Michael T. Wolfinger

Barrier Trees of Degenerate Landscapes

The heights of energy barriers separating two (macro-)states are useful for estimating transition frequencies. In non-degenerate landscapes the decomposition of a landscape into basins surrounding local minima connected by saddle points is straightforward and yields a useful definition of macro-states. In this work we develop a rigorous concept of barrier trees for degenerate landscapes. We present a program that efficiently computes such barrier trees, and apply it to two well known examples of landscapes.

Efficient computation of RNA folding dynamics

Barrier trees consisting of local minima and their connecting saddle points imply a natural coarse-graining for the description of the energy landscape of RNA secondary structures. Here we show that, based on this approach, it is possible to predict the folding behaviour of RNA molecules by numerical integration. Comparison with stochastic folding simulations shows reasonable agreement of the resulting folding dynamics and a drastic increase in computational efficiency that makes it possible to investigate the folding dynamics of RNA of at least tRNA size. Our approach is readily applicable to bistable RNA molecules and promises to facilitate studies on the dynamic behaviour of RNA switches.

Folding kinetics of large RNAs.

We introduce here a heuristic approach to kinetic RNA folding that constructs secondary structures by stepwise combination of building blocks. These blocks correspond to subsequences and their thermodynamically optimal structures. These are determined by the standard dynamic programming approach to RNA folding. Folding trajectories are modeled at base-pair resolution using the Morgan-Higgs heuristic and a barrier tree-based heuristic to connect combinations of the local building blocks. Implemented in the program Kinwalker, the algorithm allows co-transcriptional folding and can be used to fold sequences of up to about 1500 nucleotides in length. A detailed comparison with several well-studied examples from the literature, including the delayed folding of bacteriophage cloverleaf structures, the adenine sensing riboswitch, and the hok RNA, shows an excellent agreement of predicted trajectories and experimental evidence. The software is available as part of the ViennaRNA Package.

SHAPE directed RNA folding

Summary: Chemical mapping experiments allow for nucleotide resolution assessment of RNA structure. We demonstrate that different strategies of integrating probing data with thermodynamics-based RNA secondary structure prediction algorithms can be implemented by means of soft constraints. This amounts to incorporating suitable pseudo-energies into the standard energy model for RNA secondary structures. As a showcase application for this new feature of the ViennaRNA Package we compare three distinct, previously published strategies to utilize SHAPE reactivities for structure prediction. The new tool is benchmarked on a set of RNAs with known reference structure. Availability and implementation: The capability for SHAPE directed RNA folding is part of the upcoming release of the ViennaRNA Package 2.2, for which a preliminary release is already freely available at http://www.tbi.univie.ac.at/RNA. Contact: michael.wolfinger@univie.ac.at Supplementary information: Supplementary data are available at Bioinformatics online.

TSSAR: TSS annotation regime for dRNA-seq data

BackgroundDifferential RNA sequencing (dRNA-seq) is a high-throughput screening technique designed to examine the architecture of bacterial operons in general and the precise position of transcription start sites (TSS) in particular. Hitherto, dRNA-seq data were analyzed by visualizing the sequencing reads mapped to the reference genome and manually annotating reliable positions. This is very labor intensive and, due to the subjectivity, biased.ResultsHere, we present TSSAR, a tool for automated de novo TSS annotation from dRNA-seq data that respects the statistics of dRNA-seq libraries. TSSAR uses the premise that the number of sequencing reads starting at a certain genomic position within a transcriptional active region follows a Poisson distribution with a parameter that depends on the local strength of expression. The differences of two dRNA-seq library counts thus follow a Skellam distribution. This provides a statistical basis to identify significantly enriched primary transcripts.We assessed the performance by analyzing a publicly available dRNA-seq data set using TSSAR and two simple approaches that utilize user-defined score cutoffs. We evaluated the power of reproducing the manual TSS annotation. Furthermore, the same data set was used to reproduce 74 experimentally validated TSS in H. pylori from reliable techniques such as RACE or primer extension. Both analyses showed that TSSAR outperforms the static cutoff-dependent approaches.ConclusionsHaving an automated and efficient tool for analyzing dRNA-seq data facilitates the use of the dRNA-seq technique and promotes its application to more sophisticated analysis. For instance, monitoring the plasticity and dynamics of the transcriptomal architecture triggered by different stimuli and growth conditions becomes possible.The main asset of a novel tool for dRNA-seq analysis that reaches out to a broad user community is usability. As such, we provide TSSAR both as intuitive RESTful Web service (http://rna.tbi.univie.ac.at/TSSAR) together with a set of post-processing and analysis tools, as well as a stand-alone version for use in high-throughput dRNA-seq data analysis pipelines.

The MazF-regulon: a toolbox for the post-transcriptional stress response in Escherichia coli

Flexible adaptation to environmental stress is vital for bacteria. An energy-efficient post-transcriptional stress response mechanism in Escherichia coli is governed by the toxin MazF. After stress-induced activation the endoribonuclease MazF processes a distinct subset of transcripts as well as the 16S ribosomal RNA in the context of mature ribosomes. As these ‘stress-ribosomes’ are specific for the MazF-processed mRNAs, the translational program is changed. To identify this ‘MazF-regulon’ we employed Poly-seq (polysome fractionation coupled with RNA-seq analysis) and analyzed alterations introduced into the transcriptome and translatome after mazF overexpression. Unexpectedly, our results reveal that the corresponding protein products are involved in all cellular processes and do not particularly contribute to the general stress response. Moreover, our findings suggest that translational reprogramming serves as a fast-track reaction to harsh stress and highlight the so far underestimated significance of selective translation as a global regulatory mechanism in gene expression. Considering the reported implication of toxin-antitoxin (TA) systems in persistence, our results indicate that MazF acts as a prime effector during harsh stress that potentially introduces translational heterogeneity within a bacterial population thereby stimulating persister cell formation.

Predicting RNA secondary structures from sequence and probing data

RNA secondary structures have proven essential for understanding the regulatory functions performed by RNA such as microRNAs, bacterial small RNAs, or riboswitches. This success is in part due to the availability of efficient computational methods for predicting RNA secondary structures. Recent advances focus on dealing with the inherent uncertainty of prediction by considering the ensemble of possible structures rather than the single most stable one. Moreover, the advent of high-throughput structural probing has spurred the development of computational methods that incorporate such experimental data as auxiliary information.

General and MicroRNA-Mediated mRNA Degradation Occurs on Ribosome Complexes in Drosophila Cells

ABSTRACT The translation and degradation of mRNAs are two key steps in gene expression that are highly regulated and targeted by many factors, including microRNAs (miRNAs). While it is well established that translation and mRNA degradation are tightly coupled, it is still not entirely clear where in the cell mRNA degradation takes place. In this study, we investigated the possibility of mRNA degradation on the ribosome in Drosophila cells. Using polysome profiles and ribosome affinity purification, we could demonstrate the copurification of various deadenylation and decapping factors with ribosome complexes. Also, AGO1 and GW182, two key factors in the miRNA-mediated mRNA degradation pathway, were associated with ribosome complexes. Their copurification was dependent on intact mRNAs, suggesting the association of these factors with the mRNA rather than the ribosome itself. Furthermore, we isolated decapped mRNA degradation intermediates from ribosome complexes and performed high-throughput sequencing analysis. Interestingly, 93% of the decapped mRNA fragments (approximately 12,000) could be detected at the same relative abundance on ribosome complexes and in cell lysates. In summary, our findings strongly indicate the association of the majority of bulk mRNAs as well as mRNAs targeted by miRNAs with the ribosome during their degradation.

ViennaNGS: A toolbox for building efficient next- generation sequencing analysis pipelines

Recent achievements in next-generation sequencing (NGS) technologies lead to a high demand for reuseable software components to easily compile customized analysis workflows for big genomics data. We present ViennaNGS, an integrated collection of Perl modules focused on building efficient pipelines for NGS data processing. It comes with functionality for extracting and converting features from common NGS file formats, computation and evaluation of read mapping statistics, as well as normalization of RNA abundance. Moreover, ViennaNGS provides software components for identification and characterization of splice junctions from RNA-seq data, parsing and condensing sequence motif data, automated construction of Assembly and Track Hubs for the UCSC genome browser, as well as wrapper routines for a set of commonly used NGS command line tools.

Differential transcriptional responses to Ebola and Marburg virus infection in bat and human cells

The unprecedented outbreak of Ebola in West Africa resulted in over 28,000 cases and 11,000 deaths, underlining the need for a better understanding of the biology of this highly pathogenic virus to develop specific counter strategies. Two filoviruses, the Ebola and Marburg viruses, result in a severe and often fatal infection in humans. However, bats are natural hosts and survive filovirus infections without obvious symptoms. The molecular basis of this striking difference in the response to filovirus infections is not well understood. We report a systematic overview of differentially expressed genes, activity motifs and pathways in human and bat cells infected with the Ebola and Marburg viruses, and we demonstrate that the replication of filoviruses is more rapid in human cells than in bat cells. We also found that the most strongly regulated genes upon filovirus infection are chemokine ligands and transcription factors. We observed a strong induction of the JAK/STAT pathway, of several genes encoding inhibitors of MAP kinases (DUSP genes) and of PPP1R15A, which is involved in ER stress-induced cell death. We used comparative transcriptomics to provide a data resource that can be used to identify cellular responses that might allow bats to survive filovirus infections.