Deducing hybrid performance from parental metabolic profiles of young primary roots of maize by using a multivariate diallel approach.
Deducing hybrid performance from parental metabolic profiles of young primary roots of maize by using a multivariate diallel approach.
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DOI：
10.1371/journal.pone.0085435
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Willmitzer L
中科院分区：
文献类型：
--
作者：
Feher K;Lisec J;Römisch-Margl L;Selbig J;Gierl A;Piepho HP;Nikoloski Z;Willmitzer L
杂种优势，即杂种比其亲本更有活力的优势，已经在玉米育种中被利用了100多年，以生产出性能更好、产量更高的优良杂种。尽管进行了广泛的研究，但形成杂种优势程度的潜在机制尚未得到很好的理解，这使得选择一组最佳亲本系的过程变得繁琐。本研究基于4个亲本玉米自交系及其对应的12个杂交种幼根的112个代谢物水平数据集，以及作为杂种优势性状的根生物量。由于亲本生物量不能很好地预测杂种生物量，因此我们建立了一个模型框架，通过亲本的代谢物谱来推断杂种的生物量。在提出的框架中，杂种代谢物水平通过结合可加性/显性的标准概念来相对于亲本水平表达，我们将其命名为联合相对水平（CRL）。我们的建模策略包括亲本水平上的特征选择步骤，这被证明可以预测许多杂交代谢物的CRL。我们证明这些选择的亲本代谢物可以进一步预测杂交生物量。我们的方法直接采用多元方式的双列杂交结构，因此我们不仅试图预测宏观表型（生物量），而且还试图预测分子表型（代谢物谱）。因此，我们的研究为进一步研究代谢和最终生长的遗传决定因素提供了第一步。最后，我们在小规模实验上的成功为大规模实验提供了一个有效的策略，在大规模实验中，亲本代谢物谱可以与选择的杂交种谱一起作为一个训练集来预测所有可能的杂交种的生物量。
Heterosis, the greater vigor of hybrids compared to their parents, has been exploited in maize breeding for more than 100 years to produce ever better performing elite hybrids of increased yield. Despite extensive research, the underlying mechanisms shaping the extent of heterosis are not well understood, rendering the process of selecting an optimal set of parental lines tedious. This study is based on a dataset consisting of 112 metabolite levels in young roots of four parental maize inbred lines and their corresponding twelve hybrids, along with the roots' biomass as a heterotic trait. Because the parental biomass is a poor predictor for hybrid biomass, we established a model framework to deduce the biomass of the hybrid from metabolite profiles of its parental lines. In the proposed framework, the hybrid metabolite levels are expressed relative to the parental levels by incorporating the standard concept of additivity/dominance, which we name the Combined Relative Level (CRL). Our modeling strategy includes a feature selection step on the parental levels which are demonstrated to be predictive of CRL across many hybrid metabolites. We demonstrate that these selected parental metabolites are further predictive of hybrid biomass. Our approach directly employs the diallel structure in a multivariate fashion, whereby we attempt to not only predict macroscopic phenotype (biomass), but also molecular phenotype (metabolite profiles). Therefore, our study provides the first steps for further investigations of the genetic determinants to metabolism and, ultimately, growth. Finally, our success on the small-scale experiments implies a valid strategy for large-scale experiments, where parental metabolite profiles may be used together with profiles of selected hybrids as a training set to predict biomass of all possible hybrids.
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影响因子：
4
作者：
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通讯作者：
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影响因子：
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