Lu Ziqing, Ma Zhuolin, Fu Minghui, Su Jianyu
Bioengieering Department, Biological and Pharmaceutical College, Guangdong University of Technology, No. 100 Waihuan Xi Road, Guangzhou Higher Education Center Mega, Guangzhou, 510006, People's Republic of China.
School of Food Science and Engineering, South China University of Technology, No. 381, Wushan Road, Guangzhou, 510641, People's Republic of China.
Biochem Genet. 2025 Apr;63(2):1310-1329. doi: 10.1007/s10528-024-10755-z. Epub 2024 Mar 30.
D-borneol is a double-loop monoterpene with a wide use in the pharmaceutical, food, and cosmetics industries. Natural D-borneol can be extracted from branches and leaves of D-borneol resource plants. With the widespread use of natural D-borneol, the identification of D-borneol resource plants and the protection of germplasm resources have become the focus of research. In this study, plant leaf morphology, chemical composition, and simple sequence repeat (SSR) molecular marker analysis were used to analyze and cluster 5 species of D-borneol resource plants and their closely related species. It was found that all three analysis methods could distinguish and cluster these D-borneol resource plants to some degree. The result of SSR analysis using capillary electrophoresis was the best, and it could distinguish Mei Pian tree from Yin Xiang as well as Longnao Zhang from An Zhang. The correlation analysis between SSR similarity matrix and leaf morphology analysis and between SSR similarity matrix and chemical composition similarity matrix revealed that they both had significant correlations (P < 0.0001) and the correlation (r = 0.588) between SSR and leaf morphology was a little higher than that (r = 0.519) between SSR and chemical composition. This indicated that the environment had a greater impact on the chemical composition than on leaf morphology. The research findings will offer efficient techniques to cluster natural D-borneol resource plants and establish a theoretical basis for their future development and utilization.
右旋龙脑是一种双环单萜,在制药、食品和化妆品行业有广泛应用。天然右旋龙脑可从右旋龙脑资源植物的枝叶中提取。随着天然右旋龙脑的广泛应用,右旋龙脑资源植物的鉴定和种质资源保护已成为研究重点。本研究采用植物叶形态、化学成分和简单序列重复(SSR)分子标记分析,对5种右旋龙脑资源植物及其近缘种进行分析和聚类。结果发现,这三种分析方法在一定程度上都能区分和聚类这些右旋龙脑资源植物。毛细管电泳SSR分析结果最佳,能区分梅片树与阴香以及龙脑樟与安南樟。SSR相似性矩阵与叶形态分析以及SSR相似性矩阵与化学成分相似性矩阵之间的相关性分析表明,它们均具有显著相关性(P < 0.0001),且SSR与叶形态的相关性(r = 0.588)略高于SSR与化学成分的相关性(r = 0.519)。这表明环境对化学成分的影响大于对叶形态的影响。研究结果将为天然右旋龙脑资源植物的聚类提供有效技术,并为其未来开发利用奠定理论基础。