A resource for the genetic analysis of complex traits

描述（由申请人提供）：复杂疾病是由大量潜在相互作用的遗传和环境因素控制的。每年有数百万美国人被诊断患有复杂的疾病，如糖尿病、心脏病、阿尔茨海默氏症和各种形式的癌症。如果能够精确地描述导致疾病风险变异的基因位点，就可以预测疾病发病率，并且可以根据具体情况修改治疗方法，以阻止疾病进展并减轻痛苦（所谓的个性化医疗）。不幸的是，确定遗传风险等位基因目录的进展一直很缓慢，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，单独只赋予轻微的疾病风险，或者可能很罕见，但影响更大。我们的建议探索了一种新的方法来表征遗传位点，结合了典型QTL（数量性状位点）和关联图谱的优势，同时最大限度地减少了它们的一些弱点。该方法的一个特点是，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。

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.