中国农业科学 ›› 2022, Vol. 55 ›› Issue (13): 2485-2499.doi: 10.3864/j.issn.0578-1752.2022.13.001

• 作物遗传育种·种质资源·分子遗传学 • 上一篇    下一篇

玉米杂交种穗部性状的全基因组关联分析

李婷(),董远,张君,冯志前,王亚鹏,郝引川,张兴华,薛吉全(),徐淑兔()   

  1. 西北农林科技大学农学院/西北旱区玉米生物与遗传改良重点实验室,陕西杨凌 712100
  • 收稿日期:2022-01-23 接受日期:2022-03-07 出版日期:2022-07-01 发布日期:2022-07-08
  • 通讯作者: 薛吉全,徐淑兔
  • 作者简介:李婷,E-mail: ltstime@163.com
  • 基金资助:
    国家现代农业产业技术体系建设专项(CARS-02-77);杨凌种业创新项目(Ylzy-ym-01)

Genome-Wide Association Study of Ear Related Traits in Maize Hybrids

LI Ting(),DONG Yuan,ZHANG Jun,FENG ZhiQian,WANG YaPeng,HAO YinChuan,ZHANG XingHua,XUE JiQuan(),XU ShuTu()   

  1. College of Agronomy, Northwest A&F University/Key Laboratory of Biology and Genetic Improvement of Maize in Arid Area of Northwest Region, Yangling 712100, Shaanxi
  • Received:2022-01-23 Accepted:2022-03-07 Online:2022-07-01 Published:2022-07-08
  • Contact: JiQuan XUE,ShuTu XU

摘要:

【目的】玉米穗部性状是产量的重要构成因子,利用全基因组关联分析(genome-wide association study,GWAS)方法解析玉米杂交种穗部性状的遗传基础、挖掘与穗部性状相关的位点,为功能基因克隆和高产玉米品种培育提供参考。【方法】选用115份来源于陕A群和陕B群的优良玉米自交系和4份国内骨干作为亲本,以基于NCⅡ遗传交配设计获得的442份玉米杂交种为材料构建关联群体,调查2个环境中群体材料的穗长、穗粗、穗行数等8个穗部性状;利用tGBS技术检测亲本基因型,推测出F1杂交种的19 461个高质量SNP,结合杂交种表型和基因型开展基于加性、显性及上位性模型的穗部性状的全基因组关联分析,并利用公共数据库中玉米穗发育相关组织的转录组数据和基因的注释信息预测候选基因。【结果】表型数据分析结果显示,试验群体的8个穗部性状均符合正态分布,表型变异为3.78%—45.25%。方差分析表明,8个穗部性状的环境效应和基因型效应均呈现极显著水平(P<0.001),广义遗传力为54.15%—68.89%。同时玉米杂交种穗部性状间呈现显著正相关或显著负相关。利用加性和显性模型分别检测到16个和3个显著SNP,上位性模型检测到79个上位性位点。3种模型检测的显著位点累积解释各性状38.21%—60.69%的表型变异,其中,加性模型检测到的显著SNP累积解释的表型变异为0.00—41.26%,上位性模型检测到的位点累积解释的表型变异为15.18%—45.36%。基于加性和显性模型检测的显著SNP的效应分析发现多数位点呈现加性和部分显性效应,仅2个为超显性。进一步分析发现,7个单SNP和5个上位性位点能够解释5%以上的表型变异。根据SNP的位置以及基因的表达信息预测了17个候选基因。【结论】玉米杂交种穗部性状主要受加性、上位性效应影响,显性效应影响较小;加性和显性模型检测的SNP主要表现为加性和部分显性效应,可通过聚合有利等位基因改良目标性状。

关键词: 玉米, 杂交种, 穗部性状, 全基因组关联分析, 遗传效应, 候选基因

Abstract:

【Objective】Ear traits are important components of grain yield in maize. Dissecting their genetic basis and mining significant SNPs using genome-wide association study (GWAS) can provide references for cloning functional genes and breeding high-yield maize varieties. 【Method】A total of 115 superior inbred lines from Shaan A group and Shaan B group, as well as four domestic backbone lines were selected as parents. Based on NCⅡ genetic design, an association population consisting of 442 hybrids was constructed, which was planted in two different environments to collect phenotype data of ear traits. Meanwhile, all parental lines were sequenced by the tunable genotyping by sequencing (tGBS) protocols. According to the genotype of inbred lines, altogether 19 461 high-quality SNPs were inferred in the association population. Then, GWAS was performed using 19 461 SNPs and phenotype data by three models including additive, dominance and epistasis, respectively. Combining with the transcriptome data of maize ear related tissues in the public database and the annotation information of genes, candidate genes were predicted. 【Result】Phenotypic data analysis showed that eight ear traits followed a continuous distribution, and there were 3.78%-45.25% of phenotypic variation. Analysis of variance indicated that environment and genotype effects reached an extremely significant level (P<0.001), and the range of broad-sense heritability was from 54.15% to 68.89%. And there were significantly positive or negative correlations among ear traits of hybrids. In total, 16, 3, 79 significant SNPs/pairs were identified under additive, dominant, and epistatic models, respectively. The significant loci detected by the three models cumulatively explained 38.21%-60.69% of the phenotypic variation of each trait. The cumulative phenotypic variation of significant SNP detected by additive model and epistatic model was 0.00-41.26% and 15.18%-45.36%, respectively. Effect analysis of significant SNPs identified by additive and dominant models showed most SNPs with additive or partial dominance effects, and only two with over-dominance effects. Further, only seven single-SNPs and five interaction pairs explained more than 5% of the phenotypic variation, and 17 candidate genes were predicted based on the SNP locations and gene expression information. 【Conclusion】Ear traits of maize hybrids were mainly affected by additive and epistasis effects, but less by dominance effects. Multiple SNPs identified by additive and dominant models showed additive and partially dominance effects, and aggregating favorable alleles of these SNPs could improve the target traits.

Key words: maize, hybrids, ear traits, genome wide association study, genetic effect, candidate gene