Fisher: A Program for Detecting H/ACA snoRNAs
Author Information
Author(s): Eva Freyhult, Sverker Edvardsson, Ivica Tamas, Vincent Moulton, Anthony M. Poole
Primary Institution: The Linnaeus Centre for Bioinformatics, Uppsala University
Hypothesis
Can the Fisher program effectively identify H/ACA snoRNAs in the yeast genome using minimum free energy secondary structure prediction?
Conclusion
The study confirms that minimum free energy (MFE) secondary structure prediction is a valid method for screening RNA families with few sequence constraints.
Supporting Evidence
- Fisher was able to identify several H/ACA snoRNAs that snoGPS missed.
- The modified Fisher program reduced the number of false positives significantly.
- The study confirmed the utility of MFE secondary structure prediction for RNA screening.
Takeaway
The Fisher program helps find specific RNA types in yeast by looking at their shapes, and it works better when comparing many yeast genomes together.
Methodology
The Fisher program was modified to improve the identification of H/ACA snoRNAs by combining secondary structure prediction with comparative genomic analysis across multiple yeast species.
Limitations
Fisher has a high false positive rate and cannot detect snoRNAs with only a 5' pseudouridylation pocket.
Digital Object Identifier (DOI)
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