The aim of the study is to identify genetic markers associated with dairy productivity parameters (milk yield, milk fat and protein content) in Holstein cattle using the genome-wide association analysis (GWAS) method on a sample of animals from breeding farms in the Sverdlovsk Region for 2018–2024. Objectives: to genotype a sample of cows using DNA bioarrays and carry out data quality control; to perform GWAS analysis of dairy productivity on the full population and on extreme phenotypic groups; to identify statistically significant single nucleotide polymorphisms (SNPs) associated with milk yield, fat and protein content; to analyze genes located near significant SNPs to understand their role in lipid metabolism, immune response and mammary tissue development; to evaluate the coincidence of genetic associations between the full sample and extreme groups to confirm the reliability of markers. GWAS analysis of milk productivity was conducted on 539 Holstein cows from 3 breeding farms in the Sverdlovsk Region (2018–2024). Milk yield, fat, and protein were analyzed on the full sample and at the extreme quartiles Q1/Q4 (milk yield: (10,028 ± 680) and (6,775 ± 653) kg; fat: (4.07 ± 0.068) and (3.79 ± 0.092) %; protein: (3.38 ± 0.066) and (3.12 ± 0.045) %). A total of 20 significant SNPs associated with cattle productivity parameters were identified. Genes responsible for fatty acid and lipid metabolism (SLC27A6), as well as those associated with milk productivity and the immune response (GPX8, CDC20B, and GZMA) are located near some polymorphisms. The identified SNPs and loci can serve as candidate markers for genomic selection of Holstein cattle. The agreement between the GWAS results for the full sample and the extreme quartiles Q1/Q4 confirms the reliability of the identified associations and the effectiveness of the extreme sampling method.
Bogatova et al. (2026) studied this question.