Abstract
Background: Milk fat is a critical economic trait in Holstein cattle; however, the identification of genomic loci associated with milk fat content remains limited, constraining progress in genetic improvement and overall dairy production efficiency. A comprehensive understanding of the genetic and regulatory mechanisms underlying milk fat synthesis is therefore essential for advancing dairy breeding and productivity. Results: We conducted a genome-wide association study (GWAS) using a linear mixed model (LMM) on the genomic estimated breeding values (GEBVs) of milk fat percentage (MFP) in 2,709 Chinese Holstein cows. Population structure and relatedness were controlled using a genomic relationship matrix (GRM), and multiple testing was corrected by applying the False Discovery Rate (FDR) method. A total of 104 significant SNPs (FDR < 0.05) were identified, including 32 SNPs clustered in the DGAT1 region on BTA14 (1.3-2.3 Mb, Bos_taurus_UMD_3.1.1). Favorable alleles for each SNP were identified. Among the significant variants, eight SNPs located within the exons of SPAG1, SLC15A5, PLEKHA5, and HERC6 were found, including four missense mutations predicted to increase protein stability according to I-Mutant and MUpro analyses. Validation in an independent population of 99 cows confirmed associations between MFP and three intergenic SNPs: BovineHD1400001112, BovineHD1400000698, and BovineHD0500026460, all located in predicted transcriptional regulatory regions. Dual-luciferase assays demonstrated that these SNPs affected transcriptional activity, with BovineHD1400001112 influencing the binding of SP1, a core regulator of milk fat synthesis. qRT-PCR in peripheral blood (T/T vs. C/C) showed differential expression of FASN and ACACA. Conclusions: These findings support the notion that BovineHD1400001112 may act as a regulatory variant influencing milk fat synthesis through modulation of key transcription factors and nearby genes, providing insights into potential targets for genetic improvement in Holstein cattle.