RR-BLUP方法预测玉米自交系M54测交后代产量  

Genomic Prediction of Hybrid Yield Performance Testcross to Inbred Line M54 Using the RR-BLUP Model

作　　者：张健 陈岩 李永军 Zhang Jian;Chen Yan;Li Yongjun(Institute of Sandy Land Control and Utilization,Fuxin,123000)

机构地区：[1]辽宁省沙地治理与利用研究所,阜新123000

出　　处：《分子植物育种》2020年第24期8267-8272,共6页Molecular Plant Breeding

摘　　要：基因组选择是一种适用于动植物数量性状改良的分子标记辅助选择策略,与传统的分子标记辅助选择策略(连锁分析和关联分析)相比,基因组选择不需要事先确定一个统计检验效应显著的分子标记子集,而是直接使用分布于全基因组的分子标记预测育种值或基因型值。基因组选择在动物和林木育种中已经得到实际应用。随着以SNP为代表的高通量分子标记技术的发展,测定育种材料全基因组分子标记的成本不断降低,如果能运用杂交亲本的基因组标记来预测杂交组合产量表现,将会减少参加田间试验的杂交组合的数量,提高育种效率,节约育种成本。本研究提出了一种在固定测验种条件下运用RR-BLUP模型预测杂交组合产量表现的应用模式。以优良玉米自交系M54为测验种,与一个双亲后代的分离衍生的高代近交系群体组配杂交组合,使用R语言Synbreed软件包中的RR-BLUP模型估计了测交群体内SNP标记效应,并进行了5重交叉验证,相关系数的平均值在0.67左右,达到中等相关水平。Genome selection is a molecular marker assisted selection strategy which is suitable for the improvement of quantitative traits.Compared with the traditional marker assisted selection strategies(Linkage Analysis and Association Analysis),genome selection does not need to determine a subset of molecular markers with significant statistical testing effect in advance,but directly uses the molecular markers distributed throughout the whole genome to predict breeding value or genotype value.Genome selection has been applied in animal and forest breeding already.With the development of high-throughput molecular marker technology represented by SNP,the cost of genotyping has been continuously reduced.Based on the actual situation of Chinese maize breeding,Tihs study proposed an application mode using RR-BLUP model to predict the yield performance testcross to only one fixed testline.We investigate the hybrid yield performance of a segregated population derived from the double parents Chang7-2 and LM-1 testcross to testline M54.A RR-BLUP model is fitted to estimate the SNP effects inside the testcross population using the R package synbreed.In the five-fold cross validation,the average correlation coefficient was 0.67,reaching a medium correlation level.

关 键 词：RR-BLUP 基因组选择 测交 产量 

分 类 号：S513[农业科学—作物学]