Research Article: ViennaRNA Package 2.0

Date Published: November 24, 2011

Publisher: BioMed Central

Author(s): Ronny Lorenz, Stephan H Bernhart, Christian Höner zu Siederdissen, Hakim Tafer, Christoph Flamm, Peter F Stadler, Ivo L Hofacker.

http://doi.org/10.1186/1748-7188-6-26

Abstract

Secondary structure forms an important intermediate level of description of nucleic acids that encapsulates the dominating part of the folding energy, is often well conserved in evolution, and is routinely used as a basis to explain experimental findings. Based on carefully measured thermodynamic parameters, exact dynamic programming algorithms can be used to compute ground states, base pairing probabilities, as well as thermodynamic properties.

The ViennaRNA Package has been a widely used compilation of RNA secondary structure related computer programs for nearly two decades. Major changes in the structure of the standard energy model, the Turner 2004 parameters, the pervasive use of multi-core CPUs, and an increasing number of algorithmic variants prompted a major technical overhaul of both the underlying RNAlib and the interactive user programs. New features include an expanded repertoire of tools to assess RNA-RNA interactions and restricted ensembles of structures, additional output information such as centroid structures and maximum expected accuracy structures derived from base pairing probabilities, or z-scores for locally stable secondary structures, and support for input in fasta format. Updates were implemented without compromising the computational efficiency of the core algorithms and ensuring compatibility with earlier versions.

The ViennaRNA Package 2.0, supporting concurrent computations via OpenMP, can be downloaded from http://www.tbi.univie.ac.at/RNA.

Partial Text

A typical single stranded-nucleic acid molecule has the propensity to form double helical structures causing the molecule to fold back onto itself. Simple rules of complementary base pairing govern this process, which results in a regular pattern of Watson-Crick and GU pairings (helices) and intervening stretches of less regularly ordered nucleotides (loops), collectively known as the molecule’s secondary structure. Secondary structure elements may be placed in close spatial proximity allowing additional non-covalent interactions. These are not as frequent and often are energetically less favorable compared to canonical base pairs, thus rendering the 3-dimensional tertiary structure of an RNA to be dominated by the underlying scaffold of the secondary structure. The canonical base pairing governs not only the thermodynamics but also the folding kinetics, which can be approximated as a hierarchical process in which secondary structure is formed before tertiary structure [1].

The algorithms implemented in the ViennaRNA Package are not only accessible by means of the interactive programs outlined in the previous section but also directly in the form of a C/C++ library. This makes them readily available for third-party programs and, with the help of included Perl-interface, to elaborate scripting pipelines.

We assess the performance of the ViennaRNA Package 2.0 both in terms of computational efficiency and in terms of prediction accuracy. We emphasize that it is not the purpose of this contribution to compare thermodynamics-based prediction algorithms against other approaches to RNA structure prediction. For such a benchmark we refer to the literature, e.g. [18,89,90].

The ViennaRNA Package has been a useful tool for the RNA bioinformatics community for almost two decades. Quite a few widely-used software tools and data analysis pipelines have been built upon this foundation, either incorporating calls to the interactive programs or directly interfacing to RNAlib. Numeric characteristics of secondary structures, such as Gibbs free energy ΔG, Minimum free energy (MFE), ensemble diversity or probabilities of MFE structures in the ensemble, have been widely used as features for machine learning classification, e.g. in microRNA precursor and target detection [91-94]. The non-coding RNA gene finder RNAz [95,96], the snoRNA detector snoReport [97], and RNAstrand [98], a tool that predicts the reading direction of structured RNAs from a multiple sequence alignment, combine thermodynamic properties computed with RNAlib functions and a machine learning component. RNAsoup [99] takes advantage of the programs RNAfold, RNAalifold and some other tools provided by the ViennaRNA Package for a structural clustering of ncRNAs. The siRNA design program RNAxs [100] employs the site accessibility predictions offered by RNAplfold, as does IntaRNA [60], a program to predict RNA interaction sites. Several secondary structure prediction tools, such as CentroidFold [22], McCaskill-MEA [101], or RNAsalsa [102], use base pair probabilities predicted by RNAfold -p as input, while the LocARNA package [59] uses them for structural alignment. The motif-based comparison and alignment tool ExpaRNA [103] and the tree alignment program RNAforester [75] also rely on the algorithms provided by RNAlib. Since its initial publication [25], no comprehensive description [104] of the ViennaRNA Package has appeared. Release 2.0 now implements the latest energy model, provides many new and improved functionalities, and – as we hope – is even easier and more efficient to use due to a thread-safe architecture, an improved API, a more consistent set of options, and a much more detailed documentation. Care has been taken to ensure backward compatibility so that ViennaRNA Package 2.0 can be readily substituted for earlier versions.

The source code of the ViennaRNA Package as well as the current reference manual can be downloaded from http://www.tbi.univie.ac.at/RNA.

The authors declare that they have no competing interests.

Work on the Vienna RNA Package is coordinated by ILH. The design and structure of version 2.0 resulted from discussion of RL with ILH, PFS, CF, SHB and CHzS. Implementation and performance analysis was performed by RL with contributions of HT (RNAplex and RNAsnoop). CHzS provided the converted new energy parameter files. Detailed documentation for the RNAlib was done by RL and SHB based on pre-existing sources. The manuscript was written by RL with major contribution by SHB, PFS, and ILH. All authors read and approved the final manuscript.

 

Source:

http://doi.org/10.1186/1748-7188-6-26

 

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