Genomic background of lactation curve parameters derived from daily milk yield in Holstein cattle using parametric functions

Lactation curve parameters (LCP) are essential in the refinement of dairy cattle breeding programs due to their relationship with the shape of lactation curves and their biological interpretations. In this context, the primary objectives of this study were to perform genome-wide association studies and functional enrichment analyses of various LCP from random regression models based on 3 nonlinear functions (Wood [WD], Wilmink [WL], and Ali-Schaeffer [AS]) in American Holstein cattle. We used 2,754,840 and 1,642,653 daily milk yield records of 11,139 first and 6,735 s parity cows, respectively, born between 2012 and 2019. A total of 14,464 animals were also genotyped with 60,277 single nucleotide polymorphisms (SNP). The SNP effects, the proportion of the total additive genetic variance explained by them, and their approximate P-values, were estimated for the random regression coefficients based on the GBLUP method. Significant SNP were identified using a modified Bonferroni multiple testing correction that accounts for the number of independent chromosomal segments. Genes and quantitative trait loci located within 100 kb upstream or downstream of the significant SNP were then examined, and functional enrichment analyses were conducted on the candidate genes identified for each LCP. For first parity cows, 81, 128, and 196 significant SNP were identified for the WD, WL, and AS parameters, respectively; whereas for second-parity cows, 120, 125, and 128 significant SNP were identified for the same parameters. The significant SNP were located on 18 autosomal chromosomes. One genomic region (BTA14: 1,801,116 bp) was common to all the parametric functions (WD, WL, and AS). The genomic markers located on BTA15 and BTA19 were unique to the WL parameters; whereas those located on BTA3 and BTA20 were unique to the AS parameters. There were significant SNP located on BTA14 capturing more than 1% of the total additive genetic variance. Twenty candidate genes (i.e., ARC, ADGRB1, C8orf90, CYP11B1, DENND3, GML, GPR20, JRK, LY6D, LY6E, LY6L, LYNX1, LYPD2, PSCA, PTK2, PTP4A3, SLURP1, SLC45A4, THEM6, and TSNARE1) were common to all the parametric functions. No significant gene ontology terms were found for the WD parameter c (i.e., decreasing slope parameter after the lactation peak yield) for first parity cows, and for the AS parameters d and f (parameters associated with the increasing slope) for second-parity cows. Previous reports have identified candidate genes within these genomic regions that possess biological functions related to apoptotic and regulation of gene expression, milk production, clinical mastitis, milk lactose, somatic cell score, fat yield, and udder morphology. This study enabled the identification of several candidate genes associated with LCP, enhancing our understanding of the genomic architecture underlying LCP in American Holstein cattle.