scholarly journals First Results of a MAS Study in Dairy Cattle with Respect to Longevity (short communication)

2000 ◽  
Vol 43 (3) ◽  
pp. 241-248 ◽  
Author(s):  
G. Freyer ◽  
G. Erhardt
Keyword(s):  
Milk Yield ◽  
Fat Content ◽  
Protein Yield ◽  
Production Traits ◽  
Milk Production Traits ◽  
Two Samples ◽  
First Results ◽  
Negative Effect ◽  
Selection For ◽  
Milk Trait

Abstract. A study where Casein loci were used to be markers for improving milk yield, fat content and protein yield in a marker assisted selection experiment focused on possible side effects of this process on longevity traits. Using the data of two samples of cows a Simulation on the data was carried out evaluating the selection differences in period of use, period of life and production of the whole life indirectly. The selection criteria were flexible using one of the milk production traits each as well as marker information. During the investigated period no negative effect of simulated selection using EBV for milk yield, fat content and protein yield alone or in combination with the Casein loci used as markers on longevity traits occurred in the population. There are no significant differences regarding the longevity traits caused by selection for Single milk trait based on pure EBV and MAS.

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.

Investigation of myostatin and calpain 3 gene polymorphisms and their association with milk-production traits in Sfakia sheep

2020 ◽  
Vol 60 (3) ◽  
pp. 347
Author(s):  
Adel H. M. Ibrahim ◽  
Nikolaos Tzanidakis ◽  
Smaragda Sotiraki ◽  
Huitong Zhou ◽  
Jonathan Hickford
Keyword(s):  
Nucleotide Sequence ◽  
Milk Production ◽  
Milk Yield ◽  
Milk Fat ◽  
Fat Content ◽  
Solid Content ◽  
Production Traits ◽  
Milk Production Traits ◽  
Banding Patterns ◽  
Milk Solid

Context Genetic selection based on genetic markers for economically important traits in Sfakia sheep. Aims The aim of the present study was to investigate variation in the ovine myostatin gene (MSTN) and calpain 3 gene (CAPN3), and their association with milk-production traits. Methods Records for milk yield, milk fat content, protein content, lactose content, and non-fat solid content, pH and somatic-cell score (log), were obtained from 376 Sfakia ewes. Polymerase chain reaction–single-strand conformational polymorphism (PCR–SSCP) analyses were used to detect variation in intron 1 of MSTN and exon 10 of CAPN3. General linear models were then used to test for associations between the variation in MSTN and CAPN3, and milk-production traits. Key results The SSCP banding patterns for MSTN showed four variants (A1, A2, A3 and A4), which contained nine nucleotide sequence differences. Four SSCP banding patterns (C1, C2, C3 and C4) were observed for CAPN3 and these contained eight nucleotide-sequence differences. The MSTN variation was associated (P &lt; 0.05) with variation in milk yield and non-fat milk solid content. Variation in CAPN3 was associated with milk yield (P &lt; 0.001), fat content (P &lt; 0.05) and lactose content (P &lt; 0.05). Association analyses between the presence/absence of MSTN and CAPN3 variants and milk-production traits showed that a variant of MSTN that had previously between associated with muscle hypertrophy was associated with decreased milk yield (P &lt; 0.05) and a lower non-fat milk solid content (P &lt; 0.01). A CAPN3 variant that had previously been associated with increased sheep-carcass loin lean-meat yield was associated with a decreased milk yield (P &lt; 0.01) and a decreased milk fat content (P &lt; 0.05). Conclusions Our results have provided an insight into the effects of variation in ovine MSTN and CAPN3 on milk-production traits in sheep. Implications To preserve the dual-purpose characteristics of Sfakia sheep, breeding goals should take into account the possible antagonism between meat and milk traits.

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 Identification of the association between <i>FABP4</i> gene polymorphisms and milk production traits in Sfakia sheep

2019 ◽  
Vol 62 (2) ◽  
pp. 413-422 ◽  
Author(s):  
Adel H. M. Ibrahim ◽  
Nikolaos Tzanidakis ◽  
Smaragda Sotiraki ◽  
Huitong Zhou ◽  
Jonathan G. H. Hickford
Keyword(s):  
Protein Content ◽  
Milk Production ◽  
Milk Yield ◽  
Fat Content ◽  
Solid Content ◽  
Production Traits ◽  
Milk Production Traits ◽  
Fatty Acid Binding ◽  
Exon 2 ◽  
Single Stranded Conformational Polymorphism

Abstract. The aim of this study was to estimate the effect of variation in the fatty acid binding protein 4 gene (FABP4) on milk production traits in Greek Sfakia sheep. Polymerase chain reaction – single-stranded conformational polymorphism (PCR-SSCP) analysis was used to genotype a total of 374 Sfakia ewes for two regions of FABP4 located around exon 2–intron 2 (Region 1) and exon 3–intron 3 (Region 2). Each month, for a period of 6 months, milk samples were collected from the ewes to measure total milk yield, fat content, protein content, lactose content, non-fat solid content, pH, and somatic cell count (SCC). A general linear model was used to test the association between the variation observed in FABP4 and milk production traits. Four gene variants (A1–A4) were found in Region 1 and two variants (C1–C2) were found in Region 2. In the first region, the FABP4 genotype significantly affected (P<0.05) non-fat solid levels, fat content, and SCC. The presence of the A2 variant was significantly associated (P<0.05) with decreased SCC, while the presence of A4 was significantly associated with decreased milk yield (P<0.01), increased non-fat solid content (P<0.05), decreased fat content (P<0.01), increased lactose content (P<0.05), and increased pH (P<0.05). In the second region, FABP4 genotype had an effect (P<0.05) on protein content and the presence of the C2 variant was associated (P<0.05) with increased protein content, decreased SCC, and lower pH. The results suggest an association between variation in ovine FABP4 and milk production traits in Greek Sfakia sheep. Nevertheless, further analyses in independent sheep populations of increased size will strengthen these findings.

scholarly journals Einfluss systematischer Umwelteffekte auf die Milchleistungsmerkmale bei Bunten Deutschen Edelziegen

2004 ◽  
Vol 47 (3) ◽  
pp. 275-285
Author(s):  
D. Bömkes ◽  
H. Hamann ◽  
O. Distl
Keyword(s):  
Somatic Cell ◽  
Protein Content ◽  
Milk Yield ◽  
Significant Influence ◽  
Milk Fat ◽  
Fixed Effects ◽  
Fat Content ◽  
Protein Yield ◽  
Production Traits ◽  
Milk Traits

Abstract. Title of the paper: Influence of systematic environmental effects on milk performance traits in German Improved Fawn The objectives of this study were to analyse the influence of fixed effects on milk traits of German Improved Fawn. The analysis was based on 27,778 test day records of 1,848 German Improved Fawn with 3,574 lactation records. The milk records were sampled between 1988 and 2002 from 229 flocks in Lower Saxony, Saxony and Baden-Wuerttemberg. The average daily milk yield was 2.87 ± 1.20 kg with a fat content of 3.08 ± 0.54% and a protein content of 3.38 ± 0.95%. Somatic cell count (SCC) was transformed into somatic cell score (SCS). Mean SCS was 5.49 ± 1.93. The average lactation length was 234.1 ± 76.4 days. The analysis of variance showed a significant influence of lactation number, stage of lactation, year of lambing and month of lambing on all analysed milk production traits. Milk yield was highest in the fourth lactation number and fat as well as protein content in the 7th to 13th lactation number. Litter size had a significant influence on milk and fat yield and on fat and protein content. The region significantly influenced protein yield and fat and protein content of German Improved Fawn but had no effect on milk and protein yield and SCS. Animals from Baden-Wuerttemberg reached the highest milk protein content but the lowest milk fat content.

Polymorphisms of kappa-casein gene and their effects on milk production traits in Holstein, Jersey and Brown Swiss cattle

2018 ◽  
Vol 58 (5) ◽  
pp. 778 ◽  
Author(s):  
Murad Gurses ◽  
Huseyin Yuce ◽  
Ebru Onalan Etem ◽  
Bahri Patir
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Gene Polymorphisms ◽  
Fragment Length Polymorphism ◽  
Fat Content ◽  
Production Traits ◽  
Milk Production Traits ◽  
Brown Swiss ◽  
Milk Samples ◽  
General Linear Model Procedure

The objectives of this study were to detect kappa-casein (κ-CN, CSN3, CASK) gene polymorphisms and to investigate the association between the κ-CN gene polymorphisms and milk yield and composition in cattle. For this purpose, a total of 365 blood and milk samples were collected from Holstein, Jersey and Brown Swiss cows. Polymorphisms of κ-CN gene were detected by the PCR and restriction fragment length polymorphism. A 776-bp fragment of exon IV was amplified by PCR and digested with HindIII and HaeIII restriction endonuclease to distinguish allele A, B and E. The analysis of associations between κ-CN genotypes and milk yield and composition were conducted with the use of the general linear model procedure. As a result, allele frequencies were detected as 0.736, 0.357, 0.308 for A allele, 0.186, 0.643, 0.692 for B allele in Holstein, Brown Swiss and Jersey breeds, respectively, and 0.079 for E allele in Holstein. This study also demonstrated the presence of E allele in Turkish Holstein. Although κ-CN genotypes were associated with protein and solids-not-fat content of milk in Hostein and Brown Swiss, they were associated with milk fat content in Jerseys (P < 0.05).

scholarly journals Sequence Variations in the Bovine Growth Hormone Gene Characterized by Single-Strand Conformation Polymorphism (SSCP) Analysis and Their Association with Milk Production Traits in Holsteins

Genetics ◽  
1996 ◽  
Vol 144 (4) ◽  
pp. 1809-1816 ◽  
Author(s):  
Jianbo Yao ◽  
Samuel E Aggrey ◽  
David Zadworny ◽  
J Flan Hayes ◽  
Urs Kühnlein
Keyword(s):  
Growth Hormone ◽  
Milk Production ◽  
Milk Yield ◽  
Single Strand Conformation Polymorphism ◽  
Sscp Analysis ◽  
Bovine Growth Hormone ◽  
Production Traits ◽  
Milk Production Traits ◽  
Sequence Variations ◽  
Conformation Polymorphism

Sequence variations in the bovine growth hormone (GH) gene were investigated by single strand conformation polymorphism (SSCP) analysis of seven amplified fragments covering almost the entire gene (2.7 kb). SSCPs were detected in four of these fragments and a total of six polymorphisms were found in a sample of 128 Holstein bulls. Two polymorphisms, a T→C transition in the third intron (designated GH4.1) and an A→C transversion in the fifth exon (designated GH6.2), were shown to be associated with milk production traits. GH4.1c/GH4.1c bulls had higher milk yield than GH4.1c/GH4.1t (P ≤ 0.005) and GH4.1t/GH4.1t (P ≤ 0.0022) bulls. GH4.1c/GH4.1c bulls had higher kg fat (P ≤ 0.0076) and protein (P ≤ 0.0018) than GH4.1c/GH4.1t bulls. Similar effects on milk production traits with the GH6.2 polymorphism were observed with the GH6.2a allele being the favorable allele. The average effects of the gene substitution for GH4.1 and GH6.2 are similar, with ±300 kg for milk yield, ±8 kg for fat content and ±7 kg for protein content per lactation. The positive association of GH4.1c and GH6.2a with milk production traits may be useful for improving milk performance in dairy cattle.

scholarly journals The relevance of milk protein polymorphisms for dairy cattle breeding.

1993 ◽  
Vol 1993 ◽  
pp. 46-46
Author(s):  
Henk Bovenhuis
Keyword(s):  
Genetic Variants ◽  
Milk Protein ◽  
Production Traits ◽  
Milk Production Traits ◽  
Breeding Scheme ◽  
Cattle Breeding ◽  
Dairy Cattle Breeding ◽  
Nucleus Breeding ◽  
Selection For ◽  
Β Lactoglobulin

Several studies have shown milk protein genetic variants to be associated with manufacturing properties of milk. The main findings were that κ-casein genetic variants affect renneting time of milk and βlactoglobulin genetic variants are associated with casein number (reviewed by Grosclaude, 1988). There are reports also of associations between milk protein genetic variants and milk production traits. Results from these studies indicate that κ-casein genotypes are associated with protein content and βlactoglobulin genotypes are related to fat content (reviewed by Bovenhuis et al., 1992). Therefore, κ-casein and βlactoglobulin genotypes might be of value as selection criteria. The aim of the present study was to quantify the potential effects of selection for κ-casein and β-lactoglobulin genotypes by using stochastic simulation of a closed adult MOET nucleus breeding scheme.

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&nbsp;454, except for locomotion, for which 53 424 animals were recorded. The numbers of animals with records of&nbsp;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 &plusmn; 0.04), while the strongest negative correlation estimated was between body condition score and fat yield (&minus;0.45 &plusmn; 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 &minus;0.17), while the strongest positive phenotypic correlations were estimated between milk yield, protein yield, and udder width (both 0.32). &nbsp;

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.

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