QTLs in Drosophila

描述（由申请人提供）：大多数与人类健康和适应性进化相关的表型变异在遗传上是复杂的，种群变异可归因于许多具有环境敏感效应的相互作用基因上的分离等位基因。该项目的长期目标是从单个位点等位基因变异的分子基础和等位基因对多个性状的影响分布等方面了解这些数量性状的遗传结构；这些影响在多大程度上取决于环境，取决于性别、遗传背景、物理和社会环境。黑腹果蝇（Drosophila melanogaster）是利用基因组全关联（genome wide association， GWA）作图阐明复杂性状遗传结构一般原理的优秀模型系统，因为果蝇高水平的分子多态性和低连锁不平衡不仅有助于鉴定与复杂性状相关的基因，而且有助于鉴定实际的因果多态性。在果蝇中定位GWA的主要障碍是需要来自约200个蝇系的完整基因组序列。国家人类基因组研究所最近批准了192个来自美国罗利种群的近交黑腹果蝇系的全基因组测序，作为果蝇遗传参考小组（DGRP）。这些细胞系和全基因组多态性数据将为在一系列环境中快速、高分辨率定位影响复杂性状的基因提供社区资源。然而，分子多态性通过扰乱转录和其他生物网络来影响数量性状。如果我们要将统计关联置于生物学背景下，了解遗传变异对潜在网络和性状遗传变异的影响是必要的。本项目期间的具体目标是利用192个DGRP自交系，在两种环境下对若干数量性状进行GWA分析；鉴定两种环境中与数量性状相关的遗传网络；并进行功能研究，以确认联系和验证网络。这些研究将对影响一系列复杂性状的相互作用位点、每个性状的等位基因效应和多效性效应的分布以及环境相互作用下基因型的分子基础提供前所未有的见解。这些研究将全面了解常见与罕见变异、大效与小效等位基因、单核苷酸多态性与拷贝数变异、编码区非同义多态性与推测的调控多态性对数量性状变异的分子基础的相对贡献。这种使用果蝇模型的系统遗传学方法将在复杂性状表现的基因型变异和表型变异之间的关系方面产生丰富的普遍适用的见解。

DESCRIPTION (provided by applicant): Most phenotypic variation relevant to human health and adaptive evolution is genetically complex, with population variation attributable to segregating alleles at many interacting genes with environmentally sensitive effects. The long-term goal of this project is to understand the genetic architecture of such quantitative traits in terms of the molecular basis of allelic variation at individual loci and the distribution of effects of alleles on multiple traits; and the extent to which these effects are context-dependent and vary depending on sex, genetic background, and the physical and social environment. Drosophila melanogaster is an excellent model system for elucidating general principles regarding the genetic architecture of complex traits using genome wide association (GWA) mapping, because high levels of molecular polymorphism and low linkage disequilibrium in Drosophila facilitate the identification of not only genes associated with complex traits, but actual causal polymorphisms. The major impediment to GWA mapping in Drosophila is that complete genome sequence from ~200 fly lines is necessary. The National Human Genome Research Institute recently approved the whole-genome sequencing of 192 inbred D. melanogaster lines, derived from the Raleigh, US population, as a Drosophila Genetic Reference Panel (DGRP). These lines and genome wide polymorphism data will be a community resource for rapid and high resolution mapping of genes affecting complex traits in a range of environments. However, molecular polymorphisms affect quantitative traits by perturbing transcriptional and other biological networks. Understanding the impact of genetic variation on both underlying networks and genetic variation for the traits is necessary if we are to place the statistical associations in biological context. The specific aims for this project period are to perform GWA analyses of several quantitative traits in two environments, using the 192 DGRP inbred lines; to identify genetic networks associated with quantitative traits in two environments; and to perform functional studies to confirm associations and validate networks. These studies will give unprecedented insight into the interacting loci affecting a range of complex traits, distributions of allelic effects for each trait and pleiotropic effects on multiple traits, and the molecular basis of genotype by environment interaction. These studies will provide a comprehensive understanding of the relative contribution of common vs. rare variants, alleles of large vs. small effects, single nucleotide polymorphisms vs. copy number variants, and non-synonymous polymorphisms in coding regions vs. putative regulatory polymorphisms to the molecular basis of variation for quantitative traits. This systems genetics approach using the Drosophila model will generate a wealth of generally applicable insights in the relationship between genotypic variation and phenotypic variation for the manifestation of complex traits. PUBLIC HEALTH RELEVANCE: Variation in human populations for susceptibility to common diseases and behavioral disorders, as well as responses to pharmacological therapies, is genetically complex. However, the organization of the human genome into haplotype blocks is an impediment to identifying causal polymorphisms associated with complex traits, and variable genetic backgrounds and environmental exposures further limit our ability to determine context-dependent phenotypic effects of molecular polymorphisms in human studies. This study takes advantage of the power of genome wide association analyses in Drosophila and the complete re-sequencing of 192 fly lines to identify molecular polymorphisms and genetic networks associated with several complex traits, and to investigate how the associations and networks are modulated by environmental stress. The insight into general principles of genotype-phenotype relationships will be applicable to human disease.