Centre for Crop Systems Analysis, Department of Plant Sciences, Wageningen University, PO Box 430, 6700 AK Wageningen, The Netherlands.
J Exp Bot. 2010 May;61(8):2171-83. doi: 10.1093/jxb/erp375. Epub 2010 Jan 4.
There is strong interplant competition in a crop stand for various limiting resources, resulting in complex compensation and regulation mechanisms along the developmental cascade of the whole crop. Despite decades-long use of principles in system dynamics (e.g. feedback control), current crop models often contain many empirical elements, and model parameters may have little biological meaning. Building on the experience in designing the relatively new model GECROS, we believe models can be made less empirical by employing existing physiological understanding and mathematical tools. In view of the potential added value of robust crop modelling to classical quantitative genetics, model input parameters are increasingly considered to represent 'genetic coefficients'. The advent of functional genomics and systems biology enables the elucidation of the molecular genetic basis of these coefficients. A number of case studies, in which the effects of quantitative trait loci or genes have been incorporated into existing ecophysiological models, have shown the promise of using models in analysing genotype-phenotype relationships of some crop traits. For further progress, crop models must be upgraded based on understanding at lower organizational levels for complicated phenomena such as sink formation in response to environmental cues, sink feedback on source activity, and photosynthetic acclimation to the prevailing environment. Within this context, the recently proposed 'crop systems biology', which combines modern genomics, traditional physiology and biochemistry, and advanced modelling, is believed ultimately to realize the expected roles of in silico modelling in narrowing genotype-phenotype gaps. This review summarizes recent findings and our opinions on perspectives for modelling genotype x environment interactions at crop level.
在作物群体中，各种限制资源之间存在强烈的种间竞争，导致整个作物发育级联过程中存在复杂的补偿和调节机制。尽管系统动力学原理已经使用了几十年（例如反馈控制），但当前的作物模型通常包含许多经验元素，而且模型参数可能没有生物学意义。在设计相对较新的 GECROS 模型的经验基础上，我们相信通过利用现有生理理解和数学工具，可以使模型减少经验成分。鉴于稳健作物建模对经典数量遗传学的潜在附加值，模型输入参数越来越被认为代表“遗传系数”。功能基因组学和系统生物学的出现使这些系数的分子遗传基础得以阐明。一些案例研究已经将数量性状基因座或基因的影响纳入现有的生理生态模型中，这些研究表明，使用模型来分析某些作物性状的基因型-表型关系具有一定的前景。为了取得进一步的进展，必须基于对复杂现象（例如对环境信号的汇形成的响应、汇对源活性的反馈以及对流行环境的光合作用适应）的较低组织层次的理解来升级作物模型。在这种情况下，最近提出的“作物系统生物学”结合了现代基因组学、传统生理学和生物化学以及高级建模，被认为最终可以实现计算机建模在缩小基因型-表型差距方面的预期作用。本文综述了最近的发现，并就作物水平上建模基因型 x 环境相互作用的观点提出了我们的看法。
