Petaloid stamens in Paeonia lactiflora constitute an important developmental phenomenon that explain double flower formation. Although research on stamen development in model plants has progressed considerably, the underlying molecular mechanism in P. lactiflora petaloid stamens is still unclear. In this study, acomparative transcriptomic analysis was performed on two cultivars of P. lactiflora (‘Fen Yu Nu’ and ‘Lian Tai’) with different stamen developmental patterns. Following transcriptome sequencing, 89,393 unigenes were identified in P. lactiflora. Trend analysis and weighted gene co-expression network analysis (WGCNA) indicated that 18 candidate genes were likely involved in the formation and development of petaloid stamens, including seven MADS-box genes, PlAP3, PlDEFA, PlPI2, PlAG-1, PlSEP3, PlSEP1-1, and PlSEP1-2, and 11 other transcription factors (TFs), PlTCP2, PlTCP4, PlTCP9, PlbHLH36, PlICE1, PlLBD38, PlNAC083, PlBLH11, PlPDF2, PlGBF1, and PlIIIA. Using these 18 selected candidate genes, we propose ahypothetical model of gene expression network that regulates the development of petaloid stamens. Our results provide acollection of candidate genes that are useful for the analysis of P. lactiflora petaloid stamens, allowing for in-depth studies of the development pattern of P. lactiflora flower organs, and providing atheoretical basis for related research on petaloid stamens of flowers in other herbaceous plants.

Background: The CRISPR-Cas9 system has emerged as one of the most promising gene-editing technologies in biology. However, off-target effects remain a significant challenge. While recent advances in deep learning have led to the development of models for off-target prediction, these models often fail to fully leverage sequence pair information. Furthermore, as the models’ parameter sizes increase, so do their complexities, limiting their practical applicability. Methods: In this study, we introduce a novel multi-feature independent encoding method, which encodes the gRNA-DNA sequence pair into three distinct feature matrices to minimize information loss. Additionally, we propose a lightweight hybrid deep learning framework, CRISPR-MFH, that integrates multi-scale separable convolutions and hybrid attention mechanisms for efficient and accurate off-target prediction. Results: Extensive experiments across multiple benchmark datasets demonstrate that the proposed encoding method effectively captures critical features and that CRISPR-MFH outperforms or matches state-of-the-art models with significantly fewer parameters across multiple evaluation metrics. Conclusions: This study offers a novel perspective for advancing deep learning technology in the realm of CRISPR-Cas9 off-target detection.

Mitogen-activated protein kinases (MAPKs) are crucial regulators in coping with abiotic and biotic stresses, including drought, salinity, fungi, and pathogens. However, little is known about the characteristics, evolution process, and functional divergence of the MAPK gene family in Rosaceae plants. A total of 97 MAPK members were identified in six Rosaceae species, including 12 genes in Fragaria vesca, 22 genes in Malus domestica, 23 genes in Pyrus bretschneideri, 12 genes in Prunus mume, 14 genes in Prunus persica, and 14 genes in Rosa chinensis. All MAPK members of six Rosaceae plants were categorized into four clusters by the phylogenetic relationship analysis. Collinearity analysis discovered that both segmental duplication and tandem duplication contributed to the expansion of MAPK family genes in Rosaceae plants. And the analysis of motifs and gene structures indicated that the evolution of the MAPK gene family was highly conserved among phylogenetic clusters in Rosaceae species. In addition, the d_N/d_S rates of MAPK paralogous gene pairs were below one, suggesting the MAPK gene family in Rosaceae was driven by purifying selective pressure. Furthermore, functional divergence analysis discovered that 14 amino acid residues were detected as potentially key sites for functional divergence of MAPK family genes between different cluster pairs, specifically Type I functional divergence. The analysis of functional distance indicated that cluster C retained more of the original functional features, while cluster B exhibited functional specialization. Moreover, the expression profiles revealed that PmMAPK8, PmMAPK9, and PmMAPK10 were both highly expressed under drought stress and low temperature conditions. This study aims to comprehensively analyze the evolutionary process and functional analyses of the MAPK gene family in Rosaceae plants, which will lay the foundation for future studies into MAPK genes of Rosaceae in response to drought and cold stress.

Flavonoid biosynthesis is proposed to play a critical role in floral organ development in Paeonia species. However, its specific involvement in stamen petalization remains unclear. This study identified and characterized 13 gene families related to flavonoid biosynthesis across four Paeonia species. Comparative and phylogenetic analysis revealed that most flavonoid biosynthesis-related genes experience lineage-specific expansion in P. ludlowii. Genes belonging to the same family were commonly clustered on chromosomes and displayed highly conserved domain and motif compositions. The cis-element analysis identified Cis-acting elements associated with light, hormonal, and stress responses, implicating their regulatory roles in flavonoid biosynthesis. To further investigate the role of these genes in stamen petalization of P. lactiflora, expression profiling analyses were performed on ‘Fen Yu Nu’ (normal stamens) and ‘Lian Tai’ (petaloid stamens) cultivars using transcriptomic data released previously. Three quercetin-related genes revealed distinct stage-specific patterns in ‘Fen Yu Nu’ and ‘Lian Tai’. Notably, PlaF3’H03 exhibited significant upregulation during petaloid stamen development in ‘Lian Tai’, suggesting its role in stamen transformation. Molecular docking identified PlaF3’H07 as a key enzyme with strong substrate-binding affinity (ΔG = −4.7 kcal/mol), supporting its catalytic function in quercetin synthesis. The expression pattern of key flavonoid biosynthetic genes was also confirmed across three developmental stages of floral buds by real-time quantitative PCR. This study provides insights into the genetic basis underlying stamen petalization in P. lactiflora and offers potential targets for genetic improvement of floral traits in Paeonia and other ornamental plants.