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Epigenetic Regulation of Production Traits in Ruminants: Implications for Breeding and Selection
Huaijing Liu1, Mewangling Qumu1, Ying Lu1
1Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China.
Abstract:
The important economic traits of ruminants result from interactions between genetic background and environmental factors, but key traits such as reproductive performance, feed efficiency, disease resistance, and livestock product quality are often not fully explained by DNA sequence variations alone. Increasing evidence suggests that epigenetic regulation serves as a crucial molecular bridge connecting environmental stimuli with changes in gene expression, allowing organisms to exhibit stable and plastic phenotypic differences without altering the DNA sequence. This review provides a structured synthesis of recent research in the field of epigenetics in ruminants, elucidating how multiple layers of epigenetic mechanisms, including DNA methylation, histone modifications, non-coding RNAs, and higher-order chromatin structures, coordinate to regulate growth, development, reproductive performance, metabolic and immune homeostasis, and livestock product traits across different tissues and developmental stages. These epigenetic marks not only demonstrate high responsiveness to nutrition, management, and environmental stressors, but can exhibit context-dependent stability within the same tissue and physiological stage when environmental conditions are comparable, thereby contributing to the regulation of phenotypic plasticity and offering potential value as predictive biomarkers. Furthermore, epigenetic information can supplement our understanding of phenotypic variation in ways that traditional genomic selection methods are unable to capture, offering new data dimensions for the prediction and improvement of low heritability, environmentally sensitive traits. Overall, integrating epigenetic information with genomic selection strategies may improve the accuracy of ruminant trait prediction and enhance environmental adaptability. This integration also offers a conceptual basis and technical pathway for developing more precise and sustainable breeding systems.
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