Thermodynamic characterization of RNA 2 × 3 nucleotide internal loops

To better elucidate RNA structure-function relationships and to improve the design of pharmaceutical agents that target specific RNA motifs, an understanding of RNA primary, secondary, and tertiary structure is necessary. The prediction of RNA secondary structure from sequence is an intermediate step in predicting RNA three-dimensional structure. RNA secondary structure is typically predicted using a nearest neighbor model based on free energy parameters. The current free energy parameters for 2 × 3 nucleotide loops are based on a 23-member data set of 2 × 3 loops and internal loops of other sizes. A database of representative RNA secondary structures was searched to identify 2 × 3 nucleotide loops that occur in nature. Seventeen of the most frequent 2 × 3 nucleotide loops in this database were studied by optical melting experiments. Fifteen of these loops melted in a two-state manner, and the associated experimental ΔG°(37,2×3) values are, on average, 0.6 and 0.7 kcal/mol different from the values predicted for these internal loops using the predictive models proposed by Lu, Turner, and Mathews [Lu, Z. J., Turner, D. H., and Mathews, D. H. (2006) Nucleic Acids Res. 34, 4912-4924] and Chen and Turner [Chen, G., and Turner, D. H. (2006) Biochemistry 45, 4025-4043], respectively. These new ΔG°(37,2×3) values can be used to update the current algorithms that predict secondary structure from sequence. To improve free energy calculations for duplexes containing 2 × 3 nucleotide loops that still do not have experimentally determined free energy contributions, an updated predictive model was derived. This new model resulted from a linear regression analysis of the data reported here combined with 31 previously studied 2 × 3 nucleotide internal loops. Most of the values for the parameters in this new predictive model are within experimental error of those of the previous models, suggesting that approximations and assumptions associated with the derivation of the previous nearest neighbor parameters were valid. The updated predictive model predicts free energies of 2 × 3 nucleotide internal loops within 0.4 kcal/mol, on average, of the experimental free energy values. Both the experimental values and the updated predictive model can be used to improve secondary structure prediction from sequence.     

Thermodynamic characterization of the complete set of sequence symmetric tandem mismatches in RNA and an improved model for predicting the free energy contribution of sequence asymmetric tandem mismatches

Because of the availability of an abundance of RNA sequence information, the ability to rapidly and accurately predict the secondary structure of RNA from sequence is becoming increasingly important. A common method for predicting RNA secondary structure from sequence is free energy minimization. Therefore, accurate free energy contributions for every RNA secondary structure motif are necessary for accurate secondary structure predictions. Tandem mismatches are prevalent in naturally occurring sequences and are biologically important. A common method for predicting the stability of a sequence asymmetric tandem mismatch relies on the stabilities of the two corresponding sequence symmetric tandem mismatches [Mathews, D. H., Sabina, J., Zuker, M., and Turner, D. H. (1999) J. Mol. Biol. 288, 911-940]. To improve the prediction of sequence asymmetric tandem mismatches, the experimental thermodynamic parameters for the 22 previously unmeasured sequence symmetric tandem mismatches are reported. These new data, however, do not improve prediction of the free energy contributions of sequence asymmetric tandem mismatches. Therefore, a new model, independent of sequence symmetric tandem mismatch free energies, is proposed. This model consists of two penalties to account for destabilizing tandem mismatches, two bonuses to account for stabilizing tandem mismatches, and two penalties to account for A-U and G-U adjacent base pairs. This model improves the prediction of asymmetric tandem mismatch free energy contributions and is likely to improve the prediction of RNA secondary structure from sequence.     

Identification of potential conserved RNA secondary structure throughout influenza A coding regions

Influenza A is a negative sense RNA virus of significant public health concern. While much is understood about the life cycle of the virus, knowledge of RNA secondary structure in influenza A virus is sparse. Predictions of RNA secondary structure can focus experimental efforts. The present study analyzes coding regions of the eight viral genome segments in both the (+) and (-) sense RNA for conserved secondary structure. The predictions are based on identifying regions of unusual thermodynamic stabilities and are correlated with studies of suppression of synonymous codon usage (SSCU). The results indicate that secondary structure is favored in the (+) sense influenza RNA. Twenty regions with putative conserved RNA structure have been identified, including two previously described structured regions. Of these predictions, eight have high thermodynamic stability and SSCU, with five of these corresponding to current annotations (e.g., splice sites), while the remaining 12 are predicted by the thermodynamics alone. Secondary structures with high conservation of base-pairing are proposed within the five regions having known function. A combination of thermodynamics, amino acid and nucleotide sequence comparisons along with SSCU was essential for revealing potential secondary structures.     

Consensus folding of unaligned RNA sequences revisited.

As one of the earliest problems in computational biology, RNA secondary structure prediction (sometimes referred to as "RNA folding") problem has attracted attention again, thanks to the recent discoveries of many novel non-coding RNA molecules. The two common approaches to this problem are de novo prediction of RNA secondary structure based on energy minimization and the consensus folding approach (computing the common secondary structure for a set of unaligned RNA sequences). Consensus folding algorithms work well when the correct seed alignment is part of the input to the problem. However, seed alignment itself is a challenging problem for diverged RNA families. In this paper, we propose a novel framework to predict the common secondary structure for unaligned RNA sequences. By matching putative stacks in RNA sequences, we make use of both primary sequence information and thermodynamic stability for prediction at the same time. We show that our method can predict the correct common RNA secondary structures even when we are given only a limited number of unaligned RNA sequences, and it outperforms current algorithms in sensitivity and accuracy.     

Secondary structure probing of the human RNase MRP RNA reveals the potential for MRP RNA subsets

RNase MRP is a ribonucleoprotein endoribonuclease involved in eukaryotic pre-rRNA processing. The enzyme possesses an RNA subunit, structurally related to that of RNase P RNA, that is thought to be catalytic. RNase MRP RNA sequences from Saccharomycetaceae species are structurally well defined through detailed phylogenetic and structural analysis. In contrast, higher eukaryote MRP RNA structure models are based on comparative sequence analysis of only five sequences and limited probing data. Detailed structural analysis of the Homo sapiens MRP RNA, entailing enzymatic and chemical probing, is reported. The data are consistent with the phylogenetic secondary structure model and demonstrate unequivocally that higher eukaryote MRP RNA structure differs significantly from that reported for Saccharomycetaceae species. Neither model can account for all of the known MRP RNAs and we thus propose the evolution of at least two subsets of RNase MRP secondary structure, differing predominantly in the predicted specificity domain.     

A specific sequence with a bulged guanosine residue(s) in a stem-bulge-stem structure of Rev-responsive element RNA is required for trans activation by human immunodeficiency virus type 1 Rev.

We demonstrate that both the in vitro RNA binding and in vivo trans activation functions of human immunodeficiency virus type 1 Rev regulatory protein Rev require the presence of a 9-nucleotide 5'-CACUAUGGG-3' RNA motif on its cognate target, the Rev-responsive element RNA. For optimal Rev recognition, this sequence must be presented as a stem-bulge-stem structure and must contain at least two G's, one of which must be unpaired, and include some or all of the CACUAU sequence upstream of the three G's. Distal mutations which result in the base pairing of the G's eliminate the Rev response. The first G is crucial, but changes at the other G's are tolerated if at least one G is unpaired. The secondary structure or the three-dimensional orientation of the B1 and B2 stem-loops of the Rev-responsive element are not relevant as long as the 5'-CACUAUGGG-3' sequence is preserved, with at least one bulged G residue.     

Determination of functional domains in intron bI1 of yeast mitochondrial RNA by studies of mitochondrial mutations and a nuclear suppressor.

The sequence of intron 1 in the cob gene in mtDNA (bI1) of the yeast strain 777-3A has been determined. Furthermore, we have performed a systematic search for complementary sequence stretches within this intron RNA, and within the RNA of intron 5 gamma of the oxi3 gene (aI5 gamma) which shares distinctive sequences with bI1. Possible secondary structure models derived from this analysis show nearly identical core structures for bI1 and aI5 gamma RNA with conserved sequence stretches in prominent positions. These core structures are similar to those previously reported for RNAs of introns having very limited sequence homology with bI1 and aI5 gamma. In two mutants which are defective in bI1 excision from cob pre-mRNA, nucleotide sequence alterations in bI1 have been determined. One mutation (G5049) apparently affects the stability of a hybrid stretch in the proposed secondary structure of bI1 RNA whereas the other one (M1301), a deletion of one A in a run of five As, affects a sequence which is conserved in bI1 and aI5 gamma and is involved in the formation of a distinct secondary structure. Out of seven revertants of M1301, three were found to have restored the wild-type bI1 sequence AAAAA, three others had the related sequence AAAAG which is functionally indistinguishable from wild-type, whereas one revertant had a nuclear mutation which suppresses the splicing defect exerted by the mitochondrial mutation M1301. This nuclear suppressor (SUP-101) is allele specific and dominant. The possible role of the sequence affected by M1301 in terms of a recognition site for a nuclear gene product will be discussed.     

Structural analyses of mammalian ribosomal ribonucleic acid and its precursors. Nucleotide sequence of ribosomal 5.8 S ribonucleic acid.

The nucleotide sequence of ribosomal 5.8 S RNA (also known as 7 S or 5.5 S rRNA) from Novikoff hepatoma ascites cells has been determined to be (see article). Estimations of the secondary structure based upon maximized base pairing and the fragments of partial ribonuclease digestion indicate that there may be five base-paired regions in the molecule, three forming a folding of the termini and two forming secondary hairpin loops. The sequence of Novikoff hepatoma 5.8 S rRNA is about 75% homologous with that of yeast 5.8 S rRNA (Rubin, G.M. (1973) J. Biol. Chem. 248, 3860-3875) and similar models for secondary structure are proposed. Both models contain a very stable G-C rich hairpin loop (residues 116 to 138), a less stable A-U-rich hairpin loop (residues 64 to 91) and two symmetrical bulges (residues 15 to 25 and 40 to 44).     

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      

A comparison of siRNA efficacy predictors

Short interfering RNA (siRNA) efficacy prediction algorithms aim to increase the probability of selecting target sites that are applicable for gene silencing by RNA interference. Many algorithms have been published recently, and they base their predictions on such different features as duplex stability, sequence characteristics, mRNA secondary structure, and target site uniqueness. We compare the performance of the algorithms on a collection of publicly available siRNAs. First, we show that our regularized genetic programming algorithm GPboost appears to have a higher and more stable performance than other algorithms on the collected datasets. Second, several algorithms gave close to random classification on unseen data, and only GPboost and three other algorithms have a reasonably high and stable performance on all parts of the dataset. Third, the results indicate that the siRNAs' sequence is sufficient input to siRNA efficacy algorithms, and that other features that have been suggested to be important may be indirectly captured by the sequence.     

Structural studies of 5 S ribosomal RNAs from a thermophilic fungus, Thermomyces lanuginosus. A comparison of generalized models for eukaryotic 5 S RNAs

The cytoplasmic ribosomes of the thermophilic fungus Thermomyces lanuginosus contain two types of 5 S RNA. The nucleotide sequence for approximately 80% of the molecules is (pp)pA-C-A-U-G-C-G-A-C-C-A-U-A-G-G-G-U-G-U-G-G-A-A-A-A-C-A-G-G-G-C-U-U-C-C-C-G-U-C-C-G-C-U-C-A-G-C-C-G-U-A-C-U-U-A-A-G-C-C-A-C-A-C-G-C-C-G-G-C-U-G-G-U-U-A-G-U-A-G-U-U-G-G-G-U-G-G-G-U-G-A-C-C-A-C-C-A-G-C-G-A-A-U-C-C-C-A-G-C-U-G-U-U-G-C-A-U-G-UOH. The remainder contains two nucleotide substitutions, C19 and G60, which preserve base complementarity. The secondary structure was probed using partial T1, pancreatic, and S1 nuclease digestion under a variety of ionic and temperature conditions and fragments were analyzed by rapid gel sequencing techniques. The results support the Y-shaped secondary structure model originally proposed by Nishikawa, K., and Takemura, S. (1974) FEBS Lett. 40, 106-109, for eukaryotic 5 S RNAs. When the thermal denaturation profile was compared with that of the yeast 5 S RNA, the thermophilic RNA exhibited not only a higher Tm but also an unusual decline in absorbency at moderate temperatures. This suggests that a functionally important structure may be maintained only at higher temperatures.     

R-CHIE: a web server and R package for visualizing RNA secondary structures

Visually examining RNA structures can greatly aid in understanding their potential functional roles and in evaluating the performance of structure prediction algorithms. As many functional roles of RNA structures can already be studied given the secondary structure of the RNA, various methods have been devised for visualizing RNA secondary structures. Most of these methods depict a given RNA secondary structure as a planar graph consisting of base-paired stems interconnected by roundish loops. In this article, we present an alternative method of depicting RNA secondary structure as arc diagrams. This is well suited for structures that are difficult or impossible to represent as planar stem-loop diagrams. Arc diagrams can intuitively display pseudo-knotted structures, as well as transient and alternative structural features. In addition, they facilitate the comparison of known and predicted RNA secondary structures. An added benefit is that structure information can be displayed in conjunction with a corresponding multiple sequence alignments, thereby highlighting structure and primary sequence conservation and variation. We have implemented the visualization algorithm as a web server R-chie as well as a corresponding R package called R4RNA, which allows users to run the software locally and across a range of common operating systems.     

基于启发式算法预测含假结RNA二级结构的研究进展

RNA二级结构的预测算法研究已有近40年的发展历程,研究假结也将近30年的历史。在此期间,RNA二级结构的预测算法取得了很大进步,但假结预测的正确率依然偏低。其中启发式算法能较好地处理复杂假结,使其成为率先解决假结预测难题可能性最大的算法。迄今为止,未见系统地专门总结预测假结的各种启发式算法及其优点与缺点的报道。本文详细介绍了近年来国际上流行的贪婪算法、遗传算法、ILM算法、HotKnots算法以及FlexStem算法等五种算法,并总结分析了每种算法的优点与不足,最后提出在未来一段时期内,利用启发式算法提高假结预测准确度应从建立更完善的假结模型、加入更多影响因素、借鉴不同算法的优势等方面入手。为含假结RNA二级结构预测的研究提供参考。     

Identification and assignment of base pairs in the "tuned helix" of intact and ribonuclease T1 cleavage fragments of wheat germ ribosomal 5S RNA via 500-MHz proton homonuclear Overhauser enhancements

Wheat germ has been chosen as a representative eukaryote for study of ribosomal 5S RNA secondary structure. Proton homonuclear Overhauser enhancements (NOE's) at 500 MHz for the hydrogen-bonded base-pair protons in the 10-15 ppm region are used to establish the identity (A X U, G X C, or G X U) and base-pair sequence (e.g., G X C-A X U-C X G) within a given helical segment. Assignment of that segment to particular base pairs in the secondary structure is based upon NOE's conducted at different temperatures (to determine which signals "melt" together), variation of salt conditions (to produce differential chemical shifts in order to better distinguish components of an unresolved spectral envelope), and isolation and purification of RNase T1 cleavage fragments (in order to reduce the spectrum to just a few base pairs). The NOE patterns for the RNase T1 fragments are the same as in the intact 5S RNA, supporting the assumption that structural features of this region in the intact 5S RNA are preserved in the fragment. Chemical shifts predicted from ring current induced effects for a proposed base-pair sequence are then compared to experimental chemical shifts. By these methods, a portion of the "tuned helix" segment (namely, the base-pair sequence C18G60-A19U59-C20G58) is demonstrated spectroscopically for the first time in any 5S RNA. The tuned helix and common arm segments are less stable than the rest of the molecule. Variation of sodium and magnesium levels reveals multiple configurations of the wheat germ 5S RNA in solution.     

Predicting RNA secondary structures with arbitrary pseudoknots by maximizing the number of stacking pairs.

The paper investigates the computational problem of predicting RNA secondary structures. The general belief is that allowing pseudoknots makes the problem hard. Existing polynomial-time algorithms are heuristic algorithms with no performance guarantee and can handle only limited types of pseudoknots. In this paper, we initiate the study of predicting RNA secondary structures with a maximum number of stacking pairs while allowing arbitrary pseudoknots. We obtain two approximation algorithms with worst-case approximation ratios of 1/2 and 1/3 for planar and general secondary structures, respectively. For an RNA sequence of n bases, the approximation algorithm for planar secondary structures runs in O(n(3)) time while that for the general case runs in linear time. Furthermore, we prove that allowing pseudoknots makes it NP-hard to maximize the number of stacking pairs in a planar secondary structure. This result is in contrast with the recent NP-hard results on psuedoknots which are based on optimizing some general and complicated energy functions.     

On realizing shapes in the theory of RNA neutral networks

It is known (Reidys et al., 1997b. Bull. Math. Biol. 59(2), 339-397) that for any two secondary structures S,S' there exists an RNA sequence compatible with both, and that this result does not extend to more than two secondary structures. Indeed, a simple formula for the number of RNA sequences compatible with secondary structures S,S' plays a role in the algorithms of Flamm et al. (2001. RNA 7, 254-265) and of Abfalter et al. (2003. Proceedings of the German Conference on Bioinformatics, ) to design an RNA switch. Here we show that a natural extension of this problem is NP-complete. Unless P=NP, there is no polynomial time algorithm, which when given secondary structures S1,...,S(k), for k4, determines the least number of positions, such that after removal of all base pairs incident to these positions there exists an RNA nucleotide sequence compatible with the given secondary structures. We also consider a restricted version of this problem with a "fixed maximum" number of possible stars and show that it has a simple polynomial time solution.     

Boltzmann probability of RNA structural neighbors and riboswitch detection

MOTIVATION: We describe algorithms implemented in a new software package, RNAbor, to investigate structures in a neighborhood of an input secondary structure S of an RNA sequence s. The input structure could be the minimum free energy structure, the secondary structure obtained by analysis of the X-ray structure or by comparative sequence analysis, or an arbitrary intermediate structure. RESULTS: A secondary structure T of s is called a delta-neighbor of S if T and S differ by exactly delta base pairs. RNAbor computes the number (N(delta)), the Boltzmann partition function (Z(delta)) and the minimum free energy (MFE(delta)) and corresponding structure over the collection of all delta-neighbors of S. This computation is done simultaneously for all delta < or = m, in run time O (mn3) and memory O(mn2), where n is the sequence length. We apply RNAbor for the detection of possible RNA conformational switches, and compare RNAbor with the switch detection method paRNAss. We also provide examples of how RNAbor can at times improve the accuracy of secondary structure prediction. AVAILABILITY: http://bioinformatics.bc.edu/clotelab/RNAbor/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Thermodynamic study of internal loops in oligoribonucleotides: symmetric loops are more stable than asymmetric loops.

Thermodynamic parameters for internal loops of unpaired adenosines in oligoribonucleotides have been measured by optical melting studies. Comparisons are made between helices containing symmetric and asymmetric loops. Asymmetric loops destabilize a helix more than symmetric loops. The differences in free energy between symmetric and asymmetric loops are roughly half the magnitude suggested from a study of parameters required to give accurate predictions of RNA secondary structure [Papanicolaou, C., Gouy, M., & Ninio, J. (1984) Nucleic Acids Res. 12, 31-44]. Circular dichroism spectra indicate no major structural difference between helices containing symmetric and asymmetric loops. The measured sequence dependence of internal loop stability is not consistent with approximations used in current algorithms for predicting RNA secondary structure.     

Energy landscape of k-point mutants of an RNA molecule

MOTIVATION: A k-point mutant of a given RNA sequence s = s(1), ..., s(n) is an RNA sequence s' = s'(1),..., s'(n) obtained by mutating exactly k-positions in s; i.e. Hamming distance between s and s' equals k. To understand the effect of pointwise mutation in RNA, we consider the distribution of energies of all secondary structures of k-point mutants of a given RNA sequence. RESULTS: Here we describe a novel algorithm to compute the mean and standard deviation of energies of all secondary structures of k-point mutants of a given RNA sequence. We then focus on the tail of the energy distribution and compute, using the algorithm AMSAG, the k-superoptimal structure; i.e. the secondary structure of a < or =k-point mutant having least free energy over all secondary structures of all k'-point mutants of a given RNA sequence, for k' < or = k. Evidence is presented that the k-superoptimal secondary structure is often closer, as measured by base pair distance and two additional distance measures, to the secondary structure derived by comparative sequence analysis than that derived by the Zuker minimum free energy structure of the original (wild type or unmutated) RNA.