Stephan H. Bernhart

ViennaRNA Package 2.0

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

The Vienna RNA Websuite

The Vienna RNA Websuite is a comprehensive collection of tools for folding, design and analysis of RNA sequences. It provides a web interface to the most commonly used programs of the Vienna RNA package. Among them, we find folding of single and aligned sequences, prediction of RNA–RNA interactions, and design of sequences with a given structure. Additionally, we provide analysis of folding landscapes using the barriers program and structural RNA alignments using LocARNA. The web server together with software packages for download is freely accessible at http://rna.tbi.univie.ac.at/.

RNAalifold: improved consensus structure prediction for RNA alignments

BackgroundThe prediction of a consensus structure for a set of related RNAs is an important first step for subsequent analyses. RNAalifold, which computes the minimum energy structure that is simultaneously formed by a set of aligned sequences, is one of the oldest and most widely used tools for this task. In recent years, several alternative approaches have been advocated, pointing to several shortcomings of the original RNAalifold approach.ResultsWe show that the accuracy of RNAalifold predictions can be improved substantially by introducing a different, more rational handling of alignment gaps, and by replacing the rather simplistic model of covariance scoring with more sophisticated RIBOSUM-like scoring matrices. These improvements are achieved without compromising the computational efficiency of the algorithm. We show here that the new version of RNAalifold not only outperforms the old one, but also several other tools recently developed, on different datasets.ConclusionThe new version of RNAalifold not only can replace the old one for almost any application but it is also competitive with other approaches including those based on SCFGs, maximum expected accuracy, or hierarchical nearest neighbor classifiers.

Recurrent mutation of the ID3 gene in Burkitt lymphoma identified by integrated genome, exome and transcriptome sequencing

Burkitt lymphoma is a mature aggressive B-cell lymphoma derived from germinal center B cells. Its cytogenetic hallmark is the Burkitt translocation t(8;14)(q24;q32) and its variants, which juxtapose the MYC oncogene with one of the three immunoglobulin loci. Consequently, MYC is deregulated, resulting in massive perturbation of gene expression. Nevertheless, MYC deregulation alone seems not to be sufficient to drive Burkitt lymphomagenesis. By whole-genome, whole-exome and transcriptome sequencing of four prototypical Burkitt lymphomas with immunoglobulin gene (IG)-MYC translocation, we identified seven recurrently mutated genes. One of these genes, ID3, mapped to a region of focal homozygous loss in Burkitt lymphoma. In an extended cohort, 36 of 53 molecularly defined Burkitt lymphomas (68%) carried potentially damaging mutations of ID3. These were strongly enriched at somatic hypermutation motifs. Only 6 of 47 other B-cell lymphomas with the IG-MYC translocation (13%) carried ID3 mutations. These findings suggest that cooperation between ID3 inactivation and IG-MYC translocation is a hallmark of Burkitt lymphomagenesis.

Alignment of RNA base pairing probability matrices

MOTIVATION Many classes of functional RNA molecules are characterized by highly conserved secondary structures but little detectable sequence similarity. Reliable multiple alignments can therefore be constructed only when the shared structural features are taken into account. Since multiple alignments are used as input for many subsequent methods of data analysis, structure-based alignments are an indispensable necessity in RNA bioinformatics. RESULTS We present here a method to compute pairwise and progressive multiple alignments from the direct comparison of base pairing probability matrices. Instead of attempting to solve the folding and the alignment problem simultaneously as in the classical Sankoffs algorithm, we use McCaskills approach to compute base pairing probability matrices which effectively incorporate the information on the energetics of each sequences. A novel, simplified variant of Sankoffs algorithms can then be employed to extract the maximum-weight common secondary structure and an associated alignment. AVAILABILITY The programs pmcomp and pmmulti described in this contribution are implemented in Perl and can be downloaded together with the example datasets from http://www.tbi.univie.ac.at/RNA/PMcomp/. A web server is available at http://rna.tbi.univie.ac.at/cgi-bin/pmcgi.pl

Partition function and base pairing probabilities of RNA heterodimers

BackgroundRNA has been recognized as a key player in cellular regulation in recent years. In many cases, non-coding RNAs exert their function by binding to other nucleic acids, as in the case of microRNAs and snoRNAs. The specificity of these interactions derives from the stability of inter-molecular base pairing. The accurate computational treatment of RNA-RNA binding therefore lies at the heart of target prediction algorithms.MethodsThe standard dynamic programming algorithms for computing secondary structures of linear single-stranded RNA molecules are extended to the co-folding of two interacting RNAs.ResultsWe present a program, RNAcofold, that computes the hybridization energy and base pairing pattern of a pair of interacting RNA molecules. In contrast to earlier approaches, complex internal structures in both RNAs are fully taken into account. RNAcofold supports the calculation of the minimum energy structure and of a complete set of suboptimal structures in an energy band above the ground state. Furthermore, it provides an extension of McCaskills partition function algorithm to compute base pairing probabilities, realistic interaction energies, and equilibrium concentrations of duplex structures.AvailabilityRNAcofold is distributed as part of the Vienna RNA Package, http://www.tbi.univie.ac.at/RNA/.ContactStephan H. Bernhart – berni@tbi.univie.ac.at

Local RNA base pairing probabilities in large sequences

SUMMARY The genome-wide search for non-coding RNAs requires efficient methods to compute and compare local secondary structures. Since the exact boundaries of such putative transcripts are typically unknown, arbitrary sequence windows have to be used in practice. Here we present a method for robustly computing the probabilities of local base pairs from long RNA sequences independent of the exact positions of the sequence window. AVAILABILITY The program RNAplfold is part of the Vienna RNA Package and can be downloaded from http://www.tbi.univie.ac.at/RNA/.

Strategies for measuring evolutionary conservation of RNA secondary structures

BackgroundEvolutionary conservation of RNA secondary structure is a typical feature of many functional non-coding RNAs. Since almost all of the available methods used for prediction and annotation of non-coding RNA genes rely on this evolutionary signature, accurate measures for structural conservation are essential.ResultsWe systematically assessed the ability of various measures to detect conserved RNA structures in multiple sequence alignments. We tested three existing and eight novel strategies that are based on metrics of folding energies, metrics of single optimal structure predictions, and metrics of structure ensembles. We find that the folding energy based SCI score used in the RNAz program and a simple base-pair distance metric are by far the most accurate. The use of more complex metrics like for example tree editing does not improve performance. A variant of the SCI performed particularly well on highly conserved alignments and is thus a viable alternative when only little evolutionary information is available. Surprisingly, ensemble based methods that, in principle, could benefit from the additional information contained in sub-optimal structures, perform particularly poorly. As a general trend, we observed that methods that include a consensus structure prediction outperformed equivalent methods that only consider pairwise comparisons.ConclusionStructural conservation can be measured accurately with relatively simple and intuitive metrics. They have the potential to form the basis of future RNA gene finders, that face new challenges like finding lineage specific structures or detecting mis-aligned sequences.

DNA methylome analysis in Burkitt and follicular lymphomas identifies differentially methylated regions linked to somatic mutation and transcriptional control

Although Burkitt lymphomas and follicular lymphomas both have features of germinal center B cells, they are biologically and clinically quite distinct. Here we performed whole-genome bisulfite, genome and transcriptome sequencing in 13 IG-MYC translocation–positive Burkitt lymphoma, nine BCL2 translocation–positive follicular lymphoma and four normal germinal center B cell samples. Comparison of Burkitt and follicular lymphoma samples showed differential methylation of intragenic regions that strongly correlated with expression of associated genes, for example, genes active in germinal center dark-zone and light-zone B cells. Integrative pathway analyses of regions differentially methylated in Burkitt and follicular lymphomas implicated DNA methylation as cooperating with somatic mutation of sphingosine phosphate signaling, as well as the TCF3-ID3 and SWI/SNF complexes, in a large fraction of Burkitt lymphomas. Taken together, our results demonstrate a tight connection between somatic mutation, DNA methylation and transcriptional control in key B cell pathways deregulated differentially in Burkitt lymphoma and other germinal center B cell lymphomas.

Translational Control by RNA-RNA Interaction: Improved Computation of RNA-RNA Binding Thermodynamics

The thermodynamics of RNA-RNA interaction consists of two components: the energy necessary to make a potential binding region accessible, i.e. unpaired, and the energy gained from the base pairing of the two interaction partners. We show here that both components can be efficiently computed using an improved variant of RNAup. The method is then applied to a set of bacterial small RNAs involved in translational control. In all cases of biologically active sRNA target interactions, the target sites predicted by RNAup are in perfect agreement with literature. In addition to prediction of target site location, RNAup can also be used to determine the mode of sRNA action. Using information about target site location and the accessibility change resulting from sRNA binding we can discriminate between positive and negative regulators of translation.