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Supplemental Digital Content is available in the text., Rationale: Gene expression profiles have been mainly determined by analysis of transcript abundance. However, these analyses cannot capture posttranscriptional gene expression control at the level of translation, which is a key step in the regulation of gene expression, as evidenced by the fact that transcript levels often poorly correlate with protein levels. Furthermore, genome-wide transcript profiling of distinct cell types is challenging due to the fact that lysates from tissues always represent a mixture of cells. Objectives: This study aimed to develop a new experimental method that overcomes both limitations and to apply this method to perform a genome-wide analysis of gene expression on the translational level in response to pressure overload. Methods and Results: By combining ribosome profiling (Ribo-seq) with a ribosome-tagging approach (Ribo-tag), it was possible to determine the translated transcriptome in specific cell types from the heart. After pressure overload, we monitored the cardiac myocyte translatome by purifying tagged cardiac myocyte ribosomes from cardiac lysates and subjecting the ribosome-protected mRNA fragments to deep sequencing. We identified subsets of mRNAs that are regulated at the translational level and found that translational control determines early changes in gene expression in response to cardiac stress in cardiac myocytes. Translationally controlled transcripts are associated with specific biological processes related to translation, protein quality control, and metabolism. Mechanistically, Ribo-seq allowed for the identification of upstream open reading frames in transcripts, which we predict to be important regulators of translation. Conclusions: This method has the potential to (1) provide a new tool for studying cell-specific gene expression at the level of translation in tissues, (2) reveal new therapeutic targets to prevent cellular remodeling, and (3) trigger follow-up studies that address both, the molecular mechanisms involved in the posttranscriptional control of gene expression in cardiac cells, and the protective functions of proteins expressed in response to cellular stress.

Circular RNAs (circRNAs) are abundant and accumulate with age in neurons of diverse species. However, only few circRNAs have been functionally characterized, and their role during aging has not been addressed. Here, we use transcriptome profiling during aging and find that accumulation of circRNAs is slowed down in long-lived insulin mutant flies. Next, we characterize the in vivo function of a circRNA generated by the sulfateless gene (circSfl), which is consistently upregulated, particularly in the brain and muscle, of diverse long-lived insulin mutants. Strikingly, lifespan extension of insulin mutants is dependent on circSfl, and overexpression of circSfl alone is sufficient to extend the lifespan. Moreover, circSfl is translated into a protein that shares the N terminus and potentially some functions with the full-length Sfl protein encoded by the host gene. Our study demonstrates that insulin signaling affects global circRNA accumulation and reveals an important role of circSfl during aging in vivo.

Background RNA-binding proteins (RBPs) are fundamental regulators of cellular biology that affect all steps in the generation and processing of RNA molecules. Recent evidence suggests that regulation of RBPs that modulate both RNA stability and translation may have a profound effect on the proteome. However, regulation of RBPs in clinically relevant experimental conditions has not been studied systematically. Methods We used RNA interactome capture, a method for the global identification of RBPs to characterize the global RNA‐binding proteome (RBPome) associated with polyA-tailed RNA species in murine ciliated epithelial cells of the inner medullary collecting duct. To study regulation of RBPs in a clinically relevant condition, we analyzed hypoxia-associated changes of the RBPome. Results We identified >1000 RBPs that had been previously found using other systems. In addition, we found a number of novel RBPs not identified by previous screens using mouse or human cells, suggesting that these proteins may be specific RBPs in differentiated kidney epithelial cells. We also found quantitative differences in RBP-binding to mRNA that were associated with hypoxia versus normoxia. Conclusions These findings demonstrate the regulation of RBPs through environmental stimuli and provide insight into the biology of hypoxia-response signaling in epithelial cells in the kidney. A repository of the RBPome and proteome in kidney tubular epithelial cells, derived from our findings, is freely accessible online, and may contribute to a better understanding of the role of RNA-protein interactions in kidney tubular epithelial cells, including the response of these cells to hypoxia.

CircRNAs are a subgroup of RNAs which form a circular molecule. During the splicing process the 3’ splice donor loops back to form a covalent bond with an upstream 5’ splice acceptor instead of the downstream 5’ acceptor. The majority of circRNAs are non-coding splice isoforms of protein coding genes showing tissue and time specific expression. Because circRNAs have no 5’ cap nor 3’ poly-A tail, they degrade slower than their linear host genes. Only few studies were able to show a specific function for circRNAs.In this work we sequenced 23 samples from three tissues (brain, muscle, and gut) at three (two for gut) time points throughout the life of the naturally short-lived African turquoise killifish (Nothobranchius furzeri). We identified 1810 unique circRNAs, half of which are conserved with humans and mice. With this study we provide a comprehensive atlas to the circRNA landscape in the ageing African turquoise killifish, which serves as a novel resource to the circRNA as well as the ageing community.

RHOA is a member of the Rho family of GTPases that are involved in fundamental cellular processes including cell adhesion, migration, and proliferation. RHOA can stimulate the formation of stress fibers and focal adhesions and is a key regulator of actomyosin dynamics in various tissues. In a Genematcher-facilitated collaboration, we were able to identify four unrelated individuals with a specific phenotype characterized by hypopigmented areas of the skin, dental anomalies, body asymmetry, and limb length discrepancy due to hemihypotrophy of one half of the body, as well as brain magnetic resonance imaging (MRI) anomalies. Using whole-exome and ultra-deep amplicon sequencing and comparing genomic data of affected and unaffected areas of the skin, we discovered that all four individuals carried the identical RHOA missense variant, c.139G>A; p.Glu47Lys, in a postzygotic state. Molecular modeling and in silico analysis of the affected p.Glu47Lys residue in RHOA indicated that this exchange is predicted to specifically alter the interaction of RHOA with its downstream effectors containing a PKN-type binding domain and thereby disrupts its ability to activate signaling. Our findings indicate that the recurrent postzygotic RHOA missense variant p.Glu47Lys causes a specific mosaic disorder in humans. peerReviewed

Rationale: Endoplasmic reticulum (ER) stress dysregulates ER proteostasis, which activates the transcription factor, ATF6 (activating transcription factor 6α), an inducer of genes that enhance protein folding and restore ER proteostasis. Because of increased protein synthesis, it is possible that protein folding and ER proteostasis are challenged during cardiac myocyte growth. However, it is not known whether ATF6 is activated, and if so, what its function is during hypertrophic growth of cardiac myocytes. Objective: To examine the activity and function of ATF6 during cardiac hypertrophy. Methods and Results: We found that ER stress and ATF6 were activated and ATF6 target genes were induced in mice subjected to an acute model of transverse aortic constriction, or to free-wheel exercise, both of which promote adaptive cardiac myocyte hypertrophy with preserved cardiac function. Cardiac myocyte-specific deletion of Atf6 (ATF6 cKO [conditional knockout]) blunted transverse aortic constriction and exercise-induced cardiac myocyte hypertrophy and impaired cardiac function, demonstrating a role for ATF6 in compensatory myocyte growth. Transcript profiling and chromatin immunoprecipitation identified RHEB (Ras homologue enriched in brain) as an ATF6 target gene in the heart. RHEB is an activator of mTORC1 (mammalian/mechanistic target of rapamycin complex 1), a major inducer of protein synthesis and subsequent cell growth. Both transverse aortic constriction and exercise upregulated RHEB , activated mTORC1, and induced cardiac hypertrophy in wild type mouse hearts but not in ATF6 cKO hearts. Mechanistically, knockdown of ATF6 in neonatal rat ventricular myocytes blocked phenylephrine- and IGF1 (insulin-like growth factor 1)-mediated RHEB induction, mTORC1 activation, and myocyte growth, all of which were restored by ectopic RHEB expression. Moreover, adeno-associated virus 9- RHEB restored cardiac growth to ATF6 cKO mice subjected to transverse aortic constriction. Finally, ATF6 induced RHEB in response to growth factors, but not in response to other activators of ATF6 that do not induce growth, indicating that ATF6 target gene induction is stress specific. Conclusions: Compensatory cardiac hypertrophy activates ER stress and ATF6, which induces RHEB and activates mTORC1. Thus, ATF6 is a previously unrecognized link between growth stimuli and mTORC1-mediated cardiac growth.

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m 6 A is the most abundant internal modification on mRNA. Recent improvements of high-throughput sequencing techniques enables its detection at the transcriptome level, even at the nucleotide resolution. However most current techniques require large amounts of starting material to detect the modification. Here, we describe a complementary technique of standard meRIP-seq/miCLIP-seq approaches to identify methylated RNA using a low amount of material. We believe this approach can be applied in vivo to identify methylated targets in specific tissues or subpopulations of cells.

Objective A vast amount of medical data is still stored in unstructured text documents. We present an automated method of information extraction from German unstructured clinical routine data from the cardiology domain enabling their usage in state-of-the-art data-driven deep learning projects. Methods We evaluated pre-trained language models to extract a set of 12 cardiovascular concepts in German discharge letters. We compared three bidirectional encoder representations from transformers pre-trained on different corpora and fine-tuned them on the task of cardiovascular concept extraction using 204 discharge letters manually annotated by cardiologists at the University Hospital Heidelberg. We compared our results with traditional machine learning methods based on a long short-term memory network and a conditional random field. Results Our best performing model, based on publicly available German pre-trained bidirectional encoder representations from the transformer model, achieved a token-wise micro-average F1-score of 86% and outperformed the baseline by at least 6%. Moreover, this approach achieved the best trade-off between precision (positive predictive value) and recall (sensitivity). Conclusion Our results show the applicability of state-of-the-art deep learning methods using pre-trained language models for the task of cardiovascular concept extraction using limited training data. This minimizes annotation efforts, which are currently the bottleneck of any application of data-driven deep learning projects in the clinical domain for German and many other European languages.

Motivation Metabolic labelling of RNA is a well-established and powerful method to estimate RNA synthesis and decay rates. The pulseR R package simplifies the analysis of RNA-seq count data that emerge from corresponding pulse-chase experiments. Results The pulseR package provides a flexible interface and readily accommodates numerous different experimental designs. To our knowledge, it is the first publicly available software solution that models count data with the more appropriate negative-binomial model. Moreover, pulseR handles labelled and unlabelled spike-in sets in its workflow and accounts for potential labeling biases (e.g. number of uridine residues). Availability and implementation The pulseR package is freely available at https://github.com/dieterich-lab/pulseR under the GPLv3.0 licence. Supplementary information Supplementary data are available at Bioinformatics online.

Circular RNAs (circRNAs) are a recent addition to the expanding universe of RNA species and originate through back-splicing events from linear primary transcripts. CircRNAs show specific expression profiles with regards to cell type and developmental stage. Importantly, only few circRNAs have been functionally characterized to date. The detection of circRNAs from RNA sequencing data is a complex computational workflow that, depending on tissue and condition typically yields candidate sets of hundreds or thousands of circRNA candidates. Here, we provide an overview on different computational analysis tools and pipelines that became available throughout the last years. We outline technical and experimental requirements that are common to all approaches and point out potential pitfalls during the computational analysis. Although computational prediction of circRNAs has become quite mature in recent years, we provide a set of valuable validation strategies, in silico as well as in vitro-based approaches. In addition to circRNA detection via back-splicing junction, we present available analysis pipelines for delineating the primary sequence and for predicting possible functions of circRNAs. Finally, we outline the most important web resources for circRNA research. This article is categorized under: RNA Methods > RNA Analyses in vitro and In Silico RNA Evolution and Genomics > Computational Analyses of RNA.

Background Huntington’s Disease (HD), is a hereditary, fatal neurodegenerative disorder due to CAG trinucleotide expansion in exon 1 of the HD gene (HTT). Recent findings revealed that the process of alternative splicing (AS) might be compromised in HD. AS regulation is crucial not only to the establishment of a repertoire of protein coding isoforms extremely relevant for the proper physiological characteristics of the nervous system, but also to the biogenesis of circular RNAs (circRNAs), unusually stable, highly expressed non-coding RNAs produced by the circularization of exons which, seems to have important roles during neuronal development and functioning. Aims Therefore, the overarching goal of our research was to take advantage of genetically engineered Htt knock-in (KI) mouse cellular and in vivo model systems bearing normal or pathological Htt CAG repeat lengths to discover alterations in linear and back-splicing events that might reflect on the levels of expression as well as the composition of a repertoire of proteins, thus contributing to HD striatal vulnerability and pathogenesis. Methods/techniques To discover alterations in linear splicing, we resourced to a publicly available dataset (Langfelder P. et al., 2016, Nature Neuroscience) analyzing full transcriptomic profiling dataset for striatum, cortex and liver at different developmental time points, identifying and quantifying the total numbers of differential AS events for each genotype/sample type and time point. Results/outcome Our analysis demonstrated that specifically for the striatum – most vulnerable to HD degeneration – the total number of detected, differential AS events increased significantly at 6 and 10 month with increasing CAG expansion. Interestingly, not all the AS events increased with CAG-expansion and age, but only a specific subtype of AS event – EXON SKIPPING – revealed to be strongly and specifically affected. On the other hand, we identified and characterized the first circular RNA originating locally from the HTT locus, expressed in whole body, but predominantly in the brain and spinal cord and presenting augmented expression level with increasing HTT CAG size. Moreover, at genome-wide level, data analysis of circRNA-seq showed a decreased circRNAs production when mutant huntingtin is expressed. Specifically, 12 circRNAs, identified by stringent cut-off criteria, showed continuous decreased expression following CAG expansion in neuronal progenitor cells. Since, most of the CAG-sensitive circRNAs have annotated human orthologues, their expression can be further characterized and functionally studied in human cell lines. Conclusions In conclusion, our results support the idea that AS machinery is responding to HD mutational process altering both linear and back-splicing events locally at the HTT locus, but also at genome-wide level. This knowledge will pave the way to new trials of therapeutic intervention aimed to possibly target spliceosomal-circRNAs alterations through specific drugs or genetic manipulation.

Medical texts are a vast resource for medical and computational research. In contrast to newswire or wikipedia texts medical texts need to be de-identified before making them accessible to a wider NLP research community. We created a prototype for German medical text de-identification and named entity recognition using a three-step approach. First, we used well known rule-based models based on regular expressions and gazetteers, second we used a spelling variant detector based on Levenshtein distance, exploiting the fact that the medical texts contain semi-structured headers including sensible personal data, and third we trained a named entity recognition model on out of domain data to add statistical capabilities to our prototype. Using a baseline based on regular expressions and gazetteers we could improve F2-score from 78% to 85% for de-identification. Our prototype is a first step for further research on German medical text de-identification and could show that using spelling variant detection and out of domain trained statistical models can improve de-identification performance significantly.

Down-regulation of cardiac inotropic EF-hand calcium sensor protein S100A1 expression is a hallmark of human heart failure and drives progression and mortality. An AAV-S100A1 gene replacement therapy, which has been shown in preclinical models to rescue chronic heart failure, is in preparation for first clinical trials. However, the nuclear mechanisms that convey S100A1 gene locus silencing in the failing heart have not been determined yet. Given the steady increase of S100A1 expression in the developing heart until young adulthood and its decrease in the aged and failing heart, we developed a novel approach to decipher the mechanisms of S100a1 transcriptional regulation. We performed serial RNAseq analyses in an in vitro cardiac differentiation model of H9c2 cells that displays robust concurrent S100A1 and e.g. sarcoplasmic reticulum calcium ATPase 2 (SERCA2a) mRNA and protein during differentiation. Potential transcription factors (TF) were derived by computational motif analysis from S100A1’s gene locus regulatory elements that delivered more than 200 candidates. Subsequent computational TF footprint binding motive analysis from all differentially expressed transcripts of the serial RNAseq data provided a smaller group of less than 30 putatively TF families in the cH9C2 model that is actively during the in vitro biological process. Additional comparative TF expression analyses with developing rat hearts then enabled subtraction of a final TF group of 10 members for RNA interference screens in the cH9C2 model using S100A1 RNA expression as a read-out. Using a siRNA-mediated TF knock-down screen, we identified a small group of TFs such as zink finger and coiled-coil TFs (e.g. KLFs) and signal transducer and activator of transcription (STATs) TFs with an hitherto unknown ability to independently regulate S100A1 expression. Of note, other inotropic factors such as SERCA2a were found to be positively co-regulated by some of the TFs, such as KLFs, that enhance S100A1 expression. Further analyses were performed to confirm these results. In summary, we present a feasible computational filter and experimental strategy to identify relevant TF networks which we have successfully applied to identify cardiac regulatory networks.

Motivation Circular RNAs (circRNAs) originate through back-splicing events from linear primary transcripts, are resistant to exonucleases, are not polyadenylated and have been shown to be highly specific for cell type and developmental stage. CircRNA detection starts from high-throughput sequencing data and is a multi-stage bioinformatics process yielding sets of potential circRNA candidates that require further analyses. While a number of tools for the prediction process already exist, publicly available analysis tools for further characterization are rare. Our work provides researchers with a harmonized workflow that covers different stages of in silico circRNA analyses, from prediction to first functional insights. Results Here, we present circtools, a modular, Python-based framework for computational circRNA analyses. The software includes modules for circRNA detection, internal sequence reconstruction, quality checking, statistical testing, screening for enrichment of RBP binding sites, differential exon RNase R resistance and circRNA-specific primer design. circtools supports researchers with visualization options and data export into commonly used formats. Availability and implementation circtools is available via https://github.com/dieterich-lab/circtools and http://circ.tools under GPLv3.0. Supplementary information Supplementary data are available at Bioinformatics online.

Summary Introduction: This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. HiGHmed brings together 24 partners from academia and industry, aiming at improvements in care provision, biomedical research and epidemiology. By establishing a shared information governance framework, data integration centers and an open platform architecture in cooperation with independent healthcare providers, the meaningful reuse of data will be facilitated. Complementary, HiGHmed integrates a total of seven Medical Informatics curricula to develop collaborative structures and processes to train medical informatics professionals, physicians and researchers in new forms of data analytics. Governance and Policies: We describe governance structures and policies that have proven effective during the conceptual phase. These were further adapted to take into account the specific needs of the development and networking phase, such as roll-out, carerelated aspects and our focus on curricula development in Medical Inform atics. Architectural Framework and Methodology: To address the challenges of organizational, technical and semantic interoperability, a concept for a scalable platform architecture, the HiGHmed Platform, was developed. We outline the basic principles and design goals of the open platform approach as well as the roles of standards and specifications such as IHE XDS, openEHR, SNOMED CT and HL7 FHIR. A shared governance framework provides the semantic artifacts which are needed to establish semantic interoperability. Use Cases: Three use cases in the fields of oncology, cardiology and infection control will demonstrate the capabilities of the HiGHmed approach. Each of the use cases entails diverse challenges in terms of data protection, privacy and security, including clinical use of genome sequencing data (oncology), continuous longitudinal monitoring of physical activity (cardiology) and cross-site analysis of patient movement data (infection control). Discussion: Besides the need for a shared governance framework and a technical infrastructure, backing from clinical leaders is a crucial factor. Moreover, firm and sustainable commitment by participating organizations to collaborate in further development of their information system architectures is needed. Other challenges including topics such as data quality, privacy regulations, and patient consent will be addressed throughout the project.

Aims Circulating immune cells have a significant impact on progression and outcome of heart failure. Long non-coding RNAs (lncRNAs) comprise novel epigenetic regulators which control cardiovascular diseases and inflammatory disorders. We aimed to identify lncRNAs regulated in circulating immune cells of the blood of heart failure patients. Methods and results Next-generation sequencing revealed 110 potentially non-coding RNA transcripts differentially expressed in peripheral blood mononuclear cells of heart failure patients with reduced ejection fraction. The up-regulated lncRNA Heat2 was further functionally characterized. Heat2 expression was detected in whole blood, PBMNCs, eosinophil and basophil granulocytes. Heat2 regulates cell division, invasion, transmigration and immune cell adhesion on endothelial cells. Conclusion Heat2 is an immune cell enriched lncRNA that is elevated in the blood of heart failure patients and controls cellular functions.

Aberrant synaptic function is thought to underlie social deficits in neurodevelopmental disorders such as autism and schizophrenia. Although microRNAs have been shown to regulate synapse development and plasticity, their potential involvement in the control of social behaviour in mammals remains unexplored. Here, we show that deletion of the placental mammal‐specific miR379‐410 cluster in mice leads to hypersocial behaviour, which is accompanied by increased excitatory synaptic transmission, and exaggerated expression of ionotropic glutamate receptor complexes in the hippocampus. Bioinformatic analyses further allowed us to identify five “hub” microRNAs whose deletion accounts largely for the upregulation of excitatory synaptic genes observed, including Cnih2, Dlgap3, Prr7 and Src. Thus, the miR379‐410 cluster acts a natural brake for sociability, and interfering with specific members of this cluster could represent a therapeutic strategy for the treatment of social deficits in neurodevelopmental disorders.

International audience; Recently discovered new chemical entities in RNA modifications have involved surprising functional groups that enlarge the chemical space of RNA. Using LC-MS, we found over 100 signals of RNA constituents that contained a ribose moiety in tRNAs from E. coli. Feeding experiments with variegated stable isotope labeled compounds identified 37 compounds that are new structures of RNA modifications. One structure was elucidated by deuterium exchange and high-resolution mass spectrometry. The structure of msms2 i6 A (2-methylthiomethylenethio-N6-isopentenyl-adenosine) was confirmed by methione-D3 feeding experiments and by synthesis of the nucleobase. The msms2 i6 A contains a thioacetal, shown in vitro to be biosynthetically derived from ms2 i6 A by the radical-SAM enzyme MiaB. This enzyme performs thiomethylation, forming ms2 i6 A from i6 A in a first turnover. The new thioacetal is formed by a second turnover. Along with the pool of 36 new modifications, this work describes a new layer of RNA modification chemistry.

Circular RNAs (circRNAs) have been first described as "scrambled exons" in the 1990s. CircRNAs originate from back splicing or exon skipping of linear RNA templates and have continuously gained attention in recent years due to the availability of high-throughput whole-transcriptome sequencing methods. Numerous manuscripts describe thousands of circRNAs throughout uni- and multicellular eukaryote species and demonstrated that they are conserved, stable, and abundant in specific tissues or conditions. This manuscript provides a walk-through of our bioinformatics toolbox, which covers all aspects of in silico circRNA analysis, starting from raw sequencing data and back-splicing junction discovery to circRNA quantitation and reconstruction of internal the circRNA structure.

Circular RNAs (circRNAs) have been first described as "scrambled exons" in the 1990s. CircRNAs originate from back splicing or exon skipping of linear RNA templates and have continuously gained attention in recent years due to the availability of high-throughput whole-transcriptome sequencing methods. Numerous manuscripts describe thousands of circRNAs throughout uni- and multicellular eukaryote species and demonstrated that they are conserved, stable, and abundant in specific tissues or conditions. This manuscript provides a walk-through of our bioinformatics toolbox, which covers all aspects of in silico circRNA analysis, starting from raw sequencing data and back-splicing junction discovery to circRNA quantitation and reconstruction of internal the circRNA structure.

Gene expression profiling provides a tool to analyze the internal states of cells or organisms, and their responses to perturbations. While global measurements of mRNA levels have thus been widely used for many years, it is only through the recent development of the ribosome profiling technique that an analogous examination of global mRNA translation programs has become possible. Ribosome profiling reveals which RNAs are being translated to what extent and where the translated open reading frames are located. In addition, different modes of translation regulation can be distinguished and characterized. Here, we present an optimized, step-by-step protocol for ribosome profiling. Although established in Caenorhabditis elegans, our protocol and optimization approaches should be equally usable for other model organisms or cell culture with little adaptation. Next to providing a protocol, we compare two different methods for isolation of single ribosomes and two different library preparations, and describe strategies to optimize the RNase digest and to reduce ribosomal RNA contamination in the libraries. Moreover, we discuss bioinformatic strategies to evaluate the quality of the data and explain how the data can be analyzed for different applications. In sum, this article seeks to facilitate the understanding, execution, and optimization of ribosome profiling experiments.

In metazoan cells, spliced mRNAs are marked by the exon junction complex (EJC), a multi-protein complex that serves as a key regulator of post-transcriptional mRNA metabolism. Deposition of EJCs on mRNA is intimately linked to the splicing process. The spliceosomal protein CWC22 directly binds the core EJC-protein eIF4A3, guides it to the spliceosome and initiates EJC assembly. In addition, CWC22 is involved in the splicing process itself, but the molecular details of its dual function remain elusive. Here we analyze the mechanisms, by which CWC22 co-regulates pre-mRNA splicing and EJC assembly. We show that the core of CWC22 is sufficient to mediate both pre-mRNA splicing and EJC assembly. Nonetheless, both processes can be functionally uncoupled with an eIF4A3-binding deficient mutant of CWC22, which impedes EJC assembly. A C-terminal domain of CWC22 strongly enhances its spliceosomal interaction and likely regulates its function. High-throughput RNA-sequencing identifies global defects of pre-mRNA splicing and downregulation of diverse gene expression pathways in CWC22-depleted cells. We propose a model, in which CWC22 represents an integral component of the spliceosome and orchestrates pre-mRNA splicing and eIF4A3 binding to achieve global assembly of exon junction complexes.

Mitofusin 2 plays an unexpected role in maintaining the terpenoid biosynthesis pathway and is necessary for mitochondrial coenzyme Q biosynthesis., Mitochondria form a dynamic network within the cell as a result of balanced fusion and fission. Despite the established role of mitofusins (MFN1 and MFN2) in mitochondrial fusion, only MFN2 has been associated with metabolic and neurodegenerative diseases, which suggests that MFN2 is needed to maintain mitochondrial energy metabolism. The molecular basis for the mitochondrial dysfunction encountered in the absence of MFN2 is not understood. Here we show that loss of MFN2 leads to impaired mitochondrial respiration and reduced ATP production, and that this defective oxidative phosphorylation process unexpectedly originates from a depletion of the mitochondrial coenzyme Q pool. Our study unravels an unexpected and novel role for MFN2 in maintenance of the terpenoid biosynthesis pathway, which is necessary for mitochondrial coenzyme Q biosynthesis. The reduced respiratory chain function in cells lacking MFN2 can be partially rescued by coenzyme Q10 supplementation, which suggests a possible therapeutic strategy for patients with diseases caused by mutations in the Mfn2 gene.

A disturbed inflammatory response following myocardial infarction (MI) is associated with poor prognosis and increased tissue damage. Monocytes are key players in healing after MI, but little is known about the role of the cardiac niche in monocyte activation. This study investigated microenvironment‐dependent changes in inflammatory monocytes after MI. RNA sequencing analysis of murine Ly6C high monocytes on day 3 after MI revealed differential regulation depending on location. Notably, the local environment strongly impacted components of the WNT signaling cascade. Analysis of WNT modulators revealed a strong upregulation of WNT Inhibitory Factor 1 (WIF1) in cardiomyocytes—but not fibroblasts or endothelial cells—upon hypoxia. Compared to wild‐type (WT) littermates, WIF1 knockout mice showed severe adverse remodeling marked by increased scar size and reduced ejection fraction 4 weeks after MI. While FACS analysis on day 1 after MI revealed no differences in neutrophil numbers, the hearts of WIF1 knockouts contained significantly more inflammatory monocytes than hearts from WT animals. Next, we induced AAV‐mediated cardiomyocyte‐specific WIF1 overexpression, which attenuated the monocyte response and improved cardiac function after MI, as compared to control‐AAV‐treated animals. Finally, WIF1 overexpression in isolated cardiomyocytes limited the activation of non‐canonical WNT signaling and led to reduced IL‐1β and IL‐6 expression in monocytes/macrophages. Taken together, we investigated the cardiac microenvironment9s interaction with recruited monocytes after MI and identified a novel mechanism of monocyte activation. The local initiation of non‐canonical WNT signaling shifts the accumulating myeloid cells toward a pro‐inflammatory state and impacts healing after myocardial infarction.

Introduction: The mTOR kinase links nutrient and growth factor signaling to cell growth by controlling mRNA translation, but the role of translationally controlled networks during cardiac stress remains unknown. We hypothesized that activation of mTOR controls translation of networks of mRNAs, independent from transcription, to rapidly adapt gene expression to physiologic and pathologic stress. We tested this hypothesis by monitoring the transcriptome and the translatome after pharmacologic and genetic inhibition of mTOR in cardiac myocytes. Methods and Results: To define the mTOR-dependent translatome, we performed ribosome profiling after pharmacologic mTOR inhibition by Torin1. We found 166 decreased and 199 unchanged mRNAs that we used for further analysis. Among the decreased mRNAs, 17% have a known TOP or TOP like motif in the 5’UTR, explaining why mTOR inhibition selectively suppresses their translation. Gene ontology analyses of Torin1-suppressed mRNAs showed enrichment for genes involved in translation and metabolism. P roline -r ich A KT s ubstrate of 40 kDa (Pras40) inhibits mTORC1 activity. In vivo, mTOR inhibition by overexpression of Pras40 blocked pathologic growth, and improved cardiac function after transverse aortic constriction (TAC). Conversely, in a cardiomyocyte-specific Pras40 knock-out mouse, heart function was reduced and growth response attenuated after TAC surgery. Similarly, physiological heart growth was inhibited after Pras40 deletion. Mechanistically and in line with the pharmacologic results, global translation rates were decreased after Pras40 depletion. Mass-spectrometric analysis identified ribonucleoproteins, ribosomal proteins and chaperones as Pras40 interaction partners, suggesting a direct function in the protein synthesis and folding machinery downstream of mTOR. Monitoring the translatome in vivo after Pras40 depletion using a ribosome tagging approach, followed by ribosome profiling, identified the mTOR-dependent translatome. Conclusions: mTOR-dependent translational control might represent a crucial way of controlling gene expression during stress in the myocardium. Once elucidated, mTOR-based therapies could be a powerful approach to prevent worsening of cardiac function.

Aims Cardiovascular disease, one of the most common causes of death in western populations, is characterized by changes in RNA splicing and expression. Circular RNAs (circRNA) originate from back-splicing events, which link a downstream 5′ splice site to an upstream 3′ splice site. Several back-splicing junctions (BSJ) have been described in heart biopsies from human, rat and mouse hearts (Werfel et al., 2016; Jakobi et al., 2016 ). Here, we use human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) to identify circRNA and host gene dynamics in cardiac development and disease. In parallel, we explore candidate interactions of selected homologs in mouse and rat via RIP-seq experiments. Methods and Results Deep RNA sequencing of cardiomyocyte development and β-adrenergic stimulation uncovered 4518 circRNAs. The set of circular RNA host genes is enriched for chromatin modifiers and GTPase activity regulators. RNA-seq and qRT-PCR data showed that circular RNA expression is highly dynamic in the hiPSC-CM model with 320 circRNAs showing significant expression changes. Intriguingly, 82 circRNAs are independently regulated to their host genes. We validated the same circRNA dynamics for circRNAs from ATXN10 , CHD7 , DNAJC6 and SLC8A1 in biopsy material from human dilated cardiomyopathy (DCM) and control patients. Finally, we could show that rodent homologs of circMYOD, circSLC8A1, circATXN7 and circPHF21A interact with either the ribosome or Argonaute2 protein complexes. Conclusion CircRNAs are dynamically expressed in a hiPSC-CM model of cardiac development and stress response. Some circRNAs show similar, host-gene independent expression dynamics in patient samples and may interact with the ribosome and RISC complex. In summary, the hiPSC-CM model uncovered a new signature of potentially disease relevant circRNAs which may serve as novel therapeutic targets.

BackgroundParasites can either respond to differences in immune defenses that exist between individual hosts plastically or, alternatively, follow a genetically canalized (“hard wired”) program of infection. Assuming that large-scale functional plasticity would be discernible in the parasite transcriptome we have performed a dual RNA-seq study of the full lifecycle ofEimeria falciformisusing infected mice with different immune status (e.g. naïve versus immune animals) as models for coccidian infections.ResultsWe compared parasite and host transcriptomes (dual transcriptome) between naïve and challenge infected mice, as well as between immune competent and immune deficient ones. Mice with different immune competence show transcriptional differences as well as differences in parasite reproduction (oocyst shedding). Broad gene categories represented by differently abundant host genes indicate enrichments for immune reaction and tissue repair functions. More specifically, TGF-beta, EGF, TNF and IL-1 and IL-6 are examples of functional annotations represented differently depending on host immune status. Much in contrast, parasite transcriptomes were neither different between Coccidia isolated from immune competent and immune deficient mice, nor between those harvested from naïve and challenge infected mice. Instead, parasite transcriptomes have distinct profiles early and late in infection, characterized largely by biosynthesis or motility associated functional gene groups, respectively. Extracellular sporozoite and oocyst stages showed distinct transcriptional profiles and sporozoite transcriptomes were found enriched for species specific genes and likely pathogenicity factors.ConclusionWe propose that the niche and host-specific parasiteE. falciformisuses a genetically canalized program of infection. This program is likely fixed in an evolutionary process rather than employing phenotypic plasticity to interact with its host. In turn this might (negatively) influence the ability of the parasite to use different host species and (positively or negatively) influence its evolutionary potential for adaptation to different hosts or niches.

While the transcriptional network of human embryonic stem cells (hESCs) has been extensively studied, relatively little is known about how post-transcriptional modulations determine hESC function. RNA-binding proteins play central roles in RNA regulation, including translation and turnover. Here we show that the RNA-binding protein CSDE1 (cold shock domain containing E1) is highly expressed in hESCs to maintain their undifferentiated state and prevent default neural fate. Notably, loss of CSDE1 accelerates neural differentiation and potentiates neurogenesis. Conversely, ectopic expression of CSDE1 impairs neural differentiation. We find that CSDE1 post-transcriptionally modulates core components of multiple regulatory nodes of hESC identity, neuroectoderm commitment and neurogenesis. Among these key pro-neural/neuronal factors, CSDE1 binds fatty acid binding protein 7 (FABP7) and vimentin (VIM) mRNAs, as well as transcripts involved in neuron projection development regulating their stability and translation. Thus, our results uncover CSDE1 as a central post-transcriptional regulator of hESC identity and neurogenesis., Unlike transcriptional regulation of hESC identity, little is known post-transcriptionally. Here, the authors show that the RNA binding protein CSDE1 regulates core components of hESC identity, neurectoderm commitment and neurogenesis to maintain pluripotency and prevent neural differentiation.

Knowledge about the nature of pathomolecular alterations preceding onset of symptoms in amyotrophic lateral sclerosis is largely lacking. It could not only pave the way for the discovery of valuable therapeutic targets but might also govern future concepts of pre-manifest disease modifying treatments. MicroRNAs are central regulators of transcriptome plasticity and participate in pathogenic cascades and/or mirror cellular adaptation to insults. We obtained comprehensive expression profiles of microRNAs in the serum of patients with familial amyotrophic lateral sclerosis, asymptomatic mutation carriers and healthy control subjects. We observed a strikingly homogenous microRNA profile in patients with familial amyotrophic lateral sclerosis that was largely independent from the underlying disease gene. Moreover, we identified 24 significantly downregulated microRNAs in pre-manifest amyotrophic lateral sclerosis mutation carriers up to two decades or more before the estimated time window of disease onset; 91.7% of the downregulated microRNAs in mutation carriers overlapped with the patients with familial amyotrophic lateral sclerosis. Bioinformatic analysis revealed a consensus sequence motif present in the vast majority of downregulated microRNAs identified in this study. Our data thus suggest specific common denominators regarding molecular pathogenesis of different amyotrophic lateral sclerosis genes. We describe the earliest pathomolecular alterations in amyotrophic lateral sclerosis mutation carriers known to date, which provide a basis for the discovery of novel therapeutic targets and strongly argue for studies evaluating presymptomatic disease-modifying treatment in amyotrophic lateral sclerosis.

Motivation: The identification of active transcriptional regulatory elements is crucial to understand regulatory networks driving cellular processes such as cell development and the onset of diseases. It has recently been shown that chromatin structure information, such as DNase I hypersensitivity (DHS) or histone modifications, significantly improves cell-specific predictions of transcription factor binding sites. However, no method has so far successfully combined both DHS and histone modification data to perform active binding site prediction. Results: We propose here a method based on hidden Markov models to integrate DHS and histone modifications occupancy for the detection of open chromatin regions and active binding sites. We have created a framework that includes treatment of genomic signals, model training and genome-wide application. In a comparative analysis, our method obtained a good trade-off between sensitivity versus specificity and superior area under the curve statistics than competing methods. Moreover, our technique does not require further training or sequence information to generate binding location predictions. Therefore, the method can be easily applied on new cell types and allow flexible downstream analysis such as de novo motif finding. Availability and implementation: Our framework is available as part of the Regulatory Genomics Toolbox. The software information and all benchmarking data are available at http://costalab.org/wp/dh-hmm . Contact: ivan.costa@rwth-aachen.de or eduardo.gusmao@rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.

RNA helicases are important regulators of gene expression that act by remodeling RNA secondary structures and RNA-protein interactions. Here, we demonstrate that MOV10 has an ATP-dependent 5' to 3' in vitro RNA unwinding activity and determine the RNA-binding sites of MOV10 and its helicase mutants using PAR-CLIP. We find that MOV10 predominantly binds to 3' UTRs upstream of regions predicted to form local secondary structures and provide evidence that MOV10 helicase mutants are impaired in their ability to translocate 5' to 3' on their mRNA targets. MOV10 interacts with UPF1, the key component of the nonsense-mediated mRNA decay pathway. PAR-CLIP of UPF1 reveals that MOV10 and UPF1 bind to RNA in close proximity. Knockdown of MOV10 resulted in increased mRNA half-lives of MOV10-bound as well as UPF1-regulated transcripts, suggesting that MOV10 functions in UPF1-mediated mRNA degradation as an RNA clearance factor to resolve structures and displace proteins from 3' UTRs.

The hermaphroditic nematode Pristionchus pacificus is an established model system for comparative studies with Caenorhabditis elegans in developmental biology, ecology, and population genetics. In this study, we present whole-genome sequencing data of 104 P. pacificus strains and the draft assembly of the obligate outcrossing sister species P. exspectatus. We characterize genetic diversity within P. pacificus and investigate the population genetic processes shaping this diversity. P. pacificus is 10 times more diverse than C. elegans and exhibits substantial population structure that allows us to probe its evolution on multiple timescales. Consistent with reduced effective recombination in this self-fertilizing species, we find haplotype blocks that span several megabases. Using the P. exspectatus genome as an outgroup, we polarized variation in P. pacificus and found a site frequency spectrum (SFS) that decays more rapidly than expected in neutral models. The SFS at putatively neutral sites is U shaped, which is a characteristic feature of pervasive linked selection. Based on the additional findings (i) that the majority of nonsynonymous variation is eliminated over timescales on the order of the separation between clades, (ii) that diversity is reduced in gene-rich regions, and (iii) that highly differentiated clades show very similar patterns of diversity, we conclude that purifying selection on many mutations with weak effects is a major force shaping genetic diversity in P. pacificus.

A key prerequisite to understand how gene regulatory processes are controlled by the interplay of RNA-binding proteins (RBPs) and ribonucleoprotein complexes with RNAs is the generation of comprehensive high-resolution maps of protein-RNA interactions. Recent advances in next-generation sequencing technology accelerated the development of various crosslinking and immunoprecipitation (CLIP) approaches to broadly identify RNA regions contacted by RNA-binding proteins. However these methods only consider single RNA-binding proteins and their contact sites, irrespective of the overall cis-regulatory sequence space contacted by other RNA interacting factors. Here we describe the application of protein occupancy profiling, a novel approach that globally displays the RNA contact sites of the poly(A)+ RNA-bound proteome. Protein occupancy profiling enables the generation of transcriptome-wide maps of protein-RNA interactions on polyadenylated transcripts and narrows the sequence search space for transcript regions involved in cis-regulation of gene expression in response to internal or external stimuli, altered cellular programs or disease.

Motivation High-throughput sequencing machines can process many samples in a single run. For Illumina systems, sequencing reads are barcoded with an additional DNA tag that is contained in the respective sequencing adapters. The recognition of barcode and adapter sequences is hence commonly needed for the analysis of next-generation sequencing data. Flexbar performs demultiplexing based on barcodes and adapter trimming for such data. The massive amounts of data generated on modern sequencing machines demand that this preprocessing is done as efficiently as possible. Results We present Flexbar 3.0, the successor of the popular program Flexbar. It employs now twofold parallelism: multi-threading and additionally SIMD vectorization. Both types of parallelism are used to speed-up the computation of pair-wise sequence alignments, which are used for the detection of barcodes and adapters. Furthermore, new features were included to cover a wide range of applications. We evaluated the performance of Flexbar based on a simulated sequencing dataset. Our program outcompetes other tools in terms of speed and is among the best tools in the presented quality benchmark. Availability and implementation https://github.com/seqan/flexbar

RNA modifications regulate the complex life of transcripts. An experimental approach called LAIC-seq was developed to characterize modification levels on a transcriptome-wide scale. In this method, the modified and unmodified molecules are separated using antibodies specific for a given RNA modification (e.g., m6A). In essence, the procedure of biochemical separation yields three fractions: Input, eluate, and supernatent, which are subjected to RNA-seq. In this work, we present a bioinformatics workflow, which starts from RNA-seq data to infer gene-specific modification levels by a statistical model on a transcriptome-wide scale. Our workflow centers around the pulseR package, which was originally developed for the analysis of metabolic labeling experiments. We demonstrate how to analyze data without external normalization (i.e., in the absence of spike-ins), given high efficiency of separation, and how, alternatively, scaling factors can be derived from unmodified spike-ins. Importantly, our workflow provides an estimate of uncertainty of modification levels in terms of confidence intervals for model parameters, such as gene expression and RNA modification levels. We also compare alternative model parametrizations, log-odds, or the proportion of the modified molecules and discuss the pros and cons of each representation. In summary, our workflow is a versatile approach to RNA modification level estimation, which is open to any read-count-based experimental approach.

Motivation: Circular RNAs (circRNAs) are a poorly characterized class of molecules that have been identified decades ago. Emerging high-throughput sequencing methods as well as first reports on confirmed functions have sparked new interest in this RNA species. However, the computational detection and quantification tools are still limited. Results: We developed the software tandem, DCC and CircTest. DCC uses output from the STAR read mapper to systematically detect back-splice junctions in next-generation sequencing data. DCC applies a series of filters and integrates data across replicate sets to arrive at a precise list of circRNA candidates. We assessed the detection performance of DCC on a newly generated mouse brain data set and publicly available sequencing data. Our software achieves a much higher precision than state-of-the-art competitors at similar sensitivity levels. Moreover, DCC estimates circRNA versus host gene expression from counting junction and non-junction reads. These read counts are finally used to test for host gene-independence of circRNA expression across different experimental conditions by our R package CircTest. We demonstrate the benefits of this approach on previously reported age-dependent circRNAs in the fruit fly. Availability and implementation: The source code of DCC and CircTest is licensed under the GNU General Public Licence (GPL) version 3 and available from https://github.com/dieterich-lab/[DCC or CircTest]. Contact: christoph.dieterich@age.mpg.de Supplementary information: Supplementary data are available at Bioinformatics online.

The Berlin Fat Mouse Inbred (BFMI) line harbors a major recessive gene defect on chromosome 3 (jobes1) leading to juvenile obesity and metabolic syndrome. The present study aimed at the identification of metabolites that might be linked to recessively acting genes in the obesity locus. Firstly, serum metabolites were analyzed between obese BFMI and lean B6 and BFMI × B6 F1 mice to identify metabolites that are different. In a second step, a metabolite–protein network analysis was performed linking metabolites typical for BFMI mice with genes of the jobes1 region. The levels of 22 diacyl-phosphatidylcholines (PC aa), two lyso-PC and three carnitines were found to be significantly lower in obese mice compared with lean mice, while serine, glycine, arginine and hydroxysphingomyelin were higher for the same comparison. The network analysis identified PC aa C42:1 as functionally linked with the genes Ccna2 and Trpc3 via the enzymes choline kinase alpha and phospholipase A2 group 1B (PLA2G1B), respectively. Gene expression analysis revealed elevated Ccna2 expression in adipose tissue of BFMI mice. Furthermore, unique mutations were found in the Ccna2 promoter of BFMI mice which are located in binding sites for transcription factors or micro RNAs and could cause differential Ccna2 mRNA levels between BFMI and B6 mice. Increased expression of Ccna2 was consistent with higher mitotic activity of adipose tissue in BFMI mice. Therefore, we suggest a higher demand for PC necessary for adipose tissue growth and remodeling. This study highlights the relationship between metabolite profiles and the underlying genetics of obesity in the BFMI line. Electronic supplementary material The online version of this article (doi:10.1007/s11306-013-0590-1) contains supplementary material, which is available to authorized users.

MicroRNAs (miRNAs) constitute an important class of small regulatory RNAs that are derived from distinct hairpin precursors (pre-miRNAs). In contrast to mature miRNAs, which have been characterized in numerous genome-wide studies of different organisms, research on global profiling of pre-miRNAs is limited. Here, using massive parallel sequencing, we have performed global characterization of both mouse mature and precursor miRNAs. In total, 87 369 704 and 252 003 sequencing reads derived from 887 mature and 281 precursor miRNAs were obtained, respectively. Our analysis revealed new aspects of miRNA/pre-miRNA processing and modification, including eight Ago2-cleaved pre-miRNAs, eight new instances of miRNA editing and exclusively 5' tailed mirtrons. Furthermore, based on the sequences of both mature and precursor miRNAs, we developed a miRNA discovery pipeline, miRGrep, which does not rely on the availability of genome reference sequences. In addition to 239 known mouse pre-miRNAs, miRGrep predicted 41 novel ones with high confidence. Similar as known ones, the mature miRNAs derived from most of these novel loci showed both reduced abundance following Dicer knockdown and the binding with Argonaute2. Evaluation on data sets obtained from Caenorhabditis elegans and Caenorhabditis sp.11 demonstrated that miRGrep could be widely used for miRNA discovery in metazoans, especially in those without genome reference sequences.

Quantitative and systems biology approaches benefit from the unprecedented depth of next-generation sequencing. A typical experiment yields millions of short reads, which oftentimes carry particular sequence tags. These tags may be: (a) specific to the sequencing platform and library construction method (e.g., adapter sequences); (b) have been introduced by experimental design (e.g., sample barcodes); or (c) constitute some biological signal (e.g., splice leader sequences in nematodes). Our software FLEXBAR enables accurate recognition, sorting and trimming of sequence tags with maximal flexibility, based on exact overlap sequence alignment. The software supports data formats from all current sequencing platforms, including color-space reads. FLEXBAR maintains read pairings and processes separate barcode reads on demand. Our software facilitates the fine-grained adjustment of sequence tag detection parameters and search regions. FLEXBAR is a multi-threaded software and combines speed with precision. Even complex read processing scenarios might be executed with a single command line call. We demonstrate the utility of the software in terms of read mapping applications, library demultiplexing and splice leader detection. FLEXBAR and additional information is available for academic use from the website: http://sourceforge.net/projects/flexbar/.

Background RNA editing is a co-transcriptional modification that increases the molecular diversity, alters secondary structure and protein coding sequences by changing the sequence of transcripts. The most common RNA editing modification is the single base substitution (A→I) that is catalyzed by the members of the Adenosine deaminases that act on RNA (ADAR) family. Typically, editing sites are identified as RNA-DNA-differences (RDDs) in a comparison of genome and transcriptome data from next-generation sequencing experiments. However, a method for robust detection of site-specific editing events from replicate RNA-seq data has not been published so far. Even more surprising, condition-specific editing events, which would show up as differences in RNA-RNA comparisons (RRDs) and depend on particular cellular states, are rarely discussed in the literature. Results We present JACUSA, a versatile one-stop solution to detect single nucleotide variant positions from comparing RNA-DNA and/or RNA-RNA sequencing samples. The performance of JACUSA has been carefully evaluated and compared to other variant callers in an in silico benchmark. JACUSA outperforms other algorithms in terms of the F measure, which combines precision and recall, in all benchmark scenarios. This performance margin is highest for the RNA-RNA comparison scenario. We further validated JACUSA’s performance by testing its ability to detect A→I events using sequencing data from a human cell culture experiment and publicly available RNA-seq data from Drosophila melanogaster heads. To this end, we performed whole genome and RNA sequencing of HEK-293 cells on samples with lowered activity of candidate RNA editing enzymes. JACUSA has a higher recall and comparable precision for detecting true editing sites in RDD comparisons of HEK-293 data. Intriguingly, JACUSA captures most A→I events from RRD comparisons of RNA sequencing data derived from Drosophila and HEK-293 data sets. Conclusion Our software JACUSA detects single nucleotide variants by comparing data from next-generation sequencing experiments (RNA-DNA or RNA-RNA). In practice, JACUSA shows higher recall and comparable precision in detecting A→I sites from RNA-DNA comparisons, while showing higher precision and recall in RNA-RNA comparisons. Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-1432-8) contains supplementary material, which is available to authorized users.

Aims: In this study, we aimed to clinically and genetically characterize LVNC patients and investigate the prevalence of variants in known and novel LVNC disease genes. Introduction: Left ventricular non-compaction cardiomyopathy (LVNC) is an increasingly recognized cause of heart failure, arrhythmia, thromboembolism, and sudden cardiac death. We sought here to dissect its genetic causes, phenotypic presentation and outcome. Methods and results: In our registry with follow-up of in the median 61 months, we analysed 95 LVNC patients (68 unrelated index patients and 27 affected relatives; definite familial LVNC = 23.5%) by cardiac phenotyping, molecular biomarkers and exome sequencing. Cardiovascular events were significantly more frequent in LVNC patients compared with an age-matched group of patients with non-ischaemic dilated cardiomyopathy (hazard ratio = 2.481, P = 0.002). Stringent genetic classification according to ACMG guidelines revealed that TTN, LMNA, and MYBPC3 are the most prevalent disease genes (13 patients are carrying a pathogenic truncating TTN variant, odds ratio = 40.7, Confidence interval = 21.6-76.6, P

Tissue mechanics drive morphogenesis, but how forces are sensed and transmitted to control stem cell fate and self-organization remains unclear. We show that a mechanosensory complex of emerin (Emd), non-muscle myosin IIA (NMIIA) and actin controls gene silencing and chromatin compaction, thereby regulating lineage commitment. Force-driven enrichment of Emd at the outer nuclear membrane of epidermal stem cells leads to defective heterochromatin anchoring to the nuclear lamina and a switch from H3K9me2,3 to H3K27me3 occupancy at constitutive heterochromatin. Emd enrichment is accompanied by the recruitment of NMIIA to promote local actin polymerization that reduces nuclear actin levels, resulting in attenuation of transcription and subsequent accumulation of H3K27me3 at facultative heterochromatin. Perturbing this mechanosensory pathway by deleting NMIIA in mouse epidermis leads to attenuated H3K27me3-mediated silencing and precocious lineage commitment, abrogating morphogenesis. Our results reveal how mechanics integrate nuclear architecture and chromatin organization to control lineage commitment and tissue morphogenesis.

Human embryonic stem cells can replicate indefinitely while maintaining their undifferentiated state and, therefore, are immortal in culture. This capacity may demand avoidance of any imbalance in protein homeostasis (proteostasis) that would otherwise compromise stem cell identity. Here we show that human pluripotent stem cells exhibit enhanced assembly of the TRiC/CCT complex, a chaperonin that facilitates the folding of 10% of the proteome. We find that ectopic expression of a single subunit (CCT8) is sufficient to increase TRiC/CCT assembly. Moreover, increased TRiC/CCT complex is required to avoid aggregation of mutant Huntingtin protein. We further show that increased expression of CCT8 in somatic tissues extends Caenorhabditis elegans lifespan in a TRiC/CCT-dependent manner. Ectopic expression of CCT8 also ameliorates the age-associated demise of proteostasis and corrects proteostatic deficiencies in worm models of Huntington's disease. Our results suggest proteostasis is a common principle that links organismal longevity with hESC immortality., Pluripotent stem cells are thought to require a highly active proteostatic machinery. Here, the authors show that CCT8, a subunit of the proteostatic chaperonin complex, is increased in pluripotent stem cells, and that overexpression of CCT8 in worms increases cellular proteostasis and organismal longevity.

The interpretation of genome-wide association study is difficult, as it is hard to understand how polymorphisms can affect gene regulation, in particular for trans-regulatory elements located far from their controlling gene. Using RNA or protein expression data as phenotypes, it is possible to correlate their variations with specific genotypes. This technique is usually referred to as expression Quantitative Trait Loci (eQTLs) analysis and only few packages exist for the integration of genotype patterns and expression profiles. In particular, tools are needed for the analysis of next-generation sequencing (NGS) data on a genome-wide scale, which is essential to identify eQTLs able to control a large number of genes (hotspots). Here we present SPIRE (Software for Polymorphism Identification Regulating Expression), a generic, modular and functionally highly flexible pipeline for eQTL processing. SPIRE integrates different univariate and multivariate approaches for eQTL analysis, paying particular attention to the scalability of the procedure in order to support cis- as well as trans-mapping, thus allowing the identification of hotspots in NGS data. In particular, we demonstrated how SPIRE can handle big association study datasets, reproducing published results and improving the identification of trans-eQTLs. Furthermore, we employed the pipeline to analyse novel data concerning the genotypes of two different C. elegans strains (N2 and Hawaii) and related miRNA expression data, obtained using RNA-Seq. A miRNA regulatory hotspot was identified in chromosome 1, overlapping the transcription factor grh-1, known to be involved in the early phases of embryonic development of C. elegans. In a follow-up qPCR experiment we were able to verify most of the predicted eQTLs, as well as to show, for a novel miRNA, a significant difference in the sequences of the two analysed strains of C. elegans. SPIRE is publicly available as open source software at https://bitbucket.org/bereste/spire, together with some example data, a readme file, supplementary material and a short tutorial.

The biodiversity of the RNA world has been underestimated for decades. RNA molecules are key building blocks, sensors, and regulators of modern cells. The biological function of RNA molecules cannot be separated from their ability to bind to and interact with a wide space of chemical species, including small molecules, nucleic acids, and proteins. Computational chemists, physicists, and biologists have developed a rich tool set for modeling and predicting RNA interactions. These interactions are to some extent determined by the binding conformation of the RNA molecule. RNA binding conformations are approximated with often acceptable accuracy by sequence and secondary structure motifs. Secondary structure ensembles of a given RNA molecule can be efficiently computed in many relevant situations by employing a standard energy model for base pair interactions and dynamic programming techniques. The case of bi-molecular RNA-RNA interactions can be seen as an extension of this approach. However, unbiased transcriptome-wide scans for local RNA-RNA interactions are computationally challenging yet become efficient if the binding motif/mode is known and other external information can be used to confine the search space. Computational methods are less developed for proteins and small molecules, which bind to RNA with very high specificity. Binding descriptors of proteins are usually determined by in vitro high-throughput assays (e.g., microarrays or sequencing). Intriguingly, recent experimental advances, which are mostly based on light-induced cross-linking of binding partners, render in vivo binding patterns accessible yet require new computational methods for careful data interpretation. The grand challenge is to model the in vivo situation where a complex interplay of RNA binders competes for the same target RNA molecule. Evidently, bioinformaticians are just catching up with the impressive pace of these developments.

Protein-RNA interactions are fundamental to core biological processes, such as mRNA splicing, localization, degradation, and translation. We developed a photoreactive nucleotide-enhanced UV crosslinking and oligo(dT) purification approach to identify the mRNA-bound proteome using quantitative proteomics and to display the protein occupancy on mRNA transcripts by next-generation sequencing. Application to a human embryonic kidney cell line identified close to 800 proteins. To our knowledge, nearly one-third were not previously annotated as RNA binding, and about 15% were not predictable by computational methods to interact with RNA. Protein occupancy profiling provides a transcriptome-wide catalog of potential cis-regulatory regions on mammalian mRNAs and showed that large stretches in 3' UTRs can be contacted by the mRNA-bound proteome, with numerous putative binding sites in regions harboring disease-associated nucleotide polymorphisms. Our observations indicate the presence of a large number of mRNA binders with diverse molecular functions participating in combinatorial posttranscriptional gene-expression networks.

The nematode Pristionchus pacificus shows two forms of phenotypic plasticity: dauer formation and dimorphism of mouth form morphologies. It can therefore serve as a model for studying the evolutionary mechanisms that underlie phenotypic plasticity. Formation of dauer larvae is observed in many other species and constitutes one of the most crucial survival strategies in nematodes, whereas the mouth form dimorphism is an evolutionary novelty observed only in P. pacificus and related nematodes. We have previously shown that the same environmental cues and steroid signaling control both dauer formation and mouth form dimorphism. Here, we examine by mutational analysis and whole-genome sequencing the function of P. pacificus (Ppa) daf-16, which encodes a forkhead transcription factor; in C. elegans, daf-16 is the target of insulin signaling and plays important roles in dauer formation. We found that mutations in Ppa-daf-16 cause strong dauer formation-defective phenotypes, suggesting that Ppa-daf-16 represents one of the evolutionarily conserved regulators of dauer formation. Upon strong dauer induction with lophenol, Ppa-daf-16 individuals formed arrested larvae that partially resemble wild-type dauer larvae, indicating that Ppa-daf-16 is also required for dauer morphogenesis. By contrast, regulation of mouth form dimorphism was unaffected by Ppa-daf-16 mutations and mutant animals responded normally to environmental cues. Our results suggest that mechanisms for dauer formation and mouth form regulation overlap partially, but not completely, and one of two key transcriptional regulators of the dauer regulatory network was either independently co-opted for, or subsequently lost by, the mouth form regulatory network.

Levels of residual structure in disordered interaction domains determine in vitro binding affinities, but whether they exert similar roles in cells is not known. Here, we show that increasing residual p53 helicity results in stronger Mdm2 binding, altered p53 dynamics, impaired target gene expression and failure to induce cell cycle arrest upon DNA damage. These results establish that residual structure is an important determinant of signaling fidelity in cells.