Pegolo S, Cannizzo F T, Biolatti B, Castagnaro M, Bargelloni L
Department of Comparative Biomedicine and Food Science, University of Padua, Viale dell'Università 16, 35020 Legnaro, Padova, Italy.
Department of Animal Pathology, University of Turin, via L. da Vinci 44, 10095, Grugliasco, Italy.
Res Vet Sci. 2014 Jun;96(3):472-81. doi: 10.1016/j.rvsc.2014.03.020. Epub 2014 Apr 2.
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.
通过DNA微阵列研究了单独含有群勃龙的类固醇激素植入物(法尼普利-H)、与17β-雌二醇联合使用(17β-E;瑞瓦洛尔-H)或与17β-E和地塞米松联合使用(瑞瓦洛尔-H加口服地塞米松)对牛肌肉转录组的影响。总体而言,大量基因被证明受不同生长促进剂(GPs)调控,且调控途径和生物学过程在各治疗组中大多相同。使用微阵列预测分析程序,通过少量预测基因可准确识别接受GP治疗的动物。还对瑞瓦洛尔组进行了荟萃分析,以潜在提高分类预测分析的稳健性。数据预处理后,使用105个预测基因标记对样本进行分类,准确率高达90%。因此,转录组学有助于识别肉牛合成代谢治疗的间接生物标志物,用于筛选屠宰后采集的肌肉样本。