Quantitative Genetic Analysis of Signal Transduction

信号转导的定量遗传分析

• 批准号: 6924864
• 负责人: GREGORY C GIBSON
• 金额: $ 21.9万
• 依托单位: NORTH CAROLINA STATE UNIVERSITY RALEIGH
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-08-01 至 2009-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6924864
• 关键词: Drosophilidae; animal population genetics; arthropod genetics; biological signal transduction; developmental genetics; embryogenesis; gene expression profiling; gene mutation; genetic regulation; genetic transcription; genotype; imaginal disc; in situ hybridization; invertebrate embryology; method development; microarray technology; molecular biology information system; morphometry; oligonucleotides; phenotype; single nucleotide polymorphism; statistics /biometry; transposon /insertion element

DESCRIPTION (provided by applicant): This is a proposal to apply systems biology approaches to evaluate how quantitative variation during signal transduction affects patterning during embryogenesis and wing patterning in the model organism, Drosophila. We will precisely quantify gene expression profiles for 1000 genes involved in receptor-mediated signaling during wing development in 210 wild-type lines and 25 mutant backgrounds, and associate SNP promoter polymorphism in 25 key genes with both transcript abundance and phenotypic variation. The patterns of covariance at the three levels (genotype, gene expression, and phenotype) in combination with knowledge of the biochemical networks connecting the components will be used to generate predictive models of how variation in individual components is either buffered by the other components or directs development into a particular trajectory. Genetic and environmental perturbations will then be introduced to test specific predictions, and to differentiate causality from correlation in the complex network of interactions. The biomedical significance of this proposal lies first in the generation of a rich data set connecting most of the known regulatory components in Drosophila development (this data set will be similar to data sets now planned for a wide variety of complex disease studies); second in the development of statistical methods for dealing with the so-called "curse of multidimensionality" in evaluating associations at the genome scale; and third in utilizing a manipulable genetic system to actually evaluate the functional significance of specific interactions. This research shifts the emphasis in molecular quantitative genetic analysis from isolation of individual SNP effects to identification of the regulatory control points that produce homeostasis in complex regulatory systems.

描述（由申请人提供）：这是应用系统生物学方法来评估信号转导过程中的定量变化如何影响模型有机体果蝇中胚胎发生和机翼模式期间图案的建议。我们将精确量化210条野生型线和25个突变背景的机翼发育过程中参与受体介导的信号传导的1000个基因的基因表达谱，并在25个具有转录物丰度和表型变异的25个关键基因中的SNP启动子多态性相关。结合连接组件的生化网络的知识结合了三个级别（基因型，基因表达和表型）的协方差模式将用于生成有关单个组件中如何通过其他组件进行缓冲的预测模型，要么将其引导到特定的轨迹中。然后将引入遗传和环境扰动，以测试特定的预测，并区分因果关系与复杂相互作用网络中的相关性。该提案的生物医学意义首先在于生成丰富的数据集，该数据集连接了果蝇开发中大多数已知的调节组件（该数据集将类似于现在计划用于多种复杂疾病研究的数据集）；在开发统计方法的开发中，以处理基因组量表评估关联的所谓“多维性诅咒”；第三种利用可操纵的遗传系统来实际评估特定相互作用的功能意义。这项研究将分子定量遗传分析的重点从单个SNP效应的分离转变为鉴定在复杂调节系统中产生稳态的调节控制点。