60 research outputs found

    Estimation of prediction error variances via Monte Carlo sampling methods using different formulations of the prediction error variance

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    Calculation of the exact prediction error variance covariance matrix is often computationally too demanding, which limits its application in REML algorithms, the calculation of accuracies of estimated breeding values and the control of variance of response to selection. Alternatively Monte Carlo sampling can be used to calculate approximations of the prediction error variance, which converge to the true values if enough samples are used. However, in practical situations the number of samples, which are computationally feasible, is limited. The objective of this study was to compare the convergence rate of different formulations of the prediction error variance calculated using Monte Carlo sampling. Four of these formulations were published, four were corresponding alternative versions, and two were derived as part of this study. The different formulations had different convergence rates and these were shown to depend on the number of samples and on the level of prediction error variance. Four formulations were competitive and these made use of information on either the variance of the estimated breeding value and on the variance of the true breeding value minus the estimated breeding value or on the covariance between the true and estimated breeding values

    Genetic parameters for EUROP carcass traits within different groups of cattle in Ireland

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    The first objective of this study was to test the ability of systems of weighing and classifying bovine carcasses used in commercial abattoirs in Ireland to provide information that can be used for the purposes of genetic evaluation of carcass weight, carcass fatness class, and carcass conformation class. Secondly, the study aimed to test whether genetic and phenotypic variances differed by breed of sire. Variance components for carcass traits were estimated for crosses between dairy cows and 8 breeds of sire commonly found in the Irish cattle population. These 8 breeds were Aberdeen Angus, Belgian Blue, Charolais, Friesian, Hereford, Holstein, Limousin, and Simmental. A multivariate animal model was used to estimate genetic parameters within the Holstein sire breed group. Univariate analyses were used to estimate variance components for the remaining 7 sire breed groups. Multivariate sire models were used to formally test differences in genetic variances in sire breed groups. Field data on 64,443 animals, which were slaughtered in commercial abattoirs between the ages of 300 and 875 d, were analyzed in 8 analyses. Carcass fat class and carcass conformation class were measured using the European Union beef carcass classification system (EUROP) scale. For all 3 traits, the sire breed group with the greatest genetic variance had a value of more than 8 times the sire breed group with least genetic variance. Heritabilities ranged from zero to moderate for carcass fatness class (0.00 to 0.40), from low to moderate for carcass conformation class (0.04 to 0.36), and from low to high for carcass weight (0.06 to 0.65). Carcass weight was the most heritable (0.26) of the 3 traits. Carcass conformation class and carcass fatness class were equally heritable (0.17). Genetic and phenotypic correlations were all positive in the Holstein sire breed group. The genetic correlations varied from 0.11 for the relationship between carcass weight and carcass fatness class to 0.44 for the relationship between carcass conformation class and carcass fatness class. Carcass weight and classification data collected in Irish abattoirs are useful for the purposes of genetic evaluation for beef traits of Irish cattle. There were significantly different variance components across the sire breed groups

    Estimation of accuracy and bias in genetic evaluations with genetic groups using sampling

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    Accuracy and bias of estimated breeding values are important measures of the quality of genetic evaluations. A sampling method that accounts for the uncertainty in the estimation of genetic group effects was used to calculate accuracy and bias of estimated effects. The method works by repeatedly simulating phenotypes for multiple traits for a defined data and pedigree structure. These simulated values are analysed using BLUP with genetic groups in the relationship matrix. Accuracies and biases are then calculated as correlations among and differences between true and estimated values across all replicates, respectively. The method was applied to the Irish beef production data set for 15 traits and with 15 genetic groups to account for differences in breed means. Accuracy and bias of estimated genetic groups effects, estimated comparisons between genetic groups effects, estimated breeding values within genetic group, and estimated breeding values across genetic group were calculated. Small biases were detected for most estimated genetic group effects and most estimated comparisons between genetic group effects. Most of these were not of importance relative to the phenotypic standard deviation of the traits involved. For example, a bias of 0.78% of the phenotypic standard deviation was detected for carcass conformation in Aberdeen Angus. However, one trait, calf quality, which has very few performance records in the data set, displayed larger bias ranging from -10.31% to 5.85% of the phenotypic standard deviation across the different estimated genetic group effects. Large differences were observed in the accuracies of genetic group effects, ranging from 0.02 for feed intake in Holstein, which had no data recorded, to >0.97 for carcass conformation, a trait with large amounts of data recorded in the different genetic groups. Large differences were also observed in the accuracies of the comparisons among genetic group effects. The accuracies of the estimated breeding values within genetic group and estimated breeding values across genetic group were sometimes different; for example, carcass conformation in Belgian Blue had an average accuracy within genetic group of 0.69 compared to an average accuracy across genetic group of 0.89. This suggests that the accuracy of genetic groups should be taken into account when publishing estimated breeding values across genetic groups

    Heterogeneity of genetic parameters for calving difficulty in Holstein heifers in Ireland

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    Calving difficulty is a trait that greatly affects animal welfare, herd profitability, and the amount of labor required by cattle farmers. It is influenced by direct and maternal genetic components. Selection and breeding strategies can optimize the accuracy of genetic evaluations and correctly emphasize calving difficulty in multiple-trait indices provided there are accurate estimates of genetic parameters. In Ireland, large differences exist in the age at which heifers first give birth to calves. The objective of this study was to estimate genetic parameters for calving difficulty in first-parity Holsteins and to determine whether these differed with age of the heifer at calving. Transformed calving difficulty records for 18,798 Holstein heifers, which calved between January 2002 and May 2006, were analyzed using univariate, multitrait, and random regression linear sire-maternal grandsire models. The model that 1) fitted a second-order random regression of dam age at first parity for the direct component, 2) treated the maternal component as a single trait regardless of dam age, and 3) fitted a single residual variance component was optimal. Heritabilities for direct (0.13) and maternal (0.04) calving difficulty were significantly different from zero. These 2 components were moderately negatively correlated (¿0.47). Estimates of direct genetic variance and heritability were heterogeneous along the dam age trajectory, decreasing initially with dam age before subsequently increasing. Heritability estimates ranged between 0.11 and 0.37 and were higher for records with younger and older dams at parturition. Genetic correlations between the direct components of calving difficulty decreased from unity to 0.5 with increasing distance between dam ages at parturition. The results of this study indicated that heterogeneity of direct genetic variance existed for calving difficulty, depending on dam age at first parturition

    Genotoxic effect induced by hydrogen peroxide in human hepatoma cells using comet assay

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    Background: Hydrogen peroxide is a common reactive oxygen intermediate generated by variousforms of oxidative stress. Aims: The aim of this study was to investigate the DNA damage capacity ofH2O2 in HepG2 cells. Methods: Cells were treated with H2O2 at concentrations of 25 μM or 50 μM for5 min, 30 min, 40 min, 1 h or 24 h in parallel. The extent of DNA damage was assessed by the cometassay. Results: Compared to the control, DNA damage by 25 μM and 50 μM H2O2 increasedsignificantly with increasing incubation time up to 1 h, but it was not increased at 24 h. Conclusions:Our Findings confirm that H2O2 is a typical DNA damage inducing agent and thus is a good modelsystem to study the effects of oxidative stress. DNA damage in HepG2 cells increased significantlywith H2O2 concentration and time of incubation but later decreased likely due to DNA repairmechanisms and antioxidant enzyme

    Heavy metal contamination in bats in Britain

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    Toxic metals are bioaccumulated by insectivorous mammals but few studies (none from Britain) have quantified residues in bats. We measured renal mercury (Hg), lead (Pb) and cadmium (Cd) concentrations in bats from south-west England to determine how they varied with species, sex, age, and over time, and if they were likely to cause adverse effects. Residues were generally highest in whiskered bats (Myotis mystacinus). Compared with other species, pipistrelle (Pipistrellus spp) and Natterer's bats (Myotis nattereri) had significantly lower kidney Hg and Pb concentrations, respectively. Renal Hg increased over time in pipistrelles but the contributory sources are unknown. Kidney Pb did not decrease over time despite concurrent declines in atmospheric Pb. Overall, median renal metal concentrations were similar to those in bats from mainland Europe and 6- to 10-fold below those associated with clinical effect, although 5% of pipistrelles had kidney Pb residues diagnostic of acute lead poisoning. Heavy metal contamination has been quantified in bats from Britain for the first time and indicates increased accumulation of Hg and no reduction in Pb
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