| 利用EST-SSR评估糜子资源遗传差异 |
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| 引用本文： | 石甜甜,何杰丽,高志军,陈凌,王海岗,乔治军,王瑞云.利用EST-SSR评估糜子资源遗传差异[J].中国农业科学,2019,52(22):4100-4109. |
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| 作者姓名： | 石甜甜 何杰丽 高志军 陈凌 王海岗 乔治军 王瑞云 |
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| 作者单位： | 1 山西农业大学农学院,山西太谷0308012 山西农业大学文理学院,山西太谷0308013 内蒙古鄂尔多斯市农牧业科学研究院,内蒙古鄂尔多斯0170004 山西省农业科学院农作物品种资源研究所/农业部黄土高原作物基因资源与种质创制重点实验室/杂粮种质资源发掘与遗传改良山西省重点实验室,太原 030031 |
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| 基金项目： | 现代农业产业技术体系建设专项(CARS-06-13.5-A16);国家自然科学基金(31271791);山西省回国留学人员科研资助项目(2016-066);山西省重点研发计划(一般项目)(农业)项目(201803D221008-5);2019山西省研究生创新项目(2019SY202) |
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| 摘 要： | 【目的】用微卫星标记分析糜子种质资源（国内外6个不同生态区）的遗传多样性水平,揭示不同来源糜子种质资源的亲缘关系和遗传结构差异,便于对糜子资源分类和优异种质的筛选利用。【方法】 用144个（高、低碱基序列重复分别为64和80个）SSR标记评估96份国内外（国内、国外分别为71和25份）糜子资源;用PowerMarker 3.25和PopGen 1.32计算遗传多样性参数,用MEGA 5.0和Structure 2.2进行遗传距离和结构聚类,用Ntsys 2.11进行主成分分析。【结果】 144个EST-SSR标记共检测出368个观测等位变异（Na）,每个位点检测到等位变异2—3个,平均为2.5556个;观测杂合度（Ho）为0.4070（RYW15）—0.9789（RYW85）,平均为0.8288;期望杂合度（He）为0.4369（RYW59）—0.6693（RYW58）,平均为0.5535;Nei's基因多样性指数（Nei）为0.4344（RYW59）—0.6653（RYW58）,平均为0.5505;多态性信息含量（PIC）为0.1811（RYW68）—0.7508（RYW58）,平均为0.4279。Shannon多样性指数（I）为0.6474—1.0956,平均为0.8415。就6个生态区材料的遗传多样性参数而言,北方春糜子区材料的PIC值和Shannon多样性指数最高,西北春夏糜子区材料最低。就不同生态区糜子种质间的遗传距离和遗传一致度而言,不同生态区糜子种质间的遗传距离为 0.0111—0.1425,遗传一致度为 0.8672—0.9889,北方春糜子区和黄土高原春夏糜子区间遗传距离最小和遗传一致度最高,西北春夏糜子区和华北夏糜子区间遗传距离最大。基于UPGMA聚类将试验材料划归3个类群（Ⅰ、Ⅱ、Ⅲ）。类群Ⅰ主要为北方春糜子区材料;类群Ⅱ主要为国外材料;类群Ⅲ主要为北方春糜子区和黄土高原春夏糜子区材料;基于Structure聚类将糜子资源划归4个群组,红色群组,主要为北方春糜子区和黄土高原春夏糜子区材料,代表北方和黄土高原基因库;绿色群组,主要为北方春糜子区材料,代表北方基因库;蓝色群组,主要包括黄土高原春夏糜子区材料,代表黄土高原基因库;黄色群组,代表国外基因库。就各分类群的遗传多样性参数而言,群组Ⅱ的PIC值最大（0.4606）,群组Ⅳ最小（0.3539）;主成分分析将试材划归6类,与其地理来源一致。【结论】 144个SSR标记可以准确评估96份糜子资源的遗传变异,基于不同依据划分的类群与6个生态区材料的地理来源基本一致,北方春糜子区材料的遗传多样性较丰富。
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| 关 键 词： | 糜子 SSR 聚类分析 遗传结构 主成分分析 |
| 收稿时间： | 2019-06-13 |
Genetic Diversity of Common Millet Resources Assessed with EST-SSR Markers |
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| SHI TianTian,HE JieLi,GAO ZhiJun,CHEN Ling,WANG HaiGang,QIAO ZhiJun,WANG RuiYun.Genetic Diversity of Common Millet Resources Assessed with EST-SSR Markers[J].Scientia Agricultura Sinica,2019,52(22):4100-4109. |
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| Authors: | SHI TianTian HE JieLi GAO ZhiJun CHEN Ling WANG HaiGang QIAO ZhiJun WANG RuiYun |
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| Institution: | 1 College of Agriculture, Shanxi Agricultural University, Taigu 030801, Shanxi2 College of Arts and Sciences, Shanxi Agricultural University, Taigu 030801, Shanxi3 Erdos Institute of Agriculture and Animal Husbandry, Erdos 017000, Inner Mongolia4 Institute of Crop Germplasms Resources of Shanxi Academy of Agricultural Sciences/Key Laboratory of Crop Gene Resources and Germplasm Enhancement on Loess Plateau, Ministry of Agriculture, Taiyuan 030031 |
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| Abstract: | 【Objective】The objective of this study is to analyze the genetic diversity and relationship of common millet accessions (six different ecotopes at home and abroad) by microsatellite markers, to provide available data for classification, selection and utilization of elite germplasm resources. 【Method】 One hundred and forty-four SSRs (64 high motif nucleotide sequence repeat and 80 low ones) are used to identify polymorphisms in ninety-six common millet accessions (71 home accessions and 25 abroad accessions). Genetic diversity parameters were calculated using software PowerMarker 3.25 and PopGen 1.32. Genetic distance and Structure on accessions were classified with software MEGA 5.0 and Structure 2.2, respectively. PCA (principal component analysis) was conducted by software Ntsys 2.11. 【Result】 Using 144 EST-SSR markers, a total of 368 observed alleles (Na) were detected with 2-3 alleles (mean = 2.5556) per locus. The observed heterozygosity (Ho) ranged from 0.4070 (RYW15) to 0.9789 ( RYW85) with an average of 0.8288. The expected heterozygosity (He) ranged from 0.4369 ( RYW59) to 0.6693 ( RYW58) with an average of 0.5535. The Nei's gene diversity index ranged from 0.4344 (RYW59) to 0.6653 (RYW58) with a mean of 0.5505. The polymorphism information content (PIC) ranged from 0.1811 (RYW68) to 0.7508 (RYW58) with an average of 0.4279. The Shannon diversity index (I) range was 0.6474 to 1.0956 with an average of 0.8415. In the case of genetic diversity parameters, the PIC and I of common millet accessions from Northern spring-sowing region were the most abundant than that of others. On the contrary, the accessions from Northwest spring & summer-sowing region were the lowest. For the different geographical regions accessions, the range of genetic distance was 0.0111 to 0.1425 and the scope of genetic consistency was 0.8672 to 0.9889. The genetic distance of accessions between Loess Plateau spring & summer-sowing region and Northern spring-sowing region was the least and their genetic consistency was the highest. The genetic distance between Northwest spring & summer-sowing region and North of China summer-sowing region was the largest and their genetic consistency was the lowest. UPGMA analysis divided 96 accessions into three groups (GroupⅠ, Ⅱ and Ⅲ). Group I were mainly Northern spring-sowing region common millet, Group Ⅱ were mainly foreign accessions, and Group Ⅲ were mainly Loess Plateau spring & summer-sowing region and Northern spring-sowing region accessions. Structure cluster divided resources into four groups. The red group contained Loess Plateau spring & summer-sowing region and Northern spring-sowing region accessions, which represented the gene pool of Loess Plateau and North. The green group included Northern spring-sowing region accessions, which represented the North gene pool. The blue group were Loess Plateau spring & summer-sowing region accessions, which represented the gene pool of Loess Plateau. The yellow group represented foreign gene pool. In terms of diversity parameters, the PIC value of GroupⅡwas the highest at 0.4606 and the Group Ⅳ was the lowest at 0.3539. The PCA analysis classified all accessions into six clusters, which are related to their geographical region. 【Conclusion】144 SSRs can evaluate 96 common millet resources accurately. The genetic relationships are related to their geographical region. Genetic diversity of accessions from Northern spring-sowing region are more abundant. |
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| Keywords: | common millet SSR cluster analysis genetic structure principal component analysis |
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