Selection of Reference Genes in Equine White Blood Cells for Real Time PCR Normalization Following Extracorporeal Shock Wave Therapy

Abstract

Selection of proper reference genes (RGs) is an essential step needed for accurate normalization of results from genomic studies. Expression of RGs is regulated by many factors such as species, age, gender, type of tissue, the presence of disease, and the administration of therapeutic treatment. The aim of the present study was to identify optimal RGs in a set of blood samples collected at different time points (0, 24, 48, 72 h) from horses following administration of extracorporeal shock wave therapy (ESWT). The mRNA expression of twelve RGs: HPRT1, ACTB, HSP90A, SDHA, GUSB, B2M, UBC, NONO, TBP, H6PD, RPL32, GAPDH was determined using real time quantitative polymerase chain reaction (qPCR). An SAS program developed on the algorithm of geNorm, SASqPCR, was used to determine stability of the expression and the number of optimal RGs. The results showed that the range of quantification cycle (Cq) values of the evaluated genes varied between 17 and 26 cycles, and that one optimal RG, ACTB, was sufficient for normalization of gene expression. Results of stability of expression demonstrated that ACTB was the optimal choice for all the samples studied. Notably, in samples collected at 72 h post ESWT, TBP showed a significant change in the expression level, and was not suitable for use as a RG. These results substantiate the importance of validating and selecting an appropriate RG.

Share and Cite:

Jiang, Z. , Chen, J. , Uboh, C. , Robinson, M. and Soma, L. (2014) Selection of Reference Genes in Equine White Blood Cells for Real Time PCR Normalization Following Extracorporeal Shock Wave Therapy. American Journal of Molecular Biology, 4, 72-80. doi: 10.4236/ajmb.2014.42009.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Ogden, J.A., Tóth-Kischkat, A., and Schultheiss, R. (2001) Principles of Shock Wave Therapy. Clinical Orthopaedics and Related Research, 387, 8-17. http://dx.doi.org/10.1097/00003086-200106000-00003
[2] Haupt, G. (1997) Use of Extracorporeal Shock Waves in the Treatment of Pseudarthrosis, Tendinopathy and Other Orthopedic Diseases. The Journal of Urology, 58, 4-11.
[3] Furia, J.P., Rompe, J.D., Cacchio, A. and Maffulli, N. (2010) Shock Wave Therapy as a Treatment of Nonunions, Avascular Necrosis, and Delayed Healing of Stress Fractures. Foot and Ankle Clinics, 15, 651-662.
http://dx.doi.org/10.1016/j.fcl.2010.07.002
[4] Wang, C.J., Huang, H.Y. and Pai, C.H. (2002) Shock Wave-Enhanced Neovascularization at the Tendon-Bone Junction: An Experiment in Dogs. The Journal of Foot and Ankle Surgery, 41, 16-22.
http://dx.doi.org/10.1016/S1067-2516(02)80005-9
[5] Chen, Y.J., Kuo, Y.R., Yang, K.D., Wang, C.J., Sheen Chen, S.M., Huang, H.C., et al. (2004) Activation of Extracellular Signal-Regulated Kinase (ERK) and p38 Kinase in Shock Wave-Promoted Bone Formation of Segmental Defect in Rats. Bone, 34, 466-477. http://dx.doi.org/10.1016/j.bone.2003.11.013
[6] Chen, Y.J., Wang, C.J., Yang, K.D., Kuo, Y.R., Huang, H.C., Huang, Y.T., et al. (2004) Extracorporeal Shock Waves Promote Healing of Collagenase-Induced Achilles Tendinitis and Increase TGF-beta1 and IGF-I Expression. Journal of Orthopaedic Research, 22, 854-861. http://dx.doi.org/10.1016/j.orthres.2003.10.013
[7] Lee, T.C., Wang, C.J., Yang, Y.L., Huang, Y.H., Lin, W.C. and Chang, S.Y. (2010) Bone Morphogenetic Protein-2 Expression in Spinal Fusion Masses Enhanced by Extracorporeal Shock Wave Treatment: A Rabbit Experiment. Acta Neurochirurgica (Wien), 152, 1779-1784. http://dx.doi.org/10.1007/s00701-010-0744-0
[8] Ma, H.Z., Zeng, B.F. and Li, X.L. (2007) Upregulation of VEGF in Subchondral Bone of Necrotic Femoral Heads in Rabbits with Use of Extracorporeal Shock Waves. Calcified Tissue International, 81, 124-131.
http://dx.doi.org/10.1007/s00223-007-9046-9
[9] Raabe, O., Shell, K., Goessl, A., Crispens, C., Delhasse, Y., Eva, A., et al. (2013) Effect of Extracorporeal Shock Wave on Proliferation and Differentiation of Equine Adipose Tissue-Derived Mesenchymal Stem Cells in Vitro. American Journal of Stem Cells, 2, 62-73.
[10] Link, K.A., Koenig, J.B., Silveira, A., Plattner, B.L. and Lillie, B.N. (2013) Effect of Unfocused Extracorporeal Shock Wave Therapy on Growth Factor Gene Expression in Wounds and Intact skin of Horses. American Journal of Veterinary Research, 74, 324-332. http://dx.doi.org/10.2460/ajvr.74.2.324
[11] Bosch, G., De Mos, M., Van Binsbergen, R., Van Schie, H.T., Van de Lest, C.H. and Van Weeren, P.R. (2009) The Effect of Focused Extracorporeal Shock Wave Therapy on Collagen Matrix and Gene Expression in Normal Tendons and Ligaments. Equine Veterinary Journal, 41, 335-341. http://dx.doi.org/10.2746/042516409X370766
[12] Huggett, J., Dheda, K., Bustin, S. and Zumla, A. (2005) Real-Time RT-PCR Normalisation; Strategies and Considerations. Genes and Immunity, 6, 279-284. http://dx.doi.org/10.1038/sj.gene.6364190
[13] Vandesompele, J., De Preter, K., Pattyn, F., Poppe, B., Van Roy, N., De Paepe, A., et al. (2002) Accurate Normalization of Real-Time Quantitative RT-PCR Data by Geometric Averaging of Multiple Internal Control Genes. Genome Biology, 3, RESEARCH0034.
[14] Selvey, S., Thompson, E.W., Matthaei, K., Lea, R.A., Irving, M.G. and Griffiths, L.R. (2001) β-Actin—An Unsuitable Internal Control for RT-PCR. Molecular and Cellular Probes, 15, 307-311. http://dx.doi.org/10.1006/mcpr.2001.0376
[15] Lee, J.H., Fitzgerald, J.B., Dimicco, M.A. and Grodzinsky, A.J. (2005) Mechanical Injury of Cartilage Explants Causes Specific Time-Dependent Changes in Chondrocyte Gene Expression. Arthritis & Rheumatism, 52, 2386-2395.
http://dx.doi.org/10.1002/art.21215
[16] Glare, E.M., Divjak, M., Bailey, M.J. and Walters, E.H. (2002) β-Actin and GAPDH Housekeeping Gene Expression in Asthmatic Airways Is Variable and Not Suitable for Normalising mRNA Levels. Thorax, 57, 765-770.
http://dx.doi.org/10.1136/thorax.57.9.765
[17] Ohl, F., Jung, M., Xu, C., Stephan, C., Rabien, A., Burkhardt, M., et al. (2005) Gene Expression Studies in Prostate Cancer Tissue: Which Reference Gene Should Be Selected for Normalization? Journal of Molecular Medicine, 83, 1014-1024. http://dx.doi.org/10.1007/s00109-005-0703-z
[18] Jiang, Z., Uboh, C.E., Chen, J. and Soma, L.R. (2013) Isolation of RNA from Equine Peripheral Blood Cells: Comparison of Methods. SpringerPlus, 2, 478. http://dx.doi.org/10.1186/2193-1801-2-478
[19] Ling, D. (2012) SASqPCR: Robust and Rapid Analysis of RT-qPCR Data in SAS. PlosOne, 7, e29788.
http://dx.doi.org/10.1371/journal.pone.0029788
[20] Andersen, C.L., Jensen, J.L. and Orntoft, T.F. (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 Research, 64, 5245-5250.
http://dx.doi.org/10.1158/0008-5472.CAN-04-0496
[21] Pfaffl, M.W., Tichopad, A., Prgomet, C. and Neuvians, T.P. (2004) Determination of Stable Housekeeping Genes, Differentially Regulated Target Genes and Sample Integrity: BestKeeper—Excel-Based Tool Using Pair-Wise Correlations. Biotechnology Letters, 26, 509-515. http://dx.doi.org/10.1023/B:BILE.0000019559.84305.47

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.