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At least 595 records · Page 33Linked to original sources
PubMed1993

An independently folding domain of RNA tertiary structure within the Tetrahymena ribozyme.

The Tetrahymena thermophila pre-rRNA contains a 413-nucleotide self-splicing group I intron. This intron has been converted into a sequence-specific endonuclease or ribozyme. A 160-nucleotide portion of the ribozyme consisting of both highly conserved sequence elements (P4 and P6) and nonconserved peripheral extensions (P5abc and P6ab) was synthesized as a separate molecule. Solvent-based Fe(II)-EDTA, a probe that monitors higher-order RNA structure, revealed a protection pattern that was a large subset of that observed in the whole ribozyme. Data from dimethyl sulfate modification and partial digestion with nucleases were also consistent with maintenance of the proper secondary and tertiary structure in the shortened RNA molecule. Thus, this 160-nucleotide molecule (P4-P6 RNA) is an independently folding domain of RNA tertiary structure. A series of mutations and deletions were made within the P4-P6 domain to further dissect its tertiary structure. Fe(II)-EDTA and dimethyl sulfate analysis of these mutants revealed that the domain consists of two substructures, a localized subdomain involving the characteristic adenosine-rich bulge in P5a, and a subdomain-stabilized structure involving long-range interactions. Therefore, like some proteins, the intron RNA is modular, containing a separable domain and subdomain of tertiary structure.

Animals↗
PubMed1996

Determining RNA solution structure by segmental isotopic labeling and NMR: application to Caenorhabditis elegans spliced leader RNA 1.

Recent developments in multidimensional heteronuclear NMR spectroscopy and large-scale synthesis of uniformly 13C- and 15N-labeled oligonucleotides have greatly improved the prospects for determination of the solution structure of RNA. However, there are circumstances in which it may be advantageous to label only a segment of the entire RNA chain. For example, in a larger RNA molecule the structural question of interest may reside in a localized domain. Labeling only the corresponding nucleotides simplifies the spectrum and resonance assignments because one can filter proton spectra for coupling to 13C and 15N. Another example is in resolving alternative secondary structure models that are indistinguishable in imino proton connectivities. Here we report a general method for enzymatic synthesis of quantities of segmentally labeled RNA molecules required for NMR spectroscopy. We use the method to distinguish definitively two competing secondary structure models for the 5' half of Caenorhabditis elegans spliced leader RNA by comparison of the two-dimensional [15N] 1H heteronuclear multiple quantum correlation spectrum of the uniformly labeled sample with that of a segmentally labeled sample. The method requires relatively small samples; solutions in the 200-300 microM concentration range, with a total of 30 nmol or approximately 40 micrograms of RNA in approximately 150 microliters, give strong NMR signals in a short accumulation time. The method can be adapted to label an internal segment of a larger RNA chain for study of localized structural problems. This definitive approach provides an alternative to the more common enzymatic and chemical footprinting methods for determination of RNA secondary structure.

Animals↗
PubMedDate not supplied

Evolution of structure in RNA.

Evidence is presented that structures formed by RNA and by RNA in association with protein have evolved from simpler structures by successive unions among them. The progressively more complex molecular structures have conferred selective advantage in evolution by progressively enhancing the specificities of the biochemical reactions. Before each union, the RNAs which joined at the time of union belonged to separate reproducing species. The record of unions in RNA therefore reflects unions among species in the biosphere, tracing the evolution of life from quite simple reproducing molecules up to well developed organisms.

Biological Evolution↗
PubMed1999

A bayesian statistical algorithm for RNA secondary structure prediction.

A Bayesian approach for predicting RNA secondary structure that addresses the following three open issues is described: (1) the need for a representation of the full ensemble of probable structures; (2) the need to specify a fixed set of energy parameters; (3) the desire to make statistical inferences on all variables in the problem. It has recently been shown that Bayesian inference can be employed to relax or eliminate the need to specify the parameters of bioinformatics recursive algorithms and to give a statistical representation of the full ensemble of probable solutions with the incorporation of uncertainty in parameter values. In this paper, we make an initial exploration of these potential advantages of the Bayesian approach. We present a Bayesian algorithm that is based on stacking energy rules but relaxes the need to specify the parameters. The algorithm returns the exact posterior distribution of the number of destabilizing loops, stacking energy matrices, and secondary structures. The algorithm generates statistically representative structures from the full ensemble of probable secondary structures in exact proportion to the posterior probabilities. Once the forward recursions for the algorithm are completed, the backward recursive sampling executes in O(n) time, providing a very efficient approach for generating representative structures. We demonstrate the utility of the Bayesian approach with several tRNA sequences. The potential of the approach for predicting RNA secondary structures and presenting alternative structures is illustrated with applications to the Escherichia coli tRNA(Ala) sequence and the Xenopus laevis oocyte 5S rRNA sequence.

Algorithms↗
PubMedDate not supplied

Synthesis of modified RNA-oligonucleotides for structural investigations.

RNA exhibits a higher structural diversity than DNA and is an important molecule in biology of life. It shows a number of secondary structures such as duplexes, hairpin loops, bulges, internal loops etc. However, in natural RNA, bases are limited to the four predominant structures U, C, A, and G and so the number of compounds that can be used for investigation of parameters of base stacking, base pairing and hydrogen bond, is limited. We synthesized different fluoromodifications of RNA building blocks: 1'-deoxy-1'-(2,4,6-trifluorophenyl)-beta-D-ribofuranose (F), 1'-deoxy-1'-(2,4,5-trifluorophenyl)-beta-D-ribofuranose (M) and 1'-deoxy-1'-(5-trifluoromethyl-1H-benzimidazol-1-yl)-beta-D-ribofuranose (D). Those amidites were incorporated and tested in a defined A, U-rich RNA sequence (12-mer, 5'-CUU UUC XUU CUU-3' paired with 3'-GAA AAG YAA GAA-5') (Schweitzer, B.A.; Kool, E.T. Aromatic nonpolar nucleosides as hydrophobic isosters of pyrimidine and purine nucleosides. J. Org. Chem. 1994, 59, 7238 pp.). Only one position was modified, marked as X and Y respectively. UV melting profiles of those oligonucleotides were measured.

Base Sequence↗
PubMed2004

Conserved RNA secondary structures in viral genomes: a survey.

SUMMARY: The genomes of RNA viruses often carry conserved RNA structures that perform vital functions during the life cycle of the virus. Such structures can be detected using a combination of structure prediction and co-variation analysis. Here we present results from pilot studies on a variety of viral families performed during bioinformatics computer lab courses in past years.

Algorithms↗
PubMed2006

Pyrrolo-C as a fluorescent probe for monitoring RNA secondary structure formation.

Pyrrolo-C (PC), or 3-[beta-D-2-ribofuranosyl]-6-methylpyrrolo[2,3-d]pyrimidin-2(3H)-one, is a fluorescent analog of the nucleoside cytidine that retains its Watson-Crick base-pairing capacity with G. Due to its red-shifted absorbance, it can be selectively excited in the presence of natural nucleosides, making it a potential site-specific probe for RNA structure and dynamics. Similar to 2-aminopurine nucleoside, which base-pairs with uridine (or thymidine), PC's fluorescence becomes reversibly quenched upon base-pairing, most likely due to stacking interactions with neighboring bases. To test its utility as an RNA probe, we examined PC's fluorescent properties over a wide range of ionic strengths, pH, organic cosolvents, and temperatures. Incorporation of PC into a single-stranded RNA results in an approximately 60% reduction of fluorescence intensity, while duplex formation reduces the fluorescence by approximately 75% relative to the free ribonucleoside. We find that the fluorescence intensity of PC is only moderately affected by ionic strength, pH, and temperature, while it is slightly enhanced by organic cosolvents, making it a versatile probe for a broad range of buffer conditions. We demonstrate two applications for PC: fluorescent measurements of the kinetics of formation and dissociation of an RNA/DNA complex, and fluorescent monitoring of the thermal denaturation of the central segment of an RNA duplex. Taken together, our data showcase the potential of pyrrolo-C as an effective fluorescent probe to study RNA structure, dynamics, and function, complementary to the popular 2-aminopurine ribonucleoside.

Base Pairing↗
PubMed1996

RNA loop structure prediction via bond scaling and relaxation.

We have developed a method for predicting the structure of small RNA loops that can be used to augment already existing RNA modeling techniques. The method requires no input constraints on loop configuration other than end-to-end distance. Initial loop structures are generated by randomizing the torsion angles, beginning at one end of the polynucleotide chain and correlating each successive angle with the previous. The bond lengths of these structures are then scaled to fit within the known end constraints and the equilibrium bond lengths of the potential energy function are scaled accordingly. Through a series of rescaling and minimization steps the structures are allowed to relax to lower energy configurations with standard bond lengths and reduced van der Waals clashes. This algorithm has been tested on the variable loops of yeast tRNA-Asp and yeast tRNA-Phe, as well as the sarcin-ricin tetraloop and the anticodon loop of yeast tRNA-Phe. The results indicate good correlation between potential energy and the loop structure predictions that are closest to the variable loop crystal structures, but poorer correlation for the more isolated stem loops. The number of stacking interactions has proven to be a good objective measure of the best loop predictions. Selecting on the basis of energy and stacking, we obtain two structures with 0.65 and 0.75 A all-atom rms deviations (RMSD) from the crystal structure for the tRNA-Asp variable loop. The best structure prediction for the tRNA-Phe variable loop has an all-atom RMSD of 2.2 A and a backbone RMSD of 1.6 A, with a single base responsible for most of the deviation. For the sarcin-ricin loop from 28S ribosomal RNA, the predicted structure's all-atom RMSD from the nmr structure is 1.0 A. We obtain a 1.8 A RMSD structure for the tRNA-Phe anticodon loop.

Algorithms↗
PubMed2006

Memory efficient folding algorithms for circular RNA secondary structures.

BACKGROUND: A small class of RNA molecules, in particular the tiny genomes of viroids, are circular. Yet most structure prediction algorithms handle only linear RNAs. The most straightforward approach is to compute circular structures from 'internal' and 'external' substructures separated by a base pair. This is incompatible, however, with the memory-saving approach of the Vienna RNA Package which builds a linear RNA structure from shorter (internal) structures only. RESULT: Here we describe how circular secondary structures can be obtained without additional memory requirements as a kind of 'post-processing' of the linear structures. AVAILABILITY: The circular folding algorithm is implemented in the current version of the of RNAfold program of the Vienna RNA Package, which can be downloaded from http://www.tbi.univie.ac.at/RNA/

Algorithms↗
PubMed2003

Characterization of the structure and variability of an internal region of hepatitis C virus RNA for M1 RNA guide sequence ribozyme targeting.

Accessibility to folded RNA and low potential of variation in the target RNA are crucial requirements for ribozyme therapy against virus infections. In hepatitis C virus (HCV), the sequence of the 5'UTR is conserved but the highly folded RNA structure severely limits the number of accessible sites. To expand investigation of targeting in the HCV genome, we have considered an internal genomic region whose sequence variation has been widely investigated and which has a particularly conserved RNA structure, which makes it accessible to the human RNase P in vitro. We have first mapped the accessibility of the genomic RNA to complementary DNAs within this internal genomic region. We performed a kinetic and thermodynamic study. Accordingly, we have designed and assayed four RNase P M1 RNA guide sequence ribozymes targeted to the selected sites. Considerations of RNA structural accessibility and sequence variation indicate that several target sites should be defined for simultaneous attack.

Base Sequence↗
PubMed1988

A program for predicting significant RNA secondary structures.

We describe a program for the analysis of RNA secondary structure. There are two new features in this program. (i) To get vector speeds on a vector pipeline machine (such as Cray X-MP/24) we have vectorized the secondary structure dynamic algorithm. (ii) The statistical significance of a locally 'optimal' secondary structure is assessed by a Monte Carlo method. The results can be depicted graphically including profiles of the stability of local secondary structures and the distribution of the potentially significant secondary structures in the RNA molecules. Interesting regions where both the potentially significant secondary structures and 'open' structures (single-stranded coils) occur can be identified by the plots mentioned above. Furthermore, the speed of the vectorized code allows repeated Monte Carlo simulations with different overlapping window sizes. Thus, the optimal size of the significant secondary structure occurring in the interesting region can be assessed by repeating the Monte Carlo simulation. The power of the program is demonstrated in the analysis of local secondary structures of human T-cell lymphotrophic virus type III (HIV).

Algorithms↗
PubMed1997

An RNA tertiary structure in the 3' untranslated region of enteroviruses is necessary for efficient replication.

RNA tertiary structures, such as pseudoknots, are known to be biologically significant in a number of virus systems. The 3' untranslated regions of the RNA genomes of all members of the Enterovirus genus of Picornaviridae exhibit a potential, pseudoknot-like, tertiary structure interaction of an unusual type. This is formed by base pairing between loop regions of two secondary structure domains. It is distinct from a potential, conventional pseudoknot, studied previously in poliovirus, which is less conserved phylogenetically. We have analyzed the tertiary structure feature in one enterovirus, coxsackievirus A9, using specific mutagenesis. A double mutant in which the potential interaction was destroyed was nonviable, and viability was restored by introducing compensating mutations, predicted to allow the interaction to reform. Phenotypic pseudorevertants of virus mutants, having mutations designed to disrupt the interaction, were all found to have acquired nucleotide changes which restored the potential interaction. Analysis of one mutant containing a single-base mutation indicated a greatly increased temperature sensitivity due to a step early in replication. The results show that, in addition to secondary structures, tertiary RNA structural interactions can play an important role in the biology of picornaviruses.

Base Sequence↗
PubMed1995

RNA secondary structure prediction using highly parallel computers.

An RNA secondary structure prediction method using a highly parallel computer is reported. We focus on finding thermodynamically stable structures of a single-stranded RNA molecule. Our approach is based on a parallel combinatorial method which calculates the free energy of a molecule as the sum of the free energies of all the physically possible hydrogen bonds. Our parallel algorithm finds many highly stable structures all at once, while most of the conventional prediction methods find only the most stable structure. The important idea in our algorithm is search tree pruning, with dynamic load balancing across the processor elements in a parallel computer. Software tools for visualization and classification of secondary structures are also presented using the sequence of cadang-cadang coconut viroid as an example. Our software system runs on CM-5.

Algorithms↗
PubMed2001

The kink-turn: a new RNA secondary structure motif.

Analysis of the Haloarcula marismortui large ribosomal subunit has revealed a common RNA structure that we call the kink-turn, or K-turn. The six K-turns in H.marismortui 23S rRNA superimpose with an r.m.s.d. of 1.7 A. There are two K-turns in the structure of Thermus thermophilus 16S rRNA, and the structures of U4 snRNA and L30e mRNA fragments form K-turns. The structure has a kink in the phosphodiester backbone that causes a sharp turn in the RNA helix. Its asymmetric internal loop is flanked by C-G base pairs on one side and sheared G-A base pairs on the other, with an A-minor interaction between these two helical stems. A derived consensus secondary structure for the K-turn includes 10 consensus nucleotides out of 15, and predicts its presence in the 5'-UTR of L10 mRNA, helix 78 in Escherichia coli 23S rRNA and human RNase MRP. Five K-turns in 23S rRNA interact with nine proteins. While the observed K-turns interact with proteins of unrelated structures in different ways, they interact with L7Ae and two homologous proteins in the same way.

Amino Acid Sequence↗
PubMed1998

Prediction of RNA secondary structure based on helical regions distribution.

MOTIVATION: RNAs play an important role in many biological processes and knowing their structure is important in understanding their function. Due to difficulties in the experimental determination of RNA secondary structure, the methods of theoretical prediction for known sequences are often used. Although many different algorithms for such predictions have been developed, this problem has not yet been solved. It is thus necessary to develop new methods for predicting RNA secondary structure. The most-used at present is Zuker's algorithm which can be used to determine the minimum free energy secondary structure. However many RNA secondary structures verified by experiments are not consistent with the minimum free energy secondary structures. In order to solve this problem, a method used to search a group of secondary structures whose free energy is close to the global minimum free energy was developed by Zuker in 1989. When considering a group of secondary structures, if there is no experimental data, we cannot tell which one is better than the others. This case also occurs in combinatorial and heuristic methods. These two kinds of methods have several weaknesses. Here we show how the central limit theorem can be used to solve these problems. RESULTS: An algorithm for predicting RNA secondary structure based on helical regions distribution is presented, which can be used to find the most probable secondary structure for a given RNA sequence. It consists of three steps. First, list all possible helical regions. Second, according to central limit theorem, estimate the occurrence probability of every helical region based on the Monte Carlo simulation. Third, add the helical region with the biggest probability to the current structure and eliminate the helical regions incompatible with the current structure. The above processes can be repeated until no more helical regions can be added. Take the current structure as the final RNA secondary structure. In order to demonstrate the confidence of the program, a test on three RNA sequences: tRNAPhe, Pre-tRNATyr, and Tetrahymena ribosomal RNA intervening sequence, is performed. AVAILABILITY: The program is written in Turbo Pascal 7.0. The source code is available upon request. CONTACT: Wujj@nic.bmi.ac.cn or Liwj@mail.bmi.ac.cn

Algorithms↗
PubMed1991

Alu RNA secondary structure consists of two independent 7 SL RNA-like folding units.

The amplification of genomic Alu elements by retroposition, i.e. by reintegration of reverse-transcribed RNA, suggests that Alu RNA plays an important role in this process. We report enzymatic studies of the secondary structure of Alu RNAs transcribed in vitro from two recently retroposed Alu elements. These experiments show that the dimeric organization of an Alu sequence is reflected in its RNA folding. Alu subunits fold independently, conserving secondary structure motifs of their progenitor 7 SL RNA molecule. Energy minimization analysis indicates that this folding pattern is also characteristic of different Alu and Alu-like sequences and has been conserved since primate divergence. By analogy to 7 SL RNA, the Alu RNA folding may be important for specific interactions with proteins. This could indicate a physiological function for Alu transcripts. However, this can be also seen as a structural adaptation leading to efficient retroposition of these sequence elements.

Base Sequence↗
PubMed1997

RnaViz, a program for the visualisation of RNA secondary structure.

RnaViz is a user-friendly, portable, windows-type program for producing publication-quality secondary structure drawings of RNA molecules. Drawings can be created starting from DCSE alignment files if they incorporate structure information or from mfold ct files. The layout of a structure can be changed easily. Display of special structural elements such as pseudo-knots or unformatted areas is possible. Sequences can be automatically numbered, and several other types of labels can be used to annotate particular bases or areas. Although the program does not try to produce an initially non-overlapping drawing, the layout of a properly positioned structure drawing can be applied to a newly created drawing using skeleton files. In this way a range of similar structures can be drawn with a minimum of effort. Skeletons for several types of RNA molecule are included with the program.

Base Sequence↗
PubMed2006

Translation of the flavivirus kunjin NS3 gene in cis but not its RNA sequence or secondary structure is essential for efficient RNA packaging.

Our previous studies using trans-complementation analysis of Kunjin virus (KUN) full-length cDNA clones harboring in-frame deletions in the NS3 gene demonstrated the inability of these defective complemented RNAs to be packaged into virus particles (W. J. Liu, P. L. Sedlak, N. Kondratieva, and A. A. Khromykh, J. Virol. 76:10766-10775). In this study we aimed to establish whether this requirement for NS3 in RNA packaging is determined by the secondary RNA structure of the NS3 gene or by the essential role of the translated NS3 gene product. Multiple silent mutations of three computer-predicted stable RNA structures in the NS3 coding region of KUN replicon RNA aimed at disrupting RNA secondary structure without affecting amino acid sequence did not affect RNA replication and packaging into virus-like particles in the packaging cell line, thus demonstrating that the predicted conserved RNA structures in the NS3 gene do not play a role in RNA replication and/or packaging. In contrast, double frameshift mutations in the NS3 coding region of full-length KUN RNA, producing scrambled NS3 protein but retaining secondary RNA structure, resulted in the loss of ability of these defective RNAs to be packaged into virus particles in complementation experiments in KUN replicon-expressing cells. Furthermore, the more robust complementation-packaging system based on established stable cell lines producing large amounts of complemented replicating NS3-deficient replicon RNAs and infection with KUN virus to provide structural proteins also failed to detect any secreted virus-like particles containing packaged NS3-deficient replicon RNAs. These results have now firmly established the requirement of KUN NS3 protein translated in cis for genome packaging into virus particles.

Animals↗