{"title":"Simulating grass phenotypic plasticity as an emergent property of growth zone responses to carbon and nitrogen metabolites","authors":"Marion Gauthier, R. Barillot, B. Andrieu","doi":"10.1093/insilicoplants/diab034","DOIUrl":null,"url":null,"abstract":"\n Phenotypic plasticity - the ability of one genotype to produce different phenotypes depending on growth conditions - is a core aspect of the interactions between plants and the environment. The model CN-Wheat simulates the functioning of a grass culm and the construction of traits as properties emerging from the feedback loops between morphogenesis, the environmental factors and source–sink activities. The plant is seen as a self-regulated system where leaf growth is driven by carbon and nitrogen metabolism within each leaf and by coordination rules between successive leaves. Here, we investigated the ability of this approach to simulate realistic grass phenotypic plasticity and explored plant behaviour in a wide range of growth conditions.The growth of grass monoculms, with traits similar to a wheat stem, was simulated for highly contrasting conditions of soil nitrogen concentration, incident light and planting density. The monoculms were kept vegetative and produced ~15 mature leaves at the end of the simulations. The model simulated highly contrasting phenotypes. Overall, the simulated trends and the magnitude of responses of leaf and plant traits to growth conditions were consistent with the literature on grass species. These results demonstrate that integrating plant functioning at organ scale can simulate, as an emergent property, the phenotypic plasticity of plants in contrasting light and nitrogen conditions. Besides, simulations of the internal variables of plants gave access to plant trophic status across plant ontogeny and plant environments. In conclusion, this framework is a significant step towards better integration of the genotype-environment interactions.","PeriodicalId":36138,"journal":{"name":"in silico Plants","volume":" ","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2021-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"in silico Plants","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/insilicoplants/diab034","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRONOMY","Score":null,"Total":0}
引用次数: 2
Abstract
Phenotypic plasticity - the ability of one genotype to produce different phenotypes depending on growth conditions - is a core aspect of the interactions between plants and the environment. The model CN-Wheat simulates the functioning of a grass culm and the construction of traits as properties emerging from the feedback loops between morphogenesis, the environmental factors and source–sink activities. The plant is seen as a self-regulated system where leaf growth is driven by carbon and nitrogen metabolism within each leaf and by coordination rules between successive leaves. Here, we investigated the ability of this approach to simulate realistic grass phenotypic plasticity and explored plant behaviour in a wide range of growth conditions.The growth of grass monoculms, with traits similar to a wheat stem, was simulated for highly contrasting conditions of soil nitrogen concentration, incident light and planting density. The monoculms were kept vegetative and produced ~15 mature leaves at the end of the simulations. The model simulated highly contrasting phenotypes. Overall, the simulated trends and the magnitude of responses of leaf and plant traits to growth conditions were consistent with the literature on grass species. These results demonstrate that integrating plant functioning at organ scale can simulate, as an emergent property, the phenotypic plasticity of plants in contrasting light and nitrogen conditions. Besides, simulations of the internal variables of plants gave access to plant trophic status across plant ontogeny and plant environments. In conclusion, this framework is a significant step towards better integration of the genotype-environment interactions.