Combining Results from Distinct MicroRNA Target Prediction Tools Enhances the Performance of Analyses

MicroRNA Transcriptomes Reveal Prevalence of Rare and Species-Specific Arm Switching Events During Zebrafish Ontogenesis

In metazoans, microRNAs (miRNAs) are essential regulators of gene expression, affecting critical cellular processes from differentiation and proliferation, to homeostasis. During miRNA biogenesis, the miRNA strand that loads onto the RNA-induced Silencing Complex (RISC) can vary, leading to changes in gene targeting and modulation of biological pathways. To investigate the impact of these "arm switching" events on gene regulation, we analyzed a diverse range of tissues and developmental stages in zebrafish by comparing 5p and 3p arms accumulation dynamics between embryonic developmental stages, adult tissues, and sexes. We also compared variable arm usage patterns observed in zebrafish to other vertebrates including arm switching data from fish, birds, and mammals. Our comprehensive analysis revealed that variable arm usage events predominantly take place during embryonic development. It is also noteworthy that isomiR occurrence correlates to changes in arm selection evidencing an important role of microRNA distinct isoforms in reinforcing and modifying gene regulation by promoting dynamics switches on miRNA 5p and 3p arms accumulation. Our results shed new light on the emergence and coordination of gene expression regulation and pave the way for future investigations in this field.

microRNAs, oxidative stress, and genotoxicity as the main inducers in the pathobiology of cancer development

Cancer is one of the most serious leading causes of death in the world. Many eclectic factors are involved in cancer progression including genetic and epigenetic alongside environmental ones. In this account, the performance and fluctuations of microRNAs are significant in cancer diagnosis and treatment, particularly as diagnostic biomarkers in oncology. So, microRNAs manage and control the gene expression after transcription by mRNA degradation, or also they can inhibit their translation. Conspicuously, these molecular structures take part in controlling the cellular, physiological and pathological functions, which many of them can accomplish as tumor inhibitors or oncogenes. Relatively, Oxidative stress is defined as the inequality between the creation of reactive oxygen species (ROS) and the body's ability to detoxify the reactive mediators or repair the resulting injury. ROS and microRNAs have been recognized as main cancer promoters and possible treatment targets. Importantly, genotoxicity has been established as the primary reason for many diseases as well as several malignancies. The procedures have no obvious link with mutagenicity and influence the organization, accuracy of the information, or fragmentation of DNA. Conclusively, mutations in these patterns can lead to carcinogenesis. In this review article, we report the impressive and practical roles of microRNAs, oxidative stress, and genotoxicity in the pathobiology of cancer development in conjunction with their importance as reliable cancer biomarkers and their association with circulating miRNA, exosomes and exosomal miRNAs, RNA remodeling, DNA methylation, and other molecular elements in oncology.

In silico identification of papaya genome-encoded microRNAs to target begomovirus genes in papaya leaf curl disease

Papaya leaf curl disease (PaLCuD) is widespread and classified in the genus begomovirus (Geminiviridae), disseminated by the vector whitefly Bemisia tabaci. RNA interference (RNAi)-based antiviral innate immunity stands as a pivotal defense mechanism and biological process in limiting viral genomes to manage plant diseases. The current study aims to identify and analyze Carica Papaya locus-derived capa-microRNAs with predicted potential for targeting divergent begomovirus species-encoded mRNAs using a 'four integrative in silico algorithms' approach. This research aims to experimentally activate the RNAi catalytic pathway using in silico-predicted endogenous capa-miRNAs and create papaya varieties capable of assessing potential resistance against begomovirus species and monitoring antiviral capabilities. This study identified 48 predicted papaya locus-derived candidates from 23 miRNA families, which were further investigated for targeting begomovirus genes. Premised all the four algorithms combined, capa-miR5021 was the most anticipated miRNA followed by capa-miR482, capa-miR5658, capa-miR530b, capa-miR3441.2, and capa-miR414 'effective' papaya locus-derived candidate capa-miRNA and respected putative binding sites for targets at the consensus nucleotide position. It was predicted to bind and target mostly to AC1 gene of the complementary strand and the AV1 gene of the virion strand of different begomovirus isolates, which were associated with replication-associated protein and encapsidation, respectively, during PaLCuD. These miRNAs were also found targeting betaC1 gene of betasatellite which were associated with retardation in leaf growth and developmental abnormalities with severe symptoms during begomovirus infection. To validate target prediction accuracy, we created an integrated Circos plot for comprehensive visualization of host-virus interaction. In silico-predicted papaya genome-wide miRNA-mediated begomovirus target gene regulatory network corroborated interactions that permit in vivo analysis, which could provide biological material and valuable evidence, leading to the development of begomovirus-resistant papaya plants. The integrative nature of our research positions it at the forefront of efforts to ensure the sustainable cultivation of papaya, particularly in the face of evolving pathogenic threats. As we move forward, the knowledge gained from this study provides a solid foundation for continued exploration and innovation in the field of papaya virology, and to the best of our knowledge, this study represents a groundbreaking endeavor, undertaken for the first time in the context of PaLCuD research.

miR-1202 acts as anti-oncomiR in myeloid leukaemia by down-modulating GATA-1S expression

Transient abnormal myelopoiesis (TAM) is a Down syndrome-related pre-leukaemic condition characterized by somatic mutations in the haematopoietic transcription factor GATA-1 that result in exclusive production of its shorter isoform (GATA-1S). Given the common hallmark of altered miRNA expression profiles in haematological malignancies and the pro-leukaemic role of GATA-1S, we aimed to search for miRNAs potentially able to modulate the expression of GATA-1 isoforms. Starting from an in silico prediction of miRNA binding sites in the GATA-1 transcript, miR-1202 came into our sight as potential regulator of GATA-1 expression. Expression studies in K562 cells revealed that miR-1202 directly targets GATA-1, negatively regulates its expression, impairs GATA-1S production, reduces cell proliferation, and increases apoptosis sensitivity. Furthermore, data from TAM and myeloid leukaemia patients provided substantial support to our study by showing that miR-1202 down-modulation is accompanied by increased GATA-1 levels, with more marked effects on GATA-1S. These findings indicate that miR-1202 acts as an anti-oncomiR in myeloid cells and may impact leukaemogenesis at least in part by down-modulating GATA-1S levels.

An in silico approach to identify potential downstream targets of miR-153 involved in Alzheimer's disease

Background: In recent years, microRNAs (miRNAs) have emerged as key players in the pathophysiology of multiple diseases including Alzheimer's disease (AD). Messenger RNA (mRNA) targeting for regulation of gene expression by miRNAs has been implicated in the annotation of disease pathophysiology as well as in the explication of their starring role in contemporary therapeutic interventions. One such miRNA is miR-153 which mediates the survival of cortical neurons and inhibits plaque formation. However, the core mRNA targets of miR-153 have not been fully illustrated. Objective: The present study aimed to elucidate the potential involvement of miR-153 in AD pathogenesis and to reveal its downstream targets. Methods: miRanda was used to identify AD-associated targets of miR-153. TargetScan, PicTar, miRmap, and miRDB were further used to validate these targets. STRING 12 was employed to assess the protein-protein interaction network while Gene ontology (GO) analysis was carried out to identify the molecular functions exhibited by these gene targets. Results: In silico analysis using miRanda predicted five important AD-related targets of miR-153, including APP, SORL1, PICALM, USF1, and PSEN1. All five target genes are negatively regulated by miR-153 and are substantially involved in AD pathogenesis. A protein interaction network using STRING 12 uncovered 30 potential interacting partners for SORL1, PICALM, and USF1. GO analysis revealed that miR-153 target genes play a critical role in neuronal survival, differentiation, exon guidance, amyloid precursor protein processing, and synapse formation. Conclusion: These findings unravel the potential role of miR-153 in the pathogenesis of AD and provide the basis for forthcoming experimental studies.

Circulatory extracellular vesicle derived miR-195-5p promotes cellular apoptosis and suppresses cell proliferation in the buffalo endometrial primary cell culture

In pregnant animals, communication between the mother and conceptus occurs via extracellular vesicles (EVs) that carry several biomolecules such as nucleic acids (miRNAs, mRNAs), proteins, and lipids. At the time of implantation, the endometrium undergoes several morphological and physiological changes, such as angiogenesis, apoptosis, and cell proliferation regulation at the implantation site, to attain a receptive state. This study was conducted to detect pregnancy-specific miRNAs derived from extracellular vesicles in the systemic circulation of Bubalus bubalis (water buffalo) and to assess their functional significance in the modulation of endometrial primary cells. The extracellular vesicles were isolated from the blood plasma using a precipitation-based method and further characterized by various methods such as Differential light scattering, Nanoparticle tracking assay, Western blot, and transmission electron microscopy. The relative expression of the selected extracellular vesicles associated miRNAs (EV-miRNA) at different intervals (days 15, 19, 25, and 30) post artificial insemination (AI) was analyzed using RT-qPCR, and expression of miR-195-5p was found to be significantly higher (P < 0.01) in pregnant animals on day 19 post AI (implantation window) as compared to day 15 post AI. The elevated expression might indicate the involvement of this miRNA in the maternal-conceptus cross-talk occurring during the implantation period. The KEGG pathway enrichment and Gene Ontology analyses of the miR-195-5p target genes revealed that these were mostly involved in the PI3-Akt, MAPK, cell cycle, ubiquitin-mediated proteolysis, and mTOR signaling pathways, which are related to the regulation of cell proliferation. Transfecting the in vitro cultured cells with miR-195-5p mimic significantly suppressed (P < 0.05) the expression of its target genes such as YWHAQ, CDC27, AKT-3, FGF-7, MAPK8, SGK1, VEGFA, CACAND1, CUL2, MKNK1, and CACAN2D1. Furthermore, the downregulation of the miR-195-5p target genes was positively correlated with a significant increase in the apoptotic rate and a decrease in the proliferation. In conclusion, the current findings provide vital information on the presence of EV miR-195-5p in maternal circulation during the implantation window indicating its important role in the modulation of buffalo endometrium epithelial cells via promoting cell death. Altogether, the milieu of miR-195-5p may serve as a novel and potential molecular factor facilitating the implantation of the early embryo during the establishment of pregnancy in buffaloes. Thus, miR-195-5p may be identified as a unique circulatory EV biomarker related to establishing pregnancy in buffaloes as early as day 19 post-AI.

Insights into Online microRNA Bioinformatics Tools

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

In Silico Identification of Cassava Genome-Encoded MicroRNAs with Predicted Potential for Targeting the ICMV-Kerala Begomoviral Pathogen of Cassava

Cassava mosaic disease (CMD) is caused by several divergent species belonging to the genus Begomovirus (Geminiviridae) transmitted by the whitefly Bemisia tabaci cryptic species group. In India and other parts of Asia, the Indian cassava mosaic virus-Kerala (ICMV-Ker) is an emergent begomovirus of cassava causing damage that results in reduced yield loss and tuber quality. Double-stranded RNA-mediated interference (RNAi) is an evolutionary conserved mechanism in eukaryotes and highly effective, innate defense system to inhibit plant viral replication and/or translation. The objective of this study was to identify and characterize cassava genome-encoded microRNAs (mes-miRNA) that are predicted to target ICMV-Ker ssDNA-encoded mRNAs, based on four in silico algorithms: miRanda, RNA22, Tapirhybrid, and psRNA. The goal is to deploy the predicted miRNAs to trigger RNAi and develop cassava plants with resistance to ICMV-Ker. Experimentally validated mature cassava miRNA sequences (n = 175) were downloaded from the miRBase biological database and aligned with the ICMV-Ker genome. The miRNAs were evaluated for base-pairing with the cassava miRNA seed regions and to complementary binding sites within target viral mRNAs. Among the 175 locus-derived mes-miRNAs evaluated, one cassava miRNA homolog, mes-miR1446a, was identified to have a predicted miRNA target binding site, at position 2053 of the ICMV-Ker genome. To predict whether the cassava miRNA might bind predicted ICMV-Ker mRNA target(s) that could disrupt viral infection of cassava plants, a cassava locus-derived miRNA-mRNA regulatory network was constructed using Circos software. The in silico-predicted cassava locus-derived mes-miRNA-mRNA network corroborated interactions between cassava mature miRNAs and the ICMV-Ker genome that warrant in vivo analysis, which could lead to the development of ICMV-Ker resistant cassava plants.

Global and precise identification of functional miRNA targets in mESCs by integrative analysis

MicroRNA (miRNA) loaded Argonaute (AGO) complexes regulate gene expression via direct base pairing with their mRNA targets. Previous works suggest that up to 60% of mammalian transcripts might be subject to miRNA‐mediated regulation, but it remains largely unknown which fraction of these interactions are functional in a specific cellular context. Here, we integrate transcriptome data from a set of miRNA‐depleted mouse embryonic stem cell (mESC) lines with published miRNA interaction predictions and AGO‐binding profiles. Using this integrative approach, combined with molecular validation data, we present evidence that < 10% of expressed genes are functionally and directly regulated by miRNAs in mESCs. In addition, analyses of the stem cell‐specific miR‐290‐295 cluster target genes identify TFAP4 as an important transcription factor for early development. The extensive datasets developed in this study will support the development of improved predictive models for miRNA‐mRNA functional interactions.

Deciphering miR-520c-3p as a probable target for immunometabolism in non-small cell lung cancer using systems biology approach

Background: Non-small cell lung cancer (NSCLC) is considered to have more than 80% of all lung cancer cases, making it the leading cause of cancer-related deaths globally. MicroRNA (miRNA) deregulation has been seen often in NSCLC and has been linked to the disease’s genesis, progression, and metastasis via affecting their target genes.

Materials and Methods: Our study focused on the functionality of down-regulated miRNAs in NSCLC. For this study, we used 91 miRNAs reported to be down-regulated in NSCLC. The targets of these miRNAs were chosen from miRNA databases with functionality in NSCLC, including miRBase, miRDB, miRTV, and others. Inter-regulatory miRNA-NSCLC networks were generated. Simulated annealing was used to improve the network’s resilience and understandability. GSEA was used to examine 24607 genes reported experimentally in order to gain physiologically relevant information about the target miR-520c-3p.

Results: The study revealed functional prominence on miR-520c-3p, down-regulated during NSCLC. The involvement of miR-520c-3p in the PI3K/AKT/mTOR signaling pathway was recognized.

Conclusions: The therapeutic usage by designing a synthetic circuit of miR-520c-3p was explored, which may help in suppressing tumors in NSCLC. Our study holds promise for the successful deployment of currently proposed miRNA-based therapies for malignant disorders, which are still in the early pre-clinical stages of development.

Differential Effects of APOE Genotype on MicroRNA Cargo of Cerebrospinal Fluid Extracellular Vesicles in Females With Alzheimer's Disease Compared to Males

Multiple biological factors, including age, sex, and genetics, influence Alzheimer's disease (AD) risk. Of the 6.2 million Americans living with Alzheimer's dementia in 2021, 3.8 million are women and 2.4 million are men. The strongest genetic risk factor for sporadic AD is apolipoprotein E-e4 (APOE-e4). Female APOE-e4 carriers develop AD more frequently than age-matched males and have more brain atrophy and memory loss. Consequently, biomarkers that are sensitive to biological risk factors may improve AD diagnostics and may provide insight into underlying mechanistic changes that could drive disease progression. Here, we have assessed the effects of sex and APOE-e4 on the miRNA cargo of cerebrospinal fluid (CSF) extracellular vesicles (EVs) in AD. We used ultrafiltration (UF) combined with size exclusion chromatography (SEC) to enrich CSF EVs (e.g., Flotillin+). CSF EVs were isolated from female and male AD or controls (CTLs) that were either APOE-e3,4 or -e3,3 positive (n = 7/group, 56 total). MiRNA expression levels were quantified using a custom TaqMan™ array that assayed 190 miRNAs previously found in CSF, including 25 miRNAs that we previously validated as candidate AD biomarkers. We identified changes in the EV miRNA cargo that were affected by both AD and sex. In total, four miRNAs (miR-16-5p, -331-3p, -409-3p, and -454-3p) were significantly increased in AD vs. CTL, independent of sex and APOE-e4 status. Pathway analysis of the predicted gene targets of these four miRNAs with identified pathways was highly relevant to neurodegeneration (e.g., senescence and autophagy). There were also three miRNAs (miR-146b-5p, -150-5p, and -342-3p) that were significantly increased in females vs. males, independent of disease state and APOE-e4 status. We then performed a statistical analysis to assess the effect of APOE genotype in AD within each sex and found that APOE-e4 status affects different subsets of CSF EV miRNAs in females vs. males. Together, this study demonstrates the complexity of the biological factors associated with AD risk and the impact on EV miRNAs, which may contribute to AD pathophysiology.

Circular RNA Profiles in Viremia and ART Suppression Predict Competing circRNA–miRNA–mRNA Networks Exclusive to HIV-1 Viremic Patients

Since the onset of the HIV-1/AIDS epidemic in 1981, 75 million people have been infected with the virus, and the disease remains a public health crisis worldwide. Circular RNAs (circRNAs) are derived from excised exons and introns during backsplicing, a form of alternative splicing. The relevance of unconventional, non-capped, and non-poly(A) transcripts to transcriptomics studies remains to be routinely investigated. Knowledge gaps to be filled are the interface between host-encoded circRNAs and viral replication in chronically progressed patients and upon treatment with antiviral drugs. We implemented a bioinformatic pipeline and repurpose publicly archived RNA sequence reads from the blood of 19 HIV-1-positive patients that previously compared transcriptomes during viremia and viremia suppression by antiretroviral therapy (ART). The in silico analysis identified viremic patients’ circRNA that became undetectable after ART. The circRNAs originated from a subset of host genes enriched in the HDAC biological pathway. These circRNAs and parental mRNAs held in common a small collection of miRNA response elements (MREs), some of which were present in HIV-1 mRNAs. The function of the MRE-containing target mRNA enriched the RNA polymerase II GO pathway. To visualize the interplay between individual circRNA–miRNA–target mRNA, important for HIV-1 and potentially other diseases, an Interactive Circos tool was developed to efficiently parse the intricately competing endogenous network of circRNA–miRNA–mRNA interactions originating from seven circRNA singled out in viremic versus non-viremic patients. The combined downregulation of the identified circRNAs warrants investigation as a novel antiviral targeting strategy.

Differences in PLA2 Constitution Distinguish the Venom of Two Endemic Brazilian Mountain Lanceheads, Bothrops cotiara and Bothrops fonsecai

Interspecific differences in snake venom compositions can result from distinct regulatory mechanisms acting in each species. However, comparative analyses focusing on identifying regulatory elements and patterns that led to distinct venom composition are still scarce. Among venomous snakes, Bothrops cotiara and Bothrops fonsecai represent ideal models to complement our understanding of the regulatory mechanisms of venom production. These recently diverged species share a similar specialized diet, habitat, and natural history, but each presents a distinct venom phenotype. Here, we integrated data from the venom gland transcriptome and miRNome and the venom proteome of B. fonsecai and B. cotiara to better understand the regulatory mechanisms that may be acting to produce differing venom compositions. We detected not only the presence of similar toxin isoforms in both species but also distinct expression profiles of phospholipases A2 (PLA2) and some snake venom metalloproteinases (SVMPs) and snake venom serine proteinases (SVSPs) isoforms. We found evidence of modular expression regulation of several toxin isoforms implicated in venom divergence and observed correlated expression of several transcription factors. We did not find strong evidence for miRNAs shaping interspecific divergence of the venom phenotypes, but we identified a subset of toxin isoforms whose final expression may be fine-tuned by specific miRNAs. Sequence analysis on orthologous toxins showed a high rate of substitutions between PLA2s, which indicates that these toxins may be under strong positive selection or represent paralogous toxins in these species. Our results support other recent studies in suggesting that gene regulation is a principal mode of venom evolution across recent timescales, especially among species with conserved ecotypes.

Computational Detection of MicroRNA Targets

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

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.

MiR 208a Regulates Mitochondrial Biogenesis in Metabolically Challenged Cardiomyocytes

Metabolic syndrome increases the risk for cardiovascular disease including metabolic cardiomyopathy that may progress to heart failure. The decline in mitochondrial metabolism is considered a critical pathogenic mechanism that drives this progression. Considering its cardiac specificity, we hypothesized that miR 208a regulates the bioenergetic metabolism in human cardiomyocytes exposed to metabolic challenges. We screened in silico for potential miR 208a targets focusing on mitochondrial outcomes, and we found that mRNA species for mediator complex subunit 7, mitochondrial ribosomal protein 28, stanniocalcin 1, and Sortin nexin 10 are rescued by the CRISPR deletion of miR 208a in human SV40 cardiomyocytes exposed to metabolic challenges (high glucose and high albumin-bound palmitate). These mRNAs translate into proteins that are involved in nuclear transcription, mitochondrial translation, mitochondrial integrity, and protein trafficking. MiR 208a suppression prevented the decrease in myosin heavy chain α isoform induced by the metabolic stress suggesting protection against a decrease in cardiac contractility. MiR 208a deficiency opposed the decrease in the mitochondrial biogenesis signaling pathway, mtDNA, mitochondrial markers, and respiratory properties induced by metabolic challenges. The benefit of miR 208a suppression on mitochondrial function was canceled by the reinsertion of miR 208a. In summary, miR 208a regulates mitochondrial biogenesis and function in cardiomyocytes exposed to diabetic conditions. MiR 208a may be a therapeutic target to promote mitochondrial biogenesis in chronic diseases associated with mitochondrial defects.

MicroRNAs hsa-miR-618 and hsa-miR-297 Might Modulate the Pleiotropic Effects Exerted by Statins in Endothelial Cells Through the Inhibition of ROCK2 Kinase: in-silico Approach

Several studies show that statin therapy improves endothelial function by cholesterol-independent mechanisms called “pleiotropic effects.” These are due to the inhibition of the RhoA/ROCK kinase pathway, its inhibition being an attractive atheroprotective treatment. In addition, recent work has shown that microRNAs, posttranscriptional regulators of gene expression, can affect the response of statins and their efficacy. For this reason, the objective of this study was to identify by bioinformatic analysis possible new microRNAs that could modulate the pleiotropic effects exerted by statins through the inhibition of ROCK kinases. A bioinformatic study was performed in which the differential expression of miRNAs in endothelial cells was compared under two conditions: Control and treated with simvastatin at 10 μM for 24 h, using a microarray. Seven miRNAs were differentially expressed, three up and four down. Within the up group, the miRNAs hsa-miR-618 and hsa-miR-297 present as a predicted target to ROCK2 kinase. Also, functional and enriched pathway analysis showed an association with mechanisms associated with atheroprotective effects. This work shows an in-silico approach of how posttranscriptional regulation mediated by miRNAs could modulate the pleiotropic effects exerted by statins on endothelial cells, through the inhibition of ROCK2 kinase and its effects.

Learning noncoding RNA biology from viruses

Insights into interactions between viral factors and the cellular machinery usually lead to discoveries concerning host cell biology. Thus, the gene expression field has historically relied on viral model systems to discover mechanisms underlying different cellular processes. In recent years, the functional characterization of the small nuclear noncoding RNAs expressed by the oncogenic Herpesvirus saimiri, called HSURs, resulted in the discovery of two mechanisms for the regulation of gene expression. HSUR1 and HSUR2 associate with host microRNAs, which are small noncoding RNAs that broadly regulate gene expression by binding to messenger RNAs. HSUR1 provided the first example of a process known as target-directed miRNA degradation that operates in cells to regulate miRNA populations. HSUR2 functions as a miRNA adaptor, uncovering an entirely new, indirect mechanism by which miRNAs can inhibit mRNA function. Here, I review the path that led to these discoveries and their implications and postulate new exciting questions about the functions of these fascinating viral noncoding RNAs.

Recent development of bioinformatics tools for microRNA target prediction

MicroRNAs (miRNAs) are central players that regulate the post-transcriptional processes of gene expression. Binding of miRNAs to target mRNAs can repress their translation by inducing the degradation or by inhibiting the translation of the target mRNAs. High-throughput experimental approaches for miRNA target identification are costly and time-consuming, depending on various factors. It is vitally important to develop the bioinformatics methods for accurately predicting miRNA targets. With the increase of RNA sequences in the post-genomic era, bioinformatics methods are being developed for miRNA studies specially for miRNA target prediction. This review summarizes the current development of state-of-the-art bioinformatics tools for miRNA target prediction, points out the progress and limitations of the available miRNA databases, and their working principles. Finally, we discuss the caveat and perspectives of the next-generation algorithms for the prediction of miRNA targets.

Global mRNA and miRNA Analysis Reveal Key Processes in the Initial Response to Infection with WSSV in the Pacific Whiteleg Shrimp

White Spot Disease (WSD) presents a major barrier to penaeid shrimp production. Mechanisms underlying White Spot Syndrome Virus (WSSV) susceptibility in penaeids are poorly understood due to limited information related to early infection. We investigated mRNA and miRNA transcription in Penaeus vannamei over 36 h following infection. Over this time course, 6192 transcripts and 27 miRNAs were differentially expressed—with limited differential expression from 3–12 h post injection (hpi) and a more significant transcriptional response associated with the onset of disease symptoms (24 hpi). During early infection, regulated processes included cytoskeletal remodelling and alterations in phagocytic activity that may assist WSSV entry and translocation, novel miRNA-induced metabolic shifts, and the downregulation of ATP-dependent proton transporter subunits that may impair cellular recycling. During later infection, uncoupling of the electron transport chain may drive cellular dysfunction and lead to high mortalities in infected penaeids. We propose that post-transcriptional silencing of the immune priming gene Dscam (downregulated following infections) by a novel shrimp miRNA (Pva-pmiR-78; upregulated) as a potential mechanism preventing future recognition of WSSV that may be suppressed in surviving shrimp. Our findings improve our understanding of WSD pathogenesis in P. vannamei and provide potential avenues for future development of prophylactics and treatments.

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

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

Comprehensive machine-learning-based analysis of microRNA-target interactions reveals variable transferability of interaction rules across species

BACKGROUND

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally via base-pairing with complementary sequences on messenger RNAs (mRNAs). Due to the technical challenges involved in the application of high-throughput experimental methods, datasets of direct bona fide miRNA targets exist only for a few model organisms. Machine learning (ML)-based target prediction models were successfully trained and tested on some of these datasets. There is a need to further apply the trained models to organisms in which experimental training data are unavailable. However, it is largely unknown how the features of miRNA-target interactions evolve and whether some features have remained fixed during evolution, raising questions regarding the general, cross-species applicability of currently available ML methods.

RESULTS

We examined the evolution of miRNA-target interaction rules and used data science and ML approaches to investigate whether these rules are transferable between species. We analyzed eight datasets of direct miRNA-target interactions in four species (human, mouse, worm, cattle). Using ML classifiers, we achieved high accuracy for intra-dataset classification and found that the most influential features of all datasets overlap significantly. To explore the relationships between datasets, we measured the divergence of their miRNA seed sequences and evaluated the performance of cross-dataset classification. We found that both measures coincide with the evolutionary distance between the compared species.

CONCLUSIONS

The transferability of miRNA-targeting rules between species depends on several factors, the most associated factors being the composition of seed families and evolutionary distance. Furthermore, our feature-importance results suggest that some miRNA-target features have evolved while others remained fixed during the evolution of the species. Our findings lay the foundation for the future development of target prediction tools that could be applied to "non-model" organisms for which minimal experimental data are available.

AVAILABILITY AND IMPLEMENTATION

The code is freely available at https://github.com/gbenor/TPVOD .

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.

Differential expression of miRNAs in the presence of B chromosome in the cichlid fish Astatotilapia latifasciata

BACKGROUND

B chromosomes (Bs) are extra elements observed in diverse eukaryotes, including animals, plants and fungi. Although Bs were first identified a century ago and have been studied in hundreds of species, their biology is still enigmatic. Recent advances in omics and big data technologies are revolutionizing the B biology field. These advances allow analyses of DNA, RNA, proteins and the construction of interactive networks for understanding the B composition and behavior in the cell. Several genes have been detected on the B chromosomes, although the interaction of B sequences and the normal genome remains poorly understood.

RESULTS

We identified 727 miRNA precursors in the A. latifasciata genome, 66% which were novel predicted sequences that had not been identified before. We were able to report the A. latifasciata-specific miRNAs and common miRNAs identified in other fish species. For the samples carrying the B chromosome (B⁺), we identified 104 differentially expressed (DE) miRNAs that are down or upregulated compared to samples without B chromosome (B^-) (p < 0.05). These miRNAs share common targets in the brain, muscle and gonads. These targets were used to construct a protein-protein-miRNA network showing the high interaction between the targets of differentially expressed miRNAs in the B⁺ chromosome samples. Among the DE-miRNA targets there are protein-coding genes reported for the B chromosome that are present in the protein-protein-miRNA network. Additionally, Gene Ontology (GO) terms related to nuclear matrix organization and response to stimulus are exclusive to DE miRNA targets of B⁺ samples.

CONCLUSIONS

This study is the first to report the connection of B chromosomes and miRNAs in a vertebrate species. We observed that the B chromosome impacts the miRNAs expression in several tissues and these miRNAs target several mRNAs involved with important biological processes.

Interplay between miRNAs and lncRNAs: Mode of action and biological roles in plant development and stress adaptation

Plants employ sophisticated mechanisms to control developmental processes and to cope with environmental changes at transcriptional and post-transcriptional levels. MicroRNAs (miRNAs) and long noncoding RNAs (lncRNAs), two classes of endogenous noncoding RNAs, are key regulators of gene expression in plants. Recent studies have identified the interplay between miRNAs and lncRNAs as a novel regulatory layer of gene expression in plants. On one hand, miRNAs target lncRNAs for the production of phased small interfering RNAs (phasiRNAs). On the other hand, lncRNAs serve as origin of miRNAs or regulate the accumulation or activity of miRNAs at transcription and post-transcriptional levels. Theses lncRNA-miRNA interplays are crucial for plant development, physiology and responses to biotic and abiotic stresses. In this review, we summarize recent advances in the biological roles, interaction mechanisms and computational predication methods of the interplay between miRNAs and lncRNAs in plants.

A comparative analysis of heart microRNAs in vertebrates brings novel insights into the evolution of genetic regulatory networks

BACKGROUND

During vertebrate evolution, the heart has undergone remarkable changes that lead to morphophysiological differences in the fully formed heart of these species, such as chamber septation, heart rate frequency, blood pressure, and cardiac output volume. Despite these differences, the heart developmental process is guided by a core gene set conserved across vertebrates. Nonetheless, the regulatory mechanisms controlling the expression of genes involved in heart development and maintenance are largely uncharted. MicroRNAs (miRNAs) have been described as important regulatory elements in several biological processes, including heart biology. These small RNA molecules are broadly conserved in sequence and genomic context in metazoans. Mutations may occur in miRNAs and/or genes that contribute to the establishment of distinct repertoires of miRNA-target interactions, thereby favoring the differential control of gene expression and, consequently, the origin of novel phenotypes. In fact, several studies showed that miRNAs are integrated into genetic regulatory networks (GRNs) governing specific developmental programs and diseases. However, studies integrating miRNAs in vertebrate heart GRNs under an evolutionary perspective are still scarce.

RESULTS

We comprehensively examined and compared the heart miRNome of 20 species representatives of the five major vertebrate groups. We found 54 miRNA families with conserved expression and a variable number of miRNA families with group-specific expression in fishes, amphibians, reptiles, birds, and mammals. We also detected that conserved miRNAs present higher expression levels and a higher number of targets, whereas the group-specific miRNAs present lower expression levels and few targets.

CONCLUSIONS

Both the conserved and group-specific miRNAs can be considered modulators orchestrating the core and peripheral genes of heart GRNs of vertebrates, which can be related to the morphophysiological differences and similarities existing in the heart of distinct vertebrate groups. We propose a hypothesis to explain evolutionary differences in the putative functional roles of miRNAs in the heart GRNs analyzed. Furthermore, we present new insights into the molecular mechanisms that could be helping modulate the diversity of morphophysiology in the heart organ of vertebrate species.

MicroRNA-367-3p induces apoptosis and suppresses migration of MCF-7 cells by downregulating the expression of human choline kinase α

Choline kinase (ChK) catalyzes the first step in the CDP-choline pathway for the synthesis of phosphatidylcholine. The α isoform of this enzyme is overexpressed in various types of cancer and its inhibition or downregulation has been applied as an anticancer strategy. In spite of increasing attention being paid to ChK expression, as well as its activity and inhibition in cancer, there are only limited studies available on the regulation of ChK, including its regulation by microRNAs (miRNAs/miRs). The dysregulation of gene expression by miRNAs is a common cause for carcinogenesis. In the present study, miR-367-3p was predicted to target the 3′-untranslated region (UTR) of the ChK α (chka) mRNA transcript. The binding of miR-367-3p to the 3′-UTR of chka was validated by a luciferase assay. The effects of the miR-367-3p mimic on chka gene and protein expression levels were determined by reverse transcription-quantitative polymerase chain reaction and western blot analysis, respectively. miR-367-3p significantly downregulated the expression of chka to ~60% of the negative control. Cells transfected with miR-367-3p exhibited higher levels of apoptosis and a lower cell migration compared with the control. To the best of our knowledge, the present study provided the first experimental evidence of the regulation of chka expression by miR-367-3p. The pro-apoptotic and suppressive effects of miR-367-3p on cell migration were similar to the anticancer effects resulting from the inhibition of ChK enzyme activity or the knockdown of chka gene expression by small interfering RNA. Therefore, these findings may potentially lead to the use of miR-367-3p in anticancer strategies that target ChK.

Integrated Analysis of Hub Genes and MicroRNAs in Human Placental Tissues from In Vitro Fertilization-Embryo Transfer

OBJECTIVE

Supraphysiological hormone exposure, in vitro culture and embryo transfer throughout the in vitro fertilization-embryo transfer (IVF-ET) procedures may affect placental development. The present study aimed to identify differences in genomic expression profiles between IVF-ET and naturally conceived placentals and to use this as a basis for understanding the underlying effects of IVF-ET on placental function.

METHODS

Full-term human placental tissues were subjected to next-generation sequencing to determine differentially expressed miRNAs (DEmiRs) and genes (DEGs) between uncomplicated IVF-ET assisted and naturally conceived pregnancies. Gene ontology (GO) enrichment analysis and transcription factor enrichment analysis were used for DEmiRs. MiRNA-mRNA interaction and protein-protein interaction (PPI) networks were constructed. In addition, hub genes were obtained by using the STRING database and Cytoscape. DEGs were analyzed using GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Differentially expressed miRNAs were validated through qRT-PCR.

RESULTS

Compared against natural pregnancies, 12 DEmiRs and 258 DEGs were identified in IVF-ET placental tissues. In a validation cohort, it was confirmed that hsa-miR-204-5p, hsa-miR-1269a, and hsa-miR-941 were downregulation, while hsa-miR-4286, hsa-miR-31-5p and hsa-miR-125b-5p were upregulation in IVF-ET placentas. Functional analysis suggested that these differentially expressed genes were significantly enriched in angiogenesis, pregnancy, PI3K-Akt and Ras signaling pathways. The miRNA-mRNA regulatory network revealed the contribution of 10 miRNAs and 109 mRNAs while EGFR was the most highly connected gene among ten hub genes in the PPI network.

CONCLUSION

Even in uncomplicated IVF-ET pregnancies, differences exist in the placental transcriptome relative to natural pregnancies. Many of the differentially expressed genes in IVF-ET are involved in essential placental functions, and moreover, they provide a ready resource of molecular markers to assess the association between placental function and safety in IVF-ET offspring.

miRNA Targets: From Prediction Tools to Experimental Validation

MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression in both animals and plants. By pairing to microRNA responsive elements (mREs) on target mRNAs, miRNAs play gene-regulatory roles, producing remarkable changes in several physiological and pathological processes. Thus, the identification of miRNA-mRNA target interactions is fundamental for discovering the regulatory network governed by miRNAs. The best way to achieve this goal is usually by computational prediction followed by experimental validation of these miRNA-mRNA interactions. This review summarizes the key strategies for miRNA target identification. Several tools for computational analysis exist, each with different approaches to predict miRNA targets, and their number is constantly increasing. The major algorithms available for this aim, including Machine Learning methods, are discussed, to provide practical tips for familiarizing with their assumptions and understanding how to interpret the results. Then, all the experimental procedures for verifying the authenticity of the identified miRNA-mRNA target pairs are described, including High-Throughput technologies, in order to find the best approach for miRNA validation. For each strategy, strengths and weaknesses are discussed, to enable users to evaluate and select the right approach for their interests.

Interactions and links among the noncoding RNAs in plants under stresses

The complex interplay among sRNAs, lncRNAs and circRNAs has been implicated in plants under biotic and abiotic stresses. Here, we review current advances in our understanding of ncRNA interactions and links, which have considerable potential for improving the agronomic traits and the environmental adaptability of plants. Plants can respond to biotic or abiotic stresses. To cope with various conditions, numerous intricate molecular regulatory mechanisms have evolved in plants. Noncoding RNAs (ncRNAs) can be divided into small noncoding RNAs (sRNAs), long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs). Emerging evidence has demonstrated that interplay among the ncRNAs acts as a novel layer in the regulatory mechanisms, which has attracted substantial interest. Links between sRNAs can affect plant immune responses and development in synergistic or antagonistic manners. Additionally, multiple interactions between lncRNAs and sRNAs are involved in crop breeding, disease resistance and high tolerance to environmental stresses. Here, we summarize current knowledge of the interactions and links among the ncRNAs in plant responses to stresses and the methods for identifying ncRNA interactions. Furthermore, challenges and prospects for further progress in elucidating ncRNA interactions and links are highlighted.

Methamphetamine use alters human plasma extracellular vesicles and their microRNA cargo: An exploratory study

Methamphetamine (MA) is the largest drug threat across the globe, with health effects including neurotoxicity and cardiovascular disease. Recent studies have begun to link microRNAs (miRNAs) to the processes related to MA use and addiction. Our studies are the first to analyse plasma EVs and their miRNA cargo in humans actively using MA (MA-ACT) and control participants (CTL). In this cohort we also assessed the effects of tobacco use on plasma EVs. We used vesicle flow cytometry to show that the MA-ACT group had an increased abundance of EV tetraspanin markers (CD9, CD63, CD81), but not pro-coagulant, platelet-, and red blood cell-derived EVs. We also found that of the 169 plasma EV miRNAs, eight were of interest in MA-ACT based on multiple statistical criteria. In smokers, we identified 15 miRNAs of interest, two that overlapped with the eight MA-ACT miRNAs. Three of the MA-ACT miRNAs significantly correlated with clinical features of MA use and target prediction with these miRNAs identified pathways implicated in MA use, including cardiovascular disease and neuroinflammation. Together our findings indicate that MA use regulates EVs and their miRNA cargo, and support that further studies are warranted to investigate their mechanistic role in addiction, recovery, and recidivism.

Regulatory Mechanisms of Epigenetic miRNA Relationships in Human Cancer and Potential as Therapeutic Targets

Simple Summary

By the virtue of targeting multiple genes, a microRNA (miRNA) can infer variable consequences on tumorigenesis by appearing as both a tumour suppressor and oncogene. miRNAs can regulate gene expression by modulating genome-wide epigenetic status of genes that are involved in various cancers. These miRNAs perform direct inhibition of key mediators of the epigenetic machinery, such as DNA methyltransferases (DNMTs) and histone deacetylases (HDACs) genes. Along with miRNAs gene expression, similar to other protein-coding genes, miRNAs are also controlled by epigenetic mechanisms. Overall, this reciprocal interaction between the miRNAs and the epigenetic architecture is significantly implicated in the aberrant expression of miRNAs detected in various human cancers. Comprehensive knowledge of the miRNA-epigenetic dynamics in cancer is essential for the discovery of novel anticancer therapeutics.

Abstract

Initiation and progression of cancer are under both genetic and epigenetic regulation. Epigenetic modifications including alterations in DNA methylation, RNA and histone modifications can lead to microRNA (miRNA) gene dysregulation and malignant cellular transformation and are hereditary and reversible. miRNAs are small non-coding RNAs which regulate the expression of specific target genes through degradation or inhibition of translation of the target mRNA. miRNAs can target epigenetic modifier enzymes involved in epigenetic modulation, establishing a trilateral regulatory “epi–miR–epi” feedback circuit. The intricate association between miRNAs and the epigenetic architecture is an important feature through which to monitor gene expression profiles in cancer. This review summarises the involvement of epigenetically regulated miRNAs and miRNA-mediated epigenetic modulations in various cancers. In addition, the application of bioinformatics tools to study these networks and the use of therapeutic miRNAs for the treatment of cancer are also reviewed. A comprehensive interpretation of these mechanisms and the interwoven bond between miRNAs and epigenetics is crucial for understanding how the human epigenome is maintained, how aberrant miRNA expression can contribute to tumorigenesis and how knowledge of these factors can be translated into diagnostic and therapeutic tool development.

Computational Methods and Software Tools for Functional Analysis of miRNA Data

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

Dynamical gene regulatory networks are tuned by transcriptional autoregulation with microRNA feedback

Concepts from dynamical systems theory, including multi-stability, oscillations, robustness and stochasticity, are critical for understanding gene regulation during cell fate decisions, inflammation and stem cell heterogeneity. However, the prevalence of the structures within gene networks that drive these dynamical behaviours, such as autoregulation or feedback by microRNAs, is unknown. We integrate transcription factor binding site (TFBS) and microRNA target data to generate a gene interaction network across 28 human tissues. This network was analysed for motifs capable of driving dynamical gene expression, including oscillations. Identified autoregulatory motifs involve 56% of transcription factors (TFs) studied. TFs that autoregulate have more interactions with microRNAs than non-autoregulatory genes and 89% of autoregulatory TFs were found in dual feedback motifs with a microRNA. Both autoregulatory and dual feedback motifs were enriched in the network. TFs that autoregulate were highly conserved between tissues. Dual feedback motifs with microRNAs were also conserved between tissues, but less so, and TFs regulate different combinations of microRNAs in a tissue-dependent manner. The study of these motifs highlights ever more genes that have complex regulatory dynamics. These data provide a resource for the identification of TFs which regulate the dynamical properties of human gene expression.

miRTil: An Extensive Repository for Nile Tilapia microRNA Next Generation Sequencing Data

Nile tilapia is the third most cultivated fish worldwide and a novel model species for evolutionary studies. Aiming to improve productivity and contribute to the selection of traits of economic impact, biotechnological approaches have been intensively applied to species enhancement. In this sense, recent studies have focused on the multiple roles played by microRNAs (miRNAs) in the post-transcriptional regulation of protein-coding genes involved in the emergence of phenotypes with relevance for aquaculture. However, there is still a growing demand for a reference resource dedicated to integrating Nile Tilapia miRNA information, obtained from both experimental and in silico approaches, and facilitating the analysis and interpretation of RNA sequencing data. Here, we present an open repository dedicated to Nile Tilapia miRNAs: the “miRTil database”. The database stores data on 734 mature miRNAs identified in 11 distinct tissues and five key developmental stages. The database provides detailed information about miRNA structure, genomic context, predicted targets, expression profiles, and relative 5p/3p arm usage. Additionally, miRTil also includes a comprehensive pre-computed miRNA-target interaction network containing 4936 targets and 19,580 interactions.

Circulating microRNA trafficking and regulation: computational principles and practice

Rapid advances in genomics discovery tools and a growing realization of microRNA's implication in intercellular communication have led to a proliferation of studies of circulating microRNA sorting and regulation across cells and different species. Although sometimes, reaching controversial scientific discoveries and conclusions, these studies have yielded new insights in the functional roles of circulating microRNA and a plethora of analytical methods and tools. Here, we consider this body of work in light of key computational principles underpinning discovery of circulating microRNAs in terms of their sorting and targeting, with the goal of providing practical guidance for applications that is focused on the design and analysis of circulating microRNAs and their context-dependent regulation. We survey a broad range of informatics methods and tools that are available to the researcher, discuss their key features, applications and various unsolved problems and close this review with prospects and broader implication of this field.

Identification of miRNA Master Regulators in Breast Cancer

Breast cancer is the neoplasm with the highest number of deaths in women. Although the molecular mechanisms associated with the development of this tumor have been widely described, metastatic disease has a high mortality rate. In recent years, several studies show that microRNAs or miRNAs regulate complex processes in different biological systems including cancer. In the present work, we describe a group of 61 miRNAs consistently over-expressed in breast cancer (BC) samples that regulate the breast cancer transcriptome. By means of data mining from TCGA, miRNA and mRNA sequencing data corresponding to 1091 BC patients and 110 normal adjacent tissues were downloaded and a miRNA-mRNA network was inferred. Calculations of their oncogenic activity demonstrated that they were involved in the regulation of classical cancer pathways such as cell cycle, PI3K-AKT, DNA repair, and k-Ras signaling. Using univariate and multivariate analysis, we found that five of these miRNAs could be used as biomarkers for the prognosis of overall survival. Furthermore, we confirmed the over-expression of two of them in 56 locally advanced BC samples obtained from the histopathological archive of the National Cancer Institute of Mexico, showing concordance with our previous bioinformatic analysis.

Ross River Virus Provokes Differentially Expressed MicroRNA and RNA Interference Responses in Aedes aegypti Mosquitoes

Alphaviruses are globally distributed and predominately transmitted by mosquitoes. Aedes species are common vectors for the clinically important alphaviruses-Chikungunya, Sindbis, and Ross River (RRV) viruses-with Aedes aegypti also being a vector for the flaviviruses dengue, Yellow Fever, and Zika viruses. Ae. aegypti was putatively implicated in the large 1979-1980 South Pacific Islands outbreak of RRV-the leading cause of arboviral disease in Australia today. The RNA interference (RNAi) defense response in mosquitoes involves a number of small RNAs, with their kinetics induced by alphaviruses being poorly understood, particularly at the tissue level. We compared the small RNA profiles between RRV-infected and noninfected Ae. aegypti midgut and fat body tissues at 2, 6, and 12 days post-inoculation (dpi). RRV induced an incremental RNAi response, yielding short interfering and P-element-induced-wimpy-testis (PIWI)-interacting RNAs. Fourteen host microRNAs were differentially expressed due to RRV with the majority in the fat body at 2 dpi. The largely congruent pattern of microRNA regulation with previous reports for alphaviruses and divergence from those for flaviviruses suggests a degree of conservation, whereas patterns of microRNA expression unique to this study provide novel insights into the tissuespecific hostvirus attributes of Ae. aegypti responses to this previously unexplored oldworld alphavirus.

A Day in the Life: Identification of Developmentally Regulated MicroRNAs in the Colorado Potato Beetle (Leptinotarsa decemlineata; Coleoptera: Chrysomelidae)

The Colorado potato beetle (Leptinotarsa decemlineata (Say)) is an important pest of the cultivated potato (Solanum tuberosum (L.) [Solanales: Solanaceae]). With its broad resistance toward commonly used insecticides, it is clear that more sophisticated control strategies are needed. Due to their importance in insect development, microRNAs (miRNAs) represent a potential tool to employ in insect control strategies. However, most studies conducted in this area have focused on model species with well-annotated genomes. In this study, next-generation sequencing was used to catalogue the miRNAs produced by L. decemlineata across all eight stages of its development, from eggs to adults. For most stages, the length of miRNAs peaked between 21 and 22 nt, though it was considerably longer for the egg stage (26 nt). Global profiling of miRNAs revealed three distinct developmental clusters: 1) egg stage; 2) early stage (first, second, and third instar); and 3) late stage (fourth instar, prepupae, pupae, and adult). We identified 86 conserved miRNAs and 33 bonafide novel miRNAs, including stage-specific miRNAs and those not previously identified in L. decemlineata. Most of the conserved miRNAs were found in multiple developmental stages, whereas the novel miRNAs were often stage specific with the bulk identified in the egg stage. The identified miRNAs have a myriad of putative functions, including growth, reproduction, and insecticide resistance. We discuss the putative roles of some of the most notable miRNAs in the regulation of L. decemlineata development, as well as the potential applications of this research in Colorado potato beetle management.

Prediction of the miRNA interactome - Established methods and upcoming perspectives

MicroRNAs (miRNAs) are well-studied small noncoding RNAs involved in post-transcriptional gene regulation in a wide range of organisms, including mammals. Their function is mediated by base pairing with their target RNAs. Although many features required for miRNA-mediated repression have been described, the identification of functional interactions is still challenging. In the last two decades, numerous Machine Learning (ML) models have been developed to predict their putative targets. In this review, we summarize the biological knowledge and the experimental data used to develop these ML models. Recently, Deep Neural Network-based models have also emerged in miRNA interaction modeling. We thus outline established and emerging models to give a perspective on the future developments needed to improve the identification of genes directly regulated by miRNAs.

MicroRNAs regulate innate immunity against uropathogenic and commensal-like Escherichia coli infections in the surrogate insect model Galleria mellonella

Uropathogenic Escherichia coli (UPEC) strains cause symptomatic urinary tract infections in humans whereas commensal-like E. coli strains in the urinary bladder cause long-term asymptomatic bacteriuria (ABU). We previously reported that UPEC and ABU strains differentially regulate key DNA methylation and histone acetylation components in the surrogate insect host Galleria mellonella to epigenetically modulate innate immunity-related gene expression, which in turn controls bacterial growth. In this follow-up study, we infected G. mellonella larvae with UPEC strain CFT073 or ABU strain 83972 to identify differences in the expression of microRNAs (miRNAs), a class of non-coding RNAs that regulate gene expression at the post-transcriptional level. Our small RNA sequencing analysis showed that UPEC and ABU infections caused significant changes in the abundance of miRNAs in the larvae, and highlighted the differential expression of 147 conserved miRNAs and 95 novel miRNA candidates. We annotated the G. mellonella genome sequence to investigate the miRNA-regulated expression of genes encoding antimicrobial peptides, signaling proteins, and enzymatic regulators of DNA methylation and histone acetylation in infected larvae. Our results indicate that miRNAs play a role in the epigenetic reprograming of innate immunity in G. mellonella larvae to distinguish between pathogenic and commensal strains of E. coli.

Improving Bioinformatics Prediction of microRNA Targets by Ranks Aggregation

microRNAs are noncoding RNAs which downregulate a large number of target mRNAs and modulate cell activity. Despite continued progress, bioinformatics prediction of microRNA targets remains a challenge since available software still suffer from a lack of accuracy and sensitivity. Moreover, these tools show fairly inconsistent results from one another. Thus, in an attempt to circumvent these difficulties, we aggregated all human results of four important prediction algorithms (miRanda, PITA, SVmicrO, and TargetScan) showing additional characteristics in order to rerank them into a single list. Instead of deciding which prediction tool to use, our method clearly helps biologists getting the best microRNA target predictions from all aggregated databases. The resulting database is freely available through a webtool called miRabel¹ which can take either a list of miRNAs, genes, or signaling pathways as search inputs. Receiver operating characteristic curves and precision-recall curves analysis carried out using experimentally validated data and very large data sets show that miRabel significantly improves the prediction of miRNA targets compared to the four algorithms used separately. Moreover, using the same analytical methods, miRabel shows significantly better predictions than other popular algorithms such as MBSTAR, miRWalk, ExprTarget and miRMap. Interestingly, an F-score analysis revealed that miRabel also significantly improves the relevance of the top results. The aggregation of results from different databases is therefore a powerful and generalizable approach to many other species to improve miRNA target predictions. Thus, miRabel is an efficient tool to guide biologists in their search for miRNA targets and integrate them into a biological context.

A novel computational approach to the silencing of Sugarcane Bacilliform Guadeloupe A Virus determines potential host-derived MicroRNAs in sugarcane (Saccharum officinarum L.)

Sugarcane Bacilliform Guadeloupe A Virus (SCBGAV, genus Badnavirus, family Caulimoviridae) is an emerging, deleterious pathogen of sugarcane which presents a substantial barrier to producing high sugarcane earnings. Sugarcane bacilliform viruses (SCBVs) are one of the main species that infect sugarcane. During the last 30 years, significant genetic changes in SCBV strains have been observed with a high risk of disease incidence associated with crop damage. SCBV infection may lead to significant losses in biomass production in susceptible sugarcane cultivars. The circular, double-stranded (ds) DNA genome of SCBGAV (7.4 Kb) is composed of three open reading frames (ORFs) on the positive strand that replicate by a reverse transcriptase. SCBGAV can infect sugarcane in a semipersistent manner via the insect vectors sugarcane mealybug species. In the current study, we used miRNA target prediction algorithms to identify and comprehensively analyze the genome-wide sugarcane (Saccharum officinarum L.)-encoded microRNA (miRNA) targets against the SCBGAV. Mature miRNA target sequences were retrieved from the miRBase (miRNA database) and were further analyzed for hybridization to the SCBGAV genome. Multiple computational approaches—including miRNA-target seed pairing, multiple target positions, minimum free energy, target site accessibility, maximum complementarity, pattern recognition and minimum folding energy for attachments—were considered by all algorithms. Among them, sof-miR396 was identified as the top effective candidate, capable of targeting the vital ORF3 of the SCBGAV genome. miRanda, RNA22 and RNAhybrid algorithms predicted hybridization of sof-miR396 at common locus position 3394. The predicted sugarcane miRNAs against viral mRNA targets possess antiviral activities, leading to translational inhibition by mRNA cleavage. Interaction network of sugarcane-encoded miRNAs with SCBGAV genes, created using Circos, allow analyze new targets. The finding of the present study acts as a first step towards the creation of SCBGAV-resistant sugarcane through the expression of the identified miRNAs.

Performance of Validated MicroRNA Biomarkers for Alzheimer's Disease in Mild Cognitive Impairment

BACKGROUND

Cerebrospinal fluid (CSF) microRNA (miRNA) biomarkers of Alzheimer's disease (AD) have been identified, but have not been evaluated in prodromal AD, including mild cognitive impairment (MCI).

OBJECTIVE

To assess whether a set of validated AD miRNA biomarkers in CSF are also sensitive to early-stage pathology as exemplified by MCI diagnosis.

METHODS

We measured the expression of 17 miRNA biomarkers for AD in CSF samples from AD, MCI, and cognitively normal controls (NC). We then examined classification performance of the miRNAs individually and in combination. For each miRNA, we assessed median expression in each diagnostic group and classified markers as trending linearly, nonlinearly, or lacking any trend across the three groups. For trending miRNAs, we assessed multimarker classification performance alone and in combination with apolipoprotein E ɛ4 allele (APOEɛ4) genotype and amyloid-β42 to total tau ratio (Aβ42:T-Tau). We identified predicted targets of trending miRNAs using pathway analysis.

RESULTS

Five miRNAs showed a linear trend of decreasing median expression across the ordered diagnoses (control to MCI to AD). The trending miRNAs jointly predicted AD with area under the curve (AUC) of 0.770, and MCI with AUC of 0.705. Aβ42:T-Tau alone predicted MCI with AUC of 0.758 and the AUC improved to 0.813 (p = 0.051) after adding the trending miRNAs. Multivariate correlation of the five trending miRNAs with Aβ42:T-Tau was weak.

CONCLUSION

Selected miRNAs combined with Aβ42:T-Tau improved classification performance (relative to protein biomarkers alone) for MCI, despite a weak correlation with Aβ42:T-Tau. Together these data suggest that that these miRNAs carry novel information relevant to AD, even at the MCI stage. Preliminary target prediction analysis suggests novel roles for these biomarkers.

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.

Understanding the Modus Operandi of MicroRNA Regulatory Clusters

MicroRNAs (miRNAs) are non-coding RNAs that regulate a wide range of biological pathways by post-transcriptionally modulating gene expression levels. Given that even a single miRNA may simultaneously control several genes enrolled in multiple biological functions, one would expect that these tiny RNAs have the ability to properly sort among distinctive cellular processes to drive protein production. To test this hypothesis, we scrutinized previously published microarray datasets and clustered protein-coding gene expression profiles according to the intensity of fold-change levels caused by the exogenous transfection of 10 miRNAs (miR-1, miR-7, miR-9, miR-124, miR-128a, miR-132, miR-133a, miR-142, miR-148b, miR-181a) in a human cell line. Through an in silico functional enrichment analysis, we discovered non-randomic regulatory patterns, proper of each cluster identified. We demonstrated that miRNAs are capable of equivalently modulate the expression signatures of target genes in regulatory clusters according to the biological function they are assigned to. Moreover, target prediction analysis applied to ten vertebrate species, suggest that such miRNA regulatory modus operandi is evolutionarily conserved within vertebrates. Overall, we discovered a complex regulatory cluster-module strategy driven by miRNAs, which relies on the controlled intensity of the repression over distinct targets under specific biological contexts. Our discovery helps to clarify the mechanisms underlying the functional activity of miRNAs and makes it easier to take the fastest and most accurate path in the search for the functions of miRNAs in any distinct biological process of interest.