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

不同温度下培养的受大丽轮枝菌胁迫的陆地棉的RNA测序分析和候选基因挖掘

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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.

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