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.     

生物信息学在植物miRNA研究中的应用

植物miRNA的研究已经从小规模实验向大规模计算分析方向发展,生物信息学的应用成为当前植物miRNA研究的热点问题。本文回顾了最近几年生物信息学在植物miRNA研究中取得的最新进展,简要介绍了植物miRNA的形成及其作用方式,重点对植物miRNA的计算识别、靶基因预测、启动子分析方法进行了讨论,并对相关的数据库资源进行了总结,最后展望了该领域研究的发展方向,将为植物miRNA的计算研究提供理论指导。     

A GAL4/UAS luciferase system to identify the miRNAs target mRNAs in <Emphasis Type="Italic">Drosophila</Emphasis> S2 cells

MicroRNAs (miRNAs) have been shown to regulate gene expression through the sequence-specific base pairing with their target mRNAs. However, our understanding of the biological roles of miRNAs is still quite limited, and only a handful of miRNAs have been assigned by genetic analysis in part owing to the difficulty in the identification of their targets. Although computational methods have shown to be helpful in the prediction of miRNA targets, a major obstacle has been the lack of quick and efficient experimental procedures to verify these targets. In this report, we describe a UAS/GAL4-based reporter system for this purpose. Our data indicate it an assay of miRNA–target gene interaction, with greater sensitivity over the previously reported methods, and may be useful for more efficient identification/validation the miRNA targets in Drosophila cell lines.     

Analysis of putative miRNA function using a novel approach, GAPPS-miRTarGE

Deciphering the function of miRNA is one of the most important research subjects directed toward understanding the regulation of gene expression. Several experimental methodologies and bioinformatics programs have been developed, however, elucidating miRNA function has not been an easy task. Herein, we suggest a new method, GAPPS-miRTar^GE, which is a novel methodology for predicting miRNA function based on the proportion of mRNA targets expressed during embryonic developmental stages, the Theilers stages (TS), in mice. GAPPS-miRTar^GE is essentially a computational approach that groups miRNAs using shared expression patterns of their target genes during the 28 different TS. In this study, we present not only several examples derived from the GAPPS-miRTar^GE analyses that confirm previously known miRNA functions but also examples of function prediction for valid but functionally unknown miRNAs. Furthermore, we show that tissue-centered GAPPS-miRTar^GE, such as brain-centered or heart-centered, is useful for predicting miRNA function on a more detailed level.     

Conservation and evolution of miRNA regulatory programs in plant development

Over the past two years, microarray technologies, large-scale small RNA and whole genome sequencing projects, and data mining have provided a wealth of information about the spectrum of miRNAs and miRNA targets present in different plant species and the alga Chlamydomonas. Such studies have shown that a number of key miRNA regulatory modules for plant development are conserved throughout the plant kingdom, suggesting that these programs were crucial to the colonization of land. New genetic and biochemical studies of miRNA pathways in Arabidopsis, the spatiotemporal expression patterns of several conserved miRNAs and their targets, and the characterization of mutations in Arabidopsis and maize have begun to reveal the functions of these ancient miRNA-regulated developmental programs. In addition to these conserved miRNAs, there are many clade and species-specific miRNAs, which have evolved more recently and whose functions are currently unknown.     

Mature MiRNAs Form Secondary Structure,which Suggests Their Function beyond RISC

The generally accepted model of the miRNA-guided RNA down-regulation suggests that mature miRNA targets mRNA in a nucleotide sequence-specific manner. However, we have shown that the nucleotide sequence of miRNA is not the only determinant of miRNA specificity. Using specific nucleases, T1, V1 and S1 as well as NMR, UV/Vis and CD spectroscopies, we found that miR-21, miR-93 and miR-296 can adopt hairpin and/or homoduplex structures. The secondary structure of those miRNAs in solution is a function of RNA concentration and ionic conditions. Additionally, we have shown that a formation of miRNA hairpin is facilitated by cellular environment.Looking for functional consequences of this observation, we have perceived that structure of these miRNAs resemble RNA aptamers, short oligonucleotides forming a stable 3D structures with a high affinity and specificity for their targets. We compared structures of anti-tenascin C (anti-Tn-C) aptamers, which inhibit brain tumor glioblastoma multiforme (GBM, WHO IV) and selected miRNA. A strong overexpression of miR-21, miR-93 as well Tn-C in GBM may imply some connections between them. The structural similarity of these miRNA hairpins and anti-Tn-C aptamers indicates that miRNAs may function also beyond RISC and are even more sophisticated regulators, that it was previously expected. We think that the knowledge of the miRNA structure may give a new insight into miRNA-dependent gene regulation mechanism and be a step forward in the understanding their function and involvement in cancerogenesis. This may improve design process of anti-miRNA therapeutics.     

microRNAs in neurons: manifold regulatory roles at the synapse

The regulation of synapse formation and plasticity in the developing and adult brain underlies a complex interplay of intrinsic genetic programs and extrinsic factors. Recent research identified microRNAs (miRNAs), a class of small non-coding RNAs, as a new functional layer in this regulatory network. Within only a few years, a network of synaptic miRNAs and their target genes has been extensively characterized, highlighting the importance of this mechanism for synapse development and physiology. Very recent data further provide insight into activity-dependent regulation of miRNAs, thereby connecting miRNAs with adaptive processes of neural circuits. First direct links between miRNA dysfunction and synaptic pathologies are emerging, raising the interest in these molecules as potential biomarkers and therapeutic targets in neurological disorders.     

Sequence variation of MicroRNAs and their binding sites in Arabidopsis

Major differences exist between plants and animals both in the extent of microRNA (miRNA)-based gene regulation and the sequence complementarity requirements for miRNA-messenger RNA pairing. Whether these differences affect how these sites evolve at the molecular level is unknown. To determine the extent of sequence variation at miRNAs and their targets in a plant species, we resequenced 16 miRNA families (66 miRNAs in total) and all 52 of the characterized binding sites for these miRNAs in the plant model Arabidopsis (Arabidopsis thaliana), accounting for around 50% of the known miRNAs and binding sites in this species. As has been shown previously in humans, we find that both miRNAs and their target binding sites have very low nucleotide variation and divergence compared to their flanking sequences in Arabidopsis, indicating strong purifying selection on these sites in this species. Sequence data flanking the mature miRNAs, however, exhibit normal levels of polymorphism for the accessions in this study and, in some cases, nonneutral evolution or subtle effects on predicted pre-miRNA secondary structure, suggesting that there is raw material for the differential function of miRNA alleles. Overall, our results show that despite differences in the architecture of miRNA-based regulation, miRNAs and their targets are similarly constrained in both plants and animals.     

Lessons from microRNA mutants in worms,flies and mice

It is apparent that microRNAs (miRNAs) are important components in the regulation of genetic networks in many biological contexts. Based on computational analysis, typical miRNAs are inferred to have tens to hundreds of conserved targets. Many miRNA-target interactions have been validated by various means, including heterologous tests in cultured cells and gain-of-function approaches that can yield striking phenotypes in whole animals. However, these strategies do not report on the endogenous importance of such miRNA activities. Likewise, studies of miRNA pathway mutants can suggest an endogenous role for miRNAs in a given setting, but do not identify roles for specific miRNAs. Therefore, these approaches must be complemented with the analysis of miRNA mutant alleles. In this review, we describe some of the lessons learned from studying miRNA gene deletions in worms, flies and mice, and discuss their implications for the control of endogenous regulatory networks.     

Systematic identification of microRNA functions by combining target prediction and expression profiling

Target predictions and validations are major obstacles facing microRNA (miRNA) researchers. Animal miRNA target prediction is challenging because of limited miRNA sequence complementarity to the targets. In addition, only a small number of predicted targets have been experimentally validated and the miRNA mechanism is poorly understood. Here we present a novel algorithm for animal miRNA target prediction. The algorithm combines relevant parameters for miRNA target recognition and heuristically assigns different weights to these parameters according to their relative importance. A score calculation scheme is introduced to reflect the strength of each parameter. We also performed microarray time course experiments to identify downregulated genes due to miRNA overexpression. The computational target prediction is combined with the miRNA transfection experiment to systematically identify the gene targets of human miR-124. miR-124 overexpression led to a significant downregulation of many cell cycle related genes. This may be the result of direct suppression of a few cell growth inhibitors at the early stage of miRNA overexpression, and these targeted genes were continuously suppressed over a long period of time. Our high-throughput approach can be generalized to globally identify the targets and functions of other miRNAs.     

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.     

Sweating the small stuff: microRNA discovery in plants

The class of small RNAs known as microRNAs (miRNAs) has a demonstrated role in the negative regulation of gene expression in both plants and animals. These small molecules have been shown to play a critical role in a wide range of developmental and physiological pathways. Although hundreds of different miRNAs have now been identified using cloning and computational approaches, characterization of their targets and biological roles has been more limited. New sequencing technologies promise to accelerate the sequencing of small RNAs and additional genetic and genomic strategies are being applied to assess their regulatory function on RNA targets. These technologies will enable the identification of large numbers of small RNAs from diverse species, and comparative genomics approaches based on these data are likely to identify additional miRNAs. Combined with bioinformatics and experimental approaches to separate miRNAs from short-interfering RNAs (siRNAs), the pace of miRNA discovery is likely to accelerate, leading to an improved understanding of miRNA function and biological significance.     

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.