Target Repression Induced by Endogenous microRNAs: Large Differences,Small Effects

MicroRNAs are small RNAs that regulate protein levels. It is commonly assumed that the expression level of a microRNA is directly correlated with its repressive activity – that is, highly expressed microRNAs will repress their target mRNAs more. Here we investigate the quantitative relationship between endogenous microRNA expression and repression for 32 mature microRNAs in Drosophila melanogaster S2 cells. In general, we find that more abundant microRNAs repress their targets to a greater degree. However, the relationship between expression and repression is nonlinear, such that a 10-fold greater microRNA concentration produces only a 10% increase in target repression. The expression/repression relationship is the same for both dominant guide microRNAs and minor mature products (so-called passenger strands/microRNA* sequences). However, we find examples of microRNAs whose cellular concentrations differ by several orders of magnitude, yet induce similar repression of target mRNAs. Likewise, microRNAs with similar expression can have very different repressive abilities. We show that the association of microRNAs with Argonaute proteins does not explain this variation in repression. The observed relationship is consistent with the limiting step in target repression being the association of the microRNA/RISC complex with the target site. These findings argue that modest changes in cellular microRNA concentration will have minor effects on repression of targets.     

miRConnect: identifying effector genes of miRNAs and miRNA families in cancer cells

micro(mi)RNAs are small non-coding RNAs that negatively regulate expression of most mRNAs. They are powerful regulators of various differentiation stages, and the expression of genes that either negatively or positively correlate with expressed miRNAs is expected to hold information on the biological state of the cell and, hence, of the function of the expressed miRNAs. We have compared the large amount of available gene array data on the steady state system of the NCI60 cell lines to two different data sets containing information on the expression of 583 individual miRNAs. In addition, we have generated custom data sets containing expression information of 54 miRNA families sharing the same seed match. We have developed a novel strategy for correlating miRNAs with individual genes based on a summed Pearson Correlation Coefficient (sPCC) that mimics an in silico titration experiment. By focusing on the genes that correlate with the expression of miRNAs without necessarily being direct targets of miRNAs, we have clustered miRNAs into different functional groups. This has resulted in the identification of three novel miRNAs that are linked to the epithelial-to-mesenchymal transition (EMT) in addition to the known EMT regulators of the miR-200 miRNA family. In addition, an analysis of gene signatures associated with EMT, c-MYC activity, and ribosomal protein gene expression allowed us to assign different activities to each of the functional clusters of miRNAs. All correlation data are available via a web interface that allows investigators to identify genes whose expression correlates with the expression of single miRNAs or entire miRNA families. miRConnect.org will aid in identifying pathways regulated by miRNAs without requiring specific knowledge of miRNA targets.     

MicroRNAs and intestinal pathophysiology

MicroRNAs (miRNAs) represent an abundant class of endogenously expressed small RNAs, which is believed to control the expression of proteins through specific interaction with their mRNAs. MiRNAs are non-coding RNAs of 18 to 24 nucleotides that negatively regulate target mRNAs by binding to their 3'-untranslated regions (UTR). Most eukaryotic cells utilize miRNA to regulate vital functions such as cell differentiation, proliferation or apopotosis. The diversity of miRNAs and of their mRNA targets strongly indicate that they play a key role in the regulation of protein expression. To date, more than 500 different miRNAs have been identified in animals and plants. There are at least 326 miRNAs in the human genome, comprising 1-4% of all expressed human genes, which makes miRNAs one of the largest classes of gene regulators. A single miRNA can bind to and regulate many different mRNA targets and, conversely, several different miRNAs can bind to and cooperatively control a single mRNA target. The correlation between the expression of miRNAs and their effects on tumorigenesis and on the proliferation of cancer cells is beginning to gain experimental evidences. Recent studies showed that abnormal expression of miRNAs represents a common feature of cancer cells and that they can function as tumor suppressor genes or as oncogenes. Therefore, this diversity of action for miRNAs on several target genes could be one of the common mechanisms involved in the deregulation of protein expression observed during intestinal disorders. In this review, the emergent functions of miRNAs in colorectal cancer and their potential role in the intestinal inflammatory process are discussed.     

microRNA及其应用研究进展

microRNA(miRNA)是在多种真核细胞和病毒中发现的一类内源性非编码单链RNA,长约22个核苷酸,在进化上具有高度的保守性。miRNA可以通过碱基互补与靶基因mRNA的特定位点结合,抑制该蛋白合成或诱导该mRNA降解,在生物体生长、发育和疾病发生等过程中发挥着重要的作用。我们简要叙述了miRNA的特点和作用机制,并对miRNA在基因表达调控、胚胎干细胞调控及免疫调节等方面的最新进展进行了综述。     

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...     

Evolutionarily conserved function of a viral microRNA

MicroRNAs (miRNAs) are potent RNA regulators of gene expression. Some viruses encode miRNAs, most of unknown function. The majority of viral miRNAs are not conserved, and whether any have conserved functions remains unclear. Here, we report that two human polyomaviruses associated with serious disease in immunocompromised individuals, JC virus and BK virus, encode miRNAs with the same function as that of the monkey polyomavirus simian virus 40 miRNAs. These miRNAs are expressed late during infection to autoregulate early gene expression. We show that the miRNAs generated from both arms of the pre-miRNA hairpin are active at directing the cleavage of the early mRNAs. This finding suggests that despite multiple differences in the miRNA seed regions, the primary target (the early mRNAs) and function (the downregulation of early gene expression) are evolutionarily conserved among the primate polyomavirus-encoded miRNAs. Furthermore, we show that these miRNAs are expressed in individuals diagnosed with polyomavirus-associated disease, suggesting their potential as targets for therapeutic intervention.     

Global analysis of microRNA target gene expression reveals that miRNA targets are lower expressed in mature mouse and Drosophila tissues than in the embryos

MicroRNAs (miRNAs) are non-coding small RNAs of ~22 nt that regulate the gene expression by base pairing with target mRNAs, leading to mRNA cleavage or translational repression. It is currently estimated that miRNAs account for ~1% of predicted genes in higher eukaryotic genomes and that up to 30% of genes might be regulated by miRNAs. However, only very few miRNAs have been functionally characterized and the general functions of miRNAs are not globally studied. In this study, we systematically analyzed the expression patterns of miRNA targets using several public microarray profiles. We found that the expression levels of miRNA targets are lower in all mouse and Drosophila tissues than in the embryos. We also found miRNAs more preferentially target ubiquitously expressed genes than tissue-specifically expressed genes. These results support the current suggestion that miRNAs are likely to be largely involved in embryo development and maintaining of tissue identity.     

Beyond HPV: Oncomirs as new players in cervical cancer

MicroRNAs (miRNAs) are a recently discovered family of 18-24 nucleotide non-coding RNAs that can negatively regulate target mRNAs. All studied multicellular eukaryotes utilize miRNAs to regulate basic cellular functions including proliferation, differentiation, and death. It is now apparent that abnormal miRNA expression is a common feature of human malignancies. This review discusses the various cancer-relevant miRNAs (oncomirs) especially in cervical tumorigenesis and the potential role of oncomirs as therapeutic agents and targets for the treatment of cervical cancer.     

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."     

Computational prediction of intronic microRNA targets using host gene expression reveals novel regulatory mechanisms

Approximately half of known human miRNAs are located in the introns of protein coding genes. Some of these intronic miRNAs are only expressed when their host gene is and, as such, their steady state expression levels are highly correlated with those of the host gene's mRNA. Recently host gene expression levels have been used to predict the targets of intronic miRNAs by identifying other mRNAs that they have consistent negative correlation with. This is a potentially powerful approach because it allows a large number of expression profiling studies to be used but needs refinement because mRNAs can be targeted by multiple miRNAs and not all intronic miRNAs are co-expressed with their host genes.Here we introduce InMiR, a new computational method that uses a linear-Gaussian model to predict the targets of intronic miRNAs based on the expression profiles of their host genes across a large number of datasets. Our method recovers nearly twice as many true positives at the same fixed false positive rate as a comparable method that only considers correlations. Through an analysis of 140 Affymetrix datasets from Gene Expression Omnibus, we build a network of 19,926 interactions among 57 intronic miRNAs and 3,864 targets. InMiR can also predict which host genes have expression profiles that are good surrogates for those of their intronic miRNAs. Host genes that InMiR predicts are bad surrogates contain significantly more miRNA target sites in their 3' UTRs and are significantly more likely to have predicted Pol II and Pol III promoters in their introns.We provide a dataset of 1,935 predicted mRNA targets for 22 intronic miRNAs. These prediction are supported both by sequence features and expression. By combining our results with previous reports, we distinguish three classes of intronic miRNAs: Those that are tightly regulated with their host gene; those that are likely to be expressed from the same promoter but whose host gene is highly regulated by miRNAs; and those likely to have independent promoters.     

Joint Genome-Wide Profiling of miRNA and mRNA Expression in Alzheimer's Disease Cortex Reveals Altered miRNA Regulation

Although microRNAs are being extensively studied for their involvement in cancer and development, little is known about their roles in Alzheimer''s disease (AD). In this study, we used microarrays for the first joint profiling and analysis of miRNAs and mRNAs expression in brain cortex from AD and age-matched control subjects. These data provided the unique opportunity to study the relationship between miRNA and mRNA expression in normal and AD brains. Using a non-parametric analysis, we showed that the levels of many miRNAs can be either positively or negatively correlated with those of their target mRNAs. Comparative analysis with independent cancer datasets showed that such miRNA-mRNA expression correlations are not static, but rather context-dependent. Subsequently, we identified a large set of miRNA-mRNA associations that are changed in AD versus control, highlighting AD-specific changes in the miRNA regulatory system. Our results demonstrate a robust relationship between the levels of miRNAs and those of their targets in the brain. This has implications in the study of the molecular pathology of AD, as well as miRNA biology in general.