Weighted gene co-expression network analysis identifies functional modules related to bovine respiratory disease

Abstract

Bovine respiratory disease (BRD) is a multifactorial disease of dairy and beef cattle that involves complex interactions with the host immune system. In the current study, a comprehensive meta-analysis was performed using a P-value combination approach. In the next step, the identified meta-genes were subjected to systems biology analysis using the weighted gene co-expression network analysis (WGCNA) method. Subsequently, the most functionally important modules and genes were validated using machine learning algorithms. Finally, the critical regulatory network associated with BRD was constructed. A total of 1,908 common meta-genes were identified through the combined analysis of differentially expressed genes (DEGs) using the Fisher and Invorm approaches. Co-expression network analysis confirmed six functional modules, among which the connectivity patterns of the blue, brown, green, and yellow modules were significantly altered in BRD- affected cattle compared with healthy controls. Functional enrichment analysis of the significant modules revealed that the ‘Salmonella infection,’ ‘NOD-like receptor signaling pathway,’ ‘Necroptosis,’ ‘Toll-like receptor signaling pathway,’ ‘TNF signaling pathway,’ ‘IL-17 signaling pathway,’ ‘Apoptosis,’ and ‘Influenza A’ pathways were the most significantly associated with BRD . The constructed regulatory network identified GABPA, TCF4, ELK1, NR2C2, and ARNT as key transcription factors (TFs) , each playing a central role in regulating immune and inflammatory pathways implicated in BRD . Finally, the constructed model revealed that differential expression of the CFB gene is significantly associated with susceptibility to BRD . In cattle, CFB expression correlates with clinical signs of respiratory disease, supporting its potential as a biomarker. Moreover, the involvement of CFB in modulating pro-inflammatory cytokines (e.g., TNF) and its integration with other immune-related pathways (e.g., NF- κ B signaling) further highlight its relevance as a biomarker. Overall, this integrative approach enhances our understanding of the molecular mechanisms underlying BRD and provides a foundation for developing diagnostic, therapeutic, and genetic selection strategies to improve cattle health and disease resistance.