降解组测序技术在植物miRNA研究中的应用

目前, 利用芯片技术和miRNA测序可快速、准确地检测到物种中所含有的miRNA。随着越来越多的miRNA被发现, miRNA靶基因的确定已成为研究miRNA生物学功能的关键。传统的miRNA靶基因的寻找主要依赖生物信息学预测、AGO蛋白免疫共沉淀和荧光素酶法等。随着高通量测序技术的持续革新, 出现了一种新的miRNA靶基因的检测方法, 即降解组测序(degradome sequencing)法, 该方法拥有高通量测序技术、生物信息学分析和RACE验证三者的优势, 并已成功应用于拟南芥(Arabidopsis thaliana)、水稻(Oryza sativa)和小立碗藓(Physcomitrella patens)等模式植物miRNA靶基因的检测。基于已发表的相关文献和联川生物降解组测序平台, 该文对降解组测序技术应用于植物miRNA靶基因的研究进展及其实验原理进行了综述, 同时对运用该技术可进行的更深入研究进行了讨论。     

Computational identification of novel microRNAs and targets in Brassica napus

MicroRNAs (miRNAs) are a newly discovered class of non-protein-coding small RNAs with roughly 22 nucleotide-long. Increasing evidence has shown that miRNAs play multiple roles in biological processes, including development, cell proliferation and apoptosis and stress responses. In this research, several approaches were combined to make computational prediction of potential miRNAs and their targets in Brassica napus. We used previously known miRNAs from Arabidopsis, rice and other plant species against both expressed sequence tags (EST) and genomic survey sequence (GSS) databases to search for potential miRNAs in B. napus. A total of 21 potential miRNAs were detected following a range of strict filtering criteria. Using these potential miRNA sequences, we could further blast the mRNA database and found 67 potential targets in this species. According to the mRNA target information provided by NCBI (http://www.ncbi.nlm.nih.gov/), most of the target mRNAs appeared to be involved in plant growth, development and stress responses. To validate the prediction of miRNAs in B. napus, we performed a RT-PCR based assay of mature miRNA expression. Five miRNAs were identified in response to auxin, cadmium stress and phosphate starvation. So far, little is known about experimental or computational identification of miRNA in B. napus species. To improve efficiency for blast search, we developed an implementation (miRNAassist) that can identify homologs of miRNAs and their targets, with high sensitivity and specificity. The program is allowed to be run on Windows Operation System platform. miRNAassist is freely available if required.     

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.     

计算识别microRNA及其靶基因

小RNA的发现为基因调控系统研究提供了新的方向。在多数物种中已经发现了大量的小RNA。这一领域已经成为了近来研究的热点,在研究起始阶段,计算学方法已经成为实验研究中不可或缺的工具,许多发现是由生物学实验与计算学方法共同合作来完成的。在这篇综述中,我们总结了前人关于小RNA及其靶基因识别的理论知识。最后,讨论了关于预测小RNA及其靶基因的计算学方法和相关软件。     

Current tools for the identification of miRNA genes and their targets

The discovery of microRNAs (miRNAs), almost 10 years ago, changed dramatically our perspective on eukaryotic gene expression regulation. However, the broad and important functions of these regulators are only now becoming apparent. The expansion of our catalogue of miRNA genes and the identification of the genes they regulate owe much to the development of sophisticated computational tools that have helped either to focus or interpret experimental assays. In this article, we review the methods for miRNA gene finding and target identification that have been proposed in the last few years. We identify some problems that current approaches have not yet been able to overcome and we offer some perspectives on the next generation of computational methods.     

microRNA计算发现方法的研究进展

microRNA (miRNA)是近几年发现的一类长度为～21 nt的内源非编码小RNA, 在植物和动物中发挥着重要而广泛的调控功能。它的发现主要有cDNA克隆测序和计算发现两条途径。由于cDNA克隆测序方法受miRNA表达的时间和组织特异性以及表达水平的影响, 而计算发现可以弥补其不足, 因此miRNA的计算发现方法研究受到了广泛的重视。文章对近几年计算发现miRNA的研究进展进行了综述, 根据计算发现方法的本质, 将计算发现方法归纳为5类, 分别是同源片段搜索方法、基于比较基因组学的预测方法、基于序列和结构特征打分的预测方法、结合作用靶标的预测方法和基于机器学习的预测方法, 并对各类方法的原理、核心思想、优点和局限性进行了分析, 最后探讨了进一步的发展方向。     

The discovery approaches and detection methods of microRNAs

MicroRNAs (miRNAs) are small, highly conserved, non-coding RNAs that regulate gene expression of target mRNAs through cleavage or translational inhibition. Computer-based approaches for miRNA gene identification are being considered as indispensable in miRNAs research. Similarly, experimental approaches for detection of miRNAs are crucial to the testing and validating of computational algorithms. The detection of miRNAs in tissues or cells can supply valuable information for investigating the biological function of these molecules. Selective and highly sensitive detection methods will pave the way for extended understanding of miRNA function within organisms. In this review, we summarize the various computational methods for identification of miRNAs as well as the methodologies that have been developed to detection miRNAs.     

microRNA在玉米生长发育及非生物胁迫响应中的调控功能

microRNA（miRNA）是一类广泛存在于真核生物中长度为20~24 nt的内源非编码小RNA，它们通过对靶基因mRNA进行切割或翻译抑制，在转录后水平调控靶基因的表达。近期研究表明，miRNA参与植物生长发育与逆境胁迫响应的多个重要生物学过程，对作物的农艺性状也起到重要的调控作用。玉米作为重要的粮食、饲料和工业原料，提高其产量和品质对于保障世界粮食安全至关重要，然而与模式植物拟南芥和水稻相比，玉米中miRNA的研究仍然相对较少，理解miRNA在玉米中的功能和调控机理有助于通过分子育种对关键农艺性状进行遗传改良。本文综述了玉米中miRNA的发现与鉴定，系统总结了参与玉米miRNA代谢途径的关键蛋白DCL、AGO和HEN1的研究进展，重点阐述了在玉米生长发育和非生物胁迫响应过程中已开展功能研究miRNA的调控作用，并对玉米miRNA研究当前存在的问题和未来的发展趋势进行了讨论。     

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.