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植物研究 ›› 2024, Vol. 44 ›› Issue (4): 540-553.doi: 10.7525/j.issn.1673-5102.2024.04.007

• 遗传与育种 • 上一篇    

虎耳草表型特征多样性分析

唐世梅1,2,3, 黄安琪2,3, 陈之林4, 罗佳琳1, 李昕1, 晋宇轩4, 田代科1,5()   

  1. 1.中国科学院分子植物科学卓越创新中心辰山科研中心/上海辰山植物园,上海 201602
    2.湖南农业大学园艺学院,长沙 410128
    3.湖南省中亚热带优质花木繁育与利用工程技术研究中心,长沙 410128
    4.贵州省农业科学院园艺研究所,贵阳 550006
    5.上海市资源植物功能基因组学重点实验室,上海 201602
  • 收稿日期:2023-11-27 出版日期:2024-07-20 发布日期:2024-07-09
  • 通讯作者: 田代科 E-mail:dktian@cemps.ac.cn
  • 作者简介:唐世梅(1998—),女,硕士研究生,主要从事国产虎耳草属的多样性及观赏价值评价。
  • 基金资助:
    上海市绿化和市容管理局科研专项(G182412)

Phenotypic Diversity Analysis of Saxifraga stolonifera

Shimei TANG1,2,3, Anqi HUANG2,3, Zhilin CHEN4, Jialin LUO1, Xin LI1, Yuxuan JIN4, Daike TIAN1,5()   

  1. 1.Chenshan Science Research Center of CAS Center for Excellence in Molecular Plant Sciences,Shanghai Chenshan Botanical Garden,Shanghai 201602
    2.College of Horticulture,Hunan Agricultural University,Changsha 410128
    3.Hunan Provincial Midsubtropical High Quality Flower and Tree Breeding and Utilization Engineering Technology Research Center,Changsha 410128
    4.Horticultural Research Institute,Guizhou Academy of Agricultural Sciences,Guiyang 550006
    5.Shanghai Key Laboratory for Plant Functional Genomics and Resources,Shanghai 201602
  • Received:2023-11-27 Online:2024-07-20 Published:2024-07-09
  • Contact: Daike TIAN E-mail:dktian@cemps.ac.cn

摘要:

为了全面理解虎耳草(Saxifraga stolonifera)的种内多样性,探讨种下分类的可能性,为资源保护及创新利用提供参考,对全国43个虎耳草居群的33个性状进行观察记录,通过数量性状变异和质量性状多样性分析、相关性分析、主成分分析和聚类分析等方法探讨该种的表型性状多样性。结果表明:(1)数量性状变异系数为0.05~0.67,质量性状多样性指数为0.19~1.39,居群间斑纹分布式样和叶色多样性水平高,匍匐茎分枝数和叶长宽比分别为最不稳定和最稳定的性状。(2)数量性状和导出性状变异系数普遍较大、质量性状的多样性指数普遍较高及各主成分的贡献率较分散,因此不宜仅仅依靠形态特征对该种进行种下分类。(3)虎耳草居群间各性状相关性存在差异,叶长和叶宽、下长花瓣长和下短花瓣长、下长花瓣宽和下短花瓣宽等性状相关性显著。(4)基于形态聚类结果可将国产虎耳草分为3个分支,并表现出一定的地域性,其中分支Ⅰ由8个西南居群、2个华东居群和3个西北居群组成;分支Ⅱ由4个华东居群、4个华中居群、4个西南居群和1个西北居群组成,这一类表型的虎耳草分布广泛;分支Ⅲ由10个华中居群、6个西南居群和1个华东居群组成。

关键词: 虎耳草属, 数量分类学, 形态, 聚类分析, 主成分分析

Abstract:

In order to better understand the intraspecific diversity of Saxifraga stolonifera and to explore the possibility of its classification, and to provide reference for the resource protection and innovative utilization of S. stolonifera germplasms, 33 traits from 43 populations of S. stolonifera in China were investigated, and the diversity of phenotypic traits was analyzed by numerical trait variation analysis, qualitative trait genetic diversity analysis, correlation analysis, principal component analysis and cluster analysis. The results showed that: (1)The coefficient of variation of numerical traits was 0.05-0.67, and the diversity index of qualitative traits was 0.19-1.39, and the distribution pattern of maculation and leaf color diversity were high among populations, and the branch number and the ratio of leaf length to width of stolon were the most unstable and the most stable traits, respectively. (2)The coefficient of variation of numerical and derived traits, and the diversity index of quality traits were generally high, and the contribution rates of each principal component were relatively scattered, so it was unsuitable to classify the species into different taxa only by morphological traits. (3)There were differences in the correlation of different personality traits among populations of S. stolonifera, and significant correlations included leaf length and width, length of long lower petal and length of short lower petal, width of long lower petal and width of short lower petal, respectively. (4)Based on the results of morphological clustering, S. stolonifera in China could be divided into three branches, which exhibited certain regional character. ClusterⅠ was composed of eight Southwest populations, two East China populations, and three Northwest populations; ClusterⅡ consisted of four populations from East China, four populations from Central China, four populations from Southwest China, and one population from Northwest China, so Cluster Ⅱ was widely distributed; Cluster Ⅲ consisted of ten Central China populations, six Southwest populations, and one East China population.

Key words: Saxifraga, numerical taxonomy, morphology, cluster analysis, principal component analysis

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