Physiological Model of Gene Regulation in Drosophila

果蝇基因调控的生理模型

基本信息

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
项目类别：
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

项目摘要

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并解释顺式调控 DNA 控制基因表达的密码。尽管顺式调控逻辑在细菌和酵母中已被很好地理解，但在多细胞生物中情况并非如此。由于具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，人类等后生动物将大片 DNA 区域用于生物学上必需的调节功能。这些调节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相关。我们开发了一种理解顺式调控逻辑的新方法，其基础是了解控制结合转录因子的哪些配置激活转录以及哪些配置抑制转录的原理。这种方法是在一个模型中实现的，该模型是根据来自黑腹果蝇胚盘阶段胚胎的细胞分辨率的定量表达数据进行训练的，我们将其用作自然生长的“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，包括来自远缘物种的高度差异的序列。我们将通过使用应用于黑腹果蝇及其兄弟物种直立果蝇和绿腹果蝇的一套工具来解释顺式监管代码。在提议的决议中对跨物种调节回路的考虑代表了网络分析的深刻延伸。支持技术包括果蝇胚胎的靶向染色体转化、对一系列问题具有既定预测能力的基于序列的转录控制模型、通过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原理，因为它们是在自然发生和人工序列以及扰动的跨环境中开发的。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器，这些增强器表达前后轴上自然发生的或任意选择的模式。 2) 构建并实验测试完整偶数跳跃基因座的胚胎表达模型。 3）建立果蝇virilis和直立果蝇母体梯度和间隙基因表达的定量图谱。 4) 构建果蝇 virilis 和果蝇直立果蝇母体间隙前夕网络的可测试模型。