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.
Highlights
Extracorporeal Shock Wave Therapy (ESWT) has been used for treatment of a wide variety of bone and tendon injuries
It was reported that ESWT increased Cx43 expression in in-vitro mesenchymal stem cells [9], suppressed TGF-β1 and increased IGF-1 expression in surgically created wounds [10]
To date, there is no report on the effects of ESWT on the equine white blood cell (WBC) transcript-ome
Summary
Extracorporeal Shock Wave Therapy (ESWT) has been used for treatment of a wide variety of bone and tendon injuries. To date, there is no report on the effects of ESWT on the equine white blood cell (WBC) transcript-ome. To investigate the effect of ESWT on this transcriptome, a microarray platform was chosen to determine the transcriptome profile in equine WBC before and after ESWT. For this reason a number of potential candidate genes with significant changes in expression were screened for and validated using real time qPCR
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