Article(id=1190373738072867565, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1190332325088039709, articleNumber=null, orderNo=null, doi=10.16438/j.0513-4870.2024-1272, pmid=null, cstr=null, oa=null, hot=1, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1734796800000, receivedDateStr=2024-12-22, revisedDate=1739116800000, revisedDateStr=2025-02-10, acceptedDate=null, acceptedDateStr=null, onlineDate=1761736815231, onlineDateStr=2025-10-29, pubDate=1746979200000, pubDateStr=2025-05-12, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1761736815231, onlineIssueDateStr=2025-10-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1761736815231, creator=13701087609, updateTime=1769160192497, updator=13701087609, issue=Issue{id=1190332325088039709, tenantId=1146029695717560320, journalId=1189982191388893191, year='2025', volume='60', issue='5', pageStart='1183', pageEnd='1572', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1761726941606, creator=13701087609, updateTime=1761813457266, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1190695198163354009, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1190332325088039709, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1190695198163354010, tenantId=1146029695717560320, journalId=1189982191388893191, issueId=1190332325088039709, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1543, endPage=1554, ext={EN=ArticleExt(id=1190373738391634670, articleId=1190373738072867565, tenantId=1146029695717560320, journalId=1189982191388893191, language=EN, title=Molecular identification of medicinal Polygonatum species based on plastid divergence hotspot regions, columnId=1190335348761793317, journalTitle=Acta Pharmaceutica Sinica, columnName=Original Articles, runingTitle=null, highlight=null, articleAbstract=

Polygonatum Mill. (Asparagaceae) is a pharmaceutically important genus with many species are of significant medicinal value. Taxonomy and interspecific identification of Polygonatum species have long been controversial due to their considerable morphological variation, wide geographic distribution, complex speciation processes, and lacking of high-resolution molecular markers. To evaluate species discrimination power of 14 plastid divergence hotspot regions (candidate sequences) and their combinations in Polygonatum, a total of 166 individuals from 32 populations representing 15 medicinal Polygonatum species distributed in China were sampled for study. The interspecific and intraspecific genetic variation of each sequence and sequence combination were estimated, and tree-based and pairwise genetic distance (PWG-distance) methods were applied. The results indicated that except for trnT-trnL, the designed primers for all the other 13 candidate sequences showed good universality. Varying degrees of overlaps were detected between intraspecific and interspecific genetic distances in each of the 14 single candidate sequences and their combinations. Nonetheless, overlaps in the combined sequences were significantly lower than those in single sequences. Species resolution of the 14 single sequences were 6.67%-40% and 20%-60% based on tree-based and PWG-distance methods, separately. The combined sequences possessed higher species-resolving power with 40%-73.33% by tree-based method and 46.67%-73.33% by PWG-distance method, accordingly. Among them, the combined sequences C0 and C1 (in both tree-based and PWG-distance methods), C2 and C3 (in tree-based method), and C25 (in PWG-distance method) all showed the best resolution degree of 73.33%, indicating that combination of sequences could effectively improve species discrimination power. In addition, sequences psaJ-rpl33, rps16-trnQ, trnF-ndhJ, trnT-trnL, trnK-matK and atpF all exhibited relatively higher species-resolving degree, which could be used as specific molecular markers for the identification of medicinal Polygonatum species, and we propose the combination of psaJ-rpl33+rps16-trnQ+trnF-ndhJ+trnK-matK+atpF as the most ideal high-resolution molecular marker for discriminating the medicinal Polygonatum. This study will provide a basis for conservation and utilization of germplasm resources and accurate identification of medicinal Polygonatum, as well as standardizing the market for Polygonati Rhizoma.

, correspAuthors=Ming-ying ZHANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright ©2025 Acta Pharmaceutica Sinica. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Jin-hao CHEN, Wen-ping CHENG, Jing GAO, Yi-min LI, Gang ZHANG, Ying CHEN, Yong-gang YAN, Ming-ying ZHANG), CN=ArticleExt(id=1190374097180787335, articleId=1190373738072867565, tenantId=1146029695717560320, journalId=1189982191388893191, language=CN, title=基于叶绿体基因组种间高变区序列的黄精属药用植物分子鉴定, columnId=1190335348896011050, journalTitle=药学学报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=

黄精属Polygonatum Mill.是天门冬科Asparagaceae一个具有重要药用价值的草本植物类群, 高度的形态多样性、广泛的地理分布、复杂的物种形成过程以及缺乏高分辨率的分子标记, 导致属下种间划分鉴定长期存在争议。本研究以中国分布的黄精属15种代表药用植物来自32个居群共166个个体为对象, 以黄精属叶绿体全基因组14个种间高变区序列作为候选分子标记, 评估其种间、种内变异情况, 并分别基于建树法(tree-based method) 和距离法(pairwise genetic distance method, PWG-distance method) 分析评估各序列及其组合对黄精属药用植物的种间鉴定分辨率。结果显示, 除trnT-trnL外, 其余13条候选分子标记序列的PCR扩增和测序成功率良好; 序列独立、联合分析的种间、种内遗传距离间均存在不同程度的重叠, 其中, 序列联合分析的种间、种内遗传距离重叠程度显著小于独立分析。14组序列独立分析基于建树法和距离法的物种鉴定分辨率分别为6.67%~40%和20%~60%, 联合分析的物种鉴定分辨率分别提升至40%~73.33%和46.67%~73.33%%。其中, 组合序列C0和C1 (建树法和距离法)、C2和C3 (建树法) 以及C25 (距离法) 的物种鉴定分辨率均为最高, 达到73.33%, 说明多序列联合分析能有效提高物种鉴定分辨率。此外, 序列psaJ-rpl33、rps16-trnQ、trnF-ndhJ、trnT-trnL、trnK-matK和atpF及组合序列psaJ-rpl33+rps16-trnQ+trnF-ndhJ+trnK-matK+atpF均具有相对较高的物种鉴定分辨率, 可作为黄精属药用植物种间鉴定的特异性高分辨率分子标记(组合)。本研究将为黄精属药用植物种质资源保护利用和该属植物来源中药材的准确鉴定及规范黄精药材市场提供理论基础。

, correspAuthors=张明英, authorNote=null, correspAuthorsNote=
*张明英, Tel: 86-29-38185165, E-mail:
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#共同第一作者.

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College of Pharmacy and Shaanxi Qinling Application Development and Engineering Center of Chinese Herbal Medicine, Shaanxi University of Chinese Medicine, Xi'an 712046, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1190694615280922803, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, authorId=1190694615075401902, language=CN, stringName=陈锦豪, firstName=锦豪, middleName=null, lastName=陈, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, #, address=1.陕西中医药大学药学院, 陕西省秦岭中草药应用开发工程技术研究中心, 陕西 西安 712046, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1190694614819549347, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, xref=null, ext=[AuthorCompanyExt(id=1190694614832132260, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, companyId=1190694614819549347, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. College of Pharmacy and Shaanxi Qinling Application Development and Engineering Center of Chinese Herbal Medicine, Shaanxi University of Chinese Medicine, Xi'an 712046, China), AuthorCompanyExt(id=1190694614840520869, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, companyId=1190694614819549347, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.陕西中医药大学药学院, 陕西省秦岭中草药应用开发工程技术研究中心, 陕西 西安 712046)])]), Author(id=1190694615394169016, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, orderNo=1, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1190694615511609531, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, authorId=1190694615394169016, language=EN, stringName=Wen-ping CHENG, firstName=Wen-ping, middleName=null, lastName=CHENG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, address=1. College of Pharmacy and Shaanxi Qinling Application Development and Engineering Center of Chinese Herbal Medicine, Shaanxi University of Chinese Medicine, Xi'an 712046, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1190694615704547517, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, authorId=1190694615394169016, language=CN, stringName=程文萍, firstName=文萍, middleName=null, lastName=程, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, #, address=1.陕西中医药大学药学院, 陕西省秦岭中草药应用开发工程技术研究中心, 陕西 西安 712046, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1190694614819549347, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, xref=null, ext=[AuthorCompanyExt(id=1190694614832132260, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, companyId=1190694614819549347, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. College of Pharmacy and Shaanxi Qinling Application Development and Engineering Center of Chinese Herbal Medicine, Shaanxi University of Chinese Medicine, Xi'an 712046, China), AuthorCompanyExt(id=1190694614840520869, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, companyId=1190694614819549347, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.陕西中医药大学药学院, 陕西省秦岭中草药应用开发工程技术研究中心, 陕西 西安 712046)])]), Author(id=1190694615809405121, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, orderNo=2, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1190694615960400069, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, authorId=1190694615809405121, language=EN, stringName=Jing GAO, firstName=Jing, middleName=null, lastName=GAO, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1. College of Pharmacy and Shaanxi Qinling Application Development and Engineering Center of Chinese Herbal Medicine, Shaanxi University of Chinese Medicine, Xi'an 712046, China
2. Key Laboratory for Research of "Qin Medicine" of Shaanxi Administration of Traditional Chinese Medicine, Shaanxi University of Chinese Medicine, Xi'an 712046, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1190694616061063367, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, authorId=1190694615809405121, language=CN, stringName=高静, firstName=静, middleName=null, lastName=高, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1.陕西中医药大学药学院, 陕西省秦岭中草药应用开发工程技术研究中心, 陕西 西安 712046
2.陕西中医药大学, 陕西省中医药管理局"秦药"研发重点实验室, 陕西 西安 712046, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1190694614819549347, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, xref=null, ext=[AuthorCompanyExt(id=1190694614832132260, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, companyId=1190694614819549347, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1. College of Pharmacy and Shaanxi Qinling Application Development and Engineering Center of Chinese Herbal Medicine, Shaanxi University of Chinese Medicine, Xi'an 712046, China), AuthorCompanyExt(id=1190694614840520869, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, companyId=1190694614819549347, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.陕西中医药大学药学院, 陕西省秦岭中草药应用开发工程技术研究中心, 陕西 西安 712046)]), AuthorCompany(id=1190694614936989863, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, xref=null, ext=[AuthorCompanyExt(id=1190694614945378472, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, companyId=1190694614936989863, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2. Key Laboratory for Research of "Qin Medicine" of Shaanxi Administration of Traditional Chinese Medicine, Shaanxi University of Chinese Medicine, Xi'an 712046, China), AuthorCompanyExt(id=1190694614953767081, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, companyId=1190694614936989863, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.陕西中医药大学, 陕西省中医药管理局"秦药"研发重点实验室, 陕西 西安 712046)])]), Author(id=1190694616153338060, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, orderNo=3, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1190694616249807056, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, authorId=1190694616153338060, language=EN, stringName=Yi-min LI, firstName=Yi-min, middleName=null, lastName=LI, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1. College of Pharmacy and Shaanxi Qinling Application Development and Engineering Center of Chinese Herbal Medicine, Shaanxi University of Chinese Medicine, Xi'an 712046, China
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College of Pharmacy and Shaanxi Qinling Application Development and Engineering Center of Chinese Herbal Medicine, Shaanxi University of Chinese Medicine, Xi'an 712046, China), AuthorCompanyExt(id=1190694614840520869, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, companyId=1190694614819549347, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.陕西中医药大学药学院, 陕西省秦岭中草药应用开发工程技术研究中心, 陕西 西安 712046)]), AuthorCompany(id=1190694614936989863, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, xref=null, ext=[AuthorCompanyExt(id=1190694614945378472, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, companyId=1190694614936989863, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2. Key Laboratory for Research of "Qin Medicine" of Shaanxi Administration of Traditional Chinese Medicine, Shaanxi University of Chinese Medicine, Xi'an 712046, China), AuthorCompanyExt(id=1190694614953767081, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, companyId=1190694614936989863, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.陕西中医药大学, 陕西省中医药管理局"秦药"研发重点实验室, 陕西 西安 712046)])], figs=[ArticleFig(id=1190694621295554830, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, language=EN, label=null, caption=null, figureFileSmall=ihJ03RgNrIknXlM1zFmn7A==, figureFileBig=kJxc5Kdmafv4aRiae6684w==, tableContent=null), ArticleFig(id=1190694622331547920, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, language=CN, label=Figure 1, caption= Percentage distribution of interspecific and intraspecific K2P distance of the 14 single candidate sequences. A: <i>trn</i>L-<i>ccs</i>A; B: <i>trn</i>V-<i>trn</i>M-<i>atp</i>E; C: <i>rpl</i>14-<i>rpl</i>16; D: <i>ycf</i>3; E: <i>atp</i>F; F: <i>ccs</i>A-<i>ndh</i>D; G: <i>trn</i>F-<i>ndh</i>J; H: <i>psa</i>J-<i>rpl</i>33; I: <i>rps</i>11-<i>rpl</i>36-<i>inf</i>A; J: <i>trn</i>K-<i>mat</i>K; K: <i>trn</i>T-<i>trn</i>L; L: <i>ycf</i>1; M: <i>rps</i>16-<i>trn</i>Q; N: <i>rps</i>15-<i>ycf</i>1 , figureFileSmall=ihJ03RgNrIknXlM1zFmn7A==, figureFileBig=kJxc5Kdmafv4aRiae6684w==, tableContent=null), ArticleFig(id=1190694622692258066, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, language=EN, label=null, caption=null, figureFileSmall=J9ShqntGNYqkUEqgXbwGHw==, figureFileBig=fIkpiSRmoGvHcOuuVt6tjA==, tableContent=null), ArticleFig(id=1190694622843253011, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, language=CN, label=Figure 2, caption= Neighbor-joining trees inferred utilizing each of the six high species-resolving power sequences. A: <i>psa</i>J-<i>rpl</i>33; B: <i>rps</i>16-<i>trn</i>Q; C: <i>trn</i>K-<i>mat</i>K; D: <i>trn</i>T-<i>trn</i>L; E: <i>trn</i>F-<i>ndh</i>J; F: <i>atp</i>F. CUR: <i>P. curvistylum</i>; GRA: <i>P. gracile</i>; SIB: <i>P. sibiricum</i>; FRA: <i>P. franchetii</i>; MAC: <i>P. macropodum</i>; INV: <i>P. involucratum</i>; FIL: <i>P. filipes</i>; KIN: <i>P. kingianum</i>; ACU: <i>P. acuminatifolium</i>; CYR: <i>P. cyrtonema</i>. Numbers along branches are bootstrap values , figureFileSmall=J9ShqntGNYqkUEqgXbwGHw==, figureFileBig=fIkpiSRmoGvHcOuuVt6tjA==, tableContent=null), ArticleFig(id=1190694622948110613, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, language=EN, label=null, caption=null, figureFileSmall=rLMmYLy3Jy3AV+TAYeZd3A==, figureFileBig=iA8Rr5h5IoJRC6edjcJNqg==, tableContent=null), ArticleFig(id=1190694623111688471, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, language=CN, label=Figure 3, caption= Neighbor-joining trees inferred utilizing the combined sequence datasets. A: C1; B: C25. MEG: <i>P. megaphyllum</i>. Numbers along branches are bootstrap values , figureFileSmall=rLMmYLy3Jy3AV+TAYeZd3A==, figureFileBig=iA8Rr5h5IoJRC6edjcJNqg==, tableContent=null), ArticleFig(id=1190694623237517593, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
Species Number of samples Locality Sample number Voucher number
P. acuminatifolium 7 Baishan City, Jilin Province ACbs1-ACbs7 1_L_2022_wuye_jl
P. cirrhifolium 16 Taibai County, Baoji City, Shaanxi Province CItb1-CItb4 P_JY_001_tb
Aba Tibetan and Qiang Autonomous Prefecture, Sichuan Province CIab1-CIab10 2_L_2022_juanye_sc
Xianyang City, Shaanxi Province CIxy1, CIxy2 15_Y_2022_juanye
P. curvistylum 9 Aba Tibetan and Qiang Autonomous Prefecture, Sichuan Province CUab1-CUab9 10_L_2022_chuiye_sc
P. cyrtonema 8 Yichang City, Hubei Province CYyc1 9_L_2022_duohua_hb
Guiyang City, Guizhou Province CYgy1-CYgy5 12_ZMY_P_gz
Guangzhou City, Guangdong Province CYgz1, CYgz2 14_Y_2022_duohua_gd
P. filipes 19 Liancheng County, Longyan City, Fujian Province FIjj1-FIjj9 3_L_2022_changgeng_gx
Nanping City, Fujian Province FInp1-FInp10 4_L_2022_changgeng_fj
P. franchetii 10 Bazhong City, Sichuan Province FRbz1-FRbz10 7_L_2022_juyao_sc
P. gracile 4 Taibai County, Baoji City, Shaanxi Province GRtb1-GRtb4 P_XGJ_001_tb
P. involucratum 2 Taibai County, Baoji City, Shaanxi Province INtb1, INtb2 P_EBHJ_001_tb
P. kingianum 10 Shimian County, Ya’an City, Sichuan Province KIsm1-KIsm10 5_L_2022_dian_sc
P. macropodum 3 Longhua County, Chengde City, Hebei Province MAdl1-MAdl3 P_RH_01_cd
P. megaphyllum 2 Taibai County, Baoji City, Shaanxi Province MEtb1, MEtb2 P_DBHJ_001_tb
P. odoratum 24 Mei County, Baoji City, Shaanxi Province ODm1 21-009_mx
Cuiji Mountain in Taibai County, Baoji City, Shaanxi Province ODtb1-ODtb9 P_YZ_001_tbcjs
Ecological Park in Taibai County, Shaanxi Province ODsy1-ODsy4 P_YZ_001_tbsty
Baishan City, Jilin Province ODbs1-ODbs10 8_L_2022_yuzhu_jl
P. sibiricum 18 Longhua County, Chengde City, Hebei Province SIlh1-SIlh8 P_huangjing_01_cd
Zhenba County, Hanzhong City, Shaanxi Province SIzb1, SIzb2 21-031_zb
Cuiji Mountain in Taibai County, Baoji City, Shaanxi Province SItb1, SItb2 P_HJ_001_tb
Bald Mountain in Taibai County, Baoji City, Shaanxi Province SIln1-SIln3 P_GTS_001_tb
Xianyang City, Shaanxi Province SIxy1-SIxy3 Y_2022_huangjing_01_xy
P. verticillatum 16 Zhenba County, Hanzhong City, Shaanxi Province VEzb1-VEzb4 21-028_zb
Mei County, Baoji City, Shaanxi Province VEm1-VEm3 21-006_mx
Bazhong City, Sichuan Province VEbz1-VEbz9 P_LY_01_sc
P. zanlanscianense 18 Zhenba County, Hanzhong City, Shaanxi Province ZAzb1 21-034_zb
Mei County, Baoji City, Shaanxi Province ZAm1, ZAm2 21-004_mx
Taibai County, Baoji City, Shaanxi Province ZAtb1-ZAtb5 P_HBHJ_001_tb
Yichang City, Hubei Province ZAyc1-ZAyc10 11_L_2022_hubei_hb
), ArticleFig(id=1190694623388512539, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, language=CN, label=Table 1, caption=

Voucher information of the studied samples

, figureFileSmall=null, figureFileBig=null, tableContent=
Species Number of samples Locality Sample number Voucher number
P. acuminatifolium 7 Baishan City, Jilin Province ACbs1-ACbs7 1_L_2022_wuye_jl
P. cirrhifolium 16 Taibai County, Baoji City, Shaanxi Province CItb1-CItb4 P_JY_001_tb
Aba Tibetan and Qiang Autonomous Prefecture, Sichuan Province CIab1-CIab10 2_L_2022_juanye_sc
Xianyang City, Shaanxi Province CIxy1, CIxy2 15_Y_2022_juanye
P. curvistylum 9 Aba Tibetan and Qiang Autonomous Prefecture, Sichuan Province CUab1-CUab9 10_L_2022_chuiye_sc
P. cyrtonema 8 Yichang City, Hubei Province CYyc1 9_L_2022_duohua_hb
Guiyang City, Guizhou Province CYgy1-CYgy5 12_ZMY_P_gz
Guangzhou City, Guangdong Province CYgz1, CYgz2 14_Y_2022_duohua_gd
P. filipes 19 Liancheng County, Longyan City, Fujian Province FIjj1-FIjj9 3_L_2022_changgeng_gx
Nanping City, Fujian Province FInp1-FInp10 4_L_2022_changgeng_fj
P. franchetii 10 Bazhong City, Sichuan Province FRbz1-FRbz10 7_L_2022_juyao_sc
P. gracile 4 Taibai County, Baoji City, Shaanxi Province GRtb1-GRtb4 P_XGJ_001_tb
P. involucratum 2 Taibai County, Baoji City, Shaanxi Province INtb1, INtb2 P_EBHJ_001_tb
P. kingianum 10 Shimian County, Ya’an City, Sichuan Province KIsm1-KIsm10 5_L_2022_dian_sc
P. macropodum 3 Longhua County, Chengde City, Hebei Province MAdl1-MAdl3 P_RH_01_cd
P. megaphyllum 2 Taibai County, Baoji City, Shaanxi Province MEtb1, MEtb2 P_DBHJ_001_tb
P. odoratum 24 Mei County, Baoji City, Shaanxi Province ODm1 21-009_mx
Cuiji Mountain in Taibai County, Baoji City, Shaanxi Province ODtb1-ODtb9 P_YZ_001_tbcjs
Ecological Park in Taibai County, Shaanxi Province ODsy1-ODsy4 P_YZ_001_tbsty
Baishan City, Jilin Province ODbs1-ODbs10 8_L_2022_yuzhu_jl
P. sibiricum 18 Longhua County, Chengde City, Hebei Province SIlh1-SIlh8 P_huangjing_01_cd
Zhenba County, Hanzhong City, Shaanxi Province SIzb1, SIzb2 21-031_zb
Cuiji Mountain in Taibai County, Baoji City, Shaanxi Province SItb1, SItb2 P_HJ_001_tb
Bald Mountain in Taibai County, Baoji City, Shaanxi Province SIln1-SIln3 P_GTS_001_tb
Xianyang City, Shaanxi Province SIxy1-SIxy3 Y_2022_huangjing_01_xy
P. verticillatum 16 Zhenba County, Hanzhong City, Shaanxi Province VEzb1-VEzb4 21-028_zb
Mei County, Baoji City, Shaanxi Province VEm1-VEm3 21-006_mx
Bazhong City, Sichuan Province VEbz1-VEbz9 P_LY_01_sc
P. zanlanscianense 18 Zhenba County, Hanzhong City, Shaanxi Province ZAzb1 21-034_zb
Mei County, Baoji City, Shaanxi Province ZAm1, ZAm2 21-004_mx
Taibai County, Baoji City, Shaanxi Province ZAtb1-ZAtb5 P_HBHJ_001_tb
Yichang City, Hubei Province ZAyc1-ZAyc10 11_L_2022_hubei_hb
), ArticleFig(id=1190694623489175837, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
Sequence name Primer name Primer Primer sequence (5′-3′) Annealing temperature/℃
trnL-ccsA M1 M1-F ACACGCTGCTCTTAGGAAGC 56.5
M1-R CCATACTGCTCCAGAAAGAATACC
trnV-trnM-atpE M13 M13-F GCCTAGCATTGAATGGGCTGGGTA 59.5
M13-R TCTGATGGGTGGTTTCGCTAG
rpl14-rpl16 M14 M14-F CATTCAAAAGGGTCTGAGGTTG 55.6
M14-R CGGTTCTGTAGTAGAGGTGGGATTA
ycf3 M17 M17-F TTATGAACTGACAGGAGCTGGTATT 57.2
M17-R TACGCTTAGTGAAGGTCAAGTTTGGAGA
atpF M18 M18-F CGTTCATTCGATACTCATCTGC 51.3
M18-R CCATAGCATTTCGTTATTCATTG
ccsA-ndhD M2 M2-F GGTATTCTTTCTGGAGCAGTATGG 54.3
M2-R CTTTCGCTATCAGTTGACAAGG
trnF-ndhJ N10 N10-F CGGGATAGCTCAGTTGGTAGA 55
N10-R GATGCCAGAAAGTTGGATGG
psaJ-rpl33 N14 N14-F GCGCCTGTGCTAACTACTCTAT 56
N14-R CGACCCGAACCTAAGAAGAC
rps11-rpl36-infA N15 N15-F ACGTGAACCAATACGTCCATTC 56.6
N15-R GGATACTGCCGGGAGATAGAGT
trnK-matK N17 N17-F CTACACTACTTACACGGGCATTTC 55.9
N17-R GGAACCTTTCTTGAGCGAACAC
trnT-trnL N18 N18-F TAAGCGGGCTCACATAACAG 51.8
N18-R GAAGGGTCGATATTCTTTCTT
ycf1 N4 N4-F GTGAGTAACGTATCAAAGCCACTT 53.2
N4-R ATGCGATGATGAGAATGAACAA
rps16-trnQ N7 N7-F ATTCAAGTACCAAGGGTTCACAA 55.8
N7-R CTTCCGTCCCAGATCGTCTC
rps15-ycf1 Y2 Y2-F GACTCCCGAATACCTAATTGACC 54.5
Y2-R TCCCGGAATTGGAATGTTGT
), ArticleFig(id=1190694623598227743, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, language=CN, label=Table 2, caption=

Information of the 14 sequences, designed primers and PCR amplification procedures

, figureFileSmall=null, figureFileBig=null, tableContent=
Sequence name Primer name Primer Primer sequence (5′-3′) Annealing temperature/℃
trnL-ccsA M1 M1-F ACACGCTGCTCTTAGGAAGC 56.5
M1-R CCATACTGCTCCAGAAAGAATACC
trnV-trnM-atpE M13 M13-F GCCTAGCATTGAATGGGCTGGGTA 59.5
M13-R TCTGATGGGTGGTTTCGCTAG
rpl14-rpl16 M14 M14-F CATTCAAAAGGGTCTGAGGTTG 55.6
M14-R CGGTTCTGTAGTAGAGGTGGGATTA
ycf3 M17 M17-F TTATGAACTGACAGGAGCTGGTATT 57.2
M17-R TACGCTTAGTGAAGGTCAAGTTTGGAGA
atpF M18 M18-F CGTTCATTCGATACTCATCTGC 51.3
M18-R CCATAGCATTTCGTTATTCATTG
ccsA-ndhD M2 M2-F GGTATTCTTTCTGGAGCAGTATGG 54.3
M2-R CTTTCGCTATCAGTTGACAAGG
trnF-ndhJ N10 N10-F CGGGATAGCTCAGTTGGTAGA 55
N10-R GATGCCAGAAAGTTGGATGG
psaJ-rpl33 N14 N14-F GCGCCTGTGCTAACTACTCTAT 56
N14-R CGACCCGAACCTAAGAAGAC
rps11-rpl36-infA N15 N15-F ACGTGAACCAATACGTCCATTC 56.6
N15-R GGATACTGCCGGGAGATAGAGT
trnK-matK N17 N17-F CTACACTACTTACACGGGCATTTC 55.9
N17-R GGAACCTTTCTTGAGCGAACAC
trnT-trnL N18 N18-F TAAGCGGGCTCACATAACAG 51.8
N18-R GAAGGGTCGATATTCTTTCTT
ycf1 N4 N4-F GTGAGTAACGTATCAAAGCCACTT 53.2
N4-R ATGCGATGATGAGAATGAACAA
rps16-trnQ N7 N7-F ATTCAAGTACCAAGGGTTCACAA 55.8
N7-R CTTCCGTCCCAGATCGTCTC
rps15-ycf1 Y2 Y2-F GACTCCCGAATACCTAATTGACC 54.5
Y2-R TCCCGGAATTGGAATGTTGT
), ArticleFig(id=1190694623765999905, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
Primer name PCR amplification success rate (%)/number of samples Sequencing success rate (%)/number of sequences Sequence receiving rate/% Aligned sequence length/bp Variable sites (bp)/rate Parsimony informative sites (bp)/rate Number of identified species/discriminatory power (%)
Tree-based method PWG-distance method
trnL-ccsA 100/166 100/166 100 575 14/2.43% 13/2.26% 1/6.67 4/26.67
trnV-trnM-atpE 99.4/165 100/165 99.4 681 25/3.67% 16/2.35% 2/13.33 6/40
rpl14-rpl16 95.78/159 99.37/158 95.18 481 41/8.52% 23/4.78% 2/13.33 5/33.33
ycf3 100/166 100/166 100 387 11/2.84% 6/1.55% 1/6.67 3/20
atpF 100/166 100/166 100 600 16/2.67% 16/2.67% 3/20 8/53.33
ccsA-ndhD 100/166 100/166 100 457 25/5.74% 23/5.03% 3/20 5/33.33
trnF-ndhJ 99.4/165 100/165 99.4 709 27/3.81% 22/3.10% 5/33.33 8/53.33
psaJ-rpl33 98.8/164 100/164 98.8 535 29/5.42% 25/4.67% 6/40 7/46.67
rps11-rpl36-infA 100/166 100/166 100 348 17/4.89% 13/3.74% 2/13.33 5/33.33
trnK-matK 100/166 100/166 100 646 23/3.56% 18/2.79% 3/20 8/53.33
trnT-trnL 65.06/108 90.47/98 59.04 662 45/6.80% 27/4.08% 5/33.33 7/46.67
ycf1 92.17/153 99.35/152 91.57 503 27/5.37% 21/4.17% 1/6.67 4/26.67
rps16-trnQ 96.99/161 100/161 96.99 744 31/4.17% 28/3.76% 5/33.33 9/60
rps15-ycf1 98.8/164 100/164 98.8 697 25/3.59% 20/2.87% 2/13.33 6/40
), ArticleFig(id=1190694623862468899, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, language=CN, label=Table 3, caption=

Results of PCR amplification, sequencing, and characteristics and species discriminatory power of the 14 sequences based on tree-based and pairwise genetic distance (PWG-distance) method

, figureFileSmall=null, figureFileBig=null, tableContent=
Primer name PCR amplification success rate (%)/number of samples Sequencing success rate (%)/number of sequences Sequence receiving rate/% Aligned sequence length/bp Variable sites (bp)/rate Parsimony informative sites (bp)/rate Number of identified species/discriminatory power (%)
Tree-based method PWG-distance method
trnL-ccsA 100/166 100/166 100 575 14/2.43% 13/2.26% 1/6.67 4/26.67
trnV-trnM-atpE 99.4/165 100/165 99.4 681 25/3.67% 16/2.35% 2/13.33 6/40
rpl14-rpl16 95.78/159 99.37/158 95.18 481 41/8.52% 23/4.78% 2/13.33 5/33.33
ycf3 100/166 100/166 100 387 11/2.84% 6/1.55% 1/6.67 3/20
atpF 100/166 100/166 100 600 16/2.67% 16/2.67% 3/20 8/53.33
ccsA-ndhD 100/166 100/166 100 457 25/5.74% 23/5.03% 3/20 5/33.33
trnF-ndhJ 99.4/165 100/165 99.4 709 27/3.81% 22/3.10% 5/33.33 8/53.33
psaJ-rpl33 98.8/164 100/164 98.8 535 29/5.42% 25/4.67% 6/40 7/46.67
rps11-rpl36-infA 100/166 100/166 100 348 17/4.89% 13/3.74% 2/13.33 5/33.33
trnK-matK 100/166 100/166 100 646 23/3.56% 18/2.79% 3/20 8/53.33
trnT-trnL 65.06/108 90.47/98 59.04 662 45/6.80% 27/4.08% 5/33.33 7/46.67
ycf1 92.17/153 99.35/152 91.57 503 27/5.37% 21/4.17% 1/6.67 4/26.67
rps16-trnQ 96.99/161 100/161 96.99 744 31/4.17% 28/3.76% 5/33.33 9/60
rps15-ycf1 98.8/164 100/164 98.8 697 25/3.59% 20/2.87% 2/13.33 6/40
), ArticleFig(id=1190694623979909413, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
Sequencea Intraspecific distance Interspecific distance
Minimum Maximum Average Minimum Maximum Average
M1 0 0.003 70 0.000 99 0. 0.012 47 0.006 07
M13 0 0.002 60 0.000 73 0. 0.013 29 0.006 70
M14 0 0.008 36 0.002 34 0. 0.023 29 0.010 05
M17 0 0.002 02 0.000 57 0. 0.007 90 0.003 12
M18 0 0.002 70 0.000 73 0.000 48 0.015 73 0.007 41
M2 0 0.010 70 0.002 68 0. 0.035 97 0.020 11
N10 0 0.002 71 0.000 80 0.000 18 0.018 01 0.009 09
N14 0 0.004 95 0.000 81 0. 0.021 07 0.010 11
N15 0 0.003 98 0.001 04 0. 0.020 39 0.008 30
N17 0 0.003 27 0.000 62 0. 0.010 10 0.005 76
N18 0 0.007 16 0.002 18 0.000 61 0.016 87 0.010 02
N4 0 0.005 39 0.001 70 0. 0.018 57 0.007 31
N7 0 0.005 29 0.001 71 0.001 80 0.030 39 0.010 98
Y2 0 0.004 82 0.001 44 0.000 88 0.016 28 0.008 50
C0 0 0.003 45 0.000 84 0.001 91 0.013 78 0.008 57
C1 0 0.003 05 0.000 98 0.001 96 0.013 42 0.008 46
C2 0 0.002 99 0.001 01 0.001 81 0.013 85 0.008 68
C3 0 0.003 22 0.001 01 0.001 92 0.013 88 0.008 77
C4 0 0.003 16 0.001 00 0.002 12 0.013 89 0.008 57
C5 0 0.003 24 0.001 03 0.002 15 0.014 42 0.008 92
C6 0 0.003 36 0.001 03 0.002 05 0.014 24 0.008 82
C7 0 0.003 18 0.001 04 0.001 76 0.014 39 0.009 03
C8 0 0.003 46 0.001 07 0.002 00 0.014 85 0.009 22
C9 0 0.003 61 0.001 17 0.002 24 0.015 26 0.009 55
C10 0 0.003 32 0.001 02 0.002 06 0.014 97 0.009 18
C11 0 0.003 74 0.001 07 0.001 93 0.014 85 0.009 31
C12 0 0.003 59 0.001 08 0.002 02 0.015 14 0.009 29
C13 0 0.003 56 0.001 10 0.002 41 0.015 65 0.009 56
C14 0 0.003 92 0.001 17 0.002 27 0.015 32 0.009 73
C15 0 0.003 76 0.001 20 0.002 07 0.015 64 0.009 66
C16 0 0.003 31 0.001 02 0.002 00 0.015 06 0.009 27
C17 0 0.003 34 0.001 04 0.002 15 0.015 40 0.009 26
C18 0 0.003 91 0.001 09 0.002 04 0.015 27 0.009 41
C19 0 0.003 42 0.001 03 0.002 19 0.015 58 0.009 37
C20 0 0.004 13 0.001 20 0.002 11 0.015 72 0.009 87
C21 0 0.003 61 0.001 13 0.002 23 0.016 01 0.009 68
C22 0 0.003 43 0.001 09 0.002 41 0.016 07 0.009 74
C23 0 0.003 57 0.001 12 0.002 31 0.016 65 0.009 91
C24 0 0.003 63 0.001 24 0.002 53 0.018 95 0.010 91
C25 0 0.002 96 0.000 91 0.001 94 0.015 44 0.008 44
C26 0 0.003 99 0.001 20 0.002 03 0.018 16 0.010 44
C27 0 0.003 14 0.000 96 0.001 89 0.016 21 0.008 69
C28 0 0.004 17 0.001 37 0.002 16 0.022 55 0.011 89
C29 0 0.003 08 0.000 99 0.002 10 0.017 09 0.009 21
C30 0 0.003 36 0.001 08 0.002 00 0.019 00 0.009 85
C31 0 0.003 41 0.000 80 0.001 12 0.017 94 0.009 52
C32 0 0.003 72 0.001 30 0.001 12 0.020 09 0.010 25
), ArticleFig(id=1190694624097349927, tenantId=1146029695717560320, journalId=1189982191388893191, articleId=1190373738072867565, language=CN, label=Table 4, caption=

Interspecific and intraspecific K2P distance of the 14 sequences and their combinations. aNames of the 14 single sequences were represented by using their primer names

, figureFileSmall=null, figureFileBig=null, tableContent=
Sequencea Intraspecific distance Interspecific distance
Minimum Maximum Average Minimum Maximum Average
M1 0 0.003 70 0.000 99 0. 0.012 47 0.006 07
M13 0 0.002 60 0.000 73 0. 0.013 29 0.006 70
M14 0 0.008 36 0.002 34 0. 0.023 29 0.010 05
M17 0 0.002 02 0.000 57 0. 0.007 90 0.003 12
M18 0 0.002 70 0.000 73 0.000 48 0.015 73 0.007 41
M2 0 0.010 70 0.002 68 0. 0.035 97 0.020 11
N10 0 0.002 71 0.000 80 0.000 18 0.018 01 0.009 09
N14 0 0.004 95 0.000 81 0. 0.021 07 0.010 11
N15 0 0.003 98 0.001 04 0. 0.020 39 0.008 30
N17 0 0.003 27 0.000 62 0. 0.010 10 0.005 76
N18 0 0.007 16 0.002 18 0.000 61 0.016 87 0.010 02
N4 0 0.005 39 0.001 70 0. 0.018 57 0.007 31
N7 0 0.005 29 0.001 71 0.001 80 0.030 39 0.010 98
Y2 0 0.004 82 0.001 44 0.000 88 0.016 28 0.008 50
C0 0 0.003 45 0.000 84 0.001 91 0.013 78 0.008 57
C1 0 0.003 05 0.000 98 0.001 96 0.013 42 0.008 46
C2 0 0.002 99 0.001 01 0.001 81 0.013 85 0.008 68
C3 0 0.003 22 0.001 01 0.001 92 0.013 88 0.008 77
C4 0 0.003 16 0.001 00 0.002 12 0.013 89 0.008 57
C5 0 0.003 24 0.001 03 0.002 15 0.014 42 0.008 92
C6 0 0.003 36 0.001 03 0.002 05 0.014 24 0.008 82
C7 0 0.003 18 0.001 04 0.001 76 0.014 39 0.009 03
C8 0 0.003 46 0.001 07 0.002 00 0.014 85 0.009 22
C9 0 0.003 61 0.001 17 0.002 24 0.015 26 0.009 55
C10 0 0.003 32 0.001 02 0.002 06 0.014 97 0.009 18
C11 0 0.003 74 0.001 07 0.001 93 0.014 85 0.009 31
C12 0 0.003 59 0.001 08 0.002 02 0.015 14 0.009 29
C13 0 0.003 56 0.001 10 0.002 41 0.015 65 0.009 56
C14 0 0.003 92 0.001 17 0.002 27 0.015 32 0.009 73
C15 0 0.003 76 0.001 20 0.002 07 0.015 64 0.009 66
C16 0 0.003 31 0.001 02 0.002 00 0.015 06 0.009 27
C17 0 0.003 34 0.001 04 0.002 15 0.015 40 0.009 26
C18 0 0.003 91 0.001 09 0.002 04 0.015 27 0.009 41
C19 0 0.003 42 0.001 03 0.002 19 0.015 58 0.009 37
C20 0 0.004 13 0.001 20 0.002 11 0.015 72 0.009 87
C21 0 0.003 61 0.001 13 0.002 23 0.016 01 0.009 68
C22 0 0.003 43 0.001 09 0.002 41 0.016 07 0.009 74
C23 0 0.003 57 0.001 12 0.002 31 0.016 65 0.009 91
C24 0 0.003 63 0.001 24 0.002 53 0.018 95 0.010 91
C25 0 0.002 96 0.000 91 0.001 94 0.015 44 0.008 44
C26 0 0.003 99 0.001 20 0.002 03 0.018 16 0.010 44
C27 0 0.003 14 0.000 96 0.001 89 0.016 21 0.008 69
C28 0 0.004 17 0.001 37 0.002 16 0.022 55 0.011 89
C29 0 0.003 08 0.000 99 0.002 10 0.017 09 0.009 21
C30 0 0.003 36 0.001 08 0.002 00 0.019 00 0.009 85
C31 0 0.003 41 0.000 80 0.001 12 0.017 94 0.009 52
C32 0 0.003 72 0.001 30 0.001 12 0.020 09 0.010 25
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基于叶绿体基因组种间高变区序列的黄精属药用植物分子鉴定
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陈锦豪 1, # , 程文萍 1, # , 高静 1, 2 , 李依民 1, 2 , 张岗 1, 2 , 陈莹 1, 2 , 颜永刚 1, 2 , 张明英 1, 2, *
药学学报 | 研究论文 2025,60(5): 1543-1554
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药学学报 | 研究论文 2025, 60(5): 1543-1554
基于叶绿体基因组种间高变区序列的黄精属药用植物分子鉴定
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陈锦豪1, #, 程文萍1, #, 高静1, 2, 李依民1, 2, 张岗1, 2, 陈莹1, 2, 颜永刚1, 2, 张明英1, 2, *
作者信息
  • 1.陕西中医药大学药学院, 陕西省秦岭中草药应用开发工程技术研究中心, 陕西 西安 712046
  • 2.陕西中医药大学, 陕西省中医药管理局"秦药"研发重点实验室, 陕西 西安 712046

通讯作者:

*张明英, Tel: 86-29-38185165, E-mail:
Molecular identification of medicinal Polygonatum species based on plastid divergence hotspot regions
Jin-hao CHEN1, Wen-ping CHENG1, Jing GAO1, 2, Yi-min LI1, 2, Gang ZHANG1, 2, Ying CHEN1, 2, Yong-gang YAN1, 2, Ming-ying ZHANG1, 2, *
Affiliations
  • 1. College of Pharmacy and Shaanxi Qinling Application Development and Engineering Center of Chinese Herbal Medicine, Shaanxi University of Chinese Medicine, Xi'an 712046, China
  • 2. Key Laboratory for Research of "Qin Medicine" of Shaanxi Administration of Traditional Chinese Medicine, Shaanxi University of Chinese Medicine, Xi'an 712046, China
出版时间: 2025-05-12 doi: 10.16438/j.0513-4870.2024-1272
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黄精属Polygonatum Mill.是天门冬科Asparagaceae一个具有重要药用价值的草本植物类群, 高度的形态多样性、广泛的地理分布、复杂的物种形成过程以及缺乏高分辨率的分子标记, 导致属下种间划分鉴定长期存在争议。本研究以中国分布的黄精属15种代表药用植物来自32个居群共166个个体为对象, 以黄精属叶绿体全基因组14个种间高变区序列作为候选分子标记, 评估其种间、种内变异情况, 并分别基于建树法(tree-based method) 和距离法(pairwise genetic distance method, PWG-distance method) 分析评估各序列及其组合对黄精属药用植物的种间鉴定分辨率。结果显示, 除trnT-trnL外, 其余13条候选分子标记序列的PCR扩增和测序成功率良好; 序列独立、联合分析的种间、种内遗传距离间均存在不同程度的重叠, 其中, 序列联合分析的种间、种内遗传距离重叠程度显著小于独立分析。14组序列独立分析基于建树法和距离法的物种鉴定分辨率分别为6.67%~40%和20%~60%, 联合分析的物种鉴定分辨率分别提升至40%~73.33%和46.67%~73.33%%。其中, 组合序列C0和C1 (建树法和距离法)、C2和C3 (建树法) 以及C25 (距离法) 的物种鉴定分辨率均为最高, 达到73.33%, 说明多序列联合分析能有效提高物种鉴定分辨率。此外, 序列psaJ-rpl33、rps16-trnQ、trnF-ndhJ、trnT-trnL、trnK-matK和atpF及组合序列psaJ-rpl33+rps16-trnQ+trnF-ndhJ+trnK-matK+atpF均具有相对较高的物种鉴定分辨率, 可作为黄精属药用植物种间鉴定的特异性高分辨率分子标记(组合)。本研究将为黄精属药用植物种质资源保护利用和该属植物来源中药材的准确鉴定及规范黄精药材市场提供理论基础。

黄精属  /  种间鉴定  /  分子标记  /  药用植物  /  序列变异

Polygonatum Mill. (Asparagaceae) is a pharmaceutically important genus with many species are of significant medicinal value. Taxonomy and interspecific identification of Polygonatum species have long been controversial due to their considerable morphological variation, wide geographic distribution, complex speciation processes, and lacking of high-resolution molecular markers. To evaluate species discrimination power of 14 plastid divergence hotspot regions (candidate sequences) and their combinations in Polygonatum, a total of 166 individuals from 32 populations representing 15 medicinal Polygonatum species distributed in China were sampled for study. The interspecific and intraspecific genetic variation of each sequence and sequence combination were estimated, and tree-based and pairwise genetic distance (PWG-distance) methods were applied. The results indicated that except for trnT-trnL, the designed primers for all the other 13 candidate sequences showed good universality. Varying degrees of overlaps were detected between intraspecific and interspecific genetic distances in each of the 14 single candidate sequences and their combinations. Nonetheless, overlaps in the combined sequences were significantly lower than those in single sequences. Species resolution of the 14 single sequences were 6.67%-40% and 20%-60% based on tree-based and PWG-distance methods, separately. The combined sequences possessed higher species-resolving power with 40%-73.33% by tree-based method and 46.67%-73.33% by PWG-distance method, accordingly. Among them, the combined sequences C0 and C1 (in both tree-based and PWG-distance methods), C2 and C3 (in tree-based method), and C25 (in PWG-distance method) all showed the best resolution degree of 73.33%, indicating that combination of sequences could effectively improve species discrimination power. In addition, sequences psaJ-rpl33, rps16-trnQ, trnF-ndhJ, trnT-trnL, trnK-matK and atpF all exhibited relatively higher species-resolving degree, which could be used as specific molecular markers for the identification of medicinal Polygonatum species, and we propose the combination of psaJ-rpl33+rps16-trnQ+trnF-ndhJ+trnK-matK+atpF as the most ideal high-resolution molecular marker for discriminating the medicinal Polygonatum. This study will provide a basis for conservation and utilization of germplasm resources and accurate identification of medicinal Polygonatum, as well as standardizing the market for Polygonati Rhizoma.

Polygonatum Mill.  /  interspecific identification  /  molecular marker  /  medicinal species  /  sequence divergence
陈锦豪, 程文萍, 高静, 李依民, 张岗, 陈莹, 颜永刚, 张明英. 基于叶绿体基因组种间高变区序列的黄精属药用植物分子鉴定. 药学学报, 2025 , 60 (5) : 1543 -1554 . DOI: 10.16438/j.0513-4870.2024-1272
Jin-hao CHEN, Wen-ping CHENG, Jing GAO, Yi-min LI, Gang ZHANG, Ying CHEN, Yong-gang YAN, Ming-ying ZHANG. Molecular identification of medicinal Polygonatum species based on plastid divergence hotspot regions[J]. Acta Pharmaceutica Sinica, 2025 , 60 (5) : 1543 -1554 . DOI: 10.16438/j.0513-4870.2024-1272
黄精属Polygonatum Mill.是天门冬科Asparagaceae黄精族Polygonateae中物种数量最多且具有重要药用价值的草本植物类群。全世界分布有黄精属植物约78种(https://powo.science.kew.org/), 中国约39种, 其中31种在不同地区入药使用[1, 2], 是中药材的重要来源。药理学研究指出, 黄精属植物含多糖、甾体皂苷、黄酮、生物碱等多种活性成分, 具有抗肿瘤、抗衰老、抗菌、抗炎、抗病毒、调节免疫、降血糖血脂等作用[3, 4], 在中医临床和现代药物研发中应用广泛。中国药典(2020年版一部) 收载的中药材黄精(Polygonati Rhizoma)、玉竹(Polygonati Odorati Rhizoma) 分别来源于黄精属药用植物黄精P. sibiricum Delar. ex Redoute、多花黄精P. cyrtonema Hua和滇黄精P. kingianum Collett & Hemsl及玉竹P. odoratum (Mill.) Druce的干燥根茎, 具有补气养阴、健脾、润肺、益肾和养阴润燥、生津止渴等功效[5]。同时, 作为重要的药食同源中药材, 黄精和玉竹也被广泛用于食品、保健品、化妆品等开发[6]
中药材基原物种的准确鉴定是保证用药安全和临床疗效的关键基础。研究表明, 黄精属不同植物所含主要药用活性成分和含量不尽相同[7-9], 入药功效也有所差异[3, 4]。然而, 由于形态变异复杂多样, 地理分布广泛重叠, 种间及同种不同居群个体间常存在形态上的过渡类型, 导致种间划分和形态鉴定长期存在争议[10-12]。而黄精属植物多以根状茎入药, 生药性状的相似性更增加了药材基原准确鉴定的难度[10, 13]。黄精属内不同物种混用、误用、非正品基原替代黄精或玉竹使用, 甚至伪品入药现象时有发生[2, 10, 13], 严重影响该属植物来源中药材的入药安全性和临床疗效。
DNA条形码分子鉴定技术基于物种遗传信息DNA序列的独特性和稳定性从基因水平为药用植物及中药材基原的客观准确鉴定提供了有力补充[14]。植物类群鉴定通用DNA条形码, 包括叶绿体基因matK、rbcL、基因间区psbA-trnH和核基因间区ITS、ITS2等序列[15-17]。此外, 一些高变异叶绿体基因及基因间区序列(rps16-trnQ、trnL-trnF、trnT-trnL、psbK-psbI、ycf1等) 也被广泛用于药用植物及其来源中药材的分子鉴定研究[18-23]。然而, 黄精属植物在物种形成过程中经历了复杂的网状进化(包括杂交和多倍化等)[12]和快速辐射分化[24], 研究表明, 通用DNA条形码序列及常规叶绿体分子标记对黄精属物种鉴定的分辨率有限, 不能实现不同种间有效区分鉴别[25]。其中, ITS和ITS2序列在黄精属不同物种中的PCR扩增成功率低(< 50%)[13, 26], matK、rbcL及psbA-trnH等序列的种间变异信息位点不足, 物种鉴定分辨率仅分别为29%~41.67%、5%~16.66%和8.33%~31%[13, 26, 27]。此外, Meng等[11]和Zhao等[28]分别利用叶绿体rbcL、trnK、psbA-trnH及trnC-petN序列和atpB-rbcL、matK、rbcL及rps16序列联合对黄精属的分子系统发育研究结果均未能有效解决其种间划分问题。
被子植物叶绿体基因组序列中常存在一些种间高变区(divergence hotspot regions), 可以作为物种鉴定的潜在分子标记, 然而, 其种间鉴定分辨率需要进一步的实验分析进行验证[19, 29]。本项目前期基于二代高通量测序获得了黄精属28个物种来自不同分布地区共58个代表个体的叶绿体全基因组序列, 对其进行了种间、种内变异比较分析, 共筛选到14个种间高变区(未发表数据)。在此基础上, 本研究拟以这14个种间高变区序列作为候选分子标记, 设计引物, 通过PCR扩增和测序获取目的序列, 进一步分析评估其对黄精属药用植物的种间鉴定分辨率, 以期挖掘适用于黄精属药用植物种间区分鉴定的特异性高分辨率分子标记, 为黄精属药用植物种质资源保护、利用及其来源中药材的准确鉴定和规范黄精药材市场提供理论依据。
实验材料  以《中国药用植物志》[2]中收载的黄精属15种代表药用植物为研究对象, 采集野生自然生长状态下的健康幼嫩叶片, 硅胶快速脱水干燥保存, 作为实验材料, 同时采集凭证标本。共采集得到来自32个居群共166份代表个体。凭证标本经陕西中医药大学中药标本馆王继涛高级实验师鉴定, 并保存于陕西中医药大学中药标本馆(实验材料及标本信息见表 1)。
基因组DNA提取  利用改良的CTAB法[30]提取基因组总DNA, TE缓冲液溶解, 并分别用1%的琼脂糖凝胶电泳和超微量分光光度计(KAIAO, K5800) 检测DNA溶液的质量与浓度, 检测合格的DNA溶液-20 ℃保存备用。
引物设计、PCR扩增、测序  以前期筛选的叶绿体全基因组14个种间高变区序列为模板, 利用Primer Premier 5.0设计引物, 分别对166份实验材料进行PCR扩增。PCR扩增反应均为50 μL混合体系, 包括2×SanTaq PCR Mix [with Blue Dye, B532061, 生工生物工程(上海) 股份有限公司] 25 μL, 正、反向引物(10 μmol·L-1) 各2 μL, 模板DNA 5 μL和ddH2O 16 μL。PCR扩增反应程序为: 94 ℃预变性5 min; 94 ℃变性30 s, 51.3~59.5 ℃退火30 s, 72 ℃延伸1 min, 共35个循环; 72 ℃延伸10 min; 反应结束后4 ℃保存(引物信息及PCR反应退火温度见表 2)。PCR扩增反应在TTM 100 Thermal Cycler (Bio-Rad, Singapore) 上完成。PCR产物经1%琼脂糖凝胶电泳检测, 扩增成功的产物进行Sanger测序。PCR引物序列合成和测序均由生工生物工程(上海) 股份有限公司完成。
序列拼接及变异分析  利用Sequencher v.4.6对测序得到的原始数据进行序列拼接, 去除引物及两端的低质量序列, 并根据测序峰图对各个位点的碱基进行检查校正。在Geneious v.8.0.2中将得到的14组候选分子标记序列分别构建多序列矩阵, 利用MAFFT完成序列比对。利用MEGA v.7.0计算各组序列的变异位点(variable site)、简约信息位点(parsimony informative site) 含量和种间、种内K2P (Kimura 2-parameter distance) 遗传距离, 评估种间、种内遗传距离间是否存在“Barcoding gap”。
物种鉴定分析  分别基于建树法(tree-based method) 和距离法(pairwise genetic distance method, PWG-distance method) 分析评估各组序列的物种鉴定分辨率。建树法即利用MEGA软件基于K2P距离和配对删除(pair-deletion) 模型, 构建邻接系统发育树(neighbor-joining tree, NJ tree), 系统树各分支节点的靴带支持率(bootstrap values, BS) 通过进行1 000次自展重复分析计算得到。当同一物种内所有个体在系统树上聚为一个单系, 且支持率高于50%, 则视为该物种被鉴定成功[16, 26]; 距离法即分别计算各组序列的种间、种内遗传距离, 当某物种与其他物种的最小种间遗传距离大于该物种种内所有个体间的最大遗传距离时, 视为该物种被鉴定成功[15]。此外, 将14组序列分别进行组合, 同样基于建树法和距离法分析评估不同序列组合的物种鉴定成功率。序列组合方法为: 首先, 将所有14组序列比对后进行串联合并, 得到组合序列C0; 其次, 由于序列trnT-trnL的PCR扩增成功率(65.06%) 和最终有效序列获得率(59.04%) 较低, 去除该序列, 并将其余13组序列根据其独立分析物种鉴定分辨率由高到低进行排序, 依次去除分辨率最低的序列(若多条序列独立分析物种鉴定分辨率相同, 则每次去除其中1条), 并将剩余序列进行串联合并, 得到组合序列C1、C2、C3……C32, 即最终共得到33组分子标记组合序列。序列组合时, 当某个体出现序列缺失情况(如2条序列组合时, 某个体只有1条序列; 3条序列组合时, 某个体只有1条或2条序列, 依次类推), 则将有序列缺失的个体在分析中去除。
PCR扩增、测序结果及序列特征见表 3。除trnT-trnL外, 其余13组序列的PCR扩增和测序成功率分别为92.17%~100%和99.35%~100%, 最终有效序列得率为91.57%~100%。14组序列比对后的长度为348~744 bp, 变异位点和简约信息位点含量分别为2.43%~8.52%和1.55%~5.03%。其中, 序列rps16-trnQ和trnF-ndhJ的长度均大于700 bp, 同时rps16-trnQ序列的简约信息位点数量亦为最多。
14条候选分子标记序列独立、联合分析的种间、种内遗传距离见表 4。独立分析的种内最小遗传距离均为0, 最大遗传距离为0.002 02~0.010 7, 平均为0.000 57~0.002 68; 种间最小遗传距离为0~0.001 8, 最大遗传距离为0.007 90~0.035 97, 平均为0.003 12~0.020 11。其中, rps16-trnQ独立分析的种间最小遗传距离最大, ycf3的种内最大遗传距离和种间最小遗传距离均为最小。33组组合序列的种内最小遗传距离亦均为0, 最大遗传距离为0.002 96~0.004 17, 平均为0.000 80~0.001 37; 种间最小遗传距离为0.001 12~0.002 53, 最大遗传距离为0.013 42~0.022 55, 平均为0.008 44~0.011 89。其中, 组合序列C25的种内最大遗传距离最小, C28的种内最大遗传距离和种间最小遗传距离均为最大, C31和C32的种间最小遗传距离相同且均为最小。
Barcoding gap分析结果显示, 序列独立、联合分析的种间、种内遗传距离均存在一定程度重叠, 两者均未检测到明显的Barcoding gap (图 1)。其中, 序列联合分析的种间、种内遗传距离重叠程度显著小于独立分析, rps16-trnQ、trnF-ndhJ、trnT-trnL及组合序列C25、C27、C29、C24和C30等的种间、种内遗传距离重叠的范围较小, ycf1、ycf3和C28、C31等的种间、种内遗传距离重叠的范围相对较多。
14条候选分子标记序列基于建树法分析的物种鉴定分辨率为6.67%~40%, 分别有1~6个物种可被不同的序列独立鉴别(表 3, 图 2)。其中, psaJ-rpl33序列的物种鉴定分辨率最高, 为40%, 黄精、距药黄精P. franchetii Hua、细根茎黄精P. gracile P. Y. Li、热河黄精P. macropodum Turcz.、垂叶黄精P. curvistylum Hua和二苞黄精P. involucratum (Franch. & Sav.) Maxim.6个物种的种内不同个体均能够以 > 50%的支持率各自聚类为单系, 被成功鉴定; rps16-trnQ、trnF-ndhJ和trnT-trnL的分辨率次之, 分别可成功鉴定5个物种; trnK-matK、ccsA-ndhD和atpF可分别成功鉴定3个物种; trnL-ccsA、ycf3和ycf1的分辨率最低, 均仅6.67%, 垂叶黄精、细根茎黄精和滇黄精依次分别被成功鉴别。
序列联合分析基于建树法的物种鉴定分辨率为40%~73.33%。其中, 组合序列C0、C1、C2、C3的物种鉴定分辨率最高, 均为73.33%, 除卷叶黄精P. cirrhifolium (Wall.) Royle、玉竹、轮叶黄精P. verticillatum (L.) All.和湖北黄精P. zanlanscianense Pamp.之外, 其余11个物种内的不同个体均以 > 50%的支持率各自聚类为单系, 被成功鉴定(图 3A)。C4、C7的分辨率均为66.67%, 可成功鉴别10个物种; C6、C8、C11、C12、C15、C18、C19、C20和C25 (图 3B), C5、C9、C10、C13、C14、C16、C17、C21、C22、C23、C24和C27, 以及C26、C29、C30、C31和C32的物种鉴定分辨率依次分别为60%、53.33%、46.67%, 可分别成功鉴别9、8及7个物种; C28分辨率最低, 为40%, 可鉴别6个物种。
14条候选分子标记序列基于距离法分析的物种鉴定分辨率为20%~60%, 分别有3~9个物种可被成功鉴别(表 3)。其中, 序列trnK-matK独立分析的物种鉴定分辨率最高, 为60%, 垂叶黄精、细根茎黄精、大苞黄精P. megaphyllum P. Y. Li、距药黄精、二苞黄精、五叶黄精P. acuminatifolium Kom.、热河黄精、长梗黄精P. filipes Merr. ex C. Jeffrey & McEwan和湖北黄精共9个物种的种内最大遗传距离均小于其与其他物种间的最小遗传距离而被成功鉴别。TrnF-ndhJ、trnK-matK和atpF分辨率次之, 均为53.33%, 可成功鉴定8个物种; psaJ-rpl33和trnT-trnL, trnV-trnM-atpE和rps15-ycf1, rpl14-rpl16、ccsA-ndhD和rps11-rpl36-infA, 以及trnL-ccsA和ycf1的物种鉴定分辨率依次分别为46.67%、40%、33.33%和26.67%, 分别有7、6、5和4个物种可被成功鉴别; ycf3的分辨最低, 为20%, 仅可成功鉴别3个物种。
33组组合序列基于距离法的物种鉴定分析结果显示, C0、C1和C25的物种鉴定分辨率最高, 均为73.33%, 其中, C0和C1均可鉴别除卷叶黄精、玉竹、轮叶黄精和湖北黄精之外的其余11个物种, 与建树法分析结果一致; C25可鉴别除卷叶黄精、玉竹、轮叶黄精、多花黄精之外的其余11个物种。C2、C3、C4、C5、C6、C7、C8、C10、C12、C16、C17、C19、C23、C29和C32的分辨率次之, 均为66.67%, 可成功鉴定10个物种; C9、C11、C13、C14、C15、C18、C20、C21、C22、C24、C26、C27、C30和C31的物种鉴定分辨率均为60%, 可成功鉴定9个物种; C28的分辨率最低, 为46.67%, 可有效鉴别7个物种。
引物通用性是评价物种鉴定分子标记的一个重要指标[15, 16]。本研究对黄精属植物叶绿体全基因组14个种间高变区设计引物, 通过PCR扩增、测序及分子鉴定分析, 综合评估其对黄精属药用植物种间鉴定效率。结果显示, 除N18 (trnT-trnL) 的PCR扩增成功率相对较低(65.06%) 之外, 其余13对引物的PCR扩增和测序成功率分别为92.17%~100%和99.35%~100%, 其中M1 (trnL-ccsA)、M17 (ycf3)、M18 (atpF)、N15 (rps11-rpl36-infA)、M2 (ccsA-ndhD) 和N17 (trnK-matK) 的PCR扩增和测序成功率均为100%。说明除trnT-trnL外, 其余13条序列的引物在黄精属植物中均具有良好的通用性。
Cong等[31]对中药材黄精基原物种的分子鉴定分析结果指出叶绿体基因间区序列rpl20-rps12可以区分黄精、多花黄精、滇黄精, 但其是否可以有效鉴别黄精属其他物种, 还有待进一步研究。本研究对包括中药材黄精3个基原物种在内的黄精属15个药用物种的分子鉴定分析结果显示, trnT-trnL序列独立分析能鉴别包括黄精、多花黄精、滇黄精在内的8个物种; atpF能鉴别包括黄精、多花黄精在内的8个物种; trnF-ndhJ及trnK-matK序列独立分析均能鉴定包括黄精、滇黄精在内的8个物种; 组合序列C0、C1、C2、C3能鉴定包括黄精、多花黄精、滇黄精在内的11个物种。这些分子标记序列及其组合将为中药材黄精基原物种及其混伪品的准确鉴别提供理论依据。
Yan等[32]对黄精属药用植物叶绿体全基因组序列变异分析结果指出, trnK-matK、trnS、trnT-psbD、psaJ-rpl33、rpl32-trnL和ndhG-ndhI等6条序列均呈现出较高的种间变异, 其中, psaJ-rpl33能够有效区分湖北黄精与黄精属其他物种, 可以作为黄精属种间鉴定的分子标记。Long等[25]对黄精属7个药用物种23份样品的分子鉴定分析结果指出, trnK-matK序列的种间鉴定效率较高, 能够有效区分黄精、滇黄精、玉竹、点花黄精P. punctatum Royle ex Kunth和湖北黄精, 可作为黄精属药用植物鉴定的DNA条形码。本研究对黄精属15个药用物种来自32个居群共166个代表个体的分子鉴定分析结果表明, psaJ-rpl33序列独立分析能够有效鉴别黄精、距药黄精、细根茎黄精、热河黄精、垂叶黄精和二苞黄精6个物种(建树法) 或黄精、距药黄精、细根茎黄精、热河黄精、垂叶黄精、二苞黄精和大苞黄精7个物种(距离法); trnK-matK独立分析可有效鉴别黄精、距药黄精和长梗黄精3个物种(建树法) 或黄精、距药黄精、长梗黄精、垂叶黄精、细根茎黄精、大苞黄精、二苞黄精和滇黄精8个物种(距离法)。因此, 支持将psaJ-rpl33和trnK-matK序列作为黄精属药用植物种间区分鉴别的有效分子标记。
Wang等[33]对黄精属植物叶绿体全基因组比较分析指出rps16-trnQ、trnT-trnL等8条基因间区序列具有较高的种间变异, 可作为黄精属植物种间鉴定的潜在分子标记。本研究分析结果亦表明rps16-trnQ和trnT-trnL序列均含有较多的变异位点(31个, 占比4.17%和45个, 占比6.80%) 及简约信息位点(28个, 占比3.76%和27个, 占比4.08%), 两者独立分析基于建树法的物种鉴定分辨率均为33.33%, 基于距离法的分辨率分别为60%和46.67%。其中, rps16-trnQ独立分析可有效鉴别距药黄精、细根茎黄精、热河黄精、垂叶黄精和长梗黄精5个物种(建树法) 或垂叶黄精、细根茎黄精、大苞黄精、距药黄精、二苞黄精、五叶黄精、热河黄精、长梗黄精和湖北黄精9个物种(距离法); trnT-trnL可鉴别黄精、热河黄精、滇黄精、二苞黄精和多花黄精5个物种(建树法) 或垂叶黄精、大苞黄精、二苞黄精、五叶黄精、滇黄精、热河黄精和黄精7个物种(距离法)。进一步支持将rps16-trnQ、trnT-trnL作为黄精属药用植物种间鉴定的有效分子标记这一结论[33]。然而, 由于trnT-trnL的引物PCR扩增成功率相对较低, 有效序列得率仅为59.04%, 因而最终用于分子鉴定分析的个体数相对较少。在后续研究中, 还需进一步优化PCR反应条件或者设计通用性更高的引物, 以提高PCR扩增成功率和有效序列得率, 并在此基础上进一步评估其物种鉴定分辨率。
此外, 序列atpF、trnF-ndhJ的PCR扩增成功率分别为100%和99.4%, 测序成功率均为100%。距离法分析结果显示, atpF、trnF-ndhJ均具有相对较高的物种鉴定分辨率, 其中, atpF独立分析可有效鉴别垂叶黄精、细根茎黄精、大苞黄精、距药黄精、二苞黄精、五叶黄精、黄精和多花黄精8个物种, trnF-ndhJ可鉴别垂叶黄精、细根茎黄精、大苞黄精、距药黄精、二苞黄精、滇黄精、热河黄精、黄精8个物种。说明atpF、trnF-ndhJ亦可作为黄精属药用植物种间鉴定的有效分子标记序列。
组合序列C0、C1、C2和C3基于建树法及C0、C1和C25基于距离法分析的物种鉴定成功率均为最高, 达73.33%, 均可同时有效鉴别11个物种。同时, C2和C3基于距离法的物种鉴定分辨率亦相对较高, 均为66.7%, 可成功鉴别10个物种; C25基于建树法的物种鉴定分辨率为60%, 可成功鉴别9个物种。说明多序列联合包含更多的物种演化信息位点, 能够有效提高物种鉴定分辨率。因此, 对于未知物种样品, 若单一序列鉴定分辨率不足, 可考虑多序列联合分析。此外, 组合序列C0、C1、C2和C3依次分别包含14、13和12条候选分子标记, 组合序列总长度分别为8 025、7 363、6 788和6 976 bp, 而C25仅包含psaJ-rpl33、rps16-trnQ、trnF-ndhJ、trnK-matK和atpF共5条序列, 组合序列总长度为3 234 bp, 且具有最小的种内最大遗传距离, 同时其种间、种内遗传距离重叠程度最低。因此, 本研究推荐将组合序列C25 (即psaJ-rpl33+rps16-trnQ+trnF-ndhJ+trnK-matK+atpF) 作为黄精属药用植物种间鉴定的特异性高分辨率分子标记组合。
由于性状较为相似, 湖北黄精、卷叶黄精等黄精属多个物种的根状茎常作为黄精入药使用[34]。湖北黄精在形态上介于黄精和卷叶黄精之间, 以小花较多、花小、花梗基部具有约与小花等长的膜质苞片而与卷叶黄精相区别, 而湖北黄精与黄精的主要区别在于花较小、花柱较短、根状茎呈连珠状或姜状。然而, 这3个物种在地理分布上广泛重叠, 同时存在形态过渡类型[35], 导致其种间区分鉴定存在较多问题。本研究结果显示, 14组候选分子标记序列中, atpF、ccsA-ndhD、trnF-ndhJ、psaJ-rpl33、rps11-rpl36-infA、trnK-matK和trnT-trnL以及组合序列C0、C1、C2、C3、C4、C5、C6、C7、C8、C9、C10、C11、C12、C13、C14、C15、C16、C17、C18、C19、C20、C21、C22、C23、C24、C25、C26和C31基于建树法和距离法均能有效将黄精与同属其他物种区别; 同时, rps16-trnQ及组合序列C25、C27、C29、C30、C31、C32基于距离法均可将湖北黄精与同属其他物种区分鉴别。此外, Floden等[36]、Xia等[37]及Wang等[27]等基于叶绿体全基因组序列对黄精属的系统发育及分子鉴定相关研究曾指出卷叶黄精、轮叶黄精、多花黄精和玉竹等多个物种均为非单系种, 这些物种的地理分布范围相对较广, 种下形态变异丰富, 且可能存在杂交等物种形成过程[24, 36], 后续研究尚需进一步结合形态性状、地理分布、核基因序列等多方面证据综合探讨其物种界定问题。
作者贡献: 共同第一作者陈锦豪和程文萍负责实验、数据分析及论文初稿撰写; 通讯作者张明英负责实验设计、数据分析和论文指导; 高静、李依民、陈莹参与实验及数据分析; 张岗参与实验设计及论文指导; 颜永刚参与实验材料采集。所有作者参与论文修改。
利益冲突: 本文所有的作者之间不存在利益冲突。
  • 国家自然科学基金项目(82003898)
  • 陕西省自然科学基础研究计划项目(2022JM-458)
  • 秦创原中医药产业创新聚集区项目(L2024-QCY-ZYYJJQ-X77)
  • 秦创原中医药产业创新聚集区项目(L2024-QCY-ZYYJJQ-X74)
  • 陕西省教育厅项目(22JC028)
  • 陕西中医药大学“秦药”品质评价及资源开发学科创新团队项目(2019-QN01)
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doi: 10.16438/j.0513-4870.2024-1272
  • 接收时间:2024-12-22
  • 首发时间:2025-10-29
  • 出版时间:2025-05-12
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  • 收稿日期:2024-12-22
  • 修回日期:2025-02-10
基金
国家自然科学基金项目(82003898)
陕西省自然科学基础研究计划项目(2022JM-458)
秦创原中医药产业创新聚集区项目(L2024-QCY-ZYYJJQ-X77)
秦创原中医药产业创新聚集区项目(L2024-QCY-ZYYJJQ-X74)
陕西省教育厅项目(22JC028)
陕西中医药大学“秦药”品质评价及资源开发学科创新团队项目(2019-QN01)
作者信息
    1.陕西中医药大学药学院, 陕西省秦岭中草药应用开发工程技术研究中心, 陕西 西安 712046
    2.陕西中医药大学, 陕西省中医药管理局"秦药"研发重点实验室, 陕西 西安 712046

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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