989 resultados para Nellore cattle


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Heritability estimates and genetic correlations were obtained for body weight and scrotal circumference, adjusted, respectively, to 12 (BW12 and SC12) and 18 (BW18 and SC18) months of age, for 10 742 male Nellore cattle. The adjustments to SC12 and SC18 were made using a nonlinear logistic function, while BW12 and BW18 were obtained by linear adjustment. The contemporary groups (CGs) were defined from animals born on the same farm, in the same year and birth season. The mean heritability estimates obtained using the restricted maximum likelihood method in bi-trait analysis were 0.25, 0.25, 0.29 and 0.42 for BW12 BW18, SC12 and SC18, respectively. The genetic correlations were 0.30 +/- 0.11, 0.21 +/- 0.13, 0.21 +/- 0.11, -0.08 +/- 0.15, 0.16 +/- 0.12 and 0.89 +/- 0.04 between the traits BW12 and BW18; BW12 and SC12; BW12 and SC18; BW18 and SC12; BW18 and SC18; and SC12 and SC18. The heritability for SC18 was considerably greater than for SC12 suggesting that this should be included as a selection criterion. The genetic correlation between BW18 and SC12 was close to zero, indicating that these traits did not influence each other The contrary occurred between SC12 and SC18, indicating that selection using one of these could alter the other Because of the mean magnitudes of heritabilities in the various measurements of weight and scrotal perimeter it is suggested that the practice of individual selection for these traits is possible.

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

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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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Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. The objective of this study was to evaluate the predictive ability and goodness of fit of different models for the analysis of this trait in cross-bred Hereford x Nellore cattle. Three models were tested: a linear model using logarithmic transformation of the observations (MLOG); a linear model without transformation of the observations (MLIN); and a generalized linear Poisson model with residual term (MPOI). All models included the classificatory effects of contemporary group and genetic group and the covariates age of animal at the time of recording and individual heterozygosis, as well as additive genetic effects as random effects. Heritability estimates were 0.08 ± 0.02, 0.10 ± 0.02 and 0.14 ± 0.04 for MLIN, MLOG and MPOI models, respectively. The model fit quality, verified by deviance information criterion (DIC) and residual mean square, indicated fit superiority of MPOI model. The predictive ability of the models was compared by validation test in independent sample. The MPOI model was slightly superior in terms of goodness of fit and predictive ability, whereas the correlations between observed and predicted tick counts were practically the same for all models. A higher rank correlation between breeding values was observed between models MLOG and MPOI. Poisson model can be used for the selection of tick-resistant animals. © 2013 Blackwell Verlag GmbH.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Background: Birth weight (BW) is an economically important trait in beef cattle, and is associated with growth- and stature-related traits and calving difficulty. One region of the cattle genome, located on Bos primigenius taurus chromosome 14 (BTA14), has been previously shown to be associated with stature by multiple independent studies, and contains orthologous genes affecting human height. A genome-wide association study (GWAS) for BW in Brazilian Nellore cattle (Bos primigenius indicus) was performed using estimated breeding values (EBVs) of 654 progeny-tested bulls genotyped for over 777,000 single nucleotide polymorphisms (SNPs).Results: The most significant SNP (rs133012258, PGC = 1.34 × 10-9), located at BTA14:25376827, explained 4.62% of the variance in BW EBVs. The surrounding 1 Mb region presented high identity with human, pig and mouse autosomes 8, 4 and 4, respectively, and contains the orthologous height genes PLAG1, CHCHD7, MOS, RPS20, LYN, RDHE2 (SDR16C5) and PENK. The region also overlapped 28 quantitative trait loci (QTLs) previously reported in literature by linkage mapping studies in cattle, including QTLs for birth weight, mature height, carcass weight, stature, pre-weaning average daily gain, calving ease, and gestation length.Conclusions: This study presents the first GWAS applying a high-density SNP panel to identify putative chromosome regions affecting birth weight in Nellore cattle. These results suggest that the QTLs on BTA14 associated with body size in taurine cattle (Bos primigenius taurus) also affect birth weight and size in zebu cattle (Bos primigenius indicus). © 2013 Utsunomiya et al.; licensee BioMed Central Ltd.

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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.

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Advances in DNA technology have created biotechnological tools that can be used in animal selection and new strategies for increasing herd productivity and quality. The objective of the present work was to associate the genotypes of leptin gene exon 2 polymorphisms with productive traits in Nellore cattle. Blood was collected from Nellore males and PCR-RFLP reactions were performed with the restriction enzymes ClaI and Kpn2I. The gene frequencies resulting from digestion by ClaI were 0.60 and 0.40 for allele A and T, respectively; the genotypic frequencies were AA = 0.20 and AT = 0.80. The gene frequencies from digestion by Kpn2I were 0.81 for allele C and 0.194 for allele T; the genotypic frequencies were CC = 0.62 and CT = 0.38. The populations in both cases were not in Hardy-Weinberg equilibrium (p > 0.05), and the TT genotype was not found. Significant associations were noted between leptin gene exon 2 polymorphisms and five productive traits in Nellore cattle: carcass fat distribution, the intensity of red muscle coloration, pH, marbling, and post-slaughter fat thickness. © 2013 Copyright Taylor and Francis Group, LLC.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The aims of this study were to assess the validity and the feasibility of the qualitative behavior assessment (QBA) method as indicator of Nellore cattle temperament under field conditions, evaluating its associations with four other traditional methods and weight gain. The temperament and live weight of 2229 Nellore cattle was assessed at approximately 550 days of age. Five measurements of cattle temperament were recorded: flight speed test (FS, in m/s), visual scores of movement in the crush (MOV), crush score (CS), temperament score (TS), and the qualitative behavior assessment method (QBA), by using a list of 12 behavioral based adjectives as descriptors of temperament. Average daily weight gain (ADG) was calculated for each animal. For statistical analysis of QBA data, the Principal Component Analysis was used. A temperament index (TI) was defined for each animal using the scores for the first principal component. Pearson's correlation coefficients were estimated between TI with FS and ADG. A mixed model ANOVA was used to analyze the TI variation as a function of TS, CS, and MOV. The score plot for the first and second principal components was used to classify the cattle in four groups (from very bad to very good temperament). The first principal component explained 49.50% of the variation in the data set, with higher positive loadings for the adjectives 'agitated' and 'active', and higher negative loadings for 'calm' and 'relaxed'. TI was significantly correlated with FS (r=0.49; P<0.01) and ADG (r=-0.10; P<0.01). The means of ADG, FS, and the temperament scores (CS, TS, MOV) differed significantly (P<0.01) among the four groups, from very bad to very good temperament. The QBA method could discriminate different behavioral profiles of Nellore cattle and were in agreement with other traditional methods used as indicators of cattle temperament. Additional studies are needed to assess the inter- and intra-observers reliability and to study its association with physiological parameters. © 2013 Elsevier B.V.

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Pós-graduação em Genética e Melhoramento Animal - FCAV

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)