Weighted Gene Co-expression Network Analysis Identifies Specific Modules and Hub Genes Related to Subacute Ruminal Acidosis

Qiuju Wang, Bingnan Gao, Xueqing Yue, Yizhe Cui, Juan J. Loor, Xiaoxia Dai, Xu Wei, Chuang Xu

Research output: Contribution to journalArticlepeer-review


Weighted gene co-expression network analysis (WGCNA) was used to understand the pathogenesis of subacute ruminal acidosis (SARA) and identify potential genes related to the disease. Microarray data from dataset GSE143765, which included 22 cows with and nine cows without SARA, were downloaded from the NCBI Gene Expression Omnibus (GEO). Results of WGCNA identified highly correlated modules of sample genes, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses allowed further biological insights into SARA-related modules. The protein-protein interaction (PPI) network, modules from the PPI network, and cistron annotation enrichment of modules were also analyzed. A total of 14,590 DEGs were used for the WGCNA. Construction of a protein-protein network identified DCXR, MMP15, and MMP17 as hub genes. Functional annotation showed that DCXR mainly exhibited L-xylulose reductase (NADP+) activity, glucose metabolic process, xylulose metabolic process, and carbonyl reductase (NADPH) activity, which are involved in the pentose and glucuronate interconversion pathways. MMP15 and MMP17 mainly have a collagen catabolic process. Overall, the results of this study aid the clarification of the biological and metabolic processes associated with SARA at the molecular level. The data highlight potential mechanisms for the future development of intervention strategies to reduce or alleviate the risk of SARA.

Original languageEnglish (US)
Article number897714
JournalFrontiers in Veterinary Science
StatePublished - Jun 10 2022


  • bioinformatic analysis
  • differentially expressed genes
  • inflammatory response
  • subacute ruminal acidosis
  • transmembrane signaling

ASJC Scopus subject areas

  • veterinary(all)


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