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Summary: The serine-/arginine-rich splicing factor 2 (SRSF2) plays pivotal roles in pre-mRNA processing and gene transcription. Recurrent mutations, particularly a proline-to-histidine substitution at position 95 (P95H), are common in neoplastic diseases. Here, we assess SRSF2’s diverse functions in squamous cell carcinoma. We show that SRSF2 deletion or homozygous P95H mutation both cause extensive DNA damage leading to cell-cycle arrest. Mechanistically, SRSF2 regulates efficient bi-directional transcription of DNA replication and repair genes, independent from its function in splicing. Further, SRSF2 haploinsufficiency induces DNA damage without halting the cell cycle. Exposing mouse skin to tumor-promoting carcinogens enhances the clonal expansion of heterozygous Srsf2 P95H epidermal cells but unexpectedly inhibits tumor formation. To survive carcinogen treatment, Srsf2 P95H+/− cells undergo substantial transcriptional rewiring and restore bi-directional gene expression. Thus, our study underscores SRSF2’s importance in regulating transcription to orchestrate the cell cycle and the DNA damage response.

Abstract Direct RNA sequencing offers the possibility to simultaneously identify canonical bases and epi-transcriptomic modifications in each single RNA molecule. Thus far, the development of computational methods has been hampered by the lack of biologically realistic training data that carries modification labels at molecular resolution. Here, we report on the synthesis of such samples and the development of a bespoke algorithm, mAFiA (m6A Finding Algorithm), that accurately detects single m6A nucleotides in both synthetic RNAs and natural mRNA on single read level. Our approach uncovers distinct modification patterns in single molecules that would appear identical at the ensemble level. Compared to existing methods, mAFiA also demonstrates improved accuracy in measuring site-level m6A stoichiometry in biological samples.

Summary: The human transcriptome predominantly consists of noncoding RNAs (ncRNAs), transcripts that do not encode proteins. The noncoding transcriptome governs a multitude of pathophysiological processes, offering a rich source of next-generation biomarkers. Toward achieving a holistic view of disease, the integration of these transcripts with clinical records and additional data from omic technologies (“multiomic” strategies) has motivated the adoption of artificial intelligence (AI) approaches. Given their intricate biological complexity, machine learning (ML) techniques are becoming a key component of ncRNA-based research. This article presents an overview of the potential and challenges associated with employing AI/ML-driven approaches to identify clinically relevant ncRNA biomarkers and to decipher ncRNA-associated pathogenetic mechanisms. Methodological and conceptual constraints are discussed, along with an exploration of ethical considerations inherent to AI applications for healthcare and research. The ultimate goal is to provide a comprehensive examination of the multifaceted landscape of this innovative field and its clinical implications.

Ribosomal RNAs are decorated by numerous post-transcriptional modifications whose exact roles in ribosome biogenesis, function, and human pathophysiology remain largely unknown. Here, we report a targeted direct rRNA sequencing approach involving a substrate selection step and demonstrate its suitability to identify differential modification sites in combination with the JACUSA2 software. We compared JACUSA2 to other tools designed for RNA modification detection and show that JACUSA2 outperforms other software with regard to detection of base modifications such as methylation, acetylation and aminocarboxypropylation. To illustrate its widespread usability, we applied our method to a collection of CRISPR-Cas9 engineered colon carcinoma cells lacking specific enzymatic activities responsible for particular rRNA modifications and systematically compared them to isogenic wild-type RNAs. Besides the numerous 2′-O methylated riboses and pseudouridylated residues, our approach was suitable to reliably identify differential base methylation and acetylation events. Importantly, our method does not require any prior knowledge of modification sites or the need to train complex models. We further report for the first time detection of human rRNA modifications by direct RNA-sequencing on Flongle flow cells, the smallest-scale nanopore flow cell available to date. The use of these smaller flow cells reduces RNA input requirements, making our workflow suitable for the analysis of samples with limited availability and clinical work.

Abstract Internal modifications of mRNA have emerged as widespread and versatile regulatory mechanism to control gene expression at the post-transcriptional level. Most of these modifications are methyl groups, making S-adenosyl-L-methionine (SAM) a central metabolic hub. Here we show that metabolic labeling with a clickable metabolic precursor of SAM, propargyl-selenohomocysteine (PSH), enables detection and identification of various methylation sites. Propargylated A, C, and G nucleosides form at detectable amounts via intracellular generation of the corresponding SAM analogue. Integration into next generation sequencing enables mapping of N 6-methyladenosine (m6A) and 5-methylcytidine (m5C) sites in mRNA with single nucleotide precision (MePMe-seq). Analysis of the termination profiles can be used to distinguish m6A from 2′-O-methyladenosine (Am) and N1-methyladenosine (m1A) sites. MePMe-seq overcomes the problems of antibodies for enrichment and sequence-motifs for evaluation, which was limiting previous methodologies. Metabolic labeling via clickable SAM facilitates the joint evaluation of methylation sites in RNA and potentially DNA and proteins.

Abstract Dilated cardiomyopathy is the second most common cause for heart failure with no cure except a high-risk heart transplantation. Approximately 30% of patients harbor heritable mutations which are amenable to CRISPR-based gene therapy. However, challenges related to delivery of the editing complex and off-target concerns hamper the broad applicability of CRISPR agents in the heart. We employ a combination of the viral vector AAVMYO with superior targeting specificity of heart muscle tissue and CRISPR base editors to repair patient mutations in the cardiac splice factor Rbm20, which cause aggressive dilated cardiomyopathy. Using optimized conditions, we repair >70% of cardiomyocytes in two Rbm20 knock-in mouse models that we have generated to serve as an in vivo platform of our editing strategy. Treatment of juvenile mice restores the localization defect of RBM20 in 75% of cells and splicing of RBM20 targets including TTN. Three months after injection, cardiac dilation and ejection fraction reach wild-type levels. Single-nuclei RNA sequencing uncovers restoration of the transcriptional profile across all major cardiac cell types and whole-genome sequencing reveals no evidence for aberrant off-target editing. Our study highlights the potential of base editors combined with AAVMYO to achieve gene repair for treatment of hereditary cardiac diseases.

Abstract We present CARDIO:DE, the first freely available and distributable large German clinical corpus from the cardiovascular domain. CARDIO:DE encompasses 500 clinical routine German doctor’s letters from Heidelberg University Hospital, which were manually annotated. Our prospective study design complies well with current data protection regulations and allows us to keep the original structure of clinical documents consistent. In order to ease access to our corpus, we manually de-identified all letters. To enable various information extraction tasks the temporal information in the documents was preserved. We added two high-quality manual annotation layers to CARDIO:DE, (1) medication information and (2) CDA-compliant section classes. To the best of our knowledge, CARDIO:DE is the first freely available and distributable German clinical corpus in the cardiovascular domain. In summary, our corpus offers unique opportunities for collaborative and reproducible research on natural language processing models for German clinical texts.

Alternative splicing (AS) appears to be altered in Huntington's disease (HD), but its significance for early, pre-symptomatic disease stages has not been inspected. Here, taking advantage of Htt CAG knock-in mouse in vitro and in vivo models, we demonstrate a correlation between Htt CAG repeat length and increased aberrant linear AS, specifically affecting neural progenitors and, in vivo, the striatum prior to overt behavioral phenotypes stages. Remarkably, a significant proportion (36%) of the aberrantly spliced isoforms are not-functional and meant to non-sense mediated decay (NMD). The expanded Htt CAG repeats further reflect on a previously neglected, global impairment of back-splicing, leading to decreased circular RNAs production in neural progenitors. Integrative transcriptomic analyses unveil a network of transcriptionally altered micro-RNAs and RNA-binding proteins (Celf, hnRNPs, Ptbp, Srsf, Upf1, Ythd2) which might influence the AS machinery, primarily in neural cells. We suggest that this unbalanced expression of linear and circular RNAs might alter neural fitness, contributing to HD pathogenesis.

Abstract Background Despite a recent increase in the number of RNA-seq datasets investigating heart failure (HF), accessibility and usability remain critical issues for medical researchers. We address the need for an intuitive and interactive web application to explore the transcriptional signatures of heart failure with this work. Methods We reanalysed the Myocardial Applied Genomics Network RNA-seq dataset, one of the largest publicly available datasets of left ventricular RNA-seq samples from patients with dilated (DCM) or hypertrophic (HCM) cardiomyopathy, as well as unmatched non-failing hearts (NFD) from organ donors and patient characteristics that allowed us to model confounding factors. We analyse differential gene expression, associated pathway signatures and reconstruct signaling networks based on inferred transcription factor activities through integer linear programming. We additionally focus, for the first time, on differential RNA transcript isoform usage (DTU) changes and predict RNA-binding protein (RBP) to target transcript interactions using a Global test approach. We report results for all pairwise comparisons (DCM, HCM, NFD). Results Focusing on the DCM versus HCM contrast (DCMvsHCM), we identified 201 differentially expressed genes, some of which can be clearly associated with changes in ERK1 and ERK2 signaling. Interestingly, the signs of the predicted activity for these two kinases have been inferred to be opposite to each other: In the DCMvsHCM contrast, we predict ERK1 to be consistently less activated in DCM while ERK2 was more activated in DCM. In the DCMvsHCM contrast, we identified 149 differently used transcripts. One of the top candidates is the O-linked N-acetylglucosamine (GlcNAc) transferase (OGT), which catalyzes a common post-translational modification known for its role in heart arrhythmias and heart hypertrophy. Moreover, we reconstruct RBP – target interaction networks and showcase the examples of CPEB1, which is differentially expressed in the DCMvsHCM contrast. Conclusion Magnetique ( https://shiny.dieterichlab.org/app/magnetique ) is the first online application to provide an interactive view of the HF transcriptome at the RNA isoform level and to include transcription factor signaling and RBP:RNA interaction networks. The source code for both the analyses ( https://github.com/dieterich-lab/magnetiqueCode2022 ) and the web application ( https://github.com/AnnekathrinSilvia/magnetique ) is available to the public. We hope that our application will help users to uncover the molecular basis of heart failure.

Abstract Circular RNAs (circRNAs) are regulators of processes like adipogenesis. Their expression can be modulated by SNPs. We analysed links between BMI-associated SNPs and circRNAs. First, we detected an enrichment of BMI-associated SNPs on circRNA genomic loci in comparison to non-significant variants. Analysis of sex-stratified GWAS data revealed that circRNA genomic loci encompassed more genome-wide significant BMI-SNPs in females than in males. To explore whether the enrichment is restricted to BMI, we investigated nine additional GWAS studies. We showed an enrichment of trait-associated SNPs in circRNAs for four analysed phenotypes (body height, chronic kidney disease, anorexia nervosa and autism spectrum disorder). To analyse the influence of BMI-affecting SNPs on circRNA levels in vitro, we examined rs4752856 located on hsa_circ_0022025. The analysis of heterozygous individuals revealed an increased level of circRNA derived from the BMI-increasing SNP allele. We conclude that genetic variation may affect the BMI partly through circRNAs.

Abstract Several high-throughput antibody-free methods for RNA modification detection from sequencing data have been developed. We present JACUSA2 as a versatile software solution and comprehensive analysis framework for RNA modification detection assays that are based on either the Illumina or Nanopore platform. Importantly, JACUSA2 can integrate information from multiple experiments, such as replicates and different conditions, and different library types, such as first- or second-strand cDNA libraries. We demonstrate its utility, showing analysis workflows for N6-methyladenosine (m6A) and pseudouridine (Ψ) detection on Illumina and Nanopore sequencing data sets. Our software and its R helper package are available as open source solutions.

Abstract Gene expression dysregulation in the brain has been associated with bipolar disorder, but little is known about the role of non-coding RNAs. Circular RNAs are a novel class of long noncoding RNAs that have recently been shown to be important in brain development and function. However, their potential role in psychiatric disorders, including bipolar disorder, has not been well investigated. In this study, we profiled circular RNAs in the brain tissue of individuals with bipolar disorder. Total RNA sequencing was initially performed in samples from the anterior cingulate cortex of a cohort comprised of individuals with bipolar disorder (N = 13) and neurotypical controls (N = 13) and circular RNAs were identified and analyzed using “circtools”. Significant circular RNAs were validated by RT-qPCR and replicated in the anterior cingulate cortex in an independent cohort (24 bipolar disorder cases and 27 controls). In addition, we conducted in vitro studies using B-lymphoblastoid cells collected from bipolar cases (N = 19) and healthy controls (N = 12) to investigate how circular RNAs respond following lithium treatment. In the discovery RNA sequencing analysis, 26 circular RNAs were significantly differentially expressed between bipolar disorder cases and controls (FDR

The noncoding RNA RN7SK regulates RNA polymerase II pausing and splicing. Here the authors deplete RN7SK in mouse and human during epidermal stem cell differentiation and reveal a novel role in orchestrating bidirectional transcription of highly expressed gene pairs.

Degradation of nonsense mediated mRNA decay (NMD) substrates is carried out by two seemingly independent pathways, SMG6-mediated endonucleolytic cleavage and/or SMG5-SMG7-induced accelerated deadenylation. Here the authors show that SMG5-SMG7 maintain NMD activity by permitting SMG6 activation.

We introduce Single-cell Nanopore Spatial Transcriptomics (scNaST), a software suite to facilitate the analysis of spatial gene expression from second- and third-generation sequencing, allowing to generate a full-length near-single-cell transcriptional landscape of the tissue microenvironment. Taking advantage of the Visium Spatial platform, we adapted a strategy recently developed to assign barcodes to long-read single-cell sequencing data for spatial capture technology. Here, we demonstrate our workflow using four short axis sections of the mouse heart following myocardial infarction. We constructed a de novo transcriptome using long-read data, and successfully assigned 19,794 transcript isoforms in total, including clinically-relevant, but yet uncharacterized modes of transcription, such as intron retention or antisense overlapping transcription. We showed a higher transcriptome complexity in the healthy regions, and identified intron retention as a mode of transcription associated with the infarct area. Our data revealed a clear regional isoform switching among differentially used transcripts for genes involved in cardiac muscle contraction and tissue morphogenesis. Molecular signatures involved in cardiac remodeling integrated with morphological context may support the development of new therapeutics towards the treatment of heart failure and the reduction of cardiac complications.

Recently, circular RNAs (circRNAs) have been extensively studied in animals and plants. circRNAs are generated by backsplicing from the same linear transcripts that are canonically spliced to produce, for example, mature mRNAs. circRNAs exhibit tissue-specific expression and are potentially involved in many diseases, among them cardiovascular diseases. The comprehensive analysis of circRNA expression patterns across larger patient cohorts requires a streamlined and cost-effective workflow designed to meet small input requirements. In this article, we present Lexo-circSeq, a targeted RNA sequencing approach that can profile up to 110 circRNAs and their corresponding linear transcripts in one experiment. We established Lexo-circSeq employing total human heart RNA and show that our protocol can detect depletion of a specific circRNA in hiPSC-derived cardiomyocytes. Finally, Lexo-circSeq was applied to biopsies from patients diagnosed with dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM), respectively. Interestingly, our results indicate that circular-to-linear-ratios for circSLC8A1 and circRBM33 are deregulated in cardiomyopathy.

Alternative RNA splicing varies across the brain. Its mapping at single cell resolution is unclear. Here, the authors provide a spatial and single-cell splicing atlas reporting brain region- and cell type-specific expression of different isoforms in the postnatal mouse brain.

Summary: To identify cellular mechanisms responsible for pressure overload triggered heart failure, we isolated cardiomyocytes, endothelial cells, and fibroblasts as most abundant cell types from mouse hearts in the subacute and chronic stages after transverse aortic constriction (TAC) and performed RNA-sequencing. We detected highly cell-type specific transcriptional responses with characteristic time courses and active intercellular communication. Cardiomyocytes after TAC exerted an early and sustained upregulation of inflammatory and matrix genes and a concomitant suppression of metabolic and ion channel genes. Fibroblasts, in contrast, showed transient early upregulation of inflammatory and matrix genes and downregulation of angiogenesis genes, but sustained induction of cell cycle and ion channel genes during TAC. Endothelial cells transiently induced cell cycle and extracellular matrix genes early after TAC, but exerted a long-lasting upregulation of inflammatory genes. As we found that matrix production by multiple cell types triggers pathological cellular responses, it might serve as a future therapeutic target.

The proper development and function of neuronal circuits rely on a tightly regulated balance between excitatory and inhibitory (E/I) synaptic transmission, and disrupting this balance can cause neurodevelopmental disorders, for example, schizophrenia. MicroRNA-dependent gene regulation in pyramidal neurons is important for excitatory synaptic function and cognition, but its role in inhibitory interneurons is poorly understood. Here, we identify miR138-5p as a regulator of short-term memory and inhibitory synaptic transmission in the mouse hippocampus. Sponge-mediated miR138-5p inactivation specifically in mouse parvalbumin (PV)-expressing interneurons impairs spatial recognition memory and enhances GABAergic synaptic input onto pyramidal neurons. Cellular and behavioral phenotypes associated with miR138-5p inactivation are paralleled by an upregulation of the schizophrenia (SCZ)-associated Erbb4, which we validated as a direct miR138-5p target gene. Our findings suggest that miR138-5p is a critical regulator of PV interneuron function in mice, with implications for cognition and SCZ. More generally, they provide evidence that microRNAs orchestrate neural circuit development by fine-tuning both excitatory and inhibitory synaptic transmission.

Despite widespread transcription of LncRNA in mammalian systems, their contribution to metabolic homeostasis at the cellular and tissue level remains elusive. Here Pradas-Juni et al. describe a transcription factor–LncRNA pathway that couples hepatocyte nutrient sensing to regulation of glucose metabolism in mice.

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.

In the adult heart, the epicardium becomes activated after injury, contributing to cardiac healing by secretion of paracrine factors. Here, we analyzed by single-cell RNA sequencing combined with RNA in situ hybridization and lineage tracing of Wilms tumor protein 1-positive (WT1+) cells, the cellular composition, location, and hierarchy of epicardial stromal cells (EpiSC) in comparison to activated myocardial fibroblasts/stromal cells in infarcted mouse hearts. We identified 11 transcriptionally distinct EpiSC populations, which can be classified into three groups, each containing a cluster of proliferating cells. Two groups expressed cardiac specification markers and sarcomeric proteins suggestive of cardiomyogenic potential. Transcripts of hypoxia-inducible factor (HIF)-1α and HIF-responsive genes were enriched in EpiSC consistent with an epicardial hypoxic niche. Expression of paracrine factors was not limited to WT1+ cells but was a general feature of activated cardiac stromal cells. Our findings provide the cellular framework by which myocardial ischemia may trigger in EpiSC the formation of cardioprotective/regenerative responses.

Decreased autophagy is a hallmark of ageing, but its inter-tissue regulation is poorly understood. Here, Zhou et al. identify mir-83 in C. elegans, which is transported across tissues and suppresses autophagy, contributing to age-related decline.

Risk prediction in patients with heart failure (HF) is essential to improve the tailoring of preventive, diagnostic, and therapeutic strategies for the individual patient, and effectively use health care resources. Risk scores derived from controlled clinical studies can be used to calculate the risk of mortality and HF hospitalizations. However, these scores are poorly implemented into routine care, predominantly because their calculation requires considerable efforts in practice and necessary data often are not available in an interoperable format. In this work, we demonstrate the feasibility of a multi-site solution to derive and calculate two exemplary HF scores from clinical routine data (MAGGIC score with six continuous and eight categorical variables; Barcelona Bio-HF score with five continuous and six categorical variables). Within HiGHmed, a German Medical Informatics Initiative consortium, we implemented an interoperable solution, collecting a harmonized HF-phenotypic core data set (CDS) within the openEHR framework. Our approach minimizes the need for manual data entry by automatically retrieving data from primary systems. We show, across five participating medical centers, that the implemented structures to execute dedicated data queries, followed by harmonized data processing and score calculation, work well in practice. In summary, we demonstrated the feasibility of clinical routine data usage across multiple partner sites to compute HF risk scores. This solution can be extended to a large spectrum of applications in clinical care.

Our understanding of the transition from physiological to pathological cardiac hypertrophy remains elusive and largely based on reductionist hypotheses. Here, we profiled the translatomes of 15 mouse hearts to provide a molecular blueprint of altered gene networks in early cardiac remodeling. Using co-expression analysis, we showed how sub-networks are orchestrated into functional modules associated with pathological phenotypes. We discovered unappreciated hub genes, many undocumented for their role in cardiac hypertrophy, and genes in the transcriptional network that were rewired in the translational network, and associated with semantically different subsets of enriched functional terms, such as Fam210a, a novel musculoskeletal modulator, or Psmd12, implicated in protein quality control. Using their correlation structure, we found that transcriptome networks are only partially reproducible at the translatome level, providing further evidence of post-transcriptional control at the level of translation. Our results provide novel insights into the complexity of the organization of in vivo cardiac regulatory networks.

Cardiovascular disease is still the leading cause of morbidity and mortality worldwide. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) have become a valuable widespread in vitro model to study cardiac disease. Herein, we employ the hiPSC-CM model to identify novel miRNA–mRNA interaction partners during cardiac differentiation and β-adrenergic stress. Whole transcriptome and small RNA sequencing data were combined to identify novel miRNA–mRNA interactions. Briefly, mRNA and miRNA expression profiles were integrated with miRNA target predictions to identify significant statistical dependencies between a miRNA and its candidate target set. We show by experimental validation that our approach discriminates true from false miRNA target predictions. Thereby, we identified several differentially expressed miRNAs and focused on the two top candidates: miR-99a-5p in the context of cardiac differentiation and miR-212-3p in the context of β-adrenergic stress. We validated some target mRNA candidates by 3′UTR luciferase assays as well as in transfection experiments in the hiPSC-CM model system. Our data show that iPSC-derived cardiomyocytes and computational modeling can be used to uncover new valid miRNA–mRNA interactions beyond current knowledge.

Until recently considered as rare, circular RNAs (circRNAs) are emerging as important regulators of gene expression. They are ubiquitously expressed and represent a novel branch of the family of non-coding RNAs. Recent investigations showed that circRNAs are regulated in the cardiovascular system and participate in its physiological and pathological development. In this review article, we will provide an overview of the role of circRNAs in cardiovascular health and disease. After a description of the biogenesis of circRNAs, we will summarize what is known of the expression, regulation and function of circRNAs in the cardiovascular system. We will then address some technical aspects of circRNAs research, discussing how artificial intelligence may aid in circRNAs research. Finally, the potential of circRNAs as biomarkers of cardiovascular disease will be addressed and directions for future research will be proposed. Keywords: Non-coding RNAs, Circular RNAs, Cardiovascular system, Cardiovascular disease, Artificial intelligence, Biomarker

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.

Abstract Lowered activity of the insulin/IGF signalling (IIS) network can ameliorate the effects of ageing in laboratory animals and, possibly, humans. Although transcriptome remodelling in long‐lived IIS mutants has been extensively documented, the causal mechanisms contributing to extended lifespan, particularly in specific tissues, remain unclear. We have characterized the proteomes of four key insulin‐sensitive tissues in a long‐lived Drosophila IIS mutant and control, and detected 44% of the predicted proteome (6,085 proteins). Expression of ribosome‐associated proteins in the fat body was reduced in the mutant, with a corresponding, tissue‐specific reduction in translation. Expression of mitochondrial electron transport chain proteins in fat body was increased, leading to increased respiration, which was necessary for IIS‐mediated lifespan extension, and alone sufficient to mediate it. Proteasomal subunits showed altered expression in IIS mutant gut, and gut‐specific over‐expression of the RPN6 proteasomal subunit, was sufficient to increase proteasomal activity and extend lifespan, whilst inhibition of proteasome activity abolished IIS‐mediated longevity. Our study thus uncovered strikingly tissue‐specific responses of cellular processes to lowered IIS acting in concert to ameliorate ageing.

Abstract Background Parasites 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 lifecycle of Eimeria falciformis using infected mice with different immune status as models for coccidian infections. Results We 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. Conclusion We propose that the niche and host-specific parasite E. falciformis uses 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. This in turn might limit the potential of the parasite to adapt to new host species or niches, forcing it to coevolve with its host.

Abstract 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 Ly6Chigh 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 microenvironment's 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.

Massively parallel RNA sequencing (RNA-seq) in combination with metabolic labeling has become the de facto standard approach to study alterations in RNA transcription, processing or decay. Regardless of advances in the experimental protocols and techniques, every experimentalist needs to specify the key aspects of experimental design: For example, which protocol should be used (biochemical separation vs. nucleotide conversion) and what is the optimal labeling time? In this work, we provide approximate answers to these questions using the asymptotic theory of optimal design. Specifically, we investigate, how the variance of degradation rate estimates depends on the time and derive the optimal time for any given degradation rate. Subsequently, we show that an increase in sample numbers should be preferred over an increase in sequencing depth. Lastly, we provide some guidance on use cases when laborious biochemical separation outcompetes recent nucleotide conversion based methods (such as SLAMseq) and show, how inefficient conversion influences the precision of estimates. Code and documentation can be found at https://github.com/dieterich-lab/DesignMetabolicRNAlabeling.

Invasive mycoses remain underdiagnosed and difficult to treat. Hospitalized individuals with compromised immunity increase in number and constitute the main risk group for severe fungal infections. Current antifungal therapy is hampered by slow and insensitive diagnostics and frequent toxic side effects of standard antifungal drugs. Identification of new antifungal compounds with high efficacy and low toxicity is therefore urgently required. We investigated the antifungal activity of tempol, a cell-permeable nitroxide. To narrow down possible mode of action we used RNA-seq technology and metabolomics to probe for pathways specifically disrupted in the human fungal pathogen Candida albicans due to tempol administration. We found genes upregulated which are involved in iron homeostasis, mitochondrial stress, steroid synthesis, and amino acid metabolism. In an ex vivo whole blood infection, tempol treatment reduced C. albicans colony forming units and at the same time increased the release of pro-inflammatory cytokines, such as interleukin 8 (IL-8, monocyte chemoattractant protein-1, and macrophage migration inhibitory factor). In a systemic mouse model, tempol was partially protective with a significant reduction of fungal burden in the kidneys of infected animals during infection onset. The results obtained propose tempol as a promising new antifungal compound and open new opportunities for the future development of novel therapies.

Diseases of the renal filtration unit—the glomerulus—are the most common cause of chronic kidney disease. Podocytes are the pivotal cell type for the function of this filter and focal-segmental glomerulosclerosis (FSGS) is a classic example of a podocytopathy leading to proteinuria and glomerular scarring. Currently, no targeted treatment of FSGS is available. This lack of therapeutic strategies is explained by a limited understanding of the defects in podocyte cell biology leading to FSGS. To date, most studies in the field have focused on protein-coding genes and their gene products. However, more than 80% of all transcripts produced by mammalian cells are actually non-coding. Here, long non-coding RNAs (lncRNAs) are a relatively novel class of transcripts and have not been systematically studied in FSGS to date. The appropriate tools to facilitate lncRNA research for the renal scientific community are urgently required due to a row of challenges compared to classical analysis pipelines optimized for coding RNA expression analysis. Here, we present the bioinformatic pipeline CALINCA as a solution for this problem. CALINCA automatically analyzes datasets from murine FSGS models and quantifies both annotated and de novo assembled lncRNAs. In addition, the tool provides in-depth information on podocyte specificity of these lncRNAs, as well as evolutionary conservation and expression in human datasets making this pipeline a crucial basis to lncRNA studies in FSGS.

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.

For several decades, cardiovascular disease has been the leading cause of death throughout all countries. There is a strong genetic component to many disease subtypes (e.g., cardiomyopathy) and we are just beginning to understand the relevant genetic factors. Several studies have related RNA splicing to cardiovascular disease and circular RNAs (circRNAs) are an emerging player. circRNAs, which originate through back-splicing events from primary transcripts, are resistant to exonucleases and typically not polyadenylated. Initial functional studies show clear phenotypic outcomes for selected circRNAs. We provide, for the first time, a comprehensive catalogue of RNase R-resistant circRNA species for the adult murine heart. This work combines state-of-the-art circle sequencing with our novel DCC software to explore the circRNA landscape of heart tissue. Overall, we identified 575 circRNA species that pass a beta-binomial test for enrichment (false discovery rate of 1%) in the exonuclease-treated sequencing sample. Several circRNAs can be directly attributed to host genes that have been previously described as associated with cardiovascular disease. Further studies of these candidate circRNAs may reveal disease-relevant properties or functions of specific circRNAs.

Removal of the C. elegans germline substantially increases organismal lifespan. Here, Nakamura et al. show that the transcription factors MML-1 and MXL-2 coordinate this process in that they reduce TOR signalling and increase autophagy by regulating activity of HLH-30.

For decades, cardiovascular disease (CVD) has been the leading cause of death throughout most developed countries. Several studies relate RNA splicing, and more recently also circular RNAs (circRNAs), to CVD. CircRNAs originate from linear transcripts and have been shown to exhibit tissue-specific expression profiles. Here, we present an in-depth analysis of sequence, structure, modification, and cardiac circRNA interactions. We used human induced pluripotent stem cell-derived cardiac myocytes (hiPSC-CMs), human healthy and diseased (ischemic cardiomyopathy, dilated cardiomyopathy) cardiac tissue, and human umbilical vein endothelial cells (HUVECs) to profile circRNAs. We identified shared circRNAs across all samples, as well as model-specific circRNA signatures. Based on these circRNAs, we identified 63 positionally conserved and expressed circRNAs in human, pig, and mouse hearts. Furthermore, we found that the sequence of circRNAs can deviate from the sequence derived from the genome sequence, an important factor in assessing potential functions. Integration of additional data yielded evidence for m6A-methylation of circRNAs, potentially linked to translation, as well as, circRNAs overlapping with potential Argonaute 2 binding sites, indicating potential association with the RISC complex. Moreover, we describe, for the first time in cardiac model systems, a sub class of circRNAs containing the start codon of their primary transcript (AUG circRNAs) and observe an enrichment for m6A-methylation for AUG circRNAs.

Circular RNAs (circRNAs) are a large class of animal RNAs. To investigate possible circRNA functions, it is important to understand circRNA biogenesis. Besides human ALU repeats, sequence features that promote exon circularization are largely unknown. We experimentally identified circRNAs in C. elegans. Reverse complementary sequences between introns bracketing circRNAs were significantly enriched in comparison to linear controls. By scoring the presence of reverse complementary sequences in human introns, we predicted and experimentally validated circRNAs. We show that introns bracketing circRNAs are highly enriched in RNA editing or hyperediting events. Knockdown of the double-strand RNA-editing enzyme ADAR1 significantly and specifically upregulated circRNA expression. Together, our data support a model of animal circRNA biogenesis in which competing RNA-RNA interactions of introns form larger structures that promote circularization of embedded exons, whereas ADAR1 antagonizes circRNA expression by melting stems within these interactions.

The transcription factor ZEB1 has gained attention in tumor biology of epithelial cancers because of its function in epithelial-mesenchymal transition, DNA repair, stem cell biology and tumor-induced immunosuppression, but its role in gliomas with respect to invasion and prognostic value is controversial. We characterized ZEB1 expression at single cell level in 266 primary brain tumors and present a comprehensive dataset of high grade gliomas with Ki67, p53, IDH1, and EGFR immunohistochemistry, as well as EGFR FISH. ZEB1 protein expression in glioma stem cell lines was compared to their parental tumors with respect to gene expression subtypes based on RNA-seq transcriptomic profiles. ZEB1 is widely expressed in glial tumors, but in a highly variable fraction of cells. In glioblastoma, ZEB1 labeling index is higher in tumors with EGFR amplification or IDH1 mutation. Co-labeling studies showed that tumor cells and reactive astroglia, but not immune cells contribute to the ZEB1 positive population. In contrast, glioma cell lines constitutively express ZEB1 irrespective of gene expression subtype. In conclusion, our data indicate that immune infiltration likely contributes to differential labelling of ZEB1 and confounds interpretation of bulk ZEB1 expression data.

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/.

Large genome size, including immense repetitive and non-coding fractions, still present challenges for capacity, bioinformatics and thus affordability of whole genome sequencing in most amphibians. Here, we test the performance of a single transcriptome to understand whether it can provide a cost-efficient resource for species with large unknown genomes. Using RNA from six different tissues from a single Palearctic green toad (Bufo viridis) specimen and Hiseq2000, we obtained 22,5 Mio reads and publish >100,000 unigene sequences. To evaluate efficacy and quality, we first use this data to identify green toad specific candidate genes, known from other vertebrates for their role in sex determination and differentiation. Of a list of 37 genes, the transcriptome yielded 32 (87%), many of which providing the first such data for this non-model anuran species. However, for many of these genes, only fragments could be retrieved. In order to allow also applications to population genetics, we further used the transcriptome for the targeted development of 21 non-anonymous microsatellites and tested them in genetic families and backcrosses. Eleven markers were specifically developed to be located on the B. viridis sex chromosomes; for eight markers we can indeed demonstrate sex-specific transmission in genetic families. Depending on phylogenetic distance, several markers, which are sex-linked in green toads, show high cross-amplification success across the anuran phylogeny, involving nine systematic anuran families. Our data support the view that single transcriptome sequencing (based on multiple tissues) provides a reliable genomic resource and cost-efficient method for non-model amphibian species with large genome size and, despite limitations, should be considered as long as genome sequencing remains unaffordable for most species.

Growing evidence suggests a key role for RNA binding proteins (RBPs) in genome stability programs. Additionally, recent developments in RNA sequencing technologies, as well as mass-spectrometry techniques, have greatly expanded our knowledge on protein-RNA interactions. We here use full transcriptome sequencing and label-free LC/MS/MS to identify global changes in protein-RNA interactions in response to etoposide-induced genotoxic stress. We show that RBPs have distinct binding patterns in response to genotoxic stress and that inactivation of the RBP regulator module, p38/MK2, can affect the entire spectrum of protein-RNA interactions that take place in response to stress. In addition to validating the role of known RBPs like Srsf1, Srsf2, Elavl1 in the genotoxic stress response, we add a new collection of RBPs to the DNA damage response. We identify Khsrp as a highly regulated RBP in response to genotoxic stress and further validate its role as a driver of the G(1/)S transition through the suppression of Cdkn1a(P21) transcripts. Finally, we identify KHSRP as an indicator of overall survival, as well as disease free survival in glioblastoma multiforme.

Nematodes and insects are the two most speciose animal phyla and nematode–insect associations encompass widespread biological interactions. To dissect the chemical signals and the genes mediating this association, we investigated the effect of an oriental beetle sex pheromone on the development and behavior of the nematode Pristionchus pacificus. We found that while the beetle pheromone is attractive to P. pacificus adults, the pheromone arrests embryo development, paralyzes J2 larva, and inhibits exit of dauer larvae. To uncover the mechanism that regulates insect pheromone sensitivity, a newly identified mutant, Ppa-obi-1, is used to reveal the molecular links between altered attraction towards the beetle pheromone, as well as hypersensitivity to its paralyzing effects. Ppa-obi-1 encodes lipid-binding domains and reaches its highest expression in various cell types, including the amphid neuron sheath and excretory cells. Our data suggest that the beetle host pheromone may be a species-specific volatile synomone that co-evolved with necromeny.

Whole genome gene order evolution in higher eukaryotes was initially considered as a random process. Gene order conservation or conserved synteny was seen as a feature of common descent and did not imply the existence of functional constraints. This view had to be revised in the light of results from sequencing dozens of vertebrate genomes.It became apparent that other factors exist that constrain gene order in some genomic regions over long evolutionary time periods. Outside of these regions, genomes diverge more rapidly in terms of gene content and order.We have developed CYNTENATOR, a progressive gene order alignment software, to identify genomic regions of conserved synteny over a large set of diverging species. CYNTENATOR does not depend on nucleotide-level alignments and a priori homology assignment. Our software implements an improved scoring function that utilizes the underlying phylogeny.In this manuscript, we report on our progressive gene order alignment approach, a and give a comparison to previous software and an analysis of 17 vertebrate genomes for conservation in gene order.CYNTENATOR has a runtime complexity of and a space complexity of with being the gene number in a genome. CYNTENATOR performs as good as state-of-the-art software on simulated pairwise gene order comparisons, but is the only algorithm that works in practice for aligning dozens of vertebrate-sized gene orders.Lineage-specific characterization of gene order across 17 vertebrate genomes revealed mechanisms for maintaining conserved synteny such as enhancers and coregulation by bidirectional promoters. Genes outside conserved synteny blocks show enrichments for genes involved in responses to external stimuli, stimuli such as immunity and olfactory response in primate genome comparisons. We even see significant gene ontology term enrichments for breakpoint regions of ancestral nodes close to the root of the phylogeny. Additionally, our analysis of transposable elements has revealed a significant accumulation of LINE-1 elements in mammalian breakpoint regions. In summary, CYNTENATOR is a flexible and scalable tool for the identification of conserved gene orders across multiple species over long evolutionary distances.

The skeleton is one of the most important features for the reconstruction of vertebrate phylogeny but few data are available to understand its molecular origin. In mammals the Runt genes are central regulators of skeletogenesis. Runx2 was shown to be essential for osteoblast differentiation, tooth development, and bone formation. Both Runx2 and Runx3 are essential for chondrocyte maturation. Furthermore, Runx2 directly regulates Indian hedgehog expression, a master coordinator of skeletal development. To clarify the correlation of Runt gene evolution and the emergence of cartilage and bone in vertebrates, we cloned the Runt genes from hagfish as representative of jawless fish (MgRunxA, MgRunxB) and from dogfish as representative of jawed cartilaginous fish (ScRunx1-3). According to our phylogenetic reconstruction the stem species of chordates harboured a single Runt gene and thereafter Runt locus duplications occurred during early vertebrate evolution. All newly isolated Runt genes were expressed in cartilage according to quantitative PCR. In situ hybridisation confirmed high MgRunxA expression in hard cartilage of hagfish. In dogfish ScRunx2 and ScRunx3 were expressed in embryonal cartilage whereas all three Runt genes were detected in teeth and placoid scales. In cephalochordates (lancelets) Runt, Hedgehog and SoxE were strongly expressed in the gill bars and expression of Runt and Hedgehog was found in endo- as well as ectodermal cells. Furthermore we demonstrate that the lancelet Runt protein binds to Runt binding sites in the lancelet Hedgehog promoter and regulates its activity. Together, these results suggest that Runt and Hedgehog were part of a core gene network for cartilage formation, which was already active in the gill bars of the common ancestor of cephalochordates and vertebrates and diversified after Runt duplications had occurred during vertebrate evolution. The similarities in expression patterns of Runt genes support the view that teeth and placoid scales evolved from a homologous developmental module.