989 resultados para GENETIC CORRELATION


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This study aimed to: a) to compare the covariance components obtained by Restricted Maximum Likelihood (REML) and by bayesian inference (BI): b) to run genetic evaluations for weights of Canchim cattle measured at weaning (W240) and at eighteen months of age (W550), adjusted or not to 240 and 550 days of age, respectively, using the mixed model methodology with covariance components obtained by REML or by BI; and c) to compare selection decisions from genetic evaluations using observed or adjusted weights and by REML or BI. Covariance components, heritabilities and genetic correlation for W240 and W550 were estimated and the predicted breeding values were used to select 10% and 50% of the best bulls and cows, respectively. The covariance components obtained by REML were smaller than the a posteriori means obtained by Bl. Selected animals from both procedures were not the same, probably because the covariance components and genetic parameters were different. The inclusion of age of animal at weighing as a covariate in the statistical model fitted by BI did not change the selected bulls and cows.

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The objective of this study was to evaluate the genotype x environment interaction for weaning and yearling weights, daily weight gain from weaning to 12 months of age and the growth performance in Canchim (5/8 Charolais + 3/8 Zebu) beef cattle estimated by a principal components analysis including those three traits. The environment was defined by season of birth (first and second semesters of the year). Genetic parameters were estimated by bayesian method with the Gibbs sampler using bivariate analyses (considering the trait in each of the two seasons as a different one) and models that included the fixed effects of year and month of birth, sex and age of cow (linear and quadratic) and the random effects of animal and residual. The results suggested that genetic evaluation and selection in Canchim beef cattle for the traits studied should consider the genotype and season of birth interaction.

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The objective of this work was to estimate, by meta-analysis, the heritability (h(2)) and the genetic (r(g)) and phenotypic (r(f)) correlations of residual feed intake (RFI), and of its component traits in beef cattle from 19 breeds or genetic groups. Twenty-two scientific papers published from 1963 to 2011, from eight countries, totaling 52,637 cattle of ages from 28 days up to slaughter, were evaluated. The estimates of RFI, dry matter intake (DMI), average daily gain (ADG) and metabolic weight (BW0.75) were weighted by the inverse of sample variance. The variation between studies of h(2) for each trait was analyzed by weighted least squares. The effects of sex, country and breed were significant for h(2) of RFI, explaining 67% of variation between studies. For DMI, country and breed effects were significant and explained 96% of variation. Pooled estimates of h(2) were: 0.255+/-0.008, 0.278+/-0.012, 0.321+/-0.015, and 0.397+/-0.032 for RFI, DMI, ADG and BW0.75, respectively. Pooled estimates of genetic and phenotypic correlations were low between RFI and ADG and between RFI and BW0.75 (from -0.021+/-0.034 to 0.025+/-0.035), and moderate between RFI and DMI (0.636+/-0.035 and 0.698+/-0.041) and between DMI, ADG and BW0.75 (0.441+/-0.062 to 0.688+/-0.032). The trait RFI has lower heritability estimates than its components.

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We conducted a two-way selection experiment in a composite rabbit population to investigate the responses to selection for postweaning ADG and feed conversion (FC). Two generations of crossing, followed by four generations of random pair matings, preceded three generations of selection. Selection was practiced within four lines: high-feed conversion (HFC), low-feed conversion (LFC), high gain (HG), and low gain (LG). Data on 1,446 rabbits from the random mating and selection generations were fitted to an animal model to estimate heritabilities of and the genetic correlation between ADG and FC. The two-trait model included rabbit and common litter random effects and line, generation, and sex fixed effects. Estimates of heritability of ADG and FC were .48 and .29, respectively, and the genetic correlation between them was -.82. Common litter environmental effects accounted for a proportion of .11 and . 13 of the phenotypic variation of the two traits, respectively. For ADG (in g/d) the regressions of mean breeding values on generation number during the selection period were 1.23 ± .12 (P < .01) in the HG line and -.86 ± .12 (P < .01) in the LG line; the regressions for FC (in g feed/g gain) were -.07 ± .01 (P < .01) in the HFC line and .03 ± .01 (P < .05) in the LFC line. Selection for ADG was effective in improving ADG and FC.

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Heterogeneity of variances for milk yield (MY) was determined for Brazilian and Colombian herds. The herds were grouped as high or low variability within each country, using as criterion the phenotypic standard deviation (PSD) of MY in the contemporary groups of cows, from the first to the sixth calving. Brazilian and Colombian herds with PSD greater than 1,168 kg or 1,012 kg, respectively, were classified as high variability while the herd groups with values lower than those were classified as low variability. The genetic parameters for MY within each herd group were estimated using bivariate analysis in an animal model and the restricted maximum likelihood method with a derivative free algorithm, using 72,280 first lactations of cows, daughters of 1,880 sires. Heterogeneous variances were found, and Brazilian herds with high PSD had the greatest additive and residual genetic variances and heritability coefficients for MY. MY genetic correlation coefficients between herds of high and low variability within each country were 0.96 and 0.93 while between countries they varied from 0.72 to 0.81, suggesting that there was a reclassification of animals in the two countries and also heterogeneity of variances. This phenomenon leads to the questioning of the strategy of imported semen usage and the need to do genetic evaluations to identify sires with greater genetic potential for (sub) tropical environmental conditions.

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The objective was to determine whether there is a genotype x environment interaction for age at first calving (AFC) in Holstein cattle in Brazil and Colombia. Data included 51,239 and 25,569 first-lactation records from Brazil and Colombia, respectively. Of 4230 sires in the data, 530 were North American sires used in both countries. Analyses were done using the REML bi-trait animal model, and AFC was considered as a distinct characteristic in each country. Fixed effects of contemporary group (herd-calving year), sire genetic group, and cow genetic group, and random effects of animal and residual variation were included in the model. Average AFC in Brazil and Colombia were 29.5 ± 4.0 and 32.1 ± 3.5 mo, respectively. Additive and residual genetic components and heritability coefficient for AFC in Brazil were 2.21 mo 2, 9.41 mo 2, and 0.19, respectively, whereas for Colombia, they were 1.02 mo 2, 6.84 mo 2, and 0.13, respectively. The genetic correlation of AFC between Brazil and Colombia was 0.78, indicating differences in ranking of sires consistent with a genotype x environment interaction. Therefore, in countries with differing environments, progeny of Holstein sires may calve at relatively younger or older ages compared with contemporary herdmates in one environment versus another.

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The objective of this work was to study the effect of selective thinning on the estimates of genetic parameters in progenies of Pinus caribaea var. hondurensis. The progeny test was installed in June 1986, following a 10 × 10, triple square lattice design, containing ten trees in linear plots in 3.0 × 3.0m spacing. Twelve years after the planting, a selective thinning based on Multi-effect index (selection for DBH) was performed, leaving six trees per plot. The assessments were done in four situations: A (before thinning); B (among thinned trees); C (among remnant trees at 13 years of age) and D (two years after the thinning). The following traits were analyzed: total height (H), diameter at breast height (DBH), volume (VOL), stem form (FOR), foxtail (FT), wood density at 1.3 m (WD1) and wood density at the half height (WD2). The thinning led to increase in the estimates of variability among progenies for VOL and decrease for ALT and DBH. There was a high and positive genetic correlation among the growth traits, mainly between DBH and VOL. The latter remained unchanged after thinning. The narrow-sense heritabilities at the individual level, showed a slight increase while at the family mean level had a reduction with the thinning. The estimates of breeding values increased with the thinning. This may lead to an easier identification of the best progenies in further selection.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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This study was conducted to estimate the genetic parameters for race times on turf and dirt tracks of Thoroughbred race horses. Data used were recorded by the Turftotal Ltd. for 343,419 racing performance of 26,713 animals, from January 1992 to January 2003. The model used in analysis included random animal and permanent environmental effects, and age, post position at start, sex and race as fixed effects. The variance and covariance components and the breeding value were estimated using the MTGSAM software. Heritability estimates were 0.29 for time on dirt track and 0.25 for time on turf track, indicating a moderate association between the animals' breeding values and their phenotypic values. Although genetic and environmental variances were smaller in turf tracks, their repeatability was equal to that of dirt (0.56), in terms of the highest estimated phenotypic variance for the latter type of track. The genetic correlation between times on different tracks was high (0.70). Considering the mean breeding value of the progeny of 465 stallions with 10 or more offspring, Spearman's correlation was 0.80, indicating that most Thoroughbred stallions produce offspring suited to both dirt and turf racing tracks.

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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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Objective of present work was study a influence of environmental and genetic effects over characteristics of milk total production (PL) and lactation duration (DL), from 2572 lactations of 477 Guzerat cows, collected since 1957 to 2002, in Rio de Janeiro State. Environmental effects were analyzed by an statistical model that include male randomized effect, fixed effect of contemporary group, and the (co)variables age of cow (lineal and quadratic) and lactation duration. The contemporary group had significant effect just for PL. Bayesian inference was used to obtain estimatives of genetic parameters over an animal model, in which was included as fixed effect the contemporary group and the covariables age of cow (linear and quadratic). The estimates of heritability and repeatability were 0.36 and 0.75 for PL and 0.29 and 0.36 for DL, respectively. The estimated genetic correlation was 0.97. The heritability estimates for PL and DL were moderate, indicating that it is possible answer to the selection of the characteristics under study. The genetic correlation was high and indicates that selection for increase milk production will be accompanied with increase in lactation duration.

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Background: The sequencing and publication of the cattle genome and the identification of single nucleotide polymorphism (SNP) molecular markers have provided new tools for animal genetic evaluation and genomic-enhanced selection. These new tools aim to increase the accuracy and scope of selection while decreasing generation interval. The objective of this study was to evaluate the enhancement of accuracy caused by the use of genomic information (Clarifide® - Pfizer) on genetic evaluation of Brazilian Nellore cattle. Review: The application of genome-wide association studies (GWAS) is recognized as one of the most practical approaches to modern genetic improvement. Genomic selection is perhaps most suited to the improvement of traits with low heritability in zebu cattle. The primary interest in livestock genomics has been to estimate the effects of all the markers on the chip, conduct cross-validation to determine accuracy, and apply the resulting information in GWAS either alone [9] or in combination with bull test and pedigree-based genetic evaluation data. The cost of SNP50K genotyping however limits the commercial application of GWAS based on all the SNPs on the chip. However, reasonable predictability and accuracy can be achieved in GWAS by using an assay that contains an optimally selected predictive subset of markers, as opposed to all the SNPs on the chip. The best way to integrate genomic information into genetic improvement programs is to have it included in traditional genetic evaluations. This approach combines traditional expected progeny differences based on phenotype and pedigree with the genomic breeding values based on the markers. Including the different sources of information into a multiple trait genetic evaluation model, for within breed dairy cattle selection, is working with excellent results. However, given the wide genetic diversity of zebu breeds, the high-density panel used for genomic selection in dairy cattle (Ilumina Bovine SNP50 array) appears insufficient for across-breed genomic predictions and selection in beef cattle. Today there is only one breed-specific targeted SNP panel and genomic predictions developed using animals across the entire population of the Nellore breed (www.pfizersaudeanimal.com), which enables genomically - enhanced selection. Genomic profiles are a way to enhance our current selection tools to achieve more accurate predictions for younger animals. Material and Methods: We analyzed the age at first calving (AFC), accumulated productivity (ACP), stayability (STAY) and heifer pregnancy at 30 months (HP30) in Nellore cattle fitting two different animal models; 1) a traditional single trait model, and 2) a two-trait model where the genomic breeding value or molecular value prediction (MVP) was included as a correlated trait. All mixed model analyses were performed using the statistical software ASREML 3.0. Results: Genetic correlation estimates between AFC, ACP, STAY, HP30 and respective MVPs ranged from 0.29 to 0.46. Results also showed an increase of 56%, 36%, 62% and 19% in estimated accuracy of AFC, ACP, STAY and HP30 when MVP information was included in the animal model. Conclusion: Depending upon the trait, integration of MVP information into genetic evaluation resulted in increased accuracy of 19% to 62% as compared to accuracy from traditional genetic evaluation. GE-EPD will be an effective tool to enable faster genetic improvement through more dependable selection of young animals.