Identification Of microRNA Targets Research Articles

Experimental design and data analysis of Ago-RIP-Seq experiments for the identification of microRNA targets.

The identification of microRNA (miRNA) target genes is crucial for understanding miRNA function. Many methods for the genome-wide miRNA target identification have been developed in recent years; however, they have several limitations including the dependence on low-confident prediction programs and artificial miRNA manipulations. Ago-RNA immunoprecipitation combined with high-throughput sequencing (Ago-RIP-Seq) is a promising alternative. However, appropriate statistical data analysis algorithms taking into account the experimental design and the inherent noise of such experiments are largely lacking.Here, we investigate the experimental design for Ago-RIP-Seq and examine biostatistical methods to identify de novo miRNA target genes. Statistical approaches considered are either based on a negative binomial model fit to the read count data or applied to transformed data using a normal distribution-based generalized linear model. We compare them by a real data simulation study using plasmode data sets and evaluate the suitability of the approaches to detect true miRNA targets by sensitivity and false discovery rates. Our results suggest that simple approaches like linear regression models on (appropriately) transformed read count data are preferable.

Computational and Experimental Identification of Tissue-Specific MicroRNA Targets.

In this chapter we discuss computational methods for the prediction of microRNA (miRNA) targets. More specifically, we consider machine learning-based approaches and explain why these methods have been relatively unsuccessful in reducing the number of false positive predictions. Further we suggest approaches designed to improve their performance by considering tissue-specific target regulation. We argue that the miRNA targetome differs depending on the tissue type and introduce a novel algorithm that predicts miRNA targets specifically for colorectal cancer. We discuss features of miRNAs and target sites that affect target recognition, and how next-generation sequencing data can support the identification of novel miRNAs, differentially expressed miRNAs and their tissue-specific mRNA targets. In addition, we introduce some experimental approaches for the validation of miRNA targets as well as web-based resources sharing predicted and validated miRNA target interactions.

MicroRNAs as regulators and mediators of forkhead box transcription factors function in human cancers.

Evidence has shown that microRNAs are widely implicated as indispensable components of tumor suppressive and oncogenic pathways in human cancers. Thus, identification of microRNA targets and their relevant pathways will contribute to the development of microRNA-based therapeutics. The forkhead box transcription factors regulate numerous processes including cell cycle progression, metabolism, metastasis and angiogenesis, thereby facilitating tumor initiation and progression. A complex network of protein and non-coding RNAs mediates the expression and activity of forkhead box transcription factors. In this review, we summarize the current knowledge and concepts concerning the involvement of microRNAs and forkhead box transcription factors and describe the roles of microRNAs-forkhead box axis in various disease states including tumor initiation and progression. Additionally, we describe some of the technical challenges in the use of the microRNA-forkhead box signaling pathway in cancer treatment.

Visualization and Analysis of MiRNA-Targets Interactions Networks.

MicroRNAs are a class of small, noncoding RNA molecules of 21-25 nucleotides in length that regulate the gene expression by base-pairing with the target mRNAs, mainly leading to down-regulation or repression of the target genes. MicroRNAs are involved in diverse regulatory pathways in normal and pathological conditions. In this context, it is highly important to identify the targets of specific microRNA in order to understand the mechanism of its regulation and consequently its involvement in disease. However, the microRNA target identification is experimentally laborious and time-consuming. The in silico prediction of microRNA targets is an extremely useful approach because you can identify potential mRNA targets, reduce the number of possibilities and then, validate a few microRNA-mRNA interactions in an in vitro experimental model. In this chapter, we describe, in a simple way, bioinformatics guidelines to use miRWalk database and Cytoscape software for analyzing microRNA-mRNA interactions through their visualization as a network.

An integrated miRNA functional screening and target validation method for organ morphogenesis.

The relative ease of identifying microRNAs and their increasing recognition as important regulators of organogenesis motivate the development of methods to efficiently assess microRNA function during organ morphogenesis. In this context, embryonic organ explants provide a reliable and reproducible system that recapitulates some of the important early morphogenetic processes during organ development. Here we present a method to target microRNA function in explanted mouse embryonic organs. Our method combines the use of peptide-based nanoparticles to transfect specific microRNA inhibitors or activators into embryonic organ explants, with a microRNA pulldown assay that allows direct identification of microRNA targets. This method provides effective assessment of microRNA function during organ morphogenesis, allows prioritization of multiple microRNAs in parallel for subsequent genetic approaches, and can be applied to a variety of embryonic organs.

Methods for the Identification of PTEN-Targeting MicroRNAs.

The identification of PTEN-targeting microRNAs usually starts from an in silico bioinformatic prediction and then requires a careful experimental validation that exploits both heterologous and endogenous systems. Here we describe the methods used to carry on these analyses and experiments, examining pitfalls and alternatives for each step. Moreover, we give an overview of the latest high-throughput microRNA target identification techniques which offer a more comprehensive view of the microRNAs that can bind a fundamental tumor suppressor such as PTEN.

Evidence for transcriptional interference in a dual-luciferase reporter system.

The dual-luciferase reporter assay is widely used for microRNA target identification and the functional validation of predicted targets. To determine whether curcumin regulates expression of the histone methyltransferase enhancer of zeste homolog 2 (EZH2) by targeting its 3′untranslated region (3′UTR), two luciferase reporter systems containing exactly the same sequence of the EZH2 3′UTR were used to perform dual-luciferase reporter assays. Surprisingly, there were certain discrepancies between the luciferase activities derived from these two reporter constructs. We normalized luciferase activity to an internal control to determine the amount of the reporter construct successfully transfected into cells, induced a transcriptional block with flavopiridol, quantified renilla luciferase mRNA levels, and compared the absolute luciferase activity among the different groups. The results suggested that curcumin promoted the transcription of the luciferase genes located downstream of the simian vacuolating virus 40 (SV40) early enhancer/promoter, but not those located downstream of the human cytomegalovirus (CMV) immediate-early or the herpes simplex virus thymidine kinase (HSV-TK) promoters. These results explain the discrepancies between the two luciferase reporter systems. The current study underscores the importance of taking caution when interpreting the results of dual-luciferase reporter assays and provides strategies to overcome the potential pitfall accompanying dual-luciferase reporter systems.

Identification of microRNAs and microRNA targets in Xenopus gastrulae: The role of miR-26 in the regulation of Smad1

MicroRNAs (miRNAs) are known to play diverse roles in the regulation of vertebrate development. To investigate miRNA-target mRNA relationships in embryonic development, we have carried out small-RNA sequencing to identify miRNAs expressed in the early gastrula of Xenopus laevis. We identify a total of 180 miRNAs, and we have identified the locations of the miRNA precursor sequences in the X. laevis genome. Of these miRNAs, 141 represent miRs previously identified in Xenopus tropicalis. Alignment to human miRNAs led to the identification of 39 miRNAs that have not previously been described for Xenopus. We have also used a biochemical approach to isolate mRNAs that are associated with the RNA-Induced Silencing Complex (RISC) in early gastrulae and thus candidate targets of miRNA-dependent regulation. Interrogation of this RISC-associated mRNA pool by RT-PCR indicates that a number of genes essential for early patterning and specification may be under regulation by miRNAs. Smad1 transcripts are associated with the RISC; target prediction algorithms identify a single miRNA-binding site for miR-26, which is common to the 3′UTRs of Smad1a and Smad1b. Disruption of the interaction between miR-26 and the Smad1 3′UTR via a Target Protector Morpholino Oligonucleotide (TPMO) leads to a 2-fold increase in Smad1 protein accumulation, moderate increases in the expression of BMP4/Smad1 target genes, and a reduction in organizer gene expression, as well as a partially ventralized phenotype in approximately 25% of embryos. Overexpression of miR-26 resulted in moderately decreased expression of Smad1-dependent genes and an expansion of the region expressing the Organizer gene not1. Our findings indicate that interactions between miR-26 and the Smad1 3′UTR modulate Smad1 function in the establishment of axial patterning; they also establish a foundation for the functional analysis of miRNAs and their regulatory interactions during gastrulation.

From microRNA target validation to therapy: lessons learned from studies on BDNF.

During the past decade, the identification of microRNA (miR) targets has become common laboratory practice, and various strategies are now used to detect interactions between miRs and their mRNA targets. However, the current lack of a standardized identification process often leads to incomplete and/or conflicting results. Here, we review the problems most commonly encountered when verifying miR–mRNA interactions, and we propose a workflow for future studies. To illustrate the challenges faced when validating a miR target, we discuss studies in which the regulation of brain-derived neurotrophic factor by miRs was investigated, and we highlight several controversies that emerged from these studies. Finally, we discuss the therapeutic use of miR inhibitors, and we discuss several questions that should be addressed before proceeding to preclinical testing.

Noncoding RNA: linking microRNAs to their targets.

The reliable identification of microRNA (miRNA) targets remains an elusive goal. A new technique, using specially modified synthetic miRNAs to directly capture bound RNAs, brings us closer.

Abstract 1545: Identification of microRNA targets in triple-negative breast cancer

Abstract Introduction: Triple negative breast cancers (TNBC) are clinically aggressive tumors that lack the expression of ER, PR and HER2 receptors, and therefore do not respond effectively to the available target therapies. The study of the molecular alterations that are present in these tumors can lead to the identification of potential therapeutic targets that can improve patient's outcome. MicroRNAs (miRNAs) are short non-coding sequences that play a role in breast tumorigenesis regulating the expression of cancer-associated genes. In the present study, we investigated miRNAs expression profile in TNBC and non-TNBC tumors and integrated the data with DNA copy number changes (array-CGH) obtained from the same samples, to obtain the most relevant miRNA targets that may be involved in the pathogenesis of TNBC. Methods: Formalin-fixed paraffin-embedded samples from 43 TNBC and 16 non-TNBC cases were profiled for miRNA using the Nanostring system. Significant differentially expressed miRNAs (with at least 2 fold differences and p≤0.05) between the lesions were calculated by the comparative Ct method (ΔΔCt). DNA copy number analysis from the same samples was performed using an Agilent array-CGH platform. The miRNA data was directly integrated with the array-CGH data from the same cases. Combinatorial target predicted algorithms in conjunction with functional and pathway annotation enrichment systems (Ingenuity Pathway, Pathway Studio) were performed to identify predicted target functions. Results: The miRNA profiling revealed 89 miRNAs significant differentially expressed between the TNBC and non-TNBC lesions. Using miRBase and MiRDB target prediction databases we identified 3,378 target genes of upregulated miRNAs and 823 for downregulated miRNAs. A number of 15 miRNAs (out of the 89) presented concomintant genomic gains or losses and miRNA increase or decrease expression, respectively. This direct integration of the data reduced the number of miRNA targets to 1,242. Ingenuity pathway analysis on these predicted targets function, identified canonical pathways, including p53, IL-8 and Rac signaling. Gene expression profiling analysis is underway to confirm the regulatory effect of the selected miRNAs on the targets identified. Conclusions: We have observed significant differentially expressed miRNAs in the analysis of TNBC cases in comparison with non-TNBC cases. The integration analysis with DNA copy number data let us to select the miRNAs with concomitant changes in copy number and gene expression and predicted target algorithms identified key pathways that may be related to the TNBC phenotype. The functional validation of these targets, by in vitro and in vivo experimental models, through the assessment of miRNA-mRNA interaction and/or modulation of miRNA expression will allow us to identify the most relevant miRNAs that are mechanistically involved in the pathogenesis of TNBC. Note: This abstract was not presented at the meeting. Citation Format: Mandeep Gill, Bruna Sugita, Silma R. Pereira, Catalin Marian, Xi Li, Yuriy Gusev, Enilze MSF Ribeiro, Iglenir J. Cavalli, Luciane R. Cavalli. Identification of microRNA targets in triple-negative breast cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1545. doi:10.1158/1538-7445.AM2014-1545

Abstract 979: microRNA-mediated leukemia-initiating cell activity

Abstract The HoxA9 transcription activator and the Gfi1 transcriptional repressor compete for the regulation of common target genes. We exploited HoxA9 versus Gfi1 antagonism to identify the genes encoding microRNA-21 and microRNA-196b as transcriptional targets of Hox-based leukemia oncoproteins. Therapeutic inhibition of microRNA-21 and microRNA-196b significantly inhibits in vitro colony forming activity, and quantitatively depletes in vivo leukemia-initiating-cell activity of Hox-based leukemias leading to leukemia-free survival of murine AML and significant delay in disease onset in xenograft models. A novel microRNA target identification platform both validates therapeutic intervention and reveals biological impact of disrupting microRNA function. These data establish microRNA as functional effectors of endogenous HoxA9 and Hox-based leukemia oncoproteins, provide a concise in vivo platform to test RNA therapeutics, and suggest therapeutic value for microRNA antagonists in AML. Citation Format: Chinavenmeni S. Velu, Aditya Chaubey, James D. Phelan, Sara Meyer, Shane R. Horman, Mark Wunderlich, Monica L. Guzman, Anil G. Jegga, Nancy J. Zeleznik-Le, Jianjun Chen, James C. Mulloy, Jose A. Cancelas, Craig T. Jordan, Bruce J. Aronow, Guido Marcucci, Balkrishen Bhat, Brian Gebelein, H. Leighton Grimes. microRNA-mediated leukemia-initiating cell activity. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 979. doi:10.1158/1538-7445.AM2014-979

MicroRNAs in the Stressed Heart: Sorting the Signal from the Noise.

The short noncoding RNAs, known as microRNAs, are of undisputed importance in cellular signaling during differentiation and development, and during adaptive and maladaptive responses of adult tissues, including those that comprise the heart. Cardiac microRNAs are regulated by hemodynamic overload resulting from exercise or hypertension, in the response of surviving myocardium to myocardial infarction, and in response to environmental or systemic disruptions to homeostasis, such as those arising from diabetes. A large body of work has explored microRNA responses in both physiological and pathological contexts but there is still much to learn about their integrated actions on individual mRNAs and signaling pathways. This review will highlight key studies of microRNA regulation in cardiac stress and suggest possible approaches for more precise identification of microRNA targets, with a view to exploiting the resulting data for therapeutic purposes.

Genome-wide identification of miR-200 targets reveals a regulatory network controlling cell invasion.

The microRNAs of the miR-200 family maintain the central characteristics of epithelia and inhibit tumor cell motility and invasiveness. Using the Ago-HITS-CLIP technology for transcriptome-wide identification of direct microRNA targets in living cells, along with extensive validation to verify the reliability of the approach, we have identified hundreds of miR-200a and miR-200b targets, providing insights into general features of miRNA target site selection. Gene ontology analysis revealed a predominant effect of miR-200 targets in widespread coordinate control of actin cytoskeleton dynamics. Functional characterization of the miR-200 targets indicates that they constitute subnetworks that underlie the ability of cancer cells to migrate and invade, including coordinate effects on Rho-ROCK signaling, invadopodia formation, MMP activity, and focal adhesions. Thus, the miR-200 family maintains the central characteristics of the epithelial phenotype by acting on numerous targets at multiple levels, encompassing both cytoskeletal effectors that control actin filament organization and dynamics, and upstream signals that locally regulate the cytoskeleton to maintain cell morphology and prevent cell migration.

Diazirine-Containing RNA Photo-Cross-Linking Probes for Capturing microRNA Targets

Here, we report the applicability of diazirine-containing RNA photo-cross-linking probes for the identification of microRNA (miRNA) targets. The RNA cross-linking probes were synthesized by substituting the RNA nucleobases with nucleoside analogues such as 1-O-[3-(3-trifluoromethyl-3H-diazirin-3-yl)]benzyl-β-d-ribofuranose or 1-O-[4-(3-trifluoromethyl-3H-diazirin-3-yl)]benzyl-β-D-ribofuranose that carry aryl trifluoromethyl diazirine moieties. The probes were successfully cross-linked with synthetic RNAs containing the four natural nucleosides on the opposite site of the nucleoside analogues. Furthermore, it was found that miRNAs containing these analogues were effective in regulating the expression of their target genes. Thus, RNAs containing the nucleoside analogues are promising candidates as photo-cross-linking probes to identify the target mRNAs of miRNAs.

MicroRNA Target Identification: Lessons from HypoxamiRs

MicroRNAs (miRNAs) are small noncoding RNAs that have emerged as key regulators of many physiological and pathological processes, including those relevant to hypoxia such as cancer, neurological dysfunctions, myocardial infarction, and lung diseases. During the last 5 years, miRNAs have been shown to play a role in the regulation of the cellular response to hypoxia. The identification of several bona fide targets of these hypoxamiRs has underlined their pleiotropic functions and the complexity of the molecular rules directing miRNA::target transcript pairing. This review outlines the main in silico and experimental approaches used to identify the targetome of hypoxamiRs and presents new recent relevant methodologies for future studies. Since hypoxia plays key roles in many pathophysiological conditions, the precise characterization of regulatory hypoxamiRs networks will be instrumental both at a fundamental level and for their future potential therapeutic applications.

Identification of microRNA targets by pulsed SILAC.

Pulsed stable isotope labeling by amino acids in cell culture (pulsed SILAC or pSILAC) allows to monitor and quantify the de novo synthesis of proteins in an unbiased fashion on a proteome-wide scale. The high applicability of this metabolic labeling technique has been demonstrated for the identification of posttranscriptional changes in gene expression on the proteome level, in particular those caused by microRNAs. The application of pSILAC allows the selective quantification of newly synthesized proteins and thus the detection of differences in protein translation. This is of particular interest in the case of microRNA-mediated regulations, which characteristically cause rather modest decreases in protein amounts that may be difficult to detect by other proteomic methods. Here, we describe a detailed protocol for using pSILAC to track miRNA-mediated changes in protein expression, using the p53-induced miR-34a microRNA as a prototypic example of microRNA-mediated regulations.

GAMUT: GPU accelerated microRNA analysis to uncover target genes through CUDA-miRanda.

BackgroundNon-coding sequences such as microRNAs have important roles in disease processes. Computational microRNA target identification (CMTI) is becoming increasingly important since traditional experimental methods for target identification pose many difficulties. These methods are time-consuming, costly, and often need guidance from computational methods to narrow down candidate genes anyway. However, most CMTI methods are computationally demanding, since they need to handle not only several million query microRNA and reference RNA pairs, but also several million nucleotide comparisons within each given pair. Thus, the need to perform microRNA identification at such large scale has increased the demand for parallel computing.MethodsAlthough most CMTI programs (e.g., the miRanda algorithm) are based on a modified Smith-Waterman (SW) algorithm, the existing parallel SW implementations (e.g., CUDASW++ 2.0/3.0, SWIPE) are unable to meet this demand in CMTI tasks. We present CUDA-miRanda, a fast microRNA target identification algorithm that takes advantage of massively parallel computing on Graphics Processing Units (GPU) using NVIDIA's Compute Unified Device Architecture (CUDA). CUDA-miRanda specifically focuses on the local alignment of short (i.e., ≤ 32 nucleotides) sequences against longer reference sequences (e.g., 20K nucleotides). Moreover, the proposed algorithm is able to report multiple alignments (up to 191 top scores) and the corresponding traceback sequences for any given (query sequence, reference sequence) pair.ResultsSpeeds over 5.36 Giga Cell Updates Per Second (GCUPs) are achieved on a server with 4 NVIDIA Tesla M2090 GPUs. Compared to the original miRanda algorithm, which is evaluated on an Intel Xeon E5620@2.4 GHz CPU, the experimental results show up to 166 times performance gains in terms of execution time. In addition, we have verified that the exact same targets were predicted in both CUDA-miRanda and the original miRanda implementations through multiple test datasets.ConclusionsWe offer a GPU-based alternative to high performance compute (HPC) that can be developed locally at a relatively small cost. The community of GPU developers in the biomedical research community, particularly for genome analysis, is still growing. With increasing shared resources, this community will be able to advance CMTI in a very significant manner. Our source code is available at https://sourceforge.net/projects/cudamiranda/.

Systematic MicroRNA Analysis Identifies ATP6V0C as an Essential Host Factor for Human Cytomegalovirus Replication

Recent advances in microRNA target identification have greatly increased the number of putative targets of viral microRNAs. However, it is still unclear whether all targets identified are biologically relevant. Here, we use a combined approach of RISC immunoprecipitation and focused siRNA screening to identify targets of HCMV encoded human cytomegalovirus that play an important role in the biology of the virus. Using both a laboratory and clinical strain of human cytomegalovirus, we identify over 200 putative targets of human cytomegalovirus microRNAs following infection of fibroblast cells. By comparing RISC-IP profiles of miRNA knockout viruses, we have resolved specific interactions between human cytomegalovirus miRNAs and the top candidate target transcripts and validated regulation by western blot analysis and luciferase assay. Crucially we demonstrate that miRNA target genes play important roles in the biology of human cytomegalovirus as siRNA knockdown results in marked effects on virus replication. The most striking phenotype followed knockdown of the top target ATP6V0C, which is required for endosomal acidification. siRNA knockdown of ATP6V0C resulted in almost complete loss of infectious virus production, suggesting that an HCMV microRNA targets a crucial cellular factor required for virus replication. This study greatly increases the number of identified targets of human cytomegalovirus microRNAs and demonstrates the effective use of combined miRNA target identification and focused siRNA screening for identifying novel host virus interactions.

Integrated analysis of transcript-level regulation of metabolism reveals disease-relevant nodes of the human metabolic network.

Metabolic diseases and comorbidities represent an ever-growing epidemic where multiple cell types impact tissue homeostasis. Here, the link between the metabolic and gene regulatory networks was studied through experimental and computational analysis. Integrating gene regulation data with a human metabolic network prompted the establishment of an open-sourced web portal, IDARE (Integrated Data Nodes of Regulation), for visualizing various gene-related data in context of metabolic pathways. Motivated by increasing availability of deep sequencing studies, we obtained ChIP-seq data from widely studied human umbilical vein endothelial cells. Interestingly, we found that association of metabolic genes with multiple transcription factors (TFs) enriched disease-associated genes. To demonstrate further extensions enabled by examining these networks together, constraint-based modeling was applied to data from human preadipocyte differentiation. In parallel, data on gene expression, genome-wide ChIP-seq profiles for peroxisome proliferator-activated receptor (PPAR) γ, CCAAT/enhancer binding protein (CEBP) α, liver X receptor (LXR) and H3K4me3 and microRNA target identification for miR-27a, miR-29a and miR-222 were collected. Disease-relevant key nodes, including mitochondrial glycerol-3-phosphate acyltransferase (GPAM), were exposed from metabolic pathways predicted to change activity by focusing on association with multiple regulators. In both cell types, our analysis reveals the convergence of microRNAs and TFs within the branched chain amino acid (BCAA) metabolic pathway, possibly providing an explanation for its downregulation in obese and diabetic conditions.