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. 2024 Jul 24;13(15):2028.
doi: 10.3390/plants13152028.

Integrative Transcriptomic and Metabolic Analyses Reveal That Flavonoid Biosynthesis Is the Key Pathway Regulating Pigment Deposition in Naturally Brown Cotton Fibers

Affiliations

Integrative Transcriptomic and Metabolic Analyses Reveal That Flavonoid Biosynthesis Is the Key Pathway Regulating Pigment Deposition in Naturally Brown Cotton Fibers

Shandang Shi et al. Plants (Basel). .

Abstract

Brown cotton is a major cultivar of naturally colored cotton, and brown cotton fibers (BCFs) are widely utilized as raw materials for textile industry production due to their advantages of being green and dyeing-pollution-free. However, the mechanisms underlying the pigmentation in fibers are still poorly understood, which significantly limits their extensive applications in related fields. In this study, we conducted a multidimensional comparative analysis of the transcriptomes and metabolomes between brown and white fibers at different developmental periods to identify the key genes and pathways regulating the pigment deposition. The transcriptomic results indicated that the pathways of flavonoid biosynthesis and phenylpropanoid biosynthesis were significantly enriched regulatory pathways, especially in the late development periods of fiber pigmentation; furthermore, the genes distributed in the pathways of PAL, CHS, F3H, DFR, ANR, and UFGT were identified as significantly up-regulated genes. The metabolic results showed that six metabolites, namely (-)-Epigallocatechin, Apiin, Cyanidin-3-O-glucoside, Gallocatechin, Myricetin, and Poncirin, were significantly accumulated in brown fibers but not in white fibers. Integrative analysis of the transcriptomic and metabolomic data demonstrated a possible regulatory network potentially regulating the pigment deposition, in which three MYB transcription factors promote the expression levels of flavonoid biosynthesis genes, thereby inducing the content increase in (-)-Epigallocatechin, Cyanidin-3-O-glucoside, Gallocatechin, and Myricetin in BCFs. Our findings provide new insights into the pigment deposition mechanism in BCFs and offer references for genetic engineering and breeding of colored cotton materials.

Keywords: brown cotton fiber; flavonoid biosynthesis; metabolome; naturally colored cotton; pigment deposition; transcriptome.

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Conflict of interest statement

Authors S.T., W.C. and Haifeng Liu are employed by the company China Colored-cotton (Group) Corporation. The remaining authors declare that this research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.

Figures

Figure 1
Figure 1
Comparative transcriptomic analysis between white (TM-1) and brown fibers (Z1282). (A) The mature fiber phenotypes of brown cotton Z1282 and white cotton TM-1. (B) Venn diagram of the UDEGs in Z1282 relative to TM-1 in 5, 10, 15, and 20 DPA fibers. (C) KEGG enrichment analysis of the UDEGs in 5, 10, 15, and 20 DPA fibers. (D) Statistical analysis of the number of UDEGs corresponding to different family members related to flavonoid biosynthesis and phenylpropanoid biosynthesis pathways. (E) Statistical analysis of the number of UDEGs corresponding to different family members of TFs. The clustering analysis was performed using hierarchical clustering by Euclidean distance and the complete linkage method.
Figure 2
Figure 2
Transcriptomic analysis of different development periods of Z1282 fibers. (A) Statistical analysis of the number of UDEGs at 5, 10, 15, and 20 DPA relative to 0 DPA in Z1282 fibers. (B) Venn diagram of the UDEGs at 5, 10, 15, and 20 DPA relative to 0 DPA in Z1282 fibers. (C) KEGG enrichment analysis of the UDEGs in 5, 10, 15, and 20 DPA Z1282 fibers. (D) Statistical analysis of the number of UDEGs corresponding to different family members related to flavonoid biosynthesis and phenylpropanoid biosynthesis pathways. (E) Statistical analysis of the number of UDEGs corresponding to different family members of TFs. The clustering analysis was performed using hierarchical clustering by Euclidean distance and the complete linkage method.
Figure 3
Figure 3
Multidimensional transcriptomic analysis of different development periods of Z1282 and TM-1 fibers. (A) Venn diagram of the UDEGs at 5, 10, 15, and 20 DPA in Z1282 and TM-1 fibers. (B) KEGG enrichment analysis of co-expressed UDEGs at 5, 10, 15, and 20 DPA in Z1282 and TM-1 fibers. (C) Heatmap of the expression levels of genes located in the pathways of flavonoid biosynthesis and phenylalanine biosynthesis in Z1282 relative to TM-1 at different fiber development periods. (D) Heatmap of the TF expression levels of Z1282 relative to TM-1 at different fiber development periods. The clustering analysis was performed using hierarchical clustering by Euclidean distance and the complete linkage method.
Figure 4
Figure 4
Protein–protein interaction (PPI) analysis of the co-expressed UDEGs located in the flavonoid biosynthesis pathway in different development periods for Z1282 and TM-1 fibers. Red and blue colors represent transcription factors and flavonoid biosynthesis pathway genes, respectively.
Figure 5
Figure 5
RT-qPCR validation of candidate transcription factors and flavonoid biosynthesis pathway genes. The genes of transcription factors (GhMYB1-GhMYB3) and flavonoid biosynthesis pathway genes (GhPAL, GhCHS1-3, GhDFR1-3, GhANR1-2, GhF3H, and GhUFGT) were selected for RT-qPCR detections using the materials of 0, 5, 10, 15, and 20 DPA ovules and fibers of Z1282 and TM-1 as templates. The black lines represent the trends of gene expression levels during different development periods for Z1282 and TM-1 fibers. The t-test was used for significant difference analysis, with *, **, and *** denoting significant differences at p < 0.05, 0.01, and 0.001 levels, respectively, and NS representing no significant difference.
Figure 6
Figure 6
Analysis of flavonoid metabolite levels in Z1282 and TM-1 fibers through extensive targeted metabolomics. (A) Heatmap and clustering analysis of content levels of all detected flavonoid metabolites. The clustering analysis was performed using hierarchical clustering by Euclidean distance and the complete linkage method. (BG) Box plots of six significantly up-regulated metabolites in fibers of Z1282 relative to TM-1. *, **, and *** denote significant differences at p < 0.05, 0.01, and 0.001 levels.
Figure 7
Figure 7
Schematic diagram of candidate genes and metabolites in flavonoid biosynthesis and phenylalanine biosynthesis pathways. The pathways were constructed based on the KEGG flavonoid and phenylalanine biosynthesis pathways. Red stars and pink arrows represent the candidate UDEGs and up-regulated metabolites in Z1282 fibers.
Figure 8
Figure 8
Proposed schematic diagram of regulatory network of TFs and flavonoid biosynthesis pathway genes and metabolites involved in pigment deposition of brown cotton fibers. The connections between transcription factors and flavonoid biosynthesis pathway genes denote the transcriptomic regulatory interactions. The connections between flavonoid biosynthesis pathway genes and metabolites represent the possibility that these genes directly participate in the synthesis of corresponding metabolites.

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