EFFECT OF HERD-YEAR PRODUCTION LEVEL ON EXPRESSION OF SIRE MERIT

1990 ◽  
Vol 70 (2) ◽  
pp. 383-388
Author(s):  
P. L. McEWEN ◽  
A. WINKELMAN
Keyword(s):  
Regression Analysis ◽  
Key Words ◽  
Regression Coefficients ◽  
Group Differences ◽  
Production Traits ◽  
Fat Percentage ◽  
Sire Group ◽  
Fat Yield ◽  
Linear Contrasts ◽  
Dairy Sire

Performance data on 110 602 first lactation Holstein cows were utilized to compare the expressions of sire proof at various herd-year production levels. Production traits analyzed were BCA milk, BCA fat and fat percentage. Herd-year averages were partitioned into six groups for each trait. Regression analysis indicated significant interactions between herd-year level and sire estimated transmitting ability (ETA) for daughter milk and fat BCA (P < 0.001). Interaction between herd group and sire proof for fat percentage was found to be insignificant. Linear contrasts were used to compare sire proof slope differences for various herd-year group comparisons. Regression coefficients for sire proof tended to increase as herd-year level increased for both milk and fat yield. The coefficient for sire fat percentage was smaller for the lowest herd-year level when compared to other herd levels. Sire proofs for milk and fat were than categorized into six and seven groups respectively. Sire group and herd-year by sire group interaction were found to account for a significant (P < 0.01) amount of variation in daughter milk and fat yield. Linear contrasts were also used to compare specific sire group differences at various herd production levels. Significant herd-year differences were observed for both daughter milk and fat yield. However specific trends were not prevalent for sire group differences as herd-year groups increased for both traits. Key words: Dairy, sire, daughter

scholarly journals SIRE-SON CORRELATIONS OF GENETIC EVALUATIONS FOR FAT PERCENTAGE IN HOLSTEIN-FRIESIANS

1987 ◽  
Vol 67 (3) ◽  
pp. 631-635 ◽  
Author(s):  
T. E. ALI ◽  
L. R. SCHAEFFER
Keyword(s):  
Key Words ◽  
Artificial Insemination ◽  
Milk Fat ◽  
Genetic Parameters ◽  
Direct Calculation ◽  
Fat Percentage ◽  
Low Correlation ◽  
Fat Yield ◽  
Genetic Evaluations ◽  
Selection Of

The correlation between sire and son genetic evaluations for fat percentage has been shown to be lower than corresponding correlations for milk or fat yield for the population of bulls in artificial insemination. The purpose of this study was to determine the cause of this low correlation. Based on 302 935 first-lactation daughters of 11 396 sires, the heritabilities of milk, fat and fat percentage were 0.28, 0.27 and 0.52, respectively. Indirect versus direct calculation of sire evluations for fat percentage were correlated at 0.997, and resulting sire-son correlations were 0.45 for directly calculated proofs and 0.43 for indirectly calculated proofs. The low sire-son correlations were due to the intense selection of sires of sons, especially for fat percentage, which resulted in a change in genetic parameters among the bulls used as sires of sons compared to the parameters in the overall population. Key words: Fat percentage, pedigree indexing, dairy sires

scholarly journals Associations between polymorphisms of SLC22A7, NGFR, ARNTL and PPP2R2B genes and Milk production traits in Chinese Holstein

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ruike Jia ◽  
Yihan Fu ◽  
Lingna Xu ◽  
Houcheng Li ◽  
Yanhua Li ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Milk Production ◽  
Association Analysis ◽  
Milk Yield ◽  
Production Traits ◽  
Milk Production Traits ◽  
Fat Percentage ◽  
Protein Percentage ◽  
Fat Yield ◽  
Percentage Protein

Abstract Background Our preliminary work confirmed that, SLC22A7 (solute carrier family 22 member 7), NGFR (nerve growth factor receptor), ARNTL (aryl hydrocarbon receptor nuclear translocator like) and PPP2R2B (protein phosphatase 2 regulatory subunit Bβ) genes were differentially expressed in dairy cows during different stages of lactation, and involved in the lipid metabolism through insulin, PI3K-Akt, MAPK, AMPK, mTOR, and PPAR signaling pathways, so we considered these four genes as the candidates affecting milk production traits. In this study, we detected polymorphisms of the four genes and verified their genetic effects on milk yield and composition traits in a Chinese Holstein cow population. Results By resequencing the whole coding region and part of the flanking region of SLC22A7, NGFR, ARNTL and PPP2R2B, we totally found 20 SNPs, of which five were located in SLC22A7, eight in NGFR, three in ARNTL, and four in PPP2R2B. Using Haploview4.2, we found three haplotype blocks including five SNPs in SLC22A7, eight in NGFR and three in ARNTL. Single-SNP association analysis showed that 19 out of 20 SNPs were significantly associated with at least one of milk yield, fat yield, fat percentage, protein yield or protein percentage in the first and second lactations (P < 0.05). Haplotype-based association analysis showed that the three haplotypes were significantly associated with at least one of milk yield, fat yield, fat percentage, protein yield or protein percentage (P < 0.05). Further, we used SOPMA software to predict a SNP, 19:g.37095131C > T in NGFR, changed the structure of NGFR protein. In addition, we used Jaspar software to found that four SNPs, 19:g.37113872C > G,19:g.37113157C > T, and 19:g.37112276C > T in NGFR and 15:g.39320936A > G in ARNTL, could change the transcription factor binding sites and might affect the expression of the corresponding genes. These five SNPs might be the potential functional mutations for milk production traits in dairy cattle. Conclusions In summary, we proved that SLC22A7, NGFR, ARNTL and PPP2R2B have significant genetic effects on milk production traits. The valuable SNPs can be used as candidate genetic markers for genomic selection of dairy cattle, and the effects of these SNPs on other traits need to be further verified.

scholarly journals Regression analysis of milk production traits in simmental cows

2011 ◽  
Vol 27 (4) ◽  
pp. 1433-1441
Author(s):  
M.D. Petrovic ◽  
V. Bogdanovic ◽  
M.M. Petrovic ◽  
S. Rakonjac
Keyword(s):  
Regression Analysis ◽  
Milk Production ◽  
Milk Fat ◽  
Regression Coefficients ◽  
Regression Equations ◽  
Production Traits ◽  
Milk Production Traits ◽  
Partial Regression ◽  
Three Generations ◽  
Lactation Length

The relationship between milk production traits over whole lactations was evaluated across three generations of Simmental cows, i.e. between daughters, dams and grand dams, by a phenotypic regression analysis with whole lactation traits in the daughter generation being used as the dependent variables (x1), and those in the dam and grand dam generations being used as the independent variables (x2 and x3). The results were obtained from a sample of 1170 daughters and as many dams and grand dams. The significance of the partial regression coefficients b2 and b3 was separately evaluated by a t-test. An analysis of variance was used to estimate the significance of the simultaneous effect of the production traits of dams and grand dams on the milk production achieved in the daughter generation. The calculated value of the partial regression coefficients for the whole lactation production traits across three generations (grand dams, dams and daughters) and their statistical significances determined by the t and F tests, as well as the regression equations used, suggested that the effect of the grand dam generation on the milk production traits in granddaughters was substantially lower than the effect of dams. The calculated partial regression coefficients (b2 and b3) were positive and statistically very significant (P<0.01), excepting the regression coefficients b3 for lactation length and b2 for milk fat content that were not statistically significant (P>0.05). A very significant change (P<0.01) was observed in all production traits in the daughter generation as simultaneously affected by the traits in the dam and grand dam generations.

Association of class I bovine lymphocyte antigens with production traits in the Ayrshire breed

1994 ◽  
Vol 74 (4) ◽  
pp. 703-705
Author(s):  
T. R. Batra ◽  
P. A. Macdonald ◽  
M. J. Stear
Keyword(s):  
Key Words ◽  
Milk Fat ◽  
Breeding Value ◽  
Additive Effects ◽  
Production Traits ◽  
Substitution Model ◽  
Ayrshire Breed ◽  
Bovine Lymphocyte ◽  
Lymphocyte Antigens ◽  
Fat Yield

Ninety progeny tested Canadian Ayrshire bulls were serologically typed for the BoLA-A locus to determine the association of these alleles with production traits. After exclusion of bulls carrying alleles that occurred at frequencies lower than 2% or whose production proofs were not available, records from 78 bulls remained for analysis. A gene substitution model, which included the effects of BoLA alleles and the breeding value of the sire of the bull as covariate, was used to evaluate the additive effects of BoLA alleles of bulls (ETAs) on the production traits of their daughters. Allele W17 was significantly associated with ETA for milk, fat and protein yields. Allele CA96 was associated with significant increases in ETA for fat yield. There was no significant association of BoLA alleles with either ETA for fat or protein percentage. Key words: BoLA, production traits, Ayrshire

Genetic parameters of milk cholesterol content in Holstein cattle

2018 ◽  
Vol 98 (4) ◽  
pp. 714-722 ◽  
Author(s):  
Duy N. Do ◽  
Allison Fleming ◽  
Flavio S. Schenkel ◽  
Filippo Miglior ◽  
Xin Zhao ◽  
...  
Keyword(s):  
Milk Fat ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Cholesterol Content ◽  
Production Traits ◽  
Fat Percentage ◽  
Bivariate Models ◽  
Estimate Heritability ◽  
Fat Yield ◽  
Using Data

This study aimed to estimate heritability for milk cholesterol (CHL) and genetic correlations between milk CHL and other production traits (test-day milk, fat, and protein yields, fat and protein percentages, and somatic cell score). Milk CHL content was determined by gas chromatography and expressed as mg of CHL in 100 g of fat (CHL_fat) or in 100 mg of milk (CHL_milk). Univariate models were used to estimate variances and heritability, whereas bivariate models were used to compute correlations using data from 1793 cows. The average concentrations (standard deviation) of CHL_fat and CHL_milk were 275.63 (75) mg and 11.16 (3.63) mg, respectively. Milk CHL content was significantly affected by days in milk and herd (P < 0.05), but not by parity, regardless of the scale of expression. Heritability estimates for CHL_fat and CHL_milk were 0.06 ± 0.04 and 0.17 ± 0.06, respectively. Phenotypic and genetic correlations between CHL_fat and CHL_milk were 0.82 and 0.44 ± 0.24, respectively. CHL_fat had nonsignificant genetic correlations with all production traits, whereas CHL_milk had significant (P < 0.05) genetic correlations with milk yield (−0.47), fat yield (0.51), protein percentage (0.56), and fat percentage (0.88). This is the first study to estimate genetic parameters for milk CHL content. Further studies are required to assess the possibility of genetically selecting cows with lower milk CHL content.

scholarly journals Single Nucleotide Polymorphisms of NUCB2 and Their Genetic Associations with Milk Production Traits in Dairy Cows

Genes ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 449 ◽  
Author(s):  
Bo Han ◽  
Yuwei Yuan ◽  
Yanhua Li ◽  
Lin Liu ◽  
Dongxiao Sun
Keyword(s):  
Nucleotide Polymorphisms ◽  
Production Traits ◽  
Genetic Associations ◽  
Milk Production Traits ◽  
Fat Percentage ◽  
Dry Period ◽  
Milk Traits ◽  
Single Nucleotide ◽  
Flanking Region ◽  
Fat Yield

We previously used the RNA sequencing technique to detect the hepatic transcriptome of Chinese Holstein cows among the dry period, early lactation, and peak of lactation, and implied that the nucleobindin 2 (NUCB2) gene might be associated with milk production traits due to its expression being significantly increased in early lactation or peak of lactation as compared to dry period (q value < 0.05). Hence, in this study, we detected the single nucleotide polymorphisms (SNPs) of NUCB2 and analyzed their genetic associations with milk yield, fat yield, fat percentage, protein yield, and protein percentage. We re-sequenced the entire coding and 2000 bp of 5′ and 3′ flanking regions of NUCB2 by pooled sequencing, and identified ten SNPs, including one in 5′ flanking region, two in 3′ untranslated region (UTR), and seven in 3′ flanking region. The single-SNP association analysis results showed that the ten SNPs were significantly associated with milk yield, fat yield, fat percentage, protein yield, or protein percentage in the first or second lactation (p values <= 1 × 10−4 and 0.05). In addition, we estimated the linkage disequilibrium (LD) of the ten SNPs by Haploview 4.2, and found that the SNPs were highly linked in one haplotype block (D′ = 0.98–1.00), and the block was also significantly associated with at least one milk traits in the two lactations (p values: 0.0002–0.047). Further, we predicted the changes of transcription factor binding sites (TFBSs) that are caused by the SNPs in the 5′ flanking region of NUCB2, and considered that g.35735477C>T might affect the expression of NUCB2 by changing the TFBSs for ETS transcription factor 3 (ELF3), caudal type homeobox 2 (CDX2), mammalian C-type LTR TATA box (VTATA), nuclear factor of activated T-cells (NFAT), and v-ets erythroblastosis virus E26 oncogene homolog (ERG) (matrix similarity threshold, MST > 0.85). However, the further study should be performed to verify the regulatory mechanisms of NUCB2 and its polymorphisms on milk traits. Our findings first revealed the genetic effects of NUCB2 on the milk traits in dairy cows, and suggested that the significant SNPs could be used in genomic selection to improve the accuracy of selection for dairy cattle breeding.

scholarly journals Association of gene BoLA DRB3.2 with production traits in a dairy herd of Antioquia, Colombia

2014 ◽  
pp. 4116-4129 ◽  
Author(s):  
Juan Zambrano A ◽  
Julián Echeverri Z ◽  
Albeiro López-Herrera
Keyword(s):  
Dairy Herd ◽  
General Linear Model ◽  
Milk Quality ◽  
Holstein Cattle ◽  
Quality Traits ◽  
Production Traits ◽  
Fat Percentage ◽  
Allelic Variants ◽  
Pcr Rflp ◽  
Fat Yield

ABSTRACTObjective. To determine the associations of BoLA DRB3.2 alleles present in Holstein and BON x Holstein cattle to production and milk quality traits in a dairy herd of Antioquia, Colombia. Materials and methods. Ninety-one cows, 66 Holstein and 25 BxH, were genotyped for the BoLA DRB3.2 gene, through PCR-RFLP technique. Furthermore, the association of the alleles of the gene BoLA DRB3.2 with milk yield (PL305), fat yield (PG305), protein yield (PP305) fat percentage (PGRA) and protein percentage (PPRO) were determined, using a general linear model. Results. Twenty-seven BoLA DRB3.2 alleles were identified; the most frequent alleles in Holstein were: BoLA DRB3.2*23, 22, and 24 with frequencies of: 0.159, 0.129, and 0.106, respectively and the most frequent alleles in BxH were: BoLA DRB3.2*23, 24 and 20 with frequencies of: 0.20, 0.140, and 0.120, respectively. Associations of BoLA DRB3.2 alleles with production and milk quality traits were also determined. In Holstein cows the BoLA DRB3.2*36 allele was associated with low PL305 (p≤0.01), high PGRA in multiparous cows (p≤0.05) and high PG305 in primiparous cows (p≤0.01). The BoLA DRB3.2*33 allele was associated with increased in the PPRO in multiparous cows (p≤0.01). In BXH cows only the BoLA DRB3*19 allele was associated with high PGRA (p≤0.05). Conclusions. The gene BoLA DRB3.2 shows high polymorphism in both groups; Holstein and BxH and some of its allelic variants were associated with production and milk quality traits

Effect of Breed and Some Non - Genetic Factors on Milk Production and Some Proportions of Its Chemical Components in Two Breeds of Local Sheep

2020 ◽  
Vol 10 (1) ◽  
pp. 227-231
Author(s):  
Rahman Hussein AL-Qasimi ◽  
Shatha Mohammed Abbas ◽  
Allawi L.D. AL-Khauzai
Keyword(s):  
Milk Production ◽  
Genetic Factors ◽  
Chemical Components ◽  
Lactation Period ◽  
Production Traits ◽  
Milk Production Traits ◽  
Fat Percentage ◽  
Awassi Sheep ◽  
Total Milk ◽  
Milk Components

The study was carried out on 19 ewes of local Awassi sheep and 12ewes local Arabi sheep in the Al-kafeel sheep station Karbala, to determine the effect of breed and some non-genetic factors such as (sex of the lamb, type of birth, age and weight of ewes at birth) on daily and total milk production and lactation period and some of milk components (fat, protein and lactose). The results showed that a significant effect (P <0.05) of the breed on milk production traits where Awassi sheep recorded the highest mean (0.91 kg , 101.63 kg , 104.86 day) compared to the Arabi sheep she was means (0.77 kg , 88.15 kg , 99.15 day) respectively. As well as in proportions of milk components with mean( 5.1 , 4.90 , 5.51) % respectively compared to the Arabi sheep (4.70 . 4.20 . 4.89) ewes with male lambs also exceeded superior ewes with female lambs in daily and total milk production and the lactation period the sex of the lamb did not affect the proportions of milk components the weight of the ewes had a significant effect (P <0.05) in milk production attributes with superior weight of ewes on lower ewes and did not affect the proportions of milk ingredients except for lactose. The type of birth and the age of the ewes did not have a significant effect in all the studied traits except for the superiority (P<0.05) of young ewes on age ewes in the fat percentage of milk.

Regression analysis of indicators of a numerical experiment to determine the cooling time of oil

2020 ◽  
pp. 89-97
Author(s):  
A. U. Yakupov ◽  
D. A. Cherentsov ◽  
K. S. Voronin ◽  
Yu. D. Zemenkov
Keyword(s):  
Regression Analysis ◽  
Computer Experiment ◽  
Calculation Model ◽  
Cooling Time ◽  
Regression Coefficients ◽  
Fisher Criterion ◽  
Empirical Relationships ◽  
Factors Affecting ◽  
Oil Pipeline ◽  
Significant Regression

The article performed the processing of the results of a computer experiment to determine the cooling time of oil in a stopped oil pipeline. We proposed a calculation model in previous works that allows you to simulate the process of cooling oil.There was a need to verify the previously obtained results when conducting a laboratory experiment on a stand with soil. To conduct the experiment, it was necessary to conduct the planning of the experiment. The factors affecting the cooling time of oil in the oil pipeline, which will vary in the proposed experiment, are determined, empirical relationships are established. A regression analysis was carried out, and the dispersion homogeneity was checked using the Cochren criterion. The estimates of reproducibility variances are calculated. The adequacy hypothesis was tested using the Fisher criterion. Significant regression coefficients are established.

scholarly journals Regression Models in Complex Survey Sampling for Sensitive Quantitative Variables

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 609
Author(s):  
María del Mar Rueda ◽  
Beatriz Cobo ◽  
Antonio Arcos
Keyword(s):  
Regression Analysis ◽  
Regression Models ◽  
Regression Coefficients ◽  
Randomized Response ◽  
Statistical Tool ◽  
Complex Survey ◽  
Complex Sample ◽  
Qualitative Variables ◽  
World Survey ◽  
Sensitive Variable

Randomized response (RR) techniques are widely used in research involving sensitive variables, such as drugs, violence or crime, especially when a population mean or prevalence must be estimated. However, they are not generally applied to examine relationships between a sensitive variable and other characteristics. This type of technique was initially applied to qualitative variables, and studies later showed that a logistic regression may be performed with RR data. Since many of the variables considered in this context are quantitative, RR techniques were extended to these cases to estimate the values required. Regression analysis is a valuable statistical tool for exploring relationships among variables and for establishing associations between responses and covariates. In this article, we propose a design-based regression analysis for complex sample designs based on the unified RR approach. We present estimators of the regression coefficients, study their theoretical properties and consider different ways to estimate their variance. The properties of these estimation techniques were simulated using various quantitative randomized models. The method proposed was also used to analyse the findings from a real-world survey.

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