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首页> 外文期刊>Trends in Plant Science >Models for navigating biological complexity in breeding improved crop plants
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Models for navigating biological complexity in breeding improved crop plants

机译：培育改良作物植物中生物复杂性的模型

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Progress in breeding higher-yielding crop plants would be greatly accelerated if the phenotypic consequences of making changes to the genetic makeup of an organism could be reliably predicted. Developing a predictive capacity that scales from genotype to phenotype is impeded by biological complexities associated with genetic controls, environmental effects and interactions among plant growth and development processes. Plant modelling can help navigate a path through this complexity. Here we profile modelling approaches for complex traits at gene network, organ and whole plant levels. Each provides a means to link phenotypic consequence to changes in genomic regions via stable associations with model coefficients. A unifying feature of the models is the relatively coarse level of granularity they use to capture system dynamics. Much of the fine detail is not directly required. Robust coarse-grained models might be the tool needed to integrate phenotypic and molecular approaches to plant breeding.
机译：如果可以可靠地预测对生物体的基因组成进行改变的表型后果，则将大大加快高产农作物育种的进展。与基因控制，环境影响以及植物生长与发育过程之间的相互作用相关的生物复杂性阻碍了从基因型到表型的预测能力的发展。工厂建模可以帮助您克服这种复杂性。在这里，我们介绍了在基因网络，器官和整个植物水平上针对复杂性状的建模方法。每个模型都提供了一种通过与模型系数的稳定关联将表型结果与基因组区域变化联系起来的方法。这些模型的统一特征是它们用于捕获系统动态性的粒度相对较粗。许多精细细节不是直接需要的。强大的粗粒度模型可能是整合表型和分子方法用于植物育种的工具。

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