Measuring covariation in RNA alignments: physical realism improves information measures
- PMID: 17038338
- DOI: 10.1093/bioinformatics/btl514
Measuring covariation in RNA alignments: physical realism improves information measures
Abstract
Motivation: The importance of non-coding RNAs is becoming increasingly evident, and often the function of these molecules depends on the structure. It is common to use alignments of related RNA sequences to deduce the consensus secondary structure by detecting patterns of co-evolution. A central part of such an analysis is to measure covariation between two positions in an alignment. Here, we rank various measures ranging from simple mutual information to more advanced covariation measures.
Results: Mutual information is still used for secondary structure prediction, but the results of this study indicate which measures are useful. Incorporating more structural information by considering e.g. indels and stacking improves accuracy, suggesting that physically realistic measures yield improved predictions. This can be used to improve both current and future programs for secondary structure prediction. The best measure tested is the RNAalifold covariation measure modified to include stacking.
Availability: Scripts, data and supplementary material can be found at http://www.binf.ku.dk/Stinus_covariation
Similar articles
-
MASTR: multiple alignment and structure prediction of non-coding RNAs using simulated annealing.Bioinformatics. 2007 Dec 15;23(24):3304-11. doi: 10.1093/bioinformatics/btm525. Epub 2007 Nov 15. Bioinformatics. 2007. PMID: 18006551
-
Multiple structural alignment and clustering of RNA sequences.Bioinformatics. 2007 Apr 15;23(8):926-32. doi: 10.1093/bioinformatics/btm049. Epub 2007 Feb 25. Bioinformatics. 2007. PMID: 17324941
-
Murlet: a practical multiple alignment tool for structural RNA sequences.Bioinformatics. 2007 Jul 1;23(13):1588-98. doi: 10.1093/bioinformatics/btm146. Epub 2007 Apr 25. Bioinformatics. 2007. PMID: 17459961
-
Energy-based RNA consensus secondary structure prediction in multiple sequence alignments.Methods Mol Biol. 2014;1097:125-41. doi: 10.1007/978-1-62703-709-9_7. Methods Mol Biol. 2014. PMID: 24639158 Review.
-
From consensus structure prediction to RNA gene finding.Brief Funct Genomic Proteomic. 2009 Nov;8(6):461-71. doi: 10.1093/bfgp/elp043. Brief Funct Genomic Proteomic. 2009. PMID: 19833701 Review.
Cited by
-
Structural constraints identified with covariation analysis in ribosomal RNA.PLoS One. 2012;7(6):e39383. doi: 10.1371/journal.pone.0039383. Epub 2012 Jun 19. PLoS One. 2012. PMID: 22724009 Free PMC article.
-
RNA covariation at helix-level resolution for the identification of evolutionarily conserved RNA structure.PLoS Comput Biol. 2023 Jul 14;19(7):e1011262. doi: 10.1371/journal.pcbi.1011262. eCollection 2023 Jul. PLoS Comput Biol. 2023. PMID: 37450549 Free PMC article.
-
Detecting coevolution without phylogenetic trees? Tree-ignorant metrics of coevolution perform as well as tree-aware metrics.BMC Evol Biol. 2008 Dec 3;8:327. doi: 10.1186/1471-2148-8-327. BMC Evol Biol. 2008. PMID: 19055758 Free PMC article.
-
Discovery of 17 conserved structural RNAs in fungi.Nucleic Acids Res. 2021 Jun 21;49(11):6128-6143. doi: 10.1093/nar/gkab355. Nucleic Acids Res. 2021. PMID: 34086938 Free PMC article.
-
Widespread purifying selection on RNA structure in mammals.Nucleic Acids Res. 2013 Sep;41(17):8220-36. doi: 10.1093/nar/gkt596. Epub 2013 Jul 11. Nucleic Acids Res. 2013. PMID: 23847102 Free PMC article.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
