Shuai Yang, Shilin Chen, Jing Mo, Junfei Liu, Qi Pan, Chi Song
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引用次数: 0
摘要
药用植物是全球宝贵的资源,在世界各地被用于维护健康和治疗疾病;然而,掺假现象的存在阻碍了药用植物的发展。DNA 条形码是一种通过标准 DNA 区域进行物种鉴定的技术,有助于迅速准确地鉴定传统药用植物。DNA 条形编码过程包括六个基本步骤:1) 处理药用植物;2) 利用离心柱法从药用植物中提取高质量的总 DNA;3) 利用植物通用引物扩增目标 DNA 区域内部转录间隔区 2 (ITS2),并进行 Sanger 测序;4) 拼接和比对序列以获得目标序列;5) 将条形码序列与条形码库进行比对以进行鉴定;6) 比对序列,比较种内和种间变异,构建系统发育邻接树。结果显示,通用引物可以扩增目标区域。基本局部比对搜索工具(BLAST)显示识别率为100%,邻接树显示剪接序列与A. sinensis OR879715.1支系聚类,支系支持值为100。该方案为应用DNA条形码技术有效鉴定药用植物和掺杂物提供了参考。
Application of DNA Barcoding to Identify Medicinal Plants.
Medicinal plants are valuable resources globally and are used worldwide to maintain health and treat disease; however, the presence of adulteration obstructs their development. DNA barcoding, a technique for species identification by standard DNA regions, facilitates prompt and accurate identification of traditional medicinal plants. The process of DNA barcoding entails six basic steps: 1) processing the medicinal plants, 2) extracting high-quality total DNA from the medicinal plants using centrifugal column method, 3) amplifying target DNA region internal transcribed spacer 2 (ITS2) with universal primers of plants and performing Sanger sequencing, 4) splicing and aligning sequence to obtain the target sequence, 5) matching the barcode sequence against the barcode library for identification, 6) aligning sequence, comparing intraspecific and interspecific variation, constructing phylogenetic neighbor-joining tree. As shown in the results, the universal primer can amplify the target region. Basic Local Alignment Search Tool (BLAST) demonstrates the percentage identified was 100%, and the neighbor-joining tree demonstrates that the splicing sequences were clustered with the A. sinensis OR879715.1 clade, and the clade support value is 100. This protocol provides a reference for applying DNA barcoding technology as an effective method to identify medicinal plants and adulterants.
期刊介绍:
JoVE, the Journal of Visualized Experiments, is the world''s first peer reviewed scientific video journal. Established in 2006, JoVE is devoted to publishing scientific research in a visual format to help researchers overcome two of the biggest challenges facing the scientific research community today; poor reproducibility and the time and labor intensive nature of learning new experimental techniques.