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.
Extensive emphasis on milk and milk fat yields with no diversion for beef performance increased the yield efficiency of North American dairy cattle. Heavy demand for North American genetics followed national strain comparison trials in Poland, and US and Canadian dairy cattle and germplasm still are an important source of genetics for many countries. Genetic improvement has accelerated in many countries because of the implementation of sampling programs for young bulls and improved evaluation procedures. Rapid access to information and more frequent calculation of genetic information also are having a positive impact on genetic improvement. Traits other than yield should be considered in a breeding program, but those traits mist have a reasonable opportunity for improvement and sufficient economic worth. Because of ever increasing efficiency, the world's milk supply comes from fewer cows each year. However, no decline in the rate of genetic improvement is apparent under current genetic practices; estimates of heritability are increasing, and a decline in yield efficiency is unlikely in the near future. As management improves, especially for subtropical conditions, many of the selection principles used in temperate climates will be adopted for more adverse environmental conditions.
The data including milk yields, fat and protein percent for 628,395 heads collected by National Agricultural Cooperative Federation, 15 type traits and final score for 62,262 heads collected by Korea Animal Improvement Association, which were born in 1998 to 2004, and net profits calculated from milk price and raising expenses of individuals were used to estimate genetic parameters. The highest positive genetic correlation, 0.81, was shown between body depth (BD) and loin strength (SR). Genetic correlations between body depth (BD) and udder depth (UD), front teat placement (TP) and front teat length (TL) were -0.23, which were lowest among the linear type traits. Furthermore, medium level of negative genetic correlations were shown the milk yield with milk contents rate traits. Mostly low level of positive genetic correlations were shown between the milk traits and linear score traits except milk yield and stature. Most of the genetic correlations of between the linear score traits and net profit were low level of positive or negative genetic correlations. Among the genetic correlations, body depth (BD), angularity (DF) and rear attachment width (UW), and final score (FS) with net profit were high as 0.17, 0.17, 0.18 and 0.18, respectively. Finally all of the genetic correlations between net profit and milk traits were positive and higher than the linear traits with positive genetic correlations. The results of this study suggest that net profit has been related with the linear traits, such as body depth (BD), angularity (DF) and rear attachment width (UW) traits, and furthermore, milk traits including yield and contents rates influence positively and greatly on net profit.
Ghiasi, Heydar;Piwczynski, Dariusz;Sitkowska, Beata;Gonzalez-Recio, Oscar
Animal Bioscience
/
v.34
no.8
/
pp.1303-1308
/
2021
Objective: The objective of this study was to define a new composite trait for Holstein dairy cows and evaluate the possibility of joint improvement in milk and fertility traits. Methods: A data set consisting 35,882 fertility related records (days open [DO], calving interval [CI], and number of services per conception [NSC], and total milk yield in each lactation [TMY]) was collected from 1998 to 2016 in Polish Holstein-Friesian breed herds. In this study TMY, DO, CI, and lactation length of each cow was used to obtain composite milk and fertility traits (CMF). Results: Moderate heritability (0.15) was estimated for composite trait that was higher than heritability of female fertility related traits: DO 0.047, CI 0.042, and NSC 0.014, and slightly lower than heritability of TMY 0.19. Favourable genetic correlations (-0.87) were estimated between CMF with TMY. Spearman rank correlation coefficients between breeding value of CMF with DO, CI, and TMY were high (>0.94) but with NSC were moderate (0.64). Selection on CMF caused favourable correlated genetic gains for DO, CI, and TMY. Different selection indices with different emphasis on fertility and milk production were constructed. The amount of correlated genetic gains obtained for DO and total milk production according to selection in CMF were higher than of genetic gains obtained for DO and TMY in selection indices with different emphasis on milk and fertility. Conclusion: The animal selection only based on a composite trait - CMF proposed in current study would simultaneously lead to favourable genetic gains for both milk and fertility related traits. In this situation CMF introduced in current study can be used to overcome to limitations of selection index and CMF could be useful for countries that have problems in recording traits, especially functional traits.
Data on 1,037 Nili-Ravi buffaloes from four institutional herds were used to study lifetime milk yield, herd life, productive life and breeding efficiency. A general linear model was used to study the environmental effects while an animal model having herd, year of birth and age at first calving (as covariate) along with random animal effect was used to estimate breeding values. The lifetime milk yield, herd life, productive life and breeding efficiency averaged $7,723{\pm}164$ kg, $3,990{\pm}41$ days, $1,061{\pm}19$ days and 64 percent, respectively. All the traits were significantly (p<0.01) affected by the year of birth and herd of calving, while the herd life was also affected (p<0.01) by the age at first calving. The heritabilities for lifetime milk yield, herd life, productive life and breeding efficiency were $0.093{\pm}0.056$, $0.001{\pm}0.055$, $0.144{\pm}0.079$ and 0.001, respectively. The definition for productive life, where each lactation gets credit upto 10 months had slightly better heritability and may be preferred over the definition where no limit is placed on lactation length. The genetic correlation between productive life and lifetime milk yield was low but high between productive life and herd life. The selection for productive life will increase herd life while lifetime milk yield will also improve. The overall phenotypic trend during the period under the study was negative for lifetime milk yield (-280 kg/year), herd life (-93 days), productive life (-42 days/year) and breeding efficiency (-0.36 percent/year), whereas the genetic trend was positive for lifetime milk yield (+15 kg/year) and productive life (+4 days/year).
Samaraweera, Amali Malshani;Boerner, Vinzent;Cyril, Hewa Waduge;Werf, Julius van der;Hermesch, Susanne
Asian-Australasian Journal of Animal Sciences
/
v.33
no.11
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pp.1741-1754
/
2020
Objective: This study was conducted to estimate genetic parameters for milk yield traits using daily milk yield records from parlour data generated in an intensively managed commercial dairy farm with Jersey and Jersey-Friesian cows in Sri Lanka. Methods: Genetic parameters were estimated for first and second lactation predicted and realized 305-day milk yield using univariate animal models. Genetic parameters were also estimated for total milk yield for each 30-day intervals of the first lactation using univariate animal models and for daily milk yield using random regression models fitting second-order Legendre polynomials and assuming heterogeneous residual variances. Breeding values for predicted 305-day milk yield were estimated using an animal model. Results: For the first lactation, the heritability of predicted 305-day milk yield in Jersey cows (0.08±0.03) was higher than that of Jersey-Friesian cows (0.02±0.01). The second lactation heritability estimates were similar to that of first lactation. The repeatability of the daily milk records was 0.28±0.01 and the heritability ranged from 0.002±0.05 to 0.19±0.02 depending on day of milk. Pearson product-moment correlations between the bull estimated breeding values (EBVs) in Australia and bull EBVs in Sri Lanka for 305-day milk yield were 0.39 in Jersey cows and -0.35 in Jersey-Friesian cows. Conclusion: The heritabilities estimated for milk yield in Jersey and Jersey-Friesian cows in Sri Lanka were low, and were associated with low additive genetic variances for the traits. Sire differences in Australia were not expressed in the tropical low-country of Sri Lanka. Therefore, genetic progress achieved by importing genetic material from Australia can be expected to be slow. This emphasizes the need for a within-country evaluation of bulls to produce locally adapted dairy cows.
Data pertained to 335 crossbred cows comprising of 1/2 Friesian (F) + 1/2 Hariana (H), 1/2 F + 1/4 Jersey (J) + 1/4 H, 1/2 F + 1/4 Brown Swiss (BS) + 1/4 H, 1/2 F + 1/4 Red Dane (R) + 1/4 H, FR (I) and FRH (I) genetic groups extending over a period of 21 years (1970-1990) maintained at Animal Farm of CCS HAU, Hisar. The averages for first lactation milk yield was $2,486.24{\pm}80.26kg$ and peak yield of first three lactation were $11.35{\pm}0.72kg$, $13.97{\pm}0.60kg$ and $16.02{\pm}0.42kg$, respectively. The lifetime milk production was observed as $11,305.16{\pm}1,004.52kg$ in crossbred cattle. The average first lactation fat yield was observed as $102.06{\pm}0.01kg$ and peak fat yield of first three lactation were $0.458{\pm}0.01$, $0.490{\pm}0.01$ and $0.500{\pm}0.02kg$, respectively. The lifetime fat production was estimated as $502.31{\pm}45.90kg$. LTMP and LTFP had reasonably good additive genetic variance which could be exploited either through mass selection/combined with family or pedigree selection. FLMY, peak yields and LTMP had significant positive phenotypic correlation with FLFY and LTFP and the correlation at the genetic level were also higher and positive for these traits. Finally, peak week milk yield of first lactation (PMY1) was the earliest available trait having desirable and significant correlation at phenotypic and positive at genetic level with FLFY, PFY1 and PFY2, PFY3 and LTFP and selection for this trait will help in early evaluation of sires and dams and will increase genetic advancement per unit of time.
Milk production traits are important economic traits for dairy cattle. The aim of the present study was to refine the position of previously detected quantitative trait loci (QTL) on bovine chromosome 6 affecting milk production traits in Chinese Holstein dairy cattle. A daughter design with 918 daughters from 8 elite sire families and 14 markers spanning the previously identified QTL region were used in the analysis. We employed a combined linkage and linkage disequilibrium analysis (LDLA) approach with two options for calculating the IBD probabilities, one was based on haplotypes of all 14 markers (named Method 1) and the other based on haplotypes with sliding windows of 5 markers (named Method 2). For milk fat yield, the two methods revealed a highly significant QTL located within a 6.5 cM interval (Method 1) and a 4.0 cM interval (Method 2), respectively. For milk protein yield, a highly significant QTL was detected within a 3.0 cM interval (Method 1) or a 2.5 cM interval (Method 2). These results confirmed the findings of our previous study and other studies, and greatly narrowed down the QTL positions.
A total of 1033 Brown Swiss and 610 Canadienne cows were phenotyped for the genetic variants ${\alpha}_{s1}$-casein, ${\beta}$-casein, ${\kappa}$-casein, ${\beta}$-lactoglobulin and ${\alpha}$-lactalbumin. In Brown Swiss, frequency distributions were: 97.3% B and 2.7% C variant of ${\alpha}_{s1}$-casein; 31.6% $A^1$, 51.8% $A^2$, 0.5% $A^3$ and 16.1% B variant of ${\beta}$-casein; 70.4% A, 29.3% B, and 0.3% C variant of ${\kappa}$-casein; 41.7% A and 58.3% B variant of ${\beta}$-lactoglobulin; and 100% B variant of ${\alpha}$-lactalbumin. Corresponding frequencies in Canadienne for those five milk proteins were: 98.6 and 1.4%;58.5, 33.5, 0.08 and 7.9%; 78.8, 21.1 and 0.1%, 42.4 and 57.6%; and 100%. Analysis of variance by least squares showed possible association between milk protein phenotypes and some lactational production traits. There were no significant association of phenotypes of ${\alpha}_{s1}$-casein, ${\beta}$-casein and ${\beta}$-lactoglobulin with milk yield, fat yield, protein yield, fat percentage and protein percentage in both breeds during the three lactations. In the Brown Swiss, ${\kappa}$-casein phenotype was associated with 305-day fat yield and protein yield during the first lactation. ${\kappa}$-Casein AB was associated with higher milk, fat and protein yield during the second lactation. During the third lactation, ${\beta}$-lactoglobulin AA in Canadienne cows was associated with higher protein content in the milk (3.70%) when compared to phenotypes AB (3.54%) and BB (3.64%).
Objective: The present study was aimed primarily for estimating various genetic parameters (heritability, genetic correlations) of reproduction (age at first calving [AFC], first service period [FSP]); production (first lactation milk, solid-not fat, and fat yield) and lifetime traits (lifetime milk yield, productive life [PL], herd life [HL]) in Tharparkar cattle to check the association of reproduction traits with lifetime traits through two different methods (Frequentist and Bayesian) for comparative purpose. Methods: Animal breeding data of Tharparkar cattle (n = 964) collected from Livestock farm unit of ICAR-NDRI Karnal for the period 1990 through 2019 were analyzed using a Frequentist least squares maximum likelihood method (LSML; Harvey, 1990) and a multi-trait Bayesian-Gibbs sampler approach (MTGSAM) for genetic correlations estimation of all the traits. Estimated breeding values of sires was obtained by BLUP and Bayesian analysis for the production traits. Results: Heritability estimates of most of the traits were medium to high with the LSML (0.20±0.44 to 0.49±0.71) and Bayesian approach (0.24±0.009 to 0.61±0.017), respectively. However, more reliable estimates were obtained using the Bayesian technique. A higher heritability estimate was obtained for AFC (0.61±0.017) followed by first lactation fat yield, first lactation solid-not fat yield, FSP, first lactation milk yield (FLMY), PL (0.60±0.013, 0.60±0.006, 0.57±0.024, 0.57±0.020, 0.42±0.025); while a lower estimate for HL (0.38±0.034) by MTGSAM approach. Genetic and phenotypic correlations were negative for AFC-PL, AFC-HL, FSP-PL, and FSP-HL (-0.59±0.19, -0.59±0.24, -0.38±0.101 and -0.34±0.076) by the multi-trait Bayesian analysis. Conclusion: Breed and traits of economic importance are important for selection decisions to ensure genetic gain in cattle breeding programs. Favourable genetic and phenotypic correlations of AFC with production and lifetime traits compared to that of FSP indicated better scope of AFC for indirect selection of life-time traits at an early age. This also indicated that the present Tharparkar cattle herd had sufficient genetic diversity through the selection of AFC for the improvement of first lactation production and lifetime traits.
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