Short communicationAssessment of reference genes for reliable analysis of gene transcription by RT-qPCR in ovine leukocytes
Introduction
The advent of next-generation sequencing has led to a vast increase in available genomic and transcriptomic data, which combined with the paucity of available reagents for analysis of protein expression in most veterinary species, has led to an increased use of quantitative reverse transcription PCR (RT-qPCR) for gene transcription profiling (Bustin et al., 2005, Bustin et al., 2009). Despite well-documented shortcomings of this technique associated with major differences in mRNA quantity, quality and optimal assay design (Nolan et al., 2006), RT-qPCR is becoming the method of choice for RNA quantification. Measuring gene transcription levels in different tissues and cell types requires accurate normalization, most often achieved using an internal reference gene. Ideal reference genes should exhibit a relatively consistent transcription profile in different cell cycle stages and experimental conditions, as failing to do this will result in erroneous interpretation of the results (Vandesompele et al., 2002).
Large animals in general, and sheep in particular, are increasingly being used in immunological research (Davenport et al., 2014, Mahakapuge et al., 2015, Neeland et al., 2014, Scheerlinck et al., 2008). In sheep, PBMCs and lymph are the most commonly used sources of leukocytes, as they are readily and repetitively accessible and arguably represent the level of immune activity within the animal. Using pre-femoral efferent lymphatic cells and PBMCs from ten physiologically normal sheep we compared the transcriptional stability of reference genes with or without Con-A mediated T-cell activation, to determine the most appropriate reference genes in sheep leukocytes.
To identify the most consistently transcribed reference genes among the selected reference genes, we used statistical algorithms, geNorm version 3.5 (Center for Medical Genetics, Ghent University Hospital, Belgium) (Vandesompele et al., 2002) and Norm Finder (Version 20) (Andersen et al., 2004) according to developers’ recommendations. GeNorm software identifies the most consistently transcribed reference genes in a set of samples tested using average pairwise variation. The outcome is expressed as an “M-value”, which can be defined as the average pairwise variation of a particular reference gene compared to all other reference genes. The ideal reference gene for a particular tissue used in different experimental conditions should be transcribed equally in all the samples selected (i.e. minimum M-value). Additionally, the software also calculates pairwise variations, providing a geNorm V-value, which reflects levels of variation in average reference gene stability with the addition of n + 1th reference gene (Vandesompele et al., 2002). Similarly, the Norm Finder algorithm also identifies optimal normalization genes amongst a given set of candidates based on overall transcription variation (Andersen et al., 2004). The software provides a stability value for each gene (as a direct measure of gene transcription variation) (Andersen et al., 2004). We used eight reference genes and 10 samples for identification of the most consistently transcribed reference genes.
Section snippets
Animals
Ten mature merino ewes (between 6 months and 2 years of age) were housed in the Faculty of Veterinary and Agricultural Sciences Animal Facility, The University of Melbourne. They were kept in raised pens and fed with lucerne chaff and commercial pellets while water was provided ad libitum. All experimental procedures were approved by the Animal Ethics Committee, The University of Melbourne.
Efferent lymphatic cannulation and lymph collection
Surgery was carried out under general gas anesthesia (Isoflurane, Henry Schein Company, Melville, USA).
Results and discussion
In this study separate analyses were performed for the ovine efferent lymphatic cells and for PBMCs with and without exposure to the T cell mitogen Con A.
Conclusions
We set out to identify consistently transcribed genes that could be used as references for the normalization of RT-qPCR data for ovine efferent lymphatic cells and PBMCs. Out of the eight reference genes evaluated, PGK1, GAPDH and YWHAZ were consistently transcribed reference genes in efferent lymphatic cells. In PBMCs, PGK1, YWHAZ and SDHA were consistently transcribed, which we recommend for RT-qPCR gene transcription profiling.
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2020, Veterinary Immunology and ImmunopathologyCitation Excerpt :For optimal normalization, the use of multiple reference genes is recommended in relative quantification studies (Vandesompele et al., 2002), therefore we included five reference genes (ACTB, GAPDH, PPIA, YWHAZ and H3F3A) that are most commonly used and reported to be stable in ovine and bovine samples (Puech et al., 2015) in the panel. Specifically YWHAZ is considered to be one of the most suitable internal controls that is consistently expressed both in ovine whole blood and PBMCs, regardless of the disease status (Mahakapuge et al., 2016; Peletto et al., 2011). This observation is confirmed in our study where YWHAZ is a good reference gene to use for both ovine and bovine samples.
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