Journal of Dairy Science最新文献

Concentrations of macro minerals and markers of energy balance are often determined in samples that have been stored frozen for a period of time. The objective of this study was to compare concentrations of Ca, P, Mg, nonesterified fatty acids (NEFA) and BHB determined in serum and plasma samples after separation of whole blood within 24 h of collection (fresh sample) and after storage at -18°C for 3 or 6 mo. Non hemolysed blood samples collected into lithium heparin or nonadditive tubes from 76 dairy cows at 21 ± 9 d postpartum (mean ± standard deviation) were used in this study. Serum or plasma was harvested into separate aliquots within 6 h of sample collection for testing as fresh (stored at 4°C until testing within 24 h of sample collection; baseline), and after 3 or 6 mo storage at -18°C on a wet chemistry analyzer. We observed effects of sample type (serum vs plasma) on P, Mg and NEFA concentrations and effects of storage time (0 vs 3 or 6 mo) on Ca, P, Mg, NEFA and BHB concentrations. In addition, effects of storage time were conditional to the sample type for P and BHB concentrations. Effects of sample type and storage for up to 3 mo were minimal, potentially biologically and diagnostically irrelevant for all the evaluated analytes. However, storage for 6 mo may have relevant effects on Ca, P and BHB concentrations. Compared with the baseline concentration, Ca concentration was 0.27 mmol/L less (95% confidence interval (CI) = -0.31 to -0.22 mmol/L). Phosphorus and BHB concentrations were significantly less after 6 mo of storage but the difference varied according to sample type [in mmol/L; P: -0.11 (95% CI = -0.30 to -0.25) in serum and -0.06 (95% CI = -0.26 to -0.21) in plasma; BHB: -0.27 (95% CI = -0.36 to -0.18) in serum and -0.18 (95% CI = -0.23 to -0.13) in plasma]. In conclusion, sample type and storage for up to 3 mo at -18°C effects were minimal, but the potential impact of longer duration of frozen storage on concentrations of Ca, P and BHB should be considered. Further research is needed to corroborate findings from this study and to describe optimum storage conditions for samples when timely testing is not feasible.

Milk fat content is a polygenic commercially important quantitative trait in ruminants. In recent decades, an increasing number of genes involved in milk fat synthesis have been identified through genome-wide association studies and validated using functional assays such as gene knockdown or overexpression. However, functional validation assays have been limited to small number of related genes, yielding insufficient data to fully understand the many different genes and biological processes in milk fat synthesis. To provide a comprehensive evaluation of the genes involved in milk fat synthesis, we performed a meta-analysis of 1, 395 effect sizes from 81 publications, which included 137 genes, spanning 4 ruminant species. In the studies analyzed knockdown/overexpression of candidate genes significantly reduced/increased Target Gene (Protein) and Related Gene (Protein) expression, and these effects were consistent across species. However, the effects of knockdown/overexpression of candidate genes across the different pathways of milk fat synthesis varied between species. Pathways related to milk fat synthesis, SREBP-, PPAR-, JAK-AKT- and the Insulin-pathway exhibited the largest effects on the synthesis of triglyceride, lipid droplet, cholesterol and unsaturated fatty acids, respectively. Key genes in these pathways, SREBPs (SREBP1, SREBF1), PPARs (PPARA, PPARD, PPARG), JAK2, STAT5α and INSIGs (INSIG1 and INSIG2) also have a greater effect on regulating the formation of triglyceride, cholesterol, lipid droplets and unsaturated fatty acids. Overall, our findings indicated that milk fat synthesis is regulated by multiple pathways and many different genes. Further studies are needed to confirm these findings and to understand the mechanisms underlying species- and pathway-specific responses during milk fat synthesis.

Improved methods previously developed for tracking new mutations within existing haplotypes for cholesterol deficiency (HCD) and muscle weakness (HMW) now also were applied to track the bovine lymphocyte intestinal retention defect (BLIRD) discovered in France. Gene tests were available in US data for HCD and HMW but not yet for BLIRD. Haplotype status for 3 million genotyped animals that also had US phenotypes were used to compare recessive effects of BLIRD homozygotes with French estimates. Heifer livability was 97.6% for normal calves with no copies of the haplotype (code 0) but averaged 88.8% for 178 homozygotes (code 2) and 94.1% for 2,029 uncertain homozygotes (code 4) with corresponding estimates of -8.6% and -3.3% from an animal model. Haplotype carriers verified by pedigree (code 1) or uncertain carriers (code 3) were not affected. Yield trait effects for 412 code 2 homozygotes were -1,799 kg milk, -63 kg fat, and -55 kg protein with a cost of -$1,206 using lifetime net merit values; other traits not yet studied may increase that cost. Mating a BLIRD carrier randomly to a population with 8.9% allele frequency would cause an economic loss of $1,653 * 0.089 / 2 = $74 because half of the progeny would inherit the carrier's normal allele. Those losses should already be reflected in evaluations which average the merit across normal, carrier, and homozygous daughters. Genomic predictions do not fully track those losses because new mutations are poorly correlated with nearby markers. However, US adjustments for future inbreeding automatically reduce evaluations of popular ancestors by more than the cost of these individual defects. Gene tests are needed for new mutations within common haplotypes because tracking can be difficult even with accurate pedigrees.

Suboptimal concentrations of circulating progesterone (P4) in the early postovulatory period have been associated with low fertility observed in high-producing lactating dairy cows. The administration of human chorionic gonadotropin (hCG) increases P4 in cattle by stimulating its endogenous production by the corpus luteum (CL) and creating an accessory CL if administered at an appropriate stage of the cycle. The aim of this study was to evaluate the effect of a single administration of hCG on d 2 of the estrus cycle on circulating P4 concentrations and pregnancy per artificial insemination (P/AI) in high-producing lactating dairy cows in confinement systems. To that end, 796 lactating Holstein-Friesian dairy cows from 15 farms were enrolled on this study. The mean ± SD parity and DIM at enrollment were 2.3 ± 1.4 and 86.7 ± 17.8, respectively. After a voluntary waiting period (50-60 d after calving), cows underwent fixed-time AI (FTAI) following a routine protocol for synchronization of ovulation (Double Ovsynch, G6G, or 7-d Ovsynch + P4). Cows on each farm were blocked on parity, DIM, BCS, and synchronization protocol and were randomly assigned to receive either 3,000 IU of hCG (n = 420) or an equivalent volume of saline solution (control; n = 376) on d 2 after estimated estrus (~16 h before FTAI = d 0). Blood samples were collected from a subset of cows from both treatments (control n = 65 and hCG n = 65) on d 0, 7, and 14 of the estrus cycle to measure serum P4 concentrations. Pregnancy per AI on d 30 after FTAI was affected by hCG treatment and parity. Moreover, there was a tendency for an interaction between treatment and parity. Overall, treatment with hCG on d 2 of the estrus cycle increased P/AI (45.2% vs. control 38.8%). In ≤2nd lactation cows, P/AI was similar between hCG-treated and control cows (47.1% vs. control 45.9%). Conversely, ≥3rd lactation cows treated with hCG had greater P/AI (42.1% vs. control 27.3%). The overall incidence of pregnancy loss between d 30 and d 70 was 14.7% and was not affected by treatment. Cows treated with hCG had higher P4 concentrations on d 7 and 14 compared with control cows (3.4 ± 0.66 vs. 3.0 ± 0.58 ng/mL and 6.6 ± 1.28 vs. 5.3 ± 1.02 ng/mL, respectively). Moreover, an interaction between treatment and parity revealed that P4 concentrations were higher in hCG-treated ≥3rd lactation cows compared with control cows in the same parity group on d 7 and 14, while no differences were observed in ≤2nd lactation cows. In conclusion, administration of hCG on d 2 of the estrus cycle increased fertility in ≥3rd lactation high-producing dairy cows in association with an early increase of circulating P4.

A2 β-CN milk has gained widespread acceptance due to its nutritional benefits. To verify the authenticity and detect adulteration and contamination in A2 milk, we developed an HPLC-MS/MS method for determining the characteristic peptides of A1 and A2 β-CN in cow milk. The method demonstrated good specificity, sensitivity, and linearity for both A1 and A2 characteristic peptides, with limit of detection of 0.01 mg/L and 0.03 mg/L, limit of quantitation of 0.03 mg/L and 0.1 mg/L, and determination coefficients of 0.9994 and 0.9992, respectively. Whereas accuracy and precision were reasonable, the recoveries varied (69.4%-151%) across concentration levels (0.04, 0.2, 1.0 g/kg), with higher recoveries for both peptides at low concentrations and lower recoveries for A2 peptide at medium and high concentrations, influenced by factors such as adsorption and ionization efficiency. We optimized the tryptic hydrolysis conditions, selecting a trypsin-to-casein ratio of 1:25 and a hydrolysis time of 6 h at 37°C. However, the hydrolysis of A1 and A2 β-CN was incomplete and asynchronous, exhibiting parabolic relationships with their respective concentrations, with hydrolysis degrees of 12.3% for A1 β-CN and 9.6% for A2 β-CN in pure powders. We finally established a regression model to calculate the actual proportion of A1 and A2 β-CN, with the detection limits of 5% for both β-CN. In the quantitation range of this model, A1 β-CN accounting for 10% to 80% or A2 β-CN accounting for 20% to 90%, the measured value of A1/A2 or A2/A1 was a power function relationship with the theoretical value. This method effectively verifies the authenticity of A1 and A2 milk, providing a reliable tool for detecting adulteration and contamination.

Genomic selection is a powerful tool to reduce methane emissions in ruminants. However, it requires large-scale on-farm phenotypic measures of methane. Current technologies to measure methane emissions have several limitations and may not be suitable for lactating animals. Because enteric methane is closely linked to the fermentation process in the rumen, which in turn affects milk composition, breeding for low-methane ruminants may change the rumen microbial and milk composition. Consequently, these compositions may provide proxy measures of methane for use in selective breeding of low-methane ruminants. We investigated the effect on rumen and milk composition in sheep bred for divergent methane yield and the potential for generating proxy measures of methane emissions from rumen or milk samples in lactating ewes. Four hundred genotyped lactating ewes from a sheep research flock bred specifically for high and low-methane emissions had methane measured and rumen and milk samples collected approximately 6 wk post-lambing across 4 lactation years. Rumen samples were processed to generate VFA and metagenomic profiles of the rumen microbial community, and fatty acid profiles and mid-infrared spectra were generated for the milk samples. Although no differences in total fat, protein, and lactose percentages in the milk were found, the milk fatty acid profiles differed between methane selection lines, with higher PUFA and branched-chain fatty acids levels, and lower total SFA contents in ewes from the low-methane line. Higher proportions of acetate relative to propionate were found in the rumen samples from the low-methane ewes. Predictions of methane were obtained from the rumen VFA and metagenomic profiles and the fatty acid profiles and mid-infrared spectra from milk. These predictions formed the proxy methane measures and were heritable (between 0.12 to 0.36) and correlated (between 0.29 and 0.42) with the measured methane values. The genetic correlation between proxies and measured methane was between 0.52 and 0.71. The estimated efficiency of indirect selection for methane was higher for the milk sample proxies (49%-75%) than the rumen metagenomic profiles (45%-47%) and rumen VFA profiles (12%-38%). These results suggest that milk fatty acid, MIR spectroscopic, and rumen microbial composition phenotypes have the potential to be used as proxy measures of methane in lactating ruminants, with the milk-based proxies showing greater promise. Results show that the number of animals with methane proxy measures could be increased substantially and will enable access to breeding technology in countries with limited methane measurement infrastructure.

Long non-coding RNAs (lncRNAs) can regulate gene expression by "sponging" microRNAs (miRNAs), reducing their inhibitory effects on mRNAs. However, this mechanism has been minimally investigated in preimplantation embryo development. In this study, we revisited existing RNA-seq and small RNA-seq data to investigate the role of lncRNAs in in vitro produced bovine preimplantation embryos. Our findings revealed that while lncRNAs exhibit expression patterns similar to mRNAs, maternal lncRNAs degrade earlier than mRNAs during embryonic genome activation (EGA). Weighted gene co-expression network analysis identified 27 modules of mRNA and lncRNA, with enrichment analysis showing a significant negative correlation between the Polycomb repressive complex pathway and blastocyst formation (R² = -0.98, P-adj = 2e-12). Additionally, bioinformatics analysis was used to predict and construct lncRNA-miRNA-mRNA networks, highlighting that lncRNAs bind more to miRNAs compared with mRNAs (P < 0.001). Moreover, lncRNA-induced lncRNA-miRNA-mRNA axes participated in mRNA degradation and biogenesis around the EGA stage. These interactions became stronger after EGA, especially after the 16-cell stage. Overall, our study provides new insights into lncRNA-mediated regulatory networks during bovine preimplantation development.

In nonruminant species, glucose tolerance and insulin sensitivity are known to be regulated by circadian rhythms, which are repeating ~24-h cycles that govern many aspects of behavior, physiology, and metabolism. However, it is unknown if these rhythms exist in dairy cows. Our objective was to determine the fit of a daily rhythm of glucose, insulin, and nonesterified fatty acid (NEFA) clearance rates independent of daily patterns of nutrient intake. To accomplish our objective, 12 multiparous lactating Holstein cows were enrolled in a within-subject design conducted over 2 experimental periods (n = 6/period). Within each period, cows were subjected to intravenous glucose tolerance tests (IVGTT) at 4 timepoints, representing different times of the day (0300, 0900, 1500, and 2100 h). The 0900 and 2100 h IVGTT were performed 36 h apart, followed by a 7-d washout, and then the 1500 and 0300 h IVGTT were performed 36 h apart. Cows were fed 12 times/d at 2-h intervals beginning 24 h before the first IVGTT in each set until the second IVGTT in each set to stabilize feed intake across the day, with 1 time/d feeding occurring during the washout period. For each IVGTT, 250 g of glucose were infused as a 50% (wt/vol) d-glucose solution via a jugular catheter and blood was collected at -15, -5, immediately before, 0, 5, 10, 15, 20, 30, 45, 60, 90, and 120 min relative to infusion. A mixed linear model with the fixed effects of cosine and sine and random effect of cow within period was used for the outcomes of clearance rate, half-life, baseline concentration, time to baseline concentration, and area under the curve (AUC) for glucose, insulin, and NEFA. A zero-amplitude test was used to determine the fit of a 24-h cosine function and cosinor rhythmometry was used to determine the amplitude and acrophase of the 24-h rhythm. Insulin concentrations at baseline followed a diurnal rhythm. Glucose and insulin clearance rate, half-life, and AUC also followed a diurnal rhythm. Glucose and insulin clearance rates peaked at 1247 h and 0944 h, respectively. No circadian rhythm was detected for plasma NEFA concentrations. Results suggest that insulin-stimulated glucose uptake is controlled differently throughout the day by circadian rhythms.

Bovine tuberculosis, caused mainly by Mycobacterium bovis, is a major disease of cattle worldwide associated with significant economic losses and is usually diagnosed using periodic tuberculin skin tests, interferon gamma release assay, or at postmortem. Recently, we have developed a multiplex test for detecting antibodies to Mycobacterium bovis in cattle which has high sensitivity and specificity using serum or individual milk samples. Here, we have assessed the performance of the test using bulk tank milk samples from skin test positive and bovine tuberculosis-free cattle herds. In non-anamnestic bulk tank milk samples, the sensitivity relative to the comparative cervical skin test was 77.2% and the specificity was 99.8% using the high sensitivity setting of the antibody test. A kappa value of 0.85 was found indicating almost perfect agreement between the test results and comparative cervical skin test status of the herds. Likelihood ratio analysis gave positive likelihood ratio of 53.1 and a negative likelihood ratio of 0.030, indicating that the test provides good diagnostic evidence of the infection being either present or absent respectively. Bulk tank milk samples from herds with inconclusive reactors to the comparative cervical skin test but no reactors gave a test positivity of 73.7%, indicating that antibody positive animals were present in the herd after removal of the reactors. Variances in herd prevalence did not result in statistically significant differences in test positivity, and the test was able to detect a herd prevalence of 0.1% of comparative cervical skin test reactors in 80% of low prevalence herds. The test showed good repeatability and reproducibility, giving complete concordance in results from 3 independent laboratories. The results show that the bulk milk antibody test could be used as a non-anamnestic surveillance tool for detecting and monitoring bovine tuberculosis in dairy cattle herds.

Lameness is a major welfare and production concern for the dairy sector worldwide. Quantifying the lameness challenge is essential for herd health management. The "Claw Health Indicator" (CHI), developed by a Norwegian dairy company, is calculated on a monthly basis using data routinely collected in the Norwegian Dairy Herd Recording System. The CHI was hypothesized to reflect the lameness prevalence on-farm. Our cross-sectional study evaluated the accuracy of predictions made about the lameness prevalence on-farm by the CHI. We also developed an alternative model for predicting the lameness prevalence using additional variables of routinely collected herd data (RHD) and evaluated its accuracy. We used data from 149 Norwegian freestall dairy herds. A univariable β regression model was built with the total proportion of lame and severely lame cows as the dependent variable and the CHI score for each herd as the independent variable. A second model, a multivariable β regression model with the same dependent variable, was built using selected variables of RHD. The accuracy of both models was assessed in terms of their concordance r and prediction errors. A higher CHI score was indicative, as hypothesized, of a lower lameness prevalence and vice versa. Moving from the lowest CHI score in our sample to the highest was equivalent to a reduction of ∼6% in the prevalence of lameness. There was, however, substantial variation in the total proportion of lame cows seen in herds with the same CHI score. The CHI model was highly inaccurate when predicting the lameness prevalence on-farm, with a concordance r of 0.05. The alternative RHD model, which included 6 independent variables of RHD, was more accurate than the CHI model but still inaccurate with a concordance correlation coefficient of 0.31. Both the CHI and the alternative RHD models were unsuitable for accurately predicting the prevalence of lameness on-farm. Whereas their constituent parts were reflective of claw health at the herd level, they failed to reflect the complex, multifactorial nature of lameness in dairy herds. The CHI may still be useful for claw health management, as a tool for identifying potential issues on-farm, and motivating producer engagement but further investigation is required. The RHD variables in the alternative model are simpler and more widely available than the CHI, facilitating replication and further development in other countries or groups of dairy herds outside of Norway.