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Sample records for multiple interacting genes

  1. The interaction between smoking and HLA genes in multiple sclerosis

    DEFF Research Database (Denmark)

    Hedström, Anna Karin; Katsoulis, Michail; Hössjer, Ola

    2017-01-01

    Interactions between environment and genetics may contribute to multiple sclerosis (MS) development. We investigated whether the previously observed interaction between smoking and HLA genotype in the Swedish population could be replicated, refined and extended to include other populations. We us...

  2. 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.

  3. Plant interactions with multiple insect herbivores: from community to genes

    NARCIS (Netherlands)

    Stam, J.M.; Kroes, A.; Li, Y.; Gols, R.; Loon, van J.J.A.; Poelman, E.H.; Dicke, M.

    2014-01-01

    Every plant is a member of a complex insect community that consists of tens to hundreds of species that belong to different trophic levels. The dynamics of this community are critically influenced by the plant, which mediates interactions between community members that can occur on the plant

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

    DEFF Research Database (Denmark)

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

    2017-01-01

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

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

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

    2008-01-01

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

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

    Science.gov (United States)

    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

  7. 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.

  8. 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/.

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

    Science.gov (United States)

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

    2015-09-01

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

  10. 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.

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

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    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

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

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    Rex, Maria; Hilton, Emma; Old, Robert

    2002-03-01

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

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

    Science.gov (United States)

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

    2009-01-01

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

  14. I just ran a thousand analyses: benefits of multiple testing in understanding equivocal evidence on gene-environment interactions.

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    Vera E Heininga

    Full Text Available In psychiatric genetics research, the volume of ambivalent findings on gene-environment interactions (G x E is growing at an accelerating pace. In response to the surging suspicions of systematic distortion, we challenge the notion of chance capitalization as a possible contributor. Beyond qualifying multiple testing as a mere methodological issue that, if uncorrected, leads to chance capitalization, we advance towards illustrating the potential benefits of multiple tests in understanding equivocal evidence in genetics literature.We focused on the interaction between the serotonin-transporter-linked promotor region (5-HTTLPR and childhood adversities with regard to depression. After testing 2160 interactions with all relevant measures available within the Dutch population study of adolescents TRAILS, we calculated percentages of significant (p < .05 effects for several subsets of regressions. Using chance capitalization (i.e. overall significance rate of 5% alpha and randomly distributed findings as a competing hypothesis, we expected more significant effects in the subsets of regressions involving: 1 interview-based instead of questionnaire-based measures; 2 abuse instead of milder childhood adversities; and 3 early instead of later adversities. Furthermore, we expected equal significance percentages across 4 male and female subsamples, and 5 various genotypic models of 5-HTTLPR.We found differences in the percentages of significant interactions among the subsets of analyses, including those regarding sex-specific subsamples and genetic modeling, but often in unexpected directions. Overall, the percentage of significant interactions was 7.9% which is only slightly above the 5% that might be expected based on chance.Taken together, multiple testing provides a novel approach to better understand equivocal evidence on G x E, showing that methodological differences across studies are a likely reason for heterogeneity in findings - but chance

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

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    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

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

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    Rajani Rai

    2015-11-01

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

  17. Mining gene expression data of multiple sclerosis.

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    Pi Guo

    Full Text Available Microarray produces a large amount of gene expression data, containing various biological implications. The challenge is to detect a panel of discriminative genes associated with disease. This study proposed a robust classification model for gene selection using gene expression data, and performed an analysis to identify disease-related genes using multiple sclerosis as an example.Gene expression profiles based on the transcriptome of peripheral blood mononuclear cells from a total of 44 samples from 26 multiple sclerosis patients and 18 individuals with other neurological diseases (control were analyzed. Feature selection algorithms including Support Vector Machine based on Recursive Feature Elimination, Receiver Operating Characteristic Curve, and Boruta algorithms were jointly performed to select candidate genes associating with multiple sclerosis. Multiple classification models categorized samples into two different groups based on the identified genes. Models' performance was evaluated using cross-validation methods, and an optimal classifier for gene selection was determined.An overlapping feature set was identified consisting of 8 genes that were differentially expressed between the two phenotype groups. The genes were significantly associated with the pathways of apoptosis and cytokine-cytokine receptor interaction. TNFSF10 was significantly associated with multiple sclerosis. A Support Vector Machine model was established based on the featured genes and gave a practical accuracy of ∼86%. This binary classification model also outperformed the other models in terms of Sensitivity, Specificity and F1 score.The combined analytical framework integrating feature ranking algorithms and Support Vector Machine model could be used for selecting genes for other diseases.

  18. Multiple Taf subunits of TFIID interact with Ino2 activation domains and contribute to expression of genes required for yeast phospholipid biosynthesis.

    Science.gov (United States)

    Hintze, Stefan; Engelhardt, Maike; van Diepen, Laura; Witt, Eric; Schüller, Hans-Joachim

    2017-12-01

    Expression of phospholipid biosynthetic genes in yeast requires activator protein Ino2 which can bind to the UAS element inositol/choline-responsive element (ICRE) and trigger activation of target genes, using two separate transcriptional activation domains, TAD1 and TAD2. However, it is still unknown which cofactors mediate activation by TADs of Ino2. Here, we show that multiple subunits of basal transcription factor TFIID (TBP-associated factors Taf1, Taf4, Taf6, Taf10 and Taf12) are able to interact in vitro with activation domains of Ino2. Interaction was no longer observed with activation-defective variants of TAD1. We were able to identify two nonoverlapping regions in the N-terminus of Taf1 (aa 1-100 and aa 182-250) each of which could interact with TAD1 of Ino2 as well as with TAD4 of activator Adr1. Specific missense mutations within Taf1 domain aa 182-250 affecting basic and hydrophobic residues prevented interaction with wild-type TAD1 and caused reduced expression of INO1. Using chromatin immunoprecipitation we demonstrated Ino2-dependent recruitment of Taf1 and Taf6 to ICRE-containing promoters INO1 and CHO2. Transcriptional derepression of INO1 was no longer possible with temperature-sensitive taf1 and taf6 mutants cultivated under nonpermissive conditions. This result supports the hypothesis of Taf-dependent expression of structural genes activated by Ino2. © 2017 John Wiley & Sons Ltd.

  19. 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

  20. Multiple Parton Interactions in ALICE

    CERN Multimedia

    CERN. Geneva

    2013-01-01

    We will present in detail the measurement of the charged particle multiplicity dependence of per-trigger pair yields in azimuthal direction induced by low-energetic di-jets produced in proton-proton collisions. Using two-particle angular correlations with low transverse momentum thresholds, jet properties are measured on a statistical basis down to the lowest possible jet energies. The analysis can give information about the contribution from multiple parton interactions to particle production. Moreover, the results allow to optimize the parametrization of the jet fragmentation in phenomenological mode...

  1. Multiple sclerosis and herpesvirus interaction

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    Guilherme Sciascia do Olival

    2013-09-01

    Full Text Available Multiple sclerosis is the most common autoimmune inflammatory demyelinating disease of the central nervous system, and its etiology is believed to have both genetic and environmental components. Several viruses have already been implicated as triggers and there are several studies that implicate members of the Herpesviridae family in the pathogenesis of MS. The most important characteristic of these viruses is that they have periods of latency and exacerbations within their biological sanctuary, the central nervous system. The Epstein-Barr, cytomegalovirus, human herpesvirus 6 and human herpesvirus 7 viruses are the members that are most studied as being possible triggers of multiple sclerosis. According to evidence in the literature, the herpesvirus family is strongly involved in the pathogenesis of this disease, but it is unlikely that they are the only component responsible for its development. There are probably multiple triggers and more studies are necessary to investigate and define these interactions.

  2. Multiplicities in high energy interactions

    International Nuclear Information System (INIS)

    Derrick, M.

    1984-01-01

    Charged particle multiplicities in hadronic collision have been measured for all energies up to √s = 540 GeV in the center of mass. Similar measurements in e + e - annihilation cover the much smaller range - up to √s = 40 GeV. Data are also available from deep inelastic neutrino scattering up to √s approx. 10 GeV. The experiments measure the mean charged multiplicity , the rapidity density at y = O, and the distributions in prong number. The mean number of photons associated with the events can be used to measure the π 0 and eta 0 multiplicities. Some information is also available on the charged pion, kaon, and nucleon fractions as well as the K 0 and Λ 0 rates and for the higher energy data, the identically equal fraction. We review this data and consider the implications of extrapolations to SSC energies. 13 references

  3. Dynamic Response Genes in CD4+ T Cells Reveal a Network of Interactive Proteins that Classifies Disease Activity in Multiple Sclerosis

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    Sandra Hellberg

    2016-09-01

    Full Text Available Multiple sclerosis (MS is a chronic inflammatory disease of the CNS and has a varying disease course as well as variable response to treatment. Biomarkers may therefore aid personalized treatment. We tested whether in vitro activation of MS patient-derived CD4+ T cells could reveal potential biomarkers. The dynamic gene expression response to activation was dysregulated in patient-derived CD4+ T cells. By integrating our findings with genome-wide association studies, we constructed a highly connected MS gene module, disclosing cell activation and chemotaxis as central components. Changes in several module genes were associated with differences in protein levels, which were measurable in cerebrospinal fluid and were used to classify patients from control individuals. In addition, these measurements could predict disease activity after 2 years and distinguish low and high responders to treatment in two additional, independent cohorts. While further validation is needed in larger cohorts prior to clinical implementation, we have uncovered a set of potentially promising biomarkers.

  4. 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.

  5. Class II HLA interactions modulate genetic risk for multiple sclerosis

    DEFF Research Database (Denmark)

    Moutsianas, Loukas; Jostins, Luke; Beecham, Ashley H

    2015-01-01

    Association studies have greatly refined the understanding of how variation within the human leukocyte antigen (HLA) genes influences risk of multiple sclerosis. However, the extent to which major effects are modulated by interactions is poorly characterized. We analyzed high-density SNP data on 17...

  6. A Study of Multiplicities in Hadronic Interactions

    Energy Technology Data Exchange (ETDEWEB)

    Estrada Tristan, Nora Patricia; /San Luis Potosi U.

    2006-02-01

    Using data from the SELEX (Fermilab E781) experiment obtained with a minimum-bias trigger, we study multiplicity and angular distributions of secondary particles produced in interactions in the experimental targets. We observe interactions of {Sigma}{sup -}, proton, {pi}{sup -}, and {pi}{sup +}, at beam momenta between 250 GeV/c and 650 GeV/c, in copper, polyethylene, graphite, and beryllium targets. We show that the multiplicity and angular distributions for meson and baryon beams at the same momentum are identical. We also show that the mean multiplicity increases with beam momentum, and presents only small variations with the target material.

  7. Predictability of Genetic Interactions from Functional Gene Modules

    Directory of Open Access Journals (Sweden)

    Jonathan H. Young

    2017-02-01

    Full Text Available Characterizing genetic interactions is crucial to understanding cellular and organismal response to gene-level perturbations. Such knowledge can inform the selection of candidate disease therapy targets, yet experimentally determining whether genes interact is technically nontrivial and time-consuming. High-fidelity prediction of different classes of genetic interactions in multiple organisms would substantially alleviate this experimental burden. Under the hypothesis that functionally related genes tend to share common genetic interaction partners, we evaluate a computational approach to predict genetic interactions in Homo sapiens, Drosophila melanogaster, and Saccharomyces cerevisiae. By leveraging knowledge of functional relationships between genes, we cross-validate predictions on known genetic interactions and observe high predictive power of multiple classes of genetic interactions in all three organisms. Additionally, our method suggests high-confidence candidate interaction pairs that can be directly experimentally tested. A web application is provided for users to query genes for predicted novel genetic interaction partners. Finally, by subsampling the known yeast genetic interaction network, we found that novel genetic interactions are predictable even when knowledge of currently known interactions is minimal.

  8. Fractional populations in multiple gene inheritance.

    Science.gov (United States)

    Chung, Myung-Hoon; Kim, Chul Koo; Nahm, Kyun

    2003-01-22

    With complete knowledge of the human genome sequence, one of the most interesting tasks remaining is to understand the functions of individual genes and how they communicate. Using the information about genes (locus, allele, mutation rate, fitness, etc.), we attempt to explain population demographic data. This population evolution study could complement and enhance biologists' understanding about genes. We present a general approach to study population genetics in complex situations. In the present approach, multiple allele inheritance, multiple loci inheritance, natural selection and mutations are allowed simultaneously in order to consider a more realistic situation. A simulation program is presented so that readers can readily carry out studies with their own parameters. It is shown that the multiplicity of the loci greatly affects the demographic results of fractional population ratios. Furthermore, the study indicates that some high infant mortality rates due to congenital anomalies can be attributed to multiple loci inheritance. The simulation program can be downloaded from http://won.hongik.ac.kr/~mhchung/index_files/yapop.htm. In order to run this program, one needs Visual Studio.NET platform, which can be downloaded from http://msdn.microsoft.com/netframework/downloads/default.asp.

  9. 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.

  10. 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.

  11. The ALMT Gene Family Performs Multiple Functions in Plants

    Directory of Open Access Journals (Sweden)

    Jie Liu

    2018-02-01

    Full Text Available The aluminium activated malate transporter (ALMT gene family is named after the first member of the family identified in wheat (Triticum aestivum L.. The product of this gene controls resistance to aluminium (Al toxicity. ALMT genes encode transmembrane proteins that function as anion channels and perform multiple functions involving the transport of organic anions (e.g., carboxylates and inorganic anions in cells. They share a PF11744 domain and are classified in the Fusaric acid resistance protein-like superfamily, CL0307. The proteins typically have five to seven transmembrane regions in the N-terminal half and a long hydrophillic C-terminal tail but predictions of secondary structure vary. Although widely spread in plants, relatively little information is available on the roles performed by other members of this family. In this review, we summarized functions of ALMT gene families, including Al resistance, stomatal function, mineral nutrition, microbe interactions, fruit acidity, light response and seed development.

  12. Dosage changes of a segment at 17p13.1 lead to intellectual disability and microcephaly as a result of complex genetic interaction of multiple genes

    DEFF Research Database (Denmark)

    Carvalho, Claudia M B; Vasanth, Shivakumar; Shinawi, Marwan

    2014-01-01

    with copy-number variants (CNVs) on 17p13.1 for whom we performed detailed clinical and molecular studies. Breakpoint mapping and retrospective analysis of published cases refined the smallest region of overlap (SRO) for microcephaly to a genomic interval containing nine genes. Dissection of this phenotype...

  13. Multiple genes encode the major surface glycoprotein of Pneumocystis carinii

    DEFF Research Database (Denmark)

    Kovacs, J A; Powell, F; Edman, J C

    1993-01-01

    hydrophobic region at the carboxyl terminus. The presence of multiple related msg genes encoding the major surface glycoprotein of P. carinii suggests that antigenic variation is a possible mechanism for evading host defenses. Further characterization of this family of genes should allow the development......The major surface antigen of Pneumocystis carinii, a life-threatening opportunistic pathogen in human immunodeficiency virus-infected patients, is an abundant glycoprotein that functions in host-organism interactions. A monoclonal antibody to this antigen is protective in animals, and thus...... blot studies using chromosomal or restricted DNA, the major surface glycoproteins are the products of a multicopy family of genes. The predicted protein has an M(r) of approximately 123,000, is relatively rich in cysteine residues (5.5%) that are very strongly conserved, and contains a well conserved...

  14. Simultaneous gene finding in multiple genomes.

    Science.gov (United States)

    König, Stefanie; Romoth, Lars W; Gerischer, Lizzy; Stanke, Mario

    2016-11-15

    As the tree of life is populated with sequenced genomes ever more densely, the new challenge is the accurate and consistent annotation of entire clades of genomes. We address this problem with a new approach to comparative gene finding that takes a multiple genome alignment of closely related species and simultaneously predicts the location and structure of protein-coding genes in all input genomes, thereby exploiting negative selection and sequence conservation. The model prefers potential gene structures in the different genomes that are in agreement with each other, or-if not-where the exon gains and losses are plausible given the species tree. We formulate the multi-species gene finding problem as a binary labeling problem on a graph. The resulting optimization problem is NP hard, but can be efficiently approximated using a subgradient-based dual decomposition approach. The proposed method was tested on whole-genome alignments of 12 vertebrate and 12 Drosophila species. The accuracy was evaluated for human, mouse and Drosophila melanogaster and compared to competing methods. Results suggest that our method is well-suited for annotation of (a large number of) genomes of closely related species within a clade, in particular, when RNA-Seq data are available for many of the genomes. The transfer of existing annotations from one genome to another via the genome alignment is more accurate than previous approaches that are based on protein-spliced alignments, when the genomes are at close to medium distances. The method is implemented in C ++ as part of Augustus and available open source at http://bioinf.uni-greifswald.de/augustus/ CONTACT: stefaniekoenig@ymail.com or mario.stanke@uni-greifswald.deSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  15. Stress Effects on Multiple Memory System Interactions

    Science.gov (United States)

    Ness, Deborah; Calabrese, Pasquale

    2016-01-01

    Extensive behavioural, pharmacological, and neurological research reports stress effects on mammalian memory processes. While stress effects on memory quantity have been known for decades, the influence of stress on multiple memory systems and their distinct contributions to the learning process have only recently been described. In this paper, after summarizing the fundamental biological aspects of stress/emotional arousal and recapitulating functionally and anatomically distinct memory systems, we review recent animal and human studies exploring the effects of stress on multiple memory systems. Apart from discussing the interaction between distinct memory systems in stressful situations, we will also outline the fundamental role of the amygdala in mediating such stress effects. Additionally, based on the methods applied in the herein discussed studies, we will discuss how memory translates into behaviour. PMID:27034845

  16. Multiple parton interactions at the LHC

    CERN Document Server

    Gaunt, Jonathan Richard

    2018-01-01

    Many high-energy collider experiments (including the current Large Hadron Collider at CERN) involve the collision of hadrons. Hadrons are composite particles consisting of partons (quarks and gluons), and this means that in any hadron–hadron collision there will typically be multiple collisions of the constituents — i.e. multiple parton interactions (MPI). Understanding the nature of the MPI is important in terms of searching for new physics in the products of the scatters, and also in its own right to gain a greater understanding of hadron structure. This book aims at providing a pedagogical introduction and a comprehensive review of different research lines linked by an involvement of MPI phenomena. It is written by pioneers as well as young leading scientists, and reviews both experimental findings and theoretical developments, discussing also the remaining open issues.

  17. Stress Effects on Multiple Memory System Interactions

    Directory of Open Access Journals (Sweden)

    Deborah Ness

    2016-01-01

    Full Text Available Extensive behavioural, pharmacological, and neurological research reports stress effects on mammalian memory processes. While stress effects on memory quantity have been known for decades, the influence of stress on multiple memory systems and their distinct contributions to the learning process have only recently been described. In this paper, after summarizing the fundamental biological aspects of stress/emotional arousal and recapitulating functionally and anatomically distinct memory systems, we review recent animal and human studies exploring the effects of stress on multiple memory systems. Apart from discussing the interaction between distinct memory systems in stressful situations, we will also outline the fundamental role of the amygdala in mediating such stress effects. Additionally, based on the methods applied in the herein discussed studies, we will discuss how memory translates into behaviour.

  18. Stress Effects on Multiple Memory System Interactions.

    Science.gov (United States)

    Ness, Deborah; Calabrese, Pasquale

    2016-01-01

    Extensive behavioural, pharmacological, and neurological research reports stress effects on mammalian memory processes. While stress effects on memory quantity have been known for decades, the influence of stress on multiple memory systems and their distinct contributions to the learning process have only recently been described. In this paper, after summarizing the fundamental biological aspects of stress/emotional arousal and recapitulating functionally and anatomically distinct memory systems, we review recent animal and human studies exploring the effects of stress on multiple memory systems. Apart from discussing the interaction between distinct memory systems in stressful situations, we will also outline the fundamental role of the amygdala in mediating such stress effects. Additionally, based on the methods applied in the herein discussed studies, we will discuss how memory translates into behaviour.

  19. Synchronization in networks with multiple interaction layers

    Science.gov (United States)

    del Genio, Charo I.; Gómez-Gardeñes, Jesús; Bonamassa, Ivan; Boccaletti, Stefano

    2016-01-01

    The structure of many real-world systems is best captured by networks consisting of several interaction layers. Understanding how a multilayered structure of connections affects the synchronization properties of dynamical systems evolving on top of it is a highly relevant endeavor in mathematics and physics and has potential applications in several socially relevant topics, such as power grid engineering and neural dynamics. We propose a general framework to assess the stability of the synchronized state in networks with multiple interaction layers, deriving a necessary condition that generalizes the master stability function approach. We validate our method by applying it to a network of Rössler oscillators with a double layer of interactions and show that highly rich phenomenology emerges from this. This includes cases where the stability of synchronization can be induced even if both layers would have individually induced unstable synchrony, an effect genuinely arising from the true multilayer structure of the interactions among the units in the network. PMID:28138540

  20. 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...

  1. 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.

  2. The Interaction Network Ontology-supported modeling and mining of complex interactions represented with multiple keywords in biomedical literature.

    Science.gov (United States)

    Özgür, Arzucan; Hur, Junguk; He, Yongqun

    2016-01-01

    The Interaction Network Ontology (INO) logically represents biological interactions, pathways, and networks. INO has been demonstrated to be valuable in providing a set of structured ontological terms and associated keywords to support literature mining of gene-gene interactions from biomedical literature. However, previous work using INO focused on single keyword matching, while many interactions are represented with two or more interaction keywords used in combination. This paper reports our extension of INO to include combinatory patterns of two or more literature mining keywords co-existing in one sentence to represent specific INO interaction classes. Such keyword combinations and related INO interaction type information could be automatically obtained via SPARQL queries, formatted in Excel format, and used in an INO-supported SciMiner, an in-house literature mining program. We studied the gene interaction sentences from the commonly used benchmark Learning Logic in Language (LLL) dataset and one internally generated vaccine-related dataset to identify and analyze interaction types containing multiple keywords. Patterns obtained from the dependency parse trees of the sentences were used to identify the interaction keywords that are related to each other and collectively represent an interaction type. The INO ontology currently has 575 terms including 202 terms under the interaction branch. The relations between the INO interaction types and associated keywords are represented using the INO annotation relations: 'has literature mining keywords' and 'has keyword dependency pattern'. The keyword dependency patterns were generated via running the Stanford Parser to obtain dependency relation types. Out of the 107 interactions in the LLL dataset represented with two-keyword interaction types, 86 were identified by using the direct dependency relations. The LLL dataset contained 34 gene regulation interaction types, each of which associated with multiple keywords. A

  3. 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.

  4. 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

  5. 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.

  6. A knowledge-driven interaction analysis reveals potential neurodegenerative mechanism of multiple sclerosis susceptibility.

    Science.gov (United States)

    Bush, W S; McCauley, J L; DeJager, P L; Dudek, S M; Hafler, D A; Gibson, R A; Matthews, P M; Kappos, L; Naegelin, Y; Polman, C H; Hauser, S L; Oksenberg, J; Haines, J L; Ritchie, M D

    2011-07-01

    Gene-gene interactions are proposed as an important component of the genetic architecture of complex diseases, and are just beginning to be evaluated in the context of genome-wide association studies (GWAS). In addition to detecting epistasis, a benefit to interaction analysis is that it also increases power to detect weak main effects. We conducted a knowledge-driven interaction analysis of a GWAS of 931 multiple sclerosis (MS) trios to discover gene-gene interactions within established biological contexts. We identify heterogeneous signals, including a gene-gene interaction between CHRM3 (muscarinic cholinergic receptor 3) and MYLK (myosin light-chain kinase) (joint P=0.0002), an interaction between two phospholipase C-β isoforms, PLCβ1 and PLCβ4 (joint P=0.0098), and a modest interaction between ACTN1 (actinin alpha 1) and MYH9 (myosin heavy chain 9) (joint P=0.0326), all localized to calcium-signaled cytoskeletal regulation. Furthermore, we discover a main effect (joint P=5.2E-5) previously unidentified by single-locus analysis within another related gene, SCIN (scinderin), a calcium-binding cytoskeleton regulatory protein. This work illustrates that knowledge-driven interaction analysis of GWAS data is a feasible approach to identify new genetic effects. The results of this study are among the first gene-gene interactions and non-immune susceptibility loci for MS. Further, the implicated genes cluster within inter-related biological mechanisms that suggest a neurodegenerative component to MS.

  7. Coulomb interaction in multiple scattering theory

    International Nuclear Information System (INIS)

    Ray, L.; Hoffmann, G.W.; Thaler, R.M.

    1980-01-01

    The treatment of the Coulomb interaction in the multiple scattering theories of Kerman-McManus-Thaler and Watson is examined in detail. By neglecting virtual Coulomb excitations, the lowest order Coulomb term in the Watson optical potential is shown to be a convolution of the point Coulomb interaction with the distributed nuclear charge, while the equivalent Kerman-McManus-Thaler Coulomb potential is obtained from an averaged, single-particle Coulombic T matrix. The Kerman-McManus-Thaler Coulomb potential is expressed as the Watson Coulomb term plus additional Coulomb-nuclear and Coulomb-Coulomb cross terms, and the omission of the extra terms in usual Kerman-McManus-Thaler applications leads to negative infinite total reaction cross section predictions and incorrect pure Coulomb scattering limits. Approximations are presented which eliminate these anomalies. Using the two-potential formula, the full projectile-nucleus T matrix is separated into two terms, one resulting from the distributed nuclear charge and the other being a Coulomb distorted nuclear T matrix. It is shown that the error resulting from the omission of the Kerman-McManus-Thaler Coulomb terms is effectively removed when the pure Coulomb T matrix in Kerman-McManus-Thaler is replaced by the analogous quantity in the Watson approach. Using the various approximations, theoretical angular distributions are obtained for 800 MeV p+ 208 Pb elastic scattering and compared with experimental data

  8. 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.

  9. Methods for monitoring multiple gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Berka, Randy [Davis, CA; Bachkirova, Elena [Davis, CA; Rey, Michael [Davis, CA

    2012-05-01

    The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

  10. Methods for monitoring multiple gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Berka, Randy; Bachkirova, Elena; Rey, Michael

    2013-10-01

    The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

  11. Class II HLA interactions modulate genetic risk for multiple sclerosis

    Science.gov (United States)

    Dilthey, Alexander T; Xifara, Dionysia K; Ban, Maria; Shah, Tejas S; Patsopoulos, Nikolaos A; Alfredsson, Lars; Anderson, Carl A; Attfield, Katherine E; Baranzini, Sergio E; Barrett, Jeffrey; Binder, Thomas M C; Booth, David; Buck, Dorothea; Celius, Elisabeth G; Cotsapas, Chris; D’Alfonso, Sandra; Dendrou, Calliope A; Donnelly, Peter; Dubois, Bénédicte; Fontaine, Bertrand; Fugger, Lars; Goris, An; Gourraud, Pierre-Antoine; Graetz, Christiane; Hemmer, Bernhard; Hillert, Jan; Kockum, Ingrid; Leslie, Stephen; Lill, Christina M; Martinelli-Boneschi, Filippo; Oksenberg, Jorge R; Olsson, Tomas; Oturai, Annette; Saarela, Janna; Søndergaard, Helle Bach; Spurkland, Anne; Taylor, Bruce; Winkelmann, Juliane; Zipp, Frauke; Haines, Jonathan L; Pericak-Vance, Margaret A; Spencer, Chris C A; Stewart, Graeme; Hafler, David A; Ivinson, Adrian J; Harbo, Hanne F; Hauser, Stephen L; De Jager, Philip L; Compston, Alastair; McCauley, Jacob L; Sawcer, Stephen; McVean, Gil

    2016-01-01

    Association studies have greatly refined the understanding of how variation within the human leukocyte antigen (HLA) genes influences risk of multiple sclerosis. However, the extent to which major effects are modulated by interactions is poorly characterized. We analyzed high-density SNP data on 17,465 cases and 30,385 controls from 11 cohorts of European ancestry, in combination with imputation of classical HLA alleles, to build a high-resolution map of HLA genetic risk and assess the evidence for interactions involving classical HLA alleles. Among new and previously identified class II risk alleles (HLA-DRB1*15:01, HLA-DRB1*13:03, HLA-DRB1*03:01, HLA-DRB1*08:01 and HLA-DQB1*03:02) and class I protective alleles (HLA-A*02:01, HLA-B*44:02, HLA-B*38:01 and HLA-B*55:01), we find evidence for two interactions involving pairs of class II alleles: HLA-DQA1*01:01–HLA-DRB1*15:01 and HLA-DQB1*03:01–HLA-DQB1*03:02. We find no evidence for interactions between classical HLA alleles and non-HLA risk-associated variants and estimate a minimal effect of polygenic epistasis in modulating major risk alleles. PMID:26343388

  12. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    Ueki Masao

    2012-05-01

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

  15. 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

  16. Gene-Lifestyle Interactions in Obesity.

    Science.gov (United States)

    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.

  17. 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 

  18. Spin-orbit interaction in multiple quantum wells

    Energy Technology Data Exchange (ETDEWEB)

    Hao, Ya-Fei, E-mail: haoyafei@zjnu.cn [Physics Department, Zhejiang Normal University, Zhejiang 321004 (China)

    2015-01-07

    In this paper, we investigate how the structure of multiple quantum wells affects spin-orbit interactions. To increase the interface-related Rashba spin splitting and the strength of the interface-related Rashba spin-orbit interaction, we designed three kinds of multiple quantum wells. We demonstrate that the structure of the multiple quantum wells strongly affected the interface-related Rashba spin-orbit interaction, increasing the interface-related Rashba spin splitting to up to 26% larger in multiple quantum wells than in a stepped quantum well. We also show that the cubic Dresselhaus spin-orbit interaction similarly influenced the spin relaxation time of multiple quantum wells and that of a stepped quantum well. The increase in the interface-related Rashba spin splitting originates from the relationship between interface-related Rashba spin splitting and electron probability density. Our results suggest that multiple quantum wells can be good candidates for spintronic devices.

  19. Spin-orbit interaction in multiple quantum wells

    International Nuclear Information System (INIS)

    Hao, Ya-Fei

    2015-01-01

    In this paper, we investigate how the structure of multiple quantum wells affects spin-orbit interactions. To increase the interface-related Rashba spin splitting and the strength of the interface-related Rashba spin-orbit interaction, we designed three kinds of multiple quantum wells. We demonstrate that the structure of the multiple quantum wells strongly affected the interface-related Rashba spin-orbit interaction, increasing the interface-related Rashba spin splitting to up to 26% larger in multiple quantum wells than in a stepped quantum well. We also show that the cubic Dresselhaus spin-orbit interaction similarly influenced the spin relaxation time of multiple quantum wells and that of a stepped quantum well. The increase in the interface-related Rashba spin splitting originates from the relationship between interface-related Rashba spin splitting and electron probability density. Our results suggest that multiple quantum wells can be good candidates for spintronic devices

  20. 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...

  1. An evolvable oestrogen receptor activity sensor: development of a modular system for integrating multiple genes into the yeast genome

    NARCIS (Netherlands)

    Fox, J.E.; Bridgham, J.T.; Bovee, T.F.H.; Thornton, J.W.

    2007-01-01

    To study a gene interaction network, we developed a gene-targeting strategy that allows efficient and stable genomic integration of multiple genetic constructs at distinct target loci in the yeast genome. This gene-targeting strategy uses a modular plasmid with a recyclable selectable marker and a

  2. A gene pathway analysis highlights the role of cellular adhesion molecules in multiple sclerosis susceptibility

    DEFF Research Database (Denmark)

    Damotte, V; Guillot-Noel, L; Patsopoulos, N A

    2014-01-01

    adhesion molecule (CAMs) biological pathway using Cytoscape software. This network is a strong candidate, as it is involved in the crossing of the blood-brain barrier by the T cells, an early event in MS pathophysiology, and is used as an efficient therapeutic target. We drew up a list of 76 genes...... in interaction with other genes as a group. Pathway analysis is an alternative way to highlight such group of genes. Using SNP association P-values from eight multiple sclerosis (MS) GWAS data sets, we performed a candidate pathway analysis for MS susceptibility by considering genes interacting in the cell...... belonging to the CAM network. We highlighted 64 networks enriched with CAM genes with low P-values. Filtering by a percentage of CAM genes up to 50% and rejecting enriched signals mainly driven by transcription factors, we highlighted five networks associated with MS susceptibility. One of them, constituted...

  3. Stress Effects on Multiple Memory System Interactions

    OpenAIRE

    Ness, Deborah; Calabrese, Pasquale

    2016-01-01

    Extensive behavioural, pharmacological, and neurological research reports stress effects on mammalian memory processes. While stress effects on memory quantity have been known for decades, the influence of stress on multiple memory systems and their distinct contributions to the learning process have only recently been described. In this paper, after summarizing the fundamental biological aspects of stress/emotional arousal and recapitulating functionally and anatomically distinct memory syst...

  4. [The multiple interactions between infertility and sexuality].

    Science.gov (United States)

    Mimoun, S

    1993-03-01

    After investigating into literature and clinical experience, we shall line out in this study 4 types of interactions between sexuality and infertility: sexual causes to feminine (vaginism, with and without heavy dyspareunia) or masculine (impotency, ante-portas ejaculation, anejaculation, dysejaculation), infertility; influence of tests and of treatments for infertility on sexual life; influence of infertility on sexuality focusing on the various ambiguous feelings (of culpability, inferiority, aggressivity, passivity); and last, the psychological and sexual interactions with medical assisted procreation, reinforcing the sexual separation of man and woman if the body is considered a machine. Psychosomatic guidance of the couple during these steps (with reassurance as the being helped conception) will allow maintaining on removing sexual attraction.

  5. A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk

    Directory of Open Access Journals (Sweden)

    Lewei Duan

    2013-01-01

    Full Text Available A variety of methods have been proposed for studying the association of multiple genes thought to be involved in a common pathway for a particular disease. Here, we present an extension of a Bayesian hierarchical modeling strategy that allows for multiple SNPs within each gene, with external prior information at either the SNP or gene level. The model involves variable selection at the SNP level through latent indicator variables and Bayesian shrinkage at the gene level towards a prior mean vector and covariance matrix that depend on external information. The entire model is fitted using Markov chain Monte Carlo methods. Simulation studies show that the approach is capable of recovering many of the truly causal SNPs and genes, depending upon their frequency and size of their effects. The method is applied to data on 504 SNPs in 38 candidate genes involved in DNA damage response in the WECARE study of second breast cancers in relation to radiotherapy exposure.

  6. 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...

  7. Architecture for Multiple Interacting Robot Intelligences

    Science.gov (United States)

    Peters, Richard Alan, II (Inventor)

    2008-01-01

    An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a database associative memory (DBAM) that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

  8. 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.

  9. 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.

  10. Aberrant gene promoter methylation associated with sporadic multiple colorectal cancer.

    Directory of Open Access Journals (Sweden)

    Victoria Gonzalo

    Full Text Available BACKGROUND: Colorectal cancer (CRC multiplicity has been mainly related to polyposis and non-polyposis hereditary syndromes. In sporadic CRC, aberrant gene promoter methylation has been shown to play a key role in carcinogenesis, although little is known about its involvement in multiplicity. To assess the effect of methylation in tumor multiplicity in sporadic CRC, hypermethylation of key tumor suppressor genes was evaluated in patients with both multiple and solitary tumors, as a proof-of-concept of an underlying epigenetic defect. METHODOLOGY/PRINCIPAL FINDINGS: We examined a total of 47 synchronous/metachronous primary CRC from 41 patients, and 41 gender, age (5-year intervals and tumor location-paired patients with solitary tumors. Exclusion criteria were polyposis syndromes, Lynch syndrome and inflammatory bowel disease. DNA methylation at the promoter region of the MGMT, CDKN2A, SFRP1, TMEFF2, HS3ST2 (3OST2, RASSF1A and GATA4 genes was evaluated by quantitative methylation specific PCR in both tumor and corresponding normal appearing colorectal mucosa samples. Overall, patients with multiple lesions exhibited a higher degree of methylation in tumor samples than those with solitary tumors regarding all evaluated genes. After adjusting for age and gender, binomial logistic regression analysis identified methylation of MGMT2 (OR, 1.48; 95% CI, 1.10 to 1.97; p = 0.008 and RASSF1A (OR, 2.04; 95% CI, 1.01 to 4.13; p = 0.047 as variables independently associated with tumor multiplicity, being the risk related to methylation of any of these two genes 4.57 (95% CI, 1.53 to 13.61; p = 0.006. Moreover, in six patients in whom both tumors were available, we found a correlation in the methylation levels of MGMT2 (r = 0.64, p = 0.17, SFRP1 (r = 0.83, 0.06, HPP1 (r = 0.64, p = 0.17, 3OST2 (r = 0.83, p = 0.06 and GATA4 (r = 0.6, p = 0.24. Methylation in normal appearing colorectal mucosa from patients with multiple and solitary CRC showed no relevant

  11. Entropy and Multifractality for the Myeloma Multiple TET 2 Gene

    Directory of Open Access Journals (Sweden)

    Carlo Cattani

    2012-01-01

    Full Text Available The nucleotide and amino-acid distributions are studied for two variants of mRNA of gene that codes for a protein which is involved in multiple myeloid. Some patches and symmetries are singled out, thus, showing some distinctions between the two variants. Fractal dimensions and entropy are discussed as well.

  12. 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.

  13. Gene-particulate matter-health interactions

    International Nuclear Information System (INIS)

    Kleeberger, Steven R.; Ohtsuka, Yoshinori

    2005-01-01

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

  14. 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.

  15. Pediatric Multiple Sclerosis: Genes, Environment, and a Comprehensive Therapeutic Approach.

    Science.gov (United States)

    Cappa, Ryan; Theroux, Liana; Brenton, J Nicholas

    2017-10-01

    Pediatric multiple sclerosis is an increasingly recognized and studied disorder that accounts for 3% to 10% of all patients with multiple sclerosis. The risk for pediatric multiple sclerosis is thought to reflect a complex interplay between environmental and genetic risk factors. Environmental exposures, including sunlight (ultraviolet radiation, vitamin D levels), infections (Epstein-Barr virus), passive smoking, and obesity, have been identified as potential risk factors in youth. Genetic predisposition contributes to the risk of multiple sclerosis, and the major histocompatibility complex on chromosome 6 makes the single largest contribution to susceptibility to multiple sclerosis. With the use of large-scale genome-wide association studies, other non-major histocompatibility complex alleles have been identified as independent risk factors for the disease. The bridge between environment and genes likely lies in the study of epigenetic processes, which are environmentally-influenced mechanisms through which gene expression may be modified. This article will review these topics to provide a framework for discussion of a comprehensive approach to counseling and ultimately treating the pediatric patient with multiple sclerosis. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. Gene expression profiling reveals multiple toxicity endpoints induced by hepatotoxicants

    Energy Technology Data Exchange (ETDEWEB)

    Huang Qihong; Jin Xidong; Gaillard, Elias T.; Knight, Brian L.; Pack, Franklin D.; Stoltz, James H.; Jayadev, Supriya; Blanchard, Kerry T

    2004-05-18

    Microarray technology continues to gain increased acceptance in the drug development process, particularly at the stage of toxicology and safety assessment. In the current study, microarrays were used to investigate gene expression changes associated with hepatotoxicity, the most commonly reported clinical liability with pharmaceutical agents. Acetaminophen, methotrexate, methapyrilene, furan and phenytoin were used as benchmark compounds capable of inducing specific but different types of hepatotoxicity. The goal of the work was to define gene expression profiles capable of distinguishing the different subtypes of hepatotoxicity. Sprague-Dawley rats were orally dosed with acetaminophen (single dose, 4500 mg/kg for 6, 24 and 72 h), methotrexate (1 mg/kg per day for 1, 7 and 14 days), methapyrilene (100 mg/kg per day for 3 and 7 days), furan (40 mg/kg per day for 1, 3, 7 and 14 days) or phenytoin (300 mg/kg per day for 14 days). Hepatic gene expression was assessed using toxicology-specific gene arrays containing 684 target genes or expressed sequence tags (ESTs). Principal component analysis (PCA) of gene expression data was able to provide a clear distinction of each compound, suggesting that gene expression data can be used to discern different hepatotoxic agents and toxicity endpoints. Gene expression data were applied to the multiplicity-adjusted permutation test and significantly changed genes were categorized and correlated to hepatotoxic endpoints. Repression of enzymes involved in lipid oxidation (acyl-CoA dehydrogenase, medium chain, enoyl CoA hydratase, very long-chain acyl-CoA synthetase) were associated with microvesicular lipidosis. Likewise, subsets of genes associated with hepatotocellular necrosis, inflammation, hepatitis, bile duct hyperplasia and fibrosis have been identified. The current study illustrates that expression profiling can be used to: (1) distinguish different hepatotoxic endpoints; (2) predict the development of toxic endpoints; and

  17. Evolutionary Dynamics of Tumor-Stroma Interactions in Multiple Myeloma.

    Directory of Open Access Journals (Sweden)

    Javad Salimi Sartakhti

    Full Text Available Cancer cells and stromal cells cooperate by exchanging diffusible factors that sustain tumor growth, a form of frequency-dependent selection that can be studied in the framework of evolutionary game theory. In the case of multiple myeloma, three types of cells (malignant plasma cells, osteoblasts and osteoclasts exchange growth factors with different effects, and tumor-stroma interactions have been analysed using a model of cooperation with pairwise interactions. Here we show that a model in which growth factors have autocrine and paracrine effects on multiple cells, a more realistic assumption for tumor-stroma interactions, leads to different results, with implications for disease progression and treatment. In particular, the model reveals that reducing the number of malignant plasma cells below a critical threshold can lead to their extinction and thus to restore a healthy balance between osteoclast and osteoblast, a result in line with current therapies against multiple myeloma.

  18. Evidence for multiple stressor interactions and effects on coral reefs.

    Science.gov (United States)

    Ban, Stephen S; Graham, Nicholas A J; Connolly, Sean R

    2014-03-01

    Concern is growing about the potential effects of interacting multiple stressors, especially as the global climate changes. We provide a comprehensive review of multiple stressor interactions in coral reef ecosystems, which are widely considered to be one of the most sensitive ecosystems to global change. First, we synthesized coral reef studies that examined interactions of two or more stressors, highlighting stressor interactions (where one stressor directly influences another) and potentially synergistic effects on response variables (where two stressors interact to produce an effect that is greater than purely additive). For stressor-stressor interactions, we found 176 studies that examined at least 2 of the 13 stressors of interest. Applying network analysis to analyze relationships between stressors, we found that pathogens were exacerbated by more costressors than any other stressor, with ca. 78% of studies reporting an enhancing effect by another stressor. Sedimentation, storms, and water temperature directly affected the largest number of other stressors. Pathogens, nutrients, and crown-of-thorns starfish were the most-influenced stressors. We found 187 studies that examined the effects of two or more stressors on a third dependent variable. The interaction of irradiance and temperature on corals has been the subject of more research (62 studies, 33% of the total) than any other combination of stressors, with many studies reporting a synergistic effect on coral symbiont photosynthetic performance (n = 19). Second, we performed a quantitative meta-analysis of existing literature on this most-studied interaction (irradiance and temperature). We found that the mean effect size of combined treatments was statistically indistinguishable from a purely additive interaction, although it should be noted that the sample size was relatively small (n = 26). Overall, although in aggregate a large body of literature examines stressor effects on coral reefs and coral

  19. Multiple parton interactions in photoproduction at HERA/H1

    Energy Technology Data Exchange (ETDEWEB)

    Magro, Lluis Marti

    2009-02-15

    Photoproduction data of HERA-I are analysed by requiring dijets with transverse momenta of at least 5 GeV. The two jets define in azimuth a towards region (leading jet), an away region (usually the 2nd jet) and transverse regions between them. The charged particle and jet with low transverse momentum multiplicity, so called minijets, are measured in these regions as a function of the variables x{sup obs}{sub {gamma}} and P{sup Jet{sub 1T}} (leading jet). The measurement is compared to predictions including parton showers and matrix elements at leading order in {alpha}{sub s}. Some predictions include contributions from multiple parton interactions and use different parton evolution equations. It was found that existing MC programs do not fully describe the measurements but the description can be improved by including multiple parton interactions. (orig.)

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

    Directory of Open Access Journals (Sweden)

    Onay Venus

    2007-08-01

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

  1. THE MULTIPLE CHOICE PROBLEM WITH INTERACTIONS BETWEEN CRITERIA

    Directory of Open Access Journals (Sweden)

    Luiz Flavio Autran Monteiro Gomes

    2015-12-01

    Full Text Available ABSTRACT An important problem in Multi-Criteria Decision Analysis arises when one must select at least two alternatives at the same time. This can be denoted as a multiple choice problem. In other words, instead of evaluating each of the alternatives separately, they must be combined into groups of n alternatives, where n = 2. When the multiple choice problem must be solved under multiple criteria, the result is a multi-criteria, multiple choice problem. In this paper, it is shown through examples how this problemcan be tackled on a bipolar scale. The Choquet integral is used in this paper to take care of interactions between criteria. A numerical application example is conducted using data from SEBRAE-RJ, a non-profit private organization that has the mission of promoting competitiveness, sustainable developmentand entrepreneurship in the state of Rio de Janeiro, Brazil. The paper closes with suggestions for future research.

  2. Mean multiplicity of secondary particles in hadron-nuclear interactions

    International Nuclear Information System (INIS)

    Alaverdyan, G.B.; Pak, A.S.

    1980-01-01

    The mean multiplicity of secondary particles in hA interactions is examined in the framework of the multiplex scattering theory. The dependence of the secondary particle multiplicity coefficient Rsub(6)=anti nsub(hA)/anti nsub(hN) (where anti nsub(hA) and anti nsub(hN) are mean multiplicities of secondary relativistic particles in hA and hN interactions, respectively) on the energy and type of incident particles and atomic number of a target nucleus is analysed. It is shown that predictions of the leading particle cascade model are in satisfactory agreement with the experimental data if the uncertainties of the inelasticity in hN interactions are taken into account. The value Rsub(A) weakly depends both on the incident particle energy and the form of parametrization anti nsub(hN)(E). Allowance of energy losses fluctuation of leading particle results in the Rsub(A) value decrease. From the model of leading particles it does not follow that Rsub(a) strictly depends on the type of incident particles at the fixed value of mean number of collisions. But quantitative values of Rsub(A) for different types of particles and at one value of anti ν, (i.e. at properly chosen value) coincide. The value of Rsub(A) is profoundly dependent on the values of inelasticity factor in hN interactions

  3. Multiplicity distributions in high-energy neutrino interactions

    International Nuclear Information System (INIS)

    Chapman, J.W.; Coffin, C.T.; Diamond, R.N.; French, H.; Louis, W.; Roe, B.P.; Seidl, A.A.; Vander Velde, J.C.; Berge, J.P.; Bogert, D.V.; DiBianca, F.A.; Cundy, D.C.; Dunaitsev, A.; Efremenko, V.; Ermolov, P.; Fowler, W.; Hanft, R.; Harigel, G.; Huson, F.R.; Kolganov, V.; Mukhin, A.; Nezrick, F.A.; Rjabov, Y.; Scott, W.G.; Smart, W.

    1976-01-01

    Results from the Fermilab 15-ft bubble chamber on the charged-particle multiplicity distributions produced in high-energy charged-current neutrino-proton interactions are presented. Comparisons are made to γp, ep, μp, and inclusive pp scattering. The mean hadronic multiplicity appears to depend only on the mass of the excited hadronic state, independent of the mode of excitation. A fit to the neutrino data gives = (1.09+-0.38) +(1.09+-0.03)lnW 2

  4. Interaction dynamics of multiple mobile robots with simple navigation strategies

    Science.gov (United States)

    Wang, P. K. C.

    1989-01-01

    The global dynamic behavior of multiple interacting autonomous mobile robots with simple navigation strategies is studied. Here, the effective spatial domain of each robot is taken to be a closed ball about its mass center. It is assumed that each robot has a specified cone of visibility such that interaction with other robots takes place only when they enter its visibility cone. Based on a particle model for the robots, various simple homing and collision-avoidance navigation strategies are derived. Then, an analysis of the dynamical behavior of the interacting robots in unbounded spatial domains is made. The article concludes with the results of computer simulations studies of two or more interacting robots.

  5. 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.

  6. Reference gene selection for quantitative gene expression studies during biological invasions: A test on multiple genes and tissues in a model ascidian Ciona savignyi.

    Science.gov (United States)

    Huang, Xuena; Gao, Yangchun; Jiang, Bei; Zhou, Zunchun; Zhan, Aibin

    2016-01-15

    As invasive species have successfully colonized a wide range of dramatically different local environments, they offer a good opportunity to study interactions between species and rapidly changing environments. Gene expression represents one of the primary and crucial mechanisms for rapid adaptation to local environments. Here, we aim to select reference genes for quantitative gene expression analysis based on quantitative Real-Time PCR (qRT-PCR) for a model invasive ascidian, Ciona savignyi. We analyzed the stability of ten candidate reference genes in three tissues (siphon, pharynx and intestine) under two key environmental stresses (temperature and salinity) in the marine realm based on three programs (geNorm, NormFinder and delta Ct method). Our results demonstrated only minor difference for stability rankings among the three methods. The use of different single reference gene might influence the data interpretation, while multiple reference genes could minimize possible errors. Therefore, reference gene combinations were recommended for different tissues - the optimal reference gene combination for siphon was RPS15 and RPL17 under temperature stress, and RPL17, UBQ and TubA under salinity treatment; for pharynx, TubB, TubA and RPL17 were the most stable genes under temperature stress, while TubB, TubA and UBQ were the best under salinity stress; for intestine, UBQ, RPS15 and RPL17 were the most reliable reference genes under both treatments. Our results suggest that the necessity of selection and test of reference genes for different tissues under varying environmental stresses. The results obtained here are expected to reveal mechanisms of gene expression-mediated invasion success using C. savignyi as a model species. Copyright © 2015 Elsevier B.V. All rights reserved.

  7. 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

  8. 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.

  9. Gene-Environment Interaction in Parkinson's Disease

    DEFF Research Database (Denmark)

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

    2016-01-01

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

  10. Interactive Visualization of DGA Data Based on Multiple Views

    Science.gov (United States)

    Geng, Yujie; Lin, Ying; Ma, Yan; Guo, Zhihong; Gu, Chao; Wang, Mingtao

    2017-01-01

    The commission and operation of dissolved gas analysis (DGA) online monitoring makes up for the weakness of traditional DGA method. However, volume and high-dimensional DGA data brings a huge challenge for monitoring and analysis. In this paper, we present a novel interactive visualization model of DGA data based on multiple views. This model imitates multi-angle analysis by combining parallel coordinates, scatter plot matrix and data table. By offering brush, collaborative filter and focus + context technology, this model provides a convenient and flexible interactive way to analyze and understand the DGA data.

  11. Pareto-Zipf law in growing systems with multiplicative interactions

    Science.gov (United States)

    Ohtsuki, Toshiya; Tanimoto, Satoshi; Sekiyama, Makoto; Fujihara, Akihiro; Yamamoto, Hiroshi

    2018-06-01

    Numerical simulations of multiplicatively interacting stochastic processes with weighted selections were conducted. A feedback mechanism to control the weight w of selections was proposed. It becomes evident that when w is moderately controlled around 0, such systems spontaneously exhibit the Pareto-Zipf distribution. The simulation results are universal in the sense that microscopic details, such as parameter values and the type of control and weight, are irrelevant. The central ingredient of the Pareto-Zipf law is argued to be the mild control of interactions.

  12. Horizontal acquisition of multiple mitochondrial genes from a parasitic plant followed by gene conversion with host mitochondrial genes

    Science.gov (United States)

    2010-01-01

    Background Horizontal gene transfer (HGT) is relatively common in plant mitochondrial genomes but the mechanisms, extent and consequences of transfer remain largely unknown. Previous results indicate that parasitic plants are often involved as either transfer donors or recipients, suggesting that direct contact between parasite and host facilitates genetic transfer among plants. Results In order to uncover the mechanistic details of plant-to-plant HGT, the extent and evolutionary fate of transfer was investigated between two groups: the parasitic genus Cuscuta and a small clade of Plantago species. A broad polymerase chain reaction (PCR) survey of mitochondrial genes revealed that at least three genes (atp1, atp6 and matR) were recently transferred from Cuscuta to Plantago. Quantitative PCR assays show that these three genes have a mitochondrial location in the one species line of Plantago examined. Patterns of sequence evolution suggest that these foreign genes degraded into pseudogenes shortly after transfer and reverse transcription (RT)-PCR analyses demonstrate that none are detectably transcribed. Three cases of gene conversion were detected between native and foreign copies of the atp1 gene. The identical phylogenetic distribution of the three foreign genes within Plantago and the retention of cytidines at ancestral positions of RNA editing indicate that these genes were probably acquired via a single, DNA-mediated transfer event. However, samplings of multiple individuals from two of the three species in the recipient Plantago clade revealed complex and perplexing phylogenetic discrepancies and patterns of sequence divergence for all three of the foreign genes. Conclusions This study reports the best evidence to date that multiple mitochondrial genes can be transferred via a single HGT event and that transfer occurred via a strictly DNA-level intermediate. The discovery of gene conversion between co-resident foreign and native mitochondrial copies suggests

  13. Horizontal acquisition of multiple mitochondrial genes from a parasitic plant followed by gene conversion with host mitochondrial genes

    Directory of Open Access Journals (Sweden)

    Hao Weilong

    2010-12-01

    Full Text Available Abstract Background Horizontal gene transfer (HGT is relatively common in plant mitochondrial genomes but the mechanisms, extent and consequences of transfer remain largely unknown. Previous results indicate that parasitic plants are often involved as either transfer donors or recipients, suggesting that direct contact between parasite and host facilitates genetic transfer among plants. Results In order to uncover the mechanistic details of plant-to-plant HGT, the extent and evolutionary fate of transfer was investigated between two groups: the parasitic genus Cuscuta and a small clade of Plantago species. A broad polymerase chain reaction (PCR survey of mitochondrial genes revealed that at least three genes (atp1, atp6 and matR were recently transferred from Cuscuta to Plantago. Quantitative PCR assays show that these three genes have a mitochondrial location in the one species line of Plantago examined. Patterns of sequence evolution suggest that these foreign genes degraded into pseudogenes shortly after transfer and reverse transcription (RT-PCR analyses demonstrate that none are detectably transcribed. Three cases of gene conversion were detected between native and foreign copies of the atp1 gene. The identical phylogenetic distribution of the three foreign genes within Plantago and the retention of cytidines at ancestral positions of RNA editing indicate that these genes were probably acquired via a single, DNA-mediated transfer event. However, samplings of multiple individuals from two of the three species in the recipient Plantago clade revealed complex and perplexing phylogenetic discrepancies and patterns of sequence divergence for all three of the foreign genes. Conclusions This study reports the best evidence to date that multiple mitochondrial genes can be transferred via a single HGT event and that transfer occurred via a strictly DNA-level intermediate. The discovery of gene conversion between co-resident foreign and native

  14. 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.

  15. Screening for interaction effects in gene expression data.

    Directory of Open Access Journals (Sweden)

    Peter J Castaldi

    Full Text Available Expression quantitative trait (eQTL studies are a powerful tool for identifying genetic variants that affect levels of messenger RNA. Since gene expression is controlled by a complex network of gene-regulating factors, one way to identify these factors is to search for interaction effects between genetic variants and mRNA levels of transcription factors (TFs and their respective target genes. However, identification of interaction effects in gene expression data pose a variety of methodological challenges, and it has become clear that such analyses should be conducted and interpreted with caution. Investigating the validity and interpretability of several interaction tests when screening for eQTL SNPs whose effect on the target gene expression is modified by the expression level of a transcription factor, we characterized two important methodological issues. First, we stress the scale-dependency of interaction effects and highlight that commonly applied transformation of gene expression data can induce or remove interactions, making interpretation of results more challenging. We then demonstrate that, in the setting of moderate to strong interaction effects on the order of what may be reasonably expected for eQTL studies, standard interaction screening can be biased due to heteroscedasticity induced by true interactions. Using simulation and real data analysis, we outline a set of reasonable minimum conditions and sample size requirements for reliable detection of variant-by-environment and variant-by-TF interactions using the heteroscedasticity consistent covariance-based approach.

  16. 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.

  17. Gene prediction using the Self-Organizing Map: automatic generation of multiple gene models.

    Science.gov (United States)

    Mahony, Shaun; McInerney, James O; Smith, Terry J; Golden, Aaron

    2004-03-05

    Many current gene prediction methods use only one model to represent protein-coding regions in a genome, and so are less likely to predict the location of genes that have an atypical sequence composition. It is likely that future improvements in gene finding will involve the development of methods that can adequately deal with intra-genomic compositional variation. This work explores a new approach to gene-prediction, based on the Self-Organizing Map, which has the ability to automatically identify multiple gene models within a genome. The current implementation, named RescueNet, uses relative synonymous codon usage as the indicator of protein-coding potential. While its raw accuracy rate can be less than other methods, RescueNet consistently identifies some genes that other methods do not, and should therefore be of interest to gene-prediction software developers and genome annotation teams alike. RescueNet is recommended for use in conjunction with, or as a complement to, other gene prediction methods.

  18. 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.

  19. 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.

  20. Adaptive Horizontal Gene Transfers between Multiple Cheese-Associated Fungi.

    Science.gov (United States)

    Ropars, Jeanne; Rodríguez de la Vega, Ricardo C; López-Villavicencio, Manuela; Gouzy, Jérôme; Sallet, Erika; Dumas, Émilie; Lacoste, Sandrine; Debuchy, Robert; Dupont, Joëlle; Branca, Antoine; Giraud, Tatiana

    2015-10-05

    Domestication is an excellent model for studies of adaptation because it involves recent and strong selection on a few, identified traits [1-5]. Few studies have focused on the domestication of fungi, with notable exceptions [6-11], despite their importance to bioindustry [12] and to a general understanding of adaptation in eukaryotes [5]. Penicillium fungi are ubiquitous molds among which two distantly related species have been independently selected for cheese making-P. roqueforti for blue cheeses like Roquefort and P. camemberti for soft cheeses like Camembert. The selected traits include morphology, aromatic profile, lipolytic and proteolytic activities, and ability to grow at low temperatures, in a matrix containing bacterial and fungal competitors [13-15]. By comparing the genomes of ten Penicillium species, we show that adaptation to cheese was associated with multiple recent horizontal transfers of large genomic regions carrying crucial metabolic genes. We identified seven horizontally transferred regions (HTRs) spanning more than 10 kb each, flanked by specific transposable elements, and displaying nearly 100% identity between distant Penicillium species. Two HTRs carried genes with functions involved in the utilization of cheese nutrients or competition and were found nearly identical in multiple strains and species of cheese-associated Penicillium fungi, indicating recent selective sweeps; they were experimentally associated with faster growth and greater competitiveness on cheese and contained genes highly expressed in the early stage of cheese maturation. These findings have industrial and food safety implications and improve our understanding of the processes of adaptation to rapid environmental changes. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  1. Obesity interacts with infectious mononucleosis in risk of multiple sclerosis.

    Science.gov (United States)

    Hedström, A K; Lima Bomfim, I; Hillert, J; Olsson, T; Alfredsson, L

    2015-03-01

    The possible interaction between adolescent obesity and past infectious mononucleosis (IM) was investigated with regard to multiple sclerosis (MS) risk. This report is based on two population-based case-control studies, one with incident cases (1780 cases, 3885 controls) and one with prevalent cases (4502 cases, 4039 controls). Subjects were categorized based on adolescent body mass index (BMI) and past IM and compared with regard to occurrence of MS by calculating odds ratios with 95% confidence intervals (CIs) employing logistic regression. A potential interaction between adolescent BMI and past IM was evaluated by calculating the attributable proportion due to interaction. Regardless of human leukocyte antigen (HLA) status, a substantial interaction was observed between adolescent obesity and past IM with regard to MS risk. The interaction was most evident when IM after the age of 10 was considered (attributable proportion due to interaction 0.8, 95% CI 0.6-1.0 in the incident study, and attributable proportion due to interaction 0.7, 95% CI 0.5-1.0 in the prevalent study). In the incident study, the odds ratio of MS was 14.7 (95% CI 5.9-36.6) amongst subjects with adolescent obesity and past IM after the age of 10, compared with subjects with none of these exposures. The corresponding odds ratio in the prevalent study was 13.2 (95% CI 5.2-33.6). An obese state both impacts the cellular immune response to infections and induces a state of chronic immune-mediated inflammation which may contribute to explain our finding of an interaction between adolescent BMI and past IM. Measures taken against adolescent obesity may thus be a preventive strategy against MS. © 2014 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.

  2. The interaction between multiple bubbles and the free surface

    International Nuclear Information System (INIS)

    Zhang Aman; Yao Xiongliang

    2008-01-01

    The flow is assumed to be potential, and a boundary integral method is used to solve the Laplace equation for the velocity potential to investigate the shape and the position of the bubble. A 3D code to study the bubble dynamics is developed, and the calculation results agree well with the experimental data. Numerical analyses are carried out for the interaction between multiple bubbles near the free surface including in-phase and out-of-phase bubbles. The calculation result shows that the bubble period increases with the decrease of the distance between bubble centres because of the depression effect between multiple bubbles. The depression has no relationship with the free surface and it is more apparent for out-of-phase bubbles. There are great differences in dynamic behaviour between the in-phase bubbles and the out-of-phase bubbles due to the depression effect. Furthermore, the interaction among eight bubbles is simulated with a three-dimensional model, and the evolving process and the relevant physical phenomena are presented. These phenomena can give a reference to the future work on the power of bubbles induced by multiple charges exploding simultaneously or continuously

  3. 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…

  4. 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.

  5. 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....

  6. Phase I metabolic genes and risk of lung cancer: multiple polymorphisms and mRNA expression.

    Directory of Open Access Journals (Sweden)

    Melissa Rotunno

    2009-05-01

    Full Text Available Polymorphisms in genes coding for enzymes that activate tobacco lung carcinogens may generate inter-individual differences in lung cancer risk. Previous studies had limited sample sizes, poor exposure characterization, and a few single nucleotide polymorphisms (SNPs tested in candidate genes. We analyzed 25 SNPs (some previously untested in 2101 primary lung cancer cases and 2120 population controls from the Environment And Genetics in Lung cancer Etiology (EAGLE study from six phase I metabolic genes, including cytochrome P450s, microsomal epoxide hydrolase, and myeloperoxidase. We evaluated the main genotype effects and genotype-smoking interactions in lung cancer risk overall and in the major histology subtypes. We tested the combined effect of multiple SNPs on lung cancer risk and on gene expression. Findings were prioritized based on significance thresholds and consistency across different analyses, and accounted for multiple testing and prior knowledge. Two haplotypes in EPHX1 were significantly associated with lung cancer risk in the overall population. In addition, CYP1B1 and CYP2A6 polymorphisms were inversely associated with adenocarcinoma and squamous cell carcinoma risk, respectively. Moreover, the association between CYP1A1 rs2606345 genotype and lung cancer was significantly modified by intensity of cigarette smoking, suggesting an underlying dose-response mechanism. Finally, increasing number of variants at CYP1A1/A2 genes revealed significant protection in never smokers and risk in ever smokers. Results were supported by differential gene expression in non-tumor lung tissue samples with down-regulation of CYP1A1 in never smokers and up-regulation in smokers from CYP1A1/A2 SNPs. The significant haplotype associations emphasize that the effect of multiple SNPs may be important despite null single SNP-associations, and warrants consideration in genome-wide association studies (GWAS. Our findings emphasize the necessity of post

  7. Detection of Gene Interactions Based on Syntactic Relations

    Directory of Open Access Journals (Sweden)

    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.

  8. 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.

  9. Parallel Beam-Beam Simulation Incorporating Multiple Bunches and Multiple Interaction Regions

    CERN Document Server

    Jones, F W; Pieloni, T

    2007-01-01

    The simulation code COMBI has been developed to enable the study of coherent beam-beam effects in the full collision scenario of the LHC, with multiple bunches interacting at multiple crossing points over many turns. The program structure and input are conceived in a general way which allows arbitrary numbers and placements of bunches and interaction points (IP's), together with procedural options for head-on and parasitic collisions (in the strong-strong sense), beam transport, statistics gathering, harmonic analysis, and periodic output of simulation data. The scale of this problem, once we go beyond the simplest case of a pair of bunches interacting once per turn, quickly escalates into the parallel computing arena, and herein we will describe the construction of an MPI-based version of COMBI able to utilize arbitrary numbers of processors to support efficient calculation of multi-bunch multi-IP interactions and transport. Implementing the parallel version did not require extensive disruption of the basic ...

  10. Interaction of multiple biomimetic antimicrobial polymers with model bacterial membranes

    Energy Technology Data Exchange (ETDEWEB)

    Baul, Upayan, E-mail: upayanb@imsc.res.in; Vemparala, Satyavani, E-mail: vani@imsc.res.in [The Institute of Mathematical Sciences, C.I.T. Campus, Taramani, Chennai 600113 (India); Kuroda, Kenichi, E-mail: kkuroda@umich.edu [Department of Biologic and Materials Sciences, University of Michigan School of Dentistry, Ann Arbor, Michigan 48109 (United States)

    2014-08-28

    Using atomistic molecular dynamics simulations, interaction of multiple synthetic random copolymers based on methacrylates on prototypical bacterial membranes is investigated. The simulations show that the cationic polymers form a micellar aggregate in water phase and the aggregate, when interacting with the bacterial membrane, induces clustering of oppositely charged anionic lipid molecules to form clusters and enhances ordering of lipid chains. The model bacterial membrane, consequently, develops lateral inhomogeneity in membrane thickness profile compared to polymer-free system. The individual polymers in the aggregate are released into the bacterial membrane in a phased manner and the simulations suggest that the most probable location of the partitioned polymers is near the 1-palmitoyl-2-oleoyl-phosphatidylglycerol (POPG) clusters. The partitioned polymers preferentially adopt facially amphiphilic conformations at lipid-water interface, despite lacking intrinsic secondary structures such as α-helix or β-sheet found in naturally occurring antimicrobial peptides.

  11. Electron-electron interaction in Multiple Quantum Wells

    Science.gov (United States)

    Zybert, M.; Marchewka, M.; Tomaka, G.; Sheregii, E. M.

    2012-07-01

    The complex investigation of the magneto-transport effects in structures containing multiple quantum well (MQWs) based on the GaAs/AlGaAs-heterostructures has been performed. The MQWs investigated have different electron densities in QWs. The parameters of 2DEG in MQWs were determined from the data of the Integer Quantum Hall Effect (IQHE) and Shubnikov-de Haas oscillations (SdH) observed at low temperatures (0.6-4.2 K). The method of calculation of the electron states energies in MQWs has been developed which is based on the splitting of these states due to the exchange interaction (SAS-splitting, see D. Płoch et al., Phys. Rev. B 79 (2009) 195434) including the screening of this interaction. The IQHE and SdH observed in these multilayer structures with the third degree of freedom for electrons are interpreted from this.

  12. Intervene: a tool for intersection and visualization of multiple gene or genomic region sets.

    Science.gov (United States)

    Khan, Aziz; Mathelier, Anthony

    2017-05-31

    A common task for scientists relies on comparing lists of genes or genomic regions derived from high-throughput sequencing experiments. While several tools exist to intersect and visualize sets of genes, similar tools dedicated to the visualization of genomic region sets are currently limited. To address this gap, we have developed the Intervene tool, which provides an easy and automated interface for the effective intersection and visualization of genomic region or list sets, thus facilitating their analysis and interpretation. Intervene contains three modules: venn to generate Venn diagrams of up to six sets, upset to generate UpSet plots of multiple sets, and pairwise to compute and visualize intersections of multiple sets as clustered heat maps. Intervene, and its interactive web ShinyApp companion, generate publication-quality figures for the interpretation of genomic region and list sets. Intervene and its web application companion provide an easy command line and an interactive web interface to compute intersections of multiple genomic and list sets. They have the capacity to plot intersections using easy-to-interpret visual approaches. Intervene is developed and designed to meet the needs of both computer scientists and biologists. The source code is freely available at https://bitbucket.org/CBGR/intervene , with the web application available at https://asntech.shinyapps.io/intervene .

  13. Multiple Syntrophic Interactions in a Terephthalate-Degrading Methanogenic Consortium

    Energy Technology Data Exchange (ETDEWEB)

    Lykidis, Athanasios; Chen, Chia-Lung; Tringe, Susannah G.; McHardy, Alice C.; Copeland, Alex 5; Kyrpides, Nikos C.; Hugenholtz, Philip; Liu, Wen-Tso

    2010-08-05

    Terephthalate (TA) is one of the top 50 chemicals produced worldwide. Its production results in a TA-containing wastewater that is treated by anaerobic processes through a poorly understood methanogenic syntrophy. Using metagenomics, we characterized the methanogenic consortium tinside a hyper-mesophilic (i.e., between mesophilic and thermophilic), TA-degrading bioreactor. We identified genes belonging to dominant Pelotomaculum species presumably involved in TA degradation through decarboxylation, dearomatization, and modified ?-oxidation to H{sub 2}/CO{sub 2} and acetate. These intermediates are converted to CH{sub 4}/CO{sub 2} by three novel hyper-mesophilic methanogens. Additional secondary syntrophic interactions were predicted in Thermotogae, Syntrophus and candidate phyla OP5 and WWE1 populations. The OP5 encodes genes capable of anaerobic autotrophic butyrate production and Thermotogae, Syntrophus and WWE1 have the genetic potential to oxidize butyrate to COsub 2}/H{sub 2} and acetate. These observations suggest that the TA-degrading consortium consists of additional syntrophic interactions beyond the standard H{sub 2}-producing syntroph ? methanogen partnership that may serve to improve community stability.

  14. PSP: rapid identification of orthologous coding genes under positive selection across multiple closely related prokaryotic genomes.

    Science.gov (United States)

    Su, Fei; Ou, Hong-Yu; Tao, Fei; Tang, Hongzhi; Xu, Ping

    2013-12-27

    With genomic sequences of many closely related bacterial strains made available by deep sequencing, it is now possible to investigate trends in prokaryotic microevolution. Positive selection is a sub-process of microevolution, in which a particular mutation is favored, causing the allele frequency to continuously shift in one direction. Wide scanning of prokaryotic genomes has shown that positive selection at the molecular level is much more frequent than expected. Genes with significant positive selection may play key roles in bacterial adaption to different environmental pressures. However, selection pressure analyses are computationally intensive and awkward to configure. Here we describe an open access web server, which is designated as PSP (Positive Selection analysis for Prokaryotic genomes) for performing evolutionary analysis on orthologous coding genes, specially designed for rapid comparison of dozens of closely related prokaryotic genomes. Remarkably, PSP facilitates functional exploration at the multiple levels by assignments and enrichments of KO, GO or COG terms. To illustrate this user-friendly tool, we analyzed Escherichia coli and Bacillus cereus genomes and found that several genes, which play key roles in human infection and antibiotic resistance, show significant evidence of positive selection. PSP is freely available to all users without any login requirement at: http://db-mml.sjtu.edu.cn/PSP/. PSP ultimately allows researchers to do genome-scale analysis for evolutionary selection across multiple prokaryotic genomes rapidly and easily, and identify the genes undergoing positive selection, which may play key roles in the interactions of host-pathogen and/or environmental adaptation.

  15. 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.

  16. Gene × physical activity interactions in obesity

    DEFF Research Database (Denmark)

    Ahmad, Shafqat; Rukh, Gull; Varga, Tibor V

    2013-01-01

    Numerous obesity loci have been identified using genome-wide association studies. A UK study indicated that physical activity may attenuate the cumulative effect of 12 of these loci, but replication studies are lacking. Therefore, we tested whether the aggregate effect of these loci is diminished...... in adults of European ancestry reporting high levels of physical activity. Twelve obesity-susceptibility loci were genotyped or imputed in 111,421 participants. A genetic risk score (GRS) was calculated by summing the BMI-associated alleles of each genetic variant. Physical activity was assessed using self...... combined using meta-analysis weighted by cohort sample size. The meta-analysis yielded a statistically significant GRS × physical activity interaction effect estimate (Pinteraction  = 0.015). However, a statistically significant interaction effect was only apparent in North American cohorts (n = 39...

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

    Directory of Open Access Journals (Sweden)

    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.

  18. Multiple Linear Regression for Reconstruction of Gene Regulatory Networks in Solving Cascade Error Problems

    Directory of Open Access Journals (Sweden)

    Faridah Hani Mohamed Salleh

    2017-01-01

    Full Text Available Gene regulatory network (GRN reconstruction is the process of identifying regulatory gene interactions from experimental data through computational analysis. One of the main reasons for the reduced performance of previous GRN methods had been inaccurate prediction of cascade motifs. Cascade error is defined as the wrong prediction of cascade motifs, where an indirect interaction is misinterpreted as a direct interaction. Despite the active research on various GRN prediction methods, the discussion on specific methods to solve problems related to cascade errors is still lacking. In fact, the experiments conducted by the past studies were not specifically geared towards proving the ability of GRN prediction methods in avoiding the occurrences of cascade errors. Hence, this research aims to propose Multiple Linear Regression (MLR to infer GRN from gene expression data and to avoid wrongly inferring of an indirect interaction (A → B → C as a direct interaction (A → C. Since the number of observations of the real experiment datasets was far less than the number of predictors, some predictors were eliminated by extracting the random subnetworks from global interaction networks via an established extraction method. In addition, the experiment was extended to assess the effectiveness of MLR in dealing with cascade error by using a novel experimental procedure that had been proposed in this work. The experiment revealed that the number of cascade errors had been very minimal. Apart from that, the Belsley collinearity test proved that multicollinearity did affect the datasets used in this experiment greatly. All the tested subnetworks obtained satisfactory results, with AUROC values above 0.5.

  19. Multiple Linear Regression for Reconstruction of Gene Regulatory Networks in Solving Cascade Error Problems.

    Science.gov (United States)

    Salleh, Faridah Hani Mohamed; Zainudin, Suhaila; Arif, Shereena M

    2017-01-01

    Gene regulatory network (GRN) reconstruction is the process of identifying regulatory gene interactions from experimental data through computational analysis. One of the main reasons for the reduced performance of previous GRN methods had been inaccurate prediction of cascade motifs. Cascade error is defined as the wrong prediction of cascade motifs, where an indirect interaction is misinterpreted as a direct interaction. Despite the active research on various GRN prediction methods, the discussion on specific methods to solve problems related to cascade errors is still lacking. In fact, the experiments conducted by the past studies were not specifically geared towards proving the ability of GRN prediction methods in avoiding the occurrences of cascade errors. Hence, this research aims to propose Multiple Linear Regression (MLR) to infer GRN from gene expression data and to avoid wrongly inferring of an indirect interaction (A → B → C) as a direct interaction (A → C). Since the number of observations of the real experiment datasets was far less than the number of predictors, some predictors were eliminated by extracting the random subnetworks from global interaction networks via an established extraction method. In addition, the experiment was extended to assess the effectiveness of MLR in dealing with cascade error by using a novel experimental procedure that had been proposed in this work. The experiment revealed that the number of cascade errors had been very minimal. Apart from that, the Belsley collinearity test proved that multicollinearity did affect the datasets used in this experiment greatly. All the tested subnetworks obtained satisfactory results, with AUROC values above 0.5.

  20. 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.

  1. Disease candidate gene identification and prioritization using protein interaction networks

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    Sivieng Jane

    2009-12-01

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

  3. Analysis and application of opinion model with multiple topic interactions.

    Science.gov (United States)

    Xiong, Fei; Liu, Yun; Wang, Liang; Wang, Ximeng

    2017-08-01

    To reveal heterogeneous behaviors of opinion evolution in different scenarios, we propose an opinion model with topic interactions. Individual opinions and topic features are represented by a multidimensional vector. We measure an agent's action towards a specific topic by the product of opinion and topic feature. When pairs of agents interact for a topic, their actions are introduced to opinion updates with bounded confidence. Simulation results show that a transition from a disordered state to a consensus state occurs at a critical point of the tolerance threshold, which depends on the opinion dimension. The critical point increases as the dimension of opinions increases. Multiple topics promote opinion interactions and lead to the formation of macroscopic opinion clusters. In addition, more topics accelerate the evolutionary process and weaken the effect of network topology. We use two sets of large-scale real data to evaluate the model, and the results prove its effectiveness in characterizing a real evolutionary process. Our model achieves high performance in individual action prediction and even outperforms state-of-the-art methods. Meanwhile, our model has much smaller computational complexity. This paper provides a demonstration for possible practical applications of theoretical opinion dynamics.

  4. 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.

  5. The evolution of multiple isotypic IgM heavy chain genes in the shark.

    Science.gov (United States)

    Lee, Victor; Huang, Jing Li; Lui, Ming Fai; Malecek, Karolina; Ohta, Yuko; Mooers, Arne; Hsu, Ellen

    2008-06-01

    The IgM H chain gene organization of cartilaginous fishes consists of 15-200 miniloci, each with a few gene segments (V(H)-D1-D2-J(H)) and one C gene. This is a gene arrangement ancestral to the complex IgH locus that exists in all other vertebrate classes. To understand the molecular evolution of this system, we studied the nurse shark, which has relatively fewer loci, and characterized the IgH isotypes for organization, functionality, and the somatic diversification mechanisms that act upon them. Gene numbers differ slightly between individuals ( approximately 15), but five active IgM subclasses are always present. Each gene undergoes rearrangement that is strictly confined within the minilocus; in B cells there is no interaction between adjacent loci located > or =120 kb apart. Without combinatorial events, the shark IgM H chain repertoire is based on junctional diversity and, subsequently, somatic hypermutation. We suggest that the significant contribution by junctional diversification reflects the selected novelty introduced by RAG in the early vertebrate ancestor, whereas combinatorial diversity coevolved with the complex translocon organization. Moreover, unlike other cartilaginous fishes, there are no germline-joined VDJ at any nurse shark mu locus, and we suggest that such genes, when functional, are species-specific and may have specialized roles. With an entire complement of IgM genes available for the first time, phylogenetic analyses were performed to examine how the multiple Ig loci evolved. We found that all domains changed at comparable rates, but V(H) appears to be under strong positive selection for increased amino acid sequence diversity, and surprisingly, so does Cmicro2.

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

    Directory of Open Access Journals (Sweden)

    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.

  7. 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.

  8. Pareto evolution of gene networks: an algorithm to optimize multiple fitness objectives

    International Nuclear Information System (INIS)

    Warmflash, Aryeh; Siggia, Eric D; Francois, Paul

    2012-01-01

    The computational evolution of gene networks functions like a forward genetic screen to generate, without preconceptions, all networks that can be assembled from a defined list of parts to implement a given function. Frequently networks are subject to multiple design criteria that cannot all be optimized simultaneously. To explore how these tradeoffs interact with evolution, we implement Pareto optimization in the context of gene network evolution. In response to a temporal pulse of a signal, we evolve networks whose output turns on slowly after the pulse begins, and shuts down rapidly when the pulse terminates. The best performing networks under our conditions do not fall into categories such as feed forward and negative feedback that also encode the input–output relation we used for selection. Pareto evolution can more efficiently search the space of networks than optimization based on a single ad hoc combination of the design criteria. (paper)

  9. Pareto evolution of gene networks: an algorithm to optimize multiple fitness objectives.

    Science.gov (United States)

    Warmflash, Aryeh; Francois, Paul; Siggia, Eric D

    2012-10-01

    The computational evolution of gene networks functions like a forward genetic screen to generate, without preconceptions, all networks that can be assembled from a defined list of parts to implement a given function. Frequently networks are subject to multiple design criteria that cannot all be optimized simultaneously. To explore how these tradeoffs interact with evolution, we implement Pareto optimization in the context of gene network evolution. In response to a temporal pulse of a signal, we evolve networks whose output turns on slowly after the pulse begins, and shuts down rapidly when the pulse terminates. The best performing networks under our conditions do not fall into categories such as feed forward and negative feedback that also encode the input-output relation we used for selection. Pareto evolution can more efficiently search the space of networks than optimization based on a single ad hoc combination of the design criteria.

  10. 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.

  11. MSAViewer: interactive JavaScript visualization of multiple sequence alignments.

    Science.gov (United States)

    Yachdav, Guy; Wilzbach, Sebastian; Rauscher, Benedikt; Sheridan, Robert; Sillitoe, Ian; Procter, James; Lewis, Suzanna E; Rost, Burkhard; Goldberg, Tatyana

    2016-11-15

    The MSAViewer is a quick and easy visualization and analysis JavaScript component for Multiple Sequence Alignment data of any size. Core features include interactive navigation through the alignment, application of popular color schemes, sorting, selecting and filtering. The MSAViewer is 'web ready': written entirely in JavaScript, compatible with modern web browsers and does not require any specialized software. The MSAViewer is part of the BioJS collection of components. The MSAViewer is released as open source software under the Boost Software License 1.0. Documentation, source code and the viewer are available at http://msa.biojs.net/Supplementary information: Supplementary data are available at Bioinformatics online. msa@bio.sh. © The Author 2016. Published by Oxford University Press.

  12. 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.

  13. Insulators form gene loops by interacting with promoters in Drosophila.

    Science.gov (United States)

    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.

  14. EIGER: Electromagnetic Interactions GEneRalized

    International Nuclear Information System (INIS)

    Champagne, N J; Sharpe, R M; Rockway, J W

    2001-01-01

    The EIGER (Electromagnetic Interactions Generalized) modeling suite is a joint development activity by the Lawrence Livermore National Lab, Sandia National Labs, the University of Houston, and the Navy (Space and Naval Warfare Systems Center-San Diego). The effort endeavors to bring the next generation of hybrid, higher-order, full-wave analysis methods into a single integrated framework. The tools are based upon frequency-domain solutions of Maxwell's equations to model scattering and radiation from complex 2D and 3D structures. The framework employs boundary element solutions of integral equation formulations and finite element solutions of the Helmholtz wave equation. A goal is to use higher-order representations to model both the geometry (using higher-order geometric elements) and numerical methods (using higher-order vector basis functions). In addition, a variety of advanced Green's functions and symmetry operators can be applied to efficiently treat geometries containing such features as layered material regions and periodic structures. Each of these methods can be brought to bear simultaneously, on different portions of a complex structure. HPC implementation issues were addressed during the design of the software architecture, so that the same package runs on platforms ranging from serial desktop workstations through advanced HPC architectures. Our current efforts on higher-order modeling and improved solver libraries will be highlighted

  15. 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

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

    Science.gov (United States)

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

    2011-06-01

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

  17. Considering Interactions among Multiple Criteria for the Server Selection

    Directory of Open Access Journals (Sweden)

    Vesna Čančer

    2010-06-01

    Full Text Available Decision-making about server selection is one of the multi-criteria decision-making (MCDM processes where interactions among criteria should be considered. The paper introduces and develops some solutions for considering interactions among criteria in the MCDM problems. In the frame procedure for MCDM by using the group of methods, based on assigning weights, special attention is given to the synthesis of the local alternatives’ values into the aggregate values where the mutual preferential independence between two criteria is not assumed. Firstly, we delineate how to complete the additive model into the multiplicative one with synergic and redundancy elements in the case that criteria are structured in one level and in two levels. Furthermore, we adapted the concept of the fuzzy Choquet integral to the multi-attribute value theory. Studying and comparing the results of the example case of the server selection obtained by both aggregation approaches, the paper highlights the advantages of the first one since it does not require from decision makers to determine the weights of all possible combinations of the criteria and it enables the further use of the most preferred MCDM methods.

  18. An Advanced N -body Model for Interacting Multiple Stellar Systems

    Energy Technology Data Exchange (ETDEWEB)

    Brož, Miroslav [Astronomical Institute of the Charles University, Faculty of Mathematics and Physics, V Holešovičkách 2, CZ-18000 Praha 8 (Czech Republic)

    2017-06-01

    We construct an advanced model for interacting multiple stellar systems in which we compute all trajectories with a numerical N -body integrator, namely the Bulirsch–Stoer from the SWIFT package. We can then derive various observables: astrometric positions, radial velocities, minima timings (TTVs), eclipse durations, interferometric visibilities, closure phases, synthetic spectra, spectral energy distribution, and even complete light curves. We use a modified version of the Wilson–Devinney code for the latter, in which the instantaneous true phase and inclination of the eclipsing binary are governed by the N -body integration. If all of these types of observations are at one’s disposal, a joint χ {sup 2} metric and an optimization algorithm (a simplex or simulated annealing) allow one to search for a global minimum and construct very robust models of stellar systems. At the same time, our N -body model is free from artifacts that may arise if mutual gravitational interactions among all components are not self-consistently accounted for. Finally, we present a number of examples showing dynamical effects that can be studied with our code and we discuss how systematic errors may affect the results (and how to prevent this from happening).

  19. Gene-Environment Interactions in the Development of Complex Disease Phenotypes

    Directory of Open Access Journals (Sweden)

    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

  20. 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.

  1. Interactions Between SNP Alleles at Multiple Loci and Variation in Skin Pigmentation in 122 Caucasians

    Directory of Open Access Journals (Sweden)

    Sumiko Anno

    2007-01-01

    Full Text Available This study was undertaken to clarify the molecular basis for human skin color variation and the environmental adaptability to ultraviolet irradiation, with the ultimate goal of predicting the impact of changes in future environments on human health risk. One hundred twenty-two Caucasians living in Toledo, Ohio participated. Back and cheek skin were assayed for melanin as a quantitative trait marker. Buccal cell samples were collected and used for DNA extraction. DNA was used for SNP genotyping using the Masscode™ system, which entails two-step PCR amplification and a platform chemistry which allows cleavable mass spectrometry tags. The results show gene-gene interaction between SNP alleles at multiple loci (not necessarily on the same chromosome contributes to inter-individual skin color variation while suggesting a high probability of linkage disequilibrium. Confirmation of these findings requires further study with other ethic groups to analyze the associations between SNP alleles at multiple loci and human skin color variation. Our overarching goal is to use remote sensing data to clarify the interaction between atmospheric environments and SNP allelic frequency and investigate human adaptability to ultraviolet irradiation. Such information should greatly assist in the prediction of the health effects of future environmental changes such as ozone depletion and increased ultraviolet exposure. If such health effects are to some extent predictable, it might be possible to prepare for such changes in advance and thus reduce the extent of their impact.

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

    OpenAIRE

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

    2017-01-01

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

  3. 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

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

    NARCIS (Netherlands)

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

    Currently, most guidelines on drug-drug interaction (DDI) neither consider the potential effect of genetic polymorphism in the strength of the interaction nor do they account for the complex interaction caused by the combination of DDI and drug-gene interaction (DGI) where there are multiple

  5. The cfr and cfr-like multiple resistance genes

    DEFF Research Database (Denmark)

    Vester, Birte

    2018-01-01

    . The cfr gene is found in various bacteria in many geographical locations and placed on plasmids or associated with transposons. Cfr-related genes providing similar resistance have been identified in Bacillales, and now also in the pathogens Clostridium difficile and Enterococcus faecium. In addition......, the presence of the cfr gene has been detected in harbours and food markets....

  6. An Interactive Database of Cocaine-Responsive Gene Expression

    Directory of Open Access Journals (Sweden)

    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.

  7. 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

  8. Interactions between Meteorus pulchricornis and Spodoptera exigua multiple nucleopolyhedrovirus.

    Science.gov (United States)

    Guo, Hui-Fang; Fang, Ji-Chao; Zhong, Wan-Fang; Liu, Bao-Sheng

    2013-01-01

    Baculoviruses may interact with parasitoids in the same host. A previous study has shown that infection of larvae with Spodoptera litura nucleopolyhedrovirus (SpltNPV) was deleterious to the survival and development of Meteorus pulchricornis (Wesmael) (Hymenoptera: Braconidae). In this paper, the interactions between M. pulchricornis and Spodoptera exigua multiple nucleopolyhedrovirus (SeMNPV) in Spodoptera exigua (Hübner) (Lepidoptera: Noctuidae), a permissive host of the virus and parasitoid, were investigated. The results showed that the effect of M. pulchricornis on SeMNPV and the effect of the virus on the parasitoid both depended on the concentration of the virus and the interval between viral infection and parasitism. Whether S. exigua was treated with the parasitoid and virus simultaneously or 1 day apart, the biological activities of 10(5), 10(6), and 10(7) OBs/mL SeMNPV were all significantly improved by M. pulchricornis. In contrast, the biological activity of 10(3) OBs/mL SeMNPV was significantly decreased when the host was exposed to the virus and parasitoid simultaneously. Regarding the impact of SeMNPV on M. pulchricornis, exposing the host to the parasitoid and SeMNPV with concentrations lower than 10(6) occlusion bodies (OBs)/mL produced no negative effects on the parasitoid. The results also showed that ingestion of SeMNPV by adult stage M. pulchricornis significantly increased the number of parasitoid offspring that successfully emerged from the host. Furthermore, M. pulchricornis was found to transmit SeMNPV among populations of S. exigua. Taken together, these findings indicate that M. pulchricornis integrated with an appropriate concentration of SeMNPV has the potential to improve the efficacy of biological control against S. exigua.

  9. Multiple Wins, Multiple Organizations—How to Manage Institutional Interaction in Financing Forest Landscape Restoration (FLR

    Directory of Open Access Journals (Sweden)

    Astrid Carrapatoso

    2018-03-01

    Full Text Available By restoring forest ecosystems and fostering resilient and sustainable land use practices, Forest Landscape Restoration (FLR contributes to climate change mitigation, adaptation and sustainable development as well as the protection of biological diversity and combating desertification. This integrative approach provides the opportunity for multiple wins, but it necessitates the management of complex institutional interactions arising from the involvement of multiple international organizations. Focusing on the pivotal aspect of financing, this article surveys the landscape of public international institutions supporting FLR and analyzes the effectiveness of existing mechanisms of inter-institutional coordination and harmonization. Methodologically, our research is based on a document analysis, complemented by participant observation of the two Bonn Climate Change Conferences in May and November 2017 as well as the Global Landscapes Forum in December 2017. We find that financial institutions have established fairly effective rules for the management of positive and negative externalities through the introduction of co-benefits and safeguards. The fact that each institution has their own safeguards provisions, however, leads to significant transaction costs for recipient countries. In the discussion, we thus recommend that institutions should refrain from an unnecessary duplication of standards and focus on best practice.

  10. Optimizing Sparse Matrix-Multiple Vectors Multiplication for Nuclear Configuration Interaction Calculations

    Energy Technology Data Exchange (ETDEWEB)

    Aktulga, Hasan Metin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Buluc, Aydin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Williams, Samuel [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Yang, Chao [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2014-08-14

    Obtaining highly accurate predictions on the properties of light atomic nuclei using the configuration interaction (CI) approach requires computing a few extremal Eigen pairs of the many-body nuclear Hamiltonian matrix. In the Many-body Fermion Dynamics for nuclei (MFDn) code, a block Eigen solver is used for this purpose. Due to the large size of the sparse matrices involved, a significant fraction of the time spent on the Eigen value computations is associated with the multiplication of a sparse matrix (and the transpose of that matrix) with multiple vectors (SpMM and SpMM-T). Existing implementations of SpMM and SpMM-T significantly underperform expectations. Thus, in this paper, we present and analyze optimized implementations of SpMM and SpMM-T. We base our implementation on the compressed sparse blocks (CSB) matrix format and target systems with multi-core architectures. We develop a performance model that allows us to understand and estimate the performance characteristics of our SpMM kernel implementations, and demonstrate the efficiency of our implementation on a series of real-world matrices extracted from MFDn. In particular, we obtain 3-4 speedup on the requisite operations over good implementations based on the commonly used compressed sparse row (CSR) matrix format. The improvements in the SpMM kernel suggest we may attain roughly a 40% speed up in the overall execution time of the block Eigen solver used in MFDn.

  11. 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...

  12. Multiple independent insertions of 5S rRNA genes in the spliced-leader gene family of trypanosome species.

    Science.gov (United States)

    Beauparlant, Marc A; Drouin, Guy

    2014-02-01

    Analyses of the 5S rRNA genes found in the spliced-leader (SL) gene repeat units of numerous trypanosome species suggest that such linkages were not inherited from a common ancestor, but were the result of independent 5S rRNA gene insertions. In trypanosomes, 5S rRNA genes are found either in the tandemly repeated units coding for SL genes or in independent tandemly repeated units. Given that trypanosome species where 5S rRNA genes are within the tandemly repeated units coding for SL genes are phylogenetically related, one might hypothesize that this arrangement is the result of an ancestral insertion of 5S rRNA genes into the tandemly repeated SL gene family of trypanosomes. Here, we use the types of 5S rRNA genes found associated with SL genes, the flanking regions of the inserted 5S rRNA genes and the position of these insertions to show that most of the 5S rRNA genes found within SL gene repeat units of trypanosome species were not acquired from a common ancestor but are the results of independent insertions. These multiple 5S rRNA genes insertion events in trypanosomes are likely the result of frequent founder events in different hosts and/or geographical locations in species having short generation times.

  13. Thymocyte migration: an affair of multiple cellular interactions?

    Directory of Open Access Journals (Sweden)

    Savino W.

    2003-01-01

    Full Text Available Cell migration is a crucial event in the general process of thymocyte differentiation. The cellular interactions involved in the control of this migration are beginning to be defined. At least chemokines and extracellular matrix proteins appear to be part of the game. Cells of the thymic microenvironment produce these two groups of molecules, whereas developing thymocytes express the corresponding receptors. Moreover, although chemokines and extracellular matrix can drive thymocyte migration per se, a combined role for these molecules appears to contribute to the resulting migration patterns of thymocytes in their various stages of differentiation. The dynamics of chemokine and extracellular matrix production and degradation is not yet well understood. However, matrix metalloproteinases are likely to play a role in the breakdown of intrathymic extracellular matrix contents. Thus, the physiological migration of thymocytes should be envisioned as a resulting vector of multiple, simultaneous and/or sequential stimuli involving chemokines, adhesive and de-adhesive extracellular matrix proteins, as well as matrix metalloproteinases. Accordingly, it is conceivable that any pathological change in any of these loops may result in the alteration of normal thymocyte migration. This seems to be the case in murine infection by the protozoan parasite Trypanosoma cruzi, the causative agent of Chagas' disease. A better knowledge of the physiological mechanisms governing thymocyte migration will provide new clues for designing therapeutic strategies targeting developing T cells.

  14. 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

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

    Directory of Open Access Journals (Sweden)

    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.

  16. 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.

  17. 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.

  18. Multiple Suboptimal Solutions for Prediction Rules in Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Osamu Komori

    2013-01-01

    Full Text Available This paper discusses mathematical and statistical aspects in analysis methods applied to microarray gene expressions. We focus on pattern recognition to extract informative features embedded in the data for prediction of phenotypes. It has been pointed out that there are severely difficult problems due to the unbalance in the number of observed genes compared with the number of observed subjects. We make a reanalysis of microarray gene expression published data to detect many other gene sets with almost the same performance. We conclude in the current stage that it is not possible to extract only informative genes with high performance in the all observed genes. We investigate the reason why this difficulty still exists even though there are actively proposed analysis methods and learning algorithms in statistical machine learning approaches. We focus on the mutual coherence or the absolute value of the Pearson correlations between two genes and describe the distributions of the correlation for the selected set of genes and the total set. We show that the problem of finding informative genes in high dimensional data is ill-posed and that the difficulty is closely related with the mutual coherence.

  19. Upregulation of Immunoglobulin-related Genes in Cortical Sections from Multiple Sclerosis Patients

    NARCIS (Netherlands)

    Torkildsen, O.; Stansberg, C.; Angelskar, S.M.; Kooi, E.J.; Geurts, J.J.G.; van der Valk, P.; Myhr, K.M.; Steen, V.M.; Bo, L.

    2010-01-01

    Multiple sclerosis (MS) is a demyelinating disease of the central nervous system (CNS). Microarray-based global gene expression profiling is a promising method, used to study potential genes involved in the pathogenesis of the disease. In the present study, we have examined global gene expression in

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

    Science.gov (United States)

    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.

  1. Structured association analysis leads to insight into Saccharomyces cerevisiae gene regulation by finding multiple contributing eQTL hotspots associated with functional gene modules.

    Science.gov (United States)

    Curtis, Ross E; Kim, Seyoung; Woolford, John L; Xu, Wenjie; Xing, Eric P

    2013-03-21

    Association analysis using genome-wide expression quantitative trait locus (eQTL) data investigates the effect that genetic variation has on cellular pathways and leads to the discovery of candidate regulators. Traditional analysis of eQTL data via pairwise statistical significance tests or linear regression does not leverage the availability of the structural information of the transcriptome, such as presence of gene networks that reveal correlation and potentially regulatory relationships among the study genes. We employ a new eQTL mapping algorithm, GFlasso, which we have previously developed for sparse structured regression, to reanalyze a genome-wide yeast dataset. GFlasso fully takes into account the dependencies among expression traits to suppress false positives and to enhance the signal/noise ratio. Thus, GFlasso leverages the gene-interaction network to discover the pleiotropic effects of genetic loci that perturb the expression level of multiple (rather than individual) genes, which enables us to gain more power in detecting previously neglected signals that are marginally weak but pleiotropically significant. While eQTL hotspots in yeast have been reported previously as genomic regions controlling multiple genes, our analysis reveals additional novel eQTL hotspots and, more interestingly, uncovers groups of multiple contributing eQTL hotspots that affect the expression level of functional gene modules. To our knowledge, our study is the first to report this type of gene regulation stemming from multiple eQTL hotspots. Additionally, we report the results from in-depth bioinformatics analysis for three groups of these eQTL hotspots: ribosome biogenesis, telomere silencing, and retrotransposon biology. We suggest candidate regulators for the functional gene modules that map to each group of hotspots. Not only do we find that many of these candidate regulators contain mutations in the promoter and coding regions of the genes, in the case of the Ribi group

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  4. Flame Interactions and Thermoacoustics in Multiple-Nozzle Combustors

    Science.gov (United States)

    Dolan, Brian

    The first major chapter of original research (Chapter 3) examines thermoacoustic oscillations in a low-emission staged multiple-nozzle lean direct injection (MLDI) combustor. This experimental program investigated a relatively practical combustor sector that was designed and built as part of a commercial development program. The research questions are both practical, such as under what conditions the combustor can be safely operated, and fundamental, including what is most significant to driving the combustion oscillations in this system. A comprehensive survey of operating conditions finds that the low-emission (and low-stability) intermediate and outer stages are necessary to drive significant thermoacoustics. Phase-averaged and time-resolved OH* imaging show that dramatic periodic strengthening and weakening of the reaction zone downstream of the low-emission combustion stages. An acoustic modal analysis shows the pressure wave shapes and identifies the dominant thermoacoustic behavior as the first longitudinal mode for this combustor geometry. Finally, a discussion of the likely significant coupling mechanisms is given. Periodic reaction zone behavior in the low-emission fuel stages is the primary contributor to unsteady heat release. Differences between the fuel stages in the air swirler design, the fuel number of the injectors, the lean blowout point, and the nominal operating conditions all likely contribute to the limit cycle behavior of the low-emission stages. Chapter 4 investigates the effects of interaction between two adjacent swirl-stabilized nozzles using experimental and numerical tools. These studies are more fundamental; while the nozzle hardware is the same as the lean direct injection nozzles used in the MLDI combustion concept, the findings are generally applicable to other swirl-stabilized combustion systems as well. Much of the work utilizes a new experiment where the distance between nozzles was varied to change the level of interaction

  5. Assessing interactions between HLA-DRB1*15 and infectious mononucleosis on the risk of multiple sclerosis.

    Science.gov (United States)

    Disanto, Giulio; Hall, Carolina; Lucas, Robyn; Ponsonby, Anne-Louise; Berlanga-Taylor, Antonio J; Giovannoni, Gavin; Ramagopalan, Sreeram V

    2013-09-01

    Gene-environment interactions may shed light on the mechanisms underlying multiple sclerosis (MS). We pooled data from two case-control studies on incident demyelination and used different methods to assess interaction between HLA-DRB1*15 (DRB1-15) and history of infectious mononucleosis (IM). Individuals exposed to both factors were at substantially increased risk of disease (OR=7.32, 95% CI=4.92-10.90). In logistic regression models, DRB1-15 and IM status were independent predictors of disease while their interaction term was not (DRB1-15*IM: OR=1.35, 95% CI=0.79-2.23). However, interaction on an additive scale was evident (Synergy index=2.09, 95% CI=1.59-2.59; excess risk due to interaction=3.30, 95%CI=0.47-6.12; attributable proportion due to interaction=45%, 95% CI=22-68%). This suggests, if the additive model is appropriate, the DRB1-15 and IM may be involved in the same causal process leading to MS and highlights the benefit of reporting gene-environment interactions on both a multiplicative and additive scale.

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

    Directory of Open Access Journals (Sweden)

    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.

  7. Investigation of heavy quark and multiple interactions at HERA

    International Nuclear Information System (INIS)

    Magro, L.M.

    2005-09-01

    This thesis is oriented to the study of heavy quark photoproduction and multiple interactions, MI. For this reason we search for D* Mesons, in order to tag the charm quark, and we restrict ourselves in the region: Q 2 2 . For the theoretical calculations we use two Monte Carlo event generators: RAPGAP 3.1 and PYTHIA 6.2. Heavy quark production provides a large hard scale and therefore a small α s , which allows to test the perturbative QCD theory. On the other hand, MI has been proven to be important in hadron-hadron collisions. In this thesis, using MC event generators, we search for possible signals of MI in heavy quark production in electron-proton, ep, collisions. The thesis begins with a Theoretical Overview, with an introduction to ep collisions physics and the heavy quark photoproduction. We also give an introduction to the MI model included in PYTHIA. The next chapter introduces the concept of jet and presents some methods for the Heavy Quark Identification. After these two theoretical chapters there is a study of the direct and photon resolved processes, as well as the parton showering with RAPGAP. Since this thesis is oriented to the study of MI, PYTHIA plays a very important role because it includes a MI model also for ep collisions. Therefore, the fourth chapter is oriented to study the different steps in the event generation in PYTHIA. Chapter 7 is a D* Meson photoproduction study, where we include a comparison between the data, taken from the PhD Thesis of Gero Flucke. Finally, chapter 8 is a search for possible signals on MI. In hadron-hadron collisions it is clear that MI play a role. In ep collisions it is not so clear although MI could play a role in resolved photon events. The aim of this chapter is to find signals where HERA measurements could be sensitive to MI. (orig.)

  8. Bayesian inference based modelling for gene transcriptional dynamics by integrating multiple source of knowledge

    Directory of Open Access Journals (Sweden)

    Wang Shu-Qiang

    2012-07-01

    Full Text Available Abstract Background A key challenge in the post genome era is to identify genome-wide transcriptional regulatory networks, which specify the interactions between transcription factors and their target genes. Numerous methods have been developed for reconstructing gene regulatory networks from expression data. However, most of them are based on coarse grained qualitative models, and cannot provide a quantitative view of regulatory systems. Results A binding affinity based regulatory model is proposed to quantify the transcriptional regulatory network. Multiple quantities, including binding affinity and the activity level of transcription factor (TF are incorporated into a general learning model. The sequence features of the promoter and the possible occupancy of nucleosomes are exploited to estimate the binding probability of regulators. Comparing with the previous models that only employ microarray data, the proposed model can bridge the gap between the relative background frequency of the observed nucleotide and the gene's transcription rate. Conclusions We testify the proposed approach on two real-world microarray datasets. Experimental results show that the proposed model can effectively identify the parameters and the activity level of TF. Moreover, the kinetic parameters introduced in the proposed model can reveal more biological sense than previous models can do.

  9. Simple and Efficient Targeting of Multiple Genes Through CRISPR-Cas9 in Physcomitrella patens

    Directory of Open Access Journals (Sweden)

    Mauricio Lopez-Obando

    2016-11-01

    Full Text Available Powerful genome editing technologies are needed for efficient gene function analysis. The CRISPR-Cas9 system has been adapted as an efficient gene-knock-out technology in a variety of species. However, in a number of situations, knocking out or modifying a single gene is not sufficient; this is particularly true for genes belonging to a common family, or for genes showing redundant functions. Like many plants, the model organism Physcomitrella patens has experienced multiple events of polyploidization during evolution that has resulted in a number of families of duplicated genes. Here, we report a robust CRISPR-Cas9 system, based on the codelivery of a CAS9 expressing cassette, multiple sgRNA vectors, and a cassette for transient transformation selection, for gene knock-out in multiple gene families. We demonstrate that CRISPR-Cas9-mediated targeting of five different genes allows the selection of a quintuple mutant, and all possible subcombinations of mutants, in one experiment, with no mutations detected in potential off-target sequences. Furthermore, we confirmed the observation that the presence of repeats in the vicinity of the cutting region favors deletion due to the alternative end joining pathway, for which induced frameshift mutations can be potentially predicted. Because the number of multiple gene families in Physcomitrella is substantial, this tool opens new perspectives to study the role of expanded gene families in the colonization of land by plants.

  10. 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.

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

    Directory of Open Access Journals (Sweden)

    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

  12. Protein Annotation from Protein Interaction Networks and Gene Ontology

    OpenAIRE

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

    2011-01-01

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

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

    Science.gov (United States)

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

    2017-09-13

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

  14. 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.

  15. APPRIS 2017: principal isoforms for multiple gene sets

    Science.gov (United States)

    Rodriguez-Rivas, Juan; Di Domenico, Tomás; Vázquez, Jesús; Valencia, Alfonso

    2018-01-01

    Abstract The APPRIS database (http://appris-tools.org) uses protein structural and functional features and information from cross-species conservation to annotate splice isoforms in protein-coding genes. APPRIS selects a single protein isoform, the ‘principal’ isoform, as the reference for each gene based on these annotations. A single main splice isoform reflects the biological reality for most protein coding genes and APPRIS principal isoforms are the best predictors of these main proteins isoforms. Here, we present the updates to the database, new developments that include the addition of three new species (chimpanzee, Drosophila melangaster and Caenorhabditis elegans), the expansion of APPRIS to cover the RefSeq gene set and the UniProtKB proteome for six species and refinements in the core methods that make up the annotation pipeline. In addition APPRIS now provides a measure of reliability for individual principal isoforms and updates with each release of the GENCODE/Ensembl and RefSeq reference sets. The individual GENCODE/Ensembl, RefSeq and UniProtKB reference gene sets for six organisms have been merged to produce common sets of splice variants. PMID:29069475

  16. Local tax interaction with multiple tax instruments: evidence from Flemish municipalities

    OpenAIRE

    S. VAN PARYS; B. MERLEVEDE; T. VERBEKE

    2010-01-01

    We investigate the long run result of strategic interaction among local jurisdictions using multiple tax instruments. Most studies about local policy interaction only consider a single policy instrument. With multiple tax instruments, however, tax interaction is more complex. We construct a simple theoretical framework based on a basic spillover model, with two tax rates and immobile resources. We show that the signs of within and cross tax interaction crucially depend on the extent to which ...

  17. 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.

  18. 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,

  19. A knowledge-driven interaction analysis reveals potential neurodegenerative mechanism of multiple sclerosis susceptibility

    NARCIS (Netherlands)

    Bush, W.S.; McCauley, J.L.; DeJager, P.L.; Dudek, S.M.; Hafler, D.A.; Gibson, R.A.; Matthews, P.M.; Kappos, L.; Naegelin, Y.; Polman, C.H.; Hauser, S.L.; Oksenberg, J.; Haines, J.L.; Ritchie, M.D.

    2011-01-01

    Gene-gene interactions are proposed as an important component of the genetic architecture of complex diseases, and are just beginning to be evaluated in the context of genome-wide association studies (GWAS). In addition to detecting epistasis, a benefit to interaction analysis is that it also

  20. 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.

  1. A search engine to identify pathway genes from expression data on multiple organisms

    Directory of Open Access Journals (Sweden)

    Zambon Alexander C

    2007-05-01

    Full Text Available Abstract Background The completion of several genome projects showed that most genes have not yet been characterized, especially in multicellular organisms. Although most genes have unknown functions, a large collection of data is available describing their transcriptional activities under many different experimental conditions. In many cases, the coregulatation of a set of genes across a set of conditions can be used to infer roles for genes of unknown function. Results We developed a search engine, the Multiple-Species Gene Recommender (MSGR, which scans gene expression datasets from multiple organisms to identify genes that participate in a genetic pathway. The MSGR takes a query consisting of a list of genes that function together in a genetic pathway from one of six organisms: Homo sapiens, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, Arabidopsis thaliana, and Helicobacter pylori. Using a probabilistic method to merge searches, the MSGR identifies genes that are significantly coregulated with the query genes in one or more of those organisms. The MSGR achieves its highest accuracy for many human pathways when searches are combined across species. We describe specific examples in which new genes were identified to be involved in a neuromuscular signaling pathway and a cell-adhesion pathway. Conclusion The search engine can scan large collections of gene expression data for new genes that are significantly coregulated with a pathway of interest. By integrating searches across organisms, the MSGR can identify pathway members whose coregulation is either ancient or newly evolved.

  2. Restriction genes for retroviruses influence the risk of multiple sclerosis

    DEFF Research Database (Denmark)

    Nexø, Bjørn A; Hansen, Bettina; Nissen, Kari K

    2013-01-01

    known for a long time. Today human restriction genes for retroviruses include amongst others TRIMs, APOBEC3s, BST2 and TREXs. We have therefore looked for a role of these retroviral restriction genes in MS using genetic epidemiology. We here report that markers in two TRIMs, TRIM5 and TRIM22...... and a marker in BST2, associated statistically with the risk of getting MS, while markers in or near APOBEC3s and TREXs showed little or no effect. This indicates that the two TRIMs and BST2 influence the risk of disease and thus supports the hypothesis of a viral involvement....

  3. 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...

  4. Novel functional polymorphism in IGF-1 gene associated with multiple sclerosis: A new insight to MS.

    Science.gov (United States)

    Shahbazi, Majid; Abdolmohammadi, Reza; Ebadi, Hamid; Farazmandfar, Touraj

    2017-04-01

    Interactions between several genes and environment may play a role in susceptibility to multiple sclerosis (MS). The IGF-1 plays a key role in proliferation, maintenance and survival of nerve cells. Therefore, we hypothesized that IGF-1 may be a target for prediction and control MS. We aimed to analysis IGF-1 gene promoter sequence, to investigate the effect of the single nucleotide variants on IGF-1 expression and its association with MS. We enrolled 339 MS patients and 431 healthy controls. A specific region in IGF-1 gene promoter was investigated by SSCP analysis. All samples were genotyped by SSP-PCR. In-vitro and in-vivo IGF-1 production was measured by ELISA assay. IGF-1 expression in PBMCs was measured using real-time PCR. We identified a T to C single nucleotide substitution at position -1089 and a C to T at position -383 from transcription start site in the IGF-1 gene promoter. There was a significant association between MS and genotypes IGF-1(-383) C/T (p=0.001) and IGF-1(-383) C/C (pMS (p=0.001). In-vitro and in-vivo IGF-1 level showed that IGF-1 production in samples with genotype IGF-1(-383) C/C significantly was less than T/T (p=0.004) but not T/C (p=0.220). According to IGF-1 roles in CNS and our results, this study suggests that low IGF-1 level may be associated with susceptibility to MS. Copyright © 2017 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

    2007-06-01

    family consume per month (50g)? 1. Vegetable oil : __________ (50g) [__]__]__] 2. Soy bean oil : ___________ (50g) [__]__]__] 3...and redissolving in a methanol acetate buffer mixture. Liquid chromatography photo diode array multiple generation mass spectrometry (LC/PDA/MS...delivery liquid chromatography system with multiple channel diode-array detection and a quadrupole ion trap mass spectrometer model ’Advantage

  6. Multiple CMS-restorer gene polymorphism in gynodioecious Plantago coronopus

    NARCIS (Netherlands)

    Damme, van J.M.M.; Hundscheid, M.P.J.; Ivanovic, S.; Koelewijn, H.P.

    2004-01-01

    The mode of inheritance of the male sterility trait is crucial for understanding the evolutionary dynamics of the sexual system gynodioecy, which is the co-occurrence of female and hermaphrodite plants in natural populations. Both cytoplasmic (CMS) and nuclear (restorer) genes are known to be

  7. Comparison of multiple gene assembly methods for metabolic engineering

    Science.gov (United States)

    Chenfeng Lu; Karen Mansoorabadi; Thomas Jeffries

    2007-01-01

    A universal, rapid DNA assembly method for efficient multigene plasmid construction is important for biological research and for optimizing gene expression in industrial microbes. Three different approaches to achieve this goal were evaluated. These included creating long complementary extensions using a uracil-DNA glycosylase technique, overlap extension polymerase...

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

    Science.gov (United States)

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

    2013-02-01

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

  9. MDM2 SNP309, gene-gene interaction, and tumor susceptibility: an updated meta-analysis

    Directory of Open Access Journals (Sweden)

    Wu Wei

    2011-05-01

    Full Text Available Abstract Background The tumor suppressor gene p53 is involved in multiple cellular pathways including apoptosis, transcriptional control, and cell cycle regulation. In the last decade it has been demonstrated that the single nucleotide polymorphism (SNP at codon 72 of the p53 gene is associated with the risk for development of various neoplasms. MDM2 SNP309 is a single nucleotide T to G polymorphism located in the MDM2 gene promoter. From the time that this well-characterized functional polymorphism was identified, a variety of case-control studies have been published that investigate the possible association between MDM2 SNP309 and cancer risk. However, the results of the published studies, as well as the subsequent meta-analyses, remain contradictory. Methods To investigate whether currently published epidemiological studies can clarify the potential interaction between MDM2 SNP309 and the functional genetic variant in p53 codon72 (Arg72Pro and p53 mutation status, we performed a meta-analysis of the risk estimate on 27,813 cases with various tumor types and 30,295 controls. Results The data we reviewed indicated that variant homozygote 309GG and heterozygote 309TG were associated with a significant increased risk of all tumor types (homozygote comparison: odds ratio (OR = 1.25, 95% confidence interval (CI = 1.13-1.37; heterozygote comparison: OR = 1.10, 95% CI = 1.03-1.17. We also found that the combination of GG and Pro/Pro, TG and Pro/Pro, GG and Arg/Arg significantly increased the risk of cancer (OR = 3.38, 95% CI = 1.77-6.47; OR = 1.88, 95% CI = 1.26-2.81; OR = 1.96, 95% CI = 1.01-3.78, respectively. In a stratified analysis by tumor location, we also found a significant increased risk in brain, liver, stomach and uterus cancer (OR = 1.47, 95% CI = 1.06-2.03; OR = 2.24, 95%CI = 1.57-3.18; OR = 1.54, 95%CI = 1.04-2.29; OR = 1.34, 95%CI = 1.07-1.29, respectively. However, no association was seen between MDM2 SNP309 and tumor susceptibility

  10. Polyuridylylation and processing of transcripts from multiple gene minicircles in chloroplasts of the dinoflagellate Amphidinium carterae

    KAUST Repository

    Barbrook, Adrian C.; Dorrell, Richard G.; Burrows, Jennifer; Plenderleith, Lindsey J.; Nisbet, R. Ellen R.; Howe, Christopher J.

    2012-01-01

    -PCR to study transcription and transcript processing in the chloroplasts of Amphidinium carterae, a model peridinin-containing dinoflagellate. These organisms have a highly unusual chloroplast genome, with genes located on multiple small 'minicircle' elements

  11. Multiple controls affect arsenite oxidase gene expression in Herminiimonas arsenicoxydans

    Directory of Open Access Journals (Sweden)

    Coppée Jean-Yves

    2010-02-01

    Full Text Available Abstract Background Both the speciation and toxicity of arsenic are affected by bacterial transformations, i.e. oxidation, reduction or methylation. These transformations have a major impact on environmental contamination and more particularly on arsenic contamination of drinking water. Herminiimonas arsenicoxydans has been isolated from an arsenic- contaminated environment and has developed various mechanisms for coping with arsenic, including the oxidation of As(III to As(V as a detoxification mechanism. Results In the present study, a differential transcriptome analysis was used to identify genes, including arsenite oxidase encoding genes, involved in the response of H. arsenicoxydans to As(III. To get insight into the molecular mechanisms of this enzyme activity, a Tn5 transposon mutagenesis was performed. Transposon insertions resulting in a lack of arsenite oxidase activity disrupted aoxR and aoxS genes, showing that the aox operon transcription is regulated by the AoxRS two-component system. Remarkably, transposon insertions were also identified in rpoN coding for the alternative N sigma factor (σ54 of RNA polymerase and in dnaJ coding for the Hsp70 co-chaperone. Western blotting with anti-AoxB antibodies and quantitative RT-PCR experiments allowed us to demonstrate that the rpoN and dnaJ gene products are involved in the control of arsenite oxidase gene expression. Finally, the transcriptional start site of the aoxAB operon was determined using rapid amplification of cDNA ends (RACE and a putative -12/-24 σ54-dependent promoter motif was identified upstream of aoxAB coding sequences. Conclusion These results reveal the existence of novel molecular regulatory processes governing arsenite oxidase expression in H. arsenicoxydans. These data are summarized in a model that functionally integrates arsenite oxidation in the adaptive response to As(III in this microorganism.

  12. Genotet: An Interactive Web-based Visual Exploration Framework to Support Validation of Gene Regulatory Networks.

    Science.gov (United States)

    Yu, Bowen; Doraiswamy, Harish; Chen, Xi; Miraldi, Emily; Arrieta-Ortiz, Mario Luis; Hafemeister, Christoph; Madar, Aviv; Bonneau, Richard; Silva, Cláudio T

    2014-12-01

    Elucidation of transcriptional regulatory networks (TRNs) is a fundamental goal in biology, and one of the most important components of TRNs are transcription factors (TFs), proteins that specifically bind to gene promoter and enhancer regions to alter target gene expression patterns. Advances in genomic technologies as well as advances in computational biology have led to multiple large regulatory network models (directed networks) each with a large corpus of supporting data and gene-annotation. There are multiple possible biological motivations for exploring large regulatory network models, including: validating TF-target gene relationships, figuring out co-regulation patterns, and exploring the coordination of cell processes in response to changes in cell state or environment. Here we focus on queries aimed at validating regulatory network models, and on coordinating visualization of primary data and directed weighted gene regulatory networks. The large size of both the network models and the primary data can make such coordinated queries cumbersome with existing tools and, in particular, inhibits the sharing of results between collaborators. In this work, we develop and demonstrate a web-based framework for coordinating visualization and exploration of expression data (RNA-seq, microarray), network models and gene-binding data (ChIP-seq). Using specialized data structures and multiple coordinated views, we design an efficient querying model to support interactive analysis of the data. Finally, we show the effectiveness of our framework through case studies for the mouse immune system (a dataset focused on a subset of key cellular functions) and a model bacteria (a small genome with high data-completeness).

  13. A pipeline to determine RT-QPCR control genes for evolutionary studies: application to primate gene expression across multiple tissues.

    Directory of Open Access Journals (Sweden)

    Olivier Fedrigo

    Full Text Available Because many species-specific phenotypic differences are assumed to be caused by differential regulation of gene expression, many recent investigations have focused on measuring transcript abundance. Despite the availability of high-throughput platforms, quantitative real-time polymerase chain reaction (RT-QPCR is often the method of choice because of its low cost and wider dynamic range. However, the accuracy of this technique heavily relies on the use of multiple valid control genes for normalization. We created a pipeline for choosing genes potentially useful as RT-QPCR control genes for measuring expression between human and chimpanzee samples across multiple tissues, using published microarrays and a measure of tissue-specificity. We identified 13 genes from the pipeline and from commonly used control genes: ACTB, USP49, ARGHGEF2, GSK3A, TBP, SDHA, EIF2B2, GPDH, YWHAZ, HPTR1, RPL13A, HMBS, and EEF2. We then tested these candidate genes and validated their expression stability across species. We established the rank order of the most preferable set of genes for single and combined tissues. Our results suggest that for at least three tissues (cerebral cortex, liver, and skeletal muscle, EIF2B2, EEF2, HMBS, and SDHA are useful genes for normalizing human and chimpanzee expression using RT-QPCR. Interestingly, other commonly used control genes, including TBP, GAPDH, and, especially ACTB do not perform as well. This pipeline could be easily adapted to other species for which expression data exist, providing taxonomically appropriate control genes for comparisons of gene expression among species.

  14. 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.

  15. 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.

  16. Ras1 interacts with multiple new signaling and cytoskeletal loci in Drosophila eggshell patterning and morphogenesis.

    Science.gov (United States)

    Schnorr, J D; Holdcraft, R; Chevalier, B; Berg, C A

    2001-10-01

    Little is known about the genes that interact with Ras signaling pathways to regulate morphogenesis. The synthesis of dorsal eggshell structures in Drosophila melanogaster requires multiple rounds of Ras signaling followed by dramatic epithelial sheet movements. We took advantage of this process to identify genes that link patterning and morphogenesis; we screened lethal mutations on the second chromosome for those that could enhance a weak Ras1 eggshell phenotype. Of 1618 lethal P-element mutations tested, 13 showed significant enhancement, resulting in forked and fused dorsal appendages. Our genetic and molecular analyses together with information from the Berkeley Drosophila Genome Project reveal that 11 of these lines carry mutations in previously characterized genes. Three mutations disrupt the known Ras1 cell signaling components Star, Egfr, and Blistered, while one mutation disrupts Sec61beta, implicated in ligand secretion. Seven lines represent cell signaling and cytoskeletal components that are new to the Ras1 pathway; these are Chickadee (Profilin), Tec29, Dreadlocks, POSH, Peanut, Smt3, and MESK2, a suppressor of dominant-negative Ksr. A twelfth insertion disrupts two genes, Nrk, a "neurospecific" receptor tyrosine kinase, and Tpp, which encodes a neuropeptidase. These results suggest that Ras1 signaling during oogenesis involves novel components that may be intimately associated with additional signaling processes and with the reorganization of the cytoskeleton. To determine whether these Ras1 Enhancers function upstream or downstream of the Egf receptor, four mutations were tested for their ability to suppress an activated Egfr construct (lambdatop) expressed in oogenesis exclusively in the follicle cells. Mutations in Star and l(2)43Bb had no significant effect upon the lambdatop eggshell defect whereas smt3 and dock alleles significantly suppressed the lambdatop phenotype.

  17. A crack growth evaluation method for interacting multiple cracks

    International Nuclear Information System (INIS)

    Kamaya, Masayuki

    2003-01-01

    When stress corrosion cracking or corrosion fatigue occurs, multiple cracks are frequently initiated in the same area. According to section XI of the ASME Boiler and Pressure Vessel Code, multiple cracks are considered as a single combined crack in crack growth analysis, if the specified conditions are satisfied. In crack growth processes, however, no prescription for the interference between multiple cracks is given in this code. The JSME Post-Construction Code, issued in May 2000, prescribes the conditions of crack coalescence in the crack growth process. This study aimed to extend this prescription to more general cases. A simulation model was applied, to simulate the crack growth process, taking into account the interference between two cracks. This model made it possible to analyze multiple crack growth behaviors for many cases (e.g. different relative position and length) that could not be studied by experiment only. Based on these analyses, a new crack growth analysis method was suggested for taking into account the interference between multiple cracks. (author)

  18. 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.

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

    Science.gov (United States)

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

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    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

  1. 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

  2. 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.

  3. IGEMS: The Consortium on Interplay of Genes and Environment Across Multiple Studies

    DEFF Research Database (Denmark)

    Pedersen, Nancy L; Christensen, Kaare; Dahl, Anna K

    2013-01-01

    The Interplay of Genes and Environment across Multiple Studies (IGEMS) group is a consortium of eight longitudinal twin studies established to explore the nature of social context effects and gene-environment interplay in late-life functioning. The resulting analysis of the combined data from ove...

  4. 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.

  5. 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/ .

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

    Science.gov (United States)

    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

  7. A BAC-bacterial recombination method to generate physically linked multiple gene reporter DNA constructs

    Directory of Open Access Journals (Sweden)

    Gong Shiaochin

    2009-03-01

    Full Text Available Abstract Background Reporter gene mice are valuable animal models for biological research providing a gene expression readout that can contribute to cellular characterization within the context of a developmental process. With the advancement of bacterial recombination techniques to engineer reporter gene constructs from BAC genomic clones and the generation of optically distinguishable fluorescent protein reporter genes, there is an unprecedented capability to engineer more informative transgenic reporter mouse models relative to what has been traditionally available. Results We demonstrate here our first effort on the development of a three stage bacterial recombination strategy to physically link multiple genes together with their respective fluorescent protein (FP reporters in one DNA fragment. This strategy uses bacterial recombination techniques to: (1 subclone genes of interest into BAC linking vectors, (2 insert desired reporter genes into respective genes and (3 link different gene-reporters together. As proof of concept, we have generated a single DNA fragment containing the genes Trap, Dmp1, and Ibsp driving the expression of ECFP, mCherry, and Topaz FP reporter genes, respectively. Using this DNA construct, we have successfully generated transgenic reporter mice that retain two to three gene readouts. Conclusion The three stage methodology to link multiple genes with their respective fluorescent protein reporter works with reasonable efficiency. Moreover, gene linkage allows for their common chromosomal integration into a single locus. However, the testing of this multi-reporter DNA construct by transgenesis does suggest that the linkage of two different genes together, despite their large size, can still create a positional effect. We believe that gene choice, genomic DNA fragment size and the presence of endogenous insulator elements are critical variables.

  8. A BAC-bacterial recombination method to generate physically linked multiple gene reporter DNA constructs.

    Science.gov (United States)

    Maye, Peter; Stover, Mary Louise; Liu, Yaling; Rowe, David W; Gong, Shiaochin; Lichtler, Alexander C

    2009-03-13

    Reporter gene mice are valuable animal models for biological research providing a gene expression readout that can contribute to cellular characterization within the context of a developmental process. With the advancement of bacterial recombination techniques to engineer reporter gene constructs from BAC genomic clones and the generation of optically distinguishable fluorescent protein reporter genes, there is an unprecedented capability to engineer more informative transgenic reporter mouse models relative to what has been traditionally available. We demonstrate here our first effort on the development of a three stage bacterial recombination strategy to physically link multiple genes together with their respective fluorescent protein (FP) reporters in one DNA fragment. This strategy uses bacterial recombination techniques to: (1) subclone genes of interest into BAC linking vectors, (2) insert desired reporter genes into respective genes and (3) link different gene-reporters together. As proof of concept, we have generated a single DNA fragment containing the genes Trap, Dmp1, and Ibsp driving the expression of ECFP, mCherry, and Topaz FP reporter genes, respectively. Using this DNA construct, we have successfully generated transgenic reporter mice that retain two to three gene readouts. The three stage methodology to link multiple genes with their respective fluorescent protein reporter works with reasonable efficiency. Moreover, gene linkage allows for their common chromosomal integration into a single locus. However, the testing of this multi-reporter DNA construct by transgenesis does suggest that the linkage of two different genes together, despite their large size, can still create a positional effect. We believe that gene choice, genomic DNA fragment size and the presence of endogenous insulator elements are critical variables.

  9. Multiple genes encode the major surface glycoprotein of Pneumocystis carinii

    DEFF Research Database (Denmark)

    Kovacs, J A; Powell, F; Edman, J C

    1993-01-01

    The major surface antigen of Pneumocystis carinii, a life-threatening opportunistic pathogen in human immunodeficiency virus-infected patients, is an abundant glycoprotein that functions in host-organism interactions. A monoclonal antibody to this antigen is protective in animals, and thus this a...

  10. Gene-environment interaction involving recently identified colorectal cancer susceptibility loci

    Science.gov (United States)

    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

  11. Protein annotation from protein interaction networks and Gene Ontology.

    Science.gov (United States)

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

    2011-10-01

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

  12. The empirical content of models with multiple equilibria in economies with social interactions

    OpenAIRE

    Alberto Bisin; Andrea Moro; Giorgio Topa

    2011-01-01

    We study a general class of models with social interactions that might display multiple equilibria. We propose an estimation procedure for these models and evaluate its efficiency and computational feasibility relative to different approaches taken to the curse of dimensionality implied by the multiplicity. Using data on smoking among teenagers, we implement the proposed estimation procedure to understand how group interactions affect health-related choices. We find that interaction effects a...

  13. A non-inheritable maternal Cas9-based multiple-gene editing system in mice

    OpenAIRE

    Takayuki Sakurai; Akiko Kamiyoshi; Hisaka Kawate; Chie Mori; Satoshi Watanabe; Megumu Tanaka; Ryuichi Uetake; Masahiro Sato; Takayuki Shindo

    2016-01-01

    The CRISPR/Cas9 system is capable of editing multiple genes through one-step zygote injection. The preexisting method is largely based on the co-injection of Cas9 DNA (or mRNA) and guide RNAs (gRNAs); however, it is unclear how many genes can be simultaneously edited by this method, and a reliable means to generate transgenic (Tg) animals with multiple gene editing has yet to be developed. Here, we employed non-inheritable maternal Cas9 (maCas9) protein derived from Tg mice with systemic Cas9...

  14. Gene-Diet Interaction and Precision Nutrition in Obesity

    Directory of Open Access Journals (Sweden)

    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.

  15. A Convenient Cas9-based Conditional Knockout Strategy for Simultaneously Targeting Multiple Genes in Mouse.

    Science.gov (United States)

    Chen, Jiang; Du, Yinan; He, Xueyan; Huang, Xingxu; Shi, Yun S

    2017-03-31

    The most powerful way to probe protein function is to characterize the consequence of its deletion. Compared to conventional gene knockout (KO), conditional knockout (cKO) provides an advanced gene targeting strategy with which gene deletion can be performed in a spatially and temporally restricted manner. However, for most species that are amphiploid, the widely used Cre-flox conditional KO (cKO) system would need targeting loci in both alleles to be loxP flanked, which in practice, requires time and labor consuming breeding. This is considerably significant when one is dealing with multiple genes. CRISPR/Cas9 genome modulation system is advantaged in its capability in targeting multiple sites simultaneously. Here we propose a strategy that could achieve conditional KO of multiple genes in mouse with Cre recombinase dependent Cas9 expression. By transgenic construction of loxP-stop-loxP (LSL) controlled Cas9 (LSL-Cas9) together with sgRNAs targeting EGFP, we showed that the fluorescence molecule could be eliminated in a Cre-dependent manner. We further verified the efficacy of this novel strategy to target multiple sites by deleting c-Maf and MafB simultaneously in macrophages specifically. Compared to the traditional Cre-flox cKO strategy, this sgRNAs-LSL-Cas9 cKO system is simpler and faster, and would make conditional manipulation of multiple genes feasible.

  16. Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis.

    Science.gov (United States)

    Cava, Claudia; Bertoli, Gloria; Colaprico, Antonio; Olsen, Catharina; Bontempi, Gianluca; Castiglioni, Isabella

    2018-01-06

    Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network. We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study. Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.

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

    Directory of Open Access Journals (Sweden)

    Nicola eLopizzo

    2015-05-01

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

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

    Science.gov (United States)

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

    2017-03-31

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

  19. Social Peer Interactions in Persons with Profound Intellectual and Multiple Disabilities: A Literature Review

    Science.gov (United States)

    Nijs, Sara; Maes, Bea

    2014-01-01

    Social interactions may positively influence developmental and quality of life outcomes. Research in persons with profound intellectual and multiple disabilities (PIMD) mostly investigated interactions with caregivers. This literature review focuses on peer interactions of persons with PIMD. A computerized literature search of three databases was…

  20. Identification of multiple FXYD genes in a teleost fish

    DEFF Research Database (Denmark)

    Tipsmark, Christian Kølbæk; Madsen, Steffen

    2007-01-01

    It is increasingly clear, that alterations in Na+,K+-ATPase kinetics to fit the demands in specialized cell types is vital for the enzyme to execute its different physiological roles in diverse tissues. In addition to tissue dependent expression of isoforms of the conventional subunits, and a and ß...... the tissue dependent expression of the different isoforms in gill, kidney, intestine, heart, muscle, brain and liver. When inspecting the relative expression levels we found, that while two isoforms were detected at comparable levels in several of the examined tissues, 6 isoforms were expressed in a more...... discrete manner. In excitatory tissues, two isoforms were highly expressed in brain and one in skeletal muscle. In osmoregulatory tissues, one isoform was expressed predominantly in gill, one in kidney and one equally in kidney and intestine. We observed that expression of several FXYD genes in kidney...

  1. 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

  2. Potential games and interactive decisions with multiple criteria

    NARCIS (Netherlands)

    Voorneveld, M.

    1999-01-01

    Game theory is a mathematical theory for analyzing strategic interaction between decision makers. This thesis covers two game-theoretic topics. The first part of this thesis deals with potential games: noncooperative games in which the information about the goals of the separate players that is

  3. Framework for Modelling Multiple Input Complex Aggregations for Interactive Installations

    DEFF Research Database (Denmark)

    Padfield, Nicolas; Andreasen, Troels

    2012-01-01

    on fuzzy logic and provides a method for variably balancing interaction and user input with the intention of the artist or director. An experimental design is presented, demonstrating an intuitive interface for parametric modelling of a complex aggregation function. The aggregation function unifies...

  4. Legumes affect alpine tundra community composition via multiple biotic interactions

    NARCIS (Netherlands)

    Soudzilovskaia, N.A.; Aksenova, A.A.; Makarov, M.I.; Onipchenko, V.G.; Logvinenko, O.A.; Braak, ter C.J.F.; Cornelissen, J.H.C.

    2012-01-01

    The soil engineering function of legumes in natural ecosystems is paramount but associated solely with soil nitrogen (N) subsidies, ignoring concomitant biotic interactions such as competitive or inhibitory effects and exchange between mycorrhizas and rhizobia. We aim to (1) disentangle legume

  5. Additive Main Effects and Multiplicative Interaction Analysis of ...

    African Journals Online (AJOL)

    This work deals with modeling and examining the GxE interaction pattern of the multi-environment trials of 43 genotypes and eight environments from Southern Ethiopia coffee (Coffea Arabica L.) collections using a randomized complete block design (RCBD) with four replications. The work further attempts to predict yield ...

  6. 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.

  7. Iron-related gene variants and brain iron in multiple sclerosis and healthy individuals

    Directory of Open Access Journals (Sweden)

    Jesper Hagemeier

    2018-01-01

    Full Text Available Brain iron homeostasis is known to be disturbed in multiple sclerosis (MS, yet little is known about the association of common gene variants linked to iron regulation and pathological tissue changes in the brain. In this study, we investigated the association of genetic determinants linked to iron regulation with deep gray matter (GM magnetic susceptibility in both healthy controls (HC and MS patients. Four hundred (400 patients with MS and 150 age- and sex-matched HCs were enrolled and obtained 3 T MRI examination. Three (3 single nucleotide polymorphisms (SNPs associated with iron regulation were genotyped: two SNPs in the human hereditary hemochromatosis protein gene HFE: rs1800562 (C282Y mutation and rs1799945 (H63D mutation, as well as the rs1049296 SNP in the transferrin gene (C2 mutation. The effects of disease and genetic status were studied using quantitative susceptibility mapping (QSM voxel-based analysis (VBA and region-of-interest (ROI analysis of the deep GM. The general linear model framework was used to compare groups. Analyses were corrected for age and sex, and adjusted for false discovery rate. We found moderate increases in susceptibility in the right putamen of participants with the C282Y (+6.1 ppb and H63D (+6.9 ppb gene variants vs. non-carriers, as well as a decrease in thalamic susceptibility of progressive MS patients with the C282Y mutation (left: −5.3 ppb, right: −6.7 ppb, p < 0.05. Female MS patients had lower susceptibility in the caudate (−6.0 ppb and putamen (left: −3.9 ppb, right: −4.6 ppb than men, but only when they had a wild-type allele (p < 0.05. Iron-gene linked increases in putamen susceptibility (in HC and relapsing remitting MS and decreases in thalamus susceptibility (in progressive MS, coupled with apparent sex interactions, indicate that brain iron in healthy and disease states may be influenced by genetic factors.

  8. Bayesian models and meta analysis for multiple tissue gene expression data following corticosteroid administration

    Directory of Open Access Journals (Sweden)

    Kelemen Arpad

    2008-08-01

    Full Text Available Abstract Background This paper addresses key biological problems and statistical issues in the analysis of large gene expression data sets that describe systemic temporal response cascades to therapeutic doses in multiple tissues such as liver, skeletal muscle, and kidney from the same animals. Affymetrix time course gene expression data U34A are obtained from three different tissues including kidney, liver and muscle. Our goal is not only to find the concordance of gene in different tissues, identify the common differentially expressed genes over time and also examine the reproducibility of the findings by integrating the results through meta analysis from multiple tissues in order to gain a significant increase in the power of detecting differentially expressed genes over time and to find the differential differences of three tissues responding to the drug. Results and conclusion Bayesian categorical model for estimating the proportion of the 'call' are used for pre-screening genes. Hierarchical Bayesian Mixture Model is further developed for the identifications of differentially expressed genes across time and dynamic clusters. Deviance information criterion is applied to determine the number of components for model comparisons and selections. Bayesian mixture model produces the gene-specific posterior probability of differential/non-differential expression and the 95% credible interval, which is the basis for our further Bayesian meta-inference. Meta-analysis is performed in order to identify commonly expressed genes from multiple tissues that may serve as ideal targets for novel treatment strategies and to integrate the results across separate studies. We have found the common expressed genes in the three tissues. However, the up/down/no regulations of these common genes are different at different time points. Moreover, the most differentially expressed genes were found in the liver, then in kidney, and then in muscle.

  9. Environment-Gene interaction in common complex diseases: New approaches

    Directory of Open Access Journals (Sweden)

    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.

  10. 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

  11. Multiplicity distribution and multiplicity moment of black and grey particles in high energy nucleus–nucleus interactions

    International Nuclear Information System (INIS)

    Ghosh, Dipak; Deb, Argha; Datta, Utpal; Bhattacharyya, S.

    2011-01-01

    In this paper we have studied the multiplicity distribution of black and grey particles emitted from 16 O–AgBr interactions at 2.1 AGeV and 60 AGeV. We have also calculated the multiplicity moment up to the fifth order for both the interactions and for both kinds of emitted particles. The variation of multiplicity moment with the order number has been investigated. It is seen that in the case of black particles multiplicity moment up to fourth order remains almost constant as energy increases from 2.1 AGeV to 60 AGeV. Fifth order multiplicity moment increases insignificantly with energy. However in the case of grey particles no such constancy of multiplicity moment with energy of the projectile beam is obtained. Later we have extended our study on the basis of Regge–Mueller approach to find the existence of second order correlation during the emission of black as well as the grey particles. The second Mueller moment is found to be positive and it increases as energy increases in the case of black particles. On the contrary in the case of grey particles the second Mueller moment decreases with energy. It can be concluded that as energy increases correlation among the black particles increases. On the other hand with the increase of energy correlation among the grey particles is found to diminish. (author)

  12. Gene expression analysis of interferon-beta treatment in multiple sclerosis

    DEFF Research Database (Denmark)

    Sellebjerg, F.; Datta, P.; Larsen, J.

    2008-01-01

    by treatment with IFN-beta. We use DNA microarrays to study gene expression in 10 multiple sclerosis (MS) patients who began de novo treatment with IFN-beta. After the first injection of IFN-beta, the expression of 74 out of 3428 genes changed at least two-fold and statistically significantly (after Bonferroni......Treatment with interferon-beta (IFN-beta) induces the expression of hundreds of genes in blood mononuclear cells, and the expression of several genes has been proposed as a marker of the effect of treatment with IFN-beta. However, to date no molecules have been identified that are stably induced...

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

    Science.gov (United States)

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

    2017-08-18

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

  14. Multiplicative interaction of functional inflammasome genetic variants in determining the risk of gout.

    Science.gov (United States)

    McKinney, Cushla; Stamp, Lisa K; Dalbeth, Nicola; Topless, Ruth K; Day, Richard O; Kannangara, Diluk Rw; Williams, Kenneth M; Janssen, Matthijs; Jansen, Timothy L; Joosten, Leo A; Radstake, Timothy R; Riches, Philip L; Tausche, Anne-Kathrin; Lioté, Frederic; So, Alexander; Merriman, Tony R

    2015-10-13

    The acute gout flare results from a localised self-limiting innate immune response to monosodium urate (MSU) crystals deposited in joints in hyperuricaemic individuals. Activation of the caspase recruitment domain-containing protein 8 (CARD8) NOD-like receptor pyrin-containing 3 (NLRP3) inflammasome by MSU crystals and production of mature interleukin-1β (IL-1β) is central to acute gouty arthritis. However very little is known about genetic control of the innate immune response involved in acute gouty arthritis. Therefore our aim was to test functional single nucleotide polymorphism (SNP) variants in the toll-like receptor (TLR)-inflammasome-IL-1β axis for association with gout. 1,494 gout cases of European and 863 gout cases of New Zealand (NZ) Polynesian (Māori and Pacific Island) ancestry were included. Gout was diagnosed by the 1977 ARA gout classification criteria. There were 1,030 Polynesian controls and 10,942 European controls including from the publicly-available Atherosclerosis Risk in Communities (ARIC) and Framingham Heart (FHS) studies. The ten SNPs were either genotyped by Sequenom MassArray or by Affymetrix SNP array or imputed in the ARIC and FHS datasets. Allelic association was done by logistic regression adjusting by age and sex with European and Polynesian data combined by meta-analysis. Sample sets were pooled for multiplicative interaction analysis, which was also adjusted by sample set. Eleven SNPs were tested in the TLR2, CD14, IL1B, CARD8, NLRP3, MYD88, P2RX7, DAPK1 and TNXIP genes. Nominally significant (P gout were detected at CARD8 rs2043211 (OR = 1.12, P = 0.007), IL1B rs1143623 (OR = 1.10, P = 0.020) and CD14 rs2569190 (OR = 1.08; P = 0.036). There was significant multiplicative interaction between CARD8 and IL1B (P = 0.005), with the IL1B risk genotype amplifying the risk effect of CARD8. There is evidence for association of gout with functional variants in CARD8, IL1B and CD14. The gout-associated allele of IL1B increases

  15. Inelastic multiple scattering of interacting bosons in weak random potentials

    International Nuclear Information System (INIS)

    Geiger, Tobias

    2013-01-01

    Within the present thesis we develop a diagrammatic scattering theory for interacting bosons in a three-dimensional, weakly disordered potential. Based on a microscopic N-body scattering theory, we identify the relevant diagrams including elastic and inelastic collision processes that are sufficient to describe quantum transport in the regime of weak disorder. By taking advantage of the statistical properties of the weak disorder potential, we demonstrate how the N-body dynamics can be reduced to a nonlinear integral equation of Boltzmann type for the single-particle diffusive flux. A presently available alternative description - based on the Gross-Pitaevskii equation - only includes elastic collisions. In contrast, we show that far from equilibrium the presence of inelastic collisions - even for weak interaction strength - must be accounted for and can induce the full thermalization of the single-particle current. In addition, we also determine the coherent corrections to the incoherent transport, leading to the effect of coherent backscattering. For the first time, we are able to analyze the influence of inelastic collisions on the coherent backscattering signal, which lead to an enhancement of the backscattered cone in a narrow spectral window, even for increasing non-linearity. With a short recollection of the presently available experimental techniques we furthermore show how an immediate implementation of our suggested setup with confined Bose-Einstein condensates can be accomplished. Thereby, the emergence of collective and/or thermodynamic behavior from fundamental, microscopic constituents can also be assessed experimentally. In a second part of this thesis, we present first results for light scattering off strongly interacting Rydberg atoms trapped in a one-dimensional, chain-like configuration. In order to monitor the time-dependence of this interacting many-body system, we devise a weak measurement scenario for which we derive a master equation for the

  16. Exclusive description of multiple production on nuclei in the additive quark model. Multiplicity distributions in interactions with heavy nuclei

    International Nuclear Information System (INIS)

    Levchenko, B.B.; Nikolaev, N.N.

    1985-01-01

    In the framework of the additive quark model of multiple production on nuclei we calculate the multiplicity distributions of secondary particles and the correlations between secondary particles in πA and pA interactions with heavy nuclei. We show that intranuclear cascades are responsible for up to 50% of the nuclear increase of the multiplicity of fast particles. We analyze the sensitivity of the multiplicities and their correlations to the choice of the quark-hadronization function. We show that with good accuracy the yield of relativistic secondary particles from heavy and intermediate nuclei depends only on the number N/sub p/ of protons knocked out of the nucleus, and not on the mass number of the nucleus (N/sub p/ scaling)

  17. Multiple post-transcriptional regulatory mechanisms in ferritin gene expression

    International Nuclear Information System (INIS)

    Mattia, E.; Den Blaauwen, J.; Van Renswoude, J.; Ashwell, G.

    1989-01-01

    The authors have investigated the mechanisms involved in the regulation of ferritin biosynthesis in K562 human erythroleukemia cells during prolonged exposure to iron. They show that, upon addition of hemin (an efficient iron donor) to the cell culture, the rate of ferritin biosynthesis reaches a maximum after a few hours and then decreases. During a 24-hr incubation with the iron donor the concentrations of total ferritin heavy (H) and light (L) subunit mRNAs rise 2- to 5-fold and 2- to 3-fold, respectively, over the control values, while the amount of the protein increases 10- to 30-fold. The hemin-induced increment in ferritin subunit mRNA is not prevented by deferoxamine, suggesting that it is not directly mediated by chelatable iron. In vitro nuclear transcription analyses performed on nuclei isolated from control cells and cells grown in the presence of hemin indicate that the rates of synthesis of H- and L-subunit mRNAs remain constant. They conclude that iron-induced ferritin biosynthesis is governed by multiple post-transcriptional regulatory mechanisms. They propose that exposure of cells to iron leads to stabilization of ferritin mRNAs, in addition to activation and translation of stored H-and L-subunit mRNAs

  18. 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 ...

  19. Sleep Duration and Depressive Symptoms: A Gene-Environment Interaction

    Science.gov (United States)

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

    2014-01-01

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

  20. Random regression models for detection of gene by environment interaction

    Directory of Open Access Journals (Sweden)

    Meuwissen Theo HE

    2007-02-01

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

  1. 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.

  2. 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

  3. Biological interactions and cooperative management of multiple species.

    Science.gov (United States)

    Jiang, Jinwei; Min, Yong; Chang, Jie; Ge, Ying

    2017-01-01

    Coordinated decision making and actions have become the primary solution for the overexploitation of interacting resources within ecosystems. However, the success of coordinated management is highly sensitive to biological, economic, and social conditions. Here, using a game theoretic framework and a 2-species model that considers various biological relationships (competition, predation, and mutualism), we compute cooperative (or joint) and non-cooperative (or separate) management equilibrium outcomes of the model and investigate the effects of the type and strength of the relationships. We find that cooperation does not always show superiority to non-cooperation in all biological interactions: (1) if and only if resources are involved in high-intensity predation relationships, cooperation can achieve a win-win scenario for ecosystem services and resource diversity; (2) for competitive resources, cooperation realizes higher ecosystem services by sacrificing resource diversity; and (3) for mutual resources, cooperation has no obvious advantage for either ecosystem services or resource evenness but can slightly improve resource abundance. Furthermore, by using a fishery model of the North California Current Marine Ecosystem with 63 species and seven fleets, we demonstrate that the theoretical results can be reproduced in real ecosystems. Therefore, effective ecosystem management should consider the interconnection between stakeholders' social relationship and resources' biological relationships.

  4. Effect of Gene and Physical Activity Interaction on Trunk Fat Percentage Among the Newfoundland Population

    Directory of Open Access Journals (Sweden)

    Anthony Payne

    2014-01-01

    Full Text Available Objective To explore the effect of FTO gene and physical activity interaction on trunk fat percentage. Design and Methods Subjects are 3,004 individuals from Newfoundland and Labrador whose trunk fat percentage and physical activity were recorded, and who were genotyped for 11 single-nucleotide polymorphisms (SNPs in the FTO gene. Subjects were stratified by gender. Multiple tests and multiple regressions were used to analyze the effects of physical activity, variants of FTO , age, and their interactions on trunk fat percentage. Dietary information and other environmental factors were not considered. Results Higher levels of physical activity tend to reduce trunk fat percentage in all individuals. Furthermore, in males, rs9939609 and rs1421085 were significant (α = 0.05 in explaining central body fat, but no SNPs were significant in females. For highly active males, trunk fat percentage varied significantly between variants of rs9939609 and rs1421085, but there is no significant effect among individuals with low activity. The other SNPs examined were not significant in explaining trunk fat percentage. Conclusions Homozygous male carriers of non-obesity risk alleles at rs9939609 and rs1421085 will have significant reduction in central body fat from physical activity in contrast to homozygous males of the obesity-risk alleles. The additive effect of these SNPs is found in males with high physical activity only.

  5. Univariate and multiple linear regression analyses for 23 single nucleotide polymorphisms in 14 genes predisposing to chronic glomerular diseases and IgA nephropathy in Han Chinese.

    Science.gov (United States)

    Wang, Hui; Sui, Weiguo; Xue, Wen; Wu, Junyong; Chen, Jiejing; Dai, Yong

    2014-09-01

    Immunoglobulin A nephropathy (IgAN) is a complex trait regulated by the interaction among multiple physiologic regulatory systems and probably involving numerous genes, which leads to inconsistent findings in genetic studies. One possibility of failure to replicate some single-locus results is that the underlying genetics of IgAN nephropathy is based on multiple genes with minor effects. To learn the association between 23 single nucleotide polymorphisms (SNPs) in 14 genes predisposing to chronic glomerular diseases and IgAN in Han males, the 23 SNPs genotypes of 21 Han males were detected and analyzed with a BaiO gene chip, and their associations were analyzed with univariate analysis and multiple linear regression analysis. Analysis showed that CTLA4 rs231726 and CR2 rs1048971 revealed a significant association with IgAN. These findings support the multi-gene nature of the etiology of IgAN and propose a potential gene-gene interactive model for future studies.

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

    Science.gov (United States)

    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

  7. Speech comprehension aided by multiple modalities: behavioural and neural interactions

    Science.gov (United States)

    McGettigan, Carolyn; Faulkner, Andrew; Altarelli, Irene; Obleser, Jonas; Baverstock, Harriet; Scott, Sophie K.

    2014-01-01

    Speech comprehension is a complex human skill, the performance of which requires the perceiver to combine information from several sources – e.g. voice, face, gesture, linguistic context – to achieve an intelligible and interpretable percept. We describe a functional imaging investigation of how auditory, visual and linguistic information interact to facilitate comprehension. Our specific aims were to investigate the neural responses to these different information sources, alone and in interaction, and further to use behavioural speech comprehension scores to address sites of intelligibility-related activation in multifactorial speech comprehension. In fMRI, participants passively watched videos of spoken sentences, in which we varied Auditory Clarity (with noise-vocoding), Visual Clarity (with Gaussian blurring) and Linguistic Predictability. Main effects of enhanced signal with increased auditory and visual clarity were observed in overlapping regions of posterior STS. Two-way interactions of the factors (auditory × visual, auditory × predictability) in the neural data were observed outside temporal cortex, where positive signal change in response to clearer facial information and greater semantic predictability was greatest at intermediate levels of auditory clarity. Overall changes in stimulus intelligibility by condition (as determined using an independent behavioural experiment) were reflected in the neural data by increased activation predominantly in bilateral dorsolateral temporal cortex, as well as inferior frontal cortex and left fusiform gyrus. Specific investigation of intelligibility changes at intermediate auditory clarity revealed a set of regions, including posterior STS and fusiform gyrus, showing enhanced responses to both visual and linguistic information. Finally, an individual differences analysis showed that greater comprehension performance in the scanning participants (measured in a post-scan behavioural test) were associated with

  8. Environmental and gene-environment interactions and risk of rheumatoid arthritis

    Science.gov (United States)

    Karlson, Elizabeth W.; Deane, Kevin

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Chen Xin

    2012-10-01

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

  10. Meta-Analysis of Multiple Sclerosis Microarray Data Reveals Dysregulation in RNA Splicing Regulatory Genes

    Directory of Open Access Journals (Sweden)

    Elvezia Maria Paraboschi

    2015-09-01

    Full Text Available Abnormalities in RNA metabolism and alternative splicing (AS are emerging as important players in complex disease phenotypes. In particular, accumulating evidence suggests the existence of pathogenic links between multiple sclerosis (MS and altered AS, including functional studies showing that an imbalance in alternatively-spliced isoforms may contribute to disease etiology. Here, we tested whether the altered expression of AS-related genes represents a MS-specific signature. A comprehensive comparative analysis of gene expression profiles of publicly-available microarray datasets (190 MS cases, 182 controls, followed by gene-ontology enrichment analysis, highlighted a significant enrichment for differentially-expressed genes involved in RNA metabolism/AS. In detail, a total of 17 genes were found to be differentially expressed in MS in multiple datasets, with CELF1 being dysregulated in five out of seven studies. We confirmed CELF1 downregulation in MS (p = 0.0015 by real-time RT-PCRs on RNA extracted from blood cells of 30 cases and 30 controls. As a proof of concept, we experimentally verified the unbalance in alternatively-spliced isoforms in MS of the NFAT5 gene, a putative CELF1 target. In conclusion, for the first time we provide evidence of a consistent dysregulation of splicing-related genes in MS and we discuss its possible implications in modulating specific AS events in MS susceptibility genes.

  11. IVisTMSA: Interactive Visual Tools for Multiple Sequence Alignments.

    Science.gov (United States)

    Pervez, Muhammad Tariq; Babar, Masroor Ellahi; Nadeem, Asif; Aslam, Naeem; Naveed, Nasir; Ahmad, Sarfraz; Muhammad, Shah; Qadri, Salman; Shahid, Muhammad; Hussain, Tanveer; Javed, Maryam

    2015-01-01

    IVisTMSA is a software package of seven graphical tools for multiple sequence alignments. MSApad is an editing and analysis tool. It can load 409% more data than Jalview, STRAP, CINEMA, and Base-by-Base. MSA comparator allows the user to visualize consistent and inconsistent regions of reference and test alignments of more than 21-MB size in less than 12 seconds. MSA comparator is 5,200% efficient and more than 40% efficient as compared to BALiBASE c program and FastSP, respectively. MSA reconstruction tool provides graphical user interfaces for four popular aligners and allows the user to load several sequence files at a time. FASTA generator converts seven formats of alignments of unlimited size into FASTA format in a few seconds. MSA ID calculator calculates identity matrix of more than 11,000 sequences with a sequence length of 2,696 base pairs in less than 100 seconds. Tree and Distance Matrix calculation tools generate phylogenetic tree and distance matrix, respectively, using neighbor joining% identity and BLOSUM 62 matrix.

  12. Characterization of osteopontin-uranyl interaction: role of multiple phosphorylations

    International Nuclear Information System (INIS)

    Qi, Lei

    2014-01-01

    While some metals are essential for Life, other ones are only toxicants for living organisms, tolerated below well-definite concentrations. This is the case for uranium, a natural element which has no known biological function. It is a low α emitter and its chemical toxicity rather than its radiological toxicity is a subject of concern. Once in the body, this metal reaches the blood and accumulates in the bones under the action of unknown mechanisms. Uranium mainly exists in form of uranyl ion (UO 2 2+ ) in aqueous media and particularly reacts with carboxylates, phenolates and phosphates of the proteins. Previous studies have highlighted that UO 2 2+ modulates the SPP1 expression, a gene which codes for osteopontin (OPN). This highly phosphorylated glycoprotein plays an important role in bone homeostasis. This role and its biochemical properties led us to hypothesize that OPN might be a potential target of UO 2 2+ and involved in its accumulation in bones. A simple and original purification process was optimized to produce very highly purified OPN starting from human and bovine milk. Various biophysical approaches were set up and confirmed that both bovine and human OPN display very high affinity for UO 2 2+ . Moreover, the formation of stable UO 2 -protein complexes originating from structural changes was evidenced. The major role of phosphorylations, both on the OPN's affinity for UO 2 2+ and the stability of the UO 2 -protein complexes, was confirmed. These results demonstrate that OPN presents all the characteristics to be a major UO 2 2+ binding-protein in vitro, and they open new insights in the understanding of the UO 2 2+ mineralization process mechanisms. (author) [fr

  13. The SH2D2A gene and susceptibility to multiple sclerosis

    DEFF Research Database (Denmark)

    Lorentzen, A.R.; Smestad, C.; Lie, B.A.

    2008-01-01

    We previously reported an association between the SH2D2A gene encoding TSAd and multiple sclerosis (MS). Here a total of 2128 Nordic MS patients and 2004 controls were genotyped for the SH2D2A promoter GA repeat polymorphism and rs926103 encoding a serine to asparagine substitution at amino acid...... that the SH2D2A gene may contribute to susceptibility to MS Udgivelsesdato: 2008/7/15...

  14. Learning Effects of Interactive Whiteboard Pedagogy for Students in Taiwan from the Perspective of Multiple Intelligences

    Science.gov (United States)

    Chen, Hong-Ren; Chiang, Chih-Hao; Lin, Wen-Shan

    2013-01-01

    With the rapid progress in information technology, interactive whiteboards have become IT-integrated in teaching activities. The theory of multiple intelligences argues that every person possesses multiple intelligences, emphasizing learners' cognitive richness and the possible role of these differences in enhanced learning. This study is the…

  15. Identification of multiple sites suitable for insertion of foreign genes in herpes simplex virus genomes.

    Science.gov (United States)

    Morimoto, Tomomi; Arii, Jun; Akashi, Hiroomi; Kawaguchi, Yasushi

    2009-03-01

    Information on sites in HSV genomes at which foreign gene(s) can be inserted without disrupting viral genes or affecting properties of the parental virus are important for basic research on HSV and development of HSV-based vectors for human therapy. The intergenic region between HSV-1 UL3 and UL4 genes has been reported to satisfy the requirements for such an insertion site. The UL3 and UL4 genes are oriented toward the intergenic region and, therefore, insertion of a foreign gene(s) into the region between the UL3 and UL4 polyadenylation signals should not disrupt any viral genes or transcriptional units. HSV-1 and HSV-2 each have more than 10 additional regions structurally similar to the intergenic region between UL3 and UL4. In the studies reported here, it has been demonstrated that insertion of a reporter gene expression cassette into several of the HSV-1 and HSV-2 intergenic regions has no effect on viral growth in cell culture or virulence in mice, suggesting that these multiple intergenic regions may be suitable HSV sites for insertion of foreign genes.

  16. Flexibility and Project Value: Interactions and Multiple Real Options

    Science.gov (United States)

    Čulík, Miroslav

    2010-06-01

    This paper is focused on a project valuation with embedded portfolio of real options including their interactions. Valuation is based on the criterion of Net Present Value on the simulation basis. Portfolio includes selected types of European-type real options: option to expand, contract, abandon and temporarily shut down and restart a project. Due to the fact, that in reality most of the managerial flexibility takes the form of portfolio of real options, selected types of options are valued not only individually, but also in combination. The paper is structured as follows: first, diffusion models for forecasting of output prices and variable costs are derived. Second, project value is estimated on the assumption, that no real options are present. Next, project value is calculated with the presence of selected European-type options; these options and their impact on project value are valued first in isolation and consequently in different combinations. Moreover, intrinsic value evolution of given real options with respect to the time of exercising is analysed. In the end, results are presented graphically; selected statistics and risk measures (Value at Risk, Expected Shortfall) of the NPV's distributions are calculated and commented.

  17. Gene-gene and gene-environment interactions in prostate, breast and colorectal cancer

    DEFF Research Database (Denmark)

    Kopp, Tine Iskov

    The incidence of cancer in the western world has increased steeply during the last 50 years. For three of the most prevalent cancer types in Denmark, prostate, breast and colorectal cancer (PC, BC and CRC, respectively), only a small fraction (1-15%) of the incidences are caused by highly penetrant...... in alcohol-related BC in postmenopausal women involving a specific polymorphism in PPARG (coding the peroxisome proliferatoractivated receptor (PPARγ)) and its interaction with the aromatase (encoded by CYP19A1) was investigated (Paper V-VI). The Danish prospective “Diet, Cancer and Health” cohort study...... as having strong influence on carcinogenesis. Therefore, very frequent, low effect polymorphisms may have a greater contribution on a population level in combination with environmental factors. Indeed, several dietary and life style factors are now well-established risk factors for different cancer types...

  18. Novel method to load multiple genes onto a mammalian artificial chromosome.

    Science.gov (United States)

    Tóth, Anna; Fodor, Katalin; Praznovszky, Tünde; Tubak, Vilmos; Udvardy, Andor; Hadlaczky, Gyula; Katona, Robert L

    2014-01-01

    Mammalian artificial chromosomes are natural chromosome-based vectors that may carry a vast amount of genetic material in terms of both size and number. They are reasonably stable and segregate well in both mitosis and meiosis. A platform artificial chromosome expression system (ACEs) was earlier described with multiple loading sites for a modified lambda-integrase enzyme. It has been shown that this ACEs is suitable for high-level industrial protein production and the treatment of a mouse model for a devastating human disorder, Krabbe's disease. ACEs-treated mutant mice carrying a therapeutic gene lived more than four times longer than untreated counterparts. This novel gene therapy method is called combined mammalian artificial chromosome-stem cell therapy. At present, this method suffers from the limitation that a new selection marker gene should be present for each therapeutic gene loaded onto the ACEs. Complex diseases require the cooperative action of several genes for treatment, but only a limited number of selection marker genes are available and there is also a risk of serious side-effects caused by the unwanted expression of these marker genes in mammalian cells, organs and organisms. We describe here a novel method to load multiple genes onto the ACEs by using only two selectable marker genes. These markers may be removed from the ACEs before therapeutic application. This novel technology could revolutionize gene therapeutic applications targeting the treatment of complex disorders and cancers. It could also speed up cell therapy by allowing researchers to engineer a chromosome with a predetermined set of genetic factors to differentiate adult stem cells, embryonic stem cells and induced pluripotent stem (iPS) cells into cell types of therapeutic value. It is also a suitable tool for the investigation of complex biochemical pathways in basic science by producing an ACEs with several genes from a signal transduction pathway of interest.

  19. Novel method to load multiple genes onto a mammalian artificial chromosome.

    Directory of Open Access Journals (Sweden)

    Anna Tóth

    Full Text Available Mammalian artificial chromosomes are natural chromosome-based vectors that may carry a vast amount of genetic material in terms of both size and number. They are reasonably stable and segregate well in both mitosis and meiosis. A platform artificial chromosome expression system (ACEs was earlier described with multiple loading sites for a modified lambda-integrase enzyme. It has been shown that this ACEs is suitable for high-level industrial protein production and the treatment of a mouse model for a devastating human disorder, Krabbe's disease. ACEs-treated mutant mice carrying a therapeutic gene lived more than four times longer than untreated counterparts. This novel gene therapy method is called combined mammalian artificial chromosome-stem cell therapy. At present, this method suffers from the limitation that a new selection marker gene should be present for each therapeutic gene loaded onto the ACEs. Complex diseases require the cooperative action of several genes for treatment, but only a limited number of selection marker genes are available and there is also a risk of serious side-effects caused by the unwanted expression of these marker genes in mammalian cells, organs and organisms. We describe here a novel method to load multiple genes onto the ACEs by using only two selectable marker genes. These markers may be removed from the ACEs before therapeutic application. This novel technology could revolutionize gene therapeutic applications targeting the treatment of complex disorders and cancers. It could also speed up cell therapy by allowing researchers to engineer a chromosome with a predetermined set of genetic factors to differentiate adult stem cells, embryonic stem cells and induced pluripotent stem (iPS cells into cell types of therapeutic value. It is also a suitable tool for the investigation of complex biochemical pathways in basic science by producing an ACEs with several genes from a signal transduction pathway of interest.

  20. A Hox Gene, Antennapedia, Regulates Expression of Multiple Major Silk Protein Genes in the Silkworm Bombyx mori.

    Science.gov (United States)

    Tsubota, Takuya; Tomita, Shuichiro; Uchino, Keiro; Kimoto, Mai; Takiya, Shigeharu; Kajiwara, Hideyuki; Yamazaki, Toshimasa; Sezutsu, Hideki

    2016-03-25

    Hoxgenes play a pivotal role in the determination of anteroposterior axis specificity during bilaterian animal development. They do so by acting as a master control and regulating the expression of genes important for development. Recently, however, we showed that Hoxgenes can also function in terminally differentiated tissue of the lepidopteranBombyx mori In this species,Antennapedia(Antp) regulates expression of sericin-1, a major silk protein gene, in the silk gland. Here, we investigated whether Antpcan regulate expression of multiple genes in this tissue. By means of proteomic, RT-PCR, and in situ hybridization analyses, we demonstrate that misexpression of Antpin the posterior silk gland induced ectopic expression of major silk protein genes such assericin-3,fhxh4, and fhxh5 These genes are normally expressed specifically in the middle silk gland as is Antp Therefore, the evidence strongly suggests that Antpactivates these silk protein genes in the middle silk gland. The putativesericin-1 activator complex (middle silk gland-intermolt-specific complex) can bind to the upstream regions of these genes, suggesting that Antpdirectly activates their expression. We also found that the pattern of gene expression was well conserved between B. moriand the wild species Bombyx mandarina, indicating that the gene regulation mechanism identified here is an evolutionarily conserved mechanism and not an artifact of the domestication of B. mori We suggest that Hoxgenes have a role as a master control in terminally differentiated tissues, possibly acting as a primary regulator for a range of physiological processes. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

  1. 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.

  2. Study of oral clefts: Indication of gene-environment interaction

    Energy Technology Data Exchange (ETDEWEB)

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

    1994-09-01

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

  3. Protein-Protein Interaction Network and Gene Ontology

    Science.gov (United States)

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

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

  4. Attentional Processes in Interactions between People with Profound Intellectual and Multiple Disabilities and Direct Support Staff

    Science.gov (United States)

    Ine, Hostyn; Heleen, Neerinckx; Bea, Maes

    2011-01-01

    Few studies have examined joint attention in interactions with persons with profound intellectual and multiple disabilities (PIMD), despite its important role in high-quality interaction. The purpose of this study is to describe the attention-directing behaviours of persons with PIMD and their direct support staff and the attention episodes…

  5. Interaction between Persons with Profound Intellectual and Multiple Disabilities and Their Partners: A Literature Review

    Science.gov (United States)

    Hostyn, Ine; Maes, Bea

    2009-01-01

    Background: High quality interactions are of crucial importance for quality of life of persons with profound intellectual and multiple disabilities (PIMD). This literature review describes and synthesises studies addressing the interaction between persons with PIMD and their partners. Method: A computerised literature search using defined…

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

    Science.gov (United States)

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

    2016-01-01

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

  7. Log-Normal Distribution in a Growing System with Weighted and Multiplicatively Interacting Particles

    Science.gov (United States)

    Fujihara, Akihiro; Tanimoto, Satoshi; Yamamoto, Hiroshi; Ohtsuki, Toshiya

    2018-03-01

    A growing system with weighted and multiplicatively interacting particles is investigated. Each particle has a quantity that changes multiplicatively after a binary interaction, with its growth rate controlled by a weight parameter in a homogeneous symmetric kernel. We consider the system using moment inequalities and analytically derive the log-normal-type tail in the probability distribution function of quantities when the parameter is negative, which is different from the result for single-body multiplicative processes. We also find that the system approaches a winner-take-all state when the parameter is positive.

  8. 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.

  9. M-GCAT: interactively and efficiently constructing large-scale multiple genome comparison frameworks in closely related species

    Directory of Open Access Journals (Sweden)

    Messeguer Xavier

    2006-10-01

    Full Text Available Abstract Background Due to recent advances in whole genome shotgun sequencing and assembly technologies, the financial cost of decoding an organism's DNA has been drastically reduced, resulting in a recent explosion of genomic sequencing projects. This increase in related genomic data will allow for in depth studies of evolution in closely related species through multiple whole genome comparisons. Results To facilitate such comparisons, we present an interactive multiple genome comparison and alignment tool, M-GCAT, that can efficiently construct multiple genome comparison frameworks in closely related species. M-GCAT is able to compare and identify highly conserved regions in up to 20 closely related bacterial species in minutes on a standard computer, and as many as 90 (containing 75 cloned genomes from a set of 15 published enterobacterial genomes in an hour. M-GCAT also incorporates a novel comparative genomics data visualization interface allowing the user to globally and locally examine and inspect the conserved regions and gene annotations. Conclusion M-GCAT is an interactive comparative genomics tool well suited for quickly generating multiple genome comparisons frameworks and alignments among closely related species. M-GCAT is freely available for download for academic and non-commercial use at: http://alggen.lsi.upc.es/recerca/align/mgcat/intro-mgcat.html.

  10. Immuno-Oncology-The Translational Runway for Gene Therapy: Gene Therapeutics to Address Multiple Immune Targets.

    Science.gov (United States)

    Weß, Ludger; Schnieders, Frank

    2017-12-01

    Cancer therapy is once again experiencing a paradigm shift. This shift is based on extensive clinical experience demonstrating that cancer cannot be successfully fought by addressing only single targets or pathways. Even the combination of several neo-antigens in cancer vaccines is not sufficient for successful, lasting tumor eradication. The focus has therefore shifted to the immune system's role in cancer and the striking abilities of cancer cells to manipulate and/or deactivate the immune system. Researchers and pharma companies have started to target the processes and cells known to support immune surveillance and the elimination of tumor cells. Immune processes, however, require novel concepts beyond the traditional "single-target-single drug" paradigm and need parallel targeting of diverse cells and mechanisms. This review gives a perspective on the role of gene therapy technologies in the evolving immuno-oncology space and identifies gene therapy as a major driver in the development and regulation of effective cancer immunotherapy. Present challenges and breakthroughs ranging from chimeric antigen receptor T-cell therapy, gene-modified oncolytic viruses, combination cancer vaccines, to RNA therapeutics are spotlighted. Gene therapy is recognized as the most prominent technology enabling effective immuno-oncology strategies.

  11. Gene expression profiling for molecular classification of multiple myeloma in newly diagnosed patients

    NARCIS (Netherlands)

    Broyl, Annemiek; Hose, Dirk; Lokhorst, Henk; de Knegt, Yvonne; Peeters, Justine; Jauch, Anna; Bertsch, Uta; Buijs, Arjan; Stevens-Kroef, Marian; Beverloo, H. Berna; Vellenga, Edo; Zweegman, Sonja; Kersten, Marie-Josée; van der Holt, Bronno; el Jarari, Laila; Mulligan, George; Goldschmidt, Hartmut; van Duin, Mark; Sonneveld, Pieter

    2010-01-01

    To identify molecularly defined subgroups in multiple myeloma, gene expression profiling was performed on purified CD138(+) plasma cells of 320 newly diagnosed myeloma patients included in the Dutch-Belgian/German HOVON-65/GMMG-HD4 trial. Hierarchical clustering identified 10 subgroups; 6

  12. Scaling of chaotic multiplicity: A new observation in high-energy interactions

    International Nuclear Information System (INIS)

    Ghosh, D.; Ghosh, P.; Roy, J.

    1990-01-01

    We analyze high-energy-interaction data to study the dependence of chaotic multiplicity on the pseudorapidity window and propose a new scaling function bar Ψ(bar z)=left-angle n 1 right-angle/left-angle n right-angle max where left-angle n 1 right-angle is the chaotic multiplicity and bar z=left-angle n right-angle/left-angle n right-angle max is the reduced multiplicity, following the quantum-optical concept of particle production. It has been observed that the proposed ''chaotic multiplicity scaling'' is obeyed by pp, p bar p, and AA collisions at different available energies

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

    Directory of Open Access Journals (Sweden)

    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.

  14. 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.

    Directory of Open Access Journals (Sweden)

    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

  15. Cell-Specific PEAR1 Methylation Studies Reveal a Locus that Coordinates Expression of Multiple Genes

    Directory of Open Access Journals (Sweden)

    Benedetta Izzi

    2018-04-01

    Full Text Available Chromosomal interactions connect distant enhancers and promoters on the same chromosome, activating or repressing gene expression. PEAR1 encodes the Platelet-Endothelial Aggregation Receptor 1, a contact receptor involved in platelet function and megakaryocyte and endothelial cell proliferation. PEAR1 expression during megakaryocyte differentiation is controlled by DNA methylation at its first CpG island. We identified a PEAR1 cell-specific methylation sensitive region in endothelial cells and megakaryocytes that showed strong chromosomal interactions with ISGL20L2, RRNAD1, MRLP24, HDGF and PRCC, using available promoter capture Hi-C datasets. These genes are involved in ribosome processing, protein synthesis, cell cycle and cell proliferation. We next studied the methylation and expression profile of these five genes in Human Umbilical Vein Endothelial Cells (HUVECs and megakaryocyte precursors. While cell-specific PEAR1 methylation corresponded to variability in expression for four out of five genes, no methylation change was observed in their promoter regions across cell types. Our data suggest that PEAR1 cell-type specific methylation changes may control long distance interactions with other genes. Further studies are needed to show whether such interaction data might be relevant for the genome-wide association data that showed a role for non-coding PEAR1 variants in the same region and platelet function, platelet count and cardiovascular risk.

  16. Association of circadian rhythm genes ARNTL/BMAL1 and CLOCK with multiple sclerosis.

    Directory of Open Access Journals (Sweden)

    Polona Lavtar

    Full Text Available Prevalence of multiple sclerosis varies with geographic latitude. We hypothesized that this fact might be partially associated with the influence of latitude on circadian rhythm and consequently that genetic variability of key circadian rhythm regulators, ARNTL and CLOCK genes, might contribute to the risk for multiple sclerosis. Our aim was to analyse selected polymorphisms of ARNTL and CLOCK, and their association with multiple sclerosis. A total of 900 Caucasian patients and 1024 healthy controls were compared for genetic signature at 8 SNPs, 4 for each of both genes. We found a statistically significant difference in genotype (ARNTL rs3789327, P = 7.5·10-5; CLOCK rs6811520 P = 0.02 distributions in patients and controls. The ARNTL rs3789327 CC genotype was associated with higher risk for multiple sclerosis at an OR of 1.67 (95% CI 1.35-2.07, P = 0.0001 and the CLOCK rs6811520 genotype CC at an OR of 1.40 (95% CI 1.13-1.73, P = 0.002. The results of this study suggest that genetic variability in the ARNTL and CLOCK genes might be associated with risk for multiple sclerosis.

  17. Circadian Enhancers Coordinate Multiple Phases of Rhythmic Gene Transcription In Vivo

    Science.gov (United States)

    Fang, Bin; Everett, Logan J.; Jager, Jennifer; Briggs, Erika; Armour, Sean M.; Feng, Dan; Roy, Ankur; Gerhart-Hines, Zachary; Sun, Zheng; Lazar, Mitchell A.

    2014-01-01

    SUMMARY Mammalian transcriptomes display complex circadian rhythms with multiple phases of gene expression that cannot be accounted for by current models of the molecular clock. We have determined the underlying mechanisms by measuring nascent RNA transcription around the clock in mouse liver. Unbiased examination of eRNAs that cluster in specific circadian phases identified functional enhancers driven by distinct transcription factors (TFs). We further identify on a global scale the components of the TF cistromes that function to orchestrate circadian gene expression. Integrated genomic analyses also revealed novel mechanisms by which a single circadian factor controls opposing transcriptional phases. These findings shed new light on the diversity and specificity of TF function in the generation of multiple phases of circadian gene transcription in a mammalian organ. PMID:25416951

  18. 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

  19. Oscillations in the interactions among multiple solitons in an optical fibre

    Energy Technology Data Exchange (ETDEWEB)

    Hu, Wen-Qiang; Gao, Yi-Tian; Zhao, Chen; Feng, Yu-Jie; Su, Chuan-Qi [Beijing University of Aeronautics and Astronautics (China). Ministry of Education Key Laboratory of Fluid Mechanics; Beijing University of Aeronautics and Astronautics (China). National Laboratory for Computational Fluid Dynamics

    2016-07-01

    In this article, under the investigation on the interactions among multiple solitons for an eighth-order nonlinear Schroedinger equation in an optical fibre, oscillations in the interaction zones are observed theoretically. With different coefficients of the operators in this equation, we find that (1) the oscillations in the solitonic interaction zones have different forms with different spectral parameters of this equation; (2) the oscillations in the interactions among the multiple solitons are affected by the choice of spectral parameters, the dispersive effects and nonlinearity of the eighth-order operator; (3) the second-, fifth-, sixth-, and seventh-order operators restrain oscillations in the solitonic interaction zones and the higher-order operators have stronger attenuated effects than the lower ones, while the third- and fourth-order operators stimulate and extend the scope of oscillations.

  20. Multiplicities of secondary hadrons produced in vp and overlinevp charged current interactions

    Science.gov (United States)

    Grässler, H.; Lanske, D.; Schulte, R.; Jones, G. T.; Middleton, R. P.; O'Neale, S. W.; Böckmann, K.; Gebel, W.; Geich-Gimbel, C.; Nellen, B.; Grant, A.; Klein, H.; Morrison, D. R. O.; Schmid, P.; Wachsmuth, H.; Chima, J. S.; Mobayyen, M. M.; Talebzadeh, M.; Villalobos-Baillie, O.; Aderholz, M.; Deck, L.; Schmitz, N.; Settles, R.; Wernhard, K. L.; Wittek, W.; Corrigan, G.; Myatt, G.; Radojicić, D.; Saitta, B.; Wells, J.; Aachen-Birmingham-Bonn-CERN-Imperial College-München (MPI)-Oxford Collaboration

    1983-08-01

    In an experiment with the hydrogen bubble chamber BEBC at CERN multiplicities of hadrons produced in νp and overlinevp interactions have been investigated. Results are presented on the multiplicities of charged hadrons and neutral pions, forward and backward multiplicities of charged hadrons and correlations between forward and backward multiplicities. Comparisons are made with hadronic reactions and e +e - annihilation. In the framework of the quark-parton model the data imply similar charged multiplicities for the fragments of a u- and a d-quark, and a larger multiplicities for the fragments of a uu- than for a ud-diquark. The correlation data suggest independent fragmentation of the quark and diquark for hadronic masses above ˜ 7 GeV and local charge compensation within an event.

  1. Multiplicities of secondary hadrons produced in vp and anti vp charged current interactions

    International Nuclear Information System (INIS)

    Graessler, H.; Lanske, D.; Schulte, R.; Chima, J.S.; Mobayyen, M.M.; Talebzadeh, M.; Villalobos-Baillie, O.; Corrigan, G.; Myatt, G.; Radojicic, D.; Saitta, B.; Wells, J.

    1983-01-01

    In an experiment with the hydrogen bubble chamber BEBC at CERN multiplicities of hadrons produced in vp and anti vp interactions have been investigated. Results are presented on the multiplicities of charged hadrons and neutral pions, forward and backward multiplicities of charged hadrons and correlations between forward and backward multiplicities. Comparisons are made with hadronic reactions and e + e - annihilation. In the framework of the quark-parton model the data imply similar charged multiplicities for the fragments of a u- and a d-quark, and larger multiplicities for the fragments of a uu- than for a ud-diquark. The correlation data suggest independent fragmentation of the quark and diquark for hadronic masses above approx.= 7 GeV and local charge compensation within an event. (orig.)

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

    Science.gov (United States)

    Schellenberg, E Glenn

    2015-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Parrish Jodi R

    2006-04-01

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

  4. EasyClone: method for iterative chromosomal integration of multiple genes in Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Jensen, Niels Bjerg; Strucko, Tomas; Kildegaard, Kanchana Rueksomtawin

    2014-01-01

    of multiple genes with an option of recycling selection markers. The vectors combine the advantage of efficient uracil excision reaction-based cloning and Cre-LoxP-mediated marker recycling system. The episomal and integrative vector sets were tested by inserting genes encoding cyan, yellow, and red...... fluorescent proteins into separate vectors and analyzing for co-expression of proteins by flow cytometry. Cells expressing genes encoding for the three fluorescent proteins from three integrations exhibited a much higher level of simultaneous expression than cells producing fluorescent proteins encoded...... on episomal plasmids, where correspondingly 95% and 6% of the cells were within a fluorescence interval of Log10 mean ± 15% for all three colors. We demonstrate that selective markers can be simultaneously removed using Cre-mediated recombination and all the integrated heterologous genes remain...

  5. Prostate cancer risk locus at 8q24 as a regulatory hub by physical interactions with multiple genomic loci across the genome.

    Science.gov (United States)

    Du, Meijun; Yuan, Tiezheng; Schilter, Kala F; Dittmar, Rachel L; Mackinnon, Alexander; Huang, Xiaoyi; Tschannen, Michael; Worthey, Elizabeth; Jacob, Howard; Xia, Shu; Gao, Jianzhong; Tillmans, Lori; Lu, Yan; Liu, Pengyuan; Thibodeau, Stephen N; Wang, Liang

    2015-01-01

    Chromosome 8q24 locus contains regulatory variants that modulate genetic risk to various cancers including prostate cancer (PC). However, the biological mechanism underlying this regulation is not well understood. Here, we developed a chromosome conformation capture (3C)-based multi-target sequencing technology and systematically examined three PC risk regions at the 8q24 locus and their potential regulatory targets across human genome in six cell lines. We observed frequent physical contacts of this risk locus with multiple genomic regions, in particular, inter-chromosomal interaction with CD96 at 3q13 and intra-chromosomal interaction with MYC at 8q24. We identified at least five interaction hot spots within the predicted functional regulatory elements at the 8q24 risk locus. We also found intra-chromosomal interaction genes PVT1, FAM84B and GSDMC and inter-chromosomal interaction gene CXorf36 in most of the six cell lines. Other gene regions appeared to be cell line-specific, such as RRP12 in LNCaP, USP14 in DU-145 and SMIN3 in lymphoblastoid cell line. We further found that the 8q24 functional domains more likely interacted with genomic regions containing genes enriched in critical pathways such as Wnt signaling and promoter motifs such as E2F1 and TCF3. This result suggests that the risk locus may function as a regulatory hub by physical interactions with multiple genes important for prostate carcinogenesis. Further understanding genetic effect and biological mechanism of these chromatin interactions will shed light on the newly discovered regulatory role of the risk locus in PC etiology and progression. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  6. Acoustically mediated long-range interaction among multiple spherical particles exposed to a plane standing wave

    International Nuclear Information System (INIS)

    Zhang, Shenwei; Qiu, Chunyin; Wang, Mudi; Ke, Manzhu; Liu, Zhengyou

    2016-01-01

    In this work, we study the acoustically mediated interaction forces among multiple well-separated spherical particles trapped in the same node or antinode plane of a standing wave. An analytical expression of the acoustic interaction force is derived, which is accurate even for the particles beyond the Rayleigh limit. Interestingly, the multi-particle system can be decomposed into a series of independent two-particle systems described by pairwise interactions. Each pairwise interaction is a long-range interaction, as characterized by a soft oscillatory attenuation (at the power exponent of n  = −1 or −2). The vector additivity of the acoustic interaction force, which is not well expected considering the nonlinear nature of the acoustic radiation force, is greatly useful for exploring a system consisting of a large number of particles. The capability of self-organizing a big particle cluster can be anticipated through such acoustically controllable long-range interaction. (paper)

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

    Science.gov (United States)

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

    2013-06-01

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

  8. NIMEFI: gene regulatory network inference using multiple ensemble feature importance algorithms.

    Directory of Open Access Journals (Sweden)

    Joeri Ruyssinck

    Full Text Available One of the long-standing open challenges in computational systems biology is the topology inference of gene regulatory networks from high-throughput omics data. Recently, two community-wide efforts, DREAM4 and DREAM5, have been established to benchmark network inference techniques using gene expression measurements. In these challenges the overall top performer was the GENIE3 algorithm. This method decomposes the network inference task into separate regression problems for each gene in the network in which the expression values of a particular target gene are predicted using all other genes as possible predictors. Next, using tree-based ensemble methods, an importance measure for each predictor gene is calculated with respect to the target gene and a high feature importance is considered as putative evidence of a regulatory link existing between both genes. The contribution of this work is twofold. First, we generalize the regression decomposition strategy of GENIE3 to other feature importance methods. We compare the performance of support vector regression, the elastic net, random forest regression, symbolic regression and their ensemble variants in this setting to the original GENIE3 algorithm. To create the ensemble variants, we propose a subsampling approach which allows us to cast any feature selection algorithm that produces a feature ranking into an ensemble feature importance algorithm. We demonstrate that the ensemble setting is key to the network inference task, as only ensemble variants achieve top performance. As second contribution, we explore the effect of using rankwise averaged predictions of multiple ensemble algorithms as opposed to only one. We name this approach NIMEFI (Network Inference using Multiple Ensemble Feature Importance algorithms and show that this approach outperforms all individual methods in general, although on a specific network a single method can perform better. An implementation of NIMEFI has been made

  9. Stable carbon isotope fractionation of chlorinated ethenes by a microbial consortium containing multiple dechlorinating genes.

    Science.gov (United States)

    Liu, Na; Ding, Longzhen; Li, Haijun; Zhang, Pengpeng; Zheng, Jixing; Weng, Chih-Huang

    2018-08-01

    The study aimed to determine the possible contribution of specific growth conditions and community structures to variable carbon enrichment factors (Ɛ- carbon ) values for the degradation of chlorinated ethenes (CEs) by a bacterial consortium with multiple dechlorinating genes. Ɛ- carbon values for trichloroethylene, cis-1,2-dichloroethylene, and vinyl chloride were -7.24% ± 0.59%, -14.6% ± 1.71%, and -21.1% ± 1.14%, respectively, during their degradation by a microbial consortium containing multiple dechlorinating genes including tceA and vcrA. The Ɛ- carbon values of all CEs were not greatly affected by changes in growth conditions and community structures, which directly or indirectly affected reductive dechlorination of CEs by this consortium. Stability analysis provided evidence that the presence of multiple dechlorinating genes within a microbial consortium had little effect on carbon isotope fractionation, as long as the genes have definite, non-overlapping functions. Copyright © 2018 Elsevier Ltd. All rights reserved.

  10. 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.

  11. Detailed assessment of gene activation levels by multiple hypoxia-responsive elements under various hypoxic conditions.

    Science.gov (United States)

    Takeuchi, Yasuto; Inubushi, Masayuki; Jin, Yong-Nan; Murai, Chika; Tsuji, Atsushi B; Hata, Hironobu; Kitagawa, Yoshimasa; Saga, Tsuneo

    2014-12-01

    HIF-1/HRE pathway is a promising target for the imaging and the treatment of intractable malignancy (HIF-1; hypoxia-inducible factor 1, HRE; hypoxia-responsive element). The purposes of our study are: (1) to assess the gene activation levels resulting from various numbers of HREs under various hypoxic conditions, (2) to evaluate the bidirectional activity of multiple HREs, and (3) to confirm whether multiple HREs can induce gene expression in vivo. Human colon carcinoma HCT116 cells were transiently transfected by the constructs containing a firefly luciferase reporter gene and various numbers (2, 4, 6, 8, 10, and 12) of HREs (nHRE+, nHRE-). The relative luciferase activities were measured under various durations of hypoxia (6, 12, 18, and 24 h), O2 concentrations (1, 2, 4, 8, and 16 %), and various concentrations of deferoxamine mesylate (20, 40, 80, 160, and 320 µg/mL growth medium). The bidirectional gene activation levels by HREs were examined in the constructs (dual-luc-nHREs) containing firefly and Renilla luciferase reporter genes at each side of nHREs. Finally, to test whether the construct containing 12HRE and the NIS reporter gene (12HRE-NIS) can induce gene expression in vivo, SPECT imaging was performed in a mouse xenograft model. (1) gene activation levels by HREs tended to increase with increasing HRE copy number, but a saturation effect was observed in constructs with more than 6 or 8 copies of an HRE, (2) gene activation levels by HREs increased remarkably during 6-12 h of hypoxia, but not beyond 12 h, (3) gene activation levels by HREs decreased with increasing O2 concentrations, but could be detected even under mild hypoxia at 16 % O2, (4) the bidirectionally proportional activity of the HRE was confirmed regardless of the hypoxic severity, and (5) NIS expression driven by 12 tandem copies of an HRE in response to hypoxia could be visualized on in vivo SPECT imaging. The results of this study will help in the understanding and assessment of

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

    NARCIS (Netherlands)

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

    2008-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Ian M Willis

    2008-07-01

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

  14. Multiple BiP genes of Arabidopsis thaliana are required for male gametogenesis and pollen competitiveness.

    Science.gov (United States)

    Maruyama, Daisuke; Sugiyama, Tomoyuki; Endo, Toshiya; Nishikawa, Shuh-Ichi

    2014-04-01

    Immunoglobulin-binding protein (BiP) is a molecular chaperone of the heat shock protein 70 (Hsp70) family. BiP is localized in the endoplasmic reticulum (ER) and plays key roles in protein translocation, protein folding and quality control in the ER. The genomes of flowering plants contain multiple BiP genes. Arabidopsis thaliana has three BiP genes. BIP1 and BIP2 are ubiquitously expressed. BIP3 encodes a less well conserved BiP paralog, and it is expressed only under ER stress conditions in the majority of organs. Here, we report that all BiP genes are expressed and functional in pollen and pollen tubes. Although the bip1 bip2 double mutation does not affect pollen viability, the bip1 bip2 bip3 triple mutation is lethal in pollen. This result indicates that lethality of the bip1 bip2 double mutation is rescued by BiP3 expression. A decrease in the copy number of the ubiquitously expressed BiP genes correlates well with a decrease in pollen tube growth, which leads to reduced fitness of mutant pollen during fertilization. Because an increased protein secretion activity is expected to increase the protein folding demand in the ER, the multiple BiP genes probably cooperate with each other to ensure ER homeostasis in cells with active secretion such as rapidly growing pollen tubes.

  15. Multiple episodes of convergence in genes of the dim light vision pathway in bats.

    Directory of Open Access Journals (Sweden)

    Yong-Yi Shen

    Full Text Available The molecular basis of the evolution of phenotypic characters is very complex and is poorly understood with few examples documenting the roles of multiple genes. Considering that a single gene cannot fully explain the convergence of phenotypic characters, we choose to study the convergent evolution of rod vision in two divergent bats from a network perspective. The Old World fruit bats (Pteropodidae are non-echolocating and have binocular vision, whereas the sheath-tailed bats (Emballonuridae are echolocating and have monocular vision; however, they both have relatively large eyes and rely more on rod vision to find food and navigate in the night. We found that the genes CRX, which plays an essential role in the differentiation of photoreceptor cells, SAG, which is involved in the desensitization of the photoactivated transduction cascade, and the photoreceptor gene RH, which is directly responsible for the perception of dim light, have undergone parallel sequence evolution in two divergent lineages of bats with larger eyes (Pteropodidae and Emballonuroidea. The multiple convergent events in the network of genes essential for rod vision is a rare phenomenon that illustrates the importance of investigating pathways and networks in the evolution of the molecular basis of phenotypic convergence.

  16. Assembly and multiple gene expression of thermophilic enzymes in Escherichia coli for in vitro metabolic engineering.

    Science.gov (United States)

    Ninh, Pham Huynh; Honda, Kohsuke; Sakai, Takaaki; Okano, Kenji; Ohtake, Hisao

    2015-01-01

    In vitro reconstitution of an artificial metabolic pathway is an emerging approach for the biocatalytic production of industrial chemicals. However, several enzymes have to be separately prepared (and purified) for the construction of an in vitro metabolic pathway, thereby limiting the practical applicability of this approach. In this study, genes encoding the nine thermophilic enzymes involved in a non-ATP-forming chimeric glycolytic pathway were assembled in an artificial operon and co-expressed in a single recombinant Escherichia coli strain. Gene expression levels of the thermophilic enzymes were controlled by their sequential order in the artificial operon. The specific activities of the recombinant enzymes in the cell-free extract of the multiple-gene-expression E. coli were 5.0-1,370 times higher than those in an enzyme cocktail prepared from a mixture of single-gene-expression strains, in each of which a single one of the nine thermophilic enzymes was overproduced. Heat treatment of a crude extract of the multiple-gene-expression cells led to the denaturation of indigenous proteins and one-step preparation of an in vitro synthetic pathway comprising only a limited number of thermotolerant enzymes. Coupling this in vitro pathway with other thermophilic enzymes including the H2 O-forming NADH oxidase or the malate/lactate dehydrogenase facilitated one-pot conversion of glucose to pyruvate or lactate, respectively. © 2014 Wiley Periodicals, Inc.

  17. 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.

  18. Decomposition of the Total Effect in the Presence of Multiple Mediators and Interactions.

    Science.gov (United States)

    Bellavia, Andrea; Valeri, Linda

    2018-06-01

    Mediation analysis allows decomposing a total effect into a direct effect of the exposure on the outcome and an indirect effect operating through a number of possible hypothesized pathways. Recent studies have provided formal definitions of direct and indirect effects when multiple mediators are of interest and have described parametric and semiparametric methods for their estimation. Investigating direct and indirect effects with multiple mediators, however, can be challenging in the presence of multiple exposure-mediator and mediator-mediator interactions. In this paper we derive a decomposition of the total effect that unifies mediation and interaction when multiple mediators are present. We illustrate the properties of the proposed framework in a secondary analysis of a pragmatic trial for the treatment of schizophrenia. The decomposition is employed to investigate the interplay of side effects and psychiatric symptoms in explaining the effect of antipsychotic medication on quality of life in schizophrenia patients. Our result offers a valuable tool to identify the proportions of total effect due to mediation and interaction when more than one mediator is present, providing the finest decomposition of the total effect that unifies multiple mediators and interactions.

  19. Supporting a child with multiple disabilities to participate in social interaction

    DEFF Research Database (Denmark)

    Norén, Niklas; Pilesjö, Maja Sigurd

    2016-01-01

    Asking a question can be a highly challenging task for a person with multiple disabilities, but questions have not received much attention in research on augmentative and alternative communication (AAC). Conversation analysis is employed to examine an instance of multiparty interaction where...... a speech and language therapist supports a child with multiple disabilities to ask a question with a communication board. The question is accomplished through a practice where the action is built as a trajectory of interactional steps. Each step is built using ways of involvement that establish different...

  20. Calculation of contribution of multiple interactions and efficiency of neutron detectors

    International Nuclear Information System (INIS)

    Androsenko, A.A.; Androsenko, P.A.; Kazakov, L.E.; Kononov, V.N.; Poletaev, E.D.

    1986-01-01

    Results of calculation of multiple neutron interactions contribution to efficiency of detectors with 6 Li glass and 10 B plate in the energy range of 0.01-1 MeV are given. The calculation was performed by the Monte-Carlo method using BRAND program complex. It is shown that a correction value for multiple neutron interaction in 6 Li glass of 1 mm thickness constitutes 4.5 % at energy of up to 100 keV and at higher energies has a complex energy dependence reaching 25 % at 440 keV

  1. 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…

  2. 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.

  3. Effects of multiple modes interaction on the resistive wall mode instability

    International Nuclear Information System (INIS)

    Chen, Longxi; Lei, Wenqing; Ma, Zhiwei; Wu, Bin

    2013-01-01

    The effects of multiple modes interaction on the resistive wall mode (RWM) are studied in a slab geometry with and without plasma flow. The modes interaction can have a large effect on both the linear growth rate and the nonlinear saturation level of the RWM. We found that modes interaction can suppress the linear growth rate for the most unstable mode. The plasma flow can also help to control the growth of the RWM. The RWM can be stabilized completely by a plasma flow when considering the modes interaction. The effect of modes interaction on the RWM is stronger for the mode rational surface in the vacuum than that in the plasma. The modes interaction results in a substantially lowered saturation level for the most unstable RWM. (paper)

  4. 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.

  5. Interactions of Polyhomeotic with Polycomb Group Genes of Drosophila Melanogaster

    OpenAIRE

    Cheng, N. N.; Sinclair, DAR.; Campbell, R. B.; Brock, H. W.

    1994-01-01

    The Polycomb (Pc) group genes of Drosophila are negative regulators of homeotic genes, but individual loci have pleiotropic phenotypes. It has been suggested that Pc group genes might form a regulatory hierarchy, or might be members of a multimeric complex that obeys the law of mass action. Recently, it was shown that polyhomeotic (ph) immunoprecipitates in a multimeric complex that includes Pc. Here, we show that duplications of ph suppress homeotic transformations of Pc and Pcl, supporting ...

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

    Science.gov (United States)

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

    2016-11-01

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

  7. 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

  8. EBF factors drive expression of multiple classes of target genes governing neuronal development.

    Science.gov (United States)

    Green, Yangsook S; Vetter, Monica L

    2011-04-30

    Early B cell factor (EBF) family members are transcription factors known to have important roles in several aspects of vertebrate neurogenesis, including commitment, migration and differentiation. Knowledge of how EBF family members contribute to neurogenesis is limited by a lack of detailed understanding of genes that are transcriptionally regulated by these factors. We performed a microarray screen in Xenopus animal caps to search for targets of EBF transcriptional activity, and identified candidate targets with multiple roles, including transcription factors of several classes. We determined that, among the most upregulated candidate genes with expected neuronal functions, most require EBF activity for some or all of their expression, and most have overlapping expression with ebf genes. We also found that the candidate target genes that had the most strongly overlapping expression patterns with ebf genes were predicted to be direct transcriptional targets of EBF transcriptional activity. The identification of candidate targets that are transcription factor genes, including nscl-1, emx1 and aml1, improves our understanding of how EBF proteins participate in the hierarchy of transcription control during neuronal development, and suggests novel mechanisms by which EBF activity promotes migration and differentiation. Other candidate targets, including pcdh8 and kcnk5, expand our knowledge of the types of terminal differentiated neuronal functions that EBF proteins regulate.

  9. EBF factors drive expression of multiple classes of target genes governing neuronal development

    Directory of Open Access Journals (Sweden)

    Vetter Monica L

    2011-04-01

    Full Text Available Abstract Background Early B cell factor (EBF family members are transcription factors known to have important roles in several aspects of vertebrate neurogenesis, including commitment, migration and differentiation. Knowledge of how EBF family members contribute to neurogenesis is limited by a lack of detailed understanding of genes that are transcriptionally regulated by these factors. Results We performed a microarray screen in Xenopus animal caps to search for targets of EBF transcriptional activity, and identified candidate targets with multiple roles, including transcription factors of several classes. We determined that, among the most upregulated candidate genes with expected neuronal functions, most require EBF activity for some or all of their expression, and most have overlapping expression with ebf genes. We also found that the candidate target genes that had the most strongly overlapping expression patterns with ebf genes were predicted to be direct transcriptional targets of EBF transcriptional activity. Conclusions The identification of candidate targets that are transcription factor genes, including nscl-1, emx1 and aml1, improves our understanding of how EBF proteins participate in the hierarchy of transcription control during neuronal development, and suggests novel mechanisms by which EBF activity promotes migration and differentiation. Other candidate targets, including pcdh8 and kcnk5, expand our knowledge of the types of terminal differentiated neuronal functions that EBF proteins regulate.

  10. SATB1 tethers multiple gene loci to reprogram expression profiledriving breast cancer metastasis

    Energy Technology Data Exchange (ETDEWEB)

    Han, Hye-Jung; Kohwi, Yoshinori; Kohwi-Shigematsu, Terumi

    2006-07-13

    Global changes in gene expression occur during tumor progression, as indicated by expression profiling of metastatic tumors. How this occurs is poorly understood. SATB1 functions as a genome organizer by folding chromatin via tethering multiple genomic loci and recruiting chromatin remodeling enzymes to regulate chromatin structure and expression of a large number of genes. Here we show that SATB1 is expressed at high levels in aggressive breast cancer cells, and is undetectable in non-malignant breast epithelial cells. Importantly, RNAi-mediated removal of SATB1 from highly-aggressive MDA-MB-231 cells altered the expression levels of over 1200 genes, restored breast-like acinar polarity in three-dimensional cultures, and prevented the metastastic phenotype in vivo. Conversely, overexpression of SATB1 in the less-aggressive breast cancer cell line Hs578T altered the gene expression profile and increased metastasis dramatically in vivo. Thus, SATB1 is a global regulator of gene expression in breast cancer cells, directly regulating crucial metastasis-associated genes, including ERRB2 (HER2/NEU), TGF-{beta}1, matrix metalloproteinase 3, and metastasin. The identification of SATB1 as a protein that re-programs chromatin organization and transcription profiles to promote breast cancer metastasis suggests a new model for metastasis and may provide means of therapeutic intervention.

  11. Investigating multiple dysregulated pathways in rheumatoid arthritis based on pathway interaction network.

    Science.gov (United States)

    Song, Xian-Dong; Song, Xian-Xu; Liu, Gui-Bo; Ren, Chun-Hui; Sun, Yuan-Bo; Liu, Ke-Xin; Liu, Bo; Liang, Shuang; Zhu, Zhu

    2018-03-01

    The traditional methods of identifying biomarkers in rheumatoid arthritis (RA) have focussed on the differentially expressed pathways or individual pathways, which however, neglect the interactions between pathways. To better understand the pathogenesis of RA, we aimed to identify dysregulated pathway sets using a pathway interaction network (PIN), which considered interactions among pathways. Firstly, RA-related gene expression profile data, protein-protein interactions (PPI) data and pathway data were taken up from the corresponding databases. Secondly, principal component analysis method was used to calculate the pathway activity of each of the pathway, and then a seed pathway was identified using data gleaned from the pathway activity. A PIN was then constructed based on the gene expression profile, pathway data, and PPI information. Finally, the dysregulated pathways were extracted from the PIN based on the seed pathway using the method of support vector machines and an area under the curve (AUC) index. The PIN comprised of a total of 854 pathways and 1064 pathway interactions. The greatest change in the activity score between RA and control samples was observed in the pathway of epigenetic regulation of gene expression, which was extracted and regarded as the seed pathway. Starting with this seed pathway, one maximum pathway set containing 10 dysregulated pathways was extracted from the PIN, having an AUC of 0.8249, and the result indicated that this pathway set could distinguish RA from the controls. These 10 dysregulated pathways might be potential biomarkers for RA diagnosis and treatment in the future.

  12. Permethrin induction of multiple cytochrome P450 genes in insecticide resistant mosquitoes, Culex quinquefasciatus.

    Science.gov (United States)

    Gong, Youhui; Li, Ting; Zhang, Lee; Gao, Xiwu; Liu, Nannan

    2013-01-01

    The expression of some insect P450 genes can be induced by both exogenous and endogenous compounds and there is evidence to suggest that multiple constitutively overexpressed P450 genes are co-responsible for the development of resistance to permethrin in resistant mosquitoes. This study characterized the permethrin induction profiles of P450 genes known to be constitutively overexpressed in resistant mosquitoes, Culex quinquefasciatus. The gene expression in 7 of the 19 P450 genes CYP325K3v1, CYP4D42v2, CYP9J45, (CYP) CPIJ000926, CYP325G4, CYP4C38, CYP4H40 in the HAmCqG8 strain, increased more than 2-fold after exposure to permethrin at an LC50 concentration (10 ppm) compared to their acetone treated counterpart; no significant differences in the expression of these P450 genes in susceptible S-Lab mosquitoes were observed after permethrin treatment. Eleven of the fourteen P450 genes overexpressed in the MAmCqG6 strain, CYP9M10, CYP6Z12, CYP9J33, CYP9J43, CYP9J34, CYP306A1, CYP6Z15, CYP9J45, CYPPAL1, CYP4C52v1, CYP9J39, were also induced more than doubled after exposure to an LC50 (0.7 ppm) dose of permethrin. No significant induction in P450 gene expression was observed in the susceptible S-Lab mosquitoes after permethrin treatment except for CYP6Z15 and CYP9J39, suggesting that permethrin induction of these two P450 genes are common to both susceptible and resistant mosquitoes while the induction of the others are specific to insecticide resistant mosquitoes. These results demonstrate that multiple P450 genes are co-up-regulated in insecticide resistant mosquitoes through both constitutive overexpression and induction mechanisms, providing additional support for their involvement in the detoxification of insecticides and the development of insecticide resistance.

  13. Visual Comparison of Multiple Gene Expression Datasets in a Genomic Context

    Directory of Open Access Journals (Sweden)

    Borowski Krzysztof

    2008-06-01

    Full Text Available The need for novel methods of visualizing microarray data is growing. New perspectives are beneficial to finding patterns in expression data. The Bluejay genome browser provides an integrative way of visualizing gene expression datasets in a genomic context. We have now developed the functionality to display multiple microarray datasets simultaneously in Bluejay, in order to provide researchers with a comprehensive view of their datasets linked to a graphical representation of gene function. This will enable biologists to obtain valuable insights on expression patterns, by allowing them to analyze the expression values in relation to the gene locations as well as to compare expression profiles of related genomes or of di erent experiments for the same genome.

  14. XCluSim: a visual analytics tool for interactively comparing multiple clustering results of bioinformatics data

    Science.gov (United States)

    2015-01-01

    Background Though cluster analysis has become a routine analytic task for bioinformatics research, it is still arduous for researchers to assess the quality of a clustering result. To select the best clustering method and its parameters for a dataset, researchers have to run multiple clustering algorithms and compare them. However, such a comparison task with multiple clustering results is cognitively demanding and laborious. Results In this paper, we present XCluSim, a visual analytics tool that enables users to interactively compare multiple clustering results based on the Visual Information Seeking Mantra. We build a taxonomy for categorizing existing techniques of clustering results visualization in terms of the Gestalt principles of grouping. Using the taxonomy, we choose the most appropriate interactive visualizations for presenting individual clustering results from different types of clustering algorithms. The efficacy of XCluSim is shown through case studies with a bioinformatician. Conclusions Compared to other relevant tools, XCluSim enables users to compare multiple clustering results in a more scalable manner. Moreover, XCluSim supports diverse clustering algorithms and dedicated visualizations and interactions for different types of clustering results, allowing more effective exploration of details on demand. Through case studies with a bioinformatics researcher, we received positive feedback on the functionalities of XCluSim, including its ability to help identify stably clustered items across multiple clustering results. PMID:26328893

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

    Directory of Open Access Journals (Sweden)

    Takahiko Kubo

    2016-05-01

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

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

    Science.gov (United States)

    Kubo, Takahiko; Yoshimura, Atsushi; Kurata, Nori

    2016-05-03

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

  17. Dependence of Xmax and multiplicity of electron and muon on different high energy interaction models

    Directory of Open Access Journals (Sweden)

    G Rastegarzadeh

    2010-06-01

    Full Text Available Different high energy interaction models are the applied in CORSIKA code to simulate Extensive Air Showers (EAS generated by Cosmic Rays (CR. In this work the effects of QGSJET01, QGSJETII, DPMJET, SIBYLL models on Xmax and multiplicity of secondary electrons and muons at observation level are studied.

  18. Computational Tools for Probing Interactions in Multiple Linear Regression, Multilevel Modeling, and Latent Curve Analysis

    Science.gov (United States)

    Preacher, Kristopher J.; Curran, Patrick J.; Bauer, Daniel J.

    2006-01-01

    Simple slopes, regions of significance, and confidence bands are commonly used to evaluate interactions in multiple linear regression (MLR) models, and the use of these techniques has recently been extended to multilevel or hierarchical linear modeling (HLM) and latent curve analysis (LCA). However, conducting these tests and plotting the…

  19. N-cadherin-mediated interaction with multiple myeloma cells inhibits osteoblast differentiation

    NARCIS (Netherlands)

    Groen, Richard W. J.; de Rooij, Martin F. M.; Kocemba, Kinga A.; Reijmers, Rogier M.; de Haan-Kramer, Anneke; Overdijk, Marije B.; Aalders, Linda; Rozemuller, Henk; Martens, Anton C. M.; Bergsagel, P. Leif; Kersten, Marie José; Pals, Steven T.; Spaargaren, Marcel

    2011-01-01

    Multiple myeloma is a hematologic malignancy characterized by a clonal expansion of malignant plasma cells in the bone marrow, which is accompanied by the development of osteolytic lesions and/or diffuse osteopenia. The intricate bi-directional interaction with the bone marrow microenvironment plays

  20. N-cadherin-mediated interaction with multiple myeloma cells inhibits osteoblast differentiation

    NARCIS (Netherlands)

    Groen, R.W.J.; de Rooij, M.F.M.; Kocemba, K.A.; Reijmers, R.M.; de Haan-Kramer, A.; Overdijk, M.B.; Aalders, L.; Rozemuller, H.; Martens, A.C.M.; Bergsagel, P.L.; Kersten, M.J.; Pals, S.T.; Spaargaren, M.

    2011-01-01

    Background Multiple myeloma is a hematologic malignancy characterized by a clonal expansion of malignant plasma cells in the bone marrow, which is accompanied by the development of osteolytic lesions and/or diffuse osteopenia. The intricate bi-directional interaction with the bone marrow

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

    Science.gov (United States)

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

    2014-01-01

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

  2. 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.

  3. 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

  4. Molecular evolution of the Paramyxoviridae and Rhabdoviridae multiple-protein-encoding P gene.

    Science.gov (United States)

    Jordan, I K; Sutter, B A; McClure, M A

    2000-01-01

    Presented here is an analysis of the molecular evolutionary dynamics of the P gene among 76 representative sequences of the Paramyxoviridae and Rhabdoviridae RNA virus families. In a number of Paramyxoviridae taxa, as well as in vesicular stomatitis viruses of the Rhabdoviridae, the P gene encodes multiple proteins from a single genomic RNA sequence. These products include the phosphoprotein (P), as well as the C and V proteins. The complexity of the P gene makes it an intriguing locus to study from an evolutionary perspective. Amino acid sequence alignments of the proteins encoded at the P and N loci were used in independent phylogenetic reconstructions of the Paramyxoviridae and Rhabdoviridae families. P-gene-coding capacities were mapped onto the Paramyxoviridae phylogeny, and the most parsimonious path of multiple-coding-capacity evolution was determined. Levels of amino acid variation for Paramyxoviridae and Rhabdoviridae P-gene-encoded products were also analyzed. Proteins encoded in overlapping reading frames from the same nucleotides have different levels of amino acid variation. The nucleotide architecture that underlies the amino acid variation was determined in order to evaluate the role of selection in the evolution of the P gene overlapping reading frames. In every case, the evolution of one of the proteins encoded in the overlapping reading frames has been constrained by negative selection while the other has evolved more rapidly. The integrity of the overlapping reading frame that represents a derived state is generally maintained at the expense of the ancestral reading frame encoded by the same nucleotides. The evolution of such multicoding sequences is likely a response by RNA viruses to selective pressure to maximize genomic information content while maintaining small genome size. The ability to evolve such a complex genomic strategy is intimately related to the dynamics of the viral quasispecies, which allow enhanced exploration of the adaptive

  5. C/EBPβ Mediates Growth Hormone-Regulated Expression of Multiple Target Genes

    Science.gov (United States)

    Cui, Tracy X.; Lin, Grace; LaPensee, Christopher R.; Calinescu, Anda-Alexandra; Rathore, Maanjot; Streeter, Cale; Piwien-Pilipuk, Graciela; Lanning, Nathan; Jin, Hui; Carter-Su, Christin; Qin, Zhaohui S.

    2011-01-01

    Regulation of c-Fos transcription by GH is mediated by CCAAT/enhancer binding protein β (C/EBPβ). This study examines the role of C/EBPβ in mediating GH activation of other early response genes, including Cyr61, Btg2, Socs3, Zfp36, and Socs1. C/EBPβ depletion using short hairpin RNA impaired responsiveness of these genes to GH, as seen for c-Fos. Rescue with wild-type C/EBPβ led to GH-dependent recruitment of the coactivator p300 to the c-Fos promoter. In contrast, rescue with C/EBPβ mutated at the ERK phosphorylation site at T188 failed to induce GH-dependent recruitment of p300, indicating that ERK-mediated phosphorylation of C/EBPβ at T188 is required for GH-induced recruitment of p300 to c-Fos. GH also induced the occupancy of phosphorylated C/EBPβ and p300 on Cyr61, Btg2, and Socs3 at predicted C/EBP-cAMP response element-binding protein motifs in their promoters. Consistent with a role for ERKs in GH-induced expression of these genes, treatment with U0126 to block ERK phosphorylation inhibited their GH-induced expression. In contrast, GH-dependent expression of Zfp36 and Socs1 was not inhibited by U0126. Thus, induction of multiple early response genes by GH in 3T3-F442A cells is mediated by C/EBPβ. A subset of these genes is regulated similarly to c-Fos, through a mechanism involving GH-stimulated ERK 1/2 activation, phosphorylation of C/EBPβ, and recruitment of p300. Overall, these studies suggest that C/EBPβ, like the signal transducer and activator of transcription proteins, regulates multiple genes in response to GH. PMID:21292824

  6. Whole exome sequencing reveals concomitant mutations of multiple FA genes in individual Fanconi anemia patients.

    Science.gov (United States)

    Chang, Lixian; Yuan, Weiping; Zeng, Huimin; Zhou, Quanquan; Wei, Wei; Zhou, Jianfeng; Li, Miaomiao; Wang, Xiaomin; Xu, Mingjiang; Yang, Fengchun; Yang, Yungui; Cheng, Tao; Zhu, Xiaofan

    2014-05-15

    Fanconi anemia (FA) is a rare inherited genetic syndrome with highly variable clinical manifestations. Fifteen genetic subtypes of FA have been identified. Traditional complementation tests for grouping studies have been used generally in FA patients and in stepwise methods to identify the FA type, which can result in incomplete genetic information from FA patients. We diagnosed five pediatric patients with FA based on clinical manifestations, and we performed exome sequencing of peripheral blood specimens from these patients and their family members. The related sequencing data were then analyzed by bioinformatics, and the FANC gene mutations identified by exome sequencing were confirmed by PCR re-sequencing. Homozygous and compound heterozygous mutations of FANC genes were identified in all of the patients. The FA subtypes of the patients included FANCA, FANCM and FANCD2. Interestingly, four FA patients harbored multiple mutations in at least two FA genes, and some of these mutations have not been previously reported. These patients' clinical manifestations were vastly different from each other, as were their treatment responses to androstanazol and prednisone. This finding suggests that heterozygous mutation(s) in FA genes could also have diverse biological and/or pathophysiological effects on FA patients or FA gene carriers. Interestingly, we were not able to identify de novo mutations in the genes implicated in DNA repair pathways when the sequencing data of patients were compared with those of their parents. Our results indicate that Chinese FA patients and carriers might have higher and more complex mutation rates in FANC genes than have been conventionally recognized. Testing of the fifteen FANC genes in FA patients and their family members should be a regular clinical practice to determine the optimal care for the individual patient, to counsel the family and to obtain a better understanding of FA pathophysiology.

  7. 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.

  8. Action of multiple intra-QTL genes concerted around a co-localized transcription factor underpins a large effect QTL

    Science.gov (United States)

    Dixit, Shalabh; Kumar Biswal, Akshaya; Min, Aye; Henry, Amelia; Oane, Rowena H.; Raorane, Manish L.; Longkumer, Toshisangba; Pabuayon, Isaiah M.; Mutte, Sumanth K.; Vardarajan, Adithi R.; Miro, Berta; Govindan, Ganesan; Albano-Enriquez, Blesilda; Pueffeld, Mandy; Sreenivasulu, Nese; Slamet-Loedin, Inez; Sundarvelpandian, Kalaipandian; Tsai, Yuan-Ching; Raghuvanshi, Saurabh; Hsing, Yue-Ie C.; Kumar, Arvind; Kohli, Ajay

    2015-01-01

    Sub-QTLs and multiple intra-QTL genes are hypothesized to underpin large-effect QTLs. Known QTLs over gene families, biosynthetic pathways or certain traits represent functional gene-clusters of genes of the same gene ontology (GO). Gene-clusters containing genes of different GO have not been elaborated, except in silico as coexpressed genes within QTLs. Here we demonstrate the requirement of multiple intra-QTL genes for the full impact of QTL qDTY12.1 on rice yield under drought. Multiple evidences are presented for the need of the transcription factor ‘no apical meristem’ (OsNAM12.1) and its co-localized target genes of separate GO categories for qDTY12.1 function, raising a regulon-like model of genetic architecture. The molecular underpinnings of qDTY12.1 support its effectiveness in further improving a drought tolerant genotype and for its validity in multiple genotypes/ecosystems/environments. Resolving the combinatorial value of OsNAM12.1 with individual intra-QTL genes notwithstanding, identification and analyses of qDTY12.1has fast-tracked rice improvement towards food security. PMID:26507552

  9. Interaction of Multiple Particles with a Solidification Front: From Compacted Particle Layer to Particle Trapping.

    Science.gov (United States)

    Saint-Michel, Brice; Georgelin, Marc; Deville, Sylvain; Pocheau, Alain

    2017-06-13

    The interaction of solidification fronts with objects such as particles, droplets, cells, or bubbles is a phenomenon with many natural and technological occurrences. For an object facing the front, it may yield various fates, from trapping to rejection, with large implications regarding the solidification pattern. However, whereas most situations involve multiple particles interacting with each other and the front, attention has focused almost exclusively on the interaction of a single, isolated object with the front. Here we address experimentally the interaction of multiple particles with a solidification front by performing solidification experiments of a monodisperse particle suspension in a Hele-Shaw cell with precise control of growth conditions and real-time visualization. We evidence the growth of a particle layer ahead of the front at a close-packing volume fraction, and we document its steady-state value at various solidification velocities. We then extend single-particle models to the situation of multiple particles by taking into account the additional force induced on an entering particle by viscous friction in the compacted particle layer. By a force balance model this provides an indirect measure of the repelling mean thermomolecular pressure over a particle entering the front. The presence of multiple particles is found to increase it following a reduction of the thickness of the thin liquid film that separates particles and front. We anticipate the findings reported here to provide a relevant basis to understand many complex solidification situations in geophysics, engineering, biology, or food engineering, where multiple objects interact with the front and control the resulting solidification patterns.

  10. 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

  11. 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 ...

  12. Cross-species multiple environmental stress responses: An integrated approach to identify candidate genes for multiple stress tolerance in sorghum (Sorghum bicolor (L. Moench and related model species.

    Directory of Open Access Journals (Sweden)

    Adugna Abdi Woldesemayat

    Full Text Available Crop response to the changing climate and unpredictable effects of global warming with adverse conditions such as drought stress has brought concerns about food security to the fore; crop yield loss is a major cause of concern in this regard. Identification of genes with multiple responses across environmental stresses is the genetic foundation that leads to crop adaptation to environmental perturbations.In this paper, we introduce an integrated approach to assess candidate genes for multiple stress responses across-species. The approach combines ontology based semantic data integration with expression profiling, comparative genomics, phylogenomics, functional gene enrichment and gene enrichment network analysis to identify genes associated with plant stress phenotypes. Five different ontologies, viz., Gene Ontology (GO, Trait Ontology (TO, Plant Ontology (PO, Growth Ontology (GRO and Environment Ontology (EO were used to semantically integrate drought related information.Target genes linked to Quantitative Trait Loci (QTLs controlling yield and stress tolerance in sorghum (Sorghum bicolor (L. Moench and closely related species were identified. Based on the enriched GO terms of the biological processes, 1116 sorghum genes with potential responses to 5 different stresses, such as drought (18%, salt (32%, cold (20%, heat (8% and oxidative stress (25% were identified to be over-expressed. Out of 169 sorghum drought responsive QTLs associated genes that were identified based on expression datasets, 56% were shown to have multiple stress responses. On the other hand, out of 168 additional genes that have been evaluated for orthologous pairs, 90% were conserved across species for drought tolerance. Over 50% of identified maize and rice genes were responsive to drought and salt stresses and were co-located within multifunctional QTLs. Among the total identified multi-stress responsive genes, 272 targets were shown to be co-localized within QTLs

  13. 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...

  14. Fine tuning of RFX/DAF-19-regulated target gene expression through binding to multiple sites in Caenorhabditis elegans

    OpenAIRE

    Chu, Jeffery S. C.; Tarailo-Graovac, Maja; Zhang, Di; Wang, Jun; Uyar, Bora; Tu, Domena; Trinh, Joanne; Baillie, David L.; Chen, Nansheng

    2011-01-01

    In humans, mutations of a growing list of regulatory factor X (RFX) target genes have been associated with devastating genetics disease conditions including ciliopathies. However, mechanisms underlying RFX transcription factors (TFs)-mediated gene expression regulation, especially differential gene expression regulation, are largely unknown. In this study, we explore the functional significance of the co-existence of multiple X-box motifs in regulating differential gene expression in Caenorha...

  15. 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...

  16. Multiplicity distributions of charged hadrons in vp and charged current interactions

    Science.gov (United States)

    Jones, G. T.; Jones, R. W. L.; Kennedy, B. W.; Morrison, D. R. O.; Mobayyen, M. M.; Wainstein, S.; Aderholz, M.; Hantke, D.; Katz, U. F.; Kern, J.; Schmitz, N.; Wittek, W.; Borner, H. P.; Myatt, G.; Radojicic, D.; Burke, S.

    1992-03-01

    Using data on vp andbar vp charged current interactions from a bubble chamber experiment with BEBC at CERN, the multiplicity distributions of charged hadrons are investigated. The analysis is based on ˜20000 events with incident v and ˜10000 events with incidentbar v. The invariant mass W of the total hadronic system ranges from 3 GeV to ˜14 GeV. The experimental multiplicity distributions are fitted by the binomial function (for different intervals of W and in different intervals of the rapidity y), by the Levy function and the lognormal function. All three parametrizations give acceptable values for X 2. For fixed W, forward and backward multiplicities are found to be uncorrelated. The normalized moments of the charged multiplicity distributions are measured as a function of W. They show a violation of KNO scaling.

  17. Dynamic evolution of Geranium mitochondrial genomes through multiple horizontal and intracellular gene transfers.

    Science.gov (United States)

    Park, Seongjun; Grewe, Felix; Zhu, Andan; Ruhlman, Tracey A; Sabir, Jamal; Mower, Jeffrey P; Jansen, Robert K

    2015-10-01

    The exchange of genetic material between cellular organelles through intracellular gene transfer (IGT) or between species by horizontal gene transfer (HGT) has played an important role in plant mitochondrial genome evolution. The mitochondrial genomes of Geraniaceae display a number of unusual phenomena including highly accelerated rates of synonymous substitutions, extensive gene loss and reduction in RNA editing. Mitochondrial DNA sequences assembled for 17 species of Geranium revealed substantial reduction in gene and intron content relative to the ancestor of the Geranium lineage. Comparative analyses of nuclear transcriptome data suggest that a number of these sequences have been functionally relocated to the nucleus via IGT. Evidence for rampant HGT was detected in several Geranium species containing foreign organellar DNA from diverse eudicots, including many transfers from parasitic plants. One lineage has experienced multiple, independent HGT episodes, many of which occurred within the past 5.5 Myr. Both duplicative and recapture HGT were documented in Geranium lineages. The mitochondrial genome of Geranium brycei contains at least four independent HGT tracts that are absent in its nearest relative. Furthermore, G. brycei mitochondria carry two copies of the cox1 gene that differ in intron content, providing insight into contrasting hypotheses on cox1 intron evolution. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

  18. An Approach for Predicting Essential Genes Using Multiple Homology Mapping and Machine Learning Algorithms.

    Science.gov (United States)

    Hua, Hong-Li; Zhang, Fa-Zhan; Labena, Abraham Alemayehu; Dong, Chuan; Jin, Yan-Ting; Guo, Feng-Biao

    Investigation of essential genes is significant to comprehend the minimal gene sets of cell and discover potential drug targets. In this study, a novel approach based on multiple homology mapping and machine learning method was introduced to predict essential genes. We focused on 25 bacteria which have characterized essential genes. The predictions yielded the highest area under receiver operating characteristic (ROC) curve (AUC) of 0.9716 through tenfold cross-validation test. Proper features were utilized to construct models to make predictions in distantly related bacteria. The accuracy of predictions was evaluated via the consistency of predictions and known essential genes of target species. The highest AUC of 0.9552 and average AUC of 0.8314 were achieved when making predictions across organisms. An independent dataset from Synechococcus elongatus , which was released recently, was obtained for further assessment of the performance of our model. The AUC score of predictions is 0.7855, which is higher than other methods. This research presents that features obtained by homology mapping uniquely can achieve quite great or even better results than those integrated features. Meanwhile, the work indicates that machine learning-based method can assign more efficient weight coefficients than using empirical formula based on biological knowledge.

  19. Phylogenetic Relationships of Pseudorasbora, Pseudopungtungia, and Pungtungia (Teleostei; Cypriniformes; Gobioninae Inferred from Multiple Nuclear Gene Sequences

    Directory of Open Access Journals (Sweden)

    Keun-Yong Kim

    2013-01-01

    Full Text Available Gobionine species belonging to the genera Pseudorasbora, Pseudopungtungia, and Pungtungia (Teleostei; Cypriniformes; Cyprinidae have been heavily studied because of problems on taxonomy, threats of extinction, invasion, and human health. Nucleotide sequences of three nuclear genes, that is, recombination activating protein gene 1 (rag1, recombination activating gene 2 (rag2, and early growth response 1 gene (egr1, from Pseudorasbora, Pseudopungtungia, and Pungtungia species residing in China, Japan, and Korea, were analyzed to elucidate their intergeneric and interspecific phylogenetic relationships. In the phylogenetic tree inferred from their multiple gene sequences, Pseudorasbora, Pseudopungtungia and Pungtungia species ramified into three phylogenetically distinct clades; the “tenuicorpa” clade composed of Pseudopungtungia tenuicorpa, the “parva” clade composed of all Pseudorasbora species/subspecies, and the “herzi” clade composed of Pseudopungtungia nigra, and Pungtungia herzi. The genus Pseudorasbora was recovered as monophyletic, while the genus Pseudopungtungia was recovered as polyphyletic. Our phylogenetic result implies the unstable taxonomic status of the genus Pseudopungtungia.

  20. Gene interactions and genetics of blast resistance and yield ...

    Indian Academy of Sciences (India)

    2014-08-11

    Aug 11, 2014 ... of chemical measures for the control and management of blast, which are not .... tion of genetic components of variation, epistasis model and gene effects in two .... and environmental variance is estimated from mean variance.

  1. 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...

  2. The wheat resistance gene Lr34 results in the constitutive induction of multiple defense pathways in transgenic barley.

    Science.gov (United States)

    Chauhan, Harsh; Boni, Rainer; Bucher, Rahel; Kuhn, Benjamin; Buchmann, Gabriele; Sucher, Justine; Selter, Liselotte L; Hensel, Goetz; Kumlehn, Jochen; Bigler, Laurent; Glauser, Gaëtan; Wicker, Thomas; Krattinger, Simon G; Keller, Beat

    2015-10-01

    The wheat gene Lr34 encodes an ABCG-type transporter which provides durable resistance against multiple pathogens. Lr34 is functional as a transgene in barley, but its mode of action has remained largely unknown both in wheat and barley. Here we studied gene expression in uninfected barley lines transgenic for Lr34. Genes from multiple defense pathways contributing to basal and inducible disease resistance were constitutively active in seedlings and mature leaves. In addition, the hormones jasmonic acid and salicylic acid were induced to high levels, and increased levels of lignin as well as hordatines were observed. These results demonstrate a strong, constitutive re-programming of metabolism by Lr34. The resistant Lr34 allele (Lr34res) encodes a protein that differs by two amino acid polymorphisms from the susceptible Lr34sus allele. The deletion of a single phenylalanine residue in Lr34sus was sufficient to induce the characteristic Lr34-based responses. Combination of Lr34res and Lr34sus in the same plant resulted in a reduction of Lr34res expression by 8- to 20-fold when the low-expressing Lr34res line BG8 was used as a parent. Crosses with the high-expressing Lr34res line BG9 resulted in an increase of Lr34sus expression by 13- to 16-fold in progenies that inherited both alleles. These results indicate an interaction of the two Lr34 alleles on the transcriptional level. Reduction of Lr34res expression in BG8 crosses reduced the negative pleiotropic effects of Lr34res on barley growth and vigor without compromising disease resistance, suggesting that transgenic combination of Lr34res and Lr34sus can result in agronomically useful resistance. © 2015 The Authors The Plant Journal © 2015 John Wiley & Sons Ltd.

  3. Overexpression of multiple detoxification genes in deltamethrin resistant Laodelphax striatellus (Hemiptera: Delphacidae in China.

    Directory of Open Access Journals (Sweden)

    Lu Xu

    Full Text Available BACKGROUND: The small brown planthopper (SBPH, Laodelphax striatellus (Fallén, is one of the major rice pests in Asia and has developed resistance to multiple classes of insecticides. Understanding resistance mechanisms is essential to the management of this pest. Biochemical and molecular assays were performed in this study to systematically characterize deltamethrin resistance mechanisms with laboratory-selected resistant and susceptible strains of SBPH. METHODOLOGY/PRINCIPAL FINDINGS: Deltamethrin resistant strains of SBPH (JH-del were derived from a field population by continuously selections (up to 30 generations in the laboratory, while a susceptible strain (JHS was obtained from the same population by removing insecticide pressure for 30 generations. The role of detoxification enzymes in the resistance was investigated using synergism and enzyme activity assays with strains of different resistant levels. Furthermore, 71 cytochrome P450, 93 esterases and 12 glutathione-S-transferases cDNAs were cloned based on transcriptome data of a field collected population. Semi-quantitative RT-PCR screening analysis of 176 identified detoxification genes demonstrated that multiple P450 and esterase genes were overexpressed (>2-fold in JH-del strains (G4 and G30 when compared to that in JHS, and the results of quantitative PCR coincided with the semi-quantitative RT-PCR results. Target mutation at IIS3-IIS6 regions encoded by the voltage-gated sodium channel gene was ruled out for conferring the observed resistance. CONCLUSION/SIGNIFICANCE: As the first attempt to discover genes potentially involved in SBPH pyrethroid resistance, this study putatively identified several candidate genes of detoxification enzymes that were significantly overexpressed in the resistant strain, which matched the synergism and enzyme activity testing. The biochemical and molecular evidences suggest that the high level pyrethroid resistance in L. striatellus could be due to

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

    Science.gov (United States)

    Zeng, Fangfang; Zhou, Linuo; Tang, Zihui

    2016-01-01

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

  5. 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

  6. 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.

  7. 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.

  8. A spatial theory for emergent multiple predator-prey interactions in food webs.

    Science.gov (United States)

    Northfield, Tobin D; Barton, Brandon T; Schmitz, Oswald J

    2017-09-01

    Predator-prey interaction is inherently spatial because animals move through landscapes to search for and consume food resources and to avoid being consumed by other species. The spatial nature of species interactions necessitates integrating spatial processes into food web theory and evaluating how predators combine to impact their prey. Here, we present a spatial modeling approach that examines emergent multiple predator effects on prey within landscapes. The modeling is inspired by the habitat domain concept derived from empirical synthesis of spatial movement and interactions studies. Because these principles are motivated by synthesis of short-term experiments, it remains uncertain whether spatial contingency principles hold in dynamical systems. We address this uncertainty by formulating dynamical systems models, guided by core habitat domain principles, to examine long-term multiple predator-prey spatial dynamics. To describe habitat domains, we use classical niche concepts describing resource utilization distributions, and assume species interactions emerge from the degree of overlap between species. The analytical results generally align with those from empirical synthesis and present a theoretical framework capable of demonstrating multiple predator effects that does not depend on the small spatial or temporal scales typical of mesocosm experiments, and help bridge between empirical experiments and long-term dynamics in natural systems.

  9. The pituitary tumor transforming gene 1 (PTTG-1: An immunological target for multiple myeloma

    Directory of Open Access Journals (Sweden)

    Gagliano Nicoletta

    2008-04-01

    Full Text Available Abstract Background Multiple Myeloma is a cancer of B plasma cells, which produce non-specific antibodies and proliferate uncontrolled. Due to the potential relapse and non-specificity of current treatments, immunotherapy promises to be more specific and may induce long-term immunity in patients. The pituitary tumor transforming gene 1 (PTTG-1 has been shown to be a novel oncogene, expressed in the testis, thymus, colon, lung and placenta (undetectable in most other tissues. Furthermore, it is over expressed in many tumors such as the pituitary adenoma, breast, gastrointestinal cancers, leukemia, lymphoma, and lung cancer and it seems to be associated with tumorigenesis, angiogenesis and cancer progression. The purpose was to investigate the presence/rate of expression of PTTG-1 in multiple myeloma patients. Methods We analyzed the PTTG-1 expression at the transcriptional and the protein level, by PCR, immunocytochemical methods, Dot-blot and ELISA performed on patient's sera in 19 multiple myeloma patients, 6 different multiple myeloma cell lines and in normal human tissue. Results We did not find PTTG-1 presence in the normal human tissue panel, but PTTG-1 mRNA was detectable in 12 of the 19 patients, giving evidence of a 63% rate of expression (data confirmed by ELISA. Four of the 6 investigated cell lines (66.6% were positive for PTTG-1. Investigations of protein expression gave evidence of 26.3% cytoplasmic expression and 16% surface expression in the plasma cells of multiple myeloma patients. Protein presence was also confirmed by Dot-blot in both cell lines and patients. Conclusion We established PTTG-1's presence at both the transcriptional and protein levels. These data suggest that PTTG-1 is aberrantly expressed in multiple myeloma plasma cells, is highly immunogenic and is a suitable target for immunotherapy of multiple myeloma.

  10. Charged multiplicity distributions in anti np interactions at 6 GeV/c

    International Nuclear Information System (INIS)

    Batyunya, B.V.; Boguslavskij, I.B.; Gramenitskij, I.M.

    1980-01-01

    Inelastic topological anti np cross sections at 6 GeV/c have been determined based on a study of the charged multiplicity distribution in antideuteron-proton collisions at 12 GeV/c. The data were obtained in an exposure of the ''Ludmila'' JINR 2 m hydrogen bubble chamber at the Serpukhov accelerator. In anti np interactions average charged multiplicity and its ratio to dispersion, /D, were found to be 3.32+-0.13 and 1.86+-0.16, respectively. Comparison with anti pn, anti pp and pp data was made

  11. Genetic diversity and population structure of Lantana camara in India indicates multiple introductions and gene flow.

    Science.gov (United States)

    Ray, A; Quader, S

    2014-05-01

    Lantana camara is a highly invasive plant, which has spread over 60 countries and island groups of Asia, Africa and Australia. In India, it was introduced in the early nineteenth century, since when it has expanded and gradually established itself in almost every available ecosystem. We investigated the genetic diversity and population structure of this plant in India in order to understand its introduction, subsequent range expansion and gene flow. A total of 179 individuals were sequenced at three chloroplast loci and 218 individuals were genotyped for six nuclear microsatellites. Both chloroplasts (nine haplotypes) and microsatellites (83 alleles) showed high genetic diversity. Besides, each type of marker confirmed the presence of private polymorphism. We uncovered low to medium population structure in both markers, and found a faint signal of isolation by distance with microsatellites. Bayesian clustering analyses revealed multiple divergent genetic clusters. Taken together, these findings (i.e. high genetic diversity with private alleles and multiple genetic clusters) suggest that Lantana was introduced multiple times and gradually underwent spatial expansion with recurrent gene flow. © 2013 German Botanical Society and The Royal Botanical Society of the Netherlands.

  12. PCA-based bootstrap confidence interval tests for gene-disease association involving multiple SNPs

    Directory of Open Access Journals (Sweden)

    Xue Fuzhong

    2010-01-01

    Full Text Available Abstract Background Genetic association study is currently the primary vehicle for identification and characterization of disease-predisposing variant(s which usually involves multiple single-nucleotide polymorphisms (SNPs available. However, SNP-wise association tests raise concerns over multiple testing. Haplotype-based methods have the advantage of being able to account for correlations between neighbouring SNPs, yet assuming Hardy-Weinberg equilibrium (HWE and potentially large number degrees of freedom can harm its statistical power and robustness. Approaches based on principal component analysis (PCA are preferable in this regard but their performance varies with methods of extracting principal components (PCs. Results PCA-based bootstrap confidence interval test (PCA-BCIT, which directly uses the PC scores to assess gene-disease association, was developed and evaluated for three ways of extracting PCs, i.e., cases only(CAES, controls only(COES and cases and controls combined(CES. Extraction of PCs with COES is preferred to that with CAES and CES. Performance of the test was examined via simulations as well as analyses on data of rheumatoid arthritis and heroin addiction, which maintains nominal level under null hypothesis and showed comparable performance with permutation test. Conclusions PCA-BCIT is a valid and powerful method for assessing gene-disease association involving multiple SNPs.

  13. Investigation of autism and GABA receptor subunit genes in multiple ethnic groups

    OpenAIRE

    Collins, Ann L.; Ma, Deqiong; Whitehead, Patrice L.; Martin, Eden R.; Wright, Harry H.; Abramson, Ruth K.; Hussman, John P.; Haines, Jonathan L.; Cuccaro, Michael L.; Gilbert, John R.; Pericak-Vance, Margaret A.

    2006-01-01

    Autism is a neurodevelopmental disorder of complex genetics, characterized by impairment in social interaction and communication, as well as repetitive behavior. Multiple lines of evidence, including alterations in levels of GABA and GABA receptors in autistic patients, indicate that the GABAergic system, which is responsible for synaptic inhibition in the adult brain, may be involved in autism. Previous studies in our lab indicated association of noncoding single nucleotide polymorphisms (SN...

  14. A gene expression system offering multiple levels of regulation: the Dual Drug Control (DDC) system.

    Science.gov (United States)

    Sudomoina, Marina; Latypova, Ekaterina; Favorova, Olga O; Golemis, Erica A; Serebriiskii, Ilya G

    2004-04-29

    Whether for cell culture studies of protein function, construction of mouse models to enable in vivo analysis of disease epidemiology, or ultimately gene therapy of human diseases, a critical enabling step is the ability to achieve finely controlled regulation of gene expression. Previous efforts to achieve this goal have explored inducible drug regulation of gene expression, and construction of synthetic promoters based on two-hybrid paradigms, among others. In this report, we describe the combination of dimerizer-regulated two-hybrid and tetracycline regulatory elements in an ordered cascade, placing expression of endpoint reporters under the control of two distinct drugs. In this Dual Drug Control (DDC) system, a first plasmid expresses fusion proteins to DBD and AD, which interact only in the presence of a small molecule dimerizer; a second plasmid encodes a cassette transcriptionally responsive to the first DBD, directing expression of the Tet-OFF protein; and a third plasmid encodes a reporter gene transcriptionally responsive to binding by Tet-OFF. We evaluate the dynamic range and specificity of this system in comparison to other available systems. This study demonstrates the feasibility of combining two discrete drug-regulated expression systems in a temporally sequential cascade, without loss of dynamic range of signal induction. The efficient layering of control levels allowed by this combination of elements provides the potential for the generation of complex control circuitry that may advance ability to regulate gene expression in vivo.

  15. A gene expression system offering multiple levels of regulation: the Dual Drug Control (DDC system

    Directory of Open Access Journals (Sweden)

    Golemis Erica A

    2004-04-01

    Full Text Available Abstract Background Whether for cell culture studies of protein function, construction of mouse models to enable in vivo analysis of disease epidemiology, or ultimately gene therapy of human diseases, a critical enabling step is the ability to achieve finely controlled regulation of gene expression. Previous efforts to achieve this goal have explored inducible drug regulation of gene expression, and construction of synthetic promoters based on two-hybrid paradigms, among others. Results In this report, we describe the combination of dimerizer-regulated two-hybrid and tetracycline regulatory elements in an ordered cascade, placing expression of endpoint reporters under the control of two distinct drugs. In this Dual Drug Control (DDC system, a first plasmid expresses fusion proteins to DBD and AD, which interact only in the presence of a small molecule dimerizer; a second plasmid encodes a cassette transcriptionally responsive to the first DBD, directing expression of the Tet-OFF protein; and a third plasmid encodes a reporter gene transcriptionally responsive to binding by Tet-OFF. We evaluate the dynamic range and specificity of this system in comparison to other available systems. Conclusion This study demonstrates the feasibility of combining two discrete drug-regulated expression systems in a temporally sequential cascade, without loss of dynamic range of signal induction. The efficient layering of control levels allowed by this combination of elements provides the potential for the generation of complex control circuitry that may advance ability to regulate gene expression in vivo.

  16. Temporal Sequence of Visuo-Auditory Interaction in Multiple Areas of the Guinea Pig Visual Cortex

    Science.gov (United States)

    Nishimura, Masataka; Song, Wen-Jie

    2012-01-01

    Recent studies in humans and monkeys have reported that acoustic stimulation influences visual responses in the primary visual cortex (V1). Such influences can be generated in V1, either by direct auditory projections or by feedback projections from extrastriate cortices. To test these hypotheses, cortical activities were recorded using optical imaging at a high spatiotemporal resolution from multiple areas of the guinea pig visual cortex, to visual and/or acoustic stimulations. Visuo-auditory interactions were evaluated according to differences between responses evoked by combined auditory and visual stimulation, and the sum of responses evoked by separate visual and auditory stimulations. Simultaneous presentation of visual and acoustic stimulations resulted in significant interactions in V1, which occurred earlier than in other visual areas. When acoustic stimulation preceded visual stimulation, significant visuo-auditory interactions were detected only in V1. These results suggest that V1 is a cortical origin of visuo-auditory interaction. PMID:23029483

  17. Comparison of charged particle multiplicity distributions in p tilde p and pp interactions and verification of the dual unitarization scheme

    International Nuclear Information System (INIS)

    Batyunya, B.V.; Boguslavsky, I.V.; Gramenitsky, I.M.

    1979-01-01

    The difference between antiproton annihilation and pp interactions has been discussed. Charged particle multiplicity distributions in anti pp-interactions at 22.4 GeV/c were used to obtain antiproton annihilation characteristics. The comparison of the topological cross section of antipp interactions with those of non-diffractive pp interactions confirms the validity of dual unitarization

  18. Temporal scale dependent interactions between multiple environmental disturbances in microcosm ecosystems.

    Science.gov (United States)

    Garnier, Aurélie; Pennekamp, Frank; Lemoine, Mélissa; Petchey, Owen L

    2017-12-01

    Global environmental change has negative impacts on ecological systems, impacting the stable provision of functions, goods, and services. Whereas effects of individual environmental changes (e.g. temperature change or change in resource availability) are reasonably well understood, we lack information about if and how multiple changes interact. We examined interactions among four types of environmental disturbance (temperature, nutrient ratio, carbon enrichment, and light) in a fully factorial design using a microbial aquatic ecosystem and observed responses of dissolved oxygen saturation at three temporal scales (resistance, resilience, and return time). We tested whether multiple disturbances combine in a dominant, additive, or interactive fashion, and compared the predictability of dissolved oxygen across scales. Carbon enrichment and shading reduced oxygen concentration in the short term (i.e. resistance); although no other effects or interactions were statistically significant, resistance decreased as the number of disturbances increased. In the medium term, only enrichment accelerated recovery, but none of the other effects (including interactions) were significant. In the long term, enrichment and shading lengthened return times, and we found significant two-way synergistic interactions between disturbances. The best performing model (dominant, additive, or interactive) depended on the temporal scale of response. In the short term (i.e. for resistance), the dominance model predicted resistance of dissolved oxygen best, due to a large effect of carbon enrichment, whereas none of the models could predict the medium term (i.e. resilience). The long-term response was best predicted by models including interactions among disturbances. Our results indicate the importance of accounting for the temporal scale of responses when researching the effects of environmental disturbances on ecosystems. © 2017 The Authors. Global Change Biology Published by John Wiley

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

    Science.gov (United States)

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

    2013-01-01

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

  20. Human mast cell tryptase: Multiple cDNAs and genes reveal a multigene serine protease family

    International Nuclear Information System (INIS)

    Vanderslice, P.; Ballinger, S.M.; Tam, E.K.; Goldstein, S.M.; Craik, C.S.; Caughey, G.H.

    1990-01-01

    Three different cDNAs and a gene encoding human skin mast cell tryptase have been cloned and sequenced in their entirety. The deduced amino acid sequences reveal a 30-amino acid prepropeptide followed by a 245-amino acid catalytic domain. The C-terminal undecapeptide of the human preprosequence is identical in dog tryptase and appears to be part of a prosequence unique among serine proteases. The differences among the three human tryptase catalytic domains include the loss of a consensus N-glycosylation site in one cDNA, which may explain some of the heterogeneity in size and susceptibility to deglycosylation seen in tryptase preparations. All three tryptase cDNAs are distinct from a recently reported cDNA obtained from a human lung mast cell library. A skin tryptase cDNA was used to isolate a human tryptase gene, the exons of which match one of the skin-derived cDNAs. The organization of the ∼1.8-kilobase-pair tryptase gene is unique and is not closely related to that of any other mast cell or leukocyte serine protease. The 5' regulatory regions of the gene share features with those of other serine proteases, including mast cell chymase, but are unusual in being separated from the protein-coding sequence by an intron. High-stringency hybridization of a human genomic DNA blot with a fragment of the tryptase gene confirms the presence of multiple tryptase genes. These findings provide genetic evidence that human mast cell tryptases are the products of a multigene family

  1. The multiple roles of hypothetical gene BPSS1356 in Burkholderia pseudomallei.

    Directory of Open Access Journals (Sweden)

    Hokchai Yam

    Full Text Available Burkholderia pseudomallei is an opportunistic pathogen and the causative agent of melioidosis. It is able to adapt to harsh environments and can live intracellularly in its infected hosts. In this study, identification of transcriptional factors that associate with the β' subunit (RpoC of RNA polymerase was performed. The N-terminal region of this subunit is known to trigger promoter melting when associated with a sigma factor. A pull-down assay using histidine-tagged B. pseudomallei RpoC N-terminal region as bait showed that a hypothetical protein BPSS1356 was one of the proteins bound. This hypothetical protein is conserved in all B. pseudomallei strains and present only in the Burkholderia genus. A BPSS1356 deletion mutant was generated to investigate its biological function. The mutant strain exhibited reduced biofilm formation and a lower cell density during the stationary phase of growth in LB medium. Electron microscopic analysis revealed that the ΔBPSS1356 mutant cells had a shrunken cytoplasm indicative of cell plasmolysis and a rougher surface when compared to the wild type. An RNA microarray result showed that a total of 63 genes were transcriptionally affected by the BPSS1356 deletion with fold change values of higher than 4. The expression of a group of genes encoding membrane located transporters was concurrently down-regulated in ΔBPSS1356 mutant. Amongst the affected genes, the putative ion transportation genes were the most severely suppressed. Deprivation of BPSS1356 also down-regulated the transcriptions of genes for the arginine deiminase system, glycerol metabolism, type III secretion system cluster 2, cytochrome bd oxidase and arsenic resistance. It is therefore obvious that BPSS1356 plays a multiple regulatory roles on many genes.

  2. Interactions between organic anions on multiple transporters in Caco-2 cells

    DEFF Research Database (Denmark)

    Grandvuinet, Anne Sophie; Steffansen, Bente

    2011-01-01

    Caco-2 cell line may be used as an overall model to predict interactions on multiple membrane transporters in the intestine. Taurocholic acid (TCA) and estrone-3-sulfate (E1S) were used as model substrates. Possible inhibitors studied were TCA, E1S, taurolithocholic acid, fluvastatin, and glipizide......-dependent bile acid transporter and the organic solute transporter α/β, and to less extent by the organic anion transporting polypeptide 2B1. However, interactions on efflux transporters were not detected, although they were expected from the literature on the investigated compounds. Biosimulation methods may...

  3. Polymorphisms in genes encoding leptin, ghrelin and their receptors in German multiple sclerosis patients.

    Science.gov (United States)

    Rey, Linda K; Wieczorek, Stefan; Akkad, Denis A; Linker, Ralf A; Chan, Andrew; Hoffjan, Sabine

    2011-01-01

    Multiple sclerosis (MS) is a neuro-inflammatory, autoimmune disease influenced by environmental and polygenic components. There is growing evidence that the peptide hormone leptin, known to regulate energy homeostasis, as well as its antagonist ghrelin play an important role in inflammatory processes in autoimmune diseases, including MS. Recently, single nucleotide polymorphisms (SNPs) in the genes encoding leptin, ghrelin and their receptors were evaluated, amongst others, in Wegener's granulomatosis and Churg-Strauss syndrome. The Lys656Asn SNP in the LEPR gene showed a significant but contrasting association with these vasculitides. We therefore aimed at investigating these polymorphisms in a German MS case-control cohort. Twelve SNPs in the LEP, LEPR, GHRL and GHSR genes were genotyped in 776 MS patients and 878 control subjects. We found an association of a haplotype in the GHSR gene with MS that could not be replicated in a second cohort. Otherwise, no significant differences in allele or genotype frequencies were observed between patients and controls in this particular cohort. Thus, the present results do not support the hypothesis that genetic variation in the leptin/ghrelin system contributes substantially to the pathogenesis of MS. However, a modest effect of GHSR variation cannot be ruled out and needs to be further evaluated in future studies. Copyright © 2011 Elsevier Ltd. All rights reserved.

  4. Multiple gene analyses identify distinct “bois noir” phytoplasma genotypes in the Republic of Macedonia

    Directory of Open Access Journals (Sweden)

    Emilija KOSTADINOVSKA

    2015-01-01

    Full Text Available “Bois noir” (BN is a grapevine yellows disease, associated with phytoplasma strains related to ‘Candidatus Phytoplasma solani’, that causes severe losses to viticulture in the Euro-Mediterranean basin. Due to the complex ecological cycle of its etiological agent, BN epidemiology is only partially known, and no effective control strategies have been developed. Numerous studies have focused on molecular characterization of BN phytoplasma strains, to identify molecular markers useful to accurately describe their genetic diversity, geographic distribution and host range. In the present study, a multiple gene analysess were carried out on 16S rRNA, tuf, vmp1, and stamp genes to study the genetic variability among 18 BN phytoplasma strains detected in diverse regions of the Republic of Macedonia. Restriction fragment length polymorphism (RFLP assays showed the presence of one 16S rRNA (16SrXII-A, two tuf (tuf-type a, tuf-type b, five vmp1 (V2-TA, V3, V4, V14, V18, and three stamp (S1, S2, S3 gene patterns among the examined strains. Based on the collective RFLP patterns, seven genotypes (Mac1 to Mac7 were described as evidence for genetic heterogeneity, and highlighting their prevalence and distribution in the investigated regions. Phylogenetic analyses on vmp1 and stamp genes underlined the affiliation of Macedonian BN phytoplasma strains to clusters associated with distinct ecologies.

  5. Multiple organ gigantism caused by mutation in VmPPD gene in blackgram (Vigna mungo).

    Science.gov (United States)

    Naito, Ken; Takahashi, Yu; Chaitieng, Bubpa; Hirano, Kumi; Kaga, Akito; Takagi, Kyoko; Ogiso-Tanaka, Eri; Thavarasook, Charaspon; Ishimoto, Masao; Tomooka, Norihiko

    2017-03-01

    Seed size is one of the most important traits in leguminous crops. We obtained a recessive mutant of blackgram that had greatly enlarged leaves, stems and seeds. The mutant produced 100% bigger leaves, 50% more biomass and 70% larger seeds though it produced 40% less number of seeds. We designated the mutant as multiple-organ-gigantism ( mog ) and found the mog phenotype was due to increase in cell numbers but not in cell size. We also found the mog mutant showed a rippled leaf ( rl ) phenotype, which was probably caused by a pleiotropic effect of the mutation. We performed a map-based cloning and successfully identified an 8 bp deletion in the coding sequence of VmPPD gene, an orthologue of Arabidopsis PEAPOD ( PPD ) that regulates arrest of cell divisions in meristematic cells . We found no other mutations in the neighboring genes between the mutant and the wild type. We also knocked down GmPPD genes and reproduced both the mog and rl phenotypes in soybean. Controlling PPD genes to produce the mog phenotype is highly valuable for breeding since larger seed size could directly increase the commercial values of grain legumes.

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

    NARCIS (Netherlands)

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

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

  7. 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

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

    Indian Academy of Sciences (India)

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

  9. Interaction of multiple plasma plumes in an atmospheric pressure plasma jet array

    International Nuclear Information System (INIS)

    Ghasemi, M; Olszewski, P; Bradley, J W; Walsh, J L

    2013-01-01

    Plasma jet arrays are considered a viable means to enhance the scale of a downstream surface treatment beyond that possible using a single plasma jet. Of paramount importance in many processing applications is the uniformity of the plasma exposure on the substrate, which can be compromised when multiple plasma jets are arranged in close proximity due to their interaction. This contribution explores a dielectric barrier plasma jet array consisting of multiple individually ballasted jets. It is shown that capacitive ballasting is a promising technique to allow simultaneous operation of the plasma plumes without the losses associated with resistive ballasting. The interaction between adjacent plasma plumes and the background gas is investigated with Schlieren imaging; it is shown that the strong repulsive force between each plasma plume causes a divergence in propagation trajectory and a reduction in the laminar flow length with significant ramifications for any downstream surface treatment.

  10. 7th International Workshop on Multiple Partonic Interactions at the LHC

    CERN Document Server

    Treleani, Daniele; Strikman, Mark; van Buuren, Nadia

    2016-01-01

    From the start of the experimental activity of the Large Hadron Collider, Multiple Partonic Interactions (MPI) are experiencing a growing popularity and are widely invoked to account for observations that cannot be explained otherwise. This includes associated hadron production (Underlying Event) in high energy hadronic collisions with jets, the rates for multiple heavy flavor production, the survival probability of large rapidity gaps in hard diffraction, etc. In particular Double Parton Interactions were observed directly and studied by a number of the FNAL and LHC experiments in different reaction channels. At the LHC a new QCD regime has now been reached, where MPIs occur with high rates, in particular in central collisions, where the production of new particles is more likely to take place. Understanding MPIs is therefore crucial, both for their significant contribution to the background of various processes of interest for the search of new physics and because MPIs are an interesting topic of research b...

  11. Screening of point mutations by multiple SSCP analysis in the dystrophin gene

    Energy Technology Data Exchange (ETDEWEB)

    Lasa, A.; Baiget, M.; Gallano, P. [Hospital Sant Pau, Barcelona (Spain)

    1994-09-01

    Duchenne muscular dystrophy (DMD) is a lethal, X-linked neuromuscular disorder. The population frequency of DMD is one in approximately 3500 boys, of which one third is thought to be a new mutant. The DMD gene is the largest known to date, spanning over 2,3 Mb in band Xp21.2; 79 exons are transcribed into a 14 Kb mRNA coding for a protein of 427 kD which has been named dystrophin. It has been shown that about 65% of affected boys have a gene deletion with a wide variation in localization and size. The remaining affected individuals who have no detectable deletions or duplications would probably carry more subtle mutations that are difficult to detect. These mutations occur in several different exons and seem to be unique to single patients. Their identification represents a formidable goal because of the large size and complexity of the dystrophin gene. SSCP is a very efficient method for the detection of point mutations if the parameters that affect the separation of the strands are optimized for a particular DNA fragment. The multiple SSCP allows the simultaneous study of several exons, and implies the use of different conditions because no single set of conditions will be optimal for all fragments. Seventy-eight DMD patients with no deletion or duplication in the dystrophin gene were selected for the multiple SSCP analysis. Genomic DNA from these patients was amplified using the primers described for the diagnosis procedure (muscle promoter and exons 3, 8, 12, 16, 17, 19, 32, 45, 48 and 51). We have observed different mobility shifts in bands corresponding to exons 8, 12, 43 and 51. In exons 17 and 45, altered electrophoretic patterns were found in different samples identifying polymorphisms already described.

  12. Association of a novel point mutation in MSH2 gene with familial multiple primary cancers

    Directory of Open Access Journals (Sweden)

    Hai Hu

    2017-10-01

    Full Text Available Abstract Background Multiple primary cancers (MPC have been identified as two or more cancers without any subordinate relationship that occur either simultaneously or metachronously in the same or different organs of an individual. Lynch syndrome is an autosomal dominant genetic disorder that increases the risk of many types of cancers. Lynch syndrome patients who suffer more than two cancers can also be considered as MPC; patients of this kind provide unique resources to learn how genetic mutation causes MPC in different tissues. Methods We performed a whole genome sequencing on blood cells and two tumor samples of a Lynch syndrome patient who was diagnosed with five primary cancers. The mutational landscape of the tumors, including somatic point mutations and copy number alternations, was characterized. We also compared Lynch syndrome with sporadic cancers and proposed a model to illustrate the mutational process by which Lynch syndrome progresses to MPC. Results We revealed a novel pathologic mutation on the MSH2 gene (G504 splicing that associates with Lynch syndrome. Systematical comparison of the mutation landscape revealed that multiple cancers in the proband were evolutionarily independent. Integrative analysis showed that truncating mutations of DNA mismatch repair (MMR genes were significantly enriched in the patient. A mutation progress model that included germline mutations of MMR genes, double hits of MMR system, mutations in tissue-specific driver genes, and rapid accumulation of additional passenger mutations was proposed to illustrate how MPC occurs in Lynch syndrome patients. Conclusion Our findings demonstrate that both germline and somatic alterations are driving forces of carcinogenesis, which may resolve the carcinogenic theory of Lynch syndrome.

  13. Multiple coupled landscapes and non-adiabatic dynamics with applications to self-activating genes.

    Science.gov (United States)

    Chen, Cong; Zhang, Kun; Feng, Haidong; Sasai, Masaki; Wang, Jin

    2015-11-21

    Many physical, chemical and biochemical systems (e.g. electronic dynamics and gene regulatory networks) are governed by continuous stochastic processes (e.g. electron dynamics on a particular electronic energy surface and protein (gene product) synthesis) coupled with discrete processes (e.g. hopping among different electronic energy surfaces and on and off switching of genes). One can also think of the underlying dynamics as the continuous motion on a particular landscape and discrete hoppings among different landscapes. The main difference of such systems from the intra-landscape dynamics alone is the emergence of the timescale involved in transitions among different landscapes in addition to the timescale involved in a particular landscape. The adiabatic limit when inter-landscape hoppings are fast compared to continuous intra-landscape dynamics has been studied both analytically and numerically, but the analytical treatment of the non-adiabatic regime where the inter-landscape hoppings are slow or comparable to continuous intra-landscape dynamics remains challenging. In this study, we show that there exists mathematical mapping of the dynamics on 2(N) discretely coupled N continuous dimensional landscapes onto one single landscape in 2N dimensional extended continuous space. On this 2N dimensional landscape, eddy current emerges as a sign of non-equilibrium non-adiabatic dynamics and plays an important role in system evolution. Many interesting physical effects such as the enhancement of fluctuations, irreversibility, dissipation and optimal kinetics emerge due to non-adiabaticity manifested by the eddy current illustrated for an N = 1 self-activator. We further generalize our theory to the N-gene network with multiple binding sites and multiple synthesis rates for discretely coupled non-equilibrium stochastic physical and biological systems.

  14. Gene expression in the tanoak-Phytophthora ramorum interaction

    Science.gov (United States)

    Katherine J. Hayden; Matteo Garbelotto; Hardeep Fai; Brian Knaus; Richard Cronn; Jessica W. Wright

    2012-01-01

    Disease processes are dynamic, involving a suite of gene expression changes in both the host and the pathogen, all within a single tissue. As such, they lend themselves well to transcriptomic analysis. Here we focus on a generalist invasive pathogen (Phytophthora ramorum) and its most susceptible California Floristic Province native host, tanoak (...

  15. Hierarchical folding of multiple sequence alignments for the prediction of structures and RNA-RNA interactions

    DEFF Research Database (Denmark)

    Seemann, Ernst Stefan; Richter, Andreas S.; Gorodkin, Jan

    2010-01-01

    of that used for individual multiple alignments. Results: We derived a rather extensive algorithm. One of the advantages of our approach (in contrast to other RNARNA interaction prediction methods) is the application of covariance detection and prediction of pseudoknots between intra- and inter-molecular base...... pairs. As a proof of concept, we show an example and discuss the strengths and weaknesses of the approach....

  16. Heat Recovery from Multiple-Fracture Enhanced Geothermal Systems: The Effect of Thermoelastic Fracture Interactions

    DEFF Research Database (Denmark)

    Vik, Hedda Slatlem; Salimzadeh, Saeed; Nick, Hamid

    2018-01-01

    This study investigates the effect of thermoelastic interactions between multiple parallel fractures on energy production from a multiple-fracture enhanced geothermal system. A coupled thermo-hydro-mechanical finite element model has been developed that accounts for non-isothermal fluid flow within...... increased to maximise the net energy production from the system. Otherwise, the multiple-fracture system fails to improve the energy recovery from the geothermal reservoir, as initially intended....... aperture in the adjacent fracture, and facilitates the creation of favourable flow pathways between the injection and production wells. These flow paths reduce the energy production from the system. The effects of fracture spacing, reservoir temperature gradient and mechanical properties of the rock matrix...

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

    Directory of Open Access Journals (Sweden)

    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.

  18. 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.

  19. 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.

  20. Numerical Simulations for Nonlinear Waves Interaction with Multiple Perforated Quasi-Ellipse Caissons

    Directory of Open Access Journals (Sweden)

    Xiaozhong Ren

    2015-01-01

    Full Text Available A three-dimensional numerical flume is developed to study cnoidal wave interaction with multiple arranged perforated quasi-ellipse caissons. The continuity equation and the Navier-Stokes equations are used as the governing equation, and the VOF method is adopted to capture the free surface elevation. The equations are discretized on staggered cells and then solved using a finite difference method. The generation and propagation of cnoidal waves in the numerical flume are tested first. And the ability of the present model to simulate interactions between waves and structures is verified by known experimental results. Then cnoidal waves with varying incident wave height and period are generated and interact with multiple quasi-ellipse caissons with and without perforation. It is found that the perforation plays an effective role in reducing wave runup/rundown and wave forces on the caissons. The wave forces on caissons reduce with the decreasing incident wave period. The influence of the transverse distance of multiple caissons on wave forces is also investigated. A closer transverse distance between caissons can produce larger wave forces. But when relative adjacent distance L/D (L is the transverse distance and D is the width of the quasi-ellipse caisson is larger than 3, the effect of adjacent distance is limited.

  1. [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

  2. 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…

  3. 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...

  4. Association of interleukin-1 gene variations with moderate to severe chronic periodontitis in multiple ethnicities

    Science.gov (United States)

    Wu, X; Offenbacher, S; Lόpez, N J; Chen, D; Wang, H-Y; Rogus, J; Zhou, J; Beck, J; Jiang, S; Bao, X; Wilkins, L; Doucette-Stamm, L; Kornman, K

    2015-01-01

    Background and Objective Genetic markers associated with disease are often non-functional and generally tag one or more functional “causative” variants in linkage disequilibrium. Markers may not show tight linkage to the causative variants across multiple ethnicities due to evolutionary divergence, and therefore may not be informative across different population groups. Validated markers of disease suggest causative variants exist in the gene and, if the causative variants can be identified, it is reasonable to hypothesize that such variants will be informative across diverse populations. The aim of this study was to test that hypothesis using functional Interleukin-1 (IL-1) gene variations across multiple ethnic populations to replace the non-functional markers originally associated with chronic adult periodontitis in Caucasians. Material and Methods Adult chronic periodontitis cases and controls from four ethnic groups (Caucasians, African Americans, Hispanics and Asians) were recruited in the USA, Chile and China. Genotypes of IL1B gene single nucleotide polymorphisms (SNPs), including three functional SNPs (rs16944, rs1143623, rs4848306) in the promoter and one intronic SNP (rs1143633), were determined using a single base extension method or TaqMan 5′ nuclease assay. Logistic regression and other statistical analyses were used to examine the association between moderate to severe periodontitis and IL1B gene variations, including SNPs, haplotypes and composite genotypes. Genotype patterns associated with disease in the discovery study were then evaluated in independent validation studies. Results Significant associations were identified in the discovery study, consisting of Caucasians and African Americans, between moderate to severe adult chronic periodontitis and functional variations in the IL1B gene, including a pattern of four IL1B SNPs (OR = 1.87, p < 0.0001). The association between the disease and this IL1B composite genotype pattern was validated

  5. Genome-Wide Constitutively Expressed Gene Analysis and New Reference Gene Selection Based on Transcriptome Data: A Case Study from Poplar/Canker Disease Interaction

    Directory of Open Access Journals (Sweden)

    Jiaping Zhao

    2017-10-01

    Full Text Available A number of transcriptome datasets for differential expression (DE genes have been widely used for understanding organismal biology, but these datasets also contain untapped information that can be used to develop more precise analytical tools. With the use of transcriptome data generated from poplar/canker disease interaction system, we describe a methodology to identify candidate reference genes from high-throughput sequencing data. This methodology will improve the accuracy of RT-qPCR and will lead to better standards for the normalization of expression data. Expression stability analysis from xylem and phloem of Populus bejingensis inoculated with the fungal canker pathogen Botryosphaeria dothidea revealed that 729 poplar transcripts (1.11% were stably expressed, at a threshold level of coefficient of variance (CV of FPKM < 20% and maximum fold change (MFC of FPKM < 2.0. Expression stability and bioinformatics analysis suggested that commonly used house-keeping (HK genes were not the most appropriate internal controls: 70 of the 72 commonly used HK genes were not stably expressed, 45 of the 72 produced multiple isoform transcripts, and some of their reported primers produced unspecific amplicons in PCR amplification. RT-qPCR analysis to compare and evaluate the expression stability of 10 commonly used poplar HK genes and 20 of the 729 newly-identified stably expressed transcripts showed that some of the newly-identified genes (such as SSU_S8e, LSU_L5e, and 20S_PSU had higher stability ranking than most of commonly used HK genes. Based on these results, we recommend a pipeline for deriving reference genes from transcriptome data. An appropriate candidate gene should have a unique transcript, constitutive expression, CV value of expression < 20% (or possibly 30% and MFC value of expression <2, and an expression level of 50–1,000 units. Lastly, when four of the newly identified HK genes were used in the normalization of expression data for 20

  6. Wide range of interacting partners of pea Gβ subunit of G-proteins suggests its multiple functions in cell signalling.

    Science.gov (United States)

    Bhardwaj, Deepak; Lakhanpaul, Suman; Tuteja, Narendra

    2012-09-01

    Climate change is a major concern especially in view of the increasing global population and food security. Plant scientists need to look for genetic tools whose appropriate usage can contribute to sustainable food availability. G-proteins have been identified as some of the potential genetic tools that could be useful for protecting plants from various stresses. Heterotrimeric G-proteins consisting of three subunits Gα, Gβ and Gγ are important components of a number of signalling pathways. Their structure and functions are already well studied in animals but their potential in plants is now gaining attention for their role in stress tolerance. Earlier we have reported that over expressing pea Gβ conferred heat tolerance in tobacco plants. Here we report the interacting partners (proteins) of Gβ subunit of Pisum sativum and their putative role in stress and development. Out of 90 transformants isolated from the yeast-two-hybrid (Y2H) screening, seven were chosen for further investigation due to their recurrence in multiple experiments. These interacting partners were confirmed using β-galactosidase colony filter lift and ONPG (O-nitrophenyl-β-D-galactopyranoside) assays. These partners include thioredoxin H, histidine-containing phosphotransfer protein 5-like, pathogenesis-related protein, glucan endo-beta-1, 3-glucosidase (acidic isoform), glycine rich RNA binding protein, cold and drought-regulated protein (corA gene) and soluble inorganic pyrophosphatase 1. This study suggests the role of pea Gβ subunit in stress signal transduction and development pathways owing to its capability to interact with a wide range of proteins of multiple functions. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

  7. Genetic evaluation with major genes and polygenic inheritance when some animals are not genotyped using gene content multiple-trait BLUP.

    Science.gov (United States)

    Legarra, Andrés; Vitezica, Zulma G

    2015-11-17

    In pedigreed populations with a major gene segregating for a quantitative trait, it is not clear how to use pedigree, genotype and phenotype information when some individuals are not genotyped. We propose to consider gene content at the major gene as a second trait correlated to the quantitative trait, in a gene content multiple-trait best linear unbiased prediction (GCMTBLUP) method. The genetic covariance between the trait and gene content at the major gene is a function of the substitution effect of the gene. This genetic covariance can be written in a multiple-trait form that accommodates any pattern of missing values for either genotype or phenotype data. Effects of major gene alleles and the genetic covariance between genotype at the major gene and the phenotype can be estimated using standard EM-REML or Gibbs sampling. Prediction of breeding values with genotypes at the major gene can use multiple-trait BLUP software. Major genes with more than two alleles can be considered by including negative covariances between gene contents at each different allele. We simulated two scenarios: a selected and an unselected trait with heritabilities of 0.05 and 0.5, respectively. In both cases, the major gene explained half the genetic variation. Competing methods used imputed gene contents derived by the method of Gengler et al. or by iterative peeling. Imputed gene contents, in contrast to GCMTBLUP, do not consider information on the quantitative trait for genotype prediction. GCMTBLUP gave unbiased estimates of the gene effect, in contrast to the other methods, with less bias and better or equal accuracy of prediction. GCMTBLUP improved estimation of genotypes in non-genotyped individuals, in particular if these individuals had own phenotype records and the trait had a high heritability. Ignoring the major gene in genetic evaluation led to serious biases and decreased prediction accuracy. CGMTBLUP is the best linear predictor of additive genetic merit including

  8. Large Display Interaction via Multiple Acceleration Curves and Multifinger Pointer Control

    Directory of Open Access Journals (Sweden)

    Andrey Esakia

    2014-01-01

    Full Text Available Large high-resolution displays combine high pixel density with ample physical dimensions. The combination of these factors creates a multiscale workspace where interactive targeting of on-screen objects requires both high speed for distant targets and high accuracy for small targets. Modern operating systems support implicit dynamic control-display gain adjustment (i.e., a pointer acceleration curve that helps to maintain both speed and accuracy. However, large high-resolution displays require a broader range of control-display gains than a single acceleration curve can usably enable. Some interaction techniques attempt to solve the problem by utilizing multiple explicit modes of interaction, where different modes provide different levels of pointer precision. Here, we investigate the alternative hypothesis of using a single mode of interaction for continuous pointing that enables both (1 standard implicit granularity control via an acceleration curve and (2 explicit switching between multiple acceleration curves in an efficient and dynamic way. We evaluate a sample solution that augments standard touchpad accelerated pointer manipulation with multitouch capability, where the choice of acceleration curve dynamically changes depending on the number of fingers in contact with the touchpad. Specifically, users can dynamically switch among three different acceleration curves by using one, two, or three fingers on the touchpad.

  9. Effects of Pilates exercises on sensory interaction, postural control and fatigue in patients with multiple sclerosis.

    Science.gov (United States)

    Soysal Tomruk, Melda; Uz, Muhammed Zahid; Kara, Bilge; İdiman, Egemen

    2016-05-01

    Decreased postural control, sensory integration deficits and fatigue are important problems that cause functional impairments in patients with multiple sclerosis (pwMS). To examine the effect of modified clinical Pilates exercises on sensory interaction and balance, postural control and fatigue in pwMS. Eleven patients with multiple sclerosis and 12 healthy matched controls were recruited in this study. Limits of stability and postural stability tests were used to evaluate postural control by Biodex Balance System and sensory interaction assessed. Fatigue was assessed by Modified Fatigue Impact Scale. Pilates exercises were applied two times a week for 10 weeks and measurements were repeated to pwMS after exercise training. Postural control and fatigue (except psychosocial parameter) of pwMS were significantly worser than healthy controls (pPilates training (ppilates exercises (p>0.05). Ten-week Pilates training is effective to improve sensory interaction and to decrease fatigue. Pilates exercises can be applied safely in ambulatory pwMS for enhance sensory interaction and balance and combat fatigue. More investigations are needed. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. Game Theory of Tumor–Stroma Interactions in Multiple Myeloma: Effect of Nonlinear Benefits

    Directory of Open Access Journals (Sweden)

    Javad Salimi Sartakhti

    2018-05-01

    Full Text Available Cancer cells and stromal cells often exchange growth factors with paracrine effects that promote cell growth: a form of cooperation that can be studied by evolutionary game theory. Previous models have assumed that interactions between cells are pairwise or that the benefit of a growth factor is a linear function of its concentration. Diffusible factors, however, affect multiple cells and generally have nonlinear effects, and these differences are known to have important consequences for evolutionary dynamics. Here, we study tumor–stroma paracrine signaling using a model with multiplayer collective interactions in which growth factors have nonlinear effects. We use multiple myeloma as an example, modelling interactions between malignant plasma cells, osteoblasts, and osteoclasts. Nonlinear benefits can lead to results not observed in linear models, including internal mixed stable equilibria and cyclical dynamics. Models with linear effects, therefore, do not lead to a meaningful characterization of the dynamics of tumor–stroma interactions. To understand the dynamics and the effect of therapies it is necessary to estimate the shape of the benefit functions experimentally and parametrize models based on these functions.

  11. Measurement of Reconstructed Charged Particle Multiplicities of Neutrino Interactions in MicroBooNE

    Energy Technology Data Exchange (ETDEWEB)

    Rafique, Aleena [Kansas State Univ., Manhattan, KS (United States)

    2017-09-25

    Here, we compare the observed charged particle multiplicity distributions in the MicroBooNE liquid argon time projection chamber from neutrino interactions in a restricted final state phase space to predictions of this distribution from several GENIE models. The measurement uses a data sample consisting of neutrino interactions with a final state muon candidate fully contained within the MicroBooNE detector. These data were collected in 2015-2016 with the Fermilab Booster Neutrino Beam (BNB), which has an average neutrino energy of 800 MeV, using an exposure corresponding to 5e19 protons-on-target. The analysis employs fully automatic event selection and charged particle track reconstruction and uses a data-driven technique to determine the contribution to each multiplicity bin from neutrino interactions and cosmic-induced backgrounds. The restricted phase space employed makes the measurement most sensitive to the higher-energy charged particles expected from primary neutrino-argon collisions and less sensitive to lower energy protons expected to be produced in final state interactions of collision products with the target argon nucleus.

  12. 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.

  13. Development of the Multiple Gene Knockout System with One-Step PCR in Thermoacidophilic Crenarchaeon Sulfolobus acidocaldarius

    Directory of Open Access Journals (Sweden)

    Shoji Suzuki

    2017-01-01

    Full Text Available Multiple gene knockout systems developed in the thermoacidophilic crenarchaeon Sulfolobus acidocaldarius are powerful genetic tools. However, plasmid construction typically requires several steps. Alternatively, PCR tailing for high-throughput gene disruption was also developed in S. acidocaldarius, but repeated gene knockout based on PCR tailing has been limited due to lack of a genetic marker system. In this study, we demonstrated efficient homologous recombination frequency (2.8 × 104 ± 6.9 × 103 colonies/μg DNA by optimizing the transformation conditions. This optimized protocol allowed to develop reliable gene knockout via double crossover using short homologous arms and to establish the multiple gene knockout system with one-step PCR (MONSTER. In the MONSTER, a multiple gene knockout cassette was simply and rapidly constructed by one-step PCR without plasmid construction, and the PCR product can be immediately used for target gene deletion. As an example of the applications of this strategy, we successfully made a DNA photolyase- (phr- and arginine decarboxylase- (argD- deficient strain of S. acidocaldarius. In addition, an agmatine selection system consisting of an agmatine-auxotrophic strain and argD marker was also established. The MONSTER provides an alternative strategy that enables the very simple construction of multiple gene knockout cassettes for genetic studies in S. acidocaldarius.

  14. 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.

  15. Probability distributions in conservative energy exchange models of multiple interacting agents

    International Nuclear Information System (INIS)

    Scafetta, Nicola; West, Bruce J

    2007-01-01

    Herein we study energy exchange models of multiple interacting agents that conserve energy in each interaction. The models differ regarding the rules that regulate the energy exchange and boundary effects. We find a variety of stochastic behaviours that manifest energy equilibrium probability distributions of different types and interaction rules that yield not only the exponential distributions such as the familiar Maxwell-Boltzmann-Gibbs distribution of an elastically colliding ideal particle gas, but also uniform distributions, truncated exponential distributions, Gaussian distributions, Gamma distributions, inverse power law distributions, mixed exponential and inverse power law distributions, and evolving distributions. This wide variety of distributions should be of value in determining the underlying mechanisms generating the statistical properties of complex phenomena including those to be found in complex chemical reactions

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

    Science.gov (United States)

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

    2008-01-01

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

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

    Science.gov (United States)

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

    2008-01-01

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

  18. Analyzing Multiple-Probe Microarray: Estimation and Application of Gene Expression Indexes

    KAUST Repository

    Maadooliat, Mehdi

    2012-07-26

    Gene expression index estimation is an essential step in analyzing multiple probe microarray data. Various modeling methods have been proposed in this area. Amidst all, a popular method proposed in Li and Wong (2001) is based on a multiplicative model, which is similar to the additive model discussed in Irizarry et al. (2003a) at the logarithm scale. Along this line, Hu et al. (2006) proposed data transformation to improve expression index estimation based on an ad hoc entropy criteria and naive grid search approach. In this work, we re-examined this problem using a new profile likelihood-based transformation estimation approach that is more statistically elegant and computationally efficient. We demonstrate the applicability of the proposed method using a benchmark Affymetrix U95A spiked-in experiment. Moreover, We introduced a new multivariate expression index and used the empirical study to shows its promise in terms of improving model fitting and power of detecting differential expression over the commonly used univariate expression index. As the other important content of the work, we discussed two generally encountered practical issues in application of gene expression index: normalization and summary statistic used for detecting differential expression. Our empirical study shows somewhat different findings from the MAQC project (MAQC, 2006).

  19. Interacting genes in the pine-fusiform rust forest pathosystem

    Science.gov (United States)

    H.V. Amerson; T.L. Kubisiak; S.A. Garcia; G.C. Kuhlman; C.D. Nelson; S.E. McKeand; T.J. Mullin; B. Li

    2005-01-01

    Fusiform rust (FR) disease of pines, caused by Cronartium quercuum f.sp. fusiforme (Cqf), is the most destructive disease in pine plantations of the southern U. S. The NCSU fusiform rust program, in conjunction with the USDA-Forest Service in Saucier, MS and Athens, GA, has research underway to elucidate some of the genetic interactions in this...

  20. Multiple caregivers' touch interactions with young children among the Bofi foragers in Central Africa.

    Science.gov (United States)

    Jung, Min-Jung; Fouts, Hillary N

    2011-02-01

    The current study examined the use of three types of touch (caregiving, active social-affectionate, and passive social-affectionate) by caregivers with young children among the Bofi foragers, a seminomadic group of hunter-gatherers in Central Africa. With the purpose of providing a more holistic view of touch interactions in early childhood, compared to extant Western mother-centric views, this study documents stylistic touch patterns used by multiple caregivers (mother, father, adult relatives, and juvenile relatives) with Bofi forager children. Thirty-five Bofi forager children, between 18 and 59 months of age, and their various caregivers were naturalistically observed over 12 daylight hours using a focal child observational technique. Frequencies of each type of touch and the rank order of types of touch that children received were compared between caregivers and examined by child age and gender. Even though nonmaternal caregivers showed high physical involvement with children, mothers exemplified the highest level of involvement. Overall, passive social-affectionate touch was utilized the most by all types of caregivers. Mothers used more caregiving touch, and fathers and adult relatives had similar frequencies of caregiving touch and active social-affectionate touch. In contrast, juvenile relatives showed more active social-affectionate touch with focal children. This study highlights the importance of examining multiple caregivers and physical interactions when studying early childhood experiences. Furthermore, by focusing on multiple caregivers and multiple types of touch, this study provides a more thorough characterization of the touch experiences of young children than previous studies of touch. Finally, the current study exemplifies the value of considering non-Western populations when investigating touch interactions.

  1. Multiple zebrafish atoh1 genes specify a diversity of neuronal types in the zebrafish cerebellum.

    Science.gov (United States)

    Kidwell, Chelsea U; Su, Chen-Ying; Hibi, Masahiko; Moens, Cecilia B

    2018-06-01

    A single Atoh1 basic-helix-loop-helix transcription factor specifies multiple neuron types in the mammalian cerebellum and anterior hindbrain. The zebrafish genome encodes three paralagous atoh1 genes whose functions in cerebellum and anterior hindbrain development we explore here. With use of a transgenic reporter, we report that zebrafish atoh1c-expressing cells are organized in two distinct domains that are separated both by space and developmental time. An early isthmic expression domain gives rise to an extracerebellar population in rhombomere 1 and an upper rhombic lip domain gives rise to granule cell progenitors that migrate to populate all four granule cell territories of the fish cerebellum. Using genetic mutants we find that of the three zebrafish atoh1 paralogs, atoh1c and atoh1a are required for the full complement of granule neurons. Surprisingly, the two genes are expressed in non-overlapping granule cell progenitor populations, indicating that fish use duplicate atoh1 genes to generate granule cell diversity that is not detected in mammals. Finally, live imaging of granule cell migration in wildtype and atoh1c mutant embryos reveals that while atoh1c is not required for granule cell specification per se, it is required for granule cells to delaminate and migrate away from the rhombic lip. Copyright © 2018 Elsevier Inc. All rights reserved.

  2. Genetic transformation and gene silencing mediated by multiple copies of a transgene in eastern white pine.

    Science.gov (United States)

    Tang, Wei; Newton, Ronald J; Weidner, Douglas A

    2007-01-01

    An efficient transgenic eastern white pine (Pinus strobus L.) plant regeneration system has been established using Agrobacterium tumefaciens strain GV3850-mediated transformation and the green fluorescent protein (gfp) gene as a reporter in this investigation. Stable integration of transgenes in the plant genome of pine was confirmed by polymerase chain reaction (PCR), Southern blot, and northern blot analyses. Transgene expression was analysed in pine T-DNA transformants carrying different numbers of copies of T-DNA insertions. Post-transcriptional gene silencing (PTGS) was mostly obtained in transgenic lines with more than three copies of T-DNA, but not in transgenic lines with one copy of T-DNA. In situ hybridization chromosome analysis of transgenic lines demonstrated that silenced transgenic lines had two or more T-DNA insertions in the same chromosome. These results suggest that two or more T-DNA insertions in the same chromosome facilitate efficient gene silencing in transgenic pine cells expressing green fluorescent protein. There were no differences in shoot differentiation and development between transgenic lines with multiple T-DNA copies and transgenic lines with one or two T-DNA copies.

  3. Hairpin RNA Targeting Multiple Viral Genes Confers Strong Resistance to Rice Black-Streaked Dwarf Virus

    Directory of Open Access Journals (Sweden)

    Fangquan Wang

    2016-05-01

    Full Text Available Rice black-streaked dwarf virus (RBSDV belongs to the genus Fijivirus in the family of Reoviridae and causes severe yield loss in rice-producing areas in Asia. RNA silencing, as a natural defence mechanism against plant viruses, has been successfully exploited for engineering virus resistance in plants, including rice. In this study, we generated transgenic rice lines harbouring a hairpin RNA (hpRNA construct targeting four RBSDV genes, S1, S2, S6 and S10, encoding the RNA-dependent RNA polymerase, the putative core protein, the RNA silencing suppressor and the outer capsid protein, respectively. Both field nursery and artificial inoculation assays of three generations of the transgenic lines showed that they had strong resistance to RBSDV infection. The RBSDV resistance in the segregating transgenic populations correlated perfectly with the presence of the hpRNA transgene. Furthermore, the hpRNA transgene was expressed in the highly resistant transgenic lines, giving rise to abundant levels of 21–24 nt small interfering RNA (siRNA. By small RNA deep sequencing, the RBSDV-resistant transgenic lines detected siRNAs from all four viral gene sequences in the hpRNA transgene, indicating that the whole chimeric fusion sequence can be efficiently processed by Dicer into siRNAs. Taken together, our results suggest that long hpRNA targeting multiple viral genes can be used to generate stable and durable virus resistance in rice, as well as other plant species.

  4. Hairpin RNA Targeting Multiple Viral Genes Confers Strong Resistance to Rice Black-Streaked Dwarf Virus.

    Science.gov (United States)

    Wang, Fangquan; Li, Wenqi; Zhu, Jinyan; Fan, Fangjun; Wang, Jun; Zhong, Weigong; Wang, Ming-Bo; Liu, Qing; Zhu, Qian-Hao; Zhou, Tong; Lan, Ying; Zhou, Yijun; Yang, Jie

    2016-05-11

    Rice black-streaked dwarf virus (RBSDV) belongs to the genus Fijivirus in the family of Reoviridae and causes severe yield loss in rice-producing areas in Asia. RNA silencing, as a natural defence mechanism against plant viruses, has been successfully exploited for engineering virus resistance in plants, including rice. In this study, we generated transgenic rice lines harbouring a hairpin RNA (hpRNA) construct targeting four RBSDV genes, S1, S2, S6 and S10, encoding the RNA-dependent RNA polymerase, the putative core protein, the RNA silencing suppressor and the outer capsid protein, respectively. Both field nursery and artificial inoculation assays of three generations of the transgenic lines showed that they had strong resistance to RBSDV infection. The RBSDV resistance in the segregating transgenic populations correlated perfectly with the presence of the hpRNA transgene. Furthermore, the hpRNA transgene was expressed in the highly resistant transgenic lines, giving rise to abundant levels of 21-24 nt small interfering RNA (siRNA). By small RNA deep sequencing, the RBSDV-resistant transgenic lines detected siRNAs from all four viral gene sequences in the hpRNA transgene, indicating that the whole chimeric fusion sequence can be efficiently processed by Dicer into siRNAs. Taken together, our results suggest that long hpRNA targeting multiple viral genes can be used to generate stable and durable virus resistance in rice, as well as other plant species.

  5. Calibration of Multiple In Silico Tools for Predicting Pathogenicity of Mismatch Repair Gene Missense Substitutions

    Science.gov (United States)

    Thompson, Bryony A.; Greenblatt, Marc S.; Vallee, Maxime P.; Herkert, Johanna C.; Tessereau, Chloe; Young, Erin L.; Adzhubey, Ivan A.; Li, Biao; Bell, Russell; Feng, Bingjian; Mooney, Sean D.; Radivojac, Predrag; Sunyaev, Shamil R.; Frebourg, Thierry; Hofstra, Robert M.W.; Sijmons, Rolf H.; Boucher, Ken; Thomas, Alun; Goldgar, David E.; Spurdle, Amanda B.; Tavtigian, Sean V.

    2015-01-01

    Classification of rare missense substitutions observed during genetic testing for patient management is a considerable problem in clinical genetics. The Bayesian integrated evaluation of unclassified variants is a solution originally developed for BRCA1/2. Here, we take a step toward an analogous system for the mismatch repair (MMR) genes (MLH1, MSH2, MSH6, and PMS2) that confer colon cancer susceptibility in Lynch syndrome by calibrating in silico tools to estimate prior probabilities of pathogenicity for MMR gene missense substitutions. A qualitative five-class classification system was developed and applied to 143 MMR missense variants. This identified 74 missense substitutions suitable for calibration. These substitutions were scored using six different in silico tools (Align-Grantham Variation Grantham Deviation, multivariate analysis of protein polymorphisms [MAPP], Mut-Pred, PolyPhen-2.1, Sorting Intolerant From Tolerant, and Xvar), using curated MMR multiple sequence alignments where possible. The output from each tool was calibrated by regression against the classifications of the 74 missense substitutions; these calibrated outputs are interpretable as prior probabilities of pathogenicity. MAPP was the most accurate tool and MAPP + PolyPhen-2.1 provided the best-combined model (R2 = 0.62 and area under receiver operating characteristic = 0.93). The MAPP + PolyPhen-2.1 output is sufficiently predictive to feed as a continuous variable into the quantitative Bayesian integrated evaluation for clinical classification of MMR gene missense substitutions. PMID:22949387

  6. 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

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

    Science.gov (United States)

    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.

  8. 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...

  9. Positive selection of Plasmodium falciparum parasites with multiple var2csa-type PfEMP1 genes during the course of infection in pregnant women

    DEFF Research Database (Denmark)

    Sander, Adam F; Salanti, Ali; Lavstsen, Thomas

    2011-01-01

    multiple genes coding for different VAR2CSA proteins, and parasites with >1 var2csa gene appear to be more common in pregnant women with placental malaria than in nonpregnant individuals. We present evidence that, in pregnant women, parasites containing multiple var2csa-type genes possess a selective...... advantage over parasites with a single var2csa gene. Accumulation of parasites with multiple copies of the var2csa gene during the course of pregnancy was also correlated with the development of antibodies involved in blocking VAR2CSA adhesion. The data suggest that multiplicity of var2csa-type genes...

  10. Multiplicities and forward-backward correlations in anti pp interactions at 22.4 GeV/c

    International Nuclear Information System (INIS)

    Boos, E.G.; Samojlov, V.V.; Tashimov, M.A.

    1977-01-01

    Forward-backward multiplicity correlations in anti pp -interactions at 22.4 GeV/c and multiplicities in a simple icle multiplicity distribution is divided into even and odd components, the probability of producting an odd state is found to be higher than that of producing an even state, which may be interpreted to be due to diffraction forward-backward and to everall multiplicities is discussed

  11. Gene-environment interaction and biological monitoring of occupational exposures

    International Nuclear Information System (INIS)

    Hirvonen, Ari

    2005-01-01

    Biological monitoring methods and biological limit values applied in occupational and environmental medicine have been traditionally developed on the assumption that individuals do not differ significantly in their biotransformation capacities. It has become clear, however, that this is not the case, but wide inter-individual differences exist in the metabolism of chemicals. Integration of the data on individual metabolic capacity in biological monitoring studies is therefore anticipated to represent a significant refinement of the currently used methods. We have recently conducted several biological monitoring studies on occupationally exposed subjects, which have included the determination of the workers' genotypes for the metabolic genes of potential importance for a given chemical exposure. The exposure levels have been measured by urine metabolites, adducts in blood macromolecules, and cytogenetic alterations in lymphocytes. Our studies indicate that genetic polymorphisms in metabolic genes may indeed be important modifiers of individual biological monitoring results of, e.g., carbon disulphide and styrene. The information is anticipated to be useful in insuring that the workplace is safe for everyone, including the most sensitive individuals. This knowledge could also be useful to occupational physicians, industrial hygienists, and regulatory bodies in charge of defining acceptable exposure limits for environmental and/or occupational pollutants

  12. Proceedings of the first international workshop on multiple partonic interactions at the LHC. MPI'08

    Energy Technology Data Exchange (ETDEWEB)

    Bartalini, Paolo [National Taiwan Univ., Taipei (China); Fano, Livio [Istituto Nazionale di Fisica Nucleare, Perugia (Italy)

    2009-06-15

    The objective of this first workshop on Multiple Partonic Interactions (MPI) at the LHC, that can be regarded as a continuation and extension of the dedicated meetings held at DESY in the years 2006 and 2007, is to raise the profile of MPI studies, summarizing the legacy from the older phenomenology at hadronic colliders and favouring further specific contacts between the theory and experimental communities. The MPI are experiencing a growing popularity and are currently widely invoked to account for observations that would not be explained otherwise: the activity of the Underlying Event, the cross sections for multiple heavy flavour production, the survival probability of large rapidity gaps in hard diffraction, etc. At the same time, the implementation of the MPI effects in the Monte Carlo models is quickly proceeding through an increasing level of sophistication and complexity that in perspective achieves deep general implications for the LHC physics. The ultimate ambition of this workshop is to promote the MPI as unification concept between seemingly heterogeneous research lines and to profit of the complete experimental picture in order to constrain their implementation in the models, evaluating the spin offs on the LHC physics program. The workshop is structured in five sections, with the first one dedicated to few selected hot highlights in the High Energy Physics and directly connected to the other ones: Multiple Parton Interactions (in both the soft and the hard regimes), Diffraction, Monte Carlo Generators and Heavy Ions. (orig.)

  13. Proceedings of the first international workshop on multiple partonic interactions at the LHC. MPI'08

    International Nuclear Information System (INIS)

    Bartalini, Paolo; Fano, Livio

    2009-06-01

    The objective of this first workshop on Multiple Partonic Interactions (MPI) at the LHC, that can be regarded as a continuation and extension of the dedicated meetings held at DESY in the years 2006 and 2007, is to raise the profile of MPI studies, summarizing the legacy from the older phenomenology at hadronic colliders and favouring further specific contacts between the theory and experimental communities. The MPI are experiencing a growing popularity and are currently widely invoked to account for observations that would not be explained otherwise: the activity of the Underlying Event, the cross sections for multiple heavy flavour production, the survival probability of large rapidity gaps in hard diffraction, etc. At the same time, the implementation of the MPI effects in the Monte Carlo models is quickly proceeding through an increasing level of sophistication and complexity that in perspective achieves deep general implications for the LHC physics. The ultimate ambition of this workshop is to promote the MPI as unification concept between seemingly heterogeneous research lines and to profit of the complete experimental picture in order to constrain their implementation in the models, evaluating the spin offs on the LHC physics program. The workshop is structured in five sections, with the first one dedicated to few selected hot highlights in the High Energy Physics and directly connected to the other ones: Multiple Parton Interactions (in both the soft and the hard regimes), Diffraction, Monte Carlo Generators and Heavy Ions. (orig.)

  14. Unravelling Darwin's entangled bank: architecture and robustness of mutualistic networks with multiple interaction types.

    Science.gov (United States)

    Dáttilo, Wesley; Lara-Rodríguez, Nubia; Jordano, Pedro; Guimarães, Paulo R; Thompson, John N; Marquis, Robert J; Medeiros, Lucas P; Ortiz-Pulido, Raul; Marcos-García, Maria A; Rico-Gray, Victor

    2016-11-30

    Trying to unravel Darwin's entangled bank further, we describe the architecture of a network involving multiple forms of mutualism (pollination by animals, seed dispersal by birds and plant protection by ants) and evaluate whether this multi-network shows evidence of a structure that promotes robustness. We found that species differed strongly in their contributions to the organization of the multi-interaction network, and that only a few species contributed to the structuring of these patterns. Moreover, we observed that the multi-interaction networks did not enhance community robustness compared with each of the three independent mutualistic networks when analysed across a range of simulated scenarios of species extinction. By simulating the removal of highly interacting species, we observed that, overall, these species enhance network nestedness and robustness, but decrease modularity. We discuss how the organization of interlinked mutualistic networks may be essential for the maintenance of ecological communities, and therefore the long-term ecological and evolutionary dynamics of interactive, species-rich communities. We suggest that conserving these keystone mutualists and their interactions is crucial to the persistence of species-rich mutualistic assemblages, mainly because they support other species and shape the network organization. © 2016 The Author(s).

  15. The Mechanisms of Water Exchange: The Regulatory Roles of Multiple Interactions in Social Wasps.

    Science.gov (United States)

    Agrawal, Devanshu; Karsai, Istvan

    2016-01-01

    Evolutionary benefits of task fidelity and improving information acquisition via multiple transfers of materials between individuals in a task partitioned system have been shown before, but in this paper we provide a mechanistic explanation of these phenomena. Using a simple mathematical model describing the individual interactions of the wasps, we explain the functioning of the common stomach, an information center, which governs construction behavior and task change. Our central hypothesis is a symmetry between foragers who deposit water and foragers who withdraw water into and out of the common stomach. We combine this with a trade-off between acceptance and resistance to water transfer. We ultimately derive a mathematical function that relates the number of interactions that foragers complete with common stomach wasps during a foraging cycle. We use field data and additional model assumptions to calculate values of our model parameters, and we use these to explain why the fullness of the common stomach stabilizes just below 50 percent, why the average number of successful interactions between foragers and the wasps forming the common stomach is between 5 and 7, and why there is a variation in this number of interactions over time. Our explanation is that our proposed water exchange mechanism places natural bounds on the number of successful interactions possible, water exchange is set to optimize mediation of water through the common stomach, and the chance that foragers abort their task prematurely is very low.

  16. Effects of biotic interactions and dispersal on the presence-absence of multiple species

    International Nuclear Information System (INIS)

    Mohd, Mohd Hafiz; Murray, Rua; Plank, Michael J.; Godsoe, William

    2017-01-01

    One of the important issues in ecology is to predict which species will be present (or absent) across a geographical region. Dispersal is thought to have an important influence on the range limits of species, and understanding this problem in a multi-species community with priority effects (i.e. initial abundances determine species presence-absence) is a challenging task because dispersal also interacts with biotic and abiotic factors. Here, we propose a simple multi-species model to investigate the joint effects of biotic interactions and dispersal on species presence-absence. Our results show that dispersal can substantially expand species ranges when biotic and abiotic forces are present; consequently, coexistence of multiple species is possible. The model also exhibits ecologically interesting priority effects, mediated by intense biotic interactions. In the absence of dispersal, competitive exclusion of all but one species occurs. We find that dispersal reduces competitive exclusion effects that occur in no-dispersal case and promotes coexistence of multiple species. These results also show that priority effects are still prevalent in multi-species communities in the presence of dispersal process. We also illustrate the existence of threshold values of competitive strength (i.e. transcritical bifurcations), which results in different species presence-absence in multi-species communities with and without dispersal.

  17. Toward a community ecology of landscapes: predicting multiple predator-prey interactions across geographic space.

    Science.gov (United States)

    Schmitz, Oswald J; Miller, Jennifer R B; Trainor, Anne M; Abrahms, Briana

    2017-09-01

    Community ecology was traditionally an integrative science devoted to studying interactions between species and their abiotic environments in order to predict species' geographic distributions and abundances. Yet for philosophical and methodological reasons, it has become divided into two enterprises: one devoted to local experimentation on species interactions to predict community dynamics; the other devoted to statistical analyses of abiotic and biotic information to describe geographic distribution. Our goal here is to instigate thinking about ways to reconnect the two enterprises and thereby return to a tradition to do integrative science. We focus specifically on the community ecology of predators and prey, which is ripe for integration. This is because there is active, simultaneous interest in experimentally resolving the nature and strength of predator-prey interactions as well as explaining patterns across landscapes and seascapes. We begin by describing a conceptual theory rooted in classical analyses of non-spatial food web modules used to predict species interactions. We show how such modules can be extended to consideration of spatial context using the concept of habitat domain. Habitat domain describes the spatial extent of habitat space that predators and prey use while foraging, which differs from home range, the spatial extent used by an animal to meet all of its daily needs. This conceptual theory can be used to predict how different spatial relations of predators and prey could lead to different emergent multiple predator-prey interactions such as whether predator consumptive or non-consumptive effects should dominate, and whether intraguild predation, predator interference or predator complementarity are expected. We then review the literature on studies of large predator-prey interactions that make conclusions about the nature of multiple predator-prey interactions. This analysis reveals that while many studies provide sufficient information

  18. Gene-environment interaction and male reproductive function

    DEFF Research Database (Denmark)

    Axelsson, Jonatan; Bonde, Jens Peter; Giwercman, Yvonne L

    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...... 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...... 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...

  19. Gene-environment interaction and male reproductive function

    DEFF Research Database (Denmark)

    Axelsson, Jonatan; Bonde, Jens Peter; Giwercman, Yvonne L

    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...

  20. Possible Synergistic Interactions Among Multiple HPV Genotypes in Women Suffering from Genital Neoplasia

    Science.gov (United States)

    Hajia, Massoud; Sohrabi, Amir

    2018-03-27

    Objective: Persistence of HPV infection is the true cause of cervical disorders. It is reported that competition may exist among HPV genotypes for colonization. This survey was designed to establish the multiple HPV genotype status in our community and the probability of multiple HPV infections involvement. Methods: All multiple HPV infections were selected for investigation in women suffering from genital infections referred to private laboratories in Tehran, Iran. A total of 160 multi HPV positive specimens from cervical scraping were identified by the HPV genotyping methods, "INNO-LiPA and Geno Array". Result: In present study, HPV 6 (LR), 16 (HR), 53 (pHR), 31 (HR) and 11 (LR) were included in 48.8% of detected infections as the most five dominant genotypes. HPV 16 was detected at the highest rate with genotypes 53, 31 and 52, while HPV 53 appeared linked with HPV 16, 51 and 56 in concurrent infections. It appears that HPV 16 and 53 may have significant tendencies to associate with each other rather than with other genotypes. Analysis of the data revealed there may be some synergistic interactions with a few particular genotypes such as "HPV 53". Conclusion: Multiple HPV genotypes appear more likely to be linked with development of cervical abnormalities especially in patients with genital infections. Since, there are various patterns of dominant HPV genotypes in different regions of world, more investigations of this type should be performed for careHPV programs in individual countries. Creative Commons Attribution License

  1. Gene-lifestyle interaction and type 2 diabetes

    DEFF Research Database (Denmark)

    Langenberg, Claudia; Sharp, Stephen J; Franks, Paul W

    2014-01-01

    the genetic score and sex, diabetes family history, physical activity, or dietary habits assessed by a Mediterranean diet score. CONCLUSIONS: The relative effect of a T2D genetic risk score is greater in younger and leaner participants. However, this sub-group is at low absolute risk and would......BACKGROUND: Understanding of the genetic basis of type 2 diabetes (T2D) has progressed rapidly, but the interactions between common genetic variants and lifestyle risk factors have not been systematically investigated in studies with adequate statistical power. Therefore, we aimed to quantify...

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

    Directory of Open Access Journals (Sweden)

    Baoman Wang

    2015-01-01

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

  3. Combination of interleukin-10 gene promoter polymorphisms with HLA-DRB1*15 allele is associated with multiple sclerosis

    Directory of Open Access Journals (Sweden)

    Majid Shahbazi

    2017-01-01

    Interpretation & conclusions: The IL-10 and HLA-DRB1*15 polymorphisms were associated with the susceptibility to MS in Iranian patients. Our results suggest that gene-gene interaction of IL-10 polymorphisms and HLA-DRB1*15 alleles may be important factors in the development of MS.

  4. 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

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

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    Zheng Lin

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

  6. 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.

  7. The presence of p53 influences the expression of multiple human cytomegalovirus genes at early times postinfection.

    Science.gov (United States)

    Hannemann, Holger; Rosenke, Kyle; O'Dowd, John M; Fortunato, Elizabeth A

    2009-05-01

    Human cytomegalovirus (HCMV) is a common cause of morbidity and mortality in immunocompromised and immunosuppressed individuals. During infection, HCMV is known to employ host transcription factors to facilitate viral gene expression. To further understand the previously observed delay in viral replication and protein expression in p53 knockout cells, we conducted microarray analyses of p53(+/+) and p53(-/-) immortalized fibroblast cell lines. At a multiplicity of infection (MOI) of 1 at 24 h postinfection (p.i.), the expression of 22 viral genes was affected by the absence of p53. Eleven of these 22 genes (group 1) were examined by real-time reverse transcriptase, or quantitative, PCR (q-PCR). Additionally, five genes previously determined to have p53 bound to their nearest p53-responsive elements (group 2) and three control genes without p53 binding sites in their upstream sequences (group 3) were also examined. At an MOI of 1, >3-fold regulation was found for five group 1 genes. The expression of group 2 and 3 genes was not changed. At an MOI of 5, all genes from group 1 and four of five genes from group 2 were found to be regulated. The expression of control genes from group 3 remained unchanged. A q-PCR time course of four genes revealed that p53 influences viral gene expression most at immediate-early and early times p.i., suggesting a mechanism for the reduced and delayed production of virions in p53(-/-) cells.

  8. Quantum correlation approach to criticality in the XX spin chain with multiple interaction

    Energy Technology Data Exchange (ETDEWEB)

    Cheng, W.W., E-mail: weien.cheng@gmail.com [Institute of Signal Processing and Transmission, Nanjing University of Posts and Telecommunication, Nanjing 210003 (China); Department of Physics, Hubei Normal University, Huangshi 435002 (China); Key Lab of Broadband Wireless Communication and Sensor Network Technology, Ministry of Education (China); Shan, C.J. [Department of Physics, Hubei Normal University, Huangshi 435002 (China); Sheng, Y.B.; Gong, L.Y.; Zhao, S.M. [Institute of Signal Processing and Transmission, Nanjing University of Posts and Telecommunication, Nanjing 210003 (China); Key Lab of Broadband Wireless Communication and Sensor Network Technology, Ministry of Education (China)

    2012-09-01

    We investigate the quantum critical behavior in the XX spin chain with a XZY-YZX type multiple interaction by means of quantum correlation (Concurrence C, quantum discord D{sub Q} and geometric discord D{sub G}). Around the critical point, the values of these quantum correlations and corresponding derivatives are investigated numerically and analytically. The results show that the non-analyticity property of the concurrence cannot signal well the quantum phase transition, but both the quantum discord and geometric discord can characterize the critical behavior in such model exactly.

  9. Analysis of multiplicities in e+e- interactions using 2-jet rates from different jet algorithms

    International Nuclear Information System (INIS)

    Dahiya, S.; Kaur, M.; Dhamija, S.

    2002-01-01

    The shoulder structure of charged particle multiplicity distribution measured in full phase space in e + e - interactions at various c.m. energies from 91 to 189 GeV has been analysed in terms of weighted superposition of two negative binomial distributions associated with 2-jet and multi-jet production. The 2-jet rates have been obtained from various jet algorithms. This phenomenological parametrization reproduces the shoulder structure behaviour quantitatively and improves the agreement with the experimental distributions than the conventional negative binomial distribution. The analysis at the higher energies where the shoulder structure appears more prominently, is important for the understanding of underlying structure. (author)

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

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

    2016-06-01

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

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

    Science.gov (United States)

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

    2017-08-09

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

  13. Laser-Bioplasma Interaction: The Blood Type Transmutation Induced by Multiple Ultrashort Wavelength Laser Beams

    Science.gov (United States)

    Stefan, V. Alexander

    2015-11-01

    The interaction of ultrashort wavelength multi laser beams with the flowing blood thin films leads to the transmutation of the blood types A, B, and AB into O type. This is a novel mechanism of importance for the transfusion medicine. Laser radiation is in resonance with the eigen-frequency modes of the antigen proteins and forces the proteins to parametrically oscillate until they get kicked out from the surface. The stripping away of antigens is done by the scanning-multiple-lasers of a high repetition rate in the blue-purple frequency domain. The guiding-lasers are in the red-green frequency domain. The laser force, (parametric interaction with the antigen eigen-oscillation), upon the antigen protein molecule must exceed its weight. The scanning laser beam is partially reflected as long as the antigen(s) is not eliminated. The process of the protein detachment can last a few minutes. Supported by Nikola Tesla Labs., Stefan University.

  14. A Vietnamese man with selective mutism: the relevance of multiple interacting 'cultures' in clinical psychiatry.

    Science.gov (United States)

    Hollifield, Michael; Geppert, Cynthia; Johnson, Yuam; Fryer, Carol

    2003-09-01

    Multiple cultural variables have effects on the psychobiology and behavioral manifestations of illness, as do patient and physician perceptions of illness. The interaction among these variables is at the heart of clinical psychiatry. This case of a Vietnamese man with selective mutism underscores the relevance of the 'cultures' of medicine, psychiatry, and war and trauma on the manifestations of illness and illness perceptions by patient and physician. The discussion focuses on how these cultures interact and play a crucial role in formulating diagnosis and treatment planning. Suggestions are given for shifts in medical education that will encourage relevant cultural paradigms to make their way into educational and clinical systems, which in turn should improve cultural competence in clinical psychiatry.

  15. Expression of osteoblast and osteoclast regulatory genes in the bone marrow microenvironment in multiple myeloma

    DEFF Research Database (Denmark)

    Kristensen, Ida B; Christensen, Jacob Haaber; Lyng, Maria Bibi

    2014-01-01

    Multiple myeloma (MM) lytic bone disease (LBD) is caused by osteoclast activation and osteoblast inhibition. RANK/RANKL/OPG play central roles in osteoclast activation and Wnt inhibitor DKK1 in osteoblast inhibition. The role of other Wnt inhibitors is less clear. We evaluated gene expression...... of osteoclast regulators (RANK, RANKL, OPG, TRAIL, MIP1A), Wnt inhibitors (DKK1, SFRP2, SFRP3, sclerostin, WIF1) and osteoblast transcription factors (RUNX2, osterix) by quantitative reverse transcriptase polymerase chain reaction (RT-PCR) in the bone marrow (BM) microenvironment using snap-frozen BM biopsies...... radiographs and the bone resorption marker CTX-1. Protein levels were evaluated by enzyme-linked immunosorbent assay (ELISA) and immunohistochemistry. Among Wnt inhibitors, only SFRP3 and DKK1 were significantly overexpressed in advanced LBD, correlating with protein levels. SFRP3 correlated with CTX-1. Our...

  16. Genetic variants of the alpha-synuclein gene SNCA are associated with multiple system atrophy.

    Directory of Open Access Journals (Sweden)

    Ammar Al-Chalabi

    Full Text Available BACKGROUND: Multiple system atrophy (MSA is a progressive neurodegenerative disorder characterized by parkinsonism, cerebellar ataxia and autonomic dysfunction. Pathogenic mechanisms remain obscure but the neuropathological hallmark is the presence of alpha-synuclein-immunoreactive glial cytoplasmic inclusions. Genetic variants of the alpha-synuclein gene, SNCA, are thus strong candidates for genetic association with MSA. One follow-up to a genome-wide association of Parkinson's disease has identified association of a SNP in SNCA with MSA. METHODOLOGY/FINDINGS: We evaluated 32 SNPs in the SNCA gene in a European population of 239 cases and 617 controls recruited as part of the Neuroprotection and Natural History in Parkinson Plus Syndromes (NNIPPS study. We used 161 independently collected samples for replication. Two SNCA SNPs showed association with MSA: rs3822086 (P = 0.0044, and rs3775444 (P = 0.012, although only the first survived correction for multiple testing. In the MSA-C subgroup the association strengthened despite more than halving the number of cases: rs3822086 P = 0.0024, OR 2.153, (95% CI 1.3-3.6; rs3775444 P = 0.0017, OR 4.386 (95% CI 1.6-11.7. A 7-SNP haplotype incorporating three SNPs either side of rs3822086 strengthened the association with MSA-C further (best haplotype, P = 8.7 x 10(-4. The association with rs3822086 was replicated in the independent samples (P = 0.035. CONCLUSIONS/SIGNIFICANCE: We report a genetic association between MSA and alpha-synuclein which has replicated in independent samples. The strongest association is with the cerebellar subtype of MSA. TRIAL REGISTRATION: ClinicalTrials.gov NCT00211224.

  17. Multiple and variable NHEJ-like genes are involved in resistance to DNA damage in Streptomyces ambofaciens

    Directory of Open Access Journals (Sweden)

    Grégory Hoff

    2016-11-01

    Full Text Available Non homologous end-joining (NHEJ is a double strand break (DSB repair pathway which does not require any homologous template and can ligate two DNA ends together. The basic bacterial NHEJ machinery involves two partners: the Ku protein, a DNA end binding protein for DSB recognition and the multifunctional LigD protein composed a ligase, a nuclease and a polymerase domain, for end processing and ligation of the broken ends. In silico analyses performed in the 38 sequenced genomes of Streptomyces species revealed the existence of a large panel of NHEJ-like genes. Indeed, ku genes or ligD domain homologues are scattered throughout the genome in multiple copies and can be distinguished in two categories: the core NHEJ gene set constituted of conserved loci and the variable NHEJ gene set constituted of NHEJ-like genes present in only a part of the species. In Streptomyces ambofaciens ATCC 23877, not only the deletion of core genes but also that of variable genes led to an increased sensitivity to DNA damage induced by electron beam irradiation. Multiple mutants of ku, ligase or polymerase encoding genes showed an aggravated phenotype compared to single mutants. Biochemical assays revealed the ability of Ku-like proteins to protect and to stimulate ligation of DNA ends. RT-qPCR and GFP fusion experiments suggested that ku-like genes show a growth phase dependent expression profile consistent with their involvement in DNA repair during spores formation and/or germination.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  20. Effects of multiple substitution upon the P...N noncovalent interaction

    International Nuclear Information System (INIS)

    Scheiner, Steve

    2011-01-01

    Graphical abstract: The presence of one halogen opposite the N results in strong attraction between P and N. This force is little affected by identity of Y atoms, whether H or halogen. Highlights: → Strong attractive force directly between trivalent P and N atoms. → P...N force is unlike H-bonds or halogen bonds, but stronger than both. → Multiple halogenation beyond a single atom on P slightly weakens the interaction. - Abstract: The attractive noncovalent interaction of a P atom with N is derived primarily from two sources. Charge transfer from the N lone pair into the σ * antibonding orbital of a P-X bond that is turned away from the N atom combines with attractive Coulombic forces. As in the case of H-bonding, which is parallel in some ways to P...N attraction, placement of an electron-withdrawing substituent on the P atom enhances both of these components, and strengthens the overall interaction. However, in stark contrast with H-bonding, halogenation beyond monosubstitution does not lead to any further strengthening of the P...N noncovalent bond. Indeed, di and tri-substitution lead to small reductions in the interaction energy. In all cases, the geometry which contains a P...N bond is more stable than other candidate structures, some of which contain hydrogen or halogen bonds.

  1. Brain Interaction during Cooperation: Evaluating Local Properties of Multiple-Brain Network.

    Science.gov (United States)

    Sciaraffa, Nicolina; Borghini, Gianluca; Aricò, Pietro; Di Flumeri, Gianluca; Colosimo, Alfredo; Bezerianos, Anastasios; Thakor, Nitish V; Babiloni, Fabio

    2017-07-21

    Subjects' interaction is the core of most human activities. This is the reason why a lack of coordination is often the cause of missing goals, more than individual failure. While there are different subjective and objective measures to assess the level of mental effort required by subjects while facing a situation that is getting harder, that is, mental workload, to define an objective measure based on how and if team members are interacting is not so straightforward. In this study, behavioral, subjective and synchronized electroencephalographic data were collected from couples involved in a cooperative task to describe the relationship between task difficulty and team coordination, in the sense of interaction aimed at cooperatively performing the assignment. Multiple-brain connectivity analysis provided information about the whole interacting system. The results showed that averaged local properties of a brain network were affected by task difficulty. In particular, strength changed significantly with task difficulty and clustering coefficients strongly correlated with the workload itself. In particular, a higher workload corresponded to lower clustering values over the central and parietal brain areas. Such results has been interpreted as less efficient organization of the network when the subjects' activities, due to high workload tendencies, were less coordinated.

  2. Assessing interactions among multiple physiological systems during walking outside a laboratory: An Android based gait monitor

    Science.gov (United States)

    Sejdić, E.; Millecamps, A.; Teoli, J.; Rothfuss, M. A.; Franconi, N. G.; Perera, S.; Jones, A. K.; Brach, J. S.; Mickle, M. H.

    2015-01-01

    Gait function is traditionally assessed using well-lit, unobstructed walkways with minimal distractions. In patients with subclinical physiological abnormalities, these conditions may not provide enough stress on their ability to adapt to walking. The introduction of challenging walking conditions in gait can induce responses in physiological systems in addition to the locomotor system. There is a need for a device that is capable of monitoring multiple physiological systems in various walking conditions. To address this need, an Android-based gait-monitoring device was developed that enabled the recording of a patient's physiological systems during walking. The gait-monitoring device was tested during self-regulated overground walking sessions of fifteen healthy subjects that included 6 females and 9 males aged 18 to 35 years. The gait-monitoring device measures the patient's stride interval, acceleration, electrocardiogram, skin conductance and respiratory rate. The data is stored on an Android phone and is analyzed offline through the extraction of features in the time, frequency and time-frequency domains. The analysis of the data depicted multisystem physiological interactions during overground walking in healthy subjects. These interactions included locomotion-electrodermal, locomotion-respiratory and cardiolocomotion couplings. The current results depicting strong interactions between the locomotion system and the other considered systems (i.e., electrodermal, respiratory and cardivascular systems) warrant further investigation into multisystem interactions during walking, particularly in challenging walking conditions with older adults. PMID:26390946

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

    Science.gov (United States)

    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).

  4. SINA: accurate high-throughput multiple sequence alignment of ribosomal RNA genes.

    Science.gov (United States)

    Pruesse, Elmar; Peplies, Jörg; Glöckner, Frank Oliver

    2012-07-15

    In the analysis of homologous sequences, computation of multiple sequence alignments (MSAs) has become a bottleneck. This is especially troublesome for marker genes like the ribosomal RNA (rRNA) where already millions of sequences are publicly available and individual studies can easily produce hundreds of thousands of new sequences. Methods have been developed to cope with such numbers, but further improvements are needed to meet accuracy requirements. In this study, we present the SILVA Incremental Aligner (SINA) used to align the rRNA gene databases provided by the SILVA ribosomal RNA project. SINA uses a combination of k-mer searching and partial order alignment (POA) to maintain very high alignment accuracy while satisfying high throughput performance demands. SINA was evaluated in comparison with the commonly used high throughput MSA programs PyNAST and mothur. The three BRAliBase III benchmark MSAs could be reproduced with 99.3, 97.6 and 96.1 accuracy. A larger benchmark MSA comprising 38 772 sequences could be reproduced with 98.9 and 99.3% accuracy using reference MSAs comprising 1000 and 5000 sequences. SINA was able to achieve higher accuracy than PyNAST and mothur in all performed benchmarks. Alignment of up to 500 sequences using the latest SILVA SSU/LSU Ref datasets as reference MSA is offered at http://www.arb-silva.de/aligner. This page also links to Linux binaries, user manual and tutorial. SINA is made available under a personal use license.

  5. Involvement of Multiple Gene-Silencing Pathways in a Paramutation-like Phenomenon in Arabidopsis

    Directory of Open Access Journals (Sweden)

    Zhimin Zheng

    2015-05-01

    Full Text Available Paramutation is an epigenetic phenomenon that has been observed in a number of multicellular organisms. The epigenetically silenced state of paramutated alleles is not only meiotically stable but also “infectious” to active homologous alleles. The molecular mechanism of paramutation remains unclear, but components involved in RNA-directed DNA methylation (RdDM are required. Here, we report a multi-copy pRD29A-LUC transgene in Arabidopsis thaliana that behaves like a paramutation locus. The silent state of LUC is induced by mutations in the DNA glycosylase gene ROS1. The silent alleles of LUC are not only meiotically stable but also able to transform active LUC alleles into silent ones, in the absence of ros1 mutations. Maintaining silencing at the LUC gene requires action of multiple pathways besides RdDM. Our study identified specific factors that are involved in the paramutation-like phenomenon and established a model system for the study of paramutation in Arabidopsis.

  6. Identification of gene expression patterns crucially involved in experimental autoimmune encephalomyelitis and multiple sclerosis

    Directory of Open Access Journals (Sweden)

    Martin M. Herrmann

    2016-10-01

    Full Text Available After encounter with a central nervous system (CNS-derived autoantigen, lymphocytes leave the lymph nodes and enter the CNS. This event leads only rarely to subsequent tissue damage. Genes relevant to CNS pathology after cell infiltration are largely undefined. Myelin-oligodendrocyte-glycoprotein (MOG-induced experimental autoimmune encephalomyelitis (EAE is an animal model of multiple sclerosis (MS, a chronic autoimmune disease of the CNS that results in disability. To assess genes that are involved in encephalitogenicity and subsequent tissue damage mediated by CNS-infiltrating cells, we performed a DNA microarray analysis from cells derived from lymph nodes and eluted from CNS in LEW.1AV1 (RT1av1 rats immunized with MOG 91-108. The data was compared to immunizations with adjuvant alone or naive rats and to immunizations with the immunogenic but not encephalitogenic MOG 73-90 peptide. Here, we show involvement of Cd38, Cxcr4 and Akt and confirm these findings by the use of Cd38-knockout (B6.129P2-Cd38tm1Lnd/J mice, S1P-receptor modulation during EAE and quantitative expression analysis in individuals with MS. The hereby-defined underlying pathways indicate cellular activation and migration pathways mediated by G-protein-coupled receptors as crucial events in CNS tissue damage. These pathways can be further explored for novel therapeutic interventions.

  7. Hydrocephalus due to multiple ependymal malformations is caused by mutations in the MPDZ gene.

    Science.gov (United States)

    Saugier-Veber, Pascale; Marguet, Florent; Lecoquierre, François; Adle-Biassette, Homa; Guimiot, Fabien; Cipriani, Sara; Patrier, Sophie; Brasseur-Daudruy, Marie; Goldenberg, Alice; Layet, Valérie; Capri, Yline; Gérard, Marion; Frébourg, Thierry; Laquerrière, Annie

    2017-05-01

    Congenital hydrocephalus is considered as either acquired due to haemorrhage, infection or neoplasia or as of developmental nature and is divided into two subgroups, communicating and obstructive. Congenital hydrocephalus is either syndromic or non-syndromic, and in the latter no cause is found in more than half of the patients. In patients with isolated hydrocephalus, L1CAM mutations represent the most common aetiology. More recently, a founder mutation has also been reported in the MPDZ gene in foetuses presenting massive hydrocephalus, but the neuropathology remains unknown. We describe here three novel homozygous null mutations in the MPDZ gene in foetuses whose post-mortem examination has revealed a homogeneous phenotype characterized by multiple ependymal malformations along the aqueduct of Sylvius, the third and fourth ventricles as well as the central canal of the medulla, consisting in multifocal rosettes with immature cell accumulation in the vicinity of ependymal lining early detached from the ventricular zone. MPDZ also named MUPP1 is an essential component of tight junctions which are expressed from early brain development in the choroid plexuses and ependyma. Alterations in the formation of tight junctions within the ependyma very likely account for the lesions observed and highlight for the first time that primary multifocal ependymal malformations of the ventricular system is genetically determined in humans. Therefore, MPDZ sequencing should be performed when neuropathological examination reveals multifocal ependymal rosette formation within the aqueduct of Sylvius, of the third and fourth ventricles and of the central canal of the medulla.

  8. The analysis of correlation between IL-1B gene expression and genotyping in multiple sclerosis patients.

    Science.gov (United States)

    Heidary, Masoumeh; Rakhshi, Nahid; Pahlevan Kakhki, Majid; Behmanesh, Mehrdad; Sanati, Mohammad Hossein; Sanadgol, Nima; Kamaladini, Hossein; Nikravesh, Abbas

    2014-08-15

    IL-1B is released by monocytes, astrocytes and brain endothelial cells and seems to be involved in inflammatory reactions of the central nervous system (CNS) in multiple sclerosis (MS). This study aims to evaluate the expression level of IL-1B mRNA in peripheral blood mononuclear cells (PBMCs), genotype the rs16944 SNP and find out the role of this SNP on the expression level of IL-1B in MS patients. We found that the expression level of IL-1B in MS patients increased 3.336 times more than controls in PBMCs but the rs16944 SNP in the promoter region of IL-1B did not affect the expression level of this gene and there was not association of this SNP with MS in the examined population. Also, our data did not reveal any correlation between normalized expressions of IL-1B gene with age of participants, age of onset, and disease duration. Copyright © 2014 Elsevier B.V. All rights reserved.

  9. Methylation of class II transactivator gene promoter IV is not associated with susceptibility to Multiple Sclerosis

    Directory of Open Access Journals (Sweden)

    Lincoln Matthew R

    2008-07-01

    Full Text Available Abstract Background Multiple sclerosis (MS is a complex trait in which alleles at or near the class II loci HLA-DRB1 and HLA-DQB1 contribute significantly to genetic risk. The MHC class II transactivator (MHC2TA is the master controller of expression of class II genes, and methylation of the promoter of this gene has been previously been shown to alter its function. In this study we sought to assess whether or not methylation of the MHC2TA promoter pIV could contribute to MS disease aetiology. Methods In DNA from peripheral blood mononuclear cells from a sample of 50 monozygotic disease discordant MS twins the MHC2TA promoter IV was sequenced and analysed by methylation specific PCR. Results No methylation or sequence variation of the MHC2TA promoter pIV was found. Conclusion The results of this study cannot support the notion that methylation of the pIV promoter of MHC2TA contributes to MS disease risk, although tissue and timing specific epigenetic modifications cannot be ruled out.

  10. 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.

  11. 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.

  12. Gene-Environment Interactions of Circadian-Related Genes for Cardiometabolic Traits

    DEFF Research Database (Denmark)

    Dashti, Hassan S; Follis, Jack L; Smith, Caren E

    2015-01-01

    OBJECTIVE: Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs13871...

  13. Gene-environment interactions of circadian-related genes for cardiometabolic traits

    Science.gov (United States)

    Objective: Common circadian-related gene variants associate with increased risk for metabolic alterations including type 2 diabetes. However, little is known about whether diet and sleep could modify associations between circadian-related variants (CLOCK-rs1801260, CRY2-rs11605924, MTNR1B-rs1387153,...

  14. A polymorphism in the HLA-DPB1 gene is associated with susceptibility to multiple sclerosis.

    Directory of Open Access Journals (Sweden)

    Judith Field

    2010-10-01

    Full Text Available We conducted an association study across the human leukocyte antigen (HLA complex to identify loci associated with multiple sclerosis (MS. Comparing 1927 SNPs in 1618 MS cases and 3413 controls of European ancestry, we identified seven SNPs that were independently associated with MS conditional on the others (each P ≤ 4 x 10(-6. All associations were significant in an independent replication cohort of 2212 cases and 2251 controls (P ≤ 0.001 and were highly significant in the combined dataset (P ≤ 6 x 10(-8. The associated SNPs included proxies for HLA-DRB1*15:01 and HLA-DRB1*03:01, and SNPs in moderate linkage disequilibrium (LD with HLA-A*02:01, HLA-DRB1*04:01 and HLA-DRB1*13:03. We also found a strong association with rs9277535 in the class II gene HLA-DPB1 (discovery set P = 9 x 10(-9, replication set P = 7 x 10(-4, combined P = 2 x 10(-10. HLA-DPB1 is located centromeric of the more commonly typed class II genes HLA-DRB1, -DQA1 and -DQB1. It is separated from these genes by a recombination hotspot, and the association is not affected by conditioning on genotypes at DRB1, DQA1 and DQB1. Hence rs9277535 represents an independent MS-susceptibility locus of genome-wide significance. It is correlated with the HLA-DPB1*03:01 allele, which has been implicated previously in MS in smaller studies. Further genotyping in large datasets is required to confirm and resolve this association.

  15. 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.

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

    Science.gov (United States)

    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.

  17. 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

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

    Directory of Open Access Journals (Sweden)

    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.

  19. Use of multiple correspondence analysis (MCA) to identify interactive meteorological conditions affecting relative throughfall

    Science.gov (United States)

    Van Stan, John T.; Gay, Trent E.; Lewis, Elliott S.

    2016-02-01

    Forest canopies alter rainfall reaching the surface by redistributing it as throughfall. Throughfall supplies water and nutrients to a variety of ecohydrological components (soil microbial communities, stream water discharge/chemistry, and stormflow pathways) and is controlled by canopy structural interactions with meteorological conditions across temporal scales. This work introduces and applies multiple correspondence analyses (MCAs) to a range of meteorological thresholds (median intensity, median absolute deviation (MAD) of intensity, median wind-driven droplet inclination angle, and MAD of wind speed) for an example throughfall problem: identification of interacting storm conditions corresponding to temporal concentration in relative throughfall beyond the median observation (⩾73% of rain). MCA results from the example show that equalling or exceeding rain intensity thresholds (median and MAD) corresponded with temporal concentration of relative throughfall across all storms. Under these intensity conditions, two wind mechanisms produced significant correspondences: (1) high, steady wind-driven droplet inclination angles increased surface wetting; and (2) sporadic winds shook entrained droplets from surfaces. A discussion is provided showing that these example MCA findings agree well with previous work relying on more historically common methods (e.g., multiple regression and analytical models). Meteorological threshold correspondences to temporal concentration of relative throughfall at our site may be a function of heavy Tillandsia usneoides coverage. Applications of MCA within other forests may provide useful insights to how temporal throughfall dynamics are affected for drainage pathways dependent on different structures (leaves, twigs, branches, etc.).

  20. Prediction of protein interaction hot spots using rough set-based multiple criteria linear programming.

    Science.gov (United States)

    Chen, Ruoying; Zhang, Zhiwang; Wu, Di; Zhang, Peng; Zhang, Xinyang; Wang, Yong; Shi, Yong

    2011-01-21

    Protein-protein interactions are fundamentally important in many biological processes and it is in pressing need to understand the principles of protein-protein interactions. Mutagenesis studies have found that only a small fraction of surface residues, known as hot spots, are responsible for the physical binding in protein complexes. However, revealing hot spots by mutagenesis experiments are usually time consuming and expensive. In order to complement the experimental efforts, we propose a new computational approach in this paper to predict hot spots. Our method, Rough Set-based Multiple Criteria Linear Programming (RS-MCLP), integrates rough sets theory and multiple criteria linear programming to choose dominant features and computationally predict hot spots. Our approach is benchmarked by a dataset of 904 alanine-mutated residues and the results show that our RS-MCLP method performs better than other methods, e.g., MCLP, Decision Tree, Bayes Net, and the existing HotSprint database. In addition, we reveal several biological insights based on our analysis. We find that four features (the change of accessible surface area, percentage of the change of accessible surface area, size of a residue, and atomic contacts) are critical in predicting hot spots. Furthermore, we find that three residues (Tyr, Trp, and Phe) are abundant in hot spots through analyzing the distribution of amino acids. Copyright © 2010 Elsevier Ltd. All rights reserved.

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

    OpenAIRE

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

    2013-01-01

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

  2. Interaction of the ADRB2 gene polymorphism with childhood trauma in predicting adult symptoms of posttraumatic stress disorder.

    Science.gov (United States)

    Liberzon, Israel; King, Anthony P; Ressler, Kerry J; Almli, Lynn M; Zhang, Peng; Ma, Sean T; Cohen, Gregory H; Tamburrino, Marijo B; Calabrese, Joseph R; Galea, Sandro

    2014-10-01

    Posttraumatic stress disorder (PTSD), while highly prevalent (7.6% over a lifetime), develops only in a subset of trauma-exposed individuals. Genetic risk factors in interaction with trauma exposure have been implicated in PTSD vulnerability. To examine the association of 3755 candidate gene single-nucleotide polymorphisms with PTSD development in interaction with a history of childhood trauma. Genetic association study in an Ohio National Guard longitudinal cohort (n = 810) of predominantly male soldiers of European ancestry, with replication in an independent Grady Trauma Project (Atlanta, Georgia) cohort (n = 2083) of predominantly female African American civilians. Continuous measures of PTSD severity, with a modified (interview) PTSD checklist in the discovery cohort and the PTSD Symptom Scale in the replication cohort. Controlling for the level of lifetime adult trauma exposure, we identified the novel association of a single-nucleotide polymorphism within the promoter region of the ADRB2 (Online Mendelian Inheritance in Man 109690) gene with PTSD symptoms in interaction with childhood trauma (rs2400707, P = 1.02 × 10-5, significant after correction for multiple comparisons). The rs2400707 A allele was associated with relative resilience to childhood adversity. An rs2400707 × childhood trauma interaction predicting adult PTSD symptoms was replicated in the independent predominantly female African American cohort. Altered adrenergic and noradrenergic function has been long believed to have a key etiologic role in PTSD development; however, direct evidence of this link has been missing. The rs2400707 polymorphism has been linked to function of the adrenergic system, but, to our knowledge, this is the first study to date linking the ADRB2 gene to PTSD or any psychiatric disorders. These findings have important implications for PTSD etiology, chronic pain, and stress-related comorbidity, as well as for both primary prevention and treatment

  3. Thermo-kinetic mechanisms for grain boundary structure multiplicity, thermal instability and defect interactions

    International Nuclear Information System (INIS)

    Burbery, N.J.; Das, R.; Ferguson, W.G.

    2016-01-01

    Grain boundaries (GBs) provide a source and/or a sink for crystal defects and store elastic energy due to the non-uniform atomic bonding structure of the GB core. GB structures are thermodynamically driven to transition to the lowest energy configuration possible; however to date there has been little evidence to explain why specific GB structures have a low energy state. Furthermore, there is little quantitative demonstration of the significance of physical and GB structure characteristics on the GB energy, thermal stability, and the effect of temporary local GB structure transformations on defect interactions. This paper evaluates the defect interactions and structure stability of multiple Σ5(310) GB structures in bi-crystals of pure aluminium, and systematically investigates the features at 0 K to characterise multiple metastable structures. Structure stability is evaluated by utilising unstable vacancy defects to initiate GB transformations, and using nudged elastic band simulations to quantify this with the activation energy. The emission of stable vacancy defects from the ‘stable’ and metastable grain boundaries is also evaluated in the same manner. A detailed analysis of dislocation nucleation at the atomistic scale demonstrates that local transformations of GB structure between stable and metastable intermediates can provide a mechanism to accommodate the generation of crystal defects. Kinetic (time-dependent) effects that compete with energetic driving forces for structural transformations of GBs are shown to cause a significant effect on the activation properties that may exceed the influence of GB potential energy. The results demonstrate that GB structural multiplicity can be associated with the generation and absorption of dislocations and vacancies. This paper demonstrates the suitability of atomistic simulations coupled with nudged elastic band simulations to evaluate fundamental thermodynamic properties of pure FCC metals. Overall, this paper

  4. Thermo-kinetic mechanisms for grain boundary structure multiplicity, thermal instability and defect interactions

    Energy Technology Data Exchange (ETDEWEB)

    Burbery, N.J. [Department of Mechanical Engineering, University of Auckland, Auckland 1010 (New Zealand); Das, R., E-mail: r.das@auckland.ac.nz [Department of Mechanical Engineering, University of Auckland, Auckland 1010 (New Zealand); Ferguson, W.G. [Department of Chemical and Materials Engineering, University of Auckland, Auckland 1010 (New Zealand)

    2016-08-15

    Grain boundaries (GBs) provide a source and/or a sink for crystal defects and store elastic energy due to the non-uniform atomic bonding structure of the GB core. GB structures are thermodynamically driven to transition to the lowest energy configuration possible; however to date there has been little evidence to explain why specific GB structures have a low energy state. Furthermore, there is little quantitative demonstration of the significance of physical and GB structure characteristics on the GB energy, thermal stability, and the effect of temporary local GB structure transformations on defect interactions. This paper evaluates the defect interactions and structure stability of multiple Σ5(310) GB structures in bi-crystals of pure aluminium, and systematically investigates the features at 0 K to characterise multiple metastable structures. Structure stability is evaluated by utilising unstable vacancy defects to initiate GB transformations, and using nudged elastic band simulations to quantify this with the activation energy. The emission of stable vacancy defects from the ‘stable’ and metastable grain boundaries is also evaluated in the same manner. A detailed analysis of dislocation nucleation at the atomistic scale demonstrates that local transformations of GB structure between stable and metastable intermediates can provide a mechanism to accommodate the generation of crystal defects. Kinetic (time-dependent) effects that compete with energetic driving forces for structural transformations of GBs are shown to cause a significant effect on the activation properties that may exceed the influence of GB potential energy. The results demonstrate that GB structural multiplicity can be associated with the generation and absorption of dislocations and vacancies. This paper demonstrates the suitability of atomistic simulations coupled with nudged elastic band simulations to evaluate fundamental thermodynamic properties of pure FCC metals. Overall, this paper

  5. The development and application of a multiple gene co-silencing system using endogenous URA3 as a reporter gene in Ganoderma lucidum.

    Directory of Open Access Journals (Sweden)

    Dashuai Mu

    Full Text Available Ganoderma lucidum is one of the most important medicinal mushrooms; however, molecular genetics research on this species has been limited due to a lack of reliable reverse genetic tools. In this study, the endogenous orotidine 5'-monophosphate decarboxylase gene (URA3 was cloned as a silencing reporter, and four gene-silencing methods using hairpin, sense, antisense, and dual promoter constructs, were introduced into G. lucidum through a simple electroporation procedure. A comparison and evaluation of silencing efficiency demonstrated that all of the four methods differentially suppressed the expression of URA3. Our data unequivocally indicate that the dual promoter silencing vector yields the highest rate of URA3 silencing compared with other vectors (up to 81.9%. To highlight the advantages of the dual promoter system, we constructed a co-silencing system based on the dual promoter method and succeeded in co-silencing URA3 and laccase in G. lucidum. The reduction of the mRNA levels of the two genes were correlated. Thus, the screening efficiency for RNAi knockdown of multiple genes may be improved by the co-silencing of an endogenous reporter gene. The molecular tools developed in this study should facilitate the isolation of genes and the characterization of the functions of multiple genes in this pharmaceutically important species, and these tools should be highly useful for the study of other basidiomycetes.

  6. 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.

  7. 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 su