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MSARI: multiple sequence alignments for statistical detection of RNA secondary structure.
Alex Coventry1, Daniel J Kleitman, Bonnie Berger
1Department of Mathematics and Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Summary
We developed msari, a new method to find conserved RNA secondary structures in genes. This tool accurately identifies these structures in large genomic datasets, improving upon existing methods.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- Identifying conserved RNA secondary structures is crucial for understanding gene function.
- Advances in genome sequencing enable large-scale comparative analyses.
- Existing methods struggle with automatically generated sequence alignments.
Purpose of the Study:
- To present a highly accurate method for identifying conserved RNA secondary structures.
- To introduce the msari software tool that implements this method.
- To demonstrate msari's superior performance in high-throughput genomic scans.
Main Methods:
- Searching multiple sequence alignments for correlated reverse-complementary regions.
- Developing the msari program to automate this search.
- Testing msari on signal recognition particle and RNaseP orthologs using ClustalW alignments.
Main Results:
- Msari achieved 89.1% sensitivity at 97.5% specificity for known structures.
- Msari demonstrated 74.4% sensitivity with no false positives in a large control set.
- A comprehensive scan revealed known and novel mRNA secondary structures in coding genes.
Conclusions:
- Msari is a highly accurate and efficient tool for detecting conserved RNA secondary structures.
- The method is particularly valuable for high-throughput analysis of genomic data.
- Msari's approach to sequence redundancy has broader applications in comparative genomics.