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RNA Secondary Structure Prediction Using High-throughput SHAPE
Published on: May 31, 2013
Evolutionary rate variation and RNA secondary structure prediction.
B Knudsen1, E S Andersen, C Damgaard
1Bioinformatics Research Center, Høegh Guldbergsgade 10, University of Aarhus, DK-8000 Arhus C, Denmark.
Computational Biology and Chemistry
|July 21, 2004
Summary
Predicting RNA secondary structure is improved by using evolutionary rates from related RNA families. This method accurately forecasts HIV-1 RNA structure, even with accelerated evolutionary rates.
Area of Science:
- Computational Biology
- Bioinformatics
- Molecular Evolution
Background:
- Predicting RNA secondary structure relies on evolutionary history from aligned RNA sequences.
- Accurate determination of evolutionary substitution rates for RNA is crucial but challenging without large, annotated alignments.
- Existing methods often use rates from well-characterized RNA families like tRNA and rRNA.
Purpose of the Study:
- To investigate the applicability of evolutionary rates from tRNA and rRNA for predicting the structure of rapidly evolving RNA.
- To assess the accuracy of RNA secondary structure prediction for the 5'-region of HIV-1 using cross-family evolutionary rates.
- To evaluate the robustness of structure prediction models to variations in evolutionary rate matrices.
Main Methods:
- Applied evolutionary substitution rates derived from transfer RNA (tRNA) and ribosomal RNA (rRNA) datasets.
- Utilized these rates to predict the secondary structure of the 5'-region of Human Immunodeficiency Virus type 1 (HIV-1).
- Introduced randomized noise into rate matrices to test prediction stability.
Main Results:
- RNA secondary structure predictions for HIV-1 showed agreement with experimental data.
- Observed significantly increased evolutionary rates between A and G in both stem and loop regions of HIV-1.
- Generated an improved alignment for the HIV-1 5' region, more consistent with its structure than existing database alignments.
- Predictions remained reliable even with considerable variations in the evolutionary rate matrices.
Conclusions:
- Transferring evolutionary rates from established RNA families (tRNA, rRNA) is a valid approach for predicting secondary structures of other RNA sequences, including rapidly evolving ones like HIV-1.
- The method is robust to variations in evolutionary rates, suggesting broad applicability.
- The study provides a more accurate structural alignment for the HIV-1 5' region.
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