e-RNA: a collection of web-servers for the prediction and visualisation of RNA secondary structure and their functional features.

e-RNA is a collection of web-servers for the prediction and visualisation of RNA secondary structures and their functional features, including in particular RNA-RNA interactions. In this updated version, we have added novel tools for RNA secondary structure prediction and have significantly updated the visualisation functionality. The new method CoBold can identify transient RNA structure features and their potential functional effects on a known RNA structure during co-transcriptional structure formation.

CYCLeR-a novel tool for the full isoform assembly and quantification of circRNAs.

Splicing is one key mechanism determining the state of any eukaryotic cell. Apart from linear splice variants, circular splice variants (circRNAs) can arise via non-canonical splicing involving a back-splice junction (BSJ). Most existing methods only identify circRNAs via the corresponding BSJ, but do not aim to estimate their full sequence identity or to identify different, alternatively spliced circular isoforms arising from the same BSJ.

Women in the European Virus Bioinformatics Center.

Viruses are the cause of a considerable burden to human, animal and plant health, while on the other hand playing an important role in regulating entire ecosystems. The power of new sequencing technologies combined with new tools for processing "Big Data" offers unprecedented opportunities to answer fundamental questions in virology. Virologists have an urgent need for virus-specific bioinformatics tools.

ShapeSorter: a fully probabilistic method for detecting conserved RNA structure features supported by SHAPE evidence.

There is an increased interest in the determination of RNA structures in vivo as it is now possible to probe them in a high-throughput manner, e.g. using SHAPE protocols.

The International Virus Bioinformatics Meeting 2020.

The International Virus Bioinformatics Meeting 2020 was originally planned to take place in Bern, Switzerland, in March 2020. However, the COVID-19 pandemic put a spoke in the wheel of almost all conferences to be held in 2020. After moving the conference to 8-9 October 2020, we got hit by the second wave and finally decided at short notice to go fully online.

CoBold: a method for identifying different functional classes of transient RNA structure features that can impact RNA structure formation in vivo.

RNA structure formation in vivo happens co-transcriptionally while the transcript is being made. The corresponding co-transcriptional folding pathway typically involves transient RNA structure features that are not part of the final, functional RNA structure. These transient features can play important functional roles of their own and also influence the formation of the final RNA structure in vivo.

R-chie: a web server and R package for visualizing cis and trans RNA-RNA, RNA-DNA and DNA-DNA interactions.

Interactions between biological entities are key to understanding their potential functional roles. Three fields of research have recently made particular progress: the investigation of transRNA-RNA and RNA-DNA transcriptome interactions and of trans DNA-DNA genome interactions. We now have both experimental and computational methods for examining these interactions in vivo and on a transcriptome- and genome-wide scale, respectively.

The dynamic proteome of influenza A virus infection identifies M segment splicing as a host range determinant.

Pandemic influenza A virus (IAV) outbreaks occur when strains from animal reservoirs acquire the ability to infect and spread among humans. The molecular basis of this species barrier is incompletely understood. Here we combine metabolic pulse labeling and quantitative proteomics to monitor protein synthesis upon infection of human cells with a human- and a bird-adapted IAV strain and observe striking differences in viral protein synthesis.

A gene expression atlas of embryonic neurogenesis in reveals complex spatiotemporal regulation of lncRNAs.

Cell type specification during early nervous system development in requires precise regulation of gene expression in time and space. Resolving the programs driving neurogenesis has been a major challenge owing to the complexity and rapidity with which distinct cell populations arise. To resolve the cell type-specific gene expression dynamics in early nervous system development, we have sequenced the transcriptomes of purified neurogenic cell types across consecutive time points covering crucial events in neurogenesis.

Transcriptional dynamics of microRNAs and their targets during Drosophila neurogenesis.

During Drosophila melanogaster embryogenesis, tight regulation of gene expression in time and space is required for the orderly emergence of specific cell types. While the general importance of microRNAs in regulating eukaryotic gene expression has been well-established, their role in early neurogenesis remains to be addressed. In this survey, we investigate the transcriptional dynamics of microRNAs and their target transcripts during neurogenesis of Drosophila melanogaster.

In silico methods for co-transcriptional RNA secondary structure prediction and for investigating alternative RNA structure expression.

RNA transcripts are the primary products of active genes in any living organism, including many viruses. Their cellular destiny not only depends on primary sequence signals, but can also be determined by RNA structure. Recent experimental evidence shows that many transcripts can be assigned more than a single functional RNA structure throughout their cellular life and that structure formation happens co-transcriptionally, i.

A comprehensive comparison of general RNA-RNA interaction prediction methods.

RNA-RNA interactions are fast emerging as a major functional component in many newly discovered non-coding RNAs. Basepairing is believed to be a major contributor to the stability of these intermolecular interactions, much like intramolecular basepairs formed in RNA secondary structure. As such, using algorithms similar to those for predicting RNA secondary structure, computational methods have been recently developed for the prediction of RNA-RNA interactions.

Genome-wide identification and characterization of tissue-specific RNA editing events in D. melanogaster and their potential role in regulating alternative splicing.

RNA editing is a widespread mechanism that plays a crucial role in diversifying gene products. Its abundance and importance in regulating cellular processes were revealed using new sequencing technologies. The majority of these editing events, however, cannot be associated with regulatory mechanisms.

Four RNA families with functional transient structures.

Protein-coding and non-coding RNA transcripts perform a wide variety of cellular functions in diverse organisms. Several of their functional roles are expressed and modulated via RNA structure. A given transcript, however, can have more than a single functional RNA structure throughout its life, a fact which has been previously overlooked.

e-RNA: a collection of web servers for comparative RNA structure prediction and visualisation.

e-RNA offers a free and open-access collection of five published RNA sequence analysis tools, each solving specific problems not readily addressed by other available tools. Given multiple sequence alignments, Transat detects all conserved helices, including those expected in a final structure, but also transient, alternative and pseudo-knotted helices. RNA-Decoder uses unique evolutionary models to detect conserved RNA secondary structure in alignments which may be partly protein-coding.

On the importance of cotranscriptional RNA structure formation.

The expression of genes, both coding and noncoding, can be significantly influenced by RNA structural features of their corresponding transcripts. There is by now mounting experimental and some theoretical evidence that structure formation in vivo starts during transcription and that this cotranscriptional folding determines the functional RNA structural features that are being formed. Several decades of research in bioinformatics have resulted in a wide range of computational methods for predicting RNA secondary structures.

Transient RNA structure features are evolutionarily conserved and can be computationally predicted.

Functional RNA structures tend to be conserved during evolution. This finding is, for example, exploited by comparative methods for RNA secondary structure prediction that currently provide the state-of-art in terms of prediction accuracy. We here provide strong evidence that homologous RNA genes not only fold into similar final RNA structures, but that their folding pathways also share common transient structural features that have been evolutionarily conserved.

COFOLD: an RNA secondary structure prediction method that takes co-transcriptional folding into account.

Existing state-of-the-art methods that take a single RNA sequence and predict the corresponding RNA secondary structure are thermodynamic methods. These aim to predict the most stable RNA structure. There exists by now ample experimental and theoretical evidence that the process of structure formation matters and that sequences in vivo fold while they are being transcribed.

The hok mRNA family.

The hok/sok toxin-antitoxin system of Escherichia coli plasmid R1 increases plasmid maintenance by killing plasmid-free daughter cells. The hok/sok locus specifies two RNAs: hok mRNA, which encodes a toxic transmembrane protein, and sok antisense RNA, which binds a complementary region in the hok mRNA and induces transcript degradation. During cell growth, the cis-encoded sok RNA inhibits expression of the Hok toxin.

The clonal and mutational evolution spectrum of primary triple-negative breast cancers.

Primary triple-negative breast cancers (TNBCs), a tumour type defined by lack of oestrogen receptor, progesterone receptor and ERBB2 gene amplification, represent approximately 16% of all breast cancers. Here we show in 104 TNBC cases that at the time of diagnosis these cancers exhibit a wide and continuous spectrum of genomic evolution, with some having only a handful of coding somatic aberrations in a few pathways, whereas others contain hundreds of coding somatic mutations. High-throughput RNA sequencing (RNA-seq) revealed that only approximately 36% of mutations are expressed.

R-CHIE: a web server and R package for visualizing RNA secondary structures.

Visually examining RNA structures can greatly aid in understanding their potential functional roles and in evaluating the performance of structure prediction algorithms. As many functional roles of RNA structures can already be studied given the secondary structure of the RNA, various methods have been devised for visualizing RNA secondary structures. Most of these methods depict a given RNA secondary structure as a planar graph consisting of base-paired stems interconnected by roundish loops.

Frequent mutation of histone-modifying genes in non-Hodgkin lymphoma.

Follicular lymphoma (FL) and diffuse large B-cell lymphoma (DLBCL) are the two most common non-Hodgkin lymphomas (NHLs). Here we sequenced tumour and matched normal DNA from 13 DLBCL cases and one FL case to identify genes with mutations in B-cell NHL. We analysed RNA-seq data from these and another 113 NHLs to identify genes with candidate mutations, and then re-sequenced tumour and matched normal DNA from these cases to confirm 109 genes with multiple somatic mutations.

Efficient algorithms for training the parameters of hidden Markov models using stochastic expectation maximization (EM) training and Viterbi training.

Background: Hidden Markov models are widely employed by numerous bioinformatics programs used today. Applications range widely from comparative gene prediction to time-series analyses of micro-array data. The parameters of the underlying models need to be adjusted for specific data sets, for example the genome of a particular species, in order to maximize the prediction accuracy.

TRANSAT-- method for detecting the conserved helices of functional RNA structures, including transient, pseudo-knotted and alternative structures.

The prediction of functional RNA structures has attracted increased interest, as it allows us to study the potential functional roles of many genes. RNA structure prediction methods, however, assume that there is a unique functional RNA structure and also do not predict functional features required for in vivo folding. In order to understand how functional RNA structures form in vivo, we require sophisticated experiments or reliable prediction methods.