Transcription Network Controlling Drosophila Development

控制果蝇发育的转录网络

• 批准号: 7111846
• 负责人: Mark D BIGGIN
• 金额: $ 291.56万
• 依托单位: UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-08-01 至 2008-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7111846
• 关键词: DNA binding protein; Drosophilidae; SDS polyacrylamide gel electrophoresis; binding sites; crosslink; embryology; gene expression; genetic regulatory element; genetic transcription; growth /development; laboratory rabbit; microarray technology; molecular biology information system; polymerase chain reaction; transcription factor

DESCRIPTION (provided by applicant): The chief aim of this grant is to establish a strategy to study complete transcription networks in animals. A fundamental challenge in the "post genome era" is to decipher the transcriptional information contained in the extensive cis-acting DNA sequences that direct intricate patterns of gene expression in complex organisms. We argue that these challenges cannot be fully met without a systematic characterization of all the components of the transcription regulatory network. The transcriptional network in the early Drosophila embryo is uniquely suited for such system-wide analyses because it offers powerful molecular and genetic tools, is relatively simple, and contains a known, tractable number of regulators. Using this system, we propose to develop methods and strategies to collect four essential classes of data and to use these data to develop bioinformatic analyses that predict which regulatory sequences transcription factors bind in vivo, the combinatorial code determining how factors interact once bound to promoters, and the patterns of expression driven by particular regulatory sequences. Throughout the project, the data collection methods will be refined and modified in response to our analysis of the data. Our specific aims are to: 1. Develop a strategy to obtain a new, more detailed understanding of the in vitro DNA binding specificities of transcription factors using a modified binding site selection protocol and other methods. 2. Optimize in vivo crosslinking and genomic microarrays to measure binding of endogenous factors to thousands of DNA elements in living embryos. 3. Develop advanced imaging methods to quantitate gene expression patterns in 3D with single cell resolution and use this information to identify transcription factor target genes. 4. Explore a novel transgenic promoter based strategy to test large numbers of predicted functional cis-regulatory sequences and determine the expression patterns they drive to aid future predictions. 5. Use engineering solutions to increase the throughout of Aims 1-4 to enable comprehensive analysis of not only the early Drosophila network, but also larger networks in other animals, including mammals. 6. Develop bioinformatic tools that utilize the data in Aims 1-4 to analyze the transcriptional network, and make the data and algorithms available to the community at large.

描述（由申请人提供）：该基金的主要目的是建立一个研究动物完整转录网络的策略。“后基因组时代”的一个根本挑战是破译包含在广泛的顺式作用DNA序列中的转录信息，这些顺式作用DNA序列指导复杂生物体中复杂的基因表达模式。我们认为，这些挑战不能完全满足没有一个系统的表征的转录调控网络的所有组件。早期果蝇胚胎中的转录网络非常适合进行这种全系统分析，因为它提供了强大的分子和遗传工具，相对简单，并且包含已知的易于处理的调节因子。使用这个系统，我们建议开发的方法和策略，收集四个基本类别的数据，并使用这些数据来开发生物信息学分析，预测哪些调控序列转录因子结合在体内，组合代码确定如何相互作用的因素一旦绑定到启动子，和特定的调控序列驱动的表达模式。 在整个项目中，数据收集方法将根据我们对数据的分析进行改进和修改。我们的具体目标是： 1. 开发一种策略，以获得一个新的，更详细的了解在体外DNA结合特异性的转录因子使用修改的结合位点选择协议和其他方法。 2. 优化体内交联和基因组微阵列，以测量内源性因子与活胚胎中数千种DNA元素的结合。 3. 开发先进的成像方法，以单细胞分辨率在3D中定量基因表达模式，并使用此信息识别转录因子靶基因。 4. 探索一种新的基于转基因启动子的策略，以测试大量预测的功能性顺式调控序列，并确定它们驱动的表达模式，以帮助未来的预测。 5. 使用工程解决方案来增加目标1-4的贯穿性，以便不仅能够全面分析早期果蝇网络，而且能够全面分析其他动物（包括哺乳动物）中的更大网络。 6. 开发生物信息学工具，利用目标1-4中的数据分析转录网络，并将数据和算法提供给整个社区。