Comparison of genetic evaluations for milk yield and fat yield using a polygenic model and three genomic–polygenic models with different sets of SNP genotypes in Thai multibreed dairy cattle

2015 ◽  
Vol 181 ◽  
pp. 58-64 ◽  
Author(s):  
Danai Jattawa ◽  
Mauricio A. Elzo ◽  
Skorn Koonawootrittriron ◽  
Thanathip Suwanasopee
Keyword(s):  
Dairy Cattle ◽  
Milk Yield ◽  
Polygenic Model ◽  
Fat Yield ◽  
Genetic Evaluations

COMPARATIVE DESCRIPTION OF MILK PRODUCTIVITY OF COWS UKRAINIAN RED-AND-WHITE DAIRY CATTLE AND UKRAINIAN BLACK-AND-WHITE DAIRY CATTLE AND HOLSTEIN BREEDS IN SERF «OLEKSANDRIVSKE»

2016 ◽  
Vol 52 ◽  
pp. 6-12 ◽  
Author(s):  
M. V. Gladiy ◽  
G. S. Kovalenko ◽  
S. V. Priyma ◽  
G. A. Holyosa ◽  
A. V. Tuchyk ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Dairy Cows ◽  
Milk Yield ◽  
Fat Content ◽  
Holstein Cows ◽  
Milk Productivity ◽  
Black And White ◽  
The Third ◽  
Fat Yield ◽  
Selection Of

The main goal of dairy breeds selection should be improving breeding and productive qualities of animals under modern conditions. The majority of farms, using native breeds to produce milk, has created optimal conditions for keeping and feeding, selection and matching, growing of replacements etc. Further improvement of created native dairy breeds for economically useful traits occurs at total use of purebred Holstein bulls (semen) of foreign selection. In order to realistically assess milk productivity (milk yield, fat content in milk and fat yield) of Ukrainian Black-and-White and Red-and-White Dairy cows should be conducted a comparative analysis of Holstein cows under the same conditions of feeding and keeping. It was established that Ukrainian Red-and-White Dairy cows were characterized by the highest milk yields for 305 days of all lactations, taken into account, the among three investigated breeds. Their milk yield during the first lactation was 5933 kg of milk, during the second – 6393 kg, the third – 6391 kg and during higher lactation – 6650 kg. Ukrainian Black-and-White Dairy cows were second by milk yield (except for the second lactation), during the first lactation – 5932 kg of milk, the third – 6462 kg and higher – 6541 kg, and Holstein cows were third, during the first lactation – 5794 kg of milk, the second – 6381 kg, the third – 6335 kg and higher – 6469 kg. The fat content was almost the same and varied within 3.49-3.58% in milk of Ukrainian Red-and-White Dairy cattle, 3.50-3.60% in milk of Ukrainian Black-and-White Dairy cattle and 3.50-3.56% in Holsteins’ milk. The difference between the breeds was within 0.01-0.04%. All the investigated breeds had predominance in fat yield for three lactations over standards of these breeds: Ukrainian Red-and-White Dairy cows from 75.1 to 93.4 kg, Ukrainian Black-and-White Dairy cows – 75.1-89.0 kg respectively and Holstein cows – 41.9-60.2 kg. It was found different level of positive correlation between milk yield and fat yield in all the cases and high correlation (r = 0.604-0.921, P < 0.001) in five cases (41.7%) Negative correlation coefficients indicate that selection of animals to higher milk yield in the herd will decrease the second trait – fat content in milk. Positive and highly significant correlation between milk yield and fat yield indicates that selection of cows in the herd to higher milk yields will increase fat yield. It was revealed that bulls were among the factors impacted the milk productivity (milk yield, fat content, fat yield) of three investigated breeds. So, the force (η²x) of father’s impact on milk yield was15.4-47.9%, fat content – 22.0-43.4% and fat yield – 14.9-47.7% taking into account a lactation and a breed. The force of lines impact (η²x) was second; it was on milk yield 6.1-24.5%, fat content – 4.1-17.1 and fat yield – 5.8-23.5%. The force of breeds impact (η²x) was last; it was on milk yield 0.3-2.9%, fat content – 0.2-0.3% and fat yield – 0.6-2.7%. So, the comparative studies of milk productivity of Ukrainian Red-and-White and Black-and-White Dairy cattle with Holsteins indicate that under similar conditions of feeding and keeping, these native breeds can compete with Holstein cattle. The milk yield for 305 days of higher lactation was 6650 kg of milk in Ukrainian Red-and-White Dairy cows, 6541 kg in Ukrainian Black-and-White Dairy cows and 6469 kg in Holsteins. It was found the inverse correlation r = -0.025-0.316 between milk yield and fat content in milk in most cases. Selection and matching of animals in the herd should be carried out simultaneously on these traits. It was found positive repeatability of milk yields between the first and second, the third and higher lactations (rs = 0.036-0.741), indicating the reliability of forecasting increase in milk productivity during the next lactations in all herd. Bulls have the greatest impact (η²x) on milk productivity among the factors taken into account: milk yield – 15.4-47.9%, fat content in milk – 22.0-43.4% and fat yield – 14.9-47.7%.

scholarly journals Inclusion of bioclimatic variables in genetic evaluations of dairy cattle

2021 ◽  
Vol 34 (2) ◽  
pp. 163-171 ◽  
Author(s):  
Renata Negri ◽  
Ignacio Aguilar ◽  
Giovani Luis Feltes ◽  
Juliana Dementshuk Machado ◽  
José Braccini Neto ◽  
...  
Keyword(s):  
Heat Stress ◽  
Dairy Cattle ◽  
Milk Yield ◽  
Fixed Effects ◽  
Information Criterion ◽  
Least Square ◽  
Random Regression ◽  
Yield Losses ◽  
Bioclimatic Variables ◽  
Genetic Evaluations

Objective: Considering the importance of dairy farming and the negative effects of heat stress, more tolerant genotypes need to be identified. The objective of this study was to investigate the effect of heat stress via temperature-humidity index (THI) and diurnal temperature variation (DTV) in the genetic evaluations for daily milk yield of Holstein dairy cattle, using random regression models.Methods: The data comprised 94,549 test-day records of 11,294 first parity Holstein cows from Brazil, collected from 1997 to 2013, and bioclimatic data (THI and DTV) from 18 weather stations. Least square linear regression models were used to determine the THI and DTV thresholds for milk yield losses caused by heat stress. In addition to the standard model (SM, without bioclimatic variables), THI and DTV were combined in various ways and tested for different days, totaling 41 models.Results: The THI and DTV thresholds for milk yield losses was THI = 74 (–0.106 kg/d/THI) and DTV = 13 (–0.045 kg/d/DTV). The model that included THI and DTV as fixed effects, considering the two-day average, presented better fit (–2logL, Akaike information criterion, and Bayesian information criterion). The estimated breeding values (EBVs) and the reliabilities of the EBVs improved when using this model.Conclusion: Sires are re-ranking when heat stress indicators are included in the model. Genetic evaluation using the mean of two days of THI and DTV as fixed effect, improved EBVs and EBVs reliability.

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.

scholarly journals Short-Term Adaptation of Dairy Cattle Production Parameters to Individualized Changes in Dietary Top Dress

Animals ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 3518
Author(s):  
Tanner P. Price ◽  
Vinícius C. Souza ◽  
Douglas M. Liebe ◽  
Mark D. Elett ◽  
Ty C. Davis ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Response Time ◽  
Milk Yield ◽  
Milk Fat ◽  
Diet Composition ◽  
Time Frame ◽  
Short Term ◽  
Production Parameters ◽  
Fat Yield ◽  
Feeding Systems

Immediate and short-term changes in diet composition can support individualized, real-time interventions in precision dairy production systems, and might increase feed efficiency (FE) of dairy cattle in the short-term. The objective of this study was to determine immediate and short-term effects of changes in diet composition on production parameters of dairy cattle fed varying amounts of top dressed commodities. A 4 × 4 replicated Latin square design was used to evaluate responses of twenty-four Holstein cows fed either no top dress (Control) or increasing amounts of: corn grain (CG), soybean meal (SBM), or chopped mixed grass hay (GH) top dressed on a total mixed ration (TMR) over four, 9-day periods. Throughout each period, top dressed commodities were incrementally increased, providing 0% to 20% of calculated net energy of lactation (NEL) intake. Measured production responses were analyzed for each 9-d period using a mixed-effects model considering two different time ranges. Samples collected from d 3 and 4 and from d 7 and 8 of each period were averaged and used to reflect “immediate” vs. “short-term” responses, respectively. In the immediate response time frame, control fed cows had lower milk yield, milk fat yield, and milk true protein yield than CG and SBM supplemented animals but similar responses to GH supplemented animals. Milk fat and protein percentages were not affected by top dress type in the immediate term. In the short-term response time-frame, GH supplemented animals had lower DMI and milk fat yield than all other groups. Control and GH supplemented cows had lower milk yield than CG and SBM fed cows. In the immediate response time frame, FE of SBM supplemented cows was superior to other groups. In the short-term time frame, FE of GH and SBM groups was improved over the control group. Results suggest that lactating dairy cows show rapid performance responses to small (<20% NEL) changes in dietary composition, which may be leveraged within automated precision feeding systems to optimize efficiency of production. Before this potential can be realized, further research is needed to examine integration of such strategies into automatic feeding systems and downstream impacts on individual animal FE and farm profitability.

CORRELATIONS BETWEEN ADJACENT TEST DAYS FOR FAT PERCENT, FAT YIELD AND MILK YIELD

1988 ◽  
Vol 68 (1) ◽  
pp. 295-298 ◽  
Author(s):  
A. J. LEE
Keyword(s):  
Dairy Cattle ◽  
Key Words ◽  
Milk Yield ◽  
Milk Fat ◽  
Early Lactation ◽  
Stage Of Lactation ◽  
Fat Yield

Retest data from the Record of Performance for dairy cattle were used to examine the day-to-day and month-to-month variation in fat percent, fat yield and milk yield and the effect of stage of lactation on this variation. The overall correlation between fat percent on successive days (retest day) was low (0.71) in Holsteins compared to that for fat yield (0.85) and milk yield (0.96). Correlations between values on either test day or retest day with those on the next test day (1 mo later) were 88–90% of those between successive day values for milk yield and fat yield but only 73% for fat percent. Correlations of fat percent on the next test day with those on the original or retest day were particularly low (< 0.40) for the first 60 d in milk. Fat percent is much more variable from day to day and from test day to test day than milk yield or fat yield, particularly in early lactation. Key words: Dairy, test-day, correlations, milk, fat

scholarly journals Mapping and analysis of dairy cattle quantitative trait loci by maximum likelihood methodology using milk protein genes as genetic markers.

Genetics ◽  
1994 ◽  
Vol 137 (1) ◽  
pp. 267-280 ◽  
Author(s):  
H Bovenhuis ◽  
J I Weller
Keyword(s):  
Maximum Likelihood ◽  
Dairy Cattle ◽  
Milk Yield ◽  
Quantitative Trait ◽  
Milk Protein ◽  
Direct Effects ◽  
Milk Protein Genes ◽  
Beta Casein ◽  
Fat Yield ◽  
Beta Lactoglobulin

Abstract Maximum likelihood methodology was used to estimate effects of both a marker gene and a linked quantitative trait locus (QTL) on quantitative traits in a segregating population. Two alleles were assumed for the QTL. In addition to the effects of genotypes at both loci on the mean of the quantitative trait, recombination frequency between the loci, frequency of the QTL alleles and the residual standard deviation were also estimated. Thus six parameters were estimated in addition to the marker genotype means. The statistical model was tested on simulated data, and used to estimate direct and linked effects of the milk protein genes, beta-lactoglobulin, kappa-casein, and beta-casein, on milk, fat, and protein production and fat and protein percent in the Dutch dairy cattle population. beta-Lactoglobulin had significant direct effects on milk yield and fat percent. kappa-Casein had significant direct effects on milk yield, protein percent and fat yield. beta-Casein had significant direct effects on milk yield, fat and protein percent and fat and protein yield. Linked QTL with significant effects on fat percent were found for kappa-casein and beta-casein. Since the beta-casein and kappa-casein genes are closely linked, it is likely that the same QTL was detected for those two markers. Further, a QTL with a significant effect on fat yield was found to be linked to kappa-casein and a QTL with a significant effect on protein yield was linked to beta-lactoglobulin.

scholarly journals An investigation into heterogeneity of variance for milk and fat yields of Holstein cows in Brazilian herd environments

1999 ◽  
Vol 22 (3) ◽  
pp. 375-381 ◽  
Author(s):  
Claudio Napolis Costa
Keyword(s):  
Milk Yield ◽  
Genetic Correlations ◽  
Selection Response ◽  
Holstein Cows ◽  
Correlated Response ◽  
Heterogeneity Of Variance ◽  
Phenotypic Standard Deviation ◽  
Fat Yield ◽  
Genetic Evaluations ◽  
Residual Variances

Heterogeneity of variance in Brazilian herd environments was studied using first-lactation 305-day mature equivalent (ME) milk and fat records of Holstein cows. Herds were divided into two categories, according to low or high herd-year phenotypic standard deviation for ME milk (HYSD). There were 330 sires with daughter records in both HYSD categories. Components of (co)variance, heritability, and genetic correlations for milk and fat yields were estimated using a sire model from bivariate analyses with a restricted maximum likelihood (REML) derivative-free algorithm. Sire and residual variances for milk yield in low HYSD herds were 79 and 57% of those obtained in high HYSD herd. For fat yield they were 67 and 60%, respectively. Heritabilities for milk and fat yields in low HYSD herds were larger (0.30 and 0.22) than in high HYSD herds (0.23 and 0.20). Genetic correlation between expression in low and high HYSD herds was 0.997 for milk yield and 0.985 for fat yield. Expected correlated response in low HYSD herds based on sires selected on half-sister information from high HYSD was 0.89 kg/kg for milk and 0.80 kg/kg for fat yield. Genetic evaluations in Brazil need to account for heterogeneity of variances to increase the accuracy of evaluations and the selection efficiency for milk and fat yields of Holstein cows. Selection response will be lower in low variance herds than in high variance herds because of reduced differences in daughter response and among breeding values of sires in low HYSD herds. Genetic investments in sire selection to improve production are more likely to be successful in high HYSD herds than in low HYSD Brazilian herds.

scholarly journals Accuracy of Genomic-Polygenic and Polygenic Breeding Values for Age at First Calving and Milk Yield in Thai Multibreed Dairy Cattle

2019 ◽  
Vol 19 (3) ◽  
pp. 633-645
Author(s):  
Tawirat Konkruea ◽  
Skorn Koonawootrittriron ◽  
Mauricio A. Elzo ◽  
Thanathip Suwanasopee
Keyword(s):  
Dairy Cattle ◽  
Milk Yield ◽  
Genomic Prediction ◽  
Variance Components ◽  
Fixed Effects ◽  
Genetic Parameters ◽  
Additive Genetic Variance ◽  
Economic Traits ◽  
Age At First Calving ◽  
Polygenic Model

AbstractSingle-nucleotide polymorphisms (SNPs) have been used in genomic prediction and shown to increase prediction accuracy and selection responses for economic traits in dairy cattle. The successful report in genomic prediction for improving age at first calving (AFC) and 305-d milk yield (MY) in multibreed dairy population is limited. Therefore, the objective of this research was to compare estimates of variance components, genetic parameters, and prediction accuracies for AFC and MY using a genomic-polygenic model (GPM) and a polygenic model (PM). The AFC and MY records of 9,106 first-lactating multibreed dairy cows, calved between 1991 and 2014, were collected from 1,012 Thai dairy farms. The SNP genotyped individuals were selected from cows that had completed pedigree and phenotypes information. The total genomic DNA samples of 2,661 dairy cattle were genotyped using various GeneSeek Genomic Profiler low-density bead chips (9K, 20K, and 80K). The 2-trait GPM and PM contained herd-year-season and heterosis as fixed effects, and animal additive genetic and residual as random effects. Variance components and genetic parameters were estimated using the procedure of average information-restricted maximum likelihood (AI-REML). Estimates of additive genetic variance components and heritabilities from GPM were higher than PM for AFC and MY. Correlations between AFC and MY were near zero for both models. Mean EBV accuracies were higher for GPM (32.95% for AFC and 38.24% for MY) than for PM (32.65% for AFC, and 32.99% for MY). Mean sire EBV accuracies were higher for GPM (31.35% for AFC and 36.25% for MY) than for PM (28.37% for AFC and 28.80% for MY). Thus, the GPM should be considered the model of choice to increase accuracy of genetic predictions for AFC and MY in the Thai multibreed dairy population.

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