Analysis of the conformational energy landscape of human snRNA with a metric based on tree representation of RNA structures

It is an outstanding problem to clarify how the RNA sequence is related to its structure and biological functions. We developed a simplified definition of a metric for tree representation of RNA secondary structures and analyzed the conformational energy landscapes of human spliceosomal snRNAs. We discuss the structural properties of the biological sequence by calculating the conformational energy landscapes based on the structural distance between each of the pairs in the set of suboptimal structures. The new index value is introduced for estimating the shapes of distribution patterns in conformational energy landscapes. We apply our method to the five human snRNAs and show that U1 snRNA has a multi-valley profile of the landscape, whereas the landscapes of the other four snRNAs have one steep valley. This result reflects different biological functions of these snRNAs in the pre-mRNA splicing process. The results of analyzing tRNAs and rRNAs show that the conformational energy landscapes of these sequences have multi-valley profiles.     

A precursor to a minor species of yeast tRNASer contains an intervening sequence.

Certain tRNAs in S. cerevisiae (tRNATyr and tRNAPhe) arise via precursor molecules which are mature at the 5' and 3' termini but contain intervening sequences adjacent to the anticodon (Knapp et al., 1978; O'Farrell et al., 1978). In addition to these molecules, precursors to several other tRNAs accumulate in a temperature-sensitive mutant (ts136) at the nonpermissive temperature. We have analyzed one of these species and shown that it is a precursor to a minor species of tRNASer. This precursor is also mature at both termini and contains an intervening sequence of 19 nucleotides adjacent to the hypermodified A residue 3' to the anticodon. The sequence can be arranged in a secondary structure in which the anticodon stem is extended by additional base-pairing, and contains the sites of excision and ligation within two looped regions. Support for this structure was provided by analysis of the products of limited digestion with RNAase T1. recently Piper (1978) reported the isolation of a minor species of tRNASer which decodes UCG. He found this species to be structurally heterogeneous and determined that the less abundant form corresponds to the tRNA which is altered in the recessive lethal SUP-RL1 amber suppressor. Our data now suggest that the more abundant form may be restricted to reading UCA in vivo; thus mutation of the minor species would result in complete loss of UCG-decoding ability and explain the recessive lethality of SUP-RL1. We have shown that the precursor which accumulates in ts136 corresponds exclusively to this minor tRNASerUCG species. Our results suggest that this may be the only gene for tRNASer in yeast which contains an intervening sequence.     

The Presence in tRNA Molecule Sequences of the Double Hairpin,an Evolutionary Stage Through Which the Origin of this Molecule is Thought to have Passed

We analyse 6,810 tRNAs, calculating the free energy of the corresponding double hairpin and ‘cigar’ secondary structures, for which we find a high thermodynamic and statistical significance. We also analyse these tRNAs for similarity and complementarity of their 5′ and 3′ halves or segments of them in intra-and inter-molecular comparisons. We find very clear signs that the two halves of tRNAs had an evident evolutionary relationship, although it is not totally clear whether this was a relationship of homology or complementarity between the 5′ and 3′ halves of tRNAs, even if there is strong evidence in favour of the homology hypothesis. Overall, these data favour models for the origin of the tRNA molecule postulating that a duplication event involving a hairpin structure as a precursor was involved in the origin of this molecule. Moreover, we interpret these results and favour the hypothesis that sees the assembly of two hairpin structures sharing a homology relationship as the intermediate evolutionary stage preceding the appearance of the cloverleaf structure of tRNA.     

On quantitative effects of RNA shape abstraction

Over the last few decades, much effort has been taken to develop approaches for identifying good predictions of RNA secondary structure. This is due to the fact that most computational prediction methods based on free energy minimization compute a number of suboptimal foldings and we have to identify the native folding among all these possible secondary structures. Using the abstract shapes approach as introduced by Giegerich et al. (Nucleic Acids Res 32(16):4843–4851, 2004), each class of similar secondary structures is represented by one shape and the native structures can be found among the top shape representatives. In this article, we derive some interesting results answering enumeration problems for abstract shapes and secondary structures of RNA. We compute precise asymptotics for the number of different shape representations of size n and for the number of different shapes showing up when abstracting from secondary structures of size n under a combinatorial point of view. A more realistic model taking primary structures into account remains an open challenge. We give some arguments why the present techniques cannot be applied in this case.     

Functional defects of pathogenic human mitochondrial tRNAs related to structural fragility

Aminoacylation of transfer RNAs (tRNAs) is essential for protein synthesis. A growing number of human diseases correlate with point mutations in tRNA genes within the mitochondrial genome. These tRNAs have unique sequences that suggest they have fragile structures. However, the structural significance of pathology-related tRNA mutations and their effects on molecular function have not been explored. Here, opthalmoplegia related mutants of a human mitochondrial tRNA have been investigated. Each mutation replaces either an A-U or G-C pair in the predicted secondary structure with an A-C pair. Aminoacylation of each mutant tRNA was severely attenuated. Moreover, each strongly inhibited aminoacylation of the wild type substrate, suggesting that the effects of these mutations might not be bypassed in the potentially heteroplasmic environment of mitochondria. The function of mutant tRNAs was rescued by single compensatory mutations that restored Watson-Crick base pairing and reintroduced stability into regions of predicted secondary structure, even though the pairs introduced were different from those found in the wild type tRNA. Thus, functional defects caused by a subset of pathogenic mutations may result from the inherent structural fragility of human mitochondrial tRNAs.     

Crystal structure of the tRNA 3' processing endoribonuclease tRNase Z from Thermotoga maritima

The maturation of the tRNA 3' end is catalyzed by a tRNA 3' processing endoribonuclease named tRNase Z (RNase Z or 3'-tRNase) in eukaryotes, Archaea, and some bacteria. The tRNase Z generally cuts the 3' extra sequence from the precursor tRNA after the discriminator nucleotide. In contrast, Thermotoga maritima tRNase Z cleaves the precursor tRNA precisely after the CCA sequence. In this study, we determined the crystal structure of T. maritima tRNase Z at 2.6-A resolution. The tRNase Z has a four-layer alphabeta/betaalpha sandwich fold, which is classified as a metallo-beta-lactamase fold, and forms a dimer. The active site is located at one edge of the beta-sandwich and is composed of conserved motifs. Based on the structure, we constructed a docking model with the tRNAs that suggests how tRNase Z may recognize the substrate tRNAs.     

Abstract shapes of RNA

The function of a non-protein-coding RNA is often determined by its structure. Since experimental determination of RNA structure is time-consuming and expensive, its computational prediction is of great interest, and efficient solutions based on thermodynamic parameters are known. Frequently, however, the predicted minimum free energy structures are not the native ones, leading to the necessity of generating suboptimal solutions. While this can be accomplished by a number of programs, the user is often confronted with large outputs of similar structures, although he or she is interested in structures with more fundamental differences, or, in other words, with different abstract shapes. Here, we formalize the concept of abstract shapes and introduce their efficient computation. Each shape of an RNA molecule comprises a class of similar structures and has a representative structure of minimal free energy within the class. Shape analysis is implemented in the program RNAshapes. We applied RNAshapes to the prediction of optimal and suboptimal abstract shapes of several RNAs. For a given energy range, the number of shapes is considerably smaller than the number of structures, and in all cases, the native structures were among the top shape representatives. This demonstrates that the researcher can quickly focus on the structures of interest, without processing up to thousands of near-optimal solutions. We complement this study with a large-scale analysis of the growth behaviour of structure and shape spaces. RNAshapes is available for download and as an online version on the Bielefeld Bioinformatics Server.     

Eukaryotic selenocysteine tRNA has the 9/4 secondary structure

There are two secondary structure models for the eukaryotic selenocysteine (Sec) tRNA(Sec). One model, the 9/4 structure, was experimentally tested and possesses acceptor and T-stems with 9 and 4 bp, respectively [Sturchler et al., 1993; Hubert et al., 1998]. The other one, the 7/5 secondary structure with a bulge in the T-stem, was derived from theoretical calculation [Ioudovitch and Steinberg, 19991. In this report, we show more experimental results supporting the 9/4 secondary structure. Several tRNA(Sec) mutants, whose secondary structure can adopt only the 9/4 structure, were active for serylation and selenylation. Some mutants that cannot base-pair between positions 26 and 44 to provide the 6 bp anticodon stem were still active, inconsistent with the model by Steinberg. We also show that the orientation of the V-arm directly or indirectly influences the selenylation activity, and that the rigid 6 bp D-stem is important. Finally, we conclude that all tRNA(Sec) possess the 13 bp domain II made by the stacking of the colinear AA and T-stems, whether they present the 9/4 structure in Eukarya and Archaea or the 8/5 structure in bacteria.     

RNA sequence analysis using covariance models.

We describe a general approach to several RNA sequence analysis problems using probabilistic models that flexibly describe the secondary structure and primary sequence consensus of an RNA sequence family. We call these models 'covariance models'. A covariance model of tRNA sequences is an extremely sensitive and discriminative tool for searching for additional tRNAs and tRNA-related sequences in sequence databases. A model can be built automatically from an existing sequence alignment. We also describe an algorithm for learning a model and hence a consensus secondary structure from initially unaligned example sequences and no prior structural information. Models trained on unaligned tRNA examples correctly predict tRNA secondary structure and produce high-quality multiple alignments. The approach may be applied to any family of small RNA sequences.     

An efficient algorithm to compute the landscape of locally optimal RNA secondary structures with respect to the Nussinov-Jacobson energy model.

We make a novel contribution to the theory of biopolymer folding, by developing an efficient algorithm to compute the number of locally optimal secondary structures of an RNA molecule, with respect to the Nussinov-Jacobson energy model. Additionally, we apply our algorithm to analyze the folding landscape of selenocysteine insertion sequence (SECIS) elements from A. Bock (personal communication), hammerhead ribozymes from Rfam (Griffiths-Jones et al., 2003), and tRNAs from Sprinzl's database (Sprinzl et al., 1998). It had previously been reported that tRNA has lower minimum free energy than random RNA of the same compositional frequency (Clote et al., 2003; Rivas and Eddy, 2000), although the situation is less clear for mRNA (Seffens and Digby, 1999; Workman and Krogh, 1999; Cohen and Skienna, 2002),(1) which plays no structural role. Applications of our algorithm extend knowledge of the energy landscape differences between naturally occurring and random RNA. Given an RNA molecule a(1), ... , a(n) and an integer k > or = 0, a k-locally optimal secondary structure S is a secondary structure on a(1), ... , a(n) which has k fewer base pairs than the maximum possible number, yet for which no basepairs can be added without violation of the definition of secondary structure (e.g., introducing a pseudoknot). Despite the fact that the number numStr(k) of k-locally optimal structures for a given RNA molecule in general is exponential in n, we present an algorithm running in time O(n (4)) and space O(n (3)), which computes numStr(k) for each k. Structurally important RNA, such as SECIS elements, hammerhead ribozymes, and tRNA, all have a markedly smaller number of k-locally optimal structures than that of random RNA of the same dinucleotide frequency, for small and moderate values of k. This suggests a potential future role of our algorithm as a tool to detect noncoding RNA genes.     

Computing the partition function and sampling for saturated secondary structures of RNA, with respect to the Turner energy model.

An RNA secondary structure is saturated if no base pairs can be added without violating the definition of secondary structure. Here we describe a new algorithm, RNAsat, which for a given RNA sequence a, an integral temperature 0 相似文献   

Comparison of crystal structure interactions and thermodynamics for stabilizing mutations in the Tetrahymena ribozyme

Although general mechanisms of RNA folding and catalysis have been elucidated, little is known about how ribozymes achieve structural stability at high temperature. A previous in vitro evolution experiment identified a small number of mutations that significantly increase the thermostability of the tertiary structure of the Tetrahymena ribozyme. Because we also determined the crystal structure of this thermostable ribozyme, we have for the first time the opportunity to compare the structural interactions and thermodynamic contributions of individual nucleotides in a ribozyme. We investigated the contribution of five mutations to thermostability by using temperature gradient gel electrophoresis. Unlike the case with several well-studied proteins, the effects of individual mutations on thermostability of this RNA were highly context dependent. The three most important mutations for thermostability were actually destabilizing in the wild-type background. A269G and A304G contributed to stability only when present as a pair, consistent with their proximity in the ribozyme structure. In an evolutionary context, this work supports and extends the idea that one advantage of protein enzyme systems over an RNA world is the ability of proteins to accumulate stabilizing single-site mutations, whereas RNA may often require much rarer double mutations to improve the stability of both its tertiary and secondary structures.     

Improved RNA secondary structure prediction by maximizing expected pair accuracy

Free energy minimization has been the most popular method for RNA secondary structure prediction for decades. It is based on a set of empirical free energy change parameters derived from experiments using a nearest-neighbor model. In this study, a program, MaxExpect, that predicts RNA secondary structure by maximizing the expected base-pair accuracy, is reported. This approach was first pioneered in the program CONTRAfold, using pair probabilities predicted with a statistical learning method. Here, a partition function calculation that utilizes the free energy change nearest-neighbor parameters is used to predict base-pair probabilities as well as probabilities of nucleotides being single-stranded. MaxExpect predicts both the optimal structure (having highest expected pair accuracy) and suboptimal structures to serve as alternative hypotheses for the structure. Tested on a large database of different types of RNA, the maximum expected accuracy structures are, on average, of higher accuracy than minimum free energy structures. Accuracy is measured by sensitivity, the percentage of known base pairs correctly predicted, and positive predictive value (PPV), the percentage of predicted pairs that are in the known structure. By favoring double-strandedness or single-strandedness, a higher sensitivity or PPV of prediction can be favored, respectively. Using MaxExpect, the average PPV of optimal structure is improved from 66% to 68% at the same sensitivity level (73%) compared with free energy minimization.     

RNAshapes: an integrated RNA analysis package based on abstract shapes

We introduce RNAshapes, a new software package that integrates three RNA analysis tools based on the abstract shapes approach: the analysis of shape representatives, the calculation of shape probabilities and the consensus shapes approach. This new package is completely reimplemented in C and outruns the original implementations significantly in runtime and memory requirements. Additionally, we added a number of useful features like suboptimal folding with correct dangling energies, structure graph output, shape matching and a sliding window approach.     

Recognition of exon-intron boundaries by the Halobacterium volcanii tRNA intron endonuclease.

The intron-containing tRNA(Trp) precursor from Halobacterium volcanii, like many intron-containing archaebacterial precursor tRNAs, can assume a structure in which the two intron endonuclease cleavage sites are localized in two three-nucleotide loops separated by four base pairs. To investigate the role of this structure in cleavage by the halophilic endonuclease, a series of mutant tRNA(Trp) RNAs were prepared and evaluated as substrates. We find that alterations in this structure result in the loss of cleavage at both 5' and 3' sites. Cleavage of a 35-nucleotide model RNA substrate, containing only these features, demonstrates that sequences and structures present at the exon-intron boundaries are sufficient for recognition and cleavage. We have also examined the mechanism used by the halophilic endonuclease to identify the cleavage sites. Addition of a single base, or a base pair in the anticodon stem above the cleavage sites, does not affect the cleavage site selection. The addition of nucleotides between the two cleavage sites significantly decreases cleavage efficiency and has an effect on the cleavage site selection. These results demonstrate that the halophilic endonuclease requires a defined structure at the exon-intron boundaries and does not identify its cleavage sites by a measurement mechanism like that employed by eukaryotic tRNA intron endonucleases.     

Characterization of ribonuclease P RNAs from thermophilic bacteria.

The catalytic RNA component of bacterial RNase P is responsible for the removal of 5' leader sequences from precursor tRNAs. As part of an on-going phylogenetic comparative characterization of bacterial RNase P, the genes encoding RNase P RNA from the thermophiles Thermotoga maritima, Thermotoga neapolitana, Thermus aquaticus, and a mesophilic relative of the latter, Deinococcus radiodurans, have been cloned and sequenced. RNAs transcribed from these genes in vitro are catalytically active in the absence of other components. Active holoenzymes have been reconstituted from the T.aquaticus and T.maritima RNAs and the protein component of RNase P from Escherichia coli. The RNase P RNAs of T.aquaticus and T.martima, synthesized in vitro, were characterized biochemically and shown to be inherently resistant to thermal disruption. Several features of these RNAs suggest mechanisms contributing to thermostability. The new sequences provide correlations that refine the secondary structure model of bacterial RNase P RNA.     

Asymptotics of RNA shapes.

RNA shapes, introduced by Giegerich et al. (2004), provide a useful classification of the branching complexity for RNA secondary structures. In this paper, we derive an exact value for the asymptotic number of RNA shapes, by relying on an elegant relation between non-ambiguous, context-free grammars, and generating functions. Our results provide a theoretical upper bound on the length of RNA sequences amenable to probabilistic shape analysis (Steffen et al., 2006; Voss et al., 2006), under the assumption that any base can basepair with any other base. Since the relation between context-free grammars and asymptotic enumeration is simple, yet not well-known in bioinformatics, we give a self-contained presentation with illustrative examples. Additionally, we prove a surprising 1-to-1 correspondence between pi-shapes and Motzkin numbers.     

Identification of nuclear encoded precursor tRNAs within the mitochondrion of Trypanosoma brucei.

RNAs that function in mitochondria are typically encoded by the mitochondrial DNA. However, the mitochondrial tRNAs of Trypanosoma brucei are encoded by the nuclear DNA and therefore must be imported into the mitochondrion. It is becoming evident that RNA import into mitochondria is phylogenetically widespread and is essential for cellular processes, but virtually nothing is known about the mechanism of RNA import. We have identified and characterized mitochondrial precursor tRNAs in T. brucei. The identification of mitochondrially located precursor tRNAs clearly indicates that mitochondrial tRNAs are imported as precursors. The mitochondrial precursor tRNAs hybridize to cloned nuclear tRNA genes, label with [alpha-32P]CTP using yeast tRNA nucleotidyltransferase and in isolated mitochondria via an endogenous nucleotidyltransferase-like activity, and are processed to mature tRNAs by Escherichia coli and yeast mitochondrial RNase P. We show that T. brucei mitochondrial extract contains an RNase P activity capable of processing a prokaryotic tRNA precursor as well as the T. brucei tRNA precursors. Precursors for tRNA(Asn) and tRNA(Leu) were detected on Northern blots of mitochondrial RNA, and the 5' ends of these RNAs were characterized by primer extension analysis. The structure of the precursor tRNAs and the significance of nuclear encoded precursor tRNAs within the mitochondrion are discussed.