Seasonal dynamics and molecular regulation of flavonoid biosynthesis in Cyclocarya paliurus (Batal.) Iljinsk

Abstract

Introduction: Cyclocarya paliurus, an economically important species known for its high flavonoid content, has potential for industrial applications. Understanding the seasonal dynamics and molecular regulation of flavonoid biosynthesis in this species is crucial for optimizing its production.

Methods: We conducted an integrated analysis of transcriptomic and metabolomic data to identify key genes involved in flavonoid biosynthesis and regulation. Seasonal variation in flavonoid content and gene expression was examined, with a focus on the genes involved in the flavonoid synthesis pathway and their correlation with flavonoid levels.

Results: Flavonoid content peaked in August and declined towards November, with quercetin and kaempferol glycosides being the most abundant compounds. Pearson correlation analysis revealed significant relationships between the functional genes of the flavonoid synthesis pathway and flavonoid content. Seasonal variations in the expression of key biosynthetic genes (CHS, CHI, F3H, DFR, FLS) and regulatory transcription factors (MYB11, MYB12, MYB111, MYB75, MYB90, bHLH, WD40) were strongly correlated with flavonoid levels, particularly under environmental stress.

Discussion: These findings provide insights into the genetic regulation of flavonoid biosynthesis in C. paliurus and highlight the importance of seasonal and environmental factors. This knowledge has practical implications for industrial breeding and biotechnological applications, particularly in enhancing the functional properties of C. paliurus for industrial use. Our study establishes a foundation for future research aimed at optimizing flavonoid production in this species and exploring its potential for bioactive compound production.

Keywords: Cyclocarya paliurus; flavonoid biosynthesis; metabolomics; seasonal variation; transcriptomics.

Figure 1

Characteristics of flavonoids in C. paliurus. (A) Total flavonoid content in C. paliurus leaves across different months. (B) Distribution of various metabolites in C. paliurus leaves. (C) PCA score plot showing the clustering of different leaf samples. (D) Heatmap clustering of the identified compounds. (E) Trends in the relative abundance of different compound classes from August to November. (F) Correlation matrix among leaf samples based on their metabolite profiles.

Figure 2

Clustering of 144 flavonoid compounds identified in C. paliurus leaves.

Figure 3

Volcano plots and GO enrichment analysis for differentially expressed genes (DEGs) in C. paliurus. (A) Volcano plot of DEGs between 8M-ML and 9M-ML samples. (B) GO enrichment analysis of DEGs between 8M-ML and 9M-ML samples. (C) Volcano plot of DEGs between 9M-ML and 10M-ML samples. (D) GO enrichment analysis of DEGs between 9M-ML and 10M-ML samples. (E) Volcano plot of DEGs between 10M-ML and 11M-ML samples. (F) GO enrichment analysis of DEGs between 10M-ML and 11M-ML samples.

Figure 4

Gene co-expression network analysis. (A) Scale independence as a function of soft-thresholding power. (B) Mean connectivity across soft-thresholding powers. (C) Heatmap showing correlations between gene expression modules. (D) Clustering dendrogram of expressed genes, with modules indicated by different colors. (E) Heatmap illustrating correlations between gene modules and various traits. (F) Co-expression network of genes in a selected module, highlighting hub genes.

Figure 5

Transcriptional expression profiles of key functional genes involved in flavonoid biosynthesis. (A) Expression profiles of genes involved in the transformation from precursor molecules to flavonoids. (B) Expression profiles of genes responsible for flavonoid biosynthesis.

Figure 6

Heatmap showing correlations between functional genes and flavonoids in C. paliurus.

Figure 7

Heatmap illustrating the correlations between transcription factors and flavonoids in C. paliurus..