NDLI: Integrated metabolomic and transcriptomic analysis of the anthocyanin regulatory networks in Salvia miltiorrhiza Bge. flowers

Content Provider	Springer Nature : BioMed Central
Author	Jiang, Tao Zhang, Meidi Wen, Chunxiu Xie, Xiaoliang Tian, Wei Wen, Saiqun Lu, Ruike Liu, Lingdi
Abstract	Background The objectives of this study were to reveal the anthocyanin biosynthesis metabolic pathway in white and purple flowers of Salvia miltiorrhiza using metabolomics and transcriptomics, to identify different anthocyanin metabolites, and to analyze the differentially expressed genes involved in anthocyanin biosynthesis. Results We analyzed the metabolomics and transcriptomics data of S. miltiorrhiza flowers. A total of 1994 differentially expressed genes and 84 flavonoid metabolites were identified between the white and purple flowers of S. miltiorrhiza. Integrated analysis of transcriptomics and metabolomics showed that cyanidin 3,5-O-diglucoside, malvidin 3,5-diglucoside, and cyanidin 3-O-galactoside were mainly responsible for the purple flower color of S. miltiorrhiza. A total of 100 unigenes encoding 10 enzymes were identified as candidate genes involved in anthocyanin biosynthesis in S. miltiorrhiza flowers. Low expression of the ANS gene decreased the anthocyanin content but enhanced the accumulation of flavonoids in S. miltiorrhiza flowers. Conclusions Our results provide valuable information on the anthocyanin metabolites and the candidate genes involved in the anthocyanin biosynthesis pathways in S. miltiorrhiza.
Related Links	https://bmcplantbiol.biomedcentral.com/counter/pdf/10.1186/s12870-020-02553-7.pdf
Ending Page	13
Page Count	13
Starting Page	1
File Format	HTM / HTML
ISSN	14712229
DOI	10.1186/s12870-020-02553-7
Journal	BMC Plant Biology
Issue Number	1
Volume Number	20
Language	English
Publisher	BioMed Central
Publisher Date	2020-07-23
Access Restriction	Open
Subject Keyword	Plant Sciences Agriculture Tree Biology S. Miltiorrhiza Medicinal plant Anthocyanin Transcriptome Metabolite
Content Type	Text
Resource Type	Article
Subject	Plant Science
Journal Impact Factor	4.3/2023
5-Year Journal Impact Factor	5.2/2023

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