GENOME WIDE ASSOCIATION MAPPING IN ARABIDOPSIS THALIANA

我们的建议将调查复杂性状的遗传和分子基础，以及它们与遗传因子的相互作用。 环境中使用的模式植物拟南芥。我们将实施一个多用途，高密度寡- 用于全基因组重测序的核苷酸平铺阵列。该示例将包括一个基本上非结构化的核心 384个野生A.拟南芥基因组This will be usedto develop发展a very high高resolution分辨率haplotype单体型map地图， 揭示了基因组范围内的变异模式，并提出了自然选择下的位点。生态上 开花时间和幼苗伸长光反应的相关数量性状将在整个 两个季节和两个地理环境，跨越了A. thaliana.这一代和未来 群落表型数据将用于开发和测试精细尺度数量性状位点的方法 (QTL)利用高密度单倍型图进行关联扫描。全基因组联合 将使用聚结模型进行探测和精细绘图。康贝特人将以 利用拟南芥遗传学的全部力量，在两个新的QTL基础上的功能分子变化。 重要的是，这项建议将开发新的技术进展，使用平铺阵列产生高 密度单倍型图作为全基因组关联研究的基础。这些方法，一旦 建立，然后可以扩展到其他模型系统。精细尺度联动的发展 不平衡作图法将得到广泛应用。 人们对复杂的疾病关联映射有极大的兴趣，但对不同的疾病关联映射存在许多争论。 方法，但迄今为止收效甚微。在拟南芥中进行的研究表明， 这一艰巨的任务，因为协会可以迅速确认，以确定新的QTL的路径。

Our proposalwill investigate the genetic and molecular basis of complex traits and their interactions with the environment using the model plant Arabidopsis thaliana. We will implement a multi use, high density oligo- nucleotide tiling array for whole genome resequencing. The sample will include a largely unstructured core set of 384 wild A. thaliana genomes. This will be usedto develop a very high resolution haplotype map, reveal genome wide patterns of variation, and suggest sites under natural selection. The ecologically relevant quantitative traits of flowering time and seedling elongation light response will be measured across two seasonal and two geographic environments which span the native range of A. thaliana. This and future community phenotypic data will be used to develop and test methods for fine scale quantitative trait locus (QTL) association scanning capitalizing on the high density haplotype map. Whole genomeassociation mapping will be developed using coalescent models for detection and fine mapping. We will determine the functional molecular changes underlying two novel QTL utilizing the full powerof Arabidopsis genetics. Importantly this proposal will develop newtechnological inroads for using tiling arrays to generate high density haplotype maps as the foundation for whole genome association studies. These methods, once established, can then be extended to other model systems. The development of fine scale linkage disequilibrium mapping methodswill be broadly applicable. There is a tremendous interest in complex disease association mapping, but much debate over different approaches and little success to date. The studies proposed here in Arabidopsis will suggest successful paths for this daunting undertaking, as associations can be quickly confirmed to identify novel QTL.