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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

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Abstract
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.
Keywords
Reference genes, B elements, APP, C5781//6J, DNA METHYLATION, REFERENCE GENES, GENOME SEQUENCE, ALU SEQUENCES, PCR DATA, RNA, TRANSCRIPTION, SELECTION, MICE, QUANTIFICATION

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MLA
Janssens, Jana et al. “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.” JOURNAL OF NEUROSCIENCE METHODS 320 (2019): 128–137. Print.
APA
Janssens, Jana, Crans, R., Van Craenenbroeck, K., Vandesompele, J., Stove, C., Van Dam, D., & De Deyn, P. P. (2019). 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. JOURNAL OF NEUROSCIENCE METHODS, 320, 128–137.
Chicago author-date
Janssens, Jana, René Crans, Kathleen Van Craenenbroeck, Jo Vandesompele, Christophe Stove, Debby Van Dam, and Peter P. De Deyn. 2019. “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.” Journal of Neuroscience Methods 320: 128–137.
Chicago author-date (all authors)
Janssens, Jana, René Crans, Kathleen Van Craenenbroeck, Jo Vandesompele, Christophe Stove, Debby Van Dam, and Peter P. De Deyn. 2019. “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.” Journal of Neuroscience Methods 320: 128–137.
Vancouver
1.
Janssens J, Crans R, Van Craenenbroeck K, Vandesompele J, Stove C, Van Dam D, et al. 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. JOURNAL OF NEUROSCIENCE METHODS. 2019;320:128–37.
IEEE
[1]
J. Janssens et al., “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,” JOURNAL OF NEUROSCIENCE METHODS, vol. 320, pp. 128–137, 2019.
@article{8616636,
  abstract     = {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.},
  author       = {Janssens, Jana and Crans, René and Van Craenenbroeck, Kathleen and Vandesompele, Jo and Stove, Christophe and Van Dam, Debby and De Deyn, Peter P.},
  issn         = {0165-0270},
  journal      = {JOURNAL OF NEUROSCIENCE METHODS},
  keywords     = {Reference genes,B elements,APP,C5781//6J,DNA METHYLATION,REFERENCE GENES,GENOME SEQUENCE,ALU SEQUENCES,PCR DATA,RNA,TRANSCRIPTION,SELECTION,MICE,QUANTIFICATION},
  language     = {eng},
  pages        = {128--137},
  title        = {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},
  url          = {http://dx.doi.org/10.1016/j.jneumeth.2019.03.005},
  volume       = {320},
  year         = {2019},
}

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