Gene expression networks for metabolic syndrome traits in mice

小鼠代谢综合征特征的基因表达网络

• 批准号: 7102232
• 负责人: THOMAS A DRAKE
• 金额: $ 31.32万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-04-15 至 2011-04-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7102232
• 关键词: diabetes mellitus genetics; gene expression; genetic mapping; genetic screening; genetic susceptibility; genetically modified animals; laboratory mouse; metabolic syndrome; microarray technology; quantitative trait loci

DESCRIPTION (provided by applicant): The metabolic syndrome is a major public health problem because of the long-term health problems it causes. This work uses genetic studies with mice to find new genes that are critical for its development. Identifying these genes will help guide studies in humans that will eventually lead to better ways to detect and treat the metabolic syndrome, and so reduce diabetes and heart disease. The overall goal of this proposal is to utilize gene expression data in a novel manner to identify and validate key genes that influence the phenotypic expression of metabolic syndrome related traits in relevant mouse models. The approach is to integrate genomic and gene expression data from F2 intercross populations to identify causative genes and construct gene expression networks that model the important gene to gene and gene to trait relationships that control metabolic syndrome related trait expression. From such causative gene analyses and gene network model construction, the most important genes that are suggested to regulate the expression the metabolic syndrome will be screened for in vivo validation using transgenic or knockout technologies. Genes found to influence metabolic syndrome traits on screening will undergo further validation and characterization. The groundwork for this project has been completed as part of prior work. The model sets for study are completed intercrosses between DBA2/J and C57BL/6J inbred strains (BXD set; n=111) and C3H/HeJ and C57BL6/J inbred strains on an apoE null background (BXH set; n=334). Both intercross populations show significant variation in expression of traits associated with the metabolic syndrome. Genome wide expression microarrays (approximately 23,000 transcripts) from all F2 mice have been completed on liver for both sets, and additionally on adipose tissue, skeletal muscle, and brain in the BXH set. There are 4 basic components to this approach that make up our specific aims. (1) To identify candidate genes underlying QTL for metabolic syndrome related traits; (2) To identify trans-regulated genes whose transcript levels in turn regulate (are "causal" with regard to) clinical trait expression; (3) To identify regulated metabolic pathways and to develop causal gene expression network models for metabolic syndrome traits; and (4) To screen and validate candidate genes that are most strongly suggested to control metabolic syndrome related-trait expression.

描述（由申请人提供）：代谢综合征是一个主要的公共卫生问题，因为它会引起长期的健康问题。这项工作利用小鼠的遗传学研究来寻找对其发育至关重要的新基因。识别这些基因将有助于指导人类研究，最终将找到更好的方法来检测和治疗代谢综合征，从而减少糖尿病和心脏病。该提案的总体目标是以一种新颖的方式利用基因表达数据来识别和验证影响相关小鼠模型中代谢综合征相关性状表型表达的关键基因。该方法是整合来自 F2 杂交群体的基因组和基因表达数据，以识别致病基因并构建基因表达网络，以模拟控制代谢综合征相关性状表达的重要基因与基因以及基因与性状关系。从这些致病基因分析和基因网络模型构建中，将筛选出调节代谢综合征表达的最重要基因，并使用转基因或敲除技术进行体内验证。在筛选中发现影响代谢综合征特征的基因将接受进一步的验证和表征。作为前期工作的一部分，该项目的基础工作已经完成。用于研究的模型组是 DBA2/J 和 C57BL/6J 自交系（BXD 组；n=111）与 apoE 无效背景上的 C3H/HeJ 和 C57BL6/J 近交系（BXH 组；n=334）之间完成的杂交。两个杂交群体在与代谢综合征相关的性状表达方面均表现出显着差异。来自所有 F2 小鼠的全基因组表达微阵列（约 23,000 个转录本）已在两组小鼠的肝脏上完成，另外还在 BXH 组中的脂肪组织、骨骼肌和大脑上完成。这种方法有 4 个基本组成部分，它们构成了我们的具体目标。 (1) 鉴定代谢综合征相关性状QTL的候选基因； (2) 鉴定反式调节基因，其转录水平反过来调节（“因果”）临床性状表达； (3) 识别受调节的代谢途径并开发代谢综合征特征的因果基因表达网络模型； (4)筛选和验证最强烈建议控制代谢综合征相关性状表达的候选基因。