Lost in translation: an assessment and perspective for computational microRNA target identification

Predicting the Effect of miRNA on Gene Regulation to Foster Translational Multi-Omics Research-A Review on the Role of Super-Enhancers

Gene regulation is crucial for cellular function and homeostasis. It involves diverse mechanisms controlling the production of specific gene products and contributing to tissue-specific variations in gene expression. The dysregulation of genes leads to disease, emphasizing the need to understand these mechanisms. Computational methods have jointly studied transcription factors (TFs), microRNA (miRNA), and messenger RNA (mRNA) to investigate gene regulatory networks. However, there remains a knowledge gap in comprehending gene regulatory networks. On the other hand, super-enhancers (SEs) have been implicated in miRNA biogenesis and function in recent experimental studies, in addition to their pivotal roles in cell identity and disease progression. However, statistical/computational methodologies harnessing the potential of SEs in deciphering gene regulation networks remain notably absent. However, to understand the effect of miRNA on mRNA, existing statistical/computational methods could be updated, or novel methods could be developed by accounting for SEs in the model. In this review, we categorize existing computational methods that utilize TF and miRNA data to understand gene regulatory networks into three broad areas and explore the challenges of integrating enhancers/SEs. The three areas include unraveling indirect regulatory networks, identifying network motifs, and enriching pathway identification by dissecting gene regulators. We hypothesize that addressing these challenges will enhance our understanding of gene regulation, aiding in the identification of therapeutic targets and disease biomarkers. We believe that constructing statistical/computational models that dissect the role of SEs in predicting the effect of miRNA on gene regulation is crucial for tackling these challenges.

Improving plant miRNA-target prediction with self-supervised k-mer embedding and spectral graph convolutional neural network

Deciphering the targets of microRNAs (miRNAs) in plants is crucial for comprehending their function and the variation in phenotype that they cause. As the highly cell-specific nature of miRNA regulation, recent computational approaches usually utilize expression data to identify the most physiologically relevant targets. Although these methods are effective, they typically require a large sample size and high-depth sequencing to detect potential miRNA-target pairs, thereby limiting their applicability in improving plant breeding. In this study, we propose a novel miRNA-target prediction framework named kmerPMTF (k-mer-based prediction framework for plant miRNA-target). Our framework effectively extracts the latent semantic embeddings of sequences by utilizing k-mer splitting and a deep self-supervised neural network. We construct multiple similarity networks based on k-mer embeddings and employ graph convolutional networks to derive deep representations of miRNAs and targets and calculate the probabilities of potential associations. We evaluated the performance of kmerPMTF on four typical plant datasets: Arabidopsis thaliana, Oryza sativa, Solanum lycopersicum, and Prunus persica. The results demonstrate its ability to achieve AUPRC values of 84.9%, 91.0%, 80.1%, and 82.1% in 5-fold cross-validation, respectively. Compared with several state-of-the-art existing methods, our framework achieves better performance on threshold-independent evaluation metrics. Overall, our study provides an efficient and simplified methodology for identifying plant miRNA-target associations, which will contribute to a deeper comprehension of miRNA regulatory mechanisms in plants.

Analysis of chimeric reads characterises the diverse targetome of AGO2-mediated regulation

Argonaute proteins are instrumental in regulating RNA stability and translation. AGO2, the major mammalian Argonaute protein, is known to primarily associate with microRNAs, a family of small RNA 'guide' sequences, and identifies its targets primarily via a 'seed' mediated partial complementarity process. Despite numerous studies, a definitive experimental dataset of AGO2 'guide'-'target' interactions remains elusive. Our study employs two experimental methods-AGO2 CLASH and AGO2 eCLIP, to generate thousands of AGO2 target sites verified by chimeric reads. These chimeric reads contain both the AGO2 loaded small RNA 'guide' and the target sequence, providing a robust resource for modeling AGO2 binding preferences. Our novel analysis pipeline reveals thousands of AGO2 target sites driven by microRNAs and a significant number of AGO2 'guides' derived from fragments of other small RNAs such as tRNAs, YRNAs, snoRNAs, rRNAs, and more. We utilize convolutional neural networks to train machine learning models that accurately predict the binding potential for each 'guide' class and experimentally validate several interactions. In conclusion, our comprehensive analysis of the AGO2 targetome broadens our understanding of its 'guide' repertoire and potential function in development and disease. Moreover, we offer practical bioinformatic tools for future experiments and the prediction of AGO2 targets. All data and code from this study are freely available at https://github.com/ML-Bioinfo-CEITEC/HybriDetector/ .

Using Attribution Sequence Alignment to Interpret Deep Learning Models for miRNA Binding Site Prediction

MicroRNAs (miRNAs) are small non-coding RNAs that play a central role in the post-transcriptional regulation of biological processes. miRNAs regulate transcripts through direct binding involving the Argonaute protein family. The exact rules of binding are not known, and several in silico miRNA target prediction methods have been developed to date. Deep learning has recently revolutionized miRNA target prediction. However, the higher predictive power comes with a decreased ability to interpret increasingly complex models. Here, we present a novel interpretation technique, called attribution sequence alignment, for miRNA target site prediction models that can interpret such deep learning models on a two-dimensional representation of miRNA and putative target sequence. Our method produces a human readable visual representation of miRNA:target interactions and can be used as a proxy for the further interpretation of biological concepts learned by the neural network. We demonstrate applications of this method in the clustering of experimental data into binding classes, as well as using the method to narrow down predicted miRNA binding sites on long transcript sequences. Importantly, the presented method works with any neural network model trained on a two-dimensional representation of interactions and can be easily extended to further domains such as protein–protein interactions.

Small RNA Targets: Advances in Prediction Tools and High-Throughput Profiling

MicroRNAs (miRNAs) are an abundant class of small non-coding RNAs that regulate gene expression at the post-transcriptional level. They are suggested to be involved in most biological processes of the cell primarily by targeting messenger RNAs (mRNAs) for cleavage or translational repression. Their binding to their target sites is mediated by the Argonaute (AGO) family of proteins. Thus, miRNA target prediction is pivotal for research and clinical applications. Moreover, transfer-RNA-derived fragments (tRFs) and other types of small RNAs have been found to be potent regulators of Ago-mediated gene expression. Their role in mRNA regulation is still to be fully elucidated, and advancements in the computational prediction of their targets are in their infancy. To shed light on these complex RNA-RNA interactions, the availability of good quality high-throughput data and reliable computational methods is of utmost importance. Even though the arsenal of computational approaches in the field has been enriched in the last decade, there is still a degree of discrepancy between the results they yield. This review offers an overview of the relevant advancements in the field of bioinformatics and machine learning and summarizes the key strategies utilized for small RNA target prediction. Furthermore, we report the recent development of high-throughput sequencing technologies, and explore the role of non-miRNA AGO driver sequences.

miRBind: A Deep Learning Method for miRNA Binding Classification

The binding of microRNAs (miRNAs) to their target sites is a complex process, mediated by the Argonaute (Ago) family of proteins. The prediction of miRNA:target site binding is an important first step for any miRNA target prediction algorithm. To date, the potential for miRNA:target site binding is evaluated using either co-folding free energy measures or heuristic approaches, based on the identification of binding 'seeds', i.e., continuous stretches of binding corresponding to specific parts of the miRNA. The limitations of both these families of methods have produced generations of miRNA target prediction algorithms that are primarily focused on 'canonical' seed targets, even though unbiased experimental methods have shown that only approximately half of in vivo miRNA targets are 'canonical'. Herein, we present miRBind, a deep learning method and web server that can be used to accurately predict the potential of miRNA:target site binding. We trained our method using seed-agnostic experimental data and show that our method outperforms both seed-based approaches and co-fold free energy approaches. The full code for the development of miRBind and a freely accessible web server are freely available.

Downregulation of NHE-3 (SLC9A3) expression by MicroRNAs in intestinal epithelial cells

Na+/H+ exchanger-3 (NHE-3) is the major apical membrane transporter involved in vectorial Na+ absorption in the intestine. Dysregulation of NHE-3 expression and/or function has been implicated in pathophysiology of diarrhea associated with gut inflammation and infections. Therefore, it is critical to understand the mechanisms involved in the regulation of NHE-3 expression. MicroRNAs (miRNAs) are highly conserved small RNAs that can regulate gene expression at the posttranscriptional level. To date, however, very little is known about the regulation of NHE-3 expression by microRNAs. Therefore, current studies were undertaken to examine the potential miRNA candidates that can regulate the expression of NHE-3 in intestinal epithelial cells. In silico analysis, using different algorithms, predicted several miRNAs that target NHE-3. MicroRNAs with highest context and target score, miR-326, miR-744-5p, and miR-330-5p, were selected for the current study. Human NHE-3 gene 3' untranslated region [3'UTR; 160 base pair (bp)] was cloned into pmirGLO vector upstream of luciferase reporter and transiently transfected with mimics of miR-326, miR-744-5p, and miR-330-5p into Caco-2, HT-29, and SK-CO15 cells. Cotransfection of NHE-3 3' UTR with miR-326 and -miR-330-5p mimics resulted in a significant decrease in relative luciferase activity. Transfection of miR-326 and -330-5p mimics into SK-CO15 cells significantly decreased the NHE-3 protein expression, with no change in NHE-3 messenger ribonucleic acid (mRNA) levels. Our findings demonstrate a novel mechanism for posttranscriptional regulation of NHE-3 by miR-326 and -330-5p by translational repression. We speculate that miR-326 and -330-5p dependent pathways may be involved in modulating NHE-3 expression under physiological and pathophysiological conditions.

MiRNA/mRNA network topology in hepatitis virus B-related liver cirrhosis reveals miR-20a-5p/340-5p as hubs initiating fibrosis

Background

The pathophysiology of hepatitis B-related liver cirrhosis (HBV-LC) remains unclear. This study aimed to explore the disease mechanisms using topological analysis of the miRNA/mRNA network.

Methods

Paired miRNA/mRNA sequencing was performed with thirty-three peripheral blood mononuclear cell samples (LC, n = 9; chronic hepatitis B, n = 12; normal controls, n = 12) collected from a prospective cohort to identify the miRNA/mRNA network. Topological features and functional implications of the network were analyzed to capture pathophysiologically important miRNAs/mRNAs, whose expression patterns were confirmed in the validation group (LC, n = 15; chronic hepatitis B, n = 15; normal controls, n = 10), and functional potentials initiating fibrogenesis were demonstrated in vitro.

Results

The miRNA/mRNA network contained 3121 interactions between 158 differentially expressed (DE) miRNAs and 442 DE-mRNAs. The topological analysis identified a core module containing 99 miRNA/mRNA interactions and two hub nodes (miR-20a-5p/miR-340-5p), which connected to 75 DE-mRNAs. The expression pattern along the disease progression of the core module was found associated with a continuous increase in wound healing, inflammation, and leukocyte migration but an inflection of immune response and lipid metabolic regulation, consistent with the pathophysiology of HBV-LC. MiR-20a-5p/miR-340-5p were found involved in macrophage polarization and hepatic stellate cell (HSC) activation in vitro (THP-1, LX-2 cell lines), and their expression levels were confirmed in the validation group independently.

Conclusion

Topological analysis of the miRNA/mRNA network in HBV-LC revealed the association between fibrosis and miR-20a-5p/miR-340-5p involving initiating activations of macrophage and HSC. Further validations should be performed to confirm the HSC/macrophage activations and the interactions between miR-20a-5p/miR-340-5p and their potential targets, which may help to develop non-invasive prognostic markers or intervention targets for HBV-LC.

Computational Detection of MicroRNA Targets

MicroRNAs (miRNAs) are small noncoding RNAs that are recognized as posttranscriptional regulators of gene expression. These molecules have been shown to play important roles in several cellular processes. MiRNAs act on their target by guiding the RISC complex and binding to the mRNA molecule. Thus, it is recognized that the function of a miRNA is determined by the function of its target (s). By using high-throughput methodologies, novel miRNAs are being identified, but their functions remain uncharted. Target validation is crucial to properly understand the specific role of a miRNA in a cellular pathway. However, molecular techniques for experimental validation of miRNA-target interaction are expensive, time-consuming, laborious, and can be not accurate in inferring true interactions. Thus, accurate miRNA target predictions are helpful to understand the functions of miRNAs. There are several algorithms proposed for target prediction and databases containing miRNA-target information. However, these available computational tools for prediction still generate a large number of false positives and fail to detect a considerable number of true targets, which indicates the necessity of highly confident approaches to identify bona fide miRNA-target interactions. This chapter focuses on tools and strategies used for miRNA target prediction, by providing practical insights and outlooks.

MicroRNA Targeting

MicroRNAs (miRNAs) are small noncoding elements that play essential roles in the posttranscriptional regulation of biochemical processes. miRNAs recognize and target multiple mRNAs; therefore, investigating miRNA dysregulation is an indispensable strategy to understand pathological conditions and to design innovative drugs. Targeting miRNAs in diseases improve outcomes of several therapeutic strategies thus, this present study highlights miRNA targeting methods through experimental assays and bioinformatics tools. The first part of this review focuses on experimental miRNA targeting approaches for elucidating key biochemical pathways. A growing body of evidence about the miRNA world reveals the fact that it is not possible to uncover these molecules' structural and functional characteristics related to the biological processes with a deterministic approach. Instead, a systemic point of view is needed to truly understand the facts behind the natural complexity of interactions and regulations that miRNA regulations present. This task heavily depends both on computational and experimental capabilities. Fortunately, several miRNA bioinformatics tools catering to nonexperts are available as complementary wet-lab approaches. For this purpose, this work provides recent research and information about computational tools for miRNA targeting research.

The effects of altered neurogenic microRNA levels and their involvement in the aggressiveness of periventricular glioblastoma

INTRODUCTION

Glioblastoma multiforme is the most common primary brain tumour, with the least favourable prognosis. Despite numerous studies and medical advances, it continues to be lethal, with an average life expectancy of 15 months after chemo-radiotherapy.

DEVELOPMENT

Recent research has addressed several factors associated with the diagnosis and prognosis of glioblastoma; one significant factor is tumour localisation, particularly the subventricular zone, which represents one of the most active neurogenic niches of the adult human brain. Glioblastomas in this area are generally more aggressive, resulting in unfavourable prognosis and a shorter life expectancy. Currently, the research into microRNAs (miRNA) has intensified, revealing different expression patterns under physiological and pathophysiological conditions. It has been reported that the expression levels of certain miRNAs, mainly those related to neurogenic processes, are dysregulated in oncogenic events, thus favouring gliomagenesis and greater tumour aggressiveness. This review discusses some of the most important miRNAs involved in subventricular neurogenic processes and their association with glioblastoma aggressiveness.

CONCLUSIONS

MiRNA regulation and function play an important role in the development and progression of glioblastoma; understanding the alterations of certain miRNAs involved in both differentiation and neural and glial maturation could help us to better understand the malignant characteristics of glioblastoma.

An updated overview and classification of bioinformatics tools for MicroRNA analysis, which one to choose?

The term 'MicroRNA' (miRNA) refers to a class of small endogenous non-coding RNAs (ncRNAs) regenerated from hairpin transcripts. Recent studies reveal miRNAs' regulatory involvement in essential biological processes through translational repression or mRNA degradation. Recently, there is a growing body of literature focusing on the importance of miRNAs and their functions. In this respect, several databases have been developed to manage the dispersed data produced. Therefore, it is necessary to know the parameters and characteristics of each database to benefit their data. Besides, selecting the correct database is of great importance to scientists who do not have enough experience in this field. A comprehensive classification along with an explanation of the information contained in each database leads to facilitating access to these resources. In this regard, we have classified relevant databases into several categories, including miRNA sequencing and annotation, validated/predicted miRNA targets, disease-related miRNA, SNP in miRNA sequence or target site, miRNA-related pathways, or gene ontology, and mRNA-miRNA interactions. Hence, this review introduces available miRNA databases and presents a convenient overview to inform researchers of different backgrounds to find suitable miRNA-related bioinformatics web tools and relevant information rapidly.

MiR-9-5p Regulates Genes Linked to Cerebral Calcification in the Osteogenic Differentiation Model and Induces Generalized Alteration in the Ion Channels

MicroRNA-9 (miR-9) modulates gene expression and demonstrates high structural conservation and wide expression in the central nervous system. Bioinformatics analysis predicts almost 100 ion channels, membrane transporters and receptors, including genes linked to primary familial brain calcification (PFBC), as possible miR-9-5p targets. PFBC is a neurodegenerative disorder, characterized by bilateral and symmetrical calcifications in the brain, associated with motor and behavioral disturbances. In this work, we seek to study the influence of miR-9-5p in regulating genes involved in PFBC, in an osteogenic differentiation model with SaOs-2 cells. During the induced calcification process, solute carrier family 20 member 2 (SLC20A2) and platelet-derived growth factor receptor beta (PDGFRB) were downregulated, while platelet-derived growth factor beta (PDGFB) showed no significant changes. Significantly decreased levels of SLC20A2 and PDGFRB were caused by the presence of miR-9-5p, while PDGFB showed no regulation. We confirmed the findings using an miR-9-5p inhibitor and also probed the cells in electrophysiological analysis to assess whether such microRNA might affect a broader range of ion channels, membrane transporters and receptors. Our electrophysiological data show that an increase of the miR-9-5p in SaOs-2 cells decreased the density and amplitude of the output ionic currents, indicating that it may influence the activity, and perhaps the expression, of some ionic channels. Additional investigations should determine whether such an effect is specific to miR-9-5p, and whether it could be used, together with the miR-9-5p inhibitor, as a therapeutic or diagnostic tool.

Potential functions of hsa-miR-155-5p and core genes in chronic myeloid leukemia and emerging role in human cancer: A joint bioinformatics analysis

Considering the critical roles of hsa-miR-155-5p participated in hematopoietic system, this study aims to clarify the possible pathogenesis of chronic myeloid leukemia (CML) induced by hsa-miR-155-5p.Three different strategies were employed, namely a network-based pipeline, a survival analysis and genetic screening method, and a simulation modeling approach, to assess the oncogenic role of hsa-miR-155-5p in CML. We identified new potential roles of hsa-miR-155-5p in CML, involving the BCR/ABL-mediated leukemogenesis through MAPK signaling. Several promising targets including E2F2, KRAS and FLI1 were screened as candidate diagnostic marker genes. The survival analysis revealed that mRNA expression of E2F2, KRAS and FLI1 was negatively correlated with hsa-miR-155-5p and these targets were significantly associated with poor overall survival. Furthermore, an overlap between CML-related genes and hsa-miR-155-5p target genes was revealed using competing endogenous RNA (ceRNA) networks analysis. Taken together, our results reveal the dynamic regulatory aspect of hsa-miR-155-5p as potential player in CML pathogenesis.

Micro-RNA Quantification, Target Gene Identification, and Pathway Analysis

RNA sequencing has become a powerful tool for profiling the expression level of small RNAs from both solid tissues and liquid biopsies. In conjunction with pathway analysis, it offers exciting possibilities for the identification of disease specific biomarkers. In this chapter, we describe a workflow for processing this type of sequencing data. We start by removing technical sequences (adapters) and by performing quality control, a critical task that is necessary to identify possible issues caused by sample preparation and library sequencing. We then describe read alignment and gene-level abundance estimation. Building on these results, we normalize expression profiles and compute differentially expressed microRNAs between sample groups of interest. We conclude by showing how to employ pathway analysis to identify molecular signatures corresponding to biological processes that are significantly altered by the action for microRNAs.

Identification of miRNAs that regulate human CYP2B6 expression

Human hepatic cytochrome P450 2B6 (CYP2B6) expressed is responsible for the metabolism of many drugs, such as cyclophosphamide, ifosfamid, and efavirenz. In the present study, the correlation between CYP2B6 mRNA and protein levels in human liver samples was found to be moderate, indicating a contribution of posttranscriptional regulation of CYP2B6. Thus, we examined the role of microRNAs (miRNAs) in the regulation of CYP2B6. We established two kinds of HEK293 cell lines stably expressing CYP2B6, including or excluding the full-length 3'-untranslated region (3'-UTR) (HEK/2B6+UTR and HEK/2B6 cells, respectively). We tested 14 miRNAs that were predicted to bind to the 3'-UTR of CYP2B6 and found that the overexpression of miR-145, miR-194, miR-222, and miR-378 decreased the CYP2B6 protein level and activity in HEK/2B6+UTR but not in HEK/2B6 cells. These results suggested that miR-145, miR-194, miR-222, and miR-378 negatively regulate CYP2B6 expression by binding to the 3'-UTR. A negative correlation was not observed between the translational efficiency of CYP2B6 and the expression level of miR-145, miR-194, miR-222, or miR-378. This is due to the contribution of multiple miRNAs to CYP2B6 regulation. In conclusion, this study demonstrated that human CYP2B6 is posttranscriptionally regulated by miR-145, miR-194, miR-222, and miR-378.

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.

Pervasive Selection against MicroRNA Target Sites in Human Populations

MicroRNA target sites are often conserved during evolution and purifying selection to maintain such sites is expected. On the other hand, comparative analyses identified a paucity of microRNA target sites in coexpressed transcripts, and novel target sites can potentially be deleterious. We proposed that selection against novel target sites pervasive. The analysis of derived allele frequencies revealed that, when the derived allele is a target site, the proportion of nontarget sites is higher than expected, particularly for highly expressed microRNAs. Thus, new alleles generating novel microRNA target sites can be deleterious and selected against. When we analyzed ancestral target sites, the derived (nontarget) allele frequency does not show statistical support for microRNA target allele conservation. We investigated the joint effects of microRNA conservation and expression and found that selection against microRNA target sites depends mostly on the expression level of the microRNA. We identified microRNA target sites with relatively high levels of population differentiation. However, when we analyze separately target sites in which the target allele is ancestral to the population, the proportion of single-nucleotide polymorphisms with high F_st significantly increases. These findings support that population differentiation is more likely in target sites that are lost than in the gain of new target sites. Our results indicate that selection against novel microRNA target sites is prevalent and, although individual sites may have a weak selective pressure, the overall effect across untranslated regions is not negligible and should be accounted when studying the evolution of genomic sequences.

Unravelling the Role of miR-20b-5p, CCNB1, HMGA2 and E2F7 in Development and Progression of Non-Small Cell Lung Cancer (NSCLC)

Lung cancer is a prime cause of worldwide cancer deaths, with non-small cell lung cancer (NSCLC) as a frequent subtype. Surgical resection, chemotherapy are the currently used treatment methods. Delayed detection, poor prognosis, tumor heterogeneity, and chemoresistance make them relatively ineffective. Genomic medicine is a budding aspect of cancer therapeutics, where miRNAs are impressively involved. miRNAs are short ncRNAs that bind to 3′UTR of target mRNA, causing its degradation or translational repression to regulate gene expression. This study aims to identify important miRNA-mRNA-TF interactions in NSCLC using bioinformatics analysis. GEO datasets containing mRNA expression data of NSCLC were used to determine differentially expressed genes (DEGs), and identification of hub genes-BIRC5, CCNB1, KIF11, KIF20A, and KIF4A (all functionally enriched in cell cycle). The FFL network involved, comprised of miR-20b-5p, CCNB1, HMGA2, and E2F7. KM survival analysis determines that these components may be effective prognostic biomarkers and would be a new contemplation in NSCLC therapeutics as they target cell cycle and immunosurveillance mechanisms via HMGA2 and E2F7. They provide survival advantage and evasion of host immune response (via downregulation of cytokines-IL6, IL1R1 and upregulation of chemokines-CXCL13, CXCL14) to NSCLC. The study has provided innovative targets, but further validation is needed to confirm the proposed mechanism.

Distinct Subsets of Noncoding RNAs Are Strongly Associated With BMD and Fracture, Studied in Weight-Bearing and Non-Weight-Bearing Human Bone

We investigated mechanisms resulting in low bone mineral density (BMD) and susceptibility to fracture by comparing noncoding RNAs (ncRNAs) in biopsies of non-weight-bearing (NWB) iliac (n = 84) and weight bearing (WB) femoral (n = 18) postmenopausal bone across BMDs varying from normal (T-score > -1.0) to osteoporotic (T-score ≤ -2.5). Global bone ncRNA concentrations were determined by PCR and microchip analyses. Association with BMD or fracture, adjusted by age and body mass index, were calculated using linear and logistic regression and least absolute shrinkage and selection operator (Lasso) analysis. At 10% false discovery rate (FDR), 75 iliac bone ncRNAs and 94 femoral bone ncRNAs were associated with total hip BMD. Eight of the ncRNAs were common for the two sites, but five of them (miR-484, miR-328-3p, miR-27a-5p, miR-28-3p, and miR-409-3p) correlated positively to BMD in femoral bone, but negatively in iliac bone. Of predicted pathways recognized in bone metabolism, ECM-receptor interaction and proteoglycans in cancer emerged at both sites, whereas fatty acid metabolism and focal adhesion were only identified in iliac bone. Lasso analysis and cross-validations identified sets of nine bone ncRNAs correlating strongly with adjusted total hip BMD in both femoral and iliac bone. Twenty-eight iliac ncRNAs were associated with risk of fracture (FDR < 0.1). The small nucleolar RNAs, RNU44 and RNU48, have a function in stabilization of ribosomal RNAs (rRNAs), and their association with fracture and BMD suggest that aberrant processing of rRNAs may be involved in development of osteoporosis. Cis-eQTL (expressed quantitative trait loci) analysis of the iliac bone biopsies identified two loci associated with microRNAs (miRNAs), one previously identified in a heel-BMD genomewide association study (GWAS). In this comprehensive investigation of the skeletal genetic background in postmenopausal women, we identified functional bone ncRNAs associated to fracture and BMD, representing distinct subsets in WB and NWB skeletal sites. © 2020 The Authors. Journal of Bone and Mineral Research published by American Society for Bone and Mineral Research.

The effects of altered neurogenic microRNA levels and their involvement in the aggressiveness of periventricular glioblastoma

INTRODUCTION

Glioblastoma multiforme is the most common primary brain tumour, with the least favourable prognosis. Despite numerous studies and medical advances, it continues to be lethal, with an average life expectancy of 15 months after chemo-radiotherapy.

DEVELOPMENT

Recent research has addressed several factors associated with the diagnosis and prognosis of glioblastoma; one significant factor is tumour localisation, particularly the subventricular zone, which represents one of the most active neurogenic niches of the adult human brain. Glioblastomas in this area are generally more aggressive, resulting in unfavourable prognosis and a shorter life expectancy. Currently, the research into microRNAs (miRNA) has intensified, revealing different expression patterns under physiological and pathophysiological conditions. It has been reported that the expression levels of certain miRNAs, mainly those related to neurogenic processes, are dysregulated in oncogenic events, thus favouring gliomagenesis and greater tumour aggressiveness. This review discusses some of the most important miRNAs involved in subventricular neurogenic processes and their association with glioblastoma aggressiveness.

CONCLUSIONS

MiRNA regulation and function play an important role in the development and progression of glioblastoma; understanding the alterations of certain miRNAs involved in both differentiation and neural and glial maturation could help us to better understand the malignant characteristics of glioblastoma.

Temporal dynamics of miRNAs in human DLPFC and its association with miRNA dysregulation in schizophrenia

Brain development is dependent on programmed gene expression, which is both genetically and epigenetically regulated. Post-transcriptional regulation of gene expression by microRNAs (miRNAs) is essential for brain development. As abnormal brain development is hypothesized to be associated with schizophrenia, miRNAs are an intriguing target for this disorder. The aims of this study were to determine the temporal dynamics of miRNA expression in the human dorsolateral prefrontal cortex (DLPFC), and the relationship between miRNA's temporal expression pattern and dysregulation in schizophrenia. This study used next-generation sequencing to characterize the temporal dynamics of miRNA expression in the DLPFC of 109 normal subjects (second trimester-74 years of age) and miRNA expression changes in 34 schizophrenia patients. Unlike mRNAs, the majority of which exhibits a wave of change in fetuses, most miRNAs are preferentially expressed during a certain period before puberty. It is noted that in schizophrenia patients, miRNAs normally enriched in infants tend to be upregulated, while those normally enriched in prepuberty tend to be downregulated, and the targets of these miRNAs are enriched for genes encoding synaptic proteins and those associated with schizophrenia. In addition, miR-936 and miR-3162 were found to be increased in the DLPFC of patients with schizophrenia. These findings reveal the temporal dynamics of miRNAs in the human DLPFC, implicate the importance of miRNAs in DLPFC development, and suggest a possible link between schizophrenia and dysregulation of miRNAs enriched in infancy and prepuberty.

Comprehensive Overview and Assessment of microRNA Target Prediction Tools in Homo sapiens and Drosophila melanogaster

Background:

MicroRNAs (miRNAs) are small non-coding RNAs that control gene expression at the post-transcriptional level through complementary base pairing with the target mRNA, leading to mRNA degradation and blocking translation process. Many dysfunctions of these small regulatory molecules have been linked to the development and progression of several diseases. Therefore, it is necessary to reliably predict potential miRNA targets.

Objective:

A large number of computational prediction tools have been developed which provide a faster way to find putative miRNA targets, but at the same time, their results are often inconsistent. Hence, finding a reliable, functional miRNA target is still a challenging task. Also, each tool is equipped with different algorithms, and it is difficult for the biologists to know which tool is the best choice for their study.

Methods:

We analyzed eleven miRNA target predictors on Drosophila melanogaster and Homo sapiens by applying significant empirical methods to evaluate and assess their accuracy and performance using experimentally validated high confident mature miRNAs and their targets. In addition, this paper also describes miRNA target prediction algorithms, and discusses common features of frequently used target prediction tools.

Results:

The results show that MicroT, microRNA and CoMir are the best performing tool on Drosopihla melanogaster; while TargetScan and miRmap perform well for Homo sapiens. The predicted results of each tool were combined in order to improve the performance in both the datasets, but any significant improvement is not observed in terms of true positives.

Conclusion:

The currently available miRNA target prediction tools greatly suffer from a large number of false positives. Therefore, computational prediction of significant targets with high statistical confidence is still an open challenge.

The Impact of Population Variation in the Analysis of microRNA Target Sites

The impact of population variation in the analysis of regulatory interactions is an underdeveloped area. MicroRNA target recognition occurs via pairwise complementarity. Consequently, a number of computational prediction tools have been developed to identify potential target sites that can be further validated experimentally. However, as microRNA target predictions are done mostly considering a reference genome sequence, target sites showing variation among populations are neglected. Here, we studied the variation at microRNA target sites in human populations and quantified their impact in microRNA target prediction. We found that African populations carry a significant number of potential microRNA target sites that are not detectable in the current human reference genome sequence. Some of these targets are conserved in primates and only lost in Out-of-Africa populations. Indeed, we identified experimentally validated microRNA/transcript interactions that are not detected in standard microRNA target prediction programs, yet they have segregating target alleles abundant in non-European populations. In conclusion, we show that ignoring population diversity may leave out regulatory elements essential to understand disease and gene expression, particularly neglecting populations of African origin.

MicroRNA-135a-5p reduces P2X7 -dependent rise in intracellular calcium and protects against excitotoxicity

Excitotoxic cell death because of the massive release of glutamate and ATP contributes to the secondary extension of cellular and tissue loss following traumatic spinal cord injury (SCI). Evidence from blockage experiments suggests that over-expression and activation of purinergic receptors, especially P2X₇ , produces excitotoxicity in neurodegenerative diseases and trauma of the central nervous system. We hypothesize that the down-regulation of specific miRNAs after the SCI contributes to the over-expression of P2X₇ and that restorative strategies can be used to reduce the excitotoxic response. In the present study, we have employed bioinformatic analyses to identify microRNAs whose down-regulation following SCI can be responsible for P2X₇ over-expression and excitotoxic activity. Additional luciferase assays validated microRNA-135a-5p (miR-135a) as a posttranscriptional modulator of P2X₇ . Moreover, gene expression analysis in spinal cord samples from a rat SCI model confirmed that the decrease in miR-135a expression correlated with P2X₇ over-expression after injury. Transfection of cultures of Neuro-2a neuronal cell line with a miR-135a inhibitory sequences (antagomiR-135a), simulating the reduction of miR-135a observed after SCI, resulted in the increase of P2X₇ expression and the subsequent ATP-dependent rise in intracellular calcium concentration. Conversely, a restorative strategy employing miR-135a mimicked reduced P2X₇ expression, attenuating the increase in intracellular calcium concentration that depends on this receptor and protecting cells from excitotoxic death. Therefore, we conclude that miR-135a is a potential therapeutic target for SCI and that restoration of its expression may reduce the deleterious effects of ATP-dependent excitotoxicity induced after a traumatic spinal cord injury.

miR-125a-5p: a novel regulator of SLC26A6 expression in intestinal epithelial cells

Putative anion transporter 1 (PAT1, SLC26A6), an intestinal epithelial Cl^-/ HCO3- exchanger, also plays a key role in oxalate homeostasis via mediating intestinal oxalate secretion. Indeed, Slc26a6-null mice showed defect in intestinal oxalate secretion and high incidence of kidney stones. Recent emergence of PAT-1 as a novel therapeutic target for nephrolithiasis warrants detailed understanding of the mechanisms of PAT-1 regulation in health and disease. Therefore, we investigated the regulation of PAT-1 expression by microRNAs (miRNA), as they have been shown to play key role in modulating expression of other ion transporters. In silico analysis of PAT-1 3'-untranslated region (UTR) revealed potential binding sites for several miRNAs, suggesting the role of miRNAs in modulating PAT1 expression. miRNAs showing highest context scores (125a-5p, 339-5p, 423-5p, 485-5p, and 501-3p) were selected as candidates for their effects on the activity of a 263-bp PAT-1 3'-untranslated region (UTR) fragment cloned into pmirGLO vector upstream of luciferase. The 3'-UTR activity was measured by dual luciferase reporter assay in Caco-2, T-84, HT-29, and SK-CO15 cells. Transient transfection of PAT-1 3'-UTR significantly decreased the relative luciferase activity compared with the empty vector suggesting binding of potential miRNA(s) to the PAT-1 3'-UTR. Among all the selected candidates, cotransfection with miRNA mimics 125a-5p and 423-5p further decreased PAT-1 3'-UTR activity. Furthermore, increasing miR-125a-5p abundance via mimic transfection in Caco-2 cells decreased both mRNA and protein levels of PAT-1. Our results demonstrate a novel regulatory mechanism of intestinal PAT-1 expression via miR-125a-5p that could be of therapeutic importance in disorders associated with decreased PAT-1 expression and function.

Identifying the optimal target genes associated with multiple myeloma by a novel bioinformatical analysis

Multiple myeloma (MM) is one of the most frequent malignant hematopoietic diseases, the pathogenesis of which remains unclear. It is well known that miRNAs are aberrantly expressed in many tumors, thus, investigating the target genes of miRNAs contributes to understanding the functional effect of miRNAs on MM. In this study, plasma samples of 147 patients with MM and 15 normal donors were collected. Using high-throughout microarray and limma package to screen the differentially expressed genes. Furthermore, to accurately predict the optimal target genes of MM, the logFC, targetScanCS and targetScanPCT values of known genes in four miRNAs (i.e. has-miR-21, has-miR-20a, has-miR-148a and has-miR-99b) were used to compute the targetScore values. As a result, 171 genes with larger difference were screened out using t-test, F-test and eBayes statistics analysis. Furthermore, 34 potential target genes associated with MM were selected by integrating the differentially expressed genes (DEGs) and the genes obtained by targetScore algorithm. Additionally, combining with the mutated genes in MM and the obtained DEGs, 41 consistently expressed genes were obtained. Finally, 5 optimal target genes, including SYK, LCP1, HIF1A, ALDH1A1 and MAFB, were screened out by the intersection of 34 DEGs and 41 mutated genes. In a word, this novel target gene prediction algorithm may contribute to improve our understanding on the pathogenesis of miRNAs in MM, which open up a new approach for future study.

MicroRNA target gene prediction of ischemic stroke by using variational Bayesian inference for Gauss mixture model

MicroRNAs (miRNAs) as biomarkers of numerous diseases, are a novel group of single-stranded, non-coding small RNA molecules, which can regulate the gene expression and transcription or translation of target genes. Therefore, accurately identifying miRNAs and predicting their potential target genes correlated with ischemic stroke contribute to quick understanding and diagnosis of the pathogenesis of ischemic stroke. In order to identify the targets of miRNAs, the differential expression and expression profiling of mRNAs in genome are integrated by using the Gene Expression Omnibus (GEO) database and limma package. Furthermore, the probabilistic scoring approach called TargetScore, is proposed as a promising new technique combined with the expression and sequence information of the known genes. In this study, the priori and posterior probabilities of target genes were obtained by Variational Bayesian-Gaussian Mixture Model (VB-GMM). Consequently, the target genes of miR-124, miR-221 and miR-223, correlated with ischemic stroke, were predicted using the new target prediction algorithm. Ultimately, the comparable downregulation target genes were obtained by integrating the transcendental and posterior values.

miRNet-Functional Analysis and Visual Exploration of miRNA-Target Interactions in a Network Context

To gain functional insights into microRNAs (miRNAs), researchers usually look for pathways or biological processes that are overrepresented in their target genes. The interpretation is often complicated by the fact that a single miRNA can target many genes and multiple miRNAs can regulate a single gene. Here we introduce miRNet ( www.mirnet.ca ), an easy-to-use web-based tool designed for creation, customization, visual exploration and functional interpretation of miRNA-target interaction networks. By integrating multiple high-quality miRNA-target data sources and advanced statistical methods into a powerful network visualization system, miRNet allows researchers to easily navigate the complex landscape of miRNA-target interactions to obtain deep biological insights. This tutorial provides a step-by-step protocol on how to use miRNet to create miRNA-target networks for visual exploration and functional analysis from different types of data inputs.

Novel microRNAs are associated with population divergence in transcriptional response to thermal stress in an intertidal copepod

The role of gene expression in adaptation to differing thermal environments has been assayed extensively. Yet, in most natural systems, analyses of gene expression reveal only one level of the complexity of regulatory machineries. MicroRNAs (miRNAs) are small noncoding RNAs which are key components of many gene regulatory networks, and they play important roles in a variety of cellular pathways by modulating post-transcriptional quantities of mRNA available for protein synthesis. The characterization of miRNA loci and their regulatory dynamics in nonmodel systems are still largely understudied. In this study, we examine the role of miRNAs in response to high thermal stress in the intertidal copepod Tigriopus californicus. Allopatric populations of this species show varying levels of local adaptation with respect to thermal regimes, and previous studies showed divergence in gene expression between populations from very different thermal environments. We examined the transcriptional response to temperature stress in two populations separated by only 8 km by utilizing RNA-seq to quantify both mRNA and miRNA levels. Using the currently available genome sequence, we first describe the repertoire of miRNAs in T. californicus and assess the degree to which transcriptional response to temperature stress is governed by miRNA activity. The two populations showed large differences in the number of genes involved, the magnitude of change in commonly used genes and in the number of miRNAs involved in transcriptional modulation during stress. Our results suggest that an increased level of regulatory network complexity may underlie improved survivorship under thermal stress in one of the populations.

MicroRNA-31 Reduces the Motility of Proinflammatory T Helper 1 Lymphocytes

Proinflammatory type 1 T helper (Th1) cells are enriched in inflamed tissues and contribute to the maintenance of chronic inflammation in rheumatic diseases. Here we show that the microRNA- (miR-) 31 is upregulated in murine Th1 cells with a history of repeated reactivation and in memory Th cells isolated from the synovial fluid of patients with rheumatic joint disease. Knock-down of miR-31 resulted in the upregulation of genes associated with cytoskeletal rearrangement and motility and induced the expression of target genes involved in T cell activation, chemokine receptor- and integrin-signaling. Accordingly, inhibition of miR-31 resulted in increased migratory activity of repeatedly activated Th1 cells. The transcription factors T-bet and FOXO1 act as positive and negative regulators of T cell receptor (TCR)-mediated miR-31 expression, respectively. Taken together, our data show that a gene regulatory network involving miR-31, T-bet, and FOXO1 controls the migratory behavior of proinflammatory Th1 cells.

MicroRNAs Regulating Reactive Oxygen Species in Cardiovascular Diseases

SIGNIFICANCE

Oxidative stress caused by overproduction of reactive oxygen species (ROS) in cells is one of the most important contributors to the pathogenesis of cardiovascular and metabolic diseases such as hypertension and atherosclerosis. Excessive accumulation of ROS impairs, while limiting oxidative stress protects cardiovascular and metabolic function through various cellular mechanisms. Recent Advances: MicroRNAs (miRNAs) are novel regulators of oxidative stress in cardiovascular cells that modulate the expression of redox-related genes. This article summarizes recent advances in our understanding of how miRNAs target major ROS generators, antioxidant signaling pathways, and effectors in cells of the cardiovascular system.

CRITICAL ISSUES

The role of miRNAs in regulating ROS in cardiovascular cells is complicated because miRNAs can target multiple redox-related genes, act on redox regulatory pathways indirectly, and display context-dependent pro- or antioxidant effects. The complex regulatory network of ROS and the plethora of targets make it difficult to pin point the role of miRNAs and develop them as therapeutics. Therefore, these properties should be considered when designing strategies for therapeutic or diagnostic development.

FUTURE DIRECTIONS

Future studies can gain a better understanding of redox-related miRNAs by investigating their own regulatory mechanisms and the dual role of ROS in the cardiovascular systems. The combination of improved study design and technical advancements will reveal newer pathophysiological importance of redox-related miRNAs.

Current knowledge of microRNA-mediated regulation of drug metabolism in humans

INTRODUCTION

Understanding the factors causing inter- and intra-individual differences in drug metabolism potencies is required for the practice of personalized or precision medicine, as well as for the promotion of efficient drug development. The expression of drug-metabolizing enzymes is controlled by transcriptional regulation by nuclear receptors and transcriptional factors, epigenetic regulation, such as DNA methylation and histone acetylation, and post-translational modification. In addition to such regulation mechanisms, recent studies revealed that microRNAs (miRNAs), endogenous ~22-nucleotide non-coding RNAs that regulate gene expression through the translational repression and degradation of mRNAs, significantly contribute to post-transcriptional regulation of drug-metabolizing enzymes. Areas covered: This review summarizes the current knowledge regarding miRNAs-dependent regulation of drug-metabolizing enzymes and transcriptional factors and its physiological and clinical significance. We also describe recent advances in miRNA-dependent regulation research, showing that the presence of pseudogenes, single-nucleotide polymorphisms, and RNA editing affects miRNA targeting. Expert opinion: It is unwavering fact that miRNAs are critical factors causing inter- and intra-individual differences in the expression of drug-metabolizing enzymes. Consideration of miRNA-dependent regulation would be a helpful tool for optimizing personalized and precision medicine.

SeedVicious: Analysis of microRNA target and near-target sites

Here I describe seedVicious, a versatile microRNA target site prediction software that can be easily fitted into annotation pipelines and run over custom datasets. SeedVicious finds microRNA canonical sites plus other, less efficient, target sites. Among other novel features, seedVicious can compute evolutionary gains/losses of target sites using maximum parsimony, and also detect near-target sites, which have one nucleotide different from a canonical site. Near-target sites are important to study population variation in microRNA regulation. Some analyses suggest that near-target sites may also be functional sites, although there is no conclusive evidence for that, and they may actually be target alleles segregating in a population. SeedVicious does not aim to outperform but to complement existing microRNA prediction tools. For instance, the precision of TargetScan is almost doubled (from 11% to ~20%) when we filter predictions by the distance between target sites using this program. Interestingly, two adjacent canonical target sites are more likely to be present in bona fide target transcripts than pairs of target sites at slightly longer distances. The software is written in Perl and runs on 64-bit Unix computers (Linux and MacOS X). Users with no computing experience can also run the program in a dedicated web-server by uploading custom data, or browse pre-computed predictions. SeedVicious and its associated web-server and database (SeedBank) are distributed under the GPL/GNU license.

Comparative study of joint bioinformatics analysis of underlying potential of 'neurimmiR', miR-212-3P/miR-132-3P, being involved in epilepsy and its emerging role in human cancer

Considering the critical roles of miR-132/212 participated in central nervous system, many researches started to explored the contributions of miR-132/212 to epilepsy and achieve something worthwhile. Further illuminates all the genes targeted by miR-132/212 may be a valuable means for us to completely understand the working mechanism playing in epilepsy, by which it can influence diverse biological process. This study attempts to establish macrocontrol regulation system and knowledge that miR-212-3p/132-3p effected the epilepsy, for this literature search, miRbase, Vienna RNAfold webserver, Human miRNA tissue atlas, DIANA-TarBase, miRtarbase, STRING, TargetScanhuman, Cytoscape plugin ClueGO + Cluepedia+STRING, DAVID Bioinformatics Resources, Starbase, GeneCards suite and GEO database are comprehensive employed, miR-132-3p/212-3p and its target gene were found have highly expressed in brain and lots of molecular function and metabolic pathways associated with epilepsy may be intervened by it. Meanwhile, the emerging role of miR-132-3p/212-3p being involved in human cancer also been analyzed by several webtools for TCGA data integrative analysis, most remarkably and well worth exploring in our research conclusion that showed miR-132-3p/212-3p may be the core molecular underlying tumor-induced epileptogenesis.

Egr2-dependent microRNA-138 is dispensable for peripheral nerve myelination

Recent studies have elucidated the crucial role for microRNAs in peripheral nerve myelination by ablating components of the microRNA synthesis machinery. Few studies have focused on the role of individual microRNAs. To fill this gap, we focused this study on miR-138, which was shown to be drastically reduced in Dicer1 and Dgcr8 knockout mice with hypomyelinating phenotypes and to potentially target the negative regulators of Schwann cell differentiation. Here, we show that of two miR-138 encoding loci, mir-138-1 is the predominant locus transcribed in Schwann cells. mir-138-1 is transcriptionally upregulated during myelination and downregulated upon nerve injury. EGR2 is required for mir-138-1 transcription during development, and both SOX10 and EGR2 bind to an active enhancer near the mir-138-1 locus. Based on expression analyses, we hypothesized that miR-138 facilitates the transition between undifferentiated Schwann cells and myelinating Schwann cells. However, in conditional knockouts, we could not detect significant changes in Schwann cell proliferation, cell cycle exit, or myelination. Overall, our results demonstrate that miR-138 is an Egr2-dependent microRNA but is dispensable for Schwann cell myelination.

Detection of Plant miRNAs Abundance in Human Breast Milk

Breast milk is a natural food and important component of infant nutrition. Apart from the alimentary substances, breast milk contains many important bioactive compounds, including endogenous microRNA molecules (miRNAs). These regulatory molecules were identified in various mammalian biological fluids and were shown to be mostly packed in exosomes. Recently, it was revealed that plant food-derived miRNAs are stably present in human blood and regulate the expression of specific human genes. Since then, the scientific community has focused its efforts on contradicting or confirming this discovery. With the same intention, qRT-PCR experiments were performed to evaluate the presence of five plant food-derived miRNAs (miR166a, miR156a, miR157a, miR172a and miR168a) in breast milk (whole milk and exosomes) from healthy volunteers. In whole milk samples, all examined miRNAs were identified, while only two of these miRNAs were confirmed to be present in exosomes. The plant miRNA concentration in the samples ranged from 4 to 700 fM. Complementary bioinformatics analysis suggests that the evaluated plant miRNAs may potentially influence several crucial biological pathways in the infant organism.

MiRNA and mRNA Profiling in Systemic Lupus Reveals a Novel Set of Cytokine - Related miRNAs and their Target Genes in Cases With and Without Renal Involvement

BACKGROUND/AIMS

MiRNAs transpire as promising elements in molecular medicine for the identification of new diagnostic, prognostic and targeting therapeutic biomarkers. This study consisted of four steps: First, to investigate one or a group of specific diagnostic miRNAs for Systemic Lupus Erythematosus (SLE) disease in patients with and without renal involvement, second, to identify cytokines genes' expression profiling, third, comparing the profiles with related amounts in the serum and finally, to study target-gene-mediated functional roles of miRNAs, which have been correlated to disease development and progression.

METHODS

In order to use in microarray assays total RNA and miRNAs were isolated from blood and serum samples that were obtained from 16 SLE patients (9 with renal involvement and 7 without renal involvement). Taking coexistence of factors such as hypocomplementemia, positive ANA and anti-DNA into account, obtained data were processed. For each differentially expressed miRNA, potential target genes were predicted by microRNAorg, TargetScan and PITA prediction tools. Obtained mRNA profiling data were interrogated for the target genes. MiRNA and mRNA microarray results were confirmed by QRT-PCR. Finally, the amounts of cytokines were measured by multiplex ELISA method.

RESULTS

The results of study showed that among differentially expressed miRNAs in SLE patients with renal involvement compared to those without renal involvement, hsa-miR-766-3p, may play pivotal roles in PI3K-AKT-mTOR pathway. In addition according to the obtained data it is suggested that blood-borne proinflammatory cytokines such as IL-4, IL-6 and TNF-α alongside with disease stage and severity may contribute to this differential expression of these miRNA which may be leading to insulin resistance. Finally, hsa-miR-621, which was differentially expressed in hypertensive SLE patients without renal involvement and a positive ANA test with its predicted target gene "Kallikrein-related peptidase 9" may play a role in the pathophysiology of hypertension in SLE.

CONCLUSIONS

We reported some human miRNAs which were differentially expressed in SLE patients according to disease activity and renal involvement. Larger studies are necessary to confirm our findings and detect further biomarkers.

miRnalyze: an interactive database linking tool to unlock intuitive microRNA regulation of cell signaling pathways

The various pathophysiological processes occurring in living systems are known to be orchestrated by delicate interplays and cross-talks between different genes and their regulators. Among the various regulators of genes, there is a class of small non-coding RNA molecules known as microRNAs. Although, the relative simplicity of miRNAs and their ability to modulate cellular processes make them attractive therapeutic candidates, their presence in large numbers make it challenging for experimental researchers to interpret the intricacies of the molecular processes they regulate. Most of the existing bioinformatic tools fail to address these challenges. Here, we present a new web resource 'miRnalyze' that has been specifically designed to directly identify the putative regulation of cell signaling pathways by miRNAs. The tool integrates miRNA-target predictions with signaling cascade members by utilizing TargetScanHuman 7.1 miRNA-target prediction tool and the KEGG pathway database, and thus provides researchers with in-depth insights into modulation of signal transduction pathways by miRNAs. miRnalyze is capable of identifying common miRNAs targeting more than one gene in the same signaling pathway-a feature that further increases the probability of modulating the pathway and downstream reactions when using miRNA modulators. Additionally, miRnalyze can sort miRNAs according to the seed-match types and TargetScan Context ++ score, thus providing a hierarchical list of most valuable miRNAs. Furthermore, in order to provide users with comprehensive information regarding miRNAs, genes and pathways, miRnalyze also links to expression data of miRNAs (miRmine) and genes (TiGER) and proteome abundance (PaxDb) data. To validate the capability of the tool, we have documented the correlation of miRnalyze's prediction with experimental confirmation studies.

Database URL

http://www.mirnalyze.in.

Expression and Function of hsa-miR-6165 in Human Cell Lines and During the NT2 Cell Neural Differentiation Process

MicroRNAs are small non-coding RNAs that posttranscriptionally regulate mRNA expression. hsa-miR-6165 which was previously discovered in our group is located in the forth intron of p75NTR gene and its function is still under investigation. As P75NTR has diverse cellular functions, some of the complexity of its function could be attributed to the internally located microRNA. Our analysis revealed that treatment of HCT116 cells with 5-azacytidine promoted differential expression of hsa-miR-6165 from its host gene which is consistent with the bioinformatic prediction of an independent promoter for hsa-miR-6165. In addition, hsa-miR-6165 promoter is capable of driving GFP reporter gene in HeLa cells. The putative target gene expression level which was detected using RT-qPCR is inversely proportional to the expression level of hsa-miR-6165 during NT2 cell neural differentiation. Furthermore, hsa-miR-6165 overexpression resulted in significant downregulation of ABLIM-1, PVRL1, and PDK1 target genes, while it attenuates NT2 neural differentiation. Hsa-miR-6165 overexpression in SW480 cells also resulted in significant downregulation of PKD1, DAGLA, and PLXNA2 putative target genes, while it increases the sub-G1 cell population of SW480 and HEK293T cells as detected by flow cytometry. Overall, in this study, we report an independent promoter for hsa-miR-6165 which is active in HeLa cells. Additionally, hsa-miR-6165 targets ABLIM-1, PVRL1, PKD1, PLXNA2, and PDK1 genes, and unlike in HEK293T and SW480 cells, hsa-miR-6165 overexpression does not affect HeLa cells while its downregulation reduces sub-G1 cell population. Our results validate that hsa-miR-6165 affects the cell cycle progression and could increase apoptosis in human cell lines.

DNA Methylation of miR-7 is a Mechanism Involved in Platinum Response through MAFG Overexpression in Cancer Cells

One of the major limitations associated with platinum use is the resistance that almost invariably develops in different tumor types. In the current study, we sought to identify epigenetically regulated microRNAs as novel biomarkers of platinum resistance in lung and ovarian cancers, the ones with highest ratios of associated chemo-resistance.

Methods: We combined transcriptomic data from microRNA and mRNA under the influence of an epigenetic reactivation treatment in a panel of four paired cisplatin -sensitive and -resistant cell lines, followed by real-time expression and epigenetic validations for accurate candidate selection in 19 human cancer cell lines. To identify specific candidate genes under miRNA regulation, we assembled “in silico” miRNAs and mRNAs sequences by using ten different algorithms followed by qRT-PCR validation. Functional assays of site-directed mutagenesis and luciferase activity, miRNAs precursor overexpression, silencing by antago-miR and cell viability were performed to confirm their specificity in gene regulation. Results were further explored in 187 primary samples obtained from ovarian tumors and controls.

Results: We identified 4 candidates, miR-7, miR-132, miR-335 and miR-148a, which deregulation seems to be a common event in the development of resistance to cisplatin in both tumor types. miR-7 presented specific methylation in resistant cell lines, and was associated with poorer prognosis in ovarian cancer patients. Our experimental results strongly support the direct regulation of MAFG through miR-7 and their involvement in the development of CDDP resistance in human tumor cells.

Conclusion: The basal methylation status of miR-7 before treatment may be a potential clinical epigenetic biomarker, predictor of the chemotherapy outcome to CDDP in ovarian cancer patients. To the best of our knowledge, this is the first report linking the regulation of MAFG by miRNA-7 and its role in chemotherapy response to CDDP. Furthermore, this data highlights the possible role of MAFG as a novel therapeutic target for platinum resistant tumors.

Preliminary profiling of microRNA in the normal and regenerating liver of Chiloscyllium plagiosum

Liver is a vital organ present in animals for detoxification, protein synthesis, digestion and other functions and its powerful regenerative capacity is well known. C. plagiosum is an abundant fish that is representative of the cartilaginous class in the southeast coastal region of China and its liver accounts for >70% of the fish's visceral weight and contains many bioactive substances. MicroRNAs (microRNAs) play important roles in a wide range of biological processes in eukaryotes, including cell proliferation, differentiation, apoptosis. However, microRNAs in response to liver regeneration has not been well studied. This study aimed to identify the microRNAs that participate in liver regeneration and other liver-related diseases and to improve our understanding of the mechanisms of liver regeneration in sharks. To this end, normal and regenerating liver tissues from C. plagiosum were harvested 0, 3, 6, 12 and 24h after partial hepatectomy (pH) and were sequenced using the Illumina/Solexa platform. In total, 309 known microRNAs and 590 novel microRNAs were identified in C. plagiosum. There were many microRNAs differentially expressed in the normal and regenerating livers between time points. Using target prediction and GO analysis, most of the differentially expressed microRNAs were assigned to functional categories that may be involved in regulating liver regeneration, such as cell proliferation, differentiation and apoptosis. The microRNA expression profile of liver regeneration will pave the way for the development of effective strategies to fight against liver disease and other related disease.

Comprehensive bioinformatics analysis of the characterization and determination underlying mechanisms of over-expression and co-expression of genes residing on 20q in colorectal cancer

The Long arm of chromosome 20 (20q) is closely related to the development of colorectal cancer, so identifying the expression profile of genes on 20q through a comprehensive overview is indispensable. In this article, preliminar experimental data, several available databases and bioinformatics tools such as the Cancer Genome Atlas, the Encyclopedia of DNA Elements, the JASPAR database and starBase were combined to analyze the correlation between genes and chromosomal aberrations, microRNA and transcription factors, as well as to explore the expression feature and potential regulative mechanism. The results showed that the most frequently unregulated genes in colorectal cancer arelocated on chromosome 20q, present a significant CNA–mRNA correlation.Furthermore, the genes with mRNA overexpression showed co-expression features and tended to be clustered within the same genomic neighborhoods. Then, several genes were selected to carry out further analysis and demonstrated that shared transcription factors, a conserved bidirectional promoter, and competition for a limited pool of microRNAin the 3’UTR of mRNA may be the underlying mechanisms behind the co-expression of physically adjacent genes.Finally, the databases, Lentivirus shRNA, and qPCR were used to find that these adjacent genes with co-expression cooperatively participated in the same biological pathways associated with the pathogenesis and development of colorectal cancer.

The Role of Epigenetic Regulation in Epstein-Barr Virus-Associated Gastric Cancer

The Epstein–Barr virus (EBV) is detected in about 10% of gastric carcinoma cases throughout the world. In EBV-associated gastric carcinoma (EBVaGC), all tumor cells harbor the clonal EBV genome. The expression of latent EBV genes is strictly regulated through the methylation of EBV DNA. The methylation of viral DNA regulates the type of EBV latency, and methylation of the tumor suppressor genes is a key abnormality in EBVaGC. The methylation frequencies of several tumor suppressor genes and cell adhesion molecules are significantly higher in EBVaGC than in control cases. EBV-derived microRNAs repress translation from viral and host mRNAs. EBV regulates the expression of non-coding RNA in gastric carcinoma. With regard to the clinical application of demethylating agents against EBVaGC, we investigated the effects of decitabine against the EBVaGC cell lines. Decitabine inhibited the cell growth of EBVaGC cells. The promoter regions of p73 and Runt-related transcription factor 3(RUNX3) were demethylated, and their expression was upregulated by the treatment. We review the role of epigenetic regulation in the development and maintenance of EBVaGC and discuss the therapeutic application of DNA demethylating agents for EBVaGC.

The microRNA miR-31 inhibits CD8+ T cell function in chronic viral infection

During infection, antigen-specific T cells undergo tightly regulated developmental transitions controlled by transcriptional and post-transcriptional regulation of gene expression. We found that the microRNA miR-31 was strongly induced by activation of the T cell antigen receptor (TCR) in a pathway involving calcium and activation of the transcription factor NFAT. During chronic infection with lymphocytic choriomeningitis virus (LCMV) clone 13, miR-31-deficent mice recovered from clinical disease, while wild-type mice continued to show signs of disease. This disease phenotype was explained by the presence of larger numbers of cytokine-secreting LCMV-specific CD8+ T cells in miR-31-deficent mice than in wild-type mice. Mechanistically, miR-31 increased the sensitivity of T cells to type I interferons, which interfered with effector T cell function and increased the expression of several proteins related to T cell dysfunction during chronic infection. These studies identify miR-31 as an important regulator of T cell exhaustion in chronic infection.