A resource for the genetic analysis of complex traits

复杂性状遗传分析的资源

• 批准号: 7893982
• 负责人: Stuart John Macdonald
• 金额: $ 52.34万
• 依托单位: UNIVERSITY OF KANSAS LAWRENCE
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-28 至 2011-08-27
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7893982
• 关键词: resource; genetic; analysis; complex; traits

DESCRIPTION (provided by applicant): Complex diseases are controlled by a large number of potentially interacting genetic and environmental factors. Each year millions of Americans are diagnosed with complex diseases such as diabetes, heart disease, Alzheimer's, and various forms of cancer. If the precise genetic loci contributing to variation in disease risk could be characterized, disease incidence might be predicted, and treatments could be modified on a case-by-case basis to halt disease progression and ameliorate suffering (so-called personalized medicine). Unfortunately, progress towards identifying the catalog of genetic risk alleles has been slow, in part because it is unclear what we are searching for: Risk alleles may be common in the population, individually conferring only slight disease risk, or may be rare, but with much larger effects. Our proposal explores a novel approach to characterize genetic loci that combines the strengths of typical QTL (Quantitative Trait Locus) and association mapping, while minimizing some of their weaknesses. A feature of the approach is that it provides a small set of candidate causative sites for each QTL mapped: Previous methodologies have had great difficulty moving from QTL to the precise nucleotides involved. The main aim of the proposal is to develop an integrated framework for the genetic dissection of complex traits in the model organism Drosophila melanogaster. A pair of synthetic laboratory populations will each be initiated with eight inbred founder lines, and following many generations of maintenance a large panel of RILs (Recombinant Inbred Lines) will be derived. The genome of each RIL will be a fine-scale mosaic of segments inherited from the eight founder strains. Following genotyping the panel will serve as a valuable community resource in which to map QTL with high resolution, and we will facilitate these user-directed experiments by creating a web-based analysis portal. The approach yields considerable power to map QTL relative to commonly applied association study methods, and offers the extremely important ability to estimate the frequency of mapped QTL, and in turn the contribution of common alleles to complex trait variation. By resequencing the genomes of the founder strains, for each QTL one can additionally identify the small handful of putatively causative DNA variants to target for future work. We will map QTL for four stress- and drug-tolerance demonstration traits, chosen for their ease of measurement and modest heritability. Each trait will be scored in three mapping designs: directly in homozygous RILs, in the heterozygous progeny of round-robin RIL-RIL crosses, and after crossing RILs to a common inbred reference strain. The two heterozygous testcrosses will examine the effect of inbreeding on QTL mapping directly in RILs. These testcrosses are relatively simple to carry out in flies, and the results may have important implications for the design of experiments using the mouse "Collaborative Cross" eight-way RILs, a system in which the testcrosses would be considerably more cumbersome and expensive to perform.

描述(由申请人提供)：复杂的疾病由大量潜在的相互作用的遗传和环境因素控制。每年，数以百万计的美国人被诊断出患有糖尿病、心脏病、阿尔茨海默氏症和各种形式的癌症等复杂疾病。如果可以确定导致疾病风险变化的精确遗传基因，就可以预测疾病发病率，并在个案的基础上修改治疗方法，以阻止疾病进展和减轻痛苦(所谓的个性化药物)。不幸的是，在确定遗传风险等位基因目录方面进展缓慢，部分原因是我们不清楚我们在寻找什么：风险等位基因可能在人群中很常见，个别只会带来轻微的疾病风险，或者可能很罕见，但影响要大得多。我们的建议探索了一种新的方法来表征遗传基因座，该方法结合了典型QTL(数量性状基因座)和关联图谱的优点，同时最小化了它们的一些缺点。这种方法的一个特点是，它为每个定位的QTL提供了一小组候选致病位点：以前的方法很难从QTL转移到所涉及的精确核苷酸。 该提案的主要目的是为模式生物黑腹果蝇复杂性状的遗传解剖开发一个完整的框架。一对合成实验室群体将分别由8个近交创始人系启动，经过多代维护，将产生大量重组自交系(RIL)。每个RIL的基因组都将是从八个创始菌株遗传的细小片段的马赛克。在基因分型之后，该小组将作为一个有价值的社区资源，在其中以高分辨率绘制QTL图，我们将通过创建基于网络的分析门户网站来促进这些用户指导的实验。与常用的关联研究方法相比，该方法提供了相当大的QTL作图能力，并提供了极其重要的能力来估计所定位的QTL的频率，进而估计共同等位基因对复杂性状变异的贡献。通过对创始人菌株的基因组进行重新测序，对于每个QTL，人们可以额外识别出少数可能导致DNA变异的目标，以用于未来的工作。 我们将定位四个压力和药物耐受性示范性状的QTL，选择这些性状是因为它们易于测量和适度的遗传力。每个性状将在三个作图设计中得分：直接在纯合RIL中，在轮回RIL-RIL杂交的杂合后代中，以及将RIL与普通近交参考品系杂交后。这两个杂合测交组合将直接检测近交对RILs中QTL定位的影响。这些测试杂交在果蝇身上进行相对简单，其结果可能对使用鼠标“协作杂交”八向RILS的实验设计有重要影响，在这种系统中，测试杂交的执行将非常繁琐和昂贵。