Breeding Values For Milk Yield Research Articles

Эффективность определения племенной ценности быков-производителей в зависимости от метода оценки

The purpose of the study is to determine the effectiveness of various methods for assessing the bree-ding value of bulls in the dairy cattle population of the Omsk Region. Objectives: to compare the effectiveness of assessing the breeding value of stud bulls using the “assessment by quality of offspring” and BLUP methods; to determine the correlation between the breeding value of bulls and the level of productivity of offspring. The object of the study was 67 bulls who were the fathers of 926 cows that completed their first lactation. The breeding value assessment using the Daughters-Peers method was carried out for 15 stud bulls. Of the bulls assessed using the Daughters-Peers method, 9 bulls were improvers, which is 60 % of all animals tested using this method. Using the BLUP method, from all bulls, positive breeding value was identified in 12 bulls, which is 17.9 % of the total number of bulls. When assessed by the Daughters-Peers method, the maximum number of bulls (33.33 %) have a breeding value for milk yield of 301–450 kg. The results of the BLUP assessment showed that 4 bulls, or 33.33 %, had a breeding value of less than 150 kg. The share of bulls with a breeding value of more than 451 kg is 25 %. The probability of error when selecting bulls with the best breeding value in terms of milk production is higher when it is determined by the Daughters-Peers method by 34 % compared to the BLUP method. When selecting bulls based on milk fat content, the assessment of breeding value using the BLUP method is more effective. The accuracy of the method is 47.7 % higher than when assessing breeding value using the Daughters-Peers method. Assessment using the BLUP method objectively and relatively accurately makes it possible to determine the genetic potential of animal productivity and optimally use them in breeding work.

Comparative evaluation of the breeding value of Holstein bulls-producers

Modern dairy cattle breeding efficiency is largely determined by the strategy of choosing a producer for herd reproduction, which determines the growth rate of herd productivity for the next 3 to 5 years. According to the results of 2022, there are 20 organisations in the Sverdlovsk region with milk production per feed cow of more than 9 thousand kg, including 10 farms with milk production of more than 10 thousand kg. The best farm in the region, APC “Kilachevsky”, produced an average of 12829 kg of milk for each of 3000 cows. Two record-breaking cows were milked there, each of which yielded more than 21 tonnes of milk for a standard lactation. Thirty-four breeding bulls were included in the study. As a result of their evaluation, it was found that in bulls whose genomic breeding value for milk yield exceeded 1000 kg of milk 80.0% of producers were actual improvers for this trait, and in bulls with low genomic breeding value for milk yield (0-99 kg) only 25.0% of producers were actual improvers. Bulls with a negative breeding value for milk production in 66.6 percent of cases turned out to be actual improvers. In terms of protein content in milk, the dependence is similar, the higher the genomic value of the sire according to MDB, the more bulls actually have a positive effect on the protein-milk content of daughters (Tables 3,4). However, the number of sires that confirmed genomic breeding value for protein-milk yield is much less than for milk yield. For milk yield, 17 sires out of 34 (50.0%) received confirmation of breeding value, and for protein-milk yield only 11 (32.0%).

Random regression models using B-splines functions provide more accurate genomic breeding values for milk yield and lactation persistence in Murrah buffaloes.

There is a great worldwide demand for cheese made with buffalo milk, due to its flavour and nutritional properties. In this context, there is a need for increasing the efficiency of buffalo milk production (including lactation persistence), which can be achieved through genomic selection. The most used methods for the genetic evaluation of longitudinal data, such as milk-related traits, are based on random regression models (RRM). The choice of the best covariance functions and polynomial order for modelling the random effects is an important step to properly fit RRM. To our best knowledge, there are no studies evaluating the impact of the order and covariance function (Legendre polynomials-LEG and B-splines-BSP) used to fit RRM for genomic prediction of breeding values in dairy buffaloes. Therefore, the main objectives of this study were to estimate variance components and evaluate the performance of LEG and BSP functions of different orders on the predictive ability of genomic breeding values for the first three lactations of milk yield (MY1, MY2, and MY3) and lactation persistence (LP1, LP2, and LP3) of Brazilian Murrah. Twenty-two models for each lactation were contrasted based on goodness of fit, genetic parameter estimates, and predictive ability. Overall, the models of higher orders of LEG or BSP had a better performance based on the deviance information criterion (DIC). The daily heritability estimates ranged from 0.01 to 0.30 for MY1, 0.08 to 0.42 for MY2, and from 0.05 to 0.47 for MY3. For lactation persistence (LP), the heritability estimates ranged from 0.09 to 0.32 for LP1, from 0.15 to 0.33 for LP2, and from 0.06 to 0.32 for LP3. In general, the curves plotted for variance components and heritability estimates based on BSP models presented lower oscillation along the lactation trajectory. Similar predictive ability was observed among the models. Considering a balance between the complexity of the model, goodness of fit, and credibility of the results, RRM using quadratic B-splines functions based on four or five segments to model the systematic, additive genetic, and permanent environment curves provide better fit with no significant differences between genetic variances estimates, heritabilities, and predictive ability for the genomic evaluation of dairy buffaloes.

Genome-wide association study for milk production of Awassi sheep in Jordan

Genetic selection is an important method to enhance productive traits in local sheep through crossbreeding and selection programs. The objectives of this study were to estimate the genetic parameters of total milk yield (MY) and lactation period (LP), and to investigate the association between the estimated breeding values of milk yield with 50 K SNP chip results in Awassi sheep. Heritability and repeatability estimates were 0.19 and 0.317 for MY and 0.085 and 0.163 for LP, respectively. The Genomic scan covered 42,478 SNPs and revealed two candidate loci (s244475780.1 and s51470.1) that significantly affect milk production, located on Spermatogenesis-Associated Protein6 (SPATA6) and Galactose-3-O-Sulfotransferase 3 (GAL3ST3) genes. The genotype frequencies for the SPATA6 gene variant were 0.0566 for AA, 0.4528 for AG, and 0.4906 for AA, with allele frequency of 0.283 for A and 0.717 for G. The genotype frequencies for the GAL3ST3 gene variants were 0.07843 for TT, 0.4118 for TG, and 0.5098 for GG, with allele frequency of 0.284 for T and 0.716 for G. The two SNPs genotypes are promising biomarkers to increase milk production during genetic selection programs by reducing the frequency of G alleles in the two loci in Awassi sheep genome.

Jersey Irkı Sığırlarda Süt Verim Özellikleri, Fenotipik, Genetik ve Çevresel Yönelimlerin Belirlenmesi

This study was conducted to determine the effects of environmental factors on milk yield traits of Jersey breed cattle reared at the Karakoy State Farm located in Samsun Province of Turkey, as well as the phenotypic, genetic and environmental trends in relation to 305 day milk yield. The Wombat software was used to estimate heritability and breeding values for milk yield. The effects of parity, season and year factors on actual and 305 day milk yields were found to be statistically significant (P

Researching 100 t cows: An innovative approach to identify intrinsic cows factors associated with a high lifetime milk production

Longevity is an important trait both from an economic and social perspective. Modern dairy cows are criticized for their short productive lifespan: only a minority of animals survives to a fourth lactation, implying that most cows are culled before reaching their maximal potential. In contrast, the population of 100 t cows (HT), reaching the threshold of 100,000 kg lifetime milk yield, is growing rapidly. As these cows combine a long lifespan with high functionality, a better understanding of their intrinsic characteristics might help us to improve the overall lifespan and lifetime production in dairy cows. The aim of the present research was to compare HT with their less-producing herd mates in order to identify intrinsic cow factors associated with longevity and high lifetime production. Therefore, we matched 26,248 HT with 691,597 herd mates, born in the same year in the same herd. Data were provided by Coöperatie rundveeverbetering (CRV) and contained birth dates, calving dates, milk yield and dam information. In addition, scores for conformation traits based on classifications in the first lactation and breeding values (for milk yield, fertility, udder health and claw health) were provided. Multivariable conditional logistic regression models were built to identify factors associated with reaching a lifetime milk yield of 100,000 kg. Results revealed cows born in September and born out of heifers to have the highest odds to become a HT. When cows received a score ≥ 83 (population average 80) for udder and feet & legs conformation, they had higher odds of reaching the 100,000 kg threshold. While a greater body condition and larger rump angle increased the odds of becoming a HT, this was decreased in cows with a large body depth. Finally, breeding values for milk yield, fertility, udder health and claw health were positively associated with the likelihood of reaching a lifetime milk yield of 100,000 kg. In conclusion, to increase lifetime milk yield in dairy herds, farmers should select heifers with high scores for conformation traits like udder and feet & legs and high breeding values for milk yield, fertility and udder health. Furthermore, our data suggest that being born in September out of a heifer potentially contributes to reaching a high lifetime milk yield.

Indirect genomic predictions for milk yield in crossbred Holstein-Jersey dairy cattle

The objective of this study was to predict genomic breeding values for milk yield of crossbred dairy cattle under different scenarios using single-step genomic BLUP (ssGBLUP). The data set included 13,880,217 milk yield measurements on 6,830,415 cows. Genotypes of 89,558 Holstein, 40,769 Jersey, and 22,373 Holstein-Jersey crossbred animals were used, of which all Holstein, 9,313 Jersey, and 1,667 crossbred animals had phenotypic records. Genotypes were imputed to 45K SNP markers. The SNP effects were estimated from single-breed evaluations for Jersey (JE), Holstein (HO) and crossbreds (CROSS), and multibreed evaluations including all Jersey and Holstein (JE_HO) or approximately equal proportions of Jersey, Holstein, and crossbred animals (MIX). Indirect predictions (IP) of the validation animals (358 crossbred animals with phenotypes excluded from evaluations) were calculated using the resulting SNP effects. Additionally, breed proportions (BP) of crossbred animals were applied as a weight when IP were estimated based on each pure breed. The predictive ability of IP was calculated as the Pearson correlation between IP and phenotypes of the validation animals adjusted for fixed effects in the model. Regression of adjusted phenotypes on IP was used to assess the inflation of IP. The predictive ability of IP for CROSS, JE, HO, JE_HO, and MIX scenario was 0.50, 0.50, 0.47, 0.50, and 0.46, respectively. Using BP was the least successful, with a predictive ability of 0.32. The inflation of the IP for crossbred animals using CROSS, JE, HO, JE_HO, MIX, and BP scenarios were 1.17, 0.65, 0.55, 0.78, 1.00, and 0.85, respectively. The IP of crossbred animals can be predicted using single-step GBLUP under a scenario that includes purebred genotypes.

К вопросу оценки эффективности линейного разведения скота симментальской породы разного происхождения

Abstract. The purpose of the research – to study the impact of related foreign pedigree resources on the Russian population of Simmental cattle. Research Methods. Studies carried out on cows of Simmental breed of different linear origin and genotypes in five regions of Russian Federation: Voronezh, Oryol, Kursk, Belgorod regions and Altayskiy krai, the total number was 35147 cows. EBV estimates were calculated through RENUMF 90, REMLF 90 and BLUPF 90 programs. Evaluation of the components of the variants of genetic and paratypical nature was carried out using the method restricted maximum likelihood – REML. Results. It is established that the largest share for animals foreign origin are 60.7 %, including German-Austrian bloodlines 46.6 % and Holsteins – 14.1 %. 39.3 % of animals are the Russian origin, which 13.5 % representatives of German-Austrian bloodlines, 17.8 % are Holsteins and 8.0 % are from domestic (Russian) bloodlines. In the general population of Simmental breed, the best productivity was shown by cows of German-Austrian bloodlines at the level of 5351 kg of milk with fat percentage 4.00 % and protein percentage 3.19 %. Representatives of German-Austrian bloodlines origin for milk yield showed the estimated breeding value (EBV) for Simmental bulls in the common population by +9.2 kg and fat percentage by +0.012 %. The negative EBV values were obtained for Russian bloodlines by –22.8 kg, and Holstein bloodlines took an intermediate position among all lines (+2.3 kg). The first calving cows, which were in the herd at the time of research, the best milk production traits were found in individuals of foreign origin, both for Holstein (6096 kg of milk with a fat content of 3.96 % and protein 3.23 %), and German-Austrian bloodlines (milk yield 5763 kg, fat 4.04 % and protein 3.19 %), with high estimates of breeding value for milk yield +33.3 kg and +15.2 kg, respectively. Low values of milk productivity among all evaluated animals were observed for animals of Russian bloodlines by 4469 kg milk 3.87 % fat and 3.20 % protein in milk. The first calving cows of Russian origin in foreign bloodlines origin exceeded their peers in Russian Simmental bloodlines in milk production by +608 kg of milk and +0.15 % fat (signed to German-Austrian bloodlines) and +924 kg and +0.06 % fat (signed to Holstein bloodlines). The average values of EBV in these lines, although had low values by –5.6 kg milk for Holstein and by +2.7 kg milk for German-Austrian bloodlines, but was significantly higher than for Russian lines by –12.7 kg milk. Scientific novelty. For the first time, scientific research aimed at improving the system of prediction to breeding abilities of bulls on dairy productivity of daughters based on optimization structure of equations of the mixed model (BLUP, the best linear unbiased prediction) has been carried out for the population Simmental cattle of Russian Federation.

Culling reasons and risk factors in Estonian dairy cows

BackgroundCulling is a major cost for dairy farms but also an essential part in managing herd productivity. This study aimed to identify the culling rates of Estonian dairy cows, identify the farmers’ stated reasons and risk factors for culling. This observational study used registry data of all cows from herds with ≥20 cow-years in 2013–2015. Cow lactation-level analyses included data of 86,373 primiparous cows from 409 herds and 177,561 lactations of 109,295 multiparous cows from 410 herds. Weibull proportional hazard regression models were used to identify risk factors for culling due to slaughter or death.ResultsThe overall culling rate of Estonian dairy cows was 26.24 (95% CI 26.02; 26.46) per 100 cow-years. The most common reasons farmers stated for culling were feet/claw disorders (26.4%), udder disorders (22.6%), metabolic and digestive disorders (18.1%) and fertility problems (12.5%). Animal-level risk factors for culling were Holstein breed, older parity, lower milk yield breeding value, older age at first calving, longer previous calving interval, having assisted calving, stillbirth and birth of twins/triplets. Lower milk yield, somatic cell count over 200,000 cells/ml and fat/protein ratio over 1.5 at first test-milking after calving were associated with greater culling hazard during the lactation. Cows from larger herds, herds with decreasing size and higher milk yields had a higher culling probability.ConclusionsThis study emphasises the need for improved management of hoof health and prevention of mastitis and metabolic diseases. It is essential to ensure easy calving and good health of cows around calving in order to lower the culling hazard.

Integrating Casein Complex SNPs Additive, Dominance and Epistatic Effects on Genetic Parameters and Breeding Values Estimation for Murciano-Granadina Goat Milk Yield and Components.

Assessing dominance and additive effects of casein complex single-nucleotide polymorphisms (SNPs) (αS1, αS2, β, and κ casein), and their epistatic relationships may maximize our knowledge on the genetic regulation of profitable traits. Contextually, new genomic selection perspectives may translate this higher efficiency into higher accuracies for milk yield and components’ genetic parameters and breeding values. A total of 2594 lactation records were collected from 159 Murciano-Granadina goats (2005–2018), genotyped for 48 casein loci-located SNPs. Bonferroni-corrected nonparametric tests, categorical principal component analysis (CATPCA), and nonlinear canonical correlations were performed to quantify additive, dominance, and interSNP epistatic effects and evaluate the outcomes of their inclusion in quantitative and qualitative milk production traits’ genetic models (yield, protein, fat, solids, and lactose contents and somatic cells count). Milk yield, lactose, and somatic cell count heritabilities increased considerably when the model including genetic effects was considered (0.46, 0.30, 0.43, respectively). Components standard prediction errors decreased, and accuracies and reliabilities increased when genetic effects were considered. Conclusively, including genetic effects and relationships among these heritable biomarkers may improve model efficiency, genetic parameters, and breeding values for milk yield and composition, optimizing selection practices profitability for components whose technological application may be especially relevant for the cheese-making dairy sector.

Associations between maternal characteristics and health, survival, and performance of dairy heifers from birth through first lactation

The objective of this study was to investigate whether health, survival, and performance of dairy heifers from birth through first lactation are associated with parity and health status of their dams. Holstein heifers (n = 1,811) derived from artificial insemination were categorized as (1) daughters of primiparous cows that, consequently, were nonlactating heifers during gestation (Prim-NoL; n = 787); (2) daughters of multiparous cows that did not have any clinical diseases in the previous lactation (Mult-NoCD; n = 638); and (3) daughters of multiparous cows that had at least one clinical disease in the previous lactation (Mult-CD; n = 386). Clinical diseases of the multiparous dams included retained placenta, metritis, mastitis, lameness, and digestive and respiratory problems. Data collected for evaluation of daughters included genotypic and phenotypic characteristics at birth, morbidity, reproductive performance, and culling from birth through 305 d in milk of first lactation. Orthogonal contrasts were used to evaluate the effect of the parity of the dam (Prim-NoL vs. Mult-NoCD + Mult-CD) and the effect of clinical disease occurrence in the previous lactation among multiparous dams (Mult-NoCD vs. Mult-CD). Compared with daughters of multiparous cows, daughters of Prim-NoL were lighter at birth (36 vs. 41 kg), had greater genetic merit for production traits (e.g., genomic estimated breeding value for milk yield: 875 vs. 746 kg), were less likely to leave the herd (17 vs. 28%) and to lose pregnancy as a heifer (9 vs. 14%), calved earlier (703 vs. 711 d old), were less likely to have clinical diseases as a first lactation cow (30 vs. 37%), and had reduced performance in the first lactation when considering their genetic merit (e.g., 305-d yield of energy-corrected milk: 11,270 vs. 11,539 kg). Compared with daughters of Mult-NoCD, daughters of Mult-CD were less likely to have digestive problems as a heifer (17 vs. 27%) and clinical disease as a first lactation cow (32 vs. 42%), but were also more likely to leave the herd as a heifer (32 vs. 25%) even though genetic merit for production traits were similar (e.g., genomic estimated breeding value for milk: 744 vs. 749 kg). In conclusion, both parity and health status of the dam in the previous lactation were associated with morbidity, survival, and performance of their daughters from birth through 305 d in milk of the first lactation and might represent factors affecting developmental programming of dairy heifers in utero.

Accuracy of genomic-polygenic estimated breeding value for milk yield and fat yield in the Thai multibreed dairy population with five single nucleotide polymorphism sets

ObjectiveThe objectives were to compare variance components, genetic parameters, prediction accuracies, and genomic-polygenic estimated breeding value (EBV) rankings for milk yield (MY) and fat yield (FY) in the Thai multibreed dairy population using five single nucleotide polymorphism (SNP) sets from GeneSeek GGP80K chip.MethodsThe dataset contained monthly MY and FY of 8,361 first-lactation cows from 810 farms. Variance components, genetic parameters, and EBV for five SNP sets from the GeneSeek GGP80K chip were obtained using a 2-trait single-step average-information restricted maximum likelihood procedure. The SNP sets were the complete SNP set (all available SNP; SNP100), top 75% set (SNP75), top 50% set (SNP50), top 25% set (SNP25), and top 5% set (SNP5). The 2-trait models included herd-year-season, heterozygosity and age at first calving as fixed effects, and animal additive genetic and residual as random effects.ResultsThe estimates of additive genetic variances for MY and FY from SNP subsets were mostly higher than those of the complete set. The SNP25 MY and FY heritability estimates (0.276 and 0.183) were higher than those from SNP75 (0.265 and 0.168), SNP50 (0.275 and 0.179), SNP5 (0.231 and 0.169), and SNP100 (0.251and 0.159). The SNP25 EBV accuracies for MY and FY (39.76% and 33.82%) were higher than for SNP75 (35.01% and 32.60%), SNP50 (39.64% and 33.38%), SNP5 (38.61% and 29.70%), and SNP100 (34.43% and 31.61%). All rank correlations between SNP100 and SNP subsets were above 0.98 for both traits, except for SNP100 and SNP5 (0.93 for MY; 0.92 for FY).ConclusionThe high SNP25 estimates of genetic variances, heritabilities, EBV accuracies, and rank correlations between SNP100 and SNP25 for MY and FY indicated that genotyping animals with SNP25 dedicated chip would be a suitable to maintain genotyping costs low while speeding up genetic progress for MY and FY in the Thai dairy population.

Genetic evolution of milk yield, udder morphology and behavior in Gir dairy cattle

ABSTRACT The objective of this study was to analyze the genetic evolution of milk production, udder morphology, and animal behavior of Gir dairy cattle. Data were obtained on the predicted breeding values for milk yield of 60,226 cows born from 1968 to 2015 and standardized predicted breeding values for udder conformation and milking behavior of 7,635 cows born from 1987 to 2015. The influence of tested bulls on genetic trends was discussed, with special focus on the period after 1993, [...]

Random regression animal models for genetic evaluation of test-day milk yield and milking duration in Saudi dairy goats

Random regression animal model was applied for analyzing the relationships between daily milk yield (MK) and milking duration (DR) in dairy goats comparing with reviewed estimates in dairy cows. The current analyzed data involved 17345 sample test-day records from multiparous Saudi dairy goats. A cubic random regression was applied for representing additive genetic variances in all studied traits across all different days in milk (12 groups). Based on multi-lactation random regression data-set analysis, the role of inheritance was greatest during the later stages of lactation. Heritability estimates of daily milk yield (h2MK) ranged from 0.15 to 0.54. While estimates of heritability for milking duration (h2DR) were very low during the first 60 days of lactation, being not more than 0.04. During the 2nd half of lactation the estimates of h2DR ranged from 0.35 to 0.39. Results of genetic variations for lactation records during early production life showed that highest milk harvest with intermediate milking rate could be achieved. Estimates of expected breeding values for milk yield and milking duration increased in different rates with progressing days in milk groups. These results indicated that individual selection results would be favorably achieved during the late part of lactation. Additive genetic correlations between measures of all traits at different lactation months continuously decreased as the interval between test days increased. Additive genetic correlations between milking duration and milk yield were positive and considerably high. Correlations between expected breeding values of both traits ranged from 0.41 to 0.83 (mean = 0.69) across different lactation months. More details on estimates of breeding values, estimates of permanent environmental and additive genetic correlations for all traits were tabulated.

WPSIII-8 The effectiveness of the using bulls evaluated by different methods.

The aim of the study was to show the efficiency of using bulls (n=18) evaluated by various methods for improvement of herds with average cow milk yield of more than 8000 kg. The material was animal databases. We used statistical data processing. Results of simultaneous calculation of breeding value in bulls, which were genomically evaluated in the USA and Canada, demonstrated that sires evaluated in Canada by their own comparison base exceeded milk breeding value of bulls evaluated in the USA by the national comparison base. Using genomic evaluations and progeny tests in Russian animal breeding one should take into account a difference of bull breeding values in the USA and Canada. Use of semen of the same genomic bulls during period of 2014–2017 demonstrated that among 25 sires with genomic evaluation in the USA one sire maintained its superiority by 95.7% and three sires improved milk yield breeding value by 4.4–35.9%. Among Canadian genomic bulls evaluated in 2017, 6 sires maintained 80.7–97.6% of the breeding value in comparison with that of 2014. Use of genomic bulls demonstrated that best progeny tested sires were also among the best of genomic evaluation. In sire selection one should take into account the superiority by productive traits of daughters of given bulls, change in breeding values which took place during years after 1st genomic scoring. Comparison of results for the same 18 sires genomically evaluated in USA,which were progeny tested in the USA and Leningrad region, resulted in correlation coefficients between EBV BLUP score and “Daughter-contemporaries” score by milk yield about 0.55, by fat content – 0.72, by protein – 0.72. Loss of efficiency of cow breeding for milk yield because of ignoring BLUP method may reach 45%. Thus,the genetic evaluation by BLUP method should be introduce in breeding in dairy cattle.

Diversity of dairy goat lactation curves in France

A high level of production at the peak of lactation may be associated with animal health disorders, high feeding costs, and reduced milk supply throughout the year. The objective of this study was to typologize the lactation curves in French dairy goats and analyze the influence of environmental and genetic factors on these curves. The data set consisted of 2,231,720 monthly test-day records of 213,534 French Saanen and Alpine goats recorded between September 2008 and June 2012. First, principal component analysis classified the shape of the lactation curves into 3 principal components: the first component accounted for milk yield level throughout lactation, the second component accounted for lactation persistency, and the third component accounted for milk yield in mid-lactation. Then, from the principal component scores, the lactations were clustered into 5 different groups. Most lactations had a similar shape to the mean curve, except 30% of the lactations that fell into 3 clusters that had a high production level at the peak and then a different persistency according to cluster. Estimated breeding value for milk yield and home region of breeding were the factors most related to lactation production level. Month of kidding, breed, and gestation stage had the biggest effect on persistency. Month of kidding was the factor most strongly linked to mid-lactation production. A herd effect was observed on all 3 principal components.

Short communication: Genomic selection in a crossbred cattle population using data from the Dairy Genetics East Africa Project

Due to the absence of accurate pedigree information, it has not been possible to implement genetic evaluations for crossbred cattle in African small-holder systems. Genomic selection techniques that do not rely on pedigree information could, therefore, be a useful alternative. The objective of this study was to examine the feasibility of using genomic selection techniques in a crossbred cattle population using data from Kenya provided by the Dairy Genetics East Africa Project. Genomic estimated breeding values for milk yield were estimated using 2 prediction methods, GBLUP and BayesC, and accuracies were calculated as the correlation between yield deviations and genomic breeding values included in the estimation process, mimicking the situation for young bulls. The accuracy of evaluation ranged from 0.28 to 0.41, depending on the validation population and prediction method used. No significant differences were found in accuracy between the 2 prediction methods. The results suggest that there is potential for implementing genomic selection for young bulls in crossbred small-holder cattle populations, and targeted genotyping and phenotyping should be pursued to facilitate this.

Effect of polymorphisms in the ABCG2, LEPR and SCD1 genes on milk production traits in Holstein cows

This study was performed to investigate the association between polymorphisms in the ABCG2 (ATP-binding cassette sub-family G member 2), LEPR (leptin receptor) and SCD1 (stearoyl-coenzyme A desaturase 1) genes and milk production traits in Holstein dairy cows in Iran. The analysis was conducted on 816 lactations from 408 Iranian Holstein cows. Genotyping was carried out using the PCR-RFLP (polymerase chain reaction-restriction fragment length polymorphism) technique. The results of the association study revealed that cows with genotype AC of the ABCG2-Y581S single nucleotide polymorphism (SNP) had lower breeding value for milk yield compared with the AA genotype, but showed significantly higher fat and protein percentages. Cows that were homozygous for allele T at the LEPR-T945M locus had higher breeding value for fat yield than those that were homozygous for the C allele. Regarding the SCD1-A293V SNP, cows with genotype AV produced a higher 305-day milk yield in comparison with cows with the VV genotype. Furthermore, cows that were homozygous for allele V showed a significantly higher protein percentage compared with AA and AV genotypes. The results of this study suggest that these SNPs have the potential to be used in programmes based on genomic selection in Iranian dairy herds. ______________________________________________________________________________________ Keywords : Genetic polymorphism, Iranian Holstein, milk fat, milk protein, SNP

Heritability of metabolic response to the intravenous glucose tolerance test in German Holstein Friesian bulls

Selection for improved health and welfare in farm animals is of increasing interest worldwide. Peripartum energy balance is a key factor for pathogenesis of diseases in dairy cows. The intravenous glucose tolerance test (ivGTT) can be used to study the metabolic response to a glucose stimulus. The aim of this study was to estimate heritability of ivGTT traits in German Holstein bulls. A total of 541 Holstein bulls aged 7 to 17 mo from 2 breeding stations were subjected to the ivGTT. Serum glucose concentrations were measured at 0, 7, 14, 21, 28, 35, 42, 49, 56, and 63 min relative to glucose infusion. The maximum increase in blood glucose concentration, glucose area equivalent, and blood glucose half-life period were calculated. Heritabilities were estimated using a univariate animal model including station-year-season and age as fixed effects, and animal additive genetic and residual as random effects. The estimated heritabilities were 0.19 for fasting glucose concentration, 0.43 for glucose area equivalent, 0.40 for glucose half-life period, 0.14 for the peak glucose concentration, and 0.12 for the maximum increase of blood glucose concentration. Correlations between ivGTT traits and breeding values for milk yield and composition were not found. The results indicate that heritability for response to glucose is high, which warrants further investigation of this trait for genetic improvement of metabolic disorders. Research is necessary to determine the target levels of ivGTT traits and potential associations between ivGTT traits in breeding bulls and periparturient diseases in their offspring.

Cluster analysis of breeding values for milk yield and lactation persistency in Guzerá cattle

ABSTRACT: The aim of this study was to explore the pattern of genetic lactation curves of Guzerá cattle using cluster analysis. Test-day milk yields of 5,274 first-lactation Guzerá cows were recorded in a progeny test. A total of 34,193 monthly records were analyzed with a random regression animal model using Legendre polynomials to fit additive genetic and permanent environmental random effects and mean trends. Hierarchical and non-hierarchical cluster analyses were performed based on the EBVs for monthly test-day milk yield, peak yield, lactation persistency, and partial cumulative and 305-day yields. The heritability estimates for test-day milk yields ranged from 0.24 to 0.52. Cluster analysis identified animals in the population that belong to different groups according to milk production level and lactation persistency.