LocARNAscan: Incorporating thermodynamic stability in sequence and structure-based RNA homology search

Abstract

BackgroundThe search for distant homologs has become an import issue in genome annotation. A particular difficulty is posed by divergent homologs that have lost recognizable sequence similarity. This same problem also arises in the recognition of novel members of large classes of RNAs such as snoRNAs or microRNAs that consist of families unrelated by common descent. Current homology search tools for structured RNAs are either based entirely on sequence similarity (such as or ) or combine sequence and secondary structure. The most prominent example of the latter class of tools is . Alternatives are descriptor-based methods. In most practical applications published to-date, however, the information contained in covariance models or manually prescribed search patterns is dominated by sequence information. Here we ask two related questions: (1) Is secondary structure alone informative for homology search and the detection of novel members of RNA classes? (2) To what extent is the thermodynamic propensity of the target sequence to fold into the correct secondary structure helpful for this task?ResultsSequence-structure alignment can be used as an alternative search strategy. In this scenario, the query consists of a base pairing probability matrix, which can be derived either from a single sequence or from a multiple alignment representing a set of known representatives. Sequence information can be optionally added to the query. The target sequence is pre-processed to obtain local base pairing probabilities. As a search engine we devised a semi-global scanning variant of ’s algorithm for sequence-structure alignment. The tool is optimized for speed and low memory consumption. In benchmarking experiments on artificial data we observe that the inclusion of thermodynamic stability is helpful, albeit only in a regime of extremely low sequence information in the query. We observe, furthermore, that the sensitivity is bounded in particular by the limited accuracy of the predicted local structures of the target sequence.ConclusionsAlthough we demonstrate that a purely structure-based homology search is feasible in principle, it is unlikely to outperform tools such as in most application scenarios, where a substantial amount of sequence information is typically available. The approach will profit, however, from high throughput methods to determine RNA secondary structure. In transcriptome-wide applications, such methods will provide accurate structure annotations on the target side.AvailabilitySource code of the free software 1.0 and supplementary data are available at http://www.bioinf.uni-leipzig.de/Software/LocARNAscan.

Computational Analysis of Conserved RNA Secondary Structure in Transcriptomes and Genomes

“…More complicated RNA structure analysis problems, including algorithms for de novo conserved structure detection and for sequence/ structure homology search (64,122) also depend on scoring schemes that require inference of an unknown secondary structure. It would be straightforward to extend the approach described here to any of these methods.…”

“…Essentially all that needs to be done is to include an empirical log probability term for the observed probing data at each base i, given the unknown structural context that an algorithm is trying to put i in. If transcriptome-wide structure probing data become readily available in a variety of organisms (37,105), we can imagine using these experimental data systematically across a variety of tasks in computational RNA structure analysis (122).…”

Partially Local Multi-way Alignments

“…It also pertains, for instance, to the concurrent alignments of RNA secondary structures. The Sankoff algorithm [67] also comes with local and semi-global variants, see e.g., [80,81] that could in principle be generalized to partially local N -way problems. Of course, the resulting algorithms will be even more expensive, scaling with O(n 3N ) rather than O(n N ) with sequence length due to the cubic scaling of the RNA folding part.…”

Fast online and index-based algorithms for approximate search of RNA sequence-structure patterns

“…We call this algorithm ScanAlign . We note that during the reviewing process of this manuscript, Will et al [27] submitted and published an algorithm for semi-global sequence-structure alignment of RNAs. As our method, this algorithm saves computation time by reusing entries of dynamic programming tables while scanning the target sequence.…”