miTALOS v2: Analyzing Tissue Specific microRNA Function

Advanced computational predictive models of miRNA-mRNA interaction efficiency

The modeling of miRNA-mRNA interactions holds significant implications for synthetic biology and human health. However, this research area presents specific challenges due to the multifaceted nature of mRNA downregulation by miRNAs, influenced by numerous factors including competition or synergism among miRNAs and mRNAs. In this study, we present an improved computational model for predicting miRNA-mRNA interactions, addressing aspects not previously modeled. Firstly, we integrated a novel set of features that significantly enhanced the predictor's performance. Secondly, we demonstrated the cell-specific nature of certain aspects of miRNA-mRNA interactions, highlighting the importance of designing models tailored to specific cell types for improved accuracy. Moreover, we introduce a miRNA binding site interaction model (miBSIM) that, for the first time, accounts for both the distribution of miRNA binding sites along the mRNA and their respective strengths in regulating mRNA stability. Our analysis suggests that distant miRNA sites often compete with each other, revealing the intricate interplay of binding site interactions. Overall, our new predictive model shows a significant improvement of up to 6.43% over previous models in the field. The code of our model is available at https://www.cs.tau.ac.il/~tamirtul/miBSIM.

Decoding the Non-coding: Tools and Databases Unveiling the Hidden World of "Junk" RNAs for Innovative Therapeutic Exploration

Non-coding RNAs are pivotal regulators of gene and protein expression, exerting crucial influences on diverse biological processes. Their dysregulation is frequently implicated in the onset and progression of diseases, notably cancer. A profound comprehension of the intricate mechanisms governing ncRNAs is imperative for devising innovative therapeutic interventions against these debilitating conditions. Significantly, nearly 80% of our genome comprises ncRNAs, underscoring their centrality in cellular processes. The elucidation of ncRNA functions is pivotal for grasping the complexities of gene regulation and its implications for human health. Modern genome sequencing techniques yield vast datasets, stored in specialized databases. To harness this wealth of information and to understand the crosstalk of non-coding RNAs, knowledge of available databases is required, and many new sophisticated computational tools have emerged. These tools play a pivotal role in the identification, prediction, and annotation of ncRNAs, thereby facilitating their experimental validation. This Review succinctly outlines the current understanding of ncRNAs, emphasizing their involvement in disease development. It also highlights the databases and tools instrumental in classifying, annotating, and evaluating ncRNAs. By extracting meaningful biological insights from seemingly "junk" data, these tools empower scientists to unravel the intricate roles of ncRNAs in shaping human health.

Trials and Tribulations of MicroRNA Therapeutics

The discovery of the link between microRNAs (miRNAs) and a myriad of human diseases, particularly various cancer types, has generated significant interest in exploring their potential as a novel class of drugs. This has led to substantial investments in interdisciplinary research fields such as biology, chemistry, and medical science for the development of miRNA-based therapies. Furthermore, the recent global success of SARS-CoV-2 mRNA vaccines against the COVID-19 pandemic has further revitalized interest in RNA-based immunotherapies, including miRNA-based approaches to cancer treatment. Consequently, RNA therapeutics have emerged as highly adaptable and modular options for cancer therapy. Moreover, advancements in RNA chemistry and delivery methods have been pivotal in shaping the landscape of RNA-based immunotherapy, including miRNA-based approaches. Consequently, the biotechnology and pharmaceutical industry has witnessed a resurgence of interest in incorporating RNA-based immunotherapies and miRNA therapeutics into their development programs. Despite substantial progress in preclinical research, the field of miRNA-based therapeutics remains in its early stages, with only a few progressing to clinical development, none reaching phase III clinical trials or being approved by the US Food and Drug Administration (FDA), and several facing termination due to toxicity issues. These setbacks highlight existing challenges that must be addressed for the broad clinical application of miRNA-based therapeutics. Key challenges include establishing miRNA sensitivity, specificity, and selectivity towards their intended targets, mitigating immunogenic reactions and off-target effects, developing enhanced methods for targeted delivery, and determining optimal dosing for therapeutic efficacy while minimizing side effects. Additionally, the limited understanding of the precise functions of miRNAs limits their clinical utilization. Moreover, for miRNAs to be viable for cancer treatment, they must be technically and economically feasible for the widespread adoption of RNA therapies. As a result, a thorough risk evaluation of miRNA therapeutics is crucial to minimize off-target effects, prevent overdosing, and address various other issues. Nevertheless, the therapeutic potential of miRNAs for various diseases is evident, and future investigations are essential to determine their applicability in clinical settings.

PanomiR: a systems biology framework for analysis of multi-pathway targeting by miRNAs

Charting microRNA (miRNA) regulation across pathways is key to characterizing their function. Yet, no method currently exists that can quantify how miRNAs regulate multiple interconnected pathways or prioritize them for their ability to regulate coordinate transcriptional programs. Existing methods primarily infer one-to-one relationships between miRNAs and pathways using differentially expressed genes. We introduce PanomiR, an in silico framework for studying the interplay of miRNAs and disease functions. PanomiR integrates gene expression, mRNA-miRNA interactions and known biological pathways to reveal coordinated multi-pathway targeting by miRNAs. PanomiR utilizes pathway-activity profiling approaches, a pathway co-expression network and network clustering algorithms to prioritize miRNAs that target broad-scale transcriptional disease phenotypes. It directly resolves differential regulation of pathways, irrespective of their differential gene expression, and captures co-activity to establish functional pathway groupings and the miRNAs that may regulate them. PanomiR uses a systems biology approach to provide broad but precise insights into miRNA-regulated functional programs. It is available at https://bioconductor.org/packages/PanomiR.

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.

Non-coding RNAs in human health and disease: potential function as biomarkers and therapeutic targets

Human diseases have been a critical threat from the beginning of human history. Knowing the origin, course of action and treatment of any disease state is essential. A microscopic approach to the molecular field is a more coherent and accurate way to explore the mechanism, progression, and therapy with the introduction and evolution of technology than a macroscopic approach. Non-coding RNAs (ncRNAs) play increasingly important roles in detecting, developing, and treating all abnormalities related to physiology, pathology, genetics, epigenetics, cancer, and developmental diseases. Noncoding RNAs are becoming increasingly crucial as powerful, multipurpose regulators of all biological processes. Parallel to this, a rising amount of scientific information has revealed links between abnormal noncoding RNA expression and human disorders. Numerous non-coding transcripts with unknown functions have been found in addition to advancements in RNA-sequencing methods. Non-coding linear RNAs come in a variety of forms, including circular RNAs with a continuous closed loop (circRNA), long non-coding RNAs (lncRNA), and microRNAs (miRNA). This comprises specific information on their biogenesis, mode of action, physiological function, and significance concerning disease (such as cancer or cardiovascular diseases and others). This study review focuses on non-coding RNA as specific biomarkers and novel therapeutic targets.

NcPath: a novel platform for visualization and enrichment analysis of human non-coding RNA and KEGG signaling pathways

SUMMARY

Non-coding RNAs play important roles in transcriptional processes and participate in the regulation of various biological functions, in particular miRNAs and lncRNAs. Despite their importance for several biological functions, the existing signaling pathway databases do not include information on miRNA and lncRNA. Here, we redesigned a novel pathway database named NcPath by integrating and visualizing a total of 178 308 human experimentally validated miRNA-target interactions (MTIs), 32 282 experimentally verified lncRNA-target interactions (LTIs) and 4837 experimentally validated human ceRNA networks across 222 KEGG pathways (including 27 sub-categories). To expand the application potential of the redesigned NcPath database, we identified 556 798 reliable lncRNA-protein-coding genes (PCG) interaction pairs by integrating co-expression relations, ceRNA relations, co-TF-binding interactions, co-histone-modification interactions, cis-regulation relations and lncPro Tool predictions between lncRNAs and PCG. In addition, to determine the pathways in which miRNA/lncRNA targets are involved, we performed a KEGG enrichment analysis using a hypergeometric test. The NcPath database also provides information on MTIs/LTIs/ceRNA networks, PubMed IDs, gene annotations and the experimental verification method used. In summary, the NcPath database will serve as an important and continually updated platform that provides annotation and visualization of the pathways on which non-coding RNAs (miRNA and lncRNA) are involved, and provide support to multimodal non-coding RNAs enrichment analysis. The NcPath database is freely accessible at http://ncpath.pianlab.cn/.

AVAILABILITY AND IMPLEMENTATION

NcPath database is freely available at http://ncpath.pianlab.cn/. The code and manual to use NcPath can be found at https://github.com/Marscolono/NcPath/.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Updated review of advances in microRNAs and complex diseases: experimental results, databases, webservers and data fusion

MicroRNAs (miRNAs) are gene regulators involved in the pathogenesis of complex diseases such as cancers, and thus serve as potential diagnostic markers and therapeutic targets. The prerequisite for designing effective miRNA therapies is accurate discovery of miRNA-disease associations (MDAs), which has attracted substantial research interests during the last 15 years, as reflected by more than 55 000 related entries available on PubMed. Abundant experimental data gathered from the wealth of literature could effectively support the development of computational models for predicting novel associations. In 2017, Chen et al. published the first-ever comprehensive review on MDA prediction, presenting various relevant databases, 20 representative computational models, and suggestions for building more powerful ones. In the current review, as the continuation of the previous study, we revisit miRNA biogenesis, detection techniques and functions; summarize recent experimental findings related to common miRNA-associated diseases; introduce recent updates of miRNA-relevant databases and novel database releases since 2017, present mainstream webservers and new webserver releases since 2017 and finally elaborate on how fusion of diverse data sources has contributed to accurate MDA prediction.

Bioinformatic Analysis of Ixodes ricinus Long Non-Coding RNAs Predicts Their Binding Ability of Host miRNAs

Ixodes ricinus ticks are distributed across Europe and are a vector of tick-borne diseases. Although I. ricinus transcriptome studies have focused exclusively on protein coding genes, the last decade witnessed a strong increase in long non-coding RNA (lncRNA) research and characterization. Here, we report for the first time an exhaustive analysis of these non-coding molecules in I. ricinus based on 131 RNA-seq datasets from three different BioProjects. Using this data, we obtained a consensus set of lncRNAs and showed that lncRNA expression is stable among different studies. While the length distribution of lncRNAs from the individual data sets is biased toward short length values, implying the existence of technical artefacts, the consensus lncRNAs show a more homogeneous distribution emphasizing the importance to incorporate data from different sources to generate a solid reference set of lncRNAs. KEGG enrichment analysis of host miRNAs putatively targeting lncRNAs upregulated upon feeding showed that these miRNAs are involved in several relevant functions for the tick-host interaction. The possibility that at least some tick lncRNAs act as host miRNA sponges was further explored by identifying lncRNAs with many target regions for a given host miRNA or sets of host miRNAs that consistently target lncRNAs together. Overall, our findings suggest that lncRNAs that may act as sponges have diverse biological roles related to the tick–host interaction in different tissues.

Hypoxia- and Inflammation-Related Transcription Factor SP3 May Be Involved in Platelet Activation and Inflammation in Intracranial Hemorrhage

The purpose of this study was to identify the biomarkers implicated in the development of intracranial hemorrhage (ICH) and potential regulatory pathways. In the transcriptomic data for patients with ICH, we identified DEmiRNAs and DEmRNAs related to hypoxia, inflammation, and their transcription factors (TFs). An ICH-based miRNA-TF-mRNA regulatory network was thus constructed, and four biomarkers (TIMP1, PLAUR, DDIT3, and CD40) were screened for their association with inflammation or hypoxia by machine learning. Following this, SP3 was found to be a transcription factor involved in hypoxia and inflammation, which regulates TIMP1 and PLAUR. From the constructed miRNA-TF-mRNA regulatory network, we identified three axes, hsa-miR-940/RUNX1/TIMP1, hsa-miR-571/SP3/TIMP1, and hsa-miR-571/SP3/PLAUR, which may be involved in the development of ICH. Upregulated TIMP1 and PLAUR were validated in an independent clinical cohort 3 days after ICH onset. According to Gene Set Enrichment Analysis (GSEA), SP3 was discovered to be important in interleukin signaling and platelet activation for hemostasis. Transcription factor SP3 associated with hypoxia or inflammation plays an important role in development of ICH. This study provides potential targets for monitoring the severity of inflammation and hypoxia in patients with ICH.

Epigenetic Profiling in the Saliva of Obese Pregnant Women

Maternal obesity is associated with inflammation and oxidative stress, strongly impacting the intrauterine environment with detrimental consequences for both mother and offspring. The saliva is a non-invasive biofluid reflecting both local and systemic health status. This observational study aimed to profile the epigenetic signature in the saliva of Obese (OB) and Normal-Weight (NW) pregnant women. Sixteen NW and sixteen OB Caucasian women with singleton spontaneous pregnancies were enrolled. microRNAs were quantified by the OpenArray Platform. The promoter region methylation of Suppressor of Cytokine Signaling 3 (SOCS3) and Transforming Growth Factor Beta 1 (TGF-Beta1) was assessed by pyrosequencing. There were 754 microRNAs evaluated: 20 microRNAs resulted in being differentially expressed between OB and NW. microRNA pathway enrichment analysis showed a significant association with the TGF-Beta signaling pathway (miTALOS) and with fatty acids biosynthesis/metabolism, lysine degradation, and ECM-receptor interaction pathways (DIANA-miRPath). Both SOCS3 and TGF-Beta1 were significantly down-methylated in OB vs. NW. These results help to clarify impaired mechanisms involved in obesity and pave the way for the understanding of specific damaged pathways. The characterization of the epigenetic profile in saliva of pregnant women can represent a promising tool for the identification of obesity-related altered mechanisms and of possible biomarkers for early diagnosis and treatment of pregnancy-adverse conditions.

Key Disease Mechanisms Linked to Amyotrophic Lateral Sclerosis in Spinal Cord Motor Neurons

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with no modifying treatments available. The molecular mechanisms underpinning disease pathogenesis are not fully understood. Recent studies have employed co-expression networks to identify key genes, known as “switch genes”, responsible for dramatic transcriptional changes in the blood of ALS patients. In this study, we directly investigate the root cause of ALS by examining the changes in gene expression in motor neurons that degenerate in patients. Co-expression networks identified in ALS patients’ spinal cord motor neurons revealed 610 switch genes in seven independent microarrays. Switch genes were enriched in several pathways, including viral carcinogenesis, PI3K-Akt, focal adhesion, proteoglycans in cancer, colorectal cancer, and thyroid hormone signaling. Transcription factors ELK1 and GATA2 were identified as key master regulators of the switch genes. Protein-chemical network analysis identified valproic acid, cyclosporine, estradiol, acetaminophen, quercetin, and carbamazepine as potential therapeutics for ALS. Furthermore, the chemical analysis identified metals and organic compounds including, arsenic, copper, nickel, and benzo(a)pyrene as possible mediators of neurodegeneration. The identification of switch genes provides insights into previously unknown biological pathways associated with ALS.

Emerging concepts of miRNA therapeutics: from cells to clinic

MicroRNAs (miRNAs) are very powerful genetic regulators, as evidenced by the fact that a single miRNA can direct entire cellular pathways via interacting with a broad spectrum of target genes. This property renders miRNAs as highly interesting therapeutic tools to restore cell functions that are altered as part of a disease phenotype. However, this strength of miRNAs is also a weakness because their cellular effects are so numerous that off-target effects can hardly be avoided. In this review, we point out the main challenges and the strategies to specifically address the problems that need to be surmounted in the push toward a therapeutic application of miRNAs. Particular emphasis is given to approaches that have already found their way into clinical studies.

MicroRNAs in Various Body Fluids and its importance in Forensic Medicine

MicroRNAs (miRNAs) are a class of noncoding RNAs which regulate gene expression. miRNAs have tissue-specific expression and are also present in various extracellular body fluids, including blood, tears, semen, vaginal fluid and urine. Additionally, expression of miRNAs in body fluids is linked to various pathological diseases, including cancer and neurodegenerative diseases. Examination of body fluids is important in forensic medicine as they serve as a valuable form of evidence. Due to its stability, miRNA offers an advantage for body fluid identification, which can be detected even after several months or from compromised samples. Identification of unique miRNA profiles for different body fluids enable the identification of these body fluid. Furthermore, miRNAs profiling can be used to estimate post-mortem interval. Various biochemical and molecular methods have been used for identification of miRNAs have shown promising results. We discuss different miRNAs as specific biomarkers and their clinical importance regarding different pathological conditions, as well as their medico-legal importance.

Beyond the Code: Noncoding RNAs in Skin Wound Healing

An increasing number of noncoding RNAs (ncRNAs) have been found to regulate gene expression and protein functions, playing important roles in diverse biological processes and diseases. Their crucial functions have been reported in almost every cell type and all stages of skin wound healing. Evidence of their pathogenetic roles in common wound complications, such as chronic nonhealing wounds and excessive scarring, is also accumulating. Given their unique expression and functional properties, ncRNAs are promising therapeutic and diagnostic entities. In this review, we discuss current knowledge about the functional roles of noncoding elements, such as microRNAs, long ncRNAs, and circular RNAs, in skin wound healing, focusing on in vivo evidence from studies of human wound samples and animal wound models. Finally, we provide a perspective on the outlook of ncRNA-based therapeutics in wound care.

MiR-571 affects the development and progression of liver fibrosis by regulating the Notch3 pathway

Exploring the expression of miR-571 in patients with liver fibrosis and its role in the progression of liver fibrosis. A total of 74 patients with liver fibrosis in our institution from September to December 2018 were collected for study, and the expression of miR-571, Notch3 and Jagged1 in patients with different progressions of liver fibrosis was determined by RT-PCR and Western blot analysis. Set up Notch3 up group and Notch3 down regulated group, RT-PCR and Western blot were used to determine the effect of Notch signaling on the expression of fibrogenic factors. CCK-8, cell scratch assays, Transwell assays, flow cytometry were used to determine the effect of miR-571 on LX-2 proliferation, migration, apoptosis in human stem stellate cells, and RT-PCR, Western blot assays were performed to determine the effect of miR-571 on the Notch3 signaling pathway and the expression of profibrogenic factors. miR-571, Notch3 and Jagged1 are up-regulated in patients with liver fibrosis and is associated with the progression of liver fibrosis. Notch3 signaling pathway can promote the expression of fibroblast in human hepatic stellate cells; miR-571 can inhibit the apoptosis of human hepatic stellate cells, promote cell proliferation and migration; up regulation of miR-571 can promote the expression of Notch3 and Jagged1, and up-regulation of miR-571 also promoted the expression of related fibroblasts. MiR-571 can promote the activation of human stem cell stellate cells and the expression of fibroblast related factors through Notch3 signaling pathway.

Reactivation of tumour suppressor in breast cancer by enhancer switching through NamiRNA network

Dysfunction of Tumour Suppressor Genes (TSGs) is a common feature in carcinogenesis. Epigenetic abnormalities including DNA hypermethylation or aberrant histone modifications in promoter regions have been described for interpreting TSG inactivation. However, in many instances, how TSGs are silenced in tumours are largely unknown. Given that miRNA with low expression in tumours is another recognized signature, we hypothesize that low expression of miRNA may reduce the activity of TSG related enhancers and further lead to inactivation of TSG during cancer development. Here, we reported that low expression of miRNA in cancer as a recognized signature leads to loss of function of TSGs in breast cancer. In 157 paired breast cancer and adjacent normal samples, tumour suppressor gene GPER1 and miR-339 are both downregulated in Luminal A/B and Triple Negative Breast Cancer subtypes. Mechanistic investigations revealed that miR-339 upregulates GPER1 expression in breast cancer cells by switching on the GPER1 enhancer, which can be blocked by enhancer deletion through the CRISPR/Cas9 system. Collectively, our findings reveal novel mechanistic insights into TSG dysfunction in cancer development, and provide evidence that reactivation of TSG by enhancer switching may be a promising alternative strategy for clinical breast cancer treatment.

miRTargetLink 2.0-interactive miRNA target gene and target pathway networks

Which genes, gene sets or pathways are regulated by certain miRNAs? Which miRNAs regulate a particular target gene or target pathway in a certain physiological context? Answering such common research questions can be time consuming and labor intensive. Especially for researchers without computational experience, the integration of different data sources, selection of the right parameters and concise visualization can be demanding. A comprehensive analysis should be central to present adequate answers to complex biological questions. With miRTargetLink 2.0, we develop an all-in-one solution for human, mouse and rat miRNA networks. Users input in the unidirectional search mode either a single gene, gene set or gene pathway, alternatively a single miRNA, a set of miRNAs or an miRNA pathway. Moreover, genes and miRNAs can jointly be provided to the tool in the bidirectional search mode. For the selected entities, interaction graphs are generated from different data sources and dynamically presented. Connected application programming interfaces (APIs) to the tailored enrichment tools miEAA and GeneTrail facilitate downstream analysis of pathways and context-annotated categories of network nodes. MiRTargetLink 2.0 is freely accessible at https://www.ccb.uni-saarland.de/mirtargetlink2.

NoRCE: non-coding RNA sets cis enrichment tool

BACKGROUND

While some non-coding RNAs (ncRNAs) are assigned critical regulatory roles, most remain functionally uncharacterized. This presents a challenge whenever an interesting set of ncRNAs needs to be analyzed in a functional context. Transcripts located close-by on the genome are often regulated together. This genomic proximity on the sequence can hint at a functional association.

RESULTS

We present a tool, NoRCE, that performs cis enrichment analysis for a given set of ncRNAs. Enrichment is carried out using the functional annotations of the coding genes located proximal to the input ncRNAs. Other biologically relevant information such as topologically associating domain (TAD) boundaries, co-expression patterns, and miRNA target prediction information can be incorporated to conduct a richer enrichment analysis. To this end, NoRCE includes several relevant datasets as part of its data repository, including cell-line specific TAD boundaries, functional gene sets, and expression data for coding & ncRNAs specific to cancer. Additionally, the users can utilize custom data files in their investigation. Enrichment results can be retrieved in a tabular format or visualized in several different ways. NoRCE is currently available for the following species: human, mouse, rat, zebrafish, fruit fly, worm, and yeast.

CONCLUSIONS

NoRCE is a platform-independent, user-friendly, comprehensive R package that can be used to gain insight into the functional importance of a list of ncRNAs of any type. The tool offers flexibility to conduct the users' preferred set of analyses by designing their own pipeline of analysis. NoRCE is available in Bioconductor and https://github.com/guldenolgun/NoRCE .

The miR-378c-Samd1 circuit promotes phenotypic modulation of vascular smooth muscle cells and foam cells formation in atherosclerosis lesions

MicroRNAs have emerged as key regulators in vascular diseases and are involved in the formation of atherosclerotic lesions. However, the atherosclerotic-specific MicroRNAs and their functional roles in atherosclerosis are unclear. Here, we report that miR-378c protects against atherosclerosis by directly targeting Sterile Alpha Motif Domain Containing 1 (Samd1), a predicted transcriptional repressor. miR-378c was strikingly reduced in atherosclerotic plaques and blood of acute coronary syndrome (ACS) patients relative to healthy controls. Suppression of miR-378c promoted vascular smooth muscle cells (VSMCs) phenotypic transition during atherosclerosis. We also reported for the first time that Samd1 prolonged immobilization of LDL on the VSMCs, thus facilitated LDL oxidation and subsequently foam cell formation. Further, we found that Samd1 contains predicted DNA binding domain and directly binds to DNA regions as a transcriptional repressor. Together, we uncovered a novel mechanism whereby miR-378c-Samd1 circuit participates in two key elements of atherosclerosis, VSMCs phenotypic transition and LDL oxidation. Our results provided a better understanding of atherosclerosis pathophysiology and potential therapeutic management by targeting miR-378c-Samd1 circuit.

An overview of graph databases and their applications in the biomedical domain

Over the past couple of decades, the explosion of densely interconnected data has stimulated the research, development and adoption of graph database technologies. From early graph models to more recent native graph databases, the landscape of implementations has evolved to cover enterprise-ready requirements. Because of the interconnected nature of its data, the biomedical domain has been one of the early adopters of graph databases, enabling more natural representation models and better data integration workflows, exploration and analysis facilities. In this work, we survey the literature to explore the evolution, performance and how the most recent graph database solutions are applied in the biomedical domain, compiling a great variety of use cases. With this evidence, we conclude that the available graph database management systems are fit to support data-intensive, integrative applications, targeted at both basic research and exploratory tasks closer to the clinic.

Recent Highlights of Research on miRNAs as Early Potential Biomarkers for Cardiovascular Complications of Type 2 Diabetes Mellitus

Type 2 diabetes mellitus (T2DM) and its complications pose a serious threat to the life and health of patients around the world. The most dangerous complications of this disease are vascular complications. Microvascular complications of T2DM include retinopathy, nephropathy, and neuropathy. In turn, macrovascular complications include coronary artery disease, peripheral artery disease, and cerebrovascular disease. The currently used diagnostic methods do not ensure detection of the disease at an early stage, and they also do not predict the risk of developing specific complications. MicroRNAs (miRNAs) are small, endogenous, noncoding molecules that are involved in key processes, such as cell proliferation, differentiation, and apoptosis. Recent research has assigned them an important role as potential biomarkers for detecting complications related to diabetes. We suggest that utilizing miRNAs can be a routine approach for early diagnosis and prognosis of diseases and may enable the development of better therapeutic approaches. In this paper, we conduct a review of the latest reports demonstrating the usefulness of miRNAs as biomarkers in the vascular complications of T2DM.

Statin-induced microRNAome alterations modulating inflammation pathways of peripheral blood mononuclear cells in patients with hypercholesterolemia

Statins inhibit cholesterol biogenesis and modulate atheroma inflammation to reduce cardiovascular risks. Promoted by immune and non-immune cells, serum C-reactive protein (CRP) might be a biomarker suboptimal to assess inflammation status. Although it has been reported that statins modulated inflammation via microRNAs (miRNAs), evidence remains lacking on comprehensive profiling of statin-induced miRNAome alterations in immune cells. We recruited 19 hypercholesterolemic patients receiving 2 mg/day pitavastatin and 15 ones receiving 10 mg/day atorvastatin treatment for 12 weeks, and performed microarray-based profiling of 1733 human mature miRNAs in peripheral blood mononuclear cells (PBMCs) before and after statin treatment. Differentially expressed miRNAs were determined if their fold changes were >1.50 or <0.67, after validated using quantitative polymerase chain reaction (qPCR). The miRSystem and miTALOS platforms were utilized for pathway analysis. Of the 34 patients aged 63.7 ± 6.2 years, 27 were male and 19 were with coronary artery disease. We discovered that statins induced differential expressions of miR-483-5p, miR-4667-5p, miR-1244, and miR-3609, with qPCR-validated fold changes of 1.74 (95% confidence interval, 1.33-2.15), 1.61 (1.25-1.98), 1.61 (1.01-2.21), and 1.68 (1.19-2.17), respectively. The fold changes of the four miRNAs were not correlated with changes of low-density-lipoprotein cholesterol or CRP, after sex, age, and statin type were adjusted. We also revealed that RhoA and transforming growth factor-β signaling pathways might be regulated by the four miRNAs. Given our findings, miRNAs might be involved in statin-induced inflammation modulation in PBMCs, providing likelihood to assess and reduce inflammation in patients with atherosclerotic cardiovascular diseases.

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.

Micro RNA Expression after Ingestion of Fucoidan; A Clinical Study

Fucoidans are a class of fucose-rich sulfated polysaccharides derived from brown macroalgae that exert a range of biological activities in vitro and in vivo. To generate an unbiased assessment of pathways and processes affected by fucoidan, a placebo-controlled double-blind pilot study was performed in healthy volunteers. Blood samples were taken immediately before and 24 h after ingestion of a single dose of 1 g of Undaria pinnatifida fucoidan (UPF) or placebo. Levels of isolated miRNAs were analyzed using Taqman Open Array Human MicroRNA panels. Out of 754 miRNAs screened, UPF affected a total of 53 miRNAs. Pathway analysis using the TALOS data analysis tool predicted 29 different pathways and processes that were largely grouped into cell surface receptor signaling, cancer-related pathways, the majority of which were previously associated with fucoidans. However, this analysis also identified nine pathways and processes that have not been associated with fucoidans before. Overall, this study illustrates that even a single dose of fucoidans has the potential to affect the expression of genes related to fundamental cellular processes. Moreover, it confirms previous data that fucoidans influence immunity, cancer cells, inflammation, and neurological function.

Integrative analysis of breast cancer profiles in TCGA by TNBC subgrouping reveals novel microRNA-specific clusters, including miR-17-92a, distinguishing basal-like 1 and basal-like 2 TNBC subtypes

Background

The term triple-negative breast cancer (TNBC) is used to describe breast cancers without expression of estrogen receptor, progesterone receptor or HER2 amplification. To advance targeted treatment options for TNBC, it is critical that the subtypes within this classification be described in regard to their characteristic biology and gene expression. The Cancer Genome Atlas (TCGA) dataset provides not only clinical and mRNA expression data but also expression data for microRNAs.

Results

In this study, we applied the Lehmann classifier to TCGA-derived TNBC cases which also contained microRNA expression data and derived subtype-specific microRNA expression patterns. Subsequent analyses integrated known and predicted microRNA-mRNA regulatory nodes as well as patient survival data to identify key networks. Notably, basal-like 1 (BL1) TNBCs were distinguished from basal-like 2 TNBCs through up-regulation of members of the miR-17-92 cluster of microRNAs and suppression of several known miR-17-92 targets including inositol polyphosphate 4-phosphatase type II, INPP4B.

Conclusions

These data demonstrate TNBC subtype-specific microRNA and target mRNA expression which may be applied to future biomarker and therapeutic development studies.

Intragenic MicroRNAs Autoregulate Their Host Genes in Both Direct and Indirect Ways-A Cross-Species Analysis

MicroRNAs (miRNAs) function as master switches for post-transcriptional gene expression. Their genes are either located in the extragenic space or within host genes, but these intragenic miRNA::host gene interactions are largely enigmatic. The aim of this study was to investigate the location and co-regulation of all to date available miRNA sequences and their host genes in an unbiased computational approach. The majority of miRNAs were located within intronic regions of protein-coding and non-coding genes. These intragenic miRNAs exhibited both increased target probability as well as higher target prediction scores as compared to a model of randomly permutated genes. This was associated with a higher number of miRNA recognition elements for the hosted miRNAs within their host genes. In addition, strong indirect autoregulation of host genes through modulation of functionally connected gene clusters by intragenic miRNAs was demonstrated. In addition to direct miRNA-to-host gene targeting, intragenic miRNAs also appeared to interact with functionally related genes, thus affecting their host gene function through an indirect autoregulatory mechanism. This strongly argues for the biological relevance of autoregulation not only for the host genes themselves but, more importantly, for the entire gene cluster interacting with the host gene.

miRPathDB 2.0: a novel release of the miRNA Pathway Dictionary Database

Since the initial release of miRPathDB, tremendous progress has been made in the field of microRNA (miRNA) research. New miRNA reference databases have emerged, a vast amount of new miRNA candidates has been discovered and the number of experimentally validated target genes has increased considerably. Hence, the demand for a major upgrade of miRPathDB, including extended analysis functionality and intuitive visualizations of query results has emerged. Here, we present the novel release 2.0 of the miRNA Pathway Dictionary Database (miRPathDB) that is freely accessible at https://mpd.bioinf.uni-sb.de/. miRPathDB 2.0 comes with a ten-fold increase of pre-processed data. In total, the updated database provides putative associations between 27 452 (candidate) miRNAs, 28 352 targets and 16 833 pathways for Homo sapiens, as well as interactions of 1978 miRNAs, 24 898 targets and 6511 functional categories for Mus musculus. Additionally, we analyzed publications citing miRPathDB to identify common use-cases and further extensions. Based on this evaluation, we added new functionality for interactive visualizations and down-stream analyses of bulk queries. In summary, the updated version of miRPathDB, with its new custom-tailored features, is one of the most comprehensive and advanced resources for miRNAs and their target pathways.

Trends in the development of miRNA bioinformatics tools

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression via recognition of cognate sequences and interference of transcriptional, translational or epigenetic processes. Bioinformatics tools developed for miRNA study include those for miRNA prediction and discovery, structure, analysis and target prediction. We manually curated 95 review papers and ∼1000 miRNA bioinformatics tools published since 2003. We classified and ranked them based on citation number or PageRank score, and then performed network analysis and text mining (TM) to study the miRNA tools development trends. Five key trends were observed: (1) miRNA identification and target prediction have been hot spots in the past decade; (2) manual curation and TM are the main methods for collecting miRNA knowledge from literature; (3) most early tools are well maintained and widely used; (4) classic machine learning methods retain their utility; however, novel ones have begun to emerge; (5) disease-associated miRNA tools are emerging. Our analysis yields significant insight into the past development and future directions of miRNA tools.

Endogenous and Exogenous Modulation of Nrf2 Mediated Oxidative Stress Response in Bovine Granulosa Cells: Potential Implication for Ovarian Function

Nrf2 is a redox sensitive transcription factor regulating the expression of antioxidant genes as defense mechanism against various stressors. The aim of this study is to investigate the potential role of noncoding miRNAs as endogenous and quercetin as exogenous regulators of Nrf2 pathway in bovine granulosa cells. For this cultured granulosa cells were used for modulation of miRNAs (miR-28, 153 and miR-708) targeting the bovine Nrf2 and supplementation of quercentin to investigate the regulatory mechanisms of the Nrf2 antioxidant system. Moreover, cultured cells were treated with hydrogen peroxide to induce oxidative stress in those cells. Our results showed that, oxidative stress activated the expression of Nrf2 as a defense mechanism, while suppressing the expression of those miRNAs. Overexpression of those miRNAs resulted in downregulation of Nrf2 expression resulted in higher ROS accumulation, reduced mitochondrial activity and cellular proliferation. Quercetin supplementation showed its protective role against oxidative stress induced by H₂O₂ by inducing the expression of antioxidant enzymes. In conclusion, this study highlighted the involvement of miR-153, miR-28 and miR-708 in regulatory network of Nrf2 mediated antioxidant system in bovine granulosa cells function. Furthermore, quercetin at a low dose played a protective role in bovine granulosa cells against oxidative stress damage.

MicroRNAs as Potential Pharmaco-targets in Ischemia-Reperfusion Injury Compounded by Diabetes

BACKGROUND

Ischemia-Reperfusion (I/R) injury is the tissue damage that results from re-oxygenation of ischemic tissues. There are many players that contribute to I/R injury. One of these factors is the family of microRNAs (miRNAs), which are currently being heavily studied. This review aims to critically summarize the latest papers that attributed roles of certain miRNAs in I/R injury, particularly in diabetic conditions and dissect their potential as novel pharmacologic targets in the treatment and management of diabetes.

METHODS

PubMed was searched for publications containing microRNA and I/R, in the absence or presence of diabetes. All papers that provided sufficient evidence linking miRNA with I/R, especially in the context of diabetes, were selected. Several miRNAs are found to be either pro-apoptotic, as in the case of miR-34a, miR-144, miR-155, and miR-200, or anti-apoptotic, as in the case of miR-210, miR-21, and miR-146a. Here, we further dissect the evidence that shows diverse cell-context dependent effects of these miRNAs, particularly in cardiomyocytes, endothelial, or leukocytes. We also provide insight into cases where the possibility of having two miRNAs working together to intensify a given response is noted.

CONCLUSIONS

This review arrives at the conclusion that the utilization of miRNAs as translational agents or pharmaco-targets in treating I/R injury in diabetic patients is promising and becoming increasingly clearer.

Noncoding RNAs Databases: Current Status and Trends

One of the most important resources for researchers of noncoding RNAs is the information available in public databases spread over the internet. However, the effective exploration of this data can represent a daunting task, given the large amount of databases available and the variety of stored data. This chapter describes a classification of databases based on information source, type of RNA, source organisms, data formats, and the mechanisms for information retrieval, detailing the relevance of each of these classifications and its usability by researchers. This classification is used to update a 2012 review, indexing now more than 229 public databases. This review will include an assessment of the new trends for ncRNA research based on the information that is being offered by the databases. Additionally, we will expand the previous analysis focusing on the usability and application of these databases in pathogen and disease research. Finally, this chapter will analyze how currently available database schemas can help the development of new and improved web resources.

Design, synthesis and activity of light deactivatable microRNA inhibitor

miRNAs are key cellular regulators and their dysregulation is associated with many human diseases. They are usually produced locally in a spatiotemporally controlled manner to target mRNAs and regulate gene expression. Thus, developing chemical tools for manipulating miRNA with spatiotemporal precise is critical for studying miRNA. Herein, we designed a strategy to control miRNA biogenesis with light controllable inhibitor targeting the pre-miRNA processing by Dicer. By conjugating two non-inhibiting units, a low affinity Dicer inhibitor and a pre-miRNA binder, through a photocleavable linker, the bifunctional molecule obtained could inhibit miRNA production. Taking advantage of the photocleavable property of the linker, the bifunctional inhibitor can be fragmented into separate non-inhibiting units and therefore be deactivated by light. We expect that this strategy could be applied to generate chemical biological tools that allow light-mediated spatiotemporal control of miRNA maturation and contribute to the study of miRNA function.

Small ncRNA-Seq Results of Human Tissues: Variations Depending on Sample Integrity

BACKGROUND

Although mature miRNAs are relatively stable in vivo, RNA degradation can have a substantial influence on small noncoding RNA (sncRNA) profiles.

METHODS

Using different tissue storage conditions and RNA isolation procedures, we analyzed the integrity and quality of RNA isolates from human lung and heart tissues. We sequenced a total of 64 RNA samples and quantified the effect of RNA degradation, DNA contamination, and other confounding factors on the sncRNA-seq data. Besides microRNAs, other noncoding RNA species (piRNAs, tRNAs, snoRNAs, rRNAs) were investigated.

RESULTS

Consistent with previous results, we found that the tissue specificity of microRNAs is generally well preserved. The distribution of microRNA isoforms was similar to the distribution of canonical forms. New miRNAs were more frequently discovered in degraded samples. sncRNA Reads generated from degraded samples mapped frequently to piRNAs, tRNAs, snoRNAs, or scaRNAs. Sequencing reads that were depleted of sncRNAs showed an increased mapping frequency to bacterial species.

CONCLUSIONS

Our data emphasize the importance of sample integrity, especially for next-generation sequencing (NGS)-based high-throughput sncRNA profiles. For the prediction of novel miRNAs in particular, only samples with the highest RNA integrity should be used in order to avoid identification of false "miRNAs."

miR2Pathway: A novel analytical method to discover MicroRNA-mediated dysregulated pathways involved in hepatocellular carcinoma

MicroRNAs (miRNAs) are small, non-coding RNAs involved in the regulation of gene expression at a post-transcriptional level. Recent studies have shown miRNAs as key regulators of a variety of biological processes, such as proliferation, differentiation, apoptosis, metabolism, etc. Aberrantly expressed miRNAs influence individual gene expression level, but rewired miRNA-mRNA connections can influence the activity of biological pathways. Here, we define rewired miRNA-mRNA connections as the differential (rewiring) effects on the activity of biological pathways between hepatocellular carcinoma (HCC) and normal phenotypes. Our work presented here uses a PageRank-based approach to measure the degree of miRNA-mediated dysregulation of biological pathways between HCC and normal samples based on rewired miRNA-mRNA connections. In our study, we regard the degree of miRNA-mediated dysregulation of biological pathways as disease risk of biological pathways. Therefore, we propose a new method, miR2Pathway, to measure and rank the degree of miRNA-mediated dysregulation of biological pathways by measuring the total differential influence of miRNAs on the activity of pathways between HCC and normal states. miR2Pathway proposed here systematically shows the first evidence for a mechanism of biological pathways being dysregulated by rewired miRNA-mRNA connections, and provides new insight into exploring mechanisms behind HCC. Thus, miR2Pathway is a novel method to identify and rank miRNA-dysregulated pathways in HCC.

Identification of microRNAs associated with glioma diagnosis and prognosis

The sensitivity and specificity of microRNAs (miRNAs) for diagnosing glioma are controversial. We therefore performed a meta-analysis to systematically identify glioma-associated miRNAs. We initially screened five miRNA microarray datasets to evaluate the differential expression of miRNAs between glioma and normal tissues. We next compared the expression of the miRNAs in different organs and tissues to assess the sensitivity and specificity of the differentially expressed miRNAs in the diagnosis of glioma. Finally, pathway analysis was performed using GeneGO. We identified 27 candidate miRNAs associated with glioma initiation, progression, and patient prognosis. Sensitivity and specificity analysis indicated miR-15a, miR-16, miR-21, miR-23a, and miR-9 were up-regulated, while miR-124 was down-regulated in glioma. Ten signaling pathways showed the strongest association with glioma development and progression: the p53 pathway feedback loops 2, Interleukin signaling pathway, Toll receptor signaling pathway, Parkinson's disease, Notch signaling pathway, Cadherin signaling pathway, Apoptosis signaling pathway, VEGF signaling pathway, Alzheimer disease-amyloid secretase pathway, and the FGF signaling pathway. Our results indicate that the integration of miRNA, gene, and protein expression data can yield valuable biomarkers for glioma diagnosis and treatment. Indeed, six of the miRNAs identified in this study may be useful diagnostic and prognostic biomarkers in glioma.

Molecular Pathogenesis of Chlamydia Disease Complications: Epithelial-Mesenchymal Transition and Fibrosis

The reproductive system complications of genital chlamydial infection include fallopian tube fibrosis and tubal factor infertility. However, the molecular pathogenesis of these complications remains poorly understood. The induction of pathogenic epithelial-mesenchymal transition (EMT) through microRNA (miRNA) dysregulation was recently proposed as the pathogenic basis of chlamydial complications. Focusing on fibrogenesis, we investigated the hypothesis that chlamydia-induced fibrosis is caused by EMT-driven generation of myofibroblasts, the effector cells of fibrosis that produce excessive extracellular matrix (ECM) proteins. The results revealed that the targets of a major category of altered miRNAs during chlamydial infection are key components of the pathophysiological process of fibrogenesis; these target molecules include collagen types I, III, and IV, transforming growth factor β (TGF-β), TGF-β receptor 1 (TGF-βR1), connective tissue growth factor (CTGF), E-cadherin, SRY-box 7 (SOX7), and NFAT (nuclear factor of activated T cells) kinase dual-specificity tyrosine (Y) phosphorylation-regulated kinase 1a (Dyrk1a). Chlamydial induction of EMT resulted in the generation of α-smooth muscle actin (α-SMA)-positive myofibroblasts that produced ECM proteins, including collagen types I and III and fibronectin. Furthermore, the inhibition of EMT prevented the generation of myofibroblasts and production of ECM proteins during chlamydial infection. These findings may provide useful avenues for targeting EMT or specific components of the EMT pathways as a therapeutic intervention strategy to prevent chlamydia-related complications.

Progesterone receptor A promotes invasiveness and metastasis of luminal breast cancer by suppressing regulation of critical microRNAs by estrogen

Distal metastasis of luminal breast cancer is frequent and incurable, yet the metastasis mechanisms are poorly understood. Estrogen, even at postmenopausal concentrations, suppresses invasiveness of luminal breast cancer cells through the estrogen receptor (ER). Invasive tumors overexpress the short progesterone receptor A (PR-A) isoform. Even at postmenopausal concentrations, progesterone activates PR-A, inducing invasiveness by counteracting estrogen's effects, particularly when cells are hypersensitized to progesterone by PR-A overexpression. To interrogate the role of this cross-talk in metastasis, we investigated selective cross-talk mechanisms of PR-A with ER. We developed a quantitative PCR-based lymph node infiltration assay to address the slowness of metastasis of tumor xenografts. We found that 15 microRNAs (miRNAs) are regulated by progesterone via PR-A, but not the longer PR-B isoform, with increased progesterone sensitivity when PR-A was overexpressed. Two of these miRNAs whose induction (miR-92a-3p) or repression (miR-26b-5p) by estrogen was suppressed by progesterone plus PR-A were critical for the PR-A-ER cross-talk causing a gene-regulatory pattern of invasiveness and metastasis and complete rescue of invasiveness in vitro Constitutive expression of miR-92a-3p or inhibition of miR-26b-5p profoundly suppressed metastasis. Finally, in primary breast tumors, PR-A expression was correlated negatively with miR-92a-3p expression and positively with miR-26b-5p expression. Therefore, hormonal cross-talk of PR-A with ER is probably a fundamental mechanism that enables metastasis of luminal breast cancer. Moreover, miRNA biomarkers of hyperactive PR-A may help predict metastatic potential of luminal breast tumors. Further, miR-92a-3p and miR-26b-5p may reveal target pathways for selective intervention to suppress hormone-regulated metastasis, both pre- and postmenopause.

CSmiRTar: Condition-Specific microRNA targets database

MicroRNAs (miRNAs) are functional RNA molecules which play important roles in the post-transcriptional regulation. miRNAs regulate their target genes by repressing translation or inducing degradation of the target genes’ mRNAs. Many databases have been constructed to provide computationally predicted miRNA targets. However, they cannot provide the miRNA targets expressed in a specific tissue and related to a specific disease at the same time. Moreover, they cannot provide the common targets of multiple miRNAs and the common miRNAs of multiple genes at the same time. To solve these two problems, we construct a database called CSmiRTar (Condition-Specific miRNA Targets). CSmiRTar collects computationally predicted targets of 2588 human miRNAs and 1945 mouse miRNAs from four most widely used miRNA target prediction databases (miRDB, TargetScan, microRNA.org and DIANA-microT) and implements functional filters which allows users to search (i) a miRNA’s targets expressed in a specific tissue or/and related to a specific disease, (ii) multiple miRNAs’ common targets expressed in a specific tissue or/and related to a specific disease, (iii) a gene’s miRNAs related to a specific disease, and (iv) multiple genes’ common miRNAs related to a specific disease. We believe that CSmiRTar will be a useful database for biologists to study the molecular mechanisms of post-transcriptional regulation in human or mouse. CSmiRTar is available at http://cosbi.ee.ncku.edu.tw/CSmiRTar/ or http://cosbi4.ee.ncku.edu.tw/CSmiRTar/.

GeNNet: an integrated platform for unifying scientific workflows and graph databases for transcriptome data analysis

There are many steps in analyzing transcriptome data, from the acquisition of raw data to the selection of a subset of representative genes that explain a scientific hypothesis. The data produced can be represented as networks of interactions among genes and these may additionally be integrated with other biological databases, such as Protein-Protein Interactions, transcription factors and gene annotation. However, the results of these analyses remain fragmented, imposing difficulties, either for posterior inspection of results, or for meta-analysis by the incorporation of new related data. Integrating databases and tools into scientific workflows, orchestrating their execution, and managing the resulting data and its respective metadata are challenging tasks. Additionally, a great amount of effort is equally required to run in-silico experiments to structure and compose the information as needed for analysis. Different programs may need to be applied and different files are produced during the experiment cycle. In this context, the availability of a platform supporting experiment execution is paramount. We present GeNNet, an integrated transcriptome analysis platform that unifies scientific workflows with graph databases for selecting relevant genes according to the evaluated biological systems. It includes GeNNet-Wf, a scientific workflow that pre-loads biological data, pre-processes raw microarray data and conducts a series of analyses including normalization, differential expression inference, clusterization and gene set enrichment analysis. A user-friendly web interface, GeNNet-Web, allows for setting parameters, executing, and visualizing the results of GeNNet-Wf executions. To demonstrate the features of GeNNet, we performed case studies with data retrieved from GEO, particularly using a single-factor experiment in different analysis scenarios. As a result, we obtained differentially expressed genes for which biological functions were analyzed. The results are integrated into GeNNet-DB, a database about genes, clusters, experiments and their properties and relationships. The resulting graph database is explored with queries that demonstrate the expressiveness of this data model for reasoning about gene interaction networks. GeNNet is the first platform to integrate the analytical process of transcriptome data with graph databases. It provides a comprehensive set of tools that would otherwise be challenging for non-expert users to install and use. Developers can add new functionality to components of GeNNet. The derived data allows for testing previous hypotheses about an experiment and exploring new ones through the interactive graph database environment. It enables the analysis of different data on humans, rhesus, mice and rat coming from Affymetrix platforms. GeNNet is available as an open source platform at https://github.com/raquele/GeNNet and can be retrieved as a software container with the command docker pull quelopes/gennet.

Visualization and Analysis of MicroRNAs within KEGG Pathways using VANESA

MicroRNAs (miRNAs) are small RNA molecules which are known to take part in post-transcriptional regulation of gene expression. Here, VANESA, an existing platform for reconstructing, visualizing, and analysis of large biological networks, has been further expanded to include all experimentally validated human miRNAs available within miRBase, TarBase and miRTarBase. This is done by integrating a custom hybrid miRNA database to DAWIS-M.D., VANESA’s main data source, enabling the visualization and analysis of miRNAs within large biological pathways such as those found within the Kyoto Encyclopedia of Genes and Genomes (KEGG). Interestingly, 99.15 % of human KEGG pathways either contain genes which are targeted by miRNAs or harbor them. This is mainly due to the high number of interaction partners that each miRNA could have (e.g.: hsa-miR-335-5p targets 2544 genes and 71 miRNAs target NUFIP2). We demonstrate the usability of our system by analyzing the measles virus KEGG pathway as a proof-of-principle model and further highlight the importance of integrating miRNAs (both experimentally validated and predicted) into biological networks for the elucidation of novel miRNA-mRNA interactions of biological importance.

Computational and Experimental Identification of Tissue-Specific MicroRNA Targets

In this chapter we discuss computational methods for the prediction of microRNA (miRNA) targets. More specifically, we consider machine learning-based approaches and explain why these methods have been relatively unsuccessful in reducing the number of false positive predictions. Further we suggest approaches designed to improve their performance by considering tissue-specific target regulation. We argue that the miRNA targetome differs depending on the tissue type and introduce a novel algorithm that predicts miRNA targets specifically for colorectal cancer. We discuss features of miRNAs and target sites that affect target recognition, and how next-generation sequencing data can support the identification of novel miRNAs, differentially expressed miRNAs and their tissue-specific mRNA targets. In addition, we introduce some experimental approaches for the validation of miRNA targets as well as web-based resources sharing predicted and validated miRNA target interactions.

MicroRNA-712 restrains macrophage pro-inflammatory responses by targeting LRRK2 leading to restoration of insulin stimulated glucose uptake by myoblasts

Chronic inflammatory diseases such as insulin resistance, Type 2 diabetes, neurodegenerative diseases etc., are shown to be caused due to imbalanced activation states of macrophages. MicroRNAs which are transcriptional/post-transcriptional regulators of gene expression drive several pathophysiological processes including macrophage polarization. However the functional role of microRNAs in regulating inflammation induced insulin resistance is ill defined. In our current study we observed that the expression of miR-712 was reduced in macrophages exposed to LPS and IFN-γ. Ectopic expression of miR-712 in RAW 264.7 mouse macrophages impaired the expression of iNOS protein and secretion of pro-inflammatory cytokines such as TNF-α, IL-6 and IFN-β which in turn led to improved insulin stimulated glucose uptake in co-cultured L6 myoblasts. Mechanistically, we identified that miR-712 targets the 3'UTR of a potent inflammatory gene LRRK2 and dampens the phosphorylation of p38 and ERK1/2 kinases. Taken together, our data underscore the regulatory role of miR-712 in restoring insulin stimulated glucose uptake by myoblasts through down-regulating macrophage mediated inflammatory responses.

IRNdb: the database of immunologically relevant non-coding RNAs

MicroRNAs (miRNAs), long non-coding RNAs (lncRNAs) and other functional non-coding RNAs (ncRNAs) have emerged as pivotal regulators involved in multiple biological processes. Recently, ncRNA control of gene expression has been identified as a critical regulatory mechanism in the immune system. Despite the great efforts made to discover and characterize ncRNAs, the functional role for most remains unknown. To facilitate discoveries in ncRNA regulation of immune system-related processes, we developed the database of immunologically relevant ncRNAs and target genes (IRNdb). We integrated mouse data on predicted and experimentally supported ncRNA-target interactions, ncRNA and gene annotations, biological pathways and processes and experimental data in a uniform format with a user-friendly web interface. The current version of IRNdb documents 12 930 experimentally supported miRNA-target interactions between 724 miRNAs and 2427 immune-related mouse targets. In addition, we recorded 22 453 lncRNA-immune target and 377 PIWI-interacting RNA-immune target interactions. IRNdb is a comprehensive searchable data repository which will be of help in studying the role of ncRNAs in the immune system.

Database URL:http://irndb.org