2018
DOI: 10.1186/s12864-018-4999-9
|View full text |Cite
|
Sign up to set email alerts
|

Gene co-expression network analysis reveals coordinated regulation of three characteristic secondary biosynthetic pathways in tea plant (Camellia sinensis)

Abstract: BackgroundThe leaves of tea plants (Camellia sinensis) are used to produce tea, which is one of the most popular beverages consumed worldwide. The nutritional value and health benefits of tea are mainly related to three abundant characteristic metabolites; catechins, theanine and caffeine. Weighted gene co-expression network analysis (WGCNA) is a powerful system for investigating correlations between genes, identifying modules among highly correlated genes, and relating modules to phenotypic traits based on ge… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

1
60
0

Year Published

2019
2019
2024
2024

Publication Types

Select...
5
3
2

Relationship

0
10

Authors

Journals

citations
Cited by 79 publications
(61 citation statements)
references
References 64 publications
1
60
0
Order By: Relevance
“…We used weighted correlation network analysis (WGCNA) to uncover the correlations between terpene content and expression levels of specific genes [44]. This method has been successfully applied in mining potential TFs in grapevine and sugarcane [45,46] and elucidating the coordinated regulation of compounds in tea plants [47]. This strategy reconstructed subnetworks with high connectivities, presenting gene targets for functional characterization.…”
Section: Introductionmentioning
confidence: 99%
“…We used weighted correlation network analysis (WGCNA) to uncover the correlations between terpene content and expression levels of specific genes [44]. This method has been successfully applied in mining potential TFs in grapevine and sugarcane [45,46] and elucidating the coordinated regulation of compounds in tea plants [47]. This strategy reconstructed subnetworks with high connectivities, presenting gene targets for functional characterization.…”
Section: Introductionmentioning
confidence: 99%
“…Another novelty of our study is that we further explored the functional relevance of target genes between tissues and functional divergence of isoforms by building an isoform-based co-expression network. Meanwhile, the reason why we selected WGCNA for coexpression analysis is its diverse functions and maturity of data processing which has been successfully applied in many gene network and functional genomic studies [38,48,49]. Our findings revealed the case that some isoforms from the same gene appear to be divergent in the isoform co-expression network and selectively targeted by miR-NAs due to their difference in sequence structure, suggesting the coordination of both structural and expression alteration during gene regulation.…”
Section: Discussionmentioning
confidence: 91%
“…Another novelty of our study is that we further explored the functional relevance of target genes between tissues and functional divergence of isoforms by building an isoform-based co-expression network. Meanwhile, the reason why we selected WGCNA for co-expression analysis is its diverse functions and maturity of data processing which has been successfully applied in many gene network and functional genomic studies [37,47,48]. Our findings revealed the case that some isoforms from the same gene appear to be divergent in the isoform coexpression network and selectively targeted by miRNAs due to their difference of sequence structure, suggesting the coordination of both structural and expression alteration during gene regulation.…”
Section: Discussionmentioning
confidence: 91%