GENOME WIDE ASSOCIATION MAPPING IN ARABIDOPSIS THALIANA

描述(由申请人提供)：我们的计划将使用模式植物拟南芥来研究复杂性状的遗传和分子基础及其与环境的相互作用。我们将实现一个多用途、高密度的寡核苷酸拼接阵列，用于全基因组重测序。该样本将包括一组基本无结构的384个野生拟南芥基因组。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地点。开花时间和幼苗伸长光响应这两个生态相关的数量性状将在两个季节和两个地理环境中进行测量，这两个环境跨越了刺参的原生范围。这些和未来的群落表型数据将被用来开发和测试利用高密度单倍型图谱进行精细尺度数量性状座位(QTL)关联扫描的方法。将使用融合模型开发全基因组关联图谱，以进行检测和精细图谱绘制。我们将利用拟南芥遗传学的全部力量来确定两个新的QTL背后的功能分子变化。重要的是，这一提议将为使用平铺阵列生成高密度单倍型图谱作为全基因组关联研究的基础开发新的技术进步。这些方法一旦建立，就可以推广到其他模型系统。发展精细连锁不平衡作图方法将具有广泛的应用前景。人们对复杂的疾病关联图谱非常感兴趣，但关于不同方法的争论很多，到目前为止收效甚微。在拟南芥上提出的研究将为这项艰巨的任务提供成功的途径，因为关联可以很快得到确认，以确定新的QTL。

DESCRIPTION (provided by applicant): Our proposal will 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 used to 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 genome association 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 power of Arabidopsis genetics. Importantly this proposal will develop new technological 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 methods will 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.