Strategies for measuring evolutionary conservation of RNA secondary structures

<p>Abstract</p> <p>Background</p> <p>Evolutionary 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.</p> <p>Results</p> <p>We 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.</p> <p>Conclusion</p> <p>Structural 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.</p

Pericardial effusion unrelated to surgery is a predictor of mortality in heart transplant patients

Background: Hemodynamically irrelevant pericardial effusion (PeEf) is a predictor of adverse outcome in heart failure patients. The clinical relevance of a PeEf unrelated to surgery in heart transplant patients remains unknown. This study assesses the prognostic value of PeEf occurring later than 1 year after transplantation. Methods: All patients undergoing heart transplantation in Zurich between 1989 and 2012 were screened. Cox proportional hazard models were used to analyze mortality (primary) and hospitalization (secondary endpoint). PeEf time points were compared to baseline for rejection, immunosuppressants, tumors, inflam­mation, heart failure, kidney function, hemodynamic, and echocardiographic parameters. Results: Of 152 patients (mean age 48.3 ± 11.9), 25 developed PeEf. Median follow-up period was 11.9 (IQR 5.8–17) years. The number of deaths was 6 in the PeEf group and 46 in the non-PeEf group. The occurrence of PeEf was associated with a 2.5-fold increased risk of death (HR 2.49, 95% CI 1.02–6.13, p = 0.046) and hospitalization (HR 2.53, 95% CI 1.57–4.1, p = 0.0002). Conclusions: This study reveals that the finding of hemodynamically irrelevant PeEf in heart trans­plant patients is a predictor of adverse outcome, suggesting that a careful clinical assessment is war­ranted in heart transplant patients exhibiting small PeEf

IntaRNA: efficient prediction of bacterial sRNA targets incorporating target site accessibility and seed regions

Motivation: During the last few years, several new small regulatory RNAs (sRNAs) have been discovered in bacteria. Most of them act as post-transcriptional regulators by base pairing to a target mRNA, causing translational repression or activation, or mRNA degradation. Numerous sRNAs have already been identified, but the number of experimentally verified targets is considerably lower. Consequently, computational target prediction is in great demand. Many existing target prediction programs neglect the accessibility of target sites and the existence of a seed, while other approaches are either specialized to certain types of RNAs or too slow for genome-wide searches

Der Klang der Lyrik: Zur Konzeptualisierung von Sprecher und Stimme, auch für die computationelle Analyse

Das Forschungsprojekt »textklang«: Mixed-Methods-Analyse von Lyrik in Text und Ton (gefördert durch das Bundesministerium für Bildung und Forschung) zielt auf die systematische und diachrone Untersuchung der Beziehung zwischen literarischen Texten, insbesondere Lyrik der Romantik, und ihrer lautsprachlichen Realisierung bei der Rezitation oder der musikalischen Aufführung. Die Vorstellungen von Mündlichkeit, Klang und Stimme, die im Besonderen mit der Lyrik verbunden sind, werden empirisch untersucht und auch im Sinne moderner Ansätze der Lyrikanalyse theoretisiert. Besondere Bedeutung kommt dabei dem experimentellen Ansatz der Sprachsynthese zu, also der computationellen Möglichkeit, eine menschliche Sprechstimme künstlich herzustellen; er ermöglicht es, eine idealtypische Realisierung des Textes zu ermitteln und menschliche Realisierungen auf ihre ästhetische Besonderheit hin zu testen.The research project »text sound«: mixed-methods-analysis of lyric poetry in text and tonal sound (funded by the Federal Ministry for Education and Research, BMBF) aims to undertake a systematic and diachronic investigation of the relationship between literary texts, especially lyric poetry from the Romantic period, and their phonetic realisation in recitations or musical performances. Ideas of orality, sound and voice, which are particularly associated with poetry, are investigated empirically and also theorised in the line with modern approaches to the analysis of lyric poetry. Of particular importance is the experimental approach of speech synthesis, i.e. using computers to artificially produce a human sounding voice; this approach makes it possible to explore an ideal-typical realisation of the text and to test the aesthetic peculiarity of human realisations

Invertebrate 7SK snRNAs

7SK RNA is a highly abundant noncoding RNA in mammalian cells whose function in transcriptional regulation has only recently been elucidated. Despite its highly conserved sequence throughout vertebrates, all attempts to discover 7SK RNA homologues in invertebrate species have failed so far. Here we report on a combined experimental and computational survey that succeeded in discovering 7SK RNAs in most of the major deuterostome clades and in two protostome phyla: mollusks and annelids. Despite major efforts, no candidates were found in any of the many available ecdysozoan genomes, however. The additional sequence data confirm the evolutionary conservation and hence functional importance of the previously described 3′ and 5′ stem-loop motifs, and provide evidence for a third, structurally well-conserved domain

PETcofold: predicting conserved interactions and structures of two multiple alignments of RNA sequences

Motivation: Predicting RNA–RNA interactions is essential for determining the function of putative non-coding RNAs. Existing methods for the prediction of interactions are all based on single sequences. Since comparative methods have already been useful in RNA structure determination, we assume that conserved RNA–RNA interactions also imply conserved function. Of these, we further assume that a non-negligible amount of the existing RNA–RNA interactions have also acquired compensating base changes throughout evolution. We implement a method, PETcofold, that can take covariance information in intra-molecular and inter-molecular base pairs into account to predict interactions and secondary structures of two multiple alignments of RNA sequences

Genomic basis of a social polymorphism in a halictid bee

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RNAalifold: improved consensus structure prediction for RNA alignments

<p>Abstract</p> <p>Background</p> <p>The 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.</p> <p>Results</p> <p>We 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.</p> <p>Conclusion</p> <p>The 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.</p

Genomic and transcriptomic changes complement each other in the pathogenesis of sporadic Burkitt lymphoma

Burkitt lymphoma (BL) is the most common B-cell lymphoma in children. Within the International Cancer Genome Consortium (ICGC), we performed whole genome and transcriptome sequencing of 39 sporadic BL. Here, we unravel interaction of structural, mutational, and transcriptional changes, which contribute to MYC oncogene dysregulation together with the pathognomonic IG-MYC translocation. Moreover, by mapping IGH translocation breakpoints, we provide evidence that the precursor of at least a subset of BL is a B-cell poised to express IGHA. We describe the landscape of mutations, structural variants, and mutational processes, and identified a series of driver genes in the pathogenesis of BL, which can be targeted by various mechanisms, including IG-non MYC translocations, germline and somatic mutations, fusion transcripts, and alternative splicing

The genomic and transcriptional landscape of primary central nervous system lymphoma

Primary lymphomas of the central nervous system (PCNSL) are mainly diffuse large B-cell lymphomas (DLBCLs) confined to the central nervous system (CNS). Molecular drivers of PCNSL have not been fully elucidated. Here, we profile and compare the whole-genome and transcriptome landscape of 51 CNS lymphomas (CNSL) to 39 follicular lymphoma and 36 DLBCL cases outside the CNS. We find recurrent mutations in JAK-STAT, NFkB, and B-cell receptor signaling pathways, including hallmark mutations in MYD88 L265P (67%) and CD79B (63%), and CDKN2A deletions (83%). PCNSLs exhibit significantly more focal deletions of HLA-D (6p21) locus as a potential mechanism of immune evasion. Mutational signatures correlating with DNA replication and mitosis are significantly enriched in PCNSL. TERT gene expression is significantly higher in PCNSL compared to activated B-cell (ABC)-DLBCL. Transcriptome analysis clearly distinguishes PCNSL and systemic DLBCL into distinct molecular subtypes. Epstein-Barr virus (EBV)+ CNSL cases lack recurrent mutational hotspots apart from IG and HLA-DRB loci. We show that PCNSL can be clearly distinguished from DLBCL, having distinct expression profiles, IG expression and translocation patterns, as well as specific combinations of genetic alterations