Background Housekeeping genes have been commonly used as reference to normalize gene expression and protein content data because of its presumed constitutive expression. In this paper, we challenge the consensual idea that housekeeping genes are reliable controls for expression studies in the retina through the investigation of a panel of reference genes potentially suitable for analysis of different stages of retinal development. Methodology/Principal Findings We applied statistical tools on combinations of retinal developmental stages to assess the most stable internal controls for quantitative RT-PCR (qRT-PCR). The stability of expression of seven putative reference genes (Actb, B2m, Gapdh, Hprt1, Mapk1, Ppia and Rn18s) was analyzed using geNorm, BestKeeper and Normfinder software. In addition, several housekeeping genes were tested as loading controls for Western blot in the same sample panel, using Image J. Overall, for qRT-PCR the combination of Gapdh and Mapk1 showed the highest stability for most experimental sets. Actb was downregulated in more mature stages, while Rn18s and Hprt1 showed the highest variability. We normalized the expression of cyclin D1 using various reference genes and demonstrated that spurious results may result from blind selection of internal controls. For Western blot significant variation could be seen among four putative internal controls (β-actin, cyclophilin b, α-tubulin and lamin A/C), while MAPK1 was stably expressed. Conclusion Putative housekeeping genes exhibit significant variation in both mRNA and protein content during retinal development. Our results showed that distinct combinations of internal controls fit for each experimental set in the case of qRT-PCR and that MAPK1 is a reliable loading control for Western blot. The results indicate that biased study outcomes may follow the use of reference genes without prior validation for qRT-PCR and Western blot.
References
[1]
Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, et al. (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 3: RESEARCH0034.
[2]
Dowling JE (1987) Retinal cells and information processing. London: The Belknap Press of Harvard University Press.
[3]
Turner DL, Cepko CL (1987) A common progenitor for neurons and glia persists in rat retina late in development. Nature 328: 131–136.
Donovan SL, Dyer MA (2005) Regulation of proliferation during central nervous system development. Semin Cell Dev Biol 16: 407–421.
[6]
Higuchi R, Fockler C, Dollinger G, Watson R (1993) Kinetic PCR analysis: real-time monitoring of DNA amplification reactions. Biotechnology (N Y) 11: 1026–1030.
[7]
Pfaffl MW (2001) A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res 29: e45.
[8]
Egger D, Bienz K (1994) Protein (western) blotting. Mol Biotechnol 1: 289–305.
[9]
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: 509–515.
[10]
Liu NK, Xu XM (2006) beta-tubulin is a more suitable internal control than beta-actin in Western blot analysis of spinal cord tissues after traumatic injury. Journal of Neurotrauma 23: 1794–1801.
[11]
Santos AR, Duarte CB (2008) Validation of internal control genes for expression studies: effects of the neurotrophin BDNF on hippocampal neurons. J Neurosci Res 86: 3684–3692.
[12]
Barnhill AE, Hecker LA, Kohutyuk O, Buss JE, Honavar VG, et al. (2010) Characterization of the retinal proteome during rod photoreceptor genesis. BMC Res Notes 3: 25.
[13]
Bustin SA (2000) Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays. Journal of Molecular Endocrinology 25: 169–193.
[14]
Goidin D, Mamessier A, Staquet MJ, Schmitt D, Berthier-Vergnes O (2001) Ribosomal 18S RNA prevails over glyceraldehyde-3-phosphate dehydrogenase and beta-actin genes as internal standard for quantitative comparison of mRNA levels in invasive and noninvasive human melanoma cell subpopulations. Analytical Biochemistry 295: 17–21.
[15]
Glare EM, Divjak M, Bailey MJ, Walters EH (2002) beta-Actin and GAPDH housekeeping gene expression in asthmatic airways is variable and not suitable for normalising mRNA levels. Thorax 57: 765–770.
[16]
Schmittgen TD, Zakrajsek BA (2000) Effect of experimental treatment on housekeeping gene expression: validation by real-time, quantitative RT-PCR. J Biochem Biophys Methods 46: 69–81.
[17]
Zhu LJ, Altmann SW (2005) mRNA and 18S-RNA coapplication-reverse transcription for quantitative gene expression analysis. Anal Biochem 345: 102–109.
[18]
Sindelka R, Ferjentsik Z, Jonak J (2006) Developmental expression profiles of Xenopus laevis reference genes. Dev Dyn 235: 754–758.
[19]
Sindelka R, Jonak J, Hands R, Bustin SA, Kubista M (2008) Intracellular expression profiles measured by real-time PCR tomography in the Xenopus laevis oocyte. Nucleic Acids Res 36: 387–392.
[20]
Derveaux S, Vandesompele J, Hellemans J (2010) How to do successful gene expression analysis using real-time PCR. Methods 50: 227–230.
[21]
Everaert BR, Boulet GA, Timmermans JP, Vrints CJ (2011) Importance of suitable reference gene selection for quantitative real-time PCR: special reference to mouse myocardial infarction studies. PLoS One 6: e23793.
[22]
Thorrez L, Van Deun K, Tranchevent LC, Van Lommel L, Engelen K, et al. (2008) Using ribosomal protein genes as reference: a tale of caution. PLoS One 3: e1854.
[23]
Artico S, Nardeli SM, Brilhante O, Grossi-de-Sa MF, Alves-Ferreira M (2010) Identification and evaluation of new reference genes in Gossypium hirsutum for accurate normalization of real-time quantitative RT-PCR data. BMC Plant Biol 10: 49.
[24]
Matta BP, Bitner-Mathe BC, Alves-Ferreira M (2011) Getting real with real-time qPCR: a case study of reference gene selection for morphological variation in Drosophila melanogaster wings. Dev Genes Evol 221: 49–57.
[25]
Andersen CL, Jensen JL, Orntoft TF (2004) Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer Res 64: 5245–5250.
[26]
Martins RA, Zindy F, Donovan S, Zhang J, Pounds S, et al. (2008) N-myc coordinates retinal growth with eye size during mouse development. Genes Dev 22: 179–193.
[27]
Njaine B, Martins RA, Santiago MF, Linden R, Silveira MS (2010) Pituitary adenylyl cyclase-activating polypeptide controls the proliferation of retinal progenitor cells through downregulation of cyclin D1. Eur J Neurosci 32: 311–321.
[28]
McNeill B, Perez-Iratxeta C, Mazerolle C, Furimsky M, Mishina Y, et al. (2012) Comparative genomics identification of a novel set of temporally regulated hedgehog target genes in the retina. Mol Cell Neurosci 49: 333–340.
[29]
Seol D, Choe H, Zheng H, Jang K, Ramakrishnan PS, et al. (2011) Selection of reference genes for normalization of quantitative real-time PCR in organ culture of the rat and rabbit intervertebral disc. BMC Res Notes 4: 162.
[30]
Dydensborg AB, Herring E, Auclair J, Tremblay E, Beaulieu JF (2006) Normalizing genes for quantitative RT-PCR in differentiating human intestinal epithelial cells and adenocarcinomas of the colon. Am J Physiol Gastrointest Liver Physiol 290: G1067–1074.
[31]
Petrs-Silva H, de Freitas FG, Linden R, Chiarini LB (2004) Early nuclear exclusion of the transcription factor max is associated with retinal ganglion cell death independent of caspase activity. J Cell Physiol 198: 179–187.
[32]
Spinsanti G, Panti C, Lazzeri E, Marsili L, Casini S, et al. (2006) Selection of reference genes for quantitative RT-PCR studies in striped dolphin (Stenella coeruleoalba) skin biopsies. Bmc Molecular Biology 7.
[33]
Ayers D, Clements DN, Salway F, Day PJ (2007) Expression stability of commonly used reference genes in canine articular connective tissues. BMC Vet Res 3: 7.
[34]
Woo CJ, Kharchenko PV, Daheron L, Park PJ, Kingston RE (2010) A region of the human HOXD cluster that confers polycomb-group responsiveness. Cell 140: 99–110.
[35]
Liu Y, Wen JK, Dong LH, Zheng B, Han M (2010) Kruppel-like factor (KLF) 5 mediates cyclin D1 expression and cell proliferation via interaction with c-Jun in Ang II-induced VSMCs. Acta Pharmacol Sin 31: 10–18.
[36]
Donovan SL, Schweers B, Martins R, Johnson D, Dyer MA (2006) Compensation by tumor suppressor genes during retinal development in mice and humans. BMC Biol 4: 14.
[37]
Luo Y, Xiao W, Zhu X, Mao Y, Liu X, et al. (2011) Differential expression of claudins in retinas during normal development and the angiogenesis of oxygen-induced retinopathy. Invest Ophthalmol Vis Sci 52: 7556–7564.
[38]
van Wijngaarden P, Brereton HM, Coster DJ, Williams KA (2007) Stability of housekeeping gene expression in the rat retina during exposure to cyclic hyperoxia. Mol Vis 13: 1508–1515.
[39]
Dijk F, van Leeuwen S, Kamphuis W (2004) Differential effects of ischemia/reperfusion on amacrine cell subtype-specific transcript levels in the rat retina. Brain Res 1026: 194–204.
Mafra V, Kubo KS, Alves-Ferreira M, Ribeiro-Alves M, Stuart RM, et al. (2012) Reference genes for accurate transcript normalization in citrus genotypes under different experimental conditions. PLoS One 7: e31263.
[42]
Marum L, Miguel A, Ricardo CP, Miguel C (2012) Reference Gene Selection for Quantitative Real-time PCR Normalization in Quercus suber. PLoS One 7: e35113.
[43]
Silveira ED, Alves-Ferreira M, Guimaraes LA, da Silva FR, Carneiro VT (2009) Selection of reference genes for quantitative real-time PCR expression studies in the apomictic and sexual grass Brachiaria brizantha. BMC Plant Biol 9: 84.
[44]
Bacchetti De Gregoris T, Borra M, Biffali E, Bekel T, Burgess JG, et al. (2009) Construction of an adult barnacle (Balanus amphitrite) cDNA library and selection of reference genes for quantitative RT-PCR studies. BMC Mol Biol 10: 62.
[45]
Wang Y, Yu K, Poysa V, Shi C, Zhou Y (2012) Selection of reference genes for normalization of qRT-PCR analysis of differentially expressed genes in soybean exposed to cadmium. Mol Biol Rep 39: 1585–1594.
[46]
Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 25: 402–408.
[47]
Hellemans J, Mortier G, De Paepe A, Speleman F, Vandesompele J (2007) qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data. Genome Biol 8: R19.
[48]
Lowry OH, Rosebrough NJ, Farr AL, Randall RJ (1951) Protein measurement with the Folin phenol reagent. J Biol Chem 193: 265–275.
