Validated reference genes for normalization of RT-qPCR in developing organs of wheat to study developmentally/spatio-temporally expressed family genes

Abstract

Abstract Quantitative real-time PCR (RT-qPCR) is one of the most accurate methods for gene expression analysis. An important step in such an examination is normalization of the results by the application of appropriate internal control. In this study, we evaluated ten candidate reference genes in wheat (Triticum aestivum) to identify the most stable for normalization across different tissues and organs of developing plants. In Experiment 1, ten reference genes were analyzed in three tissues of the Ostka cultivar, with stability rankings generated using BestKeeper, NormFinder, geNorm, and RefFinder. Among these, Ta2776, eF1a, Cyclophilin, Ta3006, Ta14126, and Ref 2 were consistently identified as the most stable, while β-tubulin, CPD, and GAPDH were the least stable. In Experiment 2, six reference genes were tested across five tissues. Ta2776, Cyclophilin, Ta3006, and Ref 2 showed high stability across tissues, whereas CPD and Actin were less reliable. Analysis of the two best performing genes, Ref 2 and Ta3006, in twelve tissues/organs from two wheat cultivars, Kontesa and Ostka, revealed no significant differences in their expression between cultivars, confirming their suitability as reference genes for broader studies. Expression analysis of two target, developmentally expressed genes, TaIPT1 and TaIPT5, was conducted using absolute and normalized values. For TaIPT1, expressed in developing spikes, normalized and absolute values showed no significant differences. In contrast, for TaIPT5, expressed across all tested tissues, significant differences were observed between absolute and normalized values in most tissues. However, normalization using Ref 2, Ta3006, or both reference genes produced consistent results, underscoring the importance of proper reference gene selection. This study highlights the reliability of Ref 2 and Ta3006 as reference genes for accurate normalization in wheat gene expression analyses, providing a robust framework for future research.