12 resultados para Heritable

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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

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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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The advent of molecular markers has created opportunities for a better understanding of quantitative inheritance and for developing novel strategies for genetic improvement of agricultural species, using information on quantitative trait loci (QTL). A QTL analysis relies on accurate genetic marker maps. At present, most statistical methods used for map construction ignore the fact that molecular data may be read with error. Often, however, there is ambiguity about some marker genotypes. A Bayesian MCMC approach for inferences about a genetic marker map when random miscoding of genotypes occurs is presented, and simulated and real data sets are analyzed. The results suggest that unless there is strong reason to believe that genotypes are ascertained without error, the proposed approach provides more reliable inference on the genetic map.

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Some modifying factors may determine the risk of brain tumors. Until now, it could not be attempted to identify people at risk and also to improve significantly disease progression. Current therapy consists of surgical resection, followed by radiation therapy and chemotherapy. Despite of these treatments, the prognosis for patients is poor. In this review, we highlight general aspects concerning genetic alterations in brain tumors, namely astrocytomas, glioblastomas, oligodendrogliomas, medulloblastomas and ependymomas. The influence of these genetic alterations in patients' prognosis is discussed. Mutagen sensivity is associated with cancer risk. The convincing studies that linked DNA damages and DNA repair alterations with brain tumors are also described. Another important modifying factor is immunity. General immune response against cancer, tumor microenvironment and immune response, mechanisms of tumor escape, CNS tumor immunology, immune defects that impair anti-tumor systemic immunity in brain tumor patients and local immunosuppressive factors within CNS are also reviewed. New hope to treatment perspectives, as dendritic-cell-based vaccines is summarized too. Concluding, it seems well established that there is association between brain tumor risk and mutagen sensivity, which is highly heritable. Primary brain tumors cause depression in systemic host immunity; local immunosuppressive factors and immunological characteristics of tumor cells may explain the poor prognosis and DNA damages responses can alert immune system. However, it is necessary to clarify if individuals with both constitutional defects in immune functions and genetic instability have higher risk of developing brain tumors. Cytogenetic prospective studies and gene copy number variations analysis also must be performed in peripheral lymphocytes from brain tumor patients. © 2011 Bentham Science Publishers Ltd.

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

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Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and Bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. © 2013 American Dairy Science Association.

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Pós-graduação em Zootecnia - FCAV

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Pós-graduação em Genética e Melhoramento Animal - FCAV

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Pós-graduação em Genética e Melhoramento Animal - FCAV

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Pós-graduação em Agronomia (Proteção de Plantas) - FCA

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Age at puberty in beef heifers can influence economic efficiency of beef production through effects on both age at first calving (2 vs. 3+ years of age) and the time of conception of heifers in their initial breeding season. An overarching factor that influences age at puberty in heifers is nutritional management during both the preweaning period and between weaning and the breeding season. Age at puberty is heritable and selection for precocious puberty in populations such as the Nelore breed has the potential to substantially influence production efficiency. Highly effective hormonal technologies exist to aid in induction of puberty in well managed heifers. Age at first ovulation and pregnancy in heifers can be substantially influenced through implementation of nutritional and/or hormonal manipulation strategies. In the long term, combinations of genetic selection, nutritional strategies, and hormonal intervention when necessary will optimize efficiency of this aspect of beef production.