Systems Genetics of Drosophila Life Span

描述（由申请人提供）：世界人口正在迅速老龄化，人口老龄化将是未来半个世纪最重要的社会和健康问题之一。寿命是一种典型的数量性状，其自然变异可归因于多个相互作用位点的分离变异，其影响对个体所处的环境非常敏感。然而，只有少数与人类寿命变异相关的候选基因已被确定。在本应用中，我们建议通过使用强大的果蝇模型系统来识别与寿命因果相关的进化保守遗传网络，该模型系统使我们能够在精确控制遗传背景和环境条件的同时精确测量寿命。作者利用果蝇遗传参考群体（DGRP）对果蝇寿命进行了综合系统遗传学分析，该群体由基因组测序的野生自交系组成。这些细胞系对迄今为止测量的所有表型都具有遗传变异，包括寿命。该应用程序的具体目的是：(1)利用基因组全关联和连锁作图的结合，以高分辨率绘制与寿命变异相关的因果等位基因；(2)推导影响寿命的因果转录共表达网络，将通过遗传作图鉴定的新位点置于适当的生物学环境中，并使用等位基因特异性表达来测试系统水平的预测；(3)利用突变和RNAi对自然变异和转录网络结构的统计分析所涉及的基因寿命的影响进行功能测试，并利用最近开发的将转基因整合到同一基因组位置的系统来进行自然等位基因因果效应的测试。这些研究的结果

DESCRIPTION (provided by applicant): The world population is rapidly growing older, and population aging will be one of the most important social and health problems in the coming half-century. Life span is a typical quantitative trait, with natural variation attributable to segregating variants at multiple interacting loci, the effects of which are sensitive to the environment to which the individuals are exposed. However, only a handful of candidate genes associated with variation in life span in human populations have been identified. In this application we propose to identify evolutionarily conserved genetic networks causally associated with life span by using the powerful Drosophila model system, which enables us to accurately measure life span while precisely controlling both genetic background and environmental conditions. We propose an integrated systems genetics analysis of life span using the Drosophila melanogaster Genetic Reference Population (DGRP), which consists of wild-derived inbred lines with sequenced genomes. The lines are genetically variable for all phenotypes measured to date, including life span. The Specific Aims of this application are: (1) To map causal alleles associated with variation in life span with high resolution using a combination of genome wide association and linkage mapping; (2) To derive causal transcriptional co-expression networks affecting life span, placing novel loci identified by genetic mapping in appropriate biological context, and to use allele specific expression to test the systems level predictions; and (3) To use mutations and RNAi to functionally test effects on life span of genes implicated by the statistical analyses of natural variation and architecture of transcriptional networks, and use the recently developed system for integrating transgenes in the same genomic location to perform tests for causal effects of natural alleles. Results from these studies are likely to uncover novel genes and evolutionarily conserved cellular pathways associated with variation in life span. Because many genes in Drosophila have human orthologues, general insights derived from our proposed studies will have translational implications for human genetic studies on life span; moreover, we argue that insights derived from systems genetic studies of life span will have a broad impact on our general understanding of quantitative traits.