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De novo Sequencing and Transcriptome Analysis of Pinellia ternata Identify the Candidate Genes Involved in the Biosynthesis of Benzoic Acid and Ephedrine

机译: Pinellia ternata 从头测序和转录组分析,鉴定了涉及苯甲酸和麻黄碱生物合成的候选基因

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Background: The medicinal herb, Pinellia ternata , is purported to be an anti-emetic with analgesic and sedative effects. Alkaloids are the main biologically active compounds in P. ternata , especially ephedrine that is a phenylpropylamino alkaloid specifically produced by Ephedra and Catha edulis . However, how ephedrine is synthesized in plants is uncertain. Only the phenylalanine ammonia lyase (PAL) and relevant genes in this pathway have been characterized. Genomic information of P. ternata is also unavailable. Results: We analyzed the transcriptome of the tuber of P. ternata with the Illumina HiSeq? 2000 sequencing platform. 66,813,052 high-quality reads were generated, and these reads were assembled de novo into 89,068 unigenes. Most known genes involved in benzoic acid biosynthesis were identified in the unigene dataset of P. ternata , and the expression patterns of some ephedrine biosynthesis-related genes were analyzed by reverse transcription quantitative real-time PCR (RT-qPCR). Also, 14,468 simple sequence repeats (SSRs) were identified from 12,000 unigenes. Twenty primer pairs for SSRs were randomly selected for the validation of their amplification effect. Conclusion: RNA-seq data was used for the first time to provide a comprehensive gene information on P. ternata at the transcriptional level. These data will advance molecular genetics in this valuable medicinal plant.
机译:背景:药用半夏据称是一种止吐药,具有镇痛和镇静作用。生物碱是P. ternata中的主要生物活性化合物,尤其是麻黄碱,它是一种由麻黄和Catha edulis专门生产的苯丙基氨基生物碱。但是,如何在植物中合成麻黄碱尚不确定。仅苯丙氨酸氨裂合酶(PAL)和此途径中的相关基因已被表征。 P. ternata的基因组信息也不可用。结果:我们用Illumina HiSeq?分析了P. ternata的块茎转录组。 2000测序平台。生成了66,813,052个高质量读段,并将这些读段从头组装为89,068个单基因。在八角山的unigene数据集中确定了与苯甲酸生物合成有关的最知名基因,并通过逆转录定量实时PCR(RT-qPCR)分析了与麻黄碱生物合成相关的基因的表达模式。此外,从12,000个单基因中鉴定出14,468个简单序列重复(SSR)。随机选择20对SSR引物,以验证其扩增效果。结论:首次使用RNA-seq数据在转录水平上提供了关于白三叶草的全面基因信息。这些数据将促进这种有价值的药用植物的分子遗传学发展。

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