The β-amylase (BAM) gene family encodes important enzymes that catalyze the conversion of starch to maltose in various biological processes of plants and play essential roles in regulating the growth and development of multiple plants. So far, BAMs have been extensively studied in Arabidopsis thaliana (A. thaliana). However, the characteristics of the BAM gene family in the crucial economic crop, cotton, have not been reported. In this study, 27 GhBAM genes in the genome of Gossypium hirsutum L (G. hirsutum) were identified by genome-wide identification, and they were divided into three groups according to sequence similarity and phylogenetic relationship. The gene structure, chromosome distribution, and collinearity of all GhBAM genes identified in the genome of G. hirsutum were analyzed. Further sequence alignment of the core domain of glucosyl hydrolase showed that all GhBAM family genes had the glycosyl hydrolase family 14 domain. We identified the BAM gene GhBAM7 and preliminarily investigated its function by transcriptional sequencing analysis, qRT-PCR, and subcellular localization. These results suggested that the GhBAM7 gene may influence fiber strength during fiber development. This systematic analysis provides new insight into the transcriptional characteristics of BAM genes in G. hirsutum. It may lay the foundation for further study of the function of these genes.

Background: DNA methylation is an important part of epigenetic regulation and plays an important role in the response of plants to adverse stress. Methods: In this study, whole-genome bisulfite sequencing (WGBS) was performed on the high-temperature-resistant material Xinluzao 36 and the high-temperature-sensitive material Che 61–72 at 0 h and 12 h under high-temperature stress conditions. Results: The results revealed that the Gossypium hirsutum methylation levels of CG and CHG (H = A, C, or T) decreased after the high-temperature stress treatment, and the methylation level of the A subgenome was significantly greater than that of the D subgenome. The methylation level of CHH increased, and the methylation level of CHH in the D subgenome was significantly greater than that in the A subgenome after high-temperature stress treatment. The methylation density of CG is lower than that of CHG and CHH, and the methylation density of the middle region of chromosomes is greater than that of both ends, which is opposite to the distribution density of genes. There were 124 common differentially methylated genes in the CG, CHG, and CHH groups, and 5130 common DEGs and differentially methylated genes were found via joint analysis with RNA-seq; these genes were significantly enriched in the biosynthesis of plant hormones, thiamine metabolism, glutathione metabolism, and tyrosine metabolism pathways. DNA methylation did not affect the expression of many genes (accounting for 85.68% of the differentially methylated genes), DNA methylation-promoted gene expression was located mainly in the downstream region of the gene or gene body, and the expression of inhibitory genes was located mainly in the upstream region of the gene. Conclusions: This study provides a theoretical basis for further exploration of the gene expression and functional regulatory mechanism of G. hirsutum DNA methylation under high-temperature stress conditions.

Cotton is an important commercial crop whose growth and yield are severely affected by drought. S-adenosylmethionine (SAM) is widely involved in the plant stress response and growth regulation; however, the role of the S-adenosylmethionine synthase (SAMS) gene family in this process is poorly understood. Here, we systematically analyzed the expression of SAMS genes in Upland Cotton (Gossypium hirsutum L.). A total of 16 SAMS genes were identified, each with a similar predicted structure. A large number of cis-acting elements involved in the response to abiotic stress were predicted based on promoter analysis, indicating a likely important role in abiotic stress responses. The results of qRT-PCR validation showed that GhSAMS genes had different expression patterns after drought stress and in response to drought stress. Analysis of a selected subset of GhSAMS genes showed increased expression in cultivar Xinluzhong 39 (drought resistant) when compared to cultivar Xinluzao 26 (drought-sensitive) upland cotton. This study provides important relevant information for further study of SAMS genes in drought resistance research of upland cotton, which is helpful for drought-resistance improvement of upland cotton.

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.

Background: In recent years, changes in climate conditions and long-term continuous cropping have led to the increased occurrence of Verticillium wilt in various cotton-growing regions, causing significant economic losses in cotton production. Research has shown that volatile substances are closely linked to plant disease resistance; however, studies on their roles in the response of cotton to Verticillium wilt, including their relationship with gene regulation, are limited. Methods: In this study, the transcriptomes and metabolomes of Xinluzao 57 (a highly susceptible Verticillium wilt variety) and 192,868 (a highly resistant Verticillium wilt variety) were sequenced at different time points after inoculation with Verticillium wilt. Results: A total of 21,911 commonly differentially expressed genes (DEGs) were identified within and between the materials, and they were clustered into eight groups. Significant annotations were made in pathways related to amino acids and anthocyanins. Metabolomics identified and annotated 26,200 volatile metabolites across nine categories. A total of 158 differentially accumulated metabolites (DAMs) were found within and between the materials; three clusters were identified, and the 10 metabolites with the most significant fold changes were highlighted. Weighted gene coexpression network analysis (WGCNA) revealed that 13 genes were significantly correlated with guanosine, 6 genes were correlated with 2-deoxyerythritol, and 32 genes were correlated with raffinose. Conclusions: Our results provide a foundation for understanding the role of volatile substances in the response of cotton to Verticillium wilt and offer new gene resources for future research on Verticillium wilt resistance.