954 resultados para Genotype-by-environment interaction


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The aim of this study was to estimate genetic parameters for milk yield (MY) in buffaloes using reaction norms. Model included the additive direct effect as random and contemporary group (herd and year of birth) were included as fixed effects and cow age classes (linear) as covariables. The animal additive direct random effect was modeled through linear Legendre polynomials on environment gradient (EG) standardized means. Mean trends were taken into account by a linear regression on Legendre polynomials of environmental group means. Residual variance was modeled trough 6 heterogeneity classes (EG). These classes of residual variance was formed : EG1: mean = 866,93 kg (621,68 kg-1011,76 kg); EG2: mean = 1193,00 kg (1011,76 kg-1251,49 kg); EG3: mean = 1309,37 kg (1251,49 kg -1393,20 kg); EG4: mean = 1497,59 kg (1393,20 kg-1593,53 kg); EG5: mean = 1664,78 kg (1593,53 kg -1727,32kg) e EG6: mean = 1973,85 kg (1727,32 kg -2422,19 kg).(Co) variance functions were estimated by restricted maximum likelihood (REML) using the GIBBS3F90 package. The heritability estimates for MY raised as the environmental gradient increased, varying from 0.20 to 0.40. However, in intermediate to favorable environments, the heritability estimates obtained with Considerable genotype-environment interaction was found for MY using reaction norms. For genetic evaluation of MY is necessary to consider heterogeneity of variances to model the residual variance.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Aim: To evaluate the association between polymorphisms XRCC1 Arg194Trp and Arg399Gln and XRCC3 Thr241Met and the risk for chronic gastritis and gastric cancer, in a Southeastern Brazilian population. Methods: Genotyping by PCR-RFLP was carried out on 202 patients with chronic gastritis (CG) and 160 patients with gastric cancer (GC), matched to 202 (C1) and 150 (C2) controls, respectively. Results: No differences were observed among the studied groups with regard to the genotype distribution of XRCC1 codons 194 and 399 and of XRCC3 codon 241. However, the combined analyses of the three variant alleles (194Trp, 399Gln and 241Met) showed an increased risk for chronic gastritis when compared to the GC group. Moreover, an interaction between the polymorphic alleles and demographic and environmental factors was observed in the CG and GC groups. XRCC1 194Trp was associated with smoking in the CG group, while the variant alleles XRCC1 399Gln and XRCC3 241Met were related with gender, smoking, drinking and H pylori infection in the CG and GC groups. Conclusion: Our results showed no evidence of a rela-tionship between the polymorphisms XRCC1 Arg194Trp and Arg399Gln and XRCC3 Thr241Met and the risk of chronic gastritis and gastric cancer in the Brazilian population, but the combined effect of these variants may interact to increase the risk for chronic gastritis, considered a premalignant lesion. Our data also indicate a gene-environment interaction in the susceptibility to chronic gastritis and gastric cancer. © 2005 The WJG Press and Elsevier Inc. All rights reserved.

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Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.

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Seven years of multi-environment yield trials of navy bean (Phaseolus vulgaris L.) grown in Queensland were examined. As is common with plant breeding evaluation trials, test entries and locations varied between years. Grain yield data were analysed for each year using cluster and ordination analyses (pattern analyses). These methods facilitate descriptions of genotype performance across environments and the discrimination among genotypes provided by the environments. The observed trends for genotypic yield performance across environments were partly consistent with agronomic and disease reactions at specific environments and also partly explainable by breeding and selection history. In some cases, similarities in discrimination among environments were related to geographic proximity, in others management practices, and in others similarities occurred between geographically widely separated environments which differed in management practices. One location was identified as having atypical line discrimination. The analysis indicated that the number of test locations was below requirements for adequate representation of line x environment interaction. The pattern analyses methods used were an effective aid in describing the patterns in data for each year and illustrated the variations in adaptive patterns from year to year. The study has implications for assessing the number and location of test sites for plant breeding multi-environment trials, and for the understanding of genetic traits contributing to line x environment interactions.

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Background: The angiotensin-converting enzyme (ACE) insertion/deletion (I/D) polymorphism gene contributes to the genesis of hypertension (HTN) and may help explain the relationship between obstructive sleep apnea (OSA) and HTN. However, ACE is a pleiotropic gene that has several influences, including skeletal muscle and control of ventilation. We therefore tested the hypothesis that ACE polymorphism influences OSA severity. Methods: Male OSA patients (apnea-hypopnea index [AHI] > 5 events/h) from 2 university sleep centers were evaluated by polysomnography and ACE I/D polymorphism genotyping. Results: We studied 266 males with OSA (age = 48 +/- 13y, body mass index = 29 5kg/m(2), AHI = 34 +/- 25events/h). HTN was present in 114 patients (43%) who were older (p < 0.01), heavier (p < 0.05) and had more severe OSA (p < 0.01). The I allele was associated with HTN in patients with mild to moderate OSA (p < 0.01), but not in those with severe OSA. ACE I/D polymorphism was not associated with apnea severity among normotensive patients. In contrast. the only variables independently associated with OSA severity among patients with hypertension in multivariate analysis were BMI (OR = 1.12) and 11 genotype (OR = 0.27). Conclusions: Our results indicate reciprocal interactions between OSA and HTN with ACE I/D polymorphism, suggesting that among hypertensive OSA males, the homozygous ACE I allele protects from severe OSA. (C) 2009 Elsevier B.V. All rights reserved.

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Pearl millet landraces from Rajasthan, India, yield significantly less than improved cultivars under optimum growing conditions, but not under stressed conditions. To successfully develop a simulation model for pearl millet, capable of capturing such genotype x environment (G x E) interactions for grain yield, we need to understand the causes of the observed yield interaction. The aim of this paper is to quantify the key parameters that determine the accumulation and partitioning of biomass: the,light extinction coefficient, radiation use efficiency (RUE), pattern of dry matter allocation to the leaf blades, the determination of grain number, and the rate and duration of dry matter accumulation into individual grains. We used data on improved cultivars and landraces, obtained from both published and unpublished sources collected at ICRISAT, Patancheru, India. Where possible, the effects of cultivar and axis (main shoot vs. tillers) on these parameters were analysed, as previous research suggested that G x E interactions for grain yield are associated with differences in tillering habit. Our results indicated there were no cultivar differences in extinction coefficient, RUE, and biomass partitioning before anthesis, and differences between axes in biomass partitioning were negligible. This indicates there was no basis for cultivar differences in the potential grain yield. Landraces, however, produced consistently less grain yield for a given rate of dry matter accumulation at anthesis than did improved cultivars. This was caused by a combination of low grain number and small grain size. The latter was predominantly due to a lower grain growth rate, as genotypic differences in the duration of grain filling were relatively small. Main shoot and tillers also had a similar duration of grain filling. The low grain yield of the landraces was associated with profuse nodal tillering, supporting the hypothesis that grain yield was below the potential yield that could be supported by assimilate availability. We hypothesise this is a survival strategy, which enhances the prospects to escape the effects of stress around anthesis. (C) 2002 E.J. van Oosterom. Published by Elsevier Science B.V. All rights reserved.

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Due to their toxicity, especially their carcinogenic potential, polycyclic aromatic hydrocarbons (PAHs) became priority pollutants in biomonitoring programmes and environmental policy, such as the European Water Framework Directive. The model substances tested in this study, namely benzo[b]fluoranthene (B[b]F), considered potentially carcinogenic to humans and an effector carcinogenic PAH to wildlife, and phenanthrene (Phe), deemed a non-carcinogenic PAH, are common PAHs in coastal waters, owning distinct properties reflected in different, albeit overlapping, mechanisms of toxicity. Still, as for similar PAHs, their interaction effects remain largely unknown. In order to study the genotoxic effects of caused by the interaction of carcinogenic and non-carcinogenic PAHs, and their relation to histopathological alterations, juvenile sea basses, Dicentrarchus labrax, a highly ecologically- and economically-relevant marine fish, were injected with different doses (5 and 10 μg.g-1 fish ww) of the two PAHs, isolated or in mixture, and incubated for 48 h. Individuals injected with B[b]F and the PAH mixture exhibited higher clastogenic/aneugenic effects and DNA strand breakage in blood cells, determined through the erythrocytic nuclear abnormalities (ENA) and Comet assays, respectively. Also, hepatic histopathological alterations were found in all animals, especially those injected with B[b]F and the PAH mixture, relating especially to inflammation. Still, Phe also exhibited genotoxic effects in sea bass, especially in higher doses, revealing a very significant acute effect that was accordant with the Microtox test performed undergone in parallel. Overall, sea bass was sensitive to B[b]F (a higher molecular weight PAH), likely due to efficient bioactivation of the pollutant (yielding genotoxic metabolites and reactive oxygen species), when compared to Phe, the latter revealing a more significant acute effect. The results indicate no significant additive effect between the substances, under the current experimental conditions. The present study highlights the importance of understanding PAH interactions in aquatic organisms, since they are usually present in the aquatic environment in complex mixtures.

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BACKGROUND: The link between host MHC (major histocompatibility complex) genotype and malaria is largely based on correlative data with little or no experimental control of potential confounding factors. We used an experimental mouse model to test for main effects of MHC-haplotypes, MHC heterozygosity, and MHC x parasite clone interactions. We experimentally infected MHC-congenic mice (F2 segregants, homo- and heterozygotes, males and females) with one of two clones of Plasmodium chabaudi and recorded disease progression. RESULTS: We found that MHC haplotype and parasite clone each have a significant influence on the course of the disease, but there was no significant host genotype by parasite genotype interaction. We found no evidence for overdominance nor any other sort of heterozygote advantage or disadvantage. CONCLUSION: When tested under experimental conditions, variation in the MHC can significantly influence the course of malaria. However, MHC heterozygote advantage through overdominance or dominance of resistance cannot be assumed in the case of single-strain infections. Future studies might focus on the interaction between MHC heterozygosity and multiple-clone infections.

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BACKGROUND: A central question for understanding the evolutionary responses of plant species to rapidly changing environments is the assessment of their potential for short-term (in one or a few generations) genetic change. In our study, we consider the case of Pinus pinaster Aiton (maritime pine), a widespread Mediterranean tree, and (i) test, under different experimental conditions (growth chamber and semi-natural), whether higher recruitment in the wild from the most successful mothers is due to better performance of their offspring; and (ii) evaluate genetic change in quantitative traits across generations at two different life stages (mature trees and seedlings) that are known to be under strong selection pressure in forest trees. RESULTS: Genetic control was high for most traits (h2 = 0.137-0.876) under the milder conditions of the growth chamber, but only for ontogenetic change (0.276), total height (0.415) and survival (0.719) under the more stressful semi-natural conditions. Significant phenotypic selection gradients were found in mature trees for traits related to seed quality (germination rate and number of empty seeds). Moreover, female relative reproductive success was significantly correlated with offspring performance for specific leaf area (SLA) in the growth chamber experiment, and stem mass fraction (SMF) in the experiment under semi-natural conditions, two adaptive traits related to abiotic stress-response in pines. Selection gradients based on genetic covariance of seedling traits and responses to selection at this stage involved traits related to biomass allocation (SMF) and growth (as decomposed by a Gompertz model) or delayed ontogenetic change, depending also on the testing environment. CONCLUSIONS: Despite the evidence of microevolutionary change in adaptive traits in maritime pine, directional or disruptive changes are difficult to predict due to variable selection at different life stages and environments. At mature-tree stages, higher female effective reproductive success can be explained by differences in their production of offspring (due to seed quality) and, to a lesser extent, by seemingly better adapted seedlings. Selection gradients and responses to selection for seedlings also differed across experimental conditions. The distinct processes involved at the two life stages (mature trees or seedlings) together with environment-specific responses advice caution when predicting likely evolutionary responses to environmental change in Mediterranean forest trees.

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The permeability-glycoprotein efflux-transporter encoded by the multidrug resistance 1 (ABCB1) gene and the cytochromes P450 3A4/5 encoded by the CYP3A4/5 genes are known to interact in the transport and metabolism of many drugs. Recent data have shown that the CYP3A5 genotypes influence blood pressure and that permeability-glycoprotein activity might influence the activity of the renin-angiotensin system. Hence, these 2 genes may contribute to blood pressure regulation in humans. We analyzed the association of variants of the ABCB1 and CYP3A5 genes with ambulatory blood pressure, plasma renin activity, plasma aldosterone, endogenous lithium clearance, and blood pressure response to treatment in 72 families (373 individuals; 55% women; mean age: 46 years) of East African descent. The ABCB1 and CYP3A5 genes interact with urinary sodium excretion in their effect on ambulatory blood pressure (daytime systolic: P=0.05; nighttime systolic and diastolic: P<0.01), suggesting a gene-gene-environment interaction. The combined action of these genes is also associated with postproximal tubular sodium reabsorption, plasma renin activity, plasma aldosterone, and with an altered blood pressure response to the angiotensin-converting enzyme inhibitor lisinopril (P<0.05). This is the first reported association of the ABCB1 gene with blood pressure in humans and demonstration that genes encoding for proteins metabolizing and transporting drugs and endogenous substrates contribute to blood pressure regulation.

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BACKGROUND AND AIM: Familial Mediterranean fever (FMF) is an autoinflammatory disease caused by mutations of the MEFV gene. We analyse the impact of ethnic, environmental and genetic factors on the severity of disease presentation in a large international registry. METHODS: Demographic, genetic and clinical data from validated paediatric FMF patients enrolled in the Eurofever registry were analysed. Three subgroups were considered: (i) patients living in the eastern Mediterranean countries; (ii) patients with an eastern Mediterranean ancestry living in western Europe; (iii) Caucasian patients living in western European countries. A score for disease severity at presentation was elaborated. RESULTS: Since November 2009, 346 FMF paediatric patients were enrolled in the Eurofever registry. The genetic and demographic features (ethnicity, age of onset, age at diagnosis) were similar among eastern Mediterranean patients whether they lived in their countries or western European countries. European patients had a lower frequency of the high penetrance M694V mutation and a significant delay of diagnosis (p<0.002). Patients living in eastern Mediterranean countries had a higher frequency of fever episodes/year and more frequent arthritis, pericarditis, chest pain, abdominal pain and vomiting compared to the other two groups. Multivariate analysis showed that the variables independently associated with severity of disease presentation were country of residence, presence of M694V mutation and positive family history. CONCLUSIONS: Eastern Mediterranean FMF patients have a milder disease phenotype once they migrate to Europe, reflecting the effect of environment on the expression of a monogenic disease.

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There is evidence across several species for genetic control of phenotypic variation of complex traits, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ∼170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ∼0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI, possibly mediated by DNA methylation. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.

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BACKGROUND & AIMS: Steatosis is a prominent feature of hepatitis C, especially in patients infected with genotype 3. The analysis of genetic polymorphisms influencing steatosis in chronic hepatitis C has been limited by the studies' small sample size, and important single nucleotide polymorphisms (SNPs), such as those in the patatin-like phospholipase family 3 protein (PNPLA3), were never evaluated. METHODS: We analyzed the role of SNPs, from 19 systematically selected candidate genes, on steatosis in 626 Caucasian hepatitis C virus (HCV) infected patients. SNPs were extracted from a genome-wide association-generated dataset. Associations of alleles with the presence and/or different severity of steatosis were evaluated by univariate and multivariate logistic regression, accounting for all relevant covariates. RESULTS: The risk of steatosis was increased by carriage of I148M in PNPLA3, but only in patients with HCV genotypes non-3 (odds ratio [OR]=1.9, 95% confidence interval [CI]=1.6-2.3, p<0.001) and similar, albeit weaker associations were found for SNPs in peroxisome proliferator-activated receptor-γ (PPARG) and interleukin-28B (IL28B). Carriage of a SNP in the microsomal triglyceride transfer protein (MTTP) increased the risk of steatosis, but only in patients with HCV genotype 3 (rs1800803, OR=3.4, 95% CI=2.4-4.9, p=0.001). CONCLUSIONS: The rs738409 SNP in PNPLA3 is associated with an increased risk of steatosis in patients infected with HCV genotypes non-3. Host genes affect steatosis depending on the infecting HCV genotype, suggesting their interaction with viral factors.

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The yearly genetic progress obtained by breeding for increased soybean yield has been considered acceptable worldwide. It is common sense, however, that this progress can be improved further if refined breeding techniques, developed from the knowledge of the genetic mechanisms controlling soybean yield, are used. In this paper, data from four cultivars and/or lines and their derived sets of F2, F3, F7, F8, F9 and F10 generations assayed in 17 environments were analyzed to allow an insight of the genetic control of soybean yield under different environmental conditions. The general picture was of a complex polygene system controlling yield in soybeans. Additive genetic effects predominated although dominance was often found to be significant. Complications such as epistasis, linkage and macro and micro genotype x environment (G x E) interactions were also commonly detected. The overall heritability was 0.29. The relative magnitude of the additive effects and the complicating factors allowed the inference that the latter are not a serious problem to the breeder. The low heritability values and the considerable magnitude of G x E interactions for yield, however, indicated that careful evaluation through experiments designed to allow for the presence of these effects is necessary for successful selection.