首页> 外文期刊>Theoretical and Applied Genetics: International Journal of Breeding Research and Cell Genetics >Factor analytic and reduced animal models for the investigation of additive genotype-by-environment interaction in outcrossing plant species with application to a Pinus radiata breeding programme
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Factor analytic and reduced animal models for the investigation of additive genotype-by-environment interaction in outcrossing plant species with application to a Pinus radiata breeding programme

机译:因子分析和简化动物模型,用于研究异源植物物种中加性基因-环境相互作用及其在辐射松育种计划中的应用

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Modelling additive genotype-by-environment interaction is best achieved with the use of factor analytic models. With numerous environments and for outcrossing plant species, computation is facilitated using reduced animal models. The development of efficient plant breeding strategies requires a knowledge of the magnitude and structure of genotype-by-environment interaction. This information can be obtained from appropriate linear mixed model analyses of phenotypic data from multi-environment trials. The use of factor analytic models for genotype-by-environment effects is known to provide a reliable, parsimonious and holistic approach for obtaining estimates of genetic correlations between all pairs of trials. When breeding for outcrossing species the focus is on estimating additive genetic correlations and effects which is achieved by including pedigree information in the analysis. The use of factor analytic models in this setting may be computationally prohibitive when the number of environments is moderate to large. In this paper, we present an approach that uses an approximate reduced animal model to overcome the computational issues associated with factor analytic models for additive genotype-by-environment effects. The approach is illustrated using a Pinus radiata breeding dataset involving 77 trials, located in environments across New Zealand and south eastern Australia, and with pedigree information on 315,581 trees. Using this approach we demonstrate the existence of substantial additive genotype-by-environment interaction for the trait of stem diameter measured at breast height. This finding has potentially significant implications for both breeding and deployment strategies. Although our approach has been developed for forest tree breeding programmes, it is directly applicable for other outcrossing plant species, including sugarcane, maize and numerous horticultural crops
机译:使用因素分析模型可以最好地实现对添加剂基因型-环境相互作用的建模。在众多环境中以及对于跨物种的植物,使用简化的动物模型可简化计算。有效植物育种策略的发展需要了解基因型-环境相互作用的强度和结构。这些信息可以从对多环境试验的表型数据进行适当的线性混合模型分析中获得。众所周知,使用因子分析模型进行逐个环境基因型分析可提供一种可靠,简约和整体的方法来获得所有试验对之间的遗传相关性估计。在为异种进行育种时,重点是估计可加遗传相关性和效应,这是通过在分析中加​​入系谱信息来实现的。当环境的数量为中等到较大时,在这种情况下使用因子分析模型可能会在计算上受到限制。在本文中,我们提出了一种使用近似的简化动物模型来克服与因子分析模型相关的计算问题的方法,以实现逐个环境附加基因型的影响。使用辐射松育种数据集对这种方法进行了说明,该数据集涉及77个试验,分布在新西兰和澳大利亚东南部的环境中,并带有315,581棵树的系谱信息。使用这种方法,我们证明了在乳房高度测量的茎径性状存在大量的累加基因型-逐环境相互作用。这一发现对育种和部署策略都有潜在的重大影响。尽管我们的方法是针对林木育种计划而开发的,但它直接适用于其他异类植物物种,包括甘蔗,玉米和许多园艺作物

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