Large-Scale Screens of miRNA-mRNA Interactions Unveiled That the 3′UTR of a Gene Is Targeted by Multiple miRNAs

Animal microRNA (miRNA) target prediction is still a challenge, although many prediction programs have been exploited. MiRNAs exert their function through partially binding the messenger RNAs (mRNAs; likely at 3′ untranslated regions [3′UTRs]), which makes it possible to detect the miRNA-mRNA interactions in vitro by co-transfection of miRNA and a luciferase reporter gene containing the target mRNA fragment into mammalian cells under a dual-luciferase assay system. Here, we constructed a human miRNA expression library and used a dual-luciferase assay system to perform large-scale screens of interactions between miRNAs and the 3′UTRs of seven genes, which included more than 3,000 interactions with triplicate experiments for each interaction. The screening results showed that the 3′UTR of one gene can be targeted by multiple miRNAs. Among the prediction algorithms, a Bayesian phylogenetic miRNA target identification algorithm and a support vector machine (SVM) presented a relatively better performance (27% for EIMMo and 24.7% for miRDB) against the average precision (17.3%) of the nine prediction programs used here. Additionally, we noticed that a relatively high conservation level was shown at the miRNA 3′ end targeted regions, as well as the 5′ end (seed region) binding sites.     

Inference of miRNA targets using evolutionary conservation and pathway analysis

Background

MicroRNAs have emerged as important regulatory genes in a variety of cellular processes and, in recent years, hundreds of such genes have been discovered in animals. In contrast, functional annotations are available only for a very small fraction of these miRNAs, and even in these cases only partially.

Results

We developed a general Bayesian method for the inference of miRNA target sites, in which, for each miRNA, we explicitly model the evolution of orthologous target sites in a set of related species. Using this method we predict target sites for all known miRNAs in flies, worms, fish, and mammals. By comparing our predictions in fly with a reference set of experimentally tested miRNA-mRNA interactions we show that our general method performs at least as well as the most accurate methods available to date, including ones specifically tailored for target prediction in fly. An important novel feature of our model is that it explicitly infers the phylogenetic distribution of functional target sites, independently for each miRNA. This allows us to infer species-specific and clade-specific miRNA targeting. We also show that, in long human 3' UTRs, miRNA target sites occur preferentially near the start and near the end of the 3' UTR. To characterize miRNA function beyond the predicted lists of targets we further present a method to infer significant associations between the sets of targets predicted for individual miRNAs and specific biochemical pathways, in particular those of the KEGG pathway database. We show that this approach retrieves several known functional miRNA-mRNA associations, and predicts novel functions for known miRNAs in cell growth and in development.

Conclusion

We have presented a Bayesian target prediction algorithm without any tunable parameters, that can be applied to sequences from any clade of species. The algorithm automatically infers the phylogenetic distribution of functional sites for each miRNA, and assigns a posterior probability to each putative target site. The results presented here indicate that our general method achieves very good performance in predicting miRNA target sites, providing at the same time insights into the evolution of target sites for individual miRNAs. Moreover, by combining our predictions with pathway analysis, we propose functions of specific miRNAs in nervous system development, inter-cellular communication and cell growth. The complete target site predictions as well as the miRNA/pathway associations are accessible on the ElMMo web server.     

MiRComb: An R Package to Analyse miRNA-mRNA Interactions. Examples across Five Digestive Cancers

MicroRNAs (miRNAs) are small RNAs that regulate the expression of target mRNAs by specific binding on the mRNA 3''UTR and promoting mRNA degradation in the majority of cases. It is often of interest to know the specific targets of a miRNA in order to study them in a particular disease context. In that sense, some databases have been designed to predict potential miRNA-mRNA interactions based on hybridization sequences. However, one of the main limitations is that these databases have too many false positives and do not take into account disease-specific interactions. We have developed an R package (miRComb) able to combine miRNA and mRNA expression data with hybridization information, in order to find potential miRNA-mRNA targets that are more reliable to occur in a specific physiological or disease context. This article summarizes the pipeline and the main outputs of this package by using as example TCGA data from five gastrointestinal cancers (colon cancer, rectal cancer, liver cancer, stomach cancer and esophageal cancer). The obtained results can be used to develop a huge number of testable hypotheses by other authors. Globally, we show that the miRComb package is a useful tool to deal with miRNA and mRNA expression data, that helps to filter the high amount of miRNA-mRNA interactions obtained from the pre-existing miRNA target prediction databases and it presents the results in a standardised way (pdf report). Moreover, an integrative analysis of the miRComb miRNA-mRNA interactions from the five digestive cancers is presented. Therefore, miRComb is a very useful tool to start understanding miRNA gene regulation in a specific context. The package can be downloaded in http://mircomb.sourceforge.net.     

miRNA与其靶mRNA的相互作用：绑定位点的质量与数量特征的整合计算分析

miRNAs通过完全或不完全的碱基互补绑定到信使RNA(mRNA)上,通过抑制翻译或者直接导致mRNA降解的方式来调节靶基因的表达．为了研究miRNAs在转录水平上面的调控作用,两种人类基因组中组织特异的miRNAs(miR-1和miR-124)被转染到HeLa细胞中,微阵列(microarray)分析转染前后细胞中各基因mRNA表达水平变化情况的结果表明：动物基因组中靶基因与miRNAs不完全的碱基互补也会导致mRNA的直接降解．通过分析实验得到的mRNA表达水平变化数据,发现这相同miRNA的不同靶基因mRNA表达水平的下调倍数有着明显的差别,推测这些靶基因mRNA序列本身存在某些影响其受调节程度的因素．为此,提取和分析这些靶基因mRNA的序列特征,通过对这些序列特征与mRNA表达水平下调数据进行统计相关分析,最终发现,miRNA靶基因受调节的程度与以下几个因素相关联：mRNA序列中miRNA靶位点的个数,靶位点与miRNA序列碱基互补的程度,以及绑定后形成二级结构的稳定程度(即最低自由能的大小)．在此基础上,初步建立起一个多因子作用下的miRNA 靶基因mRNA表达水平下调程度模型,分析表明：该模型在一定程度上可以反映了部分序列特征对于miRNA靶基因mRNA表达水平下调程度的影响．     

Quantitative prediction of miRNA-mRNA interaction based on equilibrium concentrations

MicroRNAs (miRNAs) suppress gene expression by forming a duplex with a target messenger RNA (mRNA), blocking translation or initiating cleavage. Computational approaches have proven valuable for predicting which mRNAs can be targeted by a given miRNA, but currently available prediction methods do not address the extent of duplex formation under physiological conditions. Some miRNAs can at low concentrations bind to target mRNAs, whereas others are unlikely to bind within a physiologically relevant concentration range. Here we present a novel approach in which we find potential target sites on mRNA that minimize the calculated free energy of duplex formation, compute the free energy change involved in unfolding these sites, and use these energies to estimate the extent of duplex formation at specified initial concentrations of both species. We compare our predictions to experimentally confirmed miRNA-mRNA interactions (and non-interactions) in Drosophila melanogaster and in human. Although our method does not predict whether the targeted mRNA is degraded and/or its translation to protein inhibited, our quantitative estimates generally track experimentally supported results, indicating that this approach can be used to predict whether an interaction occurs at specified concentrations. Our approach offers a more-quantitative understanding of post-translational regulation in different cell types, tissues, and developmental conditions.     

星形细胞瘤生存预后相关miRNA-mRNA调控关系对筛选

利用GEO数据库中的芯片数据,筛选与星形细胞瘤生存预后相关的miRNA-mRNA调控关系对,为后续研究提供理论支持.下载芯片数据利用R语言进行差异表达分析,得到星形细胞瘤较正常组织表达显著改变的miRNA与mRNA;通过miRNA靶基因预测,将靶基因与差异表达mRNA取交集,明确mRNA与miRNA之间的关系;利用GE...     

Interactions of intergenic microRNAs with mRNAs of genes involved in carcinogenesis

miRNAs regulate gene expression by binding with mRNAs of many genes. Studying their effects on genes involved in oncogenesis is important in cancer diagnostics and therapeutics. The RNAHybrid 2.1 program was used to predict the strong miRNA binding sites (p < 0.0005) in target mRNAs. The program Finder 2.2 was created to verify 784 intergenic miRNAs (ig-miRNA) origin. Among 54 considered oncogenes and tumor suppressor genes, 47 genes are the best targets for ig-miRNAs. Accordingly, these genes are strongly regulated by 111 ig-miRNAs. Some miRNAs bind several mRNAs, and some mRNAs have several binding sites for miRNAs. Of the 54 mRNAs, 21.8%, 43.0%, and 35.2% of the miRNA binding sites are present in the 5'UTRs, CDSes, and 3'UTRs, respectively. The average density of the binding sites for miRNAs in the 5'UTR was 4.4 times and 4.1 times greater than in the CDS and the 3'UTR, respectively. Three types of interactions between miRNAs and mRNAs were identified, which differ according to the region of the miRNA bound to the mRNA: 1) binding occurs predominantly via the 3'-region of the miRNA; 2) binding occurs predominantly through the central region of the miRNA; and 3) binding occurs predominantly via the 5'-region of the miRNA. Several miRNAs effectively regulate only one gene, and this information could be useful in molecular medicine to modulate translation of the target mRNA. We recommend described new sites for validation by experimental investigation.     

Molecular architecture of a miRNA-regulated 3' UTR

Animal genomes contain hundreds of microRNAs (miRNAs), small regulatory RNAs that control gene expression by binding to complementary sites in target mRNAs. Some rules that govern miRNA/target interaction have been elucidated but their general applicability awaits further experimentation on a case-by-case basis. We use here an assay system in transgenic nematodes to analyze the interaction of the Caenorhabditis elegans lsy-6 miRNA with 3' UTR sequences. In contrast to many previously described assay systems used to analyze miRNA/target interactions, our assay system operates within the cellular context in which lsy-6 normally functions, a single neuron in the nervous system of C. elegans. Through extensive mutational analysis, we define features in the known and experimentally validated target of lsy-6, the 3' UTR of the cog-1 homeobox gene, that are required for a functional miRNA/target interaction. We describe that both in the context of the cog-1 3' UTR and in the context of heterologous 3' UTRs, one or more seed matches are not a reliable predictor for a functional miRNA/target interaction. We rather find that two nonsequence specific contextual features beyond miRNA target sites are critical determinants of miRNA-mediated 3' UTR regulation. The contextual features reside 3' of lsy-6 binding sites in the 3' UTR and act in a combinatorial manner; mutation of each results in limited defects in 3' UTR regulation, but a combinatorial deletion results in complete loss of 3' UTR regulation. Together with two lsy-6 sites, these two contextual features are capable of imparting regulation on a heterologous 3' UTR. Moreover, the contextual features need to be present in a specific configuration relative to miRNA binding sites and could either represent protein binding sites or provide an appropriate structural context. We conclude that a given target site resides in a 3' UTR context that evolved beyond target site complementarity to support regulation by a specific miRNA. The large number of 3' UTRs that we analyzed in this study will also be useful to computational biologists in designing the next generation of miRNA/target prediction algorithms.     

Cooperative interplay of let-7 mimic and HuR with MYC RNA

Both RNA-binding proteins (RBP) and miRNA play important roles in the regulation of mRNA expression, often acting together to regulate a target mRNA. In some cases the RBP and miRNA have been reported to act competitively, but in other instances they function cooperatively. Here, we investigated HuR function as an enhancer of let-7-mediated translational repression of c-Myc despite the separation of their binding sites. Using an in vitro system, we determined that a let-7 mimic, consisting of single-stranded (ss)DNA complementary to the let-7 binding site, enhanced the affinity of HuR for a 122-nt MYC RNA encompassing both binding sites. This finding supports the biophysical principle of cooperative binding by an RBP and miRNA purely through interactions at distal mRNA binding sites.     

A wide repertoire of miRNA binding sites: prediction and functional implications

MOTIVATION: Over the past decade, deciphering the roles of microRNAs (miRNAs) has relied heavily upon the identification of their targets. Most of the targets that were computationally and experimentally characterized were evolutionarily conserved 'seed' targets, containing a perfect 6-8 nt match between the miRNA 5(')-region and the messenger RNA (mRNA). Gradually, it has become evident that other types of miRNA binding can confer target regulation, but their characterization has been lagging behind. RESULTS: Here, we complement the putative evolutionarily-conserved seed-containing targets by a wide repertoire of putative targets exhibiting a variety of miRNA binding patterns, predicted by our algorithm RepTar. These include non-conserved sites, 'seed' binding sites with G:U-wobbles within the seed, '3(') compensatory' sites and 'centered' sites. Apart from the centered sites, we demonstrate the functionality of these sites and characterize the target profile of a miRNA by the types of binding sites predicted in its target 3(') UTRs. We find that different miRNAs have individual target profiles, with some more inclined to seed binding and others more inclined to binding through 3(') compensatory sites. This diversity in targeting patterns is also evident within several miRNA families (defined by common seed sequences), leading to divergence in the target sets of members of the same family. The prediction of non-conventional miRNA targets is also beneficial in the search for targets of the non-conserved viral miRNAs. Analyzing the cellular targets of viral miRNAs, we show that viral miRNAs use various binding patterns to exploit cellular miRNA binding sites and suggest roles for these targets in virus-host interactions.