Selection and Validation of Reference Genes for Gene Expression Analysis in Switchgrass (Panicum virgatum) Using Quantitative Real-Time RT-PCR

Abstract

Switchgrass (Panicum virgatum) has received a lot of attention as a forage and bioenergy crop during the past few years. Gene expression studies are in progress to improve new traits and develop new cultivars. Quantitative real time PCR (qRT-PCR) has emerged as an important technique to study gene expression analysis. For accurate and reliable results, normalization of data with reference genes is essential. In this work, we evaluate the stability of expression of genes to use as reference for qRT-PCR in the grass P. virgatum. Eleven candidate reference genes, including eEF-1α, UBQ6, ACT12, TUB6, eIF-4a, GAPDH, SAMDC, TUA6, CYP5, U2AF, and FTSH4, were validated for qRT-PCR normalization in different plant tissues and under different stress conditions. The expression stability of these genes was verified by the use of two distinct algorithms, geNorm and NormFinder. Differences were observed after comparison of the ranking of the candidate reference genes identified by both programs but eEF-1α, eIF-4a, CYP5 and U2AF are ranked as the most stable genes in the samples sets under study. Both programs discard the use of SAMDC and TUA6 for normalization. Validation of the reference genes proposed by geNorm and NormFinder were performed by normalization of transcript abundance of a group of target genes in different samples. Results show similar expression patterns when the best reference genes selected by both programs were used but differences were detected in the transcript abundance of the target genes. Based on the above research, we recommend the use of different statistical algorithms to identify the best reference genes for expression data normalization. The best genes selected in this study will help to improve the quality of gene expression data in a wide variety of samples in switchgrass.

Selection and validation of reference house­keeping genes in the J774A1 macrophage cell line for quantitative real-time PCR

“…The reliability and stability of PPIA was verified in macrophages under all culture conditions, similar to that observed in normal and ovarian cancer cells (Jacob et al, 2013). Previous studies have reported GAPDH to be a highly unstable gene (Jacob et al, 2013;Gimeno et al, 2014;Matoušková et al, 2014), as the gene expression can be influenced by certain experimental conditions (Barber et al, 2005). Herein, we suggest that GAPDH can be considered as an internal control for macrophages, based on its stability and lower variance under various experimental conditions, as shown by BestKeeper analysis and the ∆∆ Ct values.…”

“…HKGs commonly used as reference genes in different tissue and cell lineages (Shah and Faridi, 2011;Jacob et al, 2013;Gimeno et al, 2014) were assessed for their use as reference genes in macrophages cultured under normal and laminin-coated conditions.…”

“…The analysis was based on the null hypothesis that amplification efficiency is comparable within sample groups allowing the detection of outlier samples, and that the amplification efficiency is comparable between sample groups in order to determine the amplification equivalence (Gimeno et al, 2014).…”

“…HKGs encode proteins that are essential for cell survival; therefore, the expression of these genes should be stable in all cells and tissues across various developmental stages and physiological and environmental conditions (Nelissen et al, 2010). However, previous studies have demonstrated that HKG expression varies under different experimental conditions (Shah and Faridi, 2011;Jacob et al, 2013;Gimeno et al, 2014); this necessitates the use of at least three reference genes to ensure the correct normalization of qPCR data (Vandesompele et al, 2002).…”

Expression of endogenous proteins in maize hybrids in a multi-location field trial in India

“…Understanding the factors that contribute to the variability in concentration of these housekeeping proteins may provide insight to explain the variability that is expected for transgenic proteins in GM crops. Actin, EF1-alpha and GAPDH were selected as example proteins for assessment because they are well studied (Brunner Cruz et al 2009;Gimeno et al 2014;Gutha et al 2010;Li et al 2011;Paolacci et al 2009), and indirect quantitative ELISA methods could be developed with commercially available antibodies. In this study, the concentrations of all three endogenous proteins were influenced by growth stage, hybrid background, and location, to some extent.…”