Inference of miRNA targets using evolutionary conservation and pathway analysis. BMC Bioinformatics. 2007;8:69. [PMID: 17331257 PMCID: PMC1838429 DOI: 10.1186/1471-2105-8-69]

Constructing lncRNA-miRNA-mRNA networks specific to individual cancer patients and finding prognostic biomarkers

BACKGROUND

The competitive endogenous RNA (ceRNA) hypothesis suggests that microRNAs (miRNAs) mediate a regulatory relation between long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) which share similar miRNA response elements (MREs) to bind to the same miRNA. Since the ceRNA hypothesis was proposed, several studies have been conducted to construct a network of lncRNAs, miRNAs and mRNAs in cancer. However, most cancer-related ceRNA networks are intended for representing a general relation of RNAs in cancer rather than for a patient-specific relation. Due to the heterogeneous nature of cancer, lncRNA-miRNA-mRNA interactions can vary in different patients.

RESULTS

We have developed a new method for constructing a ceRNA network of lncRNAs, miRNAs and mRNAs, which is specific to an individual cancer patient and for finding prognostic biomarkers consisting of lncRNA-miRNA-mRNA triplets. We tested our method on extensive data sets of three types of cancer (breast cancer, liver cancer, and lung cancer) and obtained potential prognostic lncRNA-miRNA-mRNA triplets for each type of cancer.

CONCLUSIONS

Analysis of expression patterns of the RNAs involved in the triplets and survival rates of cancer patients revealed several interesting findings. First, even for the same cancer type, prognostic lncRNA-miRNA-mRNA triplets can be different depending on whether lncRNA and mRNA show opposite or similar expression patterns. Second, prognostic lncRNA-miRNA-mRNA triplets are often more predictive of survival rates than RNA pairs or individual RNAs. Our approach will be useful for constructing patient-specific lncRNA-miRNA-mRNA networks and for finding prognostic biomarkers from the networks.

Gra-CRC-miRTar: The pre-trained nucleotide-to-graph neural networks to identify potential miRNA targets in colorectal cancer

Colorectal cancer (CRC) is the third most diagnosed cancer and the second deadliest cancer worldwide representing a major public health problem. In recent years, increasing evidence has shown that microRNA (miRNA) can control the expression of targeted human messenger RNA (mRNA) by reducing their abundance or translation, acting as oncogenes or tumor suppressors in various cancers, including CRC. Due to the significant up-regulation of oncogenic miRNAs in CRC, elucidating the underlying mechanism and identifying dysregulated miRNA targets may provide a basis for improving current therapeutic interventions. In this paper, we proposed Gra-CRC-miRTar, a pre-trained nucleotide-to-graph neural network framework, for identifying potential miRNA targets in CRC. Different from previous studies, we constructed two pre-trained models to encode RNA sequences and transformed them into de Bruijn graphs. We employed different graph neural networks to learn the latent representations. The embeddings generated from de Bruijn graphs were then fed into a Multilayer Perceptron (MLP) to perform the prediction tasks. Our extensive experiments show that Gra-CRC-miRTar achieves better performance than other deep learning algorithms and existing predictors. In addition, our analyses also successfully revealed 172 out of 201 functional interactions through experimentally validated miRNA-mRNA pairs in CRC. Collectively, our effort provides an accurate and efficient framework to identify potential miRNA targets in CRC, which can also be used to reveal miRNA target interactions in other malignancies, facilitating the development of novel therapeutics.

On the rules of engagement for microRNAs targeting protein coding regions

MiRNAs post-transcriptionally repress gene expression by binding to mRNA 3'UTRs, but the extent to which they act through protein coding regions (CDS regions) is less well established. MiRNA interaction studies show a substantial proportion of binding occurs in CDS regions, however sequencing studies show much weaker effects on mRNA levels than from 3'UTR interactions, presumably due to competition from the translating ribosome. Consequently, most target prediction algorithms consider only 3'UTR interactions. However, the consequences of CDS interactions may have been underestimated, with the reporting of a novel mode of miRNA-CDS interaction requiring base pairing of the miRNA 3' end, but not the canonical seed site, leading to repression of translation with little effect on mRNA turnover. Using extensive reporter, western blotting and bioinformatic analyses, we confirm that miRNAs can indeed suppress genes through CDS-interaction in special circumstances. However, in contrast to that previously reported, we find repression requires extensive base-pairing, including of the canonical seed, but does not strictly require base pairing of the 3' miRNA terminus and is mediated through reducing mRNA levels. We conclude that suppression of endogenous genes can occur through miRNAs binding to CDS, but the requirement for extensive base-pairing likely limits the regulatory impacts to modest effects on a small subset of targets.

Unique miRNome and transcriptome profiles underlie microvascular heterogeneity in mouse kidney

Endothelial cells in blood vessels in the kidney exert different functions depending on the (micro)vascular bed they are located in. The present study aimed to investigate microRNA and mRNA transcription patterns that underlie these differences. We zoomed in on microvascular compartments in the mouse renal cortex by laser microdissecting the microvessels prior to small RNA- and RNA-sequencing analyses. By these means, we characterized microRNA and mRNA transcription profiles of arterioles, glomeruli, peritubular capillaries, and postcapillary venules. Quantitative RT-PCR, in situ hybridization, and immunohistochemistry were used to validate sequencing results. Unique microRNA and mRNA transcription profiles were found in all microvascular compartments, with dedicated marker microRNAs and mRNAs showing enriched transcription in a single microvascular compartment. In situ hybridization validated the localization of microRNAs mmu-miR-140-3p in arterioles, mmu-miR-322-3p in glomeruli, and mmu-miR-451a in postcapillary venules. Immunohistochemical staining showed that von Willebrand factor protein was mainly expressed in arterioles and postcapillary venules, whereas GABRB1 expression was enriched in glomeruli, and IGF1 was enriched in postcapillary venules. More than 550 compartment-specific microRNA-mRNA interaction pairs were identified that carry functional implications for microvascular behavior. In conclusion, our study identified unique microRNA and mRNA transcription patterns in microvascular compartments of the mouse kidney cortex that underlie microvascular heterogeneity. These patterns provide important molecular information for future studies into differential microvascular engagement in health and disease.NEW & NOTEWORTHY Renal endothelial cells display a high level of heterogeneity depending on the (micro)vascular bed they reside in. The molecular basis contributing to these differences is poorly understood yet of high importance to increase understanding of microvascular engagement in the kidney in health and disease. This report describes m(icro)RNA expression profiles of microvascular beds in the mouse renal cortex and uncovers microvascular compartment-specific m(icro)RNAs and miRNA-mRNA pairs, thereby revealing important molecular mechanisms underlying renal microvascular heterogeneity.

Finding miRNA-RNA Network Biomarkers for Predicting Metastasis and Prognosis in Cancer

Despite remarkable progress in cancer research and treatment over the past decades, cancer ranks as a leading cause of death worldwide. In particular, metastasis is the major cause of cancer deaths. After an extensive analysis of miRNAs and RNAs in tumor tissue samples, we derived miRNA-RNA pairs with substantially different correlations from those in normal tissue samples. Using the differential miRNA-RNA correlations, we constructed models for predicting metastasis. A comparison of our model to other models with the same data sets of solid cancer showed that our model is much better than the others in both lymph node metastasis and distant metastasis. The miRNA-RNA correlations were also used in finding prognostic network biomarkers in cancer patients. The results of our study showed that miRNA-RNA correlations and networks consisting of miRNA-RNA pairs were more powerful in predicting prognosis as well as metastasis. Our method and the biomarkers obtained using the method will be useful for predicting metastasis and prognosis, which in turn will help select treatment options for cancer patients and targets of anti-cancer drug discovery.

Determinants of Functional MicroRNA Targeting

MicroRNAs (miRNAs) play cardinal roles in regulating biological pathways and processes, resulting in significant physiological effects. To understand the complex regulatory network of miRNAs, previous studies have utilized massivescale datasets of miRNA targeting and attempted to computationally predict the functional targets of miRNAs. Many miRNA target prediction tools have been developed and are widely used by scientists from various fields of biology and medicine. Most of these tools consider seed pairing between miRNAs and their mRNA targets and additionally consider other determinants to improve prediction accuracy. However, these tools exhibit limited prediction accuracy and high false positive rates. The utilization of additional determinants, such as RNA modifications and RNA-binding protein binding sites, may further improve miRNA target prediction. In this review, we discuss the determinants of functional miRNA targeting that are currently used in miRNA target prediction and the potentially predictive but unappreciated determinants that may improve prediction accuracy.

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.

Association of Circular RNA and Long Non-Coding RNA Dysregulation with the Clinical Response to Immune Checkpoint Blockade in Cutaneous Metastatic Melanoma

Cutaneous melanoma (CM) is the most lethal form of skin cancer if it becomes metastatic, where treatment options and survival chances decrease dramatically. Immunotherapy treatments based on the immunologic checkpoint inhibitors programmed death cell protein 1 (PD-1) and cytotoxic T-lymphocyte antigen 4 (CTLA-4) constituted a main breakthrough in the treatment of metastatic CM, particularly for the achievement of long-term benefits. Even though it is a very promising therapy, resistance to primary immune checkpoint blockade (ICB) arises in about 70% of CM patients treated with a CTLA-4 inhibitor, and 40–65% of CM patients administered with a PD-1-targeting treatment. Some long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) are implicated in triggering pro- and anti-tumorigenic responses to various cancer treatments. The relationship between lncRNAs, circRNAs and ICB immunotherapy has not been explored in cutaneous metastatic melanoma (CMM). The aim of this pilot study is to evaluate the potential role of circRNA and lncRNA expression as pre-treatment predictors of the clinical response to immunotherapy in CMM patients. RNA-seq from 12 formalin-fixed paraffin-embedded (FFPE) samples from the metastatic biopsies of CMM patients treated with nivolumab was used to identify response-associated transcripts. Our findings indicate that specific lncRNAs and circRNAs, probably acting as competitive endogenous RNAs (ceRNAs), are involved in the regulatory networks of the immune response against metastatic melanoma that these patients have under treatment with nivolumab. Moreover, we established a risk score that yields predictions of the overall survival (OS) and progression-free survival (PFS) of CMM patients with high accuracy. This proof-of-principle work provides a possible insight into the function of ceRNAs, contributing to efforts to decipher the complex molecular mechanisms of ICB cancer treatment response.

Identification of stage-associated exosome miRNAs in colorectal cancer by improved robust and corroborative approach embedded miRNA-target network

Background

Colorectal cancer (CRC) is a common gastrointestinal tumor with high morbidity and mortality. At the molecular level, patients at different stages present considerable heterogeneity. Although the miRNA in exosome is an effective biomarker to reveal tumor progression, studies based on stage-associated exosome miRNA regulatory network analysis still lacking. This study aims to identify CRC stage-associated exosome miRNAs and reveal their potential function in tumor progression.

Methods

In this study, serum and cellular exosome miRNA expression microarrays associated with CRC were downloaded from GEO database. Stage-common (SC) and stage-specific (SS) differentially expressed miRNAs were extracted and their targets were identified based on 11 databases. Furthermore, miRNA SC and SS regulatory function networks were built based on the CRC phenotypic relevance of miRNA targets, and the corresponding transcription factors were identified. Concurrently, the potential stage-associated miRNAs were identified by receiver-operating characteristic (ROC) curve analysis, survival analysis, drug response analysis, ceRNA analysis, pathway analysis and a comprehensive investigation of 159 publications.

Results

Ten candidate stage-associated miRNAs were identified, with three SC (miR-146a-5p, miR-22-3p, miR-23b-3p) and seven SS (I: miR-301a-3p, miR-548i; IIIA: miR-23a-3p; IV: miR-194-3p, miR-33a-3p, miR-485-3p, miR-194-5p) miRNAs. Additionally, their targets were enriched in several vital cancer-associated pathways such as TGF-beta, p53, and hippo signaling pathways. Moreover, five key hotspot target genes (CCNA2, MAPK1, PTPRD, MET, and CDKN1A) were demonstrated to associated with better overall survival in CRC patients. Finally, miR-23b-3p, miR-301a-3p and miR-194-3p were validated being the most stably expressed stage-associated miRNAs in CRC serum exosomes, cell exosomes and tissues.

Conclusions

These CRC stage-associated exosome miRNAs aid to further mechanism research of tumor progression and provide support for better clinical management in patients with different stages.

The microRNA-10b-Bim axis promotes cancer progression through activating autophagy in oral squamous cell carcinoma

Autophagy is related to many cellular mechanisms and dysregulation of autophagy involves the pathological process in cancer. miR-10b activates autophagy, which promotes invasion and migration of OSCC. Its functional role in the mechanism of OSCC to autophagy remains to be unclear. Overexpression of miR-10b was followed by enhanced OSCC invasion and migration and activated autophagic protein, such as LC3II/ATG5. MiR-10b attracted Bim directly according to the Bio-informatics analyses and double luciferases reporter assays. Functional experiments further revealed that miR-10b could promote invasion and migration in vitro. In addition, miR-10b induced autophagy via inhibiting Bim in invasion and migration of OSCC. Notably, animal experiments confirmed that miR-10b-Bim promoted proliferation and autophagy in OSCC. In addition, this study provides a theoretical support for regulating the mechanism of OSCC by inducing autophagy with miR-10b-Bim as a target.

Integrated analysis of expression profiles with meat quality traits in cattle

MicroRNAs (miRNAs) play a vital role in improving meat quality by binding to messenger RNAs (mRNAs). We performed an integrated analysis of miRNA and mRNA expression profiling between bulls and steers based on the differences in meat quality traits. Fat and fatty acids are the major phenotypic indices of meat quality traits to estimate between-group variance. In the present study, 90 differentially expressed mRNAs (DEGs) and 18 differentially expressed miRNAs (DEMs) were identified. Eighty-three potential DEG targets and 18 DEMs were used to structure a negative interaction network, and 75 matching target genes were shown in this network. Twenty-six target genes were designated as intersection genes, screened from 18 DEMs, and overlapped with the DEGs. Seventeen of these genes enriched to 19 terms involved in lipid metabolism. Subsequently, 13 DEGs and nine DEMs were validated using quantitative real-time PCR, and seven critical genes were selected to explore the influence of fat and fatty acids through hub genes and predict functional association. A dual-luciferase reporter and Western blot assays confirmed a predicted miRNA target (bta-miR-409a and PLIN5). These findings provide substantial evidence for molecular genetic controls and interaction among genes in cattle.

Upregulation of miR-34a-5p, miR-20a-3p and miR-29a-3p by Onconase in A375 Melanoma Cells Correlates with the Downregulation of Specific Onco-Proteins

Onconase (ONC) is an amphibian secretory ribonuclease displaying cytostatic and cytotoxic activities against many mammalian tumors, including melanoma. ONC principally damages tRNA species, but also other non-coding RNAs, although its precise targets are not known. We investigated the ONC ability to modulate the expression of 16 onco-suppressor microRNAs (miRNAs) in the A375 BRAF-mutated melanoma cell line. RT-PCR and immunoblots were used to measure the expression levels of miRNAs and their regulated proteins, respectively. In silico study was carried out to verify the relations between miRNAs and their mRNA targets. A375 cell transfection with miR-20a-3p and miR-34a-5p mimics or inhibitors was performed. The onco-suppressors miR-20a-3p, miR-29a-3p and miR-34a-5p were highly expressed in 48-h ONC-treated A375 cells. The cytostatic effect of ONC in A375 cells was mechanistically explained by the sharp inhibition of cyclins D1 and A2 expression level, as well as by downregulation of retinoblastoma protein and cyclin-dependent-kinase-2 activities. Remarkably, the expression of kinases ERK1/2 and Akt, as well as of the hypoxia inducible factor-1α, was inhibited by ONC. All these proteins control pro-survival pathways. Finally, many crucial proteins involved in migration, invasion and metastatic potential were downregulated by ONC. Results obtained from transfection of miR-20a-3p and miR-34a-5p inhibitors in the presence of ONC show that these miRNAs may participate in the antitumor effects of ONC in the A375 cell line. In conclusion, we identified many intracellular downregulated proteins involved in melanoma cell proliferation, metabolism and progression. All mRNAs coding these proteins may be targets of miR-20a-3p, miR-29a-3p and/or miR-34a-5p, which are in turn upregulated by ONC. Data suggest that several known ONC anti-proliferative and anti-metastatic activities in A375 melanoma cells might depend on the upregulation of onco-suppressor miRNAs. Notably, miRNAs stability depends on the upstream regulation by long-non-coding-RNAs or circular-RNAs that can, in turn, be damaged by ONC ribonucleolytic activity.

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.

In Silico Investigation of Conserved miRNAs and Their Targets From the Expressed Sequence Tags in Neospora Caninum Genome

Neospora caninum is a protozoan parasite, the etiologic agent of Neosporosis—a common cause of abortion in cattle worldwide. Herd level prevalence of Neosporosis could be as high as 90%. However, there is no approved treatment and vaccines available for Neosporosis. MicroRNA (miRNA) based prophylaxis and therapeutics could be options for Neosporosis in cattle and other animals. The current study aimed to investigate the genome of Neospora caninum to identify and characterize the conserved miRNAs through Expressed Sequence Tags (ESTs) dependent homology search. A total of 1,041 mature miRNAs of reference organisms were employed against 336 non-redundant ESTs available in the genome of Neospora caninum. The study predicted one putative miRNA “nca-miR-9388-5p” of 19 nucleotides with MFEI value -1.51 kcal/mol and (A + U) content% 72.94% corresponding with its pre-miRNA. A comprehensive search for specific gene targets was performed and discovered 16 potential genes associated with different protozoal physiological functions. Significantly, the gene “Protein phosphatase” was found responsible for the virulence of Neospora caninum. The other genes were accounted for gene expression, vesicular transport, cell signaling, cell proliferation, DNA repair mechanism, and different developmental stages of the protozoon. Therefore, this study finding will provide pivotal information to future aspirants upon Bovine Neosporosis. It will also serve as the baseline information for further studies of the bioinformatics approach to identify other protozoal miRNAs.

Prediction methods for microRNA targets in bilaterian animals: Toward a better understanding by biologists

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression at the posttranscriptional level. Because of their wide network of interactions, miRNAs have become the focus of many studies over the past decade, particularly in animal species. To streamline the number of potential wet lab experiments, the use of miRNA target prediction tools is currently the first step undertaken. However, the predictions made may vary considerably depending on the tool used, which is mostly due to the complex and still not fully understood mechanism of action of miRNAs. The discrepancies complicate the choice of the tool for miRNA target prediction. To provide a comprehensive view of this issue, we highlight in this review the main characteristics of miRNA-target interactions in bilaterian animals, describe the prediction models currently used, and provide some insights for the evaluation of predictor performance.

A bioinformatics approach to investigate serum and hematopoietic cell-specific therapeutic microRNAs targeting the 3' UTRs of all four Dengue virus serotypes

Hyperendemic circulation of all four Dengue virus (DENV) serotypes is a severe global public health problem, so any vaccine or therapeutics should be able to target all four of them. Cells of hemopoietic origin are believed to be primary sites of DENV replication. This study aimed to identify potential host miRNAs that target 3' UTR of all four DENV serotypes, thereby directly regulating viral gene expression or indirectly modulating the host system at different virus infection steps. We used four prediction algorithms viz. miRanda, RNA22, RNAhybrid and StarMir for predicting miRNA, targeting 3'UTR of all four DENV serotypes. Statistically, the most significant miRNA targets were screened based on their Log10 P-value (> 0.0001) of Gene Ontology (GO) term and Kyoto Encyclopaedia of Gene and Genome (KEGG) pathway enrichment analysis. The intersection test of at least three prediction tools identified a total of 30 miRNAs, which could bind to 3'UTR of all four DENV serotypes. Of the 30, eight miRNAs were of hematopoietic cell origin. GO term enrichment and KEGG analysis showed four hemopoietic origin miRNAs target genes of the biological processes mainly involved in the innate immune response, mRNA 3'-end processing, antigen processing and presentation and nuclear-transcribed mRNA catabolic process.

Shortening of HO1 3'UTRs by Alternative Polyadenylation Suppresses Adipogenesis in 3T3-L1

Appropriately increasing intramuscular fat content can help improve meat quality, so it is necessary to explore the internal molecular mechanism of preadipocyte differentiation. The role of heme oxygenase 1 (HO1) in cell oxidative stress, energy metabolism, cell proliferation, and differentiation has gradually been revealed. Here, we used 3'RACE to identify the full-length 3' untranslated region (3'UTR) of HO1 and found that a very short 3'UTR variant was produced by alternative polyadenylation (APA). HO1 with a long 3'UTR variant was identified as a direct target of miR155-5P and miR377-3P. Our experimental results verified the inhibitory effect of HO1 on preadipocyte differentiation. In addition, our research confirms that by escaping microRNA inhibitory effects, the HO1 3'UTR short variant produced by APA has a higher level of expression. Thus, the HO1 3'UTR short variant has a stronger inhibitory effect on the preadipocyte differentiation than the HO1 3'UTR long variants in 3T3-L1.

Evaluating the Effect of 3'-UTR Variants in DICER1 and DROSHA on Their Tissue-Specific Expression by miRNA Target Prediction

Untranslated gene regions (UTRs) play an important role in controlling gene expression. 3'-UTRs are primarily targeted by microRNA (miRNA) molecules that form complex gene regulatory networks. Cancer genomes are replete with non-coding mutations, many of which are connected to changes in tumor gene expression that accompany the development of cancer and are associated with resistance to therapy. Therefore, variants that occurred in 3'-UTR under cancer progression should be analysed to predict their phenotypic effect on gene expression, e.g., by evaluating their impact on miRNA target sites. Here, we analyze 3'-UTR variants in DICER1 and DROSHA genes in the context of myelodysplastic syndrome (MDS) development. The key features of this analysis include an assessment of both "canonical" and "non-canonical" types of mRNA-miRNA binding and tissue-specific profiling of miRNA interactions with wild-type and mutated genes. As a result, we obtained a list of DICER1 and DROSHA variants likely altering the miRNA sites and, therefore, potentially leading to the observed tissue-specific gene downregulation. All identified variants have low population frequency consistent with their potential association with pathology progression.

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.

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.

Hypoxic naked mole-rat brains use microRNA to coordinate hypometabolic fuels and neuroprotective defenses

Naked mole-rats are among the mammalian champions of hypoxia tolerance. They evolved adaptations centered around reducing metabolic rate to overcome the challenges experienced in their underground burrows. In this study, we used next-generation sequencing to investigate one of the factors likely supporting hypoxia tolerance in naked mole-rat brains, posttranscriptional microRNAs (miRNAs). Of the 212 conserved miRNAs identified using small RNA sequencing, 18 displayed significant differential expression during hypoxia. Bioinformatic enrichment revealed that hypoxia-mediated miRNAs were suppressing energy expensive processes including de novo protein translation and cellular proliferation. This suppression occurred alongside the activation of neuroprotective and neuroinflammatory pathways, and the induction of central signal transduction pathways including HIF-1α and NFκB via miR-335, miR-101, and miR-155. MiRNAs also coordinated anaerobic glycolytic fuel sources, where hypoxia-upregulated miR-365 likely suppressed protein levels of ketohexokinase, the enzyme responsible for catalyzing the first committed step of fructose catabolism. This was further supported by a hypoxia-mediated reduction in glucose transporter 5 proteins that import fructose into the cell. Yet, messenger RNA and protein levels of lactate dehydrogenase, which converts pyruvate to lactate in the absence of oxygen, were elevated during hypoxia. Together, this demonstrated the induction of anaerobic glycolysis despite a lack of reliance on fructose as the primary fuel source, suggesting that hypoxic brains are metabolically different than anoxic naked mole-rat brains that were previously found to shift to fructose-based glycolysis. Our findings contribute to the growing body of oxygen-responsive miRNAs "OxymiRs" that facilitate natural miRNA-mediated mechanisms for successful hypoxic exposures.

Hla-C genetic diversity and evolutionary insights in two samples from Brazil and Benin

Human leukocyte antigen-C (HLA-C) is a classical HLA class I molecule that binds and presents peptides to cytotoxic T lymphocytes in the cell surface. HLA-C has a dual function because it also interacts with Killer-cell immunoglobulin-like receptors (KIR) receptors expressed in natural killer and T cells, modulating their activity. The structure and diversity of the HLA-C regulatory regions, as well as the relationship among variants along the HLA-C locus, are poorly addressed, and few population-based studies explored the HLA-C variability in the entire gene in different population samples. Here we present a molecular and bioinformatics method to evaluate the entire HLA-C diversity, including regulatory sequences. Then, we applied this method to survey the HLA-C diversity in two population samples with different demographic histories, one highly admixed from Brazil with major European contribution, and one from Benin with major African contribution. The HLA-C promoter and 3'UTR were very polymorphic with the presence of few, but highly divergent haplotypes. These segments also present conserved sequences that are shared among different primate species. Nucleotide diversity was higher in other segments rather than exons 2 and 3, particularly around exon 5 and the second half of the 3'UTR region. We detected evidence of balancing selection on the entire HLA-C locus and positive selection in the HLA-C leader peptide, for both populations. HLA-C motifs previously associated with KIR interaction and expression regulation are similar between both populations. Each allele group is associated with specific regulatory sequences, reflecting the high linkage disequilibrium along the entire HLA-C locus in both populations.

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.

Modelling and measuring intracellular competition for finite resources during gene expression

Dissecting the competition between genes for shared expressional resources is of fundamental importance for understanding the interplay between cellular components. Owing to the relationship between gene expression and cellular fitness, genomes are shaped by evolution to improve resource allocation. Whereas experimental approaches to investigate intracellular competition require technical resources and human expertise, computational models and in silico simulations allow vast numbers of experiments to be carried out and controlled easily, and with significantly reduced costs. Thus, modelling competition has a pivotal role in understanding the effects of competition on the biophysics of the cell. In this article, we review various computational models proposed to describe the different types of competition during gene expression. We also present relevant synthetic biology experiments and their biotechnological implications, and discuss the open questions in the field.

Role of microRNA 690 in Mediating Angiotensin II Effects on Inflammation and Endoplasmic Reticulum Stress

Overactivation of the renin–angiotensin system (RAS) during obesity disrupts adipocyte metabolic homeostasis and induces endoplasmic reticulum (ER) stress and inflammation; however, underlying mechanisms are not well known. We propose that overexpression of angiotensinogen (Agt), the precursor protein of RAS in adipose tissue or treatment of adipocytes with Angiotensin II (Ang II), RAS bioactive hormone, alters specific microRNAs (miRNA), that target ER stress and inflammation leading to adipocyte dysfunction. Epididymal white adipose tissue (WAT) from B6 wild type (Wt) and transgenic male mice overexpressing Agt (Agt-Tg) in adipose tissue and adipocytes treated with Ang II were used. Small RNA sequencing and microarray in WAT identified differentially expressed miRNAs and genes, out of which miR-690 and mitogen-activated protein kinase kinase 3 (MAP2K3) were validated as significantly up- and down-regulated, respectively, in Agt-Tg, and in Ang II-treated adipocytes compared to respective controls. Additionally, the direct regulatory role of miR-690 on MAP2K3 was confirmed using mimic, inhibitors and dual-luciferase reporter assay. Downstream protein targets of MAP2K3 which include p38, NF-κB, IL-6 and CHOP were all reduced. These results indicate a critical post-transcriptional role for miR-690 in inflammation and ER stress. In conclusion, miR-690 plays a protective function and could be a useful target to reduce obesity.

Multi-Omic Regulation of the PAM50 Gene Signature in Breast Cancer Molecular Subtypes

Breast cancer is a disease that exhibits heterogeneity that goes from the genomic to the clinical levels. This heterogeneity is thought to be captured (at least partially) by the so-called breast cancer molecular subtypes. These molecular subtypes were initially defined based on the unsupervised clustering of gene expression and its correlate with histological, morphological, phenotypic and clinical features already known. Later, a 50-gene signature, PAM50, was defined in order to identify the biological subtype of a given sample within the clinical setting. The PAM50 signature was obtained by the use of unsupervised statistical methods, and therefore no limitation was set on the biological relevance (or lack of) of the selected genes beyond its predictive capacity. An open question that remains is what are the regulatory elements that drive the various expression behaviors of this set of genes in the different molecular subtypes. This question becomes more relevant as the measurement of more biological layers of regulation becomes accessible. In this work, we analyzed the gene expression regulation of the 50 genes in the PAM50 signature, in terms of (a) gene co-expression, (b) transcription factors, (c) micro-RNAs, and (d) methylation. Using data from the Cancer Genome Atlas (TCGA) for the Luminal A and B, Basal, and HER2-enriched molecular subtypes as well as normal tumor adjacent tissue, we identified predictors for gene expression through the use of an elastic net model. We compare and contrast the sets of identified regulators for the gene signature in each molecular subtype, and systematically compare them to current literature. We also identified a unique set of predictors for the expression of genes in the PAM50 signature associated with each of the molecular subtypes. Most selected predictors are exclusive for a PAM50 gene and predictors are not shared across subtypes. There are only 13 coding transcripts and 2 miRNAs selected for the four subtypes. MiR-21 and miR-10b connect almost all the PAM50 genes in all the subtypes and normal tissue, but do it in an exclusive manner, suggesting a cancer switch from miR-10b coordination in normal tissue to miR-21. The PAM50 gene sets of selected predictors that enrich for a function across subtypes, support that different regulatory molecular mechanisms are taking place. With this study we aim to a wider understanding of the regulatory mechanisms that differentiate the expression of the PAM50 signature, which in turn could perhaps help understand the molecular basis of the differences between the molecular subtypes.

RNAInter in 2020: RNA interactome repository with increased coverage and annotation

Research on RNA-associated interactions has exploded in recent years, and increasing numbers of studies are not limited to RNA-RNA and RNA-protein interactions but also include RNA-DNA/compound interactions. To facilitate the development of the interactome and promote understanding of the biological functions and molecular mechanisms of RNA, we updated RAID v2.0 to RNAInter (RNA Interactome Database), a repository for RNA-associated interactions that is freely accessible at http://www.rna-society.org/rnainter/ or http://www.rna-society.org/raid/. Compared to RAID v2.0, new features in RNAInter include (i) 8-fold more interaction data and 94 additional species; (ii) more definite annotations organized, including RNA editing/localization/modification/structure and homology interaction; (iii) advanced functions including fuzzy/batch search, interaction network and RNA dynamic expression and (iv) four embedded RNA interactome tools: RIscoper, IntaRNA, PRIdictor and DeepBind. Consequently, RNAInter contains >41 million RNA-associated interaction entries, involving more than 450 thousand unique molecules, including RNA, protein, DNA and compound. Overall, RNAInter provides a comprehensive RNA interactome resource for researchers and paves the way to investigate the regulatory landscape of cellular RNAs.

Computational Network Analysis Identifies Evolutionarily Conserved miRNA Gene Interactions Potentially Regulating Immune Response in Bovine Trypanosomosis

Bovine trypanosomosis is a devastating disease that causes huge economic loss to the global cattle industry on a yearly basis. Selection of accurate biomarkers are important in early disease diagnosis and treatment. Of late, micro-RNAs (miRNAs) are becoming the most useful biomarkers for both infectious and non-infectious diseases in humans, but this is not the case in animals. miRNAs are non-coding RNAs that regulate gene expression through binding to the 3'-, 5'-untranslated regions (UTR) or coding sequence (CDS) region of one or more target genes. The molecular identification of miRNAs that regulates the expression of immune genes responding to bovine trypanosomosis is poorly defined, as is the possibility that these miRNAs could serve as potential biomarkers for disease diagnosis and treatment currently unknown. To this end, we utilized in silico tools to elucidate conserved miRNAs regulating immune response genes during infection, in addition to cataloging significant genes. Based on the p value of 1.77E-32, we selected 25 significantly expressed immune genes. Using prediction analysis, we identified a total of 4,251 bovine miRNAs targeting these selected genes across the 3'UTR, 5'UTR and CDS regions. Thereafter, we identified candidate miRNAs based on the number of gene targets and their abundance at the three regions. In all, we found the top 13 miRNAs that are significantly conserved targeting 7 innate immune response genes, including bta-mir-2460, bta-mir-193a, bta-mir-2316, and bta-mir-2456. Our gene ontology analysis suggests that these miRNAs are involved in gene silencing, cellular protein modification process, RNA-induced silencing complex, regulation of humoral immune response mediated by circulating immunoglobulin and negative regulation of chronic inflammatory response, among others. In conclusion, this study identifies specific miRNAs that may be involved in the regulation of gene expression during bovine trypanosomosis. These miRNAs have the potential to be used as biomarkers in the animal and veterinary research community to facilitate the development of tools for early disease diagnosis/detection, drug targeting, and the rational design of drugs to facilitate disease treatment.

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/.

Systematic review regulatory principles of non-coding RNAs in cardiovascular diseases

Cardiovascular diseases (CVDs) continue to be a major cause of morbidity and mortality, and non-coding RNAs (ncRNAs) play critical roles in CVDs. With the recent emergence of high-throughput technologies, including small RNA sequencing, investigations of CVDs have been transformed from candidate-based studies into genome-wide undertakings, and a number of ncRNAs in CVDs were discovered in various studies. A comprehensive review of these ncRNAs would be highly valuable for researchers to get a complete picture of the ncRNAs in CVD. To address these knowledge gaps and clinical needs, in this review, we first discussed dysregulated ncRNAs and their critical roles in cardiovascular development and related diseases. Moreover, we reviewed >28 561 published papers and documented the ncRNA-CVD association benchmarking data sets to summarize the principles of ncRNA regulation in CVDs. This data set included 13 249 curated relationships between 9503 ncRNAs and 139 CVDs in 12 species. Based on this comprehensive resource, we summarized the regulatory principles of dysregulated ncRNAs in CVDs, including the complex associations between ncRNA and CVDs, tissue specificity and ncRNA synergistic regulation. The highlighted principles are that CVD microRNAs (miRNAs) are highly expressed in heart tissue and that they play central roles in miRNA-miRNA functional synergistic network. In addition, CVD-related miRNAs are close to one another in the functional network, indicating the modular characteristic features of CVD miRNAs. We believe that the regulatory principles summarized here will further contribute to our understanding of ncRNA function and dysregulation mechanisms in CVDs.

Alternative cleavage and polyadenylation in health and disease

Most human genes have multiple sites at which RNA 3' end cleavage and polyadenylation can occur, enabling the expression of distinct transcript isoforms under different conditions. Novel methods to sequence RNA 3' ends have generated comprehensive catalogues of polyadenylation (poly(A)) sites; their analysis using innovative computational methods has revealed how poly(A) site choice is regulated by core RNA 3' end processing factors, such as cleavage factor I and cleavage and polyadenylation specificity factor, as well as by other RNA-binding proteins, particularly splicing factors. Here, we review the experimental and computational methods that have enabled the global mapping of mRNA and of long non-coding RNA 3' ends, quantification of the resulting isoforms and the discovery of regulators of alternative cleavage and polyadenylation (APA). We highlight the different types of APA-derived isoforms and their functional differences, and illustrate how APA contributes to human diseases, including cancer and haematological, immunological and neurological diseases.

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.

anamiR: integrated analysis of MicroRNA and gene expression profiling

BACKGROUND

With advancements in high-throughput technologies, the cost of obtaining expression profiles of both mRNA and microRNA in the same individual has substantially decreased. Integrated analysis of these profiles can help to elucidate the functional effects of RNA expression in complex diseases, such as cancer. However, fundamental discrepancies are observed in the results from microRNA-mRNA target gene prediction algorithms, and few packages can be used to analyze microRNA and mRNA expression levels simultaneously.

RESULTS

To address these issues, an R package, anamiR, was developed. A total of 10 experimental/prediction databases were integrated. Two analytical functions are provided in anamiR, including the single marker test and functional gene set enrichment analysis, and several parameters can be changed by users. Here we demonstrate the potential application of the anamiR package to 2 publicly available microarray datasets.

CONCLUSION

The anamiR package is effective for an integrated analysis of both RNA and microRNA profiles. By characterizing biological functions and signaling pathways, this package helps identify dysregulated genes/miRNAs from biological and medical experiments. The source code and manual of the anamiR package are freely available at https://bioconductor.org/packages/release/bioc/html/anamiR.html .

Global identification of functional microRNA-mRNA interactions in Drosophila

MicroRNAs (miRNAs) are key mediators of post-transcriptional gene expression silencing. So far, no comprehensive experimental annotation of functional miRNA target sites exists in Drosophila. Here, we generated a transcriptome-wide in vivo map of miRNA-mRNA interactions in Drosophila melanogaster, making use of single nucleotide resolution in Argonaute1 (AGO1) crosslinking and immunoprecipitation (CLIP) data. Absolute quantification of cellular miRNA levels presents the miRNA pool in Drosophila cell lines to be more diverse than previously reported. Benchmarking two CLIP approaches, we identify a similar predictive potential to unambiguously assign thousands of miRNA-mRNA pairs from AGO1 interaction data at unprecedented depth, achieving higher signal-to-noise ratios than with computational methods alone. Quantitative RNA-seq and sub-codon resolution ribosomal footprinting data upon AGO1 depletion enabled the determination of miRNA-mediated effects on target expression and translation. We thus provide the first comprehensive resource of miRNA target sites and their quantitative functional impact in Drosophila.

Overexpression of microRNA‑101 causes anti‑tumor effects by targeting CREB1 in colon cancer

Accumulating evidence has demonstrated that aberrantly expressed microRNAs (miRNAs) are involved in the initiation and progression of numerous types of human cancer. Although a number of miRNAs have been demonstrated to be associated with the diagnosis, progression and prognosis of colon cancer, the function of miRNA‑101 (miR‑101) in colon cancer remains unclear, and the molecular mechanisms underlying the effects of miR‑101 in colon cancer require further investigation. The present study investigated the role of miR‑101 in colon cancer, and the results suggested that miR‑101 expression levels were significantly decreased in colorectal carcinoma tissues and in three types of colorectal cancer cell lines. Furthermore, overexpression of miR‑101 inhibited cell proliferation and migration in HT29 cells. The transcription factor cAMP responsive element binding protein 1 (CREB1) was identified to be a direct target of miR‑101 using a luciferase reporter assay, reverse transcription‑quantitative polymerase chain reaction analysis and western blot assay. miR‑101 overexpression in tumor xenografts in vivo decreased the expression levels of proliferating cell nuclear antigen and CREB1, and suppressed tumor growth. The present results suggested that miR‑101 may serve a role in colon cancer by directly targeting CREB1. Collectively, the present study may contribute to the development of improved diagnosis and prognostics for colon cancer.

Comprehensive Investigation of miRNome Identifies Novel Candidate miRNA-mRNA Interactions Implicated in T-Cell Acute Lymphoblastic Leukemia

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive malignancy originating from T-cell precursors. The genetic landscape of T-ALL has been largely characterized by next-generation sequencing. Yet, the transcriptome of miRNAs (miRNome) of T-ALL has been less extensively studied. Using small RNA sequencing, we characterized the miRNome of 34 pediatric T-ALL samples, including the expression of isomiRs and the identification of candidate novel miRNAs (not previously annotated in miRBase). For the first time, we show that immunophenotypic subtypes of T-ALL present different miRNA expression profiles. To extend miRNome characteristics in T-ALL (to 82 T-ALL cases), we combined our small RNA-seq results with data available in Gene Expression Omnibus. We report on miRNAs most abundantly expressed in pediatric T-ALL and miRNAs differentially expressed in T-ALL versus normal mature T-lymphocytes and thymocytes, representing candidate oncogenic and tumor suppressor miRNAs. Using eight target prediction algorithms and pathway enrichment analysis, we identified differentially expressed miRNAs and their predicted targets implicated in processes (defined in Gene Ontology and Kyoto Encyclopedia of Genes and Genomes) of potential importance in pathogenesis of T-ALL, including interleukin-6-mediated signaling, mTOR signaling, and regulation of apoptosis. We finally focused on hsa-mir-106a-363 cluster and functionally validated direct interactions of hsa-miR-20b-5p and hsa-miR-363-3p with 3' untranslated regions of their predicted targets (PTEN, SOS1, LATS2), overrepresented in regulation of apoptosis. hsa-mir-106a-363 is a paralogue of prototypic oncogenic hsa-mir-17-92 cluster with yet unestablished role in the pathogenesis of T-ALL. Our study provides a firm basis and data resource for functional analyses on the role of miRNA-mRNA interactions in T-ALL.

Large-scale identification of functional microRNA targeting reveals cooperative regulation of the hemostatic system

Essentials MicroRNAs (miRNAs) regulate the molecular networks controlling biological functions such as hemostasis. We utilized novel methods to analyze miRNA-mediated regulation of the hemostatic system. 52 specific miRNA interactions with 11 key hemostatic associated genes were identified. Functionality and drugability of miRNA-19b-3p against antithrombin were demonstrated in vivo. SUMMARY: Background microRNAs (miRNAs) confer robustness to complex molecular networks regulating biological functions. However, despite the involvement of miRNAs in almost all biological processes, and the importance of the hemostatic system for a multitude of actions in and beyond blood coagulation, the role of miRNAs in hemostasis is poorly defined. Objectives Here we comprehensively illuminate miRNA-mediated regulation of the hemostatic system in an unbiased manner. Methods In contrast to widely applied association studies, we used an integrative screening approach that combines functional aspects of miRNA silencing with biophysical miRNA interaction based on RNA pull-downs (miTRAP) coupled to next-generation sequencing. Results Examination of a panel of 27 hemostasis-associated gene 3'UTRs revealed the majority to possess substantial Dicer-dependent silencing capability, suggesting functional miRNA targeting. miTRAP revealed 150 specific miRNA interactions with 14 3'UTRs, of which 52, involving 40 miRNAs, were functionally confirmed. This includes cooperative miRNA regulation of key hemostatic genes comprising procoagulant (F7, F8, F11, FGA, FGG and KLKB1) and anticoagulant (SERPINA10, PROZ, SERPIND1 and SERPINC1) as well as fibrinolytic (PLG) components. Bioinformatic analysis of miRNA functionality reveals established and potential novel links between the hemostatic system and other pathologies, such as cancer, bone metabolism and renal function. Conclusions Our findings provide, along with an in-vivo proof of concept, deep insights into the network of miRNAs regulating the hemostatic system and present a foundation for biomarker discovery and novel targeted therapeutics for correction of de-regulated hemostasis and associated processes in the future. A repository of the miRNA targetome covering 14 hemostatic components is provided.

New miRNA Signature Heralds Human NK Cell Subsets at Different Maturation Steps: Involvement of miR-146a-5p in the Regulation of KIR Expression

Natural killer cells are cytotoxic innate lymphoid cells that play an important role for early host defenses against infectious pathogens and surveillance against tumor. In humans, NK cells may be divided in various subsets on the basis of the relative CD56 expression and of the low-affinity FcγRIIIA CD16. In particular, the two main NK cell subsets are represented by the CD56^bright/CD16^−/dim and the CD56^dim/CD16^bright NK cells. Experimental evidences indicate that CD56^bright and CD56^dim NK cells represent different maturative stages of the NK cell developmental pathway. We identified multiple miRNAs differentially expressed in CD56^bright/CD16⁻ and CD56^dim/CD16^bright NK cells using both univariate and multivariate analyses. Among these, we found a few miRNAs with a consistent differential expression in the two NK cell subsets, and with an intermediate expression in the CD56^bright/CD16^dim NK cell subset, representing a transitional step of maturation of NK cells. These analyses allowed us to establish the existence of a miRNA signature able to efficiently discriminate the two main NK cell subsets regardless of their surface phenotype. In addition, by analyzing the putative targets of representative miRNAs we show that hsa-miR-146a-5p, may be involved in the regulation of killer Ig-like receptor (KIR) expression. These results contribute to a better understanding of the physiologic significance of miRNAs in the regulation of the development/function of human NK cells. Moreover, our results suggest that hsa-miR-146a-5p targeting, resulting in KIR down-regulation, may be exploited to generate/increment the effect of NK KIR-mismatching against HLA-class I⁺ tumor cells and thus improve the NK-mediated anti-tumor activity.

Predicting microRNA targeting efficacy in Drosophila

Background

MicroRNAs (miRNAs) are short regulatory RNAs that derive from hairpin precursors. Important for understanding the functional roles of miRNAs is the ability to predict the messenger RNA (mRNA) targets most responsive to each miRNA. Progress towards developing quantitative models of miRNA targeting in Drosophila and other invertebrate species has lagged behind that of mammals due to the paucity of datasets measuring the effects of miRNAs on mRNA levels.

Results

We acquired datasets suitable for the quantitative study of miRNA targeting in Drosophila. Analyses of these data expanded the types of regulatory sites known to be effective in flies, expanded the mRNA regions with detectable targeting to include 5′ untranslated regions, and identified features of site context that correlate with targeting efficacy in fly cells. Updated evolutionary analyses evaluated the probability of conserved targeting for each predicted site and indicated that more than a third of the Drosophila genes are preferentially conserved targets of miRNAs. Based on these results, a quantitative model was developed to predict targeting efficacy in insects. This model performed better than existing models, and it drives the most recent version, v7, of TargetScanFly.

Conclusions

Our evolutionary and functional analyses expand the known scope of miRNA targeting in flies and other insects. The existence of a quantitative model that has been developed and trained using Drosophila data will provide a valuable resource for placing miRNAs into gene regulatory networks of this important experimental organism.

Electronic supplementary material

The online version of this article (10.1186/s13059-018-1504-3) contains supplementary material, which is available to authorized users.

A Filtering Method for Identification of Significant Target mRNAs of Coexpressed and Differentially Expressed MicroRNA Clusters

MicroRNA (miRNA) binding is primarily based on sequence, but structure-specific binding is also possible. Various prediction algorithms have been developed for predicting miRNA target genes; the results, however, have relatively high levels of false positives, and the degree of overlap between predicted targets from different methods is poor or null. We devised a new method for identifying significant miRNA target genes from an extensive list of predicted miRNA target gene relationships using hypergeometric distributions. We evaluated our method in statistical and semantic aspects using a common miRNA cluster from six solid tumors. Our method provides statistically and semantically significant miRNA target genes. Complementing target prediction algorithms with our proposed method may have a significant synergistic effect in finding and evaluating functional annotation and enrichment analysis for miRNA.

An innovative approach to predict immune-associated genes mutually targeted by cow and human milk microRNAs expression profiles

Aim:

Milk is rich in miRNAs - the endogenous small non-coding RNA responsible for gene post-transcriptional silencing. Milk miRNAs were previously evidenced to affect consumer’s immune response. While most studies relied on a few well-characterized milk miRNAs to relate their immunoregulatory roles on target genes among mammals, this study introduced a procedure to predict the target genes based on overall milk miRNA expression profiles - the miRNome data of cow and human.

Materials and Methods:

Cow and human milk miRNome expression datasets of cow and human milk lipids at 2, 4, and 6 months of lactation periods were preprocessed and predicted for their target genes using TargetScanHuman. Enrichment analysis was performed using target genes to extract the immune-associated gene ontology (GO) terms shared between the two species. The genes within these terms with more than 50 different miRNAs of each species targeting were selected and reviewed for their immunological functions.

Results:

A total of 146 and 129 miRNAs were identified in cow and human milk with several miRNAs reproduced from other previous reports. Enrichment analysis revealed nine immune-related GO terms shared between cow and human (adjusted p≤0.01). There were 14 genes related to these terms with more than 50 miRNA genes of each species targeting them. These genes were evidenced for their major roles in lymphocyte stimulation and differentiation.

Conclusion:

A novel procedure to determine mutual immune-associated genes targeted by milk miRNAs was demonstrated using cow and human milk miRNome data. As far as we know, this was the 1st time that milk miRNA target genes had been identified based on such cross-species approach. Hopefully, the introduced strategy should hereby facilitate a variety of cross-species miRNA studies in the future.

Single-cell mRNA profiling reveals the hierarchical response of miRNA targets to miRNA induction

miRNAs are small RNAs that regulate gene expression post-transcriptionally. By repressing the translation and promoting the degradation of target mRNAs, miRNAs may reduce the cell-to-cell variability in protein expression, induce correlations between target expression levels, and provide a layer through which targets can influence each other's expression as "competing RNAs" (ceRNAs). However, experimental evidence for these behaviors is limited. Combining mathematical modeling with RNA sequencing of individual human embryonic kidney cells in which the expression of two distinct miRNAs was induced over a wide range, we have inferred parameters describing the response of hundreds of miRNA targets to miRNA induction. Individual targets have widely different response dynamics, and only a small proportion of predicted targets exhibit high sensitivity to miRNA induction. Our data reveal for the first time the response parameters of the entire network of endogenous miRNA targets to miRNA induction, demonstrating that miRNAs correlate target expression and at the same time increase the variability in expression of individual targets across cells. The approach is generalizable to other miRNAs and post-transcriptional regulators to improve the understanding of gene expression dynamics in individual cell types.

A data-driven, knowledge-based approach to biomarker discovery: application to circulating microRNA markers of colorectal cancer prognosis

Recent advances in high-throughput technologies have provided an unprecedented opportunity to identify molecular markers of disease processes. This plethora of complex-omics data has simultaneously complicated the problem of extracting meaningful molecular signatures and opened up new opportunities for more sophisticated integrative and holistic approaches. In this era, effective integration of data-driven and knowledge-based approaches for biomarker identification has been recognised as key to improving the identification of high-performance biomarkers, and necessary for translational applications. Here, we have evaluated the role of circulating microRNA as a means of predicting the prognosis of patients with colorectal cancer, which is the second leading cause of cancer-related death worldwide. We have developed a multi-objective optimisation method that effectively integrates a data-driven approach with the knowledge obtained from the microRNA-mediated regulatory network to identify robust plasma microRNA signatures which are reliable in terms of predictive power as well as functional relevance. The proposed multi-objective framework has the capacity to adjust for conflicting biomarker objectives and to incorporate heterogeneous information facilitating systems approaches to biomarker discovery. We have found a prognostic signature of colorectal cancer comprising 11 circulating microRNAs. The identified signature predicts the patients' survival outcome and targets pathways underlying colorectal cancer progression. The altered expression of the identified microRNAs was confirmed in an independent public data set of plasma samples of patients in early stage vs advanced colorectal cancer. Furthermore, the generality of the proposed method was demonstrated across three publicly available miRNA data sets associated with biomarker studies in other diseases.

RBiomirGS: an all-in-one miRNA gene set analysis solution featuring target mRNA mapping and expression profile integration

Background

With the continuous discovery of microRNA's (miRNA) association with a wide range of biological and cellular processes, expression profile-based functional characterization of such post-transcriptional regulation is crucial for revealing its significance behind particular phenotypes. Profound advancement in bioinformatics has been made to enable in depth investigation of miRNA's role in regulating cellular and molecular events, resulting in a huge quantity of software packages covering different aspects of miRNA functional analysis. Therefore, an all-in-one software solution is in demand for a comprehensive yet highly efficient workflow. Here we present RBiomirGS, an R package for a miRNA gene set (GS) analysis.

Methods

The package utilizes multiple databases for target mRNA mapping, estimates miRNA effect on the target mRNAs through miRNA expression profile and conducts a logistic regression-based GS enrichment. Additionally, human ortholog Entrez ID conversion functionality is included for target mRNAs.

Results

By incorporating all the core steps into one package, RBiomirGS eliminates the need for switching between different software packages. The modular structure of RBiomirGS enables various access points to the analysis, with which users can choose the most relevant functionalities for their workflow.

Conclusions

With RBiomirGS, users are able to assess the functional significance of the miRNA expression profile under the corresponding experimental condition by minimal input and intervention. Accordingly, RBiomirGS encompasses an all-in-one solution for miRNA GS analysis. RBiomirGS is available on GitHub (http://github.com/jzhangc/RBiomirGS). More information including instruction and examples can be found on website (http://kenstoreylab.com/?page_id=2865).

Methods for Using Small Non-Coding RNAs to Improve Recombinant Protein Expression in Mammalian Cells

The ability to produce recombinant proteins by utilizing different “cell factories” revolutionized the biotherapeutic and pharmaceutical industry. Chinese hamster ovary (CHO) cells are the dominant industrial producer, especially for antibodies. Human embryonic kidney cells (HEK), while not being as widely used as CHO cells, are used where CHO cells are unable to meet the needs for expression, such as growth factors. Therefore, improving recombinant protein expression from mammalian cells is a priority, and continuing effort is being devoted to this topic. Non-coding RNAs are RNA segments that are not translated into a protein and often have a regulatory role. Since their discovery, major progress has been made towards understanding their functions. Non-coding RNA has been investigated extensively in relation to disease, especially cancer, and recently they have also been used as a method for engineering cells to improve their protein expression capability. In this review, we provide information about methods used to identify non-coding RNAs with the potential of improving recombinant protein expression in mammalian cell lines.

Construction of an oesophageal cancer-specific ceRNA network based on miRNA, lncRNA, and mRNA expression data

AIM

To explore the expression profiles of microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and mRNAs in oesophageal squamous cell carcinoma (ESCC) in order to construct an oesophageal cancer-specific competing endogenous RNA (ceRNA) network.

METHODS

In this work, the expression data of miRNAs, lncRNAs, and mRNAs in ESCC were obtained. An oesophageal cancer-specific ceRNA network was then constructed and investigated.

RESULTS

CeRNAs have the ability to reduce the targeting activity of miRNAs, leading to the de-repression of specific mRNAs with common miRNA response elements. CeRNA interactions have a critical effect in gene regulation and cancer development.

CONCLUSION

This study suggests a novel perspective on potential oesophageal cancer mechanisms as well as novel pathways for modulating ceRNA networks for treating cancers.

Overexpression of Exportin-5 Overrides the Inhibitory Effect of miRNAs Regulation Control and Stabilize Proteins via Posttranslation Modifications in Prostate Cancer

Although XPO5 has been characterized to have tumor-suppressor features in the miRNA biogenesis pathway, the impact of altered expression of XPO5 in cancers is unexplored. Here we report a novel "oncogenic" role of XPO5 in advanced prostate cancer. Using prostate cancer models, we found that excess levels of XPO5 override the inhibitory effect of the canoncial miRNA-mRNA regulation, resulting in a global increase in proteins expression. Importantly, we found that decreased expression of XPO5 could promote an increase in proteasome degradation, whereas overexpression of XPO5 leads to altered protein posttranslational modification via hyperglycosylation, resulting in cellular protein stability. We evaluated the therapeutic advantage of targeting XPO5 in prostate cancer and found that knocking down XPO5 in prostate cancer cells suppressed cellular proliferation and tumor development without significantly impacting normal fibroblast cells survival. To our knowledge, this is the first report describing the oncogenic role of XPO5 in overriding the miRNAs regulation control. Furthermore, we believe that these findings will provide an explanation as to why, in some cancers that express higher abundance of mature miRNAs, fail to suppress their potential protein targets.