Department of Plant and Environmental Sciences, Copenhagen Plant Science Centre, University of Copenhagen, Højbakkegård Allé 13, 2630 Taastrup, Denmark.
Department of Plant and Environmental Sciences, Copenhagen Plant Science Centre, University of Copenhagen, Højbakkegård Allé 13, 2630 Taastrup, Denmark Global Change Research Centre, Czech Globe AS CR, v.v.i.., Drásov 470, Cz-664 24 Drásov, Czech Republic
J Exp Bot. 2015 Sep;66(18):5429-40. doi: 10.1093/jxb/erv345. Epub 2015 Jul 10.
Plants are affected by complex genome×environment×management interactions which determine phenotypic plasticity as a result of the variability of genetic components. Whereas great advances have been made in the cost-efficient and high-throughput analyses of genetic information and non-invasive phenotyping, the large-scale analyses of the underlying physiological mechanisms lag behind. The external phenotype is determined by the sum of the complex interactions of metabolic pathways and intracellular regulatory networks that is reflected in an internal, physiological, and biochemical phenotype. These various scales of dynamic physiological responses need to be considered, and genotyping and external phenotyping should be linked to the physiology at the cellular and tissue level. A high-dimensional physiological phenotyping across scales is needed that integrates the precise characterization of the internal phenotype into high-throughput phenotyping of whole plants and canopies. By this means, complex traits can be broken down into individual components of physiological traits. Since the higher resolution of physiological phenotyping by 'wet chemistry' is inherently limited in throughput, high-throughput non-invasive phenotyping needs to be validated and verified across scales to be used as proxy for the underlying processes. Armed with this interdisciplinary and multidimensional phenomics approach, plant physiology, non-invasive phenotyping, and functional genomics will complement each other, ultimately enabling the in silico assessment of responses under defined environments with advanced crop models. This will allow generation of robust physiological predictors also for complex traits to bridge the knowledge gap between genotype and phenotype for applications in breeding, precision farming, and basic research.
植物受到复杂的基因组×环境×管理相互作用的影响,这些相互作用决定了表型可塑性,这是遗传成分可变性的结果。虽然在遗传信息的成本效益高和高通量分析以及非侵入性表型分析方面取得了巨大进展,但基础生理机制的大规模分析却滞后了。外部表型是由代谢途径和细胞内调控网络的复杂相互作用的总和决定的,这反映在内部的生理和生化表型中。这些不同尺度的动态生理响应需要被考虑,基因型和外部表型应该与细胞和组织水平的生理学联系起来。需要进行跨尺度的高维生理表型分析,将内部表型的精确描述整合到整个植物和冠层的高通量表型分析中。通过这种方式,可以将复杂的性状分解为生理性状的单个组成部分。由于“湿化学”的生理表型更高分辨率在通量方面固有地受到限制,因此需要跨尺度验证和验证高通量非侵入性表型,将其作为基础过程的替代物。通过这种跨学科和多维的表型组学方法,植物生理学、非侵入性表型分析和功能基因组学将相互补充,最终使先进的作物模型能够在定义的环境下对响应进行计算机模拟评估。这将允许为复杂性状生成稳健的生理预测因子,以弥合基因型和表型之间的知识差距,从而应用于育种、精准农业和基础研究。