveal that subgenome expression asymmetry exists at the translational level. We further perform in vivo RNA structure profiling to obtain the wheat RNA structure landscape and find that mRNA structure has a strong impact on translation, independent of GC content. We discover a previously uncharacterized contribution of RNA structure in subgenome translation asymmetry. We identify 3564 single-nucleotide variations (SNVs) across the transcriptomes between the two tetraploid wheat subgenomes, which induce large RNA structure disparities. These SNVs are highly conserved within durum wheat cultivars but are divergent in both domesticated and wild emmer wheat.ConclusionsWe successfully determine both the translatome and in vivo RNA structurome in tetraploid wheat. We reveal that RNA structure serves as an important modulator of translational subgenome expression asymmetry in polyploids. Our work provides a new perspective for molecular breeding of major polyploid crops.

Progress toward SHAPE Constrained Computational Prediction of Tertiary Interactions in RNA Structure.

As more sequencing data accumulate and novel puzzling genetic regulations are discovered, the need for accurate automated modeling of RNA structure increases. RNA structure modeling from chemical probing experiments has made tremendous progress, however accurately predicting large RNA structures is still challenging for several reasons: RNA are inherently flexible and often adopt many energetically similar structures, which are not reliably distinguished by the available, incomplete thermodynamic model. Moreover, computationally, the problem is aggravated by the relevance of pseudoknots and non-canonical base pairs, which are hardly predicted efficiently. To identify nucleotides involved in pseudoknots and non-canonical interactions, we scrutinized the SHAPE reactivity of each nucleotide of the 188 nt long lariat-capping ribozyme under multiple conditions. Reactivities analyzed in the light of the X-ray structure were shown to report accurately the nucleotide status. Those that seemed paradoxical were rationalized by the nucleotide behavior along molecular dynamic simulations. We show that valuable information on intricate interactions can be deduced from probing with different reagents, and in the presence or absence of Mg2+. Furthermore, probing at increasing temperature was remarkably efficient at pointing to non-canonical interactions and pseudoknot pairings. The possibilities of following such strategies to inform structure modeling software are discussed.

Solution NMR readily reveals distinct structural folds and interactions in doubly 13C- and 19F-labeled RNAs.

RNAs form critical components of biological processes implicated in human diseases, making them attractive for small-molecule therapeutics. Expanding the sites accessible to nuclear magnetic resonance (NMR) spectroscopy will provide atomic-level insights into RNA interactions. Here, we present an efficient strategy to introduce 19F-13C spin pairs into RNA by using a 5-fluorouridine-5'-triphosphate and T7 RNA polymerase-based in vitro transcription. Incorporating the 19F-13C label in two model RNAs produces linewidths that are twice as sharp as the commonly used 1H-13C spin pair. Furthermore, the high sensitivity of the 19F nucleus allows for clear delineation of helical and nonhelical regions as well as GU wobble and Watson-Crick base pairs. Last, the 19F-13C label enables rapid identification of a small-molecule binding pocket within human hepatitis B virus encapsidation signal epsilon (hHBV ε) RNA. We anticipate that the methods described herein will expand the size limitations of RNA NMR and aid with RNA-drug discovery efforts.

Activation of viral transcription by stepwise largescale folding of an RNA virus genome.

The genomes of RNA viruses contain regulatory elements of varying complexity. Many plus-strand RNA viruses employ largescale intra-genomic RNA-RNA interactions as a means to control viral processes. Here, we describe an elaborate RNA structure formed by multiple distant regions in a tombusvirus genome that activates transcription of a viral subgenomic mRNA. The initial step in assembly of this intramolecular RNA complex involves the folding of a large viral RNA domain, which generates a discontinuous binding pocket. Next, a distally-located protracted stem-loop RNA structure docks, via base-pairing, into the binding site and acts as a linchpin that stabilizes the RNA complex and activates transcription. A multi-step RNA folding pathway is proposed in which rate-limiting steps contribute to a delay in transcription of the capsid protein-encoding viral subgenomic mRNA. This study provides an exceptional example of the complexity of genome-scale viral regulation and offers new insights into the assembly schemes utilized by large intra-genomic RNA structures.

An NMR-based approach reveals the core structure of the functional domain of SINEUP lncRNAs.

Long non-coding RNAs (lncRNAs) are attracting widespread attention for their emerging regulatory, transcriptional, epigenetic, structural and various other functions. Comprehensive transcriptome analysis has revealed that retrotransposon elements (REs) are transcribed and enriched in lncRNA sequences. However, the functions of lncRNAs and the molecular roles of the embedded REs are largely unknown. The secondary and tertiary structures of lncRNAs and their embedded REs are likely to have essential functional roles, but experimental determination and reliable computational prediction of large RNA structures have been extremely challenging. We report here the nuclear magnetic resonance (NMR)-based secondary structure determination of the 167-nt inverted short interspersed nuclear element (SINE) B2, which is embedded in antisense Uchl1 lncRNA and upregulates the translation of sense Uchl1 mRNAs. By using NMR ‘fingerprints’ as a sensitive probe in the domain survey, we successfully divided the full-length inverted SINE B2 into minimal units made of two discrete structured domains and one dynamic domain without altering their original structures after careful boundary adjustments. This approach allowed us to identify a structured domain in nucleotides 31–119 of the inverted SINE B2. This approach will be applicable to determining the structures of other regulatory lncRNAs.

Accretion history of large ribosomal subunits deduced from theoretical minimal RNA rings is congruent with histories derived from phylogenetic and structural methods

Accretions of tRNAs presumably formed the large complex ribosomal RNA structures. Similarities of tRNA secondary structures with rRNA secondary structures increase with the integration order of their cognate amino acid in the genetic code, indicating tRNA evolution towards rRNA-like structures. Here analyses rank secondary structure subelements of three large ribosomal RNAs (Prokaryota: Archaea: Thermus thermophilus; Bacteria: Escherichia coli; Eukaryota: Saccharomyces cerevisiae) in relation to their similarities with secondary structures formed by presumed proto-tRNAs, represented by 25 theoretical minimal RNA rings. These ranks are compared to those derived from two independent methods (ranks provide a relative evolutionary age to the rRNA substructure), (a) cladistic phylogenetic analyses and (b) 3D-crystallography where core subelements are presumed ancient and peripheral ones recent. Comparisons of rRNA secondary structure subelements with RNA ring secondary structures show congruence between ranks deduced by this method and both (a) and (b) (more with (a) than (b)), especially for RNA rings with predicted ancient cognate amino acid. Reconstruction of accretion histories of large rRNAs will gain from adequately integrating information from independent methods. Theoretical minimal RNA rings, sequences deterministically designed in silico according to specific coding constraints, might produce adequate scales for prebiotic and early life molecular evolution.

Advanced approaches for elucidating structures of large RNAs using NMR spectroscopy and complementary methods.

NMR spectroscopy is a key technique that has significantly advanced our understanding of RNA structure and dynamics. However, determination of large RNA structures by NMR spectroscopy remains a significant technical challenge. In this review, we highlight advances that facilitate NMR studies of large RNAs, including methods for sample preparation, isotope labeling strategies, and data acquisition. In addition, we review hybrid approaches that have been instrumental in the structure determination of large RNAs.

Advances that facilitate the study of large RNA structure and dynamics by nuclear magnetic resonance spectroscopy.

The characterization of functional yet nonprotein coding (nc) RNAs has expanded the role of RNA in the cell from a passive player in the central dogma of molecular biology to an active regulator of gene expression. The misregulation of ncRNA function has been linked with a variety of diseases and disorders ranging from cancers to neurodegeneration. However, a detailed molecular understanding of how ncRNAs function has been limited; due, in part, to the difficulties associated with obtaining high‐resolution structures of large RNAs. Tertiary structure determination of RNA as a whole is hampered by various technical challenges, all of which are exacerbated as the size of the RNA increases. Namely, RNAs tend to be highly flexible and dynamic molecules, which are difficult to crystallize. Biomolecular nuclear magnetic resonance (NMR) spectroscopy offers a viable alternative to determining the structure of large RNA molecules that do not readily crystallize, but is itself hindered by some technical limitations. Recently, a series of advancements have allowed the biomolecular NMR field to overcome, at least in part, some of these limitations. These advances include improvements in sample preparation strategies as well as methodological improvements. Together, these innovations pave the way for the study of ever larger RNA molecules that have important biological function.This article is categorized under: RNA Structure and Dynamics > RNA Structure, Dynamics, and ChemistryRegulatory RNAs/RNAi/Riboswitches > Regulatory RNAsRNA Structure and Dynamics > Influence of RNA Structure in Biological Systems

Design and Characterization of RNA Nanotubes.

RNA is a functionally rich and diverse biomaterial responsible for regulating several cellular processes. This functionality has been harnessed to build predominately small nanoscale structures for drug delivery and the treatment of disease. The understanding of design principles to build large RNA structures will allow for further control of stoichiometry and spatial arrangement drugs and ligands. We present the design and characterization of RNA nanotubes that self-assemble from programmable monomers, or tiles, formed by five distinct RNA strands. Tiles include double crossover junctions and assemble via single-stranded sticky-end domains. We find that nanotube formation is dependent on the intertile crossover distance. The average length observed for the annealed RNA nanotubes is ≈1.5 μm, with many nanotubes exceeding 10 μm, enabling the characterization of RNA nanotubes length distribution via fluorescence microscopy. Assembled tubes were observed to be stable for more than 24 h, however post-annealing growth under isothermal conditions does not occur. Nanotubes assemble also from RNA tiles modified to include a single-stranded overhang (toehold), suggesting that it may be possible to decorate these large RNA scaffolds with nanoparticles or other nucleic acid molecules.

The Npa1p complex chaperones the assembly of the earliest eukaryotic large ribosomal subunit precursor.

The early steps of the production of the large ribosomal subunit are probably the least understood stages of eukaryotic ribosome biogenesis. The first specific precursor to the yeast large ribosomal subunit, the first pre-60S particle, contains 30 assembly factors (AFs), including 8 RNA helicases. These helicases, presumed to drive conformational rearrangements, usually lack substrate specificity in vitro. The mechanisms by which they are targeted to their correct substrate within pre-ribosomal particles and their precise molecular roles remain largely unknown. We demonstrate that the Dbp6p helicase, essential for the normal accumulation of the first pre-60S pre-ribosomal particle in S. cerevisiae, associates with a complex of four AFs, namely Npa1p, Npa2p, Nop8p and Rsa3p, prior to their incorporation into the 90S pre-ribosomal particles. By tandem affinity purifications using yeast extracts depleted of one component of the complex, we show that Npa1p forms the backbone of the complex. We provide evidence that Npa1p and Npa2p directly bind Dbp6p and we demonstrate that Npa1p is essential for the insertion of the Dbp6p helicase within 90S pre-ribosomal particles. In addition, by an in vivo cross-linking analysis (CRAC), we map Npa1p rRNA binding sites on 25S rRNA adjacent to the root helices of the first and last secondary structure domains of 25S rRNA. This finding supports the notion that Npa1p and Dbp6p function in the formation and/or clustering of root helices of large subunit rRNAs which creates the core of the large ribosomal subunit RNA structure. Npa1p also crosslinks to snoRNAs involved in decoding center and peptidyl transferase center modifications and in the immediate vicinity of the binding sites of these snoRNAs on 25S rRNA. Our data suggest that the Dbp6p helicase and the Npa1p complex play key roles in the compaction of the central core of 25S rRNA and the control of snoRNA-pre-rRNA interactions.

In Crystallo Selection to Establish New RNA Crystal Contacts

Crystallography is a major technique for determining large RNA structures. Obtaining diffraction-quality crystals has been the bottleneck. Although several RNA crystallization methods have been developed, the field strongly needs additional approaches. Here we invented an in crystallo selection strategy for identifying mutations that enhance a target RNA's crystallizability. The strategy includes constructing an RNA pool containing random mutations, obtaining crystals, and amplifying the sequences enriched by crystallization. We demonstrated a proof-of-principle application to the P4-P6 domain from the Tetrahymena ribozyme. We further determined the structures of four selected mutants. All four establish new crystal lattice contacts while maintaining the native structure. Three mutants achieve this by relocating bulges and one by making a helix more flexible. In crystallo selection provides opportunities to improve crystals of RNAs or RNA-ligand complexes. Our results also suggest that mutants may be rationally designed for crystallization by "walking" a bulge along the RNA chain.

RNApdbee 2.0: multifunctional tool for RNA structure annotation.

In the field of RNA structural biology and bioinformatics, an access to correctly annotated RNA structure is of crucial importance, especially in the secondary and 3D structure predictions. RNApdbee webserver, introduced in 2014, primarily aimed to address the problem of RNA secondary structure extraction from the PDB files. Its new version, RNApdbee 2.0, is a highly advanced multifunctional tool for RNA structure annotation, revealing the relationship between RNA secondary and 3D structure given in the PDB or PDBx/mmCIF format. The upgraded version incorporates new algorithms for recognition and classification of high-ordered pseudoknots in large RNA structures. It allows analysis of isolated base pairs impact on RNA structure. It can visualize RNA secondary structures—including that of quadruplexes—with depiction of non-canonical interactions. It also annotates motifs to ease identification of stems, loops and single-stranded fragments in the input RNA structure. RNApdbee 2.0 is implemented as a publicly available webserver with an intuitive interface and can be freely accessed at http://rnapdbee.cs.put.poznan.pl/

TRAVeLer: a tool for template-based RNA secondary structure visualization

BackgroundVisualization of RNA secondary structures is a complex task, and, especially in the case of large RNA structures where the expected layout is largely habitual, the existing visualization tools often fail to produce suitable visualizations. This led us to the idea to use existing layouts as templates for the visualization of new RNAs similarly to how templates are used in homology-based structure prediction.ResultsThis article introduces Traveler, a software tool enabling visualization of a target RNA secondary structure using an existing layout of a sufficiently similar RNA structure as a template. Traveler is based on an algorithm which converts the target and template structures into corresponding tree representations and utilizes tree edit distance coupled with layout modification operations to transform the template layout into the target one. Traveler thus accepts a pair of secondary structures and a template layout and outputs a layout for the target structure.ConclusionsTraveler is a command-line open source tool able to quickly generate layouts for even the largest RNA structures in the presence of a sufficiently similar layout. It is available at http://github.com/davidhoksza/traveler.

An efficient algorithm for planar drawing of RNA structures with pseudoknots of any type.

An RNA pseudoknot is a tertiary structural element in which bases of a loop pair with complementary bases are outside the loop. A drawing of RNA secondary structures is a tree, but a drawing of RNA pseudoknots is a graph that has an inner cycle within a pseudoknot and possibly outer cycles formed between the pseudoknot and other structural elements. Visualizing a large-scale RNA structure with pseudoknots as a planar drawing is challenging because a planar drawing of an RNA structure requires both pseudoknots and an entire structure enclosing the pseudoknots to be embedded into a plane without overlapping or crossing. This paper presents an efficient heuristic algorithm for visualizing a pseudoknotted RNA structure as a planar drawing. The algorithm consists of several parts for finding crossing stems and page mapping the stems, for the layout of stem-loops and pseudoknots, and for overlap detection between structural elements and resolving it. Unlike previous algorithms, our algorithm generates a planar drawing for a large RNA structure with pseudoknots of any type and provides a bracket view of the structure. It generates a compact and aesthetic structure graph for a large pseudoknotted RNA structure in O([Formula: see text]) time, where n is the number of stems of the RNA structure.

Self-assembly of large RNA structures: learning from DNA nanotechnology

AbstractNucleic acid nanotechnology offers many methods to build self-assembled structures using RNA and DNA. These scaffolds are valuable in multiple applications, such as sensing, drug delivery and nanofabrication. Although RNA and DNA are similar molecules, they also have unique chemical and structural properties. RNA is generally less stable than DNA, but it folds into a variety of tertiary motifs that can be used to produce complex and functional nanostructures. Another advantage of using RNA over DNA is its ability to be encoded into genes and to be expressed in vivo. Here we review existing approaches for the self-assembly of RNA and DNA nanostructures and specifically methods to assemble large RNA structures. We describe de novo design approaches used in DNA nanotechnology that can be ported to RNA. Lastly, we discuss some of the challenges yet to be solved to build micron-scale, multi stranded RNA scaffolds.

Automated RNA 3D Structure Prediction with RNAComposer.

RNAs adopt specific structures to perform their activities and these are critical to virtually all RNA-mediated processes. Because of difficulties in experimentally assessing structures of large RNAs using NMR, X-ray crystallography, or cryo-microscopy, there is currently great demand for new high-resolution 3D structure prediction methods. Recently we reported on RNAComposer, a knowledge-based method for the fully automated RNA 3D structure prediction from a user-defined secondary structure. RNAComposer method is especially suited for structural biology users. Since our initial report in 2012, both servers, freely available at http://rnacomposer.ibch.poznan.pl and http://rnacomposer.cs.put.poznan.pl have been often visited. Therefore this chapter provides guidance for using RNAComposer and discusses points that should be considered when predicting 3D RNA structure. An application example presents current scope and limitations of RNAComposer.