目的 获得三叉苦Melicope pteleifolia转录组信息特征。方法 以三叉苦幼苗根、茎、叶混合样品为对象，采用二代高通量测序平台Illumina HiSeq^TM 2000进行转录组测序并进行系统的生物信息学分析。结果 转录组测序分析共获得47 045 040条高质量序列（clean reads），Trinity de novo组装获得67 956条unigenes，平均长度787 nt。BLAST分析显示分别有42 749（61.92%）、31 152（45.84%）、26 563（39.0 9%）、17 481（25.72%）条unigenes在NR、Swiss-port、KOG、KEGG数据库得到注释信息，参与生物过程、细胞组分和分子功能3个GO类别的47个小组，共9 807条unigenes注释到130个KEGG代谢通路中，筛选到19条次生代谢通路，KOG功能分类分析获得25个不同的KOG功能类群。预测共有高等植物转录因子56个家族；借助MISA软件发现7 748个SSRs，三碱基重复SSRs数量最丰富，有4 117个，出现频率为53.1%，五碱基重复SSRs相对较少，占2.2%。结论 利用高通量测序技术和生物信息分析获得三叉苦转录组信息特征，为后续三叉苦功能基因的挖掘、次生代谢途径解析及其调控机制研究奠定基础。

Objective To obtain the transcriptome sequence database of Melicope pteleifolia. Methods The transcriptome sequencing and systematic bioinformatics analysis were carried out using the second generation high-throughput sequencing platform Illumina HiSeq^TM 2000 with mixed root, stem and leaf samples of M. pteleifolia. Results A total of 47 045 040 high quality sequences (clean reads) were obtained by transcriptome sequencing analysis. A total of 67 956 unigenes were assembled by Trinity de novo, with an average length of 787 nt. BLAST analysis showed that 42 749 (61.92%), 31 152 (45.84%), 26 563 (39.09%), and 17 481 (25.72%) unigenes were annotated in NR, Swiss port, KOG and KEGG databases respectively, and 47 groups were involved in three GO classification: biological process, cellular component and molecular function. A total of 9807 unigenes were annotated to 130 KEGG metabolic pathways, 19 secondary metabolic pathways were screened. Twenty-five different KOG functional groups were obtained by the analysis of KOG functional classification. It was predicted that there were 56 families of higher plant transcription factors. A total of 7 748 simple sequence repeats (SSRs) were found by MISA software. The number (4 117) of the tri-nucleotide SSRs was the richest, with a frequency of 53.1%, and the number of the penta-nucleotide SSRs was relatively small, accounting for 2.2%. Conclusion The transcriptome information characteristics of root, stem, and leaf of M. pteleifolia can be obtained by high-throughput Illumina sequencing technology and bioinformatics analysis, which will lay a foundation for further research on functional gene mining, secondary metabolic pathway analysis and regulation mechanism of M. pteleifolia.

R282.12

国家自然科学基金委青年基金项目（81102764）；广东省教育厅重点提升平台建设项目——岭南中药资源教育部重点实验室（2014KTSPT016）；广东省教育厅创新团队项目——中药资源创新团队（2016KCXTD015）