Expressed repetitive elements are broadly applicable reference targets for normalization of reverse transcription-qPCR data in mice.
Marjolijn Renard, Suzanne Vanhauwaert, Marine Vanhomwegen, Ali Rihani, Niels Vandamme, Steven Goossens, Geert Berx, Pieter Van Vlierberghe, Jody J Haigh, Bieke Decaesteker, Jolien Van Laere, Irina Lambertz, Frank Speleman, Jo Vandesompele, Andy Willaert
Author Information
Marjolijn Renard: Center for Medical Genetics, Ghent University, Ghent, Belgium.
Suzanne Vanhauwaert: Center for Medical Genetics, Ghent University, Ghent, Belgium.
Marine Vanhomwegen: Center for Medical Genetics, Ghent University, Ghent, Belgium.
Ali Rihani: Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden. ORCID
Niels Vandamme: Molecular and Cellular Oncology Lab, Inflammation Research Center, VIB, Ghent, Belgium.
Steven Goossens: Center for Medical Genetics, Ghent University, Ghent, Belgium.
Geert Berx: Molecular and Cellular Oncology Lab, Inflammation Research Center, VIB, Ghent, Belgium.
Pieter Van Vlierberghe: Center for Medical Genetics, Ghent University, Ghent, Belgium. ORCID
Jody J Haigh: Mammalian Functional Genetics Group, Australian Centre for Blood Diseases, Monash University, Melbourne, Australia.
Bieke Decaesteker: Center for Medical Genetics, Ghent University, Ghent, Belgium.
Jolien Van Laere: Center for Medical Genetics, Ghent University, Ghent, Belgium.
Irina Lambertz: Center for Medical Genetics, Ghent University, Ghent, Belgium.
Frank Speleman: Center for Medical Genetics, Ghent University, Ghent, Belgium.
Jo Vandesompele: Center for Medical Genetics, Ghent University, Ghent, Belgium. ORCID
Andy Willaert: Center for Medical Genetics, Ghent University, Ghent, Belgium. andy.willaert@ugent.be.
Reverse transcription quantitative PCR (RT-qPCR) is the gold standard method for gene expression analysis on mRNA level. To remove experimental variation, expression levels of the gene of interest are typically normalized to the expression level of stably expressed endogenous reference genes. Identifying suitable reference genes and determining the optimal number of reference genes should precede each quantification study. Popular reference genes are not necessarily stably expressed in the examined conditions, possibly leading to inaccurate results. Stably and universally expressed repetitive elements (ERE) have previously been shown to be an excellent alternative for normalization using classic reference genes in human and zebrafish samples. Here, we confirm that in mouse tissues, EREs are broadly applicable reference targets for RT-qPCR normalization, provided that the RNA samples undergo a thorough DNase treatment. We identified Orr1a0, Rltr2aiap, and Rltr13a3 as the most stably expressed mouse EREs across six different experimental conditions. Therefore, we propose this set of ERE reference targets as good candidates for normalization of RT-qPCR data in a plethora of conditions. The identification of widely applicable stable mouse RT-qPCR reference targets for normalization has great potential to facilitate future murine gene expression studies and improve the validity of RT-qPCR data.
