ABSTRACT: Rosa species hold considerable economic and medicinal importance, used in traditional medicine, essential oils, and landscaping. However, the mechanisms of floral scent formation in roses are not well understood, hindering genetic improvement. To bridge this gap, we conducted a combined transcriptome and metabolome analysis, identifying nine key fragrance compounds. Using Weighted Gene Co-expression Network Analysis (WGCNA), we linked 574 genes to these compounds. From these, we identified candidate genes through differential expression, functional annotations, and protein-protein interaction (PPI) networks. We predicted candidate genes, NUDIX1, NUDIX2, GERD, AFS1, AFS2, CYP82G1, HMG1, NCED2, CCD7, PSY, ICMEL2, MAD1, and MAD2 that might terpenoid-related genes, as well as potential benzeno
