Differentiation of cells by flow cytometry provides informative somatic cell counts (SCCs) that allow analyzing leukocyte population patterns in udder infections of different etiologies. Postulating that this approach also enhances the statistical power to detect genetic variants linked to cell levels in milk of healthy mammary glands, we used monoclonal antibodies anti-CD18, anti-CD4, anti--CD14, and anti-PMN to count cells presenting these surface antigens, and performed a genome-wide association study of these counts in 125 Israeli Holsteins genotyped using SNP BeadChips. We identified an informative haplotype of 15 SNPs in the centromeric end of BTA3 that was strongly associated with CD18 cells (p < 2.3 × 10-9). Within this region, examination of the network of genes interacting with ITGB2 (CD18) indicated an Fc-γ-receptor gene cluster, including FCGR2A (CD32). Sanger-sequence analysis of FCGR2s-linked exon 3 variation to CD18 counts. Meta-analysis of RNA-Seq data revealed a significant negative correlation (R = -0.51) between expression of CD32 and CD18 in milk. Assembly of DNA-Seq reads uncovered FCGR copy-number variation and a variant, designated V7, was abundant in dairy cattle, probably reflecting adaptation to selection pressure for low SCC in Holstein milk.
Keywords: GWAS; SNP BeadChip; classification determinant; cluster of differentiation; immunogenetics; mastitis; milk.