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The lactation curve in dairy cows is influenced by the calving season, which is highly dependent on the warm climate in semi-arid regions. Objective herein was to evaluate effects of calving season on the parameters and components of the lactation curve in Holstein cows. The study included 278,317 milk records collected from 1086 cows from the 1st to 5th calving and good body condition score. The cows were grouped according to the season in which they calved: winter-calved (CS1), summer-calved (CS2), and autumn-calved cows (CS3). Ambient temperature and humidity data were used to calculate the temperature-humidity index (THI). The NLIN procedure was used to estimate the parameters of the lactation curve that served to calculate the components. The mixed procedure was executed to analyze the fixed effect of calving season. Associations between lactation curve traits were tested using correlation and regression analyses. A univariate model was utilized to calculate heritability. Average THI values during the lactation period were 73.5, 68.5, and 69.5 units for CS1, CS2, and CS3 groups, respectively. Initial milk production and increasing rate to the maximum milk yield in CS1 and CS3 groups were higher (P < 0.05) than CS2 cows. However, persistency and total milk yield during the entire lactation period were superior (P < 0.05) for CS2 and CS3 cows compared to CS1 cows, probably due to the moderate heat stress during the lactation period in the CS1 group. In cows from CS2 and CS3 groups, total milk production at 305 days was moderately correlated with initial milk production (r = 0.47; P < 0.05), and highly correlated with milk yield at peak day (r = 0.91; P < 0.05) which resulted as reliable predictor for total milk yield during the entire lactation (R 2  = 0.83). In conclusion, the THI prevailing during the different calving seasons appeared to be an important factor influencing the performance of the lactation curve., (© 2022. The Author(s), under exclusive licence to Springer Nature B.V.)

The objective of this study was to examine five different sources of RNA, namely mammary gland tissue (MGT), milk somatic cells (SC), laser microdissected mammary epithelial cells (LCMEC), milk fat globules (MFG) and antibody-captured milk mammary epithelial cells (mMEC) to analyze the bovine mammary gland transcriptome using RNA-Sequencing. Our results provide a comparison between different sampling methods (invasive and non-invasive) to define the transcriptome of mammary gland tissue and milk cells. This information will be of value to investigators in choosing the most appropriate sampling method for different research applications to study specific physiological states during lactation. One of the simplest procedures to study the transcriptome associated with milk appears to be the isolation of total RNA directly from SC or MFG released into milk during lactation. Our results indicate that the SC and MFG transcriptome are representative of MGT and LCMEC and can be used as effective and alternative samples to study mammary gland expression without the need to perform a tissue biopsy.

Background: Studies of normal human mammary gland development and function have mostly relied on cell culture, limited surgical specimens, and rodent models. Although RNA extracted from human milk has been used to assay the mammary transcriptome non-invasively, this assay has not been adequately validated in primates. Thus, the objectives of the current study were to assess the suitability of lactating rhesus macaques as a model for lactating humans and to determine whether RNA extracted from milk fractions is representative of RNA extracted from mammary tissue for the purpose of studying the transcriptome of milk-producing cells., Results: We confirmed that macaque milk contains cytoplasmic crescents and that ample high-quality RNA can be obtained for sequencing. Using RNA sequencing, RNA extracted from macaque milk fat and milk cell fractions more accurately represented RNA from mammary epithelial cells (cells that produce milk) than did RNA from whole mammary tissue. Mammary epithelium-specific transcripts were more abundant in macaque milk fat, whereas adipose or stroma-specific transcripts were more abundant in mammary tissue. Functional analyses confirmed the validity of milk as a source of RNA from milk-producing mammary epithelial cells., Conclusions: RNA extracted from the milk fat during lactation accurately portrayed the RNA profile of milk-producing mammary epithelial cells in a non-human primate. However, this sample type clearly requires protocols that minimize RNA degradation. Overall, we validated the use of RNA extracted from human and macaque milk and provided evidence to support the use of lactating macaques as a model for human lactation.

Human milk lactoferrin (hmLF) is the most abundant glycoprotein present in human milk and displays a broad range of protective functions in the gut of newborn infants. hmLF is N-glycosylated, but little is known about the lactation stage-related development of the glycosylation phenotype. hmLF glycosylation from milk samples from five donors during the first 10 weeks of lactation was assessed and observed to be more diverse than previously reported. During this period dynamic changes in glycosylation were observed corresponding to a decrease in glycosylation in the second week followed by an increase in total glycosylation as well as higher order fucosylation thereafter. Gene expression analysis was performed in milk somatic cells from a sixth subject. It was found that fucosyltransferase expression increased during entire period, whereas expression of genes for the oligosaccharyl transferase complex decreased in the second week. The effect of hmLF glycosylation was examined for the protein's ability to affect bacterial binding to epithelial cells. hmLF significantly inhibited pathogen adhesion and purified hmLF glycans significantly reduced Salmonella invasion of colonic epithelial cells to levels associated with non-invasive deletion mutants. This study indicates that hmLF glycosylation is tightly regulated by gene expression and that glyco-variation is involved in modulating pathogen association.

To fine map a quantitative trait locus (QTL) affecting milk production traits previously associated with microsatellite RM188, we implemented an interval mapping analysis by using microsatellite markers in a large Israeli Holstein half-sib sire family, and linkage disequilibrium (LD) mapping in a large set of US Holstein bulls. Interval mapping located the target QTL to the near vicinity of RM188. For the LD mapping, we identified 42 single nucleotide polymorphisms (SNP) in 15 genes in a 12-Mb region on bovine chromosome 4. A total of 24 tag SNP were genotyped in 882 bulls belonging to the University of California Davis archival collection of Holstein bull DNA samples with predicted transmitted ability phenotypes. Marker-to-marker LD analysis revealed 2 LD blocks, with intrablock r(2) values of 0.10 and 0.46, respectively; outside the blocks, r(2) values ranged from 0.002 to 0.23. A standard additive/dominance model using the generalized linear model procedure of SAS and the regression module of HelixTree software were used to test marker-trait associations. Single nucleotide polymorphism 9 on ARL4A, SNP10 on XR&#95;027435.1, SNP12 on ETV1, SNP21 on SNX13, and SNP24 were significantly associated with milk production traits. We propose the interval encompassing ARL4A and SNX13 genes as a candidate region in bovine chromosome 4 for a concordant QTL related to milk protein traits in dairy cattle. Functional studies are needed to confirm this result.

Background: The newly assembled Bos taurus genome sequence enables the linkage of bovine milk and lactation data with other mammalian genomes., Results: Using publicly available milk proteome data and mammary expressed sequence tags, 197 milk protein genes and over 6,000 mammary genes were identified in the bovine genome. Intersection of these genes with 238 milk production quantitative trait loci curated from the literature decreased the search space for milk trait effectors by more than an order of magnitude. Genome location analysis revealed a tendency for milk protein genes to be clustered with other mammary genes. Using the genomes of a monotreme (platypus), a marsupial (opossum), and five placental mammals (bovine, human, dog, mice, rat), gene loss and duplication, phylogeny, sequence conservation, and evolution were examined. Compared with other genes in the bovine genome, milk and mammary genes are: more likely to be present in all mammals; more likely to be duplicated in therians; more highly conserved across Mammalia; and evolving more slowly along the bovine lineage. The most divergent proteins in milk were associated with nutritional and immunological components of milk, whereas highly conserved proteins were associated with secretory processes., Conclusions: Although both copy number and sequence variation contribute to the diversity of milk protein composition across species, our results suggest that this diversity is primarily due to other mechanisms. Our findings support the essentiality of milk to the survival of mammalian neonates and the establishment of milk secretory mechanisms more than 160 million years ago.

The objectives of this study were to form appropriate composite kappa-beta-alpha(s1)-CN genotypes in order to assess which genotypes were favorably associated with first lactation milk production, fat and protein percentages, and fat and protein production for data of 916 Holstein and 116 Jersey cows. Multiple-trait animal models were used with assumed fixed effects for herd, year and season of calving, age at calving, days open, composite kappa-beta-alpha(s1)-CN genotypes, and beta-LG genotypes. The differences between the beta-LG genotypes for production traits were not statistically significant for either breed. The proportion of phenotypic variance that was due to the composite kappa-beta-alpha(s1)-Cn genotypes was 5% for milk production, 4% for protein production, and 3% for fat percentage. The kappa-beta-alpha(s1)-CN genotype ABA1A2BB was superior to the comparable AAA1A2BB and ABA1A1BB genotypes by 252 and 338 kg for first lactation milk yield, respectively, and 8.7 and 11.5 kg for protein yield, respectively. Thus, neither the beta-CN A2 allele nor the kappa-CN B allele alone had a positive effect on milk and protein production, but the joint effect was strongly positive. These results may be explained by epistatic effects between the kappa-CN and beta-CN loci and possibly by closely linked quantitative trait loci with favorable alleles on the kappa-beta-alpha(s1)-CN BA2B haplotype.

The objective of this work was to estimate the contribution of milk protein genotype to production traits of Holstein cattle. Two approaches were employed. The first was based on an animal model analysis of milk records in which cows were genotyped for milk protein variants. The second approach was the analysis of PTA of sires in which the sires were genotyped for their milk protein variants. Results of the animal model analysis agreed qualitatively with previously published analyses of cow records, indicating only a minor contribution of milk protein genotype to production traits. Qualitative similarity was also found between the analysis of sire transmitting abilities and the animal model. Algebraic results suggested, however, that an indirect analysis of published sire transmitting abilities does not provide unbiased estimates of differences in milk protein genotypes. Although analysis of PTA is simple, only a direct analysis of genotyped cows with an animal model provides unbiased estimates of genotype differences.

Genotypes of 112 Israeli Holstein sires were determined for beta-lactoglobulin and kappa-casein by restriction fragment length polymorphism analysis of amplified DNA. Frequencies of the A alleles were .89 and .52 for kappa-casein and beta-lactoglobulin, respectively. Genotype frequencies were in accordance with Hardy-Weinberg equilibrium. Two models were used to test the effect of these loci on production of milk, fat, and protein and on fat and protein percentages. The dependent variable in the first model was production of 84,593 daughters of 110 genotyped sires, and the independent variables were herd-year-season, sire genotype for beta-lactoglobulin and kappa-casein, the interaction of the two loci, and sire nested within genotype. In the second model, the dependent variable was individual animal model genetic evaluations of 111 sires for production traits, and milk protein genotypes were the independent variables. The only significant effect of genotype with both models was the interaction of the two loci on fat percentage. When sires, rather than cows, were genotyped, the contrasted groups differed by only one-half of the genotype effect, but the residual variance was reduced.