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RNA Secondary Structure Prediction Using High-throughput SHAPE
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bpRNA-align: improved RNA secondary structure global alignment for comparing and clustering RNA structures.

Brittany Lasher1, David A Hendrix2,3

  • 1Department of Biochemistry and Biophysics, Oregon State University, Corvallis, Oregon 97331, USA.

RNA (New York, N.Y.)
|February 9, 2023
PubMed
Summary

A new method, bpRNA-align, improves the identification of common ribonucleic acid (RNA) structural motifs. This tool enhances RNA structure comparison for better database accuracy and discovery of new RNA families.

Keywords:
RNARNA secondary structureRNA structural alignmentRNA structural clusteringclustering

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Biology

Background:

  • Ribonucleic acid (RNA) structure is crucial for its biological function, with secondary structures being highly conserved.
  • Advances in RNA structure characterization yield more accurate secondary structure data.
  • Identifying common RNA structural motifs and their functions via comparison is challenging but vital for RNA databases and family discovery.

Purpose of the Study:

  • To present a novel method for aligning RNA secondary structures.
  • To improve the discovery of common RNA structural motifs and RNA families.

Main Methods:

  • Developed bpRNA-align, a customized global structural alignment method.
  • Implemented an inverted, context-specific affine gap penalty.
  • Utilized a structural, feature-specific substitution matrix for similarity scoring.
  • Evaluated similarity scores using affinity propagation clustering on known structure types.

Main Results:

  • bpRNA-align demonstrates improved clustering performance compared to other methods.
  • The method shows effectiveness across a wide range of RNA structure types.
  • Novel RNA structural motifs and families can potentially be discovered.

Conclusions:

  • bpRNA-align offers a robust approach for RNA secondary structure comparison.
  • The method advances the analysis of RNA structures, aiding in database enhancement and the discovery of new RNA families.
  • This work contributes to a deeper understanding of RNA structure-function relationships.