Background： The increase in global population, climate change and stagnancy in crop yield on unit land area basis in recent decades urgently call for a new approach to support contemporary crop improvements, ePlant i...Background： The increase in global population, climate change and stagnancy in crop yield on unit land area basis in recent decades urgently call for a new approach to support contemporary crop improvements, ePlant is a mathematical model of plant growth and development with a high level of mechanistic details to meet this challenge. Results： ePlant integrates modules developed for processes occurring at drastically different temporal （10-8-106 seconds） and spatial （10-10-10 meters） scales, incorporating diverse physical, biophysical and biochemical processes including gene regulation, metabolic reaction, substrate transport and diffusion, energy absorption, transfer and conversion, organ morphogenesis, plant environment interaction, etc. Individual modules are developed using a divide-and-conquer approach; modules at different temporal and spatial scales are integrated through transfer variables. We further propose a supervised learning procedure based on information geometry to combine model and data for both knowledge discovery and model extension or advances. We finally discuss the recent formation of a global consortium, which includes experts in plant biology, computer science, statistics, agronomy, phenomics, etc. aiming to expedite the development and application of ePlant or its equivalents by promoting a new model development paradigm where models are developed as a community effort instead of driven mainly by individual labs＇ effort. Conclusions： ePlant, as a major research tool to support quantitative and predictive plant science research, will play a crucial role in the future model guided crop engineering, breeding and agronomy.展开更多
A large number of genes related to source, sink,and flow have been identified after decades of research in plant genetics. Unfortunately, these genes have not been effectively utilized in modern crop breeding. This pe...A large number of genes related to source, sink,and flow have been identified after decades of research in plant genetics. Unfortunately, these genes have not been effectively utilized in modern crop breeding. This perspective paper aims to examine the reasons behind such a phenomenon and propose a strategy to resolve this situation. Specifically, we first systematically survey the currently cloned genes related to source, sink, and flow;then we discuss three factors hindering effective application of these identified genes, which include the lack of effective methods to identify limiting or critical steps in a signaling network, the misplacement of emphasis on properties, at the leaf, instead of the whole canopy level,and the non-linear complex interaction between source,sink, and flow. Finally, we propose the development of systems models of source, sink and flow, together with a detailed simulation of interactions between them and their surrounding environments, to guide effective use of the identified elements in modern rice breeding. These systems models will contribute directly to the definition of crop ideotype and also identification of critical features and parameters that limit the yield potential in current cultivars.展开更多
基金supported by the National Natural Science Foundation of China(32088102,31730103,31825003,32050081,and 31870218)the CAS Project for Young Scientists in Basic Research(YSBR-011)+2 种基金the Strategic Priority Research Program “Molecular Mechanism of Plant Growth and Development”of the Chinese Academy of Sciences(XDB27040207)the National Key R&D Program of China(2019YFA0904703 and 2016YFA0500502)the Young Elite Scientists Sponsorship Program by CAST(20202022QNRC001/2/3)。
基金The work in XGZ＇s lab is supported by CAS strategic leading project on designer breeding by molecular module （No. XDA08020301）, the National High Technology Development Plan of the Ministry of Science and Technology of China （2014AA101601）, the National Natural Science Foundation of China （No. C020401）, the National Key Basic Research Program of China （No. 2015CB150104）, Bill and Melinda Gates Foundation （No. OPP1060461）, CAS-CSIRO Cooperative Research Program （No. GJHZ1501）.
文摘Background： The increase in global population, climate change and stagnancy in crop yield on unit land area basis in recent decades urgently call for a new approach to support contemporary crop improvements, ePlant is a mathematical model of plant growth and development with a high level of mechanistic details to meet this challenge. Results： ePlant integrates modules developed for processes occurring at drastically different temporal （10-8-106 seconds） and spatial （10-10-10 meters） scales, incorporating diverse physical, biophysical and biochemical processes including gene regulation, metabolic reaction, substrate transport and diffusion, energy absorption, transfer and conversion, organ morphogenesis, plant environment interaction, etc. Individual modules are developed using a divide-and-conquer approach; modules at different temporal and spatial scales are integrated through transfer variables. We further propose a supervised learning procedure based on information geometry to combine model and data for both knowledge discovery and model extension or advances. We finally discuss the recent formation of a global consortium, which includes experts in plant biology, computer science, statistics, agronomy, phenomics, etc. aiming to expedite the development and application of ePlant or its equivalents by promoting a new model development paradigm where models are developed as a community effort instead of driven mainly by individual labs＇ effort. Conclusions： ePlant, as a major research tool to support quantitative and predictive plant science research, will play a crucial role in the future model guided crop engineering, breeding and agronomy.
基金Research funding by the CAS Strategic Leading Project (XDA08020301)National Natural Science Foundation of China (31501240)+4 种基金the open funding from State Key Laboratory of Hybrid Rice (2016KF06)the CAS-CSIRO collaboration grant (GJHZ1501)National Key Research and Development Program of China (2017YFD0301502)the project of Hunan Provincial Natural Science Foundation of China (2018JJ2286)the project of Hunan Academy of Agricultural Sciences (2017JC04)
文摘A large number of genes related to source, sink,and flow have been identified after decades of research in plant genetics. Unfortunately, these genes have not been effectively utilized in modern crop breeding. This perspective paper aims to examine the reasons behind such a phenomenon and propose a strategy to resolve this situation. Specifically, we first systematically survey the currently cloned genes related to source, sink, and flow;then we discuss three factors hindering effective application of these identified genes, which include the lack of effective methods to identify limiting or critical steps in a signaling network, the misplacement of emphasis on properties, at the leaf, instead of the whole canopy level,and the non-linear complex interaction between source,sink, and flow. Finally, we propose the development of systems models of source, sink and flow, together with a detailed simulation of interactions between them and their surrounding environments, to guide effective use of the identified elements in modern rice breeding. These systems models will contribute directly to the definition of crop ideotype and also identification of critical features and parameters that limit the yield potential in current cultivars.
