Abstract
BackgroundMany regulatory non-coding RNAs (ncRNAs) function through complementary binding with mRNAs or other ncRNAs, e.g., microRNAs, snoRNAs and bacterial sRNAs. Predicting these RNA interactions is essential for functional studies of putative ncRNAs or for the design of artificial RNAs. Many ncRNAs show clear signs of undergoing compensating base changes over evolutionary time. Here, we postulate that a non-negligible part of the existing RNA-RNA interactions contain preserved but covarying patterns of interactions.MethodsWe present a novel method that takes compensating base changes across the binding sites into account. The algorithm works in two steps on two pre-generated multiple alignments. In the first step, individual base pairs with high reliability are found using the PETfold algorithm, which includes evolutionary and thermodynamic properties. In step two (where high reliability base pairs from step one are constrained as unpaired), the principle of cofolding is combined with hierarchical folding. The final prediction of intra- and inter-molecular base pairs consists of the reliabilities computed from the constrained expected accuracy scoring, which is an extended version of that used for individual multiple alignments.ResultsWe derived a rather extensive algorithm. One of the advantages of our approach (in contrast to other RNA-RNA interaction prediction methods) is the application of covariance detection and prediction of pseudoknots between intra- and inter-molecular base pairs. As a proof of concept, we show an example and discuss the strengths and weaknesses of the approach.
Highlights
Many regulatory non-coding RNAs function through complementary binding with mRNAs or other ncRNAs, e.g., microRNAs, snoRNAs and bacterial sRNAs
RNAup has a complexity of O(n3 + nw5), whereas IntaRNA has a complexity of O(n2), which makes it fast enough to be used in genome-wide screens
As a proof of concept, we present an example of a bacterial sRNAmRNA interaction
Summary
Many regulatory non-coding RNAs (ncRNAs) function through complementary binding with mRNAs or other ncRNAs, e.g., microRNAs, snoRNAs and bacterial sRNAs. Predicting RNA-RNA interactions is a rapidly growing area within RNA bioinformatics and is essential for the process of assigning function to known as well as de novo predicted non-coding RNAs (ncRNAs) such as those identified in in silico screens for RNA structures [1,2,3,4,5,6,7]. This candidate information along with the data generated from deep sequencing analyses emphasise the need to predict RNA-RNA interactions. Both methods are able to predict complex interactions, like kissing
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