Effects of mutations on gene expression noise and cellular memory

突变对基因表达噪音和细胞记忆的影响

• 批准号: 7276243
• 负责人: Scott Rifkin
• 金额: $ 4.96万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-05-01 至 2010-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7276243
• 关键词: Alleles; Biochemical; Biochemical Reaction; Biological Models; Buffers; Cell physiology; Cells; Complex; Computer Architectures; Condition; Disease; Equilibrium; Evolution; Exhibits; Face; Feedback; Fellowship; Galactose; Gene Expression; Genes; Genetic; Genetic Transcription; Genome; Lead; Link; Malignant Neoplasms; Measures; Memory; Modeling; Molds; Molecular; Molecular Probes; Monitor; Mutation; National Research Service Awards; Natural Selections; Noise; Numbers; Paper; Phenotype; Play; Population Growth; Process; Production; Proteins; Rate; Role; Saccharomyces cerevisiae; System; TATA Box; Testing; Transcriptional Activation; Translations; Variant; Yeasts; in vivo; mutant; promoter; simulation; theories; trait; transcription factor

DESCRIPTION (provided by applicant): Noise is an inescapable feature of genetic networks, causing variation among genetically identical cells even under identical environmental conditions. Because expression is a multistep process involving many biochemical reactions, many recent studies have conjectured that natural selection can tune levels of noise to avoid fluctuations which could impair cellular function. One important parameter in tests for selection is the rate at which new variation in a trait is generated by mutation. This proposal aims to (1) estimate the rate at which noise and its effects on network activity evolve solely due to mutation, using the well-studied galactose network of Saccharomyces cerevisiae as a model system, (2) measure how robust the key positive feedback loop of this network is to regulatory mutations, and (3) use theory and simulation to analyze the evolution of a basic regulatory network under mutation and selection. Aims (1) and (2) will be pursued through in vivo monitoring of gene and network activity in cells exposed to varying levels of galactose carrying mutations randomly throughout the genome (1), or targeted to a particular network component (2). Mutant alleles play an important role in congenital diseases, and the accumulation of mutations is one of the features of cellular progression to cancer. In both of these cases, mutant alleles probably disrupt normal genetic network functioning, and so it is important to understand how genetic networks buffer the effects of mutations and how easily network function can be compromised.

描述(申请人提供)：噪声是遗传网络的一个不可避免的特征，即使在相同的环境条件下，也会导致遗传相同的细胞之间的差异。由于表达是一个涉及许多生化反应的多步骤过程，最近的许多研究推测，自然选择可以调节噪音水平，以避免可能损害细胞功能的波动。选择测试中的一个重要参数是突变产生性状新变异的速度。这个建议的目的是(1)以酿酒酵母半乳糖网络为模型系统，估计噪声及其对网络活动的影响单独由于突变而进化的速度；(2)测量该网络的关键正反馈环路对调控突变的健壮性；(3)使用理论和模拟来分析基本调控网络在突变和选择下的进化。目标(1)和(2)将通过体内监测暴露于整个基因组(1)中随机或针对特定网络组件(2)的不同水平携带半乳糖突变的细胞中的基因和网络活动来实现。突变等位基因在先天性疾病中起着重要作用，突变的积累是细胞向癌症进展的特征之一。在这两种情况下，突变的等位基因可能会扰乱正常的遗传网络功能，因此了解遗传网络如何缓冲突变的影响以及网络功能如何容易受到损害是很重要的。