Silencing the silencer: strategies to inhibit microRNA activity

Plants and animals microRNAs (miRNAs) have been proposed to be key regulators of many fundamental processes. However defining miRNAs function has been problematic due to the paucity of miRNA loss-of-function mutants. This is likely due to their small gene size and redundancy as most miRNA have highly related family members. Consequently, the analysis of miRNA function has been primarily based on predictive bioinformatic or transgenic gain-of-function approaches. However, a number of new methodologies have been developed able to result in loss-of-function phenotypes. This includes miRNA sponges in animals and target mimicry in plants, both of which sequesters the mature miRNAs, disrupting endogenous miRNA:mRNA target relationships. Furthermore, artificial miRNAs and RNA interference in plants have been shown to be potent silencers of MIRNA genes. We will discuss the strengths and weaknesses of these methodologies which are potentially of great biotechnological use in medicine and agriculture.     

Embryogenomics: developmental biology meets genomics

Fundamental questions in developmental biology are: what genes are expressed, where and when they are expressed, what is the level of expression and how are these programs changed by the functional and structural alteration of genes? These questions have been addressed by studying one gene at a time, but a new research field that handles many genes in parallel is emerging. The methodology is at the interface of large-scale genomics approaches and developmental biology. Genomics needs developmental biology because one of the goals of genomics – collection and analysis of all genes in an organism – cannot be completed without working on embryonic tissues in which many genes are uniquely expressed. However, developmental biology needs genomics – the high-throughput approaches of genomics generate information about genes and pathways that can give an integrated view of complex processes. This article discusses these new approaches and their applications to mammalian developmental biology.     

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.     

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.     

植物MicroRNA

MicroRNA (miRNA)是一类长度约为22个核苷酸的内源单链非编码RNA,在结构上相当保守,因而可以借助生物信息学方法进行预测. 从2002年证实miRNA在植物中的存在以来,关于植物miRNA的研究进展异常迅速,短短几年内就已发现200多种. 植物miRNA主要通过切割靶mRNA,或抑制靶mRNA翻译,来调控植物个体生长发育并影响其生理过程,是一种新的基因调控方式. 本文将就植物miRNA的形成、特征、作用机制、生物功能及其与siRNA的关系进行综述.     

miRNA Genes of an Invasive Vector Mosquito,Aedes albopictus

Aedes albopictus, a vector of Dengue and Chikungunya viruses, is a robust invasive species in both tropical and temperate environments. MicroRNAs (miRNAs) regulate gene expression and biological processes including embryonic development, innate immunity and infection. While a number of miRNAs have been discovered in some mosquitoes, no comprehensive effort has been made to characterize them from different developmental stages from a single species. Systematic analysis of miRNAs in Ae. albopictus will improve our understanding of its basic biology and inform novel strategies to prevent virus transmission. Between 10–14 million Illumina sequencing reads per sample were obtained from embryos, larvae, pupae, adult males, sugar-fed and blood-fed adult females. A total of 119 miRNA genes represented by 215 miRNA or miRNA star (miRNA*) sequences were identified, 15 of which are novel. Eleven, two, and two of the newly-discovered miRNA genes appear specific to Aedes, Culicinae, and Culicidae, respectively. A number of miRNAs accumulate predominantly in one or two developmental stages and the large number that showed differences in abundance following a blood meal likely are important in blood-induced mosquito biology. Gene Ontology (GO) analysis of the targets of all Ae. albopictus miRNAs provides a useful starting point for the study of their functions in mosquitoes. This study is the first systematic analysis of miRNAs based on deep-sequencing of small RNA samples of all developmental stages of a mosquito species. A number of miRNAs are related to specific physiological states, most notably, pre- and post-blood feeding. The distribution of lineage-specific miRNAs is consistent with mosquito phylogeny and the presence of a number of Aedes-specific miRNAs likely reflects the divergence between the Aedes and Culex genera.     

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.     

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。     

miReader: Discovering Novel miRNAs in Species without Sequenced Genome

Along with computational approaches, NGS led technologies have caused a major impact upon the discoveries made in the area of miRNA biology, including novel miRNAs identification. However, to this date all microRNA discovery tools compulsorily depend upon the availability of reference or genomic sequences. Here, for the first time a novel approach, miReader, has been introduced which could discover novel miRNAs without any dependence upon genomic/reference sequences. The approach used NGS read data to build highly accurate miRNA models, molded through a Multi-boosting algorithm with Best-First Tree as its base classifier. It was comprehensively tested over large amount of experimental data from wide range of species including human, plants, nematode, zebrafish and fruit fly, performing consistently with >90% accuracy. Using the same tool over Illumina read data for Miscanthus, a plant whose genome is not sequenced; the study reported 21 novel mature miRNA duplex candidates. Considering the fact that miRNA discovery requires handling of high throughput data, the entire approach has been implemented in a standalone parallel architecture. This work is expected to cause a positive impact over the area of miRNA discovery in majority of species, where genomic sequence availability would not be a compulsion any more.     

The microRNA Expression Profile in Donation after Cardiac Death (DCD) Livers and Its Ability to Identify Primary Non Function

Donation after cardiac death (DCD) livers are marginal organs for transplant and their use is associated with a higher risk of primary non function (PNF) or early graft dysfunction (EGD). The aim was to determine if microRNA (miRNA) was able to discriminate between DCD livers of varying clinical outcome. DCD groups were categorized as PNF retransplanted within a week (n=7), good functional outcome (n=7) peak aspartate transaminase (AST) ≤ 1000 IU/L and EGD (n=9) peak AST ≥ 2500 IU/L. miRNA was extracted from archival formalin fixed post-perfusion tru-cut liver biopsies. High throughput expression analysis was performed using miRNA arrays. Bioinformatics for expression data analysis was performed and validated with real time quantitative PCR (RT-qPCR). The function of miRNA of interest was investigated using computational biology prediction algorithms. From the array analysis 16 miRNAs were identified as significantly different (p<0.05). On RT-qPCR miR-155 and miR-940 had the highest expression across all three DCD clinical groups. Only one miRNA, miR-22, was validated with marginal significance, to have differential expression between the three groups (p=0.049). From computational biology miR-22 was predicted to affect signalling pathways that impact protein turnover, metabolism and apoptosis/cell cycle. In conclusion, microRNA expression patterns have a low diagnostic potential clinically in discriminating DCD liver quality and outcome.     

Mathematical modeling of combinatorial regulation suggests that apparent positive regulation of targets by miRNA could be an artifact resulting from competition for mRNA

MicroRNAs bind to and regulate the abundance and activity of target messenger RNA through sequestration, enhanced degradation, and suppression of translation. Although miRNA have a predominantly negative effect on the target protein concentration, several reports have demonstrated a positive effect of miRNA, i.e., increase in target protein concentration on miRNA overexpression and decrease in target concentration on miRNA repression. miRNA–target pair-specific effects such as protection of mRNA degradation owing to miRNA binding can explain some of these effects. However, considering such pairs in isolation might be an oversimplification of the RNA biology, as it is known that one miRNA interacts with several targets, and conversely target mRNA are subject to regulation by several miRNAs. We formulate a mathematical model of this combinatorial regulation of targets by multiple miRNA. Through mathematical analysis and numerical simulations of this model, we show that miRNA that individually have a negative effect on their targets may exhibit an apparently positive net effect when the concentration of one miRNA is experimentally perturbed by repression/overexpression in such a multi-miRNA multitarget situation. We show that this apparent unexpected effect is due to competition and will not be observed when miRNA interact noncompetitively with the target mRNA. This result suggests that some of the observed unusual positive effects of miRNA may be due to the combinatorial complexity of the system rather than due to any inherently unusual positive effect of the miRNA on its target.