MOTIVATION: Although small nucleolar RNAs form an important class of non-coding RNAs, no comprehensive annotation efforts have been undertaken, presumably because the task is complicated by both the large number of distinct small nucleolar RNA families and their relatively rapid pace of sequence evolution. RESULTS: With snoStrip we present an automatic annotation pipeline developed specifically for comparative genomics of small nucleolar RNAs. It makes use of sequence conservation, canonical box motifs as well as secondary structure and predicts putative targets. AVAILABILITY AND IMPLEMENTATION: The snoStrip web service and the download version is available at http://snostrip.bioinf.uni-leipzig.de/

MOTIVATION: Small nucleolar RNAs (snoRNAs) are an abundant class of non-coding RNAs with a wide variety of cellular functions including chemical modification of RNA, telomere maintanance, pre-rRNA processing and regulatory activities in alternative splicing. The main role of box C/D snoRNAs is to determine the targets for 2'-O-ribose methylation, which is important for rRNA maturation and splicing regulation of some mRNAs. The targets are still unknown, however, for many 'orphan' snoRNAs. While a fast and efficient target predictor for box H/ACA snoRNAs is available, no comparable tool exists for box C/D snoRNAs, even though they bind to their targets in a much less complex manner. RESULTS: PLEXY is a dynamic programming algorithm that computes thermodynamically optimal interactions of a box C/D snoRNA with a putative target RNA. Implemented as scanner for large input sequences and equipped with filters on the duplex structure, PLEXY is an efficient and reliable tool for the prediction of box C/D snoRNA target sites. AVAILABILITY: The perl script PLEXY is freely available at http://www.bioinf.uni-leipzig.de/Software/PLEXY.

MOTIVATION: Currently, the best RNA-RNA interaction prediction tools are based on approaches that consider both the inter- and intramolecular interactions of hybridizing RNAs. While accurate, these methods are too slow and memory-hungry to be employed in genome-wide RNA target scans. Alternative methods neglecting intramolecular structures are fast enough for genome-wide applications, but are too inaccurate to be of much practical use. RESULTS: A new approach for RNA-RNA interaction was developed, with a prediction accuracy that is similar to that of algorithms that explicitly consider intramolecular structures, but running at least three orders of magnitude faster than RNAup. This is achieved by using a combination of precomputed accessibility profiles with an approximate energy model. This approach is implemented in the new version of RNAplex. The software also provides a variant using multiple sequences alignments as input, resulting in a further increase in specificity. AVAILABILITY: RNAplex is available at www.bioinf.uni-leipzig.de/Software/RNAplex.

MOTIVATION: Small nucleolar RNAs are an abundant class of non-coding RNAs that guide chemical modifications of rRNAs, snRNAs and some mRNAs. In the case of many 'orphan' snoRNAs, the targeted nucleotides remain unknown, however. The box H/ACA subclass determines uridine residues that are to be converted into pseudouridines via specific complementary binding in a well-defined secondary structure configuration that is outside the scope of common RNA (co-)folding algorithms. RESULTS: RNAsnoop implements a dynamic programming algorithm that computes thermodynamically optimal H/ACA-RNA interactions in an efficient scanning variant. Complemented by an support vector machine (SVM)-based machine learning approach to distinguish true binding sites from spurious solutions and a system to evaluate comparative information, it presents an efficient and reliable tool for the prediction of H/ACA snoRNA target sites. We apply RNAsnoop to identify the snoRNAs that are responsible for several of the remaining 'orphan' pseudouridine modifications in human rRNAs, and we assign a target to one of the five orphan H/ACA snoRNAs in Drosophila. AVAILABILITY: The C source code of RNAsnoop is freely available at http://www.tbi.univie.ac.at/ -htafer/RNAsnoop

MOTIVATION: Regulatory RNAs often unfold their action via RNA-RNA interaction. Transcriptional gene silencing by means of siRNAs and miRNA as well as snoRNA directed RNA editing rely on this mechanism. Additionally ncRNA regulation in bacteria is mainly based upon RNA duplex formation. Finding putative target sites for newly discovered ncRNAs is a lengthy task as tools for cofolding RNA molecules like RNAcofold and RNAup are too slow for genome-wide search. Tools like RNAhybrid that neglects intramolecular interactions have runtimes proportional to O(m x n), albeit with a large prefactor. Still in many cases the need for even faster methods exists. RESULTS: We present a new program, RNAplex, especially designed to quickly find possible hybridization sites for a query RNA in large RNA databases. RNAplex uses a slightly different energy model which reduces the computational time by a factor 10-27 compared to RNAhybrid. In addition a length penalty allows to focus the target search on short highly stable interactions. AVAILABILITY: RNAplex can be downloaded at http://www.tbi.univie.ac.at/~htafer/ SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: Reliable prediction of RNA-RNA binding energies is crucial, e.g. for the understanding on RNAi, microRNA-mRNA binding and antisense interactions. The thermodynamics of such RNA-RNA interactions can be understood as the sum of two energy contributions: (1) the energy necessary to 'open' the binding site and (2) the energy gained from hybridization. METHODS: We present an extension of the standard partition function approach to RNA secondary structures that computes the probabilities Pu[i, j] that a sequence interval [i, j] is unpaired. RESULTS: Comparison with experimental data shows that Pu[i, j] can be applied as a significant determinant of local target site accessibility for RNA interference (RNAi). Furthermore, these quantities can be used to rigorously determine binding free energies of short oligomers to large mRNA targets. The resource consumption is comparable with a single partition function computation for the large target molecule. We can show that RNAi efficiency correlates well with the binding energies of siRNAs to their respective mRNA target. AVAILABILITY: RNAup will be distributed as part of the Vienna RNA Package, www.tbi.univie.ac.at/~ivo/RNA/