Annotating the Cis-Regulatory Binding Sites in Sequenced Prokaryotic Genomes

“该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。位于夏洛特的北卡罗来纳州大学获得了一笔赠款，用于开发软件和数据库资源，以表征测序细菌中的顺式调节结合位点。细菌细胞的生物学功能是由细胞内基因产物（蛋白质和RNA）来实现的，但在不同的生理和环境条件下，这些蛋白质和RNA的表达时间、地点、表达量和表达速度主要由特定的转录因子蛋白与染色体上基因上游区域的顺式调控结合位点之间的相互作用来控制。更好地了解原核生物在全球生态控制，高效农业，更好的医药和健康以及可再生能源生产方面具有重要意义。然而，我们对大多数测序的细菌基因组中顺式调控系统的一般理解是非常有限的，这是由于缺乏有效和准确的实验和计算方法来表征它们。本项目的研究团队将开发：1）一种更准确预测细菌操纵子的新工具，因为操纵子是细菌的基本转录单位，了解基因组中操纵子的结构可以促进其顺式调控结合位点的预测。2)一个高效、准确的全基因组顺式调控结合位点预测工具。3）一个数据库系统，用于存储所有测序的细菌基因组中预测的操纵子和顺式调控结合位点。此外，这些预测工具的结果将得到验证，并进一步完善通过实验验证的大部分预测的新的顺式调控位点在大肠杆菌。coli K12。这些软件、数据库和实验程序将免费向公众开放，因此研究人员可以1）直接将软件应用于他们感兴趣的基因组; 2）在表征某些基因组中的顺式调控系统时，使用数据库进行靶标选择、实验设计和假设检验; 3）利用实验方法验证预测的顺式调控结合位点，同时鉴定同源转录因子。因此，这些工具和数据库将从根本上改变生物学家研究细菌顺式调控系统的方式。该项目还将提供一个独特的教育平台，以培养下一代计算生物学家，因为一名博士后研究员，三名博士毕业生，以及各种数量的本科生和高中生将在该项目中接受培训。将特别鼓励传统上代表性不足的少数民族学生和/或女生参加该项目。此外，该项目产生的算法和结果将纳入主要研究者？位于夏洛特的北卡罗来纳州大学新开发的课程。有关该项目的更多信息可以在http://gleclubs.uncc.edu/pbs上找到，有关研究团队的信息可以在http://sulab.uncc.edu上找到。

"This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5)."University of North Carolina at Charlotte has been awarded a grant to develop software and a database resource for characterizing cis-regulatory binding sites in sequenced bacteria. Biological functions of a bacterial cell are carried out by the products of genes (proteins and RNAs) in the cell, but when, where, how much and how fast these proteins and RNAs should be expressed under different physiological and environmental conditions are mainly controlled by the interactions between specific transcription factor proteins and the cis-regulatory binding sites in the upstream regions of the genes on the chromosome. A better understanding of prokaryotes in general has great significance in global ecological control, efficient agriculture, better medicine and health, and renewable energy production. However, our general understanding of cis-regulatory systems in most sequenced bacterial genomes is very limited due to the lack of efficient and accurate experimental and computational methods for their characterization. The research team of this project will develop: 1) A new tool for more accurate prediction of operons in bacteria, since operons are the basic transcription units in bacteria and knowing operon structures in a genome can facilitate its cis-regulatory binding site prediction. 2) An efficient and accurate tool for genome-wide prediction of cis-regulatory binding sites in bacteria.3) A database system to store the predicted operons and cis-regulatory binding sites in all sequenced bacteria genomes. In addition, the results of these prediction tools will be verified and further refined through experimental validation of a large portion of the predicted novel cis-regulatory sites in E. coli K12. These software, database and experimental procedures will be freely available to the public, thus researchers can 1) directly apply the software to their genomes of interest; 2) use the database for target selection, experimental design and testing hypotheses when characterizing cis-regulatory systems in certain genomes; and 3) use the experimental procedures to verify the predicted cis-regulatory binding sites, and at the same time, identify the cognate transcription factors. Therefore, these tools and database will fundamentally change the way that biologists study cis-regulatory systems in bacteria. This project will also provide a unique educational platform to train the next generation of computational biologists, as one postdoctoral fellow, three PhD graduates, and various numbers of undergraduates and high school students will be trained in the project. Traditionally underrepresented minority and/or female students will be particularly encouraged to participate in the project. Furthermore, the algorithms and results generated from this project will be incorporated into the principle investigator?s newly developed courses at the University of North Carolina at Charlotte. More information about the project can be found at http://gleclubs.uncc.edu/pbs and information about the research team can be found at http://sulab.uncc.edu.