Mining for the association of bovine mastitis linked genes to pathological signatures and pathways

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Khan M. Z., Belhan S., Çetin N., Ayan A., Khan A., Ahmad I., ...More

Annals of Animal Science, vol.22, no.2, pp.583-591, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 22 Issue: 2
  • Publication Date: 2022
  • Doi Number: 10.2478/aoas-2021-0049
  • Journal Name: Annals of Animal Science
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Agricultural & Environmental Science Database, Animal Behavior Abstracts, CAB Abstracts, EMBASE, Food Science & Technology Abstracts, Veterinary Science Database
  • Page Numbers: pp.583-591
  • Keywords: bovine mastitis, bioinformatics tools, biological signalling, genetic markers, STAPHYLOCOCCUS-AUREUS, MUTATIONS, CATTLE, CELLS
  • Van Yüzüncü Yıl University Affiliated: Yes

Abstract

© 2022 Muhammad Zahoor Khan et al., published by Sciendo.Background: Bovine mastitis is a common infectious disease with a serious threat to the dairy industry and public health. Mastitis is a polygenetic trait under the control of many genes. In the current study, our research attempted to address the role of mastitis-associated genes in various signalings including parasitic, viral, cancer and fungal diseases by using online bioinformatics software. Methods: We selected mastitis-associated genes from already published data and using online bioinformatics tools including DAVID and String classified the pathological role of relevant genes. A Venn diagram was used to show the status of overlapping genes among different biological function processes. Result: This study revealed that the genes gathered in published resources of mastitis were significantly correlated with influenza A, chagas disease, leishmaniasis, toxoplasmosis, tuberculosis, cancer signaling, hepatitis B, type I & II diabetes mellitus and prion diseases biological pathways. Based on our findings, we concluded that mastitis-linked genes could be used as markers for many other diseases. Moreover, the bioinformatics tools applied in the current study might be helpful in screening the genes involved in one disease and their association with other diseases as well.