Fast Prediction of RNA-RNA Interaction

Abstract

Background: Regulatory antisense RNAs are a class of ncRNAs that regulate gene expression by prohibiting the translation of an mRNA by establishing stable interactions with a target sequence. There is great demand for efficient computational methods to predict the specific interaction between an ncRNA and its target mRNA(s). There are a number of algorithms in the literature which can predict a variety of such interactions -unfortunately at a very high computational cost. Although some existing target prediction approaches are much faster, they are specialized for interactions with a single binding site. Methods: In this paper we present a novel algorithm to accurately predict the minimum free energy structure of RNA-RNA interaction under the most general type of interactions studied in the literature. Moreover, we introduce a fast heuristic method to predict the specific (multiple) binding sites of two interacting RNAs.

MicroRNA Target and Gene Validation in Viruses and Bacteria

“…It is important to estimate the degree of folding conservation in the selected regions. This analysis allows to estimate, even if with many limitations, all the possible RNA-RNA interactions [ 28 ]. This analysis allows to determine those conformations that have the highest probability to be functional.…”

Computational detection of abundant long-range nucleotide covariation inDrosophilagenomes

“…Several programs for predicting nonlocal RNA-RNA interactions have been described. RNA-RNA prediction programs use as input either pairs of single nucleotide sequences (Tafer and Hofacker 2008;Huang et al 2009c,d;Kato et al 2010;Salari et al 2010;Seemann et al 2010a,b) or two multiple sequence alignments (Bernhart et al 2006;Seemann et al 2008Seemann et al , 2010a. Methods for computing consensus RNA secondary structures given unaligned homologous sequences have been described for the case of intramolecular structure, but to our knowledge, not for the case of RNA-RNA interactions.…”

Regulatory RNAs in Prokaryotes

“…Interaction components of OxyS and fhlA as presented in Argaman and Altuvia (2000) where n is the length of the input sequence(s)). On the one hand, a technique called sparsification, which has already been successfully used in secondary structure prediction and alignment (Wexler et al, 2006;Ziv-Ukelson et al, 2008;Backofen et al, 2009), greatly improved both time and space requirements for the problem of predicting an optimal joint structure (Salari et al, 2010). On the other hand, there were attempts to reduce this complexity by considering approximations to the original problem.…”

“…Thus, conditional probabilities have to be used instead. Albeit that seemed to be too complex to be calculated, a Bayesian approximation of these conditional probabilities was introduced by Chitsaz et al (2009a) and Salari et al (2009). This allowed a fast calculation of these conditional probabilities and resulted in a fast heuristic method for predicting the specific (multiple) binding sites of two interacting RNAs.…”