NMR-assisted prediction of RNA secondary structure: identification of a probable pseudoknot in the coding region of an R2 retrotransposon

Structural RNA components supervise the sequential DNA cleavage in R2 retrotransposon

Retroelements are the widespread jumping elements considered as major drivers for genome evolution, which can also be repurposed as gene-editing tools. Here, we determine the cryo-EM structures of eukaryotic R2 retrotransposon with ribosomal DNA target and regulatory RNAs. Combined with biochemical and sequencing analysis, we reveal two essential DNA regions, Drr and Dcr, required for recognition and cleavage. The association of 3' regulatory RNA with R2 protein accelerates the first-strand cleavage, blocks the second-strand cleavage, and initiates the reverse transcription starting from the 3'-tail. Removing 3' regulatory RNA by reverse transcription allows the association of 5' regulatory RNA and initiates the second-strand cleavage. Taken together, our work explains the DNA recognition and RNA supervised sequential retrotransposition mechanisms by R2 machinery, providing insights into the retrotransposon and application reprogramming.

Using Unassigned NMR Chemical Shifts to Model RNA Secondary Structure

NMR-derived chemical shifts are sensitive probes of RNA structure. However, the need to assign NMR spectra hampers their utility as a direct source of structural information. In this report, we describe a simple method that uses unassigned 2D NMR spectra to model the secondary structure of RNAs. As in the case of assigned chemical shifts, we could use unassigned chemical shift data to reweight conformational libraries such that the highest weighted structure closely resembles their reference NMR structure. Furthermore, the application of our approach to the 3'- and 5'-UTR of the SARS-CoV-2 genome yields structures that are, for the most part, consistent with the secondary structure models derived from chemical probing data. Therefore, we expect the framework we describe here will be useful as a general strategy for rapidly generating preliminary structural RNA models directly from unassigned 2D NMR spectra. As we demonstrated for the 337-nt and 472-nt UTRs of SARS-CoV-2, our approach could be especially valuable for modeling the secondary structures of large RNA.

Using RNA Sequence and Structure for the Prediction of Riboswitch Aptamer: A Comprehensive Review of Available Software and Tools

RNA molecules are essential players in many fundamental biological processes. Prokaryotes and eukaryotes have distinct RNA classes with specific structural features and functional roles. Computational prediction of protein structures is a research field in which high confidence three-dimensional protein models can be proposed based on the sequence alignment between target and templates. However, to date, only a few approaches have been developed for the computational prediction of RNA structures. Similar to proteins, RNA structures may be altered due to the interaction with various ligands, including proteins, other RNAs, and metabolites. A riboswitch is a molecular mechanism, found in the three kingdoms of life, in which the RNA structure is modified by the binding of a metabolite. It can regulate multiple gene expression mechanisms, such as transcription, translation initiation, and mRNA splicing and processing. Due to their nature, these entities also act on the regulation of gene expression and detection of small metabolites and have the potential to helping in the discovery of new classes of antimicrobial agents. In this review, we describe software and web servers currently available for riboswitch aptamer identification and secondary and tertiary structure prediction, including applications.

RNA Secondary Structure Determination by NMR

Dynamic programming methods for predicting RNA secondary structure often use thermodynamics and experimental restraints and/or constraints to limit folding space. Chemical mapping results typically restrain certain nucleotides not to be in AU or GC pairs. Two-dimensional nuclear magnetic resonance (NMR) spectra can reveal the order of AU, GC, and GU pairs in double helixes. This chapter describes a program, NMR-assisted prediction of secondary structure and chemical shifts (NAPSS-CS), that constrains possible secondary structures on the basis of the NMR determined order and 5'-3' direction of AU, GC, and GU pairs in helixes. NAPSS-CS minimally requires input of the order of base pairs as determined from nuclear Overhauser effect spectroscopy (NOESY) of imino protons. The program deduces the 5'-3' direction of the base pairs if certain chemical shifts are also input. Secondary structures predicted by the program provide assignments of input chemical shifts to particular nucleotides in the sequence, thus facilitating an important step for determination of the three dimensional structure by NMR. The method is particularly useful for revealing pseudoknots and an example is provided. The method may also allow determination of secondary structures when a sequence folds into two structures that exchange slowly.

Nuclear Magnetic Resonance Structure of an 8 × 8 Nucleotide RNA Internal Loop Flanked on Each Side by Three Watson-Crick Pairs and Comparison to Three-Dimensional Predictions

The prediction of RNA three-dimensional structure from sequence alone has been a long-standing goal. High-resolution, experimentally determined structures of simple noncanonical pairings and motifs are critical to the development of prediction programs. Here, we present the nuclear magnetic resonance structure of the (5'CCAGAAACGGAUGGA)₂ duplex, which contains an 8 × 8 nucleotide internal loop flanked by three Watson-Crick pairs on each side. The loop is comprised of a central 5'AC/3'CA nearest neighbor flanked by two 3RRs motifs, a known stable motif consisting of three consecutive sheared GA pairs. Hydrogen bonding patterns between base pairs in the loop, the all-atom root-mean-square deviation for the loop, and the deformation index were used to compare the structure to automated predictions by MC-sym, RNA FARFAR, and RNAComposer.

Experiment-Assisted Secondary Structure Prediction with RNAstructure

Experimental probing data can be used to improve the accuracy of RNA secondary structure prediction. The software package RNAstructure can take advantage of enzymatic cleavage data, FMN cleavage data, traditional chemical modification reactivity data, and SHAPE reactivity data for secondary structure modeling. This chapter provides protocols for using experimental probing data with RNAstructure to restrain or constrain RNA secondary structure prediction.

NMR Methods for Characterization of RNA Secondary Structure

Knowledge of RNA secondary structure is often sufficient to identify relationships between the structure of RNA and processing pathways, and the design of therapeutics. Nuclear magnetic resonance (NMR) can identify types of nucleotide base pairs and the sequence, thus limiting possible secondary structures. Because NMR experiments, like chemical mapping, are performed in solution, not in single crystals, experiments can be initiated as soon as the biomolecule is expressed and purified. This chapter summarizes NMR methods that permit rapid identification of RNA secondary structure, information that can be used as supplements to chemical mapping, and/or as preliminary steps required for 3D structure determination. The primary aim is to provide guidelines to enable a researcher with minimal knowledge of NMR to quickly extract secondary structure information from basic datasets. Instrumental and sample considerations that can maximize data quality are discussed along with some details for optimal data acquisition and processing parameters. Approaches for identifying base pair types in both unlabeled and isotopically labeled RNA are covered. Common problems, such as missing signals and overlaps, and approaches to address them are considered. Programs under development for merging NMR data with structure prediction algorithms are briefly discussed.

Nuclear Magnetic Resonance-Assisted Prediction of Secondary Structure for RNA: Incorporation of Direction-Dependent Chemical Shift Constraints

Knowledge of RNA structure is necessary to determine structure–function relationships and to facilitate design of potential therapeutics. RNA secondary structure prediction can be improved by applying constraints from nuclear magnetic resonance (NMR) experiments to a dynamic programming algorithm. Imino proton walks from NOESY spectra reveal double-stranded regions. Chemical shifts of protons in GH1, UH3, and UH5 of GU pairs, UH3, UH5, and AH2 of AU pairs, and GH1 of GC pairs were analyzed to identify constraints for the 5′ to 3′ directionality of base pairs in helices. The 5′ to 3′ directionality constraints were incorporated into an NMR-assisted prediction of secondary structure (NAPSS-CS) program. When it was tested on 18 structures, including nine pseudoknots, the sensitivity and positive predictive value were improved relative to those of three unrestrained programs. The prediction accuracy for the pseudoknots improved the most. The program also facilitates assignment of chemical shifts to individual nucleotides, a necessary step for determining three-dimensional structure.

Microarrays for identifying binding sites and probing structure of RNAs

Oligonucleotide microarrays are widely used in various biological studies. In this review, application of oligonucleotide microarrays for identifying binding sites and probing structure of RNAs is described. Deep sequencing allows fast determination of DNA and RNA sequence. High-throughput methods for determination of secondary structures of RNAs have also been developed. Those methods, however, do not reveal binding sites for oligonucleotides. In contrast, microarrays directly determine binding sites while also providing structural insights. Microarray mapping can be used over a wide range of experimental conditions, including temperature, pH, various cations at different concentrations and the presence of other molecules. Moreover, it is possible to make universal microarrays suitable for investigations of many different RNAs, and readout of results is rapid. Thus, microarrays are used to provide insight into oligonucleotide sequences potentially able to interfere with biological function. Better understanding of structure-function relationships of RNA can be facilitated by using microarrays to find RNA regions capable to bind oligonucleotides. That information is extremely important to design optimal sequences for antisense oligonucleotides and siRNA because both bind to single-stranded regions of target RNAs.

Molecular crowders and cosolutes promote folding cooperativity of RNA under physiological ionic conditions

Folding mechanisms of functional RNAs under idealized in vitro conditions of dilute solution and high ionic strength have been well studied. Comparatively little is known, however, about mechanisms for folding of RNA in vivo where Mg(2+) ion concentrations are low, K(+) concentrations are modest, and concentrations of macromolecular crowders and low-molecular-weight cosolutes are high. Herein, we apply a combination of biophysical and structure mapping techniques to tRNA to elucidate thermodynamic and functional principles that govern RNA folding under in vivo-like conditions. We show by thermal denaturation and SHAPE studies that tRNA folding cooperativity increases in physiologically low concentrations of Mg(2+) (0.5-2 mM) and K(+) (140 mM) if the solution is supplemented with physiological amounts (∼ 20%) of a water-soluble neutral macromolecular crowding agent such as PEG or dextran. Low-molecular-weight cosolutes show varying effects on tRNA folding cooperativity, increasing or decreasing it based on the identity of the cosolute. For those additives that increase folding cooperativity, the gain is manifested in sharpened two-state-like folding transitions for full-length tRNA over its secondary structural elements. Temperature-dependent SHAPE experiments in the absence and presence of crowders and cosolutes reveal extent of cooperative folding of tRNA on a nucleotide basis and are consistent with the melting studies. Mechanistically, crowding agents appear to promote cooperativity by stabilizing tertiary structure, while those low molecular cosolutes that promote cooperativity stabilize tertiary structure and/or destabilize secondary structure. Cooperative folding of functional RNA under physiological-like conditions parallels the behavior of many proteins and has implications for cellular RNA folding kinetics and evolution.

The nuclear magnetic resonance of CCCC RNA reveals a right-handed helix, and revised parameters for AMBER force field torsions improve structural predictions from molecular dynamics

The sequence dependence of RNA energetics is important for predicting RNA structure. Hairpins with C(n) loops are consistently less stable than hairpins with other loops, which suggests the structure of C(n) regions could be unusual in the "unfolded" state. For example, previous nuclear magnetic resonance (NMR) evidence suggested that polycytidylic acid forms a left-handed helix. In this study, UV melting experiments show that the hairpin formed by r(5'GGACCCCCGUCC) is less stable than r(5'GGACUUUUGUCC). NMR spectra for single-stranded C(4) oligonucleotide, mimicking the unfolded hairpin loop, are consistent with a right-handed A-form-like helix. Comparisons between NMR spectra and molecular dynamics (MD) simulations suggest that recent reparametrizations, parm99χ_YIL and parm99TOR, of the AMBER parm99 force field improve the agreement between structural features for C(4) determined by NMR and predicted by MD. Evidently, the force field revisions to parm99 improve the modeling of RNA energetics and therefore structure.

Computational prediction of RNA secondary structure

The purpose of this section is to detail methods for the computational prediction of RNA secondary structure. This protocol is intended to provide an easy entry into the field of RNA structure prediction for those wishing to utilize it in their research and to suggest 'best practices' for going from sequence to secondary structure depending on the available data.

Testing the nearest neighbor model for canonical RNA base pairs: revision of GU parameters

Thermodynamic parameters for GU pairs are important for predicting the secondary structures of RNA and for finding genomic sequences that code for structured RNA. Optical melting curves were measured for 29 RNA duplexes with GU pairs to improve nearest neighbor parameters for predicting stabilities of helixes. The updated model eliminates a prior penalty assumed for terminal GU pairs. Six additional duplexes with the 5'GG/3'UU motif were added to the single representation in the previous database. This revises the ΔG°(37) for the 5'GG/3'UU motif from an unfavorable 0.5 kcal/mol to a favorable -0.2 kcal/mol. Similarly, the ΔG°(37) for the 5'UG/3'GU motif changes from 0.3 to -0.6 kcal/mol. The correlation coefficients between predicted and experimental ΔG°(37), ΔH°, and ΔS° for the expanded database are 0.95, 0.89, and 0.87, respectively. The results should improve predictions of RNA secondary structure.

RNA-PAIRS: RNA probabilistic assignment of imino resonance shifts

The significant biological role of RNA has further highlighted the need for improving the accuracy, efficiency and the reach of methods for investigating RNA structure and function. Nuclear magnetic resonance (NMR) spectroscopy is vital to furthering the goals of RNA structural biology because of its distinctive capabilities. However, the dispersion pattern in the NMR spectra of RNA makes automated resonance assignment, a key step in NMR investigation of biomolecules, remarkably challenging. Herein we present RNA Probabilistic Assignment of Imino Resonance Shifts (RNA-PAIRS), a method for the automated assignment of RNA imino resonances with synchronized verification and correction of predicted secondary structure. RNA-PAIRS represents an advance in modeling the assignment paradigm because it seeds the probabilistic network for assignment with experimental NMR data, and predicted RNA secondary structure, simultaneously and from the start. Subsequently, RNA-PAIRS sets in motion a dynamic network that reverberates between predictions and experimental evidence in order to reconcile and rectify resonance assignments and secondary structure information. The procedure is halted when assignments and base-parings are deemed to be most consistent with observed crosspeaks. The current implementation of RNA-PAIRS uses an initial peak list derived from proton-nitrogen heteronuclear multiple quantum correlation ((1)H-(15)N 2D HMQC) and proton-proton nuclear Overhauser enhancement spectroscopy ((1)H-(1)H 2D NOESY) experiments. We have evaluated the performance of RNA-PAIRS by using it to analyze NMR datasets from 26 previously studied RNAs, including a 111-nucleotide complex. For moderately sized RNA molecules, and over a range of comparatively complex structural motifs, the average assignment accuracy exceeds 90%, while the average base pair prediction accuracy exceeded 93%. RNA-PAIRS yielded accurate assignments and base pairings consistent with imino resonances for a majority of the NMR resonances, even when the initial predictions are only modestly accurate. RNA-PAIRS is available as a public web-server at http://pine.nmrfam.wisc.edu/RNA/.

Secondary structure of the HIV reverse transcription initiation complex by NMR

Initiation of reverse transcription of genomic RNA is a key early step in replication of the human immunodeficiency virus (HIV) upon infection of a host cell. Viral reverse transcriptase initiates from a specific RNA-RNA complex formed between a host transfer RNA (tRNA(Lys)(3)) and a region at the 5' end of genomic RNA; the 3' end of the tRNA acts as a primer for reverse transcription of genomic RNA. We report here the secondary structure of the HIV genomic RNA-human tRNA(Lys)(3) initiation complex using heteronuclear nuclear magnetic resonance methods. We show that both RNAs undergo large-scale conformational changes upon complex formation. Formation of the 18-bp primer helix with the 3' end of tRNA(Lys)(3) drives large conformational rearrangements of the tRNA at the 5' end while maintaining the anticodon loop for potential loop-loop interactions. HIV RNA forms an intramolecular helix adjacent to the intermolecular primer helix. This helix, which must be broken by reverse transcription, likely acts as a kinetic block to reverse transcription.

NMR structure of a 4 x 4 nucleotide RNA internal loop from an R2 retrotransposon: identification of a three purine-purine sheared pair motif and comparison to MC-SYM predictions

The NMR solution structure is reported of a duplex, 5'GUGAAGCCCGU/3'UCACAGGAGGC, containing a 4 × 4 nucleotide internal loop from an R2 retrotransposon RNA. The loop contains three sheared purine-purine pairs and reveals a structural element found in other RNAs, which we refer to as the 3RRs motif. Optical melting measurements of the thermodynamics of the duplex indicate that the internal loop is 1.6 kcal/mol more stable at 37°C than predicted. The results identify the 3RRs motif as a common structural element that can facilitate prediction of 3D structure. Known examples include internal loops having the pairings: 5'GAA/3'AGG, 5'GAG/3'AGG, 5'GAA/3'AAG, and 5'AAG/3'AGG. The structural information is compared with predictions made with the MC-Sym program.

The R2 retrotransposon RNA families

Analysis of the R2 retrotransposons from multiple silkmoth and fruitfly species have revealed three segments that contain conserved RNA secondary structures. These conserved structures play important roles in the propagation of the R2 element, including R2 RNA processing and transposon integration into the host genome as well as a likely role in translation. Two of the structured regions comprise protein binding sites: one is located in the 3' UTR and the other is in the 5' UTR close to the putative start of the R2 open reading frame (ORF). The 3' structure was deduced from chemical mapping and sequence comparison. The 5' structure was determined using a combination of chemical mapping, oligonucleotide binding, NMR and sequence analysis and contains an unusual pseudoknot structure. The third structure occurs at the 5' end of the R2 RNA and is responsible for self-cleavage of the 5' end of the element from a 28S ribosomal RNA co-transcript. A structure for this fragment was proposed based on motif searching and sequence comparison. There is remarkable similarity in sequence and structure to the hepatitis delta virus (HDV) ribozyme. Seed alignments for the 5' structure and the R2 ribozyme, containing representative sequences and consensus structures, have been submitted to the Rfam database.

Computational approaches for RNA energy parameter estimation

Methods for efficient and accurate prediction of RNA structure are increasingly valuable, given the current rapid advances in understanding the diverse functions of RNA molecules in the cell. To enhance the accuracy of secondary structure predictions, we developed and refined optimization techniques for the estimation of energy parameters. We build on two previous approaches to RNA free-energy parameter estimation: (1) the Constraint Generation (CG) method, which iteratively generates constraints that enforce known structures to have energies lower than other structures for the same molecule; and (2) the Boltzmann Likelihood (BL) method, which infers a set of RNA free-energy parameters that maximize the conditional likelihood of a set of reference RNA structures. Here, we extend these approaches in two main ways: We propose (1) a max-margin extension of CG, and (2) a novel linear Gaussian Bayesian network that models feature relationships, which effectively makes use of sparse data by sharing statistical strength between parameters. We obtain significant improvements in the accuracy of RNA minimum free-energy pseudoknot-free secondary structure prediction when measured on a comprehensive set of 2518 RNA molecules with reference structures. Our parameters can be used in conjunction with software that predicts RNA secondary structures, RNA hybridization, or ensembles of structures. Our data, software, results, and parameter sets in various formats are freely available at http://www.cs.ubc.ca/labs/beta/Projects/RNA-Params.

Comparisons between chemical mapping and binding to isoenergetic oligonucleotide microarrays reveal unexpected patterns of binding to the Bacillus subtilis RNase P RNA specificity domain

Microarrays with isoenergetic pentamer and hexamer 2'-O-methyl oligonucleotide probes with LNA (locked nucleic acid) and 2,6-diaminopurine substitutions were used to probe the binding sites on the RNase P RNA specificity domain of Bacillus subtilis. Unexpected binding patterns were revealed. Because of their enhanced binding free energies, isoenergetic probes can break short duplexes, merge adjacent loops, and/or induce refolding. This suggests new approaches to the rational design of short oligonucleotide therapeutics but limits the utility of microarrays for providing constraints for RNA structure determination. The microarray results are compared to results from chemical mapping experiments, which do provide constraints. Results from both types of experiments indicate that the RNase P RNA folds similarly in 1 M Na(+) and 10 mM Mg(2+).

Folding and finding RNA secondary structure

Optimal exploitation of the expanding database of sequences requires rapid finding and folding of RNAs. Methods are reviewed that automate folding and discovery of RNAs with algorithms that couple thermodynamics with chemical mapping, NMR, and/or sequence comparison. New functional noncoding RNAs in genome sequences can be found by combining sequence comparison with the assumption that functional noncoding RNAs will have more favorable folding free energies than other RNAs. When a new RNA is discovered, experiments and sequence comparison can restrict folding space so that secondary structure can be rapidly determined with the help of predicted free energies. In turn, secondary structure restricts folding in three dimensions, which allows modeling of three-dimensional structure. An example from a domain of a retrotransposon is described. Discovery of new RNAs and their structures will provide insights into evolution, biology, and design of therapeutics. Applications to studies of evolution are also reviewed.

RNA internal loops with tandem AG pairs: the structure of the 5'GAGU/3'UGAG loop can be dramatically different from others, including 5'AAGU/3'UGAA

Thermodynamic stabilities of 2 × 2 nucleotide tandem AG internal loops in RNA range from −1.3 to +3.4 kcal/mol at 37 °C and are not predicted well with a hydrogen-bonding model. To provide structural information to facilitate development of more sophisticated models for the sequence dependence of stability, we report the NMR solution structures of five RNA duplexes: (rGACGAGCGUCA)₂, (rGACUAGAGUCA)₂, (rGACAAGUGUCA)₂, (rGGUAGGCCA)₂, and (rGACGAGUGUCA)₂. The structures of these duplexes are compared to that of the previously solved (rGGCAGGCC)₂ (Wu, M., SantaLucia, J., Jr., and Turner, D. H. (1997) Biochemistry 36, 4449−4460). For loops bounded by Watson−Crick pairs, the AG and Watson−Crick pairs are all head-to-head imino-paired (cis Watson−Crick/Watson−Crick). The structures suggest that the sequence-dependent stability may reflect non-hydrogen-bonding interactions. Of the two loops bounded by G-U pairs, only the 5′UAGG/3′GGAU loop adopts canonical UG wobble pairing (cis Watson−Crick/Watson−Crick), with AG pairs that are only weakly imino-paired. Strikingly, the 5′GAGU/3′UGAG loop has two distinct duplex conformations, the major of which has both guanosine residues (G4 and G6 in (rGACGAGUGUCA)₂) in a syn glycosidic bond conformation and forming a sheared GG pair (G4-G6*, GG trans Watson−Crick/Hoogsteen), both uracils (U7 and U7*) flipped out of the helix, and an AA pair (A5-A5*) in a dynamic or stacked conformation. These structures provide benchmarks for computational investigations into interactions responsible for the unexpected differences in loop free energies and structure.

Evaluation of the information content of RNA structure mapping data for secondary structure prediction

Structure mapping experiments (using probes such as dimethyl sulfate [DMS], kethoxal, and T1 and V1 RNases) are used to determine the secondary structures of RNA molecules. The process is iterative, combining the results of several probes with constrained minimum free-energy calculations to produce a model of the structure. We aim to evaluate whether particular probes provide more structural information, and specifically, how noise in the data affects the predictions. Our approach involves generating "decoy" RNA structures (using the sFold Boltzmann sampling procedure) and evaluating whether we are able to identify the correct structure from this ensemble of structures. We show that with perfect information, we are always able to identify the optimal structure for five RNAs of known structure. We then collected orthogonal structure mapping data (DMS and RNase T1 digest) under several solution conditions using our high-throughput capillary automated footprinting analysis (CAFA) technique on two group I introns of known structure. Analysis of these data reveals the error rates in the data under optimal (low salt) and suboptimal solution conditions (high MgCl(2)). We show that despite these errors, our computational approach is less sensitive to experimental noise than traditional constraint-based structure prediction algorithms. Finally, we propose a novel approach for visualizing the interaction of chemical and enzymatic mapping data with RNA structure. We project the data onto the first two dimensions of a multidimensional scaling of the sFold-generated decoy structures. We are able to directly visualize the structural information content of structure mapping data and reconcile multiple data sets.

Fluorescence competition assay measurements of free energy changes for RNA pseudoknots

RNA pseudoknots have important functions, and thermodynamic stability is a key to predicting pseudoknots in RNA sequences and to understanding their functions. Traditional methods, such as UV melting and differential scanning calorimetry, for measuring RNA thermodynamics are restricted to temperature ranges around the melting temperature for a pseudoknot. Here, we report RNA pseudoknot free energy changes at 37 °C measured by fluorescence competition assays. Sequence-dependent studies for the loop 1−stem 2 region reveal (1) the individual nearest-neighbor hydrogen bonding (INN-HB) model provides a reasonable estimate for the free energy change when a Watson−Crick base pair in stem 2 is changed, (2) the loop entropy can be estimated by a statistical polymer model, although some penalty for certain loop sequences is necessary, and (3) tertiary interactions can significantly stabilize pseudoknots and extending the length of stem 2 may alter tertiary interactions such that the INN-HB model does not predict the net effect of adding a base pair. The results can inform writing of algorithms for predicting and/or designing RNA secondary structures.

RNAstructure: software for RNA secondary structure prediction and analysis

Background

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

Results

RNAstructure is a software package for RNA secondary structure prediction and analysis. It uses thermodynamics and utilizes the most recent set of nearest neighbor parameters from the Turner group. It includes methods for secondary structure prediction (using several algorithms), prediction of base pair probabilities, bimolecular structure prediction, and prediction of a structure common to two sequences. This contribution describes new extensions to the package, including a library of C++ classes for incorporation into other programs, a user-friendly graphical user interface written in JAVA, and new Unix-style text interfaces. The original graphical user interface for Microsoft Windows is still maintained.

Conclusion

The extensions to RNAstructure serve to make RNA secondary structure prediction user-friendly. The package is available for download from the Mathews lab homepage at http://rna.urmc.rochester.edu/RNAstructure.html.

5-Fluoro pyrimidines: labels to probe DNA and RNA secondary structures by 1D 19F NMR spectroscopy

¹⁹F NMR spectroscopy has proved to be a valuable tool to monitor functionally important conformational transitions of nucleic acids. Here, we present a systematic investigation on the application of 5-fluoro pyrimidines to probe DNA and RNA secondary structures. Oligonucleotides with the propensity to adapt secondary structure equilibria were chosen as model systems and analyzed by 1D ¹⁹F and ¹H NMR spectroscopy. A comparison with the unmodified analogs revealed that the equilibrium characteristics of the bistable DNA and RNA oligonucleotides were hardly affected upon fluorine substitution at C5 of pyrimidines. This observation was in accordance with UV spectroscopic melting experiments which demonstrated that single 5-fluoro substitutions in double helices lead to comparable thermodynamic stabilities. Thus, 5-fluoro pyrimidine labeling of DNA and RNA can be reliably applied for NMR based nucleic acid secondary structure evaluation. Furthermore, we developed a facile synthetic route towards 5-fluoro cytidine phosphoramidites that enables their convenient site-specific incorporation into oligonucleotides by solid-phase synthesis.

RNA pseudoknots: folding and finding

RNA pseudoknots are important for function. Three-dimensional structural information is available, insights into factors affecting pseudoknot stability are being reported, and computer programs are available for predicting pseudoknots.

Binding of short oligonucleotides to RNA: studies of the binding of common RNA structural motifs to isoenergetic microarrays

Binding of short oligonucleotides to RNA is important for many biological processes. On the basis of RNAi phenomena, antisense, and ribozyme approaches, it is useful in the inhibition of biological functions. To be considered as potential therapeutics, oligonucleotides must bind strongly and selectively to a complementary fragment of target RNA. Microarray technologies also involve the binding of oligonucleotide probes to DNA or RNA. Herein, the hybridization of common structural motifs of RNA, i.e., hairpins, internal loops, bulges, 3'- and 5'-dangling ends, and pseudoknots to isoenergetic microarray probes is presented. The analysis demonstrates that microarray probes bind to bulges, internal loops, and dangling ends as expected. Probes may also bind to terminal helixes, however, possibly due to the rearrangement of base pairs. These results suggest that isoenergetic microarray mapping can provide data to facilitate and improve RNA secondary structure prediction. However, optimal results require combination with chemical and/or enzymatic mapping.

Evidence for pseudoknot formation of class I preQ1 riboswitch aptamers

All in a knot. The smallest riboswitch forms a pseudoknot in solution. This is demonstrated for preQ(1) class I aptamers by mutational analysis in combination with (1)H NMR-based structure probing. How pseudoknot formation mediates the mRNA response through its expression platform is now open for investigation.

Stochastic sampling of the RNA structural alignment space

A novel method is presented for predicting the common secondary structures and alignment of two homologous RNA sequences by sampling the 'structural alignment' space, i.e. the joint space of their alignments and common secondary structures. The structural alignment space is sampled according to a pseudo-Boltzmann distribution based on a pseudo-free energy change that combines base pairing probabilities from a thermodynamic model and alignment probabilities from a hidden Markov model. By virtue of the implicit comparative analysis between the two sequences, the method offers an improvement over single sequence sampling of the Boltzmann ensemble. A cluster analysis shows that the samples obtained from joint sampling of the structural alignment space cluster more closely than samples generated by the single sequence method. On average, the representative (centroid) structure and alignment of the most populated cluster in the sample of structures and alignments generated by joint sampling are more accurate than single sequence sampling and alignment based on sequence alone, respectively. The 'best' centroid structure that is closest to the known structure among all the centroids is, on average, more accurate than structure predictions of other methods. Additionally, cluster analysis identifies, on average, a few clusters, whose centroids can be presented as alternative candidates. The source code for the proposed method can be downloaded at http://rna.urmc.rochester.edu.

Secondary structures for 5' regions of R2 retrotransposon RNAs reveal a novel conserved pseudoknot and regions that evolve under different constraints

Sequences from the 5' region of R2 retrotransposons of four species of silk moth are reported. In Bombyx mori, this region of the R2 messenger RNA contains a binding site for R2 protein and mediates interactions critical to R2 element insertion into the host genome. A model of secondary structure for a segment of this RNA is proposed on the basis of binding to oligonucleotide microarrays, chemical mapping, and comparative sequence analysis. Five conserved secondary structures are identified, including a novel pseudoknot. There is an apparent transition from an entirely RNA structure coding function in most of the 5' segment to a protein coding function near the 3' end. This suggests that local regions evolved under separate functional constraints (structural, coding, or both).

Predicting structures and stabilities for H-type pseudoknots with interhelix loops

RNA pseudoknots play a critical role in RNA-related biology from the assembly of ribosome to the regulation of viral gene expression. A predictive model for pseudoknot structure and stability is essential for understanding and designing RNA structure and function. A previous statistical mechanical theory allows us to treat canonical H-type RNA pseudoknots that contain no intervening loop between the helices (see S. Cao and S.J. Chen [2006] in Nucleic Acids Research, Vol. 34; pp. 2634-2652). Biologically significant RNA pseudoknots often contain interhelix loops. Predicting the structure and stability for such more-general pseudoknots remains an unsolved problem. In the present study, we develop a predictive model for pseudoknots with interhelix loops. The model gives conformational entropy, stability, and the free-energy landscape from RNA sequences. The main features of this new model are the computation of the conformational entropy and folding free-energy base on the complete conformational ensemble and rigorous treatment for the excluded volume effects. Extensive tests for the structural predictions show overall good accuracy with average sensitivity and specificity equal to 0.91 and 0.91, respectively. The theory developed here may be a solid starting point for first-principles modeling of more complex, larger RNAs.