Human microRNA target identification by RRSM

MicroRNAs (miRNAs) are small endogenously expressed non-coding RNAs that regulate target messenger RNAs in various biological processes. In recent years, there have been many studies concentrated on the discovery of new miRNAs and identification of their mRNA targets. Although researchers have identified many miRNAs, few miRNA targets have been identified by actual experimental methods. To expedite the identification of miRNA targets for experimental verification, in the literature approaches based on the sequence or microarray expression analysis have been established to discover the potential miRNA targets. In this study, we focus on the human miRNA target prediction and propose a generalized relative R2 method (RRSM) to find many high-confidence targets. Many targets have been confirmed from previous studies. The targets for several miRNAs discovered by the HITS-CLIP method in a recent study have also been selected by our study.     

Characterization of microRNAs from sheep (<Emphasis Type="Italic">Ovis aries</Emphasis>) using computational and experimental analyses

Ovis aries is one of the most important agricultural livestock for meat production, and also is an ideal model organism for biological and comparative genomics studies. Many miRNAs have been reported for their important roles in developmental processes in various animals, but there is limited information about O. aries miRNAs. In this study, combining a computational method based on expressed sequence tag (EST) analysis with experimental identification based on small RNA cDNA library, we identified 31 miRNAs belong to 24 families in sheep, 2 of which were novel miRNAs which had never been previously identified in any species. Especially, we cloned 12 miRNAs from the sheep skeletal muscle, which were good candidate miRNAs to be studied about the miRNA-dependant regulated process of muscle development, and we identified four pairs of miRNA/miRNA* and one pair of miRNA-3p/miRNA-5p from sheep EST sequences. Expression analysis indicated that some miRNAs were expressed in a specific tissue, and the pair of miRNA-3p/miRNA-5p and one pair of miRNA/miRNA* had a similar relative expression pattern in some tissues, respectively. Further, we predicted 120 potential target genes of 31 oar-miRNAs on the 3′UTR of O. aries genes. Gene ontology analysis showed that most of these genes took part in the cellular process and metabolic process. Our results enriched the O. aries miRNA database and provided useful information for investigating biological functions of miRNAs and miRNA* in sheep.     

The diverse functions of microRNAs in animal development and disease

MicroRNAs (miRNAs) control gene expression by translational inhibition and destabilization of mRNAs. While hundreds of miRNAs have been found, only a few have been studied in detail. miRNAs have been implicated in tissue morphogenesis, cellular processes like apoptosis, and major signaling pathways. Emerging evidence suggests a direct link between miRNAs and disease, and miRNA expression signatures are associated with various types of cancer. In addition, the gain and loss of miRNA target sites appears to be causal to some genetic disorders. Here, we discuss the current literature on the role of miRNAs in animal development and disease.     

miRNAs的表达调控机制

microRNAs(miRNAs)是一类在转录后基因调控中发挥功能的非编码小RNAs,在发育、生长和分化等过程中发挥重要作用.至今已经在动物、植物和微生物等不同生物体中鉴定出来数千种miRNAs. miRNAs可以通过降解mRNA或抑制蛋白翻译的方式调节特异基因表达.生物体内约30%的基因都受miRNAs的调节.miRNAs的表达与功能受到转录因子、表观遗传学、多核苷酸多态性及其RNA编辑等多种因素的调节.此外,特异miRNA基因敲除的成功为研究miRNAs功能提供了有力的实验模型.     

SCMFMDA: Predicting microRNA-disease associations based on similarity constrained matrix factorization

miRNAs belong to small non-coding RNAs that are related to a number of complicated biological processes. Considerable studies have suggested that miRNAs are closely associated with many human diseases. In this study, we proposed a computational model based on Similarity Constrained Matrix Factorization for miRNA-Disease Association Prediction (SCMFMDA). In order to effectively combine different disease and miRNA similarity data, we applied similarity network fusion algorithm to obtain integrated disease similarity (composed of disease functional similarity, disease semantic similarity and disease Gaussian interaction profile kernel similarity) and integrated miRNA similarity (composed of miRNA functional similarity, miRNA sequence similarity and miRNA Gaussian interaction profile kernel similarity). In addition, the L₂ regularization terms and similarity constraint terms were added to traditional Nonnegative Matrix Factorization algorithm to predict disease-related miRNAs. SCMFMDA achieved AUCs of 0.9675 and 0.9447 based on global Leave-one-out cross validation and five-fold cross validation, respectively. Furthermore, the case studies on two common human diseases were also implemented to demonstrate the prediction accuracy of SCMFMDA. The out of top 50 predicted miRNAs confirmed by experimental reports that indicated SCMFMDA was effective for prediction of relationship between miRNAs and diseases.     

Detection of microRNA Expression in Human Peripheral Blood Microvesicles

Background

MicroRNAs (miRNA) are small non-coding RNAs that regulate translation of mRNA and protein. Loss or enhanced expression of miRNAs is associated with several diseases, including cancer. However, the identification of circulating miRNA in healthy donors is not well characterized. Microvesicles, also known as exosomes or microparticles, circulate in the peripheral blood and can stimulate cellular signaling. In this study, we hypothesized that under normal healthy conditions, microvesicles contain miRNAs, contributing to biological homeostasis.

Methodology/Principal Findings

Microvesicles were isolated from the plasma of normal healthy individuals. RNA was isolated from both the microvesicles and matched mononuclear cells and profiled for 420 known mature miRNAs by real-time PCR. Hierarchical clustering of the data sets indicated significant differences in miRNA expression between peripheral blood mononuclear cells (PBMC) and plasma microvesicles. We observed 71 miRNAs co-expressed between microvesicles and PBMC. Notably, we found 33 and 4 significantly differentially expressed miRNAs in the plasma microvesicles and mononuclear cells, respectively. Prediction of the gene targets and associated biological pathways regulated by the detected miRNAs was performed. The majority of the miRNAs expressed in the microvesicles from the blood were predicted to regulate cellular differentiation of blood cells and metabolic pathways. Interestingly, a select few miRNAs were also predicted to be important modulators of immune function.

Conclusions

This study is the first to identify and define miRNA expression in circulating plasma microvesicles of normal subjects. The data generated from this study provides a basis for future studies to determine the predictive role of peripheral blood miRNA signatures in human disease and will enable the definition of the biological processes regulated by these miRNA.     

Analysis of microRNA signatures using size-coded ligation-mediated PCR

The expression pattern and regulatory functions of microRNAs (miRNAs) are intensively investigated in various tissues, cell types and disorders. Differential miRNA expression signatures have been revealed in healthy and unhealthy tissues using high-throughput profiling methods. For further analyses of miRNA signatures in biological samples, we describe here a simple and efficient method to detect multiple miRNAs simultaneously in total RNA. The size-coded ligation-mediated polymerase chain reaction (SL-PCR) method is based on size-coded DNA probe hybridization in solution, followed-by ligation, PCR amplification and gel fractionation. The new method shows quantitative and specific detection of miRNAs. We profiled miRNAs of the let-7 family in a number of organisms, tissues and cell types and the results correspond with their incidence in the genome and reported expression levels. Finally, SL-PCR detected let-7 expression changes in human embryonic stem cells as they differentiate to neuron and also in young and aged mice brain and bone marrow. We conclude that the method can efficiently reveal miRNA signatures in a range of biological samples.     

Computational approaches for microRNA studies: a review

MicroRNAs (miRNAs) are one class of tiny, endogenous RNAs that can regulate messenger RNA (mRNA) expression by targeting homologous sequences in mRNAs. Their aberrant expressions have been observed in many cancers and several miRNAs have been convincingly shown to play important roles in carcinogenesis. Since the discovery of this small regulator, computational methods have been indispensable tools in miRNA gene finding and functional studies. In this review we first briefly outline the biological findings of miRNA genes, such as genomic feature, biogenesis, gene structure, and functional mechanism. We then discuss in detail the three main aspects of miRNA computational studies: miRNA gene finding, miRNA target prediction, and regulation of miRNA genes. Finally, we provide perspectives on some emerging issues, including combinatorial regulation by miRNAs and functional binding sites beyond the 3′-untranslated region (3′UTR) of target mRNAs. Available online resources for miRNA computational studies are also provided.