建立世界級MicroRNA生物資料庫和MicroRNA-基因調控網路分析平台

Abstract

背景與重要性: 微小核醣核酸(microRNA/miRNA)為一段長約由22個核苷酸組成的非編碼寡核醣核酸分子，主要功能為抑制蛋白質轉譯或降解mRNA來降低基因表現量。近年高通量實驗技術的發展，除了技術較成熟的Microarray之外，新世代定序(Next generation Sequencing: NGS)的發展也使miRNA相關研究變的更為發達，促使更多的生物機制和調控模式被闡明。因此，發展miRNA知識庫、系統化分析miRNA的NGS資料、重建及分析miRNA調控網路極為重要。 研究目的與研究方法: 本研究運用資料探勘方法，結合生物資訊計算統計分析及高通量實驗與分析技術。首先，建立miRNA知識庫，接下來系統化分析miRNA的NGS資料，重建miRNA調控網路包括miRNA的轉錄調控、miRNA-RNA結合蛋白的控制以及miRNA最終扮演的基因down-regulation功能。本研究所提出的研究目標，摘要如下： (1)建立miRNA知識庫: 整合所有miRNA研究中重要的研究資源，以建立一個全新全面的miRNA知識庫，不但幫助我們後續的研究，同時也提供重要資源給科學家使用。 (2)miRTarBase的擴充: 目前此資料庫已經是研究miRNA-target中最完整的資料庫，我們不斷的在更新資料，並且計畫新增次世代定序技術資料，以維持其領先的地位。 (3)建立同源miRNA標的基因資料庫: 先前研究已經有許多證據顯示miRNA標的基因的位置是具高度保留性，利用已驗證的miRNA標的基因資料(from miRTarBase)來將所有同源基因的miRNA標的基因位置做分析，建立同源miRNA標的基因資料庫。預測標靶基因方法是利用機器學習來選擇與尋找序列特徵的方法，對已驗證的miRNA標的基因資料集(from miRTarBase)做分析，找出降低偽陽性預測的條件，提高預測的準確度。 (4)系統化分析新世代定序技術的miRNA與miRNA標的基因資料: 建立系統化分析平台，輸入資料為新世代定序技術之miRNA或miRNA標的基因序列，迅速的分析得到序列資訊、表現量及功能性預測分析。 (5)miRNA-RNA結合蛋白的分析: 目前已發現有多種miRNA-RNA結合蛋白調控模組，建立這些調控模組的調控關係來分析其它RNA結合蛋白，以找出更多的miRNA-RNA結合蛋白。 (6)重建miRNA 調控網路: 經由特定的基因表現資料或蛋白質表現資料與miRNA表現資料作功能性分析，建立miRNA直接調控與間接調控基因的調控網路圖譜。 預期研究成果: 本研究發展的重要資料庫，Web服務器或分析工具等資源，預計會廣泛的被研究人員所使用。另外我們也持續的與生物實驗學者合作，利用生物資訊分析結合實驗驗證資料，也可以迅速的闡明許多miRNA在生物體中所扮演的調控角色。

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.