scholarly journals Estimation of genetic and phenotypic parameters for production traits in Holstein and Jersey from Colombia

2015 ◽  
pp. 4962-4973 ◽  
Author(s):  
Juan Rincón F ◽  
Juan Zambrano A ◽  
Julián Echeverri
Keyword(s):  
Somatic Cell ◽  
Milk Yield ◽  
Genetic Correlations ◽  
Somatic Cell Score ◽  
Production Traits ◽  
Fat Percentage ◽  
Multiple Trait ◽  
Protein Percentage ◽  
Selection Indices ◽  
The Tropics

ABSTRACT Objective. Determine the genetic and phenotypic parameters for milk yield, fat percentage, protein percentage and somatic cell score. Materials and methods. 18134 lactation records were used to Holstein and 1377 lactations for Jersey in different herds. The (co) variance components and genetic parameters were estimated using the software Multiple Trait Derivative-Free Restricted Maximum Likelihood MTDFREML. Results. The Holstein and Jersey heritability’s (and standard error) for milk yield were: 0.16 (0.082) and 0.15 (0.306), 0.30 (0.079) and 0.37 (0.319) for protein percentage, 0.32 (0.076) and 0.46 (0.313) for fat percentage and for somatic cell score were: 0.01 (0.054) and 0.01 (0.233), respectively. The largest genetic correlations were found between the percentage of fat and percentage of protein, with values of 0.82 (0.126) and 0.98 (0.852) for Holstein and Jersey respectively. The lowest correlations were between fat percentage and somatic cell score with -0.01 (1.147) and -0.01 (1. 734). Phenotypic correlations were generally found low and repeatability showed a significant effect of permanent environment on milk production per lactation. Conclusions. It is important to emphasize the development of research to help guide breeding programs in the tropics, using selection indices of multi-traits.

Association of MAP4K4 gene single nucleotide polymorphism with mastitis and milk traits in Chinese Holstein cattle

2017 ◽  
Vol 84 (1) ◽  
pp. 76-79 ◽  
Author(s):  
Dinesh Bhattarai ◽  
Xing Chen ◽  
Zia ur Rehman ◽  
Xingjie Hao ◽  
Farman Ullah ◽  
...  
Keyword(s):  
Candidate Gene ◽  
Somatic Cell ◽  
Milk Yield ◽  
Somatic Cell Score ◽  
Production Traits ◽  
Chromosome 11 ◽  
Fat Percentage ◽  
Milk Traits ◽  
Single Nucleotide ◽  
Protein Percentage

The objective of the studies presented in this Research Communication was to investigate the association of single nucleotide polymorphisms present in the MAP4K4 gene with different milk traits in dairy cows. Based on previous QTL fine mapping results on bovine chromosome 11, the MAP4K4 gene was selected as a candidate gene to evaluate its effect on somatic cell count and milk traits in ChineseHolstein cows. Milk production traits including milk yield, fat percentage, and protein percentage of each cow were collected using 305 d lactation records. Association between MAP4K4 genotype and different traits and Somatic Cell Score (SCS) was performed using General Linear Regression Model of R. Two SNPs at exon 18 (c.2061T > G and c.2196T > C) with genotype TT in both SNPs were found significantly higher for somatic SCS. We found the significant effect of exon 18 (c.2061T > G) on protein percentage, milk yield and SCS. We identified SNPs at different location of MAP4K4 gene of the cattle and several of them were significantly associated with the somatic cell score and other different milk traits. Thus, MAP4K4 gene could be a useful candidate gene for selection of dairy cattle against mastitis and the identified polymorphisms might potentially be strong genetic markers.

scholarly journals Analyses of genetic relationships between linear type traits, fat-to-protein ratio, milk production traits, and somatic cell count in first-parity Czech Holstein cows

2014 ◽  
Vol 59 (No. 12) ◽  
pp. 539-547 ◽  
Author(s):  
V. Zink ◽  
L. Zavadilová ◽  
J. Lassen ◽  
M. Štípková ◽  
M. Vacek ◽  
...  
Keyword(s):  
Somatic Cell ◽  
Milk Yield ◽  
Somatic Cell Score ◽  
Protein Yield ◽  
Production Traits ◽  
Linear Type ◽  
Protein Percentage ◽  
Phenotypic Correlations ◽  
Type Traits ◽  
Fat Yield

Genetic and phenotypic correlations between production traits, selected linear type traits, and somatic cell score were estimated. The results could be useful for breeding programs involving Czech Holstein dairy cows or other populations. A series of bivariate analyses was applied whereby (co)variance components were estimated using average information (AI-REML) implemented via the DMU statistical package. Chosen phenotypic data included average somatic cell score per a 305-day standard first lactation as well as the production traits milk yield, fat yield, protein yield, fat percentage, and protein percentage per the standard first lactation. Fifteen classified linear type traits were added, as they were measured at first lactation in the Czech Holstein population. All phenotypic data were collected within the progeny testing program of the Czech-Moravian Breeders Corporation from 2005 to 2009. The number of animals for each linear type trait was 59 454, except for locomotion, for which 53 424 animals were recorded. The numbers of animals with records of milk production data were 43 992 for milk yield, fat percentage, protein percentage, and fat-to-protein percentage ratio and 43 978 for fat yield and protein yield. In total, 27 098 somatic cell score records were available. The strongest positive genetic correlation between production traits and linear type traits was estimated between udder width and fat yield (0.51 ± 0.04), while the strongest negative correlation estimated was between body condition score and fat yield (−0.45 ± 0.03). Other estimated correlations were between those two extremes but generally they were close to zero or positive. The strongest negative phenotypic correlations were estimated between udder depth and milk yield and protein yield (both −0.17), while the strongest positive phenotypic correlations were estimated between milk yield, protein yield, and udder width (both 0.32).  

scholarly journals Genetic parameters between somatic cell score and production traits for Holstein cattle in Southern Brazil

2020 ◽  
Vol 33 (1) ◽  
pp. 60-70
Author(s):  
Gabrieli S Romano ◽  
Luis Fernando B Pinto ◽  
Altair A Valloto ◽  
José-Augusto Horst ◽  
Victor B Pedrosa
Keyword(s):  
Somatic Cell ◽  
Milk Yield ◽  
Variance Components ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Milk Quality ◽  
Somatic Cell Score ◽  
Fat Percentage ◽  
Fat Yield ◽  
Selection For

Background: Somatic cell score is an important parameter to predict milk quality and health of cows. However, in countries like Brazil, this trait is still not selected on a large scale, and no genetic parameters are reported in the literature. Objective: To estimate the variance components and genetic parameters for somatic cell score, milk yield, fat yield, protein yield, fat percentage, and protein percentage in Holstein cows. Methods: Records from 56,718 animals were used to estimate variance components, heritability, and genetic correlations using a multi-trait animal model by the REML method. Results: The heritability estimates were 0.19 for somatic cell score, 0.22 for milk yield, 0.26 for fat yield, 0.18 for protein yield, 0.61 for fat percentage, and 0.65 for protein percentage. The estimates of genetic correlations among analyzed traits ranged from -0.50 to 0.82. Conclusion: The low heritability observed for somatic cell score indicates that selection for this trait should result in benefits related to animal health and milk quality, but only in the long term. The low correlation between productive traits and somatic cell score indicates that inclusion of somatic cell score in animal breeding programs does not interfere negatively with the genetic selection for milk yield or solids.Keywords: Holstein; genetic correlation; genetic parameters; heritability; mastitis; milk quality; milk yield; multi-trait model; somatic cell score; variance components.  Resumen Antecedentes: El conteo de células somáticas es un parámetro importante para predecir la calidad de la leche y la salud de las vacas. Sin embargo, en países como Brasil, esta característica aún no se selecciona a gran escala y no se reportan parámetros genéticos en la literatura. Objetivo: Estimar los componentes de varianza y parámetros genéticos para el conteo de células somáticas, producción de leche, producción de grasa, producción de proteína, porcentaje de grasa y porcentaje de proteína en vacas de la raza Holstein. Métodos: Se usaron registros de 56.718 animales para estimar los componentes de la varianza, heredabilidad y correlaciones genéticas usando un modelo animal multicaracterístico por medio del método REML. Resultados: Las estimaciones de heredabilidad fueron 0,19 para el conteo de células somáticas, 0,22 para la producción de leche, 0,26 para la producción de grasa, 0,18 para producción de proteína, 0,61 para el porcentaje de grasa y 0,65 para el porcentaje de proteína. Las estimaciones de correlación genética entre las características analizadas variaron entre -0,50 a 0,82. Conclusión: La baja heredabilidad encontrada para conteo de células somáticas demostró que la selección para esta característica podría resultar en beneficios para la salud animal y calidad de la leche, pero sólo a largo plazo. La baja correlación genética existente entre las características productivas y el conteo de células somáticas indica que la inclusión del conteo de células somáticas en programas de selección no interfiere negativamente en la selección genética para la producción de leche o sólidos.Palabras clave: calidad de leche; correlación genética; conteo de células somáticas; componentes de varianza; heredabilidad; Holstein; mastitis; modelo multicaracteristico; parametros geneticos; producción de leche; selección genetica. Resumo Antecedentes: O escore de células somáticas é um parâmetro importante para a predição da qualidade do leite, bem como para a saúde das vacas. No entanto, em alguns países como o Brasil, essa característica não é selecionada em larga escala e não há parâmetros genéticos disponíveis na literatura. Objetivo: Estimar os componentes de variância e parâmetros genéticos para o escore de células somáticas, produção de leite, produção de gordura, produção de proteína, porcentagem de gordura e porcentagem de proteína em vacas da raça Holandesa. Métodos: Foi utilizado um total de 56.718 animais para estimar os componentes de variância, herdabilidade e correlações genéticas, considerando-se o modelo animal multicaracterística por meio do método REML. Resultados: As estimativas de herdabilidade foram de 0,19 para o escore de células somáticas, 0,22 para a produção de leite, 0,26 para a produção de gordura, 0,18 para produção de proteína, 0,61 para a porcentagem de gordura e 0,65 para a porcentagem de proteína. As estimativas de correlação genética entre as características analisadas variaram entre -0,50 a 0,82. Conclusão: A baixa herdabilidade encontrada para o escore de células somáticas demonstrou que a seleção para esta característica poderá resultar em benefícios para a saúde animal e qualidade do leite, porém, somente a longo prazo. A baixa correlação genética existente entre as características produtivas e o escore de células somáticas demonstrou que a inclusão do escore de células somáticas em programas de seleção não causa interferência negativa na seleção genética para a produção de leite ou sólidos.Palavras-chave: componentes de variância; correlação genéticas; escore de células somáticas; herdabilidade; mastite; modelo multicaracterística; parâmetros genéticos; produção de leite; qualidade do leite; raça Holandesa; seleção genética.

scholarly journals The use of dijkstra mechanistic model for genetic analysis of the lactation curve characteristics and their relationships with age at first calving and somatic cell score of Iranian dairy cows

2020 ◽  
Vol 42 ◽  
pp. e50181
Author(s):  
Mahdi Elahi Torshizi ◽  
Homayoun Farhangfar
Keyword(s):  
Somatic Cell ◽  
Genetic Correlation ◽  
Milk Yield ◽  
Mechanistic Model ◽  
Genetic Correlations ◽  
Somatic Cell Score ◽  
Specific Rate ◽  
Lactation Period ◽  
Age At First Calving ◽  
Lactation Curve

The objective of this study was to estimate lactation curve parameters with Dijkstra mechanistic model and to evaluate genetic and phenotypic relationships between the parameters and the average somatic cell count in primiparous cows. The finding indicated that heritability estimates for partial milk yield (PMY1, PMY2 and PMY3), total 305-day milk yield (TMY305), decay parameter (λ2), age at first calving (AFC) and peak yield (PY) were moderate while the heritability of persistency (PS%), average somatic cell score (AVGSCS), time to peak yield (TP), initial milk production (λ0), specific rate of cell proliferation at parturition (λ1), and specific rate of cell death (λ3) were quite low. Genetic correlations between both AFC and PS% traits with average somatic cell scores was negative (-0.047 and -0.060) but low positive genetic correlation were between partial milk yields (PMY1 and PMY3) while negative genetic correlation (-0.06) was obtained between TMY305 and AVGSCS. Differences between TMY305 of cows with less than 100000 cells mL-1 and cows with >1,500,000 cells mL-1 was approximately 708 Kg and is equivalent to 8% loss of milk yield/cow during lactation period and also loss of persistency (11.1 %( was shown for the extreme classes of SCC in this study.

scholarly journals Heritability of Teat Condition in Italian Holstein Friesian and Its Relationship with Milk Production and Somatic Cell Score

Animals ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 2271
Author(s):  
Francesco Tiezzi ◽  
Antonio Marco Maisano ◽  
Stefania Chessa ◽  
Mario Luini ◽  
Stefano Biffani
Keyword(s):  
Dairy Cattle ◽  
Somatic Cell ◽  
Milk Yield ◽  
Genetic Factors ◽  
Genetic Correlations ◽  
Somatic Cell Score ◽  
Cattle Industry ◽  
Holstein Friesian ◽  
Selection For ◽  
Current Selection

In spite of the impressive advancements observed on both management and genetic factors, udder health still represents one of most demanding objectives to be attained in the dairy cattle industry. Udder morphology and especially teat condition might represent the first physical barrier to pathogens’ access. The objectives of this study were to investigate the genetic component of teat condition and to elucidate its relationship with both milk yield and somatic cell scores in dairy cattle. Moreover, the effect of selection for both milk yield and somatic cell scores on teat condition was also investigated. A multivariate analysis was conducted on 10,776 teat score records and 30,160 production records from 2469 Italian Holstein cows. Three teat scoring traits were defined and included in the analysis. Heritability estimates for the teat score traits were moderate to low, ranging from 0.084 to 0.238. When teat score was based on a four-classes ordinal scoring, its genetic correlation with milk yields and somatic cell score were 0.862 and 0.439, respectively. The scale used to classify teat-end score has an impact on the magnitude of the estimates. Genetic correlations suggest that selection for milk yield could deteriorate teat health, unless more emphasis is given to somatic cell scores. Considering that both at national and international level, the current selection objectives are giving more emphasis to health traits, a further genetic deterioration in teat condition is not expected.

Using quantile regression for fitting lactation curve in dairy cows

2019 ◽  
Vol 86 (1) ◽  
pp. 19-24
Author(s):  
Hossein Naeemipour Younesi ◽  
Mohammad Mahdi Shariati ◽  
Saeed Zerehdaran ◽  
Mehdi Jabbari Nooghabi ◽  
Peter Løvendahl
Keyword(s):  
Quantile Regression ◽  
Dairy Cows ◽  
Milk Production ◽  
Milk Yield ◽  
Information Criterion ◽  
Production Traits ◽  
Milk Production Traits ◽  
Fat Percentage ◽  
Protein Percentage ◽  
Breeding Center

AbstractThe main objective of this study was to compare the performance of different ‘nonlinear quantile regression’ models evaluated at theτth quantile (0·25, 0·50, and 0·75) of milk production traits and somatic cell score (SCS) in Iranian Holstein dairy cows. Data were collected by the Animal Breeding Center of Iran from 1991 to 2011, comprising 101 051 monthly milk production traits and SCS records of 13 977 cows in 183 herds. Incomplete gamma (Wood), exponential (Wilmink), Dijkstra and polynomial (Ali & Schaeffer) functions were implemented in the quantile regression. Residual mean square, Akaike information criterion and log-likelihood from different models and quantiles indicated that in the same quantile, the best models were Wilmink for milk yield, Dijkstra for fat percentage and Ali & Schaeffer for protein percentage. Over all models the best model fit occurred at quantile 0·50 for milk yield, fat and protein percentage, whereas, for SCS the 0·25th quantile was best. The best model to describe SCS was Dijkstra at quantiles 0·25 and 0·50, and Ali & Schaeffer at quantile 0·75. Wood function had the worst performance amongst all traits. Quantile regression is specifically appropriate for SCS which has a mixed multimodal distribution.

scholarly journals Random regression models to estimate genetic parameters for test-day milk yield and composition in Iranian buffaloes

2013 ◽  
Vol 56 (1) ◽  
pp. 276-284 ◽  
Author(s):  
M. Madad ◽  
N. Ghavi Hossein-Zadeh ◽  
A. A. Shadparvar ◽  
D. Kianzad
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Milk Protein ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Random Regression ◽  
Production Traits ◽  
Environmental Correlations ◽  
Protein Percentage ◽  
Heritability Estimates

Abstract. The objective of this study was to estimate genetic parameters for milk yield and milk percentages of fat and protein in Iranian buffaloes. A total of 9,278 test-day production records obtained from 1,501 first lactation buffaloes on 414 herds in Iran between 1993 and 2009 were used for the analysis. Genetic parameters for productive traits were estimated using random regression test-day models. Regression curves were modeled using Legendre polynomials (LPs). Heritability estimates were low to moderate for milk production traits and ranged from 0.09 to 0.33 for milk yield, 0.01 to 0.27 for milk protein percentage and 0.03 to 0.24 for milk fat percentage, respectively. Genetic correlations ranged from −0.24 to 1 for milk yield between different days in milk over the lactation. Genetic correlations of milk yield at different days in milk were often higher than permanent environmental correlations. Genetic correlations for milk protein percentage ranged from −0.89 to 1 between different days in milk. Also, genetic correlations for milk percentage of fat ranged from −0.60 to 1 between different days in milk. The highest estimates of genetic and permanent environmental correlations for milk traits were observed at adjacent test-days. Ignoring heritability estimates for milk yield and milk protein percentage in the first and final days of lactation, these estimates were higher in the 120 days of lactation. Test-day milk yield heritability estimates were moderate in the course of the lactation, suggesting that this trait could be applied as selection criteria in Iranian milking buffaloes.

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.

DGAT1 polymorphism in Riverine buffalo, Swamp buffalo and crossbred buffalo

2018 ◽  
Vol 85 (4) ◽  
pp. 412-415 ◽  
Author(s):  
Jun Li ◽  
Shenhe Liu ◽  
Zipeng Li ◽  
Shujun Zhang ◽  
Guohua Hua ◽  
...  
Keyword(s):  
Milk Production ◽  
Milk Yield ◽  
Buffalo Milk ◽  
Production Performance ◽  
Production Traits ◽  
Coding Region ◽  
Fat Percentage ◽  
Protein Percentage ◽  
Dgat1 Gene ◽  
Swamp Buffalo

This Research Communication describes the polymorphisms in the coding region of DGAT1 gene in Riverine buffalo, Swamp buffalo and crossbred buffalo, and associations between polymorphisms and milk production performance in Riverine buffalo. Two polymorphisms of DGAT1were identified, located in exon 13 and exon 17, respectively. The distribution of the genotypes of the two SNP loci in different buffalo population varied, especially the polymorphism located in exon 13 which was not found in the Swamp buffalo. Moreover, SNP located in exon 17 was a nonsynonymous switch resulting in the animo acid sequence changed from an arginine (Arg) to a histidine (His) at position 484. Both SNPs were in Hardy–Weinberg equilibrium, and the polymorphism of g.8330T>C in the exon 13 was significantly associated with peak milk yield, total milk yield and protein percentage. The C variant was associated with an increase in milk yield and peak yield but less in protein percentage compared with the T variant. The polymorphisms of g.9046T>C in exon 17 were significantly associated with fat percentage, in that the buffaloes with TT genotype had a significantly higher fat percentage than those with CC genotype. These findings reveal the difference in the genetic evolution of the DGAT1 between Riverine buffalo and Swamp buffalo, and provide evidence that the DGAT1 gene has potential effects for Riverine buffalo milk production traits, which can be used as a candidate gene for marker-assisted selection in buffalo breeding.

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