Taxonomic delimitation and molecular identification of clusters within the species Zanthoxylum nitidum (Rutaceae) in China

By

秦云蕊, Qin Yun
Hu, Renchuan
Hui, Zhao
Wei, Guiyuan
Lu, Zhiqiang
Huang, Yun-Feng

Type

Article

Date of Publication

2022

Original Publication

PhytoKeys

Volume

196

Pages

1--20

Subjects

Classification and identification , Liang-Mian-Zhen , medicinal materials , taxonomic delimitation

Contributed by

Pensoft Publishers

Language

English

Published by

Sofia, Bulgaria Pensoft Publishers [2010]-

Identifiers

DOI: https://doi.org/10.3897/phytokeys.196.79566

 

Abstract

Zanthoxylum nitidum, known as Liang-Mian-Zhen in China, is a traditional Chinese medicinal plant used to treat traumatic injury, rheumatism, paralysis, toothache, stomach ache, and venomous snake bites. Two varieties of the species have been described and three morphological types have been reported within the original variety. However, taxonomic delimitation and molecular markers for distinguishing these varieties and types within this species remain unknown. Since different populations exhibit varying chemical compositions, easy identification of intraspecific taxa is crucial. We collected 420 individuals from 38 natural populations, 3 samples of standard medicinal material, and 17 folk-medicine samples to perform classification and identification within Zanthoxylum nitidum. Four distinct genetic clusters (A, B, C, and D) were highly supported by the nuclear barcode. Two distinct chloroplast clusters (A1 and A2) were further detected within A, and three others had one-to-one correspondence with the remaining nuclear clusters. Molecular identification showed that the 17 folk samples comprised A1, A2, B, and D, while the 3 standard samples belonged to A2. The internal transcribed spacer (ITS) region and rbcL gene are proposed as barcodes for rapid and accurate identification of the different Liang-Mian-Zhen lineages in China. This study highlights the importance of accurate taxonomic delimitation in combination with rapid and accurate molecular identification of medicinal plants.