Extraction of cause-and-effect transcriptomic relationship in mammary gland tissue of dairy cattle using Bayesian network

The aim of this study was to identify regulatory genes affecting mastitis in dairy cattle using DNA microarray data. To reach this goal, the gene expression data with the largest number of arrays pertained to GPL1221 Platform with accession number GSE24560 was extracted from the GEO database. For quality control of data, ArrayQualityMetrics package and for preprocessing of data, three step function in AffyPLM, an add-in package in R environment were used. After identifying differentially expressed genes, a Tabu search algorithm was used to determine regulatory genes using bnlearn package in R environment. The results of this study revealed the causative and regulatory role for BCL2A, CCL2, S100A12, AOX1 and MGP genes on expression of other genes in mastitis of dairy cattle. Gene anthology analysis, revealed significant differences in 7 groups of molecular function, 48 groups of biological process and 11 groups of cellular components. Also, the results of the enrichment of the gene expression data set showed that most of the differentially genes expressed in this study that were significantly (P<0.05) active in metabolic pathways (GO: 0009605, GO: 0002376 and GO: 0006954) involved in response to pathogens, immune response and response to inflammation in the mammary tissue of dairy cattle.