980 resultados para genetic correlations


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Descriptive herd variables (DVHE) were used to explain genotype by environment interactions (G x E) for milk yield (MY) in Brazilian and Colombian production environments and to develop a herd-cluster model to estimate covariance components and genetic parameters for each herd environment group. Data consisted of 180,522 lactation records of 94,558 Holstein cows from 937 Brazilian and 400 Colombian herds. Herds in both countries were jointly grouped in thirds according to 8 DVHE: production level, phenotypic variability, age at first calving, calving interval, percentage of imported semen, lactation length, and herd size. For each DVHE, REML bivariate animal model analyses were used to estimate genetic correlations for MY between upper and lower thirds of the data. Based on estimates of genetic correlations, weights were assigned to each DVHE to group herds in a cluster analysis using the FASTCLUS procedure in SAS. Three clusters were defined, and genetic and residual variance components were heterogeneous among herd clusters. Estimates of heritability in clusters 1 and 3 were 0.28 and 0.29, respectively, but the estimate was larger (0.39) in Cluster 2. The genetic correlations of MY from different clusters ranged from 0.89 to 0.97. The herd-cluster model based on DVHE properly takes into account G x E by grouping similar environments accordingly and seems to be an alternative to simply considering country borders to distinguish between environments.

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The genetic variation in the growth of seven 19-year-old Liquidambar styraciflua provenances was studied in Paraguaçu Paulista, São Paulo State, Brazil. The trial was established in a complete randomized block design with seven provenances, four replications and twelve-tree square plots. Significant differences among provenances were detected for diameter at breast height, height and volume, indicating the possibility of increasing timber yield through selection of the most productive provenances. Genetic correlations between growth traits were high and statistically significant. The provenance from Finca las Victorias, Guatemala had the best and the provenance from Franklin, Virginia, United States the poorest performance for all traits. A growth comparison of Pinus caribaea var. bahamensis with the best provenance at the same site indicated that the potential of L. styraciflua for silviculture in the region of Paraguaçu Paulista is high.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The aim of this study was estimate genetic, environmental and phenotypic correlations between movement and conformation traits in Mangalarga horses, in Brazil. The data were provided by Brazilian Association of Mangalarga Horses Breeders, comprised 9865 observations for movement and conformation traits. The data were organized by SAS, and the (co)variance components were estimated by the program MTGSAM. The heritabilities estimates varied from 0.22 (shoulder) to 0.29 (limbs), and the genetic correlations ranged from 0.51 (movement and neck) to 0.31 (movement and limbs).

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A total of 5575 monthly test-day yield records from 796 lactations buffaloes first in the north coast of Colombia. The model included random direct additive genetic and permanent environment effects. As fixed effects were included, contemporary groups, and age of cow at calving as covaraible, linear and quadratic effects. Test-day (PLDC) yield was 3.89 ± 1.14 kg. The PLDC ranged from 2.86 kg to 4.26 kg while the highest values towards the middle of lactation. The heritability estimates obtained for PLDC ranged from 0.23 to 0.47. Genetic correlations between PLDC, declining steadily increased the distance between PLDC. Phenotypic variances were higher in the initial PLDC and decreasing towards the end of lactation. The results found in this study indicate that there is a high genetic variability for the PLDC in the population studied using a random regression model.

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The objective of this study was to determine whether there is a genotype by environment interaction (GxE) for dairy buffaloes in Brazil and Colombia. The (co)variance components were estimated by using a bi-trait repeatability animal model with the REML method. Each trait consisted in the milk yield obtained in both countries. Contemporary group (herd, year and season of parity) and age at parity (linear and quadratic covariate) fixed effects, along with the additive genetic, permanent environment, and the residual random effects were included in the model. Genetic, permanent environmental and residual variance and heritabilities were different for both countries. The genetic correlations for milk yield between Brazil and Colombia were low (between 0.10 and 0.13), indicating a GxE interaction between both countries. Knowing that this interaction influences the genetic progress of buffalo populations in Brazil and Colombia, we recommend choosing sires tested in the country they will be used, along with conducting joint genetic evaluations that consider GxE interaction effects.

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The test-day model is the preferred method for genetic evaluations in dairy cattle. For this study, 28372 test-day records of 1220 lactations from 1997 to 2009 were used. The (co)variance components for milk in test-day were estimated using a Uni and multiple-traits repeated animal model with the Restricted Maximum Likelihood method (REML). The Contemporary Group (herd, year, and season of parity) and the age of parity (linear and quadratic) fixed effects, and the additive genetic, permanent environmental, and residual random effects were included in the model. The heritabilities ranged between 0.06 and 0.45 during lactation. The genetic correlations were greater than 0.93. In conclusion, the test-day model is appropriate for the genetic evaluation of dairy buffaloes in Colombia.

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Aiming to establish selection criteria for the Brahman cattle in Brazil, the objective of this paper was to estimate genetic and environmental parameters for birth weight (BW), gestation length (GL) and scrotal circumference at 365 (SC365), 455 (SC455) and 550 (SC 550) days of age, and relative efficiency of indirect versus direct selection for these traits. Data were obtained from 15 851 animals belonging to 16 herds in six states, enrolled in a genetic breeding program. (Co)variance and heritability coefficients and genetic and environmental correlations between traits were estimated by restricted maximum likelihood (REML) under a multi trait animal model. The model included as fixed effects the contemporary group and the age of cow at calving as a covariate (linear and quadratic), and as random the direct genetic, the permanent environmental and residual effects. For BW and GL it was also considered the maternal genetic effect as random. Estimates of direct heritabilities were 0.36, 0.29, 0.55, 0.43 and 0.40 for BW, GL, SC365, SC455 and SC550, respectively. Genetic correlations between BW and GL, GL and SC365, GL and SC455, GL and SC550, SC365 and SC455, SC365 and SC550 and SC455 and SC550, were respectively 0.06, 0.13, 0.20, 0.13, 0.96, 0.98 and 0.99. The heritabilities estimates for all traits indicated these show enough additive genetic variability to respond favorably to selection. For sexual precocity, the best option would be SC365, due to the high value of heritability and to indirect selection at this age being more efficient than direct selection for PE455.

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The objective of this study was to define production environments by grouping different environmental factors and, consequently, to assess genotype by production environment interactions on weaning weight (WW) in the Angus populations of Brazil and Uruguay. Climatic conditions were represented by monthly temperature means (°C), minimum and maximum temperatures in winter and summer respectively and accumulated rainfall (mm/year). Mode in month of birth and weaning, and calf weight (kg) and age (days) at weaning were used as indicators of management conditions of 33 and 161 herds in 13 and 34 regions in Uruguay and Brazil, respectively. Two approaches were developed: (a) a bi-character analysis of extreme sub-datasets within each environmental factor (bottom and top 33% of regions), (b) three different production environments (including farms from both countries) were defined in a cluster analysis using standardized environmental factors. To identify the variables that influenced the cluster formation, a discriminant analysis was previously carried out. Management (month, age and weight at weaning) and climatic factors (accumulated rainfalls and winter and summer temperatures) were the most important factors in the clustering of farms. Bi or trivariate analyses were performed to estimate heritability and genetic correlations for WW in extreme sub-datasets within environmental factor or between clusters, using MTDFREML software. Heritability estimates of WW in the first approach ranged from 0.27 to 0.54, and genetic correlations between top and bottom sub-datasets within environmental factors, from -0.29 to 0.70. In the cluster approach, heritabilities were 0.58±0.04 for cluster 1, 0.31±0.01 for Cluster 2 and 0.40±0.02 for Cluster 3. Genetic correlations were 0.27±0.08, 0.32±0.09 and 0.33±0.09, between clusters 1 and 2, 1 and 3, and 2 and 3, respectively. Both approaches suggest the existence of genotype x environment interaction for weaning weight in Angus breed of Brazil and Uruguay. © 2012 Elsevier B.V.

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The aim of this study was to estimate genetic parameters for growth traits in Somalis Brasileira hair sheep breed. The data used in this study were from the flock of Embrapa Caprinos and Ovinos, located in the city of Sobral - CE, Brazil. Data contained records of 1,120 animals in the pedigree file. The analyzed traits were birth weight (PN), weaning weight (PD), weight gain from birth to weaning (GND) and adult weight (PA). Estimates of (co)variances and genetic parameters were obtained by Derivative Free Restricted Maximum Likelihood Method (DFREML) using the MTDFREML software. The heritabilities were low to moderate in univariate analysis. The maternal heritabilities were higher than direct heritabilities. The heritabilities in multivariate analysis exceeded those in univariate analysis. The values of genetic correlations varied widely.

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The objectives of this study were to estimate genetic parameters involving yearling weight (Ps), carcass weight (Pc), hip height (Ag) and the scores of conformation (C), precocity (P) and musculature (M) and carcass yield (Rd) and finishing score (Ac) in Nellore cattle in order to define criteria for selection in this breed. The data of the 20 732 animals were obtained from Agrope-cuária Jacarezinho, SP. Data were analyzed by restricted maximum likelihood using animal model multi-trait analysis, which included fixed effects of contemporary groups (animals born at the same month and slaughtered on the same day) and the covariate age at slaughter (linear) for carcass traits, and contemporary groups (animals of the same farm, age, sex and management group at weaning and yearling) and yearling age (linear) for growth and as random, the additive effects and residual effects. Estimates ranged from 0.13 (Ac and Rd) to 0.36 (Ag) for heritability and from -0.59 ± 0.62 (Rd with Ac) to 0.71 ± 0.17 (Pc with C) for genetic correlations. Selection for Pc, C, P, M, Ag or Ps may be efficient because their heritability estimates are of magnitude moderate. Selection for Ps and C can favor heavier Pc, considering their positive and high genetic correlation.

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We analyzed 46,161 monthly test-day records of milk production from 7453 first lactations of crossbred dairy Gyr (Bos indicus) x Holstein cows. The following seven models were compared: standard multivariate model (M10), three reduced rank models fitting the first 2, 3, or 4 genetic principal components, and three models considering a 2-, 3-, or 4-factor structure for the genetic covariance matrix. Full rank residual covariance matrices were considered for all models. The model fitting the first two principal components (PC2) was the best according to the model selection criteria. Similar phenotypic, genetic, and residual variances were obtained with models M10 and PC2. The heritability estimates ranged from 0.14 to 0.21 and from 0.13 to 0.21 for models M10 and PC2, respectively. The genetic correlations obtained with model PC2 were slightly higher than those estimated with model M10. PC2 markedly reduced the number of parameters estimated and the time spent to reach convergence. We concluded that two principal components are sufficient to model the structure of genetic covariances between test-day milk yields. © FUNPEC-RP.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)