Modeling rice metabolism: from elucidating environmental effects on cellular phenotype to guiding crop improvement

Frontiers in Plant Science

卷:7

Meiyappan Lakshmanan¹  Bijayalaxmi Mohanty²  Dong-Yup Lee²  Maurice C. Y. Cheung² 

[1] Bioprocessing Technology Institute;

[2] National University of Singapore;

关键词: Metabolism;    Systems Biology;    rice;    Flux-balance analysis;    -omics data;    genome-scale metabolic networks and models;   

DOI  :  10.3389/fpls.2016.01795

来源: DOAJ

【 摘 要 】

Crop productivity is severely limited by various biotic and abiotic stresses. Thus, it is highly needed to understand the underlying mechanisms of environmental stress response and tolerance in plants, which could be addressed by systems biology approach. To this end, high-throughput omics profiling and in silico modeling can be considered to explore the environmental effects on phenotypic states and metabolic behaviors of rice crops at the systems level. Especially, the advent of constraint-based metabolic reconstruction and analysis paves a way to characterize the plant cellular physiology under various stresses by combining the mathematical network models with multi-omics data. Rice metabolic networks have been reconstructed since 2013 and currently 6 such networks are available, where 5 are at genome-scale. Since their publication, these models have been utilized to systematically elucidate the rice abiotic stress responses and identify agronomic traits for crop improvement. In this review, we summarize the current status of the existing rice metabolic networks and models with their applications. Furthermore, we also highlight future directions of rice modeling studies, particularly stressing how these models can be used to contextualize the affluent multi-omics data that are readily available in the public domain. Overall, we envisage a number of studies in the future, exploiting the available metabolic models to enhance the yield and quality of rice and other food crops.

【 授权许可】

Unknown