Detecting and Assessing Conserved Stems for Accurate Structural Alignment of RNA Sequences

Since comparative sequence analysis is effective for non-coding RNA detection and RNA secondary structure prediction, efficient computational methods are expected for structuraf alignment of RNA sequences. However, it is very difficuit to construct a weft structuraf afignment without knowing the secondary structures. In this paper, we present a new method for constructing structural alignment of RNA sequences by detecting and assessing conserved stems. The method can be summarized by: 1) we detect conserved stems across multiple RNA sequences using the so-called position matrix with which some common paired positions are uncovered; 2) we assess the conserved stems using the Signal-to-Noise; 3) we build the structural alignment by incorporating some compatible conserved stems with the initial sequence alignment constructed by Clustal W program. We tested our method on the data sets composed of known structural alignments taken from the Rfam database. Experimentai resufts show that our method can buifd structuraf afignment of RNA sequences with much greater sensitivity and specificity than Clustal W.