Physiological Model of Gene Regulation in Drosophila

果蝇基因调控的生理模型

• 批准号: 9203640
• 负责人: John B. Reinitz
• 金额: $ 59.64万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-01-01 至 2019-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9203640
• 关键词: Anterior; Bacteria; Base Sequence; Basic Science; Binding; Biological; Biological Assay; Blastoderm; Cell Count; Cell Differentiation process; Cell Nucleus; Chromatin; Chromatin Loop; Code; Congenital Abnormality; DNA; DNA Sequence; Data; Databases; Disease susceptibility; Distant; Drosophila genus; Drosophila melanogaster; Elements; Embryo; Engineering; Enhancers; Environment; Gene Chips; Gene Expression; Gene Expression Regulation; Genes; Genetic; Genetic Materials; Genetic Polymorphism; Genetic Transcription; Genome; Genomics; Goals; Histones; Human; Insulator Elements; Investigation; Length; Logic; Malignant Neoplasms; Maps; Medical; Methods; Modeling; Nuclear; Nucleic Acid Regulatory Sequences; Nucleotides; Organism; Output; Pathway Analysis; Pattern; Positioning Attribute; Procedures; Proteins; Regulatory Element; Reporting; Resolution; Sepsis; Sequence Homology; Siblings; Skeleton; System; Techniques; Testing; Time; Training; Transcript; Transcriptional Regulation; Transgenes; Work; Yeasts; activating transcription factor; base; cell type; design; egg; experimental study; fly; genetic regulatory protein; insight; novel strategies; physiologic model; promoter; public health relevance; tool; transcription factor

DESCRIPTION (provided by applicant): The goal of this proposal is to discover and interpret the code by which cis-regulatory DNA controls gene expression. Although cis-regulatory logic is reasonably well understood in bacteria and yeast, this is not the case in multicellular organisms. With a very large number of types of differentiated cells, each of which have the same genetic material but express different sets of genes, metazoans such as humans devote large regions of DNA to biologically essential regulatory functions. These regulatory regions are targets of selection and evolutionary change, and noncoding polymorphisms are connected to disease susceptibility. We have developed a new approach to understanding cis-regulatory logic based on understanding the principles that govern which configurations of bound transcription factors activate transcription and which configurations repress it. This approach is implemented in a model trained on quantitative expression data at cellular resolution from blastoderm stage embryos of Drosophila melanogaster, which we use as a naturally grown "gene chip". The model is able to correctly predict expression from DNA not used in the training procedure, including highly diverged sequence from distantly related species. We will interpret the cis-regulatory code by making use of a suite of tools applied to D. melanogaster and its sibling species D. erecta and D. virilis. The consideration of regulatory circuits across species at the resolution proposed represents a profound extension of network analysis. Supporting techniques include targeted chromosomal transformation of Drosophilid embryos, a sequence-based model of transcriptional control having an established predictive capability for a range of problems, whole-locus transgenes engineered at single-nucleotide resolution with recombineering, and methods for designing and testing synthetic enhancers. The forgoing methods will allow us to test proposed principles of cis-regulatory logic as they are developed in the context of naturally occurring and artificial sequences, and in perturbed trans-environments. Our ultimate goal is to predict the expression patterns of whole genes and synthetic enhancers directly from genomic sequence and data on transcription factor expression. These objectives are summarized the following four specific aims. 1) Design, synthesize, and experimentally test completely defined artificial enhancers that express naturally occurring or arbitrarily chosen patterns on the anterior-posterior axis. 2) Construct and experimentally test a model of the embryonic expression of the complete even-skipped locus. 3) Build a quantitative map of maternal gradients and gap gene expression in Drosophila virilis and Drosophila erecta. 4) Construct testable models of the maternal-gap-eve networks in Drosophila virilis and Drosophila erecta.

描述（由申请人提供）：本提案的目标是发现和解释顺式调控DNA控制基因表达的密码。虽然顺式调控逻辑在细菌和酵母中得到了合理的理解，但在多细胞生物中并非如此。由于有大量类型的分化细胞，每种细胞都具有相同的遗传物质，但表达不同的基因组，后生动物（如人类）将大部分DNA区域用于生物学上必要的调节功能。这些调控区域是选择和进化变化的目标，非编码多态性与疾病易感性有关。我们已经开发了一种新的方法来理解顺式调控逻辑的基础上理解的原则，支配的结合转录因子激活transcription的配置和配置represseit.This方法是在一个模型中实现的定量表达数据在细胞分辨率从胚盘阶段的果蝇胚胎，我们使用作为一个自然生长的“基因芯片”。该模型能够正确预测训练过程中未使用的DNA的表达，包括来自远亲物种的高度分歧序列。 我们将利用一套应用于D. melanogaster及其姊妹种D. erecta和D.男子气概考虑跨物种的监管电路的决议提出了网络分析的一个深刻的延伸。支持技术包括果蝇胚胎的靶向染色体转化，基于序列的转录控制模型，具有对一系列问题的既定预测能力，用重组工程以单核苷酸分辨率工程化的全基因座转基因，以及用于设计和测试合成增强子的方法。上述方法将使我们能够测试所提出的顺式调控逻辑的原则，因为它们是在自然发生的和人工序列的背景下，并在扰动的反式环境中开发的。我们的最终目标是直接从基因组序列和转录因子表达数据预测整个基因和合成增强子的表达模式。这些目标概括为以下四个具体目标。1)设计，合成和实验测试完全定义的人工增强子，表达自然发生的或任意选择的模式上的前后轴。2)构建并实验检测完整偶跳位点的胚胎表达模型。3)建立一个定量地图的母系梯度和差距基因表达的果蝇virilis和果蝇直立。4)构建果蝇和直立果蝇的母沟-前夜网络的可测试模型。