东方蜜蜂微孢子虫孢子中微小RNA的鉴定与分析

【目的】丰富东方蜜蜂微孢子虫Nosema ceranae的微小RNA(microRNA, miRNA)信息,并为深入探究miRNA在病原孢子和病原侵染中的功能提供理论和实验依据。【方法】基于已获得的small RNA-seq数据,利用生物信息学软件对东方蜜蜂微孢子虫的纯净孢子中的miRNA进行鉴定和分析。采用茎环反转录PCR(stem-loop RT-PCR)检测已鉴定的miRNA的表达;通过分子克隆与Sanger测序验证miRNA的序列。使用TargetFinder软件预测这些miRNA的靶基因,并对靶基因进行数据库注释。根据miRNA与靶基因的靶向结合关系构建调控网络,再利用Cytoscape软件进行可视化。【结果】在东方蜜蜂微孢子虫孢子中共鉴定到10个miRNA;这些miRNA的长度分布介于21~25 nt,首位碱基表现出U偏向性,每一位碱基的偏向性差异明显。Stem-loop RT-PCR检测结果表明这10个miRNA均真实表达;Sanger测序结果证实了随机选取的其中2个miRNA的序列真实性。共预测出249个靶基因,其中分别有249, 118, 136和3个靶基因可注释到Nr,Swiss-Prot, KOG和eggNOG数据库。此外,分别有134和71个靶基因可分别注释到GO数据库的30个功能条目和KEGG数据库的54条通路。【结论】本研究揭示了东方蜜蜂微孢子虫孢子中miRNA的存在和表达;这些miRNA通过调控潜在靶基因的表达参与孢子的生命活动。     

基于EST和GSS序列的玉米未知微RNA的数据挖掘

miRNAs通过与靶基因互补位点配对结合,在转录后水平负性调控靶基因的表达.根据miRNA进化上的保守性,以拟南芥、水稻等已知的植物miRNAs为探针,与相关数据库中玉米表达序列标签(EST)和基因组序列(GSS)中的非编码序列比对,采用一系列的标准进行筛选,最后预测得到24个玉米miRNA前体,通过靶基因的预测共得到61个靶基因.通过生物信息学方法大大提高了人们发现miRNAs及其靶基因的效率,补充了玉米miRNA数据库的不足.     

肾透明细胞癌预后相关miRNAs的生物信息学分析

目的寻找可作为肾透明细胞癌（ccRCC）生物标志物的miRNA,以及ccRCC与正常组织间miRNA差异表达情况。 方法利用TCGA数据库下载ccRCC中miRNA表达数据,分析肿瘤与正常组织间差异表达miRNA。使用Kaplan-Meier曲线对患者进行生存分析,筛选出表达情况与临床预后相关的miRNA。通过生物信息学对miRNA的靶基因进行预测,然后运用FunRich软件和ClueGO对靶基因进行GO和KEGG富集分析。 结果通过TCGA数据库分析发现,ccRCC较正常组织差异表达miRNA共54个,其中上调33个,下调21个。通过生存分析发现hsa-miR-21和hsa-miR-155与患者预后相关,P≤0.05。进一步通过Perl软件在Targetscan、miRDB、miRTarBase、miRPath这四个数据库中预测miRNA靶基因并将结果取交集,共发现129个靶基因。GO和KEGG分析结果表明,这些靶基因主要与转录因子活性、信号转导以及FoxO、TNF等信号通路密切相关。 结论通过生物信息学分析发现了ccRCC与正常组织的差异表达miRNA;其中hsa-miR-21和hsa-miR-155与患者总体生存率相关,并通过调控靶基因参与相关的信号通路进而影响ccRCC的发生发展进程,提示hsa-miR-21和hsa-miR-155可能是ccRCC潜在的生物标志物。     

MicroRNA及其在人和动物上的研究进展

MicroRNA是一种长约22nt的非编码RNA, 通过与靶基因的3′UTR区结合来调控靶基因的表达。目前已证实miRNA在生物体生长、发育和疾病发生等过程中发挥着重要的作用。文章介绍了miRNA的特征、作用机制, 综述了关于miRNA的功能、miRNA基因的鉴定与靶基因预测的最新研究进展。     

玉米microRNAs及其靶基因的生物信息学预测

microRNAs (miRNAs) 是一类非编码的小分子RNA, 通过碱基互补调控靶基因的表达。鉴定和发现新的miRNAs及其靶基因, 对揭示miRNAs在基因表达调控中的作用至关重要。玉米全基因组测序工作开展较晚, 已经鉴定登记的miRNAs很少, 对靶基因的调控作用尚待解明。文章根据miRNA进化上的保守性, 以已知的植物miRNAs为探针, 与相关数据库中玉米表达序列标签(EST)和基因组序列(GSS)中的非编码序列比对, 共发现11个新的miRNA前体。虽然在序列长度和二级结构方面各有变化, 但这11个前体均可折叠形成miRNA家族的标准二级结构。通过靶基因预测, 找到其中7条miRNAs的26个靶基因, 分别编码与新陈代谢、信号转导、转录调节、跨膜运输、生物和非生物胁迫及叶绿体组装等相关的蛋白。这些miRNAs及其靶基因的鉴定, 补充了miRNA数据库的不足。     

三阴性乳腺癌相关miRNA筛选及其靶基因的生物信息学分析

应用生物信息学方法筛选并分析三阴性乳腺癌（triple-negative breast cancer,TNBC）相关miRNA及其靶基因,为TNBC的研究提供潜在的分子靶点。采用GEO2R分析TNBC相关miRNA芯片数据集,筛选差异表达倍数最大的5个上调和5个下调miRNA。miRWalk、TargetScan和miRDB预测靶基因并进行Veen分析取交集。利用DAVID对靶基因进行GO富集分析和KEGG通路分析。利用STRING数据库构建蛋白互作网络,并结合Cytoscape构建miRNA-靶基因调控网络,从而筛选出关键的miRNA及其关键靶基因。利用GEPIA2数据库对靶基因进行生存分析。GEO2R筛选出486个差异miRNA,上调和下调的miRNA分别有298个和188个。对差异倍数最大的5个上调和5个下调miRNA的靶基因进行富集分析显示,靶基因主要参与ErbB信号通路、癌症中转录调控紊乱和cGMP-PKG信号通路等。miRNA-靶基因调控网络显示,表达上调的关键miRNA为miR-611,其关键靶基因为CDC27、UBE2D2、UBR1、SPSB1、HERC2和RLIM;表达下调的关键miRNA为miR-1205,其关键靶基因为WSB1、FBXL8、UBE2W、PTPN11、ARF6、DNAJC6和COPS2。生存分析表明,UBR1（P=0.007 2）和PTPN11（P=0.029）表达上调可显著降低TNBC患者的整体生存率。经筛选获得的关键miRNA及其关键靶基因可作为潜在分子标记物用于TNBC的早期诊断、治疗靶点选择和预后判断,并为后续的研究提供参考依据。     

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。     

MicroRNA靶基因的寻找及鉴定方法研究进展

microRNA（miRNA）的生物学功能是人们非常关注的问题.而miRNA靶基因的确定是研究miRNA生物学功能的关键.目前有关miRNA靶基因的确定主要靠计算机生物信息学软件预测和生物学实验方法.其中生物信息学方法主要根据已证实的miRNA及其靶基因序列之间相互作用的规律性,遵循几个常用原则设计的软件完成,如miRanda,TargetScan和TargetScanS,RNAhybrid,DIANA-microT,PicTar,RNA22及FindTar等.生物学实验方法主要是利用免疫共沉淀寻找与AGO蛋白相互作用的mRNA,或研究受miRNA调控的mRNA水平和蛋白质水平变化来寻找miRNA靶基因.计算机预测方法和生物学实验方法相互补充和完善,使人们能够更加方便地确定miRNA的靶基因,从而进一步研究其生物学功能.本文主要介绍了miRNA靶基因的寻找及鉴定方法的研究进展.     

癌症相关microRNA与靶基因的生物信息学分析

MicroRNAs(miRNAs)是一类长度约为22nt的内源性非编码RNA,通过与靶基因转录本互补结合调控基因的表达。近年来,研究发现miRNA与癌症发生密切相关,miRNA可以直接充当癌基因或者抑癌基因而影响肿瘤的发生和生长。为更进一步揭示癌症相关miRNA的特征及靶基因的功能,文章通过数据库搜索及文献检索,在人类基因组中发现了475个癌症相关miRNA,系统地比较了癌症相关miRNA与非癌症miRNA以及基因内和基因间区癌症相关miRNA在保守性、SNP位点分布、癌谱及转录调控等特性。研究发现,癌症相关miRNA比非癌症miRNA保守性要强,发生SNP概率比较低,同时发现miRNA所涉及癌症数目与保守性成正相关。基因组定位分析发现,癌症相关miRNA比非癌症miRNA更倾向于成簇存在。进一步对宿主基因、癌症相关miRNA及作用的靶基因与癌症发生进行关联分析,发现一些非癌症miRNA的宿主基因倾向于被癌症miRNA作用。本研究结果为深入理解miRNA与癌症之间的关系,以及进一步为miRNA作为癌症诊断指示物提供理论依据。     

微RNA与肺癌

微RNA(microRNA,miRNA)是一类长度为21～22nt的非编码RNA分子,其通过转录后基因沉默调控靶基因的活性,在包括肺癌在内的肿瘤发生中起重要作用。随着对miRNA靶基因及miRNA分子行为认识的提高,miRNA很有可能成为癌症治疗新的途径。本文介绍了miRNA的生成,miRNA在肺癌中的作用机理及诊断治疗方面的最新进展。     

miRDB: a microRNA target prediction and functional annotation database with a wiki interface

MicroRNAs (miRNAs) are short noncoding RNAs that are involved in the regulation of thousands of gene targets. Recent studies indicate that miRNAs are likely to be master regulators of many important biological processes. Due to their functional importance, miRNAs are under intense study at present, and many studies have been published in recent years on miRNA functional characterization. The rapid accumulation of miRNA knowledge makes it challenging to properly organize and present miRNA function data. Although several miRNA functional databases have been developed recently, this remains a major bioinformatics challenge to miRNA research community. Here, we describe a new online database system, miRDB, on miRNA target prediction and functional annotation. Flexible web search interface was developed for the retrieval of target prediction results, which were generated with a new bioinformatics algorithm we developed recently. Unlike most other miRNA databases, miRNA functional annotations in miRDB are presented with a primary focus on mature miRNAs, which are the functional carriers of miRNA-mediated gene expression regulation. In addition, a wiki editing interface was established to allow anyone with Internet access to make contributions on miRNA functional annotation. This is a new attempt to develop an interactive community-annotated miRNA functional catalog. All data stored in miRDB are freely accessible at http://mirdb.org.     

Current approaches to micro-RNA analysis and target gene prediction

It is becoming increasingly evident that micro-RNAs (miRNA) play a significant role in regulating the cellular machinery. These ∼22-nt non-coding RNAs function as negative regulators of gene expression. Since their discovery, considerable information has been obtained on miRNA biology and the mechanism of their action. Guidelines have been established for miRNA nomenclature and databases have been built to house all miRNA from many species. A number of methodologies are available for miRNA analysis. There is a lot of interest in developing bioinformatics approaches to predict miRNA target genes. This article will bring together the information on our current knowledge of miRNA biology, the approaches for miRNA analysis, and computational strategies to gain insight in miRNA functional roles.     

Identification of candidate microRNA biomarkers in renal fibrosis: a meta-analysis of profiling studies

Abstract

The prognostic, diagnostic and therapeutic value of microRNA (miRNA) expression aberrations in renal fibrosis has been studied in recent years. However, the miRNA expression profiling efforts have led to inconsistent results between the studies. The aim of this study was to perform a meta-analysis on the renal fibrosis miRNA expression profiling studies to identify candidate diagnostic biomarkers. We performed comprehensive literature searches in several databases to identify miRNA expression studies of renal fibrosis in animal models and humans. The miRNAs expression data were extracted from 20 included studies, and both miRNA vote-counting strategy and Robust Rank Aggregation method were utilized to identify significant miRNA meta-signatures. The predicted and validated targets of miRNA meta-signature were obtained by using MultiMiR package in 11 databases. Then a gene set enrichment analysis (KEGG, PANTHER pathways and GO processes) were carried out with GeneCodis web tool to recognize pathways that are most strongly influenced by modified expressions of these miRNAs. We recognized in both meta-analysis approaches a significant miRNA meta-signature of five up-regulated (miR-142-3p, miR-223-3p, miR-21-5p, miR-142-5p and miR-214-3p) and two down-regulated (miR-29c-3p and miR-200a-3p) miRNAs. Enrichment analysis confirmed that miRNA meta-signature cooperatively target functionally related genes in signalling and developmental pathways in renal fibrosis. This meta-analysis identified seven highly significant and consistently dysregulated miRNAs from 20 datasets, as the focus of future investigations to discover their potential influence to renal fibrosis and their clinical utility as biomarkers and/or as therapeutic mediators against chronic kidney disease..     

miRSystem: An Integrated System for Characterizing Enriched Functions and Pathways of MicroRNA Targets

Background

Many prediction tools for microRNA (miRNA) targets have been developed, but inconsistent predictions were observed across multiple algorithms, which can make further analysis difficult. Moreover, the nomenclature of human miRNAs changes rapidly. To address these issues, we developed a web-based system, miRSystem, for converting queried miRNAs to the latest annotation and predicting the function of miRNA by integrating miRNA target gene prediction and function/pathway analyses.

Results

First, queried miRNA IDs were converted to the latest annotated version to prevent potential conflicts resulting from multiple aliases. Next, by combining seven algorithms and two validated databases, potential gene targets of miRNAs and their functions were predicted based on the consistency across independent algorithms and observed/expected ratios. Lastly, five pathway databases were included to characterize the enriched pathways of target genes through bootstrap approaches. Based on the enriched pathways of target genes, the functions of queried miRNAs could be predicted.

Conclusions

MiRSystem is a user-friendly tool for predicting the target genes and their associated pathways for many miRNAs simultaneously. The web server and the documentation are freely available at http://mirsystem.cgm.ntu.edu.tw/.     

miRNA靶基因的筛选方法及其相关网络资源

微小RNA（microRNA,miRNA）是一类广泛存在于动植物中,大小约22 nt的单链非编码小分子RNA.它通过与靶mRNA 3′末端非翻译区（untranslational region, UTR）结合,使mRNA降解或翻译抑制.大量的研究结果表明,miRNA在动植物的生长发育、细胞分化、细胞增殖与凋亡、肿瘤发生等诸多环节发挥着重要的调节作用.目前,miRNA靶基因的筛选方法主要有生物信息学筛选和实验方法两大类,且在互联网上拥有大量相关的网络共享资源.本文通过对现有miRNA靶基因的筛选方法及其相关网络资源进行整理与比较分析,以有效指导并辅助miRNA领域的研究.     

Profiling microRNA expression with microarrays

The discovery of several types of small RNAs (sRNAs) has led to a steady increase in available RNA databases. Many of these sRNAs remain to be validated and functionally characterized. Recent advances in microRNA (miRNA)-expression profiling of different tissues, stages of development and physiological or pathological states are beginning to be explored using several technological approaches. In this review, these recent advances in miRNA microarray technology and their applications, particularly in basic research and clinical diagnosis, will be summarized and discussed. The methods for miRNA enrichment and probe design and labeling will also be discussed with an emphasis on evaluation of predicted miRNA sequences, analysis of miRNA expression and exploration of the potential roles of miRNA sequences in the regulation of stem cell differentiation and tissue- and time-specific profiling patterns of their target genes.     

miRNApath: a database of miRNAs, target genes and metabolic pathways

MicroRNAs (miRNAs) are small non-coding RNAs that regulate target gene expression and hence play important roles in metabolic pathways. Recent studies have evidenced the interrelation of miRNAs with cell proliferation, differentiation, development, and diseases. Since they are involved in gene regulation, they are intrinsically related to metabolic pathways. This leads to questions that are particularly interesting for investigating medical and laboratorial applications. We developed an miRNApath online database that uses miRNA target genes to link miRNAs to metabolic pathways. Currently, databases about miRNA target genes (DIANA miRGen), genomic maps (miRNAMap) and sequences (miRBase) do not provide such correlations. Additionally, miRNApath offers five search services and a download area. For each search, there is a specific type of input, which can be a list of target genes, miRNAs, or metabolic pathways, which results in different views, depending upon the input data, concerning relationships between the target genes, miRNAs and metabolic pathways. There are also internal links that lead to a deeper analysis and cross-links to other databases with more detailed information. miRNApath is being continually updated and is available at http://lgmb.fmrp.usp.br/mirnapath.