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A Rapid High-throughput Method for Mapping Ribonucleoproteins RNPs on Human pre-mRNA
Published on: December 2, 2009
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RNAcmap: a fully automatic pipeline for predicting contact maps of RNAs by evolutionary coupling analysis
Tongchuan Zhang1, Jaswinder Singh2, Thomas Litfin1
1Institute for Glycomics and School of Information and Communication Technology, Griffith University, Parklands Dr. Southport, Queensland 4222, Australia.
Bioinformatics (Oxford, England)
|May 22, 2021
Summary
RNAcmap automates evolutionary coupling analysis for RNA sequences, improving structure prediction accuracy. Its performance rivals manual methods and is adaptable for novel RNA families.
Area of Science:
- Computational Biology
- Bioinformatics
- Structural Biology
Background:
- Accurate RNA structure prediction benefits from evolutionary coupling analysis.
- Current methods rely on manually curated alignments from Rfam, limiting scope.
- Millions of non-coding RNA sequences exist beyond Rfam.
Purpose of the Study:
- To develop an automated pipeline, RNAcmap, for evolutionary coupling analysis of any RNA sequence.
- To enable accurate RNA structure prediction for sequences not present in curated databases.
Main Methods:
- RNAcmap uses INFERNAL to build covariance models for homology search.
- It integrates two secondary structure predictors: RNAfold and SPOT-RNA.
- The pipeline performs fully automatic evolutionary coupling analysis.
Main Results:
- RNAcmap's performance depends more on secondary structure predictor accuracy than the coupling tool.
- SPOT-RNA yielded the best performance, comparable to Rfam-based methods.
- RNAcmap is effective for sequences outside Rfam and can be improved with meta-predictors.
Conclusions:
- RNAcmap provides reliable base-pairing information for RNA structure prediction.
- The pipeline enhances the analysis of RNA sequences lacking curated alignments.
- RNAcmap facilitates broader application of evolutionary coupling in RNA research.
