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本文引用的文献

1
Mass spectrometry-based metabolomics in health and medical science: a systematic review.基于质谱的代谢组学在健康与医学科学中的应用:一项系统综述。
RSC Adv. 2020 Jan 17;10(6):3092-3104. doi: 10.1039/c9ra08985c. eCollection 2020 Jan 16.
2
Genetic and metabolomic architecture of variation in diet restriction-mediated lifespan extension in Drosophila.饮食限制介导的果蝇寿命延长的遗传和代谢组学结构。
PLoS Genet. 2020 Jul 9;16(7):e1008835. doi: 10.1371/journal.pgen.1008835. eCollection 2020 Jul.
3
Can metabolic prediction be an alternative to genomic prediction in barley?代谢预测能否替代大麦中的基因组预测?
PLoS One. 2020 Jun 5;15(6):e0234052. doi: 10.1371/journal.pone.0234052. eCollection 2020.
4
The metabolome as a link in the genotype-phenotype map for peroxide resistance in the fruit fly, Drosophila melanogaster.果蝇中过氧化物抗性的基因型-表型图谱中的代谢组作为联系。
BMC Genomics. 2020 May 4;21(1):341. doi: 10.1186/s12864-020-6739-1.
5
Polygenic and clinical risk scores and their impact on age at onset and prediction of cardiometabolic diseases and common cancers.多基因和临床风险评分及其对发病年龄和心血管代谢疾病及常见癌症预测的影响。
Nat Med. 2020 Apr;26(4):549-557. doi: 10.1038/s41591-020-0800-0. Epub 2020 Apr 7.
6
An evaluation of machine-learning for predicting phenotype: studies in yeast, rice, and wheat.用于预测表型的机器学习评估:酵母、水稻和小麦的研究
Mach Learn. 2020;109(2):251-277. doi: 10.1007/s10994-019-05848-5. Epub 2019 Oct 23.
7
Metabolomic networks and pathways associated with feed efficiency and related-traits in Duroc and Landrace pigs.与杜洛克猪和长白猪的饲料效率及相关性状相关的代谢组学网络和途径。
Sci Rep. 2020 Jan 14;10(1):255. doi: 10.1038/s41598-019-57182-4.
8
qgg: an R package for large-scale quantitative genetic analyses.qgg:一个用于大规模数量遗传学分析的 R 包。
Bioinformatics. 2020 Apr 15;36(8):2614-2615. doi: 10.1093/bioinformatics/btz955.
9
Assessing the performance of genome-wide association studies for predicting disease risk.评估全基因组关联研究预测疾病风险的性能。
PLoS One. 2019 Dec 5;14(12):e0220215. doi: 10.1371/journal.pone.0220215. eCollection 2019.
10
Systems genetics of the metabolome.代谢组的系统遗传学。
Genome Res. 2020 Mar;30(3):392-405. doi: 10.1101/gr.243030.118. Epub 2019 Nov 6.

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.

DOI:10.1038/s41437-021-00404-1
PMID:33510469
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8102504/
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。