Genome-enable prediction for health traits using high-density SNP panel in US Holstein cattle

A comprehensive meta-analysis of genetic parameters for resilience and productivity indicator traits in Holstein cattle

Selection for resilience indicator (RIND) traits in Holstein cattle is becoming an important breeding objective as the worldwide population is expected to be exposed to increased environmental stressors due to both climate change and changing industry standards. However, genetic correlations between RIND and productivity indicator (PIND) traits, which are already being selected for and have the most economic value, are often unfavorable. As a result, it is necessary to fully understand these genetic relationships when incorporating novel traits into selection indices, so that informed decisions can be made to fully optimize selection for both groups of traits. In the past 2 decades, there have been many estimates of RIND traits published in the literature, albeit in small populations. To provide valuable pooled summary estimates, a random-effects meta-analysis was conducted for heritability and genetic correlation estimates for PIND and RIND traits in worldwide Holstein cattle. In total, 926 heritability estimates for 9 PIND and 27 RIND traits, along with 362 estimates of genetic correlation (PIND × RIND traits) were collected. Resilience indicator traits were grouped into the following subgroups: Metabolic Diseases, Hoof Health, Udder Health, Fertility, Heat Tolerance, Longevity, and Other. Pooled estimates of heritability for PIND traits ranged from 0.201 ± 0.05 (energy-corrected milk) to 0.377 ± 0.06 (protein content), while pooled estimates of heritability for RIND traits ranged from 0.032 ± 0.02 (incidence of lameness, incidence of milk fever) to 0.497 ± 0.05 (measures of body weight). Pooled estimates of genetic correlations ranged from -0.360 ± 0.25 (protein content vs. milk acetone concentration) to 0.535 ± 0.72 (measures of fat-to-protein ratio vs. milk acetone concentration). Additionally, out of 243 potential genetic correlations between PIND and RIND traits that could have been reported, only 40 had enough published estimates to implement the meta-analysis model. Our results confirmed that the interactions between PIND and RIND traits are complex, and all relationships should be evaluated when incorporating novel traits into selection indices. This study provides a valuable reference for breeders looking to incorporate RIND traits for Holstein cattle into selection indices.

Genetic parameters for health traits and their association with fertility and milk production in Chinese Holsteins

Herd health is one of the key problems influencing the efficiency of the dairy industry. Genetic selection, with a focus on animal health, is important for herd improvement. This study aimed to estimate genetic parameters for health traits and their correlations with fertility and milk production traits in dairy cattle. Based on records from 58,549 lactating cows calved between 2015 and 2021, a total of 24 health traits (six composite health traits and 18 independent health traits), four fertility traits and five milk production traits were analysed. First, linear and threshold animal models were used to estimate the variance components and heritabilities of the health traits. Second, a bivariate linear animal model was used to estimate genetic correlations among all 24 health traits. Finally, a bivariate linear animal model based on records from the first lactation was used to estimate the correlations between health traits and fertility or milk production traits. The results showed that all health traits had low heritabilities, ranging from 0.002 (0.001) to 0.048 (0.004) in the linear model and from <0.001 (0.021) to 0.226 (0.035) in the threshold model. Genetic correlations between health traits across categories were generally low, whereas the relatively high genetic correlations were found between health traits within the same category. In this study, only a few significant and moderate genetic correlations were observed between health traits and fertility or milk production traits. Clinical mastitis showed relatively moderate correlations with fertility traits, ranging from 0.277 (0.113) (interval from first to last insemination) to 0.401 (0.104) (calving interval). Moreover, there were moderate genetic correlations between hoof health and milk production traits. The results from the current study will support balanced dairy breeding to genetically improve disease resistance in dairy cows.

Genome-wide association and genomic prediction for a reproductive index summarizing fertility outcomes in U.S. Holsteins

Subfertility represents one major challenge to enhancing dairy production and efficiency. Herein, we use a reproductive index (RI) expressing the predicted probability of pregnancy following artificial insemination (AI) with Illumina 778K genotypes to perform single and multi-locus genome-wide association analyses (GWAA) on 2,448 geographically diverse U.S. Holstein cows and produce genomic heritability estimates. Moreover, we use genomic best linear unbiased prediction (GBLUP) to investigate the potential utility of the RI by performing genomic predictions with cross validation. Notably, genomic heritability estimates for the U.S. Holstein RI were moderate (h2 = 0.1654 ± 0.0317-0.2550 ± 0.0348), while single and multi-locus GWAA revealed overlapping quantitative trait loci (QTL) on BTA6 and BTA29, including the known QTL for the daughter pregnancy rate (DPR) and cow conception rate (CCR). Multi-locus GWAA revealed seven additional QTL, including one on BTA7 (60 Mb) which is adjacent to a known heifer conception rate (HCR) QTL (59 Mb). Positional candidate genes for the detected QTL included male and female fertility loci (i.e. spermatogenesis and oogenesis), meiotic and mitotic regulators, and genes associated with immune response, milk yield, enhanced pregnancy rates, and the reproductive longevity pathway. Based on the proportion of the phenotypic variance explained (PVE), all detected QTL (n = 13; P ≤ 5e - 05) were estimated to have moderate (1.0% < PVE ≤ 2.0%) or small effects (PVE ≤ 1.0%) on the predicted probability of pregnancy. Genomic prediction using GBLUP with cross validation (k = 3) produced mean predictive abilities (0.1692-0.2301) and mean genomic prediction accuracies (0.4119-0.4557) that were similar to bovine health and production traits previously investigated.

Combined effect of purulent vaginal discharge and anovulation on pregnancy status in a large multi-state population of Holstein cows

The objective of this observational prospective cohort study was to evaluate the combined effect of purulent vaginal discharge (PVD) and anovulation (ANOV) on the reproductive performance of a large multi-state population of Holstein cows. Data were prospectively collected from 11,729 cows in 16 herds located in 4 regions in the United States [Northeast (4 herds), Midwest (6), Southeast (1), and Southwest (5)]. Cows were enrolled at calving and monitored weekly for disease occurrence, reproductive events, and survival. Prevalence of PVD was evaluated at 28 ± 3 d in milk and defined by the presence of mucopurulent to fetid vaginal discharge. Resumption of ovarian cyclicity was determined via transrectal ultrasonography at 40 ± 3 and 54 ± 3 d postpartum. Pregnancy diagnosis was performed by ultrasonography on d 32 ± 3 after artificial insemination (AI) and reconfirmed at d 60 ± 3 of gestation. Pregnancy loss (PL) was defined as a cow diagnosed pregnant at 32 ± 3 but nonpregnant at 60 ± 3 d after AI. The association of PVD and ANOV with pregnancy traits was analyzed using 4 PVD-cyclicity categories that considered the following combinations: NPVD-CYC = absence of PVD and cycling; PVD-CYC = presence of PVD and cycling; NPVD-ANOV = absence of PVD and anovular; and PVD-ANOV = presence of PVD and anovular. Multiple logistic regression and Cox proportional regression were used for the analysis of potential associations between PVD and cyclicity categories and pregnancy at first AI (PAI1), days from calving to pregnancy, and PL at first AI. The odds (95% confidence intervals) of pregnancy increased from cows in the PVD-ANOV category (reference category) to cows in NPVD-ANOV [2.09 (1.62-2.50)], PVD-CYC [2.52 (2.02-3.14)], and NPVD-CYC [3.46 (2.84-4.23)]. Similarly, days from calving to pregnancy were less for NPVD-CYC, followed by PVD-CYC, NPVD-ANOV, and PVD-ANOV (121.4, 137.2, 137.3, and 157.4 d, respectively). On the contrary, no clear association was identified between groups and PL. The results indicate that both PVD and ANOV had a negative impact on PAI1 and days from calving to pregnancy. The results indicated a variable magnitude in the negative impact on the reproductive traits analyzed when both conditions were combined.

The Transition Period Updated: A Review of the New Insights into the Adaptation of Dairy Cows to the New Lactation

Recent research on the transition period (TP) of dairy cows has highlighted the pivotal role of immune function in affecting the severity of metabolic challenges the animals face when approaching calving. This suggests that the immune system may play a role in the etiology of metabolic diseases occurring in early lactation. Several studies have indicated that the roots of immune dysfunctions could sink way before the “classical” TP (e.g., 3 weeks before and 3 weeks after calving), extending the time frame deemed as “risky” for the development of early lactation disorders at the period around the dry-off. Several distressing events occurring during the TP (i.e., dietary changes, heat stress) can boost the severity of pre-existing immune dysfunctions and metabolic changes that physiologically affect this phase of the lactation cycle, further increasing the likelihood of developing diseases. Based on this background, several operational and nutritional strategies could be adopted to minimize the detrimental effects of immune dysfunctions on the adaptation of dairy cows to the new lactation. A suitable environment (i.e., optimal welfare) and a balanced diet (which guarantees optimal nutrient partitioning to improve immune functions in cow and calf) are key aspects to consider when aiming to minimize TP challenges at the herd level. Furthermore, several prognostic behavioral and physiological indicators could help in identifying subjects that are more likely to undergo a “bad transition”, allowing prompt intervention through specific modulatory treatments. Recent genomic advances in understanding the linkage between metabolic disorders and the genotype of dairy cows suggest that genetic breeding programs aimed at improving dairy cows’ adaptation to the new lactation challenges (i.e., through increasing immune system efficiency or resilience against metabolic disorders) could be expected in the future. Despite these encouraging steps forward in understanding the physiological mechanisms driving metabolic responses of dairy cows during their transition to calving, it is evident that these processes still require further investigation, and that the TP—likely extended from dry-off—continues to be “the final frontier” for research in dairy sciences.

Effect of body condition change and health status during early lactation on performance and survival of Holstein cows

Body condition score (BCS) and disease records are commonly available in dairy operations. However, the effect of BCS changes (ΔBCS) considering specific health profiles has not been investigated extensively. The objective of this study was to assess the effects of different levels of ΔBCS on fertility, milk yield, and survival of Holstein cows diagnosed with reproductive disorders (REP; dystocia, twins, retained fetal membranes, metritis, and clinical endometritis), other health disorders (OTH; subclinical ketosis, left displaced abomasum, lameness, clinical mastitis, and respiratory disease), or with no disease events (HLT) within 40 days in milk (DIM). Data included lactation information from 11,733 cows calving between November 2012 and October 2014 in 16 herds across 4 geographical regions in the United States (Northeast, Midwest, Southwest, Southeast). Cows were evaluated for BCS at 5 ± 3 DIM (BCS5) and at 40 ± 3 DIM (BCS40) and the difference between BCS40 and BCS5 was classified as excessive loss of BCS (EL; ΔBCS ≤-0.75), moderate loss (ML; ΔBCS = -0.5 to -0.25), no change (NC; ΔBCS = 0), or gain of BCS (GN; ΔBCS ≥0.25). Multivariable logistic regression was used for assessing potential associations between the outcomes of interest and ΔBCS and health. The effect of the interaction term ΔBCS by health group was not statistically significant for any of the study outcomes. The odds of resumption of ovarian cyclicity (ROC), in GN, NC, and ML cows were 1.94 (95% CI: 1.57-2.40), 1.59 (1.28-1.97), and 1.27 (1.10-1.47) times greater than the odds of ROC in EL cows, respectively. The odds of pregnancy at 150 DIM (P150) in GN cows were 1.61 (1.20-2.17) times greater than the odds of P150 in EL cows. Cows with REP or OTH disorders had smaller odds of ROC compared with HLT cows [REP: OR = 0.65 (0.56-0.76) and OTH: OR = 0.79 (0.68-0.92)]. For pregnancy outcomes, REP cows had smaller odds of pregnancy at the first artificial insemination compared with HLT cows [0.70 (0.58-0.84)]. Similarly, REP cows had smaller odds of being diagnosed pregnant by 150 and 305 DIM compared with HLT cows [P150: 0.73 (0.59-0.87), P305: 0.58 (0.49-0.69)]. Overall, average daily milk within the first 90 DIM was greater in EL (39.5 ± 1.13 kg/d) and ML (38.9 ± 1.11 kg/d) cows than in NC (37.8 ± 1.12 kg/d) and GN (36.2 ± 1.12 kg/d) cows. On the other hand, average daily milk within the first 90 DIM was lower in REP (37.0 ± 1.11 kg/d) cows compared with OTH (38.7 ± 1.12 kg/d) and HLT cows (38.6 ± 1.11 kg/d). The magnitude of ΔBCS and the health status of early lactation cows should be considered when assessing subsequent cow performance and survival.

Serum Vitamin D Is Associated with Antioxidant Potential in Peri-Parturient Cows

Dairy cows experience increased oxidative stress during periods of transition such as at the cessation of lactation and around the periparturient period, thus increasing disease risk. Despite routine supplementation of transition cow diets with certain vitamins in an attempt to mitigate oxidative stress, there is no currently available data directly linking vitamin supplementation with antioxidant potential (AOP) in transition cows. The objective of this study was to determine the association between serum vitamins and biomarkers of oxidative stress in healthy cows. Blood samples were collected from 240 cows at dry off (DO), close up (CU), and 2-10 days post-calving (DIM2-10). Blood samples were analyzed for vitamins (A, D, E), β-carotene, reactive oxygen species (ROS), and AOP. Spearman correlations and mixed linear regression models were used to assess associations between vitamins and measures of oxidant status. Vitamin D concentrations were positively associated with AOP at the CU and DIM2-10. Based on the positive association with AOP, additional in-vitro studies were conducted that showed vitamin D mitigated barrier integrity loss in endothelial cells during oxidative stress. These results indicate for the first time that vitamin D may have a role in promoting antioxidant potential in transition dairy cows.

Genomic Analysis, Progress and Future Perspectives in Dairy Cattle Selection: A Review

Genomics comprises a set of current and valuable technologies implemented as selection tools in dairy cattle commercial breeding programs. The intensive progeny testing for production and reproductive traits based on genomic breeding values (GEBVs) has been crucial to increasing dairy cattle productivity. The knowledge of key genes and haplotypes, including their regulation mechanisms, as markers for productivity traits, may improve the strategies on the present and future for dairy cattle selection. Genome-wide association studies (GWAS) such as quantitative trait loci (QTL), single nucleotide polymorphisms (SNPs), or single-step genomic best linear unbiased prediction (ssGBLUP) methods have already been included in global dairy programs for the estimation of marker-assisted selection-derived effects. The increase in genetic progress based on genomic predicting accuracy has also contributed to the understanding of genetic effects in dairy cattle offspring. However, the crossing within inbred-lines critically increased homozygosis with accumulated negative effects of inbreeding like a decline in reproductive performance. Thus, inaccurate-biased estimations based on empirical-conventional models of dairy production systems face an increased risk of providing suboptimal results derived from errors in the selection of candidates of high genetic merit-based just on low-heritability phenotypic traits. This extends the generation intervals and increases costs due to the significant reduction of genetic gains. The remarkable progress of genomic prediction increases the accurate selection of superior candidates. The scope of the present review is to summarize and discuss the advances and challenges of genomic tools for dairy cattle selection for optimizing breeding programs and controlling negative inbreeding depression effects on productivity and consequently, achieving economic-effective advances in food production efficiency. Particular attention is given to the potential genomic selection-derived results to facilitate precision management on modern dairy farms, including an overview of novel genome editing methodologies as perspectives toward the future.

Early-lactation diseases and fertility in 2 seasons of calving across US dairy herds

The objective of this study was to characterize incidences of health disorders during early lactation in a large population of Holstein cows calving in 2 seasons across multiple US dairy herds. In addition, cumulative effects of combinations of health-related events on fertility and survival by season of calving and parity number were tested. Data were prospectively collected from a total of 11,729 cows in 16 herds located in 2 regions in the United States [north (7,820 cows in 10 herds) and south (3,909 cows in 6 herds)]. Cows were enrolled at parturition and monitored weekly for disease occurrence, reproductive events, and survival. Health-related events were grouped into reproductive disorders (REP; dystocia, twins, retained fetal membranes, metritis, and clinical endometritis) and other disorders (OTH; subclinical ketosis, mastitis, displaced abomasum, and pneumonia). Counts of health events within 50 d postpartum were added into each of the groups and categorized as 0, 1, 2, 3, and ≥4 for REP and 0, 1, 2, and ≥3 for OTH. Multivariable logistic regression was used for testing potential associations between categories of disease occurrence and outcome variables, including resumption of ovarian cyclicity, pregnancy per artificial insemination (AI), pregnancy loss, and survival up to and after 50 DIM. The incidence of disease varied with season of calving and parity, and these 2 variables were associated with the reproductive and survival outcomes. The size of the detrimental effect of disease incidence on reproduction and survival depended on disease group and varied for each specific outcome. Resumption of ovarian cyclicity decreased as incidences of disorders increased in both REP and OTH categories. Pregnancy at first AI also was smaller in greater number of REP categories, but the effect of number of OTH categories on pregnancy at first AI was not consistent. Similarly, pregnancy loss at first AI was not affected consistently by REP or OTH. Survival was reduced by REP and OTH. The magnitude of these negative effects was variable, depending on season of calving and parity, but consistently increased with the number of health events during early lactation.

Recent advances and future directions for uterine diseases diagnosis, pathogenesis, and management in dairy cows

Researchers, veterinarians, and farmers' pursuit of a consistent diagnosis, treatment, and prevention of uterine diseases remains challenging. The diagnosis and treatment of metritis is inconsistent, a concerning situation when considered the global threat of antimicrobial resistance dissemination. Endometritis is an insidious disease absent on routine health programs in many dairy farms and from pharmaceutical therapeutics arsenal in places like the US market. Conversely, a multitude of studies advanced the understanding of how uterine diseases compromise oocyte, follicle, and embryo development, and the uterine environment having long-lasting effects on fertility. The field of uterine disease microbiome also experienced tremendous progress and created opportunities for the development of novel preventives to improve the management of uterine diseases. Activity monitors, biomarkers, genomic selection, and machine learning predictive models are other innovative developments that have been explored in recent years to help mitigate the negative impacts of uterine diseases. Albeit novel tools such as vaccines for metritis, immune modulators, probiotics, genomic selection, and selective antimicrobial therapy are promising, further research is warranted to implement these technologies in a systematic and cost-effective manner.