Discovery of RNA Motifs Using a Computational Pipeline that Allows Insertions in Paired Regions and Filtering of Candidate Sequences
The enormous impact of noncoding RNAs on biology and biotechnology has motivated the development of systematic approaches to their discovery and characterization. Here we present a methodology for reliable detection of genomic ribozymes that centers on pipelined structure-based searches, utilizing two versatile algorithms for structure prediction. RNArobo is a prototype structure-based search package that enables a single search to return all sequences matching a designated motif descriptor, taking into account the possibility of single nucleotide insertions within base-paired regions. These outputs are then filtered through a structure prediction algorithm based on free energy minimization in order to maximize the proportion of catalytically active RNA motifs. This pipeline provides a fast approach to uncovering new catalytic RNAs with known secondary structures and verifying their activity in vitro.
Key wordsRibozymes Pseudoknots RNABOB RNArobo RNAfold
The authors gratefully acknowledge support from VEGA (1/0210/10) to T.V. at the Faculty of Mathematics, Physics and Informatics, Comenius University; and the Pew Charitable Trusts, the NIH (GM094929-01), and the University of California–Irvine to A.L.