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Article

Transcriptomic and Metabolomic Analysis Reveals Improved Fruit Quality in Grafted Watermelon

by
Kang Ning
1,†,
Xiaoqi Cai
1,†,
Leiyan Yan
2,
Weixin Zhou
1,
An Xie
1,
Yuhong Wang
2 and
Pei Xu
1,*
1
Key Laboratory of Specialty Agri-Product Quality and Hazard Controlling Technology of Zhejiang Province, College of Life Sciences, China Jiliang University, Hangzhou 310018, China
2
Ningbo Key Laboratory of Characteristic Horticultural Crops in Quality Adjustment and Resistance Breeding, Ningbo Academy of Agricultural Sciences, Ningbo 315042, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Horticulturae 2024, 10(12), 1269; https://doi.org/10.3390/horticulturae10121269
Submission received: 24 October 2024 / Revised: 26 November 2024 / Accepted: 26 November 2024 / Published: 28 November 2024
(This article belongs to the Special Issue New Advances in Secondary Metabolism of Vegetable Crops)
Browse Figures
Versions Notes

Abstract

:
Grafting technology can improve the yield and quality of crops. In this study, we investigated the effects of grafting on watermelon using transcriptomic and metabolomic analysis. A total of 216 differentially accumulated metabolites (DAMs) were identified between pumpkin-grafted watermelon and self-grafted watermelon. KO (Kyoto Encyclopedia of Genes and Genomes Orthology) analysis revealed that the DAMs were mainly enriched in the flavone and flavonol biosynthesis pathway. In addition, high levels of phloretin and citric acid were found in pumpkin-grafted watermelon, which contributes to fruit quality. Meanwhile, compounds such as olivetol and ferulaldehyde, which confer a bitter taste, were downregulated in pumpkin-grafted watermelon. The transcriptome data indicated that the differentially expressed genes (DEGs) identified in the pulp were enriched in fructose and mannose metabolism, biosynthesis of secondary metabolites, and flavone and flavonol biosynthesis pathways. Moreover, genes related to the microtubule, cell wall, and fiber were highly expressed in the stem of pumpkin-grafted watermelon, suggesting that grafting could change the structure of the stem and improve the quality of watermelon fruit. Our study provides a comprehensive picture of the transcriptional and metabolic profile of watermelon induced by grafting, which furthers our understanding of the molecular mechanisms involved in improving watermelon fruit quality by grafting.

1. Introduction

Watermelon (Citrullus lanatus) is a flowering plant species in the Cucurbitaceae family, known for producing the edible fruit of the same name. It is a scrambling, trailing vine widely grown across the globe, with over 1000 varieties. Watermelon is famous for its large size, sweet, juicy flesh, and high content of vitamins and antioxidants, making it a great source of hydration [1,2]. Studying the genetics of watermelons can contribute to advancements in plant breeding, allowing for the development of varieties that are more resilient to climate change and pests [3]. Watermelons with different flesh colors show significant differences in phenolic metabolites, making these compounds an important target for assessing fruit quality [4].
The practice of grafting dates back thousands of years, with early use documented in ancient China and Mesopotamia [5]. It was also practiced by the Greeks and Romans, indicating its long-standing importance in agriculture. Grafting is a commonly used technique in modern horticulture to enhance the quality, yield, and disease resistance of crops, playing a vital role in improving horticultural production [6]. The rootstock influences the plant’s vigor, disease resistance, soil adaptability, and overall compatibility with the scion. Optimal rootstock–scion combinations can significantly increase yield, improve quality, and improve stress resistance. For example, watermelon plants are susceptible to several common diseases, such as fusarium wilt, downy mildew, and powdery mildew, which can affect their growth, yield, and fruit quality. However, watermelon plants grafted onto Lagenaria siceraria L. rootstock can overcome Fusarium wilt [7]. Grafting has also been reported to increase watermelon yield, including improved fruit weight in large-fruited cultivars or a higher number of fruits per plant in small-fruited cultivars [8]. Grafting has positive effects on disease resistance, salt tolerance, and cold resistance [9]. The grafted pepper can cope with low-temperature environments by activating ROS (Reactive oxygen species)-related genes and producing a large amount of ROS [10,11]. Grafting can also affect the nutritional status of the grafted plant. Moreover, the vigor of the scion can largely affect the uptake and translocation of nutrients [12]. Aslam et al. revealed that grafting can alter metabolites in watermelon fruits by using high-throughput LC-ESI-MS/MS. Pumpkin-grafted watermelon accumulated more aromatic and nitrogen-rich amino acids, stress-related metabolites, vitamin B5, and several flavonoids [13]. Aslam et al. also investigated the effects of grafting on watermelon quality during fruit development by analyzing primary metabolites and the transcriptome [14]. This demonstrates that multi-omics analysis is a valuable approach for understanding regulatory networks in biological processes and identifying crucial regulatory genes.
Previous studies primarily focused on metabolite changes in watermelon fruits, and only a few studies focused on the transcriptional changes in the stem and pulp of the grafted watermelon. This study analyzed the transcriptome and metabolome to explore the effects of grafting on watermelon quality at the transcriptional and metabolic levels. We found that pumpkin-grafted watermelon showed higher concentrations of metabolites conferring a high fruit quality, while substances contributing to a bitter taste were found at lower concentrations. Transcriptome showed that microtubule, cell wall, and fiber-related genes are highly expressed in the stem of pumpkin-grafted watermelon, suggesting that grafting could change the structure of the stem. Our study reveals the effects of grafting on watermelon quality from the transcriptional level and metabolic level and provides information for future exploration of the molecular mechanism of grafting to improve watermelon fruit quality.

2. Materials and Methods

2.1. Plant Materials and Grafting Approach

Watermelon (cultivar ‘8424’) and pumpkin (cultivar ‘SiZhuang’) were used as plant materials. The seeds were soaked in water for 6 h, and then placed on wet filter paper. The germinated seeds were planted in a pot with a soil mixture (turf soil/vermiculite = 1:1). When the cotyledons had fully opened, the watermelon was grafted onto the pumpkin by splice grafting. Pumpkin-grafted watermelons were used in this study, and self-grafted watermelons were used as a control. The pulp of pumpkin-grafted watermelon (YG), self-grafted watermelon (XG), and stem of pumpkin-grafted watermelon (YJ) and self-grafted watermelon (XJ) were used for transcriptome analysis; the pulp of pumpkin-grafted watermelon (YG) and self-grafted watermelon (XG) were used for metabolome analysis. The plants were grown in greenhouses under normal conditions (light phase: 16 h, humidity 60%, 25 ± 2 °C and dark phase: 8 h, humidity 60%, 20 ± 2 °C).

2.2. Sample Preparation, Extraction, and LC-MS/MS for Untargeted Metabolomic Analysis

The pulp from both types of watermelon was collected 35 days after flowering (35 DAF) and stored at −80 °C. Then, 100 mg of plant tissue was ground in liquid nitrogen, and the resulting powder was resuspended in pre-chilled 80% methanol with 0.1% formic acid, followed by thorough vortexing. The samples were incubated on ice for 5 min and centrifuged at 15,000 rpm at 4 °C for 5 min. A portion of the supernatant was diluted with LC-MS grade water to obtain a final concentration of 53% methanol. The diluted samples were transferred to a new Eppendorf tube and centrifuged at 15,000× g at 4 °C for 10 min. Finally, the supernatant was injected into the LC-MS/MS system for analysis [15].

2.3. HPLC-MS/MS Analysis

HPLC-MS/MS analysis was performed using a Vanquish HPLC system paired with an Orbitrap Q Exactive™ HF mass spectrometer (Thermo Fisher, Waltham, MA, USA) at Biozeron Co., Ltd. (Shanghai, China). Samples were injected onto a Hypersil Gold column (100 × 2.1 mm, 1.9 µm particle size, column temperature 40 °C) with a 17 min linear gradient at a flow rate of 0.2 mL/min. In positive polarity mode, the eluents consisted of eluent A (0.1% formic acid in water) and eluent B (methanol), while in negative polarity mode, eluent A was 5 mM ammonium acetate (pH 9.0) and eluent B was methanol. The solvent gradient was programmed as follows: 2% B for 1.5 min, a gradual increase from 2% to 100% B over 12 min, held at 100% B until 14 min, returning to 2% B at 14.1 min, and maintained at 2% B until the 17 min mark. The Q Exactive™ HF mass spectrometer operated under both positive and negative modes, with a spray voltage of 3.2 kV, a capillary temperature of 320 °C, and sheath and auxiliary gas flow rates of 40 and 10 arbitrary units, respectively [14].

2.4. Data Processing and Metabolite Identification

The raw data files generated from HPLC-MS/MS analysis were processed through Compound Discoverer 3.1 (CD3.1, Thermo Fisher, Waltham, MA, USA) for tasks such as peak alignment, detection, and metabolite quantification. Key parameters were configured as follows: a retention time tolerance of 0.2 min, mass accuracy tolerance of 5 ppm, signal intensity variation tolerance of 30%, a signal-to-noise ratio of 3, and a minimum signal intensity of 100,000. Afterward, peak intensities were normalized to the total spectral intensity. These normalized values were then used to predict molecular formulas, incorporating additive ions, molecular ion peaks, and fragment ions. The resulting peaks were also cross-referenced with the mzCloud (20 September 2023 https://www.mzcloud.org/, accessed on 23 October 2024), mzVault, and MassList (built by biozeron Bio) databases for precise qualitative and relative quantitative identification. Statistical analysis was performed using R (version 3.4.3), Python (version 2.7.6), and CentOS (version 6.6) [16].

2.5. Differentially Accumulated Metabolites Identification

The metabolites were identified utilizing several databases, including KEGG (20 September 2023 https://www.genome.jp/kegg/pathway.html, accessed on 23 October 2024), HMDB (20 September 2023 https://hmdb.ca/metabolites, accessed on 23 October 2024), and LIPID Maps (20 September 2023 http://www.lipidmaps.org, accessed on 23 October 2024). Additionally, principal components analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were performed using metaX [17]. The transcriptome and metabolome data were autoscaled for PCA. A univariate analysis, specifically a t-test, was executed to assess statistical significance (p-value). Differential metabolites were defined as those with VIP (Variable importance in the projection) values exceeding 1, p-values below 0.05, and fold changes greater than 2 or less than 0.5. To illustrate metabolites of interest, volcano plots were generated based on their log2(Fold Change) and -log(p-value).

2.6. RNA-Seq and Analysis

RNA was extracted from the pulp and stem of both pumpkin-grafted watermelon and self-grafted watermelon. All samples were frozen in liquid nitrogen and ground into a fine powder under these conditions. Total RNA was isolated using TRIzol® Reagent following the manufacturer’s guidelines (Invitrogen, Carlsbad, CA, USA), and genomic DNA was eliminated with DNase I (TaKara, Tokyo, Japan). Sequencing was performed on the Illumina 6000 platform (Shanghai BIOZERON Co., Ltd., Shanghai, China). The raw data underwent trimming and quality control before mapping to the reference genome and counting. Gene expression levels were determined using the fragments per kilobase of exon per million mapped reads (FPKM) method. Differentially expressed genes (DEGs) were identified based on the criteria of a log fold change greater than 2 and a false discovery rate below 0.05. DEGs were significantly enriched in Gene Ontology (GO) terms and metabolic pathways when their Bonferroni-corrected p-value was less than 0.05. KEGG pathway analysis was performed using Goatools (accessed on 20 September 2023, https://github.com/tanghaibao/goatools).

2.7. RT-PCR

To confirm the reliability of the transcriptome data, Cla97C07G129320, Cla97C08G154840, Cla97C02G032060, and Cla97C01G001780, which showed significant expression differences between samples, were chosen to perform RT-PCR. RNA used for RNA-seq was used for RT-PCR, cDNA was synthesized using the T7 RNAi Transcription Kit (Vazyme, Nanjing, China), and a-Tubulin was used as a reference gene [18]. Fold change was calculated using the 2−ΔΔCt method [19]. Details regarding the RT-PCR primers are listed in Supplementary Table S1.

3. Results and Discussion

3.1. Metabolic Fingerprinting Profiling of Watermelon Graft with Different Stock

Untargeted metabolomics was performed to explore the differences in metabolites in watermelon that were grafted onto different rootstocks. Totally, 1128 metabolites, including 258 lipids, 149 organic acids and derivatives, 121 phenylpropanoids, 107 organoheterocyclic compounds, 75 benzenoids, 13 alkaloids, and 11 lignans were putatively identified (Figure 1a,b). The detailed information of these metabolites is shown in Supplementary Table S2. Regardless of grafting, DL-malic acid, L-phenylalanine, L-(+)-citrulline, L-tryptophan, citric acid, DL-arginine, methionine, oleamide, and D-(-)-fructose were among the high concentration metabolites. Most of them were organic acids. Organoleptic properties play a pivotal role in determining fruit quality, primarily driven by the relative number of sugars and acids [20]. Natural organic acids may have multiple benefits for fruits, including regulating osmotic pressure, pH homeostasis, stress resistance, and fruit quality [21]. These large numbers of organic acids might contribute to the quality of the watermelon fruit.
The correlation heatmap revealed that one sample (XG-3) showed poor correlation to the remaining replicates; thus, XG-3 was discarded for further analysis. Therefore, it is necessary to increase the repetition of omics in the future to avoid the abnormality of biological repetition and to increase the feasibility of data. High correlation coefficients (R = 0.97–0.995) were noted among the remaining biological replicates for each sample (Figure 1c). Principal component analysis (PCA) revealed distinct separation of the samples (YG and XG) along PC1 and PC2, which accounted for 97.65% and 1.68% of the variance, respectively (Figure 1d). These findings indicate that the data are both reproducible and reliable, making them suitable for further analysis.

3.2. Different Metabolites with Different Stock

A total of 216 metabolites were identified as differentially accumulated between the pulp of self-grafted watermelon (XG) and the pulp of pumpkin-grafted watermelon (YG), with 124 metabolites showing high accumulation in XG and 92 in YG (Figure 2a). The radar chart showed that pristimerin, neonuezhenide, N-acetyl-L-histidine 8-epiloganic acid, and sweroside showed significantly different accumulation between pulp of self-grafted watermelon (XG) and pumpkin-grafted watermelon (YG) (Figure 2b). KO (Kyoto Encyclopedia of Genes and Genomes Orthology (KO)) analysis indicated that differentially accumulated metabolites (DAMs) were primarily enriched in flavone and flavonol biosynthesis, flavonoid biosynthesis, and arachidonic acid metabolism pathways (Figure 2c). The metabolite network revealed that metabolites involved in the biosynthesis of the secondary metabolites pathway (ko01110), the flavonoid biosynthesis pathway (ko00941), and carbon metabolism (ko01200) showed differences in accumulation between the pulp of self-grafted watermelon (XG) and pumpkin-grafted watermelon (YG) (Figure 2d). For example, phloretin, a natural phenolic compound belonging to the dihydrochalcone class, exhibits strong antioxidant properties and offers potential agricultural benefits, particularly in enhancing disease resistance and improving crop quality [22]. Citric acid is an organic acid commonly found in watermelon and other fruits and can balance the taste and add flavor complexity. It can adjust the pH value of watermelon juice and affect the flavor release and taste of the fruit [23]. Metabolome analysis suggested that phloretin and citric acid are highly accumulated in YG. Several substances with antioxidant properties, such as tectorigenin, cryptotanshinone, polydatin, and taxifolin, were found to be highly accumulated in pumpkin-grafted watermelon [23]. Phenols are related to flesh color and taste in watermelon [24], and our data showed that several phenols are differently accumulated in the pulp of self-grafted watermelon (XG) and pumpkin-grafted watermelon (YG). For example, N-caffeoylagmatine, olivetol, ferulaldehyde, and 10-gingerol contribute to the bitter taste [25,26]; these compounds were down-accumulated when watermelon was grafted onto the pumpkin. These results suggest that grafting onto pumpkin (rootstock) can alter the concentration of metabolites in watermelon (scion), influencing watermelon quality.

3.3. Generation of Transcriptomic Data

To further explore the mechanism of the effect of different rootstocks on watermelon quality, a comparative transcriptome analysis of the pulp and stem of pumpkin-grafted watermelon and self-grafted watermelon was performed. A total of 19,991,501 clean reads were obtained from 12 samples, with three replicates for each sample. Each sample generated at least 39,102,454 clean reads (Supplementary Table S3). After assembly, 181,716 unigene sequences were identified, with an average length of 679.55 nucleotides (nt). FPKM showed strong correlations among the replicate samples. Principal component analysis (PCA) indicated that the biological replicates clustered closely, demonstrating the reproducibility and reliability of the data (Figure 3a). PCA also showed that XJ samples were separate from the YJ samples, whereas the YG and XG samples overlapped. These findings suggested that the two materials showed a small transcriptional difference in the pulps but a great transcriptional difference in the stems. These results indicated that grafting alters watermelon fruit quality by altering transcriptional regulation in stems. Several genes were selected to perform RT-PCR. These genes showed similar expression patterns in RT-PCR and transcriptome, which indicated that our transcriptome is reliable (Supplementary Figure S1a).

3.4. Analysis of the Differentially Expressed Genes

The DEGs between two grafted watermelons were compared. A total of 1505 and 3116 DEGs were identified in the comparison of YG vs. XG and YJ vs. XJ, respectively (Figure 3b). Subsequently, GO and KO analyses were performed on these DEGs.
The comparison was conducted between the pulp of self-grafted watermelon (XG) and pumpkin-grafted watermelon (YG). KO analysis indicated that the DEGs with higher expression levels in YG were predominantly enriched in pathways related to protein processing in the endoplasmic reticulum, as well as fructose and mannose metabolism (Figure 3c and Figure S1b). For example, phosphofructokinase B-type (pfkB)-like carbohydrate kinase proteins play an essential role in carbohydrate metabolism and are involved in the regulation of glycolysis and gluconeogenesis [27]. Genes encoding pfkB carbohydrate kinase protein (Cla97C06G110160) are highly expressed in the pulp of pumpkin-grafted watermelon (YG). DEGs with higher expression in XG were predominantly enriched in pathways related to secondary metabolite biosynthesis, as well as flavone and flavonol biosynthesis. Genes encoding chalcone-flavanone isomerase and chalcone synthase [28], which are key genes involved in the flavone biosynthesis pathway, showed high expression in the pulp of self-grafted watermelon. ABC transporter-related genes, which are involved in the transport of a wide variety of molecules across extra- and intra-cellular membranes, are also highly expressed in the pulp of self-grafted watermelon. Cutin, suberine, and wax biosynthesis-related genes are also highly expressed in the pulp of self-grafted watermelon (XG), which suggests that grafting can also affect wax synthesis in watermelons.
Furthermore, the DEGs identified between the stem of self-grafted watermelon and pumpkin-grafted watermelon were enriched in pentose and glucuronate interconversions and amino sugar and nucleotide sugar metabolism-related items. These genes were highly expressed in the stem of pumpkin-grafted plants (Figure 3d and Figure S1c). Several genes encoding pectinesterases were found to be highly expressed in the stem of pumpkin-grafted plants. The stem is essential for distributing photosynthetic products, and alterations in gene expression can influence the movement of sugars and other organic compounds to the fruit [29]. Glucose-1-phosphate adenylyltransferase, also known as GPT, is a key intermediate in glucose metabolism [30]. Several family members are highly expressed in the stem of pumpkin-grafted plants. GO analysis revealed that genes enriched in items belonging to microtubule (microtubule binding and microtubule-based process), cell wall (plant-type cell wall organization or biogenesis and cell wall organization or biogenesis), and fiber (polymeric cytoskeletal fiber and supramolecular fiber) are highly expressed in the stem of pumpkin-grafted plants. These findings suggested that grafting can change the rigidity and transport capacity of the stem by affecting the cell wall and the content of microtubules and fibers in it to improve the quality of the watermelon fruit. Studies showed that mRNA can move from rootstock to scion, and the mRNA identified in the transcriptome might move to the fruit of scion to alter the phenotype. It is possible that the changes in metabolites in the fruit are caused by gene shifts in the pumpkin rootstock [31,32,33].

4. Conclusions

In this study, transcriptomic and metabolomic analyses were performed to uncover the effects of fruit grafting on fruit quality. The metabolomic analysis revealed that phloretin and citric acid, which affect fruit quality, are highly accumulated in pumpkin-grafted watermelon. Moreover, substances with antioxidant properties showed higher concentrations. In contrast, substances contributing to a bitter taste were found at lower concentrations. Transcriptome showed that microtubule, cell wall, and fiber-related genes are highly expressed in the stem of pumpkin-grafted watermelon, suggesting that grafting could change the structure of the stem. Our study reveals the effects of grafting on watermelon quality from the transcriptional level and metabolic level and provides information for future exploration of the molecular mechanism of grafting to improve watermelon fruit quality.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/horticulturae10121269/s1, Figure S1: Transcriptome validation and function analysis of DEGs; Table S1: Primers used in this study; Table S2: Metabolite characteristics; Table S3: Summary of transcriptome.

Author Contributions

Data curation, A.X.; Methodology, K.N. and P.X.; Project administration, Y.W.; Resources, L.Y.; Supervision, P.X.; Validation, K.N., X.C. and L.Y.; Visualization, W.Z.; Writing—original draft, K.N. and X.C.; Writing—review and editing, P.X. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Ningbo Science and Technology Innovation 2025 major project, grant number 2021Z006.

Data Availability Statement

Data will be made available on request. The raw RNA-seq data (Accession no. PRJNA1151145) were uploaded to NCBI.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Overview of the detected metabolites in grafted watermelons. (a) Classification of all metabolites. (b) The clustering heatmap displays all metabolites, with each sample represented by a column and each metabolite by a row. The abundance of metabolites is illustrated through colored bars, where upregulated metabolites are shown in varying shades of red, while downregulated metabolites are represented in different shades of blue. Phylogenetic tree was constructed according to the neighbor-joining method. (c) Heatmap of correlation of samples. (d) PCA score plot.
Figure 1. Overview of the detected metabolites in grafted watermelons. (a) Classification of all metabolites. (b) The clustering heatmap displays all metabolites, with each sample represented by a column and each metabolite by a row. The abundance of metabolites is illustrated through colored bars, where upregulated metabolites are shown in varying shades of red, while downregulated metabolites are represented in different shades of blue. Phylogenetic tree was constructed according to the neighbor-joining method. (c) Heatmap of correlation of samples. (d) PCA score plot.
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Figure 2. Summary of the metabolites identified in grafted watermelon. (a) Venn diagram illustrating the differential metabolites between XG and JG. A total of 124 metabolites are highly accumulated in XG, while 92 metabolites are highly accumulated in YG. A total of 912 metabolites are not different between the two types of watermelon. (b) Radar chart displaying the top 10 differentially accumulated metabolites (DAMs). The y-axis represents the multiple of difference. (c) KEGG analysis of the differentially accumulated metabolites is presented. In this plot, each bubble corresponds to a metabolic pathway, where the x-axis and bubble size together reflect the pathway’s impact factors; larger bubbles signify greater impact. The x-axis indicates the enrichment ratio of metabolites within each pathway, while the colors of the bubbles represent the p-values from the enrichment analysis. The results are organized according to the p-value. (d) Network representation of the top hub metabolites, with yellow squares indicating pathways, red circles denoting upregulated metabolites, and blue circles representing downregulated metabolites.
Figure 2. Summary of the metabolites identified in grafted watermelon. (a) Venn diagram illustrating the differential metabolites between XG and JG. A total of 124 metabolites are highly accumulated in XG, while 92 metabolites are highly accumulated in YG. A total of 912 metabolites are not different between the two types of watermelon. (b) Radar chart displaying the top 10 differentially accumulated metabolites (DAMs). The y-axis represents the multiple of difference. (c) KEGG analysis of the differentially accumulated metabolites is presented. In this plot, each bubble corresponds to a metabolic pathway, where the x-axis and bubble size together reflect the pathway’s impact factors; larger bubbles signify greater impact. The x-axis indicates the enrichment ratio of metabolites within each pathway, while the colors of the bubbles represent the p-values from the enrichment analysis. The results are organized according to the p-value. (d) Network representation of the top hub metabolites, with yellow squares indicating pathways, red circles denoting upregulated metabolites, and blue circles representing downregulated metabolites.
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Figure 3. Transcriptional profile and grafting-induced changes in watermelon. (a) Principal component analysis (PCA) score plot of RNA-Seq data, where XG and YG represent the pulp of pumpkin-grafted and self-grafted watermelon, respectively, and XJ and YJ represent the stem of pumpkin-grafted and self-grafted watermelon, respectively. (b) The number of upregulated and downregulated differentially expressed genes (DEGs) across different comparisons. (c) Enrichment of Kyoto Encyclopedia of Genes and Genomes Orthology (KO) terms for DEGs in the YG vs. XG comparison. (d) Gene Ontology (GO) term enrichment for DEGs in the YJ vs. XJ comparison.
Figure 3. Transcriptional profile and grafting-induced changes in watermelon. (a) Principal component analysis (PCA) score plot of RNA-Seq data, where XG and YG represent the pulp of pumpkin-grafted and self-grafted watermelon, respectively, and XJ and YJ represent the stem of pumpkin-grafted and self-grafted watermelon, respectively. (b) The number of upregulated and downregulated differentially expressed genes (DEGs) across different comparisons. (c) Enrichment of Kyoto Encyclopedia of Genes and Genomes Orthology (KO) terms for DEGs in the YG vs. XG comparison. (d) Gene Ontology (GO) term enrichment for DEGs in the YJ vs. XJ comparison.
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MDPI and ACS Style

Ning, K.; Cai, X.; Yan, L.; Zhou, W.; Xie, A.; Wang, Y.; Xu, P. Transcriptomic and Metabolomic Analysis Reveals Improved Fruit Quality in Grafted Watermelon. Horticulturae 2024, 10, 1269. https://doi.org/10.3390/horticulturae10121269

AMA Style

Ning K, Cai X, Yan L, Zhou W, Xie A, Wang Y, Xu P. Transcriptomic and Metabolomic Analysis Reveals Improved Fruit Quality in Grafted Watermelon. Horticulturae. 2024; 10(12):1269. https://doi.org/10.3390/horticulturae10121269

Chicago/Turabian Style

Ning, Kang, Xiaoqi Cai, Leiyan Yan, Weixin Zhou, An Xie, Yuhong Wang, and Pei Xu. 2024. "Transcriptomic and Metabolomic Analysis Reveals Improved Fruit Quality in Grafted Watermelon" Horticulturae 10, no. 12: 1269. https://doi.org/10.3390/horticulturae10121269

APA Style

Ning, K., Cai, X., Yan, L., Zhou, W., Xie, A., Wang, Y., & Xu, P. (2024). Transcriptomic and Metabolomic Analysis Reveals Improved Fruit Quality in Grafted Watermelon. Horticulturae, 10(12), 1269. https://doi.org/10.3390/horticulturae10121269

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