The Polymorphism in Various Milk Protein Genes in Polish Holstein-Friesian Dairy Cattle

Effects of protein genetic variants on their phosphorylation levels, milk composition, milk proteome, and milk coagulation ability in Chinese Holstein bovine milk

Milk samples were collected from 3625 Chinese Holstein cows to assess the effects of κ-casein (κ-CN) and β-lactoglobulin (β-LG) genetic variants on its milk coagulation properties. The results show that Chinese Holstein cows have a higher frequency of the κ-CN AA and AB variants, and β-LG of the AB and AA variants. Of these, κ-CN B variants, the β-LG AA and BB variants were more frequent in milk showing good coagulation. The effects of the genetic variants on milk composition, milk proteome, and protein phosphorylation sites were studied. The results showed that higher concentrations of protein and dry matter were found in κ-CN BE variant. Moreover, large variations in milk proteome among different κ-CN and β-LG variants were observed. Highly phosphorylated for κ-CN, especially Ser97, was observed in cows with the κ-CN BE variant, but no effect of β-LG variants on phosphorylation site was found. Of the various factors examined, variation of κ-CN phosphorylation sites Ser97 may be the most important in affecting casein structure and milk coagulation ability. Some milk protein contents were found to be negative factors for milk coagulation. In summary, this study showed that κ-CN genetic variants contained different milk compositions and phosphorylation site Ser97 influenced milk coagulation.

Genome-wide association study and functional annotation analyses for nitrogen efficiency index and its composition traits in dairy cattle

The aims of this study were (1) to identify genomic regions associated with a N efficiency index (NEI) and its composition traits and (2) to analyze the functional annotation of identified genomic regions. The NEI included N intake (NINT1), milk true protein N (MTPN1), milk urea N yield (MUNY1) in primiparous cattle, and N intake (NINT2+), milk true protein N (MTPN2+), and milk urea N yield (MUNY2+) in multiparous cattle (2 to 5 parities). The edited data included 1,043,171 records on 342,847 cows distributed in 1,931 herds. The pedigree consisted of 505,125 animals (17,797 males). Data of 565,049 SNPs were available for 6,998 animals included in the pedigree (5,251 females and 1,747 males). The SNP effects were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 50 consecutive SNPs (with an average size of about 240 kb) was calculated. The top 3 genomic regions explaining the largest rate of the total additive genetic variance of the NEI and its composition traits were selected for candidate gene identification and quantitative trait loci (QTL) annotation. The selected genomic regions explained from 0.17% (MTPN2+) to 0.58% (NEI) of the total additive genetic variance. The largest explanatory genomic regions of NEI, NINT1, NINT2+, MTPN1, MTPN2+, MUNY1, and MUNY2+ were Bos taurus autosome 14 (1.52-2.09 Mb), 26 (9.24-9.66 Mb), 16 (75.41-75.51 Mb), 6 (8.73-88.92 Mb), 6 (8.73-88.92 Mb), 11 (103.26-103.41 Mb), 11 (103.26-103.41 Mb). Based on the literature, gene ontology, Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction, 16 key candidate genes were identified for NEI and its composition traits, which are mainly expressed in the milk cell, mammary, and liver tissues. The number of enriched QTL related to NEI, NINT1, NINT2+, MTPN1, and MTPN2+ were 41, 6, 4, 11, 36, 32, and 32, respectively, and most of them were related to the milk, health, and production classes. In conclusion, this study identified genomic regions associated with NEI and its composition traits, and identified key candidate genes describing the genetic mechanisms of N use efficiency-related traits. Furthermore, the NEI reflects not only its composition traits but also the interactions among them.

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.