Quantitative Genetic Analysis of Signal Transduction

信号转导的定量遗传分析

• 批准号: 7025823
• 负责人: GREGORY C GIBSON
• 金额: $ 21.23万
• 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/7025823
• 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）：这是一项应用系统生物学方法来评价信号转导过程中的定量变化如何影响模式生物果蝇胚胎发生和翅膀图案形成过程中的图案形成的建议。我们将精确地量化1000个基因的基因表达谱参与受体介导的信号在210个野生型品系和25个突变体背景的翅膀发育过程中，并关联SNP启动子多态性在25个关键基因的转录丰度和表型变异。三个水平（基因型、基因表达和表型）的协方差模式与连接组分的生化网络的知识相结合，将用于生成预测模型，预测单个组分的变化如何被其他组分缓冲或引导发展进入特定轨迹。然后将引入遗传和环境扰动来测试特定的预测，并在复杂的相互作用网络中区分因果关系和相关性。这一提议的生物医学意义首先在于产生了一个丰富的数据集，连接了果蝇发育中大多数已知的调控成分（该数据集将类似于目前计划用于各种复杂疾病研究的数据集）;第二，在评估基因组规模的关联性时，开发处理所谓“多维灾难”的统计方法;第三，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效应的分离转移到识别在复杂调控系统中产生稳态的调控控制点。