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

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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.

Gene-gene, gene-environment, gene-nutrient interactions and single nucleotide polymorphisms of inflammatory cytokines.

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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.

Systematic Search for Gene-Gene Interaction Effect on Prostate Cancer Risk

Science.gov (United States)

2013-07-01

Systematic Search for Gene-Gene Interaction 5a. CONTRACT NUMBER Effect on Prostate Cancer Risk 5b. GRANT NUMBER W81XWH-09-1-0488 5c. PROGRAM...Supported by this grant ) 1. Tao S, Wang Z, Feng J, Hsu FC, Jin G, Kin ST, Zhang Z, Gronberg H, Zheng, SL, Isaacs WB, XU J, Sun J. A Genome-Wide Search for...order interactions among estrogen- metabolism genes in sporadic breast cancer. Am J Hum Genet, 69, 138-47. 48. Marchini, J., Donnelly, P. and Cardon

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

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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.

Gene-Environment Interactions in Severe Mental Illness

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Rudolf eUher

2014-05-01

Full Text Available Severe mental illness is a broad category that includes schizophrenia, bipolar disorder and severe depression. Both genetic disposition and environmental exposures play important roles in the development of severe mental illness. Multiple lines of evidence suggest that the roles of genetic and environmental depend on each other. Gene-environment interactions may underlie the paradox of strong environmental factors for highly heritable disorders, the low estimates of shared environmental influences in twin studies of severe mental illness and the heritability gap between twin and molecular heritability estimates. Sons and daughters of parents with severe mental illness are more vulnerable to the effects of prenatal and postnatal environmental exposures, suggesting that the expression of genetic liability depends on environment. In the last decade, gene-environment interactions involving specific molecular variants in candidate genes have been identified. Replicated findings include an interaction between a polymorphism in the AKT1 gene and cannabis use in the development of psychosis and an interaction between the length polymorphism of the serotonin transporter gene and childhood maltreatment in the development of persistent depressive disorder. Bipolar disorder has been underinvestigated, with only a single study showing an interaction between a functional polymorphism in BDNF and stressful life events triggering bipolar depressive episodes. The first systematic search for gene-environment interactions has found that a polymorphism in CTNNA3 may sensitise the developing brain to the pathogenic effect of cytomegalovirus in utero, leading to schizophrenia in adulthood. Strategies for genome-wide investigations will likely include coordination between epidemiological and genetic research efforts, systematic assessment of multiple environmental factors in large samples, and prioritization of genetic variants.

Ultrahigh-dimensional variable selection method for whole-genome gene-gene interaction analysis

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Ueki Masao

2012-05-01

Full Text Available Abstract Background Genome-wide gene-gene interaction analysis using single nucleotide polymorphisms (SNPs is an attractive way for identification of genetic components that confers susceptibility of human complex diseases. Individual hypothesis testing for SNP-SNP pairs as in common genome-wide association study (GWAS however involves difficulty in setting overall p-value due to complicated correlation structure, namely, the multiple testing problem that causes unacceptable false negative results. A large number of SNP-SNP pairs than sample size, so-called the large p small n problem, precludes simultaneous analysis using multiple regression. The method that overcomes above issues is thus needed. Results We adopt an up-to-date method for ultrahigh-dimensional variable selection termed the sure independence screening (SIS for appropriate handling of numerous number of SNP-SNP interactions by including them as predictor variables in logistic regression. We propose ranking strategy using promising dummy coding methods and following variable selection procedure in the SIS method suitably modified for gene-gene interaction analysis. We also implemented the procedures in a software program, EPISIS, using the cost-effective GPGPU (General-purpose computing on graphics processing units technology. EPISIS can complete exhaustive search for SNP-SNP interactions in standard GWAS dataset within several hours. The proposed method works successfully in simulation experiments and in application to real WTCCC (Wellcome Trust Case–control Consortium data. Conclusions Based on the machine-learning principle, the proposed method gives powerful and flexible genome-wide search for various patterns of gene-gene interaction.

Ontology-based literature mining of E. coli vaccine-associated gene interaction networks.

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Hur, Junguk; Özgür, Arzucan; He, Yongqun

2017-03-14

Pathogenic Escherichia coli infections cause various diseases in humans and many animal species. However, with extensive E. coli vaccine research, we are still unable to fully protect ourselves against E. coli infections. To more rational development of effective and safe E. coli vaccine, it is important to better understand E. coli vaccine-associated gene interaction networks. In this study, we first extended the Vaccine Ontology (VO) to semantically represent various E. coli vaccines and genes used in the vaccine development. We also normalized E. coli gene names compiled from the annotations of various E. coli strains using a pan-genome-based annotation strategy. The Interaction Network Ontology (INO) includes a hierarchy of various interaction-related keywords useful for literature mining. Using VO, INO, and normalized E. coli gene names, we applied an ontology-based SciMiner literature mining strategy to mine all PubMed abstracts and retrieve E. coli vaccine-associated E. coli gene interactions. Four centrality metrics (i.e., degree, eigenvector, closeness, and betweenness) were calculated for identifying highly ranked genes and interaction types. Using vaccine-related PubMed abstracts, our study identified 11,350 sentences that contain 88 unique INO interactions types and 1,781 unique E. coli genes. Each sentence contained at least one interaction type and two unique E. coli genes. An E. coli gene interaction network of genes and INO interaction types was created. From this big network, a sub-network consisting of 5 E. coli vaccine genes, including carA, carB, fimH, fepA, and vat, and 62 other E. coli genes, and 25 INO interaction types was identified. While many interaction types represent direct interactions between two indicated genes, our study has also shown that many of these retrieved interaction types are indirect in that the two genes participated in the specified interaction process in a required but indirect process. Our centrality analysis of

Detection of Gene Interactions Based on Syntactic Relations

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Mi-Young Kim

2008-01-01

Full Text Available Interactions between proteins and genes are considered essential in the description of biomolecular phenomena, and networks of interactions are applied in a system's biology approach. Recently, many studies have sought to extract information from biomolecular text using natural language processing technology. Previous studies have asserted that linguistic information is useful for improving the detection of gene interactions. In particular, syntactic relations among linguistic information are good for detecting gene interactions. However, previous systems give a reasonably good precision but poor recall. To improve recall without sacrificing precision, this paper proposes a three-phase method for detecting gene interactions based on syntactic relations. In the first phase, we retrieve syntactic encapsulation categories for each candidate agent and target. In the second phase, we construct a verb list that indicates the nature of the interaction between pairs of genes. In the last phase, we determine direction rules to detect which of two genes is the agent or target. Even without biomolecular knowledge, our method performs reasonably well using a small training dataset. While the first phase contributes to improve recall, the second and third phases contribute to improve precision. In the experimental results using ICML 05 Workshop on Learning Language in Logic (LLL05 data, our proposed method gave an F-measure of 67.2% for the test data, significantly outperforming previous methods. We also describe the contribution of each phase to the performance.

The Cumulative Effect of Gene-Gene and Gene-Environment Interactions on the Risk of Prostate Cancer in Chinese Men

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Ming Liu

2016-01-01

Full Text Available Prostate cancer (PCa is a multifactorial disease involving complex genetic and environmental factors interactions. Gene-gene and gene-environment interactions associated with PCa in Chinese men are less studied. We explored the association between 36 SNPs and PCa in 574 subjects from northern China. Body mass index (BMI, smoking, and alcohol consumption were determined through self-administered questionnaires in 134 PCa patients. Then gene-gene and gene-environment interactions among the PCa-associated SNPs were analyzed using the generalized multifactor dimensionality reduction (GMDR and logistic regression methods. Allelic and genotypic association analyses showed that six variants were associated with PCa and the cumulative effect suggested men who carried any combination of 1, 2, or ≥3 risk genotypes had a gradually increased PCa risk (odds ratios (ORs = 1.79–4.41. GMDR analysis identified the best gene-gene interaction model with scores of 10 for both the cross-validation consistency and sign tests. For gene-environment interactions, rs6983561 CC and rs16901966 GG in individuals with a BMI ≥ 28 had ORs of 7.66 (p = 0.032 and 5.33 (p = 0.046, respectively. rs7679673 CC + CA and rs12653946 TT in individuals that smoked had ORs of 2.77 (p = 0.007 and 3.11 (p = 0.024, respectively. rs7679673 CC in individuals that consumed alcohol had an OR of 4.37 (p = 0.041. These results suggest that polymorphisms, either individually or by interacting with other genes or environmental factors, contribute to an increased risk of PCa.

Novel interactions between vertebrate Hox genes

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Hooiveld, MHW; Morgan, R; Rieden, PID; Houtzager, E; Pannese, M; Damen, K; Boncinelli, E; Durston, AJ

1999-01-01

Understanding why metazoan Hox/HOM-C genes are expressed in spatiotemporal sequences showing colinearity with their genomic sequence is a central challenge in developmental biology. Here, we studied the consequences of ectopically expressing Hox genes to investigate whether Hox-Hox interactions

Combining many interaction networks to predict gene function and analyze gene lists.

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Mostafavi, Sara; Morris, Quaid

2012-05-01

In this article, we review how interaction networks can be used alone or in combination in an automated fashion to provide insight into gene and protein function. We describe the concept of a "gene-recommender system" that can be applied to any large collection of interaction networks to make predictions about gene or protein function based on a query list of proteins that share a function of interest. We discuss these systems in general and focus on one specific system, GeneMANIA, that has unique features and uses different algorithms from the majority of other systems. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Gene-based testing of interactions in association studies of quantitative traits.

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Li Ma

Full Text Available Various methods have been developed for identifying gene-gene interactions in genome-wide association studies (GWAS. However, most methods focus on individual markers as the testing unit, and the large number of such tests drastically erodes statistical power. In this study, we propose novel interaction tests of quantitative traits that are gene-based and that confer advantage in both statistical power and biological interpretation. The framework of gene-based gene-gene interaction (GGG tests combine marker-based interaction tests between all pairs of markers in two genes to produce a gene-level test for interaction between the two. The tests are based on an analytical formula we derive for the correlation between marker-based interaction tests due to linkage disequilibrium. We propose four GGG tests that extend the following P value combining methods: minimum P value, extended Simes procedure, truncated tail strength, and truncated P value product. Extensive simulations point to correct type I error rates of all tests and show that the two truncated tests are more powerful than the other tests in cases of markers involved in the underlying interaction not being directly genotyped and in cases of multiple underlying interactions. We applied our tests to pairs of genes that exhibit a protein-protein interaction to test for gene-level interactions underlying lipid levels using genotype data from the Atherosclerosis Risk in Communities study. We identified five novel interactions that are not evident from marker-based interaction testing and successfully replicated one of these interactions, between SMAD3 and NEDD9, in an independent sample from the Multi-Ethnic Study of Atherosclerosis. We conclude that our GGG tests show improved power to identify gene-level interactions in existing, as well as emerging, association studies.

Leveraging gene-environment interactions and endotypes for asthma gene discovery

DEFF Research Database (Denmark)

Bønnelykke, Klaus; Ober, Carole

2016-01-01

, 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......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...

Association testing to detect gene-gene interactions on sex chromosomes in trio data

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Yeonok eLee

2013-11-01

Full Text Available Autism Spectrum Disorder (ASD occurs more often among males than females in a 4:1 ratio. Among theories used to explain the causes of ASD, the X chromosome and the Y chromosome theories attribute ASD to X-linked mutation and the male-limited gene expressions on the Y chromosome, respectively. Despite the rationale of the theory, studies have failed to attribute the sex-biased ratio to the significant linkage or association on the regions of interest on X chromosome. We further study the gender biased ratio by examining the possible interaction effects between two genes in the sex chromosomes. We propose a logistic regression model with mixed effects to detect gene-gene interactions on sex chromosomes. We investigated the power and type I error rates of the approach for a range of minor allele frequencies and varying linkage disequilibrium between markers and QTLs. We also evaluated the robustness of the model to population stratification. We applied the model to a trio-family data set with an ASD affected male child to study gene-gene interactions on sex chromosomes.

Network Graph Analysis of Gene-Gene Interactions in Genome-Wide Association Study Data

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Sungyoung Lee

2012-12-01

Full Text Available Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs. For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR is one of the powerful and efficient methods for detecting high-order gene-gene (GxG interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI. Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.

Network graph analysis of gene-gene interactions in genome-wide association study data.

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Lee, Sungyoung; Kwon, Min-Seok; Park, Taesung

2012-12-01

Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene (GxG) interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.

Double-Bottom Chaotic Map Particle Swarm Optimization Based on Chi-Square Test to Determine Gene-Gene Interactions

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Yang, Cheng-Hong; Chang, Hsueh-Wei

2014-01-01

Gene-gene interaction studies focus on the investigation of the association between the single nucleotide polymorphisms (SNPs) of genes for disease susceptibility. Statistical methods are widely used to search for a good model of gene-gene interaction for disease analysis, and the previously determined models have successfully explained the effects between SNPs and diseases. However, the huge numbers of potential combinations of SNP genotypes limit the use of statistical methods for analysing high-order interaction, and finding an available high-order model of gene-gene interaction remains a challenge. In this study, an improved particle swarm optimization with double-bottom chaotic maps (DBM-PSO) was applied to assist statistical methods in the analysis of associated variations to disease susceptibility. A big data set was simulated using the published genotype frequencies of 26 SNPs amongst eight genes for breast cancer. Results showed that the proposed DBM-PSO successfully determined two- to six-order models of gene-gene interaction for the risk association with breast cancer (odds ratio > 1.0; P value <0.05). Analysis results supported that the proposed DBM-PSO can identify good models and provide higher chi-square values than conventional PSO. This study indicates that DBM-PSO is a robust and precise algorithm for determination of gene-gene interaction models for breast cancer. PMID:24895547

Inverse gene-for-gene interactions contribute additively to tan spot susceptibility in wheat.

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Liu, Zhaohui; Zurn, Jason D; Kariyawasam, Gayan; Faris, Justin D; Shi, Gongjun; Hansen, Jana; Rasmussen, Jack B; Acevedo, Maricelis

2017-06-01

Tan spot susceptibility is conferred by multiple interactions of necrotrophic effector and host sensitivity genes. Tan spot of wheat, caused by Pyrenophora tritici-repentis, is an important disease in almost all wheat-growing areas of the world. The disease system is known to involve at least three fungal-produced necrotrophic effectors (NEs) that interact with the corresponding host sensitivity (S) genes in an inverse gene-for-gene manner to induce disease. However, it is unknown if the effects of these NE-S gene interactions contribute additively to the development of tan spot. In this work, we conducted disease evaluations using different races and quantitative trait loci (QTL) analysis in a wheat recombinant inbred line (RIL) population derived from a cross between two susceptible genotypes, LMPG-6 and PI 626573. The two parental lines each harbored a single known NE sensitivity gene with LMPG-6 having the Ptr ToxC sensitivity gene Tsc1 and PI 626573 having the Ptr ToxA sensitivity gene Tsn1. Transgressive segregation was observed in the population for all races. QTL mapping revealed that both loci (Tsn1 and Tsc1) were significantly associated with susceptibility to race 1 isolates, which produce both Ptr ToxA and Ptr ToxC, and the two genes contributed additively to tan spot susceptibility. For isolates of races 2 and 3, which produce only Ptr ToxA and Ptr ToxC, only Tsn1 and Tsc1 were associated with tan spot susceptibility, respectively. This work clearly demonstrates that tan spot susceptibility in this population is due primarily to two NE-S interactions. Breeders should remove both sensitivity genes from wheat lines to obtain high levels of tan spot resistance.

A model of gene-gene and gene-environment interactions and its implications for targeting environmental interventions by genotype

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Wallace Helen M

2006-10-01

Full Text Available Abstract Background The potential public health benefits of targeting environmental interventions by genotype depend on the environmental and genetic contributions to the variance of common diseases, and the magnitude of any gene-environment interaction. In the absence of prior knowledge of all risk factors, twin, family and environmental data may help to define the potential limits of these benefits in a given population. However, a general methodology to analyze twin data is required because of the potential importance of gene-gene interactions (epistasis, gene-environment interactions, and conditions that break the 'equal environments' assumption for monozygotic and dizygotic twins. Method A new model for gene-gene and gene-environment interactions is developed that abandons the assumptions of the classical twin study, including Fisher's (1918 assumption that genes act as risk factors for common traits in a manner necessarily dominated by an additive polygenic term. Provided there are no confounders, the model can be used to implement a top-down approach to quantifying the potential utility of genetic prediction and prevention, using twin, family and environmental data. The results describe a solution space for each disease or trait, which may or may not include the classical twin study result. Each point in the solution space corresponds to a different model of genotypic risk and gene-environment interaction. Conclusion The results show that the potential for reducing the incidence of common diseases using environmental interventions targeted by genotype may be limited, except in special cases. The model also confirms that the importance of an individual's genotype in determining their risk of complex diseases tends to be exaggerated by the classical twin studies method, owing to the 'equal environments' assumption and the assumption of no gene-environment interaction. In addition, if phenotypes are genetically robust, because of epistasis

Gene-physical activity interactions and their impact on diabetes

DEFF Research Database (Denmark)

Oskari Kilpeläinen, Tuomas; Franks, Paul W

2014-01-01

to an equal bout of physical activity. Individuals with specific genetic profiles are also expected to be more responsive to the beneficial effects of physical activity in the prevention of type 2 diabetes. Identification of such gene-physical activity interactions could give new insights into the biological...... the reader to the recent advances in the genetics of type 2 diabetes, summarize the current evidence on gene-physical activity interactions in relation to type 2 diabetes, and outline how information on gene-physical activity interactions might help improve the prevention and treatment of type 2 diabetes....... Finally, we will discuss the existing and emerging strategies that might enhance our ability to identify and exploit gene-physical activity interactions in the etiology of type 2 diabetes. © 2014 S. Karger AG, Basel....

Identification of human disease genes from interactome network using graphlet interaction.

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Xiao-Dong Wang

Full Text Available Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes.

Identification of Human Disease Genes from Interactome Network Using Graphlet Interaction

Science.gov (United States)

Yang, Lun; Wei, Dong-Qing; Qi, Ying-Xin; Jiang, Zong-Lai

2014-01-01

Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes. PMID:24465923

Mining disease genes using integrated protein-protein interaction and gene-gene co-regulation information.

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Li, Jin; Wang, Limei; Guo, Maozu; Zhang, Ruijie; Dai, Qiguo; Liu, Xiaoyan; Wang, Chunyu; Teng, Zhixia; Xuan, Ping; Zhang, Mingming

2015-01-01

In humans, despite the rapid increase in disease-associated gene discovery, a large proportion of disease-associated genes are still unknown. Many network-based approaches have been used to prioritize disease genes. Many networks, such as the protein-protein interaction (PPI), KEGG, and gene co-expression networks, have been used. Expression quantitative trait loci (eQTLs) have been successfully applied for the determination of genes associated with several diseases. In this study, we constructed an eQTL-based gene-gene co-regulation network (GGCRN) and used it to mine for disease genes. We adopted the random walk with restart (RWR) algorithm to mine for genes associated with Alzheimer disease. Compared to the Human Protein Reference Database (HPRD) PPI network alone, the integrated HPRD PPI and GGCRN networks provided faster convergence and revealed new disease-related genes. Therefore, using the RWR algorithm for integrated PPI and GGCRN is an effective method for disease-associated gene mining.

Large-scale extraction of gene interactions from full-text literature using DeepDive.

Science.gov (United States)

Mallory, Emily K; Zhang, Ce; Ré, Christopher; Altman, Russ B

2016-01-01

A complete repository of gene-gene interactions is key for understanding cellular processes, human disease and drug response. These gene-gene interactions include both protein-protein interactions and transcription factor interactions. The majority of known interactions are found in the biomedical literature. Interaction databases, such as BioGRID and ChEA, annotate these gene-gene interactions; however, curation becomes difficult as the literature grows exponentially. DeepDive is a trained system for extracting information from a variety of sources, including text. In this work, we used DeepDive to extract both protein-protein and transcription factor interactions from over 100,000 full-text PLOS articles. We built an extractor for gene-gene interactions that identified candidate gene-gene relations within an input sentence. For each candidate relation, DeepDive computed a probability that the relation was a correct interaction. We evaluated this system against the Database of Interacting Proteins and against randomly curated extractions. Our system achieved 76% precision and 49% recall in extracting direct and indirect interactions involving gene symbols co-occurring in a sentence. For randomly curated extractions, the system achieved between 62% and 83% precision based on direct or indirect interactions, as well as sentence-level and document-level precision. Overall, our system extracted 3356 unique gene pairs using 724 features from over 100,000 full-text articles. Application source code is publicly available at https://github.com/edoughty/deepdive_genegene_app russ.altman@stanford.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Artificial neural network inference (ANNI: a study on gene-gene interaction for biomarkers in childhood sarcomas.

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Dong Ling Tong

Full Text Available OBJECTIVE: To model the potential interaction between previously identified biomarkers in children sarcomas using artificial neural network inference (ANNI. METHOD: To concisely demonstrate the biological interactions between correlated genes in an interaction network map, only 2 types of sarcomas in the children small round blue cell tumors (SRBCTs dataset are discussed in this paper. A backpropagation neural network was used to model the potential interaction between genes. The prediction weights and signal directions were used to model the strengths of the interaction signals and the direction of the interaction link between genes. The ANN model was validated using Monte Carlo cross-validation to minimize the risk of over-fitting and to optimize generalization ability of the model. RESULTS: Strong connection links on certain genes (TNNT1 and FNDC5 in rhabdomyosarcoma (RMS; FCGRT and OLFM1 in Ewing's sarcoma (EWS suggested their potency as central hubs in the interconnection of genes with different functionalities. The results showed that the RMS patients in this dataset are likely to be congenital and at low risk of cardiomyopathy development. The EWS patients are likely to be complicated by EWS-FLI fusion and deficiency in various signaling pathways, including Wnt, Fas/Rho and intracellular oxygen. CONCLUSIONS: The ANN network inference approach and the examination of identified genes in the published literature within the context of the disease highlights the substantial influence of certain genes in sarcomas.

Gene-Lifestyle Interactions in Obesity.

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van Vliet-Ostaptchouk, Jana V; Snieder, Harold; Lagou, Vasiliki

2012-01-01

Obesity is a complex multifaceted disease resulting from interactions between genetics and lifestyle. The proportion of phenotypic variance ascribed to genetic variance is 0.4 to 0.7 for obesity and recent years have seen considerable success in identifying disease-susceptibility variants. Although with the advent of genome-wide association studies the list of genetic variants predisposing to obesity has significantly increased the identified variants only explain a fraction of disease heritability. Studies of gene-environment interactions can provide more insight into the biological mechanisms involved in obesity despite the challenges associated with such designs. Epigenetic changes that affect gene function without DNA sequence modifications may be a key factor explaining interindividual differences in obesity, with both genetic and environmental factors influencing the epigenome. Disentangling the relative contributions of genetic, environmental and epigenetic marks to the establishment of obesity is a major challenge given the complex interplay between these determinants.

[Gene-gene interaction on central obesity in school-aged children in China].

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Fu, L W; Zhang, M X; Wu, L J; Gao, L W; Mi, J

2017-07-10

Objective: To investigate possible effect of 6 obesity-associated SNPs in contribution to central obesity and examine whether there is an interaction in the 6 SNPs in the cause of central obesity in school-aged children in China. Methods: A total of 3 502 school-aged children who were included in Beijing Child and Adolescent Metabolic Syndrome (BCAMS) Study were selected, and based on the age and sex specific waist circumference (WC) standards in the BCAMS study, 1 196 central obese cases and 2 306 controls were identified. Genomic DNA was extracted from peripheral blood white cells using the salt fractionation method. A total of 6 single nucleotide polymorphisms ( FTO rs9939609, MC4R rs17782313, BDNF rs6265, PCSK1 rs6235, SH2B1 rs4788102, and CSK rs1378942) were genotyped by TaqMan allelic discrimination assays with the GeneAmp 7900 sequence detection system (Applied Biosystems, Foster City, CA, USA). Logistic regression model was used to investigate the association between 6 SNPs and central obesity. Gene-gene interactions among 6 polymorphic loci were analyzed by using the Generalized Multifactor Dimensionality Reduction (GMDR) method, and then logistic regression model was constructed to confirm the best combination of loci identified in the GMDR. Results: After adjusting gender, age, Tanner stage, physical activity and family history of obesity, the FTO rs9939609-A, MC4R rs17782313-C and BDNF rs6265-G alleles were associated with central obesity under additive genetic model ( OR =1.24, 95 %CI : 1.06-1.45, P =0.008; OR =1.26, 95 %CI : 1.11-1.43, P =2.98×10(-4); OR =1.18, 95 % CI : 1.06-1.32, P =0.003). GMDR analysis showed a significant gene-gene interaction between MC4R rs17782313 and BDNF rs6265 ( P =0.001). The best two-locus combination showed the cross-validation consistency of 10/10 and testing accuracy of 0.539. This interaction showed the maximum consistency and minimum prediction error among all gene-gene interaction models evaluated. Moreover, the

Blood lead levels, iron metabolism gene polymorphisms and homocysteine: a gene-environment interaction study.

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Kim, Kyoung-Nam; Lee, Mee-Ri; Lim, Youn-Hee; Hong, Yun-Chul

2017-12-01

Homocysteine has been causally associated with various adverse health outcomes. Evidence supporting the relationship between lead and homocysteine levels has been accumulating, but most prior studies have not focused on the interaction with genetic polymorphisms. From a community-based prospective cohort, we analysed 386 participants (aged 41-71 years) with information regarding blood lead and plasma homocysteine levels. Blood lead levels were measured between 2001 and 2003, and plasma homocysteine levels were measured in 2007. Interactions of lead levels with 42 genotyped single-nucleotide polymorphisms (SNPs) in five genes ( TF , HFE , CBS , BHMT and MTR ) were assessed via a 2-degree of freedom (df) joint test and a 1-df interaction test. In secondary analyses using imputation, we further assessed 58 imputed SNPs in the TF and MTHFR genes. Blood lead concentrations were positively associated with plasma homocysteine levels (p=0.0276). Six SNPs in the TF and MTR genes were screened using the 2-df joint test, and among them, three SNPs in the TF gene showed interactions with lead with respect to homocysteine levels through the 1-df interaction test (plead levels. Blood lead levels were positively associated with plasma homocysteine levels measured 4-6 years later, and three SNPs in the TF gene modified the association. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Spatially Uniform ReliefF (SURF for computationally-efficient filtering of gene-gene interactions

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Greene Casey S

2009-09-01

Full Text Available Abstract Background Genome-wide association studies are becoming the de facto standard in the genetic analysis of common human diseases. Given the complexity and robustness of biological networks such diseases are unlikely to be the result of single points of failure but instead likely arise from the joint failure of two or more interacting components. The hope in genome-wide screens is that these points of failure can be linked to single nucleotide polymorphisms (SNPs which confer disease susceptibility. Detecting interacting variants that lead to disease in the absence of single-gene effects is difficult however, and methods to exhaustively analyze sets of these variants for interactions are combinatorial in nature thus making them computationally infeasible. Efficient algorithms which can detect interacting SNPs are needed. ReliefF is one such promising algorithm, although it has low success rate for noisy datasets when the interaction effect is small. ReliefF has been paired with an iterative approach, Tuned ReliefF (TuRF, which improves the estimation of weights in noisy data but does not fundamentally change the underlying ReliefF algorithm. To improve the sensitivity of studies using these methods to detect small effects we introduce Spatially Uniform ReliefF (SURF. Results SURF's ability to detect interactions in this domain is significantly greater than that of ReliefF. Similarly SURF, in combination with the TuRF strategy significantly outperforms TuRF alone for SNP selection under an epistasis model. It is important to note that this success rate increase does not require an increase in algorithmic complexity and allows for increased success rate, even with the removal of a nuisance parameter from the algorithm. Conclusion Researchers performing genetic association studies and aiming to discover gene-gene interactions associated with increased disease susceptibility should use SURF in place of ReliefF. For instance, SURF should be

You've gotta be lucky: Coverage and the elusive gene-gene interaction.

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Reimherr, Matthew; Nicolae, Dan L

2011-01-01

Genome-wide association studies (GWAS) have led to a large number of single-SNP association findings, but there has been, so far, no investigation resulting in the discovery of a replicable gene-gene interaction. In this paper, we examine some of the possible explanations for the lack of findings, and argue that coverage of causal variation not only has a large effect on the loss in power, but that the effect is larger than in the single-SNP analyses. We show that the product of linkage disequilibrium measures, r², between causal and tested SNPs offers a good approximation to the loss in efficiency as defined by the ratio of sample sizes that lead to similar power. We also demonstrate that, in addition to the huge search space, the loss in power due to coverage when using commercially available platforms makes the search for gene-gene interactions daunting. © 2010 The Authors Annals of Human Genetics © 2010 Blackwell Publishing Ltd/University College London.

Methodological issues in detecting gene-gene interactions in breast cancer susceptibility: a population-based study in Ontario

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Onay Venus

2007-08-01

Full Text Available Abstract Background There is growing evidence that gene-gene interactions are ubiquitous in determining the susceptibility to common human diseases. The investigation of such gene-gene interactions presents new statistical challenges for studies with relatively small sample sizes as the number of potential interactions in the genome can be large. Breast cancer provides a useful paradigm to study genetically complex diseases because commonly occurring single nucleotide polymorphisms (SNPs may additively or synergistically disturb the system-wide communication of the cellular processes leading to cancer development. Methods In this study, we systematically studied SNP-SNP interactions among 19 SNPs from 18 key genes involved in major cancer pathways in a sample of 398 breast cancer cases and 372 controls from Ontario. We discuss the methodological issues associated with the detection of SNP-SNP interactions in this dataset by applying and comparing three commonly used methods: the logistic regression model, classification and regression trees (CART, and the multifactor dimensionality reduction (MDR method. Results Our analyses show evidence for several simple (two-way and complex (multi-way SNP-SNP interactions associated with breast cancer. For example, all three methods identified XPD-[Lys751Gln]*IL10-[G(-1082A] as the most significant two-way interaction. CART and MDR identified the same critical SNPs participating in complex interactions. Our results suggest that the use of multiple statistical approaches (or an integrated approach rather than a single methodology could be the best strategy to elucidate complex gene interactions that have generally very different patterns. Conclusion The strategy used here has the potential to identify complex biological relationships among breast cancer genes and processes. This will lead to the discovery of novel biological information, which will improve breast cancer risk management.

Gene-Gene Interactions in the Folate Metabolic Pathway and the Risk of Conotruncal Heart Defects

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Philip J. Lupo

2010-01-01

Full Text Available Conotruncal and related heart defects (CTRD are common, complex malformations. Although there are few established risk factors, there is evidence that genetic variation in the folate metabolic pathway influences CTRD risk. This study was undertaken to assess the association between inherited (i.e., case and maternal gene-gene interactions in this pathway and the risk of CTRD. Case-parent triads (n=727, ascertained from the Children's Hospital of Philadelphia, were genotyped for ten functional variants of nine folate metabolic genes. Analyses of inherited genotypes were consistent with the previously reported association between MTHFR A1298C and CTRD (adjusted P=.02, but provided no evidence that CTRD was associated with inherited gene-gene interactions. Analyses of the maternal genotypes provided evidence of a MTHFR C677T/CBS 844ins68 interaction and CTRD risk (unadjusted P=.02. This association is consistent with the effects of this genotype combination on folate-homocysteine biochemistry but remains to be confirmed in independent study populations.

Risk score modeling of multiple gene to gene interactions using aggregated-multifactor dimensionality reduction

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Dai Hongying

2013-01-01

Full Text Available Abstract Background Multifactor Dimensionality Reduction (MDR has been widely applied to detect gene-gene (GxG interactions associated with complex diseases. Existing MDR methods summarize disease risk by a dichotomous predisposing model (high-risk/low-risk from one optimal GxG interaction, which does not take the accumulated effects from multiple GxG interactions into account. Results We propose an Aggregated-Multifactor Dimensionality Reduction (A-MDR method that exhaustively searches for and detects significant GxG interactions to generate an epistasis enriched gene network. An aggregated epistasis enriched risk score, which takes into account multiple GxG interactions simultaneously, replaces the dichotomous predisposing risk variable and provides higher resolution in the quantification of disease susceptibility. We evaluate this new A-MDR approach in a broad range of simulations. Also, we present the results of an application of the A-MDR method to a data set derived from Juvenile Idiopathic Arthritis patients treated with methotrexate (MTX that revealed several GxG interactions in the folate pathway that were associated with treatment response. The epistasis enriched risk score that pooled information from 82 significant GxG interactions distinguished MTX responders from non-responders with 82% accuracy. Conclusions The proposed A-MDR is innovative in the MDR framework to investigate aggregated effects among GxG interactions. New measures (pOR, pRR and pChi are proposed to detect multiple GxG interactions.

DGIdb 3.0: a redesign and expansion of the drug-gene interaction database.

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Cotto, Kelsy C; Wagner, Alex H; Feng, Yang-Yang; Kiwala, Susanna; Coffman, Adam C; Spies, Gregory; Wollam, Alex; Spies, Nicholas C; Griffith, Obi L; Griffith, Malachi

2018-01-04

The drug-gene interaction database (DGIdb, www.dgidb.org) consolidates, organizes and presents drug-gene interactions and gene druggability information from papers, databases and web resources. DGIdb normalizes content from 30 disparate sources and allows for user-friendly advanced browsing, searching and filtering for ease of access through an intuitive web user interface, application programming interface (API) and public cloud-based server image. DGIdb v3.0 represents a major update of the database. Nine of the previously included 24 sources were updated. Six new resources were added, bringing the total number of sources to 30. These updates and additions of sources have cumulatively resulted in 56 309 interaction claims. This has also substantially expanded the comprehensive catalogue of druggable genes and anti-neoplastic drug-gene interactions included in the DGIdb. Along with these content updates, v3.0 has received a major overhaul of its codebase, including an updated user interface, preset interaction search filters, consolidation of interaction information into interaction groups, greatly improved search response times and upgrading the underlying web application framework. In addition, the expanded API features new endpoints which allow users to extract more detailed information about queried drugs, genes and drug-gene interactions, including listings of PubMed IDs, interaction type and other interaction metadata.

Exploring Plant Co-Expression and Gene-Gene Interactions with CORNET 3.0.

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Van Bel, Michiel; Coppens, Frederik

2017-01-01

Selecting and filtering a reference expression and interaction dataset when studying specific pathways and regulatory interactions can be a very time-consuming and error-prone task. In order to reduce the duplicated efforts required to amass such datasets, we have created the CORNET (CORrelation NETworks) platform which allows for easy access to a wide variety of data types: coexpression data, protein-protein interactions, regulatory interactions, and functional annotations. The CORNET platform outputs its results in either text format or through the Cytoscape framework, which is automatically launched by the CORNET website.CORNET 3.0 is the third iteration of the web platform designed for the user exploration of the coexpression space of plant genomes, with a focus on the model species Arabidopsis thaliana. Here we describe the platform: the tools, data, and best practices when using the platform. We indicate how the platform can be used to infer networks from a set of input genes, such as upregulated genes from an expression experiment. By exploring the network, new target and regulator genes can be discovered, allowing for follow-up experiments and more in-depth study. We also indicate how to avoid common pitfalls when evaluating the networks and how to avoid over interpretation of the results.All CORNET versions are available at http://bioinformatics.psb.ugent.be/cornet/ .

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

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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.

Evidence for plasticity genotypes in a gene-gene-environment interaction : the TRAILS study

NARCIS (Netherlands)

Nederhof, E; Bouma, Esther; Riese, Harriette; Laceulle, Odilia; Ormel, J.; Oldehinkel, A.J.

2010-01-01

The purpose was to study how functional polymorphisms in the brain derived neurotrophic factor gene (BDNF val66met) and the serotonin transporter gene linked promotor region (5-HTTLPR) interact with childhood adversities in predicting Effortful Control. Effortful Control refers to the ability to

GBOOST: a GPU-based tool for detecting gene-gene interactions in genome-wide case control studies.

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Yung, Ling Sing; Yang, Can; Wan, Xiang; Yu, Weichuan

2011-05-01

Collecting millions of genetic variations is feasible with the advanced genotyping technology. With a huge amount of genetic variations data in hand, developing efficient algorithms to carry out the gene-gene interaction analysis in a timely manner has become one of the key problems in genome-wide association studies (GWAS). Boolean operation-based screening and testing (BOOST), a recent work in GWAS, completes gene-gene interaction analysis in 2.5 days on a desktop computer. Compared with central processing units (CPUs), graphic processing units (GPUs) are highly parallel hardware and provide massive computing resources. We are, therefore, motivated to use GPUs to further speed up the analysis of gene-gene interactions. We implement the BOOST method based on a GPU framework and name it GBOOST. GBOOST achieves a 40-fold speedup compared with BOOST. It completes the analysis of Wellcome Trust Case Control Consortium Type 2 Diabetes (WTCCC T2D) genome data within 1.34 h on a desktop computer equipped with Nvidia GeForce GTX 285 display card. GBOOST code is available at http://bioinformatics.ust.hk/BOOST.html#GBOOST.

Genome-wide analysis of E. coli cell-gene interactions.

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Cardinale, S; Cambray, G

2017-11-23

The pursuit of standardization and reliability in synthetic biology has achieved, in recent years, a number of advances in the design of more predictable genetic parts for biological circuits. However, even with the development of high-throughput screening methods and whole-cell models, it is still not possible to predict reliably how a synthetic genetic construct interacts with all cellular endogenous systems. This study presents a genome-wide analysis of how the expression of synthetic genes is affected by systematic perturbations of cellular functions. We found that most perturbations modulate expression indirectly through an effect on cell size, putting forward the existence of a generic Size-Expression interaction in the model prokaryote Escherichia coli. The Size-Expression interaction was quantified by inserting a dual fluorescent reporter gene construct into each of the 3822 single-gene deletion strains comprised in the KEIO collection. Cellular size was measured for single cells via flow cytometry. Regression analyses were used to discriminate between expression-specific and gene-specific effects. Functions of the deleted genes broadly mapped onto three systems with distinct primary influence on the Size-Expression map. Perturbations in the Division and Biosynthesis (DB) system led to a large-cell and high-expression phenotype. In contrast, disruptions of the Membrane and Motility (MM) system caused small-cell and low-expression phenotypes. The Energy, Protein synthesis and Ribosome (EPR) system was predominantly associated with smaller cells and positive feedback on ribosome function. Feedback between cell growth and gene expression is widespread across cell systems. Even though most gene disruptions proximally affect one component of the Size-Expression interaction, the effect therefore ultimately propagates to both. More specifically, we describe the dual impact of growth on cell size and gene expression through cell division and ribosomal content

Genome-wide search for gene-gene interactions in colorectal cancer.

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Shuo Jiao

Full Text Available Genome-wide association studies (GWAS have successfully identified a number of single-nucleotide polymorphisms (SNPs associated with colorectal cancer (CRC risk. However, these susceptibility loci known today explain only a small fraction of the genetic risk. Gene-gene interaction (GxG is considered to be one source of the missing heritability. To address this, we performed a genome-wide search for pair-wise GxG associated with CRC risk using 8,380 cases and 10,558 controls in the discovery phase and 2,527 cases and 2,658 controls in the replication phase. We developed a simple, but powerful method for testing interaction, which we term the Average Risk Due to Interaction (ARDI. With this method, we conducted a genome-wide search to identify SNPs showing evidence for GxG with previously identified CRC susceptibility loci from 14 independent regions. We also conducted a genome-wide search for GxG using the marginal association screening and examining interaction among SNPs that pass the screening threshold (p<10(-4. For the known locus rs10795668 (10p14, we found an interacting SNP rs367615 (5q21 with replication p = 0.01 and combined p = 4.19×10(-8. Among the top marginal SNPs after LD pruning (n = 163, we identified an interaction between rs1571218 (20p12.3 and rs10879357 (12q21.1 (nominal combined p = 2.51×10(-6; Bonferroni adjusted p = 0.03. Our study represents the first comprehensive search for GxG in CRC, and our results may provide new insight into the genetic etiology of CRC.

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

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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.

Gene interactions and genetics for yield and its attributes in grass ...

Indian Academy of Sciences (India)

A. K. PARIHAR

explaining the manifestation of complex traits such as yield. ... interactions (i, j, l) contributed towards the inheritance of traits in the given crosses. ... Keywords. grass pea; scaling test; gene interactions; gene effects; heritability; Lathyrus sativus.

Influence of SNPs in nutrient-sensitive candidate genes and gene-diet interactions on blood lipids

DEFF Research Database (Denmark)

Brahe, Lena Kirchner; Angquist, Lars; Larsen, Lesli Hingstrup

2013-01-01

Blood lipid response to a given dietary intervention could be determined by the effect of diet, gene variants or gene-diet interactions. The objective of the present study was to investigate whether variants in presumed nutrient-sensitive genes involved in lipid metabolism modified lipid profile ...

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

DEFF Research Database (Denmark)

Liu, Gang; Lee, Seunggeun; Lee, Alice W

2018-01-01

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 power gain compared to the standard logistic regression analysis and better control of Type I error when compared to the analysis......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 the 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. This paper extends the empirical Bayes (EB) approach previously developed for multiplicative interaction that trades off between bias and efficiency...

Gene-environment interactions involving functional variants

DEFF Research Database (Denmark)

Barrdahl, Myrto; Rudolph, Anja; Hopper, John L

2017-01-01

.36, 95% CI: 1.16-1.59, pint  = 1.9 × 10(-5) ) in relation to ER- disease risk. The remaining two gene-environment interactions were also identified in relation to ER- breast cancer risk and were found between 3p21-rs6796502 and age at menarche (ORint  = 1.26, 95% CI: 1.12-1.43, pint =1.8 × 10...... epidemiological breast cancer risk factors in relation to breast cancer. Analyses were conducted on up to 58,573 subjects (26,968 cases and 31,605 controls) from the Breast Cancer Association Consortium, in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor (ER......) positive (ER+) and ER negative (ER-) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four potential gene-environment interactions were identified as noteworthy (BFDP 

Ranking candidate disease genes from gene expression and protein interaction: a Katz-centrality based approach.

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Jing Zhao

Full Text Available Many diseases have complex genetic causes, where a set of alleles can affect the propensity of getting the disease. The identification of such disease genes is important to understand the mechanistic and evolutionary aspects of pathogenesis, improve diagnosis and treatment of the disease, and aid in drug discovery. Current genetic studies typically identify chromosomal regions associated specific diseases. But picking out an unknown disease gene from hundreds of candidates located on the same genomic interval is still challenging. In this study, we propose an approach to prioritize candidate genes by integrating data of gene expression level, protein-protein interaction strength and known disease genes. Our method is based only on two, simple, biologically motivated assumptions--that a gene is a good disease-gene candidate if it is differentially expressed in cases and controls, or that it is close to other disease-gene candidates in its protein interaction network. We tested our method on 40 diseases in 58 gene expression datasets of the NCBI Gene Expression Omnibus database. On these datasets our method is able to predict unknown disease genes as well as identifying pleiotropic genes involved in the physiological cellular processes of many diseases. Our study not only provides an effective algorithm for prioritizing candidate disease genes but is also a way to discover phenotypic interdependency, cooccurrence and shared pathophysiology between different disorders.

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

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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…

Diet-gene interactions between dietary fat intake and common polymorphisms in determining lipid metabolism

Energy Technology Data Exchange (ETDEWEB)

Corella, D.

2009-07-01

Current dietary guidelines for fat intake have not taken into consideration the possible genetic differences underlying the individual variability in responsiveness to dietary components. Genetic variability has been identified in humans for all the known lipid metabolism-related genes resulting in a plethora of candidate genes and genetic variants to examine in diet-gene interaction studies focused on fat consumption. Some examples of fat-gene interaction are reviewed. These include: the interaction between total intake and the 14C/T in the hepatic lipase gene promoter in determining high-density lipoprotein cholesterol (HDL-C) metabolism; the interaction between polyunsaturated fatty acids (PUFA) and the 5G/A polymorphism in the APOA1 gene plasma HDL-C concentrations; the interaction between PUFA and the L162V polymorphism in the PPARA gene in determining triglycerides and APOC3 concentrations; and the interaction between PUFA intake and the -1131T>C in the APOA5 gene in determining triglyceride metabolism. Although hundreds of diet-gene interaction studies in lipid metabolism have been published, the level of evidence to make specific nutritional recommendations to the population is still low and more research in nutrigenetics has to be undertaken. (Author) 31 refs.

Integration of human adipocyte chromosomal interactions with adipose gene expression prioritizes obesity-related genes from GWAS.

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Pan, David Z; Garske, Kristina M; Alvarez, Marcus; Bhagat, Yash V; Boocock, James; Nikkola, Elina; Miao, Zong; Raulerson, Chelsea K; Cantor, Rita M; Civelek, Mete; Glastonbury, Craig A; Small, Kerrin S; Boehnke, Michael; Lusis, Aldons J; Sinsheimer, Janet S; Mohlke, Karen L; Laakso, Markku; Pajukanta, Päivi; Ko, Arthur

2018-04-17

Increased adiposity is a hallmark of obesity and overweight, which affect 2.2 billion people world-wide. Understanding the genetic and molecular mechanisms that underlie obesity-related phenotypes can help to improve treatment options and drug development. Here we perform promoter Capture Hi-C in human adipocytes to investigate interactions between gene promoters and distal elements as a transcription-regulating mechanism contributing to these phenotypes. We find that promoter-interacting elements in human adipocytes are enriched for adipose-related transcription factor motifs, such as PPARG and CEBPB, and contribute to heritability of cis-regulated gene expression. We further intersect these data with published genome-wide association studies for BMI and BMI-related metabolic traits to identify the genes that are under genetic cis regulation in human adipocytes via chromosomal interactions. This integrative genomics approach identifies four cis-eQTL-eGene relationships associated with BMI or obesity-related traits, including rs4776984 and MAP2K5, which we further confirm by EMSA, and highlights 38 additional candidate genes.

Assessment of gene-by-sex interaction effect on bone mineral density

DEFF Research Database (Denmark)

Liu, Ching-Ti; Estrada, Karol; Yerges-Armstrong, Laura M

2012-01-01

Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however, the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome-wide, and ......Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however, the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome...

Assessment of Multifactor Gene-Environment Interactions and Ovarian Cancer Risk

DEFF Research Database (Denmark)

Usset, Joseph L; Raghavan, Rama; Tyrer, Jonathan P

2016-01-01

and non-obese women. METHODS: We considered interactions between 11,441 SNPs within 80 candidate genes related to hormone biosynthesis and metabolism and insulin-like growth factors with six hormone-related factors (oral contraceptive use, parity, endometriosis, tubal ligation, hormone replacement therapy...... Future work is needed to develop powerful statistical methods able to detect these complex interactions. IMPACT: Assessment of multifactor interaction is feasible, and, here, suggests that the relationship between genetic variants within candidate genes and hormone-related risk factors may vary EOC...

FunGeneNet: a web tool to estimate enrichment of functional interactions in experimental gene sets.

Science.gov (United States)

Tiys, Evgeny S; Ivanisenko, Timofey V; Demenkov, Pavel S; Ivanisenko, Vladimir A

2018-02-09

Estimation of functional connectivity in gene sets derived from genome-wide or other biological experiments is one of the essential tasks of bioinformatics. A promising approach for solving this problem is to compare gene networks built using experimental gene sets with random networks. One of the resources that make such an analysis possible is CrossTalkZ, which uses the FunCoup database. However, existing methods, including CrossTalkZ, do not take into account individual types of interactions, such as protein/protein interactions, expression regulation, transport regulation, catalytic reactions, etc., but rather work with generalized types characterizing the existence of any connection between network members. We developed the online tool FunGeneNet, which utilizes the ANDSystem and STRING to reconstruct gene networks using experimental gene sets and to estimate their difference from random networks. To compare the reconstructed networks with random ones, the node permutation algorithm implemented in CrossTalkZ was taken as a basis. To study the FunGeneNet applicability, the functional connectivity analysis of networks constructed for gene sets involved in the Gene Ontology biological processes was conducted. We showed that the method sensitivity exceeds 0.8 at a specificity of 0.95. We found that the significance level of the difference between gene networks of biological processes and random networks is determined by the type of connections considered between objects. At the same time, the highest reliability is achieved for the generalized form of connections that takes into account all the individual types of connections. By taking examples of the thyroid cancer networks and the apoptosis network, it is demonstrated that key participants in these processes are involved in the interactions of those types by which these networks differ from random ones. FunGeneNet is a web tool aimed at proving the functionality of networks in a wide range of sizes of

GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature

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Ning Ye

2015-01-01

Full Text Available The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.

Prioritization of gene regulatory interactions from large-scale modules in yeast

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Bringas Ricardo

2008-01-01

Full Text Available Abstract Background The identification of groups of co-regulated genes and their transcription factors, called transcriptional modules, has been a focus of many studies about biological systems. While methods have been developed to derive numerous modules from genome-wide data, individual links between regulatory proteins and target genes still need experimental verification. In this work, we aim to prioritize regulator-target links within transcriptional modules based on three types of large-scale data sources. Results Starting with putative transcriptional modules from ChIP-chip data, we first derive modules in which target genes show both expression and function coherence. The most reliable regulatory links between transcription factors and target genes are established by identifying intersection of target genes in coherent modules for each enriched functional category. Using a combination of genome-wide yeast data in normal growth conditions and two different reference datasets, we show that our method predicts regulatory interactions with significantly higher predictive power than ChIP-chip binding data alone. A comparison with results from other studies highlights that our approach provides a reliable and complementary set of regulatory interactions. Based on our results, we can also identify functionally interacting target genes, for instance, a group of co-regulated proteins related to cell wall synthesis. Furthermore, we report novel conserved binding sites of a glycoprotein-encoding gene, CIS3, regulated by Swi6-Swi4 and Ndd1-Fkh2-Mcm1 complexes. Conclusion We provide a simple method to prioritize individual TF-gene interactions from large-scale transcriptional modules. In comparison with other published works, we predict a complementary set of regulatory interactions which yields a similar or higher prediction accuracy at the expense of sensitivity. Therefore, our method can serve as an alternative approach to prioritization for

Synergistic interactions of biotic and abiotic environmental stressors on gene expression.

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Altshuler, Ianina; McLeod, Anne M; Colbourne, John K; Yan, Norman D; Cristescu, Melania E

2015-03-01

Understanding the response of organisms to multiple stressors is critical for predicting if populations can adapt to rapid environmental change. Natural and anthropogenic stressors often interact, complicating general predictions. In this study, we examined the interactive and cumulative effects of two common environmental stressors, lowered calcium concentration, an anthropogenic stressor, and predator presence, a natural stressor, on the water flea Daphnia pulex. We analyzed expression changes of five genes involved in calcium homeostasis - cuticle proteins (Cutie, Icp2), calbindin (Calb), and calcium pump and channel (Serca and Ip3R) - using real-time quantitative PCR (RT-qPCR) in a full factorial experiment. We observed strong synergistic interactions between low calcium concentration and predator presence. While the Ip3R gene was not affected by the stressors, the other four genes were affected in their transcriptional levels by the combination of the stressors. Transcriptional patterns of genes that code for cuticle proteins (Cutie and Icp2) and a sarcoplasmic calcium pump (Serca) only responded to the combination of stressors, changing their relative expression levels in a synergistic response, while a calcium-binding protein (Calb) responded to low calcium stress and the combination of both stressors. The expression pattern of these genes (Cutie, Icp2, and Serca) were nonlinear, yet they were dose dependent across the calcium gradient. Multiple stressors can have complex, often unexpected effects on ecosystems. This study demonstrates that the dominant interaction for the set of tested genes appears to be synergism. We argue that gene expression patterns can be used to understand and predict the type of interaction expected when organisms are exposed simultaneously to natural and anthropogenic stressors.

Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks.

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Deeter, Anthony; Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui

2017-01-01

The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways.

A novel approach to simulate gene-environment interactions in complex diseases

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Nicodemi Mario

2010-01-01

Full Text Available Abstract Background Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.. Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason can be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. An improvement in this direction would lead to a better understanding and description of gene-environment interactions. To this aim, a possible strategy is to challenge the different statistical methods against data sets where the underlying phenomenon is completely known and fully controllable, for example simulated ones. Results We present a mathematical approach that models gene-environment interactions. By this method it is possible to generate simulated populations having gene-environment interactions of any form, involving any number of genetic and environmental factors and also allowing non-linear interactions as epistasis. In particular, we implemented a simple version of this model in a Gene-Environment iNteraction Simulator (GENS, a tool designed to simulate case-control data sets where a one gene-one environment interaction influences the disease risk. The main aim has been to allow the input of population characteristics by using standard epidemiological measures and to implement constraints to make the simulator behaviour biologically meaningful. Conclusions By the multi-logistic model implemented in GENS it is possible to simulate case-control samples of complex disease where gene-environment interactions influence the disease risk. The user has full control of the main characteristics of the simulated population and a Monte

Methylobacterium-plant interaction genes regulated by plant exudate and quorum sensing molecules

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Manuella Nóbrega Dourado

2013-12-01

Full Text Available Bacteria from the genus Methylobacterium interact symbiotically (endophytically and epiphytically with different plant species. These interactions can promote plant growth or induce systemic resistance, increasing plant fitness. The plant colonization is guided by molecular communication between bacteria-bacteria and bacteria-plants, where the bacteria recognize specific exuded compounds by other bacteria (e.g. homoserine molecules and/or by the plant roots (e.g. flavonoids, ethanol and methanol, respectively. In this context, the aim of this study was to evaluate the effect of quorum sensing molecules (N-acyl-homoserine lactones and plant exudates (including ethanol in the expression of a series of bacterial genes involved in Methylobacterium-plant interaction. The selected genes are related to bacterial metabolism (mxaF, adaptation to stressful environment (crtI, phoU and sss, to interactions with plant metabolism compounds (acdS and pathogenicity (patatin and phoU. Under in vitro conditions, our results showed the differential expression of some important genes related to metabolism, stress and pathogenesis, thereby AHL molecules up-regulate all tested genes, except phoU, while plant exudates induce only mxaF gene expression. In the presence of plant exudates there is a lower bacterial density (due the endophytic and epiphytic colonization, which produce less AHL, leading to down regulation of genes when compared to the control. Therefore, bacterial density, more than plant exudate, influences the expression of genes related to plant-bacteria interaction.

ReliefSeq: a gene-wise adaptive-K nearest-neighbor feature selection tool for finding gene-gene interactions and main effects in mRNA-Seq gene expression data.

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Brett A McKinney

Full Text Available Relief-F is a nonparametric, nearest-neighbor machine learning method that has been successfully used to identify relevant variables that may interact in complex multivariate models to explain phenotypic variation. While several tools have been developed for assessing differential expression in sequence-based transcriptomics, the detection of statistical interactions between transcripts has received less attention in the area of RNA-seq analysis. We describe a new extension and assessment of Relief-F for feature selection in RNA-seq data. The ReliefSeq implementation adapts the number of nearest neighbors (k for each gene to optimize the Relief-F test statistics (importance scores for finding both main effects and interactions. We compare this gene-wise adaptive-k (gwak Relief-F method with standard RNA-seq feature selection tools, such as DESeq and edgeR, and with the popular machine learning method Random Forests. We demonstrate performance on a panel of simulated data that have a range of distributional properties reflected in real mRNA-seq data including multiple transcripts with varying sizes of main effects and interaction effects. For simulated main effects, gwak-Relief-F feature selection performs comparably to standard tools DESeq and edgeR for ranking relevant transcripts. For gene-gene interactions, gwak-Relief-F outperforms all comparison methods at ranking relevant genes in all but the highest fold change/highest signal situations where it performs similarly. The gwak-Relief-F algorithm outperforms Random Forests for detecting relevant genes in all simulation experiments. In addition, Relief-F is comparable to the other methods based on computational time. We also apply ReliefSeq to an RNA-Seq study of smallpox vaccine to identify gene expression changes between vaccinia virus-stimulated and unstimulated samples. ReliefSeq is an attractive tool for inclusion in the suite of tools used for analysis of mRNA-Seq data; it has power to

Insulators form gene loops by interacting with promoters in Drosophila.

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Erokhin, Maksim; Davydova, Anna; Kyrchanova, Olga; Parshikov, Alexander; Georgiev, Pavel; Chetverina, Darya

2011-09-01

Chromatin insulators are regulatory elements involved in the modulation of enhancer-promoter communication. The 1A2 and Wari insulators are located immediately downstream of the Drosophila yellow and white genes, respectively. Using an assay based on the yeast GAL4 activator, we have found that both insulators are able to interact with their target promoters in transgenic lines, forming gene loops. The existence of an insulator-promoter loop is confirmed by the fact that insulator proteins could be detected on the promoter only in the presence of an insulator in the transgene. The upstream promoter regions, which are required for long-distance stimulation by enhancers, are not essential for promoter-insulator interactions. Both insulators support basal activity of the yellow and white promoters in eyes. Thus, the ability of insulators to interact with promoters might play an important role in the regulation of basal gene transcription.

A high-resolution gene expression atlas of epistasis between gene-specific transcription factors exposes potential mechanisms for genetic interactions.

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Sameith, Katrin; Amini, Saman; Groot Koerkamp, Marian J A; van Leenen, Dik; Brok, Mariel; Brabers, Nathalie; Lijnzaad, Philip; van Hooff, Sander R; Benschop, Joris J; Lenstra, Tineke L; Apweiler, Eva; van Wageningen, Sake; Snel, Berend; Holstege, Frank C P; Kemmeren, Patrick

2015-12-23

Genetic interactions, or non-additive effects between genes, play a crucial role in many cellular processes and disease. Which mechanisms underlie these genetic interactions has hardly been characterized. Understanding the molecular basis of genetic interactions is crucial in deciphering pathway organization and understanding the relationship between genotype, phenotype and disease. To investigate the nature of genetic interactions between gene-specific transcription factors (GSTFs) in Saccharomyces cerevisiae, we systematically analyzed 72 GSTF pairs by gene expression profiling double and single deletion mutants. These pairs were selected through previously published growth-based genetic interactions as well as through similarity in DNA binding properties. The result is a high-resolution atlas of gene expression-based genetic interactions that provides systems-level insight into GSTF epistasis. The atlas confirms known genetic interactions and exposes new ones. Importantly, the data can be used to investigate mechanisms that underlie individual genetic interactions. Two molecular mechanisms are proposed, "buffering by induced dependency" and "alleviation by derepression". These mechanisms indicate how negative genetic interactions can occur between seemingly unrelated parallel pathways and how positive genetic interactions can indirectly expose parallel rather than same-pathway relationships. The focus on GSTFs is important for understanding the transcription regulatory network of yeast as it uncovers details behind many redundancy relationships, some of which are completely new. In addition, the study provides general insight into the complex nature of epistasis and proposes mechanistic models for genetic interactions, the majority of which do not fall into easily recognizable within- or between-pathway relationships.

Gene × Environment Interactions in Schizophrenia: Evidence from Genetic Mouse Models.

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Moran, Paula; Stokes, Jennifer; Marr, Julia; Bock, Gavin; Desbonnet, Lieve; Waddington, John; O'Tuathaigh, Colm

2016-01-01

The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia.

Gene × Environment Interactions in Schizophrenia: Evidence from Genetic Mouse Models

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Marr, Julia; Bock, Gavin; Desbonnet, Lieve; Waddington, John

2016-01-01

The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia. PMID:27725886

Gene-gene interactions of IRF5, STAT4, IKZF1 and ETS1 in systemic lupus erythematosus.

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Dang, J; Shan, S; Li, J; Zhao, H; Xin, Q; Liu, Y; Bian, X; Liu, Q

2014-06-01

Interferon (IFN) activation signaling and T helper 17 (Th17)-cell/B-cell regulation play a critical role in the pathogenesis of systemic lupus erythematosus (SLE). Several studies have provided convincing evidence that polymorphisms in IRF5, STAT4, IKZF1 and ETS1 from these pathways may be involved in SLE by affecting gene expression or epistasis. We analyzed the genetic interaction in known SLE susceptibility loci from the four genes in northern Han Chinese. A total of 946 northern Han Chinese participated in this study (370 unrelated SLE patients and 576 healthy controls). Subjects underwent genotyping for the single-nucleotide polymorphisms (SNPs) rs2004640 in IRF5, rs7574865 in STAT4, rs4917014 in IKZF1 and rs1128334 in ETS1 by use of a TaqMan SNP genotyping assay and direct sequencing. Gene-gene interaction analysis involved direct counting, multifactor dimensionality reduction (MDR) and linear regression analysis. SLE patients and controls differed in allele frequencies of rs7574865, rs1128334 (P < 0.001) and rs4917014 (P < 0.01). Direct counting revealed that the frequency of risk homozygote combinations was higher for SLE patients than controls (P < 0.01). Furthermore, 2-, 3- and 4-way gene-gene epistasis in SLE was confirmed by parametric methods and MDR analysis. Gene expression analysis partially supported the findings. Our study confirmed the association of the IFN pathway or Th17/B-cells and the pathogenesis of SLE, and gene-gene interaction in this pathway may increase the risk of SLE. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Gene-Environment Interactions in the Development of Complex Disease Phenotypes

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Kenneth Olden

2008-03-01

Full Text Available The lack of knowledge about the earliest events in disease development is due to the multi-factorial nature of disease risk. This information gap is the consequence of the lack of appreciation for the fact that most diseases arise from the complex interactions between genes and the environment as a function of the age or stage of development of the individual. Whether an environmental exposure causes illness or not is dependent on the efficiency of the so-called “environmental response machinery” (i.e., the complex of metabolic pathways that can modulate response to environmental perturbations that one has inherited. Thus, elucidating the causes of most chronic diseases will require an understanding of both the genetic and environmental contribution to their etiology. Unfortunately, the exploration of the relationship between genes and the environment has been hampered in the past by the limited knowledge of the human genome, and by the inclination of scientists to study disease development using experimental models that consider exposure to a single environmental agent. Rarely in the past were interactions between multiple genes or between genes and environmental agents considered in studies of human disease etiology. The most critical issue is how to relate exposure-disease association studies to pathways and mechanisms. To understand how genes and environmental factors interact to perturb biological pathways to cause injury or disease, scientists will need tools with the capacity to monitor the global expression of thousands of genes, proteins and metabolites simultaneously. The generation of such data in multiple species can be used to identify conserved and functionally significant genes and pathways involved in geneenvironment interactions. Ultimately, it is this knowledge that will be used to guide agencies such as the U.S. Department of Health and Human Services in decisions regarding biomedical research funding

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

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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…

ToxCast Data Expands Universe of Chemical-Gene Interactions (SOT)

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Characterizing the effects of chemicals in biological systems is often summarized by chemical-gene interactions, which have sparse coverage in literature. The ToxCast chemical screening program has produced bioactivity data for nearly 2000 chemicals and over 450 gene targets. Thi...

Gene-gene interaction between MSX1 and TP63 in Asian case-parent trios with nonsyndromic cleft lip with or without cleft palate.

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Liu, Dongjing; Schwender, Holger; Wang, Mengying; Wang, Hong; Wang, Ping; Zhu, Hongping; Zhou, Zhibo; Li, Jing; Wu, Tao; Beaty, Terri H

2018-03-01

Small ubiquitin-like modification, also known as sumoylation, is a crucial post-translational regulatory mechanisms involved in development of the lip and palate. Recent studies reported two sumoylation target genes, MSX1 and TP63, to have achieved genome-wide level significance in tests of association with nonsyndromic clefts. Here, we performed a candidate gene analysis considering gene-gene and gene-environment interaction for SUMO1, MSX1, and TP63 to further explore the etiology of nonsyndromic cleft lip with or without cleft palate (NSCL/P). A total of 130 single-nucleotide polymorphisms (SNPs) in or near SUMO1, MSX1, and TP63 was analyzed among 1,038 Asian NSCL/P trios ascertained through an international consortium. Conditional logistic regression models were used to explore gene-gene (G × G) and gene-environment (G × E) interaction involving maternal environmental tobacco smoke and multivitamin supplementation. Bonferroni correction was used for G × E analysis and permutation tests were used for G × G analysis. While transmission disequilibrium tests and gene-environment interaction analysis showed no significant results, we did find signals of gene-gene interaction between SNPs near MSX1 and TP63. Three pairwise interactions yielded significant p values in permutation tests (rs884690 and rs9290890 with p = 9.34 × 10 -5 and empirical p = 1.00 × 10 -4 , rs1022136 and rs4687098 with p = 2.41 × 10 -4 and empirical p = 2.95 × 10 -4 , rs6819546 and rs9681004 with p = 5.15 × 10 -4 and empirical p = 3.02 × 10 -4 ). Gene-gene interaction between MSX1 and TP63 may influence the risk of NSCL/P in Asian populations. Our study provided additional understanding of the genetic etiology of NSCL/P and underlined the importance of considering gene-gene interaction in the etiology of this common craniofacial malformation. © 2018 Wiley Periodicals, Inc.

Pharmacogenomics of Hypertension and Preeclampsia: Focus on Gene–Gene Interactions

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Marcelo R. Luizon

2018-02-01

Full Text Available Hypertension is a leading cause of cardiovascular mortality, but only about half of patients on antihypertensive therapy achieve blood pressure control. Preeclampsia is defined as pregnancy-induced hypertension and proteinuria, and is associated with increased maternal and perinatal mortality and morbidity. Similarly, a large number of patients with preeclampsia are non-responsive to antihypertensive therapy. Pharmacogenomics may help to guide the personalized treatment for non-responsive hypertensive patients. There is evidence for the association of genetic variants with variable response to the most commonly used antihypertensive drugs. However, further replication is needed to confirm these associations in different populations. The failure to replicate findings from single-locus association studies has prompted the search for novel statistical methods for data analysis, which are required to detect the complex effects from multiple genes to drug response phenotypes. Notably, gene–gene interaction analyses have been applied to pharmacogenetic studies, including antihypertensive drug response. In this perspective article, we present advances of considering the interactions among genetic polymorphisms of different candidate genes within pathways relevant to antihypertensive drug response, and we highlight recent findings related to gene–gene interactions on pharmacogenetics of hypertension and preeclampsia. Finally, we discuss the future directions that are needed to unravel additional genes and variants involved in the responsiveness to antihypertensive drugs.

Gene × Environment Interactions in Schizophrenia: Evidence from Genetic Mouse Models

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Paula Moran

2016-01-01

Full Text Available The study of gene × environment, as well as epistatic interactions in schizophrenia, has provided important insight into the complex etiopathologic basis of schizophrenia. It has also increased our understanding of the role of susceptibility genes in the disorder and is an important consideration as we seek to translate genetic advances into novel antipsychotic treatment targets. This review summarises data arising from research involving the modelling of gene × environment interactions in schizophrenia using preclinical genetic models. Evidence for synergistic effects on the expression of schizophrenia-relevant endophenotypes will be discussed. It is proposed that valid and multifactorial preclinical models are important tools for identifying critical areas, as well as underlying mechanisms, of convergence of genetic and environmental risk factors, and their interaction in schizophrenia.

An Interactive Database of Cocaine-Responsive Gene Expression

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Willard M. Freeman

2002-01-01

Full Text Available The postgenomic era of large-scale gene expression studies is inundating drug abuse researchers and many other scientists with findings related to gene expression. This information is distributed across many different journals, and requires laborious literature searches. Here, we present an interactive database that combines existing information related to cocaine-mediated changes in gene expression in an easy-to-use format. The database is limited to statistically significant changes in mRNA or protein expression after cocaine administration. The Flash-based program is integrated into a Web page, and organizes changes in gene expression based on neuroanatomical region, general function, and gene name. Accompanying each gene is a description of the gene, links to the original publications, and a link to the appropriate OMIM (Online Mendelian Inheritance in Man entry. The nature of this review allows for timely modifications and rapid inclusion of new publications, and should help researchers build second-generation hypotheses on the role of gene expression changes in the physiology and behavior of cocaine abuse. Furthermore, this method of organizing large volumes of scientific information can easily be adapted to assist researchers in fields outside of drug abuse.

A gene-gene interaction between polymorphisms in the OCT2 and MATE1 genes influences the renal clearance of metformin

DEFF Research Database (Denmark)

Hougaard Christensen, Mette Marie; Pedersen, Rasmus Steen; Stage, Tore Bjerregaard

2013-01-01

The aim of this study was to determine the association between the renal clearance (CL(renal)) of metformin in healthy Caucasian volunteers and the single-nucleotide polymorphism (SNP) c.808G>T (rs316019) in OCT2 as well as the relevance of the gene-gene interactions between this SNP and (a) the ...

DNMT1-interacting RNAs block gene specific DNA methylation

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Di Ruscio, Annalisa; Ebralidze, Alexander K.; Benoukraf, Touati; Amabile, Giovanni; Goff, Loyal A.; Terragni, Joylon; Figueroa, Maria Eugenia; De Figureido Pontes, Lorena Lobo; Alberich-Jorda, Meritxell; Zhang, Pu; Wu, Mengchu; D’Alò, Francesco; Melnick, Ari; Leone, Giuseppe; Ebralidze, Konstantin K.; Pradhan, Sriharsa; Rinn, John L.; Tenen, Daniel G.

2013-01-01

Summary DNA methylation was described almost a century ago. However, the rules governing its establishment and maintenance remain elusive. Here, we present data demonstrating that active transcription regulates levels of genomic methylation. We identified a novel RNA arising from the CEBPA gene locus critical in regulating the local DNA methylation profile. This RNA binds to DNMT1 and prevents CEBPA gene locus methylation. Deep sequencing of transcripts associated with DNMT1 combined with genome-scale methylation and expression profiling extended the generality of this finding to numerous gene loci. Collectively, these results delineate the nature of DNMT1-RNA interactions and suggest strategies for gene selective demethylation of therapeutic targets in disease. PMID:24107992

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

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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

Gene-environment interaction: Does fluoride influence the reproductive hormones in male farmers modified by ERα gene polymorphisms?

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Ma, Qiang; Huang, Hui; Sun, Long; Zhou, Tong; Zhu, Jingyuan; Cheng, Xuemin; Duan, Lijv; Li, Zhiyuan; Cui, Liuxin; Ba, Yue

2017-12-01

The occurrence of endemic fluorosis is derived from high fluoride levels in drinking water and industrial fumes or dust. Reproductive disruption is also a major harm caused by fluoride exposure besides dental and skeletal lesions. However, few studies focus on the mechanism of fluoride exposure on male reproductive function, especially the possible interaction of fluoride exposure and gene polymorphism on male reproductive hormones. Therefore, we conducted a cross-sectional study in rural areas of Henan province in China to explore the interaction between the estrogen receptor alpha (ERα) gene and fluoride exposure on reproductive hormone levels in male farmers living in the endemic fluorosis villages. The results showed that fluoride exposure significantly increased the serum level of estradiol in the hypothalamic-pituitary-testicular (HPT) axis in male farmers. Moreover, the observations indicated that fluoride exposure and genetic markers had an interaction on serum concentration of follicle-stimulating hormone and estradiol, and the interaction among different loci of the ERα gene could impact the serum testosterone level. Findings in the present work suggest that chronic fluoride exposure in drinking water could modulate the levels of reproductive hormones in males living in endemic fluorosis areas, and the interaction between fluoride exposure and ERα polymorphisms might affect the serum levels of hormones in the HPT axis in male farmers. Copyright © 2017 Elsevier Ltd. All rights reserved.

Finding gene-environment interactions for Phobias

OpenAIRE

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

2008-01-01

Phobias are common disorders causing a great deal of suffering. Studies of gene-environment interaction (G × 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 × Es for phobias. In addition to the careful concep...

Two-Way Gene Interaction From Microarray Data Based on Correlation Methods.

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Alavi Majd, Hamid; Talebi, Atefeh; Gilany, Kambiz; Khayyer, Nasibeh

2016-06-01

Gene networks have generated a massive explosion in the development of high-throughput techniques for monitoring various aspects of gene activity. Networks offer a natural way to model interactions between genes, and extracting gene network information from high-throughput genomic data is an important and difficult task. The purpose of this study is to construct a two-way gene network based on parametric and nonparametric correlation coefficients. The first step in constructing a Gene Co-expression Network is to score all pairs of gene vectors. The second step is to select a score threshold and connect all gene pairs whose scores exceed this value. In the foundation-application study, we constructed two-way gene networks using nonparametric methods, such as Spearman's rank correlation coefficient and Blomqvist's measure, and compared them with Pearson's correlation coefficient. We surveyed six genes of venous thrombosis disease, made a matrix entry representing the score for the corresponding gene pair, and obtained two-way interactions using Pearson's correlation, Spearman's rank correlation, and Blomqvist's coefficient. Finally, these methods were compared with Cytoscape, based on BIND, and Gene Ontology, based on molecular function visual methods; R software version 3.2 and Bioconductor were used to perform these methods. Based on the Pearson and Spearman correlations, the results were the same and were confirmed by Cytoscape and GO visual methods; however, Blomqvist's coefficient was not confirmed by visual methods. Some results of the correlation coefficients are not the same with visualization. The reason may be due to the small number of data.

Functional modules by relating protein interaction networks and gene expression.

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Tornow, Sabine; Mewes, H W

2003-11-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

Genetic interaction analysis of point mutations enables interrogation of gene function at a residue-level resolution

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Braberg, Hannes; Moehle, Erica A.; Shales, Michael; Guthrie, Christine; Krogan, Nevan J.

2014-01-01

We have achieved a residue-level resolution of genetic interaction mapping – a technique that measures how the function of one gene is affected by the alteration of a second gene – by analyzing point mutations. Here, we describe how to interpret point mutant genetic interactions, and outline key applications for the approach, including interrogation of protein interaction interfaces and active sites, and examination of post-translational modifications. Genetic interaction analysis has proven effective for characterizing cellular processes; however, to date, systematic high-throughput genetic interaction screens have relied on gene deletions or knockdowns, which limits the resolution of gene function analysis and poses problems for multifunctional genes. Our point mutant approach addresses these issues, and further provides a tool for in vivo structure-function analysis that complements traditional biophysical methods. We also discuss the potential for genetic interaction mapping of point mutations in human cells and its application to personalized medicine. PMID:24842270

A novel test for gene-ancestry interactions in genome-wide association data.

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Joanna L Davies

Full Text Available Genome-wide association study (GWAS data on a disease are increasingly available from multiple related populations. In this scenario, meta-analyses can improve power to detect homogeneous genetic associations, but if there exist ancestry-specific effects, via interactions on genetic background or with a causal effect that co-varies with genetic background, then these will typically be obscured. To address this issue, we have developed a robust statistical method for detecting susceptibility gene-ancestry interactions in multi-cohort GWAS based on closely-related populations. We use the leading principal components of the empirical genotype matrix to cluster individuals into "ancestry groups" and then look for evidence of heterogeneous genetic associations with disease or other trait across these clusters. Robustness is improved when there are multiple cohorts, as the signal from true gene-ancestry interactions can then be distinguished from gene-collection artefacts by comparing the observed interaction effect sizes in collection groups relative to ancestry groups. When applied to colorectal cancer, we identified a missense polymorphism in iron-absorption gene CYBRD1 that associated with disease in individuals of English, but not Scottish, ancestry. The association replicated in two additional, independently-collected data sets. Our method can be used to detect associations between genetic variants and disease that have been obscured by population genetic heterogeneity. It can be readily extended to the identification of genetic interactions on other covariates such as measured environmental exposures. We envisage our methodology being of particular interest to researchers with existing GWAS data, as ancestry groups can be easily defined and thus tested for interactions.

Discovering disease-associated genes in weighted protein-protein interaction networks

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Cui, Ying; Cai, Meng; Stanley, H. Eugene

2018-04-01

Although there have been many network-based attempts to discover disease-associated genes, most of them have not taken edge weight - which quantifies their relative strength - into consideration. We use connection weights in a protein-protein interaction (PPI) network to locate disease-related genes. We analyze the topological properties of both weighted and unweighted PPI networks and design an improved random forest classifier to distinguish disease genes from non-disease genes. We use a cross-validation test to confirm that weighted networks are better able to discover disease-associated genes than unweighted networks, which indicates that including link weight in the analysis of network properties provides a better model of complex genotype-phenotype associations.

[Dopamine and excessive alcohol consumption: how genes interact with their environment

NARCIS (Netherlands)

Schellekens, A.F.A.; Scholte, R.H.J.; Engels, R.C.M.E.; Verkes, R.J.

2013-01-01

SUMMARY BACKGROUND: Hereditary factors account for approximately 50% of the risk of developing alcohol dependence. Genes that affect the dopamine function in the brain have been extensively studied as candidate genes. AIM: To present the results of recent Dutch studies on the interaction between

Differential gene expression and Hog1 interaction with osmoresponsive genes in the extremely halotolerant black yeast Hortaea werneckii

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Plemenitaš Ana

2007-08-01

Full Text Available Abstract Background Fluctuations in external salinity force eukaryotic cells to respond by changes in the gene expression of proteins acting in protective biochemical processes, thus counteracting the changing osmotic pressure. The high-osmolarity glycerol (HOG signaling pathway is essential for the efficient up-regulation of the osmoresponsive genes. In this study, the differential gene expression of the extremely halotolerant black yeast Hortaea werneckii was explored. Furthermore, the interaction of mitogen-activated protein kinase HwHog1 and RNA polymerase II with the chromatin in cells adapted to an extremely hypersaline environment was analyzed. Results A cDNA subtraction library was constructed for H. werneckii, adapted to moderate salinity or an extremely hypersaline environment of 4.5 M NaCl. An uncommon osmoresponsive set of 95 differentially expressed genes was identified. The majority of these had not previously been connected with the adaptation of salt-sensitive S. cerevisiae to hypersaline conditions. The transcriptional response in hypersaline-adapted and hypersaline-stressed cells showed that only a subset of the identified genes responded to acute salt-stress, whereas all were differentially expressed in adapted cells. Interaction with HwHog1 was shown for 36 of the 95 differentially expressed genes. The majority of the identified osmoresponsive and HwHog1-dependent genes in H. werneckii have not been previously reported as Hog1-dependent genes in the salt-sensitive S. cerevisiae. The study further demonstrated the co-occupancy of HwHog1 and RNA polymerase II on the chromatin of 17 up-regulated and 2 down-regulated genes in 4.5 M NaCl-adapted H. werneckii cells. Conclusion Extremely halotolerant H. werneckii represents a suitable and highly relevant organism to study cellular responses to environmental salinity. In comparison with the salt-sensitive S. cerevisiae, this yeast shows a different set of genes being expressed at

Bayesian logistic regression in detection of gene-steroid interaction for cancer at PDLIM5 locus.

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Wang, Ke-Sheng; Owusu, Daniel; Pan, Yue; Xie, Changchun

2016-06-01

The PDZ and LIM domain 5 (PDLIM5) gene may play a role in cancer, bipolar disorder, major depression, alcohol dependence and schizophrenia; however, little is known about the interaction effect of steroid and PDLIM5 gene on cancer. This study examined 47 single-nucleotide polymorphisms (SNPs) within the PDLIM5 gene in the Marshfield sample with 716 cancer patients (any diagnosed cancer, excluding minor skin cancer) and 2848 noncancer controls. Multiple logistic regression model in PLINK software was used to examine the association of each SNP with cancer. Bayesian logistic regression in PROC GENMOD in SAS statistical software, ver. 9.4 was used to detect gene- steroid interactions influencing cancer. Single marker analysis using PLINK identified 12 SNPs associated with cancer (Plogistic regression in PROC GENMOD showed that both rs6532496 and rs951613 revealed strong gene-steroid interaction effects (OR=2.18, 95% CI=1.31-3.63 with P = 2.9 × 10⁻³ for rs6532496 and OR=2.07, 95% CI=1.24-3.45 with P = 5.43 × 10⁻³ for rs951613, respectively). Results from Bayesian logistic regression showed stronger interaction effects (OR=2.26, 95% CI=1.2-3.38 for rs6532496 and OR=2.14, 95% CI=1.14-3.2 for rs951613, respectively). All the 12 SNPs associated with cancer revealed significant gene-steroid interaction effects (P logistic regression and OR=2.59, 95% CI=1.4-3.97 from Bayesian logistic regression; respectively). This study provides evidence of common genetic variants within the PDLIM5 gene and interactions between PLDIM5 gene polymorphisms and steroid use influencing cancer.

5C analysis of the Epidermal Differentiation Complex locus reveals distinct chromatin interaction networks between gene-rich and gene-poor TADs in skin epithelial cells.

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Krzysztof Poterlowicz

2017-09-01

Full Text Available 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

Community Structure Analysis of Gene Interaction Networks in Duchenne Muscular Dystrophy.

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Tejaswini Narayanan

Full Text Available Duchenne Muscular Dystrophy (DMD is an important pathology associated with the human skeletal muscle and has been studied extensively. Gene expression measurements on skeletal muscle of patients afflicted with DMD provides the opportunity to understand the underlying mechanisms that lead to the pathology. Community structure analysis is a useful computational technique for understanding and modeling genetic interaction networks. In this paper, we leverage this technique in combination with gene expression measurements from normal and DMD patient skeletal muscle tissue to study the structure of genetic interactions in the context of DMD. We define a novel framework for transforming a raw dataset of gene expression measurements into an interaction network, and subsequently apply algorithms for community structure analysis for the extraction of topological communities. The emergent communities are analyzed from a biological standpoint in terms of their constituent biological pathways, and an interpretation that draws correlations between functional and structural organization of the genetic interactions is presented. We also compare these communities and associated functions in pathology against those in normal human skeletal muscle. In particular, differential enhancements are observed in the following pathways between pathological and normal cases: Metabolic, Focal adhesion, Regulation of actin cytoskeleton and Cell adhesion, and implication of these mechanisms are supported by prior work. Furthermore, our study also includes a gene-level analysis to identify genes that are involved in the coupling between the pathways of interest. We believe that our results serve to highlight important distinguishing features in the structural/functional organization of constituent biological pathways, as it relates to normal and DMD cases, and provide the mechanistic basis for further biological investigations into specific pathways differently regulated

Common sources of bias in gene-lifestyle interaction studies of cardiometabolic disease

DEFF Research Database (Denmark)

Oskari Kilpeläinen, Tuomas

2013-01-01

The role of gene x lifestyle interactions in the development of cardiometabolic diseases is often highlighted, but very few robustly replicated examples of interactions exist in the literature. The slow pace of discoveries may largely be due to interaction effects being generally small in magnitude...

Gene environment interaction studies in depression and suicidal behavior: An update.

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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.

Improving functional modules discovery by enriching interaction networks with gene profiles

KAUST Repository

Salem, Saeed

2013-05-01

Recent advances in proteomic and transcriptomic technologies resulted in the accumulation of vast amount of high-throughput data that span multiple biological processes and characteristics in different organisms. Much of the data come in the form of interaction networks and mRNA expression arrays. An important task in systems biology is functional modules discovery where the goal is to uncover well-connected sub-networks (modules). These discovered modules help to unravel the underlying mechanisms of the observed biological processes. While most of the existing module discovery methods use only the interaction data, in this work we propose, CLARM, which discovers biological modules by incorporating gene profiles data with protein-protein interaction networks. We demonstrate the effectiveness of CLARM on Yeast and Human interaction datasets, and gene expression and molecular function profiles. Experiments on these real datasets show that the CLARM approach is competitive to well established functional module discovery methods.

The SKP1-like gene family of Arabidopsis exhibits a high degree of differential gene expression and gene product interaction during development.

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Mohammad H Dezfulian

Full Text Available The Arabidopsis thaliana genome encodes several families of polypeptides that are known or predicted to participate in the formation of the SCF-class of E3-ubiquitin ligase complexes. One such gene family encodes the Skp1-like class of polypeptide subunits, where 21 genes have been identified and are known to be expressed in Arabidopsis. Phylogenetic analysis based on deduced polypeptide sequence organizes the family of ASK proteins into 7 clades. The complexity of the ASK gene family, together with the close structural similarity among its members raises the prospect of significant functional redundancy among select paralogs. We have assessed the potential for functional redundancy within the ASK gene family by analyzing an expanded set of criteria that define redundancy with higher resolution. The criteria used include quantitative expression of locus-specific transcripts using qRT-PCR, assessment of the sub-cellular localization of individual ASK:YFP auto-fluorescent fusion proteins expressed in vivo as well as the in planta assessment of individual ASK-F-Box protein interactions using bimolecular fluorescent complementation techniques in combination with confocal imagery in live cells. The results indicate significant functional divergence of steady state transcript abundance and protein-protein interaction specificity involving ASK proteins in a pattern that is poorly predicted by sequence-based phylogeny. The information emerging from this and related studies will prove important for defining the functional intersection of expression, localization and gene product interaction that better predicts the formation of discrete SCF complexes, as a prelude to investigating their molecular mode of action.

Association of peroxisome proliferator-activated receptor single-nucleotide polymorphisms and gene-gene interactions with the lipoprotein(a)

Institute of Scientific and Technical Information of China (English)

解惠坚

2014-01-01

Objective To examine the associations of 10 singlenucleotide polymorphisms(SNPs)in peroxisome proliferator-activated receptor(PPARs)gene with lipoprotein(a)level,and to investigate if there is gene-gene interaction among the SNPs on lipoprotein(a)level.Methods Totally 644 subjects(234 men and 410 women)were enrolled from Prevention of Multiple Metabolic Disorders and Metabolic Syndrome Study Cohort,which was an urban community survey study conducted in Jiangsu province.Ten SNPs in PPARα(rs135539,rs4253778,

Genome-wide diet-gene interaction analyses for risk of colorectal cancer.

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Jane C Figueiredo

2014-04-01

Full Text Available Dietary factors, including meat, fruits, vegetables and fiber, are associated with colorectal cancer; however, there is limited information as to whether these dietary factors interact with genetic variants to modify risk of colorectal cancer. We tested interactions between these dietary factors and approximately 2.7 million genetic variants for colorectal cancer risk among 9,287 cases and 9,117 controls from ten studies. We used logistic regression to investigate multiplicative gene-diet interactions, as well as our recently developed Cocktail method that involves a screening step based on marginal associations and gene-diet correlations and a testing step for multiplicative interactions, while correcting for multiple testing using weighted hypothesis testing. Per quartile increment in the intake of red and processed meat were associated with statistically significant increased risks of colorectal cancer and vegetable, fruit and fiber intake with lower risks. From the case-control analysis, we detected a significant interaction between rs4143094 (10p14/near GATA3 and processed meat consumption (OR = 1.17; p = 8.7E-09, which was consistently observed across studies (p heterogeneity = 0.78. The risk of colorectal cancer associated with processed meat was increased among individuals with the rs4143094-TG and -TT genotypes (OR = 1.20 and OR = 1.39, respectively and null among those with the GG genotype (OR = 1.03. Our results identify a novel gene-diet interaction with processed meat for colorectal cancer, highlighting that diet may modify the effect of genetic variants on disease risk, which may have important implications for prevention.

Differential reconstructed gene interaction networks for deriving toxicity threshold in chemical risk assessment.

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Yang, Yi; Maxwell, Andrew; Zhang, Xiaowei; Wang, Nan; Perkins, Edward J; Zhang, Chaoyang; Gong, Ping

2013-01-01

Pathway alterations reflected as changes in gene expression regulation and gene interaction can result from cellular exposure to toxicants. Such information is often used to elucidate toxicological modes of action. From a risk assessment perspective, alterations in biological pathways are a rich resource for setting toxicant thresholds, which may be more sensitive and mechanism-informed than traditional toxicity endpoints. Here we developed a novel differential networks (DNs) approach to connect pathway perturbation with toxicity threshold setting. Our DNs approach consists of 6 steps: time-series gene expression data collection, identification of altered genes, gene interaction network reconstruction, differential edge inference, mapping of genes with differential edges to pathways, and establishment of causal relationships between chemical concentration and perturbed pathways. A one-sample Gaussian process model and a linear regression model were used to identify genes that exhibited significant profile changes across an entire time course and between treatments, respectively. Interaction networks of differentially expressed (DE) genes were reconstructed for different treatments using a state space model and then compared to infer differential edges/interactions. DE genes possessing differential edges were mapped to biological pathways in databases such as KEGG pathways. Using the DNs approach, we analyzed a time-series Escherichia coli live cell gene expression dataset consisting of 4 treatments (control, 10, 100, 1000 mg/L naphthenic acids, NAs) and 18 time points. Through comparison of reconstructed networks and construction of differential networks, 80 genes were identified as DE genes with a significant number of differential edges, and 22 KEGG pathways were altered in a concentration-dependent manner. Some of these pathways were perturbed to a degree as high as 70% even at the lowest exposure concentration, implying a high sensitivity of our DNs approach

Gene-Lifestyle Interactions in Complex Diseases: Design and Description of the GLACIER and VIKING Studies.

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Kurbasic, Azra; Poveda, Alaitz; Chen, Yan; Agren, Asa; Engberg, Elisabeth; Hu, Frank B; Johansson, Ingegerd; Barroso, Ines; Brändström, Anders; Hallmans, Göran; Renström, Frida; Franks, Paul W

2014-12-01

Most complex diseases have well-established genetic and non-genetic risk factors. In some instances, these risk factors are likely to interact, whereby their joint effects convey a level of risk that is either significantly more or less than the sum of these risks. Characterizing these gene-environment interactions may help elucidate the biology of complex diseases, as well as to guide strategies for their targeted prevention. In most cases, the detection of gene-environment interactions will require sample sizes in excess of those needed to detect the marginal effects of the genetic and environmental risk factors. Although many consortia have been formed, comprising multiple diverse cohorts to detect gene-environment interactions, few robust examples of such interactions have been discovered. This may be because combining data across studies, usually through meta-analysis of summary data from the contributing cohorts, is often a statistically inefficient approach for the detection of gene-environment interactions. Ideally, single, very large and well-genotyped prospective cohorts, with validated measures of environmental risk factor and disease outcomes should be used to study interactions. The presence of strong founder effects within those cohorts might further strengthen the capacity to detect novel genetic effects and gene-environment interactions. Access to accurate genealogical data would also aid in studying the diploid nature of the human genome, such as genomic imprinting (parent-of-origin effects). Here we describe two studies from northern Sweden (the GLACIER and VIKING studies) that fulfill these characteristics.

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

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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.

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

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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

Interaction of two photoreceptors in the regulation of bacterial photosynthesis genes.

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Metz, Sebastian; Haberzettl, Kerstin; Frühwirth, Sebastian; Teich, Kristin; Hasewinkel, Christian; Klug, Gabriele

2012-07-01

The expression of photosynthesis genes in the facultatively photosynthetic bacterium Rhodobacter sphaeroides is controlled by the oxygen tension and by light quantity. Two photoreceptor proteins, AppA and CryB, have been identified in the past, which are involved in this regulation. AppA senses light by its N-terminal BLUF domain, its C-terminal part binds heme and is redox-responsive. Through its interaction to the transcriptional repressor PpsR the AppA photoreceptor controls expression of photosynthesis genes. The cryptochrome-like protein CryB was shown to affect regulation of photosynthesis genes, but the underlying signal chain remained unknown. Here we show that CryB interacts with the C-terminal domain of AppA and modulates the binding of AppA to the transcriptional repressor PpsR in a light-dependent manner. Consequently, binding of the transcription factor PpsR to its DNA target is affected by CryB. In agreement with this, all genes of the PpsR regulon showed altered expression levels in a CryB deletion strain after blue-light illumination. These results elucidate for the first time how a bacterial cryptochrome affects gene expression.

Multiple genetic interaction experiments provide complementary information useful for gene function prediction.

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Magali Michaut

Full Text Available Genetic interactions help map biological processes and their functional relationships. A genetic interaction is defined as a deviation from the expected phenotype when combining multiple genetic mutations. In Saccharomyces cerevisiae, most genetic interactions are measured under a single phenotype - growth rate in standard laboratory conditions. Recently genetic interactions have been collected under different phenotypic readouts and experimental conditions. How different are these networks and what can we learn from their differences? We conducted a systematic analysis of quantitative genetic interaction networks in yeast performed under different experimental conditions. We find that networks obtained using different phenotypic readouts, in different conditions and from different laboratories overlap less than expected and provide significant unique information. To exploit this information, we develop a novel method to combine individual genetic interaction data sets and show that the resulting network improves gene function prediction performance, demonstrating that individual networks provide complementary information. Our results support the notion that using diverse phenotypic readouts and experimental conditions will substantially increase the amount of gene function information produced by genetic interaction screens.

Trends in gastrectomy and ADH1B and ALDH2 genotypes in Japanese alcoholic men and their gene-gastrectomy, gene-gene and gene-age interactions for risk of alcoholism.

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Yokoyama, Akira; Yokoyama, Tetsuji; Matsui, Toshifumi; Mizukami, Takeshi; Kimura, Mitsuru; Matsushita, Sachio; Higuchi, Susumu; Maruyama, Katsuya

2013-01-01

The life-time drinking profiles of Japanese alcoholics have shown that gastrectomy increases susceptibility to alcoholism. We investigated the trends in gastrectomy and alcohol dehydrogenase-1B (ADH1B) and aldehyde dehydrogenase-2 (ALDH2) genotypes and their interactions in alcoholics. This survey was conducted on 4879 Japanese alcoholic men 40 years of age or older who underwent routine gastrointestinal endoscopic screening during the period 1996-2010. ADH1B/ALDH2 genotyping was performed in 3702 patients. A history of gastrectomy was found in 508 (10.4%) patients. The reason for the gastrectomy was peptic ulcer in 317 patients and gastric cancer in 187 patients. The frequency of gastrectomy had gradually decreased from 13.3% in 1996-2000 to 10.5% in 2001-2005 and to 7.8% in 2006-2010 (P alcoholism-susceptibility genotypes, ADH1B*1/*1 and ALDH2*1/*1, modestly but significantly tended not to occur in the same individual (P = 0.026). The frequency of ADH1B*1/*1 decreased with ascending age groups. The high frequency of history of gastrectomy suggested that gastrectomy is still a risk factor for alcoholism, although the percentage decreased during the period. The alcoholism-susceptibility genotype ADH1B*1/*1 was less frequent in the gastrectomy group, suggesting a competitive gene-gastrectomy interaction for alcoholism. A gene-gene interaction and gene-age interactions regarding the ADH1B genotype were observed.

Genomewide Expression and Functional Interactions of Genes under Drought Stress in Maize

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Nepolean Thirunavukkarasu

2017-01-01

Full Text Available A genomewide transcriptome assay of two subtropical genotypes of maize was used to observe the expression of genes at seedling stage of drought stress. The number of genes expressed differentially was greater in HKI1532 (a drought tolerant genotype than in PC3 (a drought sensitive genotype, indicating primary differences at the transcriptional level in stress tolerance. The global coexpression networks of the two genotypes differed significantly with respect to the number of modules and the coexpression pattern within the modules. A total of 174 drought-responsive genes were selected from HKI1532, and their coexpression network revealed key correlations between different adaptive pathways, each cluster of the network representing a specific biological function. Transcription factors related to ABA-dependent stomatal closure, signalling, and phosphoprotein cascades work in concert to compensate for reduced photosynthesis. Under stress, water balance was maintained by coexpression of the genes involved in osmotic adjustments and transporter proteins. Metabolism was maintained by the coexpression of genes involved in cell wall modification and protein and lipid metabolism. The interaction of genes involved in crucial biological functions during stress was identified and the results will be useful in targeting important gene interactions to understand drought tolerance in greater detail.

Interactive effects of antioxidant genes and air pollution on respiratory function and airway disease: a HuGE review.

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Minelli, Cosetta; Wei, Igor; Sagoo, Gurdeep; Jarvis, Debbie; Shaheen, Seif; Burney, Peter

2011-03-15

Susceptibility to the respiratory effects of air pollution varies between individuals. Although some evidence suggests higher susceptibility for subjects carrying variants of antioxidant genes, findings from gene-pollution interaction studies conflict in terms of the presence and direction of interactions. The authors conducted a systematic review on antioxidant gene-pollution interactions which included 15 studies, with 12 supporting the presence of interactions. For the glutathione S-transferase M1 gene (GSTM1) (n=10 studies), only 1 study found interaction with the null genotype alone, although 5 observed interactions when GSTM1 was evaluated jointly with other genes (mainly NAD(P)H dehydrogenase [quinone] 1 (NQO1)). All studies on the glutathione S-transferase P1 (GSTP1) Ile105Val polymorphism (n=11) provided some evidence of interaction, but findings conflicted in terms of risk allele. Results were negative for glutathione S-transferase T1 (GSTT1) (n=3) and positive for heme oxygenase 1 (HMOX-1) (n=2). Meta-analysis could not be performed because there were insufficient data available for any specific gene-pollutant-outcome combination. Overall the evidence supports the presence of gene-pollution interactions, although which pollutant interacts with which gene is unclear. However, issues regarding multiple testing, selective reporting, and publication bias raise the possibility of false-positive findings. Larger studies with greater accuracy of pollution assessment and improved quality of conduct and reporting are required. © The Author 2011. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved.

Comparison of information-theoretic to statistical methods for gene-gene interactions in the presence of genetic heterogeneity

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Sucheston Lara

2010-09-01

Full Text Available Abstract Background Multifactorial diseases such as cancer and cardiovascular diseases are caused by the complex interplay between genes and environment. The detection of these interactions remains challenging due to computational limitations. Information theoretic approaches use computationally efficient directed search strategies and thus provide a feasible solution to this problem. However, the power of information theoretic methods for interaction analysis has not been systematically evaluated. In this work, we compare power and Type I error of an information-theoretic approach to existing interaction analysis methods. Methods The k-way interaction information (KWII metric for identifying variable combinations involved in gene-gene interactions (GGI was assessed using several simulated data sets under models of genetic heterogeneity driven by susceptibility increasing loci with varying allele frequency, penetrance values and heritability. The power and proportion of false positives of the KWII was compared to multifactor dimensionality reduction (MDR, restricted partitioning method (RPM and logistic regression. Results The power of the KWII was considerably greater than MDR on all six simulation models examined. For a given disease prevalence at high values of heritability, the power of both RPM and KWII was greater than 95%. For models with low heritability and/or genetic heterogeneity, the power of the KWII was consistently greater than RPM; the improvements in power for the KWII over RPM ranged from 4.7% to 14.2% at for α = 0.001 in the three models at the lowest heritability values examined. KWII performed similar to logistic regression. Conclusions Information theoretic models are flexible and have excellent power to detect GGI under a variety of conditions that characterize complex diseases.

The interaction of BDNF and NTRK2 gene increases the susceptibility of paranoid schizophrenia.

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Zheng Lin

Full Text Available The association between BDNF gene functional Val66Met polymorphism rs6265 and the schizophrenia is far from being consistent. In addition to the heterogeneous in schizophrenia per se leading to the inconsistent results, the interaction among multi-genes is probably playing the main role in the pathogenesis of schizophrenia, but not a single gene. Neurotrophic tyrosine kinase receptor 2 (NTRK2 is the high-affinity receptor of BDNF, and was reported to be associated with mood disorders, though no literature reported the association with schizophrenia. Thus, in the present study, total 402 patients with paranoid schizophrenia (the most common subtype of schizophrenia and matched 406 healthy controls were recruited to investigate the role of rs6265 in BDNF, three polymorphisms in NTRK2 gene (rs1387923, rs2769605 and rs1565445 and their interaction in the susceptibility to paranoid schizophrenia in a Chinese Han population. We did not observe significant differences in allele and genotype frequencies between patients and healthy controls for all four polymorphisms separately. The haplotype analysis also showed no association between haplotype of NTRK2 genes (rs1387923, rs2769605, and rs1565445 and paranoid schizophrenia. However, we found the association between the interaction of BDNF and NTRK2 with paranoid schizophrenia by using the MDR method followed by conventional statistical analysis. The best gene-gene interaction model was a three-locus model (BDNF rs6265, NTRK2 rs1387923 and NTRK2 rs2769605, in which one low-risk and three high-risk four-locus genotype combinations were identified. Our findings implied that single polymorphism of rs6265 rs1387923, rs2769605, and rs1565445 in BDNF and NTRK2 were not associated with the development of paranoid schizophrenia in a Han population, however, the interaction of BDNF and NTRK2 genes polymorphisms (BDNF-rs6265, NTRK2-rs1387923 and NTRK2-rs2769605 may be involved in the susceptibility to paranoid

The interaction of BDNF and NTRK2 gene increases the susceptibility of paranoid schizophrenia.

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Lin, Zheng; Su, Yousong; Zhang, Chengfang; Xing, Mengjuan; Ding, Wenhua; Liao, Liwei; Guan, Yangtai; Li, Zezhi; Cui, Donghong

2013-01-01

The association between BDNF gene functional Val66Met polymorphism rs6265 and the schizophrenia is far from being consistent. In addition to the heterogeneous in schizophrenia per se leading to the inconsistent results, the interaction among multi-genes is probably playing the main role in the pathogenesis of schizophrenia, but not a single gene. Neurotrophic tyrosine kinase receptor 2 (NTRK2) is the high-affinity receptor of BDNF, and was reported to be associated with mood disorders, though no literature reported the association with schizophrenia. Thus, in the present study, total 402 patients with paranoid schizophrenia (the most common subtype of schizophrenia) and matched 406 healthy controls were recruited to investigate the role of rs6265 in BDNF, three polymorphisms in NTRK2 gene (rs1387923, rs2769605 and rs1565445) and their interaction in the susceptibility to paranoid schizophrenia in a Chinese Han population. We did not observe significant differences in allele and genotype frequencies between patients and healthy controls for all four polymorphisms separately. The haplotype analysis also showed no association between haplotype of NTRK2 genes (rs1387923, rs2769605, and rs1565445) and paranoid schizophrenia. However, we found the association between the interaction of BDNF and NTRK2 with paranoid schizophrenia by using the MDR method followed by conventional statistical analysis. The best gene-gene interaction model was a three-locus model (BDNF rs6265, NTRK2 rs1387923 and NTRK2 rs2769605), in which one low-risk and three high-risk four-locus genotype combinations were identified. Our findings implied that single polymorphism of rs6265 rs1387923, rs2769605, and rs1565445 in BDNF and NTRK2 were not associated with the development of paranoid schizophrenia in a Han population, however, the interaction of BDNF and NTRK2 genes polymorphisms (BDNF-rs6265, NTRK2-rs1387923 and NTRK2-rs2769605) may be involved in the susceptibility to paranoid schizophrenia.

Finding gene-environment interactions for phobias.

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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.

HSD3B and gene-gene interactions in a pathway-based analysis of genetic susceptibility to bladder cancer.

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Angeline S Andrew

Full Text Available Bladder cancer is the 4(th most common cancer among men in the U.S. We analyzed variant genotypes hypothesized to modify major biological processes involved in bladder carcinogenesis, including hormone regulation, apoptosis, DNA repair, immune surveillance, metabolism, proliferation, and telomere maintenance. Logistic regression was used to assess the relationship between genetic variation affecting these processes and susceptibility in 563 genotyped urothelial cell carcinoma cases and 863 controls enrolled in a case-control study of incident bladder cancer conducted in New Hampshire, U.S. We evaluated gene-gene interactions using Multifactor Dimensionality Reduction (MDR and Statistical Epistasis Network analysis. The 3'UTR flanking variant form of the hormone regulation gene HSD3B2 was associated with increased bladder cancer risk in the New Hampshire population (adjusted OR 1.85 95%CI 1.31-2.62. This finding was successfully replicated in the Texas Bladder Cancer Study with 957 controls, 497 cases (adjusted OR 3.66 95%CI 1.06-12.63. The effect of this prevalent SNP was stronger among males (OR 2.13 95%CI 1.40-3.25 than females (OR 1.56 95%CI 0.83-2.95, (SNP-gender interaction P = 0.048. We also identified a SNP-SNP interaction between T-cell activation related genes GATA3 and CD81 (interaction P = 0.0003. The fact that bladder cancer incidence is 3-4 times higher in males suggests the involvement of hormone levels. This biologic process-based analysis suggests candidate susceptibility markers and supports the theory that disrupted hormone regulation plays a role in bladder carcinogenesis.

Clustering gene expression data based on predicted differential effects of GV interaction.

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Pan, Hai-Yan; Zhu, Jun; Han, Dan-Fu

2005-02-01

Microarray has become a popular biotechnology in biological and medical research. However, systematic and stochastic variabilities in microarray data are expected and unavoidable, resulting in the problem that the raw measurements have inherent "noise" within microarray experiments. Currently, logarithmic ratios are usually analyzed by various clustering methods directly, which may introduce bias interpretation in identifying groups of genes or samples. In this paper, a statistical method based on mixed model approaches was proposed for microarray data cluster analysis. The underlying rationale of this method is to partition the observed total gene expression level into various variations caused by different factors using an ANOVA model, and to predict the differential effects of GV (gene by variety) interaction using the adjusted unbiased prediction (AUP) method. The predicted GV interaction effects can then be used as the inputs of cluster analysis. We illustrated the application of our method with a gene expression dataset and elucidated the utility of our approach using an external validation.

Multiple Gene-Environment Interactions on the Angiogenesis Gene-Pathway Impact Rectal Cancer Risk and Survival

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Noha Sharafeldin

2017-09-01

Full Text Available Characterization of gene-environment interactions (GEIs in cancer is limited. We aimed at identifying GEIs in rectal cancer focusing on a relevant biologic process involving the angiogenesis pathway and relevant environmental exposures: cigarette smoking, alcohol consumption, and animal protein intake. We analyzed data from 747 rectal cancer cases and 956 controls from the Diet, Activity and Lifestyle as a Risk Factor for Rectal Cancer study. We applied a 3-step analysis approach: first, we searched for interactions among single nucleotide polymorphisms on the pathway genes; second, we searched for interactions among the genes, both steps using Logic regression; third, we examined the GEIs significant at the 5% level using logistic regression for cancer risk and Cox proportional hazards models for survival. Permutation-based test was used for multiple testing adjustment. We identified 8 significant GEIs associated with risk among 6 genes adjusting for multiple testing: TNF (OR = 1.85, 95% CI: 1.10, 3.11, TLR4 (OR = 2.34, 95% CI: 1.38, 3.98, and EGR2 (OR = 2.23, 95% CI: 1.04, 4.78 with smoking; IGF1R (OR = 1.69, 95% CI: 1.04, 2.72, TLR4 (OR = 2.10, 95% CI: 1.22, 3.60 and EGR2 (OR = 2.12, 95% CI: 1.01, 4.46 with alcohol; and PDGFB (OR = 1.75, 95% CI: 1.04, 2.92 and MMP1 (OR = 2.44, 95% CI: 1.24, 4.81 with protein. Five GEIs were associated with survival at the 5% significance level but not after multiple testing adjustment: CXCR1 (HR = 2.06, 95% CI: 1.13, 3.75 with smoking; and KDR (HR = 4.36, 95% CI: 1.62, 11.73, TLR2 (HR = 9.06, 95% CI: 1.14, 72.11, EGR2 (HR = 2.45, 95% CI: 1.42, 4.22, and EGFR (HR = 6.33, 95% CI: 1.95, 20.54 with protein. GEIs between angiogenesis genes and smoking, alcohol, and animal protein impact rectal cancer risk. Our results support the importance of considering the biologic hypothesis to characterize GEIs associated with cancer outcomes.

Gene-environment interaction and male reproductive function

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Axelsson, Jonatan; Bonde, Jens Peter; Giwercman, Yvonne L.; Rylander, Lars; Giwercman, Aleksander

2010-01-01

As genetic factors can hardly explain the changes taking place during short time spans, environmental and lifestyle-related factors have been suggested as the causes of time-related deterioration of male reproductive function. However, considering the strong heterogeneity of male fecundity between and within populations, genetic variants might be important determinants of the individual susceptibility to the adverse effects of environment or lifestyle. Although the possible mechanisms of such interplay in relation to the reproductive system are largely unknown, some recent studies have indicated that specific genotypes may confer a larger risk of male reproductive disorders following certain exposures. This paper presents a critical review of animal and human evidence on how genes may modify environmental effects on male reproductive function. Some examples have been found that support this mechanism, but the number of studies is still limited. This type of interaction studies may improve our understanding of normal physiology and help us to identify the risk factors to male reproductive malfunction. We also shortly discuss other aspects of gene-environment interaction specifically associated with the issue of reproduction, namely environmental and lifestyle factors as the cause of sperm DNA damage. It remains to be investigated to what extent such genetic changes, by natural conception or through the use of assisted reproductive techniques, are transmitted to the next generation, thereby causing increased morbidity in the offspring. PMID:20348940

Topological and organizational properties of the products of house-keeping and tissue-specific genes in protein-protein interaction networks.

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Lin, Wen-Hsien; Liu, Wei-Chung; Hwang, Ming-Jing

2009-03-11

Human cells of various tissue types differ greatly in morphology despite having the same set of genetic information. Some genes are expressed in all cell types to perform house-keeping functions, while some are selectively expressed to perform tissue-specific functions. In this study, we wished to elucidate how proteins encoded by human house-keeping genes and tissue-specific genes are organized in human protein-protein interaction networks. We constructed protein-protein interaction networks for different tissue types using two gene expression datasets and one protein-protein interaction database. We then calculated three network indices of topological importance, the degree, closeness, and betweenness centralities, to measure the network position of proteins encoded by house-keeping and tissue-specific genes, and quantified their local connectivity structure. Compared to a random selection of proteins, house-keeping gene-encoded proteins tended to have a greater number of directly interacting neighbors and occupy network positions in several shortest paths of interaction between protein pairs, whereas tissue-specific gene-encoded proteins did not. In addition, house-keeping gene-encoded proteins tended to connect with other house-keeping gene-encoded proteins in all tissue types, whereas tissue-specific gene-encoded proteins also tended to connect with other tissue-specific gene-encoded proteins, but only in approximately half of the tissue types examined. Our analysis showed that house-keeping gene-encoded proteins tend to occupy important network positions, while those encoded by tissue-specific genes do not. The biological implications of our findings were discussed and we proposed a hypothesis regarding how cells organize their protein tools in protein-protein interaction networks. Our results led us to speculate that house-keeping gene-encoded proteins might form a core in human protein-protein interaction networks, while clusters of tissue-specific gene

Interactions of renin-angiotensin system gene polymorphisms and antihypertensive effect of benazepril in Chinese population.

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Chen, Qing; Yu, Can-Qing; Tang, Xun; Chen, Da-Fang; Tian, Jun; Cao, Yang; Fan, Wen-Yi; Cao, Wei-Hua; Zhan, Si-Yan; Lv, Jun; Guo, Xiao-Xia; Hu, Yong-Hua; Lee, Li-Ming

2011-05-01

Angiotensin-converting enzyme inhibitors are widely used antihypertensive drugs with individual response variation. We studied whether interactions of AGT, AGTR1 and ACE2 gene polymorphisms affect this response. Our study is based on a 3-year field trial with 1831 hypertensive patients prescribed benazepril. Generalized multifactor dimensionality reduction was used to explore interaction models and logistic regressions were used to confirm them. A two-locus model involving the AGT and ACE2 genes was found in males, the sensitive genotypes showed an odds ratio (OR) of 1.9 (95% CI: 1.3-2.8) when compared with nonsensitive genotypes. Two AGT-AGTR1 models were found in females, with an OR of 3.5 (95% CI: 2.0-5.9) and 3.1 (95% CI: 1.8-5.3). Gender-specific gene-gene interactions of the AGT, AGTR1 and ACE2 genes were associated with individual variation of response to benazepril. Further studies are needed to confirm this finding.

Rice-arsenate interactions in hydroponics: a three-gene model for tolerance.

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Norton, Gareth J; Nigar, Meher; Williams, Paul N; Dasgupta, Tapash; Meharg, Andrew A; Price, Adam H

2008-01-01

In this study, the genetic mapping of the tolerance of root growth to 13.3 muM arsenate [As(V)] using the BalaxAzucena population is improved, and candidate genes for further study are identified. A remarkable three-gene model of tolerance is advanced, which appears to involve epistatic interaction between three major genes, two on chromosome 6 and one on chromosome 10. Any combination of two of these genes inherited from the tolerant parent leads to the plant having tolerance. Lists of potential positional candidate genes are presented. These are then refined using whole genome transcriptomics data and bioinformatics. Physiological evidence is also provided that genes related to phosphate transport are unlikely to be behind the genetic loci conferring tolerance. These results offer testable hypotheses for genes related to As(V) tolerance that might offer strategies for mitigating arsenic (As) accumulation in consumed rice.

Rice–arsenate interactions in hydroponics: a three-gene model for tolerance

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Norton, Gareth J.; Nigar, Meher; Dasgupta, Tapash; Meharg, Andrew A.; Price, Adam H.

2008-01-01

In this study, the genetic mapping of the tolerance of root growth to 13.3 μM arsenate [As(V)] using the Bala×Azucena population is improved, and candidate genes for further study are identified. A remarkable three-gene model of tolerance is advanced, which appears to involve epistatic interaction between three major genes, two on chromosome 6 and one on chromosome 10. Any combination of two of these genes inherited from the tolerant parent leads to the plant having tolerance. Lists of potential positional candidate genes are presented. These are then refined using whole genome transcriptomics data and bioinformatics. Physiological evidence is also provided that genes related to phosphate transport are unlikely to be behind the genetic loci conferring tolerance. These results offer testable hypotheses for genes related to As(V) tolerance that might offer strategies for mitigating arsenic (As) accumulation in consumed rice. PMID:18453529

Gene-diet-interactions in folate-mediated one-carbon metabolism modify colon cancer risk.

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Liu, Amy Y; Scherer, Dominique; Poole, Elizabeth; Potter, John D; Curtin, Karen; Makar, Karen; Slattery, Martha L; Caan, Bette J; Ulrich, Cornelia M

2013-04-01

The importance of folate-mediated one-carbon metabolism (FOCM) in colorectal carcinogenesis is emphasized by observations that high dietary folate intake is associated with decreased risk of colon cancer (CC) and its precursors. Additionally, polymorphisms in FOCM-related genes have been repeatedly associated with risk, supporting a causal relationship between folate and colorectal carcinogenesis. We investigated ten candidate polymorphisms with defined or probable functional impact in eight FOCM-related genes (SHMT1, DHFR, DNMT1, MTHFD1, MTHFR, MTRR, TCN2, and TDG) in 1609 CC cases and 1974 controls for association with CC risk and for interaction with dietary factors. No polymorphism was statistically significantly associated with overall risk of CC. However, statistically significant interactions modifying CC risk were observed for DNMT1 I311V with dietary folate, methionine, vitamin B2 , and vitamin B12 intake and for MTRR I22M with dietary folate, a predefined one-carbon dietary pattern, and vitamin B6 intake. We observed statistically significant gene-diet interactions with five additional polymorphisms. Our results provide evidence that FOCM-related dietary intakes modify the association between CC risk and FOCM allelic variants. These findings add to observations showing that folate-related gene-nutrient interactions play an important role in modifying the risk of CC. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Global map of physical interactions among differentially expressed genes in multiple sclerosis relapses and remissions.

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Tuller, Tamir; Atar, Shimshi; Ruppin, Eytan; Gurevich, Michael; Achiron, Anat

2011-09-15

Multiple sclerosis (MS) is a central nervous system autoimmune inflammatory T-cell-mediated disease with a relapsing-remitting course in the majority of patients. In this study, we performed a high-resolution systems biology analysis of gene expression and physical interactions in MS relapse and remission. To this end, we integrated 164 large-scale measurements of gene expression in peripheral blood mononuclear cells of MS patients in relapse or remission and healthy subjects, with large-scale information about the physical interactions between these genes obtained from public databases. These data were analyzed with a variety of computational methods. We find that there is a clear and significant global network-level signal that is related to the changes in gene expression of MS patients in comparison to healthy subjects. However, despite the clear differences in the clinical symptoms of MS patients in relapse versus remission, the network level signal is weaker when comparing patients in these two stages of the disease. This result suggests that most of the genes have relatively similar expression levels in the two stages of the disease. In accordance with previous studies, we found that the pathways related to regulation of cell death, chemotaxis and inflammatory response are differentially expressed in the disease in comparison to healthy subjects, while pathways related to cell adhesion, cell migration and cell-cell signaling are activated in relapse in comparison to remission. However, the current study includes a detailed report of the exact set of genes involved in these pathways and the interactions between them. For example, we found that the genes TP53 and IL1 are 'network-hub' that interacts with many of the differentially expressed genes in MS patients versus healthy subjects, and the epidermal growth factor receptor is a 'network-hub' in the case of MS patients with relapse versus remission. The statistical approaches employed in this study enabled us

Clock genes × stress × reward interactions in alcohol and substance use disorders.

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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.

Systemic virus-induced gene silencing allows functional characterization of maize genes during biotrophic interaction with Ustilago maydis.

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van der Linde, Karina; Kastner, Christine; Kumlehn, Jochen; Kahmann, Regine; Doehlemann, Gunther

2011-01-01

Infection of maize (Zea mays) plants with the corn smut fungus Ustilago maydis leads to the formation of large tumors on the stem, leaves and inflorescences. In this biotrophic interaction, plant defense responses are actively suppressed by the pathogen, and previous transcriptome analyses of infected maize plants showed massive and stage-specific changes in host gene expression during disease progression. To identify maize genes that are functionally involved in the interaction with U. maydis, we adapted a virus-induced gene silencing (VIGS) system based on the brome mosaic virus (BMV) for maize. Conditions were established that allowed successful U. maydis infection of BMV-preinfected maize plants. This set-up enabled quantification of VIGS and its impact on U. maydis infection using a quantitative real-time PCR (qRT-PCR)-based readout. In proof-of-principle experiments, an U. maydis-induced terpene synthase was shown to negatively regulate disease development while a protein involved in cell death inhibition was required for full virulence of U. maydis. The results suggest that this system is a versatile tool for the rapid identification of maize genes that determine compatibility with U. maydis. © (2010) Max Planck Society. Journal compilation © New Phytologist Trust (2010).

Modeling Gene-Environment Interactions With Quasi-Natural Experiments.

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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.

Genetic interaction motif finding by expectation maximization – a novel statistical model for inferring gene modules from synthetic lethality

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Ye Ping

2005-12-01

Full Text Available Abstract Background Synthetic lethality experiments identify pairs of genes with complementary function. More direct functional associations (for example greater probability of membership in a single protein complex may be inferred between genes that share synthetic lethal interaction partners than genes that are directly synthetic lethal. Probabilistic algorithms that identify gene modules based on motif discovery are highly appropriate for the analysis of synthetic lethal genetic interaction data and have great potential in integrative analysis of heterogeneous datasets. Results We have developed Genetic Interaction Motif Finding (GIMF, an algorithm for unsupervised motif discovery from synthetic lethal interaction data. Interaction motifs are characterized by position weight matrices and optimized through expectation maximization. Given a seed gene, GIMF performs a nonlinear transform on the input genetic interaction data and automatically assigns genes to the motif or non-motif category. We demonstrate the capacity to extract known and novel pathways for Saccharomyces cerevisiae (budding yeast. Annotations suggested for several uncharacterized genes are supported by recent experimental evidence. GIMF is efficient in computation, requires no training and automatically down-weights promiscuous genes with high degrees. Conclusion GIMF effectively identifies pathways from synthetic lethality data with several unique features. It is mostly suitable for building gene modules around seed genes. Optimal choice of one single model parameter allows construction of gene networks with different levels of confidence. The impact of hub genes the generic probabilistic framework of GIMF may be used to group other types of biological entities such as proteins based on stochastic motifs. Analysis of the strongest motifs discovered by the algorithm indicates that synthetic lethal interactions are depleted between genes within a motif, suggesting that synthetic

Pharmacogenetics of drug-drug interaction and drug-drug-gene interaction: a systematic review on CYP2C9, CYP2C19 and CYP2D6.

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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.

Gene-environment interaction involving recently identified colorectal cancer susceptibility loci

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Kantor, Elizabeth D.; Hutter, Carolyn M.; Minnier, Jessica; Berndt, Sonja I.; Brenner, Hermann; Caan, Bette J.; Campbell, Peter T.; Carlson, Christopher S.; Casey, Graham; Chan, Andrew T.; Chang-Claude, Jenny; Chanock, Stephen J.; Cotterchio, Michelle; Du, Mengmeng; Duggan, David; Fuchs, Charles S.; Giovannucci, Edward L.; Gong, Jian; Harrison, Tabitha A.; Hayes, Richard B.; Henderson, Brian E.; Hoffmeister, Michael; Hopper, John L.; Jenkins, Mark A.; Jiao, Shuo; Kolonel, Laurence N.; Le Marchand, Loic; Lemire, Mathieu; Ma, Jing; Newcomb, Polly A.; Ochs-Balcom, Heather M.; Pflugeisen, Bethann M.; Potter, John D.; Rudolph, Anja; Schoen, Robert E.; Seminara, Daniela; Slattery, Martha L.; Stelling, Deanna L.; Thomas, Fridtjof; Thornquist, Mark; Ulrich, Cornelia M.; Warnick, Greg S.; Zanke, Brent W.; Peters, Ulrike; Hsu, Li; White, Emily

2014-01-01

BACKGROUND Genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) that are associated with risk of colorectal cancer (CRC). Prior research has evaluated the presence of gene-environment interaction involving the first 10 identified susceptibility loci, but little work has been conducted on interaction involving SNPs at recently identified susceptibility loci, including: rs10911251, rs6691170, rs6687758, rs11903757, rs10936599, rs647161, rs1321311, rs719725, rs1665650, rs3824999, rs7136702, rs11169552, rs59336, rs3217810, rs4925386, and rs2423279. METHODS Data on 9160 cases and 9280 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and Colon Cancer Family Registry (CCFR) were used to evaluate the presence of interaction involving the above-listed SNPs and sex, body mass index (BMI), alcohol consumption, smoking, aspirin use, post-menopausal hormone (PMH) use, as well as intake of dietary calcium, dietary fiber, dietary folate, red meat, processed meat, fruit, and vegetables. Interaction was evaluated using a fixed-effects meta-analysis of an efficient Empirical Bayes estimator, and permutation was used to account for multiple comparisons. RESULTS None of the permutation-adjusted p-values reached statistical significance. CONCLUSIONS The associations between recently identified genetic susceptibility loci and CRC are not strongly modified by sex, BMI, alcohol, smoking, aspirin, PMH use, and various dietary factors. IMPACT Results suggest no evidence of strong gene-environment interactions involving the recently identified 16 susceptibility loci for CRC taken one at a time. PMID:24994789

Gene-Diet Interaction and Precision Nutrition in Obesity

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Yoriko Heianza

2017-04-01

Full Text Available The rapid rise of obesity during the past decades has coincided with a profound shift of our living environment, including unhealthy dietary patterns, a sedentary lifestyle, and physical inactivity. Genetic predisposition to obesity may have interacted with such an obesogenic environment in determining the obesity epidemic. Growing studies have found that changes in adiposity and metabolic response to low-calorie weight loss diets might be modified by genetic variants related to obesity, metabolic status and preference to nutrients. This review summarized data from recent studies of gene-diet interactions, and discussed integration of research of metabolomics and gut microbiome, as well as potential application of the findings in precision nutrition.

Dynamic changes in the interchromosomal interaction of early histone gene loci during development of sea urchin.

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Matsushita, Masaya; Ochiai, Hiroshi; Suzuki, Ken-Ichi T; Hayashi, Sayaka; Yamamoto, Takashi; Awazu, Akinori; Sakamoto, Naoaki

2017-12-15

The nuclear positioning and chromatin dynamics of eukaryotic genes are closely related to the regulation of gene expression, but they have not been well examined during early development, which is accompanied by rapid cell cycle progression and dynamic changes in nuclear organization, such as nuclear size and chromatin constitution. In this study, we focused on the early development of the sea urchin Hemicentrotus pulcherrimus and performed three-dimensional fluorescence in situ hybridization of gene loci encoding early histones (one of the types of histone in sea urchin). There are two non-allelic early histone gene loci per sea urchin genome. We found that during the morula stage, when the early histone gene expression levels are at their maximum, interchromosomal interactions were often formed between the early histone gene loci on separate chromosomes and that the gene loci were directed to locate to more interior positions. Furthermore, these interactions were associated with the active transcription of the early histone genes. Thus, such dynamic interchromosomal interactions may contribute to the efficient synthesis of early histone mRNA during the morula stage of sea urchin development. © 2017. Published by The Company of Biologists Ltd.

Diet-gene interactions between dietary fat intake and common polymorphisms in determining lipid metabolism

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Corella, Dolores

2009-03-01

Full Text Available Current dietary guidelines for fat intake have not taken into consideration the possible genetic differences underlying the individual variability in responsiveness to dietary components. Genetic variability has been identified in humans for all the known lipid metabolim-related genes resulting in a plethora of candidate genes and genetic variants to examine in diet-gene interaction studies focused on fat consumption. Some examples of fat-gene interaction are reviewed. These include: the interaction between total intake and the 514C/T in the hepatic lipase gene promoter in determining high-density lipoprotein cholesterol (HDL-C metabolism; the interaction between polyunsaturated fatty acids (PUFA and the 75G/A polymorphism in the APOA1 gene plasma HDL-C concentrations; the interaction between PUFA and the L162V polymorphism in the PPARA gene in determining triglycerides and APOC3 concentrations; and the interaction between PUFA intake and the 1131TC in the APOA5 gene in determining triglyceride metabolism. Although hundreds of diet-gene interaction studies in lipid metabolism have been published, the level of evidence to make specific nutritional recommendations to the population is still low and more research in nutrigenetics has to be undertaken.Las recomendaciones dietéticas actuales referentes al consumo de grasas en la dieta han sido realizadas sin tener en cuenta las posibles diferencias genéticas de las personas que podrían ser las responsables de las diferentes respuestas interindividuales que frecuentemente se observan ante la misma dieta. La presencia de variabilidad genética ha sido puesta de manifiesto para todos los genes relacionados con el metabolismo lipídico, por lo que existe un ingente número de genes y de variantes genéticas para ser incluidas en los estudios sobre interacciones dieta-genotipo en el ámbito específico del consumo de grasas y aceites. Se revisarán algunos ejemplos sobre interacciones grasa

Distilling a Visual Network of Retinitis Pigmentosa Gene-Protein Interactions to Uncover New Disease Candidates.

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Daniel Boloc

Full Text Available Retinitis pigmentosa (RP is a highly heterogeneous genetic visual disorder with more than 70 known causative genes, some of them shared with other non-syndromic retinal dystrophies (e.g. Leber congenital amaurosis, LCA. The identification of RP genes has increased steadily during the last decade, and the 30% of the cases that still remain unassigned will soon decrease after the advent of exome/genome sequencing. A considerable amount of genetic and functional data on single RD genes and mutations has been gathered, but a comprehensive view of the RP genes and their interacting partners is still very fragmentary. This is the main gap that needs to be filled in order to understand how mutations relate to progressive blinding disorders and devise effective therapies.We have built an RP-specific network (RPGeNet by merging data from different sources: high-throughput data from BioGRID and STRING databases, manually curated data for interactions retrieved from iHOP, as well as interactions filtered out by syntactical parsing from up-to-date abstracts and full-text papers related to the RP research field. The paths emerging when known RP genes were used as baits over the whole interactome have been analysed, and the minimal number of connections among the RP genes and their close neighbors were distilled in order to simplify the search space.In contrast to the analysis of single isolated genes, finding the networks linking disease genes renders powerful etiopathological insights. We here provide an interactive interface, RPGeNet, for the molecular biologist to explore the network centered on the non-syndromic and syndromic RP and LCA causative genes. By integrating tissue-specific expression levels and phenotypic data on top of that network, a more comprehensive biological view will highlight key molecular players of retinal degeneration and unveil new RP disease candidates.

Gene interactions in the DNA damage-response pathway identified by genome-wide RNA-interference analysis of synthetic lethality

NARCIS (Netherlands)

van Haaften, Gijs; Vastenhouw, Nadine L; Nollen, Ellen A A; Plasterk, Ronald H A; Tijsterman, Marcel

2004-01-01

Here, we describe a systematic search for synthetic gene interactions in a multicellular organism, the nematode Caenorhabditis elegans. We established a high-throughput method to determine synthetic gene interactions by genome-wide RNA interference and identified genes that are required to protect

Gene-Diet Interactions in Type 2 Diabetes: The Chicken and Egg Debate

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Ortega, Ángeles; Berná, Genoveva; Rojas, Anabel; Martín, Franz; Soria, Bernat

2017-01-01

Consistent evidence from both experimental and human studies indicates that Type 2 diabetes mellitus (T2DM) is a complex disease resulting from the interaction of genetic, epigenetic, environmental, and lifestyle factors. Nutrients and dietary patterns are important environmental factors to consider in the prevention, development and treatment of this disease. Nutritional genomics focuses on the interaction between bioactive food components and the genome and includes studies of nutrigenetics, nutrigenomics and epigenetic modifications caused by nutrients. There is evidence supporting the existence of nutrient-gene and T2DM interactions coming from animal studies and family-based intervention studies. Moreover, many case-control, cohort, cross-sectional cohort studies and clinical trials have identified relationships between individual genetic load, diet and T2DM. Some of these studies were on a large scale. In addition, studies with animal models and human observational studies, in different countries over periods of time, support a causative relationship between adverse nutritional conditions during in utero development, persistent epigenetic changes and T2DM. This review provides comprehensive information on the current state of nutrient-gene interactions and their role in T2DM pathogenesis, the relationship between individual genetic load and diet, and the importance of epigenetic factors in influencing gene expression and defining the individual risk of T2DM. PMID:28574454

Representing virus-host interactions and other multi-organism processes in the Gene Ontology.

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Foulger, R E; Osumi-Sutherland, D; McIntosh, B K; Hulo, C; Masson, P; Poux, S; Le Mercier, P; Lomax, J

2015-07-28

The Gene Ontology project is a collaborative effort to provide descriptions of gene products in a consistent and computable language, and in a species-independent manner. The Gene Ontology is designed to be applicable to all organisms but up to now has been largely under-utilized for prokaryotes and viruses, in part because of a lack of appropriate ontology terms. To address this issue, we have developed a set of Gene Ontology classes that are applicable to microbes and their hosts, improving both coverage and quality in this area of the Gene Ontology. Describing microbial and viral gene products brings with it the additional challenge of capturing both the host and the microbe. Recognising this, we have worked closely with annotation groups to test and optimize the GO classes, and we describe here a set of annotation guidelines that allow the controlled description of two interacting organisms. Building on the microbial resources already in existence such as ViralZone, UniProtKB keywords and MeGO, this project provides an integrated ontology to describe interactions between microbial species and their hosts, with mappings to the external resources above. Housing this information within the freely-accessible Gene Ontology project allows the classes and annotation structure to be utilized by a large community of biologists and users.

Disease candidate gene identification and prioritization using protein interaction networks

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Aronow Bruce J

2009-02-01

Full Text Available Abstract Background Although most of the current disease candidate gene identification and prioritization methods depend on functional annotations, the coverage of the gene functional annotations is a limiting factor. In the current study, we describe a candidate gene prioritization method that is entirely based on protein-protein interaction network (PPIN analyses. Results For the first time, extended versions of the PageRank and HITS algorithms, and the K-Step Markov method are applied to prioritize disease candidate genes in a training-test schema. Using a list of known disease-related genes from our earlier study as a training set ("seeds", and the rest of the known genes as a test list, we perform large-scale cross validation to rank the candidate genes and also evaluate and compare the performance of our approach. Under appropriate settings – for example, a back probability of 0.3 for PageRank with Priors and HITS with Priors, and step size 6 for K-Step Markov method – the three methods achieved a comparable AUC value, suggesting a similar performance. Conclusion Even though network-based methods are generally not as effective as integrated functional annotation-based methods for disease candidate gene prioritization, in a one-to-one comparison, PPIN-based candidate gene prioritization performs better than all other gene features or annotations. Additionally, we demonstrate that methods used for studying both social and Web networks can be successfully used for disease candidate gene prioritization.

Gene-environment interaction and behavioral disorders: a developmental perspective based on endophenotypes.

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Battaglia, Marco; Marino, Cecilia; Maziade, Michel; Molteni, Massimo; D'Amato, Francesca

2008-01-01

It has been observed that 'No aspect of human behavioral genetics has caused more confusion and generated more obscurantism than the analysis and interpretation of various types of non-additivity and non-independence of gene and environmental action and interaction' (Eaves LJ et al 1977 Br J Math Stat Psychol 30:1-42). On the other hand, a bulk of newly published studies appear to speak in favour of common and frequent interplay--and possibly interaction--between identified genetic polymorphisms and specified environmental variables in shaping behavior and behavioral disorders. Considerable interest has arisen from the introduction of putative functional 'endophenotypes' which would represent a more proximate biological link to genes, as well as an obligatory intermediate of behavior. While explicit criteria to identify valid endophenotypes have been offered, a number of new 'alternative phenotypes' are now being proposed as possible 'endophenotypes' for behavioral and psychiatric genetics research, sometimes with less than optimal stringency. Nonetheless, we suggest that some endophenotypes can be helpful in investigating several instances of gene-environment interactions and be employed as additional tools to reduce the risk for spurious results in this controversial area.

Inference of gene-phenotype associations via protein-protein interaction and orthology.

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Panwen Wang

Full Text Available One of the fundamental goals of genetics is to understand gene functions and their associated phenotypes. To achieve this goal, in this study we developed a computational algorithm that uses orthology and protein-protein interaction information to infer gene-phenotype associations for multiple species. Furthermore, we developed a web server that provides genome-wide phenotype inference for six species: fly, human, mouse, worm, yeast, and zebrafish. We evaluated our inference method by comparing the inferred results with known gene-phenotype associations. The high Area Under the Curve values suggest a significant performance of our method. By applying our method to two human representative diseases, Type 2 Diabetes and Breast Cancer, we demonstrated that our method is able to identify related Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The web server can be used to infer functions and putative phenotypes of a gene along with the candidate genes of a phenotype, and thus aids in disease candidate gene discovery. Our web server is available at http://jjwanglab.org/PhenoPPIOrth.

Animal model for schizophrenia that reflects gene-environment interactions.

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Nagai, Taku; Ibi, Daisuke; Yamada, Kiyofumi

2011-01-01

Schizophrenia is a devastating psychiatric disorder that impairs mental and social functioning and affects approximately 1% of the population worldwide. Genetic susceptibility factors for schizophrenia have recently been reported, some of which are known to play a role in neurodevelopment; these include neuregulin-1, dysbindin, and disrupted-in-schizophrenia 1 (DISC1). Moreover, epidemiologic studies suggest that environmental insults, such as prenatal infection and perinatal complication, are involved in the development of schizophrenia. The possible interaction between environment and genetic susceptibility factors, especially during neurodevelopment, is proposed as a promising disease etiology of schizophrenia. Polyriboinosinic-polyribocytidilic acid (polyI : C) is a synthetic analogue of double-stranded RNA that leads to the pronounced but time-limited production of pro-inflammatory cytokines. Maternal immune activation by polyI : C exposure in rodents is known to precipitate a wide spectrum of behavioral, cognitive, and pharmacological abnormalities in adult offspring. Recently, we have reported that neonatal injection of polyI : C in mice results in schizophrenia-like behavioral alterations in adulthood. In this review, we show how gene-environment interactions during neurodevelopment result in phenotypic changes in adulthood by injecting polyI : C into transgenic mice that express a dominant-negative form of human DISC1 (DN-DISC1). Our findings suggest that polyI : C-treated DN-DISC1 mice are a well-validated animal model for schizophrenia that reflects gene-environment interactions.

GENIE: a software package for gene-gene interaction analysis in genetic association studies using multiple GPU or CPU cores

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Wang Kai

2011-05-01

Full Text Available Abstract Background Gene-gene interaction in genetic association studies is computationally intensive when a large number of SNPs are involved. Most of the latest Central Processing Units (CPUs have multiple cores, whereas Graphics Processing Units (GPUs also have hundreds of cores and have been recently used to implement faster scientific software. However, currently there are no genetic analysis software packages that allow users to fully utilize the computing power of these multi-core devices for genetic interaction analysis for binary traits. Findings Here we present a novel software package GENIE, which utilizes the power of multiple GPU or CPU processor cores to parallelize the interaction analysis. GENIE reads an entire genetic association study dataset into memory and partitions the dataset into fragments with non-overlapping sets of SNPs. For each fragment, GENIE analyzes: 1 the interaction of SNPs within it in parallel, and 2 the interaction between the SNPs of the current fragment and other fragments in parallel. We tested GENIE on a large-scale candidate gene study on high-density lipoprotein cholesterol. Using an NVIDIA Tesla C1060 graphics card, the GPU mode of GENIE achieves a speedup of 27 times over its single-core CPU mode run. Conclusions GENIE is open-source, economical, user-friendly, and scalable. Since the computing power and memory capacity of graphics cards are increasing rapidly while their cost is going down, we anticipate that GENIE will achieve greater speedups with faster GPU cards. Documentation, source code, and precompiled binaries can be downloaded from http://www.cceb.upenn.edu/~mli/software/GENIE/.

Mapping of Wnt-Frizzled interactions by multiplex CRISPR targeting of receptor gene families.

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Voloshanenko, Oksana; Gmach, Philipp; Winter, Jan; Kranz, Dominique; Boutros, Michael

2017-11-01

Signaling pathway modules are often encoded by several closely related paralogous genes that can have redundant roles and are therefore difficult to analyze by loss-of-function analysis. A typical example is the Wnt signaling pathway, which in mammals is mediated by 19 Wnt ligands that can bind to 10 Frizzled (FZD) receptors. Although significant progress in understanding Wnt-FZD receptor interactions has been made in recent years, tools to generate systematic interaction maps have been largely lacking. Here we generated cell lines with multiplex mutant alleles of FZD1 , FZD2 , and FZD7 and demonstrate that these cells are unresponsive to canonical Wnt ligands. Subsequently, we performed genetic rescue experiments with combinations of FZDs and canonical Wnts to create a functional ligand-receptor interaction map. These experiments showed that whereas several Wnt ligands, such as Wnt3a, induce signaling through a broad spectrum of FZD receptors, others, such as Wnt8a, act through a restricted set of FZD genes. Together, our results map functional interactions of FZDs and 10 Wnt ligands and demonstrate how multiplex targeting by clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 can be used to systematically elucidate the functions of multigene families.-Voloshanenko, O., Gmach, P., Winter, J., Kranz, D., Boutros, M. Mapping of Wnt-Frizzled interactions by multiplex CRISPR targeting of receptor gene families. © The Author(s).

Early life adversity and serotonin transporter gene variation interact to affect DNA methylation of the corticotropin-releasing factor gene promoter region in the adult rat brain

NARCIS (Netherlands)

Doelen, R.H.A. van der; Arnoldussen, I.A.C.; Ghareh, H.; Och, L. van; Homberg, J.R.; Kozicz, L.T.

2015-01-01

The interaction between childhood maltreatment and the serotonin transporter (5-HTT) gene linked polymorphic region has been associated with increased risk to develop major depression. This Gene x Environment interaction has furthermore been linked with increased levels of anxiety and glucocorticoid

Overview of diet-gene interactions and the example of xanthophylls.

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Demmig-Adams, Barbara; Adams, William W

2010-01-01

This chapter provides an overview of diet-gene interaction and the role of dietary factors in human health and disease. Human master control genes that regulate processes of fundamental importance, such as cell proliferation and the immune response, are introduced and their modulation by nutraceuticals, produced by plants and photosynthetic microbes, is reviewed. Emphasis is placed on antioxidants and polyunsaturated fatty acids as regulators of master control genes. Furthermore, a case study is presented on xanthophylls, a group of carotenoids with multiple health benefits in the protection against eye disease and other chronic diseases, as well as the synergism between xanthophylls and other dietary factors. Lastly, dietary sources of the xanthophylls zeaxanthin and lutein are reviewed and their enhancement via genetic engineering is discussed.

The Interaction of TXNIP and AFq1 Genes Increases the Susceptibility of Schizophrenia.

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Su, Yousong; Ding, Wenhua; Xing, Mengjuan; Qi, Dake; Li, Zezhi; Cui, Donghong

2017-08-01

Although previous studies showed the reduced risk of cancer in patients with schizophrenia, whether patients with schizophrenia possess genetic factors that also contribute to tumor suppressor is still unknown. In the present study, based on our previous microarray data, we focused on the tumor suppressor genes TXNIP and AF1q, which differentially expressed in patients with schizophrenia. A total of 413 patients and 578 healthy controls were recruited. We found no significant differences in genotype, allele, or haplotype frequencies at the selected five single nucleotide polymorphisms (SNPs) (rs2236566 and rs7211 in TXNIP gene; rs10749659, rs2140709, and rs3738481 in AF1q gene) between patients with schizophrenia and controls. However, we found the association between the interaction of TXNIP and AF1q with schizophrenia by using the MDR method followed by traditional statistical analysis. The best gene-gene interaction model identified was a three-locus model TXNIP (rs2236566, rs7211)-AF1q (rs2140709). After traditional statistical analysis, we found the high-risk genotype combination was rs2236566 (GG)-rs7211(CC)-rs2140709(CC) (OR = 1.35 [1.03-1.76]). The low-risk genotype combination was rs2236566 (GT)-rs7211(CC)-rs2140709(CC) (OR = 0.67 [0.49-0.91]). Our finding suggested statistically significant role of interaction of TXNIP and AF1q polymorphisms (TXNIP-rs2236566, TXNIP-rs7211, and AF1q-rs2769605) in schizophrenia susceptibility.

Gene-Environment Interactions in Genome-Wide Association Studies: Current Approaches and New Directions

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Winham, Stacey J.; Biernacka, Joanna M.

2013-01-01

Background: Complex psychiatric traits have long been thought to be the result of a combination of genetic and environmental factors, and gene-environment interactions are thought to play a crucial role in behavioral phenotypes and the susceptibility and progression of psychiatric disorders. Candidate gene studies to investigate hypothesized…

In vivo protein-DNA interactions at the β-globin gene locus

International Nuclear Information System (INIS)

Tohru Ikuta; Yuet Wai Kan

1991-01-01

The authors have investigated in vivo protein-DNA interactions in the β-globin gene locus by dimethyl sulfate (DMS) footprinting in K562 cells, which express var-epsilon- and γ-globin but not β-globin. In the locus control region, hypersensitive site 2 (HS-2) exhibited footprints in several putative protein binding motifs. HS-3 was not footprinted. The β promoter was also not footprinted, while extensive footprints were observed in the promoter of the active γ-globin gene. No footprints were seen in the A γ and β3' enhancers. With several motifs, additional protein interactions and alterations in binding patterns occurred with hemin induction. In HeLa cells, some footprints were observed in some of the motifs in HS-2, compatible with the finding that HS-2 has some enhancer function in HeLa cells, albeit much weaker than its activity in K562 cells. No footprint was seen in B lymphocytes. In vivo footprinting is a useful method for studying relevant protein-DNA interactions in erythroid cells

Improving functional modules discovery by enriching interaction networks with gene profiles

KAUST Repository

Salem, Saeed; Alroobi, Rami; Banitaan, Shadi; Seridi, Loqmane; Aljarah, Ibrahim; Brewer, James

2013-01-01

networks. We demonstrate the effectiveness of CLARM on Yeast and Human interaction datasets, and gene expression and molecular function profiles. Experiments on these real datasets show that the CLARM approach is competitive to well established functional

Influenza NA and PB1 Gene Segments Interact during the Formation of Viral Progeny: Localization of the Binding Region within the PB1 Gene

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Brad Gilbertson

2016-08-01

Full Text Available The influenza A virus genome comprises eight negative-sense viral RNAs (vRNAs that form individual ribonucleoprotein (RNP complexes. In order to incorporate a complete set of each of these vRNAs, the virus uses a selective packaging mechanism that facilitates co-packaging of specific gene segments but whose molecular basis is still not fully understood. Recently, we used a competitive transfection model where plasmids encoding the A/Puerto Rico/8/34 (PR8 and A/Udorn/307/72 (Udorn PB1 gene segments were competed to show that the Udorn PB1 gene segment is preferentially co-packaged into progeny virions with the Udorn NA gene segment. Here we created chimeric PB1 genes combining both Udorn and PR8 PB1 sequences to further define the location within the Udorn PB1 gene that drives co-segregation of these genes and show that nucleotides 1776–2070 of the PB1 gene are crucial for preferential selection. In vitro assays examining specific interactions between Udorn NA vRNA and purified vRNAs transcribed from chimeric PB1 genes also supported the importance of this region in the PB1-NA interaction. Hence, this work identifies an association between viral genes that are co-selected during packaging. It also reveals a region potentially important in the RNP-RNP interactions within the supramolecular complex that is predicted to form prior to budding to allow one of each segment to be packaged in the viral progeny. Our study lays the foundation to understand the co-selection of specific genes, which may be critical to the emergence of new viruses with pandemic potential.

A double-mutant collection targeting MAP kinase related genes in Arabidopsis for studying genetic interactions.

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Su, Shih-Heng; Krysan, Patrick J

2016-12-01

Mitogen-activated protein kinase cascades are conserved in all eukaryotes. In Arabidopsis thaliana there are approximately 80 genes encoding MAP kinase kinase kinases (MAP3K), 10 genes encoding MAP kinase kinases (MAP2K), and 20 genes encoding MAP kinases (MAPK). Reverse genetic analysis has failed to reveal abnormal phenotypes for a majority of these genes. One strategy for uncovering gene function when single-mutant lines do not produce an informative phenotype is to perform a systematic genetic interaction screen whereby double-mutants are created from a large library of single-mutant lines. Here we describe a new collection of 275 double-mutant lines derived from a library of single-mutants targeting genes related to MAP kinase signaling. To facilitate this study, we developed a high-throughput double-mutant generating pipeline using a system for growing Arabidopsis seedlings in 96-well plates. A quantitative root growth assay was used to screen for evidence of genetic interactions in this double-mutant collection. Our screen revealed four genetic interactions, all of which caused synthetic enhancement of the root growth defects observed in a MAP kinase 4 (MPK4) single-mutant line. Seeds for this double-mutant collection are publicly available through the Arabidopsis Biological Resource Center. Scientists interested in diverse biological processes can now screen this double-mutant collection under a wide range of growth conditions in order to search for additional genetic interactions that may provide new insights into MAP kinase signaling. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.

Prediction of the Ebola Virus Infection Related Human Genes Using Protein-Protein Interaction Network.

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Cao, HuanHuan; Zhang, YuHang; Zhao, Jia; Zhu, Liucun; Wang, Yi; Li, JiaRui; Feng, Yuan-Ming; Zhang, Ning

2017-01-01

Ebola hemorrhagic fever (EHF) is caused by Ebola virus (EBOV). It is reported that human could be infected by EBOV with a high fatality rate. However, association factors between EBOV and host still tend to be ambiguous. According to the "guilt by association" (GBA) principle, proteins interacting with each other are very likely to function similarly or the same. Based on this assumption, we tried to obtain EBOV infection-related human genes in a protein-protein interaction network using Dijkstra algorithm. We hope it could contribute to the discovery of novel effective treatments. Finally, 15 genes were selected as potential EBOV infection-related human genes. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Attachment style and oxytocin receptor gene variation interact in influencing social anxiety.

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Notzon, S; Domschke, K; Holitschke, K; Ziegler, C; Arolt, V; Pauli, P; Reif, A; Deckert, J; Zwanzger, P

2016-01-01

Social anxiety has been suggested to be promoted by an insecure attachment style. Oxytocin is discussed as a mediator of trust and social bonding as well as a modulator of social anxiety. Applying a gene-environment (G × E) interaction approach, in the present pilot study the main and interactive effects of attachment styles and oxytocin receptor (OXTR) gene variation were probed in a combined risk factor model of social anxiety in healthy probands. Participants (N = 388; 219 females, 169 males; age 24.7 ± 4.7 years) were assessed for anxiety in social situations (Social Phobia and Anxiety Inventory) depending on attachment style (Adult Attachment Scale, AAS) and OXTR rs53576 A/G genotype. A less secure attachment style was significantly associated with higher social anxiety. This association was partly modulated by OXTR genotype, with a stronger negative influence of a less secure attachment style on social anxiety in A allele carriers as compared to GG homozygotes. The present pilot data point to a strong association of less secure attachment and social anxiety as well as to a gene-environment interaction effect of OXTR rs53576 genotype and attachment style on social anxiety possibly constituting a targetable combined risk marker of social anxiety disorder.

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

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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

Genome-wide gene-environment study identifies glutamate receptor gene GRIN2A as a Parkinson's disease modifier gene via interaction with coffee.

OpenAIRE

Taye H Hamza; Honglei Chen; Erin M Hill-Burns; Shannon L Rhodes; Jennifer Montimurro; Denise M Kay; Albert Tenesa; Victoria I Kusel; Patricia Sheehan; Muthukrishnan Eaaswarkhanth; Dora Yearout; Ali Samii; John W Roberts; Pinky Agarwal; Yvette Bordelon

2011-01-01

Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal compo...

Interaction between LRP5 and periostin gene polymorphisms on serum periostin levels and cortical bone microstructure.

Science.gov (United States)

Pepe, J; Bonnet, N; Herrmann, F R; Biver, E; Rizzoli, R; Chevalley, T; Ferrari, S L

2018-02-01

We investigated the interaction between periostin SNPs and the SNPs of the genes assumed to modulate serum periostin levels and bone microstructure in a cohort of postmenopausal women. We identified an interaction between LRP5 SNP rs648438 and periostin SNP rs9547970 on serum periostin levels and on radial cortical porosity. The purpose of this study is to investigate the interaction between periostin gene polymorphisms (SNPs) and other genes potentially responsible for modulating serum periostin levels and bone microstructure in a cohort of postmenopausal women. In 648 postmenopausal women from the Geneva Retirees Cohort, we analyzed 6 periostin SNPs and another 149 SNPs in 14 genes, namely BMP2, CTNNB1, ESR1, ESR2, LRP5, LRP6, PTH, SPTBN1, SOST, TGFb1, TNFRSF11A, TNFSF11, TNFRSF11B and WNT16. Volumetric BMD and bone microstructure were measured by high-resolution peripheral quantitative computed tomography at the distal radius and tibia. Serum periostin levels were associated with radial cortical porosity, including after adjustment for age, BMI, and years since menopause (p = 0.036). Sixteen SNPs in the ESR1, LRP5, TNFRSF11A, SOST, SPTBN1, TNFRSF11B and TNFSF11 genes were associated with serum periostin levels (p range 0.03-0.001) whereas 26 SNPs in 9 genes were associated with cortical porosity at the radius and/or at the tibia. WNT 16 was the gene with the highest number of SNPs associated with both trabecular and cortical microstructure. The periostin SNP rs9547970 was also associated with cortical porosity (p = 0.04). In particular, SNPs in LRP5, ESR1 and near the TNFRSF11A gene were associated with both cortical porosity and serum periostin levels. Eventually, we identified an interaction between LRP5 SNP rs648438 and periostin SNP rs9547970 on serum periostin levels (interaction p = 0.01) and on radial cortical porosity (interaction p = 0.005). These results suggest that periostin expression is genetically modulated, particularly by polymorphisms

The influence of nutrigenetics on the lipid profile: interaction between genes and dietary habits.

Science.gov (United States)

de Andrade, Fabiana M; Bulhões, Andréa C; Maluf, Sharbel W; Schuch, Jaqueline B; Voigt, Francine; Lucatelli, Juliana F; Barros, Alessandra C; Hutz, Mara H

2010-04-01

Nutrigenetics is a new field with few studies in Latin America. Our aim is to investigate the way in which different genes related to the lipid profile influence the response to specific dietary habits. Eight polymorphisms on seven genes were investigated in a sample (n = 567) from Porto Alegre, RS, Brazil. All the volunteers completed a food diary that was then assessed and classified into nine food groups. A number of nutrigenetic interactions were detected primarily related to the apolipoprotein E (apoE) gene. For example, frequent consumption of foods rich in polyunsaturated fat resulted in the beneficial effect of increasing HDL-C only in individuals who were not carriers of the E*4 allele of the APOE gene, whereas variations in eating habits of E*4 carriers did not affect their HDL-C (P = 0.018). Our data demonstrate for the first time nutrigenetic interactions in a Brazilian population.

Radioresistance related genes screened by protein-protein interaction network analysis in nasopharyngeal carcinoma

International Nuclear Information System (INIS)

Zhu Xiaodong; Guo Ya; Qu Song; Li Ling; Huang Shiting; Li Danrong; Zhang Wei

2012-01-01

Objective: To discover radioresistance associated molecular biomarkers and its mechanism in nasopharyngeal carcinoma by protein-protein interaction network analysis. Methods: Whole genome expression microarray was applied to screen out differentially expressed genes in two cell lines CNE-2R and CNE-2 with different radiosensitivity. Four differentially expressed genes were randomly selected for further verification by the semi-quantitative RT-PCR analysis with self-designed primers. The common differentially expressed genes from two experiments were analyzed with the SNOW online database in order to find out the central node related to the biomarkers of nasopharyngeal carcinoma radioresistance. The expression of STAT1 in CNE-2R and CNE-2 cells was measured by Western blot. Results: Compared with CNE-2 cells, 374 genes in CNE-2R cells were differentially expressed while 197 genes showed significant differences. Four randomly selected differentially expressed genes were verified by RT-PCR and had same change trend in consistent with the results of chip assay. Analysis with the SNOW database demonstrated that those 197 genes could form a complicated interaction network where STAT1 and JUN might be two key nodes. Indeed, the STAT1-α expression in CNE-2R was higher than that in CNE-2 (t=4.96, P<0.05). Conclusions: The key nodes of STAT1 and JUN may be the molecular biomarkers leading to radioresistance in nasopharyngeal carcinoma, and STAT1-α might have close relationship with radioresistance. (authors)

Impact of Maspin Polymorphism rs2289520 G/C and Its Interaction with Gene to Gene, Alcohol Consumption Increase Susceptibility to Oral Cancer Occurrence.

Science.gov (United States)

Yang, Po-Yu; Miao, Nae-Fang; Lin, Chiao-Wen; Chou, Ying-Erh; Yang, Shun-Fa; Huang, Hui-Chuan; Chang, Hsiu-Ju; Tsai, Hsiu-Ting

2016-01-01

The purpose of this study was to identify gene polymorphisms of mammary serine protease inhibitor (Maspin) specific to patients with oral cancer susceptibility and clinicopathological status. Three single-nucleotide polymorphisms (SNPs) of the Maspin gene from 741 patients with oral cancer and 601 non-cancer controls were analyzed by real-time PCR. The participants with G/G homozygotes or with G/C heterozygotes of Maspin rs2289520 polymorphism had a 2.07-fold (p = 0.01) and a 2.01-fold (p = 0.02) risk of developing oral cancer compared to those with C/C homozygotes. Moreover, gene-gene interaction increased the risk of oral cancer susceptibility among subjects expose to oral cancer related risk factors, including areca, alcohol, and tobacco consumption. G allele of Maspin rs2289520 polymorphism may be a factor that increases the susceptibility to oral cancer. The interactions of gene to oral cancer-related environmental risk factors have a synergetic effect that can further enhance oral cancer development.

Gene-particulate matter-health interactions

International Nuclear Information System (INIS)

Kleeberger, Steven R.; Ohtsuka, Yoshinori

2005-01-01

Inter-individual variation in human responses to air pollutants suggests that some subpopulations are at increased risk to the detrimental effects of pollutant exposure. Extrinsic factors such as previous exposure and nutritional status may influence individual susceptibility. Intrinsic (host) factors that determine susceptibility include age, gender, and pre-existing disease (e.g., asthma), and it is becoming clear that genetic background also contributes to individual susceptibility. Environmental exposures to particulates and genetic factors associated with disease risk likely interact in a complex fashion that varies from one population and one individual to another. The relationships between genetic background and disease risk and severity are often evaluated through traditional family-based linkage studies and positional cloning techniques. However, case-control studies based on association of disease or disease subphenotypes with candidate genes have advantages over family pedigree studies for complex disease phenotypes. This is based in part on continued development of quantitative analysis and the discovery and availability of simple sequence repeats and single nucleotide polymorphisms. Linkage analyses with genetically standardized animal models also provide a useful tool to identify genetic determinants of responses to environmental pollutants. These approaches have identified significant susceptibility quantitative trait loci on mouse chromosomes 1, 6, 11, and 17. Physical mapping and comparative mapping between human and mouse genomes will yield candidate susceptibility genes that may be tested by association studies in human subjects. Human studies and mouse modeling will provide important insight to understanding genetic factors that contribute to differential susceptibility to air pollutants

Lack of evidence for intermolecular epistatic interactions between adiponectin and resistin gene polymorphisms in Malaysian male subjects

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Cia-Hin Lau

2012-01-01

Full Text Available Epistasis (gene-gene interaction is a ubiquitous component of the genetic architecture of complex traits such as susceptibility to common human diseases. Given the strong negative correlation between circulating adiponectin and resistin levels, the potential intermolecular epistatic interactions between ADIPOQ (SNP+45T > G, SNP+276G > T, SNP+639T > C and SNP+1212A > G and RETN (SNP-420C > G and SNP+299G > A gene polymorphisms in the genetic risk underlying type 2 diabetes (T2DM and metabolic syndrome (MS were assessed. The potential mutual influence of the ADIPOQ and RETN genes on their adipokine levels was also examined. The rare homozygous genotype (risk alleles of SNP-420C > G at the RETN locus tended to be co-inherited together with the common homozygous genotypes (protective alleles of SNP+639T > C and SNP+1212A > G at the ADIPOQ locus. Despite the close structural relationship between the ADIPOQ and RETN genes, there was no evidence of an intermolecular epistatic interaction between these genes. There was also no reciprocal effect of the ADIPOQ and RETN genes on their adipokine levels, i.e., ADIPOQ did not affect resistin levels nor did RETN affect adiponectin levels. The possible influence of the ADIPOQ gene on RETN expression warrants further investigation.

Arabidopsis mRNA polyadenylation machinery: comprehensive analysis of protein-protein interactions and gene expression profiling

Directory of Open Access Journals (Sweden)

Mo Min

2008-05-01

Full Text Available Abstract Background The polyadenylation of mRNA is one of the critical processing steps during expression of almost all eukaryotic genes. It is tightly integrated with transcription, particularly its termination, as well as other RNA processing events, i.e. capping and splicing. The poly(A tail protects the mRNA from unregulated degradation, and it is required for nuclear export and translation initiation. In recent years, it has been demonstrated that the polyadenylation process is also involved in the regulation of gene expression. The polyadenylation process requires two components, the cis-elements on the mRNA and a group of protein factors that recognize the cis-elements and produce the poly(A tail. Here we report a comprehensive pairwise protein-protein interaction mapping and gene expression profiling of the mRNA polyadenylation protein machinery in Arabidopsis. Results By protein sequence homology search using human and yeast polyadenylation factors, we identified 28 proteins that may be components of Arabidopsis polyadenylation machinery. To elucidate the protein network and their functions, we first tested their protein-protein interaction profiles. Out of 320 pair-wise protein-protein interaction assays done using the yeast two-hybrid system, 56 (~17% showed positive interactions. 15 of these interactions were further tested, and all were confirmed by co-immunoprecipitation and/or in vitro co-purification. These interactions organize into three distinct hubs involving the Arabidopsis polyadenylation factors. These hubs are centered around AtCPSF100, AtCLPS, and AtFIPS. The first two are similar to complexes seen in mammals, while the third one stands out as unique to plants. When comparing the gene expression profiles extracted from publicly available microarray datasets, some of the polyadenylation related genes showed tissue-specific expression, suggestive of potential different polyadenylation complex configurations. Conclusion An

Interactions between the FTO and GNB3 genes contribute to varied clinical phenotypes in hypertension.

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Rahul Kumar

Full Text Available The genes FTO and GNB3 are implicated in essential hypertension but their interaction remains to be explored. This study investigates the role of interaction between the two genes in the pathophysiology of essential hypertension.In a case-control study comprising 750 controls and 550 patients, interaction between the polymorphisms of FTO and GNB3 was examined using multifactor dimensionality reduction (MDR. The influence of interaction on clinical phenotypes like systolic and diastolic blood pressure, mean arterial pressure and body mass index was also investigated. The 3-locus MDR model comprising FTO rs8050136C/A and GNB3 rs1129649T/C and rs5443C/T emerged as the best disease conferring model. Moreover, the interacted-genotypes having either 1, 2, 3, 4 or 5 risk alleles correlated with linearly increasing odds ratios of 1.91 (P = 0.027; 3.93 (P = 2.08E-06; 4.51 (P = 7.63E-07; 7.44 (P = 3.66E-08 and 11.57 (P = 1.18E-05, respectively, when compared with interacted-genotypes devoid of risk alleles. Furthermore, interactions among haplotypes of FTO (H1-9 and GNB3 (Ha-d differed by >1.5-fold for protective-haplotypes, CTGGC+TC [H2+Ha] and CTGAC+TC [H4+Ha] (OR = 0.39, P = 0.003; OR = 0.22, P = 6.86E-05, respectively and risk-haplotypes, AAAGC+CT [H3+Hc] and AAAGC+TT [H3+Hd] (OR = 2.91, P = 9.98E-06; OR = 2.50, P = 0.004, respectively compared to individual haplotypes. Moreover, the effectiveness of gene-gene interaction was further corroborated with a 1.29-, 1.25- and 1.38-fold higher SBP, MAP and BMI, respectively, in patients having risk interacted-haplotype H3+Hc and 2.48-fold higher SBP having risk interacted-haplotype H3+Hd compared to individual haplotypes.Interactions between genetic variants of FTO and GNB3 influence clinical parameters to augment hypertension.

Gene Environment Interactions and Predictors of Colorectal Cancer in Family-Based, Multi-Ethnic Groups.

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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 relation to gene-environment interactions in the prevention of CRC.

Interactions between Bmp-4 and Msx-1 act to restrict gene expression to odontogenic mesenchyme.

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Tucker, A S; Al Khamis, A; Sharpe, P T

1998-08-01

Tooth development is regulated by a reciprocal series of epithelial-mesenchymal interactions. Bmp4 has been identified as a candidate signalling molecule in these interactions, initially as an epithelial signal and then later at the bud stage as a mesenchymal signal (Vainio et al. [1993] Cell 75:45-58). A target gene for Bmp4 signalling is the homeobox gene Msx-1, identified by the ability of recombinant Bmp4 protein to induce expression in mesenchyme. There is, however, no evidence that Bmp4 is the endogenous inducer of Msx-1 expression. Msx-1 and Bmp-4 show dynamic, interactive patterns of expression in oral epithelium and ectomesenchyme during the early stages of tooth development. In this study, we compare the temporal and spatial expression of these two genes to determine whether the changing expression patterns of these genes are consistent with interactions between the two molecules. We show that changes in Bmp-4 expression precede changes in Msx-1 expression. At embryonic day (E)10.5-E11.0, expression patterns are consistent with BMP4 from the epithelium, inducing or maintaining Msx-1 in underlying mesenchyme. At E11.5, Bmp-4 expression shifts from epithelium to mesenchyme and is rapidly followed by localised up-regulation of Msx-1 expression at the sites of Bmp-4 expression. Using cultured explants of developing mandibles, we confirm that exogenous BMP4 is capable of replacing the endogenous source in epithelium and inducing Msx-1 gene expression in mesenchyme. By using noggin, a BMP inhibitor, we show that endogenous Msx-1 expression can be inhibited at E10.5 and E11.5, providing the first evidence that endogenous Bmp-4 from the epithelium is responsible for regulating the early spatial expression of Msx-1. We also show that the mesenchymal shift in Bmp-4 is responsible for up-regulating Msx-1 specifically at the sites of future tooth formation. Thus, we establish that a reciprocal series of interactions act to restrict expression of both genes to future

Gene Environment Interactions and Predictors of Colorectal Cancer in Family-Based, Multi-Ethnic Groups

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S. Pamela K. Shiao

2018-02-01

Full Text Available 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.

Genes related to antioxidant metabolism are involved in Methylobacterium mesophilicum-soybean interaction.

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Araújo, Welington Luiz; Santos, Daiene Souza; Dini-Andreote, Francisco; Salgueiro-Londoño, Jennifer Katherine; Camargo-Neves, Aline Aparecida; Andreote, Fernando Dini; Dourado, Manuella Nóbrega

2015-10-01

The genus Methylobacterium is composed of pink-pigmented methylotrophic bacterial species that are widespread in natural environments, such as soils, stream water and plants. When in association with plants, this genus colonizes the host plant epiphytically and/or endophytically. This association is known to promote plant growth, induce plant systemic resistance and inhibit plant infection by phytopathogens. In the present study, we focused on evaluating the colonization of soybean seedling-roots by Methylobacterium mesophilicum strain SR1.6/6. We focused on the identification of the key genes involved in the initial step of soybean colonization by methylotrophic bacteria, which includes the plant exudate recognition and adaptation by planktonic bacteria. Visualization by scanning electron microscopy revealed that M. mesophilicum SR1.6/6 colonizes soybean roots surface effectively at 48 h after inoculation, suggesting a mechanism for root recognition and adaptation before this period. The colonization proceeds by the development of a mature biofilm on roots at 96 h after inoculation. Transcriptomic analysis of the planktonic bacteria (with plant) revealed the expression of several genes involved in membrane transport, thus confirming an initial metabolic activation of bacterial responses when in the presence of plant root exudates. Moreover, antioxidant genes were mostly expressed during the interaction with the plant exudates. Further evaluation of stress- and methylotrophic-related genes expression by qPCR showed that glutathione peroxidase and glutathione synthetase genes were up-regulated during the Methylobacterium-soybean interaction. These findings support that glutathione (GSH) is potentially a key molecule involved in cellular detoxification during plant root colonization. In addition to methylotrophic metabolism, antioxidant genes, mainly glutathione-related genes, play a key role during soybean exudate recognition and adaptation, the first step in

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

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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.

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

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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 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

PREFACE: Physics approaches to protein interactions and gene regulation Physics approaches to protein interactions and gene regulation

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Nussinov, Ruth; Panchenko, Anna R.; Przytycka, Teresa

2011-06-01

networks have been identified, including scale free distribution of the vertex degree, network motifs, and modularity, to name a few. These studies of network organization require the network to be as complete as possible, which given the limitations of experimental techniques is not currently the case. Therefore, experimental procedures for detecting biomolecular interactions should be complemented by computational approaches. The paper by Lees et al provides a review of computational methods, integrating multiple independent sources of data to infer physical and functional protein-protein interaction networks. One of the important aspects of protein interactions that should be accounted for in the prediction of protein interaction networks is that many proteins are composed of distinct domains. Protein domains may mediate protein interactions while proteins and their interaction networks may gain complexity through gene duplication and expansion of existing domain architectures via domain rearrangements. The latter mechanisms have been explored in detail in the paper by Cohen-Gihon et al. Protein-protein interactions are not the only component of the cell's interactome. Regulation of cell activity can be achieved at the level of transcription and involve a transcription factor—DNA binding which typically requires recognition of a specific DNA sequence motif. Chip-Chip and the more recent Chip-Seq technologies allow in vivo identification of DNA binding sites and, together with novel in vitro approaches, provide data necessary for deciphering the corresponding binding motifs. Such information, complemented by structures of protein-DNA complexes and knowledge of the differences in binding sites among homologs, opens the door to constructing predictive binding models. The paper by Persikov and Singh provides an example of such a model in the Cys2His2 zinc finger family. Recent studies have indicated that the presence of such binding motifs is, however, neither necessary

A modifier screen for Bazooka/PAR-3 interacting genes in the Drosophila embryo epithelium.

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Wei Shao

2010-04-01

Full Text Available The development and homeostasis of multicellular organisms depends on sheets of epithelial cells. Bazooka (Baz; PAR-3 localizes to the apical circumference of epithelial cells and is a key hub in the protein interaction network regulating epithelial structure. We sought to identify additional proteins that function with Baz to regulate epithelial structure in the Drosophila embryo.The baz zygotic mutant cuticle phenotype could be dominantly enhanced by loss of known interaction partners. To identify additional enhancers, we screened molecularly defined chromosome 2 and 3 deficiencies. 37 deficiencies acted as strong dominant enhancers. Using deficiency mapping, bioinformatics, and available single gene mutations, we identified 17 interacting genes encoding known and predicted polarity, cytoskeletal, transmembrane, trafficking and signaling proteins. For each gene, their loss of function enhanced adherens junction defects in zygotic baz mutants during early embryogenesis. To further evaluate involvement in epithelial polarity, we generated GFP fusion proteins for 15 of the genes which had not been found to localize to the apical domain previously. We found that GFP fusion proteins for Drosophila ASAP, Arf79F, CG11210, Septin 5 and Sds22 could be recruited to the apical circumference of epithelial cells. Nine of the other proteins showed various intracellular distributions, and one was not detected.Our enhancer screen identified 17 genes that function with Baz to regulate epithelial structure in the Drosophila embryo. Our secondary localization screen indicated that some of the proteins may affect epithelial cell polarity by acting at the apical cell cortex while others may act through intracellular processes. For 13 of the 17 genes, this is the first report of a link to baz or the regulation of epithelial structure.

Shame and Guilt-Proneness in Adolescents: Gene-Environment Interactions.

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Szentágotai-Tătar, Aurora; Chiș, Adina; Vulturar, Romana; Dobrean, Anca; Cândea, Diana Mirela; Miu, Andrei C

2015-01-01

Rooted in people's preoccupation with how they are perceived and evaluated, shame and guilt are self-conscious emotions that play adaptive roles in social behavior, but can also contribute to psychopathology when dysregulated. Shame and guilt-proneness develop during childhood and adolescence, and are influenced by genetic and environmental factors that are little known to date. This study investigated the effects of early traumatic events and functional polymorphisms in the brain-derived neurotrophic factor (BDNF) gene and the serotonin transporter gene promoter (5-HTTLPR) on shame and guilt in adolescents. A sample of N = 271 healthy adolescents between 14 and 17 years of age filled in measures of early traumatic events and proneness to shame and guilt, and were genotyped for the BDNF Val66Met and 5-HTTLPR polymorphisms. Results of moderator analyses indicated that trauma intensity was positively associated with guilt-proneness only in carriers of the low-expressing Met allele of BDNF Val66Met. This is the first study that identifies a gene-environment interaction that significantly contributes to guilt proneness in adolescents, with potential implications for developmental psychopathology.

Protein-Protein Interaction Network and Gene Ontology

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Choi, Yunkyu; Kim, Seok; Yi, Gwan-Su; Park, Jinah

Evolution of computer technologies makes it possible to access a large amount and various kinds of biological data via internet such as DNA sequences, proteomics data and information discovered about them. It is expected that the combination of various data could help researchers find further knowledge about them. Roles of a visualization system are to invoke human abilities to integrate information and to recognize certain patterns in the data. Thus, when the various kinds of data are examined and analyzed manually, an effective visualization system is an essential part. One instance of these integrated visualizations can be combination of protein-protein interaction (PPI) data and Gene Ontology (GO) which could help enhance the analysis of PPI network. We introduce a simple but comprehensive visualization system that integrates GO and PPI data where GO and PPI graphs are visualized side-by-side and supports quick reference functions between them. Furthermore, the proposed system provides several interactive visualization methods for efficiently analyzing the PPI network and GO directedacyclic- graph such as context-based browsing and common ancestors finding.

Using phylogenetically-informed annotation (PIA) to search for light-interacting genes in transcriptomes from non-model organisms.

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Speiser, Daniel I; Pankey, M Sabrina; Zaharoff, Alexander K; Battelle, Barbara A; Bracken-Grissom, Heather D; Breinholt, Jesse W; Bybee, Seth M; Cronin, Thomas W; Garm, Anders; Lindgren, Annie R; Patel, Nipam H; Porter, Megan L; Protas, Meredith E; Rivera, Ajna S; Serb, Jeanne M; Zigler, Kirk S; Crandall, Keith A; Oakley, Todd H

2014-11-19

Tools for high throughput sequencing and de novo assembly make the analysis of transcriptomes (i.e. the suite of genes expressed in a tissue) feasible for almost any organism. Yet a challenge for biologists is that it can be difficult to assign identities to gene sequences, especially from non-model organisms. Phylogenetic analyses are one useful method for assigning identities to these sequences, but such methods tend to be time-consuming because of the need to re-calculate trees for every gene of interest and each time a new data set is analyzed. In response, we employed existing tools for phylogenetic analysis to produce a computationally efficient, tree-based approach for annotating transcriptomes or new genomes that we term Phylogenetically-Informed Annotation (PIA), which places uncharacterized genes into pre-calculated phylogenies of gene families. We generated maximum likelihood trees for 109 genes from a Light Interaction Toolkit (LIT), a collection of genes that underlie the function or development of light-interacting structures in metazoans. To do so, we searched protein sequences predicted from 29 fully-sequenced genomes and built trees using tools for phylogenetic analysis in the Osiris package of Galaxy (an open-source workflow management system). Next, to rapidly annotate transcriptomes from organisms that lack sequenced genomes, we repurposed a maximum likelihood-based Evolutionary Placement Algorithm (implemented in RAxML) to place sequences of potential LIT genes on to our pre-calculated gene trees. Finally, we implemented PIA in Galaxy and used it to search for LIT genes in 28 newly-sequenced transcriptomes from the light-interacting tissues of a range of cephalopod mollusks, arthropods, and cubozoan cnidarians. Our new trees for LIT genes are available on the Bitbucket public repository ( http://bitbucket.org/osiris_phylogenetics/pia/ ) and we demonstrate PIA on a publicly-accessible web server ( http://galaxy-dev.cnsi.ucsb.edu/pia/ ). Our new

Interactions between SNPs affecting inflammatory response genes are associated with multiple myeloma disease risk and survival

DEFF Research Database (Denmark)

Nielsen, Kaspar René; Rodrigo-Domingo, Maria; Steffensen, Rudi

2017-01-01

The origin of multiple myeloma depends on interactions with stromal cells in the course of normal B-cell differentiation and evolution of immunity. The concept of the present study is that genes involved in MM pathogenesis, such as immune response genes, can be identified by screening for single......3L1 gene promoters. The occurrence of single polymorphisms, haplotypes and SNP-SNP interactions were statistically analyzed for association with disease risk and outcome following high-dose therapy. Identified genes that carried SNPs or haplotypes that were identified as risk or prognostic factors......= .005). The 'risk genes' were analyzed for expression in normal B-cell subsets (N = 6) from seven healthy donors and we found TNFA and IL-6 expressed both in naïve and in memory B cells when compared to preBI, II, immature and plasma cells. The 'prognosis genes' CHI3L1, IL-6 and IL-10 were differential...

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

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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.

The properties of genome conformation and spatial gene interaction and regulation networks of normal and malignant human cell types.

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Zheng Wang

Full Text Available The spatial conformation of a genome plays an important role in the long-range regulation of genome-wide gene expression and methylation, but has not been extensively studied due to lack of genome conformation data. The recently developed chromosome conformation capturing techniques such as the Hi-C method empowered by next generation sequencing can generate unbiased, large-scale, high-resolution chromosomal interaction (contact data, providing an unprecedented opportunity to investigate the spatial structure of a genome and its applications in gene regulation, genomics, epigenetics, and cell biology. In this work, we conducted a comprehensive, large-scale computational analysis of this new stream of genome conformation data generated for three different human leukemia cells or cell lines by the Hi-C technique. We developed and applied a set of bioinformatics methods to reliably generate spatial chromosomal contacts from high-throughput sequencing data and to effectively use them to study the properties of the genome structures in one-dimension (1D and two-dimension (2D. Our analysis demonstrates that Hi-C data can be effectively applied to study tissue-specific genome conformation, chromosome-chromosome interaction, chromosomal translocations, and spatial gene-gene interaction and regulation in a three-dimensional genome of primary tumor cells. Particularly, for the first time, we constructed genome-scale spatial gene-gene interaction network, transcription factor binding site (TFBS - TFBS interaction network, and TFBS-gene interaction network from chromosomal contact information. Remarkably, all these networks possess the properties of scale-free modular networks.

Interaction between the RGS6 gene and psychosocial stress on obesity-related traits.

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Kim, Hyun-Jin; Min, Jin-Young; Min, Kyoung-Bok

2017-03-31

Obesity is a major risk factor for chronic diseases and arises from the interactions between environmental factors and multiple genes. Psychosocial stress may affect the risk for obesity, modifying food intake and choice. A recent study suggested regulator of G-protein signaling 6 (RGS6) as a novel candidate gene for obesity in terms of reward-related feeding under stress. In this study, we tried to verify the unidentified connection between RGS6 and human obesity with psychosocial stress in a Korean population. A total of 1,462 adult subjects, who participated in the Korean Association Resource cohort project, were included for this analysis. Obesity-related traits including waist circumference, body mass index, and visceral adipose tissue were recorded. A total of 4 intronic SNPs for the RGS6 gene were used for this study. We found that interactions between SNP rs2239219 and psychosocial stress are significantly associated with abdominal obesity (p = 0.007). As risk allele of this SNP increased, prevalence of abdominal obesity under high-stress conditions gradually increased (p = 0.013). However, we found no SNPs-by-stress interaction effect on other adiposity phenotypes. This study suggests that RGS6 is closely linked to stress-induced abdominal obesity in Korean adults.

Variable Persister Gene Interactions with (pppGpp for Persister Formation in Escherichia coli

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Shuang Liu

2017-09-01

Full Text Available Persisters comprise a group of phenotypically heterogeneous metabolically quiescent bacteria with multidrug tolerance and contribute to the recalcitrance of chronic infections. Although recent work has shown that toxin-antitoxin (TA system HipAB depends on stringent response effector (pppGppin persister formation, whether other persister pathways are also dependent on stringent response has not been explored. Here we examined the relationship of (pppGpp with 15 common persister genes (dnaK, clpB, rpoS, pspF, tnaA, sucB, ssrA, smpB, recA, umuD, uvrA, hipA, mqsR, relE, dinJ using Escherichia coli as a model. By comparing the persister levels of wild type with their single gene knockout and double knockout mutants with relA, we divided their interactions into five types, namely A “dependent” (dnaK, recA, B “positive reinforcement” (rpoS, pspF, ssrA, recA, C “antagonistic” (clpB, sucB, umuD, uvrA, hipA, mqsR, relE, dinJ, D “epistasis” (clpB, rpoS, tnaA, ssrA, smpB, hipA, and E “irrelevant” (dnaK, clpB, rpoS, tnaA, sucB, smpB, umuD, uvrA, hipA, mqsR, relE, dinJ. We found that the persister gene interactions are intimately dependent on bacterial culture age, cell concentrations (diluted versus undiluted culture, and drug classifications, where the same gene may belong to different groups with varying antibiotics, culture age or cell concentrations. Together, this study represents the first attempt to systematically characterize the intricate relationships among the different mechanisms of persistence and as such provide new insights into the complexity of the persistence phenomenon at the level of persister gene network interactions.

Gene-environment interaction in Major Depression: focus on experience-dependent biological systems

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Nicola eLopizzo

2015-05-01

Full Text Available 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 life long 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 X 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, in this review we aim to underlie the role of genetic and epigenetic processes involved in stress and neuroplasticity related biological systems on development of MDD after exposure to early life stress, thereby building the basis for future research and clinical interventions.

Protein Annotation from Protein Interaction Networks and Gene Ontology

OpenAIRE

Nguyen, Cao D.; Gardiner, Katheleen J.; Cios, Krzysztof J.

2011-01-01

We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precis...

Melanopsin gene variations interact with season to predict sleep onset and chronotype.

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Roecklein, Kathryn A; Wong, Patricia M; Franzen, Peter L; Hasler, Brant P; Wood-Vasey, W Michael; Nimgaonkar, Vishwajit L; Miller, Megan A; Kepreos, Kyle M; Ferrell, Robert E; Manuck, Stephen B

2012-10-01

The human melanopsin gene has been reported to mediate risk for seasonal affective disorder (SAD), which is hypothesized to be caused by decreased photic input during winter when light levels fall below threshold, resulting in differences in circadian phase and/or sleep. However, it is unclear if melanopsin increases risk of SAD by causing differences in sleep or circadian phase, or if those differences are symptoms of the mood disorder. To determine if melanopsin sequence variations are associated with differences in sleep-wake behavior among those not suffering from a mood disorder, the authors tested associations between melanopsin gene polymorphisms and self-reported sleep timing (sleep onset and wake time) in a community sample (N = 234) of non-Hispanic Caucasian participants (age 30-54 yrs) with no history of psychological, neurological, or sleep disorders. The authors also tested the effect of melanopsin variations on differences in preferred sleep and activity timing (i.e., chronotype), which may reflect differences in circadian phase, sleep homeostasis, or both. Daylength on the day of assessment was measured and included in analyses. DNA samples were genotyped for melanopsin gene polymorphisms using fluorescence polarization. P10L genotype interacted with daylength to predict self-reported sleep onset (interaction p sleep onset among those with the TT genotype was later in the day when individuals were assessed on longer days and earlier in the day on shorter days, whereas individuals in the other genotype groups (i.e., CC and CT) did not show this interaction effect. P10L genotype also interacted in an analogous way with daylength to predict self-reported morningness (interaction p sleep onset and chronotype as a function of daylength, whereas other genotypes at P10L do not seem to have effects that vary by daylength. A better understanding of how melanopsin confers heightened responsivity to daylength may improve our understanding of a broad range of

Differential reconstructed gene interaction networks for deriving toxicity threshold in chemical risk assessment

OpenAIRE

Yang, Yi; Maxwell, Andrew; Zhang, Xiaowei; Wang, Nan; Perkins, Edward J; Zhang, Chaoyang; Gong, Ping

2013-01-01

Background Pathway alterations reflected as changes in gene expression regulation and gene interaction can result from cellular exposure to toxicants. Such information is often used to elucidate toxicological modes of action. From a risk assessment perspective, alterations in biological pathways are a rich resource for setting toxicant thresholds, which may be more sensitive and mechanism-informed than traditional toxicity endpoints. Here we developed a novel differential networks (DNs) appro...

Gene interactions and genetics for yield and its attributes in grass pea

Indian Academy of Sciences (India)

[Parihar A. K., Dixit G. P. and Singh D. 2016 Gene interactions and genetics for yield and its attributes .... Biological yield. Seed yield factors. Plant height. Primary branches plant pod ..... indicates that these traits are under the control of several.

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

Science.gov (United States)

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.

Synergistic interactions between Drosophila orthologues of genes spanned by de novo human CNVs support multiple-hit models of autism.

Science.gov (United States)

Grice, Stuart J; Liu, Ji-Long; Webber, Caleb

2015-03-01

Autism spectrum disorders (ASDs) are highly heritable and characterised by deficits in social interaction and communication, as well as restricted and repetitive behaviours. Although a number of highly penetrant ASD gene variants have been identified, there is growing evidence to support a causal role for combinatorial effects arising from the contributions of multiple loci. By examining synaptic and circadian neurological phenotypes resulting from the dosage variants of unique human:fly orthologues in Drosophila, we observe numerous synergistic interactions between pairs of informatically-identified candidate genes whose orthologues are jointly affected by large de novo copy number variants (CNVs). These CNVs were found in the genomes of individuals with autism, including a patient carrying a 22q11.2 deletion. We first demonstrate that dosage alterations of the unique Drosophila orthologues of candidate genes from de novo CNVs that harbour only a single candidate gene display neurological defects similar to those previously reported in Drosophila models of ASD-associated variants. We then considered pairwise dosage changes within the set of orthologues of candidate genes that were affected by the same single human de novo CNV. For three of four CNVs with complete orthologous relationships, we observed significant synergistic effects following the simultaneous dosage change of gene pairs drawn from a single CNV. The phenotypic variation observed at the Drosophila synapse that results from these interacting genetic variants supports a concordant phenotypic outcome across all interacting gene pairs following the direction of human gene copy number change. We observe both specificity and transitivity between interactors, both within and between CNV candidate gene sets, supporting shared and distinct genetic aetiologies. We then show that different interactions affect divergent synaptic processes, demonstrating distinct molecular aetiologies. Our study illustrates

Evidence for gene-environment interaction in a genome wide study of nonsyndromic cleft palate

DEFF Research Database (Denmark)

Beaty, Terri H; Ruczinski, Ingo; Murray, Jeffrey C

2011-01-01

Nonsyndromic cleft palate (CP) is a common birth defect with a complex and heterogeneous etiology involving both genetic and environmental risk factors. We conducted a genome-wide association study (GWAS) using 550 case-parent trios, ascertained through a CP case collected in an international...... consortium. Family-based association tests of single nucleotide polymorphisms (SNP) and three common maternal exposures (maternal smoking, alcohol consumption, and multivitamin supplementation) were used in a combined 2 df test for gene (G) and gene-environment (G × E) interaction simultaneously, plus...... multiple SNPs associated with higher risk of CP in the presence of maternal smoking. Additional evidence of reduced risk due to G × E interaction in the presence of multivitamin supplementation was observed for SNPs in BAALC on chr. 8. These results emphasize the need to consider G × E interaction when...

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

Science.gov (United States)

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.

Diet-Gene Interactions and PUFA Metabolism: A Potential Contributor to Health Disparities and Human Diseases

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Floyd H. Chilton

2014-05-01

Full Text Available The “modern western” diet (MWD has increased the onset and progression of chronic human diseases as qualitatively and quantitatively maladaptive dietary components give rise to obesity and destructive gene-diet interactions. There has been a three-fold increase in dietary levels of the omega-6 (n-6 18 carbon (C18, polyunsaturated fatty acid (PUFA linoleic acid (LA; 18:2n-6, with the addition of cooking oils and processed foods to the MWD. Intense debate has emerged regarding the impact of this increase on human health. Recent studies have uncovered population-related genetic variation in the LCPUFA biosynthetic pathway (especially within the fatty acid desaturase gene (FADS cluster that is associated with levels of circulating and tissue PUFAs and several biomarkers and clinical endpoints of cardiovascular disease (CVD. Importantly, populations of African descent have higher frequencies of variants associated with elevated levels of arachidonic acid (ARA, CVD biomarkers and disease endpoints. Additionally, nutrigenomic interactions between dietary n-6 PUFAs and variants in genes that encode for enzymes that mobilize and metabolize ARA to eicosanoids have been identified. These observations raise important questions of whether gene-PUFA interactions are differentially driving the risk of cardiovascular and other diseases in diverse populations, and contributing to health disparities, especially in African American populations.

Genetic susceptibility loci, environmental exposures, and Parkinson's disease: a case-control study of gene-environment interactions.

Science.gov (United States)

Chung, Sun Ju; Armasu, Sebastian M; Anderson, Kari J; Biernacka, Joanna M; Lesnick, Timothy G; Rider, David N; Cunningham, Julie M; Ahlskog, J Eric; Frigerio, Roberta; Maraganore, Demetrius M

2013-06-01

Prior studies causally linked mutations in SNCA, MAPT, and LRRK2 genes with familial Parkinsonism. Genome-wide association studies have demonstrated association of single nucleotide polymorphisms (SNPs) in those three genes with sporadic Parkinson's disease (PD) susceptibility worldwide. Here we investigated the interactions between SNPs in those three susceptibility genes and environmental exposures (pesticides application, tobacco smoking, coffee drinking, and alcohol drinking) also associated with PD susceptibility. Pairwise interactions between environmental exposures and 18 variants (16 SNPs and two variable number tandem repeats, or "VNTRs") in SNCA, MAPT and LRRK2, were investigated using data from 1098 PD cases from the upper Midwest, USA and 1098 matched controls. Environmental exposures were assessed using a validated telephone interview script. Five pairwise interactions had uncorrected P-values coffee drinking × MAPT H1/H2 haplotype or MAPT rs16940806, and alcohol drinking × MAPT rs2435211. None of these interactions remained significant after Bonferroni correction. Secondary analyses in strata defined by type of control (sibling or unrelated), sex, or age at onset of the case also did not identify significant interactions after Bonferroni correction. This study documented limited pairwise interactions between established genetic and environmental risk factors for PD; however, the associations were not significant after correction for multiple testing. Copyright © 2013 Elsevier Ltd. All rights reserved.

Gene-diet interaction effects on BMI levels in the Singapore Chinese population.

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Chang, Xuling; Dorajoo, Rajkumar; Sun, Ye; Han, Yi; Wang, Ling; Khor, Chiea-Chuen; Sim, Xueling; Tai, E-Shyong; Liu, Jianjun; Yuan, Jian-Min; Koh, Woon-Puay; van Dam, Rob M; Friedlander, Yechiel; Heng, Chew-Kiat

2018-02-24

Recent genome-wide association studies (GWAS) have identified 97 body-mass index (BMI) associated loci. We aimed to evaluate if dietary intake modifies BMI associations at these loci in the Singapore Chinese population. We utilized GWAS information from six data subsets from two adult Chinese population (N = 7817). Seventy-eight genotyped or imputed index BMI single nucleotide polymorphisms (SNPs) that passed quality control procedures were available in all datasets. Alternative Healthy Eating Index (AHEI)-2010 score and ten nutrient variables were evaluated. Linear regression analyses between z score transformed BMI (Z-BMI) and dietary factors were performed. Interaction analyses were performed by introducing the interaction term (diet x SNP) in the same regression model. Analysis was carried out in each cohort individually and subsequently meta-analyzed using the inverse-variance weighted method. Analyses were also evaluated with a weighted gene-risk score (wGRS) contructed by BMI index SNPs from recent large-scale GWAS studies. Nominal associations between Z-BMI and AHEI-2010 and some dietary factors were identified (P = 0.047-0.010). The BMI wGRS was robustly associated with Z-BMI (P = 1.55 × 10 - 15 ) but not with any dietary variables. Dietary variables did not significantly interact with the wGRS to modify BMI associations. When interaction analyses were repeated using individual SNPs, a significant association between cholesterol intake and rs4740619 (CCDC171) was identified (β = 0.077, adjP interaction  = 0.043). The CCDC171 gene locus may interact with cholesterol intake to increase BMI in the Singaporean Chinese population, however most known obesity risk loci were not associated with dietary intake and did not interact with diet to modify BMI levels.

Interaction between CRHR1 and BDNF genes increases the risk of recurrent major depressive disorder in Chinese population.

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Zheman Xiao

Full Text Available BACKGROUND: An important etiological hypothesis about depression is stress has neurotoxic effects that damage the hippocampal cells. Corticotropin-releasing hormone (CRH regulates brain-derived neurotrophic factor (BDNF expression through influencing cAMP and Ca2+ signaling pathways during the course. The aim of this study is to examine the single and combined effects of CRH receptor 1 (CRHR1 and BDNF genes in recurrent major depressive disorder (MDD. METHODOLOGY/PRINCIPAL FINDING: The sample consists of 181 patients with recurrent MDD and 186 healthy controls. Whether genetic variations interaction between CRHR1 and BDNF genes might be associated with increased susceptibility to recurrent MDD was studied by using a gene-based association analysis of single-nucleotide polymorphisms (SNPs. CRHR1 gene (rs1876828, rs242939 and rs242941 and BDNF gene (rs6265 were identified in the samples of patients diagnosed with recurrent MDD and matched controls. Allelic association between CRHR1 rs242939 and recurrent MDD was found in our sample (allelic: p = 0.018, genotypic: p = 0.022 with an Odds Ratio 0.454 (95% CI 0.266-0.775. A global test of these four haplotypes showed a significant difference between recurrent MDD group and control group (chi-2 = 13.117, df = 3, P = 0.016. Furthermore, BDNF and CRHR1 interactions were found in the significant 2-locus, gene-gene interaction models (p = 0.05 using a generalized multifactor dimensionality reduction (GMDR method. CONCLUSION: Our results suggest that an interaction between CRHR1 and BDNF genes constitutes susceptibility to recurrent MDD.

Evidence for gene-environment interaction in a genome wide study of isolated, non-syndromic cleft palate

Science.gov (United States)

Beaty, Terri H.; Ruczinski, Ingo; Murray, Jeffrey C.; Marazita, Mary L.; Munger, Ronald G.; Hetmanski, Jacqueline B.; Murray, Tanda; Redett, Richard J.; Fallin, M. Daniele; Liang, Kung Yee; Wu, Tao; Patel, Poorav J.; Jin, Sheng C.; Zhang, Tian Xiao; Schwender, Holger; Wu-Chou, Yah Huei; Chen, Philip K; Chong, Samuel S; Cheah, Felicia; Yeow, Vincent; Ye, Xiaoqian; Wang, Hong; Huang, Shangzhi; Jabs, Ethylin W.; Shi, Bing; Wilcox, Allen J.; Lie, Rolv T.; Jee, Sun Ha; Christensen, Kaare; Doheny, Kimberley F.; Pugh, Elizabeth W.; Ling, Hua; Scott, Alan F.

2011-01-01

Non-syndromic cleft palate (CP) is a common birth defect with a complex and heterogeneous etiology involving both genetic and environmental risk factors. We conducted a genome wide association study (GWAS) using 550 case-parent trios, ascertained through a CP case collected in an international consortium. Family based association tests of single nucleotide polymorphisms (SNP) and three common maternal exposures (maternal smoking, alcohol consumption and multivitamin supplementation) were used in a combined 2 df test for gene (G) and gene-environment (G×E) interaction simultaneously, plus a separate 1 df test for G×E interaction alone. Conditional logistic regression models were used to estimate effects on risk to exposed and unexposed children. While no SNP achieved genome wide significance when considered alone, markers in several genes attained or approached genome wide significance when G×E interaction was included. Among these, MLLT3 and SMC2 on chromosome 9 showed multiple SNPs resulting in increased risk if the mother consumed alcohol during the peri-conceptual period (3 months prior to conception through the first trimester). TBK1 on chr. 12 and ZNF236 on chr. 18 showed multiple SNPs associated with higher risk of CP in the presence of maternal smoking. Additional evidence of reduced risk due to G×E interaction in the presence of multivitamin supplementation was observed for SNPs in BAALC on chr. 8. These results emphasize the need to consider G×E interaction when searching for genes influencing risk to complex and heterogeneous disorders, such as non-syndromic CP. PMID:21618603

Identifying Novel Candidate Genes Related to Apoptosis from a Protein-Protein Interaction Network

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Baoman Wang

2015-01-01

Full Text Available Apoptosis is the process of programmed cell death (PCD that occurs in multicellular organisms. This process of normal cell death is required to maintain the balance of homeostasis. In addition, some diseases, such as obesity, cancer, and neurodegenerative diseases, can be cured through apoptosis, which produces few side effects. An effective comprehension of the mechanisms underlying apoptosis will be helpful to prevent and treat some diseases. The identification of genes related to apoptosis is essential to uncover its underlying mechanisms. In this study, a computational method was proposed to identify novel candidate genes related to apoptosis. First, protein-protein interaction information was used to construct a weighted graph. Second, a shortest path algorithm was applied to the graph to search for new candidate genes. Finally, the obtained genes were filtered by a permutation test. As a result, 26 genes were obtained, and we discuss their likelihood of being novel apoptosis-related genes by collecting evidence from published literature.

Hippocampal gene expression patterns in oxytocin male knockout mice are related to impaired social interaction.

Science.gov (United States)

Lazzari, Virginia Meneghini; Zimmermann-Peruzatto, Josi Maria; Agnes, Grasiela; Becker, Roberta Oriques; de Moura, Ana Carolina; Almeida, Silvana; Guedes, Renata Padilha; Giovenardi, Marcia

2017-11-02

Social interaction between animals is crucial for the survival and life in groups. It is well demonstrated that oxytocin (OT) and vasopressin (AVP) play critical roles in the regulation of social behaviors in mammals, however, other neurotransmitters and hormones are involved in the brain circuitry related to these behaviors. The present study aimed to investigate the gene expression of neurotransmitter receptors in the brain of OT knockout (OTKO) male mice. In this study, we evaluated the expression levels of the OT receptor (Oxtr), AVP receptors 1a and 1b (Avpr1a; Avpr1b), dopamine receptor 2 (Drd2), and the estrogen receptors alpha and beta (Esr1; Esr2) genes in the hippocampus (HPC), olfactory bulb (OB), hypothalamus (HPT) and prefrontal cortex (PFC). AVP gene (Avp) expression was analyzed in the HPT. Gene expression results were discussed regarding to social interaction and sexual behavior findings. Additionally, we analyzed the influence of OT absence on the Avp mRNA expression levels in the HPT. RNA extraction and cDNAs synthesis followed by quantitative polymerase chain reaction were performed for gene expression determination. Results were calculated with the 2 -ΔΔCt method. Our main finding was that HPC is more susceptible to gene expression changes due to the lack of OT. OTKOs exhibited decreased expression of Drd2 and Avpr1b, but increased expression of Oxtr in the HPC. In the PFC, Esr2 was increased. In the HPT, there was a reduced Avp expression in the OTKO group. No differences were detected in the OB and HPT. Despite these changes in gene expression, sexual behavior was not affected. However, OTKO showed higher social investigation and lower aggressive performance than wild-type mice. Our data highlight the importance of OT for proper gene expression of neurotransmitter receptors related to the regulation of social interaction in male mice. Copyright © 2017. Published by Elsevier B.V.

Chemical-Gene Interactions from ToxCast Bioactivity Data Expands Universe of Literature Network-Based Associations (SOT)

Science.gov (United States)

Characterizing the effects of chemicals in biological systems is often summarized by chemical-gene interactions, which have sparse coverage in the literature. The ToxCast chemical screening program has produced bioactivity data for nearly 2000 chemicals and over 450 gene targets....

Systematically characterizing and prioritizing chemosensitivity related gene based on Gene Ontology and protein interaction network

Directory of Open Access Journals (Sweden)

Chen Xin

2012-10-01

Full Text Available Abstract Background The identification of genes that predict in vitro cellular chemosensitivity of cancer cells is of great importance. Chemosensitivity related genes (CRGs have been widely utilized to guide clinical and cancer chemotherapy decisions. In addition, CRGs potentially share functional characteristics and network features in protein interaction networks (PPIN. Methods In this study, we proposed a method to identify CRGs based on Gene Ontology (GO and PPIN. Firstly, we documented 150 pairs of drug-CCRG (curated chemosensitivity related gene from 492 published papers. Secondly, we characterized CCRGs from the perspective of GO and PPIN. Thirdly, we prioritized CRGs based on CCRGs’ GO and network characteristics. Lastly, we evaluated the performance of the proposed method. Results We found that CCRG enriched GO terms were most often related to chemosensitivity and exhibited higher similarity scores compared to randomly selected genes. Moreover, CCRGs played key roles in maintaining the connectivity and controlling the information flow of PPINs. We then prioritized CRGs using CCRG enriched GO terms and CCRG network characteristics in order to obtain a database of predicted drug-CRGs that included 53 CRGs, 32 of which have been reported to affect susceptibility to drugs. Our proposed method identifies a greater number of drug-CCRGs, and drug-CCRGs are much more significantly enriched in predicted drug-CRGs, compared to a method based on the correlation of gene expression and drug activity. The mean area under ROC curve (AUC for our method is 65.2%, whereas that for the traditional method is 55.2%. Conclusions Our method not only identifies CRGs with expression patterns strongly correlated with drug activity, but also identifies CRGs in which expression is weakly correlated with drug activity. This study provides the framework for the identification of signatures that predict in vitro cellular chemosensitivity and offers a valuable

Pharmacogenetics of drug-drug interaction and drug-drug-gene interaction : A systematic review on CYP2C9, CYP2C19 and CYP2D6

NARCIS (Netherlands)

Bahar, Muh Akbar; Setiawan, Didik; Hak, Eelko; Wilffert, Bob

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

Understanding Epistatic Interactions between Genes Targeted by Non-coding Regulatory Elements in Complex Diseases

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Min Kyung Sung

2014-12-01

Full Text Available Genome-wide association studies have proven the highly polygenic architecture of complex diseases or traits; therefore, single-locus-based methods are usually unable to detect all involved loci, especially when individual loci exert small effects. Moreover, the majority of associated single-nucleotide polymorphisms resides in non-coding regions, making it difficult to understand their phenotypic contribution. In this work, we studied epistatic interactions associated with three common diseases using Korea Association Resource (KARE data: type 2 diabetes mellitus (DM, hypertension (HT, and coronary artery disease (CAD. We showed that epistatic single-nucleotide polymorphisms (SNPs were enriched in enhancers, as well as in DNase I footprints (the Encyclopedia of DNA Elements [ENCODE] Project Consortium 2012, which suggested that the disruption of the regulatory regions where transcription factors bind may be involved in the disease mechanism. Accordingly, to identify the genes affected by the SNPs, we employed whole-genome multiple-cell-type enhancer data which discovered using DNase I profiles and Cap Analysis Gene Expression (CAGE. Assigned genes were significantly enriched in known disease associated gene sets, which were explored based on the literature, suggesting that this approach is useful for detecting relevant affected genes. In our knowledge-based epistatic network, the three diseases share many associated genes and are also closely related with each other through many epistatic interactions. These findings elucidate the genetic basis of the close relationship between DM, HT, and CAD.

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

Science.gov (United States)

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.

C-State: an interactive web app for simultaneous multi-gene visualization and comparative epigenetic pattern search.

Science.gov (United States)

Sowpati, Divya Tej; Srivastava, Surabhi; Dhawan, Jyotsna; Mishra, Rakesh K

2017-09-13

Comparative epigenomic analysis across multiple genes presents a bottleneck for bench biologists working with NGS data. Despite the development of standardized peak analysis algorithms, the identification of novel epigenetic patterns and their visualization across gene subsets remains a challenge. We developed a fast and interactive web app, C-State (Chromatin-State), to query and plot chromatin landscapes across multiple loci and cell types. C-State has an interactive, JavaScript-based graphical user interface and runs locally in modern web browsers that are pre-installed on all computers, thus eliminating the need for cumbersome data transfer, pre-processing and prior programming knowledge. C-State is unique in its ability to extract and analyze multi-gene epigenetic information. It allows for powerful GUI-based pattern searching and visualization. We include a case study to demonstrate its potential for identifying user-defined epigenetic trends in context of gene expression profiles.

Environment-Gene interaction in common complex diseases: New approaches

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William A. Toscano, Jr.

2014-10-01

Full Text Available Approximately 100,000 different environmental chemicals that are in use as high production volume chemicals confront us in our daily lives. Many of the chemicals we encounter are persistent and have long half-lives in the environment and our bodies. These compounds are referred to as Persistent Organic Pollutants, or POPS. The total environment however is broader than just toxic pollutants. It includes social capital, social economic status, and other factors that are not commonly considered in traditional approaches to studying environment-human interactions. The mechanism of action of environmental agents in altering the human phenotype from health to disease is more complex than once thought. The focus in public health has shifted away from the study of single-gene rare diseases and has given way to the study of multifactorial complex diseases that are common in the population. To understand common complex diseases, we need teams of scientists from different fields working together with common aims. We review some approaches for studying the action of the environment by discussing use-inspired research, and transdisciplinary research approaches. The Genomic era has yielded new tools for study of gene-environment interactions, including genomics, epigenomics, and systems biology. We use environmentally-driven diabetes mellitus type two as an example of environmental epigenomics and disease. The aim of this review is to start the conversation of how the application of advances in biomedical science can be used to advance public health.

Interaction between Social/Psychosocial Factors and Genetic Variants on Body Mass Index: A Gene-Environment Interaction Analysis in a Longitudinal Setting.

Science.gov (United States)

Zhao, Wei; Ware, Erin B; He, Zihuai; Kardia, Sharon L R; Faul, Jessica D; Smith, Jennifer A

2017-09-29

Obesity, which develops over time, is one of the leading causes of chronic diseases such as cardiovascular disease. However, hundreds of BMI (body mass index)-associated genetic loci identified through large-scale genome-wide association studies (GWAS) only explain about 2.7% of BMI variation. Most common human traits are believed to be influenced by both genetic and environmental factors. Past studies suggest a variety of environmental features that are associated with obesity, including socioeconomic status and psychosocial factors. This study combines both gene/regions and environmental factors to explore whether social/psychosocial factors (childhood and adult socioeconomic status, social support, anger, chronic burden, stressful life events, and depressive symptoms) modify the effect of sets of genetic variants on BMI in European American and African American participants in the Health and Retirement Study (HRS). In order to incorporate longitudinal phenotype data collected in the HRS and investigate entire sets of single nucleotide polymorphisms (SNPs) within gene/region simultaneously, we applied a novel set-based test for gene-environment interaction in longitudinal studies (LGEWIS). Childhood socioeconomic status (parental education) was found to modify the genetic effect in the gene/region around SNP rs9540493 on BMI in European Americans in the HRS. The most significant SNP (rs9540488) by childhood socioeconomic status interaction within the rs9540493 gene/region was suggestively replicated in the Multi-Ethnic Study of Atherosclerosis (MESA) ( p = 0.07).

Interaction between Social/Psychosocial Factors and Genetic Variants on Body Mass Index: A Gene-Environment Interaction Analysis in a Longitudinal Setting

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Wei Zhao

2017-09-01

Full Text Available Obesity, which develops over time, is one of the leading causes of chronic diseases such as cardiovascular disease. However, hundreds of BMI (body mass index-associated genetic loci identified through large-scale genome-wide association studies (GWAS only explain about 2.7% of BMI variation. Most common human traits are believed to be influenced by both genetic and environmental factors. Past studies suggest a variety of environmental features that are associated with obesity, including socioeconomic status and psychosocial factors. This study combines both gene/regions and environmental factors to explore whether social/psychosocial factors (childhood and adult socioeconomic status, social support, anger, chronic burden, stressful life events, and depressive symptoms modify the effect of sets of genetic variants on BMI in European American and African American participants in the Health and Retirement Study (HRS. In order to incorporate longitudinal phenotype data collected in the HRS and investigate entire sets of single nucleotide polymorphisms (SNPs within gene/region simultaneously, we applied a novel set-based test for gene-environment interaction in longitudinal studies (LGEWIS. Childhood socioeconomic status (parental education was found to modify the genetic effect in the gene/region around SNP rs9540493 on BMI in European Americans in the HRS. The most significant SNP (rs9540488 by childhood socioeconomic status interaction within the rs9540493 gene/region was suggestively replicated in the Multi-Ethnic Study of Atherosclerosis (MESA (p = 0.07.

Interactions Between Variation in Candidate Genes and Environmental Factors in the Etiology of Schizophrenia and Bipolar Disorder: a Systematic Review.

Science.gov (United States)

Misiak, Błażej; Stramecki, Filip; Gawęda, Łukasz; Prochwicz, Katarzyna; Sąsiadek, Maria M; Moustafa, Ahmed A; Frydecka, Dorota

2017-08-18

Schizophrenia and bipolar disorder (BD) are complex and multidimensional disorders with high heritability rates. The contribution of genetic factors to the etiology of these disorders is increasingly being recognized as the action of multiple risk variants with small effect sizes, which might explain only a minor part of susceptibility. On the other site, numerous environmental factors have been found to play an important role in their causality. Therefore, in recent years, several studies focused on gene × environment interactions that are believed to bridge the gap between genetic underpinnings and environmental insults. In this article, we performed a systematic review of studies investigating gene × environment interactions in BD and schizophrenia spectrum phenotypes. In the majority of studies from this field, interacting effects of variation in genes encoding catechol-O-methyltransferase (COMT), brain-derived neurotrophic factor (BDNF), and FK506-binding protein 5 (FKBP5) have been explored. Almost consistently, these studies revealed that polymorphisms in COMT, BDNF, and FKBP5 genes might interact with early life stress and cannabis abuse or dependence, influencing various outcomes of schizophrenia spectrum disorders and BD. Other interactions still require further replication in larger clinical and non-clinical samples. In addition, future studies should address the direction of causality and potential mechanisms of the relationship between gene × environment interactions and various categories of outcomes in schizophrenia and BD.

Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions

DEFF Research Database (Denmark)

Shungin, Dmitry; Deng, Wei Q; Varga, Tibor V

2017-01-01

Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between...... variance effects (Pv), G×E interaction effects (with smoking and physical activity), and marginal genetic effects (Pm). Correlations between Pv and Pm were stronger for SNPs with established marginal effects (Spearman's ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI) compared to all SNPs. When Pv...... and Pm were compared for all pruned SNPs, only BMI was statistically significant (Spearman's ρ = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the Pv distribution (Pbinomial BMI had...

Dairy Product Consumption Interacts with Glucokinase (GCK Gene Polymorphisms Associated with Insulin Resistance

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Marine S. Da Silva

2017-08-01

Full Text Available Dairy product intake and a person’s genetic background have been reported to be associated with the risk of type 2 diabetes (T2D. The objective of this study was to examine the interaction between dairy products and genes related to T2D on glucose-insulin homeostasis parameters. A validated food frequency questionnaire, fasting blood samples, and glucokinase (GCK genotypes were analyzed in 210 healthy participants. An interaction between rs1799884 in GCK and dairy intake on the homeostasis model assessment of insulin resistance was identified. Secondly, human hepatocellular carcinoma cells (HepG2 were grown in a high-glucose medium and incubated with either 1-dairy proteins: whey, caseins, and a mixture of whey and casein; and 2-four amino acids (AA or mixtures of AA. The expression of GCK-related genes insulin receptor substrate-1 (IRS-1 and fatty acid synthase (FASN was increased with whey protein isolate or hydrolysate. Individually, leucine increased IRS-1 expression, whereas isoleucine and valine decreased FASN expression. A branched-chain AA mixture decreased IRS-1 and FASN expression. In conclusion, carriers of the A allele for rs1799884 in the GCK gene may benefit from a higher intake of dairy products to maintain optimal insulin sensitivity. Moreover, the results show that whey proteins affect the expression of genes related to glucose metabolism.

Measuring the genetic influence on human life span: gene-environment interaction and sex-specific genetic effects

DEFF Research Database (Denmark)

Tan, Qihua; De Benedictis, G; Yashin, Annatoli

2001-01-01

New approaches are needed to explore the different ways in which genes affect the human life span. One needs to assess the genetic effects themselves, as well as gene–environment interactions and sex dependency. In this paper, we present a new model that combines both genotypic and demographicinf......New approaches are needed to explore the different ways in which genes affect the human life span. One needs to assess the genetic effects themselves, as well as gene–environment interactions and sex dependency. In this paper, we present a new model that combines both genotypic...

An environmental analysis of genes associated with schizophrenia: hypoxia and vascular factors as interacting elements in the neurodevelopmental model.

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Schmidt-Kastner, R; van Os, J; Esquivel, G; Steinbusch, H W M; Rutten, B P F

2012-12-01

Investigating and understanding gene-environment interaction (G × E) in a neurodevelopmentally and biologically plausible manner is a major challenge for schizophrenia research. Hypoxia during neurodevelopment is one of several environmental factors related to the risk of schizophrenia, and links between schizophrenia candidate genes and hypoxia regulation or vascular expression have been proposed. Given the availability of a wealth of complex genetic information on schizophrenia in the literature without knowledge on the connections to environmental factors, we now systematically collected genes from candidate studies (using SzGene), genome-wide association studies (GWAS) and copy number variation (CNV) analyses, and then applied four criteria to test for a (theoretical) link to ischemia-hypoxia and/or vascular factors. In all, 55% of the schizophrenia candidate genes (n=42 genes) met the criteria for a link to ischemia-hypoxia and/or vascular factors. Genes associated with schizophrenia showed a significant, threefold enrichment among genes that were derived from microarray studies of the ischemia-hypoxia response (IHR) in the brain. Thus, the finding of a considerable match between genes associated with the risk of schizophrenia and IHR and/or vascular factors is reproducible. An additional survey of genes identified by GWAS and CNV analyses suggested novel genes that match the criteria. Findings for interactions between specific variants of genes proposed to be IHR and/or vascular factors with obstetric complications in patients with schizophrenia have been reported in the literature. Therefore, the extended gene set defined here may form a reasonable and evidence-based starting point for hypothesis-based testing of G × E interactions in clinical genetic and translational neuroscience studies.

Pollen Killer Gene S35 Function Requires Interaction with an Activator That Maps Close to S24, Another Pollen Killer Gene in Rice

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Takahiko Kubo

2016-05-01

Full Text Available Pollen killer genes disable noncarrier pollens, and are responsible for male sterility and segregation distortion in hybrid populations of distantly related plant species. The genetic networks and the molecular mechanisms underlying the pollen killer system remain largely unknown. Two pollen killer genes, S24 and S35, have been found in an intersubspecific cross of Oryza sativa ssp. indica and japonica. The effect of S24 is counteracted by an unlinked locus EFS. Additionally, S35 has been proposed to interact with S24 to induce pollen sterility. These genetic interactions are suggestive of a single S24-centric genetic pathway (EFS–S24–S35 for the pollen killer system. To examine this hypothetical genetic pathway, the S35 and the S24 regions were further characterized and genetically dissected in this study. Our results indicated that S35 causes pollen sterility independently of both the EFS and S24 genes, but is dependent on a novel gene close to the S24 locus, named incentive for killing pollen (INK. We confirmed the phenotypic effect of the INK gene separately from the S24 gene, and identified the INK locus within an interval of less than 0.6 Mb on rice chromosome 5. This study characterized the genetic effect of the two independent genetic pathways of INK–S35 and EFS–S24 in indica–japonica hybrid progeny. Our results provide clear evidence that hybrid male sterility in rice is caused by several pollen killer networks with multiple factors positively and negatively regulating pollen killer genes.

Pollen Killer Gene S35 Function Requires Interaction with an Activator That Maps Close to S24, Another Pollen Killer Gene in Rice.

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Kubo, Takahiko; Yoshimura, Atsushi; Kurata, Nori

2016-05-03

Pollen killer genes disable noncarrier pollens, and are responsible for male sterility and segregation distortion in hybrid populations of distantly related plant species. The genetic networks and the molecular mechanisms underlying the pollen killer system remain largely unknown. Two pollen killer genes, S24 and S35, have been found in an intersubspecific cross of Oryza sativa ssp. indica and japonica The effect of S24 is counteracted by an unlinked locus EFS Additionally, S35 has been proposed to interact with S24 to induce pollen sterility. These genetic interactions are suggestive of a single S24-centric genetic pathway (EFS-S24-S35) for the pollen killer system. To examine this hypothetical genetic pathway, the S35 and the S24 regions were further characterized and genetically dissected in this study. Our results indicated that S35 causes pollen sterility independently of both the EFS and S24 genes, but is dependent on a novel gene close to the S24 locus, named incentive for killing pollen (INK). We confirmed the phenotypic effect of the INK gene separately from the S24 gene, and identified the INK locus within an interval of less than 0.6 Mb on rice chromosome 5. This study characterized the genetic effect of the two independent genetic pathways of INK-S35 and EFS-S24 in indica-japonica hybrid progeny. Our results provide clear evidence that hybrid male sterility in rice is caused by several pollen killer networks with multiple factors positively and negatively regulating pollen killer genes. Copyright © 2016 Kubo et al.

SLC6A1 gene involvement in susceptibility to attention-deficit/hyperactivity disorder: A case-control study and gene-environment interaction.

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Yuan, Fang-Fen; Gu, Xue; Huang, Xin; Zhong, Yan; Wu, Jing

2017-07-03

Attention-deficit/hyperactivity disorder (ADHD) is an early onset childhood neurodevelopmental disorder with an estimated heritability of approximately 76%. We conducted a case-control study to explore the role of the SLC6A1 gene in ADHD. The genotypes of eight variants were determined using Sequenom MassARRAY technology. The participants in the study were 302 children with ADHD and 411 controls. ADHD symptoms were assessed using the Conners Parent Symptom Questionnaire. In our study, rs2944366 was consistently shown to be associated with the ADHD risk in the dominant model (odds ratio [OR]=0.554, 95% confidence interval [CI]=0.404-0.760), and nominally associated with Hyperactive index score (P=0.027). In addition, rs1170695 has been found to be associated with the ADHD risk in the addictive model (OR=1.457, 95%CI=1.173-1.809), while rs9990174 was associated with the Hyperactive index score (P=0.010). Intriguingly, gene-environmental interactions analysis consistently revealed the potential interactions of rs1170695 with blood lead (P mul =0.044) to modify the ADHD risk. Expression quantitative trait loci analysis suggested that these positive single nucleotide polymorphisms (SNPs) may mediate SLC6A1 gene expression. Therefore, our results suggest that selected SLC6A1 gene variants may have a significant effect on the ADHD risk. Copyright © 2017 Elsevier Inc. All rights reserved.

Transcriptomic profiling of interacting nasal staphylococci species reveals global changes in gene and non-coding RNA expression

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Hermansen, Grith Miriam Maigaard; Sazinas, Pavelas; Kofod, Ditte

2018-01-01

Interspecies interactions between bacterial pathogens and the commensal microbiota can influence disease outcome. In the nasal cavities, Staphylococcus epidermidis has been shown to be a determining factor for Staphylococcus aureus colonization and biofilm formation. However, the interaction...... between S. epidermidis and S. aureus has mainly been described by phenotypic analysis, and little is known about how this interaction modulates gene expression.This study aimed to determine the interactome of nasal S. aureus and S. epidermidis isolates to understand the molecular effect of interaction...... also identified putative non-coding RNAs (ncRNAs) and, interestingly, detected a putative ncRNA transcribed antisense to esp, the serine protease of S. epidermidis, that has previously been shown to inhibit nasal colonization of S. aureus. In our study, the gene encoding Esp and the antisense nc...

The Omics Dashboard for interactive exploration of gene-expression data.

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Paley, Suzanne; Parker, Karen; Spaulding, Aaron; Tomb, Jean-Francois; O'Maille, Paul; Karp, Peter D

2017-12-01

The Omics Dashboard is a software tool for interactive exploration and analysis of gene-expression datasets. The Omics Dashboard is organized as a hierarchy of cellular systems. At the highest level of the hierarchy the Dashboard contains graphical panels depicting systems such as biosynthesis, energy metabolism, regulation and central dogma. Each of those panels contains a series of X-Y plots depicting expression levels of subsystems of that panel, e.g. subsystems within the central dogma panel include transcription, translation and protein maturation and folding. The Dashboard presents a visual read-out of the expression status of cellular systems to facilitate a rapid top-down user survey of how all cellular systems are responding to a given stimulus, and to enable the user to quickly view the responses of genes within specific systems of interest. Although the Dashboard is complementary to traditional statistical methods for analysis of gene-expression data, we show how it can detect changes in gene expression that statistical techniques may overlook. We present the capabilities of the Dashboard using two case studies: the analysis of lipid production for the marine alga Thalassiosira pseudonana, and an investigation of a shift from anaerobic to aerobic growth for the bacterium Escherichia coli. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Gene-gene combination effect and interactions among ABCA1, APOA1, SR-B1, and CETP polymorphisms for serum high-density lipoprotein-cholesterol in the Japanese population.

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Akihiko Nakamura

Full Text Available BACKGROUND/OBJECTIVE: Gene-gene interactions in the reverse cholesterol transport system for high-density lipoprotein-cholesterol (HDL-C are poorly understood. The present study observed gene-gene combination effect and interactions between single nucleotide polymorphisms (SNPs in ABCA1, APOA1, SR-B1, and CETP in serum HDL-C from a cross-sectional study in the Japanese population. METHODS: The study population comprised 1,535 men and 1,515 women aged 35-69 years who were enrolled in the Japan Multi-Institutional Collaborative Cohort (J-MICC Study. We selected 13 SNPs in the ABCA1, APOA1, CETP, and SR-B1 genes in the reverse cholesterol transport system. The effects of genetic and environmental factors were assessed using general linear and logistic regression models after adjusting for age, sex, and region. PRINCIPAL FINDINGS: Alcohol consumption and daily activity were positively associated with HDL-C levels, whereas smoking had a negative relationship. The T allele of CETP, rs3764261, was correlated with higher HDL-C levels and had the highest coefficient (2.93 mg/dL/allele among the 13 SNPs, which was statistically significant after applying the Bonferroni correction (p<0.001. Gene-gene combination analysis revealed that CETP rs3764261 was associated with high HDL-C levels with any combination of SNPs from ABCA1, APOA1, and SR-B1, although no gene-gene interaction was apparent. An increasing trend for serum HDL-C was also observed with an increasing number of alleles (p<0.001. CONCLUSIONS: The present study identified a multiplier effect from a polymorphism in CETP with ABCA1, APOA1, and SR-B1, as well as a dose-dependence according to the number of alleles present.

The temporal dynamics of differential gene expression in Aspergillus fumigatus interacting with human immature dendritic cells in vitro.

LENUS (Irish Health Repository)

Morton, Charles O

2011-01-01

Dendritic cells (DC) are the most important antigen presenting cells and play a pivotal role in host immunity to infectious agents by acting as a bridge between the innate and adaptive immune systems. Monocyte-derived immature DCs (iDC) were infected with viable resting conidia of Aspergillus fumigatus (Af293) for 12 hours at an MOI of 5; cells were sampled every three hours. RNA was extracted from both organisms at each time point and hybridised to microarrays. iDC cell death increased at 6 h in the presence of A. fumigatus which coincided with fungal germ tube emergence; >80% of conidia were associated with iDC. Over the time course A. fumigatus differentially regulated 210 genes, FunCat analysis indicated significant up-regulation of genes involved in fermentation, drug transport, pathogenesis and response to oxidative stress. Genes related to cytotoxicity were differentially regulated but the gliotoxin biosynthesis genes were down regulated over the time course, while Aspf1 was up-regulated at 9 h and 12 h. There was an up-regulation of genes in the subtelomeric regions of the genome as the interaction progressed. The genes up-regulated by iDC in the presence of A. fumigatus indicated that they were producing a pro-inflammatory response which was consistent with previous transcriptome studies of iDC interacting with A. fumigatus germ tubes. This study shows that A. fumigatus adapts to phagocytosis by iDCs by utilising genes that allow it to survive the interaction rather than just up-regulation of specific virulence genes.

The temporal dynamics of differential gene expression in Aspergillus fumigatus interacting with human immature dendritic cells in vitro.

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Charles O Morton

2011-01-01

Full Text Available Dendritic cells (DC are the most important antigen presenting cells and play a pivotal role in host immunity to infectious agents by acting as a bridge between the innate and adaptive immune systems. Monocyte-derived immature DCs (iDC were infected with viable resting conidia of Aspergillus fumigatus (Af293 for 12 hours at an MOI of 5; cells were sampled every three hours. RNA was extracted from both organisms at each time point and hybridised to microarrays. iDC cell death increased at 6 h in the presence of A. fumigatus which coincided with fungal germ tube emergence; >80% of conidia were associated with iDC. Over the time course A. fumigatus differentially regulated 210 genes, FunCat analysis indicated significant up-regulation of genes involved in fermentation, drug transport, pathogenesis and response to oxidative stress. Genes related to cytotoxicity were differentially regulated but the gliotoxin biosynthesis genes were down regulated over the time course, while Aspf1 was up-regulated at 9 h and 12 h. There was an up-regulation of genes in the subtelomeric regions of the genome as the interaction progressed. The genes up-regulated by iDC in the presence of A. fumigatus indicated that they were producing a pro-inflammatory response which was consistent with previous transcriptome studies of iDC interacting with A. fumigatus germ tubes. This study shows that A. fumigatus adapts to phagocytosis by iDCs by utilising genes that allow it to survive the interaction rather than just up-regulation of specific virulence genes.

A gene-environment interaction analysis of plasma selenium with prevalent and incident diabetes: The Hortega study.

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Galan-Chilet, Inmaculada; Grau-Perez, Maria; De Marco, Griselda; Guallar, Eliseo; Martin-Escudero, Juan Carlos; Dominguez-Lucas, Alejandro; Gonzalez-Manzano, Isabel; Lopez-Izquierdo, Raul; Briongos-Figuero, Laisa Socorro; Redon, Josep; Chaves, Felipe Javier; Tellez-Plaza, Maria

2017-08-01

Selenium and single-nucleotide-polymorphisms in selenoprotein genes have been associated to diabetes. However, the interaction of selenium with genetic variation in diabetes and oxidative stress-related genes has not been evaluated as a potential determinant of diabetes risk. We evaluated the cross-sectional and prospective associations of plasma selenium concentrations with type 2 diabetes, and the interaction of selenium concentrations with genetic variation in candidate polymorphisms, in a representative sample of 1452 men and women aged 18-85 years from Spain. The geometric mean of plasma selenium levels in the study sample was 84.2µg/L. 120 participants had diabetes at baseline. Among diabetes-free participants who were not lost during the follow-up (N=1234), 75 developed diabetes over time. The multivariable adjusted odds ratios (95% confidence interval) for diabetes prevalence comparing the second and third to the first tertiles of plasma selenium levels were 1.80 (1.03, 3.14) and 1.97 (1.14, 3.41), respectively. The corresponding hazard ratios (95% CI) for diabetes incidence were 1.76 (0.96, 3.22) and 1.80 (0.98, 3.31), respectively. In addition, we observed significant interactions between selenium and polymorphisms in PPARGC1A, and in genes encoding mitochondrial proteins, such as BCS1L and SDHA, and suggestive interactions of selenium with other genes related to selenoproteins and redox metabolism. Plasma selenium was positively associated with prevalent and incident diabetes. While the statistical interactions of selenium with polymorphisms involved in regulation of redox and insulin signaling pathways provide biological plausibility to the positive associations of selenium with diabetes, further research is needed to elucidate the causal pathways underlying these associations. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

MINER: exploratory analysis of gene interaction networks by machine learning from expression data

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Sivieng Jane

2009-12-01

Full Text Available Abstract Background The reconstruction of gene regulatory networks from high-throughput "omics" data has become a major goal in the modelling of living systems. Numerous approaches have been proposed, most of which attempt only "one-shot" reconstruction of the whole network with no intervention from the user, or offer only simple correlation analysis to infer gene dependencies. Results We have developed MINER (Microarray Interactive Network Exploration and Representation, an application that combines multivariate non-linear tree learning of individual gene regulatory dependencies, visualisation of these dependencies as both trees and networks, and representation of known biological relationships based on common Gene Ontology annotations. MINER allows biologists to explore the dependencies influencing the expression of individual genes in a gene expression data set in the form of decision, model or regression trees, using their domain knowledge to guide the exploration and formulate hypotheses. Multiple trees can then be summarised in the form of a gene network diagram. MINER is being adopted by several of our collaborators and has already led to the discovery of a new significant regulatory relationship with subsequent experimental validation. Conclusion Unlike most gene regulatory network inference methods, MINER allows the user to start from genes of interest and build the network gene-by-gene, incorporating domain expertise in the process. This approach has been used successfully with RNA microarray data but is applicable to other quantitative data produced by high-throughput technologies such as proteomics and "next generation" DNA sequencing.

Protein-Protein Interactions Prediction Based on Iterative Clique Extension with Gene Ontology Filtering

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Lei Yang

2014-01-01

Full Text Available Cliques (maximal complete subnets in protein-protein interaction (PPI network are an important resource used to analyze protein complexes and functional modules. Clique-based methods of predicting PPI complement the data defection from biological experiments. However, clique-based predicting methods only depend on the topology of network. The false-positive and false-negative interactions in a network usually interfere with prediction. Therefore, we propose a method combining clique-based method of prediction and gene ontology (GO annotations to overcome the shortcoming and improve the accuracy of predictions. According to different GO correcting rules, we generate two predicted interaction sets which guarantee the quality and quantity of predicted protein interactions. The proposed method is applied to the PPI network from the Database of Interacting Proteins (DIP and most of the predicted interactions are verified by another biological database, BioGRID. The predicted protein interactions are appended to the original protein network, which leads to clique extension and shows the significance of biological meaning.

A methodology to establish a database to study gene environment interactions for childhood asthma

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McCormick Jonathan

2010-12-01

Full Text Available Abstract Background Gene-environment interactions are likely to explain some of the heterogeneity in childhood asthma. Here, we describe the methodology and experiences in establishing a database for childhood asthma designed to study gene-environment interactions (PAGES - Paediatric Asthma Gene Environment Study. Methods Children with asthma and under the care of a respiratory paediatrician are being recruited from 15 hospitals between 2008 and 2011. An asthma questionnaire is completed and returned by post. At a routine clinic visit saliva is collected for DNA extraction. Detailed phenotyping in a proportion of children includes spirometry, bronchodilator response (BDR, skin prick reactivity, exhaled nitric oxide and salivary cotinine. Dietary and quality of life questionnaires are completed. Data are entered onto a purpose-built database. Results To date 1045 children have been invited to participate and data collected in 501 (48%. The mean age (SD of participants is 8.6 (3.9 years, 57% male. DNA has been collected in 436 children. Spirometry has been obtained in 172 children, mean % predicted (SD FEV1 97% (15 and median (IQR BDR is 5% (2, 9. There were differences in age, socioeconomic status, severity and %FEV1 between the different centres (p≤0.024. Reasons for non-participation included parents not having time to take part, children not attending clinics and, in a small proportion, refusal to take part. Conclusions It is feasible to establish a national database to study gene-environment interactions within an asthmatic paediatric population; there are barriers to participation and some different characteristics in individuals recruited from different centres. Recruitment to our study continues and is anticipated to extend current understanding of asthma heterogeneity.

Gene-environment interactions linking air pollution and inflammation in Parkinson's disease.

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Lee, Pei-Chen; Raaschou-Nielsen, Ole; Lill, Christina M; Bertram, Lars; Sinsheimer, Janet S; Hansen, Johnni; Ritz, Beate

2016-11-01

Both air pollution exposure and systemic inflammation have been linked to Parkinson's disease (PD). In the PASIDA study, 408 incident cases of PD diagnosed in 2006-2009 and their 495 population controls were interviewed and provided DNA samples. Markers of long term traffic related air pollution measures were derived from geographic information systems (GIS)-based modeling. Furthermore, we genotyped functional polymorphisms in genes encoding proinflammatory cytokines, namely rs1800629 in TNFα (tumor necrosis factor alpha) and rs16944 in IL1B (interleukin-1β). In logistic regression models, long-term exposure to NO 2 increased PD risk overall (odds ratio (OR)=1.06 per 2.94μg/m 3 increase, 95% CI=1.00-1.13). The OR for PD in individuals with high NO 2 exposure (≧75th percentile) and the AA genotype of IL1B rs16944 was 3.10 (95% CI=1.14-8.38) compared with individuals with lower NO 2 exposure (<75th percentile) and the GG genotype. The interaction term was nominally significant on the multiplicative scale (p=0.01). We did not find significant gene-environment interactions with TNF rs1800629. Our finds may provide suggestive evidence that a combination of traffic-related air pollution and genetic variation in the proinflammatory cytokine gene IL1B contribute to risk of developing PD. However, as statistical evidence was only modest in this large sample we cannot rule out that these results represent a chance finding, and additional replication efforts are warranted. Copyright © 2016 Elsevier Inc. All rights reserved.

Hox gene function and interaction in the milkweed bug Oncopeltus fasciatus (Hemiptera).

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Angelini, David R; Liu, Paul Z; Hughes, Cynthia L; Kaufman, Thomas C

2005-11-15

Studies in genetic model organisms such as Drosophila have demonstrated that the homeotic complex (Hox) genes impart segmental identity during embryogenesis. Comparative studies in a wide range of other insect taxa have shown that the Hox genes are expressed in largely conserved domains along the anterior-posterior body axis, but whether they are performing the same functions in different insects is an open question. Most of the Hox genes have been studied functionally in only a few holometabolous insects that undergo metamorphosis. Thus, it is unclear how the Hox genes are functioning in the majority of direct-developing insects and other arthropods. To address this question, we used a combination of RNAi and in situ hybridization to reveal the expression, functions, and regulatory interactions of the Hox genes in the milkweed bug Oncopeltus fasciatus. Our results reveal many similarities and some interesting differences compared to Drosophila. We find that the gene Antennapedia is required for the identity of all three thoracic segments, while Ultrabithorax, abdominal-A and Abdominal-B cooperate to pattern the abdomen. The three abdominal genes exhibit posterior prevalence like in Drosophila, but apparently via some post-transcriptional mechanism. The functions of the head genes proboscipedia, Deformed, and Sex combs reduced were shown previously, and here we find that the complex temporal expression of pb in the labium is like that of other insects, but its regulatory relationship with Scr is unique. Overall, our data reveal that the evolution of insect Hox genes has included many small changes within general conservation of expression and function, and that the milkweed bug provides a useful model for understanding the roles of Hox genes in a direct-developing insect.

Interactions of early adversity with stress-related gene polymorphisms impact regional brain structure in females.

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Gupta, Arpana; Labus, Jennifer; Kilpatrick, Lisa A; Bonyadi, Mariam; Ashe-McNalley, Cody; Heendeniya, Nuwanthi; Bradesi, Sylvie; Chang, Lin; Mayer, Emeran A

2016-04-01

Early adverse life events (EALs) have been associated with regional thinning of the subgenual cingulate cortex (sgACC), a brain region implicated in the development of disorders of mood and affect, and often comorbid functional pain disorders, such as irritable bowel syndrome (IBS). Regional neuroinflammation related to chronic stress system activation has been suggested as a possible mechanism underlying these neuroplastic changes. However, the interaction of genetic and environmental factors in these changes is poorly understood. The current study aimed to evaluate the interactions of EALs and candidate gene polymorphisms in influencing thickness of the sgACC. 210 female subjects (137 healthy controls; 73 IBS) were genotyped for stress and inflammation-related gene polymorphisms. Genetic variation with EALs, and diagnosis on sgACC thickness was examined, while controlling for race, age, and total brain volume. Compared to HCs, IBS had significantly reduced sgACC thickness (p = 0.03). Regardless of disease group (IBS vs. HC), thinning of the left sgACC was associated with a significant gene-gene environment interaction between the IL-1β genotype, the NR3C1 haplotype, and a history of EALs (p = 0.05). Reduced sgACC thickness in women with the minor IL-1β allele, was associated with EAL total scores regardless of NR3C1 haplotype status (p = 0.02). In subjects homozygous for the major IL-1β allele, reduced sgACC with increasing levels of EALs was seen only with the less common NR3C1 haplotype (p = 0.02). These findings support an interaction between polymorphisms related to stress and inflammation and early adverse life events in modulating a key region of the emotion arousal circuit.

Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool.

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Chen, Edward Y; Tan, Christopher M; Kou, Yan; Duan, Qiaonan; Wang, Zichen; Meirelles, Gabriela Vaz; Clark, Neil R; Ma'ayan, Avi

2013-04-15

System-wide profiling of genes and proteins in mammalian cells produce lists of differentially expressed genes/proteins that need to be further analyzed for their collective functions in order to extract new knowledge. Once unbiased lists of genes or proteins are generated from such experiments, these lists are used as input for computing enrichment with existing lists created from prior knowledge organized into gene-set libraries. While many enrichment analysis tools and gene-set libraries databases have been developed, there is still room for improvement. Here, we present Enrichr, an integrative web-based and mobile software application that includes new gene-set libraries, an alternative approach to rank enriched terms, and various interactive visualization approaches to display enrichment results using the JavaScript library, Data Driven Documents (D3). The software can also be embedded into any tool that performs gene list analysis. We applied Enrichr to analyze nine cancer cell lines by comparing their enrichment signatures to the enrichment signatures of matched normal tissues. We observed a common pattern of up regulation of the polycomb group PRC2 and enrichment for the histone mark H3K27me3 in many cancer cell lines, as well as alterations in Toll-like receptor and interlukin signaling in K562 cells when compared with normal myeloid CD33+ cells. Such analyses provide global visualization of critical differences between normal tissues and cancer cell lines but can be applied to many other scenarios. Enrichr is an easy to use intuitive enrichment analysis web-based tool providing various types of visualization summaries of collective functions of gene lists. Enrichr is open source and freely available online at: http://amp.pharm.mssm.edu/Enrichr.

Multiple interactions between maternally-activated signalling pathways control Xenopus nodal-related genes.

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Rex, Maria; Hilton, Emma; Old, Robert

2002-03-01

We have investigated the induction of the six Xenopus nodal-related genes, Xnr1-Xnr6, by maternal determinants. The beta-catenin pathway was modelled by stimulation using Xwnt8, activin-like signalling was modelled by activin, and VegT action was studied by overexpression in animal cap explants. Combinations of factors were examined, and previously unrecognised interactions were revealed in animal caps and whole embryos. For the induction of Xnr5 and Xnr6 in whole embryos, using a beta-catenin antisense morpholino oligonucleotide or a dominant negative XTcf3, we have demonstrated an absolute permissive requirement for the beta-catenin/Tcf pathway, in addition to the requirement for VegT action. In animal caps Xnr5 and Xnr6 are induced in response to VegT overexpression, and this induction is dependent upon the concomitant activation of the beta-catenin pathway that VegT initiates in animal caps. For the induction of Xnr3, VegT interacts negatively so as to inhibit the induction otherwise observed with wnt-signalling alone. The negative effect of VegT is not the result of a general inhibition of wnt-signalling, and does not result from an inhibition of wnt-induced siamois expression. A 294 bp proximal promoter fragment of the Xnr3 gene is sufficient to mediate the negative effect of VegT. Further experiments, employing cycloheximide to examine the dependence of Xnr gene expression upon proteins translated after the mid-blastula stage, demonstrated that Xnrs 4, 5 and 6 are 'primary' Xnr genes whose expression in the late blastula is solely dependent upon factors present before the mid-blastula stage.

Gene expression analysis uncovers novel Hedgehog interacting protein (HHIP) effects in human bronchial epithelial cells

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Zhou, Xiaobo; Qiu, Weiliang; Sathirapongsasuti, J. Fah.; Cho, Michael H.; Mancini, John D.; Lao, Taotao; Thibault, Derek M.; Litonjua, Gus; Bakke, Per S.; Gulsvik, Amund; Lomas, David A.; Beaty, Terri H.; Hersh, Craig P.; Anderson, Christopher; Geigenmuller, Ute; Raby, Benjamin A.; Rennard, Stephen I.; Perrella, Mark A.; Choi, Augustine M.K.; Quackenbush, John; Silverman, Edwin K.

2013-01-01

Hedgehog Interacting Protein (HHIP) was implicated in chronic obstructive pulmonary disease (COPD) by genome-wide association studies (GWAS). However, it remains unclear how HHIP contributes to COPD pathogenesis. To identify genes regulated by HHIP, we performed gene expression microarray analysis in a human bronchial epithelial cell line (Beas-2B) stably infected with HHIP shRNAs. HHIP silencing led to differential expression of 296 genes; enrichment for variants nominally associated with COPD was found. Eighteen of the differentially expressed genes were validated by real-time PCR in Beas-2B cells. Seven of 11 validated genes tested in human COPD and control lung tissues demonstrated significant gene expression differences. Functional annotation indicated enrichment for extracellular matrix and cell growth genes. Network modeling demonstrated that the extracellular matrix and cell proliferation genes influenced by HHIP tended to be interconnected. Thus, we identified potential HHIP targets in human bronchial epithelial cells that may contribute to COPD pathogenesis. PMID:23459001

Protein annotation from protein interaction networks and Gene Ontology.

Science.gov (United States)

Nguyen, Cao D; Gardiner, Katheleen J; Cios, Krzysztof J

2011-10-01

We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precision and 60% recall versus 45% and 26% for Majority and 24% and 61% for χ²-statistics, respectively. Copyright © 2011 Elsevier Inc. All rights reserved.

Gene-Environment Interaction in Parkinson's Disease: Coffee, ADORA2A, and CYP1A2.

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Chuang, Yu-Hsuan; Lill, Christina M; Lee, Pei-Chen; Hansen, Johnni; Lassen, Christina F; Bertram, Lars; Greene, Naomi; Sinsheimer, Janet S; Ritz, Beate

2016-01-01

Drinking caffeinated coffee has been reported to provide protection against Parkinson's disease (PD). Caffeine is an adenosine A2A receptor (encoded by the gene ADORA2A) antagonist that increases dopaminergic neurotransmission and Cytochrome P450 1A2 (gene: CYP1A2) metabolizes caffeine; thus, gene polymorphisms in ADORA2A and CYP1A2 may influence the effect coffee consumption has on PD risk. In a population-based case-control study (PASIDA) in Denmark (1,556 PD patients and 1,606 birth year- and gender-matched controls), we assessed interactions between lifetime coffee consumption and 3 polymorphisms in ADORA2A and CYP1A2 for all subjects, and incident and prevalent PD cases separately using logistic regression models. We also conducted a meta-analysis combining our results with those from previous studies. We estimated statistically significant interactions for ADORA2A rs5760423 and heavy vs. light coffee consumption in incident (OR interaction = 0.66 [95% CI 0.46-0.94], p = 0.02) but not prevalent PD. We did not observe interactions for CYP1A2 rs762551 and rs2472304 in incident or prevalent PD. In meta-analyses, PD associations with daily coffee consumption were strongest among carriers of variant alleles in both ADORA2A and CYP1A2. We corroborated results from a previous report that described interactions between ADORA2A and CYP1A2 polymorphisms and coffee consumption. Our results also suggest that survivor bias may affect results of studies that enroll prevalent PD cases. © 2017 S. Karger AG, Basel.

Banana ethylene response factors are involved in fruit ripening through their interactions with ethylene biosynthesis genes.

Science.gov (United States)

Xiao, Yun-yi; Chen, Jian-ye; Kuang, Jiang-fei; Shan, Wei; Xie, Hui; Jiang, Yue-ming; Lu, Wang-jin

2013-05-01

The involvement of ethylene response factor (ERF) transcription factor (TF) in the transcriptional regulation of ethylene biosynthesis genes during fruit ripening remains largely unclear. In this study, 15 ERF genes, designated as MaERF1-MaERF15, were isolated and characterized from banana fruit. These MaERFs were classified into seven of the 12 known ERF families. Subcellular localization showed that MaERF proteins of five different subfamilies preferentially localized to the nucleus. The 15 MaERF genes displayed differential expression patterns and levels in peel and pulp of banana fruit, in association with four different ripening treatments caused by natural, ethylene-induced, 1-methylcyclopropene (1-MCP)-delayed, and combined 1-MCP and ethylene treatments. MaERF9 was upregulated while MaERF11 was downregulated in peel and pulp of banana fruit during ripening or after treatment with ethylene. Furthermore, yeast-one hybrid (Y1H) and transient expression assays showed that the potential repressor MaERF11 bound to MaACS1 and MaACO1 promoters to suppress their activities and that MaERF9 activated MaACO1 promoter activity. Interestingly, protein-protein interaction analysis revealed that MaERF9 and -11 physically interacted with MaACO1. Taken together, these results suggest that MaERFs are involved in banana fruit ripening via transcriptional regulation of or interaction with ethylene biosynthesis genes.

Identification of T1D susceptibility genes within the MHC region by combining protein interaction networks and SNP genotyping data

DEFF Research Database (Denmark)

Brorsson, C.; Hansen, Niclas Tue; Hansen, Kasper Lage

2009-01-01

genes. We have developed a novel method that combines single nucleotide polymorphism (SNP) genotyping data with protein-protein interaction (ppi) networks to identify disease-associated network modules enriched for proteins encoded from the MHC region. Approximately 2500 SNPs located in the 4 Mb MHC......To develop novel methods for identifying new genes that contribute to the risk of developing type 1 diabetes within the Major Histocompatibility Complex (MHC) region on chromosome 6, independently of the known linkage disequilibrium (LD) between human leucocyte antigen (HLA)-DRB1, -DQA1, -DQB1...... region were analysed in 1000 affected offspring trios generated by the Type 1 Diabetes Genetics Consortium (T1DGC). The most associated SNP in each gene was chosen and genes were mapped to ppi networks for identification of interaction partners. The association testing and resulting interacting protein...

Random regression models for detection of gene by environment interaction

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Meuwissen Theo HE

2007-02-01

Full Text Available Abstract Two random regression models, where the effect of a putative QTL was regressed on an environmental gradient, are described. The first model estimates the correlation between intercept and slope of the random regression, while the other model restricts this correlation to 1 or -1, which is expected under a bi-allelic QTL model. The random regression models were compared to a model assuming no gene by environment interactions. The comparison was done with regards to the models ability to detect QTL, to position them accurately and to detect possible QTL by environment interactions. A simulation study based on a granddaughter design was conducted, and QTL were assumed, either by assigning an effect independent of the environment or as a linear function of a simulated environmental gradient. It was concluded that the random regression models were suitable for detection of QTL effects, in the presence and absence of interactions with environmental gradients. Fixing the correlation between intercept and slope of the random regression had a positive effect on power when the QTL effects re-ranked between environments.

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

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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.…

Differential gene expression in foxtail millet during incompatible interaction with Uromyces setariae-italicae.

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Zhi Yong Li

Full Text Available Foxtail millet (Setaria italica is an important food and fodder grain crop that is grown for human consumption. Production of this species is affected by several plant diseases, such as rust. The cultivar Shilixiang has been identified as resistant to the foxtail millet rust pathogen, Uromyces setariae-italicae. In order to identify signaling pathways and genes related to the plant's defense mechanisms against rust, the Shilixiang cultivar was used to construct a digital gene expression (DGE library during the interaction of foxtail millet with U. setariae-italicae. In this study, we determined the most abundant differentially expressed signaling pathways of up-regulated genes in foxtail millet and identified significantly up-regulated genes. Finally, quantitative real-time polymerase chain reaction (qRT-PCR analysis was used to analyze the expression of nine selected genes, and the patterns observed agreed well with DGE analysis. Expression levels of the genes were also compared between a resistant cultivar Shilixiang and a susceptible cultivar Yugu-1, and the result indicated that expression level of Shilixiang is higher than that of Yugu-1. This study reveals the relatively comprehensive mechanisms of rust-responsive transcription in foxtail millet.

False positive reduction in protein-protein interaction predictions using gene ontology annotations

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Lin Yen-Han

2007-07-01

Full Text Available Abstract Background Many crucial cellular operations such as metabolism, signalling, and regulations are based on protein-protein interactions. However, the lack of robust protein-protein interaction information is a challenge. One reason for the lack of solid protein-protein interaction information is poor agreement between experimental findings and computational sets that, in turn, comes from huge false positive predictions in computational approaches. Reduction of false positive predictions and enhancing true positive fraction of computationally predicted protein-protein interaction datasets based on highly confident experimental results has not been adequately investigated. Results Gene Ontology (GO annotations were used to reduce false positive protein-protein interactions (PPI pairs resulting from computational predictions. Using experimentally obtained PPI pairs as a training dataset, eight top-ranking keywords were extracted from GO molecular function annotations. The sensitivity of these keywords is 64.21% in the yeast experimental dataset and 80.83% in the worm experimental dataset. The specificities, a measure of recovery power, of these keywords applied to four predicted PPI datasets for each studied organisms, are 48.32% and 46.49% (by average of four datasets in yeast and worm, respectively. Based on eight top-ranking keywords and co-localization of interacting proteins a set of two knowledge rules were deduced and applied to remove false positive protein pairs. The 'strength', a measure of improvement provided by the rules was defined based on the signal-to-noise ratio and implemented to measure the applicability of knowledge rules applying to the predicted PPI datasets. Depending on the employed PPI-predicting methods, the strength varies between two and ten-fold of randomly removing protein pairs from the datasets. Conclusion Gene Ontology annotations along with the deduced knowledge rules could be implemented to partially

A database and tool, IM Browser, for exploring and integrating emerging gene and protein interaction data for Drosophila

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Parrish Jodi R

2006-04-01

Full Text Available Abstract Background Biological processes are mediated by networks of interacting genes and proteins. Efforts to map and understand these networks are resulting in the proliferation of interaction data derived from both experimental and computational techniques for a number of organisms. The volume of this data combined with the variety of specific forms it can take has created a need for comprehensive databases that include all of the available data sets, and for exploration tools to facilitate data integration and analysis. One powerful paradigm for the navigation and analysis of interaction data is an interaction graph or map that represents proteins or genes as nodes linked by interactions. Several programs have been developed for graphical representation and analysis of interaction data, yet there remains a need for alternative programs that can provide casual users with rapid easy access to many existing and emerging data sets. Description Here we describe a comprehensive database of Drosophila gene and protein interactions collected from a variety of sources, including low and high throughput screens, genetic interactions, and computational predictions. We also present a program for exploring multiple interaction data sets and for combining data from different sources. The program, referred to as the Interaction Map (IM Browser, is a web-based application for searching and visualizing interaction data stored in a relational database system. Use of the application requires no downloads and minimal user configuration or training, thereby enabling rapid initial access to interaction data. IM Browser was designed to readily accommodate and integrate new types of interaction data as it becomes available. Moreover, all information associated with interaction measurements or predictions and the genes or proteins involved are accessible to the user. This allows combined searches and analyses based on either common or technique-specific attributes

Environmental and gene-environment interactions and risk of rheumatoid arthritis

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Karlson, Elizabeth W.; Deane, Kevin

2012-01-01

Multiple environmental factors including hormones, dietary factors, infections and exposure to tobacco smoke as well as gene-environment interactions have been associated with increased risk for rheumatoid arthritis (RA). Importantly, the growing understanding of the prolonged period prior to the first onset of symptoms of RA suggests that these environmental and genetic factors are likely acting to drive the development of RA-related autoimmunity long before the appearance of the first joint symptoms and clinical findings that are characteristic of RA. Herein we will review these factors and interactions, especially those that have been investigated in a prospective fashion prior to the symptomatic onset of RA. We will also discuss how these factors may be explored in future study to further the understanding of the pathogenesis of RA, and ultimately perhaps develop preventive measures for this disease. PMID:22819092

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

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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

A case-only genome-wide association study for assessing gene-sex interaction in Allergic rhinitis

DEFF Research Database (Denmark)

Mohammadnejad, Afsaneh; Brasch-Andersen, Charlotte; Haagerup, Annette

-value = 2.8 × 10−5) sits in C5orf66 gene on 5q31. Poster abstract 2 Discussion: Our study was able to detect a significant SNP rs4251459 mapping to IRAK4 gene on 12q12 locus which appeared to increase the risk of AR in females than males. This gene has previously been reported to have a sex dependent effect...... on AR. C5orf66 loci might also be an interesting candidate for AR, but its role warrants further validations. Additionally, pathway analysis from GSEA identified a pathway related to immune system which is biologically meaningful and supportive. In conclusion, our study revealed the gene-sex interaction...

Gene-Environment Interaction Research and Transgenic Mouse Models of Alzheimer's Disease

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L. Chouliaras

2010-01-01

Full Text Available The etiology of the sporadic form of Alzheimer's disease (AD remains largely unknown. Recent evidence has suggested that gene-environment interactions (GxE may play a crucial role in its development and progression. Whereas various susceptibility loci have been identified, like the apolipoprotein E4 allele, these cannot fully explain the increasing prevalence of AD observed with aging. In addition to such genetic risk factors, various environmental factors have been proposed to alter the risk of developing AD as well as to affect the rate of cognitive decline in AD patients. Nevertheless, aside from the independent effects of genetic and environmental risk factors, their synergistic participation in increasing the risk of developing AD has been sparsely investigated, even though evidence points towards such a direction. Advances in the genetic manipulation of mice, modeling various aspects of the AD pathology, have provided an excellent tool to dissect the effects of genes, environment, and their interactions. In this paper we present several environmental factors implicated in the etiology of AD that have been tested in transgenic animal models of the disease. The focus lies on the concept of GxE and its importance in a multifactorial disease like AD. Additionally, possible mediating mechanisms and future challenges are discussed.

Geographical patterns of adaptation within a species' range : Interactions between drift and gene flow

NARCIS (Netherlands)

Alleaume-Benharira, M; Pen, IR; Ronce, O

We use individual-based stochastic simulations and analytical deterministic predictions to investigate the interaction between drift, natural selection and gene flow on the patterns of local adaptation across a fragmented species' range under clinally varying selection. Migration between populations

Discerning molecular interactions: A comprehensive review on biomolecular interaction databases and network analysis tools.

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Miryala, Sravan Kumar; Anbarasu, Anand; Ramaiah, Sudha

2018-02-05

Computational analysis of biomolecular interaction networks is now gaining a lot of importance to understand the functions of novel genes/proteins. Gene interaction (GI) network analysis and protein-protein interaction (PPI) network analysis play a major role in predicting the functionality of interacting genes or proteins and gives an insight into the functional relationships and evolutionary conservation of interactions among the genes. An interaction network is a graphical representation of gene/protein interactome, where each gene/protein is a node, and interaction between gene/protein is an edge. In this review, we discuss the popular open source databases that serve as data repositories to search and collect protein/gene interaction data, and also tools available for the generation of interaction network, visualization and network analysis. Also, various network analysis approaches like topological approach and clustering approach to study the network properties and functional enrichment server which illustrates the functions and pathway of the genes and proteins has been discussed. Hence the distinctive attribute mentioned in this review is not only to provide an overview of tools and web servers for gene and protein-protein interaction (PPI) network analysis but also to extract useful and meaningful information from the interaction networks. Copyright © 2017 Elsevier B.V. All rights reserved.

The role of genes involved in neuroplasticity and neurogenesis in the observation of a gene-environment interaction (GxE) in schizophrenia.

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Le Strat, Yann; Ramoz, Nicolas; Gorwood, Philip

2009-05-01

Schizophrenia is a multifactorial disease characterized by a high heritability. Several candidate genes have been suggested, with the strongest evidences for genes encoding dystrobrevin binding protein 1 (DTNBP1), neuregulin 1 (NRG1), neuregulin 1 receptor (ERBB4) and disrupted in schizophrenia 1 (DISC1), as well as several neurotrophic factors. These genes are involved in neuronal plasticity and play also a role in adult neurogenesis. Therefore, the genetic basis of schizophrenia could involve different factors more or less specifically required for neuroplasticity, including the synapse maturation, potentiation and plasticity as well as neurogenesis. Following the model of Knudson in tumors, we propose a two-hit hypothesis of schizophrenia. In this model of gene-environment interaction, a variant in a gene related to neurogenesis is transmitted to the descent (first hit), and, secondarily, an environmental factor occurs during the development of the central nervous system (second hit). Both of these vulnerability and trigger factors are probably necessary to generate a deficit in neurogenesis and therefore to cause schizophrenia. The literature supporting this gene x environment hypothesis is reviewed, with emphasis on some molecular pathways, raising the possibility to propose more specific molecular medicine.

The genetic interacting landscape of 63 candidate genes in Major Depressive Disorder: an explorative study.

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Lekman, Magnus; Hössjer, Ola; Andrews, Peter; Källberg, Henrik; Uvehag, Daniel; Charney, Dennis; Manji, Husseini; Rush, John A; McMahon, Francis J; Moore, Jason H; Kockum, Ingrid

2014-01-01

Genetic contributions to major depressive disorder (MDD) are thought to result from multiple genes interacting with each other. Different procedures have been proposed to detect such interactions. Which approach is best for explaining the risk of developing disease is unclear. This study sought to elucidate the genetic interaction landscape in candidate genes for MDD by conducting a SNP-SNP interaction analysis using an exhaustive search through 3,704 SNP-markers in 1,732 cases and 1,783 controls provided from the GAIN MDD study. We used three different methods to detect interactions, two logistic regressions models (multiplicative and additive) and one data mining and machine learning (MDR) approach. Although none of the interaction survived correction for multiple comparisons, the results provide important information for future genetic interaction studies in complex disorders. Among the 0.5% most significant observations, none had been reported previously for risk to MDD. Within this group of interactions, less than 0.03% would have been detectable based on main effect approach or an a priori algorithm. We evaluated correlations among the three different models and conclude that all three algorithms detected the same interactions to a low degree. Although the top interactions had a surprisingly large effect size for MDD (e.g. additive dominant model Puncorrected = 9.10E-9 with attributable proportion (AP) value = 0.58 and multiplicative recessive model with Puncorrected = 6.95E-5 with odds ratio (OR estimated from β3) value = 4.99) the area under the curve (AUC) estimates were low (< 0.54). Moreover, the population attributable fraction (PAF) estimates were also low (< 0.15). We conclude that the top interactions on their own did not explain much of the genetic variance of MDD. The different statistical interaction methods we used in the present study did not identify the same pairs of interacting markers. Genetic interaction studies may uncover previously

GENE X ENVIRONMENT INTERACTIONS IN SCHIZOPHRENIA AND BIPOLAR DISORDER:EVIDENCE FROM NEUROIMAGING

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Pierre Alexis Geoffroy

2013-10-01

Full Text Available Introduction: Schizophrenia (SZ and Bipolar disorder (BD are considered as severe multifactorial diseases, stemming from genetic and environmental influences. Growing evidence supports gene x environment (GxE interactions in these disorders and neuroimaging studies can help us to understand how those factors mechanistically interact. No reviews synthesized the existing data of neuroimaging studies in these issues.Methods: We conduct a systematic review on the neuroimaging studies exploring GxE interactions relative to SZ or BD in PubMed.Results: First results of the influence of genetic and environmental risks on brain structures came from monozygotic twin pairs concordant and discordant for SZ or BD. Few structural magnetic resonance imaging (sMRI studies have explored the GxE interactions. No other imaging methods were found. Two main GxE interactions on brain volumes have arisen. First, an interaction between genetic liability to SZ and obstetric complications on gray matter, cerebrospinal fluid and hippocampal volumes. Second, cannabis use and genetic liability interaction effects on cortical thickness and white matter volumes.Conclusion: Combining GxE interactions and neuroimaging domains is a promising approach. Genetic risk and environmental exposures such as cannabis or obstetrical complications seem to interact leading to specific neuroimaging cerebral alterations in SZ. They are suggestive of GxE interactions that confer phenotypic abnormalities in SZ and possibly BD. We need further, larger neuroimaging studies of GxE interactions for which we may propose a framework focusing on GxE interactions data already known to have a clinical effect such as infections, early stress, urbanicity and substance abuse.

Thermo-Regulation of Genes Mediating Motility and Plant Interactions in Pseudomonas syringae

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Hockett, Kevin L.; Burch, Adrien Y.; Lindow, Steven E.

2013-01-01

Pseudomonas syringae is an important phyllosphere colonist that utilizes flagellum-mediated motility both as a means to explore leaf surfaces, as well as to invade into leaf interiors, where it survives as a pathogen. We found that multiple forms of flagellum-mediated motility are thermo-suppressed, including swarming and swimming motility. Suppression of swarming motility occurs between 28° and 30°C, which coincides with the optimal growth temperature of P. syringae. Both fliC (encoding flagellin) and syfA (encoding a non-ribosomal peptide synthetase involved in syringafactin biosynthesis) were suppressed with increasing temperature. RNA-seq revealed 1440 genes of the P. syringae genome are temperature sensitive in expression. Genes involved in polysaccharide synthesis and regulation, phage and IS elements, type VI secretion, chemosensing and chemotaxis, translation, flagellar synthesis and motility, and phytotoxin synthesis and transport were generally repressed at 30°C, while genes involved in transcriptional regulation, quaternary ammonium compound metabolism and transport, chaperone/heat shock proteins, and hypothetical genes were generally induced at 30°C. Deletion of flgM, a key regulator in the transition from class III to class IV gene expression, led to elevated and constitutive expression of fliC regardless of temperature, but did not affect thermo-regulation of syfA. This work highlights the importance of temperature in the biology of P. syringae, as many genes encoding traits important for plant-microbe interactions were thermo-regulated. PMID:23527276

Relationships among estrogen receptor, oxytocin and vasopressin gene expression and social interaction in male mice.

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Murakami, G; Hunter, R G; Fontaine, C; Ribeiro, A; Pfaff, D

2011-08-01

The incidence of social disorders such as autism and schizophrenia is significantly higher in males, and the presentation more severe, than in females. This suggests the possible contribution of sex hormones to the development of these psychiatric disorders. There is also evidence that these disorders are highly heritable. To contribute toward our understanding of the mechanisms underlying social behaviors, particularly social interaction, we assessed the relationship of social interaction with gene expression for two neuropeptides, oxytocin (OT) and arginine vasopressin (AVP), using adult male mice. Social interaction was positively correlated with: oxytocin receptor (OTR) and vasopressin receptor (V1aR) mRNA expression in the medial amygdala; and OT and AVP mRNA expression in the paraventricular nucleus of the hypothalamus (PVN). When mice representing extremes of social interaction were compared, all of these mRNAs were more highly expressed in high social interaction mice than in low social interaction mice. OTR and V1aR mRNAs were highly correlated with estrogen receptor α (ERα) mRNA in the medial amygdala, and OT and AVP mRNAs with estrogen receptor β (ERβ) mRNA in the PVN, indicating that OT and AVP systems are tightly regulated by estrogen receptors. A significant difference in the level of ERα mRNA in the medial amygdala between high and low social interaction mice was also observed. These results support the hypothesis that variations of estrogen receptor levels are associated with differences in social interaction through the OT and AVP systems, by upregulating gene expression for those peptides and their receptors. © 2011 The Authors. European Journal of Neuroscience © 2011 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Genes2FANs: connecting genes through functional association networks

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2012-01-01

Background Protein-protein, cell signaling, metabolic, and transcriptional interaction networks are useful for identifying connections between lists of experimentally identified genes/proteins. However, besides physical or co-expression interactions there are many ways in which pairs of genes, or their protein products, can be associated. By systematically incorporating knowledge on shared properties of genes from diverse sources to build functional association networks (FANs), researchers may be able to identify additional functional interactions between groups of genes that are not readily apparent. Results Genes2FANs is a web based tool and a database that utilizes 14 carefully constructed FANs and a large-scale protein-protein interaction (PPI) network to build subnetworks that connect lists of human and mouse genes. The FANs are created from mammalian gene set libraries where mouse genes are converted to their human orthologs. The tool takes as input a list of human or mouse Entrez gene symbols to produce a subnetwork and a ranked list of intermediate genes that are used to connect the query input list. In addition, users can enter any PubMed search term and then the system automatically converts the returned results to gene lists using GeneRIF. This gene list is then used as input to generate a subnetwork from the user’s PubMed query. As a case study, we applied Genes2FANs to connect disease genes from 90 well-studied disorders. We find an inverse correlation between the counts of links connecting disease genes through PPI and links connecting diseases genes through FANs, separating diseases into two categories. Conclusions Genes2FANs is a useful tool for interpreting the relationships between gene/protein lists in the context of their various functions and networks. Combining functional association interactions with physical PPIs can be useful for revealing new biology and help form hypotheses for further experimentation. Our finding that disease genes in

Interaction of two photoreceptors in the regulation of bacterial photosynthesis genes

OpenAIRE

Metz, Sebastian; Haberzettl, Kerstin; Frühwirth, Sebastian; Teich, Kristin; Hasewinkel, Christian; Klug, Gabriele

2012-01-01

The expression of photosynthesis genes in the facultatively photosynthetic bacterium Rhodobacter sphaeroides is controlled by the oxygen tension and by light quantity. Two photoreceptor proteins, AppA and CryB, have been identified in the past, which are involved in this regulation. AppA senses light by its N-terminal BLUF domain, its C-terminal part binds heme and is redox-responsive. Through its interaction to the transcriptional repressor PpsR the AppA photoreceptor controls expression of ...

Assessing SNP-SNP interactions among DNA repair, modification and metabolism related pathway genes in breast cancer susceptibility.

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Yadav Sapkota

Full Text Available Genome-wide association studies (GWASs have identified low-penetrance common variants (i.e., single nucleotide polymorphisms, SNPs associated with breast cancer susceptibility. Although GWASs are primarily focused on single-locus effects, gene-gene interactions (i.e., epistasis are also assumed to contribute to the genetic risks for complex diseases including breast cancer. While it has been hypothesized that moderately ranked (P value based weak single-locus effects in GWASs could potentially harbor valuable information for evaluating epistasis, we lack systematic efforts to investigate SNPs showing consistent associations with weak statistical significance across independent discovery and replication stages. The objectives of this study were i to select SNPs showing single-locus effects with weak statistical significance for breast cancer in a GWAS and/or candidate-gene studies; ii to replicate these SNPs in an independent set of breast cancer cases and controls; and iii to explore their potential SNP-SNP interactions contributing to breast cancer susceptibility. A total of 17 SNPs related to DNA repair, modification and metabolism pathway genes were selected since these pathways offer a priori knowledge for potential epistatic interactions and an overall role in breast carcinogenesis. The study design included predominantly Caucasian women (2,795 cases and 4,505 controls from Alberta, Canada. We observed two two-way SNP-SNP interactions (APEX1-rs1130409 and RPAP1-rs2297381; MLH1-rs1799977 and MDM2-rs769412 in logistic regression that conferred elevated risks for breast cancer (P(interaction<7.3 × 10(-3. Logic regression identified an interaction involving four SNPs (MBD2-rs4041245, MLH1-rs1799977, MDM2-rs769412, BRCA2-rs1799943 (P(permutation = 2.4 × 10(-3. SNPs involved in SNP-SNP interactions also showed single-locus effects with weak statistical significance, while BRCA2-rs1799943 showed stronger statistical significance (P

A study for association and interaction analysis to metabolic syndrome and the ESR1 gene on cardiovascular autonomic neuropathy in a Chinese Han population.

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Zeng, Fangfang; Zhou, Linuo; Tang, Zihui

2016-01-01

The aim of this study was to investigate the association and interaction of metabolic syndrome (MetS) and estrogen receptor alpha 1 (ESR1) gene polymorphisms on cardiovascular autonomic neuropathy (CAN). A large-scale, population-based study was conducted to analyze the interaction of MetS and ESR1 gene polymorphisms to CAN, including a total of 1977 Chinese subjects. The most common studied single nucleotide polymorphism of ESR1 gene-rs9340799, was genotyped. Multiple logistic regression (MLR) was performed to evaluate the interaction effect of environmental variables and gene polymorphisms. Interaction on an additive scale can be calculated by using the relative excess risk due to interaction (RERI), the proportion attributable to interaction (AP), and the synergy index (S). After controlling potential confounders, MLR showed that significant association between MetS and CAN (p interaction was estimated by using RETI = 0.396 (95 % CI 0.262 to 0.598), AP = 0.216 (95 % CI -0.784 to 1.216) and S = 1.906 (95 % CI 0.905 to 4.015). The present findings suggest that MetS is significantly associated with CAN and provide evidence for the hypothesis that MetS and ESR1 gene polymorphism (rs9340799) have interactive effects on CAN. ClinicalTrials gov Identifier NCT02461342.

Gene-environment interaction in Parkinson’s disease: coffee, ADORA2A, and CYP1A2

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Chuang, Yu-Hsuan; Lill, Christina M.; Lee, Pei-Chen; Hansen, Johnni; Lassen, Christina Funch; Bertram, Lars; Greene, Naomi; Sinsheimer, Janet S.; Ritz, Beate

2017-01-01

Background and purpose Drinking caffeinated coffee has been reported to protect against Parkinson’s disease (PD). Caffeine is an adenosine A2A receptor (encoded by the gene ADORA2A) antagonist that increases dopaminergic neurotransmission and Cytochrome P450 1A2 (gene: CYP1A2) metabolizes caffeine, thus gene polymorphisms in ADORA2A and CYP1A2 may influence the effect coffee consumption has on PD risk. Methods In a population-based case control study (PASIDA) in Denmark (1,556 PD patients and 1,606 birth year- and sex- matched controls), we assessed interactions between lifetime coffee consumption and three polymorphisms in ADORA2A and CYP1A2 for all subjects and incident and prevalent PD cases separately using logistic regression models. We also conducted a meta-analysis combining our results with those from previous studies. Results We estimated statistically significant interactions for ADORA2A rs5760423 and heavy vs. light coffee consumption in incident (OR interaction=0.66 [0.46–0.94], p=0.02) but not prevalent PD. We did not observe interactions for CYP1A2 rs762551 and rs2472304 in incident or prevalent PD. In meta-analyses, PD associations with daily coffee consumption were strongest among carriers of variant alleles in both ADORA2A and CYP1A2. Conclusion We corroborated results from a previous report that described interactions between ADORA2A and CYP1A2 polymorphisms and coffee consumption. Our results also suggest that survivor bias may affect results of studies that enrol prevalent PD cases. PMID:28135712

Verticillium dahliae-Arabidopsis Interaction Causes Changes in Gene Expression Profiles and Jasmonate Levels on Different Time Scales

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Sandra S. Scholz

2018-02-01

Full Text Available Verticillium dahliae is a soil-borne vascular pathogen that causes severe wilt symptoms in a wide range of plants. Co-culture of the fungus with Arabidopsis roots for 24 h induces many changes in the gene expression profiles of both partners, even before defense-related phytohormone levels are induced in the plant. Both partners reprogram sugar and amino acid metabolism, activate genes for signal perception and transduction, and induce defense- and stress-responsive genes. Furthermore, analysis of Arabidopsis expression profiles suggests a redirection from growth to defense. After 3 weeks, severe disease symptoms can be detected for wild-type plants while mutants impaired in jasmonate synthesis and perception perform much better. Thus, plant jasmonates have an important influence on the interaction, which is already visible at the mRNA level before hormone changes occur. The plant and fungal genes that rapidly respond to the presence of the partner might be crucial for early recognition steps and the future development of the interaction. Thus they are potential targets for the control of V. dahliae-induced wilt diseases.

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

Science.gov (United States)

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.

Genetic interactions of MAF1 identify a role for Med20 in transcriptional repression of ribosomal protein genes.

Directory of Open Access Journals (Sweden)

Ian M Willis

2008-07-01

Full Text Available Transcriptional repression of ribosomal components and tRNAs is coordinately regulated in response to a wide variety of environmental stresses. Part of this response involves the convergence of different nutritional and stress signaling pathways on Maf1, a protein that is essential for repressing transcription by RNA polymerase (pol III in Saccharomyces cerevisiae. Here we identify the functions buffering yeast cells that are unable to down-regulate transcription by RNA pol III. MAF1 genetic interactions identified in screens of non-essential gene-deletions and conditionally expressed essential genes reveal a highly interconnected network of 64 genes involved in ribosome biogenesis, RNA pol II transcription, tRNA modification, ubiquitin-dependent proteolysis and other processes. A survey of non-essential MAF1 synthetic sick/lethal (SSL genes identified six gene-deletions that are defective in transcriptional repression of ribosomal protein (RP genes following rapamycin treatment. This subset of MAF1 SSL genes included MED20 which encodes a head module subunit of the RNA pol II Mediator complex. Genetic interactions between MAF1 and subunits in each structural module of Mediator were investigated to examine the functional relationship between these transcriptional regulators. Gene expression profiling identified a prominent and highly selective role for Med20 in the repression of RP gene transcription under multiple conditions. In addition, attenuated repression of RP genes by rapamycin was observed in a strain deleted for the Mediator tail module subunit Med16. The data suggest that Mediator and Maf1 function in parallel pathways to negatively regulate RP mRNA and tRNA synthesis.

Combining random gene fission and rational gene fusion to discover near-infrared fluorescent protein fragments that report on protein-protein interactions.

Science.gov (United States)

Pandey, Naresh; Nobles, Christopher L; Zechiedrich, Lynn; Maresso, Anthony W; Silberg, Jonathan J

2015-05-15

Gene fission can convert monomeric proteins into two-piece catalysts, reporters, and transcription factors for systems and synthetic biology. However, some proteins can be challenging to fragment without disrupting function, such as near-infrared fluorescent protein (IFP). We describe a directed evolution strategy that can overcome this challenge by randomly fragmenting proteins and concomitantly fusing the protein fragments to pairs of proteins or peptides that associate. We used this method to create libraries that express fragmented IFP as fusions to a pair of associating peptides (IAAL-E3 and IAAL-K3) and proteins (CheA and CheY) and screened for fragmented IFP with detectable near-infrared fluorescence. Thirteen novel fragmented IFPs were identified, all of which arose from backbone fission proximal to the interdomain linker. Either the IAAL-E3 and IAAL-K3 peptides or CheA and CheY proteins could assist with IFP fragment complementation, although the IAAL-E3 and IAAL-K3 peptides consistently yielded higher fluorescence. These results demonstrate how random gene fission can be coupled to rational gene fusion to create libraries enriched in fragmented proteins with AND gate logic that is dependent upon a protein-protein interaction, and they suggest that these near-infrared fluorescent protein fragments will be suitable as reporters for pairs of promoters and protein-protein interactions within whole animals.

Learning Motivation Mediates Gene-by-Socioeconomic Status Interaction on Mathematics Achievement in Early Childhood

Science.gov (United States)

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…

Identification of novel type 1 diabetes candidate genes by integrating genome-wide association data, protein-protein interactions, and human pancreatic islet gene expression

DEFF Research Database (Denmark)

Bergholdt, Regine; Brorsson, Caroline; Palleja, Albert

2012-01-01

Genome-wide association studies (GWAS) have heralded a new era in susceptibility locus discovery in complex diseases. For type 1 diabetes, >40 susceptibility loci have been discovered. However, GWAS do not inevitably lead to identification of the gene or genes in a given locus associated with dis......-cells. Our results provide novel insight to the mechanisms behind type 1 diabetes pathogenesis and, thus, may provide the basis for the design of novel treatment strategies.......Genome-wide association studies (GWAS) have heralded a new era in susceptibility locus discovery in complex diseases. For type 1 diabetes, >40 susceptibility loci have been discovered. However, GWAS do not inevitably lead to identification of the gene or genes in a given locus associated...... with disease, and they do not typically inform the broader context in which the disease genes operate. Here, we integrated type 1 diabetes GWAS data with protein-protein interactions to construct biological networks of relevance for disease. A total of 17 networks were identified. To prioritize...

An Empirical Comparison of Joint and Stratified Frameworks for Studying G × E Interactions: Systolic Blood Pressure and Smoking in the CHARGE Gene-Lifestyle Interactions Working Group

NARCIS (Netherlands)

Sung, Y.J. (Yun Ju); T.W. Winkler (Thomas W.); A.K. Manning (Alisa); H. Aschard (Hugues); V. Gudnason (Vilmundur); T.B. Harris (Tamara); A.V. Smith (Albert Vernon); E.A. Boerwinkle (Eric); M.R. Brown; A.C. Morrison (Alanna); M. Fornage (Myriam); L.-A. Lin (Li-An); Richard, M. (Melissa); T.M. Bartz (Traci M.); B.M. Psaty (Bruce); C. Hayward (Caroline); O. Polasek (Ozren); J. Marten (Jonathan); I. Rudan (Igor); M.F. Feitosa (Mary Furlan); A. Kraja (Aldi); M.A. Province (Mike); Deng, X. (Xuan); Fisher, V.A. (Virginia A.); Y. Zhou (Yanhua); L.F. Bielak (Lawrence F.); J.A. Smith (Jennifer A); J.E. Huffman (Jennifer); S. Padmanabhan (Sandosh); B.H. Smith (Blair); Ding, J. (Jingzhong); Y. Liu (YongMei); Lohman, K. (Kurt); C. Bouchard (Claude); T. Rankinen (Tuomo); Rice, T.K. (Treva K.); D.K. Arnett (Donna); K. Schwander; X. Guo (Xiuqing); W. Palmas (Walter); Rotter, J.I. (Jerome I.); Alfred, T. (Tamuno); E.P. Bottinger (Erwin); R.J.F. Loos (Ruth); N. Amin (Najaf); O.H. Franco (Oscar); C.M. van Duijn (Cornelia); D. Vojinovic (Dina); D.I. Chasman (Daniel); P.M. Ridker (Paul); L.M. Rose (Lynda); S.L.R. Kardia (Sharon); X. Zhu (Xiaofeng); K.M. Rice (Kenneth); I.B. Borecki (Ingrid); D.C. Rao (Dabeeru C.); Gauderman, W.J. (W. James); L.A. Cupples (Adrienne)

2016-01-01

textabstractStudying gene-environment (G × E) interactions is important, as they extend our knowledge of the genetic architecture of complex traits and may help to identify novel variants not detected via analysis of main effects alone. The main statistical framework for studying G × E interactions

Coordinated rates of evolution between interacting plastid and nuclear genes in Geraniaceae.

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Zhang, Jin; Ruhlman, Tracey A; Sabir, Jamal; Blazier, J Chris; Jansen, Robert K

2015-03-01

Although gene coevolution has been widely observed within individuals and between different organisms, rarely has this phenomenon been investigated within a phylogenetic framework. The Geraniaceae is an attractive system in which to study plastid-nuclear genome coevolution due to the highly elevated evolutionary rates in plastid genomes. In plants, the plastid-encoded RNA polymerase (PEP) is a protein complex composed of subunits encoded by both plastid (rpoA, rpoB, rpoC1, and rpoC2) and nuclear genes (sig1-6). We used transcriptome and genomic data for 27 species of Geraniales in a systematic evaluation of coevolution between genes encoding subunits of the PEP holoenzyme. We detected strong correlations of dN (nonsynonymous substitutions) but not dS (synonymous substitutions) within rpoB/sig1 and rpoC2/sig2, but not for other plastid/nuclear gene pairs, and identified the correlation of dN/dS ratio between rpoB/C1/C2 and sig1/5/6, rpoC1/C2 and sig2, and rpoB/C2 and sig3 genes. Correlated rates between interacting plastid and nuclear sequences across the Geraniales could result from plastid-nuclear genome coevolution. Analyses of coevolved amino acid positions suggest that structurally mediated coevolution is not the major driver of plastid-nuclear coevolution. The detection of strong correlation of evolutionary rates between SIG and RNAP genes suggests a plausible explanation for plastome-genome incompatibility in Geraniaceae. © 2015 American Society of Plant Biologists. All rights reserved.

Identification and comprehensive evaluation of reference genes for RT-qPCR analysis of host gene-expression in Brassica juncea-aphid interaction using microarray data.

Science.gov (United States)

Ram, Chet; Koramutla, Murali Krishna; Bhattacharya, Ramcharan

2017-07-01

Brassica juncea is a chief oil yielding crop in many parts of the world including India. With advancement of molecular techniques, RT-qPCR based study of gene-expression has become an integral part of experimentations in crop breeding. In RT-qPCR, use of appropriate reference gene(s) is pivotal. The virtue of the reference genes, being constant in expression throughout the experimental treatments, needs to be validated case by case. Appropriate reference gene(s) for normalization of gene-expression data in B. juncea during the biotic stress of aphid infestation is not known. In the present investigation, 11 reference genes identified from microarray database of Arabidopsis-aphid interaction at a cut off FDR ≤0.1, along with two known reference genes of B. juncea, were analyzed for their expression stability upon aphid infestation. These included 6 frequently used and 5 newly identified reference genes. Ranking orders of the reference genes in terms of expression stability were calculated using advanced statistical approaches such as geNorm, NormFinder, delta Ct and BestKeeper. The analysis suggested CAC, TUA and DUF179 as the most suitable reference genes. Further, normalization of the gene-expression data of STP4 and PR1 by the most and the least stable reference gene, respectively has demonstrated importance and applicability of the recommended reference genes in aphid infested samples of B. juncea. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Genetic interactions between Shox2 and Hox genes during the regional growth and development of the mouse limb.

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Neufeld, Stanley J; Wang, Fan; Cobb, John

2014-11-01

The growth and development of the vertebrate limb relies on homeobox genes of the Hox and Shox families, with their independent mutation often giving dose-dependent effects. Here we investigate whether Shox2 and Hox genes function together during mouse limb development by modulating their relative dosage and examining the limb for nonadditive effects on growth. Using double mRNA fluorescence in situ hybridization (FISH) in single embryos, we first show that Shox2 and Hox genes have associated spatial expression dynamics, with Shox2 expression restricted to the proximal limb along with Hoxd9 and Hoxa11 expression, juxtaposing the distal expression of Hoxa13 and Hoxd13. By generating mice with all possible dosage combinations of mutant Shox2 alleles and HoxA/D cluster deletions, we then show that their coordinated proximal limb expression is critical to generate normally proportioned limb segments. These epistatic interactions tune limb length, where Shox2 underexpression enhances, and Shox2 overexpression suppresses, Hox-mutant phenotypes. Disruption of either Shox2 or Hox genes leads to a similar reduction in Runx2 expression in the developing humerus, suggesting their concerted action drives cartilage maturation during normal development. While we furthermore provide evidence that Hox gene function influences Shox2 expression, this regulation is limited in extent and is unlikely on its own to be a major explanation for their genetic interaction. Given the similar effect of human SHOX mutations on regional limb growth, Shox and Hox genes may generally function as genetic interaction partners during the growth and development of the proximal vertebrate limb. Copyright © 2014 by the Genetics Society of America.

Application of Various Statistical Models to Explore Gene-Gene Interactions in Folate, Xenobiotic, Toll-Like Receptor and STAT4 Pathways that Modulate Susceptibility to Systemic Lupus Erythematosus.

Science.gov (United States)

Rupasree, Yedluri; Naushad, Shaik Mohammad; Varshaa, Ravi; Mahalakshmi, Govindaraj Swathika; Kumaraswami, Konda; Rajasekhar, Liza; Kutala, Vijay Kumar

2016-02-01

In view of our previous studies showing an independent association of genetic polymorphisms in folate, xenobiotic, and toll-like receptor (TLR) pathways with the risk for systemic lupus erythematosus (SLE), we have developed three statistical models to delineate complex gene-gene interactions between folate, xenobiotic, TLR, and signal transducer and activator of transcription 4 (STAT4) signaling pathways in association with the molecular pathophysiology of SLE. We developed additive, multifactor dimensionality reduction (MDR), and artificial neural network (ANN) models. The additive model, although the simplest, suggested a moderate predictability of 30 polymorphisms of these four pathways (area under the curve [AUC] 0.66). MDR analysis revealed significant gene-gene interactions among glutathione-S-transferase (GST)T1 and STAT4 (rs3821236 and rs7574865) polymorphisms, which account for moderate predictability of SLE. The MDR model for specific auto-antibodies revealed the importance of gene-gene interactions among cytochrome P450, family1, subfamily A, polypeptide 1 (CYP1A1) m1, catechol-O-methyltransferase (COMT) H108L, solute carrier family 19 (folate transporter), member 1 (SLC19A1) G80A, estrogen receptor 1 (ESR1), TLR5, 5-methyltetrahydrofolate-homocysteine methyltransferase reductase (MTRR), thymidylate synthase (TYMS). and STAT4 polymorphisms. The ANN model for disease prediction showed reasonably good predictability of SLE risk with 30 polymorphisms (AUC 0.76). These polymorphisms contribute towards the production of SSB and anti-dsDNA antibodies to the extent of 48 and 40%, respectively, while their contribution for the production of antiRNP, SSA, and anti-cardiolipin antibodies varies between 20 and 30%. The current study highlighted the importance of genetic polymorphisms in folate, xenobiotic, TLR, and STAT4 signaling pathways as moderate predictors of SLE risk and delineates the molecular pathophysiology associated with these single nucleotide

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

Science.gov (United States)

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.

A Simple Negative Interaction in the Positive Transcriptional Feedback of a Single Gene Is Sufficient to Produce Reliable Oscillations

Science.gov (United States)

Miró-Bueno, Jesús M.; Rodríguez-Patón, Alfonso

2011-01-01

Negative and positive transcriptional feedback loops are present in natural and synthetic genetic oscillators. A single gene with negative transcriptional feedback needs a time delay and sufficiently strong nonlinearity in the transmission of the feedback signal in order to produce biochemical rhythms. A single gene with only positive transcriptional feedback does not produce oscillations. Here, we demonstrate that this single-gene network in conjunction with a simple negative interaction can also easily produce rhythms. We examine a model comprised of two well-differentiated parts. The first is a positive feedback created by a protein that binds to the promoter of its own gene and activates the transcription. The second is a negative interaction in which a repressor molecule prevents this protein from binding to its promoter. A stochastic study shows that the system is robust to noise. A deterministic study identifies that the dynamics of the oscillator are mainly driven by two types of biomolecules: the protein, and the complex formed by the repressor and this protein. The main conclusion of this paper is that a simple and usual negative interaction, such as degradation, sequestration or inhibition, acting on the positive transcriptional feedback of a single gene is a sufficient condition to produce reliable oscillations. One gene is enough and the positive transcriptional feedback signal does not need to activate a second repressor gene. This means that at the genetic level an explicit negative feedback loop is not necessary. The model needs neither cooperative binding reactions nor the formation of protein multimers. Therefore, our findings could help to clarify the design principles of cellular clocks and constitute a new efficient tool for engineering synthetic genetic oscillators. PMID:22205920

Sleep Duration and Depressive Symptoms: A Gene-Environment Interaction

Science.gov (United States)

Watson, Nathaniel F.; Harden, Kathryn Paige; Buchwald, Dedra; Vitiello, Michael V.; Pack, Allan I.; Strachan, Eric; Goldberg, Jack

2014-01-01

Objective: We used quantitative genetic models to assess whether sleep duration modifies genetic and environmental influences on depressive symptoms. Method: Participants were 1,788 adult twins from 894 same-sex twin pairs (192 male and 412 female monozygotic [MZ] pairs, and 81 male and 209 female dizygotic [DZ] pairs] from the University of Washington Twin Registry. Participants self-reported habitual sleep duration and depressive symptoms. Data were analyzed using quantitative genetic interaction models, which allowed the magnitude of additive genetic, shared environmental, and non-shared environmental influences on depressive symptoms to vary with sleep duration. Results: Within MZ twin pairs, the twin who reported longer sleep duration reported fewer depressive symptoms (ec = -0.17, SE = 0.06, P sleep duration interaction effect on depressive symptoms (a'c = 0.23, SE = 0.08, P sleep duration and depressive symptoms. Among individuals with sleep duration within the normal range (7-8.9 h/night), the total heritability (h2) of depressive symptoms was approximately 27%. However, among individuals with sleep duration within the low (sleep duration extremes (5 h/night: h2 = 53%; 10 h/night: h2 = 49%). Conclusion: Genetic contributions to depressive symptoms increase at both short and long sleep durations. Citation: Watson NF; Harden KP; Buchwald D; Vitiello MV; Pack AI; Stachan E; Goldberg J. Sleep duration and depressive symptoms: a gene-environment interaction. SLEEP 2014;37(2):351-358. PMID:24497663

TranscriptomeBrowser 3.0: introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks.

Science.gov (United States)

Lepoivre, Cyrille; Bergon, Aurélie; Lopez, Fabrice; Perumal, Narayanan B; Nguyen, Catherine; Imbert, Jean; Puthier, Denis

2012-01-31

Deciphering gene regulatory networks by in silico approaches is a crucial step in the study of the molecular perturbations that occur in diseases. The development of regulatory maps is a tedious process requiring the comprehensive integration of various evidences scattered over biological databases. Thus, the research community would greatly benefit from having a unified database storing known and predicted molecular interactions. Furthermore, given the intrinsic complexity of the data, the development of new tools offering integrated and meaningful visualizations of molecular interactions is necessary to help users drawing new hypotheses without being overwhelmed by the density of the subsequent graph. We extend the previously developed TranscriptomeBrowser database with a set of tables containing 1,594,978 human and mouse molecular interactions. The database includes: (i) predicted regulatory interactions (computed by scanning vertebrate alignments with a set of 1,213 position weight matrices), (ii) potential regulatory interactions inferred from systematic analysis of ChIP-seq experiments, (iii) regulatory interactions curated from the literature, (iv) predicted post-transcriptional regulation by micro-RNA, (v) protein kinase-substrate interactions and (vi) physical protein-protein interactions. In order to easily retrieve and efficiently analyze these interactions, we developed In-teractomeBrowser, a graph-based knowledge browser that comes as a plug-in for Transcriptome-Browser. The first objective of InteractomeBrowser is to provide a user-friendly tool to get new insight into any gene list by providing a context-specific display of putative regulatory and physical interactions. To achieve this, InteractomeBrowser relies on a "cell compartments-based layout" that makes use of a subset of the Gene Ontology to map gene products onto relevant cell compartments. This layout is particularly powerful for visual integration of heterogeneous biological information

Study of oral clefts: Indication of gene-environment interaction

Energy Technology Data Exchange (ETDEWEB)

Hwang, S.J.; Beaty, T.H.; Panny, S. [Johns Hopkins Univ., Baltimore, MD (United States)] [and others

1994-09-01

In this study of infants with isolated birth defects, 69 cleft palate-only (CPO) cases, 114 cleft lip with or without palate (CL/P), and 284 controls with non-cleft birth defects (all born in Maryland during 1984-1992) were examined to test for associations among genetic markers and different oral clefts. Modest associations were found between transforming growth factor {alpha} (TGF{alpha}) marker and CPO, as well as that between D17S579 (Mfd188) and CL/P in this study. The association between TGF{alpha} marker and CPO reflects a statistical interaction between mother`s smoking and child`s TGF{alpha} genotype. A significantly higher risk of CPO was found among those reporting maternal smoking during pregnancy and carrying less common TGF{alpha} TaqI allele (odds ratio=7.02 with 95% confidence interval 1.8-27.6). This gene-environment interaction was also found among those who reported no family history of any type of birth defect (odds ratio=5.60 with 95% confidence interval 1.4-22.9). Similar associations were seen for CL/P, but these were not statistically significant.

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

Science.gov (United States)

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.

A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties of functional gene network

Directory of Open Access Journals (Sweden)

Han Kyungsook

2010-06-01

Full Text Available Abstract Background Genetic interaction profiles are highly informative and helpful for understanding the functional linkages between genes, and therefore have been extensively exploited for annotating gene functions and dissecting specific pathway structures. However, our understanding is rather limited to the relationship between double concurrent perturbation and various higher level phenotypic changes, e.g. those in cells, tissues or organs. Modifier screens, such as synthetic genetic arrays (SGA can help us to understand the phenotype caused by combined gene mutations. Unfortunately, exhaustive tests on all possible combined mutations in any genome are vulnerable to combinatorial explosion and are infeasible either technically or financially. Therefore, an accurate computational approach to predict genetic interaction is highly desirable, and such methods have the potential of alleviating the bottleneck on experiment design. Results In this work, we introduce a computational systems biology approach for the accurate prediction of pairwise synthetic genetic interactions (SGI. First, a high-coverage and high-precision functional gene network (FGN is constructed by integrating protein-protein interaction (PPI, protein complex and gene expression data; then, a graph-based semi-supervised learning (SSL classifier is utilized to identify SGI, where the topological properties of protein pairs in weighted FGN is used as input features of the classifier. We compare the proposed SSL method with the state-of-the-art supervised classifier, the support vector machines (SVM, on a benchmark dataset in S. cerevisiae to validate our method's ability to distinguish synthetic genetic interactions from non-interaction gene pairs. Experimental results show that the proposed method can accurately predict genetic interactions in S. cerevisiae (with a sensitivity of 92% and specificity of 91%. Noticeably, the SSL method is more efficient than SVM, especially for

Dopamine en overmatig alcoholgebruik: genen in interactie met hun omgeving [Dopamine and excessive alcohol consumption: how genes interact with their environment

NARCIS (Netherlands)

Schellekens, A.F.A.; Scholte, R.H.J.; Engels, R.C.M.E.; Verkes, R.J.

2013-01-01

background Hereditary factors account for approximately 50% of the risk of developing alcohol dependence. Genes that affect the dopamine function in the brain have been extensively studied as candidate genes. aim To present the results of recent Dutch studies on the interaction between genes and

APOA2, dietary fat and body mass index: replication of a gene-diet interaction in three independent populations

Science.gov (United States)

Background: Nutrigenetics studies the role of genetic variation on interactions between diet and health aimed at providing more personalized dietary advice. However, replication has been very low and our aim was to study the interaction between a functional polymorphism of the APOA2 gene, food intak...

Mining tissue specificity, gene connectivity and disease association to reveal a set of genes that modify the action of disease causing genes

Directory of Open Access Journals (Sweden)

Reverter Antonio

2008-09-01

Full Text Available Abstract Background The tissue specificity of gene expression has been linked to a number of significant outcomes including level of expression, and differential rates of polymorphism, evolution and disease association. Recent studies have also shown the importance of exploring differential gene connectivity and sequence conservation in the identification of disease-associated genes. However, no study relates gene interactions with tissue specificity and disease association. Methods We adopted an a priori approach making as few assumptions as possible to analyse the interplay among gene-gene interactions with tissue specificity and its subsequent likelihood of association with disease. We mined three large datasets comprising expression data drawn from massively parallel signature sequencing across 32 tissues, describing a set of 55,606 true positive interactions for 7,197 genes, and microarray expression results generated during the profiling of systemic inflammation, from which 126,543 interactions among 7,090 genes were reported. Results Amongst the myriad of complex relationships identified between expression, disease, connectivity and tissue specificity, some interesting patterns emerged. These include elevated rates of expression and network connectivity in housekeeping and disease-associated tissue-specific genes. We found that disease-associated genes are more likely to show tissue specific expression and most frequently interact with other disease genes. Using the thresholds defined in these observations, we develop a guilt-by-association algorithm and discover a group of 112 non-disease annotated genes that predominantly interact with disease-associated genes, impacting on disease outcomes. Conclusion We conclude that parameters such as tissue specificity and network connectivity can be used in combination to identify a group of genes, not previously confirmed as disease causing, that are involved in interactions with disease causing

A Multiple Interaction Analysis Reveals ADRB3 as a Potential Candidate for Gallbladder Cancer Predisposition via a Complex Interaction with Other Candidate Gene Variations

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Rajani Rai

2015-11-01

Full Text Available Gallbladder cancer is the most common and a highly aggressive biliary tract malignancy with a dismal outcome. The pathogenesis of the disease is multifactorial, comprising the combined effect of multiple genetic variations of mild consequence along with numerous dietary and environmental risk factors. Previously, we demonstrated the association of several candidate gene variations with GBC risk. In this study, we aimed to identify the combination of gene variants and their possible interactions contributing towards genetic susceptibility of GBC. Here, we performed Multifactor-Dimensionality Reduction (MDR and Classification and Regression Tree Analysis (CRT to investigate the gene–gene interactions and the combined effect of 14 SNPs in nine genes (DR4 (rs20576, rs6557634; FAS (rs2234767; FASL (rs763110; DCC (rs2229080, rs4078288, rs7504990, rs714; PSCA (rs2294008, rs2978974; ADRA2A (rs1801253; ADRB1 (rs1800544; ADRB3 (rs4994; CYP17 (rs2486758 involved in various signaling pathways. Genotyping was accomplished by PCR-RFLP or Taqman allelic discrimination assays. SPSS software version 16.0 and MDR software version 2.0 were used for all the statistical analysis. Single locus investigation demonstrated significant association of DR4 (rs20576, rs6557634, DCC (rs714, rs2229080, rs4078288 and ADRB3 (rs4994 polymorphisms with GBC risk. MDR analysis revealed ADRB3 (rs4994 to be crucial candidate in GBC susceptibility that may act either alone (p < 0.0001, CVC = 10/10 or in combination with DCC (rs714 and rs2229080, p < 0.0001, CVC = 9/10. Our CRT results are in agreement with the above findings. Further, in-silico results of studied SNPs advocated their role in splicing, transcriptional and/or protein coding regulation. Overall, our result suggested complex interactions amongst the studied SNPs and ADRB3 rs4994 as candidate influencing GBC susceptibility.

Interaction between the SLC19A1 gene and maternal first trimester fever on offspring neural tube defects.

Science.gov (United States)

Pei, Lijun; Zhu, Huiping; Ye, Rongwei; Wu, Jilei; Liu, Jianmeng; Ren, Aiguo; Li, Zhiwen; Zheng, Xiaoying

2015-01-01

Many studies have indicated that the reduced folate carrier gene (SLC19A1) is associated with an increased risk of neural tube defects (NTDs). However, the interaction between the SLC19A1 gene variant and maternal fever exposure and NTD risk remains unknown. The aim of this study was to investigate whether the risk for NTDs was influenced by the interactions between the SLC19A1 (rs1051266) variant and maternal first trimester fever. We investigated the potential interaction between maternal first trimester fever and maternal or offspring SLC19A1 polymorphism through a population-based case-control study. One hundred and four nuclear families with NTDs and 100 control families with nonmal newborns were included in the study. SLC19A1 polymorphism was determined using polymerase chain reaction-restricted fragment length polymorphism. Mothers who had the GG/GA genotype and first trimester fever had an elevated risk of NTDs (adjusted odds ratio, 11.73; 95% confidence interval, 3.02-45.58) as compared to absence of maternal first trimester fever and AA genotype after adjusting for maternal education, paternal education, and age, and had a significant interactive coefficient (γ = 3.17) between maternal GG/GA genotype and first trimester fever. However, there was no interaction between offspring's GG/GA genotype and maternal first trimester fever (the interactive coefficient γ = 0.97) after adjusting for confounding factors. Our findings suggested that the risk of NTDs was potentially influenced by a gene-environment interaction between maternal SLC19A1 rs1051266 GG/GA genotype and first trimester fever. Maternal GG/GA genotype may strengthen the effect of maternal fever exposure on NTD risk in this Chinese population. © 2014 Wiley Periodicals, Inc.

Metabolic syndrome, diabetes and atherosclerosis: Influence of gene-environment interaction

Energy Technology Data Exchange (ETDEWEB)

Andreassi, Maria Grazia, E-mail: andreas@ifc.cnr.it [CNR Institute of Clinical Physiology, G. Pasquinucci Hospital, Via Aurelia Sud, Massa (Italy)

2009-07-10

Despite remarkable progress in diagnosis and understanding of risk factors, cardiovascular disease (CVD) remains still the leading cause of morbidity and mortality in the world's developed countries. The metabolic syndrome, a cluster of risk factors (visceral obesity, insulin resistance, dyslipidaemia, and hypertension), is increasingly being recognized as a new risk factor for type 2 diabetes and atherosclerotic cardiovascular disease. Nevertheless, there is wide variation in both the occurrence of disease and age of onset, even in individuals who display very similar risk profiles. There is now compelling evidence that a complex interplay between genetic determinants and environmental factors (still largely unknown) is the reason for this large inter-individual variation in disease susceptibility. The purpose of the present review is to describe the current status of our knowledge concerning the gene-environment interactions potentially implicated in the pathogenesis of metabolic syndrome, diabetes and cardiovascular disease. It focuses predominantly on studies of genes (peroxisome proliferator-activated receptor-gamma, alcohol dehydrogenase type 1C, apolipoprotein E, glutathione S-transferases T1 and M1) that are known to be modified by dietary and lifestyle habits (fat diet, intake of alcohol and smoking habit). It also describes the limited current understanding of the role of genetic variants of xenobiotic metabolizing enzymes and their interactions with environmental toxicants. Additional studies are needed in order to clarify whether inter-individual differences in detoxification of environmental toxicants may have an essential role in the development of CVD and contribute to the emerging field of 'environmental cardiology'. Such knowledge may be particularly relevant for improving cardiovascular risk stratification and conceiving the development of 'personalized intervention program'.

Metabolic syndrome, diabetes and atherosclerosis: Influence of gene-environment interaction

International Nuclear Information System (INIS)

Andreassi, Maria Grazia

2009-01-01

Despite remarkable progress in diagnosis and understanding of risk factors, cardiovascular disease (CVD) remains still the leading cause of morbidity and mortality in the world's developed countries. The metabolic syndrome, a cluster of risk factors (visceral obesity, insulin resistance, dyslipidaemia, and hypertension), is increasingly being recognized as a new risk factor for type 2 diabetes and atherosclerotic cardiovascular disease. Nevertheless, there is wide variation in both the occurrence of disease and age of onset, even in individuals who display very similar risk profiles. There is now compelling evidence that a complex interplay between genetic determinants and environmental factors (still largely unknown) is the reason for this large inter-individual variation in disease susceptibility. The purpose of the present review is to describe the current status of our knowledge concerning the gene-environment interactions potentially implicated in the pathogenesis of metabolic syndrome, diabetes and cardiovascular disease. It focuses predominantly on studies of genes (peroxisome proliferator-activated receptor-gamma, alcohol dehydrogenase type 1C, apolipoprotein E, glutathione S-transferases T1 and M1) that are known to be modified by dietary and lifestyle habits (fat diet, intake of alcohol and smoking habit). It also describes the limited current understanding of the role of genetic variants of xenobiotic metabolizing enzymes and their interactions with environmental toxicants. Additional studies are needed in order to clarify whether inter-individual differences in detoxification of environmental toxicants may have an essential role in the development of CVD and contribute to the emerging field of 'environmental cardiology'. Such knowledge may be particularly relevant for improving cardiovascular risk stratification and conceiving the development of 'personalized intervention program'.

Identification of New Genetic Susceptibility Loci for Breast Cancer Through Consideration of Gene-Environment Interactions

Science.gov (United States)

Schoeps, Anja; Rudolph, Anja; Seibold, Petra; Dunning, Alison M.; Milne, Roger L.; Bojesen, Stig E.; Swerdlow, Anthony; Andrulis, Irene; Brenner, Hermann; Behrens, Sabine; Orr, Nicholas; Jones, Michael; Ashworth, Alan; Li, Jingmei; Cramp, Helen; Connley, Dan; Czene, Kamila; Darabi, Hatef; Chanock, Stephen J.; Lissowska, Jolanta; Figueroa, Jonine D.; Knight, Julia; Glendon, Gord; Mulligan, Anna M.; Dumont, Martine; Severi, Gianluca; Baglietto, Laura; Olson, Janet; Vachon, Celine; Purrington, Kristen; Moisse, Matthieu; Neven, Patrick; Wildiers, Hans; Spurdle, Amanda; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana M.; Hamann, Ute; Ko, Yon-Dschun; Dieffenbach, Aida K.; Arndt, Volker; Stegmaier, Christa; Malats, Núria; Arias Perez, JoséI.; Benítez, Javier; Flyger, Henrik; Nordestgaard, Børge G.; Truong, Théresè; Cordina-Duverger, Emilie; Menegaux, Florence; Silva, Isabel dos Santos; Fletcher, Olivia; Johnson, Nichola; Häberle, Lothar; Beckmann, Matthias W.; Ekici, Arif B.; Braaf, Linde; Atsma, Femke; van den Broek, Alexandra J.; Makalic, Enes; Schmidt, Daniel F.; Southey, Melissa C.; Cox, Angela; Simard, Jacques; Giles, Graham G.; Lambrechts, Diether; Mannermaa, Arto; Brauch, Hiltrud; Guénel, Pascal; Peto, Julian; Fasching, Peter A.; Hopper, John; Flesch-Janys, Dieter; Couch, Fergus; Chenevix-Trench, Georgia; Pharoah, Paul D. P.; Garcia-Closas, Montserrat; Schmidt, Marjanka K.; Hall, Per; Easton, Douglas F.; Chang-Claude, Jenny

2014-01-01

Genes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene-environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P-values = 3 × 10−07), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m2 (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m2 or higher (OR = 0.89, 95% CI 0.72–1.11, P for interaction = 3.2 × 10−05). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci. PMID:24248812

The Integration of Epistasis Network and Functional Interactions in a GWAS Implicates RXR Pathway Genes in the Immune Response to Smallpox Vaccine.

Directory of Open Access Journals (Sweden)

Brett A McKinney

Full Text Available Although many diseases and traits show large heritability, few genetic variants have been found to strongly separate phenotype groups by genotype. Complex regulatory networks of variants and expression of multiple genes lead to small individual-variant effects and difficulty replicating the effect of any single variant in an affected pathway. Interaction network modeling of GWAS identifies effects ignored by univariate models, but population differences may still cause specific genes to not replicate. Integrative network models may help detect indirect effects of variants in the underlying biological pathway. In this study, we used gene-level functional interaction information from the Integrative Multi-species Prediction (IMP tool to reveal important genes associated with a complex phenotype through evidence from epistasis networks and pathway enrichment. We test this method for augmenting variant-based network analyses with functional interactions by applying it to a smallpox vaccine immune response GWAS. The integrative analysis spotlights the role of genes related to retinoid X receptor alpha (RXRA, which has been implicated in a previous epistasis network analysis of smallpox vaccine.

Biomarker Identification for Prostate Cancer and Lymph Node Metastasis from Microarray Data and Protein Interaction Network Using Gene Prioritization Method

Directory of Open Access Journals (Sweden)

Carlos Roberto Arias

2012-01-01

Full Text Available Finding a genetic disease-related gene is not a trivial task. Therefore, computational methods are needed to present clues to the biomedical community to explore genes that are more likely to be related to a specific disease as biomarker. We present biomarker identification problem using gene prioritization method called gene prioritization from microarray data based on shortest paths, extended with structural and biological properties and edge flux using voting scheme (GP-MIDAS-VXEF. The method is based on finding relevant interactions on protein interaction networks, then scoring the genes using shortest paths and topological analysis, integrating the results using a voting scheme and a biological boosting. We applied two experiments, one is prostate primary and normal samples and the other is prostate primary tumor with and without lymph nodes metastasis. We used 137 truly prostate cancer genes as benchmark. In the first experiment, GP-MIDAS-VXEF outperforms all the other state-of-the-art methods in the benchmark by retrieving the truest related genes from the candidate set in the top 50 scores found. We applied the same technique to infer the significant biomarkers in prostate cancer with lymph nodes metastasis which is not established well.

Association and Interaction Effect of AGTR1 and AGTR2 Gene Polymorphisms with Dietary Pattern on Metabolic Risk Factors of Cardiovascular Disease in Malaysian Adults

OpenAIRE

Yap, Roseline Wai Kuan; Shidoji, Yoshihiro; Yap, Wai Sum; Masaki, Motofumi

2017-01-01

Gene-diet interaction using a multifactorial approach is preferred to study the multiple risk factors of cardiovascular disease (CVD). This study examined the association and gene-diet interaction effects of the angiotensin II type 1 receptor (AGTR1) gene (rs5186), and type 2 receptor (AGTR2) gene (rs1403543) polymorphisms on metabolic risk factors of CVD in Malaysian adults. CVD parameters (BMI, blood pressure, glycated hemoglobin, total cholesterol (TC), triglycerides, low-density lipoprote...

GeneWiz browser: An Interactive Tool for Visualizing Sequenced Chromosomes

DEFF Research Database (Denmark)

Hallin, Peter Fischer; Stærfeldt, Hans Henrik; Rotenberg, Eva

2009-01-01

, standard atlases are pre-generated for all prokaryotic genomes available in GenBank, providing a fast overview of all available genomes, including recently deposited genome sequences. The tool is available online from http://www.cbs.dtu.dk/services/gwBrowser. [Supplemental material including interactive...... atlases is available online at http://www.cbs.dtu.dk/services/gwBrowser/suppl/]....... readability and increased functionality compared to other browsers. The tool allows the user to select the display of various genomic features, color setting and data ranges. Custom numerical data can be added to the plot, allowing for example visualization of gene expression and regulation data. Further...

Global changes in gene expression during compatible and incompatible interactions of cowpea (Vigna unguiculata L.) with the root parasitic angiosperm Striga gesnerioides.

Science.gov (United States)

Huang, Kan; Mellor, Karolina E; Paul, Shom N; Lawson, Mark J; Mackey, Aaron J; Timko, Michael P

2012-08-17

Cowpea, Vigna unguiculata L. Walp., is one of the most important food and forage legumes in the semi-arid tropics. While most domesticated forms of cowpea are susceptible to the root parasitic weed Striga gesnerioides, several cultivars have been identified that show race-specific resistance. Cowpea cultivar B301 contains the RSG3-301 gene for resistance to S. gesnerioides race SG3, but is susceptible to race SG4z. When challenged by SG3, roots of cultivar B301 develop a strong resistance response characterized by a hypersensitive reaction and cell death at the site of parasite attachment. In contrast, no visible response occurs in B301 roots parasitized by SG4z. Gene expression in the roots of the cowpea cultivar B301 during compatible (susceptible) and incompatible (resistant) interactions with S. gesnerioides races SG4z and SG3, respectively, were investigated at the early (6 days post-inoculation (dpi)) and late (13 dpi) stages of the resistance response using a Nimblegen custom design cowpea microarray. A total of 111 genes were differentially expressed in B301 roots at 6 dpi; this number increased to 2102 genes at 13 dpi. At 13 dpi, a total of 1944 genes were differentially expressed during compatible (susceptible) interactions of B301 with SG4z. Genes and pathways involved in signal transduction, programmed cell death and apoptosis, and defense response to biotic and abiotic stress were differentially expressed in the early resistance response; at the later time point, enrichment was primarily for defense-related gene expression, and genes encoding components of lignifications and secondary wall formation. In compatible interactions (B301-SG4z), multiple defense pathways were repressed, including those involved in lignin biosynthesis and secondary cell wall modifications, while cellular transport processes for nitrogen and sulfur were increased. Distinct changes in global gene expression profiles occur in host roots following successful and unsuccessful

Assessing the joint effect of population stratification and sample selection in studies of gene-gene (environment interactions

Directory of Open Access Journals (Sweden)

Cheng KF

2012-01-01

Full Text Available Abstract Background It is well known that the presence of population stratification (PS may cause the usual test in case-control studies to produce spurious gene-disease associations. However, the impact of the PS and sample selection (SS is less known. In this paper, we provide a systematic study of the joint effect of PS and SS under a more general risk model containing genetic and environmental factors. We provide simulation results to show the magnitude of the bias and its impact on type I error rate of the usual chi-square test under a wide range of PS level and selection bias. Results The biases to the estimation of main and interaction effect are quantified and then their bounds derived. The estimated bounds can be used to compute conservative p-values for the association test. If the conservative p-value is smaller than the significance level, we can safely claim that the association test is significant regardless of the presence of PS or not, or if there is any selection bias. We also identify conditions for the null bias. The bias depends on the allele frequencies, exposure rates, gene-environment odds ratios and disease risks across subpopulations and the sampling of the cases and controls. Conclusion Our results show that the bias cannot be ignored even the case and control data were matched in ethnicity. A real example is given to illustrate application of the conservative p-value. These results are useful to the genetic association studies of main and interaction effects.

BPhyOG: An interactive server for genome-wide inference of bacterial phylogenies based on overlapping genes

Directory of Open Access Journals (Sweden)

Lin Kui

2007-07-01

Full Text Available Abstract Background Overlapping genes (OGs in bacterial genomes are pairs of adjacent genes of which the coding sequences overlap partly or entirely. With the rapid accumulation of sequence data, many OGs in bacterial genomes have now been identified. Indeed, these might prove a consistent feature across all microbial genomes. Our previous work suggests that OGs can be considered as robust markers at the whole genome level for the construction of phylogenies. An online, interactive web server for inferring phylogenies is needed for biologists to analyze phylogenetic relationships among a set of bacterial genomes of interest. Description BPhyOG is an online interactive server for reconstructing the phylogenies of completely sequenced bacterial genomes on the basis of their shared overlapping genes. It provides two tree-reconstruction methods: Neighbor Joining (NJ and Unweighted Pair-Group Method using Arithmetic averages (UPGMA. Users can apply the desired method to generate phylogenetic trees, which are based on an evolutionary distance matrix for the selected genomes. The distance between two genomes is defined by the normalized number of their shared OG pairs. BPhyOG also allows users to browse the OGs that were used to infer the phylogenetic relationships. It provides detailed annotation for each OG pair and the features of the component genes through hyperlinks. Users can also retrieve each of the homologous OG pairs that have been determined among 177 genomes. It is a useful tool for analyzing the tree of life and overlapping genes from a genomic standpoint. Conclusion BPhyOG is a useful interactive web server for genome-wide inference of any potential evolutionary relationship among the genomes selected by users. It currently includes 177 completely sequenced bacterial genomes containing 79,855 OG pairs, the annotation and homologous OG pairs of which are integrated comprehensively. The reliability of phylogenies complemented by

Interactive visualization of gene regulatory networks with associated gene expression time series data

NARCIS (Netherlands)

Westenberg, M.A.; Hijum, van S.A.F.T.; Lulko, A.T.; Kuipers, O.P.; Roerdink, J.B.T.M.; Linsen, L.; Hagen, H.; Hamann, B.

2008-01-01

We present GENeVis, an application to visualize gene expression time series data in a gene regulatory network context. This is a network of regulator proteins that regulate the expression of their respective target genes. The networks are represented as graphs, in which the nodes represent genes,

Effects of circadian clock genes and health-related behavior on metabolic syndrome in a Taiwanese population: Evidence from association and interaction analysis.

Directory of Open Access Journals (Sweden)

Eugene Lin

Full Text Available Increased risk of developing metabolic syndrome (MetS has been associated with the circadian clock genes. In this study, we assessed whether 29 circadian clock-related genes (including ADCYAP1, ARNTL, ARNTL2, BHLHE40, CLOCK, CRY1, CRY2, CSNK1D, CSNK1E, GSK3B, HCRTR2, KLF10, NFIL3, NPAS2, NR1D1, NR1D2, PER1, PER2, PER3, REV1, RORA, RORB, RORC, SENP3, SERPINE1, TIMELESS, TIPIN, VIP, and VIPR2 are associated with MetS and its individual components independently and/or through complex interactions in a Taiwanese population. We also analyzed the interactions between environmental factors and these genes in influencing MetS and its individual components. A total of 3,000 Taiwanese subjects from the Taiwan Biobank were assessed in this study. Metabolic traits such as waist circumference, triglyceride, high-density lipoprotein cholesterol, systolic and diastolic blood pressure, and fasting glucose were measured. Our data showed a nominal association of MetS with several single nucleotide polymorphisms (SNPs in five key circadian clock genes including ARNTL, GSK3B, PER3, RORA, and RORB; but none of these SNPs persisted significantly after performing Bonferroni correction. Moreover, we identified the effect of GSK3B rs2199503 on high fasting glucose (P = 0.0002. Additionally, we found interactions among the ARNTL rs10832020, GSK3B rs2199503, PER3 rs10746473, RORA rs8034880, and RORB rs972902 SNPs influenced MetS (P < 0.001 ~ P = 0.002. Finally, we investigated the influence of interactions between ARNTL rs10832020, GSK3B rs2199503, PER3 rs10746473, and RORB rs972902 with environmental factors such as alcohol consumption, smoking status, and physical activity on MetS and its individual components (P < 0.001 ~ P = 0.002. Our study indicates that circadian clock genes such as ARNTL, GSK3B, PER3, RORA, and RORB genes may contribute to the risk of MetS independently as well as through gene-gene and gene-environment interactions.

The Ethics of Translational Science: Imagining Public Benefit in Gene-Environment Interaction Research

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Sara L. Ackerman

2017-06-01

Full Text Available Biomedical research is increasingly informed by expectations of “translation,” which call for the production of scientific knowledge that can be used to create services and products that improve health outcomes. In this paper, we ask how translation, in particular the idea of social responsibility, is understood and enacted in the post-genomic life sciences. Drawing on theories examining what constitutes “good science,” and interviews with 35 investigators who study the role of gene-environment interactions in the etiology of cancer, diabetes, and cardiovascular disease, we describe the dynamic and unsettled ethics of translational science through which the expected social value of scientific knowledge about complex disease causation is negotiated. To describe how this ethics is formed, we first discuss the politics of knowledge production in interdisciplinary research collectives. Researchers described a commitment to working across disciplines to examine a wide range of possible causes of disease, but they also pointed to persistent disciplinary and ontological divisions that rest on the dominance of molecular conceptions of disease risk. The privileging of molecular-level causation shapes and constrains the kinds of knowledge that can be created about gene-environment interactions. We then turn to scientists’ ideas about how this knowledge should be used, including personalized prevention strategies, targeted therapeutics, and public policy interventions. Consensus about the relative value of these anticipated translations was elusive, and many scientists agreed that gene-environment interaction research is part of a shift in biomedical research away from considering important social, economic, political and historical causes of disease and disease disparities. We conclude by urging more explicit engagement with questions about the ethics of translational science in the post-genomic life sciences. This would include a consideration

The ASK1 gene regulates development and interacts with the UFO gene to control floral organ identity in Arabidopsis.

Science.gov (United States)

Zhao, D; Yang, M; Solava, J; Ma, H

1999-09-01

Normal flower development likely requires both specific and general regulators. We have isolated an Arabidopsis mutant ask1-1 (for -Arabidopsis skp1-like1-1), which exhibits defects in both vegetative and reproductive development. In the ask1-1mutant, rosette leaf growth is reduced, resulting in smaller than normal rosette leaves, and internodes in the floral stem are shorter than normal. Examination of cell sizes in these organs indicates that cell expansion is normal in the mutant, but cell number is reduced. In the mutant, the numbers of petals and stamens are reduced, and many flowers have one or more petals with a reduced size. In addition, all mutant flowers have short stamen filaments. Furthermore, petal/stamen chimeric organs are found in many flowers. These results indicate that the ASK1 gene affects the size of vegetative and floral organs. The ask1 floral phenotype resembles somewhat that of the Arabidopsis ufo mutants in that both genes affect whorls 2 and 3. We therefore tested for possible interactions between ASK1 and UFO by analyzing the phenotypes of ufo-2 ask1-1 double mutant plants. In these plants, vegetative development is similar to that of the ask1-1 single mutant, whereas the floral defects are more severe than those in either single mutant. Interior to the first whorl, the double mutant flowers have more sepals or sepal-like organs than are found in ufo-2, and less petals than ask1-1. Our results suggest that ASK1 interacts with UFO to control floral organ identity in whorls 2 and 3. This is very intriguing because ASK1 is very similar in sequence to the yeast SKP1 protein and UFO contains an F-box, a motif known to interact with SKP1 in yeast. Although the precise mechanism of ASK1 and UFO action is unknown, our results support the hypothesis that these two proteins physically interact in vivo. Copyright 1999 Wiley-Liss, Inc.

The interaction of corticotropin-releasing hormone receptor gene and early life stress on emotional empathy.

Science.gov (United States)

Grimm, Simone; Wirth, Katharina; Fan, Yan; Weigand, Anne; Gärtner, Matti; Feeser, Melanie; Dziobek, Isabel; Bajbouj, Malek; Aust, Sabine

2017-06-30

Early life stress (ELS) is associated with increased vulnerability for depression, changes to the corticotropin-releasing hormone (CRH) system and structural and functional changes in hippocampus. Single nucleotide polymorphisms in the CRH receptor 1 (CRHR1) gene interact with ELS to predict depression, cognitive functions and hippocampal activity. Social cognition has been related to hippocampal function and might be crucial for maintaining mental health. However, the interaction of CRHR1 gene variation and ELS on social cognition has not been investigated yet. We assessed social cognition in 502 healthy subjects to test effects of ELS and the CRHR1 gene. Participants were genotyped for rs110402 and rs242924. ELS was assessed by Childhood Trauma Questionnaire, social cognition was measured via Multifaceted Empathy Test and Empathy Quotient. Severity of ELS was associated with decreased emotional, but not cognitive empathy. Subjects with the common homozygous GG GG genotype showed decreased implicit emotional empathy after ELS exposure regardless of its severity. The results reveal that specific CRHR1 polymorphisms moderate the effect of ELS on emotional empathy. Exposure to ELS in combination with a vulnerable genotype results in impaired emotional empathy in adulthood, which might represent an early marker of increased vulnerability after ELS. Copyright © 2017 Elsevier B.V. All rights reserved.

TranscriptomeBrowser 3.0: introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks

Directory of Open Access Journals (Sweden)

Lepoivre Cyrille

2012-01-01

Full Text Available Abstract Background Deciphering gene regulatory networks by in silico approaches is a crucial step in the study of the molecular perturbations that occur in diseases. The development of regulatory maps is a tedious process requiring the comprehensive integration of various evidences scattered over biological databases. Thus, the research community would greatly benefit from having a unified database storing known and predicted molecular interactions. Furthermore, given the intrinsic complexity of the data, the development of new tools offering integrated and meaningful visualizations of molecular interactions is necessary to help users drawing new hypotheses without being overwhelmed by the density of the subsequent graph. Results We extend the previously developed TranscriptomeBrowser database with a set of tables containing 1,594,978 human and mouse molecular interactions. The database includes: (i predicted regulatory interactions (computed by scanning vertebrate alignments with a set of 1,213 position weight matrices, (ii potential regulatory interactions inferred from systematic analysis of ChIP-seq experiments, (iii regulatory interactions curated from the literature, (iv predicted post-transcriptional regulation by micro-RNA, (v protein kinase-substrate interactions and (vi physical protein-protein interactions. In order to easily retrieve and efficiently analyze these interactions, we developed In-teractomeBrowser, a graph-based knowledge browser that comes as a plug-in for Transcriptome-Browser. The first objective of InteractomeBrowser is to provide a user-friendly tool to get new insight into any gene list by providing a context-specific display of putative regulatory and physical interactions. To achieve this, InteractomeBrowser relies on a "cell compartments-based layout" that makes use of a subset of the Gene Ontology to map gene products onto relevant cell compartments. This layout is particularly powerful for visual integration

Gene-Environment Interaction in Parkinson's Disease

DEFF Research Database (Denmark)

Chuang, Yu-Hsuan; Lill, Christina M; Lee, Pei-Chen

2016-01-01

BACKGROUND AND PURPOSE: Drinking caffeinated coffee has been reported to provide protection against Parkinson's disease (PD). Caffeine is an adenosine A2A receptor (encoded by the gene ADORA2A) antagonist that increases dopaminergic neurotransmission and Cytochrome P450 1A2 (gene: CYP1A2...

The apolipoprotein L family of programmed cell death and immunity genes rapidly evolved in primates at discrete sites of host-pathogen interactions.

Science.gov (United States)

Smith, Eric E; Malik, Harmit S

2009-05-01

Apolipoprotein L1 (APOL1) is a human protein that confers immunity to Trypanosoma brucei infections but can be countered by a trypanosome-encoded antagonist SRA. APOL1 belongs to a family of programmed cell death genes whose proteins can initiate host apoptosis or autophagic death. We report here that all six members of the APOL gene family (APOL1-6) present in humans have rapidly evolved in simian primates. APOL6, furthermore, shows evidence of an adaptive sweep during recent human evolution. In each APOL gene tested, we found rapidly evolving codons in or adjacent to the SRA-interacting protein domain (SID), which is the domain of APOL1 that interacts with SRA. In APOL6, we also found a rapidly changing 13-amino-acid cluster in the membrane-addressing domain (MAD), which putatively functions as a pH sensor and regulator of cell death. We predict that APOL genes are antagonized by pathogens by at least two distinct mechanisms: SID antagonists, which include SRA, that interact with the SID of various APOL proteins, and MAD antagonists that interact with the MAD hinge base of APOL6. These antagonists either block or prematurely cause APOL-mediated programmed cell death of host cells to benefit the infecting pathogen. These putative interactions must occur inside host cells, in contrast to secreted APOL1 that trafficks to the trypanosome lysosome. Hence, the dynamic APOL gene family appears to be an important link between programmed cell death of host cells and immunity to pathogens.

Multiple analytical approaches reveal distinct gene-environment interactions in smokers and non smokers in lung cancer.

Directory of Open Access Journals (Sweden)

Rakhshan Ihsan

Full Text Available Complex disease such as cancer results from interactions of multiple genetic and environmental factors. Studying these factors singularly cannot explain the underlying pathogenetic mechanism of the disease. Multi-analytical approach, including logistic regression (LR, classification and regression tree (CART and multifactor dimensionality reduction (MDR, was applied in 188 lung cancer cases and 290 controls to explore high order interactions among xenobiotic metabolizing genes and environmental risk factors. Smoking was identified as the predominant risk factor by all three analytical approaches. Individually, CYP1A1*2A polymorphism was significantly associated with increased lung cancer risk (OR = 1.69;95%CI = 1.11-2.59,p = 0.01, whereas EPHX1 Tyr113His and SULT1A1 Arg213His conferred reduced risk (OR = 0.40;95%CI = 0.25-0.65,p<0.001 and OR = 0.51;95%CI = 0.33-0.78,p = 0.002 respectively. In smokers, EPHX1 Tyr113His and SULT1A1 Arg213His polymorphisms reduced the risk of lung cancer, whereas CYP1A1*2A, CYP1A1*2C and GSTP1 Ile105Val imparted increased risk in non-smokers only. While exploring non-linear interactions through CART analysis, smokers carrying the combination of EPHX1 113TC (Tyr/His, SULT1A1 213GG (Arg/Arg or AA (His/His and GSTM1 null genotypes showed the highest risk for lung cancer (OR = 3.73;95%CI = 1.33-10.55,p = 0.006, whereas combined effect of CYP1A1*2A 6235CC or TC, SULT1A1 213GG (Arg/Arg and betel quid chewing showed maximum risk in non-smokers (OR = 2.93;95%CI = 1.15-7.51,p = 0.01. MDR analysis identified two distinct predictor models for the risk of lung cancer in smokers (tobacco chewing, EPHX1 Tyr113His, and SULT1A1 Arg213His and non-smokers (CYP1A1*2A, GSTP1 Ile105Val and SULT1A1 Arg213His with testing balance accuracy (TBA of 0.6436 and 0.6677 respectively. Interaction entropy interpretations of MDR results showed non-additive interactions of tobacco chewing with

Gene-environment interaction in the onset of eczema in infancy

DEFF Research Database (Denmark)

Bisgaard, Hans; Simpson, Angela; Palmer, Colin N A

2008-01-01

BACKGROUND: Loss-of-function variants in the gene encoding filaggrin (FLG) are major determinants of eczema. We hypothesized that weakening of the physical barrier in FLG-deficient individuals may potentiate the effect of environmental exposures. Therefore, we investigated whether there is an int......BACKGROUND: Loss-of-function variants in the gene encoding filaggrin (FLG) are major determinants of eczema. We hypothesized that weakening of the physical barrier in FLG-deficient individuals may potentiate the effect of environmental exposures. Therefore, we investigated whether...... there is an interaction between FLG loss-of-function mutations with environmental exposures (pets and dust mites) in relation to the development of eczema. METHODS AND FINDINGS: We used data obtained in early life in a high-risk birth cohort in Denmark and replicated the findings in an unselected birth cohort...... in the United Kingdom. Primary outcome was age of onset of eczema; environmental exposures included pet ownership and mite and pet allergen levels. In Copenhagen (n = 379), FLG mutation increased the risk of eczema during the first year of life (hazard ratio [HR] 2.26, 95% confidence interval [CI] 1.27-4.00, p...

batman Interacts with polycomb and trithorax group genes and encodes a BTB/POZ protein that is included in a complex containing GAGA factor.

Science.gov (United States)

Faucheux, M; Roignant, J-Y; Netter, S; Charollais, J; Antoniewski, C; Théodore, L

2003-02-01

Polycomb and trithorax group genes maintain the appropriate repressed or activated state of homeotic gene expression throughout Drosophila melanogaster development. We have previously identified the batman gene as a Polycomb group candidate since its function is necessary for the repression of Sex combs reduced. However, our present genetic analysis indicates functions of batman in both activation and repression of homeotic genes. The 127-amino-acid Batman protein is almost reduced to a BTB/POZ domain, an evolutionary conserved protein-protein interaction domain found in a large protein family. We show that this domain is involved in the interaction between Batman and the DNA binding GAGA factor encoded by the Trithorax-like gene. The GAGA factor and Batman codistribute on polytene chromosomes, coimmunoprecipitate from nuclear embryonic and larval extracts, and interact in the yeast two-hybrid assay. Batman, together with the GAGA factor, binds to MHS-70, a 70-bp fragment of the bithoraxoid Polycomb response element. This binding, like that of the GAGA factor, requires the presence of d(GA)n sequences. Together, our results suggest that batman belongs to a subset of the Polycomb/trithorax group of genes that includes Trithorax-like, whose products are involved in both activation and repression of homeotic genes.

Carbon: Nitrogen Interaction Regulates Expression of Genes Involved in N-Uptake and Assimilation in Brassica juncea L.

Science.gov (United States)

Goel, Parul; Bhuria, Monika; Kaushal, Mamta

2016-01-01

In plants, several cellular and metabolic pathways interact with each other to regulate processes that are vital for their growth and development. Carbon (C) and Nitrogen (N) are two main nutrients for plants and coordination of C and N pathways is an important factor for maintaining plant growth and development. In the present work, influence of nitrogen and sucrose (C source) on growth parameters and expression of genes involved in nitrogen transport and assimilatory pathways was studied in B. juncea seedlings. For this, B. juncea seedlings were treated with four combinations of C and N source viz., N source alone (-Suc+N), C source alone (+Suc-N), with N and C source (+Suc+N) or without N and C source (-Suc-N). Cotyledon size and shoot length were found to be increased in seedlings, when nitrogen alone was present in the medium. Distinct expression pattern of genes in both, root and shoot tissues was observed in response to exogenously supplied N and C. The presence or depletion of nitrogen alone in the medium leads to severe up- or down-regulation of key genes involved in N-uptake and transport (BjNRT1.1, BjNRT1.8) in root tissue and genes involved in nitrate reduction (BjNR1 and BjNR2) in shoot tissue. Moreover, expression of several genes, like BjAMT1.2, BjAMT2 and BjPK in root and two genes BjAMT2 and BjGS1.1 in shoot were found to be regulated only when C source was present in the medium. Majority of genes were found to respond in root and shoot tissues, when both C and N source were present in the medium, thus reflecting their importance as a signal in regulating expression of genes involved in N-uptake and assimilation. The present work provides insight into the regulation of genes of N-uptake and assimilatory pathway in B. juncea by interaction of both carbon and nitrogen. PMID:27637072

Carbon: Nitrogen Interaction Regulates Expression of Genes Involved in N-Uptake and Assimilation in Brassica juncea L.

Directory of Open Access Journals (Sweden)

Parul Goel

Full Text Available In plants, several cellular and metabolic pathways interact with each other to regulate processes that are vital for their growth and development. Carbon (C and Nitrogen (N are two main nutrients for plants and coordination of C and N pathways is an important factor for maintaining plant growth and development. In the present work, influence of nitrogen and sucrose (C source on growth parameters and expression of genes involved in nitrogen transport and assimilatory pathways was studied in B. juncea seedlings. For this, B. juncea seedlings were treated with four combinations of C and N source viz., N source alone (-Suc+N, C source alone (+Suc-N, with N and C source (+Suc+N or without N and C source (-Suc-N. Cotyledon size and shoot length were found to be increased in seedlings, when nitrogen alone was present in the medium. Distinct expression pattern of genes in both, root and shoot tissues was observed in response to exogenously supplied N and C. The presence or depletion of nitrogen alone in the medium leads to severe up- or down-regulation of key genes involved in N-uptake and transport (BjNRT1.1, BjNRT1.8 in root tissue and genes involved in nitrate reduction (BjNR1 and BjNR2 in shoot tissue. Moreover, expression of several genes, like BjAMT1.2, BjAMT2 and BjPK in root and two genes BjAMT2 and BjGS1.1 in shoot were found to be regulated only when C source was present in the medium. Majority of genes were found to respond in root and shoot tissues, when both C and N source were present in the medium, thus reflecting their importance as a signal in regulating expression of genes involved in N-uptake and assimilation. The present work provides insight into the regulation of genes of N-uptake and assimilatory pathway in B. juncea by interaction of both carbon and nitrogen.

Hybrid male sterility in rice controlled by interaction between divergent alleles of two adjacent genes.

Science.gov (United States)

Long, Yunming; Zhao, Lifeng; Niu, Baixiao; Su, Jing; Wu, Hao; Chen, Yuanling; Zhang, Qunyu; Guo, Jingxin; Zhuang, Chuxiong; Mei, Mantong; Xia, Jixing; Wang, Lan; Wu, Haibin; Liu, Yao-Guang

2008-12-02

Sterility is common in hybrids between divergent populations, such as the indica and japonica subspecies of Asian cultivated rice (Oryza sativa). Although multiple loci for plant hybrid sterility have been identified, it remains unknown how alleles of the loci interact at the molecular level. Here we show that a locus for indica-japonica hybrid male sterility, Sa, comprises two adjacent genes, SaM and SaF, encoding a small ubiquitin-like modifier E3 ligase-like protein and an F-box protein, respectively. Most indica cultivars contain a haplotype SaM(+)SaF(+), whereas all japonica cultivars have SaM(-)SaF(-) that diverged by nucleotide variations in wild rice. Male semi-sterility in this heterozygous complex locus is caused by abortion of pollen carrying SaM(-). This allele-specific gamete elimination results from a selective interaction of SaF(+) with SaM(-), a truncated protein, but not with SaM(+) because of the presence of an inhibitory domain, although SaM(+) is required for this male sterility. Lack of any one of the three alleles in recombinant plants does not produce male sterility. We propose a two-gene/three-component interaction model for this hybrid male sterility system. The findings have implications for overcoming male sterility in inter-subspecific hybrid rice breeding.

Bioinformatics, interaction network analysis, and neural networks to characterize gene expression of radicular cyst and periapical granuloma.

Science.gov (United States)

Poswar, Fabiano de Oliveira; Farias, Lucyana Conceição; Fraga, Carlos Alberto de Carvalho; Bambirra, Wilson; Brito-Júnior, Manoel; Sousa-Neto, Manoel Damião; Santos, Sérgio Henrique Souza; de Paula, Alfredo Maurício Batista; D'Angelo, Marcos Flávio Silveira Vasconcelos; Guimarães, André Luiz Sena

2015-06-01

Bioinformatics has emerged as an important tool to analyze the large amount of data generated by research in different diseases. In this study, gene expression for radicular cysts (RCs) and periapical granulomas (PGs) was characterized based on a leader gene approach. A validated bioinformatics algorithm was applied to identify leader genes for RCs and PGs. Genes related to RCs and PGs were first identified in PubMed, GenBank, GeneAtlas, and GeneCards databases. The Web-available STRING software (The European Molecular Biology Laboratory [EMBL], Heidelberg, Baden-Württemberg, Germany) was used in order to build the interaction map among the identified genes by a significance score named weighted number of links. Based on the weighted number of links, genes were clustered using k-means. The genes in the highest cluster were considered leader genes. Multilayer perceptron neural network analysis was used as a complementary supplement for gene classification. For RCs, the suggested leader genes were TP53 and EP300, whereas PGs were associated with IL2RG, CCL2, CCL4, CCL5, CCR1, CCR3, and CCR5 genes. Our data revealed different gene expression for RCs and PGs, suggesting that not only the inflammatory nature but also other biological processes might differentiate RCs and PGs. Copyright © 2015 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Agrobacterium-mediated transformation of verticillium dahliae with gfr gene to study cotton-pathogen interaction using a novel inoculation method

International Nuclear Information System (INIS)

Li, F.; Bibi, N.; Fan, K.; Wang, M.

2016-01-01

Verticillium dahliae is a soil-born fungal pathogen which causes Verticillium wilt in economically important crops including cotton. We conducted a study to monitor the interaction between the fungus and cotton. V. dahliae was transformed with the gene encoding green fluorescent protein. The gene can be constitutively expressed and fluorescence was clearly visible in both hyphae and spores. Due to heterogeneous gene insertion, the growth rate, colony morphology and pathogenicity of fungus transformants showed differences compared with corresponding wild type. Similarly, quantitative real-time PCR analysis also indicated significant differences in the gene expression among different V. dahliae transformants. To study cotton-pathogen interaction, we devised a novel inoculation method and developed a successful infection by keeping GFP-expressed mycelial plug along with aseptic cotton seedlings. After 6-day inoculation, the LSM microscopic image showed that the fungus rapidly formed a mycelial network on the surface of the stems and colonized into plant tissue, displayed an intercellular infection pattern. The early events during cotton colonization by V. dahliae can be successfully observed in 10 days including the plant growth period. Besides, pathological changes of seedlings like tissue discoloration, wilting, stem dehiscence and necrosis can be clearly observed without the influences of soil and other microbes. This inoculation method provides a rapid, effective and environmental friendly technique for the study of cotton-pathogen interaction and identification of resistant plant cultivars. (author)

Association of apolipoprotein e gene polymorphisms with blood lipids and their interaction with dietary factors

DEFF Research Database (Denmark)

Shatwan, Israa M.; Winther, Kristian Hillert; Ellahi, Basma

2018-01-01

of two single nucleotide polymorphisms (SNPs) at LPL, seven tagging SNPs at the APOE gene, and a common APOE haplotype (two SNPs) with blood lipids, and examined the interaction of these SNPs with dietary factors. Methods: The population studied for this investigation included 660 individuals from...... the Prevention of Cancer by Intervention with Selenium (PRECISE) study who supplied baseline data. The findings of the PRECISE study were further replicated using 1238 individuals from the Caerphilly Prospective cohort (CaPS). Dietary intake was assessed using a validated food-frequency questionnaire (FFQ......Background: Several candidate genes have been identified in relation to lipid metabolism, and among these, lipoprotein lipase (LPL) and apolipoprotein E (APOE) gene polymorphisms are major sources of genetically determined variation in lipid concentrations. This study investigated the association...

The immediate early gene product EGR1 and polycomb group proteins interact in epigenetic programming during chondrogenesis.

Directory of Open Access Journals (Sweden)

Frank Spaapen

Full Text Available Initiation of and progression through chondrogenesis is driven by changes in the cellular microenvironment. At the onset of chondrogenesis, resting mesenchymal stem cells are mobilized in vivo and a complex, step-wise chondrogenic differentiation program is initiated. Differentiation requires coordinated transcriptomic reprogramming and increased progenitor proliferation; both processes require chromatin remodeling. The nature of early molecular responses that relay differentiation signals to chromatin is poorly understood. We here show that immediate early genes are rapidly and transiently induced in response to differentiation stimuli in vitro. Functional ablation of the immediate early factor EGR1 severely deregulates expression of key chondrogenic control genes at the onset of differentiation. In addition, differentiating cells accumulate DNA damage, activate a DNA damage response and undergo a cell cycle arrest and prevent differentiation associated hyper-proliferation. Failed differentiation in the absence of EGR1 affects global acetylation and terminates in overall histone hypermethylation. We report novel molecular connections between EGR1 and Polycomb Group function: Polycomb associated histone H3 lysine27 trimethylation (H3K27me3 blocks chromatin access of EGR1. In addition, EGR1 ablation results in abnormal Ezh2 and Bmi1 expression. Consistent with this functional interaction, we identify a number of co-regulated targets genes in a chondrogenic gene network. We here describe an important role for EGR1 in early chondrogenic epigenetic programming to accommodate early gene-environment interactions in chondrogenesis.

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).

Science.gov (United States)

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.

Media portrayals and health inequalities: a case study of characterizations of Gene x Environment interactions.

Science.gov (United States)

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.

Interactions between the nuclear matrix and an enhancer of the tryptophan oxygenase gene

International Nuclear Information System (INIS)

Kaneoka, Hidenori; Miyake, Katsuhide; Iijima, Shinji

2009-01-01

The gene for tryptophan oxygenase (TO) is expressed in adult hepatocytes in a tissue- and differentiation-specific manner. The TO promoter has two glucocorticoid-responsive elements (GREs), and its expression is regulated by glucocorticoid hormone in the liver. We found a novel GRE in close proximity to a scaffold/matrix attachment region (S/MAR) that was located around -8.5 kb from the transcriptional start site of the TO gene by electrophoretic mobility shift and chromatin immunoprecipitation (ChIP) assays. A combination of nuclear fractionation and quantitative PCR analysis showed that the S/MAR was tethered to the nuclear matrix in both fetal and adult hepatocytes. ChIP assay showed that, in adult hepatocytes, the S/MAR-GRE and the promoter proximal regions interacted with lamin and heterogeneous nuclear ribonucleoprotein U in a dexamethasone dependent manner, but this was not the case in fetal cells, suggesting that developmental stage-specific expression of the TO gene might rely on the binding of the enhancer (the -8.5 kb S/MAR-GRE) and the promoter to the inner nuclear matrix.

Interactions between the nuclear matrix and an enhancer of the tryptophan oxygenase gene

Energy Technology Data Exchange (ETDEWEB)

Kaneoka, Hidenori [Department of Biotechnology, Graduate School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603 (Japan); Miyake, Katsuhide, E-mail: miyake@nubio.nagoya-u.ac.jp [Department of Biotechnology, Graduate School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603 (Japan); Iijima, Shinji [Department of Biotechnology, Graduate School of Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603 (Japan)

2009-10-02

The gene for tryptophan oxygenase (TO) is expressed in adult hepatocytes in a tissue- and differentiation-specific manner. The TO promoter has two glucocorticoid-responsive elements (GREs), and its expression is regulated by glucocorticoid hormone in the liver. We found a novel GRE in close proximity to a scaffold/matrix attachment region (S/MAR) that was located around -8.5 kb from the transcriptional start site of the TO gene by electrophoretic mobility shift and chromatin immunoprecipitation (ChIP) assays. A combination of nuclear fractionation and quantitative PCR analysis showed that the S/MAR was tethered to the nuclear matrix in both fetal and adult hepatocytes. ChIP assay showed that, in adult hepatocytes, the S/MAR-GRE and the promoter proximal regions interacted with lamin and heterogeneous nuclear ribonucleoprotein U in a dexamethasone dependent manner, but this was not the case in fetal cells, suggesting that developmental stage-specific expression of the TO gene might rely on the binding of the enhancer (the -8.5 kb S/MAR-GRE) and the promoter to the inner nuclear matrix.

Discovering implicit entity relation with the gene-citation-gene network.

Directory of Open Access Journals (Sweden)

Min Song

Full Text Available In this paper, we apply the entitymetrics model to our constructed Gene-Citation-Gene (GCG network. Based on the premise there is a hidden, but plausible, relationship between an entity in one article and an entity in its citing article, we constructed a GCG network of gene pairs implicitly connected through citation. We compare the performance of this GCG network to a gene-gene (GG network constructed over the same corpus but which uses gene pairs explicitly connected through traditional co-occurrence. Using 331,411 MEDLINE abstracts collected from 18,323 seed articles and their references, we identify 25 gene pairs. A comparison of these pairs with interactions found in BioGRID reveal that 96% of the gene pairs in the GCG network have known interactions. We measure network performance using degree, weighted degree, closeness, betweenness centrality and PageRank. Combining all measures, we find the GCG network has more gene pairs, but a lower matching rate than the GG network. However, combining top ranked genes in both networks produces a matching rate of 35.53%. By visualizing both the GG and GCG networks, we find that cancer is the most dominant disease associated with the genes in both networks. Overall, the study indicates that the GCG network can be useful for detecting gene interaction in an implicit manner.

Interactions of checkpoint-genes RAD9, RAD17, RAD24 and RAD53 determining radioresistance of Yeast Saccharomyces Cerevisiae

International Nuclear Information System (INIS)

Koltovaya, N.A.; Nikulushkina, Yu.V.; Roshchina, M.P.; Devin, A.B.

2007-01-01

The mechanisms of genetic control of progress through the division cell cycle (checkpoint-control) in yeast Saccharomyces cerevisiae have been studied intensively. To investigate the role of checkpoint-genes RAD9, RAD17, RAD24, RAD53 in cell radioresistance we have investigated cell sensitivity of double mutants to γ-ray. Double mutants involving various combinations with rad9Δ show epistatic interactions, i.e. the sensitivity of the double mutants to γ-ray was no greater than that of more sensitive of the two single mutants. This suggests that all these genes govern the same pathway. This group of genes was named RAD9-epistasis group. It is interesting to note that the genes RAD9 and RAD53 have positive effect but RAD17 and RAD24 have negative effect on radiosensitivity of yeast cells. Interactions between mutations may differ depending on the agent γ-ray or UV-light, for example mutations rad9Δ and rad24Δ show additive effect for γ-ray and epistatic effect for UV-light

Evidence of gene-environment interactions between common breast cancer susceptibility loci and established environmental risk factors

DEFF Research Database (Denmark)

Nickels, Stefan; Truong, Thérèse; Hein, Rebecca

2013-01-01

Various common genetic susceptibility loci have been identified for breast cancer; however, it is unclear how they combine with lifestyle/environmental risk factors to influence risk. We undertook an international collaborative study to assess gene-environment interaction for risk of breast cance...

Evidence of gene-environment interactions between common breast cancer susceptibility loci and established environmental risk factors

NARCIS (Netherlands)

Nickels, S.; Truong, T.; Hein, R.; Stevens, K.; Buck, K.; Behrens, S.; Eilber, U.; Schmidt, M.; Haberle, L.; Vrieling, A.; Gaudet, M.; Figueroa, J.; Schoof, N.; Spurdle, A.B.; Rudolph, A.; Fasching, P.A.; Hopper, J.L.; Makalic, E.; Schmidt, D.F.; Southey, M.C.; Beckmann, M.W.; Ekici, A.B.; Fletcher, O.; Gibson, L.; Idos, S. Silva; Peto, J.; Humphreys, M.K.; Wang, J; Cordina-Duverger, E.; Menegaux, F.; Nordestgaard, B.G.; Bojesen, S.E.; Lanng, C.; Anton-Culver, H.; Ziogas, A.; Bernstein, L.; Clarke, C.A.; Brenner, H.; Muller, H.; Arndt, V.; Stegmaier, C.; Brauch, H.; Bruning, T.; Harth, V.; Genica, N.; Mannermaa, A.; Kataja, V.; Kosma, V.M.; Hartikainen, J.M.; Lambrechts, D.; Smeets, D.; Neven, P.; Paridaens, R.; Flesch-Janys, D.; Obi, N.; Wang-Gohrke, S.; Couch, F.J.; Olson, J.E.; Vachon, C.M.; Giles, G.G.; Severi, G.; Baglietto, L.; Offit, K.; John, E.M.; Miron, A.; Andrulis, I.L.; Knight, J.A.; Glendon, G.; Mulligan, A.M.; Chanock, S.J.; Lissowska, J.; Liu, J.; Cox, A; Cramp, H.; Connley, D.; Balasubramanian, S.; Dunning, A.M.; Shah, M.; Trentham-Dietz, A.; Newcomb, P.; Titus, L.; Egan, K.; Cahoon, E.K.; Rajaraman, P.; Sigurdson, A.J.; Doody, M.M.; Guenel, P.; Pharoah, P.D.; Schmidt, M.K.; Hall, P.; Easton, D.F.; Garcia-Closas, M.; Milne, R.L.; Chang-Claude, J.; et al.,

2013-01-01

Various common genetic susceptibility loci have been identified for breast cancer; however, it is unclear how they combine with lifestyle/environmental risk factors to influence risk. We undertook an international collaborative study to assess gene-environment interaction for risk of breast cancer.

Gene x environment interactions in conduct disorder: Implications for future treatments.

Science.gov (United States)

Holz, Nathalie E; Zohsel, Katrin; Laucht, Manfred; Banaschewski, Tobias; Hohmann, Sarah; Brandeis, Daniel

2016-08-18

Conduct disorder (CD) causes high financial and social costs, not only in affected families but across society, with only moderately effective treatments so far. There is consensus that CD is likely caused by the convergence of many different factors, including genetic and adverse environmental factors. There is ample evidence of gene-environment interactions in the etiology of CD on a behavioral level regarding genetically sensitive designs and candidate gene-driven approaches, most prominently and consistently represented by MAOA. However, conclusive indications of causal GxE patterns are largely lacking. Inconsistent findings, lack of replication and methodological limitations remain a major challenge. Likewise, research addressing the identification of affected brain pathways which reflect plausible biological mechanisms underlying GxE is still very sparse. Future research will have to take multilevel approaches into account, which combine genetic, environmental, epigenetic, personality, neural and hormone perspectives. A better understanding of relevant GxE patterns in the etiology of CD might enable researchers to design customized treatment options (e.g. biofeedback interventions) for specific subgroups of patients. Copyright © 2016 Elsevier Ltd. All rights reserved.

Interaction Effects of Season of Birth and Cytokine Genes on Schizotypal Traits in the General Population

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Margarita V. Alfimova

2017-01-01

Full Text Available Literature suggests that the effect of winter birth on vulnerability to schizophrenia might be mediated by increased expression of proinflammatory cytokines due to prenatal infection and its inadequate regulation by anti-inflammatory factors. As the response of the immune system depends on genotype, this study assessed the interaction effects of cytokine genes and season of birth (SOB on schizotypy measured with the Schizotypal Personality Questionnaire (SPQ-74. We searched for associations of IL1B rs16944, IL4 rs2243250, and IL-1RN VNTR polymorphisms, SOB, and their interactions with the SPQ-74 total score in a sample of 278 healthy individuals. A significant effect of the IL4 X SOB interaction was found, p=0.007 and η2=0.028. We confirmed this effect using an extended sample of 373 individuals. Homozygotes CC born in winter showed the highest SPQ total score and differed significantly from winter-born T allele carriers, p=0.049. This difference was demonstrated for cognitive-perceptual and disorganized but not interpersonal dimensions. The findings are consistent with the hypothesis that the cytokine genes by SOB interaction can influence variability of schizotypal traits in the general population. The IL4 T allele appeared to have a protective effect against the development of positive and disorganized schizotypal traits in winter-born individuals.

Interaction Effects of Season of Birth and Cytokine Genes on Schizotypal Traits in the General Population.

Science.gov (United States)

Alfimova, Margarita V; Korovaitseva, Galina I; Lezheiko, Tatyana V; Golimbet, Vera E

2017-01-01

Literature suggests that the effect of winter birth on vulnerability to schizophrenia might be mediated by increased expression of proinflammatory cytokines due to prenatal infection and its inadequate regulation by anti-inflammatory factors. As the response of the immune system depends on genotype, this study assessed the interaction effects of cytokine genes and season of birth (SOB) on schizotypy measured with the Schizotypal Personality Questionnaire (SPQ-74). We searched for associations of IL1B rs16944, IL4 rs2243250, and IL-1RN VNTR polymorphisms, SOB, and their interactions with the SPQ-74 total score in a sample of 278 healthy individuals. A significant effect of the IL4 X SOB interaction was found, p = 0.007 and η 2 = 0.028. We confirmed this effect using an extended sample of 373 individuals. Homozygotes CC born in winter showed the highest SPQ total score and differed significantly from winter-born T allele carriers, p = 0.049. This difference was demonstrated for cognitive-perceptual and disorganized but not interpersonal dimensions. The findings are consistent with the hypothesis that the cytokine genes by SOB interaction can influence variability of schizotypal traits in the general population. The IL4 T allele appeared to have a protective effect against the development of positive and disorganized schizotypal traits in winter-born individuals.

Interaction between alcohol dehydrogenase II gene, alcohol consumption, and risk for breast cancer

OpenAIRE

St?rmer, T; Wang-Gohrke, S; Arndt, V; Boeing, H; Kong, X; Kreienberg, R; Brenner, H

2002-01-01

MaeIII Restriction Fragment Length Polymorphism in exon 3 of the alcohol dehydrogenase II was assessed in serum from 467 randomly selected German women and 278 women with invasive breast cancer to evaluate the interaction between a polymorphism of the alcohol dehydrogenase II gene, alcohol consumption and risk for breast cancer. In both groups, usual consumption of different alcoholic beverages was asked for using semiquantitative food frequency questionnaires. We used multivariable logistic ...

tagtog: interactive and text-mining-assisted annotation of gene mentions in PLOS full-text articles.

Science.gov (United States)

Cejuela, Juan Miguel; McQuilton, Peter; Ponting, Laura; Marygold, Steven J; Stefancsik, Raymund; Millburn, Gillian H; Rost, Burkhard

2014-01-01

The breadth and depth of biomedical literature are increasing year upon year. To keep abreast of these increases, FlyBase, a database for Drosophila genomic and genetic information, is constantly exploring new ways to mine the published literature to increase the efficiency and accuracy of manual curation and to automate some aspects, such as triaging and entity extraction. Toward this end, we present the 'tagtog' system, a web-based annotation framework that can be used to mark up biological entities (such as genes) and concepts (such as Gene Ontology terms) in full-text articles. tagtog leverages manual user annotation in combination with automatic machine-learned annotation to provide accurate identification of gene symbols and gene names. As part of the BioCreative IV Interactive Annotation Task, FlyBase has used tagtog to identify and extract mentions of Drosophila melanogaster gene symbols and names in full-text biomedical articles from the PLOS stable of journals. We show here the results of three experiments with different sized corpora and assess gene recognition performance and curation speed. We conclude that tagtog-named entity recognition improves with a larger corpus and that tagtog-assisted curation is quicker than manual curation. DATABASE URL: www.tagtog.net, www.flybase.org.

Novel Genes Affecting the Interaction between the Cabbage Whitefly and Arabidopsis Uncovered by Genome-Wide Association Mapping.

Directory of Open Access Journals (Sweden)

Colette Broekgaarden

Full Text Available Plants have evolved a variety of ways to defend themselves against biotic attackers. This has resulted in the presence of substantial variation in defense mechanisms among plants, even within a species. Genome-wide association (GWA mapping is a useful tool to study the genetic architecture of traits, but has so far only had limited exploitation in studies of plant defense. Here, we study the genetic architecture of defense against the phloem-feeding insect cabbage whitefly (Aleyrodes proletella in Arabidopsis thaliana. We determined whitefly performance, i.e. the survival and reproduction of whitefly females, on 360 worldwide selected natural accessions and subsequently performed GWA mapping using 214,051 SNPs. Substantial variation for whitefly adult survival and oviposition rate (number of eggs laid per female per day was observed between the accessions. We identified 39 candidate SNPs for either whitefly adult survival or oviposition rate, all with relatively small effects, underpinning the complex architecture of defense traits. Among the corresponding candidate genes, i.e. genes in linkage disequilibrium (LD with candidate SNPs, none have previously been identified as a gene playing a role in the interaction between plants and phloem-feeding insects. Whitefly performance on knock-out mutants of a number of candidate genes was significantly affected, validating the potential of GWA mapping for novel gene discovery in plant-insect interactions. Our results show that GWA analysis is a very useful tool to gain insight into the genetic architecture of plant defense against herbivorous insects, i.e. we identified and validated several genes affecting whitefly performance that have not previously been related to plant defense against herbivorous insects.

A mental retardation gene, motopsin/prss12, modulates cell morphology by interaction with seizure-related gene 6.

Science.gov (United States)

Mitsui, Shinichi; Hidaka, Chiharu; Furihata, Mutsuo; Osako, Yoji; Yuri, Kazunari

2013-07-12

A serine protease, motopsin (prss12), plays a significant role in cognitive function and the development of the brain, since the loss of motopsin function causes severe mental retardation in humans and enhances social behavior in mice. Motopsin is activity-dependently secreted from neuronal cells, is captured around the synaptic cleft, and cleaves a proteoglycan, agrin. The multi-domain structure of motopsin, consisting of a signal peptide, a proline-rich domain, a kringle domain, three scavenger receptor cysteine-rich domains, and a protease domain at the C-terminal, suggests the interaction with other molecules through these domains. To identify a protein interacting with motopsin, we performed yeast two-hybrid screening and found that seizure-related gene 6 (sez-6), a transmembrane protein on the plasma membrane of neuronal cells, bound to the proline-rich/kringle domain of motopsin. Pull-down and immunoprecipitation analyses indicated the interaction between these proteins. Immunocytochemical and immunohistochemical analyses suggested the co-localization of motopsin and sez-6 at neuronal cells in the developmental mouse brain and at motor neurons in the anterior horn of human spinal cords. Transient expression of motopsin in neuro2a cells increased the number and length of neurites as well as the level of neurite branching. Interestingly, co-expression of sez-6 with motopsin restored the effect of motopsin at the basal level, while sez-6 expression alone showed no effects on cell morphology. Our results suggest that the interaction of motopsin and sez-6 modulates the neuronal cell morphology. Copyright © 2013 Elsevier Inc. All rights reserved.

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

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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.

Protein-protein interaction inference based on semantic similarity of Gene Ontology terms.

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Zhang, Shu-Bo; Tang, Qiang-Rong

2016-07-21

Identifying protein-protein interactions is important in molecular biology. Experimental methods to this issue have their limitations, and computational approaches have attracted more and more attentions from the biological community. The semantic similarity derived from the Gene Ontology (GO) annotation has been regarded as one of the most powerful indicators for protein interaction. However, conventional methods based on GO similarity fail to take advantage of the specificity of GO terms in the ontology graph. We proposed a GO-based method to predict protein-protein interaction by integrating different kinds of similarity measures derived from the intrinsic structure of GO graph. We extended five existing methods to derive the semantic similarity measures from the descending part of two GO terms in the GO graph, then adopted a feature integration strategy to combines both the ascending and the descending similarity scores derived from the three sub-ontologies to construct various kinds of features to characterize each protein pair. Support vector machines (SVM) were employed as discriminate classifiers, and five-fold cross validation experiments were conducted on both human and yeast protein-protein interaction datasets to evaluate the performance of different kinds of integrated features, the experimental results suggest the best performance of the feature that combines information from both the ascending and the descending parts of the three ontologies. Our method is appealing for effective prediction of protein-protein interaction. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

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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

The genetics of music accomplishment: evidence for gene-environment correlation and interaction.

Science.gov (United States)

Hambrick, David Z; Tucker-Drob, Elliot M

2015-02-01

Theories of skilled performance that emphasize training history, such as K. Anders Ericsson and colleagues' deliberate-practice theory, have received a great deal of recent attention in both the scientific literature and the popular press. Twin studies, however, have demonstrated evidence for moderate-to-strong genetic influences on skilled performance. Focusing on musical accomplishment in a sample of over 800 pairs of twins, we found evidence for gene-environment correlation, in the form of a genetic effect on music practice. However, only about one quarter of the genetic effect on music accomplishment was explained by this genetic effect on music practice, suggesting that genetically influenced factors other than practice contribute to individual differences in music accomplishment. We also found evidence for gene-environment interaction, such that genetic effects on music accomplishment were most pronounced among those engaging in music practice, suggesting that genetic potentials for skilled performance are most fully expressed and fostered by practice.

Dopamine en overmatig alcoholgebruik: genen in interactie met hun omgeving [Dopamine and excessive alcohol consumption: how genes interact with their environment

OpenAIRE

Schellekens, A.F.A.; Scholte, R.H.J.; Engels, R.C.M.E.; Verkes, R.J.

2013-01-01

background Hereditary factors account for approximately 50% of the risk of developing alcohol dependence. Genes that affect the dopamine function in the brain have been extensively studied as candidate genes. aim To present the results of recent Dutch studies on the interaction between genes and their environment in relation to dopamine function and excessive alcohol use. method Two large scale research projects were recently carried out in order to study the relation between dopamine genes a...

Interaction between serotonin transporter and serotonin receptor 1 B genes polymorphisms may be associated with antisocial alcoholism.

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Wang, Tzu-Yun; Lee, Sheng-Yu; Chen, Shiou-Lan; Chang, Yun-Hsuan; Chen, Shih-Heng; Chu, Chun-Hsien; Huang, San-Yuan; Tzeng, Nian-Sheng; Wang, Chen-Lin; Lee, I Hui; Yeh, Tzung Lieh; Yang, Yen Kuang; Lu, Ru-Band

2012-07-11

Several studies have hypothesized that genes regulating the components of the serotonin system, including serotonin transporter (5-HTTLPR) and serotonin 1 B receptor (5-HT1B), may be associated with alcoholism, but their results are contradictory because of alcoholism's heterogeneity. Therefore, we examined whether the 5-HTTLPR gene and 5-HT1B gene G861C polymorphism are susceptibility factors for a specific subtype of alcoholism, antisocial alcoholism in Han Chinese in Taiwan. We recruited 273 Han Chinese male inmates with antisocial personality disorder (ASPD) [antisocial alcoholism (AS-ALC) group (n=120) and antisocial non-alcoholism (AS-N-ALC) group (n=153)] and 191 healthy male controls from the community. Genotyping was done using PCR-RFLP. There were no significant differences in the genotypic frequency of the 5-HT1B G861C polymorphism between the 3 groups. Although AS-ALC group members more frequently carried the 5-HTTLPR S/S, S/LG, and LG/LG genotypes than controls, the difference became non-significant after controlling for the covarying effects of age. However, the 5-HTTLPR S/S, S/LG, and LG/LG genotypes may have interacted with the 5-HT1B G861C C/C polymorphism and increased the risk of becoming antisocial alcoholism. Our study suggests that neither the 5-HTTLPR gene nor the 5-HT1B G861C polymorphism alone is a risk factor for antisocial alcoholism in Taiwan's Han Chinese population, but that the interaction between both genes may increase susceptibility to antisocial alcoholism.

Neuroplasticity of selective attention: Research foundations and preliminary evidence for a gene by intervention interaction

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Stevens, Courtney; Pakulak, Eric; Hampton Wray, Amanda; Bell, Theodore A.; Neville, Helen J.

2017-01-01

This article reviews the trajectory of our research program on selective attention, which has moved from basic research on the neural processes underlying selective attention to translational studies using selective attention as a neurobiological target for evidence-based interventions. We use this background to present a promising preliminary investigation of how genetic and experiential factors interact during development (i.e., gene × intervention interactions). Our findings provide evidence on how exposure to a family-based training can modify the associations between genotype (5-HTTLPR) and the neural mechanisms of selective attention in preschool children from lower socioeconomic status backgrounds. PMID:28819066

Neuroplasticity of selective attention: Research foundations and preliminary evidence for a gene by intervention interaction.

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Isbell, Elif; Stevens, Courtney; Pakulak, Eric; Hampton Wray, Amanda; Bell, Theodore A; Neville, Helen J

2017-08-29

This article reviews the trajectory of our research program on selective attention, which has moved from basic research on the neural processes underlying selective attention to translational studies using selective attention as a neurobiological target for evidence-based interventions. We use this background to present a promising preliminary investigation of how genetic and experiential factors interact during development (i.e., gene × intervention interactions). Our findings provide evidence on how exposure to a family-based training can modify the associations between genotype (5-HTTLPR) and the neural mechanisms of selective attention in preschool children from lower socioeconomic status backgrounds.

Cell-cycle-specific interaction of nuclear DNA-binding proteins with a CCAAT sequence from the human thymidine kinase gene

International Nuclear Information System (INIS)

Knight, G.B.; Gudas, J.M.; Pardee, A.B.

1987-01-01

Induction of thymidine kinase parallels the onset of DNA synthesis. To investigate the transcriptional regulation of the thymidine kinase gene, the authors have examined whether specific nuclear factors interact in a cell-cycle-dependent manner with sequences upstream of this gene. Two inverted CCAAT boxes near the transcriptional initiation sites were observed to form complexes with nuclear DNA-binding proteins. The nature of the complexes changes dramatically as the cells approach DNA synthesis and correlates well with the previously reported transcriptional increase of the thymidine kinase gene

Interaction Effects of BDNF and COMT Genes on Resting-State Brain Activity and Working Memory

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Chen, Wen; Chen, Chunhui; Xia, Mingrui; Wu, Karen; Chen, Chuansheng; He, Qinghua; Xue, Gui; Wang, Wenjing; He, Yong; Dong, Qi

2016-01-01

Catechol-O-methyltransferase (COMT) and brain-derived neurotrophic factor (BDNF) genes have been found to interactively influence working memory (WM) as well as brain activation during WM tasks. However, whether the two genes have interactive effects on resting-state activities of the brain and whether these spontaneous activations correlate with WM are still unknown. This study included behavioral data from WM tasks and genetic data (COMT rs4680 and BDNF Val66Met) from 417 healthy Chinese adults and resting-state fMRI data from 298 of them. Significant interactive effects of BDNF and COMT were found for WM performance as well as for resting-state regional homogeneity (ReHo) in WM-related brain areas, including the left medial frontal gyrus (lMeFG), left superior frontal gyrus (lSFG), right superior and medial frontal gyrus (rSMFG), right medial orbitofrontal gyrus (rMOFG), right middle frontal gyrus (rMFG), precuneus, bilateral superior temporal gyrus, left superior occipital gyrus, right middle occipital gyrus, and right inferior parietal lobule. Simple effects analyses showed that compared to other genotypes, subjects with COMT-VV/BDNF-VV had higher WM and lower ReHo in all five frontal brain areas. The results supported the hypothesis that COMT and BDNF polymorphisms influence WM performance and spontaneous brain activity (i.e., ReHo). PMID:27853425

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

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David A. Brown

2017-09-01

Full Text Available 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.

The interaction between cannabis use and the Val158Met polymorphism of the COMT gene in psychosis: A transdiagnostic meta - analysis

NARCIS (Netherlands)

Vaessen, Thomas Stephanus Johannes; de Jong, Lea; Schäfer, Annika Theresia; Damen, Thomas; Uittenboogaard, Aniek; Krolinski, Pauline; Nwosu, Chinyere Vicky; Pinckaers, Florentina Maria Egidius; Rotee, Iris Leah Marije; Smeets, Antonius Petrus Wilhelmus; Ermiş, Ayşegül; Kennedy, James L.; Nieman, Dorien H.; Tiwari, Arun; van Os, Jim; Drukker, Marjan

2018-01-01

Neither environmental nor genetic factors are sufficient to predict the transdiagnostic expression of psychosis. Therefore, analysis of gene-environment interactions may be productive. A meta-analysis was performed using papers investigating the interaction between cannabis use and catechol-O-methyl

BDNF Val66Met polymorphism, life stress and depression: A meta-analysis of gene-environment interaction.

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Zhao, Mingzhe; Chen, Lu; Yang, Jiarun; Han, Dong; Fang, Deyu; Qiu, Xiaohui; Yang, Xiuxian; Qiao, Zhengxue; Ma, Jingsong; Wang, Lin; Jiang, Shixiang; Song, Xuejia; Zhou, Jiawei; Zhang, Jian; Chen, Mingqi; Qi, Dong; Yang, Yanjie; Pan, Hui

2018-02-01

Depression is thought to be multifactorial in etiology, including genetic and environmental components. While a number of gene-environment interaction studies have been carried out, meta-analyses are scarce. The present meta-analysis aimed to quantify evidence on the interaction between brain-derived neurotrophic factor (BDNF) Val66Met polymorphism and stress in depression. Included were 31 peer-reviewed with a pooled total of 21060 participants published before October 2016 and literature searches were conducted using PubMed, Wolters Kluwer, Web of Science, EBSCO, Elsevier Science Direct and Baidu Scholar databases. The results indicated that the Met allele of BDNF Val66Met polymorphism significantly moderated the relationship between stress and depression (Z=2.666, p = 0.003). The results of subgroup analysis concluded that stressful life events and childhood adversity separately interacted with the Met allele of BDNF Val66Met polymorphism in depression (Z = 2.552, p = 0.005; Z = 1.775, p = 0.03). The results could be affected by errors or bias in primary studies which had small sample sizes with relatively lower statistic power. We could not estimate how strong the interaction effect between gene and environment was. We found evidence that supported the hypothesis that BDNF Val66Met polymorphism moderated the relationship between stress and depression, despite the fact that many included individual studies did not show this effect. Copyright © 2017 Elsevier B.V. All rights reserved.

RINT-1 interacts with MSP58 within nucleoli and plays a role in ribosomal gene transcription

International Nuclear Information System (INIS)

Yang, Chuan-Pin; Kuo, Yu-Liang; Lee, Yi-Chao; Lee, Kuen-Haur; Chiang, Chi-Wu; Wang, Ju-Ming; Hsu, Che-Chia

2016-01-01

The nucleolus is the cellular site of ribosomal (r)DNA transcription and ribosome biogenesis. The 58-kDa microspherule protein (MSP58) is a nucleolar protein involved in rDNA transcription and cell proliferation. However, regulation of MSP58-mediated rDNA transcription remains unknown. Using a yeast two-hybrid system with MSP58 as bait, we isolated complementary (c)DNA encoding Rad50-interacting protein 1 (RINT-1), as a MSP58-binding protein. RINT-1 was implicated in the cell cycle checkpoint, membrane trafficking, Golgi apparatus and centrosome dynamic integrity, and telomere length control. Both in vitro and in vivo interaction assays showed that MSP58 directly interacts with RINT-1. Interestingly, microscopic studies revealed the co-localization of MSP58, RINT-1, and the upstream binding factor (UBF), a rRNA transcription factor, in the nucleolus. We showed that ectopic expression of MSP58 or RINT-1 resulted in decreased rRNA expression and rDNA promoter activity, whereas knockdown of MSP58 or RINT-1 by siRNA exerted the opposite effect. Coexpression of MSP58 and RINT-1 robustly decreased rRNA synthesis compared to overexpression of either protein alone, whereas depletion of RINT-1 from MSP58-transfected cells enhanced rRNA synthesis. We also found that MSP58, RINT-1, and the UBF were associated with the rDNA promoter using a chromatin immunoprecipitation assay. Because aberrant ribosome biogenesis contributes to neoplastic transformation, our results revealed a novel protein complex involved in the regulation of rRNA gene expression, suggesting a role for MSP58 and RINT-1 in cancer development. - Highlights: • RINT-1 is a novel MSP58-interacting protein. • RINT-1 is a nucleolar protein that suppresses ribosomal RNA gene transcription. • RINT-1 and MSP58 cooperate to suppress ribosomal RNA gene transcription. • RINT-1, MSP58, and UBF form a complex on the rDNA promoter.

Serine Proteases-Like Genes in the Asian Rice Gall Midge Show Differential Expression in Compatible and Incompatible Interactions with Rice

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Suresh Nair

2011-04-01

Full Text Available The Asian rice gall midge, Orseolia oryzae (Wood-Mason, is a serious pest of rice. Investigations into the gall midge-rice interaction will unveil the underlying molecular mechanisms which, in turn, can be used as a tool to assist in developing suitable integrated pest management strategies. The insect gut is known to be involved in various physiological and biological processes including digestion, detoxification and interaction with the host. We have cloned and identified two genes, OoprotI and OoprotII, homologous to serine proteases with the conserved His87, Asp136 and Ser241 residues. OoProtI shared 52.26% identity with mosquito-type trypsin from Hessian fly whereas OoProtII showed 52.49% identity to complement component activated C1s from the Hessian fly. Quantitative real time PCR analysis revealed that both the genes were significantly upregulated in larvae feeding on resistant cultivar than in those feeding on susceptible cultivar. These results provide an opportunity to understand the gut physiology of the insect under compatible or incompatible interactions with the host. Phylogenetic analysis grouped these genes in the clade containing proteases of phytophagous insects away from hematophagous insects.

Polymorphisms in Genes Involved in Fatty Acid β-Oxidation Interact with Dietary Fat Intakes to Modulate the Plasma TG Response to a Fish Oil Supplementation

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Bouchard-Mercier, Annie; Rudkowska, Iwona; Lemieux, Simone; Couture, Patrick; Vohl, Marie-Claude

2014-01-01

A large inter-individual variability in the plasma triglyceride (TG) response to an omega-3 polyunsaturated fatty acid (n-3 PUFA) supplementation has been observed. The objective was to examine gene-diet interaction effects on the plasma TG response after a fish oil supplementation, between single-nucleotide polymorphisms (SNPs) within genes involved in fatty acid β-oxidation and dietary fat intakes. Two hundred and eight (208) participants were recruited in the greater Quebec City area. The participants completed a six-week fish oil supplementation (5 g fish oil/day: 1.9–2.2 g EPA and 1.1 g DHA). Dietary fat intakes were measured using three-day food records. SNPs within RXRA, CPT1A, ACADVL, ACAA2, ABCD2, ACOX1 and ACAA1 genes were genotyped using TAQMAN methodology. Gene-diet interaction effects on the plasma TG response were observed for SNPs within RXRA (rs11185660, rs10881576 and rs12339187) and ACOX1 (rs17583163) genes. For rs11185660, fold changes in RXRA gene expression levels were different depending on SFA intakes for homozygotes T/T. Gene-diet interaction effects of SNPs within genes involved in fatty acid β-oxidation and dietary fat intakes may be important in understanding the inter-individual variability in plasma TG levels and in the plasma TG response to a fish oil supplementation. PMID:24647074

Polymorphisms in Genes Involved in Fatty Acid β-Oxidation Interact with Dietary Fat Intakes to Modulate the Plasma TG Response to a Fish Oil Supplementation

Directory of Open Access Journals (Sweden)

Annie Bouchard-Mercier

2014-03-01

Full Text Available A large inter-individual variability in the plasma triglyceride (TG response to an omega-3 polyunsaturated fatty acid (n-3 PUFA supplementation has been observed. The objective was to examine gene-diet interaction effects on the plasma TG response after a fish oil supplementation, between single-nucleotide polymorphisms (SNPs within genes involved in fatty acid β-oxidation and dietary fat intakes. Two hundred and eight (208 participants were recruited in the greater Quebec City area. The participants completed a six-week fish oil supplementation (5 g fish oil/day: 1.9–2.2 g EPA and 1.1 g DHA. Dietary fat intakes were measured using three-day food records. SNPs within RXRA, CPT1A, ACADVL, ACAA2, ABCD2, ACOX1 and ACAA1 genes were genotyped using TAQMAN methodology. Gene-diet interaction effects on the plasma TG response were observed for SNPs within RXRA (rs11185660, rs10881576 and rs12339187 and ACOX1 (rs17583163 genes. For rs11185660, fold changes in RXRA gene expression levels were different depending on SFA intakes for homozygotes T/T. Gene-diet interaction effects of SNPs within genes involved in fatty acid β-oxidation and dietary fat intakes may be important in understanding the inter-individual variability in plasma TG levels and in the plasma TG response to a fish oil supplementation.

Co-evolutionary interactions between host resistance and pathogen avirulence genes in rice-Magnaporthe oryzae pathosystem.

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Singh, Pankaj Kumar; Ray, Soham; Thakur, Shallu; Rathour, Rajeev; Sharma, Vinay; Sharma, Tilak Raj

2018-06-01

Rice and Magnaporthe oryzae constitutes an ideal pathosystem for studying host-pathogen interaction in cereals crops. There are two alternative hypotheses, viz. Arms race and Trench warfare, which explain the co-evolutionary dynamics of hosts and pathogens which are under continuous confrontation. Arms race proposes that both R- and Avr- genes of host and pathogen, respectively, undergo positive selection. Alternatively, trench warfare suggests that either R- or Avr- gene in the pathosystem is under balanced selection intending to stabilize the genetic advantage gained over the opposition. Here, we made an attempt to test the above-stated hypotheses in rice-M. oryzae pathosystem at loci of three R-Avr gene pairs, Piz-t-AvrPiz-t, Pi54-AvrPi54 and Pita-AvrPita using allele mining approach. Allele mining is an efficient way to capture allelic variants existing in the population and to study the selective forces imposed on the variants during evolution. Results of nucleotide diversity, neutrality statistics and phylogenetic analyses reveal that Piz-t, Pi54 and AvrPita are diversified and under positive selection at their corresponding loci, while their counterparts, AvrPiz-t, AvrPi54 and Pita are conserved and under balancing selection, in nature. These results imply that rice-M. oryzae populations are engaged in a trench warfare at least at the three R/Avr loci studied. It is a maiden attempt to study the co-evolution of three R-Avr gene pairs in this pathosystem. Knowledge gained from this study will help in understanding the evolutionary dynamics of host-pathogen interaction in a better way and will also aid in developing new durable blast resistant rice varieties in future. Copyright © 2018 Elsevier Inc. All rights reserved.

Alpha-crystallins are involved in specific interactions with the murine gamma D/E/F-crystallin-encoding gene.

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Pietrowski, D; Durante, M J; Liebstein, A; Schmitt-John, T; Werner, T; Graw, J

1994-07-08

The promoter of the murine gamma E-crystallin (gamma E-Cry) encoding gene (gamma E-cry) was analyzed for specific interactions with lenticular proteins in a gel-retardation assay. A 21-bp fragment immediately downstream of the transcription initiation site (DOTIS) is demonstrated to be responsible for specific interactions with lens extracts. The DOTIS-binding protein(s) accept only the sense DNA strand as target; anti-sense or double-stranded DNA do not interact with these proteins. The DOTIS sequence element is highly conserved among the murine gamma D-, gamma E- and gamma F-cry and is present at comparable positions in the orthologous rat genes. Only a weak or even no protein-binding activity is observed if a few particular bases are changed, as in the rat gamma A-, gamma C- and gamma E-cry elements. DOTIS-binding proteins were found in commercially available bovine alpha-Cry preparations. The essential participation of alpha-Cry in the DNA-binding protein complex was confirmed using alpha-Cry-specific monoclonal antibody. The results reported here point to a novel function of alpha-Cry besides the structural properties in the lens.

Does parental divorce moderate the heritability of body dissatisfaction? An extension of previous gene-environment interaction effects.

Science.gov (United States)

O'Connor, Shannon M; Klump, Kelly L; VanHuysse, Jessica L; McGue, Matt; Iacono, William

2016-02-01

Previous research suggests that parental divorce moderates genetic influences on body dissatisfaction. Specifically, the heritability of body dissatisfaction is higher in children of divorced versus intact families, suggesting possible gene-environment interaction effects. However, prior research is limited to a single, self-reported measure of body dissatisfaction. The primary aim of this study was to examine whether these findings extend to a different dimension of body dissatisfaction: body image perceptions. Participants were 1,534 female twins from the Minnesota Twin Family Study, aged 16-20 years. The Body Rating Scale (BRS) was used to assess body image perceptions. Although BRS scores were heritable in twins from divorced and intact families, the heritability estimates in the divorced group were not significantly greater than estimates in the intact group. However, there were differences in nonshared environmental effects, where the magnitude of these environmental influences was larger in the divorced as compared with the intact families. Different dimensions of body dissatisfaction (i.e., negative self-evaluation versus body image perceptions) may interact with environmental risk, such as parental divorce, in discrete ways. Future research should examine this possibility and explore differential gene-environment interactions using diverse measures. © 2015 Wiley Periodicals, Inc.

Comparison of weighting approaches for genetic risk scores in gene-environment interaction studies.

Science.gov (United States)

Hüls, Anke; Krämer, Ursula; Carlsten, Christopher; Schikowski, Tamara; Ickstadt, Katja; Schwender, Holger

2017-12-16

Weighted genetic risk scores (GRS), defined as weighted sums of risk alleles of single nucleotide polymorphisms (SNPs), are statistically powerful for detection gene-environment (GxE) interactions. To assign weights, the gold standard is to use external weights from an independent study. However, appropriate external weights are not always available. In such situations and in the presence of predominant marginal genetic effects, we have shown in a previous study that GRS with internal weights from marginal genetic effects ("GRS-marginal-internal") are a powerful and reliable alternative to single SNP approaches or the use of unweighted GRS. However, this approach might not be appropriate for detecting predominant interactions, i.e. interactions showing an effect stronger than the marginal genetic effect. In this paper, we present a weighting approach for such predominant interactions ("GRS-interaction-training") in which parts of the data are used to estimate the weights from the interaction terms and the remaining data are used to determine the GRS. We conducted a simulation study for the detection of GxE interactions in which we evaluated power, type I error and sign-misspecification. We compared this new weighting approach to the GRS-marginal-internal approach and to GRS with external weights. Our simulation study showed that in the absence of external weights and with predominant interaction effects, the highest power was reached with the GRS-interaction-training approach. If marginal genetic effects were predominant, the GRS-marginal-internal approach was more appropriate. Furthermore, the power to detect interactions reached by the GRS-interaction-training approach was only slightly lower than the power achieved by GRS with external weights. The power of the GRS-interaction-training approach was confirmed in a real data application to the Traffic, Asthma and Genetics (TAG) Study (N = 4465 observations). When appropriate external weights are unavailable, we

cDNA-AFLP analysis reveals differential gene expression in compatible interaction of wheat challenged with Puccinia striiformis f. sp. tritici

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Huang Lili

2009-06-01

Full Text Available Abstract Background Puccinia striiformis f. sp. tritici is a fungal pathogen causing stripe rust, one of the most important wheat diseases worldwide. The fungus is strictly biotrophic and thus, completely dependent on living host cells for its reproduction, which makes it difficult to study genes of the pathogen. In spite of its economic importance, little is known about the molecular basis of compatible interaction between the pathogen and wheat host. In this study, we identified wheat and P. striiformis genes associated with the infection process by conducting a large-scale transcriptomic analysis using cDNA-AFLP. Results Of the total 54,912 transcript derived fragments (TDFs obtained using cDNA-AFLP with 64 primer pairs, 2,306 (4.2% displayed altered expression patterns after inoculation, of which 966 showed up-regulated and 1,340 down-regulated. 186 TDFs produced reliable sequences after sequencing of 208 TDFs selected, of which 74 (40% had known functions through BLAST searching the GenBank database. Majority of the latter group had predicted gene products involved in energy (13%, signal transduction (5.4%, disease/defence (5.9% and metabolism (5% of the sequenced TDFs. BLAST searching of the wheat stem rust fungus genome database identified 18 TDFs possibly from the stripe rust pathogen, of which 9 were validated of the pathogen origin using PCR-based assays followed by sequencing confirmation. Of the 186 reliable TDFs, 29 homologous to genes known to play a role in disease/defense, signal transduction or uncharacterized genes were further selected for validation of cDNA-AFLP expression patterns using qRT-PCR analyses. Results confirmed the altered expression patterns of 28 (96.5% genes revealed by the cDNA-AFLP technique. Conclusion The results show that cDNA-AFLP is a reliable technique for studying expression patterns of genes involved in the wheat-stripe rust interactions. Genes involved in compatible interactions between wheat and the

Genetic interactions between planar cell polarity genes cause diverse neural tube defects in mice

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Jennifer N. Murdoch

2014-10-01

Full Text Available Neural tube defects (NTDs are among the commonest and most severe forms of developmental defect, characterized by disruption of the early embryonic events of central nervous system formation. NTDs have long been known to exhibit a strong genetic dependence, yet the identity of the genetic determinants remains largely undiscovered. Initiation of neural tube closure is disrupted in mice homozygous for mutations in planar cell polarity (PCP pathway genes, providing a strong link between NTDs and PCP signaling. Recently, missense gene variants have been identified in PCP genes in humans with NTDs, although the range of phenotypes is greater than in the mouse mutants. In addition, the sequence variants detected in affected humans are heterozygous, and can often be detected in unaffected individuals. It has been suggested that interactions between multiple heterozygous gene mutations cause the NTDs in humans. To determine the phenotypes produced in double heterozygotes, we bred mice with all three pairwise combinations of Vangl2Lp, ScribCrc and Celsr1Crsh mutations, the most intensively studied PCP mutants. The majority of double-mutant embryos had open NTDs, with the range of phenotypes including anencephaly and spina bifida, therefore reflecting the defects observed in humans. Strikingly, even on a uniform genetic background, variability in the penetrance and severity of the mutant phenotypes was observed between the different double-heterozygote combinations. Phenotypically, Celsr1Crsh;Vangl2Lp;ScribCrc triply heterozygous mutants were no more severe than doubly heterozygous or singly homozygous mutants. We propose that some of the variation between double-mutant phenotypes could be attributed to the nature of the protein disruption in each allele: whereas ScribCrc is a null mutant and produces no Scrib protein, Celsr1Crsh and Vangl2Lp homozygotes both express mutant proteins, consistent with dominant effects. The variable outcomes of these genetic

Genome-Wide Gene-Environment Study Identifies Glutamate Receptor Gene GRIN2A as a Parkinson's Disease Modifier Gene via Interaction with Coffee

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Hamza, Taye H.; Chen, Honglei; Hill-Burns, Erin M.; Rhodes, Shannon L.; Montimurro, Jennifer; Kay, Denise M.; Tenesa, Albert; Kusel, Victoria I.; Sheehan, Patricia; Eaaswarkhanth, Muthukrishnan; Yearout, Dora; Samii, Ali; Roberts, John W.; Agarwal, Pinky; Bordelon, Yvette; Park, Yikyung; Wang, Liyong; Gao, Jianjun; Vance, Jeffery M.; Kendler, Kenneth S.; Bacanu, Silviu-Alin; Scott, William K.; Ritz, Beate; Nutt, John; Factor, Stewart A.; Zabetian, Cyrus P.; Payami, Haydeh

2011-01-01

Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal components. We then stratified subjects as heavy or light coffee-drinkers and performed genome-wide association study (GWAS) in each group. We replicated the most significant SNP. Finally, we imputed the NGRC dataset, increasing genomic coverage to examine the region of interest in detail. The primary analyses (GWAIS, GWAS, Replication) were performed using genotyped data. In GWAIS, the most significant signal came from rs4998386 and the neighboring SNPs in GRIN2A. GRIN2A encodes an NMDA-glutamate-receptor subunit and regulates excitatory neurotransmission in the brain. Achieving P2df = 10−6, GRIN2A surpassed all known PD susceptibility genes in significance in the GWAIS. In stratified GWAS, the GRIN2A signal was present in heavy coffee-drinkers (OR = 0.43; P = 6×10−7) but not in light coffee-drinkers. The a priori Replication hypothesis that “Among heavy coffee-drinkers, rs4998386_T carriers have lower PD risk than rs4998386_CC carriers” was confirmed: ORReplication = 0.59, PReplication = 10−3; ORPooled = 0.51, PPooled = 7×10−8. Compared to light coffee-drinkers with rs4998386_CC genotype, heavy coffee-drinkers with rs4998386_CC genotype had 18% lower risk (P = 3×10−3), whereas heavy coffee-drinkers with rs4998386_TC genotype had 59% lower risk (P = 6×10−13). Imputation revealed a block of SNPs that achieved P2dfcoffee-drinkers. This study is proof of concept that inclusion of environmental factors can help identify genes that

Genome-wide gene-environment study identifies glutamate receptor gene GRIN2A as a Parkinson's disease modifier gene via interaction with coffee.

Science.gov (United States)

Hamza, Taye H; Chen, Honglei; Hill-Burns, Erin M; Rhodes, Shannon L; Montimurro, Jennifer; Kay, Denise M; Tenesa, Albert; Kusel, Victoria I; Sheehan, Patricia; Eaaswarkhanth, Muthukrishnan; Yearout, Dora; Samii, Ali; Roberts, John W; Agarwal, Pinky; Bordelon, Yvette; Park, Yikyung; Wang, Liyong; Gao, Jianjun; Vance, Jeffery M; Kendler, Kenneth S; Bacanu, Silviu-Alin; Scott, William K; Ritz, Beate; Nutt, John; Factor, Stewart A; Zabetian, Cyrus P; Payami, Haydeh

2011-08-01

Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal components. We then stratified subjects as heavy or light coffee-drinkers and performed genome-wide association study (GWAS) in each group. We replicated the most significant SNP. Finally, we imputed the NGRC dataset, increasing genomic coverage to examine the region of interest in detail. The primary analyses (GWAIS, GWAS, Replication) were performed using genotyped data. In GWAIS, the most significant signal came from rs4998386 and the neighboring SNPs in GRIN2A. GRIN2A encodes an NMDA-glutamate-receptor subunit and regulates excitatory neurotransmission in the brain. Achieving P(2df) = 10(-6), GRIN2A surpassed all known PD susceptibility genes in significance in the GWAIS. In stratified GWAS, the GRIN2A signal was present in heavy coffee-drinkers (OR = 0.43; P = 6×10(-7)) but not in light coffee-drinkers. The a priori Replication hypothesis that "Among heavy coffee-drinkers, rs4998386_T carriers have lower PD risk than rs4998386_CC carriers" was confirmed: OR(Replication) = 0.59, P(Replication) = 10(-3); OR(Pooled) = 0.51, P(Pooled) = 7×10(-8). Compared to light coffee-drinkers with rs4998386_CC genotype, heavy coffee-drinkers with rs4998386_CC genotype had 18% lower risk (P = 3×10(-3)), whereas heavy coffee-drinkers with rs4998386_TC genotype had 59% lower risk (P = 6×10(-13)). Imputation revealed a block of SNPs that achieved P(2df)coffee-drinkers. This study is proof of concept that inclusion of environmental factors can help identify

Interaction between Serotonin Transporter and Serotonin Receptor 1 B genes polymorphisms may be associated with antisocial alcoholism

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Wang Tzu-Yun

2012-07-01

Full Text Available Abstract Background Several studies have hypothesized that genes regulating the components of the serotonin system, including serotonin transporter (5-HTTLPR and serotonin 1 B receptor (5-HT1B, may be associated with alcoholism, but their results are contradictory because of alcoholism’s heterogeneity. Therefore, we examined whether the 5-HTTLPR gene and 5-HT1B gene G861C polymorphism are susceptibility factors for a specific subtype of alcoholism, antisocial alcoholism in Han Chinese in Taiwan. Methods We recruited 273 Han Chinese male inmates with antisocial personality disorder (ASPD [antisocial alcoholism (AS-ALC group (n = 120 and antisocial non-alcoholism (AS-N-ALC group (n = 153] and 191 healthy male controls from the community. Genotyping was done using PCR-RFLP. Results There were no significant differences in the genotypic frequency of the 5-HT1B G861C polymorphism between the 3 groups. Although AS-ALC group members more frequently carried the 5-HTTLPR S/S, S/LG, and LG/LG genotypes than controls, the difference became non-significant after controlling for the covarying effects of age. However, the 5-HTTLPR S/S, S/LG, and LG/LG genotypes may have interacted with the 5-HT1B G861C C/C polymorphism and increased the risk of becoming antisocial alcoholism. Conclusion Our study suggests that neither the 5-HTTLPR gene nor the 5-HT1B G861C polymorphism alone is a risk factor for antisocial alcoholism in Taiwan’s Han Chinese population, but that the interaction between both genes may increase susceptibility to antisocial alcoholism.

Social Integration and Sleep Disturbance: A Gene-Environment Interaction Study

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David A. Sbarra

2016-03-01

Full Text Available Objective: Low levels of perceived social integration, or loneliness, are associated with increased risk for a range of poor health outcomes. Sleep disturbance plays a central role in the evolutionary theory of loneliness, which provides a mechanistic account of how low levels of social integration may negatively impact health. No studies, however, have examined whether the association between social integration and sleep disturbance is consistent with a causal effect after accounting for genes that are common to both variables.  Method: Using twin data ('N' = 905 twin pairs from the nationally-representative Midlife in the United States (MIDUS survey, I evaluated a series of bivariate twin models exploring whether the phenotypic association between low social integration and sleep disturbance can be explained by shared genetics. In addition, the current study specified a series of quantitative models for studying gene x environment (G X E interactions to determine whether the genetic and environmental influences on sleep disturbance differ as a function of social integration. Results: The phenotypic association between social integration and sleep disturbance was fully accounted for by genes that are common between the two variables, suggesting that within-twin pair differences in social integration do not exert a causal influence on sleep disturbance. Social integration, however, moderated the non-shared environmental influence on sleep disturbances, with the greatest environmental influences observed at the lowest levels of social integration. Conclusions: The results of this study suggest that an essential feature of the evolutionary model of loneliness may need refinement or elaboration. The moderation findings are discussed in terms of the fit with a stress-buffering model of social support in which environmental influences on sleep disturbance are strongest when social resources are low.

Identifying genes involved in the interaction of Aggregatibacter actinomycetemcomitans with Maillard reaction products (MRP)

Science.gov (United States)

Jaha, Raniah Abdulmohsen

Aggregatibacter (Actinobacillus) actinomycelemcomitcrns is a gram-negative bacterium that is a facultative anaerobe which can grow in either aerobic or anaerobic conditions. The bacteria cause localized aggressive periodontitis that can result in the loss of teeth and endocarditis, which is an infection of the heart valves. A rich medium is an essential requirement for its growth. There arc some difficulties associated with growing the bacteria as they easily switch from the rough to smooth phenotype under no specific conditions. The bacteria start to lose viability after about 19 hours of growth in broth or about three days on plates. Colonies in the dense part of the streak on plates die earlier. It was shown that acid secreted by the colonies is responsible for the loss of viability as the bacteria are extremely sensitive to low pH. Autoclaving the growth medium for A. actinomycetemcomitans causes the bacteria to grow slowly because of the formation of Maillard reaction products (MRPs). A method has been developed to make the A. actinomycetemcomitans growth medium using the microwave instead of the autoclave. This method produces much less of the inhibitory product since the heating time is only six minutes, compared to more than an hour when using the autoclave. Two approaches were sought in this research. The first approach was the identification of genes responsible for the interaction between the MRP and A. actinomycetemcomitans. The gene responsible for this interaction was found to be a Lys M protein which is found in many genes responsible for the cell wall integrity. The second approach was to develop a new drug made of glucose and lysine with a minimum inhibitory concentration as 75mM.

Isolation and Characterization of Pepper Genes Interacting with the CMV-P1 Helicase Domain.

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Yoomi Choi

Full Text Available Cucumber mosaic virus (CMV is a destructive pathogen affecting Capsicum annuum (pepper production. The pepper Cmr1 gene confers resistance to most CMV strains, but is overcome by CMV-P1 in a process dependent on the CMV-P1 RNA1 helicase domain (P1 helicase. Here, to identify host factors involved in CMV-P1 infection in pepper, a yeast two-hybrid library derived from a C. annuum 'Bukang' cDNA library was screened, producing a total of 76 potential clones interacting with the P1 helicase. Beta-galactosidase filter lift assay, PCR screening, and sequencing analysis narrowed the candidates to 10 genes putatively involved in virus infection. The candidate host genes were silenced in Nicotiana benthamiana plants that were then inoculated with CMV-P1 tagged with the green fluorescent protein (GFP. Plants silenced for seven of the genes showed development comparable to N. benthamiana wild type, whereas plants silenced for the other three genes showed developmental defects including stunting and severe distortion. Silencing formate dehydrogenase and calreticulin-3 precursor led to reduced virus accumulation. Formate dehydrogenase-silenced plants showed local infection in inoculated leaves, but not in upper (systemic leaves. In the calreticulin-3 precursor-silenced plants, infection was not observed in either the inoculated or the upper leaves. Our results demonstrate that formate dehydrogenase and calreticulin-3 precursor are required for CMV-P1 infection.

Genome mining of Streptomyces scabrisporus NF3 reveals symbiotic features including genes related to plant interactions

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Rodríguez-Luna, Stefany Daniela; Cruz Vázquez, Angélica Patricia; Jiménez Suárez, Verónica; Rodríguez-Sanoja, Romina; Alvarez-Buylla, Elena R.; Sánchez, Sergio

2018-01-01

Endophytic bacteria are wide-spread and associated with plant physiological benefits, yet their genomes and secondary metabolites remain largely unidentified. In this study, we explored the genome of the endophyte Streptomyces scabrisporus NF3 for discovery of potential novel molecules as well as genes and metabolites involved in host interactions. The complete genomes of seven Streptomyces and three other more distantly related bacteria were used to define the functional landscape of this unique microbe. The S. scabrisporus NF3 genome is larger than the average Streptomyces genome and not structured for an obligate endosymbiotic lifestyle; this and the fact that can grow in R2YE media implies that it could include a soil-living stage. The genome displays an enrichment of genes associated with amino acid production, protein secretion, secondary metabolite and antioxidants production and xenobiotic degradation, indicating that S. scabrisporus NF3 could contribute to the metabolic enrichment of soil microbial communities and of its hosts. Importantly, besides its metabolic advantages, the genome showed evidence for differential functional specificity and diversification of plant interaction molecules, including genes for the production of plant hormones, stress resistance molecules, chitinases, antibiotics and siderophores. Given the diversity of S. scabrisporus mechanisms for host upkeep, we propose that these strategies were necessary for its adaptation to plant hosts and to face changes in environmental conditions. PMID:29447216

Genome mining of Streptomyces scabrisporus NF3 reveals symbiotic features including genes related to plant interactions.

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Corina Diana Ceapă

Full Text Available Endophytic bacteria are wide-spread and associated with plant physiological benefits, yet their genomes and secondary metabolites remain largely unidentified. In this study, we explored the genome of the endophyte Streptomyces scabrisporus NF3 for discovery of potential novel molecules as well as genes and metabolites involved in host interactions. The complete genomes of seven Streptomyces and three other more distantly related bacteria were used to define the functional landscape of this unique microbe. The S. scabrisporus NF3 genome is larger than the average Streptomyces genome and not structured for an obligate endosymbiotic lifestyle; this and the fact that can grow in R2YE media implies that it could include a soil-living stage. The genome displays an enrichment of genes associated with amino acid production, protein secretion, secondary metabolite and antioxidants production and xenobiotic degradation, indicating that S. scabrisporus NF3 could contribute to the metabolic enrichment of soil microbial communities and of its hosts. Importantly, besides its metabolic advantages, the genome showed evidence for differential functional specificity and diversification of plant interaction molecules, including genes for the production of plant hormones, stress resistance molecules, chitinases, antibiotics and siderophores. Given the diversity of S. scabrisporus mechanisms for host upkeep, we propose that these strategies were necessary for its adaptation to plant hosts and to face changes in environmental conditions.

Association and Interaction Effect of AGTR1 and AGTR2 Gene Polymorphisms with Dietary Pattern on Metabolic Risk Factors of Cardiovascular Disease in Malaysian Adults.

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Yap, Roseline Wai Kuan; Shidoji, Yoshihiro; Yap, Wai Sum; Masaki, Motofumi

2017-08-09

Gene-diet interaction using a multifactorial approach is preferred to study the multiple risk factors of cardiovascular disease (CVD). This study examined the association and gene-diet interaction effects of the angiotensin II type 1 receptor ( AGTR1 ) gene (rs5186), and type 2 receptor ( AGTR2 ) gene (rs1403543) polymorphisms on metabolic risk factors of CVD in Malaysian adults. CVD parameters (BMI, blood pressure, glycated hemoglobin, total cholesterol (TC), triglycerides, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol (HDL-C), and TC/HDL-C ratio), and constructed dietary patterns "vegetables, fruits, and soy diet" (VFSD), and "rice, egg, and fish diet" (REFD) were obtained from previous studies. Genotyping analysis was performed by real-time PCR using Taqman probes. The subjects were 507 adults (151 Malays; 179 Chinese; and 177 Indians). Significant genetic associations were obtained on blood lipids for rs5186 in Malays and Chinese, and rs1403543 in Chinese females. The significant gene-diet interaction effects after adjusting for potential confounders were: rs5186 × VFSD on blood pressure in Malays ( p = 0.016), and in Chinese on blood lipids for rs5186 × REFD ( p = 0.009-0.023), and rs1403543 × VFSD in female subjects ( p = 0.001-0.011). Malays and Chinese showed higher risk for blood pressure and/or lipids involving rs5186 and rs1403543 SNPs together with gene-diet interactions, but not Indians.

Epistasis × environment interactions among Arabidopsis thaliana glucosinolate genes impact complex traits and fitness in the field

DEFF Research Database (Denmark)

Kerwin, Rachel E.; Feusier, Julie; Muok, Alise

2017-01-01

(GSL) defense chemistry, leaf damage, and relative fitness using mutant lines of Arabidopsis thaliana varying at pairs of causal aliphatic GSL defense genes to test the impact of epistatic and epistasis × environment interactions on adaptive trait variation. We found that aliphatic GSL accumulation...

The Oxytocin Receptor Gene (OXTR) and gazing behavior during social interaction: An observational study in young adults

NARCIS (Netherlands)

Verhagen, M.; Engels, R.C.M.E.; Roekel, G.H. van

2014-01-01

Background: In the present study, the relation between a polymorphic marker within the OXTR gene (rs53576) and gazing behavior during two separate social interaction tasks was examined. Gazing behavior was considered to be an integral part of belonging regulation processes. Methods: We conducted an

Music training and speech perception: a gene-environment interaction.

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Schellenberg, E Glenn

2015-03-01

Claims of beneficial side effects of music training are made for many different abilities, including verbal and visuospatial abilities, executive functions, working memory, IQ, and speech perception in particular. Such claims assume that music training causes the associations even though children who take music lessons are likely to differ from other children in music aptitude, which is associated with many aspects of speech perception. Music training in childhood is also associated with cognitive, personality, and demographic variables, and it is well established that IQ and personality are determined largely by genetics. Recent evidence also indicates that the role of genetics in music aptitude and music achievement is much larger than previously thought. In short, music training is an ideal model for the study of gene-environment interactions but far less appropriate as a model for the study of plasticity. Children seek out environments, including those with music lessons, that are consistent with their predispositions; such environments exaggerate preexisting individual differences. © 2015 New York Academy of Sciences.

Adolescent Loneliness and the Interaction between the Serotonin Transporter Gene (5-HTTLPR and Parental Support: A Replication Study.

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Annette W M Spithoven

Full Text Available Gene-by-environment interaction (GxEs studies have gained popularity over the last decade, but the robustness of such observed interactions has been questioned. The current study contributes to this debate by replicating the only study on the interaction between the serotonin transporter gene (5-HTTLPR and perceived parental support on adolescents' peer-related loneliness. A total of 1,111 adolescents (51% boys with an average age of 13.70 years (SD = 0.93 participated and three annual waves of data were collected. At baseline, adolescent-reported parental support and peer-related loneliness were assessed and genetic information was collected. Assessment of peer-related loneliness was repeated at Waves 2 and 3. Using a cohort-sequential design, a Latent Growth Curve Model was estimated. Overall, a slight increase of loneliness over time was found. However, the development of loneliness over time was found to be different for boys and girls: girls' levels of loneliness increased over time, whereas boys' levels of loneliness decreased. Parental support was inversely related to baseline levels of loneliness, but unrelated to change of loneliness over time. We were unable to replicate the main effect of 5-HTTLPR or the 5-HTTLPR x Support interaction effect. In the Discussion, we examine the implications of our non-replication.

An interaction map of circulating metabolites, immune gene networks, and their genetic regulation.

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Nath, Artika P; Ritchie, Scott C; Byars, Sean G; Fearnley, Liam G; Havulinna, Aki S; Joensuu, Anni; Kangas, Antti J; Soininen, Pasi; Wennerström, Annika; Milani, Lili; Metspalu, Andres; Männistö, Satu; Würtz, Peter; Kettunen, Johannes; Raitoharju, Emma; Kähönen, Mika; Juonala, Markus; Palotie, Aarno; Ala-Korpela, Mika; Ripatti, Samuli; Lehtimäki, Terho; Abraham, Gad; Raitakari, Olli; Salomaa, Veikko; Perola, Markus; Inouye, Michael

2017-08-01

Immunometabolism plays a central role in many cardiometabolic diseases. However, a robust map of immune-related gene networks in circulating human cells, their interactions with metabolites, and their genetic control is still lacking. Here, we integrate blood transcriptomic, metabolomic, and genomic profiles from two population-based cohorts (total N = 2168), including a subset of individuals with matched multi-omic data at 7-year follow-up. We identify topologically replicable gene networks enriched for diverse immune functions including cytotoxicity, viral response, B cell, platelet, neutrophil, and mast cell/basophil activity. These immune gene modules show complex patterns of association with 158 circulating metabolites, including lipoprotein subclasses, lipids, fatty acids, amino acids, small molecules, and CRP. Genome-wide scans for module expression quantitative trait loci (mQTLs) reveal five modules with mQTLs that have both cis and trans effects. The strongest mQTL is in ARHGEF3 (rs1354034) and affects a module enriched for platelet function, independent of platelet counts. Modules of mast cell/basophil and neutrophil function show temporally stable metabolite associations over 7-year follow-up, providing evidence that these modules and their constituent gene products may play central roles in metabolic inflammation. Furthermore, the strongest mQTL in ARHGEF3 also displays clear temporal stability, supporting widespread trans effects at this locus. This study provides a detailed map of natural variation at the blood immunometabolic interface and its genetic basis, and may facilitate subsequent studies to explain inter-individual variation in cardiometabolic disease.

Gene-by-Psychosocial Factor Interactions Influence Diastolic Blood Pressure in European and African Ancestry Populations: Meta-Analysis of Four Cohort Studies

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Jennifer A. Smith

2017-12-01

Full Text Available Inter-individual variability in blood pressure (BP is influenced by both genetic and non-genetic factors including socioeconomic and psychosocial stressors. A deeper understanding of the gene-by-socioeconomic/psychosocial factor interactions on BP may help to identify individuals that are genetically susceptible to high BP in specific social contexts. In this study, we used a genomic region-based method for longitudinal analysis, Longitudinal Gene-Environment-Wide Interaction Studies (LGEWIS, to evaluate the effects of interactions between known socioeconomic/psychosocial and genetic risk factors on systolic and diastolic BP in four large epidemiologic cohorts of European and/or African ancestry. After correction for multiple testing, two interactions were significantly associated with diastolic BP. In European ancestry participants, outward/trait anger score had a significant interaction with the C10orf107 genomic region (p = 0.0019. In African ancestry participants, depressive symptom score had a significant interaction with the HFE genomic region (p = 0.0048. This study provides a foundation for using genomic region-based longitudinal analysis to identify subgroups of the population that may be at greater risk of elevated BP due to the combined influence of genetic and socioeconomic/psychosocial risk factors.

Adult onset asthma and interaction between genes and active tobacco smoking: The GABRIEL consortium.

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J M Vonk

Full Text Available Genome-wide association studies have identified novel genetic associations for asthma, but without taking into account the role of active tobacco smoking. This study aimed to identify novel genes that interact with ever active tobacco smoking in adult onset asthma.We performed a genome-wide interaction analysis in six studies participating in the GABRIEL consortium following two meta-analyses approaches based on 1 the overall interaction effect and 2 the genetic effect in subjects with and without smoking exposure. We performed a discovery meta-analysis including 4,057 subjects of European descent and replicated our findings in an independent cohort (LifeLines Cohort Study, including 12,475 subjects.First approach: 50 SNPs were selected based on an overall interaction effect at p<10-4. The most pronounced interaction effect was observed for rs9969775 on chromosome 9 (discovery meta-analysis: ORint = 0.50, p = 7.63*10-5, replication: ORint = 0.65, p = 0.02. Second approach: 35 SNPs were selected based on the overall genetic effect in exposed subjects (p <10-4. The most pronounced genetic effect was observed for rs5011804 on chromosome 12 (discovery meta-analysis ORint = 1.50, p = 1.21*10-4; replication: ORint = 1.40, p = 0.03.Using two genome-wide interaction approaches, we identified novel polymorphisms in non-annotated intergenic regions on chromosomes 9 and 12, that showed suggestive evidence for interaction with active tobacco smoking in the onset of adult asthma.

A functional polymorphism in a serotonin transporter gene (5-HTTLPR) interacts with 9/11 to predict gun-carrying behavior.

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Barnes, J C; Beaver, Kevin M; Boutwell, Brian B

2013-01-01

On September 11, 2001, one of the deadliest terrorist attacks in US history took place on American soil and people around the world were impacted in myriad ways. Building on prior literature which suggests individuals are more likely to purchase a gun for self-protection if they are fearful of being victimized, the authors hypothesized that the terrorist attacks of 9/11 would lead to an increase in gun carrying among US residents. At the same time, a line of research has shown that a polymorphism in the 5-HTT gene (i.e., 5-HTTLPR) interacts with environmental stressors to predict a range of psychopathologies and behaviors. Thus, it was hypothesized that 9/11 and 5-HTTLPR would interact to predict gun carrying. The results supported both hypotheses by revealing a positive association between 9/11 and gun carrying (b = .426, odds ratio = 1.531, standard error for b = .194, z = 2.196, p = .028) in the full sample of respondents (n = 15,052) and a statistically significant interaction between 9/11 and 5-HTTLPR in the prediction of gun carrying (b = -1.519, odds ratio = .219, standard error for b = .703, z = -2.161, p = .031) in the genetic subsample of respondents (n = 2,350). This is one of the first studies to find an association between 9/11 and gun carrying and, more importantly, is the first study to report a gene-environment interaction (GxE) between a measured gene and a terrorist attack.

Gene-environment interaction and covariation in schizophrenia: the role of obstetric complications.

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Mittal, Vijay A; Ellman, Lauren M; Cannon, Tyrone D

2008-11-01

While genetic factors account for a significant proportion of liability to schizophrenia, a body of evidence attests to a significant environmental contribution. Understanding the mechanisms through which genetic and environmental factors coalesce in influencing schizophrenia is critical for elucidating the pathways underlying psychotic illness and for developing primary prevention strategies. Although obstetric complications (OCs) remain among the most well-documented environmental indicators of risk for schizophrenia, the pathogenic role they play in the etiology of schizophrenia continues to remain poorly understood. A question of major importance is do these factors result from a genetic diathesis to schizophrenia (as in gene-environment covariation), act additively or interactively with predisposing genes for the disorder in influencing disease risk, or independently cause disease onset? In this review, we evaluate 3 classes of OCs commonly related to schizophrenia including hypoxia-associated OCs, maternal infection during pregnancy, and maternal stress during pregnancy. In addition, we discuss several mechanisms by which OCs impact on genetically susceptible brain regions, increasing constitutional vulnerability to neuromaturational events and stressors later in life (ie, adolescence), which may in turn contribute to triggering psychosis.

Structure-function analysis of RBP-J-interacting and tubulin-associated (RITA) reveals regions critical for repression of Notch target genes.

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Tabaja, Nassif; Yuan, Zhenyu; Oswald, Franz; Kovall, Rhett A

2017-06-23

The Notch pathway is a cell-to-cell signaling mechanism that is essential for tissue development and maintenance, and aberrant Notch signaling has been implicated in various cancers, congenital defects, and cardiovascular diseases. Notch signaling activates the expression of target genes, which are regulated by the transcription factor CSL (CBF1/RBP-J, Su(H), Lag-1). CSL interacts with both transcriptional corepressor and coactivator proteins, functioning as both a repressor and activator, respectively. Although Notch activation complexes are relatively well understood at the structural level, less is known about how CSL interacts with corepressors. Recently, a new RBP-J (mammalian CSL ortholog)-interacting protein termed RITA has been identified and shown to export RBP-J out of the nucleus, thereby leading to the down-regulation of Notch target gene expression. However, the molecular details of RBP-J/RITA interactions are unclear. Here, using a combination of biochemical/cellular, structural, and biophysical techniques, we demonstrate that endogenous RBP-J and RITA proteins interact in cells, map the binding regions necessary for RBP-J·RITA complex formation, and determine the X-ray structure of the RBP-J·RITA complex bound to DNA. To validate the structure and glean more insights into function, we tested structure-based RBP-J and RITA mutants with biochemical/cellular assays and isothermal titration calorimetry. Whereas our structural and biophysical studies demonstrate that RITA binds RBP-J similarly to the RAM (RBP-J-associated molecule) domain of Notch, our biochemical and cellular assays suggest that RITA interacts with additional regions in RBP-J. Taken together, these results provide molecular insights into the mechanism of RITA-mediated regulation of Notch signaling, contributing to our understanding of how CSL functions as a transcriptional repressor of Notch target genes. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

VEGF-A isoforms differentially regulate ATF-2-dependent VCAM-1 gene expression and endothelial-leukocyte interactions.

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Fearnley, Gareth W; Odell, Adam F; Latham, Antony M; Mughal, Nadeem A; Bruns, Alexander F; Burgoyne, Nicholas J; Homer-Vanniasinkam, Shervanthi; Zachary, Ian C; Hollstein, Monica C; Wheatcroft, Stephen B; Ponnambalam, Sreenivasan

2014-08-15

Vascular endothelial growth factor A (VEGF-A) regulates many aspects of vascular physiology. VEGF-A stimulates signal transduction pathways that modulate endothelial outputs such as cell migration, proliferation, tubulogenesis, and cell-cell interactions. Multiple VEGF-A isoforms exist, but the biological significance of this is unclear. Here we analyzed VEGF-A isoform-specific stimulation of VCAM-1 gene expression, which controls endothelial-leukocyte interactions, and show that this is dependent on both ERK1/2 and activating transcription factor-2 (ATF-2). VEGF-A isoforms showed differential ERK1/2 and p38 MAPK phosphorylation kinetics. A key feature of VEGF-A isoform-specific ERK1/2 activation and nuclear translocation was increased phosphorylation of ATF-2 on threonine residue 71 (T71). Using reverse genetics, we showed ATF-2 to be functionally required for VEGF-A-stimulated endothelial VCAM-1 gene expression. ATF-2 knockdown blocked VEGF-A-stimulated VCAM-1 expression and endothelial-leukocyte interactions. ATF-2 was also required for other endothelial cell outputs, such as cell migration and tubulogenesis. In contrast, VCAM-1 was essential only for promoting endothelial-leukocyte interactions. This work presents a new paradigm for understanding how soluble growth factor isoforms program complex cellular outputs and responses by modulating signal transduction pathways. © 2014 Fearnley et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

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