Tree Decomposition Based Fast Search of RNA Structures Including Pseudoknots in Genomes

  • Authors:
  • Yinglei Song;Chunmei Liu;Russell Malmberg;Fangfang Pan;Liming Cai

  • Affiliations:
  • University of Georgia;University of Georgia;University of Georgia;University of Georgia;University of Georgia

  • Venue:
  • CSB '05 Proceedings of the 2005 IEEE Computational Systems Bioinformatics Conference
  • Year:
  • 2005

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Abstract

Searching genomes for RNA secondary structure with computational methods has become an important approach to the annotation of non-coding RNAs. However, due to the lack of efficient algorithms for accurate RNA structure-sequence alignment, computer programs capable of fast and effectively searching genomes for RNA secondary structures have not been available. In this paper, a novel RNA structure profiling model is introduced based on the notion of a conformational graph to specify the consensus structure of an RNA family. Tree decomposition yields a small tree width t for such conformation graphs (e.g., t = 2 for stem loops and only a slight increase for pseudo-knots). Within this modelling framework, the optimal alignment of a sequence to the structure model corresponds to finding a maximum valued isomorphic subgraph and consequently can be accomplished through dynamic programming on the tree decomposition of the conformational graph in time 0(k^t N^2 ), where k is a small parameter; and N is the size of the projiled RNA structure. Experiments show that the application of the alignment algorithm to search in genomes yields the same search accuracy as methods based on a Covariance model with a significant reduction in computation time. In particular; very accurate searches of tmRNAs in bacteria genomes and of telomerase RNAs in yeast genomes can be accomplished in days, as opposed to months required by other methods. The tree decomposition based searching tool is free upon request and can be downloaded at our site h t t p ://w.uga.edu/RNA-informatics/software/index.php.