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PePPER:一个用于预测原核生物启动子元件和调控子的网络服务器。

PePPER: a webserver for prediction of prokaryote promoter elements and regulons.

机构信息

Department of Molecular Genetics, University of Groningen, Groningen Biomolecular Sciences and Biotechnology Institute, 9747 AG Groningen, The Netherlands.

出版信息

BMC Genomics. 2012 Jul 2;13:299. doi: 10.1186/1471-2164-13-299.

Abstract

BACKGROUND

Accurate prediction of DNA motifs that are targets of RNA polymerases, sigma factors and transcription factors (TFs) in prokaryotes is a difficult mission mainly due to as yet undiscovered features in DNA sequences or structures in promoter regions. Improved prediction and comparison algorithms are currently available for identifying transcription factor binding sites (TFBSs) and their accompanying TFs and regulon members.

RESULTS

We here extend the current databases of TFs, TFBSs and regulons with our knowledge on Lactococcus lactis and developed a webserver for prediction, mining and visualization of prokaryote promoter elements and regulons via a novel concept. This new approach includes an all-in-one method of data mining for TFs, TFBSs, promoters, and regulons for any bacterial genome via a user-friendly webserver. We demonstrate the power of this method by mining WalRK regulons in Lactococci and Streptococci and, vice versa, use L. lactis regulon data (CodY) to mine closely related species.

CONCLUSIONS

The PePPER webserver offers, besides the all-in-one analysis method, a toolbox for mining for regulons, promoters and TFBSs and accommodates a new L. lactis regulon database in addition to already existing regulon data. Identification of putative regulons and full annotation of intergenic regions in any bacterial genome on the basis of existing knowledge on a related organism can now be performed by biologists and it can be done for a wide range of regulons. On the basis of the PePPER output, biologist can design experiments to further verify the existence and extent of the proposed regulons. The PePPER webserver is freely accessible at http://pepper.molgenrug.nl.

摘要

背景

准确预测原核生物中 RNA 聚合酶、σ 因子和转录因子 (TF) 的 DNA 基序是一项艰巨的任务,主要是因为启动子区域中的 DNA 序列或结构中存在尚未发现的特征。目前可提供改进的预测和比较算法,用于识别转录因子结合位点 (TFBS) 及其伴随的 TF 和调控子成员。

结果

我们在这里扩展了当前的 TF、TFBS 和调控子数据库,将我们对乳球菌属的知识纳入其中,并通过一种新的概念开发了一个用于预测、挖掘和可视化原核生物启动子元件和调控子的网络服务器。这种新方法包括一种全合一的方法,用于通过用户友好的网络服务器挖掘任何细菌基因组中的 TF、TFBS、启动子和调控子。我们通过挖掘乳球菌属和链球菌属中的 WalRK 调控子证明了这种方法的强大功能,反之,我们使用乳球菌属调控子数据 (CodY) 挖掘密切相关的物种。

结论

PePPER 网络服务器除了提供全合一的分析方法外,还提供了一个用于挖掘调控子、启动子和 TFBS 的工具箱,并容纳了一个新的乳球菌属调控子数据库,以及现有的调控子数据。现在,生物学家可以基于相关生物体的现有知识,对任何细菌基因组中的假定调控子进行鉴定,并对基因间区域进行完整注释。基于 PePPER 的输出,生物学家可以设计实验来进一步验证拟议调控子的存在和范围。PePPER 网络服务器可在 http://pepper.molgenrug.nl 免费访问。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ef47/3472324/8ca3c5ac5140/1471-2164-13-299-1.jpg

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