Mining genes associated with furanocoumarin biosynthesis in an endangered medicinal plant, Glehnia littoralis.

Abstract:

:The endangered medicinal plant Glehnia littoralis is one of the important natural source of furanocoumarin, which has been used as mucolytic, antitussive, antitumour and antibacterial. However, the genetic information of furanocoumarin biosynthesis in G. littoralis is scarce at present. The objective of this study was to mine the putative candidate genes involved in the biosynthesis pathwayof furanocoumarin and provide references for gene identification, and functional genomics of G. littoralis. We carried out the transcriptome analysis of leaves and roots in G. littoralis, which provided a dataset for gene mining. Psoralen, imperatorin and isoimperatorin were detected in G. littoralis by high performance liquid chromatography analysis. Candidate key genes were mined based on the annotations and local BLAST with homologous sequences using BioEdit software. The relative expression of genes was analysed using quantitative real-time polymerase chain reaction. Further, the CYP450 genes were mined using phylogenetic analyses using MEGA 6.0 software. Atotal of 156,949 unigenes were generated, of which 9021 were differentially-expressed between leaves and roots. A total of 82 unigenes encoding eight enzymes in furanocoumarin biosynthetic pathway were first obtained. Seven genes that encoded key enzymes in the downstream furanocoumarin biosynthetic pathway and expressed more in roots than leaves were screened. Twenty-six candidate CYP450 unigenes expressed abundantly in roots and were chiefly concentrated in CYP71, CYP85 and CYP72 clans. Finally, we filtered 102 differentially expressed transcription factors (TFs) unigenes. The transcriptome of G. littoralis was characterized which would help to elucidate the furanocoumarin biosynthetic pathway in G. littoralis and provide an invaluable resource for further study of furanocoumarin.

journal_name

J Genet

journal_title

Journal of genetics

authors

Song J,Luo H,Xu Z,Zhang Y,Xin H,Zhu D,Zhu X,Liu M,Wang W,Ren H,Chen H,Gao T

subject

Has Abstract

pub_date

2020-01-01 00:00:00

eissn

0022-1333

issn

0973-7731

journal_volume

99

pub_type

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