National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100094, China; Frontiers Science Center for Molecular Design Breeding, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100094, China.
National Maize Improvement Center, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100094, China; Frontiers Science Center for Molecular Design Breeding, College of Agronomy and Biotechnology, China Agricultural University, Beijing 100094, China.
Plant Commun. 2023 May 8;4(3):100548. doi: 10.1016/j.xplc.2023.100548. Epub 2023 Jan 11.
Phenotypic plasticity, the ability of an individual to alter its phenotype in response to changes in the environment, has been proposed as a target for breeding crop varieties with high environmental fitness. Here, we used phenotypic and genotypic data from multiple maize (Zea mays L.) populations to mathematically model phenotypic plasticity in response to the environment (PPRE) in inbred and hybrid lines. PPRE can be simply described by a linear model in which the two main parameters, intercept a and slope b, reflect two classes of genes responsive to endogenous (class A) and exogenous (class B) signals that coordinate plant development. Together, class A and class B genes contribute to the phenotypic plasticity of an individual in response to the environment. We also made connections between phenotypic plasticity and hybrid performance or general combining ability (GCA) of yield using 30 F hybrid populations generated by crossing the same maternal line with 30 paternal lines from different maize heterotic groups. We show that the parameters a and b from two given parental lines must be concordant to reach an ideal GCA of F yield. We hypothesize that coordinated regulation of the two classes of genes in the F hybrid genome is the basis for high GCA. Based on this theory, we built a series of predictive models to evaluate GCA in silico between parental lines of different heterotic groups.
表型可塑性，即个体在环境变化时改变表型的能力，被认为是培育具有高环境适应性的作物品种的目标。在这里，我们使用来自多个玉米（Zea mays L.）群体的表型和基因型数据，通过数学模型来模拟自交系和杂交系对环境的表型可塑性响应（PPRE）。PPRE 可以简单地用一个线性模型来描述，其中两个主要参数，截距 a 和斜率 b，反映了对内在（A 类）和外在（B 类）信号做出响应的两类基因，这些信号协调植物的发育。A 类和 B 类基因共同影响个体对环境的表型可塑性。我们还通过 30 个由同一母本与 30 个来自不同玉米杂种群的父本杂交产生的 F1 杂交群体，将表型可塑性与杂种表现或产量的一般配合力（GCA）联系起来。我们表明，两个给定亲本系的参数 a 和 b 必须一致，才能达到 F1 产量的理想 GCA。我们假设，F1 杂种基因组中两类基因的协调调控是高 GCA 的基础。基于这一理论，我们构建了一系列预测模型，以在不同杂种群的亲本系之间进行虚拟的 GCA 评估。
