發(fā)布時(shí)間：2018-01-16 04:24

  本文關(guān)鍵詞：細(xì)菌sRNA靶標(biāo)數(shù)據(jù)庫(kù)3.0構(gòu)建及其功能注釋研究　出處：《中國(guó)人民解放軍軍事醫(yī)學(xué)科學(xué)院》2016年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 細(xì)菌sRNA 靶標(biāo)mRNA 數(shù)據(jù)庫(kù)

【摘要】：細(xì)菌s RNA是與多種生物學(xué)過(guò)程相關(guān)的重要調(diào)控RNA,例如新陳代謝、群體感應(yīng)(quorum sensing)、生物膜形成、鐵元素調(diào)控和毒力調(diào)節(jié)等。它們主要通過(guò)與靶標(biāo)m RNA或者蛋白質(zhì)結(jié)合發(fā)揮功能,因此,系統(tǒng)收集實(shí)驗(yàn)證實(shí)的細(xì)菌s RNA靶標(biāo),并開(kāi)發(fā)相應(yīng)的數(shù)據(jù)庫(kù)管理分析系統(tǒng),不僅可為深入了解s RNA功能和作用機(jī)制提供幫助,也可為開(kāi)發(fā)細(xì)菌s RNA靶標(biāo)預(yù)測(cè)模型提供支持。目前與細(xì)菌s RNA相關(guān)的數(shù)據(jù)庫(kù)主要有s RNAMap、s RNAdb、Rfam、Regulon DB、NPInter、BSRD和s RNATar Base,這些數(shù)據(jù)庫(kù)在數(shù)據(jù)收集與數(shù)據(jù)注釋方面各有側(cè)重。例如s RNAMap是一個(gè)革蘭氏陰性細(xì)菌s RNA數(shù)據(jù)庫(kù),包含了來(lái)自70個(gè)微生物基因組的397個(gè)s RNA、62個(gè)s RNA轉(zhuǎn)錄因子和60個(gè)s RNA靶標(biāo)。此外數(shù)據(jù)庫(kù)還提供了s RNA的二級(jí)結(jié)構(gòu)預(yù)測(cè)、s RNA表達(dá)條件和s RNA表達(dá)水平等信息。s RNAdb則是一個(gè)收集革蘭氏陽(yáng)性細(xì)菌s RNA的數(shù)據(jù)庫(kù)平臺(tái),該數(shù)據(jù)庫(kù)包括了558個(gè)革蘭氏陽(yáng)性細(xì)菌基因組和質(zhì)粒、671個(gè)實(shí)驗(yàn)證實(shí)的細(xì)菌s RNA以及9993個(gè)預(yù)測(cè)的細(xì)菌s RNA,并可以對(duì)用戶輸入的s RNA數(shù)據(jù)進(jìn)行分析,尋找其同源s RNA。Rfam數(shù)據(jù)庫(kù)主要收集來(lái)自真核與原核生物的各種nc RNA家族,并提供二級(jí)結(jié)構(gòu)信息,在細(xì)菌s RNA方面,主要收集相關(guān)s RNA序列信息,不涉及s RNA靶標(biāo)。數(shù)據(jù)庫(kù)Regulon DB則是一個(gè)關(guān)于大腸桿菌K-12中轉(zhuǎn)錄調(diào)控網(wǎng)絡(luò)的數(shù)據(jù)庫(kù),其中包括轉(zhuǎn)錄單元(transcription units,TUs)、啟動(dòng)子和轉(zhuǎn)錄調(diào)控子(transcriptional regulators,TRs)等信息。該數(shù)據(jù)庫(kù)收錄了110個(gè)s RNA和227對(duì)s RNA-target相互作用,其中包含53個(gè)靶標(biāo)m RNA結(jié)合位點(diǎn)。NPInter主要收集實(shí)驗(yàn)證實(shí)的非編碼RNA(排除t RNA和r RNA)和其他生物分子(蛋白質(zhì)、RNA和基因組DNA)的相互作用。NPInter v2.0含有201107個(gè)相互作用條目,涉及18個(gè)物種。其中包括32個(gè)細(xì)菌s RNA以及107個(gè)細(xì)菌s RNAtarget相互作用數(shù)據(jù),但沒(méi)有收錄結(jié)合位點(diǎn)信息。BSRD是由Huang等人2013年開(kāi)發(fā)的一個(gè)綜合性的細(xì)菌s RNA數(shù)據(jù)庫(kù),它系統(tǒng)收集了細(xì)菌s RNA信息并整合了大量的注釋信息。BSRD通過(guò)整合其他數(shù)據(jù)庫(kù)信息和手工文獻(xiàn)收集的方法共收集了897個(gè)實(shí)驗(yàn)證實(shí)的細(xì)菌s RNA、8248個(gè)s RNA同系物以及高通量測(cè)序數(shù)據(jù)預(yù)測(cè)得到的507個(gè)候選s RNA。在s RNA靶標(biāo)方面,主要整合了s RNA預(yù)測(cè)靶標(biāo)和s RNATar Base數(shù)據(jù)庫(kù)提供的靶標(biāo)信息。s RNATar Base是我們課題組2010年開(kāi)發(fā)的一個(gè)實(shí)驗(yàn)證實(shí)的細(xì)菌s RNA靶標(biāo)數(shù)據(jù)庫(kù)。該數(shù)據(jù)庫(kù)共收錄數(shù)據(jù)392例,涉及17個(gè)細(xì)菌基因組,包含68個(gè)s RNA和227個(gè)靶標(biāo)(或非靶標(biāo)),特別是還包含了s RNA-m RNA相互作用結(jié)合位點(diǎn)信息。通過(guò)上述分析,可以看到,除了s RNATar Base,目前并沒(méi)有數(shù)據(jù)庫(kù)提供完整的細(xì)菌s RNA靶標(biāo)信息,特別是沒(méi)有s RNA-m RNA相互作用位點(diǎn)信息,不利于s RNA靶標(biāo)m RNA預(yù)測(cè)模型的開(kāi)發(fā)。其次,s RNATar Base數(shù)據(jù)庫(kù)久未更新。為此,本課題擬在s RNATar Base的基礎(chǔ)上構(gòu)建全新的細(xì)菌s RNA靶標(biāo)數(shù)據(jù)庫(kù),并在數(shù)據(jù)庫(kù)的基礎(chǔ)上開(kāi)展功能注釋研究。為構(gòu)建一個(gè)數(shù)據(jù)全面、功能豐富的細(xì)菌s RNA靶標(biāo)數(shù)據(jù)庫(kù),本研究采用三個(gè)策略進(jìn)行數(shù)據(jù)收集工作:(1)根據(jù)NCBI基因組最新注釋信息以及s RNATar Base2.0各條目的對(duì)應(yīng)文獻(xiàn),對(duì)2.0版的392條數(shù)據(jù)進(jìn)行全面校驗(yàn)和系統(tǒng)更新,如s RNA和靶標(biāo)的NCBI識(shí)別編號(hào)鏈接、基因組位置、序列、各種位點(diǎn)坐標(biāo)等信息。(2)采用不同關(guān)鍵詞組合,例如bacterial s RNA target、bacterial small regulatory RNA target等,在Pub Med數(shù)據(jù)庫(kù)中搜索細(xì)菌s RNA靶標(biāo)相關(guān)文獻(xiàn),共得到在2010年1月1日-2015年6月1日之間發(fā)表的3124篇文獻(xiàn)。根據(jù)摘要,從中篩選出120篇包含細(xì)菌s RNA靶標(biāo)數(shù)據(jù)的文獻(xiàn),然后詳細(xì)閱讀這些文獻(xiàn)并提取需要的s RNA-靶標(biāo)信息和實(shí)驗(yàn)證據(jù)。(3)為防止靶標(biāo)數(shù)據(jù)的遺漏,從所有細(xì)菌s RNA靶標(biāo)預(yù)測(cè)工具的文獻(xiàn)中提取s RNA-靶標(biāo)數(shù)據(jù)集,并與數(shù)據(jù)庫(kù)中的數(shù)據(jù)進(jìn)行比對(duì)。最后,截至2015年6月1日,數(shù)據(jù)庫(kù)共包含來(lái)自53個(gè)基因組的771個(gè)s RNA-靶標(biāo)數(shù)據(jù),其中有492個(gè)經(jīng)實(shí)驗(yàn)證實(shí)細(xì)菌s RNA-靶標(biāo)數(shù)據(jù)和279個(gè)無(wú)相互作用數(shù)據(jù)。數(shù)據(jù)庫(kù)中包含752條s RNA-m RNA記錄,和19條s RNA-蛋白質(zhì)記錄。此外,我們搭建了全新的數(shù)據(jù)庫(kù)網(wǎng)站服務(wù)器,為用戶提供更好的服務(wù)。數(shù)據(jù)庫(kù)網(wǎng)站(http://ccb1.bmi.ac.cn/srnatarbase/)主要包括6個(gè)主要功能。(1)通過(guò)常見(jiàn)信息(s RNA信息、靶標(biāo)信息、s RNA-靶標(biāo)相互作用信息和實(shí)驗(yàn)證據(jù))、序列(Blast功能)以及文獻(xiàn)對(duì)數(shù)據(jù)庫(kù)進(jìn)行檢索,同時(shí)還支持多條件組合查詢。(2)RNA二級(jí)結(jié)構(gòu)動(dòng)態(tài)展示。(3)細(xì)菌s RNA-靶標(biāo)相互作用的NCBI序列展示。(4)細(xì)菌s RNA-靶標(biāo)調(diào)控網(wǎng)絡(luò)展示。(5)基于s RNATarget和s Tar Picker靶標(biāo)預(yù)測(cè),并對(duì)得到的預(yù)測(cè)靶標(biāo)進(jìn)行功能富集分析。網(wǎng)站提供DAVID、GOEAST和PANTHER三個(gè)注釋平臺(tái)供用戶選擇。(6)進(jìn)化分析(Phylogenetic analysis),用來(lái)檢測(cè)s RNA-靶標(biāo)相互作用在相近基因組中的保守性。在數(shù)據(jù)庫(kù)中我們發(fā)現(xiàn)一些s RNA擁有多個(gè)靶標(biāo),一些靶標(biāo)被多個(gè)s RNA調(diào)控。為了研究一個(gè)s RNA與一組靶標(biāo)或一個(gè)靶標(biāo)與一組s RNA之間的關(guān)系,我們開(kāi)發(fā)了在線服務(wù)器Cos Tar,一個(gè)用于分析細(xì)菌s RNA靶標(biāo)協(xié)同調(diào)控作用的分析工具。對(duì)于實(shí)驗(yàn)中產(chǎn)生的s RNA(或者基因)集合,例如在不同條件下差異表達(dá)基因集合,Cos Tar可以預(yù)測(cè)可能和它們相互作用的基因(或者s RNA)列表,從而對(duì)進(jìn)一步的實(shí)驗(yàn)提供指導(dǎo)。我們從BSRD數(shù)據(jù)庫(kù)中得到897個(gè)s RNA序列,從NCBI數(shù)據(jù)庫(kù)中下載最新的細(xì)菌基因組序列。然后選取s RNATarge和s Tar Picker兩種預(yù)測(cè)工具對(duì)選取的s RNA進(jìn)行批量預(yù)測(cè),將得到的結(jié)果按照統(tǒng)一的格式存入預(yù)測(cè)靶標(biāo)數(shù)據(jù)庫(kù)中。輸入為一組s RNA時(shí),我們采用統(tǒng)計(jì)學(xué)中的超幾何分布來(lái)計(jì)算每一個(gè)m RNA的P值,依據(jù)P值對(duì)所有靶標(biāo)進(jìn)行排序。其中P值小于給定閾值的m RNA可以作為這一組s RNA的預(yù)測(cè)靶標(biāo)。為方便相關(guān)研究人員的使用,我們還構(gòu)建了在線分析服務(wù)器Cos Tar。綜上所述,本文以細(xì)菌s RNA為中心,開(kāi)展了兩部分的工作:(1)我們成功地構(gòu)建了細(xì)菌s RNA靶標(biāo)數(shù)據(jù)庫(kù)3.0。數(shù)據(jù)庫(kù)共包含來(lái)自213篇文獻(xiàn)的771條記錄,其中實(shí)驗(yàn)證實(shí)的細(xì)菌s RNA-靶標(biāo)數(shù)據(jù)有492個(gè),結(jié)合位點(diǎn)有316個(gè)。與其他細(xì)菌s RNA數(shù)據(jù)庫(kù)(Regulon DB、BSRD、s RNAMap和NPInter等)相比,s RNATar Base3.0不僅提供了最新最全的細(xì)菌s RNA靶標(biāo)數(shù)據(jù),同時(shí)還包含了316個(gè)結(jié)合位點(diǎn)數(shù)據(jù)以及實(shí)驗(yàn)中的突變信息。此外,全新的數(shù)據(jù)庫(kù)網(wǎng)站提供了NCBI序列展示、s RNA調(diào)控網(wǎng)絡(luò)、預(yù)測(cè)靶標(biāo)及其GO注釋和進(jìn)化分析等各項(xiàng)功能,使得s RNATar Base3.0成為一個(gè)功能豐富的細(xì)菌s RNA靶標(biāo)數(shù)據(jù)庫(kù)。(2)我們成功構(gòu)建了一個(gè)用于預(yù)測(cè)細(xì)菌s RNA-靶標(biāo)協(xié)同調(diào)控作用的在線服務(wù)器Cos Tar。Cos Tar提供s RNA-Gene和Gene-s RNA兩個(gè)功能,不僅能預(yù)測(cè)一組s RNA協(xié)同調(diào)控的靶標(biāo)m RNA,還可以預(yù)測(cè)調(diào)控一組靶標(biāo)m RNA的s RNA。該工作的主要特色與創(chuàng)新點(diǎn)有三個(gè)方面:(1)構(gòu)建的細(xì)菌s RNA靶標(biāo)數(shù)據(jù)庫(kù)3.0擁有最為全面的細(xì)菌s RNA靶標(biāo)數(shù)據(jù),可以為相關(guān)研究(例如開(kāi)發(fā)細(xì)菌s RNA靶標(biāo)預(yù)測(cè)模型等)提供全面、準(zhǔn)確的數(shù)據(jù)。(2)構(gòu)建的數(shù)據(jù)庫(kù)網(wǎng)站提供NCBI基因組展示、s RNA調(diào)控網(wǎng)絡(luò)和GO分析等多種工具,可以從各個(gè)角度解讀s RNA靶標(biāo)數(shù)據(jù),能夠?yàn)橄嚓P(guān)研究人員提供幫助。(3)構(gòu)建的Cos Tar在線分析工具是首次從協(xié)同調(diào)控角度分析細(xì)菌s RNA-靶標(biāo)數(shù)據(jù)的工具,可以為相關(guān)人員提供幫助。
[Abstract]:Bacterial s RNA is an important regulator of RNA, associated with a variety of biological processes such as The new supersedes the old. (quorum sensing), quorum sensing, biofilm formation, iron regulation and virulence regulation. They mainly through the function and target of M RNA or protein binding system therefore, collect experiments confirmed that bacterial s RNA target, and the development of the corresponding database management and analysis system, not only can provide help for the function and mechanism of the in-depth understanding of s RNA, also can forecast model to support the development of s RNA. The target bacteria associated with bacterial s RNA database to s RNAMap, s RNAdb, Rfam Regulon, DB, NPInter, BSRD and s RNATar Base. The database in the data collection and data annotation respectively. For example, s RNAMap is a gram-negative bacterium s RNA database, including 397 s RNA from 70 microbial genomes, 62 s transcription factor RNA And 60 s of RNA target. In addition the database also provides a forecast for the two level structure of s RNA, s RNA and s RNA expression of the expression level of.S RNAdb information is a collection of gram positive bacteria s RNA database platform, the database includes 558 gram positive bacterial genomes and plasmids, 671 experiments confirmed bacterial s RNA and 9993 s RNA and prediction of bacteria, can s RNA user input data analysis, find the homologous s RNA.Rfam database is mainly collected from various eukaryotic and prokaryotic NC RNA family, and provides two levels of structure information, the bacterium s RNA, the main collection s RNA sequence information, does not involve the S RNA target. Regulon DB is a database of Escherichia coli K- 12 transcriptional regulatory network database, including transcription units (transcription, units, TUs) promoter and transcription factor (trans Criptional regulators, TRs) and other information. The database is a collection of 110 s RNA and 227 s RNA-target interaction, which contains 53 target m RNA RNA confirmed.NPInter loci encoding with non main collection experiment (t RNA and R RNA excluded) and other biological molecules (proteins, RNA and genomic DNA) each other.NPInter v2.0 contains 201107 interactions involving 18 items, including 32 bacterial species. S RNA and s RNAtarget 107 bacterial interaction data, but without binding site information.BSRD is a comprehensive Huang et al in 2013 the development of bacterial s RNA database system, it collects the information of bacterial s RNA and the integration of a large number of.BSRD through the method of annotation information integration of database information and manual collection of literature collected a total of 897 experiments confirmed that bacteria s RNA, 8248 s RNA homologues and high flux measurement The predicted 507 candidate s RNA. in s RNA on the target sequence data, mainly the integration of s RNA and s RNATar Base forecast target database provides information of.S RNATar Base is the target we confirmed a subject of experimental group in 2010 the development of bacterial s RNA target database. This database collected data of 392 cases, involving 17 bacterial genome contains 68 s RNA and 227 target (or target), especially s RNA-m RNA also contains the binding site of the interaction information. Through the above analysis, we can see that in addition to s RNATar Base, there is no database to provide complete information of the target bacteria s RNA s RNA-m RNA, especially not mutually site information, is not conducive to the development of predictive model of s RNA m RNA target. Secondly, the s RNATar Base database for a long time not updated. Therefore, this paper intends to build a new bacterial s RNA target data based on s RNATar Base. Library, and carry out functional annotation research based on the database. Data for the construction of a comprehensive, feature rich bacterial s RNA target database, this study adopts three strategies for data collection work: (1) according to the latest NCBI genome annotation information and s RNATar Base2.0 to the corresponding literature, a comprehensive update check the system of 392 and 2 version of the data, such as NCBI RNA and s link identification number, target sequence, genomic location, site coordinates and other information. (2) using different combination of keywords, such as bacterial s RNA target, bacterial small regulatory RNA target s RNA, the search target bacteria related literature in Pub Med database in a total of 3124 articles published between January 1, 2010 -2015 June 1st. According to the summary, screened from 120 included bacterial s RNA target data of the literature, then read the text in detail Offer and extract needed s RNA- target information and experimental evidence. (3) to prevent the target missing data extraction, s RNA- target data set from all the bacteria s RNA target prediction tools in the literature, and compared with the data in the database. Finally, as of June 1, 2015, the database contains a total of 771 s RNA- target data from the 53 genomes, including 492 experiments of bacterial s RNA- target data and 279 non interaction data. The database contains 752 records of RNA s RNA-m, and 19 s RNA- protein records. In addition, we build a new database web server, to provide users with better service. The database website (http://ccb1.bmi.ac.cn/srnatarbase/) mainly includes 6 main functions. (1) through the common information (s RNA, s RNA- target target information, interaction information and experimental evidence), the sequence (Blast) and the Offer the retrieval of the database, and also supports multi condition combination query. (2) RNA two level structure dynamic display. (3) NCBI sequences show bacterial s RNA- target interactions. (4) bacterial s RNA- target regulatory network display. (5) s RNATarget and s Tar Picker target prediction based on and on the prediction of target enrichment analysis. The site provides DAVID, GOEAST and PANTHER three annotation platform for users to choose. (6) (Phylogenetic analysis), phylogenetic analysis to detect s RNA- in the genome of the target are similar to conservative. In the database we found some s RNA with multiple targets, some target by multiple s RNA regulation. In order to study the relationship between a s RNA and a group of target or a target and a group of s RNA, we developed an online server Cos Tar, an analysis tool for analysis of synergistic regulation of bacterial s RNA on the target. S RNA in the set (or genes), such as the differences in gene expression under different conditions set, Cos Tar can predict genes and their mutual action (or s RNA) list, so as to provide guidance for further experiment. We are from the BSRD database to the 897 s RNA sequence, Download bacteria the latest genome sequence from NCBI database. Then select s RNATarge and s Tar Picker two prediction tools to predict s RNA batch selection, the results will be in accordance with the unified format stored in the database. The input predicted targets for a group of s RNA, we used hypergeometric distribution statistics to calculate each a m RNA P, according to the P value to sort all targets. The P value of M RNA is less than a given threshold can be used as the predicted targets of a group of s RNA. For the convenience of research staff, we also constructed in Line analysis server Cos Tar. based on s RNA in bacteria as the center, to carry out the work of two parts: (1) we have successfully constructed the bacterial s RNA target database 3.0. database contains 771 records from 213 articles, of which s RNA- bacteria target experiments confirmed the calibration data of 492, binding site 316. And other bacteria s RNA database (Regulon DB, BSRD s, RNAMap and NPInter) compared to s RNATar Base3.0 not only provides a bacterial s RNA target data of the latest, but also includes the combination of 316 mutation site data and information in the experiment. In addition, the new database website the NCBI sequence of s RNA display, regulatory network, the function of GO and its predicted target annotation and phylogenetic analysis, the s RNATar Base3.0 has become a rich function of bacterial s RNA target database. (2) we have successfully constructed for a pre Detection of bacterial s RNA- target synergistic regulation Cos Tar.Cos Tar online server provides s RNA-Gene and Gene-s RNA two, m RNA can not only predict the target of a group of s RNA cooperative regulation, the main characteristics and innovations can also predict a group of M RNA control target s RNA. the work has three aspects: (1) construction of the bacterial s RNA target database 3 has the most bacteria s RNA target data comprehensively, can for related research (such as the development of bacterial s RNA target prediction model) to provide comprehensive and accurate data. (2) the construction of database website NCBI genome display, a variety of tools s RNA control network and GO analysis so, s RNA target data can be interpreted from various angles, to provide help for the related researchers. (3) Cos Tar online analysis tool construction is the first analysis of bacterial s RNA- target data from the collaborative tools for the phase angle control, The personnel are provided with help.

【學(xué)位授予單位】：中國(guó)人民解放軍軍事醫(yī)學(xué)科學(xué)院
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：Q78

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