Integrated analysis of the transcriptome and metabolome in young and mature leaves of Ginkgo biloba L

[Display omitted] •Ginkgo is rich in bioactive compounds (e.g., flavonoids and terpenoids).•1256 differentially expressed genes were identified between young and mature leaves.•A gene in phenylpropanoid pathway was significantly upregulated.•38 significantly different metabolites were detected betwe...

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Veröffentlicht in:Industrial crops and products 2020-01, Vol.143, p.111906, Article 111906
Hauptverfasser: Guo, Jing, Wu, Yaqiong, Wang, Guibin, Wang, Tongli, Cao, Fuliang
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Sprache:eng
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Zusammenfassung:[Display omitted] •Ginkgo is rich in bioactive compounds (e.g., flavonoids and terpenoids).•1256 differentially expressed genes were identified between young and mature leaves.•A gene in phenylpropanoid pathway was significantly upregulated.•38 significantly different metabolites were detected between young and mature leaves.•Ginkgo metabolites promote the ginkgo-related pharmaceutical industry development. Ginkgo (Ginkgo biloba L.) is a unique medicinal tree species that mainly depends on the flavonoids and terpenoids found in its leaves. However, the biosynthesis of these metabolites is controlled and regulated by gene actions which remain poorly understood. To improve our understanding of this process, we produced a transcriptome library from young and mature leaves of ginkgo trees using the Illumina HiSeq X Ten sequencing platformin this study. We obtained a total of 57.5 million clean reads, compared with seven databases and revealed 39,404 annotated unigenes. The key differentially expressed genes (DEGs) in young and mature leaves of ginkgo were explored through GO and KEGG metabolic pathway analysis. A total of 1,256 DEGs, including 561 upregulated and 695 downregulated genes were obtained in the ginkgo transcriptome in the mature leaves compared with that of the young leaves. These genes included 23 bHLH, 9 MYB, 5 WRKY, and 4 bZIP genes that act as regulators in flavonoid and terpenoid biosynthesis. One key gene involved in the diterpenoid pathway was downregulated. A gene in the phenylpropanoid biosynthesis pathway was significantly upregulated and significantly negatively correlated with serine in metabolites. Additionally, a metabolomics analysis detected 283 metabolites, and 38 significantly different metabolites were identified. The combined metabolome and transcriptome approach employed in this study constitutes an effective method for assessing the relationships between the expression of critical genes and metabolites related to biosynthetic pathways. Our study provides new ideas for analyzing biosynthesis at the molecular level and will encourage further development of the ginkgo-related pharmaceutical industry.
ISSN:0926-6690
1872-633X
DOI:10.1016/j.indcrop.2019.111906