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. 2023 Nov 16;24(22):16384.
doi: 10.3390/ijms242216384.

Integration of Metabolomics and Transcriptomics to Explore Dynamic Alterations in Fruit Color and Quality in 'Comte de Paris' Pineapples during Ripening Processes

Kanghua Song  1 , Xiumei Zhang  1 , Jiameng Liu  2 , Quansheng Yao  1 , Yixing Li  3 , Xiaowan Hou  1 , Shenghui Liu  1 , Xunxia Qiu  2 , Yue Yang  1 , Li Chen  1 , Keqian Hong  1 , Lijing Lin  2
Affiliations

Integration of Metabolomics and Transcriptomics to Explore Dynamic Alterations in Fruit Color and Quality in 'Comte de Paris' Pineapples during Ripening Processes

Kanghua Song et al. Int J Mol Sci. .

Abstract

Pineapple color yellowing and quality promotion gradually manifest as pineapple fruit ripening progresses. To understand the molecular mechanism underlying yellowing in pineapples during ripening, coupled with alterations in fruit quality, comprehensive metabolome and transcriptome investigations were carried out. These investigations were conducted using pulp samples collected at three distinct stages of maturity: young fruit (YF), mature fruit (MF), and fully mature fruit (FMF). This study revealed a noteworthy increase in the levels of total phenols and flavones, coupled with a concurrent decline in lignin and total acid contents as the fruit transitioned from YF to FMF. Furthermore, the analysis yielded 167 differentially accumulated metabolites (DAMs) and 2194 differentially expressed genes (DEGs). Integration analysis based on DAMs and DEGs revealed that the biosynthesis of plant secondary metabolites, particularly the flavonol, flavonoid, and phenypropanoid pathways, plays a pivotal role in fruit yellowing. Additionally, RNA-seq analysis showed that structural genes, such as FLS, FNS, F3H, DFR, ANR, and GST, in the flavonoid biosynthetic pathway were upregulated, whereas the COMT, CCR, and CAD genes involved in lignin metabolism were downregulated as fruit ripening progressed. APX as well as PPO, and ACO genes related to the organic acid accumulations were upregulated and downregulated, respectively. Importantly, a comprehensive regulatory network encompassing genes that contribute to the metabolism of flavones, flavonols, lignin, and organic acids was proposed. This network sheds light on the intricate processes that underlie fruit yellowing and quality alterations. These findings enhance our understanding of the regulatory pathways governing pineapple ripening and offer valuable scientific insight into the molecular breeding of pineapples.

Keywords: fruit quality; metabolomics; pineapple; ripening; transcriptomics; yellowing.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
The changes in appearance (A) and (B) peel color B (a–c), pulp color B (d–f), Total soluble solid (Bg) (g), Vitamin C content (Bh) (h), Total acid content (Bi) (i), Total phenol content (Bj) (j), Total flavonoids content (Bk) (k), Lignin content (Bl) (l) of pineapple fruit at 18, 19, and 20 weeks after floral induction, respectively. Scale bar = 8 cm. Different letters indicate statistically significant differences (p ≤ 0.05).
Figure 2
Figure 2
Preliminary analysis of 167 differentially accumulated metabolites (DAMs). (A) Pie chart of identified types and quantities of metabolites. (B) The red and blue bars indicate the numbers of upregulated and downregulated DAMs between YF and MF, YF and FMF, and MF and FMF, respectively.
Figure 2
Figure 2
Preliminary analysis of 167 differentially accumulated metabolites (DAMs). (A) Pie chart of identified types and quantities of metabolites. (B) The red and blue bars indicate the numbers of upregulated and downregulated DAMs between YF and MF, YF and FMF, and MF and FMF, respectively.
Figure 3
Figure 3
K-means clustering analysis of DAMs. (A) Six clusters of K-means (designated C1–C6). (B) The distribution of different substance categories in the 6 clusters. The table below the histogram shows the number of each type of metabolite in different clusters. (C) KEGG enrichment analysis for DAMs in the 6 clusters. (D) The top 10 pathways clustering analysis on the change trends of DAMs profiles in pineapple fruit from YF, MF, and FMF groups.
Figure 3
Figure 3
K-means clustering analysis of DAMs. (A) Six clusters of K-means (designated C1–C6). (B) The distribution of different substance categories in the 6 clusters. The table below the histogram shows the number of each type of metabolite in different clusters. (C) KEGG enrichment analysis for DAMs in the 6 clusters. (D) The top 10 pathways clustering analysis on the change trends of DAMs profiles in pineapple fruit from YF, MF, and FMF groups.
Figure 3
Figure 3
K-means clustering analysis of DAMs. (A) Six clusters of K-means (designated C1–C6). (B) The distribution of different substance categories in the 6 clusters. The table below the histogram shows the number of each type of metabolite in different clusters. (C) KEGG enrichment analysis for DAMs in the 6 clusters. (D) The top 10 pathways clustering analysis on the change trends of DAMs profiles in pineapple fruit from YF, MF, and FMF groups.
Figure 4
Figure 4
Preliminary analysis of 2094 differentially expressed genes (DEGs). (A) Principal component analysis (PCA) of the RNA-seq data. (B) Heatmap of 2094 DEGs from three developmental stages.
Figure 4
Figure 4
Preliminary analysis of 2094 differentially expressed genes (DEGs). (A) Principal component analysis (PCA) of the RNA-seq data. (B) Heatmap of 2094 DEGs from three developmental stages.
Figure 5
Figure 5
Preliminary analysis of 2194 differentially expressed genes (DEGs). (A) The numbers of upregulated and downregulated DEGs between YF and MF, YF and FMF, and MF and FMF, respectively. (B) Venn diagrams illustrating the overlap of DEGs revealed via paired comparison between YF and MF, YF and FMF, and MF and FMF, respectively. (C) Ten clusters of K-means (designated T1–T10). (D) KEGG enrichment analysis for DEGs in the 10 clusters.
Figure 5
Figure 5
Preliminary analysis of 2194 differentially expressed genes (DEGs). (A) The numbers of upregulated and downregulated DEGs between YF and MF, YF and FMF, and MF and FMF, respectively. (B) Venn diagrams illustrating the overlap of DEGs revealed via paired comparison between YF and MF, YF and FMF, and MF and FMF, respectively. (C) Ten clusters of K-means (designated T1–T10). (D) KEGG enrichment analysis for DEGs in the 10 clusters.
Figure 6
Figure 6
Correlations of 2194 DEGs with physiological indexes based on weighted gene co-expression network analysis (WGCNA). (A) Clustering dendrogram showing 6 modules of co-expressed genes with WGCNA. (B) Module–trait relationships. Each row corresponds to a module, and each column corresponds to a quality characteristic trait. Note: L*, L* value; a*, a* value; b*, b* value; TP, total phenols content; TF, total flavones content; TSS, total soluble solid; Vc, vitamin C; TA, total acid.
Figure 6
Figure 6
Correlations of 2194 DEGs with physiological indexes based on weighted gene co-expression network analysis (WGCNA). (A) Clustering dendrogram showing 6 modules of co-expressed genes with WGCNA. (B) Module–trait relationships. Each row corresponds to a module, and each column corresponds to a quality characteristic trait. Note: L*, L* value; a*, a* value; b*, b* value; TP, total phenols content; TF, total flavones content; TSS, total soluble solid; Vc, vitamin C; TA, total acid.
Figure 7
Figure 7
Expression levels of 14 candidate genes associated with the ripening of pineapple fruit via qRT-PCR and correlation analysis based on RNA-Seq and qRT-PCR data. Notes: FC, fold change.
Figure 8
Figure 8
Dynamics of metabolites and genes related to pineapple fruit ripening. Note: Three blocks represent YF, MF, and FMF, respectively. SPS, sucrose phosphate synthase; APX, ascorbates peroxidase; ACO, aconitase; PPO, polyphenol oxidase; 4CL, p-coumarate: CoA ligase; CAD, cinnamyl alcohol dehydrogenase; CCR, cinnamoyl CoA reductase; COMT, caffeic acid O-methyl transferase; HCT, hydroxycinnamoyltransferase; POD, peroxidase; LAC, laccase; CHI, chalcone isomerase; F3H, flavanone 3-hydroxylase; DFR, dihydroflavonol-4-reductase; ANR, anthocyanidin reductase; LDOX, leucoantho-cyanidin dioxygenase; GST, glutathione transferases.
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