Candidate gene association analysis for milk yield and composition traits, coagulation properties and somatic cell count in Italian Holstein Friesian bulls

Advances in DNA-based marker technology enabled the identification of genomic regions underlying complex phenotypic traits in livestock species. The incorporation of detected quantitative trait loci into genetic evaluation provides a great potential to enhance selection accuracies, hence expediting the genetic improvement of economically important traits. The objective of the present study was to evaluate the association of 96 individual single nucleotide polymorphisms (SNP), located in 53 candidate genes, with milk production (milk yield, MY; protein yield, PY; casein yield, CY; fat yield, FY) and composition (protein percentage, PP; fat percentage, FP; casein percentage, CP) traits, somatic cell score (SCS) and milk coagulation properties (MCP), i.e., rennet coagulation time (RCT) and curd firmness 30 min after rennet addition (a30), in a population of Italian Holstein Friesian sires. Phenotypic records for 292,007 milk samples from 45,115 lactating cows reared in Veneto Region (northeast Italy) were collected and analyzed using mid-infrared spectroscopy. Through the use of de-regressed estimated breeding values (EBV), data from the semen sample of 423 Italian Holstein Friesian bulls were genotyped with the Illumina GoldenGate Assay (Illumina) to test the association of polymorphic SNP with the selected phenotypic traits. After data editing, of the 96-selected SNP, a total of 65 SNP in 43 candidate genes were successfully genotyped. Forty-five SNP in 32 genes were associated with at least one of the tested traits. In particular, most significant SNP-trait associations, having favorable effect on the milk traits, were observed for polymorphisms located in genes: CCL3 and AGPAT6 on FY; DGKG on MY; PPARGC1A, AGPAT6 and CSN1S1 on FP; GHR on PP and CP; TLR4 on PP, CP and FP; CSN2 and POU1F1 on RCT; GHR on a30; and AGPAT6 on both RCT and a30. GHR and POU1F1 polymorphisms were associated with an important reduction of SCS. Genomic regions found to be significantly associated with milk technological traits will contribute to the identification of the genes regulating those traits in dairy cattle. Moreover, our results can be considered as preliminary foundation for further studies based on gene-assisted selection and genomic selection programs.