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Journal of Molecular Neuroscience

, Volume 64, Issue 3, pp 431–439 | Cite as

Analysis of Housekeeping Genes for Accurate Normalization of qPCR Data During Early Postnatal Brain Development

  • V. A. Shaydurov
  • A. Kasianov
  • A. P. Bolshakov
Article

Abstract

Maturation of the neocortex during the first three postnatal weeks is a complex process that is characterized by different time courses of maturation of different areas of the neocortex. Analysis of gene expression using quantitative PCR after reverse transcription during this period of ontogeny and comparison of different cortical areas require optimal selection of reference genes for correct normalization of the data. Here, we compared expression of nine reference genes in the somatosensory and visual areas of the neocortex at the age of 5, 8, 10, 13, and 20 days. Using widely used GeNorm and NormFinder applications, as well as a novel approach, we compared stability of expression of GAPDH, YWHAZ, TFR1, RPS18, Rn18S, HPRT1, KIF5C, OSBP, and UQCRFS1. We found that, in both neocortical areas studied, YWHAZ and UQCRFS1 are the best reference genes whereas GAPDH and TFR1 are also stably expressed in the somatosensory cortex and OSBP is stable in the visual cortex. Additionally, analysis of stability of expression of these genes by a novel approach showed that the expression of these genes is stable during the entire period from the 5th to the 20th postnatal days.

Keywords

qPCR Neocortex Normalization Neurons Reference genes 

Notes

Funding Information

This study was supported by the Russian Foundation for Basic Research, project no. 15-04-06115-a.

Compliance with Ethical Standards

All experiments were conducted in accordance with the guidelines of the animal ethics committee of the Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences following the Directive 2010/63/EU of the European Parliament and the EU Council from Sept. 22, 2010.

References

  1. Ahmad Y, Sharma NK, Ahmad MF, Sharma M, Garg I, Srivastava M, Bhargava K (2015) The proteome of hypobaric induced hypoxic lung: insights from temporal proteomic profiling for biomarker discovery. Sci Rep 5:10681.  https://doi.org/10.1038/srep10681 CrossRefPubMedPubMedCentralGoogle Scholar
  2. Andersen C, Jensen J, Orntoft T (2004) Normalization of real­time quantitative reverse transcription­PCR data: a model­based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer Res 64:5245–5250.  https://doi.org/10.1158/0008 CrossRefPubMedGoogle Scholar
  3. Cholfin JA, Rubenstein JLR (2008) Frontal cortex subdivision patterning is coordinately regulated by Fgf8, Fgf17, and Emx2. J Comp Neurol 509:144–155.  https://doi.org/10.1002/cne.21709 CrossRefPubMedPubMedCentralGoogle Scholar
  4. Colonnese MT, Kaminska A, Minlebaev M, Milh M, Bloem B, Lescure S, Moriette G, Chiron C, Ben-Ari Y, Khazipov R (2010) A conserved switch in sensory processing prepares developing neocortex for vision. Neuron 67:480–498.  https://doi.org/10.1016/j.neuron.2010.07.015 CrossRefPubMedPubMedCentralGoogle Scholar
  5. Dillman AA, Hauser DN, Gibbs JR, Nalls MA, McCoy MK, Rudenko IN, Galter D, Cookson MR (2013) mRNA expression, splicing and editing in the embryonic and adult mouse cerebral cortex. Nat Neurosci 16:499–506.  https://doi.org/10.1038/nn.3332 CrossRefPubMedPubMedCentralGoogle Scholar
  6. Han D, Lerner AG, Vande Walle L, Upton JP, Xu W, Hagen A, Backes BJ, Oakes SA, Papa FR (2009) IRE1alpha kinase activation modes control alternate endoribonuclease outputs to determine divergent cell fates. Cell 138:562–575.  https://doi.org/10.1016/j.cell.2009.07.017 CrossRefPubMedPubMedCentralGoogle Scholar
  7. Khazipov R, Minlebaev M, Valeeva G (2013) Early gamma oscillations. Neuroscience 250:240–252.  https://doi.org/10.1016/j.neuroscience.2013.07.019 CrossRefPubMedGoogle Scholar
  8. Kroeze Y, Oti M, Beusekom E Van, et al (2017) Transcriptome analysis identifies multifaceted regulatory mechanisms dictating a genetic switch from neuronal network establishment to maintenance during postnatal prefrontal cortex development. 1–19. doi:  https://doi.org/10.1093/cercor/bhw407
  9. Peregud DI, Panchenko LF, Gulyaeva NV (2015) Elevation of BDNF exon I-specific transcripts in the frontal cortex and midbrain of rat during spontaneous morphine withdrawal is accompanied by enhanced pCreb1 occupancy at the corresponding promoter. Neurochem Res 40:130–138.  https://doi.org/10.1007/s11064-014-1476-y CrossRefPubMedGoogle Scholar
  10. Pfaffl MW, Tichopad A, Prgomet C, Neuvians TP (2004) Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper—Excel-based tool using pair-wise correlations. Biotechnol Lett 26:509–515CrossRefPubMedGoogle Scholar
  11. Sheikh N, Dudas J, Ramadori G (2007) Changes of gene expression of iron regulatory proteins during turpentine oil-induced acute-phase response in the rat. Lab Investig 87:713–725.  https://doi.org/10.1038/labinvest.3700553 CrossRefPubMedGoogle Scholar
  12. Vandesompele J, Preter K, De PB et al (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control. genes:1–12Google Scholar
  13. Wang Y, Li Y, Toth JI, Petroski MD, Zhang Z, Zhao JC (2014) N6-methyladenosine modification destabilizes developmental regulators in embryonic stem cells. Nat Cell Biol 16:191–198CrossRefPubMedPubMedCentralGoogle Scholar
  14. Zhang Y, Chen K, Sloan SA, Bennett ML, Scholze AR, O’Keeffe S, Phatnani HP, Guarnieri P, Caneda C, Ruderisch N, Deng S, Liddelow SA, Zhang C, Daneman R, Maniatis T, Barres BA, Wu JQ (2014) An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex. J Neurosci 34:11929–11947.  https://doi.org/10.1523/JNEUROSCI.1860-14.2014 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • V. A. Shaydurov
    • 1
    • 2
  • A. Kasianov
    • 3
  • A. P. Bolshakov
    • 1
    • 2
  1. 1.Institute of Higher Nervous Activity and NeurophysiologyRussian Academy of SciencesMoscowRussia
  2. 2.Pirogov Russian National Research Medical UniversityMoscowRussia
  3. 3.Koltsov Institute of General GeneticsRussian Academy of SciencesMoscowRussia

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