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

Neuronal-expressed microRNA-targeted pseudogenes compete with coding genes in the human brain

MicroRNAs orchestrate brain functioning via interaction with microRNA recognition elements (MRE) on target transcripts. However, the global impact of potential competition on the microRNA pool between coding and non-coding brain transcripts that share MREs with them remains unexplored. Here we report that non-coding pseudogene transcripts carrying MREs (PSG^+MRE) often show duplicated origin, evolutionary conservation and higher expression in human temporal lobe neurons than comparable duplicated MRE-deficient pseudogenes (PSG^-MRE). PSG^+MRE participate in neuronal RNA-induced silencing complexes (RISC), indicating functional involvement. Furthermore, downregulation cell culture experiments validated bidirectional co-regulation of PSG^+MRE with MRE-sharing coding transcripts, frequently not their mother genes, and with targeted microRNAs; also, PSG^+MRE single-nucleotide polymorphisms associated with schizophrenia, bipolar disorder and autism, suggesting interaction with mental diseases. Our findings indicate functional roles of duplicated PSG^+MRE in brain development and cognition, supporting physiological impact of the reciprocal co-regulation of PSG^+MRE with MRE-sharing coding transcripts in human brain neurons.

Comparative miRomics of Salt-Tolerant and Salt-Sensitive Rice

Increase in soil salt causes osmotic and ionic stress to plants, which inhibits their growth and productivity. Rice production is also hampered by salinity and the effect of salt is most severe at the seedling and reproductive stages. Salainity tolerance is a quantitative property controlled by multiple genes coding for signaling molecules, ion transporters, metabolic enzymes and transcription regulators. MicroRNAs are key modulators of gene-expression that act at the post-transcriptional level by translation repression or transcript cleavage. They also play an important role in regulating plant's response to salt-stress. In this work we adopted the approach of comparative and integrated data-mining to understand the miRNA-mediated regulation of salt-stress in rice. We profiled and compared the miRNA regulations using natural varieties and transgenic lines with contrasting behaviors in response to salt-stress. The information obtained from sRNAseq, RNAseq and degradome datasets was integrated to identify the salt-deregulated miRNAs, their targets and the associated metabolic pathways. The analysis revealed the modulation of many biological pathways, which are involved in salt-tolerance and play an important role in plant phenotype and physiology. The end modifications of the miRNAs were also studied in our analysis and isomiRs having a dynamic role in salt-tolerance mechanism were identified.

miRNAs target databases: developmental methods and target identification techniques with functional annotations

PURPOSE

microRNA (miRNA) regulates diverse biological mechanisms and metabolisms in plants and animals. Thus, the discoveries of miRNA has revolutionized the life sciences and medical research.The miRNA represses and cleaves the targeted mRNA by binding perfect or near perfect or imperfect complementary base pairs by RNA-induced silencing complex (RISC) formation during biogenesis process. One miRNA interacts with one or more mRNA genes and vice versa, hence takes part in causing various diseases. In this paper, the different microRNA target databases and their functional annotations developed by various researchers have been reviewed. The concurrent research review aims at comprehending the significance of miRNA and presenting the existing status of annotated miRNA target resources built by researchers henceforth discovering the knowledge for diagnosis and prognosis.

METHODS AND RESULTS

This review discusses the applications and developmental methodologies for constructing target database as well as the utility of user interface design. An integrated architecture is drawn and a graphically comparative study of present status of miRNA targets in diverse diseases and various biological processes is performed. These databases comprise of information such as miRNA target-associated disease, transcription factor binding sites (TFBSs) in miRNA genomic locations, polymorphism in miRNA target, A-to-I edited target, Gene Ontology (GO), genome annotations, KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, target expression analysis, TF-miRNA and miRNA-mRNA interaction networks, drugs-targets interactions, etc.

CONCLUSION

miRNA target databases contain diverse experimentally and computationally predicted target through various algorithms. The comparison of various miRNA target database has been performed on various parameters. The computationally predicted target databases suffer from false positive information as there is no common theory for prediction of miRNA targets. The review conclusion emphasizes the need of more intelligent computational improvement for the miRNA target identification, their functional annotations and datasbase development.

Genome-Wide Scleral Micro- and Messenger-RNA Regulation During Myopia Development in the Mouse

Purpose

MicroRNA (miRNAs) have been previously implicated in scleral remodeling in normal eye growth. They have the potential to be therapeutic targets for prevention/retardation of exaggerated eye growth in myopia by modulating scleral matrix remodeling. To explore this potential, genome-wide miRNA and messenger RNA (mRNA) scleral profiles in myopic and control eyes from mice were studied.

Methods

C57BL/6J mice (n = 7; P28) reared under a 12L:12D cycle were form-deprived (FD) unilaterally for 2 weeks. Refractive error and axial length changes were measured using photorefraction and 1310-nm spectral-domain optical coherence tomography, respectively. Scleral RNA samples from FD and fellow control eyes were processed for microarray assay. Statistical analyses were performed using National Institute of Aging array analysis tool; group comparisons were made using ANOVA, and gene ontologies were identified using software available on the Web. Findings were confirmed using quantitative PCR in a separate group of mice (n = 7).

Results

Form-deprived eyes showed myopic shifts in refractive error (−2.02 ± 0.47 D; P < 0.01). Comparison of the scleral RNA profiles of test eyes with those of control eyes revealed 54 differentially expressed miRNAs and 261 mRNAs fold-change >1.25 (maximum fold change = 1.63 and 2.7 for miRNAs and mRNAs, respectively) (P < 0.05; minimum, P = 0.0001). Significant ontologies showing gene over-representation (P < 0.05) included intermediate filament organization, scaffold protein binding, detection of stimuli, calcium ion, G protein, and phototransduction. Significant differential expression of Let-7a and miR-16-2, and Smok4a, Prph2, and Gnat1 were confirmed.

Conclusions

Scleral mi- and mRNAs showed differential expression linked to myopia, supporting the involvement of miRNAs in eye growth regulation. The observed general trend of relatively small fold-changes suggests a tightly controlled, regulatory mechanism for scleral gene expression.

miRTar2GO: a novel rule-based model learning method for cell line specific microRNA target prediction that integrates Ago2 CLIP-Seq and validated microRNA-target interaction data

MicroRNAs (miRNAs) are ∼19-22 nucleotides (nt) long regulatory RNAs that regulate gene expression by recognizing and binding to complementary sequences on mRNAs. The key step in revealing the function of a miRNA, is the identification of miRNA target genes. Recent biochemical advances including PAR-CLIP and HITS-CLIP allow for improved miRNA target predictions and are widely used to validate miRNA targets. Here, we present miRTar2GO, which is a model, trained on the common rules of miRNA-target interactions, Argonaute (Ago) CLIP-Seq data and experimentally validated miRNA target interactions. miRTar2GO is designed to predict miRNA target sites using more relaxed miRNA-target binding characteristics. More importantly, miRTar2GO allows for the prediction of cell-type specific miRNA targets. We have evaluated miRTar2GO against other widely used miRNA target prediction algorithms and demonstrated that miRTar2GO produced significantly higher F1 and G scores. Target predictions, binding specifications, results of the pathway analysis and gene ontology enrichment of miRNA targets are freely available at http://www.mirtar2go.org.

RAID v2.0: an updated resource of RNA-associated interactions across organisms

With the development of biotechnologies and computational prediction algorithms, the number of experimental and computational prediction RNA-associated interactions has grown rapidly in recent years. However, diverse RNA-associated interactions are scattered over a wide variety of resources and organisms, whereas a fully comprehensive view of diverse RNA-associated interactions is still not available for any species. Hence, we have updated the RAID database to version 2.0 (RAID v2.0, www.rna-society.org/raid/) by integrating experimental and computational prediction interactions from manually reading literature and other database resources under one common framework. The new developments in RAID v2.0 include (i) over 850-fold RNA-associated interactions, an enhancement compared to the previous version; (ii) numerous resources integrated with experimental or computational prediction evidence for each RNA-associated interaction; (iii) a reliability assessment for each RNA-associated interaction based on an integrative confidence score; and (iv) an increase of species coverage to 60. Consequently, RAID v2.0 recruits more than 5.27 million RNA-associated interactions, including more than 4 million RNA-RNA interactions and more than 1.2 million RNA-protein interactions, referring to nearly 130 000 RNA/protein symbols across 60 species.

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.

Genome-Wide Analysis of MicroRNA-Regulated Transcripts

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression by either degrading transcripts or repressing translation . Over the past decade the significance of miRNAs has been unraveled by the characterization of their involvement in crucial cellular functions and the development of disease. However, continued progress in understanding the endogenous importance of miRNAs, as well as their potential uses as therapeutic tools, has been hindered by the difficulty of positively identifying miRNA targets. To face this challenge algorithmic approaches have primarily been utilized to date, but strictly mathematical models have thus far failed to produce a generally accurate, widely accepted methodology for accurate miRNA target determination. As such, several laboratory-based, comprehensive strategies for experimentally identifying all cellular miRNA regulations simultaneously have recently been developed. This chapter discusses the advantages and limitations of both classic and comprehensive strategies for miRNA target prediction .

Computational Prediction of MicroRNA Target Genes, Target Prediction Databases, and Web Resources

MicroRNA (miRNA) mediated silencing and repression of mRNA molecules requires complementary base pairing between the "seed" region of the miRNA and the "seed match" region of target mRNAs. While this mechanism is fairly well understood, accurate prediction of valid miRNA targets remains challenging due to factors such as imperfect sequence specificity, target site availability, and the thermodynamic stability of the mRNA structure itself. As knowledge of what genes are being targeted by each miRNA is arguably the most important facet of miRNA biology, many approaches have been developed to address the need for reliable prediction and ranking of putative targets, with most using a combination of various strategies such as evolutionary conservation, statistical inference, and distinct features of the target sequences themselves. This chapter reviews the pros and cons of a number of different prediction algorithms, showcases some databases that store experimentally validated miRNA targets, and also provides a case study that profiles some of the potential microRNA-mRNA interactions predicted by each methodology for various human genes.

A microRNA negative feedback loop downregulates vesicle transport and inhibits fear memory

The SNARE-mediated vesicular transport pathway plays major roles in synaptic remodeling associated with formation of long-term memories, but the mechanisms that regulate this pathway during memory acquisition are not fully understood. Here we identify miRNAs that are up-regulated in the rodent hippocampus upon contextual fear-conditioning and identify the vesicular transport and synaptogenesis pathways as the major targets of the fear-induced miRNAs. We demonstrate that miR-153, a member of this group, inhibits the expression of key components of the vesicular transport machinery, and down-regulates Glutamate receptor A1 trafficking and neurotransmitter release. MiR-153 expression is specifically induced during LTP induction in hippocampal slices and its knockdown in the hippocampus of adult mice results in enhanced fear memory. Our results suggest that miR-153, and possibly other fear-induced miRNAs, act as components of a negative feedback loop that blocks neuronal hyperactivity at least partly through the inhibition of the vesicular transport pathway.

DOI:http://dx.doi.org/10.7554/eLife.22467.001

Tools for Sequence-Based miRNA Target Prediction: What to Choose?

MicroRNAs (miRNAs) are defined as small non-coding RNAs ~22 nt in length. They regulate gene expression at a post-transcriptional level through complementary base pairing with the target mRNA, leading to mRNA degradation and therefore blocking translation. In the last decade, the dysfunction of miRNAs has been related to the development and progression of many diseases. Currently, researchers need a method to identify precisely the miRNA targets, prior to applying experimental approaches that allow a better functional characterization of miRNAs in biological processes and can thus predict their effects. Computational prediction tools provide a rapid method to identify putative miRNA targets. However, since a large number of tools for the prediction of miRNA:mRNA interactions have been developed, all with different algorithms, the biological researcher sometimes does not know which is the best choice for his study and many times does not understand the bioinformatic basis of these tools. This review describes the biological fundamentals of these prediction tools, characterizes the main sequence-based algorithms, and offers some insights into their uses by biologists.

IRNdb: the database of immunologically relevant non-coding RNAs

MicroRNAs (miRNAs), long non-coding RNAs (lncRNAs) and other functional non-coding RNAs (ncRNAs) have emerged as pivotal regulators involved in multiple biological processes. Recently, ncRNA control of gene expression has been identified as a critical regulatory mechanism in the immune system. Despite the great efforts made to discover and characterize ncRNAs, the functional role for most remains unknown. To facilitate discoveries in ncRNA regulation of immune system-related processes, we developed the database of immunologically relevant ncRNAs and target genes (IRNdb). We integrated mouse data on predicted and experimentally supported ncRNA-target interactions, ncRNA and gene annotations, biological pathways and processes and experimental data in a uniform format with a user-friendly web interface. The current version of IRNdb documents 12 930 experimentally supported miRNA-target interactions between 724 miRNAs and 2427 immune-related mouse targets. In addition, we recorded 22 453 lncRNA-immune target and 377 PIWI-interacting RNA-immune target interactions. IRNdb is a comprehensive searchable data repository which will be of help in studying the role of ncRNAs in the immune system.

Database URL:http://irndb.org

A position-specific 3'UTR sequence that accelerates mRNA decay

The 3′ untranslated regions (3′UTRs) of mammalian mRNAs direct an extensive range of alternative post-transcriptional outcomes, including regulation of mRNA decay and translation, contributing significantly to overall gene regulation. However, our knowledge of the underlying sequences and mechanisms is incomplete. We identified a novel 3′UTR sequence motif in mammals that targets mRNAs for transcript degradation. The motif is found in hundreds of mRNAs and is enriched in transcripts encoding regulatory proteins, such as transcription and signaling factors. Degradation of mRNAs containing the motif is mediated by the CCR4-NOT deadenylation complex. We identified hnRNPs A1 and A2/B1 as trans factors that directly bind to the motif, indicating a novel role for these proteins in deadenylation. Interestingly, a genome-wide analysis of the impact of this new regulatory pathway showed that the most active motifs are located within the 5′ and 3′-terminal portions of 3′UTRs, whereas elements in the center tend to be inactive. The highly position-specific function of the motif adds a new layer of regulation to gene expression mediated by 3′UTRs.

MicroRNA-regulated viral vectors for gene therapy

Safe and effective gene therapy approaches require targeted tissue-specific transfer of a therapeutic transgene. Besides traditional approaches, such as transcriptional and transductional targeting, microRNA-dependent post-transcriptional suppression of transgene expression has been emerging as powerful new technology to increase the specificity of vector-mediated transgene expression. MicroRNAs are small non-coding RNAs and often expressed in a tissue-, lineage-, activation- or differentiation-specific pattern. They typically regulate gene expression by binding to imperfectly complementary sequences in the 3' untranslated region (UTR) of the mRNA. To control exogenous transgene expression, tandem repeats of artificial microRNA target sites are usually incorporated into the 3' UTR of the transgene expression cassette, leading to subsequent degradation of transgene mRNA in cells expressing the corresponding microRNA. This targeting strategy, first shown for lentiviral vectors in antigen presenting cells, has now been used for tissue-specific expression of vector-encoded therapeutic transgenes, to reduce immune response against the transgene, to control virus tropism for oncolytic virotherapy, to increase safety of live attenuated virus vaccines and to identify and select cell subsets for pluripotent stem cell therapies, respectively. This review provides an introduction into the technical mechanism underlying microRNA-regulation, highlights new developments in this field and gives an overview of applications of microRNA-regulated viral vectors for cardiac, suicide gene cancer and hematopoietic stem cell therapy, as well as for treatment of neurological and eye diseases.

ImiRP: a computational approach to microRNA target site mutation

BACKGROUND

MicroRNAs (miRNAs) are small ~22 nucleotide non-coding RNAs that function as post-transcriptional regulators of messenger RNA (mRNA) through base-pairing to 6-8 nucleotide long target sites, usually located within the mRNA 3' untranslated region. A common approach to validate and probe microRNA-mRNA interactions is to mutate predicted target sites within the mRNA and determine whether it affects miRNA-mediated activity. The introduction of miRNA target site mutations, however, is potentially problematic as it may generate new, "illegitimate sites" target sites for other miRNAs, which may affect the experimental outcome. While it is possible to manually generate and check single miRNA target site mutations, this process can be time consuming, and becomes particularly onerous and error prone when multiple sites are to be mutated simultaneously. We have developed a modular Java-based system called ImiRP (Illegitimate miRNA Predictor) to solve this problem and to facilitate miRNA target site mutagenesis.

RESULTS

The ImiRP interface allows users to input a sequence of interest, specify the locations of multiple predicted target sites to mutate, and set parameters such as species, mutation strategy, and disallowed illegitimate target site types. As mutant sequences are generated, ImiRP utilizes the miRBase high confidence miRNA dataset to identify illegitimate target sites in each mutant sequence by comparing target site predictions between input and mutant sequences. ImiRP then assembles a final mutant sequence in which all specified target sites have been mutated.

CONCLUSIONS

ImiRP is a mutation generator program that enables selective disruption of specified miRNA target sites while ensuring predicted target sites for other miRNAs are not inadvertently created. ImiRP supports mutagenesis of single and multiple miRNA target sites within a given sequence, including sites that overlap. This software will be particularly useful for studies looking at microRNA cooperativity, where mutagenesis of multiple microRNA target sites may be desired. The software is available at imirp.org and is available open source for download through GitHub ( https://github.com/imirp ).

MiR-200b/200c/429 subfamily negatively regulates Rho/ROCK signaling pathway to suppress hepatocellular carcinoma metastasis

MiR-200 family is an important regulator of epithelial-mesenchymal transition and has been implicated in human carcinogenesis. However, their expression and functions in human cancers remain controversial. In the work presented here, we showed that miR-200 family members were frequently down-regulated in hepatocellular carcinoma (HCC). Although all five members of miR-200 family inhibited ZEB1/2 expression in HCC cell lines, we showed that overexpression only of the miR-200b/200c/429 subfamily, but not the miR-200a/141 subfamily, resulted in impeded HCC cell migration. Further investigations led to the identification of RhoA and ROCK2 as specific down-stream targets of the miR-200b/200c/429 subfamily. We demonstrated that the miR-200b/200c/429 subfamily inhibited HCC cell migration through modulating Rho/ROCK mediated cell cytoskeletal reorganization and cell-substratum adhesion. Re-expression of miR-200b significantly suppressed lung metastasis of HCC cells in an orthotopic liver implantation model in vivo. In conclusion, our findings identified the miR-200b/200c/429 subfamily as metastasis suppressor microRNAs in human HCC and highlighted the functional discrepancy among miR-200 family members.

Inflammatory gene networks in term human decidual cells define a potential signature for cytokine-mediated parturition

BACKGROUND

Inflammation is a proximate mediator of preterm birth and fetal injury. During inflammation several microRNAs (22 nucleotide noncoding ribonucleic acid (RNA) molecules) are up-regulated in response to cytokines such as interleukin-1β. MicroRNAs, in most cases, fine-tune gene expression, including both up-regulation and down-regulation of their target genes. However, the role of pro- and antiinflammatory microRNAs in this process is poorly understood.

OBJECTIVE

The principal goal of the work was to examine the inflammatory genomic profile of human decidual cells challenged with a proinflammatory cytokine known to be present in the setting of preterm parturition. We determined the coding (messenger RNA) and noncoding (microRNA) sequences to construct a network of interacting genes during inflammation using an in vitro model of decidual stromal cells.

STUDY DESIGN

The effects of interleukin-1β exposure on mature microRNA expression were tested in human decidual cell cultures using the multiplexed NanoString platform, whereas the global inflammatory transcriptional response was measured using oligonucleotide microarrays. Differential expression of select transcripts was confirmed by quantitative real time-polymerase chain reaction. Bioinformatics tools were used to infer transcription factor activation and regulatory interactions.

RESULTS

Interleukin-1β elicited up- and down-regulation of 350 and 78 nonredundant transcripts (false discovery rate < 0.1), respectively, including induction of numerous cytokines, chemokines, and other inflammatory mediators. Whereas this transcriptional response included marked changes in several microRNA gene loci, the pool of fully processed, mature microRNA was comparatively stable following a cytokine challenge. Of a total of 6 mature microRNAs identified as being differentially expressed by NanoString profiling, 2 (miR-146a and miR-155) were validated by quantitative real time-polymerase chain reaction. Using complementary bioinformatics approaches, activation of several inflammatory transcription factors could be inferred downstream of interleukin-1β based on the overall transcriptional response. Further analysis revealed that miR-146a and miR-155 both target genes involved in inflammatory signaling, including Toll-like receptor and mitogen-activated protein kinase pathways.

CONCLUSION

Stimulation of decidual cells with interleukin-1β alters the expression of microRNAs that function to temper proinflammatory signaling. In this setting, some microRNAs may be involved in tissue-level inflammation during the bulk of gestation and assist in pregnancy maintenance.

MicroRNAs Expressed during Viral Infection: Biomarker Potential and Therapeutic Considerations

MicroRNAs (miRNAs) are short sequences of noncoding single-stranded RNAs that exhibit inhibitory effects on complementary target mRNAs. Recently, it has been discovered that certain viruses express their own miRNAs, while other viruses activate the transcription of cellular miRNAs for their own benefit. This review summarizes the viral and/or cellular miRNAs that are transcribed during infection, with a focus on the biomarker and therapeutic potential of miRNAs (or their antagomirs). Several human viruses of clinical importance are discussed, namely, herpesviruses, polyomaviruses, hepatitis B virus, hepatitis C virus, human papillomavirus, and human immunodeficiency virus.

Bioinformatic tools for microRNA dissection

Recently, microRNAs (miRNAs) have emerged as important elements of gene regulatory networks. MiRNAs are endogenous single-stranded non-coding RNAs (~22-nt long) that regulate gene expression at the post-transcriptional level. Through pairing with mRNA, miRNAs can down-regulate gene expression by inhibiting translation or stimulating mRNA degradation. In some cases they can also up-regulate the expression of a target gene. MiRNAs influence a variety of cellular pathways that range from development to carcinogenesis. The involvement of miRNAs in several human diseases, particularly cancer, makes them potential diagnostic and prognostic biomarkers. Recent technological advances, especially high-throughput sequencing, have led to an exponential growth in the generation of miRNA-related data. A number of bioinformatic tools and databases have been devised to manage this growing body of data. We analyze 129 miRNA tools that are being used in diverse areas of miRNA research, to assist investigators in choosing the most appropriate tools for their needs.

Improving microRNA target prediction by modeling with unambiguously identified microRNA-target pairs from CLIP-ligation studies

MOTIVATION

MicroRNAs (miRNAs) are small non-coding RNAs that are extensively involved in many physiological and disease processes. One major challenge in miRNA studies is the identification of genes targeted by miRNAs. Currently, most researchers rely on computational programs to initially identify target candidates for subsequent validation. Although considerable progress has been made in recent years for computational target prediction, there is still significant room for algorithmic improvement.

RESULTS

Here, we present an improved target prediction algorithm, which was developed by modeling high-throughput profiling data from recent CLIPL (crosslinking and immunoprecipitation followed by RNA ligation) sequencing studies. In these CLIPL-seq studies, the RNA sequences in each miRNA-target pair were covalently linked and unambiguously determined experimentally. By analyzing the CLIPL data, many known and novel features relevant to target recognition were identified and then used to build a computational model for target prediction. Comparative analysis showed that the new algorithm had improved performance over existing algorithms when applied to independent experimental data.

AVAILABILITY AND IMPLEMENTATION

All the target prediction data as well as the prediction tool can be accessed at miRDB (http://mirdb.org).

CONTACT

xwang@radonc.wustl.edu.

miRNA-target chimeras reveal miRNA 3'-end pairing as a major determinant of Argonaute target specificity

microRNAs (miRNAs) act as sequence-specific guides for Argonaute (AGO) proteins, which mediate posttranscriptional silencing of target messenger RNAs. Despite their importance in many biological processes, rules governing AGO–miRNA targeting are only partially understood. Here we report a modified AGO HITS-CLIP strategy termed CLEAR (covalent ligation of endogenous Argonaute-bound RNAs)-CLIP, which enriches miRNAs ligated to their endogenous mRNA targets. CLEAR-CLIP mapped ∼130,000 endogenous miRNA–target interactions in mouse brain and ∼40,000 in human hepatoma cells. Motif and structural analysis define expanded pairing rules for over 200 mammalian miRNAs. Most interactions combine seed-based pairing with distinct, miRNA-specific patterns of auxiliary pairing. At some regulatory sites, this specificity confers distinct silencing functions to miRNA family members with shared seed sequences but divergent 3′-ends. This work provides a means for explicit biochemical identification of miRNA sites in vivo, leading to the discovery that miRNA 3′-end pairing is a general determinant of AGO binding specificity.

microRNAs (miRNAs) act as sequence-specific guides for Argonaute (AGO) proteins. By using a modified AGO HITS-CLIP strategy that enriches miRNAs ligated to their endogenous mRNA targets, here the authors show that miRNA 3' end pairing is a general determinant of AGO binding specificity.

Comparative Characterization of Cardiac Development Specific microRNAs: Fetal Regulators for Future

MicroRNAs (miRNAs) are small, conserved RNAs known to regulate several biological processes by influencing gene expression in eukaryotes. The implication of miRNAs as another player of regulatory layers during heart development and diseases has recently been explored. However, there is no study which elucidates the profiling of miRNAs during development of heart till date. Very limited miRNAs have been reported to date in cardiac context. In addition, integration of large scale experimental data with computational and comparative approaches remains an unsolved challenge.The present study was designed to identify the microRNAs implicated in heart development using next generation sequencing, bioinformatics and experimental approaches. We sequenced six small RNA libraries prepared from different developmental stages of the heart using chicken as a model system to produce millions of short sequence reads. We detected 353 known and 703 novel miRNAs involved in heart development. Out of total 1056 microRNAs identified, 32.7% of total dataset of known microRNAs displayed differential expression whereas seven well studied microRNAs namely let-7, miR-140, miR-181, miR-30, miR-205, miR-103 and miR-22 were found to be conserved throughout the heart development. The 3'UTR sequences of genes were screened from Gallus gallus genome for potential microRNA targets. The target mRNAs were appeared to be enriched with genes related to cell cycle, apoptosis, signaling pathways, extracellular remodeling, metabolism, chromatin remodeling and transcriptional regulators. Our study presents the first comprehensive overview of microRNA profiling during heart development and prediction of possible cardiac specific targets and has a big potential in future to develop microRNA based therapeutics against cardiac pathologies where fetal gene re-expression is witnessed in adult heart.

Bespoke RNA recognition by Pumilios

Pumilio is an RNA-binding protein originally identified in Drosophila, with a Puf domain made up of eight Puf repeats, three helix bundles arranged in a rainbow architecture, where each repeat recognizes a single base of the RNA-binding sequence. The eight-base recognition sequence can therefore be modified simply via mutation of the repeat that recognizes the base to be changed and this is understood in detail via high-resolution crystal structures. The binding mechanism is also altered in a variety of homologues from different species, with bases flipped out from the binding site to regenerate a consensus sequence. Thus Pumilios can be designed with bespoke RNA recognition sequences and can be fused to nucleases, split GFP, etc. as tools in vitro and in cells.

Predicting effective microRNA target sites in mammalian mRNAs

MicroRNA targets are often recognized through pairing between the miRNA seed region and complementary sites within target mRNAs, but not all of these canonical sites are equally effective, and both computational and in vivo UV-crosslinking approaches suggest that many mRNAs are targeted through non-canonical interactions. Here, we show that recently reported non-canonical sites do not mediate repression despite binding the miRNA, which indicates that the vast majority of functional sites are canonical. Accordingly, we developed an improved quantitative model of canonical targeting, using a compendium of experimental datasets that we pre-processed to minimize confounding biases. This model, which considers site type and another 14 features to predict the most effectively targeted mRNAs, performed significantly better than existing models and was as informative as the best high-throughput in vivo crosslinking approaches. It drives the latest version of TargetScan (v7.0; targetscan.org), thereby providing a valuable resource for placing miRNAs into gene-regulatory networks.

Experimental procedures to identify and validate specific mRNA targets of miRNAs

Functionally matured microRNAs (miRNAs) are small single-stranded non-coding RNA molecules which are emerging as important post-transcriptional regulators of gene expression and consequently are central players in many physiological and pathological processes. Since the biological roles of individual miRNAs will be dictated by the mRNAs that they regulate, the identification and validation of miRNA/mRNA target interactions is critical for our understanding of the regulatory networks governing biological processes. We promulgate the combined use of prediction algorithms, the examination of curated databases of experimentally supported miRNA/mRNA interactions, manual sequence inspection of cataloged miRNA binding sites in specific target mRNAs, and review of the published literature as a reliable practice for identifying and prioritizing biologically important miRNA/mRNA target pairs. Once a preferred miRNA/mRNA target pair has been selected, we propose that the authenticity of a functional miRNA/mRNA target pair be validated by fulfilling four well-defined experimental criteria. This review summarizes our current knowledge of miRNA biology, miRNA/mRNA target prediction algorithms, validated miRNA/mRNA target data bases, and outlines several experimental methods by which miRNA/mRNA targets can be authenticated. In addition, a case study of human endoglin is presented as an example of the utilization of these methodologies.

Transcriptome dynamics of the microRNA inhibition response

We report a high-resolution time series study of transcriptome dynamics following antimiR-mediated inhibition of miR-9 in a Hodgkin lymphoma cell-line—the first such dynamic study of the microRNA inhibition response—revealing both general and specific aspects of the physiological response. We show miR-9 inhibition inducing a multiphasic transcriptome response, with a direct target perturbation before 4 h, earlier than previously reported, amplified by a downstream peak at ∼32 h consistent with an indirect response due to secondary coherent regulation. Predictive modelling indicates a major role for miR-9 in post-transcriptional control of RNA processing and RNA binding protein regulation. Cluster analysis identifies multiple co-regulated gene regulatory modules. Functionally, we observe a shift over time from mRNA processing at early time points to translation at later time points. We validate the key observations with independent time series qPCR and we experimentally validate key predicted miR-9 targets. Methodologically, we developed sensitive functional data analytic predictive methods to analyse the weak response inherent in microRNA inhibition experiments. The methods of this study will be applicable to similar high-resolution time series transcriptome analyses and provides the context for more accurate experimental design and interpretation of future microRNA inhibition studies.

ComiRNet: a web-based system for the analysis of miRNA-gene regulatory networks

Background

The understanding of mechanisms and functions of microRNAs (miRNAs) is fundamental for the study of many biological processes and for the elucidation of the pathogenesis of many human diseases. Technological advances represented by high-throughput technologies, such as microarray and next-generation sequencing, have significantly aided miRNA research in the last decade. Nevertheless, the identification of true miRNA targets and the complete elucidation of the rules governing their functional targeting remain nebulous. Computational tools have been proven to be fundamental for guiding experimental validations for the discovery of new miRNAs, for the identification of their targets and for the elucidation of their regulatory mechanisms.

Description

ComiRNet (Co-clustered miRNA Regulatory Networks) is a web-based database specifically designed to provide biologists and clinicians with user-friendly and effective tools for the study of miRNA-gene target interaction data and for the discovery of miRNA functions and mechanisms. Data in ComiRNet are produced by a combined computational approach based on: 1) a semi-supervised ensemble-based classifier, which learns to combine miRNA-gene target interactions (MTIs) from several prediction algorithms, and 2) the biclustering algorithm HOCCLUS2, which exploits the large set of produced predictions, with the associated probabilities, to identify overlapping and hierarchically organized biclusters that represent miRNA-gene regulatory networks (MGRNs).

Conclusions

ComiRNet represents a valuable resource for elucidating the miRNAs' role in complex biological processes by exploiting data on their putative function in the context of MGRNs. ComiRnet currently stores about 5 million predicted MTIs between 934 human miRNAs and 30,875 mRNAs, as well as 15 bicluster hierarchies, each of which represents MGRNs at different levels of granularity. The database can be freely accessed at: http://comirnet.di.uniba.it.

miRGate: a curated database of human, mouse and rat miRNA-mRNA targets

MicroRNAs (miRNAs) are small non-coding elements involved in the post-transcriptional down-regulation of gene expression through base pairing with messenger RNAs (mRNAs). Through this mechanism, several miRNA-mRNA pairs have been described as critical in the regulation of multiple cellular processes, including early embryonic development and pathological conditions. Many of these pairs (such as miR-15 b/BCL2 in apoptosis or BART-6/BCL6 in diffuse large B-cell lymphomas) were experimentally discovered and/or computationally predicted. Available tools for target prediction are usually based on sequence matching, thermodynamics and conservation, among other approaches. Nevertheless, the main issue on miRNA-mRNA pair prediction is the little overlapping results among different prediction methods, or even with experimentally validated pairs lists, despite the fact that all rely on similar principles. To circumvent this problem, we have developed miRGate, a database containing novel computational predicted miRNA-mRNA pairs that are calculated using well-established algorithms. In addition, it includes an updated and complete dataset of sequences for both miRNA and mRNAs 3'-Untranslated region from human (including human viruses), mouse and rat, as well as experimentally validated data from four well-known databases. The underlying methodology of miRGate has been successfully applied to independent datasets providing predictions that were convincingly validated by functional assays. miRGate is an open resource available at http://mirgate.bioinfo.cnio.es. For programmatic access, we have provided a representational state transfer web service application programming interface that allows accessing the database at http://mirgate.bioinfo.cnio.es/API/ Database URL: http://mirgate.bioinfo.cnio.es

Re-thinking miRNA-mRNA interactions: intertwining issues confound target discovery

Despite a library full of literature on miRNA biology, core issues relating to miRNA target detection, biological effect, and mode of action remain controversial. This essay proposes that the predominant mechanism of direct miRNA action is translational inhibition, whereas the bulk of miRNA effects are mRNA based. It explores several issues confounding miRNA target detection, and discusses their impact on the dominance of “miRNA seed” dogma and the exploration of non-canonical binding sites. Finally, it makes comparisons between miRNA target prediction and transcription factor binding prediction, and questions the value of characterizing miRNA binding sites based on which miRNA nucleotides are paired with an mRNA.

Accurate transcriptome-wide prediction of microRNA targets and small interfering RNA off-targets with MIRZA-G

Small interfering RNA (siRNA)-mediated knock-down is a widely used experimental approach to characterizing gene function. Although siRNAs are designed to guide the cleavage of perfectly complementary mRNA targets, acting similarly to microRNAs (miRNAs), siRNAs down-regulate the expression of hundreds of genes to which they have only partial complementarity. Prediction of these siRNA ‘off-targets’ remains difficult, due to the incomplete understanding of siRNA/miRNA–target interactions. Combining a biophysical model of miRNA–target interaction with structure and sequence features of putative target sites we developed a suite of algorithms, MIRZA-G, for the prediction of miRNA targets and siRNA off-targets on a genome-wide scale. The MIRZA-G variant that uses evolutionary conservation performs better than currently available methods in predicting canonical miRNA target sites and in addition, it predicts non-canonical miRNA target sites with similarly high accuracy. Furthermore, MIRZA-G variants predict siRNA off-target sites with an accuracy unmatched by currently available programs. Thus, MIRZA-G may prove instrumental in the analysis of data resulting from large-scale siRNA screens.

Interactions between cancer cells and normal cells via miRNAs in extracellular vesicles

MicroRNAs (miRNAs) exhibit many functions in biological activities. Recent studies have shown that miRNAs exist outside cells and are transferred between cells. Extracellular miRNAs are protected from ribonucleases found in body fluids through binding to specific proteins or by being encapsulated in lipid bilayer vesicles. Here, we review the mechanisms of the secretion and uptake as well as the functions of extracellular miRNAs, particularly those encapsulated in extracellular vesicles. Extracellular vesicles are related to cancer progression, and some miRNAs in extracellular vesicles are associated with cancer cells. We describe the transfer of cancer-related miRNAs between cancer cells and non-cancerous cells. Finally, we discuss the anticipated applications of miRNAs present in extracellular vesicles in diagnostics and therapeutics.

miR-CLIP capture of a miRNA targetome uncovers a lincRNA H19-miR-106a interaction

Identifying the interaction partners of noncoding RNAs is essential for elucidating their functions. We have developed an approach, termed microRNA crosslinking and immunoprecipitation (miR-CLIP), using pre-miRNAs modified with psoralen and biotin to capture their targets in cells. Photo-crosslinking and Argonaute 2 immunopurification followed by streptavidin affinity purification of probe-linked RNAs provided selectivity in the capture of targets, which were identified by deep sequencing. miR-CLIP with pre-miR-106a, a miR-17-5p family member, identified hundreds of putative targets in HeLa cells, many carrying conserved sequences complementary to the miRNA seed but also many that were not predicted computationally. miR-106a overexpression experiments confirmed that miR-CLIP captured functional targets, including H19, a long noncoding RNA that is expressed during skeletal muscle cell differentiation. We showed that miR-17-5p family members bind H19 in HeLa cells and myoblasts. During myoblast differentiation, levels of H19, miR-17-5p family members and mRNA targets changed in a manner suggesting that H19 acts as a 'sponge' for these miRNAs.

Improving miRNA-mRNA interaction predictions

Background

MicroRNAs are short RNA molecules that post-transcriptionally regulate gene expression. Today, microRNA target prediction remains challenging since very few have been experimentally validated and sequence-based predictions have large numbers of false positives. Furthermore, due to the different measuring rules used in each database of predicted interactions, the selection of the most reliable ones requires extensive knowledge about each algorithm.

Results

Here we propose two methods to measure the confidence of predicted interactions based on experimentally validated information. The output of the methods is a combined database where new scores and statistical confidences are re-assigned to each predicted interaction. The new scores allow the robust combination of several databases without the effect of low-performing algorithms dragging down good-performing ones. The combined databases obtained using both algorithms described in this paper outperform each of the existing predictive algorithms that were considered for the combination.

Conclusions

Our approaches are a useful way to integrate predicted interactions from different databases. They reduce the selection of interactions to a unique database based on an intuitive score and allow comparing databases between them.

Hunting the needle in the haystack: a guide to obtain biologically meaningful microRNA targets

MicroRNAs (miRNAs) are endogenous small non-coding RNAs of ~23 nucleotides in length that form up a novel class of regulatory determinants, with a large set of target mRNAs postulated for every single miRNA. Thousands of miRNAs have been discovered so far, with hundreds of them shown to govern biological processes with impact on disease. However, very little is known about how they specifically interfere with biological pathways and disease mechanisms. To investigate this interaction, the hunt for direct miRNA targets that mediate the miRNA effects—the “needle in the haystack”—is an essential step. In this review we provide a comprehensive workflow of successfully applied methods starting from the identification of putative miRNA-target pairs, followed by validation of direct miRNA–mRNA interactions, and finally presenting methods that dissect the impact of particular miRNA-target pairs on a biological process or disease. This guide allows the way to be paved for obtaining biologically meaningful miRNA targets.

Cupid: simultaneous reconstruction of microRNA-target and ceRNA networks

We introduce a method for simultaneous prediction of microRNA–target interactions and their mediated competitive endogenous RNA (ceRNA) interactions. Using high-throughput validation assays in breast cancer cell lines, we show that our integrative approach significantly improves on microRNA–target prediction accuracy as assessed by both mRNA and protein level measurements. Our biochemical assays support nearly 500 microRNA–target interactions with evidence for regulation in breast cancer tumors. Moreover, these assays constitute the most extensive validation platform for computationally inferred networks of microRNA–target interactions in breast cancer tumors, providing a useful benchmark to ascertain future improvements.

Exploring the miRNA regulatory network using evolutionary correlations

Post-transcriptional regulation by miRNAs is a widespread and highly conserved phenomenon in metazoans, with several hundreds to thousands of conserved binding sites for each miRNA, and up to two thirds of all genes under miRNA regulation. At the same time, the effect of miRNA regulation on mRNA and protein levels is usually quite modest and associated phenotypes are often weak or subtle. This has given rise to the notion that the highly interconnected miRNA regulatory network exerts its function less through any individual link and more via collective effects that lead to a functional interdependence of network links. We present a Bayesian framework to quantify conservation of miRNA target sites using vertebrate whole-genome alignments. The increased statistical power of our phylogenetic model allows detection of evolutionary correlation in the conservation patterns of site pairs. Such correlations could result from collective functions in the regulatory network. For instance, co-conservation of target site pairs supports a selective benefit of combinatorial regulation by multiple miRNAs. We find that some miRNA families are under pronounced co-targeting constraints, indicating a high connectivity in the regulatory network, while others appear to function in a more isolated way. By analyzing coordinated targeting of different curated gene sets, we observe distinct evolutionary signatures for protein complexes and signaling pathways that could reflect differences in control strategies. Our method is easily scalable to analyze upcoming larger data sets, and readily adaptable to detect high-level selective constraints between other genomic loci. We thus provide a proof-of-principle method to understand regulatory networks from an evolutionary perspective.

MicroRNA target identification: lessons from hypoxamiRs

SIGNIFICANCE

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.

RECENT ADVANCES

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.

CRITICAL ISSUES

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.

FUTURE DIRECTIONS

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.

A systems biology approach identified different regulatory networks targeted by KSHV miR-K12-11 in B cells and endothelial cells

Background

Kaposi’s sarcoma associated herpes virus (KSHV) is associated with tumors of endothelial and lymphoid origin. During latent infection, KSHV expresses miR-K12-11, an ortholog of the human tumor gene hsa-miR-155. Both gene products are microRNAs (miRNAs), which are important post-transcriptional regulators that contribute to tissue specific gene expression. Advances in target identification technologies and molecular interaction databases have allowed a systems biology approach to unravel the gene regulatory networks (GRNs) triggered by miR-K12-11 in endothelial and lymphoid cells. Understanding the tissue specific function of miR-K12-11 will help to elucidate underlying mechanisms of KSHV pathogenesis.

Results

Ectopic expression of miR-K12-11 differentially affected gene expression in BJAB cells of lymphoid origin and TIVE cells of endothelial origin. Direct miRNA targeting accounted for a small fraction of the observed transcriptome changes: only 29 genes were identified as putative direct targets of miR-K12-11 in both cell types. However, a number of commonly affected biological pathways, such as carbohydrate metabolism and interferon response related signaling, were revealed by gene ontology analysis. Integration of transcriptome profiling, bioinformatic algorithms, and databases of protein-protein interactome from the ENCODE project identified different nodes of GRNs utilized by miR-K12-11 in a tissue-specific fashion. These effector genes, including cancer associated transcription factors and signaling proteins, amplified the regulatory potential of a single miRNA, from a small set of putative direct targets to a larger set of genes.

Conclusions

This is the first comparative analysis of miRNA-K12-11’s effects in endothelial and B cells, from tissues infected with KSHV in vivo. MiR-K12-11 was able to broadly modulate gene expression in both cell types. Using a systems biology approach, we inferred that miR-K12-11 establishes its GRN by both repressing master TFs and influencing signaling pathways, to counter the host anti-viral response and to promote proliferation and survival of infected cells. The targeted GRNs are more reproducible and informative than target gene identification, and our approach can be applied to other regulatory factors of interest.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-668) contains supplementary material, which is available to authorized users.

The multiMiR R package and database: integration of microRNA-target interactions along with their disease and drug associations

microRNAs (miRNAs) regulate expression by promoting degradation or repressing translation of target transcripts. miRNA target sites have been catalogued in databases based on experimental validation and computational prediction using various algorithms. Several online resources provide collections of multiple databases but need to be imported into other software, such as R, for processing, tabulation, graphing and computation. Currently available miRNA target site packages in R are limited in the number of databases, types of databases and flexibility. We present multiMiR, a new miRNA-target interaction R package and database, which includes several novel features not available in existing R packages: (i) compilation of nearly 50 million records in human and mouse from 14 different databases, more than any other collection; (ii) expansion of databases to those based on disease annotation and drug microRNAresponse, in addition to many experimental and computational databases; and (iii) user-defined cutoffs for predicted binding strength to provide the most confident selection. Case studies are reported on various biomedical applications including mouse models of alcohol consumption, studies of chronic obstructive pulmonary disease in human subjects, and human cell line models of bladder cancer metastasis. We also demonstrate how multiMiR was used to generate testable hypotheses that were pursued experimentally.

Embryonic stem cell-specific microRNAs contribute to pluripotency by inhibiting regulators of multiple differentiation pathways

The findings that microRNAs (miRNAs) are essential for early development in many species and that embryonic miRNAs can reprogram somatic cells into induced pluripotent stem cells suggest that these miRNAs act directly on transcriptional and chromatin regulators of pluripotency. To elucidate the transcription regulatory networks immediately downstream of embryonic miRNAs, we extended the motif activity response analysis approach that infers the regulatory impact of both transcription factors (TFs) and miRNAs from genome-wide expression states. Applying this approach to multiple experimental data sets generated from mouse embryonic stem cells (ESCs) that did or did not express miRNAs of the ESC-specific miR-290-295 cluster, we identified multiple TFs that are direct miRNA targets, some of which are known to be active during cell differentiation. Our results provide new insights into the transcription regulatory network downstream of ESC-specific miRNAs, indicating that these miRNAs act on cell cycle and chromatin regulators at several levels and downregulate TFs that are involved in the innate immune response.

Identification and consequences of miRNA-target interactions--beyond repression of gene expression

Comparative genomics analyses and high-throughput experimental studies indicate that a microRNA (miRNA) binds to hundreds of sites across the transcriptome. Although the knockout of components of the miRNA biogenesis pathway has profound phenotypic consequences, most predicted miRNA targets undergo small changes at the mRNA and protein levels when the expression of the miRNA is perturbed. Alternatively, miRNAs can establish thresholds in and increase the coherence of the expression of their target genes, as well as reduce the cell-to-cell variability in target gene expression. Here, we review the recent progress in identifying miRNA targets and the emerging paradigms of how miRNAs shape the dynamics of target gene expression.

Therapeutic targeting of microRNAs: current status and future challenges

MicroRNAs (miRNAs) are evolutionarily conserved small non-coding RNAs that have crucial roles in regulating gene expression. Increasing evidence supports a role for miRNAs in many human diseases, including cancer and autoimmune disorders. The function of miRNAs can be efficiently and specifically inhibited by chemically modified antisense oligonucleotides, supporting their potential as targets for the development of novel therapies for several diseases. In this Review we summarize our current knowledge of the design and performance of chemically modified miRNA-targeting antisense oligonucleotides, discuss various in vivo delivery strategies and analyse ongoing challenges to ensure the specificity and efficacy of therapeutic oligonucleotides in vivo. Finally, we review current progress on the clinical development of miRNA-targeting therapeutics.

Resources for Small Regulatory RNAs

Over the past twenty years, new classes of regulatory RNAs have been discovered, previously hidden in the transcriptome mostly due to their small size. These small regulatory RNAs include small interfering RNAs (siRNAs), microRNAs (miRNAs), and Piwi-interacting RNAs (piRNAs). Numerous databases have been developed to store information about these small regulatory RNAs, and many tools have been developed to work with the data. This overview introduces the reader to the many resources available for working with small regulatory RNAs.

MicroRNA target prediction: theory and practice

The present study is one of the few that includes tissue samples in the evaluation of target prediction algorithms designed to detect microRNA (miRNA) sequences that might interact with particular messenger RNA (mRNA) sequences. Twelve different target prediction tools were used to find miRNA sequences that might interact with CCL20 gene expression. Different algorithms predicted controversial miRNA sequences for CCL20 regulation due to a different weighting of parameters. Hsa-miR-21 and hsa-miR-145 suggested by four or more programs were chosen for further investigation. Possible real interaction of these miRNA sequences with CCL20 gene expression was monitored using luciferase assays and expression analyses of tissue samples of colorectal adenocarcinoma by either qRT-PCR or ELISA. Folding status of seed-binding sites in complete mRNA and 3'UTR of CCL20 was predicted. Prediction of miRNA expression was attempted based on CCL20 expression data. Eight of the target prediction tools forecasted a role for hsa-miR-21 and four mentioned hsa-miR-145 in CCL20 gene regulation. Laboratory experimentation showed that CCL20 may serve as a target of hsa-miR-21 but not hsa-miR-145. Expression of the molecules resulted in no clear assertion. Folding of seed-binding sites was predicted to be relatively constant for the complete mRNA and 3'UTR. Predicting miRNA expression based on target gene expression was impossible. This might be attributable to the fact that effects of miRNA activity may oscillate between gene product repression and activation. Additional systematic studies are needed to address this issue.