期刊论文详细信息
BMC Research Notes
Bone to pick: the importance of evaluating reference genes for RT-qPCR quantification of gene expression in craniosynostosis and bone-related tissues and cells
Barry C Powell1  Peter J Anderson1  Xiongzheng Mu2  Susan J Hinze3  Jodie T Hatfield3  Xianxian Yang3 
[1] Discipline of Paediatrics, University of Adelaide, Adelaide, Australia;Department of Plastic and Reconstructive Surgery, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China;Women’s and Children’s Health Research Institute, Adelaide, Australia
关键词: Mineralization;    Bone;    Craniosynostosis;    Normfinder;    geNorm;    β-actin;    Gapdh;    18 S RNA;    Alkaline phosphatase;    Osteocalcin;   
Others  :  1166451
DOI  :  10.1186/1756-0500-5-222
 received in 2011-12-19, accepted in 2012-04-05,  发布年份 2012
PDF
【 摘 要 】

Background

RT-qPCR is a common tool for quantification of gene expression, but its accuracy is dependent on the choice and stability (steady state expression levels) of the reference gene/s used for normalization. To date, in the bone field, there have been few studies to determine the most stable reference genes and, usually, RT-qPCR data is normalised to non-validated reference genes, most commonly GAPDH, ACTB and 18 S rRNA. Here we draw attention to the potential deleterious impact of using classical reference genes to normalise expression data for bone studies without prior validation of their stability.

Results

Using the geNorm and Normfinder programs, panels of mouse and human genes were assessed for their stability under three different experimental conditions: 1) disease progression of Crouzon syndrome (craniosynostosis) in a mouse model, 2) proliferative culture of cranial suture cells isolated from craniosynostosis patients and 3) osteogenesis of a mouse bone marrow stromal cell line. We demonstrate that classical reference genes are not always the most ‘stable’ genes and that gene ‘stability’ is highly dependent on experimental conditions. Selected stable genes, individually or in combination, were then used to normalise osteocalcin and alkaline phosphatase gene expression data during cranial suture fusion in the craniosynostosis mouse model and strategies compared. Strikingly, the expression trends of alkaline phosphatase and osteocalcin varied significantly when normalised to the least stable, the most stable or the three most stable genes.

Conclusion

To minimise errors in evaluating gene expression levels, analysis of a reference panel and subsequent normalization to several stable genes is strongly recommended over normalization to a single gene. In particular, we conclude that use of single, non-validated “housekeeping” genes such as GAPDH, ACTB and 18 S rRNA, currently a widespread practice by researchers in the bone field, is likely to produce data of questionable reliability when changes are 2 fold or less, and such data should be interpreted with due caution.

【 授权许可】

   
2012 Yang et al.; licensee BioMed Central Ltd.

【 预 览 】
附件列表
Files Size Format View
20150416044744393.pdf 336KB PDF download
Figure 1. 40KB Image download
【 图 表 】

Figure 1.

【 参考文献 】
  • [1]Bustin SA, Nolan T: Data analysis and interpretation. In In A-Z of Quantitative PCR. Edited by Bustin SA. CA, USA: International University Line, La Jolla; 2004:441-492.
  • [2]Bustin SA, Benes V, Garson JA, Hellemans J, Huggett J, Kubista M, Mueller R, Nolan T, Pfaffl MW, Shipley GL, et al.: The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin Chem 2009, 55:611-622.
  • [3]Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F: Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 2002., 3RESEARCH0034
  • [4]Andersen CL, Jensen JL, Torben FO: 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 2004, 64:5245-5250.
  • [5]Yousfi M, Lasmoles F, Lomri A, Delannoy P, Marie PJ: Increased bone formation and decreased osteocalcin expression induced by reduced Twist dosage in Saethre-Chotzen syndrome. J Clin Invest 2001, 107:1153-1161.
  • [6]Nakamura A, Dohi Y, Akahane M, Ohgushi H, Nakajima H, Funaoka H, Takakura Y: Osteocalcin secretion as an early marker of in vitro osteogenic differentiation of rat mesenchymal stem cells. Tissue Eng Part C Methods 2009, 15:169-180.
  • [7]Braga V, Gatti D, Rossini M, Colapietro F, Battaglia E, Viapiana O, Adami S: Bone turnover markers in patients with osteogenesis imperfecta. Bone 2004, 34:1013-1016.
  • [8]Huang C, Lee C, Chen M, Tsai H, Hsu H, Tang C: Adiponectin increases BMP-2 expression in osteoblasts via adipoR receptor signaling pathway. J Cell Physiol 2010, 224:475-486.
  • [9]De Pollack C, Renier D, Hott M, Marie PJ: Increased bone formation and osteoblastic cell phenotype in premature cranial suture ossification (craniosynostosis). J Bone Miner Res 1996, 11:401-407.
  • [10]Eswarakumar VP, Horowitz MC, Locklin R, Morriss-Kay GM, Lonai P: A gain-of-function mutation of Fgfr2c demonstrates the roles of this receptor variant in osteogenesis. Proc Natl Acad Sci U S A 2004, 101:12555-12560.
  • [11]Hellemans J, Mortier G, De Paepe A, Speleman F, Vandesompele J: qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data. Genome Biol 2007, 8:R19. BioMed Central Full Text
  • [12]Di S, Tian Z, Qian A, Gao X, Yu D, Brandi ML, Shang P: Selection of suitable reference genes from bone cells in large gradient high magnetic field based on geNorm algorithm. Electromagn Biol Med 2011, 30:261-269.
  • [13]Rho HW, Lee BC, Choi ES, Choi IJ, Lee YS, Goh SH: Identification of valid reference genes for gene expression studies of human stomach cancer by reverse transcription-qPCR. BMC Cancer 2010, 10:240. BioMed Central Full Text
  • [14]Tatsumi K, Ohashi K, Taminishi S, Okano T, Yoshioka A, Shima M: Reference gene selection for real-time RT-PCR in regenerating mouse livers. Biochem Biophys Res Commun 2008, 374:106-110.
  • [15]Piehler AP, Grimholt RM, Ovstebo R, Berg JP: Gene expression results in lipopolysaccharide-stimulated monocytes depend significantly on the choice of reference genes. BMC Immunol 2010, 11:21. BioMed Central Full Text
  • [16]Sorby LA, Andersen SN, Bukholm IR, Jacobsen MB: Evaluation of suitable reference genes for normalization of real-time reverse transcription PCR analysis in colon cancer. J Exp Clin Cancer Res 2010, 29:144. BioMed Central Full Text
  • [17]Caradec J, Sirab N, Keumeugni C, Moutereau S, Chimingqi M, Matar C, Revaud D, Bah M, Manivet P, Conti M, Loric S: 'Desperate house genes': the dramatic example of hypoxia. Br J Cancer 2010, 102:1037-1043.
  • [18]Pfaffl MW, Tichopad A, Prgomet C, Neuvians TP: Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper–Excel-based tool using pair-wise correlations. Biotechnol Lett 2004, 26:509-515.
  • [19]Hruz T, Wyss M, Docquier M, Pfaffl MW, Masanetz S, Borghi L, Verbrugge P, Kalaydjieva L, Bleuler S, Laule O, et al.: RefGenes: identification of reliable and condition specific reference genes for RT-qPCR data normalization. BMC Genomics 2011, 12:156. BioMed Central Full Text
  • [20]Anderson PJ, Cox TC, Roscioli T, Elakis G, Smithers L, David DJ, Powell B: Somatic FGFR and TWIST mutations are not a common cause of isolated nonsyndromic single suture craniosynostosis. J Craniofac Surg 2007, 18:312-314.
  • [21]Coussens AK, Hughes IP, Wilkinson CR, Morris CP, Anderson PJ, Powell BC, van Daal A: Identification of genes differentially expressed by prematurely fused human sutures using a novel in vivo - in vitro approach. Differentiation 2008, 76:531-545.
  • [22]Allan EH, Ho PW, Umezawa A, Hata J, Makishima F, Gillespie MT, Martin TJ: Differentiation potential of a mouse bone marrow stromal cell line. J Cell Biochem 2003, 90:158-169.
  文献评价指标  
  下载次数:18次 浏览次数:32次