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

描述(由申请人提供)： 项目摘要：2型糖尿病(T2D)影响全球超过1.7亿人，预计到2025年这一数字将翻一番(91)。T2D是导致肾衰竭、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T2D的遗传机制将有助于该疾病的预防和治疗。虽然最近在人类全基因组关联研究中发现了许多基因，但这些基因只解释了种群变异的一小部分(94)，表明还有更多的基因尚未被识别。我的实验室已经成功地使用了一种独特的遗传资源--异质种(HS)大鼠，在大鼠第一染色体上的单个区域内精细地定位了多个代谢特征。其中许多基因座的可信区间小于5兆碱基。这种资源利用了动物中现有的重组(位置克隆的主要限制)，显著提高了地图分辨率。我们现在准备利用HS大鼠加快全基因组基因座的发现。我们假设这个资源将有助于在全基因组范围内快速精细地定位代谢特征，从而提供一个资源来识别与T2D和其他代谢紊乱相关的新基因。到目前为止，我们的实验室已经对500多只HS大鼠进行了多种代谢表型(葡萄糖挑战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)的表型鉴定。在这项建议的具体目标1中，我们将使用HS大鼠在全基因组范围内精细定位这些特征。我们计划对另外500只大鼠进行表型，并使用Affymetrix 10K单核苷酸多态性阵列对这1000只动物进行基因分型。我们将使用单基因座和多基因座作图方法识别精细定位的基因座。我们希望在基因组中为每个测量的性状确定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。在本提案的特定目标2中，我们计划在特定目标1中确定的精细定位区域中的一个或多个与糖尿病或代谢紊乱有关的基因。我们将使用测序和表达分析来缩小该区域内的候选基因范围。重要的是，在HS中发现的多个等位基因为识别候选变异提供了更大的能力。测序分析的目标将是将该区域内的候选变异从数千个缩小到不到100个。然后，这些变异将作为一种手段，利用新陈代谢相关组织中的mRNA表达分析，对待进一步测试的候选基因进行优先排序。这项工作的主要影响将是加速发现与T2D和相关代谢紊乱有关的基因，达到以前在动物模型中使用传统定位方法所不可能达到的水平。 公共卫生相关性： 项目简介：2型糖尿病是导致肾衰竭、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。随着这种疾病在世界范围内以惊人的速度增长，了解这种疾病的潜在遗传机制是当务之急。这项提案中概述的工作将作为一种手段，识别与2型糖尿病有关的新基因，从而改进人类的治疗和/或更好的预防方法。

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. PUBLIC HEALTH RELEVANCE: Project Narrative: Type 2 diabetes is the leading cause of kidney failure, blindness and limb amputation and a major risk factor for heart disease and stroke. With the prevalence of this disorder increasing at alarming rates worldwide, it is imperative to understand the underlying genetic mechanisms of this disorder. The work outlined in this proposal will serve as a means for identifying novel genes involved in type 2 diabetes, thereby leading to improved treatment and/or better prevention methods in humans.