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. 2024 May 21;8(5):e590.
doi: 10.1002/pld3.590. eCollection 2024 May.

Transcriptomic analysis of the defense response in "Cabernet Sauvignon" grape leaf induced by Apolygus lucorum feeding

Heng Yao  1   2 , Suhong Gao  1   2 , Tianhua Sun  3 , Guona Zhou  3 , Changkuan Lu  1 , Baojia Gao  3 , Wenshu Chen  1   2 , Yiming Liang  1   2
Affiliations

Transcriptomic analysis of the defense response in "Cabernet Sauvignon" grape leaf induced by Apolygus lucorum feeding

Heng Yao et al. Plant Direct. .

Abstract

To investigate the molecular mechanism of the defense response of "Cabernet Sauvignon" grapes to feeding by Apolygus lucorum, high-throughput sequencing technology was used to analyze the transcriptome of grape leaves under three different treatments: feeding by A. lucorum, puncture injury, and an untreated control. The research findings indicated that the differentially expressed genes were primarily enriched in three aspects: cellular composition, molecular function, and biological process. These genes were found to be involved in 42 metabolic pathways, particularly in plant hormone signaling metabolism, plant-pathogen interaction, MAPK signaling pathway, and other metabolic pathways associated with plant-induced insect resistance. Feeding by A. lucorum stimulated and upregulated a significant number of genes related to jasmonic acid and calcium ion pathways, suggesting their crucial role in the defense molecular mechanism of "Cabernet Sauvignon" grapes. The consistency between the gene expression and transcriptome sequencing results further supports these findings. This study provides a reference for the further exploration of the defense response in "Cabernet Sauvignon" grapes by elucidating the expression of relevant genes during feeding by A. lucorum.

Keywords: Apolygus lucorum; Cabernet Sauvignon; defense response; differentially expressed gene; metabolic pathway; transcriptome sequencing.

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Conflict of interest statement

The authors declare that this research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
RNA quality analysis on nine “Cabernet Sauvignon” grape leaf samples and analysis of differentially expressed genes (DEGs) among the three treatments. (a) RNA quality detection showing clear and complete bands for all nine samples. (b) PCA analysis was performed to examine the differential genes among the three treatments. (c) Volcano maps were created to visualize the DEGs across the different treatments.
FIGURE 2
FIGURE 2
Cluster analysis was conducted on differentially expressed genes (DEGs) using the K‐means algorithm. (a) Clustering pattern analysis of DEGs(p adjust < .05). Note: Red represents upregulated genes, and blue represents downregulated genes. (b) Clustering pattern analysis of DEGs when Sum = 3. (c) |Log2FC| ≥ 5 pairs of screened DEGs cluster analysis with a difference of more than 5
FIGURE 3
FIGURE 3
GO functional classification and metabolic pathway enrichment. (a) GO annotation of differentially expressed genes (DEGs) in various treatments (|Log2FC| ≥ 2). Note: The x axis represents the functional categories of GO, and the y axis represents the number of genes associated with each function. (b) GO enrichment analysis of DEGs between the PI and CK treatments and the AI and CK treatments. (c) GO enrichment analysis of DEGs between the AI and PI treatments
FIGURE 4
FIGURE 4
KEGG functional analysis and enrichment analysis were performed on the differentially expressed genes (DEGs). A histogram of KEGG function annotations was generated to compare the DEGs between AI&CK and PI&CK.
FIGURE 5
FIGURE 5
Enrichment chord plot analysis was conducted to compare differentially expressed genes (DEGs) between the treatments. (a–c) GO enrichment chord plots (|log2FC| ≥ 2; p < .05). (a) DEGs between the PI and CK treatments, (b) DEGs between the AI and CK treatments, and (c) DEGs between the AI and PI treatments. Similarly, (d)–(f) depict the KEGG enrichment chord plot analysis of DEGs between different treatments (|log2FC| ≥ 2; p < .05). (d) KEGG enrichment of DEGs in “Cabernet Sauvignon” leaves compared with the AI and CK treatments, (e) KEGG enrichment of DEGs in “Cabernet Sauvignon” leaves compared with the PI and CK treatments, and (f) comparison of the AI and PI treatments. Note: The genes/transcripts on the left are arranged in descending order of log2FC, indicating the expression difference between upregulated and downregulated genes/transcripts. A larger log2FC value indicates a greater expression difference for upregulated genes/transcripts, while a smaller log2FC value indicates a greater expression difference for downregulated genes/transcripts. The closer the value of log2FC is to 0, the smaller the differential expression of genes/transcripts.
FIGURE 6
FIGURE 6
Compared with the CK treatment, the signal pathway map of DEGs in the AI treatment was significantly localized. Map 04075 is the plant hormone signal transfer pathway, and homologous genes such as JAZ and MYC2 have been annotated. Map 04626 is the interaction metabolic pathway of plant pathogens, which is mainly mapped to the expression of defense genes related to Ca2+ and allergic reactions. Map 04016 is the MAPK signaling pathway, in which the phosphorylation of MAPK kinases causes the stress response of “Cabernet Sauvignon.” Note: “formula image” represents known genes/transcripts, “formula image” represents upregulated genes, “formula image” represents downregulated genes, “formula image” represents up + downregulated genes, “formula image” represents new genes/transcripts, and “formula image” represents known + new genes/transcripts.
FIGURE 7
FIGURE 7
Validation map for RT‐qPCR includes the following: (a) PCR amplification electrophoresis; (b) melting curves of 20 differential genes and internal reference genes; and (c) linear regression analysis of the RNA‐seq and RT‐qPCR data
See this image and copyright information in PMC

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