Regulatory Mechanisms of the Resistance to Common Bacterial Blight Revealed by Transcriptomic Analysis in Common Bean (Phaseolus vulgaris L.)

Abstract

Common bean blight (CBB), primarily caused by Xanthomonas axonopodis pv. phaseoli (Xap), is one of the most destructive diseases of common bean (Phaseolus vulgaris L.). The tepary bean genotype PI 319443 displays high resistance to Xap, and the common bean genotypes HR45 and Bilu display high resistance and susceptibility to Xap, respectively. To identify candidate genes related to Xap resistance, transcriptomic analysis was performed to compare gene expression levels with Xap inoculation at 0, 24, and 48 h post inoculation (hpi) among the three genotypes. A total of 1,146,009,876 high-quality clean reads were obtained. Differentially expressed gene (DEG) analysis showed that 1,688 DEGs responded to pathogen infection in the three genotypes. Weighted gene coexpression network analysis (WGCNA) was also performed to identify three modules highly correlated with Xap resistance, in which 334 DEGs were likely involved in Xap resistance. By combining differential expression analysis and WGCNA, 139 DEGs were identified as core resistance-responsive genes, including 18 genes encoding resistance (R) proteins, 19 genes belonging to transcription factor families, 63 genes encoding proteins with oxidoreductase activity, and 33 plant hormone signal transduction-related genes, which play important roles in the resistance to pathogen infection. The expression patterns of 20 DEGs were determined by quantitative real-time PCR (qRT-PCR) and confirmed the reliability of the RNA-seq results.

Genetic variation in a tepary bean (Phaseolus acutifolius A. Gray) diversity panel reveals loci associated with biotic stress resistance

“…Quantitative trait locus (QTL) were considered high confidence if they were statistically significant and detected by multiple mapping algorithms. Candidate gene identification was aided by previously generated datasets (Moghaddam et al., 2021; Schmutz et al., 2014; Yang et al., 2021).…”

Full-length transcriptome and RNA-Seq analyses reveal the resistance mechanism of sesame in response to Corynespora cassiicola

“…To date, the molecular mechanisms of resistance to Corynespora leaf spot in sesame have not yet been reported. Due to the advantages of transcriptome analysis in the study of plant-pathogen interactions, transcriptome analysis has been widely used to study the mechanisms of crop stress response [29][30][31]. Previous large-scale sequencing of cDNA has been instrumental for gene discovery in sesame, but the sequences rarely cover entire transcripts due to the limitation of NGS technologies [32].…”

Revealing Genetic Differences in Fiber Elongation between the Offspring of Sea Island Cotton and Upland Cotton Backcross Populations Based on Transcriptome and Weighted Gene Coexpression Networks

“…WGCNA is suitable for complex data patterns and can be applied to studies on developmental regulation of different organs or tissue types [ 77 , 78 , 79 ], developmental regulation of the same tissue at different times [ 108 , 109 ], response to abiotic stress at different time points [ 110 , 111 , 112 ], and response to pathogen infestation at different time points [ 73 , 113 , 114 ]. Zhou et al [ 77 ] used WGCNA to reveal five genes mediated by auxin and gibberellin as node genes in the regulatory network of flowering time in cotton.…”