Identification of Candidate Reference Genes in Perennial Ryegrass for Quantitative RT-PCR under Various Abiotic Stress Conditions

Abstract

BackgroundQuantitative 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 FindingsIn 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 CT, 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/SignificanceThese 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.

Selection of reference genes for quantitative real-time PCR normalization in creeping bentgrass involved in four abiotic stresses

“…To our knowledge, the current study is the first to identify stable reference genes in leaves and roots of creeping bentgrass under different abiotic stresses (salt, drought, heat, and cold) using the combination of GeNorm, NormFinder, BestKeeper, and RefFinder (Andersen et al 2004;Vandesompele et al 2002). The previous study indicated that different reference genes could be determined by three different softwares (GeNorm, NormFinder, and BestKeeper) based on different mathematical methods or parameters (Chen et al 2014;Huang et al 2014;Zhu et al 2012). Therefore, a comprehensive analysis method named RefFinder was used to achieve reliable results based on the data of different softwares.…”

“…The four traditional reference genes (ACT, TUB, GAPDH, and EF1a) exhibited stable expression in certain plant species but had varied expressions in other species (Gimeno et al 2014;Huang et al 2014;Zhu et al 2013). For example, GAPDH was identified as the most stable reference gene in heat-stressed buffalograss (Buchloe dactyloides) ) but exhibited unstable expression in Oryza sativa under different environmental conditions (Jain et al 2006).…”

“…The comprehensive rankings of candidate references shown in Table 2 were determined by RefFinder tool (http://www.leonxie.com/referencegene.php) based on different software programs including GeNorm, NormFinder, and BestKeeper (Chen et al 2014;Huang et al 2014;Zhu et al 2012). PP2A, CACS, and GAPDH were identified as the three most stable reference genes in the total samples.…”

“…However, accurate determination of candidate gene expression levels and patterns depends on the use of stable internal reference genes (RGs) (Chen et al 2014;Jain et al 2006;Kundu et al 2013;Li et al 2012;Pfaffl 2001;Wang et al 2014a). Several RGs such as actin (ACT), tubulin (TUB), elongation factor 1a (EF1a), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and 18s ribosomal RNA (18S rRNA) involved in primary metabolism or other cellular processes were commonly utilized in previous studies and exhibited either stable and constitutive expression at certain developmental stages in specific tissues or responding to experimental stimuli Li et al 2014) but were unstable under other experimental conditions (Chen et al 2014;Huang et al 2014;Zhu et al 2013). Recent studies have identified several novel RGs such as SAND family protein (SAND) (Demidenko et al 2011), clathrin adapter complex subunit family protein (CACS) (Marum et al 2012), F-box/kelch-repeat protein (F-box) (Lin et al 2013), phosphoenolpyruvate carboxylase-related kinase 1 (PEPKR1) (Chi et al 2012), TIP41-like family protein (TIP41) (Zhu et al 2013), and protein phosphatase 2A (PP2A) (Lovdal and Lillo 2009).…”

2D-DIGE-based proteome expression changes in leaves of rice seedlings exposed to low-level gamma radiation at Iitate village, Fukushima

“…The gene expressing this protein has been shown to be stably expressed during drought and salt stress, but not necessarily during oxidative or other types of stress. 25 …”