GENOME WIDE ASSOCIATION MAPPING IN ARABIDOPSIS THALIANA

拟南芥全基因组关联图谱

基本信息

批准号：
7191729
负责人：
JUSTIN O BOREVITZ
金额：
$ 49.1万
依托单位：
UNIVERSITY OF CHICAGO
依托单位国家：
美国
项目类别：
财政年份：
2006
资助国家：
美国
起止时间：
2006-03-01 至 2011-02-28
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7191729
关键词：
Accounting Affect Algorithms Alleles Alternative Splicing Arabidopsis Atlases Base Pairing Beds Bioconductor Biological Models Candidate Disease Gene Cataloging Catalogs Color Communities Complex Condition Cues DNA Resequencing Data Data Set Depth Detection Development Disease Association Environment Evolution Flowers Foundations Future Gene Expression Generations Genes Genetic Genetic Complementation Test Genetic Crosses Genetic Polymorphism Genetic Recombination Genetic Variation Genome Genotype Graph Growth Haplotypes Humidity Hybridization Array Individual Inherited Joints Knock-out Light Linkage Disequilibrium Linkage Disequilibrium Mapping Maps Measures Methods Mining Modeling Molecular Molecular Genetics Molecular Profiling Mouse-ear Cress Mutation Natural Selections Noise Nucleotides Numbers Oligonucleotides Pattern Phenotype Plant Model Polymorphism Analysis Population Population Genetics Principal Investigator Quantitative Trait Loci Range Rate Residual state Resolution Resources Sampling Scanning Seasons Seedling Siblings Site Spain Staging Stratification Structure Sum Surveys Sweden System Temperature Testing Time Transgenic Organisms Trees Variant base day day length density falls follow-up functional genomics gene discovery genetic resource genome wide association study genome-wide linkage insertion/deletion mutation interest light intensity markov model novel open source programs research study response simulation statistics success trait water treatment

项目摘要

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.

描述（由申请人提供）：我们的建议将使用模型植物拟南芥研究复杂性状的遗传和分子基础及其与环境的相互作用。我们将实施多种用途的高密度寡核苷酸瓷砖阵列，以进行整个基因组重新方程。该样品将包括384个野生A. thaliana基因组的非结构化核心集。这将用于开发非常高的分辨率单倍型图，揭示基因组宽的变异模式，并建议在自然选择下进行位点。在两个季节性和两个地理环境中，将测量开花时间和幼苗伸长伸长响应的生态相关定量特征，这些特征跨越了A. thaliana的天然范围。此和未来的社区表型数据将用于开发和测试精细规模定量特质基因座（QTL）关联协会在高密度单倍型图上资本化的扫描。整个基因组关联映射将使用合并模型进行检测和精细映射开发。我们将利用拟南芥遗传学的全部力量来确定两个新型QTL的功能分子变化。重要的是，该提案将开发新的技术侵犯，用于使用平铺阵列来生成高密度单倍型图作为整个基因组关联研究的基础。这些方法一旦建立，就可以扩展到其他模型系统。精细链接不平衡映射方法的开发将广泛适用。人们对复杂疾病关联的映射有极大的兴趣，但迄今为止，不同的方法和成功少了很多争论。在拟南芥中提出的研究将为这项艰巨的任务提出成功的途径，因为可以快速确认关联以识别新型QTL。