Detecting conserved secondary structures in RNA molecules using constrained structural alignment.
Constrained sequence alignment has been studied extensively in the past. Different forms of constraints have been investigated, where a constraint can be a subsequence, a regular expression, or a probability matrix of symbols and positions. However, constrained structural alignment has been investigated to a much lesser extent. In this paper, we present an efficient method for constrained structural alignment and apply the method to detecting conserved secondary structures, or structural motifs, in a set of RNA molecules. The proposed method combines both sequence and structural information of RNAs to find an optimal local alignment between two RNA secondary structures, one of which is a query and the other is a subject structure in the given set. The method allows a biologist to annotate conserved regions, or constraints, in the query RNA structure and incorporates these regions into the alignment process to obtain biologically more meaningful alignment scores. A statistical measure is developed to assess the significance of the scores. Experimental results based on detecting internal ribosome entry sites in the RNA molecules of hepatitis C virus and Trypanosoma brucei demonstrate the effectiveness of the proposed method and its superiority over existing techniques.
Khaladkar
Mugdha
M
Bioinformatics Program and Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, USA.
Patel
Vandanaben
V
Bellofatto
Vivian
V
Wilusz
Jeffrey
J
Wang
Jason T L
JT
D000465:Algorithms; D000818:Animals; D001483:Base Sequence; D019295:Computational Biology / Q000379:methods*; D016174:Hepacivirus / Q000235:genetics; D008969:Molecular Sequence Data; D009690:Nucleic Acid Conformation; D012313:RNA / Q000737:chemistry* / Q000235:genetics; D014346:Trypanosoma brucei brucei / Q000235:genetics
D012313:RNA