miRNA Target Recognition Research Articles

Role of Recognition MicroRNAs in Hemaphysalis longicornis and Theileria orientalis Interactions.

Ticks are an important type of pathogen transmission vector, and pathogens not only cause serious harm to livestock but can also infect humans. Because of the roles that ticks play in disease transmission, reducing tick pathogen infectivity has become increasingly important and requires the identification and characterization of these pathogens and their interaction mechanisms. In this study, we determined the miRNA expression profile of Hemaphysalis longicornis infected with Theileria orientalis, predicted the target genes of miRNAs involved in this infection process, and investigated the role of miRNA target recognition during host-pathogen interactions. The results showed that longipain is a target gene of miR-5309, which was differentially expressed at different developmental stages and in various tissues in the control group. However, the miR-5309 level was reduced in the infection group. Analysis of the interaction between miRNA and the target gene showed that miR-5309 negatively regulated the expression of the longipain protein during the infection of H. longicornis with T. orientalis. To verify this inference, we compared longipain with the blocking agent orientalis. In this study, the expression of longipain was upregulated by the inhibition of miR-5309 in ticks, and the ability of the antibody produced by the tick-derived protein to attenuate T. orientalis infection was verified through animal immunity and antigen-antibody binding tests. The results showed that expression of the longipain + GST fusion protein caused the cattle to produce antibodies that could be successfully captured by ticks, and cellular immunity was subsequently activated in the ticks, resulting in a subtractive effect on T. orientalis infection. This research provides ideas for the control of ticks and tickborne diseases and a research basis for studying the mechanism underlying the interaction between ticks and pathogens.

An efficient deep learning based predictor for identifying miRNA-triggered phasiRNA loci in plant.

Phasic small interfering RNAs are plant secondary small interference RNAs that typically generated by the convergence of miRNAs and polyadenylated mRNAs. A growing number of studies have shown that miRNA-initiated phasiRNA plays crucial roles in regulating plant growth and stress responses. Experimental verification of miRNA-initiated phasiRNA loci may take considerable time, energy and labor. Therefore, computational methods capable of processing high throughput data have been proposed one by one. In this work, we proposed a predictor (DIGITAL) for identifying miRNA-initiated phasiRNAs in plant, which combined a multi-scale residual network with a bi-directional long-short term memory network. The negative dataset was constructed based on positive data, through replacing 60% of nucleotides randomly in each positive sample. Our predictor achieved the accuracy of 98.48% and 94.02% respectively on two independent test datasets with different sequence length. These independent testing results indicate the effectiveness of our model. Furthermore, DIGITAL is of robustness and generalization ability, and thus can be easily extended and applied for miRNA target recognition of other species. We provide the source code of DIGITAL, which is freely available at https://github.com/yuanyuanbu/DIGITAL.

Overview of Computational and Experimental Methods to Identify Tissue-Specific MicroRNA Targets.

As ubiquitous posttranscriptional regulators of gene expression, microRNAs (miRNAs) play key roles in cell physiology and function across taxa. In the last two decades, we have gained a good understanding about miRNA biogenesis pathways, modes of action, and consequences of miRNA-mediated gene regulation. More recently, research has focused on exploring causes for miRNA dysregulation, miRNA-mediated crosstalk between genes and signaling pathways, and the role of miRNAs in disease.This chapter discusses methods for the identification of miRNA-target interactions and causes for tissue-specific miRNA-target regulation. Computational approaches for predicting miRNA target sites and assessing tissue-specific target regulation are discussed. Moreover, there is an emphasis on features that affect miRNA target recognition and how high-throughput sequencing protocols can help in assessing miRNA-mediated gene regulation on a genome-wide scale. In addition, this chapter introduces some experimental approaches for the validation of miRNA targets as well as web-based resources sharing predicted and validated miRNA-target interactions.

Single Base-Pair Conformational Switch Modulates miR-34a Targeting of Sirt1 mRNA

MicroRNAs (miRNAs) regulate numerous messenger RNAs levels and translation, via binding to the protein Argonaute (Ago). The base pairing between the miRNA and mRNA in the seed region governs target selection and repression efficiency. Biochemical studies and X-ray crystallography structures elucidated the role of Ago and miRNA in this complex, however, structural information on the miRNA-mRNA duplex and its dynamics are still missing. We employ Nuclear Magnetic Resonance R1ρ Relaxation Dispersion and molecular simulations to study the structure and dynamics of miR-34a binding to mRNA of Sirt1, regulating p53 activity. We reveal a switching mode based on a single base pair rearrangement in the miRNA-mRNA duplex, elongating the 6/7mer seed to an 8mer seed. The base pair switch correlates with changing in overall structure of these conformers, which, in hAgo2, indicates two distinct binding modes and the stabilization of the minor conformer exhibit enhanced target repression in cells, shown by luciferase reporter assay. This change in activity indicates that the conformational switch in the miRNA-mRNA duplex can push the complex from an initial “screening” state to an “active” state. Our observations tie together current understanding of the step-wise miRNA target recognition process and shed light on the role of miRNA binding to mRNA beyond the seed.

Bringing MicroRNAs to Light: Methods for MicroRNA Quantification and Visualization in Live Cells.

MiRNAs are small non-coding RNAs that interact with their target mRNAs for posttranscriptional gene regulation. Finely controlled miRNA biogenesis, target recognition and degradation indicate that maintaining miRNA homeostasis is essential for regulating cell proliferation, growth, differentiation and apoptosis. Increasingly, miRNAs have been recognized as a potential biomarker for disease diagnosis. MiRNAs can be found in blood, plasma, and tissues, and miRNA expression and activity differ in developmental stages, tissues and in response to external stimuli. MiRNA transcripts are matured from pri-miRNA over pre-miRNA to mature miRNA, a process that includes multiple steps and enzymes. Many tools are available to identify and quantify specific miRNAs, ranging from measuring total miRNA, specific miRNA activity, miRNA arrays and miRNA localization. The various miRNA assays differ in accuracy, cost, efficiency and convenience of monitoring miRNA dynamics. To acknowledge the significance and increasing research interest in miRNAs, we summarize the traditional as well as novel methods of miRNA quantification with strengths and limitations of various techniques in biochemical and medical research.

Toward a Comprehensive View of MicroRNA Biology.

In this issue of Molecular Cell, two complementary studies illuminate miRNA biology with unprecedented depth and breadth. Reichholf etal. (2019) present a quantitative view of miRNA biogenesis and turnover, while Becker etal. (2019) describe an exhaustive evaluation of miRNA target recognition.

The Role of Tertiary Structure in MicroRNA Target Recognition.

Translational repression and degradation of transcripts by microRNAs (miRNAs) is mediated by a ribonucleoprotein complex called the miRNA-induced silencing complex (miRISC, or RISC). Advances in experimental determination of RISC structures have enabled detailed analysis and modeling of known miRNA targets, yet a full appreciation of the structural factors influencing target recognition remains a challenge, primarily because target recognition involves a combination of RNA-RNA and RNA-protein interactions that can vary greatly among different miRNA-target pairs. In this chapter, we review progress toward understanding the role of tertiary structure in miRNA target recognition using computational approaches to assemble RISC complexes at known targets and physics-based methods for computing target interactions. Using this framework to examine RISC structures and dynamics, we describe how the conformational flexibility of Argonautes plays an important role in accommodating the diversity of miRNA-target duplexes formed at canonical and noncanonical target sites. We then discuss applications of tertiary structure-based approaches to emerging topics, including the structural effects of SNPs in miRNA targets and cooperative interactions involving Argonaute-Argonaute complexes. We conclude by assessing the prospects for genome-scale modeling of RISC structures and modeling of higher-order Argonaute complexes associated with miRNA biogenesis, mRNA regulation, and other functions.

MiRNAtools: Advanced Training Using the miRNA Web of Knowledge.

Micro-RNAs (miRNAs) are small non-coding RNAs that act as negative regulators of the genomic output. Their intrinsic importance within cell biology and human disease is well known. Their mechanism of action based on the base pairing binding to their cognate targets have helped the development not only of many computer applications for the prediction of miRNA target recognition but also of specific applications for functional assessment and analysis. Learning about miRNA function requires practical training in the use of specific computer and web-based applications that are complementary to wet-lab studies. In order to guide the learning process about miRNAs, we have created miRNAtools (http://mirnatools.eu), a web repository of miRNA tools and tutorials. This article compiles tools with which miRNAs and their regulatory action can be analyzed and that function to collect and organize information dispersed on the web. The miRNAtools website contains a collection of tutorials that can be used by students and tutors engaged in advanced training courses. The tutorials engage in analyses of the functions of selected miRNAs, starting with their nomenclature and genomic localization and finishing with their involvement in specific cellular functions.

MicroRNA Target Recognition: Insights from Transcriptome-Wide Non-Canonical Interactions.

MicroRNAs (miRNAs) are small non-coding RNAs (∼22 nucleotides) regulating gene expression at the post-transcriptional level. By directing the RNA-induced silencing complex (RISC) to bind specific target mRNAs, miRNA can repress target genes and affect various biological phenotypes. Functional miRNA target recognition is known to majorly attribute specificity to consecutive pairing with seed region (position 2–8) of miRNA. Recent advances in a transcriptome-wide method of mapping miRNA binding sites (Ago HITS-CLIP) elucidated that a large portion of miRNA-target interactions in vivo are mediated not only through the canonical “seed sites” but also via non-canonical sites (∼15–80%), setting the stage to expand and determine their properties. Here we focus on recent findings from transcriptome-wide non-canonical miRNA-target interactions, specifically regarding “nucleation bulges” and “seed-like motifs”. We also discuss insights from Ago HITS-CLIP data alongside structural and biochemical studies, which highlight putative mechanisms of miRNA target recognition, and the biological significance of these non-canonical sites mediating marginal repression.

SomamiR 2.0: a database of cancer somatic mutations altering microRNA-ceRNA interactions.

SomamiR 2.0 (http://compbio.uthsc.edu/SomamiR) is a database of cancer somatic mutations in microRNAs (miRNA) and their target sites that potentially alter the interactions between miRNAs and competing endogenous RNAs (ceRNA) including mRNAs, circular RNAs (circRNA) and long noncoding RNAs (lncRNA). Here, we describe the recent major updates to the SomamiR database. We expanded the scope of the database by including somatic mutations that impact the interactions between miRNAs and two classes of non-coding RNAs, circRNAs and lncRNAs. Recently, a large number of miRNA target sites have been discovered by newly emerged high-throughput technologies for mapping the miRNA interactome. We have mapped 388 247 somatic mutations to the experimentally identified miRNA target sites. The updated database also includes a list of somatic mutations in the miRNA seed regions, which contain the most important guiding information for miRNA target recognition. A recently developed webserver, miR2GO, was integrated with the database to provide a seamless pipeline for assessing functional impacts of somatic mutations in miRNA seed regions. Data and functions from multiple sources including biological pathways and genome-wide association studies were updated and integrated with SomamiR 2.0 to make it a better platform for functional analysis of somatic mutations altering miRNA–ceRNA interactions.

Towards a molecular understanding of microRNA-mediated gene silencing.

MicroRNAs (miRNAs) are a conserved class of small non-coding RNAs that assemble with Argonaute proteins into miRNA-induced silencing complexes (miRISCs) to direct post-transcriptional silencing of complementary mRNA targets. Silencing is accomplished through a combination of translational repression and mRNA destabilization, with the latter contributing to most of the steady-state repression in animal cell cultures. Degradation of the mRNA target is initiated by deadenylation, which is followed by decapping and 5'-to-3' exonucleolytic decay. Recent work has enhanced our understanding of the mechanisms of silencing, making it possible to describe in molecular terms a continuum of direct interactions from miRNA target recognition to mRNA deadenylation, decapping and 5'-to-3' degradation. Furthermore, an intricate interplay between translational repression and mRNA degradation is emerging.

Two decades of miRNA biology: lessons and challenges.

The celebration of 20 years of RNA is opportune to reflect on what has been learned during this time regarding miRNA biology, and challenges that lay ahead. I focus this perspective on genetics, which arguably laid the foundation for the miRNA field. Indeed, genetic studies revealed critical miRNA:target interactions, the fundamental logic of miRNA target recognition, and phenotypically vital usages of miRNA regulation, all prior to formal recognition of the miRNA pathway. Ironically then, deciphering miRNA biology remains as challenging as ever, despite extensive mechanistic insights gained from biochemical and structural approaches, and a wealth of data garnered from genomewide approaches. Nevertheless, accumulating knowledge on miRNA function and ever-expanding genetic resources for manipulating miRNAs and their targets promise an exciting future in understanding in vivo necessities of these tiny RNAs. The miRNA era exploded in 2001 with the revelation that myriad hairpin-encoding loci generate ∼22 nucleotide (nt) RNAs. However, miRNA studies were already well on their way at that point, through developmental analyses in invertebrates. As is evident from their low-numbered gene names, mutants of the founding miRNAs lin-4 and let-7 were amongst the earliest C. elegans mutants recovered. Notably, the stage for comprehending their cloned sequences was set by genetic inquiries, initially by Chalfie and Ambros, which revealed antagonistic control of heterochronic identity by lin-4 and its major target lin-14. Ruvkun and colleagues studied gain-of-function lin-14 3′ UTR deletion mutants that phenocopied lin-4 loss-of-function, and these were critical to establish the cis-regulatory domain of lin-4 and its impact on lin-14 activity. However, there are older precedents for which loss of miRNA-mediated target regulation has phenotypic consequences. In 1923, Bridges isolated the dominant Drosophila wing serration mutant Beadex. Its eventual cloning showed that recurrent 3′ UTR disruptions underlie gain-of-function of dLMO. Interestingly, mir-9a knockouts exhibit similar wing serration, and miR-9a directly represses dLMO. Strikingly, removal of one dLMO allele fully restores mir-9a mutant wings, defining it as a critical miR-9a target. Thus, genetics revealed a miRNA-related phenotype nearly a century ago.

Gene expression regulation: lessons from noncoding RNAs.

Gene expression regulation: lessons from noncoding RNAs.

Key principles of miRNA involvement in human diseases.

Although rapid progress in our understanding of the functions of miRNA has been made by experimentation and computational approach, a considerable effort still has to be done in determining the general principles that govern the miRNA’s mode of action in human diseases. We will further discuss how these principles are being progressively approached by molecular studies, as well as the importance of miRNA in regulating different target genes and functions in specific biological contexts. There is a great demand to understand the principles of context-specific miRNA target recognition in order to design future experiments and models of normal developmental and disease states.

The miR-206/133b cluster is dispensable for development, survival and regeneration of skeletal muscle.

BackgroundThree different gene clusters code for the muscle-specific miRNAs miR-206, miR-1 and miR-133a/b. The two miR-1/133a clusters generate identical mature miR-1 and miR-133a miRNAs in heart and skeletal muscle, while the cognate miR-206/133b cluster is exclusively expressed in skeletal muscle. Since sequences of the miRNAs miR-133a and miR-133b are almost identical, it seems likely that they share potential targets. Similarly, miR-1 and miR-206 are structurally related and contain identical seed sequences important for miRNA-target recognition. In the past, different functions of these miRNAs were suggested for development, function and regeneration of skeletal muscle using different in vivo and in vitro models; however, mutants lacking the complete miR-206/133b cluster, which generates a single pri-miRNA constituting a functional unit, have not been analyzed.MethodsWe generated miR-206/133b knock-out mice and analyzed these mice morphologically; at the transcriptome and proteome level to elucidate the contribution of this miRNA cluster for skeletal muscle development, differentiation, regeneration in vivo; and by systematic analysis. In addition, we studied the consequences of a genetic loss of miR-206/133b for expression of Pax7 and satellite cell differentiation in vitro.ResultsDeletion of the miR-206/133b cluster did not reveal any obvious essential function of the miRNA-cluster for development and differentiation of skeletal muscle. Careful examination of skeletal muscles of miR-206/133b mutants revealed no structural alterations or molecular changes at the transcriptome and proteome level. In contrast to previous studies, deletion of the miR-206/133b cluster did not impair regeneration of skeletal muscle in mdx mice. Likewise, differentiation of miR-206/133b deficient satellite cells in vitro was unaffected and no change in Pax7 protein concentration was apparent.ConclusionsWe conclude that the miR-206/133b cluster is dispensable for development, function and regeneration of skeletal muscle, probably due to overlapping functions of the related miR-1/133a clusters, which are strongly expressed in skeletal muscle. We reason that the miR-206/133b cluster alone is not an essential regulator of skeletal muscle regeneration, although more subtle functions might exist that are not apparent under laboratory conditions.

The characterization of microRNA-mediated gene regulation as impacted by both target site location and seed match type.

MicroRNAs (miRNAs) are small RNA molecules that play important roles in gene regulation and translational repression. The mechanisms that facilitate miRNA target binding and recognition have been extensively studied in recent years. However, it is still not well known how the miRNA regulation is affected by the location and the flanking sequences of miRNA target sites. In this study, we systematically quantify the contribution of a wide spectrum of target sites on miRNA-mediated gene expression regulation. Our study investigates target sites located in four different gene regions, including 3' untranslated regions, coding sequences, 5′ untranslated regions and promoter regions. We have also introduced four additional non-canonical types of seed matches beyond the canonical seed matches, and included them in our study. Computational analysis of quantitative proteomic data has demonstrated that target sites located in different regions impact the miRNA-mediated repression differently but synergistically. In addition, we have shown the synergistic effects among non-canonical seed matches and canonical ones that enhance the miRNA regulatory effects. Further systematic analysis on the site accessibility near the target regions and the secondary structure of the mRNA sequences have demonstrated substantial variations among target sites of different locations and of different types of seed matches, suggesting the mRNA secondary structure could explain some of the difference in the miRNA regulatory effects impacted by these different target sites. Our study implies miRNAs might regulate their targets under different mechanisms when target sites vary in both their locations and the types of seed matches they contain.

The functional scope of plant microRNA-mediated silencing.

Deep sequencing has identified a complex set of plant miRNAs that potentially regulates many target genes of high complementarity. Furthermore, the discovery that many plant miRNAs work through a translational repression mechanism, along with the identification of noncanonical targets, has encouraged bioinformatic searches with less stringent parameters, identifying an even wider range of potential targets. Together, these findings suggest that any given plant miRNA family may regulate a highly diverse set of mRNAs. Here we present evolutionary, genetic, and mechanistic evidence that opposes this idea but instead suggests that families of sequence-related miRNAs regulate very few functionally related targets. We propose that complexities beyond complementarity impact plant miRNA target recognition, possibly explaining the current disparity between bioinformatic prediction and functional evidence.

Understanding functional miRNA-target interactions in vivo by site-specific genome engineering.

MicroRNA (miRNA) target recognition is largely dictated by short ‘seed’ sequences, and single miRNAs therefore have the potential to regulate a large number of genes. Understanding the contribution of specific miRNA–target interactions to the regulation of biological processes in vivo remains challenging. Here we use transcription activator-like effector nuclease (TALEN) and clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 technologies to interrogate the functional relevance of predicted miRNA response elements (MREs) to post-transcriptional silencing in zebrafish and Drosophila. We also demonstrate an effective strategy that uses CRISPR-mediated homology-directed repair with short oligonucleotide donors for the assessment of MRE activity in human cells. These methods facilitate analysis of the direct phenotypic consequences resulting from blocking specific miRNA–MRE interactions at any point during development.

A DDX6-CNOT1 Complex and W-Binding Pockets in CNOT9 Reveal Direct Links between miRNA Target Recognition and Silencing

CCR4-NOT is a major effector complex in miRNA-mediated gene silencing. It is recruited to miRNA targets through interactions with tryptophan (W)-containing motifs in TNRC6/GW182 proteins and is required for both translational repression and degradation of miRNA targets. Here, we elucidate the structural basis for the repressive activity of CCR4-NOT and its interaction with TNRC6/GW182s. We show that the conserved CNOT9 subunit attaches to a domain of unknown function (DUF3819) in the CNOT1 scaffold. The resulting complex provides binding sites for TNRC6/GW182, and its crystal structure reveals tandem W-binding pockets located in CNOT9. We further show that the CNOT1 MIF4G domain interacts with the C-terminal RecA domain of DDX6, a translational repressor and decapping activator. The crystal structure of this complex demonstrates striking similarity to the eIF4G-eIF4A complex. Together, our data provide the missing physical links in a molecular pathway that connects miRNA target recognition with translational repression, deadenylation, and decapping.

Composition of seed sequence is a major determinant of microRNA targeting patterns

MicroRNAs (miRNAs) are small non-coding RNAs that are extensively involved in gene expression regulation. One major roadblock in functional miRNA studies is the reliable prediction of genes targeted by miRNAs, as rules defining miRNA target recognition have not been well-established to date. Availability of high-throughput experimental data from a recent CLASH (cross linking, ligation and sequencing of hybrids) study has presented an unprecedented opportunity to characterize miRNA target recognition patterns, which may provide guidance for improved miRNA target prediction. The CLASH data were analysed to identify distinctive sequence features that characterize canonical and non-canonical miRNA target types. Most miRNA targets were of non-canonical type, i.e. without involving perfect pairing to canonical miRNA seed region. Different miRNAs have distinct targeting patterns, and this miRNA-to-miRNA variability was associated with seed sequence composition. Specifically, seed-based canonical target recognition was dependent on the GC content of the miRNA seed. For miRNAs with low GC content of the seed region, non-canonical targeting was the dominant mechanism for target recognition. In contrast to canonical targeting, non-canonical targeting did not lead to significant target downregulation at either the RNA or protein level. xwang@radonc.wustl.edu.