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Cardiac remodelling involves structural, cellular and molecular alterations in the heart after injury, resulting in progressive loss of heart function and ultimately leading to heart failure. Circular RNAs (circRNAs) are a recently rediscovered class of non-coding RNAs that play regulatory roles in the pathogenesis of cardiovascular diseases, including heart failure. Thus, a more comprehensive understanding of the role of circRNAs in the processes governing cardiac remodelling may set the ground for the development of circRNA-based diagnostic and therapeutic strategies. In this review, the current knowledge about circRNA origin, conservation, characteristics and function is summarized. Bioinformatics and wet-lab methods used in circRNA research are discussed. The regulatory function of circRNAs in cardiac remodelling mechanisms such as cell death, cardiomyocyte hypertrophy, inflammation, fibrosis and metabolism is highlighted. Finally, key challenges and opportunities in circRNA research are discussed, and orientations for future work to address the pharmacological potential of circRNAs in heart failure are proposed. LINKED ARTICLES: This article is part of a themed issue Non-coding RNA Therapeutics. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v182.2/issuetoc., (© 2024 The Authors. British Journal of Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)

Microglia are strongly implicated in demyelinating neurodegenerative diseases with increasing evidence for roles in protection and healing, but the mechanisms that control CNS remyelination are poorly understood. Here, we show that microglia-specific deletion of tumor necrosis factor receptor 1 (TNFR1) and pharmacological inhibition of soluble TNF (solTNF) or downstream interleukin-1 receptor (IL-1R) allow maturation of highly activated disease-associated microglia with increased size and myelin phagocytosis capacity that accelerate cortical remyelination and motor recovery. Single-cell transcriptomic analysis of cortex at disease onset reveals that solTNF inhibition enhances reparative IL-10-responsive while preventing damaging IL-1-related signatures of disease-associated microglia. Longitudinal brain transcriptome analysis through disease reveals earlier recovery upon therapeutic loss of microglia TNFR1. The functional relevance of microglia inflammatory polarization pathways for disease is validated in vivo. Furthermore, disease-state microglia producing downstream IL-1/IL-18/caspase-11 targets are identified in human demyelinating lesions. Overall, redirecting disease microglia polarization by targeting cytokines is a potential approach for improving CNS repair in demyelinating disorders., Competing Interests: Declaration of interests R.J.T. is CEO and C.J.B. is vice president of Neuroscience of INmune Bio. Both R.J.T. and C.J.B. own shares in INmuneBio. INmune Bio owns a patent application related to this work., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

microRNAs (miRNAs) are central post-transcriptional gene expression regulators in healthy and diseased states. Despite decades of effort, deciphering miRNA targets remains challenging, leading to an incomplete miRNA interactome and partially elucidated miRNA functions. Here, we introduce microT-CNN, an avant-garde deep convolutional neural network model that moves the needle by integrating hundreds of tissue-matched (in-)direct experiments from 26 distinct cell types, corresponding to a unique training and evaluation set of >60 000 miRNA binding events and ~30 000 unique miRNA-gene target pairs. The multilayer sequence-based design enables the prediction of both host and virus-encoded miRNA interactions, providing for the first time up to 67% of direct genuine Epstein-Barr virus- and Kaposi's sarcoma-associated herpesvirus-derived miRNA-target pairs corresponding to one out of four binding events of virus-encoded miRNAs. microT-CNN fills the existing gap of the miRNA-target prediction by providing functional targets beyond the canonical sites, including 3' compensatory miRNA pairings, prompting 1.4-fold more validated miRNA binding events compared to other implementations and shedding light on previously unexplored facets of the miRNA interactome., (© The Author(s) 2024. Published by Oxford University Press.)

Tomato ( Solanum lycopersicum ) is a major horticultural crop of high economic importance. Phelipanche and Orobanche genera (broomrapes) are parasitic weeds, constituting biotic stressors that impact tomato production. Developing varieties with tolerance to broomrapes has become imperative for sustainable agriculture. Solanum pennellii , a wild relative of cultivated tomato, has been utilized as breeding material for S . lycopersicum. In the present study, it is the first time that an in-depth analysis has been conducted for these two specific introgression lines (ILs), IL6-2 and IL6-3 ( S . lycopersicum X S. pennellii ), which were employed to identify genes and metabolic pathways associated with resistance against broomrape. Comparative transcriptomic analysis revealed a multitude of differentially expressed genes (DEGs) in roots, especially in the resistant genotype IL6-3, several of which were validated by quantitative PCR. DEG and pathway enrichment analysis (PEA) revealed diverse molecular mechanisms that can potentially be implicated in the host's defense response and the establishment of resistance. The identified DEGs were mostly up-regulated in response to broomrape parasitism and play crucial roles in various processes different from strigolactone regulation. Our findings indicate that, in addition to the essential role of strigolactone metabolism, multiple cellular processes may be involved in the tomato's response to broomrapes. The insights gained from this study will enhance our understanding and facilitate molecular breeding methods regarding broomrape parasitism. Moreover, they will assist in developing sustainable strategies and providing alternative solutions for weed management in tomatoes and other agronomically important crops.

Small open reading frames (sORFs; <300 nucleotides or <100 amino acids) are widespread across all genomes, and an increasing variety of them appear to be translating from non-genic regions. Over the past few decades, peptides produced from sORFs have been identified as functional in various organisms, from bacteria to humans. Despite recent advances in next-generation sequencing and proteomics, accurate annotation and classification of sORFs remain a rate-limiting step toward reliable and high-throughput detection of small proteins from non-genic regions. Additionally, the cost of computational methods utilizing machine learning is lower than that of biological experiments, and they can be employed to detect sORFs, laying the groundwork for biological experiments. We present D-sORF, a machine-learning framework that integrates the statistical nucleotide context and motif information around the start codon to predict coding sORFs. D-sORF scores directly for coding identity and requires only the underlying genomic sequence, without incorporating parameters such as the conservation, which, in the case of sORFs, may increase the dispersion of scores within the significantly less conserved non-genic regions. D-sORF achieves 94.74% precision and 92.37% accuracy for small ORFs (using the 99 nt medium length window). When D-sORF is applied to sORFs associated with ribosomes, the identification of transcripts producing peptides (annotated by the Ensembl IDs) is similar to or superior to experimental methodologies based on ribosome-sequencing (Ribo-Seq) profiling. In parallel, the recognition of putative negative data, such as the intron-containing transcripts that associate with ribosomes, remains remarkably low, indicating that D-sORF could be efficiently applied to filter out false-positive sORFs from Ribo-Seq data because of the non-productive ribosomal binding or noise inherent in these protocols.

Purpose: Studies during the past 9 years suggest that delivering radiation at dose rates exceeding 40 Gy/s, known as "FLASH" radiation therapy, enhances the therapeutic index of radiation therapy (RT) by decreasing normal tissue damage while maintaining tumor response compared with conventional (or standard) RT. This study demonstrates the cardioprotective benefits of FLASH proton RT (F-PRT) compared with standard (conventional) proton RT (S-PRT), as evidenced by reduced acute and chronic cardiac toxicities., Methods and Materials: Mice were imaged using cone beam computed tomography to precisely determine the heart's apex as the beam isocenter. Irradiation was conducted using a shoot-through technique with a 5-mm diameter circular collimator. Bulk RNA-sequencing was performed on nonirradiated samples, as well as apexes treated with F-PRT or S-PRT, at 2 weeks after a single 40 Gy dose. Inflammatory responses were assessed through multiplex cytokine/chemokine microbead assay and immunofluorescence analyses. Levels of perivascular fibrosis were quantified using Masson's Trichrome and Picrosirius red staining. Additionally, cardiac tissue functionality was evaluated by 2-dimensional echocardiograms at 8- and 30-weeks post-PRT., Results: Radiation damage was specifically localized to the heart's apex. RNA profiling of cardiac tissues treated with PRT revealed that S-PRT uniquely upregulated pathways associated with DNA damage response, induction of tumor necrosis factor superfamily, and inflammatory response, and F-PRT primarily affected cytoplasmic translation, mitochondrion organization, and adenosine triphosphate synthesis. Notably, F-PRT led to a milder inflammatory response, accompanied by significantly attenuated changes in transforming growth factor β1 and α smooth muscle actin levels. Critically, F-PRT decreased collagen deposition and better preserved cardiac functionality compared with S-PRT., Conclusions: This study demonstrated that F-PRT reduces the induction of an inflammatory environment with lower expression of inflammatory cytokines and profibrotic factors. Importantly, the results indicate that F-PRT better preserves cardiac functionality, as confirmed by echocardiography analysis, while also mitigating the development of long-term fibrosis., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

In the last decade, the immense growth in the field of bacterial small RNAs (sRNAs), along with the biotechnological breakthroughs in Deep Sequencing permitted the deeper understanding of sRNA-RNA interactions. However, microbiology is currently lacking a thoroughly curated collection of this rapidly expanding universe. We present Agnodice (https://dianalab.e-ce.uth.gr/agnodice), our effort to systematically catalog and annotate experimentally supported bacterial sRNA-RNA interactions. Agnodice, for the first time, incorporates thousands of bacterial sRNA-RNA interactions derived from a diverse set of experimental methodologies including state-of-the-art Deep Sequencing interactome identification techniques. It comprises 39,600 entries which are annotated at strain-level resolution and pertain to 399 sRNAs and 12,137 target RNAs identified in 71 bacterial strains. The database content is exclusively experimentally supported, incorporating interactions derived via low yield as well as state-of-the-art high-throughput methods. The entire content of the database is freely accessible and can be directly downloaded for further analysis. Agnodice will serve as a valuable source, enabling microbiologists to form novel hypotheses, design/identify novel sRNA-based drug targets, and explore the therapeutic potential of microbiomes from the perspective of small regulatory RNAs.IMPORTANCEAgnodice (https://dianalab.e-ce.uth.gr/agnodice) is an effort to systematically catalog and annotate experimentally supported bacterial small RNA (sRNA)-RNA interactions. Agnodice, for the first time, incorporates thousands of bacterial sRNA-RNA interactions derived from a diverse set of experimental methodologies including state-of-the-art Next Generation Sequencing interactome identification techniques., Competing Interests: The authors declare no conflict of interest.

TarBase is a reference database dedicated to produce, curate and deliver high quality experimentally-supported microRNA (miRNA) targets on protein-coding transcripts. In its latest version (v9.0, https://dianalab.e-ce.uth.gr/tarbasev9), it pushes the envelope by introducing virally-encoded miRNAs, interactions leading to target-directed miRNA degradation (TDMD) events and the largest collection of miRNA-gene interactions to date in a plethora of experimental settings, tissues and cell-types. It catalogues ∼6 million entries, comprising ∼2 million unique miRNA-gene pairs, supported by 37 experimental (high- and low-yield) protocols in 172 tissues and cell-types. Interactions are annotated with rich metadata including information on genes/transcripts, miRNAs, samples, experimental contexts and publications, while millions of miRNA-binding locations are also provided at cell-type resolution. A completely re-designed interface with state-of-the-art web technologies, incorporates more features, and allows flexible and ingenious use. The new interface provides the capability to design sophisticated queries with numerous filtering criteria including cell lines, experimental conditions, cell types, experimental methods, species and/or tissues of interest. Additionally, a plethora of fine-tuning capacities have been integrated to the platform, offering the refinement of the returned interactions based on miRNA confidence and expression levels, while boundless local retrieval of the offered interactions and metadata is enabled., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Parkin is an E3 ubiquitin ligase, which plays a key role in the development of Parkinson disease. Parkin defects also occur in numerous cancers, and a growing body of evidence indicates that Parkin functions as a tumor suppressor that impedes a number of cellular processes involved in tumorigenesis. Here, we generated murine and human models that closely mimic the advanced-stage tumors where Parkin deficiencies are found to provide deeper insights into the tumor suppressive functions of Parkin. Loss of Parkin expression led to aggressive tumor growth, which was associated with poor tumor antigen presentation and limited antitumor CD8+ T-cell infiltration and activation. The effect of Parkin deficiency on tumor growth was lost following depletion of CD8+ T cells. In line with previous findings, Parkin deficiency was linked with mitochondria-associated metabolic stress, PTEN degradation, and enhanced Akt activation. Increased Akt signaling led to dysregulation of antigen presentation, and treatment with the Akt inhibitor MK2206-2HCl restored antigen presentation in Parkin-deficient tumors. Analysis of data from patients with clear cell renal cell carcinoma indicated that Parkin expression was downregulated in tumors and that low expression correlated with reduced overall survival. Furthermore, low Parkin expression correlated with reduced patient response to immunotherapy. Overall, these results identify a role for Parkin deficiency in promoting tumor immune evasion that may explain the poor prognosis associated with loss of Parkin across multiple types of cancer., Significance: Parkin prevents immune evasion by regulating tumor antigen processing and presentation through the PTEN/Akt network, which has important implications for immunotherapy treatments in patients with Parkin-deficient tumors., (©2023 The Authors; Published by the American Association for Cancer Research.)

Scientists have been trying to identify every gene in the human genome since the initial draft was published in 2001. In the years since, much progress has been made in identifying protein-coding genes, currently estimated to number fewer than 20,000, with an ever-expanding number of distinct protein-coding isoforms. Here we review the status of the human gene catalogue and the efforts to complete it in recent years. Beside the ongoing annotation of protein-coding genes, their isoforms and pseudogenes, the invention of high-throughput RNA sequencing and other technological breakthroughs have led to a rapid growth in the number of reported non-coding RNA genes. For most of these non-coding RNAs, the functional relevance is currently unclear; we look at recent advances that offer paths forward to identifying their functions and towards eventually completing the human gene catalogue. Finally, we examine the need for a universal annotation standard that includes all medically significant genes and maintains their relationships with different reference genomes for the use of the human gene catalogue in clinical settings., (© 2023. Springer Nature Limited.)

MicroRNAs (miRNAs) are short noncoding RNAs that can regulate all steps of gene expression (induction, transcription, and translation). Several virus families, primarily double-stranded DNA viruses, encode small RNAs (sRNAs), including miRNAs. These virus-derived miRNAs (v-miRNAs) help the virus evade the host's innate and adaptive immune system and maintain an environment of chronic latent infection. In this review, the functions of the sRNA-mediated virus-host interactions are highlighted, delineating their implication in chronic stress, inflammation, immunopathology, and disease. We provide insights into the latest viral RNA-based research-in silico approaches for functional characterization of v-miRNAs and other RNA types. The latest research can assist toward the identification of therapeutic targets to combat viral infections.

DIANA-miRPath is an online miRNA analysis platform harnessing predicted or experimentally supported miRNA interactions towards the exploration of combined miRNA effects. In its latest version (v4.0, http://www.microrna.gr/miRPathv4), DIANA-miRPath breaks new ground by introducing the capacity to tailor its target-based miRNA functional analysis engine to specific biological and/or experimental contexts. Via a redesigned modular interface with rich interaction, annotation and parameterization options, users can now perform enrichment analysis on Gene Ontology (GO) terms, KEGG and REACTOME pathways, sets from Molecular Signatures Database (MSigDB) and PFAM. Included miRNA interaction sets are derived from state-of-the-art resources of experimentally supported (DIANA-TarBase v8.0, miRTarBase and microCLIP cell-type-specific interactions) or from in silico miRNA-target interactions (updated DIANA-microT-CDS and TargetScan predictions). Bulk and single-cell expression datasets from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression project (GTEx) and adult/fetal single-cell atlases are integrated and can be used to assess the expression of enriched term components across a wide range of states. A discrete module enabling enrichment analyses using CRISPR knock-out screen datasets enables the detection of selected miRNAs with potentially crucial roles within conditions under study. Notably, the option to upload custom interaction, term, expression and screen sets further expands the versatility of miRPath webserver., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

DIANA-microT-CDS is a state-of-the-art miRNA target prediction algorithm catering the scientific community since 2009. It is one of the first algorithms to predict miRNA binding sites in both the 3' Untranslated Region (3'-UTR) and the coding sequence (CDS) of transcripts, with increased performance. Its current version, DIANA-microT 2023 (www.microrna.gr/microt&#95;webserver/), brings forward a significantly updated set of interactions. DIANA-microT-CDS has been executed utilizing annotation information from Ensembl v102, miRBase 22.1 and, for the first time, MirGeneDB 2.1, yielding more than 83 million interactions in human, mouse, rat, chicken, fly and worm species. Additionally, this version delivers predicted interactions of miRNAs encoded from 20 viruses against host transcripts from human, mouse and chicken species. Numerous resources have been interconnected into DIANA-microT, including DIANA-TarBase, plasmiR, HMDD, UCSC, dbSNP, ClinVar, as well as miRNA/gene abundance values for 369 distinct cell-lines/tissues. The server interface has been redesigned allowing users to use smart filtering options, identify abundance patterns of interest, pinpoint known SNPs residing on binding sites and obtain miRNA-disease information. The contents of DIANA-microT webserver are freely accessible and can also be locally downloaded without any login requirements., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The microRNA (miRNA) miR-124 has been employed supplementary to neurogenic transcription factors (TFs) and other miRNAs to enhance direct neurogenic conversion. The aim of this study was to investigate whether miR-124 is sufficient to drive direct reprogramming of astrocytes to induced neurons (iNs) on its own and elucidate its independent mechanism of reprogramming action. Our data show that miR-124 is a potent driver of the reprogramming switch of astrocytes toward an immature neuronal fate by directly targeting the RNA-binding protein Zfp36L1 implicated in ARE-mediated mRNA decay and subsequently derepressing Zfp36L1 neurogenic interactome. To this end, miR-124 contribution in iNs' production largely recapitulates endogenous neurogenesis pathways, being further enhanced upon addition of the neurogenic compound ISX9, which greatly improves iNs' differentiation and functional maturation. Importantly, miR-124 is potent in guiding direct conversion of reactive astrocytes to immature iNs in vivo following cortical trauma, while ISX9 supplementation confers a survival advantage to newly produced iNs., Competing Interests: Conflict of interests The authors declare no competing interests., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: The widespread usage of Cap Analysis of Gene Expression (CAGE) has led to numerous breakthroughs in understanding the transcription mechanisms. Recent evidence in the literature, however, suggests that CAGE suffers from transcriptional and technical noise. Regardless of the sample quality, there is a significant number of CAGE peaks that are not associated with transcription initiation events. This type of signal is typically attributed to technical noise and more frequently to random five-prime capping or transcription bioproducts. Thus, the need for computational methods emerges, that can accurately increase the signal-to-noise ratio in CAGE data, resulting in error-free transcription start site (TSS) annotation and quantification of regulatory region usage. In this study, we present DeepTSS, a novel computational method for processing CAGE samples, that combines genomic signal processing (GSP), structural DNA features, evolutionary conservation evidence and raw DNA sequence with Deep Learning (DL) to provide single-nucleotide TSS predictions with unprecedented levels of performance., Results: To evaluate DeepTSS, we utilized experimental data, protein-coding gene annotations and computationally-derived genome segmentations by chromatin states. DeepTSS was found to outperform existing algorithms on all benchmarks, achieving 98% precision and 96% sensitivity (accuracy 95.4%) on the protein-coding gene strategy, with 96.66% of its positive predictions overlapping active chromatin, 98.27% and 92.04% co-localized with at least one transcription factor and H3K4me3 peak., Conclusions: CAGE is a key protocol in deciphering the language of transcription, however, as every experimental protocol, it suffers from biological and technical noise that can severely affect downstream analyses. DeepTSS is a novel DL-based method for effectively removing noisy CAGE signal. In contrast to existing software, DeepTSS does not require feature selection since the embedded convolutional layers can readily identify patterns and only utilize the important ones for the classification task. This study highlights the key role that DL can play in Molecular Biology, by removing the inherent flaws of experimental protocols, that form the backbone of contemporary research. Here, we show how DeepTSS can unleash the full potential of an already popular and mature method such as CAGE, and push the boundaries of coding and non-coding gene expression regulator research even further., (© 2022. The Author(s).)

Leishmania parasites are capable of effectively invading dendritic cells (DCs), a cell population orchestrating immune responses against several diseases, including leishmaniasis, by bridging innate and adaptive immunity. Leishmania on the other hand has evolved various mechanisms to subvert DCs activation and establish infection. Thus, the transcriptional profile of DCs derived from bone marrow (BMDCs) that have been infected with Leishmania infantum parasite or of DCs exposed to chemically inactivated parasites was investigated via RNA sequencing, aiming to better understand the host-pathogen interplay. Flow cytometry analysis revealed that L. infantum actively inhibits maturation of not only infected but also bystander BMDCs. Analysis of double-sorted L. infantum infected BMDCs revealed significantly increased expression of genes mainly associated with metabolism and particularly glycolysis. Moreover, differentially expressed genes (DEGs) related to DC-T cell interactions were also found to be upregulated exclusively in infected BMDCs. On the contrary, transcriptome analysis of fixed parasites containing BMDCs indicated that energy production was mediated through TCA cycle and oxidative phosphorylation. In addition, DEGs related to differentiation of DCs leading to activation and differentiation of Th17 subpopulations were detected. These findings suggest an important role of metabolism on DCs- Leishmania interplay and eventually disease establishment.

Bidirectional signalling between the tumour and stroma shapes tumour aggressiveness and metastasis. ATF4 is a major effector of the Integrated Stress Response, a homeostatic mechanism that couples cell growth and survival to bioenergetic demands. Using conditional knockout ATF4 mice, we show that global, or fibroblast-specific loss of host ATF4, results in deficient vascularization and a pronounced growth delay of syngeneic melanoma and pancreatic tumours. Single-cell transcriptomics of tumours grown in Atf4 Δ/Δ mice uncovered a reduction in activation markers in perivascular cancer-associated fibroblasts (CAFs). Atf4 Δ/Δ fibroblasts displayed significant defects in collagen biosynthesis and deposition and a reduced ability to support angiogenesis. Mechanistically, ATF4 regulates the expression of the Col1a1 gene and levels of glycine and proline, the major amino acids of collagen. Analyses of human melanoma and pancreatic tumours revealed a strong correlation between ATF4 and collagen levels. Our findings establish stromal ATF4 as a key driver of CAF functionality, malignant progression and metastasis., (© 2022. The Author(s).)

We introduce AGAMEMNON ( https://github.com/ivlachos/agamemnon ) for the acquisition of microbial abundances from shotgun metagenomics and metatranscriptomic samples, single-microbe sequencing experiments, or sequenced host samples. AGAMEMNON delivers accurate abundances at genus, species, and strain resolution. It incorporates a time and space-efficient indexing scheme for fast pattern matching, enabling indexing and analysis of vast datasets with widely available computational resources. Host-specific modules provide exceptional accuracy for microbial abundance quantification from tissue RNA/DNA sequencing, enabling the expansion of experiments lacking metagenomic/metatranscriptomic analyses. AGAMEMNON provides an R-Shiny application, permitting performance of investigations and visualizations from a graphics interface., (© 2022. The Author(s).)

microRNAs (miRNAs) are short (∼23nt) single-stranded non-coding RNAs that act as potent post-transcriptional gene expression regulators. Information about miRNA expression and distribution across cell types and tissues is crucial to the understanding of their function and for their translational use as biomarkers or therapeutic targets. DIANA-miTED is the most comprehensive and systematic collection of miRNA expression values derived from the analysis of 15 183 raw human small RNA-Seq (sRNA-Seq) datasets from the Sequence Read Archive (SRA) and The Cancer Genome Atlas (TCGA). Metadata quality maximizes the utility of expression atlases, therefore we manually curated SRA and TCGA-derived information to deliver a comprehensive and standardized set, incorporating in total 199 tissues, 82 anatomical sublocations, 267 cell lines and 261 diseases. miTED offers rich instant visualizations of the expression and sample distributions of requested data across variables, as well as study-wide diagrams and graphs enabling efficient content exploration. Queries also generate links towards state-of-the-art miRNA functional resources, deeming miTED an ideal starting point for expression retrieval, exploration, comparison, and downstream analysis, without requiring bioinformatics support or expertise. DIANA-miTED is freely available at http://www.microrna.gr/mited., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

In studies of electron and proton radiotherapy, ultrahigh dose rates of FLASH radiotherapy appear to produce fewer toxicities than standard dose rates while maintaining local tumor control. FLASH-proton radiotherapy (F-PRT) brings the spatial advantages of PRT to FLASH dose rates (>40 Gy/second), making it important to understand if and how F-PRT spares normal tissues while providing antitumor efficacy that is equivalent to standard-proton radiotherapy (S-PRT). Here we studied PRT damage to skin and mesenchymal tissues of muscle and bone and found that F-PRT of the C57BL/6 murine hind leg produced fewer severe toxicities leading to death or requiring euthanasia than S-PRT of the same dose. RNA-seq analyses of murine skin and bone revealed pathways upregulated by S-PRT yet unaltered by F-PRT, such as apoptosis signaling and keratinocyte differentiation in skin, as well as osteoclast differentiation and chondrocyte development in bone. Corroborating these findings, F-PRT reduced skin injury, stem cell depletion, and inflammation, mitigated late effects including lymphedema, and decreased histopathologically detected myofiber atrophy, bone resorption, hair follicle atrophy, and epidermal hyperplasia. F-PRT was equipotent to S-PRT in control of two murine sarcoma models, including at an orthotopic intramuscular site, thereby establishing its relevance to mesenchymal cancers. Finally, S-PRT produced greater increases in TGFβ1 in murine skin and the skin of canines enrolled in a phase I study of F-PRT versus S-PRT. Collectively, these data provide novel insights into F-PRT-mediated tissue sparing and support its ongoing investigation in applications that would benefit from this sparing of skin and mesenchymal tissues. SIGNIFICANCE: These findings will spur investigation of FLASH radiotherapy in sarcoma and additional cancers where mesenchymal tissues are at risk, including head and neck cancer, breast cancer, and pelvic malignancies., (©2021 The Authors; Published by the American Association for Cancer Research.)

Only recently, microRNAs (miRNAs) were found to exist in traceable and distinctive amounts in the human circulatory system, bringing forth the intriguing possibility of using them as minimally invasive biomarkers. miRNAs are short non-coding RNAs that act as potent post-transcriptional regulators of gene expression. Extensive studies in cancer and other disease landscapes investigate the protective/pathogenic functions of dysregulated miRNAs, as well as their biomarker potential. A specialized resource amassing experimentally verified, circulating miRNA biomarkers does not exist. We queried the existing literature to identify articles assessing diagnostic/prognostic roles of miRNAs in blood, serum, or plasma samples. Articles were scrutinized in order to exclude instances lacking sufficient experimental documentation or employing no biomarker assessment methods. We incorporated information from more than 200 biomedical articles, annotating crucial meta-information including cohort sizes, inclusion-exclusion criteria, disease/healthy confirmation methods and quantification details. miRNAs and diseases were systematically characterized using reference resources. Our circulating miRNA biomarker collection is provided as an online database, plasmiR . It consists of 1021 entries regarding 251 miRNAs and 112 diseases. More than half of plasmiR 's entries refer to cancerous and neoplastic conditions, 183 of them (32%) describing prognostic associations. plasmiR facilitates smart queries, emphasizing visualization and exploratory modes for all researchers.

We present Peryton (https://dianalab.e-ce.uth.gr/peryton/), a database of experimentally supported microbe-disease associations. Its first version constitutes a novel resource hosting more than 7900 entries linking 43 diseases with 1396 microorganisms. Peryton's content is exclusively sustained by manual curation of biomedical articles. Diseases and microorganisms are provided in a systematic, standardized manner using reference resources to create database dictionaries. Information about the experimental design, study cohorts and the applied high- or low-throughput techniques is meticulously annotated and catered to users. Several functionalities are provided to enhance user experience and enable ingenious use of Peryton. One or more microorganisms and/or diseases can be queried at the same time. Advanced filtering options and direct text-based filtering of results enable refinement of returned information and the conducting of tailored queries suitable to different research questions. Peryton also provides interactive visualizations to effectively capture different aspects of its content and results can be directly downloaded for local storage and downstream analyses. Peryton will serve as a valuable source, enabling scientists of microbe-related disease fields to form novel hypotheses but, equally importantly, to assist in cross-validation of findings., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Long noncoding RNAs (lncRNAs) are noncoding transcripts, usually longer than 200 nt, that constitute one of the largest and significantly heterogeneous RNA families. The annotation of lncRNAs and the characterization of their function is a constantly evolving field. LncRNA interplay with microRNAs (miRNAs) is thoroughly studied in several physiological and disease states. miRNAs are small noncoding RNAs (~22 nt) that posttranscriptionally regulate the expression of protein coding genes, through mRNA target cleavage, degradation or direct translational suppression. miRNAs can affect lncRNA half-life by promoting their degradation, or lncRNAs can act as miRNA "sponges," reducing miRNA regulatory effect on target mRNAs. This chapter outlines the miRNA-lncRNA interplay and provides hands-on methodologies for experimentally supported and in silico-guided analyses. The proposed techniques are a valuable asset to further understand lncRNA functions and can be appropriately adapted to become the backbone for further downstream analyses., (© 2021. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)

microRNAs (miRNAs) are small non-coding RNAs (~22 nts) that are considered central post-transcriptional regulators of gene expression and key components in many pathological conditions. Next-Generation Sequencing (NGS) technologies have led to inexpensive, massive data production, revolutionizing every research aspect in the fields of biology and medicine. Particularly, small RNA-Seq (sRNA-Seq) enables small non-coding RNA quantification on a high-throughput scale, providing a closer look into the expression profiles of these crucial regulators within the cell. Here, we present DIANA-microRNA-Analysis-Pipeline (DIANA-mAP), a fully automated computational pipeline that allows the user to perform miRNA NGS data analysis from raw sRNA-Seq libraries to quantification and Differential Expression Analysis in an easy, scalable, efficient, and intuitive way. Emphasis has been given to data pre-processing, an early, critical step in the analysis for the robustness of the final results and conclusions. Through modularity, parallelizability and customization, DIANA-mAP produces high quality expression results, reports and graphs for downstream data mining and statistical analysis. In an extended evaluation, the tool outperforms similar tools providing pre-processing without any adapter knowledge. Closing, DIANA-mAP is a freely available tool. It is available dockerized with no dependency installations or standalone, accompanied by an installation manual through Github.

Helicobacter pylori infection induces a plethora of DNA damages. Gastric epithelial cells, in order to maintain genomic integrity, require an integrous DNA damage repair (DDR) machinery, which, however, is reported to be modulated by the infection. CagA is a major H. pylori virulence factor, associated with increased risk for gastric carcinogenesis. Its pathogenic activity is partly regulated by phosphorylation on EPIYA motifs. Our aim was to identify effects of H. pylori infection and CagA on DDR, investigating the transcriptome of AGS cells, infected with wild-type, ΔCagA and EPIYA-phosphorylation-defective strains. Upon RNA-Seq-based transcriptomic analysis, we observed that a notable number of DDR genes were found deregulated during the infection, potentially resulting to base excision repair and mismatch repair compromise and an intricate deregulation of nucleotide excision repair, homologous recombination and non-homologous end-joining. Transcriptome observations were further investigated on the protein expression level, utilizing infections of AGS and GES-1 cells. We observed that CagA contributed to the downregulation of Nth Like DNA Glycosylase 1 (NTHL1), MutY DNA Glycosylase (MUTYH), Flap Structure-Specific Endonuclease 1 (FEN1), RAD51 Recombinase, DNA Polymerase Delta Catalytic Subunit (POLD1), and DNA Ligase 1 (LIG1) and, contrary to transcriptome results, Apurinic/Apyrimidinic Endodeoxyribonuclease 1 (APE1) upregulation. Our study accentuates the role of CagA as a significant contributor of H. pylori infection-mediated DDR modulation, potentially disrupting the balance between DNA damage and repair, thus favoring genomic instability and carcinogenesis.

Integrating differential RNA and miRNA expression during neuronal lineage induction of human embryonic stem cells we identified miR-934, a primate-specific miRNA that displays a stage-specific expression pattern during progenitor expansion and early neuron generation. We demonstrate the biological relevance of this finding by comparison with data from early to mid-gestation human cortical tissue. Further we find that miR-934 directly controls progenitor to neuroblast transition and impacts on neurite growth of newborn neurons. In agreement, miR-934 targets are involved in progenitor proliferation and neuronal differentiation whilst miR-934 inhibition results in profound global transcriptome changes associated with neurogenesis, axonogenesis, neuronal migration and neurotransmission. Interestingly, miR-934 inhibition affects the expression of genes associated with the subplate zone, a transient compartment most prominent in primates that emerges during early corticogenesis. Our data suggest that mir-934 is a novel regulator of early human neurogenesis with potential implications for a species-specific evolutionary role in brain function., Competing Interests: KP, IV, MG, GK, AH, RM No competing interests declared, (© 2020, Prodromidou et al.)

Small non-coding RNAs (sncRNAs) play important roles in health and disease. Next Generation Sequencing (NGS) technologies are considered as the most powerful and versatile methodologies to explore small RNA (sRNA) transcriptomes in diverse experimental and clinical studies. Small RNA-Seq (sRNA-Seq) data analysis proved to be challenging due to non-unique genomic origin, short length, and abundant post-transcriptional modifications of sRNA species. Here, we present Manatee, an algorithm for the quantification of sRNA classes and the detection of novel expressed non-coding loci. Manatee combines prior annotation of sRNAs with reliable alignment density information and extensive rescue of usually neglected multimapped reads to provide accurate transcriptome-wide sRNA expression quantification. Comparison of Manatee against state-of-the-art implementations using real and simulated data demonstrates its high accuracy across diverse sRNA classes. Manatee also goes beyond common pipelines by identifying and quantifying expression from unannotated loci and microRNA isoforms (isomiRs). It is user-friendly, can be easily incorporated in pipelines, and provides a simplified output suitable for direct usage in downstream analyses and functional studies.

DIANA-LncBase v3.0 (www.microrna.gr/LncBase) is a reference repository with experimentally supported miRNA targets on non-coding transcripts. Its third version provides approximately half a million entries, corresponding to ∼240 000 unique tissue and cell type specific miRNA-lncRNA pairs. This compilation of interactions is derived from the manual curation of publications and the analysis of >300 high-throughput datasets. miRNA targets are supported by 14 experimental methodologies, applied to 243 distinct cell types and tissues in human and mouse. The largest part of the database is highly confident, AGO-CLIP-derived miRNA-binding events. LncBase v3.0 is the first relevant database to employ a robust CLIP-Seq-guided algorithm, microCLIP framework, to analyze 236 AGO-CLIP-Seq libraries and catalogue ∼370 000 miRNA binding events. The database was redesigned from the ground up, providing new functionalities. Known short variant information, on >67,000 experimentally supported target sites and lncRNA expression profiles in different cellular compartments are catered to users. Interactive visualization plots, portraying correlations of miRNA-lncRNA pairs, as well as lncRNA expression profiles in a wide range of cell types and tissues, are presented for the first time through a dedicated page. LncBase v3.0 constitutes a valuable asset for ncRNA research, providing new insights to the understanding of the still widely unexplored lncRNA functions., (© The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Visceral leishmaniasis (VL) caused by Leishmania donovani and L . infantum is a potentially fatal disease. To date there are no registered vaccines for disease prevention despite the fact that several vaccines are in preclinical development. Thus, new strategies are needed to improve vaccine efficacy based on a better understanding of the mechanisms mediating protective immunity and mechanisms of host immune responses subversion by immunopathogenic components of Leishmania . We found that mice vaccinated with CPA 162-189 -loaded p8-PLGA nanoparticles, an experimental nanovaccine, induced the differentiation of antigen-specific CD8 + T cells in spleen compared to control mice, characterized by increased dynamics of proliferation and high amounts of IFN-γ production after ex vivo re-stimulation with CPA 162-189 antigen. Vaccination with CPA 162-189 -loaded p8-PLGA nanoparticles resulted in about 80% lower parasite load in spleen and liver at 4 weeks after challenge with L. infantum promastigotes as compared to control mice. However, 16 weeks after infection the parasite load in spleen was comparable in both mouse groups. Decreased protection levels in vaccinated mice were followed by up-regulation of the anti-inflammatory IL-10 production although at lower levels in comparison to control mice. Microarray analysis in spleen tissue at 4 weeks post challenge revealed different immune-related profiles among the two groups. Specifically, vaccinated mice were characterized by similar profile to naïve mice. On the other hand, the transcriptome of the non-vaccinated mice was dominated by increased expression of genes related to interferon type I, granulocyte chemotaxis, and immune cells suppression. This profile was significantly enriched at 16 weeks post challenge, a time-point which is relative to disease establishment, and was common for both groups, further suggesting that type I signaling and granulocyte influx has a significant role in disease establishment, pathogenesis and eventually in decreased vaccine efficacy for stimulating long-term protection. Overall, we put a spotlight on host immune networks during active VL as potential targets to improve and design more effective vaccines against disease., (Copyright © 2019 Agallou, Athanasiou, Kammona, Tastsoglou, Hatzigeorgiou, Kiparissides and Karagouni.)

Argonaute crosslinking and immunoprecipitation (CLIP) experiments are the most widely used high-throughput methodologies for miRNA targetome characterization. The analysis of Photoactivatable Ribonucleoside-Enhanced (PAR) CLIP methodology focuses on sequence clusters containing T-to-C conversions. Here, we demonstrate for the first time that the non-T-to-C clusters, frequently observed in PAR-CLIP experiments, exhibit functional miRNA-binding events and strong RNA accessibility. This discovery is based on the analysis of an extensive compendium of bona fide miRNA-binding events, and is further supported by numerous miRNA perturbation experiments and structural sequencing data. The incorporation of these previously neglected clusters yields an average of 14% increase in miRNA-target interactions per PAR-CLIP library. Our findings are integrated in microCLIP ( www.microrna.gr/microCLIP ), a cutting-edge framework that combines deep learning classifiers under a super learning scheme. The increased performance of microCLIP in CLIP-Seq-guided detection of miRNA interactions, uncovers previously elusive regulatory events and miRNA-controlled pathways.

DIANA-TarBase v8 (http://www.microrna.gr/tarbase) is a reference database devoted to the indexing of experimentally supported microRNA (miRNA) targets. Its eighth version is the first database indexing >1 million entries, corresponding to ∼670 000 unique miRNA-target pairs. The interactions are supported by >33 experimental methodologies, applied to ∼600 cell types/tissues under ∼451 experimental conditions. It integrates information on cell-type specific miRNA-gene regulation, while hundreds of thousands of miRNA-binding locations are reported. TarBase is coming of age, with more than a decade of continuous support in the non-coding RNA field. A new module has been implemented that enables the browsing of interactions through different filtering combinations. It permits easy retrieval of positive and negative miRNA targets per species, methodology, cell type and tissue. An incorporated ranking system is utilized for the display of interactions based on the robustness of their supporting methodologies. Statistics, pie-charts and interactive bar-plots depicting the database content are available through a dedicated result page. An intuitive interface is introduced, providing a user-friendly application with flexible options to different queries., (© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.)

MicroRNAs (miRNAs) are small non-coding RNAs that can regulate gene expression playing vital role in nearly all biological pathways. Even though miRNAs have been intensely studied for more than two decades, information regarding miRNA transcription regulation remains limited. The rapid cleavage of primary miRNA transcripts (pri-miRNAs) by Drosha in the nucleus hinders their identification with conventional RNA-seq approaches. Identifying the transcription start site (TSS) of miRNAs will enable genome-wide identification of their expression regulators, including transcription factors (TFs), other non-coding RNAs (ncRNAs) and epigenetic modifiers, providing significant breakthroughs in understanding the mechanisms underlying miRNA expression in development and disease. Here we present a protocol that utilizes microTSS, a versatile computational framework for accurate and single-nucleotide resolution miRNA TSS predictions as well as miRGen, a database of miRNA gene TSSs coupled with genome-wide maps of TF binding sites.

α-Synuclein (αSyn) is the major gene linked to sporadic Parkinson's disease (PD), whereas the G209A (p.A53T) αSyn mutation causes a familial form of PD characterized by early onset and a generally severe phenotype, including nonmotor manifestations. Here we generated de novo induced pluripotent stem cells (iPSCs) from patients harboring the p.A53T mutation and developed a robust model that captures PD pathogenic processes under basal conditions. iPSC-derived mutant neurons displayed novel disease-relevant phenotypes, including protein aggregation, compromised neuritic outgrowth, and contorted or fragmented axons with swollen varicosities containing αSyn and Tau. The identified neuropathological features closely resembled those in brains of p.A53T patients. Small molecules targeting αSyn reverted the degenerative phenotype under both basal and induced stress conditions, indicating a treatment strategy for PD and other synucleinopathies. Furthermore, mutant neurons showed disrupted synaptic connectivity and widespread transcriptional alterations in genes involved in synaptic signaling, a number of which have been previously linked to mental disorders, raising intriguing implications for potentially converging disease mechanisms., Competing Interests: The authors declare no conflict of interest.

Aβ peptide that accumulates in Alzheimer's disease brain, derives from proteolytic processing of the amyloid precursor protein (APP) that exists in three main isoforms derived by alternative splicing. The isoform APP695, lacking exons 7 and 8, is predominately expressed in neurons and abnormal neuronal splicing of APP has been observed in the brain of patients with Alzheimer's disease. Herein, we demonstrate that expression of the neuronal members of the ELAVL protein family (nELAVLs) correlate with APP695 levels in vitro and in vivo. Moreover, we provide evidence that nELAVLs regulate the production of APP695; by using a series of reporters we show that concurrent binding of nELAVLs to sequences located both upstream and downstream of exon 7 is required for its skipping, whereas nELAVL-binding to a highly conserved U-rich sequence upstream of exon 8, is sufficient for its exclusion. Finally, we report that nELAVLs block APP exon 7 or 8 definition by reducing the binding of the essential splicing factor U2AF65, an effect facilitated by the concurrent binding of AUF-1. Our study provides new insights into the regulation of APP pre-mRNA processing, supports the role for nELAVLs as neuron-specific splicing regulators and reveals a novel function of AUF1 in alternative splicing.

microRNAs (miRNAs) are central regulators of gene expression. They are actively studied for their involvement in numerous physiological and pathological conditions but also as diagnostic biomarkers or promising therapeutic targets. The increased complexity of the miRNA interactomes hinders straightforward interpretation of miRNA expression differences between states and conditions. To this end, functional analysis web servers process and combine experimental and in silico data, enabling researchers to uncover targeted pathways and transcriptional mechanisms that are hidden within numerous interactions and vast expression datasets. DIANA-tools ( www.microrna.gr ) is a web server hosting state-of-the-art utilities and databases for miRNA functional investigation. Available utilities cover a wide scope of different needs and research scenarios, rendering DIANA website a one-stop-shop for miRNA analyses. The most commonly utilized databases and algorithms include DIANA-microT-CDS, DIANA-TarBase v7.0, DIANA-lncBase v2.0, DIANA-miRGen v3.0, DIANA-miRPath v3.0, and DIANA-mirExTra v2.0.In the presented protocol, we will utilize different online tools in order to explore miRNA functions and to identify probable targets of interest for downstream analyses and wet lab experiments. The combined use of different applications from the DIANA suite can shed light to numerous different aspects of miRNA regulation and regulatory function, without the necessity for extensive bioinformatics expertise or computational infrastructure.

Background: The Mediterranean fruit fly (medfly), Ceratitis capitata, is a major destructive insect pest due to its broad host range, which includes hundreds of fruits and vegetables. It exhibits a unique ability to invade and adapt to ecological niches throughout tropical and subtropical regions of the world, though medfly infestations have been prevented and controlled by the sterile insect technique (SIT) as part of integrated pest management programs (IPMs). The genetic analysis and manipulation of medfly has been subject to intensive study in an effort to improve SIT efficacy and other aspects of IPM control., Results: The 479 Mb medfly genome is sequenced from adult flies from lines inbred for 20 generations. A high-quality assembly is achieved having a contig N50 of 45.7 kb and scaffold N50 of 4.06 Mb. In-depth curation of more than 1800 messenger RNAs shows specific gene expansions that can be related to invasiveness and host adaptation, including gene families for chemoreception, toxin and insecticide metabolism, cuticle proteins, opsins, and aquaporins. We identify genes relevant to IPM control, including those required to improve SIT., Conclusions: The medfly genome sequence provides critical insights into the biology of one of the most serious and widespread agricultural pests. This knowledge should significantly advance the means of controlling the size and invasive potential of medfly populations. Its close relationship to Drosophila, and other insect species important to agriculture and human health, will further comparative functional and structural studies of insect genomes that should broaden our understanding of gene family evolution.

microRNAs (miRNAs) are short non-coding RNAs (∼22 nts) present in animals, plants, and viruses. They are considered central post-transcriptional regulators of gene expression and are key components in a great number of physiological and pathological conditions. The accurate characterization of their targets is considered essential to a series of applications and basic or applied research settings. DIANA-TarBase (http://www.microrna.gr/tarbase) was initially launched in 2006. It is a reference repository indexing experimentally derived miRNA-gene interactions in different cell types, tissues, and conditions across numerous species. This unit focuses on the study of experimentally supported miRNA-gene interactions, as well as their functional interpretation through the use of available tools in the DIANA suite (http://www.microrna.gr). The proposed use-case scenarios are presented in protocols, describing how to utilize the DIANA-TarBase database and DIANA-microT-CDS server and perform miRNA-targeted pathway analysis with DIANA-miRPath-v3. All analyses are directly invoked or initiated from DIANA-TarBase. © 2016 by John Wiley & Sons, Inc., (Copyright © 2016 John Wiley & Sons, Inc.)

Differential expression analysis (DEA) is one of the main instruments utilized for revealing molecular mechanisms in pathological and physiological conditions. DIANA-mirExTra v2.0 (http://www.microrna.gr/mirextrav2) performs a combined DEA of mRNAs and microRNAs (miRNAs) to uncover miRNAs and transcription factors (TFs) playing important regulatory roles between two investigated states. The web server uses as input miRNA/RNA-Seq read count data sets that can be uploaded for analysis. Users can combine their data with 350 small-RNA-Seq and 65 RNA-Seq in-house analyzed libraries which are provided by DIANA-mirExTra v2.0.The web server utilizes miRNA:mRNA, TF:mRNA and TF:miRNA interactions derived from extensive experimental data sets. More than 450 000 miRNA interactions and 2 000 000 TF binding sites from specific or high-throughput techniques have been incorporated, while accurate miRNA TSS annotation is obtained from microTSS experimental/in silico framework. These comprehensive data sets enable users to perform analyses based solely on experimentally supported information and to uncover central regulators within sequencing data: miRNAs controlling mRNAs and TFs regulating mRNA or miRNA expression. The server also supports predicted miRNA:gene interactions from DIANA-microT-CDS for 4 species (human, mouse, nematode and fruit fly). DIANA-mirExTra v2.0 has an intuitive user interface and is freely available to all users without any login requirement., (© The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.)

The canonical Wnt pathway plays a central role in stem cell maintenance, differentiation, and proliferation in the intestinal epithelium. Constitutive, aberrant activity of the TCF4/β-catenin transcriptional complex is the primary transforming factor in colorectal cancer. We identify a nuclear long non-coding RNA, termed WiNTRLINC1, as a direct target of TCF4/β-catenin in colorectal cancer cells. WiNTRLINC1 positively regulates the expression of its genomic neighbor ASCL2, a transcription factor that controls intestinal stem cell fate. WiNTRLINC1 interacts with TCF4/β-catenin to mediate the juxtaposition of its promoter with the regulatory regions of ASCL2. ASCL2, in turn, regulates WiNTRLINC1 transcriptionally, closing a feedforward regulatory loop that controls stem cell-related gene expression. This regulatory circuitry is highly amplified in colorectal cancer and correlates with increased metastatic potential and decreased patient survival. Our results uncover the interplay between non-coding RNA-mediated regulation and Wnt signaling and point to the diagnostic and therapeutic potential of WiNTRLINC1., (Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.)

microRNAs (miRNAs) are short non-coding RNAs (ncRNAs) that act as post-transcriptional regulators of coding gene expression. Long non-coding RNAs (lncRNAs) have been recently reported to interact with miRNAs. The sponge-like function of lncRNAs introduces an extra layer of complexity in the miRNA interactome. DIANA-LncBase v1 provided a database of experimentally supported and in silico predicted miRNA Recognition Elements (MREs) on lncRNAs. The second version of LncBase (www.microrna.gr/LncBase) presents an extensive collection of miRNA:lncRNA interactions. The significantly enhanced database includes more than 70 000 low and high-throughput, (in)direct miRNA:lncRNA experimentally supported interactions, derived from manually curated publications and the analysis of 153 AGO CLIP-Seq libraries. The new experimental module presents a 14-fold increase compared to the previous release. LncBase v2 hosts in silico predicted miRNA targets on lncRNAs, identified with the DIANA-microT algorithm. The relevant module provides millions of predicted miRNA binding sites, accompanied with detailed metadata and MRE conservation metrics. LncBase v2 caters information regarding cell type specific miRNA:lncRNA regulation and enables users to easily identify interactions in 66 different cell types, spanning 36 tissues for human and mouse. Database entries are also supported by accurate lncRNA expression information, derived from the analysis of more than 6 billion RNA-Seq reads., (© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.)

microRNAs (miRNAs) are small non-coding RNAs that actively fine-tune gene expression. The accurate characterization of the mechanisms underlying miRNA transcription regulation will further expand our knowledge regarding their implication in homeostatic and pathobiological networks. Aim of DIANA-miRGen v3.0 (http://www.microrna.gr/mirgen) is to provide for the first time accurate cell-line-specific miRNA gene transcription start sites (TSSs), coupled with genome-wide maps of transcription factor (TF) binding sites in order to unveil the mechanisms of miRNA transcription regulation. To this end, more than 7.3 billion RNA-, ChIP- and DNase-Seq next generation sequencing reads were analyzed/assembled and combined with state-of-the-art miRNA TSS prediction and TF binding site identification algorithms. The new database schema and web interface facilitates user interaction, provides advanced queries and innate connection with other DIANA resources for miRNA target identification and pathway analysis. The database currently supports 276 miRNA TSSs that correspond to 428 precursors and >19M binding sites of 202 TFs on a genome-wide scale in nine cell-lines and six tissues of Homo sapiens and Mus musculus., (© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Long noncoding RNAs (lncRNAs) are noncoding transcripts usually longer than 200 nts that have recently emerged as one of the largest and significantly diverse RNA families. The biological role and functions of lncRNAs are still mostly uncharacterized. Their target-mimetic, sponge/decoy function on microRNAs was recently uncovered. miRNAs are a class of noncoding RNA species (~22 nts) that play a central role in posttranscriptional regulation of protein coding genes by mRNA cleavage, direct translational repression and/or mRNA destabilization. LncRNAs can act as miRNA sponges, reducing their regulatory effect on mRNAs. This function introduces an extra layer of complexity in the miRNA-target interaction network. This chapter focuses on the study of miRNA-lncRNA interactions with either in silico or experimentally supported analyses. The proposed methodologies can be appropriately adapted in order to become the backbone of advanced multistep functional miRNA analyses.

The functional characterization of miRNAs is still an open challenge. Here, we present DIANA-miRPath v3.0 (http://www.microrna.gr/miRPathv3) an online software suite dedicated to the assessment of miRNA regulatory roles and the identification of controlled pathways. The new miRPath web server renders possible the functional annotation of one or more miRNAs using standard (hypergeometric distributions), unbiased empirical distributions and/or meta-analysis statistics. DIANA-miRPath v3.0 database and functionality have been significantly extended to support all analyses for KEGG molecular pathways, as well as multiple slices of Gene Ontology (GO) in seven species (Homo sapiens, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Caenorhabditis elegans, Gallus gallus and Danio rerio). Importantly, more than 600 000 experimentally supported miRNA targets from DIANA-TarBase v7.0 have been incorporated into the new schema. Users of DIANA-miRPath v3.0 can harness this wealth of information and substitute or combine the available in silico predicted targets from DIANA-microT-CDS and/or TargetScan v6.2 with high quality experimentally supported interactions. A unique feature of DIANA-miRPath v3.0 is its redesigned Reverse Search module, which enables users to identify and visualize miRNAs significantly controlling selected pathways or belonging to specific GO categories based on in silico or experimental data. DIANA-miRPath v3.0 is freely available to all users without any login requirement., (© The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.)

microRNAs (miRNAs) are short non-coding RNA species, which act as potent gene expression regulators. Accurate identification of miRNA targets is crucial to understanding their function. Currently, hundreds of thousands of miRNA:gene interactions have been experimentally identified. However, this wealth of information is fragmented and hidden in thousands of manuscripts and raw next-generation sequencing data sets. DIANA-TarBase was initially released in 2006 and it was the first database aiming to catalog published experimentally validated miRNA:gene interactions. DIANA-TarBase v7.0 (http://www.microrna.gr/tarbase) aims to provide for the first time hundreds of thousands of high-quality manually curated experimentally validated miRNA:gene interactions, enhanced with detailed meta-data. DIANA-TarBase v7.0 enables users to easily identify positive or negative experimental results, the utilized experimental methodology, experimental conditions including cell/tissue type and treatment. The new interface provides also advanced information ranging from the binding site location, as identified experimentally as well as in silico, to the primer sequences used for cloning experiments. More than half a million miRNA:gene interactions have been curated from published experiments on 356 different cell types from 24 species, corresponding to 9- to 250-fold more entries than any other relevant database. DIANA-TarBase v7.0 is freely available., (© The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.)

A large fraction of microRNAs (miRNAs) are derived from intergenic non-coding loci and the identification of their promoters remains 'elusive'. Here, we present microTSS, a machine-learning algorithm that provides highly accurate, single-nucleotide resolution predictions for intergenic miRNA transcription start sites (TSSs). MicroTSS integrates high-resolution RNA-sequencing data with active transcription marks derived from chromatin immunoprecipitation and DNase-sequencing to enable the characterization of tissue-specific promoters. MicroTSS is validated with a specifically designed Drosha-null/conditional-null mouse model, generated using the conditional by inversion (COIN) methodology. Analyses of global run-on sequencing data revealed numerous pri-miRNAs in human and mouse either originating from divergent transcription at promoters of active genes or partially overlapping with annotated long non-coding RNAs. MicroTSS is readily applicable to any cell or tissue samples and constitutes the missing part towards integrating the regulation of miRNA transcription into the modelling of tissue-specific regulatory networks.