Evolutionary rate variation and RNA secondary structure prediction

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  • B Knudsen, Division of Genetics, Institute of Animal Science and Animal Health, The Royal Veterinary and Agricultural University, Denmark
  • E S Andersen
  • Christian Kroun Damgaard
  • Jørgen Kjems
  • Jan Gorodkin, Division of Genetics, Institute of Animal Science and Animal Health, The Royal Veterinary and Agricultural University, Denmark
Predicting RNA secondary structure using evolutionary history can be carried out by using an alignment of related RNA sequences with conserved structure. Accurately determining evolutionary substitution rates for base pairs and single stranded nucleotides is a concern for methods based on this type of approach. Determining these rates can be hard to do reliably without a large and accurate initial alignment, which ideally also has structural annotation. Hence, one must often apply rates extracted from other RNA families with trusted alignments and structures. Here, we investigate this problem by applying rates derived from tRNA and rRNA to the prediction of the much more rapidly evolving 5'-region of HIV-1. We find that the HIV-1 prediction is in agreement with experimental data, even though the relative evolutionary rate between A and G is significantly increased, both in stem and loop regions. In addition we obtained an alignment of the 5' HIV-1 region that is more consistent with the structure than that currently in the database. We added randomized noise to the original values of the rates to investigate the stability of predictions to rate matrix deviations. We find that changes within a fairly large range still produce reliable predictions and conclude that using rates from a limited set of RNA sequences is valid over a broader range of sequences.
Original languageEnglish
JournalComputational Biology and Chemistry
Volume28
Issue3
Pages (from-to)219-26
Number of pages8
ISSN1476-9271
DOIs
Publication statusPublished - Jul 2004

    Research areas

  • Algorithms, Base Pairing, Databases, Nucleic Acid, Evolution, Molecular, HIV-1, Kinetics, Models, Genetic, Nucleic Acid Conformation, Point Mutation, RNA, RNA, Ribosomal, RNA, Transfer, RNA, Viral, Sequence Alignment

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