Systems Genetics of Drosophila Life Span

描述(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的座位上的分离变异，其影响对个体所处的环境敏感。然而，只有少数与人类人口寿命变化相关的候选基因被识别出来。在这项应用中，我们建议通过使用强大的果蝇模型系统来识别与寿命相关的进化保守的遗传网络，这使我们能够准确地测量寿命，同时精确地控制遗传背景和环境条件。我们提出了利用黑腹果蝇遗传参考群体(DGRP)对寿命进行综合的系统遗传学分析，DGRP由野生来源的近交系和测序基因组组成。到目前为止，这些品系对包括寿命在内的所有表型都是遗传可变的。这一应用的具体目的是：(1)利用全基因组关联和连锁作图的组合，以高分辨率定位与寿命变化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，将通过遗传作图识别的新基因座置于适当的生物学背景中，并利用等位基因特异性表达来检验系统水平的预测；(3)使用突变和RNAi从功能上测试自然变异和转录网络结构的统计分析所涉及的基因对寿命的影响，并使用最近开发的整合同一基因组位置的转基因的系统来测试自然等位基因的因果效应。这些研究的结果 可能会发现与寿命变化相关的新基因和进化上保守的细胞途径。由于果蝇中的许多基因都与人类同源，我们所提出的研究得出的一般见解将对人类寿命的遗传学研究具有翻译意义；此外，我们认为，来自寿命系统遗传学研究的见解将对我们对数量性状的一般理解产生广泛的影响。

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.