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EN
A method for the detection of segregating major genes based on the analysis of estimated marginal posterior major gene variance density was examined. The properties of the method were investigated using data sets simulated for a real population of laying hens consisting of eleven generations. Marginal posterior densities of model parameters were estimated by the Gibbs sampling approach proposed by JANSS et al. (1995). With the data of about 4000 observations it was possible to detect a major gene responsible for one third of the genetic variance and one tenth of the phenotypic variance, irrespectively of the degree of dominance at the major locus. The inference based on the posterior marginal major gene variance can be sensitive to skewness of the data. It was shown that skewness of 0.2 can lead to a false detection of a major gene. The method is robust against a non-genetic mixture of normal distributions.
EN
Despite the use of antibiotics, the prognosis of bacterial meningitis is still poor due to central nervous system (CNS) complications, such as brain edema formation, cerebrovascular alterations, and intracranial hemorrhage. Experimental studies with animal models have given new insights into its pathophysiology during the acute phase of the disease. In recent years, genetically engineered mice have become a powerful tool in investigating the role of particular genes by targeted deletion and have also been applied in bacterial meningitis research. By using knockout mice, new knowledge of the roles of the different cytokines, proteases, and oxidants involved in the inflammatory cascade has emerged. In the future, temporal and cell type-specific control of gene expression will provide even more information on the impact of a particular gene on meningitis-induced brain damage.
EN
This study presents a new approach to obtain dominance estimates without using the full Henderson?s mixed model equations (MMEs) related to an additive plus dominance animal model. This reduction could decrease substantially the computing time and hence its cost. In contrast to a procedure that we proposed before, the method developed in this paper does not require D?1 and provides best linear unbiased prediction (BLUP) of genetic values that is close to that given by processing the full MMEs. In the previous study, we also elaborated an algorithm (denoted ?-REML) in order to approximate restricted maximum likelihood estimation of variance components via the expectation maximization (EM) algorithm. The ?-REML algorithm has been modified to be adapted to our new resolution approach. Through a numerical example, we show that there is a good agreement between REML-(EM), ?-REML and modified ?-REML estimates and that the latter algorithm is more efficient than our first proposition in terms of computing time and memory conservation.
EN
The selection index and single- and multi-trait animal models were used for genetic evaluation of 100,983 cows. Genetic and environmenta? al (co)variances of five milk production traits were estimated using MTDFREML. The highest heritabilities were found for fat and protein contents in all three lactations (0.29-0.33), and the lowest for protein yield in the third lactation (0.08). Phenotypic and genetic correlations between yield traits in adjacent lactations were higher than between the first and third lactations. Correlations between breeding values for fat content were higher than for yield traits. The magnitude of correlations between the index and animal model evaluations depended on the number of lactation records included in both procedures. Usually the relationships between breeding values based on the same lactations were close to unity. The correlations between single-trait and multi-trait evaluations decreased with increasing numbers of lactations in the model. This was the result of using variances and covariances of later lactations in the multi-trait model.
EN
Henderson's mixed model equations system is generally required in a Gibbs sampling application. In two previous studies, we proposed two indirect solving approaches that give dominance values in an animal model context with no need to process all this system. The first one does not require D-1 and the second is based on processing the additive animal model residuals. In the present work, we show that these two methods can be handled iteratively. Since the Bayesian approach is now a widely used tool in estimation of genetic parameters, the main part of this work is devoted to a Gibbs sampling application that can be accelerated by means of the aforementioned indirect solving methods. Three replicates of a population data set are simulated in the paper to compare the applications and estimates. This shows effectively that the estimates given by implementing a Gibbs sampler with each of the two suggested solving methods are obtained with less computational time and are comparable to those given by considering the integral system, particularly when priors are more weighted.
EN
The etiology and pathogenesis of inflammatory bowel disease (IBD) remains unsolved but improved experimental models of enterocolitis have led to progress. Intestinal inflammation can be induced by chemical or dietary factors or by microbial products and experimental IBD. Many animal models of IBD can be used to evaluate new anti-inflammatory drugs. These models, however, usually demonstrate acute, self-limiting colitis. The spontaneous colitis models developed in the monkey, cotton-top tamarin, and C3H/HeJBir mouse mimic more features of human IBD. Inflammation is chronic and is under genetic control. The differential genetic susceptibility of inbred rat strains to chronic inflammation have been exploited. Lewis rats injected with bacterial products, peptidoglycan polysaccharide or indomethicin develop chronic relapsing enterocolitis, whereas closely related Buffalo or Fisher rat strains develop only transient inflammation and the specific inhibition of inflammatory mediators and target molecules have been tested. Over-expression (transgenic) or deletion (knockout) of specific genes have led to the development of rodent models of spontaneous colitis. Inflammation arises from a number of mutations of immunomodulatory molecules supporting the concept of genetic heterogeneity for IBD. The results obtained from experimental models have generated new hypotheses, expanded human studies, and suggested novel forms of therapy for IBD patients.
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2009
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vol. 59
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issue 1
57-66
EN
Sjogren's syndrome (SjS) is chronic autoimmune disease manifested by the loss of saliva and/or tear secretion by salivary and/or lacrimal glands, respectively. The pathogenesis of the disease remains elusive, perhaps due to the multiple triggers of the disease. However, substantial advances have been made in attempting to resolve the complexity of SjS using both animal models and human subjects. The primary objectives of this review are to provide a better understanding of the disease processes with major emphasis on the use of mouse models, how genetic predisposition plays a role in the natural history of the disease, as well as a presentation of new findings pertaining to the role of TH1, TH2, and TH17 cells in the pathogenesis of SjS.
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