Bovine mastitis is a widespread disease in dairy cows, and is often caused by bacterial mammary gland infection. Reduced milk production, reduced milk quality, additional labor costs, increased cattle replacement rates, veterinary costs, and treatment costs all strengthen the importance of effective disease control. In this study to uncover the genes involved in the development of mastitis, was performed a meta-analysis using publicly available GEO microarray datasets (GSE15019, GSE24217, GSE24560, GSE25413 and GSE50685). The datasets were processed using the metaDE package in R language was used to do meta-analysis. In this way, Fisher's exact test was used. Next, clustering analysis was performed to detect the distinguishing effect of metaDE on differential expression in different sample groups. The threshold for DEGs was set at a false discovery rate (FDR) of <0.01 to statistically screen out significant difference between gene expressions. The results of DNA microarray meta-analysis shown that a total of 32 genes were identified to be differentially expressed (P <0.01) across GEO datasets. In this study EST-based homology search is applied to find potential miRNA in bovine mastitis. For blast between EST & microRNA, Blastn program version 2.3.1 was used to predict miRNA target. In this study, 940 miRNAs were predicted from 32 genes were identified to be differentially expressed by using a bioinformatics-based gene search. The results of the analysis of miRNAs showed that mRNAs bta-mir-1777b, bta-mir-1777a, bta-mir-2382-3p, bta-mir-2382-5p, bta-mir-671, bta-mir-2888 and bta-mir-370 have the highest frequency. These miRNAs have the most effect on mastitis through the four cell signaling pathways Toll-like receptor signaling pathway, pathway in cancer, Estrogen signaling pathway and Progesterone-mediated oocyte maturation (Diagram 2-5). These miRNAs result in this pathway through cell cycle processes, DNA repair and cell proliferation, glycolysis, gluconeogenesis,
