Abstract
BACKGROUND: The somatic embryogenesis tissue culture process has been utilized to propagate high yielding oil palm. Due to the low callogenesis and embryogenesis rates, molecular studies were initiated to identify genes regulating the process, and their expression levels are usually quantified using reverse transcription quantitative real-time PCR (RT-qPCR). With the recent release of oil palm genome sequences, it is crucial to establish a proper strategy for gene analysis using RT-qPCR. Selection of the most suitable reference genes should be performed for accurate quantification of gene expression levels. RESULTS: In this study, eight candidate reference genes selected from cDNA microarray study and literature review were evaluated comprehensively across 26 tissue culture samples using RT-qPCR. These samples were collected from two tissue culture lines and media treatments, which consisted of leaf explants cultures, callus and embryoids from consecutive developmental stages. Three statistical algorithms (geNorm, NormFinder and BestKeeper) confirmed that the expression stability of novel reference genes (pOP-EA01332, PD00380 and PD00569) outperformed classical housekeeping genes (GAPDH, NAD5, TUBULIN, UBIQUITIN and ACTIN). PD00380 and PD00569 were identified as the most stably expressed genes in total samples, MA2 and MA8 tissue culture lines. Their applicability to validate the expression profiles of a putative ethylene-responsive transcription factor 3-like gene demonstrated the importance of using the geometric mean of two genes for normalization. CONCLUSIONS: Systematic selection of the most stably expressed reference genes for RT-qPCR was established in oil palm tissue culture samples. PD00380 and PD00569 were selected for accurate and reliable normalization of gene expression data from RT-qPCR. These data will be valuable to the research associated with the tissue culture process. Also, the method described here will facilitate the selection of appropriate reference genes in other oil palm tissues and in the expression profiling of genes relating to yield, biotic and abiotic stresses.