基于SSR分子标记的沙枣遗传多样性分析和指纹图谱构建
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国家重点研发计划(2020YFD1000500);北京园林绿化增彩延绿科技创新工程(2019-KJC-02-10);北京市园林绿化局《沙枣培育技术规程》制定标准项目(20211245);北京林业大学建设世界一流学科和特色发展引导专项资金项目(2019XKJS0324)


Genetic diversity and fingerprinting of Elaeagnus angustifolia based on SSR molecular markers
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    摘要:

    为了促进沙枣新品种选育、种质资源鉴定保护和生态经济型沙枣产业综合发展,对沙枣(Elaeagnus angustifolia)种质资源进行遗传多样性分析,构建DNA指纹图谱,挖掘沙枣种质来源和遗传背景。本研究采用多态性好、条带清晰、重复性好的11对引物,利用简单重复序列(simple sequence repeats,SSR)分子标记技术,对甘肃省和北京市来源的150份沙枣材料的遗传多样性进行了研究,基于遗传距离进行非加权组平均法(unweighted pair-group method with arithmetic means,UPGMA)聚类分析,基于贝叶斯模型的Structure v2.3.3软件解析150份种质的遗传结构。在遗传多样性分析中,平均等位基因数为(number of alleles,Na)7.636 4,平均有效等位基因数(number of effective alleles,Ne)为2.832 6,平均Shannon信息指数(Shannon genetic diversity index,I)为1.178 1,Nei’s平均基因多样性指数(Nei’s gene diversity index,H)为0.582 1,平均观测杂合度(observed heterozygosity,Ho)为0.489 9,平均期望杂合度(expected heterozygosity,He)为0.584 0,平均多态信息含量(polymorphism information content,PIC)为0.535 4,平均遗传相似性系数(genetic similarity,GS)为0.831 5,表明所研究的沙枣之间具有显著的遗传差异和丰富的遗传多样性。聚类分析将150份材料划分为3个类群,平均遗传距离(genetic distance,GD)为0.422 9,聚类结果和地理来源并不完全一致。Structure群体结构分析将供试材料分为2个种群。利用8对多态信息含量最高的引物,构建了150份沙枣材料的指纹图谱。本研究成功构建了甘肃和北京沙枣种质资源的DNA指纹图谱,阐明了其亲缘关系,为沙枣种质资源鉴定、优异种质筛选、园林应用和分子辅助育种工作提供了理论依据。

    Abstract:

    DNA fingerprinting can reveal the genetic diversity of Elaeagnus angustifolia germplasm resources and clarify the source and genetic background of E. angustifolia germplasm, which are the preconditions for the breeding of new varieties, the identification and protection of germplasm resources, and the comprehensive development of the E. angustifolia industry considering both ecological and economic benefits. We employed 11 pairs of primers with high polymorphism, clear bands, and high reproducibility to analyze the genetic diversity of 150 E. angustifolia germplasm accessions from Gansu and Beijing by the simple sequence repeat (SSR) molecular markers. We then employed the unweighted pair-group method with arithmetic means (UPGMA) to perform the cluster analysis based on genetic distance and analyzed the genetic structure of the 150 germplasm accessions based on a Bayesian model in Structure v2.3.3. The genetic diversity analysis revealed the mean number of alleles (Na) of 7.636 4, the mean number of effective alleles (Ne) of 2.832 6, the mean Shannon genetic diversity index (I) of 1.178 1, the mean Nei’s gene diversity index (H) of 0.582 1, the mean observed heterozygosity (Ho) of 0.489 9, the mean expected heterozygosity (He) of 0.584 0, the mean polymorphism information content (PIC) of 0.535 4, and the mean genetic similarity (GS) of 0.831 5. These results suggested that the E. angustifolia germplasm resources we studied exhibited significant genetic differences and rich genetic diversity. The cluster analysis revealed that the tested materials can be classified into 3 groups, with the main genetic distance (GD) of 0.422 9. The clustering results were not completely consistent with the geographic origin. The population structure analysis classified the germplasm accessions into 2 populations. We used 8 pairs of primers with high PIC to construct the fingerprints of 150 E. angustifolia germplasm accessions. The present study successfully constructs the DNA fingerprints and clarified the genetic relationship of the E. angustifolia germplasm resources in Gansu and Beijing, providing a theoretical basis for germplasm resource identification, breeding of elite varieties, application in gardening, and molecular-assisted breeding of E. angustifolia.

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王梓煦,曾郅涵,秦孝天,李子航,童宇航,刘克林,李庆卫. 基于SSR分子标记的沙枣遗传多样性分析和指纹图谱构建[J]. 生物工程学报, 2024, 40(10): 3530-3547

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  • 收稿日期:2024-04-02
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  • 在线发布日期: 2024-10-12
  • 出版日期: 2024-10-25
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