ArticleVeterinary sciences2026
Identification of Key Candidate Genes Potentially Associated with Lactation Traits in Dairy Cows Using Weighted Gene Co-Expression Network Analysis.
Article in Veterinary sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Lactation traits are important indicators for evaluating the production performance of dairy cows and the economic efficiency of dairy production. Identifying potential regulatory genes is essential for elucidating the molecular mechanisms underlying lactation and facilitating molecular breeding. This study aimed to identify candidate genes and regulatory pathways potentially associated with lactation traits in dairy cows by integrating transcriptome expression profiles of primary bovine mammary epithelial cells (BMECs) from eight Holstein cows with lactation phenotypic data. A gene co-expression network was constructed using weighted gene co-expression network analysis (WGCNA). Co-expression modules associated with lactation traits were identified, and candidate genes were further screened by integrating gene significance, module membership, functional enrichment analysis, random forest analysis, gene-phenotype association analysis, single-gene gene set enrichment analysis (GSEA), ROC curve analysis, and tissue expression profiling. Four co-expression modules, namely MEdarkturquoise, MEsteelblue, MEbrown, and MEskyblue3, were significantly associated with lactation traits (
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