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基于SRAP分子标记的13份贵州芒果种质资源遗传多样性分析 被引量:11

Genetic Diversity Analysis of Thirteen Mango Germplasm Resources Based on SRAP Molecular Markers
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摘要 探索贵州芒果种质资源的遗传多样性和亲缘关系,为芒果种质资源的鉴定、创新与利用提供理论依据。利用SRAP标记对13份芒果种质资源进行遗传多样性分析。对108对引物组合进行筛选,其中有17对引物扩增的条带多且多态性好。17对引物共产生扩增带161条,多态性条带为133条,多态性比率为82.61%,显示较高的遗传多态性。遗传相似系数在0.602~0.820,其中桂热芒10号与攀西红芒的相似系数最大,而桂热芒82号和红象牙芒两者之间的相似系数最小。UPGMA聚类分析结果显示,Mi-8与桂热芒82号的亲缘关系较近,Mi-9与红芒6号的亲缘关系较近,野生种质资源Mi-5与串芒、桂热芒10号和攀西红芒的亲缘关系较近,野生种质资源Mi-6与凯特芒和金煌芒的亲缘关系较近。以上研究结果说明SRAP技术能用于贵州芒果种质资源遗传多样性分析,也表明了贵州地区芒果种质资源遗传背景的复杂性。 The genetic diversity and genetic relationship of mango germplasm resources were explored in Guizhou to provide the theoretical basis for mango germplasm identification, innovation and utilization. SRAP was used to assess the genetic diversity of 13 mango germplasm resources. 161 bands were amplified using 17 pairs of primers selected from 108 primers, of which 133 were polymorphic bands, and the polymorphic percentage of bands was 82.61%. Genetic similarity coefficients between genotypes was in the range of 0.602–0.820, with the minimum between mango Guire 10 and Panxi Red Mango, and the maximum between Guire 82 and Hongxiangya. Cluster analysis results showed that Mi-8 and Guire 82 had the closest relatives. Mi-9 and Red Mango 6 had the closest relatives. Mi-5, Chuan Mango, Guire 10 and Panxi Red Mango had the closest genetic relationship. Mi-6, Kate Mango and Jinhuang Mango had the closest genetic relationship. The test showed that SRAP technology could be used in the genetic diversity analysis of mango germplasm resources in Guizhou, and the genetic background of mango germplasm resources was complex in Guizhou.
作者 刘荣 龚德勇 刘清国 黄海 范建新 LIU Rong;GONG Deyong;LIU Qingguo;HUANG Hai;FAN Jianxin(Institute of Subtropical Crops, Guizhou Academy of Agricultural Sciences, Xingyi, Guizhou 562400, China)
出处 《热带作物学报》 CSCD 北大核心 2019年第1期87-91,共5页 Chinese Journal of Tropical Crops
基金 贵州省科技支撑计划项目(黔科合支撑[2016]2526号 黔科合支撑[2018]2284号) 贵州省人才基地项目(黔人领发[2016]22号)
关键词 芒果 种质资源 SRAP标记 聚类分析 贵州 mango germplasm resources SRAP cluster analysis Guizhou
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