1. Transcriptomic profiling as a screening tool to detect trenbolone treatment in beef cattle
- Author
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Luca Bargelloni, Massimo Castagnaro, Sara Pegolo, Francesca Tiziana Cannizzo, and Bartolomeo Biolatti
- Subjects
Male ,Microarray ,Anabolism ,medicine.medical_treatment ,Computational biology ,Beef cattle ,Biology ,Bioinformatics ,Polymerase Chain Reaction ,Transcriptome ,Random Allocation ,Anabolic Agents ,Trenbolone ,medicine ,Animals ,RNA, Messenger ,Muscle, Skeletal ,Oligonucleotide Array Sequence Analysis ,General Veterinary ,Body Weight ,Steroid hormone ,Genetic marker ,Cattle ,Trenbolone Acetate ,DNA microarray ,medicine.drug - Abstract
The effects of steroid hormone implants containing trenbolone alone (Finaplix-H), combined with 17β-oestradiol (17β-E; Revalor-H), or with 17β-E and dexamethasone (Revalor-H plus dexamethasone per os) on the bovine muscle transcriptome were examined by DNA-microarray. Overall, large sets of genes were shown to be modulated by the different growth promoters (GPs) and the regulated pathways and biological processes were mostly shared among the treatment groups. Using the Prediction Analysis of Microarray program, GP-treated animals were accurately identified by a small number of predictive genes. A meta-analysis approach was also carried out for the Revalor group to potentially increase the robustness of class prediction analysis. After data pre-processing, a high level of accuracy (90%) was obtained in the classification of samples, using 105 predictive gene markers. Transcriptomics could thus help in the identification of indirect biomarkers for anabolic treatment in beef cattle to be applied for the screening of muscle samples collected after slaughtering.
- Published
- 2014
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