Constructing Structural Alignment of RNA Sequences by Detecting and Assessing Conserved Stems

Abstract

The comparative methods for predicting RNA secondary structure can be facilitated by taking structural alignments of homologous sequences as input. However, it is very difficult to construct a well structural alignment of RNA sequences without knowing the secondary structures. In this paper, we present a stem-based method for constructing structural alignment of RNA sequences with unknown structures. The method can be summarized by: 1) we detect possible stems in the RNA sequence using the so-called position matrix with which some possibly paired positions are uncovered; 2) we detect conserved stems across multiple sequences by multiplying the position matrices; 3) we assess the conserved stems using the Signal-to-Noise and the new SCFG model; 4) we construct structural alignment of RNA sequences by incorporating conserved stems with Clustal W which is a popular program for multiple sequence alignment. We tested our method on data sets composed of known structural alignments which are downloaded from the Rfam database. The accuracy, measured as sensitivity and true positive rate, of our method is much greater than alignments by Clustal W.