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...

Genes: Interactions with Language on Three Levels—Inter-Individual Variation, Historical Correlations and Genetic Biasing

Science.gov (United States)

Dediu, Dan

The complex inter-relationships between genetics and linguistics encompass all four scales highlighted by the contributions to this book and, together with cultural transmission, the genetics of language holds the promise to offer a unitary understanding of this fascinating phenomenon. There are inter-individual differences in genetic makeup which contribute to the obvious fact that we are not identical in the way we understand and use language and, by studying them, we will be able to both better treat and enhance ourselves. There are correlations between the genetic configuration of human groups and their languages, reflecting the historical processes shaping them, and there also seem to exist genes which can influence some characteristics of language, biasing it towards or against certain states by altering the way language is transmitted across generations. Besides the joys of pure knowledge, the understanding of these three aspects of genetics relevant to language will potentially trigger advances in medicine, linguistics, psychology or the understanding of our own past and, last but not least, a profound change in the way we regard one of the emblems of being human: our capacity for language.

GxGrare: gene-gene interaction analysis method for rare variants from high-throughput sequencing data.

Science.gov (United States)

Kwon, Minseok; Leem, Sangseob; Yoon, Joon; Park, Taesung

2018-03-19

With the rapid advancement of array-based genotyping techniques, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with common complex diseases. However, it has been shown that only a small proportion of the genetic etiology of complex diseases could be explained by the genetic factors identified from GWAS. This missing heritability could possibly be explained by gene-gene interaction (epistasis) and rare variants. There has been an exponential growth of gene-gene interaction analysis for common variants in terms of methodological developments and practical applications. Also, the recent advancement of high-throughput sequencing technologies makes it possible to conduct rare variant analysis. However, little progress has been made in gene-gene interaction analysis for rare variants. Here, we propose GxGrare which is a new gene-gene interaction method for the rare variants in the framework of the multifactor dimensionality reduction (MDR) analysis. The proposed method consists of three steps; 1) collapsing the rare variants, 2) MDR analysis for the collapsed rare variants, and 3) detect top candidate interaction pairs. GxGrare can be used for the detection of not only gene-gene interactions, but also interactions within a single gene. The proposed method is illustrated with 1080 whole exome sequencing data of the Korean population in order to identify causal gene-gene interaction for rare variants for type 2 diabetes. The proposed GxGrare performs well for gene-gene interaction detection with collapsing of rare variants. GxGrare is available at http://bibs.snu.ac.kr/software/gxgrare which contains simulation data and documentation. Supported operating systems include Linux and OS X.

Genome-wide identification of key modulators of gene-gene interaction networks in breast cancer.

Science.gov (United States)

Chiu, Yu-Chiao; Wang, Li-Ju; Hsiao, Tzu-Hung; Chuang, Eric Y; Chen, Yidong

2017-10-03

With the advances in high-throughput gene profiling technologies, a large volume of gene interaction maps has been constructed. A higher-level layer of gene-gene interaction, namely modulate gene interaction, is composed of gene pairs of which interaction strengths are modulated by (i.e., dependent on) the expression level of a key modulator gene. Systematic investigations into the modulation by estrogen receptor (ER), the best-known modulator gene, have revealed the functional and prognostic significance in breast cancer. However, a genome-wide identification of key modulator genes that may further unveil the landscape of modulated gene interaction is still lacking. We proposed a systematic workflow to screen for key modulators based on genome-wide gene expression profiles. We designed four modularity parameters to measure the ability of a putative modulator to perturb gene interaction networks. Applying the method to a dataset of 286 breast tumors, we comprehensively characterized the modularity parameters and identified a total of 973 key modulator genes. The modularity of these modulators was verified in three independent breast cancer datasets. ESR1, the encoding gene of ER, appeared in the list, and abundant novel modulators were illuminated. For instance, a prognostic predictor of breast cancer, SFRP1, was found the second modulator. Functional annotation analysis of the 973 modulators revealed involvements in ER-related cellular processes as well as immune- and tumor-associated functions. Here we present, as far as we know, the first comprehensive analysis of key modulator genes on a genome-wide scale. The validity of filtering parameters as well as the conservativity of modulators among cohorts were corroborated. Our data bring new insights into the modulated layer of gene-gene interaction and provide candidates for further biological investigations.

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.

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

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Ma'ayan Avi

2007-10-01

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

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

Science.gov (United States)

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.

Is the Milky Way an interacting galaxy?

International Nuclear Information System (INIS)

Verschuur, G.L.

1988-01-01

The Milky Way Galaxy is an interacting galaxy, according to radio astronomers. The disk of stars we live in is linked to the Magellanic Clouds, our Galaxy's satellites, by an enormous arc of neutral hydrogen called the Magellanic Stream. These startling facts have recently been established by piecing together many seemingly unrelated bits of evidence into a new picture of our Milky Way Galaxy. The discoveries that led up to this grand picture of the Milky Way's interaction data back over fifty years to create one of the best detective stories in modern astronomy. The realization that ours is an interacting galaxy is only the latest result of an intensive effort to map the Milky Way. Since the 1930s, astronomers have tried to discover just how our Galaxy is built. Charting the Milky Way hasn't been easy, because we are inside it and our view of the Milky Way is obscured by cosmic dust. This dust creates a region called the zone of avoidance, a band centered along the galactic plane that blocks visible light from objects beyond nearby objects in the Galaxy. Thus radio astronomers have become the Milky Way mappers because cosmic radio waves penetrate the dust and reveal the grand scheme of our Galaxy

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.

Dealing with Organizational Double Binds: Three-way Interactive Effects of Role Stressors and Coping on Worker Exhaustion.

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Hornung, Severin; Lampert, Bettina; Glaser, Jürgen

2016-04-01

Based on theory regarding the dynamics of organizational double binds, hypotheses were developed about interactive effects of role conflict, role ambiguity, and coping on psychological exhaustion. Hypotheses were tested in a sample of 948 civil servants employed by a government administration in Germany. The sample included 250 (26.4%) women (M age = 43.6 year, SD = 8.3) and average organizational tenure was 17.1 year (SD = 10.0). Moderated multiple regression supported the two hypothesized three-way interactions. Under conditions of high role conflict and high role ambiguity, exhaustion was lower in workers reporting high control coping than in workers reporting low control coping. Under conditions of high role conflict and high role ambiguity, worker exhaustion was more pronounced when support coping was high than when it was low. Problem-focused control coping seems crucial to maintain mental health in dealing with contradictory and unclear work role expectations. Emotion-focused support coping appears symptomatic of prolonged involvement in psychologically dysfunctional work situations that cannot otherwise be addressed. Implications are discussed in the context of growing awareness of the contradictory demands organizations impose on employees. © The Author(s) 2016.

Meiotic behaviour in three interspecific three-way hybrids between ...

Indian Academy of Sciences (India)

The meiotic behaviour of three three-way interspecific promising hybrids (H17, H27, and H34) was evaluated. ... Arrangement of parental genomes in distinct ... vanna due to its physiological tolerance to low fertility acid ... nomic evaluations.

Duplicability of self-interacting human genes.

LENUS (Irish Health Repository)

Pérez-Bercoff, Asa

2010-01-01

BACKGROUND: There is increasing interest in the evolution of protein-protein interactions because this should ultimately be informative of the patterns of evolution of new protein functions within the cell. One model proposes that the evolution of new protein-protein interactions and protein complexes proceeds through the duplication of self-interacting genes. This model is supported by data from yeast. We examined the relationship between gene duplication and self-interaction in the human genome. RESULTS: We investigated the patterns of self-interaction and duplication among 34808 interactions encoded by 8881 human genes, and show that self-interacting proteins are encoded by genes with higher duplicability than genes whose proteins lack this type of interaction. We show that this result is robust against the system used to define duplicate genes. Finally we compared the presence of self-interactions amongst proteins whose genes have duplicated either through whole-genome duplication (WGD) or small-scale duplication (SSD), and show that the former tend to have more interactions in general. After controlling for age differences between the two sets of duplicates this result can be explained by the time since the gene duplication. CONCLUSIONS: Genes encoding self-interacting proteins tend to have higher duplicability than proteins lacking self-interactions. Moreover these duplicate genes have more often arisen through whole-genome rather than small-scale duplication. Finally, self-interacting WGD genes tend to have more interaction partners in general in the PIN, which can be explained by their overall greater age. This work adds to our growing knowledge of the importance of contextual factors in gene duplicability.

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.

A genetic ensemble approach for gene-gene interaction identification

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Ho Joshua WK

2010-10-01

Full Text Available Abstract Background It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases. Though a considerable effort has been put into developing statistical models and algorithmic strategies for identifying such interactions, the accurate identification of those genetic interactions has been proven to be very challenging. Methods In this paper, we propose a new approach for identifying such gene-gene and gene-environment interactions underlying complex diseases. This is a hybrid algorithm and it combines genetic algorithm (GA and an ensemble of classifiers (called genetic ensemble. Using this approach, the original problem of SNP interaction identification is converted into a data mining problem of combinatorial feature selection. By collecting various single nucleotide polymorphisms (SNP subsets as well as environmental factors generated in multiple GA runs, patterns of gene-gene and gene-environment interactions can be extracted using a simple combinatorial ranking method. Also considered in this study is the idea of combining identification results obtained from multiple algorithms. A novel formula based on pairwise double fault is designed to quantify the degree of complementarity. Conclusions Our simulation study demonstrates that the proposed genetic ensemble algorithm has comparable identification power to Multifactor Dimensionality Reduction (MDR and is slightly better than Polymorphism Interaction Analysis (PIA, which are the two most popular methods for gene-gene interaction identification. More importantly, the identification results generated by using our genetic ensemble algorithm are highly complementary to those obtained by PIA and MDR. Experimental results from our simulation studies and real world data application also confirm the effectiveness of the proposed genetic ensemble algorithm, as well as the potential benefits of

Transport with three-particle interaction

International Nuclear Information System (INIS)

Morawetz, K.

2000-01-01

Starting from a point - like two - and three - particle interaction the kinetic equation is derived. While the drift term of the kinetic equation turns out to be determined by the known Skyrme mean field the collision integral appears in two - and three - particle parts. The cross section results from the same microscopic footing and is naturally density dependent due to the three - particle force. By this way no hybrid model for drift and cross section is needed for nuclear transport. The resulting equation of state has besides the mean field correlation energy also a two - and three - particle correlation energy which both are calculated analytically for the ground state. These energies contribute to the equation of state and lead to an occurrence of a maximum at 3 times nuclear density in the total energy. (author)

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.

Research progress in machine learning methods for gene-gene interaction detection.

Science.gov (United States)

Peng, Zhe-Ye; Tang, Zi-Jun; Xie, Min-Zhu

2018-03-20

Complex diseases are results of gene-gene and gene-environment interactions. However, the detection of high-dimensional gene-gene interactions is computationally challenging. In the last two decades, machine-learning approaches have been developed to detect gene-gene interactions with some successes. In this review, we summarize the progress in research on machine learning methods, as applied to gene-gene interaction detection. It systematically examines the principles and limitations of the current machine learning methods used in genome wide association studies (GWAS) to detect gene-gene interactions, such as neural networks (NN), random forest (RF), support vector machines (SVM) and multifactor dimensionality reduction (MDR), and provides some insights on the future research directions in the field.

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.

Science.gov (United States)

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.

Development and application of an interaction network ontology for literature mining of vaccine-associated gene-gene interactions.

Science.gov (United States)

Hur, Junguk; Özgür, Arzucan; Xiang, Zuoshuang; He, Yongqun

2015-01-01

Literature mining of gene-gene interactions has been enhanced by ontology-based name classifications. However, in biomedical literature mining, interaction keywords have not been carefully studied and used beyond a collection of keywords. In this study, we report the development of a new Interaction Network Ontology (INO) that classifies >800 interaction keywords and incorporates interaction terms from the PSI Molecular Interactions (PSI-MI) and Gene Ontology (GO). Using INO-based literature mining results, a modified Fisher's exact test was established to analyze significantly over- and under-represented enriched gene-gene interaction types within a specific area. Such a strategy was applied to study the vaccine-mediated gene-gene interactions using all PubMed abstracts. The Vaccine Ontology (VO) and INO were used to support the retrieval of vaccine terms and interaction keywords from the literature. INO is aligned with the Basic Formal Ontology (BFO) and imports terms from 10 other existing ontologies. Current INO includes 540 terms. In terms of interaction-related terms, INO imports and aligns PSI-MI and GO interaction terms and includes over 100 newly generated ontology terms with 'INO_' prefix. A new annotation property, 'has literature mining keywords', was generated to allow the listing of different keywords mapping to the interaction types in INO. Using all PubMed documents published as of 12/31/2013, approximately 266,000 vaccine-associated documents were identified, and a total of 6,116 gene-pairs were associated with at least one INO term. Out of 78 INO interaction terms associated with at least five gene-pairs of the vaccine-associated sub-network, 14 terms were significantly over-represented (i.e., more frequently used) and 17 under-represented based on our modified Fisher's exact test. These over-represented and under-represented terms share some common top-level terms but are distinct at the bottom levels of the INO hierarchy. The analysis of these

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

Science.gov (United States)

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.

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...

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

Science.gov (United States)

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 Nonlinear Model for Gene-Based Gene-Environment Interaction

Directory of Open Access Journals (Sweden)

Jian Sa

2016-06-01

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

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

Directory of Open Access Journals (Sweden)

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

Burnout Disrupts Anxiety Buffer Functioning Among Nurses: A Three-Way Interaction Model

Directory of Open Access Journals (Sweden)

Elena Trifiletti

2017-08-01

Full Text Available Over the last 40 years, job burnout has attracted a great deal of attention among researchers and practitioners and, after decades of research and interventions, it is still regarded as an important issue. With the aim of extending the Anxiety Buffer Disruption Theory (ABDT, in this paper we argue that high levels of burnout may disrupt the anxiety buffer functioning that protects people from death concerns. ABDT was developed from Terror Management Theory (TMT. According to TMT, reminders of one’s mortality are an essential part of humans’ daily experience and have the potential to awake paralyzing fear and anxiety. In order to cope with death concerns, people typically activate an anxiety-buffering system centered on their cultural worldview and self-esteem. Recent ABDT research shows that individuals with post-traumatic stress disorder are unable to activate such anxiety buffering defenses. In line with these results, we hypothesized that the burnout syndrome may have similar effects, and that individuals with higher levels of burnout will be less likely to activate an anxiety buffering response when their mortality is made salient. Participants were 418 nurses, who completed a questionnaire including: a mortality salience (MS manipulation, a delay manipulation, and measures of burnout, work-related self-efficacy, and representation of oneself as a valuable caregiver. Nurses are daily exposed both to the risk of burnout and to mortality reminders, and thus constituted an ideal population for this study. In line with an anxiety buffer disruption hypothesis, we found a significant three-way interaction between burnout, MS and delay. Participants with lower levels of burnout reported higher levels of self-efficacy and a more positive representation as caregivers in the MS condition compared to the control condition, when there was a delay between MS manipulation and the assessment of the dependent measures. The difference was non

Two-Way Interactive Television: An Emerging Technology for University Level Business School Instruction.

Science.gov (United States)

Heiens, Richard A.; Hulse, Deborah B.

1996-01-01

An organizational behavior course was delivered via two-way interactive television to a campus site (71 students) and three remote locations (48 students). Remote students were slightly older and predominantly female. There were no significant differences in academic performance between on-campus and remote students. (SK)

Responding to Destructive Interpersonal Interactions: A way forward ...

African Journals Online (AJOL)

Responding to Destructive Interpersonal Interactions: A way forward for ... cultural intolerance and other destructive interpersonal interactions and relationships clearly ... This work is licensed under a Creative Commons Attribution 3.0 License.

SNP-SNP interactions of three new pri-miRNAs with the target gene PGC and multidimensional analysis of H. pylori in the gastric cancer/atrophic gastritis risk in a Chinese population.

Science.gov (United States)

Xu, Qian; Wu, Ye-Feng; Li, Ying; He, Cai-Yun; Sun, Li-Ping; Liu, Jing-Wei; Yuan, Yuan

2016-04-26

Gastric cancer (GC) is a multistep complex disease involving multiple genes, and gene-gene interactions have a greater effect than a single gene in determining cancer susceptibility. This study aimed to explore the interaction of the let-7e rs8111742, miR-365b rs121224, and miR-4795 rs1002765 single nucleotide polymorphisms (SNPs) with SNPs of the predicted target gene PGC and Helicobacter pylori status in GC and atrophic gastritis (AG) risk. Three miRNA SNPs and seven PGC SNPs were detected in 2448 cases using the Sequenom MassArray platform. Two pairwise combinations of miRNA and PGC SNPs were associated with increased AG risk (let-7e rs8111742 - PGC rs6458238 and miR-4795 rs1002765 - PGC rs9471643). Singly, miR-365b rs121224 and PGC rs6912200 had no effect individually but in combination they demonstrated an epistatic interaction associated with AG risk. Similarly, let-7e rs8111742 and miR-4795 rs1002765 SNPs interacted with H. pylori infection to increase GC risk (rs8111742: Pinteraction = 0.024; rs1002765: Pinteraction = 0.031, respectively). A three-dimensional interaction analysis found miR-4795 rs1002765, PGC rs9471643, and H. pylori infection positively interacted to increase AG risk (Pinteraction = 0.027). Also, let-7e rs8111742, PGC rs6458238, and H. pylori infection positively interacted to increase GC risk (Pinteraction = 0.036). Furthermore, both of these three-dimensional interactions had a dosage-effect correspondence (Ptrend < 0.001) and were verified by MDR. In conclusion, the miRNAs SNPs (let-7e rs8111742 and miR-4795 rs1002765) might have more superior efficiency when combined with PGC SNPs and/or H. pylori for GC or AG risk than a single SNP on its own.

Modeling Gene-Environment Interactions With Quasi-Natural Experiments.

Science.gov (United States)

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.

Environmental confounding in gene-environment interaction studies.

Science.gov (United States)

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

2013-07-01

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

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

Science.gov (United States)

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.

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.

Gene-gene interactions and gene polymorphisms of VEGFA and EG-VEGF gene systems in recurrent pregnancy loss.

Science.gov (United States)

Su, Mei-Tsz; Lin, Sheng-Hsiang; Chen, Yi-Chi; Kuo, Pao-Lin

2014-06-01

Both vascular endothelial growth factor A (VEGFA) and endocrine gland-derived vascular endothelial growth factor (EG-VEGF) systems play major roles in angiogenesis. A body of evidence suggests VEGFs regulate critical processes during pregnancy and have been associated with recurrent pregnancy loss (RPL). However, little information is available regarding the interaction of these two major major angiogenesis-related systems in early human pregnancy. This study was conducted to investigate the association of gene polymorphisms and gene-gene interaction among genes in VEGFA and EG-VEGF systems and idiopathic RPL. A total of 98 women with history of idiopathic RPL and 142 controls were included, and 5 functional SNPs selected from VEGFA, KDR, EG-VEGF (PROK1), PROKR1 and PROKR2 were genotyped. We used multifactor dimensionality reduction (MDR) analysis to choose a best model and evaluate gene-gene interactions. Ingenuity pathways analysis (IPA) was introduced to explore possible complex interactions. Two receptor gene polymorphisms [KDR (Q472H) and PROKR2 (V331M)] were significantly associated with idiopathic RPL (P<0.01). The MDR test revealed that the KDR (Q472H) polymorphism was the best loci to be associated with RPL (P=0.02). IPA revealed EG-VEGF and VEGFA systems shared several canonical signaling pathways that may contribute to gene-gene interactions, including the Akt, IL-8, EGFR, MAPK, SRC, VHL, HIF-1A and STAT3 signaling pathways. Two receptor gene polymorphisms [KDR (Q472H) and PROKR2 (V331M)] were significantly associated with idiopathic RPL. EG-VEGF and VEGFA systems shared several canonical signaling pathways that may contribute to gene-gene interactions, including the Akt, IL-8, EGFR, MAPK, SRC, VHL, HIF-1A and STAT3.

Polymorphisms in ATP-binding cassette transporter genes and interaction with diet and life style factors in relation to colorectal cancer in a Danish prospective case-cohort study

DEFF Research Database (Denmark)

Kopp, Tine Iskov; Andersen, Vibeke; Tjonneland, Anne

2015-01-01

to assess whether polymorphisms in ABCB1, ABCC2 and ABCG2 were associated with risk of colorectal cancer (CRC) and to investigate gene-environment (dietary factors, smoking and use of non-steroidal anti-inflammatory drugs) and gene-gene interactions between previously studied polymorphisms in IL1B and IL10......The ATP-binding cassette (ABC) transporter family transports various molecules across the enterocytes in the gut protecting the intestine against potentially harmful substances. Moreover, ABC transporters are involved in mucosal immune defence through interaction with cytokines. The study aimed...... of the polymorphisms were associated with CRC, but ABCB1 and ABCG2 haplotypes were associated with risk of CRC. ABCB1/rs1045642 interacted with intake of cereals and fiber (p-Value for interaction (Pint) = 0.001 and 0.01, respectively). In a three-way analysis, both ABCB1/rs1045642 and ABCG2/rs2231137 in combination...

Gene-Gene and Gene-Environment Interactions in the Etiology of Breast Cancer

National Research Council Canada - National Science Library

Adegoke, Olufemi

2003-01-01

The objective of this CDA is to evaluate the gene-gene and gene-environment interactions in the etiology of breast cancer in two ongoing case-control studies, the Shanghai Breast Cancer Study (SBCS...

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

Science.gov (United States)

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

N-way FRET microscopy of multiple protein-protein interactions in live cells.

Directory of Open Access Journals (Sweden)

Adam D Hoppe

Full Text Available Fluorescence Resonance Energy Transfer (FRET microscopy has emerged as a powerful tool to visualize nanoscale protein-protein interactions while capturing their microscale organization and millisecond dynamics. Recently, FRET microscopy was extended to imaging of multiple donor-acceptor pairs, thereby enabling visualization of multiple biochemical events within a single living cell. These methods require numerous equations that must be defined on a case-by-case basis. Here, we present a universal multispectral microscopy method (N-Way FRET to enable quantitative imaging for any number of interacting and non-interacting FRET pairs. This approach redefines linear unmixing to incorporate the excitation and emission couplings created by FRET, which cannot be accounted for in conventional linear unmixing. Experiments on a three-fluorophore system using blue, yellow and red fluorescent proteins validate the method in living cells. In addition, we propose a simple linear algebra scheme for error propagation from input data to estimate the uncertainty in the computed FRET images. We demonstrate the strength of this approach by monitoring the oligomerization of three FP-tagged HIV Gag proteins whose tight association in the viral capsid is readily observed. Replacement of one FP-Gag molecule with a lipid raft-targeted FP allowed direct observation of Gag oligomerization with no association between FP-Gag and raft-targeted FP. The N-Way FRET method provides a new toolbox for capturing multiple molecular processes with high spatial and temporal resolution in living cells.

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.

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

Science.gov (United States)

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

Evolutionary adaptation in three-way interactions between plants, microbes and arthropods

NARCIS (Netherlands)

Biere, A.; Tack, A.J.M.

2013-01-01

Evolutionary adaptations in interactions between plants, microbes and arthropods are generally studied in interactions that involve only two of these groups, that is, plants and microbes, plants and arthropods or arthropods and microbes. We review the accumulating evidence from a wide variety of

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

Directory of Open Access Journals (Sweden)

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.

Science.gov (United States)

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.

The role of gene-gene interaction in the prediction of criminal behavior.

Science.gov (United States)

Boutwell, Brian B; Menard, Scott; Barnes, J C; Beaver, Kevin M; Armstrong, Todd A; Boisvert, Danielle

2014-04-01

A host of research has examined the possibility that environmental risk factors might condition the influence of genes on various outcomes. Less research, however, has been aimed at exploring the possibility that genetic factors might interact to impact the emergence of human traits. Even fewer studies exist examining the interaction of genes in the prediction of behavioral outcomes. The current study expands this body of research by testing the interaction between genes involved in neural transmission. Our findings suggest that certain dopamine genes interact to increase the odds of criminogenic outcomes in a national sample of Americans. Copyright © 2014 Elsevier Inc. All rights reserved.

Genotypes Do Not Confer Risk For Delinquency ut Rather Alter Susceptibility to Positive and Negative Environmental Factors: Gene-Environment Interactions of BDNF Val66Met, 5-HTTLPR, and MAOA-uVNTR

Science.gov (United States)

Comasco, Erika; Hodgins, Sheilagh; Oreland, Lars; Åslund, Cecilia

2015-01-01

Background: Previous evidence of gene-by-environment interactions associated with emotional and behavioral disorders is contradictory. Differences in findings may result from variation in valence and dose of the environmental factor, and/or failure to take account of gene-by-gene interactions. The present study investigated interactions between the brain-derived neurotrophic factor gene (BDNF Val66Met), the serotonin transporter gene-linked polymorphic region (5-HTTLPR), the monoamine oxidase A (MAOA-uVNTR) polymorphisms, family conflict, sexual abuse, the quality of the child-parent relationship, and teenage delinquency. Methods: In 2006, as part of the Survey of Adolescent Life in Västmanland, Sweden, 1 337 high-school students, aged 17–18 years, anonymously completed questionnaires and provided saliva samples for DNA analyses. Results: Teenage delinquency was associated with two-, three-, and four-way interactions of each of the genotypes and the three environmental factors. Significant four-way interactions were found for BDNF Val66Met × 5-HTTLPR×MAOA-uVNTR × family conflicts and for BDNF Val66Met × 5-HTTLPR×MAOA-uVNTR × sexual abuse. Further, the two genotype combinations that differed the most in expression levels (BDNF Val66Met Val, 5-HTTLPR LL, MAOA-uVNTR LL [girls] and L [boys] vs BDNF Val66Met Val/Met, 5-HTTLPR S/LS, MAOA-uVNTR S/SS/LS) in interaction with family conflict and sexual abuse were associated with the highest delinquency scores. The genetic variants previously shown to confer vulnerability for delinquency (BDNF Val66Met Val/Met × 5-HTTLPR S × MAOA-uVNTR S) were associated with the lowest delinquency scores in interaction with a positive child-parent relationship. Conclusions: Functional variants of the MAOA-uVNTR, 5-HTTLPR, and BDNF Val66Met, either alone or in interaction with each other, may be best conceptualized as modifying sensitivity to environmental factors that confer either risk or protection for teenage delinquency. PMID

A deeper look at two concepts of measuring gene-gene interactions: logistic regression and interaction information revisited.

Science.gov (United States)

Mielniczuk, Jan; Teisseyre, Paweł

2018-03-01

Detection of gene-gene interactions is one of the most important challenges in genome-wide case-control studies. Besides traditional logistic regression analysis, recently the entropy-based methods attracted a significant attention. Among entropy-based methods, interaction information is one of the most promising measures having many desirable properties. Although both logistic regression and interaction information have been used in several genome-wide association studies, the relationship between them has not been thoroughly investigated theoretically. The present paper attempts to fill this gap. We show that although certain connections between the two methods exist, in general they refer two different concepts of dependence and looking for interactions in those two senses leads to different approaches to interaction detection. We introduce ordering between interaction measures and specify conditions for independent and dependent genes under which interaction information is more discriminative measure than logistic regression. Moreover, we show that for so-called perfect distributions those measures are equivalent. The numerical experiments illustrate the theoretical findings indicating that interaction information and its modified version are more universal tools for detecting various types of interaction than logistic regression and linkage disequilibrium measures. © 2017 WILEY PERIODICALS, INC.

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.

Bootstrap confidence intervals for three-way methods

NARCIS (Netherlands)

Kiers, Henk A.L.

Results from exploratory three-way analysis techniques such as CANDECOMP/PARAFAC and Tucker3 analysis are usually presented without giving insight into uncertainties due to sampling. Here a bootstrap procedure is proposed that produces percentile intervals for all output parameters. Special

Animal models of gene-environment interactions in schizophrenia.

Science.gov (United States)

Ayhan, Yavuz; Sawa, Akira; Ross, Christopher A; Pletnikov, Mikhail V

2009-12-07

The pathogenesis of schizophrenia and related mental illnesses likely involves multiple interactions between susceptibility genes of small effects and environmental factors. Gene-environment interactions occur across different stages of neurodevelopment to produce heterogeneous clinical and pathological manifestations of the disease. The main obstacle for mechanistic studies of gene-environment interplay has been the paucity of appropriate experimental systems for elucidating the molecular pathways that mediate gene-environment interactions relevant to schizophrenia. Recent advances in psychiatric genetics and a plethora of experimental data from animal studies allow us to suggest a new approach to gene-environment interactions in schizophrenia. We propose that animal models based on identified genetic mutations and measurable environment factors will help advance studies of the molecular mechanisms of gene-environment interplay.

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

Directory of Open Access Journals (Sweden)

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

Gene-based interaction analysis shows GABAergic genes interacting with parenting in adolescent depressive symptoms

NARCIS (Netherlands)

Van Assche, Evelien; Moons, Tim; Cinar, Ozan; Viechtbauer, Wolfgang; Oldehinkel, Albertine J.; Van Leeuwen, Karla; Verschueren, Karine; Colpin, Hilde; Lambrechts, Diether; Van den Noortgate, Wim; Goossens, Luc; Claes, Stephan; van Winkel, Ruud

2017-01-01

BACKGROUND: Most gene-environment interaction studies (G × E) have focused on single candidate genes. This approach is criticized for its expectations of large effect sizes and occurrence of spurious results. We describe an approach that accounts for the polygenic nature of most psychiatric

A Three-Way Transcriptomic Interaction Study of a Biocontrol Agent (Clonostachys rosea), a Fungal Pathogen (Helminthosporium solani), and a Potato Host (Solanum tuberosum).

Science.gov (United States)

Lysøe, Erik; Dees, Merete W; Brurberg, May Bente

2017-08-01

Helminthosporium solani causes silver scurf, which affects the quality of potato. The biocontrol agent Clonostachys rosea greatly limited the severity of silver scurf symptoms and amount of H. solani genomic DNA in laboratory experiments. Transcriptomic analysis during interaction showed that H. solani gene expression was highly reduced when coinoculated with the biocontrol agent C. rosea, whereas gene expression of C. rosea was clearly boosted as a response to the pathogen. The most notable upregulated C. rosea genes were those encoding proteins involved in cellular response to oxidative stress, proteases, G-protein signaling, and the methyltransferase LaeA. The most notable potato response to both fungi was downregulation of defense-related genes and mitogen-activated protein kinase kinase kinases. At a later stage, this shifted, and most potato defense genes were turned on, especially those involved in terpenoid biosynthesis when H. solani was present. Some biocontrol-activated defense-related genes in potato were upregulated during early interaction with C. rosea alone that were not triggered by H. solani alone. Our results indicate that the reductions of silver scurf using C. rosea are probably due to a combination of mechanisms, including mycoparasitism, biocontrol-activated stimulation of plant defense mechanisms, microbial competition for nutrients, space, and antibiosis.

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...

Every which way--nanos gene regulation in echinoderms.

Science.gov (United States)

Oulhen, Nathalie; Wessel, Gary M

2014-03-01

Nanos is an essential factor of germ line success in all animals tested. This gene encodes a Zn-finger RNA-binding protein that in complex with its partner pumilio binds to and changes the fate of several known transcripts. We summarize here the documented functions of Nanos in several key organisms, and then emphasize echinoderms as a working model for how nanos expression is regulated. Nanos presence outside of the target cells is often detrimental to the animal, and in sea urchins, nanos expression appears to be regulated at every step of transcription, and post-transcriptional activity, making this gene product exciting, every which way. Copyright © 2013 Wiley Periodicals, Inc.

Towards Ways to Promote Interaction in Digital Learning Spaces

OpenAIRE

Olsson , Hanna ,

2012-01-01

Part 7: Doctoral Student Papers; International audience; Social learning is dependent on social interactions. I am exploring ways to promote interaction in Digital Learning Spaces. As theoretical framework I use the types of interaction between learner, instructor and content. That learners feel isolated and lonely in DLSs is a problem which comes at high cost for social learning. My aim is to promote social interaction by offering the edentity: a system for making participants visible to eac...

A review for detecting gene-gene interactions using machine learning methods in genetic epidemiology.

Science.gov (United States)

Koo, Ching Lee; Liew, Mei Jing; Mohamad, Mohd Saberi; Salleh, Abdul Hakim Mohamed

2013-01-01

Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs), support vector machine (SVM), and random forests (RFs) in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.

A Review for Detecting Gene-Gene Interactions Using Machine Learning Methods in Genetic Epidemiology

Directory of Open Access Journals (Sweden)

Ching Lee Koo

2013-01-01

Full Text Available Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs, support vector machine (SVM, and random forests (RFs in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.

Study of neutral red interaction with DNA by resolution of rank deficient multi-way fluorescence data

DEFF Research Database (Denmark)

Moghaddam, Fatemeh Ghasemi; Kompany Zare, Mohsen; Gholami, Somayeh

2012-01-01

The interaction of neutral red (NR) as an efficient anticancer drug with DNA was studied under physiological pH condition. Three-way data array were recorded by measuring excitation-emission fluorescence during the titration of neutral red with DNA at constant pH. The acid-base equilibrium constant...

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

Science.gov (United States)

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.

Genome-Wide Prediction of the Performance of Three-Way Hybrids in Barley

Directory of Open Access Journals (Sweden)

Zuo Li

2017-03-01

Full Text Available Predicting the grain yield performance of three-way hybrids is challenging. Three-way crosses are relevant for hybrid breeding in barley ( L. and maize ( L. adapted to East Africa. The main goal of our study was to implement and evaluate genome-wide prediction approaches of the performance of three-way hybrids using data of single-cross hybrids for a scenario in which parental lines of the three-way hybrids originate from three genetically distinct subpopulations. We extended the ridge regression best linear unbiased prediction (RRBLUP and devised a genomic selection model allowing for subpopulation-specific marker effects (GSA-RRBLUP: general and subpopulation-specific additive RRBLUP. Using an empirical barley data set, we showed that applying GSA-RRBLUP tripled the prediction ability of three-way hybrids from 0.095 to 0.308 compared with RRBLUP, modeling one additive effect for all three subpopulations. The experimental findings were further substantiated with computer simulations. Our results emphasize the potential of GSA-RRBLUP to improve genome-wide hybrid prediction of three-way hybrids for scenarios of genetically diverse parental populations. Because of the advantages of the GSA-RRBLUP model in dealing with hybrids from different parental populations, it may also be a promising approach to boost the prediction ability for hybrid breeding programs based on genetically diverse heterotic groups.

Genetic basis of autism: is there a way forward?

Science.gov (United States)

Eapen, Valsamma

2011-05-01

This paper outlines some of the key findings from genetic research carried out in the last 12-18 months, which indicate that autism spectrum disorder (ASD) is a complex disorder involving interactions between genetic, epigenetic and environmental factors. The current literature highlights the presence of genetic and phenotypic heterogeneity in ASD with a number of underlying pathogenetic mechanisms. In this regard, there are at least three phenotypic presentations with distinct genetic underpinnings: autism plus phenotype characterized by syndromic ASD caused by rare, single-gene disorders; broad autism phenotype caused by genetic variations in single or multiple genes, each of these variations being common and distributed continually in the general population, but resulting in varying clinical phenotypes when it reaches a certain threshold through complex gene-gene and gene-environment interactions; and severe and specific phenotype caused by 'de-novo' mutations in the patient or transmitted through asymptomatic carriers of such mutation. Understanding the neurobiological processes by which genotypes become phenotypes, along with the advances in developmental neuroscience and neuronal networks at the cellular and molecular level, is paving the way for translational research involving targeted interventions of affected molecular pathways and early intervention programs that promote normal brain responses to stimuli and alter the developmental trajectory.

Towards Understanding the Two Way Interaction Effects of Extraversion and Openness to Experience on Career Commitment

Science.gov (United States)

Arora, Ridhi; Rangnekar, Santosh

2016-01-01

In this study, we examined potential two-way interaction effects of the Big Five personality traits extraversion and openness to experience on career commitment measured in terms of three components of career identity, career resilience, and career planning. Participants included 450 managers from public and private sector organizations in North…

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.

Science.gov (United States)

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

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Every which way – nanos gene regulation in echinoderms

Science.gov (United States)

Oulhen, Nathalie; Wessel, Gary M.

2014-01-01

Nanos is an essential factor of germ line success in all animals tested. This gene encodes a Zn-finger RNA-binding protein that in complex with its partner pumilio, binds to and changes the fate of several known transcripts. We summarize here the documented functions of nanos in several key organisms, and then emphasize echinoderms as a working model for how nanos expression is regulated. Nanos presence outside of the target cells is often detrimental to the animal, and in sea urchins, nanos expression appears to be regulated at every step of transcription, and post-transcriptional activity, making this gene product exciting, every which way. PMID:24376110

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

Science.gov (United States)

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

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

Directory of Open Access Journals (Sweden)

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.

Three-way flexible cantilever probes for static contact

DEFF Research Database (Denmark)

Wang, Fei; Petersen, Dirch Hjorth; Jensen, Helle Vendelbo

2011-01-01

In micro four-point probe measurements, three-way flexible L-shaped cantilever probes show significant advantages over conventional straight cantilever probes. The L-shaped cantilever allows static contact to the sample surface which reduces the frictional wear of the cantilever tips. We analyze...

Novel interactions between vertebrate Hox genes

NARCIS (Netherlands)

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.

Science.gov (United States)

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.

Synergistic interactions between RAD5, RAD16, and RAD54, three partially homologous yeast DNA repair genes each in a different repair pathway

International Nuclear Information System (INIS)

Glassner, B.J.; Mortimer, R.K.

1994-01-01

Considerable homology has recently been noted between the proteins encoded by the RAD5, RAD16 and RAD54 genes of Saccharomyces cerevisiae. These genes are members of the RAD6, RAD3 and RAD50 epistasis groups, respectively, which correspond to the three major DNA repair pathways in yeast. These proteins also share homology with other eucaryotic proteins, including those encoded by SNF2 and MO1 of yeast, brahma and lodestar of Drosophila and the human ERCC6 gene. The homology shares features with known helicases, suggesting a newly identified helicase subfamily. We have constructed a series of congenic single-, double- and triple-deletion mutants involving RAD5, RAD16 and RAD54 to examine the interactions between these genes. Each deletion mutation alone has only a moderate effect on survival after exposure to UV radiation. Each pairwise-double mutant exhibits marked synergism. The triple-deletion mutant displays further synergism. These results confirm the assignment of the RAD54 gene to the RAD50 epistasis group and suggest that the RAD16 gene plays a larger role in DNA repair after exposure to UV radiation than has been suggested previously. Additionally, the proteins encoded by RAD5, RAD16, and RAD54 may compete for the same substrate after damage induced by UV radiation, possibly at an early step in their respective pathways. 49 refs., 6 figs., 2 tabs

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

Science.gov (United States)

Kerwin, Rachel E; Feusier, Julie; Muok, Alise; Lin, Catherine; Larson, Brandon; Copeland, Daniel; Corwin, Jason A; Rubin, Matthew J; Francisco, Marta; Li, Baohua; Joseph, Bindu; Weinig, Cynthia; Kliebenstein, Daniel J

2017-08-01

Despite the growing number of studies showing that genotype × environment and epistatic interactions control fitness, the influences of epistasis × environment interactions on adaptive trait evolution remain largely uncharacterized. Across three field trials, we quantified aliphatic glucosinolate (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 was primarily influenced by additive and epistatic genetic variation, leaf damage was primarily influenced by environmental variation and relative fitness was primarily influenced by epistasis and epistasis × environment interactions. Epistasis × environment interactions accounted for up to 48% of the relative fitness variation in the field. At a single field site, the impact of epistasis on relative fitness varied significantly over 2 yr, showing that epistasis × environment interactions within a location can be temporally dynamic. These results suggest that the environmental dependency of epistasis can profoundly influence the response to selection, shaping the adaptive trajectories of natural populations in complex ways, and deserves further consideration in future evolutionary studies. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

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

Directory of Open Access Journals (Sweden)

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...

Characterization of three-way automotive catalysts

Energy Technology Data Exchange (ETDEWEB)

Kenik, E.A.; More, K.L. [Oak Ridge National Laboratory, TN (United States); LaBarge, W. [General Motors-AC Delco Systems, Flint, MI (United States)] [and others

1995-05-01

This has been the second year of a CRADA between General Motors - AC Delco Systems (GM-ACDS) and Martin Marietta Energy Systems (MMES) aimed at improved performance/lifetime of platinum-rhodium based three-way-catalysts (TWC) for automotive emission control systems. While current formulations meet existing emission standards, higher than optimum Pt-Rh loadings are often required. In additionk, more stringent emission standards have been imposed for the near future, demanding improved performance and service life from these catalysts. Understanding the changes of TWC conversion efficiency with ageing is a critical need in improving these catalysts.

Genome-Wide Analysis in Three Fusarium Pathogens Identifies Rapidly Evolving Chromosomes and Genes Associated with Pathogenicity

Science.gov (United States)

Sperschneider, Jana; Gardiner, Donald M.; Thatcher, Louise F.; Lyons, Rebecca; Singh, Karam B.; Manners, John M.; Taylor, Jennifer M.

2015-01-01

Pathogens and hosts are in an ongoing arms race and genes involved in host–pathogen interactions are likely to undergo diversifying selection. Fusarium plant pathogens have evolved diverse infection strategies, but how they interact with their hosts in the biotrophic infection stage remains puzzling. To address this, we analyzed the genomes of three Fusarium plant pathogens for genes that are under diversifying selection. We found a two-speed genome structure both on the chromosome and gene group level. Diversifying selection acts strongly on the dispensable chromosomes in Fusarium oxysporum f. sp. lycopersici and on distinct core chromosome regions in Fusarium graminearum, all of which have associations with virulence. Members of two gene groups evolve rapidly, namely those that encode proteins with an N-terminal [SG]-P-C-[KR]-P sequence motif and proteins that are conserved predominantly in pathogens. Specifically, 29 F. graminearum genes are rapidly evolving, in planta induced and encode secreted proteins, strongly pointing toward effector function. In summary, diversifying selection in Fusarium is strongly reflected as genomic footprints and can be used to predict a small gene set likely to be involved in host–pathogen interactions for experimental verification. PMID:25994930

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

Directory of Open Access Journals (Sweden)

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.

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

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

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.

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....

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

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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.

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.

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.

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.

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

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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.

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

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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 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.

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.

Heat Shock Protein Genes Undergo Dynamic Alteration in Their Three-Dimensional Structure and Genome Organization in Response to Thermal Stress.

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Chowdhary, Surabhi; Kainth, Amoldeep S; Gross, David S

2017-12-15

Three-dimensional (3D) chromatin organization is important for proper gene regulation, yet how the genome is remodeled in response to stress is largely unknown. Here, we use a highly sensitive version of chromosome conformation capture in combination with fluorescence microscopy to investigate Heat Shock Protein ( HSP ) gene conformation and 3D nuclear organization in budding yeast. In response to acute thermal stress, HSP genes undergo intense intragenic folding interactions that go well beyond 5'-3' gene looping previously described for RNA polymerase II genes. These interactions include looping between upstream activation sequence (UAS) and promoter elements, promoter and terminator regions, and regulatory and coding regions (gene "crumpling"). They are also dynamic, being prominent within 60 s, peaking within 2.5 min, and attenuating within 30 min, and correlate with HSP gene transcriptional activity. With similarly striking kinetics, activated HSP genes, both chromosomally linked and unlinked, coalesce into discrete intranuclear foci. Constitutively transcribed genes also loop and crumple yet fail to coalesce. Notably, a missense mutation in transcription factor TFIIB suppresses gene looping, yet neither crumpling nor HSP gene coalescence is affected. An inactivating promoter mutation, in contrast, obviates all three. Our results provide evidence for widespread, transcription-associated gene crumpling and demonstrate the de novo assembly and disassembly of HSP gene foci. Copyright © 2017 American Society for Microbiology.

[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

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.

Four-particle scattering with three-particle interactions

International Nuclear Information System (INIS)

Adhikari, S.K.

1979-01-01

The four-particle scattering formalism proposed independently by Alessandrini, by Mitra et al., by Rosenberg, and by Takahashi and Mishima is extended to include a possible three-particle interaction. The kernel of the new equations we get contain both two- and three-body connected parts and gets four-body connected after one iteration. On the other hand, the kernel of the original equations in the absence of three-particle interactions does not have a two-body connected part. We also write scattering equations for the transition operators connecting the two-body fragmentation channels. They are generalization of the Sloan equations in the presence of three-particle interactions. We indicate how to include approximately the effect of a weak three-particle interaction in a practical four-particle scattering calculation

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

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.

Three-dimensional theory for interaction between atomic ensembles and free-space light

International Nuclear Information System (INIS)

Duan, L.-M.; Cirac, J.I.; Zoller, P.

2002-01-01

Atomic ensembles have shown to be a promising candidate for implementations of quantum information processing by many recently discovered schemes. All these schemes are based on the interaction between optical beams and atomic ensembles. For description of these interactions, one assumed either a cavity-QED model or a one-dimensional light propagation model, which is still inadequate for a full prediction and understanding of most of the current experimental efforts that are actually taken in the three-dimensional free space. Here, we propose a perturbative theory to describe the three-dimensional effects in interaction between atomic ensembles and free-space light with a level configuration important for several applications. The calculations reveal some significant effects that were not known before from the other approaches, such as the inherent mode-mismatching noise and the optimal mode-matching conditions. The three-dimensional theory confirms the collective enhancement of the signal-to-noise ratio which is believed to be one of the main advantages of the ensemble-based quantum information processing schemes, however, it also shows that this enhancement needs to be understood in a more subtle way with an appropriate mode-matching method

Long-range interactions among three alkali-metal atoms

International Nuclear Information System (INIS)

Marinescu, M.; Starace, A.F.

1996-01-01

The long-range asymptotic form of the interaction potential surface for three neutral alkali-metal atoms in their ground states may be expressed as an expansion in inverse powers of inter-nuclear distances. The first leading powers are proportional to the dispersion coefficients for pairwise atomic interactions. They are followed by a term responsible for a three body dipole interaction. The authors results consist in evaluation of the three body dipole interaction coefficient between three alkali-metal atoms. The generalization to long-range n atom interaction terms will be discussed qualitatively

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.

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

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.

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...

TRAP: A Three-Way Handshake Server for TCP Connection Establishment

Directory of Open Access Journals (Sweden)

Fu-Hau Hsu

2016-11-01

Full Text Available Distributed denial of service attacks have become more and more frequent nowadays. In 2013, a massive distributed denial of service (DDoS attack was launched against Spamhaus causing the service to shut down. In this paper, we present a three-way handshaking server for Transmission Control Protocol (TCP connection redirection utilizing TCP header options. When a legitimate client attempted to connect to a server undergoing an SYN-flood DDoS attack, it will try to initiate a three-way handshake. After it has successfully established a connection, the server will reply with a reset (RST packet, in which a new server address and a secret is embedded. The client can, thus, connect to the new server that only accepts SYN packets with the corrected secret using the supplied secret.

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

Science.gov (United States)

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

Association of COMT and COMT-DRD2 interaction with creative potential

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Shun eZhang

2014-04-01

Full Text Available Several lines of evidence suggest that genes involved in dopamine (DA transmission may contribute to creativity. Among these genes, the catechol-O-methyltransferase gene (COMT and the dopamine D2 receptor gene (DRD2 are the most promising candidates. Our previous study has revealed evidence for the involvement of DRD2 in creative potential. The present study extended our previous study by systematically exploring the association of COMT with creative potential as well as the interaction between COMT and DRD2. Twelve single nucleotide polymorphisms (SNPs covering COMT were genotyped in 543 healthy Chinese college students whose creative potentials were assessed by divergent thinking tests. Single SNP analysis showed that rs174697 was nominally associated with verbal originality, two SNPs (rs737865 and rs5993883 were nominally associated with figural fluency, and two SNPs (rs737865 and rs4680 were nominally associated with figural originality. Haplotype analysis showed that, the TCT and CCT haplotype (rs737865-rs174675-rs5993882 were nominally associated with figural originality, and the TATGCAG and CGCGGGA haplotype (rs4646312-rs6269-rs4633-rs6267-rs4818-rs4680-rs769224 were nominally associated with figural originality and verbal flexibility, respectively. However, none of these nominal findings survived correction for multiple testing. Gene-gene interaction analysis identified one significant four-way interaction of rs174675 (COMT, rs174697 (COMT, rs1076560 (DRD2 and rs4436578 (DRD2 on verbal fluency, one significant four-way interaction of rs174675 (COMT, rs4818 (COMT, rs1076560 (DRD2 and rs4648317 (DRD2 on verbal flexibility, and one significant three-way interaction of rs5993883 (COMT, rs4648319 (DRD2 and rs4648317 (DRD2 on figural flexibility. In conclusion, the present study provides nominal evidence for the involvement of COMT in creative potential and suggests that DA related genes may act in coordination to contribute to creativity.

Three gene expression vector sets for concurrently expressing multiple genes in Saccharomyces cerevisiae.

Science.gov (United States)

Ishii, Jun; Kondo, Takashi; Makino, Harumi; Ogura, Akira; Matsuda, Fumio; Kondo, Akihiko

2014-05-01

Yeast has the potential to be used in bulk-scale fermentative production of fuels and chemicals due to its tolerance for low pH and robustness for autolysis. However, expression of multiple external genes in one host yeast strain is considerably labor-intensive due to the lack of polycistronic transcription. To promote the metabolic engineering of yeast, we generated systematic and convenient genetic engineering tools to express multiple genes in Saccharomyces cerevisiae. We constructed a series of multi-copy and integration vector sets for concurrently expressing two or three genes in S. cerevisiae by embedding three classical promoters. The comparative expression capabilities of the constructed vectors were monitored with green fluorescent protein, and the concurrent expression of genes was monitored with three different fluorescent proteins. Our multiple gene expression tool will be helpful to the advanced construction of genetically engineered yeast strains in a variety of research fields other than metabolic engineering. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

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

Science.gov (United States)

Keers, Robert; Pluess, Michael

2017-12-01

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

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

Science.gov (United States)

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

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.

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

Science.gov (United States)

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.

Driven, autoresonant three-oscillator interactions

International Nuclear Information System (INIS)

Yaakobi, O.; Friedland, L.; Henis, Z.

2007-01-01

An efficient control scheme of resonant three-oscillator interactions using an external chirped frequency drive is suggested. The approach is based on formation of a double phase-locked (autoresonant) state in the system, as the driving oscillation passes linear resonance with one of the interacting oscillators. When doubly phase locked, the amplitudes of the oscillators increase with time in proportion to the driving frequency deviation from the linear resonance. The stability of this phase-locked state and the effects of dissipation and of the initial three-oscillator frequency mismatch on the autoresonance are analyzed. The associated autoresonance threshold phenomenon in the driving amplitude is also discussed. In contrast to other nonlinear systems, driven, autoresonant three-oscillator excitations are independent of the sign of the driving frequency chirp rate

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

Science.gov (United States)

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.

Science.gov (United States)

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.

Science.gov (United States)

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.

Science.gov (United States)

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.

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.

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

Directory of Open Access Journals (Sweden)

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.

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 ...

Application of Multiple Imputation for Missing Values in Three-Way Three-Mode Multi-Environment Trial Data.

Science.gov (United States)

Tian, Ting; McLachlan, Geoffrey J; Dieters, Mark J; Basford, Kaye E

2015-01-01

It is a common occurrence in plant breeding programs to observe missing values in three-way three-mode multi-environment trial (MET) data. We proposed modifications of models for estimating missing observations for these data arrays, and developed a novel approach in terms of hierarchical clustering. Multiple imputation (MI) was used in four ways, multiple agglomerative hierarchical clustering, normal distribution model, normal regression model, and predictive mean match. The later three models used both Bayesian analysis and non-Bayesian analysis, while the first approach used a clustering procedure with randomly selected attributes and assigned real values from the nearest neighbour to the one with missing observations. Different proportions of data entries in six complete datasets were randomly selected to be missing and the MI methods were compared based on the efficiency and accuracy of estimating those values. The results indicated that the models using Bayesian analysis had slightly higher accuracy of estimation performance than those using non-Bayesian analysis but they were more time-consuming. However, the novel approach of multiple agglomerative hierarchical clustering demonstrated the overall best performances.

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 

Dynamic performance of self-operated three-way valve used in a hybrid air conditioner

International Nuclear Information System (INIS)

Zhang, Penglei; Zhou, Dehai; Shi, Wenxing; Li, Xianting; Wang, Baolong

2014-01-01

A hybrid air conditioner combining a thermosyphon cycle with a vapor compression refrigeration cycle has a large energy saving potential compared with a common air conditioner for spaces requiring year-round cooling. The performance of the switch between the vapor compression mode and the thermosyphon mode largely impacts the safety and reliability of hybrid air conditioners. Therefore, a self-operated three-way valve is proposed. A thermodynamic model and a kinetic model are developed in this paper to evaluate the dynamic performance of the switch valve. The effects of the spring force constant, compressor discharging volume, fit clearance and piston length on the dynamic performance of the switch valve are analyzed. In conclusion, the proposed self-operated three-way valve can realize the switch operation accurately. - Highlights: •A self-operated three-way valve is proposed for hybrid air conditioners. •The thermodynamic model and kinetic model of the self-operated three-way valve are developed. •The validity of models is verified by experiments. •Effects of four main design parameters on the operating performance of the valve are researched

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

Directory of Open Access Journals (Sweden)

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.

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

Science.gov (United States)

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.

Efficient strategy for detecting gene × gene joint action and its application in schizophrenia.

Science.gov (United States)

Won, Sungho; Kwon, Min-Seok; Mattheisen, Manuel; Park, Suyeon; Park, Changsoon; Kihara, Daisuke; Cichon, Sven; Ophoff, Roel; Nöthen, Markus M; Rietschel, Marcella; Baur, Max; Uitterlinden, Andre G; Hofmann, A; Lange, Christoph

2014-01-01

We propose a new approach to detect gene × gene joint action in genome-wide association studies (GWASs) for case-control designs. This approach offers an exhaustive search for all two-way joint action (including, as a special case, single gene action) that is computationally feasible at the genome-wide level and has reasonable statistical power under most genetic models. We found that the presence of any gene × gene joint action may imply differences in three types of genetic components: the minor allele frequencies and the amounts of Hardy-Weinberg disequilibrium may differ between cases and controls, and between the two genetic loci the degree of linkage disequilibrium may differ between cases and controls. Using Fisher's method, it is possible to combine the different sources of genetic information in an overall test for detecting gene × gene joint action. The proposed statistical analysis is efficient and its simplicity makes it applicable to GWASs. In the current study, we applied the proposed approach to a GWAS on schizophrenia and found several potential gene × gene interactions. Our application illustrates the practical advantage of the proposed method. © 2013 WILEY PERIODICALS, INC.

THREE-DIMENSIONAL DOPPLER TOMOGRAPHY OF THE RS VULPECULAE INTERACTING BINARY

International Nuclear Information System (INIS)

Richards, Mercedes T.; Sharova, Olga I.; Agafonov, Michail I.

2010-01-01

Three-dimensional Doppler tomography has been used to study the Hα emission sources in the RS Vulpeculae (RS Vul) interacting binary. The two-dimensional tomogram of this binary suggested that most of the emission arises from the cool mass losing star with additional evidence of a gas stream flowing close to its predicted trajectory. However, the three-dimensional tomogram revealed surprising evidence that the gas stream has an average velocity of -85 km s -1 relative to the central velocity plane at V z = 0 km s -1 , unlike U CrB in which the stream was prominent along this central plane. These unexpected V z motions may result from the interaction between magnetic activity on the cool star and the gravitationally induced Roche lobe overflow from that star. Evidence of a loop prominence on the cool star close to the L1 point has been found in the three-dimensional tomogram of RS Vul; hence, the magnetic field lines may have deflected the gas stream relative to the central plane. This result is consistent with earlier detections of RS Vul as both an X-ray and a radio source, and represents the first detection of a loop prominence in an interacting binary based on tomography. Moreover, recent radio images of β Per, the prototype of the Algols, show that the magnetic field of the mass losing star is asymmetric and extends well beyond the orbital plane of the binary, so it is now plausible that the gas flow between the stars in RS Vul could be deflected in an asymmetric way by the magnetic field.

A comparative study of three different gene expression analysis methods.

Science.gov (United States)

Choe, Jae Young; Han, Hyung Soo; Lee, Seon Duk; Lee, Hanna; Lee, Dong Eun; Ahn, Jae Yun; Ryoo, Hyun Wook; Seo, Kang Suk; Kim, Jong Kun

2017-12-04

TNF-α regulates immune cells and acts as an endogenous pyrogen. Reverse transcription polymerase chain reaction (RT-PCR) is one of the most commonly used methods for gene expression analysis. Among the alternatives to PCR, loop-mediated isothermal amplification (LAMP) shows good potential in terms of specificity and sensitivity. However, few studies have compared RT-PCR and LAMP for human gene expression analysis. Therefore, in the present study, we compared one-step RT-PCR, two-step RT-LAMP and one-step RT-LAMP for human gene expression analysis. We compared three gene expression analysis methods using the human TNF-α gene as a biomarker from peripheral blood cells. Total RNA from the three selected febrile patients were subjected to the three different methods of gene expression analysis. In the comparison of three gene expression analysis methods, the detection limit of both one-step RT-PCR and one-step RT-LAMP were the same, while that of two-step RT-LAMP was inferior. One-step RT-LAMP takes less time, and the experimental result is easy to determine. One-step RT-LAMP is a potentially useful and complementary tool that is fast and reasonably sensitive. In addition, one-step RT-LAMP could be useful in environments lacking specialized equipment or expertise.

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

Science.gov (United States)

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.

Temporal analysis of social networks using three-way DEDICOM.

Energy Technology Data Exchange (ETDEWEB)

Bader, Brett William; Harshman, Richard A. (University of Ontario, London, Ontario, Canada); Kolda, Tamara Gibson (Sandia National Laboratories, Livermore, CA)

2006-06-01

DEDICOM is an algebraic model for analyzing intrinsically asymmetric relationships, such as the balance of trade among nations or the flow of information among organizations or individuals. It provides information on latent components in the data that can be regarded as ''properties'' or ''aspects'' of the objects, and it finds a few patterns that can be combined to describe many relationships among these components. When we apply this technique to adjacency matrices arising from directed graphs, we obtain a smaller graph that gives an idealized description of its patterns. Three-way DEDICOM is a higher-order extension of the model that has certain uniqueness properties. It allows for a third mode of the data, such as time, and permits the analysis of semantic graphs. We present an improved algorithm for computing three-way DEDICOM on sparse data and demonstrate it by applying it to the adjacency tensor of a semantic graph with time-labeled edges. Our application uses the Enron email corpus, from which we construct a semantic graph corresponding to email exchanges among Enron personnel over a series of 44 months. Meaningful patterns are recovered in which the representation of asymmetries adds insight into the social networks at Enron.

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

Directory of Open Access Journals (Sweden)

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.

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...

One, Two, Three: Polycomb Proteins Hit All Dimensions of Gene Regulation

Directory of Open Access Journals (Sweden)

Stefania del Prete

2015-07-01

Full Text Available Polycomb group (PcG proteins contribute to the formation and maintenance of a specific repressive chromatin state that prevents the expression of genes in a particular space and time. Polycomb repressive complexes (PRCs consist of several PcG proteins with specific regulatory or catalytic properties. PRCs are recruited to thousands of target genes, and various recruitment factors, including DNA-binding proteins and non-coding RNAs, are involved in the targeting. PcG proteins contribute to a multitude of biological processes by altering chromatin features at different scales. PcG proteins mediate both biochemical modifications of histone tails and biophysical modifications (e.g., chromatin fiber compaction and three-dimensional (3D chromatin conformation. Here, we review the role of PcG proteins in nuclear architecture, describing their impact on the structure of the chromatin fiber, on chromatin interactions, and on the spatial organization of the genome in nuclei. Although little is known about the role of plant PcG proteins in nuclear organization, much is known in the animal field, and we highlight similarities and differences in the roles of PcG proteins in 3D gene regulation in plants and animals.

Gonadal mosaicism in ARID1B gene causes intellectual disability and dysmorphic features in three siblings.

Science.gov (United States)

Ben-Salem, Salma; Sobreira, Nara; Akawi, Nadia A; Al-Shamsi, Aisha M; John, Anne; Pramathan, Thachillath; Valle, David; Ali, Bassam R; Al-Gazali, Lihadh

2016-01-01

The gene encoding the AT-rich interaction domain-containing protein 1B (ARID1B) has recently been shown to be one of the most frequently mutated genes in patients with intellectual disability (ID). The phenotypic spectrums associated with variants in this gene vary widely ranging for mild to severe non-specific ID to Coffin-Siris syndrome. In this study, we evaluated three children from a consanguineous Emirati family affected with ID and dysmorphic features. Genomic DNA from all affected siblings was analyzed using CGH array and whole-exome sequencing (WES). Based on a recessive mode of inheritance, homozygous or compound heterozygous variants shared among all three affected children could not be identified. However, further analysis revealed a heterozygous variant (c.4318C>T; p.Q1440*) in the three affected children in an autosomal dominant ID causing gene, ARID1B. This variant was absent in peripheral blood samples obtained from both parents and unaffected siblings. Therefore, we propose that the most likely explanation for this situation is that one of the parents is a gonadal mosaic for the variant. To the best of our knowledge, this is the first report of a gonadal mosaicism inheritance of an ARID1B variant leading to familial ID recurrence. © 2015 Wiley Periodicals, Inc.

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

Directory of Open Access Journals (Sweden)

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.

Learning Gene Expression Through Modelling and Argumentation. A Case Study Exploring the Connections Between the Worlds of Knowledge

Science.gov (United States)

Puig, Blanca; Ageitos, Noa; Jiménez-Aleixandre, María Pilar

2017-12-01

There is emerging interest on the interactions between modelling and argumentation in specific contexts, such as genetics learning. It has been suggested that modelling might help students understand and argue on genetics. We propose modelling gene expression as a way to learn molecular genetics and diseases with a genetic component. The study is framed in Tiberghien's (2000) two worlds of knowledge, the world of "theories & models" and the world of "objects & events", adding a third component, the world of representations. We seek to examine how modelling and argumentation interact and connect the three worlds of knowledge while modelling gene expression. It is a case study of 10th graders learning about diseases with a genetic component. The research questions are as follows: (1) What argumentative and modelling operations do students enact in the process of modelling gene expression? Specifically, which operations allow connecting the three worlds of knowledge? (2) What are the interactions between modelling and argumentation in modelling gene expression? To what extent do these interactions help students connect the three worlds of knowledge and modelling gene expression? The argumentative operation of using evidence helps students to relate the three worlds of knowledge, enacted in all the connections. It seems to be a relationship among the number of interactions between modelling and argumentation, the connections between world of knowledge and students' capacity to develop a more sophisticated representation. Despite this is a case study, this approach of analysis reveals potentialities for a deeper understanding of learning genetics though scientific practices.

Strength and deformational characteristics of three-way reinforced concrete containment models subjected to lateral forces

International Nuclear Information System (INIS)

Aoyagi, Y.; Yamada, K.; Takahashi, T.

1981-01-01

With a view to investigating the earthquake resistance characteristics of reinforced concrete containments two cylindrical models with three-way system of bars were made and loaded laterally up to failure combined with or without internal pressures, simulating the conditions in which containments were subjected to earthquake forces at a simultaneous LOCA or at normal operation. The main conclusions obtained withing the limit of the experiments are as follows. (1) Stresses in reinforcements in three-way reinforced concrete plate elements can reasonably be estimated by the equations proposed by Baumann. It is, however, necessary to take into consideration the contributions of concrete between cracks to the deformation in order to accurately estimate the average strains in the plate elements, applying such a formula as CEB as reformed by the authors. (2) The strength capacity of three-way reinforced concrete containments against lateral forces combined with internal pressure is somewhat inferior to that of orthogonally reinforced one if compared on the condition that the volumetric reinforcement ratios are the same for the two cases of reinforcement arrangements. However, three-way reinforcement improves initial shear rigidity as well as ultimate horizontal deformability for lateral forces. (3) The ability for three-way reinforced concrete containment to absorb strain energy in the range of large deformations is superior to that of orthogonally reinforced one. The equivalent viscous damping coefficient for the former is markedly larger than that for the latter, especially at the increased deformational stages. These experimental evidences suggent that three-way system of reinforcement may constitute one of the prospective measures to improve the earthquake resistance of reinforced concrete containments. (orig./HP)

Characterization of three-way automotive catalysts

Energy Technology Data Exchange (ETDEWEB)

Kenik, E.A.; More, K.L. [Oak Ridge National Lab., TN (United States); LaBarge, W. [Delphi Automotive Systems, Flint, MI (United States)] [and others

1997-04-01

The CRADA between Delphi Automotive Systems (Delphi; formerly General Motors - AC Delco, Systems) and Lockheed Martin Energy Research (LMER) on automotive catalysts was completed at the end of FY96, after a ten month, no-cost extension. The CRADA was aimed at improved performance and lifetime of noble metal based three-way-catalysts (TWC), which are the primary catalytic system for automotive emission control systems. While these TWC can meet the currently required emission standards, higher than optimum noble metal loadings are often required to meet lifetime requirements. In addition, more stringent emission standards will be imposed in the near future, demanding improved performance and service life from these catalysts. Understanding the changes of TWC conversion efficiency with ageing is a critical need in improving these catalysts. Initially in a fresh catalyst, the active material is often distributed on a very fine scale, approaching single atoms or small atomic clusters. As such, a wide range of analytical techniques have been employed to provide high spatial resolution characterization of the evolving state of the catalytic material.

Towards a gestural 3D interaction for tangible and three-dimensional GIS visualizations

Science.gov (United States)

Partsinevelos, Panagiotis; Agadakos, Ioannis; Pattakos, Nikolas; Maragakis, Michail

2014-05-01

The last decade has been characterized by a significant increase of spatially dependent applications that require storage, visualization, analysis and exploration of geographic information. GIS analysis of spatiotemporal geographic data is operated by highly trained personnel under an abundance of software and tools, lacking interoperability and friendly user interaction. Towards this end, new forms of querying and interaction are emerging, including gestural interfaces. Three-dimensional GIS representations refer to either tangible surfaces or projected representations. Making a 3D tangible geographic representation touch-sensitive may be a convenient solution, but such an approach raises the cost significantly and complicates the hardware and processing required to combine touch-sensitive material (for pinpointing points) with deformable material (for displaying elevations). In this study, a novel interaction scheme upon a three dimensional visualization of GIS data is proposed. While gesture user interfaces are not yet fully acceptable due to inconsistencies and complexity, a non-tangible GIS system where 3D visualizations are projected, calls for interactions that are based on three-dimensional, non-contact and gestural procedures. Towards these objectives, we use the Microsoft Kinect II system which includes a time of flight camera, allowing for a robust and real time depth map generation, along with the capturing and translation of a variety of predefined gestures from different simultaneous users. By incorporating these features into our system architecture, we attempt to create a natural way for users to operate on GIS data. Apart from the conventional pan and zoom features, the key functions addressed for the 3-D user interface is the ability to pinpoint particular points, lines and areas of interest, such as destinations, waypoints, landmarks, closed areas, etc. The first results shown, concern a projected GIS representation where the user selects points

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.

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

Science.gov (United States)

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.

Science.gov (United States)

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.

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

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

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

Directory of Open Access Journals (Sweden)

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.

Two-way and three-way approaches to ultra high performance liquid chromatography-photodiode array dataset for the quantitative resolution of a two-component mixture containing ciprofloxacin and ornidazole.

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Dinç, Erdal; Ertekin, Zehra Ceren; Büker, Eda

2016-09-01

Two-way and three-way calibration models were applied to ultra high performance liquid chromatography with photodiode array data with coeluted peaks in the same wavelength and time regions for the simultaneous quantitation of ciprofloxacin and ornidazole in tablets. The chromatographic data cube (tensor) was obtained by recording chromatographic spectra of the standard and sample solutions containing ciprofloxacin and ornidazole with sulfadiazine as an internal standard as a function of time and wavelength. Parallel factor analysis and trilinear partial least squares were used as three-way calibrations for the decomposition of the tensor, whereas three-way unfolded partial least squares was applied as a two-way calibration to the unfolded dataset obtained from the data array of ultra high performance liquid chromatography with photodiode array detection. The validity and ability of two-way and three-way analysis methods were tested by analyzing validation samples: synthetic mixture, interday and intraday samples, and standard addition samples. Results obtained from two-way and three-way calibrations were compared to those provided by traditional ultra high performance liquid chromatography. The proposed methods, parallel factor analysis, trilinear partial least squares, unfolded partial least squares, and traditional ultra high performance liquid chromatography were successfully applied to the quantitative estimation of the solid dosage form containing ciprofloxacin and ornidazole. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

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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

Molecular Characterization and Functional Analysis of Three Pathogenesis-Related Cytochrome P450 Genes from Bursaphelenchus xylophilus (Tylenchida: Aphelenchoidoidea

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Xiao-Lu Xu

2015-03-01

Full Text Available Bursaphelenchus xylophilus, the causal agent of pine wilt disease, causes huge economic losses in pine forests. The high expression of cytochrome P450 genes in B. xylophilus during infection in P. thunbergii indicated that these genes had a certain relationship with the pathogenic process of B. xylophilus. Thus, we attempted to identify the molecular characterization and functions of cytochrome P450 genes in B. xylophilus. In this study, full-length cDNA of three cytochrome P450 genes, BxCYP33C9, BxCYP33C4 and BxCYP33D3 were first cloned from B. xylophilus using 3' and 5' RACE PCR amplification. Sequence analysis showed that all of them contained a highly-conserved cytochrome P450 domain. The characteristics of the three putative proteins were analyzed with bioinformatic methods. RNA interference (RNAi was used to assess the functions of BxCYP33C9, BxCYP33C4 and BxCYP33D3. The results revealed that these cytochrome P450 genes were likely to be associated with the vitality, dispersal ability, reproduction, pathogenicity and pesticide metabolism of B. xylophilus. This discovery confirmed the molecular characterization and functions of three cytochrome P450 genes from B. xylophilus and provided fundamental information in elucidating the molecular interaction mechanism between B. xylophilus and its host plant.

Detecting microRNA activity from gene expression data

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Madden, Stephen F

2010-05-18

Abstract Background MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions. Results Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in gene expression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with gene expression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. Conclusions We describe a technique to integrate gene expression data and miRNA target predictions from multiple sources.

Detecting microRNA activity from gene expression data.

LENUS (Irish Health Repository)

Madden, Stephen F

2010-01-01

BACKGROUND: MicroRNAs (miRNAs) are non-coding RNAs that regulate gene expression by binding to the messenger RNA (mRNA) of protein coding genes. They control gene expression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA gene expression microarray data to predict miRNAs associated with particular diseases or conditions. RESULTS: Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in gene expression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with gene expression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. CONCLUSIONS: We describe a technique to integrate gene expression data and miRNA target predictions from multiple sources.

Kinetic considerations of three-way catalysis in automobile exhaust converters

International Nuclear Information System (INIS)

Botas, J.A.; Gutierrez-Ortiz, M.A.; Gonzalez-Marcos, M.P.; Gonzalez-Marcos, J.A.; Gonzalez-Velasco, J.R.

2001-01-01

The activity of three-way catalysts is highly dependent on the reactants present in the automobile exhaust gases (CO, NO x , HC, O 2 , H 2 O, CO 2 , N 2 ) as well as their relative concentration. Thus, the influence of each reactant on the kinetic behavior of the whole mixture makes difficult to establish the accurate kinetics of the system. Activity experiments carried out close to the real operation conditions (GHSV, concentration, etc.) with a Pt/CeO 2 /Al 2 O 3 catalyst supplied data on the CO and HC oxidation and NO reduction reactions in environments formed by different reactant combinations (from binary mixtures to the whole mixture simulating the real conditions at the automobile converter).The obtained results have shown notable variations in the oxidation/reduction mechanisms depending on the presence (or absence) of components in the environment. The presence of water always promoted the three-way activity of the catalyst. The compensation effect applied to the CO, NO and HC conversions confirmed that kinetic expressions obtained with partial mixtures (not very close to the real converter environment) have only limited application for determining the whole kinetic scheme occurring in the automobile converters

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

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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

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

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

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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.

Topology and weights in a protein domain interaction network--a novel way to predict protein interactions.

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Wuchty, Stefan

2006-05-23

While the analysis of unweighted biological webs as diverse as genetic, protein and metabolic networks allowed spectacular insights in the inner workings of a cell, biological networks are not only determined by their static grid of links. In fact, we expect that the heterogeneity in the utilization of connections has a major impact on the organization of cellular activities as well. We consider a web of interactions between protein domains of the Protein Family database (PFAM), which are weighted by a probability score. We apply metrics that combine the static layout and the weights of the underlying interactions. We observe that unweighted measures as well as their weighted counterparts largely share the same trends in the underlying domain interaction network. However, we only find weak signals that weights and the static grid of interactions are connected entities. Therefore assuming that a protein interaction is governed by a single domain interaction, we observe strong and significant correlations of the highest scoring domain interaction and the confidence of protein interactions in the underlying interactions of yeast and fly. Modeling an interaction between proteins if we find a high scoring protein domain interaction we obtain 1, 428 protein interactions among 361 proteins in the human malaria parasite Plasmodium falciparum. Assessing their quality by a logistic regression method we observe that increasing confidence of predicted interactions is accompanied by high scoring domain interactions and elevated levels of functional similarity and evolutionary conservation. Our results indicate that probability scores are randomly distributed, allowing to treat static grid and weights of domain interactions as separate entities. In particular, these finding confirms earlier observations that a protein interaction is a matter of a single interaction event on domain level. As an immediate application, we show a simple way to predict potential protein interactions

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.

Comparison of three-way and four-way calibration for the real-time quantitative analysis of drug hydrolysis in complex dynamic samples by excitation-emission matrix fluorescence

Science.gov (United States)

Yin, Xiao-Li; Gu, Hui-Wen; Liu, Xiao-Lu; Zhang, Shan-Hui; Wu, Hai-Long

2018-03-01

Multiway calibration in combination with spectroscopic technique is an attractive tool for online or real-time monitoring of target analyte(s) in complex samples. However, how to choose a suitable multiway calibration method for the resolution of spectroscopic-kinetic data is a troubling problem in practical application. In this work, for the first time, three-way and four-way fluorescence-kinetic data arrays were generated during the real-time monitoring of the hydrolysis of irinotecan (CPT-11) in human plasma by excitation-emission matrix fluorescence. Alternating normalization-weighted error (ANWE) and alternating penalty trilinear decomposition (APTLD) were used as three-way calibration for the decomposition of the three-way kinetic data array, whereas alternating weighted residual constraint quadrilinear decomposition (AWRCQLD) and alternating penalty quadrilinear decomposition (APQLD) were applied as four-way calibration to the four-way kinetic data array. The quantitative results of the two kinds of calibration models were fully compared from the perspective of predicted real-time concentrations, spiked recoveries of initial concentration, and analytical figures of merit. The comparison study demonstrated that both three-way and four-way calibration models could achieve real-time quantitative analysis of the hydrolysis of CPT-11 in human plasma under certain conditions. However, it was also found that both of them possess some critical advantages and shortcomings during the process of dynamic analysis. The conclusions obtained in this paper can provide some helpful guidance for the reasonable selection of multiway calibration models to achieve the real-time quantitative analysis of target analyte(s) in complex dynamic systems.

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

Science.gov (United States)

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

Principles for the organization of gene-sets.

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Li, Wentian; Freudenberg, Jan; Oswald, Michaela

2015-12-01

A gene-set, an important concept in microarray expression analysis and systems biology, is a collection of genes and/or their products (i.e. proteins) that have some features in common. There are many different ways to construct gene-sets, but a systematic organization of these ways is lacking. Gene-sets are mainly organized ad hoc in current public-domain databases, with group header names often determined by practical reasons (such as the types of technology in obtaining the gene-sets or a balanced number of gene-sets under a header). Here we aim at providing a gene-set organization principle according to the level at which genes are connected: homology, physical map proximity, chemical interaction, biological, and phenotypic-medical levels. We also distinguish two types of connections between genes: actual connection versus sharing of a label. Actual connections denote direct biological interactions, whereas shared label connection denotes shared membership in a group. Some extensions of the framework are also addressed such as overlapping of gene-sets, modules, and the incorporation of other non-protein-coding entities such as microRNAs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Genes2FANs: connecting genes through functional association networks

Science.gov (United States)

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

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.

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

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

Science.gov (United States)

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…

Transcriptomic and phylogenetic analysis of Culex pipiens quinquefasciatus for three detoxification gene families

Directory of Open Access Journals (Sweden)

Yan Liangzhen

2012-11-01

Full Text Available Abstract Background The genomes of three major mosquito vectors of human diseases, Anopheles gambiae, Aedes aegypti, and Culex pipiens quinquefasciatus, have been previously sequenced. C. p. quinquefasciatus has the largest number of predicted protein-coding genes, which partially results from the expansion of three detoxification gene families: cytochrome P450 monooxygenases (P450, glutathione S-transferases (GST, and carboxyl/cholinesterases (CCE. However, unlike An. gambiae and Ae. aegypti, which have large amounts of gene expression data, C. p. quinquefasciatus has limited transcriptomic resources. Knowledge of complete gene expression information is very important for the exploration of the functions of genes involved in specific biological processes. In the present study, the three detoxification gene families of C. p. quinquefasciatus were analyzed for phylogenetic classification and compared with those of three other dipteran insects. Gene expression during various developmental stages and the differential expression responsible for parathion resistance were profiled using the digital gene expression (DGE technique. Results A total of 302 detoxification genes were found in C. p. quinquefasciatus, including 71 CCE, 196 P450, and 35 cytosolic GST genes. Compared with three other dipteran species, gene expansion in Culex mainly occurred in the CCE and P450 families, where the genes of α-esterases, juvenile hormone esterases, and CYP325 of the CYP4 subfamily showed the most pronounced expansion on the genome. For the five DGE libraries, 3.5-3.8 million raw tags were generated and mapped to 13314 reference genes. Among 302 detoxification genes, 225 (75% were detected for expression in at least one DGE library. One fourth of the CCE and P450 genes were detected uniquely in one stage, indicating potential developmentally regulated expression. A total of 1511 genes showed different expression levels between a parathion-resistant and a

ToxCast Data Expands Universe of Chemical-Gene Interactions (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 literature. The ToxCast chemical screening program has produced bioactivity data for nearly 2000 chemicals and over 450 gene targets. Thi...

Moderation of maltreatment effects on childhood borderline personality symptoms by gender and oxytocin receptor and FK506 binding protein 5 genes

Science.gov (United States)

Cicchetti, Dante; Rogosch, Fred A.; Hecht, Kathryn F.; Crick, Nicki R; Hetzel, Susan

2014-01-01

In this investigation, gene-environment-gender interaction effects in predicting child borderline personality disorder symptomatology among maltreated and nonmaltreated low-income children (N = 1,051) were examined. In the context of a summer research camp, adult-peer-, and self-report assessments of borderline precursor indicators were obtained, as well as child self-report on the Borderline Personality Features Scale-Children. Genetic variants of the OXTR genotype and the FKPB5 CATT haplotype were investigated. Children who self-reported high levels of borderline personality symptomatology were differentiated by adults, peers, and additional self-report on indicators of emotional instability, conflictual relationships with peers and adults, preoccupied attachment, and indicators of self-harm and suicidal ideation. Maltreated children also were more likely to evince many of these difficulties relative to nonmaltreated children. In a series of ANCOVAs, controlling for age and ancestrally informative markers, indicated significant maltreatment X gene X gender three-way interactions. Consideration of the maltreatment parameters of subtype, onset, and recency expanded understanding of variation among maltreated children. The three-way interaction effects demonstrated differential patterns among girls and boys. Among girls, the gene-environment interaction was more consistent with a diathesis-stress model, whereas among boys a differential-sensitivity interaction effect was indicated. Moreover, the genetic variants associated with greater risk for higher borderline symptomatology, dependent on maltreatment experiences, were opposite in girls compared to boys. The findings have important implications for understanding variability in early predictors of borderline personality pathology. PMID:25047302

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.

Directory of Open Access Journals (Sweden)

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.

Three-Way Channels With Multiple Unicast Sessions: Capacity Approximation via Network Transformation

KAUST Repository

Chaaban, Anas

2016-09-28

A network of three nodes mutually communicating with each other is studied. This multi-way network is a suitable model for three-user device-to-device communications. The main goal of this paper is to characterize the capacity region of the underlying Gaussian three-way channel (3WC) within a constant gap. To this end, a capacity outer bound is derived using cut-set bounds and genie-aided bounds. For achievability, the 3WC is first transformed into an equivalent star channel. This latter is then decomposed into a set of “successive” sub-channels, leading to a sub-channel allocation problem. Using backward decoding, interference neutralization, and known results on the capacity of the star-channel relying of physical-layer network coding, an achievable rate region for the 3WC is obtained. It is then shown that the achievable rate region is within a constant gap of the developed outer bound, leading to the desired capacity approximation. Interestingly, in contrast to the Gaussian two-way channel (TWC), adaptation is necessary in the 3WC. Furthermore, message splitting is another ingredient of the developed scheme for the 3WC, which is not required in the TWC. The two setups are, however, similar in terms of their sum-capacity pre-log, which is equal to 2. Finally, some interesting networks and their approximate capacities are recovered as special cases of the 3WC, such as the cooperative broadcast channel and multiple access channel.

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.

Foucault's Three Ways of Decentering the State

DEFF Research Database (Denmark)

Villadsen, Kaspar

no interior” (Foucault, 2008: 90). In the stream of scholarship inspired by Foucault it has become an interpretative orthodoxy that the state should be viewed as decentered, without a unifying center, resting upon networks of mobile power relations. In this way, political decision making is delocalized......It is well known that Michel Foucault challenged the centrality of the state, advancing a view of the state as ‘decentered’. He said: “The state has no heart, as we well know, but not just in the sense that it has no feelings, either good or bad, but it has no heart in the sense that it has......, and sovereignty is dissolved in dispersed and mundane practices. Here, I wish to examine the three routes by which Foucault during the 1970s reached his renowned ‘decentered’ approach to the state. These routes never arrived at any ultimate conception of the state, since they were experimental explorations...

Comparison of three-way and four-way calibration for the real-time quantitative analysis of drug hydrolysis in complex dynamic samples by excitation-emission matrix fluorescence.

Science.gov (United States)

Yin, Xiao-Li; Gu, Hui-Wen; Liu, Xiao-Lu; Zhang, Shan-Hui; Wu, Hai-Long

2018-03-05

Multiway calibration in combination with spectroscopic technique is an attractive tool for online or real-time monitoring of target analyte(s) in complex samples. However, how to choose a suitable multiway calibration method for the resolution of spectroscopic-kinetic data is a troubling problem in practical application. In this work, for the first time, three-way and four-way fluorescence-kinetic data arrays were generated during the real-time monitoring of the hydrolysis of irinotecan (CPT-11) in human plasma by excitation-emission matrix fluorescence. Alternating normalization-weighted error (ANWE) and alternating penalty trilinear decomposition (APTLD) were used as three-way calibration for the decomposition of the three-way kinetic data array, whereas alternating weighted residual constraint quadrilinear decomposition (AWRCQLD) and alternating penalty quadrilinear decomposition (APQLD) were applied as four-way calibration to the four-way kinetic data array. The quantitative results of the two kinds of calibration models were fully compared from the perspective of predicted real-time concentrations, spiked recoveries of initial concentration, and analytical figures of merit. The comparison study demonstrated that both three-way and four-way calibration models could achieve real-time quantitative analysis of the hydrolysis of CPT-11 in human plasma under certain conditions. However, it was also found that both of them possess some critical advantages and shortcomings during the process of dynamic analysis. The conclusions obtained in this paper can provide some helpful guidance for the reasonable selection of multiway calibration models to achieve the real-time quantitative analysis of target analyte(s) in complex dynamic systems. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Directory of Open Access Journals (Sweden)

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.

Genome-wide transcriptome study in wheat identified candidate genes related to processing quality, majority of them showing interaction (quality x development) and having temporal and spatial distributions

Science.gov (United States)

2014-01-01

Background The cultivated bread wheat (Triticum aestivum L.) possesses unique flour quality, which can be processed into many end-use food products such as bread, pasta, chapatti (unleavened flat bread), biscuit, etc. The present wheat varieties require improvement in processing quality to meet the increasing demand of better quality food products. However, processing quality is very complex and controlled by many genes, which have not been completely explored. To identify the candidate genes whose expressions changed due to variation in processing quality and interaction (quality x development), genome-wide transcriptome studies were performed in two sets of diverse Indian wheat varieties differing for chapatti quality. It is also important to understand the temporal and spatial distributions of their expressions for designing tissue and growth specific functional genomics experiments. Results Gene-specific two-way ANOVA analysis of expression of about 55 K transcripts in two diverse sets of Indian wheat varieties for chapatti quality at three seed developmental stages identified 236 differentially expressed probe sets (10-fold). Out of 236, 110 probe sets were identified for chapatti quality. Many processing quality related key genes such as glutenin and gliadins, puroindolines, grain softness protein, alpha and beta amylases, proteases, were identified, and many other candidate genes related to cellular and molecular functions were also identified. The ANOVA analysis revealed that the expression of 56 of 110 probe sets was involved in interaction (quality x development). Majority of the probe sets showed differential expression at early stage of seed development i.e. temporal expression. Meta-analysis revealed that the majority of the genes expressed in one or a few growth stages indicating spatial distribution of their expressions. The differential expressions of a few candidate genes such as pre-alpha/beta-gliadin and gamma gliadin were validated by RT

Genome-wide transcriptome study in wheat identified candidate genes related to processing quality, majority of them showing interaction (quality x development) and having temporal and spatial distributions.

Science.gov (United States)

Singh, Anuradha; Mantri, Shrikant; Sharma, Monica; Chaudhury, Ashok; Tuli, Rakesh; Roy, Joy

2014-01-16

The cultivated bread wheat (Triticum aestivum L.) possesses unique flour quality, which can be processed into many end-use food products such as bread, pasta, chapatti (unleavened flat bread), biscuit, etc. The present wheat varieties require improvement in processing quality to meet the increasing demand of better quality food products. However, processing quality is very complex and controlled by many genes, which have not been completely explored. To identify the candidate genes whose expressions changed due to variation in processing quality and interaction (quality x development), genome-wide transcriptome studies were performed in two sets of diverse Indian wheat varieties differing for chapatti quality. It is also important to understand the temporal and spatial distributions of their expressions for designing tissue and growth specific functional genomics experiments. Gene-specific two-way ANOVA analysis of expression of about 55 K transcripts in two diverse sets of Indian wheat varieties for chapatti quality at three seed developmental stages identified 236 differentially expressed probe sets (10-fold). Out of 236, 110 probe sets were identified for chapatti quality. Many processing quality related key genes such as glutenin and gliadins, puroindolines, grain softness protein, alpha and beta amylases, proteases, were identified, and many other candidate genes related to cellular and molecular functions were also identified. The ANOVA analysis revealed that the expression of 56 of 110 probe sets was involved in interaction (quality x development). Majority of the probe sets showed differential expression at early stage of seed development i.e. temporal expression. Meta-analysis revealed that the majority of the genes expressed in one or a few growth stages indicating spatial distribution of their expressions. The differential expressions of a few candidate genes such as pre-alpha/beta-gliadin and gamma gliadin were validated by RT-PCR. Therefore, this study

Three-way interactions between Fusarium species, their plant hosts and biocontrol organisms

DEFF Research Database (Denmark)

Kosawang, Chatchai

of ABC transporters in mycoparasitic fungi focused on C. rosea and Trichoderma spp. We showed that expression of zhd101 depended on concentrations of ZEA and that the gene was not induced by other agents, suggesting specificity of the enzyme towards ZEA and its derivates. To investigate effects of ZEA...... identified expansion of ABC transporter families in C. rosea as in Trichoderma virens and T. harzianum, but not in T. reesei and T. atroviridae. The expansion was profoundly observed in the subfamily G of C. rosea ABC transporters and the subfamily C of Trichoderma spp, repectively. The subfamilies C and G...

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.

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.

Uniqueness conditions for constrained three-way factor decompositions with linearly dependent loadings

NARCIS (Netherlands)

Stegeman, Alwin; De Almeida, Andre L. F.

2009-01-01

In this paper, we derive uniqueness conditions for a constrained version of the parallel factor (Parafac) decomposition, also known as canonical decomposition (Candecomp). Candecomp/Parafac (CP) decomposes a three-way array into a prespecified number of outer product arrays. The constraint is that

DTFP-Growth: Dynamic Threshold-Based FP-Growth Rule Mining Algorithm Through Integrating Gene Expression, Methylation, and Protein-Protein Interaction Profiles.

Science.gov (United States)

Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan; Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan; Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan

2018-04-01

Association rule mining is an important technique for identifying interesting relationships between gene pairs in a biological data set. Earlier methods basically work for a single biological data set, and, in maximum cases, a single minimum support cutoff can be applied globally, i.e., across all genesets/itemsets. To overcome this limitation, in this paper, we propose dynamic threshold-based FP-growth rule mining algorithm that integrates gene expression, methylation and protein-protein interaction profiles based on weighted shortest distance to find the novel associations among different pairs of genes in multi-view data sets. For this purpose, we introduce three new thresholds, namely, Distance-based Variable/Dynamic Supports (DVS), Distance-based Variable Confidences (DVC), and Distance-based Variable Lifts (DVL) for each rule by integrating co-expression, co-methylation, and protein-protein interactions existed in the multi-omics data set. We develop the proposed algorithm utilizing these three novel multiple threshold measures. In the proposed algorithm, the values of , , and are computed for each rule separately, and subsequently it is verified whether the support, confidence, and lift of each evolved rule are greater than or equal to the corresponding individual , , and values, respectively, or not. If all these three conditions for a rule are found to be true, the rule is treated as a resultant rule. One of the major advantages of the proposed method compared with other related state-of-the-art methods is that it considers both the quantitative and interactive significance among all pairwise genes belonging to each rule. Moreover, the proposed method generates fewer rules, takes less running time, and provides greater biological significance for the resultant top-ranking rules compared to previous methods.

Topology and weights in a protein domain interaction network – a novel way to predict protein interactions

Directory of Open Access Journals (Sweden)

Wuchty Stefan

2006-05-01

show a simple way to predict potential protein interactions by utilizing expectation scores of single domain interactions.

Cloning and chromosomal localization of the three human syntrophin genes

Energy Technology Data Exchange (ETDEWEB)

Feener, C.A.; Anderson, M.D.S.; Selig, S. [Children`s Hospital, Boston, MA (United States)] [and others

1994-09-01

Dystrophin, the protein product the Duchenne muscular dystrophy locus, is normally found to be associated with a complex of proteins. Among these dystrophin-associated proteins are the syntrophins, a group of 59 kDa membrane-associated proteins. When the syntrophins are purified based upon their association with dystrophin, they have been shown previously to form two distinct groups, the acidic ({alpha}) and basic ({beta}) forms. Based on peptide and rodent cDNA sequences, three separate syntrophin genes have been cloned and characterized from human tissues. The predicted amino acid sequences from these cDNA reveal that these proteins are related but are distinct with respect to charge, as predicted from their biochemistry. The family consists of one acidic ({alpha}-syntrophin, analogous to mouse syntrophin-1) and two basic ({beta}{sub 1}-syntrophin; and {beta}{sub 2}-syntrophin, analogous to mouse syntrophin-2) genes. Each of the three genes are widely expressed in a variety of human tissues, but the relative abundance of the three are unique with respect to each other. {alpha}-syntrophin is expressed primarily in skeletal muscle and heart as a single transcript. {beta}{sub 1}-syntrophin is expressed widely in up to five distinct transcript sizes, and is most abundant in brain. The human chromosomal locations of the three syntrophins are currently being mapped. {beta}{sub 1}-syntrophin maps to chromosome 8q23-24 and {beta}{sub 2}-syntrophin to chromosome 16. The {alpha}-syntrophin gene will be mapped accordingly. Although all three genes are candidates for neuromuscular diseases, the predominant expression of {alpha}-syntrophin in skeletal muscle and heart makes it a strong candidate to be involved in a neuromuscular disease.

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

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 ...

System and method for determining an ammonia generation rate in a three-way catalyst

Science.gov (United States)

Sun, Min; Perry, Kevin L; Kim, Chang H

2014-12-30

A system according to the principles of the present disclosure includes a rate determination module, a storage level determination module, and an air/fuel ratio control module. The rate determination module determines an ammonia generation rate in a three-way catalyst based on a reaction efficiency and a reactant level. The storage level determination module determines an ammonia storage level in a selective catalytic reduction (SCR) catalyst positioned downstream from the three-way catalyst based on the ammonia generation rate. The air/fuel ratio control module controls an air/fuel ratio of an engine based on the ammonia storage level.

Three ways of assembling a house

DEFF Research Database (Denmark)

Beim, Anne; Nielsen, Jesper; Vibæk, Kasper Sánchez

The Scandinavian construction industry is characterised by high quality craftsmanship, but also by an array of highly industrialised, but not always coordinated building systems. This book aims to shed some light on these systems and their underlying concepts. By looking at both the systems...... themselves, the way they are produced and the business models behind them, the systems and concepts are assessed in their broader organisational context and not just as physical manifestations of their design intentions. Acknowledging that there is more than one possible way of enhancing the application...

Handling large numbers of observation units in three-way methods for the analysis of qualitative and quantitative two-way data

NARCIS (Netherlands)

Kiers, Henk A.L.; Marchetti, G.M.

1994-01-01

Recently, a number of methods have been proposed for the exploratory analysis of mixtures of qualitative and quantitative variables. In these methods for each variable an object by object similarity matrix is constructed, and these are consequently analyzed by means of three-way methods like

Three-Way Channels With Multiple Unicast Sessions: Capacity Approximation via Network Transformation

KAUST Repository

Chaaban, Anas; Maier, Henning; Sezgin, Aydin; Mathar, Rudolf

2016-01-01

of the underlying Gaussian three-way channel (3WC) within a constant gap. To this end, a capacity outer bound is derived using cut-set bounds and genie-aided bounds. For achievability, the 3WC is first transformed into an equivalent star channel. This latter

Bioinformatics approach of three partial polyprenol reductase genes in Kandelia obovata

Science.gov (United States)

Basyuni, M.; Wati, R.; Sagami, H.; Oku, H.; Baba, S.

2018-03-01

This present study describesthe bioinformatics approach to analyze three partial polyprenol reductase genes from mangrove plant, Kandeliaobovataas well aspredictedphysical and chemical properties, potential peptide, subcellular localization, and phylogenetic. The diversity was noted in the physical and chemical properties of three partial polyprenol reductase genes. The values of chloroplast were relatively high, showed that chloroplast transit peptide occurred in mangrove polyprenol reductase. The target peptide value of mitochondria varied from 0.088 to 0.198 indicated it was possible to be present. These results suggested the importance of understanding the diversity of physicochemical properties of the different amino acids in polyprenol reductase. The subcellular localization of two partial genes located in the plasma membrane. To confirm the homology among the polyprenol reductase in the database, a dendrogram was drawn. The phylogenetic tree depicts that there are three clusters, the partial genes of K. obovata joined the largest one: C23157 was close to Ricinus communis polyprenol reductase. Whereas, C23901 and C24171 were grouped with Ipomoea nil polyprenol reductase, suggested that these polyprenol reductase genes form distinct separation into tropical habitat plants.

Three Ways to Link Merge with Hierarchical Concept-Combination

Directory of Open Access Journals (Sweden)

Chris Thornton

2016-11-01

Full Text Available In the Minimalist Program, language competence is seen to stem from a fundamental ability to construct hierarchical structure, an operation dubbed ‘Merge’. This raises the problem of how to view hierarchical concept-combination. This is a conceptual operation which also builds hierarchical structure. We can conceive of a garden that consists of a lawn and a flower-bed, for example, or a salad consisting of lettuce, fennel and rocket, or a crew consisting of a pilot and engineer. In such cases, concepts are put together in a way that makes one the accommodating element with respect to the others taken in combination. The accommodating element becomes the root of a hierarchical unit. Since this unit is itself a concept, the operation is inherently recursive. Does this mean the mind has two independent systems of hierarchical construction? Or is some form of integration more likely? Following a detailed examination of the operations involved, this paper shows there are three main ways in which Merge might be linked to hierarchical concept-combination. Also examined are the architectural implications that arise in each case.

Interaction range perturbation theory for three-particle problem

International Nuclear Information System (INIS)

Simenog, I.V.; Shapoval, D.V.

1988-01-01

The limit of zero interaction range is correctly defined for a system of three spinless particles and three particles in a doublet state. The scattering amplitude is expanded with respect to the interaction range r, and the corrections of order r ln r, r, and r 2 ln2 r are found. An explicit model-independent asymptotic expression is obtained for the scattering amplitude in terms of the scattering length, and its accuracy is established

Genes2WordCloud: a quick way to identify biological themes from gene lists and free text.

Science.gov (United States)

Baroukh, Caroline; Jenkins, Sherry L; Dannenfelser, Ruth; Ma'ayan, Avi

2011-10-13

Word-clouds recently emerged on the web as a solution for quickly summarizing text by maximizing the display of most relevant terms about a specific topic in the minimum amount of space. As biologists are faced with the daunting amount of new research data commonly presented in textual formats, word-clouds can be used to summarize and represent biological and/or biomedical content for various applications. Genes2WordCloud is a web application that enables users to quickly identify biological themes from gene lists and research relevant text by constructing and displaying word-clouds. It provides users with several different options and ideas for the sources that can be used to generate a word-cloud. Different options for rendering and coloring the word-clouds give users the flexibility to quickly generate customized word-clouds of their choice. Genes2WordCloud is a word-cloud generator and a word-cloud viewer that is based on WordCram implemented using Java, Processing, AJAX, mySQL, and PHP. Text is fetched from several sources and then processed to extract the most relevant terms with their computed weights based on word frequencies. Genes2WordCloud is freely available for use online; it is open source software and is available for installation on any web-site along with supporting documentation at http://www.maayanlab.net/G2W. Genes2WordCloud provides a useful way to summarize and visualize large amounts of textual biological data or to find biological themes from several different sources. The open source availability of the software enables users to implement customized word-clouds on their own web-sites and desktop applications.

Finding the limit of diverging components in three-way Candecomp/Parafac : A demonstration of its practical merits

NARCIS (Netherlands)

Stegeman, Alwin

Three-way Candecomp/Parafac (CP) is a three-way generalization of principal component analysis (PCA) for matrices. Contrary to PCA, a CP decomposition is rotationally unique under mild conditions. However, a CP analysis may be hampered by the non-existence of a best-fitting CP decomposition with R≤2

Identification of microRNA genes in three opisthorchiids.

Directory of Open Access Journals (Sweden)

Vladimir Y Ovchinnikov

2015-04-01

Full Text Available Opisthorchis felineus, O. viverrini, and Clonorchis sinensis (family Opisthorchiidae are parasitic flatworms that pose a serious threat to humans in some countries and cause opisthorchiasis/clonorchiasis. Chronic disease may lead to a risk of carcinogenesis in the biliary ducts. MicroRNAs (miRNAs are small noncoding RNAs that control gene expression at post-transcriptional level and are implicated in the regulation of various cellular processes during the parasite- host interplay. However, to date, the miRNAs of opisthorchiid flukes, in particular those essential for maintaining their complex biology and parasitic mode of existence, have not been satisfactorily described.Using a SOLiD deep sequencing-bioinformatic approach, we identified 43 novel and 18 conserved miRNAs for O. felineus (miracidia, metacercariae and adult worms, 20 novel and 16 conserved miRNAs for O. viverrini (adult worms, and 33 novel and 18 conserved miRNAs for C. sinensis (adult worms. The analysis of the data revealed differences in the expression level of conserved miRNAs among the three species and among three the developmental stages of O. felineus. Analysis of miRNA genes revealed two gene clusters, one cluster-like region and one intronic miRNA in the genome. The presence and structure of the two gene clusters were validated using a PCR-based approach in the three flukes.This study represents a comprehensive description of miRNAs in three members of the family Opistorchiidae, significantly expands our knowledge of miRNAs in multicellular parasites and provides a basis for understanding the structural and functional evolution of miRNAs in these metazoan parasites. Results of this study also provides novel resources for deeper understanding the complex parasite biology, for further research on the pathogenesis and molecular events of disease induced by the liver flukes. The present data may also facilitate the development of novel approaches for the prevention and

DNMT1-interacting RNAs block gene specific DNA methylation

Science.gov (United States)

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

Science.gov (United States)

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

Three-dimensional reacting shock–bubble interaction

NARCIS (Netherlands)

Diegelmann, Felix; Hickel, S.; Adams, Nikolaus A.

2017-01-01

We investigate a reacting shock–bubble interaction through three-dimensional numerical simulations with detailed chemistry. The convex shape of the bubble focuses the shock and generates regions of high pressure and temperature, which are sufficient to ignite the diluted stoichiometric

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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...

Climate change and species interactions: ways forward.

Science.gov (United States)

Angert, Amy L; LaDeau, Shannon L; Ostfeld, Richard S

2013-09-01

With ongoing and rapid climate change, ecologists are being challenged to predict how individual species will change in abundance and distribution, how biotic communities will change in structure and function, and the consequences of these climate-induced changes for ecosystem functioning. It is now well documented that indirect effects of climate change on species abundances and distributions, via climatic effects on interspecific interactions, can outweigh and even reverse the direct effects of climate. However, a clear framework for incorporating species interactions into projections of biological change remains elusive. To move forward, we suggest three priorities for the research community: (1) utilize tractable study systems as case studies to illustrate possible outcomes, test processes highlighted by theory, and feed back into modeling efforts; (2) develop a robust analytical framework that allows for better cross-scale linkages; and (3) determine over what time scales and for which systems prediction of biological responses to climate change is a useful and feasible goal. We end with a list of research questions that can guide future research to help understand, and hopefully mitigate, the negative effects of climate change on biota and the ecosystem services they provide. © 2013 New York Academy of Sciences.

Interactive Ways of Becoming a Specialist Fine Art of the Ukrainian Danube Region

Directory of Open Access Journals (Sweden)

Ivan Pastyr

2016-08-01

Full Text Available In modern conditions the method of education is especially effective if it is built on the intensification of mental activity and is aimed at developing a creative personality. The study presents a system of interactive ways of becoming a specialist in Izmail State Liberal Arts University.

The System Dynamics Model in Electronic Products Closed-Loop Supply Chain Distribution Network with Three-Way Recovery and the Old-for-New Policy

Directory of Open Access Journals (Sweden)

Xiao-qing Zhang

2016-01-01

Full Text Available With the technological developments and rapid changes in demand pattern, diverse varieties of electronic products are entering into the market with reduced lifecycle which leads to the environmental problems. The awareness of electronic products take-back and recovery has been increasing in electronic products supply chains. In this paper, we build a system dynamics model for electronic products closed-loop supply chain distribution network with the old-for-new policy and three electronic products recovery ways, namely, electronic products remanufacturing, electronic component reuse and remanufacturing, and electronic raw material recovery. In the simulation study, we investigate the significance of various factors including the old-for-new policy, collection and remanufacturing, their interactions and the type of their impact on bullwhip, and profitability through sensitivity analysis. Our results instruct that the old-for-new policy and three electronic products recovery ways can reduce the bullwhip effect in the retailers and the distributors and increases the profitability in the closed-loop supply chain distribution network.

Three-wave interaction in two-component quadratic nonlinear lattices

DEFF Research Database (Denmark)

Konotop, V. V.; Cunha, M. D.; Christiansen, Peter Leth

1999-01-01

We investigate a two-component lattice with a quadratic nonlinearity and find with the multiple scale technique that integrable three-wave interaction takes place between plane wave solutions when these fulfill resonance conditions. We demonstrate that. energy conversion and pulse propagation known...... from three-wave interaction is reproduced in the lattice and that exact phase matching of parametric processes can be obtained in non-phase-matched lattices by tilting the interacting plane waves with respect to each other. [S1063-651X(99)15110-9]....

Functional modules by relating protein interaction networks and gene expression.

Science.gov (United States)

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.

Coherent Destruction of Tunneling of Bosons with Effective Three-Body Interactions

International Nuclear Information System (INIS)

Niu Zhen-Xia; Yu Zi-Fa; Xue Ju-Kui

2015-01-01

The tunneling dynamics of dilute boson gases with three-body interactions in a periodically driven double wells are investigated both theoretically and numerically. In our findings, when the system is with only repulsive two-body interactions or only three-body interactions, the tunneling will be suppressed; while in the case of the coupling between two- and three-body interactions, the tunneling can be either suppressed or enhanced. Particularly, when attractive three-body interactions are twice large as repulsive two-body interactions, CDT occurs at isolated points of driving force, which is similar to the linear case. Considering different interaction, the system can experience different transformation from coherent tunneling to coherent destruction of tunneling (CDT). The quasi-energy of the system as the function of the periodically driving force shows a triangular structure, which provides a deep insight into the tunneling dynamics of the system. (paper)

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

Science.gov (United States)

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

Genes2WordCloud: a quick way to identify biological themes from gene lists and free text

Directory of Open Access Journals (Sweden)

Ma'ayan Avi

2011-10-01

Full Text Available Abstract Background Word-clouds recently emerged on the web as a solution for quickly summarizing text by maximizing the display of most relevant terms about a specific topic in the minimum amount of space. As biologists are faced with the daunting amount of new research data commonly presented in textual formats, word-clouds can be used to summarize and represent biological and/or biomedical content for various applications. Results Genes2WordCloud is a web application that enables users to quickly identify biological themes from gene lists and research relevant text by constructing and displaying word-clouds. It provides users with several different options and ideas for the sources that can be used to generate a word-cloud. Different options for rendering and coloring the word-clouds give users the flexibility to quickly generate customized word-clouds of their choice. Methods Genes2WordCloud is a word-cloud generator and a word-cloud viewer that is based on WordCram implemented using Java, Processing, AJAX, mySQL, and PHP. Text is fetched from several sources and then processed to extract the most relevant terms with their computed weights based on word frequencies. Genes2WordCloud is freely available for use online; it is open source software and is available for installation on any web-site along with supporting documentation at http://www.maayanlab.net/G2W. Conclusions Genes2WordCloud provides a useful way to summarize and visualize large amounts of textual biological data or to find biological themes from several different sources. The open source availability of the software enables users to implement customized word-clouds on their own web-sites and desktop applications.

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

Science.gov (United States)

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.

Directory of Open Access Journals (Sweden)

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

Science.gov (United States)

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

Directory of Open Access Journals (Sweden)

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

Global gene expression analysis of the zoonotic parasite Trichinella spiralis revealed novel genes in host parasite interaction.

Directory of Open Access Journals (Sweden)

Xiaolei Liu

Full Text Available BACKGROUND: Trichinellosis is a typical food-borne zoonotic disease which is epidemic worldwide and the nematode Trichinella spiralis is the main pathogen. The life cycle of T. spiralis contains three developmental stages, i.e. adult worms, new borne larva (new borne L1 larva and muscular larva (infective L1 larva. Stage-specific gene expression in the parasites has been investigated with various immunological and cDNA cloning approaches, whereas the genome-wide transcriptome and expression features of the parasite have been largely unknown. The availability of the genome sequence information of T. spiralis has made it possible to deeply dissect parasite biology in association with global gene expression and pathogenesis. METHODOLOGY AND PRINCIPAL FINDINGS: In this study, we analyzed the global gene expression patterns in the three developmental stages of T. spiralis using digital gene expression (DGE analysis. Almost 15 million sequence tags were generated with the Illumina RNA-seq technology, producing expression data for more than 9,000 genes, covering 65% of the genome. The transcriptome analysis revealed thousands of differentially expressed genes within the genome, and importantly, a panel of genes encoding functional proteins associated with parasite invasion and immuno-modulation were identified. More than 45% of the genes were found to be transcribed from both strands, indicating the importance of RNA-mediated gene regulation in the development of the parasite. Further, based on gene ontological analysis, over 3000 genes were functionally categorized and biological pathways in the three life cycle stage were elucidated. CONCLUSIONS AND SIGNIFICANCE: The global transcriptome of T. spiralis in three developmental stages has been profiled, and most gene activity in the genome was found to be developmentally regulated. Many metabolic and biological pathways have been revealed. The findings of the differential expression of several protein

Rotation gate for a three-level superconducting quantum interference device qubit with resonant interaction

International Nuclear Information System (INIS)

Yang, C.-P.; Han Siyuan

2006-01-01

We show a way to realize an arbitrary rotation gate in a three-level superconducting quantum interference device (SQUID) qubit using resonant interaction. In this approach, the two logical states of the qubit are represented by the two lowest levels of the SQUID and a higher-energy intermediate level is utilized for the gate manipulation. By considering spontaneous decay from the intermediate level during the gate operation, we present a formula for calculating average fidelity over all possible initial states. Finally, based on realistic system parameters, we show that an arbitrary rotation gate can be achieved with a high fidelity in a SQUID

Candidate genes and their interactions with other genetic/environmental risk factors in the etiology of schizophrenia.

Science.gov (United States)

Prasad, K M; Talkowski, M E; Chowdari, K V; McClain, L; Yolken, R H; Nimgaonkar, V L

2010-09-30

Identification of causative factors for common, chronic disorders is a major focus of current human health science research. These disorders are likely to be caused by multiple etiological agents. Available evidence also suggests that interactions between the risk factors may explain some of their pathogenic effects. While progress in genomics and allied biological research has brought forth powerful analytic techniques, the predicted complexity poses daunting analytic challenges. The search for pathogenesis of schizophrenia shares most of these challenges. We have reviewed the analytic and logistic problems associated with the search for pathogenesis. Evidence for pathogenic interactions is presented for selected diseases and for schizophrenia. We end by suggesting 'recursive analyses' as a potential design to address these challenges. This scheme involves initial focused searches for interactions motivated by available evidence, typically involving identified individual risk factors, such as candidate gene variants. Putative interactions are tested rigorously for replication and for biological plausibility. Support for the interactions from statistical and functional analyses motivates a progressively larger array of interactants that are evaluated recursively. The risk explained by the interactions is assessed concurrently and further elaborate searches may be guided by the results of such analyses. By way of example, we summarize our ongoing analyses of dopaminergic polymorphisms, as well as infectious etiological factors in schizophrenia genesis. Copyright © 2009 Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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.

Directory of Open Access Journals (Sweden)

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...

MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers.

Science.gov (United States)

Allot, Alexis; Chennen, Kirsley; Nevers, Yannis; Poidevin, Laetitia; Kress, Arnaud; Ripp, Raymond; Thompson, Julie Dawn; Poch, Olivier; Lecompte, Odile

2017-06-16

The constant and massive increase of biological data offers unprecedented opportunities to decipher the function and evolution of genes and their roles in human diseases. However, the multiplicity of sources and flow of data mean that efficient access to useful information and knowledge production has become a major challenge. This challenge can be addressed by taking inspiration from Web 2.0 and particularly social networks, which are at the forefront of big data exploration and human-data interaction. MyGeneFriends is a Web platform inspired by social networks, devoted to genetic disease analysis, and organized around three types of proactive agents: genes, humans, and genetic diseases. The aim of this study was to improve exploration and exploitation of biological, postgenomic era big data. MyGeneFriends leverages conventions popularized by top social networks (Facebook, LinkedIn, etc), such as networks of friends, profile pages, friendship recommendations, affinity scores, news feeds, content recommendation, and data visualization. MyGeneFriends provides simple and intuitive interactions with data through evaluation and visualization of connections (friendships) between genes, humans, and diseases. The platform suggests new friends and publications and allows agents to follow the activity of their friends. It dynamically personalizes information depending on the user's specific interests and provides an efficient way to share information with collaborators. Furthermore, the user's behavior itself generates new information that constitutes an added value integrated in the network, which can be used to discover new connections between biological agents. We have developed MyGeneFriends, a Web platform leveraging conventions from popular social networks to redefine the relationship between humans and biological big data and improve human processing of biomedical data. MyGeneFriends is available at lbgi.fr/mygenefriends. ©Alexis Allot, Kirsley Chennen, Yannis

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

Science.gov (United States)

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.

Three-way flexible cantilever probes for static contact

International Nuclear Information System (INIS)

Wang, Fei; Petersen, Dirch H; Hansen, Christian; Mortensen, Dennis; Friis, Lars; Hansen, Ole; Jensen, Helle V

2011-01-01

In micro four-point probe measurements, three-way flexible L-shaped cantilever probes show significant advantages over conventional straight cantilever probes. The L-shaped cantilever allows static contact to the sample surface which reduces the frictional wear of the cantilever tips. We analyze the geometrical design space that must be fulfilled for the cantilevers to obtain static contact with the test sample. The design space relates the spring constant tensor of the cantilevers to the minimal value of the static tip-to-sample friction coefficient. Using an approximate model, we provide the analytical calculation of the compliance matrix of the L-shaped cantilever. Compared to results derived from finite element model simulations, the theoretical model provides a good qualitative analysis while deviations for the absolute values are seen. From a statistical analysis, the deviation is small for cantilevers with low effective spring constants, while the deviation is significant for large spring constants where the quasi one-dimensional approximation is no longer valid

Culture Three Ways: Culture and Subcultures Within Countries.

Science.gov (United States)

Oyserman, Daphna

2017-01-03

Culture can be thought of as a set of everyday practices and a core theme-individualism, collectivism, or honor-as well as the capacity to understand each of these themes. In one's own culture, it is easy to fail to see that a cultural lens exists and instead to think that there is no lens at all, only reality. Hence, studying culture requires stepping out of it. There are two main methods to do so: The first involves using between-group comparisons to highlight differences and the second involves using experimental methods to test the consequences of disruption to implicit cultural frames. These methods highlight three ways that culture organizes experience: (a) It shields reflexive processing by making everyday life feel predictable, (b) it scaffolds which cognitive procedure (connect, separate, or order) will be the default in ambiguous situations, and (c) it facilitates situation-specific accessibility of alternate cognitive procedures. Modern societal social-demographic trends reduce predictability and increase collectivism and honor-based go-to cognitive procedures.

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,

Genetic and epigenetic alteration among three homoeologous genes of a class E MADS box gene in hexaploid wheat.

Science.gov (United States)

Shitsukawa, Naoki; Tahira, Chikako; Kassai, Ken-Ichiro; Hirabayashi, Chizuru; Shimizu, Tomoaki; Takumi, Shigeo; Mochida, Keiichi; Kawaura, Kanako; Ogihara, Yasunari; Murai, Koji

2007-06-01

Bread wheat (Triticum aestivum) is a hexaploid species with A, B, and D ancestral genomes. Most bread wheat genes are present in the genome as triplicated homoeologous genes (homoeologs) derived from the ancestral species. Here, we report that both genetic and epigenetic alterations have occurred in the homoeologs of a wheat class E MADS box gene. Two class E genes are identified in wheat, wheat SEPALLATA (WSEP) and wheat LEAFY HULL STERILE1 (WLHS1), which are homologs of Os MADS45 and Os MADS1 in rice (Oryza sativa), respectively. The three wheat homoeologs of WSEP showed similar genomic structures and expression profiles. By contrast, the three homoeologs of WLHS1 showed genetic and epigenetic alterations. The A genome WLHS1 homoeolog (WLHS1-A) had a structural alteration that contained a large novel sequence in place of the K domain sequence. A yeast two-hybrid analysis and a transgenic experiment indicated that the WLHS1-A protein had no apparent function. The B and D genome homoeologs, WLHS1-B and WLHS1-D, respectively, had an intact MADS box gene structure, but WLHS1-B was predominantly silenced by cytosine methylation. Consequently, of the three WLHS1 homoeologs, only WLHS1-D functions in hexaploid wheat. This is a situation where three homoeologs are differentially regulated by genetic and epigenetic mechanisms.

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.

Interactions of adolescent social experiences and dopamine genes to predict physical intimate partner violence perpetration.

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Laura M Schwab-Reese

Full Text Available We examined the interactions between three dopamine gene alleles (DAT1, DRD2, DRD4 previously associated with violent behavior and two components of the adolescent environment (exposure to violence, school social environment to predict adulthood physical intimate partner violence (IPV perpetration among white men and women.We used data from Wave IV of the National Longitudinal Study of Adolescent to Adult Health, a cohort study following individuals from adolescence to adulthood. Based on the prior literature, we categorized participants as at risk for each of the three dopamine genes using this coding scheme: two 10-R alleles for DAT1; at least one A-1 allele for DRD2; at least one 7-R or 8-R allele for DRD4. Adolescent exposure to violence and school social environment was measured in 1994 and 1995 when participants were in high school or middle school. Intimate partner violence perpetration was measured in 2008 when participants were 24 to 32 years old. We used simple and multivariable logistic regression models, including interactions of genes and the adolescent environments for the analysis.Presence of risk alleles was not independently associated with IPV perpetration but increasing exposure to violence and disconnection from the school social environment was associated with physical IPV perpetration. The effects of these adolescent experiences on physical IPV perpetration varied by dopamine risk allele status. Among individuals with non-risk dopamine alleles, increased exposure to violence during adolescence and perception of disconnection from the school environment were significantly associated with increased odds of physical IPV perpetration, but individuals with high risk alleles, overall, did not experience the same increase.Our results suggested the effects of adolescent environment on adulthood physical IPV perpetration varied by genetic factors. This analysis did not find a direct link between risk alleles and violence, but

Replication of type 2 diabetes candidate genes variations in three geographically unrelated Indian population groups.

Science.gov (United States)

Ali, Shafat; Chopra, Rupali; Manvati, Siddharth; Singh, Yoginder Pal; Kaul, Nabodita; Behura, Anita; Mahajan, Ankit; Sehajpal, Prabodh; Gupta, Subash; Dhar, Manoj K; Chainy, Gagan B N; Bhanwer, Amarjit S; Sharma, Swarkar; Bamezai, Rameshwar N K

2013-01-01

Type 2 diabetes (T2D) is a syndrome of multiple metabolic disorders and is genetically heterogeneous. India comprises one of the largest global populations with highest number of reported type 2 diabetes cases. However, limited information about T2D associated loci is available for Indian populations. It is, therefore, pertinent to evaluate the previously associated candidates as well as identify novel genetic variations in Indian populations to understand the extent of genetic heterogeneity. We chose to do a cost effective high-throughput mass-array genotyping and studied the candidate gene variations associated with T2D in literature. In this case-control candidate genes association study, 91 SNPs from 55 candidate genes have been analyzed in three geographically independent population groups from India. We report the genetic variants in five candidate genes: TCF7L2, HHEX, ENPP1, IDE and FTO, are significantly associated (after Bonferroni correction, ppopulation. Interestingly, SNP rs7903146 of the TCF7L2 gene passed the genome wide significance threshold (combined P value = 2.05E-08) in the studied populations. We also observed the association of rs7903146 with blood glucose (fasting and postprandial) levels, supporting the role of TCF7L2 gene in blood glucose homeostasis. Further, we noted that the moderate risk provided by the independently associated loci in combined population with Odds Ratio (OR)<1.38 increased to OR = 2.44, (95%CI = 1.67-3.59) when the risk providing genotypes of TCF7L2, HHEX, ENPP1 and FTO genes were combined, suggesting the importance of gene-gene interactions evaluation in complex disorders like T2D.

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

Science.gov (United States)

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

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

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

Science.gov (United States)

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.

Exact calculation of three-body contact interaction to second order

International Nuclear Information System (INIS)

Kaiser, N.

2012-01-01

For a system of fermions with a three-body contact interaction the second-order contributions to the energy per particle anti E(k f ) are calculated exactly. The three-particle scattering amplitude in the medium is derived in closed analytical form from the corresponding two-loop rescattering diagram. We compare the (genuine) second-order three-body contribution to anti E(k f )∝k f 10 with the second-order term due to the density-dependent effective two-body interaction, and find that the latter term dominates. The results of the present study are of interest for nuclear many-body calculations where chiral three-nucleon forces are treated beyond leading order via a density-dependent effective two-body interaction. (orig.)

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

Science.gov (United States)

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

Science.gov (United States)

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

Does the FTO Gene Interact with the Socio‐Economic Status on the Obesity Development Among Young European Children?

DEFF Research Database (Denmark)

Foraita, Ronja; Günther, Frauke; Gwozdz, Wencke

Various twin studies revealed that the influence of genetic factors on psychological diseases or behavior is more expressed in socio‐economically advantaged environments. Other studies predominantly show an inverse relation between socio‐economic status (SES) and childhood obesity in western...... developed countries. The aim of this study is to investigate whether the FTO gene interacts with the socio‐economic status (SES) on childhood obesity in a subsample of the IDEFICS cohort (N=4406). A structural equation model (SEM) is applied with the latent constructs obesity, dietary habits, physical...... activity and fitness habits, and parental SES to estimate the main effects of the latter three variables and a FTO polymorphism on obesity. Further, a multiple group SEM is used to explore whether an interaction effect between the single nucleotide polymorphism rs9939609 within the FTO gene and SES exists...

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

Science.gov (United States)

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.

Interactive multiobjective optimization for anatomy-based three-dimensional HDR brachytherapy

Science.gov (United States)

Ruotsalainen, Henri; Miettinen, Kaisa; Palmgren, Jan-Erik; Lahtinen, Tapani

2010-08-01

In this paper, we present an anatomy-based three-dimensional dose optimization approach for HDR brachytherapy using interactive multiobjective optimization (IMOO). In brachytherapy, the goals are to irradiate a tumor without causing damage to healthy tissue. These goals are often conflicting, i.e. when one target is optimized the other will suffer, and the solution is a compromise between them. IMOO is capable of handling multiple and strongly conflicting objectives in a convenient way. With the IMOO approach, a treatment planner's knowledge is used to direct the optimization process. Thus, the weaknesses of widely used optimization techniques (e.g. defining weights, computational burden and trial-and-error planning) can be avoided, planning times can be shortened and the number of solutions to be calculated is small. Further, plan quality can be improved by finding advantageous trade-offs between the solutions. In addition, our approach offers an easy way to navigate among the obtained Pareto optimal solutions (i.e. different treatment plans). When considering a simulation model of clinical 3D HDR brachytherapy, the number of variables is significantly smaller compared to IMRT, for example. Thus, when solving the model, the CPU time is relatively short. This makes it possible to exploit IMOO to solve a 3D HDR brachytherapy optimization problem. To demonstrate the advantages of IMOO, two clinical examples of optimizing a gynecologic cervix cancer treatment plan are presented.

Interactive multiobjective optimization for anatomy-based three-dimensional HDR brachytherapy

International Nuclear Information System (INIS)

Ruotsalainen, Henri; Miettinen, Kaisa; Palmgren, Jan-Erik; Lahtinen, Tapani

2010-01-01

In this paper, we present an anatomy-based three-dimensional dose optimization approach for HDR brachytherapy using interactive multiobjective optimization (IMOO). In brachytherapy, the goals are to irradiate a tumor without causing damage to healthy tissue. These goals are often conflicting, i.e. when one target is optimized the other will suffer, and the solution is a compromise between them. IMOO is capable of handling multiple and strongly conflicting objectives in a convenient way. With the IMOO approach, a treatment planner's knowledge is used to direct the optimization process. Thus, the weaknesses of widely used optimization techniques (e.g. defining weights, computational burden and trial-and-error planning) can be avoided, planning times can be shortened and the number of solutions to be calculated is small. Further, plan quality can be improved by finding advantageous trade-offs between the solutions. In addition, our approach offers an easy way to navigate among the obtained Pareto optimal solutions (i.e. different treatment plans). When considering a simulation model of clinical 3D HDR brachytherapy, the number of variables is significantly smaller compared to IMRT, for example. Thus, when solving the model, the CPU time is relatively short. This makes it possible to exploit IMOO to solve a 3D HDR brachytherapy optimization problem. To demonstrate the advantages of IMOO, two clinical examples of optimizing a gynecologic cervix cancer treatment plan are presented.

Three-dimensional theory for light-matter interaction

DEFF Research Database (Denmark)

Sørensen, Martin Westring; Sørensen, Anders Søndberg

2008-01-01

We present a full quantum mechanical three dimensional theory describing an electromagnetic field interacting with an ensemble of identical atoms. The theory is constructed such that it describes recent experiments on light-matter quantum interfaces, where the quantum fluctuations of light...... to a dressed state picture, where the light modes are solutions to the diffraction problem, and develop a perturbative expansion in the fluctuations. The fluctuations are due to quantum fluctuations as well as the random positions of the atoms. In this perturbative expansion we show how the quantum...... fluctuations are mapped between atoms and light while the random positioning of the atoms give rise to decay due to spontaneous emission. Furthermore we identify limits, where the full three dimensional theory reduce to the one dimensional theory typically used to describe the interaction....

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.

Observation of the Borromean Three-Body Förster Resonances for Three Interacting Rb Rydberg Atoms.

Science.gov (United States)

Tretyakov, D B; Beterov, I I; Yakshina, E A; Entin, V M; Ryabtsev, I I; Cheinet, P; Pillet, P

2017-10-27

Three-body Förster resonances at long-range interactions of Rydberg atoms were first predicted and observed in Cs Rydberg atoms by Faoro et al. [Nat. Commun. 6, 8173 (2015)NCAOBW2041-172310.1038/ncomms9173]. In these resonances, one of the atoms carries away an energy excess preventing the two-body resonance, leading thus to a Borromean type of Förster energy transfer. But they were in fact observed as the average signal for the large number of atoms N≫1. In this Letter, we report on the first experimental observation of the three-body Förster resonances 3×nP_{3/2}(|M|)→nS_{1/2}+(n+1)S_{1/2}+nP_{3/2}(|M^{*}|) in a few Rb Rydberg atoms with n=36, 37. We have found here clear evidence that there is no signature of the three-body Förster resonance for exactly two interacting Rydberg atoms, while it is present for N=3-5 atoms. This demonstrates the assumption that three-body resonances can generalize to any Rydberg atom. As such resonance represents an effective three-body operator, it can be used to directly control the three-body interactions in quantum simulations and quantum information processing with Rydberg atoms.

Three nucleon interaction and nuclear composition

International Nuclear Information System (INIS)

Pandharipande, V.R.

1983-01-01

The author discusses results of some of the calculations carried out by J. Carlson, I. Lagaris, J. Lomnitz-Adler, R.A. Smith, R.B. Wiringa and himself to study the three nucleon interaction. The group has attempted to calculate the wavefunctions and binding energies of 3 H, 3 He, 4 He and nuclear matter, with the variational method, from a nonrelativistic Hamiltonian. Only nucleon degrees of freedom are retained in this Hamiltonian; the effects of other degrees of freedom are implicit in the two and three nucleon potentials. The author discusses further the calculations carried out, in collaboration with B. Friman, and R.B. Wiringa, to study the composition of nuclei. Nucleons interact by many processes including exchange of pions with or without excitation to isobar (Δ) states. Thus the nucleus contains pions being exchanged, and some nucleons in the Δ state. The group attempts to calculate the number and momentum distribution of these exchanged pions, and the fraction of time a nucleon in the nucleus is in the Δ state. 21 references, 4 figures

Nucleotide diversity analysis of three major bacterial blight resistance genes in rice.

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Waikhom Bimolata

Full Text Available Nucleotide sequence polymorphisms among R gene alleles influence the process of co-evolutionary interaction between host and pathogen by shaping the response of host plants towards invading pathogens. Here, we present the DNA sequence polymorphisms and diversities present among natural alleles of three rice bacterial blight resistance genes, Xa21, Xa26 and xa5. The diversity was examined across different wild relatives and cultivars of Oryza species. Functional significance of selected alleles was evaluated through semi-quantitative reverse transcription polymerase chain reaction and real time PCR. The greatest nucleotide diversity and singleton variable sites (SVS were present in Xa26 (π = 0.01958; SVS = 182 followed by xa5 and Xa21 alleles. The highest frequency of single nucleotide polymorphisms were observed in Xa21 alleles and least in xa5. Transition bias was observed in all the genes and 'G' to 'A' transitions were more favored than other form of transitions. Neutrality tests failed to show the presence of selection at these loci, though negative Tajima's D values indicate the presence of a rare form of polymorphisms. At the interspecies level, O. nivara exhibited more diversity than O. sativa. We have also identified two nearly identical resistant alleles of xa5 and two sequentially identical alleles of Xa21. The alleles of xa5 showed basal levels of expression while Xa21 alleles were functionally not expressed.

Resequencing three candidate genes discovers seven potentially deleterious variants susceptibility to major depressive disorder and suicide attempts in Chinese.

Science.gov (United States)

Rao, Shitao; Leung, Cherry She Ting; Lam, Macro Hb; Wing, Yun Kwok; Waye, Mary Miu Yee; Tsui, Stephen Kwok Wing

2017-03-01

To date almost 200 genes were found to be associated with major depressive disorder (MDD) or suicide attempts (SA), but very few genes were reported for their molecular mechanisms. This study aimed to find out whether there were common or rare variants in three candidate genes altering the risk for MDD and SA in Chinese. Three candidate genes (HOMER1, SLC6A4 and TEF) were chosen for resequencing analysis and association studies as they were reported to be involved in the etiology of MDD and SA. Following that, bioinformatics analyses were applied on those variants of interest. After resequencing analysis and alignment for the amplicons, a total of 34 common or rare variants were found in the randomly selected 36 Hong Kong Chinese patients with both MDD and SA. Among those, seven variants show potentially deleterious features. Rs60029191 and a rare variant located in regulatory region of the HOMER1 gene may affect the promoter activities through interacting with predicted transcription factors. Two missense mutations existed in the SLC6A4 coding regions were firstly reported in Hong Kong Chinese MDD and SA patients, and both of them could affect the transport efficiency of SLC6A4 to serotonin. Moreover, a common variant rs6354 located in the untranslated region of this gene may affect the expression level or exonic splicing of serotonin transporter. In addition, both of a most studied polymorphism rs738499 and a low-frequency variant in the promoter region of the TEF gene were found to be located in potential transcription factor binding sites, which may let the two variants be able to influence the promoter activities of the gene. This study elucidated the potentially molecular mechanisms of the three candidate genes altering the risk for MDD and SA. These findings implied that not only common variants but rare variants could make contributions to the genetic susceptibility to MDD and SA in Chinese. Copyright © 2016 Elsevier B.V. All rights reserved.

Daf-2, Daf-16 and Daf-23: Genetically Interacting Genes Controlling Dauer Formation in Caenorhabditis Elegans

OpenAIRE

Gottlieb, S.; Ruvkun, G.

1994-01-01

Under conditions of high population density and low food, Caenorhabditis elegans forms an alternative third larval stage, called the dauer stage, which is resistant to desiccation and harsh environments. Genetic analysis of some dauer constitutive (Daf-c) and dauer defective (Daf-d) mutants has revealed a complex pathway that is likely to function in particular neurons and/or responding tissues. Here we analyze the genetic interactions between three genes which comprise a branch of the dauer ...

Algebraic diagrammatic construction formalism with three-body interactions

Science.gov (United States)

Raimondi, Francesco; Barbieri, Carlo

2018-05-01

Background: Self-consistent Green's function theory has recently been extended to the basic formalism needed to account for three-body interactions [Carbone, Cipollone, Barbieri, Rios, and Polls, Phys. Rev. C 88, 054326 (2013), 10.1103/PhysRevC.88.054326]. The contribution of three-nucleon forces has so far been included in ab initio calculations on nuclear matter and finite nuclei only as averaged two-nucleon forces. Purpose: We derive the working equations for all possible two- and three-nucleon terms that enter the expansion of the self-energy up to the third order, thus including the interaction-irreducible (i.e., not averaged) diagrams with three-nucleon forces that have been previously neglected. Methods: We employ the algebraic diagrammatic construction up to the third order as an organization scheme for generating a nonperturbative self-energy, in which ring (particle-hole) and ladder (particle-particle) diagrams are resummed to all orders. Results: We derive expressions of the static and dynamic self-energy up to the third order, by taking into account the set of diagrams required when either the skeleton or nonskeleton expansions of the single-particle propagator are assumed. A hierarchy of importance among different diagrams is revealed, and a particular emphasis is given to a third-order diagram [see Fig. 2(c)] that is expected to play a significant role among those featuring an interaction-irreducible three-nucleon force. Conclusion: A consistent formalism to resum at infinite order correlations induced by three-nucleon forces in the self-consistent Green's function theory is now available and ready to be implemented in the many-body solvers.

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.

Replication of type 2 diabetes candidate genes variations in three geographically unrelated Indian population groups.

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Shafat Ali

Full Text Available Type 2 diabetes (T2D is a syndrome of multiple metabolic disorders and is genetically heterogeneous. India comprises one of the largest global populations with highest number of reported type 2 diabetes cases. However, limited information about T2D associated loci is available for Indian populations. It is, therefore, pertinent to evaluate the previously associated candidates as well as identify novel genetic variations in Indian populations to understand the extent of genetic heterogeneity. We chose to do a cost effective high-throughput mass-array genotyping and studied the candidate gene variations associated with T2D in literature. In this case-control candidate genes association study, 91 SNPs from 55 candidate genes have been analyzed in three geographically independent population groups from India. We report the genetic variants in five candidate genes: TCF7L2, HHEX, ENPP1, IDE and FTO, are significantly associated (after Bonferroni correction, p<5.5E-04 with T2D susceptibility in combined population. Interestingly, SNP rs7903146 of the TCF7L2 gene passed the genome wide significance threshold (combined P value = 2.05E-08 in the studied populations. We also observed the association of rs7903146 with blood glucose (fasting and postprandial levels, supporting the role of TCF7L2 gene in blood glucose homeostasis. Further, we noted that the moderate risk provided by the independently associated loci in combined population with Odds Ratio (OR<1.38 increased to OR = 2.44, (95%CI = 1.67-3.59 when the risk providing genotypes of TCF7L2, HHEX, ENPP1 and FTO genes were combined, suggesting the importance of gene-gene interactions evaluation in complex disorders like T2D.

Three novel and two known androgen receptor gene mutations ...

Indian Academy of Sciences (India)

with androgen insensitivity syndrome in sex-reversed XY female patients. BALACHANDRAN .... Three novel AR gene mutations associated with AIS in XY sex-reversed females. Ta b le. 1 . ( contd. ) ..... disease, 1st edition. Springer Science + ...

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

Science.gov (United States)

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.

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

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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

Finding gene-environment interactions for phobias.

Science.gov (United States)

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.

Gene-environment Interactions in Human Health: Case Studies and Strategies for developing new paradigms and research methodologies

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Fatimah L.C. Jackson

2014-08-01

Full Text Available The synergistic effects of genes and the environment on health are explored in three case studies: adult lactase persistence, autism spectrum disorders, and the metabolic syndrome, providing examples of the interactive complexities underlying these phenotypes. Since the phenotypes are the initial targets of evolutionary processes, understanding the specific environmental contexts of the genetic, epigenetic, and proteomic changes associated with these phenotypes is essential in predicting their health implications. Robust databases must be developed on the local scale to deconstruct both the population substructure and the unique components of the environment that stimulate geographically-specific changes in gene expression patterns. To produce these databases and make valid predictions, new, locally-focused and information-dense models are needed that incorporate data on evolutionary ecology, environmental complexity, local geographic patterns of gene expression, and population substructure.

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.

Science.gov (United States)

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.

Turbulent spectra from three drift-wave interactions

International Nuclear Information System (INIS)

Terry, P.W.; Horton, W.

1982-02-01

Hydrodynamic equations for the drift-wave instability containing the rvec E x rvec B convective nonlinearity are used to show that the three wave interactions lead to temporal chaos with broad-band frequency spectra in the saturated state. 7 refs., 2 figs

Locating one pairwise interaction: Three recursive constructions

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Charles J. Colbourn

2016-09-01

Full Text Available In a complex component-based system, choices (levels for components (factors may interact tocause faults in the system behaviour. When faults may be caused by interactions among few factorsat specific levels, covering arrays provide a combinatorial test suite for discovering the presence offaults. While well studied, covering arrays do not enable one to determine the specific levels of factorscausing the faults; locating arrays ensure that the results from test suite execution suffice to determinethe precise levels and factors causing faults, when the number of such causes is small. Constructionsfor locating arrays are at present limited to heuristic computational methods and quite specific directconstructions. In this paper three recursive constructions are developed for locating arrays to locateone pairwise interaction causing a fault.

Gene-environment interaction and male reproductive function

Science.gov (United States)

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

Partial characterization of three β-defensin gene transcripts in river ...

African Journals Online (AJOL)

In this study, the tracheal tissues from Egyptian river buffalo and cattle were screened for the presence of three bovine β-defensin gene transcripts. Three primer pairs were designed on the basis of published Bos taurus sequences for partial amplification of β-defensin 4, β-defensin 10 and β-defensin 11 complementary DNA ...

Genotypes do not confer risk for delinquency but rather alter susceptibility to positive and negative environmental factors: gene-environmentinteractions of BDNF Val66Met, 5-HTTLPR, and MAOA-uVNTR [corrected].

Science.gov (United States)

Nilsson, Kent W; Comasco, Erika; Hodgins, Sheilagh; Oreland, Lars; Åslund, Cecilia

2014-12-10

Previous evidence of gene-by-environment interactions associated with emotional and behavioral disorders is contradictory. Differences in findings may result from variation in valence and dose of the environmental factor, and/or failure to take account of gene-by-gene interactions. The present study investigated interactions between the brain-derived neurotrophic factor gene (BDNF Val66Met), the serotonin transporter gene-linked polymorphic region (5-HTTLPR), the monoamine oxidase A (MAOA-uVNTR) polymorphisms, family conflict, sexual abuse, the quality of the child-parent relationship, and teenage delinquency. In 2006, as part of the Survey of Adolescent Life in Västmanland, Sweden, 1 337 high-school students, aged 17-18 years, anonymously completed questionnaires and provided saliva samples for DNA analyses. Teenage delinquency was associated with two-, three-, and four-way interactions of each of the genotypes and the three environmental factors. Significant four-way interactions were found for BDNF Val66Met × 5-HTTLPR×MAOA-uVNTR × family conflicts and for BDNF Val66Met × 5-HTTLPR×MAOA-uVNTR × sexual abuse. Further, the two genotype combinations that differed the most in expression levels (BDNF Val66Met Val, 5-HTTLPR LL, MAOA-uVNTR LL [girls] and L [boys] vs BDNF Val66Met Val/Met, 5-HTTLPR S/LS, MAOA-uVNTR S/SS/LS) in interaction with family conflict and sexual abuse were associated with the highest delinquency scores. The genetic variants previously shown to confer vulnerability for delinquency (BDNF Val66Met Val/Met × 5-HTTLPR S × MAOA-uVNTR S) were associated with the lowest delinquency scores in interaction with a positive child-parent relationship. Functional variants of the MAOA-uVNTR, 5-HTTLPR, and BDNF Val66Met, either alone or in interaction with each other, may be best conceptualized as modifying sensitivity to environmental factors that confer either risk or protection for teenage delinquency. © The Author 2015. Published by Oxford University

Conventional and fluorescence in situ hybridization analysis of three-way complex BCR-ABL rearrangement in a chronic myeloid leukemia patient

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Ganguly Bani

2007-01-01

Full Text Available Chromosomal analysis was carried out in bone marrow sample of an 11-year-old girl suspected of myeloproliferative disorder. Conventional G-banding study detected a complex three-way translocation involving 7, 9 and 22, which has resulted in the formation of a variant Philadelphia chromosome causing rearrangement of abl and bcr genes in 87% cells. Fluorescence in situ hybridization (FISH confirmed the fusion of bcr-abl oncogene. Thus the bone marrow karyotype was observed as 46,XX (13% / 46,XX,t(7;9;22(q11;q34;q11 (87%. Hyperdiploidy was present in two cells. In this study, both conventional cytogenetic and FISH diagnosis proved to be significant to identify the variant nature of the Philadelphia chromosome and hyperdiploid condition for introduction of a suitable treatment regimen and estimation of life expectancy of the young girl.

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.

Three-dimensional interactive atlas of cranial nerve-related disorders.

Science.gov (United States)

Nowinski, W L; Chua, B C

2013-06-01

Anatomical knowledge of the cranial nerves (CN) is fundamental in education, research and clinical practice. Moreover, understanding CN-related pathology with underlying neuroanatomy and the resulting neurological deficits is of vital importance. To facilitate CN knowledge anatomy and pathology understanding, we created an atlas of CN-related disorders, which is a three-dimensional (3D) interactive tool correlating CN pathology with the underlying surface and sectional neuroanatomy as well as the resulting neurological deficits. A computer platform was developed with: 1) anatomy browser along with the normal brain atlas (built earlier); 2) simulator of CN lesions; 3) tools to label CN-related pathology; and 4) CN pathology database with lesions and disorders, and the resulting signs, symptoms and/or syndromes. The normal neuroanatomy comprises about 2,300 3D components subdivided into modules. Cranial nerves contain more than 600 components: all 12 pairs of cranial nerves (CN I - CN XII) and the brainstem CN nuclei. The CN pathology database was populated with 36 lesions compiled from clinical textbooks. The initial view of each disorder was preset in terms of lesion location and size, surrounding surface and sectional neuroanatomy, and disorder and neuroanatomy labeling. Moreover, path selection from a CN nucleus to a targeted organ further enhances pathology-anatomy relationships. This atlas of CN-related disorders is potentially useful to a wide variety of users ranging from medical students and residents to general practitioners, neuroradiologists and neurologists, as it contains both normal brain anatomy and CN-related pathology correlated with neurological disorders presented in a visual and interactive way.

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.

A New Way of Using the Interactive Whiteboard in a High School Physics Classroom: A Case Study

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Gregorcic, Bor; Etkina, Eugenia; Planinsic, Gorazd

2018-01-01

In recent decades, the interactive whiteboard (IWB) has become a relatively common educational tool in Western schools. The IWB is essentially a large touch screen, that enables the user to interact with digital content in ways that are not possible with an ordinary computer-projector-canvas setup. However, the unique possibilities of IWBs are…

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

nor sufficient for transcription factor activity. Transcription regulation is a complex and still not fully understood process involving, in addition to protein-DNA binding, other factors such as epigenetic modifications and three-dimensional DNA organization. In this issue, Levens and Benham discuss another important mechanism which is likely to contribute to overall gene regulation—changes of DNA secondary structure in response to supercoiling-induced stress. Pointing out that DNA is "more than a cipher", they argue that the DNA structural transitions driven by negative supercoiling may have profound consequences for the cell and have to be accounted for in detailed models. There is considerable progress in physical modeling of DNA dynamics in response to stress. Such efforts, supported by experimental data, will bring us closer to an understanding of the role of supercoiling in gene regulation. Large-scale biomolecular interaction networks not only provide a system-level view of cellular processes, but are also increasingly used to model communications between molecules. The lack of sufficient biochemical data and the gigantic scale of the network prevented detailed modeling of network dynamics and have stimulated the development of simplified models such as the information flow approach described by Kim et al in this issue. Importantly, despite their simplicity, such models proved to be extremely useful for identifying network modules, essential nodes, and molecular pathways which are dysregulated in complex diseases such as cancer. Finally, moving from studies of single cells towards populations, one has to recognize the heterogeneity present within a population of cells. In the context of protein abundance, such cell-to-cell variation within clonal populations of cells, referred to as expression noise, has recently become a focus of intense cross-disciplinary research. Concerted efforts of experimentalists, physicists and mathematicians have brought us closer

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.

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.

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

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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.

Housekeeping genes for quantitative expression studies in the three-spined stickleback Gasterosteus aculeatus

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Becker Sven

2008-01-01

Full Text Available Abstract Background During the last years the quantification of immune response under immunological challenges, e.g. parasitation, has been a major focus of research. In this context, the expression of immune response genes in teleost fish has been surveyed for scientific and commercial purposes. Despite the fact that it was shown in teleostei and other taxa that the gene for beta-actin is not the most stably expressed housekeeping gene (HKG, depending on the tissue and experimental treatment, the gene has been used as a reference gene in such studies. In the three-spined stickleback, Gasterosteus aculeatus, other HKG than the one for beta-actin have not been established so far. Results To establish a reliable method for the measurement of immune gene expression in Gasterosteus aculeatus, sequences from the now available genome database and an EST library of the same species were used to select oligonucleotide primers for HKG, in order to perform quantitative reverse-transcription (RT PCR. The expression stability of ten candidate reference genes was evaluated in three different tissues, and in five parasite treatment groups, using the three algorithms BestKeeper, geNorm and NormFinder. Our results showed that in most of the tissues and treatments HKG that could not be used so far due to unknown sequences, proved to be more stably expressed than the one for beta-actin. Conclusion As they were the most stably expressed genes in all tissues examined, we suggest using the genes for the L13a ribosomal binding protein and ubiquitin as alternative or additional reference genes in expression analysis in Gasterosteus aculeatus.

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).

A Hybrid One-Way ANOVA Approach for the Robust and Efficient Estimation of Differential Gene Expression with Multiple Patterns.

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Mohammad Manir Hossain Mollah

Full Text Available Identifying genes that are differentially expressed (DE between two or more conditions with multiple patterns of expression is one of the primary objectives of gene expression data analysis. Several statistical approaches, including one-way analysis of variance (ANOVA, are used to identify DE genes. However, most of these methods provide misleading results for two or more conditions with multiple patterns of expression in the presence of outlying genes. In this paper, an attempt is made to develop a hybrid one-way ANOVA approach that unifies the robustness and efficiency of estimation using the minimum β-divergence method to overcome some problems that arise in the existing robust methods for both small- and large-sample cases with multiple patterns of expression.The proposed method relies on a β-weight function, which produces values between 0 and 1. The β-weight function with β = 0.2 is used as a measure of outlier detection. It assigns smaller weights (≥ 0 to outlying expressions and larger weights (≤ 1 to typical expressions. The distribution of the β-weights is used to calculate the cut-off point, which is compared to the observed β-weight of an expression to determine whether that gene expression is an outlier. This weight function plays a key role in unifying the robustness and efficiency of estimation in one-way ANOVA.Analyses of simulated gene expression profiles revealed that all eight methods (ANOVA, SAM, LIMMA, EBarrays, eLNN, KW, robust BetaEB and proposed perform almost identically for m = 2 conditions in the absence of outliers. However, the robust BetaEB method and the proposed method exhibited considerably better performance than the other six methods in the presence of outliers. In this case, the BetaEB method exhibited slightly better performance than the proposed method for the small-sample cases, but the the proposed method exhibited much better performance than the BetaEB method for both the small- and large

Nuclear structure with unitarily transformed two-body plus phenomenological three-body interactions

Energy Technology Data Exchange (ETDEWEB)

Guenther, Anneke

2011-02-02

The importance of three-nucleon forces for a variety of nuclear structure phenomena is apparent in various investigations. This thesis provides a first step towards the inclusion of realistic three-nucleon forces by studying simple phenomenological threebody interactions. The Unitary Correlation Operator Method (UCOM) and the Similarity Renormalization Group (SRG) provide two different approaches to derive soft phase-shift equivalent nucleon-nucleon (NN) interactions via unitary transformations. Although their motivations are quite different the NN interactions obtained with the two methods exhibit some similarities. The application of the UCOM- or SRG-transformed Argonne V18 potential in the Hartree-Fock (HF) approximation and including the second-order energy corrections emerging from many-body perturbation theory (MBPT) reveals that the systematics of experimental ground-state energies can be reproduced by some of the interactions considering a series of closed-shell nuclei across the whole nuclear chart. However, charge radii are systematically underestimated, especially for intermediate and heavy nuclei. This discrepancy to experimental data is expected to result from neglected three-nucleon interactions. As first ansatz for a three-nucleon force, we consider a finite-range three-body interaction of Gaussian shape. Its influence on ground-state energies and charge radii is discussed in detail on the basis of HF plus MBPT calculations and shows a significant improvement in the description of experimental data. As the handling of the Gaussian three-body interaction is time-extensive, we show that it can be replaced by a regularized three-body contact interaction exhibiting a very similar behavior. An extensive study characterizes its properties in detail and confirms the improvements with respect to nuclear properties. To take into account information of an exact numerical solution of the nuclear eigenvalue problem, the No-Core Shell Model is applied to

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

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

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.

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.

A rapid, ratiometric, enzyme-free, and sensitive single-step miRNA detection using three-way junction based FRET probes

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Luo, Qingying; Liu, Lin; Yang, Cai; Yuan, Jing; Feng, Hongtao; Chen, Yan; Zhao, Peng; Yu, Zhiqiang; Jin, Zongwen

2018-03-01

MicroRNAs (miRNAs) are single stranded endogenous molecules composed of only 18-24 nucleotides which are critical for gene expression regulating the translation of messenger RNAs. Conventional methods based on enzyme-assisted nucleic acid amplification techniques have many problems, such as easy contamination, high cost, susceptibility to false amplification, and tendency to have sequence mismatches. Here we report a rapid, ratiometric, enzyme-free, sensitive, and highly selective single-step miRNA detection using three-way junction assembled (or self-assembled) FRET probes. The developed strategy can be operated within the linear range from subnanomolar to hundred nanomolar concentrations of miRNAs. In comparison with the traditional approaches, our method showed high sensitivity for the miRNA detection and extreme selectivity for the efficient discrimination of single-base mismatches. The results reveal that the strategy paved a new avenue for the design of novel highly specific probes applicable in diagnostics and potentially in microscopic imaging of miRNAs in real biological environments.

Cloning and expression of three thaumatin-like protein genes from Polyporus umbellatus

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Mengmeng Liu

2017-05-01

Full Text Available Genes encoding thaumatin-like protein (TLPs are frequently found in fungal genomes. However, information on TLP genes in Polyporus umbellatus is still limited. In this study, three TLP genes were cloned from P. umbellatus. The full-length coding sequence of PuTLP1, PuTLP2 and PuTLP3 were 768, 759 and 561 bp long, respectively, encoding for 256, 253 and 187 amino acids. Phylogenetic trees showed that P. umbellatus PuTLP1, PuTLP2 and PuTLP3 were clustered with sequences from Gloeophyllum trabeum, Trametes versicolor and Stereum hirsutum, respectively. The expression patterns of the three TLP genes were higher in P. umbellatus with Armillaria mellea infection than in the sclerotia without A. mellea. Furthermore, over-expression of three PuTLPs were carried out in Escherichia coli BL21 (DE3 strain, and high quality proteins were obtained using Ni-NTA resin that can be used for preparation of specific antibodies. These results suggest that PuTLP1, PuTLP2 and PuTLP3 in P. umbellatus may be involved in the defense response to A. mellea infections.

Two-way Fluid-Structure Interaction Simulation of a Micro Horizontal Axis Wind Turbine

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Yi-Bao Chen

2015-01-01

Full Text Available A two-way Fluid-Structure Interaction (FSI analyses performed on a micro horizontal axis wind turbine (HAWT which coupled the CFX solver with Structural solver in ANSYS Workbench was conducted in this paper. The partitioned approach-based non-conforming mesh methods and the k-ε turbulence model were adopted to perform the study. Both the results of one-way and two-way FSI analyses were presented and compared with each other, and discrepancy of the results, especially the mechanical properties, were analysed. Grid convergence which is crucial to the results was performed, and the relationship between the inner flow field domain (rotational domain and the number of grids (number of cells, elements was verified for the first time. Dynamical analyses of the wind turbine were conducted using the torque as a reference value, to verify the rationality of the model which dominates the accuracy of results. The optimal case was verified and used to conduct the study, thus, the results derived from the simulation of the FSI are accurate and credible.

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

Three-body interactions and the elastic constants of hcp solid 4He

Science.gov (United States)

Barnes, Ashleigh L.; Hinde, Robert J.

2017-09-01

The effect of three-body interactions on the elastic properties of hexagonal close packed solid 4He is investigated using variational path integral (VPI) Monte Carlo simulations. The solid's nonzero elastic constants are calculated, at T = 0 K and for a range of molar volumes from 7.88 cm3/mol to 20.78 cm3/mol, from the bulk modulus and the three pure shear constants C0, C66, and C44. Three-body interactions are accounted for using our recently reported perturbative treatment based on the nonadditive three-body potential of Cencek et al. Previous studies have attempted to account for the effect of three-body interactions on the elastic properties of solid 4He; however, these calculations have treated zero point motions using either the Einstein or Debye approximations, which are insufficient in the molar volume range where solid 4He is characterized as a quantum solid. Our VPI calculations allow for a more accurate treatment of the zero point motions which include atomic correlation. From these calculations, we find that agreement with the experimental bulk modulus is significantly improved when three-body interactions are considered. In addition, three-body interactions result in non-negligible differences in the calculated pure shear constants and nonzero elastic constants, particularly at higher densities, where differences of up to 26.5% are observed when three-body interactions are included. We compare to the available experimental data and find that our results are generally in as good or better agreement with experiment as previous theoretical investigations.

Effects of three-body interactions on the dynamics of entanglement in spin chains

International Nuclear Information System (INIS)

Shi Cuihua; Wu Yinzhong; Li Zhenya

2009-01-01

With the consideration of three-body interaction, dynamics of pairwise entanglement in spin chains is studied. The dependence of pairwise entanglement dynamics on the type of coupling, and distance between the spins is analyzed in a finite chain for different initial states. It is found that, for an Ising chain, three-body interactions are not in favor of preparing entanglement between the nearest neighbor spins, while three-body interactions are favorable for creating entanglement between remote spins from a separable initial state. For an isotropic Heisenberg chain, the pairwise concurrence will decrease when three-body interactions are considered both for a separable initial state and for a maximally entangled initial state, however, three-body interactions will retard the decay of the concurrence in an Ising chain when the initial state takes the maximally entangled state.

Association and interaction analyses of 5-HT3 receptor and serotonin transporter genes with alcohol, cocaine, and nicotine dependence using the SAGE data.

Science.gov (United States)

Yang, Jiekun; Li, Ming D

2014-07-01

Previous studies have implicated genes encoding the 5-HT3AB receptors (HTR3A and HTR3B) and the serotonin transporter (SLC6A4), both independently and interactively, in alcohol (AD), cocaine (CD), and nicotine dependence (ND). However, whether these genetic effects also exist in subjects with comorbidities remains largely unknown. We used 1,136 African-American (AA) and 2,428 European-American (EA) subjects from the Study of Addiction: Genetics and Environment (SAGE) to determine associations between 88 genotyped or imputed variants within HTR3A, HTR3B, and SLC6A4 and three types of addictions, which were measured by DSM-IV diagnoses of AD, CD, and ND and the Fagerström Test for Nicotine Dependence (FTND), an independent measure of ND commonly used in tobacco research. Individual SNP-based association analysis revealed a significant association of rs2066713 in SLC6A4 with FTND in AA (β = -1.39; P = 1.6E - 04). Haplotype-based association analysis found one major haplotype formed by SNPs rs3891484 and rs3758987 in HTR3B that was significantly associated with AD in the AA sample, and another major haplotype T-T-G, formed by SNPs rs7118530, rs12221649, and rs2085421 in HTR3A, which showed significant association with FTND in the EA sample. Considering the biologic roles of the three genes and their functional relations, we used the GPU-based Generalized Multifactor Dimensionality Reduction (GMDR-GPU) program to test SNP-by-SNP interactions within the three genes and discovered two- to five-variant models that have significant impacts on AD, CD, ND, or FTND. Interestingly, most of the SNPs included in the genetic interaction model(s) for each addictive phenotype are either overlapped or in high linkage disequilibrium for both AA and EA samples, suggesting these detected variants in HTR3A, HTR3B, and SLC6A4 are interactively contributing to etiology of the three addictive phenotypes examined in this study.

Exome sequencing identifies three novel candidate genes implicated in intellectual disability.

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Zehra Agha

Full Text Available Intellectual disability (ID is a major health problem mostly with an unknown etiology. Recently exome sequencing of individuals with ID identified novel genes implicated in the disease. Therefore the purpose of the present study was to identify the genetic cause of ID in one syndromic and two non-syndromic Pakistani families. Whole exome of three ID probands was sequenced. Missense variations in two plausible novel genes implicated in autosomal recessive ID were identified: lysine (K-specific methyltransferase 2B (KMT2B, zinc finger protein 589 (ZNF589, as well as hedgehog acyltransferase (HHAT with a de novo mutation with autosomal dominant mode of inheritance. The KMT2B recessive variant is the first report of recessive Kleefstra syndrome-like phenotype. Identification of plausible causative mutations for two recessive and a dominant type of ID, in genes not previously implicated in disease, underscores the large genetic heterogeneity of ID. These results also support the viewpoint that large number of ID genes converge on limited number of common networks i.e. ZNF589 belongs to KRAB-domain zinc-finger proteins previously implicated in ID, HHAT is predicted to affect sonic hedgehog, which is involved in several disorders with ID, KMT2B associated with syndromic ID fits the epigenetic module underlying the Kleefstra syndromic spectrum. The association of these novel genes in three different Pakistani ID families highlights the importance of screening these genes in more families with similar phenotypes from different populations to confirm the involvement of these genes in pathogenesis of ID.

Effect of pairwise dipole–dipole interaction among three-atom systems

Indian Academy of Sciences (India)

2014-07-18

Jul 18, 2014 ... We present an analysis of a system of three two-level atoms interacting with one another through dipole–dipole interaction. The interaction manifests between the excited state of one of the atoms and the ground state of its nearest neighbour. Steady-state populations of the density matrix elements are ...

Two-way text messaging: an interactive mobile learning environment in higher education

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H.K. Salinda Premadasa

2016-11-01

Full Text Available Short messaging service (SMS is perhaps the most popular mobile technology prevalent among students in higher education due to its ubiquitous nature and the capability of two-way communication. However, a major limitation in two-way text messaging is sending back a part of received data with the reply message. This limitation results in users of a mobile learning environment being unable to reply back to the correct destination. This article presents a two-way text messaging system that can be integrated into a learning management system (LMS to provide an interactive learning experience to the user community. Initially, a database is integrated into the LMS that holds message information such as recipient's phone number, message body and user data header. A specific port associated with the SMS is used to conceal and exchange data of a particular course unit. Subsequently, software in the student's mobile device captures this message and sends back the reply message to the appropriate course unit allowing both teachers and students to view messages sent and replies received pertaining to a particular course. Results indicate the educational impact of the proposed system in improving the learning environment and benefits it offers to the community in a campus-wide implementation.

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.

Science.gov (United States)

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.

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.

Degrees-of-Freedom of the MIMO Three-Way Channel with Node-Intermittency

KAUST Repository

Neu, Joachim

2017-08-28

The characterization of fundamental performance bounds of many-to-many communication systems in which participating nodes are active in an intermittent way is one of the major challenges in communication theory. In order to address this issue, we introduce the multiple-input multiple-output (MIMO) three-way channel (3WC) with an intermittent node and study its degrees-of-freedom (DoF) region and sum-DoF. We devise a non-adaptive encoding scheme based on zero-forcing, interference alignment and erasure coding, and show its DoF region (and thus sum-DoF) optimality for non-intermittent 3WCs and its sum-DoF optimality for (node-)intermittent 3WCs. However, we show by example that in general some DoF tuples in the intermittent 3WC can only be achieved by adaptive schemes, such as multi-hop or decode-forward relaying. This shows that non-adaptive encoding is sufficient for the non-intermittent 3WC and for the sum-DoF of intermittent 3WCs, but adaptive encoding is necessary for the DoF region of intermittent 3WCs. Our work contributes to a better understanding of the fundamental limits of multi-way communication systems with intermittency and the impact of adaptation therein.

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.

Science.gov (United States)

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.

Science.gov (United States)

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

Social Regulation of Gene Expression in Threespine Sticklebacks.

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Anna K Greenwood

Full Text Available Identifying genes that are differentially expressed in response to social interactions is informative for understanding the molecular basis of social behavior. To address this question, we described changes in gene expression as a result of differences in the extent of social interactions. We housed threespine stickleback (Gasterosteus aculeatus females in either group conditions or individually for one week, then measured levels of gene expression in three brain regions using RNA-sequencing. We found that numerous genes in the hindbrain/cerebellum had altered expression in response to group or individual housing. However, relatively few genes were differentially expressed in either the diencephalon or telencephalon. The list of genes upregulated in fish from social groups included many genes related to neural development and cell adhesion as well as genes with functions in sensory signaling, stress, and social and reproductive behavior. The list of genes expressed at higher levels in individually-housed fish included several genes previously identified as regulated by social interactions in other animals. The identified genes are interesting targets for future research on the molecular mechanisms of normal social interactions.

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

Science.gov (United States)

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.

Three-body interactions and the Landau levels using Nikiforov ...

Indian Academy of Sciences (India)

In this article, the eigenvalues for the three-body interactions on the line and the Landau levels in the presence of topological defects have been regenerated by the Nikiforov–Uvarov (NU) method. Two exhaustive lists of such exactly solvable potentials are given. Keywords. Nikiforov–Uvarov (NU) method; three-body ...

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.

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

Science.gov (United States)

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…

Three invariant Hi-C interaction patterns: Applications to genome assembly.

Science.gov (United States)

Oddes, Sivan; Zelig, Aviv; Kaplan, Noam

2018-06-01

Assembly of reference-quality genomes from next-generation sequencing data is a key challenge in genomics. Recently, we and others have shown that Hi-C data can be used to address several outstanding challenges in the field of genome assembly. This principle has since been developed in academia and industry, and has been used in the assembly of several major genomes. In this paper, we explore the central principles underlying Hi-C-based assembly approaches, by quantitatively defining and characterizing three invariant Hi-C interaction patterns on which these approaches can build: Intrachromosomal interaction enrichment, distance-dependent interaction decay and local interaction smoothness. Specifically, we evaluate to what degree each invariant pattern holds on a single locus level in different species, cell types and Hi-C map resolutions. We find that these patterns are generally consistent across species and cell types but are affected by sequencing depth, and that matrix balancing improves consistency of loci with all three invariant patterns. Finally, we overview current Hi-C-based assembly approaches in light of these invariant patterns and demonstrate how local interaction smoothness can be used to easily detect scaffolding errors in extremely sparse Hi-C maps. We suggest that simultaneously considering all three invariant patterns may lead to better Hi-C-based genome assembly methods. Copyright © 2018 Elsevier Inc. All rights reserved.

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

Directory of Open Access Journals (Sweden)

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.

Science.gov (United States)

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.

Science.gov (United States)

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.

Cloning and Expression of Three New Azotobacter vinelandii Genes Closely Related to a Previously Described Gene Family Encoding Mannuronan C-5-Epimerases

OpenAIRE

Svanem, Britt Iren Glærum; Skjåk-Bræk, Gudmund; Ertesvåg, Helga; Valla, Svein

1999-01-01

The cloning and expression of a family of five modular-type mannuronan C-5-epimerase genes from Azotobacter vinelandii (algE1 to -5) has previously been reported. The corresponding proteins catalyze the Ca2+-dependent polymer-level epimerization of β-d-mannuronic acid to α-l-guluronic acid (G) in the commercially important polysaccharide alginate. Here we report the identification of three additional structurally similar genes, designated algE6, algE7, and algY. All three genes were sequenced...

A Novel WT1 Gene Mutation in a Three-Generation Family with Progressive Isolated Focal Segmental Glomerulosclerosis

Science.gov (United States)

Caridi, Gianluca; Malaventura, Cristina; Dagnino, Monica; Leonardi, Emanuela; Artifoni, Lina; Ghiggeri, Gian Marco; Tosatto, Silvio C.E.; Murer, Luisa

2010-01-01

Background and objectives: Wilms tumor-suppressor gene-1 (WT1) plays a key role in kidney development and function. WT1 mutations usually occur in exons 8 and 9 and are associated with Denys-Drash, or in intron 9 and are associated with Frasier syndrome. However, overlapping clinical and molecular features have been reported. Few familial cases have been described, with intrafamilial variability. Sporadic cases of WT1 mutations in isolated diffuse mesangial sclerosis or focal segmental glomerulosclerosis have also been reported. Design, setting, participants, & measurements: Molecular analysis of WT1 exons 8 and 9 was carried out in five members on three generations of a family with late-onset isolated proteinuria. The effect of the detected amino acid substitution on WT1 protein's structure was studied by bioinformatics tools. Results: Three family members reached end-stage renal disease in full adulthood. None had genital abnormalities or Wilms tumor. Histologic analysis in two subjects revealed focal segmental glomerulosclerosis. The novel sequence variant c.1208G>A in WT1 exon 9 was identified in all of the affected members of the family. Conclusions: The lack of Wilms tumor or other related phenotypes suggests the expansion of WT1 gene analysis in patients with focal segmental glomerulosclerosis, regardless of age or presence of typical Denys-Drash or Frasier syndrome clinical features. Structural analysis of the mutated protein revealed that the mutation hampers zinc finger-DNA interactions, impairing target gene transcription. This finding opens up new issues about WT1 function in the maintenance of the complex gene network that regulates normal podocyte function. PMID:20150449

Density-dependent effective baryon–baryon interaction from chiral three-baryon forces

Energy Technology Data Exchange (ETDEWEB)

Petschauer, Stefan, E-mail: stefan.petschauer@ph.tum.de [Physik Department, Technische Universität München, D-85747 Garching (Germany); Haidenbauer, Johann [Institute for Advanced Simulation, Institut für Kernphysik and Jülich Center for Hadron Physics, Forschungszentrum Jülich, D-52425 Jülich (Germany); Kaiser, Norbert [Physik Department, Technische Universität München, D-85747 Garching (Germany); Meißner, Ulf-G. [Institute for Advanced Simulation, Institut für Kernphysik and Jülich Center for Hadron Physics, Forschungszentrum Jülich, D-52425 Jülich (Germany); Helmholtz-Institut für Strahlen- und Kernphysik, Universität Bonn, D-53115 Bonn (Germany); Bethe Center for Theoretical Physics, Universität Bonn, D-53115 Bonn (Germany); Weise, Wolfram [Physik Department, Technische Universität München, D-85747 Garching (Germany)

2017-01-15

A density-dependent effective potential for the baryon–baryon interaction in the presence of the (hyper)nuclear medium is constructed, based on the leading (irreducible) three-baryon forces derived within SU(3) chiral effective field theory. We evaluate the contributions from three classes: contact terms, one-pion exchange and two-pion exchange. In the strangeness-zero sector we recover the known result for the in-medium nucleon–nucleon interaction. Explicit expressions for the ΛN in-medium potential in (asymmetric) nuclear matter are presented. Our results are suitable for implementation into calculations of (hyper)nuclear matter. In order to estimate the low-energy constants of the leading three-baryon forces we introduce the decuplet baryons as explicit degrees of freedom and construct the relevant terms in the minimal non-relativistic Lagrangian. With these, the constants are estimated through decuplet saturation. Utilizing this approximation we provide numerical results for the effect of the three-body force in symmetric nuclear matter and pure neutron matter on the ΛN interaction. A moderate repulsion that increases with density is found in comparison to the free ΛN interaction.

Extinction maps toward the Milky Way bulge: Two-dimensional and three-dimensional tests with apogee

Energy Technology Data Exchange (ETDEWEB)

Schultheis, M. [Université de Nice Sophia-Antipolis, CNRS, Observatoire de Côte d' Azur, Laboratoire Lagrange, 06304 Nice Cedex 4 (France); Zasowski, G. [Department of Physics and Astronomy, Johns Hopkins University, Baltimore, MD 21218 (United States); Allende Prieto, C. [Instituto de Astrofísica de Canarias, Calle Vía Láctea s/n, E-38205 La Laguna, Tenerife (Spain); Anders, F.; Chiappini, C. [Leibniz-Institut für Astrophysik Potsdam (AIP), D-14482 Potsdam (Germany); Beaton, R. L.; García Pérez, A. E.; Majewski, S. R. [Department of Astronomy, University of Virginia, Charlottesville, VA 22904 (United States); Beers, T. C. [National Optical Astronomy Observatory, Tucson, AZ 85719 (United States); Bizyaev, D. [Apache Point Observatory, Sunspot, NM 88349 (United States); Frinchaboy, P. M. [Department of Physics and Astronomy, Texas Christian University, TCU Box 298840, Fort Worth, TX 76129 (United States); Ge, J. [Astronomy Department, University of Florida, Gainesville, FL 32611 (United States); Hearty, F.; Schneider, D. P. [Department of Astronomy and Astrophysics, The Pennsylvania State University, University Park, PA 16802 (United States); Holtzman, J. [New Mexico State University, Las Cruces, NM 88003 (United States); Muna, D. [Department of Astronomy, The Ohio State University, Columbus, OH 43210 (United States); Nidever, D. [Department of Astronomy, University of Michigan, Ann Arbor, MI 48109 (United States); Shetrone, M., E-mail: mathias.schultheis@oca.eu, E-mail: gail.zasowski@gmail.com [McDonald Observatory, The University of Texas at Austin, Austin, TX 78712 (United States)

2014-07-01

Galactic interstellar extinction maps are powerful and necessary tools for Milky Way structure and stellar population analyses, particularly toward the heavily reddened bulge and in the midplane. However, due to the difficulty of obtaining reliable extinction measures and distances for a large number of stars that are independent of these maps, tests of their accuracy and systematics have been limited. Our goal is to assess a variety of photometric stellar extinction estimates, including both two-dimensional and three-dimensional extinction maps, using independent extinction measures based on a large spectroscopic sample of stars toward the Milky Way bulge. We employ stellar atmospheric parameters derived from high-resolution H-band Apache Point Observatory Galactic Evolution Experiment (APOGEE) spectra, combined with theoretical stellar isochrones, to calculate line-of-sight extinction and distances for a sample of more than 2400 giants toward the Milky Way bulge. We compare these extinction values to those predicted by individual near-IR and near+mid-IR stellar colors, two-dimensional bulge extinction maps, and three-dimensional extinction maps. The long baseline, near+mid-IR stellar colors are, on average, the most accurate predictors of the APOGEE extinction estimates, and the two-dimensional and three-dimensional extinction maps derived from different stellar populations along different sightlines show varying degrees of reliability. We present the results of all of the comparisons and discuss reasons for the observed discrepancies. We also demonstrate how the particular stellar atmospheric models adopted can have a strong impact on this type of analysis, and discuss related caveats.

Extinction maps toward the Milky Way bulge: Two-dimensional and three-dimensional tests with apogee

International Nuclear Information System (INIS)

Schultheis, M.; Zasowski, G.; Allende Prieto, C.; Anders, F.; Chiappini, C.; Beaton, R. L.; García Pérez, A. E.; Majewski, S. R.; Beers, T. C.; Bizyaev, D.; Frinchaboy, P. M.; Ge, J.; Hearty, F.; Schneider, D. P.; Holtzman, J.; Muna, D.; Nidever, D.; Shetrone, M.

2014-01-01

Galactic interstellar extinction maps are powerful and necessary tools for Milky Way structure and stellar population analyses, particularly toward the heavily reddened bulge and in the midplane. However, due to the difficulty of obtaining reliable extinction measures and distances for a large number of stars that are independent of these maps, tests of their accuracy and systematics have been limited. Our goal is to assess a variety of photometric stellar extinction estimates, including both two-dimensional and three-dimensional extinction maps, using independent extinction measures based on a large spectroscopic sample of stars toward the Milky Way bulge. We employ stellar atmospheric parameters derived from high-resolution H-band Apache Point Observatory Galactic Evolution Experiment (APOGEE) spectra, combined with theoretical stellar isochrones, to calculate line-of-sight extinction and distances for a sample of more than 2400 giants toward the Milky Way bulge. We compare these extinction values to those predicted by individual near-IR and near+mid-IR stellar colors, two-dimensional bulge extinction maps, and three-dimensional extinction maps. The long baseline, near+mid-IR stellar colors are, on average, the most accurate predictors of the APOGEE extinction estimates, and the two-dimensional and three-dimensional extinction maps derived from different stellar populations along different sightlines show varying degrees of reliability. We present the results of all of the comparisons and discuss reasons for the observed discrepancies. We also demonstrate how the particular stellar atmospheric models adopted can have a strong impact on this type of analysis, and discuss related caveats.

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

Science.gov (United States)

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 ...

Science.gov (United States)

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...

How do walkers behave when crossing the way of a mobile robot that replicates human interaction rules?

Science.gov (United States)

Vassallo, Christian; Olivier, Anne-Hélène; Souères, Philippe; Crétual, Armel; Stasse, Olivier; Pettré, Julien

2018-02-01

Previous studies showed the existence of implicit interaction rules shared by human walkers when crossing each other. Especially, each walker contributes to the collision avoidance task and the crossing order, as set at the beginning, is preserved along the interaction. This order determines the adaptation strategy: the first arrived increases his/her advance by slightly accelerating and changing his/her heading, whereas the second one slows down and moves in the opposite direction. In this study, we analyzed the behavior of human walkers crossing the trajectory of a mobile robot that was programmed to reproduce this human avoidance strategy. In contrast with a previous study, which showed that humans mostly prefer to give the way to a non-reactive robot, we observed similar behaviors between human-human avoidance and human-robot avoidance when the robot replicates the human interaction rules. We discuss this result in relation with the importance of controlling robots in a human-like way in order to ease their cohabitation with humans. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Three-Dimensional Structural Aspects of Protein–Polysaccharide Interactions

Directory of Open Access Journals (Sweden)

Masamichi Nagae

2014-03-01

Full Text Available Linear polysaccharides are typically composed of repeating mono- or disaccharide units and are ubiquitous among living organisms. Polysaccharide diversity arises from chain-length variation, branching, and additional modifications. Structural diversity is associated with various physiological functions, which are often regulated by cognate polysaccharide-binding proteins. Proteins that interact with linear polysaccharides have been identified or developed, such as galectins and polysaccharide-specific antibodies, respectively. Currently, data is accumulating on the three-dimensional structure of polysaccharide-binding proteins. These proteins are classified into two types: exo-type and endo-type. The former group specifically interacts with the terminal units of polysaccharides, whereas the latter with internal units. In this review, we describe the structural aspects of exo-type and endo-type protein-polysaccharide interactions. Further, we discuss the structural basis for affinity and specificity enhancement in the face of inherently weak binding interactions.

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

A facile way to realize exchange coupling interaction in hard/soft magnetic composites

Energy Technology Data Exchange (ETDEWEB)

Li, Dongyun, E-mail: lidongyun@cjlu.edu.cn [College of Materials Science and Engineering, China Jiliang University, Hangzhou 310018 (China); Wang, Fan [College of Materials Science and Engineering, China Jiliang University, Hangzhou 310018 (China); Xia, Ailin, E-mail: alxia@126.com [Anhui Key Laboratory of Metal Materials and Processing, School of Materials Science and Engineering, Anhui University of Technology, Maanshan 243032 (China); Zhang, Lijiao [School of Science, Hebei University of Science and Technology, Shijiazhuang 050018 (China); Li, Tingting; Jin, Chuangui; Liu, Xianguo [Anhui Key Laboratory of Metal Materials and Processing, School of Materials Science and Engineering, Anhui University of Technology, Maanshan 243032 (China)

2016-11-01

SrFe{sub 12}O{sub 19}/CoFe{sub 2}O{sub 4} and SrFe{sub 12}O{sub 19}/Fe–B hard/soft magnetic composites were obtained by using powders synthesized via a hydrothermal and a molten salt method, respectively. The exchange coupling interaction was found to exist in the composites after a facile grinding according to the results of magnetic hysteresis loops and irreversible sloping recoil loops. It can be found that different grinding time affects their magnetic properties slightly. Our study proves that the conditions of realizing exchange coupling interaction may not be so stringent. - Highlights: • SrM/CFO and SrM/Fe–B with exchange coupling were obtained via a grinding way. • Different grinding time affects their magnetic properties slightly. • The conditions of realizing exchange coupling may not be so stringent.

Web Delivery of Interactive Laboratories: Comparison of Three Authoring Tools

Science.gov (United States)

Silbar, Richard R.

2002-04-01

It is well-known that the more a student interacts with a subject, the better he or she will learn it. This is particularly true in technical subjects. One way to do this is to have computer-based "laboratories" in which the student manipulates objects on the screen with keyboard or mouse and then sees the outcome of those actions. One example of such a laboratory we have built, using Macromedia's Authorware, deals with addition of two vectors in the geometric approach. The problem with Authorware, however, is that, if one wants to deliver the training over the Web, that requires the download and installation of a big plug-in. Therefore, as an experiment, I built clones of the Vector Addition Laboratory using Macromedia's Director or Flash, each of which have smaller plug-ins which are often already installed in the user's browser. The Director and Flash versions are similar to (but definitely not the same as) the Authorware version. This talk goes into these differences and demonstrates the techniques used. You can view the three examples on-line at http://www.whistlesoft.com/ silbar.

Design Science in Human-Computer Interaction: A Model and Three Examples

Science.gov (United States)

Prestopnik, Nathan R.

2013-01-01

Humanity has entered an era where computing technology is virtually ubiquitous. From websites and mobile devices to computers embedded in appliances on our kitchen counters and automobiles parked in our driveways, information and communication technologies (ICTs) and IT artifacts are fundamentally changing the ways we interact with our world.…

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

Directory of Open Access Journals (Sweden)

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

Gene inactivation in the plant pathogen Glomerella cingulata: three strategies for the disruption of the pectin lyase gene pnlA.

Science.gov (United States)

Bowen, J K; Templeton, M D; Sharrock, K R; Crowhurst, R N; Rikkerink, E H

1995-01-20

The feasibility of performing routine transformation-mediated mutagenesis in Glomerella cingulata was analysed by adopting three one-step gene disruption strategies targeted at the pectin lyase gene pnlA. The efficiencies of disruption following transformation with gene replacement- or gene truncation-disruption vectors were compared. To effect replacement-disruption, G. cingulata was transformed with a vector carrying DNA from the pnlA locus in which the majority of the coding sequence had been replaced by the gene for hygromycin B resistance. Two of the five transformants investigated contained an inactivated pnlA gene (pnlA-); both also contained ectopically integrated vector sequences. The efficacy of gene disruption by transformation with two gene truncation-disruption vectors was also assessed. Both vectors carried at 5' and 3' truncated copy of the pnlA coding sequence, adjacent to the gene for hygromycin B resistance. The promoter sequences controlling the selectable marker differed in the two vectors. In one vector the homologous G. cingulata gpdA promoter controlled hygromycin B phosphotransferase expression (homologous truncation vector), whereas in the second vector promoter elements were from the Aspergillus nidulans gpdA gene (heterologous truncation vector). Following transformation with the homologous truncation vector, nine transformants were analysed by Southern hybridisation; no transformants contained a disrupted pnlA gene. Of nineteen heterologous truncation vector transformants, three contained a disrupted pnlA gene; Southern analysis revealed single integrations of vector sequence at pnlA in two of these transformants. pnlA mRNA was not detected by Northern hybridisation in pnlA- transformants. pnlA- transformants failed to produce a PNLA protein with a pI identical to one normally detected in wild-type isolates by silver and activity staining of isoelectric focussing gels. Pathogenesis on Capsicum and apple was unaffected by disruption of

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)

A High-Efficiency 100-W GaN Three-Way Doherty Amplifier for Base-Station Applications

NARCIS (Netherlands)

Pelk, M.J.; Neo, W.C.E.; Gajadharsing, J.R.; Pengelly, R.S.; De Vreede, L.C.N.

2008-01-01

A three-way Doherty 100-W GaN base-station power amplifier at 2.14 GHz is presented. Simple, but accurate design equations for the output power combiner of the amplifier are introduced. Mixed-signal techniques are utilized for uncompromised control of the amplifier stages to optimize efficiency, as

Designing for Interactional Empowerment

OpenAIRE

Ståhl, Anna

2014-01-01

This thesis further defines how to reach Interactional Empowerment through design for users. Interactional Empowerment is an interaction design program within the general area of affective interaction, focusing on the users’ abil­ity to reflect, express themselves and engage in profound meaning-making. This has been explored through design of three systems eMoto, Affective Di­ary and Affective Health, which all mirror users’ emotions or bodily reactions in interaction in some way. From these ...