Gero Doose1, Dirk Metzler. 1. Department of Biology, LMU Biocenter, Ludwig-Maximilians-Universität München, Planegg-Martinsried, Germany. gero@bioinf.uni-leipzig.de
Abstract
MOTIVATION: Today many non-coding RNAs are known to play an active role in various important biological processes. Since RNA's functionality is correlated with specific structural motifs that are often conserved in phylogenetically related molecules, computational prediction of RNA structure should ideally be based on a set of homologous primary structures. But many available RNA secondary structure prediction programs that use sequence alignments do not consider pseudoknots or their estimations consist on a single structure without information on uncertainty. RESULTS: In this article we present a method that takes advantage of the evolutionary history of a group of aligned RNA sequences for sampling consensus secondary structures, including pseudoknots, according to their approximate posterior probability. We investigate the benefit of using evolutionary history and demonstrate the competitiveness of our method compared with similar methods based on RNase P RNA sequences and simulated data. AVAILABILITY: PhyloQFold, a C + + implementation of our method, is freely available from http://evol.bio.lmu.de/_statgen/software/phyloqfold/.
MOTIVATION: Today many non-coding RNAs are known to play an active role in various important biological processes. Since RNA's functionality is correlated with specific structural motifs that are often conserved in phylogenetically related molecules, computational prediction of RNA structure should ideally be based on a set of homologous primary structures. But many available RNA secondary structure prediction programs that use sequence alignments do not consider pseudoknots or their estimations consist on a single structure without information on uncertainty. RESULTS: In this article we present a method that takes advantage of the evolutionary history of a group of aligned RNA sequences for sampling consensus secondary structures, including pseudoknots, according to their approximate posterior probability. We investigate the benefit of using evolutionary history and demonstrate the competitiveness of our method compared with similar methods based on RNase P RNA sequences and simulated data. AVAILABILITY: PhyloQFold, a C + + implementation of our method, is freely available from http://evol.bio.lmu.de/_statgen/software/phyloqfold/.