scholarly journals The effectiveness of genomic selection for milk production traits of Holstein dairy cattle

2020 ◽  
Vol 33 (3) ◽  
pp. 382-389 ◽  
Author(s):  
Yun-Mi Lee ◽  
Chang-Gwon Dang ◽  
Mohammad Z. Alam ◽  
You-Sam Kim ◽  
Kwang-Hyeon Cho ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Milk Production ◽  
Genetic Gain ◽  
Milk Fat ◽  
Breeding Value ◽  
Production Traits ◽  
Milk Production Traits ◽  
Data Set ◽  
Selection For ◽  
Estimated Breeding Value

Objective: This study was conducted to test the efficiency of genomic selection for milk production traits in a Korean Holstein cattle population.Methods: A total of 506,481 milk production records from 293,855 animals (2,090 heads with single nucleotide polymorphism information) were used to estimate breeding value by single step best linear unbiased prediction.Results: The heritability estimates for milk, fat, and protein yields in the first parity were 0.28, 0.26, and 0.23, respectively. As the parity increased, the heritability decreased for all milk production traits. The estimated generation intervals of sire for the production of bulls (L<sub>SB</sub>) and that for the production of cows (L<sub>SC</sub>) were 7.9 and 8.1 years, respectively, and the estimated generation intervals of dams for the production of bulls (L<sub>DB</sub>) and cows (L<sub>DC</sub>) were 4.9 and 4.2 years, respectively. In the overall data set, the reliability of genomic estimated breeding value (GEBV) increased by 9% on average over that of estimated breeding value (EBV), and increased by 7% in cows with test records, about 4% in bulls with progeny records, and 13% in heifers without test records. The difference in the reliability between GEBV and EBV was especially significant for the data from young bulls, i.e. 17% on average for milk (39% vs 22%), fat (39% vs 22%), and protein (37% vs 22%) yields, respectively. When selected for the milk yield using GEBV, the genetic gain increased about 7.1% over the gain with the EBV in the cows with test records, and by 2.9% in bulls with progeny records, while the genetic gain increased by about 24.2% in heifers without test records and by 35% in young bulls without progeny records.Conclusion: More genetic gains can be expected through the use of GEBV than EBV, and genomic selection was more effective in the selection of young bulls and heifers without test records.

scholarly journals Effect of DGAT1, BTN1A1, OLR1, and STAT1 genes on milk production and reproduction traits in the Czech Fleckvieh breed

2014 ◽  
Vol 59 (No. 2) ◽  
pp. 45-53 ◽  
Author(s):  
J. Rychtářová ◽  
Z. Sztankóová ◽  
J. Kyselová ◽  
V. Zink ◽  
M. Štípková ◽  
...  
Keyword(s):  
Milk Production ◽  
Low Density Lipoprotein ◽  
Density Lipoprotein ◽  
Breeding Value ◽  
Production Traits ◽  
Milk Production Traits ◽  
Heterogeneous Effects ◽  
Reproduction Traits ◽  
Estimated Breeding Value ◽  
The Impact

The impact of polymorphism of the diacylglycerol acyltransferase (DGAT1), butyrophilin (BTN1A1), oxidized low-density lipoprotein receptor (OLR1), and signal transducer and activator of transcription 1 (STAT1) genes on milk production and reproduction traits in 419 Czech Fleckvieh cows was examined using polymerase chain reaction and restriction fragment length polymorphism. The loci DGAT1 and BTN1A1 were observed simultaneously to affect milk production, estimated breeding value of milk production traits, as well as reproduction parameters. Significant differences were found also between genotypes of the STAT1 loci in relation to estimated breeding value of milk production traits. Similar findings in pure dairy breeds suggest that heterogeneous effects of the observed loci can be explained by different genetic backgrounds in various breed populations selected to achieve different commercial goals. Thus, it is necessary to determine variability and influence of a molecular marker in a specific population when considering its inclusion into a breeding programme. &nbsp;

scholarly journals Genomic Selection for Milk Production Traits in Xinjiang Brown Cattle

Animals ◽  
2022 ◽  
Vol 12 (2) ◽  
pp. 136
Author(s):  
Menghua Zhang ◽  
Hanpeng Luo ◽  
Lei Xu ◽  
Yuangang Shi ◽  
Jinghang Zhou ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Bayesian Methods ◽  
Breeding Value ◽  
Production Traits ◽  
Milk Production Traits ◽  
Linear Unbiased Prediction ◽  
Brown Cattle ◽  
Best Linear Unbiased ◽  
Estimated Breeding Value ◽  
Better Than

One-step genomic selection is a method for improving the reliability of the breeding value estimation. This study aimed to compare the reliability of pedigree-based best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP), single-trait and multitrait models, and the restricted maximum likelihood (REML) and Bayesian methods. Data were collected from the production performance records of 2207 Xinjiang Brown cattle in Xinjiang from 1983 to 2018. A cross test was designed to calculate the genetic parameters and reliability of the breeding value of 305 daily milk yield (305 dMY), milk fat yield (MFY), milk protein yield (MPY), and somatic cell score (SCS) of Xinjiang Brown cattle. The heritability of 305 dMY, MFY, MPY, and SCS estimated using the REML and Bayesian multitrait models was approximately 0.39 (0.02), 0.40 (0.03), 0.49 (0.02), and 0.07 (0.02), respectively. The heritability and estimated breeding value (EBV) and the reliability of milk production traits of these cattle calculated based on PBLUP and ssGBLUP using the multitrait model REML and Bayesian methods were higher than those of the single-trait model REML method; the ssGBLUP method was significantly better than the PBLUP method. The reliability of the estimated breeding value can be improved from 0.9% to 3.6%, and the reliability of the genomic estimated breeding value (GEBV) for the genotyped population can reach 83%. Therefore, the genetic evaluation of the multitrait model is better than that of the single-trait model. Thus, genomic selection can be applied to small population varieties such as Xinjiang Brown cattle, in improving the reliability of the genomic estimated breeding value.

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.

Association of the Leu127 variant of the bovine growth hormone (bGH) gene with increased yield of milk, fat, and protein in Australian Holstein-Friesians

2000 ◽  
Vol 51 (4) ◽  
pp. 515 ◽  
Author(s):  
M. R. Shariflou ◽  
C. Moran ◽  
F. W. Nicholas
Keyword(s):  
Growth Hormone ◽  
Milk Production ◽  
Milk Fat ◽  
Bovine Growth Hormone ◽  
Data Sets ◽  
Production Traits ◽  
Milk Production Traits ◽  
Maximum Benefit ◽  
Pcr Products ◽  
Trait Locus

The occurrence of the Leu127/Val127 variants of the bovine growth hormone (bGH) gene and their effect on milk production traits was investigated in Australian Holstein-Friesian cattle. Animals were genotyped for the Leu127/Val127 variants, with RFLP methodology, using PCR and AluI digestion of PCR products (AluI-RFLP). Alleles Leu127 and Val127 occurred with frequencies of 82% and 18%, respectively. The quantitative effect of this polymorphic site on milk-production traits was estimated from lactation data and test-day data. Results from the 2 data sets consistently showed that the Leu127 allele is associated with higher production of milk, fat, and protein and is dominant to Val127. The average effects of the gene substitution are 95 L for milk yield, 7 kg for fat yield, and 3 kg for protein yield per lactation. This locus may be directly responsible for quantitative variation or it may be a marker for a closely linked quantitative trait locus (QTL) for milk-production traits in Australian dairy cattle. In either case, it will be useful as an aid to selection for improvement of milk production traits. As the Leu127 allele is dominant, selection of AI sires homozygous for the Leu127 allele (Leu127/Leu127) will result in maximum benefit without the need for genotyping cows.

Season and reproductive status rather than genetic factors influence change in ewe weight and fat over time. 4. Genetic relationships of ewe weight and fat score with fleece, reproduction and milk traits

2016 ◽  
Vol 56 (4) ◽  
pp. 708 ◽  
Author(s):  
S. F. Walkom ◽  
F. D. Brien ◽  
M. L. Hebart ◽  
N. M. Fogarty ◽  
S. Hatcher ◽  
...  
Keyword(s):  
Milk Production ◽  
Milk Fat ◽  
Genetic Relationships ◽  
Fibre Diameter ◽  
Reproductive Traits ◽  
Production Cycle ◽  
Production Traits ◽  
Milk Production Traits ◽  
Milk Traits ◽  
Fat Score

The profitability of a sheep enterprise is greatly influenced by the ability of the ewe to produce a lamb annually. This paper examines the between- and within-breed association between the liveweight and fat score of the adult ewe and key fleece, reproduction and milk production traits. The study analysed the performance of 2846 first-cross Merino and Corriedale ewes from the maternal central progeny test (MCPT) over their first three production cycles. Breed (9 sire breeds) and within-breed (91 sires) correlations were calculated from bivariate correlations of adult liveweight and fat score with fleece, reproduction and milk production traits. The mean liveweight and fatness of the breeds were low to moderately negatively correlated with greasy fleece weight (–0.55 and –0.25, respectively) and moderate to strongly positively correlated with fibre diameter (0.88 and 0.41, respectively). However, the within-breed correlations were generally low to negligible. The genetic relationships between ewe fat score and reproductive traits at the breed and within-breed level was generally low to negligible and, in some cases, negative under production conditions where the ewes were well managed and averaged a fat score of 3.5 pre-joining and became too fat across the production cycle. Strong breed correlations between ewe fat score and milk fat concentration (0.88) suggest that selection of fatter sire breeds will lead to increased fat in their progenies’ milk, which was associated with larger lambs. The potential advantages of selecting for more fat to improve the maternal performance of the ewe seem to be limited in enterprises where the production system can easily be adjusted to restrict the influence of temporary and long-term feed deficiencies, as was achieved within the MCPT research flocks.

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.

scholarly journals L-selectin gene polymorphism and its association with clinical mastitis, somatic cell score, and milk production in Polish Holstein-Friesian cattle

2018 ◽  
Vol 63 (No. 7) ◽  
pp. 256-262 ◽  
Author(s):  
M. Dusza ◽  
J. Pokorska ◽  
J. Makulska ◽  
D. Kulaj ◽  
M. Cupial
Keyword(s):  
Somatic Cell ◽  
Milk Production ◽  
Milk Fat ◽  
Bacterial Infections ◽  
Clinical Mastitis ◽  
Somatic Cell Score ◽  
Production Traits ◽  
Milk Production Traits ◽  
Holstein Friesian ◽  
Friesian Cows

Bovine mastitis is a widespread disease of the mammary gland, highly contributing to the increase in veterinary costs in dairy industry. In the present study, the genetic polymorphism within bovine L-selectin gene was analysed and its impact on clinical mastitis occurrence, somatic cell score (SCS), and milk production traits in Polish Holstein-Friesian cows was examined. Polymorphism within L-selectin gene, molecule responsible for neutrophil attachment to endothelium, might have a potential role in immune response to bacterial infections and udder health. Two hundred and six Polish Holstein-Friesian cows were genotyped by polymerase chain reaction-restriction fragment length polymorphism method. Two single nucleotide polymorphisms mutations within the coding sequence of L-selectin gene were identified (c.165G&gt;A and c.567C&gt;T). The effect of c.165G&gt;A and c.567C&gt;T mutations on SCS was highly significant (P = 0.0019 and P = 0.0003, respectively). Strong associations (P ≤ 0.0001) were also observed between L-selectin polymorphism and milk production traits (milk yield, milk fat percentage, and milk protein percentage). However, the polymorphism in the analysed gene had no influence on the resistance or susceptibility of cows to clinical mastitis (only the tendency toward significance, P = 0.06 for c.567C&gt;T mutation was found). Potential exploitation of the information on the identified associations in genetic selection needs to confirm the obtained results in further investigations.

Linear and threshold model genetic parameters for disease, fertility and milk production in dairy cattle

2000 ◽  
Vol 71 (3) ◽  
pp. 411-419 ◽  
Author(s):  
H. N. Kadarmideen ◽  
R. Thompson ◽  
G. Simm
Keyword(s):  
Dairy Cattle ◽  
Milk Production ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
Threshold Model ◽  
Production Traits ◽  
Milk Production Traits ◽  
Model Framework ◽  
Data Set ◽  
Fertility Traits

AbstractThis study provides estimates of genetic parameters for various diseases, fertility and 305-day milk production traits in dairy cattle using data from a UK national milk recording scheme. The data set consisted of 63891 multiple lactation records on diseases (mastitis, lameness, milk fever, ketosis and tetany), fertility traits (calving interval, conception to first service, number of services for a conception, and number of days to first service), dystocia and 305-day milk, fat and protein yield. All traits were analysed by multi-trait repeatability linear animal models (LM). Binary diseases and fertility traits were further analysed by threshold sire models (TM). Both LM and TM analyses were based on the generalized linear mixed model framework. The LM included herd-year-season of calving (HYS), age at calving and parity as fixed effects and genetic, permanent environmental and residual effects as random. The TM analyses included the same effects as for LM, but HYS effects were treated as random to avoid convergence problems when HYS sub-classes had 0 or 100% incidence. Because HYS effects were treated as random, herd effects were fitted as fixed effects to account for effect of herds in the data. The LM estimates of heritability ranged from 0•389 to 0•399 for 305-day milk production traits, 0•010 to 0•029 for fertility traits and 0•004 to 0•038 for diseases. The LM estimates of repeatability ranged from 0•556 to 0•586 for 305-day milk production traits, 0•029 to 0•086 for fertility traits and 0•004 to 0•100 for diseases. The TM estimates of heritabilities and repeatabilities were greater than LM estimates for binary traits and were in the range 0•012 to 0•126 and 0•013 to 0•168, respectively. Genetic correlations between milk production traits and fertility and diseases were all unfavorable: they ranged from 0•07 to 0•37 for milk production and diseases, 0•31 to 0•54 for milk production and poor fertility and 0•06 to 0•41 for diseases and poor fertility. These results show that future selection programmes should include disease and fertility for genetic improvement of health and reproduction and for sustained economic growth in the dairy cattle industry.

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