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）：该提案的目的是发现和解释顺式调节DNA控制基因表达的代码。尽管在细菌和酵母中对顺式调节逻辑众所周知，在多细胞生物中并非如此。具有大量类型的分化细胞，每种细胞具有相同的遗传物质，但表达了不同的基因，类似人类（例如人类）将大量DNA区域用于生物学上必不可少的调节功能。这些调节区域是选择和进化变化的靶标，非编码多态性与疾病的敏感性有关。我们已经开发了一种新的方法来理解顺式调节逻辑，该逻辑基于理解控制哪种结合转录因子的原理激活转录以及哪些配置抑制它。这种方法是在果蝇果蝇胚胎阶段胚胎的细胞分辨率下对定量表达数据进行训练的模型中实现的，我们用作天然生长的“基因芯片”。该模型能够正确预测训练程序中未使用的DNA的表达，包括来自远距离相关物种的高度分歧的序列。我们将使用应用于D. Melanogaster及其兄弟姐妹的D. erecta和D. virilis的一套工具来解释顺式调节法规。在提出的决议中，对跨物种的监管回路的考虑代表了网络分析的深刻扩展。支撑技术包括果蝇胚胎的靶向染色体转化，果蝇胚胎是一种基于序列的转录控制模型，具有针对一系列问题的确定预测能力，在重新混合使用的单核苷酸分辨率以及用于设计和测试合成增强剂的方法的全核转基因。前进的方法将使我们能够在自然发生和人工序列以及扰动的反环境中开发的顺式调节逻辑原理。我们的最终目标是直接从基因组序列以及转录因子表达数据的数据直接预测整个基因和合成增强子的表达模式。这些目标总结了以下四个特定目标。 1）设计，合成和实验测试完全定义的人工增强剂，这些增强剂表达在前后轴上自然存在或任意选择的模式。 2）构造和实验测试完整偶数座基因座的胚胎表达模型。 3）在果蝇病毒和果蝇勃起中构建孕产妇梯度和间隙基因表达的定量图。 4）在果蝇和果蝇勃起中构建母体间隙 - eve网络的可测试模型。