Abstract
The aim of this study was to perform genome-wide associations (GWAS) and gene-set enrichment analyses with protein composition and cheesemaking-related latent variables (factors; F) in a cohort of 1,011 Italian Brown Swiss cows. Factor analysis was applied to identify latent structures of 26 phenotypes related to bovine milk quantity and quality, protein fractions [αS1-, αS2-, β-, and κ-casein (CN), β-lactoglobulin, and α-lactalbumin (α-LA)], coagulation and curd firming at time t (CFt) measures, and cheese properties [cheese yield (%CY) and nutrients recovery in the curd] of individual cows. Ten orthogonal F were extracted, explaining 74% of the original variability. Factor 1%CY underlined the %CY characteristics, F2CFt was related to the CFt process parameters, F3Yield was considered as descriptor of milk and solids yield, whereas F4Cheese N underscored the presence of nitrogenous compounds (N) into the cheese. Four more F were related to the milk caseins (F5αS1-β-CN, F7β-κ-CN, F8αS2-CN, and F9αS1-CN-Ph) and 1 F was linked to the whey protein (F10α-LA); 1 F underlined the udder health status (F6Udder health). All cows were genotyped with the Illumina BovineSNP50 Bead Chip v.2 (Illumina Inc., San Diego, CA). Single marker regression GWAS were fitted. Gene-set enrichment analysis was run on GWAS results, using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway databases, to reveal ontologies or pathways associated with the F. All F but F3Yield showed significance in GWAS. Signals in 10 Bos taurus autosomes (BTA) were detected. High peaks on BTA6 (∼87 Mbp) were found for F6β-κ-CN, F5αS1-β-CN, and at the tail of BTA11 (∼104 Mbp) for F4Cheese N. Gene-set enrichment analyses showed significant results (false discovery rate at 5%) for F8αS2-CN, F1%CY, F4Cheese N, and F10α-LA. For F8αS2-CN, 33 Gene Ontology terms and 3 Kyoto Encyclopedia of Genes and Genomes categories were enriched, including terms related to ion transport and homeostasis, neuron function or part, and GnRH signaling pathway. Our results support the feasibility of factor analysis as a dimension reduction technique in genomic studies and evidenced a potential key role of αS2-CN in milk quality and composition.