Genetic variation and evolution of translational control in Drosophila

项目摘要 大多数人类疾病和性状都是复杂的数量性状，涉及大量的基因、DNA 序列变异和环境因素，以及它们之间复杂的相互作用。尽管引人注目 在高分辨率遗传作图方面的进展，我们对序列变异如何导致表型 变异仍然不完整。最近的研究纳入了中间分子表型，包括RNA， 蛋白质和代谢物丰度促进了DNA之间关联的功能描绘， 人类和模式生物的变异和复杂的数量性状。虽然mRNA翻译 是一个关键的生物学过程，自然序列变异如何导致翻译中的遗传变异， 控制以及这种水平的监管变化如何有助于种群内和物种间 多样性有待理解。使用果蝇胚胎作为模型系统，我们建议填补这一空白， 1)在多个阶段对胚胎之间的翻译效率的遗传变异进行定量和作图， 全测序和深度表型化的黑腹果蝇种群的近交系; 2）作图 顺式或反式调控变异导致种间翻译差异的基因 效率;和3）开发大规模平行的报告基因测定，以系统地测试顺式调节的作用。 mRNA翻译的变化。这些全面的研究，当与广泛的现有数据相结合时， 使用的研究人群，提供了一个表征的基因型-表型地图在前所未有的细节。 他们将大大推进我们对DNA变异如何促进表型变异的理解， 以及物种之间的差异，包括人类群体中个体之间疾病风险的差异。

Project Summary Most human diseases and traits are complex quantitative traits, involving a large number of genes, DNA sequence variants and environmental factors, and the complex interactions among them. Despite remarkable progress in high resolution genetic mapping, our understanding of how sequence variants cause phenotypic variation remains incomplete. Recent studies incorporating intermediate molecular phenotypes including RNA, protein, and metabolite abundances have facilitated functional delineation of associations between DNA variants and complex quantitative traits in humans and model organisms. However, although mRNA translation is a critical biological process, how natural sequence variation may lead to genetic variation in translational control and how this level of regulatory variation can contribute to within-population and between-species diversity remain to be understood. Using Drosophila embryos as a model system, we propose to fill this gap by 1) quantifying and mapping genetic variation of translation efficiency among embryos at multiple stages from inbred strains of a fully sequenced and deeply phenotyped Drosophila melanogaster population; 2) mapping genes whose cis or trans regulatory variation contributes to between-species divergence in translation efficiency; and 3) developing a massively parallel reporter assay to systematically test effects of cis regulatory variation on mRNA translation. These comprehensive studies, when integrated with existing data in the widely used study population, provide a characterization of the genotype-phenotype maps in unprecedented details. They will significantly advance our understanding of how DNA variants contribute to phenotypic variation within and between species, including variation in disease risks among individuals in human populations.