| Autor: |
Bouzeraa L; Department of Animal Sciences, Faculty of Agricultural and Food Sciences, Laval University, Québec, QC, Canada.; Research Center in Reproduction, Development, Intergenerational Health (CRDSI), Québec, QC, Canada., Martin H; Department of Animal Sciences, Faculty of Agricultural and Food Sciences, Laval University, Québec, QC, Canada.; Research Center in Reproduction, Development, Intergenerational Health (CRDSI), Québec, QC, Canada., Plessis C; Department of Molecular Medicine, Faculty of Medicine, Laval University, Québec, QC, Canada., Dufour P; Department of Molecular Medicine, Faculty of Medicine, Laval University, Québec, QC, Canada., Marques JCS; Faculty of Land and Food Systems, University of British Columbia, Vancouver, Canada., Moore S; Faculty of Land and Food Systems, University of British Columbia, Vancouver, Canada., Cerri R; Faculty of Land and Food Systems, University of British Columbia, Vancouver, Canada., Sirard MA; Department of Animal Sciences, Faculty of Agricultural and Food Sciences, Laval University, Québec, QC, Canada.; Research Center in Reproduction, Development, Intergenerational Health (CRDSI), Québec, QC, Canada. |
| Abstrakt: |
Cattle farming faces challenges linked to intensive exploitation and climate change, requiring the reinforcement of animal resilience in response to these dynamic environments. Currently, genetic selection is used to enhance resilience by identifying animals resistant to specific diseases; however, certain diseases, such as mastitis, pose difficulties in genetic prediction. This study introduced the utilization of enzymatic methyl sequencing (EM-seq) of the blood genomic DNA from twelve dairy cows to identify DNA methylation biomarkers, with the aim of predicting resilience and susceptibility to mastitis. The analysis uncovered significant differences between cows resilient and susceptible to mastitis, with 196,275 differentially methylated cytosines (DMCs) and 1,227 Differentially Methylated Regions (DMRs). Key genes associated with the immune response and morphological traits, including ENOPH1, MYL10 and KIR2DL5A, were identified by our analysis. Quantitative trait loci (QTL) were also highlighted and the body weight trait was the most targeted by DMCs and DMRs. Based on our results, the risk of developing mastitis can potentially be estimated with as few as fifty methylation biomarkers, paving the way for early animal selection. This research sets the stage for improved animal health management and economic yields within the framework of agricultural sustainability through early selection based on the epigenetic status of animals. |
