Effects of feeding whole-cracked rapeseeds, nitrate, and 3-nitrooxypropanol on composition and functional properties of the milk fat fraction from Danish Holstein cows.

The aim of this study was to determine the individual and combined effects of supplementing fat (FAT), nitrate (NITRATE) and 3-nitrooxypropanol (3-NOP) on compositional and functional properties of milk fat. An 8 × 8 incomplete Latin square design was conducted with 48 lactating Danish Holstein cows over 6 periods of 21 d each. Eight diets were 2 × 2 × 2 factorially arranged: FAT (30 or 63 g crude fat/kg DM), NITRATE (0 or 10 g nitrate/kg DM), and 3-NOP (0 or 80 mg 3-NOP/kg DM) and cows were fed ad libitum. Milk samples were analyzed for general composition, fatty acids (FA) and thermal properties of milk fat. Milk fat content was decreased by FAT and NITRATE and increased by 3-NOP. The changes in FA composition were mainly driven by the FAT × 3-NOP interaction. FAT shifted milk FA composition toward lower content of saturated FA (SFA) and greater contents of mono- and poly-unsaturated FA (MUFA and PUFA), whereas these effects of FAT were smaller in combination with 3-NOP. However, 3-NOP had no effects on SFA, MUFA and PUFA in low fat diets. FAT lowered solid fat content in milk fat because of decreased SFA content. The onset crystallization temperature of milk fat was decreased by 3-NOP when supplemented in low fat diets. According to the FAT × 3-NOP interaction, supplementation of fat without 3-NOP shifted peak temperature of low melting fraction of milk fat toward low temperature as a result of decreased proportion of C16:0, and increased proportions of C18:1 cis-9, C18:1 trans-11, C18:2 cis-9, and CLA cis-9,trans-11. In conclusion, no additive effects were observed among FAT, NITRATE and 3-NOP on chemical and thermal properties of milk fat and fat supplementation largely changed milk FA composition and in turn affected the thermal properties of milk fat.

Effects of feeding whole-cracked rapeseeds, nitrate, and 3-nitrooxypropanol on protein composition, minerals, and vitamin B in milk from Danish Holstein cows.

The present study was conducted to assess the individual or combined effects of feeding dietary fat (whole-cracked rapeseed), nitrate, and 3-nitrooxypropanol (3-NOP) on protein profile, mineral composition, B vitamins, and nitrate residues in milk from dairy cows. Forty-eight Danish Holstein cows used in an 8 × 8 incomplete Latin square design were fed 8 factorially arranged diets ((30 or 63 g crude fat/kg DM) × (0 or 10 g nitrate/kg DM) × (0 or 80 mg 3-NOP/kg DM)) over 6 periods of 21 d each. In each period, milk samples were collected from individual cows during the third week by pooling milk obtained from 4 consecutive milkings, and analyzed for protein profile including protein modifications, mineral composition, riboflavin, cobalamin, and presence of nitrate residues. Fat supplementation led to an increase in the phosphorylation degree of αS1-CN by 8.5% due to a decreased relative proportion of αS1-CN 8P and an increased relative proportion of αS1-CN 9P and further to a decrease in the relative proportion of αS2-CN by 2.4%. Additionally, fat supplementation decreased the relative proportions of glycosylated and unglycosylated forms of κ-CN, consequently leading to a 3.6% decrease in total κ-CN. In skim milk, K, Ca, P, and Mg concentrations were altered by individual use of fat, nitrate, and 3-NOP. Feeding nitrate resulted in a 5.4% increase in riboflavin concentration in milk while supplementing 3-NOP increased cobalamin concentration in milk by 21.1%. The nitrate concentration in milk was increased upon feeding nitrate however, this increased concentration was well below the maximum permissible limit of nitrate in milk (<50 mg/L). In conclusion, no major changes were observed in milk protein, and mineral compositions by feeding fat, nitrate, and 3-NOP to dairy cows while the increased riboflavin and cobalamin by nitrate and 3-NOP, respectively, could be of beneficial nutritional value for milk consumers.

Estimation of heritability for milk urea and genetic correlations with milk production traits in 3 Danish dairy breeds.

The aim of this study was to estimate genetic parameters for milk urea (MU) content in 3 main Danish dairy breeds. As a part of the Danish milk recording system, milk samples from cows on commercial farms were analyzed for MU concentration (mmol/L) and the percentages of fat and protein. There were 323,800 Danish Holstein, 70,634 Danish Jersey, and 27,870 Danish Red cows sampled with a total of 1,436,580, 368,251, and 133,922 test-day records per breed, respectively, included in the data set. Heritabilities for MU were low to moderate (0.22, 0.18, and 0.24 for the Holstein, Jersey, and Red breeds, respectively). The genetic correlation was close to zero between MU and milk yield in Jersey and Red, and -0.14 for Holstein. The genetic correlations between MU and fat and protein percentages, respectively, were positive for all 3 dairy breeds. Herd-test-day explained 51%, 54%, and 49% of the variation in MU in Holstein, Jersey, and Red, respectively. This indicates that MU levels in milk can be reduced by farm management. The current study shows that there are possibilities to influence MU by genetic selection as well as by farm management.

Identification of rare genetic variants of the αS-caseins in milk from native Norwegian dairy breeds and comparison of protein composition with milk from high-yielding Norwegian Red cows.

Several factors influence the composition of milk. Among these, genetic variation within and between cattle breeds influences milk protein composition, protein heterogeneity, and their posttranslational modifications. Such variations may further influence technological properties, which are of importance for the utilization of milk into dairy products. Furthermore, these potential variations may also facilitate the production of differentiated products (e.g., related to specific breeds or specific genetic variants). The objective of this study was to investigate the genetic variation and relative protein composition of the major proteins in milk from 6 native Norwegian dairy breeds representing heterogeneity in geographical origin, using the modern Norwegian breed, Norwegian Red, as reference. In total, milk samples from 144 individual cows were collected and subjected to liquid chromatography-electrospray ionization/mass spectrometry-based proteomics for identification of genetic and posttranslational modification isoforms of the 4 caseins (αS1-CN, αS2-CN, ß-CN, κ-CN) and the 2 most abundant whey proteins (α-lactalbumin and ß-lactoglobulin). Relative quantification of these proteins and their major isoforms, including phosphorylations of αS1-CN and glycosylation of κ-CN, were determined based on UV absorbance. The presence and frequency of genetic variants of the breeds were found to be very diverse and it was possible to identify rare variants of the CN, which, to our knowledge, have not been identified in these breeds before. Thus, αS1-CN variant D was identified in low frequency in 3 of the 6 native Norwegian breeds. In general, αS1-CN was found to be quite diverse between the native breeds, and the even less frequent A and C variants were furthermore detected in 1 and 5 of the native breeds, respectively. The αS1-CN variant C was also identified in samples from the Norwegian Red cattle. The variant E of κ-CN was identified in 2 of the native Norwegian breeds. Another interesting finding was the identification of αS2-CN variant D, which was found in relatively high frequencies in the native breeds. Diversity in more common protein genetic variants were furthermore observed in the protein profiles of the native breeds compared with milk from the high-yielding Norwegian Reds, probably reflecting the more diverse genetic background between the native breeds.

Effects on feed intake, milk production, and methane emission in dairy cows fed silage or fresh grass with concentrate or fresh grass harvested at early or late maturity stage without concentrate.

The objective of the study was to quantify the effects on dry matter intake (DMI), nutrient digestibility, gas exchange, milk production, and milk quality in dairy cows fed fresh grass harvested at different maturity stages. Sixteen Danish Holstein cows in mid-lactation were divided into 4 blocks and used in 4 incomplete 4 × 2 Latin squares with 2 periods of 21 d. The cows received 1 of 4 treatments in each period, resulting in 8 cows per treatment, as follows: grass-clover silage supplemented with 6 kg/d concentrate pellets (SILc), fresh grass harvested at late maturity stage supplemented with 6 kg/d concentrate pellets (LATc), fresh grass harvested at late maturity stage (LAT), and fresh grass harvested at early maturity stage (ERL). The cows were housed in tiestalls and milked twice daily. The cows had ad libitum access to the forage, and concentrate pellets were divided into equal amounts and fed separately in the morning and afternoon. Fecal samples were collected to determine apparent total-tract digestibility, and samples of rumen fluid were collected for determination of short chain fatty acid composition. Halters were used for measuring eating and rumination time. Gas exchange was measured in open-circuit respiration chambers. Total DMI was higher in LATc and ERL (16.9 ± 0.45 and 15.5 ± 0.39 kg/d, respectively) compared with LAT (14.1 ± 0.42 kg/d). Relative to SILc, cows fed fresh grass experienced a convex pattern in DMI during the experiment. The changes in DMI were related to changes in leaf to stem ratio, fiber concentration, and organic matter digestibility determined in vitro in samples of the fresh grass harvested throughout the experiment. The apparent total-tract digestibility of organic matter was higher in SILc and LAT compared with LATc. Methane yield was lower for LATc compared with LAT (19.5 ± 0.61 vs. 22.6 ± 0.55 g of CH4/kg of DMI), and was not different between LAT and ERL. Compared with LAT, milk yield was higher for ERL (21.1 ± 1.14 vs. 23.4 ± 1.11 kg/d) and energy-corrected milk (ECM) yield was higher for LATc (21.5 ± 0.99 vs. 25.3 ± 1.03 kg/d). We detected no differences in milk or ECM yield between SILc and LATc. Milk protein yield was higher and milk fat concentration was lower in LATc compared with LAT. The fatty acid percentages of ∑C4-C14:1 and ∑C16 in milk were higher for SILc compared with LATc, signifying pronounced de novo synthesis. The n-6:n-3 ratio in milk fatty acids was lower for SILc and LAT compared with LATc, indicating improved nutritional quality for SILc and LAT. However, retinol concentration in milk was lower in SILc compared with all other treatments. The study implies that feeding silage instead of fresh grass has no effect on DMI, ECM yield, or CH4 yield, and that concentrate supplementation can increase milk production, affects milk quality, and reduces the effect on climate, whereas feeding less mature grass increases DMI and milk yield, but has no effect on CH4 yield.

Effect of protein concentrate mixtures and dietary addition of exogenous phytase on major milk minerals and proteins, including casein phosphorylation.

Variations in major milk minerals, proteins, and their posttranslational modifications are largely under genetic influence, whereas the effect of nongenetic factors is less studied. Through a controlled feeding experiment (incomplete balanced Latin square design), the effect of concentrate mixtures, based on fava beans, rapeseed meal, or soybean meal as main P and protein sources, on milk composition was examined under typical Danish management conditions. Concentrations of P, Ca, and Mg, together with proteomics for relative quantification of major milk proteins and their isoforms, were analyzed in milk samples from 24 cows sampled in 4 periods. Each cow was fed 1 of the 3 diets in each period with or without addition of exogenous phytase. Cows were blocked by lactation stage into early and mid-lactation (23.3 ± 6.7 and 176 ± 15 d in milk, respectively, at the beginning of the experiment, mean ± standard deviation). Significant effects of feed concentrate mixture were observed for milk protein concentration, milk urea nitrogen, citrate, and the percentage of mixed and preformed fatty acids as well as mineral composition, and their distributions within micellar or serum phases. Furthermore, relative contents of αS1-casein (CN) 9P form and unglycosylated κ-CN and thereby phosphorylation degree of αS1-CN (PD) and the glycosylation degree of κ-CN were found to be significantly affected by these diets. To our knowledge, we are the first to document that feed concentrate mixture can affect the relative concentrations of αS1-CN phosphorylation isoforms in milk, and the results suggested an effect on αS1-CN 9P and PD, but not on αS1-CN 8P. Furthermore, although only significant for αS1-CN 8P, we found a lower relative concentration of αS1-CN 8P and higher αS1-CN 9P (and thus higher PD) in milk from cows in mid compared with early lactation. Also, protein concentration and concentration of Mg in skim milk and serum as well as relative concentration of α-lactalbumin were found to be significantly affected by lactation stage. Addition of dietary exogenous phytase only had a minor effect on milk composition or functionality with significant effect detected for α-lactalbumin and micellar Mg concentration.

Genetic analysis on infrared-predicted milk minerals for Danish dairy cattle.

A group of milk components that has shown potential to be predicted with milk spectra is milk minerals. Milk minerals are important for human health and cow health. Having an inexpensive and fast way to measure milk mineral concentrations would open doors for research, herd management, and selective breeding. The first aim of this study was to predict milk minerals with infrared milk spectra. Additionally, milk minerals were predicted with infrared-predicted fat, protein, and lactose content. The second aim was to perform a genetic analysis on infrared-predicted milk minerals, to identify QTL, and estimate variance components. For training and validating a multibreed prediction model for individual milk minerals, 264 Danish Jersey cows and 254 Danish Holstein cows were used. Partial least square regression prediction models were built for Ca, Cu, Fe, K, Mg, Mn, Na, P, Se, and Zn based on 80% of the cows, selected randomly. Prediction models were externally validated with 8 herds based on the remaining 20% of the cows. The prediction models were applied on a population of approximately 1,400 Danish Holstein cows with 5,600 infrared spectral records and 1,700 Danish Jersey cows with 7,200 infrared spectral records. Cows from this population had 50k imputed genotypes. Prediction accuracy was good for P and Ca, with external R2 ≥ 0.80 and a relative prediction error of 5.4% for P and 6.3% for Ca. Prediction was moderately good for Na with an external R2 of 0.63, and a relative error of 18.8%. Prediction accuracies of milk minerals based on infrared-predicted fat, protein, and lactose content were considerably lower than those based on the infrared milk spectra. This shows that the milk infrared spectrum contains valuable information on milk minerals, which is currently not used. Heritability for infrared-predicted Ca, Na, and P varied from low (0.13) to moderate (0.36). Several QTL for infrared-predicted milk minerals were observed that have been associated with gold standard milk minerals previously. In conclusion, this study has shown infrared milk spectra were good at predicting Ca, Na, and P in milk. Infrared-predicted Ca, Na, and P had low to moderate heritability estimates.

Genetic analysis of orotic acid predicted with Fourier transform infrared milk spectra.

Fourier transform infrared spectral analysis is a cheap and fast method to predict milk composition. A not very well studied milk component is orotic acid. Orotic acid is an intermediate in the biosynthesis pathway of pyrimidine nucleotides and is an indicator for the metabolic cattle disorder deficiency of uridine monophosphate synthase. The function of orotic acid in milk and its effect on calf health, health of humans consuming milk or milk products, manufacturing properties of milk, and its potential as an indicator trait are largely unknown. The aims of this study were to determine if milk orotic acid can be predicted from infrared milk spectra and to perform a large-scale phenotypic and genetic analysis of infrared-predicted milk orotic acid. An infrared prediction model for orotic acid was built using a training population of 292 Danish Holstein and 299 Danish Jersey cows, and a validation population of 381 Danish Holstein cows. Milk orotic acid concentration was determined with nuclear magnetic resonance spectroscopy. For genetic analysis of infrared orotic acid, 3 study populations were used: 3,210 Danish Holstein cows, 3,360 Danish Jersey cows, and 1,349 Dutch Holstein Friesian cows. Using partial least square regression, a prediction model for orotic acid was built with 18 latent variables. The error of the prediction for the infrared model varied from 1.0 to 3.2 mg/L, and the accuracy varied from 0.68 to 0.86. Heritability of infrared orotic acid predicted with the standardized prediction model was 0.18 for Danish Holstein, 0.09 for Danish Jersey, and 0.37 for Dutch Holstein Friesian. We conclude that milk orotic acid can be predicted with moderate to good accuracy based on infrared milk spectra and that infrared-predicted orotic acid is heritable. The availability of a cheap and fast method to predict milk orotic acid opens up possibilities to study the largely unknown functions of milk orotic acid.

Multi-population GWAS and enrichment analyses reveal novel genomic regions and promising candidate genes underlying bovine milk fatty acid composition.

BACKGROUND: The power of genome-wide association studies (GWAS) is often limited by the sample size available for the analysis. Milk fatty acid (FA) traits are scarcely recorded due to expensive and time-consuming analytical techniques. Combining multi-population datasets can enhance the power of GWAS enabling detection of genomic region explaining medium to low proportions of the genetic variation. GWAS often detect broader genomic regions containing several positional candidate genes making it difficult to untangle the causative candidates. Post-GWAS analyses with data on pathways, ontology and tissue-specific gene expression status might allow prioritization among positional candidate genes. RESULTS: Multi-population GWAS for 16 FA traits quantified using gas chromatography (GC) in sample populations of the Chinese, Danish and Dutch Holstein with high-density (HD) genotypes detects 56 genomic regions significantly associated to at least one of the studied FAs; some of which have not been previously reported. Pathways and gene ontology (GO) analyses suggest promising candidate genes on the novel regions including OSBPL6 and AGPS on Bos taurus autosome (BTA) 2, PRLH on BTA 3, SLC51B on BTA 10, ABCG5/8 on BTA 11 and ALG5 on BTA 12. Novel genes in previously known regions, such as FABP4 on BTA 14, APOA1/5/7 on BTA 15 and MGST2 on BTA 17, are also linked to important FA metabolic processes. CONCLUSION: Integration of multi-population GWAS and enrichment analyses enabled detection of several novel genomic regions, explaining relatively smaller fractions of the genetic variation, and revealed highly likely candidate genes underlying the effects. Detection of such regions and candidate genes will be crucial in understanding the complex genetic control of FA metabolism. The findings can also be used to augment genomic prediction models with regions collectively capturing most of the genetic variation in the milk FA traits.

Natural variations of citrate and calcium in milk and their effects on milk processing properties.

Natural variations among milk constituents, and their relations to each other as well as to processing parameters, represent possibilities for differentiation of milk to produce high-quality natural products. In this study, we focused on natural variations in milk citrate and its interplay with calcium distribution in milk, in relation to processing properties. Milk samples from individual cows from farms varying in feeding and management practices were collected from April to June 2017 to maximize natural variations in citrate and calcium. Chemical composition, rennet coagulation properties, and ethanol stability were analyzed for all milk samples. We focused particularly on calcium distribution and citrate content and the correlation of these to other milk parameters. No significant change in citrate content was observed during the sampling period, which suggests that mechanisms other than feeding affect citrate levels in milk. Several significant correlations were found, including a positive correlation between complexed serum calcium and citrate, and a negative correlation between urea and ionic calcium. These are both of interest in relation to further processing, as with regard to the stability of UHT milk and in cheese making. Although the correlation between complexed serum calcium and citrate may be explained by their affinity, the underlying driver for the negative relationship between natural milk urea and ionic calcium needs to be clarified by further studies. Furthermore, milk from the different farms varied not only with regard to organic versus conventional farming systems; feeding practices between farms also play an important role in milk composition and functionality. However, none of the differences in milk composition between farms were found to decrease milk functionality and thus would probably not cause any processing problems.

Combining multi-population datasets for joint genome-wide association and meta-analyses: The case of bovine milk fat composition traits.

In genome-wide association studies (GWAS), sample size is the most important factor affecting statistical power that is under control of the investigator, posing a major challenge in understanding the genetics underlying difficult-to-measure traits. Combining data sets available from different populations for joint or meta-analysis is a promising alternative to increasing sample sizes available for GWAS. Simulation studies indicate statistical advantages from combining raw data or GWAS summaries in enhancing quantitative trait loci (QTL) detection power. However, the complexity of genetics underlying most quantitative traits, which itself is not fully understood, is difficult to fully capture in simulated data sets. In this study, population-specific and combined-population GWAS as well as a meta-analysis of the population-specific GWAS summaries were carried out with the objective of assessing the advantages and challenges of different data-combining strategies in enhancing detection power of GWAS using milk fatty acid (FA) traits as examples. Gas chromatography (GC) quantified milk FA samples and high-density (HD) genotypes were available from 1,566 Dutch, 614 Danish, and 700 Chinese Holstein Friesian cows. Using the joint GWAS, 28 additional genomic regions were detected, with significant associations to at least 1 FA, compared with the population-specific analyses. Some of these additional regions were also detected using the implemented meta-analysis. Furthermore, using the frequently reported variants of the diacylglycerol acyltransferase 1 (DGAT1) and stearoyl-CoA desaturase (SCD1) genes, we show that significant associations were established with more FA traits in the joint GWAS than the remaining scenarios. However, there were few regions detected in the population-specific analyses that were not detected using the joint GWAS or the meta-analyses. Our results show that combining multi-population data set can be a powerful tool to enhance detection power in GWAS for seldom-recorded traits. Detection of a higher number of regions using the meta-analysis, compared with any of the population-specific analyses also emphasizes the utility of these methods in the absence of raw multi-population data sets to undertake joint GWAS.

Factors influencing degree of glycosylation and phosphorylation of caseins in individual cow milk samples.

The aim of this study was to examine variations in posttranslational modifications (PTM) of caseins (CN) in milk from individual cows and determine how these differ between breeds, across lactation, and between variants. Furthermore, we examined the variation of casein PTM in relation to rennet coagulation properties of milk. In total, detailed protein composition of milk from 892 Danish Holstein and Jersey cows was determined by liquid chromatography/electrospray ionization-mass spectrometry. The method measured relative contents of the main milk proteins as well as several variants and PTM. The results showed that the 2 breeds had distinct milk protein composition. Milk from Danish Holstein cows was mainly characterized by higher relative contents of ß-CN, α-lactalbumin (α-LA), and ß-lactoglobulin, and a higher fraction of glycosylated κ-CN (G κ-CN), whereas milk from Danish Jersey cows was characterized by higher relative contents of κ-CN, αS2-CN, and the less phosphorylated forms of αS1-CN and αS2-CN. Univariate linear models including days in milk and parity as class effects showed variation in the detailed protein profile across and between lactations; in particular, changes in the degree of glycosylation of κ-CN were pronounced, but changes in αS1-CN 8P to total αS1-CN and αS2-CN 11P to αS2-CN were also observed over lactation for both breeds. The phosphorylated forms of αS1-CN and αS2-CN were, to some extent, correlated. Further, the κ-CN BB genotype was associated with higher relative contents of both unglycosylated κ-CN (UG κ-CN) and G κ-CN compared with κ-CN AA; κ-CN AB showed intermediate results in both breeds. The influence of protein composition on rennet coagulation properties was explored based on 4 classes for curd firming rate: noncoagulation, and poor, average, and good coagulation. The results revealed breed differences: Holstein milk, higher relative content of κ-CN to total protein, and higher content of G κ-CN were associated with improved milk coagulation. In contrast, relative content of α-LA was the main component associated with milk coagulation properties in Danish Jerseys and it was shown to affect milk coagulation properties negatively. In addition, variation in phosphorylation degrees of αS1-CN also played a role. This study demonstrates that although the genetic influence of glycosylation seems to be the same in both breeds, nongenetic variation differs, which is further reflected in different associations with milk coagulation properties.

Short communication: Multi-trait estimation of genetic parameters for milk protein composition in the Danish Holstein.

Genetic parameters were estimated for the major milk proteins using bivariate and multi-trait models based on genomic relationships between animals. The analyses included, apart from total protein percentage, αS1-casein (CN), αS2-CN, ß-CN, κ-CN, α-lactalbumin, and ß-lactoglobulin, as well as the posttranslational sub-forms of glycosylated κ-CN and αS1-CN-8P (phosphorylated). Standard errors of the estimates were used to compare the models. In total, 650 Danish Holstein cows across 4 parities and days in milk ranging from 9 to 481d were selected from 21 herds. The multi-trait model generally resulted in lower standard errors of heritability estimates, suggesting that genetic parameters can be estimated with high accuracy using multi-trait analyses with genomic relationships for scarcely recorded traits. The heritability estimates from the multi-trait model ranged from low (0.05 for ß-CN) to high (0.78 for κ-CN). Genetic correlations between the milk proteins and the total milk protein percentage were generally low, suggesting the possibility to alter protein composition through selective breeding with little effect on total milk protein percentage.

Quantification of bovine milk protein composition and coagulation properties using infrared spectroscopy and chemometrics: A result of collinearity among reference variables.

Predicting protein fractions and coagulation properties in bovine milk using Fourier transform infrared (FT-IR) measurements is desirable. However, such predictions may rely on correlations with total protein content. The aim of this study was to show how correlations between total protein content, protein fractions, and coagulation properties are responsible for the successful prediction of protein fractions and rennet-induced coagulation properties in milk samples. This study comprised 832 bovine milk samples from 2 breeds (426 Holstein and 406 Jersey). Holstein samples were collected from 20 Danish dairy herds from October to December 2009; Jersey samples were collected from 22 Danish dairy herds from February to April 2010. All samples were from conventional herds and taken while cows were housed. The results showed that κ-CN, αS1-CN, αS1-CN with 8 phosphorylated groups attached (αS1-CN 8P), and curd firming rate could be predicted from FT-IR measurements of the milk samples (with coefficients of determination between 0.66 and 0.71). However, the success of these FT-IR-based predictions was based on indirect relationships with total protein content. Hence, the FT-IR predictions relied on covariance structures with total protein content rather than absorption bands directly associated with the protein fractions and coagulation properties. If covariance structures between the protein fractions, coagulation properties, and total protein content used to calibrate partial least squares models were not conserved in future samples, these samples would show incorrect predictions of the protein fractions and coagulation properties. We demonstrated this using samples from 1 breed to calibrate and samples from the other breed to validate partial least squares models for ß-CN. The 2 breeds had different covariance structures between ß-CN and total protein content, and the validation samples yielded incorrect predictions. This finding may limit the usefulness of FT-IR-based predictions of protein fractions in milk recording, because indirect covariance structures in the calibration set must be valid for future samples, or future samples will show incorrect predictions.

Good sensory quality and cheesemaking properties in milk from Holstein cows managed for an 18-month calving interval.

Extended calving interval (CInt) for high-yielding dairy cows beyond the traditional 12mo has been suggested as a profitable, environmentally and welfare-friendly production strategy. However, concerns exist on whether extending cow CInt, and consequently prolonging lactation length, impairs milk quality. The aim of this study was to compare the quality of milk produced during the extended lactation period to mid lactation. In particular, milk indicators related to udder integrity and cheesemaking properties when cows were fed low- or high-energy diets in early lactation mobilization period. Forty-seven healthy Danish Holstein cows (15 primi- and 32 multiparous) were fed 2 distinct weight-adjusted diets in early lactation: either a high-density diet for approximately 42d in milk (DIM) followed by a low-density diet (n=22), or a low-density diet throughout the whole experiment (n=25). Milk quality was explored at 3 lactation periods: 140 to 175 DIM (P1), 280 to 315 DIM (P2), and 385 to 420 DIM (P3). Lactation period was found to be the main factor affecting milk yield, quality, and cheesemaking properties. Primiparous cows kept the same daily milk yield throughout the studied periods, whereas multiparous cows produced, on average, 10.2kg/d less in P3 compared with P1. Fat, protein, and casein concentrations increased, respectively, by 18, 16, and 16%, from P1 to P3. Cheesemaking properties, such as curd-firming rate, gel strength, and wet and dry curd yield, got an improvement from P1 to P3 and were strongly correlated with milk concentrations of protein and casein. The udder integrity indicators, somatic cells count, level of free amino terminals as an index of proteolysis, and milk pH, remained unchanged throughout the studied lactation periods. Feeding cows either high- or low-density diets during the early lactation mobilization period did not exert any relevant carryover effect on milk composition, and thus had no effect on cheesemaking properties in extended lactation. Further, sensory quality of mid- and extended-lactation milk was assessed by a trained sensory panel. The sensory quality of milk from P3 reflected sensory descriptors related to the increased levels of fat and protein over lactation, but, importantly, milk produced in P3 did not present sensory demerits when compared with milk produced in P1. In conclusion, high-yielding Holstein cows undergoing an 18-mo CInt produced high-quality milk from mid to extended lactation.

Effects of the diacylglycerol o-acyltransferase 1 (DGAT1) K232A polymorphism on fatty acid, protein, and mineral composition of dairy cattle milk.

Several studies have described associations between the diacylglycerol o-acyltransferase 1 (DGAT1) K232A polymorphism and routinely collected milk production traits but not much is known about effects of the DGAT1 polymorphism on detailed milk composition. The aim of this study was to estimate effects of the DGAT1 polymorphism on milk fatty acid, protein, and mineral composition. We looked for effects that were significant and consistent in Danish Holstein Friesian (HF), Danish Jersey, and Dutch HF as these are likely to be true effects of the DGAT1 K232A polymorphism rather than being effects of linked loci. For fatty acid composition, significant and consistent effects of the DGAT1 polymorphism were detected on C14:0, C16:0, C15:0, C16:1, C18:1 cis-9, conjugated linoleic acid (CLA) cis-9,trans-11, C18:2 cis-9,cis-12, and C18:3 cis-9,cis-12,cis-15 content (percent by weight, wt/wt %). For C16:0, C16:1, and C18:1 cis-9, the DGAT1 polymorphism explained more than 10% of the phenotypic variation. Significant effects on milk protein composition in Dutch HF could not be confirmed in Danish Jersey or Danish HF. For mineral content, significant and consistent effects of the DGAT1 polymorphism on calcium, phosphorus, and zinc were detected. In the Dutch HF population, the contribution of the DGAT1 K232A polymorphism to phenotypic variance was 12.0% for calcium, 8.3% for phosphorus, and 6.1% for zinc. Different from effects on fatty acid composition, effects of the DGAT1 polymorphism on yields of long-chain fatty acids C18:1 cis-9, CLA cis-9,trans-11, C18:2 cis-9,cis-12, and C18:3 cis-9,cis-12,cis-15 were not significant. This indicates that effects of DGAT1 on these fatty acids are indirect, not direct, effects: DGAT1 affects de novo synthesis of fatty acids and, consequently, the contribution of the long-chain fatty acids to total fat is decreased. In addition, effects of the DGAT1 polymorphism on yields of Ca, P, and Zn were not significant, which indicates that effects on these minerals are the result of indirect rather than direct effects of DGAT1: effects on calcium, phosphorus, and zinc content can be explained by effects of DGAT1 on milk volume. The reported effects of the DGAT1 polymorphism on fatty acid and mineral composition of milk are substantial and therefore relevant for milk quality.

Phenotypic and genetic associations of milk traits with milk coagulation properties.

The aim of this study was to examine milk composition and rennet-induced coagulation properties of milk from 892 individual Danish Holstein and Danish Jersey cows and determine the genetic influences on these properties by determining heritability and genomic correlations with single nucleotide polymorphisms identified by the bovine HD Beadchip (Illumina Inc., San Diego, CA). Despite no signs of clinical mastitis, milk from cows with somatic cell counts >500,000 cells/mL showed altered milk composition, indicating impaired barrier between the milk and the blood. Curd-firming rate (CFR) and rennet coagulation time (RCT) were used to describe milk coagulation properties (MCP). These traits describe the second phase of milk coagulation and were mutually negatively correlated, but only to some extent associated with the same compositional traits. In both breeds, CFR were highly correlated with protein content, whereas longer RCT were primarily associated with lower milk pH. Estimated heritabilities for milk production and compositional traits ranged from 0.09 for yield to 0.82 for citric acid in Danish Jersey cows, and from 0.21 for yield to 0.59 for citric acid in Danish Holstein cows. Heritabilities for MCP traits varied considerably between breeds, and were estimated to be 0.28 for RCT and 0.75 for CFR in Danish Holstein cows and 0.45 for RCT and 0.15 for CFR in Danish Jersey cows. This difference was further reflected in the genomic correlations between RCT and CFR which was -0.90 in Danish Holstein and 0.06 in Danish Jersey. These data suggest that potential for changing MCP through breeding exists, but the genetic background of the MCP traits might be different in different breeds; therefore, using Danish Holstein as background for Danish Jersey is not trivial. Thereby, the study underlines the need for breed-specific models.

In vitro digestion of purified ß-casein variants A(1), A(2), B, and I: effects on antioxidant and angiotensin-converting enzyme inhibitory capacity.

Genetic polymorphisms of bovine milk proteins affect the protein profile of the milk and, hence, certain technological properties, such as casein (CN) number and cheese yield. However, reports show that such polymorphisms may also affect the health-related properties of milk. Therefore, to gain insight into their digestion pattern and bioactive potential, ß-CN was purified from bovine milk originating from cows homozygous for the variants A(1), A(2), B, and I by a combination of cold storage, ultracentrifugation, and acid precipitation. The purity of the isolated ß-CN was determined by HPLC, variants were verified by mass spectrometry, and molar extinction coefficients at λ=280nm were determined. ß-Casein from each of the variants was subjected to in vitro digestion using pepsin and pancreatic enzymes. Antioxidant and angiotensin-converting enzyme (ACE) inhibitory capacities of the hydrolysates were assessed at 3 stages of digestion and related to that of the undigested samples. Neither molar extinction coefficients nor overall digestibility varied significantly between these 4 variants; however, clear differences in digestion pattern were indicated by gel electrophoresis. In particular, after 60min of pepsin followed by 5min of pancreatic enzyme digestion, one ≈4kDa peptide with the N-terminal sequence (106)H-K-E-M-P-F-P-K- was absent from ß-CN variant B. This is likely a result of the (122)Ser to (122)Arg substitution in variant B introducing a novel trypsin cleavage site, leading to the changed digestion pattern. All investigated ß-CN variants exhibited a significant increase in antioxidant capacity upon digestion, as measured by the Trolox-equivalent antioxidant capacity assay. After 60min of pepsin + 120min of pancreatic enzyme digestion, the accumulated increase in antioxidant capacity was ≈1.7-fold for the 4 ß-CN variants. The ACE inhibitory capacity was also significantly increased by digestion, with the B variant reaching the highest inhibitory capacity at the end of digestion (60min of pepsin + 120min of pancreatic enzymes), possibly because of the observed alternative digestion pattern. These results demonstrate that genetic polymorphisms affect the digestion pattern and bioactivity of milk proteins. Moreover, their capacity for radical scavenging and ACE inhibition is affected by digestion.

Joint genome-wide association study for milk fatty acid traits in Chinese and Danish Holstein populations.

The identification of causal genes or genomic regions associated with fatty acids (FA) will enhance our understanding of the pathways underlying FA synthesis and provide opportunities for changing milk fat composition through a genetic approach. The linkage disequilibrium between adjacent markers is highly consistent between the Chinese and Danish Holstein populations, such that a joint genome-wide association study (GWAS) can be performed. In this study, a joint GWAS was performed for 16 milk FA traits based on data of 784 Chinese and 371 Danish Holstein cows genotyped by a high-density bovine single nucleotide polymorphism (SNP) array. A total of 486,464 SNP markers on 29 bovine autosomes were used. Bonferroni corrections were applied to adjust the significance thresholds for multiple testing at the genome- and chromosome-wide levels. According to the analysis of either the Chinese or Danish data individually, the total numbers of overlapping SNP that were significant at the chromosome level were 94 for C14:1, 208 for the C14 index, and 1 for C18:0. Joint analysis using the combined data of the 2 populations detected greater numbers of significant SNP compared with either of the individual populations alone for 7 and 10 traits at the genome- and chromosome-wide significance levels, respectively. Greater numbers of significant SNP were detected for C18:0 and the C18 index in the Chinese population compared with the joint analysis. Sixty-five significant SNP across all traits had significantly different effects in the 2 populations. Ten FA were influenced by a quantitative trait loci (QTL) region including DGAT1. Both C14:1 and the C14 index were influenced by a QTL region including SCD1 in the combined population. Other QTL regions also showed significant associations with the studied FA. A large region (14.9-24.9 Mbp) in BTA26 significantly influenced C14:1 and the C14 index in both populations, mostly likely due to the SNP in SCD1. A QTL region (69.97-73.69 Mbp) on BTA9 showed a significantly different effect on C18:0 between the 2 populations. Detection of these important SNP and the corresponding QTL regions will be helpful for follow-up studies to identify causal mutations and their interaction with environments for milk FA in dairy cattle.

Bovine chromosomal regions affecting rheological traits in rennet-induced skim milk gels.

Optimizing cheese yield and quality is of central importance to cheese manufacturing. The yield is associated with the time it takes before the gel has an optimal consistency for further processing, and it is well known that gel formation differs between individual milk samples. By identifying genomic regions affecting traits related to rennet-induced gelation, the aim of this study was to identify potential candidate genes affecting these traits. Hence, rennet-induced gelation, including rennet coagulation time, gel strength, and yield stress, was measured in skim milk samples collected from 379 animals of the Swedish Red breed using low-amplitude oscillation measurements. All animals had genotypes for almost 621,000 segregating single nucleotide polymorphisms (SNP), identified using the Bovine HD SNPChip (Illumina Inc., San Diego, CA). The genome was scanned for associations, haplotypes based on SNP sets comprising highly associated SNP were inferred, and the effects of the 2 most common haplotypes within each region were analyzed using mixed models. Even though the number of animals was relatively small, a total of 21 regions were identified, with 4 regions showing association with more than one trait. A major quantitative trait locus for all traits was identified around the casein cluster explaining between 9.3 to 15.2% of the phenotypic variation of the different traits. In addition, 3 other possible candidate genes were identified; that is, UDP-N-acetyl-α-d-galactosamine:polypeptide N-acetylgalactosaminyl-transferase 1 (GALNT1), playing a role in O-glycosylation of κ-casein, and 2 cathepsins, CTSZ and CTSC, possibly involved in proteolysis of milk proteins. We have shown that other genes than the casein genes themselves may be involved in the regulation of gelation traits. However, additional analysis is needed to confirm these results. To our knowledge, this is the first study identifying quantitative trait loci affecting rennet-induced gelation of skim milk through a high-density genome-wide association study.