Identification Of microRNA Targets Research Articles

MicroRNA Isolation, Expression Profiling, and Target Identification for Neuroprotection in Alzheimer's Disease.

Millions of people throughout the world are affected by neurodegenerative disorders like Alzheimer's disease (AD), making them a major public health concern. To create successful medicines, early diagnosis and illness monitoring are required. Emerging as possible diagnostic and treatment tools for neurodegenerative illnesses are biomarkers such as microRNAs (miRNAs). In the realm of neuroscience, miRNAs have been discovered to function as essential regulators of gene expression, with roles spanning development, differentiation, and illness. Several neurodegenerative diseases, including AD, have been linked to miRNA dysregulation. As high-throughput methods have been developed for monitoring miRNA expression and identifying miRNA targets, miRNAs have become a prime candidate for use in diagnostics and therapy. The techniques for isolating miRNAs and the most up-to-date computational methods for finding miRNA target transcripts are both described in this chapter. This chapter will be a helpful reference for anyone investigating the role of miRNAs in AD and related neurodegenerative illnesses.

MicroRNA Target Identification: Revisiting Accessibility and Seed Anchoring.

By pairing to messenger RNAs (mRNAs for short), microRNAs (miRNAs) regulate gene expression in animals and plants. Accurately identifying which mRNAs interact with a given miRNA and the precise location of the interaction sites is crucial to reaching a more complete view of the regulatory network of an organism. Only a few experimental approaches, however, allow the identification of both within a single experiment. Computational predictions of miRNA-mRNA interactions thus remain generally the first step used, despite their drawback of a high rate of false-positive predictions. The major computational approaches available rely on a diversity of features, among which anchoring the miRNA seed and measuring mRNA accessibility are the key ones, with the first being universally used, while the use of the second remains controversial. Revisiting the importance of each is the aim of this paper, which uses Cross-Linking, Ligation, And Sequencing of Hybrids (CLASH) datasets to achieve this goal. Contrary to what might be expected, the results are more ambiguous regarding the use of the seed match as a feature, while accessibility appears to be a feature worth considering, indicating that, at least under some conditions, it may favour anchoring by miRNAs.

MicroRNA-Target Identification: A Combinatorial In Silico Approach.

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

A deep learning method for miRNA/isomiR target detection

Accurate identification of microRNA (miRNA) targets at base-pair resolution has been an open problem for over a decade. The recent discovery of miRNA isoforms (isomiRs) adds more complexity to this problem. Despite the existence of many methods, none considers isomiRs, and their performance is still suboptimal. We hypothesize that by taking the isomiR–mRNA interactions into account and applying a deep learning model to study miRNA–mRNA interaction features, we may improve the accuracy of miRNA target predictions. We developed a deep learning tool called DMISO to capture the intricate features of miRNA/isomiR–mRNA interactions. Based on tenfold cross-validation, DMISO showed high precision (95%) and recall (90%). Evaluated on three independent datasets, DMISO had superior performance to five tools, including three popular conventional tools and two recently developed deep learning-based tools. By applying two popular feature interpretation strategies, we demonstrated the importance of the miRNA regions other than their seeds and the potential contribution of the RNA-binding motifs within miRNAs/isomiRs and mRNAs to the miRNA/isomiR–mRNA interactions.

Identification of microRNA Targets in colorectal cancer through Data Sequencing

Colorectal cancer (CRC) is the third leading cause of cancer‐related mortality globally. MicroRNAs (miRNAs, miRs), a class of small non‐coding RNA molecules, have demonstrated important roles in carcinogenesis and its progression through the regulation of the epithelialmesenchymal transition (EMT), oncogenic signaling pathways, and metastasis. Despite the increase in miRNA studies and extensive analyzes of their expression, the role and function of many individual miRNAs in CRC remains poorly understood. The aim of this study was to identify miRNA targets in CRC through data sequencing, which could be a solid prognostic prediction tool and help clinical strategy.MethodsCRC gene expression data sets were collected from the public database, The Cancer Genome Atlas (TCGA). In addition, web‐based tools were used to explore TCGA data, specifically the one developed by the Broad Institute TCGA GDAC Firehose, which provides data sets, algorithms, and analysis results standardized for TCGA. This pipeline has the following steps: The CLR (Context Likelihood of Relatedness) approach is applied to infer putative miRNA regulatory connections: gene; miRNA filtering: gene pairs based on Pearson's correlation (<= ‐0.3); and miRNA filtering: gene pairs based on predicted interactions in three sequence prediction databases (Miranda, Pictar, Targetscan). The CLR algorithm was applied on 617 miRs and 18012 mRNAs across 220 samples. After 2 filtering steps, the number of 9 miR:genes pairs were detected.ResultsThe initial search with the term “Colorectal adenocarcinoma”, “COADREAD” yielded 631 cases. After the analysis of these samples, data on the significance miR:gene pairs were obtained and Table 1 shows the results of miR:gene pairs with corr < ‐0.30 and predicted interactions in three sequence prediction databases. About the miRNA connections, Table 2 shows all miRNA hubs with their associated genes in the putative direct target network. Finally, about gene connections, Table 3 shows all gene hubs with their associated miRNAs in the putative direct target network.ConclusionThe use of miRNAs as biomarkers for CRC could provide a new and less invasive technique to detect CRC and help determine prognosis. These miRNAs and their targets require further evaluation for a better understanding of their associations, ultimately, with the potential to develop new therapeutic targets. Therefore, it is proposed to develop a screening panel that should consist of multiple miRNAs that would provide a more accurate and efficient screening tool for CRC.

Genome-wide identification of microRNA targets reveals positive regulation of the Hippo pathway by miR-122 during liver development

Liver development is a highly complex process that is regulated by the orchestrated interplay of epigenetic regulators, transcription factors, and microRNAs (miRNAs). Owing to the lack of global in vivo targets of all miRNAs during liver development, the mechanisms underlying the dynamic control of hepatocyte differentiation by miRNAs remain elusive. Here, using Argonaute (Ago) high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP) in the mouse liver at different developmental stages, we characterized massive Ago-binding RNAs and obtained a genome-wide map of liver miRNA-mRNA interactions. The dynamic changes of five clusters of miRNAs and their potential targets were identified to be differentially involved at specific stages, a dozen of high abundant miRNAs and their epigenetic regulation by super-enhancer were found during liver development. Remarkably, miR-122, a liver-specific and most abundant miRNA in newborn and adult livers, was found by its targetome and pathway reporter analyses to regulate the Hippo pathway, which is crucial for liver size control and homeostasis. Mechanistically, we further demonstrated that miR-122 negatively regulates the outcomes of the Hippo pathway transcription factor TEAD by directly targeting a number of hippo pathway regulators, including the coactivator TAZ and a key factor of the phosphatase complex PPP1CC, which contributes to the dephosphorylation of YAP, another coactivator downstream of the Hippo pathway. This study identifies for the first time the genome-wide miRNA targetomes during mouse liver development and demonstrates a novel mechanism of terminal differentiation of hepatocytes regulated by the miR-122/Hippo pathway in a coordinated manner. As the Hippo pathway plays important roles in cell proliferation and liver pathological processes like inflammation, fibrosis, and hepatocellular carcinoma (HCC), our study could also provide a new insight into the function of miR-122 in liver pathology.

MicroRNA Expression Profiling, Target Identification, and Validation in Chondrocytes.

MicroRNAs (miRNAs) are a class of noncoding small RNAs, which play a critical role in various biological processes including musculoskeletal formation and arthritis pathogenesis via regulating target gene expressions, raising the potentially substantial effects on gene expression networks. Over 2000 miRNAs are encoded in the human genome and a single miRNA potentially targets hundreds of genes. To examine the expression and function of miRNAs in chondrocytes and arthritis pathogenesis, we describe the protocols for the current miRNA related experiments including miRNA expression profiling by (1) Next Generation Sequencing and by TaqMan Array system, (2) miRNA target prediction by TargetScan, (3) miRNA target screening by cell-based reporter library assay, and (4) miRNA and its target interaction by HITS-CLIP (high-throughput sequencing of RNAs isolated by cross-linking immunoprecipitation) in cartilage and chondrocyte research.

Exploiting PERL for Micro-RNA Target Identification: A Potential Drug Site for COVID-19

The functioning of gene expression or ribonucleic acid (RNA) silencing is governed by microRNA also known as miRNA. It is a small non-coding RNA molecule which finds its existence in animals, viruses, or plants. The large part of miRNAs is found to be transcribed from DNA sequences to form primary miRNAs followed by the processing of the precursor miRNAs and mature miRNAs. The miRNAs interconnect with their target genes in an effective manner which is dependent on factors like sub-cellular location of miRNAs, the availability of miRNAs and target miRNAs along with their interaction affinities, as seen in case of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Together with its involvement in normal functioning of eukaryotic cells, microRNA deregulation is associated with cancer, i.e., chronic lymphocytic leukemia. Therefore, microRNA target identification becomes important to unwind the relationship between microRNA deregulation and human diseases, thereby paving a path for structure-baseddrug discovery. Towards that direction, we have attempted to use the platform of PERL programming (a user-friendly and dynamic language to easily process and manipulate long sequences), to detect the microRNA target sites in genomic sequences, thereby trying to suppress the expression level for prognosis.

High-Resolution In Vivo Identification of miRNA Targets by Halo-Enhanced Ago2 Pull-Down

The identification of microRNA (miRNA) targets by Ago2 crosslinking-immunoprecipitation (CLIP) methods has provided major insights into the biology of this important class of non-coding RNAs. However, these methods are technically challenging and not easily applicable to an invivo setting. To overcome these limitations and facilitate the investigation of miRNA functions invivo, we have developed a method based on a genetically engineered mouse harboring a conditional Halo-Ago2 allele expressed from the endogenous Ago2 locus. By using a resin conjugated to the HaloTag ligand, Ago2-miRNA-mRNA complexes can be purified from cells and tissues expressing the endogenous Halo-Ago2 allele. We demonstrate the reproducibility and sensitivity of this method in mouse embryonic stem cells, developing embryos, adult tissues, and autochthonous mouse models of human brain and lung cancers. This method and the datasets we have generated will facilitate the characterization of miRNA-mRNA networks invivo under physiological and pathological conditions.

Analysis and Identification of Tumorigenic Targets of MicroRNA in Cancer Cells by Photoreactive Chemical Probes.

Photoactive RNA probes have unique advantages in the identification of microRNA (miR) targets due to their ability for efficient conjugation to the target sequences by covalent crosslinking, providing stable miR-mRNA complexes for further analysis. Here, we report a highly efficient and straightforward method for miR target identification that is based on photo-reactive chemical probes and RNA-seq technology (denotes PCP-Seq). UV reactive probes were prepared by incorporating psoralen in the specific position of the seed sequence of miR. Cancer cells that were transfected with the miR probes were treated with UV, following the isolation of poly(A) RNA and sequencing of the transcriptome. Quantitative analysis of RNA-seq reads and subsequent validation by qPCR, dual luciferase assay as well as western blotting confirmed that PCP-Seq could highly efficiently identify multiple targets of different miRs in the lung cancer cell line, such as targets PTTG1 and PTGR1 of miR-29a and ILF2 of miR-34a. Collectively, our data showed that PCP-Seq is a robust strategy for miR targets identification, and unique in the identification of the targets that escape degradation by miRISC and maintain normal cellular level, although their translation is repressed.

Genome-Wide Identification of MicroRNA Targets Reveals Positive Regulation of the Hippo Pathway by miR-122 During Liver Development

Liver development is a highly complex process that is regulated by the orchestrated interplay of epigenetic regulators, transcription factors and microRNAs (miRNAs). Owing to the lack of global in vivo targets of all miRNAs during liver development, the mechanisms underlying the dynamic control of hepatocyte differentiation by miRNAs remain elusive. Here, using Argonaute (Ago) high-throughput sequencing of RNA isolated by crosslinking immunoprecipitation (HITS-CLIP) in the mouse liver at different developmental stages, we characterized massive Ago-binding RNAs and obtained a genome-wide map of liver miRNA-mRNA interactions. The dynamic changes of five clusters of miRNAs and their potential targets were identified to be differentially involved at specific stages, a dozen of high abundant miRNAs and their epigenetic regulation by super-enhancer were found during liver development. Remarkably, miR-122, a liver-specific and most abundant miRNA in newborn and adult livers, was found by its targetome and pathway reporter analyses to regulate the Hippo pathway, which is crucial for liver size control and homeostasis. Mechanistically, we further demonstrated that miR-122 negatively regulates the outcomes of the Hippo pathway transcription factor TEAD by directly targeting a number of hippo pathway regulators, including the coactivator Taz and a key factor of the phosphatase complex Ppp1cc, which contributes to the dephosphorylation of YAP, another coactivator downstream of the Hippo pathway. This study identifies for the first time the genome-wide miRNA targetome during mouse liver development and demonstrates a novel mechanism of terminal differentiation of hepatocytes regulated by the miR-122/Hippo pathway in a coordinated manner.

A photoactivatable microRNA probe for identification of microRNA targets and light-controlled suppression of microRNA target expression.

Here, we report a novel dual-functional microRNA (miRNA) probe, PA-miRNA, for miRNA target identification and light control of miRNA target expression. PA-miRNA is a miRNA mimic with a 3'-biotin tag linked via a photo-cleavable linker. Using PA-miR-34a, intracellular targets of miR-34a in HeLa cells were isolated and confirmed. Moreover, PA-miR-34a upon transfection into HeLa cells was inactive until light irradiation to break the photo-cleavable linker to release functional miR-34a. We demonstrated that miR-34a target expression as well as miR-34a-promoted cell apoptosis were regulated by PA-miR-34a in a photo-controllable manner.

Click RNA for Rapid Capture and Identification of Intracellular MicroRNA Targets.

Rapid capture and identification of the intracellular target genes of microRNAs (miRNAs) are the key to understanding miRNA functions and development of RNA-based therapeutics. However, developing biochemical tools that can fish out the target genes of miRNAs in live cells is a significant technical challenge. Here, we report a remarkably simple yet powerful technology capable of loading virtually any miRNA into Ago2 of the RNA-induced silencing complexes (RISCs). This surprising discovery enables rapid capture and identification of target mRNAs and long noncoding RNAs. It is achieved by linking dibenzocyclooctyne (DBCO), a classical chemical moiety in copper-free click chemistry, to the 3' end of miRNAs. DBCO serves as a high-affinity tag to the Ago2 protein, thus boosting the formation of RISCs with miRNA target genes in living cells. Upon cell lysing, DBCO's routine function in click chemistry allows rapid enrichment of target genes for analysis without the need of additional molecular handles. A series of miR-21 and miR-27a target genes that were previously unknown were pulled down from various cell lines and identified with qRT-PCR, demonstrating the utility of this innovative technology in both transcriptomic research and RNA-based studies.

Inconsistencies and Limitations of Current MicroRNA Target Identification Methods.

MicroRNAs and their Argonaute protein partners constitute the RISC complex, which can repress specific target mRNAs. The identification of microRNA targets is of central importance, and various experimental and computational methods have been developed over the last 15 years. Most experimental methods are based on the assumption that mRNAs which interact physically with the RISC complex constitute regulatory targets and, similarly, some computational methods only aim at predicting physical interactors for RISC. Besides specific limitations, which we discuss for each method, the mere concept of assuming a functional role for every detected molecular event is likely to identify many deceptive interactions (i.e., interactions that really exist at the molecular scale, but without controlling any biological function at the macroscopic scale).In order to select biologically important interactions, some computational tools interrogate the phylogenetic conservation of microRNA/mRNA interactions, thus theoretically selecting only biologically relevant targets. Yet even comparative genomics can yield false positives.Conceptual and technical limitations for all these techniques tend to be overlooked by the scientific community. This review sums them up, emphasizing on the implications of these issues on our understanding of microRNA biology.

Mass Spectrometry-Based Proteomics to Unveil the Non-coding RNA World.

The interaction between non-coding RNAs (ncRNAs) and proteins is crucial for the stability, localization and function of the different classes of ncRNAs. Although ncRNAs, when embedded in various ribonucleoprotein (RNP) complexes, control the fundamental processes of gene expression, their biological functions and mechanisms of action are still largely unexplored. Mass Spectrometry (MS)-based proteomics has emerged as powerful tool to study the ncRNA world: on the one hand, by identifying the proteins interacting with distinct ncRNAs; on the other hand, by measuring the impact of ncRNAs on global protein levels. Here, we will first provide a concise overview on the basic principles of MS-based proteomics for systematic protein identification and quantification; then, we will recapitulate the main approaches that have been implemented for the screening of ncRNA interactors and the dissection of ncRNA-protein complex composition. Finally, we will describe examples of various proteomics strategies developed to characterize the effect of ncRNAs on gene expression, with a focus on the systematic identification of microRNA (miRNA) targets.

Diazirine-containing tag-free RNA probes for efficient RISC-loading and photoaffinity labeling of microRNA targets

We designed and synthesized a photo-reactive and tag-free RNA probe for the identification of microRNA (miRNA) targets. To synthesize the RNA probe, we designed a novel nucleoside analog 1-O-[3-ethynyl-5-(3-trifluoromethyl-3H-diazirine-3-yl)]benzyl-β-d-ribofuranose containing aryl trifluoromethyl diazirine and ethynyl moieties. The RNA probe containing this analog was observed to form crosslinks with complementary RNA by UV irradiation and was rapidly tagged by Cu-catalyzed azide alkyne cycloaddition (CuAAC). In addition, the tag-free and photo-reactive miRNA-145 probe showed comparable gene silencing activity to that of unmodified miRNA-145. Therefore, miRNA probes containing the nucleoside analog are promising candidates for the identification of target mRNAs of miRNAs.

MicroRNA-mediated regulatory circuits: outlook and perspectives

MicroRNAs have been found to be necessary for regulating genes implicated in almost all signaling pathways, and consequently their dysfunction influences many diseases, including cancer. Understanding of the complexity of the microRNA-mediated regulatory network has grown in terms of size, connectivity and dynamics with the development of computational and, more recently, experimental high-throughput approaches for microRNA target identification. Newly developed studies on recurrent microRNA-mediated circuits in regulatory networks, also known as network motifs, have substantially contributed to addressing this complexity, and therefore to helping understand the ways by which microRNAs achieve their regulatory role. This review provides a summarizing view of the state-of-the-art, and perspectives of research efforts on microRNA-mediated regulatory motifs. In this review, we discuss the topological properties characterizing different types of circuits, and the regulatory features theoretically enabled by such properties, with a special emphasis on examples of circuits typifying their biological significance in experimentally validated contexts. Finally, we will consider possible future developments, in particular regarding microRNA-mediated circuits involving long non-coding RNAs and epigenetic regulators.

Issues in current microRNA target identification methods

ABSTRACTmicroRNAs are currently believed to control a large diversity of physiologic processes, through the collective repression of thousands of target genes. Both experimental and computational analyses indeed suggest that each microRNA regulates tens or hundreds of genes. But some observations suggest that the phenotypic consequences of many published miRNA/mRNA interactions are dubious. For example, the reported amplitude of miRNA-guided repression is very small, while biologic processes tend to be robust to small changes in gene expression. We recently showed, on one particular miRNA, that for most predicted targets, miRNA-guided repression is even smaller than inter-individual variability among wild-type specimens. We also put forward several sources of computational false positives. These issues are generally neglected by the scientific community, probably resulting in the frequent publication of irreproducible or misinterpreted results regarding microRNA function. We propose novel types of analyses, easily accessible to the community, that could help improve microRNA target identification.

Identification of MicroRNA Targets of Capsicum spp. Using MiRTrans-a Trans-Omics Approach.

The microRNA (miRNA) can regulate the transcripts that are involved in eukaryotic cell proliferation, differentiation, and metabolism. Especially for plants, our understanding of miRNA targets, is still limited. Early attempts of prediction on sequence alignments have been plagued by enormous false positives. It is helpful to improve target prediction specificity by incorporating the other data sources such as the dependency between miRNA and transcript expression or even cleaved transcripts by miRNA regulations, which are referred to as trans-omics data. In this paper, we developed MiRTrans (Prediction of MiRNA targets by Trans-omics data) to explore miRNA targets by incorporating miRNA sequencing, transcriptome sequencing, and degradome sequencing. MiRTrans consisted of three major steps. First, the target transcripts of miRNAs were predicted by scrutinizing their sequence characteristics and collected as an initial potential targets pool. Second, false positive targets were eliminated if the expression of miRNA and its targets were weakly correlated by lasso regression. Third, degradome sequencing was utilized to capture the miRNA targets by examining the cleaved transcripts that regulated by miRNAs. Finally, the predicted targets from the second and third step were combined by Fisher's combination test. MiRTrans was applied to identify the miRNA targets for Capsicum spp. (i.e., pepper). It can generate more functional miRNA targets than sequence-based predictions by evaluating functional enrichment. MiRTrans identified 58 miRNA-transcript pairs with high confidence from 18 miRNA families conserved in eudicots. Most of these targets were transcription factors; this lent support to the role of miRNA as key regulator in pepper. To our best knowledge, this work is the first attempt to investigate the miRNA targets of pepper, as well as their regulatory networks. Surprisingly, only a small proportion of miRNA-transcript pairs were shared between degradome sequencing and expression dependency predictions, suggesting that miRNA targets predicted by a single technology alone may be prone to report false negatives.

Genome-wide identification of microRNA targets in the neglected disease pathogens of the genus Echinococcus

MicroRNAs (miRNAs), a class of small non-coding RNAs, are key regulators of gene expression at post-transcriptional level and play essential roles in biological processes such as development. MiRNAs silence target mRNAs by binding to complementary sequences in the 3′untranslated regions (3′UTRs). The parasitic helminths of the genus Echinococcus are the causative agents of echinococcosis, a zoonotic neglected disease. In previous work, we performed a comprehensive identification and characterization of Echinococcus miRNAs. However, current knowledge about their targets is limited. Since target prediction algorithms rely on complementarity between 3′UTRs and miRNA sequences, a major limitation is the lack of accurate sequence information of 3′UTR for most species including parasitic helminths. We performed RNA-seq and developed a pipeline that integrates the transcriptomic data with available genomic data of this parasite in order to identify 3′UTRs of Echinococcus canadensis. The high confidence set of 3′UTRs obtained allowed the prediction of miRNA targets in Echinococcus through a bioinformatic approach. We performed for the first time a comparative analysis of miRNA targets in Echinococcus and Taenia. We found that many evolutionarily conserved target sites in Echinococcus and Taenia may be functional and under selective pressure. Signaling pathways such as MAPK and Wnt were among the most represented pathways indicating miRNA roles in parasite growth and development. Genome-wide identification and characterization of miRNA target genes in Echinococcus provide valuable information to guide experimental studies in order to understand miRNA functions in the parasites biology. miRNAs involved in essential functions, especially those being absent in the host or showing sequence divergence with respect to host orthologs, might be considered as novel therapeutic targets for echinococcosis control.