Advanced Plant Technology Program, Clemson University, Clemson, SC 29634, USA.
Department of Plant and Environmental Sciences, Clemson University, Clemson, SC 29634, USA.
G3 (Bethesda). 2023 Apr 11;13(4). doi: 10.1093/g3journal/jkac311.
Hybrid breeding in sorghum [Sorghum bicolor (L.) Moench] utilizes the cytoplasmic-nuclear male sterility (CMS) system for seed production and subsequently harnesses heterosis. Since the cost of developing and evaluating inbred and hybrid lines in the CMS system is costly and time-consuming, genomic prediction of parental lines and hybrids is based on genetic data genotype. We generated 602 hybrids by crossing two female (A) lines with 301 diverse and elite male (R) lines from the sorghum association panel and collected phenotypic data for agronomic traits over two years. We genotyped the inbred parents using whole genome resequencing and used 2,687,342 high quality (minor allele frequency > 2%) single nucleotide polymorphisms for genomic prediction. For grain yield, the experimental hybrids exhibited an average mid-parent heterosis of 40%. Genomic best linear unbiased prediction (GBLUP) for hybrid performance yielded an average prediction accuracy of 0.76-0.93 under the prediction scenario where both parental lines in validation sets were included in the training sets (T2). However, when only female tester was shared between training and validation sets (T1F), prediction accuracies declined by 12-90%, with plant height showing the greatest decline. Mean accuracies for predicting the general combining ability of male parents ranged from 0.33 to 0.62 for all traits. Our results showed hybrid performance for agronomic traits can be predicted with high accuracy, and optimizing genomic relationship is essential for optimal training population design for genomic selection in sorghum breeding.
高粱[高粱 bicolor（L.）Moench]的杂种优势利用细胞质-核雄性不育（CMS）系统进行种子生产，然后利用杂种优势。由于开发和评估 CMS 系统中自交系和杂交系的成本高且耗时，因此基于遗传数据基因型对亲本系和杂交系进行基因组预测。我们通过将两个雌性（A）系与来自高粱协会面板的 301 个不同的和优秀的雄性（R）系杂交，生成了 602 个杂种，并在两年内收集了农艺性状的表型数据。我们使用全基因组重测序对自交系进行了基因型分析，并使用了 2687342 个高质量（次要等位基因频率>2%）单核苷酸多态性进行基因组预测。对于粒重，实验杂种表现出平均中亲杂种优势为 40%。杂种性能的基因组最佳线性无偏预测（GBLUP）在预测情景下，验证集的两个亲本系都包含在训练集中（T2），平均预测准确率为 0.76-0.93。然而，当训练集和验证集仅共享雌性测试者（T1F）时，预测准确率下降了 12-90%，其中株高下降最大。预测所有性状雄性亲本一般配合力的平均准确率范围为 0.33 到 0.62。我们的结果表明，农艺性状的杂种性能可以高精度预测，优化基因组关系对于高粱育种中基因组选择的最优训练群体设计至关重要。
