GENOME WIDE ASSOCIATION MAPPING IN ARABIDOPSIS THALIANA

我们的建议将研究复杂性状的遗传和分子基础，以及它们与 环境采用模式植物拟南芥。我们将实施多用途、高密度的寡头- 用于全基因组重测序的核苷酸拼接阵列。样品将包括一个基本上无结构的岩心 一套384个野生拟南芥子基因组。这将被用来开发非常高分辨率的单倍型图谱， 揭示全基因组的变异模式，并建议在自然选择下的位置。生态化 将测量开花时间和幼苗伸长光响应的相关数量性状 两个季节和两个地理环境，跨越了A.thaliana的原生范围。现在和未来 群体表型数据将被用于开发和测试精细尺度数量性状基因座的方法 利用高密度单倍型图谱进行(QTL)关联扫描。全基因组联合 将使用用于检测和精细测绘的合并模型来开发测绘。我们将确定 利用拟南芥遗传学的全部力量，两个新的QTL潜在的功能分子变化。 重要的是，这项提议将开发新的技术进步，使用平铺阵列来产生高 密度单倍型图谱是全基因组关联研究的基础。这些方法，一旦 建立，然后可以推广到其他模型系统。细尺度连杆机构的发展 不平衡作图方法将得到广泛应用。 人们对复杂的疾病关联图谱有着极大的兴趣，但对于不同的 方法，但迄今为止收效甚微。这里提出的关于拟南芥的研究将显示成功。 这一艰巨任务的路径，因为关联可以被快速确认以确定新的QTL。

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.