Genetic analysis of health traits and their associations with longevity, fertility, production, and conformation traits in Holstein cattle

Health traits have high economic values in dairy cattle breeding, which can cause considerable financial loss through involuntary culling. In this study, fourteen health traits were analysed, including five composite health traits: reproductive disorders, udder health (UH), digestive disorders, metabolic disorders, locomotory diseases (LD), and nine independent health traits: gestation disorders and peripartum disorders, irregular estrus cycle and sterility, metritis (ME), mastitis (MA), abomasal displacement (AD), enteritis (EN), and ketosis, claw diseases (CD), laminitis complex. This study analysed variance components for health traits through both single and bivariate repeatability animal models. All health traits showed low heritability, ranging from 0.001 to 0.025. Most of the health traits in five categories showed negative genetic correlations, ranging from -0.012 (CD and EN) to -0.634 (ME and EN). Strong positive genetic correlations appeared within the same category, ranging from 0.469 (EN and AD) to 0.994 (UH and MA, LD and CD). Furthermore, approximate genetic correlations were evaluated between health traits and routinely collected traits (longevity, fertility, production, and conformation). In general, the low to moderate approximate genetic correlations were estimated between health traits and routinely collected traits. The estimated correlations between health traits and longevity, fertility, production, and conformation traits could provide an indirect reference for disease-resistance breeding in Holstein cattle.

Heritability of subclinical endometritis in Norwegian Red cows

Subclinical endometritis (SCE) is highly prevalent in dairy cows, causing negative effects on reproductive outcomes and the producer economy. Genetic selection for animals with better resilience against uterine disease should be prioritized due to both sustainability and animal welfare. Therefore, the aim of the present study was to estimate the heritability of SCE in the Norwegian Red (NR) population. Moreover, future perspectives of the condition as a fertility phenotype for breeding are discussed. A total of 1,642 NR cows were sampled for SCE at the time of artificial insemination, using cytotape. The percentage of polymorphonuclear cells (PMN) in each sample was established by cytology, through the counting of 300 PMN and epithelial cells. The mean percentage of PMN was 5%. Different trait definitions were examined, and SCE was defined as binary traits, based on the following cut-off levels of PMN: Cyto0 = PMN >0, Cyto3 = PMN >3%, Cyto5 = PMN >5%, Cyto10 = PMN >10%, and Cyto20 = PMN >20%. The mean ranged from 0.07 (Cyto20) to 0.59 (Cyto0). We also analyzed PMN as a continuous variable using percent PMN. Information on the animals and herds was obtained from the Norwegian Dairy Herd Recording System. The pedigree of cows with data included a total of 24,066 animals. A linear animal model was used to estimate the heritability. The only trait definition that had an estimated genetic variance larger than the standard error was Cyto5, with an estimated heritability of 0.04. For all other definitions, the genetic variance was not significantly different from zero. A cut-off level of 5% PMN has been established as a general threshold for the definition of SCE in earlier literature. The standard errors of the estimated variance components were relatively large, and results should be interpreted with caution. However, the current study indicates that SCE is heritable at a similar level to that of clinical endometritis and metritis, and has potential as a future fertility phenotype to be used for breeding purposes. A more feasible method to diagnose SCE is needed to establish larger data sets.

Genomic loci and genetic parameters for uterine diseases in first-parity Holstein cows and associations with milk production and fertility

Based on the clinical stage (e.g., vaginal discharge) and bacterial species, several forms of uterine diseases (UD) exist and can be classified as different traits [i.e., different stages of endometritis (EM) and metritis (MET)], which may differ in their genetic background and causal physiological mechanisms. Consequently, the present study aimed to study (1) the effect of UD on 305-d lactation and fertility, (2) the estimation of heritabilities for UD traits using pedigree- and SNP-based relationships, and (3) genome-wide associations to detect significant SNP markers and to infer candidate genes for UD traits. The data set contained herd manager and veterinarian recorded UD traits of 14,810 first-lactating genotyped Holstein cows from 63 large-scale contract herds. Binary defined UD traits (healthy or diseased) according to the clinical stage were endometritis catarrhalis (EM I), endometritis mucopurulenta (EM II), endometritis purulenta (EM III), pyometra (EM IV), endometritis (EM_SOD; superordinate diagnosis = no specific clinical stage defined), and MET. The binary defined trait UDall included all EM and MET diagnoses. The prevalence of UDall was 26.7%. The effect of UD on 305-d lactation and fertility was estimated via linear and generalized linear mixed models. We applied linear single-trait animal models and threshold models to estimate pedigree- and SNP-based heritabilities for UD traits, and bivariate linear models for genetic correlation estimations between UDall with 305-d lactation and fertility traits. A diagnosis for UDall had significant unfavorable effects on the female fertility traits calving interval, interval from calving to first service, days open, and nonreturn rate after 90 d, but was unrelated to 305-d lactation records for production traits milk yield, protein yield, and fat yield. Heritabilities for UDall and EM stages were close to zero, displaying maximal values of 0.05 for pedigree and 0.07 for SNP-based relationship matrices. For MET, pedigree- and SNP-based heritabilities were <0.001 and 0.07, respectively. Genetic correlations ranged from 0.20 to 0.31 between UDall with 305-d milk, protein, and fat yield, and from 0.17 to 0.40 with fertility traits. The GWAS revealed 5 SNP on bovine chromosomes (BTA) 1, 8, 10, 23 for UDall, 5 SNP on BTA 26 for EM I, 1 SNP on BTA 19 for EM II, 4 SNP on BTA 2, 18, 20, 25 for EM III, and 4 SNP on BTA 4, 16, 20 for EM IV above the significance threshold. For EM_SOD, we identified 15 significantly associated SNP on 4 chromosomes, and 4 significant SNP on BTA 3, 20, 22, 28 for MET. Marker associations for UD traits were annotated to 24 potential candidate genes using the ENSEMBL database. Six of these genes were previously reported to be involved in uterine defense mechanisms or in endometritis. Further detected genes contribute to immune response mechanisms during bacterial infections. Different SNP significantly influenced different UD stages, explaining the inter-individual variations in clinical severity of uterine infections.

Genetic parameters and weighted single-step genome-wide association study for supernumerary teats in Holstein cattle

Supernumerary teats (SNT) are a common epidermal abnormality of udders in mammals. The SNT negatively affect machine milking ability, udder health, and animal welfare and sometimes act as reservoirs for undesirable bacteria, resulting in economic losses on calves and lactating cows due to the cost of SNT removal surgery, early culling, and low milk yield. This study aimed to analyze the incidence and genetic parameter of SNT and detect SNT-related genes in Chinese Holstein cattle. In this study, the incidence of SNT was recorded in 4,670 Chinese Holstein cattle (born between 2008 and 2017) from 2 farms, including 734 genotyped cows with 114,485 SNPs. The SNT had a total frequency of 9.8% and estimated heritability of 0.22 (SE = 0.07), which were obtained using a threshold model in the studied Chinese Holstein population. Furthermore, we calculated approximate genetic correlations between SNT and the following indicator traits: 12 milk production, 28 body conformation, 5 fertility and reproduction, 5 health, and 9 longevity. Generally, the estimated correlations, such as 305-d milk yield for third parity (-0.55; SE = 0.02) and age at first calving in heifer (0.19; SE = 0.03), were low to moderate. A single-step GWAS was implemented, and 10 genes associated with SNT located in BTA4 were identified. The region (112.70-112.90 Mb) on BTA4 showed the highest genetic variance for SNT. The quantitative trait loci on BTA4 was mapped into the RARRES2 gene, which was previously shown to affect adipogenesis and hormone secretion. The WIF1 gene, which was located in BTA5, was also considered as a candidate gene for SNT. Overall, these findings provide useful information for breeders who are interested in reducing SNT.

Single-step genomic best linear unbiased predictor genetic parameter estimations and genome-wide associations for milk fatty acid profiles, interval from calving to first insemination, and ketosis in Holstein cattle

Milk fatty acids (FA) have been suggested as biomarkers for early-lactation metabolic diseases and for female fertility status. The aim of the present study was to infer associations between FA, the metabolic disorder ketosis (KET), and the interval from calving to first insemination (ICF) genetically and genomically. In this regard, we focused on a single-step genomic BLUP approach, allowing consideration of genotyped and ungenotyped cows simultaneously. The phenotypic data set considered 38,375 first-lactation Holstein cows, kept in 45 large-scale co-operator herds from 2 federal states in Germany. The calving years for these cows were from 2014 to 2017. Concentrations in milk from the first official milk recording test-day for saturated, unsaturated (UFA), monounsaturated (MUFA), polyunsaturated, palmitic, and stearic (C18:0) FA were determined via Fourier-transform infrared spectroscopy. Ketosis was defined as a binary trait according to a veterinarian diagnosis key, considering diagnoses within a 6-wk interval after calving. A subset of 9,786 cows was genotyped for 40,989 SNP markers. Variance components and heritabilities for all Gaussian distributed FA and for ICF, and for binary KET were estimated by applying single-step genomic BLUP single-trait linear and threshold models, respectively. Genetic correlations were estimated in series of bivariate runs. Genomic breeding values for the single-step genomic BLUP estimations were dependent traits in single-step GWAS. Heritabilities for FA were moderate in the range from 0.09 to 0.20 (standard error = 0.02-0.03), but quite small for ICF (0.08, standard error = 0.01) and for KET (0.05 on the underlying liability scale, posterior standard deviation = 0.02). Genetic correlations between KET and UFA, MUFA, and C18:0 were large (0.74 to 0.85, posterior standard deviation = 0.14-0.19), and low positive between KET and ICF (0.17, posterior standard deviation = 0.22). Genetic correlations between UFA, MUFA, and C18:0 with ICF ranged from 0.34 to 0.46 (standard error = 0.12). In single-step GWAS, we identified a large proportion of overlapping genomic regions for the different FA, especially for UFA and MUFA, and for saturated and palmitic FA. One identical significantly associated SNP was identified for C18:0 and KET on BTA 15. However, there was no genomic segment simultaneously significantly affecting all trait categories ICF, FA, and KET. Nevertheless, some of the annotated potential candidate genes DGKA, IGFBP4, and CXCL8 play a role in lipid metabolism and fertility mechanisms, and influence production diseases in early lactation. Genetic and genomic associations indicate that Fourier-transform infrared spectroscopy FA concentrations in milk from the first official test-day are valuable predictors for KET and for ICF.

Autoregressive model for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle

Reproductive efficiency is major determinant of the dairy herd profitability. Thus, reproductive traits have been widely used as selection objectives in the current dairy cattle breeding programs. We aimed to evaluate strategies to model days open (DO), calving interval (CI) and daughter pregnancy rate (DPR) in Brazilian Holstein cattle. These reproductive traits were analysed by the autoregressive (AR) model and compared with classical repeatability (REP) model using 127,280, 173,092 and 127,280 phenotypic records, respectively. The first three calving orders of cows from 1,469 Holstein herds were used here. The AR model reported lower values for Akaike Information Criteria and Mean Square Errors, as well as larger model probabilities, for all evaluated traits. Similarly, larger additive genetic and lower residual variances were estimated from AR model. Heritability and repeatability estimates were similar for both models. Heritabilities for DO, CI and DPR were 0.04, 0.07 and 0.04; and 0.05, 0.06 and 0.04 for AR and REP models, respectively. Individual EBV reliabilities estimated from AR for DO, CI and DPR were, in average, 0.29, 0.30 and 0.29 units higher than those obtained from REP model. Rank correlation between EBVs obtained from AR and REP models considering the top 10 bulls ranged from 0.72 to 0.76; and increased from 0.98 to 0.99 for the top 100 bulls. The percentage of coincidence between selected bulls from both methods increased over the number of bulls included in the top groups. Overall, the results of model-fitting criteria, genetic parameters estimates and EBV predictions were favourable to the AR model, indicating that it may be applied for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle.

Autoregressive repeatability model for genetic evaluation of longitudinal reproductive traits in dairy cattle

We investigated the efficiency of the autoregressive repeatability model (AR) for genetic evaluation of longitudinal reproductive traits in Portuguese Holstein cattle and compared the results with those from the conventional repeatability model (REP). The data set comprised records taken during the first four calving orders, corresponding to a total of 416, 766, 872 and 766 thousand records for interval between calving to first service, days open, calving interval and daughter pregnancy rate, respectively. Both models included fixed (month and age classes associated to each calving order) and random (herd-year-season, animal and permanent environmental) effects. For AR model, a first-order autoregressive (co)variance structure was fitted for the herd-year-season and permanent environmental effects. The AR outperformed the REP model, with lower Akaike Information Criteria, lower Mean Square Error and Akaike Weights close to unity. Rank correlations between estimated breeding values (EBV) with AR and REP models ranged from 0.95 to 0.97 for all studied reproductive traits, when the total bulls were considered. When considering only the top-100 selected bulls, the rank correlation ranged from 0.72 to 0.88. These results indicate that the re-ranking observed at the top level will provide more opportunities for selecting the best bulls. The EBV reliabilities provided by AR model was larger for all traits, but the magnitudes of the annual genetic progress were similar between two models. Overall, the proposed AR model was suitable for genetic evaluations of longitudinal reproductive traits in dairy cattle, outperforming the REP model.

Symposium review: The choice and collection of new relevant phenotypes for fertility selection

In dairy production, high fertility contributes to herd profitability by achieving greater production and maintaining short calving intervals. Improved management practices and genetic selection have contributed to reversing negative trends in dairy cow fertility, but further progress is still required. Phenotypes included in current genetic evaluations are largely interval and binary traits calculated from insemination and calving date records. Several indicator traits such as calving, health, variation in body condition score, and longevity traits also apply to genetic improvement of fertility. Several fertility traits are included in the selection indices of many countries, but for improved selection, the development of novel phenotypes that more closely describe the physiology of reproduction and limit management bias could be more effective. Progesterone-based phenotypes can be determined from milk samples to describe the heritable interval from calving to corpus luteum activity, as well as additional measures of cow cyclicity. A fundamental component of artificial insemination practices is the observation of estrus. Novel phenotypes collected on estrous activity could be used to select for cows clearly displaying heat, as those cows are more likely to be inseminated at the right time and therefore have greater fertility performance. On-farm technologies, including in-line milk testing and activity monitors, may allow for phenotyping novel traits on large numbers of animals. Additionally, selection for improved fertility using traditional traits could benefit from refined and accurate recording and implementation of parameters such as pregnancy confirmation and reproductive management strategy, to differentiate embryonic or fetal loss, and to ensure selection for reproductive capability without producer intervention. Opportunities exist to achieve genetic improvement of reproductive efficiency in cattle using novel phenotypes, which is required for long-term sustainability of the dairy cattle population and industry.

Bovine gonadotrophs express anti-Müllerian hormone (AMH): comparison of AMH mRNA and protein expression levels between old Holsteins and young and old Japanese Black females

Anti-Müllerian hormone (AMH) is secreted from ovaries and stimulates gonadotrophin secretion from bovine gonadotroph cells. Other important hormones for endocrinological gonadotroph regulation (e.g. gonadotrophin-releasing hormone, inhibin and activin) have paracrine and autocrine roles. Therefore, in this study, AMH expression in bovine gonadotroph cells and the relationships between AMH expression in the bovine anterior pituitary (AP) and oestrous stage, age and breed were evaluated. AMH mRNA expression was detected in APs of postpubertal heifers (26 months old) by reverse transcription-polymerase chain reaction. Based on western blotting using an antibody to mature C-terminal AMH, AMH protein expression was detected in APs. Immunofluorescence microscopy utilising the same antibody indicated that AMH is expressed in gonadotrophs. The expression of AMH mRNA and protein in APs did not differ between oestrous phases (P&gt;0.1). We compared expression levels between old Holsteins (79.2±10.3 months old) and young (25.9±0.6 months old) and old Japanese Black females (89.7±20.3 months old). The APs of old Holsteins exhibited lower AMH mRNA levels (P&lt;0.05) but higher AMH protein levels than those of young Japanese Black females (P&lt;0.05). In conclusion, bovine gonadotrophs express AMH and this AMH expression may be breed-dependent.