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A Multi-Level Strategy Based on Metabolic and Molecular Genetic Approaches for the Characterization of Different Coptis Medicines Using HPLC-UV and RAD-seq Techniques

机译:基于代谢和分子遗传方法的多级策略使用HPLC-UV和RAD-seq技术表征不同的黄连药物

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摘要

Coptis plants (Ranunculaceae) to have played an important role in the prevention and treatment human diseases in Chinese history. In this study, a multi-level strategy based on metabolic and molecular genetic methods was performed for the characterization of four Coptis herbs (C. chinensis, C. deltoidea, C. omeiensis and C. teeta) using high performance liquid chromatography-ultraviolet (HPLC-UV) and restriction site-associated DNA sequencing (RAD-seq) techniques. Protoberberine alkaloids including berberine, palmatine, coptisine, epiberberine, columbamine, jatrorrhizine, magnoflorine and groenlandicine in rhizomes were identified and determined based on the HPLC-UV method. Among them, berberine was demonstrated as the most abundant compound in these plants. RAD-seq was applied to discover single nucleotide polymorphisms (SNPs) data. A total of 44,747,016 reads were generated and 2,443,407 SNPs were identified in regarding to four plants. Additionally, with respect to complicated metabolic and SNP data, multivariable statistical methods of principal component analysis (PCA) and hierarchical cluster analysis (HCA) were successively applied to interpret the structure characteristics. The metabolic variation and genetic relationship among different Coptis plants were successfully illustrated based on data visualization. Summarily, this comprehensive strategy has been proven as a reliable and effective approach to characterize Coptis plants, which can provide additional information for their quality assessment.
机译:黄连植物(毛an科)在中国历史上对人类疾病的预防和治疗中起着重要作用。在这项研究中,采用高效液相色谱-紫外光谱(UV),基于代谢和分子遗传方法的多级策略对四种黄连(C. chinensis,C。deltoidea,C。omeiensis和C.teeta)进行表征。 HPLC-UV)和与限制性酶切位点相关的DNA测序(RAD-seq)技术。基于HPLC-UV方法鉴定并确定了根茎中的小ber碱原生物碱,包括小ber碱,棕榈碱,黄连碱,表皮小ine碱,哥伦巴胺,麻风树碱,厚朴碱和罗汉兰碱。其中,小ber碱被证明是这些植物中含量最高的化合物。 RAD-seq用于发现单核苷酸多态性(SNP)数据。总共产生了44,747,016个读段,并针对4株植物鉴定了2,443,407个SNP。此外,对于复杂的代谢和SNP数据,相继采用主成分分析(PCA)和层次聚类分析(HCA)的多变量统计方法来解释结构特征。基于数据可视化成功地说明了不同黄连植物之间的代谢变异和遗传关系。综上所述,该综合策略已被证明是表征黄连植物的可靠且有效的方法,可为其质量评估提供更多信息。

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