The aim of this study was to assess genome-wide autozygosity in a Nellore cattle population and to characterize ROH patterns and autozygosity islands that may have occurred due to selection within its lineages. It attempts also to compare estimates of inbreeding calculated from ROH (FROH), genomic relationship matrix (FGRM), and pedigree-based coefficient (FPED). The average number of ROH per animal was 55.15 ± 13.01 with an average size of 3.24 Mb. The Nellore genome is composed mostly by a high number of shorter segments accounting for 78% of all ROH, although the proportion of the genome covered by them was relatively small. The genome autozygosity proportion indicates moderate to high inbreeding levels for classical standards, with an average value of 7.15% (178.70 Mb). The average of FPED and FROH, and their correlations (− 0.05 to 0.26) were low. Estimates of correlation between FGRM-FPED was zero, while the correlation (− 0.01 to − 0.07) between FGRM-FROH decreased as a function of ROH length, except for FROH > 8Mb (− 0.03). Overall, inbreeding coefficients were not high for the genotyped animals. Autozygosity islands were evident across the genome (n = 62) and their genomic location did not largely differ within lineages. Enriched terms (p < 0.01) associated with defense response to bacteria (GO:0042742), immune complex reaction (GO:0045647), pregnancy-associated glycoproteins genes (GO:0030163), and organism growth (GO:0040014) were described within the autozygotic islands. Low FPED-FROH correlation estimates indicate that FPED is not the most suitable method for capturing ancient inbreeding when the pedigree does not extend back many generations and FROH should be used instead. Enriched terms (p < 0.01) suggest a strong selection for immune response. Non-overlapping islands within the lineages greatly explain the mechanism underlying selection for functionally important traits in Nellore cattle.

The objective of this study was to evaluate the efficacy of wellness trait genetic predictions in commercial herds of US Holstein cows from herds that do not contribute phenotypic information to the evaluation. Tissue samples for DNA extraction were collected from more than 3,400 randomly selected pregnant Holstein females in 11 herds and 2 age groups (69% nulliparous, 31% primiparous) approximately 30 to 60 d before their expected calving date. Lactation records from cows that calved between September 1, 2015, and December 31, 2015, were included in the analysis. Genomically enhanced predicted transmitting abilities for the wellness traits of retained placenta, metritis, ketosis, displaced abomasum, mastitis, and lameness were estimated by the Zoetis genetic evaluation and converted into standardized transmitting abilities. Mean reliabilities of the animals in the study ranged between 45 and 47% for each of the 6 traits. Animals were ranked by their standardized transmitting abilities within herd and age group then assigned to 1 of 4 groups of percentile-based genetic groups of equal size. Adverse health events, including retained placenta, metritis, ketosis, displaced abomasum, mastitis, and lameness, were collected from on-farm herd management software, and animal phenotype was coded as either healthy (0), diseased (1), or excluded for each of the 6 outcomes of interest. Statistical analysis was performed using a generalized linear mixed model with genetic group, age group, and lactation as fixed effects, whereas herd and animal nested within herd were set as random effects. Results of the analysis indicated that the wellness trait predictions were associated with differences in phenotypic disease incidence between the worst and best genetic groups. The difference between the worst and best genetic groups in recorded disease incidence was 2.9% for retained placenta, 10.8% for metritis, 1.1% for displaced abomasum, 1.7% for ketosis, 7.4% for mastitis, and 3.9% for lameness. Odds ratio estimates between the highest and lowest genetic groups ranged from 1.6 (lameness) to 17.1 (displaced abomasum) for the 6 traits analyzed. These results indicate that wellness trait information of young calves and heifers can be used to effectively predict meaningful differences in future health performance. Improving wellness traits through direct genetic selection presents a compelling opportunity for dairy producers to help reduce disease incidence and improve profitability when coupled with sound management practices.

Selection indices are a critical component of many breeding programs. A common purpose of a selection index is to predict an animal's genetic potential for total economic merit. The objective of this study was to evaluate retrospectively whether a specific selection index comprising genomically-enhanced predicted transmitting abilities had the ability to predict observed lifetime profit in US Holstein animals. The selection index evaluated was dairy wellness profit (DWP$). In total, 2,185 animals were included in this study. Index values were used to rank and assign animals to quartiles (genetic groups: worst 25%, 26-50%, 51-75%, and best 25%). Generalized linear mixed effects models were applied to estimate the associations between index quartile and defined economic outcomes. Similar analyses were conducted to estimate associations between index quartile and observed phenotype to characterize the extent to which profitability outcomes were driven by economically relevant production and health traits. Differences in lifetime profit and annuity value between the best and worst genetic groups for DWP$ were $811 (±297) and $232 (±88), respectively. Significant differences were also observed between top and bottom quartiles for milk production (8,077 kg), fat production (336 kg), protein production (264 kg), live calves (0.5), time spent in the lactating herd (6.6 mo), and cow mortality (8.4%). Additionally, differences in disease incidence were significant between the best and worst DWP$ quartiles for metritis (5.2%), mastitis (14.9%), and lameness (15.9%). The observed results of this study demonstrated the ability of DWP$ predictions to predict lifetime profitability of Holstein animals and its potential utility as a tool to guide selection and breeding programs. Improving DWP$ through genetic selection, when combined with good management practices, provides an opportunity for dairy producers to improve overall herd profitability.

Twinning is a multifactorial trait influenced by both genetic and environmental factors that can negatively impact animal welfare and economic sustainability on commercial dairy operations. To date, using genetic selection as a tool for reducing twinning rates on commercial dairies has been proposed, but not yet implemented. In response to this market need, Zoetis (Kalamazoo, MI, USA) has developed a genomic prediction for twin pregnancies, and included it in a comprehensive multitrait selection index. The objectives of this study were to (1) describe a genetic evaluation for twinning in Holstein cattle, (2) demonstrate the efficacy of the predictions, (3) propose strategies to reduce twin pregnancies using this information. Data were retrieved from commercial dairies and provided directly by producers upon obtaining their permission. The twin pregnancies trait (TWIN) was defined as a pregnancy resulting in birth or abortion of twin calves, classified as a binary (0,1) event, and analysed using a threshold animal model. Predictions for a subset of cows were compared to their on-farm twin records. The heritability for twin pregnancies was 0.088, and genomic predicted transmitting abilities ((g)PTAs) ranged from −7.45–20.79. Genetic correlations between TWIN and other traits were low, meaning that improvement for TWIN will not negatively impact improvement for other traits. TWIN was effectively demonstrated to identify cows most and least likely to experience a twin pregnancy in a given lactation, regardless of reproductive protocol used. Effective inclusion of the prediction in a multitrait selection index offers producers a comprehensive tool to inform selection and management decisions. When combined with sound management practices, this presents a compelling opportunity for dairy producers to proactively reduce the incidence of twin pregnancies on commercial dairy operations.

The objective of this randomized controlled experiment was to evaluate the effect of reproductive management programs that prioritized artificial insemination (AI) at detected estrus (AIE) or timed AI (TAI) during the first lactation on the economic performance of dairy cows of different genomically enhanced predicted transmitting ability for fertility. Lactating primiparous Holstein cows from 6 commercial farms were stratified into high, medium, and low fertility groups based on a reproduction index value calculated from multiple genomically enhanced predicted transmitting abilities to predict the number of days to achieve pregnancy. Within herd and fertility group, cows were randomly assigned either to a program that prioritized AIE (P-AIE; n = 1,416) and used TAI for cows not AIE for all AI services or another that prioritized TAI and had an extended voluntary waiting period for first service and prioritized TAI for second and greater AI services (P-TAI; n = 1,338). Cash flow (CF) per cow accumulated for the experimental (first) and second calving interval (CIN) and cash flow per slot per 28 mo after calving in the experimental lactation were calculated. Market and rearing heifer cost values were used for estimating CF. For cows in the high fertility group, a positive effect of delayed pregnancy on milk income during the first lactation was observed (+$248 for P-TAI) but was insufficient to generate significant differences in CF between treatments mainly because of milk income compensation in the second lactation (+$125 for P-AIE) and minor reductions in reproductive cost and gains in calf value for the P-AIE treatment. In this regard, CF for 2 CIN was greater for the P-TAI treatment by $61 and $86 for market and rearing replacement heifer cost, respectively. Similarly, CF per slot was favorable to the P-TAI treatment but only by $13 and $47 for market and rearing replacement heifer cost, respectively. For cows in the low fertility group, CF was numerically in favor of the P-AIE treatment due to a pregnancy and herd exit dynamics that resulted in gains in milk income over feed cost during the first ($29) and second ($113) lactation. Differences in CF for the 2 CIN were $58 and $47 for market or rearing heifer value, respectively, and $77 and $19 for market and rearing heifer values, respectively for the slot analysis. Differences in CF between cows of different genetic merit for fertility were consistent across treatment and estimation method. Of note, cows in the low fertility group had greater CF than cows in the high fertility group in all comparisons, ranging from $198 per cow for 2 CIN to as much as $427 per slot. For the low fertility group, greater milk production contributed directly (milk income over feed cost) and indirectly (reduced culling) to increased CF. We concluded that genetic merit for fertility and CF are associated because cows of inferior genetic potential for fertility had greater CF than cows of superior genetic for fertility despite some increased costs and reduced revenues. Also, the magnitude of the CF differences observed for cows of different genetic merit for fertility managed with the P-AIE or P-TAI program may be valuable to commercial dairy farms but did not allow to conclusively support the choice of a type of reproductive management strategy for cows of different genetic merit for fertility.

Our objective was to compare reproductive outcomes of primiparous lactating Holstein cows of different genetic merit for fertility submitted for insemination with management programs that prioritized artificial insemination (AI) at detected estrus (AIE) or timed AI (TAI). Moreover, we aimed to determine whether subgroups of cows with different fertility potential would present a distinct response to the reproductive management strategies compared. Lactating primiparous Holstein cows (n = 6 commercial farms) were stratified into high (Hi-Fert), medium (Med-Fert), and low (Lo-Fert) genetic fertility groups (FG) based on a Reproduction Index value calculated from multiple genomic-enhanced predicted transmitting abilities. Within herd and FG, cows were randomly assigned either to a program that prioritized TAI and had an extended voluntary waiting period (P-TAI; n = 1,338) or another that prioritized AIE (P-AIE; n = 1,416) and used TAI for cows, not AIE. Cows in P-TAI received first service by TAI at 84 ± 3 d in milk (DIM) after a Double-Ovsynch protocol, were AIE if detected in estrus after a previous AI, and received TAI after an Ovsynch-56 protocol at 35 ± 3 d after a previous AI if a corpus luteum (CL) was visualized at nonpregnancy diagnosis (NPD) 32 ± 3 d after AI. Cows with no CL visualized at NPD received TAI at 42 ± 3 d after AI after an Ovsynch-56 protocol with progesterone supplementation (P4-Ovsynch). Cows in P-AIE were eligible for AIE after a PGF_2α treatment at 53 ± 3 DIM and after a previous AI. Cows not AIE by 74 ± 3 DIM or by NPD 32 ± 3 d after AI received P4-Ovsynch for TAI at 74 ± 3 DIM or 42 ± 3 d after AI. Binary data were analyzed with logistic regression, count data with Poisson regression, continuous data by ANOVA, and time to event data by Cox's proportional hazard regression. Pregnancy per AI (P/AI) to first service was greater for cows in the Hi-Fert (59.8%) than the Med-Fert (53.6%) and Lo-Fert (47.7%) groups, and for the P-TAI (58.7%) than the P-AIE (48.7%) treatment. Overall, P/AI for all second and subsequent AI combined did not differ by treatment (P-TAI = 45.2%; P-AIE = 44.5%) or FG (Hi-Fert = 46.1%; Med-Fert = 46.0%; Lo-Fert = 42.4%). The hazard of pregnancy after calving was greater for the P-AIE than the P-TAI treatment [hazard ratio (HR) = 1.27, 95% CI: 1.17 to 1.37)], and for the Hi-Fert than the Med-Fert (HR = 1.16, 95% CI: 1.05 to 1.28) and Lo-Fert (HR = 1.34, 95% CI: 1.20 to 1.49) groups. More cows in the Hi-Fert (91.2%) than the Med-Fert (88.4%) and Lo-Fert (85.8%) groups were pregnant at 200 DIM. Within FG, the hazard of pregnancy was greater for the P-AIE than the P-TAI treatment for the Hi-Fert (HR = 1.41, 95% CI: 1.22 to 1.64) and Med-Fert (HR = 1.28, 95% CI: 1.12 to 1.46) groups but not for the Lo-Fert group (HR = 1.13, 95% CI: 0.98 to 1.31). We conclude that primiparous Holstein cows of superior genetic merit for fertility had better reproductive performance than cows of inferior genetic merit for fertility, regardless of the type of reproductive management used. In addition, the effect of programs that prioritized AIE or TAI on reproductive performance for cows of superior or inferior genetic merit for fertility depended on the outcomes evaluated. Thus, programs that prioritize AIE or TAI could be used to affect certain outcomes of reproductive performance or management.