• Animal cells and systems
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• v.1 no.4
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• pp.603-608
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• 1997

Analysis of the 5'-regulatory sequence of the caprine ${\beta}$-lactoglobulin (BLG) gene promoter revealed that two different types of activation were mediated by discrete regions, from -740 to -470 and from -205 to 109, in cultured mammary HC11 cells. Activation mediated by the proximal region was observed regardless of cell growth status. Distal activation, however, was observed only after confluent growth of the cells and was enhanced by the lactogenic hormones. This activation was accompanied by appearance of binding activity of proteins to these regions in the mammary HC11 cells. The binding motifs were broadly distributed over the upstream regulatory sequence. Comparison of the binding regions and mutation analysis suggest that a binding motif homologous to the ${\gamma}$-interferon responsive element (${\gamma}$-IRE) is responsible for transcriptional activation by hormonal induction in the mammary HC11 cells. The multiple ${\gamma}$-IRE homologous motifs seem to play a significant role in enhancing mammary cell-specific activation of the caprine BLG gene.

• Development and Reproduction
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• v.4 no.2
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• pp.221-229
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• 2000

Lactogenesis in mammary gland is under the control of various lactogenic hormones including hypophysial growth hormone and prolactin. Recent studies reported that such pituitary lactogenic hormones are also expressed in mammary cells as well as in pituitary. For the purpose to analyze the role of these non-pituitary hormones in mammary cells, $\beta$ -lactoglobulin (BLG) gene promoter was selected as a model system. The growth hormone suppressed BLG promoter activity when it was applied alone on cultured mammary HCll cells. Along with lactogenic hormones such as insulin, prolactin and glucocorticoid, however, it significantly enhanced expression of BLG promoter activity in a dosage- dependent manner. Exogenous expression of the growth hormone gene in cultured mammary cells also strongly promoted cell proliferation and BLG promoter activity. Bovine growth hormone promoter, on the contrary, did not revealed any notable activity. Above results suggest that endogenous expression of the pituitary hormone genes in mammary cells is not a regulation leakage but a physiological control. Moreover, artificial overproduction of the growth hormone in mammary gland may help increase milk production.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.8
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• pp.1175-1182
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• 2017

Objective: To create genetically modified goat as a biopharming source of recombinant human lacotoferrin (hLF) with transcription activator-like effector nucleases. Methods: TALENs and targeting vector were transferred into cultured fibroblasts to insert hLF cDNA in the goat beta-lactoglobulin (BLG) locus with homology-directed repair. The gene targeted efficiency was checked using sequencing and TE7I assay. The bi-allelic gene targeted colonies were isolated and confirmed with polymerase chain reaction, and used as donor cells for somatic cell nuclear transfer (SCNT). Results: The targeted efficiency for BLG gene was approximately 10%. Among 12 Bi-allelic gene targeted colonies, five were used in first round SCNT and 4 recipients (23%) were confirmed pregnant at 30 d. In second round SCNT, 7 (53%), 4 (31%), and 3 (23%) recipients were confirmed to be pregnant by ultrasound on 30 d, 60 d, and 90 d. Conclusion: This finding signifies the combined use of TALENs and SCNT can generate biallelic knock-in fibroblasts that can be cloned in a fetus. Therefore, it might lay the foundation for transgenic hLF goat generation and possible use of their mammary gland as a bioreactor for large-scale production of recombinant hLF.

• Asian-Australasian Journal of Animal Sciences
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• v.11 no.4
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• pp.422-427
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• 1998

The gene and genotypic frequencies of ${\kappa}$-casein (${\kappa}$-CN), ${\beta}$-lactoglobulin (${\beta}$-LG), growth hormone (bGH) and prolactin (bPRL) loci in Korean cattle were investigated using PCR-RFLP analyses. Genomic DNA samples were obtained from 290 cows and 30 AI bulls. In both cows and bulls, the most predominant genotypes of ${\kappa}$-CN, ${\beta}$-LG, bGH and bPRL loci were AB, BB, AA and AA, respecitively. The frequencies of A and B alleles for ${\kappa}$-CN locus were .612 and .388 for cows and .567 and .433 for bulls. The respective frequencies of A and B alleles for ${\beta}$-LG locus were .153 and .847 in cows and .217 and .783 in bulls. The frequencies of A and B alleles for bGH locus were .769 and .231 in cows and .784 and .216 in bulls, respectively. The frequencies of A and B alleles for bPRL locus were .678 and .322 for cows and .767 and .233 for bulls. Differences in frequencies of these alleles were not significant between cows and bulls at all loci examined. If the DNA polymorphisms of these candidate genes are associated with economically important traits, they could serve as genetic markers for genetic improvement in future marker-assisted selection programs in Korean cattle.

• Animal Bioscience
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• v.34 no.8
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• pp.1283-1289
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• 2021

Objective: The progestogen-associated endometrial protein (PAEP) gene encodes the main whey protein in milk, β-lactoglobulin. The aim of the study was to investigate polymorphism in the PAEP gene and its association with milk yield, composition, and quality. Methods: Test-day records for 782 dairy cows were analysed. A total of 10 single nucleotide polymorphisms (SNP) within the PAEP gene were investigated. The following parameters were recorded: milk yield (MY, kg/d), percent milk fat (%), protein (PP, %), dry matter (DMP, %) and lactose (LP, %), urea content (UC, mg/L) as well as natural logarithm for somatic cell count (LnSCC, ln). Effect on genomic estimated breeding values accuracy was evaluated with pedigree and single step model. Results: Results show that only three SNPs were polymorphic, creating 5 composite genotypes: P1 to P5. Differences in MY between composite genotypes were noted in the two tested herds. Cows with P5 composite genotypes were characterised by the highest PP and LnSCC and the lowest LP and UC (p<0.05). P4 was linked to an increased DMP and UC, while P3 to an increase in LP and decrease in PP and LnSCC. Both factors are important markers in herd management and have high influences on the herds economics. For 5 out of 7 traits the accuracy of prediction was improved by including the haplotype as a fixed effect. Conclusion: Presented results may suggest a new way to optimise breeding programmes and demonstrate the impact of using genomic data during that process.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.12
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• pp.1684-1688
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• 2017

Objective: From a review of published information on genetic association studies, a meta-analysis was conducted to determine the influence of the genes ${\kappa}-casein$ (CSN3) and ${\beta}-lactoglobulin$ (LGB) on milk yield traits in Holstein, Jersey, Brown Swiss, and Fleckvieh. Methods: The GLIMMIX procedure was used to analyze milk production and percentage of protein and fat in milk. Models included the main effects and all their possible two-way interactions; not estimable effects and non-significant (p>0.05) two-way interactions were dropped from the models. The three traits analyzed used Poisson distribution and a log link function and were determined with the Interactive Data Analysis of SAS software. Least square means and multiple mean comparisons were obtained and performed for significant main effects and their interactions (p<0.0255). Results: Interaction of breed by gene showed that Holstein and Fleckvieh were the breeds on which CSN3 ($6.01%{\pm}0.19%$ and $5.98%{\pm}0.22%$), and LGB ($6.02%{\pm}0.19%$ and $5.70%{\pm}0.22%$) have the greatest influence. Interaction of breed by genotype nested in the analyzed gene indicated that Holstein and Jersey showed greater influence of the CSN3 AA genotype, $6.04%{\pm}0.22%$ and $5.59%{\pm}0.31%$ than the other genotypes, while LGB AA genotype had the largest influence on the traits analyzed, $6.05%{\pm}0.20%$ and $5.60%{\pm}0.19%$, respectively. Furthermore, interaction of type of statistical model by genotype nested in the analyzed gene indicated that CSN3 and LGB genes had similar behavior, maintaining a difference of more than 7% across analyzed genotypes. These results could indicate that both Holstein and Jersey have had lower substitution allele effect in selection programs that include CSN3 and LGB genes than Brown Swiss and Fleckvieh. Conclusion: Breed determined which genotypes had the greatest association with analyzed traits. The mixed model based in Bayesian or Ridge Regression was the best alternative to analyze CSN3 and LGB gene effects on milk yield and protein and fat percentages.

• Korean Journal of Agricultural Science
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• v.20 no.1
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• pp.56-67
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• 1993

To applying of genetic markers of milk proteins as dairy cow registration and selection aids for genetic improvement, genopypes controlling the 4 milk protein loci, ${\alpha}S1$-casein (${\alpha}S1$-CN), ${\beta}$-casein(${\beta}$-CN), ${\kappa}$-casein(${\kappa}$-CN), and ${\beta}$-lactoglobulin(${\beta}$-LG), from a total of 159 Holstein lactating cows reared at National Animal Breeding Station in 1992 were detected by polyacrylamide gel(PAGE) electrophoresis, and associations between genetic polymorphisms of milk proteins and milk compositions were analyzed. The observed distribution of phenotypes for ${\alpha}S1$-CN, ${\beta}$-CN, ${\kappa}$-CN and ${\beta}$-LG were agreement with those expected under the assumption of genetic equilibrium. The observed genotypic frequencies of the ${\alpha}S1$-CN BB, ${\beta}$-CN AA, ${\kappa}$-CN AA and ${\beta}$-LG AB genotypes were founded to be very high as 79.87%, 84.28%, 71.70% and 49.10%, respectively. Gene frequencies were 0.899 and 0.101 for ${\alpha}S1-CN^B$ and ${\alpha}S1-CN^C$, 0.921 and 0.079 for ${\beta}-CN^A$ and ${\beta}-CN^B$, 0.837 and 0.163 for ${\kappa}-CN^A$ and ${\kappa}-CN^B$, 0.378 and 0.622 for ${\beta}-LG^A$ and ${\beta}-CN^B$. According to the results of analysis of variance, the genotypes of the ${\alpha}S1-CN$, ${\beta}-CN$, ${\kappa}-CN$ and ${\beta}-LG$ were significantly difference for fat, protein and total solid percentage in milk compositions. On milk compositions, the ${\kappa}$-CN BB genotype was very high fat and protein percentage more than ${\kappa}$-CN AA and AB genotypes, and ${\beta}$-LG AA genotype was very high fat percentage more than ${\beta}$-LG AB and BB genotype at 5% level of significant difference, respectively. As a consequence, the fat and protein percentage may be improved to select to ${\kappa}$-CN BB and ${\beta}$-LG AA genotypes.

• Animal Bioscience
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• v.34 no.1
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• pp.2-11
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• 2021

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.

• Animal Bioscience
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• v.35 no.1
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• pp.13-21
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• 2022

Objective: The aim of the study was to evaluate the influence of gene polymorphisms and nongenetic factors on the somatic cell score (SCS) in the milk of Holstein (n = 148) and Simmental (n = 73) cows and their crosses (n = 6). Methods: The SCS was calculated by the formula SCS = log₂(SCC/100,000)+3, where SCC is the somatic cell count. Polymorphisms in the casein alpha S1 (CSN1S1), beta-casein (CSN2), kappa-casein (CSN3), beta-lactoglobulin (LGB), acyl-CoA diacylglycerol transferase 1 (DGAT1), leptin (LEP), fatty acid synthase (FASN), stearoyl CoA desaturase 1 (SCD1), and 1-acylglycerol-3-phosphate O-acyltransferase 6 (AGPAT6) genes were genotyped, and association analysis to the SCS in the cow's milk was performed. Further, the impact of breed, farm, year, month of the year, lactation stage and parity on the SCS were analysed. Phenotype correlations among SCS and milk constituents were computed by Pearson correlation coefficients. Results: Only CSN2 genotypes A¹/A² were found to have significant association with the SCS (p<0.05), and alleles of CSN1S1 and DGAT1 genes (p<0.05). Other polymorphisms were not found to be significant. SCS had significant association with the combined effect of farm and year, lactation stage and month of the year. Lactation parity and breed had not significant association with SCS. The phenotypic correlation of SCS to lactose content was negative and significant, while the correlation to protein content was positive and significant. The correlations of SCS to fat, casein, nonfat solids, urea, citric acid, acetone and ketones contents were very low and not significant. Conclusion: Only CSN2 genotypes, CSN1S1 and DGAT1 alleles did show an obvious association to the SCS. The results confirmed the importance of general quality management of farms on the microbial milk quality, and effects of lactation stage and month of the year. The lactose content in milk reflects the health status of the udder.