Expanding the horizons of microRNA bioinformatics

NAP-seq reveals multiple classes of structured noncoding RNAs with regulatory functions

Up to 80% of the human genome produces "dark matter" RNAs, most of which are noncapped RNAs (napRNAs) that frequently act as noncoding RNAs (ncRNAs) to modulate gene expression. Here, by developing a method, NAP-seq, to globally profile the full-length sequences of napRNAs with various terminal modifications at single-nucleotide resolution, we reveal diverse classes of structured ncRNAs. We discover stably expressed linear intron RNAs (sliRNAs), a class of snoRNA-intron RNAs (snotrons), a class of RNAs embedded in miRNA spacers (misRNAs) and thousands of previously uncharacterized structured napRNAs in humans and mice. These napRNAs undergo dynamic changes in response to various stimuli and differentiation stages. Importantly, we show that a structured napRNA regulates myoblast differentiation and a napRNA DINAP interacts with dyskerin pseudouridine synthase 1 (DKC1) to promote cell proliferation by maintaining DKC1 protein stability. Our approach establishes a paradigm for discovering various classes of ncRNAs with regulatory functions.

The landscape of microRNA interaction annotation: analysis of three rare disorders as a case study

In recent years, a huge amount of data on ncRNA interactions has been described in scientific papers and databases. Although considerable effort has been made to annotate the available knowledge in public repositories, there are still significant discrepancies in how different resources capture and interpret data on ncRNA functional and physical associations. In the present paper, we present a collection of microRNA-mRNA interactions annotated from the scientific literature following recognized standard criteria and focused on microRNAs, which regulate genes associated with rare diseases as a case study. The list of protein-coding genes with a known role in specific rare diseases was retrieved from the Genome England PanelApp, and associated microRNA-mRNA interactions were annotated in the IntAct database and compared with other datasets. RNAcentral identifiers were used for unambiguous, stable identification of ncRNAs. The information about the interaction was enhanced by a detailed description of the cell types and experimental conditions, providing a computer-interpretable summary of the published data, integrated with the huge amount of protein interactions already gathered in the database. Furthermore, for each interaction, the binding sites of the microRNA are precisely mapped on a well-defined mRNA transcript of the target gene. This information is crucial to conceive and design optimal microRNA mimics or inhibitors to interfere in vivo with a deregulated process. As these approaches become more feasible, high-quality, reliable networks of microRNA interactions are needed to help, for instance, in the selection of the best target to be inhibited and to predict potential secondary off-target effects. Database URL https://www.ebi.ac.uk/intact.

Insights into Online microRNA Bioinformatics Tools

MicroRNAs (miRNAs) are members of the small non-coding RNA family regulating gene expression at the post-transcriptional level. MiRNAs have been found to have critical roles in various biological and pathological processes. Research in this field has significantly progressed, with increased recognition of the importance of miRNA regulation. As a result of the vast data and information available regarding miRNAs, numerous online tools have emerged to address various biological questions related to their function and influence across essential cellular processes. This review includes a brief introduction to available resources for an investigation covering aspects such as miRNA sequences, target prediction/validation, miRNAs associated with disease, pathway analysis and genetic variants within miRNAs.

miRinGO: Prediction of Biological Processes Indirectly Targeted by Human microRNAs

MicroRNAs (miRNAs) are small non-coding RNAs that are known for their role in the post-transcriptional regulation of target genes. Typically, their functions are predicted by first identifying their target genes and then finding biological processes enriched in these targets. Current tools for miRNA functional analysis use only genes with physical binding sites as their targets and exclude other genes that are indirectly targeted transcriptionally through transcription factors. Here, we introduce a method to predict gene ontology (GO) annotations indirectly targeted by microRNAs. The proposed method resulted in better performance in predicting known miRNA-GO term associations compared to the canonical approach. To facilitate miRNA GO enrichment analysis, we developed an R Shiny application, miRinGO, that is freely available online at GitHub.

Beyond AOPs: A Mechanistic Evaluation of NAMs in DART Testing

New Approach Methodologies (NAMs) promise to offer a unique opportunity to enable human-relevant safety decisions to be made without the need for animal testing in the context of exposure-driven Next Generation Risk Assessment (NGRA). Protecting human health against the potential effects a chemical may have on embryo-foetal development and/or aspects of reproductive biology using NGRA is particularly challenging. These are not single endpoint or health effects and risk assessments have traditionally relied on data from Developmental and Reproductive Toxicity (DART) tests in animals. There are numerous Adverse Outcome Pathways (AOPs) that can lead to DART, which means defining and developing strict testing strategies for every AOP, to predict apical outcomes, is neither a tenable goal nor a necessity to ensure NAM-based safety assessments are fit-for-purpose. Instead, a pragmatic approach is needed that uses the available knowledge and data to ensure NAM-based exposure-led safety assessments are sufficiently protective. To this end, the mechanistic and biological coverage of existing NAMs for DART were assessed and gaps to be addressed were identified, allowing the development of an approach that relies on generating data relevant to the overall mechanisms involved in human reproduction and embryo-foetal development. Using the knowledge of cellular processes and signalling pathways underlying the key stages in reproduction and development, we have developed a broad outline of endpoints informative of DART. When the existing NAMs were compared against this outline to determine whether they provide comprehensive coverage when integrated in a framework, we found them to generally cover the reproductive and developmental processes underlying the traditionally evaluated apical endpoint studies. The application of this safety assessment framework is illustrated using an exposure-led case study.

Observation of Unique Circulating miRNA Signatures in Non-Human Primates Exposed to Total-Body vs. Whole Thorax Lung Irradiation

A radiological/nuclear (RAD-NUC) incident, especially in an urban setting, results in diverse radiation-induced injuries due to heterogeneities in dose, the extent of partial-body shielding, human biodiversity and pre-existing health conditions. For example, acute radiation syndrome (ARS) can result in death within days to weeks of exposure to 0.7-10 Gy doses and is associated with destruction of the bone marrow, known as hematopoietic ARS (H-ARS). However, partial-body shielding that spares a portion of the bone marrow from exposure can significantly reduce the occurrence of H-ARS, but delayed effects of acute radiation exposure (DEARE) can still occur within months or years after exposure depending on the individual. In a mass casualty event, ideal triage must be able to pre-symptomatically identify individuals likely to develop radiation-induced injuries and provide an appropriate treatment plan. Today, while there are FDA approved treatments for hematopoietic ARS, there are no approved diagnosis for radiation injury and no approved treatments for the broad spectra of injuries associated with radiation. This has resulted in a major capability gap in the nations preparedness to a potentially catastrophic RAD-NUC event. Circulating microRNA (miRNA) are a promising class of biomarkers for this application because the molecules are accessible via a routine blood draw and are excreted by various tissues throughout the body. To test if miRNA can be used to predict distinct tissue-specific radiation-induced injuries, we compared the changes to the circulating miRNA profiles after total-body irradiation (TBI) and whole thorax lung irradiation (WTLI) in non-human primates at doses designed to induce ARS (day 2 postirradiation; 2-6.5 Gy) and DEARE (day 15 postirradiation; 9.8 or 10.7 Gy), respectively. In both models, miRNA sequences were identified that correlated with the onset of severe neutropenia (counts <500 µL-1; TBI) or survival (WTLI). This method identified panels of eleven miRNA for both model and assigned functional roles for the panel members using gene ontology enrichment analysis. A common signature of radiation-induced injury was observed in both models: apoptosis, DNA damage repair, p53 signaling, pro-inflammatory response, and growth factor/cytokine signaling pathways were predicted to be disrupted. In addition, injury-specific pathways were identified. In TBI, pathways associated with ubiquitination, specifically of histone H2A, were enriched, suggesting more impact to DNA damage repair mechanisms and apoptosis. In WTLI, pro-fibrotic pathways including transforming growth factor (TGF-β) and bone morphogenetic protein (BMP) signaling pathways were enriched, consistent with the onset of late lung injury. These results suggest that miRNA may indeed be able to predict the onset of distinct types of radiation-induced injuries.

The Gene Regulation Knowledge Commons: The action area of GREEKC

The COST Action Gene Regulation Ensemble Effort for the Knowledge Commons (GREEKC, CA15205, www.greekc.org) organized nine workshops in a four-year period, starting September 2016. The workshops brought together a wide range of experts from all over the world working on various parts of the knowledge cycle that is central to understanding gene regulatory mechanisms. The discussions between ontologists, curators, text miners, biologists, bioinformaticians, philosophers and computational scientists spawned a host of activities aimed to update and standardise existing knowledge management workflows, encourage new experimental approaches and thoroughly involve end-users in the process to design the Gene Regulation Knowledge Commons (GRKC). The GREEKC consortium describes its main achievements, contextualised in a state-of-the-art of current tools and resources that today represent the GRKC.

Gene Ontology curation of the blood-brain barrier to improve the analysis of Alzheimer's and other neurological diseases

The role of the blood-brain barrier (BBB) in Alzheimer's and other neurodegenerative diseases is still the subject of many studies. However, those studies using high-throughput methods have been compromised by the lack of Gene Ontology (GO) annotations describing the role of proteins in the normal function of the BBB. The GO Consortium provides a gold-standard bioinformatics resource used for analysis and interpretation of large biomedical data sets. However, the GO is also used by other research communities and, therefore, must meet a variety of demands on the breadth and depth of information that is provided. To meet the needs of the Alzheimer's research community we have focused on the GO annotation of the BBB, with over 100 transport or junctional proteins prioritized for annotation. This project has led to a substantial increase in the number of human proteins associated with BBB-relevant GO terms as well as more comprehensive annotation of these proteins in many other processes. Furthermore, data describing the microRNAs that regulate the expression of these priority proteins have also been curated. Thus, this project has increased both the breadth and depth of annotation for these prioritized BBB proteins. Database URLhttps://www.ebi.ac.uk/QuickGO/.

The Role of Deregulated MicroRNAs in Age-Related Macular Degeneration Pathology

Purpose

We previously identified three microRNAs (miRNAs) with significantly increased expression in the serum of patients with age-related macular degeneration (AMD) compared with healthy controls. Our objective was to identify potential functional roles of these upregulated miRNAs (miR-19a, miR-126, and miR-410) in AMD, using computational tools for miRNAs prediction and identification, and to demonstrate the miRNAs target genes and signaling pathways. We also aim to demonstrate the pathologic role of isolated sera-derived exosomes from patients with AMD and controls using in vitro models.

Methods

miR-19a, miR-126, and miR-410 were investigated using bioinformatic approaches, including DIANA-mirPath and miR TarBase. Data on the resulting target genes and signaling pathways were incorporated with the differentially expressed miRNAs in AMD. Apoptosis markers, human apoptosis miRNAs polymerase chain reaction arrays and angiogenesis/vasculogenesis assays were performed by adding serum-isolated AMD patient or control patient derived exosomes into an in vitro human angiogenesis model and ARPE-19 cell lines.

Results

A number of pathways known to be involved in AMD development and progression were predicted, including the vascular endothelial growth factor signaling, apoptosis, and neurodegenerative pathways. The study also provides supporting evidence for the involvement of serum-isolated AMD-derived exosomes in the pathology of AMD, via apoptosis and/or angiogenesis.

Conclusions

miR-19a, miR-126, miR-410 and their target genes had a significant correlation with AMD pathogenesis. As such, they could be potential new targets as predictive biomarkers or therapies for patients with AMD.

Translational Relevance

The functional analysis and the pathologic role of altered miRNA expression in AMD may be applicable in developing new therapies for AMD through the disruption of individual or multiple pathophysiologic pathways.

emiRIT: a text-mining-based resource for microRNA information

microRNAs (miRNAs) are essential gene regulators, and their dysregulation often leads to diseases. Easy access to miRNA information is crucial for interpreting generated experimental data, connecting facts across publications and developing new hypotheses built on previous knowledge. Here, we present extracting miRNA Information from Text (emiRIT), a text-miningbased resource, which presents miRNA information mined from the literature through a user-friendly interface. We collected 149 ,233 miRNA –PubMed ID pairs from Medline between January 1997 and May 2020. emiRIT currently contains ‘miRNA –gene regulation’ (69 ,152 relations), ‘miRNA disease (cancer)’ (12 ,300 relations), ‘miRNA –biological process and pathways’ (23, 390 relations) and circulatory ‘miRNAs in extracellular locations’ (3782 relations). Biological entities and their relation to miRNAs were extracted from Medline abstracts using publicly available and in-house developed text-mining tools, and the entities were normalized to facilitate querying and integration. We built a database and an interface to store and access the integrated data, respectively. We provide an up-to-date and user-friendly resource to facilitate access to comprehensive miRNA information from the literature on a large scale, enabling users to navigate through different roles of miRNA and examine them in a context specific to their information needs. To assess our resource’s information coverage, we have conducted two case studies focusing on the target and differential expression information of miRNAs in the context of cancer and a third case study to assess the usage of emiRIT in the curation of miRNA information.

Database URL: https://research.bioinformatics.udel.edu/emirit/

Gene Ontology Curation of Neuroinflammation Biology Improves the Interpretation of Alzheimer's Disease Gene Expression Data

BACKGROUND

Gene Ontology (GO) is a major bioinformatic resource used for analysis of large biomedical datasets, for example from genome-wide association studies, applied universally across biological fields, including Alzheimer's disease (AD) research.

OBJECTIVE

We aim to demonstrate the applicability of GO for interpretation of AD datasets to improve the understanding of the underlying molecular disease mechanisms, including the involvement of inflammatory pathways and dysregulated microRNAs (miRs).

METHODS

We have undertaken a systematic full article GO annotation approach focused on microglial proteins implicated in AD and the miRs regulating their expression. PANTHER was used for enrichment analysis of previously published AD data. Cytoscape was used for visualizing and analyzing miR-target interactions captured from published experimental evidence.

RESULTS

We contributed 3,084 new annotations for 494 entities, i.e., on average six new annotations per entity. This included a total of 1,352 annotations for 40 prioritized microglial proteins implicated in AD and 66 miRs regulating their expression, yielding an average of twelve annotations per prioritized entity. The updated GO resource was then used to re-analyze previously published data. The re-analysis showed novel processes associated with AD-related genes, not identified in the original study, such as 'gliogenesis', 'regulation of neuron projection development', or 'response to cytokine', demonstrating enhanced applicability of GO for neuroscience research.

CONCLUSIONS

This study highlights ongoing development of the neurobiological aspects of GO and demonstrates the value of biocuration activities in the area, thus helping to delineate the molecular bases of AD to aid the development of diagnostic tools and treatments.

Integrative approaches for analysis of mRNA and microRNA high-throughput data

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Review on tools and databases linking miRNA and its mRNA targetome.

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Databases show little overlap in miRNA targetome predictions suggesting strong contextual effects.

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Deconvolution and deep learning approaches are promising new approaches to improve miRNA targetome predictions.

Advanced sequencing technologies such as RNASeq provide the means for production of massive amounts of data, including transcriptome-wide expression levels of coding RNAs (mRNAs) and non-coding RNAs such as miRNAs, lncRNAs, piRNAs and many other RNA species. In silico analysis of datasets, representing only one RNA species is well established and a variety of tools and pipelines are available. However, attaining a more systematic view of how different players come together to regulate the expression of a gene or a group of genes requires a more intricate approach to data analysis. To fully understand complex transcriptional networks, datasets representing different RNA species need to be integrated. In this review, we will focus on miRNAs as key post-transcriptional regulators summarizing current computational approaches for miRNA:target gene prediction as well as new data-driven methods to tackle the problem of comprehensively and accurately dissecting miRNome-targetome interactions.

RNAcentral 2021: secondary structure integration, improved sequence search and new member databases

RNAcentral is a comprehensive database of non-coding RNA (ncRNA) sequences that provides a single access point to 44 RNA resources and >18 million ncRNA sequences from a wide range of organisms and RNA types. RNAcentral now also includes secondary (2D) structure information for >13 million sequences, making RNAcentral the world's largest RNA 2D structure database. The 2D diagrams are displayed using R2DT, a new 2D structure visualization method that uses consistent, reproducible and recognizable layouts for related RNAs. The sequence similarity search has been updated with a faster interface featuring facets for filtering search results by RNA type, organism, source database or any keyword. This sequence search tool is available as a reusable web component, and has been integrated into several RNAcentral member databases, including Rfam, miRBase and snoDB. To allow for a more fine-grained assignment of RNA types and subtypes, all RNAcentral sequences have been annotated with Sequence Ontology terms. The RNAcentral database continues to grow and provide a central data resource for the RNA community. RNAcentral is freely available at https://rnacentral.org.

Can miRNAs Be Considered as Diagnostic and Therapeutic Molecules in Ischemic Stroke Pathogenesis?-Current Status

Ischemic stroke is one of the leading causes of death worldwide. Clinical manifestations of stroke are long-lasting and causing economic burden on the patients and society. Current therapeutic modalities to treat ischemic stroke (IS) are unsatisfactory due to the intricate pathophysiology and poor functional recovery of brain cellular compartment. MicroRNAs (miRNA) are endogenously expressed small non-coding RNA molecules, which can act as translation inhibitors and play a pivotal role in the pathophysiology associated with IS. Moreover, miRNAs may be used as potential diagnostic and therapeutic tools in clinical practice; yet, the complete role of miRNAs is enigmatic during IS. In this review, we explored the role of miRNAs in the regulation of stroke risk factors viz., arterial hypertension, metabolic disorders, and atherosclerosis. Furthermore, the role of miRNAs were reviewed during IS pathogenesis accompanied by excitotoxicity, oxidative stress, inflammation, apoptosis, angiogenesis, neurogenesis, and Alzheimer's disease. The functional role of miRNAs is a double-edged sword effect in cerebral ischemia as they could modulate pathological mechanisms associated with risk factors of IS. miRNAs pertaining to IS pathogenesis could be potential biomarkers for stroke; they could help researchers to identify a particular stroke type and enable medical professionals to evaluate the severity of brain injury. Thus, ascertaining the role of miRNAs may be useful in deciphering their diagnostic role consequently it is plausible to envisage a suitable therapeutic modality against IS.

Computational Methods and Software Tools for Functional Analysis of miRNA Data

miRNAs are important regulators of gene expression that play a key role in many biological processes. High-throughput techniques allow researchers to discover and characterize large sets of miRNAs, and enrichment analysis tools are becoming increasingly important in decoding which miRNAs are implicated in biological processes. Enrichment analysis of miRNA targets is the standard technique for functional analysis, but this approach carries limitations and bias; alternatives are currently being proposed, based on direct and curated annotations. In this review, we describe the two workflows of miRNAs enrichment analysis, based on target gene or miRNA annotations, highlighting statistical tests, software tools, up-to-date databases, and functional annotations resources in the study of metazoan miRNAs.

RNAcentral: a hub of information for non-coding RNA sequences

RNAcentral is a comprehensive database of non-coding RNA (ncRNA) sequences, collating information on ncRNA sequences of all types from a broad range of organisms. We have recently added a new genome mapping pipeline that identifies genomic locations for ncRNA sequences in 296 species. We have also added several new types of functional annotations, such as tRNA secondary structures, Gene Ontology annotations, and miRNA-target interactions. A new quality control mechanism based on Rfam family assignments identifies potential contamination, incomplete sequences, and more. The RNAcentral database has become a vital component of many workflows in the RNA community, serving as both the primary source of sequence data for academic and commercial groups, as well as a source of stable accessions for the annotation of genomic and functional features. These examples are facilitated by an improved RNAcentral web interface, which features an updated genome browser, a new sequence feature viewer, and improved text search functionality. RNAcentral is freely available at https://rnacentral.org.

miRBase: from microRNA sequences to function

miRBase catalogs, names and distributes microRNA gene sequences. The latest release of miRBase (v22) contains microRNA sequences from 271 organisms: 38 589 hairpin precursors and 48 860 mature microRNAs. We describe improvements to the database and website to provide more information about the quality of microRNA gene annotations, and the cellular functions of their products. We have collected 1493 small RNA deep sequencing datasets and mapped a total of 5.5 billion reads to microRNA sequences. The read mapping patterns provide strong support for the validity of between 20% and 65% of microRNA annotations in different well-studied animal genomes, and evidence for the removal of >200 sequences from the database. To improve the availability of microRNA functional information, we are disseminating Gene Ontology terms annotated against miRBase sequences. We have also used a text-mining approach to search for microRNA gene names in the full-text of open access articles. Over 500 000 sentences from 18 542 papers contain microRNA names. We score these sentences for functional information and link them with 12 519 microRNA entries. The sentences themselves, and word clouds built from them, provide effective summaries of the functional information about specific microRNAs. miRBase is publicly and freely available at http://mirbase.org/.

Non-coding RNA regulatory networks

It is well established that the vast majority of human RNA transcripts do not encode for proteins and that non-coding RNAs regulate cell physiology and shape cellular functions. A subset of them is involved in gene regulation at different levels, from epigenetic gene silencing to post-transcriptional regulation of mRNA stability. Notably, the aberrant expression of many non-coding RNAs has been associated with aggressive pathologies. Rapid advances in network biology indicates that the robustness of cellular processes is the result of specific properties of biological networks such as scale-free degree distribution and hierarchical modularity, suggesting that regulatory network analyses could provide new insights on gene regulation and dysfunction mechanisms. In this study we present an overview of public repositories where non-coding RNA-regulatory interactions are collected and annotated, we discuss unresolved questions for data integration and we recall existing resources to build and analyse networks.

Music-performance regulates microRNAs in professional musicians

Musical training and performance require precise integration of multisensory and motor centres of the human brain and can be regarded as an epigenetic modifier of brain functions. Numerous studies have identified structural and functional differences between the brains of musicians and non-musicians and superior cognitive functions in musicians. Recently, music-listening and performance has also been shown to affect the regulation of several genes, many of which were identified in songbird singing. MicroRNAs affect gene regulation and studying their expression may give new insights into the epigenetic effect of music. Here, we studied the effect of 2 hours of classical music-performance on the peripheral blood microRNA expressions in professional musicians with respect to a control activity without music for the same duration. As detecting transcriptomic changes in the functional human brain remains a challenge for geneticists, we used peripheral blood to study music-performance induced microRNA changes and interpreted the results in terms of potential effects on brain function, based on the current knowledge about the microRNA function in blood and brain. We identified significant (FDR <0.05) up-regulation of five microRNAs; hsa-miR-3909, hsa-miR-30d-5p, hsa-miR-92a-3p, hsa-miR-222-3p and hsa-miR-30a-5p; and down-regulation of two microRNAs; hsa-miR-6803-3p and hsa-miR-1249-3p. hsa-miR-222-3p and hsa-miR-92a-3p putatively target FOXP2, which was found down-regulated by microRNA regulation in songbird singing. miR-30d and miR-222 corroborate microRNA response observed in zebra finch song-listening/learning. miR-222 is induced by ERK cascade, which is important for memory formation, motor neuron functions and neuronal plasticity. miR-222 is also activated by FOSL1, an immediate early gene from the FOS family of transcriptional regulators which are activated by auditory-motor stimuli. miR-222 and miR-92 promote neurite outgrowth by negatively regulating the neuronal growth inhibitor, PTEN, and by activating CREB expression and phosphorylation. The up-regulation of microRNAs previously found to be regulators of auditory and nervous system functions (miR-30d, miR-92a and miR-222) is indicative of the sensory perception processes associated with music-performance. Akt signalling pathway which has roles in cell survival, cell differentiation, activation of CREB signalling and dopamine transmission was one of the functions regulated by the up-regulated microRNAs; in accordance with functions identified from songbird learning. The up-regulated microRNAs were also found to be regulators of apoptosis, suggesting repression of apoptotic mechanisms in connection with music-performance. Furthermore, comparative analyses of the target genes of differentially expressed microRNAs with that of the song-responsive microRNAs in songbirds suggest convergent regulatory mechanisms underlying auditory perception.