The occurrence of noncoagulating milk and the association of bovine milk coagulation properties with genetic variants of the caseins in 3 Scandinavian dairy breeds

Recent advances in the bovine β-casein gene mutants on functional characteristics and nutritional health of dairy products: Status, challenges, and prospects

β-casein is the second most abundant form of casein in milk. Changes in amino acid sequence at specific positions in the primary structure of β-casein in milk will produce gene mutations that affect the physicochemical properties of dairy products and the hydrolysis site of digestive enzymes. The screening method of β-casein allele frequency detection in dairy products also has attracted the extensive attention of scientists and farmers. The A1 and A2 β-casein is the two usual mutation types, distinguished by histidine and proline at position 67 in the peptide chain. This paper summarizes the effects of A1 and A2 β-casein on the physicochemical properties of dairy products and evaluates the effects on human health, and the genotyping methods were also concluded. Impressively, this review presents possible future opportunities and challenges for the promising field of A2 β-casein, providing a valuable reference for the development of the functional dairy market.

A discussion on A1-free milk: Nuances and comments beyond implications to the health

This chapter provides an overarching view of the multifaceted aspects of milk β-casein, focusing on its genetic variants A1 and A2. The work examines the current landscape of A1-free milk versus regular milk, delving into health considerations, protein detection methods, technological impacts on dairy production, non-bovine protein, and potential avenues for future research. Firstly, it discussed ongoing debates surrounding categorizing milk based on A1 and A2 β-casein variants, highlighting challenges in establishing clear regulatory standards and quality control methods. The chapter also addressed the molecular distinction between A1 and A2 variants at position 67 of the amino acid chain. This trait affects protein conformation, casein micelle properties, and enzymatic susceptibility. Variations in β-casein across animal species are acknowledged, casting doubt on non-bovine claims of "A2-like" milk due to terminology and genetic differences. Lastly, this work explores the burgeoning field of biotechnology in milk production.

A2 milk consumption and its health benefits: an update

Milk is a widely consumed nutrient-rich food containing protein variants such as casein A2 and A1. A1 differs from A2 in an amino acid at position 67 (Pro67 to His67). The breakdown of β-casein yields β-casomorphins (BCM), among which BCM-7 is extensively studied for its effects on the human body. Animal studies have shown that A1 β-casein milk increases digestive transit time and enhances myeloperoxidase activity. Individuals with lactose intolerance prefer A2 milk to conventional A1 milk, as BCM-7 in A1 milk can lead to inflammation and discomfort in sensitive individuals. A2 milk, which contains A2 β-casein, is believed to be more easily digestible than A1 β-casein. Its popularity has grown owing to reports linking A1 casein to diseases such as type 1 diabetes, heart disease, and autism. A2 milk has gained popularity as an alternative to A1 milk, primarily because of its potential benefits for individuals with certain diseases. This review aims to provide an updated understanding of A2 milk consumption and its health benefits. This review aims to provide an updated understanding of A2 milk consumption and its health benefits.

Milk coagulation and gastric emptying in women experiencing gastrointestinal symptoms after ingestion of cow's milk

BACKGROUND

Gastrointestinal symptoms after drinking milk are often attributed to lactose intolerance or cow's milk allergy. However, some individuals without either condition still report gastrointestinal symptoms after drinking milk. This may be caused by gastric emptying (GE) rate or gastric protein coagulation. This study aimed to compare GE rate and protein coagulation after milk consumption between individuals reporting gastrointestinal symptoms and those without symptoms using a novel gastric MRI approach.

METHODS

Thirty women were included in this case-control study, of whom 15 reported gastrointestinal symptoms after drinking milk and 15 were controls. Participants underwent gastric MRI before and up to 90 min after consumption of 250 mL cow's milk. Gastric content volume and image texture of the stomach contents were used to determine GE and changes in the degree of coagulation.

KEY RESULTS

GE half-time did not differ between the groups (gastrointestinal symptom group 66 ± 18 min; control group 61 ± 14 min, p = 0.845). The gastrointestinal symptom group reported symptoms from 30 min onwards and rated pain highest at 90 min. The control group reported no symptoms. Image texture analyses showed a significantly higher percentage of coagulum and lower percentage of liquid in the group in the GI symptom group (MD 11%, 95% CI [3.9, 17], p = 0.003). In vitro data suggests that pH and proteolytic enzyme activity influence the coagulum structure.

CONCLUSIONS AND INFERENCES

Gastric milk coagulation and emptied fraction of stomach content may differ between individuals experiencing symptoms after milk consumption, possibly due to differences in pH and proteolytic enzyme activity.

CSN1S1 and LALBA Polymorphisms and Other Factors Influencing Yield, Composition, Somatic Cell Score, and Technological Properties of Cow's Milk

We evaluated the influence of CSN1S1 and LALBA polymorphisms on cow's milk yield and quality. The analysis was done on Czech Simmental and Holstein cows. Non-genetic factors were included as well. CSN1S1 did not influence the milk performance in the first lactation. In the second lactation, cows with the BB genotype had significantly higher milk, protein, and fat yields than BC. The differences between LALBA genotypes were non-significant in the first lactation, while in the second lactation, the fat percentage was significantly higher in BB than in AB. The farm significantly influenced milk, protein, and fat yields in both the first and second lactations and fat percentage in the first lactation. The effect of CSN1S1 and LALBA genotypes on the milk technological quality was non-significant. Breed did not influence any of the evaluated technological traits and SCS. The ethanol test was not influenced by farm, season, lactation phase, protein percentage, breed, or non-fat solids percentage. Farm, season, and protein percentage significantly influenced milk fermentation ability, renneting, and SCS. The lactose content is a good indicator of udder health.

An approach on detection, quantification, technological properties, and trends market of A2 cow milk

The genetic variant A2 β-casein integrates the casein protein group in milk and has been often associated with positive health outcomes. Therefore, this review explores the present understanding of A2 β-casein, including detection methods and the market trends for dairy from A2 milk. Also, the interaction of A2 β-casein with αs₁-casein and κ-casein genotypes was examined in terms of technological impacts on A2 milk. A limited number of preliminary studies has aimed to investigate the sensorial and technological impacts of β-casein variants in milk matrices, for instance, in yogurt and other derivatives. Nevertheless, considering studies carried out so far, it is concluded that the manufacture of dairy products from A2 milk is perfectly feasible, as the products presented slight differences when compared to those derived from traditional milk. In one of the works, sensitive drops in rennet coagulation time and curd firmness values were observed in cheese traits. However, it is relevant to point out that variant A of κ-casein plays a negative role in the coagulation features of milk. Therefore, alterations in the pattern of cheese-making properties are not uniquely related to β-casein variants. Attempts to produce A2 β-casein in laboratory (non-natural source), through biosynthesis, for example, have not been found so far. This knowledge gap offers a promising area for future studies concerning proteins and bioactive peptide production.

A Study of Milk Composition and Coagulation Properties of Holstein-Friesian, Jersey, and Their Cross Milked Once or Twice a Day

The objective of the study was to explore the effect of breed on the composition and coagulation properties (rennet coagulation time (min), curd firming rate (min), and curd firmness (mm)) of milk from cows milked once a day or twice a day in the morning and afternoon, using a Formagraph. Thirty cows (11 Holstein-Friesian, 8 Holstein-Friesian × Jersey cross, and 11 Jersey) from a once-a-day milking herd and thirty cows (16 Holstein-Friesian, 10 Holstein-Friesian × Jersey cross, and 4 Jersey) from a twice-a-day milking herd were sampled in late lactation. The milk composition and coagulation properties were analysed for each milk sample. Jersey cows had better milk coagulation properties at each milking frequency-milking time compared to Holstein-Friesian cows. Curd firmness 30 min after the addition of rennet was positively (p < 0.05) correlated with the protein concentration. However, the correlations were inconsistent between milking frequencies and milking times, resulting in poor prediction of the changes in cheese-making potential. This study indicated that milk composition and coagulation properties were affected by breed and milking frequency. The effect of the breed could be due to the variation in the composition of the milk, but firm recommendations were hampered by a low number of samples. Further research with larger cow numbers is justified.

Acid and Rennet Coagulation Properties of A2 Milk

This study investigated the acid and rennet milk coagulation properties of A2 milk (β-casein (CN) A2A2 genotype), in comparison to a control milk (blend of A2A1/A1A1/A2A2 genotypes). Acid and rennet coagulation were evaluated using the Optigraph^® system, measuring the coagulation time, aggregation rate, and gel density or curd firmness. The acidification kinetics were monitored using a CINAC^® system, evaluating the time to reach pH 4.6, the acidification rate, the maximum acidification rate, the time required to reach it, and the latency time. The water-holding capacity of acid milk gels and the potential yield, total solids, and syneresis of enzymatic gels were also evaluated. Some variables were highly influenced by the farm factor, showing the importance of the effect of extrinsic parameters. Acid and enzymatic coagulation times were not affected in either milk. The A2 milk presented higher acid gel density and latency time than the control milk. Although the differences in water-holding capacity were not statistically significant, the A2 milk presented lower values, related with the higher gel density. The A2 milk also showed higher rennet aggregation rate and curd firmness than the control milk. Potential yield and syneresis were higher in the A2 milk, which is in accordance with the higher firmness of curd. Coagulation results and gel and curd properties indicate that it is possible to manufacture acid and rennet coagulation dairy products from A2 milk with no major differences when compared with a control milk.

What is the impact of amino acid mutations in the primary structure of caseins on the composition and functionality of milk and dairy products?

The impact of amino acid mutations within the peptide structure of bovine milk protein is important to understand as it can effect processability and subsequently effect its physiological properties. Genetic polymorphisms of bovine caseins can influence the chemical, structural, and technological properties, including casein micelle morphology, calcium distribution, network creation upon gelation, and surface activity. The A1 and A2 genetic variants of β-casein have recently acquired growing attention from both academia and industry, prompting new developments in the area. The difference between these two genetic variants is the inclusion of either proline in β-casein A2 or histidine in β-casein A1 at position 67 in the peptide chain. The aim of this review was to examine the extent to which milk and ingredient functionality is influenced by β-casein phenotype. One of the main findings of this review was although β-casein A1 was found to be the dominant variant in milks with superior acid gelation and rennet coagulation properties, milks comprised of β-casein A2 possessed greater emulsion and foam formation capabilities. The difference in the casein micelle assembly, hydrophobicity, and chaperone activity of caseins may explain the contrast in the functionality of milks containing β-casein from either A1 or A2 families. This review provides new insights into the subtle variations in the physicochemical properties of bovine milks, which could potentially support dairy producers in the development of new dairy products with different functional properties.

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Impact of β- and other caseins on the casein micelle structure and functionality.

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Proline and histidine in β-caseins play a key role in casein micelle conformation.

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Chaperone activity of β-casein A2 towards heat-induced aggregation of whey protein.

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Gels prepared of milks with β-casein A1 possess a denser and firmer structure.

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Ordered structure of β-casein A2 led to improved emulsion and foam formation.

A2 Milk: New Perspectives for Food Technology and Human Health

Although milk consumption is increasing worldwide, in some geographical regions, its consumption has persistently declined in recent decades. This fact, together with the increase in milk production prices, has caused both milk producers and the dairy industry to be immersed in a major crisis. Some possible solutions to this problem are to get people who do not currently consume milk to start drinking it again, or to market milk and dairy products with a higher added value. In this context, a type of milk called A2 has recently received attention from the industry. This type of milk, characterized by a difference in an amino acid at position 67 of the β-casein polypeptide chain, releases much smaller amounts of bioactive opioid peptide β-casomorphin 7 upon digestion, which has been linked to harmful effects on human health. Additionally, A2 milk has been attributed worse technological properties in the production of some dairy products. Thus, doubts exist about the convenience for the dairy industry to bet on this product. The aim of this review is to provide an update on the effects on human health of A2 milk, as well as its different technological properties to produce dairy products.

Properties of sodium caseinate as affected by the β-casein phenotypes

The aim of the study was to investigate the properties of sodium caseinate dispersions and oil-in-water emulsions obtained from cows' milk of either A1/A1, A1/A2, or A2/A2 β-casein phenotype. Protein structural characterisation was examined using Fourier Transform Infrared and Nuclear Magnetic Resonance spectroscopies, with physicochemical and interfacial properties assessed by analysing adsorbed protein content, hydrophobicity, solubility, and emulsion stability of the samples. Results showed variations in the secondary structure of all samples dependent of the presence of A1 or A2 β-caseins. The main differences included greater amounts of α-helix and β-sheet in A1/A1 and A1/A2 sodium caseinate dispersions that influenced their lower solubility, while random coils/polyproline II helixes were found only in A2/A2 sodium caseinate dispersion. In contrast, upon adsorption on the interface of A2/A2 sodium caseinate emulsion, the protein adopted ordered conformational motifs. This conformational shift supposedly arose from structural differences between the two β-casein proteoforms, which most likely enhanced the emulsion properties of A2/A2 sodium caseinate compared to either A1/A1 or A1/A2 sodium caseinates. The A2 β-casein in both, A1/A2 and A2/A2 sodium caseinates, appears to be able to more rapidly reach the oil droplet surface and was more efficient as emulsifying agent. The current results demonstrated that the conformational rearrangement of proteins upon adsorption to emulsion interfaces was dependent not only on hydrophobicity and on solubility, but also on the conformational flexibility of A1/A1, A1/A2, and A2/A2 β-casein phenotypes. These findings can assist in predicting the behaviour of sodium caseinates during relevant industrial processing.

Phosphorylation and glycosylation isoforms of bovine κ-casein variant E in homozygous Swedish Red cow milk detected by liquid chromatography-electrospray ionization mass spectrometry

Variations in the phosphorylation and glycosylation patterns of the common κ-casein (CN) variants A and B have been explored, whereas studies on variant E heterogeneity are scarce. This study reports for the first time the detailed phosphorylation and glycosylation pattern of the κ-CN variant E in comparison with variants A and B. Individual cow milk samples representing κ-CN genotype EE (n = 12) were obtained from Swedish Red cows, and the natural posttranslational modifications of its κ-CN were identified and quantified by liquid chromatography-electrospray mass spectrometry. In total, 12 unique isoform masses of κ-CN variant E were identified. In comparison, AA and BB milk consisted of 14 and 17 unique isoform masses, respectively. The most abundant κ-CN E isoform detected in the EE milk was the monophosphorylated, unglycosylated [1P 0G, ∼70%; where P indicates phosphorylation from single to triple phosphorylation (1-3P), and G indicates glycosylation from single to triple glycosylation (1-3G)] form, followed by diphosphorylated, unglycosylated (2P 0G, ∼12%) form, resembling known patterns from variants A and B. However, a clear distinction was the presence of the rare triphosphorylated, nonglycosylated (3P 0G, ∼0.05%) κ-CN isoform in the EE milk. All isoforms detected in variant E were phosphorylated, giving a phosphorylation degree of 100%. This is comparable with the phosphorylation degree of variants A and B, being also almost 100%, though with very small amounts of nonphosphorylated, glycosylated isoforms detected. The glycosylation degree of variant E was found to be around 17%, a bit higher than observed for variant B (around 14%), and higher than variant A (around 7%). Among glycosylation, the glycan e was the most common type identified for all 3 variants, followed by c/d (straight and branched chain trisaccharides, respectively), and b. In contrast to κ-CN variants A and B, no glycan of type a was found in variant E. Taken together, this study shows that the posttranslational modification pattern of variant E resembles that of known variants to a large extent, but with subtle differences.

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 (α_S1-CN, α_S2-CN, β-CN, κ-CN) and the 2 most abundant whey proteins (α-lactalbumin and β-lactoglobulin). Relative quantification of these proteins and their major isoforms, including phosphorylations of α_S1-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, α_S1-CN variant D was identified in low frequency in 3 of the 6 native Norwegian breeds. In general, α_S1-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 α_S1-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 α_S2-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.

Effect of Protein Genotypes on Physicochemical Properties and Protein Functionality of Bovine Milk: A Review

Milk protein comprises caseins (CNs) and whey proteins, each of which has different genetic variants. Several studies have reported the frequencies of these genetic variants and the effects of variants on milk physicochemical properties and functionality. For example, the C variant and the BC haplotype of αS1-casein (αS1-CN), β-casein (β-CN) B and A1 variants, and κ-casein (κ-CN) B variant, are favourable for rennet coagulation, as well as the B variant of β-lactoglobulin (β-lg). κ-CN is reported to be the only protein influencing acid gel formation, with the AA variant contributing to a firmer acid curd. For heat stability, κ-CN B variant improves the heat resistance of milk at natural pH, and the order of heat stability between phenotypes is BB > AB > AA. The A2 variant of β-CN is more efficient in emulsion formation, but the emulsion stability is lower than the A1 and B variants. Foaming properties of milk with β-lg variant B are better than A, but the differences between β-CN A1 and A2 variants are controversial. Genetic variants of milk proteins also influence milk yield, composition, quality and processability; thus, study of such relationships offers guidance for the selection of targeted genetic variants.

Sequence-based genome-wide association study of individual milk mid-infrared wavenumbers in mixed-breed dairy cattle

BACKGROUND

Fourier-transform mid-infrared (FT-MIR) spectroscopy provides a high-throughput and inexpensive method for predicting milk composition and other novel traits from milk samples. While there have been many genome-wide association studies (GWAS) conducted on FT-MIR predicted traits, there have been few GWAS for individual FT-MIR wavenumbers. Using imputed whole-genome sequence for 38,085 mixed-breed New Zealand dairy cattle, we conducted GWAS on 895 individual FT-MIR wavenumber phenotypes, and assessed the value of these direct phenotypes for identifying candidate causal genes and variants, and improving our understanding of the physico-chemical properties of milk.

RESULTS

Separate GWAS conducted for each of 895 individual FT-MIR wavenumber phenotypes, identified 450 1-Mbp genomic regions with significant FT-MIR wavenumber QTL, compared to 246 1-Mbp genomic regions with QTL identified for FT-MIR predicted milk composition traits. Use of mammary RNA-seq data and gene annotation information identified 38 co-localized and co-segregating expression QTL (eQTL), and 31 protein-sequence mutations for FT-MIR wavenumber phenotypes, the latter including a null mutation in the ABO gene that has a potential role in changing milk oligosaccharide profiles. For the candidate causative genes implicated in these analyses, we examined the strength of association between relevant loci and each wavenumber across the mid-infrared spectrum. This revealed shared association patterns for groups of genomically-distant loci, highlighting clusters of loci linked through their biological roles in lactation and their presumed impacts on the chemical composition of milk.

CONCLUSIONS

This study demonstrates the utility of FT-MIR wavenumber phenotypes for improving our understanding of milk composition, presenting a larger number of QTL and putative causative genes and variants than found from FT-MIR predicted composition traits. Examining patterns of significance across the mid-infrared spectrum for loci of interest further highlighted commonalities of association, which likely reflects the physico-chemical properties of milk constituents.

Differential in vitro digestion rates in gastric phase of bovine milk with different κ-casein phenotypes

Casein (CN) micelles will coagulate in the stomach after ingestion, which is similar to the cheesemaking process. Although genetic variants of bovine proteins, especially κ-CN, have been confirmed to influence the coagulation properties of the CN micelle, its influence on milk digestibility has not been revealed yet. This study aimed to investigate how genetic variants, glycosylation degree of κ-CN, and CN micelle size influence digestion rates during in vitro gastrointestinal digestion. Three milk pools, representing κ-CN phenotypes of either AA, BB, or AB composition were prepared from milk of individual Danish Holstein cows representing these different genotypes. In vitro digestion of the 3 milk pools, AA, BB, or AB, was investigated by sodium dodecyl sulfate-PAGE, liquid chromatography-mass spectrometry, and degree of hydrolysis. The results showed that κ-CN AA milk had faster digestion rate in the gastric phase compared with BB and AB milks, whereas only small differences were apparent in the intestinal digestion phase. The results further documented that the milk pools representing κ-CN phenotypes BB and AB had comparable overall glycosylation degrees (50.9% and 50.0%, respectively) and higher than that of the AA milk pool (46.9%). Further, the AA milk pool was associated with larger CN micelles. These differences in CN micelle sizes and glycosylation degrees can be part of underlying explanations for the differential in vitro digestion rates observed between the AA, BB, and AB κ-CN milk pools.

Gene polymorphisms influencing yield, composition and technological properties of milk from Czech Simmental and Holstein cows

Objective

The aim of the study was to evaluate the influence of polymorphic loci and other factors on milk performance and the technological properties of milk.

Methods

The analysis was performed on Simmental and Holstein cows in field conditions (n = 748). Milk yield in kg, fat and protein percentage and yield were evaluated. Technological properties were evaluated by milk fermentation ability, renneting, and an alcohol test. Polymorphisms in the acyl-CoA diacylgycerol transferase 1 (DGAT1), leptin (LEP), fatty acid synthase (FASN), stearoyl CoA desaturase 1 (SCD1), casein beta (CSN2), casein kappa (CSN3), and lactoglobulin beta genes were genotyped, and association analysis was performed.

Results

The DGAT1 AA genotype was associated with higher milk, protein and fat yields (p<0.05). The MM genotype in the LEP gene was associated with a lower protein percentage and the W allele with a higher protein percentage (p<0.05). In cows with the FASN GG genotype, the protein percentage was higher, but the A allele was associated with higher milk, protein and fat yields than the G allele. The TT genotype in SCD1 was associated with the lowest milk, protein and fat yields and with the highest milk protein percentage (p<0.01). The T allele had higher values than the C allele (p<0.05) except for fat percentage. The genotype CSN3 AA was associated with a significantly heightened milk yield; BB was associated with a high protein percentage. The effect of the alleles on the technological properties was not significant. The CSN2 BB genotype was associated with the best alcohol test (p<0.01), and the renneting order was inverse. Milk from cows with the CSN2 A¹A¹ genotype was best in the milk fermentation ability. CSN3 significantly affected the technological properties.

Conclusion

The findings revealed the potential of some polymorphic loci for use in dairy cattle breeding and for the management of milk quality. In field research, the pivotal role of farms in milk yield, composition and technological properties was confirmed.

A genome-wide association study reveals specific transferases as candidate loci for bovine milk oligosaccharides synthesis

BACKGROUND

Human milk oligosaccharides (OS) play a key role in brain and gut microbiota development of the neonate, but the underlying biosynthetic steps of OS in the mammary gland are still largely unknown. As bovine milk contains OS with somewhat similar structures and functionalities there is increased interest in further understanding the genetic basis underlying the OS content of milk for eventual extraction and generation of value-added ingredients for infant formulas and nutraceuticals. The present study is the first to report on genetic parameter estimation as well as on a genome wide association study (GWAS) from the largest bovine milk OS dataset analyzed to date.

RESULTS

In total 15 different bovine milk OS were monitored. Heritabilities ranged from 0 to 0.68 in Danish Holstein and from 0 to 0.92 in Danish Jersey. The GWAS identified in total 1770 SNPs (FDR < 0.10) for five different OS in Danish Holstein and 6913 SNPs (FDR < 0.10) for 11 OS in Danish Jersey. In Danish Holstein, a major overlapping QTL was identified on BTA1 for LNH and LNT explaining 24% of the variation in these OS. The most significant SNPs were associated with B3GNT5, a gene encoding a glycosyltransferase involved in glycan synthesis. In Danish Jersey, a very strong QTL was detected for the OS with composition 2 Hex 1 HexNAc (isomer 1) on BTA11. The most significant SNP had -log10(P-value) of 52.88 (BOVINEHD1100030300) and was assigned to ABO, a gene encoding ABO blood group glycosyltransferases. This SNP has been reported to be a missense mutation and explains 56% of the OS variation. Other candidate genes of interest identified for milk OS were ALG3, B3GALNT2, LOC520336, PIGV, MAN1C1, ST6GALNAC6, GLT6D1, GALNT14, GALNT17, COLGALT2, LFNG and SIGLEC.

CONCLUSION

To our knowledge, this is the first study documenting a solid breeding potential for bovine milk OS and a strong indication of specific candidate genes related to OS synthesis underlying this genetic influence. This new information has the potential to guide breeding strategies to achieve production of milk with higher diversity and concentration of OS and ultimately facilitate large-scale extraction of bovine milk OS.

Genetic variation in serum protein pattern and blood β-hydroxybutyrate and their relationships with udder health traits, protein profile, and cheese-making properties in Holstein cows

The aim of this study was to investigate in Holstein cows the genetic basis of blood serum metabolites [i.e., total protein, albumin, globulin, albumin:globulin ratio (A:G), and blood β-hydroxybutyrate (BHB)], a set of milk phenotypes related to udder health, milk quality technological characteristics, and genetic relationships among them. Samples of milk were collected from 498 Holstein cows belonging to 28 herds. All animal welfare and milk phenotypes were assessed using standard analytical methodology. A set of Bayesian univariate and bivariate animal models was implemented via Gibbs sampling, and statistical inference was based on the marginal posterior distributions of parameters of concern. We observed a small additive genetic influence for serum albumin concentrations, moderate heritability (≥0.20) for total proteins, globulins, and A:G, and high heritability (0.37) for blood BHB. Udder health traits (somatic cell score, milk lactose, and milk pH) showed low or moderate heritabilities (0.15-0.20), whereas variations in milk protein fraction concentrations were confirmed as mostly under genetic control (heritability: 0.21-0.71). The moderate and high heritabilities observed for milk coagulation properties and curd firming modeling parameters provided confirmation that genetic background exerts a strong influence on the cheese-making ability of milk, largely due to genetic polymorphisms in the major milk protein genes. Blood BHB showed strong negative genetic correlations with globulins (-0.619) but positive correlations with serum albumin (0.629) and A:G (0.717), which suggests that alterations in the serum protein pattern and BHB blood levels are likely to be genetically related. Strong relationships were found between albumin and fat percentages (-0.894), between globulin and α_S2-CN (-0.610), and, to a lesser extent, between serum protein pattern and milk technological characteristics. Genetic relationships between blood BHB and traits related to udder health and milk quality and technological characteristics were mostly weak. This study provides evidence that there is exploitable additive genetic variation for traits related to animal health and welfare and throws light on the shared genetic basis of these traits and the phenotypes related to the quality and cheese-making ability of milk.

Modeling heterogeneous (co)variances from adjacent-SNP groups improves genomic prediction for milk protein composition traits

Background

Accurate genomic prediction requires a large reference population, which is problematic for traits that are expensive to measure. Traits related to milk protein composition are not routinely recorded due to costly procedures and are considered to be controlled by a few quantitative trait loci of large effect. The amount of variation explained may vary between regions leading to heterogeneous (co)variance patterns across the genome. Genomic prediction models that can efficiently take such heterogeneity of (co)variances into account can result in improved prediction reliability. In this study, we developed and implemented novel univariate and bivariate Bayesian prediction models, based on estimates of heterogeneous (co)variances for genome segments (BayesAS). Available data consisted of milk protein composition traits measured on cows and de-regressed proofs of total protein yield derived for bulls. Single-nucleotide polymorphisms (SNPs), from 50K SNP arrays, were grouped into non-overlapping genome segments. A segment was defined as one SNP, or a group of 50, 100, or 200 adjacent SNPs, or one chromosome, or the whole genome. Traditional univariate and bivariate genomic best linear unbiased prediction (GBLUP) models were also run for comparison. Reliabilities were calculated through a resampling strategy and using deterministic formula.

Results

BayesAS models improved prediction reliability for most of the traits compared to GBLUP models and this gain depended on segment size and genetic architecture of the traits. The gain in prediction reliability was especially marked for the protein composition traits β-CN, κ-CN and β-LG, for which prediction reliabilities were improved by 49 percentage points on average using the MT-BayesAS model with a 100-SNP segment size compared to the bivariate GBLUP. Prediction reliabilities were highest with the BayesAS model that uses a 100-SNP segment size. The bivariate versions of our BayesAS models resulted in extra gains of up to 6% in prediction reliability compared to the univariate versions.

Conclusions

Substantial improvement in prediction reliability was possible for most of the traits related to milk protein composition using our novel BayesAS models. Grouping adjacent SNPs into segments provided enhanced information to estimate parameters and allowing the segments to have different (co)variances helped disentangle heterogeneous (co)variances across the genome.

Milk protein polymorphisms and casein haplotypes in Butana cattle

Butana is a Bos indicus dairy cattle breed that is well adapted to the local environment of Sudan. The breed has been gradually declining in number due to breed substitution. Therefore, conservation and improvement strategies are required to maintain this breed. The aim of the present study was to assess genetic variation that is characteristic for Butana cattle in the milk protein genes CSN1S1, CSN2, CSN1S2, CSN3, LALBA, and LGB. In a first step, genomic DNA of five unrelated individuals was comparatively sequenced across all exon and flanking sequences. Ninety-three single nucleotide polymorphisms (SNPs) were identified in Butana cattle compared with the Bos taurus reference sequence at Ensembl. We confirmed the recently identified protein variants CSN2*J, CSN2*L, and LALBA*E. Fifty-two SNPs in non-coding regions are novel. Among the novel SNPs, five are located in promoter regions, three of them are in putative transcription factor binding sites (TFBSs) of the CSN1S2 promoter. Fifteen SNPs potentially affect miRNA target sites. In a second step, 50 unrelated Butana cattle were genotyped. This allowed deriving haplotypes for the casein gene cluster on BTA6. The most frequent haplotype was CSN1S1*C-CSN2*A ² -CSN1S2*A-CSN3*A (C-A ² -A-A, frequency 0.1546). Considering the newly identified CSN1S2 promoter variants, the most frequent haplotype was C-A ² -TTC-A-A (0.1046), with TTC as the promoter variant. The information on protein and promoter variants can be used for the development of conservation and breeding strategies for this local breed.

Breed of cow and herd productivity affect milk composition and modeling of coagulation, curd firming, and syneresis

Milk coagulation properties (MCP) have been widely investigated in the past using milk collected from different cattle breeds and herds. However, to our knowledge, no previous studies have assessed MCP in individual milk samples from several multi-breed herds characterized by either high or low milk productivity, thereby allowing the effects of herd and cow breed to be evaluated independently. Multi-breed herds (n=41) were classified into 2 categories based on milk productivity (high vs. low), defined according to the average milk net energy yielded daily by lactating cows. Milk samples were taken from 1,508 cows of 6 different breeds: 3 specialized dairy (Holstein-Friesian, Brown Swiss, Jersey) and 3 dual-purpose (Simmental, Rendena, Alpine Grey) breeds, and analyzed in duplicate (3,016 tests) using 2 lactodynamographs to obtain 240 curd firming (CF) measurements over 60min (1 every 15 s) for each duplicate. The 5 traditional single-point MCP (RCT, k₂₀, a₃₀, a₄₅, and a₆₀) were yielded directly by the instrument from the available CF measures. All 240 CF measures of each replicate were also used to estimate 4 individual equation parameters: RCT estimated according to curd firm change over time modeling (RCT_eq), asymptotic potential curd firmness (CF_P), curd firming instant rate constant (k_CF), and syneresis instant rate constant (k_SR) and 2 derived traits: maximum curd firmness achieved within 45min (CF_max) and time at achievement of CF_max (t_max) by curvilinear regression using a nonlinear procedure. Results showed that the effect of herd-date on traditional and modeled MCP was modest, ranging from 6.1% of total variance for k₂₀ to 10.7% for RCT, whereas individual animal variance was the highest, ranging from 32.0% for t_max to 82.5% for RCT_eq. The repeatability of MCP was high (>80%) for all traits except those associated with the last part of the lactodynamographic curve (i.e., a₆₀, k_SR, k_CF, and t_max: 57 to 71%). Reproducibility, taking into account the effect of instrument, was equal to or slightly lower than repeatability. Milk samples collected in farms characterized by high productivity exhibited delayed coagulation (RCT_eq: 18.6 vs. 16.3min) but greater potential curd firmness (CF_P: 76.8 vs. 71.9mm) compared with milk samples collected from low-productivity herds. Parity and days in milk influenced almost all MCP. Large differences in all MCP traits were observed among breeds, both between specialized and dual-purpose breeds and within these 2 groups of breeds, even after adjusting for milk quality and yield. Milk quality and MCP of samples from Jersey cows, and coagulation time of samples from Rendena cows were better than in milk from Holstein-Friesian cows, and intermediate results were found with the other breeds of Alpine origin. The results of this study, taking into account the intrinsic limitation of this technique, show that the effects of breed on traditional and modeled MCP are much greater than the effects of herd productivity class, parity, and DIM. Moreover, the variance in individual animals is much greater than the variance in individual herds within herd productivity class. It seems that improvement in MCP depends more on genetics (e.g., breed, selection) than on environmental and management factors.

Quantitation and Identification of Intact Major Milk Proteins for High-Throughput LC-ESI-Q-TOF MS Analyses

Cow's milk is an important source of proteins in human nutrition. On average, cow's milk contains 3.5% protein. The most abundant proteins in bovine milk are caseins and some of the whey proteins, namely beta-lactoglobulin, alpha-lactalbumin, and serum albumin. A number of allelic variants and post-translationally modified forms of these proteins have been identified. Their occurrence varies with breed, individuality, stage of lactation, and health and nutritional status of the animal. It is therefore essential to have reliable methods of detection and quantitation of these proteins. Traditionally, major milk proteins are quantified using liquid chromatography (LC) and ultra violet detection method. However, as these protein variants co-elute to some degree, another dimension of separation is beneficial to accurately measure their amounts. Mass spectrometry (MS) offers such a tool. In this study, we tested several RP-HPLC and MS parameters to optimise the analysis of intact bovine proteins from milk. From our tests, we developed an optimum method that includes a 20-28-40% phase B gradient with 0.02% TFA in both mobile phases, at 0.2 mL/min flow rate, using 75°C for the C8 column temperature, scanning every 3 sec over a 600-3000 m/z window. The optimisations were performed using external standards commercially purchased for which ionisation efficiency, linearity of calibration, LOD, LOQ, sensitivity, selectivity, precision, reproducibility, and mass accuracy were demonstrated. From the MS analysis, we can use extracted ion chromatograms (EICs) of specific ion series of known proteins and integrate peaks at defined retention time (RT) window for quantitation purposes. This optimum quantitative method was successfully applied to two bulk milk samples from different breeds, Holstein-Friesian and Jersey, to assess differences in protein variant levels.