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应用低密度SNP芯片解析玉米遗传多样性
引用本文:高嵩,张楠,何欢,郑淑波,赵桐,周小辉,代秀云,黄威,王薪淇.应用低密度SNP芯片解析玉米遗传多样性[J].玉米科学,2024,32(1):26-32.
作者姓名:高嵩  张楠  何欢  郑淑波  赵桐  周小辉  代秀云  黄威  王薪淇
作者单位:吉林省农业科学院, 长春 130033;吉林省农业科学院, 长春 130033;吉林农业大学, 长春 130118
基金项目:吉林省发改委预算内基本建设资金-创新能力建设项目(2022c038-3)、吉林省科协人才托举项目(QT202108)、吉林农业科技创新工程项目(CXGC2021ZY005)
摘    要:利用1K低密度SNP标记,对不同亚群的95份自交系材料进行群体遗传结构、遗传多样性和类群间遗传关系分析。结果表明,来自不同玉米亚群的95份自交系可划分为4个主要类群,符合血缘背景;主等位基因频率平均值为0.760 7,基因多样性平均值为0.317 8,杂合度观测值平均值为0.073 4,PIC值平均值为0.257 0。在1 249个SNP标记中,多态性较好的占比72.06%。基于GenoBaits的基因型鉴定技术可低成本且高效地解析种质的遗传背景和亲缘关系,为专、特用玉米分子标记辅助育种提供了可靠的技术依托。

关 键 词:玉米  SNP  类群划分  聚类分析
收稿时间:2023/2/27 0:00:00

Application of Low-Density SNP Chips to Resolve Genetic Diversity in Maize
GAO Song,ZHANG Nan,HE Huan,ZHENG Shu-bo,ZHAO Tong,ZHOU Xiao-hui,DAI Xiu-yu,HUANG Wei,WANG Xin-qi.Application of Low-Density SNP Chips to Resolve Genetic Diversity in Maize[J].Journal of Maize Sciences,2024,32(1):26-32.
Authors:GAO Song  ZHANG Nan  HE Huan  ZHENG Shu-bo  ZHAO Tong  ZHOU Xiao-hui  DAI Xiu-yu  HUANG Wei  WANG Xin-qi
Institution:Jilin Academy of Agricultural Sciences, Changchun 130033;Jilin Academy of Agricultural Sciences, Changchun 130033;Jilin Agricultural University, Changchun 130118, China
Abstract:By using 1K low-density SNP markers, population genetic structure, genetic diversity, and genetic relationships among taxa were analyzed in 95 inbred accessions from different subgroups. The results showed that 95 inbred lines from different maize subgroups could be divided into 4 major groups, and the mean main allele frequency was 0.760 7; the mean gene diversity was 0.317 8; the observed value of heterozygosity was 0.073 4, and the mean PIC value was 0.257 0. Among the 1 249 SNP markers, 72.06% of the polymorphisms were better. The genotype identification technology based on GenoBaits can analyze the genetic background and kinship of germplasm at low cost and high efficiency, and provides a reliable technical support for specialized and targeted molecular marker-assisted breeding in maize.
Keywords:Maize  SNP  Group classification  Cluster analysis
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