Genomic prediction, the joint analysis of high-density molecular marker data and phenotype to predict the performance of individuals for breeding purpose, is now a method used in routine in many plant and animal breeding programs. This opens several new design questions such as how to select a subset of preexisting individuals for phenotyping based on the molecular marker data to estimate marker effects with the highest precision, in hybrid species, how to choose the hybrids combination to create and phenotype to best predict the performance of the unobserved hybrid combinations and last from a list of individuals, which new populations of individuals to create to optimize marker effects estimation with a budget constraint. Those three designs questions are interrelated and critical to improve the efficiency of breeding. In this article we present efficient optimization methods to answer those three designs questions. Validation results using real data and simulations are presented. Results show that in several situations significant gain in precision of evaluation of selection candidates and marker effects are possible to help increase further the efficiency of plant breeding.

中文翻译：

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用于基因组预测的选择性表型和种群设计的优化

基因组预测，即高密度分子标记数据和表型的联合分析以预测个体的性能以进行育种，现在已成为许多植物和动物育种计划中常规使用的方法。这开启了几个新的设计问题，例如如何根据分子标记数据选择预先存在的个体子集进行表型分析，以最高精度估计杂交物种中的标记效应，如何选择要创建的杂交组合和最佳预测的表型未观察到的混合组合的性能，最后来自一个个体列表，创建新的个体群体以优化具有预算约束的标记效应估计。这三个设计问题相互关联，对提高育种效率至关重要。在本文中，我们提出了有效的优化方法来回答这三个设计问题。提供了使用真实数据和模拟的验证结果。结果表明，在几种情况下，选择候选物的评估精度和标记效应的显着提高可能有助于进一步提高植物育种的效率。