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。寿命是一个典型的数量性状，自然变异归因于多个相互作用的基因座上的分离变异，其影响对个体所暴露的环境敏感。然而，只有少数与人类寿命变化相关的候选基因已经被确定。在这个应用程序中，我们建议使用强大的果蝇模型系统，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，以确定进化保守的遗传网络因果关系与寿命。我们提出了一个综合系统遗传学分析寿命使用果蝇遗传参考群体（DGRP），其中包括野生衍生的近交系测序基因组。这些品系对于迄今为止测量的所有表型都是遗传可变的，包括寿命。本申请的具体目的是：（1）使用全基因组关联和连锁作图的组合以高分辨率作图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，将通过遗传作图鉴定的新基因座置于适当的生物学背景中，并使用等位基因特异性表达来测试系统水平预测;以及（3）使用突变和RNAi来功能性地测试对基因寿命的影响，所述基因的寿命由对自然变异和转录网络的结构的统计分析所暗示，并且使用最近开发的用于将转基因整合到相同基因组位置的系统来执行对自然等位基因的因果影响的测试。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通路。由于果蝇中的许多基因都有人类的直系同源物，因此我们提出的研究所得出的一般见解将对人类寿命遗传学研究产生翻译影响;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.