Identification of potential genes involved in triterpenoid saponins biosynthesis in Gleditsia sinensis by transcriptome and metabolome analyses View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-03

AUTHORS

Yusuke Kuwahara, Daisuke Nakajima, Sayaka Shinpo, Michimi Nakamura, Noriaki Kawano, Nobuo Kawahara, Mami Yamazaki, Kazuki Saito, Hideyuki Suzuki, Hideki Hirakawa

ABSTRACT

Gleditsia sinensis is widely used as a medicinal plant in Asia, especially in China. Triterpenes, alkaloids, and sterols were isolated from Gleditsia species. Among them, triterpenoid saponins are very important metabolites owing to their various pharmacological activities. However, the triterpenoid saponin biosynthesis pathway has not been well characterized. In the present study, we performed de novo transcriptome assembly for 14.3 Gbps of clean reads sequenced from nine tissues of G. sinensis. The results showed that 81,511 unique transcripts (unitranscripts) (47,855 unigenes) were constructed, of which 31,717 unigenes were annotated with Gene Ontology and EC numbers by Blast2GO against the NCBI-nr protein database. We also analyzed the metabolite contents in the same nine tissues by LS-MS/MS, and saponins including gleditsioside I were found in fruit at higher levels. Many of the genes with tissue-specific expression in fruit are involved in the flavonoid biosynthesis pathway, and many of those have UDP-glucosyltransferase (UGT) activity. We constructed a saponin biosynthesis pathway and identified two key enzyme families in the triterpenoid saponin biosynthesis pathway, cytochrome P450 and UDP-glucosyltransferase, that are encoded by 37 unigenes and 77 unigenes, respectively. CYP72A, CYP716A, and CYP88D, which are known as key enzymes for saponin biosynthesis, were also identified among the P450s. Our results provide insight into the secondary metabolite biosynthesis and serve as important resources for future research and cultivation of G. sinensis. More... »

PAGES

369-380

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11418-018-1270-2

DOI

http://dx.doi.org/10.1007/s11418-018-1270-2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1110580482

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30547286


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