Lakshmanan Meiyappan, Cheung C Y Maurice, Mohanty Bijayalaxmi, Lee Dong-Yup
Bioprocessing Technology Institute, Agency for Science, Technology and Research Singapore, Singapore.
Department of Chemical and Biomolecular Engineering, National University of Singapore Singapore, Singapore.
Front Plant Sci. 2016 Nov 29;7:1795. doi: 10.3389/fpls.2016.01795. eCollection 2016.
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 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 six such networks are available, where five 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.
作物生产力受到各种生物和非生物胁迫的严重限制。因此，迫切需要了解植物对环境胁迫响应和耐受的潜在机制，而系统生物学方法可以解决这一问题。为此，可以考虑采用高通量组学分析和建模，从系统层面探索环境对水稻作物表型状态和代谢行为的影响。特别是，基于约束的代谢重建和分析的出现，通过将数学网络模型与多组学数据相结合，为表征各种胁迫下的植物细胞生理学铺平了道路。自2013年以来，水稻代谢网络已被重建，目前有六个这样的网络，其中五个是基因组规模的。自这些模型发表以来，它们已被用于系统地阐明水稻非生物胁迫响应，并确定用于作物改良的农艺性状。在这篇综述中，我们总结了现有水稻代谢网络和模型的现状及其应用。此外，我们还强调了水稻建模研究的未来方向，特别强调如何利用这些模型来诠释公共领域中随时可用的丰富多组学数据。总体而言，我们设想未来会有一系列研究，利用现有的代谢模型来提高水稻和其他粮食作物的产量和质量。
