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| 基于SSR标记的风兰品种资源遗传多样性分析与DNA指纹图谱构建 |
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何月秋1,2, 丁楚蔚3, 林立1,2, 胡康婷1,2, 陈志3, 葛武国4
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1. 宁波城市职业技术学院,浙江 宁波 315100；2. 宁波市观赏植物遗传育种与重点实验室,浙江 宁波 315100；3. 浙江省农业科学院,杭州 310021；4. 宁波莘园农业科技有限公司,浙江 宁波 315010
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| 摘要: |
| 为探清风兰品种资源的遗传背景并构建可精准鉴定的DNA指纹图谱，该研究通过转录组测序开发筛选出20对SSR多态性引物，对99份风兰种质进行聚类与遗传多样性分析。结果表明：（1）20对引物共检测到214个等位基因，平均等位基因数（Na）10.7，平均期望杂合度（He）0.678 4，平均多态性信息含量（PIC）0.634 8，表明风兰栽培群体具有较高的遗传多样性。（2）99份风兰种质的遗传距离介于0~3.919 7之间，平均遗传距离为0.920 3，部分品种可能为同物异名或遗传背景高度一致的克隆材料。（3）聚类分析和主坐标分析将99份种质划分为15个类群，各类群在花色、根型等表型特征上呈现明显聚集趋势，且类群遗传多样性差异与类群规模、品种起源密切相关。（4）在遗传多样性分析的基础上，构建了基于SSR等位基因大小编码的数字指纹体系，并生成二维码，包含品种名、叶形、叶色、花色、根色、开花时间及数字指纹编号，实现92个品种（区分率92.9%）的精准分子鉴定。该指纹图谱为风兰品种权保护、市场鉴定及育种亲本选配提供了可靠工具，为风兰种质资源保护与品种创新奠定了分子基础。该研究完成了99份风兰种质的遗传分析与SSR指纹库构建，为该领域的系统研究提供了重要数据支撑。 |
| 关键词: 风兰，SSR标记，遗传多样性，DNA指纹，聚类分析，品种鉴定 |
| DOI：10.11931/guihaia.gxzw202602016 |
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| 基金项目:宁波市奉化区农业与社会发展科技计划项目（202402106）。 |
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| Genetic diversity analysis and DNA fingerprint construction of?Neofinetia falcata?varieties based on SSR markers |
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HE Yueqiu1,2, DING Chuwei3, LIN Li1,2, HU Kangting1,2, CHEN Zhi3, GE Wuguo4
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1. Ningbo City College of Vocational Technology, Ningbo 315100, Zhejiang, China; 2. Ningbo Key Laboratory of Ornamental Plant Genetics, Breeding and Utilization, Ningbo City College of Vocational Technology, Ningbo 315000, Zhejiang, China；3. Zhejiang Academy of Agricultural Sciences, Hangzhou 310021, China; 4. Ningbo Shenyuan Agricultural Technology Co., Ltd., Ningbo 315010, Zhejiang, China
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| Abstract: |
| To reveal the genetic background and germplasm characteristics of Neofinetia falcata, and to establish an accurate DNA fingerprint construction, 20 pairs of polymorphic SSR markers developed from transcriptome sequencing were used to evaluate the genetic diversity and relationships of 99 accessions. The results were as follows: (1) A total of 214 alleles were detected across the 20 primer pairs, with an average number of alleles per locus (Na) of 10.7, an average expected heterozygosity (He) of 0.678 4, and an average polymorphism information content (PIC) of 0.634 8, indicating a relatively high level of genetic diversity within the cultivated population. (2) The genetic distances among the 99 germplasms ranged from 0 to 3.919 7, with an average of 0.920 3, suggesting that some varieties might be synonyms or clonal materials with highly consistent genetic backgrounds. (3) Cluster analysis and principal coordinate analysis divided the 99 germplasms into 15 groups, showing evident aggregation trends in phenotypic traits such as flower color and root type; moreover, the genetic diversity of these groups was closely related to group size and varietal origin. (4) Based on the genetic diversity analysis, a digital fingerprinting system encoding SSR allele sizes was constructed, and corresponding QR codes containing variety name, leaf shape, leaf color, flower color, root color, flowering time, and digital fingerprint number were generated, enabling accurate molecular identification of 92 varieties (distinguishing rate of 92.9%). This fingerprint database provides a reliable tool for variety rights protection, market authentication, and parental selection in breeding, thereby laying a molecular foundation for the conservation and innovative utilization of Neofinetia falcata germplasm resources. This study systematically presents the genetic analysis and SSR fingerprint library construction of 99 Neofinetia falcata germplasms, providing important data support for systematic research in this field. |
| Key words: Neofinetia falcata,SSR markers,genetic diversity,DNA fingerprint,cluster analysis,variety identification |
