植物学报 ›› 2025, Vol. 60 ›› Issue (4): 533-550.DOI: 10.11983/CBB24196  cstr: 32102.14.CBB24196

• 研究论文 • 上一篇    下一篇

影响中国东北和日本粳稻食味品质差异的质构因素及其遗传基础解析

崔娟, 于晓玉, 于跃娇, 梁铖玮, 孙健*(), 陈温福*()   

  1. 沈阳农业大学水稻研究所, 沈阳 110866
  • 收稿日期:2024-12-20 接受日期:2025-03-18 出版日期:2025-07-10 发布日期:2025-03-18
  • 通讯作者: *孙健, 沈阳农业大学教授, 博士生导师。入选首批国家“神农青年英才”计划, 获“辽宁青年科技奖”等奖励或荣誉。主要研究方向为水稻种质资源创新。主持“国家自然科学基金面上项目”等多项国家与省部级项目。围绕杂草稻种质创新开展了系统性研究工作, 阐明了杂草稻的分类学地位, 提出起源演化新假说, 克隆了多个对栽培稻遗传改良具有重要价值的新基因。带领团队设计研发了粳稻种质资源芯片, 在粳稻资源评价、分子设计育种、全基因组选择等方面开展了广泛应用。研究成果在Nature Communications、Molecular Plant、New Phytologist等国际著名期刊上发表。E-mail: sunjian811119@syau.edu.cn;陈温福, 辽宁法库人, 我国著名水稻专家和生物炭专家, 中国工程院院士, 沈阳农业大学教授。第十一届、第十二届、第十三届全国人大代表, 第十四届全国政协委员。曾任国家重点学科“作物栽培学与耕作学”学科带头人, 国务院学位委员会第五届、第六届学科评议组成员和作物学科组召集人, 国家农作物品种审定委员会委员, 农业农村部第九届科技委常委、水稻专家组成员, 辽宁省科协副主席。曾获全国劳动模范和五一劳动奖章、全国模范教师、全国教学名师、创先争优奖、全国农业科技先进工作者、中华农业英才奖、辽宁省特等劳动模范、辽宁省科技功勋奖等多项荣誉。E-mail: wfchen@syau.edu.cn
  • 作者简介:

    †共同第一作者

  • 基金资助:
    国家自然科学基金(32372107)

Analysis of the Texture Factors and Genetic Basis Influencing the Differences in Eating Quality between Northeast China and Japanese Japonica Rice

Juan Cui, Xiaoyu Yu, Yuejiao Yu, Chengwei Liang, Jian Sun*(), Wenfu Chen*()   

  1. Rice Research Institute, Shenyang Agricultural University, Shenyang 110866, China

摘要: 由于育种目标的差异, 使得东北粳稻(Oryza sativa subsp. geng or japonica)在单产水平上比日本粳稻更具优势, 而日本粳米食味品质则明显优于中国粳米。明确中日粳米间食味品质差异的遗传基础, 对于培育高产优质兼顾的粳稻具有重要意义。以274份中日粳稻为研究材料, 应用质构参数量化食味品质, 并将诸多参数降维后结合全基因组关联分析揭示影响中日粳米食味差异的遗传基础。结果表明, 中日粳稻食味值的显著差异体现在粘力(adhesion force, ADF)、第一可恢复形变循环(first recoverable deformation cycle, FRDC)和弹性指数(elasticity index, EI)三个质构特征参数上。同时, 食味值与30个质构特性指标相关性分析表明, 24个指标与米饭食味之间呈显著或极显著相关性。将30个质构特性指标降维为4个可解释群体80%表型变异的主成分, 通过对其特征值进行全基因组关联分析挖掘到2个影响中日粳米质构特性的主效位点qFPC4.3qFPC9.2。该研究从质构角度量化了食味品质参数, 由此解析了中日稻米食味品质特性差异的遗传基础, 为我国粳稻食味品质遗传改良提供了有价值的遗传信息和理论依据。

关键词: 粳米, 质构特性, 食味品质, 全基因组关联分析, 主成分分析

Abstract: INTRODUCTION Due to differences in breeding objectives, northeast japonica rice (Oryza sativa subsp. geng or japonica) is more advantageous than Japanese japonica rice in terms of yield level, whereas Japanese japonica rice is significantly better than Chinese japonica rice in terms of eating quality. Clarifying the genetic basis of the differences in eating quality between Chinese and Japanese japonica rice is highly valuable for the cultivation of high-yield and high-quality japonica rice. RATIONALEA total of 274 Chinese and Japanese japonica rice varieties were used as research materials to quantify the eating quality of the rice and to analyze the genetic basis of the taste differences between Chinese and Japanese japonica rice by combining genome-wide association analysis with the downscaling of many parameters. RESULTSThe results revealed that the significant differences in the taste values of Chinese and Japanese japonica rice were reflected in three textural parameters: the adhesion force (ADF), first recoverable deformation cycle (FRDC), and elasticity index (EI). Moreover, the correlation analysis between the taste values and 30 textural characters showed that 24 characters were significantly correlated with the taste value of rice. The 30 metrics of textural characterization were downscaled to four principal components that explained 80% of the phenotypic variation in the population, and the genome-wide associations of their eigenvalues were mined to two primary effector loci affecting the textural characterization of Chinese-Japanese japonica rice, qFPC4.3 and qFPC9.2. CONCLUSION In this study, we quantified the parameters of eating quality from a qualitative perspective, and thus analyzed the genetic basis of the differences in eating quality between Chinese and Japanese rice, which provided valuable genetic information and a theoretical basis for the genetic improvement of the eating quality of japonica rice in China.
PCA analysis and genome-wide association studies based on principal component eigenvalues of texture characteristics indicators. PCA analysis was performed using 2021 data.

Key words: japonica rice, textural characteristics, eating quality, genome-wide association study, principal component analysis