利用玉米F_(1)群体进行玉米全株鲜重的全基因组预测分析

Whole-Genome Predictive Analysis of Fresh Weight per Plant Using the Maize F1 Population

基因组预测是一种可以提高育种效率的分子育种技术。利用中北410(SN915,YH-1)和北农368(60271,2193)的亲本为父本与120个玉米自交系组配4个杂交群体。利用10k的SNP芯片对亲本进行基因分型,在3个环境下对4个群体的全株鲜重进行评价。结果表明,从环境来看,甘肃种植的全株鲜重最高;从群体来看,群体2的鲜重最高;4个群体的变异系数为0.27~0.33,表明4个测交群体的表型变异较大。通过实施一对一(利用其中一个群体为训练群体分别预测其他群体)以及多对一(利用3个群体及第4个群体的一半作为训练群体预测第4个群体的另一半)的预测方案,表明杂交群体间(一对一)的基因组预测准确性低于群体内(多对一)的基因组预测准确性,亲缘关系近的群体间预测效果更好。通过在训练群体中加入与预测群体有亲缘关系的材料可以改进基因组预测的效果。

Genomic prediction is a molecular technique that can improve the efficiency of molecular breeding.In this study,120 maize inbred lines were crossed to the parents of Zhongbei 410(SN915,YH-1)and Beinong 368(60271,2193)to construct four testcross populations.The 10k SNP chip was used to genotype the parental lines,and the whole-plant fresh weight of the four populations were evaluated in three environments.The results showed that the fresh weight was highest in Gansu environment,and population 2 had the highest whole plant fresh weight.The coefficients of variances of the four populations ranged from 0.27 to 0.33,indicating the phenotypic variations of the four populations were great.By implementing the one-to-one(one population was used as the training population to predict other populations)and multiple-to-one(three populations and a half of the forth population were used as the training population to predict the other half of the forth population)prediction schemes,we found that the prediction accuracy of one-to-one genome prediction was lower than that of the multiple-to-one prediction,and closely related groups predicted better.The accuracy of genomic prediction could be improved by adding the relatives of the prediction population in the training population and optimizing the relationship between the training population and the predicted population.