Abstract
Accurate measurement of gene expression levels is vital for advancing plant biology research. This study explores the identification and validation of stable reference genes (RGs) for gene expression analysis in Spinacia oleracea. Leveraging transcriptome data from various developmental stages, we employed rigorous statistical analyses to identify potential RGs. A total of 1196 candidate genes were initially screened based on expression variability, with subsequent refinement using criteria such as low variance and stability. Among 12 commonly used candidate RGs, EF1α and H3 emerged as the most stable across diverse experimental conditions, while GRP and PPR exhibited lower stability. These findings were further validated through qRT-PCR assays and comprehensive statistical analyses, including geNorm, NormFinder, BestKeeper, and RefFinder. Our study underscores the importance of systematic RG selection to ensure accurate normalization in gene expression studies, particularly in the context of S. oleracea developmental stages and physiological processes like flowering. These validated RGs provide a robust foundation for future gene expression analysis in S. oleracea and contribute to the advancement of molecular research in plant biology.