Meta-analysis of transcriptomic data of mammary gland infected by Escherichia coli Bacteria in dairy cows

Document Type : Research Paper


1 Ph. D. Candidate, Faculty of Agriculture, Isfahan University of Technology, Isfahan, Iran

2 Associate Professor, Faculty of Agriculture, Isfahan University of Technology, Isfahan, Iran

3 Associate Professor, Institute of Biotechnology, Shiraz Univeristy, Shiraz, Iran, and School of Biological Science, Faculty of Science and Engineering, Flinders University of Adelaide, Australia


Identification of disease-causing genes that underlie complex traits such as susceptibility to disease not only can improve diagnosis and the prevention of illness, but also help breeder to select resistance animals against diseases. In the current study to aim the higher power of statistical analysis to identification of genes and biological pathways related to mastitis disease, we used Fisher meta-analysis to combine p-values obtained from individual analysis of datasets extracted from 6 microarray-based studies which investigate transcriptomic data of mammary gland tissue infected by Escherichia coli (E. coli) in dairy cows. Identification of genes that did not show a significant p-value in any of the independent studies may confirm the aim and lead to introduce a more complete set of biological pathways involved in this disease such as the pathways related to immune response, inflammation, proteolysis, growth, and death of cell. Positive regulation of transcription from RNA polymerase II promoter, is new pathways related to this disease which despite of the enrichment by maximum number of up-regulated genes in this study, have not been reported in previous mastitis studies.


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