Abstract
BACKGROUND: The use of stably expressed genes as normalizers has crucial role in accurate and reliable expression analysis estimated by quantitative real-time polymerase chain reaction (qPCR). Recent studies have shown that, the expression levels of common housekeeping genes are varying in different tissues and experimental conditions. The genomic DNA contamination in RNA samples is another important factor that also influence the interpretation of the data obtained from qPCR. It is estimated that the gDNA contamination in gene expression analysis lead to an overestimation of the RNA transcript level. The aim of this study was to validate the most stably expressed reference genes in two different tissues of Aeluropus littoralis-halophyte grass at salt stress and recovery condition. Also, a qPCR-based approach for monitoring contamination with gDNA was conducted. RESULTS: Ten candidate reference genes participating in different biological processes were analyzed in four groups of samples including root and leaf tissues, salt stress and recovery condition. To determine the most stably expressed reference genes, three statistical methods (geNorm, NormFinder and BestKeeper) were applied. According to results obtained, ten candidate reference genes were ranked based on the stability of their expression. Here, our results show that a set of four housekeeping genes (HKGs) e.g. RPS3, EF1A, GTF and RPS12 could be used as general reference genes for the all selected conditions and tissues. Also, four set of reference genes were proposed for each tissue and condition including: RPS3, EF1A and UBQ for salt stress and root samples; RPS3, EF1A, UBQ as well as GAPDH for recovery condition; U2SURP and GTF for leaf samples. Additionally, for assessing DNA contamination in RNA samples, a set of unique primers were designed based on the conserved region of ribosomal DNA (rDNA). The universality, specificity and sensitivity of these primer pairs were also evaluated in Poaceae. CONCLUSIONS: Overall, the sets of reference genes proposed in this study are ideal normalizers for qPCR analysis in A. littoralis transcriptome. The novel reference gene e.g. RPS3 that applied this study had higher expression stability than commonly used housekeeping genes. The application of rDNA-based primers in qPCR analysis was addressed.