柳树DNA条形码的筛选与鉴定研究
Screening and identification of DNA barcodes in willow
郑纪伟 1何旭东 1隋德宗 1王保松1
作者信息
- 1. 江苏省林业科学研究院,江苏 南京 211153
- 折叠
摘要
柳树具观赏、生物修复、生物能源等多种功能,对其开展DNA条形码评估在种质资源保护和利用方面具有非常重要的应用价值.通过对柳树样品进行ITS、ITS2、matK、rbcL和rpoCl片段扩增和测序,结合GenBank数据,共获得柳树22个种,63份样品共计396条序列.比较了 5个DNA片段的通用性、序列特征、种内和种间变异,并基于Best Match(BM)、Best Close Match(BCM)、BLAST 及 Neighbor Joining(NJ)4 种方法评估 DNA 条形码在柳树中的鉴定能力.结果表明,5个DNA条形码中,ITS在柳树种扩增效率和测序成功率高,种内和种间遗传变异明显,鉴定效率最高,建议作为首选的单位点DNA条形码;3个条形码组合中,ITS+ITS2+rbcL鉴定成功率最高,为78.16％,4个DNA条形码组合中,ITS+ITS2+matK+rbcL物种鉴别成功率最高,为88.28％,建议ITS+ITS2+matK+rbcL作为柳树分子鉴定最优条形码组合.
Abstract
DNA barcoding evaluation of willow is of great application value in germplasm resource protection and utilization,as willow showing multifunctional,integrating ornament,bioremediation and bioenergy.Through the amplification and se-quencing of ITS,ITS2,matK,rbcL and rpoCl fragments of willow samples,combined with GenBank data,we obtained 396 sequences from 22 species of willow.The comparisons of effective sequence ratios,characteristics of sequences,divergence of intra-and inter-varieties among the five DNA fragments had been performed to evaluate the recognition ability of DNA barcodes by using four methods as Best Match(BM),Best Close Match(BCM),BLAST and Neighbor Joining(NJ).The results showed that ITS,among the 5 DNA barcodes,had high amplification efficiency and sequencing success rate,obvi-ous intraspecific and interspecific genetic variation,and the highest identification efficiency in willow species.Therefore,it was recommended to be the preferred unit point DNA barcode.Among the 3 barcode combinations,the success rate of ITS+ITS2+rbcL identification was the highest(78.16％)while among the 4 DNA barcode combinations,the success rate of ITS+ITS2+matK+rbcL identification was the highest(88.28％).Thus,it is suggested that ITS+ITS2+matK+rbcL be the best barcode combination for molecular identification of willow.
关键词
柳树/DNA条形码/筛选/ITS/分子鉴定Key words
Salix/DNA barcode/Screening/ITS/Molecular identification引用本文复制引用
基金项目
江苏省林业科学研究院青年基金项目(JAF-2016-01)
江苏省林业科技创新与推广项目(LYKJ[2021]08)
江苏省林业科学研究院自主科研项目(ZZKY202101)
出版年
2024
NETL
NSTL
万方数据