RNA Structural Alignments, Part I: Sankoff-Based Approaches for Structural Alignments
Simultaneous alignment and secondary structure prediction of RNA sequences is often referred to as “RNA structural alignment.” A class of the methods for structural alignment is based on the principles proposed by Sankoff more than 25 years ago. The Sankoff algorithm simultaneously folds and aligns two or more sequences. The advantage of this algorithm over those that separate the folding and alignment steps is that it makes better predictions. The disadvantage is that it is slower and requires more computer memory to run. The amount of computational resources needed to run the Sankoff algorithm is so high that it took more than a decade before the first implementation of a Sankoff style algorithm was published. However, with the faster computers available today and the improved heuristics used in the implementations the Sankoff-based methods have become practical. This chapter describes the methods based on the Sankoff algorithm. All the practical implementations of the algorithm use heuristics to make them run in reasonable time and memory. These heuristics are also described in this chapter.
Key wordsStructural RNA alignment Simultaneous folding and alignment of RNA sequences Sankoff algorithm
This work is supported by the Danish Council for Independent Research (Technology and Production Sciences), the Danish Council for Strategic Research (Programme Commission on Strategic Growth Technologies), as well as the Danish Center for Scientific Computing.
- 16.Mathews D (2004) Predicting the secondary structure common to two RNA sequences with Dynalign. Curr Protoc Bioinformatics. Unit 12.4Google Scholar
- 30.Torarinsson E, Lindgreen S (2008) WAR: Webserver for aligning structural RNAs. Nucleic Acids Res 36(Web server issue):W79–W84Google Scholar
- 35.Widmann J, Stombaugh J, McDonald D, Chocholousova J, Gardner P, Iyer MK, Liu Z, Lozupone CA, Quinn J, Smit S, Wikman S, Zaneveld JR, Knight R (2012) RNASTAR: an RNA STructural Alignment Repository that provides insight into the evolution of natural and artificial RNAs. RNA 18(7):1319– 1327PubMedCentralPubMedCrossRefGoogle Scholar
- 37.Ding Y, Lawrence CE (2003) A statistical sampling algorithm for RNA secondary structure prediction Nucleic Acids Res 31(24):7280–7301Google Scholar
- 40.Höner zu Siederdissen C, Bernhart SH, Stadler PF, Hofacker IL (2011) A folding algorithm for extended RNA secondary structures. Bioinformatics 27(13):i129– i136Google Scholar