Genome-wide association study for somatic cell score in Argentinean dairy cattle

•GWAS analysis revealed genomic regions influencing traits derived from SCC in Argentinean herds.•Different traits showed different SNP associated.•Identified SNPs were located close to several promising candidate genes.

This study aimed to understand the genomic architecture of Argentinean dairy herds by measuring linkage disequilibrium (LD) and identifying loci associated with parameters calculated from somatic cell count (SCC). Phenotypic data consisted of 3530 SCC records from 544 Holstein and Holstein x Jersey cows owned by a single dairy company located in the Central dairy area of Argentina. SCC was recorded every 40 days. After quality control, genotypic data consisted in 38,872 single nucleotide polymorphisms (SNP). The squared correlation of the alleles at two loci (r2) was computed for all SNP pairs on each chromosome. At marker distances less than 10 kb the average r2 was 0.40. Between 40 and 50 kb the average r2 was 0.25 and 0.18 for 100 kb apart. Three different variables were calculated from the somatic cell score (SCS): the arithmetic mean (AM), the maximum value (MAX) and the arithmetic mean of the top 3 values (TOP3). Few significant SNP associations were found. As expected, polygenic traits such as SCC are influenced by multiple loci throughout the genome, each with a relatively small effect. AM on one side and TOP3 and MAX on the other, showed different SNP associated showing that they capture different aspects of mastitis response. AM was significantly associated with two SNP: ARS-BFGL-NGS-114608 (BTA1) and Hapmap60306-rs29023088 (BTA5). MAX and TOP3 were significantly associated with four SNP: ARS-BFGL-NGS-107594, ARS-BFGL-NGS-104220 (BTA10), BTA-43543-no-rs (BTA18) and ARS-BFGL-NGS-109705 (BTA26). MAX and TOP3 were equivalent phenotypic variables to be used in a GWAS. These results contribute to gain insight into the genomic regions influencing the SCC in Argentinean herds.