Identification of candidate reference genes in perennial ryegrass for quantitative RT-PCR under various abiotic stress conditions

Abstract

Background: Quantitative real-time reverse-transcriptase PCR (qRT-PCR) is an important technique for analyzing differences in gene expression due to its sensitivity, accuracy and specificity. However, the stability of the expression of reference genes is necessary to ensure accurate qRT-PCR assessment of expression in genes of interest. Perennial ryegrass (Lolium perenne L.) is important forage and turf grass species in temperate regions, but the expression stability of its reference genes under various stresses has not been well-studied. Methodology/Principal Findings: In this study, 11 candidate reference genes were evaluated for use as controls in qRT-PCR to quantify gene expression in perennial ryegrass under drought, high salinity, heat, waterlogging, and ABA (abscisic acid) treatments. Four approaches - Delta C T, geNorm, BestKeeper and Normfinder were used to determine the stability of expression in these reference genes. The results are consistent with the idea that the best reference genes depend on the stress treatment under investigation. Eukaryotic initiation factor 4 alpha (eIF4A), Transcription elongation factor 1 (TEF1) and Tat binding protein-1 (TBP-1) were the three most stably expressed genes under drought stress and were also the three best genes for studying salt stress. eIF4A, TBP-1, and Ubiquitin-conjugating enzyme (E2) were the most suitable reference genes to study heat stress, while eIF4A, TEF1, and E2 were the three best reference genes for studying the effects of ABA. Finally, Ubiquitin (UBQ), TEF1, and eIF4A were the three best reference genes for waterlogging treatments. Conclusions/Significance: These results will be helpful in choosing the best reference genes for use in studies related to various abiotic stresses in perennial ryegrass. The stability of expression in these reference genes will enable better normalization and quantification of the transcript levels for studies of gene expression in such studies. © 2014 Huang et al.