标题: | 建立世界级MicroRNA生物资料库和MicroRNA-基因调控网路分析平台 Establishing World-Class MicroRNA Databases and Pipelines for Deciphering MicroRNA-Gene Networks |
作者: | 黄宪达 Huang Hsien-Da 国立交通大学生物科技学系(所) |
公开日期: | 2012 |
摘要: | 背景与重要性: 微小核醣核酸(microRNA/miRNA)为一段长约由22个核苷酸组成的非编码寡核醣核酸分子,主要功能为抑制蛋白质转译或降解mRNA来降低基因表现量。近年高通量实验技术的发展,除了技术较成熟的Microarray之外,新世代定序(Next generation Sequencing: NGS)的发展也使miRNA相关研究变的更为发达,促使更多的生物机制和调控模式被阐明。因此,发展miRNA知识库、系统化分析miRNA的NGS资料、重建及分析miRNA调控网路极为重要。 研究目的与研究方法: 本研究运用资料探勘方法,结合生物资讯计算统计分析及高通量实验与分析技术。首先,建立miRNA知识库,接下来系统化分析miRNA的NGS资料,重建miRNA调控网路包括miRNA的转录调控、miRNA-RNA结合蛋白的控制以及miRNA最终扮演的基因down-regulation功能。本研究所提出的研究目标,摘要如下: (1)建立miRNA知识库: 整合所有miRNA研究中重要的研究资源,以建立一个全新全面的miRNA知识库,不但帮助我们后续的研究,同时也提供重要资源给科学家使用。 (2)miRTarBase的扩充: 目前此资料库已经是研究miRNA-target中最完整的资料库,我们不断的在更新资料,并且计画新增次世代定序技术资料,以维持其领先的地位。 (3)建立同源miRNA标的基因资料库: 先前研究已经有许多证据显示miRNA标的基因的位置是具高度保留性,利用已验证的miRNA标的基因资料(from miRTarBase)来将所有同源基因的miRNA标的基因位置做分析,建立同源miRNA标的基因资料库。预测标靶基因方法是利用机器学习来选择与寻找序列特征的方法,对已验证的miRNA标的基因资料集(from miRTarBase)做分析,找出降低伪阳性预测的条件,提高预测的准确度。 (4)系统化分析新世代定序技术的miRNA与miRNA标的基因资料: 建立系统化分析平台,输入资料为新世代定序技术之miRNA或miRNA标的基因序列,迅速的分析得到序列资讯、表现量及功能性预测分析。 (5)miRNA-RNA结合蛋白的分析: 目前已发现有多种miRNA-RNA结合蛋白调控模组,建立这些调控模组的调控关系来分析其它RNA结合蛋白,以找出更多的miRNA-RNA结合蛋白。 (6)重建miRNA 调控网路: 经由特定的基因表现资料或蛋白质表现资料与miRNA表现资料作功能性分析,建立miRNA直接调控与间接调控基因的调控网路图谱。 预期研究成果: 本研究发展的重要资料库,Web服务器或分析工具等资源,预计会广泛的被研究人员所使用。另外我们也持续的与生物实验学者合作,利用生物资讯分析结合实验验证资料,也可以迅速的阐明许多miRNA在生物体中所扮演的调控角色。 Backgrounds and Significance: miRNAs/microRNAs are 22-nucleotides-length non-coding RNA molecules. The main function of miRNAs is to reduce gene expression via degrading RNA molecules or suppressing protein translation. Recently, high-throughput techniques have been utilized in miRNA studies. Except the well-developed techniques such as microarray, the next generation sequencing technology also has been used to accelerate the miRNA study and to assist to reveal more bio-regulatory mechanisms. Therefore, it is necessary to develop a systematic pipeline to analyze next generation sequencing data. The Aims and Methods: This study is based on data mining approach, bioinformatics computing, statistical analysis and high-throughput experiment and analysis to develop a novel resource for cluing unknown regulatory mechanisms. First, the miRNA knowledge base will be constructed and then the next generation sequencing data will be systematically analyzed. Finally, the miRNA regulatory network including the control of translational regulator of miRNA, miRNA-RNA binding protein, and the function of miRNA down-regulation will be reconstructed. Our research goals are summarized below: (1)miRNA Repository: All of the well-known miRNA resource will be integrated to reconstruct a novel and comprehensive miRNA repository. (2)miRTarBase extension and expansion: This database is frequently updated and have become a leading resource in experiment validate of miRNA-target interactions. We aim to integrate the NGS data such as CLIP-Seq to keep the database as a leading status. (3)Homologous miRNA-target interaction database: In previous studies, it has been showed that the miRNA target sites are well-conserved in homologous genes. After reconstructing the miRNA knowledge bases, the miRNA target sites in homologous genes will be analyzed to confirm whether the target sites are conserved in different species. All conserved miRNA target sites will be collected to establish the homologous miRNA-target interaction database. miRNA-target sequence feature extract from comprehensive miRNA-target dataset in miRTarBase, feature select via machine learning approach to reduce false-positive prediction and raise prediction accuracy. (4)Systematic analysis of miRNAs and miRNA-target interaction using NGS technology: A systematic pipeline will be established to analyze next generation sequencing data concisely and to obtain information. Furthermore, the functional annotation and prediction will be included in this system. (5)Identify the mechanism of miRNA-RNA-binding protein: The several types of miRNA-RNA binding protein regulation modules were discovered. The analysis will be applied to identify the regulation model of undiscovered miRNA-RNA binding protein to discover novel miRNA-RNA binding protein. (6)Reconstructing miRNA regulatory networks: Analysis specific gene expression or protein expression data combines miRNA expression profile. The direct and indirect miRNA-target gene could be reconstructed a significant miRNA regulatory network. The Anticipated Results and Scientific Impacts: In this study, we will develop several important database, web server, or stand-alone package to furnish a highly usage resource for miRNA researchers. We also cooperate with our collaborators to combine bioinformatics analysis and experimental data to verify the role of miRNA regulation or discover the novel regulatory mechanisms in organisms. |
官方说明文件#: | NSC101-2311-B009-005-MY3 |
URI: | http://hdl.handle.net/11536/98799 https://www.grb.gov.tw/search/planDetail?id=2645549&docId=399104 |
显示于类别: | Research Plans |