From candidate genes to whole-genome approaches: current insights into the genetic architecture of ovine milk production and quality traits

Milk production and composition traits are important characteristics in dairy sheep, influencing milk quality, cheesemaking performance, and the economic value of dairy products. Early genetic studies focused on candidate genes, particularly milk protein genes, endocrine regulators, and lipid-metabolism genes. Among these, the casein gene cluster and the alpha-lactalbumin gene ( LALBA ) remain consistently replicated loci associated with milk composition traits across breeds and analytical frameworks. The development of genome-wide technologies has expanded our understanding of the genetic architecture underlying ovine dairy traits. Quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), regional heritability mapping, and single-step GWAS have identified loci associated with milk yield, milk composition, somatic cell score, coagulation properties, and cheesemaking performance. Whole-genome sequencing and selection-signature approaches have expanded the catalogue of candidate genomic regions and biological pathways relevant to dairy performance. These studies indicate that ovine milk traits are polygenic and involve biological pathways related to milk protein synthesis, lipid metabolism, mammary gland development, immune function, tissue remodeling, and environmental adaptation. Recent advances in functional genomics, transcriptomics, and multi-omics integration provide opportunities to prioritize candidate genes and investigate the biological mechanisms underlying dairy phenotypes. Developments in sequence-based genomic resources, structural-variant discovery, and functional genomics are expected to improve the detection of causal variants and support efficient and sustainable breeding strategies. This review summarizes knowledge on candidate genes and genomic regions associated with ovine milk production and quality traits, highlighting the transition from classical candidate-gene studies to genome-wide and post-genomic approaches.