一个Diel多组织基因组规模的Vitis vinifera的代谢模型
Marta Sampaio1, Miguel Rocha1,2, Oscar Dias1,2
1Centre of Biological Engineering, University of Minho, Campus of Gualtar, Braga, Portugal.
PLoS computational biology
|October 10, 2024
概括
这项研究提出了第一个基因组规模的Vitis vinifera (葡萄藤) 的代谢模型,使葡萄代谢和品质的详细分析成为可能. 将这种模型与机器学习相结合,为葡萄藤生理学提供了新的见解.
科学领域:
- 植物新陈代谢 植物新陈代谢
- 系统生物学 系统生物学
- 计算生物学 计算生物学
背景情况:
- 葡萄酒 (葡萄藤) 对葡萄酒生产至关重要,因此葡萄的质量及其潜在的代谢过程是重要的研究领域.
- 基因组规模代谢模型 (GSMMs) 是研究植物代谢的强大工具,越来越多地整合了omics数据.
- 机器学习 (ML) 对于奥米克数据分析是有效的,但其与GSMM用于植物研究的组合尚未得到充分探索.
研究的目的:
- 重建和验证Vitis vinifera的第一个GSMM.
- 开发葡萄藤的组织特异性和多组织模型.
- 探索ML与GSMM的整合,以分析葡萄的发育代谢.
主要方法:
- 一个葡萄酒GSMM (7199个基因,5399个反应,5141个代谢物) 的重建和验证.
- 使用RNA-Seq数据集成生成特定组织模型 (茎,叶子,果).
- 创建DIEL多组织模型,并将ML应用于流量学数据.
主要成果:
- 成功建立并验证了Vitis vinifera的全面GSMM.
- 产生了特定组织和多组织的模型,捕捉了组织间的动态.
- 对流体学数据的ML分析提供了对葡萄各个发育阶段的新陈代谢的见解.
结论:
- 开发的GSMM是研究葡萄酒代谢的宝贵工具.
- 这些模型有助于更深入地了解影响葡萄和葡萄酒质量的因素.
- ML与GSMM的整合显示了植物代谢研究的巨大潜力.
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