Laboratório de Biometria, Universidade Federal de Viçosa, Viçosa, Minas Gerais 36570-900, Brazil.
Sweet Corn Breeding and Genomics Lab, University of Florida, Gainesville, FL 32611, USA.
G3 (Bethesda). 2024 Aug 7;14(8). doi: 10.1093/g3journal/jkae128.
Genomic selection and doubled haploids hold significant potential to enhance genetic gains and shorten breeding cycles across various crops. Here, we utilized stochastic simulations to investigate the best strategies for optimize a sweet corn breeding program. We assessed the effects of incorporating varying proportions of old and new parents into the crossing block (3:1, 1:1, 1:3, and 0:1 ratio, representing different degrees of parental substitution), as well as the implementation of genomic selection in two distinct pipelines: one calibrated using the phenotypes of testcross parents (GSTC scenario) and another using F1 individuals (GSF1). Additionally, we examined scenarios with doubled haploids, both with (DH) and without (DHGS) genomic selection. Across 20 years of simulated breeding, we evaluated scenarios considering traits with varying heritabilities, the presence or absence of genotype-by-environment effects, and two program sizes (50 vs 200 crosses per generation). We also assessed parameters such as parental genetic mean, average genetic variance, hybrid mean, and implementation costs for each scenario. Results indicated that within a conventional selection program, a 1:3 parental substitution ratio (replacing 75% of parents each generation with new lines) yielded the highest performance. Furthermore, the GSTC model outperformed the GSF1 model in enhancing genetic gain. The DHGS model emerged as the most effective, reducing cycle time from 5 to 4 years and enhancing hybrid gains despite increased costs. In conclusion, our findings strongly advocate for the integration of genomic selection and doubled haploids into sweet corn breeding programs, offering accelerated genetic gains and efficiency improvements.
基因组选择和加倍单倍体在各种作物中具有显著的潜力，可以提高遗传增益并缩短育种周期。在这里，我们利用随机模拟来研究优化甜玉米育种计划的最佳策略。我们评估了在杂交群体中纳入不同比例的旧亲本和新亲本的效果（3:1、1:1、1:3 和 0:1 比例，代表不同程度的亲本替代），以及在两个不同管道中实施基因组选择的效果：一个使用测验交亲本的表型进行校准（GSTC 情景），另一个使用 F1 个体进行校准（GSF1）。此外，我们还研究了加倍单倍体的情景，包括使用（DH）和不使用（DHGS）基因组选择的情景。在 20 年的模拟育种中，我们评估了考虑具有不同遗传力、基因型-环境效应存在或不存在以及两种方案规模（每代 50 对与 200 对杂交）的情景。我们还评估了每个情景的亲本遗传平均值、平均遗传方差、杂种平均值和实施成本等参数。结果表明，在常规选择方案中，1:3 的亲本替代比例（每代用新系替代 75%的亲本）可获得最高的表现。此外，GSTC 模型在提高遗传增益方面优于 GSF1 模型。DHGS 模型是最有效的，尽管成本增加，但它将周期时间从 5 年缩短到 4 年，并提高了杂种增益。总之，我们的研究结果强烈支持将基因组选择和加倍单倍体纳入甜玉米育种计划，以实现加速的遗传增益和效率提高。
