多环境下谷子株高、穗重和穗粒重遗传特性分析  

Genetic Characteristics Analysis of Plant Height,Panicle Weight and Grain Weight of Foxtail Millet(Setaria italica)in Multiple Environments

作　　者：李颜方 刘燕 杜晓芬 王智兰 韩康妮 连世超 李禹欣 张林义 王军[1,2] LI Yan-Fang;LIU Yan;DU Xiao-Fen;WANG Zhi-Lan;HAN Kang-Ni;LIAN Shi-Chao;LI Yu-Xin;ZHANG Lin-Yi;WANG Jun(Millet Research Institute,Shanxi Agricultural University/Hou Ji Laboratory in Shanxi Province,Changzhi 046011,China;College of Agriculture,Shanxi Agricultural University,Taigu 030801,China)

机构地区：[1]山西农业大学谷子研究所/山西省后稷实验室,长治046011 [2]山西农业大学农学院,太谷030801

出　　处：《农业生物技术学报》2025年第3期486-497,共12页Journal of Agricultural Biotechnology

基　　金：国家重点研发计划(2018YFD1000700);国家重要特色物种谷子育种联合攻关(NYGG19-2);山西省现代农业产业技术体系(2024CYJSTX04-01);山西省基础研究计划(202203021212453)。

摘　　要：谷子(Setaria italica)高产育种的关键目标包括优化植株高度、增加单穗重量及提升单穗籽粒重量。为探究谷子株高、单穗穗重和单穗粒重的遗传规律,本研究以'矮宁黄'为母本,'晋谷21'为父本进行杂交,构建重组自交系(recombinant inbred line, RIL)群体,2019~2021年在山西省不同生态条件下的7个环境种植,利用R软件包SEA v2.0对RIL群体的株高、单穗穗重和单穗粒重等性状进行主基因+多基因混合遗传模型分析。结果表明,株高、单穗穗重和单穗粒重三者显著相关,其中单穗穗重与单穗粒重的相关系数为0.98 (P≤0.001)。株高的最优模型为多基因模型PG-AI,多基因遗传率为97.56%;单穗穗重的最优模型为多基因模型PG-A,多基因遗传率为84.04%,以加性效应为主,多基因加性效应值为-2.95,表现为负向遗传效应;单穗粒重的最优模型为MX2-ED-A,受2对具有显性上位性的主基因及加性多基因共同调控,其中主基因遗传率为62.53%,多基因遗传率为50.52%,第2对主基因的加性效应占主导,加性上位性互作效应值为-11.50,表明存在负向的遗传影响。谷子株高与单穗穗重的最优遗传模型相似,均表现出多基因遗传特征,具有较高的遗传率,且受环境因素的影响相对较小;相比之下,单穗粒重的遗传受到主基因与多基因混合遗传模式的控制。本研究对谷子株高、单穗穗重和穗粒重等关键性状的遗传改良和基因定位提供理论参考。The primary objectives of high-yield breeding for foxtail millet(Setaria italica)encompass the optimization of plant height,enhancement of panicle weight,and augmentation of panicle grain weight.In order to investigate the genetic variation of plant height,panicle weight and panicle grain weight of foxtail millet,this study utilized'Aininghuang'as the maternal parent and'Jingu 21'as the paternal parent to established a recombinant inbred line(RIL)population,and the RIL population was cultivated at 7 locations over a span of 3 years(2019~2021)in Shanxi province,R-based software package SEA v2.0 was employed to analyze the main gene+multi-gene hybrid genetic model for RIL population traits such as plant height,panicle weight and grain weight.The results demonstrated significant correlations among plant height,panicle weight and grain weight,and the correlation coefficient between panicle weight and grain weight was 0.98(P≤0.001).The optimal model for plant height was determined to be PG-AI with the polygenic heritability of 97.56%;Similarly,the optimal model for panicle weight was identified as PG-A with the polygenic heritability of 84.04%,primarily influenced by additive effects resulting in an additive effect value of-2.95 indicating negative genetic impact;The most suitable model for grain weight was MX2-ED-A,which was controlled by 2 dominant epistatic major genes along with additive polygenes contributing to mixed inheritance pattern,with major gene heritability accounted for 62.53%and polygene contributed approximately 50.52%,the additive effect of the second major gene was dominant,and the additive epistatic interaction effect value was-11.50,showed a negative genetic effect.The optimal genetic models of plant height and panicle weight in foxtail millet were similar,exhibited a polygenic nature with substantial heritability and little environmental influence;In contrast,the inheritance of grain weight was primarily controlled by a combination of major gene effects and polygenic factors.This study offers v

关 键 词：谷子 多环境 主基因+多基因模型 遗传分析 

分 类 号：S515[农业科学—作物学]