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1.
Records of birth weight (BW), weaning weight (WW) and condition score (CS) from 1,467 Brahman and Brahman X Angus crossbred calves from Brahman and crossbred Brahman sires and Brahman, crossbred Brahman and Angus dams were collected at the Subtropical Agricultural Research Station, Brooksville, Florida, from 1971 to 1982. Best linear unbiased estimates (BLUE) of Brahman sire and dam group additive genetic effects (as deviations from Angus) and Brahman X Angus dam and calf group nonadditive (intralocus) genetic effects (as deviations from intralocus group genetic effects in the parental breeds) were obtained. Linear combinations of these were used to compute direct and maternal Brahman additive and Brahman X Angus nonadditive (intralocus) group genetic effects. The respective BLUE of these four effects were 5.99 +/- 2.08, -5.70 +/- 1.91, .52 +/- 1.81 and 2.85 +/- .72 kg for BW; 9.60 +/- 10.29, 8.76 +/- 9.47, 9.47 +/- 8.96 and 20.95 +/- 3.56 kg for WW; and -1.10 +/- .55, 1.64 +/- .50, 1.47 +/- .47 and .05 +/- .19 units for CS. Linear combinations of the BLUE of sire, dam and calf group genetic effects can be used to predict the genetic worth of crossbred groups composed of any combination of Brahman and Angus breeding. Nonadditive maternal group genetic effects were the most important factor for BW and WW, whereas nonadditive direct group genetic effects were the most important for CS.  相似文献   

2.
Genetic parameters and genetic trends for weaning weight adjusted to 240 d of age (WW240), and weight gain from weaning to 24 mo of age (GW730) were estimated in a Colombian beef cattle population composed of Blanco Orejinegro, Romosinuano, Angus, and Zebu straightbred and crossbred animals. Calves were born and weaned in a single farm, and moved to 14 farms postweaning. Data were analyzed using a multiple trait mixed model procedures. Estimates of variance components and genetic parameters were obtained by Restricted Maximum Likelihood. The 2-trait model included the fixed effects of contemporary group (herd–year–season–sex), age of dam (WW240 only), breed direct genetic effects (as a function of breed fractions of calves), breed maternal genetic effects (as a function of breed fractions of dams; WW240 only), individual heterosis (as a function of calf heterozygosity), and maternal heterosis (as a function of dam heterozygosity; WW240 only). Random effects for WW240 were calf direct genetic, dam maternal genetic, permanent environmental maternal, and residual. Random effects for GW730 were calf direct genetic and residual. All relationships among animals were accounted for. Program AIREML was used to perform computations. Estimates of heritabilities for additive direct genetic effects were 0.20 ± 0.003 for WW240, and 0.32 ± 0.004 for GW730. Maternal heritability was 0.14 ± 0.002 for WW240. Estimates of heritability suggest that selection for preweaning and postweaning growth in this population is feasible. Low direct and maternal preweaning heritabilities suggest that nutrition and management should be improved to allow fuller expressions of calf direct growth and cow maternal ability. The genetic correlation between direct additive and maternal additive effects for WW240 was − 0.42 ± 0.009, indicating an antagonistic relationship between these effects. The correlation between additive direct genetic effects for WW240 and GW730 was almost zero (− 0.04 ± 0.009), suggesting that genes affecting growth preweaning may differ from those influencing growth postweaning. Trends were negative for direct WW240 and GW730 weighted yearly means of calves, sires, and dams from 1995 to 2006. Maternal WW240 showed near zero trends during these years. Trends for calf direct WW240 and GW730 followed sire trends closely, suggesting that more emphasis was placed on choosing sires than on dam replacements.  相似文献   

3.
Several studies have noted high negative correlations between maternal genetic and direct additive effects and their influence on additive and maternal heritability of early growth traits in sheep. Multigeneration data from the Suffolk Sire Reference Scheme (SSRS) were used to investigate the effect of data structure on estimates of direct and maternal (co)variances for lamb 8-wk weight. In all analyses the additive, maternal genetic, maternal environmental, and residual effects were fitted along with the covariance between direct and maternal additive effects. The contributions of particular genetic relationships to the estimates were studied by analyzing subsets of the SSRS data. A further eight subsets were formed having 10% or 50% of the dams with their own records and having one or two, three or four, five or six, and more than six offspring per dam. Analysis of data having only 10% of the dams with their own record and one or two offspring records yielded a high negative correlation (-0.99) between direct and maternal genetic effects. However, the seven other data sets with more records per dam or a higher proportion of dams with their own records produced values of -0.35 to -0.51. Data structure and the number of dams and granddams with records are important determinants of estimated direct and maternal effects in early growth traits.  相似文献   

4.
The aim of this study was to estimate genetic parameters for BW of Angus cattle up to 5 yr of age and to discuss options for including mature weight (MW) in their genetic evaluation. Data were obtained from the American Angus Association. Only records from herds with at least 500 animals and with >10% of animals with BW at ≥ 2 yr of age were considered. Traits were weaning weight (WW, n = 81,525), yearling weight (YW, n = 62,721), and BW measured from 2 to 5 yr of age (MW2, n = 15,927; MW3, n = 12,404; MW4, n = 9,805; MW5, n = 7,546). Genetic parameters were estimated using an AIREML algorithm with a multiple-trait animal model. Fixed effects were contemporary group and departure of the actual age from standard age (205, 365, 730, 1,095, 1,460, and 1,825 d of age for WW, YW, MW2, MW3, MW4, and MW5, respectively). Random effects were animal direct additive genetic, maternal additive genetic, maternal permanent environment, and residual. Estimates of direct genetic variances (kg(2)) were 298 ± 71.8, 563 ± 15.1, 925 ± 52.1, 1,221 ± 65.8, 1,406 ± 80.4, and 1,402 ± 66.9; maternal genetic variances were 167 ± 4.8, 153 ± 6.1, 123 ± 9.1, 136 ± 12.25, 167 ± 18.0, and 110 ± 14.0; maternal permanent environment variances were 124 ± 2.9, 120 ± 4.3, 61 ± 7.5, 69 ± 11.9, 103 ± 15.9, and 134 ± 35.2; and residual variances were 258 ± 3.8, 608 ± 8.6, 829 ± 34.2, 1,016 ± 38.8, 1,017 ± 52.1, and 1,202 ± 63.22 for WW, YW, MW2, MW3, MW4, and MW5, respectively. The direct genetic correlation between WW and YW was 0.84 ± 0.14 and between WW and MW ranged from 0.66 ± 0.06 (WW and MW4) to 0.72 ± 0.11 (WW and MW2). Direct genetic correlations ranged from 0.77 ± 0.08 (YW and MW5) to 0.85 ± 0.07 (YW and MW2) between YW and MW, and they were ≥ 0.95 among MW2, MW3, MW4, and MW5. Maternal genetic correlations between WW and YW and MW ranged from 0.52 ± 0.05 (WW and MW4) to 0.95 ± 0.07 (WW and YW), and among MW they ranged from 0.54 ± 0.14 (MW4 and MW5) to 0.94 ± 0.07 (MW2 and MW3). Genetic correlations suggest that a genetic evaluation for MW may be MW2-based and that including BW from older ages could be accomplished by adjusting records to the scale of MW2.  相似文献   

5.
Estimates of genetic parameters for growth traits in Kermani sheep   总被引:3,自引:0,他引:3  
Birth weight (BW), weaning weight (WW), 6-month weight (W6), 9-month weight (W9) and yearling weight (YW) of Kermani lambs were used to estimate genetic parameters. The data were collected from Shahrbabak Sheep Breeding Research Station in Iran during the period of 1993-1998. The fixed effects in the model were lambing year, sex, type of birth and age of dam. Number of days between birth date and the date of obtaining measurement of each record was used as a covariate. Estimates of (co)variance components and genetic parameters were obtained by restricted maximum likelihood, using single and two-trait animal models. Based on the most appropriate fitted model, direct and maternal heritabilities of BW, WW, W6, W9 and YW were estimated to be 0.10 +/- 0.06 and 0.27 +/- 0.04, 0.22 +/- 0.09 and 0.19 +/- 0.05, 0.09 +/- 0.06 and 0.25 +/- 0.04, 0.13 +/- 0.08 and 0.18 +/- 0.05, and 0.14 +/- 0.08 and 0.14 +/- 0.06 respectively. Direct and maternal genetic correlations between the lamb weights varied between 0.66 and 0.99, and 0.11 and 0.99. The results showed that the maternal influence on lamb weights decreased with age at measurement. Ignoring maternal effects in the model caused overestimation of direct heritability. Maternal effects are significant sources of variation for growth traits and ignoring maternal effects in the model would cause inaccurate genetic evaluation of lambs.  相似文献   

6.
The aim of this study was to estimate genetic parameters for growth traits in Mexican Nellore cattle. A univariate animal model was used to estimate (co)variance components and genetic parameters. The traits evaluated were birth weight (BW), weaning weight (WW), and yearling weight (YW). Models used included the fixed effects of contemporary groups (herd, sex, year, and season of birth) and age of dam (linear and quadratic) as a covariate. They also included the animal, dam, and residual as random effects. Phenotypic means (SD) for BW, WW, and YW were 31.4 (1.6), 175 (32), and 333 (70) kg, respectively. Direct heritability, maternal heritability, and the genetic correlation between additive direct and maternal effects were 0.59, 0.17, and −0.90 for BW; 0.29, 0.17, and −0.90 for WW; and 0.24, 0.15, and −0.86 for YW, respectively. The results showed moderate direct and maternal heritabilities for the studied traits. The genetic correlations between direct and maternal effects were negative and high for all the traits indicating important tradeoffs between direct and maternal effects. There are significant possibilities for genetic progress for the growth traits studied if they are included in a breeding program considering these associations.  相似文献   

7.
Parameters for direct and maternal dominance were estimated in models that included non-additive genetic effects. The analyses used weaning weight records adjusted for age of dam from populations of Canadian Hereford (n = 467,814), American Gelbvieh (n = 501,552), and American Charolais (n = 314,552). Method R estimates of direct additive genetic, maternal additive genetic, permanent maternal environment, direct dominance, and maternal dominance variances as a proportion of the total variance were 23, 12, 13, 19, and 14% in Hereford; 27, 7, 10, 18, and 2% in Gelbvieh; and 34, 15, 15, 23, and 2% in Charolais. The correlations between direct and maternal additive genetic effects were -0.30, -0.23, and -0.47 in Hereford, Gelbvieh, and Charolais, respectively. The correlations between direct and maternal dominance were -0.38, -0.02, and -0.04 in Hereford, Gelbvieh, and Charolais, respectively. Estimates of inbreeding depression were -0.20, -0.18, and -0.13 kg per 1% of inbreeding for Hereford, Gelbvieh, and Charolais, respectively. Estimates of the maternal inbreeding depression were -0.01, -0.02, and -0.02 kg, respectively. The high ratio of direct dominance to additive genetic variances provided some evidence that direct dominance effects should be considered in beef cattle evaluation. However, maternal dominance effects seemed to be important only for Hereford cattle.  相似文献   

8.
  • 1.?A study was conducted to study direct dominance genetic and maternal effects on genetic evaluation of production traits in dual-purpose chickens. The data set consisted of records of body weight and egg production of 49 749 Mazandaran fowls from 19 consecutive generations. Based on combinations of different random effects, including direct additive and dominance genetic and maternal additive genetic and environmental effects, 8 different models were compared.

  • 2.?Inclusion of a maternal genetic effect in the models noticeably improved goodness of fit for all traits. Direct dominance genetic effect did not have noticeable effects on goodness of fit but simultaneous inclusion of both direct dominance and maternal additive genetic effects improved fitting criteria and accuracies of genetic parameter estimates for hatching body weight and egg production traits.

  • 3.?Estimates of heritability (h2) for body weights at hatch, 8 weeks and 12 weeks of age (BW0, BW8 and BW12, respectively), age at sexual maturity (ASM), average egg weights at 28–32 weeks of laying period (AEW), egg number (EN) and egg production intensity (EI) were 0.08, 0.21, 0.22, 0.22, 0.21, 0.09 and 0.10, respectively. For BW0, BW8, BW12, ASM, AEW, EN and EI, proportion of dominance genetic to total phenotypic variance (d2) were 0.06, 0.08, 0.01, 0.06, 0.06, 0.08 and 0.07 and maternal heritability estimates (m2) were 0.05, 0.04, 0.03, 0.13, 0.21, 0.07 and 0.03, respectively. Negligible coefficients of maternal environmental effect (c2) from 0.01 to 0.08 were estimated for all traits, other than BW0, which had an estimate of 0.30.

  • 4.?Breeding values (BVs) estimated for body weights at early ages (BW0 and BW8) were considerably affected by components of the models, but almost similar BVs were estimated by different models for higher age body weight (BW12) and egg production traits (ASM, AEW, EN and EI). Generally, it could be concluded that inclusion of maternal effects (both genetic and environmental) and, to a lesser extent, direct dominance genetic effect would improve the accuracy of genetic evaluation for early age body weights in dual-purpose chickens.

  相似文献   

9.
Analysis of variance (ANOVA) and symmetric differences squared (SDS) methods were used to estimate additive genetic and environmental variances and covariances associated with weaning weight. The two methods were applied to 503 beef records collected over 19 yr from a relatively unselected university Angus herd. The SDS methodology was used with four models. The first model included direct (g) and maternal (gm) additive genetic effects, the genetic covariance between direct and maternal additive genetic effects (sigma ggm), permanent maternal environmental effects (m) and temporary environmental effects (e). The second model also allowed for a nonzero environmental covariance (sigma mem) between dam and offspring weaning weights. Models 3 and 4 were models 1 and 2, respectively, expanded to include a grandmaternal genetic effect (gn) and covariances sigma ggn and sigma gmgn. Two ANOVA solution sets for the parameters of model 4 were based on sire, dam, maternal grandsire, maternal grandam and phenotypic variances and offspring-dam (covOD), offspring-sire (covOS), offspring-grandam (covOGD) and offspring-maternal half-aunt or uncle (covOMH) covariances. Four ANOVA solution sets for the parameters of model 2 were based on sire, dam, within dam and maternal grandsire variances, covOD and either covOS or covOGD. Symmetric differences squared estimates of h2g and h2gm averaged .30 and .16, respectively. All SDS estimates of rho ggm (correlation between direct and maternal genetic effects) were less than -1. Estimates of sigma mem were positive. Both SDS estimates and one of the two ANOVA estimates of the grandmaternal variance were negative. The ANOVA model 4 estimates of h2g were .33. The estimates of h2gm were .44 and .39, while the estimates for rho ggm were -.88 and -.80. Both estimates of sigma mem were positive. The four ANOVA model 2 estimates of h2g and h2gm averaged .33 and .48, respectively. Three of the four estimates of rho ggm were less than -.97; the fourth was .35. Three of the four estimates of sigma mem were positive. Expectations show the extent to which SDS and ANOVA estimators were biased by nonzero grandmaternal components that were not accounted for. The extent to which dominance components bias the ANOVA estimators also is shown. Nonzero grandmaternal effects need to be taken into account in either SDS or ANOVA solution sets, or important biases occur with most of the estimators. More numerous, and generally more severe, biases occur with ANOVA estimators than with SDS estimators in solution sets that do not account for grandmaternal effects.  相似文献   

10.
Phenotypic variances for linear and transformed weight traits were partitioned into residual, direct genetic (D) and maternal genetic (M) components using REML techniques with American Simmental Association data from calves born 1969 to 1985. Variance components were estimated separately from subclasses defined by sex (male, female) and percent Simmental (50, greater than or equal to 75). The model included fixed effects of contemporary group and age-of-dam (less than 3, 3 to 5, greater than 5 yr). Additive relationships among sires and maternal grandsires were included. Results follow for a sire-maternal grandsire model for greater than or equal to 75% Simmental untransformed data based on 143,280 male and 281,805 female weaning weights (WW) representing 4,763 and 7,406 sires, respectively. Female results are bracketed. For computational simplification, 47,650 [30,909] postweaning gain (PW) records were included in the analysis only for 114,404 [182,255] calves with birth weight (BW). Phenotypic standard deviations (kg) were: BW, 4.5 [4.1]; WW, 26.9 [23.2]; and PW, 25.9 [19.9]. Heritabilities were: BWD, .40 [.45]; WWD, .32 [.39]; PWD, .26 [.32]; BWM, .13 [.15]; WWM, .20 [.16]; and PWM, .01 [.01]. These heritabilities are higher than previously used for genetic evaluations in this breed. Moderate and positive correlations .26 to .50, existed between direct effects and were similar for both sexes. Direct and maternal effects on the same trait were correlated negatively: BW, -.45 [-.31]; and WW, -.27 [-.34]. Genetic correlation between BWM and WWM was .53 [.49]. First-cross progeny exhibited less genetic and residual variation and had lower heritabilities than Simmental calves of higher percent. Correlations between sire evaluations on the subsets were consistent with those expected given a perfect genetic correlation between traits for each sex and percent Simmental. Logarithmic transformed records were no more homogeneous than untransformed records.  相似文献   

11.
绵羊生长性状母本效应方差组分、遗传参数估计的研究   总被引:5,自引:0,他引:5  
本文利用公畜母畜模型和公畜外祖父模型估计了初生重、断奶重的直接加性遗传方差、母本遗传方差和遗传参数,得出初生重的直接加性遗传效应、母本遗传效应和总的加性遗传效应的遗传力分别为:0.164、0.101、0.103;断奶重相应的各遗传力为:0.076、0.108、0.081。初生重和断奶重二性状加性遗传效应和母本遗传效应间的遗传相关为:-0.57和-0.36。  相似文献   

12.
This study investigates the estimation of direct and maternal genetic (co)variances, accounting for environmental covariances between direct and maternal effects. Estimated genetic correlations between direct and maternal effects presented in the literature have often been strongly negative, and their validity has been questioned. Explanations of extreme estimates have focused on the existence of environmental covariances between dam and offspring. As a solution, models including a regression on dam-phenotype have been proposed, but have yielded biased estimates. The performance of models that implement the variance structure arising from the classical model of Willham, however, has not been evaluated. This study investigated the covariance structure of the parts of the residual term that arise from Willham's model. Results show that a correlation between the residual of the record of an individual and that of its dam is a direct consequence of combining Willham's model with the usual assumption that phenotypic covariances between different traits are the sum of additive genetic and environmental covariances. Stochastic simulations show that fitting this structure yields unbiased estimates of the genetic (co)variances. When correlated residuals were ignored in the cases investigated, the bias in the estimated genetic correlations was approximately equal to the value of the environmental correlation. In contrast to models including a regression on dam-phenotype, there were no difficulties with interpretation of results, and the approach was consistent with standard quantitative genetic theory. The use of Willham's model while accounting for correlated residuals is conceptually appealing and yields unbiased results, with no need for regression on dam phenotype. Inclusion of the ability to fit the residual variance structure required for maternal effects into existing software packages would be helpful to animal breeders.  相似文献   

13.
Survival of 16,838 potential embryos was determined by counting corpora lutea and fetuses at 50 d of gestation for 1,081 litters by 225 sires. These data, coded as 1 or 0 depending on whether an ovulation was represented by a fetus, were used to estimate direct and maternal additive genetic variances and their covariance for embryonic survival. Data were from first-parity gilts of a Large White-Landrace composite population subdivided into two lines, one selected for an index of ovulation rate and embryonic survival for seven generations and a contemporary control line. Variance components were obtained by ANOVA and expectations of covariances among relatives and by derivative-free restricted maximum likelihood (DFREML) in an animal model. As a trait of the embryo, heritability of direct effects obtained with ANOVA was 3.8%, heritability of maternal effects was 1.5%, and the genetic correlation between them was -.51. After adjustment of embryonic survival for ovulation rate, lower estimates of each parameter were obtained with ANOVA. Heritability of embryonic survival as a trait of the dam was 9 to 10%. Estimates of heritability of both direct and maternal effects obtained with DFREML were less than 1% and the genetic correlation between them was -.64. When survival of embryos from only those dams with 15 or more ovulations was analyzed, heritability of maternal effects was 4.4%. Estimates of common environmental effects on embryonic survival ranged from 5 to 7%.  相似文献   

14.
Analysis of variance (ANOVA) and symmetric differences squared (SDS) methods for estimating genetic and environmental variances and covariances associated with beef cattle weaning weight were compared via simulation. Simulation was based on the pedigree and record structure of 503 beef weaning weights collected over 19 yr from a university herd. The SDS methodology was used with four models. The simplest model included direct (g) and maternal (gm) additive genetic effects, genetic covariance between direct and maternal additive genetic effects (sigma ggm), permanent maternal environmental effects (m) and temporary environmental effects (e). The second model also allowed for a nonzero environmental covariance (sigma mem) between dam and offspring weaning weights. Models 3 and 4 were models 1 and 2, respectively, expanded to include a grandmaternal genetic effect (gn) and covariances sigma ggn and sigma gmgn. Two ANOVA solution sets for the parameters of model 4 were obtained using sire, dam, maternal grandsire, maternal grandam and phenotypic variances and offspring-dam (covOD), offspring-sire (covOS), offspring-grandam (covOGD), and offspring-maternal half-aunt or uncle (covOMH) covariances. Four ANOVA solution sets for the parameters of model 2 were obtained using sire, dam, within dam and maternal grandsire variances, covOD and either covOS or covOGD. Two sets of 1,000 replicates of the data were simulated. These data were used to compare precision and accuracy of SDS and ANOVA estimators, to estimate correlations among SDS and ANOVA estimators, and to study the importance of taking inbreeding into account with SDS methodology. All ANOVA estimators for rho ggm were biased downward. The SDS procedure had a clear advantage over ANOVA. Averages of SDS estimates were closer to parameter values used to simulate the data and their standard deviations were generally smaller. The standard deviations of both SDS and ANOVA estimates of rho ggm were very large. It is important to allow for a nonzero sigma mem (at least when it is negative) when using SDS methods; otherwise estimators of sigma 2gm and sigma ggm are biased upward and downward, respectively.  相似文献   

15.
The genetic parameters for Brahman cattle under the tropical conditions of Mexico are scarce. Therefore, heritabilities, additive direct and maternal correlations, and genetic correlations for birth weight (BW) and 205 days adjusted weaning weight (WW205) were estimated in four Brahman cattle herds in Yucatan, Mexico. Parameters were estimated fitting a bivariate animal model, with 4,531 animals in the relationship matrix, of which 2,905 had BW and 2,264 had WW205. The number of sires and dams identified for both traits were 122 and 962, respectively. Direct heritability estimates for BW and WW205 were 0.41?±?0.09 and 0.43?±?0.09, and maternal heritabilities were 0.15?±?0.07 and 0.38?±?0.08, respectively. Genetic correlations between direct additive and maternal genetic effects for BW and WW205 were ?0.41?±?0.22 and ?0.50?±?0.15, respectively. The direct genetic, maternal, and phenotypic correlations between BW and WW205 were 0.77?±?0.09, 0.61?±?0.18, and 0.35, respectively. The moderate to high genetic parameter estimates suggest that genetic improvement by selection is possible for those traits. The maternal effects and their correlation with direct effects should be taken into account to reduce bias in genetic evaluations.  相似文献   

16.
Genetic parameters and genetic trends for birth weight (BW), weaning weight (WW), 6-month weight (6MW), and yearling weight (YW) traits were estimated by using records of 5,634 Makooei lambs, descendants of 289 sires and 1,726 dams, born between 1996 and 2009 at the Makooei sheep breeding station, West Azerbaijan, Iran. The (co)variance components were estimated with different animal models using a restricted maximum likelihood procedure and the most appropriate model for each trait was determined by Akaike’s Information Criterion. Breeding values of animals were predicted with best linear unbiased prediction methodology under multi-trait animal models and genetic trends were estimated by regression mean breeding values on birth year. The most appropriate model for BW was a model including direct and maternal genetic effects, regardless of their covariance. The model for WW and 6MW included direct additive genetic effects. The model for YW included direct genetic effects only. Direct heritabilities based on the best model were estimated 0.15?±?0.04, 0.16?±?0.03, 0.21?±?0.04, and 0.22?±?0.06 for BW, WW, 6MW, and YW, respectively, and maternal heritability obtained 0.08?±?0.02 for BW. Genetic correlations among the traits were positive and varied from 0.28 for BW–YW to 0.66 for BW–WW and phenotypic correlations were generally lower than the genetic correlations. Genetic trends were 8.1?±?2, 67.4?±?5, 38.7?±?4, and 47.6?±?6 g per year for BW, WW, 6MW, and YW, respectively.  相似文献   

17.
Data from the American Angus Association, American Gelbvieh Association, and the North American Limousin Foundation were analyzed to determine whether parental genetic differences are associated with Mendelian sampling of their bull progeny or with Mendelian sampling variances and weight variances of their bull progeny's offspring. Parental differences were measured as the difference between the parents' EPD for birth weight (DIF(BW)), weaning weight direct (DIF(WW)), and yearling weight (DIF(YW)). A bull's data were used if both parents had calculated EPD and the bull had at least 25 progeny with records for the specific trait. Traits calculated for each bull were his Mendelian sampling (MS(Bull)), progeny Mendelian sampling variance (MSsigma2progeny), progeny weight variance (WTsigma2), and progeny corrected weight variance (CWTsigma2 = adjusted weight minus appropriate dam EPD) for birth, weaning, and yearling weights. Pearson correlations were computed between DIF(BW), DIF(WW), and DIF(YW) and MS(Bull), MSsigma2progeny, WTsigma2, and CWTsigma2 for each trait, within each breed. Across breeds, the correlations ranged from -.07 to .11 for MS(Bull) .01 to .14 for MSsigma2progeny, -.06 to .09 for WTsigma2, and -.06 to .08 for CWTsigma2. Although some of the correlations were significantly different from zero their relatively small magnitude indicates little relationship between parental differences in genetic merit and subsequent offspring variability for each of the three breeds.  相似文献   

18.
Weaning weights from Gelbvieh (GV; n = 82,138) and Limousin (LM; n = 88,639) calves were used to estimate genetic and environmental variance components with models that included different values for the correlation (lambda) between permanent environmental effects of dams and their daughters. Each analysis included fixed discrete effects of contemporary group, sex of calf, age of dam at calving, and month of calving, a fixed continuous effect of age of calf, random direct and maternal additive genetic effects, permanent environmental effects due to dams, and residual effects. The REML procedure was employed with a "grid search," in which the likelihood was computed for a series of values for lambda. For both breeds, models that included a nonzero value for lambda fitted the data significantly better than the model that did not include lambda. The maximum restricted likelihood was obtained for lambda of approximately -0.2 for both breeds. Estimates of residual and direct genetic variances were similar for all values of lambda, including zero; however, estimates of maternal genetic variance and maternal heritability increased slightly, and maternal permanent environmental variance and the proportion of the maternal variance to the total (phenotypic) variance decreased slightly, when the correlated structure for permanent environmental effects was assumed. As the value of lambda became more negative, absolute values of the direct-maternal genetic covariance and direct-maternal correlation estimates were decreased. Pearson and rank correlations for direct genetic, maternal genetic, and maternal environmental effects estimated with and without lambda were very high (>0.99). These results indicated that the linear relationship between maternal permanent environmental effects of dams and their daughters for weaning weight is negative but low in both breeds. Considering this relationship in the operational model did not significantly affect estimated breeding values, and thus, it may not be important in genetic evaluations.  相似文献   

19.
SUMMARY: Field data on weight recordings provided by the Australian Simmental Breeders Association was analysed. From a data set of 64,962 animals, which had either birth (BW), weaning (WW), yearling (YW), or final weight (FW) records a subset of 17 herds comprising 18,083 animals was used to obtain uni- and bivariate estimates of variance components. This subset had to be subdivided into six further subsets, called group herds. The models used allowed for additive genetic, maternal genetic, and permanent environmental effects and for a covariance between additive direct and maternal genetic effects. Estimates were pooled across group herds. The results for BW, WW, YW, FW were .33, .35, .37, and .30, respectively, for heritabilities and .074, .18, and .11 for maternal heritabilities (not estimated for FW). Significant correlations between direct and maternal genetic effects (rAM) existed for WW and YW in the magnitude of -.39 and -.22. However, further research is needed due to the problems associated with the estimation of r(AM) . ZUSAMMENFASSUNG: Sch?tzung direkter und maternaler (Ko)Varianz-Komponenten für Wachstumsmerkmale bei australischem Fleckvieh Gegenstand der Untersuchung waren im Feld erhobene Gewichte, die von der Australischen Simmental Breeders Association bereitgestellt worden waren. Aus einer Datei von 64.962 Tieren, die entweder ein Geburtsgewicht (GG), ein Absetzgewicht (AG), ein J?hrlingsgewicht (JG) oder ein Endgewicht (EG) aufwiesen, wurde ein Teildatensatz von 18.083 Tieren extrahiert und einer uni- und bivariaten Sch?tzung von Varianzkomponenten unterzogen. Diese Datei mu?te weiterhin in sechs verschiedene Dateien aufgeteilt werden; diese wurden Gruppenherden genannt. Die verwendeten Modelle erlaubten additiv-genetische, maternal-genetische und permanente Umwelteffekte sowie das Vorhandensein einer Kovarianz zwischen additiv-genetischem und maternal-genetischem Effekt. Die Sch?tzwerte wurden über die Gruppenherden gepoolt. Die Ergebnisse in der Reihenfolge GG, AG, JG und EG waren 0,33, 0,35, 0,37 und 0,30 für die Heritabilit?ten sowie 0,074, 0,18 und 0,11 für die maternalen Heritabilit?ten (nicht gesch?tzt für EG). Signifikante Korrelationen zwischen direktem und maternal-genetischem Effekt (r(AM) ) existierten für AG und JG in der Gr??enordnung von -0,39 und -0,22. Trotz dieses Ergebnisses sind weitere Untersuchungen n?tig, weil die Sch?tzung von r(AM) problematisch ist.  相似文献   

20.
Data and pedigree information used in the present study were 3,022 records of kids obtained from the breeding station of Raini goat. The studied traits were birth weight (BW), weaning weight (WW), average daily gain from birth to weaning (ADG) and Kleiber ratio at weaning (KR). The model included the fixed effects of sex of kid, type of birth, age of dam, year of birth, month of birth, and age of kid (days) as covariate that had significant effects, and random effects direct additive genetic, maternal additive genetic, maternal permanent environmental effects and residual. (Co) variance components were estimated using univariate and multivariate analysis by WOMBAT software applying four animal models including and ignoring maternal effects. Likelihood ratio test used to determine the most appropriate models. Heritability ( \texth\texta2 ) \left( {{\text{h}}_{\text{a}}^2} \right) estimates for BW, WW, ADG, and KR according to suitable model were 0.12 ± 0.05, 0.08 ± 0.06, 0.10 ± 0.06, and 0.06 ± 0.05, respectively. Estimates of the proportion of maternal permanent environmental effect to phenotypic variance (c 2) were 0.17 ± 0.03, 0.07 ± 0.03, and 0.07 ± 0.03 for BW, WW, and ADG, respectively. Genetic correlations among traits were positive and ranged from 0.53 (BW-ADG) to 1.00 (WW-ADG, WW-KR, and ADG-KR). The maternal permanent environmental correlations between BW-WW, BW-ADG, and WW-ADG were 0.54, 0.48, and 0.99, respectively. Results indicated that maternal effects, especially maternal permanent environmental effects are an important source of variation in pre-weaning growth trait and ignoring those in the model redound incorrect genetic evaluation of kids.  相似文献   

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