Genome-Wide Identification of the Dirigent Gene Family and Expression Pattern Analysis Under Drought and Salt Stresses of Sorghum bicolor (L.)

<b>Background:</b> The <i>Dirigent</i> (<i>DIR</i>) gene family is pivotal for lignin polymerization and stress adaptation in plants, yet its systematic characterization in <i>Sorghum bicolor</i> (<i>S. bicolor</i>), a critical bioenergy crop, remains underexplored. <b>Methods:</b> Leveraging the <i>S. bicolor</i> genome database, we conducted a genome-wide identification, phylogenetic classification, and expression profiling of the <i>DIR</i> gene family. Evolutionary dynamics, gene structure variations, promoter cis-regulatory elements, and spatiotemporal transcriptome patterns were analyzed using bioinformatics and experimental validation (RT-qPCR). <b>Results:</b> A total of 53 <i>SbDIR</i> genes were systematically identified, exhibiting uneven chromosomal distribution. Phylogenetic analysis clustered them into five clades (DIR-a, DIR-b/d, DIR-c, DIR-e, DIR-f), with subfamily-specific exon number variations suggesting functional divergence. Evolutionary studies revealed tandem duplication (TD) as the primary driver of family expansion, accompanied by strong purifying selection. Promoter analysis highlighted abundant hormone- and stress-responsive cis-elements. Tissue-specific RNA-seq data revealed root-enriched expression of <i>SbDIR2/4/18/39/44/53</i>, implicating their roles in root development. Notably, <i>SbDIR39</i> and <i>SbDIR53</i> were significantly upregulated (2.8- and 5-fold, respectively) under 150 mM NaCl stress, underscoring their stress-responsive functions. <b>Conclusions:</b> This study provides the first comprehensive atlas of the <i>DIR</i> gene family in <i>S. bicolor</i>, elucidating its evolutionary mechanisms and tissue-specific/stress-induced expression profiles. Key candidates (<i>SbDIR39/53</i>) were identified as promising targets for molecular breeding or CRISPR-based editing to enhance stress resilience in <i>S. bicolor</i>. These findings lay a foundation for translating genomic insights into agronomic improvements.