Experimental validation of miRNA targets

MicroRNAs are natural, single-stranded, small RNA molecules that regulate gene expression by binding to target mRNAs and suppress its translation or initiate its degradation. In contrast to the identification and validation of many miRNA genes is the lack of experimental evidence identifying their corresponding mRNA targets. The most fundamental challenge in miRNA biology is to define the rules of miRNA target recognition. This is critical since the biological role of individual miRNAs will be dictated by the mRNAs that they regulate. Therefore, only as target mRNAs are validated will it be possible to establish commonalities that will enable more precise predictions of miRNA/mRNA interactions. Currently there is no clear agreement as to what experimental procedures should be followed to demonstrate that a given mRNA is a target of a specific miRNA. Therefore, this review outlines several methods by which to validate miRNA targets. Additionally, we propose that multiple criteria should be met before miRNA target validation should be considered "confirmed."     

Tandem affinity purification of miRNA target mRNAs (TAP-Tar)

MicroRNAs (miRNAs) bind to Argonaute proteins, and together they form the RISC complex and regulate target mRNA translation and/or stability. Identification of mRNA targets is key to deciphering the physiological functions and mode of action of miRNAs. In mammals, miRNAs are generally poorly homologous to their target sequence, and target identification cannot be based solely on bioinformatics. Here, we describe a biochemical approach, based on tandem affinity purification, in which mRNA/miRNA complexes are sequentially pulled down, first via the Argonaute moiety and then via the miRNA. Our ‘TAP-Tar’ procedure allows the specific pull down of mRNA targets of miRNA. It is useful for validation of targets predicted in silico, and, potentially, for discovery of previously uncharacterized targets.     

Assessing the utility of thermodynamic features for microRNA target prediction under relaxed seed and no conservation requirements

Background

Many computational microRNA target prediction tools are focused on several key features, including complementarity to 5′seed of miRNAs and evolutionary conservation. While these features allow for successful target identification, not all miRNA target sites are conserved and adhere to canonical seed complementarity. Several studies have propagated the use of energy features of mRNA:miRNA duplexes as an alternative feature. However, different independent evaluations reported conflicting results on the reliability of energy-based predictions. Here, we reassess the usefulness of energy features for mammalian target prediction, aiming to relax or eliminate the need for perfect seed matches and conservation requirement.

Methodology/Principal Findings

We detect significant differences of energy features at experimentally supported human miRNA target sites and at genome-wide sites of AGO protein interaction. This trend is confirmed on datasets that assay the effect of miRNAs on mRNA and protein expression changes, and a simple linear regression model leads to significant correlation of predicted versus observed expression change. Compared to 6-mer seed matches as baseline, application of our energy-based model leads to ∼3–5-fold enrichment on highly down-regulated targets, and allows for prediction of strictly imperfect targets with enrichment above baseline.

Conclusions/Significance

In conclusion, our results indicate significant promise for energy-based miRNA target prediction that includes a broader range of targets without having to use conservation or impose stringent seed match rules.     

Differential sRNA Regulation in Leaves and Roots of Sugarcane under Water Depletion

Plants have developed multiple regulatory mechanisms to respond and adapt to stress. Drought stress is one of the major constraints to agricultural productivity worldwide and recent reports have highlighted the importance of plant sRNA in the response and adaptation to water availability. In order to increase our understanding of the roles of sRNA in response to water depletion, cultivars of sugarcane were submitted to treatment of ceasing drip irrigation for 24 hours. Deep sequencing analysis was carried out to identify the sRNA regulated in leaves and roots of sugarcane cultivars with different drought sensitivities. The pool of sRNA selected allowed the analysis of different sRNA classes (miRNA and siRNA). Twenty-eight and 36 families of conserved miRNA were identified in leaf and root libraries, respectively. Dynamic regulation of miRNA was observed and the expression profiles of eight miRNA were verified in leaf samples from three biological replicates by stem-loop qRT-PCR assay using the cultivars: SP90–1638 - sensitive cultivar- and; SP83–2847 and SP83–5073 - tolerant cultivars. Altered miRNA regulation was correlated with changes in mRNA levels of specific targets. Two leaf libraries from individual sugarcane cultivars with contrasting drought-tolerance properties were also analyzed. An enrichment of 22-nt sRNA species was observed in leaf libraries. 22-nt miRNA triggered siRNA production by cleavage of their targets in response to water depletion. A number of genes of the sRNA biogenesis pathway were down-regulated in tolerant genotypes and up-regulated in sensitive in response to water depletion treatment. Our analysis contributes to increase the knowledge on the roles of sRNA in sugarcane submitted to water depletion.     

Specific sequence determinants of miR-15/107 microRNA gene group targets

MicroRNAs (miRNAs) target mRNAs in human cells via complex mechanisms that are still incompletely understood. Using anti-Argonaute (anti-AGO) antibody co-immunoprecipitation, followed by microarray analyses and downstream bioinformatics, 'RIP-Chip' experiments enable direct analyses of miRNA targets. RIP-Chip studies (and parallel assessments of total input mRNA) were performed in cultured H4 cells after transfection with miRNAs corresponding to the miR-15/107 gene group (miR-103, miR-107, miR-16 and miR-195), and five control miRNAs. Three biological replicates were run for each condition with a total of 54 separate human Affymetrix Human Gene 1.0 ST array replicates. Computational analyses queried for determinants of miRNA:mRNA binding. The analyses support four major findings: (i) RIP-Chip studies correlated with total input mRNA profiling provides more comprehensive information than using either RIP-Chip or total mRNA profiling alone after miRNA transfections; (ii) new data confirm that miR-107 paralogs target coding sequence (CDS) of mRNA; (iii) biochemical and computational studies indicate that the 3' portion of miRNAs plays a role in guiding miR-103/7 to the CDS of targets; and (iv) there are major sequence-specific targeting differences between miRNAs in terms of CDS versus 3'-untranslated region targeting, and stable AGO association versus mRNA knockdown. Future studies should take this important miRNA-to-miRNA variability into account.     

Tissue and Process Specific microRNA–mRNA Co-Expression in Mammalian Development and Malignancy

An association between enrichment and depletion of microRNA (miRNA) binding sites, 3′ UTR length, and mRNA expression has been demonstrated in various developing tissues and tissues from different mature organs; but functional, context-dependent miRNA regulations have yet to be elucidated. Towards that goal, we examined miRNA–mRNA interactions by measuring miRNA and mRNA in the same tissue during development and also in malignant conditions. We identified significant miRNA-mediated biological process categories in developing mouse cerebellum and lung using non-targeted mRNA expression as the negative control. Although miRNAs in general suppress target mRNA messages, many predicted miRNA targets demonstrate a significantly higher level of co-expression than non-target genes in developing cerebellum. This phenomenon is tissue specific since it is not observed in developing lungs. Comparison of mouse cerebellar development and medulloblastoma demonstrates a shared miRNA–mRNA co-expression program for brain-specific neurologic processes such as synaptic transmission and exocytosis, in which miRNA target expression increases with the accumulation of multiple miRNAs in developing cerebellum and decreases with the loss of these miRNAs in brain tumors. These findings demonstrate the context-dependence of miRNA–mRNA co-expression.     

Algorithms for mapping of mRNA targets for microRNA

MicroRNAs (miRNAs) are involved in human health and disease as endogenous suppressors of the translation of coding genes. At this early point of time in miRNA biology, it is important to identify specific cognate mRNA targets for miRNA. Investigation of the significance of miRNAs in disease processes relies on algorithms that hypothetically link specific miRNAs to their putative target genes. The development of such algorithms represents a hot area of research in biomedical informatics. Lack of biological data linking specific miRNAs to their respective mRNA targets represents the most serious limitation at this time. This article presents a concise review addressing the most popular concepts underlying state-of-the-art algorithms and principles aimed at target mapping for specific miRNAs. Strategies for improvement of the current bioinformatics tools and effective approaches for biological validation are discussed.     

miRTar Hunter: A prediction system for identifying human microRNA target sites

MicroRNAs (miRNAs) are important regulators of gene expression and play crucial roles in many biological processes including apoptosis, differentiation, development, and tumorigenesis. Recent estimates suggest that more than 50% of human protein coding genes may be regulated by miRNAs and that each miRNA may bind to 300–400 target genes. Approximately 1,000 human miRNAs have been identified so far with each having up to hundreds of unique target mRNAs. However, the targets for a majority of these miRNAs have not been identified due to the lack of large-scale experimental detection techniques. Experimental detection of miRNA target sites is a costly and time-consuming process, even though identification of miRNA targets is critical to unraveling their functions in various biological processes. To identify miRNA targets, we developed miRTar Hunter, a novel computational approach for predicting target sites regardless of the presence or absence of a seed match or evolutionary sequence conservation. Our approach is based on a dynamic programming algorithm that incorporates more sequence-specific features and reflects the properties of various types of target sites that determine diverse aspects of complementarities between miRNAs and their targets. We evaluated the performance of our algorithm on 532 known human miRNA:target pairs and 59 experimentally-verified negative miRNA:target pairs, and also compared our method with three popular programs for 481 miRNA:target pairs. miRTar Hunter outperformed three popular existing algorithms in terms of recall and precision, indicating that our unique scheme to quantify the determinants of complementary sites is effective at detecting miRNA targets. miRTar Hunter is now available at http://203.230.194.162/~kbkim.     

A convenient system for highly specific and sensitive detection of miRNA expression

Since the first miRNA was discovered in 1993, miRNAs have become a hotspot for biological research. In order to feed this demand, a robust method is required to detect miRNA gene expression. Development of a detection method is more difficult for miRNAs than for long RNAs, such as mRNA, owing to their small size. Existing methods have limitations; thus, new methods are required. We describe a new system for detecting miRNA expression, which can distinguish miRNA from its precursor and has single-nucleotide resolution. It has single molecule and multiplex detection potential. It may be performed as a polymerase chain reaction (PCR) method, a blotting method, or a macroarray method according to the analyst''s preference. This personalized system provides a convenient tool for the detection of miRNA gene expression.     

SeqTar: an effective method for identifying microRNA guided cleavage sites from degradome of polyadenylated transcripts in plants

In plants, microRNAs (miRNAs) regulate their mRNA targets by precisely guiding cleavages between the 10th and 11th nucleotides in the complementary regions. High-throughput sequencing-based methods, such as PARE or degradome profiling coupled with a computational analysis of the sequencing data, have recently been developed for identifying miRNA targets on a genome-wide scale. The existing algorithms limit the number of mismatches between a miRNA and its targets and strictly do not allow a mismatch or G:U Wobble pair at the position 10 or 11. However, evidences from recent studies suggest that cleavable targets with more mismatches exist indicating that a relaxed criterion can find additional miRNA targets. In order to identify targets including the ones with weak complementarities from degradome data, we developed a computational method called SeqTar that allows more mismatches and critically mismatch or G:U pair at the position 10 or 11. Precisely, two statistics were introduced in SeqTar, one to measure the alignment between miRNA and its target and the other to quantify the abundance of reads at the center of the miRNA complementary site. By applying SeqTar to publicly available degradome data sets from Arabidopsis and rice, we identified a substantial number of novel targets for conserved and non-conserved miRNAs in addition to the reported ones. Furthermore, using RLM 5'-RACE assay, we experimentally verified 12 of the novel miRNA targets (6 each in Arabidopsis and rice), of which some have more than 4 mismatches and have mismatches or G:U pairs at the position 10 or 11 in the miRNA complementary sites. Thus, SeqTar is an effective method for identifying miRNA targets in plants using degradome data sets.     

Integrated analysis of miRNA and mRNA expression profiles in response to gut microbiota depletion in the abdomens of female Bactrocera dorsalis

Insect gut microbiota has been reported to participate in regulating host multiple biological processes including metabolism and reproduction. However, the corresponding molecular mechanisms remain largely unknown. Recent studies suggest that microRNAs (miRNAs) are involved in complex interactions between the gut microbiota and the host. Here, we used next-generation sequencing technology to characterize miRNA and mRNA expression profiles and construct the miRNA–gene regulatory network in response to gut microbiota depletion in the abdomens of female Bactrocera dorsalis. A total of 3016 differentially expressed genes (DEGs) and 18 differentially expressed miRNAs (DEMs) were identified. Based on the integrated analysis of miRNA and mRNA sequencing data, 229 negatively correlated miRNA–gene pairs were identified from the miRNA–mRNA network. Gene ontology enrichment analysis indicated that DEMs could target several genes involved in the metabolic process, oxidation–reduction process, oogenesis, and insulin signaling pathway. Finally, real-time quantitative polymerase chain reaction further verified the accuracy of RNA sequencing results. In conclusion, our study provides the profiles of miRNA and mRNA expressions under antibiotics treatment and provides an insight into the roles of miRNAs and their target genes in the interaction between the gut microbiota and its host.     

Anti-Argonaute RIP-Chip shows that miRNA transfections alter global patterns of mRNA recruitment to microribonucleoprotein complexes

MicroRNAs (miRNAs) play key roles in gene expression regulation by guiding Argonaute (AGO)-containing microribonucleoprotein (miRNP) effector complexes to target polynucleotides. There are still uncertainties about how miRNAs interact with mRNAs. Here we employed a biochemical approach to isolate AGO-containing miRNPs from human H4 tumor cells by co-immunoprecipitation (co-IP) with a previously described anti-AGO antibody. Co-immunoprecipitated (co-IPed) RNAs were subjected to downstream Affymetrix Human Gene 1.0 ST microarray analysis. During rigorous validation, the “RIP-Chip” assay identified target mRNAs specifically associated with AGO complexes. RIP-Chip was performed after transfecting brain-enriched miRNAs (miR-107, miR-124, miR-128, and miR-320) and nonphysiologic control miRNA to identify miRNA targets. As expected, the miRNA transfections altered the mRNA content of the miRNPs. Specific mRNA species recruited to miRNPs after miRNA transfections were moderately in agreement with computational target predictions. In addition to recruiting mRNA targets into miRNPs, miR-107 and to a lesser extent miR-128, but not miR-124 or miR-320, caused apparent exclusion of some mRNAs that are normally associated with miRNPs. MiR-107 and miR-128 transfections also result in decreased AGO mRNA and protein levels. However, AGO mRNAs were not recruited to miRNPs after either miR-107 or miR-128 transfection, confirming that miRNAs may alter gene expression without stable association between particular mRNAs and miRNPs. In summary, RIP-Chip assays constitute an optimized, validated, direct, and high-throughput biochemical assay that provides data about specific miRNA:mRNA interactions, as well as global patterns of regulation by miRNAs.