研究报告

利用SSR分子标记分析云南陆稻品种遗传多样性

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  • 云南农业大学 农业生物多样性与植物病害控制教育部重点实验室, 云南 昆明 650201

收稿日期: 2011-07-15

  修回日期: 2011-01-06

  网络出版日期: 2012-03-10

基金资助

国家973计划资助项目(2006CB100205); 云南省水稻产业技术体系资助项目(A3006517)。

Genetic Diversity of Upland Rice Varieties in Yunnan Province Revealed by SSR Markers

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  • Ministry of Education, Key Laboratory of Agrobiodiversity  and Plant Disease Management,   Yunnan Agricultural University,  Kunming 650201, China;

Received date: 2011-07-15

  Revised date: 2011-01-06

  Online published: 2012-03-10

摘要

利用24对SSR引物对云南131个陆稻品种进行遗传多样性分析。共检测到195个等位基因。每个位点的等位基因数平均为8.125个,范围在5(RM55)~13(RM218、RM241)之间;平均表观杂合度为0.0014,平均期望杂合度为0.6545;平均ShannonWeaver指数(I)为1.381;Nei基因多样性指数(H)平均为0.6543,变幅为0.2073(RM235)~0.8689(RM218)。不同地区间陆稻种质资源遗传多样性比较分析表明,滇西南和滇南地区存在丰富的遗传变异,是云南陆稻品种遗传多样性的分布中心。藏缅语族和孟高棉语族所种植的陆稻品种遗传多样性最丰富。AMOVA分析表明陆稻的遗传变异主要存在于地区内品种间(82%),只有3%遗传变异存在于地区间,品种内的遗传变异占15%。聚类分析显示Nei遗传相似系数为0.22时,云南陆稻品种分为籼粳两个类群,主坐标分析与UPGMA聚类结果基本吻合,并将类群Ⅳ的4个偏籼品种从粳稻类群中重新划归到籼稻类群中,校正了UPGMA聚类的误差,但是不能区分地理组。

本文引用格式

徐建欣,王云月*,姚春,刘云霞,汤淼,陆明兴 . 利用SSR分子标记分析云南陆稻品种遗传多样性[J]. 中国水稻科学, 2012 , 26(2) : 155 -164 . DOI: 10.3969/j.issn.10017216.2012.02.004

Abstract

Genetic diversity of 131 Yunnan upland rice varieties was analyzed by using 24 SSR markers. The average number of alleles per locus was 8.125 with a range from 5(RM55) to 13(RM218, RM241).Mean observed heterozygosity and mean expected heterozygosity were 0.0014 and 0.6545, respectively. Average ShannonWeaver index (I) was 1.381. The Nei′s genetic diversity index (H) ranged from 0.2073(RM235) to 0.8689(RM218) with an average value of 0.6543. The southwest, south of Yunnan were the distribution center of genetic diversity of upland rice varieties in Yunnan, because the highest genetic variation was found in these areas. The analysis of molecular variance(AMOVA) indicated that 82% of the variation was from differences among varieties within regions, and only 3% was due to differences among regions and 15% within varieties.  The upland rice varieties  planted by TibetoBurman and the MonKhmer family had the most abundant genetic diversity. Cluster analysis showed those varieties could be divided into indica and japonica at the Nei′s genetic similarity of 0.22, but not by geographical distribution. The results of principal coordinates analysis were basically consistent with the UPGMA cluster, four partial indica varieties from group Ⅳ were reclassified into japonica group, the error of the UPGMA cluster was corrected. 

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