996 resultados para MULTIPLE-TRAIT


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Foram analisados registros de 1.698 animais de um rebanho Caracu selecionado para peso pós-desmame entre os anos 1979 e 2002 com o objetivo de verificar a existência de variabilidade genética aditiva nas características de crescimento e suas interpretações. As características analisadas foram: peso ao nascer (PN), peso padronizado aos 120 dias (P120), peso ao desmame padronizado aos 210 dias (P210), peso de machos ao final da prova de ganho de peso (P378) e ganhos diários do nascimento ao desmame (GND), dos machos na prova de ganho de peso (G112), do desmame ao sobreano em machos (GDSm), peso de fêmeas padronizado aos 550 dias (P550) e ganhos das fêmeas em pastagem do desmame ao sobreano (GDSf), além da altura da garupa a um ano em machos (ALTm) e ao sobreano em fêmeas (ALTf). Os componentes de (co) variâncias, as herdabilidades e as correlações genéticas foram estimados por máxima verossimilhança restrita não-derivativa utilizando-se o software MTDFREML. As estimativas de herdabilidade e os erros-padrão foram iguais a 0,34±0,06; 0,11±0,05; 0,13±0,05; 0,11±0,05; 0,35±0,09; 0,42±0,09; 0,31±0,09; 0,13±0,06; 0,21±0,08; 0,55±0,11; 0,51±0,09 para PN, P120, P210, GND, P378, P550, GDSm, GDSf, G112, ALTm e ALTf, respectivamente. As correlações genéticas entre as características foram de moderadas a altas e positivas, com exceção de algumas correlações com a característica GDSf e o PN. A seleção com base no desempenho do próprio indivíduo, como tem sido realizada, proporciona progresso genético nas características de seleção direta, assim como em algumas características com alta correlação genética.

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Objetivou-se com este trabalho estimar as herdabilidades (h²) e as correlações genéticas (r g) entre idade ao primeiro parto (IPP) e primeiro intervalo de partos (PIEP) e outras características como peso (PS) ao ano (A) e ao sobreano (S), altura do posterior (ALT) e perímetro escrotal (PE450) em animais da raça Nelore. Os parâmetros genéticos foram estimados em uma análise multicaracterística por modelo animal, utilizando-se a inferência bayesiana via algoritmo de Gibbs Sampling. Os parâmetros genéticos estimados sugerem a existência de variabilidade genética para IPP (h² = 0,26), sendo que a seleção para a diminuição da IPP de fêmeas Nelore deve responder à seleção individual, sem causar antagonismo do valor genético dos animais para PS (r g = -0,22 (A) e -0,44 (S)) e PE450 (r g = 0,02). A seleção para a diminuição da IPP, no longo prazo, pode levar a um aumento da ALT dos animais, embora essa associação seja relativamente baixa (-0,35). A estimativa de herdabilidade a posteriori para a característica PIEP foi baixa, 0,11±0,03. As r g entre PIEP e as demais características estudadas indicam que a seleção para essas características de crescimento não afetará o PIEP.

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

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The objective of this study was to apply factor analysis to describe lactation curves in dairy buffaloes in order to estimate the phenotypic and genetic association between common latent factors and cumulative milk yield. A total of 31 257 monthly test-day milk yield records from buffaloes belonging to herds located in the state of São Paulo were used to estimate two common latent factors, which were then analysed in a multi-trait animal model for estimating genetic parameters. Estimates of (co)variance components for the two common latent factors and cumulated 270-d milk yield were obtained by Bayesian inference using a multiple trait animal model. Contemporary group, number of milkings per day (two levels) and age of buffalo cow at calving (linear and quadratic) as covariate were included in the model as fixed effects. The additive genetic, permanent environmental and residual effects were included as random effects. The first common latent factor (F1) was associated with persistency of lactation and the second common latent factor (F2) with the level of production in early lactation. Heritability estimates for Fl and F2 were 0.12 and 0.07, respectively. Genetic correlation estimates between El and F2 with cumulative milk yield were positive and moderate (0.63 and 0.52). Multivariate statistics employing factor analysis allowed the extraction of two variables (latent factors) that described the shape of the lactation curve. It is expected that the response to selection to increase lactation persistency is higher than the response obtained from selecting animals to increase lactation peak. Selection for higher total milk yield would result in a favourable correlated response to increase the level of production in early lactation and the lactation persistency.

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The information in this study has been provided by the Brazilian Association of Racehorse Breeders [Associação do Brasileira dos Criadores do Cavalo de Corrida (ABCCC)]. It can be found in the files on the CD-ROM developed by the ABCCC in 1999. A total of 5008 finishing time records related to 2545 winning horses that ran in the classical calendar on Brazilian hippodromes during 25 years (197498) were analysed. There were a total of 9949 horses on the relationship matrix. The variance components were estimated using the multiple-trait derivate-free restricted maximum likelihood (MTDFREML) program, for an animal model. Generation intervals were higher in the maternal side (10.91 years) than in the paternal one (10.41 years). The estimates for genetic permanent environmental and phenotypic variances and heritability were 0.291, 0.161, 3.486 and 0.08, respectively. The phenotypic standard deviation for time in races was 1.86729 s. Genetic time trend on Thoroughbred races in Brazil was small and could be accelerated if selection considered the trait time effectively. With respect to the animal's country of birth, the results show that there has been an intense participation of foreign animals in breeding Brazilian Thoroughbreds.

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

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

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

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The objective of this study was to estimate the relative effects of genetic and phenotypic factors on the efficacy and efficiency of superovulation for Holstein-Friesian cows reared in Brazil. A database, established by the Associacao Brasileira de Criadores de Bovinos da Raca Holandesa, consisting of a total of 5387 superovulations of 2941 cows distributed over 473 herds and sired by 690 bulls was used for the analysis. The records were analyzed by MTDFREML (Multiple Trait Derivative-Free Restricted Maximum Likelihood), using a repeatability animal model. The fixed effects included in the model were contemporaneous group (veterinarian, herd, year and season of the superovulation); number of semen doses; cow age; and superovulation order. The estimated repeatability of the number of the transferable embryos was low (0.13), and the estimated heritability was 0.03. These results indicate that environmental factors play a critical role in the response of a cow to a superovulation treatment. There is little evidence that future responses to superovulation by individual females can be predicted by previous treatment(s) or that superovulation response is an heritable trait.

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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.

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The objective of this study was to evaluate the effect of genotype by environment interaction (GEI) on the weight of Tabapuã cattle at 240 (W240), 365 (W365) and 450 (W450) days of age. In total, 35,732 records of 8,458 Tabapuã animalswhich were born in the state of Bahia, Brazil, from 1975 to 2001, from 167 sires and 3,707 dams, were used. Two birth seasons were tested as for the environment effect: the dry (D) and rainy (R) ones. The covariance components were obtainedby a multiple-trait analysis using Bayesian inference, in which each trait was considered as being different in each season. Covariance components were estimated by software gibbs2f90. As for W240, the model was comprised of contemporary groups and cow age (in classes) as fixed effects; animal and maternal genetic additive, maternal permanent environmental and residual were considered as random effects. Concerning W365 and W450, the model included only the contemporary aged cow groups as fixed effects and the genetic additive and residual effects of the animal as the random ones. The GEI was assessed considering the genetic correlation, in which values below 0.80 indicated the presence of GEI. Regarding W365 and W450, the GEI was found in both seasons. As for post-weaning weight (W240), the effect of such interaction was not observed. ©2012 Sociedade Brasileira de Zootecnia.

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A total of 61,528 weight records from 22,246 Nellore animals born between 1984 and 2002 were used to compare different multiple-trait analysis methods for birth to mature weights. The following models were used: standard multivarite model (MV), five reduced-rank models fitting the first 1, 2, 3, 4 and 5 genetic principal components, and five models using factor analysis with 1, 2, 3, 4 and 5 factors. Direct additive genetic random effects and residual effects were included in all models. In addition, maternal genetic and maternal permanent environmental effects were included as random effects for birth and weaning weight. The models included contemporary group as fixed effect and age of animal at recording (except for birth weight) and age of dam at calving as linear and quadratic effects (for birth weight and weaning weight). The maternal genetic, maternal permanent environmental and residual (co)variance matrices were assumed to be full rank. According to model selection criteria, the model fitting the three first principal components (PC3) provided the best fit, without the need for factor analysis models. Similar estimates of phenotypic, direct additive and maternal genetic, maternal permanent environmental and residual (co)variances were obtained with models MV and PC3. Direct heritability ranged from 0.21 (birth weight) to 0.45 (weight at 6 years of age). The genetic and phenotypic correlations obtained with model PC3 were slightly higher than those estimated with model MV. In general, the reduced-rank model substantially decreased the number of parameters in the analyses without reducing the goodness-of-fit. © 2013 Elsevier B.V.

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The objective of this study was to estimate genetic parameters for female mature weight (FMW), age at first calving (AFC), weight gain from birth to 120 days (WG_B_120), from 210 to 365 days (WG_210_365), rib eye area (REA), back fat thickness (BF), rump fat (RF) and body weight at scanning date (BWS) using single and multiple-trait animal models by the REML method from Nellore cattle data. The estimates of heritability ranged from 0.163±0.011 for WG_210_365 to 0.309±0.028 for RF using the single-trait model and from 0.163±0.010 for WG_210_365 to 0.382±0.025 for BWS using the multiple-trait model. The estimates of genetic correlations ranged from -0.35±0.08 between AFC with BF to 0.69±0.04 between WG_B_120 with BWS. Selection for weights gains, REA, and BWS can improve FMW. © 2013 Elsevier B.V.