RNA-Seq Analysis and Candidate Gene Mining of Gossypium hirsutum Stressed by Verticillium dahliae Cultured at Different Temperatures

Abstract

The occurrence and spread of Verticillium dahliae (V. dahliae) in cotton depends on the combined effects of pathogens, host plants, and the environment, among which temperature is one of the most important environmental factors. Studying how temperature impacts the occurrence of V. dahliae in cotton and the mechanisms governing host defense responses is crucial for disease prevention and control. Understanding the dual effects of temperature on both pathogens and hosts can provide valuable insights for developing effective strategies to manage this destructive fungal infection in cotton. This study was based on the deciduous V. dahliae Vd-3. Through cultivation at different temperatures, Vd-3 formed the most microsclerotia and had the largest colony diameter at 25 °C. Endospore toxins were extracted, and 48 h was determined to be the best pathogenic time point for endotoxins to infect cotton leaves through a chlorophyll fluorescence imaging system and phenotypic evaluation. Transcriptome sequencing was performed on cotton leaves infected with Vd-3 endotoxins for 48 h at different culture temperatures. A total of 34,955 differentially expressed genes (DEGs) were identified between each temperature and CK (no pathogen inoculation), including 17,422 common DEGs. The results of the enrichment analysis revealed that all the DEGs were involved mainly in photosynthesis and sugar metabolism. Among the 34,955 DEGs, genes in the biosynthesis and signal transduction pathways of jasmonic acid (JA), salicylic acid (SA), and ethylene (ET) were identified, and their expression patterns were determined. A total of 5652 unique DEGs were clustered into six clusters using the k-means clustering algorithm, and the functions and main transcription factors (TFs) of each cluster were subsequently annotated. In addition, we constructed a gene regulatory network via weighted correlation network analysis (WGCNA) and identified twelve key genes related to cotton defense against V. dahliae at different temperatures, including four genes encoding transcription factors. These findings provide a theoretical foundation for investigating temperature regulation in V. dahliae infecting cotton and introduce novel genetic resources for enhancing resistance to this disease in cotton plants.

Keywords: G. hirsutum; RNA-seq; V. dahliae; candidate genes; temperature.

Figure 1

(a) Phenotype and colony diameter of Vd-3 colonies after 14 days of culture at different temperatures, bar = 1 cm. Different letters indicate the significance level of difference in colony diameter at different temperatures (p < 0.05). (b) Phenotype and chlorophyll fluorescence imaging of cotton leaves infected with the spore toxin protein at different times under normal conditions; bar = 1 cm. (c) Phenotype and chlorophyll fluorescence imaging of cotton leaves infected with spore toxin protein at different temperatures for 48 h; bar = 1 cm.

Figure 2

(a) Correlation analysis of RNA-seq data from cotton leaves infected with the spore toxin protein at different temperatures. (b) PCA of RNA-seq data from cotton leaves infected with the spore toxin protein at different temperatures.

Figure 3

(a) Numbers of upregulated and downregulated DEGs at different temperatures. (b) Numbers of common and unique DEGs at different temperatures. (c) GO enrichment analysis of DEGs. (d) KEGG enrichment analysis of DEGs.

Figure 4

Line graph of the cluster analysis of DEGs. The green numbers represent the numbers of DEGs and TFs in each cluster.

Figure 5

(a) Line graph of the cluster analysis of unique DEGs. (b) Heatmap of TF proportions in each cluster. (c) Heatmap of the KEGG enrichment analysis results for each cluster.

Figure 6

(a) Calorimetry of JA biosynthesis and signaling-related DEGs. (b) Calorimetry of SA biosynthesis and signaling-related DEGs. (c) Calorimetry of ET biosynthesis and signaling-related DEGs.

Figure 7

(a) WGCNA module hierarchical clustering tree diagram; different modules are represented by different colors. (b) Correlation and significance heatmaps between samples and modules. (c) Red module gene interaction network diagram. (d) Turquoise module gene interaction network diagram. (e) Yellow module gene interaction network diagram. (f) Black module gene interaction network diagram.

Figure 8

Analysis of the expression patterns of candidate genes under different temperature conditions (error bars represent the means ± SEs of three replicates, * p < 0.05 and ** p < 0.01).