Decoding early-lactation energy balance in dairy cows using blood coexpression networks and candidate markers

Energy balance (EB) can be an important health indicator in dairy cows because a severe or prolonged period of negative energy balance is a key risk factor for metabolic disorders, impaired immune function, and reduced fertility. Understanding the biological mechanisms of EB is fundamental to developing strategies that improve energy intake, mitigate negative energy balance, and enhance the management of metabolic challenges in dairy cows. This study employed whole-blood transcriptomic as a scalable approach to unravel the molecular networks governing EB in early-lactation Holstein cows. Whole-blood RNA sequencing analysis during early lactation (24-32 d postcalving) identified 26 differentially expressed genes associated with EB. These genes were found to be engaged in pathways critical to metabolic adaptation, including PPAR signaling (PRDM16), extracellular matrix organization (COL18A1, EMID1), and cell fate commitment (SOX13, WNT5A). Weighted gene coexpression network analysis identified a key module (87 genes) strongly correlated with EB. Protein-protein interaction networks further connected DBN1 to cytoskeletal signaling (L1CAM, AMPH) and COL18A1 to WNT-integrin signaling (LAMA4, PTK2), suggesting novel mechanisms for systemic stress adaptation. These findings advance the understanding of EB as a polygenic trait characterized by multitissue interactions and proposes actionable markers that can be applied to dairy cow management as targets for genetic selection to improve metabolic resilience. Future work will seek to validate these findings using tissue-specific analyses, and functional assays to elucidate mechanistic roles of prioritized genes.