scholarly journals Estimation of (co)variance components and breeding values for test-day milk production traits of Holstein dairy cattle via Bayesian approach

2014 ◽  
Vol 30 (1) ◽  
pp. 15-28 ◽  
Author(s):  
R. Mosharraf ◽  
J. Shodja ◽  
M. Bohlouli ◽  
S. Alijani ◽  
S.A. Rafat
Keyword(s):  
Dairy Cattle ◽  
Regression Model ◽  
Milk Production ◽  
Milk Fat ◽  
Variance Components ◽  
Random Regression ◽  
Production Traits ◽  
Milk Production Traits ◽  
Breeding Values ◽  
Random Regression Model

Genetic parameters of milk, fat, and protein yields were estimated in the first lactation of Holstein dairy cattle. The records were collected during the period 2006 to 2011 and analyzed fitting the random regression model. The data included 41178, 25397 and 18716 test-day records of milk, fat and protein yields, respectively that produced by 4746, 3437 and 2525 cows respectively. Fixed effects in model included herd-year-month of test day and age-season of calving. The fixed and random regressions were modeled with normalized Legendre polynomials and (co)variance components were estimated by Bayesian method and Gibbs sampling was used to obtain posterior distributions. Estimates of heritability for milk, fat and protein yields ranged from 0.18 to 0.26; 0.06 to 0.11 and 0.09 to 0.22, respectively. Heritabilities for 305-d milk, fat and protein yields were 0.36, 0.23 and 0.29, respectively. For milk and protein yields, heritabilities were lower at the early of lactation due to the trends of lower additive genetic variance, higher permanent environmental variance. Genetic correlations for milk, fat and protein yields ranged from 0.14 to 1.00; 0.39 to 1.00 and 0.27 to 1.00, respectively. Ranges of estimated breeding values for 305-d yield of milk, fat and protein yields were from -1194.48 to 1412.44; -210.57 to 271.22 and -194.08 to 203.25, respectively. According to the results of this study, random regression model seems to be a flexible and reliable procedure for the genetic evaluation of milk production traits and it can be useful in the breeding programs for Iranian dairy cattle.

scholarly journals Comparison of different polynomial functions in Random Regression Model for milk production traits of Iranian Holstein dairy cattle

2014 ◽  
Vol 14 (1) ◽  
pp. 55-68 ◽  
Author(s):  
Ali Mohammadi ◽  
Sadegh Alijani ◽  
Hossein Daghighkia
Keyword(s):  
Dairy Cattle ◽  
Regression Model ◽  
Milk Production ◽  
Genetic Parameters ◽  
Random Regression ◽  
Polynomial Functions ◽  
Early Lactation ◽  
Production Traits ◽  
Milk Production Traits ◽  
Random Regression Model

Abstract The aim of this research was to compare different polynomial functions including Legendre polynomials (LP), Wilmink (WRR) and Ali-Schaeffer (ARR) functions, in random regression model (RRM) for estimation of genetic parameters for milk production traits of Iranian Holstein dairy cattle. For this purpose the performance records obtained from test-day (TD) regarding milk yield, fat and protein contents of the cows calving for the first time were used. The numbers of records for the above mentioned traits were 701212, 657004, and 560775, respectively. These records were collected from the years 2006 to 2010 by the National Breeding Center of Iran. The genetic parameters were estimated using Restricted Maximum Likelihood (REML) method by applying RRM. Residual variances were considered homogeneous over the lactation period. To compare the model, different criteria (-2Logl, AIC, BIC and RV) were used for considered traits. Based on the results obtained, for all traits, RRM with LP function (2,5) were chosen as the best model. Considering residual variance (RV), LP (2,2) was proved to be a model which has the lowest performance, while using -2Logl, AIC, BIC criteria, RRM with ARR function was the worst model. According to the results, it is recommended to use LP with low orders for the additive genetic effects and with more orders for the permanent environment effects in the RRM for Iranian Holstein cattle. Permanent environment variance was higher in early lactation than during lactation and additive genetic variance in the early lactation was lower than at the end of lactation. Heritability range of milk yield, fat and protein contents was estimated to be from 0.08 to 0.23, 0.05 to 0.20 and 0.08 to 0.14, respectively. Phenotypic variance of the considered traits during lactation was not constant and it was higher at the beginning and the end of lactation. The additive genetic correlation between adjacent test days was higher than between distant test days.

Association of bovineCD4andSTAT5bsingle nucleotide polymorphisms with somatic cell scores and milk production traits in Chinese Holsteins

2011 ◽  
Vol 78 (2) ◽  
pp. 242-249 ◽  
Author(s):  
Yanghua He ◽  
Qin Chu ◽  
Peipei Ma ◽  
Yachun Wang ◽  
Qin Zhang ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Somatic Cell ◽  
Milk Production ◽  
Milk Yield ◽  
Milk Fat ◽  
Protein Yield ◽  
Nucleotide Polymorphisms ◽  
Production Traits ◽  
Milk Production Traits ◽  
Chinese Holstein

CD4+T cells play a key role in the immune response of pathogen-induced mastitis in dairy cattle. Mammary gland factor STAT5b is involved in the regulation of CD4+T cell differentiation during inflammatory response and milk production. Little is known about the genetic variation effects of bovineCD4andSTAT5bgenes on somatic cell score (SCS) and milk production traits in dairy cattle. The aim of the study was to investigate the single nucleotide polymorphisms (SNPs) of bovineCD4andSTAT5bin Chinese Holsteins and to analyse their association with estimated breeding values (EBVs) for SCS and milk production traits. In the present study, SNPs ofCD4(NC_007303 g.13598C>T) andSTAT5b(NC_007317 g.31562 T>C) were identified and genotyped in Chinese Holstein population. The results showed that both SNPs were significantly associated with the EBVs for milk yield and protein yield in Chinese Holstein cows, and the SNP inCD4was associated with the EBV for SCS (P<0·01). The additive effect ofCD4SNP on protein yield was significant (P<0·05), and the dominant effect ofSTAT5bSNP was significant on milk yield and protein yield (P<0·01). Cows with combination genotype C7 (CCTT:CD4g.13598C>T andSTAT5bg.31562 T>C) had the highest SCS EBV but lower milk yield, while cows with C2 (TTTC) produced more milk, fat and protein than the other eight combination genotypes. These results suggested that the SNPs inCD4andSTAT5bmay be potential genetic markers for SCS and milk/protein yields selecting and warrant further functional research.

scholarly journals The relation of GH1, GHR and DGAT1 polymorphisms with estimated breeding values for milk production traits of German Holstein sires

2008 ◽  
Vol 53 (No. 6) ◽  
pp. 238-246 ◽  
Author(s):  
E. Hradecká ◽  
J. Čítek ◽  
L. Panicke ◽  
V. Řehout ◽  
L. Hanusová
Keyword(s):  
Growth Hormone ◽  
Milk Production ◽  
Milk Fat ◽  
Milk Protein ◽  
Growth Hormone Gene ◽  
Production Traits ◽  
Milk Production Traits ◽  
Breeding Values ◽  
Fat Yield ◽  
Estimated Breeding Values

: We analysed the relations of estimated breeding values (EBV) of 315 German Holstein sires to their genotypes in growth hormone gene (<i>GH1</i>), growth hormone receptor gene (<i>GHR</i>) and acylCoA-diacylglycerol acyltransferase 1 (<i>DGAT1</i>). The strong relation of <i>DGAT1 K232A</i> to the estimated breeding values for milk production traits has been confirmed, when allele <i>DGAT1<sup>K</sup></i> was connected with higher milk fat yield, milk fat and milk protein content, while allele <i>DGAT1<sup>A</sup></i> increased milk yield and milk protein yield. The effect of <i>DGAT1</i> genotype explained from 4.70% of variability of EBVs for fat yield to 31.90% of variability of EBVs for fat content. The evaluation of <i>GH1</i> 127 Leu/Val and <i>GHR</i> 257 SNP polymorphisms did not reveal an association of their polymorphism with EBVs for milk production traits, except the EBVs of <i>GHR<sup>G</sup>/GHR<sup>G</sup></i> homozygotes for fat yield, which were significantly lower. The effect of <i>GH1</i> or <i>GHR genotype explained only a negligible portion of variability of EBVs (<i>R</i><sup>2</sup> < 1.00% in most cases).

scholarly journals The association of five polymorphisms with milk production traits in Czech Fleckvieh cattle

2012 ◽  
Vol 57 (No. 2) ◽  
pp. 45-53 ◽  
Author(s):  
J. Boleckova ◽  
J. Matejickova ◽  
M. Stipkova ◽  
J. Kyselova ◽  
L. Barton
Keyword(s):  
Linkage Disequilibrium ◽  
Milk Production ◽  
Milk Yield ◽  
Milk Fat ◽  
Milk Protein ◽  
Future Research ◽  
Production Traits ◽  
Milk Production Traits ◽  
Breeding Values ◽  
Prl Gene

The aim of this study was to estimate allelic and genotypic frequencies of five DNA markers that are positional and functional candidates for milk production traits in Czech Fleckvieh cattle. In addition, we evaluated the association of these markers with milk production traits and breeding values for milk production traits and also estimated linkage disequilibrium (LD) between two markers within the prolactin (PRL) gene. As part of this study, 505 Czech Fleckvieh cows were genotyped. The markers in proliferator-activated receptor gamma coactivator 1-alpha (PPARGC1A), secreted phosphoprotein (SPP1), cytochrome P450 family 11 subfamily B hydroxylase (CYP11B1), and the two polymorphisms in the prolactin gene (PRL) showed evidence of segregation in our study. The PPARGC1A polymorphism was associated with milk yield, milk fat and protein traits. The polymorphism in SPP1 was significantly associated with milk protein percentage. The CYP11B1 polymorphism showed positive associations with milk composition traits and breeding values for milk yield, milk fat, and protein traits. Both polymorphisms within the PRL gene were associated with milk yield, milk fat and milk protein yield (individually and grouped). Linkage disequilibrium between the two polymorphisms in PRL was not observed. In conclusion, all markers examined in this study are important markers for milk production traits in Czech Fleckvieh cattle, and both markers within the PRL gene should be evaluated in future research. &nbsp;

Multivariate REML estimates of genetic parameters of monthly test day milk production traits in first parity Iranian Holstein cows with the use of a repeatability test day model

2003 ◽  
Vol 2003 ◽  
pp. 139-139
Author(s):  
H. Farhangfar ◽  
P. Rowlinson ◽  
M. B. Willis
Keyword(s):  
Dairy Cattle ◽  
Milk Production ◽  
Genetic Parameters ◽  
Large Population ◽  
Genetic Evaluation ◽  
Major Influence ◽  
Production Traits ◽  
Milk Production Traits ◽  
Breeding Values ◽  
Repeatability Test

In practical dairy cattle breeding programmes, usually a small number of animals (selected from a large population) have a major influence on the genetic gain of the concerned population over a period of time (Hofer, 1998). Candidate animals are usually selected based on their breeding values that are predicted by using animal models. In order to predict breeding values, genetic parameters (calculated from variance and covariance components) of the traits under consideration should be estimated to be used in genetic evaluation systems either based on lactation or test day models. The use of test day models has increasingly become of interest in genetic evaluation of dairy cattle due to the fact that they can take more accurate account of the effects of environmental factors influencing test day milk yield over the course of lactation. The main objective of this study was to use a repeatability test day animal model to estimate genetic parameters of monthly test day milk production traits in first parity Iranian Holsteins.

An association analysis between PRL genotype and milk production traits in Italian Mediterranean river buffalo

2017 ◽  
Vol 84 (4) ◽  
pp. 430-433 ◽  
Author(s):  
Jun Li ◽  
Aixin Liang ◽  
Zipeng Li ◽  
Chao Du ◽  
Guohua Hua ◽  
...  
Keyword(s):  
Milk Production ◽  
Milk Yield ◽  
Milk Fat ◽  
Fat Content ◽  
Phenotypic Variance ◽  
River Buffalo ◽  
Production Traits ◽  
Milk Production Traits ◽  
Exon 2 ◽  
Mediterranean River

This Research Communication describes the association between genetic variation within the prolactin (PRL) gene and the milk production traits of Italian Mediterranean river buffalo (Bufala mediterranea Italiana). High resolution melting (HRM) techniques were developed for genotyping 465 buffaloes. The association of genetic polymorphism with milk production traits was performed and subsequently the effects of parity and calving season were evaluated. Single nucleotide polymorphisms (SNPs) were identified at exons 2 and 5 and at introns 1 and 2. All the SNPs were in Hardy–Weinberg equilibrium, and statistical analysis showed that the polymorphism of intron1 was significantly (P < 0·05) associated with milk yield, milk protein content and peak milk yield. The average contribution of the intron1 genotype (r2intron1) to total phenotypic variance in milk production traits was 0·09, and the TT genotype showed lower values than CC and CT genotypes. A nonsynonymous SNP was identified in exon 2, which resulted in an amino acid change from arginine to cysteine. Moreover, the polymorphism of exon 2 was associated significantly with milk fat content (P < 0·05), and the buffaloes with TT genotype showed higher total fat content than the buffaloes with CT genotype. These findings provide evidence that polymorphisms of the buffalo PRL gene are associated with milk production traits and PRL can be used as a candidate gene for marker-assisted selection in Italian Mediterranean river buffalo breeding.

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