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Genomic Selection in Preliminary Yield Trials in a Winter Wheat Breeding Program

机译:冬小麦育种计划初步产量试验中的基因组选择

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摘要

Genomic prediction (GP) is now routinely performed in crop plants to predict unobserved phenotypes. The use of predicted phenotypes to make selections is an active area of research. Here, we evaluate GP for predicting grain yield and compare genomic and phenotypic selection by tracking lines advanced. We examined four independent nurseries of F3:6 and F3:7 lines trialed at 6 to 10 locations each year. Yield was analyzed using mixed models that accounted for experimental design and spatial variations. Genotype-by-sequencing provided nearly 27,000 high-quality SNPs. Average genomic predictive ability, estimated for each year by randomly masking lines as missing in steps of 10% from 10 to 90%, and using the remaining lines from the same year as well as lines from other years in a training set, ranged from 0.23 to 0.55. The predictive ability estimated for a new year using the other years ranged from 0.17 to 0.28. Further, we tracked lines advanced based on phenotype from each of the four F3:6 nurseries. Lines with both above average genomic estimated breeding value (GEBV) and phenotypic value (BLUP) were retained for more years compared to lines with either above average GEBV or BLUP alone. The number of lines selected for advancement was substantially greater when predictions were made with 50% of the lines from the testing year added to the training set. Hence, evaluation of only 50% of the lines yearly seems possible. This study provides insights to assess and integrate genomic selection in breeding programs of autogamous crops.
机译:现在,通常在农作物中进行基因组预测(GP)以预测未观察到的表型。使用预测表型进行选择是一个活跃的研究领域。在这里,我们评估GP来预测谷物产量,并通过跟踪行来比较基因组和表型选择。我们检查了每年在6至10个地点试行的F3:6和F3:7品系的四个独立苗圃。使用考虑了实验设计和空间变化的混合模型分析了产量。测序基因型提供了近27,000个高质量SNP。平均基因组预测能力,每年通过随机掩盖品系(从10%到90%以10%的步长缺失),并使用同一年的剩余品系以及训练集中其他年份的品系来估算,为0.23至0.55。使用其他年份估算的新一年的预测能力在0.17至0.28之间。此外,我们追踪了基于F3:6四个苗圃中每个苗圃的表型而前进的品系。与仅具有高于平均GEBV或BLUP的品系相比,具有高于平均基因组估计育种值(GEBV)和表型值(BLUP)的品系被保留了更多年。当将测试年份的50%的行添加到训练集中进行预测时,选择晋升的行数量会大大增加。因此,似乎有可能每年仅评估50%的生产线。这项研究提供了见解,以评估和整合基因选择育种的自配作物。

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