Creating Comprehensive Maps of Worm and Fly Transcription Factor Binding Sites

创建蠕虫和苍蝇转录因子结合位点的综合图谱

• 批准号: 8737930
• 负责人: ROBERT H WATERSTON
• 金额: $ 235.87万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-20 至 2017-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8737930
• 关键词: Accounting; Amino Acid Sequence; Animal Model; Animals; Antibodies; Award; Beds; Binding; Binding Sites; Bioinformatics; Biological Testing; Biology; Caenorhabditis elegans; Code; Communities; Data; Data Quality; Data Set; Databases; Development; Disease; Drosophila genus; Drosophila melanogaster; Elements; Foundations; Funding; Gene Expression; Gene Expression Profile; Gene Expression Profiling; Gene Fusion; Gene Targeting; Gene Transfer Techniques; Genes; Genetic Transcription; Genome; Genomics; Grant; Health; Homologous Gene; Human; Instruction; Life Cycle Stages; Link; Maps; Metric; Mus; National Human Genome Research Institute; Nematoda; Organism; Pattern; Peptide Sequence Determination; Phase; Principal Investigator; Process; Production; Property; Publications; RNA Interference; Reading; Regulatory Element; Relative (related person); Research; Science; Site; Staging; Standardization; Study models; Testing; Time; Transcript; Transcription factor genes; United States National Institutes of Health; Validation; Work; base; computerized data processing; enhanced green fluorescent protein; fly; genome sequencing; human disease; improved; in vivo; insight; member; model organisms databases; research study; transcription factor; transcriptome sequencing

DESCRIPTION (provided by applicant): Our project seeks to identify the regulatory elements recognized by the vast majority of transcription factors (TFs) in the fruit fly Drosophila melanogaster and the nematode Caenorhabditis elegans. In the initial modENCODE project, an experimental pipeline was developed and applied to -100 TFs in each organism. In this intervening year, we expect to capture data for another 75-100 factors. The present project builds on the advances made by the groups in the initial phase and also combines the production pipelines to increase efficiency and to realize economies of scale. With these improvements, we will generate data sets for another 400 factors from each organism, which when combined with previous work will represent the bulk of all transcription factors in these key model organisms. For both organisms, the overall strategy tags transcription factor genes by fusion with an enhanced Green Fluorescent Protein (eGFP) sequence through recombineering of large insert clones, and introducing the tagged genes into the genome by transgenesis. ChlP-seq using a high quality anti-GFP antibody is performed on the developmental stage(s) with maximal GFP expression, as guided by available RNA-seq expression data. The aligned sequence reads are analyzed to identify candidate binding sites and likely target genes. We will prioritize TFs with human homologs to maximize the broader utility of the data. We will also perform RNAi of 125 TFs in each organism, followed by RNA-seq, to validate called peaks and their assigned target genes. Finally, we will integrate the information for the different data setsto construct regulatory networks implied by the TF binding site data. We will coordinate with ENCODE projects on human TFs, and our data will provide key in vivo and developmental regulatory information that will be essential to delineate both fundamentally conserved as well as human-specific properties of TFs. RELEVANCE (See instructions): Insights from the study of the model organisms Drosophila and C. elegans provide the basis for broad understanding of fundamental processes of animal biology. Because many of their genes have clear relatives in humans, these studies have also led directly to improved understanding of human diseases and in some cases to therapies. Similarly, creating a comprehensive understanding of transcription factor binding sites and building regulatory networks in these key model organisms will create the foundation for understanding human regulatory networks both in health and disease.

描述(申请人提供)：我们的项目旨在确定果蝇和线虫秀丽线虫中绝大多数转录因子(TF)识别的调控元件。在最初的modENCODE项目中，开发了一条实验管道，并将其应用于每个生物体中的-100个TF。在这中间的一年里，我们预计还会有75-100个因素的数据。本项目建立在各小组在初始阶段取得的进展的基础上，还结合了生产管道，以提高效率和实现规模经济。有了这些改进，我们将从每个生物体中生成另外400个因子的数据集，当与以前的工作相结合时，这些数据集将代表这些关键模式生物体中所有转录因子的大部分。对于这两种生物，总体策略是通过大插入克隆的重组工程与增强的绿色荧光蛋白(EGFP)序列融合来标记转录因子基因，并通过转基因将标记的基因引入基因组。在已有的RNA-seq表达数据的指导下，使用高质量的抗绿色荧光蛋白抗体在具有最高绿色荧光蛋白表达的发育阶段(S)进行ChLP-seq。对比对的序列读数进行分析，以确定候选结合位点和可能的靶基因。我们将优先考虑具有人类同源基因的函数，以最大限度地提高数据的更广泛效用。我们还将在每个生物体中进行125个转录因子的RNAi，然后进行RNA-SEQ，以验证所谓的峰及其分配的目标基因。最后，我们将整合不同数据集的信息，以构建由TF结合位点数据暗示的调控网络。我们将与ENCODE关于人类转录因子的项目进行协调，我们的数据将提供关键的体内和发育调控信息，这些信息对于描述从根本上保守的以及人类特有的转录因子特性至关重要。相关性(见说明)：对模式生物果蝇和线虫的研究提供了广泛理解动物生物学基本过程的基础。由于它们中的许多基因在人类中有明确的亲缘关系，这些研究也直接导致了对人类疾病的理解，在某些情况下还有助于治疗。同样，全面了解转录因子结合位点，并在这些关键模式生物中建立调控网络，将为理解人类在健康和疾病方面的调控网络奠定基础。