Nucleotide sequences of three poriferan 5 S ribosomal RNAs.

We have determined the nucleotide sequences of 5 S ribosomal RNAs isolated from the sponges Halichondria panicea, Hymeniacidon sanguinea, and Haliclona oculata. The structures can be fitted in a universal five-helix secondary structure model (De Wachter, Chen and Vandenberghe (1982) Biochimie 64, 311-329) applicable to all 5 S RNAs hitherto sequenced. The base pairing scheme proves to be extremely conserved throughout the metazoan kingdom, yet four slightly different variants of the model may be distinguished among the 5 S RNAs from the seven animal phyla investigated until now.     

Sequences of the 5S rRNAs of the thermo-acidophilic archaebacterium Sulfolobus solfataricus (Caldariella acidophila) and the thermophilic eubacteria Bacillus acidocaldarius and Thermus aquaticus.

We have determined the nucleotide sequences of the 5 S rRNAs of three thermophilic bacteria: the archaebacterium Sulfolobus solfataricus, also named Caldariella acidophila, and the eubacteria Bacillus acidocaldarius and Thermus aquaticus. A 5 S RNA sequence for the latter species had already been published, but it looked suspect on the basis of its alignment with other 5 S RNA sequences and its base-pairing pattern. The corrected sequence aligns much better and fits in the universal five helix secondary structure model, as do the sequences for the two other examined species. The sequence found for Sulfolobus solfataricus is identical to that determined by others for Sulfolobus acidocaldarius. The secondary structure of its 5 S RNA shows a number of exceptional features which distinguish it not only from eubacterial and eukaryotic 5 S RNAs, but also from the limited number of archaebacterial 5 S RNA structures hitherto published. The free energy change of secondary structure formation is large in the three examined 5 S RNAs.     

Nucleotide sequence, secondary structure and evolution of the 5S ribosomal RNA from five bacterial species

The nucleotide sequences of the 5S ribosomal RNAs of the bacteria Agrobacterium tumefaciens, Alcaligenes faecalis, Pseudomonas cepacia, Aquaspirillum serpens and Acinetobacter calcoaceticus have been determined. The sequences fit in a generally accepted model for 5S RNA secondary structure. However, a closer comparative examination of these and other bacterial 5S RNA primary structures reveals the potential of additional base pairing and of multiple equilibria between a set of slightly different alternative secondary structures in one area of the molecule. The phylogenetic position of the examined bacteria is derived from a 5S RNA sequence alignment by a clustering method and compared with the position derived on the basis of 16S ribosomal RNA oligonucleotide catalogs.     

STRAL: progressive alignment of non-coding RNA using base pairing probability vectors in quadratic time

MOTIVATION: Alignment of RNA has a wide range of applications, for example in phylogeny inference, consensus structure prediction and homology searches. Yet aligning structural or non-coding RNAs (ncRNAs) correctly is notoriously difficult as these RNA sequences may evolve by compensatory mutations, which maintain base pairing but destroy sequence homology. Ideally, alignment programs would take RNA structure into account. The Sankoff algorithm for the simultaneous solution of RNA structure prediction and RNA sequence alignment was proposed 20 years ago but suffers from its exponential complexity. A number of programs implement lightweight versions of the Sankoff algorithm by restricting its application to a limited type of structure and/or only pairwise alignment. Thus, despite recent advances, the proper alignment of multiple structural RNA sequences remains a problem. RESULTS: Here we present StrAl, a heuristic method for alignment of ncRNA that reduces sequence-structure alignment to a two-dimensional problem similar to standard multiple sequence alignment. The scoring function takes into account sequence similarity as well as up- and downstream pairing probability. To test the robustness of the algorithm and the performance of the program, we scored alignments produced by StrAl against a large set of published reference alignments. The quality of alignments predicted by StrAl is far better than that obtained by standard sequence alignment programs, especially when sequence homologies drop below approximately 65%; nevertheless StrAl's runtime is comparable to that of ClustalW.     

The nucleotide sequences of the 5 S rRNAs of seven molds and a yeast and their use in studying ascomycete phylogeny.

The sequences of the 5 S rRNAs isolated from 8 ascomycete species belonging to the genera Aspergillus, Penicillium, Acremonium and Candida are reported. Two of the examined strains each yielded a mixture of 3 slightly different 5 S RNAs, which were individually sequenced after fractionation. A previously published sequence for Aspergillus nidulans 5 S RNA was found to contain errors. Reconstruction of an evolutionary tree based on 5 S RNA sequences showed that the 16 presently examined ascomycetes form three clusters. The same threefold partition can be observed in the secondary structure pattern, each cluster showing a slightly different variant of the general 5-helix model for 5 S rRNA (De Wachter, Chen and Vandenberghe (1982) Biochimie 64, 311-329), and different sets of secondary structure equilibrium forms in helices C and E of the aforementioned model.     

Variable base pairing in a helix of eubacterial 5 S ribosomal RNA points to the existence of a conformational switch

A survey of 160 published sequences of eubacterial 5 S rRNAs shows that there exists structural variability in one of the helices of the generally accepted secondary structure model. Four structural variants are found, which differ with respect to the position and the number of bulges present. Most eubacterial 5 S RNAs fit into at least two of these conformations. A reaction scheme connecting the four observed conformations by changes in the base pairing scheme is proposed. Each of the known 5 S RNA sequences fits into conformations interconvertible by the proposed reactions.     

Model-Free RNA Sequence and Structure Alignment Informed by SHAPE Probing Reveals a Conserved Alternate Secondary Structure for 16S rRNA

Discovery and characterization of functional RNA structures remains challenging due to deficiencies in de novo secondary structure modeling. Here we describe a dynamic programming approach for model-free sequence comparison that incorporates high-throughput chemical probing data. Based on SHAPE probing data alone, ribosomal RNAs (rRNAs) from three diverse organisms – the eubacteria E. coli and C. difficile and the archeon H. volcanii – could be aligned with accuracies comparable to alignments based on actual sequence identity. When both base sequence identity and chemical probing reactivities were considered together, accuracies improved further. Derived sequence alignments and chemical probing data from protein-free RNAs were then used as pseudo-free energy constraints to model consensus secondary structures for the 16S and 23S rRNAs. There are critical differences between these experimentally-informed models and currently accepted models, including in the functionally important neck and decoding regions of the 16S rRNA. We infer that the 16S rRNA has evolved to undergo large-scale changes in base pairing as part of ribosome function. As high-quality RNA probing data become widely available, structurally-informed sequence alignment will become broadly useful for de novo motif and function discovery.     

Molecular evolution of 5S RNA

Summary Based on the comparative analyses of the primary structure of 5S RNAs from 19 organisms, a secondary structure model of 5S RNA is proposed. 5S RNA has essentially the same structure among all prokaryotic species. The same is true for eukaryotic 5S RNAs. Prokaryotic and eukaryotic 5S RNAs are also quite similar to each other, except for a difference in a specific region.By comparing the nucleotide alignment from the juxtaposed 5S RNA secondary structures, a phylogenic tree of nineteen organisms was constructed. The time of divergence between prokaryotes and eukaryotes was estimated to be 2.5×10⁹ years ago (minimum estimate: 2.1×10⁹).     

Nucleotide sequence and structure of cytoplasmic 5S RNA and 5.8S RNA of Chlamydomonas reinhardii.

Three small RNAs of the cytoplasmic 8OS ribosomes of the green unicellular alga Chlamydomonas reinhardii have been sequenced. They include two species of ribosomal 5S RNA, a major and a minor one of 122 and 121 nucleotides respectively, which differ from each other by 17 bases, and also the ribosomal 5.8S RNA of 156 nucleotides. Novel structural features can be recognized in the 5S RNAs of C. reinhardii by a comparison with published 5S RNA sequences. In addition the secondary structure of these small RNA molecules has been examined using a newly developed method based on differential nuclease susceptibility.     

裸子植物5S rRNA基因序列变异及二级结构特征

在高等植物中,5SrRNA基因一级结构是高度保守的,二级结构也相当一致。通过比较18种裸子植物5SrRNA基因序列和二级结构变异,发现55％的核苷酸位点是可变的,这种变异有68％发生在干区（双链区）,其中一些变异,如双链的互补性核苷酸替代,GU配对等能够维系5SrRNA二级结构的稳定性。环区相对保守,这与5SrRNA三级结构折叠或在转录翻译过程中蛋白质、RNA的结合相关。另外,首次报道了松属环E区核苷酸的变异性,这可能与其他区域的变异一样,是假基因造成的结果。5SrRNA基因信息可反映大分类群的系统进化关系,但由于基因长度短,信息量小,其在近缘种系统分类的应用受到限制。     

Pair hidden Markov models on tree structures

MOTIVATION: Computationally identifying non-coding RNA regions on the genome has much scope for investigation and is essentially harder than gene-finding problems for protein-coding regions. Since comparative sequence analysis is effective for non-coding RNA detection, efficient computational methods are expected for structural alignments of RNA sequences. On the other hand, Hidden Markov Models (HMMs) have played important roles for modeling and analysing biological sequences. Especially, the concept of Pair HMMs (PHMMs) have been examined extensively as mathematical models for alignments and gene finding. RESULTS: We propose the pair HMMs on tree structures (PHMMTSs), which is an extension of PHMMs defined on alignments of trees and provides a unifying framework and an automata-theoretic model for alignments of trees, structural alignments and pair stochastic context-free grammars. By structural alignment, we mean a pairwise alignment to align an unfolded RNA sequence into an RNA sequence of known secondary structure. First, we extend the notion of PHMMs defined on alignments of 'linear' sequences to pair stochastic tree automata, called PHMMTSs, defined on alignments of 'trees'. The PHMMTSs provide various types of alignments of trees such as affine-gap alignments of trees and an automata-theoretic model for alignment of trees. Second, based on the observation that a secondary structure of RNA can be represented by a tree, we apply PHMMTSs to the problem of structural alignments of RNAs. We modify PHMMTSs so that it takes as input a pair of a 'linear' sequence and a 'tree' representing a secondary structure of RNA to produce a structural alignment. Further, the PHMMTSs with input of a pair of two linear sequences is mathematically equal to the pair stochastic context-free grammars. We demonstrate some computational experiments to show the effectiveness of our method for structural alignments, and discuss a complexity issue of PHMMTSs.     

Sequences of three molluscan 5 S ribosomal RNAs confirm the validity of a dynamic secondary structure model.

The collection of known 5 S rRNA primary structures is enriched with the sequences from three mollusca, the snails Helix pomatia and Arion rufus, and the mussel Mytilus edulis. The three sequences can be fitted in a five-helix secondary structure model previously shown (De Wachter et al. (1982) Biochimie 64, 311-329) to apply to all 5 S RNAs regardless of their origin. One of the helices in this model can undergo a bulge-internal loop transition. Within the metazoan kingdom, the dimensions of each helix and loop are rigidly conserved, except for one helix which can comprise either 6 or 7 base pairs.     

PARTS: probabilistic alignment for RNA joinT secondary structure prediction

A novel method is presented for joint prediction of alignment and common secondary structures of two RNA sequences. The joint consideration of common secondary structures and alignment is accomplished by structural alignment over a search space defined by the newly introduced motif called matched helical regions. The matched helical region formulation generalizes previously employed constraints for structural alignment and thereby better accommodates the structural variability within RNA families. A probabilistic model based on pseudo free energies obtained from precomputed base pairing and alignment probabilities is utilized for scoring structural alignments. Maximum a posteriori (MAP) common secondary structures, sequence alignment and joint posterior probabilities of base pairing are obtained from the model via a dynamic programming algorithm called PARTS. The advantage of the more general structural alignment of PARTS is seen in secondary structure predictions for the RNase P family. For this family, the PARTS MAP predictions of secondary structures and alignment perform significantly better than prior methods that utilize a more restrictive structural alignment model. For the tRNA and 5S rRNA families, the richer structural alignment model of PARTS does not offer a benefit and the method therefore performs comparably with existing alternatives. For all RNA families studied, the posterior probability estimates obtained from PARTS offer an improvement over posterior probability estimates from a single sequence prediction. When considering the base pairings predicted over a threshold value of confidence, the combination of sensitivity and positive predictive value is superior for PARTS than for the single sequence prediction. PARTS source code is available for download under the GNU public license at http://rna.urmc.rochester.edu.     

Alignment of RNA base pairing probability matrices

MOTIVATION: Many classes of functional RNA molecules are characterized by highly conserved secondary structures but little detectable sequence similarity. Reliable multiple alignments can therefore be constructed only when the shared structural features are taken into account. Since multiple alignments are used as input for many subsequent methods of data analysis, structure-based alignments are an indispensable necessity in RNA bioinformatics. RESULTS: We present here a method to compute pairwise and progressive multiple alignments from the direct comparison of base pairing probability matrices. Instead of attempting to solve the folding and the alignment problem simultaneously as in the classical Sankoff's algorithm, we use McCaskill's approach to compute base pairing probability matrices which effectively incorporate the information on the energetics of each sequences. A novel, simplified variant of Sankoff's algorithms can then be employed to extract the maximum-weight common secondary structure and an associated alignment. AVAILABILITY: The programs pmcomp and pmmulti described in this contribution are implemented in Perl and can be downloaded together with the example datasets from http://www.tbi.univie.ac.at/RNA/PMcomp/. A web server is available at http://rna.tbi.univie.ac.at/cgi-bin/pmcgi.pl     

The 5S ribosomal RNA of Euglena gracilis cytoplasmic ribosomes is closely homologous to the 5S RNA of the trypanosomatid protozoa.

The complete nucleotide sequence of the major species of cytoplasmic 5S ribosomal RNA of Euglena gracilis has been determined. The sequence is: 5' GGCGUACGGCCAUACUACCGGGAAUACACCUGAACCCGUUCGAUUUCAGAAGUUAAGCCUGGUCAGGCCCAGUUAGUAC UGAGGUGGGCGACCACUUGGGAACACUGGGUGCUGUACGCUUOH3'. This sequence can be fitted to the secondary structural models recently proposed for eukaryotic 5S ribosomal RNAs (1,2). Several properties of the Euglena 5S RNA reveal a close phylogenetic relationship between this organism and the protozoa. Large stretches of nucleotide sequences in predominantly single-stranded regions of the RNA are homologous to that of the trypanosomatid protozoan Crithidia fasticulata. There is less homology when compared to the RNAs of the green alga Chlorella or to the RNAs of the higher plants. The sequence AGAAC near position 40 that is common to plant 5S RNAs is CGAUU in both Euglena and Crithidia. The Euglena 5S RNA has secondary structural features at positions 79-99 similar to that of the protozoa and different from that of the plants. The conclusions drawn from comparative studies of cytochrome c structures which indicate a close phylogenetic relatedness between Euglena and the trypanosomatid protozoa are supported by the comparative data with 5S ribosomal RNAs.     

Two 5S genes are expressed in chicken somatic cells.

Two 5S RNA species were detected in chicken cells. 5S I RNA has the nucleotide sequence of chicken 5S RNA previously published by Brownlee et al. (1) and 5S II RNA differs from it by 10 mutations. The secondary structure of both species is compatible with that proposed for other eukaryotic 5S RNAs. 5S II RNA represents 50-60% of 5S I RNA. Both species were found in total chicken liver and brain and were present in polysomes in the same relative proportions. Only one 5S RNA species could be detected in rat liver and HeLa cells. Chicken is the first vertebrate described so far in which two 5S RNA genes are expressed in somatic cells.     

5S RNA structure and interaction with transcription factor A. 1. Ribonuclease probe of the structure of 5S RNA from Xenopus laevis oocytes

The structure of Xenopus laevis oocyte (Xlo) 5S ribosomal RNA has been probed with single-strand-specific ribonucleases T1, T2, and A with double-strand-specific ribonuclease V1 from cobra venom. The digestion of 5'- or 3'-labeled renatured 5S RNA samples followed by gel purification of the digested samples allowed the determination of primary cleavage sites. Results of these ribonuclease digestions provide support for the generalized 5S RNA secondary structural model derived from comparative sequence analysis. However, three putative single-stranded regions of the molecule exhibited unexpected V1 cuts, found at C36, U73, U76, and U102. These V1 cuts reflect additional secondary structural features of the RNA including A.G base pairs and support the extended base pairing in the stem containing helices IV and V which was proposed by Stahl et al. [Stahl, D. A., Luehrsen, K. R., Woese, C. R., & Pace, N. R. (1981) Nucleic Acids Res. 9, 6129-6137]. A conserved structure for helix V having a common unpaired uracil residue at Xlo position 84 is proposed for all eukaryotic 5S RNAs. Our results are compared with nuclease probes of other 5S RNAs.     

Highly conserved 5S ribosomal RNA sequences in four rust fungi and atypical 5S rRNA secondary structure in Microstroma juglandis.

The 5S ribosomal RNA nucleotide sequences of five basidiomycetous fungi, Coleosporium tussilaginis , Gymnosporangium clavariaeforme , Puccinia poarum , Endophyllum sempervivi and Microstroma juglandis were determined. Despite high differentiation in their host spectra the four rust species are highly conserved with respect to their 5S rRna sequences, which fit with the basidiomycete cluster 5 described by Walker and Doolittle (1). The sequences obtained from the first three rust fungi were proven to be identical while the sequence from Endophyllum sempervivi showed two base substitutions compared with the other rust fungi. The Microstroma juglandis 5S rRNA sequence differs from all other basidiomycete 5S rRNA sequences published so far in respect to its secondary structure which shows an atypical 'CCA' loop in helix D, but it reveals typical basidiomycetous signature nucleotides. Therefore Microstroma juglandis represents a cluster of its own within the Basidiomycetes. A dendrogram was constructed based on Kimura's "Neutral Theory of Molecular Evolution".