Predicting common foldings of homologous RNAs

GHOST-NOT and GHOST-YES: Two programs for generating high-speed biosensors with randomized oligonucleotide binding sites with NOT or YES Boolean logic functions based on experimentally validated algorithms

High-speed allosteric hammerhead ribozymes can be engineered to distinguish well between a perfectly matching effector and the nucleic acid sequences with a few mismatches under physiologically relevant conditions. Such ribozymes can be designed to control the expression of exogenous mRNAs and can be used to develop new gene therapies, including anticancer treatments. The in vivo selection of such ribozymes is a complicated and lengthy procedure with no guarantee of success. Thus, in silico selection of high-speed ribozymes can be employed using secondary RNA structure computation based on the partition function of the RNA folding in combination with random search algorithms. This approach has already been proven very accurate in designing allosteric hammerhead ribozymes. Herein, we present two programs for the computational design of allosteric ribozymes sensing randomized oligonucleotides based on the extended version of the hammerhead ribozyme. A Generator for High-speed Oligonucleotide Sensing allosteric ribozymes with NOT logic function (GHOST-NOT) and a Generator for High-speed Oligonucleotide Sensing allosteric ribozymes with YES logic function (GHOST-YES) for computational design of high-speed allosteric ribozymes are described. The allosteric hammerhead ribozymes had a high self-cleavage rate of about 1.8 per minute and were very selective in sensing an effector sequence.

Use of ribozymes in cellular aging research

Ribozymes are naturally-occurring catalytic RNAs from the viroid world and are being engineered in the laboratory to perform sequence-specific cleavage of a desired mRNA target. Since their Nobel Prize-winning discovery, there has been considerable interest in the utility of ribozymes as gene therapeutic agents to silence disease-causing genes. This technology is not perfect, but extensive efforts to improve upon natural design of ribozymes have enabled these RNA molecules to perform various tasks. In this chapter, we highlight the construction of two types of ribozymes: conventional and hybrid hammerhead ribozymes. The hybrid ribozyme described here is an improved version of the basic hammerhead motif with the following features: (a) the use of the RNA polymerase III (polIII) tRNAVal promoter to achieve a high level of transcription, (b) 5' linkage to the cloverleaf-shaped tRNAVal to enhance intracellular stability and cytoplasmic transport, and (c) a 3' end poly-(A) tail to act as a "molecular anchor" for endogenous RNA helicases endowing the ribozyme ability to disentangle higher-order structures of the target mRNA. Randomized hybrid ribozyme libraries have been used successfully for revelation of gene functions involved in metastasis, invasion, differentiation, apoptosis, endoplasmic reticulum stress and may be extended to gene functions involved in innate or induced cellular senescence of human cells.

Predicted Secondary Structure for 28S and 18S rRNA from Ichneumonoidea (Insecta: Hymenoptera: Apocrita): Impact on Sequence Alignment and Phylogeny Estimation

We utilize the secondary structural properties of the 28S rRNA D2-D10 expansion segments to hypothesize a multiple sequence alignment for major lineages of the hymenopteran superfamily Ichneumonoidea (Braconidae, Ichneumonidae). The alignment consists of 290 sequences (originally analyzed in Belshaw and Quicke, Syst Biol 51:450-477, 2002) and provides the first global alignment template for this diverse group of insects. Predicted structures for these expansion segments as well as for over half of the 18S rRNA are given, with highly variable regions characterized and isolated within conserved structures. We demonstrate several pitfalls of optimization alignment and illustrate how these are potentially addressed with structure-based alignments. Our global alignment is presented online at (http://hymenoptera.tamu.edu/rna) with summary statistics, such as basepair frequency tables, along with novel tools for parsing structure-based alignments into input files for most commonly used phylogenetic software. These resources will be valuable for hymenopteran systematists, as well as researchers utilizing rRNA sequences for phylogeny estimation in any taxon. We explore the phylogenetic utility of our structure-based alignment by examining a subset of the data under a variety of optimality criteria using results from Belshaw and Quicke (2002) as a benchmark.

Prediction of consensus RNA secondary structures including pseudoknots

Most functional RNA molecules have characteristic structures that are highly conserved in evolution. Many of them contain pseudoknots. Here, we present a method for computing the consensus structures including pseudoknots based on alignments of a few sequences. The algorithm combines thermodynamic and covariation information to assign scores to all possible base pairs, the base pairs are chosen with the help of the maximum weighted matching algorithm. We applied our algorithm to a number of different types of RNA known to contain pseudoknots. All pseudoknots were predicted correctly and more than 85 percent of the base pairs were identified.

Distinct RNA motifs are important for coactivation of steroid hormone receptors by steroid receptor RNA activator (SRA)

Steroid receptor RNA activator (SRA) is an RNA transcript that functions as a eukaryotic transcriptional coactivator for steroid hormone receptors. We report here the isolation and functional characterization of distinct RNA substructures within the SRA molecule that constitute its coactivation function. We used comparative sequence analysis and free energy calculations to systematically study SRA RNA subdomains for identification of structured regions and base pairings, and we used site-directed mutagenesis to assess their functional consequences. Together with genetic deletion analysis, this approach identified six RNA motifs in SRA important for coactivation. Because all nucleotide changes in the mutants that disrupted SRA function were silent mutations presumed not to alter deduced encoded amino acid sequence, our analysis provides strong evidence that SRA-mediated coactivation is executed by distinct RNA motifs and not by an encoded protein.

Secondary structure prediction for aligned RNA sequences

Most functional RNA molecules have characteristic secondary structures that are highly conserved in evolution. Here we present a method for computing the consensus structure of a set aligned RNA sequences taking into account both thermodynamic stability and sequence covariation. Comparison with phylogenetic structures of rRNAs shows that a reliability of prediction of more than 80% is achieved for only five related sequences. As an application we show that the Early Noduline mRNA contains significant secondary structure that is supported by sequence covariation.

Conserved RNA secondary structures in Picornaviridae genomes

The family Picornaviridae contains important pathogens including, for example, hepatitis A virus and foot-and-mouth disease virus. The genome of these viruses is a single messenger-active (+)-RNA of 7200-8500 nt. Besides coding for the viral proteins, it also contains functionally important RNA secondary structures, among them an internal ribosomal entry site (IRES) region towards the 5'-end. This contribution provides a comprehensive computational survey of the complete genomic RNAs and a detailed comparative analysis of the conserved structural elements in seven of the currently nine genera in the family PICORNAVIRIDAE: Compared with previous studies we find: (i) that only smaller sections of the IRES region than previously reported are conserved at single base-pair resolution and (ii) that there is a number of significant structural elements in the coding region. Furthermore, we identify potential cis-acting replication elements in four genera where this feature has not been reported so far.

Phenotypic characterization of three phylogenetically conserved stem-loop motifs in the mengovirus 3' untranslated region

An alignment of cardiovirus sequences led to the prediction of three conserved stem-loops in the 3' untranslated region (UTR) of mengovirus. Deletions of each stem were engineered in mengovirus cDNAs and also in mengovirus replicons, in which part of the viral capsid sequences were replaced with the firefly luciferase gene. The effect of deletion on RNA infectivity and plaque phenotype was evaluated after transfection of viral transcripts into HeLa cells or by luciferase assays of cellular extracts after transfection with RNA replicons. Stem I (mengovirus bases 7666 to 7687) was found to be dispensable for viral growth or exponential luciferase expression. Deletion of stem III (bases 7711 to 7721) was lethal to the virus, and the replicons were incapable of RNA synthesis. Deletion of stem II (DeltaII; bases 7692 to 7705) produced an intermediate phenotype, in that replicons had marginal RNA synthesis activity but transfection with genomic RNA usually failed to produce plaques after normal incubation times (31 h, 37 degrees C). In a few of the DeltaII transfections, however, plaques were observed after long incubation, especially if the cells received large amounts of RNA (3 microg per 3 x 10(6) cells). Viruses from two DeltaII-derived plaques were isolated and amplified. Their RNAs were converted into cDNA, sequenced, and mapped for genotype. Each maintained the DeltaII deletion and, in addition, had one or two reversion mutations, which were characterized by reverse genetics as responsible for the phenotypes. One reversion caused an amino acid change in the polymerase (3D(pol)), and the other was localized to the 3' UTR, upstream of stem I.

ConStruct: a tool for thermodynamic controlled prediction of conserved secondary structure

A tool for prediction of conserved secondary structure of a set of homologous single-stranded RNAs is presented. For each RNA of the set the structure distribution is calculated and stored in a base pair probability matrix. Gaps, resulting from a multiple sequence alignment of the RNA set, are introduced into the individual probability matrices. These 'aligned' probability matrices are summed up to give a consensus probability matrix emphasizing the conserved structural elements of the RNA set. Because the multiple sequence alignment is independent of any structural constraints, such an alignment may result in introduction of gaps into the homologous probability matrices that disrupt a common consensus structure. By use of its graphical user interface the presented tool allows the removal of such misalignments, which are easily recognized, from the individual probability matrices by optimizing the sequence alignment with respect to a structural alignment. From the consensus probability matrix a consensus structure is extracted, which is viewable in three different graphical representations. The functionality of the tool is demonstrated using a small set of U7 RNAs, which are involved in 3'-end processing of histone mRNA precursors. Supplementary Material lists further results obtained. Advantages and drawbacks of the tool are discussed in comparison to several other algorithms.

Prediction of sequentially optimal RNA secondary structures

A rigorous mathematical modeling of the RNA sequential folding process during transcription is proposed. It is based, at each transcription step, on a homogeneous markovian jump process, the state space of which is the set of structures constructible on the part of the RNA already transcribed. A theoretical formula permitting the computation of the structures probabilities at the end of the RNA transcription is derived. Successive approximations, aimed at reducing the size of the state space, permit the design of a prediction algorithm. The algorithm is tested on some structural RNAs (tRNA, 5S, 16S, hammerhead, ...), results are discussed and possible improvements are proposed.

Stochastic context-free grammars for tRNA modeling

Stochastic context-free grammars (SCFGs) are applied to the problems of folding, aligning and modeling families of tRNA sequences. SCFGs capture the sequences' common primary and secondary structure and generalize the hidden Markov models (HMMs) used in related work on protein and DNA. Results show that after having been trained on as few as 20 tRNA sequences from only two tRNA subfamilies (mitochondrial and cytoplasmic), the model can discern general tRNA from similar-length RNA sequences of other kinds, can find secondary structure of new tRNA sequences, and can produce multiple alignments of large sets of tRNA sequences. Our results suggest potential improvements in the alignments of the D- and T-domains in some mitochondrial tRNAs that cannot be fit into the canonical secondary structure.

Neural computing in discovering RNA interactions

High-order RNA structures are involved in regulating many biological processes; various algorithms have been designed to predict them. Experimental methods to probe such structures and to decipher the results are tedious. Artificial intelligence and the neural network approach can support the process of discovering RNA structures. Secondary structures of RNA molecules are probed by autoradiographing gels, separating end-labeled fragments generated by base-specific RNases. This process is performed in both conditions, denaturing (for sequencing purposes) and native. The resultant autoradiograms are scanned using line-detection techniques to identify the fragments by comparing the lines with those obtained by 'alkaline ladders'. The identified paired bases are treated by either one of two methods to find the foldings which are consistent with the RNases' 'cutting' rules. One exploits the maximum independent set algorithm; the other, the planarization algorithm. They require, respectively, n and n2 processing elements, where n is the number of base pairs. The state of the system usually converges to the near-optimum solution within about 500 iteration steps, where each processing element implements the McCulloch-Pitts binary neuron. Our simulator, based on the proposed algorithm, discovered a new structure in a sequence of 38 bases, which is more stable than that formerly proposed.

Analysis of the gene encoding the RNA subunit of ribonuclease P from T. thermophilus HB8

The gene for the RNA subunit of ribonuclease P from the extreme thermophilic eubacterium T. thermophilus HB8 was cloned using oligonucleotide probes complementary to conserved regions of RNase P RNA subunits from proteobacteria. The monocistronic gene and its flanking regions were sequenced. The gene is enclosed by a promoter and a rho-independent terminator. Nuclease S1 protection analyses showed that the primary transcript is identical with the mature RNA, i.e. no processing events are involved. The stem and loop structure of the terminator remains part of the mature molecule. In vitro transcription of the cloned gene with purified RNA polymerase from T. thermophilus yields the same RNA product as in vivo, indicating that no other components except RNA polymerase are involved in the synthesis of the RNA. RNase P RNA from T. thermophilus cleaved a pre-tRNA(Tyr) from E. coli with highest efficiency between 55 degrees C and 65 degrees C. The T. thermophilus RNA, which has a G-C content of 86% in helical regions, displays several structural idiosyncrasies, although its secondary structure is similar to that of proteobacteria. Numerous invariable nucleotides in the structural core of eubacterial RNase P RNAs are also conserved in the RNA from the extreme thermophilic eubacterium.