Reproduction

Metabolomic Analysis of Fertility Traits in Transitioning Dairy Cows

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Abstract

Female fertility is essential for dairy cattle herd productivity and profitability, with poor fertility costing the global dairy industry an estimated $65 billion annually. The goal of this study was to identify differentially abundant metabolites, biological processes, and biomarkers associated with fertility traits in Jersey and Holstein cattle during the transition period. Seventy cows were classified into high-, medium-, or low-fertility groups based on the average ± one standard deviation for two fertility traits: times bred (number of artificial insemination [AI] services required for conception) and days open (number of days from calving to subsequent conception). For times bred, the high-fertility was categorized as one AI service (n=27), medium-fertility as two to four AI services (n=34), and low-fertility as greater than five AI services (n=9). For days open, high-fertility was designatedas ≤ 76 days (n=13), medium-fertility as 77 - 158 days (n=37), and low-fertility as ≥ 159 days (n=20). Throughout the duration of the study, cows were housed in the same pen and under identical management practices including health checks, diet, and Double-Ovsynch breeding synchronization protocol. Blood samples were collected at weeks 1, 2, 3, and 4 postpartum and then centrifuged to obtain serum. A total of 271 samples were sent to the Carver Metabolomics Core, University of Illinois Urbana-Champaign for metabolomic profiling using liquid chromatography-mass spectrometry (LC-MS) as an untargeted approach for metabolite detection. Quality control for the LC-MS analysis included calibration and equilibration of the instruments, sequence randomization, and utilization of control samples. A total of 133 metabolites passed quality control. Metabolomic profiles were analyzed using a mixed linear model implemented in PROC MIXED in SAS. The statistical model included fertility group, breed, health status, and age at the sampling point as fixed effects. The biological pathway, network, and enrichment analyses were performed using MetaboAnalyst. In total, 20 metabolites were significantly associated with days open and 37 metabolites with times bred across various postpartum time points (P < 0.05). Enrichment and pathway analysis revealed several key biological pathways, including propanoate metabolism, pyrimidine metabolism, and beta-alanine metabolism. These results reveal promising biomarkers that could improve reproductive management and selection strategies, while also offering new insights into the molecular mechanisms that modulate fertility. Overall, this research detected metabolic signatures that may serve as early predictors of female fertility, supporting improved herd management and long-term sustainability in dairy production.

Keywords: 2026

How to Cite:

Grace, K., Seto, D., Campos, F., Peterson, D., Anderson, P., Pokharel, S., Gallagher, G., Sprayberry, K. & Abo-Ismail, M., (2026) “Metabolomic Analysis of Fertility Traits in Transitioning Dairy Cows”, World Congress on Genetics Applied to Livestock Production Digital Archive 2026(1): 2287111. doi: https://doi.org/10.31274/wcgalp.24215

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