Ago2 Immunoprecipitation Identifies Predicted MicroRNAs in Human Embryonic Stem Cells and Neural Precursors

Background

MicroRNAs are required for maintenance of pluripotency as well as differentiation, but since more microRNAs have been computationally predicted in genome than have been found, there are likely to be undiscovered microRNAs expressed early in stem cell differentiation.

Methodology/Principal Findings

SOLiD ultra-deep sequencing identified >10⁷ unique small RNAs from human embryonic stem cells (hESC) and neural-restricted precursors that were fit to a model of microRNA biogenesis to computationally predict 818 new microRNA genes. These predicted genomic loci are associated with chromatin patterns of modified histones that are predictive of regulated gene expression. 146 of the predicted microRNAs were enriched in Ago2-containing complexes along with 609 known microRNAs, demonstrating association with a functional RISC complex. This Ago2 IP-selected subset was consistently expressed in four independent hESC lines and exhibited complex patterns of regulation over development similar to previously-known microRNAs, including pluripotency-specific expression in both hESC and iPS cells. More than 30% of the Ago2 IP-enriched predicted microRNAs are new members of existing families since they share seed sequences with known microRNAs.

Conclusions/Significance

Extending the classic definition of microRNAs, this large number of new microRNA genes, the majority of which are less conserved than their canonical counterparts, likely represent evolutionarily recent regulators of early differentiation. The enrichment in Ago2 containing complexes, the presence of chromatin marks indicative of regulated gene expression, and differential expression over development all support the identification of 146 new microRNAs active during early hESC differentiation.     

美洲大蠊microRNA的初步研究

美洲大蠊Periplaneta americana是一种世界性的卫生害虫,但其提取物有较高的药用价值。本研究对饲养的雌雄美洲大蠊成虫进行microRNA测序,分别在雄性和雌性中得到12 155 616条和9 847 263条序列。序列长度主要为18～23 nt,且在22 nt和29 nt处有2个峰值。将所得序列与数据库(NCBI、Rfam)进行比对注释,最终在雄性成虫中鉴定到57种已知的microRNA和152种潜在的新microRNA,在雌性成虫中鉴定到53种已知的microRNA和94种潜在的新microRNA。差异表达分析发现只有一种microRNA:miR-750在雌雄之间差异表达,其在雌虫中表达量显著高于雄虫。本研究首次在基因组水平研究了美洲大蠊microRNA的组成并对其功能进行了预测,为其后续研究奠定了基础。     

MicroRNAs and cancer

The review is devoted to analyzing the data on the role of microRNAs in human tumor progression. The following topics are thoroughly discussed in the review: (1) general characteristics of microRNAs; (2) their expression pattern in human tumors and specificity of this expression; (3) the possible role of microRNAs as oncogenes and tumor growth suppressors; and (4) their participation in the processes responsible for the transformed phenotype of tumor cells; and (5) the role of microRNAs in early diagnostics of the disease and its prognosis.     

Unintentional miRNA ablation is a risk factor in gene knockout studies: a short report

One of the most powerful techniques for studying the function of a gene is to disrupt the expression of that gene using genetic engineering strategies such as targeted recombination or viral integration of gene trap cassettes. The tremendous utility of these tools was recognized this year with the awarding of the Nobel Prize in Physiology or Medicine to Capecchi, Evans, and Smithies for their pioneering work in targeted recombination mutagenesis in mammals. Another noteworthy discovery made nearly a decade ago was the identification of a novel class of non-coding genes called microRNAs. MicroRNAs are among the largest known classes of regulatory elements with more than 1000 predicted to exist in the mouse genome. Over 50% of known microRNAs are located within introns of coding genes. Given that currently about half of the genes in mouse have been knocked out, we investigated the possibility that intronic microRNAs may have been coincidentally deleted or disrupted in some of these mouse models. We searched published murine knockout studies and gene trap embryonic stem cell line databases for cases where a microRNA was located within or near the manipulated genomic loci, finding almost 200 cases where microRNA expression may have been disrupted along with another gene. Our results draw attention to the need for careful planning in future knockout studies to minimize the unintentional disruption of microRNAs. These data also raise the possibility that many knockout studies may need to be reexamined to determine if loss of a microRNA contributes to the phenotypic consequences attributed to loss of a protein-encoding gene.     

Prediction of personalized microRNA activity

MicroRNAs have been known to regulate almost all physiological and pathological processes by suppressing their target genes. In humans, more than 1000 microRNAs have been identified, each of which targets dozens or even hundreds of genes. Facing this huge repertoire of microRNA targeting, it is important to identify which microRNAs are active, i.e., down-regulating their targets, in specific physiological or pathological conditions. Predicting active microRNAs is different from predicting microRNA targets because the authentic target genes of a microRNA are often not directly and solely regulated by that microRNA, leading to inconsistent expression changes between the microRNA and its true targets. Several computational programs have been proposed to predict the activity of a microRNA from the expressions of its target genes. These programs performed well when being applied on the expression data obtained from distinct tissue types or from experiments that transfect a microRNA into cells (i.e., non-physiological). But the performance of microRNA activity prediction is not clear on the expression data from the same tissue type in two physiological conditions, e.g., liver tissues from cancer patients and healthy people. In this work, we evaluate the performance of two microRNA activity prediction programs using seven expression data sets, all of which compare samples in two physiological conditions, as well as propose a new approach that predicts microRNA activity with an accuracy of over 80%. Unlike current methods, which predict active microRNAs by comparing two groups of samples, e.g., tumor versus normal, our new approach compares each diseased sample with all the samples in the control group. In other words, it can predict the microRNA activity of a person. In this work, this new application is named to predict “personalized microRNA activity”.     

A MicroRNA Network Dysregulated in Asthma Controls IL-6 Production in Bronchial Epithelial Cells

MicroRNAs are short non-coding single stranded RNAs that regulate gene expression. While much is known about the effects of individual microRNAs, there is now growing evidence that they can work in co-operative networks. MicroRNAs are known to be dysregulated in many diseases and affect pathways involved in the pathology. We investigated dysregulation of microRNA networks using asthma as the disease model. Asthma is a chronic inflammatory disease of the airways characterized by bronchial hyperresponsiveness and airway remodelling. The airway epithelium is a major contributor to asthma pathology and has been shown to produce an excess of inflammatory and pro-remodelling cytokines such as TGF-β, IL-6 and IL-8 as well as deficient amounts of anti-viral interferons. After performing microRNA arrays, we found that microRNAs -18a, -27a, -128 and -155 are down-regulated in asthmatic bronchial epithelial cells, compared to cells from healthy donors. Interestingly, these microRNAs are predicted in silico to target several components of the TGF-β, IL-6, IL-8 and interferons pathways. Manipulation of the levels of individual microRNAs in bronchial epithelial cells did not have an effect on any of these pathways. Importantly, knock-down of the network of microRNAs miR-18a, -27a, -128 and -155 led to a significant increase of IL-8 and IL-6 expression. Interestingly, despite strong in silico predictions, down-regulation of the pool of microRNAs did not have an effect on the TGF-β and Interferon pathways. In conclusion, using both bioinformatics and experimental tools we found a highly relevant potential role for microRNA dysregulation in the control of IL-6 and IL-8 expression in asthma. Our results suggest that microRNAs may have different roles depending on the presence of other microRNAs. Thus, interpretation of in silico analysis of microRNA function should be confirmed experimentally in the relevant cellular context taking into account interactions with other microRNAs when studying disease.     

Functional screen reveals essential roles of miR‐27a/24 in differentiation of embryonic stem cells

MicroRNAs play important roles in controlling the embryonic stem cell (ESC) state. Although much is known about microRNAs maintaining ESC state, microRNAs that are responsible for promoting ESC differentiation are less reported. Here, by screening 40 microRNAs pre-selected by their expression patterns and predicted targets in Dgcr8-null ESCs, we identify 14 novel differentiation-associated microRNAs. Among them, miR-27a and miR-24, restrained by c-Myc in ESC, exert their roles of silencing self-renewal through directly targeting several important pluripotency-associated factors, such as Oct4, Foxo1 and Smads. CRISPR/Cas9-mediated knockout of all miR-27/24 in ESCs leads to serious deficiency in ESC differentiation in vitro and in vivo. Moreover, depleting of them in mouse embryonic fibroblasts can evidently promote somatic cell reprogramming. Altogether, our findings uncover the essential role of miR-27 and miR-24 in ESC differentiation and also demonstrate novel microRNAs responsible for ESC differentiation.     

Altered microRNA expression in human heart disease.

MicroRNAs are recently discovered regulators of gene expression and are becoming increasingly recognized as important regulators of heart function. Genome-wide profiling of microRNAs in human heart failure has not been reported previously. We measured expression of 428 microRNAs in 67 human left ventricular samples belonging to control (n = 10), ischemic cardiomyopathy (ICM, n = 19), dilated cardiomyopathy (DCM, n = 25), or aortic stenosis (AS, n = 13) diagnostic groups. miRNA expression between disease and control groups was compared by ANOVA with Dunnett's post hoc test. We controlled for multiple testing by estimating the false discovery rate. Out of 428 microRNAs measured, 87 were confidently detected; 43 were differentially expressed in at least one disease group. In supervised clustering, microRNA expression profiles correctly grouped samples by their clinical diagnosis, indicating that microRNA expression profiles are distinct between diagnostic groups. This was further supported by class prediction approaches, in which the class (control, ICM, DCM, AS) predicted by a microRNA-based classifier matched the clinical diagnosis 69% of the time (P < 0.001). These data show that expression of many microRNAs is altered in heart disease and that different types of heart disease are associated with distinct changes in microRNA expression. These data will guide further studies of the contribution of microRNAs to heart disease pathogenesis.     

miR-30d负性调节HeLa细胞的增殖

有证据显示,microRNA( miRNA)可作为癌基因或抑癌基因发挥功能,参与细胞增殖和凋等 调控;PI3K/Akt通路的持续活化与肿瘤的发生、发展密切相关．在本研究中,我们通过microarray技术在HeLa细胞中检测经ly294002作用24 h阻断PI3K/Akt通路后microRNA的表达变化．Taqman 实时 PCR实验结果显示,has-miR-30d的表达在PI3K/Akt通路被阻断后明显上调．萤光素酶报告基因转染结合Taqman 实时 PCR显示,稳定转染miR- 30d过表达质粒的HeLa细胞系中miR-30d的表达量升高并且有活性．MTT及流式细胞术分析显示,过表达miR-30d的HeLa细胞其增殖受到抑制．这些结果说明,has-miR-30d可抑制HeLa细胞增殖,负性调节细胞生长,是一个潜在的抑癌基因．