Genome-wide fine-mapping of metabolic traits in heterogeneous stock rats

异种大鼠代谢特征的全基因组精细图谱

• 批准号: 8469856
• 负责人: Leah Catherine Solberg Woods
• 金额: $ 34.46万
• 依托单位: MEDICAL COLLEGE OF WISCONSIN
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-01 至 2015-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8469856
• 关键词: Accounting; Address; Affect; Alleles; Animal Model; Animals; Area; Blindness; Body Weight; Body fat; Breeding; Candidate Disease Gene; Cholesterol; Chromosome Mapping; Chromosomes; Complex; Confidence Intervals; Diabetes Mellitus; Disease; Exhibits; Fasting; Genes; Genetic; Genetic Recombination; Genome; Genotype; Glucose; Goals; Grant; Heart Diseases; Human; Human Genome; Inbred Strain; Inbreeding; Insulin; Kidney Failure; Laboratories; Maps; Measurement; Measures; Mentored Research Scientist Development Award; Metabolic; Metabolic Diseases; Methods; Non-Insulin-Dependent Diabetes Mellitus; Pattern; Peptides; Phenotype; Plasma; Play; Population; Prevalence; Prevention; Quantitative Trait Loci; Rattus; Recombinants; Resolution; Resources; Risk Factors; Role; Sequence Analysis; Single Nucleotide Polymorphism; Stroke; Structure; Technology; Testing; Tissues; Triglycerides; Variant; Weight; Work; blood glucose regulation; design; family structure; fasting glucose; follow-up; gene discovery; genetic resource; genome wide association study; genome-wide; glucose tolerance; improved; limb amputation; mRNA Expression; novel; positional cloning; public health relevance; response; trait

DESCRIPTION (provided by applicant): Project Summary: Type 2 diabetes (T2D) affects more than 170 million people worldwide and this number is expected to double by 2025 (91). T2D is a leading cause of kidney failure, blindness and limb amputation and a major risk factor for heart disease and stroke (18). Understanding the genetic mechanisms involved in T2D will help in prevention and treatment of this disease. While many genes have recently been identified in human genome wide association studies (GWAS), these genes explain only a small percentage of the population variance (94), indicating that many more genes have yet to be identified. My laboratory has successfully used a unique genetic resource, heterogeneous stock (HS) rats, to fine- map multiple metabolic traits within a single region on rat chromosome one. The confidence interval of many of these loci was less than 5 Megabases. This resource leverages existing recombinations (the major limitation in positional cloning) in the animals, markedly improving map resolution. We are now poised to accelerate the discovery of loci genome-wide using HS rats. We hypothesize that this resource will be useful for rapidly fine-mapping metabolic traits genome-wide, thereby providing a resource to identify novel genes involved in T2D and other metabolic disorders. To date, our laboratory has phenotyped over 500 HS rats for multiple metabolic phenotypes (glucose and insulin after a glucose challenge, fasting plasma cholesterol and triglyceride levels, body weight and fat pad weight). In Specific Aim 1 of this proposal, we will fine-map these traits genome-wide using HS rats. We plan to phenotype an additional 500 rats and genotype these 1000 animals using the Affymetrix 10K single nucleotide polymorphism array. We will identify fine-mapped loci using single and multiple locus mapping methods. We expect to identify 3-15 loci across the genome for each trait measured and will follow-up at least one of these new loci in the following aim. In Specific Aim 2 of this proposal, we plan to identify a gene or genes involved in diabetes or metabolic disorders within one of the fine-mapped regions identified in Specific Aim 1. We will use both sequencing and expression analyses to narrow candidate genes within this region. Importantly, the multiple alleles found in the HS provide increased power for identifying candidate variants. The goal of the sequencing analysis will be to narrow the candidate variants within this region from several thousand to less than 100. These variants will then serve as a means for prioritizing candidate genes to be tested further using mRNA expression analysis in metabolically relevant tissues. The major impact of this work will be to accelerate discovery of genes involved in T2D and related metabolic disorders to a level that has not previously been possible using conventional mapping methods in animal models.

描述（由申请人提供）： 2型糖尿病（T2 D）影响全球超过1.7亿人，预计到2025年这一数字将翻一番。T2 D是肾衰竭、失明和截肢的主要原因，也是心脏病和中风的主要风险因素（18）。了解T2 D的遗传机制将有助于预防和治疗这种疾病。虽然最近在人类全基因组关联研究（GWAS）中鉴定了许多基因，但这些基因只能解释一小部分群体方差（94），这表明还有更多的基因有待鉴定。我的实验室已经成功地使用了一种独特的遗传资源，异质性股票（HS）大鼠，精细映射多个代谢性状在一个单一的区域在大鼠染色体一。许多位点的置信区间小于5兆碱基。这种资源利用了动物中现有的重组（定位克隆的主要限制），显着提高了地图分辨率。我们现在准备加速使用HS大鼠发现全基因组的位点。我们假设，这一资源将是有用的快速精细映射代谢性状全基因组，从而提供了一个资源，以确定新的基因参与T2 D和其他代谢紊乱。迄今为止，我们的实验室已经对500多只HS大鼠的多种代谢表型（葡萄糖激发后的葡萄糖和胰岛素、空腹血浆胆固醇和甘油三酯水平、体重和脂肪垫重量）进行了表型分析。在本提案的具体目标1中，我们将使用HS大鼠在全基因组范围内对这些性状进行精细定位。我们计划对另外500只大鼠进行表型分析，并使用Affyester 10 K单核苷酸多态性阵列对这1000只动物进行基因分型。我们将使用单个和多个基因座作图方法来确定精细作图的基因座。我们期望为每个测量的性状在基因组中鉴定3-15个基因座，并将在以下目标中跟踪这些新基因座中的至少一个。在该提案的具体目标2中，我们计划在具体目标1中确定的精细映射区域之一内确定与糖尿病或代谢紊乱相关的一个或多个基因。我们将使用测序和表达分析来缩小该区域内的候选基因。重要的是，在HS中发现的多个等位基因为鉴定候选变体提供了增加的能力。测序分析的目标是将该区域内的候选变体从几千个缩小到不到100个。然后，这些变体将作为一种手段，用于优先考虑候选基因，以进一步使用代谢相关组织中的mRNA表达分析进行测试。这项工作的主要影响将是加速发现参与T2 D和相关代谢紊乱的基因，达到以前在动物模型中使用传统作图方法不可能达到的水平。