In plant breeding, selecting cross‐combinations that are more likely to result in superior lines for cultivar development is critical. This step, however, is subjective with decisions being based on available genomic and phenotypic data for prospective parents. Genomic prediction (GP) provides new opportunities to accelerate genetic gain for a target trait by identifying superior crosses through simulation of progeny performance. In this context, this study deployed GP using the phenotype and genotype of potential parents to predict the progeny genetic variance (VG) and means of overall, inferior 10%, and superior 10% (μ, μip, and μsp, respectively). This retrospective experimental design investigated whether the crosses that produced superior soft red winter wheat breeding lines would have been made if progeny simulations had guided crossing decisions of breeding programs. Here, data from historical wheat breeding lines were used to train GP models and predict VG and means for yield, test weight, heading date, and plant height for all combinations of 217 parents. Predicted and observed data for 670 lines derived from biparental crosses were compared to assess the accuracy of progeny simulations, and low‐to‐moderate prediction accuracy was observed for the four traits (0.25–0.52). Of the pedigrees that produced lines that were selected and advanced into later stage nurseries, 76% were predicted to give rise to progeny with above‐average yield. The moderate correlation found between predicted progeny means and observed line per se performance justifies using cross‐combination prediction as a tool to reduce crossing number and focus on segregating populations that harbor future cultivars.

中文翻译：

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使用基因组学预测冬小麦的优良杂交：评估准确性的回顾性研究


在植物育种中，选择更有可能产生优良品系的杂交组合对于品种开发至关重要。然而，这一步骤是主观的，因为决策是基于准父母可用的基因组和表型数据。基因组预测（GP）通过模拟后代表现来识别优良杂交，为加速目标性状的遗传增益提供了新的机会。在此背景下，本研究部署了 GP，使用潜在亲本的表型和基因型来预测后代遗传方差 (VG) 以及整体、劣 10% 和优 10% 的平均值（分别为 μ、μip 和 μsp）。这项回顾性实验设计调查了如果后代模拟指导育种计划的杂交决策，是否会产生产生优质软红冬小麦育种品系的杂交。在这里，来自历史小麦育种系的数据用于训练 GP 模型并预测 217 个亲本的所有组合的 VG 和产量、检重、抽穗日期和株高平均值。对来自双亲杂交的 670 个品系的预测和观察数据进行了比较，以评估后代模拟的准确性，观察到四个性状的预测准确性为低至中等（0.25-0.52）。在被选择并进入后期苗圃的品系系谱中，预计 76% 的后代产量将高于平均水平。在预测的后代平均值和观察到的品系本身性能之间发现的适度相关性证明使用交叉组合预测作为减少杂交数量并专注于分离包含未来品种的群体的工具是合理的。