USDA-ARS, RW Holley Center for Agriculture and Health, Ithaca, NY 14853, USA.
Genet Sel Evol. 2010 Aug 16;42(1):35. doi: 10.1186/1297-9686-42-35.
Simulation and empirical studies of genomic selection (GS) show accuracies sufficient to generate rapid gains in early selection cycles. Beyond those cycles, allele frequency changes, recombination, and inbreeding make analytical prediction of gain impossible. The impacts of GS on long-term gain should be studied prior to its implementation.
A simulation case-study of this issue was done for barley, an inbred crop. On the basis of marker data on 192 breeding lines from an elite six-row spring barley program, stochastic simulation was used to explore the effects of large or small initial training populations with heritabilities of 0.2 or 0.5, applying GS before or after phenotyping, and applying additional weight on low-frequency favorable marker alleles. Genomic predictions were from ridge regression or a Bayesian analysis.
Assuming that applying GS prior to phenotyping shortened breeding cycle time by 50%, this practice strongly increased early selection gains but also caused the loss of many favorable QTL alleles, leading to loss of genetic variance, loss of GS accuracy, and a low selection plateau. Placing additional weight on low-frequency favorable marker alleles, however, allowed GS to increase their frequency earlier on, causing an initial increase in genetic variance. This dynamic led to higher long-term gain while mitigating losses in short-term gain. Weighted GS also increased the maintenance of marker polymorphism, ensuring that QTL-marker linkage disequilibrium was higher than in unweighted GS.
Losing favorable alleles that are in weak linkage disequilibrium with markers is perhaps inevitable when using GS. Placing additional weight on low-frequency favorable alleles, however, may reduce the rate of loss of such alleles to below that of phenotypic selection. Applying such weights at the beginning of GS implementation is important.
基因组选择(GS)的模拟和实证研究表明,其准确性足以在早期选择周期中产生快速增益。超出这些周期后,等位基因频率变化、重组和近交使得增益的分析预测变得不可能。在实施 GS 之前,应该研究其对长期增益的影响。
针对高度自交的作物大麦,进行了这一问题的模拟案例研究。基于来自一个六棱春大麦精英计划的 192 个育种系的标记数据,采用随机模拟方法,探讨了初始训练群体大小(大或小)、遗传率(0.2 或 0.5)、GS 在表型之前或之后的应用,以及对低频有利标记等位基因的附加权重的影响。基因组预测是基于岭回归或贝叶斯分析。
假设在表型之前应用 GS 可以将育种周期缩短 50%,这种做法虽然强烈增加了早期选择增益,但也导致了许多有利 QTL 等位基因的丢失,从而导致遗传方差丧失、GS 准确性丧失和选择平台降低。然而,对低频有利标记等位基因施加额外权重,可以使 GS 更早地增加它们的频率,从而导致遗传方差的初始增加。这种动态导致了更高的长期增益,同时减轻了短期增益的损失。加权 GS 还增加了标记多态性的维持,确保了 QTL-标记连锁不平衡高于未加权 GS。
在使用 GS 时,丢失与标记弱连锁的有利等位基因可能是不可避免的。然而,对低频有利等位基因施加额外权重可能会降低这些等位基因的丢失速度,使其低于表型选择的速度。在 GS 实施开始时应用这些权重很重要。