[Genetic diversity and fingerprinting of Elaeagnus angustifolia based on SSR molecular markers].

Q4 Biochemistry, Genetics and Molecular Biology Sheng wu gong cheng xue bao = Chinese journal of biotechnology Pub Date : 2024-10-25 DOI:10.13345/j.cjb.240284
Zixu Wang, Zhihan Zeng, Xiaotian Qin, Zihang Li, Yuhang Tong, Kelin Liu, Qingwei Li
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引用次数: 0

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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[基于 SSR 分子标记的 Elaeagnus angustifolia 遗传多样性和指纹图谱]。
DNA指纹图谱可以揭示榆叶梅种质资源的遗传多样性,明确榆叶梅种质资源的来源和遗传背景,为培育新品种、鉴定和保护种质资源、全面发展榆叶梅产业的生态效益和经济效益提供先决条件。我们采用11对多态性高、条带清晰、重现性好的引物,通过简单序列重复(SSR)分子标记分析了甘肃和北京150份藁本种质资源的遗传多样性。然后,我们采用算术平均的非加权成对分组法(UPGMA)进行了基于遗传距离的聚类分析,并在Structure v2.3.3中基于贝叶斯模型分析了150份种质材料的遗传结构。遗传多样性分析表明,等位基因的平均数量(Na)为 7.636 4,有效等位基因的平均数量(Ne)为 2.832 6,香农遗传多样性指数(I)的平均值为 1.178 1,内氏基因多样性指数(H)的平均值为 0.582 1,观察到的杂合度(Ho)的平均值为 0.这些结果表明,我们研究的 E. angustifolia 种质资源表现出显著的遗传差异和丰富的遗传多样性。聚类分析显示,受试材料可分为 3 组,主要遗传距离(GD)为 0.422 9。聚类结果与地理起源并不完全一致。种群结构分析将种质材料分为 2 个种群。我们使用 8 对高 PIC 引物构建了 150 份 E. angustifolia 种质材料的指纹图谱。本研究成功构建了甘肃和北京两地白花蛇舌草种质资源的DNA指纹图谱,阐明了白花蛇舌草种质资源的遗传关系,为白花蛇舌草种质资源鉴定、优良品种选育、园林应用和分子辅助育种提供了理论依据。
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来源期刊
Sheng wu gong cheng xue bao = Chinese journal of biotechnology
Sheng wu gong cheng xue bao = Chinese journal of biotechnology Biochemistry, Genetics and Molecular Biology-Biotechnology
CiteScore
1.50
自引率
0.00%
发文量
298
期刊介绍: Chinese Journal of Biotechnology (Chinese edition) , sponsored by the Institute of Microbiology, Chinese Academy of Sciences and the Chinese Society for Microbiology, is a peer-reviewed international journal. The journal is cited by many scientific databases , such as Chemical Abstract (CA), Biology Abstract (BA), MEDLINE, Russian Digest , Chinese Scientific Citation Index (CSCI), Chinese Journal Citation Report (CJCR), and Chinese Academic Journal (CD version). The Journal publishes new discoveries, techniques and developments in genetic engineering, cell engineering, enzyme engineering, biochemical engineering, tissue engineering, bioinformatics, biochips and other fields of biotechnology.
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