Phenotypic analysis of pregnancy effect on milk, fat, and protein yields of Canadian Ayrshire, Jersey, Brown Swiss, and Guernsey breeds

Association between days post-conception and lactation persistency in dairy cattle

Determining the optimal insemination moment for individual cows is complex, particularly when considering the effects of pregnancy on milk production. The effect of pregnancy on the absolute milk yield has already been reported in several studies. Currently, there is limited quantitative knowledge about the association between days post-conception (DPC) and lactation persistency, based on a lactation curve model, and, specifically, how persistency changes during pregnancy and relates to the days in milk at conception (DIMc). Understanding this association might provide valuable insights to determine the optimal insemination moment. This study, therefore, aimed to investigate the association between DPC and lactation persistency, with an additional focus on the influence of DIMc. Available milk production data from 2005 to 2022 were available for 23,908 cows from 87 herds located throughout the Netherlands and Belgium. Persistency was measured by a lactation curve characteristic decay, representing the time taken to halve milk production after peak yield. Decay was calculated for 8 DPC (0, 30, 60, 90, 120, 150, 180, and 210 d after DIMc) and served as the dependent variable. Independent variables included DPC, DIMc (≤60, 61-90, 91-120, 121-150, 151-180, 181-210, >210), parity group, DPC × parity group, DPC × DIMc, and variables from 30 d before DIMc as covariates. The results showed an increase in decay, which is to say, a decrease in persistency, during pregnancy for both parity groups, albeit in different ways. Specifically, from DPC 150 to DPC 210, multiparous cows showed a greater decline in persistency compared with primiparous cows. Furthermore, a later DIMc (cows conceiving later) was associated with higher persistency. Except for the early DIMc groups (DIMc <90), DIMc does not affect the change in persistency by gestation. The findings from this study contribute to a better understanding of how DPC and DIMc during lactation influence lactation persistency, enabling more informed decision-making by farmers who wish to take persistency into account in their reproduction management.

Association between Days Open and Parity, Calving Season or Milk Spectral Data

Milk spectral data on 2118 cows from nine herds located in northern China were used to access the association of days open (DO). Meanwhile, the parity and calving season of dairy cows were also studied to characterize the difference in DO between groups of these two cow-level factors. The result of the linear mixed-effects model revealed that no significant differences were observed between the parity groups. However, a significant difference in DO exists between calving season groups. The interaction between parity and calving season presented that primiparous cows always exhibit lower DO among all calving season groups, and the variation in DO among parity groups was especially clearer in winter. Survival analysis revealed that the difference in DO between calving season groups might be caused by the different P/AI at the first TAI. In addition, the summer group had a higher chance of conception in the subsequent services than other groups, implying that the micro-environment featured by season played a critical role in P/AI. A weak linkage between DO and wavenumbers ranging in the mid-infrared region was detected. In summary, our study revealed that the calving season of dairy cows can be used to optimize the reproduction management. The potential application of mid-infrared spectroscopy in dairy cows needs to be further developed.

Pregnancy status predicted using milk mid-infrared spectra from dairy cattle

Accurate and timely pregnancy diagnosis is an important component of effective herd management in dairy cattle. Predicting pregnancy from Fourier-transform mid-infrared (FT-MIR) spectroscopy data is of particular interest because the data are often already available from routine milk testing. The purpose of this study was to evaluate how well pregnancy status could be predicted in a large data set of 1,161,436 FT-MIR milk spectra records from 863,982 mixed-breed pasture-based New Zealand dairy cattle managed within seasonal calving systems. Three strategies were assessed for defining the nonpregnant cows when partitioning the records according to pregnancy status in the training population. Two of these used records for cows with a subsequent calving only, whereas the third also included records for cows without a subsequent calving. For each partitioning strategy, partial least squares discriminant analysis models were developed, whereby spectra from all the cows in 80% of herds were used to train the models, and predictions on cows in the remaining herds were used for validation. A separate data set was also used as a secondary validation, whereby pregnancy diagnosis had been assigned according to the presence of pregnancy-associated glycoproteins (PAG) in the milk samples. We examined different ways of accounting for stage of lactation in the prediction models, either by including it as an effect in the prediction model, or by pre-adjusting spectra before fitting the model. For a subset of strategies, we also assessed prediction accuracies from deep learning approaches, utilizing either the raw spectra or images of spectra. Across all strategies, prediction accuracies were highest for models using the unadjusted spectra as model predictors. Strategies for cows with a subsequent calving performed well in herd-independent validation with sensitivities above 0.79, specificities above 0.91 and area under the receiver operating characteristic curve (AUC) values over 0.91. However, for these strategies, the specificity to predict nonpregnant cows in the external PAG data set was poor (0.002-0.04). The best performing models were those that included records for cows without a subsequent calving, and used unadjusted spectra and days in milk as predictors, with consistent results observed across the training, herd-independent validation and PAG data sets. For the partial least squares discriminant analysis model, sensitivity was 0.71, specificity was 0.54 and AUC values were 0.68 in the PAG data set; and for an image-based deep learning model, the sensitivity was 0.74, specificity was 0.52 and the AUC value was 0.69. Our results demonstrate that in pasture-based seasonal calving herds, confounding between pregnancy status and spectral changes associated with stage of lactation can inflate prediction accuracies. When the effect of this confounding was reduced, prediction accuracies were not sufficiently high enough to use as a sole indicator of pregnancy status.

Response to Oxidative Burst-Induced Hypoxia Is Associated With Macrophage Inflammatory Profiles as Revealed by Cellular Genome-Wide Association

Background

In mammalian species, hypoxia is a prominent feature of inflammation. The role of hypoxia in regulating macrophage responses via alteration in metabolic pathways is well established. Recently, oxidative burst-induced hypoxia has been shown in murine macrophages after phagocytosis. Despite the available detailed information on the regulation of macrophage function at transcriptomic and epigenomic levels, the association of genetic polymorphism and macrophage function has been less explored. Previously, we have shown that host genetics controls approximately 80% of the variation in an oxidative burst as measured by nitric oxide (NO^-). Further studies revealed two clusters of transcription factors (hypoxia-related and inflammatory-related) are under the genetic control that shapes macrophages’ pro-inflammatory characteristics.

Material and Methods

In the current study, the association between 43,066 autosomal Single Nucleic Polymorphism (SNPs) and the ability of MDMs in production of NO^- in response to E. coli was evaluated in 58 Holstein cows. The positional candidate genes near significant SNPs were selected to perform functional analysis. In addition, the interaction between the positional candidate genes and differentially expressed genes from our previous study was investigated.

Results

Sixty SNPs on 22 chromosomes of the bovine genome were found to be significantly associated with NO^- production of macrophages. The functional genomic analysis showed a significant interaction between positional candidate genes and mitochondria-related differentially expressed genes from the previous study. Further examination showed 7 SNPs located in the vicinity of genes with roles in response to hypoxia, shaping approximately 73% of the observed individual variation in NO^- production by MDM. Regarding the normoxic condition of macrophage culture in this study, it was hypothesized that oxidative burst is responsible for causing hypoxia at the cellular level.

Conclusion

The results suggest that the genetic polymorphism via regulation of response to hypoxia is a candidate step that perhaps shapes macrophage functional characteristics in the pathway of phagocytosis leading to oxidative burst, hypoxia, cellular response to hypoxia and finally the pro-inflammatory responses. Since all cells in one individual carry the same alleles, the effect of genetic predisposition of sensitivity to hypoxia will likely be notable on the clinical outcome to a broad range of host-pathogen interactions.

Phenotypic and genetic effects of pregnancy on milk production traits in Holstein-Friesian cattle

Pregnancy is a prerequisite for the initiation of lactation and for maintaining the milk production cycle. Pregnancy affects milk production and therefore should be accounted for in the genetic evaluation. Furthermore, there might be genetic differences in pregnancy effects on milk composition. The objective of this study was to estimate phenotypic and genetic effects of pregnancy on milk production traits. For this purpose, test-day records and conception dates of 1,359 first-parity Holstein-Friesian cows were analyzed. Significant effects of pregnancy on all milk production traits were detected except somatic cell score (e.g., the cumulative effects of pregnancy on milk yield were -247 kg). The pregnancy effects on milk yield, lactose yield, protein yield, fat yield, and fat content were small during early gestation (<150 d) and substantially increased in late gestation. The effects of pregnancy on milk protein yield were relatively stronger than those on fat yield. The effects of pregnancy on milk production traits differed for DGAT1 genotypes. Milk yield, lactose yield, protein yield, and fat yield of DGAT1 AA cows were more affected by pregnancy than that of DGAT1 KK cows (e.g., the cumulative effects of pregnancy on milk yield were negligible for DGAT1 KK cows and were -443 kg for DGAT1 AA cows). These results suggest that DGAT1 KK cows may be more suitable for shortening or omitting the dry period than DGAT1 AA cows.

Genome-wide association study for genotype by lactation stage interaction of milk production traits in dairy cattle

Substantial evidence demonstrates that the genetic background of milk production traits changes during lactation. However, most GWAS for milk production traits assume that genetic effects are constant during lactation and therefore might miss those quantitative trait loci (QTL) whose effects change during lactation. The GWAS for genotype by lactation stage interaction are aimed at explicitly detecting the QTL whose effects change during lactation. The purpose of this study was to perform GWAS for genotype by lactation stage interaction for milk yield, lactose yield, lactose content, fat yield, fat content, protein yield, and somatic cell score to detect QTL with changing effects during lactation. For this study, 19,286 test-day records of 1,800 first-parity Dutch Holstein cows were available and cows were genotyped using a 50K SNP panel. A total of 7 genomic regions with effects that change during lactation were detected in the GWAS for genotype by lactation stage interaction. Two regions on Bos taurus autosome (BTA)14 and BTA19 were also significant based on a GWAS that assumed constant genetic effects during lactation. Five regions on BTA4, BTA10, BTA11, BTA16, and BTA23 were only significant in the GWAS for genotype by lactation stage interaction. The biological mechanisms that cause these changes in genetic effects are still unknown, but negative energy balance and effects of pregnancy may play a role. These findings increase our understanding of the genetic background of lactation and may contribute to the development of better management indicators based on milk composition.

Evaluation of automatic milking system variables in dairy cows with different levels of lactation stage and reproduction status

In this study, we hypothesized that differences of automatic milking systems (AMS) variables in dairy cows during estrus and through diverse stages of lactation can be suggested as alternative indicators to support the pregnancy in dairy farms using automatic milking systems. The key objectives were: (1) to determine the variation of automatic milking system indicators during lactation and to estimate the relationship with reproduction status in dairy cows; (2) to test the hypothesis that milking traits of cows can be influenced by estrus and conceiving, and can be used as a predictor of the likelihood of reproductive success in dairy herds. Estrus synchronization was performed in 368 healthy Lithuanian Black and White cows. All cows (n = 368) were synchronized and inseminated for the first time on the 91st day in milk (DIM). Cows not pregnant (17.39%) were synchronized and inseminated again at 132 DIM. After the first insemination pregnant (n = 304) cows were identified as group 1, after the second insemination pregnant (n = 58) cows - as group 2. Overall, 12 01 713 records of udder quarters in cows from 5 to 305 DIM were evaluated. The results revealed the reduction in milk yield during estrus 11.05% on 91 DIM and 13.89% on 132 DIM (P < 0.001) and an increment in milk flow traits in cows after 91 DIM (P < 0.05), also a slight decline in milk flow traits on 132 DIM. Furthermore, milking frequency (MF) of cows decreased significantly (P < 0.001) after conceiving. The interval between milkings (MI) increased (40.30%) during estrus of cows in group 1 (P < 0.001), and thereafter gradually increased, however in group 2 there was a temporary increment (6.06%) on the 91 DIM and steady rise (42.13%) on 132 DIM was noticed. The results highlight that changes in AMS indicators of cows may be considered as an additional tool for improvement of reproductive management in dairy herds, but further research-based studies are necessary before practical application.

The effect of host genetics on in vitro performance of bovine monocyte-derived macrophages

The dynamic interaction between the host and pathogens, along with environmental factors, influences the regulation of mammalian immune responses. Therefore, comprehensive in vivo immune-phenotyping during an active response to a pathogen can be complex and prone to confounding effects. Evaluating critical fundamental aspects of the immune system at a cellular level is an alternative approach to reduce this complexity. Therefore, the objective of the current study was to examine an in vitro model for functional phenotyping of bovine monocyte-derived macrophages (MDM), cells which play a crucial role at all phases of inflammation, as well influence downstream immune responses. As indicators of MDM function, phagocytosis and nitric oxide (NO^-) production were tested in MDM of 16 cows in response to 2 common bacterial pathogens of dairy cows, Escherichia coli and Staphylococcus aureus. Notable functional variations were observed among the individuals (coefficient of variation: 33% for phagocytosis and 70% in the production of NO^-). The rank correlation analysis revealed a significant, positive, and strong correlation (rho = 0.92) between NO^- production in response to E. coli and S. aureus, and a positive but moderate correlation (rho = 0.58) between phagocytosis of E. coli and S. aureus. To gain further insight into this trait, another 58 cows were evaluated solely for NO^- response against E. coli. The pedigree of the tested animals was added to the statistical model and the heritability was estimated to be 0.776. Overall, the finding of this study showed a strong effect of host genetics on the in vitro activities of MDM and the possibility of ranking Holstein cows based on the in vitro functional variation of MDM.

Using geometric morphometrics for the genetics analysis of shape and size of lactation curves in Israeli first-parity Holstein cattle

Our objective was to combine the methods of geometric morphometrics and multivariate quantitative genetics to genetic evaluation of the size and shape of lactation curves of milk of 3,492 Israeli first-parity Holstein cattle. Lactation records were treated as morphological data, for which 2 different lactation shape functions were evaluated, one depicted by a line graph and the other by an orbital graph. The lactation curves from both shape functions were represented by 2-dimensional Cartesian landmark coordinates. The 2 sets of landmarks were then analyzed individually for each shape function with geometric morphometrics to separate variation into components of size and shape. The analysis yielded 2 size measures and 2 sets of shape variables, and they were the inputs to estimate variance components using the MTC REML individual animal model program. Variance components were also estimated for the 305-d lactation production as a reference. Shape variables showed negligible correlation with 305-d production, providing evidence of size and shape of lactation curve as separate characters. The size measure derived from the orbital-depicted lactation curve had equal heritability (0.39 ± 0.01; ± standard error) and complete genetic and environmental correlations with 305-d production, whereas the size measure derived from the line-depicted lactation curve showed low heritability (0.09 ± 0.01) and environmental correlation (0.02 ± 0.004) and relative high genetic correlation with 305-d production (0.48 ± 0.04). This may validate both the orbital graph to depict lactation records and the use of geometric morphometrics to split variation of lactation curve into size and shape components. The maximal heritability for shape of lactation curve was 0.55 for orbital- and 0.56 for line-depicted lactation curves. The respective patterns of variations were visualized as shape changes from the mean shape in the data set. Geometric morphometrics are well grounded within the theory of shape analysis and can be paired with conventional methods in the field to characterize the patterns of phenotypic and genetic variation of shape and size of lactation curve in dairy cattle.

Ovarian activity and embryo yield in relation to the postpartum period in superovulated dairy cows

The aim of this study was to evaluate superovulation response in cows at various postpartum periods (early postpartum period up to 3.5 months; middle postpartum period 3.7–7 months; later postpartum period above 7.5 months after calving). The data included observation of 55 Holstein cows superovulated at one farm in the Czech Republic during the years 2010 and 2013. Reproduction traits (dependent variable) were represented as number of the corpora lutea, number of transferable embryos, morulae, blastocysts, total number of embryos and embryo recovery. For statistical evaluation we used the PROC GLM of SAS® with fixed effect - breeding value of milk production. The study results show significant differences (P < 0.05–0.01) in the three postpartum periods (early, middle, and later postpartum periods) and the number of corpora lutea (4.6; 7.4; 10.8), number of total embryos (3.2; 2.9; 6.5) and transferable embryos (1.8; 1.7; 4.4). Effective timing of embryo transfer in the later postpartum period resulted in greater ovarian activity and embryo yield compared to early lactation periods.

Effect of pregnancy on the genetic evaluation of dairy cattle

We investigated the effect of stage of pregnancy on estimates of breeding values for milk yield and milk persistency in Gyr and Holstein dairy cattle in Brazil. Test-day milk yield records were analyzed using random regression models with or without the effect of pregnancy. Models were compared using residual variances, heritabilities, rank correlations of estimated breeding values of bulls and cows, and number of nonpregnant cows in the top 200 for milk yield and milk persistency. The estimates of residual variance and heritabilities obtained with the models with or without the effect of pregnancy were similar for the two breeds. Inclusion of the effect of pregnancy in genetic evaluation models for these populations did not affect the ranking of cows and sires based on their predicted breeding values for 305-day cumulative milk yield. In contrast, when we examined persistency of milk yield, lack of adjustment for the effect of pregnancy overestimated breeding values of nonpregnant cows and cows with a long days open period and underestimated breeding values of cows with a short days open period. We recommend that models include the effect of days of pregnancy for estimation of adjustment factors for the effect of pregnancy in genetic evaluations of Dairy Gyr and Holstein cattle.

Short communication: effect of preadjusting test-day yields for stage of pregnancy on variance component estimation in Canadian Ayrshires

Preadjustment of phenotypic records is an alternative to accounting for the effect of pregnancy within the genetic evaluation model. Variance components used in the Canadian Test-Day Model may need to be re-estimated after preadjusting for pregnancy. The objective of this study was to assess the effect of preadjusting test-day yields on variance components and estimated breeding values using a random regression test-day model in a random sample of Ayrshire cows. A random sample of 981 Canadian Ayrshire cows from 18 complete herds (average of 54.5 cows/herd) was analyzed. Two data sets were created using the same animals, one with unadjusted milk, fat, and protein yields, and one data set with test-day records adjusted for pregnancy effects. Pregnancy effect estimates from a previous study were used for additive preadjustment of records. Variance components were estimated using both data sets. Results were very similar between the 2 data sets for all estimated genetic parameters (heritabilities, genetic, and permanent environmental correlations). The relative squared differences were very small: 0.05% for heritabilities, 0.20% for genetic correlations, and 0.18% for permanent environmental correlations. Furthermore, paired Student's t-tests showed that the differences between the genetic parameters of data sets adjusted and unadjusted for pregnancy effect were not significantly different from 0. Results from this study show that preadjusting data for pregnancy did not yield changes in covariance component estimates, thus suggesting that preadjusting test-day records could be a feasible solution to account for pregnancy in the Canadian Test-Day Model without changing the current model. Estimated breeding values (EBV) were calculated for both data sets to observe the impact of preadjusting for pregnancy. Overall, the largest changes in EBV seen when preadjusting for pregnancy (compared with unadjusted records) occurred for nonpregnant elite cows, whose EBV declined. Preadjusting for pregnancy before genetic evaluations improves the estimation of breeding values by adding the negative impact of pregnancy back onto pregnant cow test-day records, causing an increase in their production EBV.