• Asian-Australasian Journal of Animal Sciences
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• v.19 no.6
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• pp.769-774
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• 2006

Fractions of herd-year-season, sire by herd interaction, additive genetic and dominance genetic variances were estimated for milk production traits in Holsteins of Japan using Method R. Inbreeding depressions for milk production traits were also estimated. Estimated fractions of herd-year-season variances ranged from 0.056 to 0.074 for yield traits and from 0.033 to 0.035 for content traits. Estimated fractions of additive genetic variances to phenotypic variances (heritabilities across a herd in the narrow sense) were 0.306, 0.287, 0.273, 0.255, 0.723, 0.697 and 0.663 for milk, fat, SNF and protein yields, and fat, SNF and protein contents, respectively. Estimated fractions of dominance genetic variances ranged from 0.019 to 0.022 for yield traits and from 0.014 to 0.018 for content traits. Fractions of variances for sire by herd interaction were estimated to range from 0.020 to 0.025 for yield traits and 0.011 to 0.012 for content traits. Estimates of inbreeding depression for milk, fat, SNF and protein yields were -36.16 kg, -1.42 kg, -3.24 kg and -1.15 kg per 1% inbreeding for milk, fat, SNF and protein yields, respectively. Estimates of depression per 1% inbreeding for content traits were positive at $0.39{\times}10^{-3}%$, $0.31{\times}10^{-3}%$ and $0.82{\times}10^{-3}%$ for fat, SNF and protein contents, respectively.

• Asian-Australasian Journal of Animal Sciences
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• v.15 no.12
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• pp.1813-1821
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• 2002

The aim of this study was to identify useful secondary traits for estimating genetic ability of milk production traits. We investigated the value of using plasma metabolites concentrations. Two hundred and nineteen cattle out of 271 had only milk production traits records (G1), 33 had only metabolites records (G2), and 19 had both milk production traits and metabolites records (G3). Fifty two calves with metabolites records (G2 and G3) were born from 1992 to 1997. Forty three calves (29 females, 14 males) were used from 10 to 90 d of age and the others (3 females, 6 males) from 10 to 60 d of age. A total of 566 records of milk yield, fat yield and protein yield for 240 to 305 d on 238 heads (G1 and G2) were collected The collected blood samples were divided into three age groups: AG1, 10 to 30 d; AG2, 40 to 60 d; and AG3, 70 to 90 d. Heritabilities of milk yield, fat yield and protein yield were $0.45{\pm}0.04$, $0.50{\pm}0.04$ and $0.38{\pm}0.04$, respectively. Heritability of plasma glucose concentration at AG1 was $0.45{\pm}0.08$. Genetic correlations between plasma glucose concentration and milk yield, fat yield and protein yield were -$0.35{\pm}0.28$, $0.64{\pm}0.24$ and $0.36{\pm}0.35$, respectively. When the plasma glucose concentration at AG1 was used to estimate genetic ability of these milk production traits, reliability of milk yield of animals without milk record increased 8.2%, fat yield increased 24.2% and protein yield increased 9.5%. Heritability of plasma total cholesterol concentration at AG3 was $0.83{\pm}0.04$. Genetic correlation between plasma total cholesterol concentration and milk yield, fat yield and protein yield were $0.58{\pm}0.21$, $0.42{\pm}0.20$ and $0.45{\pm}0.22$, respectively. When the plasma total cholesterol concentration at AG3 was using to estimate genetic ability of these milk production traits, reliability of milk yield of animals without milk record increased 19.0%, fat yield increased 9.6%, and protein yield increased 13.5%. The annual genetic gain is in proportion to the reliability of selection. These results show that the plasma metabolite concentrations would be useful for improvement of genetic ability for milk production traits in the genetic improvement in herd of cows, where half of the animals selected are from a herd without its own milk record.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.3
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• pp.309-319
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• 2017

Objective: Holsteins are known as the world's highest-milk producing dairy cattle. The purpose of this study was to identify genetic regions strongly associated with milk traits (milk production, fat, and protein) using Korean Holstein data. Methods: This study was performed using single nucleotide polymorphism (SNP) chip data (Illumina BovineSNP50 Beadchip) of 911 Korean Holstein individuals. We inferred each genomic estimated breeding values based on best linear unbiased prediction (BLUP) and ridge regression using BLUPF90 and R. We then performed a genome-wide association study and identified genetic regions related to milk traits. Results: We identified 9, 6, and 17 significant genetic regions related to milk production, fat and protein, respectively. These genes are newly reported in the genetic association with milk traits of Holstein. Conclusion: This study complements a recent Holstein genome-wide association studies that identified other SNPs and genes as the most significant variants. These results will help to expand the knowledge of the polygenic nature of milk production in Holsteins.

• Animal Bioscience
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• v.35 no.3
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• pp.377-384
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• 2022

Objective: This study was conducted to estimate multi-trait genetic parameters for somatic cell score (SCS), milk yield and type traits in Nigerian Dwarf (ND) goats from the United States. Methods: Data from 1,041 ND goats in the United States with kiddings in 95 herds were used to estimate multi-trait genetic parameters for SCS, milk (MILK), fat (FAT), and protein (PROT) yields, and 14 type traits. An 18-trait mixed linear animal model for lactation mean SCS (Log₂), MILK, FAT, PROT, and 14 type traits was applied. A factor analytic approach (FA1) in ASReml software was used to obtain convergence. Results: Averages for SCS were low (2.85±1.29 Log₂), and were 314±110.6, 20.9±7.4, and 14±4.9 kg, respectively, for MILK, FAT, and PROT. Heritabilities for SCS, MILK, FAT, and PROT were 0.32, 0.16, 0.16, and 0.10, respectively. The highest heritabilities for type traits were for stature (0.72), teat diameter (0.49), and rump width (0.48), and the lowest estimates were for dairyness (0.003) and medial suspensory ligament (0.03). Genetic correlations of SCS with MILK, FAT, and PROT were positive but low (0.25, 0.18, and 0.23, respectively). Genetic and phenotypic correlations between MILK, FAT, and PROT were high and positive (≥0.66). Absolute values of genetic correlations involving SCS with type traits were generally low or no different from zero. Most of the phenotypic correlations involving SCS with type traits were low. No serious unfavorable genetic correlations between milk yield traits and SCS or between milk yield traits or SCS and type traits were found. Conclusion: Genetic variation exists in the ND breed for most studied traits. The development of selection programs based on these estimates may help accelerate favorable multi-trait genetic changes in this breed.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.11
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• pp.1479-1483
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• 2004

Milk protein polymorphisms were genotyped by polyacrylamide gel electrophoresis (PAGE) from 109 Maiwa and 100 Jiulong yaks. The relationships between milk protein polymorphisms and 3 milking traits were studied. The results showed that $\beta$-CN, $\kappa$-CN and $\alpha$-La were monomorphic, and ${\alpha}_{s1}$-CN and $\beta$-Lg were polymorphic, with ${\alpha}_{s1}$-CN D and $\beta$-Lg E as dominant genes, respectively. The frequencies of ${\alpha}_{s1}$-CN D were 0.8073 and 0.6000 in two populations and $\beta$-Lg E were 0.9770 and 0.9700. The mean heterozygosities were 0.1021 and 0.1867 in the two populations. No significant effects on milking traits and milk protein compositions were observed except for ${\alpha}_{s1}$-CN locus on fat percentage in Jiulong yak.

• Food Science of Animal Resources
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• v.26 no.1
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• pp.121-126
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• 2006

Major milk proteins have considerable variane which comes from substitution and deletions in their amino arid sequences. Variants in genes that code for milk proteins, such as ${\beta}$-lactoglobulin (${\beta}-LG$) have been established as genetic markers for milk production and milk protein composition in dairy cattle. The effect of ${\beta}-LG$ variant on milk production traits, such as milk yield. fat yield, protein yield, fat percentage and protein percentage, was estimated for 482 Holstein cows in the first lactation. The ${\beta}-LG$ variants were determined by PCR-RFLP technique at the DNA level. Single trait linear model was used for the statistical analysis of the data. Results of this study indicated that ${\beta}-LG$ variants affected significantly protein yield (p<0.05) and fat percentage (p<0.05). Animals with the AA variant produced 31kg of milk protein more than animals with the BB variant. On the contrary, cows with the BB variant had fat percentage higher by 0.35 and 0.32% compared with cows with the AA and AB variants, respectively. No associations between the ${\beta}-LG$ variants and milk yield, protein percentage and fat yield were found Therefore, milk production traits could be improved through ${\beta}-LG$ typing by increasing the frequency of A variant for protein yield or the frequency of B variant for fat content in Holstein dairy cattle population.

• Animal Bioscience
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• v.34 no.4
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• pp.489-498
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• 2021

Objective: Milk production is one of the most desirable traits in livestock. Recently, the toll-like receptor (TLR) has been identified as a candidate gene for milk traits in cows. So far, there is no information concerning the contribution of this gene in milk traits in sheep. This study was designed to investigate the TLR 4 gene polymorphisms in Barki ewes in Egypt and then correlate that with milk traits in order to identify potential single nucleotide polymorphisms (SNPs) for these traits in sheep. Methods: A part of the ovine TLR 4 gene was amplified in Barki ewes, to identify the SNPs. Consequently; Barki ewes were genotyped using polymerase chain reaction-single strand conformation polymorphism protocol. These genotypes were correlated with milk traits, which were the daily milk yield (DMY), protein percentage (PP), fat percentage (FP), lactose percentage, and total solid percentage (TSP). Results: Age and parity of the ewe had a significant effect (p<0.05 or p<0.01) on DMY, FP, and TSP. The direct sequencing identified a missense mutation located in the coding sequence of the gene (rs592076818; c.1710C>A) and was predicted to change the amino acid sequence of the resulted protein (p.Asn570Lys). The association analyses suggested a significant effect (p<0.05) of the TLR genotype on the FP and PP, while the DMY tended to be influenced as well (p = 0.07). Interestingly, the presence of the G allele tended to increase the DMY (+40.5 g/d) and significantly (p<0.05 or p<0.01) decreased the FP (-1.11%), PP (-1.21%), and TSP (-7.98%). Conclusion: The results of this study suggested the toll-like receptor 4 (TLR4) as a candidate gene to improve milk traits in sheep worldwide, which will enhance the ability to understand the genetic architecture of genes underlying SNPs that affect such traits.

• Food Science of Animal Resources
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• v.25 no.3
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• pp.328-332
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• 2005

The effect of k-casein (k-CN) variant on milk production traits (milk yield, fat yield, protein yield, fat percentage and protein percentage) was estimated for 568 Holstein cows in the first lactation. The k-CN valiant were determined by PCR-RFLP (restriction fragment length polymorphism) technique at the DNA level. Single trait linear model was used for the statistical analysis of the data. Result of this study indicated that k-CN variant affected significantly milk yield (P<0.05) and protein yield (P<0.01). Animals with the BB variant produced 622kg milk more and had protein yield higher by 32kg compared with animals with the AA variant No associations between the k-CN variants and other milk production trait were found. Therefore, milk and protein yield may be improved through milk protein typing by increasing the frequencies of k-CN B variant in dairy cattle population. In cheese making, it will be also preferable to have milk with the B variant of k-CN, which gives higher yield having a better quality than the A variant milk.

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.2
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• pp.166-171
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• 2007

The objective of this study was to assess the association of polymorphisms in ${\kappa}$-cn, ${\beta}$-lg, ${\beta}$-lg 5′ flanking region, CSN1S2, and IGFBP-3 genes with milk production traits and mastitis-related traits in Chinese Holstein. Traits analyzed were 305 day standard milk yield, protein percentage, fat percentage, the ratio of fat percentage and protein percentage, pre-somatic cell count, somatic cell count, and somatic cell score, respectively. CSN1S2 locus was uninformative because only one genotype BB was found in Chinese Holstein. Allele frequencies of A and B in IGFBP-3 gene were 0.5738 and 0.4262 in Chinese Holstein population, which was different from reported Qinchuan cattle population. The genotypes of animals at IGFBP-3 locus significantly affected 305 day standard milk yield, protein percentage, and somatic cell score. The ${\beta}$-lg genotypes had a significant effect on protein percentage and the ratio of fat percentage and protein percentage. Polymorphism in ${\beta}$-lg 5′ flanking region was associated with 305 day standard milk yield, protein percentage, fat percentage, pre-somatic cell count, and somatic cell count. No significant associations of the polymorphism in ${\kappa}$-cn gene were observed for any trait.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.4
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• pp.459-466
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• 2019

Objective: This study assessed the possible existence of genotype by environment interactions for milk, fat and protein yields in Holstein cattle raised in one of the most important milk production basins in Brazil. Methods: Changes in the genetic parameters and breeding values were evaluated for 57,967 animals from three distinct regions of southern Brazil, divided according to differences in climate. The genotype by environment interaction was determined by genetic correlations between regions, estimated by the restricted maximum likelihood, considering the animal model. Bull rankings were investigated to verify the ratio of coincident selected animals between regions for each trait. Results: The estimates of heritability coefficients were similar between two regions, but were lower in the third evaluated area, for all traits. Genetic correlations between regions were high, ranging from 0.91 to 0.99 for milk, fat and protein yields, representing the absence of a genotype by environment interaction for productive traits. The percentage of selection error between regions for the top 10% of animals ranged from 0.88% to 2.07% for milk yield, 0.99% to 2.46% for fat yield and 0.59% to 3.15% for protein yield. Conclusion: A slight change in genotype between areas was expected since no significant genotype by environment interactions were identified, facilitating the process of selecting Holstein cattle in southern Brazil.