Pseudouridine is one of the well-known chemical modifications in various RNA species. Current advances to detect pseudouridine show that the pseudouridine landscape is dynamic and affects multiple cellular processes. Although our understanding of this post-transcriptional modification mainly depends on yeast and human models, the recent findings provide strong evidence for the critical role of pseudouridine in plants. Here, we review the current knowledge of pseudouridine in plant RNAs, including its synthesis, degradation, regulatory mechanisms, and functions. Moreover, we propose future areas of research on pseudouridine modification in plants.

The phosphatidylethanolamine-binding protein (PEBP) gene family is critical for regulating plant growth, development, and flowering. Sunflower (Helianthus annuus L.) is the fourth most important oilseed crop globally. However, the genomic structure and functional diversity of PEBP genes in sunflower remain unexplored. Leveraging the recently assembled telomere-to-telomere (T2T) sunflower genome, a genome-wide analysis of the HaPEBP family was carried out. A total of 12 PEBP genes were identified in sunflower and categorized into three subfamilies: TFL1-like, FT-like, and MFT-like. Phylogenetic and synteny analyses revealed that tandem duplication events have substantially contributed to the evolution and expansion of the HaPEBP gene family. Furthermore, the analysis of the promoter regions revealed 77 distinct cis-acting elements, including 35 related to light signaling and growth regulation, highlighting their potential involvement in the regulation of flowering and development in sunflower. Expression profile analysis using RNA-seq data across various tissues indicated that FT-like and TFL1-like HaPEBP genes may be the key regulators of flowering time and plant architecture in sunflower varieties. This study offers valuable insights into the structural, evolutional, and functional dynamics of the HaPEBP gene family and holds significant implications for sunflower breeding strategies aimed at optimizing flowering time and plant architecture traits.

Introduction: Immunology education faces persistent challenges, including abstract concepts, theory-practice disconnect, and delayed feedback. Generative AI offers opportunities, yet its integration into pedagogical frameworks remains underexplored. Methods: We developed an Iterative AI-Augmented Immunology Education (IAIE) model integrating generative AI with the 4C/ID model and cognitive load theory. A 12-week quasi-experimental study enrolled 177 medical undergraduates (experimental: n = 88; control: n = 89), with outcomes assessed using the Host-Pathogen Interactions Concept Inventory (HPI-CI) and a modified Clinical Decision-Making in Nursing Scale (CDMNS). Results: The experimental group showed significantly greater knowledge mastery (82.7 vs. 70.1, Cohen’s d =1.12) and clinical decision-making accuracy (+31.7%). Over 84% of students recognized AI’s value in understanding complex mechanisms. Reflective practice scores indicated high levels of reflective ability, and DREEM assessments confirmed strong student acceptance of the learning environment. Discussion: The IAIE model effectively bridges theory and practice through AI-driven scaffolding that modulates cognitive load, fostering higher-order thinking and critical engagement with AI-generated content. This theory-informed framework offers a transferable approach for competency-based medical education.

Shoot branching plays a crucial role in shaping plant architecture, influencing both yield potential and ornamental qualities in sunflower (Helianthus annuus L.), but the genetic mechanisms underlying this trait are still not well understood. To investigate this, we performed a genome-wide association study (GWAS) using 82 sunflower accessions with diverse branching phenotypes and identified 62 significant single-nucleotide polymorphisms (SNPs). Of these, sixty SNPs clustered within a 12.40–17.13 Mb region on chromosome 10. Linkage disequilibrium (LD) block analysis delineated this region, containing 113 genes. Integration of transcriptomic analysis of shoot apical meristems of both branched and unbranched lines revealed 12 differentially expressed genes (DEGs) within the GWAS interval, including two long non-coding RNAs (lncRNAs) that demonstrated significant co-expression with several protein-coding candidates. Notably, one gene (HanXRQr2_Chr10g0423211) harbored a nonsynonymous SNP and displayed moderate differences in expression. Tissue-specific RNA-seq and qRT-PCR confirmed the involvement of these 13 genes in branching regulation. Overall, this study advances our understanding of the genetic mechanisms controlling shoot branching in sunflower and highlights candidate genes for targeted breeding to enhance plant architecture.