Wang Huange, Paulo Joao, Kruijer Willem, Boer Martin, Jansen Hans, Tikunov Yury, Usadel Björn, van Heusden Sjaak, Bovy Arnaud, van Eeuwijk Fred
Biometris, Wageningen University and Research Centre, PO Box 16, 6700AA Wageningen, The Netherlands.
Mol Biosyst. 2015 Nov;11(11):3101-10. doi: 10.1039/c5mb00477b. Epub 2015 Sep 7.
Modeling genotype-phenotype relationships is a central objective in plant genetics and breeding. Commonly, variations in phenotypic traits are modeled directly in relation to variations at the DNA level, regardless of intermediate levels of biological variation. Here we present an integrative method for the simultaneous modeling of a set of multilevel phenotypic responses to variations at the DNA level. More specifically, for ripe tomato fruits, we use Gaussian graphical models and causal inference techniques to learn the dependencies of 24 sensory traits on 29 metabolites and the dependencies of those sensory and metabolic traits on 21 QTLs. The inferred dependency network which, though not essentially representing biological pathways, suggests how the effects of allele substitutions propagate through multilevel phenotypes. Such simultaneous study of the underlying genetic architecture and multifactorial interactions is expected to enhance the prediction and manipulation of complex traits.
建立基因型-表型关系模型是植物遗传学和育种的核心目标。通常，表型性状的变异直接与DNA水平的变异相关联进行建模，而不考虑生物变异的中间水平。在此，我们提出了一种综合方法，用于同时对一组多水平表型对DNA水平变异的响应进行建模。更具体地说，对于成熟番茄果实，我们使用高斯图形模型和因果推断技术来研究24种感官性状对29种代谢物的依赖性，以及这些感官和代谢性状对21个数量性状位点（QTL）的依赖性。推断出的依赖网络虽然本质上并不代表生物途径，但它揭示了等位基因替换的效应如何通过多水平表型进行传播。对潜在遗传结构和多因素相互作用的这种同时研究有望增强对复杂性状的预测和操控。
