Evaluating the applicability of mouse SINEs as an alternative normalization approach for RT-qPCR in brain tissue of the APP23 model for Alzheimer's disease

Jana Janssens, Rene A. J. Crans, Kathleen Van Craenenbroeck, Jo Vandesompele, Christophe P. Stove, Debby Van Dam*, Peter P. De Deyn

*Bijbehorende auteur voor dit werk

OnderzoeksoutputAcademicpeer review

5 Citaten (Scopus)
157 Downloads (Pure)


Background: The choice of appropriate reference genes (RGs) for use in reverse transcription quantitative polymerase chain reaction (RT-qPCR) has been thoroughly investigated, since the inclusion of unstable RGs might cause inaccurate gene expression results.

New method: Short interspersed nuclear elements (SINEs) such as B elements, might represent an alternative solution given the high occurrence of these repetitive elements in the rodent genome and transcriptome. We performed RT-qPCR to investigate the stability of nine commonly used RGs and two B elements, B1 and B2, across different age- and genotype-related experimental conditions in the hippocampus and cortex of the APP23 amyloidosis mouse model for Alzheimer's disease. Gene stability was assessed using geNorm, NormFinder and BestKeeper. Human amyloid precursor protein (APP) levels in transgenic versus wild-type animals were also determined to validate the use of B elements as an alternative normalization approach.

Results: Whereas B elements were stably expressed in the hippocampus, they were ranked as least stable in the cortex. The optimal normalization factor (NF) in hippocampus was a combination of Gapdh and Rpl13a, whereas in cortex, Actb and Tbp constituted the ideal NF.

Comparison with existing method: When comparing B1 and B2 as NFs for APP with the optimal panel of RGs in hippocampus, we found that B1 and B2 performed similarly to the optimal NF, while these SINEs performed less well in cortex.

Conclusions: Although B elements are suitable as an alternative normalization strategy in the hippocampus, they do not represent a universal normalization approach in the APP23 model.

Originele taal-2English
Pagina's (van-tot)128-137
Aantal pagina's10
TijdschriftJournal of Neuroscience Methods
StatusPublished - 15-mei-2019

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