Bioinformatics discovery of non-coding RNAs
Non-coding RNAs have been discovered using both experimental and bioinformatic approaches. Bioinformatic approaches can be divided into three main categories. The first involves homology search, although these techniques are by definition unable to find new classes of ncRNAs. The second category includes algorithms designed to discover specific types of ncRNAs that have similar properties. Finally, some discovery methods are based on very general properties of RNA, and are thus able to discovery entirely new kinds of ncRNAs.
Discovery by homology search
Homology search refers to the process of searching a sequence database for RNAs that are similar to already known RNA sequences. Any algorithm that is designed for homology search of nucleic acid sequences can be used, e.g., BLAST[1]. However, such algorithms typically are not as sensitive or accurate as algorithms specifically designed for RNA.
Of particular importance for RNA is its conservation of a secondary structure, which can be modeled to achieve additional accuracy in searches. For example, Covariance models[2] can be viewed as an extension to a profile hidden Markov model that also reflects conserved secondary structure. Covariance models are implemented in the Infernal software package.[3]
Discovery of specific types of ncRNAs
Discovery by general properties
References
- ^ Altschul SF, Madden TL, Schäffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ (September 1997). "Gapped BLAST and PSI-BLAST: a new generation of protein database search programs". Nucleic Acids Res. 25 (17): 3389–402. PMC 146917. PMID 9254694.
- ^ Eddy SR, Durbin R (June 1994). "RNA sequence analysis using covariance models". Nucleic Acids Res. 22 (11): 2079–88. PMC 308124. PMID 8029015.
- ^ Nawrocki EP, Eddy SR (November 2013). "Infernal 1.1: 100-fold faster RNA homology searches". Bioinformatics. 29 (22): 2933–5. doi:10.1093/bioinformatics/btt509. PMC 3810854. PMID 24008419.
