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：
7367934
负责人：
JUSTIN O BOREVITZ
金额：
$ 46.96万
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/7367934
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

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.

我们的提案将研究复杂性状的遗传和分子基础及其与环境使用模型植物拟南芥。我们将实施多用途、高密度寡聚用于全基因组重测序的核苷酸平铺阵列。该样本将包括一个很大程度上非结构化的核心一组 384 个野生拟南芥基因组。这将用于开发非常高分辨率的单倍型图谱，揭示基因组范围内的变异模式，并提出自然选择下的位点。生态上将测量开花时间和幼苗伸长光响应的相关数量性状跨越拟南芥原生范围的两个季节和两个地理环境。这和未来群落表型数据将用于开发和测试精细数量性状基因座的方法 (QTL)关联扫描利用高密度单倍型图。全基因组关联将使用用于检测和精细绘图的合并模型来开发绘图。我们将确定利用拟南芥遗传学的全部力量，研究两个新 QTL 的功能性分子变化。重要的是，该提案将开发新的技术进步，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，一次建立后，可以扩展到其他模型系统。精细化规模联动发展不平衡作图方法将得到广泛应用。人们对复杂疾病关联图谱有着极大的兴趣，但对于不同的疾病存在很多争议方法，但迄今为止收效甚微。这里提出的拟南芥研究将表明成功这项艰巨任务的路径，因为可以快速确认关联以识别新的 QTL。