Childhood temperament: passive gene-environment correlation, gene-environment interaction, and the hidden importance of the family environment.

PubMed

Lemery-Chalfant, Kathryn; Kao, Karen; Swann, Gregory; Goldsmith, H Hill

2013-02-01

Biological parents pass on genotypes to their children, as well as provide home environments that correlate with their genotypes; thus, the association between the home environment and children's temperament can be genetically (i.e., passive gene-environment correlation) or environmentally mediated. Furthermore, family environments may suppress or facilitate the heritability of children's temperament (i.e., gene-environment interaction). The sample comprised 807 twin pairs (mean age = 7.93 years) from the longitudinal Wisconsin Twin Project. Important passive gene-environment correlations emerged, such that home environments were less chaotic for children with high effortful control, and this association was genetically mediated. Children with high extraversion/surgency experienced more chaotic home environments, and this correlation was also genetically mediated. In addition, heritability of children's temperament was moderated by home environments, such that effortful control and extraversion/surgency were more heritable in chaotic homes, and negative affectivity was more heritable under crowded or unsafe home conditions. Modeling multiple types of gene-environment interplay uncovered the complex role of genetic factors and the hidden importance of the family environment for children's temperament and development more generally.

Cancer risk and the complexity of the interactions between environmental and host factors: HENVINET interactive diagrams as simple tools for exploring and understanding the scientific evidence.

PubMed

Merlo, Domenico F; Filiberti, Rosangela; Kobernus, Michael; Bartonova, Alena; Gamulin, Marija; Ferencic, Zeljko; Dusinska, Maria; Fucic, Aleksandra

2012-06-28

Development of graphical/visual presentations of cancer etiology caused by environmental stressors is a process that requires combining the complex biological interactions between xenobiotics in living and occupational environment with genes (gene-environment interaction) and genomic and non-genomic based disease specific mechanisms in living organisms. Traditionally, presentation of causal relationships includes the statistical association between exposure to one xenobiotic and the disease corrected for the effect of potential confounders. Within the FP6 project HENVINET, we aimed at considering together all known agents and mechanisms involved in development of selected cancer types. Selection of cancer types for causal diagrams was based on the corpus of available data and reported relative risk (RR). In constructing causal diagrams the complexity of the interactions between xenobiotics was considered a priority in the interpretation of cancer risk. Additionally, gene-environment interactions were incorporated such as polymorphisms in genes for repair and for phase I and II enzymes involved in metabolism of xenobiotics and their elimination. Information on possible age or gender susceptibility is also included. Diagrams are user friendly thanks to multistep access to information packages and the possibility of referring to related literature and a glossary of terms. Diagrams cover both chemical and physical agents (ionizing and non-ionizing radiation) and provide basic information on the strength of the association between type of exposure and cancer risk reported by human studies and supported by mechanistic studies. Causal diagrams developed within HENVINET project represent a valuable source of information for professionals working in the field of environmental health and epidemiology, and as educational material for students. Cancer risk results from a complex interaction of environmental exposures with inherited gene polymorphisms, genetic burden collected during development and non genomic capacity of response to environmental insults. In order to adopt effective preventive measures and the associated regulatory actions, a comprehensive investigation of cancer etiology is crucial. Variations and fluctuations of cancer incidence in human populations do not necessarily reflect environmental pollution policies or population distribution of polymorphisms of genes known to be associated with increased cancer risk. Tools which may be used in such a comprehensive research, including molecular biology applied to field studies, require a methodological shift from the reductionism that has been used until recently as a basic axiom in interpretation of data. The complexity of the interactions between cells, genes and the environment, i.e. the resonance of the living matter with the environment, can be synthesized by systems biology. Within the HENVINET project such philosophy was followed in order to develop interactive causal diagrams for the investigation of cancers with possible etiology in environmental exposure. Causal diagrams represent integrated knowledge and seed tool for their future development and development of similar diagrams for other environmentally related diseases such as asthma or sterility. In this paper development and application of causal diagrams for cancer are presented and discussed.

A Nonlinear Model for Gene-Based Gene-Environment Interaction.

PubMed

Sa, Jian; Liu, Xu; He, Tao; Liu, Guifen; Cui, Yuehua

2016-06-04

A vast amount of literature has confirmed the role of gene-environment (G×E) interaction in the etiology of complex human diseases. Traditional methods are predominantly focused on the analysis of interaction between a single nucleotide polymorphism (SNP) and an environmental variable. Given that genes are the functional units, it is crucial to understand how gene effects (rather than single SNP effects) are influenced by an environmental variable to affect disease risk. Motivated by the increasing awareness of the power of gene-based association analysis over single variant based approach, in this work, we proposed a sparse principle component regression (sPCR) model to understand the gene-based G×E interaction effect on complex disease. We first extracted the sparse principal components for SNPs in a gene, then the effect of each principal component was modeled by a varying-coefficient (VC) model. The model can jointly model variants in a gene in which their effects are nonlinearly influenced by an environmental variable. In addition, the varying-coefficient sPCR (VC-sPCR) model has nice interpretation property since the sparsity on the principal component loadings can tell the relative importance of the corresponding SNPs in each component. We applied our method to a human birth weight dataset in Thai population. We analyzed 12,005 genes across 22 chromosomes and found one significant interaction effect using the Bonferroni correction method and one suggestive interaction. The model performance was further evaluated through simulation studies. Our model provides a system approach to evaluate gene-based G×E interaction.

Complex Genotype by Environment interactions and changing genetic architectures across thermal environments in the Australian field cricket, Teleogryllus oceanicus

PubMed Central

2011-01-01

Background Biologists studying adaptation under sexual selection have spent considerable effort assessing the relative importance of two groups of models, which hinge on the idea that females gain indirect benefits via mate discrimination. These are the good genes and genetic compatibility models. Quantitative genetic studies have advanced our understanding of these models by enabling assessment of whether the genetic architectures underlying focal phenotypes are congruent with either model. In this context, good genes models require underlying additive genetic variance, while compatibility models require non-additive variance. Currently, we know very little about how the expression of genotypes comprised of distinct parental haplotypes, or how levels and types of genetic variance underlying key phenotypes, change across environments. Such knowledge is important, however, because genotype-environment interactions can have major implications on the potential for evolutionary responses to selection. Results We used a full diallel breeding design to screen for complex genotype-environment interactions, and genetic architectures underlying key morphological traits, across two thermal environments (the lab standard 27°C, and the cooler 23°C) in the Australian field cricket, Teleogryllus oceanicus. In males, complex three-way interactions between sire and dam parental haplotypes and the rearing environment accounted for up to 23 per cent of the scaled phenotypic variance in the traits we measured (body mass, pronotum width and testes mass), and each trait harboured significant additive genetic variance in the standard temperature (27°C) only. In females, these three-way interactions were less important, with interactions between the paternal haplotype and rearing environment accounting for about ten per cent of the phenotypic variance (in body mass, pronotum width and ovary mass). Of the female traits measured, only ovary mass for crickets reared at the cooler temperature (23°C), exhibited significant levels of additive genetic variance. Conclusions Our results show that the genetics underlying phenotypic expression can be complex, context-dependent and different in each of the sexes. We discuss the implications of these results, particularly in terms of the evolutionary processes that hinge on good and compatible genes models. PMID:21791118

Challenges and Opportunities in Genome-Wide Environmental Interaction (GWEI) studies

PubMed Central

Aschard, Hugues; Lutz, Sharon; Maus, Bärbel; Duell, Eric J.; Fingerlin, Tasha; Chatterjee, Nilanjan; Kraft, Peter; Van Steen, Kristel

2012-01-01

The interest in performing gene-environment interaction studies has seen a significant increase with the increase of advanced molecular genetics techniques. Practically, it became possible to investigate the role of environmental factors in disease risk and hence to investigate their role as genetic effect modifiers. The understanding that genetics is important in the uptake and metabolism of toxic substances is an example of how genetic profiles can modify important environmental risk factors to disease. Several rationales exist to set up gene-environment interaction studies and the technical challenges related to these studies – when the number of environmental or genetic risk factors is relatively small – has been described before. In the post-genomic era, it is now possible to study thousands of genes and their interaction with the environment. This brings along a whole range of new challenges and opportunities. Despite a continuing effort in developing efficient methods and optimal bioinformatics infrastructures to deal with the available wealth of data, the challenge remains how to best present and analyze Genome-Wide Environmental Interaction (GWEI) studies involving multiple genetic and environmental factors. Since GWEIs are performed at the intersection of statistical genetics, bioinformatics and epidemiology, usually similar problems need to be dealt with as for Genome-Wide Association gene-gene Interaction (GWAI) studies. However, additional complexities need to be considered which are typical for large-scale epidemiological studies, but are also related to “joining” two heterogeneous types of data in explaining complex disease trait variation or for prediction purposes. PMID:22760307

Childhood Temperament: Passive Gene-Environment Correlation, Gene-Environment Interaction, and the Hidden Importance of the Family Environment

PubMed Central

Lemery-Chalfant, Kathryn; Kao, Karen; Swann, Gregory; Goldsmith, H. Hill

2013-01-01

Biological parents pass on genotypes to their children, as well as provide home environments that correlate with their genotypes; thus, the association between the home environment and children's temperament can be genetically (i.e. passive gene-environment correlation) or environmentally mediated. Furthermore, family environments may suppress or facilitate the heritability of children's temperament (i.e. gene-environment interaction). The sample comprised 807 twin pairs (M age = 7.93 years) from the longitudinal Wisconsin Twin Project. Important passive gene-environment correlations emerged, such that home environments were less chaotic for children with high Effortful Control, and this association was genetically mediated. Children with high Extraversion/Surgency experienced more chaotic home environments, and this correlation was also genetically mediated. In addition, heritability of children's temperament was moderated by home environments, such that Effortful Control and Extraversion/Surgency were more heritable in chaotic homes, and Negative Affectivity was more heritable under crowded or unsafe home conditions. Modeling multiple types of gene-environment interplay uncovered the complex role of genetic factors and the hidden importance of the family environment for children's temperament and development more generally. PMID:23398752

Next-generation analysis of cataracts: determining knowledge driven gene-gene interactions using Biofilter, and gene-environment interactions using the PhenX Toolkit.

PubMed

Pendergrass, Sarah A; Verma, Shefali S; Holzinger, Emily R; Moore, Carrie B; Wallace, John; Dudek, Scott M; Huggins, Wayne; Kitchner, Terrie; Waudby, Carol; Berg, Richard; McCarty, Catherine A; Ritchie, Marylyn D

2013-01-01

Investigating the association between biobank derived genomic data and the information of linked electronic health records (EHRs) is an emerging area of research for dissecting the architecture of complex human traits, where cases and controls for study are defined through the use of electronic phenotyping algorithms deployed in large EHR systems. For our study, 2580 cataract cases and 1367 controls were identified within the Marshfield Personalized Medicine Research Project (PMRP) Biobank and linked EHR, which is a member of the NHGRI-funded electronic Medical Records and Genomics (eMERGE) Network. Our goal was to explore potential gene-gene and gene-environment interactions within these data for 529,431 single nucleotide polymorphisms (SNPs) with minor allele frequency > 1%, in order to explore higher level associations with cataract risk beyond investigations of single SNP-phenotype associations. To build our SNP-SNP interaction models we utilized a prior-knowledge driven filtering method called Biofilter to minimize the multiple testing burden of exploring the vast array of interaction models possible from our extensive number of SNPs. Using the Biofilter, we developed 57,376 prior-knowledge directed SNP-SNP models to test for association with cataract status. We selected models that required 6 sources of external domain knowledge. We identified 5 statistically significant models with an interaction term with p-value < 0.05, as well as an overall model with p-value < 0.05 associated with cataract status. We also conducted gene-environment interaction analyses for all GWAS SNPs and a set of environmental factors from the PhenX Toolkit: smoking, UV exposure, and alcohol use; these environmental factors have been previously associated with the formation of cataracts. We found a total of 288 models that exhibit an interaction term with a p-value ≤ 1×10(-4) associated with cataract status. Our results show these approaches enable advanced searches for epistasis and gene-environment interactions beyond GWAS, and that the EHR based approach provides an additional source of data for seeking these advanced explanatory models of the etiology of complex disease/outcome such as cataracts.

3D Reconstruction of Frozen Plant Tissue: a unique histological analysis to image post-freeze responses

USDA-ARS?s Scientific Manuscript database

Winter hardiness in plants is the result of a complex interaction between genes, the tissue where those genes are expressed and the environment. The light microscope is a valuable tool to understand this complexity which will ultimately help researchers improve the tolerance of plants to freezing st...

Testing for gene-environment interaction under exposure misspecification.

PubMed

Sun, Ryan; Carroll, Raymond J; Christiani, David C; Lin, Xihong

2017-11-09

Complex interplay between genetic and environmental factors characterizes the etiology of many diseases. Modeling gene-environment (GxE) interactions is often challenged by the unknown functional form of the environment term in the true data-generating mechanism. We study the impact of misspecification of the environmental exposure effect on inference for the GxE interaction term in linear and logistic regression models. We first examine the asymptotic bias of the GxE interaction regression coefficient, allowing for confounders as well as arbitrary misspecification of the exposure and confounder effects. For linear regression, we show that under gene-environment independence and some confounder-dependent conditions, when the environment effect is misspecified, the regression coefficient of the GxE interaction can be unbiased. However, inference on the GxE interaction is still often incorrect. In logistic regression, we show that the regression coefficient is generally biased if the genetic factor is associated with the outcome directly or indirectly. Further, we show that the standard robust sandwich variance estimator for the GxE interaction does not perform well in practical GxE studies, and we provide an alternative testing procedure that has better finite sample properties. © 2017, The International Biometric Society.

Culture as a mediator of gene-environment interaction: Cultural consonance, childhood adversity, a 2A serotonin receptor polymorphism, and depression in urban Brazil.

PubMed

Dressler, William W; Balieiro, Mauro C; Ferreira de Araújo, Luiza; Silva, Wilson A; Ernesto Dos Santos, José

2016-07-01

Research on gene-environment interaction was facilitated by breakthroughs in molecular biology in the late 20th century, especially in the study of mental health. There is a reliable interaction between candidate genes for depression and childhood adversity in relation to mental health outcomes. The aim of this paper is to explore the role of culture in this process in an urban community in Brazil. The specific cultural factor examined is cultural consonance, or the degree to which individuals are able to successfully incorporate salient cultural models into their own beliefs and behaviors. It was hypothesized that cultural consonance in family life would mediate the interaction of genotype and childhood adversity. In a study of 402 adult Brazilians from diverse socioeconomic backgrounds, conducted from 2011 to 2014, the interaction of reported childhood adversity and a polymorphism in the 2A serotonin receptor was associated with higher depressive symptoms. Further analysis showed that the gene-environment interaction was mediated by cultural consonance in family life, and that these effects were more pronounced in lower social class neighborhoods. The findings reinforce the role of the serotonergic system in the regulation of stress response and learning and memory, and how these processes in turn interact with environmental events and circumstances. Furthermore, these results suggest that gene-environment interaction models should incorporate a wider range of environmental experience and more complex pathways to better understand how genes and the environment combine to influence mental health outcomes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Gene and environment interaction: is the differential susceptibility hypothesis relevant for obesity?

PubMed Central

Dalle Molle, Roberta; Fatemi, Hajar; Dagher, Alain; Levitan, Robert D.; Silveira, Patricia P.; Dubé, Laurette

2017-01-01

The differential susceptibility model states that a given genetic variant is associated with an increased risk of pathology in negative environments but greater than average resilience in enriched ones. While this theory was first implemented in psychiatric-genetic research, it may also help us to unravel the complex ways that genes and environments interact to influence feeding behavior and obesity. We reviewed evidence on gene vs. environment interactions that influence obesity development, aiming to support the applicability of the differential susceptibility model for this condition, and propose that various environmental “layers” relevant for human development should be considered when bearing the differential susceptibility model in mind. Mother-child relationship, socioeconomic status and individual's response are important modifiers of BMI and food intake when interacting with gene variants, “for better and for worse”. While only a few studies to date have investigated obesity outcomes using this approach, we propose that the differential susceptibility hypothesis is in fact highly applicable to the study of genetic and environmental influences on feeding behavior and obesity risk. PMID:28024828

Gene-Environment Interactions in Cardiovascular Disease

PubMed Central

Flowers, Elena; Froelicher, Erika Sivarajan; Aouizerat, Bradley E.

2011-01-01

Background Historically, models to describe disease were exclusively nature-based or nurture-based. Current theoretical models for complex conditions such as cardiovascular disease acknowledge the importance of both biologic and non-biologic contributors to disease. A critical feature is the occurrence of interactions between numerous risk factors for disease. The interaction between genetic (i.e. biologic, nature) and environmental (i.e. non-biologic, nurture) causes of disease is an important mechanism for understanding both the etiology and public health impact of cardiovascular disease. Objectives The purpose of this paper is to describe theoretical underpinnings of gene-environment interactions, models of interaction, methods for studying gene-environment interactions, and the related concept of interactions between epigenetic mechanisms and the environment. Discussion Advances in methods for measurement of genetic predictors of disease have enabled an increasingly comprehensive understanding of the causes of disease. In order to fully describe the effects of genetic predictors of disease, it is necessary to place genetic predictors within the context of known environmental risk factors. The additive or multiplicative effect of the interaction between genetic and environmental risk factors is often greater than the contribution of either risk factor alone. PMID:21684212

Gene–environment interaction in tobacco-related cancers

PubMed Central

Taioli, Emanuela

2008-01-01

This review summarizes the carcinogenic effects of tobacco smoke and the basis for interaction between tobacco smoke and genetic factors. Examples of published papers on gene–tobacco interaction and cancer risk are presented. The assessment of gene–environment interaction in tobacco-related cancers has been more complex than originally expected for several reasons, including the multiplicity of genes involved in tobacco metabolism, the numerous substrates metabolized by the relevant genes and the interaction of smoking with other metabolic pathways. Future studies on gene–environment interaction and cancer risk should include biomarkers of smoking dose, along with markers of quantitative historical exposure to tobacco. Epigenetic studies should be added to classic genetic analyses, in order to better understand gene–environmental interaction and individual susceptibility. Other metabolic pathways in competition with tobacco genetic metabolism/repair should be incorporated in epidemiological studies to generate a more complete picture of individual cancer risk associated with environmental exposure to carcinogens. PMID:18550573

Nature versus nurture: A systematic approach to elucidate gene-environment interactions in the development of myopic refractive errors.

PubMed

Miraldi Utz, Virginia

2017-01-01

Myopia is the most common eye disorder and major cause of visual impairment worldwide. As the incidence of myopia continues to rise, the need to further understand the complex roles of molecular and environmental factors controlling variation in refractive error is of increasing importance. Tkatchenko and colleagues applied a systematic approach using a combination of gene set enrichment analysis, genome-wide association studies, and functional analysis of a murine model to identify a myopia susceptibility gene, APLP2. Differential expression of refractive error was associated with time spent reading for those with low frequency variants in this gene. This provides support for the longstanding hypothesis of gene-environment interactions in refractive error development.

System Analysis of LWDH Related Genes Based on Text Mining in Biological Networks

PubMed Central

Miao, Yingbo; Zhang, Liangcai; Wang, Yang; Feng, Rennan; Yang, Lei; Zhang, Shihua; Jiang, Yongshuai; Liu, Guiyou

2014-01-01

Liuwei-dihuang (LWDH) is widely used in traditional Chinese medicine (TCM), but its molecular mechanism about gene interactions is unclear. LWDH genes were extracted from the existing literatures based on text mining technology. To simulate the complex molecular interactions that occur in the whole body, protein-protein interaction networks (PPINs) were constructed and the topological properties of LWDH genes were analyzed. LWDH genes have higher centrality properties and may play important roles in the complex biological network environment. It was also found that the distances within LWDH genes are smaller than expected, which means that the communication of LWDH genes during the biological process is rapid and effectual. At last, a comprehensive network of LWDH genes, including the related drugs and regulatory pathways at both the transcriptional and posttranscriptional levels, was constructed and analyzed. The biological network analysis strategy used in this study may be helpful for the understanding of molecular mechanism of TCM. PMID:25243143

Meta-analysis identifies gene-by-environment interactions as demonstrated in a study of 4,965 mice.

PubMed

Kang, Eun Yong; Han, Buhm; Furlotte, Nicholas; Joo, Jong Wha J; Shih, Diana; Davis, Richard C; Lusis, Aldons J; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study.

Meta-Analysis Identifies Gene-by-Environment Interactions as Demonstrated in a Study of 4,965 Mice

PubMed Central

Joo, Jong Wha J.; Shih, Diana; Davis, Richard C.; Lusis, Aldons J.; Eskin, Eleazar

2014-01-01

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study. PMID:24415945

The genetics of human longevity: an intricacy of genes, environment, culture and microbiome.

PubMed

Dato, Serena; Rose, Giuseppina; Crocco, Paolina; Monti, Daniela; Garagnani, Paolo; Franceschi, Claudio; Passarino, Giuseppe

2017-07-01

Approximately one-quarter of the variation in lifespan in developed countries can be attributed to genetic factors. However, even large population based studies investigating genetic influence on human lifespan have been disappointing, identifying only a few genes accounting for genetic susceptibility to longevity. Some environmental and lifestyle determinants associated with longevity have been identified, which interplay with genetic factors in an intricate way. The study of gene-environment and gene-gene interactions can significantly improve our chance to disentangle this complex scenario. In this review, we first describe the most recent approaches for genetic studies of longevity, from those enriched with health parameters and frailty measures to pathway-based and SNP-SNP interaction analyses. Then, we go deeper into the concept of "environmental influences" in human aging and longevity, focusing on the contribution of life style changes, social and cultural influences, as important determinants of survival differences among individuals in a population. Finally, we discuss the contribution of the microbiome in human longevity, as an example of complex interaction between organism and environment. In conclusion, evidences collected from the latest studies on human longevity provide a support for the collection of life-long genetic and environmental/lifestyle variables with beneficial or detrimental effects on health, to improve our understanding of the determinants of human lifespan. Copyright © 2017 Elsevier B.V. All rights reserved.

An integrative model of evolutionary covariance: a symposium on body shape in fishes.

PubMed

Walker, Jeffrey A

2010-12-01

A major direction of current and future biological research is to understand how multiple, interacting functional systems coordinate in producing a body that works. This understanding is complicated by the fact that organisms need to work well in multiple environments, with both predictable and unpredictable environmental perturbations. Furthermore, organismal design reflects a history of past environments and not a plan for future environments. How complex, interacting functional systems evolve, then, is a truly grand challenge. In accepting the challenge, an integrative model of evolutionary covariance is developed. The model combines quantitative genetics, functional morphology/physiology, and functional ecology. The model is used to convene scientists ranging from geneticists, to physiologists, to ecologists, to engineers to facilitate the emergence of body shape in fishes as a model system for understanding how complex, interacting functional systems develop and evolve. Body shape of fish is a complex morphology that (1) results from many developmental paths and (2) functions in many different behaviors. Understanding the coordination and evolution of the many paths from genes to body shape, body shape to function, and function to a working fish body in a dynamic environment is now possible given new technologies from genetics to engineering and new theoretical models that integrate the different levels of biological organization (from genes to ecology).

Systems Modeling at Multiple Levels of Regulation: Linking Systems and Genetic Networks to Spatially Explicit Plant Populations

PubMed Central

Kitchen, James L.; Allaby, Robin G.

2013-01-01

Selection and adaptation of individuals to their underlying environments are highly dynamical processes, encompassing interactions between the individual and its seasonally changing environment, synergistic or antagonistic interactions between individuals and interactions amongst the regulatory genes within the individual. Plants are useful organisms to study within systems modeling because their sedentary nature simplifies interactions between individuals and the environment, and many important plant processes such as germination or flowering are dependent on annual cycles which can be disrupted by climate behavior. Sedentism makes plants relevant candidates for spatially explicit modeling that is tied in with dynamical environments. We propose that in order to fully understand the complexities behind plant adaptation, a system that couples aspects from systems biology with population and landscape genetics is required. A suitable system could be represented by spatially explicit individual-based models where the virtual individuals are located within time-variable heterogeneous environments and contain mutable regulatory gene networks. These networks could directly interact with the environment, and should provide a useful approach to studying plant adaptation. PMID:27137364

A multilevel prediction of physiological response to challenge: Interactions among child maltreatment, neighborhood crime, endothelial nitric oxide synthase gene (eNOS), and GABA(A) receptor subunit alpha-6 gene (GABRA6).

PubMed

Lynch, Michael; Manly, Jody Todd; Cicchetti, Dante

2015-11-01

Physiological response to stress has been linked to a variety of healthy and pathological conditions. The current study conducted a multilevel examination of interactions among environmental toxins (i.e., neighborhood crime and child maltreatment) and specific genetic polymorphisms of the endothelial nitric oxide synthase gene (eNOS) and GABA(A) receptor subunit alpha-6 gene (GABRA6). One hundred eighty-six children were recruited at age 4. The presence or absence of child maltreatment as well as the amount of crime that occurred in their neighborhood during the previous year were determined at that time. At age 9, the children were brought to the lab, where their physiological response to a cognitive challenge (i.e., change in the amplitude of the respiratory sinus arrhythmia) was assessed and DNA samples were collected for subsequent genotyping. The results confirmed that complex Gene × Gene, Environment × Environment, and Gene × Environment interactions were associated with different patterns of respiratory sinus arrhythmia reactivity. The implications for future research and evidence-based intervention are discussed.

The challenge of causal inference in gene-environment interaction research: leveraging research designs from the social sciences.

PubMed

Fletcher, Jason M; Conley, Dalton

2013-10-01

The integration of genetics and the social sciences will lead to a more complex understanding of the articulation between social and biological processes, although the empirical difficulties inherent in this integration are large. One key challenge is the implications of moving "outside the lab" and away from the experimental tools available for research with model organisms. Social science research methods used to examine human behavior in nonexperimental, real-world settings to date have not been fully taken advantage of during this disciplinary integration, especially in the form of gene-environment interaction research. This article outlines and provides examples of several prominent research designs that should be used in gene-environment research and highlights a key benefit to geneticists of working with social scientists.

Gene-Environment Interactions in Cancer Epidemiology: A National Cancer Institute Think Tank Report

PubMed Central

Hutter, Carolyn M.; Mechanic, Leah E.; Chatterjee, Nilanjan; Kraft, Peter; Gillander, Elizabeth M.

2014-01-01

Cancer risk is determined by a complex interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified hundreds of common (minor allele frequency [MAF]>0.05) and less common (0.01

Social defeat interacts with Disc1 mutations in the mouse to affect behavior.

PubMed

Haque, F Nipa; Lipina, Tatiana V; Roder, John C; Wong, Albert H C

2012-08-01

DISC1 (Disrupted-in-schizophrenia 1) is a strong candidate susceptibility gene for psychiatric disease that was originally discovered in a family with a chromosomal translocation severing this gene. Although the family members with the translocation had an identical genetic mutation, their clinical diagnosis and presentation varied significantly. Gene-environment interactions have been proposed as a mechanism underlying the complex heritability and variable phenotype of psychiatric disorders such as major depressive disorder and schizophrenia. We hypothesized that gene-environment interactions would affect behavior in a mutant Disc1 mouse model. We examined the effect of chronic social defeat (CSD) as an environmental stressor in two lines of mice carrying different Disc1 point mutations, on behaviors relevant to psychiatric illness: locomotion in a novel open field (OF), pre-pulse inhibition (PPI) of the acoustic startle response, latent inhibition (LI), elevated plus maze (EPM), forced swim test (FST), sucrose consumption (SC), and the social interaction task for sociability and social novelty (SSN). We found that Disc1-L100P +/- and wild-type mice have similar anxiety responses to CSD, while Q31L +/- mice had a very different response. We also found evidence of significant gene-environment interactions in the OF, EPM and SSN. Copyright © 2012 Elsevier B.V. All rights reserved.

Finding gene-environment interactions for phobias.

PubMed

Gregory, Alice M; Lau, Jennifer Y F; Eley, Thalia C

2008-03-01

Phobias are common disorders causing a great deal of suffering. Studies of gene-environment interaction (G x E) have revealed much about the complex processes underlying the development of various psychiatric disorders but have told us little about phobias. This article describes what is already known about genetic and environmental influences upon phobias and suggests how this information can be used to optimise the chances of discovering G x Es for phobias. In addition to the careful conceptualisation of new studies, it is suggested that data already collected should be re-analysed in light of increased understanding of processes influencing phobias.

Ecogeographic Genetic Epidemiology

PubMed Central

Sloan, Chantel D.; Duell, Eric J.; Shi, Xun; Irwin, Rebecca; Andrew, Angeline S.; Williams, Scott M.; Moore, Jason H.

2009-01-01

Complex diseases such as cancer and heart disease result from interactions between an individual's genetics and environment, i.e. their human ecology. Rates of complex diseases have consistently demonstrated geographic patterns of incidence, or spatial “clusters” of increased incidence relative to the general population. Likewise, genetic subpopulations and environmental influences are not evenly distributed across space. Merging appropriate methods from genetic epidemiology, ecology and geography will provide a more complete understanding of the spatial interactions between genetics and environment that result in spatial patterning of disease rates. Geographic Information Systems (GIS), which are tools designed specifically for dealing with geographic data and performing spatial analyses to determine their relationship, are key to this kind of data integration. Here the authors introduce a new interdisciplinary paradigm, ecogeographic genetic epidemiology, which uses GIS and spatial statistical analyses to layer genetic subpopulation and environmental data with disease rates and thereby discern the complex gene-environment interactions which result in spatial patterns of incidence. PMID:19025788

A method to associate all possible combinations of genetic and environmental factors using GxE landscape plot.

PubMed

Nagaie, Satoshi; Ogishima, Soichi; Nakaya, Jun; Tanaka, Hiroshi

2015-01-01

Genome-wide association studies (GWAS) and linkage analysis has identified many single nucleotide polymorphisms (SNPs) related to disease. There are many unknown SNPs whose minor allele frequencies (MAFs) as low as 0.005 having intermediate effects with odds ratio between 1.5~3.0. Low frequency variants having intermediate effects on disease pathogenesis are believed to have complex interactions with environmental factors called gene-environment interactions (GxE). Hence, we describe a model using 3D Manhattan plot called GxE landscape plot to visualize the association of p-values for gene-environment interactions (GxE). We used the Gene-Environment iNteraction Simulator 2 (GENS2) program to simulate interactions between two genetic loci and one environmental factor in this exercise. The dataset used for training contains disease status, gender, 20 environmental exposures and 100 genotypes for 170 subjects, and p-values were calculated by Cochran-Mantel-Haenszel chi-squared test on known data. Subsequently, we created a 3D GxE landscape plot of negative logarithm of the association of p-values for all the possible combinations of genetic and environmental factors with their hierarchical clustering. Thus, the GxE landscape plot is a valuable model to predict association of p-values for GxE and similarity among genotypes and environments in the context of disease pathogenesis. GxE - Gene-environment interactions, GWAS - Genome-wide association study, MAFs - Minor allele frequencies, SNPs - Single nucleotide polymorphisms, EWAS - Environment-wide association study, FDR - False discovery rate, JPT+CHB - HapMap population of Japanese in Tokyo, Japan - Han Chinese in Beijing.

Genotype-based association models of complex diseases to detect gene-gene and gene-environment interactions.

PubMed

Lobach, Iryna; Fan, Ruzong; Manga, Prashiela

A central problem in genetic epidemiology is to identify and rank genetic markers involved in a disease. Complex diseases, such as cancer, hypertension, diabetes, are thought to be caused by an interaction of a panel of genetic factors, that can be identified by markers, which modulate environmental factors. Moreover, the effect of each genetic marker may be small. Hence, the association signal may be missed unless a large sample is considered, or a priori biomedical data are used. Recent advances generated a vast variety of a priori information, including linkage maps and information about gene regulatory dependence assembled into curated pathway databases. We propose a genotype-based approach that takes into account linkage disequilibrium (LD) information between genetic markers that are in moderate LD while modeling gene-gene and gene-environment interactions. A major advantage of our method is that the observed genetic information enters a model directly thus eliminating the need to estimate haplotype-phase. Our approach results in an algorithm that is inexpensive computationally and does not suffer from bias induced by haplotype-phase ambiguity. We investigated our model in a series of simulation experiments and demonstrated that the proposed approach results in estimates that are nearly unbiased and have small variability. We applied our method to the analysis of data from a melanoma case-control study and investigated interaction between a set of pigmentation genes and environmental factors defined by age and gender. Furthermore, an application of our method is demonstrated using a study of Alcohol Dependence.

The transcriptomic responses of the eastern oyster, Crassostrea virginica, to environmental conditions.

PubMed

Chapman, Robert W; Mancia, Annalaura; Beal, Marion; Veloso, Artur; Rathburn, Charles; Blair, Anne; Holland, A F; Warr, G W; Didinato, Guy; Sokolova, Inna M; Wirth, Edward F; Duffy, Edward; Sanger, Denise

2011-04-01

Understanding the mechanisms by which organisms adapt to environmental conditions is a fundamental question for ecology and evolution. In this study, we evaluate changes in gene expression of a marine mollusc, the eastern oyster Crassostrea virginica, associated with the physico-chemical conditions and the levels of metals and other contaminants in their environment. The results indicate that transcript signatures can effectively disentangle the complex interactive gene expression responses to the environment and are also capable of disentangling the complex dynamic effects of environmental factors on gene expression. In this context, the mapping of environment to gene and gene to environment is reciprocal and mutually reinforcing. In general, the response of transcripts to the environment is driven by major factors known to affect oyster physiology such as temperature, pH, salinity, and dissolved oxygen, with pollutant levels playing a relatively small role, at least within the range of concentrations found in the studied oyster habitats. Further, the two environmental factors that dominate these effects (temperature and pH) interact in a dynamic and nonlinear fashion to impact gene expression. Transcriptomic data obtained in our study provide insights into the mechanisms of physiological responses to temperature and pH in oysters that are consistent with the known effects of these factors on physiological functions of ectotherms and indicate important linkages between transcriptomics and physiological outcomes. Should these linkages hold in further studies and in other organisms, they may provide a novel integrated approach for assessing the impacts of climate change, ocean acidification and anthropogenic contaminants on aquatic organisms via relatively inexpensive microarray platforms. © 2011 Blackwell Publishing Ltd.

The role of gene-environment interplay in occupational and environmental diseases: current concepts and knowledge gaps.

PubMed

Kwo, Elizabeth; Christiani, David

2017-03-01

The interplay between genetic susceptibilities and environmental exposures in the pathogenesis of a variety of diseases is an area of increased scientific, epidemiologic, and social interest. Given the variation in methodologies used in the field, this review aims to create a framework to help understand occupational exposures as they currently exist and provide a foundation for future inquiries into the biological mechanisms of the gene-environment interactions. Understanding of this complex interplay will be important in the context of occupational health, given the public health concerns surrounding a variety of occupational exposures. Studies found evidence that suggest genetics influence the progression of disease postberyllium exposure through genetically encoded major histocompatibility complex, class II, DP alpha 2 (HLA-DP2)-peptide complexes as it relates to T-helper cells. This was characterized at the molecular level by the accumulation of Be-responsive CD4 T cells in the lung, which resulted in posttranslational change in the HLA-DPB1 complex. These studies provide important evidence of gene-environment association, and many provide insights into specific pathogenic mechanisms. The following includes a review of the literature regarding gene-environment associations with a focus on pulmonary diseases as they relate to the workplace.

Advances in asthma and allergy genetics in 2007.

PubMed

Vercelli, Donata

2008-08-01

This review discusses the main advances in the genetics of asthma and allergy published in the Journal in 2007. The association studies discussed herein addressed 3 main topics: the effect of the environment and gene-environment interactions on asthma/allergy susceptibility, the contribution of T(H)2 immunity gene variants to allergic inflammation, and the role of filaggrin mutations in atopic dermatitis and associated phenotypes. Other articles revealed novel, potentially important candidate genes or confirmed known ones. Collectively, the works published in 2007 reiterate that allergy and asthma are typical complex diseases; that is, they are disorders in which intricate interactions among environmental and genetic factors modify disease susceptibility by altering the fundamental structural and functional properties of target organs at critical developmental windows.

An Efficient Test for Gene-Environment Interaction in Generalized Linear Mixed Models with Family Data.

PubMed

Mazo Lopera, Mauricio A; Coombes, Brandon J; de Andrade, Mariza

2017-09-27

Gene-environment (GE) interaction has important implications in the etiology of complex diseases that are caused by a combination of genetic factors and environment variables. Several authors have developed GE analysis in the context of independent subjects or longitudinal data using a gene-set. In this paper, we propose to analyze GE interaction for discrete and continuous phenotypes in family studies by incorporating the relatedness among the relatives for each family into a generalized linear mixed model (GLMM) and by using a gene-based variance component test. In addition, we deal with collinearity problems arising from linkage disequilibrium among single nucleotide polymorphisms (SNPs) by considering their coefficients as random effects under the null model estimation. We show that the best linear unbiased predictor (BLUP) of such random effects in the GLMM is equivalent to the ridge regression estimator. This equivalence provides a simple method to estimate the ridge penalty parameter in comparison to other computationally-demanding estimation approaches based on cross-validation schemes. We evaluated the proposed test using simulation studies and applied it to real data from the Baependi Heart Study consisting of 76 families. Using our approach, we identified an interaction between BMI and the Peroxisome Proliferator Activated Receptor Gamma ( PPARG ) gene associated with diabetes.

A Fast Multiple-Kernel Method With Applications to Detect Gene-Environment Interaction.

PubMed

Marceau, Rachel; Lu, Wenbin; Holloway, Shannon; Sale, Michèle M; Worrall, Bradford B; Williams, Stephen R; Hsu, Fang-Chi; Tzeng, Jung-Ying

2015-09-01

Kernel machine (KM) models are a powerful tool for exploring associations between sets of genetic variants and complex traits. Although most KM methods use a single kernel function to assess the marginal effect of a variable set, KM analyses involving multiple kernels have become increasingly popular. Multikernel analysis allows researchers to study more complex problems, such as assessing gene-gene or gene-environment interactions, incorporating variance-component based methods for population substructure into rare-variant association testing, and assessing the conditional effects of a variable set adjusting for other variable sets. The KM framework is robust, powerful, and provides efficient dimension reduction for multifactor analyses, but requires the estimation of high dimensional nuisance parameters. Traditional estimation techniques, including regularization and the "expectation-maximization (EM)" algorithm, have a large computational cost and are not scalable to large sample sizes needed for rare variant analysis. Therefore, under the context of gene-environment interaction, we propose a computationally efficient and statistically rigorous "fastKM" algorithm for multikernel analysis that is based on a low-rank approximation to the nuisance effect kernel matrices. Our algorithm is applicable to various trait types (e.g., continuous, binary, and survival traits) and can be implemented using any existing single-kernel analysis software. Through extensive simulation studies, we show that our algorithm has similar performance to an EM-based KM approach for quantitative traits while running much faster. We also apply our method to the Vitamin Intervention for Stroke Prevention (VISP) clinical trial, examining gene-by-vitamin effects on recurrent stroke risk and gene-by-age effects on change in homocysteine level. © 2015 WILEY PERIODICALS, INC.

ATHENA: A knowledge-based hybrid backpropagation-grammatical evolution neural network algorithm for discovering epistasis among quantitative trait Loci

PubMed Central

2010-01-01

Background Growing interest and burgeoning technology for discovering genetic mechanisms that influence disease processes have ushered in a flood of genetic association studies over the last decade, yet little heritability in highly studied complex traits has been explained by genetic variation. Non-additive gene-gene interactions, which are not often explored, are thought to be one source of this "missing" heritability. Methods Stochastic methods employing evolutionary algorithms have demonstrated promise in being able to detect and model gene-gene and gene-environment interactions that influence human traits. Here we demonstrate modifications to a neural network algorithm in ATHENA (the Analysis Tool for Heritable and Environmental Network Associations) resulting in clear performance improvements for discovering gene-gene interactions that influence human traits. We employed an alternative tree-based crossover, backpropagation for locally fitting neural network weights, and incorporation of domain knowledge obtainable from publicly accessible biological databases for initializing the search for gene-gene interactions. We tested these modifications in silico using simulated datasets. Results We show that the alternative tree-based crossover modification resulted in a modest increase in the sensitivity of the ATHENA algorithm for discovering gene-gene interactions. The performance increase was highly statistically significant when backpropagation was used to locally fit NN weights. We also demonstrate that using domain knowledge to initialize the search for gene-gene interactions results in a large performance increase, especially when the search space is larger than the search coverage. Conclusions We show that a hybrid optimization procedure, alternative crossover strategies, and incorporation of domain knowledge from publicly available biological databases can result in marked increases in sensitivity and performance of the ATHENA algorithm for detecting and modelling gene-gene interactions that influence a complex human trait. PMID:20875103

Chronic obstructive pulmonary disease: nature-nurture interactions.

PubMed

Clancy, John; Nobes, Maggie

A person's health status is rarely constant, it is usually subject to continual change as a person moves from health to illness and usually back to health again; the health-illness continuum illustrates this dynamism. This highlights the person's various states of health and illness (ranging from extremely good health to clinically defined mild, moderate and severe illness) and their fluctuations throughout the life span, until ultimately leading to the pathology associated with the person's death. Maintenance of a stable homeostatic environment within the body to support the stability of this continuum depends on a complex series of ultimately intracellular chemical reactions. These reactions are activated by environmental factors that cause the expression of genes associated with healthy phenotypes as well as illness susceptibility genes associated with homeostatic imbalances. Obviously, the body aims to support intracellular and extracellular environments allied with health; however, the complexity of these nature-nurture interactions results in illness throughout an individual's life span. This paper will discuss the nature-nurture interactions of chronic obstructive pulmonary disease.

A Combinatorial Approach to Detecting Gene-Gene and Gene-Environment Interactions in Family Studies

PubMed Central

Lou, Xiang-Yang; Chen, Guo-Bo; Yan, Lei; Ma, Jennie Z.; Mangold, Jamie E.; Zhu, Jun; Elston, Robert C.; Li, Ming D.

2008-01-01

Widespread multifactor interactions present a significant challenge in determining risk factors of complex diseases. Several combinatorial approaches, such as the multifactor dimensionality reduction (MDR) method, have emerged as a promising tool for better detecting gene-gene (G × G) and gene-environment (G × E) interactions. We recently developed a general combinatorial approach, namely the generalized multifactor dimensionality reduction (GMDR) method, which can entertain both qualitative and quantitative phenotypes and allows for both discrete and continuous covariates to detect G × G and G × E interactions in a sample of unrelated individuals. In this article, we report the development of an algorithm that can be used to study G × G and G × E interactions for family-based designs, called pedigree-based GMDR (PGMDR). Compared to the available method, our proposed method has several major improvements, including allowing for covariate adjustments and being applicable to arbitrary phenotypes, arbitrary pedigree structures, and arbitrary patterns of missing marker genotypes. Our Monte Carlo simulations provide evidence that the PGMDR method is superior in performance to identify epistatic loci compared to the MDR-pedigree disequilibrium test (PDT). Finally, we applied our proposed approach to a genetic data set on tobacco dependence and found a significant interaction between two taste receptor genes (i.e., TAS2R16 and TAS2R38) in affecting nicotine dependence. PMID:18834969

Specification, testing, and interpretation of gene-by-measured-environment interaction models in the presence of gene-environment correlation

PubMed Central

Rathouz, Paul J.; Van Hulle, Carol A.; Lee Rodgers, Joseph; Waldman, Irwin D.; Lahey, Benjamin B.

2009-01-01

Purcell (2002) proposed a bivariate biometric model for testing and quantifying the interaction between latent genetic influences and measured environments in the presence of gene-environment correlation. Purcell’s model extends the Cholesky model to include gene-environment interaction. We examine a number of closely-related alternative models that do not involve gene-environment interaction but which may fit the data as well Purcell’s model. Because failure to consider these alternatives could lead to spurious detection of gene-environment interaction, we propose alternative models for testing gene-environment interaction in the presence of gene-environment correlation, including one based on the correlated factors model. In addition, we note mathematical errors in the calculation of effect size via variance components in Purcell’s model. We propose a statistical method for deriving and interpreting variance decompositions that are true to the fitted model. PMID:18293078

Gemini surfactants mediate efficient mitochondrial gene delivery and expression.

PubMed

Cardoso, Ana M; Morais, Catarina M; Cruz, A Rita; Cardoso, Ana L; Silva, Sandra G; do Vale, M Luísa; Marques, Eduardo F; Pedroso de Lima, Maria C; Jurado, Amália S

2015-03-02

Gene delivery targeting mitochondria has the potential to transform the therapeutic landscape of mitochondrial genetic diseases. Taking advantage of the nonuniversal genetic code used by mitochondria, a plasmid DNA construct able to be specifically expressed in these organelles was designed by including a codon, which codes for an amino acid only if read by the mitochondrial ribosomes. In the present work, gemini surfactants were shown to successfully deliver plasmid DNA to mitochondria. Gemini surfactant-based DNA complexes were taken up by cells through a variety of routes, including endocytic pathways, and showed propensity for inducing membrane destabilization under acidic conditions, thus facilitating cytoplasmic release of DNA. Furthermore, the complexes interacted extensively with lipid membrane models mimicking the composition of the mitochondrial membrane, which predicts a favored interaction of the complexes with mitochondria in the intracellular environment. This work unravels new possibilities for gene therapy toward mitochondrial diseases.

Annual Research Review: Developmental Considerations of Gene by Environment Interactions

ERIC Educational Resources Information Center

Lenroot, Rhoshel K.; Giedd, Jay N.

2011-01-01

Biological development is driven by a complex dance between nurture and nature, determined not only by the specific features of the interacting genetic and environmental influences but also by the timing of their rendezvous. The initiation of large-scale longitudinal studies, ever-expanding knowledge of genetics, and increasing availability of…

LPHN3 and Attention-Deficit/Hyperactivity Disorder: Interaction with Maternal Stress during Pregnancy

ERIC Educational Resources Information Center

Choudhry, Zia; Sengupta, Sarojini M.; Grizenko, Natalie; Fortier, Marie-Eve; Thakur, Geeta A.; Bellingham, Johanne; Joober, Ridha

2012-01-01

Background: Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous behavioral disorder, complex both in etiology and clinical expression. Both genetic and environmental factors have been implicated, and it has been suggested that gene-environment interactions may play a pivotal role in the disorder. Recently, a significant association…

Genes for normal sleep and sleep disorders.

PubMed

Tafti, Mehdi; Maret, Stéphanie; Dauvilliers, Yves

2005-01-01

Sleep and wakefulness are complex behaviors that are influenced by many genetic and environmental factors, which are beginning to be discovered. The contribution of genetic components to sleep disorders is also increasingly recognized as important. Point mutations in the prion protein, period 2, and the prepro-hypocretin/orexin gene have been found as the cause of a few sleep disorders but the possibility that other gene defects may contribute to the pathophysiology of major sleep disorders is worth in-depth investigations. However, single gene disorders are rare and most common disorders are complex in terms of their genetic susceptibility, environmental effects, gene-gene, and gene-environment interactions. We review here the current progress in the genetics of normal and pathological sleep.

Mapping DNA damage-dependent genetic interactions in yeast via party mating and barcode fusion genetics.

PubMed

Díaz-Mejía, J Javier; Celaj, Albi; Mellor, Joseph C; Coté, Atina; Balint, Attila; Ho, Brandon; Bansal, Pritpal; Shaeri, Fatemeh; Gebbia, Marinella; Weile, Jochen; Verby, Marta; Karkhanina, Anna; Zhang, YiFan; Wong, Cassandra; Rich, Justin; Prendergast, D'Arcy; Gupta, Gaurav; Öztürk, Sedide; Durocher, Daniel; Brown, Grant W; Roth, Frederick P

2018-05-28

Condition-dependent genetic interactions can reveal functional relationships between genes that are not evident under standard culture conditions. State-of-the-art yeast genetic interaction mapping, which relies on robotic manipulation of arrays of double-mutant strains, does not scale readily to multi-condition studies. Here, we describe barcode fusion genetics to map genetic interactions (BFG-GI), by which double-mutant strains generated via en masse "party" mating can also be monitored en masse for growth to detect genetic interactions. By using site-specific recombination to fuse two DNA barcodes, each representing a specific gene deletion, BFG-GI enables multiplexed quantitative tracking of double mutants via next-generation sequencing. We applied BFG-GI to a matrix of DNA repair genes under nine different conditions, including methyl methanesulfonate (MMS), 4-nitroquinoline 1-oxide (4NQO), bleomycin, zeocin, and three other DNA-damaging environments. BFG-GI recapitulated known genetic interactions and yielded new condition-dependent genetic interactions. We validated and further explored a subnetwork of condition-dependent genetic interactions involving MAG1 , SLX4, and genes encoding the Shu complex, and inferred that loss of the Shu complex leads to an increase in the activation of the checkpoint protein kinase Rad53. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.

Dissecting gene-environment interactions: A penalized robust approach accounting for hierarchical structures.

PubMed

Wu, Cen; Jiang, Yu; Ren, Jie; Cui, Yuehua; Ma, Shuangge

2018-02-10

Identification of gene-environment (G × E) interactions associated with disease phenotypes has posed a great challenge in high-throughput cancer studies. The existing marginal identification methods have suffered from not being able to accommodate the joint effects of a large number of genetic variants, while some of the joint-effect methods have been limited by failing to respect the "main effects, interactions" hierarchy, by ignoring data contamination, and by using inefficient selection techniques under complex structural sparsity. In this article, we develop an effective penalization approach to identify important G × E interactions and main effects, which can account for the hierarchical structures of the 2 types of effects. Possible data contamination is accommodated by adopting the least absolute deviation loss function. The advantage of the proposed approach over the alternatives is convincingly demonstrated in both simulation and a case study on lung cancer prognosis with gene expression measurements and clinical covariates under the accelerated failure time model. Copyright © 2017 John Wiley & Sons, Ltd.

A simulation study of gene-by-environment interactions in GWAS implies ample hidden effects

PubMed Central

Marigorta, Urko M.; Gibson, Greg

2014-01-01

The switch to a modern lifestyle in recent decades has coincided with a rapid increase in prevalence of obesity and other diseases. These shifts in prevalence could be explained by the release of genetic susceptibility for disease in the form of gene-by-environment (GxE) interactions. Yet, the detection of interaction effects requires large sample sizes, little replication has been reported, and a few studies have demonstrated environmental effects only after summing the risk of GWAS alleles into genetic risk scores (GRSxE). We performed extensive simulations of a quantitative trait controlled by 2500 causal variants to inspect the feasibility to detect gene-by-environment interactions in the context of GWAS. The simulated individuals were assigned either to an ancestral or a modern setting that alters the phenotype by increasing the effect size by 1.05–2-fold at a varying fraction of perturbed SNPs (from 1 to 20%). We report two main results. First, for a wide range of realistic scenarios, highly significant GRSxE is detected despite the absence of individual genotype GxE evidence at the contributing loci. Second, an increase in phenotypic variance after environmental perturbation reduces the power to discover susceptibility variants by GWAS in mixed cohorts with individuals from both ancestral and modern environments. We conclude that a pervasive presence of gene-by-environment effects can remain hidden even though it contributes to the genetic architecture of complex traits. PMID:25101110

Gene-gene and gene-environment interactions: new insights into the prevention, detection and management of coronary artery disease.

PubMed

Lanktree, Matthew B; Hegele, Robert A

2009-02-26

Despite the recent success of genome-wide association studies (GWASs) in identifying loci consistently associated with coronary artery disease (CAD), a large proportion of the genetic components of CAD and its metabolic risk factors, including plasma lipids, type 2 diabetes and body mass index, remain unattributed. Gene-gene and gene-environment interactions might produce a meaningful improvement in quantification of the genetic determinants of CAD. Testing for gene-gene and gene-environment interactions is thus a new frontier for large-scale GWASs of CAD. There are several anecdotal examples of monogenic susceptibility to CAD in which the phenotype was worsened by an adverse environment. In addition, small-scale candidate gene association studies with functional hypotheses have identified gene-environment interactions. For future evaluation of gene-gene and gene-environment interactions to achieve the same success as the single gene associations reported in recent GWASs, it will be important to pre-specify agreed standards of study design and statistical power, environmental exposure measurement, phenomic characterization and analytical strategies. Here we discuss these issues, particularly in relation to the investigation and potential clinical utility of gene-gene and gene-environment interactions in CAD.

Gene-Diet Interactions in Childhood Obesity

PubMed Central

Garver, William S

2011-01-01

Childhood overweight and obesity have reached epidemic proportions worldwide, and the increase in weight-associated co-morbidities including premature type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease will soon become major healthcare and economic problems. A number of studies now indicate that the childhood obesity epidemic which has emerged during the past 30 years is a complex multi-factorial disease resulting from interaction of susceptibility genes with an obesogenic environment. This review will focus on gene-diet interactions suspected of having a prominent role in promoting childhood obesity. In particular, the specific genes that will be presented (FTO, MC4R, and NPC1) have recently been associated with childhood obesity through a genome-wide association study (GWAS) and were shown to interact with nutritional components to increase weight gain. Although a fourth gene (APOA2) has not yet been associated with childhood obesity, this review will also present information on what now represents the best characterized gene-diet interaction in promoting weight gain. PMID:22043166

Using imputed genotype data in the joint score tests for genetic association and gene-environment interactions in case-control studies.

PubMed

Song, Minsun; Wheeler, William; Caporaso, Neil E; Landi, Maria Teresa; Chatterjee, Nilanjan

2018-03-01

Genome-wide association studies (GWAS) are now routinely imputed for untyped single nucleotide polymorphisms (SNPs) based on various powerful statistical algorithms for imputation trained on reference datasets. The use of predicted allele counts for imputed SNPs as the dosage variable is known to produce valid score test for genetic association. In this paper, we investigate how to best handle imputed SNPs in various modern complex tests for genetic associations incorporating gene-environment interactions. We focus on case-control association studies where inference for an underlying logistic regression model can be performed using alternative methods that rely on varying degree on an assumption of gene-environment independence in the underlying population. As increasingly large-scale GWAS are being performed through consortia effort where it is preferable to share only summary-level information across studies, we also describe simple mechanisms for implementing score tests based on standard meta-analysis of "one-step" maximum-likelihood estimates across studies. Applications of the methods in simulation studies and a dataset from GWAS of lung cancer illustrate ability of the proposed methods to maintain type-I error rates for the underlying testing procedures. For analysis of imputed SNPs, similar to typed SNPs, the retrospective methods can lead to considerable efficiency gain for modeling of gene-environment interactions under the assumption of gene-environment independence. Methods are made available for public use through CGEN R software package. © 2017 WILEY PERIODICALS, INC.

Interactome of Obesity: Obesidome : Genetic Obesity, Stress Induced Obesity, Pathogenic Obesity Interaction.

PubMed

Geronikolou, Styliani A; Pavlopoulou, Athanasia; Cokkinos, Dennis; Chrousos, George

2017-01-01

Obesity is a chronic disease of increasing prevalence reaching epidemic proportions. Genetic defects as well as epigenetic effects contribute to the obesity phenotype. Investigating gene (e.g. MC4R defects)-environment (behavior, infectious agents, stress) interactions is a relative new field of great research interest. In this study, we have made an effort to create an interactome (henceforth referred to as "obesidome"), where extrinsic stressors response, intrinsic predisposition, immunity response to inflammation and autonomous nervous system implications are integrated. These pathways are presented in one interactome network for the first time. In our study, obesity-related genes/gene products were found to form a complex interactions network.

Gene-environment studies: any advantage over environmental studies?

PubMed

Bermejo, Justo Lorenzo; Hemminki, Kari

2007-07-01

Gene-environment studies have been motivated by the likely existence of prevalent low-risk genes that interact with common environmental exposures. The present study assessed the statistical advantage of the simultaneous consideration of genes and environment to investigate the effect of environmental risk factors on disease. In particular, we contemplated the possibility that several genes modulate the environmental effect. Environmental exposures, genotypes and phenotypes were simulated according to a wide range of parameter settings. Different models of gene-gene-environment interaction were considered. For each parameter combination, we estimated the probability of detecting the main environmental effect, the power to identify the gene-environment interaction and the frequency of environmentally affected individuals at which environmental and gene-environment studies show the same statistical power. The proportion of cases in the population attributable to the modeled risk factors was also calculated. Our data indicate that environmental exposures with weak effects may account for a significant proportion of the population prevalence of the disease. A general result was that, if the environmental effect was restricted to rare genotypes, the power to detect the gene-environment interaction was higher than the power to identify the main environmental effect. In other words, when few individuals contribute to the overall environmental effect, individual contributions are large and result in easily identifiable gene-environment interactions. Moreover, when multiple genes interacted with the environment, the statistical benefit of gene-environment studies was limited to those studies that included major contributors to the gene-environment interaction. The advantage of gene-environment over plain environmental studies also depends on the inheritance mode of the involved genes, on the study design and, to some extend, on the disease prevalence.

Dissection of complicate genetic architecture and breeding perspective of cottonseed traits by genome-wide association study.

PubMed

Du, Xiongming; Liu, Shouye; Sun, Junling; Zhang, Gengyun; Jia, Yinhua; Pan, Zhaoe; Xiang, Haitao; He, Shoupu; Xia, Qiuju; Xiao, Songhua; Shi, Weijun; Quan, Zhiwu; Liu, Jianguang; Ma, Jun; Pang, Baoyin; Wang, Liru; Sun, Gaofei; Gong, Wenfang; Jenkins, Johnie N; Lou, Xiangyang; Zhu, Jun; Xu, Haiming

2018-06-13

Cottonseed is one of the most important raw materials for plant protein, oil and alternative biofuel for diesel engines. Understanding the complex genetic basis of cottonseed traits is requisite for achieving efficient genetic improvement of the traits. However, it is not yet clear about their genetic architecture in genomic level. GWAS has been an effective way to explore genetic basis of quantitative traits in human and many crops. This study aims to dissect genetic mechanism seven cottonseed traits by a GWAS for genetic improvement. A genome-wide association study (GWAS) based on a full gene model with gene effects as fixed and gene-environment interaction as random, was conducted for protein, oil and 5 fatty acids using 316 accessions and ~ 390 K SNPs. Totally, 124 significant quantitative trait SNPs (QTSs), consisting of 16, 21, 87 for protein, oil and fatty acids (palmitic, linoleic, oleic, myristic, stearic), respectively, were identified and the broad-sense heritability was estimated from 71.62 to 93.43%; no QTS-environment interaction was detected for the protein, the palmitic and the oleic contents; the protein content was predominantly controlled by epistatic effects accounting for 65.18% of the total variation, but the oil content and the fatty acids except the palmitic were mainly determined by gene main effects and no epistasis was detected for the myristic and the stearic. Prediction of superior pure line and hybrid revealed the potential of the QTSs in the improvement of cottonseed traits, and the hybrid could achieve higher or lower genetic values compared with pure lines. This study revealed complex genetic architecture of seven cottonseed traits at whole genome-wide by mixed linear model approach; the identified genetic variants and estimated genetic component effects of gene, gene-gene and gene-environment interaction provide cotton geneticist or breeders new knowledge on the genetic mechanism of the traits and the potential molecular breeding design strategy.

Prevention of asthma: where are we in the 21st century?

PubMed

Propp, Phaedra; Becker, Allan

2013-12-01

Asthma is the most common chronic disease of childhood and, in the latter part of the 20th century, reached epidemic proportions. Asthma is generally believed to result from gene-environment interactions. There is consensus that a 'window of opportunity' exists during pregnancy and early in life when environmental factors may influence its development. We review multiple environmental, biologic and sociologic factors that may be important in the development of asthma. Meta-analyses of studies have demonstrated that multifaceted interventions are required in order to develop asthma prevention. Multifaceted allergen reduction studies have shown clinical benefits. Asthma represents a dysfunctional interaction with our genes and the environment to which they are exposed, especially in fetal and early infant life. The increasing prevalence of asthma also may be an indication of increased population risk for the development of other chronic non-communicable autoimmune diseases. This review will focus on the factors which may be important in the primary prevention of asthma. Better understanding of the complex gene-environment interactions involved in the development of asthma will provide insight into personalized interventions for asthma prevention.

Levels of behavioral organization and the evolution of division of labor

NASA Astrophysics Data System (ADS)

Page, Robert E.; Erber, Joachim

2002-03-01

The major features of insect societies that fascinate biologists are the self-sacrificing altruism expressed by colony members, the complex division of labor, and the tremendous plasticity demonstrated in the face of changing environments. The social behavior of insects is a result of complex interactions at different levels of biological organization. Genes give rise to proteins and peptides that build the nervous and muscular systems, regulate their own synthesis, interact with each other, and affect the behavior of individuals. Social behavior emerges from the complex interactions of individuals that are themselves far removed from the direct effects of the genes. In order to understand how social organization evolves, we must understand the mechanisms that link the different levels of organization. In this review, we discuss how behavior is influenced by genes and the neural system and how social behavior emerges from the behavioral activities of individuals. We show how different levels of organization share common features and are linked through common mechanisms. We focus on the behavior of the honey bee, the best studied of all social insects.

Environmental confounding in gene-environment interaction studies.

PubMed

Vanderweele, Tyler J; Ko, Yi-An; Mukherjee, Bhramar

2013-07-01

We show that, in the presence of uncontrolled environmental confounding, joint tests for the presence of a main genetic effect and gene-environment interaction will be biased if the genetic and environmental factors are correlated, even if there is no effect of either the genetic factor or the environmental factor on the disease. When environmental confounding is ignored, such tests will in fact reject the joint null of no genetic effect with a probability that tends to 1 as the sample size increases. This problem with the joint test vanishes under gene-environment independence, but it still persists if estimating the gene-environment interaction parameter itself is of interest. Uncontrolled environmental confounding will bias estimates of gene-environment interaction parameters even under gene-environment independence, but it will not do so if the unmeasured confounding variable itself does not interact with the genetic factor. Under gene-environment independence, if the interaction parameter without controlling for the environmental confounder is nonzero, then there is gene-environment interaction either between the genetic factor and the environmental factor of interest or between the genetic factor and the unmeasured environmental confounder. We evaluate several recently proposed joint tests in a simulation study and discuss the implications of these results for the conduct of gene-environment interaction studies.

Autism risk factors: genes, environment, and gene-environment interactions

PubMed Central

Chaste, Pauline; Leboyer, Marion

2012-01-01

The aim of this review is to summarize the key findings from genetic and epidemiological research, which show that autism is a complex disorder resulting from the combination of genetic and environmental factors. Remarkable advances in the knowledge of genetic causes of autism have resulted from the great efforts made in the field of genetics. The identification of specific alleles contributing to the autism spectrum has supplied important pieces for the autism puzzle. However, many questions remain unanswered, and new questions are raised by recent results. Moreover, given the amount of evidence supporting a significant contribution of environmental factors to autism risk, it is now clear that the search for environmental factors should be reinforced. One aspect of this search that has been neglected so far is the study of interactions between genes and environmental factors. PMID:23226953

Positional cloning in mice and its use for molecular dissection of inflammatory arthritis.

PubMed

Abe, Koichiro; Yu, Philipp

2009-02-01

One of the upcoming next quests in the field of genetics might be molecular dissection of the genetic and environmental components of human complex diseases. In humans, however, there are certain experimental limitations for identification of a single component of the complex interactions by genetic analyses. Experimental animals offer simplified models for genetic and environmental interactions in human complex diseases. In particular, mice are the best mammalian models because of a long history and ample experience for genetic analyses. Forward genetics, which includes genetic screen and subsequent positional cloning of the causative genes, is a powerful strategy to dissect a complex phenomenon without preliminarily molecular knowledge of the process. In this review, first, we describe a general scheme of positional cloning in mice. Next, recent accomplishments on the patho-mechanisms of inflammatory arthritis by forward genetics approaches are introduced; Positional cloning effort for skg, Ali5, Ali18, cmo, and lupo mutants are provided as examples for the application to human complex diseases. As seen in the examples, the identification of genetic factors by positional cloning in the mouse have potential in solving molecular complexity of gene-environment interactions in human complex diseases.

Learning contextual gene set interaction networks of cancer with condition specificity

PubMed Central

2013-01-01

Background Identifying similarities and differences in the molecular constitutions of various types of cancer is one of the key challenges in cancer research. The appearances of a cancer depend on complex molecular interactions, including gene regulatory networks and gene-environment interactions. This complexity makes it challenging to decipher the molecular origin of the cancer. In recent years, many studies reported methods to uncover heterogeneous depictions of complex cancers, which are often categorized into different subtypes. The challenge is to identify diverse molecular contexts within a cancer, to relate them to different subtypes, and to learn underlying molecular interactions specific to molecular contexts so that we can recommend context-specific treatment to patients. Results In this study, we describe a novel method to discern molecular interactions specific to certain molecular contexts. Unlike conventional approaches to build modular networks of individual genes, our focus is to identify cancer-generic and subtype-specific interactions between contextual gene sets, of which each gene set share coherent transcriptional patterns across a subset of samples, termed contextual gene set. We then apply a novel formulation for quantitating the effect of the samples from each subtype on the calculated strength of interactions observed. Two cancer data sets were analyzed to support the validity of condition-specificity of identified interactions. When compared to an existing approach, the proposed method was much more sensitive in identifying condition-specific interactions even in heterogeneous data set. The results also revealed that network components specific to different types of cancer are related to different biological functions than cancer-generic network components. We found not only the results that are consistent with previous studies, but also new hypotheses on the biological mechanisms specific to certain cancer types that warrant further investigations. Conclusions The analysis on the contextual gene sets and characterization of networks of interaction composed of these sets discovered distinct functional differences underlying various types of cancer. The results show that our method successfully reveals many subtype-specific regions in the identified maps of biological contexts, which well represent biological functions that can be connected to specific subtypes. PMID:23418942

The Tangled Tale of Genes and Environment: Moore's The Dependent Gene: The Fallacy of “nature VS. Nurture”

PubMed Central

Schneider, Susan M

2007-01-01

Nature–nurture views that smack of genetic determinism remain prevalent. Yet, the increasing knowledge base shows ever more clearly that environmental factors and genes form a fully interactional system at all levels. Moore's book covers the major topics of discovery and dispute, including behavior genetics and the twin studies, developmental psychobiology, and developmental systems theory. Knowledge of this larger life-sciences context for behavior principles will become increasingly important as the full complexity of gene–environment relations is revealed. Behavior analysis both contributes to and gains from the larger battle for the recognition of how nature and nurture really work.

Accounting for Population Structure in Gene-by-Environment Interactions in Genome-Wide Association Studies Using Mixed Models.

PubMed

Sul, Jae Hoon; Bilow, Michael; Yang, Wen-Yun; Kostem, Emrah; Furlotte, Nick; He, Dan; Eskin, Eleazar

2016-03-01

Although genome-wide association studies (GWASs) have discovered numerous novel genetic variants associated with many complex traits and diseases, those genetic variants typically explain only a small fraction of phenotypic variance. Factors that account for phenotypic variance include environmental factors and gene-by-environment interactions (GEIs). Recently, several studies have conducted genome-wide gene-by-environment association analyses and demonstrated important roles of GEIs in complex traits. One of the main challenges in these association studies is to control effects of population structure that may cause spurious associations. Many studies have analyzed how population structure influences statistics of genetic variants and developed several statistical approaches to correct for population structure. However, the impact of population structure on GEI statistics in GWASs has not been extensively studied and nor have there been methods designed to correct for population structure on GEI statistics. In this paper, we show both analytically and empirically that population structure may cause spurious GEIs and use both simulation and two GWAS datasets to support our finding. We propose a statistical approach based on mixed models to account for population structure on GEI statistics. We find that our approach effectively controls population structure on statistics for GEIs as well as for genetic variants.

Gene-environment interactions in mental disorders

PubMed Central

Tsuang, Ming T; Bar, Jessica L; Stone, William S; Faraone, Stephen V

2004-01-01

Research clearly shows that both nature and nurture play important roles in the genesis of psychopathology. In this paper, we focus on 'gene-environment interaction' in mental disorders, using genetic control of sensitivity to the environment as our definition of that term. We begin with an examination of methodological issues involving gene-environment interactions, with examples concerning psychiatric and neurological conditions. Then we review the interactions in psychiatric disorders using twin, adoption and association designs. Finally, we consider gene-environment interactions in selected neurodevelopmental disorders (autism and schizophrenia). PMID:16633461

Differential susceptibility to maternal expressed emotion in children with ADHD and their siblings? Investigating plasticity genes, prosocial and antisocial behaviour.

PubMed

Richards, Jennifer S; Hartman, Catharina A; Franke, Barbara; Hoekstra, Pieter J; Heslenfeld, Dirk J; Oosterlaan, Jaap; Arias Vásquez, Alejandro; Buitelaar, Jan K

2015-02-01

The differential susceptibility theory states that children differ in their susceptibility towards environmental experiences, partially due to plasticity genes. Individuals carrying specific variants in such genes will be more disadvantaged in negative but, conversely, more advantaged in positive environments. Understanding gene-environment interactions may help unravel the causal mechanisms involved in multifactorial psychiatric disorders such as Attention-Deficit/Hyperactivity Disorder (ADHD). The differential susceptibility theory was examined by investigating the presence of interaction effects between maternal expressed emotion (EE; warmth and criticism) and the solitary and combined effects of plasticity genes (DAT1, DRD4, 5-HTT) on prosocial and antisocial behaviour (measured with parent- and self-reports) in children with ADHD and their siblings (N = 366, M = 17.11 years, 74.9% male). Maternal warmth was positively associated with prosocial behaviour and negatively with antisocial behaviour, while maternal criticism was positively associated with antisocial behaviour and negatively with prosocial behaviour. No evidence of differential susceptibility was found. The current study found no evidence for differential susceptibility based on the selected plasticity genes, in spite of strong EE-behaviour associations. It is likely that additional factors play a role in the complex relationship between genes, environment and behaviour.

Differential Susceptibility to Maternal Expressed Emotion in Children with ADHD and their Siblings? Investigating Plasticity Genes, Prosocial and Antisocial Behaviour

PubMed Central

Richards, Jennifer S.; Hartman, Catharina A.; Franke, Barbara; Hoekstra, Pieter J.; Heslenfeld, Dirk J.; Oosterlaan, Jaap; Vásquez, Alejandro Arias; Buitelaar, Jan K.

2014-01-01

Background The differential susceptibility theory states that children differ in their susceptibility towards environmental experiences, partially due to plasticity genes. Individuals carrying specific variants in such genes will be more disadvantaged in negative but, conversely, more advantageous in positive environments. Understanding gene-environment interactions may help unravel the causal mechanisms involved in multifactorial psychiatric disorders such as Attention-Deficit/Hyperactivity Disorder (ADHD). Methods The differential susceptibility theory was examined by investigating the presence of interaction effects between maternal expressed emotion (EE; warmth and criticism) and the solitary and combined effects of plasticity genes (DAT1, DRD4, 5-HTT) on prosocial and antisocial behaviour (measured with parent- and self-reports) in children with ADHD and their siblings (N=366, M=17.11 years, 74.9 % male). Results Maternal warmth was positively associated with prosocial behaviour and negatively with antisocial behaviour, while maternal criticism was positively associated with antisocial behaviour and negatively with prosocial behaviour. No evidence of differential susceptibility was found. Conclusions The current study found no evidence for differential susceptibility based on the selected plasticity genes, in spite of strong EE-behaviour associations. It is likely that additional factors play a role in the complex relationship between genes, environment and behaviour. PMID:24929324

Genetic determinants of prepubertal and pubertal growth and development.

PubMed

Thomis, Martine A; Towne, Bradford

2006-12-01

This article surveys the current general understanding of genetic influences on within- and between-population variation in growth and development in the context of establishing an International Growth Standard for Preadolescent and Adolescent Children. Traditional genetic epidemiologic analysis methods are reviewed, and evidence from family studies for genetic effects on different measures of growth and development is then presented. Findings from linkage and association studies seeking to identify specific genomic locations and allelic variants of genes influencing variation in growth and maturation are then summarized. Special mention is made of the need to study the interactions between genes and environments. At present, specific genes and polymorphisms contributing to variation in growth and maturation are only beginning to be identified. Larger genetic epidemiologic studies are needed in different parts of the world to better explore population differences in gene frequencies and gene-environment interactions. As advances continue to be made in molecular and statistical genetic methods, the genetic architecture of complex processes, including those of growth and development, will become better elucidated. For now, it can only be concluded that although the fundamental genetic underpinnings of the growth and development of children worldwide are likely to be essentially the same, there are also likely to be differences between populations in the frequencies of allelic gene variants that influence growth and maturation and in the nature of gene-environment interactions. This does not necessarily preclude an international growth reference, but it does have important implications for the form that such a reference might ultimately take.

Review: the Contribution of both Nature and Nurture to Carcinogenesis and Progression in Solid Tumours.

PubMed

Hyndman, Iain Joseph

2016-04-01

Cancer is a leading cause of mortality worldwide. Cancer arises due to a series of somatic mutations that accumulate within the nucleus of a cell which enable the cell to proliferate in an unregulated manner. These mutations arise as a result of both endogenous and exogenous factors. Genes that are commonly mutated in cancer cells are involved in cell cycle regulation, growth and proliferation. It is known that both nature and nurture play important roles in cancer development through complex gene-environment interactions; however, the exact mechanism of these interactions in carcinogenesis is presently unclear. Key environmental factors that play a role in carcinogenesis include smoking, UV light and oncoviruses. Angiogenesis, inflammation and altered cell metabolism are important factors in carcinogenesis and are influenced by both genetic and environmental factors. Although the exact mechanism of nature-nurture interactions in solid tumour formation are not yet fully understood, it is evident that neither nature nor nurture can be considered in isolation. By understanding more about gene-environment interactions, it is possible that cancer mortality could be reduced.

Genetic and environmental influences on the development of alcoholism: resilience vs. risk.

PubMed

Enoch, Mary-Anne

2006-12-01

The physiological changes of adolescence may promote risk-taking behaviors, including binge drinking. Approximately 40% of alcoholics were already drinking heavily in late adolescence. Most cases of alcoholism are established by the age of 30 years with the peak prevalence at 18-23 years of age. Therefore the key time frame for the development, and prevention, of alcoholism lies in adolescence and young adulthood. Severe childhood stressors have been associated with increased vulnerability to addiction, however, not all stress-exposed children go on to develop alcoholism. Origins of resilience can be both genetic (variation in alcohol-metabolizing genes, increased susceptibility to alcohol's sedative effects) and environmental (lack of alcohol availability, positive peer and parental support). Genetic vulnerability is likely to be conferred by multiple genes of small to modest effects, possibly only apparent in gene-environment interactions. For example, it has been shown that childhood maltreatment interacts with a monoamine oxidase A (MAOA) gene variant to predict antisocial behavior that is often associated with alcoholism, and an interaction between early life stress and a serotonin transporter promoter variant predicts alcohol abuse in nonhuman primates and depression in humans. In addition, a common Met158 variant in the catechol-O-methyltransferase (COMT) gene can confer both risk and resilience to alcoholism in different drinking environments. It is likely that a complex mix of gene(s)-environment(s) interactions underlie addiction vulnerability and development. Risk-resilience factors can best be determined in longitudinal studies, preferably starting during pregnancy. This kind of research is important for planning future measures to prevent harmful drinking in adolescence.

The interaction of combined effects of the BDNF and PRKCG genes and negative life events in major depressive disorder.

PubMed

Yang, Chunxia; Sun, Ning; Liu, Zhifen; Li, Xinrong; Xu, Yong; Zhang, Kerang

2016-03-30

Major depressive disorder (MDD) is a mental disorder that results from complex interplay between multiple and partially overlapping sets of susceptibility genes and environmental factors. The brain derived neurotrophic factor (BDNF) and Protein kinase C gamma type (PRKCG) are logical candidate genes in MDD. Among diverse environmental factors, negative life events have been suggested to exert a crucial impact on brain development. In the present study, we hypothesized that interactions between genetic variants in BDNF and PRKCG and negative life events may play an important role in the development of MDD. We recruited a total of 406 patients with MDD and 391 age- and gender-matched control subjects. Gene-environment interactions were analyzed using generalized multifactor dimensionality reduction (GMDR). Under a dominant model, we observed a significant three-way interaction among BDNF rs6265, PRKCG rs3745406, and negative life events. The gene-environment combination of PRKCG rs3745406 C allele, BDNF rs6265 G allele and high level of negative life events (C-G-HN) was significantly associated with MDD (OR, 5.97; 95% CI, 2.71-13.15). To our knowledge, this is the first report of evidence that the BDNF-PRKCG interaction may modify the relationship between negative life events and MDD in the Chinese population. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Quantitative gene-gene and gene-environment mapping for leaf shape variation using tree-based models.

PubMed

Fu, Guifang; Dai, Xiaotian; Symanzik, Jürgen; Bushman, Shaun

2017-01-01

Leaf shape traits have long been a focus of many disciplines, but the complex genetic and environmental interactive mechanisms regulating leaf shape variation have not yet been investigated in detail. The question of the respective roles of genes and environment and how they interact to modulate leaf shape is a thorny evolutionary problem, and sophisticated methodology is needed to address it. In this study, we investigated a framework-level approach that inputs shape image photographs and genetic and environmental data, and then outputs the relative importance ranks of all variables after integrating shape feature extraction, dimension reduction, and tree-based statistical models. The power of the proposed framework was confirmed by simulation and a Populus szechuanica var. tibetica data set. This new methodology resulted in the detection of novel shape characteristics, and also confirmed some previous findings. The quantitative modeling of a combination of polygenetic, plastic, epistatic, and gene-environment interactive effects, as investigated in this study, will improve the discernment of quantitative leaf shape characteristics, and the methods are ready to be applied to other leaf morphology data sets. Unlike the majority of approaches in the quantitative leaf shape literature, this framework-level approach is data-driven, without assuming any pre-known shape attributes, landmarks, or model structures. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Genotype-environment interaction and sociology: contributions and complexities.

PubMed

Seabrook, Jamie A; Avison, William R

2010-05-01

Genotype-environment interaction (G x E) refers to situations in which genetic effects connected to a phenotype are dependent upon variability in the environment, or when genes modify an organism's sensitivity to particular environmental features. Using a typology suggested in the G x E literature, we provide an overview of recent papers that show how social context can trigger a genetic vulnerability, compensate for a genetic vulnerability, control behaviors for which a genetic vulnerability exists, and improve adaptation via proximal causes. We argue that to improve their understanding of social structure, sociologists can take advantage of research in behavior genetics by assessing the impact of within-group variance of various health outcomes and complex human behaviors that are explainable by genotype, environment and their interaction. Insights from life course sociology can aid in ensuring that the dynamic nature of the environment in G x E has been accounted for. Identification of an appropriate entry point for sociologists interested in G x E research could begin with the choice of an environmental feature of interest, a genetic factor of interest, and/or behavior of interest. Optimizing measurement in order to capture the complexity of G x E is critical. Examining the interaction between poorly measured environmental factors and well measured genetic variables will overestimate the effects of genetic variables while underestimating the effect of environmental influences, thereby distorting the interaction between genotype and environment. Although the expense of collecting environmental data is very high, reliable and precise measurement of an environmental pathogen enhances a study's statistical power. Copyright 2010 Elsevier Ltd. All rights reserved.

Exploring the complexity of intellectual disability in fetal alcohol spectrum disorders.

PubMed

Chokroborty-Hoque, Aniruddho; Alberry, Bonnie; Singh, Shiva M

2014-01-01

Brain development in mammals is long lasting. It begins early during embryonic growth and is finalized in early adulthood. This progression represents a delicate choreography of molecular, cellular, and physiological processes initiated and directed by the fetal genotype in close interaction with environment. Not surprisingly, most aberrations in brain functioning including intellectual disability (ID) are attributed to either gene(s), or environment or the interaction of the two. The ensuing complexity has made the assessment of this choreography, ever challenging. A model to assess this complexity has used a mouse model (C57BL/6J or B6) that is subjected to prenatal alcohol exposure. The resulting pups show learning and memory deficits similar to patients with fetal alcohol spectrum disorder (FASD), which is associated with life-long changes in gene expression. Interestingly, this change in gene expression underlies epigenetic processes including DNA methylation and miRNAs. This paradigm is applicable to ethanol exposure at different developmental times (binge at trimesters 1, 2, and 3 as well as continuous preference drinking (70%) of 10% alcohol by B6 females during pregnancy). The exposure leads to life-long changes in neural epigenetic marks, gene expression, and a variety of defects in neurodevelopment and CNS function. We argue that this cascade may be reversed postnatally via drugs, chemicals, and environment including maternal care. Such conclusions are supported by two sets of results. First, antipsychotic drugs that are used to treat ID including psychosis function via changes in DNA methylation, a major epigenetic mark. Second, post-natal environment may improve (with enriched environments) or worsen (with negative and maternal separation stress) the cognitive ability of pups that were prenatally exposed to ethanol as well as their matched controls. In this review, we will discuss operational epigenetic mechanisms involved in the development of intellectual ability/disability in response to alcohol during prenatal or post-natal development. In doing so, we will explore the potential of epigenetic manipulation in the treatment of FASD and related disorders implicated in ID.

Exploring the Complexity of Intellectual Disability in Fetal Alcohol Spectrum Disorders

PubMed Central

Chokroborty-Hoque, Aniruddho; Alberry, Bonnie; Singh, Shiva M.

2014-01-01

Brain development in mammals is long lasting. It begins early during embryonic growth and is finalized in early adulthood. This progression represents a delicate choreography of molecular, cellular, and physiological processes initiated and directed by the fetal genotype in close interaction with environment. Not surprisingly, most aberrations in brain functioning including intellectual disability (ID) are attributed to either gene(s), or environment or the interaction of the two. The ensuing complexity has made the assessment of this choreography, ever challenging. A model to assess this complexity has used a mouse model (C57BL/6J or B6) that is subjected to prenatal alcohol exposure. The resulting pups show learning and memory deficits similar to patients with fetal alcohol spectrum disorder (FASD), which is associated with life-long changes in gene expression. Interestingly, this change in gene expression underlies epigenetic processes including DNA methylation and miRNAs. This paradigm is applicable to ethanol exposure at different developmental times (binge at trimesters 1, 2, and 3 as well as continuous preference drinking (70%) of 10% alcohol by B6 females during pregnancy). The exposure leads to life-long changes in neural epigenetic marks, gene expression, and a variety of defects in neurodevelopment and CNS function. We argue that this cascade may be reversed postnatally via drugs, chemicals, and environment including maternal care. Such conclusions are supported by two sets of results. First, antipsychotic drugs that are used to treat ID including psychosis function via changes in DNA methylation, a major epigenetic mark. Second, post-natal environment may improve (with enriched environments) or worsen (with negative and maternal separation stress) the cognitive ability of pups that were prenatally exposed to ethanol as well as their matched controls. In this review, we will discuss operational epigenetic mechanisms involved in the development of intellectual ability/disability in response to alcohol during prenatal or post-natal development. In doing so, we will explore the potential of epigenetic manipulation in the treatment of FASD and related disorders implicated in ID. PMID:25207264

Nutrigenomics and nutrigenetics in inflammatory bowel diseases.

PubMed

Gruber, Lisa; Lichti, Pia; Rath, Eva; Haller, Dirk

2012-10-01

Inflammatory bowel diseases (IBD) including ulcerative colitis and Crohn's disease are chronically relapsing, immune-mediated disorders of the gastrointestinal tract. A major challenge in the treatment of IBD is the heterogenous nature of these pathologies. Both, ulcerative colitis and Crohn's disease are of multifactorial etiology and feature a complex interaction of host genetic susceptibility and environmental factors such as diet and gut microbiota. Genome-wide association studies identified disease-relevant single-nucleotide polymorphisms in approximately 100 genes, but at the same time twin studies also clearly indicated a strong environmental impact in disease development. However, attempts to link dietary factors to the risk of developing IBD, based on epidemiological observations showed controversial outcomes. Yet, emerging high-throughput technologies implying complete biological systems might allow taking nutrient-gene interactions into account for a better classification of patient subsets in the future. In this context, 2 new scientific fields, "nutrigenetics" and "nutrigenomics" have been established. "Nutrigenetics," studying the effect of genetic variations on nutrient-gene interactions and "Nutrigenomics," describing the impact of nutrition on physiology and health status on the level of gene transcription, protein expression, and metabolism. It is hoped that the integration of both research areas will promote the understanding of the complex gene-environment interaction in IBD etiology and in the long-term will lead to personalized nutrition for disease prevention and treatment. This review briefly summarizes data on the impact of nutrients on intestinal inflammation, highlights nutrient-gene interactions, and addresses the potential of applying "omic" technologies in the context of IBD.

Genotype-Based Association Mapping of Complex Diseases: Gene-Environment Interactions with Multiple Genetic Markers and Measurement Error in Environmental Exposures

PubMed Central

Lobach, Irvna; Fan, Ruzone; Carroll, Raymond T.

2011-01-01

With the advent of dense single nucleotide polymorphism genotyping, population-based association studies have become the major tools for identifying human disease genes and for fine gene mapping of complex traits. We develop a genotype-based approach for association analysis of case-control studies of gene-environment interactions in the case when environmental factors are measured with error and genotype data are available on multiple genetic markers. To directly use the observed genotype data, we propose two genotype-based models: genotype effect and additive effect models. Our approach offers several advantages. First, the proposed risk functions can directly incorporate the observed genotype data while modeling the linkage disequihbrium information in the regression coefficients, thus eliminating the need to infer haplotype phase. Compared with the haplotype-based approach, an estimating procedure based on the proposed methods can be much simpler and significantly faster. In addition, there is no potential risk due to haplotype phase estimation. Further, by fitting the proposed models, it is possible to analyze the risk alleles/variants of complex diseases, including their dominant or additive effects. To model measurement error, we adopt the pseudo-likelihood method by Lobach et al. [2008]. Performance of the proposed method is examined using simulation experiments. An application of our method is illustrated using a population-based case-control study of association between calcium intake with the risk of colorectal adenoma development. PMID:21031455

Gene-environment interactions in cancer epidemiology: a National Cancer Institute Think Tank report.

PubMed

Hutter, Carolyn M; Mechanic, Leah E; Chatterjee, Nilanjan; Kraft, Peter; Gillanders, Elizabeth M

2013-11-01

Cancer risk is determined by a complex interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified hundreds of common (minor allele frequency [MAF] > 0.05) and less common (0.01 < MAF < 0.05) genetic variants associated with cancer. The marginal effects of most of these variants have been small (odds ratios: 1.1-1.4). There remain unanswered questions on how best to incorporate the joint effects of genes and environment, including gene-environment (G × E) interactions, into epidemiologic studies of cancer. To help address these questions, and to better inform research priorities and allocation of resources, the National Cancer Institute sponsored a "Gene-Environment Think Tank" on January 10-11, 2012. The objective of the Think Tank was to facilitate discussions on (1) the state of the science, (2) the goals of G × E interaction studies in cancer epidemiology, and (3) opportunities for developing novel study designs and analysis tools. This report summarizes the Think Tank discussion, with a focus on contemporary approaches to the analysis of G × E interactions. Selecting the appropriate methods requires first identifying the relevant scientific question and rationale, with an important distinction made between analyses aiming to characterize the joint effects of putative or established genetic and environmental factors and analyses aiming to discover novel risk factors or novel interaction effects. Other discussion items include measurement error, statistical power, significance, and replication. Additional designs, exposure assessments, and analytical approaches need to be considered as we move from the current small number of success stories to a fuller understanding of the interplay of genetic and environmental factors. © 2013 WILEY PERIODICALS, INC.

Evolution of environmental exposure science: Using breath-borne biomarkers for “discovery” of the human exposome

EPA Science Inventory

According to recent research, 70-90% of long-term latency and chronic human disease incidence is attributable to environmental (human exposome) factors through the gene x environment interaction. Environmental exposures are complex and involve many thousands of chemicals, a mult...

Epigenetic regulation in murine offspring as a novel mechanism for transmaternal asthma protection induced by microbes

USDA-ARS?s Scientific Manuscript database

Bronchial asthma is a chronic inflammatory disease resulting from complex gene-environment interactions. Natural microbial exposure has been identified as an important environmental condition that provides asthma protection in a prenatal window of opportunity. Epigenetic regulation is an important m...

Divergent functional isoforms drive niche specialisation for nutrient acquisition and use in rumen microbiome.

PubMed

Rubino, Francesco; Carberry, Ciara; M Waters, Sinéad; Kenny, David; McCabe, Matthew S; Creevey, Christopher J

2017-04-01

Many microbes in complex competitive environments share genes for acquiring and utilising nutrients, questioning whether niche specialisation exists and if so, how it is maintained. We investigated the genomic signatures of niche specialisation in the rumen microbiome, a highly competitive, anaerobic environment, with limited nutrient availability determined by the biomass consumed by the host. We generated individual metagenomic libraries from 14 cows fed an ad libitum diet of grass silage and calculated functional isoform diversity for each microbial gene identified. The animal replicates were used to calculate confidence intervals to test for differences in diversity of functional isoforms between microbes that may drive niche specialisation. We identified 153 genes with significant differences in functional isoform diversity between the two most abundant bacterial genera in the rumen (Prevotella and Clostridium). We found Prevotella possesses a more diverse range of isoforms capable of degrading hemicellulose, whereas Clostridium for cellulose. Furthermore, significant differences were observed in key metabolic processes indicating that isoform diversity plays an important role in maintaining their niche specialisation. The methods presented represent a novel approach for untangling complex interactions between microorganisms in natural environments and have resulted in an expanded catalogue of gene targets central to rumen cellulosic biomass degradation.

Host Genotype and Microbiota Contribute Asymmetrically to Transcriptional Variation in the Threespine Stickleback Gut

PubMed Central

Small, Clayton M.; Milligan-Myhre, Kathryn; Bassham, Susan; Guillemin, Karen

2017-01-01

Recent studies of interactions between hosts and their resident microbes have revealed important ecological and evolutionary consequences that emerge from these complex interspecies relationships, including diseases that occur when the interactions go awry. Given the preponderance of these interactions, we hypothesized that effects of the microbiota on gene expression in the developing gut—an important aspect of host biology—would be pervasive, and that these effects would be both comparable in magnitude to and contingent on effects of the host genetic background. To evaluate the effects of the microbiota, host genotype, and their interaction on gene expression in the gut of a genetically diverse, gnotobiotic host model, the threespine stickleback (Gasterosteus aculeatus), we compared RNA-seq data among 84 larval fish. Surprisingly, we found that stickleback population and family differences explained substantially more gene expression variation than the presence of microbes. Expression levels of 72 genes, however, were affected by our microbiota treatment. These genes, including many associated with innate immunity, comprise a tractable subset of host genetic factors for precise, systems-level study of host–microbe interactions in the future. Importantly, our data also suggest subtle signatures of a statistical interaction between host genotype and the microbiota on expression patterns of genetic pathways associated with innate immunity, coagulation and complement cascades, focal adhesion, cancer, and peroxisomes. These genotype-by-environment interactions may prove to be important leads to the understanding of host genetic mechanisms commonly at the root of sometimes complex molecular relationships between hosts and their resident microbes. PMID:28391321

SNP by SNP by environment interaction network of alcoholism.

PubMed

Zollanvari, Amin; Alterovitz, Gil

2017-03-14

Alcoholism has a strong genetic component. Twin studies have demonstrated the heritability of a large proportion of phenotypic variance of alcoholism ranging from 50-80%. The search for genetic variants associated with this complex behavior has epitomized sequence-based studies for nearly a decade. The limited success of genome-wide association studies (GWAS), possibly precipitated by the polygenic nature of complex traits and behaviors, however, has demonstrated the need for novel, multivariate models capable of quantitatively capturing interactions between a host of genetic variants and their association with non-genetic factors. In this regard, capturing the network of SNP by SNP or SNP by environment interactions has recently gained much interest. Here, we assessed 3,776 individuals to construct a network capable of detecting and quantifying the interactions within and between plausible genetic and environmental factors of alcoholism. In this regard, we propose the use of first-order dependence tree of maximum weight as a potential statistical learning technique to delineate the pattern of dependencies underpinning such a complex trait. Using a predictive based analysis, we further rank the genes, demographic factors, biological pathways, and the interactions represented by our SNP [Formula: see text]SNP[Formula: see text]E network. The proposed framework is quite general and can be potentially applied to the study of other complex traits.

Epigenetics and obesity: the devil is in the details.

PubMed

Franks, Paul W; Ling, Charlotte

2010-12-21

Obesity is a complex disease with multiple well-defined risk factors. Nevertheless, susceptibility to obesity and its sequelae within obesogenic environments varies greatly from one person to the next, suggesting a role for gene × environment interactions in the etiology of the disorder. Epigenetic regulation of the human genome provides a putative mechanism by which specific environmental exposures convey risk for obesity and other human diseases and is one possible mechanism that underlies the gene × environment/treatment interactions observed in epidemiological studies and clinical trials. A study published in BMC Medicine this month by Wang et al. reports on an examination of DNA methylation in peripheral blood leukocytes of lean and obese adolescents, comparing methylation patterns between the two groups. The authors identified two genes that were differentially methylated, both of which have roles in immune function. Here we overview the findings from this study in the context of those emerging from other recent genetic and epigenetic studies, discuss the strengths and weaknesses of the study and speculate on the future of epigenetics in chronic disease research.

Robustness of meta-analyses in finding gene × environment interactions

PubMed Central

Shi, Gang; Nehorai, Arye

2017-01-01

Meta-analyses that synthesize statistical evidence across studies have become important analytical tools for genetic studies. Inspired by the success of genome-wide association studies of the genetic main effect, researchers are searching for gene × environment interactions. Confounders are routinely included in the genome-wide gene × environment interaction analysis as covariates; however, this does not control for any confounding effects on the results if covariate × environment interactions are present. We carried out simulation studies to evaluate the robustness to the covariate × environment confounder for meta-regression and joint meta-analysis, which are two commonly used meta-analysis methods for testing the gene × environment interaction or the genetic main effect and interaction jointly. Here we show that meta-regression is robust to the covariate × environment confounder while joint meta-analysis is subject to the confounding effect with inflated type I error rates. Given vast sample sizes employed in genome-wide gene × environment interaction studies, non-significant covariate × environment interactions at the study level could substantially elevate the type I error rate at the consortium level. When covariate × environment confounders are present, type I errors can be controlled in joint meta-analysis by including the covariate × environment terms in the analysis at the study level. Alternatively, meta-regression can be applied, which is robust to potential covariate × environment confounders. PMID:28362796

MapReduce Algorithms for Inferring Gene Regulatory Networks from Time-Series Microarray Data Using an Information-Theoretic Approach.

PubMed

Abduallah, Yasser; Turki, Turki; Byron, Kevin; Du, Zongxuan; Cervantes-Cervantes, Miguel; Wang, Jason T L

2017-01-01

Gene regulation is a series of processes that control gene expression and its extent. The connections among genes and their regulatory molecules, usually transcription factors, and a descriptive model of such connections are known as gene regulatory networks (GRNs). Elucidating GRNs is crucial to understand the inner workings of the cell and the complexity of gene interactions. To date, numerous algorithms have been developed to infer gene regulatory networks. However, as the number of identified genes increases and the complexity of their interactions is uncovered, networks and their regulatory mechanisms become cumbersome to test. Furthermore, prodding through experimental results requires an enormous amount of computation, resulting in slow data processing. Therefore, new approaches are needed to expeditiously analyze copious amounts of experimental data resulting from cellular GRNs. To meet this need, cloud computing is promising as reported in the literature. Here, we propose new MapReduce algorithms for inferring gene regulatory networks on a Hadoop cluster in a cloud environment. These algorithms employ an information-theoretic approach to infer GRNs using time-series microarray data. Experimental results show that our MapReduce program is much faster than an existing tool while achieving slightly better prediction accuracy than the existing tool.

Leveraging Gene-Environment Interactions and Endotypes for Asthma Gene Discovery

PubMed Central

Bønnelykke, Klaus; Ober, Carole

2016-01-01

Asthma is a heterogeneous clinical syndrome that includes subtypes of disease with different underlying causes and disease mechanisms. Asthma is caused by a complex interaction between genes and environmental exposures; early-life exposures in particular play an important role. Asthma is also heritable, and a number of susceptibility variants have been discovered in genome-wide association studies, although the known risk alleles explain only a small proportion of the heritability. In this review, we present evidence supporting the hypothesis that focusing on more specific asthma phenotypes, such as childhood asthma with severe exacerbations, and on relevant exposures that are involved in gene-environment interactions (GEIs), such as rhinovirus infections, will improve detection of asthma genes and our understanding of the underlying mechanisms. We will discuss the challenges of considering GEIs and the advantages of studying responses to asthma-associated exposures in clinical birth cohorts, as well as in cell models of GEIs, to dissect the context-specific nature of genotypic risks, to prioritize variants in genome-wide association studies, and to identify pathways involved in pathogenesis in subgroups of patients. We propose that such approaches, in spite of their many challenges, present great opportunities for better understanding of asthma pathogenesis and heterogeneity and, ultimately, for improving prevention and treatment of disease. PMID:26947980

PROP taster status interacts with the built environment to influence children's food acceptance and body weight status.

PubMed

Burd, Carlye; Senerat, Araliya; Chambers, Earle; Keller, Kathleen L

2013-04-01

Eating behaviors and obesity are complex phenotypes influenced by genes and the environment, but few studies have investigated the interaction of these two variables. The purpose of this study was to use a gene-environment interaction model to test for differences in children's food acceptance and body weights. Inherited ability to taste 6-n-propylthiouracil (PROP) was assessed as a marker of oral taste responsiveness. Food environment was classified as "healthy" or "unhealthy" based on proximity to outlets that sell fruits/vegetables and fast foods using Geographic Information Systems (GIS). The cohort consisted of 120 children, ages 4-6 years, recruited from New York City over 2005-2010. Home address and other demographic variables were reported by parents and PROP status, food acceptance, and anthropometrics were assessed in the laboratory. Based on a screening test, children were classified as PROP tasters or non-tasters. Hierarchical linear models analysis of variance was performed to examine differences in food acceptance and body mass index (BMI) z-scores as a function of PROP status, the food environment ("healthy" vs. "unhealthy"), and their interaction. Results showed an interaction between taster status and the food environment on BMI z-score and food acceptance. Non-taster children living in healthy food environments had greater acceptance of vegetables than taster children living in healthy food environments (P ≤ 0.005). Moreover, non-tasters from unhealthy food environments had higher BMI z-scores than all other groups (P ≤ 0.005). Incorporating genetic markers of taste into studies that assess the built environment may improve the ability of these measures to predict risk for obesity and eating behaviors. Copyright © 2012 The Obesity Society.

PROP taster status interacts with the built environment to influence children's food acceptance and body weight status

PubMed Central

Burd, Carlye; Senerat, Araliya; Chambers, Earle; Keller, Kathleen L.

2012-01-01

Eating behaviors and obesity are complex phenotypes influenced by genes and access to foods in the environment, but few studies have investigated the interaction of these two variables. The purpose of this study was to use a gene-environment interaction model to test for differences in children's food acceptance and body weights. Inherited ability to taste 6-n-propylthiouracil (PROP) was assessed as a marker of oral taste responsiveness. Food environment was classified as “healthy” or “unhealthy” based on proximity to outlets that sell fruits/vegetables and fast foods using Geographic Information Systems (GIS). The cohort consisted of 120 children, ages 4–6 years, recruited from New York City over 2005–2010. Home address and other demographic variables were reported by parents and PROP status, food acceptance, and anthropometrics were assessed in the laboratory. Based on a screening test, children were classified as PROP tasters or non-tasters. Hierarchical linear models analysis of variance was performed to examine differences in food acceptance and body mass index (BMI) z-scores as a function of PROP status, the food environment (“healthy” vs. “unhealthy”), and their interaction. Results showed an interaction between taster status and the food environment on BMI z-score and food acceptance. Non-taster children living in healthy food environments had greater acceptance of vegetables than taster children living in healthy food environments (p≤0.005). Moreover, non-tasters from unhealthy food environments had higher BMI z-scores than all other groups (p≤0.005). Incorporating genetic markers of taste into studies that assess the built environment may improve the ability of these measures to predict risk for obesity and eating behaviors. PMID:23401219

Gene-environment interaction in major depression: focus on experience-dependent biological systems.

PubMed

Lopizzo, Nicola; Bocchio Chiavetto, Luisella; Cattane, Nadia; Plazzotta, Giona; Tarazi, Frank I; Pariante, Carmine M; Riva, Marco A; Cattaneo, Annamaria

2015-01-01

Major depressive disorder (MDD) is a multifactorial and polygenic disorder, where multiple and partially overlapping sets of susceptibility genes interact each other and with the environment, predisposing individuals to the development of the illness. Thus, MDD results from a complex interplay of vulnerability genes and environmental factors that act cumulatively throughout individual's lifetime. Among these environmental factors, stressful life experiences, especially those occurring early in life, have been suggested to exert a crucial impact on brain development, leading to permanent functional changes that may contribute to lifelong risk for mental health outcomes. In this review, we will discuss how genetic variants (polymorphisms, SNPs) within genes operating in neurobiological systems that mediate stress response and synaptic plasticity, can impact, by themselves, the vulnerability risk for MDD; we will also consider how this MDD risk can be further modulated when gene × environment interaction is taken into account. Finally, we will discuss the role of epigenetic mechanisms, and in particular of DNA methylation and miRNAs expression changes, in mediating the effect of the stress on the vulnerability risk to develop MDD. Taken together, we aim to underlie the role of genetic and epigenetic processes involved in stress- and neuroplasticity-related biological systems on the development of MDD after exposure to early life stress, thereby building the basis for future research and clinical interventions.

Gene-environment interaction and suicidal behavior.

PubMed

Roy, Alec; Sarchiopone, Marco; Carli, Vladimir

2009-07-01

Studies have increasingly shown that gene-environment interactions are important in psychiatry. Suicidal behavior is a major public health problem. Suicide is generally considered to be a multi-determined act involving various areas of proximal and distal risk. Genetic risk factors are estimated to account for approximately 30% to 40% of the variance in suicidal behavior. In this article, the authors review relevant studies concerning the interaction between the serotonin transporter gene and environmental variables as a model of gene-environment interactions that may have an impact on suicidal behavior. The findings reviewed here suggest that there may be meaningful interactions between distal and proximal suicide risk factors that may amplify the risk of suicidal behavior. Future studies of suicidal behavior should examine both genetic and environmental variables and examine for gene-environment interactions.

Measured Gene-by-Environment Interaction in Relation to Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Nigg, Joel; Nikolas, Molly; Burt, S. Alexandra

2010-01-01

Objective: To summarize and evaluate the state of knowledge regarding the role of measured gene-by-environment interactions in relation to attention-deficit/hyperactivity disorder. Method: A selective review of methodologic issues was followed by a systematic search for relevant articles on measured gene-by-environment interactions; the search…

Why study gene-environment interactions?

USDA-ARS?s Scientific Manuscript database

PURPOSE OF REVIEW: We examine the reasons for investigating gene-environment interactions and address recent reports evaluating interactions between genes and environmental modulators in relation to cardiovascular disease and its common risk factors. RECENT FINDINGS: Studies focusing on smoking, phy...

Chemical-gene interaction networks and causal reasoning for biological effects prediction and prioritization of contaminants for environmental monitoring and surveillance

EPA Science Inventory

Evaluating the potential human health and ecological risks associated with exposures to complex chemical mixtures in the environment is one of the main challenges of chemical safety assessment and environmental protection. There is a need for approaches that can help to integrat...

Chemical-gene interaction networks and causal reasoning for biological effects prediction and prioritization of contaminants for environmental monitoring and surveillance (poster)

EPA Science Inventory

Product Description:Evaluation of the potential effects of complex mixtures of chemicals in the environment is challenged by the lack of extensive toxicity data for many chemicals. However, there are growing sources of online information that curate and compile literature reports...

Conceptual shifts needed to understand the dynamic interactions of genes, environment, epigenetics, social processes, and behavioral choices.

PubMed

Jackson, Fatimah L C; Niculescu, Mihai D; Jackson, Robert T

2013-10-01

Social and behavioral research in public health is often intimately tied to profound, but frequently neglected, biological influences from underlying genetic, environmental, and epigenetic events. The dynamic interplay between the life, social, and behavioral sciences often remains underappreciated and underutilized in addressing complex diseases and disorders and in developing effective remediation strategies. Using a case-study format, we present examples as to how the inclusion of genetic, environmental, and epigenetic data can augment social and behavioral health research by expanding the parameters of such studies, adding specificity to phenotypic assessments, and providing additional internal control in comparative studies. We highlight the important roles of gene-environment interactions and epigenetics as sources of phenotypic change and as a bridge between the life and social and behavioral sciences in the development of robust interdisciplinary analyses.

Gene-Environment Interplay in the Association between Pubertal Timing and Delinquency in Adolescent Girls

PubMed Central

Harden, K. Paige; Mendle, Jane

2014-01-01

Early pubertal timing places girls at elevated risk for a breadth of negative outcomes, including involvement in delinquent behavior. While previous developmental research has emphasized the unique social challenges faced by early maturing girls, this relation is complicated by genetic influences for both delinquent behavior and pubertal timing, which are seldom controlled for in existing research. The current study uses genetically informed data on 924 female-female twin and sibling pairs drawn from the National Longitudinal Study of Adolescent Health to (1) disentangle biological versus environmental mechanisms for the effects of early pubertal timing and (2) test for gene-environment interactions. Results indicate that early pubertal timing influences girls’ delinquency through a complex interplay between biological risk and environmental experiences. Genes related to earlier age at menarche and higher perceived development significantly predict increased involvement in both non-violent and violent delinquency. Moreover, after accounting for this genetic association between pubertal timing and delinquency, the impact of non-shared environmental influences on delinquency are significantly moderated by pubertal timing, such that the non-shared environment is most important among early maturing girls. This interaction effect is particularly evident for non-violent delinquency. Overall, results suggest early maturing girls are vulnerable to an interaction between genetic and environmental risks for delinquent behavior. PMID:21668078

Environmental Interactions and Epistasis Are Revealed in the Proteomic Responses to Complex Stimuli

PubMed Central

Samir, Parimal; Rahul; Slaughter, James C.; Link, Andrew J.

2015-01-01

Ultimately, the genotype of a cell and its interaction with the environment determine the cell’s biochemical state. While the cell’s response to a single stimulus has been studied extensively, a conceptual framework to model the effect of multiple environmental stimuli applied concurrently is not as well developed. In this study, we developed the concepts of environmental interactions and epistasis to explain the responses of the S. cerevisiae proteome to simultaneous environmental stimuli. We hypothesize that, as an abstraction, environmental stimuli can be treated as analogous to genetic elements. This would allow modeling of the effects of multiple stimuli using the concepts and tools developed for studying gene interactions. Mirroring gene interactions, our results show that environmental interactions play a critical role in determining the state of the proteome. We show that individual and complex environmental stimuli behave similarly to genetic elements in regulating the cellular responses to stimuli, including the phenomena of dominance and suppression. Interestingly, we observed that the effect of a stimulus on a protein is dominant over other stimuli if the response to the stimulus involves the protein. Using publicly available transcriptomic data, we find that environmental interactions and epistasis regulate transcriptomic responses as well. PMID:26247773

Environmentally induced changes in correlated responses to selection reveal variable pleiotropy across a complex genetic network.

PubMed

Sikkink, Kristin L; Reynolds, Rose M; Cresko, William A; Phillips, Patrick C

2015-05-01

Selection in novel environments can lead to a coordinated evolutionary response across a suite of characters. Environmental conditions can also potentially induce changes in the genetic architecture of complex traits, which in turn could alter the pattern of the multivariate response to selection. We describe a factorial selection experiment using the nematode Caenorhabditis remanei in which two different stress-related phenotypes (heat and oxidative stress resistance) were selected under three different environmental conditions. The pattern of covariation in the evolutionary response between phenotypes or across environments differed depending on the environment in which selection occurred, including asymmetrical responses to selection in some cases. These results indicate that variation in pleiotropy across the stress response network is highly sensitive to the external environment. Our findings highlight the complexity of the interaction between genes and environment that influences the ability of organisms to acclimate to novel environments. They also make clear the need to identify the underlying genetic basis of genetic correlations in order understand how patterns of pleiotropy are distributed across complex genetic networks. © 2015 The Author(s).

ENVIRONMENTALLY INDUCED CHANGES IN CORRELATED RESPONSES TO SELECTION REVEAL VARIABLE PLEIOTROPY ACROSS A COMPLEX GENETIC NETWORK

PubMed Central

Sikkink, Kristin L.; Reynolds, Rose M.; Cresko, William A.; Phillips, Patrick C.

2017-01-01

Selection in novel environments can lead to a coordinated evolutionary response across a suite of characters. Environmental conditions can also potentially induce changes in the genetic architecture of complex traits, which in turn could alter the pattern of the multivariate response to selection. We describe a factorial selection experiment using the nematode Caenorhabditis remanei in which two different stress-related phenotypes (heat and oxidative stress resistance) were selected under three different environmental conditions. The pattern of covariation in the evolutionary response between phenotypes or across environments differed depending on the environment in which selection occurred, including asymmetrical responses to selection in some cases. These results indicate that variation in pleiotropy across the stress response network is highly sensitive to the external environment. Our findings highlight the complexity of the interaction between genes and environment that influences the ability of organisms to acclimate to novel environments. They also make clear the need to identify the underlying genetic basis of genetic correlations in order understand how patterns of pleiotropy are distributed across complex genetic networks. PMID:25809411

Review of the Gene-Environment Interaction Literature in Cancer: What Do We Know?

PubMed

Simonds, Naoko I; Ghazarian, Armen A; Pimentel, Camilla B; Schully, Sheri D; Ellison, Gary L; Gillanders, Elizabeth M; Mechanic, Leah E

2016-07-01

Risk of cancer is determined by a complex interplay of genetic and environmental factors. Although the study of gene-environment interactions (G×E) has been an active area of research, little is reported about the known findings in the literature. To examine the state of the science in G×E research in cancer, we performed a systematic review of published literature using gene-environment or pharmacogenomic flags from two curated databases of genetic association studies, the Human Genome Epidemiology (HuGE) literature finder and Cancer Genome-Wide Association and Meta Analyses Database (CancerGAMAdb), from January 1, 2001, to January 31, 2011. A supplemental search using HuGE was conducted for articles published from February 1, 2011, to April 11, 2013. A 25% sample of the supplemental publications was reviewed. A total of 3,019 articles were identified in the original search. From these articles, 243 articles were determined to be relevant based on inclusion criteria (more than 3,500 interactions). From the supplemental search (1,400 articles identified), 29 additional relevant articles (1,370 interactions) were included. The majority of publications in both searches examined G×E in colon, rectal, or colorectal; breast; or lung cancer. Specific interactions examined most frequently included environmental factors categorized as energy balance (e.g., body mass index, diet), exogenous (e.g., oral contraceptives) and endogenous hormones (e.g., menopausal status), chemical environment (e.g., grilled meats), and lifestyle (e.g., smoking, alcohol intake). In both searches, the majority of interactions examined were using loci from candidate genes studies and none of the studies were genome-wide interaction studies (GEWIS). The most commonly reported measure was the interaction P-value, of which a sizable number of P-values were considered statistically significant (i.e., <0.05). In addition, the magnitude of interactions reported was modest. Observations of published literature suggest that opportunity exists for increased sample size in G×E research, including GWAS-identified loci in G×E studies, exploring more GWAS approaches in G×E such as GEWIS, and improving the reporting of G×E findings. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Review of the Gene-Environment Interaction Literature in Cancer: What do we know?

PubMed Central

Simonds, Naoko I.; Ghazarian, Armen A.; Pimentel, Camilla B.; Schully, Sheri D.; Ellison, Gary L.; Gillanders, Elizabeth M.; Mechanic, Leah E.

2016-01-01

Background Risk of cancer is determined by a complex interplay of genetic and environmental factors. Although the study of gene-environment (GxE) interactions has been an active area of research, little is reported about the known findings in the literature. Methods To examine the state of the science in GxE research in cancer, we performed a systematic review of published literature using gene-environment or pharmacogenomic flags from two curated databases of genetic association studies, the Human Genome Epidemiology (HuGE) literature finder and Cancer Genome-Wide Association and Meta Analyses Database (CancerGAMAdb), from January 1, 2001, to January 31, 2011. A supplemental search using HuGE was conducted for articles published February 1, 2011, to April 11, 2013. A 25% sample of the supplemental publications was reviewed. Results A total of 3,019 articles were identified in the original search. From these articles, 243 articles were determined to be relevant based on inclusion criteria (more than 3,500 interactions). From the supplemental search (1,400 articles identified), 29 additional relevant articles (1,370 interactions) were included. The majority of publications in both searches examined GxE in colon, rectal, or colorectal cancer types; breast; or lung cancer. Specific interactions examined most frequently included environmental factors categorized as energy balance (e.g., body mass index (BMI), diet), exogenous (e.g., oral contraceptives) and endogenous hormones (e.g., menopausal status), chemical environment (e.g., grilled meats), and lifestyle (e.g., smoking, alcohol intake). In both searches, the majority of interactions examined were using loci from candidate genes studies and none of the studies were genome-wide interaction studies (GEWIS). The most commonly reported measure was the interaction p-value, of which a sizable number of p-values were considered statistically significant (i.e., < 0.05). In addition, the magnitudes of interactions reported were modest. Conclusion Observations of published literature suggest that opportunity exists for increased sample size in GxE research, including GWAS identified loci in GxE studies, exploring more GWAS approaches in GxE such as GEWIS, and improving the reporting of GxE findings. PMID:27061572

An Arabidopsis Gene Regulatory Network for Secondary Cell Wall Synthesis

PubMed Central

Taylor-Teeples, M; Lin, L; de Lucas, M; Turco, G; Toal, TW; Gaudinier, A; Young, NF; Trabucco, GM; Veling, MT; Lamothe, R; Handakumbura, PP; Xiong, G; Wang, C; Corwin, J; Tsoukalas, A; Zhang, L; Ware, D; Pauly, M; Kliebenstein, DJ; Dehesh, K; Tagkopoulos, I; Breton, G; Pruneda-Paz, JL; Ahnert, SE; Kay, SA; Hazen, SP; Brady, SM

2014-01-01

Summary The plant cell wall is an important factor for determining cell shape, function and response to the environment. Secondary cell walls, such as those found in xylem, are composed of cellulose, hemicelluloses and lignin and account for the bulk of plant biomass. The coordination between transcriptional regulation of synthesis for each polymer is complex and vital to cell function. A regulatory hierarchy of developmental switches has been proposed, although the full complement of regulators remains unknown. Here, we present a protein-DNA network between Arabidopsis transcription factors and secondary cell wall metabolic genes with gene expression regulated by a series of feed-forward loops. This model allowed us to develop and validate new hypotheses about secondary wall gene regulation under abiotic stress. Distinct stresses are able to perturb targeted genes to potentially promote functional adaptation. These interactions will serve as a foundation for understanding the regulation of a complex, integral plant component. PMID:25533953

Genetic and environmental factors affecting cryptic variations in gene regulatory networks

PubMed Central

2013-01-01

Background Cryptic genetic variation (CGV) is considered to facilitate phenotypic evolution by producing visible variations in response to changes in the internal and/or external environment. Several mechanisms enabling the accumulation and release of CGVs have been proposed. In this study, we focused on gene regulatory networks (GRNs) as an important mechanism for producing CGVs, and examined how interactions between GRNs and the environment influence the number of CGVs by using individual-based simulations. Results Populations of GRNs were allowed to evolve under various stabilizing selections, and we then measured the number of genetic and phenotypic variations that had arisen. Our results showed that CGVs were not depleted irrespective of the strength of the stabilizing selection for each phenotype, whereas the visible fraction of genetic variation in a population decreased with increasing strength of selection. On the other hand, increasing the number of different environments that individuals encountered within their lifetime (i.e., entailing plastic responses to multiple environments) suppressed the accumulation of CGVs, whereas the GRNs with more genes and interactions were favored in such heterogeneous environments. Conclusions Given the findings that the number of CGVs in a population was largely determined by the size (order) of GRNs, we propose that expansion of GRNs and adaptation to novel environments are mutually facilitating and sustainable sources of evolvability and hence the origins of biological diversity and complexity. PMID:23622056

Genetic and environmental factors affecting cryptic variations in gene regulatory networks.

PubMed

Iwasaki, Watal M; Tsuda, Masaki E; Kawata, Masakado

2013-04-26

Cryptic genetic variation (CGV) is considered to facilitate phenotypic evolution by producing visible variations in response to changes in the internal and/or external environment. Several mechanisms enabling the accumulation and release of CGVs have been proposed. In this study, we focused on gene regulatory networks (GRNs) as an important mechanism for producing CGVs, and examined how interactions between GRNs and the environment influence the number of CGVs by using individual-based simulations. Populations of GRNs were allowed to evolve under various stabilizing selections, and we then measured the number of genetic and phenotypic variations that had arisen. Our results showed that CGVs were not depleted irrespective of the strength of the stabilizing selection for each phenotype, whereas the visible fraction of genetic variation in a population decreased with increasing strength of selection. On the other hand, increasing the number of different environments that individuals encountered within their lifetime (i.e., entailing plastic responses to multiple environments) suppressed the accumulation of CGVs, whereas the GRNs with more genes and interactions were favored in such heterogeneous environments. Given the findings that the number of CGVs in a population was largely determined by the size (order) of GRNs, we propose that expansion of GRNs and adaptation to novel environments are mutually facilitating and sustainable sources of evolvability and hence the origins of biological diversity and complexity.

The impact of horizontal gene transfer on the adaptive ability of the human oral microbiome.

PubMed

Roberts, Adam P; Kreth, Jens

2014-01-01

The oral microbiome is composed of a multitude of different species of bacteria, each capable of occupying one or more of the many different niches found within the human oral cavity. This community exhibits many types of complex interactions which enable it to colonize and rapidly respond to changes in the environment in which they live. One of these interactions is the transfer, or acquisition, of DNA within this environment, either from co-resident bacterial species or from exogenous sources. Horizontal gene transfer in the oral cavity gives some of the resident bacteria the opportunity to sample a truly enormous metagenome affording them considerable adaptive potential which may be key to survival in such a varying environment. In this review the underlying mechanisms of HGT are discussed in relation to the oral microbiome with numerous examples described where the direct acquisition of exogenous DNA has contributed to the fitness of the bacterial host within the human oral cavity.

Is Lead Exposure in Early Life An Environmental Risk Factor for Schizophrenia? Neurobiological Connections and Testable Hypotheses

PubMed Central

Guilarte, Tomás R.; Opler, Mark; Pletnikov, Mikhail

2013-01-01

Schizophrenia is a devastating neuropsychiatric disorder of unknown etiology. There is general agreement in the scientific community that schizophrenia is a disorder of neurodevelopmental origin in which both genes and environmental factors come together to produce a schizophrenia phenotype later in life. The challenging questions have been which genes and what environmental factors? Although there is evidence that different chromosome loci and several genes impart susceptibility for schizophrenia; and epidemiological studies point to broad aspects of the environment, only recently there has been an interest in studying gene × environment interactions. Recent evidence of a potential association between prenatal lead (Pb2+) exposure and schizophrenia precipitated the search for plausible neurobiological connections. The most promising connection is that in schizophrenia and in developmental Pb2+ exposure there is strong evidence for hypoactivity of the N-methyl-d-aspartate (NMDA) subtype of excitatory amino acid receptors as an underlying neurobiological mechanism in both conditions. A hypofunction of the NMDA receptor (NMDAR) complex during critical periods of development may alter neurobiological processes that are essential for brain growth and wiring, synaptic plasticity and cognitive and behavioral outcomes associated with schizophrenia. We also describe on-going proof of concept gene-environment interaction studies of early life Pb2+ exposure in mice expressing the human mutant form of the disrupted in schizophrenia 1 (DISC-1) gene, a gene that is strongly associated with schizophrenia and allied mental disorders. PMID:22178136

Polygenic scores predict alcohol problems in an independent sample and show moderation by the environment.

PubMed

Salvatore, Jessica E; Aliev, Fazil; Edwards, Alexis C; Evans, David M; Macleod, John; Hickman, Matthew; Lewis, Glyn; Kendler, Kenneth S; Loukola, Anu; Korhonen, Tellervo; Latvala, Antti; Rose, Richard J; Kaprio, Jaakko; Dick, Danielle M

2014-04-10

Alcohol problems represent a classic example of a complex behavioral outcome that is likely influenced by many genes of small effect. A polygenic approach, which examines aggregate measured genetic effects, can have predictive power in cases where individual genes or genetic variants do not. In the current study, we first tested whether polygenic risk for alcohol problems-derived from genome-wide association estimates of an alcohol problems factor score from the age 18 assessment of the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 4304 individuals of European descent; 57% female)-predicted alcohol problems earlier in development (age 14) in an independent sample (FinnTwin12; n = 1162; 53% female). We then tested whether environmental factors (parental knowledge and peer deviance) moderated polygenic risk to predict alcohol problems in the FinnTwin12 sample. We found evidence for both polygenic association and for additive polygene-environment interaction. Higher polygenic scores predicted a greater number of alcohol problems (range of Pearson partial correlations 0.07-0.08, all p-values ≤ 0.01). Moreover, genetic influences were significantly more pronounced under conditions of low parental knowledge or high peer deviance (unstandardized regression coefficients (b), p-values (p), and percent of variance (R2) accounted for by interaction terms: b = 1.54, p = 0.02, R2 = 0.33%; b = 0.94, p = 0.04, R2 = 0.30%, respectively). Supplementary set-based analyses indicated that the individual top single nucleotide polymorphisms (SNPs) contributing to the polygenic scores were not individually enriched for gene-environment interaction. Although the magnitude of the observed effects are small, this study illustrates the usefulness of polygenic approaches for understanding the pathways by which measured genetic predispositions come together with environmental factors to predict complex behavioral outcomes.

Computational intelligence in bioinformatics: SNP/haplotype data in genetic association study for common diseases.

PubMed

Kelemen, Arpad; Vasilakos, Athanasios V; Liang, Yulan

2009-09-01

Comprehensive evaluation of common genetic variations through association of single-nucleotide polymorphism (SNP) structure with common complex disease in the genome-wide scale is currently a hot area in human genome research due to the recent development of the Human Genome Project and HapMap Project. Computational science, which includes computational intelligence (CI), has recently become the third method of scientific enquiry besides theory and experimentation. There have been fast growing interests in developing and applying CI in disease mapping using SNP and haplotype data. Some of the recent studies have demonstrated the promise and importance of CI for common complex diseases in genomic association study using SNP/haplotype data, especially for tackling challenges, such as gene-gene and gene-environment interactions, and the notorious "curse of dimensionality" problem. This review provides coverage of recent developments of CI approaches for complex diseases in genetic association study with SNP/haplotype data.

Divergent functional isoforms drive niche specialisation for nutrient acquisition and use in rumen microbiome

PubMed Central

Rubino, Francesco; Carberry, Ciara; M Waters, Sinéad; Kenny, David; McCabe, Matthew S; Creevey, Christopher J

2017-01-01

Many microbes in complex competitive environments share genes for acquiring and utilising nutrients, questioning whether niche specialisation exists and if so, how it is maintained. We investigated the genomic signatures of niche specialisation in the rumen microbiome, a highly competitive, anaerobic environment, with limited nutrient availability determined by the biomass consumed by the host. We generated individual metagenomic libraries from 14 cows fed an ad libitum diet of grass silage and calculated functional isoform diversity for each microbial gene identified. The animal replicates were used to calculate confidence intervals to test for differences in diversity of functional isoforms between microbes that may drive niche specialisation. We identified 153 genes with significant differences in functional isoform diversity between the two most abundant bacterial genera in the rumen (Prevotella and Clostridium). We found Prevotella possesses a more diverse range of isoforms capable of degrading hemicellulose, whereas Clostridium for cellulose. Furthermore, significant differences were observed in key metabolic processes indicating that isoform diversity plays an important role in maintaining their niche specialisation. The methods presented represent a novel approach for untangling complex interactions between microorganisms in natural environments and have resulted in an expanded catalogue of gene targets central to rumen cellulosic biomass degradation. PMID:28085156

Why nature prevails over nurture in the making of the elite athlete.

PubMed

Georgiades, Evelina; Klissouras, Vassilis; Baulch, Jamie; Wang, Guan; Pitsiladis, Yannis

2017-11-14

While the influence of nature (genes) and nurture (environment) on elite sporting performance remains difficult to precisely determine, the dismissal of either as a contributing factor to performance is unwarranted. It is accepted that a complex interaction of a combination of innumerable factors may mold a talented athlete into a champion. The prevailing view today is that understanding elite human performance will require the deciphering of two major sources of individual differences, genes and the environment. It is widely accepted that superior performers are endowed with a high genetic potential actualised through hard and prodigious effort. Heritability studies using the twin model have provided the basis to disentangle genetic and environmental factors that contribute to complex human traits and have paved the way to the detection of specific genes for elite sport performance. Yet, the heritability for most phenotypes essential to elite human performance is above 50% but below 100%, meaning that the environment is also important. Furthermore, individual differences can potentially also be explained not only by the impact of DNA sequence variation on biology and behaviour, but also by the effects of epigenetic changes which affect phenotype by modifying gene expression. Despite this complexity, the overwhelming and accumulating evidence, amounted through experimental research spanning almost two centuries, tips the balance in favour of nature in the "nature" and "nurture" debate. In other words, truly elite-level athletes are built - but only from those born with innate ability.

Interactive Effects of in Utero Nutrition and Genetic Inheritance on Cognition: New Evidence Using Sibling Comparisons1

PubMed Central

Cook, C. Justin; Fletcher, Jason M.

2013-01-01

A large literature links early environments and later outcomes, such as cognition; however, little is known about the mechanisms. One potential mechanism is sensitivity to early environments that is moderated or amplified by the genotype. With this mechanism in mind, a complementary literature outside economics examines the interaction between genes and environments, but often problems of endogeneity and bias in estimation are uncorrected. A key issue in the literature is exploring environmental variation that is not exogenous, which is potentially problematic if there are gene-environment correlation or gene-gene interactions. Using sibling pairs with genetic data in the Wisconsin Longitudinal Study we extend a previous, and widely cited, gene-environment study that explores an interaction between the FADS2 gene, which is associated with the processing of essential fatty acids related to cognitive development, and early life nutrition in explaining later-life IQ. Our base OLS findings suggest that individuals with specific FADS2 variants gain roughly 0.15 standard deviations in IQ for each standard deviation increase in birth weight, our measure of the early nutrition environment; while, individuals with other variants of FADS2 do not have a statistically significant association with early nutrition, implying the genotype is influencing the effects of environmental exposure. When including family-level fixed effects, however, the magnitude of the gene-environment interaction is reduced by half and statistical significance dissipates, implying the interaction between FADS2 and early nutrition in explaining later life IQ may in part be due to unobserved, family-level factors. The example has wider implications for the practice of investigating gene-environment interactions when the environmental exposure is not exogenous and robustness to unobserved variation in the genome is not controlled for in the analysis. PMID:24172871

Gene-Environment Interactions in Schizophrenia: Review of Epidemiological Findings and Future Directions

PubMed Central

van Os, Jim; Rutten, Bart PF; Poulton, Richie

2008-01-01

Concern is building about high rates of schizophrenia in large cities, and among immigrants, cannabis users, and traumatized individuals, some of which likely reflects the causal influence of environmental exposures. This, in combination with very slow progress in the area of molecular genetics, has generated interest in more complicated models of schizophrenia etiology that explicitly posit gene-environment interactions (EU-GEI. European Network of Schizophrenia Networks for the Study of Gene Environment Interactions. Schizophrenia aetiology: do gene-environment interactions hold the key? [published online ahead of print April 25, 2008] Schizophr Res; S0920-9964(08) 00170–9). Although findings of epidemiological gene-environment interaction (G × E) studies are suggestive of widespread gene-environment interactions in the etiology of schizophrenia, numerous challenges remain. For example, attempts to identify gene-environment interactions cannot be equated with molecular genetic studies with a few putative environmental variables “thrown in”: G × E is a multidisciplinary exercise involving epidemiology, psychology, psychiatry, neuroscience, neuroimaging, pharmacology, biostatistics, and genetics. Epidemiological G × E studies using indirect measures of genetic risk in genetically sensitive designs have the advantage that they are able to model the net, albeit nonspecific, genetic load. In studies using direct molecular measures of genetic variation, a hypothesis-driven approach postulating synergistic effects between genes and environment impacting on a final common pathway, such as “sensitization” of mesolimbic dopamine neurotransmission, while simplistic, may provide initial focus and protection against the numerous false-positive and false-negative results that these investigations engender. Experimental ecogenetic approaches with randomized assignment may help to overcome some of the limitations of observational studies and allow for the additional elucidation of underlying mechanisms using a combination of functional enviromics and functional genomics. PMID:18791076

Genetic Dissection of Learning and Memory in Mice

PubMed Central

Mineur, Yann S.; Crusio, Wim E.; Sluyter, Frans

2004-01-01

In this minireview, we discuss different strategies to dissect genetically the keystones of learning and memory. First, we broadly sketch the neurogenetic analysis of complex traits in mice. We then discuss two general strategies to find genes affecting learning and memory: candidate gene studies and whole genome searches. Next, we briefly review more recently developed techniques, such as microarrays and RNA interference. In addition, we focus on gene-environment interactions and endophenotypes. All sections are illustrated with examples from the learning and memory field, including a table summarizing the latest information about genes that have been shown to have effects on learning and memory. PMID:15656270

Meta-analysis of gene-environment-wide association scans accounting for education level identifies additional loci for refractive error.

PubMed

Fan, Qiao; Verhoeven, Virginie J M; Wojciechowski, Robert; Barathi, Veluchamy A; Hysi, Pirro G; Guggenheim, Jeremy A; Höhn, René; Vitart, Veronique; Khawaja, Anthony P; Yamashiro, Kenji; Hosseini, S Mohsen; Lehtimäki, Terho; Lu, Yi; Haller, Toomas; Xie, Jing; Delcourt, Cécile; Pirastu, Mario; Wedenoja, Juho; Gharahkhani, Puya; Venturini, Cristina; Miyake, Masahiro; Hewitt, Alex W; Guo, Xiaobo; Mazur, Johanna; Huffman, Jenifer E; Williams, Katie M; Polasek, Ozren; Campbell, Harry; Rudan, Igor; Vatavuk, Zoran; Wilson, James F; Joshi, Peter K; McMahon, George; St Pourcain, Beate; Evans, David M; Simpson, Claire L; Schwantes-An, Tae-Hwi; Igo, Robert P; Mirshahi, Alireza; Cougnard-Gregoire, Audrey; Bellenguez, Céline; Blettner, Maria; Raitakari, Olli; Kähönen, Mika; Seppala, Ilkka; Zeller, Tanja; Meitinger, Thomas; Ried, Janina S; Gieger, Christian; Portas, Laura; van Leeuwen, Elisabeth M; Amin, Najaf; Uitterlinden, André G; Rivadeneira, Fernando; Hofman, Albert; Vingerling, Johannes R; Wang, Ya Xing; Wang, Xu; Tai-Hui Boh, Eileen; Ikram, M Kamran; Sabanayagam, Charumathi; Gupta, Preeti; Tan, Vincent; Zhou, Lei; Ho, Candice E H; Lim, Wan'e; Beuerman, Roger W; Siantar, Rosalynn; Tai, E-Shyong; Vithana, Eranga; Mihailov, Evelin; Khor, Chiea-Chuen; Hayward, Caroline; Luben, Robert N; Foster, Paul J; Klein, Barbara E K; Klein, Ronald; Wong, Hoi-Suen; Mitchell, Paul; Metspalu, Andres; Aung, Tin; Young, Terri L; He, Mingguang; Pärssinen, Olavi; van Duijn, Cornelia M; Jin Wang, Jie; Williams, Cathy; Jonas, Jost B; Teo, Yik-Ying; Mackey, David A; Oexle, Konrad; Yoshimura, Nagahisa; Paterson, Andrew D; Pfeiffer, Norbert; Wong, Tien-Yin; Baird, Paul N; Stambolian, Dwight; Wilson, Joan E Bailey; Cheng, Ching-Yu; Hammond, Christopher J; Klaver, Caroline C W; Saw, Seang-Mei; Rahi, Jugnoo S; Korobelnik, Jean-François; Kemp, John P; Timpson, Nicholas J; Smith, George Davey; Craig, Jamie E; Burdon, Kathryn P; Fogarty, Rhys D; Iyengar, Sudha K; Chew, Emily; Janmahasatian, Sarayut; Martin, Nicholas G; MacGregor, Stuart; Xu, Liang; Schache, Maria; Nangia, Vinay; Panda-Jonas, Songhomitra; Wright, Alan F; Fondran, Jeremy R; Lass, Jonathan H; Feng, Sheng; Zhao, Jing Hua; Khaw, Kay-Tee; Wareham, Nick J; Rantanen, Taina; Kaprio, Jaakko; Pang, Chi Pui; Chen, Li Jia; Tam, Pancy O; Jhanji, Vishal; Young, Alvin L; Döring, Angela; Raffel, Leslie J; Cotch, Mary-Frances; Li, Xiaohui; Yip, Shea Ping; Yap, Maurice K H; Biino, Ginevra; Vaccargiu, Simona; Fossarello, Maurizio; Fleck, Brian; Yazar, Seyhan; Tideman, Jan Willem L; Tedja, Milly; Deangelis, Margaret M; Morrison, Margaux; Farrer, Lindsay; Zhou, Xiangtian; Chen, Wei; Mizuki, Nobuhisa; Meguro, Akira; Mäkelä, Kari Matti

2016-03-29

Myopia is the most common human eye disorder and it results from complex genetic and environmental causes. The rapidly increasing prevalence of myopia poses a major public health challenge. Here, the CREAM consortium performs a joint meta-analysis to test single-nucleotide polymorphism (SNP) main effects and SNP × education interaction effects on refractive error in 40,036 adults from 25 studies of European ancestry and 10,315 adults from 9 studies of Asian ancestry. In European ancestry individuals, we identify six novel loci (FAM150B-ACP1, LINC00340, FBN1, DIS3L-MAP2K1, ARID2-SNAT1 and SLC14A2) associated with refractive error. In Asian populations, three genome-wide significant loci AREG, GABRR1 and PDE10A also exhibit strong interactions with education (P<8.5 × 10(-5)), whereas the interactions are less evident in Europeans. The discovery of these loci represents an important advance in understanding how gene and environment interactions contribute to the heterogeneity of myopia.

Identifying candidate genes affecting developmental time in Drosophila melanogaster: pervasive pleiotropy and gene-by-environment interaction

PubMed Central

Mensch, Julián; Lavagnino, Nicolás; Carreira, Valeria Paula; Massaldi, Ana; Hasson, Esteban; Fanara, Juan José

2008-01-01

Background Understanding the genetic architecture of ecologically relevant adaptive traits requires the contribution of developmental and evolutionary biology. The time to reach the age of reproduction is a complex life history trait commonly known as developmental time. In particular, in holometabolous insects that occupy ephemeral habitats, like fruit flies, the impact of developmental time on fitness is further exaggerated. The present work is one of the first systematic studies of the genetic basis of developmental time, in which we also evaluate the impact of environmental variation on the expression of the trait. Results We analyzed 179 co-isogenic single P[GT1]-element insertion lines of Drosophila melanogaster to identify novel genes affecting developmental time in flies reared at 25°C. Sixty percent of the lines showed a heterochronic phenotype, suggesting that a large number of genes affect this trait. Mutant lines for the genes Merlin and Karl showed the most extreme phenotypes exhibiting a developmental time reduction and increase, respectively, of over 2 days and 4 days relative to the control (a co-isogenic P-element insertion free line). In addition, a subset of 42 lines selected at random from the initial set of 179 lines was screened at 17°C. Interestingly, the gene-by-environment interaction accounted for 52% of total phenotypic variance. Plastic reaction norms were found for a large number of developmental time candidate genes. Conclusion We identified components of several integrated time-dependent pathways affecting egg-to-adult developmental time in Drosophila. At the same time, we also show that many heterochronic phenotypes may arise from changes in genes involved in several developmental mechanisms that do not explicitly control the timing of specific events. We also demonstrate that many developmental time genes have pleiotropic effects on several adult traits and that the action of most of them is sensitive to temperature during development. Taken together, our results stress the need to take into account the effect of environmental variation and the dynamics of gene interactions on the genetic architecture of this complex life-history trait. PMID:18687152

Gene-environment interaction between the oxytocin receptor (OXTR) gene and parenting behaviour on children's theory of mind.

PubMed

Wade, Mark; Hoffmann, Thomas J; Jenkins, Jennifer M

2015-12-01

Theory of mind (ToM) is the ability to interpret and understand human behaviour by representing the mental states of others. Like many human capacities, ToM is thought to develop through both complex biological and socialization mechanisms. However, no study has examined the joint effect of genetic and environmental influences on ToM. This study examined how variability in the oxytocin receptor gene (OXTR) and parenting behavior--two widely studied factors in ToM development-interacted to predict ToM in pre-school-aged children. Participants were 301 children who were part of an ongoing longitudinal birth cohort study. ToM was assessed at age 4.5 using a previously validated scale. Parenting was assessed through observations of mothers' cognitively sensitive behaviours. Using a family-based association design, it was suggestive that a particular variant (rs11131149) interacted with maternal cognitive sensitivity on children's ToM (P = 0.019). More copies of the major allele were associated with higher ToM as a function of increasing cognitive sensitivity. A sizeable 26% of the variability in ToM was accounted for by this interaction. This study provides the first empirical evidence of gene-environment interactions on ToM, supporting the notion that genetic factors may be modulated by potent environmental influences early in development. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Chapter 20: geographic variability in growth of forest trees

Treesearch

Robert Z. Callaham

1962-01-01

Tree growth, like all plant characters, is a product of the interaction of genes and environment; however, the genes, environment, and interaction are not the same for every individual of a species. Genes exert master control over the plant's growth mechanisms. They control mechanisms for responding to environment and for utilizing environment in growth. Usually...

Adaptation of the Mitochondrial Genome in Cephalopods: Enhancing Proton Translocation Channels and the Subunit Interactions

PubMed Central

Almeida, Daniela; Maldonado, Emanuel; Vasconcelos, Vitor; Antunes, Agostinho

2015-01-01

Mitochondrial protein-coding genes (mt genes) encode subunits forming complexes of crucial cellular pathways, including those involved in the vital process of oxidative phosphorylation (OXPHOS). Despite the vital role of the mitochondrial genome (mt genome) in the survival of organisms, little is known with respect to its adaptive implications within marine invertebrates. The molluscan Class Cephalopoda is represented by a marine group of species known to occupy contrasting environments ranging from the intertidal to the deep sea, having distinct metabolic requirements, varied body shapes and highly advanced visual and nervous systems that make them highly competitive and successful worldwide predators. Thus, cephalopods are valuable models for testing natural selection acting on their mitochondrial subunits (mt subunits). Here, we used concatenated mt genes from 17 fully sequenced mt genomes of diverse cephalopod species to generate a robust mitochondrial phylogeny for the Class Cephalopoda. We followed an integrative approach considering several branches of interest–covering cephalopods with distinct morphologies, metabolic rates and habitats–to identify sites under positive selection and localize them in the respective protein alignment and/or tridimensional structure of the mt subunits. Our results revealed significant adaptive variation in several mt subunits involved in the energy production pathway of cephalopods: ND5 and ND6 from Complex I, CYTB from Complex III, COX2 and COX3 from Complex IV, and in ATP8 from Complex V. Furthermore, we identified relevant sites involved in protein-interactions, lining proton translocation channels, as well as disease/deficiencies related sites in the aforementioned complexes. A particular case, revealed by this study, is the involvement of some positively selected sites, found in Octopoda lineage in lining proton translocation channels (site 74 from ND5) and in interactions between subunits (site 507 from ND5) of Complex I. PMID:26285039

Developmental programming: Interaction between prenatal BPA and postnatal overfeeding on cardiac tissue gene expression in female sheep.

PubMed

Koneva, L A; Vyas, A K; McEachin, R C; Puttabyatappa, M; Wang, H-S; Sartor, M A; Padmanabhan, V

2017-01-01

Epidemiologic studies and studies in rodents point to potential risks from developmental exposure to BPA on cardiometabolic diseases. Furthermore, it is becoming increasingly evident that the manifestation and severity of adverse outcomes is the result of interaction between developmental insults and the prevailing environment. Consistent with this premise, recent studies in sheep found prenatal BPA treatment prevented the adverse effects of postnatal obesity in inducing hypertension. The gene networks underlying these complex interactions are not known. mRNA-seq of myocardium was performed on four groups of four female sheep to assess the effects of prenatal BPA exposure, postnatal overfeeding and their interaction on gene transcription, pathway perturbations and functional effects. The effects of prenatal exposure to BPA, postnatal overfeeding, and prenatal BPA with postnatal overfeeding all resulted in transcriptional changes (85-141 significant differentially expressed genes). Although the effects of prenatal BPA and postnatal overfeeding did not involve dysregulation of many of the same genes, they affected a remarkably similar set of biological pathways. Furthermore, an additive or synergistic effect was not found in the combined treatment group, but rather prenatal BPA treatment led to a partial reversal of the effects of overfeeding alone. Many genes previously known to be affected by BPA and involved in obesity, hypertension, or heart disease were altered following these treatments, and AP-1, EGR1, and EGFR were key hubs affected by BPA and/or overfeeding. Environ. Mol. Mutagen. 58:4-18, 2017. © 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

The Genetic Architecture of Noise-Induced Hearing Loss: Evidence for a Gene-by-Environment Interaction.

PubMed

Lavinsky, Joel; Ge, Marshall; Crow, Amanda L; Pan, Calvin; Wang, Juemei; Salehi, Pezhman; Myint, Anthony; Eskin, Eleazar; Allayee, Hooman; Lusis, Aldons J; Friedman, Rick A

2016-10-13

The discovery of environmentally specific genetic effects is crucial to the understanding of complex traits, such as susceptibility to noise-induced hearing loss (NIHL). We describe the first genome-wide association study (GWAS) for NIHL in a large and well-characterized population of inbred mouse strains, known as the Hybrid Mouse Diversity Panel (HMDP). We recorded auditory brainstem response (ABR) thresholds both pre and post 2-hr exposure to 10-kHz octave band noise at 108 dB sound pressure level in 5-6-wk-old female mice from the HMDP (4-5 mice/strain). From the observation that NIHL susceptibility varied among the strains, we performed a GWAS with correction for population structure and mapped a locus on chromosome 6 that was statistically significantly associated with two adjacent frequencies. We then used a "genetical genomics" approach that included the analysis of cochlear eQTLs to identify candidate genes within the GWAS QTL. In order to validate the gene-by-environment interaction, we compared the effects of the postnoise exposure locus with that from the same unexposed strains. The most significant SNP at chromosome 6 (rs37517079) was associated with noise susceptibility, but was not significant at the same frequencies in our unexposed study. These findings demonstrate that the genetic architecture of NIHL is distinct from that of unexposed hearing levels and provide strong evidence for gene-by-environment interactions in NIHL. Copyright © 2016 Lavinsky et al.

Enacting the molecular imperative: How gene-environment interaction research links bodies and environments in the post-genomic age.

PubMed

Darling, Katherine Weatherford; Ackerman, Sara L; Hiatt, Robert H; Lee, Sandra Soo-Jin; Shim, Janet K

2016-04-01

Despite a proclaimed shift from 'nature versus nurture' to 'genes and environment' paradigms within biomedical and genomic science, capturing the environment and identifying gene-environment interactions (GEIs) has remained a challenge. What does 'the environment' mean in the post-genomic age? In this paper, we present qualitative data from a study of 33 principal investigators funded by the U.S. National Institutes of Health to conduct etiological research on three complex diseases (cancer, cardiovascular disease and diabetes). We examine their research practices and perspectives on the environment through the concept of molecularization: the social processes and transformations through which phenomena (diseases, identities, pollution, food, racial/ethnic classifications) are re-defined in terms of their molecular components and described in the language of molecular biology. We show how GEI researchers' expansive conceptualizations of the environment ultimately yield to the imperative to molecularize and personalize the environment. They seek to 'go into the body' and re-work the boundaries between bodies and environments. In the process, they create epistemic hinges to facilitate a turn from efforts to understand social and environmental exposures outside the body, to quantifying their effects inside the body. GEI researchers respond to these emergent imperatives with a mixture of excitement, ambivalence and frustration. We reflect on how GEI researchers struggle to make meaning of molecules in their work, and how they grapple with molecularization as a methodological and rhetorical imperative as well as a process transforming biomedical research practices. Copyright © 2016 Elsevier Ltd. All rights reserved.

Animal models of gene-environment interaction in schizophrenia: a dimensional perspective

PubMed Central

Ayhan, Yavuz; McFarland, Ross; Pletnikov, Mikhail V.

2015-01-01

Schizophrenia has long been considered as a disorder with multifactorial origins. Recent discoveries have advanced our understanding of the genetic architecture of the disease. However, even with the increase of identified risk variants, heritability estimates suggest an important contribution of non-genetic factors. Various environmental risk factors have been proposed to play a role in the etiopathogenesis of schizophrenia. These include season of birth, maternal infections, obstetric complications, adverse events at early childhood, and drug abuse. Despite the progress in identification of genetic and environmental risk factors, we still have a limited understanding of the mechanisms whereby gene-environment interactions (GxE) operate in schizophrenia and psychoses at large. In this review we provide a critical analysis of current animal models of GxE relevant to psychotic disorders and propose that dimensional perspective will advance our understanding of the complex mechanisms of these disorders. PMID:26510407

Studying Gene and Gene-Environment Effects of Uncommon and Common Variants on Continuous Traits: A Marker-Set Approach Using Gene-Trait Similarity Regression

PubMed Central

Tzeng, Jung-Ying; Zhang, Daowen; Pongpanich, Monnat; Smith, Chris; McCarthy, Mark I.; Sale, Michèle M.; Worrall, Bradford B.; Hsu, Fang-Chi; Thomas, Duncan C.; Sullivan, Patrick F.

2011-01-01

Genomic association analyses of complex traits demand statistical tools that are capable of detecting small effects of common and rare variants and modeling complex interaction effects and yet are computationally feasible. In this work, we introduce a similarity-based regression method for assessing the main genetic and interaction effects of a group of markers on quantitative traits. The method uses genetic similarity to aggregate information from multiple polymorphic sites and integrates adaptive weights that depend on allele frequencies to accomodate common and uncommon variants. Collapsing information at the similarity level instead of the genotype level avoids canceling signals that have the opposite etiological effects and is applicable to any class of genetic variants without the need for dichotomizing the allele types. To assess gene-trait associations, we regress trait similarities for pairs of unrelated individuals on their genetic similarities and assess association by using a score test whose limiting distribution is derived in this work. The proposed regression framework allows for covariates, has the capacity to model both main and interaction effects, can be applied to a mixture of different polymorphism types, and is computationally efficient. These features make it an ideal tool for evaluating associations between phenotype and marker sets defined by linkage disequilibrium (LD) blocks, genes, or pathways in whole-genome analysis. PMID:21835306

Disentangling Gene-Environment Correlations and Interactions on Adolescent Depressive Symptoms

ERIC Educational Resources Information Center

Lau, Jennifer Y. F.; Eley, Thalia C.

2008-01-01

Background: Genetic risks for depression may be expressed through greater exposure towards environmental stressors (gene-environment correlation, rGE) and increased susceptibility to these stressors (gene-environment interaction, G x E). While these effects are often studied independently, evidence supports their co-occurrence on depression.…

Modification of the association between early adversity and obsessive-compulsive disorder by polymorphisms in the MAOA, MAOB and COMT genes.

PubMed

McGregor, N W; Hemmings, S M J; Erdman, L; Calmarza-Font, I; Stein, D J; Lochner, C

2016-12-30

The monoamine oxidases (MAOA/B) and catechol-O-methyltransferase (COMT) enzymes break down regulatory components within serotonin and dopamine pathways, and polymorphisms within these genes are candidates for OCD susceptibility. Childhood trauma has been linked OCD psychopathology, but little attention has been paid to the interactions between genes and environment in OCD aetiology. This pilot study investigated gene-by-environment interactions between childhood trauma and polymorphisms in the MAOA, MAOB and COMT genes in OCD. Ten polymorphisms (MAOA: 3 variants, MAOB: 4 variants, COMT: 3 variants) were genotyped in a cohort of OCD patients and controls. Early-life trauma was assessed using the Childhood Trauma Questionnaire (CTQ). Gene-by-gene (GxG) and gene-by-environment interactions (GxE) of the variants and childhood trauma were assessed using logistic regression models. Significant GxG interactions were found between rs362204 (COMT) and two independent polymorphisms in the MAOB gene (rs1799836 and rs6651806). Haplotype associations for OCD susceptibility were found for MAOB. Investigation of GxE interactions indicated that the sexual abuse sub-category was significantly associated with all three genes in haplotype x environment interaction analyses. Preliminary findings indicate that polymorphisms within the MAOB and COMT genes interact resulting in risk for OCD. Childhood trauma interacts with haplotypes in COMT, MAOA and MAOB, increasing risk for OCD. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

NATURE VERSUS NURTURE: DEATH OF A DOGMA, AND THE ROAD AHEAD

PubMed Central

Traynor, Bryan J.; Singleton, Andrew B.

2010-01-01

Interaction between the genome and the environment has been widely discussed in the literature, but has the importance ascribed to understanding these interactions been overstated? In this opinion piece, we critically discuss gene-environment interactions and attempt to answer three key questions: First, is it likely that gene-environment interactions actually exist? Second, what is the realistic value of trying to unravel these interactions, both in terms of understanding disease pathogenesis and as a means of ameliorating disease? Finally, and most importantly, do the technologies and methodologies exist to facilitate an unbiased search for gene-environment interactions? Addressing these questions highlights key areas of feasibility that must be considered in this area of research. PMID:20955927

Antisocial Peer Affiliation and Externalizing Disorders: Evidence for Gene × Environment × Development Interaction

PubMed Central

Samek, Diana R.; Hicks, Brian M.; Keyes, Margaret A.; Iacono, William G.; McGue, Matt

2016-01-01

Gene × environment interaction contributes to externalizing disorders in adolescence, but little is known about whether such effects are long-lasting or present in adulthood. We examined gene-environment interplay in the concurrent and prospective associations between antisocial peer affiliation and externalizing disorders (antisocial behavior and substance use disorders) at ages 17, 20, 24, and 29. The sample included 1,382 same-sex twin pairs participating in the Minnesota Twin Family Study. We detected a gene × environment interaction at age 17, such that additive genetic influences on antisocial behavior and substance use disorders were greater in the context of greater antisocial peer affiliation. This gene × environment interaction was not present for antisocial behavior symptoms after age 17, but was for substance use disorder symptoms through age 29 (though effect sizes were largest at age 17). Results suggest adolescence is a critical period for the development of externalizing disorders wherein exposure to greater environmental adversity is associated with a greater expression of genetic risk. This form of gene × environment interaction may persist through young adulthood for substance use disorders, but is limited to adolescence for antisocial behavior. PMID:27580681

Antisocial peer affiliation and externalizing disorders: Evidence for Gene × Environment × Development interaction.

PubMed

Samek, Diana R; Hicks, Brian M; Keyes, Margaret A; Iacono, William G; McGue, Matt

2017-02-01

Gene × Environment interaction contributes to externalizing disorders in childhood and adolescence, but little is known about whether such effects are long lasting or present in adulthood. We examined gene-environment interplay in the concurrent and prospective associations between antisocial peer affiliation and externalizing disorders (antisocial behavior and substance use disorders) at ages 17, 20, 24, and 29. The sample included 1,382 same-sex twin pairs participating in the Minnesota Twin Family Study. We detected a Gene × Environment interaction at age 17, such that additive genetic influences on antisocial behavior and substance use disorders were greater in the context of greater antisocial peer affiliation. This Gene × Environment interaction was not present for antisocial behavior symptoms after age 17, but it was for substance use disorder symptoms through age 29 (though effect sizes were largest at age 17). The results suggest adolescence is a critical period for the development of externalizing disorders wherein exposure to greater environmental adversity is associated with a greater expression of genetic risk. This form of Gene × Environment interaction may persist through young adulthood for substance use disorders, but it appears to be limited to adolescence for antisocial behavior.

Construction of ontology augmented networks for protein complex prediction.

PubMed

Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian

2013-01-01

Protein complexes are of great importance in understanding the principles of cellular organization and function. The increase in available protein-protein interaction data, gene ontology and other resources make it possible to develop computational methods for protein complex prediction. Most existing methods focus mainly on the topological structure of protein-protein interaction networks, and largely ignore the gene ontology annotation information. In this article, we constructed ontology augmented networks with protein-protein interaction data and gene ontology, which effectively unified the topological structure of protein-protein interaction networks and the similarity of gene ontology annotations into unified distance measures. After constructing ontology augmented networks, a novel method (clustering based on ontology augmented networks) was proposed to predict protein complexes, which was capable of taking into account the topological structure of the protein-protein interaction network, as well as the similarity of gene ontology annotations. Our method was applied to two different yeast protein-protein interaction datasets and predicted many well-known complexes. The experimental results showed that (i) ontology augmented networks and the unified distance measure can effectively combine the structure closeness and gene ontology annotation similarity; (ii) our method is valuable in predicting protein complexes and has higher F1 and accuracy compared to other competing methods.

Tissue Architecture and Microenvironment Sustain Hormone Signaling | Center for Cancer Research

Cancer.gov

Cells interact with their environments in part through protein receptors embedded in the cell membrane. Activation of a receptor by external signaling molecules sets off a complex chain of events within the cell that can result in alterations in protein structure and function and/or changes in gene expression. Proper integration of these signals is crucial for normal cell

Effects of circadian clock genes and environmental factors on cognitive aging in old adults in a Taiwanese population.

PubMed

Lin, Eugene; Kuo, Po-Hsiu; Liu, Yu-Li; Yang, Albert C; Kao, Chung-Feng; Tsai, Shih-Jen

2017-04-11

Previous animal studies have indicated associations between circadian clock genes and cognitive impairment . In this study, we assessed whether 11 circadian clockgenes are associated with cognitive aging independently and/or through complex interactions in an old Taiwanese population. We also analyzed the interactions between environmental factors and these genes in influencing cognitive aging. A total of 634 Taiwanese subjects aged over 60 years from the Taiwan Biobank were analyzed. Mini-Mental State Examinations (MMSE) were administered to all subjects, and MMSE scores were used to evaluate cognitive function. Our data showed associations between cognitive aging and single nucleotide polymorphisms (SNPs) in 4 key circadian clock genes, CLOCK rs3749473 (p = 0.0017), NPAS2 rs17655330 (p = 0.0013), RORA rs13329238 (p = 0.0009), and RORB rs10781247 (p = 7.9 x 10-5). We also found that interactions between CLOCK rs3749473, NPAS2 rs17655330, RORA rs13329238, and RORB rs10781247 affected cognitive aging (p = 0.007). Finally, we investigated the influence of interactions between CLOCK rs3749473, RORA rs13329238, and RORB rs10781247 with environmental factors such as alcohol consumption, smoking status, physical activity, and social support on cognitive aging (p = 0.002 ~ 0.01). Our study indicates that circadian clock genes such as the CLOCK, NPAS2, RORA, and RORB genes may contribute to the risk of cognitive aging independently as well as through gene-gene and gene-environment interactions.

The Interacting Effect of the BDNF Val66Met Polymorphism and Stressful Life Events on Adolescent Depression Is Not an Artifact of Gene-Environment Correlation: Evidence from a Longitudinal Twin Study

ERIC Educational Resources Information Center

Chen, Jie; Li, Xinying; McGue, Matt

2013-01-01

Background: Confounding introduced by gene-environment correlation (rGE) may prevent one from observing a true gene-environment interaction (G × E) effect on psychopathology. The present study investigated the interacting effect of the BDNF Val66Met polymorphism and stressful life events (SLEs) on adolescent depression while controlling for the…

Bayesian Variable Selection for Hierarchical Gene-Environment and Gene-Gene Interactions

PubMed Central

Liu, Changlu; Ma, Jianzhong; Amos, Christopher I.

2014-01-01

We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions and gene by environment interactions in the same model. Our approach incorporates the natural hierarchical structure between the main effects and interaction effects into a mixture model, such that our methods tend to remove the irrelevant interaction effects more effectively, resulting in more robust and parsimonious models. We consider both strong and weak hierarchical models. For a strong hierarchical model, both of the main effects between interacting factors must be present for the interactions to be considered in the model development, while for a weak hierarchical model, only one of the two main effects is required to be present for the interaction to be evaluated. Our simulation results show that the proposed strong and weak hierarchical mixture models work well in controlling false positive rates and provide a powerful approach for identifying the predisposing effects and interactions in gene-environment interaction studies, in comparison with the naive model that does not impose this hierarchical constraint in most of the scenarios simulated. We illustrated our approach using data for lung cancer and cutaneous melanoma. PMID:25154630

Design of a Family Study Among High-Risk Caribbean Hispanics: The Northern Manhattan Family Study

PubMed Central

Sacco, Ralph L.; Sabala, Edison A.; Rundek, Tanja; Juo, Suh-Hang Hank; Huang, Jinaping Sam; DiTullio, Marco; Homma, Shunichi; Almonte, Katihurka; Lithgow, Carlos García; Boden-Albala, Bernadette

2008-01-01

Stroke continues to kill disproportionately more Blacks and Hispanics than Whites in the United States. Racial/ethnic variations in the incidence of stroke and prevalence of stroke risk factors are probably explained by both genetic and environmental influences. Family studies can help identify genetic predisposition to stroke and potential stroke precursors. Few studies have evaluated the heritability of these stroke risk factors among non-White populations, and none have focused on Caribbean Hispanic populations. The aim of the Northern Manhattan Family Study (NOMAFS) is to investigate the gene-environment interaction of stroke risk factors among Caribbean Hispanics. The unique recruitment and methodologic approaches used in this study are relevant to the design and conduct of genetic aggregation studies to investigate complex genetic disorders in non-White populations. The aim of this paper is to describe the NOMAFS and report enrollment and characteristics of the participants. The NO-MAFS will provide a data resource for the exploration of the genetic determinants of highly heritable stroke precursor phenotypes that are less complex than the stroke phenotype. Understanding the gene environment interaction is the critical next step toward the development of new and unique approaches to disease prevention and interventions. PMID:17682370

Nature versus nurture: death of a dogma, and the road ahead.

PubMed

Traynor, Bryan J; Singleton, Andrew B

2010-10-21

Interaction between the genome and the environment has been widely discussed in the literature, but has the importance ascribed to understanding these interactions been overstated? In this opinion piece, we critically discuss gene-environment interactions and attempt to answer three key questions. First, is it likely that gene-environment interactions actually exist? Second, what is the realistic value of trying to unravel these interactions, both in terms of understanding disease pathogenesis and as a means of ameliorating disease? Finally, and most importantly, do the technologies and methodologies exist to facilitate an unbiased search for gene-environment interactions? Addressing these questions highlights key areas of feasibility that must be considered in this area of research. Copyright © 2010 Elsevier Inc. All rights reserved.

The association of interacting neighborhood gene-environment risk with cortisol and blood pressure in African-American adults

PubMed Central

Coulon, Sandra M.; Wilson, Dawn K.; Van Horn, M. L.; Hand, Gregory A.; Kresovich, Stephen

2016-01-01

Background African-American adults are disproportionately affected by stress-related chronic conditions like high blood pressure (BP), and both environmental stress and genetic risk may play a role in its development. Purpose This study tested whether the dual risk of low neighborhood socioeconomic status (SES) and glucocorticoid genetic sensitivity interacted to predict waking cortisol and BP. Methods Cross-sectional waking cortisol and BP were collected from 208 African-American adults who were participating in a follow-up visit as part of the Positive Action for Today’s Health trial. Three single nucleotide polymorphisms were genotyped, salivary cortisol samples were collected, and neighborhood SES was calculated using 2010 Census data. Results The sample was mostly female (65%), with weight classified as overweight or obese (MBMI=32.74, SD=8.88), and a mean age of 55.64 (SD=15.21). The gene-by-neighborhood SES interaction predicted cortisol (B=0.235, p=.001, r2=.036), but not BP. For adults with high genetic risk, waking cortisol was lower with lower SES but higher with higher SES (B=0.87). Lower neighborhood SES was also related to higher systolic BP (B=−0.794, p=.028). Conclusions Findings demonstrated an interaction whereby African-American adults with high genetic sensitivity had high levels of waking cortisol with higher neighborhood SES, and low levels with lower neighborhood SES. This moderation effect is consistent with a differential susceptibility gene-environment pattern, rather than a dual-risk pattern. These findings contribute to a growing body of evidence that demonstrates the importance of investigating complex gene-environment relations in order to better understand stress-related health disparities. PMID:26685668

Enacting the molecular imperative: How gene-environment interaction research links bodies and environments in the Post-Genomic Age

PubMed Central

Darling, Katherine Weatherford; Ackerman, Sara L.; Hiatt, Robert H.; Lee, Sandra Soo-Jin; Shim, Janet K.

2016-01-01

Despite a proclaimed shift from ‘nature versus nurture’ to ‘genes and environment’ paradigms within biomedical and genomic science, capturing the environment and identifying gene-environment interactions (GEIs) has remained a challenge. What does ‘the environment’ mean in the post-genomic age? In this paper, we present qualitative data from a study of 33 principal investigators funded by the U.S. National Institutes of Health to conduct etiological research on three complex diseases (cancer, cardiovascular disease and diabetes). We examine their research practices and perspectives on the environment through the concept of molecularization: the social processes and transformations through which phenomena (diseases, identities, pollution, food, racial/ethnic classifications) are re-defined in terms of their molecular components and described in the language of molecular biology. We show how GEI researchers’ expansive conceptualizations of the environment ultimately yield to the imperative to molecularize and personalize the environment. They seek to ‘go into the body’ and re-work the boundaries between bodies and environments. In the process, they create epistemic hinges to facilitate a turn from efforts to understand social and environmental exposures outside the body, to quantifying their effects inside the body. GEI researchers respond to these emergent imperatives with a mixture of excitement, ambivalence and frustration. We reflect on how GEI researchers struggle to make meaning of molecules in their work, and how they grapple with molecularization as a methodological and rhetorical imperative as well as a process transforming biomedical research practices. PMID:26994357

Meta-analysis of Polyploid Cotton QTL Shows Unequal Contributions of Subgenomes to a Complex Network of Genes and Gene Clusters Implicated in Lint Fiber Development

PubMed Central

Rong, Junkang; Feltus, F. Alex; Waghmare, Vijay N.; Pierce, Gary J.; Chee, Peng W.; Draye, Xavier; Saranga, Yehoshua; Wright, Robert J.; Wilkins, Thea A.; May, O. Lloyd; Smith, C. Wayne; Gannaway, John R.; Wendel, Jonathan F.; Paterson, Andrew H.

2007-01-01

QTL mapping experiments yield heterogeneous results due to the use of different genotypes, environments, and sampling variation. Compilation of QTL mapping results yields a more complete picture of the genetic control of a trait and reveals patterns in organization of trait variation. A total of 432 QTL mapped in one diploid and 10 tetraploid interspecific cotton populations were aligned using a reference map and depicted in a CMap resource. Early demonstrations that genes from the non-fiber-producing diploid ancestor contribute to tetraploid lint fiber genetics gain further support from multiple populations and environments and advanced-generation studies detecting QTL of small phenotypic effect. Both tetraploid subgenomes contribute QTL at largely non-homeologous locations, suggesting divergent selection acting on many corresponding genes before and/or after polyploid formation. QTL correspondence across studies was only modest, suggesting that additional QTL for the target traits remain to be discovered. Crosses between closely-related genotypes differing by single-gene mutants yield profoundly different QTL landscapes, suggesting that fiber variation involves a complex network of interacting genes. Members of the lint fiber development network appear clustered, with cluster members showing heterogeneous phenotypic effects. Meta-analysis linked to synteny-based and expression-based information provides clues about specific genes and families involved in QTL networks. PMID:17565937

Meta-analysis of polyploid cotton QTL shows unequal contributions of subgenomes to a complex network of genes and gene clusters implicated in lint fiber development.

PubMed

Rong, Junkang; Feltus, F Alex; Waghmare, Vijay N; Pierce, Gary J; Chee, Peng W; Draye, Xavier; Saranga, Yehoshua; Wright, Robert J; Wilkins, Thea A; May, O Lloyd; Smith, C Wayne; Gannaway, John R; Wendel, Jonathan F; Paterson, Andrew H

2007-08-01

QTL mapping experiments yield heterogeneous results due to the use of different genotypes, environments, and sampling variation. Compilation of QTL mapping results yields a more complete picture of the genetic control of a trait and reveals patterns in organization of trait variation. A total of 432 QTL mapped in one diploid and 10 tetraploid interspecific cotton populations were aligned using a reference map and depicted in a CMap resource. Early demonstrations that genes from the non-fiber-producing diploid ancestor contribute to tetraploid lint fiber genetics gain further support from multiple populations and environments and advanced-generation studies detecting QTL of small phenotypic effect. Both tetraploid subgenomes contribute QTL at largely non-homeologous locations, suggesting divergent selection acting on many corresponding genes before and/or after polyploid formation. QTL correspondence across studies was only modest, suggesting that additional QTL for the target traits remain to be discovered. Crosses between closely-related genotypes differing by single-gene mutants yield profoundly different QTL landscapes, suggesting that fiber variation involves a complex network of interacting genes. Members of the lint fiber development network appear clustered, with cluster members showing heterogeneous phenotypic effects. Meta-analysis linked to synteny-based and expression-based information provides clues about specific genes and families involved in QTL networks.

Cross-Study Comparison Reveals Common Genomic, Network, and Functional Signatures of Desiccation Resistance in Drosophila melanogaster

PubMed Central

Telonis-Scott, Marina; Sgrò, Carla M.; Hoffmann, Ary A.; Griffin, Philippa C.

2016-01-01

Repeated attempts to map the genomic basis of complex traits often yield different outcomes because of the influence of genetic background, gene-by-environment interactions, and/or statistical limitations. However, where repeatability is low at the level of individual genes, overlap often occurs in gene ontology categories, genetic pathways, and interaction networks. Here we report on the genomic overlap for natural desiccation resistance from a Pool-genome-wide association study experiment and a selection experiment in flies collected from the same region in southeastern Australia in different years. We identified over 600 single nucleotide polymorphisms associated with desiccation resistance in flies derived from almost 1,000 wild-caught genotypes, a similar number of loci to that observed in our previous genomic study of selected lines, demonstrating the genetic complexity of this ecologically important trait. By harnessing the power of cross-study comparison, we narrowed the candidates from almost 400 genes in each study to a core set of 45 genes, enriched for stimulus, stress, and defense responses. In addition to gene-level overlap, there was higher order congruence at the network and functional levels, suggesting genetic redundancy in key stress sensing, stress response, immunity, signaling, and gene expression pathways. We also identified variants linked to different molecular aspects of desiccation physiology previously verified from functional experiments. Our approach provides insight into the genomic basis of a complex and ecologically important trait and predicts candidate genetic pathways to explore in multiple genetic backgrounds and related species within a functional framework. PMID:26733490

Machine Learning for Detecting Gene-Gene Interactions

PubMed Central

McKinney, Brett A.; Reif, David M.; Ritchie, Marylyn D.; Moore, Jason H.

2011-01-01

Complex interactions among genes and environmental factors are known to play a role in common human disease aetiology. There is a growing body of evidence to suggest that complex interactions are ‘the norm’ and, rather than amounting to a small perturbation to classical Mendelian genetics, interactions may be the predominant effect. Traditional statistical methods are not well suited for detecting such interactions, especially when the data are high dimensional (many attributes or independent variables) or when interactions occur between more than two polymorphisms. In this review, we discuss machine-learning models and algorithms for identifying and characterising susceptibility genes in common, complex, multifactorial human diseases. We focus on the following machine-learning methods that have been used to detect gene-gene interactions: neural networks, cellular automata, random forests, and multifactor dimensionality reduction. We conclude with some ideas about how these methods and others can be integrated into a comprehensive and flexible framework for data mining and knowledge discovery in human genetics. PMID:16722772

Mapping fusiform rust resistance genes within a complex mating design of loblolly pine

Treesearch

Tania Quesada; Marcio F.R. Resende Jr.; Patricio Munoz; Jill L. Wegrzyn; David B. Neale; Matias Kirst; Gary F. Peter; Salvador A. Gezan; C.Dana Nelson; John M. Davis

2014-01-01

Fusiform rust resistance can involve gene-for-gene interactions where resistance (Fr) genes in the host interact with corresponding avirulence genes in the pathogen, Cronartium quercuum f.sp. fusiforme (Cqf). Here, we identify trees with Fr genes in a loblolly pine population derived from a complex mating design challenged with two Cqf inocula (one gall and 10 gall...

Genetic mouse models relevant to schizophrenia: taking stock and looking forward.

PubMed

Harrison, Paul J; Pritchett, David; Stumpenhorst, Katharina; Betts, Jill F; Nissen, Wiebke; Schweimer, Judith; Lane, Tracy; Burnet, Philip W J; Lamsa, Karri P; Sharp, Trevor; Bannerman, David M; Tunbridge, Elizabeth M

2012-03-01

Genetic mouse models relevant to schizophrenia complement, and have to a large extent supplanted, pharmacological and lesion-based rat models. The main attraction is that they potentially have greater construct validity; however, they share the fundamental limitations of all animal models of psychiatric disorder, and must also be viewed in the context of the uncertain and complex genetic architecture of psychosis. Some of the key issues, including the choice of gene to target, the manner of its manipulation, gene-gene and gene-environment interactions, and phenotypic characterization, are briefly considered in this commentary, illustrated by the relevant papers reported in this special issue. Copyright © 2011 Elsevier Ltd. All rights reserved.

Binding and condensation of plasmid DNA onto functionalized carbon nanotubes: toward the construction of nanotube-based gene delivery vectors.

PubMed

Singh, Ravi; Pantarotto, Davide; McCarthy, David; Chaloin, Olivier; Hoebeke, Johan; Partidos, Charalambos D; Briand, Jean-Paul; Prato, Maurizio; Bianco, Alberto; Kostarelos, Kostas

2005-03-30

Carbon nanotubes (CNTs) constitute a class of nanomaterials that possess characteristics suitable for a variety of possible applications. Their compatibility with aqueous environments has been made possible by the chemical functionalization of their surface, allowing for exploration of their interactions with biological components including mammalian cells. Functionalized CNTs (f-CNTs) are being intensively explored in advanced biotechnological applications ranging from molecular biosensors to cellular growth substrates. We have been exploring the potential of f-CNTs as delivery vehicles of biologically active molecules in view of possible biomedical applications, including vaccination and gene delivery. Recently we reported the capability of ammonium-functionalized single-walled CNTs to penetrate human and murine cells and facilitate the delivery of plasmid DNA leading to expression of marker genes. To optimize f-CNTs as gene delivery vehicles, it is essential to characterize their interactions with DNA. In the present report, we study the interactions of three types of f-CNTs, ammonium-functionalized single-walled and multiwalled carbon nanotubes (SWNT-NH3+; MWNT-NH3+), and lysine-functionalized single-walled carbon nanotubes (SWNT-Lys-NH3+), with plasmid DNA. Nanotube-DNA complexes were analyzed by scanning electron microscopy, surface plasmon resonance, PicoGreen dye exclusion, and agarose gel shift assay. The results indicate that all three types of cationic carbon nanotubes are able to condense DNA to varying degrees, indicating that both nanotube surface area and charge density are critical parameters that determine the interaction and electrostatic complex formation between f-CNTs with DNA. All three different f-CNT types in this study exhibited upregulation of marker gene expression over naked DNA using a mammalian (human) cell line. Differences in the levels of gene expression were correlated with the structural and biophysical data obtained for the f-CNT:DNA complexes to suggest that large surface area leading to very efficient DNA condensation is not necessary for effective gene transfer. However, it will require further investigation to determine whether the degree of binding and tight association between DNA and nanotubes is a desirable trait to increase gene expression efficiency in vitro or in vivo. This study constitutes the first thorough investigation into the physicochemical interactions between cationic functionalized carbon nanotubes and DNA toward construction of carbon nanotube-based gene transfer vector systems.

Epistasis and Its Implications for Personal Genetics

PubMed Central

Moore, Jason H.; Williams, Scott M.

2009-01-01

The widespread availability of high-throughput genotyping technology has opened the door to the era of personal genetics, which brings to consumers the promise of using genetic variations to predict individual susceptibility to common diseases. Despite easy access to commercial personal genetics services, our knowledge of the genetic architecture of common diseases is still very limited and has not yet fulfilled the promise of accurately predicting most people at risk. This is partly because of the complexity of the mapping relationship between genotype and phenotype that is a consequence of epistasis (gene-gene interaction) and other phenomena such as gene-environment interaction and locus heterogeneity. Unfortunately, these aspects of genetic architecture have not been addressed in most of the genetic association studies that provide the knowledge base for interpreting large-scale genetic association results. We provide here an introductory review of how epistasis can affect human health and disease and how it can be detected in population-based studies. We provide some thoughts on the implications of epistasis for personal genetics and some recommendations for improving personal genetics in light of this complexity. PMID:19733727

Epistasis and its implications for personal genetics.

PubMed

Moore, Jason H; Williams, Scott M

2009-09-01

The widespread availability of high-throughput genotyping technology has opened the door to the era of personal genetics, which brings to consumers the promise of using genetic variations to predict individual susceptibility to common diseases. Despite easy access to commercial personal genetics services, our knowledge of the genetic architecture of common diseases is still very limited and has not yet fulfilled the promise of accurately predicting most people at risk. This is partly because of the complexity of the mapping relationship between genotype and phenotype that is a consequence of epistasis (gene-gene interaction) and other phenomena such as gene-environment interaction and locus heterogeneity. Unfortunately, these aspects of genetic architecture have not been addressed in most of the genetic association studies that provide the knowledge base for interpreting large-scale genetic association results. We provide here an introductory review of how epistasis can affect human health and disease and how it can be detected in population-based studies. We provide some thoughts on the implications of epistasis for personal genetics and some recommendations for improving personal genetics in light of this complexity.

Early Life Precursors, Epigenetics, and the Development of Food Allergy1

PubMed Central

Hong, Xiumei; Wang, Xiaobin

2012-01-01

Food allergy (FA), a major clinical and public health concern worldwide, is caused by a complex interplay of environmental exposures, genetic variants, gene-environment interactions, and epigenetic alterations. This review summarizes recent advances surrounding these key factors, with a particular focus on the potential role of epigenetics in the development of FA. Epidemiologic studies have reported a number of non-genetic factors that may influence the risk of FA, such as timing of food introduction and feeding pattern, diet/nutrition, exposure to environmental tobacco smoking, prematurity and low birthweight, microbial exposure, and race/ethnicity. Current studies on the genetics of FA are mainly conducted using candidate gene approaches, which have linked more than 10 genes to the genetic susceptibility of FA. Studies on gene-environment interactions of FA are very limited. Epigenetic alteration has been proposed as one of the mechanisms to mediate the influence of early-life environmental exposures and gene-environment interactions on the development of diseases later in life. The role of epigenetics in the regulation of the immune system and the epigenetic effects of some FA-associated environmental exposures are discussed in this review. There is a particular lack of large-scale prospective birth cohort studies that simultaneously assess the inter-relationships of early life exposures, genetic susceptibility, epigenomic alterations and the development of FA. The identification of these key factors and their independent and joint contributions to FA will allow us to gain important insight into the biological mechanisms by which environmental exposures and genetic susceptibility affect the risk of FA, and will provide essential information to develop more effective new paradigms in the diagnosis, prevention and management of FA. PMID:22777545

The Impact of Gene-Environment Dependence and Misclassification in Genetic Association Studies Incorporating Gene-Environment Interactions

PubMed Central

Lindström, Sara; Yen, Yu-Chun; Spiegelman, Donna; Kraft, Peter

2009-01-01

The possibility of gene-environment interaction can be exploited to identify genetic variants associated with disease using a joint test of genetic main effect and gene-environment interaction. We consider how exposure misclassification and dependence between the true exposure E and the tested genetic variant G affect this joint test in absolute terms and relative to three other tests: the marginal test (G), the standard test for multiplicative gene-environment interaction (GE), and the case-only test for interaction (GE-CO). All tests can have inflated Type I error rate when E and G are correlated in the underlying population. For the GE and G-GE tests this inflation is only noticeable when the gene-environment dependence is unusually strong; the inflation can be large for the GE-CO test even for modest correlation. The joint G-GE test has greater power than the GE test generally, and greater power than the G test when there is no genetic main effect and the measurement error is small to moderate. The joint G-GE test is an attractive test for assessing genetic association when there is limited knowledge about casual mechanisms a priori, even in the presence of misclassification in environmental exposure measurement and correlation between exposure and genetic variants. PMID:19521099

An Arabidopsis gene regulatory network for secondary cell wall synthesis

DOE PAGES

Taylor-Teeples, M.; Lin, L.; de Lucas, M.; ...

2014-12-24

The plant cell wall is an important factor for determining cell shape, function and response to the environment. Secondary cell walls, such as those found in xylem, are composed of cellulose, hemicelluloses and lignin and account for the bulk of plant biomass. The coordination between transcriptional regulation of synthesis for each polymer is complex and vital to cell function. A regulatory hierarchy of developmental switches has been proposed, although the full complement of regulators remains unknown. In this paper, we present a protein–DNA network between Arabidopsis thaliana transcription factors and secondary cell wall metabolic genes with gene expression regulated bymore » a series of feed-forward loops. This model allowed us to develop and validate new hypotheses about secondary wall gene regulation under abiotic stress. Distinct stresses are able to perturb targeted genes to potentially promote functional adaptation. Finally, these interactions will serve as a foundation for understanding the regulation of a complex, integral plant component.« less

Chemical-gene interaction networks and causal reasoning for ...

EPA Pesticide Factsheets

Evaluating the potential human health and ecological risks associated with exposures to complex chemical mixtures in the environment is one of the main challenges of chemical safety assessment and environmental protection. There is a need for approaches that can help to integrate chemical monitoring and biological effects data to evaluate risks associated with chemicals present in the environment. Here, we used prior knowledge about chemical-gene interactions to develop a knowledge assembly model for detected chemicals at five locations near the North Branch and Chisago wastewater treatment plants (WWTP) in the St. Croix River Basin, MN and WI. The assembly model was used to generate hypotheses about the biological impacts of the chemicals at each location. The hypotheses were tested using empirical hepatic gene expression data from fathead minnows exposed for 12 d at each location. Empirical gene expression data were also mapped to the assembly models to evaluate the likelihood of a chemical contributing to the observed biological responses using richness and concordance statistics. The prior knowledge approach was able predict the observed biological pathways impacted at one site but not the other. Atrazine was identified as a potential contributor to the observed gene expression responses at a location upstream of the North Branch WTTP. Four chemicals were identified as contributors to the observed biological responses at the effluent and downstream o

A global interaction network maps a wiring diagram of cellular function

PubMed Central

Costanzo, Michael; VanderSluis, Benjamin; Koch, Elizabeth N.; Baryshnikova, Anastasia; Pons, Carles; Tan, Guihong; Wang, Wen; Usaj, Matej; Hanchard, Julia; Lee, Susan D.; Pelechano, Vicent; Styles, Erin B.; Billmann, Maximilian; van Leeuwen, Jolanda; van Dyk, Nydia; Lin, Zhen-Yuan; Kuzmin, Elena; Nelson, Justin; Piotrowski, Jeff S.; Srikumar, Tharan; Bahr, Sondra; Chen, Yiqun; Deshpande, Raamesh; Kurat, Christoph F.; Li, Sheena C.; Li, Zhijian; Usaj, Mojca Mattiazzi; Okada, Hiroki; Pascoe, Natasha; Luis, Bryan-Joseph San; Sharifpoor, Sara; Shuteriqi, Emira; Simpkins, Scott W.; Snider, Jamie; Suresh, Harsha Garadi; Tan, Yizhao; Zhu, Hongwei; Malod-Dognin, Noel; Janjic, Vuk; Przulj, Natasa; Troyanskaya, Olga G.; Stagljar, Igor; Xia, Tian; Ohya, Yoshikazu; Gingras, Anne-Claude; Raught, Brian; Boutros, Michael; Steinmetz, Lars M.; Moore, Claire L.; Rosebrock, Adam P.; Caudy, Amy A.; Myers, Chad L.; Andrews, Brenda; Boone, Charles

2017-01-01

We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing over 23 million double mutants, identifying ~550,000 negative and ~350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell. PMID:27708008

Genetics of preeclampsia: what are the challenges?

PubMed

Bernard, Nathalie; Giguère, Yves

2003-07-01

Despite recent efforts to identify susceptibility genes of preeclampsia, the genetic determinants of the condition remain ill-defined, as is the situation for most disorders of complex inheritance patterns. The angiotensinogen, factor V, and methylenetetrahydrofolate reductase genes have been investigated in different populations, as have other genes involved in blood pressure, vascular volume control, thrombophilia, lipid metabolism, oxidative stress, and endothelial dysfunction. The study of the genetics of complex traits is faced with both methodological and genetic issues; these include adequate sample size to allow for the identification of modest genetic effects, of gene-gene and gene-environment interactions, the study of adequate quantitative traits and extreme phenotypes, haplotype analyses, statistical genetics, genome-wide (hypothesis-free) versus candidate-gene (hypothesis-driven) approaches, and the validation of positive associations. The use of genetically well-characterized populations showing a founder effect, such as the French-Canadian population of Quebec, in genetic association studies, may help to unravel the susceptibility genes of disorders showing complex inheritance, such as preeclampsia. It is necessary to better evaluate the role of the fetal genome in the resulting predisposition to preeclampsia and its complications. Eventually, we may be able to integrate genetic information to better identify the women at risk of developing preeclampsia, and to improve the management of those suffering from this condition.

Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence.

PubMed

Liu, Gang; Mukherjee, Bhramar; Lee, Seunggeun; Lee, Alice W; Wu, Anna H; Bandera, Elisa V; Jensen, Allan; Rossing, Mary Anne; Moysich, Kirsten B; Chang-Claude, Jenny; Doherty, Jennifer A; Gentry-Maharaj, Aleksandra; Kiemeney, Lambertus; Gayther, Simon A; Modugno, Francesmary; Massuger, Leon; Goode, Ellen L; Fridley, Brooke L; Terry, Kathryn L; Cramer, Daniel W; Ramus, Susan J; Anton-Culver, Hoda; Ziogas, Argyrios; Tyrer, Jonathan P; Schildkraut, Joellen M; Kjaer, Susanne K; Webb, Penelope M; Ness, Roberta B; Menon, Usha; Berchuck, Andrew; Pharoah, Paul D; Risch, Harvey; Pearce, Celeste Leigh

2018-02-01

There have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances statistical power for testing multiplicative interaction in case-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated type I error in the corresponding tests can occur. In this paper, we extend the empirical Bayes (EB) approach previously developed for multiplicative interaction, which trades off between bias and efficiency in a data-adaptive way, to the additive scale. An EB estimator of the relative excess risk due to interaction is derived, and the corresponding Wald test is proposed with a general regression setting under a retrospective likelihood framework. We study the impact of gene-environment association on the resultant test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides a gain in power compared with the standard logistic regression analysis and better control of type I error when compared with the analysis assuming gene-environment independence. We illustrate the methods with data from the Ovarian Cancer Association Consortium. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Beyond main effects of gene-sets: harsh parenting moderates the association between a dopamine gene-set and child externalizing behavior.

PubMed

Windhorst, Dafna A; Mileva-Seitz, Viara R; Rippe, Ralph C A; Tiemeier, Henning; Jaddoe, Vincent W V; Verhulst, Frank C; van IJzendoorn, Marinus H; Bakermans-Kranenburg, Marian J

2016-08-01

In a longitudinal cohort study, we investigated the interplay of harsh parenting and genetic variation across a set of functionally related dopamine genes, in association with children's externalizing behavior. This is one of the first studies to employ gene-based and gene-set approaches in tests of Gene by Environment (G × E) effects on complex behavior. This approach can offer an important alternative or complement to candidate gene and genome-wide environmental interaction (GWEI) studies in the search for genetic variation underlying individual differences in behavior. Genetic variants in 12 autosomal dopaminergic genes were available in an ethnically homogenous part of a population-based cohort. Harsh parenting was assessed with maternal (n = 1881) and paternal (n = 1710) reports at age 3. Externalizing behavior was assessed with the Child Behavior Checklist (CBCL) at age 5 (71 ± 3.7 months). We conducted gene-set analyses of the association between variation in dopaminergic genes and externalizing behavior, stratified for harsh parenting. The association was statistically significant or approached significance for children without harsh parenting experiences, but was absent in the group with harsh parenting. Similarly, significant associations between single genes and externalizing behavior were only found in the group without harsh parenting. Effect sizes in the groups with and without harsh parenting did not differ significantly. Gene-environment interaction tests were conducted for individual genetic variants, resulting in two significant interaction effects (rs1497023 and rs4922132) after correction for multiple testing. Our findings are suggestive of G × E interplay, with associations between dopamine genes and externalizing behavior present in children without harsh parenting, but not in children with harsh parenting experiences. Harsh parenting may overrule the role of genetic factors in externalizing behavior. Gene-based and gene-set analyses offer promising new alternatives to analyses focusing on single candidate polymorphisms when examining the interplay between genetic and environmental factors.

Cytoscape: a software environment for integrated models of biomolecular interaction networks.

PubMed

Shannon, Paul; Markiel, Andrew; Ozier, Owen; Baliga, Nitin S; Wang, Jonathan T; Ramage, Daniel; Amin, Nada; Schwikowski, Benno; Ideker, Trey

2003-11-01

Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

Linking Genes to Cardiovascular Diseases: Gene Action and Gene–Environment Interactions

PubMed Central

2016-01-01

A unique myocardial characteristic is its ability to grow/remodel in order to adapt; this is determined partly by genes and partly by the environment and the milieu intérieur. In the “post-genomic” era, a need is emerging to elucidate the physiologic functions of myocardial genes, as well as potential adaptive and maladaptive modulations induced by environmental/epigenetic factors. Genome sequencing and analysis advances have become exponential lately, with escalation of our knowledge concerning sometimes controversial genetic underpinnings of cardiovascular diseases. Current technologies can identify candidate genes variously involved in diverse normal/abnormal morphomechanical phenotypes, and offer insights into multiple genetic factors implicated in complex cardiovascular syndromes. The expression profiles of thousands of genes are regularly ascertained under diverse conditions. Global analyses of gene expression levels are useful for cataloging genes and correlated phenotypes, and for elucidating the role of genes in maladies. Comparative expression of gene networks coupled to complex disorders can contribute insights as to how “modifier genes” influence the expressed phenotypes. Increasingly, a more comprehensive and detailed systematic understanding of genetic abnormalities underlying, for example, various genetic cardiomyopathies is emerging. Implementing genomic findings in cardiology practice may well lead directly to better diagnosing and therapeutics. There is currently evolving a strong appreciation for the value of studying gene anomalies, and doing so in a non-disjointed, cohesive manner. However, it is challenging for many—practitioners and investigators—to comprehend, interpret, and utilize the clinically increasingly accessible and affordable cardiovascular genomics studies. This survey addresses the need for fundamental understanding in this vital area. PMID:26545598

Nature versus nurture in determining athletic ability.

PubMed

Brutsaert, Tom D; Parra, Esteban J

2009-01-01

This chapter provides an overview of the truism that both nature and nurture determine human athletic ability. The major thesis developed is that environmental effects work through the process of growth and development and interact with an individual's genetic background to produce a specific adult phenotype, i.e. an athletic or nonathletic phenotype. On the nature side (genetics), a brief historical review is provided with emphasis on several areas that are likely to command future attention including the rise of genome-wide association as a mapping strategy, the problem of false positives using association approaches, as well as the relatively unknown effects of gene-gene interaction(epistasis), gene-environment interaction, and genome structure on complex trait variance. On the nurture side (environment), common environmental effects such as training-level and sports nutrition are largely ignored in favor of developmental environmental effects that are channeled through growth and development processes. Developmental effects are difficult to distinguish from genetic effects as phenotypic plasticity in response to early life environmental perturbation can produce lasting effects into adulthood. In this regard, the fetal programming (FP) hypothesis is reviewed in some detail as FP provides an excellent example of how developmental effects work and also interact with genetics. In general, FP has well-documented effects on adult body composition and the risk for adult chronic disease, but there is emerging evidence that FP affects human athletic performance as well. 2009 S. Karger AG, Basel

Classification and Clustering Methods for Multiple Environmental Factors in Gene-Environment Interaction: Application to the Multi-Ethnic Study of Atherosclerosis.

PubMed

Ko, Yi-An; Mukherjee, Bhramar; Smith, Jennifer A; Kardia, Sharon L R; Allison, Matthew; Diez Roux, Ana V

2016-11-01

There has been an increased interest in identifying gene-environment interaction (G × E) in the context of multiple environmental exposures. Most G × E studies analyze one exposure at a time, but we are exposed to multiple exposures in reality. Efficient analysis strategies for complex G × E with multiple environmental factors in a single model are still lacking. Using the data from the Multiethnic Study of Atherosclerosis, we illustrate a two-step approach for modeling G × E with multiple environmental factors. First, we utilize common clustering and classification strategies (e.g., k-means, latent class analysis, classification and regression trees, Bayesian clustering using Dirichlet Process) to define subgroups corresponding to distinct environmental exposure profiles. Second, we illustrate the use of an additive main effects and multiplicative interaction model, instead of the conventional saturated interaction model using product terms of factors, to study G × E with the data-driven exposure subgroups defined in the first step. We demonstrate useful analytical approaches to translate multiple environmental exposures into one summary class. These tools not only allow researchers to consider several environmental exposures in G × E analysis but also provide some insight into how genes modify the effect of a comprehensive exposure profile instead of examining effect modification for each exposure in isolation.

Simple F Test Reveals Gene-Gene Interactions in Case-Control Studies

PubMed Central

Chen, Guanjie; Yuan, Ao; Zhou, Jie; Bentley, Amy R.; Adeyemo, Adebowale; Rotimi, Charles N.

2012-01-01

Missing heritability is still a challenge for Genome Wide Association Studies (GWAS). Gene-gene interactions may partially explain this residual genetic influence and contribute broadly to complex disease. To analyze the gene-gene interactions in case-control studies of complex disease, we propose a simple, non-parametric method that utilizes the F-statistic. This approach consists of three steps. First, we examine the joint distribution of a pair of SNPs in cases and controls separately. Second, an F-test is used to evaluate the ratio of dependence in cases to that of controls. Finally, results are adjusted for multiple tests. This method was used to evaluate gene-gene interactions that are associated with risk of Type 2 Diabetes among African Americans in the Howard University Family Study. We identified 18 gene-gene interactions (P < 0.0001). Compared with the commonly-used logistical regression method, we demonstrate that the F-ratio test is an efficient approach to measuring gene-gene interactions, especially for studies with limited sample size. PMID:22837643

Routine Discovery of Complex Genetic Models using Genetic Algorithms

PubMed Central

Moore, Jason H.; Hahn, Lance W.; Ritchie, Marylyn D.; Thornton, Tricia A.; White, Bill C.

2010-01-01

Simulation studies are useful in various disciplines for a number of reasons including the development and evaluation of new computational and statistical methods. This is particularly true in human genetics and genetic epidemiology where new analytical methods are needed for the detection and characterization of disease susceptibility genes whose effects are complex, nonlinear, and partially or solely dependent on the effects of other genes (i.e. epistasis or gene-gene interaction). Despite this need, the development of complex genetic models that can be used to simulate data is not always intuitive. In fact, only a few such models have been published. We have previously developed a genetic algorithm approach to discovering complex genetic models in which two single nucleotide polymorphisms (SNPs) influence disease risk solely through nonlinear interactions. In this paper, we extend this approach for the discovery of high-order epistasis models involving three to five SNPs. We demonstrate that the genetic algorithm is capable of routinely discovering interesting high-order epistasis models in which each SNP influences risk of disease only through interactions with the other SNPs in the model. This study opens the door for routine simulation of complex gene-gene interactions among SNPs for the development and evaluation of new statistical and computational approaches for identifying common, complex multifactorial disease susceptibility genes. PMID:20948983

Pas de deux: An Intricate Dance of Anther Smut and Its Host.

PubMed

San Toh, Su; Chen, Zehua; Rouchka, Eric C; Schultz, David J; Cuomo, Christina A; Perlin, Michael H

2018-02-02

The successful interaction between pathogen/parasite and host requires a delicate balance between fitness of the former and survival of the latter. To optimize fitness a parasite/pathogen must effectively create an environment conducive to reproductive success, while simultaneously avoiding or minimizing detrimental host defense response. The association between Microbotryum lychnidis-dioicae and its host Silene latifolia serves as an excellent model to examine such interactions. This fungus is part of a species complex that infects species of the Caryophyllaceae, replacing pollen with the fungal spores. In the current study, transcriptome analyses of the fungus and its host were conducted during discrete stages of bud development so as to identify changes in fungal gene expression that lead to spore development and to identify changes associated with infection in the host plant. In contrast to early biotrophic phase stages of infection for the fungus, the latter stages involve tissue necrosis and in the case of infected female flowers, further changes in the developmental program in which the ovary aborts and a pseudoanther is produced. Transcriptome analysis via Illumina RNA sequencing revealed enrichment of fungal genes encoding small secreted proteins, with hallmarks of effectors and genes found to be relatively unique to the Microbotryum species complex. Host gene expression analyses also identified interesting sets of genes up-regulated, including those involving stress response, host defense response, and several agamous-like MADS-box genes (AGL61 and AGL80), predicted to interact and be involved in male gametophyte development. Copyright © 2018 Toh et al.

Computational gene network study on antibiotic resistance genes of Acinetobacter baumannii.

PubMed

Anitha, P; Anbarasu, Anand; Ramaiah, Sudha

2014-05-01

Multi Drug Resistance (MDR) in Acinetobacter baumannii is one of the major threats for emerging nosocomial infections in hospital environment. Multidrug-resistance in A. baumannii may be due to the implementation of multi-combination resistance mechanisms such as β-lactamase synthesis, Penicillin-Binding Proteins (PBPs) changes, alteration in porin proteins and in efflux pumps against various existing classes of antibiotics. Multiple antibiotic resistance genes are involved in MDR. These resistance genes are transferred through plasmids, which are responsible for the dissemination of antibiotic resistance among Acinetobacter spp. In addition, these resistance genes may also have a tendency to interact with each other or with their gene products. Therefore, it becomes necessary to understand the impact of these interactions in antibiotic resistance mechanism. Hence, our study focuses on protein and gene network analysis on various resistance genes, to elucidate the role of the interacting proteins and to study their functional contribution towards antibiotic resistance. From the search tool for the retrieval of interacting gene/protein (STRING), a total of 168 functional partners for 15 resistance genes were extracted based on the confidence scoring system. The network study was then followed up with functional clustering of associated partners using molecular complex detection (MCODE). Later, we selected eight efficient clusters based on score. Interestingly, the associated protein we identified from the network possessed greater functional similarity with known resistance genes. This network-based approach on resistance genes of A. baumannii could help in identifying new genes/proteins and provide clues on their association in antibiotic resistance. Copyright © 2014 Elsevier Ltd. All rights reserved.

Testing in semiparametric models with interaction, with applications to gene-environment interactions.

PubMed

Maity, Arnab; Carroll, Raymond J; Mammen, Enno; Chatterjee, Nilanjan

2009-01-01

Motivated from the problem of testing for genetic effects on complex traits in the presence of gene-environment interaction, we develop score tests in general semiparametric regression problems that involves Tukey style 1 degree-of-freedom form of interaction between parametrically and non-parametrically modelled covariates. We find that the score test in this type of model, as recently developed by Chatterjee and co-workers in the fully parametric setting, is biased and requires undersmoothing to be valid in the presence of non-parametric components. Moreover, in the presence of repeated outcomes, the asymptotic distribution of the score test depends on the estimation of functions which are defined as solutions of integral equations, making implementation difficult and computationally taxing. We develop profiled score statistics which are unbiased and asymptotically efficient and can be performed by using standard bandwidth selection methods. In addition, to overcome the difficulty of solving functional equations, we give easy interpretations of the target functions, which in turn allow us to develop estimation procedures that can be easily implemented by using standard computational methods. We present simulation studies to evaluate type I error and power of the method proposed compared with a naive test that does not consider interaction. Finally, we illustrate our methodology by analysing data from a case-control study of colorectal adenoma that was designed to investigate the association between colorectal adenoma and the candidate gene NAT2 in relation to smoking history.

Nonclassical Regulation of Transcription: Interchromosomal Interactions at the Malic enzyme Locus of Drosophila melanogaster

PubMed Central

Lum, Thomas E.; Merritt, Thomas J. S.

2011-01-01

Regulation of transcription can be a complex process in which many cis- and trans-interactions determine the final pattern of expression. Among these interactions are trans-interactions mediated by the pairing of homologous chromosomes. These trans-effects are wide ranging, affecting gene regulation in many species and creating complex possibilities in gene regulation. Here we describe a novel case of trans-interaction between alleles of the Malic enzyme (Men) locus in Drosophila melanogaster that results in allele-specific, non-additive gene expression. Using both empirical biochemical and predictive bioinformatic approaches, we show that the regulatory elements of one allele are capable of interacting in trans with, and modifying the expression of, the second allele. Furthermore, we show that nonlocal factors—different genetic backgrounds—are capable of significant interactions with individual Men alleles, suggesting that these trans-effects can be modified by both locally and distantly acting elements. In sum, these results emphasize the complexity of gene regulation and the need to understand both small- and large-scale interactions as more complete models of the role of trans-interactions in gene regulation are developed. PMID:21900270

[Association between MAOA-u VNTR polymorphism and its interaction with stressful life events and major depressive disorder in adolescents].

PubMed

Ma, Jing; Yu, Shun-Ying; Liang, Shan; Ding, Jun; Feng, Zhe; Yang, Fan; Gao, Wei-Jia; Lin, Jia-Ni; Huang, Chun-Xiang; Liu, Xue-Jun; Su, Lin-Yan

2013-07-01

To investigate whether the genetic polymorphism, upstream variable number of tandem repeats (uVNTR), in the monoamine oxidase A (MAOA) gene, is associated with major depressive disorder (MDD) in adolescents and to test whether there is gene-environment interaction between MAOA-uVNTR polymorphism and stressful life events (SLEs). A total of 394 Chinese Han subjects, including 187 adolescent patients with MDD and 207 normal students as a control group, were included in the study. Genotyping was performed by SNaP-shot assay. SLEs in the previous 12 months were evaluated. The groups were compared in terms of the frequency distributions of MAOA-uVNTR genotypes and alleles using statistical software. The binary logistic regression model of gene-environment interaction was established to analyze the association of the gene-environment interaction between MAOA-u VNTR genotypes and SLEs with adolescent MDD. The distribution profiles of MAOA-u VNTR genotypes and alleles were not related to the onset of MDD, severity of depression, comorbid anxiety and suicidal ideation/behavior/attempt in adolescents. The gene-environment interaction between MAOA-u VNTR genotypes and SLEs was not associated with MDD in male or female adolescents. It is not proven that MAOA-u VNTR polymorphism is associated with adolescent MDD. There is also no gene-environment interaction between MAOA-u VNTR polymorphism and SLEs that is associated with adolescent MDD.

Functionality of resistance gene Hero, which controls plant root-infecting potato cyst nematodes, in leaves of tomato.

PubMed

Poch, H L Cabrera; López, R H Manzanilla; Kanyuka, K

2006-07-01

The expression of host genomes is modified locally by root endoparasitic nematode secretions to induce the development of complex cellular structures referred as feeding sites. In compatible interactions, the feeding sites provide the environment and nutrients for the completion of the nematode's life cycle, whereas in an incompatible (resistant) interaction, the host immune system triggers a plant cell death programme, often in the form of a hypersensitive reaction, which restricts nematode reproduction. These processes have been studied in great detail in organ tissues normally infected by these nematodes: the roots. Here we show that host leaves can support a similar set of programmed developmental events in the potato cyst nematode Globodera rostochiensis life cycle that are typical of the root-invading nematodes. We also show that a gene-for-gene type specific disease resistance that is effective against potato cyst nematodes (PCN) in roots also operates in leaves: the expression of the resistance (R) gene Hero and members of its gene family in leaves correlates with the elicitation of a hypersensitive response only during the incompatible interaction. These findings, and the ability to isolate RNA from relevant parasitic stages of the nematode, may have significant implications for the identification of nematode factors involved in incompatible interactions.

Models of Cultural Niche Construction with Selection and Assortative Mating

PubMed Central

Feldman, Marcus W.

2012-01-01

Niche construction is a process through which organisms modify their environment and, as a result, alter the selection pressures on themselves and other species. In cultural niche construction, one or more cultural traits can influence the evolution of other cultural or biological traits by affecting the social environment in which the latter traits may evolve. Cultural niche construction may include either gene-culture or culture-culture interactions. Here we develop a model of this process and suggest some applications of this model. We examine the interactions between cultural transmission, selection, and assorting, paying particular attention to the complexities that arise when selection and assorting are both present, in which case stable polymorphisms of all cultural phenotypes are possible. We compare our model to a recent model for the joint evolution of religion and fertility and discuss other potential applications of cultural niche construction theory, including the evolution and maintenance of large-scale human conflict and the relationship between sex ratio bias and marriage customs. The evolutionary framework we introduce begins to address complexities that arise in the quantitative analysis of multiple interacting cultural traits. PMID:22905167

Gene-Environment Interactions in Asthma: Genetic and Epigenetic Effects.

PubMed

Lee, Jong-Uk; Kim, Jeong Dong; Park, Choon-Sik

2015-07-01

Over the past three decades, a large number of genetic studies have been aimed at finding genetic variants associated with the risk of asthma, applying various genetic and genomic approaches including linkage analysis, candidate gene polymorphism studies, and genome-wide association studies (GWAS). However, contrary to general expectation, even single nucleotide polymorphisms (SNPs) discovered by GWAS failed to fully explain the heritability of asthma. Thus, application of rare allele polymorphisms in well defined phenotypes and clarification of environmental factors have been suggested to overcome the problem of 'missing' heritability. Such factors include allergens, cigarette smoke, air pollutants, and infectious agents during pre- and post-natal periods. The first and simplest interaction between a gene and the environment is a candidate interaction of both a well known gene and environmental factor in a direct physical or chemical interaction such as between CD14 and endotoxin or between HLA and allergens. Several GWAS have found environmental interactions with occupational asthma, aspirin exacerbated respiratory disease, tobacco smoke-related airway dysfunction, and farm-related atopic diseases. As one of the mechanisms behind gene-environment interaction is epigenetics, a few studies on DNA CpG methylation have been reported on subphenotypes of asthma, pitching the exciting idea that it may be possible to intervene at the junction between the genome and the environment. Epigenetic studies are starting to include data from clinical samples, which will make them another powerful tool for re-search on gene-environment interactions in asthma.

Yeast Phenomics: An Experimental Approach for Modeling Gene Interaction Networks that Buffer Disease

PubMed Central

Hartman, John L.; Stisher, Chandler; Outlaw, Darryl A.; Guo, Jingyu; Shah, Najaf A.; Tian, Dehua; Santos, Sean M.; Rodgers, John W.; White, Richard A.

2015-01-01

The genome project increased appreciation of genetic complexity underlying disease phenotypes: many genes contribute each phenotype and each gene contributes multiple phenotypes. The aspiration of predicting common disease in individuals has evolved from seeking primary loci to marginal risk assignments based on many genes. Genetic interaction, defined as contributions to a phenotype that are dependent upon particular digenic allele combinations, could improve prediction of phenotype from complex genotype, but it is difficult to study in human populations. High throughput, systematic analysis of S. cerevisiae gene knockouts or knockdowns in the context of disease-relevant phenotypic perturbations provides a tractable experimental approach to derive gene interaction networks, in order to deduce by cross-species gene homology how phenotype is buffered against disease-risk genotypes. Yeast gene interaction network analysis to date has revealed biology more complex than previously imagined. This has motivated the development of more powerful yeast cell array phenotyping methods to globally model the role of gene interaction networks in modulating phenotypes (which we call yeast phenomic analysis). The article illustrates yeast phenomic technology, which is applied here to quantify gene X media interaction at higher resolution and supports use of a human-like media for future applications of yeast phenomics for modeling human disease. PMID:25668739

Gene x Environment Interactions in Reading Disability and Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Pennington, Bruce F.; McGrath, Lauren M.; Rosenberg, Jenni; Barnard, Holly; Smith, Shelley D.; Willcutt, Erik G.; Friend, Angela; DeFries, John C.; Olson, Richard K.

2009-01-01

This article examines Gene x Environment (G x E) interactions in two comorbid developmental disorders--reading disability (RD) and attention-deficit/hyperactivity disorder (ADHD)--as a window on broader issues on G x E interactions in developmental psychology. The authors first briefly review types of G x E interactions, methods for detecting…

Gene-Gene and Gene-Environment Interactions in Ulcerative Colitis

PubMed Central

Wang, Ming-Hsi; Fiocchi, Claudio; Zhu, Xiaofeng; Ripke, Stephan; Kamboh, M. Ilyas; Rebert, Nancy; Duerr, Richard H.; Achkar, Jean-Paul

2014-01-01

Genome-wide association studies (GWAS) have identified at least 133 ulcerative colitis (UC) associated loci. The role of genetic factors in clinical practice is not clearly defined. The relevance of genetic variants to disease pathogenesis is still uncertain because of not characterized gene-gene and gene-environment interactions. We examined the predictive value of combining the 133 UC risk loci with genetic interactions in an ongoing inflammatory bowel disease (IBD) GWAS. The Wellcome Trust Case-Control Consortium (WTCCC) IBD GWAS was used as a replication cohort. We applied logic regression (LR), a novel adaptive regression methodology, to search for high order interactions. Exploratory genotype correlations with UC sub-phenotypes (extent of disease, need of surgery, age of onset, extra-intestinal manifestations and primary sclerosing cholangitis (PSC)) were conducted. The combination of 133 UC loci yielded good UC risk predictability (area under the curve [AUC] of 0.86). A higher cumulative allele score predicted higher UC risk. Through LR, several lines of evidence for genetic interactions were identified and successfully replicated in the WTCCC cohort. The genetic interactions combined with the gene-smoking interaction significantly improved predictability in the model (AUC, from 0.86 to 0.89, P=3.26E-05). Explained UC variance increased from 37% to 42% after adding the interaction terms. A within case analysis found suggested genetic association with PSC. Our study demonstrates that the LR methodology allows the identification and replication of high order genetic interactions in UC GWAS datasets. UC risk can be predicted by a 133 loci and improved by adding gene-gene and gene-environment interactions. PMID:24241240

Chimeric Protein Complexes in Hybrid Species Generate Novel Phenotypes

PubMed Central

Piatkowska, Elzbieta M.; Naseeb, Samina; Knight, David; Delneri, Daniela

2013-01-01

Hybridization between species is an important mechanism for the origin of novel lineages and adaptation to new environments. Increased allelic variation and modification of the transcriptional network are the two recognized forces currently deemed to be responsible for the phenotypic properties seen in hybrids. However, since the majority of the biological functions in a cell are carried out by protein complexes, inter-specific protein assemblies therefore represent another important source of natural variation upon which evolutionary forces can act. Here we studied the composition of six protein complexes in two different Saccharomyces “sensu stricto” hybrids, to understand whether chimeric interactions can be freely formed in the cell in spite of species-specific co-evolutionary forces, and whether the different types of complexes cause a change in hybrid fitness. The protein assemblies were isolated from the hybrids via affinity chromatography and identified via mass spectrometry. We found evidence of spontaneous chimericity for four of the six protein assemblies tested and we showed that different types of complexes can cause a variety of phenotypes in selected environments. In the case of TRP2/TRP3 complex, the effect of such chimeric formation resulted in the fitness advantage of the hybrid in an environment lacking tryptophan, while only one type of parental combination of the MBF complex allowed the hybrid to grow under respiratory conditions. These phenotypes were dependent on both genetic and environmental backgrounds. This study provides empirical evidence that chimeric protein complexes can freely assemble in cells and reveals a new mechanism to generate phenotypic novelty and plasticity in hybrids to complement the genomic innovation resulting from gene duplication. The ability to exchange orthologous members has also important implications for the adaptation and subsequent genome evolution of the hybrids in terms of pattern of gene loss. PMID:24137105

Assessment of the reliability of protein-protein interactions and protein function prediction.

PubMed

Deng, Minghua; Sun, Fengzhu; Chen, Ting

2003-01-01

As more and more high-throughput protein-protein interaction data are collected, the task of estimating the reliability of different data sets becomes increasingly important. In this paper, we present our study of two groups of protein-protein interaction data, the physical interaction data and the protein complex data, and estimate the reliability of these data sets using three different measurements: (1) the distribution of gene expression correlation coefficients, (2) the reliability based on gene expression correlation coefficients, and (3) the accuracy of protein function predictions. We develop a maximum likelihood method to estimate the reliability of protein interaction data sets according to the distribution of correlation coefficients of gene expression profiles of putative interacting protein pairs. The results of the three measurements are consistent with each other. The MIPS protein complex data have the highest mean gene expression correlation coefficients (0.256) and the highest accuracy in predicting protein functions (70% sensitivity and specificity), while Ito's Yeast two-hybrid data have the lowest mean (0.041) and the lowest accuracy (15% sensitivity and specificity). Uetz's data are more reliable than Ito's data in all three measurements, and the TAP protein complex data are more reliable than the HMS-PCI data in all three measurements as well. The complex data sets generally perform better in function predictions than do the physical interaction data sets. Proteins in complexes are shown to be more highly correlated in gene expression. The results confirm that the components of a protein complex can be assigned to functions that the complex carries out within a cell. There are three interaction data sets different from the above two groups: the genetic interaction data, the in-silico data and the syn-express data. Their capability of predicting protein functions generally falls between that of the Y2H data and that of the MIPS protein complex data. The supplementary information is available at the following Web site: http://www-hto.usc.edu/-msms/AssessInteraction/.

Genome-wide gene by lead exposure interaction analysis identifies UNC5D as a candidate gene for neurodevelopment.

PubMed

Wang, Zhaoxi; Claus Henn, Birgit; Wang, Chaolong; Wei, Yongyue; Su, Li; Sun, Ryan; Chen, Han; Wagner, Peter J; Lu, Quan; Lin, Xihong; Wright, Robert; Bellinger, David; Kile, Molly; Mazumdar, Maitreyi; Tellez-Rojo, Martha Maria; Schnaas, Lourdes; Christiani, David C

2017-07-28

Neurodevelopment is a complex process involving both genetic and environmental factors. Prenatal exposure to lead (Pb) has been associated with lower performance on neurodevelopmental tests. Adverse neurodevelopmental outcomes are more frequent and/or more severe when toxic exposures interact with genetic susceptibility. To explore possible loci associated with increased susceptibility to prenatal Pb exposure, we performed a genome-wide gene-environment interaction study (GWIS) in young children from Mexico (n = 390) and Bangladesh (n = 497). Prenatal Pb exposure was estimated by cord blood Pb concentration. Neurodevelopment was assessed using the Bayley Scales of Infant Development. We identified a locus on chromosome 8, containing UNC5D, and demonstrated evidence of its genome-wide significance with mental composite scores (rs9642758, p meta  = 4.35 × 10 -6 ). Within this locus, the joint effects of two independent single nucleotide polymorphisms (SNPs, rs9642758 and rs10503970) had a p-value of 4.38 × 10 -9 for mental composite scores. Correlating GWIS results with in vitro transcriptomic profiles identified one common gene, SLC1A5, which is involved in synaptic function, neuronal development, and excitotoxicity. Further analysis revealed interconnected interactions that formed a large network of 52 genes enriched with oxidative stress genes and neurodevelopmental genes. Our findings suggest that certain genetic polymorphisms within/near genes relevant to neurodevelopment might modify the toxic effects of Pb exposure via oxidative stress.

Identifying novel interventional strategies for psychiatric disorders: integrating genomics, 'enviromics' and gene-environment interactions in valid preclinical models.

PubMed

McOmish, Caitlin E; Burrows, Emma L; Hannan, Anthony J

2014-10-01

Psychiatric disorders affect a substantial proportion of the population worldwide. This high prevalence, combined with the chronicity of the disorders and the major social and economic impacts, creates a significant burden. As a result, an important priority is the development of novel and effective interventional strategies for reducing incidence rates and improving outcomes. This review explores the progress that has been made to date in establishing valid animal models of psychiatric disorders, while beginning to unravel the complex factors that may be contributing to the limitations of current methodological approaches. We propose some approaches for optimizing the validity of animal models and developing effective interventions. We use schizophrenia and autism spectrum disorders as examples of disorders for which development of valid preclinical models, and fully effective therapeutics, have proven particularly challenging. However, the conclusions have relevance to various other psychiatric conditions, including depression, anxiety and bipolar disorders. We address the key aspects of construct, face and predictive validity in animal models, incorporating genetic and environmental factors. Our understanding of psychiatric disorders is accelerating exponentially, revealing extraordinary levels of genetic complexity, heterogeneity and pleiotropy. The environmental factors contributing to individual, and multiple, disorders also exhibit breathtaking complexity, requiring systematic analysis to experimentally explore the environmental mediators and modulators which constitute the 'envirome' of each psychiatric disorder. Ultimately, genetic and environmental factors need to be integrated via animal models incorporating the spatiotemporal complexity of gene-environment interactions and experience-dependent plasticity, thus better recapitulating the dynamic nature of brain development, function and dysfunction. © 2014 The British Pharmacological Society.

Computational modeling identifies key gene regulatory interactions underlying phenobarbital-mediated tumor promotion

PubMed Central

Luisier, Raphaëlle; Unterberger, Elif B.; Goodman, Jay I.; Schwarz, Michael; Moggs, Jonathan; Terranova, Rémi; van Nimwegen, Erik

2014-01-01

Gene regulatory interactions underlying the early stages of non-genotoxic carcinogenesis are poorly understood. Here, we have identified key candidate regulators of phenobarbital (PB)-mediated mouse liver tumorigenesis, a well-characterized model of non-genotoxic carcinogenesis, by applying a new computational modeling approach to a comprehensive collection of in vivo gene expression studies. We have combined our previously developed motif activity response analysis (MARA), which models gene expression patterns in terms of computationally predicted transcription factor binding sites with singular value decomposition (SVD) of the inferred motif activities, to disentangle the roles that different transcriptional regulators play in specific biological pathways of tumor promotion. Furthermore, transgenic mouse models enabled us to identify which of these regulatory activities was downstream of constitutive androstane receptor and β-catenin signaling, both crucial components of PB-mediated liver tumorigenesis. We propose novel roles for E2F and ZFP161 in PB-mediated hepatocyte proliferation and suggest that PB-mediated suppression of ESR1 activity contributes to the development of a tumor-prone environment. Our study shows that combining MARA with SVD allows for automated identification of independent transcription regulatory programs within a complex in vivo tissue environment and provides novel mechanistic insights into PB-mediated hepatocarcinogenesis. PMID:24464994

Microsatellite polymorphisms associated with human behavioural and psychological phenotypes including a gene-environment interaction.

PubMed

Bagshaw, Andrew T M; Horwood, L John; Fergusson, David M; Gemmell, Neil J; Kennedy, Martin A

2017-02-03

The genetic and environmental influences on human personality and behaviour are a complex matter of ongoing debate. Accumulating evidence indicates that short tandem repeats (STRs) in regulatory regions are good candidates to explain heritability not accessed by genome-wide association studies. We tested for associations between the genotypes of four selected repeats and 18 traits relating to personality, behaviour, cognitive ability and mental health in a well-studied longitudinal birth cohort (n = 458-589) using one way analysis of variance. The repeats were a highly conserved poly-AC microsatellite in the upstream promoter region of the T-box brain 1 (TBR1) gene and three previously studied STRs in the activating enhancer-binding protein 2-beta (AP2-β) and androgen receptor (AR) genes. Where significance was found we used multiple regression to assess the influence of confounding factors. Carriers of the shorter, most common, allele of the AR gene's GGN microsatellite polymorphism had fewer anxiety-related symptoms, which was consistent with previous studies, but in our study this was not significant following Bonferroni correction. No associations with two repeats in the AP2-β gene withstood this correction. A novel finding was that carriers of the minor allele of the TBR1 AC microsatellite were at higher risk of conduct problems in childhood at age 7-9 (p = 0.0007, which did pass Bonferroni correction). Including maternal smoking during pregnancy (MSDP) in models controlling for potentially confounding influences showed that an interaction between TBR1 genotype and MSDP was a significant predictor of conduct problems in childhood and adolescence (p < 0.001), and of self-reported criminal behaviour up to age 25 years (p ≤ 0.02). This interaction remained significant after controlling for possible confounders including maternal age at birth, socio-economic status and education, and offspring birth weight. The potential functional importance of the TBR1 gene's promoter microsatellite deserves further investigation. Our results suggest that it participates in a gene-environment interaction with MDSP and antisocial behaviour. However, previous evidence that mothers who smoke during pregnancy carry genes for antisocial behaviour suggests that epistasis may influence the interaction.

Protein content and methyl donors in maternal diet interact to influence the proliferation rate and cell fate of neural stem cells in rat hippocampus.

PubMed

Amarger, Valérie; Lecouillard, Angèle; Ancellet, Laure; Grit, Isabelle; Castellano, Blandine; Hulin, Philippe; Parnet, Patricia

2014-10-14

Maternal diet during pregnancy and early postnatal life influences the setting up of normal physiological functions in the offspring. Epigenetic mechanisms regulate cell differentiation during embryonic development and may mediate gene/environment interactions. We showed here that high methyl donors associated with normal protein content in maternal diet increased the in vitro proliferation rate of neural stem/progenitor cells isolated from rat E19 fetuses. Gene expression on whole hippocampi at weaning confirmed this effect as evidenced by the higher expression of the Nestin and Igf2 genes, suggesting a higher amount of undifferentiated precursor cells. Additionally, protein restriction reduced the expression of the insulin receptor gene, which is essential to the action of IGFII. Inhibition of DNA methylation in neural stem/progenitor cells in vitro increased the expression of the astrocyte-specific Gfap gene and decreased the expression of the neuron-specific Dcx gene, suggesting an impact on cell differentiation. Our data suggest a complex interaction between methyl donors and protein content in maternal diet that influence the expression of major growth factors and their receptors and therefore impact the proliferation and differentiation capacities of neural stem cells, either through external hormone signals or internal genomic regulation.

Using protein-protein interactions for refining gene networks estimated from microarray data by Bayesian networks.

PubMed

Nariai, N; Kim, S; Imoto, S; Miyano, S

2004-01-01

We propose a statistical method to estimate gene networks from DNA microarray data and protein-protein interactions. Because physical interactions between proteins or multiprotein complexes are likely to regulate biological processes, using only mRNA expression data is not sufficient for estimating a gene network accurately. Our method adds knowledge about protein-protein interactions to the estimation method of gene networks under a Bayesian statistical framework. In the estimated gene network, a protein complex is modeled as a virtual node based on principal component analysis. We show the effectiveness of the proposed method through the analysis of Saccharomyces cerevisiae cell cycle data. The proposed method improves the accuracy of the estimated gene networks, and successfully identifies some biological facts.

Polygenic interactions with environmental adversity in the aetiology of major depressive disorder.

PubMed

Mullins, N; Power, R A; Fisher, H L; Hanscombe, K B; Euesden, J; Iniesta, R; Levinson, D F; Weissman, M M; Potash, J B; Shi, J; Uher, R; Cohen-Woods, S; Rivera, M; Jones, L; Jones, I; Craddock, N; Owen, M J; Korszun, A; Craig, I W; Farmer, A E; McGuffin, P; Breen, G; Lewis, C M

2016-03-01

Major depressive disorder (MDD) is a common and disabling condition with well-established heritability and environmental risk factors. Gene-environment interaction studies in MDD have typically investigated candidate genes, though the disorder is known to be highly polygenic. This study aims to test for interaction between polygenic risk and stressful life events (SLEs) or childhood trauma (CT) in the aetiology of MDD. The RADIANT UK sample consists of 1605 MDD cases and 1064 controls with SLE data, and a subset of 240 cases and 272 controls with CT data. Polygenic risk scores (PRS) were constructed using results from a mega-analysis on MDD by the Psychiatric Genomics Consortium. PRS and environmental factors were tested for association with case/control status and for interaction between them. PRS significantly predicted depression, explaining 1.1% of variance in phenotype (p = 1.9 × 10(-6)). SLEs and CT were also associated with MDD status (p = 2.19 × 10(-4) and p = 5.12 × 10(-20), respectively). No interactions were found between PRS and SLEs. Significant PRSxCT interactions were found (p = 0.002), but showed an inverse association with MDD status, as cases who experienced more severe CT tended to have a lower PRS than other cases or controls. This relationship between PRS and CT was not observed in independent replication samples. CT is a strong risk factor for MDD but may have greater effect in individuals with lower genetic liability for the disorder. Including environmental risk along with genetics is important in studying the aetiology of MDD and PRS provide a useful approach to investigating gene-environment interactions in complex traits.

Genetics, environmental factors and the emerging role of epigenetics in neurodegenerative diseases.

PubMed

Migliore, Lucia; Coppedè, Fabio

2009-07-10

In the present review we summarize recent advances in the understanding of the interaction between genetics and environmental factors involved in complex multi-factorial neurodegenerative disorders such as Alzheimer's disease (AD), Parkinson's disease (PD) and Amyotrophic Lateral Sclerosis (ALS). The discovery of several genes responsible for the familial forms has led to a better comprehension of the molecular pathways involved in the selective neuronal degeneration which is specific for each of these disorders. However, the vast majority of the cases occurs as sporadic forms, likely resulting from complex gene-gene and gene-environment interplay. Several environmental factors, including, pesticides, metals, head injuries, lifestyles and dietary habits have been associated with increased disease risk or even with protection. Hundreds of genetic variants have been investigated as possible risk factors for the sporadic forms, but results are often conflicting, not repeated or inconclusive. New approaches to environmental health research are revealing us that at the basis there could be chemically induced changes in gene regulation and emphasise the importance of understanding the susceptibility of the human epigenome to dietary and other environmental effects.

Enhancing the gene-environment interaction framework through a quasi-experimental research design: evidence from differential responses to September 11.

PubMed

Fletcher, Jason M

2014-01-01

This article uses a gene-environment interaction framework to examine the differential responses to an objective external stressor based on genetic variation in the production of depressive symptoms. This article advances the literature by utilizing a quasi-experimental environmental exposure design, as well as a regression discontinuity design, to control for seasonal trends, which limit the potential for gene-environment correlation and allow stronger causal claims. Replications are attempted for two prominent genes (5-HTT and MAOA), and three additional genes are explored (DRD2, DRD4, and DAT1). This article provides evidence of a main effect of 9/11 on reports of feelings of sadness and fails to replicate a common finding of interaction using 5-HTT but does show support for interaction with MAOA in men. It also provides new evidence that variation in the DRD4 gene modifies an individual's response to the exposure, with individuals with no 7-repeats found to have a muted response.

Allele-specific gene expression in a wild nonhuman primate population

PubMed Central

Tung, J.; Akinyi, M. Y.; Mutura, S.; Altmann, J.; Wray, G. A.; Alberts, S. C.

2015-01-01

Natural populations hold enormous potential for evolutionary genetic studies, especially when phenotypic, genetic and environmental data are all available on the same individuals. However, untangling the genotype-phenotype relationship in natural populations remains a major challenge. Here, we describe results of an investigation of one class of phenotype, allele-specific gene expression (ASGE), in the well-studied natural population of baboons of the Amboseli basin, Kenya. ASGE measurements identify cases in which one allele of a gene is overexpressed relative to the alternative allele of the same gene, within individuals, thus providing a control for background genetic and environmental effects. Here, we characterize the incidence of ASGE in the Amboseli baboon population, focusing on the genetic and environmental contributions to ASGE in a set of eleven genes involved in immunity and defence. Within this set, we identify evidence for common ASGE in four genes. We also present examples of two relationships between cis-regulatory genetic variants and the ASGE phenotype. Finally, we identify one case in which this relationship is influenced by a novel gene-environment interaction. Specifically, the dominance rank of an individual’s mother during its early life (an aspect of that individual’s social environment) influences the expression of the gene CCL5 via an interaction with cis-regulatory genetic variation. These results illustrate how environmental and ecological data can be integrated into evolutionary genetic studies of functional variation in natural populations. They also highlight the potential importance of early life environmental variation in shaping the genetic architecture of complex traits in wild mammals. PMID:21226779

Gene-environment interaction from international cohorts: impact on development and evolution of occupational and environmental lung and airway disease.

PubMed

Gaffney, Adam; Christiani, David C

2015-06-01

Environmental and occupational pulmonary diseases impose a substantial burden of morbidity and mortality on the global population. However, it has been long observed that only some of those who are exposed to pulmonary toxicants go on to develop disease; increasingly, it is being recognized that genetic differences may underlie some of this person-to-person variability. Studies performed throughout the globe are demonstrating important gene-environment interactions for diseases as diverse as chronic beryllium disease, coal workers' pneumoconiosis, silicosis, asbestosis, byssinosis, occupational asthma, and pollution-associated asthma. These findings have, in many instances, elucidated the pathogenesis of these highly complex diseases. At the same time, however, translation of this research into clinical practice has, for good reasons, proceeded slowly. No genetic test has yet emerged with sufficiently robust operating characteristics to be clearly useful or practicable in an occupational or environmental setting. In addition, occupational genetic testing raises serious ethical and policy concerns. Therefore, the primary objective must remain ensuring that the workplace and the environment are safe for all. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Epidemiología genética sobre las teorías causales y la patogénesis de la diabetes mellitus tipo 2.

PubMed

Castro-Juárez, Carlos Jonnathan; Ramírez-García, Sergio Alberto; Villa-Ruano, Nemesio; García-Cruz, Diana

2017-01-01

Diabetes mellitus type 2 (DM2) is a worldwide public health problem. The etiology of the disease is multifactorial and is characterized by great heterogeneity of metabolic disorders. The most common are the insufficient production of insulin, insulin resistance and impaired incretin system. The specialist must understand the multi-causal nature of DM2 in the post-genomic era. This nature is determined by the additive effect of genes and environment, so there is no simple genetic epidemiological model to explain the inheritance pattern. Hence the need to establish the proportion of disease that is determined by genes and the contribution of environmental factors, the combination of which regulates the threshold or tolerance level for diabetes development. Given this complexity in DM2 in this work are discussed the various existing theories of causality of this disease, which will permit us to understand the interaction between the environment and the human genome, and also to know how risk factors or predisposition to this disease influence, laying the grounds that delimit environment interaction with the genome. Copyright: © 2017 SecretarÍa de Salud.

Advancing the science of environmental exposures during pregnancy and the gene-environment through the National Children's Study.

PubMed

Pak, Victoria; Souders, Margaret C

2012-01-01

In this article we provide nurses with information on the importance of studying environmental exposures during fetal, infant, and childhood development in the National Children's Study. Nurses should be aware of this study to aid in mitigating the complex health problems that arise from environment-health interactions. Nurses may help to educate the public, patients, and caregivers and are in an ideal position to be strong advocates for policy change and regulatory monitoring and enforcement. © 2012 AWHONN, the Association of Women's Health, Obstetric and Neonatal Nurses.

Genetic Contributions of Inflammation to Depression

PubMed Central

Barnes, Jacob; Mondelli, Valeria; Pariante, Carmine M

2017-01-01

This paper describes the effects of immune genes genetic variants and mRNA expression on depression's risk, severity, and response to antidepressant treatment, through a systematic review on all papers published between 2000 and 2016. Our results, based largely on case–control studies, suggest that common genetic variants and gene-expression pathways are involved in both immune activation and depression. The most replicated and relevant genetic variants include polymorphisms in the genes for interleukin (IL)-1β, IL-6, IL-10, monocyte chemoattractant protein-1, tumor necrosis factor-alpha, C-reactive protein, and phospholipase A2. Moreover, increased blood cytokines mRNA expression (especially of IL-1β) identifies patients that are less likely to respond to conventional antidepressants. However, even for the most replicated findings there are inconsistent results, not only between studies, but also between the immune effects of the genetic variants and the resulting effects on depression. We find evidence that these discrepant findings may be explained, at least in part, by the heterogeneity of the depression immunophenotype, by environmental influences and gene × environment interactions, and by the complex interfacing of genetic variants with gene expression. Indeed, some of the most robust findings have been obtained in patients developing depression in the context of treatment with interferon-alpha, a widely used model to mimic depression in the context of inflammation. Further ‘omics' approaches, through GWAS and transcriptomics, will finally shed light on the interaction between immune genes, their expression, and the influence of the environment, in the pathogenesis of depression. PMID:27555379

Effects of the Family Environment: Gene-Environment Interaction and Passive Gene-Environment Correlation

ERIC Educational Resources Information Center

Price, Thomas S.; Jaffee, Sara R.

2008-01-01

The classical twin study provides a useful resource for testing hypotheses about how the family environment influences children's development, including how genes can influence sensitivity to environmental effects. However, existing statistical models do not account for the possibility that children can inherit exposure to family environments…

Gene-Environment Interplay between Number of Friends and Prosocial Leadership Behavior in Children

ERIC Educational Resources Information Center

Rivizzigno, Alessandra S.; Brendgen, Mara; Feng, Bei; Vitaro, Frank; Dionne, Ginette; Tremblay, Richard E.; Boivin, Michel

2014-01-01

Enriched environments may moderate the effect of genetic factors on prosocial leadership (gene-environment interaction, G × E). However, positive environmental experiences may also themselves be influenced by a genetic disposition for prosocial leadership (gene-environment correlation, rGE). Relating these processes to friendships, the present…

A database of gene-environment interactions pertaining to blood lipid traits, cardiovascular disease and type 2 diabetes

USDA-ARS?s Scientific Manuscript database

As the role of the environment – diet, exercise, alcohol and tobacco use and sleep among others – is accorded a more prominent role in modifying the relationship between genetic variants and clinical measures of disease, consideration of gene-environment (GxE) interactions is a must. To facilitate i...

[Progress in transgenic fish techniques and application].

PubMed

Ye, Xing; Tian, Yuan-Yuan; Gao, Feng-Ying

2011-05-01

Transgenic technique provides a new way for fish breeding. Stable lines of growth hormone gene transfer carps, salmon and tilapia, as well as fluorescence protein gene transfer zebra fish and white cloud mountain minnow have been produced. The fast growth characteristic of GH gene transgenic fish will be of great importance to promote aquaculture production and economic efficiency. This paper summarized the progress in transgenic fish research and ecological assessments. Microinjection is still the most common used method, but often resulted in multi-site and multi-copies integration. Co-injection of transposon or meganuclease will greatly improve the efficiency of gene transfer and integration. "All fish" gene or "auto gene" should be considered to produce transgenic fish in order to eliminate misgiving on food safety and to benefit expression of the transferred gene. Environmental risk is the biggest obstacle for transgenic fish to be commercially applied. Data indicates that transgenic fish have inferior fitness compared with the traditional domestic fish. However, be-cause of the genotype-by-environment effects, it is difficult to extrapolate simple phenotypes to the complex ecological interactions that occur in nature based on the ecological consequences of the transgenic fish determined in the laboratory. It is critical to establish highly naturalized environments for acquiring reliable data that can be used to evaluate the environ-mental risk. Efficacious physical and biological containment strategies remain to be crucial approaches to ensure the safe application of transgenic fish technology.

Identification of susceptible genes for complex chronic diseases based on disease risk functional SNPs and interaction networks.

PubMed

Li, Wan; Zhu, Lina; Huang, Hao; He, Yuehan; Lv, Junjie; Li, Weimin; Chen, Lina; He, Weiming

2017-10-01

Complex chronic diseases are caused by the effects of genetic and environmental factors. Single nucleotide polymorphisms (SNPs), one common type of genetic variations, played vital roles in diseases. We hypothesized that disease risk functional SNPs in coding regions and protein interaction network modules were more likely to contribute to the identification of disease susceptible genes for complex chronic diseases. This could help to further reveal the pathogenesis of complex chronic diseases. Disease risk SNPs were first recognized from public SNP data for coronary heart disease (CHD), hypertension (HT) and type 2 diabetes (T2D). SNPs in coding regions that were classified into nonsense and missense by integrating several SNP functional annotation databases were treated as functional SNPs. Then, regions significantly associated with each disease were screened using random permutations for disease risk functional SNPs. Corresponding to these regions, 155, 169 and 173 potential disease susceptible genes were identified for CHD, HT and T2D, respectively. A disease-related gene product interaction network in environmental context was constructed for interacting gene products of both disease genes and potential disease susceptible genes for these diseases. After functional enrichment analysis for disease associated modules, 5 CHD susceptible genes, 7 HT susceptible genes and 3 T2D susceptible genes were finally identified, some of which had pleiotropic effects. Most of these genes were verified to be related to these diseases in literature. This was similar for disease genes identified from another method proposed by Lee et al. from a different aspect. This research could provide novel perspectives for diagnosis and treatment of complex chronic diseases and susceptible genes identification for other diseases. Copyright © 2017 Elsevier Inc. All rights reserved.

[Quorum sensing in bacteria and yeast].

PubMed

March Rosselló, Gabriel Alberto; Eiros Bouza, José María

2013-10-19

Bacterial sets are complex dynamic systems, which interact with each other and through the interaction, bacteria coexist, collaborate, compete and share information in a coordinated manner. A way of bacterial communication is quorum sensing. Through this mechanism the bacteria can recognize its concentration in a given environment and they can decide the time at which the expression of a particular set of genes should be started for developing a specific and simultaneous response. The result of these interconnections raises properties that cannot be explained from a single isolated bacterial cell. Copyright © 2012 Elsevier España, S.L. All rights reserved.

A combination test for detection of gene-environment interaction in cohort studies.

PubMed

Coombes, Brandon; Basu, Saonli; McGue, Matt

2017-07-01

Identifying gene-environment (G-E) interactions can contribute to a better understanding of disease etiology, which may help researchers develop disease prevention strategies and interventions. One big criticism of studying G-E interaction is the lack of power due to sample size. Studies often restrict the interaction search to the top few hundred hits from a genome-wide association study or focus on potential candidate genes. In this paper, we test interactions between a candidate gene and an environmental factor to improve power by analyzing multiple variants within a gene. We extend recently developed score statistic based genetic association testing approaches to the G-E interaction testing problem. We also propose tests for interaction using gene-based summary measures that pool variants together. Although it has recently been shown that these summary measures can be biased and may lead to inflated type I error, we show that under several realistic scenarios, we can still provide valid tests of interaction. These tests use significantly less degrees of freedom and thus can have much higher power to detect interaction. Additionally, we demonstrate that the iSeq-aSum-min test, which combines a gene-based summary measure test, iSeq-aSum-G, and an interaction-based summary measure test, iSeq-aSum-I, provides a powerful alternative to test G-E interaction. We demonstrate the performance of these approaches using simulation studies and illustrate their performance to study interaction between the SNPs in several candidate genes and family climate environment on alcohol consumption using the Minnesota Center for Twin and Family Research dataset. © 2017 WILEY PERIODICALS, INC.

The visual orientation memory of Drosophila requires Foraging (PKG) upstream of Ignorant (RSK2) in ring neurons of the central complex

PubMed Central

Kuntz, Sara; Poeck, Burkhard; Sokolowski, Marla B.; Strauss, Roland

2012-01-01

Orientation and navigation in a complex environment requires path planning and recall to exert goal-driven behavior. Walking Drosophila flies possess a visual orientation memory for attractive targets which is localized in the central complex of the adult brain. Here we show that this type of working memory requires the cGMP-dependent protein kinase encoded by the foraging gene in just one type of ellipsoid-body ring neurons. Moreover, genetic and epistatic interaction studies provide evidence that Foraging functions upstream of the Ignorant Ribosomal-S6 Kinase 2, thus revealing a novel neuronal signaling pathway necessary for this type of memory in Drosophila. PMID:22815538

Multiple Vibrio fischeri genes are involved in biofilm formation and host colonization

PubMed Central

Chavez-Dozal, Alba; Hogan, David; Gorman, Clayton; Quintanal-Villalonga, Alvaro; Nishiguchi, Michele K.

2012-01-01

Biofilms are increasingly recognized as the predominant form for survival in the environment for most bacteria. The successful colonization of Vibrio fischeri in its squid host Euprymna tasmanica, involves complex microbe-host interactions mediated by specific genes that are essential for biofilm formation and colonization. In the present investigation, structural and regulatory genes were selected to study their role in biofilm formation and host colonization. We have mutated several genes (pilT, pilU, flgF, motY, ibpA and mifB) by an insertional inactivation strategy. Results demonstrate that structural genes responsible for synthesis of type IV pili and flagella are crucial for biofilm formation and host infection. Moreover, regulatory genes affect colony aggregation by various mechanisms including alteration of synthesis of transcriptional factors and regulation of extracellular polysaccharide production. These results reflect the significance of how genetic alterations influence communal behavior, which is important in understanding symbiotic relationships. PMID:22486781

Life events and borderline personality features: the influence of gene-environment interaction and gene-environment correlation.

PubMed

Distel, M A; Middeldorp, C M; Trull, T J; Derom, C A; Willemsen, G; Boomsma, D I

2011-04-01

Traumatic life events are generally more common in patients with borderline personality disorder (BPD) than in non-patients or patients with other personality disorders. This study investigates whether exposure to life events moderates the genetic architecture of BPD features. As the presence of genotype-environment correlation (rGE) can lead to spurious findings of genotype-environment interaction (G × E), we also test whether BPD features increase the likelihood of exposure to life events. The extent to which an individual is at risk to develop BPD was assessed with the Personality Assessment Inventory - Borderline features scale (PAI-BOR). Life events under study were a divorce/break-up, traffic accident, violent assault, sexual assault, robbery and job loss. Data were available for 5083 twins and 1285 non-twin siblings. Gene-environment interaction and correlation were assessed by using structural equation modelling (SEM) and the co-twin control design. There was evidence for both gene-environment interaction and correlation. Additive genetic influences on BPD features interacted with the exposure to sexual assault, with genetic variance being lower in exposed individuals. In individuals who had experienced a divorce/break-up, violent assault, sexual assault or job loss, environmental variance for BPD features was higher, leading to a lower heritability of BPD features in exposed individuals. Gene-environment correlation was present for some life events. The genes that influence BPD features thus also increased the likelihood of being exposed to certain life events. To our knowledge, this study is the first to test the joint effect of genetic and environmental influences and the exposure to life events on BPD features in the general population. Our results indicate the importance of both genetic vulnerability and life events.

Behavioral science and the study of gene-nutrition and gene-physical activity interactions in obesity research.

PubMed

Faith, Myles S

2008-12-01

This report summarizes emerging opportunities for behavioral science to help advance the field of gene-environment and gene-behavior interactions, based on presentations at The National Cancer Institute (NCI) Workshop, "Gene-Nutrition and Gene-Physical Activity Interactions in the Etiology of Obesity." Three opportunities are highlighted: (i) designing potent behavioral "challenges" in experiments, (ii) determining viable behavioral phenotypes for genetics studies, and (iii) identifying specific measures of the environment or environmental exposures. Additional points are underscored, including the need to incorporate novel findings from neuroimaging studies regarding motivation and drive for eating and physical activity. Advances in behavioral science theory and methods can play an important role in advancing understanding of gene-brain-behavior relationships in obesity onset.

Combining inferred regulatory and reconstructed metabolic networks enhances phenotype prediction in yeast.

PubMed

Wang, Zhuo; Danziger, Samuel A; Heavner, Benjamin D; Ma, Shuyi; Smith, Jennifer J; Li, Song; Herricks, Thurston; Simeonidis, Evangelos; Baliga, Nitin S; Aitchison, John D; Price, Nathan D

2017-05-01

Gene regulatory and metabolic network models have been used successfully in many organisms, but inherent differences between them make networks difficult to integrate. Probabilistic Regulation Of Metabolism (PROM) provides a partial solution, but it does not incorporate network inference and underperforms in eukaryotes. We present an Integrated Deduced And Metabolism (IDREAM) method that combines statistically inferred Environment and Gene Regulatory Influence Network (EGRIN) models with the PROM framework to create enhanced metabolic-regulatory network models. We used IDREAM to predict phenotypes and genetic interactions between transcription factors and genes encoding metabolic activities in the eukaryote, Saccharomyces cerevisiae. IDREAM models contain many fewer interactions than PROM and yet produce significantly more accurate growth predictions. IDREAM consistently outperformed PROM using any of three popular yeast metabolic models and across three experimental growth conditions. Importantly, IDREAM's enhanced accuracy makes it possible to identify subtle synthetic growth defects. With experimental validation, these novel genetic interactions involving the pyruvate dehydrogenase complex suggested a new role for fatty acid-responsive factor Oaf1 in regulating acetyl-CoA production in glucose grown cells.

The case-only test for gene-environment interaction is not uniformly powerful: an empirical example

PubMed Central

Wu, Chen; Chang, Jiang; Ma, Baoshan; Miao, Xiaoping; Zhou, Yifeng; Liu, Yu; Li, Yun; Wu, Tangchun; Hu, Zhibin; Shen, Hongbing; Jia, Weihua; Zeng, Yixin; Lin, Dongxin; Kraft, Peter

2016-01-01

The case-only test has been proposed as a more powerful approach to detect gene-environment (G×E) interactions. This approach assumes that the genetic and environmental factors are independent. While it is well known that Type I error rate will increase if this assumption is violated, it is less widely appreciated that gene-environment correlation can also lead to power loss. We illustrate this phenomenon by comparing the performance of the case-only test to other approaches to detect G×E interactions in a genome-wide association study of esophageal squamous carcinoma (ESCC) in Chinese populations. Some of these approaches do not use information on the correlation between exposure and genotype (standard logistic regression), while others seek to use this information in a robust fashion to boost power without increasing Type I error (two-step, empirical Bayes and cocktail methods). G×E interactions were identified involving drinking status and two regions containing genes in the alcohol metabolism pathway, 4q23 and 12q24. Although the case-only test yielded the most significant tests of G×E interaction in the 4q23 region, the case-only test failed to identify significant interactions in the 12q24 region which were readily identified using other approaches. The low power of the case-only test in the 12q24 region is likely due to the strong inverse association between the SNPs in this region and drinking status. This example underscores the need to consider multiple approaches to detect gene-environment interactions, as different tests are more or less sensitive to different alternative hypotheses and violations of the gene-environment independence assumption. PMID:23595356

Gene–environment interaction between the oxytocin receptor (OXTR) gene and parenting behaviour on children’s theory of mind

PubMed Central

Wade, Mark; Hoffmann, Thomas J.; Jenkins, Jennifer M.

2015-01-01

Theory of mind (ToM) is the ability to interpret and understand human behaviour by representing the mental states of others. Like many human capacities, ToM is thought to develop through both complex biological and socialization mechanisms. However, no study has examined the joint effect of genetic and environmental influences on ToM. This study examined how variability in the oxytocin receptor gene (OXTR) and parenting behaviour—two widely studied factors in ToM development—interacted to predict ToM in pre-school-aged children. Participants were 301 children who were part of an ongoing longitudinal birth cohort study. ToM was assessed at age 4.5 using a previously validated scale. Parenting was assessed through observations of mothers’ cognitively sensitive behaviours. Using a family-based association design, it was suggestive that a particular variant (rs11131149) interacted with maternal cognitive sensitivity on children’s ToM (P = 0.019). More copies of the major allele were associated with higher ToM as a function of increasing cognitive sensitivity. A sizeable 26% of the variability in ToM was accounted for by this interaction. This study provides the first empirical evidence of gene–environment interactions on ToM, supporting the notion that genetic factors may be modulated by potent environmental influences early in development. PMID:25977357

The exposome concept in a human nutrigenomics study: evaluating the impact of exposure to a complex mixture of phytochemicals using transcriptomics signatures.

PubMed

van Breda, Simone G J; Wilms, Lonneke C; Gaj, Stan; Jennen, Danyel G J; Briedé, Jacob J; Kleinjans, Jos C S; de Kok, Theo M C M

2015-11-01

The application of transcriptome analyses in molecular epidemiology studies has become a promising tool in order to evaluate the impact of environmental exposures. These analyses have a great value in establishing the exposome, the totality of human exposures, both by identifying the chemical nature of the exposures and the induced molecular responses. Transcriptomic signatures can be regarded as biomarker of exposure as well as markers of effect which reflect the interaction between individual genetic background and exposure levels. However, the biological interpretation of modulated gene expression profiles is a challenging task and translating affected molecular pathways into risk assessment, for instance in terms of cancer promoting or disease preventing responses, is a far from standardised process. Here, we describe the in-depth analyses of the gene expression responses in a human dietary intervention in which the interaction between genotype and exposure to a blueberry-apple juice containing a complex mixture of phytochemicals is investigated. We also describe how data on differences in genetic background combined with different effect markers can provide a better understanding of gene-environment interactions. Pathway analyses of differentially expressed genes in combination with gene were used to identify complex but strong changes in several biological processes like immune response, cell adhesion, lipid metabolism and apoptosis. These observed changes may lead to upgraded growth control, induced immunity, reduced platelet aggregation and activation, diminished production of reactive oxidative species by platelets, blood glucose homeostasis, regulation of blood lipid levels and increased apoptosis. Our findings demonstrate that applying transcriptomics to well-controlled human dietary intervention studies can provide insight into mechanistic pathways involved in disease prevention by dietary factors. © The Author 2015. Published by Oxford University Press on behalf of the UK Environmental Mutagen Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The interaction of early life experiences with COMT val158met affects anxiety sensitivity.

PubMed

Baumann, C; Klauke, B; Weber, H; Domschke, K; Zwanzger, P; Pauli, P; Deckert, J; Reif, A

2013-11-01

The pathogenesis of anxiety disorders is considered to be multifactorial with a complex interaction of genetic factors and individual environmental factors. Therefore, the aim of this study was to examine gene-by-environment interactions of the genes coding for catechol-O-methyltransferase (COMT) and monoamine oxidase A (MAOA) with life events on measures related to anxiety. A sample of healthy subjects (N = 782; thereof 531 women; mean age M = 24.79, SD = 6.02) was genotyped for COMT rs4680 and MAOA-uVNTR (upstream variable number of tandem repeats), and was assessed for childhood adversities [Childhood Trauma Questionnaire (CTQ)], anxiety sensitivity [Anxiety Sensitivity Index (ASI)] and anxious apprehension [Penn State Worry Questionnaire (PSWQ)]. Main and interaction effects of genotype, environment and gender on measures related to anxiety were assessed by means of regression analyses. Association analysis showed no main gene effect on either questionnaire score. A significant interactive effect of childhood adversities and COMT genotype was observed: Homozygosity for the low-active met allele and high CTQ scores was associated with a significant increment of explained ASI variance [R(2) = 0.040, false discovery rate (FDR) corrected P = 0.04]. A borderline interactive effect with respect to MAOA-uVNTR was restricted to the male subgroup. Carriers of the low-active MAOA allele who reported more aversive experiences in childhood exhibited a trend for enhanced anxious apprehension (R(2) = 0.077, FDR corrected P = 0.10). Early aversive life experiences therefore might increase the vulnerability to anxiety disorders in the presence of homozygosity for the COMT 158met allele or low-active MAOA-uVNTR alleles. © 2013 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Toward a 3D model of human brain development for studying gene/environment interactions

PubMed Central

2013-01-01

This project aims to establish and characterize an in vitro model of the developing human brain for the purpose of testing drugs and chemicals. To accurately assess risk, a model needs to recapitulate the complex interactions between different types of glial cells and neurons in a three-dimensional platform. Moreover, human cells are preferred over cells from rodents to eliminate cross-species differences in sensitivity to chemicals. Previously, we established conditions to culture rat primary cells as three-dimensional aggregates, which will be humanized and evaluated here with induced pluripotent stem cells (iPSCs). The use of iPSCs allows us to address gene/environment interactions as well as the potential of chemicals to interfere with epigenetic mechanisms. Additionally, iPSCs afford us the opportunity to study the effect of chemicals during very early stages of brain development. It is well recognized that assays for testing toxicity in the developing brain must consider differences in sensitivity and susceptibility that arise depending on the time of exposure. This model will reflect critical developmental processes such as proliferation, differentiation, lineage specification, migration, axonal growth, dendritic arborization and synaptogenesis, which will probably display differences in sensitivity to different types of chemicals. Functional endpoints will evaluate the complex cell-to-cell interactions that are affected in neurodevelopment through chemical perturbation, and the efficacy of drug intervention to prevent or reverse phenotypes. The model described is designed to assess developmental neurotoxicity effects on unique processes occurring during human brain development by leveraging human iPSCs from diverse genetic backgrounds, which can be differentiated into different cell types of the central nervous system. Our goal is to demonstrate the feasibility of the personalized model using iPSCs derived from individuals with neurodevelopmental disorders caused by known mutations and chromosomal aberrations. Notably, such a human brain model will be a versatile tool for more complex testing platforms and strategies as well as research into central nervous system physiology and pathology. PMID:24564953

Gene-Environment Interactions across Development: Exploring DRD2 Genotype and Prenatal Smoking Effects on Self-Regulation

ERIC Educational Resources Information Center

Wiebe, Sandra A.; Espy, Kimberly Andrews; Stopp, Christian; Respass, Jennifer; Stewart, Peter; Jameson, Travis R.; Gilbert, David G.; Huggenvik, Jodi I.

2009-01-01

Genetic factors dynamically interact with both pre- and postnatal environmental influences to shape development. Considerable attention has been devoted to gene-environment interactions (G x E) on important outcomes (A. Caspi & T. E. Moffitt, 2006). It is also important to consider the possibility that these G x E effects may vary across…

Confirmatory and Competitive Evaluation of Alternative Gene-Environment Interaction Hypotheses

ERIC Educational Resources Information Center

Belsky, Jay; Pluess, Michael; Widaman, Keith F.

2013-01-01

Background: Most gene-environment interaction (GXE) research, though based on clear, vulnerability-oriented hypotheses, is carried out using exploratory rather than hypothesis-informed statistical tests, limiting power and making formal evaluation of competing GXE propositions difficult. Method: We present and illustrate a new regression technique…

Developmental programming: interaction between prenatal BPA and postnatal overfeeding on cardiac tissue gene expression in female sheep

PubMed Central

Koneva, LA; Vyas, AK; McEachin, RC; Puttabyatappa, M; H-S, Wang; Sartor, MA; Padmanabhan, V

2017-01-01

Epidemiologic studies and studies in rodents point to potential risks from developmental exposure to BPA on cardiometabolic diseases. Furthermore, it is becoming increasingly evident that the manifestation and severity of adverse outcomes is the result of interaction between developmental insults and the prevailing environment. Consistent with this premise, recent studies in sheep found prenatal BPA treatment prevented the adverse effects of postnatal obesity in inducing hypertension. The gene networks underlying these complex interactions are not known. mRNA-seq of myocardium was performed on four groups of four female sheep to assess the effects of prenatal BPA exposure, postnatal overfeeding and their interaction on gene transcription, pathway perturbations and functional effects. The effects of prenatal exposure to BPA, postnatal overfeeding, and prenatal BPA with postnatal overfeeding all resulted in transcriptional changes (85–141 significant differentially expressed genes). Although the effects of prenatal BPA and postnatal overfeeding did not involve dysregulation of many of the same genes, they affected a remarkably similar set of biological pathways. Furthermore, an additive or synergistic effect was not found in the combined treatment group, but rather prenatal BPA treatment led to a partial reversal of the effects of overfeeding alone. Many genes previously known to be affected by BPA and involved in obesity, hypertension, or heart disease were altered following these treatments, and AP-1, EGR1, and EGFR were key hubs affected by BPA and/or overfeeding. PMID:28079927

Prospects and challenges for fungal metatranscriptomes of complex communities

DOE PAGES

Kuske, Cheryl Rae; Hesse, Cedar Nelson; Challacombe, Jean Faust; ...

2015-01-22

We report that the ability to extract and purify messenger RNA directly from plants, decomposing organic matter and soil, followed by high-throughput sequencing of the pool of expressed genes, has spawned the emerging research area of metatranscriptomics. Each metatranscriptome provides a snapshot of the composition and relative abundance of actively transcribed genes, and thus provides an assessment of the interactions between soil microorganisms and plants, and collective microbial metabolic processes in many environments. We highlight current approaches for analysis of fungal transcriptome and metatranscriptome datasets across a gradient of community complexity, and note benefits and pitfalls associated with those approaches.more » Finally, we discuss knowledge gaps that limit our current ability to interpret metatranscriptome datasets and suggest future research directions that will require concerted efforts within the scientific community.« less

Next Generation Analytic Tools for Large Scale Genetic Epidemiology Studies of Complex Diseases

PubMed Central

Mechanic, Leah E.; Chen, Huann-Sheng; Amos, Christopher I.; Chatterjee, Nilanjan; Cox, Nancy J.; Divi, Rao L.; Fan, Ruzong; Harris, Emily L.; Jacobs, Kevin; Kraft, Peter; Leal, Suzanne M.; McAllister, Kimberly; Moore, Jason H.; Paltoo, Dina N.; Province, Michael A.; Ramos, Erin M.; Ritchie, Marylyn D.; Roeder, Kathryn; Schaid, Daniel J.; Stephens, Matthew; Thomas, Duncan C.; Weinberg, Clarice R.; Witte, John S.; Zhang, Shunpu; Zöllner, Sebastian; Feuer, Eric J.; Gillanders, Elizabeth M.

2012-01-01

Over the past several years, genome-wide association studies (GWAS) have succeeded in identifying hundreds of genetic markers associated with common diseases. However, most of these markers confer relatively small increments of risk and explain only a small proportion of familial clustering. To identify obstacles to future progress in genetic epidemiology research and provide recommendations to NIH for overcoming these barriers, the National Cancer Institute sponsored a workshop entitled “Next Generation Analytic Tools for Large-Scale Genetic Epidemiology Studies of Complex Diseases” on September 15–16, 2010. The goal of the workshop was to facilitate discussions on (1) statistical strategies and methods to efficiently identify genetic and environmental factors contributing to the risk of complex disease; and (2) how to develop, apply, and evaluate these strategies for the design, analysis, and interpretation of large-scale complex disease association studies in order to guide NIH in setting the future agenda in this area of research. The workshop was organized as a series of short presentations covering scientific (gene-gene and gene-environment interaction, complex phenotypes, and rare variants and next generation sequencing) and methodological (simulation modeling and computational resources and data management) topic areas. Specific needs to advance the field were identified during each session and are summarized. PMID:22147673

A Penalized Robust Method for Identifying Gene-Environment Interactions

PubMed Central

Shi, Xingjie; Liu, Jin; Huang, Jian; Zhou, Yong; Xie, Yang; Ma, Shuangge

2015-01-01

In high-throughput studies, an important objective is to identify gene-environment interactions associated with disease outcomes and phenotypes. Many commonly adopted methods assume specific parametric or semiparametric models, which may be subject to model mis-specification. In addition, they usually use significance level as the criterion for selecting important interactions. In this study, we adopt the rank-based estimation, which is much less sensitive to model specification than some of the existing methods and includes several commonly encountered data and models as special cases. Penalization is adopted for the identification of gene-environment interactions. It achieves simultaneous estimation and identification and does not rely on significance level. For computation feasibility, a smoothed rank estimation is further proposed. Simulation shows that under certain scenarios, for example with contaminated or heavy-tailed data, the proposed method can significantly outperform the existing alternatives with more accurate identification. We analyze a lung cancer prognosis study with gene expression measurements under the AFT (accelerated failure time) model. The proposed method identifies interactions different from those using the alternatives. Some of the identified genes have important implications. PMID:24616063

Translating Mendelian and complex inheritance of Alzheimer's disease genes for predicting unique personal genome variants

PubMed Central

Regan, Kelly; Wang, Kanix; Doughty, Emily; Li, Haiquan; Li, Jianrong; Lee, Younghee; Kann, Maricel G

2012-01-01

Objective Although trait-associated genes identified as complex versus single-gene inheritance differ substantially in odds ratio, the authors nonetheless posit that their mechanistic concordance can reveal fundamental properties of the genetic architecture, allowing the automated interpretation of unique polymorphisms within a personal genome. Materials and methods An analytical method, SPADE-gen, spanning three biological scales was developed to demonstrate the mechanistic concordance between Mendelian and complex inheritance of Alzheimer's disease (AD) genes: biological functions (BP), protein interaction modeling, and protein domain implicated in the disease-associated polymorphism. Results Among Gene Ontology (GO) biological processes (BP) enriched at a false detection rate <5% in 15 AD genes of Mendelian inheritance (Online Mendelian Inheritance in Man) and independently in those of complex inheritance (25 host genes of intragenic AD single-nucleotide polymorphisms confirmed in genome-wide association studies), 16 overlapped (empirical p=0.007) and 45 were similar (empirical p<0.009; information theory). SPAN network modeling extended the canonical pathway of AD (KEGG) with 26 new protein interactions (empirical p<0.0001). Discussion The study prioritized new AD-associated biological mechanisms and focused the analysis on previously unreported interactions associated with the biological processes of polymorphisms that affect specific protein domains within characterized AD genes and their direct interactors using (1) concordant GO-BP and (2) domain interactions within STRING protein–protein interactions corresponding to the genomic location of the AD polymorphism (eg, EPHA1, APOE, and CD2AP). Conclusion These results are in line with unique-event polymorphism theory, indicating how disease-associated polymorphisms of Mendelian or complex inheritance relate genetically to those observed as ‘unique personal variants’. They also provide insight for identifying novel targets, for repositioning drugs, and for personal therapeutics. PMID:22319180

Transcriptomic analysis suggests a key role for SQUAMOSA PROMOTER BINDING PROTEIN LIKE, NAC and YUCCA genes in the heteroblastic development of the temperate rainforest tree Gevuina avellana (Proteaceae).

PubMed

Ostria-Gallardo, Enrique; Ranjan, Aashish; Chitwood, Daniel H; Kumar, Ravi; Townsley, Brad T; Ichihashi, Yasunori; Corcuera, Luis J; Sinha, Neelima R

2016-04-01

Heteroblasty, the temporal development of the meristem, can produce diverse leaf shapes within a plant. Gevuina avellana, a tree from the South American temperate rainforest shows strong heteroblasty affecting leaf shape, transitioning from juvenile simple leaves to highly pinnate adult leaves. Light availability within the forest canopy also modulates its leaf size and complexity. Here we studied how the interaction between the light environment and the heteroblastic progression of leaves is coordinated in this species. We used RNA-seq on the Illumina platform to compare the range of transcriptional responses in leaf primordia of G. avellana at different heteroblastic stages and growing under different light environments. We found a steady up-regulation of SQUAMOSA PROMOTER BINDING PROTEIN LIKE (SPL), NAC, YUCCA and AGAMOUS-LIKE genes associated with increases in age, leaf complexity, and light availability. In contrast, expression of TCP, TPR and KNOTTED1 homeobox genes showed a sustained down-regulation. Additionally, genes involved in auxin synthesis/transport and jasmonate activity were differentially expressed, indicating an active regulation of processes controlled by these hormones. Our large-scale transcriptional analysis of the leaf primordia of G. avellana sheds light on the integration of internal and external cues during heteroblastic development in this species. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

The Nuclear Pore-Associated TREX-2 Complex Employs Mediator to Regulate Gene Expression

PubMed Central

Schneider, Maren; Hellerschmied, Doris; Schubert, Tobias; Amlacher, Stefan; Vinayachandran, Vinesh; Reja, Rohit; Pugh, B. Franklin; Clausen, Tim; Köhler, Alwin

2015-01-01

Summary Nuclear pore complexes (NPCs) influence gene expression besides their established function in nuclear transport. The TREX-2 complex localizes to the NPC basket and affects gene-NPC interactions, transcription, and mRNA export. How TREX-2 regulates the gene expression machinery is unknown. Here, we show that TREX-2 interacts with the Mediator complex, an essential regulator of RNA Polymerase (Pol) II. Structural and biochemical studies identify a conserved region on TREX-2, which directly binds the Mediator Med31/Med7N submodule. TREX-2 regulates assembly of Mediator with the Cdk8 kinase and is required for recruitment and site-specific phosphorylation of Pol II. Transcriptome and phenotypic profiling confirm that TREX-2 and Med31 are functionally interdependent at specific genes. TREX-2 additionally uses its Mediator-interacting surface to regulate mRNA export suggesting a mechanism for coupling transcription initiation and early steps of mRNA processing. Our data provide mechanistic insight into how an NPC-associated adaptor complex accesses the core transcription machinery. PMID:26317468

Integration of mRNP formation and export.

PubMed

Björk, Petra; Wieslander, Lars

2017-08-01

Expression of protein-coding genes in eukaryotes relies on the coordinated action of many sophisticated molecular machineries. Transcription produces precursor mRNAs (pre-mRNAs) and the active gene provides an environment in which the pre-mRNAs are processed, folded, and assembled into RNA-protein (RNP) complexes. The dynamic pre-mRNPs incorporate the growing transcript, proteins, and the processing machineries, as well as the specific protein marks left after processing that are essential for export and the cytoplasmic fate of the mRNPs. After release from the gene, the mRNPs move by diffusion within the interchromatin compartment, making up pools of mRNPs. Here, splicing and polyadenylation can be completed and the mRNPs recruit the major export receptor NXF1. Export competent mRNPs interact with the nuclear pore complex, leading to export, concomitant with compositional and conformational changes of the mRNPs. We summarize the integrated nuclear processes involved in the formation and export of mRNPs.

Role of peroxisome proliferator-activated receptors gene polymorphisms in type 2 diabetes and metabolic syndrome

PubMed Central

Dong, Chen; Zhou, Hui; Shen, Chong; Yu, Lu-Gang; Ding, Yi; Zhang, Yong-Hong; Guo, Zhi-Rong

2015-01-01

Metabolic syndrome (MetS) and type 2 diabetes mellitus (T2DM) are the serious public health problems worldwide. Moreover, it is estimated that MetS patients have about five-fold greater risk of the T2DM development compared with people without the syndrome. Peroxisome proliferator-activated receptors are a subgroup of the nuclear hormone receptor superfamily of ligand-activated transcription factors which play an important role in the pathogenesis of MetS and T2DM. All three members of the peroxisome proliferator-activated receptor (PPAR) nuclear receptor subfamily, PPARα, PPARβ/δ and PPARγ are critical in regulating insulin sensitivity, adipogenesis, lipid metabolism, and blood pressure. Recently, more and more studies indicated that the gene polymorphism of PPARs, such as Leu162Val and Val227Ala of PPARα, +294T > C of PPARβ/δ, Pro12Ala and C1431T of PPARγ, are significantly associated with the onset and progressing of MetS and T2DM in different population worldwide. Furthermore, a large body of evidence demonstrated that the glucose metabolism and lipid metabolism were influenced by gene-gene interaction among PPARs genes. However, given the complexity pathogenesis of metabolic disease, it is unlikely that genetic variation of a single locus would provide an adequate explanation of inter-individual differences which results in diverse clinical syndromes. Thus, gene-gene interactions and gene-environment interactions associated with T2DM and MetS need future comprehensive studies. PMID:25987964

Gestational Exposure to Bisphenol A Produces Transgenerational Changes in Behaviors and Gene Expression

PubMed Central

Wolstenholme, Jennifer T.; Edwards, Michelle; Shetty, Savera R. J.; Gatewood, Jessica D.; Taylor, Julia A.; Connelly, Jessica J.

2012-01-01

Bisphenol A (BPA) is a plasticizer and an endocrine-disrupting chemical. It is present in a variety of products used daily including food containers, paper, and dental sealants and is now widely detected in human urine and blood. Exposure to BPA during development may affect brain organization and behavior, perhaps as a consequence of its actions as a steroid hormone agonist/antagonist and/or an epigenetic modifier. Here we show that BPA produces transgenerational alterations in genes and behavior. Female mice received phytoestrogen-free chow with or without BPA before mating and throughout gestation. Plasma levels of BPA in supplemented dams were in a range similar to those measured in humans. Juveniles in the first generation exposed to BPA in utero displayed fewer social interactions as compared with control mice, whereas in later generations (F2 and F4), the effect of BPA was to increase these social interactions. Brains from embryos (embryonic d 18.5) exposed to BPA had lower gene transcript levels for several estrogen receptors, oxytocin, and vasopressin as compared with controls; decreased vasopressin mRNA persisted into the F4 generation, at which time oxytocin was also reduced but only in males. Thus, exposure to a low dose of BPA, only during gestation, has immediate and long-lasting, transgenerational effects on mRNA in brain and social behaviors. Heritable effects of an endocrine-disrupting chemical have implications for complex neurological diseases and highlight the importance of considering gene-environment interactions in the etiology of complex disease. PMID:22707478

Gene by Social-Context Interactions for Number of Sexual Partners Among White Male Youths: Genetics-informed Sociology

PubMed Central

Guo, Guang; Tong, Yuying; Cai, Tianji

2010-01-01

In this study, we set out to investigate whether introducing molecular genetic measures into an analysis of sexual partner variety will yield novel sociological insights. The data source is the white male DNA sample in the National Longitudinal Study of Adolescent Health. Our empirical analysis has produced a robust protective effect of the 9R/9R genotype relative to the Any10R genotype in the dopamine transporter gene (DAT1). The gene-environment interaction analysis demonstrates that the protective effect of 9R/9R tends to be lost in schools in which higher proportions of students start having sex early or among those with relatively low levels of cognitive ability. Our genetics-informed sociological analysis suggests that the “one size” of a single social theory may not fit all. Explaining a human trait or behavior may require a theory that accommodates the complex interplay between social contextual and individual influences and genetic predispositions. PMID:19569400

Cationic liposome/DNA complexes: from structure to interactions with cellular membranes.

PubMed

Caracciolo, Giulio; Amenitsch, Heinz

2012-10-01

Gene-based therapeutic approaches are based upon the concept that, if a disease is caused by a mutation in a gene, then adding back the wild-type gene should restore regular function and attenuate the disease phenotype. To deliver the gene of interest, both viral and nonviral vectors are used. Viruses are efficient, but their application is impeded by detrimental side-effects. Among nonviral vectors, cationic liposomes are the most promising candidates for gene delivery. They form stable complexes with polyanionic DNA (lipoplexes). Despite several advantages over viral vectors, the transfection efficiency (TE) of lipoplexes is too low compared with those of engineered viral vectors. This is due to lack of knowledge about the interactions between complexes and cellular components. Rational design of efficient lipoplexes therefore requires deeper comprehension of the interactions between the vector and the DNA as well as the cellular pathways and mechanisms involved. The importance of the lipoplex structure in biological function is revealed in the application of synchrotron small-angle X-ray scattering in combination with functional TE measurements. According to current understanding, the structure of lipoplexes can change upon interaction with cellular membranes and such changes affect the delivery efficiency. Recently, a correlation between the mechanism of gene release from complexes, the structure, and the physical and chemical parameters of the complexes has been established. Studies aimed at correlating structure and activity of lipoplexes are reviewed herein. This is a fundamental step towards rational design of highly efficient lipid gene vectors.

Meta genome-wide network from functional linkages of genes in human gut microbial ecosystems.

PubMed

Ji, Yan; Shi, Yixiang; Wang, Chuan; Dai, Jianliang; Li, Yixue

2013-03-01

The human gut microbial ecosystem (HGME) exerts an important influence on the human health. In recent researches, meta-genomics provided deep insights into the HGME in terms of gene contents, metabolic processes and genome constitutions of meta-genome. Here we present a novel methodology to investigate the HGME on the basis of a set of functionally coupled genes regardless of their genome origins when considering the co-evolution properties of genes. By analyzing these coupled genes, we showed some basic properties of HGME significantly associated with each other, and further constructed a protein interaction map of human gut meta-genome to discover some functional modules that may relate with essential metabolic processes. Compared with other studies, our method provides a new idea to extract basic function elements from meta-genome systems and investigate complex microbial environment by associating its biological traits with co-evolutionary fingerprints encoded in it.

Interaction of childhood urbanicity and variation in dopamine genes alters adult prefrontal function as measured by functional magnetic resonance imaging (fMRI).

PubMed

Reed, Jessica L; D'Ambrosio, Enrico; Marenco, Stefano; Ursini, Gianluca; Zheutlin, Amanda B; Blasi, Giuseppe; Spencer, Barbara E; Romano, Raffaella; Hochheiser, Jesse; Reifman, Ann; Sturm, Justin; Berman, Karen F; Bertolino, Alessandro; Weinberger, Daniel R; Callicott, Joseph H

2018-01-01

Brain phenotypes showing environmental influence may help clarify unexplained associations between urban exposure and psychiatric risk. Heritable prefrontal fMRI activation during working memory (WM) is such a phenotype. We hypothesized that urban upbringing (childhood urbanicity) would alter this phenotype and interact with dopamine genes that regulate prefrontal function during WM. Further, dopamine has been hypothesized to mediate urban-associated factors like social stress. WM-related prefrontal function was tested for main effects of urbanicity, main effects of three dopamine genes-catechol-O-methyltransferase (COMT), dopamine receptor D1 (DRD1), and dopamine receptor D2 (DRD2)-and, importantly, dopamine gene-by-urbanicity interactions. For COMT, three independent human samples were recruited (total n = 487). We also studied 253 subjects genotyped for DRD1 and DRD2. 3T fMRI activation during the N-back WM task was the dependent variable, while childhood urbanicity, dopamine genotype, and urbanicity-dopamine interactions were independent variables. Main effects of dopamine genes and of urbanicity were found. Individuals raised in an urban environment showed altered prefrontal activation relative to those raised in rural or town settings. For each gene, dopamine genotype-by-urbanicity interactions were shown in prefrontal cortex-COMT replicated twice in two independent samples. An urban childhood upbringing altered prefrontal function and interacted with each gene to alter genotype-phenotype relationships. Gene-environment interactions between multiple dopamine genes and urban upbringing suggest that neural effects of developmental environmental exposure could mediate, at least partially, increased risk for psychiatric illness in urban environments via dopamine genes expressed into adulthood.

Multiscale Modeling of Gene-Behavior Associations in an Artificial Neural Network Model of Cognitive Development.

PubMed

Thomas, Michael S C; Forrester, Neil A; Ronald, Angelica

2016-01-01

In the multidisciplinary field of developmental cognitive neuroscience, statistical associations between levels of description play an increasingly important role. One example of such associations is the observation of correlations between relatively common gene variants and individual differences in behavior. It is perhaps surprising that such associations can be detected despite the remoteness of these levels of description, and the fact that behavior is the outcome of an extended developmental process involving interaction of the whole organism with a variable environment. Given that they have been detected, how do such associations inform cognitive-level theories? To investigate this question, we employed a multiscale computational model of development, using a sample domain drawn from the field of language acquisition. The model comprised an artificial neural network model of past-tense acquisition trained using the backpropagation learning algorithm, extended to incorporate population modeling and genetic algorithms. It included five levels of description-four internal: genetic, network, neurocomputation, behavior; and one external: environment. Since the mechanistic assumptions of the model were known and its operation was relatively transparent, we could evaluate whether cross-level associations gave an accurate picture of causal processes. We established that associations could be detected between artificial genes and behavioral variation, even under polygenic assumptions of a many-to-one relationship between genes and neurocomputational parameters, and when an experience-dependent developmental process interceded between the action of genes and the emergence of behavior. We evaluated these associations with respect to their specificity (to different behaviors, to function vs. structure), to their developmental stability, and to their replicability, as well as considering issues of missing heritability and gene-environment interactions. We argue that gene-behavior associations can inform cognitive theory with respect to effect size, specificity, and timing. The model demonstrates a means by which researchers can undertake multiscale modeling with respect to cognition and develop highly specific and complex hypotheses across multiple levels of description. Copyright © 2015 Cognitive Science Society, Inc.

Gene-environment interaction study for BMI reveals interactions between genetic factors and physical activity, alcohol consumption and socioeconomic status

PubMed Central

Karlsson, Torgny; Ek, Weronica E.

2017-01-01

Previous genome-wide association studies (GWAS) have identified hundreds of genetic loci to be associated with body mass index (BMI) and risk of obesity. Genetic effects can differ between individuals depending on lifestyle or environmental factors due to gene-environment interactions. In this study, we examine gene-environment interactions in 362,496 unrelated participants with Caucasian ancestry from the UK Biobank resource. A total of 94 BMI-associated SNPs, selected from a previous GWAS on BMI, were used to construct weighted genetic scores for BMI (GSBMI). Linear regression modeling was used to estimate the effect of gene-environment interactions on BMI for 131 lifestyle factors related to: dietary habits, smoking and alcohol consumption, physical activity, socioeconomic status, mental health, sleeping patterns, as well as female-specific factors such as menopause and childbirth. In total, 15 lifestyle factors were observed to interact with GSBMI, of which alcohol intake frequency, usual walking pace, and Townsend deprivation index, a measure of socioeconomic status, were all highly significant (p = 1.45*10−29, p = 3.83*10−26, p = 4.66*10−11, respectively). Interestingly, the frequency of alcohol consumption, rather than the total weekly amount resulted in a significant interaction. The FTO locus was the strongest single locus interacting with any of the lifestyle factors. However, 13 significant interactions were also observed after omitting the FTO locus from the genetic score. Our analyses indicate that many lifestyle factors modify the genetic effects on BMI with some groups of individuals having more than double the effect of the genetic score. However, the underlying causal mechanisms of gene-environmental interactions are difficult to deduce from cross-sectional data alone and controlled experiments are required to fully characterise the causal factors. PMID:28873402

Chemical compounds from anthropogenic environment and immune evasion mechanisms: potential interactions

PubMed Central

Kravchenko, Julia; Corsini, Emanuela; Williams, Marc A.; Decker, William; Manjili, Masoud H.; Otsuki, Takemi; Singh, Neetu; Al-Mulla, Faha; Al-Temaimi, Rabeah; Amedei, Amedeo; Colacci, Anna Maria; Vaccari, Monica; Mondello, Chiara; Scovassi, A. Ivana; Raju, Jayadev; Hamid, Roslida A.; Memeo, Lorenzo; Forte, Stefano; Roy, Rabindra; Woodrick, Jordan; Salem, Hosni K.; Ryan, Elizabeth P.; Brown, Dustin G.; Lowe, Leroy; Lyerly, H.Kim

2015-01-01

An increasing number of studies suggest an important role of host immunity as a barrier to tumor formation and progression. Complex mechanisms and multiple pathways are involved in evading innate and adaptive immune responses, with a broad spectrum of chemicals displaying the potential to adversely influence immunosurveillance. The evaluation of the cumulative effects of low-dose exposures from the occupational and natural environment, especially if multiple chemicals target the same gene(s) or pathway(s), is a challenge. We reviewed common environmental chemicals and discussed their potential effects on immunosurveillance. Our overarching objective was to review related signaling pathways influencing immune surveillance such as the pathways involving PI3K/Akt, chemokines, TGF-β, FAK, IGF-1, HIF-1α, IL-6, IL-1α, CTLA-4 and PD-1/PDL-1 could individually or collectively impact immunosurveillance. A number of chemicals that are common in the anthropogenic environment such as fungicides (maneb, fluoxastrobin and pyroclostrobin), herbicides (atrazine), insecticides (pyridaben and azamethiphos), the components of personal care products (triclosan and bisphenol A) and diethylhexylphthalate with pathways critical to tumor immunosurveillance. At this time, these chemicals are not recognized as human carcinogens; however, it is known that they these chemicalscan simultaneously persist in the environment and appear to have some potential interfere with the host immune response, therefore potentially contributing to promotion interacting with of immune evasion mechanisms, and promoting subsequent tumor growth and progression. PMID:26002081

Therapeutic potential of Mediator complex subunits in metabolic diseases.

PubMed

Ranjan, Amol; Ansari, Suraiya A

2018-01-01

The multisubunit Mediator is an evolutionary conserved transcriptional coregulatory complex in eukaryotes. It is needed for the transcriptional regulation of gene expression in general as well as in a gene specific manner. Mediator complex subunits interact with different transcription factors as well as components of RNA Pol II transcription initiation complex and in doing so act as a bridge between gene specific transcription factors and general Pol II transcription machinery. Specific interaction of various Mediator subunits with nuclear receptors (NRs) and other transcription factors involved in metabolism has been reported in different studies. Evidences indicate that ligand-activated NRs recruit Mediator complex for RNA Pol II-dependent gene transcription. These NRs have been explored as therapeutic targets in different metabolic diseases; however, they show side-effects as targets due to their overlapping involvement in different signaling pathways. Here we discuss the interaction of various Mediator subunits with transcription factors involved in metabolism and whether specific interaction of these transcription factors with Mediator subunits could be potentially utilized as therapeutic strategy in a variety of metabolic diseases. Copyright © 2017 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM). All rights reserved.

Filtering Gene Ontology semantic similarity for identifying protein complexes in large protein interaction networks.

PubMed

Wang, Jian; Xie, Dong; Lin, Hongfei; Yang, Zhihao; Zhang, Yijia

2012-06-21

Many biological processes recognize in particular the importance of protein complexes, and various computational approaches have been developed to identify complexes from protein-protein interaction (PPI) networks. However, high false-positive rate of PPIs leads to challenging identification. A protein semantic similarity measure is proposed in this study, based on the ontology structure of Gene Ontology (GO) terms and GO annotations to estimate the reliability of interactions in PPI networks. Interaction pairs with low GO semantic similarity are removed from the network as unreliable interactions. Then, a cluster-expanding algorithm is used to detect complexes with core-attachment structure on filtered network. Our method is applied to three different yeast PPI networks. The effectiveness of our method is examined on two benchmark complex datasets. Experimental results show that our method performed better than other state-of-the-art approaches in most evaluation metrics. The method detects protein complexes from large scale PPI networks by filtering GO semantic similarity. Removing interactions with low GO similarity significantly improves the performance of complex identification. The expanding strategy is also effective to identify attachment proteins of complexes.

Genomic and Epigenomic Insights into Nutrition and Brain Disorders

PubMed Central

Dauncey, Margaret Joy

2013-01-01

Considerable evidence links many neuropsychiatric, neurodevelopmental and neurodegenerative disorders with multiple complex interactions between genetics and environmental factors such as nutrition. Mental health problems, autism, eating disorders, Alzheimer’s disease, schizophrenia, Parkinson’s disease and brain tumours are related to individual variability in numerous protein-coding and non-coding regions of the genome. However, genotype does not necessarily determine neurological phenotype because the epigenome modulates gene expression in response to endogenous and exogenous regulators, throughout the life-cycle. Studies using both genome-wide analysis of multiple genes and comprehensive analysis of specific genes are providing new insights into genetic and epigenetic mechanisms underlying nutrition and neuroscience. This review provides a critical evaluation of the following related areas: (1) recent advances in genomic and epigenomic technologies, and their relevance to brain disorders; (2) the emerging role of non-coding RNAs as key regulators of transcription, epigenetic processes and gene silencing; (3) novel approaches to nutrition, epigenetics and neuroscience; (4) gene-environment interactions, especially in the serotonergic system, as a paradigm of the multiple signalling pathways affected in neuropsychiatric and neurological disorders. Current and future advances in these four areas should contribute significantly to the prevention, amelioration and treatment of multiple devastating brain disorders. PMID:23503168

The Oxytocin Receptor Gene (OXTR) in Relation to State Levels of Loneliness in Adolescence: Evidence for Micro-Level Gene-Environment Interactions

PubMed Central

van Roekel, Eeske; Verhagen, Maaike; Scholte, Ron H. J.; Kleinjan, Marloes; Goossens, Luc; Engels, Rutger C. M. E.

2013-01-01

Previous research has shown that the rs53576 variant of the oxytocin receptor gene (OXTR) is associated with trait levels of loneliness, but results are inconsistent. The aim of the present study is to examine micro-level effects of the OXTR rs53576 variant on state levels of loneliness in early adolescents. In addition, gene-environment interactions are examined between this OXTR variant and positive and negative perceptions of company. Data were collected in 278 adolescents (58% girls), by means of the Experience Sampling Method (ESM). Sampling periods consisted of six days with nine assessments per day. A relation was found between the OXTR rs53576 variant and state loneliness, in girls only. Girls carrying an A allele had higher levels of state loneliness than girls carrying the GG genotype. In addition, adolescents with an A allele were more affected by negative perceptions of company than GG carriers, on weekend days only. No significant gene-environment interactions were found with positive company. Adolescents carrying an A allele were more susceptible to negative environments during weekend days than GG carriers. Our findings emphasize the importance of operationalizing the phenotype and the environment accurately. PMID:24223720

The oxytocin receptor gene (OXTR) in relation to state levels of loneliness in adolescence: evidence for micro-level gene-environment interactions.

PubMed

van Roekel, Eeske; Verhagen, Maaike; Scholte, Ron H J; Kleinjan, Marloes; Goossens, Luc; Engels, Rutger C M E

2013-01-01

Previous research has shown that the rs53576 variant of the oxytocin receptor gene (OXTR) is associated with trait levels of loneliness, but results are inconsistent. The aim of the present study is to examine micro-level effects of the OXTR rs53576 variant on state levels of loneliness in early adolescents. In addition, gene-environment interactions are examined between this OXTR variant and positive and negative perceptions of company. Data were collected in 278 adolescents (58% girls), by means of the Experience Sampling Method (ESM). Sampling periods consisted of six days with nine assessments per day. A relation was found between the OXTR rs53576 variant and state loneliness, in girls only. Girls carrying an A allele had higher levels of state loneliness than girls carrying the GG genotype. In addition, adolescents with an A allele were more affected by negative perceptions of company than GG carriers, on weekend days only. No significant gene-environment interactions were found with positive company. Adolescents carrying an A allele were more susceptible to negative environments during weekend days than GG carriers. Our findings emphasize the importance of operationalizing the phenotype and the environment accurately.

The Folate Pathway and Nonsyndromic Cleft Lip and Palate

PubMed Central

Blanton, Susan H.; Henry, Robin R.; Yuan, Quiping; Mulliken, John B.; Stal, Samuel; Finnell, Richard H.; Hecht, Jacqueline T.

2013-01-01

Nonsyndromic cleft lip with or without cleft palate (NSCLP) is a common birth malformation caused by genetic, environmental and gene-environment interactions. Periconceptional supplementation with folic acid, a key component in DNA synthesis and cell division, has reduced the birth prevalence of neural tube defects (NTDs) and may similarly reduce the birth prevalence of other complex birth defects including NSCLP. Past studies investigating the role of two common methylenetetrahydrofolate reductase (MTHFR) SNP polymorphisms, C677T (rs1801133) and A1298C (rs1801131), in NSCLP have produced conflicting results. Most studies of folate pathway genes have been limited in scope, as few genes/SNPs have been interrogated. In this study, we asked whether variations in a more comprehensive group of folate pathway genes were associated with NSCLP and, if so, were there detectable interactions between these genes and environmental exposures. In addition, we evaluated the data for a sex effect. Fourteen folate metabolism related genes were interrogated using eighty-nine SNPs in multiplex and simplex non-Hispanic White (NHW) (317) and Hispanic (128) NSCLP families. Evidence for a risk association between NSCLP and SNPs in nitrous oxide 3 (NOS3) and thymidylate synthetase (TYMS) was detected in the NHW group, whereas associations with methionine synthase (MTR), betaine-homocysteine methyltransferase (BHMT2), MTHFS and SLC19A1 were detected in the Hispanic group. Evidence for over-transmission of haplotypes and gene interactions in the methionine arm was detected. These results suggest that perturbations of the genes in the folate pathway may contribute to NSCLP. There was evidence for an interaction between several SNPs and maternal smoking, and for one SNP with sex of the offspring. These results provide support for other studies that suggest that high maternal homocysteine levels may contribute to NSCLP and should be further investigated. PMID:21254359

Map making in the 21st century: charting breast cancer susceptibility pathways in rodent models.

PubMed

Blackburn, Anneke C; Jerry, D Joseph

2011-04-01

Genetic factors play an important role in determining risk and resistance to increased breast cancer. Recent technological advances have made it possible to analyze hundreds of thousands of single nucleotide polymorphisms in large-scale association studies in humans and have resulted in identification of alleles in over 20 genes that influence breast cancer risk. Despite these advances, the challenge remains in identifying what the functional polymorphisms are that confer the increased risk, and how these genetic variants interact with each other and with environmental factors. In rodents, the incidence of mammary tumors varies among strains, such that they can provide alternate ideas for candidate pathways involved in humans. Mapping studies in animals have unearthed numerous loci for breast cancer susceptibility that have been validated in human populations. In a reciprocal manner, knockin and knockout mice have been used to validate the tumorigenicity of risk alleles found in population studies. Rodent studies also underscore the complexity of interactions among alleles. The fact that genes affecting risk and resistance to mammary tumors in rodents depend greatly upon the carcinogenic challenge emphasizes the importance of gene x environment interactions. The challenge to rodent geneticists now is to capitalize on the ability to control the genetics and environment in rodent models of tumorigenesis to better understand the biology of breast cancer development, to identify those polymorphisms most relevant to human susceptibility and to identify compensatory pathways that can be targeted for improved prevention in women at highest risk of developing breast cancer.

Simulating the yield impacts of organ-level quantitative trait loci associated with drought response in maize: a "gene-to-phenotype" modeling approach.

PubMed

Chenu, Karine; Chapman, Scott C; Tardieu, François; McLean, Greg; Welcker, Claude; Hammer, Graeme L

2009-12-01

Under drought, substantial genotype-environment (G x E) interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to our inability to account for the interplay of genetic controls, physiological traits, and environmental conditions throughout the crop cycle. We propose a modeling approach to bridge this "gene-to-phenotype" gap. For maize under drought, we simulated the impact of quantitative trait loci (QTL) controlling two key processes (leaf and silk elongation) that influence crop growth, water use, and grain yield. Substantial G x E interaction for yield was simulated for hypothetical recombinant inbred lines (RILs) across different seasonal patterns of drought. QTL that accelerated leaf elongation caused an increase in crop leaf area and yield in well-watered or preflowering water deficit conditions, but a reduction in yield under terminal stresses (as such "leafy" genotypes prematurely exhausted the water supply). The QTL impact on yield was substantially enhanced by including pleiotropic effects of these QTL on silk elongation and on consequent grain set. The simulations obtained illustrated the difficulty of interpreting the genetic control of yield for genotypes influenced only by the additive effects of QTL associated with leaf and silk growth. The results highlight the potential of integrative simulation modeling for gene-to-phenotype prediction and for exploiting G x E interactions for complex traits such as drought tolerance.

Tissue Architecture and Microenvironment Sustain Hormone Signaling | Center for Cancer Research

Cancer.gov

Cells interact with their environments in part through protein receptors embedded in the cell membrane. Activation of a receptor by external signaling molecules sets off a complex chain of events within the cell that can result in alterations in protein structure and function and/or changes in gene expression. Proper integration of these signals is crucial for normal cell growth and development. A more complete understanding of these normal processes will help elucidate how aberrant signaling results in diseases such as cancer.  

Metabolic characteristics of dominant microbes and key rare species from an acidic hot spring in Taiwan revealed by metagenomics

DOE PAGES

Lin, Kuei -Han; Liao, Ben -Yang; Chang, Hao -Wei; ...

2015-12-03

Microbial diversity and community structures in acidic hot springs have been characterized by 16S rRNA gene-based diversity surveys. However, our understanding regarding the interactions among microbes, or between microbes and environmental factors, remains limited. In the present study, a metagenomic approach, followed by bioinformatics analyses, were used to predict interactions within the microbial ecosystem in Shi-Huang-Ping (SHP), an acidic hot spring in northern Taiwan. Characterizing environmental parameters and potential metabolic pathways highlighted the importance of carbon assimilatory pathways. Four distinct carbon assimilatory pathways were identified in five dominant genera of bacteria. Of those dominant carbon fixers, Hydrogenobaculum bacteria outcompeted othermore » carbon assimilators and dominated the SHP, presumably due to their ability to metabolize hydrogen and to withstand an anaerobic environment with fluctuating temperatures. Furthermore, most dominant microbes were capable of metabolizing inorganic sulfur-related compounds (abundant in SHP). However, Acidithiobacillus ferrooxidans was the only species among key rare microbes with the capability to fix nitrogen, suggesting a key role in nitrogen cycling. In addition to potential metabolic interactions, based on the 16S rRNAs gene sequence of Nanoarchaeum-related and its potential host Ignicoccus-related archaea, as well as sequences of viruses and CRISPR arrays, we inferred that there were complex microbe-microbe interactions. In conclusion, our study provided evidence that there were numerous microbe-microbe and microbe-environment interactions within the microbial community in an acidic hot spring. We proposed that Hydrogenobaculum bacteria were the dominant microbial genus, as they were able to metabolize hydrogen, assimilate carbon and live in an anaerobic environment with fluctuating temperatures.« less

Metabolic characteristics of dominant microbes and key rare species from an acidic hot spring in Taiwan revealed by metagenomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Kuei -Han; Liao, Ben -Yang; Chang, Hao -Wei

Microbial diversity and community structures in acidic hot springs have been characterized by 16S rRNA gene-based diversity surveys. However, our understanding regarding the interactions among microbes, or between microbes and environmental factors, remains limited. In the present study, a metagenomic approach, followed by bioinformatics analyses, were used to predict interactions within the microbial ecosystem in Shi-Huang-Ping (SHP), an acidic hot spring in northern Taiwan. Characterizing environmental parameters and potential metabolic pathways highlighted the importance of carbon assimilatory pathways. Four distinct carbon assimilatory pathways were identified in five dominant genera of bacteria. Of those dominant carbon fixers, Hydrogenobaculum bacteria outcompeted othermore » carbon assimilators and dominated the SHP, presumably due to their ability to metabolize hydrogen and to withstand an anaerobic environment with fluctuating temperatures. Furthermore, most dominant microbes were capable of metabolizing inorganic sulfur-related compounds (abundant in SHP). However, Acidithiobacillus ferrooxidans was the only species among key rare microbes with the capability to fix nitrogen, suggesting a key role in nitrogen cycling. In addition to potential metabolic interactions, based on the 16S rRNAs gene sequence of Nanoarchaeum-related and its potential host Ignicoccus-related archaea, as well as sequences of viruses and CRISPR arrays, we inferred that there were complex microbe-microbe interactions. In conclusion, our study provided evidence that there were numerous microbe-microbe and microbe-environment interactions within the microbial community in an acidic hot spring. We proposed that Hydrogenobaculum bacteria were the dominant microbial genus, as they were able to metabolize hydrogen, assimilate carbon and live in an anaerobic environment with fluctuating temperatures.« less

The SET1 Complex Selects Actively Transcribed Target Genes via Multivalent Interaction with CpG Island Chromatin.

PubMed

Brown, David A; Di Cerbo, Vincenzo; Feldmann, Angelika; Ahn, Jaewoo; Ito, Shinsuke; Blackledge, Neil P; Nakayama, Manabu; McClellan, Michael; Dimitrova, Emilia; Turberfield, Anne H; Long, Hannah K; King, Hamish W; Kriaucionis, Skirmantas; Schermelleh, Lothar; Kutateladze, Tatiana G; Koseki, Haruhiko; Klose, Robert J

2017-09-05

Chromatin modifications and the promoter-associated epigenome are important for the regulation of gene expression. However, the mechanisms by which chromatin-modifying complexes are targeted to the appropriate gene promoters in vertebrates and how they influence gene expression have remained poorly defined. Here, using a combination of live-cell imaging and functional genomics, we discover that the vertebrate SET1 complex is targeted to actively transcribed gene promoters through CFP1, which engages in a form of multivalent chromatin reading that involves recognition of non-methylated DNA and histone H3 lysine 4 trimethylation (H3K4me3). CFP1 defines SET1 complex occupancy on chromatin, and its multivalent interactions are required for the SET1 complex to place H3K4me3. In the absence of CFP1, gene expression is perturbed, suggesting that normal targeting and function of the SET1 complex are central to creating an appropriately functioning vertebrate promoter-associated epigenome. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

A global evolutionary and metabolic analysis of human obesity gene risk variants.

PubMed

Castillo, Joseph J; Hazlett, Zachary S; Orlando, Robert A; Garver, William S

2017-09-05

It is generally accepted that the selection of gene variants during human evolution optimized energy metabolism that now interacts with our obesogenic environment to increase the prevalence of obesity. The purpose of this study was to perform a global evolutionary and metabolic analysis of human obesity gene risk variants (110 human obesity genes with 127 nearest gene risk variants) identified using genome-wide association studies (GWAS) to enhance our knowledge of early and late genotypes. As a result of determining the mean frequency of these obesity gene risk variants in 13 available populations from around the world our results provide evidence for the early selection of ancestral risk variants (defined as selection before migration from Africa) and late selection of derived risk variants (defined as selection after migration from Africa). Our results also provide novel information for association of these obesity genes or encoded proteins with diverse metabolic pathways and other human diseases. The overall results indicate a significant differential evolutionary pattern for the selection of obesity gene ancestral and derived risk variants proposed to optimize energy metabolism in varying global environments and complex association with metabolic pathways and other human diseases. These results are consistent with obesity genes that encode proteins possessing a fundamental role in maintaining energy metabolism and survival during the course of human evolution. Copyright © 2017. Published by Elsevier B.V.

Three Approaches to Modeling Gene-Environment Interactions in Longitudinal Family Data: Gene-Smoking Interactions in Blood Pressure.

PubMed

Basson, Jacob; Sung, Yun Ju; de Las Fuentes, Lisa; Schwander, Karen L; Vazquez, Ana; Rao, Dabeeru C

2016-01-01

Blood pressure (BP) has been shown to be substantially heritable, yet identified genetic variants explain only a small fraction of the heritability. Gene-smoking interactions have detected novel BP loci in cross-sectional family data. Longitudinal family data are available and have additional promise to identify BP loci. However, this type of data presents unique analysis challenges. Although several methods for analyzing longitudinal family data are available, which method is the most appropriate and under what conditions has not been fully studied. Using data from three clinic visits from the Framingham Heart Study, we performed association analysis accounting for gene-smoking interactions in BP at 31,203 markers on chromosome 22. We evaluated three different modeling frameworks: generalized estimating equations (GEE), hierarchical linear modeling, and pedigree-based mixed modeling. The three models performed somewhat comparably, with multiple overlaps in the most strongly associated loci from each model. Loci with the greatest significance were more strongly supported in the longitudinal analyses than in any of the component single-visit analyses. The pedigree-based mixed model was more conservative, with less inflation in the variant main effect and greater deflation in the gene-smoking interactions. The GEE, but not the other two models, resulted in substantial inflation in the tail of the distribution when variants with minor allele frequency <1% were included in the analysis. The choice of analysis method should depend on the model and the structure and complexity of the familial and longitudinal data. © 2015 WILEY PERIODICALS, INC.

Antioxidant Defense Enzyme Genes and Asthma Susceptibility: Gender-Specific Effects and Heterogeneity in Gene-Gene Interactions between Pathogenetic Variants of the Disease

PubMed Central

Polonikov, Alexey V.; Ivanov, Vladimir P.; Bogomazov, Alexey D.; Freidin, Maxim B.; Illig, Thomas; Solodilova, Maria A.

2014-01-01

Oxidative stress resulting from an increased amount of reactive oxygen species and an imbalance between oxidants and antioxidants plays an important role in the pathogenesis of asthma. The present study tested the hypothesis that genetic susceptibility to allergic and nonallergic variants of asthma is determined by complex interactions between genes encoding antioxidant defense enzymes (ADE). We carried out a comprehensive analysis of the associations between adult asthma and 46 single nucleotide polymorphisms of 34 ADE genes and 12 other candidate genes of asthma in Russian population using set association analysis and multifactor dimensionality reduction approaches. We found for the first time epistatic interactions between ADE genes underlying asthma susceptibility and the genetic heterogeneity between allergic and nonallergic variants of the disease. We identified GSR (glutathione reductase) and PON2 (paraoxonase 2) as novel candidate genes for asthma susceptibility. We observed gender-specific effects of ADE genes on the risk of asthma. The results of the study demonstrate complexity and diversity of interactions between genes involved in oxidative stress underlying susceptibility to allergic and nonallergic asthma. PMID:24895604

Major Gene for Field Stem Rust Resistance Co-Locates with Resistance Gene Sr12 in ‘Thatcher’ Wheat

PubMed Central

Hiebert, Colin W.; Kolmer, James A.; McCartney, Curt A.; Briggs, Jordan; Fetch, Tom; Bariana, Harbans; Choulet, Frederic; Rouse, Matthew N.; Spielmeyer, Wolfgang

2016-01-01

Stem rust, caused by Puccinia graminis (Pgt), is a damaging disease of wheat that can be controlled by utilizing effective stem rust resistance genes. ‘Thatcher’ wheat carries complex resistance to stem rust that is enhanced in the presence of the resistance gene Lr34. The purpose of this study was to examine APR in ‘Thatcher’ and look for genetic interactions with Lr34. A RIL population was tested for stem rust resistance in field nurseries in Canada, USA, and Kenya. BSA was used to find SNP markers associated with reduced stem rust severity. A major QTL was identified on chromosome 3BL near the centromere in all environments. Seedling testing showed that Sr12 mapped to the same region as the QTL for APR. The SNP markers were physically mapped and the region carrying the resistance was searched for sequences with homology to members of the NB-LRR resistance gene family. SNP marker from one NB-LRR-like sequence, NB-LRR3 co-segregated with Sr12. Two additional populations, including one that lacked Lr34, were tested in field nurseries. NB-LRR3 mapped near the maximum LOD for reduction in stem rust severity in both populations. Lines from a population that segregated for Sr12 and Lr34 were tested for seedling Pgt biomass and infection type, as well as APR to field stem rust which showed an interaction between the genes. We concluded that Sr12, or a gene closely linked to Sr12, was responsible for ‘Thatcher’-derived APR in several environments and this resistance was enhanced in the presence of Lr34. PMID:27309724

Major Gene for Field Stem Rust Resistance Co-Locates with Resistance Gene Sr12 in 'Thatcher' Wheat.

PubMed

Hiebert, Colin W; Kolmer, James A; McCartney, Curt A; Briggs, Jordan; Fetch, Tom; Bariana, Harbans; Choulet, Frederic; Rouse, Matthew N; Spielmeyer, Wolfgang

2016-01-01

Stem rust, caused by Puccinia graminis (Pgt), is a damaging disease of wheat that can be controlled by utilizing effective stem rust resistance genes. 'Thatcher' wheat carries complex resistance to stem rust that is enhanced in the presence of the resistance gene Lr34. The purpose of this study was to examine APR in 'Thatcher' and look for genetic interactions with Lr34. A RIL population was tested for stem rust resistance in field nurseries in Canada, USA, and Kenya. BSA was used to find SNP markers associated with reduced stem rust severity. A major QTL was identified on chromosome 3BL near the centromere in all environments. Seedling testing showed that Sr12 mapped to the same region as the QTL for APR. The SNP markers were physically mapped and the region carrying the resistance was searched for sequences with homology to members of the NB-LRR resistance gene family. SNP marker from one NB-LRR-like sequence, NB-LRR3 co-segregated with Sr12. Two additional populations, including one that lacked Lr34, were tested in field nurseries. NB-LRR3 mapped near the maximum LOD for reduction in stem rust severity in both populations. Lines from a population that segregated for Sr12 and Lr34 were tested for seedling Pgt biomass and infection type, as well as APR to field stem rust which showed an interaction between the genes. We concluded that Sr12, or a gene closely linked to Sr12, was responsible for 'Thatcher'-derived APR in several environments and this resistance was enhanced in the presence of Lr34.

Convergence of placenta biology and genetic risk for schizophrenia.

PubMed

Ursini, Gianluca; Punzi, Giovanna; Chen, Qiang; Marenco, Stefano; Robinson, Joshua F; Porcelli, Annamaria; Hamilton, Emily G; Mitjans, Marina; Maddalena, Giancarlo; Begemann, Martin; Seidel, Jan; Yanamori, Hidenaga; Jaffe, Andrew E; Berman, Karen F; Egan, Michael F; Straub, Richard E; Colantuoni, Carlo; Blasi, Giuseppe; Hashimoto, Ryota; Rujescu, Dan; Ehrenreich, Hannelore; Bertolino, Alessandro; Weinberger, Daniel R

2018-06-01

Defining the environmental context in which genes enhance disease susceptibility can provide insight into the pathogenesis of complex disorders. We report that the intra-uterine environment modulates the association of schizophrenia with genomic risk (in this study, genome-wide association study-derived polygenic risk scores (PRSs)). In independent samples from the United States, Italy, and Germany, the liability of schizophrenia explained by PRS is more than five times greater in the presence of early-life complications (ELCs) compared with their absence. Patients with ELC histories have significantly higher PRS than patients without ELC histories, which is confirmed in additional samples from Germany and Japan. The gene set composed of schizophrenia loci that interact with ELCs is highly expressed in placenta, is differentially expressed in placentae from complicated in comparison with normal pregnancies, and is differentially upregulated in placentae from male compared with female offspring. Pathway analyses reveal that genes driving the PRS-ELC interaction are involved in cellular stress response; genes that do not drive such interaction implicate orthogonal biological processes (for example, synaptic function). We conclude that a subset of the most significant genetic variants associated with schizophrenia converge on a developmental trajectory sensitive to events that affect the placental response to stress, which may offer insights into sex biases and primary prevention.

Complex Adaptive System Models and the Genetic Analysis of Plasma HDL-Cholesterol Concentration

PubMed Central

Rea, Thomas J.; Brown, Christine M.; Sing, Charles F.

2006-01-01

Despite remarkable advances in diagnosis and therapy, ischemic heart disease (IHD) remains a leading cause of morbidity and mortality in industrialized countries. Recent efforts to estimate the influence of genetic variation on IHD risk have focused on predicting individual plasma high-density lipoprotein cholesterol (HDL-C) concentration. Plasma HDL-C concentration (mg/dl), a quantitative risk factor for IHD, has a complex multifactorial etiology that involves the actions of many genes. Single gene variations may be necessary but are not individually sufficient to predict a statistically significant increase in risk of disease. The complexity of phenotype-genotype-environment relationships involved in determining plasma HDL-C concentration has challenged commonly held assumptions about genetic causation and has led to the question of which combination of variations, in which subset of genes, in which environmental strata of a particular population significantly improves our ability to predict high or low risk phenotypes. We document the limitations of inferences from genetic research based on commonly accepted biological models, consider how evidence for real-world dynamical interactions between HDL-C determinants challenges the simplifying assumptions implicit in traditional linear statistical genetic models, and conclude by considering research options for evaluating the utility of genetic information in predicting traits with complex etiologies. PMID:17146134

Peer Influence, Genetic Propensity, and Binge Drinking: A Natural Experiment and a Replication.

PubMed

Guo, Guang; Li, Yi; Wang, Hongyu; Cai, Tianji; Duncan, Greg J

2015-11-01

The authors draw data from the College Roommate Study (ROOM) and the National Longitudinal Study of Adolescent Health to investigate gene-environment interaction effects on youth binge drinking. In ROOM, the environmental influence was measured by the precollege drinking behavior of randomly assigned roommates. Random assignment safeguards against friend selection and removes the threat of gene-environment correlation that makes gene-environment interaction effects difficult to interpret. On average, being randomly assigned a drinking peer as opposed to a nondrinking peer increased college binge drinking by 0.5-1.0 episodes per month, or 20%-40% the average amount of binge drinking. However, this peer influence was found only among youths with a medium level of genetic propensity for alcohol use; those with either a low or high genetic propensity were not influenced by peer drinking. A replication of the findings is provided in data drawn from Add Health. The study shows that gene-environment interaction analysis can uncover social-contextual effects likely to be missed by traditional sociological approaches.

Unconditional analyses can increase efficiency in assessing gene-environment interaction of the case-combined-control design.

PubMed

Goldstein, Alisa M; Dondon, Marie-Gabrielle; Andrieu, Nadine

2006-08-01

A design combining both related and unrelated controls, named the case-combined-control design, was recently proposed to increase the power for detecting gene-environment (GxE) interaction. Under a conditional analytic approach, the case-combined-control design appeared to be more efficient and feasible than a classical case-control study for detecting interaction involving rare events. We now propose an unconditional analytic strategy to further increase the power for detecting gene-environment (GxE) interactions. This strategy allows the estimation of GxE interaction and exposure (E) main effects under certain assumptions (e.g. no correlation in E between siblings and the same exposure frequency in both control groups). Only the genetic (G) main effect cannot be estimated because it is biased. Using simulations, we show that unconditional logistic regression analysis is often more efficient than conditional analysis for detecting GxE interaction, particularly for a rare gene and strong effects. The unconditional analysis is also at least as efficient as the conditional analysis when the gene is common and the main and joint effects of E and G are small. Under the required assumptions, the unconditional analysis retains more information than does the conditional analysis for which only discordant case-control pairs are informative leading to more precise estimates of the odds ratios.

Exposure enriched outcome dependent designs for longitudinal studies of gene-environment interaction.

PubMed

Sun, Zhichao; Mukherjee, Bhramar; Estes, Jason P; Vokonas, Pantel S; Park, Sung Kyun

2017-08-15

Joint effects of genetic and environmental factors have been increasingly recognized in the development of many complex human diseases. Despite the popularity of case-control and case-only designs, longitudinal cohort studies that can capture time-varying outcome and exposure information have long been recommended for gene-environment (G × E) interactions. To date, literature on sampling designs for longitudinal studies of G × E interaction is quite limited. We therefore consider designs that can prioritize a subsample of the existing cohort for retrospective genotyping on the basis of currently available outcome, exposure, and covariate data. In this work, we propose stratified sampling based on summaries of individual exposures and outcome trajectories and develop a full conditional likelihood approach for estimation that adjusts for the biased sample. We compare the performance of our proposed design and analysis with combinations of different sampling designs and estimation approaches via simulation. We observe that the full conditional likelihood provides improved estimates for the G × E interaction and joint exposure effects over uncorrected complete-case analysis, and the exposure enriched outcome trajectory dependent design outperforms other designs in terms of estimation efficiency and power for detection of the G × E interaction. We also illustrate our design and analysis using data from the Normative Aging Study, an ongoing longitudinal cohort study initiated by the Veterans Administration in 1963. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Gene by Environment Interactions Influencing Reading Disability and the Inattentive Symptom Dimension of Attention Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Rosenberg, Jenni; Pennington, Bruce F.; Willcutt, Erik G.; Olson, Richard K.

2012-01-01

Background: Reading disability (RD) and attention deficit/hyperactivity disorder (ADHD) are comorbid and genetically correlated, especially the inattentive dimension of ADHD (ADHD-I). However, previous research indicates that RD and ADHD enter into opposite gene by environment (G x E) interactions. Methods: This study used behavioral genetic…

A kernel regression approach to gene-gene interaction detection for case-control studies.

PubMed

Larson, Nicholas B; Schaid, Daniel J

2013-11-01

Gene-gene interactions are increasingly being addressed as a potentially important contributor to the variability of complex traits. Consequently, attentions have moved beyond single locus analysis of association to more complex genetic models. Although several single-marker approaches toward interaction analysis have been developed, such methods suffer from very high testing dimensionality and do not take advantage of existing information, notably the definition of genes as functional units. Here, we propose a comprehensive family of gene-level score tests for identifying genetic elements of disease risk, in particular pairwise gene-gene interactions. Using kernel machine methods, we devise score-based variance component tests under a generalized linear mixed model framework. We conducted simulations based upon coalescent genetic models to evaluate the performance of our approach under a variety of disease models. These simulations indicate that our methods are generally higher powered than alternative gene-level approaches and at worst competitive with exhaustive SNP-level (where SNP is single-nucleotide polymorphism) analyses. Furthermore, we observe that simulated epistatic effects resulted in significant marginal testing results for the involved genes regardless of whether or not true main effects were present. We detail the benefits of our methods and discuss potential genome-wide analysis strategies for gene-gene interaction analysis in a case-control study design. © 2013 WILEY PERIODICALS, INC.

Alcoholism: a systems approach from molecular physiology to addictive behavior.

PubMed

Spanagel, Rainer

2009-04-01

Alcohol consumption is an integral part of daily life in many societies. The benefits associated with the production, sale, and use of alcoholic beverages come at an enormous cost to these societies. The World Health Organization ranks alcohol as one of the primary causes of the global burden of disease in industrialized countries. Alcohol-related diseases, especially alcoholism, are the result of cumulative responses to alcohol exposure, the genetic make-up of an individual, and the environmental perturbations over time. This complex gene x environment interaction, which has to be seen in a life-span perspective, leads to a large heterogeneity among alcohol-dependent patients, in terms of both the symptom dimensions and the severity of this disorder. Therefore, a reductionistic approach is not very practical if a better understanding of the pathological processes leading to an addictive behavior is to be achieved. Instead, a systems-oriented perspective in which the interactions and dynamics of all endogenous and environmental factors involved are centrally integrated, will lead to further progress in alcohol research. This review adheres to a systems biology perspective such that the interaction of alcohol with primary and secondary targets within the brain is described in relation to the behavioral consequences. As a result of the interaction of alcohol with these targets, alterations in gene expression and synaptic plasticity take place that lead to long-lasting alteration in neuronal network activity. As a subsequent consequence, alcohol-seeking responses ensue that can finally lead via complex environmental interactions to an addictive behavior.

Gene × Smoking Interactions on Human Brain Gene Expression: Finding Common Mechanisms in Adolescents and Adults

ERIC Educational Resources Information Center

Wolock, Samuel L.; Yates, Andrew; Petrill, Stephen A.; Bohland, Jason W.; Blair, Clancy; Li, Ning; Machiraju, Raghu; Huang, Kun; Bartlett, Christopher W.

2013-01-01

Background: Numerous studies have examined gene × environment interactions (G × E) in cognitive and behavioral domains. However, these studies have been limited in that they have not been able to directly assess differential patterns of gene expression in the human brain. Here, we assessed G × E interactions using two publically available datasets…

Genetic Interactions with Prenatal Social Environment: Effects on Academic and Behavioral Outcomes

ERIC Educational Resources Information Center

Conley, Dalton; Rauscher, Emily

2013-01-01

Numerous studies report gene-environment interactions, suggesting that specific alleles have different effects on social outcomes depending on environment. In all these studies, however, environmental conditions are potentially endogenous to unmeasured genetic characteristics. That is, it could be that the observed interaction effects actually…

A Partial Least Square Approach for Modeling Gene-gene and Gene-environment Interactions When Multiple Markers Are Genotyped

PubMed Central

Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C.

2008-01-01

Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense SNPs in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches: the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey’s 1-df model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women’s Health Initiative (WHI), this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with BMI. PMID:18615621

A partial least-square approach for modeling gene-gene and gene-environment interactions when multiple markers are genotyped.

PubMed

Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C

2009-01-01

Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense single nucleotype polymorphisms (SNPs) in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches, the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey's one-degree-of-freedom model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women's Health Initiative, this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with body mass index.

Functional Logistic Regression Approach to Detecting Gene by Longitudinal Environmental Exposure Interaction in a Case-Control Study

PubMed Central

Wei, Peng; Tang, Hongwei; Li, Donghui

2014-01-01

Most complex human diseases are likely the consequence of the joint actions of genetic and environmental factors. Identification of gene-environment (GxE) interactions not only contributes to a better understanding of the disease mechanisms, but also improves disease risk prediction and targeted intervention. In contrast to the large number of genetic susceptibility loci discovered by genome-wide association studies, there have been very few successes in identifying GxE interactions which may be partly due to limited statistical power and inaccurately measured exposures. While existing statistical methods only consider interactions between genes and static environmental exposures, many environmental/lifestyle factors, such as air pollution and diet, change over time, and cannot be accurately captured at one measurement time point or by simply categorizing into static exposure categories. There is a dearth of statistical methods for detecting gene by time-varying environmental exposure interactions. Here we propose a powerful functional logistic regression (FLR) approach to model the time-varying effect of longitudinal environmental exposure and its interaction with genetic factors on disease risk. Capitalizing on the powerful functional data analysis framework, our proposed FLR model is capable of accommodating longitudinal exposures measured at irregular time points and contaminated by measurement errors, commonly encountered in observational studies. We use extensive simulations to show that the proposed method can control the Type I error and is more powerful than alternative ad hoc methods. We demonstrate the utility of this new method using data from a case-control study of pancreatic cancer to identify the windows of vulnerability of lifetime body mass index on the risk of pancreatic cancer as well as genes which may modify this association. PMID:25219575

Functional logistic regression approach to detecting gene by longitudinal environmental exposure interaction in a case-control study.

PubMed

Wei, Peng; Tang, Hongwei; Li, Donghui

2014-11-01

Most complex human diseases are likely the consequence of the joint actions of genetic and environmental factors. Identification of gene-environment (G × E) interactions not only contributes to a better understanding of the disease mechanisms, but also improves disease risk prediction and targeted intervention. In contrast to the large number of genetic susceptibility loci discovered by genome-wide association studies, there have been very few successes in identifying G × E interactions, which may be partly due to limited statistical power and inaccurately measured exposures. Although existing statistical methods only consider interactions between genes and static environmental exposures, many environmental/lifestyle factors, such as air pollution and diet, change over time, and cannot be accurately captured at one measurement time point or by simply categorizing into static exposure categories. There is a dearth of statistical methods for detecting gene by time-varying environmental exposure interactions. Here, we propose a powerful functional logistic regression (FLR) approach to model the time-varying effect of longitudinal environmental exposure and its interaction with genetic factors on disease risk. Capitalizing on the powerful functional data analysis framework, our proposed FLR model is capable of accommodating longitudinal exposures measured at irregular time points and contaminated by measurement errors, commonly encountered in observational studies. We use extensive simulations to show that the proposed method can control the Type I error and is more powerful than alternative ad hoc methods. We demonstrate the utility of this new method using data from a case-control study of pancreatic cancer to identify the windows of vulnerability of lifetime body mass index on the risk of pancreatic cancer as well as genes that may modify this association. © 2014 Wiley Periodicals, Inc.

Oh, Behave! Behavior as an Interaction between Genes & the Environment

ERIC Educational Resources Information Center

Weigel, Emily G.; DeNieu, Michael; Gall, Andrew J.

2014-01-01

This lesson is designed to teach students that behavior is a trait shaped by both genes and the environment. Students will read a scientific paper, discuss and generate predictions based on the ideas and data therein, and model the relationships between genes, the environment, and behavior. The lesson is targeted to meet the educational goals of…

Global Mapping of the Yeast Genetic Interaction Network

NASA Astrophysics Data System (ADS)

Tong, Amy Hin Yan; Lesage, Guillaume; Bader, Gary D.; Ding, Huiming; Xu, Hong; Xin, Xiaofeng; Young, James; Berriz, Gabriel F.; Brost, Renee L.; Chang, Michael; Chen, YiQun; Cheng, Xin; Chua, Gordon; Friesen, Helena; Goldberg, Debra S.; Haynes, Jennifer; Humphries, Christine; He, Grace; Hussein, Shamiza; Ke, Lizhu; Krogan, Nevan; Li, Zhijian; Levinson, Joshua N.; Lu, Hong; Ménard, Patrice; Munyana, Christella; Parsons, Ainslie B.; Ryan, Owen; Tonikian, Raffi; Roberts, Tania; Sdicu, Anne-Marie; Shapiro, Jesse; Sheikh, Bilal; Suter, Bernhard; Wong, Sharyl L.; Zhang, Lan V.; Zhu, Hongwei; Burd, Christopher G.; Munro, Sean; Sander, Chris; Rine, Jasper; Greenblatt, Jack; Peter, Matthias; Bretscher, Anthony; Bell, Graham; Roth, Frederick P.; Brown, Grant W.; Andrews, Brenda; Bussey, Howard; Boone, Charles

2004-02-01

A genetic interaction network containing ~1000 genes and ~4000 interactions was mapped by crossing mutations in 132 different query genes into a set of ~4700 viable gene yeast deletion mutants and scoring the double mutant progeny for fitness defects. Network connectivity was predictive of function because interactions often occurred among functionally related genes, and similar patterns of interactions tended to identify components of the same pathway. The genetic network exhibited dense local neighborhoods; therefore, the position of a gene on a partially mapped network is predictive of other genetic interactions. Because digenic interactions are common in yeast, similar networks may underlie the complex genetics associated with inherited phenotypes in other organisms.

The free-energy cost of interaction between DNA loops.

PubMed

Huang, Lifang; Liu, Peijiang; Yuan, Zhanjiang; Zhou, Tianshou; Yu, Jianshe

2017-10-03

From the viewpoint of thermodynamics, the formation of DNA loops and the interaction between them, which are all non-equilibrium processes, result in the change of free energy, affecting gene expression and further cell-to-cell variability as observed experimentally. However, how these processes dissipate free energy remains largely unclear. Here, by analyzing a mechanic model that maps three fundamental topologies of two interacting DNA loops into a 4-state model of gene transcription, we first show that a longer DNA loop needs more mean free energy consumption. Then, independent of the type of interacting two DNA loops (nested, side-by-side or alternating), the promotion between them always consumes less mean free energy whereas the suppression dissipates more mean free energy. More interestingly, we find that in contrast to the mechanism of direct looping between promoter and enhancer, the facilitated-tracking mechanism dissipates less mean free energy but enhances the mean mRNA expression, justifying the facilitated-tracking hypothesis, a long-standing debate in biology. Based on minimal energy principle, we thus speculate that organisms would utilize the mechanisms of loop-loop promotion and facilitated tracking to survive in complex environments. Our studies provide insights into the understanding of gene expression regulation mechanism from the view of energy consumption.

[Nutritional genomics: an approach to the genome-environment interaction].

PubMed

Xacur-García, Fiona; Castillo-Quan, Jorge I; Hernández-Escalante, Víctor M; Laviada-Molina, Hugo

2008-11-01

Nutritional genomics forms part of the genomic sciences and addresses the interaction between genes and the human diet, its influence on metabolism and subsequent susceptibility to develop common diseases. It encompasses both nutrigenomics, which explores the effects of nutrients on the genome, proteome and metabolome; and nutrigenetics, that explores the effects of genetic variations on the diet/disease interaction. A number of mechanisms drive the gene/diet interaction: elements in the diet can act as links for transcription factor receptors and after intermediary concentrations, thereby modifying chromatin and impacting genetic regulation; affect signal pathways, regulating phosphorylation of tyrosine in receptors; decrease signaling through the inositol pathway; and act through epigenetic mechanisms, silencing DNA fragments by methylation of cytosine. The signals generated by polyunsaturated fatty acids are so powerful that they can even bypass insulin mediated lipogenesis, stimulated by carbohydrates. Some fatty acids modify the expression of genes that participate in fatty acid transport by lipoproteins. Nutritional genomics has myriad possible therapeutic and preventive applications: in patients with enzymatic deficiencies; in those with a genetic predisposition to complex diseases such as dyslipidemia, diabetes and cancer; in those that already suffer these diseases; in those with altered mood or memory; during the aging process; in pregnant women; and as a preventive measure in the healthy population.

[The role of genotype in the intergenerational transmission of experiences of childhood adversity].

PubMed

Reichl, Corinna; Kaess, Michael; Resch, Franz; Brunner, Romuald

2014-09-01

The prevalence of childhood abuse and maltreatment is estimated to lie at about 15% in the overall German population. Previous research suggested that about one third of all individuals who had experienced childhood adversity subsequently maltreated their own children or responded insensitively to their children's needs. Empirical studies imply that interindividual differences in the responsiveness to childhood adversity can partially be explained by gene-environment interactions. This article discusses the potential interplay of genes and environment in the context of transmitting maltreating behavior and (in)sensitive parenting against the background of current challenges in genetic research. Selected studies on gene × environment interactions are presented and relevant gene polymorphisms are identified. Overall, previous studies reported interactions between polymorphisms of the serotonergic, dopaminergic, oxytocin-related, and arginine vasopressin-related systems and childhood experiences of care and abuse in the prediction of social behaviors during mother-child interactions. The results indicate a differential susceptibility toward both negative and positive environments which is dependent on genetic characteristics. Future research should thus investigate the effects of children's presumed risk gene variants toward negative as well as positive parenting. This could contribute to a deeper understanding of the underlying mechanisms of the intergenerational transmission of abusive and beneficial parenting behavior and help to avoid false stigmatizations.

Detecting regulatory gene-environment interactions with unmeasured environmental factors.

PubMed

Fusi, Nicoló; Lippert, Christoph; Borgwardt, Karsten; Lawrence, Neil D; Stegle, Oliver

2013-06-01

Genomic studies have revealed a substantial heritable component of the transcriptional state of the cell. To fully understand the genetic regulation of gene expression variability, it is important to study the effect of genotype in the context of external factors such as alternative environmental conditions. In model systems, explicit environmental perturbations have been considered for this purpose, allowing to directly test for environment-specific genetic effects. However, such experiments are limited to species that can be profiled in controlled environments, hampering their use in important systems such as human. Moreover, even in seemingly tightly regulated experimental conditions, subtle environmental perturbations cannot be ruled out, and hence unknown environmental influences are frequent. Here, we propose a model-based approach to simultaneously infer unmeasured environmental factors from gene expression profiles and use them in genetic analyses, identifying environment-specific associations between polymorphic loci and individual gene expression traits. In extensive simulation studies, we show that our method is able to accurately reconstruct environmental factors and their interactions with genotype in a variety of settings. We further illustrate the use of our model in a real-world dataset in which one environmental factor has been explicitly experimentally controlled. Our method is able to accurately reconstruct the true underlying environmental factor even if it is not given as an input, allowing to detect genuine genotype-environment interactions. In addition to the known environmental factor, we find unmeasured factors involved in novel genotype-environment interactions. Our results suggest that interactions with both known and unknown environmental factors significantly contribute to gene expression variability. and implementation: Software available at http://pmbio.github.io/envGPLVM/. Supplementary data are available at Bioinformatics online.

Childhood quality influences genetic sensitivity to environmental influences across adulthood: A life-course Gene × Environment interaction study.

PubMed

Keers, Robert; Pluess, Michael

2017-12-01

While environmental adversity has been shown to increase risk for psychopathology, individuals differ in their sensitivity to these effects. Both genes and childhood experiences are thought to influence sensitivity to the environment, and these factors may operate synergistically such that the effects of childhood experiences on later sensitivity are greater in individuals who are more genetically sensitive. In line with this hypothesis, several recent studies have reported a significant three-way interaction (Gene × Environment × Environment) between two candidate genes and childhood and adult environment on adult psychopathology. We aimed to replicate and extend these findings in a large, prospective multiwave longitudinal study using a polygenic score of environmental sensitivity and objectively measured childhood and adult material environmental quality. We found evidence for both Environment × Environment and Gene × Environment × Environment effects on psychological distress. Children with a poor-quality material environment were more sensitive to the negative effects of a poor environment as adults, reporting significantly higher psychological distress scores. These effects were further moderated by a polygenic score of environmental sensitivity. Genetically sensitive children were more vulnerable to adversity as adults, if they had experienced a poor childhood environment but were significantly less vulnerable if their childhood environment was positive. These findings are in line with the differential susceptibility hypothesis and suggest that a life course approach is necessary to elucidate the role of Gene × Environment in the development of mental illnesses.

Commentary: Gene-Environment Interplay in the Context of Genetics, Epigenetics, and Gene Expression.

ERIC Educational Resources Information Center

Kramer, Douglas A.

2005-01-01

Objective: To comment on the article in this issue of the Journal by Professor Michael Rutter, "Environmentally Mediated Risks for Psychopathology: Research Strategies and Findings," in the context of current research findings on gene-environment interaction, epigenetics, and gene expression. Method: Animal and human studies are reviewed that…

Genetic control of root growth: from genes to networks

PubMed Central

Slovak, Radka; Ogura, Takehiko; Satbhai, Santosh B.; Ristova, Daniela; Busch, Wolfgang

2016-01-01

Background Roots are essential organs for higher plants. They provide the plant with nutrients and water, anchor the plant in the soil, and can serve as energy storage organs. One remarkable feature of roots is that they are able to adjust their growth to changing environments. This adjustment is possible through mechanisms that modulate a diverse set of root traits such as growth rate, diameter, growth direction and lateral root formation. The basis of these traits and their modulation are at the cellular level, where a multitude of genes and gene networks precisely regulate development in time and space and tune it to environmental conditions. Scope This review first describes the root system and then presents fundamental work that has shed light on the basic regulatory principles of root growth and development. It then considers emerging complexities and how they have been addressed using systems-biology approaches, and then describes and argues for a systems-genetics approach. For reasons of simplicity and conciseness, this review is mostly limited to work from the model plant Arabidopsis thaliana, in which much of the research in root growth regulation at the molecular level has been conducted. Conclusions While forward genetic approaches have identified key regulators and genetic pathways, systems-biology approaches have been successful in shedding light on complex biological processes, for instance molecular mechanisms involving the quantitative interaction of several molecular components, or the interaction of large numbers of genes. However, there are significant limitations in many of these methods for capturing dynamic processes, as well as relating these processes to genotypic and phenotypic variation. The emerging field of systems genetics promises to overcome some of these limitations by linking genotypes to complex phenotypic and molecular data using approaches from different fields, such as genetics, genomics, systems biology and phenomics. PMID:26558398

Have studies of the developmental regulation of behavioral phenotypes revealed the mechanisms of gene-environment interactions?

PubMed Central

Hall, F. Scott; Perona, Maria T. G.

2012-01-01

This review addresses the recent convergence of our long-standing knowledge of the regulation of behavioral phenotypes by developmental experience with recent advances in our understanding of mechanisms regulating gene expression. This review supports a particular perspective on the developmental regulation of behavioral phenotypes: That the role of common developmental experiences (e.g. maternal interactions, peer interactions, exposure to a complex environment, etc.) is to fit individuals to the circumstances of their lives within bounds determined by long-standing (evolutionary) mechanisms that have shaped responses to critical and fundamental types of experience via those aspects of gene structure that regulate gene expression. The phenotype of a given species is not absolute for a given genotype but rather variable within bounds that are determined by mechanisms regulated by experience (e.g. epigenetic mechanisms). This phenotypic variation is not necessarily random, or evenly distributed along a continuum of description or measurement, but often highly disjointed, producing distinct, even opposing, phenotypes. The potentiality for these varying phenotypes is itself the product of evolution, the potential for alternative phenotypes itself conveying evolutionary advantage. Examples of such phenotypic variation, resulting from environmental or experiential influences, have a long history of study in neurobiology, and a number of these will be discussed in this review: neurodevelopmental experiences that produce phenotypic variation in visual perception, cognitive function, and emotional behavior. Although other examples will be discussed, particular emphasis will be made on the role of social behavior on neurodevelopment and phenotypic determination. It will be argued that an important purpose of some aspects of social behavior is regulation of neurobehavioral phenotypes by experience via genetic regulatory mechanisms. PMID:22643448

Genes under weaker stabilizing selection increase network evolvability and rapid regulatory adaptation to an environmental shift.

PubMed

Laarits, T; Bordalo, P; Lemos, B

2016-08-01

Regulatory networks play a central role in the modulation of gene expression, the control of cellular differentiation, and the emergence of complex phenotypes. Regulatory networks could constrain or facilitate evolutionary adaptation in gene expression levels. Here, we model the adaptation of regulatory networks and gene expression levels to a shift in the environment that alters the optimal expression level of a single gene. Our analyses show signatures of natural selection on regulatory networks that both constrain and facilitate rapid evolution of gene expression level towards new optima. The analyses are interpreted from the standpoint of neutral expectations and illustrate the challenge to making inferences about network adaptation. Furthermore, we examine the consequence of variable stabilizing selection across genes on the strength and direction of interactions in regulatory networks and in their subsequent adaptation. We observe that directional selection on a highly constrained gene previously under strong stabilizing selection was more efficient when the gene was embedded within a network of partners under relaxed stabilizing selection pressure. The observation leads to the expectation that evolutionarily resilient regulatory networks will contain optimal ratios of genes whose expression is under weak and strong stabilizing selection. Altogether, our results suggest that the variable strengths of stabilizing selection across genes within regulatory networks might itself contribute to the long-term adaptation of complex phenotypes. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Meta-analysis of gene–environment-wide association scans accounting for education level identifies additional loci for refractive error

PubMed Central

Fan, Qiao; Verhoeven, Virginie J. M.; Wojciechowski, Robert; Barathi, Veluchamy A.; Hysi, Pirro G.; Guggenheim, Jeremy A.; Höhn, René; Vitart, Veronique; Khawaja, Anthony P.; Yamashiro, Kenji; Hosseini, S Mohsen; Lehtimäki, Terho; Lu, Yi; Haller, Toomas; Xie, Jing; Delcourt, Cécile; Pirastu, Mario; Wedenoja, Juho; Gharahkhani, Puya; Venturini, Cristina; Miyake, Masahiro; Hewitt, Alex W.; Guo, Xiaobo; Mazur, Johanna; Huffman, Jenifer E.; Williams, Katie M.; Polasek, Ozren; Campbell, Harry; Rudan, Igor; Vatavuk, Zoran; Wilson, James F.; Joshi, Peter K.; McMahon, George; St Pourcain, Beate; Evans, David M.; Simpson, Claire L.; Schwantes-An, Tae-Hwi; Igo, Robert P.; Mirshahi, Alireza; Cougnard-Gregoire, Audrey; Bellenguez, Céline; Blettner, Maria; Raitakari, Olli; Kähönen, Mika; Seppala, Ilkka; Zeller, Tanja; Meitinger, Thomas; Ried, Janina S.; Gieger, Christian; Portas, Laura; van Leeuwen, Elisabeth M.; Amin, Najaf; Uitterlinden, André G.; Rivadeneira, Fernando; Hofman, Albert; Vingerling, Johannes R.; Wang, Ya Xing; Wang, Xu; Tai-Hui Boh, Eileen; Ikram, M. Kamran; Sabanayagam, Charumathi; Gupta, Preeti; Tan, Vincent; Zhou, Lei; Ho, Candice E. H.; Lim, Wan'e; Beuerman, Roger W.; Siantar, Rosalynn; Tai, E-Shyong; Vithana, Eranga; Mihailov, Evelin; Khor, Chiea-Chuen; Hayward, Caroline; Luben, Robert N.; Foster, Paul J.; Klein, Barbara E. K.; Klein, Ronald; Wong, Hoi-Suen; Mitchell, Paul; Metspalu, Andres; Aung, Tin; Young, Terri L.; He, Mingguang; Pärssinen, Olavi; van Duijn, Cornelia M.; Jin Wang, Jie; Williams, Cathy; Jonas, Jost B.; Teo, Yik-Ying; Mackey, David A.; Oexle, Konrad; Yoshimura, Nagahisa; Paterson, Andrew D.; Pfeiffer, Norbert; Wong, Tien-Yin; Baird, Paul N.; Stambolian, Dwight; Wilson, Joan E. Bailey; Cheng, Ching-Yu; Hammond, Christopher J.; Klaver, Caroline C. W.; Saw, Seang-Mei; Rahi, Jugnoo S.; Korobelnik, Jean-François; Kemp, John P.; Timpson, Nicholas J.; Smith, George Davey; Craig, Jamie E.; Burdon, Kathryn P.; Fogarty, Rhys D.; Iyengar, Sudha K.; Chew, Emily; Janmahasatian, Sarayut; Martin, Nicholas G.; MacGregor, Stuart; Xu, Liang; Schache, Maria; Nangia, Vinay; Panda-Jonas, Songhomitra; Wright, Alan F.; Fondran, Jeremy R.; Lass, Jonathan H.; Feng, Sheng; Zhao, Jing Hua; Khaw, Kay-Tee; Wareham, Nick J.; Rantanen, Taina; Kaprio, Jaakko; Pang, Chi Pui; Chen, Li Jia; Tam, Pancy O.; Jhanji, Vishal; Young, Alvin L.; Döring, Angela; Raffel, Leslie J.; Cotch, Mary-Frances; Li, Xiaohui; Yip, Shea Ping; Yap, Maurice K.H.; Biino, Ginevra; Vaccargiu, Simona; Fossarello, Maurizio; Fleck, Brian; Yazar, Seyhan; Tideman, Jan Willem L.; Tedja, Milly; Deangelis, Margaret M.; Morrison, Margaux; Farrer, Lindsay; Zhou, Xiangtian; Chen, Wei; Mizuki, Nobuhisa; Meguro, Akira; Mäkelä, Kari Matti

2016-01-01

Myopia is the most common human eye disorder and it results from complex genetic and environmental causes. The rapidly increasing prevalence of myopia poses a major public health challenge. Here, the CREAM consortium performs a joint meta-analysis to test single-nucleotide polymorphism (SNP) main effects and SNP × education interaction effects on refractive error in 40,036 adults from 25 studies of European ancestry and 10,315 adults from 9 studies of Asian ancestry. In European ancestry individuals, we identify six novel loci (FAM150B-ACP1, LINC00340, FBN1, DIS3L-MAP2K1, ARID2-SNAT1 and SLC14A2) associated with refractive error. In Asian populations, three genome-wide significant loci AREG, GABRR1 and PDE10A also exhibit strong interactions with education (P<8.5 × 10−5), whereas the interactions are less evident in Europeans. The discovery of these loci represents an important advance in understanding how gene and environment interactions contribute to the heterogeneity of myopia. PMID:27020472

Topographical mapping of α- and β-keratins on developing chicken skin integuments: Functional interaction and evolutionary perspectives

PubMed Central

Wu, Ping; Ng, Chen Siang; Yan, Jie; Lai, Yung-Chih; Chen, Chih-Kuan; Lai, Yu-Ting; Wu, Siao-Man; Chen, Jiun-Jie; Luo, Weiqi; Widelitz, Randall B.; Li, Wen-Hsiung; Chuong, Cheng-Ming

2015-01-01

Avian integumentary organs include feathers, scales, claws, and beaks. They cover the body surface and play various functions to help adapt birds to diverse environments. These keratinized structures are mainly composed of corneous materials made of α-keratins, which exist in all vertebrates, and β-keratins, which only exist in birds and reptiles. Here, members of the keratin gene families were used to study how gene family evolution contributes to novelty and adaptation, focusing on tissue morphogenesis. Using chicken as a model, we applied RNA-seq and in situ hybridization to map α- and β-keratin genes in various skin appendages at embryonic developmental stages. The data demonstrate that temporal and spatial α- and β-keratin expression is involved in establishing the diversity of skin appendage phenotypes. Embryonic feathers express a higher proportion of β-keratin genes than other skin regions. In feather filament morphogenesis, β-keratins show intricate complexity in diverse substructures of feather branches. To explore functional interactions, we used a retrovirus transgenic system to ectopically express mutant α- or antisense β-keratin forms. α- and β-keratins show mutual dependence and mutations in either keratin type results in disrupted keratin networks and failure to form proper feather branches. Our data suggest that combinations of α- and β-keratin genes contribute to the morphological and structural diversity of different avian skin appendages, with feather-β-keratins conferring more possible composites in building intrafeather architecture complexity, setting up a platform of morphological evolution of functional forms in feathers. PMID:26598683

Gene-Environment Interaction in Externalizing Problems among Adolescents: Evidence from the Pelotas 1993 Birth Cohort Study

ERIC Educational Resources Information Center

Kieling, Christian; Hutz, Mara H.; Genro, Julia P.; Polanczyk, Guilherme V.; Anselmi, Luciana; Camey, Suzi; Hallal, Pedro C.; Barros, Fernando C.; Victora, Cesar G.; Menezes, Ana M. B.; Rohde, Luis Augusto

2013-01-01

Background: The study of gene-environment interactions (G by E) is one of the most promising strategies to uncover the origins of mental disorders. Replication of initial findings, however, is essential because there is a strong possibility of publication bias in the literature. In addition, there is a scarcity of research on the topic originated…

How Gene-Environment Interaction Affects Children's Anxious and Fearful Behavior. Science Briefs

ERIC Educational Resources Information Center

National Scientific Council on the Developing Child, 2007

2007-01-01

"Science Briefs" summarize the findings and implications of a recent study in basic science or clinical research. This brief reports on the study "Evidence for a Gene-Environment Interaction in Predicting Behavioral Inhibition in Middle Childhood" (N. A. Fox, K E. Nichols, H. A. Henderson, K. Rubin, L. Schmidt, D. Hamer, M. Ernst, and D. S.…

Genome Dynamics in Legionella: The Basis of Versatility and Adaptation to Intracellular Replication

PubMed Central

Gomez-Valero, Laura; Buchrieser, Carmen

2013-01-01

Legionella pneumophila is a bacterial pathogen present in aquatic environments that can cause a severe pneumonia called Legionnaires’ disease. Soon after its recognition, it was shown that Legionella replicates inside amoeba, suggesting that bacteria replicating in environmental protozoa are able to exploit conserved signaling pathways in human phagocytic cells. Comparative, evolutionary, and functional genomics suggests that the Legionella–amoeba interaction has shaped this pathogen more than previously thought. A complex evolutionary scenario involving mobile genetic elements, type IV secretion systems, and horizontal gene transfer among Legionella, amoeba, and other organisms seems to take place. This long-lasting coevolution led to the development of very sophisticated virulence strategies and a high level of temporal and spatial fine-tuning of bacteria host–cell interactions. We will discuss current knowledge of the evolution of virulence of Legionella from a genomics perspective and propose our vision of the emergence of this human pathogen from the environment. PMID:23732852

Genome dynamics in Legionella: the basis of versatility and adaptation to intracellular replication.

PubMed

Gomez-Valero, Laura; Buchrieser, Carmen

2013-06-01

Legionella pneumophila is a bacterial pathogen present in aquatic environments that can cause a severe pneumonia called Legionnaires' disease. Soon after its recognition, it was shown that Legionella replicates inside amoeba, suggesting that bacteria replicating in environmental protozoa are able to exploit conserved signaling pathways in human phagocytic cells. Comparative, evolutionary, and functional genomics suggests that the Legionella-amoeba interaction has shaped this pathogen more than previously thought. A complex evolutionary scenario involving mobile genetic elements, type IV secretion systems, and horizontal gene transfer among Legionella, amoeba, and other organisms seems to take place. This long-lasting coevolution led to the development of very sophisticated virulence strategies and a high level of temporal and spatial fine-tuning of bacteria host-cell interactions. We will discuss current knowledge of the evolution of virulence of Legionella from a genomics perspective and propose our vision of the emergence of this human pathogen from the environment.

The maternal environment interacts with genetic variation in regulating seed dormancy in Swedish Arabidopsis thaliana

PubMed Central

Nordborg, Magnus

2017-01-01

Seed dormancy is a complex adaptive trait that controls the timing of seed germination, one of the major fitness components in many plant species. Despite being highly heritable, seed dormancy is extremely plastic and influenced by a wide range of environmental cues. Here, using a set of 92 Arabidopsis thaliana lines from Sweden, we investigate the effect of seed maturation temperature on dormancy variation at the population level. The response to temperature differs dramatically between lines, demonstrating that genotype and the maternal environment interact in controlling the trait. By performing a genome-wide association study (GWAS), we identified several candidate genes that could presumably account for this plasticity, two of which are involved in the photoinduction of germination. Altogether, our results provide insight into both the molecular mechanisms and the evolution of dormancy plasticity, and can serve to improve our understanding of environmentally dependent life-history transitions. PMID:29281703

Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases.

PubMed

Berger, Seth I; Posner, Jeremy M; Ma'ayan, Avi

2007-10-04

In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP), generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

Research Review: Gene-Environment Interaction Research in Youth Depression--A Systematic Review with Recommendations for Future Research

ERIC Educational Resources Information Center

Dunn, Erin C.; Uddin, Monica; Subramanian, S. V.; Smoller, Jordan W.; Galea, Sandro; Koenen, Karestan C.

2011-01-01

Background: Depression is a major public health problem among youth, currently estimated to affect as many as 9% of US children and adolescents. The recognition that both genes (nature) and environments (nurture) are important for understanding the etiology of depression has led to a rapid growth in research exploring gene-environment interactions…

Root Systems Biology: Integrative Modeling across Scales, from Gene Regulatory Networks to the Rhizosphere1

PubMed Central

Hill, Kristine; Porco, Silvana; Lobet, Guillaume; Zappala, Susan; Mooney, Sacha; Draye, Xavier; Bennett, Malcolm J.

2013-01-01

Genetic and genomic approaches in model organisms have advanced our understanding of root biology over the last decade. Recently, however, systems biology and modeling have emerged as important approaches, as our understanding of root regulatory pathways has become more complex and interpreting pathway outputs has become less intuitive. To relate root genotype to phenotype, we must move beyond the examination of interactions at the genetic network scale and employ multiscale modeling approaches to predict emergent properties at the tissue, organ, organism, and rhizosphere scales. Understanding the underlying biological mechanisms and the complex interplay between systems at these different scales requires an integrative approach. Here, we describe examples of such approaches and discuss the merits of developing models to span multiple scales, from network to population levels, and to address dynamic interactions between plants and their environment. PMID:24143806

The Homeodomain of PDX-1 Mediates Multiple Protein-Protein Interactions in the Formation of a Transcriptional Activation Complex on the Insulin Promoter

PubMed Central

Ohneda, Kinuko; Mirmira, Raghavendra G.; Wang, Juehu; Johnson, Jeffrey D.; German, Michael S.

2000-01-01

Activation of insulin gene transcription specifically in the pancreatic β cells depends on multiple nuclear proteins that interact with each other and with sequences on the insulin gene promoter to build a transcriptional activation complex. The homeodomain protein PDX-1 exemplifies such interactions by binding to the A3/4 region of the rat insulin I promoter and activating insulin gene transcription by cooperating with the basic-helix-loop-helix (bHLH) protein E47/Pan1, which binds to the adjacent E2 site. The present study provides evidence that the homeodomain of PDX-1 acts as a protein-protein interaction domain to recruit multiple proteins, including E47/Pan1, BETA2/NeuroD1, and high-mobility group protein I(Y), to an activation complex on the E2A3/4 minienhancer. The transcriptional activity of this complex results from the clustering of multiple activation domains capable of interacting with coactivators and the basal transcriptional machinery. These interactions are not common to all homeodomain proteins: the LIM homeodomain protein Lmx1.1 can also activate the E2A3/4 minienhancer in cooperation with E47/Pan1 but does so through different interactions. Cooperation between Lmx1.1 and E47/Pan1 results not only in the aggregation of multiple activation domains but also in the unmasking of a potent activation domain on E47/Pan1 that is normally silent in non-β cells. While more than one activation complex may be capable of activating insulin gene transcription through the E2A3/4 minienhancer, each is dependent on multiple specific interactions among a unique set of nuclear proteins. PMID:10629047

Refining the Candidate Environment: Interpersonal Stress, the Serotonin Transporter Polymorphism, and Gene-Environment Interactions in Major Depression.

PubMed

Vrshek-Schallhorn, Suzanne; Mineka, Susan; Zinbarg, Richard E; Craske, Michelle G; Griffith, James W; Sutton, Jonathan; Redei, Eva E; Wolitzky-Taylor, Kate; Hammen, Constance; Adam, Emma K

2014-05-01

Meta-analytic evidence supports a gene-environment (G×E) interaction between life stress and the serotonin transporter polymorphism (5-HTTLPR) on depression, but few studies have examined factors that influence detection of this effect, despite years of inconsistent results. We propose that the "candidate environment" (akin to a candidate gene) is key. Theory and evidence implicate major stressful life events (SLEs)-particularly major interpersonal SLEs-as well as chronic family stress. Participants ( N = 400) from the Youth Emotion Project (which began with 627 high school juniors oversampled for high neuroticism) completed up to five annual diagnostic and life stress interviews and provided DNA samples. A significant G×E effect for major SLEs and S -carrier genotype was accounted for significantly by major interpersonal SLEs but not significantly by major non-interpersonal SLEs. S -carrier genotype and chronic family stress also significantly interacted. Identifying such candidate environments may facilitate future G×E research in depression and psychopathology more broadly.

A genome-wide association and gene-environment interaction study for serum triglycerides levels in a healthy Chinese male population.

PubMed

Tan, Aihua; Sun, Jielin; Xia, Ning; Qin, Xue; Hu, Yanling; Zhang, Shijun; Tao, Sha; Gao, Yong; Yang, Xiaobo; Zhang, Haiying; Kim, Seong-Tae; Peng, Tao; Lin, Xiaoling; Li, Li; Mo, Linjian; Liang, Zhengjia; Shi, Deyi; Huang, Zhang; Huang, Xianghua; Liu, Ming; Ding, Qiang; Trent, Jeffrey M; Zheng, S Lilly; Mo, Zengnan; Xu, Jianfeng

2012-04-01

Triglyceride (TG) is a complex phenotype influenced by both genetic and environmental factors. Recent genome-wide association studies (GWAS) have identified genes or loci affecting lipid levels; however, such studies in Chinese populations are limited. A two-stage GWAS were conducted to identify genetic variants that were associated with TG in a Chinese population of 3495 men. Gene-environment interactions on serum TG levels were further investigated for the seven single nucleotide polymorphisms (SNPs) that were studied in both stages. Two previously reported SNPs (rs651821 in APOA5, rs328 in LPL) were replicated in the second stage, and the combined P-values were 9.19 × 10(-26) and 1.41 × 10(-9) for rs651821 and rs328, respectively. More importantly, a significant interaction between aldehyde dehydrogenase 2 (ALDH2) rs671 and alcohol consumption on serum TG levels were observed (P = 3.34 × 10(-5)). Rs671 was significantly associated with serum TG levels in drinkers (P = 1.90 × 10(-10)), while no association was observed in non-drinkers (P > 0.05). For drinkers, men carrying the AA/AG genotype have significantly lower serum TG levels, compared with men carrying the GG genotype. For men with the GG genotype, the serum TG levels increased with the quantity of alcohol intake (P = 1.28 × 10(-8) for trend test). We identified a novel, significant interaction effect between alcohol consumption and the ALDH2 rs671 polymorphism on TG levels, which suggests that the effect of alcohol intake on TG occurs in a two-faceted manner. Just one drink can increase TG level in susceptible individuals who carry the GG genotype, while individuals carrying AA/AG genotypes may actually benefit from moderate drinking.

The moderating effect of ANKK1 on the association of family environment with longitudinal executive function following traumatic brain injury in early childhood: A preliminary study.

PubMed

Smith-Paine, Julia; Wade, Shari L; Treble-Barna, Amery; Zhang, Nanhua; Zang, Huaiyu; Martin, Lisa J; Yeates, Keith Owen; Taylor, H Gerry; Kurowski, Brad G

2018-05-02

This study examined whether the ankyrin repeat and kinase domain containing 1 gene (ANKK1) C/T single-nucleotide polymorphism (SNP) rs1800497 moderated the association of family environment with long-term executive function (EF) following traumatic injury in early childhood. Caregivers of children with traumatic brain injury (TBI) and children with orthopedic injury (OI) completed the Behavior Rating Inventory of Executive Function (BRIEF) at post injury visits. DNA was collected to identify the rs1800497 genotype in the ANKK1 gene. General linear models examined gene-environment interactions as moderators of the effects of TBI on EF at two times post injury (12 months and 7 years). At 12 months post injury, analyses revealed a significant 3-way interaction of genotype with level of permissive parenting and injury type. Post-hoc analyses showed genetic effects were more pronounced for children with TBI from more positive family environments, such that children with TBI who were carriers of the risk allele (T-allele) had significantly poorer EF compared to non-carriers only when they were from more advantaged environments. At 7 years post injury, analyses revealed a significant 2-way interaction of genotype with level of authoritarian parenting. Post-hoc analyses found that carriers of the risk allele had significantly poorer EF compared to non-carriers only when they were from more advantaged environments. These results suggest a gene-environment interaction involving the ANKK1 gene as a predictor of EF in a pediatric injury population. The findings highlight the importance of considering environmental influences in future genetic studies on recovery following TBI and other traumatic injuries in childhood.

ORTHOPAEDIC GENE THERAPY – LOST IN TRANSLATION?

PubMed Central

Evans, C.H.; Ghivizzani, S.C.; Robbins, P.D.

2011-01-01

Orthopaedic gene therapy has been the topic of considerable research for two decades. The preclinical data are impressive and many orthopaedic conditions are well suited to genetic therapies. But there have been few clinical trials and no FDA-approved product exists. This paper examines why this is so. The reasons are multifactorial. Clinical translation is expensive and difficult to fund by traditional academic routes. Because gene therapy is viewed as unsafe and risky, it does not attract major funding from the pharmaceutical industry. Start-up companies are burdened by the complex intellectual property environment and difficulties in dealing with the technology transfer offices of major universities. Successful translation requires close interactions between scientists, clinicians and experts in regulatory and compliance issues. It is difficult to create such a favourable translational environment. Other promising fields of biological therapy have contemplated similar frustrations approximately 20 years after their founding, so there seem to be more general constraints on translation that are difficult to define. Gene therapy has noted some major clinical successes in recent years, and a sense of optimism is returning to the field. We hope that orthopaedic applications will benefit collaterally from this upswing and move expeditiously into advanced clinical trials. PMID:21948071

Early warm-rewarding parenting moderates the genetic contributions to callous-unemotional traits in childhood.

PubMed

Henry, Jeffrey; Dionne, Ginette; Viding, Essi; Vitaro, Frank; Brendgen, Mara; Tremblay, Richard E; Boivin, Michel

2018-04-23

Previous gene-environment interaction studies of CU traits have relied on the candidate gene approach, which does not account for the entire genetic load of complex phenotypes. Moreover, these studies have not examined the role of positive environmental factors such as warm/rewarding parenting. The aim of the present study was to determine whether early warm/rewarding parenting moderates the genetic contributions (i.e., heritability) to callous-unemotional (CU) traits at school age. Data were collected in a population sample of 662 twin pairs (Quebec Newborn Twin Study - QNTS). Mothers reported on their warm/rewarding parenting. Teachers assessed children's CU traits. These reports were subjected to twin modeling. Callous-unemotional traits were highly heritable, with the remaining variance accounted for by nonshared environmental factors. Warm/rewarding parenting significantly moderated the role of genes in CU traits; heritability was lower when children received high warm/rewarding parenting than when they were exposed to low warm/rewarding parenting. High warm/rewarding parenting may partly impede the genetic expression of CU traits. Developmental models of CU traits need to account for such gene-environment processes. © 2018 Association for Child and Adolescent Mental Health.

Multi-omics approach identifies molecular mechanisms of plant-fungus mycorrhizal interaction

DOE PAGES

Larsen, Peter E.; Sreedasyam, Avinash; Trivedi, Geetika; ...

2016-01-19

In mycorrhizal symbiosis, plant roots form close, mutually beneficial interactions with soil fungi. Before this mycorrhizal interaction can be established however, plant roots must be capable of detecting potential beneficial fungal partners and initiating the gene expression patterns necessary to begin symbiosis. To predict a plant root – mycorrhizal fungi sensor systems, we analyzed in vitro experiments of Populus tremuloides (aspen tree) and Laccaria bicolor (mycorrhizal fungi) interaction and leveraged over 200 previously published transcriptomic experimental data sets, 159 experimentally validated plant transcription factor binding motifs, and more than 120-thousand experimentally validated protein-protein interactions to generate models of pre-mycorrhizal sensormore » systems in aspen root. These sensor mechanisms link extracellular signaling molecules with gene regulation through a network comprised of membrane receptors, signal cascade proteins, transcription factors, and transcription factor biding DNA motifs. Modeling predicted four pre-mycorrhizal sensor complexes in aspen that interact with fifteen transcription factors to regulate the expression of 1184 genes in response to extracellular signals synthesized by Laccaria. Predicted extracellular signaling molecules include common signaling molecules such as phenylpropanoids, salicylate, and, jasmonic acid. Lastly, this multi-omic computational modeling approach for predicting the complex sensory networks yielded specific, testable biological hypotheses for mycorrhizal interaction signaling compounds, sensor complexes, and mechanisms of gene regulation.« less

Multi-omics approach identifies molecular mechanisms of plant-fungus mycorrhizal interaction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larsen, Peter E.; Sreedasyam, Avinash; Trivedi, Geetika

In mycorrhizal symbiosis, plant roots form close, mutually beneficial interactions with soil fungi. Before this mycorrhizal interaction can be established however, plant roots must be capable of detecting potential beneficial fungal partners and initiating the gene expression patterns necessary to begin symbiosis. To predict a plant root – mycorrhizal fungi sensor systems, we analyzed in vitro experiments of Populus tremuloides (aspen tree) and Laccaria bicolor (mycorrhizal fungi) interaction and leveraged over 200 previously published transcriptomic experimental data sets, 159 experimentally validated plant transcription factor binding motifs, and more than 120-thousand experimentally validated protein-protein interactions to generate models of pre-mycorrhizal sensormore » systems in aspen root. These sensor mechanisms link extracellular signaling molecules with gene regulation through a network comprised of membrane receptors, signal cascade proteins, transcription factors, and transcription factor biding DNA motifs. Modeling predicted four pre-mycorrhizal sensor complexes in aspen that interact with fifteen transcription factors to regulate the expression of 1184 genes in response to extracellular signals synthesized by Laccaria. Predicted extracellular signaling molecules include common signaling molecules such as phenylpropanoids, salicylate, and, jasmonic acid. Lastly, this multi-omic computational modeling approach for predicting the complex sensory networks yielded specific, testable biological hypotheses for mycorrhizal interaction signaling compounds, sensor complexes, and mechanisms of gene regulation.« less

An Overview of Mongenic and Syndromic Obesities in Humans

PubMed Central

Chung, Wendy K.

2011-01-01

Obesity is increasing in prevalence in the United States with over 65% of adults considered overweight and 16% of children with BMI > 95 percentile. The heritability of obesity is estimated between 40 and 70%, but the genetics of obesity for most individuals are complex and involve the interaction of multiple genes and environment. There are however several syndromic and non-syndromic forms of obesity that are monogenic and oligogenic that provide insight into the underlying molecular control of food intake and the neural networks that control ingestive behavior and satiety to regulate body weight and which may interact with treatment exposures to produce or exacerbate obesity in childhood cancer survivors. PMID:21994130

Interaction of rearing environment and reproductive tactic on gene expression profiles in Atlantic salmon

USGS Publications Warehouse

Aubin-Horth, N.; Letcher, B.H.; Hofmann, H.A.

2005-01-01

Organisms that share the same genotype can develop into divergent phenotypes, depending on environmental conditions. In Atlantic salmon, young males of the same age can be found either as sneakers or immature males that are future anadromous fish. Just as the organism-level phenotype varies between divergent male developmental trajectories, brain gene expression is expected to vary as well. We hypothesized that rearing environment can also have an important effect on gene expression in the brain and possibly interact with the reproductive tactic adopted. We tested this hypothesis by comparing brain gene expression profiles of the two male tactics in fish from the same population that were reared in either a natural stream or under laboratory conditions. We found that expression of certain genes was affected by rearing environment only, while others varied between male reproductive tactics independent of rearing environment. Finally, more than half of all genes that showed variable expression varied between the two male tactics only in one environment. Thus, in these fish, very different molecular pathways can give rise to similar macro-phenotypes depending on rearing environment. This result gives important insights into the molecular underpinnings of developmental plasticity in relationship to the environment. ?? 2005 The American Genetic Association.

Modeling Gene-Environment Interactions With Quasi-Natural Experiments.

PubMed

Schmitz, Lauren; Conley, Dalton

2017-02-01

This overview develops new empirical models that can effectively document Gene × Environment (G×E) interactions in observational data. Current G×E studies are often unable to support causal inference because they use endogenous measures of the environment or fail to adequately address the nonrandom distribution of genes across environments, confounding estimates. Comprehensive measures of genetic variation are incorporated into quasi-natural experimental designs to exploit exogenous environmental shocks or isolate variation in environmental exposure to avoid potential confounders. In addition, we offer insights from population genetics that improve upon extant approaches to address problems from population stratification. Together, these tools offer a powerful way forward for G×E research on the origin and development of social inequality across the life course. © 2015 Wiley Periodicals, Inc.

Challenges in reproducibility of genetic association studies: lessons learned from the obesity field.

PubMed

Li, A; Meyre, D

2013-04-01

A robust replication of initial genetic association findings has proved to be difficult in human complex diseases and more specifically in the obesity field. An obvious cause of non-replication in genetic association studies is the initial report of a false positive result, which can be explained by a non-heritable phenotype, insufficient sample size, improper correction for multiple testing, population stratification, technical biases, insufficient quality control or inappropriate statistical analyses. Replication may, however, be challenging even when the original study describes a true positive association. The reasons include underpowered replication samples, gene × gene, gene × environment interactions, genetic and phenotypic heterogeneity and subjective interpretation of data. In this review, we address classic pitfalls in genetic association studies and provide guidelines for proper discovery and replication genetic association studies with a specific focus on obesity.

Powerful multilocus tests of genetic association in the presence of gene-gene and gene-environment interactions.

PubMed

Chatterjee, Nilanjan; Kalaylioglu, Zeynep; Moslehi, Roxana; Peters, Ulrike; Wacholder, Sholom

2006-12-01

In modern genetic epidemiology studies, the association between the disease and a genomic region, such as a candidate gene, is often investigated using multiple SNPs. We propose a multilocus test of genetic association that can account for genetic effects that might be modified by variants in other genes or by environmental factors. We consider use of the venerable and parsimonious Tukey's 1-degree-of-freedom model of interaction, which is natural when individual SNPs within a gene are associated with disease through a common biological mechanism; in contrast, many standard regression models are designed as if each SNP has unique functional significance. On the basis of Tukey's model, we propose a novel but computationally simple generalized test of association that can simultaneously capture both the main effects of the variants within a genomic region and their interactions with the variants in another region or with an environmental exposure. We compared performance of our method with that of two standard tests of association, one ignoring gene-gene/gene-environment interactions and the other based on a saturated model of interactions. We demonstrate major power advantages of our method both in analysis of data from a case-control study of the association between colorectal adenoma and DNA variants in the NAT2 genomic region, which are well known to be related to a common biological phenotype, and under different models of gene-gene interactions with use of simulated data.

The influence of urban/rural residency on depressive symptoms is moderated by the serotonin receptor 2A gene.

PubMed

Jokela, Markus; Lehtimäki, Terho; Keltikangas-Järvinen, Liisa

2007-10-05

Gene-environment interactions are thought to be involved in the development of depression. Here we examined the interaction effect between urban/rural residency and the serotonin receptor 2A (HTR2A) gene on subclinical depressive symptoms. The participants were 1,224 Finnish men and women being followed in the on-going population-based study of "Cardiovascular Risk in Young Finns". Urban/rural residency was determined on the basis of a (1) subjective report and (2) the population density of the residential area. Depressive symptoms were measured in two test settings four years apart. There was a significant gene-environment interaction, such that the urban residency was associated with low depressive symptoms in individuals carrying the T/T or T/C genotype of the T102C polymorphism, but not in those carrying the C/C genotype. The T allele was associated with high depressive symptoms in remote rural areas, but with low depressive symptoms in urban or suburban areas. The gene-environment interaction was not accounted by level of education, social support, unemployment, or partnership status. The HTR2A gene may be involved in the development of depression by influencing how individuals respond to environmental conditions. (c) 2007 Wiley-Liss, Inc.

Gene by Environment Interaction and Resilience: Effects of Child Maltreatment and Serotonin, Corticotropin Releasing Hormone, Dopamine, and Oxytocin Genes

PubMed Central

Cicchetti, Dante; Rogosch, Fred A.

2013-01-01

In this investigation, gene-environment interaction effects in predicting resilience in adaptive functioning among maltreated and nonmaltreated low-income children (N = 595) were examined. A multi-component index of resilient functioning was derived and levels of resilient functioning were identified. Variants in four genes, 5-HTTLPR, CRHR1, DRD4 -521C/T, and OXTR, were investigated. In a series of ANCOVAs, child maltreatment demonstrated a strong negative main effect on children’s resilient functioning, whereas no main effects for any of the genotypes of the respective genes were found. However, gene-environment interactions involving genotypes of each of the respective genes and maltreatment status were obtained. For each respective gene, among children with a specific genotype, the relative advantage in resilient functioning of nonmaltreated compared to maltreated children was stronger than was the case for nonmaltreated and maltreated children with other genotypes of the respective gene. Across the four genes, a composite of the genotypes that more strongly differentiated resilient functioning between nonmaltreated and maltreated children provided further evidence of genetic variations influencing resilient functioning in nonmaltreated children, whereas genetic variation had a negligible effect on promoting resilience among maltreated children. Additional effects were observed for children based on the number of subtypes of maltreatment children experienced, as well as for abuse and neglect subgroups. Finally, maltreated and nonmaltreated children with high levels of resilience differed in their average number of differentiating genotypes. These results suggest that differential resilient outcomes are based on the interaction between genes and developmental experiences. PMID:22559122

Interactive effects of 5-HTTLPR genotype and rearing environment on affective attitude towards own infant in Japanese mothers.

PubMed

Sawano, Erika; Doi, Hirokazu; Nagai, Tomoko; Ikeda, Satoko; Shinohara, Kauyuki

2017-05-15

Maternal positive attitude towards one's own infant is the cornerstone of effective parenting. Previous research has revealed an influence of both genetic and environmental factors on maternal parenting behavior, but little is known of the potential gene-environment interaction in shaping a mother's affective attitude. To address this gap, we investigated the effect of a mother's childhood rearing environment and a serotonin transporter gene polymorphism (5-HTTLPR) on affective attitude towards her infant. Our analyses found an interactive effect between rearing environment and 5-HTTLPR genotype on maternal attitude. Specifically, a poor rearing environment (characterized by low maternal care and high paternal overprotection) decreased positive attitude towards one's own infant in mothers with homozygous short allele genotype. In contrast, this detrimental effect was almost eliminated in long allele carriers. Altogether, our results indicate that the 5-HTTLPR gene moderates the influence of experienced rearing environment on maternal parental behavior in a manner consistent with the notion that the short 5-HTTLPR allele amplifies environmental influence. Copyright © 2016 Elsevier B.V. All rights reserved.

Juxtaposed Polycomb complexes co-regulate vertebral identity.

PubMed

Kim, Se Young; Paylor, Suzanne W; Magnuson, Terry; Schumacher, Armin

2006-12-01

Best known as epigenetic repressors of developmental Hox gene transcription, Polycomb complexes alter chromatin structure by means of post-translational modification of histone tails. Depending on the cellular context, Polycomb complexes of diverse composition and function exhibit cooperative interaction or hierarchical interdependency at target loci. The present study interrogated the genetic, biochemical and molecular interaction of BMI1 and EED, pivotal constituents of heterologous Polycomb complexes, in the regulation of vertebral identity during mouse development. Despite a significant overlap in dosage-sensitive homeotic phenotypes and co-repression of a similar set of Hox genes, genetic analysis implicated eed and Bmi1 in parallel pathways, which converge at the level of Hox gene regulation. Whereas EED and BMI1 formed separate biochemical entities with EzH2 and Ring1B, respectively, in mid-gestation embryos, YY1 engaged in both Polycomb complexes. Strikingly, methylated lysine 27 of histone H3 (H3-K27), a mediator of Polycomb complex recruitment to target genes, stably associated with the EED complex during the maintenance phase of Hox gene repression. Juxtaposed EED and BMI1 complexes, along with YY1 and methylated H3-K27, were detected in upstream regulatory regions of Hoxc8 and Hoxa5. The combined data suggest a model wherein epigenetic and genetic elements cooperatively recruit and retain juxtaposed Polycomb complexes in mammalian Hox gene clusters toward co-regulation of vertebral identity.

Examining Gene-Environment Interactions in Comorbid Depressive and Disruptive Behavior Disorders using a Bayesian Approach

PubMed Central

Adrian, Molly; Kiff, Cara; Glazner, Chris; Kohen, Ruth; Tracy, Julia Helen; Zhou, Chuan; McCauley, Elizabeth; Stoep, Ann Vander

2015-01-01

Objective The objective of this study was to apply a Bayesian statistical analytic approach that minimizes multiple testing problems to explore the combined effects of chronic low familial support and variants in 12 candidate genes on risk for a common and debilitating childhood mental health condition. Method Bayesian mixture modeling was used to examine gene by environment interactions among genetic variants and environmental factors (family support) associated in previous studies with the occurrence of comorbid depression and disruptive behavior disorders youth, using a sample of 255 children. Results One main effects, variants in the oxytocin receptor (OXTR, rs53576) was associated with increased risk for comorbid disorders. Two significant gene x environment and one signification gene x gene interaction emerged. Variants in the nicotinic acetylcholine receptor α5 subunit (CHRNA5, rs16969968) and in the glucocorticoid receptor chaperone protein FK506 binding protein 5 (FKBP5, rs4713902) interacted with chronic low family support in association with child mental health status. One gene x gene interaction, 5-HTTLPR variant of the serotonin transporter (SERT/SLC6A4) in combination with μ opioid receptor (OPRM1, rs1799971) was associated with comorbid depression and conduct problems. Conclusions Results indicate that Bayesian modeling is a feasible strategy for conducting behavioral genetics research. This approach, combined with an optimized genetic selection strategy (Vrieze, Iacono, & McGue, 2012), revealed genetic variants involved in stress regulation ( FKBP5, SERTxOPMR), social bonding (OXTR), and nicotine responsivity (CHRNA5) in predicting comorbid status. PMID:26228411

Gene-Environment Interplay in the Link of Friends' and Nonfriends' Behaviors with Children's Social Reticence in a Competitive Situation

ERIC Educational Resources Information Center

Guimond, Fanny-Alexandra; Brendgen, Mara; Vitaro, Frank; Forget-Dubois, Nadine; Dionne, Ginette; Tremblay, Richard E.; Boivin, Michel

2014-01-01

This study used a genetically informed design to assess the effects of friends' and nonfriends' reticent and dominant behaviors on children's observed social reticence in a competitive situation. Potential gene-environment correlations (rGE) and gene-environment interactions (GxE) in the link between (a) friends' and…

Integrating genome-wide association study summaries and element-gene interaction datasets identified multiple associations between elements and complex diseases.

PubMed

He, Awen; Wang, Wenyu; Prakash, N Tejo; Tinkov, Alexey A; Skalny, Anatoly V; Wen, Yan; Hao, Jingcan; Guo, Xiong; Zhang, Feng

2018-03-01

Chemical elements are closely related to human health. Extensive genomic profile data of complex diseases offer us a good opportunity to systemically investigate the relationships between elements and complex diseases/traits. In this study, we applied gene set enrichment analysis (GSEA) approach to detect the associations between elements and complex diseases/traits though integrating element-gene interaction datasets and genome-wide association study (GWAS) data of complex diseases/traits. To illustrate the performance of GSEA, the element-gene interaction datasets of 24 elements were extracted from the comparative toxicogenomics database (CTD). GWAS summary datasets of 24 complex diseases or traits were downloaded from the dbGaP or GEFOS websites. We observed significant associations between 7 elements and 13 complex diseases or traits (all false discovery rate (FDR) < 0.05), including reported relationships such as aluminum vs. Alzheimer's disease (FDR = 0.042), calcium vs. bone mineral density (FDR = 0.031), magnesium vs. systemic lupus erythematosus (FDR = 0.012) as well as novel associations, such as nickel vs. hypertriglyceridemia (FDR = 0.002) and bipolar disorder (FDR = 0.027). Our study results are consistent with previous biological studies, supporting the good performance of GSEA. Our analyzing results based on GSEA framework provide novel clues for discovering causal relationships between elements and complex diseases. © 2017 WILEY PERIODICALS, INC.

Development and use of the Cytoscape app GFD-Net for measuring semantic dissimilarity of gene networks

PubMed Central

Diaz-Montana, Juan J.; Diaz-Diaz, Norberto

2014-01-01

Gene networks are one of the main computational models used to study the interaction between different elements during biological processes being widely used to represent gene–gene, or protein–protein interaction complexes. We present GFD-Net, a Cytoscape app for visualizing and analyzing the functional dissimilarity of gene networks. PMID:25400907

Cerebellum Transcriptome of Mice Bred for High Voluntary Activity Offers Insights into Locomotor Control and Reward-Dependent Behaviors.

PubMed

Caetano-Anollés, Kelsey; Rhodes, Justin S; Garland, Theodore; Perez, Sam D; Hernandez, Alvaro G; Southey, Bruce R; Rodriguez-Zas, Sandra L

2016-01-01

The role of the cerebellum in motivation and addictive behaviors is less understood than that in control and coordination of movements. High running can be a self-rewarding behavior exhibiting addictive properties. Changes in the cerebellum transcriptional networks of mice from a line selectively bred for High voluntary running (H) were profiled relative to an unselected Control (C) line. The environmental modulation of these changes was assessed both in activity environments corresponding to 7 days of Free (F) access to running wheel and to Blocked (B) access on day 7. Overall, 457 genes exhibited a significant (FDR-adjusted P-value < 0.05) genotype-by-environment interaction effect, indicating that activity genotype differences in gene expression depend on environmental access to running. Among these genes, network analysis highlighted 6 genes (Nrgn, Drd2, Rxrg, Gda, Adora2a, and Rab40b) connected by their products that displayed opposite expression patterns in the activity genotype contrast within the B and F environments. The comparison of network expression topologies suggests that selection for high voluntary running is linked to a predominant dysregulation of hub genes in the F environment that enables running whereas a dysregulation of ancillary genes is favored in the B environment that blocks running. Genes associated with locomotor regulation, signaling pathways, reward-processing, goal-focused, and reward-dependent behaviors exhibited significant genotype-by-environment interaction (e.g. Pak6, Adora2a, Drd2, and Arhgap8). Neuropeptide genes including Adcyap1, Cck, Sst, Vgf, Npy, Nts, Penk, and Tac2 and related receptor genes also exhibited significant genotype-by-environment interaction. The majority of the 183 differentially expressed genes between activity genotypes (e.g. Drd1) were under-expressed in C relative to H genotypes and were also under-expressed in B relative to F environments. Our findings indicate that the high voluntary running mouse line studied is a helpful model for understanding the molecular mechanisms in the cerebellum that influence locomotor control and reward-dependent behaviors.

Cerebellum Transcriptome of Mice Bred for High Voluntary Activity Offers Insights into Locomotor Control and Reward-Dependent Behaviors

PubMed Central

Caetano-Anollés, Kelsey; Rhodes, Justin S.; Garland, Theodore; Perez, Sam D.; Hernandez, Alvaro G.; Southey, Bruce R.; Rodriguez-Zas, Sandra L.

2016-01-01

The role of the cerebellum in motivation and addictive behaviors is less understood than that in control and coordination of movements. High running can be a self-rewarding behavior exhibiting addictive properties. Changes in the cerebellum transcriptional networks of mice from a line selectively bred for High voluntary running (H) were profiled relative to an unselected Control (C) line. The environmental modulation of these changes was assessed both in activity environments corresponding to 7 days of Free (F) access to running wheel and to Blocked (B) access on day 7. Overall, 457 genes exhibited a significant (FDR-adjusted P-value < 0.05) genotype-by-environment interaction effect, indicating that activity genotype differences in gene expression depend on environmental access to running. Among these genes, network analysis highlighted 6 genes (Nrgn, Drd2, Rxrg, Gda, Adora2a, and Rab40b) connected by their products that displayed opposite expression patterns in the activity genotype contrast within the B and F environments. The comparison of network expression topologies suggests that selection for high voluntary running is linked to a predominant dysregulation of hub genes in the F environment that enables running whereas a dysregulation of ancillary genes is favored in the B environment that blocks running. Genes associated with locomotor regulation, signaling pathways, reward-processing, goal-focused, and reward-dependent behaviors exhibited significant genotype-by-environment interaction (e.g. Pak6, Adora2a, Drd2, and Arhgap8). Neuropeptide genes including Adcyap1, Cck, Sst, Vgf, Npy, Nts, Penk, and Tac2 and related receptor genes also exhibited significant genotype-by-environment interaction. The majority of the 183 differentially expressed genes between activity genotypes (e.g. Drd1) were under-expressed in C relative to H genotypes and were also under-expressed in B relative to F environments. Our findings indicate that the high voluntary running mouse line studied is a helpful model for understanding the molecular mechanisms in the cerebellum that influence locomotor control and reward-dependent behaviors. PMID:27893846

MYC interaction with the tumor suppressive SWI/SNF complex member INI1 regulates transcription and cellular transformation

PubMed Central

Stojanova, Angelina; Tu, William B.; Ponzielli, Romina; Kotlyar, Max; Chan, Pak-Kei; Boutros, Paul C.; Khosravi, Fereshteh; Jurisica, Igor; Raught, Brian; Penn, Linda Z.

2016-01-01

ABSTRACT MYC is a key driver of cellular transformation and is deregulated in most human cancers. Studies of MYC and its interactors have provided mechanistic insight into its role as a regulator of gene transcription. MYC has been previously linked to chromatin regulation through its interaction with INI1 (SMARCB1/hSNF5/BAF47), a core member of the SWI/SNF chromatin remodeling complex. INI1 is a potent tumor suppressor that is inactivated in several types of cancers, most prominently as the hallmark alteration in pediatric malignant rhabdoid tumors. However, the molecular and functional interaction of MYC and INI1 remains unclear. Here, we characterize the MYC-INI1 interaction in mammalian cells, mapping their minimal binding domains to functionally significant regions of MYC (leucine zipper) and INI1 (repeat motifs), and demonstrating that the interaction does not interfere with MYC-MAX interaction. Protein-protein interaction network analysis expands the MYC-INI1 interaction to the SWI/SNF complex and a larger network of chromatin regulatory complexes. Genome-wide analysis reveals that the DNA-binding regions and target genes of INI1 significantly overlap with those of MYC. In an INI1-deficient rhabdoid tumor system, we observe that with re-expression of INI1, MYC and INI1 bind to common target genes and have opposing effects on gene expression. Functionally, INI1 re-expression suppresses cell proliferation and MYC-potentiated transformation. Our findings thus establish the antagonistic roles of the INI1 and MYC transcriptional regulators in mediating cellular and oncogenic functions. PMID:27267444

Recursive expectation-maximization clustering: A method for identifying buffering mechanisms composed of phenomic modules

NASA Astrophysics Data System (ADS)

Guo, Jingyu; Tian, Dehua; McKinney, Brett A.; Hartman, John L.

2010-06-01

Interactions between genetic and/or environmental factors are ubiquitous, affecting the phenotypes of organisms in complex ways. Knowledge about such interactions is becoming rate-limiting for our understanding of human disease and other biological phenomena. Phenomics refers to the integrative analysis of how all genes contribute to phenotype variation, entailing genome and organism level information. A systems biology view of gene interactions is critical for phenomics. Unfortunately the problem is intractable in humans; however, it can be addressed in simpler genetic model systems. Our research group has focused on the concept of genetic buffering of phenotypic variation, in studies employing the single-cell eukaryotic organism, S. cerevisiae. We have developed a methodology, quantitative high throughput cellular phenotyping (Q-HTCP), for high-resolution measurements of gene-gene and gene-environment interactions on a genome-wide scale. Q-HTCP is being applied to the complete set of S. cerevisiae gene deletion strains, a unique resource for systematically mapping gene interactions. Genetic buffering is the idea that comprehensive and quantitative knowledge about how genes interact with respect to phenotypes will lead to an appreciation of how genes and pathways are functionally connected at a systems level to maintain homeostasis. However, extracting biologically useful information from Q-HTCP data is challenging, due to the multidimensional and nonlinear nature of gene interactions, together with a relative lack of prior biological information. Here we describe a new approach for mining quantitative genetic interaction data called recursive expectation-maximization clustering (REMc). We developed REMc to help discover phenomic modules, defined as sets of genes with similar patterns of interaction across a series of genetic or environmental perturbations. Such modules are reflective of buffering mechanisms, i.e., genes that play a related role in the maintenance of physiological homeostasis. To develop the method, 297 gene deletion strains were selected based on gene-drug interactions with hydroxyurea, an inhibitor of ribonucleotide reductase enzyme activity, which is critical for DNA synthesis. To partition the gene functions, these 297 deletion strains were challenged with growth inhibitory drugs known to target different genes and cellular pathways. Q-HTCP-derived growth curves were used to quantify all gene interactions, and the data were used to test the performance of REMc. Fundamental advantages of REMc include objective assessment of total number of clusters and assignment to each cluster a log-likelihood value, which can be considered an indicator of statistical quality of clusters. To assess the biological quality of clusters, we developed a method called gene ontology information divergence z-score (GOid_z). GOid_z summarizes total enrichment of GO attributes within individual clusters. Using these and other criteria, we compared the performance of REMc to hierarchical and K-means clustering. The main conclusion is that REMc provides distinct efficiencies for mining Q-HTCP data. It facilitates identification of phenomic modules, which contribute to buffering mechanisms that underlie cellular homeostasis and the regulation of phenotypic expression.

Simulating the Yield Impacts of Organ-Level Quantitative Trait Loci Associated With Drought Response in Maize: A “Gene-to-Phenotype” Modeling Approach

PubMed Central

Chenu, Karine; Chapman, Scott C.; Tardieu, François; McLean, Greg; Welcker, Claude; Hammer, Graeme L.

2009-01-01

Under drought, substantial genotype–environment (G × E) interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to our inability to account for the interplay of genetic controls, physiological traits, and environmental conditions throughout the crop cycle. We propose a modeling approach to bridge this “gene-to-phenotype” gap. For maize under drought, we simulated the impact of quantitative trait loci (QTL) controlling two key processes (leaf and silk elongation) that influence crop growth, water use, and grain yield. Substantial G × E interaction for yield was simulated for hypothetical recombinant inbred lines (RILs) across different seasonal patterns of drought. QTL that accelerated leaf elongation caused an increase in crop leaf area and yield in well-watered or preflowering water deficit conditions, but a reduction in yield under terminal stresses (as such “leafy” genotypes prematurely exhausted the water supply). The QTL impact on yield was substantially enhanced by including pleiotropic effects of these QTL on silk elongation and on consequent grain set. The simulations obtained illustrated the difficulty of interpreting the genetic control of yield for genotypes influenced only by the additive effects of QTL associated with leaf and silk growth. The results highlight the potential of integrative simulation modeling for gene-to-phenotype prediction and for exploiting G × E interactions for complex traits such as drought tolerance. PMID:19786622

On meta- and mega-analyses for gene-environment interactions.

PubMed

Huang, Jing; Liu, Yulun; Vitale, Steve; Penning, Trevor M; Whitehead, Alexander S; Blair, Ian A; Vachani, Anil; Clapper, Margie L; Muscat, Joshua E; Lazarus, Philip; Scheet, Paul; Moore, Jason H; Chen, Yong

2017-12-01

Gene-by-environment (G × E) interactions are important in explaining the missing heritability and understanding the causation of complex diseases, but a single, moderately sized study often has limited statistical power to detect such interactions. With the increasing need for integrating data and reporting results from multiple collaborative studies or sites, debate over choice between mega- versus meta-analysis continues. In principle, data from different sites can be integrated at the individual level into a "mega" data set, which can be fit by a joint "mega-analysis." Alternatively, analyses can be done at each site, and results across sites can be combined through a "meta-analysis" procedure without integrating individual level data across sites. Although mega-analysis has been advocated in several recent initiatives, meta-analysis has the advantages of simplicity and feasibility, and has recently led to several important findings in identifying main genetic effects. In this paper, we conducted empirical and simulation studies, using data from a G × E study of lung cancer, to compare the mega- and meta-analyses in four commonly used G × E analyses under the scenario that the number of studies is small and sample sizes of individual studies are relatively large. We compared the two data integration approaches in the context of fixed effect models and random effects models separately. Our investigations provide valuable insights in understanding the differences between mega- and meta-analyses in practice of combining small number of studies in identifying G × E interactions. © 2017 WILEY PERIODICALS, INC.

Genetics and Peer Relations: A Review

ERIC Educational Resources Information Center

Brendgen, Mara

2012-01-01

Researchers have become increasingly interested in uncovering how genetic factors work together with the peer environment in influencing development. This article offers an overview of the state of knowledge. It first describes the different types of gene-environment correlations (rGE) and gene-environment interactions (GxE) that are of relevance…

Epigenetic switch from repressive to permissive chromatin in response to cold stress.

PubMed

Park, Junghoon; Lim, Chae Jin; Shen, Mingzhe; Park, Hee Jin; Cha, Joon-Yung; Iniesto, Elisa; Rubio, Vicente; Mengiste, Tesfaye; Zhu, Jian-Kang; Bressan, Ray A; Lee, Sang Yeol; Lee, Byeong-Ha; Jin, Jing Bo; Pardo, Jose M; Kim, Woe-Yeon; Yun, Dae-Jin

2018-06-05

Switching from repressed to active status in chromatin regulation is part of the critical responses that plants deploy to survive in an ever-changing environment. We previously reported that HOS15, a WD40-repeat protein, is involved in histone deacetylation and cold tolerance in Arabidopsis However, it remained unknown how HOS15 regulates cold responsive genes to affect cold tolerance. Here, we show that HOS15 interacts with histone deacetylase 2C (HD2C) and both proteins together associate with the promoters of cold-responsive COR genes, COR15A and COR47 Cold induced HD2C degradation is mediated by the CULLIN4 (CUL4)-based E3 ubiquitin ligase complex in which HOS15 acts as a substrate receptor. Interference with the association of HD2C and the COR gene promoters by HOS15 correlates with increased acetylation levels of histone H3. HOS15 also interacts with CBF transcription factors to modulate cold-induced binding to the COR gene promoters. Our results here demonstrate that cold induces HOS15-mediated chromatin modifications by degrading HD2C. This switches the chromatin structure status and facilitates recruitment of CBFs to the COR gene promoters. This is an apparent requirement to acquire cold tolerance. Copyright © 2018 the Author(s). Published by PNAS.

Epigenetic switch from repressive to permissive chromatin in response to cold stress

PubMed Central

Park, Junghoon; Lim, Chae Jin; Shen, Mingzhe; Park, Hee Jin; Cha, Joon-Yung; Iniesto, Elisa; Rubio, Vicente; Mengiste, Tesfaye; Bressan, Ray A.; Lee, Sang Yeol; Lee, Byeong-ha; Kim, Woe-Yeon; Yun, Dae-Jin

2018-01-01

Switching from repressed to active status in chromatin regulation is part of the critical responses that plants deploy to survive in an ever-changing environment. We previously reported that HOS15, a WD40-repeat protein, is involved in histone deacetylation and cold tolerance in Arabidopsis. However, it remained unknown how HOS15 regulates cold responsive genes to affect cold tolerance. Here, we show that HOS15 interacts with histone deacetylase 2C (HD2C) and both proteins together associate with the promoters of cold-responsive COR genes, COR15A and COR47. Cold induced HD2C degradation is mediated by the CULLIN4 (CUL4)-based E3 ubiquitin ligase complex in which HOS15 acts as a substrate receptor. Interference with the association of HD2C and the COR gene promoters by HOS15 correlates with increased acetylation levels of histone H3. HOS15 also interacts with CBF transcription factors to modulate cold-induced binding to the COR gene promoters. Our results here demonstrate that cold induces HOS15-mediated chromatin modifications by degrading HD2C. This switches the chromatin structure status and facilitates recruitment of CBFs to the COR gene promoters. This is an apparent requirement to acquire cold tolerance. PMID:29784800

A Critical Look at Entropy-Based Gene-Gene Interaction Measures.

PubMed

Lee, Woojoo; Sjölander, Arvid; Pawitan, Yudi

2016-07-01

Several entropy-based measures for detecting gene-gene interaction have been proposed recently. It has been argued that the entropy-based measures are preferred because entropy can better capture the nonlinear relationships between genotypes and traits, so they can be useful to detect gene-gene interactions for complex diseases. These suggested measures look reasonable at intuitive level, but so far there has been no detailed characterization of the interactions captured by them. Here we study analytically the properties of some entropy-based measures for detecting gene-gene interactions in detail. The relationship between interactions captured by the entropy-based measures and those of logistic regression models is clarified. In general we find that the entropy-based measures can suffer from a lack of specificity in terms of target parameters, i.e., they can detect uninteresting signals as interactions. Numerical studies are carried out to confirm theoretical findings. © 2016 WILEY PERIODICALS, INC.

Growth Hormone and Craniofacial Tissues. An update

PubMed Central

Litsas, George

2015-01-01

Growth hormone is an important regulator of bone homeostasis. In childhood, it determines the longitudinal bone growth, skeletal maturation, and acquisition of bone mass. In adulthood, it is necessary to maintain bone mass throughout life. Although an association between craniofacial and somatic development has been clearly established, craniofacial growth involves complex interactions of genes, hormones and environment. Moreover, as an anabolic hormone seems to have an important role in the regulation of bone remodeling, muscle enhancement and tooth development. In this paper the influence of growth hormone on oral tissues is reviewed. PMID:25674165

LHX3 interacts with inhibitor of histone acetyltransferase complex subunits LANP and TAF-1β to modulate pituitary gene regulation.

PubMed

Hunter, Chad S; Malik, Raleigh E; Witzmann, Frank A; Rhodes, Simon J

2013-01-01

LIM-homeodomain 3 (LHX3) is a transcription factor required for mammalian pituitary gland and nervous system development. Human patients and animal models with LHX3 gene mutations present with severe pediatric syndromes that feature hormone deficiencies and symptoms associated with nervous system dysfunction. The carboxyl terminus of the LHX3 protein is required for pituitary gene regulation, but the mechanism by which this domain operates is unknown. In order to better understand LHX3-dependent pituitary hormone gene transcription, we used biochemical and mass spectrometry approaches to identify and characterize proteins that interact with the LHX3 carboxyl terminus. This approach identified the LANP/pp32 and TAF-1β/SET proteins, which are components of the inhibitor of histone acetyltransferase (INHAT) multi-subunit complex that serves as a multifunctional repressor to inhibit histone acetylation and modulate chromatin structure. The protein domains of LANP and TAF-1β that interact with LHX3 were mapped using biochemical techniques. Chromatin immunoprecipitation experiments demonstrated that LANP and TAF-1β are associated with LHX3 target genes in pituitary cells, and experimental alterations of LANP and TAF-1β levels affected LHX3-mediated pituitary gene regulation. Together, these data suggest that transcriptional regulation of pituitary genes by LHX3 involves regulated interactions with the INHAT complex.

LHX3 Interacts with Inhibitor of Histone Acetyltransferase Complex Subunits LANP and TAF-1β to Modulate Pituitary Gene Regulation

PubMed Central

Witzmann, Frank A.; Rhodes, Simon J.

2013-01-01

LIM-homeodomain 3 (LHX3) is a transcription factor required for mammalian pituitary gland and nervous system development. Human patients and animal models with LHX3 gene mutations present with severe pediatric syndromes that feature hormone deficiencies and symptoms associated with nervous system dysfunction. The carboxyl terminus of the LHX3 protein is required for pituitary gene regulation, but the mechanism by which this domain operates is unknown. In order to better understand LHX3-dependent pituitary hormone gene transcription, we used biochemical and mass spectrometry approaches to identify and characterize proteins that interact with the LHX3 carboxyl terminus. This approach identified the LANP/pp32 and TAF-1β/SET proteins, which are components of the inhibitor of histone acetyltransferase (INHAT) multi-subunit complex that serves as a multifunctional repressor to inhibit histone acetylation and modulate chromatin structure. The protein domains of LANP and TAF-1β that interact with LHX3 were mapped using biochemical techniques. Chromatin immunoprecipitation experiments demonstrated that LANP and TAF-1β are associated with LHX3 target genes in pituitary cells, and experimental alterations of LANP and TAF-1β levels affected LHX3-mediated pituitary gene regulation. Together, these data suggest that transcriptional regulation of pituitary genes by LHX3 involves regulated interactions with the INHAT complex. PMID:23861948

The role of interindividual variation in human carcinogenesis.

PubMed

Lai, C; Shields, P G

1999-02-01

The process of chemical carcinogenesis is a complex multistage process initiated by DNA damage in growth control genes. Carcinogens enter the body from a variety of sources, but most require metabolic activation before they can damage DNA. There are multiple protective processes that include detoxification and conjugation, DNA repair and programmed cell death. Most of these functions exhibit wide interindividual variation in the population and thus are thought to affect cancer risk. The role of gene-environment interactions is being explored, and current data indicate that genetic susceptibilities can modify carcinogen exposures from the diet and tobacco smoking, although much more data exist for the latter. This review addresses the relationships of human carcinogenesis to these interindividual differences of phase I, phase II and DNA repair enzymes.

Gene-by-Environment Interactions in Pancreatic Cancer: Implications for Prevention

PubMed Central

Jansen, Rick J.; Tan, Xiang-Lin; Petersen, Gloria M.

2015-01-01

Pancreatic cancer (PC) has been estimated to have higher incidence and correspondingly higher mortality rates in more developed regions worldwide. Overall, the age-adjusted incidence rate is 4.9/105 and age-adjusted mortality rate is at 4.8/105. We review here our current knowledge of modifiable risk factors (cigarette smoking, obesity, diet, and alcohol) for PC, genetic variants implicated by genome-wide association studies, possible genetic interactions with risk factors, and prevention strategies to provide future research directions that may further our understanding of this complex disease. Cigarette smoking is consistently associated with a two-fold increased PC risk. PC associations with dietary intake have been largely inconsistent, with the potential exception of certain unsaturated fatty acids decreasing risk and well-done red meat or meat mutagens increasing risk. There is strong evidence to support that obesity (and related measures) increase risk of PC. Only the heaviest alcohol drinkers seem to be at an increased risk of PC. Currently, key prevention strategies include avoiding tobacco and excessive alcohol consumption and adopting a healthy lifestyle. Screening technologies and PC chemoprevention are likely to become more sophisticated, but may only apply to those at high risk. Risk stratification may be improved by taking into account gene environment interactions. Research on these modifiable risk factors is key to reducing the incidence of PC and understanding who in the population can be considered high risk. PMID:26029010

A computational interactome for prioritizing genes associated with complex agronomic traits in rice (Oryza sativa).

PubMed

Liu, Shiwei; Liu, Yihui; Zhao, Jiawei; Cai, Shitao; Qian, Hongmei; Zuo, Kaijing; Zhao, Lingxia; Zhang, Lida

2017-04-01

Rice (Oryza sativa) is one of the most important staple foods for more than half of the global population. Many rice traits are quantitative, complex and controlled by multiple interacting genes. Thus, a full understanding of genetic relationships will be critical to systematically identify genes controlling agronomic traits. We developed a genome-wide rice protein-protein interaction network (RicePPINet, http://netbio.sjtu.edu.cn/riceppinet) using machine learning with structural relationship and functional information. RicePPINet contained 708 819 predicted interactions for 16 895 non-transposable element related proteins. The power of the network for discovering novel protein interactions was demonstrated through comparison with other publicly available protein-protein interaction (PPI) prediction methods, and by experimentally determined PPI data sets. Furthermore, global analysis of domain-mediated interactions revealed RicePPINet accurately reflects PPIs at the domain level. Our studies showed the efficiency of the RicePPINet-based method in prioritizing candidate genes involved in complex agronomic traits, such as disease resistance and drought tolerance, was approximately 2-11 times better than random prediction. RicePPINet provides an expanded landscape of computational interactome for the genetic dissection of agronomically important traits in rice. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Gene-Environment Interplay between Parent-Child Relationship Problems and Externalizing Disorders in Adolescence and Young Adulthood

PubMed Central

Samek, Diana R.; Hicks, Brian M.; Keyes, Margaret A.; Bailey, Jennifer; McGue, Matt; Iacono, William G.

2014-01-01

Background Previous studies have shown that genetic risk for externalizing (EXT) disorders is greater in the context of adverse family environments during adolescence, but it is unclear whether these effects are long-lasting. The current study evaluated developmental changes in gene-environment interplay in the concurrent and prospective associations between parent-child relationship problems and EXT at ages 18 and 25. Method The sample included 1,382 twin pairs (48% male) from the Minnesota Twin Family Study, participating in assessments at ages 18 (M = 17.8 years, SD = 0.69) and 25 (M = 25.0 years, SD = 0.90). Perceptions of parent-child relationship problems were assessed using questionnaires. Structured interviews were used to assess symptoms of adult antisocial behavior and nicotine, alcohol, and illicit drug dependence. Results We detected a gene-environment interaction at age 18, such that the genetic influence on EXT was greater in the context of more parent-child relationship problems. This moderation effect was not present at age 25, nor did parent-relationship problems at age 18 moderate genetic influence on EXT at age 25. Rather, common genetic influences accounted for this longitudinal association. Conclusions Gene-environment interaction evident in the relationship between adolescent parent-child relationship problems and EXT is both proximal and developmentally limited. Common genetic influence, rather than a gene-environment interaction, accounts for the long-term association between parent-child relationship problems at age 18 and EXT at age 25. These results are consistent with a relatively pervasive importance of gene-environmental correlation in the transition from late adolescence to young adulthood. PMID:25066478

Old meets new: using interspecies interactions to detect secondary metabolite production in actinomycetes.

PubMed

Seyedsayamdost, Mohammad R; Traxler, Matthew F; Clardy, Jon; Kolter, Roberto

2012-01-01

Actinomycetes, a group of filamentous, Gram-positive bacteria, have long been a remarkable source of useful therapeutics. Recent genome sequencing and transcriptomic studies have shown that these bacteria, responsible for half of the clinically used antibiotics, also harbor a large reservoir of gene clusters, which have the potential to produce novel secreted small molecules. Yet, many of these clusters are not expressed under common culture conditions. One reason why these clusters have not been linked to a secreted small molecule lies in the way that actinomycetes have typically been studied: as pure cultures in nutrient-rich media that do not mimic the complex environments in which these bacteria evolved. New methods based on multispecies culture conditions provide an alternative approach to investigating the products of these gene clusters. We have recently implemented binary interspecies interaction assays to mine for new secondary metabolites and to study the underlying biology of interactinomycete interactions. Here, we describe the detailed biological and chemical methods comprising these studies. Copyright © 2012 Elsevier Inc. All rights reserved.

Integrative multicellular biological modeling: a case study of 3D epidermal development using GPU algorithms

PubMed Central

2010-01-01

Background Simulation of sophisticated biological models requires considerable computational power. These models typically integrate together numerous biological phenomena such as spatially-explicit heterogeneous cells, cell-cell interactions, cell-environment interactions and intracellular gene networks. The recent advent of programming for graphical processing units (GPU) opens up the possibility of developing more integrative, detailed and predictive biological models while at the same time decreasing the computational cost to simulate those models. Results We construct a 3D model of epidermal development and provide a set of GPU algorithms that executes significantly faster than sequential central processing unit (CPU) code. We provide a parallel implementation of the subcellular element method for individual cells residing in a lattice-free spatial environment. Each cell in our epidermal model includes an internal gene network, which integrates cellular interaction of Notch signaling together with environmental interaction of basement membrane adhesion, to specify cellular state and behaviors such as growth and division. We take a pedagogical approach to describing how modeling methods are efficiently implemented on the GPU including memory layout of data structures and functional decomposition. We discuss various programmatic issues and provide a set of design guidelines for GPU programming that are instructive to avoid common pitfalls as well as to extract performance from the GPU architecture. Conclusions We demonstrate that GPU algorithms represent a significant technological advance for the simulation of complex biological models. We further demonstrate with our epidermal model that the integration of multiple complex modeling methods for heterogeneous multicellular biological processes is both feasible and computationally tractable using this new technology. We hope that the provided algorithms and source code will be a starting point for modelers to develop their own GPU implementations, and encourage others to implement their modeling methods on the GPU and to make that code available to the wider community. PMID:20696053

Gender specific gene-environment interactions on laboratory-assessed aggression.

PubMed

Verona, Edelyn; Joiner, Thomas E; Johnson, Frank; Bender, Theodore W

2006-01-01

We examined gene-environment interactive effects on aggressive behavior among men and women genotyped (short versus long alleles) for the serotonin transporter gene. Aggressive behavior was indexed via a laboratory paradigm that measured the intensity and duration of shocks delivered to a putative "employee". Half of the participants were exposed to a physical stressor during the procedure (stress) and half were not (no-stress). Participants' physiological responses were gauged via acoustic startle eyeblink reactions (startle reactivity). Results were that men with the homozygous short (s/s) genotype showed increased aggression only under stress, whereas women and men carrying the long allele did not show differences in aggression in stress versus no-stress. However, although stress exposure produced increases in startle reactivity, there were no genotype or gender differences in physiology. These results replicate longitudinal research findings confirming the interactive effects of genes and environment on behavioral reactivity and on the development of externalizing psychopathological syndromes, at least in men.

Brain-derived neurotrophic factor as a model system for examining gene by environment interactions across development.

PubMed

Casey, B J; Glatt, C E; Tottenham, N; Soliman, F; Bath, K; Amso, D; Altemus, M; Pattwell, S; Jones, R; Levita, L; McEwen, B; Magariños, A M; Gunnar, M; Thomas, K M; Mezey, J; Clark, A G; Hempstead, B L; Lee, F S

2009-11-24

There has been a dramatic rise in gene x environment studies of human behavior over the past decade that have moved the field beyond simple nature versus nurture debates. These studies offer promise in accounting for more variability in behavioral and biological phenotypes than studies that focus on genetic or experiential factors alone. They also provide clues into mechanisms of modifying genetic risk or resilience in neurodevelopmental disorders. Yet, it is rare that these studies consider how these interactions change over the course of development. In this paper, we describe research that focuses on the impact of a polymorphism in a brain-derived neurotrophic factor (BDNF) gene, known to be involved in learning and development. Specifically we present findings that assess the effects of genotypic and environmental loadings on neuroanatomic and behavioral phenotypes across development. The findings illustrate the use of a genetic mouse model that mimics the human polymorphism, to constrain the interpretation of gene-environment interactions across development in humans.

The search for the genetic basis of hypertension.

PubMed

Yagil, Yoram; Yagil, Chana

2005-03-01

This review surveys the literature on the search for the genetic basis of hypertension during the 10 months since November 2003. The goals set forth by this search are defined and the highlights of the work accomplished are provided. The search for the genetic basis of hypertension is ongoing, generating an abundance of new data. These data consist of a large number of candidate genes, association of previously known and novel candidate genes with various facets of hypertension, detection of new quantitative trait loci and identification of genes that mediate susceptibility to hypertension. The renin-zangiotensin-aldosterone system continues to dominate the interest of investigators. Other gene systems are also emerging but a single-gene system cannot be singled out beyond the renin-angiotensin-aldosterone system and the data are mostly sporadic and do not reflect a guided or coordinated effort to resolve unanswered issues. The notion that hypertension is polygenic is reinforced, yet few data are provided as to the actual number of genes involved, gene-gene interaction or gene-environment interaction. Advanced biotechnological tools involving transcriptomics and proteomics are underused. Research on the genetic basis of hypertension has generated over the past year a large number of candidate genes and tied them to various aspects of hypertension. How these genes fit into the complex pathophysiological network that induces hypertension remains unclear. The task of putting together these genes into a cohesive framework still lies ahead, but promises to enlighten us as to the true nature of hypertension, the pathogenic mechanisms involved and improved therapeutic and preventive measures.

Teleosts as Model Organisms To Understand Host-Microbe Interactions.

PubMed

Lescak, Emily A; Milligan-Myhre, Kathryn C

2017-08-01

Host-microbe interactions are influenced by complex host genetics and environment. Studies across animal taxa have aided our understanding of how intestinal microbiota influence vertebrate development, disease, and physiology. However, traditional mammalian studies can be limited by the use of isogenic strains, husbandry constraints that result in small sample sizes and limited statistical power, reliance on indirect characterization of gut microbial communities from fecal samples, and concerns of whether observations in artificial conditions are actually reflective of what occurs in the wild. Fish models are able to overcome many of these limitations. The extensive variation in the physiology, ecology, and natural history of fish enriches studies of the evolution and ecology of host-microbe interactions. They share physiological and immunological features common among vertebrates, including humans, and harbor complex gut microbiota, which allows identification of the mechanisms driving microbial community assembly. Their accelerated life cycles and large clutch sizes and the ease of sampling both internal and external microbial communities make them particularly well suited for robust statistical studies of microbial diversity. Gnotobiotic techniques, genetic manipulation of the microbiota and host, and transparent juveniles enable novel insights into mechanisms underlying development of the digestive tract and disease states. Many diseases involve a complex combination of genes which are difficult to manipulate in homogeneous model organisms. By taking advantage of the natural genetic variation found in wild fish populations, as well as of the availability of powerful genetic tools, future studies should be able to identify conserved genes and pathways that contribute to human genetic diseases characterized by dysbiosis. Copyright © 2017 Lescak and Milligan-Myhre.

Teleosts as Model Organisms To Understand Host-Microbe Interactions

PubMed Central

2017-01-01

ABSTRACT Host-microbe interactions are influenced by complex host genetics and environment. Studies across animal taxa have aided our understanding of how intestinal microbiota influence vertebrate development, disease, and physiology. However, traditional mammalian studies can be limited by the use of isogenic strains, husbandry constraints that result in small sample sizes and limited statistical power, reliance on indirect characterization of gut microbial communities from fecal samples, and concerns of whether observations in artificial conditions are actually reflective of what occurs in the wild. Fish models are able to overcome many of these limitations. The extensive variation in the physiology, ecology, and natural history of fish enriches studies of the evolution and ecology of host-microbe interactions. They share physiological and immunological features common among vertebrates, including humans, and harbor complex gut microbiota, which allows identification of the mechanisms driving microbial community assembly. Their accelerated life cycles and large clutch sizes and the ease of sampling both internal and external microbial communities make them particularly well suited for robust statistical studies of microbial diversity. Gnotobiotic techniques, genetic manipulation of the microbiota and host, and transparent juveniles enable novel insights into mechanisms underlying development of the digestive tract and disease states. Many diseases involve a complex combination of genes which are difficult to manipulate in homogeneous model organisms. By taking advantage of the natural genetic variation found in wild fish populations, as well as of the availability of powerful genetic tools, future studies should be able to identify conserved genes and pathways that contribute to human genetic diseases characterized by dysbiosis. PMID:28439034

Host Genotype and Harvest Practices Shape the Leaf and Root Microbiomes of the Biofuel Crop Switchgrass

NASA Astrophysics Data System (ADS)

Singer, E.; Gonzalez, J.; Juenger, T. E.; Woyke, T.

2016-12-01

Growing energy demands and concerns for climate change have urgently pushed forward the timeline for the implementation of biofuel energies. Switchgrass (Panicum virgatum) is a leading biofuel crop in the United States. Bacteria living on and inside leaves and roots affect plant health, hence a plant's genetic control over its microbiota is of great interest to crop breeders and evolutionary biologists. We present a large-scale field experiment to untangle the effects of genotype, environment, soil horizon and harvest treatment practices on prokaryotic and fungal communities associated with leaves and roots of switchgrass. Using V4 16S rRNA and ITS gene as well as metagenome sequencing, we show that host genotype is significant in both, leaves and roots, and varies among sites. Microbiome composition along the rhizosphere also shifts with soil depth. Furthermore, plant harvest significantly changes both, leaf surface and rhizosphere communities, which can be seen a year after the harvest event. Gene function analysis shows that rhizosphere communities are enriched in genes encoding nitrate reduction, carbohydrate transport and metabolism, motility, and sensory and signal transduction proteins relative to leaf surface communities. Our results demonstrate how genotype-environment interactions contribute to the complexity of microbiome assembly in natural environments.

BDNF rs6265 methylation and genotype interact on risk for schizophrenia.

PubMed

Ursini, Gianluca; Cavalleri, Tommaso; Fazio, Leonardo; Angrisano, Tiziana; Iacovelli, Luisa; Porcelli, Annamaria; Maddalena, Giancarlo; Punzi, Giovanna; Mancini, Marina; Gelao, Barbara; Romano, Raffaella; Masellis, Rita; Calabrese, Francesca; Rampino, Antonio; Taurisano, Paolo; Di Giorgio, Annabella; Keller, Simona; Tarantini, Letizia; Sinibaldi, Lorenzo; Quarto, Tiziana; Popolizio, Teresa; Caforio, Grazia; Blasi, Giuseppe; Riva, Marco A; De Blasi, Antonio; Chiariotti, Lorenzo; Bollati, Valentina; Bertolino, Alessandro

2016-01-01

Epigenetic mechanisms can mediate gene-environment interactions relevant for complex disorders. The BDNF gene is crucial for development and brain plasticity, is sensitive to environmental stressors, such as hypoxia, and harbors the functional SNP rs6265 (Val(66)Met), which creates or abolishes a CpG dinucleotide for DNA methylation. We found that methylation at the BDNF rs6265 Val allele in peripheral blood of healthy subjects is associated with hypoxia-related early life events (hOCs) and intermediate phenotypes for schizophrenia in a distinctive manner, depending on rs6265 genotype: in ValVal individuals increased methylation is associated with exposure to hOCs and impaired working memory (WM) accuracy, while the opposite is true for ValMet subjects. Also, rs6265 methylation and hOCs interact in modulating WM-related prefrontal activity, another intermediate phenotype for schizophrenia, with an analogous opposite direction in the 2 genotypes. Consistently, rs6265 methylation has a different association with schizophrenia risk in ValVals and ValMets. The relationships of methylation with BDNF levels and of genotype with BHLHB2 binding likely contribute to these opposite effects of methylation. We conclude that BDNF rs6265 methylation interacts with genotype to bridge early environmental exposures to adult phenotypes, relevant for schizophrenia. The study of epigenetic changes in regions containing genetic variation relevant for human diseases may have beneficial implications for the understanding of how genes are actually translated into phenotypes.

Effect of Resveratrol, a SIRT1 Activator, on the Interactions of the CLOCK/BMAL1 Complex

PubMed Central

Park, Insung; Lee, Yool; Kim, Hee-Dae

2014-01-01

Background In mammals, the CLOCK/BMAL1 heterodimer is a key transcription factor complex that drives the cyclic expression of clock-controlled genes involved in various physiological functions and behavioral consequences. Recently, a growing number of studies have reported a molecular link between the circadian clock and metabolism. In the present study, we explored the regulatory effects of SIRTUIN1 (SIRT1), an NAD+-dependent deacetylase, on CLOCK/BMAL1-mediated clock gene expression. Methods To investigate the interaction between SIRT1 and CLOCK/BMAL1, we conducted bimolecular fluorescence complementation (BiFC) analyses supplemented with immunocytochemistry assays. BiFC experiments employing deletion-specific mutants of BMAL1 were used to elucidate the specific domains that are necessary for the SIRT1-BMAL1 interaction. Additionally, luciferase reporter assays were used to delineate the effects of SIRT1 on circadian gene expression. Results BiFC analysis revealed that SIRT1 interacted with both CLOCK and BMAL1 in most cell nuclei. As revealed by BiFC assays using various BMAL1 deletion mutants, the PAS-B domain of BMAL1 was essential for interaction with SIRT1. Activation of SIRT1 with resveratrol did not exert any significant change on the interaction with the CLOCK/BMAL1 complex. However, promoter analysis using Per1-Luc and Ebox-Luc reporters showed that SIRT1 significantly downregulated both promoter activities. This inhibitory effect was intensified by treatment with resveratrol, indicating a role for SIRT1 and its activator in CLOCK/BMAL1-mediated transcription of clock genes. Conclusion These results suggest that SIRT1 may form a regulatory complex with CLOCK/BMAL1 that represses clock gene expression, probably via deacetylase activity. PMID:25309798

Differences and similarities in the serotonergic diathesis for suicide attempts and mood disorders: a 22-year longitudinal gene-environment study.

PubMed

Brezo, J; Bureau, A; Mérette, C; Jomphe, V; Barker, E D; Vitaro, F; Hébert, M; Carbonneau, R; Tremblay, R E; Turecki, G

2010-08-01

To investigate similarities and differences in the serotonergic diathesis for mood disorders and suicide attempts, we conducted a study in a cohort followed longitudinally for 22 years. A total of 1255 members of this cohort, which is representative of the French-speaking population of Quebec, were investigated. Main outcome measures included (1) mood disorders (bipolar disorder and major depression) and suicide attempts by early adulthood; (2) odds ratios and probabilities associated with 143 single nucleotide polymorphisms in 11 serotonergic genes, acting directly or as moderators in gene-environment interactions with childhood sexual or childhood physical abuse (CPA), and in gene-gene interactions; (3) regression coefficients for putative endophenotypes for mood disorders (childhood anxiousness) and suicide attempts (childhood disruptiveness). Five genes showed significant adjusted effects (HTR2A, TPH1, HTR5A, SLC6A4 and HTR1A). Of these, HTR2A variation influenced both suicide attempts and mood disorders, although through different mechanisms. In suicide attempts, HTR2A variants (rs6561333, rs7997012 and rs1885884) were involved through interactions with histories of sexual and physical abuse whereas in mood disorders through one main effect (rs9316235). In terms of phenotype-specific contributions, TPH1 variation (rs10488683) was relevant only in the diathesis for suicide attempts. Three genes contributed exclusively to mood disorders, one through a main effect (HTR5A (rs1657268)) and two through gene-environment interactions with CPA (HTR1A (rs878567) and SLC6A4 (rs3794808)). Childhood anxiousness did not mediate the effects of HTR2A and HTR5A on mood disorders, nor did childhood disruptiveness mediate the effects of TPH1 on suicide attempts. Of the serotonergic genes implicated in mood disorders and suicidal behaviors, four exhibited phenotype-specific effects, suggesting that despite their high concordance and common genetic determinants, suicide attempts and mood disorders may also have partially independent etiological pathways. To identify where these pathways diverge, we need to understand the differential, phenotype-specific gene-environment interactions such as the ones observed in the present study, using suitably powered samples.

Transcriptomic Insights into Phenological Development and Cold Tolerance of Wheat Grown in the Field1[OPEN

PubMed Central

Li, Qiang; Byrns, Brook; Badawi, Mohamed A.; Diallo, Abdoulaye Banire; Danyluk, Jean; Sarhan, Fathey; Zou, Jitao

2018-01-01

Cold acclimation and winter survival in cereal species is determined by complicated environmentally regulated gene expression. However, studies investigating these complex cold responses are mostly conducted in controlled environments that only consider the responses to single environmental variables. In this study, we have comprehensively profiled global transcriptional responses in crowns of field-grown spring and winter wheat (Triticum aestivum) genotypes and their near-isogenic lines with the VRN-A1 alleles swapped. This in-depth analysis revealed multiple signaling, interactive pathways that influence cold tolerance and phenological development to optimize plant growth and development in preparation for a wide range of over-winter stresses. Investigation of genetic differences at the VRN-A1 locus revealed that a vernalization requirement maintained a higher level of cold response pathways while VRN-A1 genetically promoted floral development. Our results also demonstrated the influence of genetic background on the expression of cold and flowering pathways. The link between delayed shoot apex development and the induction of cold tolerance was reflected by the gradual up-regulation of abscisic acid-dependent and C-REPEAT-BINDING FACTOR pathways. This was accompanied by the down-regulation of key genes involved in meristem development as the autumn progressed. The chromosome location of differentially expressed genes between the winter and spring wheat genetic backgrounds showed a striking pattern of biased gene expression on chromosomes 6A and 6D, indicating a transcriptional regulation at the genome level. This finding adds to the complexity of the genetic cascades and gene interactions that determine the evolutionary patterns of both phenological development and cold tolerance traits in wheat. PMID:29259104

Integrating genetic and toxicogenomic information for determining underlying susceptibility to developmental disorders.

PubMed

Robinson, Joshua F; Port, Jesse A; Yu, Xiaozhong; Faustman, Elaine M

2010-10-01

To understand the complex etiology of developmental disorders, an understanding of both genetic and environmental risk factors is needed. Human and rodent genetic studies have identified a multitude of gene candidates for specific developmental disorders such as neural tube defects (NTDs). With the emergence of toxicogenomic-based assessments, scientists now also have the ability to compare and understand the expression of thousands of genes simultaneously across strain, time, and exposure in developmental models. Using a systems-based approach in which we are able to evaluate information from various parts and levels of the developing organism, we propose a framework for integrating genetic information with toxicogenomic-based studies to better understand gene-environmental interactions critical for developmental disorders. This approach has allowed us to characterize candidate genes in the context of variables critical for determining susceptibility such as strain, time, and exposure. Using a combination of toxicogenomic studies and complementary bioinformatic tools, we characterize NTD candidate genes during normal development by function (gene ontology), linked phenotype (disease outcome), location, and expression (temporally and strain-dependent). In addition, we show how environmental exposures (cadmium, methylmercury) can influence expression of these genes in a strain-dependent manner. Using NTDs as an example of developmental disorder, we show how simple integration of genetic information from previous studies into the standard microarray design can enhance analysis of gene-environment interactions to better define environmental exposure-disease pathways in sensitive and resistant mouse strains. © Wiley-Liss, Inc.

Early Adverse Environments and Genetic Influences on Age at First Sex: Evidence for Gene × Environment Interaction

ERIC Educational Resources Information Center

Carlson, Marie D.; Mendle, Jane; Harden, K. Paige

2014-01-01

Youth who experience adverse environments in early life initiate sexual activity at a younger age, on average, than those from more advantaged circumstances. Evolutionary theorists have posited that ecological stress precipitates earlier reproductive and sexual onset, but it is unclear how stressful environments interact with genetic influences on…

Quantitative genetic-interaction mapping in mammalian cells

PubMed Central

Roguev, Assen; Talbot, Dale; Negri, Gian Luca; Shales, Michael; Cagney, Gerard; Bandyopadhyay, Sourav; Panning, Barbara; Krogan, Nevan J

2013-01-01

Mapping genetic interactions (GIs) by simultaneously perturbing pairs of genes is a powerful tool for understanding complex biological phenomena. Here we describe an experimental platform for generating quantitative GI maps in mammalian cells using a combinatorial RNA interference strategy. We performed ~11,000 pairwise knockdowns in mouse fibroblasts, focusing on 130 factors involved in chromatin regulation to create a GI map. Comparison of the GI and protein-protein interaction (PPI) data revealed that pairs of genes exhibiting positive GIs and/or similar genetic profiles were predictive of the corresponding proteins being physically associated. The mammalian GI map identified pathways and complexes but also resolved functionally distinct submodules within larger protein complexes. By integrating GI and PPI data, we created a functional map of chromatin complexes in mouse fibroblasts, revealing that the PAF complex is a central player in the mammalian chromatin landscape. PMID:23407553

Bisphenol-A and Female Infertility: A Possible Role of Gene-Environment Interactions

PubMed Central

Huo, Xiaona; Chen, Dan; He, Yonghua; Zhu, Wenting; Zhou, Wei; Zhang, Jun

2015-01-01

Background: Bisphenol-A (BPA) is widely used and ubiquitous in the environment. Animal studies indicate that BPA affects reproduction, however, the gene-environment interaction mechanism(s) involved in this association remains unclear. We performed a literature review to summarize the evidence on this topic. Methods: A comprehensive search was conducted in PubMed using as keywords BPA, gene, infertility and female reproduction. Full-text articles in both human and animals published in English prior to December 2014 were selected. Results: Evidence shows that BPA can interfere with endocrine function of hypothalamic-pituitary axis, such as by changing gonadotropin-releasing hormones (GnRH) secretion in hypothalamus and promoting pituitary proliferation. Such actions affect puberty, ovulation and may even result in infertility. Ovary, uterus and other reproductive organs are also targets of BPA. BPA exposure impairs the structure and functions of female reproductive system in different times of life cycle and may contribute to infertility. Both epidemiological and experimental evidences demonstrate that BPA affects reproduction-related gene expression and epigenetic modification that are closely associated with infertility. The detrimental effects on reproduction may be lifelong and transgenerational. Conclusions: Evidence on gene-environment interactions, especially from human studies, is still limited. Further research on this topic is warranted. PMID:26371021

Rigorous tests of gene-environment interactions in a lab study of the oxytocin receptor gene (OXTR), alcohol exposure, and aggression.

PubMed

LoParo, Devon; Johansson, Ada; Walum, Hasse; Westberg, Lars; Santtila, Pekka; Waldman, Irwin

2016-07-01

Naturalistic studies of gene-environment interactions (G X E) have been plagued by several limitations, including difficulty isolating specific environmental risk factors from other correlated aspects of the environment, gene-environment correlation (rGE ), and the use of a single genetic variant to represent the influence of a gene. We present results from 235 Finnish young men in two lab studies of aggression and alcohol challenge that attempt to redress these limitations of the extant G X E literature. Specifically, we use a latent variable modeling approach in an attempt to more fully account for genetic variation across the oxytocin receptor gene (OXTR) and to robustly test its main effects on aggression and its interaction with alcohol exposure. We also modeled aggression as a latent variable comprising various indices, including the average and maximum levels of aggression, the earliest trial on which aggression was expressed, and the proportion of trials on which the minimum and maximum levels of aggression were expressed. The best fitting model for the genetic variation across OXTR included six factors derived from an exploratory factor analysis, roughly corresponding to six haplotype blocks. Aggression levels were higher on trials in which participants were administered alcohol, won, or were provoked. There was a significant main effect of OXTR on aggression across studies after controlling for covariates. The interaction of OXTR and alcohol was also significant across studies, such that OXTR had stronger effects on aggression in the alcohol administration condition. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Differential sensitivity to the environment: contribution of cognitive biases and genes to psychological wellbeing.

PubMed

Fox, E; Beevers, C G

2016-12-01

Negative cognitive biases and genetic variation have been associated with risk of psychopathology in largely independent lines of research. Here, we discuss ways in which these dynamic fields of research might be fruitfully combined. We propose that gene by environment (G × E) interactions may be mediated by selective cognitive biases and that certain forms of genetic 'reactivity' or 'sensitivity' may represent heightened sensitivity to the learning environment in a 'for better and for worse' manner. To progress knowledge in this field, we recommend including assessments of cognitive processing biases; examining G × E interactions in 'both' negative and positive environments; experimentally manipulating the environment when possible; and moving beyond single-gene effects to assess polygenic sensitivity scores. We formulate a new methodological framework encapsulating cognitive and genetic factors in the development of both psychopathology and optimal wellbeing that holds long-term promise for the development of new personalized therapies.

Quantitative nanoparticle tracking: applications to nanomedicine.

PubMed

Huang, Feiran; Dempsey, Christopher; Chona, Daniela; Suh, Junghae

2011-06-01

Particle tracking is an invaluable technique to extract quantitative and qualitative information regarding the transport of nanomaterials through complex biological environments. This technique can be used to probe the dynamic behavior of nanoparticles as they interact with and navigate through intra- and extra-cellular barriers. In this article, we focus on the recent developments in the application of particle-tracking technology to nanomedicine, including the study of synthetic and virus-based materials designed for gene and drug delivery. Specifically, we cover research where mean square displacements of nanomaterial transport were explicitly determined in order to quantitatively assess the transport of nanoparticles through biological environments. Particle-tracking experiments can provide important insights that may help guide the design of more intelligent and effective diagnostic and therapeutic nanoparticles.

Minireview: Epigenetics of Obesity and Diabetes in Humans

PubMed Central

Slomko, Howard; Heo, Hye J.

2012-01-01

Understanding the determinants of human health and disease is overwhelmingly complex, particularly for common, late-onset, chronic disorders, such as obesity and diabetes. Elucidating the genetic and environmental factors that influence susceptibility to disruptions in energy homeostasis and metabolic regulation remain a challenge, and progress will entail the integration of multiple assessments of temporally dynamic environmental exposures in the context of each individual's genotype. To meet this challenge, researchers are increasingly exploring the epigenome, which is the malleable interface of gene-environment interactions. Epigenetic variation, whether innate or induced, contributes to variation in gene expression, the range of potential individual responses to internal and external cues, and risk for metabolic disease. Ultimately, advancement in our understanding of chronic disease susceptibility in humans will depend on refinement of exposure assessment tools and systems biology approaches to interpretation. In this review, we present recent progress in epigenetics of human obesity and diabetes, existing challenges, and the potential for new approaches to unravel the complex biology of metabolic dysregulation. PMID:22253427

Minireview: Epigenetics of obesity and diabetes in humans.

PubMed

Slomko, Howard; Heo, Hye J; Einstein, Francine H

2012-03-01

Understanding the determinants of human health and disease is overwhelmingly complex, particularly for common, late-onset, chronic disorders, such as obesity and diabetes. Elucidating the genetic and environmental factors that influence susceptibility to disruptions in energy homeostasis and metabolic regulation remain a challenge, and progress will entail the integration of multiple assessments of temporally dynamic environmental exposures in the context of each individual's genotype. To meet this challenge, researchers are increasingly exploring the epigenome, which is the malleable interface of gene-environment interactions. Epigenetic variation, whether innate or induced, contributes to variation in gene expression, the range of potential individual responses to internal and external cues, and risk for metabolic disease. Ultimately, advancement in our understanding of chronic disease susceptibility in humans will depend on refinement of exposure assessment tools and systems biology approaches to interpretation. In this review, we present recent progress in epigenetics of human obesity and diabetes, existing challenges, and the potential for new approaches to unravel the complex biology of metabolic dysregulation.

Pathology supported genetic testing and treatment of cardiovascular disease in middle age for prevention of Alzheimer's disease.

PubMed

Kotze, Maritha J; van Rensburg, Susan J

2012-09-01

Chronic, multi-factorial conditions caused by a complex interaction between genetic and environmental risk factors frequently share common disease mechanisms, as evidenced by an overlap between genetic risk factors for cardiovascular disease (CVD) and Alzheimer's disease (AD). Single nucleotide polymorphisms (SNPs) in several genes including ApoE, MTHFR, HFE and FTO are known to increase the risk of both conditions. The E4 allele of the ApoE polymorphism is the most extensively studied risk factor for AD and increases the risk of coronary heart disease by approximately 40%. It furthermore displays differential therapeutic responses with use of cholesterol-lowering statins and acetylcholinesterase inhibitors, which may also be due to variation in the CYP2D6 gene in some patients. Disease expression may be triggered by gene-environment interaction causing conversion of minor metabolic abnormalities into major brain disease due to cumulative risk. A growing body of evidence supports the assessment and treatment of CVD risk factors in midlife as a preventable cause of cognitive decline, morbidity and mortality in old age. In this review, the concept of pathology supported genetic testing (PSGT) for CVD is described in this context. PSGT combines DNA testing with biochemical measurements to determine gene expression and to monitor response to treatment. The aim is to diagnose treatable disease subtypes of complex disorders, facilitate prevention of cumulative risk and formulate intervention strategies guided from the genetic background. CVD provides a model to address the lifestyle link in most chronic diseases with a genetic component. Similar preventative measures would apply for optimisation of heart and brain health.

A divalent interaction between HPS1 and HPS4 is required for the formation of the biogenesis of lysosome-related organelle complex-3 (BLOC-3).

PubMed

Carmona-Rivera, Carmelo; Simeonov, Dimitre R; Cardillo, Nicholas D; Gahl, William A; Cadilla, Carmen L

2013-03-01

Hermansky-Pudlak syndrome (HPS) is a group of rare autosomal recessive disorders characterized by oculocutaneous albinism, a bleeding tendency, and sporadic pulmonary fibrosis, granulomatous colitis or infections. Nine HPS-causing genes have been identified in humans. HPS-1 is the most severe subtype with a prevalence of ~1/1800 in northwest Puerto Rico due to a founder mutation in the HPS1 gene. Mutations in HPS genes affect the biogenesis of lysosome-related organelles such as melanosomes in melanocytes and platelet dense granules. Two of these genes (HPS1 and HPS4) encode the HPS1 and HPS4 proteins, which assemble to form a complex known as Biogenesis of Lysosome-related Organelle Complex 3 (BLOC-3). We report the identification of the interacting regions in HPS1 and HPS4 required for the formation of this complex. Two regions in HPS1, spanning amino acids 1-249 and 506-700 are required for binding to HPS4; the middle portion of HPS1 (residues 250-505) is not required for this interaction. Further interaction studies showed that the N-termini of HPS1 and HPS4 interact with each other and that a discrete region of HPS4 (residues 340-528) interacts with both the N- and C-termini of the HPS1 protein. Several missense mutations found in HPS-1 patients did not affect interaction with HPS4, but some mutations involving regions interacting with HPS4 caused instability of HPS1. These observations extend our understanding of BLOC-3 assembly and represent an important first step in the identification of domains responsible for the biogenesis of lysosome-related organelles. Copyright © 2012 Elsevier B.V. All rights reserved.

Comparative genomics of free-living Gammaproteobacteria: pathogenesis-related genes or interaction-related genes?

PubMed

Vázquez-Rosas-Landa, Mirna; Ponce-Soto, Gabriel Yaxal; Eguiarte, Luis E; Souza, V

2017-07-31

Bacteria have numerous strategies to interact with themselves and with their environment, but genes associated with these interactions are usually cataloged as pathogenic. To understand the role that these genes have not only in pathogenesis but also in bacterial interactions, we compared the genomes of eight bacteria from human-impacted environments with those of free-living bacteria from the Cuatro Ciénegas Basin (CCB), a relatively pristine oligotrophic site. Fifty-one genomes from CCB bacteria, including Pseudomonas, Vibrio, Photobacterium and Aeromonas, were analyzed. We found that the CCB strains had several virulence-related genes, 15 of which were common to all strains and were related to flagella and chemotaxis. We also identified the presence of Type III and VI secretion systems, which leads us to propose that these systems play an important role in interactions among bacterial communities beyond pathogenesis. None of the CCB strains had pathogenicity islands, despite having genes associated with antibiotics. Integrons were rare, while CRISPR elements were common. The idea that pathogenicity-related genes in many cases form part of a wider strategy used by bacteria to interact with other organisms could help us to understand the role of pathogenicity-related elements in an ecological and evolutionary framework leading toward a more inclusive One Health concept. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Human genome and philosophy: what ethical challenge will human genome studies bring to the medical practices in the 21st century?

PubMed

Renzong, Q

2001-12-01

A human being or person cannot be reduced to a set of human genes, or human genome. Genetic essentialism is wrong, because as a person the entity should have self-conscious and social interaction capacity which is grown in an interpersonal relationship. Genetic determinism is wrong too, the relationship between a gene and a trait is not a linear model of causation, but rather a non-linear one. Human genome is a complexity system and functions in a complexity system of human body and a complexity of systems of natural/social environment. Genetic determinism also caused the issue of how much responsibility an agent should take for her/his action, and how much degrees of freedom will a human being have. Human genome research caused several conceptual issues. Can we call a gene 'good' or 'bad', 'superior' of 'inferior'? Is a boy who is detected to have the gene of Huntington's chorea or Alzheimer disease a patient? What should the term 'eugenics' mean? What do the terms such as 'gene therapy', 'treatment' and 'enhancement' and 'human cloning' mean etc.? The research of human genome and its application caused and will cause ethical issues. Can human genome research and its application be used for eugenics, or only for the treatment and prevention of diseases? Must the principle of informed consent/choice be insisted in human genome research and its application? How to protecting gene privacy and combating the discrimination on the basis of genes? How to promote the quality between persons, harmony between ethnic groups and peace between countries? How to establish a fair, just, equal and equitable relationship between developing and developed countries in regarding to human genome research and its application?

The psychiatric phenotype in triple X syndrome: New hypotheses illustrated in two cases

PubMed Central

Otter, Maarten; Schrander-Stumpel, Constance T. R. M.; Didden, Robert; Curfs, Leopold M. G.

2012-01-01

Background: Triple X syndrome (47,XXX or trisomy X) is a relatively frequent cytogenetic condition with a large variety of physical and behavioural phenotypes. Method: Two adult patients with a triple X karyotype are described. Results: Their karyotype was unknown until some years ago. What these patients have in common is that they were diagnosed with a broader autism phenotype, they were sexually abused, they suffer from psychotic illness and they show challenging behaviour, suicidality and a decline in occupational capacity. Discussion: These gene-environment interactions are discussed. Gene-environment interactions may explain the variety of behavioural and psychiatric phenotypes in triple X syndrome. Ongoing atypical development in adults is hypothesized. Conclusions: Gene-environment interactions and ongoing atypical development in adults should be taken into account in research concerning the psychiatric phenotype of developmental disorders, especially those involving triple X syndrome. PMID:22582855

Beyond genome-wide association studies: genetic heterogeneity and individual predisposition to cancer

PubMed Central

Galvan, Antonella; Ioannidis, John P.A.; Dragani, Tommaso A.

2010-01-01

Genome-wide association studies (GWAS) using population-based designs have identified many genetic loci associated with risk of a range of complex diseases including cancer; however, each locus exerts a very small effect and most heritability remains unexplained. Family-based pedigree studies have also suggested tentative loci linked to increased cancer risk, often characterized by pedigree-specificity. However, a comparison between the results of population-and those of family-based studies shows little concordance. Explanations for this unidentified genetic ‘dark matter’ of cancer include phenotype ascertainment issues, limited power, gene-gene and gene-environment interactions, population heterogeneity, parent-of-origin-specific effects, rare and unexplored variants. Many of these reasons converge towards the concept of genetic heterogeneity that might implicate hundreds of genetic variants in regulating cancer risk. Dissecting the dark matter is a challenging task. Further insights can be gained from both population association and pedigree studies. PMID:20106545

Volatile affairs in microbial interactions

PubMed Central

Schmidt, Ruth; Cordovez, Viviane; de Boer, Wietse; Raaijmakers, Jos; Garbeva, Paolina

2015-01-01

Microorganisms are important factors in shaping our environment. One key characteristic that has been neglected for a long time is the ability of microorganisms to release chemically diverse volatile compounds. At present, it is clear that the blend of volatiles released by microorganisms can be very complex and often includes many unknown compounds for which the chemical structures remain to be elucidated. The biggest challenge now is to unravel the biological and ecological functions of these microbial volatiles. There is increasing evidence that microbial volatiles can act as infochemicals in interactions among microbes and between microbes and their eukaryotic hosts. Here, we review and discuss recent advances in understanding the natural roles of volatiles in microbe–microbe interactions. Specific emphasis will be given to the antimicrobial activities of microbial volatiles and their effects on bacterial quorum sensing, motility, gene expression and antibiotic resistance. PMID:26023873

The developmental origins of externalizing behavioral problems: parental disengagement and the role of gene-environment interplay.

PubMed

Boutwell, Brian B; Beaver, Kevin M; Barnes, James C; Vaske, Jamie

2012-05-30

A line of research has revealed that the influence of genes on behavioral development is closely tied to environmental experiences. Known as gene-environment interaction, research in this area is beginning to reveal that variation in parenting behaviors may moderate genetic influences on antisocial behaviors in children. Despite growing interest in gene-environment interaction research, little evidence exists concerning the role of maternal disengagement in the conditioning of genetic influences on childhood behavioral problems. The current study is intended to address this gap in the literature by analyzing a sample of twin pairs drawn from the Early Childhood Longitudinal Study, Birth Cohort (ECLS-B). Analysis of the ECLS-B provided evidence that maternal disengagement moderates genetic influences on the development of externalizing problems. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Complexity in models of cultural niche construction with selection and homophily.

PubMed

Creanza, Nicole; Feldman, Marcus W

2014-07-22

Niche construction is the process by which organisms can alter the ecological environment for themselves, their descendants, and other species. As a result of niche construction, differences in selection pressures may be inherited across generations. Homophily, the tendency of like phenotypes to mate or preferentially associate, influences the evolutionary dynamics of these systems. Here we develop a model that includes selection and homophily as independent culturally transmitted traits that influence the fitness and mate choice determined by another focal cultural trait. We study the joint dynamics of a focal set of beliefs, a behavior that can differentially influence the fitness of those with certain beliefs, and a preference for partnering based on similar beliefs. Cultural transmission, selection, and homophily interact to produce complex evolutionary dynamics, including oscillations, stable polymorphisms of all cultural phenotypes, and simultaneous stability of oscillation and fixation, which have not previously been observed in models of cultural evolution or gene-culture interactions. We discuss applications of this model to the interaction of beliefs and behaviors regarding education, contraception, and animal domestication.

The metazoan Mediator co-activator complex as an integrative hub for transcriptional regulation.

PubMed

Malik, Sohail; Roeder, Robert G

2010-11-01

The Mediator is an evolutionarily conserved, multiprotein complex that is a key regulator of protein-coding genes. In metazoan cells, multiple pathways that are responsible for homeostasis, cell growth and differentiation converge on the Mediator through transcriptional activators and repressors that target one or more of the almost 30 subunits of this complex. Besides interacting directly with RNA polymerase II, Mediator has multiple functions and can interact with and coordinate the action of numerous other co-activators and co-repressors, including those acting at the level of chromatin. These interactions ultimately allow the Mediator to deliver outputs that range from maximal activation of genes to modulation of basal transcription to long-term epigenetic silencing.

Transcriptional and Physiological Characterizations of Escherichia coli MG1655 that have been grown under Low Shear Stress Environment for 1000 Generations

NASA Astrophysics Data System (ADS)

Karouia, Fathi; Tirumalai, Madhan R.; Nelman-Gonzalez, Mayra A.; Sams, Clarence F.; Ott, Mark C.; Pierson, Duane L.; Fofanov, Yuriy; Willson, Richard C.; Fox, George E.

Human space travelers experience a unique environment that affects homeostasis and physio-logic adaptation. One of the important regulatory biology interactions affected by space flight is the alteration of the immune response. As such, the impairment of the immune system may lead to higher risk of bacterial and/or viral infection during human space flight missions. Mi-crobiological contaminants have been a source of concern over the years for NASA and there is evidence to suggest that microbes in space do not behave like they do on Earth. Previ-ous studies have examined the physiological response of bacteria when exposed to short-term microgravity either during spaceflight or in a Low Shear Modeled Microgravity (LSMMG) en-vironment. Exposure to these environments has been found to induce increased resistance to stresses and antibiotics, and in one case increase of virulence. As NASA increases the duration of space flight missions and is starting to envision human presence on the lunar surface and Mars, it becomes legitimate to question the long-term effects of microgravity on bacteria. The effect of long-term exposure to LSMMG on microbial gene expression and physiology in Escherichia coli (E. coli) is being examined using functional genomics, and molecular tech-niques. In previous E. coli short term studies, reproducible changes in transcription were seen but no direct responses to changes in the gravity vector were identified. Instead, absence of shear and a randomized gravity vector appeared to cause local extra-cellular environmental changes, which elicited cellular responses. In order to evaluate the long-term effects of micro-gravity on bacteria, E. coli was grown under simulated microgravity for 1000 generations and gene expression patterns and cellular physiology were analyzed in comparison with short-term exposure. The analysis revealed that the long-term response differed significantly from the short-term exposure and 357 genes were expressed significantly differently. Fimbriae encoding genes were significantly up-regulated whereas genes encoding the flagellar motor complex were down-regulated. Additionally, 81 significantly expressed genes have been implicated in and/or associated with biofilm formation. The remaining up-regulated genes seemed to be involved in a response that triggered expression of genes associated with the type II secretion complex. This complex has been involved in virulence factors and members of the multidrug efflux system which confer resistance to a multitude of antimicrobial agents and antibiotics. Biofilm formation and the aggregation of cells were evaluated by scanning electron microscopy (SEM). The analysis revealed that extracellular matrix and complex cellular networking were present among cells that were exposed to the long-term LSMMG environment. In addition the response to a variety of stresses and antibiotics were examined. Significant differences were seen between long-term exposure to LSMMG and the short-term control. Changes in expression may predispose the cells to more efficiently attach to surfaces and/or other cells and thereby confer resistance to antibiotics. Future studies will seek to determine the extent to which the long-term adaptation is influenced by genomic changes. These studies will contribute to the knowledge base needed to develop countermeasures that will decrease the risks associated with astronaut health and mission integrity that are presented by microorganisms.

The Interaction Network Ontology-supported modeling and mining of complex interactions represented with multiple keywords in biomedical literature.

PubMed

Özgür, Arzucan; Hur, Junguk; He, Yongqun

2016-01-01

The Interaction Network Ontology (INO) logically represents biological interactions, pathways, and networks. INO has been demonstrated to be valuable in providing a set of structured ontological terms and associated keywords to support literature mining of gene-gene interactions from biomedical literature. However, previous work using INO focused on single keyword matching, while many interactions are represented with two or more interaction keywords used in combination. This paper reports our extension of INO to include combinatory patterns of two or more literature mining keywords co-existing in one sentence to represent specific INO interaction classes. Such keyword combinations and related INO interaction type information could be automatically obtained via SPARQL queries, formatted in Excel format, and used in an INO-supported SciMiner, an in-house literature mining program. We studied the gene interaction sentences from the commonly used benchmark Learning Logic in Language (LLL) dataset and one internally generated vaccine-related dataset to identify and analyze interaction types containing multiple keywords. Patterns obtained from the dependency parse trees of the sentences were used to identify the interaction keywords that are related to each other and collectively represent an interaction type. The INO ontology currently has 575 terms including 202 terms under the interaction branch. The relations between the INO interaction types and associated keywords are represented using the INO annotation relations: 'has literature mining keywords' and 'has keyword dependency pattern'. The keyword dependency patterns were generated via running the Stanford Parser to obtain dependency relation types. Out of the 107 interactions in the LLL dataset represented with two-keyword interaction types, 86 were identified by using the direct dependency relations. The LLL dataset contained 34 gene regulation interaction types, each of which associated with multiple keywords. A hierarchical display of these 34 interaction types and their ancestor terms in INO resulted in the identification of specific gene-gene interaction patterns from the LLL dataset. The phenomenon of having multi-keyword interaction types was also frequently observed in the vaccine dataset. By modeling and representing multiple textual keywords for interaction types, the extended INO enabled the identification of complex biological gene-gene interactions represented with multiple keywords.

Social Environmental Variation, Plasticity Genes, and Aggression: Evidence for the Differential Susceptibility Hypothesis

PubMed Central

Simons, Ronald L.; Lei, Man Kit; Beach, Steven R.H.; Brody, Gene H.; Philibert, Robert A.; Gibbons, Frederick X.

2011-01-01

Although G×E studies are typically based on the assumption that some individuals possess genetic variants that enhance their vulnerability to environmental adversity, the differential susceptibility perspective posits that these individuals are simply more susceptible to environmental influence than others. An important implication of this model is that those persons most vulnerable to adverse social environments are the same ones who reap the most benefit from environmental support. The present study tested several implications of this proposition. Using longitudinal data from a sample of several hundred African Americans, we found that relatively common variants of the dopamine receptor gene and the serotonin transporter gene interact with social environmental conditions to predict aggression in a manner consonant with differential susceptibility. When the social environment was adverse, individuals with these genetic variants manifested more aggression than other genotypes, whereas when the environment was supportive they demonstrated less aggression than other genotypes. Further, we found that these genetic variants interact with environmental conditions to foster various cognitive schemas and emotions in a manner consistent with differential susceptibility and that a latent construct formed by these schemas and emotions mediated the effect of gene by environment interaction on aggression. PMID:22199399

Adenovirus Small E1A Employs the Lysine Acetylases p300/CBP and Tumor Suppressor Rb to Repress Select Host Genes and Promote Productive Virus Infection

PubMed Central

Ferrari, Roberto; Gou, Dawei; Jawdekar, Gauri; Johnson, Sarah A.; Nava, Miguel; Su, Trent; Yousef, Ahmed F.; Zemke, Nathan R.; Pellegrini, Matteo; Kurdistani, Siavash K.; Berk, Arnold J.

2015-01-01

SUMMARY Oncogenic transformation by adenovirus small e1a depends on simultaneous interactions with the host lysine acetylases p300/CBP and the tumor suppressor RB. How these interactions influence cellular gene expression remains unclear. We find that e1a displaces RBs from E2F transcription factors and promotes p300 acetylation of RB1 K873/K874 to lock it into a repressing conformation that interacts with repressive chromatin-modifying enzymes. These repressing p300-e1a-RB1 complexes specifically interact with host genes that have unusually high p300 association within the gene body. The TGFβ-, TNF-, and interleukin-signaling pathway components are enriched among such p300-targeted genes. The p300-e1a-RB1 complex condenses chromatin in a manner dependent on HDAC activity, p300 lysine acetylase activity, the p300 bromodomain, and RB K873/K874 and e1a K239 acetylation to repress host genes that would otherwise inhibit productive virus infection. Thus, adenovirus employs e1a to repress host genes that interfere with viral replication. PMID:25525796

Syntrophic growth of Desulfovibrio alaskensis requires genes for H2 and formate metabolism as well as those for flagellum and biofilm formation.

PubMed

Krumholz, Lee R; Bradstock, Peter; Sheik, Cody S; Diao, Yiwei; Gazioglu, Ozcan; Gorby, Yuri; McInerney, Michael J

2015-04-01

In anaerobic environments, mutually beneficial metabolic interactions between microorganisms (syntrophy) are essential for oxidation of organic matter to carbon dioxide and methane. Syntrophic interactions typically involve a microorganism degrading an organic compound to primary fermentation by-products and sources of electrons (i.e., formate, hydrogen, or nanowires) and a partner producing methane or respiring the electrons via alternative electron accepting processes. Using a transposon gene mutant library of the sulfate-reducing Desulfovibrio alaskensis G20, we screened for mutants incapable of serving as the electron-accepting partner of the butyrate-oxidizing bacterium, Syntrophomonas wolfei. A total of 17 gene mutants of D. alaskensis were identified as incapable of serving as the electron-accepting partner. The genes identified predominantly fell into three categories: membrane surface assembly, flagellum-pilus synthesis, and energy metabolism. Among these genes required to serve as the electron-accepting partner, the glycosyltransferase, pilus assembly protein (tadC), and flagellar biosynthesis protein showed reduced biofilm formation, suggesting that each of these components is involved in cell-to-cell interactions. Energy metabolism genes encoded proteins primarily involved in H2 uptake and electron cycling, including a rhodanese-containing complex that is phylogenetically conserved among sulfate-reducing Deltaproteobacteria. Utilizing an mRNA sequencing approach, analysis of transcript abundance in wild-type axenic and cocultures confirmed that genes identified as important for serving as the electron-accepting partner were more highly expressed under syntrophic conditions. The results imply that sulfate-reducing microorganisms require flagellar and outer membrane components to effectively couple to their syntrophic partners; furthermore, H2 metabolism is essential for syntrophic growth of D. alaskensis G20. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Syntrophic Growth of Desulfovibrio alaskensis Requires Genes for H2 and Formate Metabolism as Well as Those for Flagellum and Biofilm Formation

PubMed Central

Bradstock, Peter; Sheik, Cody S.; Diao, Yiwei; Gazioglu, Ozcan; Gorby, Yuri; McInerney, Michael J.

2015-01-01

In anaerobic environments, mutually beneficial metabolic interactions between microorganisms (syntrophy) are essential for oxidation of organic matter to carbon dioxide and methane. Syntrophic interactions typically involve a microorganism degrading an organic compound to primary fermentation by-products and sources of electrons (i.e., formate, hydrogen, or nanowires) and a partner producing methane or respiring the electrons via alternative electron accepting processes. Using a transposon gene mutant library of the sulfate-reducing Desulfovibrio alaskensis G20, we screened for mutants incapable of serving as the electron-accepting partner of the butyrate-oxidizing bacterium, Syntrophomonas wolfei. A total of 17 gene mutants of D. alaskensis were identified as incapable of serving as the electron-accepting partner. The genes identified predominantly fell into three categories: membrane surface assembly, flagellum-pilus synthesis, and energy metabolism. Among these genes required to serve as the electron-accepting partner, the glycosyltransferase, pilus assembly protein (tadC), and flagellar biosynthesis protein showed reduced biofilm formation, suggesting that each of these components is involved in cell-to-cell interactions. Energy metabolism genes encoded proteins primarily involved in H2 uptake and electron cycling, including a rhodanese-containing complex that is phylogenetically conserved among sulfate-reducing Deltaproteobacteria. Utilizing an mRNA sequencing approach, analysis of transcript abundance in wild-type axenic and cocultures confirmed that genes identified as important for serving as the electron-accepting partner were more highly expressed under syntrophic conditions. The results imply that sulfate-reducing microorganisms require flagellar and outer membrane components to effectively couple to their syntrophic partners; furthermore, H2 metabolism is essential for syntrophic growth of D. alaskensis G20. PMID:25616787

Sensory trait variation in an echolocating bat suggests roles for both selection and plasticity

PubMed Central

2014-01-01

Background Across heterogeneous environments selection and gene flow interact to influence the rate and extent of adaptive trait evolution. This complex relationship is further influenced by the rarely considered role of phenotypic plasticity in the evolution of adaptive population variation. Plasticity can be adaptive if it promotes colonization and survival in novel environments and in doing so may increase the potential for future population differentiation via selection. Gene flow between selectively divergent environments may favour the evolution of phenotypic plasticity or conversely, plasticity itself may promote gene flow, leading to a pattern of trait differentiation in the presence of gene flow. Variation in sensory traits is particularly informative in testing the role of environment in trait and population differentiation. Here we test the hypothesis of ‘adaptive differentiation with minimal gene flow’ in resting echolocation frequencies (RF) of Cape horseshoe bats (Rhinolophus capensis) across a gradient of increasingly cluttered habitats. Results Our analysis reveals a geographically structured pattern of increasing RF from open to highly cluttered habitats in R. capensis; however genetic drift appears to be a minor player in the processes influencing this pattern. Although Bayesian analysis of population structure uncovered a number of spatially defined mitochondrial groups and coalescent methods revealed regional-scale gene flow, phylogenetic analysis of mitochondrial sequences did not correlate with RF differentiation. Instead, habitat discontinuities between biomes, and not genetic and geographic distances, best explained echolocation variation in this species. We argue that both selection for increased detection distance in relatively less cluttered habitats and adaptive phenotypic plasticity may have influenced the evolution of matched echolocation frequencies and habitats across different populations. Conclusions Our study reveals significant sensory trait differentiation in the presence of historical gene flow and suggests roles for both selection and plasticity in the evolution of echolocation variation in R. capensis. These results highlight the importance of population level analyses to i) illuminate the subtle interplay between selection, plasticity and gene flow in the evolution of adaptive traits and ii) demonstrate that evolutionary processes may act simultaneously and that their relative influence may vary across different environments. PMID:24674227

Sensory trait variation in an echolocating bat suggests roles for both selection and plasticity.

PubMed

Odendaal, Lizelle J; Jacobs, David S; Bishop, Jacqueline M

2014-03-27

Across heterogeneous environments selection and gene flow interact to influence the rate and extent of adaptive trait evolution. This complex relationship is further influenced by the rarely considered role of phenotypic plasticity in the evolution of adaptive population variation. Plasticity can be adaptive if it promotes colonization and survival in novel environments and in doing so may increase the potential for future population differentiation via selection. Gene flow between selectively divergent environments may favour the evolution of phenotypic plasticity or conversely, plasticity itself may promote gene flow, leading to a pattern of trait differentiation in the presence of gene flow. Variation in sensory traits is particularly informative in testing the role of environment in trait and population differentiation. Here we test the hypothesis of 'adaptive differentiation with minimal gene flow' in resting echolocation frequencies (RF) of Cape horseshoe bats (Rhinolophus capensis) across a gradient of increasingly cluttered habitats. Our analysis reveals a geographically structured pattern of increasing RF from open to highly cluttered habitats in R. capensis; however genetic drift appears to be a minor player in the processes influencing this pattern. Although Bayesian analysis of population structure uncovered a number of spatially defined mitochondrial groups and coalescent methods revealed regional-scale gene flow, phylogenetic analysis of mitochondrial sequences did not correlate with RF differentiation. Instead, habitat discontinuities between biomes, and not genetic and geographic distances, best explained echolocation variation in this species. We argue that both selection for increased detection distance in relatively less cluttered habitats and adaptive phenotypic plasticity may have influenced the evolution of matched echolocation frequencies and habitats across different populations. Our study reveals significant sensory trait differentiation in the presence of historical gene flow and suggests roles for both selection and plasticity in the evolution of echolocation variation in R. capensis. These results highlight the importance of population level analyses to i) illuminate the subtle interplay between selection, plasticity and gene flow in the evolution of adaptive traits and ii) demonstrate that evolutionary processes may act simultaneously and that their relative influence may vary across different environments.

Genome-Wide Association Study (GWAS) and Genome-Wide Environment Interaction Study (GWEIS) of Depressive Symptoms in African American and Hispanic/Latina Women

PubMed Central

Dunn, Erin C.; Wiste, Anna; Radmanesh, Farid; Almli, Lynn M.; Gogarten, Stephanie M.; Sofer, Tamar; Faul, Jessica D.; Kardia, Sharon L.R.; Smith, Jennifer A.; Weir, David R.; Zhao, Wei; Soare, Thomas W.; Mirza, Saira S.; Hek, Karin; Tiemeier, Henning W.; Goveas, Joseph S.; Sarto, Gloria E.; Snively, Beverly M.; Cornelis, Marilyn; Koenen, Karestan C.; Kraft, Peter; Purcell, Shaun; Ressler, Kerry J.; Rosand, Jonathan; Wassertheil-Smoller, Sylvia; Smoller, Jordan W.

2016-01-01

Background Genome-wide association studies (GWAS) have been unable to identify variants linked to depression. We hypothesized that examining depressive symptoms and considering gene-environment interaction (G×E) might improve efficiency for gene discovery. We therefore conducted a GWAS and genome-wide environment interaction study (GWEIS) of depressive symptoms. Methods Using data from the SHARe cohort of the Women’s Health Initiative, comprising African Americans (n=7179) and Hispanics/Latinas (n=3138), we examined genetic main effects and G×E with stressful life events and social support. We also conducted a heritability analysis using genome-wide complex trait analysis (GCTA). Replication was attempted in four independent cohorts. Results No SNPs achieved genome-wide significance for main effects in either discovery sample. The top signals in African Americans were rs73531535 (located 20kb from GPR139, p=5.75×10−8) and rs75407252 (intronic to CACNA2D3, p=6.99×10−7). In Hispanics/Latinas, the top signals were rs2532087 (located 27kb from CD38, p=2.44×10−7) and rs4542757 (intronic to DCC, p=7.31×10−7). In the GWEIS with stressful life events, one interaction signal was genome-wide significant in African Americans (rs4652467; p=4.10×10−10; located 14kb from CEP350). This interaction was not observed in a smaller replication cohort. Although heritability estimates for depressive symptoms and stressful life events were each less than 10%, they were strongly genetically correlated (rG=0.95), suggesting that common variation underlying depressive symptoms and stressful life event exposure, though modest on their own, were highly overlapping in this sample. Conclusions Our results underscore the need for larger samples, more GWEIS, and greater investigation into genetic and environmental determinants of depressive symptoms in minorities. PMID:27038408

GENOME-WIDE ASSOCIATION STUDY (GWAS) AND GENOME-WIDE BY ENVIRONMENT INTERACTION STUDY (GWEIS) OF DEPRESSIVE SYMPTOMS IN AFRICAN AMERICAN AND HISPANIC/LATINA WOMEN.

PubMed

Dunn, Erin C; Wiste, Anna; Radmanesh, Farid; Almli, Lynn M; Gogarten, Stephanie M; Sofer, Tamar; Faul, Jessica D; Kardia, Sharon L R; Smith, Jennifer A; Weir, David R; Zhao, Wei; Soare, Thomas W; Mirza, Saira S; Hek, Karin; Tiemeier, Henning; Goveas, Joseph S; Sarto, Gloria E; Snively, Beverly M; Cornelis, Marilyn; Koenen, Karestan C; Kraft, Peter; Purcell, Shaun; Ressler, Kerry J; Rosand, Jonathan; Wassertheil-Smoller, Sylvia; Smoller, Jordan W

2016-04-01

Genome-wide association studies (GWAS) have made little progress in identifying variants linked to depression. We hypothesized that examining depressive symptoms and considering gene-environment interaction (GxE) might improve efficiency for gene discovery. We therefore conducted a GWAS and genome-wide by environment interaction study (GWEIS) of depressive symptoms. Using data from the SHARe cohort of the Women's Health Initiative, comprising African Americans (n = 7,179) and Hispanics/Latinas (n = 3,138), we examined genetic main effects and GxE with stressful life events and social support. We also conducted a heritability analysis using genome-wide complex trait analysis (GCTA). Replication was attempted in four independent cohorts. No SNPs achieved genome-wide significance for main effects in either discovery sample. The top signals in African Americans were rs73531535 (located 20 kb from GPR139, P = 5.75 × 10(-8) ) and rs75407252 (intronic to CACNA2D3, P = 6.99 × 10(-7) ). In Hispanics/Latinas, the top signals were rs2532087 (located 27 kb from CD38, P = 2.44 × 10(-7) ) and rs4542757 (intronic to DCC, P = 7.31 × 10(-7) ). In the GEWIS with stressful life events, one interaction signal was genome-wide significant in African Americans (rs4652467; P = 4.10 × 10(-10) ; located 14 kb from CEP350). This interaction was not observed in a smaller replication cohort. Although heritability estimates for depressive symptoms and stressful life events were each less than 10%, they were strongly genetically correlated (rG = 0.95), suggesting that common variation underlying self-reported depressive symptoms and stressful life event exposure, though modest on their own, were highly overlapping in this sample. Our results underscore the need for larger samples, more GEWIS, and greater investigation into genetic and environmental determinants of depressive symptoms in minorities. © 2016 Wiley Periodicals, Inc.

Gene-gene, gene-environment, gene-nutrient interactions and single nucleotide polymorphisms of inflammatory cytokines.

PubMed

Nadeem, Amina; Mumtaz, Sadaf; Naveed, Abdul Khaliq; Aslam, Muhammad; Siddiqui, Arif; Lodhi, Ghulam Mustafa; Ahmad, Tausif

2015-05-15

Inflammation plays a significant role in the etiology of type 2 diabetes mellitus (T2DM). The rise in the pro-inflammatory cytokines is the essential step in glucotoxicity and lipotoxicity induced mitochondrial injury, oxidative stress and beta cell apoptosis in T2DM. Among the recognized markers are interleukin (IL)-6, IL-1, IL-10, IL-18, tissue necrosis factor-alpha (TNF-α), C-reactive protein, resistin, adiponectin, tissue plasminogen activator, fibrinogen and heptoglobins. Diabetes mellitus has firm genetic and very strong environmental influence; exhibiting a polygenic mode of inheritance. Many single nucleotide polymorphisms (SNPs) in various genes including those of pro and anti-inflammatory cytokines have been reported as a risk for T2DM. Not all the SNPs have been confirmed by unifying results in different studies and wide variations have been reported in various ethnic groups. The inter-ethnic variations can be explained by the fact that gene expression may be regulated by gene-gene, gene-environment and gene-nutrient interactions. This review highlights the impact of these interactions on determining the role of single nucleotide polymorphism of IL-6, TNF-α, resistin and adiponectin in pathogenesis of T2DM.

Identifying the genes of unconventional high temperature superconductors.

PubMed

Hu, Jiangping

We elucidate a recently emergent framework in unifying the two families of high temperature (high [Formula: see text]) superconductors, cuprates and iron-based superconductors. The unification suggests that the latter is simply the counterpart of the former to realize robust extended s-wave pairing symmetries in a square lattice. The unification identifies that the key ingredients (gene) of high [Formula: see text] superconductors is a quasi two dimensional electronic environment in which the d -orbitals of cations that participate in strong in-plane couplings to the p -orbitals of anions are isolated near Fermi energy. With this gene, the superexchange magnetic interactions mediated by anions could maximize their contributions to superconductivity. Creating the gene requires special arrangements between local electronic structures and crystal lattice structures. The speciality explains why high [Formula: see text] superconductors are so rare. An explicit prediction is made to realize high [Formula: see text] superconductivity in Co/Ni-based materials with a quasi two dimensional hexagonal lattice structure formed by trigonal bipyramidal complexes.

Managing Multiple Tasks in Complex, Dynamic Environments

NASA Technical Reports Server (NTRS)

Freed, Michael; Null, Cynthia H. (Technical Monitor)

1998-01-01

Sketchy planners are designed to achieve goals in realistically complex, time-pressured, and uncertain task environments. However, the ability to manage multiple, potentially interacting tasks in such environments requires extensions to the functionality these systems typically provide. This paper identifies a number of factors affecting how interacting tasks should be prioritized, interrupted, and resumed, and then describes a sketchy planner called APEX that takes account of these factors when managing multiple tasks.

Gene-Environment Correlation and Interaction in Peer Effects on Adolescent Alcohol and Tobacco Use

PubMed Central

Harden, K. Paige; Hill, Jennifer E.; Turkheimer, Eric; Emery, Robert E.

2010-01-01

Peer relationships are commonly thought to be critical for adolescent socialization, including the development of negative health behaviors such as alcohol and tobacco use. The interplay between genetic liability and peer influences on the development of adolescent alcohol and tobacco use was examined using a nationally-representative sample of adolescent sibling pairs and their best friends. Genetic factors, some of them related to an adolescent's own substance use and some of them independent of use, were associated with increased exposure to best friends with heavy substance use—a gene-environment correlation. Moreover, adolescents who were genetically liable to substance use were more vulnerable to the adverse influences of their best friends—a gene-environment interaction. PMID:18368474

Genome-wide gene–environment interaction analysis for asbestos exposure in lung cancer susceptibility

PubMed Central

Wei, Qingyi Wei

2012-01-01

Asbestos exposure is a known risk factor for lung cancer. Although recent genome-wide association studies (GWASs) have identified some novel loci for lung cancer risk, few addressed genome-wide gene–environment interactions. To determine gene–asbestos interactions in lung cancer risk, we conducted genome-wide gene–environment interaction analyses at levels of single nucleotide polymorphisms (SNPs), genes and pathways, using our published Texas lung cancer GWAS dataset. This dataset included 317 498 SNPs from 1154 lung cancer cases and 1137 cancer-free controls. The initial SNP-level P-values for interactions between genetic variants and self-reported asbestos exposure were estimated by unconditional logistic regression models with adjustment for age, sex, smoking status and pack-years. The P-value for the most significant SNP rs13383928 was 2.17×10–6, which did not reach the genome-wide statistical significance. Using a versatile gene-based test approach, we found that the top significant gene was C7orf54, located on 7q32.1 (P = 8.90×10–5). Interestingly, most of the other significant genes were located on 11q13. When we used an improved gene-set-enrichment analysis approach, we found that the Fas signaling pathway and the antigen processing and presentation pathway were most significant (nominal P < 0.001; false discovery rate < 0.05) among 250 pathways containing 17 572 genes. We believe that our analysis is a pilot study that first describes the gene–asbestos interaction in lung cancer risk at levels of SNPs, genes and pathways. Our findings suggest that immune function regulation-related pathways may be mechanistically involved in asbestos-associated lung cancer risk. Abbreviations:CIconfidence intervalEenvironmentFDRfalse discovery rateGgeneGSEAgene-set-enrichment analysisGWASgenome-wide association studiesi-GSEAimproved gene-set-enrichment analysis approachORodds ratioSNPsingle nucleotide polymorphism PMID:22637743

Interrogation of Mammalian Protein Complex Structure, Function, and Membership Using Genome-Scale Fitness Screens.

PubMed

Pan, Joshua; Meyers, Robin M; Michel, Brittany C; Mashtalir, Nazar; Sizemore, Ann E; Wells, Jonathan N; Cassel, Seth H; Vazquez, Francisca; Weir, Barbara A; Hahn, William C; Marsh, Joseph A; Tsherniak, Aviad; Kadoch, Cigall

2018-05-23

Protein complexes are assemblies of subunits that have co-evolved to execute one or many coordinated functions in the cellular environment. Functional annotation of mammalian protein complexes is critical to understanding biological processes, as well as disease mechanisms. Here, we used genetic co-essentiality derived from genome-scale RNAi- and CRISPR-Cas9-based fitness screens performed across hundreds of human cancer cell lines to assign measures of functional similarity. From these measures, we systematically built and characterized functional similarity networks that recapitulate known structural and functional features of well-studied protein complexes and resolve novel functional modules within complexes lacking structural resolution, such as the mammalian SWI/SNF complex. Finally, by integrating functional networks with large protein-protein interaction networks, we discovered novel protein complexes involving recently evolved genes of unknown function. Taken together, these findings demonstrate the utility of genetic perturbation screens alone, and in combination with large-scale biophysical data, to enhance our understanding of mammalian protein complexes in normal and disease states. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Interaction Network Estimation: Predicting Problem-Solving Diversity in Interactive Environments

ERIC Educational Resources Information Center

Eagle, Michael; Hicks, Drew; Barnes, Tiffany

2015-01-01

Intelligent tutoring systems and computer aided learning environments aimed at developing problem solving produce large amounts of transactional data which make it a challenge for both researchers and educators to understand how students work within the environment. Researchers have modeled student-tutor interactions using complex networks in…

Modeling the vegetation-atmosphere carbon dioxide and water vapor interactions along a controlled CO2 gradient

USDA-ARS?s Scientific Manuscript database

Ecosystem functioning is intimately linked to the physical environment by complex two-way interactions. These two-way interactions arise because vegetation both responds to the external environment and actively regulates its micro-environment. By altering stomatal aperture, for example, plants modif...

Chemical compounds from anthropogenic environment and immune evasion mechanisms: potential interactions.

PubMed

Kravchenko, Julia; Corsini, Emanuela; Williams, Marc A; Decker, William; Manjili, Masoud H; Otsuki, Takemi; Singh, Neetu; Al-Mulla, Faha; Al-Temaimi, Rabeah; Amedei, Amedeo; Colacci, Anna Maria; Vaccari, Monica; Mondello, Chiara; Scovassi, A Ivana; Raju, Jayadev; Hamid, Roslida A; Memeo, Lorenzo; Forte, Stefano; Roy, Rabindra; Woodrick, Jordan; Salem, Hosni K; Ryan, Elizabeth P; Brown, Dustin G; Bisson, William H; Lowe, Leroy; Lyerly, H Kim

2015-06-01

An increasing number of studies suggest an important role of host immunity as a barrier to tumor formation and progression. Complex mechanisms and multiple pathways are involved in evading innate and adaptive immune responses, with a broad spectrum of chemicals displaying the potential to adversely influence immunosurveillance. The evaluation of the cumulative effects of low-dose exposures from the occupational and natural environment, especially if multiple chemicals target the same gene(s) or pathway(s), is a challenge. We reviewed common environmental chemicals and discussed their potential effects on immunosurveillance. Our overarching objective was to review related signaling pathways influencing immune surveillance such as the pathways involving PI3K/Akt, chemokines, TGF-β, FAK, IGF-1, HIF-1α, IL-6, IL-1α, CTLA-4 and PD-1/PDL-1 could individually or collectively impact immunosurveillance. A number of chemicals that are common in the anthropogenic environment such as fungicides (maneb, fluoxastrobin and pyroclostrobin), herbicides (atrazine), insecticides (pyridaben and azamethiphos), the components of personal care products (triclosan and bisphenol A) and diethylhexylphthalate with pathways critical to tumor immunosurveillance. At this time, these chemicals are not recognized as human carcinogens; however, it is known that they these chemicalscan simultaneously persist in the environment and appear to have some potential interfere with the host immune response, therefore potentially contributing to promotion interacting with of immune evasion mechanisms, and promoting subsequent tumor growth and progression. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Mapping microbial ecosystems and spoilage-gene flow in breweries highlights patterns of contamination and resistance

PubMed Central

Bokulich, Nicholas A; Bergsveinson, Jordyn; Ziola, Barry; Mills, David A

2015-01-01

Distinct microbial ecosystems have evolved to meet the challenges of indoor environments, shaping the microbial communities that interact most with modern human activities. Microbial transmission in food-processing facilities has an enormous impact on the qualities and healthfulness of foods, beneficially or detrimentally interacting with food products. To explore modes of microbial transmission and spoilage-gene frequency in a commercial food-production scenario, we profiled hop-resistance gene frequencies and bacterial and fungal communities in a brewery. We employed a Bayesian approach for predicting routes of contamination, revealing critical control points for microbial management. Physically mapping microbial populations over time illustrates patterns of dispersal and identifies potential contaminant reservoirs within this environment. Habitual exposure to beer is associated with increased abundance of spoilage genes, predicting greater contamination risk. Elucidating the genetic landscapes of indoor environments poses important practical implications for food-production systems and these concepts are translatable to other built environments. DOI: http://dx.doi.org/10.7554/eLife.04634.001 PMID:25756611

Gene × environment interaction on intergroup bias: the role of 5-HTTLPR and perceived outgroup threat.

PubMed

Cheon, Bobby K; Livingston, Robert W; Hong, Ying-Yi; Chiao, Joan Y

2014-09-01

Perceived threat from outgroups is a consistent social-environmental antecedent of intergroup bias (i.e. prejudice, ingroup favoritism). The serotonin transporter gene polymorphism (5-HTTLPR) has been associated with individual variations in sensitivity to context, particularly stressful and threatening situations. Here, we examined how 5-HTTLPR and environmental factors signaling potential outgroup threat dynamically interact to shape intergroup bias. Across two studies, we provide novel evidence for a gene-environment interaction on the acquisition of intergroup bias and prejudice. Greater exposure to signals of outgroup threat, such as negative prior contact with outgroups and perceived danger from the social environment, were more predictive of intergroup bias among participants possessing at least one short allele (vs two long alleles) of 5-HTTLPR. Furthermore, this gene x environment interaction was observed for biases directed at diverse ethnic and arbitrarily-defined outgroups across measures reflecting intergroup biases in evaluation and discriminatory behavior. These findings reveal a candidate genetic mechanism for the acquisition of intergroup bias, and suggest that intergroup bias is dually inherited and transmitted through the interplay of social (i.e. contextual cues of outgroup threat) and biological mechanisms (i.e. genetic sensitivity toward threatening contexts) that regulate perceived intergroup threats. © The Author (2013). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Enhancement of efficiency of chitosan-based complexes for gene transfection with poly(γ-glutamic acid) by augmenting their cellular uptake and intracellular unpackage.

PubMed

Liao, Zi-Xian; Peng, Shu-Fen; Chiu, Ya-Ling; Hsiao, Chun-Wen; Liu, Hung-Yi; Lim, Woon-Hui; Lu, Hsiang-Ming; Sung, Hsing-Wen

2014-11-10

As a cationic polysaccharide, chitosan (CS) has been identified for its potential use as a non-viral vector for exogenous gene transfection. However, owing to their electrostatic interactions, CS complexes may cause difficulties in gene release upon their arrival at the site of action, thus limiting their transfection efficiency. In this work, an attempt is made to facilitate the release of a gene by incorporating a negatively-charged poly(γ-glutamic acid) (γPGA) into CS complexes in order to diminish their attractive interactions. The mechanisms of exploiting γPGA to enhance the transfection efficiency of CS complexes are elucidated. The feasibility of using this CS/γPGA-based system for DNA or siRNA transfer is explored as well. Additionally, potential of the CS/γPGA formulation to deliver disulfide bond-conjugated dual PEGylated siRNAs for multiple gene silencing is also examined. Moreover, the genetic use of pKillerRed-mem, delivered using complexes of CS and γPGA, to express a membrane-targeted KillerRed as an intrinsically generated photosensitizer for photodynamic therapy is described. Copyright © 2014 Elsevier B.V. All rights reserved.

Does MAOA Increase Susceptibility to Prenatal Stress in Young Children?

PubMed Central

Massey, Suena H.; Hatcher, Amalia E.; Clark, Caron A.C.; Burns, James L.; Pine, Daniel S.; Skol, Andrew D.; Mroczek, Daniel K.; Espy, Kimberly A.; Goldman, David; Cook, Edwin; Wakschlag, Lauren S.

2017-01-01

Background We previously demonstrated a gene-by-prenatal-environment interaction whereby the monoamine oxidase A gene (MAOA) modified the impact of prenatal tobacco exposure (PTE) on adolescent disruptive behavior (DB), with the MAOA risk genotype varying by sex. We extend this work by examining whether this mechanism is evident with another common adversity, prenatal stress exposure (PSE), and whether sex differences are present earlier in development in closer proximity to exposure. Methods Participants were 281 mothers and their 285 children derived from a prenatal cohort with in-depth prospective measures of PSE and PTE. We assessed DB at age 5 via dimensional developmentally-sensitive measurement. Analyses were stratified by sex based on prior evidence for sex differences. Results Concurrent stress exposure predicted DB in children (β=.310, p=.001), while main effects of prenatal exposures were seen only in boys. We found a three-way interaction of MAOAxPSExsex on DB (β=.813, p=.022). Boys with MAOA-H had more DB as a function of PSE, controlling for PTE (β=.774, p=.015), and as a function of PTE, controlling for PSE (β=.362, p=.037). Boys with MAOA-L did not show this susceptibility. MAOA did not interact with PSE (β=−.133, p=.561) nor PTE (β= −.144; p=.505) in predicting DB in girls. Examination of gene-environment correlation (rGE) showed a correlation between paternal MAOA-L and daughters’ concurrent stress exposure (r=−.240, p=.013). Discussion Findings underscore complex mechanisms linking genetic susceptibility and early adverse exposures. Replication in larger cohorts followed from the pregnancy through adolescence is suggested to elucidate mechanisms that appear to have varying developmental expression. PMID:28163169

Does MAOA increase susceptibility to prenatal stress in young children?

PubMed

Massey, Suena H; Hatcher, Amalia E; Clark, Caron A C; Burns, James L; Pine, Daniel S; Skol, Andrew D; Mroczek, Daniel K; Espy, Kimberly A; Goldman, David; Cook, Edwin; Wakschlag, Lauren S

2017-05-01

We previously demonstrated a gene-by-prenatal-environment interaction whereby the monoamine oxidase A gene (MAOA) modified the impact of prenatal tobacco exposure (PTE) on adolescent disruptive behavior (DB), with the MAOA risk genotype varying by sex. We extend this work by examining whether this mechanism is evident with another common adversity, prenatal stress exposure (PSE), and whether sex differences are present earlier in development in closer proximity to exposure. Participants were 281 mothers and their 285 children derived from a prenatal cohort with in-depth prospective measures of PSE and PTE. We assessed DB at age 5 via dimensional developmentally-sensitive measurement. Analyses were stratified by sex based on prior evidence for sex differences. Concurrent stress exposure predicted DB in children (β=0.310, p=0.001), while main effects of prenatal exposures were seen only in boys. We found a three-way interaction of MAOA×PSE×sex on DB (β=0.813, p=0.022). Boys with MAOA-H had more DB as a function of PSE, controlling for PTE (β=0.774, p=0.015), and as a function of PTE, controlling for PSE (β=0.362, p=0.037). Boys with MAOA-L did not show this susceptibility. MAOA did not interact with PSE (β=-0.133, p=0.561) nor PTE (β=-0.144; p=0.505) in predicting DB in girls. Examination of gene-environment correlation (rGE) showed a correlation between paternal MAOA-L and daughters' concurrent stress exposure (r=-0.240, p=0.013). Findings underscore complex mechanisms linking genetic susceptibility and early adverse exposures. Replication in larger cohorts followed from the pregnancy through adolescence is suggested to elucidate mechanisms that appear to have varying developmental expression. Copyright © 2017 Elsevier Inc. All rights reserved.

[From stone-craved genes to Michelangelo: significance and different aspects of gene-environment interaction].

PubMed

Lazary, Judit

2017-12-01

Although genetic studies have improved a lot in recent years, without clinical relevance sometimes their significance is devalued. Reviewing the major milestones of psychogenomics it can be seen that break-through success is just a question of time. Investigations of direct effect of genetic variants on phenotypes have not yielded positive findings. However, an important step was taken by adapting the gene-environment interaction model. In this model genetic vulnerability stepped into the place of "stone craved" pathology. Further progress happened when studies of environmental factors were combined with genetic function (epigenetics). This model provided the possibility for investigation of therapeutic interventions as environmental factors and it was proven that effective treatments exert a modifying effect on gene expression. Moreover, recent developments focus on therapeutic manipulation of gene function (e.g. chemogenetics). Instead of "stone craved" genes up-to-date dynamically interacting gene function became the basis of psychogenomics in which correction of the expression is a potential therapeutic tool. Keeping in mind these trends and developments, there is no doubt that genetics will be a fundamental part of daily clinical routine in the future.

Gene Polymorphism Association with Type 2 Diabetes and Related Gene-Gene and Gene-Environment Interactions in a Uyghur Population

PubMed Central

Xiao, Shan; Zeng, Xiaoyun; Fan, Yong; Su, Yinxia; Ma, Qi; Zhu, Jun; Yao, Hua

2016-01-01

Background We investigated the association between 8 single-nucleotide polymorphisms (SNPs) at 3 genetic loci (CDKAL1, CDKN2A/2B and FTO) with type 2 diabetes (T2D) in a Uyghur population. Material/Methods A case-control study of 879 Uyghur patients with T2D and 895 non-diabetic Uyghur controls was conducted at the Hospital of Xinjiang Medical University between 2010 and 2013. Eight SNPs in CDKAL1, CDKN2A/2B and FTO were analyzed using Sequenom MassARRAY®SNP genotyping. Factors associated with T2D were assessed by logistic regression analyses. Gene-gene and gene-environment interactions were analyzed by generalized multifactor dimensionality reduction. Results Genotype distributions of rs10811661 (CDKN2A/2B), rs7195539, rs8050136, and rs9939609 (FTO) and allele frequencies of rs8050136 and rs9939609 differed significantly between diabetes and control groups (all P<0.05). While rs10811661, rs8050136, and rs9939609 were eliminated after adjusting for covariates (P>0.05), rs7195539 distribution differed significantly in co-dominant and dominant models (P<0.05). In gene-gene interaction analysis, after adjusting for covariates the two-locus rs10811661-rs7195539 interaction model had a cross-validation consistency of 10/10 and the highest balanced accuracy of 0.5483 (P=0.014). In gene-environment interaction analysis, the 3-locus interaction model TG-HDL-family history of diabetes had a cross-validation consistency of 10/10 and the highest balanced accuracy of 0.7072 (P<0.001). The 4-locus interaction model, rs7195539-TG-HDL-family history of diabetes had a cross-validation consistency of 8/10 (P<0.001). Conclusions Polymorphisms in CDKN2A/2B and FTO, but not CDKAL1, may be associated with T2D, and alleles rs8050136 and rs9939609 are likely risk alleles for T2D in this population. There were potential interactions among CDKN2A/2B (rs10811661) – FTO (rs7195539) or FTO (rs7195539)-TG-HDL-family history of diabetes in the pathogenesis of T2D in a Uyghur population. PMID:26873362

A distinct and replicable variant of the squamous cell carcinoma gene inositol polyphosphate-5-phosphatase modifies the susceptibility of arsenic-associated skin lesions in Bangladesh.

PubMed

Seow, Wei Jie; Pan, Wen-Chi; Kile, Molly L; Tong, Lin; Baccarelli, Andrea A; Quamruzzaman, Quazi; Rahman, Mahmuder; Mostofa, Golam; Rakibuz-Zaman, Muhammad; Kibriya, Muhammad; Ahsan, Habibul; Lin, Xihong; Christiani, David C

2015-07-01

Single-nucleotide polymorphisms (SNPs) in inflammation, one-carbon metabolism, and skin cancer genes might influence susceptibility to arsenic-induced skin lesions. A case-control study was conducted in Pabna, Bangladesh (2001-2003), and the drinking-water arsenic concentration was measured for each participant. A panel of 25 candidate SNPs was analyzed in 540 cases and 400 controls. Logistic regression was used to estimate the association between each SNP and the potential for gene-environment interactions in the skin lesion risk, with adjustments for relevant covariates. Replication testing was conducted in an independent Bangladesh population with 488 cases and 2,794 controls. In the discovery population, genetic variants in the one-carbon metabolism genes phosphatidylethanolamine N-methyltransferase (rs2278952, P for interaction  = .004; rs897453, P for interaction = .05) and dihydrofolate reductase (rs1650697, P for interaction = .02), the inflammation gene interleukin 10 (rs3024496, P for interaction =.04), and the skin cancer genes inositol polyphosphate-5-phosphatase (INPP5A; rs1133400, P for interaction = .03) and xeroderma pigmentosum complementation group C (rs2228000, P for interaction = .01) significantly modified the association between arsenic and skin lesions after adjustments for multiple comparisons. The significant gene-environment interaction between a SNP in the INPP5A gene (rs1133400) and water arsenic with respect to the skin lesion risk was successfully replicated in an independent population (P for interaction = .03). Minor allele carriers of the skin cancer gene INPP5A modified the odds of arsenic-induced skin lesions in both main and replicative populations. Genetic variation in INPP5A appears to have a role in susceptibility to arsenic toxicity. © 2015 American Cancer Society.

Gene × environment interaction studies have not properly controlled for potential confounders: the problem and the (simple) solution.

PubMed

Keller, Matthew C

2014-01-01

Candidate gene × environment (G × E) interaction research tests the hypothesis that the effects of some environmental variable (e.g., childhood maltreatment) on some outcome measure (e.g., depression) depend on a particular genetic polymorphism. Because this research is inherently nonexperimental, investigators have been rightly concerned that detected interactions could be driven by confounders (e.g., ethnicity, gender, age, socioeconomic status) rather than by the specified genetic or environmental variables per se. In an attempt to eliminate such alternative explanations for detected G × E interactions, investigators routinely enter the potential confounders as covariates in general linear models. However, this practice does not control for the effects these variables might have on the G × E interaction. Rather, to properly control for confounders, researchers need to enter the covariate × environment and the covariate × gene interaction terms in the same model that tests the G × E term. In this manuscript, I demonstrate this point analytically and show that the practice of improperly controlling for covariates is the norm in the G × E interaction literature to date. Thus, many alternative explanations for G × E findings that investigators had thought were eliminated have not been. © 2013 Society of Biological Psychiatry Published by Society of Biological Psychiatry All rights reserved.

A novel gene, MdSSK1, as a component of the SCF complex rather than MdSBP1 can mediate the ubiquitination of S-RNase in apple.

PubMed

Yuan, Hui; Meng, Dong; Gu, Zhaoyu; Li, Wei; Wang, Aide; Yang, Qing; Zhu, Yuandi; Li, Tianzhong

2014-07-01

As a core factor in S-RNase-based gametophytic self-incompatibility (GSI), the SCF (SKP1-Cullin1-F-box-Rbx1) complex (including pollen determinant SLF, S-locus-F-box) functions as an E3 ubiquitin ligase on non-self S-RNase. The SCF complex is formed by SKP1 bridging between SLF, CUL1, and Rbx1; however, it is not known whether an SCF complex lacking SKP1 can mediate the ubiquitination of S-RNase. Three SKP1-like genes from pollen were cloned based on the structural features of the SLF-interacting-SKP1-like (SSK) gene and the 'Golden Delicious' apple genome. These genes have a motif of five amino acids following the standard 'WAFE' at the C terminal and, in addition, contain eight sheets and two helices. All three genes were expressed exclusively in pollen. In the yeast two-hybrid and pull-down assays only one was found to interact with MdSFBB and MdCUL1, suggesting it is the SLF-interacting SKP1-like gene in apple which was named MdSSK1. In vitro experiments using MdSSK1, S2-MdSFBB1 (S2-Malus domestica S-locus-F-box brother) and MdCUL1 proteins incubated with S 2-RNase and ubiquitin revealed that the SCF complex ubiquitinylates S-RNase in vitro, while MdSBP1 (Malus domestica S-RNase binding protein 1) could not functionally replace MdSSK1 in the SCF complex in ubiquitinylating S-RNase. According to the above experiments, MdSBP1 is probably the only factor responsible for recognition with S-RNase, while not a component of the SCF complex, and an SCF complex containing MdSSK1 is required for mediating the ubiquitination of S-RNase. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology.

How well do you know your mutation? Complex effects of genetic background on expressivity, complementation, and ordering of allelic effects

PubMed Central

Choi, Lin; DeNieu, Michael; Sonnenschein, Anne; Hummel, Kristen; Marier, Christian; Victory, Andrew; Porter, Cody; Mammel, Anna; Holms, Julie; Sivaratnam, Gayatri

2017-01-01

For a given gene, different mutations influence organismal phenotypes to varying degrees. However, the expressivity of these variants not only depends on the DNA lesion associated with the mutation, but also on factors including the genetic background and rearing environment. The degree to which these factors influence related alleles, genes, or pathways similarly, and whether similar developmental mechanisms underlie variation in the expressivity of a single allele across conditions and among alleles is poorly understood. Besides their fundamental biological significance, these questions have important implications for the interpretation of functional genetic analyses, for example, if these factors alter the ordering of allelic series or patterns of complementation. We examined the impact of genetic background and rearing environment for a series of mutations spanning the range of phenotypic effects for both the scalloped and vestigial genes, which influence wing development in Drosophila melanogaster. Genetic background and rearing environment influenced the phenotypic outcome of mutations, including intra-genic interactions, particularly for mutations of moderate expressivity. We examined whether cellular correlates (such as cell proliferation during development) of these phenotypic effects matched the observed phenotypic outcome. While cell proliferation decreased with mutations of increasingly severe effects, surprisingly it did not co-vary strongly with the degree of background dependence. We discuss these findings and propose a phenomenological model to aid in understanding the biology of genes, and how this influences our interpretation of allelic effects in genetic analysis. PMID:29166655

Correcting systematic inflation in genetic association tests that consider interaction effects: application to a genome-wide association study of posttraumatic stress disorder.

PubMed

Almli, Lynn M; Duncan, Richard; Feng, Hao; Ghosh, Debashis; Binder, Elisabeth B; Bradley, Bekh; Ressler, Kerry J; Conneely, Karen N; Epstein, Michael P

2014-12-01

Genetic association studies of psychiatric outcomes often consider interactions with environmental exposures and, in particular, apply tests that jointly consider gene and gene-environment interaction effects for analysis. Using a genome-wide association study (GWAS) of posttraumatic stress disorder (PTSD), we report that heteroscedasticity (defined as variability in outcome that differs by the value of the environmental exposure) can invalidate traditional joint tests of gene and gene-environment interaction. To identify the cause of bias in traditional joint tests of gene and gene-environment interaction in a PTSD GWAS and determine whether proposed robust joint tests are insensitive to this problem. The PTSD GWAS data set consisted of 3359 individuals (978 men and 2381 women) from the Grady Trauma Project (GTP), a cohort study from Atlanta, Georgia. The GTP performed genome-wide genotyping of participants and collected environmental exposures using the Childhood Trauma Questionnaire and Trauma Experiences Inventory. We performed joint interaction testing of the Beck Depression Inventory and modified PTSD Symptom Scale in the GTP GWAS. We assessed systematic bias in our interaction analyses using quantile-quantile plots and genome-wide inflation factors. Application of the traditional joint interaction test to the GTP GWAS yielded systematic inflation across different outcomes and environmental exposures (inflation-factor estimates ranging from 1.07 to 1.21), whereas application of the robust joint test to the same data set yielded no such inflation (inflation-factor estimates ranging from 1.01 to 1.02). Simulated data further revealed that the robust joint test is valid in different heteroscedasticity models, whereas the traditional joint test is invalid. The robust joint test also has power similar to the traditional joint test when heteroscedasticity is not an issue. We believe the robust joint test should be used in candidate-gene studies and GWASs of psychiatric outcomes that consider environmental interactions. To make the procedure useful for applied investigators, we created a software tool that can be called from the popular PLINK package for analysis.

Correcting Systematic Inflation in Genetic Association Tests That Consider Interaction Effects

PubMed Central

Almli, Lynn M.; Duncan, Richard; Feng, Hao; Ghosh, Debashis; Binder, Elisabeth B.; Bradley, Bekh; Ressler, Kerry J.; Conneely, Karen N.; Epstein, Michael P.

2015-01-01

IMPORTANCE Genetic association studies of psychiatric outcomes often consider interactions with environmental exposures and, in particular, apply tests that jointly consider gene and gene-environment interaction effects for analysis. Using a genome-wide association study (GWAS) of posttraumatic stress disorder (PTSD), we report that heteroscedasticity (defined as variability in outcome that differs by the value of the environmental exposure) can invalidate traditional joint tests of gene and gene-environment interaction. OBJECTIVES To identify the cause of bias in traditional joint tests of gene and gene-environment interaction in a PTSD GWAS and determine whether proposed robust joint tests are insensitive to this problem. DESIGN, SETTING, AND PARTICIPANTS The PTSD GWAS data set consisted of 3359 individuals (978 men and 2381 women) from the Grady Trauma Project (GTP), a cohort study from Atlanta, Georgia. The GTP performed genome-wide genotyping of participants and collected environmental exposures using the Childhood Trauma Questionnaire and Trauma Experiences Inventory. MAIN OUTCOMES AND MEASURES We performed joint interaction testing of the Beck Depression Inventory and modified PTSD Symptom Scale in the GTP GWAS. We assessed systematic bias in our interaction analyses using quantile-quantile plots and genome-wide inflation factors. RESULTS Application of the traditional joint interaction test to the GTP GWAS yielded systematic inflation across different outcomes and environmental exposures (inflation-factor estimates ranging from 1.07 to 1.21), whereas application of the robust joint test to the same data set yielded no such inflation (inflation-factor estimates ranging from 1.01 to 1.02). Simulated data further revealed that the robust joint test is valid in different heteroscedasticity models, whereas the traditional joint test is invalid. The robust joint test also has power similar to the traditional joint test when heteroscedasticity is not an issue. CONCLUSIONS AND RELEVANCE We believe the robust joint test should be used in candidate-gene studies and GWASs of psychiatric outcomes that consider environmental interactions. To make the procedure useful for applied investigators, we created a software tool that can be called from the popular PLINK package for analysis. PMID:25354142

Mental and physical distress is modulated by a polymorphism in the 5-HT transporter gene interacting with social stressors and chronic disease burden.

PubMed

Grabe, H J; Lange, M; Wolff, B; Völzke, H; Lucht, M; Freyberger, H J; John, U; Cascorbi, I

2005-02-01

Previous studies have yielded conflicting results as to the putative role of the functional polymorphism of the promoter region of the serotonin transporter gene (SLC6A4) in the etiology of anxiety-related traits and depressive disorders. Recently, a significant gene-environment interaction was found between life stressors, the short allele of the SLC6A4 polymorphism and depression. The aim of the present study was to investigate if such a gene-environment interaction could be replicated within a different population with a different risk structure. A total of 1005 subjects from a general population sample (Study of Health in Pomerania) were genotyped. Mental and physical distress were assessed on 38 items of the modified complaint scale (BL-38). The interaction between the SLC6A4 genotype, social stressors and chronic diseases with regard to the BL-38 score was evaluated by ANOVA. There was no independent association of genotype with mental and physical distress. However, significant interactions between genotype, unemployment and chronic diseases (F = 6.6; df = 3, 671; P < 0.001) were found in females but not in males. The genotype explained 2% of the total variance of the BL-38 score and 9.1% of the explained variance. The results partly confirm previous findings of a significant gene-environment interaction of the short allele, indicating a higher mental vulnerability to social stressors and chronic diseases. The relevance of this finding is sustained by the fact that the sample characteristics and the risk structure were highly different from previous studies.

Nutrigenetics and prostate cancer: 2011 and beyond.

PubMed

Yuan, Yinan; Ferguson, Lynnette R

2011-01-01

Prostate cancer runs in families and shows a clear dietary involvement. Until recently, the key risk gene(s) have proved elusive. We summarise current understandings of nutrient-gene interactions in prostate cancer risk and progression. A MEDLINE-based literature search was conducted. Hypothesis-directed candidate gene approaches provide plausible, albeit statistically weak, nutrient-gene interactions. These are based on early understandings of factors likely to impact on carcinogenesis, including both nutrient and genetic effects on androgen biosynthesis and action, xenobiotic metabolism, DNA damage and DNA repair. Non-hypothesis-directed genome-wide association studies provide much stronger evidence for other genes, not hitherto suspected for involvement. Although only a few of these have been formally tested for dietary associations in well-designed epidemiologic studies, the nature of many of the genes suggests that their activity may be regulated by nutrients. These effects may not only be relevant to prostate cancer susceptibility, but also to disease progression. It will be important to move beyond studying single nucleotide polymorphisms, into more complex chromosomal rearrangements and to epigenetic changes. For future progress, large international cohorts will not only need to provide proof of individual nutrient-gene interactions, but also to relate these to more complex nutrient-gene-gene interactions, as parts of pathways. Bioinformatics and biostatistics will be increasingly important tools in nutrigenetic studies beyond 2011. Copyright © 2011 S. Karger AG, Basel.

Markov Logic Networks in the Analysis of Genetic Data

PubMed Central

Sakhanenko, Nikita A.

2010-01-01

Abstract Complex, non-additive genetic interactions are common and can be critical in determining phenotypes. Genome-wide association studies (GWAS) and similar statistical studies of linkage data, however, assume additive models of gene interactions in looking for genotype-phenotype associations. These statistical methods view the compound effects of multiple genes on a phenotype as a sum of influences of each gene and often miss a substantial part of the heritable effect. Such methods do not use any biological knowledge about underlying mechanisms. Modeling approaches from the artificial intelligence (AI) field that incorporate deterministic knowledge into models to perform statistical analysis can be applied to include prior knowledge in genetic analysis. We chose to use the most general such approach, Markov Logic Networks (MLNs), for combining deterministic knowledge with statistical analysis. Using simple, logistic regression-type MLNs we can replicate the results of traditional statistical methods, but we also show that we are able to go beyond finding independent markers linked to a phenotype by using joint inference without an independence assumption. The method is applied to genetic data on yeast sporulation, a complex phenotype with gene interactions. In addition to detecting all of the previously identified loci associated with sporulation, our method identifies four loci with smaller effects. Since their effect on sporulation is small, these four loci were not detected with methods that do not account for dependence between markers due to gene interactions. We show how gene interactions can be detected using more complex models, which can be used as a general framework for incorporating systems biology with genetics. PMID:20958249

Media portrayals and health inequalities: a case study of characterizations of Gene x Environment interactions.

PubMed

Horwitz, Allan V

2005-10-01

This article examines how genetic and environmental interactions associated with health inequalities are constructed and framed in the presentation of scientific research. It uses the example of a major article about depression in a longitudinal study of young adults that appeared in Science in 2003. This portrayal of findings related to health inequalities uses a genetic lens that privileges genetic influences and diminishes environmental ones. The emphasis on the genetic side of Gene x Environment interactions can serve to deflect attention away from the important impact of social inequalities on health.

Childhood and adolescent anxiety and depression: beyond heritability.

PubMed

Franić, Sanja; Middeldorp, Christel M; Dolan, Conor V; Ligthart, Lannie; Boomsma, Dorret I

2010-08-01

To review the methodology of behavior genetics studies addressing research questions that go beyond simple heritability estimation and illustrate these using representative research on childhood and adolescent anxiety and depression. The classic twin design and its extensions may be used to examine age and gender differences in the genetic determinants of complex traits and disorders, the role of genetic factors in explaining comorbidity, the interaction of genes and the environment, and the effect of social interaction among family members. An overview of the methods typically employed to address such questions is illustrated by a review of 34 recent studies on childhood anxiety and depression. The review provides relatively consistent evidence for small to negligible sex differences in the genetic etiology of childhood anxiety and depression, a substantial role of genetic factors in accounting for the temporal stability of these disorders, a partly genetic basis of the comorbidity between anxiety and depression, a possible role of the interaction between genotype and the environment in affecting liability to these disorders, a role of genotype-environment correlation, and a minor, if any, etiological role of sibling interaction. The results clearly demonstrate a role for genetic factors in the etiology and temporal stability of individual differences in childhood anxiety and depression. Clinical implications of the findings are discussed. 2010 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Transitions from mono- to co- to tri-culture uniquely affect gene expression in breast cancer, stromal, and immune compartments.

PubMed

Regier, Mary C; Maccoux, Lindsey J; Weinberger, Emma M; Regehr, Keil J; Berry, Scott M; Beebe, David J; Alarid, Elaine T

2016-08-01

Heterotypic interactions in cancer microenvironments play important roles in disease initiation, progression, and spread. Co-culture is the predominant approach used in dissecting paracrine interactions between tumor and stromal cells, but functional results from simple co-cultures frequently fail to correlate to in vivo conditions. Though complex heterotypic in vitro models have improved functional relevance, there is little systematic knowledge of how multi-culture parameters influence this recapitulation. We therefore have employed a more iterative approach to investigate the influence of increasing model complexity; increased heterotypic complexity specifically. Here we describe how the compartmentalized and microscale elements of our multi-culture device allowed us to obtain gene expression data from one cell type at a time in a heterotypic culture where cells communicated through paracrine interactions. With our device we generated a large dataset comprised of cell type specific gene-expression patterns for cultures of increasing complexity (three cell types in mono-, co-, or tri-culture) not readily accessible in other systems. Principal component analysis indicated that gene expression was changed in co-culture but was often more strongly altered in tri-culture as compared to mono-culture. Our analysis revealed that cell type identity and the complexity around it (mono-, co-, or tri-culture) influence gene regulation. We also observed evidence of complementary regulation between cell types in the same heterotypic culture. Here we demonstrate the utility of our platform in providing insight into how tumor and stromal cells respond to microenvironments of varying complexities highlighting the expanding importance of heterotypic cultures that go beyond conventional co-culture.

Molecular basis of atopic dermatitis.

PubMed

Bonness, Sonja; Bieber, Thomas

2007-10-01

Atopic dermatitis is a common chronic inflammatory skin disease and there are numerous publications on this topic. This review will focus on developments in understanding the molecular basis of atopic dermatitis while considering the genetic background, skin barrier impairment, immune system deviation and microbial superinfections. Atopic dermatitis is a complex genetic disease in which gene-gene and gene-environment interactions play a key role. Surprisingly some genetic regions of interest were found to be overlapping with loci identified to play a role in another very common inflammatory skin disease, psoriasis, while no overlap has so far been observed with asthma. Impairment of the skin barrier followed by antigens trespassing seems to play an important role, favouring sensitization via transepidermal penetration which is the focus of current investigations. Superinfections by pathogens such as Staphylococcus aureus due to a weak innate defence seem to be significant in atopic dermatitis as they elicit a strong inflammatory response. Atopic dermatitis is a chronic inflammatory skin disease with a high incidence in school children and adults. Disease pathogenesis is complex and the background is multifactorial, making the underlying predispositions elusive. Understanding new pathogenic pathways may lead to the development of new drugs with enhanced benefit for the patient.

The Complex Relationship between Virulence and Antibiotic Resistance

PubMed Central

Schroeder, Meredith; Brooks, Benjamin D.; Brooks, Amanda E.

2017-01-01

Antibiotic resistance, prompted by the overuse of antimicrobial agents, may arise from a variety of mechanisms, particularly horizontal gene transfer of virulence and antibiotic resistance genes, which is often facilitated by biofilm formation. The importance of phenotypic changes seen in a biofilm, which lead to genotypic alterations, cannot be overstated. Irrespective of if the biofilm is single microbe or polymicrobial, bacteria, protected within a biofilm from the external environment, communicate through signal transduction pathways (e.g., quorum sensing or two-component systems), leading to global changes in gene expression, enhancing virulence, and expediting the acquisition of antibiotic resistance. Thus, one must examine a genetic change in virulence and resistance not only in the context of the biofilm but also as inextricably linked pathologies. Observationally, it is clear that increased virulence and the advent of antibiotic resistance often arise almost simultaneously; however, their genetic connection has been relatively ignored. Although the complexities of genetic regulation in a multispecies community may obscure a causative relationship, uncovering key genetic interactions between virulence and resistance in biofilm bacteria is essential to identifying new druggable targets, ultimately providing a drug discovery and development pathway to improve treatment options for chronic and recurring infection. PMID:28106797

Crop epigenetics and the molecular hardware of genotype × environment interactions.

PubMed

King, Graham J

2015-01-01

Crop plants encounter thermal environments which fluctuate on a diurnal and seasonal basis. Future climate resilient cultivars will need to respond to thermal profiles reflecting more variable conditions, and harness plasticity that involves regulation of epigenetic processes and complex genomic regulatory networks. Compartmentalization within plant cells insulates the genomic central processing unit within the interphase nucleus. This review addresses the properties of the chromatin hardware in which the genome is embedded, focusing on the biophysical and thermodynamic properties of DNA, histones and nucleosomes. It explores the consequences of thermal and ionic variation on the biophysical behavior of epigenetic marks such as DNA cytosine methylation (5mC), and histone variants such as H2A.Z, and how these contribute to maintenance of chromatin integrity in the nucleus, while enabling specific subsets of genes to be regulated. Information is drawn from theoretical molecular in vitro studies as well as model and crop plants and incorporates recent insights into the role epigenetic processes play in mediating between environmental signals and genomic regulation. A preliminary speculative framework is outlined, based on the evidence of what appears to be a cohesive set of interactions at molecular, biophysical and electrostatic level between the various components contributing to chromatin conformation and dynamics. It proposes that within plant nuclei, general and localized ionic homeostasis plays an important role in maintaining chromatin conformation, whilst maintaining complex genomic regulation that involves specific patterns of epigenetic marks. More generally, reversible changes in DNA methylation appear to be consistent with the ability of nuclear chromatin to manage variation in external ionic and temperature environment. Whilst tentative, this framework provides scope to develop experimental approaches to understand in greater detail the internal environment of plant nuclei. It is hoped that this will generate a deeper understanding of the molecular mechanisms underlying genotype × environment interactions that may be beneficial for long-term improvement of crop performance in less predictable climates.

Crop epigenetics and the molecular hardware of genotype × environment interactions

PubMed Central

King, Graham J.

2015-01-01

Crop plants encounter thermal environments which fluctuate on a diurnal and seasonal basis. Future climate resilient cultivars will need to respond to thermal profiles reflecting more variable conditions, and harness plasticity that involves regulation of epigenetic processes and complex genomic regulatory networks. Compartmentalization within plant cells insulates the genomic central processing unit within the interphase nucleus. This review addresses the properties of the chromatin hardware in which the genome is embedded, focusing on the biophysical and thermodynamic properties of DNA, histones and nucleosomes. It explores the consequences of thermal and ionic variation on the biophysical behavior of epigenetic marks such as DNA cytosine methylation (5mC), and histone variants such as H2A.Z, and how these contribute to maintenance of chromatin integrity in the nucleus, while enabling specific subsets of genes to be regulated. Information is drawn from theoretical molecular in vitro studies as well as model and crop plants and incorporates recent insights into the role epigenetic processes play in mediating between environmental signals and genomic regulation. A preliminary speculative framework is outlined, based on the evidence of what appears to be a cohesive set of interactions at molecular, biophysical and electrostatic level between the various components contributing to chromatin conformation and dynamics. It proposes that within plant nuclei, general and localized ionic homeostasis plays an important role in maintaining chromatin conformation, whilst maintaining complex genomic regulation that involves specific patterns of epigenetic marks. More generally, reversible changes in DNA methylation appear to be consistent with the ability of nuclear chromatin to manage variation in external ionic and temperature environment. Whilst tentative, this framework provides scope to develop experimental approaches to understand in greater detail the internal environment of plant nuclei. It is hoped that this will generate a deeper understanding of the molecular mechanisms underlying genotype × environment interactions that may be beneficial for long-term improvement of crop performance in less predictable climates. PMID:26594221

The development of peripartum depressive symptoms is associated with gene polymorphisms of MAOA, 5-HTT and COMT.

PubMed

Doornbos, Bennard; Dijck-Brouwer, D A Janneke; Kema, Ido P; Tanke, Marit A C; van Goor, Saskia A; Muskiet, Frits A J; Korf, Jakob

2009-10-01

Polymorphisms of monoamine-related genes have been associated with depression following life events. The peripartum is a physiologically and psychologically challenging period, characterized by fluctuations in depressive symptoms, therefore facilitating prospective investigations in this gene x environment (G x E) interaction. Eighty nine pregnant women filled in two Edinburgh Postpartum Depression Scale (EPDS) questionnaires during pregnancy and two in the postpartum period. MAOA, COMT and 5-HTT polymorphisms were analyzed. We found a significant interaction between the development of depressive symptoms in the course of pregnancy and polymorphisms in 5-HTT (p=0.019); MAOA (p=0.044) and COMT (p=0.026), and MAOA x COMT (p<0.001). Particularly, women carrying the combination of low activity variants of MAOA and COMT showed increased EPDS scores at week 36 of pregnancy and 6 weeks postpartum, but not during early pregnancy or 12 weeks postpartum. We found that MAOA in combination with COMT appears to regulate not only the stress response in laboratory experiments, but also seems to influence the stress-evoked onset of mood during normal, mild, stressful events, such as experienced in the peripartum period. These findings support the GxE concept for depression, but they underline the complexity of this concept, as the cumulating effects of these polymorphic genes (i.e. MAOA+COMT) might be needed and the effects of these polymorphic genes becomes apparent in special environmental or physiological conditions (i.e. the peripartum period). We therefore suggest that G x E interactions become especially noticeable from longitudinal study designs in specific physiological or social challenging periods.

Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

PubMed

Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia

2015-06-01

To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.

Effect of summer daylight exposure and genetic background on growth in growth hormone-deficient children.

PubMed

De Leonibus, C; Chatelain, P; Knight, C; Clayton, P; Stevens, A

2016-11-01

The response to growth hormone in humans is dependent on phenotypic, genetic and environmental factors. The present study in children with growth hormone deficiency (GHD) collected worldwide characterised gene-environment interactions on growth response to recombinant human growth hormone (r-hGH). Growth responses in children are linked to latitude, and we found that a correlate of latitude, summer daylight exposure (SDE), was a key environmental factor related to growth response to r-hGH. In turn growth response was determined by an interaction between both SDE and genes known to affect growth response to r-hGH. In addition, analysis of associated networks of gene expression implicated a role for circadian clock pathways and specifically the developmental transcription factor NANOG. This work provides the first observation of gene-environment interactions in children treated with r-hGH.

Modeling transcriptional networks regulating secondary growth and wood formation in forest trees

Treesearch

Lijun Liu; Vladimir Filkov; Andrew Groover

2013-01-01

The complex interactions among the genes that underlie a biological process can be modeled and presented as a transcriptional network, in which genes (nodes) and their interactions (edges) are shown in a graphical form similar to a wiring diagram. A large number of genes have been identified that are expressed during the radial woody growth of tree stems (secondary...

Hypercompetitive Environments: An Agent-based model approach

NASA Astrophysics Data System (ADS)

Dias, Manuel; Araújo, Tanya

Information technology (IT) environments are characterized by complex changes and rapid evolution. Globalization and the spread of technological innovation have increased the need for new strategic information resources, both from individual firms and management environments. Improvements in multidisciplinary methods and, particularly, the availability of powerful computational tools, are giving researchers an increasing opportunity to investigate management environments in their true complex nature. The adoption of a complex systems approach allows for modeling business strategies from a bottom-up perspective — understood as resulting from repeated and local interaction of economic agents — without disregarding the consequences of the business strategies themselves to individual behavior of enterprises, emergence of interaction patterns between firms and management environments. Agent-based models are at the leading approach of this attempt.

MEDIATOR25 Acts as an Integrative Hub for the Regulation of Jasmonate-Responsive Gene Expression in Arabidopsis1[C][W

PubMed Central

Çevik, Volkan; Kidd, Brendan N.; Zhang, Peijun; Hill, Claire; Kiddle, Steve; Denby, Katherine J.; Holub, Eric B.; Cahill, David M.; Manners, John M.; Schenk, Peer M.; Beynon, Jim; Kazan, Kemal

2012-01-01

The PHYTOCHROME AND FLOWERING TIME1 gene encoding the MEDIATOR25 (MED25) subunit of the eukaryotic Mediator complex is a positive regulator of jasmonate (JA)-responsive gene expression in Arabidopsis (Arabidopsis thaliana). Based on the function of the Mediator complex as a bridge between DNA-bound transcriptional activators and the RNA polymerase II complex, MED25 has been hypothesized to function in association with transcriptional regulators of the JA pathway. However, it is currently not known mechanistically how MED25 functions to regulate JA-responsive gene expression. In this study, we show that MED25 physically interacts with several key transcriptional regulators of the JA signaling pathway, including the APETALA2 (AP2)/ETHYLENE RESPONSE FACTOR (ERF) transcription factors OCTADECANOID-RESPONSIVE ARABIDOPSIS AP2/ERF59 and ERF1 as well as the master regulator MYC2. Physical interaction detected between MED25 and four group IX AP2/ERF transcription factors was shown to require the activator interaction domain of MED25 as well as the recently discovered Conserved Motif IX-1/EDLL transcription activation motif of MED25-interacting AP2/ERFs. Using transcriptional activation experiments, we also show that OCTADECANOID-RESPONSIVE ARABIDOPSIS AP2/ERF59- and ERF1-dependent activation of PLANT DEFENSIN1.2 as well as MYC2-dependent activation of VEGETATIVE STORAGE PROTEIN1 requires a functional MED25. In addition, MED25 is required for MYC2-dependent repression of pathogen defense genes. These results suggest an important role for MED25 as an integrative hub within the Mediator complex during the regulation of JA-associated gene expression. PMID:22822211

Genetic Mechanisms Leading to Sex Differences Across Common Diseases and Anthropometric Traits.

PubMed

Traglia, Michela; Bseiso, Dina; Gusev, Alexander; Adviento, Brigid; Park, Daniel S; Mefford, Joel A; Zaitlen, Noah; Weiss, Lauren A

2017-02-01

Common diseases often show sex differences in prevalence, onset, symptomology, treatment, or prognosis. Although studies have been performed to evaluate sex differences at specific SNP associations, this work aims to comprehensively survey a number of complex heritable diseases and anthropometric traits. Potential genetically encoded sex differences we investigated include differential genetic liability thresholds or distributions, gene-sex interaction at autosomal loci, major contribution of the X-chromosome, or gene-environment interactions reflected in genes responsive to androgens or estrogens. Finally, we tested the overlap between sex-differential association with anthropometric traits and disease risk. We utilized complementary approaches of assessing GWAS association enrichment and SNP-based heritability estimation to explore explicit sex differences, as well as enrichment in sex-implicated functional categories. We do not find consistent increased genetic load in the lower-prevalence sex, or a disproportionate role for the X-chromosome in disease risk, despite sex-heterogeneity on the X for several traits. We find that all anthropometric traits show less than complete correlation between the genetic contribution to males and females, and find a convincing example of autosome-wide genome-sex interaction in multiple sclerosis (P = 1 × 10 -9 ). We also find some evidence for hormone-responsive gene enrichment, and striking evidence of the contribution of sex-differential anthropometric associations to common disease risk, implying that general mechanisms of sexual dimorphism determining secondary sex characteristics have shared effects on disease risk. Copyright © 2017 by the Genetics Society of America.

The genetics of insomnia--evidence for epigenetic mechanisms?

PubMed

Palagini, Laura; Biber, Knut; Riemann, Dieter

2014-06-01

Sleep is a complex physiological process and still remains one of the great mysteries of science. Over the past 10 y, genetic research has provided a new avenue to address the regulation and function of sleep. Gene loci that contribute quantitatively to sleep characteristics and variability have already been identified. However, up to now, a genetic basis has been established only for a few sleep disorders. Little is yet known about the genetic background of insomnia, one of the most common sleep disorders. According to the conceptualisation of the 3P model of insomnia, predisposing, precipitating and perpetuating factors contribute to the development and maintenance of insomnia. Growing evidence from studies of predisposing factors suggests a certain degree of heritability for insomnia and for a reactivity of sleep patterns to stressful events, explaining the emergence of insomnia in response to stressful life events. While a genetic susceptibility may modulate the impact of stress on the brain, this finding does not provide us with a complete understanding of the capacity of stress to produce long-lasting perturbations of brain and behaviour. Epigenetic gene-environment interactions have been identified just recently and may provide a more complex understanding of the genetic control of sleep and its disorders. It was recently hypothesised that stress-response-related brain plasticity might be epigenetically controlled and, moreover, several epigenetic mechanisms have been assumed to be involved in the regulation of sleep. Hence, it might be postulated that insomnia may be influenced by an epigenetic control process of both sleep mechanisms and stress-response-related gene-environment interactions having an impact on brain plasticity. This paper reviews the evidence for the genetic basis of insomnia and recent theories about epigenetic mechanisms involved in both sleep regulation and brain-stress response, leading to the hypothesis of an involvement of epigenetic mechanisms in the development and maintenance of insomnia. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multiple molecular effect pathways of an environmental oestrogen in fish.

PubMed

Filby, Amy L; Thorpe, Karen L; Tyler, Charles R

2006-08-01

Complex interrelationships in the signalling of oestrogenic effects mean that environmental oestrogens present in the aquatic environment have the potential to disrupt physiological function in fish in a more complex manner than portrayed in the present literature. Taking a broader approach to investigate the possible effect pathways and the likely consequences of environmental oestrogen exposure in fish, the effects of 17beta-oestradiol (E(2)) were studied on the expression of a suite of genes which interact to mediate growth, development and thyroid and interrenal function (growth hormone GH (gh), GH receptor (ghr ), insulin-like growth factor (IGF-I) (igf1), IGF-I receptor (igf1r ), thyroid hormone receptors-alpha (thra) and -beta (thrb) and glucocorticoid receptor (gr )) together with the expression analyses of sex-steroid receptors and ten other genes centrally involved in sexual development and reproduction in fathead minnow (fhm; Pimephales promelas). Exposure of adult fhm to 35 ng E(2)/l for 14 days induced classic oestrogen biomarker responses (hepatic oestrogen receptor 1 and plasma vitellogenin), and impacted on the reproductive axis, feminising "male" steroidogenic enzyme expression profiles and suppressing genes involved in testis differentiation. However, E(2) also triggered a cascade of responses for gh, ghr, igf1, igf1r, thra, thrb and gr in the pituitary, brain, liver, gonad and gill, with potential consequences for the functioning of many physiological processes, not just reproduction. Molecular responses to E(2) were complex, with most genes showing differential responses between tissues and sexes. For example, igf1 expression increased in brain but decreased in gill on exposure to E(2), and responded in an opposite way in males compared with females in liver, gonad and pituitary. These findings demonstrate the importance of developing a deeper understanding of the endocrine interactions for unravelling the mechanisms of environmental oestrogen action and predicting the likely health consequences.

Genetic control of root growth: from genes to networks.

PubMed

Slovak, Radka; Ogura, Takehiko; Satbhai, Santosh B; Ristova, Daniela; Busch, Wolfgang

2016-01-01

Roots are essential organs for higher plants. They provide the plant with nutrients and water, anchor the plant in the soil, and can serve as energy storage organs. One remarkable feature of roots is that they are able to adjust their growth to changing environments. This adjustment is possible through mechanisms that modulate a diverse set of root traits such as growth rate, diameter, growth direction and lateral root formation. The basis of these traits and their modulation are at the cellular level, where a multitude of genes and gene networks precisely regulate development in time and space and tune it to environmental conditions. This review first describes the root system and then presents fundamental work that has shed light on the basic regulatory principles of root growth and development. It then considers emerging complexities and how they have been addressed using systems-biology approaches, and then describes and argues for a systems-genetics approach. For reasons of simplicity and conciseness, this review is mostly limited to work from the model plant Arabidopsis thaliana, in which much of the research in root growth regulation at the molecular level has been conducted. While forward genetic approaches have identified key regulators and genetic pathways, systems-biology approaches have been successful in shedding light on complex biological processes, for instance molecular mechanisms involving the quantitative interaction of several molecular components, or the interaction of large numbers of genes. However, there are significant limitations in many of these methods for capturing dynamic processes, as well as relating these processes to genotypic and phenotypic variation. The emerging field of systems genetics promises to overcome some of these limitations by linking genotypes to complex phenotypic and molecular data using approaches from different fields, such as genetics, genomics, systems biology and phenomics. © The Author 2015. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Gene-based interaction analysis shows GABAergic genes interacting with parenting in adolescent depressive symptoms.

PubMed

Van Assche, Evelien; Moons, Tim; Cinar, Ozan; Viechtbauer, Wolfgang; Oldehinkel, Albertine J; Van Leeuwen, Karla; Verschueren, Karine; Colpin, Hilde; Lambrechts, Diether; Van den Noortgate, Wim; Goossens, Luc; Claes, Stephan; van Winkel, Ruud

2017-12-01

Most gene-environment interaction studies (G × E) have focused on single candidate genes. This approach is criticized for its expectations of large effect sizes and occurrence of spurious results. We describe an approach that accounts for the polygenic nature of most psychiatric phenotypes and reduces the risk of false-positive findings. We apply this method focusing on the role of perceived parental support, psychological control, and harsh punishment in depressive symptoms in adolescence. Analyses were conducted on 982 adolescents of Caucasian origin (M age (SD) = 13.78 (.94) years) genotyped for 4,947 SNPs in 263 genes, selected based on a literature survey. The Leuven Adolescent Perceived Parenting Scale (LAPPS) and the Parental Behavior Scale (PBS) were used to assess perceived parental psychological control, harsh punishment, and support. The Center for Epidemiologic Studies Depression Scale (CES-D) was the outcome. We used gene-based testing taking into account linkage disequilibrium to identify genes containing SNPs exhibiting an interaction with environmental factors yielding a p-value per single gene. Significant results at the corrected p-value of p < 1.90 × 10 -4 were examined in an independent replication sample of Dutch adolescents (N = 1354). Two genes showed evidence for interaction with perceived support: GABRR1 (p = 4.62 × 10 -5 ) and GABRR2 (p = 9.05 × 10 -6 ). No genes interacted significantly with psychological control or harsh punishment. Gene-based analysis was unable to confirm the interaction of GABRR1 or GABRR2 with support in the replication sample. However, for GABRR2, but not GABRR1, the correlation of the estimates between the two datasets was significant (r (46) = .32; p = .027) and a gene-based analysis of the combined datasets supported GABRR2 × support interaction (p = 1.63 × 10 -4 ). We present a gene-based method for gene-environment interactions in a polygenic context and show that genes interact differently with particular aspects of parenting. This accentuates the importance of polygenic approaches and the need to accurately assess environmental exposure in G × E. © 2017 Association for Child and Adolescent Mental Health.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wagner, Maggie R.; Lundberg, Derek S.; del Rio, Tijana G.

Bacteria living on and in leaves and roots influence many aspects of plant health, so the extent of a plant's genetic control over its microbiota is of great interest to crop breeders and evolutionary biologists. Laboratory-based studies, because they poorly simulate true environmental heterogeneity, may misestimate or totally miss the influence of certain host genes on the microbiome. Here we report a large-scale field experiment to disentangle the effects of genotype, environment, age and year of harvest on bacterial communities associated with leaves and roots of Boechera stricta (Brassicaceae), a perennial wild mustard. Host genetic control of the microbiome ismore » evident in leaves but not roots, and varies substantially among sites. Microbiome composition also shifts as plants age. Furthermore, a large proportion of leaf bacterial groups are shared with roots, suggesting inoculation from soil. Our results demonstrate how genotype-by-environment interactions contribute to the complexity of microbiome assembly in natural environments.« less

From Genes to Networks: Characterizing Gene-Regulatory Interactions in Plants.

PubMed

Kaufmann, Kerstin; Chen, Dijun

2017-01-01

Plants, like other eukaryotes, have evolved complex mechanisms to coordinate gene expression during development, environmental response, and cellular homeostasis. Transcription factors (TFs), accompanied by basic cofactors and posttranscriptional regulators, are key players in gene-regulatory networks (GRNs). The coordinated control of gene activity is achieved by the interplay of these factors and by physical interactions between TFs and DNA. Here, we will briefly outline recent technological progress made to elucidate GRNs in plants. We will focus on techniques that allow us to characterize physical interactions in GRNs in plants and to analyze their regulatory consequences. Targeted manipulation allows us to test the relevance of specific gene-regulatory interactions. The combination of genome-wide experimental approaches with mathematical modeling allows us to get deeper insights into key-regulatory interactions and combinatorial control of important processes in plants.

5C analysis of the Epidermal Differentiation Complex locus reveals distinct chromatin interaction networks between gene-rich and gene-poor TADs in skin epithelial cells

PubMed Central

Malashchuk, Igor; Lajoie, Brian R.; Mardaryev, Andrei N.; Gdula, Michal R.; Sharov, Andrey A.; Kohwi-Shigematsu, Terumi; Fessing, Michael Y.

2017-01-01

Mammalian genomes contain several dozens of large (>0.5 Mbp) lineage-specific gene loci harbouring functionally related genes. However, spatial chromatin folding, organization of the enhancer-promoter networks and their relevance to Topologically Associating Domains (TADs) in these loci remain poorly understood. TADs are principle units of the genome folding and represents the DNA regions within which DNA interacts more frequently and less frequently across the TAD boundary. Here, we used Chromatin Conformation Capture Carbon Copy (5C) technology to characterize spatial chromatin interaction network in the 3.1 Mb Epidermal Differentiation Complex (EDC) locus harbouring 61 functionally related genes that show lineage-specific activation during terminal keratinocyte differentiation in the epidermis. 5C data validated by 3D-FISH demonstrate that the EDC locus is organized into several TADs showing distinct lineage-specific chromatin interaction networks based on their transcription activity and the gene-rich or gene-poor status. Correlation of the 5C results with genome-wide studies for enhancer-specific histone modifications (H3K4me1 and H3K27ac) revealed that the majority of spatial chromatin interactions that involves the gene-rich TADs at the EDC locus in keratinocytes include both intra- and inter-TAD interaction networks, connecting gene promoters and enhancers. Compared to thymocytes in which the EDC locus is mostly transcriptionally inactive, these interactions were found to be keratinocyte-specific. In keratinocytes, the promoter-enhancer anchoring regions in the gene-rich transcriptionally active TADs are enriched for the binding of chromatin architectural proteins CTCF, Rad21 and chromatin remodeler Brg1. In contrast to gene-rich TADs, gene-poor TADs show preferential spatial contacts with each other, do not contain active enhancers and show decreased binding of CTCF, Rad21 and Brg1 in keratinocytes. Thus, spatial interactions between gene promoters and enhancers at the multi-TAD EDC locus in skin epithelial cells are cell type-specific and involve extensive contacts within TADs as well as between different gene-rich TADs, forming the framework for lineage-specific transcription. PMID:28863138

Genes-environment interactions in obesity- and diabetes-associated pancreatic cancer: a GWAS data analysis.

PubMed

Tang, Hongwei; Wei, Peng; Duell, Eric J; Risch, Harvey A; Olson, Sara H; Bueno-de-Mesquita, H Bas; Gallinger, Steven; Holly, Elizabeth A; Petersen, Gloria M; Bracci, Paige M; McWilliams, Robert R; Jenab, Mazda; Riboli, Elio; Tjønneland, Anne; Boutron-Ruault, Marie Christine; Kaaks, Rudolf; Trichopoulos, Dimitrios; Panico, Salvatore; Sund, Malin; Peeters, Petra H M; Khaw, Kay-Tee; Amos, Christopher I; Li, Donghui

2014-01-01

Obesity and diabetes are potentially alterable risk factors for pancreatic cancer. Genetic factors that modify the associations of obesity and diabetes with pancreatic cancer have previously not been examined at the genome-wide level. Using genome-wide association studies (GWAS) genotype and risk factor data from the Pancreatic Cancer Case Control Consortium, we conducted a discovery study of 2,028 cases and 2,109 controls to examine gene-obesity and gene-diabetes interactions in relation to pancreatic cancer risk by using the likelihood-ratio test nested in logistic regression models and Ingenuity Pathway Analysis (IPA). After adjusting for multiple comparisons, a significant interaction of the chemokine signaling pathway with obesity (P = 3.29 × 10(-6)) and a near significant interaction of calcium signaling pathway with diabetes (P = 1.57 × 10(-4)) in modifying the risk of pancreatic cancer were observed. These findings were supported by results from IPA analysis of the top genes with nominal interactions. The major contributing genes to the two top pathways include GNGT2, RELA, TIAM1, and GNAS. None of the individual genes or single-nucleotide polymorphism (SNP) except one SNP remained significant after adjusting for multiple testing. Notably, SNP rs10818684 of the PTGS1 gene showed an interaction with diabetes (P = 7.91 × 10(-7)) at a false discovery rate of 6%. Genetic variations in inflammatory response and insulin resistance may affect the risk of obesity- and diabetes-related pancreatic cancer. These observations should be replicated in additional large datasets. A gene-environment interaction analysis may provide new insights into the genetic susceptibility and molecular mechanisms of obesity- and diabetes-related pancreatic cancer.

Genomic and genetic analyses of diversity and plant interactions of Pseudomonas fluorescens

PubMed Central

Silby, Mark W; Cerdeño-Tárraga, Ana M; Vernikos, Georgios S; Giddens, Stephen R; Jackson, Robert W; Preston, Gail M; Zhang, Xue-Xian; Moon, Christina D; Gehrig, Stefanie M; Godfrey, Scott AC; Knight, Christopher G; Malone, Jacob G; Robinson, Zena; Spiers, Andrew J; Harris, Simon; Challis, Gregory L; Yaxley, Alice M; Harris, David; Seeger, Kathy; Murphy, Lee; Rutter, Simon; Squares, Rob; Quail, Michael A; Saunders, Elizabeth; Mavromatis, Konstantinos; Brettin, Thomas S; Bentley, Stephen D; Hothersall, Joanne; Stephens, Elton; Thomas, Christopher M; Parkhill, Julian; Levy, Stuart B; Rainey, Paul B; Thomson, Nicholas R

2009-01-01

Background Pseudomonas fluorescens are common soil bacteria that can improve plant health through nutrient cycling, pathogen antagonism and induction of plant defenses. The genome sequences of strains SBW25 and Pf0-1 were determined and compared to each other and with P. fluorescens Pf-5. A functional genomic in vivo expression technology (IVET) screen provided insight into genes used by P. fluorescens in its natural environment and an improved understanding of the ecological significance of diversity within this species. Results Comparisons of three P. fluorescens genomes (SBW25, Pf0-1, Pf-5) revealed considerable divergence: 61% of genes are shared, the majority located near the replication origin. Phylogenetic and average amino acid identity analyses showed a low overall relationship. A functional screen of SBW25 defined 125 plant-induced genes including a range of functions specific to the plant environment. Orthologues of 83 of these exist in Pf0-1 and Pf-5, with 73 shared by both strains. The P. fluorescens genomes carry numerous complex repetitive DNA sequences, some resembling Miniature Inverted-repeat Transposable Elements (MITEs). In SBW25, repeat density and distribution revealed 'repeat deserts' lacking repeats, covering approximately 40% of the genome. Conclusions P. fluorescens genomes are highly diverse. Strain-specific regions around the replication terminus suggest genome compartmentalization. The genomic heterogeneity among the three strains is reminiscent of a species complex rather than a single species. That 42% of plant-inducible genes were not shared by all strains reinforces this conclusion and shows that ecological success requires specialized and core functions. The diversity also indicates the significant size of genetic information within the Pseudomonas pan genome. PMID:19432983

Adenovirus small E1A employs the lysine acetylases p300/CBP and tumor suppressor Rb to repress select host genes and promote productive virus infection.

PubMed

Ferrari, Roberto; Gou, Dawei; Jawdekar, Gauri; Johnson, Sarah A; Nava, Miguel; Su, Trent; Yousef, Ahmed F; Zemke, Nathan R; Pellegrini, Matteo; Kurdistani, Siavash K; Berk, Arnold J

2014-11-12

Oncogenic transformation by adenovirus small e1a depends on simultaneous interactions with the host lysine acetylases p300/CBP and the tumor suppressor RB. How these interactions influence cellular gene expression remains unclear. We find that e1a displaces RBs from E2F transcription factors and promotes p300 acetylation of RB1 K873/K874 to lock it into a repressing conformation that interacts with repressive chromatin-modifying enzymes. These repressing p300-e1a-RB1 complexes specifically interact with host genes that have unusually high p300 association within the gene body. The TGF-β, TNF-, and interleukin-signaling pathway components are enriched among such p300-targeted genes. The p300-e1a-RB1 complex condenses chromatin in a manner dependent on HDAC activity, p300 lysine acetylase activity, the p300 bromodomain, and RB K873/K874 and e1a K239 acetylation to repress host genes that would otherwise inhibit productive virus infection. Thus, adenovirus employs e1a to repress host genes that interfere with viral replication. Copyright © 2014 Elsevier Inc. All rights reserved.

Differential sensitivity to the environment: contribution of cognitive biases and genes to psychological wellbeing

PubMed Central

Fox, E; Beevers, C G

2016-01-01

Negative cognitive biases and genetic variation have been associated with risk of psychopathology in largely independent lines of research. Here, we discuss ways in which these dynamic fields of research might be fruitfully combined. We propose that gene by environment (G × E) interactions may be mediated by selective cognitive biases and that certain forms of genetic ‘reactivity' or ‘sensitivity' may represent heightened sensitivity to the learning environment in a ‘for better and for worse' manner. To progress knowledge in this field, we recommend including assessments of cognitive processing biases; examining G × E interactions in ‘both' negative and positive environments; experimentally manipulating the environment when possible; and moving beyond single-gene effects to assess polygenic sensitivity scores. We formulate a new methodological framework encapsulating cognitive and genetic factors in the development of both psychopathology and optimal wellbeing that holds long-term promise for the development of new personalized therapies. PMID:27431291

BDNF rs6265 methylation and genotype interact on risk for schizophrenia

PubMed Central

Ursini, Gianluca; Cavalleri, Tommaso; Fazio, Leonardo; Angrisano, Tiziana; Iacovelli, Luisa; Porcelli, Annamaria; Maddalena, Giancarlo; Punzi, Giovanna; Mancini, Marina; Gelao, Barbara; Romano, Raffaella; Masellis, Rita; Calabrese, Francesca; Rampino, Antonio; Taurisano, Paolo; Giorgio, Annabella Di; Keller, Simona; Tarantini, Letizia; Sinibaldi, Lorenzo; Quarto, Tiziana; Popolizio, Teresa; Caforio, Grazia; Blasi, Giuseppe; Riva, Marco A.; De Blasi, Antonio; Chiariotti, Lorenzo; Bollati, Valentina; Bertolino, Alessandro

2016-01-01

Abstract Epigenetic mechanisms can mediate gene-environment interactions relevant for complex disorders. The BDNF gene is crucial for development and brain plasticity, is sensitive to environmental stressors, such as hypoxia, and harbors the functional SNP rs6265 (Val66Met), which creates or abolishes a CpG dinucleotide for DNA methylation. We found that methylation at the BDNF rs6265 Val allele in peripheral blood of healthy subjects is associated with hypoxia-related early life events (hOCs) and intermediate phenotypes for schizophrenia in a distinctive manner, depending on rs6265 genotype: in ValVal individuals increased methylation is associated with exposure to hOCs and impaired working memory (WM) accuracy, while the opposite is true for ValMet subjects. Also, rs6265 methylation and hOCs interact in modulating WM-related prefrontal activity, another intermediate phenotype for schizophrenia, with an analogous opposite direction in the 2 genotypes. Consistently, rs6265 methylation has a different association with schizophrenia risk in ValVals and ValMets. The relationships of methylation with BDNF levels and of genotype with BHLHB2 binding likely contribute to these opposite effects of methylation. We conclude that BDNF rs6265 methylation interacts with genotype to bridge early environmental exposures to adult phenotypes, relevant for schizophrenia. The study of epigenetic changes in regions containing genetic variation relevant for human diseases may have beneficial implications for the understanding of how genes are actually translated into phenotypes. PMID:26889735

Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns.

PubMed

Lezon, Timothy R; Banavar, Jayanth R; Cieplak, Marek; Maritan, Amos; Fedoroff, Nina V

2006-12-12

We describe a method based on the principle of entropy maximization to identify the gene interaction network with the highest probability of giving rise to experimentally observed transcript profiles. In its simplest form, the method yields the pairwise gene interaction network, but it can also be extended to deduce higher-order interactions. Analysis of microarray data from genes in Saccharomyces cerevisiae chemostat cultures exhibiting energy metabolic oscillations identifies a gene interaction network that reflects the intracellular communication pathways that adjust cellular metabolic activity and cell division to the limiting nutrient conditions that trigger metabolic oscillations. The success of the present approach in extracting meaningful genetic connections suggests that the maximum entropy principle is a useful concept for understanding living systems, as it is for other complex, nonequilibrium systems.

Central and Peripheral Regulation of Food Intake and Physical Activity: Pathways and Genes

PubMed Central

Lenard, Natalie R.; Berthoud, Hans-Rudolf

2009-01-01

A changing environment and lifestyle on the background of evolutionary engraved and perinatally imprinted physiological response patterns is the foremost explanation for the current obesity epidemic. However, it is not clear what the mechanisms are by which the modern environment overrides the physiological controls of appetite and homeostatic body-weight regulation. Food intake and energy expenditure are controlled by complex, redundant, and distributed neural systems involving thousands of genes and reflecting the fundamental biological importance of adequate nutrient supply and energy balance. There has been much progress in identifying the important role of hypothalamus and caudal brainstem in the various hormonal and neural mechanisms by which the brain informs itself about availability of ingested and stored nutrients and, in turn, generates behavioral, autonomic, and endocrine output. Some of the genes involved in this “homeostatic” regulator are crucial for energy balance as manifested in the well-known monogenic obesity models. However, it can be clearly demonstrated that much larger portions of the nervous system of animals and humans, including the cortex, basal ganglia, and the limbic system, are concerned with the procurement of food as a basic and evolutionarily conserved survival mechanism to defend the lower limits of adiposity. By forming representations and reward expectancies through processes of learning and memory, these systems evolved to engage powerful emotions for guaranteed supply with, and ingestion of, beneficial foods from a sparse and often hostile environment. They are now simply overwhelmed with an abundance of food and food cues no longer contested by predators and interrupted by famines. The anatomy, chemistry, and functions of these elaborate neural systems and their interactions with the “homeostatic” regulator in the hypothalamus are poorly understood, and many of the genes involved are either unknown or not well characterized. This is regrettable because these systems are directly and primarily involved in the interactions of the modern environment and lifestyle with the human body. They are no less “physiological” than metabolic-regulatory mechanisms that have attracted most of the research during the past 15 years. PMID:19190620

ORCHIDS: an observational randomized controlled trial on childhood differential susceptibility.

PubMed

Chhangur, Rabia R; Weeland, Joyce; Overbeek, Geertjan; Matthys, Walterchj; Orobio de Castro, Bram

2012-10-29

A central tenet in developmental psychopathology is that childhood rearing experiences have a major impact on children's development. Recently, candidate genes have been identified that may cause children to be differentially susceptible to these experiences (i.e., susceptibility genes). However, our understanding of the differential impact of parenting is limited at best. Specifically, more experimental research is needed. The ORCHIDS study will investigate gene-(gene-)environment interactions to obtain more insight into a) moderating effects of polymorphisms on the link between parenting and child behavior, and b) behavioral mechanisms that underlie these gene-(gene-)environment interactions in an experimental design. The ORCHIDS study is a randomized controlled trial, in which the environment will be manipulated with an intervention (i.e., Incredible Years parent training). In a screening, families with children aged 4-8 who show mild to (sub)clinical behavior problems will be targeted through community records via two Dutch regional healthcare organizations. Assessments in both the intervention and control condition will be conducted at baseline (i.e., pretest), after 6 months (i.e., posttest), and after 10 months (i.e., follow-up). This study protocol describes the design of a randomized controlled trial that investigates gene-(gene-)environment interactions in the development of child behavior. Two hypotheses will be tested. First, we expect that children in the intervention condition who carry one or more susceptibility genes will show significantly lower levels of problem behavior and higher levels of prosocial behavior after their parent(s) received the Incredible Years training, compared to children without these genes, or children in the control group. Second, we expect that children carrying one or more susceptibility genes will show a heightened sensitivity to changes in parenting behaviors, and will manifest higher emotional synchronization in dyadic interchanges with their parents. This may lead to either more prosocial behavior or antisocial behavior depending on their parents' behavior. Dutch Trial Register (NTR3594).

The BDNF Val66Met Polymorphism Interacts with Maternal Parenting Influencing Adolescent Depressive Symptoms: Evidence of Differential Susceptibility Model.

PubMed

Zhang, Leilei; Li, Zhi; Chen, Jie; Li, Xinying; Zhang, Jianxin; Belsky, Jay

2016-03-01

Although depressive symptoms are common during adolescence, little research has examined gene-environment interaction on youth depression. This study chose the brain-derived neurotrophic factor (BDNF) gene, tested the interaction between a functional polymorphism resulting amino acid substitution of valine (Val) to methionine (Met) in the proBDNF protein at codon 66 (Val66Met), and maternal parenting on youth depressive symptoms in a sample of 780 community adolescents of Chinese Han ethnicity (aged 11-17, M = 13.6, 51.3 % females). Participants reported their depressive symptoms and perceived maternal parenting. Results indicated the BDNF Val66Met polymorphism significantly moderated the influence of maternal warmth-reasoning, but not harshness-hostility, on youth depressive symptoms. Confirmatory model evaluation indicated that the interaction effect involving warmth-reasoning conformed to the differential-susceptibility rather than diathesis-stress model of person-X-environment interaction. Thus, Val carriers experienced less depressive symptoms than Met homozygotes when mothering was more positive but more symptoms when mothering was less positive. The findings provided evidence in support of the differential susceptibility hypothesis of youth depressive symptoms and shed light on the importance of examining the gene-environment interaction from a developmental perspective.

Aberrant gene expression in mucosa adjacent to tumor reveals a molecular crosstalk in colon cancer

PubMed Central

2014-01-01

Background A colorectal tumor is not an isolated entity growing in a restricted location of the body. The patient’s gut environment constitutes the framework where the tumor evolves and this relationship promotes and includes a complex and tight correlation of the tumor with inflammation, blood vessels formation, nutrition, and gut microbiome composition. The tumor influence in the environment could both promote an anti-tumor or a pro-tumor response. Methods A set of 98 paired adjacent mucosa and tumor tissues from colorectal cancer (CRC) patients and 50 colon mucosa from healthy donors (246 samples in total) were included in this work. RNA extracted from each sample was hybridized in Affymetrix chips Human Genome U219. Functional relationships between genes were inferred by means of systems biology using both transcriptional regulation networks (ARACNe algorithm) and protein-protein interaction networks (BIANA software). Results Here we report a transcriptomic analysis revealing a number of genes activated in adjacent mucosa from CRC patients, not activated in mucosa from healthy donors. A functional analysis of these genes suggested that this active reaction of the adjacent mucosa was related to the presence of the tumor. Transcriptional and protein-interaction networks were used to further elucidate this response of normal gut in front of the tumor, revealing a crosstalk between proteins secreted by the tumor and receptors activated in the adjacent colon tissue; and vice versa. Remarkably, Slit family of proteins activated ROBO receptors in tumor whereas tumor-secreted proteins transduced a cellular signal finally activating AP-1 in adjacent tissue. Conclusions The systems-level approach provides new insights into the micro-ecology of colorectal tumorogenesis. Disrupting this intricate molecular network of cell-cell communication and pro-inflammatory microenvironment could be a therapeutic target in CRC patients. PMID:24597571

Genetic interactions within inositol-related pathways are associated with longitudinal changes in ventricle size

PubMed Central

Koran, Mary Ellen I.; Hohman, Timothy J.; Meda, Shashwath A.; Thornton-Wells, Tricia A.

2013-01-01

The genetic etiology of late onset Alzheimer disease (LOAD) has proven complex, involving clinical and genetic heterogeneity and gene-gene interactions. Recent genome wide association studies (GWAS) in LOAD have led to the discovery of novel genetic risk factors; however, the investigation of gene-gene interactions has been limited. Conventional genetic studies often use binary disease status as the primary phenotype, but for complex brain-based diseases, neuroimaging data can serve as quantitative endophenotypes that correlate with disease status and closely reflect pathological changes. In the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, we tested for association of genetic interactions with longitudinal MRI measurements of the inferior lateral ventricles (ILVs), which have repeatedly shown a relationship to LOAD status and progression. We performed linear regression to evaluate the ability of pathway-derived SNP-SNP pairs to predict the slope of change in volume of the ILVs. After Bonferroni correction, we identified four significant interactions in the right ILV (RILV) corresponding to gene-gene pairs SYNJ2-PI4KA, PARD3-MYH2, PDE3A-ABHD12B and OR2L13-PRKG1 and one significant interaction in the left ILV (LILV) corresponding to SYNJ2-PI4KA. The SNP-SNP interaction corresponding to SYNJ2-PI4KA was identical in the RILV and LILV and was the most significant interaction in each (RILV: p=9.10×10−12; LILV: p=8.20×10−13). Both genes belong to the inositol phosphate signaling pathway which has been previously associated with neurodegeneration in AD and we discuss the possibility that perturbation of this pathway results in a down-regulation of the Akt cell survival pathway and, thereby, decreased neuronal survival, as reflected by increased volume of the ventricles. PMID:24077433

Breast and Prostate Cancer and Hormone-Related Gene Variant Study

Cancer.gov

The Breast and Prostate Cancer and Hormone-Related Gene Variant Study allows large-scale analyses of breast and prostate cancer risk in relation to genetic polymorphisms and gene-environment interactions that affect hormone metabolism.

Gene Environment Interactions and Predictors of Colorectal Cancer in Family-Based, Multi-Ethnic Groups.

PubMed

Shiao, S Pamela K; Grayson, James; Yu, Chong Ho; Wasek, Brandi; Bottiglieri, Teodoro

2018-02-16

For the personalization of polygenic/omics-based health care, the purpose of this study was to examine the gene-environment interactions and predictors of colorectal cancer (CRC) by including five key genes in the one-carbon metabolism pathways. In this proof-of-concept study, we included a total of 54 families and 108 participants, 54 CRC cases and 54 matched family friends representing four major racial ethnic groups in southern California (White, Asian, Hispanics, and Black). We used three phases of data analytics, including exploratory, family-based analyses adjusting for the dependence within the family for sharing genetic heritage, the ensemble method, and generalized regression models for predictive modeling with a machine learning validation procedure to validate the results for enhanced prediction and reproducibility. The results revealed that despite the family members sharing genetic heritage, the CRC group had greater combined gene polymorphism rates than the family controls ( p < 0.05), on MTHFR C677T , MTR A2756G , MTRR A66G, and DHFR 19 bp except MTHFR A1298C. Four racial groups presented different polymorphism rates for four genes (all p < 0.05) except MTHFR A1298C. Following the ensemble method, the most influential factors were identified, and the best predictive models were generated by using the generalized regression models, with Akaike's information criterion and leave-one-out cross validation methods. Body mass index (BMI) and gender were consistent predictors of CRC for both models when individual genes versus total polymorphism counts were used, and alcohol use was interactive with BMI status. Body mass index status was also interactive with both gender and MTHFR C677T gene polymorphism, and the exposure to environmental pollutants was an additional predictor. These results point to the important roles of environmental and modifiable factors in relation to gene-environment interactions in the prevention of CRC.

Structural dissection of an interaction between transcription initiation and termination factors implicated in promoter-terminator cross-talk.

PubMed

Bratkowski, Matthew; Unarta, Ilona Christy; Zhu, Lizhe; Shubbar, Murtada; Huang, Xuhui; Liu, Xin

2018-02-02

Functional cross-talk between the promoter and terminator of a gene has long been noted. Promoters and terminators are juxtaposed to form gene loops in several organisms, and gene looping is thought to be involved in transcriptional regulation. The general transcription factor IIB (TFIIB) and the C-terminal domain phosphatase Ssu72, essential factors of the transcription preinitiation complex and the mRNA processing and polyadenylation complex, respectively, are important for gene loop formation. TFIIB and Ssu72 interact both genetically and physically, but the molecular basis of this interaction is not known. Here we present a crystal structure of the core domain of TFIIB in two new conformations that differ in the relative distance and orientation of the two cyclin-like domains. The observed extraordinary conformational plasticity may underlie the binding of TFIIB to multiple transcription factors and promoter DNAs that occurs in distinct stages of transcription, including initiation, reinitiation, and gene looping. We mapped the binding interface of the TFIIB-Ssu72 complex using a series of systematic, structure-guided in vitro binding and site-specific photocross-linking assays. Our results indicate that Ssu72 competes with acidic activators for TFIIB binding and that Ssu72 disrupts an intramolecular TFIIB complex known to impede transcription initiation. We also show that the TFIIB-binding site on Ssu72 overlaps with the binding site of symplekin, a component of the mRNA processing and polyadenylation complex. We propose a hand-off model in which Ssu72 mediates a conformational transition in TFIIB, accounting for the role of Ssu72 in transcription reinitiation, gene looping, and promoter-terminator cross-talk. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Genome-Wide Localization Study of Yeast Pex11 Identifies Peroxisome–Mitochondria Interactions through the ERMES Complex

PubMed Central

Mattiazzi Ušaj, M.; Brložnik, M.; Kaferle, P.; Žitnik, M.; Wolinski, H.; Leitner, F.; Kohlwein, S.D.; Zupan, B.; Petrovič, U.

2015-01-01

Pex11 is a peroxin that regulates the number of peroxisomes in eukaryotic cells. Recently, it was found that a mutation in one of the three mammalian paralogs, PEX11β, results in a neurological disorder. The molecular function of Pex11, however, is not known. Saccharomyces cerevisiae Pex11 has been shown to recruit to peroxisomes the mitochondrial fission machinery, thus enabling proliferation of peroxisomes. This process is essential for efficient fatty acid β-oxidation. In this study, we used high-content microscopy on a genome-wide scale to determine the subcellular localization pattern of yeast Pex11 in all non-essential gene deletion mutants, as well as in temperature-sensitive essential gene mutants. Pex11 localization and morphology of peroxisomes was profoundly affected by mutations in 104 different genes that were functionally classified. A group of genes encompassing MDM10, MDM12 and MDM34 that encode the mitochondrial and cytosolic components of the ERMES complex was analyzed in greater detail. Deletion of these genes caused a specifically altered Pex11 localization pattern, whereas deletion of MMM1, the gene encoding the fourth, endoplasmic-reticulum-associated component of the complex, did not result in an altered Pex11 localization or peroxisome morphology phenotype. Moreover, we found that Pex11 and Mdm34 physically interact and that Pex11 plays a role in establishing the contact sites between peroxisomes and mitochondria through the ERMES complex. Based on these results, we propose that the mitochondrial/cytosolic components of the ERMES complex establish a direct interaction between mitochondria and peroxisomes through Pex11. PMID:25769804

Explaining human uniqueness: genome interactions with environment, behaviour and culture.

PubMed

Varki, Ajit; Geschwind, Daniel H; Eichler, Evan E

2008-10-01

What makes us human? Specialists in each discipline respond through the lens of their own expertise. In fact, 'anthropogeny' (explaining the origin of humans) requires a transdisciplinary approach that eschews such barriers. Here we take a genomic and genetic perspective towards molecular variation, explore systems analysis of gene expression and discuss an organ-systems approach. Rejecting any 'genes versus environment' dichotomy, we then consider genome interactions with environment, behaviour and culture, finally speculating that aspects of human uniqueness arose because of a primate evolutionary trend towards increasing and irreversible dependence on learned behaviours and culture - perhaps relaxing allowable thresholds for large-scale genomic diversity.

Comparative analysis of methods for detecting interacting loci

PubMed Central

2011-01-01

Background Interactions among genetic loci are believed to play an important role in disease risk. While many methods have been proposed for detecting such interactions, their relative performance remains largely unclear, mainly because different data sources, detection performance criteria, and experimental protocols were used in the papers introducing these methods and in subsequent studies. Moreover, there have been very few studies strictly focused on comparison of existing methods. Given the importance of detecting gene-gene and gene-environment interactions, a rigorous, comprehensive comparison of performance and limitations of available interaction detection methods is warranted. Results We report a comparison of eight representative methods, of which seven were specifically designed to detect interactions among single nucleotide polymorphisms (SNPs), with the last a popular main-effect testing method used as a baseline for performance evaluation. The selected methods, multifactor dimensionality reduction (MDR), full interaction model (FIM), information gain (IG), Bayesian epistasis association mapping (BEAM), SNP harvester (SH), maximum entropy conditional probability modeling (MECPM), logistic regression with an interaction term (LRIT), and logistic regression (LR) were compared on a large number of simulated data sets, each, consistent with complex disease models, embedding multiple sets of interacting SNPs, under different interaction models. The assessment criteria included several relevant detection power measures, family-wise type I error rate, and computational complexity. There are several important results from this study. First, while some SNPs in interactions with strong effects are successfully detected, most of the methods miss many interacting SNPs at an acceptable rate of false positives. In this study, the best-performing method was MECPM. Second, the statistical significance assessment criteria, used by some of the methods to control the type I error rate, are quite conservative, thereby limiting their power and making it difficult to fairly compare them. Third, as expected, power varies for different models and as a function of penetrance, minor allele frequency, linkage disequilibrium and marginal effects. Fourth, the analytical relationships between power and these factors are derived, aiding in the interpretation of the study results. Fifth, for these methods the magnitude of the main effect influences the power of the tests. Sixth, most methods can detect some ground-truth SNPs but have modest power to detect the whole set of interacting SNPs. Conclusion This comparison study provides new insights into the strengths and limitations of current methods for detecting interacting loci. This study, along with freely available simulation tools we provide, should help support development of improved methods. The simulation tools are available at: http://code.google.com/p/simulation-tool-bmc-ms9169818735220977/downloads/list. PMID:21729295

Comparative analysis of methods for detecting interacting loci.

PubMed

Chen, Li; Yu, Guoqiang; Langefeld, Carl D; Miller, David J; Guy, Richard T; Raghuram, Jayaram; Yuan, Xiguo; Herrington, David M; Wang, Yue

2011-07-05

Interactions among genetic loci are believed to play an important role in disease risk. While many methods have been proposed for detecting such interactions, their relative performance remains largely unclear, mainly because different data sources, detection performance criteria, and experimental protocols were used in the papers introducing these methods and in subsequent studies. Moreover, there have been very few studies strictly focused on comparison of existing methods. Given the importance of detecting gene-gene and gene-environment interactions, a rigorous, comprehensive comparison of performance and limitations of available interaction detection methods is warranted. We report a comparison of eight representative methods, of which seven were specifically designed to detect interactions among single nucleotide polymorphisms (SNPs), with the last a popular main-effect testing method used as a baseline for performance evaluation. The selected methods, multifactor dimensionality reduction (MDR), full interaction model (FIM), information gain (IG), Bayesian epistasis association mapping (BEAM), SNP harvester (SH), maximum entropy conditional probability modeling (MECPM), logistic regression with an interaction term (LRIT), and logistic regression (LR) were compared on a large number of simulated data sets, each, consistent with complex disease models, embedding multiple sets of interacting SNPs, under different interaction models. The assessment criteria included several relevant detection power measures, family-wise type I error rate, and computational complexity. There are several important results from this study. First, while some SNPs in interactions with strong effects are successfully detected, most of the methods miss many interacting SNPs at an acceptable rate of false positives. In this study, the best-performing method was MECPM. Second, the statistical significance assessment criteria, used by some of the methods to control the type I error rate, are quite conservative, thereby limiting their power and making it difficult to fairly compare them. Third, as expected, power varies for different models and as a function of penetrance, minor allele frequency, linkage disequilibrium and marginal effects. Fourth, the analytical relationships between power and these factors are derived, aiding in the interpretation of the study results. Fifth, for these methods the magnitude of the main effect influences the power of the tests. Sixth, most methods can detect some ground-truth SNPs but have modest power to detect the whole set of interacting SNPs. This comparison study provides new insights into the strengths and limitations of current methods for detecting interacting loci. This study, along with freely available simulation tools we provide, should help support development of improved methods. The simulation tools are available at: http://code.google.com/p/simulation-tool-bmc-ms9169818735220977/downloads/list.

[The development of antisocial behavior: psychobiological and environmental factors and gene-environment interactions].

PubMed

Gallardo-Pujol, D; Forero, C G; Maydeu-Olivares, A; Andrés-Pueyo, A

Antisocial behavior is a complex phenomenon with strong implications in neurology and psychiatry. In order to study the ontogenetic development of antisocial behavior, we must check for the existence of physiological mechanisms related to it, and to understand its environmentally-modulated functioning. To review the state-of-the-art of the development of antisocial behavior, and especially, of the interaction between environmental and genetic factors. Recent research has highlighted certain brain alterations linked to violent behavior, either at structural, or functional or biochemical levels. Genetic research has also made some advances in this field, discovering some genes--i.e. monoamineoxidase A (MAOA)--related to antisocial behavior. However, the importance of environmental factors in its development must not be left behind. Recent studies have shown that individuals carrying a low transcriptional activity allele of the MAOA gene, and that also suffered severe maltreatment are more prone to antisocial behavior. This interaction is biologically relevant, as there are underlying biological mechanisms that may be able to explain the ethiopathogeny of antisocial behavior. Although the works herein presented pioneered the field, they are limited by the fact that all the reviewed variables are associated to antisocial behavior, but they lack direct causal evidence of their effects on antisocial behavior. Undoubtedly, future research on psychobiological mechanisms and the understanding of their environmental modulation will help finding therapeutic targets and preventive strategies for antisocial behavior.

Gene × environment interaction on intergroup bias: the role of 5-HTTLPR and perceived outgroup threat

PubMed Central

Livingston, Robert W.; Hong, Ying-Yi; Chiao, Joan Y.

2014-01-01

Perceived threat from outgroups is a consistent social-environmental antecedent of intergroup bias (i.e. prejudice, ingroup favoritism). The serotonin transporter gene polymorphism (5-HTTLPR) has been associated with individual variations in sensitivity to context, particularly stressful and threatening situations. Here, we examined how 5-HTTLPR and environmental factors signaling potential outgroup threat dynamically interact to shape intergroup bias. Across two studies, we provide novel evidence for a gene–environment interaction on the acquisition of intergroup bias and prejudice. Greater exposure to signals of outgroup threat, such as negative prior contact with outgroups and perceived danger from the social environment, were more predictive of intergroup bias among participants possessing at least one short allele (vs two long alleles) of 5-HTTLPR. Furthermore, this gene x environment interaction was observed for biases directed at diverse ethnic and arbitrarily-defined outgroups across measures reflecting intergroup biases in evaluation and discriminatory behavior. These findings reveal a candidate genetic mechanism for the acquisition of intergroup bias, and suggest that intergroup bias is dually inherited and transmitted through the interplay of social (i.e. contextual cues of outgroup threat) and biological mechanisms (i.e. genetic sensitivity toward threatening contexts) that regulate perceived intergroup threats. PMID:23887814

Probing Teachers' Lesson Planning: Promoting Metacognition

ERIC Educational Resources Information Center

Eilam, Billie

2017-01-01

Classrooms are complex systems, with dynamic interactions of different kinds among their composing varied elements. Such complex interactions lead to the system's unpredictable emergent learning behaviors. To support teachers' lesson planning and monitoring in the complex environment of classrooms, the present article examines the core…

Epigenetics in Developmental Disorder: ADHD and Endophenotypes

PubMed Central

Archer, Trevor; Oscar-Berman, Marlene; Blum, Kenneth

2011-01-01

Heterogeneity in attention-deficit/hyperactivity disorder (ADHD), with complex interactive operations of genetic and environmental factors, is expressed in a variety of disorder manifestations: severity, co-morbidities of symptoms, and the effects of genes on phenotypes. Neurodevelopmental influences of genomic imprinting have set the stage for the structural-physiological variations that modulate the cognitive, affective, and pathophysiological domains of ADHD. The relative contributions of genetic and environmental factors provide rapidly proliferating insights into the developmental trajectory of the condition, both structurally and functionally. Parent-of-origin effects seem to support the notion that genetic risks for disease process debut often interact with the social environment, i.e., the parental environment in infants and young children. The notion of endophenotypes, markers of an underlying liability to the disorder, may facilitate detection of genetic risks relative to a complex clinical disorder. Simple genetic association has proven insufficient to explain the spectrum of ADHD. At a primary level of analysis, the consideration of epigenetic regulation of brain signalling mechanisms, dopamine, serotonin, and noradrenaline is examined. Neurotrophic factors that participate in the neurogenesis, survival, and functional maintenance of brain systems, are involved in neuroplasticity alterations underlying brain disorders, and are implicated in the genetic predisposition to ADHD, but not obviously, nor in a simple or straightforward fashion. In the context of intervention, genetic linkage studies of ADHD pharmacological intervention have demonstrated that associations have fitted the “drug response phenotype,” rather than the disorder diagnosis. Despite conflicting evidence for the existence, or not, of genetic associations between disorder diagnosis and genes regulating the structure and function of neurotransmitters and brain-derived neurotrophic factor (BDNF), associations between symptoms-profiles endophenotypes and single nucleotide polymorphisms appear reassuring. PMID:22224195

Transitions from mono- to co- to tri-culture uniquely affect gene expression in breast cancer, stromal, and immune compartments

PubMed Central

Weinberger, Emma M.; Regehr, Keil J.; Berry, Scott M.; Beebe, David J.; Alarid, Elaine T.

2016-01-01

Heterotypic interactions in cancer microenvironments play important roles in disease initiation, progression, and spread. Co-culture is the predominant approach used in dissecting paracrine interactions between tumor and stromal cells, but functional results from simple co-cultures frequently fail to correlate to in vivo conditions. Though complex heterotypic in vitro models have improved functional relevance, there is little systematic knowledge of how multi-culture parameters influence this recapitulation. We therefore have employed a more iterative approach to investigate the influence of increasing model complexity; increased heterotypic complexity specifically. Here we describe how the compartmentalized and microscale elements of our multi-culture device allowed us to obtain gene expression data from one cell type at a time in a heterotypic culture where cells communicated through paracrine interactions. With our device we generated a large dataset comprised of cell type specific gene-expression patterns for cultures of increasing complexity (three cell types in mono-, co-, or tri-culture) not readily accessible in other systems. Principal component analysis indicated that gene expression was changed in co-culture but was often more strongly altered in tri-culture as compared to mono-culture. Our analysis revealed that cell type identity and the complexity around it (mono-, co-, or tri-culture) influence gene regulation. We also observed evidence of complementary regulation between cell types in the same heterotypic culture. Here we demonstrate the utility of our platform in providing insight into how tumor and stromal cells respond to microenvironments of varying complexities highlighting the expanding importance of heterotypic cultures that go beyond conventional co-culture. PMID:27432323

Genome-environment interactions and prospective technology assessment: evolution from pharmacogenomics to nutrigenomics and ecogenomics.

PubMed

Ozdemir, Vural; Motulsky, Arno G; Kolker, Eugene; Godard, Béatrice

2009-02-01

The relationships between food, nutrition science, and health outcomes have been mapped over the past century. Genomic variation among individuals and populations is a new factor that enriches and challenges our understanding of these complex relationships. Hence, the confluence of nutritional science and genomics-nutrigenomics--was the focus of the OMICS: A Journal of Integrative Biology in December 2008 (Part 1). The 2009 Special Issue (Part 2) concludes the analysis of nutrigenomics research and innovations. Together, these two issues expand the scope and depth of critical scholarship in nutrigenomics, in keeping with an integrated multidisciplinary analysis across the bioscience, omics technology, social, ethical, intellectual property and policy dimensions. Historically, the field of pharmacogenetics provided the first examples of specifically identifiable gene variants predisposing to unexpected responses to drugs since the 1950s. Brewer coined the term ecogenetics in 1971 to broaden the concept of gene-environment interactions from drugs and nutrition to include environmental agents in general. In the mid-1990s, introduction of high-throughput technologies led to the terms pharmacogenomics, nutrigenomics and ecogenomics to describe, respectively, the contribution of genomic variability to differential responses to drugs, food, and environment defined in the broadest sense. The distinctions, if any, between these newer fields (e.g., nutrigenomics) and their predecessors (e.g., nutrigenetics) remain to be delineated. For nutrigenomics, its reliance on genome-wide analyses may lead to detection of new biological mechanisms governing host response to food. Recognizing "genome-environment interactions" as the conceptual thread that connects and runs through pharmacogenomics, nutrigenomics, and ecogenomics may contribute toward anticipatory governance and prospective real-time analysis of these omics fields. Such real-time analysis of omics technologies and innovations is crucial, because it can influence and positively shape them as these approaches develop, and help avoid predictable pitfalls, and thus ensure their effective and ethical application in the laboratory, clinic, and society.

A mathematical model of in vivo bovine blastocyst developmental to gestational Day 15.

PubMed

Shorten, P R; Donnison, M; McDonald, R M; Meier, S; Ledgard, A M; Berg, D

2018-06-20

Bovine embryo growth involves a complex interaction between the developing embryo and the growth-promoting potential of the uterine environment. We have previously established links between embryonic factors (embryo stage, embryo gene expression), maternal factors (progesterone, body condition score), and embryonic growth to 8 d after bulk transfer of Day 7 in vitro-produced blastocysts. In this study we recovered blastocysts on Days 7 and 15 after artificial insemination to test the hypothesis that in vivo and in vitro embryos follow a similar growth program. We conducted our study using 4 commercial farms and repeated our study over 2 yr (2014, 2015), with data available from 2 of the 4 farms in the second year. Morphological and gene expression measurements (196 candidate genes) of the Day 7 embryos were measured and the progesterone concentration of the cows were measured throughout the reproductive cycle as a reflection of the state of the uterine environment. These data were also used to assess the interaction between the uterine environment and the developing embryo and to examine how well Day 7 embryo stage can be predicted from the Day 7 gene expression profile. Progesterone was not a strong predictor of in vivo embryo growth to Day 15. This contrasts with a range of Day 7 embryo transfer studies which demonstrated that progesterone is a very good predictor of embryo growth to Day 15. Our analysis demonstrates that in vivo embryos are 3 times less sensitive to progesterone than in vitro-transferred embryos (up to Day 15). This highlights that caution must be applied when extrapolating the results of in vitro embryo transfer studies to the in vivo situation. The similar variance in measured and predicted (based on Day 15 length) Day 7 embryo stage indicate low stochastic perturbations for in vivo embryo growth (large stochastic growth effects would generate a significantly larger standard deviation in measured embryo length on Day 15). We also identified that Day 7 embryo stage could be predicted based on the Day 7 gene expression profile (58% overall success rate for classification of 5 embryo stages). Our analysis also associated genes with each developmental stage and demonstrates the high level of temporal regulation of genes that occurs during early embryonic development. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Mediator complex cooperatively regulates transcription of retinoic acid target genes with Polycomb Repressive Complex 2 during neuronal differentiation.

PubMed

Fukasawa, Rikiya; Iida, Satoshi; Tsutsui, Taiki; Hirose, Yutaka; Ohkuma, Yoshiaki

2015-11-01

The Mediator complex (Mediator) plays key roles in transcription and functions as the nexus for integration of various transcriptional signals. Previously, we screened for Mediator cyclin-dependent kinase (CDK)-interacting factors and identified three proteins related to chromatin regulation. One of them, SUZ12 is required for both stability and activity of Polycomb Repressive Complex 2 (PRC2). PRC2 primarily suppresses gene expression through histone H3 lysine 27 trimethylation, resulting in stem cell maintenance and differentiation; perturbation of this process leads to oncogenesis. Recent work showed that Mediator contributes to the embryonic stem cell state through DNA loop formation, which is strongly associated with chromatin architecture; however, it remains unclear how Mediator regulates gene expression in cooperation with chromatin regulators (i.e. writers, readers and remodelers). We found that Mediator CDKs interact directly with the PRC2 subunit EZH2, as well as SUZ12. Known PRC2 target genes were deregulated by Mediator CDK knockdown during neuronal differentiation, and both Mediator and PRC2 complexes co-occupied the promoters of developmental genes regulated by retinoic acid. Our results provide a mechanistic link between Mediator and PRC2 during neuronal differentiation. © The Authors 2015. Published by Oxford University Press on behalf of the Japanese Biochemical Society. All rights reserved.

Pharmacogenetics of drug-drug interaction and drug-drug-gene interaction: a systematic review on CYP2C9, CYP2C19 and CYP2D6.

PubMed

Bahar, Muh Akbar; Setiawan, Didik; Hak, Eelko; Wilffert, Bob

2017-05-01

Currently, most guidelines on drug-drug interaction (DDI) neither consider the potential effect of genetic polymorphism in the strength of the interaction nor do they account for the complex interaction caused by the combination of DDI and drug-gene interaction (DGI) where there are multiple biotransformation pathways, which is referred to as drug-drug-gene interaction (DDGI). In this systematic review, we report the impact of pharmacogenetics on DDI and DDGI in which three major drug-metabolizing enzymes - CYP2C9, CYP2C19 and CYP2D6 - are central. We observed that several DDI and DDGI are highly gene-dependent, leading to a different magnitude of interaction. Precision drug therapy should take pharmacogenetics into account when drug interactions in clinical practice are expected.

A Social Network Approach Reveals Associations between Mouse Social Dominance and Brain Gene Expression.

PubMed

So, Nina; Franks, Becca; Lim, Sean; Curley, James P

2015-01-01

Modelling complex social behavior in the laboratory is challenging and requires analyses of dyadic interactions occurring over time in a physically and socially complex environment. In the current study, we approached the analyses of complex social interactions in group-housed male CD1 mice living in a large vivarium. Intensive observations of social interactions during a 3-week period indicated that male mice form a highly linear and steep dominance hierarchy that is maintained by fighting and chasing behaviors. Individual animals were classified as dominant, sub-dominant or subordinate according to their David's Scores and I& SI ranking. Using a novel dynamic temporal Glicko rating method, we ascertained that the dominance hierarchy was stable across time. Using social network analyses, we characterized the behavior of individuals within 66 unique relationships in the social group. We identified two individual network metrics, Kleinberg's Hub Centrality and Bonacich's Power Centrality, as accurate predictors of individual dominance and power. Comparing across behaviors, we establish that agonistic, grooming and sniffing social networks possess their own distinctive characteristics in terms of density, average path length, reciprocity out-degree centralization and out-closeness centralization. Though grooming ties between individuals were largely independent of other social networks, sniffing relationships were highly predictive of the directionality of agonistic relationships. Individual variation in dominance status was associated with brain gene expression, with more dominant individuals having higher levels of corticotropin releasing factor mRNA in the medial and central nuclei of the amygdala and the medial preoptic area of the hypothalamus, as well as higher levels of hippocampal glucocorticoid receptor and brain-derived neurotrophic factor mRNA. This study demonstrates the potential and significance of combining complex social housing and intensive behavioral characterization of group-living animals with the utilization of novel statistical methods to further our understanding of the neurobiological basis of social behavior at the individual, relationship and group levels.

A Social Network Approach Reveals Associations between Mouse Social Dominance and Brain Gene Expression

PubMed Central

So, Nina; Franks, Becca; Lim, Sean; Curley, James P.

2015-01-01

Modelling complex social behavior in the laboratory is challenging and requires analyses of dyadic interactions occurring over time in a physically and socially complex environment. In the current study, we approached the analyses of complex social interactions in group-housed male CD1 mice living in a large vivarium. Intensive observations of social interactions during a 3-week period indicated that male mice form a highly linear and steep dominance hierarchy that is maintained by fighting and chasing behaviors. Individual animals were classified as dominant, sub-dominant or subordinate according to their David’s Scores and I& SI ranking. Using a novel dynamic temporal Glicko rating method, we ascertained that the dominance hierarchy was stable across time. Using social network analyses, we characterized the behavior of individuals within 66 unique relationships in the social group. We identified two individual network metrics, Kleinberg’s Hub Centrality and Bonacich’s Power Centrality, as accurate predictors of individual dominance and power. Comparing across behaviors, we establish that agonistic, grooming and sniffing social networks possess their own distinctive characteristics in terms of density, average path length, reciprocity out-degree centralization and out-closeness centralization. Though grooming ties between individuals were largely independent of other social networks, sniffing relationships were highly predictive of the directionality of agonistic relationships. Individual variation in dominance status was associated with brain gene expression, with more dominant individuals having higher levels of corticotropin releasing factor mRNA in the medial and central nuclei of the amygdala and the medial preoptic area of the hypothalamus, as well as higher levels of hippocampal glucocorticoid receptor and brain-derived neurotrophic factor mRNA. This study demonstrates the potential and significance of combining complex social housing and intensive behavioral characterization of group-living animals with the utilization of novel statistical methods to further our understanding of the neurobiological basis of social behavior at the individual, relationship and group levels. PMID:26226265

NRIP enhances HPV gene expression via interaction with either GR or E2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, Szu-Wei; Lu, Pei-Yu; Guo, Jih-Huong

We previously identified a gene, nuclear receptor-interaction protein (NRIP), which functions as a transcription cofactor in glucocorticoid receptor (GR) and human papillomavirus E2 (HPV E2)-driven gene expression. Here, we comprehensively evaluated the role of NRIP in HPV-16 gene expression. NRIP acts as a transcription cofactor to enhance GR-regulated HPV-16 gene expression in the presence of hormone. NRIP also can form complex with E2 that caused NRIP-induced HPV gene expression via E2-binding sites in a hormone-independent manner. Furthermore, NRIP can associate with GR and E2 to form tri-protein complex to activate HPV gene expression via GRE, not the E2-binding site, inmore » a hormone-dependent manner. These results indicate that NRIP and GR are viral E2-binding proteins and that NRIP regulates HPV gene expression via GRE and/or E2 binding site in the HPV promoter in a hormone-dependent or independent manner, respectively.« less

Transcription factor 19 interacts with histone 3 lysine 4 trimethylation and controls gluconeogenesis via the nucleosome-remodeling-deacetylase complex.

PubMed

Sen, Sabyasachi; Sanyal, Sulagna; Srivastava, Dushyant Kumar; Dasgupta, Dipak; Roy, Siddhartha; Das, Chandrima

2017-12-15

Transcription factor 19 (TCF19) has been reported as a type 1 diabetes-associated locus involved in maintenance of pancreatic β cells through a fine-tuned regulation of cell proliferation and apoptosis. TCF19 also exhibits genomic association with type 2 diabetes, although the precise molecular mechanism remains unknown. It harbors both a plant homeodomain and a forkhead-associated domain implicated in epigenetic recognition and gene regulation, a phenomenon that has remained unexplored. Here, we show that TCF19 selectively interacts with histone 3 lysine 4 trimethylation through its plant homeodomain finger. Knocking down TCF19 under high-glucose conditions affected many metabolic processes, including gluconeogenesis. We found that TCF19 overexpression represses de novo glucose production in HepG2 cells. The transcriptional repression of key genes, induced by TCF19, coincided with NuRD (nucleosome-remodeling-deacetylase) complex recruitment to the promoters of these genes. TCF19 interacted with CHD4 (chromodomain helicase DNA-binding protein 4), which is a part of the NuRD complex, in a glucose concentration-independent manner. In summary, our results show that TCF19 interacts with an active transcription mark and recruits a co-repressor complex to regulate gluconeogenic gene expression in HepG2 cells. Our study offers critical insights into the molecular mechanisms of transcriptional regulation of gluconeogenesis and into the roles of chromatin readers in metabolic homeostasis. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Is Each Light-Harvesting Complex Protein Important for Plant Fitness?1[w

PubMed Central

Ganeteg, Ulrika; Külheim, Carsten; Andersson, Jenny; Jansson, Stefan

2004-01-01

Many of the photosynthetic genes are conserved among all higher plants, indicating that there is strong selective pressure to maintain the genes of each protein. However, mutants of these genes often lack visible growth phenotypes, suggesting that they are important only under certain conditions or have overlapping functions. To assess the importance of specific genes encoding the light-harvesting complex (LHC) proteins for the survival of the plant in the natural environment, we have combined two different scientific traditions by using an ecological fitness assay on a set of genetically modified Arabidopsis plants with differing LHC protein contents. The fitness of all of the LHC-deficient plants was reduced in some of the growth environments, supporting the hypothesis that each of the genes has been conserved because they provide ecological flexibility, which is of great adaptive value given the highly variable conditions encountered in nature. PMID:14730076

Evidence of Reactive Gene-Environment Correlation in Preschoolers' Prosocial Play with Unfamiliar Peers

ERIC Educational Resources Information Center

DiLalla, Lisabeth Fisher; Bersted, Kyle; John, Sufna Gheyara

2015-01-01

The development of prosocial behaviors during the preschool years is essential for children's positive interactions with peers in school and other social situations. Although there is some evidence of genetic influences on prosocial behaviors, very little is known about how genes and environment, independently and in concert, affect prosocial…

Chronic and Acute Stress, Gender, and Serotonin Transporter Gene-Environment Interactions Predicting Depression Symptoms in Youth

ERIC Educational Resources Information Center

Hammen, Constance; Brennan, Patricia A.; Keenan-Miller, Danielle; Hazel, Nicholas A.; Najman, Jake M.

2010-01-01

Background: Many recent studies of serotonin transporter gene by environment effects predicting depression have used stress assessments with undefined or poor psychometric methods, possibly contributing to wide variation in findings. The present study attempted to distinguish between effects of acute and chronic stress to predict depressive…

Linking Gene, Brain, and Behavior

PubMed Central

Schmidt, Louis A.; Fox, Nathan A.; Perez-Edgar, Koraly; Hamer, Dean H.

2009-01-01

Gene-environment interactions involving exogenous environmental factors are known to shape behavior and personality development. Although gene-environment interactions involving endogenous environmental factors are hypothesized to play an equally important role, this conceptual approach has not been empirically applied in the study of early-developing temperament in humans. Here we report evidence for a gene-endoenvironment (i.e., resting frontal brain electroencephalogram, EEG, asymmetry) interaction in predicting child temperament. The DRD4 gene (long allele vs. short allele) moderated the relation between resting frontal EEG asymmetry (left vs. right) at 9 months and temperament at 48 months. Children who exhibited left frontal EEG asymmetry at 9 months and who possessed the DRD4 long allele were significantly more soothable at 48 months than other children. Among children with right frontal EEG asymmetry at 9 months, those with the DRD4 long allele had significantly more difficulties focusing and sustaining attention at 48 months than those with the DRD4 short allele. Resting frontal EEG asymmetry did not influence temperament in the absence of the DRD4 long allele. We discuss how the interaction of genetic and endoenvironment factors may confer risk and protection for different behavioral styles in children. PMID:19493320

Clock genes × stress × reward interactions in alcohol and substance use disorders.

PubMed

Perreau-Lenz, Stéphanie; Spanagel, Rainer

2015-06-01

Adverse life events and highly stressful environments have deleterious consequences for mental health. Those environmental factors can potentiate alcohol and drug abuse in vulnerable individuals carrying specific genetic risk factors, hence producing the final risk for alcohol- and substance-use disorders development. The nature of these genes remains to be fully determined, but studies indicate their direct or indirect relation to the stress hypothalamo-pituitary-adrenal (HPA) axis and/or reward systems. Over the past decade, clock genes have been revealed to be key-players in influencing acute and chronic alcohol/drug effects. In parallel, the influence of chronic stress and stressful life events in promoting alcohol and substance use and abuse has been demonstrated. Furthermore, the reciprocal interaction of clock genes with various HPA-axis components, as well as the evidence for an implication of clock genes in stress-induced alcohol abuse, have led to the idea that clock genes, and Period genes in particular, may represent key genetic factors to consider when examining gene × environment interaction in the etiology of addiction. The aim of the present review is to summarize findings linking clock genes, stress, and alcohol and substance abuse, and to propose potential underlying neurobiological mechanisms. Copyright © 2015 Elsevier Inc. All rights reserved.

Modeling synthetic lethality

PubMed Central

Le Meur, Nolwenn; Gentleman, Robert

2008-01-01

Background Synthetic lethality defines a genetic interaction where the combination of mutations in two or more genes leads to cell death. The implications of synthetic lethal screens have been discussed in the context of drug development as synthetic lethal pairs could be used to selectively kill cancer cells, but leave normal cells relatively unharmed. A challenge is to assess genome-wide experimental data and integrate the results to better understand the underlying biological processes. We propose statistical and computational tools that can be used to find relationships between synthetic lethality and cellular organizational units. Results In Saccharomyces cerevisiae, we identified multi-protein complexes and pairs of multi-protein complexes that share an unusually high number of synthetic genetic interactions. As previously predicted, we found that synthetic lethality can arise from subunits of an essential multi-protein complex or between pairs of multi-protein complexes. Finally, using multi-protein complexes allowed us to take into account the pleiotropic nature of the gene products. Conclusions Modeling synthetic lethality using current estimates of the yeast interactome is an efficient approach to disentangle some of the complex molecular interactions that drive a cell. Our model in conjunction with applied statistical methods and computational methods provides new tools to better characterize synthetic genetic interactions. PMID:18789146

The Genetics Underlying Natural Variation in the Biotic Interactions of Arabidopsis thaliana: The Challenges of Linking Evolutionary Genetics and Community Ecology.

PubMed

Roux, F; Bergelson, J

2016-01-01

In the context of global change, predicting the responses of plant communities in an ever-changing biotic environment calls for a multipronged approach at the interface of evolutionary genetics and community ecology. However, our understanding of the genetic basis of natural variation involved in mediating biotic interactions, and associated adaptive dynamics of focal plants in their natural communities, is still in its infancy. Here, we review the genetic and molecular bases of natural variation in the response to biotic interactions (viruses, bacteria, fungi, oomycetes, herbivores, and plants) in the model plant Arabidopsis thaliana as well as the adaptive value of these bases. Among the 60 identified genes are a number that encode nucleotide-binding site leucine-rich repeat (NBS-LRR)-type proteins, consistent with early examples of plant defense genes. However, recent studies have revealed an extensive diversity in the molecular mechanisms of defense. Many types of genetic variants associate with phenotypic variation in biotic interactions, even among the genes of large effect that tend to be identified. In general, we found that (i) balancing selection rather than directional selection explains the observed patterns of genetic diversity within A. thaliana and (ii) the cost/benefit tradeoffs of adaptive alleles can be strongly dependent on both genomic and environmental contexts. Finally, because A. thaliana rarely interacts with only one biotic partner in nature, we highlight the benefit of exploring diffuse biotic interactions rather than tightly associated host-enemy pairs. This challenge would help to improve our understanding of coevolutionary quantitative genetics within the context of realistic community complexity. © 2016 Elsevier Inc. All rights reserved.

Reconstruction of the bifidobacterial pan-secretome reveals the network of extracellular interactions between bifidobacteria and the infant gut.

PubMed

Lugli, Gabriele Andrea; Mancino, Walter; Milani, Christian; Duranti, Sabrina; Turroni, Francesca; van Sinderen, Douwe; Ventura, Marco

2018-06-08

The repertoire of secreted proteins decoded by a microorganism represents proteins released from or associated with the cell's surface. In gut commensals, such as bifidobacteria, these proteins are perceived to be functionally relevant as they regulate the interaction with the gut environment. In the current study, we have screened the predicted proteome of over 300 bifidobacterial strains amongst the currently recognized bifidobacterial species to generate a comprehensive database encompassing bifidobacterial extracellular proteins. A glycobiome analysis of this predicted bifidobacterial secretome revealed that a correlation exists between particular bifidobacterial species and their capability to hydrolyze HMOs and intestinal glyconjugates such as mucin. Furthermore, exploration of metatranscriptomic datasets of the infant gut microbiota allowed the evaluation of the expression of bifidobacterial genes encoding extracellular proteins, represented by ABC transporter substrate-binding proteins and glycoside hydrolases enzymes involved in the degradation of human milk oligosaccharides and mucin. Overall, this study provides insights into how bifidobacteria interact with their natural yet highly complex environment, the infant gut. Importance The ecological success of bifidobacteria relies on the activity of extracellular proteins that are involved in the metabolism of nutrients and the interaction with the environment. To date, information on secreted proteins encoded by bifidobacteria are incomplete and just related to few species. In this study, we reconstructed the bifidobacterial pan-secretome, revealing extracellular proteins that modulate the interaction of bifidobacteria with their natural environment. Furthermore, a survey of secretion system between bifidobacterial genomes allowed the identification of a conserved Sec-dependent secretion machinery in all the analyzed genomes and the Tat protein translocation system in the chromosomes of 23 strains belonging to Bifidobacterium longum subsp. longum and Bifidobacterium aesculapii . Copyright © 2018 American Society for Microbiology.

Monoamine Oxidase A (MAOA) and Catechol-O-Methyltransferase (COMT) Gene Polymorphisms Interact with Maternal Parenting in Association with Adolescent Reactive Aggression but not Proactive Aggression: Evidence of Differential Susceptibility.

PubMed

Zhang, Wenxin; Cao, Cong; Wang, Meiping; Ji, Linqin; Cao, Yanmiao

2016-04-01

To date, whether and how gene-environment (G × E) interactions operate differently across distinct subtypes of aggression remains untested. More recently, in contrast with the diathesis-stress hypothesis, an alternative hypothesis of differential susceptibility proposes that individuals could be differentially susceptible to environments depending on their genotypes in a "for better and for worse" manner. The current study examined interactions between monoamine oxidase A (MAOA) T941G and catechol-O-methyltransferase (COMT) Val158Met polymorphisms with maternal parenting on two types of aggression: reactive and proactive. Moreover, whether these potential G × E interactions would be consistent with the diathesis-stress versus the differential susceptibility hypothesis was tested. Within the sample of 1399 Chinese Han adolescents (47.2 % girls, M age = 12.32 years, SD = 0.50), MAOA and COMT genes both interacted with positive parenting in their associations with reactive but not proactive aggression. Adolescents with T alleles/TT homozygotes of MAOA gene or Met alleles of COMT gene exhibited more reactive aggression when exposed to low positive parenting, but less reactive aggression when exposed to high positive parenting. These findings provide the first evidence for distinct G × E interaction effects on reactive versus proactive aggression and lend further support for the differential susceptibility hypothesis.

Multifactor-Dimensionality Reduction Reveals High-Order Interactions among Estrogen-Metabolism Genes in Sporadic Breast Cancer

PubMed Central

Ritchie, Marylyn D.; Hahn, Lance W.; Roodi, Nady; Bailey, L. Renee; Dupont, William D.; Parl, Fritz F.; Moore, Jason H.

2001-01-01

One of the greatest challenges facing human geneticists is the identification and characterization of susceptibility genes for common complex multifactorial human diseases. This challenge is partly due to the limitations of parametric-statistical methods for detection of gene effects that are dependent solely or partially on interactions with other genes and with environmental exposures. We introduce multifactor-dimensionality reduction (MDR) as a method for reducing the dimensionality of multilocus information, to improve the identification of polymorphism combinations associated with disease risk. The MDR method is nonparametric (i.e., no hypothesis about the value of a statistical parameter is made), is model-free (i.e., it assumes no particular inheritance model), and is directly applicable to case-control and discordant-sib-pair studies. Using simulated case-control data, we demonstrate that MDR has reasonable power to identify interactions among two or more loci in relatively small samples. When it was applied to a sporadic breast cancer case-control data set, in the absence of any statistically significant independent main effects, MDR identified a statistically significant high-order interaction among four polymorphisms from three different estrogen-metabolism genes. To our knowledge, this is the first report of a four-locus interaction associated with a common complex multifactorial disease. PMID:11404819

Gravitropic mechanisms derived from space experiments and magnetic gradients.

NASA Astrophysics Data System (ADS)

Hasenstein, Karl H.; Park, Myoung Ryoul

2016-07-01

Gravitropism is the result of a complex sequence of events that begins with the movement of dense particles, typically starch-filled amyloplasts in response to reorientation. Although these organelles change positions, it is not clear whether the critical signal is derived from sedimentation or dynamic interactions of amyloplasts with relevant membranes. Substituting gravity by high-gradient magnetic fields (HGMF) provides a localized stimulus for diamagnetic starch that is specific for amyloplasts and comparable to gravity without affecting other organelles. Experiments with Brassica rapa showed induction of root curvature by HGMF when roots moved sufficiently close to the magnetic gradient-inducing foci. The focused and short-range effectiveness of HGMFs provided a gravity-like stimulus and affected related gene expression. Root curvature was sensitive to the mutual alignment between roots and HGMF direction. Unrelated to any HGMF effects, the size of amyloplasts in space-grown roots increased by 30% compared to ground controls and suggests enhanced sensitivity in a gravity-reduced environment. Accompanying gene transcription studies showed greater differences between HGMF-exposed and space controls than between space and ground controls. This observation may lead to the identification of gravitropism-relevant genes. However, space grown roots showed stronger transcription of common reference genes such as actin and ubiquitin in magnetic fields than in non-magnetic conditions. In contrast, α-amylase, glucokinase and PIN encoding genes were transcribed stronger under non-magnetic conditions than under HGMF. The large number of comparisons between space, ground, and HGMF prompted the assessment of transcription differences between root segments, root-shoot junction, and seeds. Because presumed transcription of reference genes varied more than genes of interest, changes in gene expression cannot be based on reference genes. The data provide an example of complex and different responses to microgravity conditions, induced curvature, ground controls, clinorotation, and magnetic field exposure.

Genomic Selection in Plant Breeding: Methods, Models, and Perspectives.

PubMed

Crossa, José; Pérez-Rodríguez, Paulino; Cuevas, Jaime; Montesinos-López, Osval; Jarquín, Diego; de Los Campos, Gustavo; Burgueño, Juan; González-Camacho, Juan M; Pérez-Elizalde, Sergio; Beyene, Yoseph; Dreisigacker, Susanne; Singh, Ravi; Zhang, Xuecai; Gowda, Manje; Roorkiwal, Manish; Rutkoski, Jessica; Varshney, Rajeev K

2017-11-01

Genomic selection (GS) facilitates the rapid selection of superior genotypes and accelerates the breeding cycle. In this review, we discuss the history, principles, and basis of GS and genomic-enabled prediction (GP) as well as the genetics and statistical complexities of GP models, including genomic genotype×environment (G×E) interactions. We also examine the accuracy of GP models and methods for two cereal crops and two legume crops based on random cross-validation. GS applied to maize breeding has shown tangible genetic gains. Based on GP results, we speculate how GS in germplasm enhancement (i.e., prebreeding) programs could accelerate the flow of genes from gene bank accessions to elite lines. Recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Method for Predicting Protein Complexes from Dynamic Weighted Protein-Protein Interaction Networks.

PubMed

Liu, Lizhen; Sun, Xiaowu; Song, Wei; Du, Chao

2018-06-01

Predicting protein complexes from protein-protein interaction (PPI) network is of great significance to recognize the structure and function of cells. A protein may interact with different proteins under different time or conditions. Existing approaches only utilize static PPI network data that may lose much temporal biological information. First, this article proposed a novel method that combines gene expression data at different time points with traditional static PPI network to construct different dynamic subnetworks. Second, to further filter out the data noise, the semantic similarity based on gene ontology is regarded as the network weight together with the principal component analysis, which is introduced to deal with the weight computing by three traditional methods. Third, after building a dynamic PPI network, a predicting protein complexes algorithm based on "core-attachment" structural feature is applied to detect complexes from each dynamic subnetworks. Finally, it is revealed from the experimental results that our method proposed in this article performs well on detecting protein complexes from dynamic weighted PPI networks.

Social context influences chemical communication in D. melanogaster males.

PubMed

Kent, Clement; Azanchi, Reza; Smith, Ben; Formosa, Amanda; Levine, Joel D

2008-09-23

Chemical communication mediates social interactions in insects. For the fruit fly, D. melanogaster, the chemical display is a key fitness trait because it leads to mating. An exchange of cues that resembles a dialogue between males and females is enacted by pheromones, chemical signals that pass between individual flies to alter physiology and behavior. Chemical signals also affect the timing of locomotor activity and sleep. We investigated genetic and environmental determinants of chemical communication. To evaluate the role of the social environment, we extracted a chemical blend from individual males selected from groups composed of one genotype and compared these extracts to those from groups of mixed genotypes. To evaluate the role of the physical environment, these comparisons were performed under a light-dark cycle or in constant darkness. Here, we show that chemical signaling is affected by the social environment, light-dark cycle, and genotype as well as the complex interplay of these variables. Gene-by-environment interactions produce highly significant effects on chemical signaling. We also examined individual responses within the groups. Strikingly, the response of one wild-type fly to another is modulated by the genotypic composition of his neighbors. Chemical signaling in D. melanogaster may be a "fickle" trait that depends on the individual's social background.

Mitochondrial-Nuclear Epistasis: Implications for Human Aging and Longevity

PubMed Central

Tranah, Gregory

2010-01-01

There is substantial evidence that mitochondria are involved in the aging process. Mitochondrial function requires the coordinated expression of hundreds of nuclear genes and a few dozen mitochondrial genes, many of which have been associated with either extended or shortened life span. Impaired mitochondrial function resulting from mtDNA and nuclear DNA variation is likely to contribute to an imbalance in cellular energy homeostasis, increased vulnerability to oxidative stress, and an increased rate of cellular senescence and aging. The complex genetic architecture of mitochondria suggests that there may be an equally complex set of gene interactions (epistases) involving genetic variation in the nuclear and mitochondrial genomes. Results from Drosophila suggest that the effects of mtDNA haplotypes on longevity vary among different nuclear allelic backgrounds, which could account for the inconsistent associations that have been observed between mitochondrial DNA (mtDNA) haplogroups and survival in humans. A diversity of pathways may influence the way mitochondria and nuclear – mitochondrial interactions modulate longevity, including: oxidative phosphorylation; mitochondrial uncoupling; antioxidant defenses; mitochondrial fission and fusion; and sirtuin regulation of mitochondrial genes. We hypothesize that aging and longevity, as complex traits having a significant genetic component, are likely to be controlled by nuclear gene variants interacting with both inherited and somatic mtDNA variability. PMID:20601194

High Fractional Occupancy of a Tandem Maf Recognition Element and Its Role in Long-Range β-Globin Gene Regulation

PubMed Central

Stees, Jared R.; Hossain, Mir A.; Sunose, Tomoki; Kudo, Yasushi; Pardo, Carolina E.; Nabilsi, Nancy H.; Darst, Russell P.; Poudyal, Rosha; Igarashi, Kazuhiko; Kladde, Michael P.

2015-01-01

Enhancers and promoters assemble protein complexes that ultimately regulate the recruitment and activity of RNA polymerases. Previous work has shown that at least some enhancers form stable protein complexes, leading to the formation of enhanceosomes. We analyzed protein-DNA interactions in the murine β-globin gene locus using the methyltransferase accessibility protocol for individual templates (MAPit). The data show that a tandem Maf recognition element (MARE) in locus control region (LCR) hypersensitive site 2 (HS2) reveals a remarkably high degree of occupancy during differentiation of mouse erythroleukemia cells. Most of the other transcription factor binding sites in LCR HS2 or in the adult β-globin gene promoter regions exhibit low fractional occupancy, suggesting highly dynamic protein-DNA interactions. Targeting of an artificial zinc finger DNA-binding domain (ZF-DBD) to the HS2 tandem MARE caused a reduction in the association of MARE-binding proteins and transcription complexes at LCR HS2 and the adult βmajor-globin gene promoter but did not affect expression of the βminor-globin gene. The data demonstrate that a stable MARE-associated footprint in LCR HS2 is important for the recruitment of transcription complexes to the adult βmajor-globin gene promoter during erythroid cell differentiation. PMID:26503787

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm.

PubMed

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene x gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene x gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms.

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm

PubMed Central

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene × gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene × gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms. PMID:18466570

Plasma selenium levels and oxidative stress biomarkers: a gene-environment interaction population-based study.

PubMed

Galan-Chilet, Inmaculada; Tellez-Plaza, Maria; Guallar, Eliseo; De Marco, Griselda; Lopez-Izquierdo, Raul; Gonzalez-Manzano, Isabel; Carmen Tormos, M; Martin-Nuñez, Gracia M; Rojo-Martinez, Gemma; Saez, Guillermo T; Martín-Escudero, Juan C; Redon, Josep; Javier Chaves, F

2014-09-01

The role of selenium exposure in preventing chronic disease is controversial, especially in selenium-repleted populations. At high concentrations, selenium exposure may increase oxidative stress. Studies evaluating the interaction of genetic variation in genes involved in oxidative stress pathways and selenium are scarce. We evaluated the cross-sectional association of plasma selenium concentrations with oxidative stress levels, measured as oxidized to reduced glutathione ratio (GSSG/GSH), malondialdehyde (MDA), and 8-oxo-7,8-dihydroguanine (8-oxo-dG) in urine, and the interacting role of genetic variation in oxidative stress candidate genes, in a representative sample of 1445 men and women aged 18-85 years from Spain. The geometric mean of plasma selenium levels in the study sample was 84.76 µg/L. In fully adjusted models the geometric mean ratios for oxidative stress biomarker levels comparing the highest to the lowest quintiles of plasma selenium levels were 0.61 (0.50-0.76) for GSSG/GSH, 0.89 (0.79-1.00) for MDA, and 1.06 (0.96-1.18) for 8-oxo-dG. We observed nonlinear dose-responses of selenium exposure and oxidative stress biomarkers, with plasma selenium concentrations above ~110 μg/L being positively associated with 8-oxo-dG, but inversely associated with GSSG/GSH and MDA. In addition, we identified potential risk genotypes associated with increased levels of oxidative stress markers with high selenium levels. Our findings support that high selenium levels increase oxidative stress in some biological processes. More studies are needed to disentangle the complexity of selenium biology and the relevance of potential gene-selenium interactions in relation to health outcomes in human populations. Copyright © 2014 Elsevier Inc. All rights reserved.

Learning Motivation Mediates Gene-by-Socioeconomic Status Interaction on Mathematics Achievement in Early Childhood

ERIC Educational Resources Information Center

Tucker-Drob, Elliot M.; Harden, K. Paige

2012-01-01

There is accumulating evidence that genetic influences on achievement are more pronounced among children living in higher socioeconomic status homes, and that these gene-by-environment interactions occur prior to children's entry into formal schooling. We hypothesized that one pathway through which socioeconomic status promotes genetic influences…

Intellectual Interest Mediates Gene x Socioeconomic Status Interaction on Adolescent Academic Achievement

ERIC Educational Resources Information Center

Tucker-Drob, Elliot M.; Harden, K. Paige

2012-01-01

Recent studies have demonstrated that genetic influences on cognitive ability and academic achievement are larger for children raised in higher socioeconomic status (SES) homes. However, little work has been done to document the psychosocial processes that underlie this Gene x Environment interaction. One process may involve the conversion of…

Visualization of the Drosophila dKeap1-CncC interaction on chromatin illumines cooperative, xenobiotic-specific gene activation

PubMed Central

Deng, Huai; Kerppola, Tom K.

2014-01-01

Interactions among transcription factors control their physiological functions by regulating their binding specificities and transcriptional activities. We implement a strategy to visualize directly the genomic loci that are bound by multi-protein complexes in single cells in Drosophila. This method is based on bimolecular fluorescence complementation (BiFC) analysis of protein interactions on polytene chromosomes. Drosophila Keap1 (dKeap1)-CncC complexes localized to the nucleus and bound chromatin loci that were not bound preferentially by dKeap1 or CncC when they were expressed separately. dKeap1 and CncC binding at these loci was enhanced by phenobarbital, but not by tert-butylhydroquinone (tBHQ) or paraquat. Endogenous dKeap1 and CncC activated transcription of the Jheh (Jheh1, Jheh2, Jheh3) and dKeap1 genes at these loci, whereas CncC alone activated other xenobiotic response genes. Ectopic dKeap1 expression increased CncC binding at the Jheh and dKeap1 gene loci and activated their transcription, whereas dKeap1 inhibited CncC binding at other xenobiotic response gene loci and suppressed their transcription. The combinatorial chromatin-binding specificities and transcriptional activities of dKeap1-CncC complexes mediated the selective activation of different sets of genes by different xenobiotic compounds, in part through feed-forward activation of dKeap1 transcription. PMID:25063457

Gene environment interaction studies in depression and suicidal behavior: An update.

PubMed

Mandelli, Laura; Serretti, Alessandro

2013-12-01

Increasing evidence supports the involvement of both heritable and environmental risk factors in major depression (MD) and suicidal behavior (SB). Studies investigating gene-environment interaction (G × E) may be useful for elucidating the role of biological mechanisms in the risk for mental disorders. In the present paper, we review the literature regarding the interaction between genes modulating brain functions and stressful life events in the etiology of MD and SB and discuss their potential added benefit compared to genetic studies only. Within the context of G × E investigation, thus far, only a few reliable results have been obtained, although some genes have consistently shown interactive effects with environmental risk in MD and, to a lesser extent, in SB. Further investigation is required to disentangle the direct and mediated effects that are common or specific to MD and SB. Since traditional G × E studies overall suffer from important methodological limitations, further effort is required to develop novel methodological strategies with an interdisciplinary approach. Copyright © 2013 Elsevier Ltd. All rights reserved.

Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns

PubMed Central

Lezon, Timothy R.; Banavar, Jayanth R.; Cieplak, Marek; Maritan, Amos; Fedoroff, Nina V.

2006-01-01

We describe a method based on the principle of entropy maximization to identify the gene interaction network with the highest probability of giving rise to experimentally observed transcript profiles. In its simplest form, the method yields the pairwise gene interaction network, but it can also be extended to deduce higher-order interactions. Analysis of microarray data from genes in Saccharomyces cerevisiae chemostat cultures exhibiting energy metabolic oscillations identifies a gene interaction network that reflects the intracellular communication pathways that adjust cellular metabolic activity and cell division to the limiting nutrient conditions that trigger metabolic oscillations. The success of the present approach in extracting meaningful genetic connections suggests that the maximum entropy principle is a useful concept for understanding living systems, as it is for other complex, nonequilibrium systems. PMID:17138668

Unveiling network-based functional features through integration of gene expression into protein networks.

PubMed

Jalili, Mahdi; Gebhardt, Tom; Wolkenhauer, Olaf; Salehzadeh-Yazdi, Ali

2018-06-01

Decoding health and disease phenotypes is one of the fundamental objectives in biomedicine. Whereas high-throughput omics approaches are available, it is evident that any single omics approach might not be adequate to capture the complexity of phenotypes. Therefore, integrated multi-omics approaches have been used to unravel genotype-phenotype relationships such as global regulatory mechanisms and complex metabolic networks in different eukaryotic organisms. Some of the progress and challenges associated with integrated omics studies have been reviewed previously in comprehensive studies. In this work, we highlight and review the progress, challenges and advantages associated with emerging approaches, integrating gene expression and protein-protein interaction networks to unravel network-based functional features. This includes identifying disease related genes, gene prioritization, clustering protein interactions, developing the modules, extract active subnetworks and static protein complexes or dynamic/temporal protein complexes. We also discuss how these approaches contribute to our understanding of the biology of complex traits and diseases. This article is part of a Special Issue entitled: Cardiac adaptations to obesity, diabetes and insulin resistance, edited by Professors Jan F.C. Glatz, Jason R.B. Dyck and Christine Des Rosiers. Copyright © 2018 Elsevier B.V. All rights reserved.

Variability in the efficacy of psychopharmaceuticals: contributions from pharmacogenomics, ethnopsychopharmacology, and psychological and psychiatric anthropologies.

PubMed

Ninnemann, Kristi M

2012-03-01

Psychological and psychiatric anthropology have long questioned the universality of psychiatric diagnoses, bringing to light the fluidity of mental disorder, and recognizing that the experience and expression of psychopathology is influenced by complex and interacting genetic, environmental, and cultural factors. The majority of our discussions, however, have remained centered around the role of culture in shaping mental illness: drawing attention to subjective experiences of mental illness and culturally patterned modes of symptom presentation, and interrogating the cogency of universal diagnostic rubrics. Psychological and psychiatric anthropology have yet to robustly engage the broadly assumed universal validity of psychiatric medications and the ways in which they are prescribed and experienced. This article provides an introduction into the fields of pharmacogenomics and ethnopsychopharmacology, areas of inquiry seeking to understand the ways in which genetic variability occurring between, and within, large population groups influences individual ability to metabolize psychotropic medications. This piece further addresses the complex issue of psychopharmaceutical efficacy, stressing the ways in which, just as with psychopathology, medications and their outcomes are likewise influenced by the complex interactions of genes, environment, and culture. Lastly, ways in which anthropology can and should engage with the growing fields of pharmacogenomics and ethnopsychopharmacology are suggested.

Deciphering the Interdependence between Ecological and Evolutionary Networks.

PubMed

Melián, Carlos J; Matthews, Blake; de Andreazzi, Cecilia S; Rodríguez, Jorge P; Harmon, Luke J; Fortuna, Miguel A

2018-05-24

Biological systems consist of elements that interact within and across hierarchical levels. For example, interactions among genes determine traits of individuals, competitive and cooperative interactions among individuals influence population dynamics, and interactions among species affect the dynamics of communities and ecosystem processes. Such systems can be represented as hierarchical networks, but can have complex dynamics when interdependencies among levels of the hierarchy occur. We propose integrating ecological and evolutionary processes in hierarchical networks to explore interdependencies in biological systems. We connect gene networks underlying predator-prey trait distributions to food webs. Our approach addresses longstanding questions about how complex traits and intraspecific trait variation affect the interdependencies among biological levels and the stability of meta-ecosystems. Copyright © 2018 Elsevier Ltd. All rights reserved.

Gene-gene-environment interactions between drugs, transporters, receptors, and metabolizing enzymes: Statins, SLCO1B1, and CYP3A4 as an example.

PubMed

Sadee, Wolfgang

2013-09-01

Pharmacogenetic biomarker tests include mostly specific single gene-drug pairs, capable of accounting for a portion of interindividual variability in drug response and toxicity. However, multiple genes are likely to contribute, either acting independently or epistatically, with the CYP2C9-VKORC1-warfarin test panel, an example of a clinically used gene-gene-dug interaction. I discuss here further instances of gene-gene-drug interactions, including a proposed dynamic effect on statin therapy by genetic variants in both a transporter (SLCO1B1) and a metabolizing enzyme (CYP3A4) in liver cells, the main target site where statins block cholesterol synthesis. These examples set a conceptual framework for developing diagnostic panels involving multiple gene-drug combinations. Copyright © 2013 Wiley Periodicals, Inc.

A gene-environment investigation on personality traits in two independent clinical sets of adult patients with personality disorder and attention deficit/hyperactive disorder.

PubMed

Jacob, Christian P; Nguyen, Thuy Trang; Dempfle, Astrid; Heine, Monika; Windemuth-Kieselbach, Christine; Baumann, Katarina; Jacob, Florian; Prechtl, Julian; Wittlich, Maike; Herrmann, Martin J; Gross-Lesch, Silke; Lesch, Klaus-Peter; Reif, Andreas

2010-06-01

While an interactive effect of genes with adverse life events is increasingly appreciated in current concepts of depression etiology, no data are presently available on interactions between genetic and environmental (G x E) factors with respect to personality and related disorders. The present study therefore aimed to detect main effects as well as interactions of serotonergic candidate genes (coding for the serotonin transporter, 5-HTT; the serotonin autoreceptor, HTR1A; and the enzyme which synthesizes serotonin in the brain, TPH2) with the burden of life events (#LE) in two independent samples consisting of 183 patients suffering from personality disorders and 123 patients suffering from adult attention deficit/hyperactivity disorder (aADHD). Simple analyses ignoring possible G x E interactions revealed no evidence for associations of either #LE or of the considered polymorphisms in 5-HTT and TPH2. Only the G allele of HTR1A rs6295 seemed to increase the risk of emotional-dramatic cluster B personality disorders (p = 0.019, in the personality disorder sample) and to decrease the risk of anxious-fearful cluster C personality disorders (p = 0.016, in the aADHD sample). We extended the initial simple model by taking a G x E interaction term into account, since this approach may better fit the data indicating that the effect of a gene is modified by stressful life events or, vice versa, that stressful life events only have an effect in the presence of a susceptibility genotype. By doing so, we observed nominal evidence for G x E effects as well as main effects of 5-HTT-LPR and the TPH2 SNP rs4570625 on the occurrence of personality disorders. Further replication studies, however, are necessary to validate the apparent complexity of G x E interactions in disorders of human personality.

Ruminant Rhombencephalitis-Associated Listeria monocytogenes Alleles Linked to a Multilocus Variable-Number Tandem-Repeat Analysis Complex ▿ †

PubMed Central

Balandyté, Lina; Brodard, Isabelle; Frey, Joachim; Oevermann, Anna; Abril, Carlos

2011-01-01

Listeria monocytogenes is among the most important food-borne pathogens and is well adapted to persist in the environment. To gain insight into the genetic relatedness and potential virulence of L. monocytogenes strains causing central nervous system (CNS) infections, we used multilocus variable-number tandem-repeat analysis (MLVA) to subtype 183 L. monocytogenes isolates, most from ruminant rhombencephalitis and some from human patients, food, and the environment. Allelic-profile-based comparisons grouped L. monocytogenes strains mainly into three clonal complexes and linked single-locus variants (SLVs). Clonal complex A essentially consisted of isolates from human and ruminant brain samples. All but one rhombencephalitis isolate from cattle were located in clonal complex A. In contrast, food and environmental isolates mainly clustered into clonal complex C, and none was classified as clonal complex A. Isolates of the two main clonal complexes (A and C) obtained by MLVA were analyzed by PCR for the presence of 11 virulence-associated genes (prfA, actA, inlA, inlB, inlC, inlD, inlE, inlF, inlG, inlJ, and inlC2H). Virulence gene analysis revealed significant differences in the actA, inlF, inlG, and inlJ allelic profiles between clinical isolates (complex A) and nonclinical isolates (complex C). The association of particular alleles of actA, inlF, and newly described alleles of inlJ with isolates from CNS infections (particularly rhombencephalitis) suggests that these virulence genes participate in neurovirulence of L. monocytogenes. The overall absence of inlG in clinical complex A and its presence in complex C isolates suggests that the InlG protein is more relevant for the survival of L. monocytogenes in the environment. PMID:21984240

microRNAs Databases: Developmental Methodologies, Structural and Functional Annotations.

PubMed

Singh, Nagendra Kumar

2017-09-01

microRNA (miRNA) is an endogenous and evolutionary conserved non-coding RNA, involved in post-transcriptional process as gene repressor and mRNA cleavage through RNA-induced silencing complex (RISC) formation. In RISC, miRNA binds in complementary base pair with targeted mRNA along with Argonaut proteins complex, causes gene repression or endonucleolytic cleavage of mRNAs and results in many diseases and syndromes. After the discovery of miRNA lin-4 and let-7, subsequently large numbers of miRNAs were discovered by low-throughput and high-throughput experimental techniques along with computational process in various biological and metabolic processes. The miRNAs are important non-coding RNA for understanding the complex biological phenomena of organism because it controls the gene regulation. This paper reviews miRNA databases with structural and functional annotations developed by various researchers. These databases contain structural and functional information of animal, plant and virus miRNAs including miRNAs-associated diseases, stress resistance in plant, miRNAs take part in various biological processes, effect of miRNAs interaction on drugs and environment, effect of variance on miRNAs, miRNAs gene expression analysis, sequence of miRNAs, structure of miRNAs. This review focuses on the developmental methodology of miRNA databases such as computational tools and methods used for extraction of miRNAs annotation from different resources or through experiment. This study also discusses the efficiency of user interface design of every database along with current entry and annotations of miRNA (pathways, gene ontology, disease ontology, etc.). Here, an integrated schematic diagram of construction process for databases is also drawn along with tabular and graphical comparison of various types of entries in different databases. Aim of this paper is to present the importance of miRNAs-related resources at a single place.

The long noncoding RNA Chaer defines an epigenetic checkpoint in cardiac hypertrophy.

PubMed

Wang, Zhihua; Zhang, Xiao-Jing; Ji, Yan-Xiao; Zhang, Peng; Deng, Ke-Qiong; Gong, Jun; Ren, Shuxun; Wang, Xinghua; Chen, Iris; Wang, He; Gao, Chen; Yokota, Tomohiro; Ang, Yen Sin; Li, Shen; Cass, Ashley; Vondriska, Thomas M; Li, Guangping; Deb, Arjun; Srivastava, Deepak; Yang, Huang-Tian; Xiao, Xinshu; Li, Hongliang; Wang, Yibin

2016-10-01

Epigenetic reprogramming is a critical process of pathological gene induction during cardiac hypertrophy and remodeling, but the underlying regulatory mechanisms remain to be elucidated. Here we identified a heart-enriched long noncoding (lnc)RNA, named cardiac-hypertrophy-associated epigenetic regulator (Chaer), which is necessary for the development of cardiac hypertrophy. Mechanistically, Chaer directly interacts with the catalytic subunit of polycomb repressor complex 2 (PRC2). This interaction, which is mediated by a 66-mer motif in Chaer, interferes with PRC2 targeting to genomic loci, thereby inhibiting histone H3 lysine 27 methylation at the promoter regions of genes involved in cardiac hypertrophy. The interaction between Chaer and PRC2 is transiently induced after hormone or stress stimulation in a process involving mammalian target of rapamycin complex 1, and this interaction is a prerequisite for epigenetic reprogramming and induction of genes involved in hypertrophy. Inhibition of Chaer expression in the heart before, but not after, the onset of pressure overload substantially attenuates cardiac hypertrophy and dysfunction. Our study reveals that stress-induced pathological gene activation in the heart requires a previously uncharacterized lncRNA-dependent epigenetic checkpoint.

Specific gene transfer mediated by galactosylated poly-L-lysine into hepatoma cells.

PubMed

Han, J; Il Yeom, Y

2000-07-20

Plasmid DNA/galactosylated poly-L-lysine(GalPLL) complex was used to transfer luciferase reporter gene in vitro into human hepatoma cells by a receptor-mediated endocytosis process. DNA was combined with galPLL via charge interaction (DNA:GalPLL:fusogenic peptide, 1:0.4:5, w/w/w) and the resulting complex was characterized by dynamic light scattering, gel retardation assay and zeta potential analyzer to determine the particle size, electrostatic charge interaction, and apparent surface charge. The complex was tested for the efficiency of gene transfer in cultured human hepatoblastoma cell line Hep G2 and fibroblast cells NIH/3T3 in vitro. The mean diameter of the complex (DNA:GalPLL=1:0.4, w/w) was 256+/-34.8 nm, and at this ratio, it was positively charged (zeta potential of this complex was 10.1 mV). Hep G2 cells, which express a galactose specific membrane lectin, were efficiently and selectively transfected with the RSV Luc/GalPLL complex in a sugar-dependent manner. NIH/3T3 cells, which do not express the galactose-specific membrane lectin, showed only a marginal level of gene expression. The transfection efficiency of GalPLL-conjugated DNA complex into Hep G2 cells was greatly enhanced in the presence of fusogenic peptide that can disrupt endosomes, where the GalPLL-DNA complex is entrapped with the fusogenic peptide. With the fusogenic peptide KALA, the luciferase activity in Hep G2 cells was ten-fold higher than that of cells transfected in the absence of the fusogenic peptide. Our gene transfer formulation may find potential application for the gene therapy of liver diseases.

Gene by environment interactions influencing reading disability and the inattentive symptom dimension of attention deficit/hyperactivity disorder.

PubMed

Rosenberg, Jenni; Pennington, Bruce F; Willcutt, Erik G; Olson, Richard K

2012-03-01

Reading disability (RD) and attention deficit/hyperactivity disorder (ADHD) are comorbid and genetically correlated, especially the inattentive dimension of ADHD (ADHD-I). However, previous research indicates that RD and ADHD enter into opposite gene by environment (G × E) interactions. This study used behavioral genetic methods to replicate these opposite G × E interactions in a sample of same-sex monozygotic and dizygotic twin pairs from the Colorado Learning Disabilities Research Center (CLDRC; DeFries et al., 1997) and to test a genetic hypothesis for why these opposite interactions occur. We replicated opposite G × E interactions for RD (bioecological) and ADHD-I (diathesis-stress) with parental education in the same sample of participants. The genetic hypothesis for this opposite pattern of interactions is that only genes specific to each disorder enter into these opposite interactions, not the shared genes underlying their comorbidity. To test this hypothesis, we used single models with an exploratory three-way interaction, in which the G × E interactions for each disorder were moderated by comorbidity. Neither three-way interaction was significant. The heritability of RD did not vary as a function of parental education and ADHD-I. Similarly, the heritability of ADHD-I did not vary as a function of parental education and RD. We documented opposite G × E interactions in RD and ADHD-I in the same overall twin sample, but the explanation for this apparent paradox remains unclear. Examining specific genes and more specific environmental factors may help resolve the paradox. © 2011 The Authors. Journal of Child Psychology and Psychiatry © 2011 Association for Child and Adolescent Mental Health.

The heritable basis of gene-environment interactions in cardiometabolic traits.

PubMed

Poveda, Alaitz; Chen, Yan; Brändström, Anders; Engberg, Elisabeth; Hallmans, Göran; Johansson, Ingegerd; Renström, Frida; Kurbasic, Azra; Franks, Paul W

2017-03-01

Little is known about the heritable basis of gene-environment interactions in humans. We therefore screened multiple cardiometabolic traits to assess the probability that they are influenced by genotype-environment interactions. Fourteen established environmental risk exposures and 11 cardiometabolic traits were analysed in the VIKING study, a cohort of 16,430 Swedish adults from 1682 extended pedigrees with available detailed genealogical, phenotypic and demographic information, using a maximum likelihood variance decomposition method in Sequential Oligogenic Linkage Analysis Routines software. All cardiometabolic traits had statistically significant heritability estimates, with narrow-sense heritabilities (h 2 ) ranging from 24% to 47%. Genotype-environment interactions were detected for age and sex (for the majority of traits), physical activity (for triacylglycerols, 2 h glucose and diastolic BP), smoking (for weight), alcohol intake (for weight, BMI and 2 h glucose) and diet pattern (for weight, BMI, glycaemic traits and systolic BP). Genotype-age interactions for weight and systolic BP, genotype-sex interactions for BMI and triacylglycerols and genotype-alcohol intake interactions for weight remained significant after multiple test correction. Age, sex and alcohol intake are likely to be major modifiers of genetic effects for a range of cardiometabolic traits. This information may prove valuable for studies that seek to identify specific loci that modify the effects of lifestyle in cardiometabolic disease.

Super-Enhancers and Broad H3K4me3 Domains Form Complex Gene Regulatory Circuits Involving Chromatin Interactions.

PubMed

Cao, Fan; Fang, Yiwen; Tan, Hong Kee; Goh, Yufen; Choy, Jocelyn Yeen Hui; Koh, Bryan Thean Howe; Hao Tan, Jiong; Bertin, Nicolas; Ramadass, Aroul; Hunter, Ewan; Green, Jayne; Salter, Matthew; Akoulitchev, Alexandre; Wang, Wilson; Chng, Wee Joo; Tenen, Daniel G; Fullwood, Melissa J

2017-05-19

Stretched histone regions, such as super-enhancers and broad H3K4me3 domains, are associated with maintenance of cell identity and cancer. We connected super-enhancers and broad H3K4me3 domains in the K562 chronic myelogenous leukemia cell line as well as the MCF-7 breast cancer cell line with chromatin interactions. Super-enhancers and broad H3K4me3 domains showed higher association with chromatin interactions than their typical counterparts. Interestingly, we identified a subset of super-enhancers that overlap with broad H3K4me3 domains and show high association with cancer-associated genes including tumor suppressor genes. Besides cell lines, we could observe chromatin interactions by a Chromosome Conformation Capture (3C)-based method, in primary human samples. Several chromatin interactions involving super-enhancers and broad H3K4me3 domains are constitutive and can be found in both cancer and normal samples. Taken together, these results reveal a new layer of complexity in gene regulation by super-enhancers and broad H3K4me3 domains.

A direct link between carbohydrate utilization and virulence in the major human pathogen group A Streptococcus.

PubMed

Shelburne, Samuel A; Keith, David; Horstmann, Nicola; Sumby, Paul; Davenport, Michael T; Graviss, Edward A; Brennan, Richard G; Musser, James M

2008-02-05

Although central to pathogenesis, the molecular mechanisms used by microbes to regulate virulence factor production in specific environments during host-pathogen interaction are poorly defined. Several recent ex vivo and in vivo studies have found that the level of group A Streptococcus (GAS) virulence factor gene transcripts is temporally related to altered expression of genes encoding carbohydrate utilization proteins. These findings stimulated us to analyze the role in pathogenesis of catabolite control protein A (CcpA), a GAS ortholog of a key global regulator of carbohydrate metabolism in Bacillus subtilis. Inasmuch as the genomewide effects of CcpA in a human pathogen are unknown, we analyzed the transcriptome of a DeltaccpA isogenic mutant strain grown in nutrient-rich medium. CcpA influences the transcript levels of many carbohydrate utilization genes and several well characterized GAS virulence factors, including the potent cytolysin streptolysin S. Compared with the wild-type parental strain, the DeltaccpA isogenic mutant strain was significantly less virulent in a mouse model of invasive infection. Moreover, the isogenic mutant strain was significantly impaired in ability to colonize the mouse oropharynx. When grown in human saliva, a nutrient-limited environment, CcpA influenced production of several key virulence factors not influenced during growth in nutrient-rich medium. Purified recombinant CcpA bound to the promoter region of the gene encoding streptolysin S. Our discovery that GAS virulence and complex carbohydrate utilization are directly linked through CcpA provides enhanced understanding of a mechanism used by a Gram-positive pathogen to modulate virulence factor production in specific environments.

Genetic Modification of the Relationship between Parental Rejection and Adolescent Alcohol Use.

PubMed

Stogner, John M; Gibson, Chris L

2016-07-01

Parenting practices are associated with adolescents' alcohol consumption, however not all youth respond similarly to challenging family situations and harsh environments. This study examines the relationship between perceived parental rejection and adolescent alcohol use, and specifically evaluates whether youth who possess greater genetic sensitivity to their environment are more susceptible to negative parental relationships. Analyzing data from the National Longitudinal Study of Adolescent Health, we estimated a series of regression models predicting alcohol use during adolescence. A multiplicative interaction term between parental rejection and a genetic index was constructed to evaluate this potential gene-environment interaction. Results from logistic regression analyses show a statistically significant gene-environment interaction predicting alcohol use. The relationship between parental rejection and alcohol use was moderated by the genetic index, indicating that adolescents possessing more 'risk alleles' for five candidate genes were affected more by stressful parental relationships. Feelings of parental rejection appear to influence the alcohol use decisions of youth, but they do not do so equally for all. Higher scores on the constructed genetic sensitivity measure are related to increased susceptibility to negative parental relationships. © The Author 2016. Medical Council on Alcohol and Oxford University Press. All rights reserved.

Genetics and Psychopharmacology: Prospects for Individualized Treatment

PubMed Central

Nnadi, Charles U.; Goldberg, Joseph F.; Malhotra, Anil K.

2008-01-01

This article provides a clear and succinct description of the components of inheritance, such as trait transmission, genetic variability, and gene interaction. Genetic sequences constitute the prime focus of pharmacogenetic studies. Variations in drug-metabolizing enzyme systems tend to be monogenic, whereas the pharmacologic effects of medications appear to be polygenic, i.e., complex phenotypes shaped by the interaction of genes and environment. Translated into clinical terms, a history of a good response to a drug in a close relative of a patient is presumed to indicate a good response to the same medication by the patient. This seems to hold for antidepressants, antipsychotics, and lithium, but the evidential studies generally have meaningful limitations. Bit by bit, information about the relationship between particular genetic formations and the effectiveness of these medications as well as their side effects, is appearing. The authors cite a number of examples, one such being an association between impaired antidepressant activity and the short allele of SLC6A4. This research promises to strengthen the accuracy, effectiveness, safety, and cost of our psychopharmacological practices. PMID:16041916

Genetics and psychopharmacology: prospects for individualized treatment.

PubMed

Nnadi, Charles U; Goldberg, Joseph F; Malhotra, Anil K

2005-01-01

This article provides a clear and succinct description of the components of inheritance, such as trait transmission, genetic variability, and gene interaction. Genetic sequences constitute the prime focus of pharmacogenetic studies. Variations in drug-metabolizing enzyme systems tend to be monogenic, whereas the pharmacologic effects of medications appear to be polygenic, i.e., complex phenotypes shaped by the interaction of genes and environment. Translated into clinical terms, a history of a good response to a drug in a close relative of a patient is presumed to predict a good response to the same medication by the patient. This seems to hold for antidepressants, antipsychotics, and lithium, but the evidential studies generally have meaningful limitations. Bit by bit, information about the relationship between particular genetic formations and the effectiveness of these medications as well as their side effects, is appearing. The authors cite a number of examples, one such being an association between impaired antidepressant activity and the short allele of SLC6A4. This research promises to strengthen the accuracy, effectiveness, safety, and cost of our psychopharmacological practices.

Child Dopamine Transporter Genotype and Parenting: Evidence for Evocative Gene-Environment Correlations

PubMed Central

Hayden, Elizabeth P.; Hanna, Brigitte; Sheikh, Haroon I.; Laptook, Rebecca S.; Kim, Jiyon; Singh, Shiva M.; Klein, Daniel N.

2017-01-01

The dopamine transporter (DAT1) gene is implicated in psychopathology risk. While the processes by which this gene exerts its effects on risk are poorly understood, a small body of research suggests that DAT1 influences early emerging negative emotionality (NE), a marker of children’s psychopathology risk. As child NE evokes negative parenting practices, the DAT1 may also play a role in gene-environment correlations. To test this model, children (N = 365) were genotyped for DAT1 and participated in standardized parent-child interaction tasks with their primary caregiver. The DAT1 9-repeat variant was associated with child negative affect expressed toward the parent during parent-child interactions, and parents of children with a 9-repeat allele exhibited more hostility and lower guidance/engagement than parents of children without a 9-repeat allele. These gene-environment associations were partially mediated by child negative affect toward the parent. Findings implicate a specific polymorphism in eliciting negative parenting, suggesting that evocative associations play a role in elevating children’s risk for emotional trajectories toward psychopathology risk. PMID:23398760

Social environment influences the relationship between genotype and gene expression in wild baboons

PubMed Central

Runcie, Daniel E.; Wiedmann, Ralph T.; Archie, Elizabeth A.; Altmann, Jeanne; Wray, Gregory A.; Alberts, Susan C.; Tung, Jenny

2013-01-01

Variation in the social environment can have profound effects on survival and reproduction in wild social mammals. However, we know little about the degree to which these effects are influenced by genetic differences among individuals, and conversely, the degree to which social environmental variation mediates genetic reaction norms. To better understand these relationships, we investigated the potential for dominance rank, social connectedness and group size to modify the effects of genetic variation on gene expression in the wild baboons of the Amboseli basin. We found evidence for a number of gene–environment interactions (GEIs) associated with variation in the social environment, encompassing social environments experienced in adulthood as well as persistent effects of early life social environment. Social connectedness, maternal dominance rank and group size all interacted with genotype to influence gene expression in at least one sex, and either in early life or in adulthood. These results suggest that social and behavioural variation, akin to other factors such as age and sex, can impact the genotype–phenotype relationship. We conclude that GEIs mediated by the social environment are important in the evolution and maintenance of individual differences in wild social mammals, including individual differences in responses to social stressors. PMID:23569293

Beyond the single gene: How epistasis and gene-by-environment effects influence crop domestication.

PubMed

Doust, Andrew N; Lukens, Lewis; Olsen, Kenneth M; Mauro-Herrera, Margarita; Meyer, Ann; Rogers, Kimberly

2014-04-29

Domestication is a multifaceted evolutionary process, involving changes in individual genes, genetic interactions, and emergent phenotypes. There has been extensive discussion of the phenotypic characteristics of plant domestication, and recent research has started to identify the specific genes and mutational mechanisms that control domestication traits. However, there is an apparent disconnect between the simple genetic architecture described for many crop domestication traits, which should facilitate rapid phenotypic change under selection, and the slow rate of change reported from the archeobotanical record. A possible explanation involves the middle ground between individual genetic changes and their expression during development, where gene-by-gene (epistatic) and gene-by-environment interactions can modify the expression of phenotypes and opportunities for selection. These aspects of genetic architecture have the potential to significantly slow the speed of phenotypic evolution during crop domestication and improvement. Here we examine whether epistatic and gene-by-environment interactions have shaped how domestication traits have evolved. We review available evidence from the literature, and we analyze two domestication-related traits, shattering and flowering time, in a mapping population derived from a cross between domesticated foxtail millet and its wild progenitor. We find that compared with wild progenitor alleles, those favored during domestication often have large phenotypic effects and are relatively insensitive to genetic background and environmental effects. Consistent selection should thus be able to rapidly change traits during domestication. We conclude that if phenotypic evolution was slow during crop domestication, this is more likely due to cultural or historical factors than epistatic or environmental constraints.

A latent variable approach to study gene-environment interactions in the presence of multiple correlated exposures.

PubMed

Sánchez, Brisa N; Kang, Shan; Mukherjee, Bhramar

2012-06-01

Many existing cohort studies initially designed to investigate disease risk as a function of environmental exposures have collected genomic data in recent years with the objective of testing for gene-environment interaction (G × E) effects. In environmental epidemiology, interest in G × E arises primarily after a significant effect of the environmental exposure has been documented. Cohort studies often collect rich exposure data; as a result, assessing G × E effects in the presence of multiple exposure markers further increases the burden of multiple testing, an issue already present in both genetic and environment health studies. Latent variable (LV) models have been used in environmental epidemiology to reduce dimensionality of the exposure data, gain power by reducing multiplicity issues via condensing exposure data, and avoid collinearity problems due to presence of multiple correlated exposures. We extend the LV framework to characterize gene-environment interaction in presence of multiple correlated exposures and genotype categories. Further, similar to what has been done in case-control G × E studies, we use the assumption of gene-environment (G-E) independence to boost the power of tests for interaction. The consequences of making this assumption, or the issue of how to explicitly model G-E association has not been previously investigated in LV models. We postulate a hierarchy of assumptions about the LV model regarding the different forms of G-E dependence and show that making such assumptions may influence inferential results on the G, E, and G × E parameters. We implement a class of shrinkage estimators to data adaptively trade-off between the most restrictive to most flexible form of G-E dependence assumption and note that such class of compromise estimators can serve as a benchmark of model adequacy in LV models. We demonstrate the methods with an example from the Early Life Exposures in Mexico City to Neuro-Toxicants Study of lead exposure, iron metabolism genes, and birth weight. © 2011, The International Biometric Society.

Genetics of healthy aging and longevity.

PubMed

Brooks-Wilson, Angela R

2013-12-01

Longevity and healthy aging are among the most complex phenotypes studied to date. The heritability of age at death in adulthood is approximately 25 %. Studies of exceptionally long-lived individuals show that heritability is greatest at the oldest ages. Linkage studies of exceptionally long-lived families now support a longevity locus on chromosome 3; other putative longevity loci differ between studies. Candidate gene studies have identified variants at APOE and FOXO3A associated with longevity; other genes show inconsistent results. Genome-wide association scans (GWAS) of centenarians vs. younger controls reveal only APOE as achieving genome-wide significance (GWS); however, analyses of combinations of SNPs or genes represented among associations that do not reach GWS have identified pathways and signatures that converge upon genes and biological processes related to aging. The impact of these SNPs, which may exert joint effects, may be obscured by gene-environment interactions or inter-ethnic differences. GWAS and whole genome sequencing data both show that the risk alleles defined by GWAS of common complex diseases are, perhaps surprisingly, found in long-lived individuals, who may tolerate them by means of protective genetic factors. Such protective factors may 'buffer' the effects of specific risk alleles. Rare alleles are also likely to contribute to healthy aging and longevity. Epigenetics is quickly emerging as a critical aspect of aging and longevity. Centenarians delay age-related methylation changes, and they can pass this methylation preservation ability on to their offspring. Non-genetic factors, particularly lifestyle, clearly affect the development of age-related diseases and affect health and lifespan in the general population. To fully understand the desirable phenotypes of healthy aging and longevity, it will be necessary to examine whole genome data from large numbers of healthy long-lived individuals to look simultaneously at both common and rare alleles, with impeccable control for population stratification and consideration of non-genetic factors such as environment.

Influence of apolipoprotein E genotype on the transmission of Alzheimer disease in a community-based sample

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jarvik, G.P.; Larson, E.B.; Goddard, K.

1996-01-01

The {epsilon}4 allele of the apolipoprotein E locus (APOE) has been found to be an important predictor of Alzheimer disease (AD). However, linkage analysis has not clarified the role of APOE in the transmission of AD. The results of the current study provide evidence that the pattern of transmission of memory disorders differs in nuclear families in which the AD-affected proband did carry an {epsilon}4 allele versus those families in which the AD-affected proband did not carry an {epsilon}4 allele. Further, risk of AD due to APOE genotype in the probands is modified by family history of memory disorders, suggestingmore » gene-by-gene interactions. Family history remained a significant predictor of AD for affected probands with some, but not all, APOE genotypes in a logistic regression analysis. Though nonadditive in the prediction of AD, APOE genotype and family history acted additively in the prediction of age at AD onset. The results of complex segregation analysis were inconsistent with Mendelian segregation of memory disorders both in families of affected probands who did or did not carry an {epsilon}4 allele, yet these two groups had significantly different parameter estimates for their transmission models. These results are consistent with gene-by-gene interactions, but also could result from common elements in the familial environment. 41 refs., 1 fig., 7 tabs.« less

Prevalence of transcription promoters within archaeal operons and coding sequences.

PubMed

Koide, Tie; Reiss, David J; Bare, J Christopher; Pang, Wyming Lee; Facciotti, Marc T; Schmid, Amy K; Pan, Min; Marzolf, Bruz; Van, Phu T; Lo, Fang-Yin; Pratap, Abhishek; Deutsch, Eric W; Peterson, Amelia; Martin, Dan; Baliga, Nitin S

2009-01-01

Despite the knowledge of complex prokaryotic-transcription mechanisms, generalized rules, such as the simplified organization of genes into operons with well-defined promoters and terminators, have had a significant role in systems analysis of regulatory logic in both bacteria and archaea. Here, we have investigated the prevalence of alternate regulatory mechanisms through genome-wide characterization of transcript structures of approximately 64% of all genes, including putative non-coding RNAs in Halobacterium salinarum NRC-1. Our integrative analysis of transcriptome dynamics and protein-DNA interaction data sets showed widespread environment-dependent modulation of operon architectures, transcription initiation and termination inside coding sequences, and extensive overlap in 3' ends of transcripts for many convergently transcribed genes. A significant fraction of these alternate transcriptional events correlate to binding locations of 11 transcription factors and regulators (TFs) inside operons and annotated genes-events usually considered spurious or non-functional. Using experimental validation, we illustrate the prevalence of overlapping genomic signals in archaeal transcription, casting doubt on the general perception of rigid boundaries between coding sequences and regulatory elements.

Amphetamine Self-Administration and Dopamine Function: Assessment of Gene x Environment Interactions in Lewis and Fischer 344 Rats

PubMed Central

Meyer, Andrew C.; Bardo, Michael T.

2015-01-01

Rationale Previous research suggests both genetic and environmental influences on substance abuse vulnerability. Objectives The current work sought to investigate the interaction of genes and environment on the acquisition of amphetamine self-administration, as well as amphetamine-stimulated dopamine (DA) release in nucleus accumbens shell using in vivo microdialysis. Methods Inbred Lewis (LEW) and Fischer (F344) rat strains were raised in either an enriched condition (EC), social condition (SC), or isolated condition (IC). Acquisition of amphetamine self-administration (0.1 mg/kg/infusion) was determined across an incrementing daily fixed ratio (FR) schedule. In a separate cohort of rats, extracellular DA and the metabolite dihydroxyphenylacetic acid (DOPAC) were measured in the nucleus accumbens shell following an acute amphetamine injection (1 mg/kg). Results “Addiction-prone” LEW had greater acquisition of amphetamine self-administration on a FR1 schedule compared to “addiction-resistant” F344 when raised in the SC environment. These genetic differences were negated in both the EC and IC environments, with enrichment buffering against self-administration and isolation enhancing self-administration in both strains. On a FR5 schedule, the isolation-induced increase in amphetamine self-administration was greater in F344 than LEW. While no group differences were obtained in extracellular DA, gene x environment differences were obtained in extracellular levels of the metabolite DOPAC. In IC rats only, LEW showed an attenuation in the amphetamine-induced decrease in DOPAC compared to F344. IC LEW rats also had an attenuated DOPAC response to amphetamine compared to EC LEW. Conclusions The current results demonstrate gene x environment interactions in amphetamine self-administration and amphetamine-induced changes in extracellular DOPAC in NAc shell. However, the behavioral and neurochemical differences were not related directly, indicating that mechanisms independent of DA metabolism in NAc shell likely mediate the gene x environment effects in amphetamine self-administration. PMID:25566972

Epistasis interaction of QTL effects as a genetic parameter influencing estimation of the genetic additive effect.

PubMed

Bocianowski, Jan

2013-03-01

Epistasis, an additive-by-additive interaction between quantitative trait loci, has been defined as a deviation from the sum of independent effects of individual genes. Epistasis between QTLs assayed in populations segregating for an entire genome has been found at a frequency close to that expected by chance alone. Recently, epistatic effects have been considered by many researchers as important for complex traits. In order to understand the genetic control of complex traits, it is necessary to clarify additive-by-additive interactions among genes. Herein we compare estimates of a parameter connected with the additive gene action calculated on the basis of two models: a model excluding epistasis and a model with additive-by-additive interaction effects. In this paper two data sets were analysed: 1) 150 barley doubled haploid lines derived from the Steptoe × Morex cross, and 2) 145 DH lines of barley obtained from the Harrington × TR306 cross. The results showed that in cases when the effect of epistasis was different from zero, the coefficient of determination was larger for the model with epistasis than for the one excluding epistasis. These results indicate that epistatic interaction plays an important role in controlling the expression of complex traits.

Context-dependent interactions and the regulation of species richness in freshwater fish.

PubMed

MacDougall, Andrew S; Harvey, Eric; McCune, Jenny L; Nilsson, Karin A; Bennett, Joseph; Firn, Jennifer; Bartley, Timothy; Grace, James B; Kelly, Jocelyn; Tunney, Tyler D; McMeans, Bailey; Matsuzaki, Shin-Ichiro S; Kadoya, Taku; Esch, Ellen; Cazelles, Kevin; Lester, Nigel; McCann, Kevin S

2018-03-06

Species richness is regulated by a complex network of scale-dependent processes. This complexity can obscure the influence of limiting species interactions, making it difficult to determine if abiotic or biotic drivers are more predominant regulators of richness. Using integrative modeling of freshwater fish richness from 721 lakes along an 11 o latitudinal gradient, we find negative interactions to be a relatively minor independent predictor of species richness in lakes despite the widespread presence of predators. Instead, interaction effects, when detectable among major functional groups and 231 species pairs, were strong, often positive, but contextually dependent on environment. These results are consistent with the idea that negative interactions internally structure lake communities but do not consistently 'scale-up' to regulate richness independently of the environment. The importance of environment for interaction outcomes and its role in the regulation of species richness highlights the potential sensitivity of fish communities to the environmental changes affecting lakes globally.

Context-dependent interactions and the regulation of species richness in freshwater fish

USGS Publications Warehouse

MacDougall, Andrew S.; Harvey, Eric; McCune, Jenny L.; Nilsson, Karin A.; Bennett, Joseph; Firn, Jennifer; Bartley, Timothy; Grace, James B.; Kelly, Jocelyn; Tunney, Tyler D.; McMeans, Bailey; Matsuzaki, Shin-Ichiro S.; Kadoya, Taku; Esch, Ellen; Cazelles, Kevin; Lester, Nigel; McCann, Kevin S.

2018-01-01

Species richness is regulated by a complex network of scale-dependent processes. This complexity can obscure the influence of limiting species interactions, making it difficult to determine if abiotic or biotic drivers are more predominant regulators of richness. Using integrative modeling of freshwater fish richness from 721 lakes along an 11olatitudinal gradient, we find negative interactions to be a relatively minor independent predictor of species richness in lakes despite the widespread presence of predators. Instead, interaction effects, when detectable among major functional groups and 231 species pairs, were strong, often positive, but contextually dependent on environment. These results are consistent with the idea that negative interactions internally structure lake communities but do not consistently ‘scale-up’ to regulate richness independently of the environment. The importance of environment for interaction outcomes and its role in the regulation of species richness highlights the potential sensitivity of fish communities to the environmental changes affecting lakes globally.

[New perspectives in monitoring of exposures to carcinogens].

PubMed

Pavanello, Sofia; Lotti, Marcello

2011-01-01

Biomonitoring occupational and environmental exposures to carcinogens is a common practice and several biomarkers have been developed for risk assessment. However, in particular, because of the lack of prospective studies, the place of these biomarkers within the complex scenario of the gene-environment interactions leading to cancer cannot be defined. New opportunities and suggestions for biomonitoring exposures to carcinogens could derive from exploring the exposome, from the results of genomewide association and omic studies. Based on these premises it is possible to envisage personalized biomonitoring procedures, as those already actuated in nutrition and clinical oncology, allowing a better predictivity of biomarkers in the preventive settings.

Socioeconomic status and genetic influences on cognitive development.

PubMed

Figlio, David N; Freese, Jeremy; Karbownik, Krzysztof; Roth, Jeffrey

2017-12-19

Accurate understanding of environmental moderation of genetic influences is vital to advancing the science of cognitive development as well as for designing interventions. One widely reported idea is increasing genetic influence on cognition for children raised in higher socioeconomic status (SES) families, including recent proposals that the pattern is a particularly US phenomenon. We used matched birth and school records from Florida siblings and twins born in 1994-2002 to provide the largest, most population-diverse consideration of this hypothesis to date. We found no evidence of SES moderation of genetic influence on test scores, suggesting that articulating gene-environment interactions for cognition is more complex and elusive than previously supposed.

A functionally conserved Polycomb response element from mouse HoxD complex responds to heterochromatin factors

NASA Astrophysics Data System (ADS)

Vasanthi, Dasari; Nagabhushan, A.; Matharu, Navneet Kaur; Mishra, Rakesh K.

2013-10-01

Anterior-posterior body axis in all bilaterians is determined by the Hox gene clusters that are activated in a spatio-temporal order. This expression pattern of Hox genes is established and maintained by regulatory mechanisms that involve higher order chromatin structure and Polycomb group (PcG) and trithorax group (trxG) proteins. We identified earlier a Polycomb response element (PRE) in the mouse HoxD complex that is functionally conserved in flies. We analyzed the molecular and genetic interactions of mouse PRE using Drosophila melanogaster and vertebrate cell culture as the model systems. We demonstrate that the repressive activity of this PRE depends on PcG/trxG genes as well as the heterochromatin components. Our findings indicate that a wide range of factors interact with the HoxD PRE that can contribute to establishing the expression pattern of homeotic genes in the complex early during development and maintain that pattern at subsequent stages.