HFE gene mutations in Brazilian thalassemic patients

Hereditary hemochromatosis is a disorder of iron metabolism characterized by increased iron intake and progressive storage and is related to mutations in the HFE gene. Interactions between thalassemia and hemochromatosis may further increase iron overload. The ethnic background of the Brazilian population is heterogeneous and studies analyzing the simultaneous presence of HFE and thalassemia-related mutations have not been carried out. The aim of this study was to evaluate the prevalence of the H63D, S65C and C282Y mutations in the HFE gene among 102 individuals with alpha-thalassemia and 168 beta-thalassemia heterozygotes and to compare them with 173 control individuals without hemoglobinopathies. The allelic frequencies found in these three groups were 0.98, 2.38, and 0.29% for the C282Y mutation, 13.72, 13.70, and 9.54% for the H63D mutation, and 0, 0.60, and 0.87% for the S65C mutation, respectively. The chi-square test for multiple independent individuals indicated a significant difference among groups for the C282Y mutation, which was shown to be significant between the beta-thalassemia heterozygote and the control group by the Fisher exact test (P value = 0.009). The higher frequency of inheritance of the C282Y mutation in the HFE gene among beta-thalassemic patients may contribute to worsen the clinical picture of these individuals. In view of the characteristics of the Brazilian population, the present results emphasize the need to screen for HFE mutations in beta-thalassemia carriers.

Study of cerebral gene expression densities using Voronoi analysis

As the available public cerebral gene expression image data increasingly grows, the demand for automated methods to analyze such large amount of data also increases. An important study that can be carried out on these data is related to the spatial relationship between gene expressions. Similar spatial density distribution of expression between genes may indicate they are functionally correlated, thus the identification of these similarities is useful in suggesting directions of investigation to discover gene interactions and their correlated functions. In this paper, we describe the use of a high-throughput methodology based on Voronoi diagrams to automatically analyze and search for possible local spatial density relationships between gene expression images. We tested this method using mouse brain section images from the Allen Mouse Brain Atlas public database. This methodology provided measurements able to characterize the similarity of the density distribution between gene expressions and allowed the visualization of the results through networks and Principal Component Analysis (PCA). These visualizations are useful to analyze the similarity level between gene expression patterns, as well as to compare connection patterns between region networks. Some genes were found to have the same type of function and to be near each other in the PCA visualizations. These results suggest cerebral density correlations between gene expressions that could be further explored. (C) 2011 Elsevier B.V. All rights reserved.

Mutual Information for Testing Gene-Environment Interaction

Despite current enthusiasm for investigation of gene-gene interactions and gene-environment interactions, the essential issue of how to define and detect gene-environment interactions remains unresolved. In this report, we define gene-environment interactions as a stochastic dependence in the context of the effects of the genetic and environmental risk factors on the cause of phenotypic variation among individuals. We use mutual information that is widely used in communication and complex system analysis to measure gene-environment interactions. We investigate how gene-environment interactions generate the large difference in the information measure of gene-environment interactions between the general population and a diseased population, which motives us to develop mutual information-based statistics for testing gene-environment interactions. We validated the null distribution and calculated the type 1 error rates for the mutual information-based statistics to test gene-environment interactions using extensive simulation studies. We found that the new test statistics were more powerful than the traditional logistic regression under several disease models. Finally, in order to further evaluate the performance of our new method, we applied the mutual information-based statistics to three real examples. Our results showed that P-values for the mutual information-based statistics were much smaller than that obtained by other approaches including logistic regression models.

DNA nucleotide excision repair gene single nucleotide polymorphisms and hereditary nonpolyposis colorectal cancer

Hereditary nonpolyposis colorectal cancer (HNPCC) is an autosomal dominant disease caused by germline mutations in DNA mismatch repair(MMR) genes. The nucleotide excision repair(NER) pathway plays a very important role in cancer development. We systematically studied interactions between NER and MMR genes to identify NER gene single nucleotide polymorphism (SNP) risk factors that modify the effect of MMR mutations on risk for cancer in HNPCC. We analyzed data from polymorphisms in 10 NER genes that had been genotyped in HNPCC patients that carry MSH2 and MLH1 gene mutations. The influence of the NER gene SNPs on time to onset of colorectal cancer (CRC) was assessed using survival analysis and a semiparametric proportional hazard model. We found the median age of onset for CRC among MMR mutation carriers with the ERCC1 mutation was 3.9 years earlier than patients with wildtype ERCC1(median 47.7 vs 51.6, log-rank test p=0.035). The influence of Rad23B A249V SNP on age of onset of HNPCC is age dependent (likelihood ratio test p=0.0056). Interestingly, using the likelihood ratio test, we also found evidence of genetic interactions between the MMR gene mutations and SNPs in ERCC1 gene(C8092A) and XPG/ERCC5 gene(D1104H) with p-values of 0.004 and 0.042, respectively. An assessment using tree structured survival analysis (TSSA) showed distinct gene interactions in MLH1 mutation carriers and MSH2 mutation carriers. ERCC1 SNP genotypes greatly modified the age onset of HNPCC in MSH2 mutation carriers, while no effect was detected in MLH1 mutation carriers. Given the NER genes in this study play different roles in NER pathway, they may have distinct influences on the development of HNPCC. The findings of this study are very important for elucidation of the molecular mechanism of colon cancer development and for understanding why some mutation carriers of the MSH2 and MLH1 gene develop CRC early and others never develop CRC. Overall, the findings also have important implications for the development of early detection strategies and prevention as well as understanding the mechanism of colorectal carcinogenesis in HNPCC. ^

Genome-wide gene-gene interaction analysis for cardiovascular disease

Numerous studies have been carried out to try to better understand the genetic predisposition for cardiovascular disease. Although it is widely believed that multifactorial diseases such as cardiovascular disease is the result from effects of many genes which working alone or interact with other genes, most genetic studies have been focused on identifying of cardiovascular disease susceptibility genes and usually ignore the effects of gene-gene interactions in the analysis. The current study applies a novel linkage disequilibrium based statistic for testing interactions between two linked loci using data from a genome-wide study of cardiovascular disease. A total of 53,394 single nucleotide polymorphisms (SNPs) are tested for pair-wise interactions, and 8,644 interactions are found to be significant with p-values less than 3.5×10-11. Results indicate that known cardiovascular disease susceptibility genes tend not to have many significantly interactions. One SNP in the CACNG1 (calcium channel, voltage-dependent, gamma subunit 1) gene and one SNP in the IL3RA (interleukin 3 receptor, alpha) gene are found to have the most significant pair-wise interactions. Findings from the current study should be replicated in other independent cohort to eliminate potential false positive results.^

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

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.

Expression of Drosophila mushroom body mutations in alternative genetic backgrounds: a case study of the mushroom body miniature gene (mbm).

Mutations in 12 genes regulating Drosophila melanogaster mushroom body (MB) development were each studied in two genetic backgrounds. In all cases, brain structure was qualitatively or quantitatively different after replacement of the "original" genetic background with that of the Canton Special wild-type strain. The mushroom body miniature gene (mbm) was investigated in detail. mbm supports the maintenance of MB Kenyon cell fibers in third instar larvae and their regrowth during metamorphosis. Adult mbm1 mutant females are lacking many or most Kenyon cell fibers and are impaired in MB-mediated associative odor learning. We show here that structural defects in mbm1 are apparent only in combination with an X-linked, dosage-dependent modifier (or modifiers). In the Canton Special genetic background, the mbm1 anatomical phenotype is suppressed, and MBs develop to a normal size. However, the olfactory learning phenotype is not fully restored, suggesting that submicroscopic defects persist in the MBs. Mutant mbm1 flies with full-sized MBs have normal retention but show a specific acquisition deficit that cannot be attributed to reductions in odor avoidance, shock reactivity, or locomotor behavior. We propose that polymorphic gene interactions (in addition to ontogenetic factors) determine MB size and, concomitantly, the ability to recognize and learn odors.

Tissue-specific gene expression in soybean (Glycine max) detected by cDNA microarray analysis

We have constructed cDNA microarrays for soybean (Glycine max L. Merrill), containing approximately 4,100 Unigene ESTs derived from axenic roots, to evaluate their application and utility for functional genomics of organ differentiation in legumes. We assessed microarray technology by conducting studies to evaluate the accuracy of microarray data and have found them to be both reliable and reproducible in repeat hybridisations. Several ESTs showed high levels (>50 fold) of differential expression in either root or shoot tissue of soybean. A small number of physiologically interesting, and differentially expressed sequences found by microarray analysis were verified by both quantitative real-time RT-PCR and Northern blot analysis. There was a linear correlation (r(2) = 0.99, over 5 orders of magnitude) between microarray and quantitative real-time RT-PCR data. Microarray analysis of soybean has enormous potential not only for the discovery of new genes involved in tissue differentiation and function, but also to study the expression of previously characterised genes, gene networks and gene interactions in wild-type, mutant or transgenic; plants.

Genetic Predictors Of Long-term Response To Growth Hormone (gh) Therapy In Children With Gh Deficiency And Turner Syndrome: The Influence Of A Socs2 Polymorphism.

There is great interindividual variability in the response to GH therapy. Ascertaining genetic factors can improve the accuracy of growth response predictions. Suppressor of cytokine signaling (SOCS)-2 is an intracellular negative regulator of GH receptor (GHR) signaling. The objective of the study was to assess the influence of a SOCS2 polymorphism (rs3782415) and its interactive effect with GHR exon 3 and -202 A/C IGFBP3 (rs2854744) polymorphisms on adult height of patients treated with recombinant human GH (rhGH). Genotypes were correlated with adult height data of 65 Turner syndrome (TS) and 47 GH deficiency (GHD) patients treated with rhGH, by multiple linear regressions. Generalized multifactor dimensionality reduction was used to evaluate gene-gene interactions. Baseline clinical data were indistinguishable among patients with different genotypes. Adult height SD scores of patients with at least one SOCS2 single-nucleotide polymorphism rs3782415-C were 0.7 higher than those homozygous for the T allele (P < .001). SOCS2 (P = .003), GHR-exon 3 (P= .016) and -202 A/C IGFBP3 (P = .013) polymorphisms, together with clinical factors accounted for 58% of the variability in adult height and 82% of the total height SD score gain. Patients harboring any two negative genotypes in these three different loci (homozygosity for SOCS2 T allele; the GHR exon 3 full-length allele and/or the -202C-IGFBP3 allele) were more likely to achieve an adult height at the lower quartile (odds ratio of 13.3; 95% confidence interval of 3.2-54.2, P = .0001). The SOCS2 polymorphism (rs3782415) has an influence on the adult height of children with TS and GHD after long-term rhGH therapy. Polymorphisms located in GHR, IGFBP3, and SOCS2 loci have an influence on the growth outcomes of TS and GHD patients treated with rhGH. The use of these genetic markers could identify among rhGH-treated patients those who are genetically predisposed to have less favorable outcomes.

Caracterização do papel dos genes TYMS e MTR no desenvolvimento de Cancro Colo-Rectal

RESUMO: O cancro colo-rectal (CCR) é um dos cancros que possui maior taxa de mortalidade a nível mundial. Em Portugal esta patologia é responsável pela morte de cerca de 3700 pessoas por ano, sendo que estes números aumentam de ano para ano. Ao longo das últimas décadas o papel das alterações genéticas na etiologia das patologias oncológicas tem vindo a ter cada vez mais um maior destaque. O número de estudos que avaliam a importância de polimorfismos, mutações, alterações na regulação génica e interacções entre genes no desenvolvimento destas patologias tem aumentado exponencialmente. Com o aumento do conhecimento da forma como estas alterações influenciam o desenvolvimento do cancro surgiram os primeiros meios de diagnóstico genético, levando assim a uma alteração da forma como são encarados o diagnóstico e a prevenção destas doenças. No CCR as formas hereditárias com alterações genéticas inequivocamente identificadas representam apenas 5% dos casos. Existem cerca de 25% que representam formas hereditárias para as quais ainda não foram estabelecidos os padrões de alterações genéticas subjacentes. Desta forma, estudos que venham contribuir para um maior conhecimento dos mecanismos moleculares responsáveis pelo aumento da susceptibilidade dos indivíduos para o desenvolvimento de CCR são extremamente importantes. O CCR é uma patologia multifactorial, onde factores genéticos interagem com factores ambientais no surgimento e desenvolvimento da doença. Assim, torna-se essencial integrar o estudo das alterações genéticas no contexto ambiental onde os indivíduos em estudo se encontram. No caso desta patologia um dos principais factores ambientais estudado é a nutrição. Vários estudos têm sido realizados ao longo dos últimos anos de forma a compreender como pode a ingestão dos nutrientes influenciar o desenvolvimento de CCR e de que forma interage com as alterações genéticas individuais. O ciclo do folato é um dos processos metabólicos onde o papel da nutrição em interacção com alterações genéticas mais tem sido estudado nos últimos anos. Deste cruzamento entre o estudo das alterações genéticas e ambientais surge a Nutrigenética. O conjunto de estudos da presente tese tem como objectivo aumentar o conhecimento do papel das alterações em genes do ciclo do folato, em interacção com factores nutricionais e de estilo de vida, não só no desenvolvimento de CCR, mas também de outra patologia do tracto gastrointestinal, a Doença de Crohn (DC), uma doença inflamatória muitas vezes associada como factor de risco para o desenvolvimento de CCR. Este estudo debruçou-se essencialmente no estudo dos genes timidilato sintetase (TYMS) e metionina sintetase (MTR) em populações com CCR e DC, bem como no padrão nutricional destas populações com particular incidência nos nutrientes envolvidos no ciclo do folato (folato, metionina, vitamina B6, vitamina B12). Analisando o conjunto de resultados obtidos para os estudos do CCR podemos concluir que quer a TYMS quer a MTR possuem um papel relevante na susceptibilidade para desenvolver esta patologia, assim como têm destaque no funcionamento do ciclo celular durante o processo oncogénico. Os resultados demonstram que os factores que levam a uma menor disponibilidade de grupos metil no ciclo de folato (baixos níveis de folato, alteração da actividade de MTR, elevada expressão de TYMS) constituem factores de risco, muito provavelmente por contribuírem para uma desregulação dos níveis de metionina disponível para a metilação do DNA da célula. Demonstram ainda que em células tumorais ocorrem alterações na regulação do ciclo do folato de forma a favorecer a síntese de DNA em detrimento da metilação do mesmo, alterando para isso a expressão dos genes de forma a que o fluxo de grupos metil provenientes do folato sejam encaminhados para a enzima TYMS. O polimorfismo de deleção 6pb da TYMS surge como um factor de diagnóstico e de prognóstico de CCR para a população portuguesa. Dos factores nutricionais analisados apenas o folato aparenta ter um papel relevante na modelação do risco de desenvolver CCR. Na doença de Crohn (DC) podemos verificar que a homocisteína e o seu metabolismo poderão contribuir para o aparecimento e desenvolvimento da patologia. O aumento da homocisteína poderá ser o responsável por um aumento da resposta auto-imune do organismo, promovendo o aparecimento da DC. O polimorfismo A2756G MTR desempenha um papel preponderante como factor de diagnóstico da DC, tendo sido associado pela primeira vez a esta patologia. Tem também um papel importante no desenvolvimento da doença, uma vez que está associado a uma idade de diagnóstico mais baixa, sugerindo assim que o desenvolvimento da doença ocorre de forma mais precoce. Concluindo, com este estudo pensamos ter contribuído para um melhor entendimento do papel do ciclo do folato no desenvolvimento de CCR e DC, sendo um ponto de partida para futuras investigações que possam revelar cada vez melhor as complexas interacções metabólicas desta via e a sua influência nas patologias estudadas. Do nosso estudo destacamos a importância de uma análise global das várias etapas do ciclo do folato para que se possa compreender a dinâmica que se estabelece no desenvolvimento destas patologias, podendo diversas alterações, quer a nível genético quer a nível nutricional, exercerem efeitos diferentes consoante o estado dos restantes intervenientes do ciclo do folato. Acreditamos que no futuro este estudo permitirá que o conhecimento do ciclo do folato tenha cada vez mais uma relevância fundamental a nível de diagnóstico e terapêutica destas patologias.------------ ABSTRACT: Colorectal Cancer (CRC) is one of the cancers that have a higher rate of mortality worldwide. In Portugal this pathology is responsible for the deaths of about 3700 people per year, and these numbers increase each year. Over the past few decades the role of genetic changes in the etiology of oncological pathologies has had an increasingly greater emphasis. The number of studies that evaluate the importance of polymorphisms, mutations, changes in gene regulation and gene interactions in the development of these diseases has increased exponentially. With the increased knowledge of how these changes influence the development of cancer, appeared the first means for genetic diagnostic, leading to a change in the way diagnosis is seen and in the prevention of these diseases. In CRC the hereditary forms with clearly identified genetic changes represent only 5% of cases. There are about 25% representing hereditary forms for which the patterns of genetic changes haven’t been established. In this way, studies that will contribute to a greater understanding of the molecular mechanisms responsible for increased susceptibility of individuals to the CRC development are extremely important. CRC is a multifactorial pathology, where genetic factors interact with environmental factors in the emergence and development of the disease.Thus, it is essential to integrate the study of genetic changes in the environmental context of the individuals under study. In the case of this pathology one of the main environmental factors studied is nutrition. Several studies have been conducted over the past few years in order to understand how the intake of nutrients can influence the development of CRC and how nutrients interact with the individual genetic changes. The folate cycle is one of the metabolic processes where the role of nutrition in interaction with genetic alterations has been studied in recent years. This cross between the study of genetic and environmental changes developed Nutrigenetics. The set of studies of this thesis aims to increase awareness of the role of changes in genes of the folate cycle, in interaction with nutritional factors and lifestyle, not only in the development of CRC, but also of another pathology of the gastrointestinal tract, Crohn's disease (CD), an inflammatory disease often associated as a risk factor for the development of CRC. This study dealt mainly in the study of genes thymidylate synthase (TYMS) and methionine synthase (MTR) in populations with CRC and CD, as well as in the nutritional pattern of these populations with particular focus on nutrients involved in the folate cycle (folate, methionine, vitamin B6, vitamin B12). Analyzing the results obtained for the CRC studies we conclude that either the MTR TYMS have a relevant role in susceptibility to develop this pathology, and have an important role in the functioning of the cell cycle during oncogenesis. The results show that the factors that lead to a lower availability of methyl groups in folate cycle (low levels of folate, change the activity of MTR, high expression of TYMS) constitute risk factors, most likely by contribute to a dysregulation of methionine levels available for DNA methylation of the cell. Our results also demonstrate that in tumor cells occur changes in the regulation of the folate cycle in order to promote the synthesis of DNA, to the detriment of methylation of the same by changing the expression of genes so that the methyl groups from folate are forwarded to the TYMS enzyme reaction. The deletion polymorphism 6bp of TYMS emerges as a diagnostic and prognostic factor of CCR for the Portuguese population. Nutritional factors analyzed only folate appears to have a major role in modulating the risk of developing CCR.In Crohn’s disease (CD) we can check that homocysteine and its metabolism may contribute to the emergence and development of this pathology. Increased homocysteine may be responsible for an increase in the body's autoimmune response, promoting the emergence of CD. The polymorphism A2756G MTR plays a leading role as a factor of diagnosis of DC, having been associated with this pathology for the first time. It also has an important role in the development of the disease, since it is associated with a lower diagnostic age, suggesting that the development of the disease occurs earlier. In conclusion, our study has contributed to a better understanding of the role of folate cycle in the development of CRC and CD, being a starting point for future research that may prove increasingly complex metabolic interactions in this via and its influence on the pathologies studied. In our study we highlight the importance of a comprehensive analysis of the various steps of the folate cycle in order to understand the dynamics that settles in the development of these pathologies, and a number of amendments, whether at the genetic level or at the nutritional level, exercise different effects depending on the stage of the remaining participants in the folate cycle. We believe that in the future this study will allow the knowledge of folate cycle to have increasingly a fundamental relevance at the level of diagnosis and treatment of these diseases.

Exploring the mechanisms regulating nutrient bioavailability and lipid metabolism through a nutrigenomics approach

SUMMARY Following the complete sequencing of the human genome, the field of nutrition has begun utilizing this vast quantity of information to comprehensively explore the interactions between diet and genes. This approach, coined nutrigenomics, aims to determine the influence of common dietary ingredients on the genome, and attempts to relate the resulting different phenotypes to differences in the cellular and/or genetic response of the biological system. However, complementary to defining the biological outcomes of dietary ingredients, we must also understand the influence of the multiple factors (such as the microbiota, bile, and function of transporters) that may contribute to the bioavailability, and ultimately bioefficacy, of these ingredients. The gastrointestinal tract (GIT) is the body's foremost tissue boundary, interacting with nutrients, exogenous compounds and microbiota, and whose condition is influenced by the complex interplay between these environmental factors and genetic elements. In order to understand GIT nutrient-gene interactions, our goal was to comprehensively elucidate the region-specific gene expression underlying intestinal functions. We found important regional differences in the expression of members of the ATP-binding cassette family of transporters in the mouse intestine, suggesting that absorption of dietary compounds may vary along the GIT. Furthermore, the influence of the microbiota on host gene expression indicated that this luminal factor predominantly influences immune function and water transport throughout the GIT; however, the identification of region-specific functions suggest distinct host-bacterial interactions along the GIT. Thus, these findings reinforce that to understand nutrient bioavailability and GIT function, one must consider the physiologically distinct regions of the gut. Nutritional molecules absorbed by the enterocytes of the GIT enter circulation and will be selectively absorbed and metabolised by tissues throughout the body; however, their bioefficacy in the body will depend on the unique and shared molecular mechanisms of the various tissues. Using a nutrigenomic approach, the biological responses of the liver and hippocampus of mice fed different long chain-polyunsaturated fatty acids diets revealed tissue-specific responses. Furthermore, we identified stearoyl-CoA desaturase as a hepatic target for arachidonic acid, suggesting a potentially novel molecular mechanism that may protect against diet-induced obesity. In summary, this work begins to unveil the fundamentally important role that nutrigenomics will play in unravelling the molecular mechanisms, and those exogenous factors capable of influencing these mechanisms, that regulate the bioefficacy of nutritional molecules. RÉSUMÉ Suite au séquençage complet du génome humain, le domaine de la nutrition a commencé à utiliser cette vaste quantité d'information pour explorer de manière globale les interactions entre la nourriture et les gènes. Cette approche, appelée « nutrigenomics », a pour but de déterminer l'influence d'ingrédients couramment utilisés dans l'alimentation sur le génome, et d'essayer de relier ces différents phénotypes, ainsi révélés, à des différences de réponses cellulaires et/ou génétiques. Cependant, en plus de définir les effets biologiques d'ingrédients alimentaires, il est important de comprendre l'influence des multiples facteurs (telle que la microflore, la bile et la fonction des transporteurs) pouvant contribuer à la bio- disponibilité et par conséquent à l'efficacité de ces ingrédients. Le tractus gastro-intestinal (TGI), qui est la première barrière vers les tissus, interagit avec les nutriments, les composés exogènes et la microflore. La fonction de cet organe est influencée par les interactions complexes entre les facteurs environnementaux et les éléments génétiques. Dans le but de comprendre les interactions entre les nutriments et les gènes au niveau du TGI, notre objectif a été de décrire de manière globale l'expression génique spécifique de chaque région de l'intestin définissant leurs fonctions. Nous avons trouvé d'importantes différences régionales dans l'expression des transporteurs de la famille des « ATP-binding cassette transporter » dans l'intestin de souris, suggérant que l'absorption des composés alimentaires puisse varier le long de l'intestin. De plus, l'étude des effets de la microflore sur l'expression des gènes hôtes a indiqué que ce facteur de la lumière intestinale influence surtout la fonction immunitaire et le transport de l'eau à travers l'intestin. Cependant, l'identification des fonctions spécifiques de chaque région suggère des interactions distinctes entre l'hôte et les bactéries le long de l'intestin. Ainsi, ces résultats renforcent l'idée que la compréhension de la bio-disponibilité des nutriments, et par conséquent la fonction du TGI, doit prendre en considération les différences régionales. Les molécules nutritionnelles transportées par les entérocytes jusqu'à la circulation sanguine, sont ensuite sélectivement absorbées et métabolisées par les différents tissus de l'organisme. Cependant, leur efficacité biologique dépendra du mécanisme commun ou spécifique de chaque tissu. En utilisant une approche « nutriogenomics », nous avons pu mettre en évidence les réponses biologiques spécifiques du foie et de l'hippocampe de souris nourris avec des régimes supplémentés avec différents acides gras poly-insaturés à chaîne longue. De plus, nous avons identifié la stearoyl-CoA desaturase comme une cible hépatique pour l'acide arachidonique, suggérant un nouveau mécanisme moléculaire pouvant potentiellement protéger contre le développement de l'obésité. En résumé, ce travail a permis de dévoiler le rôle fondamental qu'une approche telle que la « nutrigenomics » peut jouer dans le décryptage des mécanismes moléculaires et de leur régulation par des facteurs exogènes, qui ensemble vont contrôler l'efficacité biologique des nutriments.

Prox1 interacts with Atoh1 and Gfi1, and regulates cellular differentiation in the inner ear sensory epithelia.

Inner ear hair cells and supporting cells arise from common precursors and, in mammals, do not show phenotypic conversion. Here, we studied the role of the homeodomain transcription factor Prox1 in the inner ear sensory epithelia. Adenoviral-mediated Prox1 transduction into hair cells in explant cultures led to strong repression of Atoh1 and Gfi1, two transcription factors critical for hair cell differentiation and survival. Luciferase assays showed that Prox1 can repress transcriptional activity of Gfi1 independently of Atoh1. Prox1 transduction into cochlear outer hair cells resulted in degeneration of these cells, consistent with the known phenotype of Gfi1-deficient mice. These results together with the widespread expression of endogenous Prox1 within the population of inner ear supporting cells point to the role for Prox1 in antagonizing the hair cell phenotype in these non-sensory cells. Further, in vivo analyses of hair cells from Gfi1-deficient mice suggest that the cyclin-dependent kinase inhibitor p57(Kip2) mediates the differentiation- and survival-promoting functions of Gfi1. These data reveal novel gene interactions and show that these interactions regulate cellular differentiation within the inner ear sensory epithelia. The data point to the tight regulation of phenotypic characteristics of hair cells and supporting cells.

A bi-dimensional genome scan for prolificacy traits in pigs shows the existence of multiple epistatic QTL

Background: Prolificacy is the most important trait influencing the reproductive efficiency of pig production systems. The low heritability and sex-limited expression of prolificacy have hindered to some extent the improvement of this trait through artificial selection. Moreover, the relative contributions of additive, dominant and epistatic QTL to the genetic variance of pig prolificacy remain to be defined. In this work, we have undertaken this issue by performing one-dimensional and bi-dimensional genome scans for number of piglets born alive (NBA) and total number of piglets born (TNB) in a three generation Iberian by Meishan F2 intercross. Results: The one-dimensional genome scan for NBA and TNB revealed the existence of two genome-wide highly significant QTL located on SSC13 (P < 0.001) and SSC17 (P < 0.01) with effects on both traits. This relative paucity of significant results contrasted very strongly with the wide array of highly significant epistatic QTL that emerged in the bi-dimensional genome-wide scan analysis. As much as 18 epistatic QTL were found for NBA (four at P < 0.01 and five at P < 0.05) and TNB (three at P < 0.01 and six at P < 0.05), respectively. These epistatic QTL were distributed in multiple genomic regions, which covered 13 of the 18 pig autosomes, and they had small individual effects that ranged between 3 to 4% of the phenotypic variance. Different patterns of interactions (a × a, a × d, d × a and d × d) were found amongst the epistatic QTL pairs identified in the current work.Conclusions: The complex inheritance of prolificacy traits in pigs has been evidenced by identifying multiple additive (SSC13 and SSC17), dominant and epistatic QTL in an Iberian × Meishan F2 intercross. Our results demonstrate that a significant fraction of the phenotypic variance of swine prolificacy traits can be attributed to first-order gene-by-gene interactions emphasizing that the phenotypic effects of alleles might be strongly modulated by the genetic background where they segregate.

FAM-MDR: a flexible family-based multifactor dimensionality reduction technique to detect epistasis using related individuals

We propose a novel multifactor dimensionality reduction method for epistasis detection in small or extended pedigrees, FAM-MDR. It combines features of the Genome-wide Rapid Association using Mixed Model And Regression approach (GRAMMAR) with Model-Based MDR (MB-MDR). We focus on continuous traits, although the method is general and can be used for outcomes of any type, including binary and censored traits. When comparing FAM-MDR with Pedigree-based Generalized MDR (PGMDR), which is a generalization of Multifactor Dimensionality Reduction (MDR) to continuous traits and related individuals, FAM-MDR was found to outperform PGMDR in terms of power, in most of the considered simulated scenarios. Additional simulations revealed that PGMDR does not appropriately deal with multiple testing and consequently gives rise to overly optimistic results. FAM-MDR adequately deals with multiple testing in epistasis screens and is in contrast rather conservative, by construction. Furthermore, simulations show that correcting for lower order (main) effects is of utmost importance when claiming epistasis. As Type 2 Diabetes Mellitus (T2DM) is a complex phenotype likely influenced by gene-gene interactions, we applied FAM-MDR to examine data on glucose area-under-the-curve (GAUC), an endophenotype of T2DM for which multiple independent genetic associations have been observed, in the Amish Family Diabetes Study (AFDS). This application reveals that FAM-MDR makes more efficient use of the available data than PGMDR and can deal with multi-generational pedigrees more easily. In conclusion, we have validated FAM-MDR and compared it to PGMDR, the current state-of-the-art MDR method for family data, using both simulations and a practical dataset. FAM-MDR is found to outperform PGMDR in that it handles the multiple testing issue more correctly, has increased power, and efficiently uses all available information.

An efficient algorithm to perform multiple testing in epistasis screening

Background: Research in epistasis or gene-gene interaction detection for human complex traits has grown over the last few years. It has been marked by promising methodological developments, improved translation efforts of statistical epistasis to biological epistasis and attempts to integrate different omics information sources into the epistasis screening to enhance power. The quest for gene-gene interactions poses severe multiple-testing problems. In this context, the maxT algorithm is one technique to control the false-positive rate. However, the memory needed by this algorithm rises linearly with the amount of hypothesis tests. Gene-gene interaction studies will require a memory proportional to the squared number of SNPs. A genome-wide epistasis search would therefore require terabytes of memory. Hence, cache problems are likely to occur, increasing the computation time. In this work we present a new version of maxT, requiring an amount of memory independent from the number of genetic effects to be investigated. This algorithm was implemented in C++ in our epistasis screening software MBMDR-3.0.3. We evaluate the new implementation in terms of memory efficiency and speed using simulated data. The software is illustrated on real-life data for Crohn’s disease. Results: In the case of a binary (affected/unaffected) trait, the parallel workflow of MBMDR-3.0.3 analyzes all gene-gene interactions with a dataset of 100,000 SNPs typed on 1000 individuals within 4 days and 9 hours, using 999 permutations of the trait to assess statistical significance, on a cluster composed of 10 blades, containing each four Quad-Core AMD Opteron(tm) Processor 2352 2.1 GHz. In the case of a continuous trait, a similar run takes 9 days. Our program found 14 SNP-SNP interactions with a multiple-testing corrected p-value of less than 0.05 on real-life Crohn’s disease (CD) data. Conclusions: Our software is the first implementation of the MB-MDR methodology able to solve large-scale SNP-SNP interactions problems within a few days, without using much memory, while adequately controlling the type I error rates. A new implementation to reach genome-wide epistasis screening is under construction. In the context of Crohn’s disease, MBMDR-3.0.3 could identify epistasis involving regions that are well known in the field and could be explained from a biological point of view. This demonstrates the power of our software to find relevant phenotype-genotype higher-order associations.