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: 9119534
• 负责人: ROBERT H WATERSTON
• 金额: $ 238.2万
• 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 2018-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9119534
• 关键词: Accounting; Amino Acid Sequence; Animal Model; Animals; Antibodies; Award; Bacterial Artificial Chromosomes; 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 Profiling; Gene Fusion; Gene Targeting; Gene Transfer Techniques; Genes; Genetic Transcription; Genome; Genomics; Grant; Health; Homologous Gene; Human; Instruction; Life Cycle Stages; Link; Maps; Mus; National Human Genome Research Institute; Nematoda; Organism; Pattern; Peptide Sequence Determination; Phase; Principal Investigator; Process; Production; Property; Publications; RNA Interference; Reading; Regulatory Element; Research; Science; Site; Staging; Standardization; Study models; Testing; Time; Transcript; 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; knock-down; member; model organisms databases; research study; transcription factor; transcriptome; 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（由申请人提供）：我们的项目旨在确定果蝇果蝇和线虫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，开发了一个实验管道，并将其应用于每种生物的-100个TFs。在这中间的一年里，我们预计将获得另外75-100个因素的数据。目前的项目建立在小组在初始阶段取得的进展的基础上，并结合了生产管道以提高效率并实现规模经济。有了这些改进，我们将从每个生物中生成另外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，总体策略是通过重组大插入克隆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。ChlP-seq使用高质量的抗GFP抗体，在GFP表达最高的发育阶段进行，并根据可用的RNA-seq表达数据进行指导。对序列进行分析，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物的tf，以最大限度地扩大数据的效用。我们还将在每个生物体中对125个tf进行RNAi，然后进行RNA-seq，以验证称为峰及其指定的靶基因。最后，我们将整合不同数据集的信息，构建由TF结合位点数据隐含的调控网络。我们将与ENCODE项目合作研究人类tf，我们的数据将提供关键的体内和发育调控信息，这些信息将对描述tf的基本保守性和人类特异性特性至关重要。相关性（见说明）：从模式生物果蝇和秀丽隐杆线虫的研究中获得的见解为广泛理解动物生物学的基本过程提供了基础。由于它们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的提高，在某些情况下还导致了治疗方法的提高。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构建调控网络，将为理解人类健康和疾病的调控网络奠定基础。