| 云南粳稻和韩国粳稻的遗传差异分析 |
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| 引用本文： | 赵国珍,杨世准,曹永灿,李彀镎,苏振喜,朱振华,邹茜,戴陆园. 云南粳稻和韩国粳稻的遗传差异分析[J]. 分子植物育种, 2008, 6(3): 451-456 |
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| 作者姓名： | 赵国珍 杨世准 曹永灿 李彀镎 苏振喜 朱振华 邹茜 戴陆园 |
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| 作者单位： | 云南省农业科学院粳稻育种中心,昆明,650205;韩国农村振兴厅国家作物科学院,水原,441857 |
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| 基金项目： | 云南省科技攻关计划 , 中-韩合作项目 |
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| 摘 要： | 采用134对SSR引物对11个云南粳稻和10个韩国粳稻进行遗传差异分析。结果表明,112对引物具有多态性,共检测到370个等位基因,每对引物检测到2-7个等位基因,平均为3.3个,SSR多态信息量（PIC）分布范围为0.091-0.807,平均为0.466。韩国粳稻比云南粳稻反映出较高的遗传多样性,10个韩国粳稻有96对引物具有多态性,共检测到273个等位基因,每对引物检测到2-5个等位基因,平均为2.84个,SSR多态信息量（PIC）分布范围为0.180-0.780,平均为0.482,遗传相似系数变幅为0.66-0.93,平均为0.79;11个云南粳稻有93对引物具有多态性,共检测到235个等位基因,每对引物检测到2-5个等位基因,平均为2.53个,SSR多态信息量（PIC）分布范围为0.165-0.744,平均为0.406,遗传相似系数变幅为0.73-0.98,平均为0.85。聚类分析表明,云南和韩国粳稻的遗传差异较大,在今后的云南粳稻品种选育中,利用韩国粳稻拓展云南粳稻的遗传基础和改善稻米品质显得十分必要。
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| 关 键 词： | 粳稻 SSR标记 遗传多样性 聚类分析 |
Analysis of Genetic Diversity between Japonica Rice of Yunnan and Korea |
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| Zhao Guozhen,Yang Seajun,Cho Youngchan,Lee Jeongheni,Su Zhenxi,Zhu Zhenhua,Zou Qian,Dai Luyuan. Analysis of Genetic Diversity between Japonica Rice of Yunnan and Korea[J]. Molecular Plant Breeding, 2008, 6(3): 451-456 |
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| Authors: | Zhao Guozhen Yang Seajun Cho Youngchan Lee Jeongheni Su Zhenxi Zhu Zhenhua Zou Qian Dai Luyuan |
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| Affiliation: | Zhao Guozhen 1 Yang Seajun 2 Cho Youngchan 2 Lee Jeongheui 2 Su Zhenxi 1 Zhu Zhenhua 1 Zou Qian 1 Dai Luyuan 11 Japonica Rice Breeding Center,Yunnan Academy of Agricultural Sciences,Kunming,650205,2 National Institute of Crop Science,Rural Development Administration,Suwon,441857 |
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| Abstract: | A total of 134 SSR markers were used to compare the genetic diversity in 11 Yunnan cultivars and 10 Korean cultivars. The result indicated that 112 of the primer pairs were polymorphic. A total of 370 alleles were detected ranging from 2 to 7 per locus, with an avarage of 3.3. The values of polymorphism information content (PIC) for each SSR locus was 0.466 with a range from 0.091~0.807. By comparison of the genetic diversity, it was found that Korean cultivars were higher than those of Yunnan cultivars. Th... |
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| Keywords: | Japonica rice SSR marker Genetic diversity Cluster analysis |
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