摘要
穗长是一个重要的农艺性状,与产量密切相关。一般配合力(general combining ability,GCA)是评价优异自交系的重要指标。因此,解析穗长GCA的遗传基础,制定相应的育种策略对玉米杂交种产量的提高具有重要意义。本研究以123个玉米自交系和8个测验种按照North Carolina II遗传交配设计组配的537个F1杂交种为试验材料,在2个环境下进行表型鉴定,利用玉米5.5 K液相育种芯片鉴定的11,734个SNP(single nucleotide polymorphisms)对2个环境以及综合环境穗长GCA进行多位点全基因组关联分析(multi-locus genome-wide association study,MGWAS)和基因组预测。利用7种MGWAS共检测到11个穗长GCA显著关联SNP标记(P<8.52E-07),单个位点解释GCA变异介于8.06%~28.23%之间。不同MGWAS共定位的SNP位点有5个。位点7_178103602在周口和综合环境利用mrMLM(multi-locus random-SNP-effect mixed linear model)方法重复检测到,可解释穗长GCA变异的26.02%~28.23%,为环境稳定的主效SNP。共挖掘10个候选基因,其中auxin amido synthetase 9和EID1-like F-box protein 2可能是控制穗长GCA的关键基因。5种随机效应模型对3个环境穗长GCA的预测准确性介于0.53~0.69之间,且模型间差异较小。在新乡和周口环境,GBLUP(genomic best linear unbiased prediction)和RKHS(reproducing kernel Hilbert space)整合不同显著位点作为固定效应均可提高穗长GCA基因组估计育种值的准确性,提高率为2.34%~14.98%,而在综合环境中除了利用FarmCPU(fixed and random model circulating probability unification)或BLINK(Bayesian-information and linkage-disequilibrium iteratively nested keyway)鉴定的1个显著位点作为固定效应会略降低预测精度外,其他2种MGWAS方法显著位点的加入均能提高基因组预测力,提高率为2.80%~6.84%。因此,MGWAS显著位点作为固定效应加入预测模型有利于提高穗长GCA基因组估计育种值的准确性,可用来对玉米亲本穗长GCA进行有效预测和选择。
Ear length is an important agronomic trait,which is closely related with yield.General combining ability(GCA)is an important index to evaluate excellent inbred lines.Therefore,the dissection of genetic basis of ear length GCA and formulation of corresponding breeding strategies is of great significance to improve maize yield.In this study,537 F1 hybrids as the experimental materials were obtained from 123 maize inbred lines and eight tester lines according to North Carolina II genetic mating design,and phenotyped under two environments.A total of 11,734 single nucleotide polymorphisms(SNPs)identified using the maize 5.5 K liquid breeding chip were used to conduct multi-locus genome-wide association study(MGWAS)and genomic prediction for ear length GCA in two environments and combined environment.A total of 11 SNPs significantly associated with ear length GCA were detected using seven MGWAS,and the variation of GCA effect explained by a single locus was 8.06%-28.23%.Five SNPs were co-located using different MGWAS.Locus 7_178103602 was repeatedly detected using mrMLM(multi-locus random-SNP-effect mixed linear model)in Zhoukou and combined environment,explaining 26.02%-28.23%of variation of ear length GCA,which was an environment-stable and major-effect SNP.11 candidate genes were identified,among which auxin amido synthetase 9 and EID1-like F-box protein 2 may be key genes for GCA of ear length.The accuracy of five random effect models for predicting ear length GCA ranged from 0.53 to 0.69 in the three environments,and there were minor differences among these models.In Xinxiang and Zhoukou environments,GBLUP(genomic best linear unbiased prediction)and RKHS(reproducing kernel Hilbert space)incorporating different significant loci as fixed effects could improve the accuracy of genomic estimated breeding value for GCA of ear length,with a percentage increase of 2.34%-14.98%.In the combined environment,except that the accuracy was slightly reduced using one significant locus derived from FarmCPU(fixed and random model circulating probability unification)or BLINK(Bayesian-information and linkage-disequilibrium iteratively nested keyway)as fixed effects,the addition of significant loci derived from the other two MGWAS methods could improve the genomic prediction ability,with a percentage increase of 2.80%-6.84%.Therefore,the incorporation of significant loci from MGWAS into the prediction models as fixed effects is helpful to improve the accuracy of the genomic estimated breeding value for ear length GCA,which could be used to effectively predict and select GCA of maize parental ear length.
作者
马娟
朱卫红
刘京宝
宇婷
黄璐
郭国俊
MA Juan;ZHU Wei-Hong;LIU Jing-Bao;YU Ting;HUANG Lu;GUO Guo-Jun(Institute of Cereal Crops,Henan Academy of Agricultural Sciences,Zhengzhou 450002,Henan,China)
出处
《作物学报》
CAS
CSCD
北大核心
2023年第6期1562-1572,共11页
Acta Agronomica Sinica
基金
河南省科技攻关项目(222102110043)
河南省农业科学院优秀青年基金项目(2020YQ04)资助
关键词
穗长
一般配合力
多位点全基因组关联分析
固定效应模型
基因组选择
ear length
general combining ability
multi-locus genome-wide association study
fixed effect model
genomic selection
