Unraveling Gene-Environment Interactions Shaping Metabolism: A Multi-Omics Analysis in Drosophila

揭示基因-环境相互作用塑造代谢：果蝇的多组学分析

• 批准号: 11016897
• 负责人: Xuan Zhuang
• 金额: $ 11.5万
• 依托单位: UNIVERSITY OF ARKANSAS AT FAYETTEVILLE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-01 至 2026-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/11016897
• 关键词: Unraveling; Gene; Environment; Interactions; Shaping

Human diseases arise from complex interactions between genetics and the environment, and as our environment changes, genetic variations that were once beneficial can now contribute to diseases. The Western high-sugar diet has led to a global surge in metabolic diseases like diabetes and obesity, but our comprehension of the genetic-diet interactions in these conditions remains limited. Studying these interactions at the organismal level is challenging due to the absence of intermediate molecular phenotypes like transcriptome and metabolome data. To address this, our project aims to identify genetic variations linked to high-sugar diet-induced disease phenotypes in Drosophila, culminating in the construction of a comprehensive gene-transcript-metabolitephenotype network. Leveraging both outbred and inbred Drosophila populations and integrating molecular phenotypes, we seek to understand how these variations influence susceptibility to complex disease traits. Our preliminary data indicates that a high-sugar diet disrupts metabolic balance, revealing cryptic genetic variations that are hard to detect under normal conditions. To achieve our objectives, we first embark on exploring the phenome by inducing disease phenotypes in Drosophila populations through a high-sugar diet. This endeavor allows us to evaluate phenotypic variation and heritability, and identify correlations among metabolic, developmental, and mitochondrial traits. Next, we delve into unraveling the genome, employing a fine mapping strategy to uncover cryptic genetic variations under high-sugar dietary stress and gene-diet interactions across different sugar concentrations. Lastly, we center on deciphering the metabolome and transcriptome, employing a systems biology approach that integrates genetic variations with metabolomic and transcriptomic data. This integration will uncover the relationships between gene expression, metabolite profiles, and complex organismal traits in the context of diet-induced metabolic disorders. Overall, we expect to reveal novel gene-diet interactions and previously elusive pathway components, offering the potential to introduce new multi-omic strategies for investigating metabolic diseases. The successful execution of this research promises to propel precision medicine, enhance metabolic well-being, and deepen our core knowledge concerning the genetics underlying complex metabolic disorders.

人类疾病源于遗传与环境之间复杂的相互作用，随着环境的变化，曾经有益的遗传变异现在可能导致疾病。西方高糖饮食导致糖尿病和肥胖等代谢疾病在全球范围内激增，但我们对这些疾病中基因与饮食相互作用的理解仍然有限。研究有机体中的这些相互作用 由于缺乏转录组和代谢组数据等中间分子表型，因此水平具有挑战性。为了解决这个问题，我们的项目旨在识别果蝇中与高糖饮食诱发的疾病表型相关的遗传变异，最终构建一个全面的基因-转录-代谢表型 网络。利用远交和近交果蝇种群并整合分子表型，我们试图了解这些变异如何影响对复杂疾病特征的易感性。我们的初步数据表明，高糖饮食会破坏代谢平衡，揭示在正常条件下难以检测到的神秘遗传变异。为了实现我们的目标，我们首先通过高糖饮食在果蝇种群中诱导疾病表型来探索表型。这项努力使我们能够评估表型变异和遗传力，并确定代谢、发育和线粒体特征之间的相关性。接下来，我们深入研究基因组，采用精细作图策略来揭示高糖饮食压力和基因与饮食相互作用下的神秘遗传变异。 不同的糖浓度。最后，我们集中于破译代谢组和转录组，采用系统生物学方法，将遗传变异与代谢组和转录组数据相结合。这种整合将揭示饮食引起的代谢紊乱背景下基因表达、代谢物谱和复杂生物体特征之间的关系。总体而言，我们期望揭示新的基因-饮食相互作用和以前难以捉摸的途径成分，从而为引入新的多组学策略来研究代谢疾病提供潜力。这项研究的成功执行有望推动精准医疗，增强代谢健康，并加深我们有关遗传学基础的核心知识 复杂的代谢紊乱。