Yabe Shiori, Hara Takashi, Ueno Mariko, Enoki Hiroyuki, Kimura Tatsuro, Nishimura Satoru, Yasui Yasuo, Ohsawa Ryo, Iwata Hiroyoshi
Graduate School of Agricultural and Life Sciences, University of Tokyo, Tokyo, Japan.
Graduate School of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan.
Front Plant Sci. 2018 Mar 21;9:276. doi: 10.3389/fpls.2018.00276. eCollection 2018.
To evaluate the potential of genomic selection (GS), a selection experiment with GS and phenotypic selection (PS) was performed in an allogamous crop, common buckwheat ( Moench). To indirectly select for seed yield per unit area, which cannot be measured on a single-plant basis, a selection index was constructed from seven agro-morphological traits measurable on a single plant basis. Over 3 years, we performed two GS and one PS cycles per year for improvement in the selection index. In GS, a prediction model was updated every year on the basis of genotypes of 14,598-50,000 markers and phenotypes. Plants grown from seeds derived from a series of generations of GS and PS populations were evaluated for the traits in the selection index and other yield-related traits. GS resulted in a 20.9% increase and PS in a 15.0% increase in the selection index in comparison with the initial population. Although the level of linkage disequilibrium in the breeding population was low, the target trait was improved with GS. Traits with higher weights in the selection index were improved more than those with lower weights, especially when prediction accuracy was high. No trait changed in an unintended direction in either GS or PS. The accuracy of genomic prediction models built in the first cycle decreased in the later cycles because the genetic bottleneck through the selection cycles changed linkage disequilibrium patterns in the breeding population. The present study emphasizes the importance of updating models in GS and demonstrates the potential of GS in mass selection of allogamous crop species, and provided a pilot example of successful application of GS to plant breeding.
为评估基因组选择(GS)的潜力,在异花授粉作物普通荞麦(蓼科)上进行了一项GS与表型选择(PS)的选择实验。为间接选择无法在单株基础上测量的单位面积种子产量,根据可在单株基础上测量的七个农艺形态性状构建了一个选择指数。在3年时间里,我们每年进行两个GS周期和一个PS周期以提高选择指数。在GS中,每年根据14598 - 50000个标记的基因型和表型更新预测模型。对从GS和PS群体的一系列世代衍生的种子长成的植株进行选择指数性状和其他产量相关性状的评估。与初始群体相比,GS使选择指数提高了20.9%,PS使选择指数提高了15.0%。尽管育种群体中的连锁不平衡水平较低,但GS仍改善了目标性状。选择指数中权重较高的性状比权重较低的性状改善得更多,尤其是在预测准确性较高时。在GS或PS中,没有性状朝着意外的方向变化。由于选择周期中的遗传瓶颈改变了育种群体中的连锁不平衡模式,第一个周期构建的基因组预测模型的准确性在后续周期中有所下降。本研究强调了在GS中更新模型的重要性,并证明了GS在异花授粉作物物种大规模选择中的潜力,还提供了GS成功应用于植物育种的一个试点实例。