目的 克隆何首乌Polygonum multiflorum糖基转移酶基因PmUGTs，并对其进行生物信息学以及差异表达分析。方法 基于何首乌转录组数据，利用PCR扩增PmUGTs全长cDNA并进行生物信息学分析；使用autodock4软件进行分子模拟对接；运用qRT-PCR检测基因在不同器官中的表达差异。结果 克隆得到4条PmUGTs，分别命名为PmUGT1、PmUGT2、PmUGT3、PmUGT4基因，开放阅读框（ORF）长度分别为1509、1506、1464和1476 bp；编码503、502、488与492个氨基酸；蛋白相对分子质量分别为56 940、54 780、54 350和54 620。PmUGTs氨基酸序列中含有UGT高度保守的PSPG盒结构域，其二级结构主要由无规则卷曲与α-螺旋组成。进化树分析表明，PmUGT1、PmUGT2、PmUGT3与拟南芥的UGT蛋白距离较近，PmUGT4则与蒺藜苜蓿UGT亲缘关系最近。根据autodock4结果可知PmUGT1、PmUGT3、PmUGT2与PmUGT4蛋白上的残基分别可以与鹰嘴豆芽素A、罗汉果醇、白藜芦醇通过氢键连接。qRT-PCR结果表明，PmUGTs表达量均在叶中最高。结论 为进一步研究何首乌糖基转移酶基因的功能及何首乌中糖苷类化合物的生物合成途径奠定基础。

Objective To clone the Polygonum multiflorum Thunb. glycosyltransferase genes (PmUGTs) and analyze their bioinformatics and relative expression levels. Methods Based on the transcriptomic data of Polygonum multiflorum Thunb., the PmUGTs full length cDNA were amplified by PCR and their bioinformatics were analysis. Autodock4 software was used for molecular docking, and qRT-PCR was used to detect PmUGTs organ-specific expression levels. Results The length of PmUGT1, PmUGT2, PmUGT3 and PmUGT4 ORF were from 1509, 1506, 1464 and 1476 bp, encoding 503, 502, 488 and 492 amino acids with the molecular mass of 56 940, 54 780, 54 350 and 54 620, respectively. PmUGTs amino acid sequences contain a highly conserved PSPG box domain, and their secondary structures are mainly composed of Random Coil and α-Helix. Phylogenetic analysis showed that PmUGT1, PmUGT2 and PmUGT3 were closed to the Arabidopsis thaliana UGTs, and PmUGT4 was closed to which from Medicago truncatula. According to the autodock4 results, PmUGT1, PmUGT3, PmUGT2 and PmUGT4 were abled to be hydrogen bonded with biochanin A, mogrol and resveratrol, respectively. Measurement of organ-specific expressions showed that the levels of PmUGTs leaves expression were the highest. Conclusion This research will laid a foundation for further study on the function of PmUGTs genes and biosynthesis pathway of P. multiflorum glycosides.

R282.12

国家重点研发计划项目（2017YFC1700704）；2017年广东省岭南中药材保护资金专项（粤财社[2017]60号）；广东省普通高校青年创新人才类项目（2018KQNCX133）