Transcriptomic analysis of skeletal muscle from beef cattle exposed to illicit schedules containing dexamethasone: identification of new candidates and their comparison with proteomics data and samples from field monitoring.

INTRODUCTION Growth promoters (GPs) such as dexamethasone (DEX) and clenbuterol (CLEN), are still abusively used in beef cattle production. Transcriptomic markers for indirect detection of such GPs have been discussed either in experimentally treated animals or commercial samples, separately. In the present study, we examined the transcriptomic signature of DEX alone or in combination with CLEN in skeletal muscle of experimentally treated beef cattle; furthermore, we compared them to previously screened commercial samples from a field-monitoring study (Pegolo et al., 2012), as well as to a proteomics data coming from the same animals (Stella et al., 2011). MATERIALS AND METHODS Using DNA microarray technology, a transcriptomic profiling was performed on 12 samples representing 3 groups of animals: DEX (0.75 mg per animal per day, n = 4), a combination of DEX (0.66 mg per animal per day) and CLEN (from 2 to 6 mg per animal per day, n = 4) and a control group (n = 4). Microarray data were normalized and analyzed by means of open access softwares, i.e: ‘R’, Significant Analysis of Microarray (SAM) and TIGR Multiple Array Viewer (TMEV). Ingenuity Pathway Analysis (IPA) was performed on the list of differentially expressed genes (DEGs), followed by an intensive literature screening for choosing some potential biomarkers. Target genes were validated by qPCR. Finally, all samples processed in this study (n = 12) and/or samples from the field monitoring study (n = 30) were visualized using the Principal Component Analysis (PCA). RESULTS AND CONCLUSIONS The analyses identified 198 and 39 DEGs in DEX and DEXCLEN groups, respectively. Both groups had no common modulated genes in-between, neither with the corresponding proteomics data. Sixteen candidate genes were validated via qPCR, and showed a high correlation with their corresponding microarray data. The PCA executed on qPCR and normalized microarray data resulted in separation of treated animals from untreated ones. Interestingly, all the PCA plots grouped the DEX positive samples (experimental or commercial) apart from each other’s. In brief, our study provided some interesting glucocorticoid-responsive biomarkers, whose expression was contradictory to what is reported in human studies. Additionally, we pointed out a dissimilarity in the transcriptomic signature between commercial and experimentally treated animals. ACKNOWLEDGEMENTS Project supported by Regione del Veneto (DGR 2862, 20.12.2012).