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 ◽  
...  

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).  

1994 ◽  
Vol 59 (2) ◽  
pp. 183-187 ◽  
Author(s):  
S. Brotherstone

AbstractFirst lactation production and linear type records of 72 559Holstein-Friesian cows, calving from 1982 to 1989, were analysed by multivariate restricted maximum likelihood, using a sire model. The data comprised offspring of 1066 randomly used sires, and 91 proven i.e. widely used bulls. All phenotypic correlations between the type traits and the yield traits were small, but moderate genetic correlations were obtained between milk, fat and protein yield and angularity (~—0·43) and between the yield traits and udder depth (~0·44), indicating that higher yielding heifers are more angular and have deeper udders. The heritabilities of the type traits were in line with previous analyses, but those for milk, fat and protein yield were rather high at 0·47, 0·52 and 0·45 respectively


2015 ◽  
pp. 4962-4973 ◽  
Author(s):  
Juan Rincón F ◽  
Juan Zambrano A ◽  
Julián Echeverri

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.


2017 ◽  
Vol 84 (1) ◽  
pp. 76-79 ◽  
Author(s):  
Dinesh Bhattarai ◽  
Xing Chen ◽  
Zia ur Rehman ◽  
Xingjie Hao ◽  
Farman Ullah ◽  
...  

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.


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

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.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ruike Jia ◽  
Yihan Fu ◽  
Lingna Xu ◽  
Houcheng Li ◽  
Yanhua Li ◽  
...  

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.


Genes ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 265 ◽  
Author(s):  
Bo Han ◽  
Yuwei Yuan ◽  
Ruobing Liang ◽  
Yanhua Li ◽  
Lin Liu ◽  
...  

Our initial RNA sequencing work identified that lipin 1 (LPIN1) was differentially expressed during dry period, early lactation, and peak of lactation in dairy cows, and it was enriched into the fat metabolic Gene Ontology (GO) terms and pathways, thus we considered LPIN1 as the candidate gene for milk production traits. In this study, we detected the polymorphisms of LPIN1 and verified their genetic effects on milk yield and composition in a Chinese Holstein cow population. We found seven SNPs by re-sequencing the entire coding region and partial flanking region of LPIN1, including one in 5′ flanking region, four in exons, and two in 3′ flanking region. Of these, four SNPs, c.637T > C, c.708A > G, c.1521C > T, and c.1555A > C, in the exons were predicted to result in the amino acid replacements. With the Haploview 4.2, we found that seven SNPs in LPIN1 formed two haplotype blocks (D′ = 0.98–1.00). Single-SNP association analyses showed that SNPs were significantly associated with milk yield, fat yield, fat percentage, or protein yield in the first or second lactation (p = < 0.0001–0.0457), and only g.86049389C > T was strongly associated with protein percentage in both lactations (p = 0.0144 and 0.0237). The haplotype-based association analyses showed that the two haplotype blocks were significantly associated with milk yield, fat yield, protein yield, or protein percentage (p = < 0.0001–0.0383). By quantitative real-time PCR (qRT-PCR), we found that LPIN1 had relatively high expression in mammary gland and liver tissues. Furthermore, we predicted three SNPs, c.637T > C, c.708A > G, and c.1521C > T, using SOPMA software, changing the LPIN1 protein structure that might be potential functional mutations. In summary, we demonstrated the significant genetic effects of LPIN1 on milk production traits, and the identified SNPs could serve as genetic markers for dairy breeding.


1987 ◽  
Vol 44 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Karin Meyer ◽  
Susan Brotherstone ◽  
W. G. Hill ◽  
Maureen R. Edwards

ABSTRACTRecords on 18 939 Friesian-Holstein cows classified for 16 linear-type traits and total score in first lactation by the British Friesian Cattle Society and similarly on 13 192 cows in second lactation were analysed to estimate heritabilities and genetic correlations among the linear traits. These comprised progeny of 542 and 477 young sires, respectively, together with older sires included to increase connections. Correlations of type with milk production traits and correlations between type in first and second lactations were estimated from subsets (of about one-half) of the data. Effects due to proportion of Holstein in the sires were removed.Heritabilities of the linear traits were similar in first and second lactations, ranging from under 0·15 for one of the leg traits to about 0·5 for stature. Genetic correlations between traits in first and second lactation were generally over 0·75, whereas phenotypic correlations for most traits ranged from 0·3 to 0·6. Genetic and phenotypic correlations among the linear traits were generally low, except for those involving size.Phenotypic correlations between linear traits and milk yield and composition were all small, none exceeding 0·3. Genetic correlations were generally almost as small: taking first and second lactations together, the only consistent non-negligible correlations with yield were for angularity (+0·3), fore-udder attachment (–0·2) and udder depth (–0·4). The linear traits are not useful predictors of yield.


2013 ◽  
Vol 56 (1) ◽  
pp. 873-881 ◽  
Author(s):  
N. G. Hossein-Zadeh

Abstract. Calving records of Holstein cows from January 1983 to December 2006 comprising 1,190 herds with 385,102 calving events were used to evaluate factors affecting the length of lactation and effect of current lactation length on the next productive and reproductive performances of Iranian Holsteins. Statistical analyses of productive and reproductive traits in this study were performed as linear mixed models. Lactation length (LL) of cows was grouped into 10 classes from <100 days through 500 days. Average LL was 314 days in Iranian Holsteins. Primiparous cows had the greatest LL and the mean of LL increased over the years from 1983 to 2006 and spring calvers had the longest LL (P<0.05). Cows within the LL class of 500 had the greatest unadjusted milk yield, adjusted milk yield, adjusted protein yield and adjusted fat yield and also had the longest calving intervals (P<0.05). Cows within the LL classes of 150–199 and 200–249 had the greatest values of adjusted protein percentage. Also, age at calving was the lowest for the LL class of 250–299 (P<0.05). There were linear and increasing trends for unadjusted milk yield, adjusted milk yield, adjusted protein yield and adjusted fat yield over the LL classes in this study, but a linear but decreasing trend was observed for adjusted protein percentage over LL classes. On the other hand, there were non-linear relationships between adjusted fat percentage, calving interval and age at calving with LL classes in the current study.


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