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Nucleic Acids Research 2004 32(16):4925-4936; doi:10.1093/nar/gkh839
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Published online 24 September 2004

Nucleic Acids Research, Vol. 32 No. 16 © Oxford University Press 2004; all rights reserved

A comparative method for finding and folding RNA secondary structures within protein-coding regions

Jakob Skou Pedersen1,*, Irmtraud Margret Meyer2, Roald Forsberg1, Peter Simmonds3 and Jotun Hein2

1 Bioinformatics Research Center, Department of Ecology and Genetics, The Institute of Biological Sciences, University of Aarhus, Ny Munkegade, Building 550, 8000 Aarhus C, Denmark, 2 Oxford Centre for Gene Function, University of Oxford, South Parks Road, Oxford OX1 3QB, United Kingdom and 3 Centre for Infectious Diseases, University of Edinburgh, Summerhall, Edinburgh EH9 1QH, United Kingdom

* To whom correspondence should be addressed at current address: Center for Biomolecular Science and Engineering, University of California, 321 Baskin Engineering Bldg, Santa Cruz, CA 95064, USA. Tel: +1 831 459 5232; Fax: +1 831 459 4829; Email: jsp{at}daimi.au.dk
The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors

Received July 30, 2004; Revised and Accepted September 2, 2004

Existing computational methods for RNA secondary-structure prediction tacitly assume RNA to only encode functional RNA structures. However, experimental studies have revealed that some RNA sequences, e.g. compact viral genomes, can simultaneously encode functional RNA structures as well as proteins, and evidence is accumulating that this phenomenon may also be found in Eukaryotes. We here present the first comparative method, called RNA-DECODER, which explicitly takes the known protein-coding context of an RNA-sequence alignment into account in order to predict evolutionarily conserved secondary-structure elements, which may span both coding and non-coding regions. RNA-DECODER employs a stochastic context-free grammar together with a set of carefully devised phylogenetic substitution-models, which can disentangle and evaluate the different kinds of overlapping evolutionary constraints which arise. We show that RNA-DECODER's parameters can be automatically trained to successfully fold known secondary structures within the HCV genome. We scan the genomes of HCV and polio virus for conserved secondary-structure elements, and analyze performance as a function of available evolutionary information. On known secondary structures, RNA-DECODER shows a sensitivity similar to the programs MFOLD, PFOLD and RNAALIFOLD. When scanning the entire genomes of HCV and polio virus for structure elements, RNA-DECODER's results indicate a markedly higher specificity than MFOLD, PFOLD and RNAALIFOLD.


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