miRTar: an integrated system for identifying miRNA-target interactions in human

Association of genetic variations of 3'-UTR in clopidogrel pharmacokinetic-relevant genes with clopidogrel response in Han Chinese patients with coronary artery disease

Dual antiplatelet therapy with aspirin and clopidogrel has reduced ischemic vascular events significantly. Genetic influence, especially those in clopidogrel pharmacokinetic-relevant genes partially accounts for interindividual pharmacodynamic variability of clopidogrel. However, most studies have concentrated on the genetic variations in introns, exons, or promoters of the candidate genes, and the association between genetic variations in 3'-UTR in clopidogrel pharmacokinetic-relevant genes and clopidogrel response is unknown. In our study, ten different algorithms were applied to pick potential miRNAs targeting the clopidogrel pharmacokinetic-relevant genes. Furthermore, the correlation between miRNA expression profiles and mRNA expression of corresponding clopidogrel pharmacokinetic-relevant genes was analyzed. Through comprehensive analysis, including bioinformatics prediction and correlation analysis of miRNA and mRNA expression profiles, miR-218-5p and miR-506-5p were supposed to regulate the expression of PON1 via binding with its 3'-UTR. Moreover, PON1 rs854551 and rs854552 were located in miRNA recognizing sequences and may serve as potential miRSNPs possibly affecting PON1 expression. The rs854552 polymorphism was genotyped and platelet reactivity index (PRI) indicative of clopidogrel response was measured in 341 Chinese coronary artery disease (CAD) patients 24 h after administration of 300 mg clopidogrel. Our results showed that PON1 rs854552 had a significant influence on PRI in CAD patients, especially in patients with CYP2C19 extensive metabolic phenotype. In conclusion, PON1 rs854552 polymorphisms may affect clopidogrel response. Bioinformatics prediction followed by functional validation could aid in decoding the contribution of unexplained variations in the 3'-UTR in drug-metabolizing enzymes on clopidogrel response.

Advanced Analysis and Validation of a microRNA Signature for Fanconi Anemia

Some years ago, we reported the generation of a Fanconi anemia (FA) microRNA signature. This study aims to develop an analytical strategy to select a smaller and more reliable set of molecules that could be tested for potential benefits for the FA phenotype, elucidate its biochemical and molecular mechanisms, address experimental activity, and evaluate its possible impact on FA therapy. In silico analyses of the data obtained in the original study were thoroughly processed and anenrichment analysis was employed to identify the classes of genes that are over-represented in the FA-miRNA population under study. Primary bone marrow mononuclear cells (MNCs) from sixFA patients and sixhealthy donors as control samples were employed in the study. RNAs containing the small RNA fractions were reverse-transcribed and real-time PCR was performed in triplicate using the specific primers. Experiments were performed in triplicate.The in-silico analysis reported six miRNAs as likely contributors to the complex pathological spectrum of FA. Among these, three miRNAs were validated by real-time PCR. Primary bone marrow mononuclear cells (MNCs) reported a significant reduction in the expression level of miRNA-1246 and miRNA-206 in the FA samples in comparison to controls.This study highlights several biochemical pathways as culprits in the phenotypic manifestations and the pathophysiological mechanisms acting in FA. A relatively low number of miRNAs appear involved in all these different phenotypes, demonstrating the extreme plasticity of the gene expression modulation. This study further highlights miR-206 as a pivotal player in regulatory functions and signaling in the bone marrow mesenchymal stem cell (BMSC) process in FA. Due to this evidence, the activity of miR-206 in FA deserves specific experimental scrutiny. The results, here presented, might be relevant in the management of FA.

Integrative pathway analysis with gene expression, miRNA, methylation and copy number variation for breast cancer subtypes

Developments in biotechnologies enable multi-platform data collection for functional genomic units apart from the gene. Profiling of non-coding microRNAs (miRNAs) is a valuable tool for understanding the molecular profile of the cell, both for canonical functions and malignant behavior due to complex diseases. We propose a graphical mixed-effects statistical model incorporating miRNA-gene target relationships. We implement an integrative pathway analysis that leverages measurements of miRNA activity for joint analysis with multimodal observations of gene activity including gene expression, methylation, and copy number variation. We apply our analysis to a breast cancer dataset, and consider differential activity in signaling pathways across breast tumor subtypes. We offer discussion of specific signaling pathways and the effect of miRNA integration, as well as publish an interactive data visualization to give public access to the results of our analysis.

Targeting MALAT1 Augments Sensitivity to PARP Inhibition by Impairing Homologous Recombination in Prostate Cancer

PARP inhibitors (PARPi) have emerged as a promising targeted therapeutic intervention for metastatic castrate-resistant prostate cancer (mCRPC). However, the clinical utility of PARPi is limited to a subset of patients who harbor aberrations in the genes associated with the homologous recombination (HR) pathway. Here, we report that targeting metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), an oncogenic long noncoding RNA (lncRNA), contrives a BRCAness-like phenotype, and augments sensitivity to PARPi. Mechanistically, we show that MALAT1 silencing reprograms the homologous recombination (HR) transcriptome and makes prostate cancer cells more vulnerable to PARPi. Particularly, coinhibition of MALAT1 and PARP1 exhibits a decline in clonogenic survival, delays resolution of γH2AX foci, and reduces tumor burden in mice xenograft model. Moreover, we show that miR-421, a tumor suppressor miRNA, negatively regulates the expression of HR genes, while in aggressive prostate cancer cases, miR-421 is sequestered by MALAT1, leading to increased expression of HR genes. Conclusively, our findings suggest that MALAT1 ablation confers sensitivity to PARPi, thus highlighting an alternative therapeutic strategy for patients with castration-resistant prostate cancer (CRPC), irrespective of the alterations in HR genes.

SIGNIFICANCE

PARPi are clinically approved for patients with metastatic CRPC carrying mutations in HR genes, but are ineffective for HR-proficient prostate cancer. Herein, we show that oncogenic lncRNA, MALAT1 is frequently overexpressed in advanced stage prostate cancer and plays a crucial role in maintaining genomic integrity. Importantly, we propose a novel therapeutic strategy that emphasizes MALAT1 inhibition, leading to HR dysfunction in both HR-deficient and -proficient prostate cancer, consequently augmenting their susceptibility to PARPi.

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.

Cholecalciferol Supplementation Induced Up-Regulation of SARAF Gene and Down-Regulated miR-155-5p Expression in Slovenian Patients with Multiple Sclerosis

Multiple sclerosis is a common immune-mediated inflammatory and demyelinating disease. Lower cholecalciferol levels are an established environmental risk factor in multiple sclerosis. Although cholecalciferol supplementation in multiple sclerosis is widely accepted, optimal serum levels are still debated. Moreover, how cholecalciferol affects pathogenic disease mechanisms is still unclear. In the present study, we enrolled 65 relapsing-remitting multiple sclerosis patients who were double-blindly divided into two groups with low and high cholecalciferol supplementation, respectively. In addition to clinical and environmental parameters, we obtained peripheral blood mononuclear cells to analyze DNA, RNA, and miRNA molecules. Importantly, we investigated miRNA-155-5p, a previously published pro-inflammatory miRNA in multiple sclerosis known to be correlated to cholecalciferol levels. Our results show a decrease in miR-155-5p expression after cholecalciferol supplementation in both dosage groups, consistent with previous observations. Subsequent genotyping, gene expression, and eQTL analyses reveal correlations between miR-155-5p and the SARAF gene, which plays a role in the regulation of calcium release-activated channels. As such, the present study is the first to explore and suggest that the SARAF miR-155-5p axis hypothesis might be another mechanism by which cholecalciferol supplementation might decrease miR-155 expression. This association highlights the importance of cholecalciferol supplementation in multiple sclerosis and encourages further investigation and functional cell studies.

The deleted in oral cancer (DOC1 aka CDK2AP1) tumor suppressor gene is downregulated in oral squamous cell carcinoma by multiple microRNAs

Cyclin-dependent kinase 2-associated protein 1 (CDK2AP1; also known as deleted in oral cancer or DOC1) is a tumor suppressor gene known to play functional roles in both cell cycle regulation and in the epigenetic control of embryonic stem cell differentiation, the latter as a core subunit of the nucleosome remodeling and histone deacetylation (NuRD) complex. In the vast majority of oral squamous cell carcinomas (OSCC), expression of the CDK2AP1 protein is reduced or lost. Notwithstanding the latter (and the DOC1 acronym), mutations or deletions in its coding sequence are extremely rare. Accordingly, CDK2AP1 protein-deficient oral cancer cell lines express as much CDK2AP1 mRNA as proficient cell lines. Here, by combining in silico and in vitro approaches, and by taking advantage of patient-derived data and tumor material in the analysis of loss of CDK2AP1 expression, we identified a set of microRNAs, namely miR-21-5p, miR-23b-3p, miR-26b-5p, miR-93-5p, and miR-155-5p, which inhibit its translation in both cell lines and patient-derived OSCCs. Of note, no synergistic effects were observed of the different miRs on the CDK2AP1-3-UTR common target. We also developed a novel approach to the combined ISH/IF tissue microarray analysis to study the expression patterns of miRs and their target genes in the context of tumor architecture. Last, we show that CDK2AP1 loss, as the result of miRNA expression, correlates with overall survival, thus highlighting the clinical relevance of these processes for carcinomas of the oral cavity.

MicroRNA Signatures in Cartilage Ageing and Osteoarthritis

Osteoarthritis is the most common degenerative joint disorder. MicroRNAs are gene expression regulators that act post-transcriptionally to control tissue homeostasis. Microarray analysis was undertaken in osteoarthritic intact, lesioned and young intact cartilage. Principal component analysis showed that young intact cartilage samples were clustered together; osteoarthritic samples had a wider distribution; and osteoarthritic intact samples were separated into two subgroups, osteoarthritic-Intact-1 and osteoarthritic-Intact-2. We identified 318 differentially expressed microRNAs between young intact and osteoarthritic lesioned cartilage, 477 between young intact and osteoarthritic-Intact-1 cartilage and 332 between young intact and osteoarthritic-Intact-2 cartilage samples. For a selected list of differentially expressed microRNAs, results were verified in additional cartilage samples using qPCR. Of the validated DE microRNAs, four-miR-107, miR-143-3p, miR-361-5p and miR-379-5p-were selected for further experiments in human primary chondrocytes treated with IL-1β. Expression of these microRNAs decreased in human primary chondrocytes treated with IL-1β. For miR-107 and miR-143-3p, gain- and loss-of-function approaches were undertaken and associated target genes and molecular pathways were investigated using qPCR and mass spectrometry proteomics. Analyses showed that WNT4 and IHH, predicted targets of miR-107, had increased expression in osteoarthritic cartilage compared to young intact cartilage and in primary chondrocytes treated with miR-107 inhibitor, and decreased expression in primary chondrocytes treated with miR-107 mimic, suggesting a role of miR-107 in chondrocyte survival and proliferation. In addition, we identified an association between miR-143-3p and EIF2 signalling and cell survival. Our work supports the role of miR-107 and miR-143-3p in important chondrocyte mechanisms regulating proliferation, hypertrophy and protein translation.

MITF Downregulation Induces Death in Human Mast Cell Leukemia Cells and Impairs IgE-Dependent Degranulation

Activating mutations in KIT (CD117) have been associated with several diseases, including gastrointestinal stromal tumors and mastocytosis. Rapidly progressing pathologies or drug resistance highlight the need for alternative treatment strategies. Previously, we reported that the adaptor molecule SH3 binding protein 2 (SH3BP2 or 3BP2) regulates KIT expression at the transcriptional level and microphthalmia-associated transcription factor (MITF) expression at the post-transcriptional level in human mast cells and gastrointestinal stromal tumor (GIST) cell lines. Lately, we have found that the SH3BP2 pathway regulates MITF through miR-1246 and miR-5100 in GIST. In this study, miR-1246 and miR-5100 were validated by qPCR in the SH3BP2-silenced human mast cell leukemia cell line (HMC-1). MiRNA overexpression reduces MITF and MITF-dependent target expression in HMC-1. The same pattern was observed after MITF silencing. In addition, MITF inhibitor ML329 treatment reduces MITF expression and affects the viability and cell cycle progression in HMC-1. We also examine whether MITF downregulation affected IgE-dependent mast cell degranulation. MiRNA overexpression, MITF silencing, and ML329 treatment reduced IgE-dependent degranulation in LAD2- and CD34⁺-derived mast cells. These findings suggest MITF may be a potential therapeutic target for allergic reactions and deregulated KIT mast-cell-mediated disorders.

miR-101a-3p Impairs Synaptic Plasticity and Contributes to Synucleinopathy

BACKGROUND

Synucleinopathies are disorders characterized by the abnormal accumulation of α-synuclein (aSyn). Synaptic compromise is observed in synucleinopathies parallel to aSyn aggregation and is accompanied by transcript deregulation.

OBJECTIVE

We sought to identify microRNAs associated with synaptic processes that may contribute to synaptic dysfunction and degeneration in synucleinopathies.

METHODS

We performed small RNA-sequencing of midbrain from 6-month-old transgenic mice expressing A30P mutant aSyn, followed by comparative expression analysis. We then used real-time quantitative polymerase chain reaction (qPCR) for validation. Functional analysis was performed in primary neurons by biochemical assays and imaging.

RESULTS

We found several deregulated biological processes linked to the synapse. miR-101a-3p was validated as a synaptic miRNA upregulated in aSyn Tg mice and in the cortex of dementia with Lewy bodies patients. Mice and primary cultured neurons overexpressing miR-101a-3p showed downregulation of postsynaptic proteins GABA Ab2 and SAPAP3 and altered dendritic morphology resembling synaptic plasticity impairments and/or synaptic damage. Interestingly, primary cultured neuron exposure to recombinant wild-type aSyn species efficiently increased miR-101a-3p levels. Finally, a dynamic role of miR-101a-3p in synapse plasticity was shown by identifying downregulation of miR-101a-3p in a condition of enhanced synaptic plasticity modelled in Wt animals housed in enriched environment.

CONCLUSION

To conclude, we correlated pathologic aSyn with high levels of miR-101a-3p and a novel dynamic role of the miRNA in synaptic plasticity.

MicroRNA-Target Identification: A Combinatorial In Silico Approach

Contemporary computational target prediction tools with their distinctive properties and stringency have been playing a vital role in pursuing putative targets for a solitary miRNA or a subcategory of miRNAs. These tools utilize a defined set of probabilistic algorithms, machine learning techniques, and information of experimentally validated miRNA targets to provide the best selection. However, there are numerous false-positive predictions, and a method to choose an archetypal approach and put the data provided by the prediction tools into context is still lacking. Moreover, sensitivity, specificity, and overall efficiency of a single tool have not yet been achieved. Therefore, a systematic combination of selective online tools combining elementary and advanced factors of miRNA target identification might reinforce the current target prediction regime. The focus of this study was to build a comprehensive workflow by combining six available online tools to facilitate the current understanding of miRNA-target prediction.

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.

SH3BP2 Silencing Increases miRNAs Targeting ETV1 and Microphthalmia-Associated Transcription Factor, Decreasing the Proliferation of Gastrointestinal Stromal Tumors

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumors of the gastrointestinal tract. Gain of function in receptor tyrosine kinases type III, KIT, or PDGFRA drives the majority of GIST. Previously, our group reported that silencing of the adaptor molecule SH3 Binding Protein 2 (SH3BP2) downregulated KIT and PDGFRA and microphthalmia-associated transcription factor (MITF) levels and reduced tumor growth. This study shows that SH3BP2 silencing also decreases levels of ETV1, a required factor for GIST growth. To dissect the SH3BP2 pathway in GIST cells, we performed a miRNA array in SH3BP2-silenced GIST cell lines. Among the most up-regulated miRNAs, we found miR-1246 and miR-5100 to be predicted to target MITF and ETV1. Overexpression of these miRNAs led to a decrease in MITF and ETV1 levels. In this context, cell viability and cell cycle progression were affected, and a reduction in BCL2 and CDK2 was observed. Interestingly, overexpression of MITF enhanced cell proliferation and significantly rescued the viability of miRNA-transduced cells. Altogether, the KIT-SH3BP2-MITF/ETV1 pathway deserves to be considered in GIST cell survival and proliferation.

miRNA therapeutics in precision oncology: a natural premium to nurture

The dynamic spectrum of microRNA (miRNA) has grown significantly over the years with its identification and exploration in cancer therapeutics and is currently identified as an important resource for innovative strategies due to its functional behavior for gene regulation and modulation of complex biological networks. The progression of cancer is the consequence of uncontrolled, nonsynchronous procedural faults in the biological system. Diversified and variable cellular response of cancerous cells has always raised challenges in effective cancer therapy. miRNAs, a class of non-coding RNAs (ncRNAs), are the natural genetic gift, responsible to preserve the homeostasis of cell to nurture. The unprecedented significance of endogenous miRNAs has exhibited promising therapeutic potential in cancer therapeutics. Currently, miRNA mimic miR-34, and an antimiR aimed against miR-122 has entered the clinical trials for cancer treatments. This review, highlights the recent breakthroughs, challenges, clinical trials, and advanced delivery vehicles in the administration of miRNA therapies for precision oncology.

The role of miR-370 and miR-138 in the regulation of BMP2 suppressor gene expression in colorectal cancer: preliminary studies

PURPOSE

Colorectal cancer (CRC) is the fourth-most common cancer worldwide and the second most common cancer cause of death in the world. The components of the TGFβ-signalling pathway, which are often affected by miRNAs, are involved in the regulation of apoptosis and cell cycle. Therefore, in the current study, the expression of BMP2 gene in CRC tissues at different clinical stages compared to the non-tumour tissues has been assessed. Moreover, the plasma BMP2 protein concentration in the same group of CRC patients has been validated. Due to the constant necessity to conduct further research of the correlation between specific miRNAs and mRNAs in CRC, in silico analysis has been performed to select miRNAs that regulate BMP2 mRNA.

METHODS

The cDNA samples from tumor and non-tumor tissue were used in a qPCR reaction to determine the mRNA expression of the BMP2 gene and the expression of selected miRNAs. The concentration of BMP2 protein in plasma samples was also measured.

RESULTS

It was indicated that BMP2 was downregulated in CRC tissue. Moreover, miR-370 and miR-138 expression showed an upward trend. Decreased BMP2 with accompanied increasing miR-370 and miR-138 expression was relevant to the malignant clinicopathological features of CRC and consequently poor patient prognosis.

CONCLUSION

Our data suggest that miR-370 with its clear expression in plasma samples may be a potential diagnostic marker to determine the severity of the disease in patients at a later stage of colorectal cancer.

Circr, a Computational Tool to Identify miRNA:circRNA Associations

Circular RNAs (circRNAs) are known to act as important regulators of the microRNA (miRNA) activity. Yet, computational resources to identify miRNA:circRNA interactions are mostly limited to already annotated circRNAs or affected by high rates of false positive predictions. To overcome these limitations, we developed Circr, a computational tool for the prediction of associations between circRNAs and miRNAs. Circr combines three publicly available algorithms for de novo prediction of miRNA binding sites on target sequences (miRanda, RNAhybrid, and TargetScan) and annotates each identified miRNA:target pairs with experimentally validated miRNA:RNA interactions and binding sites for Argonaute proteins derived from either ChIPseq or CLIPseq data. The combination of multiple tools for the identification of a single miRNA recognition site with experimental data allows to efficiently prioritize candidate miRNA:circRNA interactions for functional studies in different organisms. Circr can use its internal annotation database or custom annotation tables to enhance the identification of novel and not previously annotated miRNA:circRNA sites in virtually any species. Circr is written in Python 3.6 and is released under the GNU GPL3.0 License at https://github.com/bicciatolab/Circr.

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.

miR+Pathway: the integration and visualization of miRNA and KEGG pathways

miRNAs represent a type of noncoding small molecule RNA. Many studies have shown that miRNAs are widely involved in the regulation of various pathways. The key to fully understanding the regulatory function of miRNAs is the determination of the pathways in which the miRNAs participate. However, the major pathway databases such as KEGG only include information regarding protein-coding genes. Here, we redesigned a pathway database (called miR+Pathway) by integrating and visualizing the 8882 human experimentally validated miRNA-target interactions (MTIs) and 150 KEGG pathways. This database is freely accessible at http://www.insect-genome.com/miR-pathway. Researchers can intuitively determine the pathways and the genes in the pathways that are regulated by miRNAs as well as the miRNAs that target the pathways. To determine the pathways in which targets of a certain miRNA or multiple miRNAs are enriched, we performed a KEGG analysis miRNAs by using the hypergeometric test. In addition, miR+Pathway provides information regarding MTIs, PubMed IDs and the experimental verification method. Users can retrieve pathways regulated by an miRNA or a gene by inputting its names.

High-throughput analysis of the interactions between viral proteins and host cell RNAs

RNA-protein interactions of a virus play a major role in the replication of RNA viruses. The replication and transcription of these viruses take place in the cytoplasm of the host cell; hence, there is a probability for the host RNA-viral protein and viral RNA-host protein interactions. The current study applies a high-throughput computational approach, including feature extraction and machine learning methods, to predict the affinity of protein sequences of ten viruses to three categories of RNA sequences. These categories include RNAs involved in the protein-RNA complexes stored in the RCSB database, the human miRNAs deposited at the mirBase database, and the lncRNA deposited in the LNCipedia database. The results show that evolution not only tries to conserve key viral proteins involved in the replication and transcription but also prunes their interaction capability. These proteins with specific interactions do not perturb the host cell through undesired interactions. On the other hand, the hypermutation rate of NSP3 is related to its affinity to host cell RNAs. The Gene Ontology (GO) analysis of the miRNA with affiliation to NSP3 suggests that these miRNAs show strongly significantly enriched GO terms related to the known symptoms of COVID-19. Docking and MD simulation study of the obtained miRNA through high-throughput analysis suggest a non-coding RNA (an RNA antitoxin, ToxI) as a natural aptamer drug candidate for NSP5 inhibition. Finally, a significant interplay of the host RNA-viral protein in the host cell can disrupt the host cell's system by influencing the RNA-dependent processes of the host cells, such as a differential expression in RNA. Furthermore, our results are useful to identify the side effects of mRNA-based vaccines, many of which are caused by the off-label interactions with the human lncRNAs.

ANMDA: anti-noise based computational model for predicting potential miRNA-disease associations

Background

A growing proportion of research has proved that microRNAs (miRNAs) can regulate the function of target genes and have close relations with various diseases. Developing computational methods to exploit more potential miRNA-disease associations can provide clues for further functional research.

Results

Inspired by the work of predecessors, we discover that the noise hiding in the data can affect the prediction performance and then propose an anti-noise algorithm (ANMDA) to predict potential miRNA-disease associations. Firstly, we calculate the similarity in miRNAs and diseases to construct features and obtain positive samples according to the Human MicroRNA Disease Database version 2.0 (HMDD v2.0). Then, we apply k-means on the undetected miRNA-disease associations and sample the negative examples equally from the k-cluster. Further, we construct several data subsets through sampling with replacement to feed on the light gradient boosting machine (LightGBM) method. Finally, the voting method is applied to predict potential miRNA-disease relationships. As a result, ANMDA can achieve an area under the receiver operating characteristic curve (AUROC) of 0.9373 ± 0.0005 in five-fold cross-validation, which is superior to several published methods. In addition, we analyze the predicted miRNA-disease associations with high probability and compare them with the data in HMDD v3.0 in the case study. The results show ANMDA is a novel and practical algorithm that can be used to infer potential miRNA-disease associations.

Conclusion

The results indicate the noise hiding in the data has an obvious impact on predicting potential miRNA-disease associations. We believe ANMDA can achieve better results from this task with more methods used in dealing with the data noise.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04266-6.

Identification of 3'-UTR single nucleotide variants and prediction of select protein imbalance in mesial temporal lobe epilepsy patients

The genetic influence in epilepsy, characterized by unprovoked and recurrent seizures, is through variants in genes critical to brain development and function. We have carried out variant calling in Mesial Temporal Lobe Epilepsy (MTLE) patients by mapping the RNA-Seq data available at SRA, NCBI, USA onto human genome assembly hg-19. We have identified 1,75,641 SNVs in patient samples. These SNVs are distributed over 14700 genes of which 655 are already known to be associated with epilepsy. Large number of variants occur in the 3'-UTR, which is one of the regions involved in the regulation of protein translation through binding of miRNAs and RNA-binding proteins (RBP). We have focused on studying the structure-function relationship of the 3'-UTR SNVs that are common to at-least 10 of the 35 patient samples. For the first time we find SNVs exclusively in the 3'-UTR of FGF12, FAR1, NAPB, SLC1A3, SLC12A6, GRIN2A, CACNB4 and FBXO28 genes. Structural modelling reveals that the variant 3'-UTR segments possess altered secondary and tertiary structures which could affect mRNA stability and binding of RBPs to form proper ribonucleoprotein (RNP) complexes. Secondly, these SNVs have either created or destroyed miRNA-binding sites, and molecular modeling reveals that, where binding sites are created, the additional miRNAs bind strongly to 3'-UTR of only variant mRNAs. These two factors affect protein production thereby creating an imbalance in the amounts of select proteins in the cell. We suggest that in the absence of missense and nonsense variants, protein-activity imbalances associated with MTLE patients can be caused through 3'-UTR variants in relevant genes by the mechanisms mentioned above. 3'-UTR SNV has already been identified as causative variant in the neurological disorder, Tourette syndrome. Inhibition of these miRNA-mRNA bindings could be a novel way of treating drug-resistant MTLE patients. We also suggest that joint occurrence of these SNVs could serve as markers for MTLE. We find, in the present study, SNV-mediated destruction of miRNA binding site in the 3'-UTR of the gene encoding glutamate receptor subunit, and, interestingly, overexpression of one of this receptor subunit is also associated with Febrile Seizures.

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 .

A combinatorial in silico approach for microRNA-target identification: Order out of chaos

Contemporary computational microRNA(miRNA)-target prediction tools have been playing a vital role in pursuing putative targets for a solitary miRNA or a group of miRNAs. These tools utilise a set of probabilistic algorithms, machine learning techniques and analyse experimentally validated miRNA targets to identify the potential miRNA-target pairs. Unfortunately, current tools generate a huge number of false-positive predictions. A standardized approach with a single tool or a combination of tools is still lacking. Moreover, sensitivity, specificity and overall efficiency of any single tool are yet to be satisfactory. Therefore, a systematic combination of selective online tools combining the factors regarding miRNA-target identification would be valuable as an miRNA-target prediction scheme. The focus of this study was to develop a theoretical framework by combining six available online tools to facilitate the current understanding of miRNA-target identification.

MicroRNAs in ascending thoracic aortic aneurysms

Thoracic Aortic Aneurysm (TAA) is characterized by the dilation of the aorta and is fatal if not diagnosed and treated appropriately. The underlying genetic mechanisms have not been completely delineated, so better knowledge of the physiopathology of TAAs is needed to improve detection and therapy. MicroRNAs (miRNAs) regulate gene expression post-transcriptionally and are known to be involved in cardiovascular diseases (CVDs). The current study aimed to identify miRNAs that can be used as possible biomarkers for the early diagnosis of patients with ascending TAAs (ATAAs). MiRNA expression was profiled by NanoString nCounter technology using 12 samples including tissue and pre- and post-surgical plasma from ATAA patients. Four miRNAs were selected and further validated by real time polymerase chain reaction (RT-PCR) in 22 plasma samples from which three miRNAs (hsa-miR140-5p, hsa-miR-191-5p and hsa-miR-214-3p) showed significant expression level differences between the two types of plasma samples. Further analyses of the corresponding predicted target genes by these miRNAs, revealed two genes (Myotubularin-related protein 4 (MTMR4) and Phosphatase 1 catalytic subunit β (PPP1CB)) whose expression was inversely correlated with the expression of their respective miRNAs. Overall, in this pilot study, we identified three miRNAs that might serve as potential biomarkers and therapeutic targets in ATAA.

The microRNA-210-Stathmin1 Axis Decreases Cell Stiffness to Facilitate the Invasiveness of Colorectal Cancer Stem Cells

Simple Summary

Metastasis of tumor cells is the leading cause of death in cancer patients. Concurrent therapy with surgical removal of primary and metastatic lesions is the main approach for cancer therapy. Currently, therapeutic resistant properties of cancer stem cells (CSCs) are known to drive malignant cancer progression, including metastasis. Our study aimed to identify molecular tools dedicated to the detection and treatment of CSCs. We confirmed that microRNA-210-3p (miR-210) was upregulated in colorectal stem-like cancer cells, which targeted stathmin1 (STMN1), to decrease cell elasticity for increasing mobility. We envision that strategies for softening cellular elasticity will reduce the onset of CSC-orientated metastasis.

Abstract

Cell migration is critical for regional dissemination and distal metastasis of cancer cells, which remain the major causes of poor prognosis and death in patients with colorectal cancer (CRC). Although cytoskeletal dynamics and cellular deformability contribute to the migration of cancer cells and metastasis, the mechanisms governing the migratory ability of cancer stem cells (CSCs), a nongenetic source of tumor heterogeneity, are unclear. Here, we expanded colorectal CSCs (CRCSCs) as colonospheres and showed that CRCSCs exhibited higher cell motility in transwell migration assays and 3D invasion assays and greater deformability in particle tracking microrheology than did their parental CRC cells. Mechanistically, in CRCSCs, microRNA-210-3p (miR-210) targeted stathmin1 (STMN1), which is known for inducing microtubule destabilization, to decrease cell elasticity in order to facilitate cell motility without affecting the epithelial–mesenchymal transition (EMT) status. Clinically, the miR-210-STMN1 axis was activated in CRC patients with liver metastasis and correlated with a worse clinical outcome. This study elucidates a miRNA-oriented mechanism regulating the deformability of CRCSCs beyond the EMT process.

An integrated workflow for biomarker development using microRNAs in extracellular vesicles for cancer precision medicine

EV-miRNAs are microRNA (miRNA) molecules encapsulated in extracellular vesicles (EVs), which play crucial roles in tumor pathogenesis, progression, and metastasis. Recent studies about EV-miRNAs have gained novel insights into cancer biology and have demonstrated a great potential to develop novel liquid biopsy assays for various applications. Notably, compared to conventional liquid biomarkers, EV-miRNAs are more advantageous in representing host-cell molecular architecture and exhibiting higher stability and specificity. Despite various available techniques for EV-miRNA separation, concentration, profiling, and data analysis, a standardized approach for EV-miRNA biomarker development is yet lacking. In this review, we performed a substantial literature review and distilled an integrated workflow encompassing important steps for EV-miRNA biomarker development, including sample collection and EV isolation, EV-miRNA extraction and quantification, high-throughput data preprocessing, biomarker prioritization and model construction, functional analysis, as well as validation. With the rapid growth of "big data", we highlight the importance of efficient mining of high-throughput data for the discovery of EV-miRNA biomarkers and integrating multiple independent datasets for in silico and experimental validations to increase the robustness and reproducibility. Furthermore, as an efficient strategy in systems biology, network inference provides insights into the regulatory mechanisms and can be used to select functionally important EV-miRNAs to refine the biomarker candidates. Despite the encouraging development in the field, a number of challenges still hinder the clinical translation. We finally summarize several common challenges in various biomarker studies and discuss potential opportunities emerging in the related fields.

Cerina: systematic circRNA functional annotation based on integrative analysis of ceRNA interactions

Circular RNAs, a family of covalently circularized RNAs with tissue-specific expression, were recently demonstrated to play important roles in mammalian biology. Regardless of extensive research to predict, quantify, and annotate circRNAs, our understanding of their functions is still in its infancy. In this study, we developed a novel computational tool: Competing Endogenous RNA for INtegrative Annotations (Cerina), to predict biological functions of circRNAs based on the competing endogenous RNA model. Pareto Frontier Analysis was employed to integrate ENCODE mRNA/miRNA data with predicted microRNA response elements to prioritize tissue-specific ceRNA interactions. Using data from several circRNA-disease databases, we demonstrated that Cerina significantly improved the functional relevance of the prioritized ceRNA interactions by several folds, in terms of precision and recall. Proof-of-concept studies on human cancers and cardiovascular diseases further showcased the efficacy of Cerina on predicting potential circRNA functions in human diseases.

Expression of Extracellular Matrix-Related Genes and Their Regulatory microRNAs in Problematic Colorectal Polyps

Colorectal carcinoma usually evolves gradually, forming a spectrum of lesions, due to accumulation of genetic mutations and epigenetic alterations. Many early lesions are detected since the introduction of screening programs. The greatest challenge is to distinguish between adenomas with epithelial misplacement (AEM) and adenomas with early carcinoma (AEC), considering the diagnosis affects prognosis and treatment. We analyzed the expression of selected extracellular matrix (ECM)-related genes and proteins, and their regulatory microRNAs using RT-qPCR and immunohistochemistry in biopsies from 44 patients. Differences were observed in AEM in comparison to AEC for DCN, EPHA4, FN1, SPON2, and SPP1, reflecting inflammatory stromal reaction to traumatisation and misplacement of dysplastic glands in the submucosa in the former, and desmoplastic stromal reaction to true invasion of dysplastic glands in the submucosa in the latter. Expression of regulatory microRNAs hsa-miR-200c and hsa-miR-146a significantly negatively correlated with the expression of their regulated genes, while significant difference between AEM and AEC was observed only for hsa-miR-29c. The described expression patterns are too complex to be used in diagnostic work, but might contribute to better understanding ECM changes in colorectal carcinoma development, helping to find new markers in the future.

Machine Learning Identifies Robust Matrisome Markers and Regulatory Mechanisms in Cancer

The expression and regulation of matrisome genes-the ensemble of extracellular matrix, ECM, ECM-associated proteins and regulators as well as cytokines, chemokines and growth factors-is of paramount importance for many biological processes and signals within the tumor microenvironment. The availability of large and diverse multi-omics data enables mapping and understanding of the regulatory circuitry governing the tumor matrisome to an unprecedented level, though such a volume of information requires robust approaches to data analysis and integration. In this study, we show that combining Pan-Cancer expression data from The Cancer Genome Atlas (TCGA) with genomics, epigenomics and microenvironmental features from TCGA and other sources enables the identification of "landmark" matrisome genes and machine learning-based reconstruction of their regulatory networks in 74 clinical and molecular subtypes of human cancers and approx. 6700 patients. These results, enriched for prognostic genes and cross-validated markers at the protein level, unravel the role of genetic and epigenetic programs in governing the tumor matrisome and allow the prioritization of tumor-specific matrisome genes (and their regulators) for the development of novel therapeutic approaches.

FREMSA: A Method That Provides Direct Evidence of the Interaction between microRNA and mRNA

microRNAs (miRNAs) modulate the expression of enzymes responsible for activation or detoxification of xenobiotics and toxicants. miRNAs are dysregulated in response to environmental exposure and have been implicated in toxicological events. Many in vivo and in vitro experimental approaches have been employed to delineate the mechanisms by which miRNAs regulate target genes; however, all these methods provide only indirect evidence for the interaction between miRNAs and their counterpart mRNA molecules. In this chapter, we describe a novel approach-a fluorescent-based RNA electrophoretic mobility shift assay (FREMSA) that is a sensitive and time-saving method, with a high specificity, to visualize the interactions among miRNAs, mRNAs, and proteins, as direct evidence of mRNA/miRNA complex formation.

(Epi)genetic regulation of osteopontin in colorectal cancerogenesis

Aim: To identify (epi)genetic regulators of osteopontin (OPN, encoded by SPP1 gene) from normal colon mucosa to adenoma, adenoma with early carcinoma and advanced carcinoma. Patients & methods: Biopsy samples of 41 patients with different patohistologic diagnosis were used. Using qPCR, pyrosequencing and statistical analysis, we determined the expression level of osteopontin regulatory miRNAs, its copy number and methylation status. Results & conclusion: We showed that hsa-miR-146a-5p expression is inversely proportional to the expression level of SPP1 and that expression might be also controlled by copy number and methylation. These results suggest that not only expression of SPP1 but also its copy number, methylation status and expression of its regulators might be used as a potential biomarker of colorectal cancer.

H19, a Long Non-coding RNA, Mediates Transcription Factors and Target Genes through Interference of MicroRNAs in Pan-Cancer

Long non-coding RNAs (lncRNAs) have recently been found to be important in gene regulation. lncRNA H19 has been reported to play an oncogenic role in many human cancers. Its specific regulatory role is still elusive. In this study, we developed a novel analytic approach by integrating the synergistic regulation among lncRNAs (e.g., H19), transcription factors (TFs), target genes, and microRNAs (miRNAs) and then applied it to the pan-cancer expression datasets from The Cancer Genome Atlas (TCGA). Using linear regression models, we identified 88 H19-TF-gene co-regulatory triplets, in which 93% of the TF-gene pairs were related to cancer, indicating that our approach was effective to identify disease-related lncRNA-TF-gene co-regulation mechanisms. lncRNAs can function as miRNA sponges. Our further experiments found that H19 might regulate SP1-TGFBR2 through let-7b and miR-200b, ETS1-TGFBR2 through miR-29a and miR-200b, and STAT3-KLF11 through miR-17 in breast cancer cell lines. Our work suggests that miRNA-mediated lncRNA-TF-gene co-regulation is complicated yet important in cancer.

RPmirDIP: Reciprocal Perspective improves miRNA targeting prediction

MicroRNAs (miRNAs) are short, non-coding RNAs that interact with messenger RNA (mRNA) to accomplish critical cellular activities such as the regulation of gene expression. Several machine learning methods have been developed to improve classification accuracy and reduce validation costs by predicting which miRNA will target which gene. Application of these predictors to large numbers of unique miRNA–gene pairs has resulted in datasets comprising tens of millions of scored interactions; the largest among these is mirDIP. We here demonstrate that miRNA target prediction can be significantly improved (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p < 0.001$$\end{document}p<0.001) through the application of the Reciprocal Perspective (RP) method, a cascaded, semi-supervised machine learning method originally developed for protein-protein interaction prediction. The RP method, aptly named RPmirDIP, augments the original mirDIP prediction scores by leveraging local thresholds from the two complimentary views available to each miRNA–gene pair, rather than apply a traditional global decision threshold. Application of this novel RPmirDIP predictor promises to help identify new, unexpected miRNA–gene interactions. A dataset of RPmirDIP-scored interactions are made available to the scientific community at cu-bic.ca/RPmirDIP and 10.5683/SP2/LD8JKJ.

miRNA target identification and prediction as a function of time in gene expression data

The understanding of miRNA target interactions is still limited due to conflicting data and the fact that high-quality validation of targets is a time-consuming process. Faster methods like high-throughput screens and bioinformatics predictions are employed but suffer from several problems. One of these, namely the potential occurrence of downstream (i.e. secondary) effects in high-throughput screens has been only little discussed so far. However, such effects limit usage for both the identification of interactions and for the training of bioinformatics tools. In order to analyse this problem more closely, we performed time-dependent microarray screening experiments overexpressing human miR-517a-3p, and, together with published time-dependent datasets of human miR-17-5p, miR-135b and miR-124 overexpression, we analysed the dynamics of deregulated genes. We show that the number of deregulated targets increases over time, whereas seed sequence content and performance of several miRNA target prediction algorithms actually decrease over time. Bioinformatics recognition success of validated miR-17 targets was comparable to that of data gained only 12 h post-transfection. We therefore argue that the timing of microarray experiments is of critical importance for detecting direct targets with high confidence and for the usability of these data for the training of bioinformatics prediction tools.

Frequency of MicroRNA Response Elements Identifies Pathologically Relevant Signaling Pathways in Triple-Negative Breast Cancer

Complex interactions between mRNAs and microRNAs influence cellular functions. The mRNA-microRNA interactions also determine the post-transcriptional availability of mRNAs and unbound microRNAs. MicroRNAs binds to one or more microRNA response elements (MREs) located on the 3′UTR of mRNAs. In this study, we leveraged MREs and their frequencies in cancer and matched normal tissues to obtain insights into disease-specific interactions between mRNAs and microRNAs. We developed a bioinformatics method “ReMIx” that utilizes RNA sequencing (RNA-Seq) data to quantify MRE frequencies across the transcriptome. We applied ReMIx to triple-negative (TN) breast cancer tumor-normal adjacent pairs and identified MREs specific to TN tumors. ReMIx identified candidate mRNAs and microRNAs in the MAPK signaling cascade. Further analysis of MAPK gene regulatory networks revealed microRNA partners that influence and modulate MAPK signaling. In conclusion, we demonstrate a novel method of using MREs in the identification of functionally relevant mRNA-microRNA interactions in TN breast cancer.

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Bioinformatics method ReMIx identify differential microRNA response rlements (MRE)

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Tumor-specific MREs frequency observed in triple-negative breast cancer (TNBC)

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MRE analysis identify MAPK signaling genes as therapeutic target for TNBC

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MREs frequency can be used to identify pathologically relevant pathways

miRNA-mRNA Profiling Reveals Prognostic Impact of SMC1A Expression in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) with NPM1 mutation is a disease driving genetic alteration with good prognosis. Although it has been suggested that NPM1 mutation induces chemosensitivity in leukemic cells, the underlying cause for the better survival of NPM1 mutated patients is still not clear. Mutant NPM1 AML has a unique microRNA and their target gene (mRNA) signature compared to wild-type NPM1. Dynamic regulation of miRNA–mRNA has been reported to influence the prognostic outcome. In the present study, in silico expression data of miRNA and mRNA in AML patients was retrieved from genome data commons, and differentially expressed miRNA and mRNA among NPM1 mutated (n = 21) and NPM1 wild-type (n = 162) cases were identified to establish a dynamic association at the molecular level. In vitro experiments using high-throughput RNA sequencing were performed on human AML cells carrying NPM1 mutated and wild-type allele. The comparison of in vitro transcriptomics data with in silico miRNA–mRNA expression network data revealed downregulation of SMC1A. On establishing miRNA–mRNA interactive pairs, it has been observed that hsa-mir-215-5p (logFC: 0.957; p = 0.0189) is involved in the downregulation of SMC1A (logFC: –0.481; p = 0.0464) in NPM1 mutated AML. We demonstrated that transient expression of NPM1 mutation upregulates miR-215-5p, which results in downregulation of SMC1A. We have also shown using a rescue experiment that neutralizing miR-215-5p reverses the effect of NPM1 mutation on SMC1A. Using the leukemic blasts from AML patients, we observed higher expression of miR-215-5p and lower expression of SMC1A in NPM1 mutated patients compared to wild-type cases. The overall survival of AML patients was significantly inferior in SMC1A high expressers compared to low expressers (20.3% vs. 58.5%, p = 0.018). The data suggest that dynamic miR-215-SMC1A regulation is potentially modulated by NPM1 mutation, which might serve as an explanation for the better outcome in NPM1 mutated AML.

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.

What's the target: understanding two decades of in silico microRNA-target prediction

MOTIVATION

Since the initial discovery of microRNAs as post-transcriptional, regulatory key players in the 1990s, a total number of $2656$ mature microRNAs have been publicly described for Homo sapiens. As discovery of new miRNAs is still on-going, target identification remains to be an essential and challenging step preceding functional annotation analysis. One key challenge for researchers seems to be the selection of the most appropriate tool out of the larger multiverse of published solutions for a given research study set-up.

RESULTS

In this review we collectively describe the field of in silico target prediction in the course of time and point out long withstanding principles as well as recent developments. By compiling a catalog of characteristics about the 98 prediction methods and identifying common and exclusive traits, we signpost a simplified mechanism to address the problem of application selection. Going further we devised interpretation strategies for common types of output as generated by frequently used computational methods. To this end, our work specifically aims to make prospective users aware of common mistakes and practical questions that arise during the application of target prediction tools.

AVAILABILITY

An interactive implementation of our recommendations including materials shown in the manuscript is freely available at https://www.ccb.uni-saarland.de/mtguide.

The Regulatory Roles of Non-coding RNAs in Angiogenesis and Neovascularization From an Epigenetic Perspective

Angiogenesis is a crucial process for organ morphogenesis and growth during development, and it is especially relevant during the repair of wounded tissue in adults. It is coordinated by an equilibrium of pro- and anti-angiogenic factors; nevertheless, when affected, it promotes several diseases. Lately, a growing body of evidence is indicating that non-coding RNAs (ncRNAs), such as miRNAs, circRNAs, and lncRNAs, play critical roles in angiogenesis. These ncRNAs can act in cis or trans and alter gene transcription by several mechanisms including epigenetic processes. In the following pages, we will discuss the functions of ncRNAs in the regulation of angiogenesis and neovascularization, both in normal and disease contexts, from an epigenetic perspective. Additionally, we will describe the contribution of Next-Generation Sequencing (NGS) techniques to the discovery and understanding of the role of ncRNAs in angiogenesis.

mirDIP 4.1-integrative database of human microRNA target predictions

MicroRNAs are important regulators of gene expression, achieved by binding to the gene to be regulated. Even with modern high-throughput technologies, it is laborious and expensive to detect all possible microRNA targets. For this reason, several computational microRNA-target prediction tools have been developed, each with its own strengths and limitations. Integration of different tools has been a successful approach to minimize the shortcomings of individual databases. Here, we present mirDIP v4.1, providing nearly 152 million human microRNA-target predictions, which were collected across 30 different resources. We also introduce an integrative score, which was statistically inferred from the obtained predictions, and was assigned to each unique microRNA-target interaction to provide a unified measure of confidence. We demonstrate that integrating predictions across multiple resources does not cumulate prediction bias toward biological processes or pathways. mirDIP v4.1 is freely available at http://ophid.utoronto.ca/mirDIP/.

Genome-wide discovery of viral microRNAs based on phylogenetic analysis and structural evolution of various human papillomavirus subtypes

In mammals, microRNAs (miRNAs) play key roles in controlling posttranscriptional regulation through binding to the mRNAs of target genes. Recently, it was discovered that viral miRNAs may be involved in human cancers and diseases. It is likely that viral miRNAs help viruses enter the latent phase of their life cycle and become undetected by the host's immune system, while increasing the host's risk for cancer development. Cervical cancer is typically related to the infection of human papillomavirus (HPV) through sexual transmission. To further understand the molecular mechanisms underlying the associations of HPV infection with genital diseases, we developed a systematic method for viral miRNA identification and viral miRNA-mediated regulatory network construction based on genome-wide sequence analysis. The complete genomes of certain high-risk HPV subtypes were used to predict putative viral pre-miRNAs by bioinformatics approaches. In addition, small RNA libraries in human cervical lesions from existing publications were collected to validate the predicted HPV pre-miRNAs. For the construction of virally encoded miRNA-mediated regulatory network of HPV infection, cervical squamous epithelial carcinoma gene expression data were extracted from the RNA sequencing platform in The Cancer Genome Atlas; the differentially expressed genes were used to identify the putative targets of viral miRNAs. Predicted cellular target genes of HPV-encoded miRNAs provide an overview of these viral miRNA's putative functions. Finally, a large-scale genome analysis was carried out to examine the phylogenetic relationship and structural evolution among genital HPV types that have the potential to cause genital cancer. In this study, we discovered putative HPV-encoded miRNAs, which were validated against the small RNA libraries in human cervical lesions. Furthermore, as indicated by their biological functions, host genes targeted by HPV-encoded miRNAs may play significant roles in virus infection and carcinogenesis. These viral miRNAs pose as promising candidates for the development of antiviral drugs. More importantly, the identified subtype-specific miRNAs have the potential to be used as biomarkers for HPV subtype determination.

Computational Resources for Prediction and Analysis of Functional miRNA and Their Targetome

microRNAs are evolutionarily conserved, endogenously produced, noncoding RNAs (ncRNAs) of approximately 19-24 nucleotides (nts) in length known to exhibit gene silencing of complementary target sequence. Their deregulated expression is reported in various disease conditions and thus has therapeutic implications. In the last decade, various computational resources are published in this field. In this chapter, we have reviewed bioinformatics resources, i.e., miRNA-centered databases, algorithms, and tools to predict miRNA targets. First section has enlisted more than 75 databases, which mainly covers information regarding miRNA registries, targets, disease associations, differential expression, interactions with other noncoding RNAs, and all-in-one resources. In the algorithms section, we have compiled about 140 algorithms from eight subcategories, viz. for the prediction of precursor (pre-) and mature miRNAs. These algorithms are developed on various sequence, structure, and thermodynamic based features incorporated into different machine learning techniques (MLTs). In addition, computational identification of miRNAs from high-throughput next generation sequencing (NGS) data and their variants, viz. isomiRs, differential expression, miR-SNPs, and functional annotation, are discussed. Prediction and analysis of miRNAs and their associated targets are also evaluated under miR-targets section providing knowledge regarding novel miRNA targets and complex host-pathogen interactions. In conclusion, we have provided comprehensive review of in silico resources published in miRNA research to help scientific community be updated and choose the appropriate tool according to their needs.

Integrated bioinformatics analysis and validation revealed potential immune-regulatory miR-892b, miR-199b-5p and miR-582-5p as diagnostic biomarkers in active tuberculosis

Tuberculosis (TB) is one of the most prevalent pulmonary diseases caused by Mycobacterium tuberculosis (Mtb). MiRNAs (miRNAs) participate in TB progression by modulating the host-pathogen interaction. Bioinformatics advancements provide basis for exploring novel immunoregulatory miRNAs and their performance as diagnostic biomarkers. Gene and miRNA expression datasets, GSE29190 and GSE54992, were downloaded from Gene Expression Omnibus (GEO) database. Based on fold changes and statistical significance, a total of 7463 differentially expressed mRNAs (DE-mRNAs) and 38 differentially expressed miRNAs (DE-miRNAs) were screened. Function annotation and protein-protein interaction (PPI) network were constructed to reveal underlying mechanisms of TB pathogenesis. Functional annotation identified the MAPK signalling pathway and leukocyte migration as the top enriched processes. The PPI and MGIP networks indicated that chemokine ligands like CXCL1/CXCL2 and receptors, like CCR7 were important down-regulated genes, implying that a protective mechanism against overdue inflammation induced cell death. MiRNA-gene-immune processes (MGIP) network enriched 7 deregulated miRNAs, and their expression was further examined with quantitative real-time PCR (qRT-PCR), in PBMC samples of 20 active TB patients and 20 healthy donors. The diagnostic performance was evaluated with ROC curves. MiR-892b; miR-199b-5p and miR-582-5p were significantly deregulated in TB patients, compared with healthy participants. The best overall performance was from miR-892b, with an area under curve (AUC) of 0.77, 55% sensitivity and 90% specificity. AUC of miR-199b-5p and miR-582-5p were 0.71 and 0.70, respectively. MiR-892b, miR-199b-5p and miR-582-5p could be considered promising novel diagnostic biomarkers for active tuberculosis.

Elevated miR-200a and miR-141 inhibit endocrine gland-derived vascular endothelial growth factor expression and ciliogenesis in preeclampsia

KEY POINTS

Endocrine gland-derived vascular endothelial growth factor (EG-VEGF) is a critical factor that facilitates trophoblast invasion in placenta. Plasma miR-141 and miR-200a levels were elevated, while EG-VEGF was decreased in peripheral blood and placenta of preeclamptic patients. Furthermore, numbers of cilia in the placenta from preeclamptic women were significantly decreased. Elevated miR-141 and miR-200a inhibited the expression of EG-VEGF, downstream extracellular signal-regulated kinase (ERK)/matrix metalloproteinase 9 signalling and cilia formation, thus leading to defective trophoblast invasion. The growth of the primary cilium, which transduced ERK signalling upon EG-VEGF induction for proper trophoblast invasion, was also inhibited by miR-141 and miR-200a upregulation.

ABSTRACT

Preeclampsia is a severe gestational complication, and inadequate trophoblast invasion during placental development is an important pathoaetiology. Endocrine gland-derived vascular endothelial growth factor (EG-VEGF) is a critical factor that facilitates trophoblast invasion in placenta. By binding to the primary cilium, EG-VEGF initiates the signalling cascade for proper embryo implantation and placental development. The miR-200 family was predicted to target the EG-VEGF 5'-untranslated region, and its specific binding site was confirmed using a dual luciferase and a co-transfection assay. In the peripheral blood and placenta of preeclamptic patients, EG-VEGF showed significantly lower expression, whereas plasma miR-141 and miR-200a had higher expression compared with the controls. The biological significance of miR-141 and miR-200a was verified using an overexpression method in a trophoblast cell line (HTR-8/SVneo). Elevated miR-141 and miR-200a inhibited the expression of EG-VEGF, matrix metalloproteinase 9 (MMP9) and downstream extracellular signal-regulated kinase (ERK) signalling, thus leading to defective trophoblast invasion. Additionally, the growth of the primary cilium, which transduces ERK/MMP9 signalling upon EG-VEGF induction, was inhibited by miR-141 and miR-200a upregulation. Furthermore, the number of cilia in the human placenta of preeclamptic women was significantly decreased compared to normal placenta. In conclusion, the study uncovers the clinical correlations among the miR-200 family, EG-VEGF and the primary cilium in preeclampsia and the underlying molecular mechanisms. The results indicate that miR-141 and miR-200a directly targeted EG-VEGF, suppressed primary cilia formation and inhibited trophoblast invasion. Thus, miR-141 and miR-200a could be explored as promising miRNA biomarkers and therapeutic targets in preeclampsia.

A Practical Guide to miRNA Target Prediction

MicroRNAs (miRNAs) are small endogenous noncoding RNA molecules that posttranscriptionally regulate gene expression. Since their discovery, a huge number of miRNAs have been identified in a wide range of species. Through binding to the 3' UTR of mRNA, miRNA can block translation or stimulate degradation of the targeted mRNA, thus affecting nearly all biological processes. Prediction and identification of miRNA target genes is crucial toward understanding the biology of miRNAs. Currently, a number of sophisticated bioinformatics approaches are available to perform effective prediction of miRNA target sites. In this chapter, we present the major features that most algorithms take into account to efficiently predict miRNA target: seed match, free energy, conservation, target site accessibility, and contribution of multiple binding sites. We also give an overview of the frequently used bioinformatics tools for miRNA target prediction. Understanding the basis of these prediction methodologies may help users to better select the appropriate tools and analyze their output.