Integrative analysis of Hub1 overexpression: driving transcriptional reprogramming and alternative splicing in Saccharomyces cerevisiae

Background Hub1, a conserved ubiquitin-like protein, is essential for pre-mRNA splicing and transcriptional regulation in Saccharomyces cerevisiae . Despite its known functions, the genome-wide effects of Hub1 overexpression remain largely uncharacterized. This study investigates the transcriptomic and splicing landscape changes triggered by Hub1 overexpression using an integrative bioinformatic approach. Results We analyzed RNA-seq data from the GSE84215 dataset, employing differential expression, alternative splicing, functional enrichment, and network-based methods. DESeq2 identified 3,915 differentially expressed genes (DEGs; 1,964 upregulated, 1,951 downregulated, padj < 0.05), demonstrating extensive transcriptional reprogramming. Principal component analysis revealed that Hub1 overexpression explained 98% of transcriptional variance, indicating its dominant regulatory influence. Using rMATS, we detected seven exon skipping events, with DYN2 showing significant differential splicing (FDR = 0.0481, ΔPSI = − 0.036). MaxEntScan analysis confirmed that DYN2 ’s 5′ splice site is significantly weaker than canonical yeast splice sites (score = − 18.32, p = 0.03), consistent with Hub1’s role in facilitating non-consensus splicing. Functional enrichment analyses revealed metabolic reprogramming, with upregulated pathways including biosynthesis of secondary metabolites and carbon metabolism, while growth-related processes like ribosome biogenesis and cell cycle were downregulated. Gene Set Enrichment Analysis (GSEA) further supported stress response activation (p53 signaling, NES = 1.255) and cell cycle suppression (NES = − 0.692). Weighted Gene Co-expression Network Analysis (WGCNA) identified 61 co-expression modules, with the brown module highly correlated with Hub1 overexpression ( r = 0.99, p < 0.001) and enriched in biosynthetic and proteasome pathways. Protein-protein interaction network analysis revealed 35 Hub1 interactors, including spliceosomal components, reinforcing its central role in RNA processing. Conclusion Our findings reveal that Hub1 overexpression drives coordinated transcriptional and post-transcriptional changes, promoting metabolic reprogramming while specifically modulating splicing of genes with weak splice sites like DYN2 . These results establish Hub1 as a dual regulator linking transcriptional control with splicing precision, suggesting a regulatory mechanism that enhances cellular adaptability under stress conditions.