Background: The zinc finger-homeodomain (ZF-HD) transcription factor family exerts pivotal regulatory functions in plant development and stress responses, yet a systematic genome-wide survey is lacking for Rosa chinensis. Methods: In this study, we performed a comprehensive genome-wide identification and analysis of RcZF-HD genes in R. chinensis using bioinformatics approaches. Nine RcZF-HD loci were mined from the rose genome and comprehensively profiled for physicochemical parameters, phylogenetic affiliations, chromosomal positions, exon–intron architectures, conserved motifs, and spatiotemporal expression landscapes. Results: The results showed that RcZF-HD genes were unevenly distributed across four chromosomes (Chr2, Chr4, Chr6, and Chr7), with tandem duplication events detected on chromosomes 2 and 7, suggesting their contribution to gene family expansion. Maximum-likelihood phylogeny placed RcZF-HD proteins within nine well-supported sub-clades alongside Arabidopsis orthologs, implying both evolutionary conservation and lineage-specific divergence. All members retain canonical zinc-finger domains, yet acquire unique motif signatures predictive of functional specialization. Gene structure analysis revealed considerable diversity in exon–intron organization. Expression profiling across six different tissues (root, stem, leaf, bud, flower, and fruit) demonstrated remarkable tissue-specific expression patterns. Notably, RchiOBHmChr2g0168531 exhibited extremely high expression in stem tissue, while RchiOBHmChr7g0181371 showed preferential expression in flower tissue, suggesting specialized roles in stem development and floral organ formation, respectively. The cold-stress challenge of ‘Old Blush’ petals further disclosed pronounced up-regulation of seven RcZF-HD genes, attesting to their critical contribution to low-temperature tolerance. Conclusions: Integrative analyses furnish a multidimensional blueprint of the rose RcZF-HD repertoire, providing molecular landmarks for future functional dissection and ornamental trait engineering.
Su et al. (Thu,) studied this question.