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A functional-structural model of rice linking quantitative genetic information with morphological development and physiological processes
Authors:Xu Lifeng  Henke Michael  Zhu Jun  Kurth Winfried  Buck-Sorlin Gerhard
Institution:1Institute of Bioinformatics, Zhejiang University, 310029 Hangzhou, P.R. China;2Department of Ecoinformatics, Biometrics and Forest Growth, Georg-August-University Göttingen, Büsgenweg 4, 37077 Göttingen, Germany;3Wageningen UR, Department Biometris, Droevendaalsesteeg 1, 6708 PB Wageningen, The Netherlands
Abstract:

Background and Aims

Although quantitative trait loci (QTL) analysis of yield-related traits for rice has developed rapidly, crop models using genotype information have been proposed only relatively recently. As a first step towards a generic genotype–phenotype model, we present here a three-dimensional functional–structural plant model (FSPM) of rice, in which some model parameters are controlled by functions describing the effect of main-effect and epistatic QTLs.

Methods

The model simulates the growth and development of rice based on selected ecophysiological processes, such as photosynthesis (source process) and organ formation, growth and extension (sink processes). It was devised using GroIMP, an interactive modelling platform based on the Relational Growth Grammar formalism (RGG). RGG rules describe the course of organ initiation and extension resulting in final morphology. The link between the phenotype (as represented by the simulated rice plant) and the QTL genotype was implemented via a data interface between the rice FSPM and the QTLNetwork software, which computes predictions of QTLs from map data and measured trait data.

Key Results

Using plant height and grain yield, it is shown how QTL information for a given trait can be used in an FSPM, computing and visualizing the phenotypes of different lines of a mapping population. Furthermore, we demonstrate how modification of a particular trait feeds back on the entire plant phenotype via the physiological processes considered.

Conclusions

We linked a rice FSPM to a quantitative genetic model, thereby employing QTL information to refine model parameters and visualizing the dynamics of development of the entire phenotype as a result of ecophysiological processes, including the trait(s) for which genetic information is available. Possibilities for further extension of the model, for example for the purposes of ideotype breeding, are discussed.Key words: Functional–structural plant model, ecophysiology, QTL analysis, plant modelling, quantitative genetics
Keywords:
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