Hammer Graeme, Cooper Mark, Tardieu François, Welch Stephen, Walsh Bruce, van Eeuwijk Fred, Chapman Scott, Podlich Dean
APSRU, School of Land and Food Sciences, University of Queensland, Brisbane, QLD 4072, Australia.
Trends Plant Sci. 2006 Dec;11(12):587-93. doi: 10.1016/j.tplants.2006.10.006. Epub 2006 Nov 7.
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.
如果能够可靠地预测改变生物体基因组成所带来的表型后果，那么培育高产作物的进展将大大加快。从基因型到表型的预测能力的发展受到与遗传控制、环境影响以及植物生长和发育过程之间相互作用相关的生物学复杂性的阻碍。植物建模有助于在这种复杂性中找到一条路径。在这里，我们概述了基因网络、器官和整株植物水平上复杂性状的建模方法。每种方法都提供了一种通过与模型系数的稳定关联将表型后果与基因组区域变化联系起来的手段。这些模型的一个统一特征是它们用于捕捉系统动态的粒度相对较粗。许多精细细节并非直接必需。强大的粗粒度模型可能是整合植物育种的表型和分子方法所需的工具。
