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Modelling selection response in plant breeding programs using crop models as mechanistic gene-to-phenotype (CGM-G2P) multi-trait link functions
bioRxiv - Genetics Pub Date : 2020-10-14 , DOI: 10.1101/2020.10.13.338301
M Cooper , O Powell , KP Voss-Fels , CD Messina , C Gho , DW Podlich , F Technow , SC Chapman , CA Beveridge , D Ortiz-Barientos , GL Hammer

Plant breeding programs are designed and operated over multiple cycles to systematically change the genetic makeup of plants to achieve improved trait performance for a Target Population of Environments (TPE). Within each cycle, selection applied to the standing genetic variation within a structured reference population of genotypes (RPG) is the primary mechanism by which breeding programs make the desired genetic changes. Selection operates to change the frequencies of the alleles of the genes controlling trait variation within the RPG. The structure of the RPG and the TPE has important implications for the design of optimal breeding strategies. The breeder's equation, together with the quantitative genetic theory behind the equation, informs many of the principles for design of breeding programs. The breeder's equation can take many forms depending on the details of the breeding strategy. Through the genetic changes achieved by selection, the cultivated varieties of crops (cultivars) are improved for use in agriculture. From a breeding perspective, selection for specific trait combinations requires a quantitative link between the effects of the alleles of the genes impacted by selection and the trait phenotypes of plants and their breeding value. This gene-to-phenotype link function provides the G2P map for one to many traits. For complex traits controlled by many genes, the infinitesimal model for trait genetic variation is the dominant G2P model of quantitative genetics. Here we consider motivations and potential benefits of using the hierarchical structure of crop models as CGM-G2P trait link functions in combination with the infinitesimal model for the design and optimisation of selection in breeding programs.

中文翻译:

使用作物模型作为机制基因对表型(CGM-G2P)多性状链接函数的植物育种程序中的选择响应建模

植物育种程序的设计和运行需要多个周期,以系统地改变植物的基因组成,从而为目标环境种群(TPE)实现更高的性状表现。在每个周期内,选择用于结构化参考基因型参考种群(RPG)内常规遗传变异的选择是育种程序进行所需遗传改变的主要机制。选择操作改变RPG内控制性状变异的基因的等位基因的频率。RPG和TPE的结构对最佳育种策略的设计具有重要意义。育种者的方程式以及该方程式背后的定量遗传理论,为育种程序设计提供了许多原理。饲养员 s方程可以采用多种形式,具体取决于育种策略的细节。通过选择实现的遗传变化,改良了农作物(栽培品种)的栽培品种,可用于农业。从育种的角度来看,选择特定性状组合需要在选择影响的基因等位基因的作用与植物的性状表型及其育种价值之间建立定量联系。这个基因-表型链接功能提供了一对多性状的G2P图。对于由许多基因控制的复杂性状,性状遗传变异的无穷小模型是定量遗传学的主要G2P模型。
更新日期:2020-10-16
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