Mastitis is the costliest disease facing dairy producers today; consequently, it has been the subject of substantial research focus. Efforts have evolved from an initial focus on understanding the etiology of intramammary infections to the application of preventative measures, including attempts to breed cows that are resistant to infection. However, breeding for resistance to infection has proven difficult, given the complexity of the disease and the high expense associated with assembling high-quality genotypes and phenotypes. This review provides a brief background on mastitis; illustrates current understanding of the genetics influencing mastitis and the application of this knowledge; and discusses challenges and limitations in understanding these mechanisms and applying these findings to genetic improvement strategies.

Our objectives were to robustly characterize a cohort of Holstein cows for udder and teat type traits and perform high-density genome-wide association studies for those traits within the same group of animals, thereby improving the accuracy of the phenotypic measurements and genomic association study. Additionally, we sought to identify a novel udder and teat trait composite risk index to determine loci with potential pleiotropic effects related to mastitis. This approach was aimed at improving the biological understanding of the genetic factors influencing mastitis. Cows (N = 471) were genotyped on the Illumina BovineHD777k beadchip and scored for front and rear teat length, width, end shape, and placement; fore udder attachment; udder cleft; udder depth; rear udder height; and rear udder width. We used principal component analysis to create a single composite measure describing type traits previously linked to high odds of developing mastitis within our cohort of cows. Genome-wide associations were performed, and 28 genomic regions were significantly associated (Bonferroni-corrected p < 0.05). Interrogation of these genomic regions revealed a number of biologically plausible genes whicht may contribute to the development of mastitis and whose functions range from regulating cell proliferation to immune system signaling, including ZNF683, DHX9, CUX1, TNNT1, and SPRY1. Genetic investigation of the risk composite trait implicated a novel locus and candidate genes that have potentially pleiotropic effects related to mastitis.

The objective of this study was to determine whether genetic regulation of bovine milk somatic cell count (SCC) varied throughout the course of an individual lactation and to identify quantitative trait loci (QTL) that may differentiate populations of chronically mastitic and robustly healthy cows. Milk SCC has long been a proxy for clinical mastitis diagnosis in management and genetic improvement strategies to control the disease. Cows (n = 471) were genotyped on the Illumina BovineHD 777K BeadChip (Illumina Inc., San Diego, CA), and composite milk samples were collected for SCC at 0-1 d in milk (DIM), 3-5 DIM, 10-14 DIM, 90-110 DIM, and 210-230 DIM, with each time span representing key physiological transitions for the cow. Median lactation somatic cell score (SCS) and area under the SCS curve were calculated from farm test data. A total of 8 genome-wide associations were performed and 167 SNP spanning the genome were significantly associated (false discovery rate <0.05). Of these associated regions, 27 of 48 associated QTL were novel for clinical mastitis or SCC. The linkage disequilibrium block surrounding the associated QTL or a 1-Mb window in the absence of linkage disequilibrium was interrogated for candidate genes, and many of those identified were related to multiple arms of the immune system, including toll-like receptor signaling, macrophage activation, B-cell maturation, T-cell recruitment, and the complement pathway. These genes included EXOC4, BAMBI, ITSN2, IL34, FCN3, CD8A, and CD8B. In addition, we identified populations of robustly healthy (SCS <= 4 from 10-14 DIM until study end), chronically mastitic (SCS >4 from 10-14 DIM until study end), and average cows with fluctuating SCS, and calculated fixation indices to identify regions of the genome differentiating these 3 populations. A total of 12 SNP were identified that showed moderate allelic differentiation (Wright's F statistic, F-ST >= 0.4) between the "chronic," "healthy," and "average" populations of cows. Candidate genes in the region surrounding differentiated QTL were related to cell signaling and immune response, such as JAKMIP1 and MADCAM1. The wide range of significantly associated QTL spanning the genome and the diversity of gene functions reinforces that mastitis is a complex trait and suggests that selection based on lactation stage-specific SCS rather than a generalized score may lead to greater success in breeding mastitis-resistant cows.

Most genotypes in the National Cooperator Database now originate from cows, but most previous studies validating genomic predictions have primarily focused on bulls. This study paired official within-breed genomic predicted transmitting ability (GPTA) and parent average (PA) for genotyped heifer calves born between 2019 and 2021 using the August 2021 database with their corresponding performance deviations (PDEV) for 17 different traits. The PDEV data became available when the heifers completed their first lactation and were extracted from the August 2023 database in which at least one PDEV value for those 17 traits existed for each genotyped heifer record. The separate breed analyses included records for 219 Ayrshires (AY), 2,715 Brown Swiss (BS), 1,055 Guernseys (GU), 949,904 Holsteins (HO), and 125,275 Jerseys (JE). These validation cows were heifer calves born between 2019 and 2021. However, due to timing or recording patterns, each trait had missing or incomplete PDEV data, leading to unbalanced distributions of records across traits. The squared accuracy of genomic prediction, or genomic reliability (r²), was divided by the corresponding heritability for each trait, as only the heritable portion of cow records could be predicted, and this reliability varied across different traits and breeds. For HO and JE, the predictive ability of GPTA outperformed PA in predicting cow PDEV for yield, productive life, somatic cell score, fertility, and health traits. The improvement ranged from 33% to 142% compared with the predictive ability of the PA. However, the results for AY, BS, and GU breeds were less consistent due to the smaller number of genotyped heifers. The r² gains in those breeds were smaller and aligned with the published reliabilities of GPTA. Weighted and unweighted regressions of PDEV on GPTA and PA traits mostly exceeded the expected value of 2.00 when predicting the future trait PDEV using GPTA or PA. The larger number of observations and lower standard error of the weighted regression coefficient prediction in HO and JE breeds contributed to more stable and consistent regression coefficients for all traits except milk fever and heifer livability. Our study suggests that herd owners may experience greater benefits from genomics than originally forecast.

Dairy producers have improved fertility of their herds by selecting bulls with higher conception rate evaluations. This research was motivated by the rapid increase in embryo transfer (ET) use to 11% of recent births and >1 million total births, with >5 times as many ET calves born in the United States in 2021 compared with just 5 yr earlier. Historical data used in genetic evaluations are stored in the National Cooperator Database. Recent records in the national pedigree database revealed that only 1% of ET calves have corresponding ET records in the breeding event database, 2% are incorrectly reported as artificial inseminations, and 97% have no associated breeding event. Embryo donation events are also rarely reported. Herd years reporting >10% of calves born by ET but less than half of the expected number of ET breeding events were removed to avoid potential biases. Heifer, cow, and sire conception rate evaluations were recalculated with this new data set according to the methods used for the official national evaluations. The edits removed about 1% of fertility records in the most recent 4 yr. Subsequent analysis showed that censoring herd years with inconsistent ET reporting had little effect on most bulls except for the highest ranking, younger bulls popular for ET use, and with largest effects on genomic selection. Improved ET reporting will be critical for providing accurate fertility evaluations, especially as the popularity of these advanced reproductive technologies continues to rise.

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