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使用黑腹果蝇代谢组预测复杂表型。

Prediction of complex phenotypes using the Drosophila melanogaster metabolome.

机构信息

Department of Chemistry and Bioscience, Aalborg University, Aalborg, Denmark.

Department of Animal Science, Aarhus University, Tjele, Denmark.

出版信息

Heredity (Edinb). 2021 May;126(5):717-732. doi: 10.1038/s41437-021-00404-1. Epub 2021 Jan 28.

Abstract

Understanding the genotype-phenotype map and how variation at different levels of biological organization is associated are central topics in modern biology. Fast developments in sequencing technologies and other molecular omic tools enable researchers to obtain detailed information on variation at DNA level and on intermediate endophenotypes, such as RNA, proteins and metabolites. This can facilitate our understanding of the link between genotypes and molecular and functional organismal phenotypes. Here, we use the Drosophila melanogaster Genetic Reference Panel and nuclear magnetic resonance (NMR) metabolomics to investigate the ability of the metabolome to predict organismal phenotypes. We performed NMR metabolomics on four replicate pools of male flies from each of 170 different isogenic lines. Our results show that metabolite profiles are variable among the investigated lines and that this variation is highly heritable. Second, we identify genes associated with metabolome variation. Third, using the metabolome gave better prediction accuracies than genomic information for four of five quantitative traits analyzed. Our comprehensive characterization of population-scale diversity of metabolomes and its genetic basis illustrates that metabolites have large potential as predictors of organismal phenotypes. This finding is of great importance, e.g., in human medicine, evolutionary biology and animal and plant breeding.

摘要

理解基因型-表型图谱以及不同层次的生物学组织变异如何相关是现代生物学的核心课题。测序技术和其他分子组学工具的快速发展使研究人员能够获得 DNA 水平变异和中间表型(如 RNA、蛋白质和代谢物)的详细信息。这有助于我们理解基因型与分子和功能机体表型之间的联系。在这里,我们使用黑腹果蝇遗传参考面板和核磁共振(NMR)代谢组学来研究代谢组预测机体表型的能力。我们对来自 170 条不同同基因系的每一条雄性果蝇的四个重复池进行了 NMR 代谢组学分析。我们的结果表明,代谢物图谱在研究的品系之间存在差异,这种差异具有高度的遗传性。其次,我们确定了与代谢组变异相关的基因。第三,使用代谢组进行分析的五个数量性状中的四个比基因组信息具有更高的预测准确性。我们对代谢组的大规模多样性及其遗传基础的全面特征描述表明,代谢物具有作为机体表型预测因子的巨大潜力。这一发现对于人类医学、进化生物学以及动植物育种等领域都具有重要意义。

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