scholarly journals Effects of balanced selection for intramuscular fat and abdominal fat percentage and estimates of genetic parameters

2017 ◽  
Vol 96 (2) ◽  
pp. 282-287 ◽  
Author(s):  
M. Jiang ◽  
W.L. Fan ◽  
S.Y. Xing ◽  
J. Wang ◽  
P. Li ◽  
...  
Keyword(s):  
Genetic Parameters ◽  
Intramuscular Fat ◽  
Abdominal Fat ◽  
Fat Percentage ◽  
Selection For

Effects of selection for ultrasound intramuscular fat percentage in Angus bulls on carcass traits of progeny

2002 ◽  
Vol 80 (8) ◽  
pp. 2017 ◽  
Author(s):  
R. L. Sapp ◽  
J. K. Bertrand ◽  
T. D. Pringle ◽  
D. E. Wilson
Keyword(s):  
Carcass Traits ◽  
Intramuscular Fat ◽  
Fat Percentage ◽  
Selection For

Selection against abdominal fat percentage may increase intramuscular fat content in broilers

2016 ◽  
Vol 133 (5) ◽  
pp. 422-428 ◽  
Author(s):  
L. Leng ◽  
H. Zhang ◽  
J.Q. Dong ◽  
Z.P. Wang ◽  
X.Y. Zhang ◽  
...  
Keyword(s):  
Intramuscular Fat ◽  
Abdominal Fat ◽  
Fat Content ◽  
Fat Percentage ◽  
Intramuscular Fat Content

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.

Genetic parameters of beef characters and the genetic relationship between meat and milk production in British Friesian cattle

1972 ◽  
Vol 14 (2) ◽  
pp. 135-148 ◽  
Author(s):  
I. L. Mason ◽  
V. E. Vial ◽  
R. Thompson
Keyword(s):  
Milk Yield ◽  
Genetic Relationship ◽  
Genetic Parameters ◽  
Genetic Correlations ◽  
Carcass Composition ◽  
Standard Errors ◽  
Fat Percentage ◽  
Selection For ◽  
Friesian Cattle ◽  
Weight For Age

SUMMARYA beef progeny test was organized for 66 British Friesian bulls standing at AI centres in England. Eighty-one progeny groups averaging 8-5 steers each were reared on the farms of various co-operating organizations and their growth and carcass characters were recorded. Heritability of various measurements of gain varied from 0 to 0·34, of carcass conformation measures from 0·24 to 0·50, of muscle and fat percentage in the rib joint was 0·58 and 0·46 respectively, of other measures of fatness varied from 0·04 to 0·18, of weight of feet was 0·4 and of weight of hide 0·5.Phenotypic correlations among beef characters gave no indication that carcass composition could be predicted from the external carcass measurements or subjective scores used in this study. Genetic correlations suggested that selection for weight for age would produce a fatter and more compact carcass. Genetic correlations were high and negative between milk yield (contemporary comparison) and weight for age, carcass weight/length, and blockiness of leg, and high and positive between milk yield, and carcass depth/length and percentage bone in the rib joint. Their standard errors were also high.

scholarly journals Increasing Fat Deposition Via Upregulates the Transcription of Peroxisome Proliferator-Activated Receptor Gamma in Native Crossbred Chickens

Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 90
Author(s):  
Supanon Tunim ◽  
Yupin Phasuk ◽  
Samuel E. Aggrey ◽  
Monchai Duangjinda
Keyword(s):  
Intramuscular Fat ◽  
Abdominal Fat ◽  
Fat Deposition ◽  
Peroxisome Proliferator ◽  
Fat Percentage ◽  
Peroxisome Proliferator Activated Receptor ◽  
Native Breed ◽  
Muscle Tissues ◽  
Chicken Breeds ◽  
Pparg Expression

This study aimed to study the role of PPARs on fat deposition in native crossbred chicken. We studied the growth, abdominal, subcutaneous, and intramuscular fat, and mRNA expression of PPARA and PPARG in adipose and muscle tissues of four chicken breeds (CH breed (100% Thai native chicken), KM1 (50% CH background), KM2 (25% CH background), and broiler (BR)). The result shows that the BR chickens had higher abdominal fat than other breeds (p < 0.05) and the KM2 had an abdominal fat percentage higher than KM1 and CH respectively (p < 0.05). The intramuscular fat of BR was greater than KM1 and CH (p < 0.05). In adipose tissue, PPARA expression was different among the chicken breeds. However, there were breed differences in PPARG expression. Study of abdominal fat PPARG expression showed the BR breed, KM1, and KM2 breed significantly greater (p < 0.05) than CH. In 8 to 12 weeks of age, the PPARG expression of the CH breed is less than (p < 0.05) KM2. Crossbreeding improved the growth of the Thai native breed, there was also a corresponding increase in carcass fatness. However, there appears to be a relationship between PPARG expression and fat deposition traits. therefore, PPARG activity hypothesized to plays a key role in lipid accumulation by up-regulation.

scholarly journals A Novel 65-bp Indel in the GOLGB1 Gene Is Associated with Chicken Growth and Carcass Traits

Animals ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 475 ◽  
Author(s):  
Rong Fu ◽  
Tuanhui Ren ◽  
Wangyu Li ◽  
Jiaying Liang ◽  
Guodong Mo ◽  
...  
Keyword(s):  
Developmental Disorders ◽  
Genetic Parameters ◽  
Biological Function ◽  
Carcass Traits ◽  
Abdominal Fat ◽  
Fat Percentage ◽  
Inhibiting Factor ◽  
Chicken Population ◽  
Yellow Index ◽  
Predominant Allele

Golgin subfamily B member 1 (GOLGB1) gene encodes the coat protein 1 vesicle inhibiting factor, giantin. Previous study showed that mutations of the GOLGB1 gene are associated with dozens of human developmental disorders and diseases. However, the biological function of GOLGB1 gene in chicken is still unclear. In this study, we detected a novel 65-bp insertion/deletion (indel) polymorphism in the chicken GOLGB1 intron 5. Association of this indel with chicken growth and carcass traits was analyzed in a yellow chicken population. Results showed that this 65-bp indel was significantly associated with chicken body weight (p < 0.05), highly significantly associated with neck weight, abdominal fat weight, abdominal fat percentage and the yellow index b of breast (p < 0.01). Analysis of genetic parameters indicated that “I” was the predominant allele. Except for the yellow index b of breast, II genotype individuals had the best growth characteristics, by comparison with the ID genotype and DD genotype individuals. Moreover, the mRNA expression of GOLGB1 was detected in the liver tissue of chicken with different GOLGB1 genotypes, where the DD genotype displayed high expression levels. These findings hinted that the 65-bp indel in GOLGB1 could be assigned to a molecular marker in chicken breeding and enhance production in the chicken industry.

Effects of selection for ultrasound intramuscular fat percentage in Angus bulls on carcass traits of progeny1,2

2002 ◽  
Vol 80 (8) ◽  
pp. 2017-2022
Author(s):  
R. L. Sapp ◽  
J. K. Bertrand ◽  
T. D. Pringle ◽  
D. E. Wilson
Keyword(s):  
Carcass Traits ◽  
Intramuscular Fat ◽  
Fat Percentage ◽  
Selection For
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