Integrated Network Analysis to Identify Key Modules and Potential Hub Genes Involved in Bovine Respiratory Disease: A Systems Biology Approach - Hasankhani, Aliakbar; Bahrami, Abolfazl; Sheybani, Negin; Fatehi, Farhang; Abadeh, Roxana; Ghaem Maghami Farahani, Hamid; Bahreini Behzadi, Mohammad Reza; Javanmard, Ghazaleh; Isapour, Sadegh; Khadem, Hosein; Barkema, Herman W. (Frontiers in Genetics, 2021)
Background: Bovine respiratory disease (BRD) is the most common disease in the beef and dairy cattle industry. However, the molecular mechanisms underlying BRD are not fully understood yet. Therefore, this study aimed to use a systems biology approach to systematically evaluate this disorder to better understand the molecular mechanisms responsible for BRD. Methods: Previously published RNA-seq data from whole blood of 18 healthy and 25 BRD samples were downloaded and then analyzed. Next, two distinct methods of weighted gene co-expression network analysis (WGCNA) i.e. module-trait relationships (MTRs) and module preservation (MP) analysis were used to identify significant highly-correlated modules with clinical traits of BRD and non-preserved modules, respectively. After identifying respective modules by the two mentioned methods of WGCNA, functional enrichment analysis was performed. Gene co-expression networks based on the hub genes were then integrated with protein-protein interaction (PPI) networks to identify hub-hub genes and potentially transcription factors (TFs). Results: Four significant highly-correlated modules with clinical traits of BRD as well as 29 non-preserved modules were identified by MTRs and MP methods, respectively. Among them, two significant highly-correlated modules (identified by MTRs) and six non-preserved modules (identified by MP) were biologically associated with immune response, pulmonary inflammation and pathogenesis of BRD. A total of 307 hub-hub genes were identified in the eight candidate modules. Interestingly, most of these hub-hub genes were reported to play an important role in the immune response and BRD pathogenesis. Among the eight candidate modules, the turquoise (identified by MTRs) and purple (identified by MP) modules were highly biologically enriched in BRD. Moreover, STAT1, STAT2, STAT3, IRF7, and IRF9 TFs were suggested to play an important role in the immune system during BRD by regulating the co-expressed genes of these modules. Additionally, a gene set containing several hub-hub genes was identified in the eight candidate modules which are potentially critical during infection with agents of bovine respiratory disease complex (BRDC). Conclusion: This study not only helps us to better understand the molecular mechanisms responsible for BRD, but also suggested eight candidate modules along with several promising hub-hub genes as diagnosis biomarkers and therapeutic targets for BRD.