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

PubMed Central

2011-01-01

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/. PMID:21615923

A latent variable approach to study gene-environment interactions in the presence of multiple correlated exposures.

PubMed

Sánchez, Brisa N; Kang, Shan; Mukherjee, Bhramar

2012-06-01

Many existing cohort studies initially designed to investigate disease risk as a function of environmental exposures have collected genomic data in recent years with the objective of testing for gene-environment interaction (G × E) effects. In environmental epidemiology, interest in G × E arises primarily after a significant effect of the environmental exposure has been documented. Cohort studies often collect rich exposure data; as a result, assessing G × E effects in the presence of multiple exposure markers further increases the burden of multiple testing, an issue already present in both genetic and environment health studies. Latent variable (LV) models have been used in environmental epidemiology to reduce dimensionality of the exposure data, gain power by reducing multiplicity issues via condensing exposure data, and avoid collinearity problems due to presence of multiple correlated exposures. We extend the LV framework to characterize gene-environment interaction in presence of multiple correlated exposures and genotype categories. Further, similar to what has been done in case-control G × E studies, we use the assumption of gene-environment (G-E) independence to boost the power of tests for interaction. The consequences of making this assumption, or the issue of how to explicitly model G-E association has not been previously investigated in LV models. We postulate a hierarchy of assumptions about the LV model regarding the different forms of G-E dependence and show that making such assumptions may influence inferential results on the G, E, and G × E parameters. We implement a class of shrinkage estimators to data adaptively trade-off between the most restrictive to most flexible form of G-E dependence assumption and note that such class of compromise estimators can serve as a benchmark of model adequacy in LV models. We demonstrate the methods with an example from the Early Life Exposures in Mexico City to Neuro-Toxicants Study of lead exposure, iron metabolism genes, and birth weight. © 2011, The International Biometric Society.

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

PubMed

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.

Incorporating gene-environment interaction in testing for association with rare genetic variants.

PubMed

Chen, Han; Meigs, James B; Dupuis, Josée

2014-01-01

The incorporation of gene-environment interactions could improve the ability to detect genetic associations with complex traits. For common genetic variants, single-marker interaction tests and joint tests of genetic main effects and gene-environment interaction have been well-established and used to identify novel association loci for complex diseases and continuous traits. For rare genetic variants, however, single-marker tests are severely underpowered due to the low minor allele frequency, and only a few gene-environment interaction tests have been developed. We aimed at developing powerful and computationally efficient tests for gene-environment interaction with rare variants. In this paper, we propose interaction and joint tests for testing gene-environment interaction of rare genetic variants. Our approach is a generalization of existing gene-environment interaction tests for multiple genetic variants under certain conditions. We show in our simulation studies that our interaction and joint tests have correct type I errors, and that the joint test is a powerful approach for testing genetic association, allowing for gene-environment interaction. We also illustrate our approach in a real data example from the Framingham Heart Study. Our approach can be applied to both binary and continuous traits, it is powerful and computationally efficient.

Genomic and Epigenomic Insights into Nutrition and Brain Disorders

PubMed Central

Dauncey, Margaret Joy

2013-01-01

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

Genes-environment interactions in obesity- and diabetes-associated pancreatic cancer: a GWAS data analysis.

PubMed

Tang, Hongwei; Wei, Peng; Duell, Eric J; Risch, Harvey A; Olson, Sara H; Bueno-de-Mesquita, H Bas; Gallinger, Steven; Holly, Elizabeth A; Petersen, Gloria M; Bracci, Paige M; McWilliams, Robert R; Jenab, Mazda; Riboli, Elio; Tjønneland, Anne; Boutron-Ruault, Marie Christine; Kaaks, Rudolf; Trichopoulos, Dimitrios; Panico, Salvatore; Sund, Malin; Peeters, Petra H M; Khaw, Kay-Tee; Amos, Christopher I; Li, Donghui

2014-01-01

Obesity and diabetes are potentially alterable risk factors for pancreatic cancer. Genetic factors that modify the associations of obesity and diabetes with pancreatic cancer have previously not been examined at the genome-wide level. Using genome-wide association studies (GWAS) genotype and risk factor data from the Pancreatic Cancer Case Control Consortium, we conducted a discovery study of 2,028 cases and 2,109 controls to examine gene-obesity and gene-diabetes interactions in relation to pancreatic cancer risk by using the likelihood-ratio test nested in logistic regression models and Ingenuity Pathway Analysis (IPA). After adjusting for multiple comparisons, a significant interaction of the chemokine signaling pathway with obesity (P = 3.29 × 10(-6)) and a near significant interaction of calcium signaling pathway with diabetes (P = 1.57 × 10(-4)) in modifying the risk of pancreatic cancer were observed. These findings were supported by results from IPA analysis of the top genes with nominal interactions. The major contributing genes to the two top pathways include GNGT2, RELA, TIAM1, and GNAS. None of the individual genes or single-nucleotide polymorphism (SNP) except one SNP remained significant after adjusting for multiple testing. Notably, SNP rs10818684 of the PTGS1 gene showed an interaction with diabetes (P = 7.91 × 10(-7)) at a false discovery rate of 6%. Genetic variations in inflammatory response and insulin resistance may affect the risk of obesity- and diabetes-related pancreatic cancer. These observations should be replicated in additional large datasets. A gene-environment interaction analysis may provide new insights into the genetic susceptibility and molecular mechanisms of obesity- and diabetes-related pancreatic cancer.

Integration of multi-omics data for integrative gene regulatory network inference.

PubMed

Zarayeneh, Neda; Ko, Euiseong; Oh, Jung Hun; Suh, Sang; Liu, Chunyu; Gao, Jean; Kim, Donghyun; Kang, Mingon

2017-01-01

Gene regulatory networks provide comprehensive insights and indepth understanding of complex biological processes. The molecular interactions of gene regulatory networks are inferred from a single type of genomic data, e.g., gene expression data in most research. However, gene expression is a product of sequential interactions of multiple biological processes, such as DNA sequence variations, copy number variations, histone modifications, transcription factors, and DNA methylations. The recent rapid advances of high-throughput omics technologies enable one to measure multiple types of omics data, called 'multi-omics data', that represent the various biological processes. In this paper, we propose an Integrative Gene Regulatory Network inference method (iGRN) that incorporates multi-omics data and their interactions in gene regulatory networks. In addition to gene expressions, copy number variations and DNA methylations were considered for multi-omics data in this paper. The intensive experiments were carried out with simulation data, where iGRN's capability that infers the integrative gene regulatory network is assessed. Through the experiments, iGRN shows its better performance on model representation and interpretation than other integrative methods in gene regulatory network inference. iGRN was also applied to a human brain dataset of psychiatric disorders, and the biological network of psychiatric disorders was analysed.

Integration of multi-omics data for integrative gene regulatory network inference

PubMed Central

Zarayeneh, Neda; Ko, Euiseong; Oh, Jung Hun; Suh, Sang; Liu, Chunyu; Gao, Jean; Kim, Donghyun

2017-01-01

Gene regulatory networks provide comprehensive insights and indepth understanding of complex biological processes. The molecular interactions of gene regulatory networks are inferred from a single type of genomic data, e.g., gene expression data in most research. However, gene expression is a product of sequential interactions of multiple biological processes, such as DNA sequence variations, copy number variations, histone modifications, transcription factors, and DNA methylations. The recent rapid advances of high-throughput omics technologies enable one to measure multiple types of omics data, called ‘multi-omics data’, that represent the various biological processes. In this paper, we propose an Integrative Gene Regulatory Network inference method (iGRN) that incorporates multi-omics data and their interactions in gene regulatory networks. In addition to gene expressions, copy number variations and DNA methylations were considered for multi-omics data in this paper. The intensive experiments were carried out with simulation data, where iGRN’s capability that infers the integrative gene regulatory network is assessed. Through the experiments, iGRN shows its better performance on model representation and interpretation than other integrative methods in gene regulatory network inference. iGRN was also applied to a human brain dataset of psychiatric disorders, and the biological network of psychiatric disorders was analysed. PMID:29354189

AprioriGWAS, a new pattern mining strategy for detecting genetic variants associated with disease through interaction effects.

PubMed

Zhang, Qingrun; Long, Quan; Ott, Jurg

2014-06-01

Identifying gene-gene interaction is a hot topic in genome wide association studies. Two fundamental challenges are: (1) how to smartly identify combinations of variants that may be associated with the trait from astronomical number of all possible combinations; and (2) how to test epistatic interaction when all potential combinations are available. We developed AprioriGWAS, which brings two innovations. (1) Based on Apriori, a successful method in field of Frequent Itemset Mining (FIM) in which a pattern growth strategy is leveraged to effectively and accurately reduce search space, AprioriGWAS can efficiently identify genetically associated genotype patterns. (2) To test the hypotheses of epistasis, we adopt a new conditional permutation procedure to obtain reliable statistical inference of Pearson's chi-square test for the [Formula: see text] contingency table generated by associated variants. By applying AprioriGWAS to age-related macular degeneration (AMD) data, we found that: (1) angiopoietin 1 (ANGPT1) and four retinal genes interact with Complement Factor H (CFH). (2) GO term "glycosaminoglycan biosynthetic process" was enriched in AMD interacting genes. The epistatic interactions newly found by AprioriGWAS on AMD data are likely true interactions, since genes interacting with CFH are retinal genes, and GO term enrichment also verified that interaction between glycosaminoglycans (GAGs) and CFH plays an important role in disease pathology of AMD. By applying AprioriGWAS on Bipolar disorder in WTCCC data, we found variants without marginal effect show significant interactions. For example, multiple-SNP genotype patterns inside gene GABRB2 and GRIA1 (AMPA subunit 1 receptor gene). AMPARs are found in many parts of the brain and are the most commonly found receptor in the nervous system. The GABRB2 mediates the fastest inhibitory synaptic transmission in the central nervous system. GRIA1 and GABRB2 are relevant to mental disorders supported by multiple evidences.

Anti-inflammatory genes associated with multiple sclerosis: a gene expression study.

PubMed

Perga, S; Montarolo, F; Martire, S; Berchialla, P; Malucchi, S; Bertolotto, A

2015-02-15

Multiple sclerosis (MS) is an autoimmune inflammatory disease of the central nervous system caused by a complex interaction between multiple genes and environmental factors. HLA region is the strongest susceptibility locus, but recent huge genome-wide association studies identified new susceptibility genes. Among these, BACH2, PTGER4, RGS1 and ZFP36L1 were highlighted. Here, a gene expression analysis revealed that three of them, namely BACH2, PTGER4 and ZFP36L1, are down-regulated in MS patients' blood cells compared to healthy subjects. Interestingly, all these genes are involved in the immune system regulation with predominant anti-inflammatory role and their reduction could predispose to MS development. Copyright © 2015 Elsevier B.V. All rights reserved.

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

PubMed

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

2017-05-01

Currently, most guidelines on drug-drug interaction (DDI) neither consider the potential effect of genetic polymorphism in the strength of the interaction nor do they account for the complex interaction caused by the combination of DDI and drug-gene interaction (DGI) where there are multiple biotransformation pathways, which is referred to as drug-drug-gene interaction (DDGI). In this systematic review, we report the impact of pharmacogenetics on DDI and DDGI in which three major drug-metabolizing enzymes - CYP2C9, CYP2C19 and CYP2D6 - are central. We observed that several DDI and DDGI are highly gene-dependent, leading to a different magnitude of interaction. Precision drug therapy should take pharmacogenetics into account when drug interactions in clinical practice are expected.

SysBioCube: A Data Warehouse and Integrative Data Analysis Platform Facilitating Systems Biology Studies of Disorders of Military Relevance

DTIC Science & Technology

2013-12-18

include interactive gene and methylation profiles, interactive heatmaps, cytoscape network views, integrative genomics viewer ( IGV ), and protein-protein...single chart. The website also provides an option to include multiple genes. Integrative Genomics Viewer ( IGV )1, is a high-performance desktop tool for

Small RNA biology is systems biology.

PubMed

Jost, Daniel; Nowojewski, Andrzej; Levine, Erel

2011-01-01

During the last decade small regulatory RNA (srRNA) emerged as central players in the regulation of gene expression in all kingdoms of life. Multiple pathways for srRNA biogenesis and diverse mechanisms of gene regulation may indicate that srRNA regulation evolved independently multiple times. However, small RNA pathways share numerous properties, including the ability of a single srRNA to regulate multiple targets. Some of the mechanisms of gene regulation by srRNAs have significant effect on the abundance of free srRNAs that are ready to interact with new targets. This results in indirect interactions among seemingly unrelated genes, as well as in a crosstalk between different srRNA pathways. Here we briefly review and compare the major srRNA pathways, and argue that the impact of srRNA is always at the system level. We demonstrate how a simple mathematical model can ease the discussion of governing principles. To demonstrate these points we review a few examples from bacteria and animals.

Limit cycles in piecewise-affine gene network models with multiple interaction loops

NASA Astrophysics Data System (ADS)

Farcot, Etienne; Gouzé, Jean-Luc

2010-01-01

In this article, we consider piecewise affine differential equations modelling gene networks. We work with arbitrary decay rates, and under a local hypothesis expressed as an alignment condition of successive focal points. The interaction graph of the system may be rather complex (multiple intricate loops of any sign, multiple thresholds, etc.). Our main result is an alternative theorem showing that if a sequence of region is periodically visited by trajectories, then under our hypotheses, there exists either a unique stable periodic solution, or the origin attracts all trajectories in this sequence of regions. This result extends greatly our previous work on a single negative feedback loop. We give several examples and simulations illustrating different cases.

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

PubMed

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.

Msx homeobox gene family and craniofacial development.

PubMed

Alappat, Sylvia; Zhang, Zun Yi; Chen, Yi Ping

2003-12-01

Vertebrate Msx genes are unlinked, homeobox-containing genes that bear homology to the Drosophila muscle segment homeobox gene. These genes are expressed at multiple sites of tissue-tissue interactions during vertebrate embryonic development. Inductive interactions mediated by the Msx genes are essential for normal craniofacial, limb and ectodermal organ morphogenesis, and are also essential to survival in mice, as manifested by the phenotypic abnormalities shown in knockout mice and in humans. This review summarizes studies on the expression, regulation, and functional analysis of Msx genes that bear relevance to craniofacial development in humans and mice. Key words: Msx genes, craniofacial, tooth, cleft palate, suture, development, transcription factor, signaling molecule.

The metazoan Mediator co-activator complex as an integrative hub for transcriptional regulation.

PubMed

Malik, Sohail; Roeder, Robert G

2010-11-01

The Mediator is an evolutionarily conserved, multiprotein complex that is a key regulator of protein-coding genes. In metazoan cells, multiple pathways that are responsible for homeostasis, cell growth and differentiation converge on the Mediator through transcriptional activators and repressors that target one or more of the almost 30 subunits of this complex. Besides interacting directly with RNA polymerase II, Mediator has multiple functions and can interact with and coordinate the action of numerous other co-activators and co-repressors, including those acting at the level of chromatin. These interactions ultimately allow the Mediator to deliver outputs that range from maximal activation of genes to modulation of basal transcription to long-term epigenetic silencing.

What Gene-Environment Interactions Can Tell Us about Social Competence in Typical and Atypical Populations

ERIC Educational Resources Information Center

Iarocci, Grace; Yager, Jodi; Elfers, Theo

2007-01-01

Social competence is a complex human behaviour that is likely to involve a system of genes that interacts with a myriad of environmental risk and protective factors. The search for its genetic and environmental origins and influences is equally complex and will require a multidimensional conceptualization and multiple methods and levels of…

Associations and interactions between SNPs in the alcohol metabolizing genes and alcoholism phenotypes in European Americans.

PubMed

Sherva, Richard; Rice, John P; Neuman, Rosalind J; Rochberg, Nanette; Saccone, Nancy L; Bierut, Laura J

2009-05-01

Alcohol dependence is a major cause of morbidity and mortality worldwide and has a strong familial component. Several linkage and association studies have identified chromosomal regions and/or genes that affect alcohol consumption, notably in genes involved in the 2-stage pathway of alcohol metabolism. Here, we use multiple regression models to test for associations and interactions between 2 alcohol-related phenotypes and SNPs in 17 genes involved in alcohol metabolism in a sample of 1,588 European American subjects. The strongest evidence for association after correcting for multiple testing was between rs1229984, a nonsynonymous coding SNP in ADH1B, and DSM-IV symptom count (p = 0.0003). This SNP was also associated with maximum number of drinks in 24 hours (p = 0.0004). Each minor allele at this SNP predicts 45% fewer DSM-IV symptoms and 18% fewer max drinks. Another SNP in a splice site in ALDH1A1 (rs8187974) showed evidence for association with both phenotypes as well (p = 0.02 and 0.004, respectively), but neither association was significant after accounting for multiple testing. Minor alleles at this SNP predict greater alcohol consumption. In addition, pairwise interactions were observed between SNPs in several genes (p = 0.00002). We replicated the large effect of rs1229984 on alcohol behavior, and although not common (MAF = 4%), this polymorphism may be highly relevant from a public health perspective in European Americans. Another SNP, rs8187974, may also affect alcohol behavior but requires replication. Also, interactions between polymorphisms in genes involved in alcohol metabolism are likely determinants of the parameters that ultimately affect alcohol consumption.

TGMI: an efficient algorithm for identifying pathway regulators through evaluation of triple-gene mutual interaction

PubMed Central

Gunasekara, Chathura; Zhang, Kui; Deng, Wenping; Brown, Laura

2018-01-01

Abstract Despite their important roles, the regulators for most metabolic pathways and biological processes remain elusive. Presently, the methods for identifying metabolic pathway and biological process regulators are intensively sought after. We developed a novel algorithm called triple-gene mutual interaction (TGMI) for identifying these regulators using high-throughput gene expression data. It first calculated the regulatory interactions among triple gene blocks (two pathway genes and one transcription factor (TF)), using conditional mutual information, and then identifies significantly interacted triple genes using a newly identified novel mutual interaction measure (MIM), which was substantiated to reflect strengths of regulatory interactions within each triple gene block. The TGMI calculated the MIM for each triple gene block and then examined its statistical significance using bootstrap. Finally, the frequencies of all TFs present in all significantly interacted triple gene blocks were calculated and ranked. We showed that the TFs with higher frequencies were usually genuine pathway regulators upon evaluating multiple pathways in plants, animals and yeast. Comparison of TGMI with several other algorithms demonstrated its higher accuracy. Therefore, TGMI will be a valuable tool that can help biologists to identify regulators of metabolic pathways and biological processes from the exploded high-throughput gene expression data in public repositories. PMID:29579312

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

PubMed

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 unsuspected effects that could provide novel insights into MDD risk, but much larger sample sizes are needed before this strategy can be powerfully applied.

Considering interactive effects in the identification of influential regions with extremely rare variants via fixed bin approach

PubMed Central

2014-01-01

In this study, we analyze the Genetic Analysis Workshop 18 (GAW18) data to identify regions of single-nucleotide polymorphisms (SNPs), which significantly influence hypertension status among individuals. We have studied the marginal impact of these regions on disease status in the past, but we extend the method to deal with environmental factors present in data collected over several exam periods. We consider the respective interactions between such traits as smoking status and age with the genetic information and hope to augment those genetic regions deemed influential marginally with those that contribute via an interactive effect. In particular, we focus only on rare variants and apply a procedure to combine signal among rare variants in a number of "fixed bins" along the chromosome. We extend the procedure in Agne et al [1] to incorporate environmental factors by dichotomizing subjects via traits such as smoking status and age, running the marginal procedure among each respective category (i.e., smokers or nonsmokers), and then combining their scores into a score for interaction. To avoid overlap of subjects, we examine each exam period individually. Out of a possible 629 fixed-bin regions in chromosome 3, we observe that 11 show up in multiple exam periods for gene-smoking score. Fifteen regions exhibit significance for multiple exam periods for gene-age score, with 4 regions deemed significant for all 3 exam periods. The procedure pinpoints SNPs in 8 "answer" genes, with 5 of these showing up as significant in multiple testing schemes (Gene-Smoking, Gene-Age for Exams 1, 2, and 3). PMID:25519400

A "candidate-interactome" aggregate analysis of genome-wide association data in multiple sclerosis.

PubMed

Mechelli, Rosella; Umeton, Renato; Policano, Claudia; Annibali, Viviana; Coarelli, Giulia; Ricigliano, Vito A G; Vittori, Danila; Fornasiero, Arianna; Buscarinu, Maria Chiara; Romano, Silvia; Salvetti, Marco; Ristori, Giovanni

2013-01-01

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a "candidate interactome" (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms.

A “Candidate-Interactome” Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

PubMed Central

Policano, Claudia; Annibali, Viviana; Coarelli, Giulia; Ricigliano, Vito A. G.; Vittori, Danila; Fornasiero, Arianna; Buscarinu, Maria Chiara; Romano, Silvia; Salvetti, Marco; Ristori, Giovanni

2013-01-01

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a “candidate interactome” (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms. PMID:23696811

The Rice Tungro Bacilliform Virus Gene II Product Interacts with the Coat Protein Domain of the Viral Gene III Polyprotein

PubMed Central

Herzog, Etienne; Guerra-Peraza, Orlene; Hohn, Thomas

2000-01-01

Rice tungro bacilliform virus (RTBV) is a plant pararetrovirus whose DNA genome contains four genes encoding three proteins and a large polyprotein. The function of most of the viral proteins is still unknown. To investigate the role of the gene II product (P2), we searched for interactions between this protein and other RTBV proteins. P2 was shown to interact with the coat protein (CP) domain of the viral gene III polyprotein (P3) both in the yeast two-hybrid system and in vitro. Domains involved in the P2-CP association have been identified and mapped on both proteins. To determine the importance of this interaction for viral multiplication, the infectivity of RTBV gene II mutants was investigated by agroinoculation of rice plants. The results showed that virus viability correlates with the ability of P2 to interact with the CP domain of P3. This study suggests that P2 could participate in RTBV capsid assembly. PMID:10666237

A Novel Test for Gene-Ancestry Interactions in Genome-Wide Association Data

PubMed Central

Dunlop, Malcolm G.; Houlston, Richard S.; Tomlinson, Ian P.; Holmes, Chris C.

2012-01-01

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. PMID:23236349

Discovery of gene-gene interactions across multiple independent data sets of late onset Alzheimer disease from the Alzheimer Disease Genetics Consortium.

PubMed

Hohman, Timothy J; Bush, William S; Jiang, Lan; Brown-Gentry, Kristin D; Torstenson, Eric S; Dudek, Scott M; Mukherjee, Shubhabrata; Naj, Adam; Kunkle, Brian W; Ritchie, Marylyn D; Martin, Eden R; Schellenberg, Gerard D; Mayeux, Richard; Farrer, Lindsay A; Pericak-Vance, Margaret A; Haines, Jonathan L; Thornton-Wells, Tricia A

2016-02-01

Late-onset Alzheimer disease (AD) has a complex genetic etiology, involving locus heterogeneity, polygenic inheritance, and gene-gene interactions; however, the investigation of interactions in recent genome-wide association studies has been limited. We used a biological knowledge-driven approach to evaluate gene-gene interactions for consistency across 13 data sets from the Alzheimer Disease Genetics Consortium. Fifteen single nucleotide polymorphism (SNP)-SNP pairs within 3 gene-gene combinations were identified: SIRT1 × ABCB1, PSAP × PEBP4, and GRIN2B × ADRA1A. In addition, we extend a previously identified interaction from an endophenotype analysis between RYR3 × CACNA1C. Finally, post hoc gene expression analyses of the implicated SNPs further implicate SIRT1 and ABCB1, and implicate CDH23 which was most recently identified as an AD risk locus in an epigenetic analysis of AD. The observed interactions in this article highlight ways in which genotypic variation related to disease may depend on the genetic context in which it occurs. Further, our results highlight the utility of evaluating genetic interactions to explain additional variance in AD risk and identify novel molecular mechanisms of AD pathogenesis. Copyright © 2016 Elsevier Inc. All rights reserved.

Genome organization and long-range regulation of gene expression by enhancers

PubMed Central

Smallwood, Andrea; Ren, Bing

2014-01-01

It is now well accepted that cell-type specific gene regulation is under the purview of enhancers. Great strides have been made recently to characterize and identify enhancers both genetically and epigenetically for multiple cell types and species, but efforts have just begun to link enhancers to their target promoters. Mapping these interactions and understanding how the 3D landscape of the genome constrains such interactions is fundamental to our understanding of mammalian gene regulation. Here, we review recent progress in mapping long-range regulatory interactions in mammalian genomes, focusing on transcriptional enhancers and chromatin organization principles. PMID:23465541

Gene-Based Testing of Interactions in Association Studies of Quantitative Traits

PubMed Central

Ma, Li; Clark, Andrew G.; Keinan, Alon

2013-01-01

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. PMID:23468652

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

PubMed Central

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

2015-01-01

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

Examination of association to autism of common genetic variationin genes related to dopamine.

PubMed

Anderson, B M; Schnetz-Boutaud, N; Bartlett, J; Wright, H H; Abramson, R K; Cuccaro, M L; Gilbert, J R; Pericak-Vance, M A; Haines, J L

2008-12-01

Autism is a severe neurodevelopmental disorder characterized by a triad of complications. Autistic individuals display significant disturbances in language and reciprocal social interactions, combined with repetitive and stereotypic behaviors. Prevalence studies suggest that autism is more common than originally believed, with recent estimates citing a rate of one in 150. Although multiple genetic linkage and association studies have yielded multiple suggestive genes or chromosomal regions, a specific risk locus has yet to be identified and widely confirmed. Because many etiologies have been suggested for this complex syndrome, we hypothesize that one of the difficulties in identifying autism genes is that multiple genetic variants may be required to significantly increase the risk of developing autism. Thus, we took the alternative approach of examining 14 prominent dopamine pathway candidate genes for detailed study by genotyping 28 single nucleotide polymorphisms. Although we did observe a nominally significant association for rs2239535 (P=0.008) on chromosome 20, single-locus analysis did not reveal any results as significant after correction for multiple comparisons. No significant interaction was identified when Multifactor Dimensionality Reduction was employed to test specifically for multilocus effects. Although genome-wide linkage scans in autism have provided support for linkage to various loci along the dopamine pathway, our study does not provide strong evidence of linkage or association to any specific gene or combination of genes within the pathway. These results demonstrate that common genetic variation within the tested genes located within this pathway at most play a minor to moderate role in overall autism pathogenesis.

Genome-wide analysis of epistasis in body mass index using multiple human populations.

PubMed

Wei, Wen-Hua; Hemani, Gib; Gyenesei, Attila; Vitart, Veronique; Navarro, Pau; Hayward, Caroline; Cabrera, Claudia P; Huffman, Jennifer E; Knott, Sara A; Hicks, Andrew A; Rudan, Igor; Pramstaller, Peter P; Wild, Sarah H; Wilson, James F; Campbell, Harry; Hastie, Nicholas D; Wright, Alan F; Haley, Chris S

2012-08-01

We surveyed gene-gene interactions (epistasis) in human body mass index (BMI) in four European populations (n<1200) via exhaustive pair-wise genome scans where interactions were computed as F ratios by testing a linear regression model fitting two single-nucleotide polymorphisms (SNPs) with interactions against the one without. Before the association tests, BMI was corrected for sex and age, normalised and adjusted for relatedness. Neither single SNPs nor SNP interactions were genome-wide significant in either cohort based on the consensus threshold (P=5.0E-08) and a Bonferroni corrected threshold (P=1.1E-12), respectively. Next we compared sub genome-wide significant SNP interactions (P<5.0E-08) across cohorts to identify common epistatic signals, where SNPs were annotated to genes to test for gene ontology (GO) enrichment. Among the epistatic genes contributing to the commonly enriched GO terms, 19 were shared across study cohorts of which 15 are previously published genome-wide association loci, including CDH13 (cadherin 13) associated with height and SORCS2 (sortilin-related VPS10 domain containing receptor 2) associated with circulating insulin-like growth factor 1 and binding protein 3. Interactions between the 19 shared epistatic genes and those involving BMI candidate loci (P<5.0E-08) were tested across cohorts and found eight replicated at the SNP level (P<0.05) in at least one cohort, which were further tested and showed limited replication in a separate European population (n>5000). We conclude that genome-wide analysis of epistasis in multiple populations is an effective approach to provide new insights into the genetic regulation of BMI but requires additional efforts to confirm the findings.

Growth factor transgenes interactively regulate articular chondrocytes.

PubMed

Shi, Shuiliang; Mercer, Scott; Eckert, George J; Trippel, Stephen B

2013-04-01

Adult articular chondrocytes lack an effective repair response to correct damage from injury or osteoarthritis. Polypeptide growth factors that stimulate articular chondrocyte proliferation and cartilage matrix synthesis may augment this response. Gene transfer is a promising approach to delivering such factors. Multiple growth factor genes regulate these cell functions, but multiple growth factor gene transfer remains unexplored. We tested the hypothesis that multiple growth factor gene transfer selectively modulates articular chondrocyte proliferation and matrix synthesis. We tested the hypothesis by delivering combinations of the transgenes encoding insulin-like growth factor I (IGF-I), fibroblast growth factor-2 (FGF-2), transforming growth factor beta1 (TGF-β1), bone morphogenetic protein-2 (BMP-2), and bone morphogenetic protien-7 (BMP-7) to articular chondrocytes and measured changes in the production of DNA, glycosaminoglycan, and collagen. The transgenes differentially regulated all these chondrocyte activities. In concert, the transgenes interacted to generate widely divergent responses from the cells. These interactions ranged from inhibitory to synergistic. The transgene pair encoding IGF-I and FGF-2 maximized cell proliferation. The three-transgene group encoding IGF-I, BMP-2, and BMP-7 maximized matrix production and also optimized the balance between cell proliferation and matrix production. These data demonstrate an approach to articular chondrocyte regulation that may be tailored to stimulate specific cell functions, and suggest that certain growth factor gene combinations have potential value for cell-based articular cartilage repair. Copyright © 2012 Wiley Periodicals, Inc.

Expression Patterns and Identified Protein-Protein Interactions Suggest That Cassava CBL-CIPK Signal Networks Function in Responses to Abiotic Stresses.

PubMed

Mo, Chunyan; Wan, Shumin; Xia, Youquan; Ren, Ning; Zhou, Yang; Jiang, Xingyu

2018-01-01

Cassava is an energy crop that is tolerant of multiple abiotic stresses. It has been reported that the interaction between Calcineurin B-like (CBL) protein and CBL-interacting protein kinase (CIPK) is implicated in plant development and responses to various stresses. However, little is known about their functions in cassava. Herein, 8 CBL ( MeCBL ) and 26 CIPK ( MeCIPK ) genes were isolated from cassava by genome searching and cloning of cDNA sequences of Arabidopsis CBL s and CIPK s. Reverse-transcriptase polymerase chain reaction (RT-PCR) analysis showed that the expression levels of MeCBL and MeCIPK genes were different in different tissues throughout the life cycle. The expression patterns of 7 CBL and 26 CIPK genes in response to NaCl, PEG, heat and cold stresses were analyzed by quantitative real-time PCR (qRT-PCR), and it was found that the expression of each was induced by multiple stimuli. Furthermore, we found that many pairs of CBLs and CIPKs could interact with each other via investigating the interactions between 8 CBL and 25 CIPK proteins using a yeast two-hybrid system. Yeast cells co-transformed with cassava MeCIPK24, MeCBL10 , and Na + /H + antiporter MeSOS1 genes exhibited higher salt tolerance compared to those with one or two genes. These results suggest that the cassava CBL-CIPK signal network might play key roles in response to abiotic stresses.

Expression Patterns and Identified Protein-Protein Interactions Suggest That Cassava CBL-CIPK Signal Networks Function in Responses to Abiotic Stresses

PubMed Central

Mo, Chunyan; Wan, Shumin; Xia, Youquan; Ren, Ning; Zhou, Yang; Jiang, Xingyu

2018-01-01

Cassava is an energy crop that is tolerant of multiple abiotic stresses. It has been reported that the interaction between Calcineurin B-like (CBL) protein and CBL-interacting protein kinase (CIPK) is implicated in plant development and responses to various stresses. However, little is known about their functions in cassava. Herein, 8 CBL (MeCBL) and 26 CIPK (MeCIPK) genes were isolated from cassava by genome searching and cloning of cDNA sequences of Arabidopsis CBLs and CIPKs. Reverse-transcriptase polymerase chain reaction (RT-PCR) analysis showed that the expression levels of MeCBL and MeCIPK genes were different in different tissues throughout the life cycle. The expression patterns of 7 CBL and 26 CIPK genes in response to NaCl, PEG, heat and cold stresses were analyzed by quantitative real-time PCR (qRT-PCR), and it was found that the expression of each was induced by multiple stimuli. Furthermore, we found that many pairs of CBLs and CIPKs could interact with each other via investigating the interactions between 8 CBL and 25 CIPK proteins using a yeast two-hybrid system. Yeast cells co-transformed with cassava MeCIPK24, MeCBL10, and Na+/H+ antiporter MeSOS1 genes exhibited higher salt tolerance compared to those with one or two genes. These results suggest that the cassava CBL-CIPK signal network might play key roles in response to abiotic stresses. PMID:29552024

Diet and Colorectal Cancer: Analysis of a Candidate Pathway Using SNPS, Haplotypes, and Multi-Gene Assessment

PubMed Central

Slattery, Martha L.; Lundgreen, Abbie; Herrick, Jennifer S.; Caan, Bette J.; Potter, John D.; Wolff, Roger K.

2012-01-01

There is considerable biologic plausibility to the hypothesis that genetic variability in pathways involved in insulin signaling and energy homeostasis may modulate dietary risk associated with colorectal cancer. We utilized data from 2 population-based case-control studies of colon (n = 1,574 cases, 1,970 controls) and rectal (n = 791 cases, 999 controls) cancer to evaluate genetic variation in candidate SNPs identified from 9 genes in a candidate pathway: PDK1, RP6KA1, RPS6KA2, RPS6KB1, RPS6KB2, PTEN, FRAP1 (mTOR), TSC1, TSC2, Akt1, PIK3CA, and PRKAG2 with dietary intake of total energy, carbohydrates, fat, and fiber. We employed SNP, haplotype, and multiple-gene analysis to evaluate associations. PDK1 interacted with dietary fat for both colon and rectal cancer and with dietary carbohydrates for colon cancer. Statistically significant interaction with dietary carbohydrates and rectal cancer was detected by haplotype analysis of PDK1. Evaluation of dietary interactions with multiple genes in this candidate pathway showed several interactions with pairs of genes: Akt1 and PDK1, PDK1 and PTEN, PDK1 and TSC1, and PRKAG2 and PTEN. Analyses show that genetic variation influences risk of colorectal cancer associated with diet and illustrate the importance of evaluating dietary interactions beyond the level of single SNPs or haplotypes when a biologically relevant candidate pathway is examined. PMID:21999454

Comprehensive Analysis of Interaction Networks of Telomerase Reverse Transcriptase with Multiple Bioinformatic Approaches: Deep Mining the Potential Functions of Telomere and Telomerase.

PubMed

Hou, Chunyu; Wang, Fei; Liu, Xuewen; Chang, Guangming; Wang, Feng; Geng, Xin

2017-08-01

Telomerase reverse transcriptase (TERT) is the protein component of telomerase complex. Evidence has accumulated showing that the nontelomeric functions of TERT are independent of telomere elongation. However, the mechanisms governing the interaction between TERT and its target genes are not clearly revealed. The biological functions of TERT are not fully elucidated and have thus far been underestimated. To further explore these functions, we investigated TERT interaction networks using multiple bioinformatic databases, including BioGRID, STRING, DAVID, GeneCards, GeneMANIA, PANTHER, miRWalk, mirTarBase, miRNet, miRDB, and TargetScan. In addition, network diagrams were built using Cytoscape software. As competing endogenous RNAs (ceRNAs) are endogenous transcripts that compete for the binding of microRNAs (miRNAs) by using shared miRNA recognition elements, they are involved in creating widespread regulatory networks. Therefore, the ceRNA regulatory networks of TERT were also investigated in this study. Interestingly, we found that the three genes PABPC1, SLC7A11, and TP53 were present in both TERT interaction networks and ceRNAs target genes. It was predicted that TERT might play nontelomeric roles in the generation or development of some rare diseases, such as Rift Valley fever and dyscalculia. Thus, our data will help to decipher the interaction networks of TERT and reveal the unknown functions of telomerase in cancer and aging-related diseases.

Multiple OPR genes influence personality traits in substance dependent and healthy subjects in two American populations

PubMed Central

Luo, Xingguang; Zuo, Lingjun; Kranzler, Henry; Zhang, Huiping; Wang, Shuang; Gelernter, Joel

2011-01-01

Background Personality traits are among the most complex quantitative traits. Certain personality traits are associated with substance dependence (SD); genetic factors may influence both. Associations between opioid receptor (OPR) genes and SD have been reported. This study investigated the relationship between OPR genes and personality traits in a case-control sample. Methods We assessed dimensions of the five-factor model of personality in 556 subjects: 250 with SD [181 European-Americans (EAs) and 69 African-Americans (AAs)] and 306 healthy subjects (266 EAs and 40 AAs). We genotyped 20 OPRM1 markers, 8 OPRD1 markers, and 7 OPRK1 markers, and 38 unlinked ancestry-informative markers in these subjects. The relationships between OPR genes and personality traits were examined using MANCOVA, controlling for gene-gene interaction effects and potential confounders. Associations were decomposed by Roy-Bargmann Stepdown ANCOVA. Results Personality traits were associated as main or interaction effects with the haplotypes, diplotypes, alleles and genotypes at the three OPR genes (0.002

Ant Species Differences Determined by Epistasis between Brood and Worker Genomes

PubMed Central

Linksvayer, Timothy A.

2007-01-01

Epistasis arising from physiological interactions between gene products often contributes to species differences, particularly those involved in reproductive isolation. In social organisms, phenotypes are influenced by the genotypes of multiple interacting individuals. In theory, social interactions can give rise to an additional type of epistasis between the genomes of social partners that can contribute to species differences. Using a full-factorial cross-fostering design with three species of closely related Temnothorax ants, I found that adult worker size was determined by an interaction between the genotypes of developing brood and care-giving workers, i.e. intergenomic epistasis. Such intergenomic social epistasis provides a strong signature of coevolution between social partners. These results demonstrate that just as physiologically interacting genes coevolve, diverge, and contribute to species differences, so do socially interacting genes. Coevolution and conflict between social partners, especially relatives such as parents and offspring, has long been recognized as having widespread evolutionary effects. This coevolutionary process may often result in coevolved socially-interacting gene complexes that contribute to species differences. PMID:17912371

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

PubMed Central

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

2008-01-01

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

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

PubMed

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

2009-01-01

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

Identification of fever and vaccine-associated gene interaction networks using ontology-based literature mining

PubMed Central

2012-01-01

Background Fever is one of the most common adverse events of vaccines. The detailed mechanisms of fever and vaccine-associated gene interaction networks are not fully understood. In the present study, we employed a genome-wide, Centrality and Ontology-based Network Discovery using Literature data (CONDL) approach to analyse the genes and gene interaction networks associated with fever or vaccine-related fever responses. Results Over 170,000 fever-related articles from PubMed abstracts and titles were retrieved and analysed at the sentence level using natural language processing techniques to identify genes and vaccines (including 186 Vaccine Ontology terms) as well as their interactions. This resulted in a generic fever network consisting of 403 genes and 577 gene interactions. A vaccine-specific fever sub-network consisting of 29 genes and 28 gene interactions was extracted from articles that are related to both fever and vaccines. In addition, gene-vaccine interactions were identified. Vaccines (including 4 specific vaccine names) were found to directly interact with 26 genes. Gene set enrichment analysis was performed using the genes in the generated interaction networks. Moreover, the genes in these networks were prioritized using network centrality metrics. Making scientific discoveries and generating new hypotheses were possible by using network centrality and gene set enrichment analyses. For example, our study found that the genes in the generic fever network were more enriched in cell death and responses to wounding, and the vaccine sub-network had more gene enrichment in leukocyte activation and phosphorylation regulation. The most central genes in the vaccine-specific fever network are predicted to be highly relevant to vaccine-induced fever, whereas genes that are central only in the generic fever network are likely to be highly relevant to generic fever responses. Interestingly, no Toll-like receptors (TLRs) were found in the gene-vaccine interaction network. Since multiple TLRs were found in the generic fever network, it is reasonable to hypothesize that vaccine-TLR interactions may play an important role in inducing fever response, which deserves a further investigation. Conclusions This study demonstrated that ontology-based literature mining is a powerful method for analyzing gene interaction networks and generating new scientific hypotheses. PMID:23256563

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

PubMed

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

2014-01-01

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

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

PubMed Central

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

2014-01-01

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

Consortium analysis of gene and gene-folate interactions in purine and pyrimidine metabolism pathways with ovarian carcinoma risk

PubMed Central

Kelemen, Linda E.; Terry, Kathryn L.; Goodman, Marc T.; Webb, Penelope M.; Bandera, Elisa V.; McGuire, Valerie; Rossing, Mary Anne; Wang, Qinggang; Dicks, Ed; Tyrer, Jonathan P.; Song, Honglin; Kupryjanczyk, Jolanta; Dansonka-Mieszkowska, Agnieszka; Plisiecka-Halasa, Joanna; Timorek, Agnieszka; Menon, Usha; Gentry-Maharaj, Aleksandra; Gayther, Simon A.; Ramus, Susan J.; Narod, Steven A.; Risch, Harvey A.; McLaughlin, John R.; Siddiqui, Nadeem; Glasspool, Rosalind; Paul, James; Carty, Karen; Gronwald, Jacek; Lubiński, Jan; Jakubowska, Anna; Cybulski, Cezary; Kiemeney, Lambertus A.; Massuger, Leon F. A. G.; van Altena, Anne M.; Aben, Katja K. H.; Olson, Sara H.; Orlow, Irene; Cramer, Daniel W.; Levine, Douglas A.; Bisogna, Maria; Giles, Graham G.; Southey, Melissa C.; Bruinsma, Fiona; Kjær, Susanne Krüger; Høgdall, Estrid; Jensen, Allan; Høgdall, Claus K.; Lundvall, Lene; Engelholm, Svend-Aage; Heitz, Florian; du Bois, Andreas; Harter, Philipp; Schwaab, Ira; Butzow, Ralf; Nevanlinna, Heli; Pelttari, Liisa M.; Leminen, Arto; Thompson, Pamela J.; Lurie, Galina; Wilkens, Lynne R.; Lambrechts, Diether; Van Nieuwenhuysen, Els; Lambrechts, Sandrina; Vergote, Ignace; Beesley, Jonathan; Fasching, Peter A.; Beckmann, Matthias W.; Hein, Alexander; Ekici, Arif B.; Doherty, Jennifer A.; Wu, Anna H.; Pearce, Celeste L.; Pike, Malcolm C.; Stram, Daniel; Chang-Claude, Jenny; Rudolph, Anja; Dörk, Thilo; Dürst, Matthias; Hillemanns, Peter; Runnebaum, Ingo B.; Bogdanova, Natalia; Antonenkova, Natalia; Odunsi, Kunle; Edwards, Robert P.; Kelley, Joseph L.; Modugno, Francesmary; Ness, Roberta B.; Karlan, Beth Y.; Walsh, Christine; Lester, Jenny; Orsulic, Sandra; Fridley, Brooke L.; Vierkant, Robert A.; Cunningham, Julie M.; Wu, Xifeng; Lu, Karen; Liang, Dong; Hildebrandt, Michelle A.T.; Weber, Rachel Palmieri; Iversen, Edwin S.; Tworoger, Shelley S.; Poole, Elizabeth M.; Salvesen, Helga B.; Krakstad, Camilla; Bjorge, Line; Tangen, Ingvild L.; Pejovic, Tanja; Bean, Yukie; Kellar, Melissa; Wentzensen, Nicolas; Brinton, Louise A.; Lissowska, Jolanta; Garcia-Closas, Montserrat; Campbell, Ian G.; Eccles, Diana; Whittemore, Alice S.; Sieh, Weiva; Rothstein, Joseph H.; Anton-Culver, Hoda; Ziogas, Argyrios; Phelan, Catherine M.; Moysich, Kirsten B.; Goode, Ellen L.; Schildkraut, Joellen M.; Berchuck, Andrew; Pharoah, Paul D.P.; Sellers, Thomas A.; Brooks-Wilson, Angela; Cook, Linda S.; Le, Nhu D.

2014-01-01

Scope We re-evaluated previously reported associations between variants in pathways of one-carbon (folate) transfer genes and ovarian carcinoma (OC) risk, and in related pathways of purine and pyrimidine metabolism, and assessed interactions with folate intake. Methods and Results Odds ratios (OR) for 446 genetic variants were estimated among 13,410 OC cases and 22,635 controls and among 2,281 cases and 3,444 controls with folate information. Following multiple testing correction, the most significant main effect associations were for DPYD variants rs11587873 (OR=0.92, P=6x10−5) and rs828054 (OR=1.06, P=1x10−4). Thirteen variants in the pyrimidine metabolism genes, DPYD, DPYS, PPAT and TYMS, also interacted significantly with folate in a multi-variant analysis (corrected P=9.9x10−6) but collectively explained only 0.2% of OC risk. Although no other associations were significant after multiple testing correction, variants in SHMT1 in one-carbon transfer, previously reported with OC, suggested lower risk at higher folate (Pinteraction=0.03-0.006). Conclusions Variation in pyrimidine metabolism genes, particularly DPYD, which was previously reported to be associated with OC, may influence risk; however, stratification by folate intake is unlikely to modify disease risk appreciably in these women. SHMT1 SNP-byfolate interactions are plausible but require further validation. Polymorphisms in selected genes in purine metabolism were not associated with OC. PMID:25066213

Serotonin transporter gene and childhood trauma--a G × E effect on anxiety sensitivity.

PubMed

Klauke, Benedikt; Deckert, Jürgen; Reif, Andreas; Pauli, Paul; Zwanzger, Peter; Baumann, Christian; Arolt, Volker; Glöckner-Rist, Angelika; Domschke, Katharina

2011-12-21

Genetic factors and environmental factors are assumed to interactively influence the pathogenesis of anxiety disorders. Thus, a gene-environment interaction (G × E) study was conducted with respect to anxiety sensitivity (AS) as a promising intermediate phenotype of anxiety disorders. Healthy subjects (N = 363) were assessed for AS, childhood maltreatment (Childhood Trauma Questionnaire), and genotyped for functional serotonin transporter gene variants (5-HTTLPR/5-HTT rs25531). The influence of genetic and environmental variables on AS and its subdimensions was determined by a step-wise hierarchical regression and a multiple indicator multiple cause (MIMIC) model. A significant G × E effect of the more active 5-HTT genotypes and childhood maltreatment on AS was observed. Furthermore, genotype (LL)-childhood trauma interaction particularly influenced somatic AS subdimensions, whereas cognitive subdimensions were affected by childhood maltreatment only. Results indicate a G × E effect of the more active 5-HTT genotypes and childhood maltreatment on AS, with particular impact on its somatic subcomponent. © 2011 Wiley Periodicals, Inc.

Genome organization and long-range regulation of gene expression by enhancers.

PubMed

Smallwood, Andrea; Ren, Bing

2013-06-01

It is now well accepted that cell-type specific gene regulation is under the purview of enhancers. Great strides have been made recently to characterize and identify enhancers both genetically and epigenetically for multiple cell types and species, but efforts have just begun to link enhancers to their target promoters. Mapping these interactions and understanding how the 3D landscape of the genome constrains such interactions is fundamental to our understanding of mammalian gene regulation. Here, we review recent progress in mapping long-range regulatory interactions in mammalian genomes, focusing on transcriptional enhancers and chromatin organization principles. Copyright © 2013. Published by Elsevier Ltd.

The Association of Multiple Interacting Genes with Specific Phenotypes in Rice Using Gene Coexpression Networks1[C][W][OA

PubMed Central

Ficklin, Stephen P.; Luo, Feng; Feltus, F. Alex

2010-01-01

Discovering gene sets underlying the expression of a given phenotype is of great importance, as many phenotypes are the result of complex gene-gene interactions. Gene coexpression networks, built using a set of microarray samples as input, can help elucidate tightly coexpressed gene sets (modules) that are mixed with genes of known and unknown function. Functional enrichment analysis of modules further subdivides the coexpressed gene set into cofunctional gene clusters that may coexist in the module with other functionally related gene clusters. In this study, 45 coexpressed gene modules and 76 cofunctional gene clusters were discovered for rice (Oryza sativa) using a global, knowledge-independent paradigm and the combination of two network construction methodologies. Some clusters were enriched for previously characterized mutant phenotypes, providing evidence for specific gene sets (and their annotated molecular functions) that underlie specific phenotypes. PMID:20668062

The association of multiple interacting genes with specific phenotypes in rice using gene coexpression networks.

PubMed

Ficklin, Stephen P; Luo, Feng; Feltus, F Alex

2010-09-01

Discovering gene sets underlying the expression of a given phenotype is of great importance, as many phenotypes are the result of complex gene-gene interactions. Gene coexpression networks, built using a set of microarray samples as input, can help elucidate tightly coexpressed gene sets (modules) that are mixed with genes of known and unknown function. Functional enrichment analysis of modules further subdivides the coexpressed gene set into cofunctional gene clusters that may coexist in the module with other functionally related gene clusters. In this study, 45 coexpressed gene modules and 76 cofunctional gene clusters were discovered for rice (Oryza sativa) using a global, knowledge-independent paradigm and the combination of two network construction methodologies. Some clusters were enriched for previously characterized mutant phenotypes, providing evidence for specific gene sets (and their annotated molecular functions) that underlie specific phenotypes.

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

PubMed

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.

Analysis of Multiple Association Studies Provides Evidence of an Expression QTL Hub in Gene-Gene Interaction Network Affecting HDL Cholesterol Levels

PubMed Central

Ma, Li; Ballantyne, Christie; Brautbar, Ariel; Keinan, Alon

2014-01-01

Epistasis has been suggested to underlie part of the missing heritability in genome-wide association studies. In this study, we first report an analysis of gene-gene interactions affecting HDL cholesterol (HDL-C) levels in a candidate gene study of 2,091 individuals with mixed dyslipidemia from a clinical trial. Two additional studies, the Atherosclerosis Risk in Communities study (ARIC; n = 9,713) and the Multi-Ethnic Study of Atherosclerosis (MESA; n = 2,685), were considered for replication. We identified a gene-gene interaction between rs1532085 and rs12980554 (P = 7.1×10−7) in their effect on HDL-C levels, which is significant after Bonferroni correction (P c = 0.017) for the number of SNP pairs tested. The interaction successfully replicated in the ARIC study (P = 7.0×10−4; P c = 0.02). Rs1532085, an expression QTL (eQTL) of LIPC, is one of the two SNPs involved in another, well-replicated gene-gene interaction underlying HDL-C levels. To further investigate the role of this eQTL SNP in gene-gene interactions affecting HDL-C, we tested in the ARIC study for interaction between this SNP and any other SNP genome-wide. We found the eQTL to be involved in a few suggestive interactions, one of which significantly replicated in MESA. Importantly, these gene-gene interactions, involving only rs1532085, explain an additional 1.4% variation of HDL-C, on top of the 0.65% explained by rs1532085 alone. LIPC plays a key role in the lipid metabolism pathway and it, and rs1532085 in particular, has been associated with HDL-C and other lipid levels. Collectively, we discovered several novel gene-gene interactions, all involving an eQTL of LIPC, thus suggesting a hub role of LIPC in the gene-gene interaction network that regulates HDL-C levels, which in turn raises the hypothesis that LIPC's contribution is largely via interactions with other lipid metabolism related genes. PMID:24651390

Two White Spot Syndrome Virus MicroRNAs Target the Dorsal Gene To Promote Virus Infection in Marsupenaeus japonicus Shrimp

PubMed Central

Ren, Qian; Huang, Xin; Cui, Yalei; Sun, Jiejie; Wang, Wen

2017-01-01

ABSTRACT In eukaryotes, microRNAs (miRNAs) serve as regulators of many biological processes, including virus infection. An miRNA can generally target diverse genes during virus-host interactions. However, the regulation of gene expression by multiple miRNAs has not yet been extensively explored during virus infection. This study found that the Spaztle (Spz)-Toll-Dorsal-antilipopolysaccharide factor (ALF) signaling pathway plays a very important role in antiviral immunity against invasion of white spot syndrome virus (WSSV) in shrimp (Marsupenaeus japonicus). Dorsal, the central gene in the Toll pathway, was targeted by two viral miRNAs (WSSV-miR-N13 and WSSV-miR-N23) during WSSV infection. The regulation of Dorsal expression by viral miRNAs suppressed the Spz-Toll-Dorsal-ALF signaling pathway in shrimp in vivo, leading to virus infection. Our study contributes novel insights into the viral miRNA-mediated Toll signaling pathway during the virus-host interaction. IMPORTANCE An miRNA can target diverse genes during virus-host interactions. However, the regulation of gene expression by multiple miRNAs during virus infection has not yet been extensively explored. The results of this study indicated that the shrimp Dorsal gene, the central gene in the Toll pathway, was targeted by two viral miRNAs during infection with white spot syndrome virus. Regulation of Dorsal expression by viral miRNAs suppressed the Spz-Toll-Dorsal-ALF signaling pathway in shrimp in vivo, leading to virus infection. Our study provides new insight into the viral miRNA-mediated Toll signaling pathway in virus-host interactions. PMID:28179524

Two White Spot Syndrome Virus MicroRNAs Target the Dorsal Gene To Promote Virus Infection in Marsupenaeus japonicus Shrimp.

PubMed

Ren, Qian; Huang, Xin; Cui, Yalei; Sun, Jiejie; Wang, Wen; Zhang, Xiaobo

2017-04-15

In eukaryotes, microRNAs (miRNAs) serve as regulators of many biological processes, including virus infection. An miRNA can generally target diverse genes during virus-host interactions. However, the regulation of gene expression by multiple miRNAs has not yet been extensively explored during virus infection. This study found that the Spaztle (Spz)-Toll-Dorsal-antilipopolysaccharide factor (ALF) signaling pathway plays a very important role in antiviral immunity against invasion of white spot syndrome virus (WSSV) in shrimp ( Marsupenaeus japonicus ). Dorsal , the central gene in the Toll pathway, was targeted by two viral miRNAs (WSSV-miR-N13 and WSSV-miR-N23) during WSSV infection. The regulation of Dorsal expression by viral miRNAs suppressed the Spz-Toll-Dorsal-ALF signaling pathway in shrimp in vivo , leading to virus infection. Our study contributes novel insights into the viral miRNA-mediated Toll signaling pathway during the virus-host interaction. IMPORTANCE An miRNA can target diverse genes during virus-host interactions. However, the regulation of gene expression by multiple miRNAs during virus infection has not yet been extensively explored. The results of this study indicated that the shrimp Dorsal gene, the central gene in the Toll pathway, was targeted by two viral miRNAs during infection with white spot syndrome virus. Regulation of Dorsal expression by viral miRNAs suppressed the Spz-Toll-Dorsal-ALF signaling pathway in shrimp in vivo , leading to virus infection. Our study provides new insight into the viral miRNA-mediated Toll signaling pathway in virus-host interactions. Copyright © 2017 American Society for Microbiology.

Gene-environment studies: any advantage over environmental studies?

PubMed

Bermejo, Justo Lorenzo; Hemminki, Kari

2007-07-01

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

Patterns of evolution at the gametophytic self-incompatibility Sorbus aucuparia (Pyrinae) S pollen genes support the non-self recognition by multiple factors model.

PubMed

Aguiar, Bruno; Vieira, Jorge; Cunha, Ana E; Fonseca, Nuno A; Reboiro-Jato, David; Reboiro-Jato, Miguel; Fdez-Riverola, Florentino; Raspé, Olivier; Vieira, Cristina P

2013-05-01

S-RNase-based gametophytic self-incompatibility evolved once before the split of the Asteridae and Rosidae. In Prunus (tribe Amygdaloideae of Rosaceae), the self-incompatibility S-pollen is a single F-box gene that presents the expected evolutionary signatures. In Malus and Pyrus (subtribe Pyrinae of Rosaceae), however, clusters of F-box genes (called SFBBs) have been described that are expressed in pollen only and are linked to the S-RNase gene. Although polymorphic, SFBB genes present levels of diversity lower than those of the S-RNase gene. They have been suggested as putative S-pollen genes, in a system of non-self recognition by multiple factors. Subsets of allelic products of the different SFBB genes interact with non-self S-RNases, marking them for degradation, and allowing compatible pollinations. This study performed a detailed characterization of SFBB genes in Sorbus aucuparia (Pyrinae) to address three predictions of the non-self recognition by multiple factors model. As predicted, the number of SFBB genes was large to account for the many S-RNase specificities. Secondly, like the S-RNase gene, the SFBB genes were old. Thirdly, amino acids under positive selection-those that could be involved in specificity determination-were identified when intra-haplotype SFBB genes were analysed using codon models. Overall, the findings reported here support the non-self recognition by multiple factors model.

Limited Agreement of Independent RNAi Screens for Virus-Required Host Genes Owes More to False-Negative than False-Positive Factors

PubMed Central

Wang, Zhishi; Craven, Mark; Newton, Michael A.; Ahlquist, Paul

2013-01-01

Systematic, genome-wide RNA interference (RNAi) analysis is a powerful approach to identify gene functions that support or modulate selected biological processes. An emerging challenge shared with some other genome-wide approaches is that independent RNAi studies often show limited agreement in their lists of implicated genes. To better understand this, we analyzed four genome-wide RNAi studies that identified host genes involved in influenza virus replication. These studies collectively identified and validated the roles of 614 cell genes, but pair-wise overlap among the four gene lists was only 3% to 15% (average 6.7%). However, a number of functional categories were overrepresented in multiple studies. The pair-wise overlap of these enriched-category lists was high, ∼19%, implying more agreement among studies than apparent at the gene level. Probing this further, we found that the gene lists implicated by independent studies were highly connected in interacting networks by independent functional measures such as protein-protein interactions, at rates significantly higher than predicted by chance. We also developed a general, model-based approach to gauge the effects of false-positive and false-negative factors and to estimate, from a limited number of studies, the total number of genes involved in a process. For influenza virus replication, this novel statistical approach estimates the total number of cell genes involved to be ∼2,800. This and multiple other aspects of our experimental and computational results imply that, when following good quality control practices, the low overlap between studies is primarily due to false negatives rather than false-positive gene identifications. These results and methods have implications for and applications to multiple forms of genome-wide analysis. PMID:24068911

Disturbed Glucose Metabolism in Rat Neurons Exposed to Cerebrospinal Fluid Obtained from Multiple Sclerosis Subjects

PubMed Central

Mathur, Deepali; María-Lafuente, Eva; Ureña-Peralta, Juan R.; Sorribes, Lucas; Hernández, Alberto; Casanova, Bonaventura; López-Rodas, Gerardo; Coret-Ferrer, Francisco; Burgal-Marti, Maria

2017-01-01

Axonal damage is widely accepted as a major cause of permanent functional disability in Multiple Sclerosis (MS). In relapsing-remitting MS, there is a possibility of remyelination by myelin producing cells and restoration of neurological function. The purpose of this study was to delineate the pathophysiological mechanisms underpinning axonal injury through hitherto unknown factors present in cerebrospinal fluid (CSF) that may regulate axonal damage, remyelinate the axon and make functional recovery possible. We employed primary cultures of rat unmyelinated cerebellar granule neurons and treated them with CSF obtained from MS and Neuromyelitis optica (NMO) patients. We performed microarray gene expression profiling to study changes in gene expression in treated neurons as compared to controls. Additionally, we determined the influence of gene-gene interaction upon the whole metabolic network in our experimental conditions using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) program. Our findings revealed the downregulated expression of genes involved in glucose metabolism in MS-derived CSF-treated neurons and upregulated expression of genes in NMO-derived CSF-treated neurons. We conclude that factors in the CSF of these patients caused a perturbation in metabolic gene(s) expression and suggest that MS appears to be linked with metabolic deformity. PMID:29267205

Mimosa: Mixture Model of Co-expression to Detect Modulators of Regulatory Interaction

NASA Astrophysics Data System (ADS)

Hansen, Matthew; Everett, Logan; Singh, Larry; Hannenhalli, Sridhar

Functionally related genes tend to be correlated in their expression patterns across multiple conditions and/or tissue-types. Thus co-expression networks are often used to investigate functional groups of genes. In particular, when one of the genes is a transcription factor (TF), the co-expression-based interaction is interpreted, with caution, as a direct regulatory interaction. However, any particular TF, and more importantly, any particular regulatory interaction, is likely to be active only in a subset of experimental conditions. Moreover, the subset of expression samples where the regulatory interaction holds may be marked by presence or absence of a modifier gene, such as an enzyme that post-translationally modifies the TF. Such subtlety of regulatory interactions is overlooked when one computes an overall expression correlation. Here we present a novel mixture modeling approach where a TF-Gene pair is presumed to be significantly correlated (with unknown coefficient) in a (unknown) subset of expression samples. The parameters of the model are estimated using a Maximum Likelihood approach. The estimated mixture of expression samples is then mined to identify genes potentially modulating the TF-Gene interaction. We have validated our approach using synthetic data and on three biological cases in cow and in yeast. While limited in some ways, as discussed, the work represents a novel approach to mine expression data and detect potential modulators of regulatory interactions.

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

PubMed

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 to report new sets of genes that according to their gene expression and physical interactions are predicted to be differentially expressed in MS versus healthy subjects, and in MS patients in relapse versus remission. Some of these genes may be useful biomarkers for diagnosing MS and predicting relapses in MS patients.

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

PubMed

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

2006-12-01

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

[Analysis of genetic models and gene effects on main agronomy characters in rapeseed].

PubMed

Li, J; Qiu, J; Tang, Z; Shen, L

1992-01-01

According to four different genetic models, the genetic patterns of 8 agronomy traits were analysed by using the data of 24 generations which included positive and negative cross of 81008 x Tower, both of the varieties are of good quality. The results showed that none of 8 characters could fit in with additive-dominance models. Epistasis was found in all of these characters, and it has significant effect on generation means. Seed weight/plant and some other main yield characters are controlled by duplicate interaction genes. The interaction between triple genes or multiple genes needs to be utilized in yield heterosis.

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

PubMed

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

2017-01-01

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

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

PubMed

Coombes, Brandon; Basu, Saonli; McGue, Matt

2017-07-01

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

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

PubMed Central

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. PMID:28250767

Evolutionary origins of a novel host plant detoxification gene in butterflies.

PubMed

Fischer, Hanna M; Wheat, Christopher W; Heckel, David G; Vogel, Heiko

2008-05-01

Chemical interactions between plants and their insect herbivores provide an excellent opportunity to study the evolution of species interactions on a molecular level. Here, we investigate the molecular evolutionary events that gave rise to a novel detoxifying enzyme (nitrile-specifier protein [NSP]) in the butterfly family Pieridae, previously identified as a coevolutionary key innovation. By generating and sequencing expressed sequence tags, genomic libraries, and screening databases we found NSP to be a member of an insect-specific gene family, which we characterized and named the NSP-like gene family. Members consist of variable tandem repeats, are gut expressed, and are found across Insecta evolving in a dynamic, ongoing birth-death process. In the Lepidoptera, multiple copies of single-domain major allergen genes are present and originate via tandem duplications. Multiple domain genes are found solely within the brassicaceous-feeding Pieridae butterflies, one of them being NSP and another called major allergen (MA). Analyses suggest that NSP and its paralog MA have a unique single-domain evolutionary origin, being formed by intragenic domain duplication followed by tandem whole-gene duplication. Duplicates subsequently experienced a period of relaxed constraint followed by an increase in constraint, perhaps after neofunctionalization. NSP and its ortholog MA are still experiencing high rates of change, reflecting a dynamic evolution consistent with the known role of NSP in plant-insect interactions. Our results provide direct evidence to the hypothesis that gene duplication is one of the driving forces for speciation and adaptation, showing that both within- and whole-gene tandem duplications are a powerful force underlying evolutionary adaptation.

Patterns of evolution at the gametophytic self-incompatibility Sorbus aucuparia (Pyrinae) S pollen genes support the non-self recognition by multiple factors model

PubMed Central

Aguiar, Bruno; Vieira, Jorge; Cunha, Ana E.; Fonseca, Nuno A.; Reboiro-Jato, David; Reboiro-Jato, Miguel; Fdez-Riverola, Florentino; Raspé, Olivier; Vieira, Cristina P.

2013-01-01

S-RNase-based gametophytic self-incompatibility evolved once before the split of the Asteridae and Rosidae. In Prunus (tribe Amygdaloideae of Rosaceae), the self-incompatibility S-pollen is a single F-box gene that presents the expected evolutionary signatures. In Malus and Pyrus (subtribe Pyrinae of Rosaceae), however, clusters of F-box genes (called SFBBs) have been described that are expressed in pollen only and are linked to the S-RNase gene. Although polymorphic, SFBB genes present levels of diversity lower than those of the S-RNase gene. They have been suggested as putative S-pollen genes, in a system of non-self recognition by multiple factors. Subsets of allelic products of the different SFBB genes interact with non-self S-RNases, marking them for degradation, and allowing compatible pollinations. This study performed a detailed characterization of SFBB genes in Sorbus aucuparia (Pyrinae) to address three predictions of the non-self recognition by multiple factors model. As predicted, the number of SFBB genes was large to account for the many S-RNase specificities. Secondly, like the S-RNase gene, the SFBB genes were old. Thirdly, amino acids under positive selection—those that could be involved in specificity determination—were identified when intra-haplotype SFBB genes were analysed using codon models. Overall, the findings reported here support the non-self recognition by multiple factors model. PMID:23606363

Axonal guidance signaling pathway interacting with smoking in modifying the risk of pancreatic cancer: a gene- and pathway-based interaction analysis of GWAS data.

PubMed

Tang, Hongwei; Wei, Peng; Duell, Eric J; Risch, Harvey A; Olson, Sara H; Bueno-de-Mesquita, H Bas; Gallinger, Steven; Holly, Elizabeth A; Petersen, Gloria; Bracci, Paige M; McWilliams, Robert R; Jenab, Mazda; Riboli, Elio; Tjønneland, Anne; Boutron-Ruault, Marie Christine; Kaaks, Rudolph; Trichopoulos, Dimitrios; Panico, Salvatore; Sund, Malin; Peeters, Petra H M; Khaw, Kay-Tee; Amos, Christopher I; Li, Donghui

2014-05-01

Cigarette smoking is the best established modifiable risk factor for pancreatic cancer. Genetic factors that underlie smoking-related pancreatic cancer have previously not been examined at the genome-wide level. Taking advantage of the existing Genome-wide association study (GWAS) genotype and risk factor data from the Pancreatic Cancer Case Control Consortium, we conducted a discovery study in 2028 cases and 2109 controls to examine gene-smoking interactions at pathway/gene/single nucleotide polymorphism (SNP) level. Using the likelihood ratio test nested in logistic regression models and ingenuity pathway analysis (IPA), we examined 172 KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, 3 manually curated gene sets, 3 nicotine dependency gene ontology pathways, 17 912 genes and 468 114 SNPs. None of the individual pathway/gene/SNP showed significant interaction with smoking after adjusting for multiple comparisons. Six KEGG pathways showed nominal interactions (P < 0.05) with smoking, and the top two are the pancreatic secretion and salivary secretion pathways (major contributing genes: RAB8A, PLCB and CTRB1). Nine genes, i.e. ZBED2, EXO1, PSG2, SLC36A1, CLSTN1, MTHFSD, FAT2, IL10RB and ATXN2 had P interaction < 0.0005. Five intergenic region SNPs and two SNPs of the EVC and KCNIP4 genes had P interaction < 0.00003. In IPA analysis of genes with nominal interactions with smoking, axonal guidance signaling $$\\left(P=2.12\\times 1{0}^{-7}\\right)$$ and α-adrenergic signaling $$\\left(P=2.52\\times 1{0}^{-5}\\right)$$ genes were significantly overrepresented canonical pathways. Genes contributing to the axon guidance signaling pathway included the SLIT/ROBO signaling genes that were frequently altered in pancreatic cancer. These observations need to be confirmed in additional data set. Once confirmed, it will open a new avenue to unveiling the etiology of smoking-associated pancreatic cancer.

Direct interaction of menin leads to ubiquitin-proteasomal degradation of β-catenin.

PubMed

Kim, Byungho; Song, Tae-Yang; Jung, Kwan Young; Kim, Seul Gi; Cho, Eun-Jung

2017-10-07

Menin, encoded by the multiple endocrine neoplasia type 1 (MEN1) gene, is a tumor suppressor and transcription regulator. Menin interacts with various proteins as a scaffold protein and is proposed to play important roles in multiple physiological and pathological processes by controlling gene expression, proliferation, and apoptosis. The mechanisms underlying menin's suppression of tumorigenesis are largely elusive. In this study, we showed that menin was essential for the regulation of canonical Wnt/β-catenin signaling in cultured cells. The C-terminal domain of menin was able to directly interact with and promote ubiquitin-mediated degradation of β-catenin. We further revealed that overexpression of menin down-regulated the transcriptional activity of β-catenin and target gene expression. Moreover, menin efficiently inhibited β-catenin protein levels, transcriptional activity, and proliferation of human renal carcinoma cells with an activated β-catenin pathway. Taken together, our results provide novel molecular insights into the tumor suppressor activity of menin, which is partly mediated by proteasomal degradation of β-catenin and inhibition of Wnt/β-catenin signaling. Copyright © 2017 Elsevier Inc. All rights reserved.

Examination of Association to Autism of Common Genetic Variation in Genes Related to Dopamine

PubMed Central

Anderson, B.M.; Schnetz-Boutaud, N.; Bartlett, J.; Wright, H.H.; Abramson, R.K.; Cuccaro, M.L.; Gilbert, J.R.; Pericak-Vance, M.A.; Haines, J.L.

2010-01-01

Autism is a severe neurodevelopmental disorder characterized by a triad of complications. Autistic individuals display significant disturbances in language and reciprocal social interactions, combined with repetitive and stereotypic behaviors. Prevalence studies suggest that autism is more common than originally believed, with recent estimates citing a rate of one in 150. Although this genomic approach has yielded multiple suggestive regions, a specific risk locus has yet to be identified and widely confirmed. Because many etiologies have been suggested for this complex syndrome, we hypothesize that one of the difficulties in identifying autism genes is that multiple genetic variants may be required to significantly increase the risk of developing autism. Thus we took the alternative approach of examining 14 prominent dopamine pathway candidate genes for detailed study by genotyping 28 SNPs. Although we did observe a nominally significant association for rs2239535 (p=.008) on chromosome 20, single locus analysis did not reveal any results as significant after correction for multiple comparisons. No significant interaction was identified when Multifactor Dimensionality Reduction (MDR) was employed to test specifically for multilocus effects. Although genome-wide linkage scans in autism have provided support for linkage to various loci along the dopamine pathway, our study does not provide strong evidence of linkage or association to any specific gene or combination of genes within the pathway. These results demonstrate that common genetic variation within the tested genes located within this pathway at most play a minor to moderate role in overall autism pathogenesis. PMID:19360691

Long-Term and Short-Term Evolutionary Impacts of Transposable Elements on Drosophila

PubMed Central

Lee, Yuh Chwen G.; Langley, Charles H.

2012-01-01

Transposable elements (TEs) are considered to be genomic parasites and their interactions with their hosts have been likened to the coevolution between host and other nongenomic, horizontally transferred pathogens. TE families, however, are vertically inherited as integral segments of the nuclear genome. This transmission strategy has been suggested to weaken the selective benefits of host alleles repressing the transposition of specific TE variants. On the other hand, the elevated rates of TE transposition and high incidences of deleterious mutations observed during the rare cases of horizontal transfers of TE families between species could create at least a transient process analogous to the influence of horizontally transmitted pathogens. Here, we formally address this analogy, using empirical and theoretical analysis to specify the mechanism of how host–TE interactions may drive the evolution of host genes. We found that host TE-interacting genes actually have more pervasive evidence of adaptive evolution than immunity genes that interact with nongenomic pathogens in Drosophila. Yet, both our theoretical modeling and empirical observations comparing Drosophila melanogaster populations before and after the horizontal transfer of P elements, which invaded D. melanogaster early last century, demonstrated that horizontally transferred TEs have only a limited influence on host TE-interacting genes. We propose that the more prevalent and constant interaction with multiple vertically transmitted TE families may instead be the main force driving the fast evolution of TE-interacting genes, which is fundamentally different from the gene-for-gene interaction of host–pathogen coevolution. PMID:22997235

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

PubMed Central

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

2015-01-01

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

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

PubMed Central

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. PMID:29049295

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

PubMed

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).

SZDB: A Database for Schizophrenia Genetic Research

PubMed Central

Wu, Yong; Yao, Yong-Gang

2017-01-01

Abstract Schizophrenia (SZ) is a debilitating brain disorder with a complex genetic architecture. Genetic studies, especially recent genome-wide association studies (GWAS), have identified multiple variants (loci) conferring risk to SZ. However, how to efficiently extract meaningful biological information from bulk genetic findings of SZ remains a major challenge. There is a pressing need to integrate multiple layers of data from various sources, eg, genetic findings from GWAS, copy number variations (CNVs), association and linkage studies, gene expression, protein–protein interaction (PPI), co-expression, expression quantitative trait loci (eQTL), and Encyclopedia of DNA Elements (ENCODE) data, to provide a comprehensive resource to facilitate the translation of genetic findings into SZ molecular diagnosis and mechanism study. Here we developed the SZDB database (http://www.szdb.org/), a comprehensive resource for SZ research. SZ genetic data, gene expression data, network-based data, brain eQTL data, and SNP function annotation information were systematically extracted, curated and deposited in SZDB. In-depth analyses and systematic integration were performed to identify top prioritized SZ genes and enriched pathways. Multiple types of data from various layers of SZ research were systematically integrated and deposited in SZDB. In-depth data analyses and integration identified top prioritized SZ genes and enriched pathways. We further showed that genes implicated in SZ are highly co-expressed in human brain and proteins encoded by the prioritized SZ risk genes are significantly interacted. The user-friendly SZDB provides high-confidence candidate variants and genes for further functional characterization. More important, SZDB provides convenient online tools for data search and browse, data integration, and customized data analyses. PMID:27451428

Genome-Wide Analysis of Gene-Gene and Gene-Environment Interactions Using Closed-Form Wald Tests.

PubMed

Yu, Zhaoxia; Demetriou, Michael; Gillen, Daniel L

2015-09-01

Despite the successful discovery of hundreds of variants for complex human traits using genome-wide association studies, the degree to which genes and environmental risk factors jointly affect disease risk is largely unknown. One obstacle toward this goal is that the computational effort required for testing gene-gene and gene-environment interactions is enormous. As a result, numerous computationally efficient tests were recently proposed. However, the validity of these methods often relies on unrealistic assumptions such as additive main effects, main effects at only one variable, no linkage disequilibrium between the two single-nucleotide polymorphisms (SNPs) in a pair or gene-environment independence. Here, we derive closed-form and consistent estimates for interaction parameters and propose to use Wald tests for testing interactions. The Wald tests are asymptotically equivalent to the likelihood ratio tests (LRTs), largely considered to be the gold standard tests but generally too computationally demanding for genome-wide interaction analysis. Simulation studies show that the proposed Wald tests have very similar performances with the LRTs but are much more computationally efficient. Applying the proposed tests to a genome-wide study of multiple sclerosis, we identify interactions within the major histocompatibility complex region. In this application, we find that (1) focusing on pairs where both SNPs are marginally significant leads to more significant interactions when compared to focusing on pairs where at least one SNP is marginally significant; and (2) parsimonious parameterization of interaction effects might decrease, rather than increase, statistical power. © 2015 WILEY PERIODICALS, INC.

Genome-wide gene phylogeny of CIPK family in cassava and expression analysis of partial drought-induced genes

PubMed Central

Hu, Wei; Xia, Zhiqiang; Yan, Yan; Ding, Zehong; Tie, Weiwei; Wang, Lianzhe; Zou, Meiling; Wei, Yunxie; Lu, Cheng; Hou, Xiaowan; Wang, Wenquan; Peng, Ming

2015-01-01

Cassava is an important food and potential biofuel crop that is tolerant to multiple abiotic stressors. The mechanisms underlying these tolerances are currently less known. CBL-interacting protein kinases (CIPKs) have been shown to play crucial roles in plant developmental processes, hormone signaling transduction, and in the response to abiotic stress. However, no data is currently available about the CPK family in cassava. In this study, a total of 25 CIPK genes were identified from cassava genome based on our previous genome sequencing data. Phylogenetic analysis suggested that 25 MeCIPKs could be classified into four subfamilies, which was supported by exon-intron organizations and the architectures of conserved protein motifs. Transcriptomic analysis of a wild subspecies and two cultivated varieties showed that most MeCIPKs had different expression patterns between wild subspecies and cultivatars in different tissues or in response to drought stress. Some orthologous genes involved in CIPK interaction networks were identified between Arabidopsis and cassava. The interaction networks and co-expression patterns of these orthologous genes revealed that the crucial pathways controlled by CIPK networks may be involved in the differential response to drought stress in different accessions of cassava. Nine MeCIPK genes were selected to investigate their transcriptional response to various stimuli and the results showed the comprehensive response of the tested MeCIPK genes to osmotic, salt, cold, oxidative stressors, and ABA signaling. The identification and expression analysis of CIPK family suggested that CIPK genes are important components of development and multiple signal transduction pathways in cassava. The findings of this study will help lay a foundation for the functional characterization of the CIPK gene family and provide an improved understanding of abiotic stress responses and signaling transduction in cassava. PMID:26579161

LNDriver: identifying driver genes by integrating mutation and expression data based on gene-gene interaction network.

PubMed

Wei, Pi-Jing; Zhang, Di; Xia, Junfeng; Zheng, Chun-Hou

2016-12-23

Cancer is a complex disease which is characterized by the accumulation of genetic alterations during the patient's lifetime. With the development of the next-generation sequencing technology, multiple omics data, such as cancer genomic, epigenomic and transcriptomic data etc., can be measured from each individual. Correspondingly, one of the key challenges is to pinpoint functional driver mutations or pathways, which contributes to tumorigenesis, from millions of functional neutral passenger mutations. In this paper, in order to identify driver genes effectively, we applied a generalized additive model to mutation profiles to filter genes with long length and constructed a new gene-gene interaction network. Then we integrated the mutation data and expression data into the gene-gene interaction network. Lastly, greedy algorithm was used to prioritize candidate driver genes from the integrated data. We named the proposed method Length-Net-Driver (LNDriver). Experiments on three TCGA datasets, i.e., head and neck squamous cell carcinoma, kidney renal clear cell carcinoma and thyroid carcinoma, demonstrated that the proposed method was effective. Also, it can identify not only frequently mutated drivers, but also rare candidate driver genes.

Interaction between polymorphisms in aspirin metabolic pathways, regular aspirin use and colorectal cancer risk: A case-control study in unselected white European populations.

PubMed

Sheth, Harsh; Northwood, Emma; Ulrich, Cornelia M; Scherer, Dominique; Elliott, Faye; Barrett, Jennifer H; Forman, David; Wolf, C Roland; Smith, Gillian; Jackson, Michael S; Santibanez-Koref, Mauro; Haile, Robert; Casey, Graham; Jenkins, Mark; Win, Aung Ko; Hopper, John L; Marchand, Loic Le; Lindor, Noralane M; Thibodeau, Stephen N; Potter, John D; Burn, John; Bishop, D Timothy

2018-01-01

Regular aspirin use is associated with reduced risk of colorectal cancer (CRC). Variation in aspirin's chemoprevention efficacy has been attributed to the presence of single nucleotide polymorphisms (SNPs). We conducted a meta-analysis using two large population-based case-control datasets, the UK-Leeds Colorectal Cancer Study Group and the NIH-Colon Cancer Family Registry, having a combined total of 3325 cases and 2262 controls. The aim was to assess 42 candidate SNPs in 15 genes whose association with colorectal cancer risk was putatively modified by aspirin use, in the literature. Log odds ratios (ORs) and standard errors were estimated for each dataset separately using logistic regression adjusting for age, sex and study site, and dataset-specific results were combined using random effects meta-analysis. Meta-analysis showed association between SNPs rs6983267, rs11694911 and rs2302615 with CRC risk reduction (All P<0.05). Association for SNP rs6983267 in the CCAT2 gene only was noteworthy after multiple test correction (P = 0.001). Site-specific analysis showed association between SNPs rs1799853 and rs2302615 with reduced colon cancer risk only (P = 0.01 and P = 0.004, respectively), however neither reached significance threshold following multiple test correction. Meta-analysis of SNPs rs2070959 and rs1105879 in UGT1A6 gene showed interaction between aspirin use and CRC risk (Pinteraction = 0.01 and 0.02, respectively); stratification by aspirin use showed an association for decreased CRC risk for aspirin users having a wild-type genotype (rs2070959 OR = 0.77, 95% CI = 0.68-0.86; rs1105879 OR = 0.77 95% CI = 0.69-0.86) compared to variant allele cariers. The direction of the interaction however is in contrast to that published in studies on colorectal adenomas. Both SNPs showed potential site-specific interaction with aspirin use and colon cancer risk only (Pinteraction = 0.006 and 0.008, respectively), with the direction of association similar to that observed for CRC. Additionally, they showed interaction between any non-steroidal anti-inflammatory drugs (including aspirin) use and CRC risk (Pinteraction = 0.01 for both). All gene x environment (GxE) interactions however were not significant after multiple test correction. Candidate gene investigation indicated no evidence of GxE interaction between genetic variants in genes involved in aspirin pathways, regular aspirin use and colorectal cancer risk.

Interaction between polymorphisms in aspirin metabolic pathways, regular aspirin use and colorectal cancer risk: A case-control study in unselected white European populations

PubMed Central

Ulrich, Cornelia M.; Scherer, Dominique; Elliott, Faye; Barrett, Jennifer H.; Forman, David; Wolf, C. Roland; Smith, Gillian; Jackson, Michael S.; Santibanez-Koref, Mauro; Haile, Robert; Casey, Graham; Jenkins, Mark; Win, Aung Ko; Hopper, John L.; Marchand, Loic Le; Lindor, Noralane M.; Thibodeau, Stephen N.; Potter, John D.; Burn, John; Bishop, D. Timothy

2018-01-01

Regular aspirin use is associated with reduced risk of colorectal cancer (CRC). Variation in aspirin’s chemoprevention efficacy has been attributed to the presence of single nucleotide polymorphisms (SNPs). We conducted a meta-analysis using two large population-based case-control datasets, the UK-Leeds Colorectal Cancer Study Group and the NIH-Colon Cancer Family Registry, having a combined total of 3325 cases and 2262 controls. The aim was to assess 42 candidate SNPs in 15 genes whose association with colorectal cancer risk was putatively modified by aspirin use, in the literature. Log odds ratios (ORs) and standard errors were estimated for each dataset separately using logistic regression adjusting for age, sex and study site, and dataset-specific results were combined using random effects meta-analysis. Meta-analysis showed association between SNPs rs6983267, rs11694911 and rs2302615 with CRC risk reduction (All P<0.05). Association for SNP rs6983267 in the CCAT2 gene only was noteworthy after multiple test correction (P = 0.001). Site-specific analysis showed association between SNPs rs1799853 and rs2302615 with reduced colon cancer risk only (P = 0.01 and P = 0.004, respectively), however neither reached significance threshold following multiple test correction. Meta-analysis of SNPs rs2070959 and rs1105879 in UGT1A6 gene showed interaction between aspirin use and CRC risk (Pinteraction = 0.01 and 0.02, respectively); stratification by aspirin use showed an association for decreased CRC risk for aspirin users having a wild-type genotype (rs2070959 OR = 0.77, 95% CI = 0.68–0.86; rs1105879 OR = 0.77 95% CI = 0.69–0.86) compared to variant allele cariers. The direction of the interaction however is in contrast to that published in studies on colorectal adenomas. Both SNPs showed potential site-specific interaction with aspirin use and colon cancer risk only (Pinteraction = 0.006 and 0.008, respectively), with the direction of association similar to that observed for CRC. Additionally, they showed interaction between any non-steroidal anti-inflammatory drugs (including aspirin) use and CRC risk (Pinteraction = 0.01 for both). All gene x environment (GxE) interactions however were not significant after multiple test correction. Candidate gene investigation indicated no evidence of GxE interaction between genetic variants in genes involved in aspirin pathways, regular aspirin use and colorectal cancer risk. PMID:29425227

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

PubMed Central

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

2014-01-01

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. PMID:25396097

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

PubMed

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.

Plasticity of genetic interactions in metabolic networks of yeast.

PubMed

Harrison, Richard; Papp, Balázs; Pál, Csaba; Oliver, Stephen G; Delneri, Daniela

2007-02-13

Why are most genes dispensable? The impact of gene deletions may depend on the environment (plasticity), the presence of compensatory mechanisms (mutational robustness), or both. Here, we analyze the interaction between these two forces by exploring the condition-dependence of synthetic genetic interactions that define redundant functions and alternative pathways. We performed systems-level flux balance analysis of the yeast (Saccharomyces cerevisiae) metabolic network to identify genetic interactions and then tested the model's predictions with in vivo gene-deletion studies. We found that the majority of synthetic genetic interactions are restricted to certain environmental conditions, partly because of the lack of compensation under some (but not all) nutrient conditions. Moreover, the phylogenetic cooccurrence of synthetically interacting pairs is not significantly different from random expectation. These findings suggest that these gene pairs have at least partially independent functions, and, hence, compensation is only a byproduct of their evolutionary history. Experimental analyses that used multiple gene deletion strains not only confirmed predictions of the model but also showed that investigation of false predictions may both improve functional annotation within the model and also lead to the discovery of higher-order genetic interactions. Our work supports the view that functional redundancy may be more apparent than real, and it offers a unified framework for the evolution of environmental adaptation and mutational robustness.

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

PubMed

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

2018-01-01

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

TimeXNet Web: Identifying cellular response networks from diverse omics time-course data.

PubMed

Tan, Phit Ling; López, Yosvany; Nakai, Kenta; Patil, Ashwini

2018-05-14

Condition-specific time-course omics profiles are frequently used to study cellular response to stimuli and identify associated signaling pathways. However, few online tools allow users to analyze multiple types of high-throughput time-course data. TimeXNet Web is a web server that extracts a time-dependent gene/protein response network from time-course transcriptomic, proteomic or phospho-proteomic data, and an input interaction network. It classifies the given genes/proteins into time-dependent groups based on the time of their highest activity and identifies the most probable paths connecting genes/proteins in consecutive groups. The response sub-network is enriched in activated genes/proteins and contains novel regulators that do not show any observable change in the input data. Users can view the resultant response network and analyze it for functional enrichment. TimeXNet Web supports the analysis of high-throughput data from multiple species by providing high quality, weighted protein-protein interaction networks for 12 model organisms. http://txnet.hgc.jp/. ashwini@hgc.jp. Supplementary data are available at Bioinformatics online.

COMPUTING THERAPY FOR PRECISION MEDICINE: COLLABORATIVE FILTERING INTEGRATES AND PREDICTS MULTI-ENTITY INTERACTIONS.

PubMed

Regenbogen, Sam; Wilkins, Angela D; Lichtarge, Olivier

2016-01-01

Biomedicine produces copious information it cannot fully exploit. Specifically, there is considerable need to integrate knowledge from disparate studies to discover connections across domains. Here, we used a Collaborative Filtering approach, inspired by online recommendation algorithms, in which non-negative matrix factorization (NMF) predicts interactions among chemicals, genes, and diseases only from pairwise information about their interactions. Our approach, applied to matrices derived from the Comparative Toxicogenomics Database, successfully recovered Chemical-Disease, Chemical-Gene, and Disease-Gene networks in 10-fold cross-validation experiments. Additionally, we could predict each of these interaction matrices from the other two. Integrating all three CTD interaction matrices with NMF led to good predictions of STRING, an independent, external network of protein-protein interactions. Finally, this approach could integrate the CTD and STRING interaction data to improve Chemical-Gene cross-validation performance significantly, and, in a time-stamped study, it predicted information added to CTD after a given date, using only data prior to that date. We conclude that collaborative filtering can integrate information across multiple types of biological entities, and that as a first step towards precision medicine it can compute drug repurposing hypotheses.

COMPUTING THERAPY FOR PRECISION MEDICINE: COLLABORATIVE FILTERING INTEGRATES AND PREDICTS MULTI-ENTITY INTERACTIONS

PubMed Central

REGENBOGEN, SAM; WILKINS, ANGELA D.; LICHTARGE, OLIVIER

2015-01-01

Biomedicine produces copious information it cannot fully exploit. Specifically, there is considerable need to integrate knowledge from disparate studies to discover connections across domains. Here, we used a Collaborative Filtering approach, inspired by online recommendation algorithms, in which non-negative matrix factorization (NMF) predicts interactions among chemicals, genes, and diseases only from pairwise information about their interactions. Our approach, applied to matrices derived from the Comparative Toxicogenomics Database, successfully recovered Chemical-Disease, Chemical-Gene, and Disease-Gene networks in 10-fold cross-validation experiments. Additionally, we could predict each of these interaction matrices from the other two. Integrating all three CTD interaction matrices with NMF led to good predictions of STRING, an independent, external network of protein-protein interactions. Finally, this approach could integrate the CTD and STRING interaction data to improve Chemical-Gene cross-validation performance significantly, and, in a time-stamped study, it predicted information added to CTD after a given date, using only data prior to that date. We conclude that collaborative filtering can integrate information across multiple types of biological entities, and that as a first step towards precision medicine it can compute drug repurposing hypotheses. PMID:26776170

Multiple interactions amongst floral homeotic MADS box proteins.

PubMed Central

Davies, B; Egea-Cortines, M; de Andrade Silva, E; Saedler, H; Sommer, H

1996-01-01

Most known floral homeotic genes belong to the MADS box family and their products act in combination to specify floral organ identity by an unknown mechanism. We have used a yeast two-hybrid system to investigate the network of interactions between the Antirrhinum organ identity gene products. Selective heterodimerization is observed between MADS box factors. Exclusive interactions are detected between two factors, DEFICIENS (DEF) and GLOBOSA (GLO), previously known to heterodimerize and control development of petals and stamens. In contrast, a third factor, PLENA (PLE), which is required for reproductive organ development, can interact with the products of MADS box genes expressed at early, intermediate and late stages. We also demonstrate that heterodimerization of DEF and GLO requires the K box, a domain not found in non-plant MADS box factors, indicating that the plant MADS box factors may have different criteria for interaction. The association of PLENA and the temporally intermediate MADS box factors suggests that part of their function in mediating between the meristem and organ identity genes is accomplished through direct interaction. These data reveal an unexpectedly complex network of interactions between the factors controlling flower development and have implications for the determination of organ identity. Images PMID:8861961

Transcriptome analysis reveals the same 17 S-locus F-box genes in two haplotypes of the self-incompatibility locus of Petunia inflata.

PubMed

Williams, Justin S; Der, Joshua P; dePamphilis, Claude W; Kao, Teh-Hui

2014-07-01

Petunia possesses self-incompatibility, by which pistils reject self-pollen but accept non-self-pollen for fertilization. Self-/non-self-recognition between pollen and pistil is regulated by the pistil-specific S-RNase gene and by multiple pollen-specific S-locus F-box (SLF) genes. To date, 10 SLF genes have been identified by various methods, and seven have been shown to be involved in pollen specificity. For a given S-haplotype, each SLF interacts with a subset of its non-self S-RNases, and an as yet unknown number of SLFs are thought to collectively mediate ubiquitination and degradation of all non-self S-RNases to allow cross-compatible pollination. To identify a complete suite of SLF genes of P. inflata, we used a de novo RNA-seq approach to analyze the pollen transcriptomes of S2-haplotype and S3-haplotype, as well as the leaf transcriptome of the S3S3 genotype. We searched for genes that fit several criteria established from the properties of the known SLF genes and identified the same seven new SLF genes in S2-haplotype and S3-haplotype, suggesting that a total of 17 SLF genes constitute pollen specificity in each S-haplotype. This finding lays the foundation for understanding how multiple SLF genes evolved and the biochemical basis for differential interactions between SLF proteins and S-RNases. © 2014 American Society of Plant Biologists. All rights reserved.

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

PubMed

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.

Exon expression in lymphoblastoid cell lines from subjects with schizophrenia before and after glucose deprivation

PubMed Central

Martin, Maureen V; Rollins, Brandi; Sequeira, P Adolfo; Mesén, Andrea; Byerley, William; Stein, Richard; Moon, Emily A; Akil, Huda; Jones, Edward G; Watson, Stanley J; Barchas, Jack; DeLisi, Lynn E; Myers, Richard M; Schatzberg, Alan; Bunney, William E; Vawter, Marquis P

2009-01-01

Background The purpose of this study was to examine the effects of glucose reduction stress on lymphoblastic cell line (LCL) gene expression in subjects with schizophrenia compared to non-psychotic relatives. Methods LCLs were grown under two glucose conditions to measure the effects of glucose reduction stress on exon expression in subjects with schizophrenia compared to unaffected family member controls. A second aim of this project was to identify cis-regulated transcripts associated with diagnosis. Results There were a total of 122 transcripts with significant diagnosis by probeset interaction effects and 328 transcripts with glucose deprivation by probeset interaction probeset effects after corrections for multiple comparisons. There were 8 transcripts with expression significantly affected by the interaction between diagnosis and glucose deprivation and probeset after correction for multiple comparisons. The overall validation rate by qPCR of 13 diagnosis effect genes identified through microarray was 62%, and all genes tested by qPCR showed concordant up- or down-regulation by qPCR and microarray. We assessed brain gene expression of five genes found to be altered by diagnosis and glucose deprivation in LCLs and found a significant decrease in expression of one gene, glutaminase, in the dorsolateral prefrontal cortex (DLPFC). One SNP with previously identified regulation by a 3' UTR SNP was found to influence IRF5 expression in both brain and lymphocytes. The relationship between the 3' UTR rs10954213 genotype and IRF5 expression was significant in LCLs (p = 0.0001), DLPFC (p = 0.007), and anterior cingulate cortex (p = 0.002). Conclusion Experimental manipulation of cells lines from subjects with schizophrenia may be a useful approach to explore stress related gene expression alterations in schizophrenia and to identify SNP variants associated with gene expression. PMID:19772658

Identification of type 2 diabetes-associated combination of SNPs using support vector machine.

PubMed

Ban, Hyo-Jeong; Heo, Jee Yeon; Oh, Kyung-Soo; Park, Keun-Joon

2010-04-23

Type 2 diabetes mellitus (T2D), a metabolic disorder characterized by insulin resistance and relative insulin deficiency, is a complex disease of major public health importance. Its incidence is rapidly increasing in the developed countries. Complex diseases are caused by interactions between multiple genes and environmental factors. Most association studies aim to identify individual susceptibility single markers using a simple disease model. Recent studies are trying to estimate the effects of multiple genes and multi-locus in genome-wide association. However, estimating the effects of association is very difficult. We aim to assess the rules for classifying diseased and normal subjects by evaluating potential gene-gene interactions in the same or distinct biological pathways. We analyzed the importance of gene-gene interactions in T2D susceptibility by investigating 408 single nucleotide polymorphisms (SNPs) in 87 genes involved in major T2D-related pathways in 462 T2D patients and 456 healthy controls from the Korean cohort studies. We evaluated the support vector machine (SVM) method to differentiate between cases and controls using SNP information in a 10-fold cross-validation test. We achieved a 65.3% prediction rate with a combination of 14 SNPs in 12 genes by using the radial basis function (RBF)-kernel SVM. Similarly, we investigated subpopulation data sets of men and women and identified different SNP combinations with the prediction rates of 70.9% and 70.6%, respectively. As the high-throughput technology for genome-wide SNPs improves, it is likely that a much higher prediction rate with biologically more interesting combination of SNPs can be acquired by using this method. Support Vector Machine based feature selection method in this research found novel association between combinations of SNPs and T2D in a Korean population.

Integrative analysis for identification of shared markers from various functional cells/tissues for rheumatoid arthritis.

PubMed

Xia, Wei; Wu, Jian; Deng, Fei-Yan; Wu, Long-Fei; Zhang, Yong-Hong; Guo, Yu-Fan; Lei, Shu-Feng

2017-02-01

Rheumatoid arthritis (RA) is a systemic autoimmune disease. So far, it is unclear whether there exist common RA-related genes shared in different tissues/cells. In this study, we conducted an integrative analysis on multiple datasets to identify potential shared genes that are significant in multiple tissues/cells for RA. Seven microarray gene expression datasets representing various RA-related tissues/cells were downloaded from the Gene Expression Omnibus (GEO). Statistical analyses, testing both marginal and joint effects, were conducted to identify significant genes shared in various samples. Followed-up analyses were conducted on functional annotation clustering analysis, protein-protein interaction (PPI) analysis, gene-based association analysis, and ELISA validation analysis in in-house samples. We identified 18 shared significant genes, which were mainly involved in the immune response and chemokine signaling pathway. Among the 18 genes, eight genes (PPBP, PF4, HLA-F, S100A8, RNASEH2A, P2RY6, JAG2, and PCBP1) interact with known RA genes. Two genes (HLA-F and PCBP1) are significant in gene-based association analysis (P = 1.03E-31, P = 1.30E-2, respectively). Additionally, PCBP1 also showed differential protein expression levels in in-house case-control plasma samples (P = 2.60E-2). This study represented the first effort to identify shared RA markers from different functional cells or tissues. The results suggested that one of the shared genes, i.e., PCBP1, is a promising biomarker for RA.

Improving the measurement of semantic similarity by combining gene ontology and co-functional network: a random walk based approach.

PubMed

Peng, Jiajie; Zhang, Xuanshuo; Hui, Weiwei; Lu, Junya; Li, Qianqian; Liu, Shuhui; Shang, Xuequn

2018-03-19

Gene Ontology (GO) is one of the most popular bioinformatics resources. In the past decade, Gene Ontology-based gene semantic similarity has been effectively used to model gene-to-gene interactions in multiple research areas. However, most existing semantic similarity approaches rely only on GO annotations and structure, or incorporate only local interactions in the co-functional network. This may lead to inaccurate GO-based similarity resulting from the incomplete GO topology structure and gene annotations. We present NETSIM2, a new network-based method that allows researchers to measure GO-based gene functional similarities by considering the global structure of the co-functional network with a random walk with restart (RWR)-based method, and by selecting the significant term pairs to decrease the noise information. Based on the EC number (Enzyme Commission)-based groups of yeast and Arabidopsis, evaluation test shows that NETSIM2 can enhance the accuracy of Gene Ontology-based gene functional similarity. Using NETSIM2 as an example, we found that the accuracy of semantic similarities can be significantly improved after effectively incorporating the global gene-to-gene interactions in the co-functional network, especially on the species that gene annotations in GO are far from complete.

An in vivo and in silico approach to study cis-antisense: a short cut to higher order response

NASA Astrophysics Data System (ADS)

Courtney, Colleen; Varanasi, Usha; Chatterjee, Anushree

2014-03-01

Antisense interactions are present in all domains of life. Typically sense, antisense RNA pairs originate from overlapping genes with convergent face to face promoters, and are speculated to be involved in gene regulation. Recent studies indicate the role of transcriptional interference (TI) in regulating expression of genes in convergent orientation. Modeling antisense, TI gene regulation mechanisms allows us to understand how organisms control gene expression. We present a modeling and experimental framework to understand convergent transcription that combines the effects of transcriptional interference and cis-antisense regulation. Our model shows that combining transcriptional interference and antisense RNA interaction adds multiple-levels of regulation which affords a highly tunable biological output, ranging from first order response to complex higher-order response. To study this system we created a library of experimental constructs with engineered TI and antisense interaction by using face-to-face inducible promoters separated by carefully tailored overlapping DNA sequences to control expression of a set of fluorescent reporter proteins. Studying this gene expression mechanism allows for an understanding of higher order behavior of gene expression networks.

Multiple levels of redundant processes inhibit Caenorhabditis elegans vulval cell fates.

PubMed

Andersen, Erik C; Saffer, Adam M; Horvitz, H Robert

2008-08-01

Many mutations cause obvious abnormalities only when combined with other mutations. Such synthetic interactions can be the result of redundant gene functions. In Caenorhabditis elegans, the synthetic multivulva (synMuv) genes have been grouped into multiple classes that redundantly inhibit vulval cell fates. Animals with one or more mutations of the same class undergo wild-type vulval development, whereas animals with mutations of any two classes have a multivulva phenotype. By varying temperature and genetic background, we determined that mutations in most synMuv genes within a single synMuv class enhance each other. However, in a few cases no enhancement was observed. For example, mutations that affect an Mi2 homolog and a histone methyltransferase are of the same class and do not show enhancement. We suggest that such sets of genes function together in vivo and in at least some cases encode proteins that interact physically. The approach of genetic enhancement can be applied more broadly to identify potential protein complexes as well as redundant processes or pathways. Many synMuv genes are evolutionarily conserved, and the genetic relationships we have identified might define the functions not only of synMuv genes in C. elegans but also of their homologs in other organisms.

Multiple Levels of Redundant Processes Inhibit Caenorhabditis elegans Vulval Cell Fates

PubMed Central

Andersen, Erik C.; Saffer, Adam M.; Horvitz, H. Robert

2008-01-01

Many mutations cause obvious abnormalities only when combined with other mutations. Such synthetic interactions can be the result of redundant gene functions. In Caenorhabditis elegans, the synthetic multivulva (synMuv) genes have been grouped into multiple classes that redundantly inhibit vulval cell fates. Animals with one or more mutations of the same class undergo wild-type vulval development, whereas animals with mutations of any two classes have a multivulva phenotype. By varying temperature and genetic background, we determined that mutations in most synMuv genes within a single synMuv class enhance each other. However, in a few cases no enhancement was observed. For example, mutations that affect an Mi2 homolog and a histone methyltransferase are of the same class and do not show enhancement. We suggest that such sets of genes function together in vivo and in at least some cases encode proteins that interact physically. The approach of genetic enhancement can be applied more broadly to identify potential protein complexes as well as redundant processes or pathways. Many synMuv genes are evolutionarily conserved, and the genetic relationships we have identified might define the functions not only of synMuv genes in C. elegans but also of their homologs in other organisms. PMID:18689876

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

PubMed Central

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

2009-01-01

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

A distinct and replicable variant of the squamous cell carcinoma gene inositol polyphosphate-5-phosphatase modifies the susceptibility of arsenic-associated skin lesions in Bangladesh.

PubMed

Seow, Wei Jie; Pan, Wen-Chi; Kile, Molly L; Tong, Lin; Baccarelli, Andrea A; Quamruzzaman, Quazi; Rahman, Mahmuder; Mostofa, Golam; Rakibuz-Zaman, Muhammad; Kibriya, Muhammad; Ahsan, Habibul; Lin, Xihong; Christiani, David C

2015-07-01

Single-nucleotide polymorphisms (SNPs) in inflammation, one-carbon metabolism, and skin cancer genes might influence susceptibility to arsenic-induced skin lesions. A case-control study was conducted in Pabna, Bangladesh (2001-2003), and the drinking-water arsenic concentration was measured for each participant. A panel of 25 candidate SNPs was analyzed in 540 cases and 400 controls. Logistic regression was used to estimate the association between each SNP and the potential for gene-environment interactions in the skin lesion risk, with adjustments for relevant covariates. Replication testing was conducted in an independent Bangladesh population with 488 cases and 2,794 controls. In the discovery population, genetic variants in the one-carbon metabolism genes phosphatidylethanolamine N-methyltransferase (rs2278952, P for interaction  = .004; rs897453, P for interaction = .05) and dihydrofolate reductase (rs1650697, P for interaction = .02), the inflammation gene interleukin 10 (rs3024496, P for interaction =.04), and the skin cancer genes inositol polyphosphate-5-phosphatase (INPP5A; rs1133400, P for interaction = .03) and xeroderma pigmentosum complementation group C (rs2228000, P for interaction = .01) significantly modified the association between arsenic and skin lesions after adjustments for multiple comparisons. The significant gene-environment interaction between a SNP in the INPP5A gene (rs1133400) and water arsenic with respect to the skin lesion risk was successfully replicated in an independent population (P for interaction = .03). Minor allele carriers of the skin cancer gene INPP5A modified the odds of arsenic-induced skin lesions in both main and replicative populations. Genetic variation in INPP5A appears to have a role in susceptibility to arsenic toxicity. © 2015 American Cancer Society.

A Comprehensive Analysis of Nuclear-Encoded Mitochondrial Genes in Schizophrenia.

PubMed

Gonçalves, Vanessa F; Cappi, Carolina; Hagen, Christian M; Sequeira, Adolfo; Vawter, Marquis P; Derkach, Andriy; Zai, Clement C; Hedley, Paula L; Bybjerg-Grauholm, Jonas; Pouget, Jennie G; Cuperfain, Ari B; Sullivan, Patrick F; Christiansen, Michael; Kennedy, James L; Sun, Lei

2018-05-01

The genetic risk factors of schizophrenia (SCZ), a severe psychiatric disorder, are not yet fully understood. Multiple lines of evidence suggest that mitochondrial dysfunction may play a role in SCZ, but comprehensive association studies are lacking. We hypothesized that variants in nuclear-encoded mitochondrial genes influence susceptibility to SCZ. We conducted gene-based and gene-set analyses using summary association results from the Psychiatric Genomics Consortium Schizophrenia Phase 2 (PGC-SCZ2) genome-wide association study comprising 35,476 cases and 46,839 control subjects. We applied the MAGMA method to three sets of nuclear-encoded mitochondrial genes: oxidative phosphorylation genes, other nuclear-encoded mitochondrial genes, and genes involved in nucleus-mitochondria crosstalk. Furthermore, we conducted a replication study using the iPSYCH SCZ sample of 2290 cases and 21,621 control subjects. In the PGC-SCZ2 sample, 1186 mitochondrial genes were analyzed, among which 159 had p values < .05 and 19 remained significant after multiple testing correction. A meta-analysis of 818 genes combining the PGC-SCZ2 and iPSYCH samples resulted in 104 nominally significant and nine significant genes, suggesting a polygenic model for the nuclear-encoded mitochondrial genes. Gene-set analysis, however, did not show significant results. In an in silico protein-protein interaction network analysis, 14 mitochondrial genes interacted directly with 158 SCZ risk genes identified in PGC-SCZ2 (permutation p = .02), and aldosterone signaling in epithelial cells and mitochondrial dysfunction pathways appeared to be overrepresented in this network of mitochondrial and SCZ risk genes. This study provides evidence that specific aspects of mitochondrial function may play a role in SCZ, but we did not observe its broad involvement even using a large sample. Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

The heritable basis of gene-environment interactions in cardiometabolic traits.

PubMed

Poveda, Alaitz; Chen, Yan; Brändström, Anders; Engberg, Elisabeth; Hallmans, Göran; Johansson, Ingegerd; Renström, Frida; Kurbasic, Azra; Franks, Paul W

2017-03-01

Little is known about the heritable basis of gene-environment interactions in humans. We therefore screened multiple cardiometabolic traits to assess the probability that they are influenced by genotype-environment interactions. Fourteen established environmental risk exposures and 11 cardiometabolic traits were analysed in the VIKING study, a cohort of 16,430 Swedish adults from 1682 extended pedigrees with available detailed genealogical, phenotypic and demographic information, using a maximum likelihood variance decomposition method in Sequential Oligogenic Linkage Analysis Routines software. All cardiometabolic traits had statistically significant heritability estimates, with narrow-sense heritabilities (h 2 ) ranging from 24% to 47%. Genotype-environment interactions were detected for age and sex (for the majority of traits), physical activity (for triacylglycerols, 2 h glucose and diastolic BP), smoking (for weight), alcohol intake (for weight, BMI and 2 h glucose) and diet pattern (for weight, BMI, glycaemic traits and systolic BP). Genotype-age interactions for weight and systolic BP, genotype-sex interactions for BMI and triacylglycerols and genotype-alcohol intake interactions for weight remained significant after multiple test correction. Age, sex and alcohol intake are likely to be major modifiers of genetic effects for a range of cardiometabolic traits. This information may prove valuable for studies that seek to identify specific loci that modify the effects of lifestyle in cardiometabolic disease.

Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries

PubMed Central

Guo, Xiuqing; Franceschini, Nora; Cheng, Ching-Yu; Sim, Xueling; Vojinovic, Dina; Marten, Jonathan; Musani, Solomon K.; Li, Changwei; Schwander, Karen; Richard, Melissa A.; Noordam, Raymond; Aschard, Hugues; Bartz, Traci M.; Bielak, Lawrence F.; Dorajoo, Rajkumar; Fisher, Virginia; Hartwig, Fernando P.; Horimoto, Andrea R. V. R.; Lohman, Kurt K.; Manning, Alisa K.; Rankinen, Tuomo; Smith, Albert V.; Wojczynski, Mary K.; Alver, Maris; Boissel, Mathilde; Cai, Qiuyin; Divers, Jasmin; Gao, Chuan; Goel, Anuj; Harris, Sarah E.; He, Meian; Hsu, Fang-Chi; Jackson, Anne U.; Kähönen, Mika; Kasturiratne, Anuradhani; Komulainen, Pirjo; Kühnel, Brigitte; Laguzzi, Federica; Luan, Jian'an; Nolte, Ilja M.; Padmanabhan, Sandosh; Robino, Antonietta; Scott, Robert A.; Sofer, Tamar; Stančáková, Alena; Takeuchi, Fumihiko; Tayo, Bamidele O.; Varga, Tibor V.; Vitart, Veronique; Wang, Yajuan; Warren, Helen R.; Wen, Wanqing; Yanek, Lisa R.; Zhang, Weihua; Zhao, Jing Hua; Afaq, Saima; Amin, Najaf; Arking, Dan E.; Aung, Tin; Boerwinkle, Eric; Borecki, Ingrid; Broeckel, Ulrich; Brown, Morris; Brumat, Marco; Burke, Gregory L.; Chakravarti, Aravinda; Charumathi, Sabanayagam; Ida Chen, Yii-Der; Connell, John M.; Correa, Adolfo; de las Fuentes, Lisa; de Mutsert, Renée; de Silva, H. Janaka; Deng, Xuan; Ding, Jingzhong; Duan, Qing; Eaton, Charles B.; Ehret, Georg; Eppinga, Ruben N.; Faul, Jessica D.; Felix, Stephan B.; Forouhi, Nita G.; Forrester, Terrence; Franco, Oscar H.; Friedlander, Yechiel; Gandin, Ilaria; Gao, He; Ghanbari, Mohsen; Gigante, Bruna; Gu, C. Charles; Gu, Dongfeng; Hagenaars, Saskia P.; Hallmans, Göran; Harris, Tamara B.; He, Jiang; Heng, Chew-Kiat; Hirata, Makoto; Howard, Barbara V.; Ikram, M. Arfan; John, Ulrich; Katsuya, Tomohiro; Khor, Chiea Chuen; Kilpeläinen, Tuomas O.; Koh, Woon-Puay; Krieger, José E.; Kritchevsky, Stephen B.; Kubo, Michiaki; Kuusisto, Johanna; Lakka, Timo A.; Langefeld, Carl D.; Langenberg, Claudia; Launer, Lenore J.; Lehne, Benjamin; Lewis, Cora E.; Li, Yize; Lin, Shiow; Liu, Jianjun; Liu, Jingmin; Loh, Marie; Louie, Tin; Mägi, Reedik; McKenzie, Colin A.; Meitinger, Thomas; Milaneschi, Yuri; Milani, Lili; Mohlke, Karen L.; Momozawa, Yukihide; Nalls, Mike A.; Nelson, Christopher P.; Sotoodehnia, Nona; Norris, Jill M.; O'Connell, Jeff R.; Palmer, Nicholette D.; Perls, Thomas; Pedersen, Nancy L.; Peters, Annette; Peyser, Patricia A.; Poulter, Neil; Raffel, Leslie J.; Raitakari, Olli T.; Roll, Kathryn; Rose, Lynda M.; Rosendaal, Frits R.; Rotter, Jerome I.; Schmidt, Carsten O.; Schreiner, Pamela J.; Schupf, Nicole; Scott, William R.; Shi, Yuan; Sidney, Stephen; Sims, Mario; Sitlani, Colleen M.; Smith, Jennifer A.; Snieder, Harold; Starr, John M.; Strauch, Konstantin; Stringham, Heather M.; Tan, Nicholas Y. Q.; Tang, Hua; Taylor, Kent D.; Teo, Yik Ying; Tham, Yih Chung; Turner, Stephen T.; Uitterlinden, André G.; Vollenweider, Peter; Waldenberger, Melanie; Wang, Lihua; Wang, Ya Xing; Wei, Wen Bin; Williams, Christine; Yao, Jie; Yu, Caizheng; Yuan, Jian-Min; Zhao, Wei; Zonderman, Alan B.; Becker, Diane M.; Boehnke, Michael; Bowden, Donald W.; Chambers, John C.; Deary, Ian J.; Esko, Tõnu; Farrall, Martin; Franks, Paul W.; Freedman, Barry I.; Froguel, Philippe; Gasparini, Paolo; Gieger, Christian; Kamatani, Yoichiro; Kato, Norihiro; Kooner, Jaspal S.; Kutalik, Zoltán; Laakso, Markku; Laurie, Cathy C.; Leander, Karin; Lehtimäki, Terho; Study, Lifelines Cohort; Magnusson, Patrik K. E.; Oldehinkel, Albertine J.; Penninx, Brenda W. J. H.; Polasek, Ozren; Porteous, David J.; Rauramaa, Rainer; Samani, Nilesh J.; Scott, James; Shu, Xiao-Ou; van der Harst, Pim; Wagenknecht, Lynne E.; Watkins, Hugh; Weir, David R.; Wickremasinghe, Ananda R.; Wu, Tangchun; Zheng, Wei; Bouchard, Claude; Christensen, Kaare; Evans, Michele K.; Gudnason, Vilmundur; Horta, Bernardo L.; Kardia, Sharon L. R.; Liu, Yongmei; Pereira, Alexandre C.; Psaty, Bruce M.; Ridker, Paul M.; van Dam, Rob M.; Gauderman, W. James; Zhu, Xiaofeng; Mook-Kanamori, Dennis O.; Fornage, Myriam; Rotimi, Charles N.; Cupples, L. Adrienne; Kelly, Tanika N.; Fox, Ervin R.; Hayward, Caroline; van Duijn, Cornelia M.; Tai, E Shyong; Wong, Tien Yin; Kooperberg, Charles; Palmas, Walter; Morrison, Alanna C.; Caulfield, Mark J.; Munroe, Patricia B.; Rao, Dabeeru C.; Province, Michael A.; Levy, Daniel

2018-01-01

Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10−5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10−8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10−8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension. PMID:29912962

Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries.

PubMed

Feitosa, Mary F; Kraja, Aldi T; Chasman, Daniel I; Sung, Yun J; Winkler, Thomas W; Ntalla, Ioanna; Guo, Xiuqing; Franceschini, Nora; Cheng, Ching-Yu; Sim, Xueling; Vojinovic, Dina; Marten, Jonathan; Musani, Solomon K; Li, Changwei; Bentley, Amy R; Brown, Michael R; Schwander, Karen; Richard, Melissa A; Noordam, Raymond; Aschard, Hugues; Bartz, Traci M; Bielak, Lawrence F; Dorajoo, Rajkumar; Fisher, Virginia; Hartwig, Fernando P; Horimoto, Andrea R V R; Lohman, Kurt K; Manning, Alisa K; Rankinen, Tuomo; Smith, Albert V; Tajuddin, Salman M; Wojczynski, Mary K; Alver, Maris; Boissel, Mathilde; Cai, Qiuyin; Campbell, Archie; Chai, Jin Fang; Chen, Xu; Divers, Jasmin; Gao, Chuan; Goel, Anuj; Hagemeijer, Yanick; Harris, Sarah E; He, Meian; Hsu, Fang-Chi; Jackson, Anne U; Kähönen, Mika; Kasturiratne, Anuradhani; Komulainen, Pirjo; Kühnel, Brigitte; Laguzzi, Federica; Luan, Jian'an; Matoba, Nana; Nolte, Ilja M; Padmanabhan, Sandosh; Riaz, Muhammad; Rueedi, Rico; Robino, Antonietta; Said, M Abdullah; Scott, Robert A; Sofer, Tamar; Stančáková, Alena; Takeuchi, Fumihiko; Tayo, Bamidele O; van der Most, Peter J; Varga, Tibor V; Vitart, Veronique; Wang, Yajuan; Ware, Erin B; Warren, Helen R; Weiss, Stefan; Wen, Wanqing; Yanek, Lisa R; Zhang, Weihua; Zhao, Jing Hua; Afaq, Saima; Amin, Najaf; Amini, Marzyeh; Arking, Dan E; Aung, Tin; Boerwinkle, Eric; Borecki, Ingrid; Broeckel, Ulrich; Brown, Morris; Brumat, Marco; Burke, Gregory L; Canouil, Mickaël; Chakravarti, Aravinda; Charumathi, Sabanayagam; Ida Chen, Yii-Der; Connell, John M; Correa, Adolfo; de Las Fuentes, Lisa; de Mutsert, Renée; de Silva, H Janaka; Deng, Xuan; Ding, Jingzhong; Duan, Qing; Eaton, Charles B; Ehret, Georg; Eppinga, Ruben N; Evangelou, Evangelos; Faul, Jessica D; Felix, Stephan B; Forouhi, Nita G; Forrester, Terrence; Franco, Oscar H; Friedlander, Yechiel; Gandin, Ilaria; Gao, He; Ghanbari, Mohsen; Gigante, Bruna; Gu, C Charles; Gu, Dongfeng; Hagenaars, Saskia P; Hallmans, Göran; Harris, Tamara B; He, Jiang; Heikkinen, Sami; Heng, Chew-Kiat; Hirata, Makoto; Howard, Barbara V; Ikram, M Arfan; John, Ulrich; Katsuya, Tomohiro; Khor, Chiea Chuen; Kilpeläinen, Tuomas O; Koh, Woon-Puay; Krieger, José E; Kritchevsky, Stephen B; Kubo, Michiaki; Kuusisto, Johanna; Lakka, Timo A; Langefeld, Carl D; Langenberg, Claudia; Launer, Lenore J; Lehne, Benjamin; Lewis, Cora E; Li, Yize; Lin, Shiow; Liu, Jianjun; Liu, Jingmin; Loh, Marie; Louie, Tin; Mägi, Reedik; McKenzie, Colin A; Meitinger, Thomas; Metspalu, Andres; Milaneschi, Yuri; Milani, Lili; Mohlke, Karen L; Momozawa, Yukihide; Nalls, Mike A; Nelson, Christopher P; Sotoodehnia, Nona; Norris, Jill M; O'Connell, Jeff R; Palmer, Nicholette D; Perls, Thomas; Pedersen, Nancy L; Peters, Annette; Peyser, Patricia A; Poulter, Neil; Raffel, Leslie J; Raitakari, Olli T; Roll, Kathryn; Rose, Lynda M; Rosendaal, Frits R; Rotter, Jerome I; Schmidt, Carsten O; Schreiner, Pamela J; Schupf, Nicole; Scott, William R; Sever, Peter S; Shi, Yuan; Sidney, Stephen; Sims, Mario; Sitlani, Colleen M; Smith, Jennifer A; Snieder, Harold; Starr, John M; Strauch, Konstantin; Stringham, Heather M; Tan, Nicholas Y Q; Tang, Hua; Taylor, Kent D; Teo, Yik Ying; Tham, Yih Chung; Turner, Stephen T; Uitterlinden, André G; Vollenweider, Peter; Waldenberger, Melanie; Wang, Lihua; Wang, Ya Xing; Wei, Wen Bin; Williams, Christine; Yao, Jie; Yu, Caizheng; Yuan, Jian-Min; Zhao, Wei; Zonderman, Alan B; Becker, Diane M; Boehnke, Michael; Bowden, Donald W; Chambers, John C; Deary, Ian J; Esko, Tõnu; Farrall, Martin; Franks, Paul W; Freedman, Barry I; Froguel, Philippe; Gasparini, Paolo; Gieger, Christian; Jonas, Jost Bruno; Kamatani, Yoichiro; Kato, Norihiro; Kooner, Jaspal S; Kutalik, Zoltán; Laakso, Markku; Laurie, Cathy C; Leander, Karin; Lehtimäki, Terho; Study, Lifelines Cohort; Magnusson, Patrik K E; Oldehinkel, Albertine J; Penninx, Brenda W J H; Polasek, Ozren; Porteous, David J; Rauramaa, Rainer; Samani, Nilesh J; Scott, James; Shu, Xiao-Ou; van der Harst, Pim; Wagenknecht, Lynne E; Wareham, Nicholas J; Watkins, Hugh; Weir, David R; Wickremasinghe, Ananda R; Wu, Tangchun; Zheng, Wei; Bouchard, Claude; Christensen, Kaare; Evans, Michele K; Gudnason, Vilmundur; Horta, Bernardo L; Kardia, Sharon L R; Liu, Yongmei; Pereira, Alexandre C; Psaty, Bruce M; Ridker, Paul M; van Dam, Rob M; Gauderman, W James; Zhu, Xiaofeng; Mook-Kanamori, Dennis O; Fornage, Myriam; Rotimi, Charles N; Cupples, L Adrienne; Kelly, Tanika N; Fox, Ervin R; Hayward, Caroline; van Duijn, Cornelia M; Tai, E Shyong; Wong, Tien Yin; Kooperberg, Charles; Palmas, Walter; Rice, Kenneth; Morrison, Alanna C; Elliott, Paul; Caulfield, Mark J; Munroe, Patricia B; Rao, Dabeeru C; Province, Michael A; Levy, Daniel

2018-01-01

Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.

Redox control of protein-DNA interactions: from molecular mechanisms to significance in signal transduction, gene expression, and DNA replication.

PubMed

Shlomai, Joseph

2010-11-01

Protein-DNA interactions play a key role in the regulation of major cellular metabolic pathways, including gene expression, genome replication, and genomic stability. They are mediated through the interactions of regulatory proteins with their specific DNA-binding sites at promoters, enhancers, and replication origins in the genome. Redox signaling regulates these protein-DNA interactions using reactive oxygen species and reactive nitrogen species that interact with cysteine residues at target proteins and their regulators. This review describes the redox-mediated regulation of several master regulators of gene expression that control the induction and suppression of hundreds of genes in the genome, regulating multiple metabolic pathways, which are involved in cell growth, development, differentiation, and survival, as well as in the function of the immune system and cellular response to intracellular and extracellular stimuli. It also discusses the role of redox signaling in protein-DNA interactions that regulate DNA replication. Specificity of redox regulation is discussed, as well as the mechanisms providing several levels of redox-mediated regulation, from direct control of DNA-binding domains through the indirect control, mediated by release of negative regulators, regulation of redox-sensitive protein kinases, intracellular trafficking, and chromatin remodeling.

Genetic interaction of the fusiform rust fungus with resistance gene FR1 in loblolly pine

Treesearch

Thomas L. Kubisiak; Henry V. Amerson; C. Dana Nelson

2005-01-01

We propose a method for defining DNA markers linked to Cronartium quercuum f. sp. fusiforme avirulence (Avr) genes. However, before this method can be successfully employed, a spore competition study was needed to determine the genetic composition of single pycnial drops and multiple drops on single galls when using the standard...

Pseudomonas sax genes overcome aliphatic isothiocyanate-mediated non-host resistance in Arabidopsis

Treesearch

Jun Fan; Casey Crooks; Gary Creissen; Lionel Hill; Shirley Fairhurst; Peter Doerner; Chris Lamb

2011-01-01

Most plant-microbe interactions do not result in disease; natural products restrict non-host pathogens. We found that sulforaphane (4-methylsulfinylbutyl isothiocyanate), a natural product derived from aliphatic glucosinolates, inhibits growth in Arabidopsis of non-host Pseudomonas bacteria in planta. Multiple sax genes (saxCAB/F/D/G) were identified in Pseudomonas...

Investigation of the role of the necrotrophic effector SnTox1 in virulence in the Stagonospora nodorum-wheat interaction

USDA-ARS?s Scientific Manuscript database

Stagonospora nodorum is a necrotrophic specialist that has been shown to secrete multiple necrotrophic effectors that are important in disease induction on wheat. These necrotrophic effectors interact directly or indirectly with dominant susceptibility genes in wheat in a genotype specific manner, ...

Regulation of epidermal cell fate in Arabidopsis roots: the importance of multiple feedback loops

PubMed Central

Schiefelbein, John; Huang, Ling; Zheng, Xiaohua

2014-01-01

The specification of distinct cell types in multicellular organisms is accomplished via establishment of differential gene expression. A major question is the nature of the mechanisms that establish this differential expression in time and space. In plants, the formation of the hair and non-hair cell types in the root epidermis has been used as a model to understand regulation of cell specification. Recent findings show surprising complexity in the number and the types of regulatory interactions between the multiple transcription factor genes/proteins influencing root epidermis cell fate. Here, we describe this regulatory network and the importance of the multiple feedback loops for its establishment and maintenance. PMID:24596575

System-level insights into the cellular interactome of a non-model organism: inferring, modelling and analysing functional gene network of soybean (Glycine max).

PubMed

Xu, Yungang; Guo, Maozu; Zou, Quan; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang

2014-01-01

Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN), a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max), due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs), in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional interactome at the genome and microRNome levels. Additionally, a web tool for information retrieval and analysis of SoyFGNs can be accessed at SoyFN: http://nclab.hit.edu.cn/SoyFN.

System-Level Insights into the Cellular Interactome of a Non-Model Organism: Inferring, Modelling and Analysing Functional Gene Network of Soybean (Glycine max)

PubMed Central

Xu, Yungang; Guo, Maozu; Zou, Quan; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang

2014-01-01

Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN), a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max), due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs), in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional interactome at the genome and microRNome levels. Additionally, a web tool for information retrieval and analysis of SoyFGNs can be accessed at SoyFN: http://nclab.hit.edu.cn/SoyFN. PMID:25423109

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

PubMed

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

2015-09-01

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

Gene-by-Socioeconomic Status Interaction on School Readiness

PubMed Central

Rhemtulla, Mijke; Tucker-Drob, Elliot M.

2017-01-01

In previous work with a nationally representative sample of over 1,400 monozygotic and dizygotic twins born in the United States, Tucker-Drob, Rhemtulla, Harden, Turkheimer, and Fask (2011; Psychological Science, 22, 125–133) uncovered a gene × environment interaction on scores on the Bayley Short Form test of mental ability at 2 years of age—higher socioeconomic status (SES) was associated not only with higher mental ability, but also with larger genetic contributions to individual differences in mental ability. The current study examined gene × SES interactions in mathematics skill and reading skill at 4 years of age (preschool age) in the same sample of twins, and further examined whether interactions detected at 4 years could be attributed to the persistence of the interaction previously observed at 2 years. For early mathematics skill but not early reading skill, genetic influences were more pronounced at higher levels of SES. This interaction was not accounted for by the interaction observed at 2 years. These findings indicate that SES moderates the etiological influences on certain cognitive functions at multiple stages of child development. PMID:22350185

Role of the Trichoderma harzianum Endochitinase Gene, ech42, in Mycoparasitism

PubMed Central

Carsolio, Carolina; Benhamou, Nicole; Haran, Shoshan; Cortés, Carlos; Gutiérrez, Ana; Chet, Ilan; Herrera-Estrella, Alfredo

1999-01-01

The role of the Trichoderma harzianum endochitinase (Ech42) in mycoparasitism was studied by genetically manipulating the gene that encodes Ech42, ech42. We constructed several transgenic T. harzianum strains carrying multiple copies of ech42 and the corresponding gene disruptants. The level of extracellular endochitinase activity when T. harzianum was grown under inducing conditions increased up to 42-fold in multicopy strains as compared with the wild type, whereas gene disruptants exhibited practically no activity. The densities of chitin labeling of Rhizoctonia solani cell walls, after interactions with gene disruptants were not statistically significantly different than the density of chitin labeling after interactions with the wild type. Finally, no major differences in the efficacies of the strains generated as biocontrol agents against R. solani or Sclerotium rolfsii were observed in greenhouse experiments. PMID:10049844

Glucagon gene polymorphism modifies the effects of smoking and physical activity on risk of type 2 diabetes mellitus in Han Chinese.

PubMed

Li, Linlin; Gao, Kaiping; Zhao, Jingzhi; Feng, Tianping; Yin, Lei; Wang, Jinjin; Wang, Chongjian; Li, Chunyang; Wang, Yan; Wang, Qian; Zhai, Yujia; You, Haifei; Ren, Yongcheng; Wang, Bingyuan; Hu, Dongsheng

2014-01-25

Few genome-wide association studies have considered interactions between multiple genetic variants and environmental factors associated with disease. The interaction was examined between a glucagon gene (GCG) polymorphism and smoking, alcohol consumption and physical activity and the association with risk of type 2 diabetes mellitus (T2DM) in a case-control study of Chinese Han subjects. The rs12104705 polymorphism of GCG and interactions with environmental variables were analyzed for 9619 participants by binary multiple logistic regression. Smoking with the C-C haplotype of rs12104705 was associated with increased risk of T2DM (OR=1.174, 95% CI=1.013-1.361). Moderate and high physical activity with the C-C genotype was associated with decreased risk of T2DM as compared with low physical activity with the genotype (OR=0.251, 95% CI=0.206-0.306 and OR=0.190, 95% CI=0.164-0.220). However, the interaction of drinking and genotype was not associated with risk of T2DM. Genetic polymorphism in rs12104705 of GCG may interact with smoking and physical activity to modify the risk of T2DM. © 2013.

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

PubMed

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.

YY1 Regulates Melanocyte Development and Function by Cooperating with MITF

PubMed Central

Bell, Robert J. A.; Tran, Thanh-Nga T.; Haq, Rizwan; Liu, Huifei; Love, Kevin T.; Langer, Robert; Anderson, Daniel G.; Larue, Lionel; Fisher, David E.

2012-01-01

Studies of coat color mutants have greatly contributed to the discovery of genes that regulate melanocyte development and function. Here, we generated Yy1 conditional knockout mice in the melanocyte-lineage and observed profound melanocyte deficiency and premature gray hair, similar to the loss of melanocytes in human piebaldism and Waardenburg syndrome. Although YY1 is a ubiquitous transcription factor, YY1 interacts with M-MITF, the Waardenburg Syndrome IIA gene and a master transcriptional regulator of melanocytes. YY1 cooperates with M-MITF in regulating the expression of piebaldism gene KIT and multiple additional pigmentation genes. Moreover, ChIP–seq identified genome-wide YY1 targets in the melanocyte lineage. These studies mechanistically link genes implicated in human conditions of melanocyte deficiency and reveal how a ubiquitous factor (YY1) gains lineage-specific functions by co-regulating gene expression with a lineage-restricted factor (M-MITF)—a general mechanism which may confer tissue-specific gene expression in multiple lineages. PMID:22570637

Saturated fat intake modulates the association between a genetic risk score of obesity and BMI in two US populations

PubMed Central

Casas-Agustench, Patricia; Arnett, Donna K.; Smith, Caren E.; Lai, Chao-Qiang; Parnell, Laurence D.; Borecki, Ingrid B.; Frazier-Wood, Alexis C.; Allison, Matthew; Chen, Yii-Der Ida; Taylor, Kent D.; Rich, Stephen S.; Rotter, Jerome I.; Lee, Yu-Chi; Ordovás, José M.

2014-01-01

Combining multiple genetic variants related to obesity into a genetic risk score (GRS) might improve identification of individuals at risk of developing obesity. Moreover, characterizing gene-diet interactions is a research challenge to establish dietary recommendations to individuals with higher predisposition to obesity. Our objective was to analyze the association between an obesity GRS and BMI in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) population, focusing on gene-diet interactions with total fat and saturated fatty acid (SFA) intake and to replicate findings in Multi-Ethnic Study of Atherosclerosis (MESA) population. Cross-sectional analyses included 783 US Caucasian participants from GOLDN and 2035 from MESA. Dietary intakes were estimated with validated food frequency questionnaires. Height and weight were measured. A weighted GRS was calculated on the basis of 63 obesity-associated variants. Multiple linear regression models adjusted by potential confounders were used to examine gene-diet interactions between dietary intake (total fat and SFA) and the obesity GRS in determining BMI. Significant interactions were found between total fat intake and the obesity GRS using these variables as continuous for BMI (P for interaction=0.010, 0.046, and 0.002 in GOLDN, MESA and meta-analysis, respectively). These association terms were stronger when assessing interactions between SFA intake and GRS for BMI (P for interaction=0.005, 0.018, and <0.001 in GOLDN, MESA and meta-analysis, respectively). SFA intake interacts with an obesity GRS in modulating BMI in two US populations. Although to determine the causal direction requires further investigation, these findings suggest that potential dietary recommendations to reduce BMI effectively in populations with high obesity GRS would be to reduce total fat intake mainly by limiting SFAs. PMID:24794412

Selection of higher order regression models in the analysis of multi-factorial transcription data.

PubMed

Prazeres da Costa, Olivia; Hoffman, Arthur; Rey, Johannes W; Mansmann, Ulrich; Buch, Thorsten; Tresch, Achim

2014-01-01

Many studies examine gene expression data that has been obtained under the influence of multiple factors, such as genetic background, environmental conditions, or exposure to diseases. The interplay of multiple factors may lead to effect modification and confounding. Higher order linear regression models can account for these effects. We present a new methodology for linear model selection and apply it to microarray data of bone marrow-derived macrophages. This experiment investigates the influence of three variable factors: the genetic background of the mice from which the macrophages were obtained, Yersinia enterocolitica infection (two strains, and a mock control), and treatment/non-treatment with interferon-γ. We set up four different linear regression models in a hierarchical order. We introduce the eruption plot as a new practical tool for model selection complementary to global testing. It visually compares the size and significance of effect estimates between two nested models. Using this methodology we were able to select the most appropriate model by keeping only relevant factors showing additional explanatory power. Application to experimental data allowed us to qualify the interaction of factors as either neutral (no interaction), alleviating (co-occurring effects are weaker than expected from the single effects), or aggravating (stronger than expected). We find a biologically meaningful gene cluster of putative C2TA target genes that appear to be co-regulated with MHC class II genes. We introduced the eruption plot as a tool for visual model comparison to identify relevant higher order interactions in the analysis of expression data obtained under the influence of multiple factors. We conclude that model selection in higher order linear regression models should generally be performed for the analysis of multi-factorial microarray data.

Genetics Home Reference: vitiligo

MedlinePlus

... PubMed or Free article on PubMed Central Smith AG, Sturm RA. Multiple genes and locus interactions in ... qualified healthcare professional . About Selection Criteria for Links Data Files & API Site Map Subscribe Customer Support USA. ...

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

PubMed

Anitha, P; Anbarasu, Anand; Ramaiah, Sudha

2014-05-01

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

Gene–environment interaction in tobacco-related cancers

PubMed Central

Taioli, Emanuela

2008-01-01

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

Moderating role of the MAOA genotype in antisocial behaviour.

PubMed

Fergusson, David M; Boden, Joseph M; Horwood, L John; Miller, Allison; Kennedy, Martin A

2012-02-01

Recent studies have examined gene×environment (G×E) interactions involving the monoamine oxidase A (MAOA) gene in moderating the associations between exposure to adversity and antisocial behaviour. The present study examined a novel method for assessing interactions between a single gene and multiple risk factors related to environmental and personal adversity. To test the hypothesis that the presence of the low-activity MAOA genotype was associated with an increased response to a series of risk factors. Participants were 399 males from the Christchurch Health and Development Study who had complete data on: (a) MAOA promoter region variable number tandem repeat genotype; (b) antisocial behaviour (criminal offending) to age 30 and convictions to age 21; and (c) maternal smoking during pregnancy, IQ, childhood maltreatment and school failure. Poisson regression models were fitted to three antisocial behaviour outcomes (property/violent offending ages 15-30; and convictions ages 17-21), using measures of exposure to adverse childhood circumstances. The analyses revealed consistent evidence of G x E interactions, such that those with the low-activity MAOA variant who were exposed to adversity in childhood were significantly more likely to report offending in late adolescence and early adulthood. The present findings add to the evidence suggesting that there is a stable G x E interaction involving MAOA, a range of adverse environmental and personal factors, and antisocial behaviour across the life course. These analyses also demonstrate the utility of using multiple environmental/personal exposures to test G×E interactions.

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

PubMed

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 (P< 0.05); especially, SNP rs6532496 revealed the strongest association with cancer (P = 6.84 × 10⁻³); while the next best signal was rs951613 (P = 7.46 × 10⁻³). Classic logistic 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 < 0.05); whereas 13 SNPs showed gene-steroid interaction effects without main effect on cancer. SNP rs4634230 revealed the strongest gene-steroid interaction effect (OR=2.49, 95% CI=1.5-4.13 with P = 4.0 × 10⁻⁴ based on the classic 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.

Interaction between IL-6 and TNF-α genotypes associated with bacteremia in multiple myeloma patients submitted to autologous stem cell transplantation (ASCT).

PubMed

Trigo, Fernanda M B; Luizon, Marcelo R; Dutra, Hélio S; Maiolino, Angelo; Nucci, Márcio; Simões, Belinda P

2014-01-01

Stem cell transplantation affects patient׳s vulnerability to infections due to immunological changes related to chemotherapy. Multiple myeloma is characterized by susceptibility to infections, and IL-6 and TNF-α increased levels affect immune response (IR). Polymorphisms in promoter region of cytokine genes may alter expression levels and affect IR. We performed interaction analysis of IL-6 (-174G/C) and TNF-α (-308G/A) polymorphisms with infection susceptibility in 148 patients classified accordingly to infection status and found an interaction when compared groups with and without bacteremia (p=0.0380). The interaction may be more important than single effects for the IR associated with the infection susceptibility in ASCT.

Genome-wide gene–gene interaction analysis for next-generation sequencing

PubMed Central

Zhao, Jinying; Zhu, Yun; Xiong, Momiao

2016-01-01

The critical barrier in interaction analysis for next-generation sequencing (NGS) data is that the traditional pairwise interaction analysis that is suitable for common variants is difficult to apply to rare variants because of their prohibitive computational time, large number of tests and low power. The great challenges for successful detection of interactions with NGS data are (1) the demands in the paradigm of changes in interaction analysis; (2) severe multiple testing; and (3) heavy computations. To meet these challenges, we shift the paradigm of interaction analysis between two SNPs to interaction analysis between two genomic regions. In other words, we take a gene as a unit of analysis and use functional data analysis techniques as dimensional reduction tools to develop a novel statistic to collectively test interaction between all possible pairs of SNPs within two genome regions. By intensive simulations, we demonstrate that the functional logistic regression for interaction analysis has the correct type 1 error rates and higher power to detect interaction than the currently used methods. The proposed method was applied to a coronary artery disease dataset from the Wellcome Trust Case Control Consortium (WTCCC) study and the Framingham Heart Study (FHS) dataset, and the early-onset myocardial infarction (EOMI) exome sequence datasets with European origin from the NHLBI's Exome Sequencing Project. We discovered that 6 of 27 pairs of significantly interacted genes in the FHS were replicated in the independent WTCCC study and 24 pairs of significantly interacted genes after applying Bonferroni correction in the EOMI study. PMID:26173972

Identifying cooperative transcriptional regulations using protein–protein interactions

PubMed Central

Nagamine, Nobuyoshi; Kawada, Yuji; Sakakibara, Yasubumi

2005-01-01

Cooperative transcriptional activations among multiple transcription factors (TFs) are important to understand the mechanisms of complex transcriptional regulations in eukaryotes. Previous studies have attempted to find cooperative TFs based on gene expression data with gene expression profiles as a measure of similarity of gene regulations. In this paper, we use protein–protein interaction data to infer synergistic binding of cooperative TFs. Our fundamental idea is based on the assumption that genes contributing to a similar biological process are regulated under the same control mechanism. First, the protein–protein interaction networks are used to calculate the similarity of biological processes among genes. Second, we integrate this similarity and the chromatin immuno-precipitation data to identify cooperative TFs. Our computational experiments in yeast show that predictions made by our method have successfully identified eight pairs of cooperative TFs that have literature evidences but could not be identified by the previous method. Further, 12 new possible pairs have been inferred and we have examined the biological relevances for them. However, since a typical problem using protein–protein interaction data is that many false-positive data are contained, we propose a method combining various biological data to increase the prediction accuracy. PMID:16126847

DNA repair variants and breast cancer risk.

PubMed

Grundy, Anne; Richardson, Harriet; Schuetz, Johanna M; Burstyn, Igor; Spinelli, John J; Brooks-Wilson, Angela; Aronson, Kristan J

2016-05-01

A functional DNA repair system has been identified as important in the prevention of tumour development. Previous studies have hypothesized that common polymorphisms in DNA repair genes could play a role in breast cancer risk and also identified the potential for interactions between these polymorphisms and established breast cancer risk factors such as physical activity. Associations with breast cancer risk for 99 single nucleotide polymorphisms (SNPs) from genes in ten DNA repair pathways were examined in a case-control study including both Europeans (644 cases, 809 controls) and East Asians (299 cases, 160 controls). Odds ratios in both additive and dominant genetic models were calculated separately for participants of European and East Asian ancestry using multivariate logistic regression. The impact of multiple comparisons was assessed by correcting for the false discovery rate within each DNA repair pathway. Interactions between several breast cancer risk factors and DNA repair SNPs were also evaluated. One SNP (rs3213282) in the gene XRCC1 was associated with an increased risk of breast cancer in the dominant model of inheritance following adjustment for the false discovery rate (P < 0.05), although no associations were observed for other DNA repair SNPs. Interactions of six SNPs in multiple DNA repair pathways with physical activity were evident prior to correction for FDR, following which there was support for only one of the interaction terms (P < 0.05). No consistent associations between variants in DNA repair genes and breast cancer risk or their modification by breast cancer risk factors were observed. © 2016 Wiley Periodicals, Inc.

Genetic variation in SLC7A2 interacts with calcium and magnesium intakes in modulating the risk of colorectal polyps.

PubMed

Sun, Pin; Zhu, Xiangzhu; Shrubsole, Martha J; Ness, Reid M; Hibler, Elizabeth A; Cai, Qiuyin; Long, Jirong; Chen, Zhi; Li, Guoliang; Hou, Lifang; Smalley, Walter E; Edwards, Todd L; Giovannucci, Edward; Zheng, Wei; Dai, Qi

2017-09-01

Solute carrier family 7, member 2 (SLC7A2) gene encodes a protein called cationic amino acid transporter 2, which mediates the transport of arginine, lysine and ornithine. l-Arginine is necessary for cancer development and progression, including an important role in colorectal cancer pathogenesis. Furthermore, previous studies found that both calcium and magnesium inhibit the transport of arginine. Thus, calcium, magnesium or calcium:magnesium intake ratio may interact with polymorphisms in the SLC7A2 gene in association with colorectal cancer. We conducted a two-phase case-control study within the Tennessee Colorectal Polyps Study. In the first phase, 23 tagging single-nucleotide polymorphisms in the SLC7A2 gene were included for 725 colorectal adenoma cases and 755 controls. In the second phase conducted in an independent set of 607 cases and 2113 controls, we replicated the significant findings in the first phase. We observed that rs2720574 significantly interacted with calcium:magnesium intake ratio in association with odds of adenoma, particularly multiple/advanced adenoma. In the combined analysis, among those with a calcium:magnesium intake ratio below 2.78, individuals who carried GC/CC genotypes demonstrated higher odds of adenoma [OR (95% CI):1.36 (1.11-1.68)] and multiple/advanced adenoma [OR (95% CI): 1.68 (1.28, 2.20)] than those who carried the GG genotype. The P values for interactions between calcium:magnesium intake ratio and rs2720574 were .002 for all adenomas and <.001 for multiple/advanced adenoma. Among those with the GG genotype, a high calcium:magnesium ratio was associated with increased odds of colorectal adenoma [OR (95% CI): 1.73 (1.27-2.36)] and advanced/multiple adenomas [1.62 (1.05-2.50)], whereas among those with the GC/CC genotypes, high calcium:magnesium ratio was related to reduced odds of colorectal adenoma [0.64 (0.42-0.99)] and advanced/multiple adenomas [0.55 (0.31-1.00)]. Copyright © 2017 Elsevier Inc. All rights reserved.

Functional Interaction Network Construction and Analysis for Disease Discovery.

PubMed

Wu, Guanming; Haw, Robin

2017-01-01

Network-based approaches project seemingly unrelated genes or proteins onto a large-scale network context, therefore providing a holistic visualization and analysis platform for genomic data generated from high-throughput experiments, reducing the dimensionality of data via using network modules and increasing the statistic analysis power. Based on the Reactome database, the most popular and comprehensive open-source biological pathway knowledgebase, we have developed a highly reliable protein functional interaction network covering around 60 % of total human genes and an app called ReactomeFIViz for Cytoscape, the most popular biological network visualization and analysis platform. In this chapter, we describe the detailed procedures on how this functional interaction network is constructed by integrating multiple external data sources, extracting functional interactions from human curated pathway databases, building a machine learning classifier called a Naïve Bayesian Classifier, predicting interactions based on the trained Naïve Bayesian Classifier, and finally constructing the functional interaction database. We also provide an example on how to use ReactomeFIViz for performing network-based data analysis for a list of genes.

Placental genome and maternal-placental genetic interactions: a genome-wide and candidate gene association study of placental abruption.

PubMed

Denis, Marie; Enquobahrie, Daniel A; Tadesse, Mahlet G; Gelaye, Bizu; Sanchez, Sixto E; Salazar, Manuel; Ananth, Cande V; Williams, Michelle A

2014-01-01

While available evidence supports the role of genetics in the pathogenesis of placental abruption (PA), PA-related placental genome variations and maternal-placental genetic interactions have not been investigated. Maternal blood and placental samples collected from participants in the Peruvian Abruptio Placentae Epidemiology study were genotyped using Illumina's Cardio-Metabochip platform. We examined 118,782 genome-wide SNPs and 333 SNPs in 32 candidate genes from mitochondrial biogenesis and oxidative phosphorylation pathways in placental DNA from 280 PA cases and 244 controls. We assessed maternal-placental interactions in the candidate gene SNPS and two imprinted regions (IGF2/H19 and C19MC). Univariate and penalized logistic regression models were fit to estimate odds ratios. We examined the combined effect of multiple SNPs on PA risk using weighted genetic risk scores (WGRS) with repeated ten-fold cross-validations. A multinomial model was used to investigate maternal-placental genetic interactions. In placental genome-wide and candidate gene analyses, no SNP was significant after false discovery rate correction. The top genome-wide association study (GWAS) hits were rs544201, rs1484464 (CTNNA2), rs4149570 (TNFRSF1A) and rs13055470 (ZNRF3) (p-values: 1.11e-05 to 3.54e-05). The top 200 SNPs of the GWAS overrepresented genes involved in cell cycle, growth and proliferation. The top candidate gene hits were rs16949118 (COX10) and rs7609948 (THRB) (p-values: 6.00e-03 and 8.19e-03). Participants in the highest quartile of WGRS based on cross-validations using SNPs selected from the GWAS and candidate gene analyses had a 8.40-fold (95% CI: 5.8-12.56) and a 4.46-fold (95% CI: 2.94-6.72) higher odds of PA compared to participants in the lowest quartile. We found maternal-placental genetic interactions on PA risk for two SNPs in PPARG (chr3:12313450 and chr3:12412978) and maternal imprinting effects for multiple SNPs in the C19MC and IGF2/H19 regions. Variations in the placental genome and interactions between maternal-placental genetic variations may contribute to PA risk. Larger studies may help advance our understanding of PA pathogenesis.

The role of KIR2DS1 in multiple sclerosis--KIR in Portuguese MS patients.

PubMed

Bettencourt, Andreia; Silva, Ana Martins; Carvalho, Cláudia; Leal, Bárbara; Santos, Ernestina; Costa, Paulo P; Silva, Berta M

2014-04-15

Killer Immunoglobulin-like Receptor (KIR) genes may influence both resistance and susceptibility to different autoimmune diseases, but their role in the pathogenesis of Multiple Sclerosis (MS) is still unclear. We investigated the influence of KIR genes on MS susceptibility in 447 MS Portuguese patients, and also whether genetic interactions between specific KIR genes and their HLA class I ligands could contribute to the pathogenesis of MS. We observed a negative association between the activating KIR2DS1 gene and MS (adjusted OR=0.450, p=0.030) independently from the presence of HLA-DRB1*15 allele. The activating KIR2DS1 receptor seems to confer protection against MS most probably through modulation of autoreactive T cells by Natural Killer cells. Copyright © 2014 Elsevier B.V. All rights reserved.

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

PubMed Central

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 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. PMID:28792482

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

PubMed

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.

Gene-Environment Interactions in Cardiovascular Disease

PubMed Central

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

2011-01-01

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

Convergent evolution of gene networks by single-gene duplications in higher eukaryotes.

PubMed

Amoutzias, Gregory D; Robertson, David L; Oliver, Stephen G; Bornberg-Bauer, Erich

2004-03-01

By combining phylogenetic, proteomic and structural information, we have elucidated the evolutionary driving forces for the gene-regulatory interaction networks of basic helix-loop-helix transcription factors. We infer that recurrent events of single-gene duplication and domain rearrangement repeatedly gave rise to distinct networks with almost identical hub-based topologies, and multiple activators and repressors. We thus provide the first empirical evidence for scale-free protein networks emerging through single-gene duplications, the dominant importance of molecular modularity in the bottom-up construction of complex biological entities, and the convergent evolution of networks.

Analysis of 30 Genes (355 SNPS) Related to Energy Homeostasis for Association with Adiposity in European-American and Yup'ik Eskimo Populations

PubMed Central

Chung, Wendy K.; Patki, Amit; Matsuoka, Naoki; Boyer, Bert B.; Liu, Nianjun; Musani, Solomon K.; Goropashnaya, Anna V.; Tan, Perciliz L.; Katsanis, Nicholas; Johnson, Stephen B.; Gregersen, Peter K.; Allison, David B.; Leibel, Rudolph L.; Tiwari, Hemant K.

2009-01-01

Objective Human adiposity is highly heritable, but few of the genes that predispose to obesity in most humans are known. We tested candidate genes in pathways related to food intake and energy expenditure for association with measures of adiposity. Methods We studied 355 genetic variants in 30 candidate genes in 7 molecular pathways related to obesity in two groups of adult subjects: 1,982 unrelated European Americans living in the New York metropolitan area drawn from the extremes of their body mass index (BMI) distribution and 593 related Yup'ik Eskimos living in rural Alaska characterized for BMI, body composition, waist circumference, and skin fold thicknesses. Data were analyzed by using a mixed model in conjunction with a false discovery rate (FDR) procedure to correct for multiple testing. Results After correcting for multiple testing, two single nucleotide polymorphisms (SNPs) in Ghrelin (GHRL) (rs35682 and rs35683) were associated with BMI in the New York European Americans. This association was not replicated in the Yup'ik participants. There was no evidence for gene × gene interactions among genes within the same molecular pathway after adjusting for multiple testing via FDR control procedure. Conclusion Genetic variation in GHRL may have a modest impact on BMI in European Americans. PMID:19077438

Analysis of 30 genes (355 SNPS) related to energy homeostasis for association with adiposity in European-American and Yup'ik Eskimo populations.

PubMed

Chung, Wendy K; Patki, Amit; Matsuoka, Naoki; Boyer, Bert B; Liu, Nianjun; Musani, Solomon K; Goropashnaya, Anna V; Tan, Perciliz L; Katsanis, Nicholas; Johnson, Stephen B; Gregersen, Peter K; Allison, David B; Leibel, Rudolph L; Tiwari, Hemant K

2009-01-01

Human adiposity is highly heritable, but few of the genes that predispose to obesity in most humans are known. We tested candidate genes in pathways related to food intake and energy expenditure for association with measures of adiposity. We studied 355 genetic variants in 30 candidate genes in 7 molecular pathways related to obesity in two groups of adult subjects: 1,982 unrelated European Americans living in the New York metropolitan area drawn from the extremes of their body mass index (BMI) distribution and 593 related Yup'ik Eskimos living in rural Alaska characterized for BMI, body composition, waist circumference, and skin fold thicknesses. Data were analyzed by using a mixed model in conjunction with a false discovery rate (FDR) procedure to correct for multiple testing. After correcting for multiple testing, two single nucleotide polymorphisms (SNPs) in Ghrelin (GHRL) (rs35682 and rs35683) were associated with BMI in the New York European Americans. This association was not replicated in the Yup'ik participants. There was no evidence for gene x gene interactions among genes within the same molecular pathway after adjusting for multiple testing via FDR control procedure. Genetic variation in GHRL may have a modest impact on BMI in European Americans.

Bioinformatics approaches to predict target genes from transcription factor binding data.

PubMed

Essebier, Alexandra; Lamprecht, Marnie; Piper, Michael; Bodén, Mikael

2017-12-01

Transcription factors regulate gene expression and play an essential role in development by maintaining proliferative states, driving cellular differentiation and determining cell fate. Transcription factors are capable of regulating multiple genes over potentially long distances making target gene identification challenging. Currently available experimental approaches to detect distal interactions have multiple weaknesses that have motivated the development of computational approaches. Although an improvement over experimental approaches, existing computational approaches are still limited in their application, with different weaknesses depending on the approach. Here, we review computational approaches with a focus on data dependency, cell type specificity and usability. With the aim of identifying transcription factor target genes, we apply available approaches to typical transcription factor experimental datasets. We show that approaches are not always capable of annotating all transcription factor binding sites; binding sites should be treated disparately; and a combination of approaches can increase the biological relevance of the set of genes identified as targets. Copyright © 2017 Elsevier Inc. All rights reserved.

Avirulence Genes in Cereal Powdery Mildews: The Gene-for-Gene Hypothesis 2.0.

PubMed

Bourras, Salim; McNally, Kaitlin E; Müller, Marion C; Wicker, Thomas; Keller, Beat

2016-01-01

The gene-for-gene hypothesis states that for each gene controlling resistance in the host, there is a corresponding, specific gene controlling avirulence in the pathogen. Allelic series of the cereal mildew resistance genes Pm3 and Mla provide an excellent system for genetic and molecular analysis of resistance specificity. Despite this opportunity for molecular research, avirulence genes in mildews remain underexplored. Earlier work in barley powdery mildew (B.g. hordei) has shown that the reaction to some Mla resistance alleles is controlled by multiple genes. Similarly, several genes are involved in the specific interaction of wheat mildew (B.g. tritici) with the Pm3 allelic series. We found that two mildew genes control avirulence on Pm3f: one gene is involved in recognition by the resistance protein as demonstrated by functional studies in wheat and the heterologous host Nicotiana benthamiana. A second gene is a suppressor, and resistance is only observed in mildew genotypes combining the inactive suppressor and the recognized Avr. We propose that such suppressor/avirulence gene combinations provide the basis of specificity in mildews. Depending on the particular gene combinations in a mildew race, different genes will be genetically identified as the "avirulence" gene. Additionally, the observation of two LINE retrotransposon-encoded avirulence genes in B.g. hordei further suggests that the control of avirulence in mildew is more complex than a canonical gene-for-gene interaction. To fully understand the mildew-cereal interactions, more knowledge on avirulence determinants is needed and we propose ways how this can be achieved based on recent advances in the field.

Avirulence Genes in Cereal Powdery Mildews: The Gene-for-Gene Hypothesis 2.0

PubMed Central

Bourras, Salim; McNally, Kaitlin E.; Müller, Marion C.; Wicker, Thomas; Keller, Beat

2016-01-01

The gene-for-gene hypothesis states that for each gene controlling resistance in the host, there is a corresponding, specific gene controlling avirulence in the pathogen. Allelic series of the cereal mildew resistance genes Pm3 and Mla provide an excellent system for genetic and molecular analysis of resistance specificity. Despite this opportunity for molecular research, avirulence genes in mildews remain underexplored. Earlier work in barley powdery mildew (B.g. hordei) has shown that the reaction to some Mla resistance alleles is controlled by multiple genes. Similarly, several genes are involved in the specific interaction of wheat mildew (B.g. tritici) with the Pm3 allelic series. We found that two mildew genes control avirulence on Pm3f: one gene is involved in recognition by the resistance protein as demonstrated by functional studies in wheat and the heterologous host Nicotiana benthamiana. A second gene is a suppressor, and resistance is only observed in mildew genotypes combining the inactive suppressor and the recognized Avr. We propose that such suppressor/avirulence gene combinations provide the basis of specificity in mildews. Depending on the particular gene combinations in a mildew race, different genes will be genetically identified as the “avirulence” gene. Additionally, the observation of two LINE retrotransposon-encoded avirulence genes in B.g. hordei further suggests that the control of avirulence in mildew is more complex than a canonical gene-for-gene interaction. To fully understand the mildew–cereal interactions, more knowledge on avirulence determinants is needed and we propose ways how this can be achieved based on recent advances in the field. PMID:26973683

Disentangling the multigenic and pleiotropic nature of molecular function

PubMed Central

2015-01-01

Background Biological processes at the molecular level are usually represented by molecular interaction networks. Function is organised and modularity identified based on network topology, however, this approach often fails to account for the dynamic and multifunctional nature of molecular components. For example, a molecule engaging in spatially or temporally independent functions may be inappropriately clustered into a single functional module. To capture biologically meaningful sets of interacting molecules, we use experimentally defined pathways as spatial/temporal units of molecular activity. Results We defined functional profiles of Saccharomyces cerevisiae based on a minimal set of Gene Ontology terms sufficient to represent each pathway's genes. The Gene Ontology terms were used to annotate 271 pathways, accounting for pathway multi-functionality and gene pleiotropy. Pathways were then arranged into a network, linked by shared functionality. Of the genes in our data set, 44% appeared in multiple pathways performing a diverse set of functions. Linking pathways by overlapping functionality revealed a modular network with energy metabolism forming a sparse centre, surrounded by several denser clusters comprised of regulatory and metabolic pathways. Signalling pathways formed a relatively discrete cluster connected to the centre of the network. Genetic interactions were enriched within the clusters of pathways by a factor of 5.5, confirming the organisation of our pathway network is biologically significant. Conclusions Our representation of molecular function according to pathway relationships enables analysis of gene/protein activity in the context of specific functional roles, as an alternative to typical molecule-centric graph-based methods. The pathway network demonstrates the cooperation of multiple pathways to perform biological processes and organises pathways into functionally related clusters with interdependent outcomes. PMID:26678917

Dose-sensitivity, conserved non-coding sequences, and duplicate gene retention through multiple tetraploidies in the grasses.

PubMed

Schnable, James C; Pedersen, Brent S; Subramaniam, Sabarinath; Freeling, Michael

2011-01-01

Whole genome duplications, or tetraploidies, are an important source of increased gene content. Following whole genome duplication, duplicate copies of many genes are lost from the genome. This loss of genes is biased both in the classes of genes deleted and the subgenome from which they are lost. Many or all classes are genes preferentially retained as duplicate copies are engaged in dose sensitive protein-protein interactions, such that deletion of any one duplicate upsets the status quo of subunit concentrations, and presumably lowers fitness as a result. Transcription factors are also preferentially retained following every whole genome duplications studied. This has been explained as a consequence of protein-protein interactions, just as for other highly retained classes of genes. We show that the quantity of conserved noncoding sequences (CNSs) associated with genes predicts the likelihood of their retention as duplicate pairs following whole genome duplication. As many CNSs likely represent binding sites for transcriptional regulators, we propose that the likelihood of gene retention following tetraploidy may also be influenced by dose-sensitive protein-DNA interactions between the regulatory regions of CNS-rich genes - nicknamed bigfoot genes - and the proteins that bind to them. Using grass genomes, we show that differential loss of CNSs from one member of a pair following the pre-grass tetraploidy reduces its chance of retention in the subsequent maize lineage tetraploidy.

Dose–Sensitivity, Conserved Non-Coding Sequences, and Duplicate Gene Retention Through Multiple Tetraploidies in the Grasses

PubMed Central

Schnable, James C.; Pedersen, Brent S.; Subramaniam, Sabarinath; Freeling, Michael

2011-01-01

Whole genome duplications, or tetraploidies, are an important source of increased gene content. Following whole genome duplication, duplicate copies of many genes are lost from the genome. This loss of genes is biased both in the classes of genes deleted and the subgenome from which they are lost. Many or all classes are genes preferentially retained as duplicate copies are engaged in dose sensitive protein–protein interactions, such that deletion of any one duplicate upsets the status quo of subunit concentrations, and presumably lowers fitness as a result. Transcription factors are also preferentially retained following every whole genome duplications studied. This has been explained as a consequence of protein–protein interactions, just as for other highly retained classes of genes. We show that the quantity of conserved noncoding sequences (CNSs) associated with genes predicts the likelihood of their retention as duplicate pairs following whole genome duplication. As many CNSs likely represent binding sites for transcriptional regulators, we propose that the likelihood of gene retention following tetraploidy may also be influenced by dose–sensitive protein–DNA interactions between the regulatory regions of CNS-rich genes – nicknamed bigfoot genes – and the proteins that bind to them. Using grass genomes, we show that differential loss of CNSs from one member of a pair following the pre-grass tetraploidy reduces its chance of retention in the subsequent maize lineage tetraploidy. PMID:22645525

Evidence for gene-gene epistatic interactions among susceptibility loci for systemic lupus erythematosus.

PubMed

Hughes, Travis; Adler, Adam; Kelly, Jennifer A; Kaufman, Kenneth M; Williams, Adrienne H; Langefeld, Carl D; Brown, Elizabeth E; Alarcón, Graciela S; Kimberly, Robert P; Edberg, Jeffrey C; Ramsey-Goldman, Rosalind; Petri, Michelle; Boackle, Susan A; Stevens, Anne M; Reveille, John D; Sanchez, Elena; Martín, Javier; Niewold, Timothy B; Vilá, Luis M; Scofield, R Hal; Gilkeson, Gary S; Gaffney, Patrick M; Criswell, Lindsey A; Moser, Kathy L; Merrill, Joan T; Jacob, Chaim O; Tsao, Betty P; James, Judith A; Vyse, Timothy J; Alarcón-Riquelme, Marta E; Harley, John B; Richardson, Bruce C; Sawalha, Amr H

2012-02-01

Several confirmed genetic susceptibility loci for lupus have been described. To date, no clear evidence for genetic epistasis in lupus has been established. The aim of this study was to test for gene-gene interactions in a number of known lupus susceptibility loci. Eighteen single-nucleotide polymorphisms tagging independent and confirmed lupus susceptibility loci were genotyped in a set of 4,248 patients with lupus and 3,818 normal healthy control subjects of European descent. Epistasis was tested by a 2-step approach using both parametric and nonparametric methods. The false discovery rate (FDR) method was used to correct for multiple testing. We detected and confirmed gene-gene interactions between the HLA region and CTLA4, IRF5, and ITGAM and between PDCD1 and IL21 in patients with lupus. The most significant interaction detected by parametric analysis was between rs3131379 in the HLA region and rs231775 in CTLA4 (interaction odds ratio 1.19, Z = 3.95, P = 7.8 × 10(-5) [FDR ≤0.05], P for multifactor dimensionality reduction = 5.9 × 10(-45)). Importantly, our data suggest that in patients with lupus, the presence of the HLA lupus risk alleles in rs1270942 and rs3131379 increases the odds of also carrying the lupus risk allele in IRF5 (rs2070197) by 17% and 16%, respectively (P = 0.0028 and P = 0.0047, respectively). We provide evidence for gene-gene epistasis in systemic lupus erythematosus. These findings support a role for genetic interaction contributing to the complexity of lupus heritability. Copyright © 2012 by the American College of Rheumatology.

The Protein Interaction Network of Bacteriophage Lambda with Its Host, Escherichia coli

PubMed Central

Blasche, Sonja; Wuchty, Stefan; Rajagopala, Seesandra V.

2013-01-01

Although most of the 73 open reading frames (ORFs) in bacteriophage λ have been investigated intensively, the function of many genes in host-phage interactions remains poorly understood. Using yeast two-hybrid screens of all lambda ORFs for interactions with its host Escherichia coli, we determined a raw data set of 631 host-phage interactions resulting in a set of 62 high-confidence interactions after multiple rounds of retesting. These links suggest novel regulatory interactions between the E. coli transcriptional network and lambda proteins. Targeted host proteins and genes required for lambda infection are enriched among highly connected proteins, suggesting that bacteriophages resemble interaction patterns of human viruses. Lambda tail proteins interact with both bacterial fimbrial proteins and E. coli proteins homologous to other phage proteins. Lambda appears to dramatically differ from other phages, such as T7, because of its unusually large number of modified and processed proteins, which reduces the number of host-virus interactions detectable by yeast two-hybrid screens. PMID:24049175

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2017-04-01

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

EINVis: a visualization tool for analyzing and exploring genetic interactions in large-scale association studies.

PubMed

Wu, Yubao; Zhu, Xiaofeng; Chen, Jian; Zhang, Xiang

2013-11-01

Epistasis (gene-gene interaction) detection in large-scale genetic association studies has recently drawn extensive research interests as many complex traits are likely caused by the joint effect of multiple genetic factors. The large number of possible interactions poses both statistical and computational challenges. A variety of approaches have been developed to address the analytical challenges in epistatic interaction detection. These methods usually output the identified genetic interactions and store them in flat file formats. It is highly desirable to develop an effective visualization tool to further investigate the detected interactions and unravel hidden interaction patterns. We have developed EINVis, a novel visualization tool that is specifically designed to analyze and explore genetic interactions. EINVis displays interactions among genetic markers as a network. It utilizes a circular layout (specially, a tree ring view) to simultaneously visualize the hierarchical interactions between single nucleotide polymorphisms (SNPs), genes, and chromosomes, and the network structure formed by these interactions. Using EINVis, the user can distinguish marginal effects from interactions, track interactions involving more than two markers, visualize interactions at different levels, and detect proxy SNPs based on linkage disequilibrium. EINVis is an effective and user-friendly free visualization tool for analyzing and exploring genetic interactions. It is publicly available with detailed documentation and online tutorial on the web at http://filer.case.edu/yxw407/einvis/. © 2013 WILEY PERIODICALS, INC.

Enhancer Sharing Promotes Neighborhoods of Transcriptional Regulation Across Eukaryotes

PubMed Central

Quintero-Cadena, Porfirio; Sternberg, Paul W.

2016-01-01

Enhancers physically interact with transcriptional promoters, looping over distances that can span multiple regulatory elements. Given that enhancer–promoter (EP) interactions generally occur via common protein complexes, it is unclear whether EP pairing is predominantly deterministic or proximity guided. Here, we present cross-organismic evidence suggesting that most EP pairs are compatible, largely determined by physical proximity rather than specific interactions. By reanalyzing transcriptome datasets, we find that the transcription of gene neighbors is correlated over distances that scale with genome size. We experimentally show that nonspecific EP interactions can explain such correlation, and that EP distance acts as a scaling factor for the transcriptional influence of an enhancer. We propose that enhancer sharing is commonplace among eukaryotes, and that EP distance is an important layer of information in gene regulation. PMID:27799341

multiDE: a dimension reduced model based statistical method for differential expression analysis using RNA-sequencing data with multiple treatment conditions.

PubMed

Kang, Guangliang; Du, Li; Zhang, Hong

2016-06-22

The growing complexity of biological experiment design based on high-throughput RNA sequencing (RNA-seq) is calling for more accommodative statistical tools. We focus on differential expression (DE) analysis using RNA-seq data in the presence of multiple treatment conditions. We propose a novel method, multiDE, for facilitating DE analysis using RNA-seq read count data with multiple treatment conditions. The read count is assumed to follow a log-linear model incorporating two factors (i.e., condition and gene), where an interaction term is used to quantify the association between gene and condition. The number of the degrees of freedom is reduced to one through the first order decomposition of the interaction, leading to a dramatically power improvement in testing DE genes when the number of conditions is greater than two. In our simulation situations, multiDE outperformed the benchmark methods (i.e. edgeR and DESeq2) even if the underlying model was severely misspecified, and the power gain was increasing in the number of conditions. In the application to two real datasets, multiDE identified more biologically meaningful DE genes than the benchmark methods. An R package implementing multiDE is available publicly at http://homepage.fudan.edu.cn/zhangh/softwares/multiDE . When the number of conditions is two, multiDE performs comparably with the benchmark methods. When the number of conditions is greater than two, multiDE outperforms the benchmark methods.

Multi-variant study of obesity risk genes in African Americans: The Jackson Heart Study.

PubMed

Liu, Shijian; Wilson, James G; Jiang, Fan; Griswold, Michael; Correa, Adolfo; Mei, Hao

2016-11-30

Genome-wide association study (GWAS) has been successful in identifying obesity risk genes by single-variant association analysis. For this study, we designed steps of analysis strategy and aimed to identify multi-variant effects on obesity risk among candidate genes. Our analyses were focused on 2137 African American participants with body mass index measured in the Jackson Heart Study and 657 common single nucleotide polymorphisms (SNPs) genotyped at 8 GWAS-identified obesity risk genes. Single-variant association test showed that no SNPs reached significance after multiple testing adjustment. The following gene-gene interaction analysis, which was focused on SNPs with unadjusted p-value<0.10, identified 6 significant multi-variant associations. Logistic regression showed that SNPs in these associations did not have significant linear interactions; examination of genetic risk score evidenced that 4 multi-variant associations had significant additive effects of risk SNPs; and haplotype association test presented that all multi-variant associations contained one or several combinations of particular alleles or haplotypes, associated with increased obesity risk. Our study evidenced that obesity risk genes generated multi-variant effects, which can be additive or non-linear interactions, and multi-variant study is an important supplement to existing GWAS for understanding genetic effects of obesity risk genes. Copyright © 2016 Elsevier B.V. All rights reserved.

A Mechanistic Model for Cooperative Behavior of Co-transcribing RNA Polymerases

PubMed Central

Heberling, Tamra; Davis, Lisa; Gedeon, Jakub; Morgan, Charles; Gedeon, Tomáš

2016-01-01

In fast-transcribing prokaryotic genes, such as an rrn gene in Escherichia coli, many RNA polymerases (RNAPs) transcribe the DNA simultaneously. Active elongation of RNAPs is often interrupted by pauses, which has been observed to cause RNAP traffic jams; yet some studies indicate that elongation seems to be faster in the presence of multiple RNAPs than elongation by a single RNAP. We propose that an interaction between RNAPs via the torque produced by RNAP motion on helically twisted DNA can explain this apparent paradox. We have incorporated the torque mechanism into a stochastic model and simulated transcription both with and without torque. Simulation results illustrate that the torque causes shorter pause durations and fewer collisions between polymerases. Our results suggest that the torsional interaction of RNAPs is an important mechanism in maintaining fast transcription times, and that transcription should be viewed as a cooperative group effort by multiple polymerases. PMID:27517607

Pirated Siderophores Promote Sporulation in Bacillus subtilis.

PubMed

Grandchamp, Gabrielle M; Caro, Lews; Shank, Elizabeth A

2017-05-15

In microbial communities, bacteria chemically and physically interact with one another. Some of these interactions are mediated by secreted specialized metabolites that act as either intraspecies or interspecies signals to alter gene expression and to change cell physiology. Bacillus subtilis is a well-characterized soil microbe that can differentiate into multiple cell types, including metabolically dormant endospores. We were interested in identifying microbial interactions that affected sporulation in B. subtilis Using a fluorescent transcriptional reporter, we observed that coculturing B. subtilis with Escherichia coli promoted sporulation gene expression via a secreted metabolite. To identify the active compound, we screened the E. coli Keio Collection and identified the sporulation-accelerating cue as the siderophore enterobactin. B. subtilis has multiple iron acquisition systems that are used to take up the B. subtilis- produced siderophore bacillibactin, as well as to pirate exogenous siderophores such as enterobactin. While B. subtilis uses a single substrate binding protein (FeuA) to take up both bacillibactin and enterobactin, we discovered that it requires two distinct genes to sporulate in response to these siderophores (the esterase gene besA for bacillibactin and a putative esterase gene, ybbA , for enterobactin). In addition, we found that siderophores from a variety of other microbial species also promote sporulation in B. subtilis Our results thus demonstrate that siderophores can act not only as bacterial iron acquisition systems but also as interspecies cues that alter cellular development and accelerate sporulation in B. subtilis IMPORTANCE While much is known about the genetic regulation of Bacillus subtilis sporulation, little is understood about how other bacteria influence this process. This work describes an interaction between Escherichia coli and B. subtilis that accelerates sporulation in B. subtilis The interaction is mediated by the E. coli siderophore enterobactin; we show that other species' siderophores also promote sporulation gene expression in B. subtilis These results suggest that siderophores not only may supply bacteria with the mineral nutrient iron but also may play a role in bacterial interspecies signaling, providing a cue for sporulation. Siderophores are produced by many bacterial species and thus potentially play important roles in altering bacterial cell physiology in diverse environments. Copyright © 2017 Grandchamp et al.

Pirated Siderophores Promote Sporulation in Bacillus subtilis

PubMed Central

Grandchamp, Gabrielle M.; Caro, Lews

2017-01-01

ABSTRACT In microbial communities, bacteria chemically and physically interact with one another. Some of these interactions are mediated by secreted specialized metabolites that act as either intraspecies or interspecies signals to alter gene expression and to change cell physiology. Bacillus subtilis is a well-characterized soil microbe that can differentiate into multiple cell types, including metabolically dormant endospores. We were interested in identifying microbial interactions that affected sporulation in B. subtilis. Using a fluorescent transcriptional reporter, we observed that coculturing B. subtilis with Escherichia coli promoted sporulation gene expression via a secreted metabolite. To identify the active compound, we screened the E. coli Keio Collection and identified the sporulation-accelerating cue as the siderophore enterobactin. B. subtilis has multiple iron acquisition systems that are used to take up the B. subtilis-produced siderophore bacillibactin, as well as to pirate exogenous siderophores such as enterobactin. While B. subtilis uses a single substrate binding protein (FeuA) to take up both bacillibactin and enterobactin, we discovered that it requires two distinct genes to sporulate in response to these siderophores (the esterase gene besA for bacillibactin and a putative esterase gene, ybbA, for enterobactin). In addition, we found that siderophores from a variety of other microbial species also promote sporulation in B. subtilis. Our results thus demonstrate that siderophores can act not only as bacterial iron acquisition systems but also as interspecies cues that alter cellular development and accelerate sporulation in B. subtilis. IMPORTANCE While much is known about the genetic regulation of Bacillus subtilis sporulation, little is understood about how other bacteria influence this process. This work describes an interaction between Escherichia coli and B. subtilis that accelerates sporulation in B. subtilis. The interaction is mediated by the E. coli siderophore enterobactin; we show that other species' siderophores also promote sporulation gene expression in B. subtilis. These results suggest that siderophores not only may supply bacteria with the mineral nutrient iron but also may play a role in bacterial interspecies signaling, providing a cue for sporulation. Siderophores are produced by many bacterial species and thus potentially play important roles in altering bacterial cell physiology in diverse environments. PMID:28283524

Gene-for-genes interactions between cotton R genes and Xanthomonas campestris pv. malvacearum avr genes.

PubMed

De Feyter, R; Yang, Y; Gabriel, D W

1993-01-01

Six plasmid-borne avirulence (avr) genes were previously cloned from strain XcmH of the cotton pathogen, Xanthomonas campestris pv. malvacearum. We have now localized all six avr genes on the cloned fragments by subcloning and Tn5-gusA insertional mutagenesis. None of these avr genes appeared to exhibit exclusively gene-for-gene patterns of interactions with cotton R genes, and avrB4 was demonstrated to confer avr gene-for-R genes (plural) avirulence to X. c. pv. malvacearum on congenic cotton lines carrying either of two different resistance loci, B1 or B4. Furthermore, the B1 locus appeared to confer R gene-for-avr genes resistance to cotton against isogenic X. c. pv. malvacearum strains carrying any one of three avr genes: avrB4, avrb6, or avrB102. Restriction enzyme, Southern blot hybridization, and DNA sequence analyses showed that the XcmH avr genes are all highly similar to each other, to avrBs3 and avrBsP from the pepper pathogen X. c. pv. vesicatoria, and to the host-specific virulence gene pthA from the citrus pathogen X. citri. The XcmH avr genes differed primarily in the multiplicity of a tandemly repeated 102-base pair motif within the central portions of the genes, repeated from 14 to 23 times in members of this gene family. The complete nucleotide sequence of avrb6 revealed that it is 97% identical in DNA sequence to avrB4, avrBs3, avrBsP, and pthA and that 62-bp inverted terminal repeats mark the boundaries of homology between avrb6 and all members of this Xanthomonas virulence/avirulence gene family sequenced to date. The terminal 38 bp of both inverted repeats are highly similar to the 38-bp consensus terminal sequence of the Tn3 family of transposons. Up to 11 members of the avr gene family appear to be present in North American strains of X. c. pv. malvacearum, including XcmH. The high level of homology observed among these avr genes and their presence in multiple copies may explain the gene-for-genes interactions and also the observed high frequencies (10(-3) to 10(-4) per locus) of X. c. pv. malvacearum race change mutations. Five spontaneous race change mutants of XcmH suffered avr locus deletions, strongly indicating intergenic recombination as the primary mechanism for generating new races in X. c. pv. malvacearum.

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

PubMed

Smith, Jennifer A; Zhao, Wei; Yasutake, Kalyn; August, Carmella; Ratliff, Scott M; Faul, Jessica D; Boerwinkle, Eric; Chakravarti, Aravinda; Diez Roux, Ana V; Gao, Yan; Griswold, Michael E; Heiss, Gerardo; Kardia, Sharon L R; Morrison, Alanna C; Musani, Solomon K; Mwasongwe, Stanford; North, Kari E; Rose, Kathryn M; Sims, Mario; Sun, Yan V; Weir, David R; Needham, Belinda L

2017-12-18

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

The Architecture of Parent-of-Origin Effects in Mice

PubMed Central

Mott, Richard; Yuan, Wei; Kaisaki, Pamela; Gan, Xiangchao; Cleak, James; Edwards, Andrew; Baud, Amelie; Flint, Jonathan

2014-01-01

Summary The number of imprinted genes in the mammalian genome is predicted to be small, yet we show here, in a survey of 97 traits measured in outbred mice, that most phenotypes display parent-of-origin effects that are partially confounded with family structure. To address this contradiction, using reciprocal F1 crosses, we investigated the effects of knocking out two nonimprinted candidate genes, Man1a2 and H2-ab1, that reside at nonimprinted loci but that show parent-of-origin effects. We show that expression of multiple genes becomes dysregulated in a sex-, tissue-, and parent-of-origin-dependent manner. We provide evidence that nonimprinted genes can generate parent-of-origin effects by interaction with imprinted loci and deduce that the importance of the number of imprinted genes is secondary to their interactions. We propose that this gene network effect may account for some of the missing heritability seen when comparing sibling-based to population-based studies of the phenotypic effects of genetic variants. PMID:24439386

Moderating role of the MAOA genotype in antisocial behaviour

PubMed Central

Fergusson, David M.; Boden, Joseph M.; Horwood, L. John; Miller, Allison; Kennedy, Martin A.

2012-01-01

Background Recent studies have examined gene×environment (G×E) interactions involving the monoamine oxidase A (MAOA) gene in moderating the associations between exposure to adversity and antisocial behaviour. The present study examined a novel method for assessing interactions between a single gene and multiple risk factors related to environmental and personal adversity. Aims To test the hypothesis that the presence of the low-activity MAOA genotype was associated with an increased response to a series of risk factors. Method Participants were 399 males from the Christchurch Health and Development Study who had complete data on: (a) MAOA promoter region variable number tandem repeat genotype; (b) antisocial behaviour (criminal offending) to age 30 and convictions to age 21; and (c) maternal smoking during pregnancy, IQ, childhood maltreatment and school failure. Results Poisson regression models were fitted to three antisocial behaviour outcomes (property/violent offending ages 15–30; and convictions ages 17–21), using measures of exposure to adverse childhood circumstances. The analyses revealed consistent evidence of G x E interactions, such that those with the low-activity MAOA variant who were exposed to adversity in childhood were significantly more likely to report offending in late adolescence and early adulthood. Conclusions The present findings add to the evidence suggesting that there is a stable G x E interaction involving MAOA, a range of adverse environmental and personal factors, and antisocial behaviour across the life course. These analyses also demonstrate the utility of using multiple environmental/personal exposures to test G×E interactions. PMID:22297589

Genetics Home Reference: familial pityriasis rubra pilaris

MedlinePlus

... interacting proteins known as nuclear factor-kappa-B (NF-κB). NF-κB regulates the activity of multiple genes, including ... but it is particularly abundant in the skin. NF-κB signaling appears to play an important role ...

Functional importance of different patterns of correlation between adjacent cassette exons in human and mouse.

PubMed

Peng, Tao; Xue, Chenghai; Bi, Jianning; Li, Tingting; Wang, Xiaowo; Zhang, Xuegong; Li, Yanda

2008-04-26

Alternative splicing expands transcriptome diversity and plays an important role in regulation of gene expression. Previous studies focus on the regulation of a single cassette exon, but recent experiments indicate that multiple cassette exons within a gene may interact with each other. This interaction can increase the potential to generate various transcripts and adds an extra layer of complexity to gene regulation. Several cases of exon interaction have been discovered. However, the extent to which the cassette exons coordinate with each other remains unknown. Based on EST data, we employed a metric of correlation coefficients to describe the interaction between two adjacent cassette exons and then categorized these exon pairs into three different groups by their interaction (correlation) patterns. Sequence analysis demonstrates that strongly-correlated groups are more conserved and contain a higher proportion of pairs with reading frame preservation in a combinatorial manner. Multiple genome comparison further indicates that different groups of correlated pairs have different evolutionary courses: (1) The vast majority of positively-correlated pairs are old, (2) most of the weakly-correlated pairs are relatively young, and (3) negatively-correlated pairs are a mixture of old and young events. We performed a large-scale analysis of interactions between adjacent cassette exons. Compared with weakly-correlated pairs, the strongly-correlated pairs, including both the positively and negatively correlated ones, show more evidence that they are under delicate splicing control and tend to be functionally important. Additionally, the positively-correlated pairs bear strong resemblance to constitutive exons, which suggests that they may evolve from ancient constitutive exons, while negatively and weakly correlated pairs are more likely to contain newly emerging exons.

Network-Assisted Investigation of Combined Causal Signals from Genome-Wide Association Studies in Schizophrenia

PubMed Central

Jia, Peilin; Wang, Lily; Fanous, Ayman H.; Pato, Carlos N.; Edwards, Todd L.; Zhao, Zhongming

2012-01-01

With the recent success of genome-wide association studies (GWAS), a wealth of association data has been accomplished for more than 200 complex diseases/traits, proposing a strong demand for data integration and interpretation. A combinatory analysis of multiple GWAS datasets, or an integrative analysis of GWAS data and other high-throughput data, has been particularly promising. In this study, we proposed an integrative analysis framework of multiple GWAS datasets by overlaying association signals onto the protein-protein interaction network, and demonstrated it using schizophrenia datasets. Building on a dense module search algorithm, we first searched for significantly enriched subnetworks for schizophrenia in each single GWAS dataset and then implemented a discovery-evaluation strategy to identify module genes with consistent association signals. We validated the module genes in an independent dataset, and also examined them through meta-analysis of the related SNPs using multiple GWAS datasets. As a result, we identified 205 module genes with a joint effect significantly associated with schizophrenia; these module genes included a number of well-studied candidate genes such as DISC1, GNA12, GNA13, GNAI1, GPR17, and GRIN2B. Further functional analysis suggested these genes are involved in neuronal related processes. Additionally, meta-analysis found that 18 SNPs in 9 module genes had P meta<1×10−4, including the gene HLA-DQA1 located in the MHC region on chromosome 6, which was reported in previous studies using the largest cohort of schizophrenia patients to date. These results demonstrated our bi-directional network-based strategy is efficient for identifying disease-associated genes with modest signals in GWAS datasets. This approach can be applied to any other complex diseases/traits where multiple GWAS datasets are available. PMID:22792057

Gene: a gene-centered information resource at NCBI.

PubMed

Brown, Garth R; Hem, Vichet; Katz, Kenneth S; Ovetsky, Michael; Wallin, Craig; Ermolaeva, Olga; Tolstoy, Igor; Tatusova, Tatiana; Pruitt, Kim D; Maglott, Donna R; Murphy, Terence D

2015-01-01

The National Center for Biotechnology Information's (NCBI) Gene database (www.ncbi.nlm.nih.gov/gene) integrates gene-specific information from multiple data sources. NCBI Reference Sequence (RefSeq) genomes for viruses, prokaryotes and eukaryotes are the primary foundation for Gene records in that they form the critical association between sequence and a tracked gene upon which additional functional and descriptive content is anchored. Additional content is integrated based on the genomic location and RefSeq transcript and protein sequence data. The content of a Gene record represents the integration of curation and automated processing from RefSeq, collaborating model organism databases, consortia such as Gene Ontology, and other databases within NCBI. Records in Gene are assigned unique, tracked integers as identifiers. The content (citations, nomenclature, genomic location, gene products and their attributes, phenotypes, sequences, interactions, variation details, maps, expression, homologs, protein domains and external databases) is available via interactive browsing through NCBI's Entrez system, via NCBI's Entrez programming utilities (E-Utilities and Entrez Direct) and for bulk transfer by FTP. Published by Oxford University Press on behalf of Nucleic Acids Research 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Functional and Genomic Features of Human Genes Mutated in Neuropsychiatric Disorders.

PubMed

Forero, Diego A; Prada, Carlos F; Perry, George

2016-01-01

In recent years, a large number of studies around the world have led to the identification of causal genes for hereditary types of common and rare neurological and psychiatric disorders. To explore the functional and genomic features of known human genes mutated in neuropsychiatric disorders. A systematic search was used to develop a comprehensive catalog of genes mutated in neuropsychiatric disorders (NPD). Functional enrichment and protein-protein interaction analyses were carried out. A false discovery rate approach was used for correction for multiple testing. We found several functional categories that are enriched among NPD genes, such as gene ontologies, protein domains, tissue expression, signaling pathways and regulation by brain-expressed miRNAs and transcription factors. Sixty six of those NPD genes are known to be druggable. Several topographic parameters of protein-protein interaction networks and the degree of conservation between orthologous genes were identified as significant among NPD genes. These results represent one of the first analyses of enrichment of functional categories of genes known to harbor mutations for NPD. These findings could be useful for a future creation of computational tools for prioritization of novel candidate genes for NPD.

Functional and Genomic Features of Human Genes Mutated in Neuropsychiatric Disorders

PubMed Central

Forero, Diego A.; Prada, Carlos F.; Perry, George

2016-01-01

Background: In recent years, a large number of studies around the world have led to the identification of causal genes for hereditary types of common and rare neurological and psychiatric disorders. Objective: To explore the functional and genomic features of known human genes mutated in neuropsychiatric disorders. Methods: A systematic search was used to develop a comprehensive catalog of genes mutated in neuropsychiatric disorders (NPD). Functional enrichment and protein-protein interaction analyses were carried out. A false discovery rate approach was used for correction for multiple testing. Results: We found several functional categories that are enriched among NPD genes, such as gene ontologies, protein domains, tissue expression, signaling pathways and regulation by brain-expressed miRNAs and transcription factors. Sixty six of those NPD genes are known to be druggable. Several topographic parameters of protein-protein interaction networks and the degree of conservation between orthologous genes were identified as significant among NPD genes. Conclusion: These results represent one of the first analyses of enrichment of functional categories of genes known to harbor mutations for NPD. These findings could be useful for a future creation of computational tools for prioritization of novel candidate genes for NPD. PMID:27990183

Prior knowledge based mining functional modules from Yeast PPI networks with gene ontology

PubMed Central

2010-01-01

Background In the literature, there are fruitful algorithmic approaches for identification functional modules in protein-protein interactions (PPI) networks. Because of accumulation of large-scale interaction data on multiple organisms and non-recording interaction data in the existing PPI database, it is still emergent to design novel computational techniques that can be able to correctly and scalably analyze interaction data sets. Indeed there are a number of large scale biological data sets providing indirect evidence for protein-protein interaction relationships. Results The main aim of this paper is to present a prior knowledge based mining strategy to identify functional modules from PPI networks with the aid of Gene Ontology. Higher similarity value in Gene Ontology means that two gene products are more functionally related to each other, so it is better to group such gene products into one functional module. We study (i) to encode the functional pairs into the existing PPI networks; and (ii) to use these functional pairs as pairwise constraints to supervise the existing functional module identification algorithms. Topology-based modularity metric and complex annotation in MIPs will be used to evaluate the identified functional modules by these two approaches. Conclusions The experimental results on Yeast PPI networks and GO have shown that the prior knowledge based learning methods perform better than the existing algorithms. PMID:21172053

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

PubMed

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

2016-03-30

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

Genes uniquely expressed in human growth plate chondrocytes uncover a distinct regulatory network.

PubMed

Li, Bing; Balasubramanian, Karthika; Krakow, Deborah; Cohn, Daniel H

2017-12-20

Chondrogenesis is the earliest stage of skeletal development and is a highly dynamic process, integrating the activities and functions of transcription factors, cell signaling molecules and extracellular matrix proteins. The molecular mechanisms underlying chondrogenesis have been extensively studied and multiple key regulators of this process have been identified. However, a genome-wide overview of the gene regulatory network in chondrogenesis has not been achieved. In this study, employing RNA sequencing, we identified 332 protein coding genes and 34 long non-coding RNA (lncRNA) genes that are highly selectively expressed in human fetal growth plate chondrocytes. Among the protein coding genes, 32 genes were associated with 62 distinct human skeletal disorders and 153 genes were associated with skeletal defects in knockout mice, confirming their essential roles in skeletal formation. These gene products formed a comprehensive physical interaction network and participated in multiple cellular processes regulating skeletal development. The data also revealed 34 transcription factors and 11,334 distal enhancers that were uniquely active in chondrocytes, functioning as transcriptional regulators for the cartilage-selective genes. Our findings revealed a complex gene regulatory network controlling skeletal development whereby transcription factors, enhancers and lncRNAs participate in chondrogenesis by transcriptional regulation of key genes. Additionally, the cartilage-selective genes represent candidate genes for unsolved human skeletal disorders.

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

PubMed Central

McKinney, Brett A.; White, Bill C.; Grill, Diane E.; Li, Peter W.; Kennedy, Richard B.; Poland, Gregory A.; Oberg, Ann L.

2013-01-01

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 detect both main effects and interaction effects. Software Availability: http://insilico.utulsa.edu/ReliefSeq.php. PMID:24339943

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

PubMed

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, we provide experimental evidence suggesting that the identified candidates do regulate the target genes predicted by GFlasso. Thus, this structured association analysis of a yeast eQTL dataset via GFlasso, coupled with extensive bioinformatics analysis, discovers a novel regulation pattern between multiple eQTL hotspots and functional gene modules. Furthermore, this analysis demonstrates the potential of GFlasso as a powerful computational tool for eQTL studies that exploit the rich structural information among expression traits due to correlation, regulation, or other forms of biological dependencies.

The same pocket in menin binds both MLL and JUND but has opposite effects on transcription

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

Huang, Jing; Gurung, Buddha; Wan, Bingbing

2013-04-08

Menin is a tumour suppressor protein whose loss or inactivation causes multiple endocrine neoplasia 1 (MEN1), a hereditary autosomal dominant tumour syndrome that is characterized by tumorigenesis in multiple endocrine organs. Menin interacts with many proteins and is involved in a variety of cellular processes. Menin binds the JUN family transcription factor JUND and inhibits its transcriptional activity. Several MEN1 missense mutations disrupt the menin-JUND interaction, suggesting a correlation between the tumour-suppressor function of menin and its suppression of JUND-activated transcription. Menin also interacts with mixed lineage leukaemia protein 1 (MLL1), a histone H3 lysine 4 methyltransferase, and functions asmore » an oncogenic cofactor to upregulate gene transcription and promote MLL1-fusion-protein-induced leukaemogenesis. A recent report on the tethering of MLL1 to chromatin binding factor lens epithelium-derived growth factor (LEDGF) by menin indicates that menin is a molecular adaptor coordinating the functions of multiple proteins. Despite its importance, how menin interacts with many distinct partners and regulates their functions remains poorly understood. Here we present the crystal structures of human menin in its free form and in complexes with MLL1 or with JUND, or with an MLL1-LEDGF heterodimer. These structures show that menin contains a deep pocket that binds short peptides of MLL1 or JUND in the same manner, but that it can have opposite effects on transcription. The menin-JUND interaction blocks JUN N-terminal kinase (JNK)-mediated JUND phosphorylation and suppresses JUND-induced transcription. In contrast, menin promotes gene transcription by binding the transcription activator MLL1 through the peptide pocket while still interacting with the chromatin-anchoring protein LEDGF at a distinct surface formed by both menin and MLL1.« less

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

PubMed Central

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

2012-01-01

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

Mechanism of Mediator recruitment by tandem Gcn4 activation domains and three Gal11 activator-binding domains.

PubMed

Herbig, Eric; Warfield, Linda; Fish, Lisa; Fishburn, James; Knutson, Bruce A; Moorefield, Beth; Pacheco, Derek; Hahn, Steven

2010-05-01

Targets of the tandem Gcn4 acidic activation domains in transcription preinitiation complexes were identified by site-specific cross-linking. The individual Gcn4 activation domains cross-link to three common targets, Gal11/Med15, Taf12, and Tra1, which are subunits of four conserved coactivator complexes, Mediator, SAGA, TFIID, and NuA4. The Gcn4 N-terminal activation domain also cross-links to the Mediator subunit Sin4/Med16. The contribution of the two Gcn4 activation domains to transcription was gene specific and varied from synergistic to less than additive. Gcn4-dependent genes had a requirement for Gal11 ranging from 10-fold dependence to complete Gal11 independence, while the Gcn4-Taf12 interaction did not significantly contribute to the expression of any gene studied. Complementary methods identified three conserved Gal11 activator-binding domains that bind each Gcn4 activation domain with micromolar affinity. These Gal11 activator-binding domains contribute additively to transcription activation and Mediator recruitment at Gcn4- and Gal11-dependent genes. Although we found that the conserved Gal11 KIX domain contributes to Gal11 function, we found no evidence of specific Gcn4-KIX interaction and conclude that the Gal11 KIX domain does not function by specific interaction with Gcn4. Our combined results show gene-specific coactivator requirements, a surprising redundancy in activator-target interactions, and an activator-coactivator interaction mediated by multiple low-affinity protein-protein interactions.

Identification of five novel modifier loci of ApcMin harbored in the BXH14 recombinant inbred strain

PubMed Central

Siracusa, Linda D.

2012-01-01

Every year thousands of people in the USA are diagnosed with small intestine and colorectal cancers (CRC). Although environmental factors affect disease etiology, uncovering underlying genetic factors is imperative for risk assessment and developing preventative therapies. Familial adenomatous polyposis is a heritable genetic disorder in which individuals carry germ-line mutations in the adenomatous polyposis coli (APC) gene that predisposes them to CRC. The Apc Min mouse model carries a point mutation in the Apc gene and develops polyps along the intestinal tract. Inbred strain background influences polyp phenotypes in Apc Min mice. Several Modifier of Min (Mom) loci that alter tumor phenotypes associated with the Apc Min mutation have been identified to date. We screened BXH recombinant inbred (RI) strains by crossing BXH RI females with C57BL/6J (B6) Apc Min males and quantitating tumor phenotypes in backcross progeny. We found that the BXH14 RI strain harbors five modifier loci that decrease polyp multiplicity. Furthermore, we show that resistance is determined by varying combinations of these modifier loci. Gene interaction network analysis shows that there are multiple networks with proven gene–gene interactions, which contain genes from all five modifier loci. We discuss the implications of this result for studies that define susceptibility loci, namely that multiple networks may be acting concurrently to alter tumor phenotypes. Thus, the significance of this work resides not only with the modifier loci we identified but also with the combinations of loci needed to get maximal protection against polyposis and the impact of this finding on human disease studies. Abbreviations:APCadenomatous polyposis coliGWASgenome-wide association studiesQTLquantitative trait lociSNPsingle-nucleotide polymorphism. PMID:22637734

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

PubMed Central

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

2016-01-01

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

Network pharmacology-based prediction of active compounds and molecular targets in Yijin-Tang acting on hyperlipidaemia and atherosclerosis.

PubMed

Lee, A Yeong; Park, Won; Kang, Tae-Wook; Cha, Min Ho; Chun, Jin Mi

2018-07-15

Yijin-Tang (YJT) is a traditional prescription for the treatment of hyperlipidaemia, atherosclerosis and other ailments related to dampness phlegm, a typical pathological symptom of abnormal body fluid metabolism in Traditional Korean Medicine. However, a holistic network pharmacology approach to understanding the therapeutic mechanisms underlying hyperlipidaemia and atherosclerosis has not been pursued. To examine the network pharmacological potential effects of YJT on hyperlipidaemia and atherosclerosis, we analysed components, performed target prediction and network analysis, and investigated interacting pathways using a network pharmacology approach. Information on compounds in herbal medicines was obtained from public databases, and oral bioavailability and drug-likeness was screened using absorption, distribution, metabolism, and excretion (ADME) criteria. Correlations between compounds and genes were linked using the STITCH database, and genes related to hyperlipidaemia and atherosclerosis were gathered using the GeneCards database. Human genes were identified and subjected to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Network analysis identified 447 compounds in five herbal medicines that were subjected to ADME screening, and 21 compounds and 57 genes formed the main pathways linked to hyperlipidaemia and atherosclerosis. Among them, 10 compounds (naringenin, nobiletin, hesperidin, galangin, glycyrrhizin, homogentisic acid, stigmasterol, 6-gingerol, quercetin and glabridin) were linked to more than four genes, and are bioactive compounds and key chemicals. Core genes in this network were CASP3, CYP1A1, CYP1A2, MMP2 and MMP9. The compound-target gene network revealed close interactions between multiple components and multiple targets, and facilitates a better understanding of the potential therapeutic effects of YJT. Pharmacological network analysis can help to explain the potential effects of YJT for treating dampness phlegm-related diseases such as hyperlipidaemia and atherosclerosis. Copyright © 2018 Elsevier B.V. All rights reserved.

Role of DISC1 interacting proteins in schizophrenia risk from genome-wide analysis of missense SNPs.

PubMed

Costas, Javier; Suárez-Rama, Jose Javier; Carrera, Noa; Paz, Eduardo; Páramo, Mario; Agra, Santiago; Brenlla, Julio; Ramos-Ríos, Ramón; Arrojo, Manuel

2013-11-01

A balanced translocation affecting DISC1 cosegregates with several psychiatric disorders, including schizophrenia, in a Scottish family. DISC1 is a hub protein of a network of protein-protein interactions involved in multiple developmental pathways within the brain. Gene set-based analysis has been proposed as an alternative to individual analysis of single nucleotide polymorphisms (SNPs) to get information from genome-wide association studies. In this work, we tested for an overrepresentation of the DISC1 interacting proteins within the top results of our ranked list of genes based on our previous genome-wide association study of missense SNPs in schizophrenia. Our data set consisted of 5100 common missense SNPs genotyped in 476 schizophrenic patients and 447 control subjects from Galicia, NW Spain. We used a modification of the Gene Set Enrichment Analysis adapted for SNPs, as implemented in the GenGen software. The analysis detected an overrepresentation of the DISC1 interacting proteins (permuted P-value=0.0158), indicative of the role of this gene set in schizophrenia risk. We identified seven leading-edge genes, MACF1, UTRN, DST, DISC1, KIF3A, SYNE1, and AKAP9, responsible for the overrepresentation. These genes are involved in neuronal cytoskeleton organization and intracellular transport through the microtubule cytoskeleton, suggesting that these processes may be impaired in schizophrenia. © 2013 John Wiley & Sons Ltd/University College London.

Gene-Environment Interplay in Common Complex Diseases: Forging an Integrative Model—Recommendations From an NIH Workshop

PubMed Central

Bookman, Ebony B.; McAllister, Kimberly; Gillanders, Elizabeth; Wanke, Kay; Balshaw, David; Rutter, Joni; Reedy, Jill; Shaughnessy, Daniel; Agurs-Collins, Tanya; Paltoo, Dina; Atienza, Audie; Bierut, Laura; Kraft, Peter; Fallin, M. Daniele; Perera, Frederica; Turkheimer, Eric; Boardman, Jason; Marazita, Mary L.; Rappaport, Stephen M.; Boerwinkle, Eric; Suomi, Stephen J.; Caporaso, Neil E.; Hertz-Picciotto, Irva; Jacobson, Kristen C.; Lowe, William L.; Goldman, Lynn R.; Duggal, Priya; Gunnar, Megan R.; Manolio, Teri A.; Green, Eric D.; Olster, Deborah H.; Birnbaum, Linda S.

2011-01-01

Although it is recognized that many common complex diseases are a result of multiple genetic and environmental risk factors, studies of gene-environment interaction remain a challenge and have had limited success to date. Given the current state-of-the-science, NIH sought input on ways to accelerate investigations of gene-environment interplay in health and disease by inviting experts from a variety of disciplines to give advice about the future direction of gene-environment interaction studies. Participants of the NIH Gene-Environment Interplay Workshop agreed that there is a need for continued emphasis on studies of the interplay between genetic and environmental factors in disease and that studies need to be designed around a multifaceted approach to reflect differences in diseases, exposure attributes, and pertinent stages of human development. The participants indicated that both targeted and agnostic approaches have strengths and weaknesses for evaluating main effects of genetic and environmental factors and their interactions. The unique perspectives represented at the workshop allowed the exploration of diverse study designs and analytical strategies, and conveyed the need for an interdisciplinary approach including data sharing, and data harmonization to fully explore gene-environment interactions. Further, participants also emphasized the continued need for high-quality measures of environmental exposures and new genomic technologies in ongoing and new studies. PMID:21308768

Cellular and synaptic network defects in autism

PubMed Central

Peça, João; Feng, Guoping

2012-01-01

Many candidate genes are now thought to confer susceptibility to autism spectrum disorder (ASD). Here we review four interrelated complexes, each composed of multiple families of genes that functionally coalesce on common cellular pathways. We illustrate a common thread in the organization of glutamatergic synapses and suggest a link between genes involved in Tuberous Sclerosis Complex, Fragile X syndrome, Angelman syndrome and several synaptic ASD candidate genes. When viewed in this context, progress in deciphering the molecular architecture of cellular protein-protein interactions together with the unraveling of synaptic dysfunction in neural networks may prove pivotal to advancing our understanding of ASDs. PMID:22440525

Dissecting DNA repair in adult high grade gliomas for patient stratification in the post-genomic era

PubMed Central

Perry, Christina; Agarwal, Devika; Abdel-Fatah, Tarek M.A.; Lourdusamy, Anbarasu; Grundy, Richard; Auer, Dorothee T.; Walker, David; Lakhani, Ravi; Scott, Ian S.; Chan, Stephen; Ball, Graham; Madhusudan, Srinivasan

2014-01-01

Deregulation of multiple DNA repair pathways may contribute to aggressive biology and therapy resistance in gliomas. We evaluated transcript levels of 157 genes involved in DNA repair in an adult glioblastoma Test set (n=191) and validated in ‘The Cancer Genome Atlas’ (TCGA) cohort (n=508). A DNA repair prognostic index model was generated. Artificial neural network analysis (ANN) was conducted to investigate global gene interactions. Protein expression by immunohistochemistry was conducted in 61 tumours. A fourteen DNA repair gene expression panel was associated with poor survival in Test and TCGA cohorts. A Cox multivariate model revealed APE1, NBN, PMS2, MGMT and PTEN as independently associated with poor prognosis. A DNA repair prognostic index incorporating APE1, NBN, PMS2, MGMT and PTEN stratified patients in to three prognostic sub-groups with worsening survival. APE1, NBN, PMS2, MGMT and PTEN also have predictive significance in patients who received chemotherapy and/or radiotherapy. ANN analysis of APE1, NBN, PMS2, MGMT and PTEN revealed interactions with genes involved in transcription, hypoxia and metabolic regulation. At the protein level, low APE1 and low PTEN remain associated with poor prognosis. In conclusion, multiple DNA repair pathways operate to influence biology and clinical outcomes in adult high grade gliomas. PMID:25026297

AURKA Phe31Ile polymorphism interacted with use of alcohol, betel quid, and cigarettes at multiplicative risk of oral cancer occurrence.

PubMed

Lee, Chi-Pin; Chiang, Shang-Lun; Lee, Chien-Hung; Tsai, Yi-Shan; Wang, Zhi-Hong; Hua, Chun-Hung; Chen, Yuan-Chien; Tsai, Eing-Mei; Ko, Ying-Chin

2015-11-01

The expression levels of two DNA repair genes (CHAF1A and CHAF1B) and a chromosome segregation gene (AURKA) were susceptible to arecoline exposure, a major alkaloid of areca nut. We hypothesize that genetic variants of these genes might also be implicated in the risk of oral cancer and could be modified by substance use of betel quid or alcohol and cigarettes. A case-control study, which included 507 patients with oral cancer and 717 matched controls, was performed in order to evaluate the cancer susceptibility by the tagging single-nucleotide polymorphisms (tagSNPs) in AURKA, CHAF1A, and CHAF1B using a genotyping assay and gene-environment interaction analysis. The Phe31Ile polymorphism (rs2273535, T91A) of AURKA was significantly associated with an increased risk of oral cancer (odds ratio (OR) = 2.1, 95% confidence interval (CI) 1.2-3.5). The gene dosage of the 91A allele also showed a significant trend in risk of oral cancer (P = 0.008). Furthermore, we found the AURKA 91AA homozygote was modifiable by substance use of alcohol, betel quid, and cigarettes (ABC), leading to increased risk of oral cancer in an additive or a multiplicative model (combined effect indexes = 1.2-4.0 and 1.5-2.2, respectively). However, no association was observed between the genetic variants of CHAF1A or CHAF1B and oral cancer risk in the study. These findings reveal the functional Phe31Ile polymorphism tagSNP of AURKA may be a strong susceptibility gene in ABC-related oral cancer occurrence. The results of this betel-related oral cancer study provide the evidence of environment-gene interaction for early prediction and molecular diagnosis.

Interactions of GST Polymorphisms in Air Pollution Exposure and Respiratory Diseases and Allergies.

PubMed

Bowatte, Gayan; Lodge, Caroline J; Perret, Jennifer L; Matheson, Melanie C; Dharmage, Shyamali C

2016-11-01

The purpose of this review is to summarize the evidence from recently published original studies investigating how glutathione S-transferase (GST) gene polymorphisms modify the impact of air pollution on asthma, allergic diseases, and lung function. Current studies in epidemiological and controlled human experiments found evidence to suggest that GSTs modify the impact of air pollution exposure on respiratory diseases and allergies. Of the nine articles included in this review, all except one identified at least one significant interaction with at least one of glutathione S-transferase pi 1 (GSTP1), glutathione S-transferase mu 1 (GSTM1), or glutathione S-transferase theta 1 (GSTT1) genes and air pollution exposure. The findings of these studies, however, are markedly different. This difference can be partially explained by regional variation in the exposure levels and oxidative potential of different pollutants and by other interactions involving a number of unaccounted environment exposures and multiple genes. Although there is evidence of an interaction between GST genes and air pollution exposure for the risk of respiratory disease and allergies, results are not concordant. Further investigations are needed to explore the reasons behind the discordancy.

Ecological engineering helps maximize function in algal oil production.

PubMed

Jackrel, Sara L; Narwani, Anita; Bentlage, Bastian; Levine, Robert B; Hietala, David C; Savage, Phillip E; Oakley, Todd H; Denef, Vincent J; Cardinale, Bradley J

2018-05-18

Algal biofuels have the potential to curb emissions of greenhouse gases from fossil fuels, but current growing methods fail to produce fuels that meet the multiple standards necessary for economical industrial use. For example, algae grown as monocultures for biofuel production have not simultaneously and economically achieved high yields of the high-quality, lipid-rich biomass desired for the industrial-scale production of bio-oil. Decades of study in the field of ecology have demonstrated that simultaneous increases in multiple functions, such as the quantity and quality of biomass, can occur in natural ecosystems by increasing biological diversity. Here we show that species consortia of algae can improve the production of bio-oil, which benefits from both high biomass yield and high quality of biomass rich in fatty acids. We explain the underlying causes of increased quantity and quality of algal biomass among species consortia by showing that, relative to monocultures, species consortia can differentially regulate lipid metabolism genes while growing to higher levels of biomass, in part due to greater utilization of nutrient resources. We identify multiple genes involved in lipid biosynthesis that are frequently upregulated in bicultures, and further show that these elevated levels of gene expression are highly predictive of the elevated levels in biculture relative to monoculture of multiple quality metrics of algal biomass. These results show that interactions between species can alter the expression of lipid metabolism genes, and further demonstrate that our understanding of diversity-function relationships from natural ecosystems can be harnessed to improve production of bio-oil. Importance section: Algal biofuels are one of the more promising forms of renewable energy. In our study, we investigate whether ecological interactions between species of microalgae regulate two important factors in cultivation - the biomass of the crop produced and quality of the biomass that is produced. We find that species interactions often improved production yields, especially the fatty acid content of the algal biomass, and that differentially expressed genes involved in fatty acid metabolism are predictive of improved quality metrics of bio-oil. Other studies have found that diversity often improves productivity and stability in agricultural and natural ecosystems. Our results provide further evidence that growing multi-species crops of microalgae may improve the production of high-quality biomass for bio-oil. Copyright © 2018 American Society for Microbiology.

Nuclear Organization and Myt1 Interaction in Transcriptional Control of Neural Cell Differentiation

DTIC Science & Technology

2002-01-01

secreted from the notochord and floor plate [4]. Oligodendrocytes also respond to cell contact- dependent interactions from the notch-signaling pathway...appendix A 1 mature oligodendrocytes sending out multiple processes to begin myelinating axons primarily during the postnatal period of...snRNA transcription [32]. 7 Gene regulation also occurs post-transcriptionally in processes such as RNA splicing. Many splicing factors are

Latent variable models for gene-environment interactions in longitudinal studies with multiple correlated exposures.

PubMed

Tao, Yebin; Sánchez, Brisa N; Mukherjee, Bhramar

2015-03-30

Many existing cohort studies designed to investigate health effects of environmental exposures also collect data on genetic markers. The Early Life Exposures in Mexico to Environmental Toxicants project, for instance, has been genotyping single nucleotide polymorphisms on candidate genes involved in mental and nutrient metabolism and also in potentially shared metabolic pathways with the environmental exposures. Given the longitudinal nature of these cohort studies, rich exposure and outcome data are available to address novel questions regarding gene-environment interaction (G × E). Latent variable (LV) models have been effectively used for dimension reduction, helping with multiple testing and multicollinearity issues in the presence of correlated multivariate exposures and outcomes. In this paper, we first propose a modeling strategy, based on LV models, to examine the association between repeated outcome measures (e.g., child weight) and a set of correlated exposure biomarkers (e.g., prenatal lead exposure). We then construct novel tests for G × E effects within the LV framework to examine effect modification of outcome-exposure association by genetic factors (e.g., the hemochromatosis gene). We consider two scenarios: one allowing dependence of the LV models on genes and the other assuming independence between the LV models and genes. We combine the two sets of estimates by shrinkage estimation to trade off bias and efficiency in a data-adaptive way. Using simulations, we evaluate the properties of the shrinkage estimates, and in particular, we demonstrate the need for this data-adaptive shrinkage given repeated outcome measures, exposure measures possibly repeated and time-varying gene-environment association. Copyright © 2014 John Wiley & Sons, Ltd.

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

PubMed

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

2013-01-01

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

Association Between Four Polymorphisms in lncRNA and Risk of Lung Cancer in a Chinese Never-Smoking Female Population.

PubMed

Gao, Min; Li, Hang; Lv, Xiaoting; Zhou, Baosen; Yin, Zhihua

2018-06-07

Long noncoding RNAs (lncRNAs) play important roles in the development of human cancers. This is the first case-control study of the association between specific polymorphisms in lncRNA genes and the risk of lung cancer, as well as the gene-environment interaction between the polymorphisms and cooking oil fume exposure in Chinese never-smoking females. A hospital-based case-control study was carried out in Shenyang, Liaoning province. The study included 395 cases and 556 controls. The polymorphisms of rs4785367, rs3803662, rs10750417, and rs1814343 in lncRNA genes were analyzed. The gene-environment interactions were explored on both additive and multiplicative scale. In addition, the results were listed as follows: for rs3803662, compared with the individuals carrying homozygous TT genotype, those with homozygous CC genotype had the decreased risk of lung cancer (adjusted odds ratio [OR] = 0.61, 95% confidence interval [CI] = 0.40-0.92, p = 0.018). As for rs4785367, compared with homozygous TT, homozygous CC could lessen the risk of lung cancer (adjusted OR = 0.54, 95% CI = 0.33-0.89, p = 0.016). The recessive models of rs3803662 and rs4785367 showed significant association (adjusted OR = 0.65, 95% CIs = 0.44-0.97, p = 0.033; adjusted OR = 0.54, 95% CIs = 0.33-0.88, p = 0.014). The C allele of rs3803662 was suggested to be protective allele of lung cancer (adjusted OR = 0.80, 95% CI = 0.66-0.97, p = 0.023). However, rs10750417 and rs1814343 polymorphisms were not significantly associated with lung cancer risks. The measures of additive interaction and logistic models suggested that the gene-environment interactions were not statistically significant on both additive and multiplicative scales.

Saturated fat intake modulates the association between an obesity genetic risk score and body mass index in two US populations.

PubMed

Casas-Agustench, Patricia; Arnett, Donna K; Smith, Caren E; Lai, Chao-Qiang; Parnell, Laurence D; Borecki, Ingrid B; Frazier-Wood, Alexis C; Allison, Matthew; Chen, Yii-Der Ida; Taylor, Kent D; Rich, Stephen S; Rotter, Jerome I; Lee, Yu-Chi; Ordovás, José M

2014-12-01

Combining multiple genetic variants related to obesity into a genetic risk score (GRS) might improve identification of individuals at risk of developing obesity. Moreover, characterizing gene-diet interactions is a research challenge to establish dietary recommendations to individuals with higher predisposition to obesity. Our objective was to analyze the association between an obesity GRS and body mass index (BMI) in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) population, focusing on gene-diet interactions with total fat and saturated fatty acid (SFA) intake, and to replicate findings in the Multi-Ethnic Study of Atherosclerosis (MESA) population. Cross-sectional analyses included 783 white US participants from GOLDN and 2,035 from MESA. Dietary intakes were estimated with validated food frequency questionnaires. Height and weight were measured. A weighted GRS was calculated on the basis of 63 obesity-associated variants. Multiple linear regression models adjusted by potential confounders were used to examine gene-diet interactions between dietary intake (total fat and SFA) and the obesity GRS in determining BMI. Significant interactions were found between total fat intake and the obesity GRS using these variables as continuous for BMI (P for interaction=0.010, 0.046, and 0.002 in GOLDN, MESA, and meta-analysis, respectively). These association terms were stronger when assessing interactions between SFA intake and GRS for BMI (P for interaction=0.005, 0.018, and <0.001 in GOLDN, MESA, and meta-analysis, respectively). SFA intake interacts with an obesity GRS in modulating BMI in two US populations. Although determining the causal direction requires further investigation, these findings suggest that potential dietary recommendations to reduce BMI effectively in populations with high obesity GRS would be to reduce total fat intake mainly by limiting SFAs. Copyright © 2014 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

Genome-wide Analysis of the H3K4 Histone Demethylase RBP2 Reveals a Transcriptional Program Controlling Differentiation

PubMed Central

Lopez-Bigas, Nuria; Kisiel, Tomasz A.; DeWaal, Dannielle C.; Holmes, Katie B.; Volkert, Tom L.; Gupta, Sumeet; Love, Jennifer; Murray, Heather L.; Young, Richard A.; Benevolenskaya, Elizaveta V.

2010-01-01

SUMMARY Retinoblastoma protein (pRB) mediates cell-cycle withdrawal and differentiation by interacting with a variety of proteins. RB-Binding Protein 2 (RBP2) has been shown to be a key effector. We sought to determine transcriptional regulation by RBP2 genome-wide by using location analysis and gene expression profiling experiments. We describe that RBP2 shows high correlation with the presence of H3K4me3 and its target genes are separated into two functionally distinct classes: differentiation-independent and differentiation-dependent genes. The former class is enriched by genes that encode mitochondrial proteins, while the latter is represented by cell-cycle genes. We demonstrate the role of RBP2 in mitochondrial biogenesis, which involves regulation of H3K4me3-modified nucleosomes. Analysis of expression changes upon RBP2 depletion depicted genes with a signature of differentiation control, analogous to the changes seen upon reintroduction of pRB. We conclude that, during differentiation, RBP2 exerts inhibitory effects on multiple genes through direct interaction with their promoters. PMID:18722178

Bellerophon: a program to detect chimeric sequences in multiple sequence alignments.

PubMed

Huber, Thomas; Faulkner, Geoffrey; Hugenholtz, Philip

2004-09-22

Bellerophon is a program for detecting chimeric sequences in multiple sequence datasets by an adaption of partial treeing analysis. Bellerophon was specifically developed to detect 16S rRNA gene chimeras in PCR-clone libraries of environmental samples but can be applied to other nucleotide sequence alignments. Bellerophon is available as an interactive web server at http://foo.maths.uq.edu.au/~huber/bellerophon.pl

MAPK genes interact with diet and lifestyle factors to alter risk of breast cancer: The Breast Cancer Health Disparities Study

PubMed Central

Slattery, Martha L.; Lundgreen, Abbie; John, Esther M.; Torres-Mejia, Gabriela; Hines, Lisa; Giuliano, Anna R.; Baumgartner, Kathy B.; Stern, Mariana C.; Wolff, Roger K.

2015-01-01

Mitogen-activated protein kinases (MAPK) are integration points for multiple biochemical signals. We evaluated 13 MAPK genes with breast cancer risk and determined if diet and lifestyle factors mediated risk. Data from three population-based case-control studies conducted in Southwestern United States, California, and Mexico included 4183 controls and 3592 cases. Percent Indigenous American (IA) ancestry was determined from 104 Ancestry Informative Markers. The adaptive rank truncated product (ARTP) was used to determine the significance of each gene and the pathway with breast cancer risk, by menopausal status, genetic ancestry level, and ER/PR strata. MAP3K9 was associated with breast cancer overall (PARTP=0.02) with strongest association among women with the highest IA ancestry (PARTP=0.04). Several SNPs in MAP3K9 were associated with ER+/PR+ tumors and interacted with dietary oxidative balance score (DOBS), dietary folate, body mass index (BMI), alcohol consumption, cigarette smoking, and a history of diabetes. DUSP4 and MAPK8 interacted with calories to alter breast cancer risk; MAPK1 interacted with DOBS, dietary fiber, folate and BMI; MAP3K2 interacted with dietary fat; and MAPK14 interacted with dietary folate and BMI. The patterns of association across diet and lifestyle factors with similar biological properties for the same SNPs within genes provide support for associations. PMID:25629224

A multicolor panel of novel lentiviral "gene ontology" (LeGO) vectors for functional gene analysis.

PubMed

Weber, Kristoffer; Bartsch, Udo; Stocking, Carol; Fehse, Boris

2008-04-01

Functional gene analysis requires the possibility of overexpression, as well as downregulation of one, or ideally several, potentially interacting genes. Lentiviral vectors are well suited for this purpose as they ensure stable expression of complementary DNAs (cDNAs), as well as short-hairpin RNAs (shRNAs), and can efficiently transduce a wide spectrum of cell targets when packaged within the coat proteins of other viruses. Here we introduce a multicolor panel of novel lentiviral "gene ontology" (LeGO) vectors designed according to the "building blocks" principle. Using a wide spectrum of different fluorescent markers, including drug-selectable enhanced green fluorescent protein (eGFP)- and dTomato-blasticidin-S resistance fusion proteins, LeGO vectors allow simultaneous analysis of multiple genes and shRNAs of interest within single, easily identifiable cells. Furthermore, each functional module is flanked by unique cloning sites, ensuring flexibility and individual optimization. The efficacy of these vectors for analyzing multiple genes in a single cell was demonstrated in several different cell types, including hematopoietic, endothelial, and neural stem and progenitor cells, as well as hepatocytes. LeGO vectors thus represent a valuable tool for investigating gene networks using conditional ectopic expression and knock-down approaches simultaneously.

Changing the Game: Using Integrative Genomics to Probe Virulence Mechanisms of the Stem Rust Pathogen Puccinia graminis f. sp. tritici.

PubMed

Figueroa, Melania; Upadhyaya, Narayana M; Sperschneider, Jana; Park, Robert F; Szabo, Les J; Steffenson, Brian; Ellis, Jeff G; Dodds, Peter N

2016-01-01

The recent resurgence of wheat stem rust caused by new virulent races of Puccinia graminis f. sp. tritici (Pgt) poses a threat to food security. These concerns have catalyzed an extensive global effort toward controlling this disease. Substantial research and breeding programs target the identification and introduction of new stem rust resistance (Sr) genes in cultivars for genetic protection against the disease. Such resistance genes typically encode immune receptor proteins that recognize specific components of the pathogen, known as avirulence (Avr) proteins. A significant drawback to deploying cultivars with single Sr genes is that they are often overcome by evolution of the pathogen to escape recognition through alterations in Avr genes. Thus, a key element in achieving durable rust control is the deployment of multiple effective Sr genes in combination, either through conventional breeding or transgenic approaches, to minimize the risk of resistance breakdown. In this situation, evolution of pathogen virulence would require changes in multiple Avr genes in order to bypass recognition. However, choosing the optimal Sr gene combinations to deploy is a challenge that requires detailed knowledge of the pathogen Avr genes with which they interact and the virulence phenotypes of Pgt existing in nature. Identifying specific Avr genes from Pgt will provide screening tools to enhance pathogen virulence monitoring, assess heterozygosity and propensity for mutation in pathogen populations, and confirm individual Sr gene functions in crop varieties carrying multiple effective resistance genes. Toward this goal, much progress has been made in assembling a high quality reference genome sequence for Pgt, as well as a Pan-genome encompassing variation between multiple field isolates with diverse virulence spectra. In turn this has allowed prediction of Pgt effector gene candidates based on known features of Avr genes in other plant pathogens, including the related flax rust fungus. Upregulation of gene expression in haustoria and evidence for diversifying selection are two useful parameters to identify candidate Avr genes. Recently, we have also applied machine learning approaches to agnostically predict candidate effectors. Here, we review progress in stem rust pathogenomics and approaches currently underway to identify Avr genes recognized by wheat Sr genes.

Network-based analysis of differentially expressed genes in cerebrospinal fluid (CSF) and blood reveals new candidate genes for multiple sclerosis

PubMed Central

Safari-Alighiarloo, Nahid; Taghizadeh, Mohammad; Tabatabaei, Seyyed Mohammad; Namaki, Saeed

2016-01-01

Background The involvement of multiple genes and missing heritability, which are dominant in complex diseases such as multiple sclerosis (MS), entail using network biology to better elucidate their molecular basis and genetic factors. We therefore aimed to integrate interactome (protein–protein interaction (PPI)) and transcriptomes data to construct and analyze PPI networks for MS disease. Methods Gene expression profiles in paired cerebrospinal fluid (CSF) and peripheral blood mononuclear cells (PBMCs) samples from MS patients, sampled in relapse or remission and controls, were analyzed. Differentially expressed genes which determined only in CSF (MS vs. control) and PBMCs (relapse vs. remission) separately integrated with PPI data to construct the Query-Query PPI (QQPPI) networks. The networks were further analyzed to investigate more central genes, functional modules and complexes involved in MS progression. Results The networks were analyzed and high centrality genes were identified. Exploration of functional modules and complexes showed that the majority of high centrality genes incorporated in biological pathways driving MS pathogenesis. Proteasome and spliceosome were also noticeable in enriched pathways in PBMCs (relapse vs. remission) which were identified by both modularity and clique analyses. Finally, STK4, RB1, CDKN1A, CDK1, RAC1, EZH2, SDCBP genes in CSF (MS vs. control) and CDC37, MAP3K3, MYC genes in PBMCs (relapse vs. remission) were identified as potential candidate genes for MS, which were the more central genes involved in biological pathways. Discussion This study showed that network-based analysis could explicate the complex interplay between biological processes underlying MS. Furthermore, an experimental validation of candidate genes can lead to identification of potential therapeutic targets. PMID:28028462

Analyses of single nucleotide polymorphisms in selected nutrient-sensitive genes in weight-regain prevention: the DIOGENES study.

PubMed

Larsen, Lesli H; Angquist, Lars; Vimaleswaran, Karani S; Hager, Jörg; Viguerie, Nathalie; Loos, Ruth J F; Handjieva-Darlenska, Teodora; Jebb, Susan A; Kunesova, Marie; Larsen, Thomas M; Martinez, J Alfredo; Papadaki, Angeliki; Pfeiffer, Andreas F H; van Baak, Marleen A; Sørensen, Thorkild Ia; Holst, Claus; Langin, Dominique; Astrup, Arne; Saris, Wim H M

2012-05-01

Differences in the interindividual response to dietary intervention could be modified by genetic variation in nutrient-sensitive genes. This study examined single nucleotide polymorphisms (SNPs) in presumed nutrient-sensitive candidate genes for obesity and obesity-related diseases for main and dietary interaction effects on weight, waist circumference, and fat mass regain over 6 mo. In total, 742 participants who had lost ≥ 8% of their initial body weight were randomly assigned to follow 1 of 5 different ad libitum diets with different glycemic indexes and contents of dietary protein. The SNP main and SNP-diet interaction effects were analyzed by using linear regression models, corrected for multiple testing by using Bonferroni correction and evaluated by using quantile-quantile (Q-Q) plots. After correction for multiple testing, none of the SNPs were significantly associated with weight, waist circumference, or fat mass regain. Q-Q plots showed that ALOX5AP rs4769873 showed a higher observed than predicted P value for the association with less waist circumference regain over 6 mo (-3.1 cm/allele; 95% CI: -4.6, -1.6; P/Bonferroni-corrected P = 0.000039/0.076), independently of diet. Additional associations were identified by using Q-Q plots for SNPs in ALOX5AP, TNF, and KCNJ11 for main effects; in LPL and TUB for glycemic index interaction effects on waist circumference regain; in GHRL, CCK, MLXIPL, and LEPR on weight; in PPARC1A, PCK2, ALOX5AP, PYY, and ADRB3 on waist circumference; and in PPARD, FABP1, PLAUR, and LPIN1 on fat mass regain for dietary protein interaction. The observed effects of SNP-diet interactions on weight, waist, and fat mass regain suggest that genetic variation in nutrient-sensitive genes can modify the response to diet. This trial was registered at clinicaltrials.gov as NCT00390637.

A genome-wide trans-ethnic interaction study links the PIGR-FCAMR locus to coronary atherosclerosis via interactions between genetic variants and residential exposure to traffic

PubMed Central

Neas, Lucas M.; Blach, Colette; Haynes, Carol S.; LaRocque-Abramson, Karen; Grass, Elizabeth; Dowdy, Z. Elaine; Devlin, Robert B.; Diaz-Sanchez, David; Cascio, Wayne E.; Miranda, Marie Lynn; Gregory, Simon G.; Shah, Svati H.; Kraus, William E.; Hauser, Elizabeth R.

2017-01-01

Air pollution is a worldwide contributor to cardiovascular disease mortality and morbidity. Traffic-related air pollution is a widespread environmental exposure and is associated with multiple cardiovascular outcomes such as coronary atherosclerosis, peripheral arterial disease, and myocardial infarction. Despite the recognition of the importance of both genetic and environmental exposures to the pathogenesis of cardiovascular disease, studies of how these two contributors operate jointly are rare. We performed a genome-wide interaction study (GWIS) to examine gene-traffic exposure interactions associated with coronary atherosclerosis. Using race-stratified cohorts of 538 African-Americans (AA) and 1562 European-Americans (EA) from a cardiac catheterization cohort (CATHGEN), we identify gene-by-traffic exposure interactions associated with the number of significantly diseased coronary vessels as a measure of chronic atherosclerosis. We found five suggestive (P<1x10-5) interactions in the AA GWIS, of which two (rs1856746 and rs2791713) replicated in the EA cohort (P < 0.05). Both SNPs are in the PIGR-FCAMR locus and are eQTLs in lymphocytes. The protein products of both PIGR and FCAMR are implicated in inflammatory processes. In the EA GWIS, there were three suggestive interactions; none of these replicated in the AA GWIS. All three were intergenic; the most significant interaction was in a regulatory region associated with SAMSN1, a gene previously associated with atherosclerosis and B cell activation. In conclusion, we have uncovered several novel genes associated with coronary atherosclerosis in individuals chronically exposed to increased ambient concentrations of traffic air pollution. These genes point towards inflammatory pathways that may modify the effects of air pollution on cardiovascular disease risk. PMID:28355232

Multiple HOM-C gene interactions specify cell fates in the nematode central nervous system.

PubMed

Salser, S J; Loer, C M; Kenyon, C

1993-09-01

Intricate patterns of overlapping HOM-C gene expression along the A/P axis have been observed in many organisms; however, the significance of these patterns in establishing the ultimate fates of individual cells is not well understood. We have examined the expression of the Caenorhabditis elegans Antennapedia homolog mab-5 and its role in specifying cell fates in the posterior of the ventral nerve cord. We find that the pattern of fates specified by mab-5 not only depends on mab-5 expression but also on post-translational interactions with the neighboring HOM-C gene lin-39 and a second, inferred gene activity. Where mab-5 expression overlaps with lin-39 activity, they can interact in two different ways depending on the cell type: They can either effectively neutralize one another where they are both expressed or lin-39 can predominate over mab-5. As observed for Antennapedia in Drosophila, expression of mab-5 itself is repressed by the next most posterior HOM-C gene, egl-5. Thus, a surprising diversity in HOM-C regulatory mechanisms exists within a small set of cells even in a simple organism.

A high-density association screen of 155 ion transport genes for involvement with common migraine

PubMed Central

Nyholt, Dale R.; LaForge, K. Steven; Kallela, Mikko; Alakurtti, Kirsi; Anttila, Verneri; Färkkilä, Markus; Hämaläinen, Eija; Kaprio, Jaakko; Kaunisto, Mari A.; Heath, Andrew C.; Montgomery, Grant W.; Göbel, Hartmut; Todt, Unda; Ferrari, Michel D.; Launer, Lenore J.; Frants, Rune R.; Terwindt, Gisela M.; de Vries, Boukje; Verschuren, W.M. Monique; Brand, Jan; Freilinger, Tobias; Pfaffenrath, Volker; Straube, Andreas; Ballinger, Dennis G.; Zhan, Yiping; Daly, Mark J.; Cox, David R.; Dichgans, Martin; van den Maagdenberg, Arn M.J.M.; Kubisch, Christian; Martin, Nicholas G.; Wessman, Maija; Peltonen, Leena; Palotie, Aarno

2008-01-01

The clinical overlap between monogenic Familial Hemiplegic Migraine (FHM) and common migraine subtypes, and the fact that all three FHM genes are involved in the transport of ions, suggest that ion transport genes may underlie susceptibility to common forms of migraine. To test this leading hypothesis, we examined common variation in 155 ion transport genes using 5257 single nucleotide polymorphisms (SNPs) in a Finnish sample of 841 unrelated migraine with aura cases and 884 unrelated non-migraine controls. The top signals were then tested for replication in four independent migraine case–control samples from the Netherlands, Germany and Australia, totalling 2835 unrelated migraine cases and 2740 unrelated controls. SNPs within 12 genes (KCNB2, KCNQ3, CLIC5, ATP2C2, CACNA1E, CACNB2, KCNE2, KCNK12, KCNK2, KCNS3, SCN5A and SCN9A) with promising nominal association (0.00041 < P < 0.005) in the Finnish sample were selected for replication. Although no variant remained significant after adjusting for multiple testing nor produced consistent evidence for association across all cohorts, a significant epistatic interaction between KCNB2 SNP rs1431656 (chromosome 8q13.3) and CACNB2 SNP rs7076100 (chromosome 10p12.33) (pointwise P = 0.00002; global P = 0.02) was observed in the Finnish case–control sample. We conclude that common variants of moderate effect size in ion transport genes do not play a major role in susceptibility to common migraine within these European populations, although there is some evidence for epistatic interaction between potassium and calcium channel genes, KCNB2 and CACNB2. Multiple rare variants or trans-regulatory elements of these genes are not ruled out. PMID:18676988

DNA methylome signature in rheumatoid arthritis.

PubMed

Nakano, Kazuhisa; Whitaker, John W; Boyle, David L; Wang, Wei; Firestein, Gary S

2013-01-01

Epigenetics can influence disease susceptibility and severity. While DNA methylation of individual genes has been explored in autoimmunity, no unbiased systematic analyses have been reported. Therefore, a genome-wide evaluation of DNA methylation loci in fibroblast-like synoviocytes (FLS) isolated from the site of disease in rheumatoid arthritis (RA) was performed. Genomic DNA was isolated from six RA and five osteoarthritis (OA) FLS lines and evaluated using the Illumina HumanMethylation450 chip. Cluster analysis of data was performed and corrected using Benjamini-Hochberg adjustment for multiple comparisons. Methylation was confirmed by pyrosequencing and gene expression was determined by qPCR. Pathway analysis was performed using the Kyoto Encyclopedia of Genes and Genomes. RA and control FLS segregated based on DNA methylation, with 1859 differentially methylated loci. Hypomethylated loci were identified in key genes relevant to RA, such as CHI3L1, CASP1, STAT3, MAP3K5, MEFV and WISP3. Hypermethylation was also observed, including TGFBR2 and FOXO1. Hypomethylation of individual genes was associated with increased gene expression. Grouped analysis identified 207 hypermethylated or hypomethylated genes with multiple differentially methylated loci, including COL1A1, MEFV and TNF. Hypomethylation was increased in multiple pathways related to cell migration, including focal adhesion, cell adhesion, transendothelial migration and extracellular matrix interactions. Confirmatory studies with OA and normal FLS also demonstrated segregation of RA from control FLS based on methylation pattern. Differentially methylated genes could alter FLS gene expression and contribute to the pathogenesis of RA. DNA methylation of critical genes suggests that RA FLS are imprinted and implicate epigenetic contributions to inflammatory arthritis.

Complex modulation of the Aedes aegypti transcriptome in response to dengue virus infection.

PubMed

Bonizzoni, Mariangela; Dunn, W Augustine; Campbell, Corey L; Olson, Ken E; Marinotti, Osvaldo; James, Anthony A

2012-01-01

Dengue fever is the most important arboviral disease world-wide, with Aedes aegypti being the major vector. Interactions between the mosquito host and dengue viruses (DENV) are complex and vector competence varies among geographically-distinct Ae. aegypti populations. Additionally, dengue is caused by four antigenically-distinct viral serotypes (DENV1-4), each with multiple genotypes. Each virus genotype interacts differently with vertebrate and invertebrate hosts. Analyses of alterations in mosquito transcriptional profiles during DENV infection are expected to provide the basis for identifying networks of genes involved in responses to viruses and contribute to the molecular-genetic understanding of vector competence. In addition, this knowledge is anticipated to support the development of novel disease-control strategies. RNA-seq technology was used to assess genome-wide changes in transcript abundance at 1, 4 and 14 days following DENV2 infection in carcasses, midguts and salivary glands of the Ae. aegypti Chetumal strain. DENV2 affected the expression of 397 Ae. aegypti genes, most of which were down-regulated by viral infection. Differential accumulation of transcripts was mainly tissue- and time-specific. Comparisons of our data with other published reports reveal conservation of functional classes, but limited concordance of specific mosquito genes responsive to DENV2 infection. These results indicate the necessity of additional studies of mosquito-DENV interactions, specifically those focused on recently-derived mosquito strains with multiple dengue virus serotypes and genotypes.

Exome sequencing of a colorectal cancer family reveals shared mutation pattern and predisposition circuitry along tumor pathways.

PubMed

Suleiman, Suleiman H; Koko, Mahmoud E; Nasir, Wafaa H; Elfateh, Ommnyiah; Elgizouli, Ubai K; Abdallah, Mohammed O E; Alfarouk, Khalid O; Hussain, Ayman; Faisal, Shima; Ibrahim, Fathelrahamn M A; Romano, Maurizio; Sultan, Ali; Banks, Lawrence; Newport, Melanie; Baralle, Francesco; Elhassan, Ahmed M; Mohamed, Hiba S; Ibrahim, Muntaser E

2015-01-01

The molecular basis of cancer and cancer multiple phenotypes are not yet fully understood. Next Generation Sequencing promises new insight into the role of genetic interactions in shaping the complexity of cancer. Aiming to outline the differences in mutation patterns between familial colorectal cancer cases and controls we analyzed whole exomes of cancer tissues and control samples from an extended colorectal cancer pedigree, providing one of the first data sets of exome sequencing of cancer in an African population against a background of large effective size typically with excess of variants. Tumors showed hMSH2 loss of function SNV consistent with Lynch syndrome. Sets of genes harboring insertions-deletions in tumor tissues revealed, however, significant GO enrichment, a feature that was not seen in control samples, suggesting that ordered insertions-deletions are central to tumorigenesis in this type of cancer. Network analysis identified multiple hub genes of centrality. ELAVL1/HuR showed remarkable centrality, interacting specially with genes harboring non-synonymous SNVs thus reinforcing the proposition of targeted mutagenesis in cancer pathways. A likely explanation to such mutation pattern is DNA/RNA editing, suggested here by nucleotide transition-to-transversion ratio that significantly departed from expected values (p-value 5e-6). NFKB1 also showed significant centrality along with ELAVL1, raising the suspicion of viral etiology given the known interaction between oncogenic viruses and these proteins.

Analysis of the dynamic co-expression network of heart regeneration in the zebrafish

PubMed Central

Rodius, Sophie; Androsova, Ganna; Götz, Lou; Liechti, Robin; Crespo, Isaac; Merz, Susanne; Nazarov, Petr V.; de Klein, Niek; Jeanty, Céline; González-Rosa, Juan M.; Muller, Arnaud; Bernardin, Francois; Niclou, Simone P.; Vallar, Laurent; Mercader, Nadia; Ibberson, Mark; Xenarios, Ioannis; Azuaje, Francisco

2016-01-01

The zebrafish has the capacity to regenerate its heart after severe injury. While the function of a few genes during this process has been studied, we are far from fully understanding how genes interact to coordinate heart regeneration. To enable systematic insights into this phenomenon, we generated and integrated a dynamic co-expression network of heart regeneration in the zebrafish and linked systems-level properties to the underlying molecular events. Across multiple post-injury time points, the network displays topological attributes of biological relevance. We show that regeneration steps are mediated by modules of transcriptionally coordinated genes, and by genes acting as network hubs. We also established direct associations between hubs and validated drivers of heart regeneration with murine and human orthologs. The resulting models and interactive analysis tools are available at http://infused.vital-it.ch. Using a worked example, we demonstrate the usefulness of this unique open resource for hypothesis generation and in silico screening for genes involved in heart regeneration. PMID:27241320

DEIVA: a web application for interactive visual analysis of differential gene expression profiles.

PubMed

Harshbarger, Jayson; Kratz, Anton; Carninci, Piero

2017-01-07

Differential gene expression (DGE) analysis is a technique to identify statistically significant differences in RNA abundance for genes or arbitrary features between different biological states. The result of a DGE test is typically further analyzed using statistical software, spreadsheets or custom ad hoc algorithms. We identified a need for a web-based system to share DGE statistical test results, and locate and identify genes in DGE statistical test results with a very low barrier of entry. We have developed DEIVA, a free and open source, browser-based single page application (SPA) with a strong emphasis on being user friendly that enables locating and identifying single or multiple genes in an immediate, interactive, and intuitive manner. By design, DEIVA scales with very large numbers of users and datasets. Compared to existing software, DEIVA offers a unique combination of design decisions that enable inspection and analysis of DGE statistical test results with an emphasis on ease of use.

Analysis of the dynamic co-expression network of heart regeneration in the zebrafish

NASA Astrophysics Data System (ADS)

Rodius, Sophie; Androsova, Ganna; Götz, Lou; Liechti, Robin; Crespo, Isaac; Merz, Susanne; Nazarov, Petr V.; de Klein, Niek; Jeanty, Céline; González-Rosa, Juan M.; Muller, Arnaud; Bernardin, Francois; Niclou, Simone P.; Vallar, Laurent; Mercader, Nadia; Ibberson, Mark; Xenarios, Ioannis; Azuaje, Francisco

2016-05-01

The zebrafish has the capacity to regenerate its heart after severe injury. While the function of a few genes during this process has been studied, we are far from fully understanding how genes interact to coordinate heart regeneration. To enable systematic insights into this phenomenon, we generated and integrated a dynamic co-expression network of heart regeneration in the zebrafish and linked systems-level properties to the underlying molecular events. Across multiple post-injury time points, the network displays topological attributes of biological relevance. We show that regeneration steps are mediated by modules of transcriptionally coordinated genes, and by genes acting as network hubs. We also established direct associations between hubs and validated drivers of heart regeneration with murine and human orthologs. The resulting models and interactive analysis tools are available at http://infused.vital-it.ch. Using a worked example, we demonstrate the usefulness of this unique open resource for hypothesis generation and in silico screening for genes involved in heart regeneration.

Haplotype-based gene-gene interaction of bone morphogenetic protein 4 and interferon regulatory factor 6 in the etiology of non-syndromic cleft lip with or without cleft palate in a Chilean population.

PubMed

Blanco, Rafael; Colombo, Alicia; Pardo, Rosa; Suazo, José

2017-04-01

Non-syndromic cleft lip with or without cleft palate (NSCL/P) is the most common craniofacial birth defect in humans, the etiology of which can be dependent on the interactions of multiple genes. We previously reported haplotype associations for polymorphic variants of interferon regulatory factor 6 (IRF6), msh homeobox 1 (MSX1), bone morphogenetic protein 4 (BMP4), and transforming growth factor beta 3 (TGFB3) in Chile. Here, we analyzed the haplotype-based gene-gene interaction for markers of these genes and NSCL/P risk in the Chilean population. We genotyped 15 single nucleoptide polymorphisms (SNPs) in 152 Chilean patients and 164 controls. Linkage disequilibrium (LD) blocks were determined using the Haploview software, and phase reconstruction was performed by the Phase program. Haplotype-based interactions were evaluated using the multifactor dimensionality reduction (MDR) method. We detected two LD blocks composed of two SNPs from BMP4 (Block 1) and three SNPs from IRF6 (Block 2). Although MDR showed no statistical significance for the global interaction model involving these blocks, we found four combinations conferring a statistically significantly increased NSCL/P risk (Block 1-Block 2): T-T/T-G C-G-T/G-A-T; T-T/T-G C-G-C/C-G-C; T-T/T-G G-A-T/G-A-T; and T-T/C-G G-A-T/G-A-T. These findings may reflect the presence of a genomic region containing potential causal variants interacting in the etiology of NSCL/P and may contribute to disentangling the complex etiology of this birth defect. © 2017 Eur J Oral Sci.

Planar Cell Polarity Pathway Genes and Risk for Spina Bifida

PubMed Central

Wen, Shu; Zhu, Huiping; Lu, Wei; Mitchell, Laura E.; Shaw, Gary M.; Lammer, Edward J.; Finnell, Richard H.

2009-01-01

Spina bifida, a neural tube closure defect (NTD) involving the posterior portion of what will ultimately give rise to the spinal cord, is one of the most common and serious birth defects. The etiology of spina bifida is thought to be multi-factorial and involve multiple interacting genes and environmental factors. The causes of this congenital malformation remain largely unknown. However, several candidate genes for spina bifida have been identified in lower vertebrates, including the planar cell polarity (PCP) genes. We used data from a case-control study conducted in California to evaluate the association between variation within several key PCP genes and the risk of spina bifida. The PCP genes included in this study were the human homologues of the Xenopus genes Flamingo, Strabismus, Prickle, Dishevelled and Scrib, two of the homologues of Xenopus Wnt genes, WNT5A and WNT11, and two of the homologues of Xenopus Frizzled, FZD3 and FZD6. None of the 172 SNPs that were evaluated were significantly associated with spina bifida in any racial/ethnic group after correction for multiple testing. However, several SNPs in the PRICKLE2 gene had unadjusted p value<0.01. In conclusion our results, though largely negative, suggest that the PRICKLE2 gene may potentially modify the risk of spina bifida and deserves further investigation. PMID:20101694

Genome-Wide Detection and Analysis of Multifunctional Genes

PubMed Central

Pritykin, Yuri; Ghersi, Dario; Singh, Mona

2015-01-01

Many genes can play a role in multiple biological processes or molecular functions. Identifying multifunctional genes at the genome-wide level and studying their properties can shed light upon the complexity of molecular events that underpin cellular functioning, thereby leading to a better understanding of the functional landscape of the cell. However, to date, genome-wide analysis of multifunctional genes (and the proteins they encode) has been limited. Here we introduce a computational approach that uses known functional annotations to extract genes playing a role in at least two distinct biological processes. We leverage functional genomics data sets for three organisms—H. sapiens, D. melanogaster, and S. cerevisiae—and show that, as compared to other annotated genes, genes involved in multiple biological processes possess distinct physicochemical properties, are more broadly expressed, tend to be more central in protein interaction networks, tend to be more evolutionarily conserved, and are more likely to be essential. We also find that multifunctional genes are significantly more likely to be involved in human disorders. These same features also hold when multifunctionality is defined with respect to molecular functions instead of biological processes. Our analysis uncovers key features about multifunctional genes, and is a step towards a better genome-wide understanding of gene multifunctionality. PMID:26436655

The Pathogen-Host Interactions database (PHI-base): additions and future developments

PubMed Central

Urban, Martin; Pant, Rashmi; Raghunath, Arathi; Irvine, Alistair G.; Pedro, Helder; Hammond-Kosack, Kim E.

2015-01-01

Rapidly evolving pathogens cause a diverse array of diseases and epidemics that threaten crop yield, food security as well as human, animal and ecosystem health. To combat infection greater comparative knowledge is required on the pathogenic process in multiple species. The Pathogen-Host Interactions database (PHI-base) catalogues experimentally verified pathogenicity, virulence and effector genes from bacterial, fungal and protist pathogens. Mutant phenotypes are associated with gene information. The included pathogens infect a wide range of hosts including humans, animals, plants, insects, fish and other fungi. The current version, PHI-base 3.6, available at http://www.phi-base.org, stores information on 2875 genes, 4102 interactions, 110 host species, 160 pathogenic species (103 plant, 3 fungal and 54 animal infecting species) and 181 diseases drawn from 1243 references. Phenotypic and gene function information has been obtained by manual curation of the peer-reviewed literature. A controlled vocabulary consisting of nine high-level phenotype terms permits comparisons and data analysis across the taxonomic space. PHI-base phenotypes were mapped via their associated gene information to reference genomes available in Ensembl Genomes. Virulence genes and hotspots can be visualized directly in genome browsers. Future plans for PHI-base include development of tools facilitating community-led curation and inclusion of the corresponding host target(s). PMID:25414340

Identification of novel candidate drivers connecting different dysfunctional levels for lung adenocarcinoma using protein-protein interactions and a shortest path approach

NASA Astrophysics Data System (ADS)

Chen, Lei; Huang, Tao; Zhang, Yu-Hang; Jiang, Yang; Zheng, Mingyue; Cai, Yu-Dong

2016-07-01

Tumors are formed by the abnormal proliferation of somatic cells with disordered growth regulation under the influence of tumorigenic factors. Recently, the theory of “cancer drivers” connects tumor initiation with several specific mutations in the so-called cancer driver genes. According to the differentiation of four basic levels between tumor and adjacent normal tissues, the cancer drivers can be divided into the following: (1) Methylation level, (2) microRNA level, (3) mutation level, and (4) mRNA level. In this study, a computational method is proposed to identify novel lung adenocarcinoma drivers based on dysfunctional genes on the methylation, microRNA, mutation and mRNA levels. First, a large network was constructed using protein-protein interactions. Next, we searched all of the shortest paths connecting dysfunctional genes on different levels and extracted new candidate genes lying on these paths. Finally, the obtained candidate genes were filtered by a permutation test and an additional strict selection procedure involving a betweenness ratio and an interaction score. Several candidate genes remained, which are deemed to be related to two different levels of cancer. The analyses confirmed our assertions that some have the potential to contribute to the tumorigenesis process on multiple levels.

Markov Logic Networks in the Analysis of Genetic Data

PubMed Central

Sakhanenko, Nikita A.

2010-01-01

Abstract Complex, non-additive genetic interactions are common and can be critical in determining phenotypes. Genome-wide association studies (GWAS) and similar statistical studies of linkage data, however, assume additive models of gene interactions in looking for genotype-phenotype associations. These statistical methods view the compound effects of multiple genes on a phenotype as a sum of influences of each gene and often miss a substantial part of the heritable effect. Such methods do not use any biological knowledge about underlying mechanisms. Modeling approaches from the artificial intelligence (AI) field that incorporate deterministic knowledge into models to perform statistical analysis can be applied to include prior knowledge in genetic analysis. We chose to use the most general such approach, Markov Logic Networks (MLNs), for combining deterministic knowledge with statistical analysis. Using simple, logistic regression-type MLNs we can replicate the results of traditional statistical methods, but we also show that we are able to go beyond finding independent markers linked to a phenotype by using joint inference without an independence assumption. The method is applied to genetic data on yeast sporulation, a complex phenotype with gene interactions. In addition to detecting all of the previously identified loci associated with sporulation, our method identifies four loci with smaller effects. Since their effect on sporulation is small, these four loci were not detected with methods that do not account for dependence between markers due to gene interactions. We show how gene interactions can be detected using more complex models, which can be used as a general framework for incorporating systems biology with genetics. PMID:20958249

Alcohol and aggressive behavior in men--moderating effects of oxytocin receptor gene (OXTR) polymorphisms.

PubMed

Johansson, A; Bergman, H; Corander, J; Waldman, I D; Karrani, N; Salo, B; Jern, P; Algars, M; Sandnabba, K; Santtila, P; Westberg, L

2012-03-01

We explored if the disposition to react with aggression while alcohol intoxicated was moderated by polymorphic variants of the oxytocin receptor gene (OXTR). Twelve OXTR polymorphisms were genotyped in 116 Finnish men [aged 18-30, M = 22.7, standard deviation (SD) = 2.4] who were randomly assigned to an alcohol condition in which they received an alcohol dose of 0.7 g pure ethanol/kg body weight or a placebo condition. Aggressive behavior was measured using a laboratory paradigm in which it was operationalized as the level of aversive noise administered to a fictive opponent. No main effects of the polymorphisms on aggressive behavior were found after controlling for multiple testing. The interactive effects between alcohol and two of the OXTR polymorphisms (rs4564970 and rs1488467) on aggressive behavior were nominally significant and remained significant for the rs4564970 when controlled for multiple tests. To the best of our knowledge, this is the first experimental study suggesting interactive effects of specific genetic variants and alcohol on aggressive behavior in humans. © 2011 The Authors. Genes, Brain and Behavior © 2011 Blackwell Publishing Ltd and International Behavioural and Neural Genetics Society.

VisANT 3.0: new modules for pathway visualization, editing, prediction and construction.

PubMed

Hu, Zhenjun; Ng, David M; Yamada, Takuji; Chen, Chunnuan; Kawashima, Shuichi; Mellor, Joe; Linghu, Bolan; Kanehisa, Minoru; Stuart, Joshua M; DeLisi, Charles

2007-07-01

With the integration of the KEGG and Predictome databases as well as two search engines for coexpressed genes/proteins using data sets obtained from the Stanford Microarray Database (SMD) and Gene Expression Omnibus (GEO) database, VisANT 3.0 supports exploratory pathway analysis, which includes multi-scale visualization of multiple pathways, editing and annotating pathways using a KEGG compatible visual notation and visualization of expression data in the context of pathways. Expression levels are represented either by color intensity or by nodes with an embedded expression profile. Multiple experiments can be navigated or animated. Known KEGG pathways can be enriched by querying either coexpressed components of known pathway members or proteins with known physical interactions. Predicted pathways for genes/proteins with unknown functions can be inferred from coexpression or physical interaction data. Pathways produced in VisANT can be saved as computer-readable XML format (VisML), graphic images or high-resolution Scalable Vector Graphics (SVG). Pathways in the format of VisML can be securely shared within an interested group or published online using a simple Web link. VisANT is freely available at http://visant.bu.edu.

Epistasis Analysis for Estrogen Metabolic and Signaling Pathway Genes on Young Ischemic Stroke Patients

PubMed Central

Hsieh, Yi-Chen; Jeng, Jiann-Shing; Lin, Huey-Juan; Hu, Chaur-Jong; Yu, Chia-Chen; Lien, Li-Ming; Peng, Giia-Sheun; Chen, Chin-I; Tang, Sung-Chun; Chi, Nai-Fang; Tseng, Hung-Pin; Chern, Chang-Ming; Hsieh, Fang-I; Bai, Chyi-Huey; Chen, Yi-Rhu; Chiou, Hung-Yi; Jeng, Jiann-Shing; Tang, Sung-Chun; Yeh, Shin-Joe; Tsai, Li-Kai; Kong, Shin; Lien, Li-Ming; Chiu, Hou-Chang; Chen, Wei-Hung; Bai, Chyi-Huey; Huang, Tzu-Hsuan; Chi-Ieong, Lau; Wu, Ya-Ying; Yuan, Rey-Yue; Hu, Chaur-Jong; Sheu, Jau- Jiuan; Yu, Jia-Ming; Ho, Chun-Sum; Chen, Chin-I; Sung, Jia-Ying; Weng, Hsing-Yu; Han, Yu-Hsuan; Huang, Chun-Ping; Chung, Wen-Ting; Ke, Der-Shin; Lin, Huey-Juan; Chang, Chia-Yu; Yeh, Poh-Shiow; Lin, Kao-Chang; Cheng, Tain-Junn; Chou, Chih-Ho; Yang, Chun-Ming; Peng, Giia-Sheun; Lin, Jiann-Chyun; Hsu, Yaw-Don; Denq, Jong-Chyou; Lee, Jiunn-Tay; Hsu, Chang-Hung; Lin, Chun-Chieh; Yen, Che-Hung; Cheng, Chun-An; Sung, Yueh-Feng; Chen, Yuan-Liang; Lien, Ming-Tung; Chou, Chung-Hsing; Liu, Chia-Chen; Yang, Fu-Chi; Wu, Yi-Chung; Tso, An-Chen; Lai, Yu- Hua; Chiang, Chun-I; Tsai, Chia-Kuang; Liu, Meng-Ta; Lin, Ying-Che; Hsu, Yu-Chuan; Chen, Chih-Hung; Sung, Pi-Shan; Chern, Chang-Ming; Hu, Han-Hwa; Wong, Wen-Jang; Luk, Yun-On; Hsu, Li-Chi; Chung, Chih-Ping; Tseng, Hung-Pin; Liu, Chin-Hsiung; Lin, Chun-Liang; Lin, Hung-Chih; Hu, Chaur-Jong

2012-01-01

Background Endogenous estrogens play an important role in the overall cardiocirculatory system. However, there are no studies exploring the hormone metabolism and signaling pathway genes together on ischemic stroke, including sulfotransferase family 1E (SULT1E1), catechol-O-methyl-transferase (COMT), and estrogen receptor α (ESR1). Methods A case-control study was conducted on 305 young ischemic stroke subjects aged ≦ 50 years and 309 age-matched healthy controls. SULT1E1 -64G/A, COMT Val158Met, ESR1 c.454−397 T/C and c.454−351 A/G genes were genotyped and compared between cases and controls to identify single nucleotide polymorphisms associated with ischemic stroke susceptibility. Gene-gene interaction effects were analyzed using entropy-based multifactor dimensionality reduction (MDR), classification and regression tree (CART), and traditional multiple regression models. Results COMT Val158Met polymorphism showed a significant association with susceptibility of young ischemic stroke among females. There was a two-way interaction between SULT1E1 -64G/A and COMT Val158Met in both MDR and CART analysis. The logistic regression model also showed there was a significant interaction effect between SULT1E1 -64G/A and COMT Val158Met on ischemic stroke of the young (P for interaction = 0.0171). We further found that lower estradiol level could increase the risk of young ischemic stroke for those who carry either SULT1E1 or COMT risk genotypes, showing a significant interaction effect (P for interaction = 0.0174). Conclusions Our findings support that a significant epistasis effect exists among estrogen metabolic and signaling pathway genes and gene-environment interactions on young ischemic stroke subjects. PMID:23112845

Effect of Aggregation Operators on Network-Based Disease Gene Prioritization: A Case Study on Blood Disorders.

PubMed

Grewal, Nivit; Singh, Shailendra; Chand, Trilok

2017-01-01

Owing to the innate noise in the biological data sources, a single source or a single measure do not suffice for an effective disease gene prioritization. So, the integration of multiple data sources or aggregation of multiple measures is the need of the hour. The aggregation operators combine multiple related data values to a single value such that the combined value has the effect of all the individual values. In this paper, an attempt has been made for applying the fuzzy aggregation on the network-based disease gene prioritization and investigate its effect under noise conditions. This study has been conducted for a set of 15 blood disorders by fusing four different network measures, computed from the protein interaction network, using a selected set of aggregation operators and ranking the genes on the basis of the aggregated value. The aggregation operator-based rankings have been compared with the "Random walk with restart" gene prioritization method. The impact of noise has also been investigated by adding varying proportions of noise to the seed set. The results reveal that for all the selected blood disorders, the Mean of Maximal operator has relatively outperformed the other aggregation operators for noisy as well as non-noisy data.

Dual control of pcdh8l/PCNS expression and function in Xenopus laevis neural crest cells by adam13/33 via the transcription factors tfap2α and arid3a.

PubMed

Khedgikar, Vikram; Abbruzzese, Genevieve; Mathavan, Ketan; Szydlo, Hannah; Cousin, Helene; Alfandari, Dominique

2017-08-22

Adam13/33 is a cell surface metalloprotease critical for cranial neural crest (CNC) cell migration. It can cleave multiple substrates including itself, fibronectin, ephrinB, cadherin-11, pcdh8 and pcdh8l (this work). Cleavage of cadherin-11 produces an extracellular fragment that promotes CNC migration. In addition, the adam13 cytoplasmic domain is cleaved by gamma secretase, translocates into the nucleus and regulates multiple genes. Here, we show that adam13 interacts with the arid3a/dril1/Bright transcription factor. This interaction promotes a proteolytic cleavage of arid3a and its translocation to the nucleus where it regulates another transcription factor: tfap2α. Tfap2α in turn activates multiple genes including the protocadherin pcdh8l (PCNS). The proteolytic activity of adam13 is critical for the release of arid3a from the plasma membrane while the cytoplasmic domain appears critical for the cleavage of arid3a. In addition to this transcriptional control of pcdh8l, adam13 cleaves pcdh8l generating an extracellular fragment that also regulates cell migration.

Dual control of pcdh8l/PCNS expression and function in Xenopus laevis neural crest cells by adam13/33 via the transcription factors tfap2α and arid3a

PubMed Central

Khedgikar, Vikram; Abbruzzese, Genevieve; Mathavan, Ketan; Szydlo, Hannah; Cousin, Helene

2017-01-01

Adam13/33 is a cell surface metalloprotease critical for cranial neural crest (CNC) cell migration. It can cleave multiple substrates including itself, fibronectin, ephrinB, cadherin-11, pcdh8 and pcdh8l (this work). Cleavage of cadherin-11 produces an extracellular fragment that promotes CNC migration. In addition, the adam13 cytoplasmic domain is cleaved by gamma secretase, translocates into the nucleus and regulates multiple genes. Here, we show that adam13 interacts with the arid3a/dril1/Bright transcription factor. This interaction promotes a proteolytic cleavage of arid3a and its translocation to the nucleus where it regulates another transcription factor: tfap2α. Tfap2α in turn activates multiple genes including the protocadherin pcdh8l (PCNS). The proteolytic activity of adam13 is critical for the release of arid3a from the plasma membrane while the cytoplasmic domain appears critical for the cleavage of arid3a. In addition to this transcriptional control of pcdh8l, adam13 cleaves pcdh8l generating an extracellular fragment that also regulates cell migration. PMID:28829038

Variation of types of alcoholism: review and subtypes identified in Han Chinese.

PubMed

Lee, Sheng-Yu; Chen, Shiou-Lan; Chang, Yun-Hsuan; Lu, Ru-Band

2014-01-03

Alcoholism, as it has been hypothesized, is caused by a highly heterogeneous genetic load. Since 1960, many reports have used the bio-psycho-social approach to subtype alcoholism; however, no subtypes have been genetically validated. We reviewed and compared the major single-gene, multiple-gene, and gene-to-gene interaction studies on alcoholism published during the past quarter-century, including many recent studies that have made contributions to the subtyping of alcoholism. Four subtypes of alcoholism have been reported: [1] pure alcoholism, [2] anxiety/depression alcoholism, [3] antisocial alcoholism, and [4] mixed alcoholism. Most of the important studies focused on three genes: DRD2, MAOA, and ALDH2. Therefore, our review focuses on these three genes. © 2013.

Discovery and validation of a glioblastoma co-expressed gene module

PubMed Central

Dunwoodie, Leland J.; Poehlman, William L.; Ficklin, Stephen P.; Feltus, Frank Alexander

2018-01-01

Tumors exhibit complex patterns of aberrant gene expression. Using a knowledge-independent, noise-reducing gene co-expression network construction software called KINC, we created multiple RNAseq-based gene co-expression networks relevant to brain and glioblastoma biology. In this report, we describe the discovery and validation of a glioblastoma-specific gene module that contains 22 co-expressed genes. The genes are upregulated in glioblastoma relative to normal brain and lower grade glioma samples; they are also hypo-methylated in glioblastoma relative to lower grade glioma tumors. Among the proneural, neural, mesenchymal, and classical glioblastoma subtypes, these genes are most-highly expressed in the mesenchymal subtype. Furthermore, high expression of these genes is associated with decreased survival across each glioblastoma subtype. These genes are of interest to glioblastoma biology and our gene interaction discovery and validation workflow can be used to discover and validate co-expressed gene modules derived from any co-expression network. PMID:29541392

Discovery and validation of a glioblastoma co-expressed gene module.

PubMed

Dunwoodie, Leland J; Poehlman, William L; Ficklin, Stephen P; Feltus, Frank Alexander

2018-02-16

Tumors exhibit complex patterns of aberrant gene expression. Using a knowledge-independent, noise-reducing gene co-expression network construction software called KINC, we created multiple RNAseq-based gene co-expression networks relevant to brain and glioblastoma biology. In this report, we describe the discovery and validation of a glioblastoma-specific gene module that contains 22 co-expressed genes. The genes are upregulated in glioblastoma relative to normal brain and lower grade glioma samples; they are also hypo-methylated in glioblastoma relative to lower grade glioma tumors. Among the proneural, neural, mesenchymal, and classical glioblastoma subtypes, these genes are most-highly expressed in the mesenchymal subtype. Furthermore, high expression of these genes is associated with decreased survival across each glioblastoma subtype. These genes are of interest to glioblastoma biology and our gene interaction discovery and validation workflow can be used to discover and validate co-expressed gene modules derived from any co-expression network.

Gcn4-Mediator Specificity Is Mediated by a Large and Dynamic Fuzzy Protein-Protein Complex.

PubMed

Tuttle, Lisa M; Pacheco, Derek; Warfield, Linda; Luo, Jie; Ranish, Jeff; Hahn, Steven; Klevit, Rachel E

2018-03-20

Transcription activation domains (ADs) are inherently disordered proteins that often target multiple coactivator complexes, but the specificity of these interactions is not understood. Efficient transcription activation by yeast Gcn4 requires its tandem ADs and four activator-binding domains (ABDs) on its target, the Mediator subunit Med15. Multiple ABDs are a common feature of coactivator complexes. We find that the large Gcn4-Med15 complex is heterogeneous and contains nearly all possible AD-ABD interactions. Gcn4-Med15 forms via a dynamic fuzzy protein-protein interface, where ADs bind the ABDs in multiple orientations via hydrophobic regions that gain helicity. This combinatorial mechanism allows individual low-affinity and specificity interactions to generate a biologically functional, specific, and higher affinity complex despite lacking a defined protein-protein interface. This binding strategy is likely representative of many activators that target multiple coactivators, as it allows great flexibility in combinations of activators that can cooperate to regulate genes with variable coactivator requirements. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2013-02-01

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

Does the FTO gene interact with the socioeconomic status on the obesity development among young European children? Results from the IDEFICS study.

PubMed

Foraita, R; Günther, F; Gwozdz, W; Reisch, L A; Russo, P; Lauria, F; Siani, A; Veidebaum, T; Tornaritis, M; Iacoviello, L; Vyncke, K; Pitsiladis, Y; Mårild, S; Molnár, D; Moreno, L A; Bammann, K; Pigeot, I

2015-01-01

Various twin studies revealed that the influence of genetic factors on psychological diseases or behaviour is more expressed in socioeconomically advantaged environments. Other studies predominantly show an inverse association between socioeconomic status (SES) and childhood obesity in Western developed countries. The aim of this study is to investigate whether the fat mass and obesity-associated (FTO) gene interacts with the SES on childhood obesity in a subsample (N = 4406) of the IDEFICS (Identification and prevention of Dietary- and lifestyle-induced health EFfects In Children and infantS) cohort. A structural equation model (SEM) is applied with the latent constructs obesity, dietary intakes, physical activity and fitness habits, and parental SES to estimate the main effects of the latter three variables and a FTO polymorphism on childhood obesity. Further, a multiple group SEM is used to explore whether an interaction effect exists between the single nucleotide polymorphism rs9939609 within the FTO gene and SES. Significant main effects are shown for physical activity and fitness (standardised [betacrc ](s) = -0.113), SES ([betacrc ](s) = -0.057) and the FTO homozygous AA risk genotype ([betacrc ](s) = -0.177). The explained variance of obesity is ~9%. According to the multiple group approach of SEM, we see an interaction between SES and FTO with respect to their effect on childhood obesity (Δχ(2) = 7.3, df = 2, P = 0.03). Children carrying the protective FTO genotype TT seem to be more protected by a favourable social environment regarding the development of obesity than children carrying the AT or AA genotype.

Gene-environment interplay in the etiology of psychosis.

PubMed

Zwicker, Alyson; Denovan-Wright, Eileen M; Uher, Rudolf

2018-01-15

Schizophrenia and other types of psychosis incur suffering, high health care costs and loss of human potential, due to the combination of early onset and poor response to treatment. Our ability to prevent or cure psychosis depends on knowledge of causal mechanisms. Molecular genetic studies show that thousands of common and rare variants contribute to the genetic risk for psychosis. Epidemiological studies have identified many environmental factors associated with increased risk of psychosis. However, no single genetic or environmental factor is sufficient to cause psychosis on its own. The risk of developing psychosis increases with the accumulation of many genetic risk variants and exposures to multiple adverse environmental factors. Additionally, the impact of environmental exposures likely depends on genetic factors, through gene-environment interactions. Only a few specific gene-environment combinations that lead to increased risk of psychosis have been identified to date. An example of replicable gene-environment interaction is a common polymorphism in the AKT1 gene that makes its carriers sensitive to developing psychosis with regular cannabis use. A synthesis of results from twin studies, molecular genetics, and epidemiological research outlines the many genetic and environmental factors contributing to psychosis. The interplay between these factors needs to be considered to draw a complete picture of etiology. To reach a more complete explanation of psychosis that can inform preventive strategies, future research should focus on longitudinal assessments of multiple environmental exposures within large, genotyped cohorts beginning early in life.

SnipViz: a compact and lightweight web site widget for display and dissemination of multiple versions of gene and protein sequences.

PubMed

Jaschob, Daniel; Davis, Trisha N; Riffle, Michael

2014-07-23

As high throughput sequencing continues to grow more commonplace, the need to disseminate the resulting data via web applications continues to grow. Particularly, there is a need to disseminate multiple versions of related gene and protein sequences simultaneously--whether they represent alleles present in a single species, variations of the same gene among different strains, or homologs among separate species. Often this is accomplished by displaying all versions of the sequence at once in a manner that is not intuitive or space-efficient and does not facilitate human understanding of the data. Web-based applications needing to disseminate multiple versions of sequences would benefit from a drop-in module designed to effectively disseminate these data. SnipViz is a client-side software tool designed to disseminate multiple versions of related gene and protein sequences on web sites. SnipViz has a space-efficient, interactive, and dynamic interface for navigating, analyzing and visualizing sequence data. It is written using standard World Wide Web technologies (HTML, Javascript, and CSS) and is compatible with most web browsers. SnipViz is designed as a modular client-side web component and may be incorporated into virtually any web site and be implemented without any programming. SnipViz is a drop-in client-side module for web sites designed to efficiently visualize and disseminate gene and protein sequences. SnipViz is open source and is freely available at https://github.com/yeastrc/snipviz.

Insights into the innate immunome of actiniarians using a comparative genomic approach.

PubMed

van der Burg, Chloé A; Prentis, Peter J; Surm, Joachim M; Pavasovic, Ana

2016-11-02

Innate immune genes tend to be highly conserved in metazoans, even in early divergent lineages such as Cnidaria (jellyfish, corals, hydroids and sea anemones) and Porifera (sponges). However, constant and diverse selection pressures on the immune system have driven the expansion and diversification of different immune gene families in a lineage-specific manner. To investigate how the innate immune system has evolved in a subset of sea anemone species (Order: Actiniaria), we performed a comprehensive and comparative study using 10 newly sequenced transcriptomes, as well as three publically available transcriptomes, to identify the origins, expansions and contractions of candidate and novel immune gene families. We characterised five conserved genes and gene families, as well as multiple novel innate immune genes, including the newly recognised putative pattern recognition receptor CniFL. Single copies of TLR, MyD88 and NF-κB were found in most species, and several copies of IL-1R-like, NLR and CniFL were found in almost all species. Multiple novel immune genes were identified with domain architectures including the Toll/interleukin-1 receptor (TIR) homology domain, which is well documented as functioning in protein-protein interactions and signal transduction in immune pathways. We hypothesise that these genes may interact as novel proteins in immune pathways of cnidarian species. Novelty in the actiniarian immunome is not restricted to only TIR-domain-containing proteins, as we identify a subset of NLRs which have undergone neofunctionalisation and contain 3-5 N-terminal transmembrane domains, which have so far only been identified in two anthozoan species. This research has significance in understanding the evolution and origin of the core eumetazoan gene set, including how novel innate immune genes evolve. For example, the evolution of transmembrane domain containing NLRs indicates that these NLRs may be membrane-bound, while all other metazoan and plant NLRs are exclusively cytosolic receptors. This is one example of how species without an adaptive immune system may evolve innovative solutions to detect pathogens or interact with native microbiota. Overall, these results provide an insight into the evolution of the innate immune system, and show that early divergent lineages, such as actiniarians, have a diverse repertoire of conserved and novel innate immune genes.

CTCF counter-regulates cardiomyocyte development and maturation programs in the embryonic heart.

PubMed

Gomez-Velazquez, Melisa; Badia-Careaga, Claudio; Lechuga-Vieco, Ana Victoria; Nieto-Arellano, Rocio; Tena, Juan J; Rollan, Isabel; Alvarez, Alba; Torroja, Carlos; Caceres, Eva F; Roy, Anna R; Galjart, Niels; Delgado-Olguin, Paul; Sanchez-Cabo, Fatima; Enriquez, Jose Antonio; Gomez-Skarmeta, Jose Luis; Manzanares, Miguel

2017-08-01

Cardiac progenitors are specified early in development and progressively differentiate and mature into fully functional cardiomyocytes. This process is controlled by an extensively studied transcriptional program. However, the regulatory events coordinating the progression of such program from development to maturation are largely unknown. Here, we show that the genome organizer CTCF is essential for cardiogenesis and that it mediates genomic interactions to coordinate cardiomyocyte differentiation and maturation in the developing heart. Inactivation of Ctcf in cardiac progenitor cells and their derivatives in vivo during development caused severe cardiac defects and death at embryonic day 12.5. Genome wide expression analysis in Ctcf mutant hearts revealed that genes controlling mitochondrial function and protein production, required for cardiomyocyte maturation, were upregulated. However, mitochondria from mutant cardiomyocytes do not mature properly. In contrast, multiple development regulatory genes near predicted heart enhancers, including genes in the IrxA cluster, were downregulated in Ctcf mutants, suggesting that CTCF promotes cardiomyocyte differentiation by facilitating enhancer-promoter interactions. Accordingly, loss of CTCF disrupts gene expression and chromatin interactions as shown by chromatin conformation capture followed by deep sequencing. Furthermore, CRISPR-mediated deletion of an intergenic CTCF site within the IrxA cluster alters gene expression in the developing heart. Thus, CTCF mediates local regulatory interactions to coordinate transcriptional programs controlling transitions in morphology and function during heart development.

CTCF counter-regulates cardiomyocyte development and maturation programs in the embryonic heart

PubMed Central

Gomez-Velazquez, Melisa; Badia-Careaga, Claudio; Lechuga-Vieco, Ana Victoria; Nieto-Arellano, Rocio; Rollan, Isabel; Alvarez, Alba; Torroja, Carlos; Caceres, Eva F.; Roy, Anna R.; Galjart, Niels; Sanchez-Cabo, Fatima; Enriquez, Jose Antonio; Gomez-Skarmeta, Jose Luis

2017-01-01

Cardiac progenitors are specified early in development and progressively differentiate and mature into fully functional cardiomyocytes. This process is controlled by an extensively studied transcriptional program. However, the regulatory events coordinating the progression of such program from development to maturation are largely unknown. Here, we show that the genome organizer CTCF is essential for cardiogenesis and that it mediates genomic interactions to coordinate cardiomyocyte differentiation and maturation in the developing heart. Inactivation of Ctcf in cardiac progenitor cells and their derivatives in vivo during development caused severe cardiac defects and death at embryonic day 12.5. Genome wide expression analysis in Ctcf mutant hearts revealed that genes controlling mitochondrial function and protein production, required for cardiomyocyte maturation, were upregulated. However, mitochondria from mutant cardiomyocytes do not mature properly. In contrast, multiple development regulatory genes near predicted heart enhancers, including genes in the IrxA cluster, were downregulated in Ctcf mutants, suggesting that CTCF promotes cardiomyocyte differentiation by facilitating enhancer-promoter interactions. Accordingly, loss of CTCF disrupts gene expression and chromatin interactions as shown by chromatin conformation capture followed by deep sequencing. Furthermore, CRISPR-mediated deletion of an intergenic CTCF site within the IrxA cluster alters gene expression in the developing heart. Thus, CTCF mediates local regulatory interactions to coordinate transcriptional programs controlling transitions in morphology and function during heart development. PMID:28846746

A novel approach to exploring potential interactions among single-nucleotide polymorphisms of inflammation genes in gliomagenesis: an exploratory case-only study.

PubMed

Amirian, E Susan; Scheurer, Michael E; Liu, Yanhong; D'Amelio, Anthony M; Houlston, Richard S; Etzel, Carol J; Shete, Sanjay; Swerdlow, Anthony J; Schoemaker, Minouk J; McKinney, Patricia A; Fleming, Sarah J; Muir, Kenneth R; Lophatananon, Artitaya; Bondy, Melissa L

2011-08-01

Despite extensive research on the topic, glioma etiology remains largely unknown. Exploration of potential interactions between single-nucleotide polymorphisms (SNP) of immune genes is a promising new area of glioma research. The case-only study design is a powerful and efficient design for exploring possible multiplicative interactions between factors that are independent of one another. The purpose of our study was to use this exploratory design to identify potential pair wise SNP-SNP interactions from genes involved in several different immune-related pathways for investigation in future studies. The study population consisted of two case groups: 1,224 histologic confirmed, non-Hispanic white glioma cases from the United States and a validation population of 634 glioma cases from the United Kingdom. Polytomous logistic regression, in which one SNP was coded as the outcome and the other SNP was included as the exposure, was utilized to calculate the ORs of the likelihood of cases simultaneously having the variant alleles of two different SNPs. Potential interactions were examined only between SNPs located in different genes or chromosomes. Using this data mining strategy, we found 396 significant SNP-SNP interactions among polymorphisms of immune-related genes that were present in both the U.S. and U.K. study populations. This exploratory study was conducted for the purpose of hypothesis generation, and thus has provided several new hypotheses that can be tested using traditional case-control study designs to obtain estimates of risk. This is the first study, to our knowledge, to take this novel approach to identifying SNP-SNP interactions relevant to glioma etiology. ©2011 AACR.

Epistatic Interactions Among Herbicide Resistances in Arabidopsis thaliana: The Fitness Cost of Multiresistance

PubMed Central

Roux, Fabrice; Camilleri, Christine; Giancola, Sandra; Brunel, Dominique; Reboud, Xavier

2005-01-01

The type of interactions among deleterious mutations is considered to be crucial in numerous areas of evolutionary biology, including the evolution of sex and recombination, the evolution of ploidy, the evolution of selfing, and the conservation of small populations. Because the herbicide resistance genes could be viewed as slightly deleterious mutations in the absence of the pesticide selection pressure, the epistatic interactions among three herbicide resistance genes (acetolactate synthase CSR, cellulose synthase IXR1, and auxin-induced AXR1 target genes) were estimated in both the homozygous and the heterozygous states, giving 27 genotype combinations in the model plant Arabidopsis thaliana. By analyzing eight quantitative traits in a segregating population for the three herbicide resistances in the absence of herbicide, we found that most interactions in both the homozygous and the heterozygous states were best explained by multiplicative effects (each additional resistance gene causes a comparable reduction in fitness) rather than by synergistic effects (each additional resistance gene causes a disproportionate fitness reduction). Dominance coefficients of the herbicide resistance cost ranged from partial dominance to underdominance, with a mean dominance coefficient of 0.07. It was suggested that the csr1-1, ixr1-2, and axr1-3 resistance alleles are nearly fully recessive for the fitness cost. More interestingly, the dominance of a specific resistance gene in the absence of herbicide varied according to, first, the presence of the other resistance genes and, second, the quantitative trait analyzed. These results and their implications for multiresistance evolution are discussed in relation to the maintenance of polymorphism at resistance loci in a heterogeneous environment. PMID:16020787

Versatile types of polysaccharide-based supramolecular polycation/pDNA nanoplexes for gene delivery

NASA Astrophysics Data System (ADS)

Hu, Yang; Zhao, Nana; Yu, Bingran; Liu, Fusheng; Xu, Fu-Jian

2014-06-01

Different polysaccharide-based supramolecular polycations were readily synthesized by assembling multiple β-cyclodextrin-cored star polycations with an adamantane-functionalized dextran via host-guest interaction in the absence or presence of bioreducible linkages. Compared with nanoplexes of the starting star polycation and pDNA, the supramolecular polycation/pDNA nanoplexes exhibited similarly low cytotoxicity, improved cellular internalization and significantly higher gene transfection efficiencies. The incorporation of disulfide linkages imparted the supramolecular polycation/pDNA nanoplexes with the advantage of intracellular bioreducibility, resulting in better gene delivery properties. In addition, the antitumor properties of supramolecular polycation/pDNA nanoplexes were also investigated using a suicide gene therapy system. The present study demonstrates that the proper assembly of cyclodextrin-cored polycations with adamantane-functionalized polysaccharides is an effective strategy for the production of new nanoplex delivery systems.Different polysaccharide-based supramolecular polycations were readily synthesized by assembling multiple β-cyclodextrin-cored star polycations with an adamantane-functionalized dextran via host-guest interaction in the absence or presence of bioreducible linkages. Compared with nanoplexes of the starting star polycation and pDNA, the supramolecular polycation/pDNA nanoplexes exhibited similarly low cytotoxicity, improved cellular internalization and significantly higher gene transfection efficiencies. The incorporation of disulfide linkages imparted the supramolecular polycation/pDNA nanoplexes with the advantage of intracellular bioreducibility, resulting in better gene delivery properties. In addition, the antitumor properties of supramolecular polycation/pDNA nanoplexes were also investigated using a suicide gene therapy system. The present study demonstrates that the proper assembly of cyclodextrin-cored polycations with adamantane-functionalized polysaccharides is an effective strategy for the production of new nanoplex delivery systems. Electronic supplementary information (ESI) available: 1H NMR assay and synthetic route of Dex-Ad and Dex-SS-Ad. See DOI: 10.1039/c4nr01590h

Predicting type 2 diabetes using genetic and environmental risk factors in a multi-ethnic Malaysian cohort.

PubMed

Abdullah, N; Abdul Murad, N A; Mohd Haniff, E A; Syafruddin, S E; Attia, J; Oldmeadow, C; Kamaruddin, M A; Abd Jalal, N; Ismail, N; Ishak, M; Jamal, R; Scott, R J; Holliday, E G

2017-08-01

Malaysia has a high and rising prevalence of type 2 diabetes (T2D). While environmental (non-genetic) risk factors for the disease are well established, the role of genetic variations and gene-environment interactions remain understudied in this population. This study aimed to estimate the relative contributions of environmental and genetic risk factors to T2D in Malaysia and also to assess evidence for gene-environment interactions that may explain additional risk variation. This was a case-control study including 1604 Malays, 1654 Chinese and 1728 Indians from the Malaysian Cohort Project. The proportion of T2D risk variance explained by known genetic and environmental factors was assessed by fitting multivariable logistic regression models and evaluating McFadden's pseudo R 2 and the area under the receiver-operating characteristic curve (AUC). Models with and without the genetic risk score (GRS) were compared using the log likelihood ratio Chi-squared test and AUCs. Multiplicative interaction between genetic and environmental risk factors was assessed via logistic regression within and across ancestral groups. Interactions were assessed for the GRS and its 62 constituent variants. The models including environmental risk factors only had pseudo R 2 values of 16.5-28.3% and AUC of 0.75-0.83. Incorporating a genetic score aggregating 62 T2D-associated risk variants significantly increased the model fit (likelihood ratio P-value of 2.50 × 10 -4 -4.83 × 10 -12 ) and increased the pseudo R 2 by about 1-2% and AUC by 1-3%. None of the gene-environment interactions reached significance after multiple testing adjustment, either for the GRS or individual variants. For individual variants, 33 out of 310 tested associations showed nominal statistical significance with 0.001 < P < 0.05. This study suggests that known genetic risk variants contribute a significant but small amount to overall T2D risk variation in Malaysian population groups. If gene-environment interactions involving common genetic variants exist, they are likely of small effect, requiring substantially larger samples for detection. Copyright © 2017 The Royal Society for Public Health. All rights reserved.

BURRITO: An Interactive Multi-Omic Tool for Visualizing Taxa–Function Relationships in Microbiome Data

PubMed Central

McNally, Colin P.; Eng, Alexander; Noecker, Cecilia; Gagne-Maynard, William C.; Borenstein, Elhanan

2018-01-01

The abundance of both taxonomic groups and gene categories in microbiome samples can now be easily assayed via various sequencing technologies, and visualized using a variety of software tools. However, the assemblage of taxa in the microbiome and its gene content are clearly linked, and tools for visualizing the relationship between these two facets of microbiome composition and for facilitating exploratory analysis of their co-variation are lacking. Here we introduce BURRITO, a web tool for interactive visualization of microbiome multi-omic data with paired taxonomic and functional information. BURRITO simultaneously visualizes the taxonomic and functional compositions of multiple samples and dynamically highlights relationships between taxa and functions to capture the underlying structure of these data. Users can browse for taxa and functions of interest and interactively explore the share of each function attributed to each taxon across samples. BURRITO supports multiple input formats for taxonomic and metagenomic data, allows adjustment of data granularity, and can export generated visualizations as static publication-ready formatted figures. In this paper, we describe the functionality of BURRITO, and provide illustrative examples of its utility for visualizing various trends in the relationship between the composition of taxa and functions in complex microbiomes. PMID:29545787

Genome-wide mapping in a house mouse hybrid zone reveals hybrid sterility loci and Dobzhansky-Muller interactions.

PubMed

Turner, Leslie M; Harr, Bettina

2014-12-09

Mapping hybrid defects in contact zones between incipient species can identify genomic regions contributing to reproductive isolation and reveal genetic mechanisms of speciation. The house mouse features a rare combination of sophisticated genetic tools and natural hybrid zones between subspecies. Male hybrids often show reduced fertility, a common reproductive barrier between incipient species. Laboratory crosses have identified sterility loci, but each encompasses hundreds of genes. We map genetic determinants of testis weight and testis gene expression using offspring of mice captured in a hybrid zone between M. musculus musculus and M. m. domesticus. Many generations of admixture enables high-resolution mapping of loci contributing to these sterility-related phenotypes. We identify complex interactions among sterility loci, suggesting multiple, non-independent genetic incompatibilities contribute to barriers to gene flow in the hybrid zone.

Detecting cells in time varying intensity images in confocal microscopy for gene expression studies in living cells

NASA Astrophysics Data System (ADS)

Mitra, Debasis; Boutchko, Rostyslav; Ray, Judhajeet; Nilsen-Hamilton, Marit

2015-03-01

In this work we present a time-lapsed confocal microscopy image analysis technique for an automated gene expression study of multiple single living cells. Fluorescence Resonance Energy Transfer (FRET) is a technology by which molecule-to-molecule interactions are visualized. We analyzed a dynamic series of ~102 images obtained using confocal microscopy of fluorescence in yeast cells containing RNA reporters that give a FRET signal when the gene promoter is activated. For each time frame, separate images are available for three spectral channels and the integrated intensity snapshot of the system. A large number of time-lapsed frames must be analyzed to identify each cell individually across time and space, as it is moving in and out of the focal plane of the microscope. This makes it a difficult image processing problem. We have proposed an algorithm here, based on scale-space technique, which solves the problem satisfactorily. The algorithm has multiple directions for even further improvement. The ability to rapidly measure changes in gene expression simultaneously in many cells in a population will open the opportunity for real-time studies of the heterogeneity of genetic response in a living cell population and the interactions between cells that occur in a mixed population, such as the ones found in the organs and tissues of multicellular organisms.

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

PubMed

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.

Detection of Epistasis for Flowering Time Using Bayesian Multilocus Estimation in a Barley MAGIC Population

PubMed Central

Mathew, Boby; Léon, Jens; Sannemann, Wiebke; Sillanpää, Mikko J.

2018-01-01

Gene-by-gene interactions, also known as epistasis, regulate many complex traits in different species. With the availability of low-cost genotyping it is now possible to study epistasis on a genome-wide scale. However, identifying genome-wide epistasis is a high-dimensional multiple regression problem and needs the application of dimensionality reduction techniques. Flowering Time (FT) in crops is a complex trait that is known to be influenced by many interacting genes and pathways in various crops. In this study, we successfully apply Sure Independence Screening (SIS) for dimensionality reduction to identify two-way and three-way epistasis for the FT trait in a Multiparent Advanced Generation Inter-Cross (MAGIC) barley population using the Bayesian multilocus model. The MAGIC barley population was generated from intercrossing among eight parental lines and thus, offered greater genetic diversity to detect higher-order epistatic interactions. Our results suggest that SIS is an efficient dimensionality reduction approach to detect high-order interactions in a Bayesian multilocus model. We also observe that many of our findings (genomic regions with main or higher-order epistatic effects) overlap with known candidate genes that have been already reported in barley and closely related species for the FT trait. PMID:29254994

Use of Network Inference to Elucidate Common and Chemical-specific Effects on Steoidogenesis

EPA Science Inventory

Microarray data is a key source for modeling gene regulatory interactions. Regulatory network models based on multiple datasets are potentially more robust and can provide greater confidence. In this study, we used network modeling on microarray data generated by exposing the fat...

Promoter-enhancer interactions identified from Hi-C data using probabilistic models and hierarchical topological domains.

PubMed

Ron, Gil; Globerson, Yuval; Moran, Dror; Kaplan, Tommy

2017-12-21

Proximity-ligation methods such as Hi-C allow us to map physical DNA-DNA interactions along the genome, and reveal its organization into topologically associating domains (TADs). As the Hi-C data accumulate, computational methods were developed for identifying domain borders in multiple cell types and organisms. Here, we present PSYCHIC, a computational approach for analyzing Hi-C data and identifying promoter-enhancer interactions. We use a unified probabilistic model to segment the genome into domains, which we then merge hierarchically and fit using a local background model, allowing us to identify over-represented DNA-DNA interactions across the genome. By analyzing the published Hi-C data sets in human and mouse, we identify hundreds of thousands of putative enhancers and their target genes, and compile an extensive genome-wide catalog of gene regulation in human and mouse. As we show, our predictions are highly enriched for ChIP-seq and DNA accessibility data, evolutionary conservation, eQTLs and other DNA-DNA interaction data.

Gene-environment interaction between adiponectin gene polymorphisms and environmental factors on the risk of diabetic retinopathy.

PubMed

Li, Yuan; Wu, Qun Hong; Jiao, Ming Li; Fan, Xiao Hong; Hu, Quan; Hao, Yan Hua; Liu, Ruo Hong; Zhang, Wei; Cui, Yu; Han, Li Yuan

2015-01-01

To evaluate whether the adiponectin gene is associated with diabetic retinopathy (DR) risk and interaction with environmental factors modifies the DR risk, and to investigate the relationship between serum adiponectin levels and DR. Four adiponectin polymorphisms were evaluated in 372 DR cases and 145 controls. Differences in environmental factors between cases and controls were evaluated by unconditional logistic regression analysis. The model-free multifactor dimensionality reduction method and traditional multiple regression models were applied to explore interactions between the polymorphisms and environmental factors. Using the Bonferroni method, we found no significant associations between four adiponectin polymorphisms and DR susceptibility. Multivariate logistic regression found that physical activity played a protective role in the progress of DR, whereas family history of diabetes (odds ratio 1.75) and insulin therapy (odds ratio 1.78) were associated with an increased risk for DR. The interaction between the C-11377 G (rs266729) polymorphism and insulin therapy might be associated with DR risk. Family history of diabetes combined with insulin therapy also increased the risk of DR. No adiponectin gene polymorphisms influenced the serum adiponectin levels. Serum adiponectin levels did not differ between the DR group and non-DR group. No significant association was identified between four adiponectin polymorphisms and DR susceptibility after stringent Bonferroni correction. The interaction between C-11377G (rs266729) polymorphism and insulin therapy, as well as the interaction between family history of diabetes and insulin therapy, might be associated with DR susceptibility.

A MAOA gene*cocaine severity interaction on impulsivity and neuropsychological measures of orbitofrontal dysfunction: preliminary results.

PubMed

Verdejo-García, Antonio; Albein-Urios, Natalia; Molina, Esther; Ching-López, Ana; Martínez-González, José M; Gutiérrez, Blanca

2013-11-01

Based on previous evidence of a MAOA gene*cocaine use interaction on orbitofrontal cortex volume attrition, we tested whether the MAOA low activity variant and cocaine use severity are interactively associated with impulsivity and behavioral indices of orbitofrontal dysfunction: emotion recognition and decision-making. 72 cocaine dependent individuals and 52 non-drug using controls (including healthy individuals and problem gamblers) were genotyped for the MAOA gene and tested using the UPPS-P Impulsive Behavior Scale, the Iowa Gambling Task and the Ekman's Facial Emotions Recognition Test. To test the main hypothesis, we conducted hierarchical multiple regression analyses including three sets of predictors: (1) age, (2) MAOA genotype and severity of cocaine use, and (3) the interaction between MAOA genotype and severity of cocaine use. UPPS-P, Ekman Test and Iowa Gambling Task's scores were the outcome measures. We computed the statistical significance of the prediction change yielded by each consecutive set, with 'a priori' interest in the MAOA*cocaine severity interaction. We found significant effects of the MAOA gene*cocaine use severity interaction on the emotion recognition scores and the UPPS-P's dimensions of Positive Urgency and Sensation Seeking: Low activity carriers with higher cocaine exposure had poorer emotion recognition and higher Positive Urgency and Sensation Seeking. Cocaine users carrying the MAOA low activity show a greater impact of cocaine use on impulsivity and behavioral measures of orbitofrontal cortex dysfunction. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Detecting epistasis with the marginal epistasis test in genetic mapping studies of quantitative traits

PubMed Central

Zeng, Ping; Mukherjee, Sayan; Zhou, Xiang

2017-01-01

Epistasis, commonly defined as the interaction between multiple genes, is an important genetic component underlying phenotypic variation. Many statistical methods have been developed to model and identify epistatic interactions between genetic variants. However, because of the large combinatorial search space of interactions, most epistasis mapping methods face enormous computational challenges and often suffer from low statistical power due to multiple test correction. Here, we present a novel, alternative strategy for mapping epistasis: instead of directly identifying individual pairwise or higher-order interactions, we focus on mapping variants that have non-zero marginal epistatic effects—the combined pairwise interaction effects between a given variant and all other variants. By testing marginal epistatic effects, we can identify candidate variants that are involved in epistasis without the need to identify the exact partners with which the variants interact, thus potentially alleviating much of the statistical and computational burden associated with standard epistatic mapping procedures. Our method is based on a variance component model, and relies on a recently developed variance component estimation method for efficient parameter inference and p-value computation. We refer to our method as the “MArginal ePIstasis Test”, or MAPIT. With simulations, we show how MAPIT can be used to estimate and test marginal epistatic effects, produce calibrated test statistics under the null, and facilitate the detection of pairwise epistatic interactions. We further illustrate the benefits of MAPIT in a QTL mapping study by analyzing the gene expression data of over 400 individuals from the GEUVADIS consortium. PMID:28746338

Control of early seed development.

PubMed

Chaudhury, A M; Koltunow, A; Payne, T; Luo, M; Tucker, M R; Dennis, E S; Peacock, W J

2001-01-01

Seed development requires coordinated expression of embryo and endosperm and has contributions from both sporophytic and male and female gametophytic genes. Genetic and molecular analyses in recent years have started to illuminate how products of these multiple genes interact to initiate seed development. Imprinting or differential expression of paternal and maternal genes seems to be involved in controlling seed development, presumably by controlling gene expression in developing endosperm. Epigenetic processes such as chromatin remodeling and DNA methylation affect imprinting of key seed-specific genes; however, the identity of many of these genes remains unknown. The discovery of FIS genes has illuminated control of autonomous endosperm development, a component of apomixis, which is an important developmental and agronomic trait. FIS genes are targets of imprinting, and the genes they control in developing endosperm are also regulated by DNA methylation and chromatin remodeling genes. These results define some exciting future areas of research in seed development.

Genetic modification of the association between peripubertal dioxin exposure and pubertal onset in a cohort of Russian boys.

PubMed

Humblet, Olivier; Korrick, Susan A; Williams, Paige L; Sergeyev, Oleg; Emond, Claude; Birnbaum, Linda S; Burns, Jane S; Altshul, Larisa M; Patterson, Donald G; Turner, Wayman E; Lee, Mary M; Revich, Boris; Hauser, Russ

2013-01-01

Exposure to dioxins has been associated with delayed pubertal onset in both epidemiologic and animal studies. Whether genetic polymorphisms may modify this association is currently unknown. Identifying such genes could provide insight into mechanistic pathways. This is one of the first studies to assess genetic susceptibility to dioxins. We evaluated whether common polymorphisms in genes affecting either molecular responses to dioxin exposure or pubertal onset influence the association between peripubertal serum dioxin concentration and male pubertal onset. In this prospective cohort of Russian adolescent boys (n = 392), we assessed gene-environment interactions for 337 tagging single-nucleotide polymorphisms (SNPs) from 46 candidate genes and two intergenic regions. Dioxins were measured in the boys' serum at age 8-9 years. Pubertal onset was based on testicular volume and on genitalia staging. Statistical approaches for controlling for multiple testing were used, both with and without prescreening for marginal genetic associations. After accounting for multiple testing, two tag SNPs in the glucocorticoid receptor (GR/NR3C1) gene and one in the estrogen receptor-α (ESR1) gene were significant (q < 0.2) modifiers of the association between peripubertal serum dioxin concentration and male pubertal onset defined by genitalia staging, although not by testicular volume. The results were sensitive to whether multiple comparison adjustment was applied to all gene-environment tests or only to those with marginal genetic associations. Common genetic polymorphisms in the glucocorticoid receptor and estrogen receptor-α genes may modify the association between peripubertal serum dioxin concentration and pubertal onset. Further studies are warranted to confirm these findings.

DISC1 regulates new neuron development in the adult brain via modulation of AKT-mTOR signaling through KIAA1212.

PubMed

Kim, Ju Young; Duan, Xin; Liu, Cindy Y; Jang, Mi-Hyeon; Guo, Junjie U; Pow-anpongkul, Nattapol; Kang, Eunchai; Song, Hongjun; Ming, Guo-li

2009-09-24

Disrupted-in-schizophrenia 1 (DISC1), a susceptibility gene for major mental illnesses, regulates multiple aspects of embryonic and adult neurogenesis. Here, we show that DISC1 suppression in newborn neurons of the adult hippocampus leads to overactivated signaling of AKT, another schizophrenia susceptibility gene. Mechanistically, DISC1 directly interacts with KIAA1212, an AKT binding partner that enhances AKT signaling in the absence of DISC1, and DISC1 binding to KIAA1212 prevents AKT activation in vitro. Functionally, multiple genetic manipulations to enhance AKT signaling in adult-born neurons in vivo exhibit similar defects as DISC1 suppression in neuronal development that can be rescued by pharmacological inhibition of mammalian target of rapamycin (mTOR), an AKT downstream effector. Our study identifies the AKT-mTOR signaling pathway as a critical DISC1 target in regulating neuronal development and provides a framework for understanding how multiple susceptibility genes may functionally converge onto a common pathway in contributing to the etiology of certain psychiatric disorders.

Intrinsic incompatibilities evolving as a by-product of divergent ecological selection: Considering them in empirical studies on divergence with gene flow.

PubMed

Kulmuni, J; Westram, A M

2017-06-01

The possibility of intrinsic barriers to gene flow is often neglected in empirical research on local adaptation and speciation with gene flow, for example when interpreting patterns observed in genome scans. However, we draw attention to the fact that, even with gene flow, divergent ecological selection may generate intrinsic barriers involving both ecologically selected and other interacting loci. Mechanistically, the link between the two types of barriers may be generated by genes that have multiple functions (i.e., pleiotropy), and/or by gene interaction networks. Because most genes function in complex networks, and their evolution is not independent of other genes, changes evolving in response to ecological selection can generate intrinsic barriers as a by-product. A crucial question is to what extent such by-product barriers contribute to divergence and speciation-that is whether they stably reduce gene flow. We discuss under which conditions by-product barriers may increase isolation. However, we also highlight that, depending on the conditions (e.g., the amount of gene flow and the strength of selection acting on the intrinsic vs. the ecological barrier component), the intrinsic incompatibility may actually destabilize barriers to gene flow. In practice, intrinsic barriers generated as a by-product of divergent ecological selection may generate peaks in genome scans that cannot easily be interpreted. We argue that empirical studies on divergence with gene flow should consider the possibility of both ecological and intrinsic barriers. Future progress will likely come from work combining population genomic studies, experiments quantifying fitness and molecular studies on protein function and interactions. © 2017 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

The BioGRID Interaction Database: 2011 update

PubMed Central

Stark, Chris; Breitkreutz, Bobby-Joe; Chatr-aryamontri, Andrew; Boucher, Lorrie; Oughtred, Rose; Livstone, Michael S.; Nixon, Julie; Van Auken, Kimberly; Wang, Xiaodong; Shi, Xiaoqi; Reguly, Teresa; Rust, Jennifer M.; Winter, Andrew; Dolinski, Kara; Tyers, Mike

2011-01-01

The Biological General Repository for Interaction Datasets (BioGRID) is a public database that archives and disseminates genetic and protein interaction data from model organisms and humans (http://www.thebiogrid.org). BioGRID currently holds 347 966 interactions (170 162 genetic, 177 804 protein) curated from both high-throughput data sets and individual focused studies, as derived from over 23 000 publications in the primary literature. Complete coverage of the entire literature is maintained for budding yeast (Saccharomyces cerevisiae), fission yeast (Schizosaccharomyces pombe) and thale cress (Arabidopsis thaliana), and efforts to expand curation across multiple metazoan species are underway. The BioGRID houses 48 831 human protein interactions that have been curated from 10 247 publications. Current curation drives are focused on particular areas of biology to enable insights into conserved networks and pathways that are relevant to human health. The BioGRID 3.0 web interface contains new search and display features that enable rapid queries across multiple data types and sources. An automated Interaction Management System (IMS) is used to prioritize, coordinate and track curation across international sites and projects. BioGRID provides interaction data to several model organism databases, resources such as Entrez-Gene and other interaction meta-databases. The entire BioGRID 3.0 data collection may be downloaded in multiple file formats, including PSI MI XML. Source code for BioGRID 3.0 is freely available without any restrictions. PMID:21071413

Environmental and gene-environment interactions and risk of rheumatoid arthritis

PubMed Central

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

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

PubMed

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

2012-08-17

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

Combinatorial interaction between CCM pathway genes precipitates hemorrhagic stroke.

PubMed

Gore, Aniket V; Lampugnani, Maria Grazia; Dye, Louis; Dejana, Elisabetta; Weinstein, Brant M

2008-01-01

Intracranial hemorrhage (ICH) is a particularly severe form of stroke whose etiology remains poorly understood, with a highly variable appearance and onset of the disease (Felbor et al., 2006; Frizzell, 2005; Lucas et al., 2003). In humans, mutations in any one of three CCM genes causes an autosomal dominant genetic ICH disorder characterized by cerebral cavernous malformations (CCM). Recent evidence highlighting multiple interactions between the three CCM gene products and other proteins regulating endothelial junctional integrity suggests that minor deficits in these other proteins could potentially predispose to, or help to initiate, CCM, and that combinations of otherwise silent genetic deficits in both the CCM and interacting proteins might explain some of the variability in penetrance and expressivity of human ICH disorders. Here, we test this idea by combined knockdown of CCM pathway genes in zebrafish. Reducing the function of rap1b, which encodes a Ras GTPase effector protein for CCM1/Krit1, disrupts endothelial junctions in vivo and in vitro, showing it is a crucial player in the CCM pathway. Importantly, a minor reduction of Rap1b in combination with similar reductions in the products of other CCM pathway genes results in a high incidence of ICH. These findings support the idea that minor polygenic deficits in the CCM pathway can strongly synergize to initiate ICH.

Complex Modulation of the Aedes aegypti Transcriptome in Response to Dengue Virus Infection

PubMed Central

Bonizzoni, Mariangela; Dunn, W. Augustine; Campbell, Corey L.; Olson, Ken E.; Marinotti, Osvaldo; James, Anthony A.

2012-01-01

Dengue fever is the most important arboviral disease world-wide, with Aedes aegypti being the major vector. Interactions between the mosquito host and dengue viruses (DENV) are complex and vector competence varies among geographically-distinct Ae. aegypti populations. Additionally, dengue is caused by four antigenically-distinct viral serotypes (DENV1–4), each with multiple genotypes. Each virus genotype interacts differently with vertebrate and invertebrate hosts. Analyses of alterations in mosquito transcriptional profiles during DENV infection are expected to provide the basis for identifying networks of genes involved in responses to viruses and contribute to the molecular-genetic understanding of vector competence. In addition, this knowledge is anticipated to support the development of novel disease-control strategies. RNA-seq technology was used to assess genome-wide changes in transcript abundance at 1, 4 and 14 days following DENV2 infection in carcasses, midguts and salivary glands of the Ae. aegypti Chetumal strain. DENV2 affected the expression of 397 Ae. aegypti genes, most of which were down-regulated by viral infection. Differential accumulation of transcripts was mainly tissue- and time-specific. Comparisons of our data with other published reports reveal conservation of functional classes, but limited concordance of specific mosquito genes responsive to DENV2 infection. These results indicate the necessity of additional studies of mosquito-DENV interactions, specifically those focused on recently-derived mosquito strains with multiple dengue virus serotypes and genotypes. PMID:23209765

Exome sequencing of a colorectal cancer family reveals shared mutation pattern and predisposition circuitry along tumor pathways

PubMed Central

Suleiman, Suleiman H.; Koko, Mahmoud E.; Nasir, Wafaa H.; Elfateh, Ommnyiah; Elgizouli, Ubai K.; Abdallah, Mohammed O. E.; Alfarouk, Khalid O.; Hussain, Ayman; Faisal, Shima; Ibrahim, Fathelrahamn M. A.; Romano, Maurizio; Sultan, Ali; Banks, Lawrence; Newport, Melanie; Baralle, Francesco; Elhassan, Ahmed M.; Mohamed, Hiba S.; Ibrahim, Muntaser E.

2015-01-01

The molecular basis of cancer and cancer multiple phenotypes are not yet fully understood. Next Generation Sequencing promises new insight into the role of genetic interactions in shaping the complexity of cancer. Aiming to outline the differences in mutation patterns between familial colorectal cancer cases and controls we analyzed whole exomes of cancer tissues and control samples from an extended colorectal cancer pedigree, providing one of the first data sets of exome sequencing of cancer in an African population against a background of large effective size typically with excess of variants. Tumors showed hMSH2 loss of function SNV consistent with Lynch syndrome. Sets of genes harboring insertions–deletions in tumor tissues revealed, however, significant GO enrichment, a feature that was not seen in control samples, suggesting that ordered insertions–deletions are central to tumorigenesis in this type of cancer. Network analysis identified multiple hub genes of centrality. ELAVL1/HuR showed remarkable centrality, interacting specially with genes harboring non-synonymous SNVs thus reinforcing the proposition of targeted mutagenesis in cancer pathways. A likely explanation to such mutation pattern is DNA/RNA editing, suggested here by nucleotide transition-to-transversion ratio that significantly departed from expected values (p-value 5e-6). NFKB1 also showed significant centrality along with ELAVL1, raising the suspicion of viral etiology given the known interaction between oncogenic viruses and these proteins. PMID:26442106

A Scalable Approach for Discovering Conserved Active Subnetworks across Species

PubMed Central

Verfaillie, Catherine M.; Hu, Wei-Shou; Myers, Chad L.

2010-01-01

Overlaying differential changes in gene expression on protein interaction networks has proven to be a useful approach to interpreting the cell's dynamic response to a changing environment. Despite successes in finding active subnetworks in the context of a single species, the idea of overlaying lists of differentially expressed genes on networks has not yet been extended to support the analysis of multiple species' interaction networks. To address this problem, we designed a scalable, cross-species network search algorithm, neXus (Network - cross(X)-species - Search), that discovers conserved, active subnetworks based on parallel differential expression studies in multiple species. Our approach leverages functional linkage networks, which provide more comprehensive coverage of functional relationships than physical interaction networks by combining heterogeneous types of genomic data. We applied our cross-species approach to identify conserved modules that are differentially active in stem cells relative to differentiated cells based on parallel gene expression studies and functional linkage networks from mouse and human. We find hundreds of conserved active subnetworks enriched for stem cell-associated functions such as cell cycle, DNA repair, and chromatin modification processes. Using a variation of this approach, we also find a number of species-specific networks, which likely reflect mechanisms of stem cell function that have diverged between mouse and human. We assess the statistical significance of the subnetworks by comparing them with subnetworks discovered on random permutations of the differential expression data. We also describe several case examples that illustrate the utility of comparative analysis of active subnetworks. PMID:21170309

Both the constitutive Cauliflower Mosaic Virus 35S and tissue-specific AGAMOUS enhancers activate transcription autonomously in Arabidopsis thaliana

USDA-ARS?s Scientific Manuscript database

The presence of multiple enhancers and promoters within a single vector often provokes complicated mutual interaction and crosstalk, thereby, altering promoter specificity, which causes serious problems for precisely engineering gene function and agronomic traits in transgenic plants. Enhancer elem...

Differential and functional interactions emphasize the multiple roles of polyamines in plants

USDA-ARS?s Scientific Manuscript database

Biogenic amines putrescine, spermidine and spermine are ubiquitous in nature and have interested researchers because they are essential for cell division and viability, and due to a large body of their pharmacological effects on growth and development in most living cells. The genes and enzymes invo...

A Genome-wide Trans-ethnic Interaction Study Links the PIGR ...

EPA Pesticide Factsheets

Air pollution is a worldwide contributor to cardiovascular disease mortality and morbidity. Traffic air pollution is a ubiquitous source of air pollution in developed nations, and is associated with multiple cardiovascular outcomes such as: coronary atherosclerosis, peripheral arterial disease, and myocardial infarction. Despite the recognition of the importance of both genetic and environmental exposures to the pathogenesis of cardiovascular disease, studies of these two contributors jointly are rare. We performed a genome-wide interaction study (GWIS) to examine gene-traffic exposure interactions associated with coronary atherosclerosis. Using race-stratified cohorts of 554 African-Americans (AA) and 1623 European-Americans (EA) from a cardiac catheterization cohort (CATHGEN), we identify gene-by-traffic exposure interactions associated with the number of significantly diseased coronary vessels as a measure of chronic atherosclerosis. We found five suggestive (P<1x10-5) interactions in the AA GWIS, of which two (rs1856746 and rs2791713) replicated in the EA cohort (P < 0.05). Both SNPs are in the PIGR-FCAMR locus and are eQTLs in lymphocytes. The protein products of both PIGR and FCAMR are implicated in inflammatory processes. In the EA GWIS, there were three suggestive interactions; none of these replicated in the AA GWIS. All three were intergenic; the most significant interaction was in a regulatory region associated with SAMSN1, a gene previously associate

Planar cell polarity pathway genes and risk for spina bifida.

PubMed

Wen, Shu; Zhu, Huiping; Lu, Wei; Mitchell, Laura E; Shaw, Gary M; Lammer, Edward J; Finnell, Richard H

2010-02-01

Spina bifida, a neural tube closure defect (NTD) involving the posterior portion of what will ultimately give rise to the spinal cord, is one of the most common and serious birth defects. The etiology of spina bifida is thought to be multi-factorial and involve multiple interacting genes and environmental factors. The causes of this congenital malformation remain largely unknown. However, several candidate genes for spina bifida have been identified in lower vertebrates, including the planar cell polarity (PCP) genes. We used data from a case-control study conducted in California to evaluate the association between variation within several key PCP genes and the risk of spina bifida. The PCP genes included in this study were the human homologs of the Xenopus genes Flamingo, Strabismus, Prickle, Dishevelled, and Scrib, two of the homologs of Xenopus Wnt genes, WNT5A and WNT11, and two of the homologs of Xenopus Frizzled, FZD3 and FZD6. None of the 172 SNPs that were evaluated were significantly associated with spina bifida in any racial/ethnic group after correction for multiple testing. However, several SNPs in the PRICKLE2 gene had unadjusted P-value <0.01. In conclusion, our results, though largely negative, suggest that the PRICKLE2 gene may potentially modify the risk of spina bifida and deserves further investigation. Copyright 2010 Wiley-Liss, Inc.

Endeavour update: a web resource for gene prioritization in multiple species

PubMed Central

Tranchevent, Léon-Charles; Barriot, Roland; Yu, Shi; Van Vooren, Steven; Van Loo, Peter; Coessens, Bert; De Moor, Bart; Aerts, Stein; Moreau, Yves

2008-01-01

Endeavour (http://www.esat.kuleuven.be/endeavourweb; this web site is free and open to all users and there is no login requirement) is a web resource for the prioritization of candidate genes. Using a training set of genes known to be involved in a biological process of interest, our approach consists of (i) inferring several models (based on various genomic data sources), (ii) applying each model to the candidate genes to rank those candidates against the profile of the known genes and (iii) merging the several rankings into a global ranking of the candidate genes. In the present article, we describe the latest developments of Endeavour. First, we provide a web-based user interface, besides our Java client, to make Endeavour more universally accessible. Second, we support multiple species: in addition to Homo sapiens, we now provide gene prioritization for three major model organisms: Mus musculus, Rattus norvegicus and Caenorhabditis elegans. Third, Endeavour makes use of additional data sources and is now including numerous databases: ontologies and annotations, protein–protein interactions, cis-regulatory information, gene expression data sets, sequence information and text-mining data. We tested the novel version of Endeavour on 32 recent disease gene associations from the literature. Additionally, we describe a number of recent independent studies that made use of Endeavour to prioritize candidate genes for obesity and Type II diabetes, cleft lip and cleft palate, and pulmonary fibrosis. PMID:18508807

The Pathogen-Host Interactions database (PHI-base): additions and future developments.

PubMed

Urban, Martin; Pant, Rashmi; Raghunath, Arathi; Irvine, Alistair G; Pedro, Helder; Hammond-Kosack, Kim E

2015-01-01

Rapidly evolving pathogens cause a diverse array of diseases and epidemics that threaten crop yield, food security as well as human, animal and ecosystem health. To combat infection greater comparative knowledge is required on the pathogenic process in multiple species. The Pathogen-Host Interactions database (PHI-base) catalogues experimentally verified pathogenicity, virulence and effector genes from bacterial, fungal and protist pathogens. Mutant phenotypes are associated with gene information. The included pathogens infect a wide range of hosts including humans, animals, plants, insects, fish and other fungi. The current version, PHI-base 3.6, available at http://www.phi-base.org, stores information on 2875 genes, 4102 interactions, 110 host species, 160 pathogenic species (103 plant, 3 fungal and 54 animal infecting species) and 181 diseases drawn from 1243 references. Phenotypic and gene function information has been obtained by manual curation of the peer-reviewed literature. A controlled vocabulary consisting of nine high-level phenotype terms permits comparisons and data analysis across the taxonomic space. PHI-base phenotypes were mapped via their associated gene information to reference genomes available in Ensembl Genomes. Virulence genes and hotspots can be visualized directly in genome browsers. Future plans for PHI-base include development of tools facilitating community-led curation and inclusion of the corresponding host target(s). © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Interactions between Bt crops and aquatic ecosystems: A review.

PubMed

Venter, Hermoine J; Bøhn, Thomas

2016-12-01

The term Bt crops collectively refers to crops that have been genetically modified to include a gene (or genes) sourced from Bacillus thuringiensis (Bt) bacteria. These genes confer the ability to produce proteins toxic to certain insect pests. The interaction between Bt crops and adjacent aquatic ecosystems has received limited attention in research and risk assessment, despite the fact that some Bt crops have been in commercial use for 20 yr. Reports of effects on aquatic organisms such as Daphnia magna, Elliptio complanata, and Chironomus dilutus suggest that some aquatic species may be negatively affected, whereas other reports suggest that the decreased use of insecticides precipitated by Bt crops may benefit aquatic communities. The present study reviews the literature regarding entry routes and exposure pathways by which aquatic organisms may be exposed to Bt crop material, as well as feeding trials and field surveys that have investigated the effects of Bt-expressing plant material on such organisms. The present review also discusses how Bt crop development has moved past single-gene events, toward multigene stacked varieties that often contain herbicide resistance genes in addition to multiple Bt genes, and how their use (in conjunction with co-technology such as glyphosate/Roundup) may impact and interact with aquatic ecosystems. Lastly, suggestions for further research in this field are provided. Environ Toxicol Chem 2016;35:2891-2902. © 2016 SETAC. © 2016 SETAC.

Prenatal exposure to drinking-water chlorination by-products, cytochrome P450 gene polymorphisms and small-for-gestational-age neonates.

PubMed

Bonou, Samuella G; Levallois, Patrick; Giguère, Yves; Rodriguez, Manuel; Bureau, Alexandre

2017-10-01

Genetic susceptibility may modulate chlorination by-products (CBPs) effects on fetal growth, especially genes coding for the cytochrome P450 involved in the metabolism of CBPs and steroidogenesis. In a case-control study of 1432 mother-child pairs, we assessed the association between maternal and child single nucleotide polymorphisms (SNPs) within CYP1A2, CYP2A6, CYP2D6 and CYP17A1 genes and small-for-gestational-age neonates (SGA<10th percentile) as well as interaction between these SNPs and maternal exposure to trihalomethanes or haloacetic acids (HAAs) during the third trimester of pregnancy. Interactions were found between mother and neonate carrying CYP17A1 rs4919687A and rs743572G alleles and maternal exposure to total trihalomethanes or five regulated HAAs species. However, these interactions became non statistically significant after correction for multiple testing. There is some evidence, albeit weak, of a potential effect modification of the association between CBPs and SGA by SNPs in CYP17A1 gene. Further studies are needed to validate these observations. Copyright © 2017 Elsevier Inc. All rights reserved.

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

PubMed

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

2016-01-01

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

Immunochip Analyses of Epistasis in Rheumatoid Arthritis Confirm Multiple Interactions within MHC and Suggest Novel Non-MHC Epistatic Signals.

PubMed

Wei, Wen-Hua; Loh, Chia-Yin; Worthington, Jane; Eyre, Stephen

2016-05-01

Studying statistical gene-gene interactions (epistasis) has been limited by the difficulties in performance, both statistically and computationally, in large enough sample numbers to gain sufficient power. Three large Immunochip datasets from cohort samples recruited in the United Kingdom, United States, and Sweden with European ancestry were used to examine epistasis in rheumatoid arthritis (RA). A full pairwise search was conducted in the UK cohort using a high-throughput tool and the resultant significant epistatic signals were tested for replication in the United States and Swedish cohorts. A forward selection approach was applied to remove redundant signals, while conditioning on the preidentified additive effects. We detected abundant genome-wide significant (p < 1.0e-13) epistatic signals, all within the MHC region. These signals were reduced substantially, but a proportion remained significant (p < 1.0e-03) in conditional tests. We identified 11 independent epistatic interactions across the entire MHC, each explaining on average 0.12% of the phenotypic variance, nearly all replicated in both replication cohorts. We also identified non-MHC epistatic interactions between RA susceptible loci LOC100506023 and IRF5 with Immunochip-wide significance (p < 1.1e-08) and between 2 neighboring single-nucleotide polymorphism near PTPN22 that were in low linkage disequilibrium with independent interaction (p < 1.0e-05). Both non-MHC epistatic interactions were statistically replicated with a similar interaction pattern in the US cohort only. There are multiple but relatively weak interactions independent of the additive effects in RA and a larger sample number is required to confidently assign additional non-MHC epistasis.

Dissecting the Gene Network of Dietary Restriction to Identify Evolutionarily Conserved Pathways and New Functional Genes

PubMed Central

Wuttke, Daniel; Connor, Richard; Vora, Chintan; Craig, Thomas; Li, Yang; Wood, Shona; Vasieva, Olga; Shmookler Reis, Robert; Tang, Fusheng; de Magalhães, João Pedro

2012-01-01

Dietary restriction (DR), limiting nutrient intake from diet without causing malnutrition, delays the aging process and extends lifespan in multiple organisms. The conserved life-extending effect of DR suggests the involvement of fundamental mechanisms, although these remain a subject of debate. To help decipher the life-extending mechanisms of DR, we first compiled a list of genes that if genetically altered disrupt or prevent the life-extending effects of DR. We called these DR–essential genes and identified more than 100 in model organisms such as yeast, worms, flies, and mice. In order for other researchers to benefit from this first curated list of genes essential for DR, we established an online database called GenDR (http://genomics.senescence.info/diet/). To dissect the interactions of DR–essential genes and discover the underlying lifespan-extending mechanisms, we then used a variety of network and systems biology approaches to analyze the gene network of DR. We show that DR–essential genes are more conserved at the molecular level and have more molecular interactions than expected by chance. Furthermore, we employed a guilt-by-association method to predict novel DR–essential genes. In budding yeast, we predicted nine genes related to vacuolar functions; we show experimentally that mutations deleting eight of those genes prevent the life-extending effects of DR. Three of these mutants (OPT2, FRE6, and RCR2) had extended lifespan under ad libitum, indicating that the lack of further longevity under DR is not caused by a general compromise of fitness. These results demonstrate how network analyses of DR using GenDR can be used to make phenotypically relevant predictions. Moreover, gene-regulatory circuits reveal that the DR–induced transcriptional signature in yeast involves nutrient-sensing, stress responses and meiotic transcription factors. Finally, comparing the influence of gene expression changes during DR on the interactomes of multiple organisms led us to suggest that DR commonly suppresses translation, while stimulating an ancient reproduction-related process. PMID:22912585

Differential Anoxic Expression of Sugar-Regulated Genes Reveals Diverse Interactions between Sugar and Anaerobic Signaling Systems in Rice

PubMed Central

Lim, Mi-na; Lee, Sung-eun; Yim, Hui-kyeong; Kim, Jeong Hoe; Yoon, In Sun; Hwang, Yong-sic

2013-01-01

The interaction between the dual roles of sugar as a metabolic fuel and a regulatory molecule was unveiled by examining the changes in sugar signaling upon oxygen deprivation, which causes the drastic alteration in the cellular energy status. In our study, the expression of anaerobically induced genes is commonly responsive to sugar, either under the control of hexokinase or non-hexokinase mediated signaling cascades. Only sugar regulation via the hexokinase pathway was susceptible for O2 deficiency or energy deficit conditions evoked by uncoupler. Examination of sugar regulation of those genes under anaerobic conditions revealed the presence of multiple paths underlying anaerobic induction of gene expression in rice, subgrouped into three distinct types. The first of these, which was found in type-1 genes, involved neither sugar regulation nor additional anaerobic induction under anoxia, indicating that anoxic induction is a simple result from the release of sugar repression by O2-deficient conditions. In contrast, type-2 genes also showed no sugar regulation, albeit with enhanced expression under anoxia. Lastly, expression of type-3 genes is highly enhanced with sugar regulation sustained under anoxia. Intriguingly, the inhibition of the mitochondrial ATP synthesis can reproduce expression pattern of a specific set of anaerobically induced genes, implying that rice cells may sense O2 deprivation, partly via perception of the perturbed cellular energy status. Our study of interaction between sugar signaling and anaerobic conditions has revealed that sugar signaling and the cellular energy status are likely to communicate with each other and influence anaerobic induction of gene expression in rice. PMID:23852132

Systematic reconstruction of autism biology from massive genetic mutation profiles

PubMed Central

Zhang, Chaolin; Jiang, Yong-hui

2018-01-01

Autism spectrum disorder (ASD) affects 1% of world population and has become a pressing medical and social problem worldwide. As a paradigmatic complex genetic disease, ASD has been intensively studied and thousands of gene mutations have been reported. Because these mutations rarely recur, it is difficult to (i) pinpoint the fewer disease-causing versus majority random events and (ii) replicate or verify independent studies. A coherent and systematic understanding of autism biology has not been achieved. We analyzed 3392 and 4792 autism-related mutations from two large-scale whole-exome studies across multiple resolution levels, that is, variants (single-nucleotide), genes (protein-coding unit), and pathways (molecular module). These mutations do not recur or replicate at the variant level, but significantly and increasingly do so at gene and pathway levels. Genetic association reveals a novel gene + pathway dual-hit model, where the mutation burden becomes less relevant. In multiple independent analyses, hundreds of variants or genes repeatedly converge to several canonical pathways, either novel or literature-supported. These pathways define recurrent and systematic ASD biology, distinct from previously reported gene groups or networks. They also present a catalog of novel ASD risk factors including 118 variants and 72 genes. At a subpathway level, most variants disrupt the pathway-related gene functions, and in the same gene, they tend to hit residues extremely close to each other and in the same domain. Multiple interacting variants spotlight key modules, including the cAMP (adenosine 3′,5′-monophosphate) second-messenger system and mGluR (metabotropic glutamate receptor) signaling regulation by GRKs (G protein–coupled receptor kinases). At a superpathway level, distinct pathways further interconnect and converge to three biology themes: synaptic function, morphology, and plasticity. PMID:29651456

Systematic reconstruction of autism biology from massive genetic mutation profiles.

PubMed

Luo, Weijun; Zhang, Chaolin; Jiang, Yong-Hui; Brouwer, Cory R

2018-04-01

Autism spectrum disorder (ASD) affects 1% of world population and has become a pressing medical and social problem worldwide. As a paradigmatic complex genetic disease, ASD has been intensively studied and thousands of gene mutations have been reported. Because these mutations rarely recur, it is difficult to (i) pinpoint the fewer disease-causing versus majority random events and (ii) replicate or verify independent studies. A coherent and systematic understanding of autism biology has not been achieved. We analyzed 3392 and 4792 autism-related mutations from two large-scale whole-exome studies across multiple resolution levels, that is, variants (single-nucleotide), genes (protein-coding unit), and pathways (molecular module). These mutations do not recur or replicate at the variant level, but significantly and increasingly do so at gene and pathway levels. Genetic association reveals a novel gene + pathway dual-hit model, where the mutation burden becomes less relevant. In multiple independent analyses, hundreds of variants or genes repeatedly converge to several canonical pathways, either novel or literature-supported. These pathways define recurrent and systematic ASD biology, distinct from previously reported gene groups or networks. They also present a catalog of novel ASD risk factors including 118 variants and 72 genes. At a subpathway level, most variants disrupt the pathway-related gene functions, and in the same gene, they tend to hit residues extremely close to each other and in the same domain. Multiple interacting variants spotlight key modules, including the cAMP (adenosine 3',5'-monophosphate) second-messenger system and mGluR (metabotropic glutamate receptor) signaling regulation by GRKs (G protein-coupled receptor kinases). At a superpathway level, distinct pathways further interconnect and converge to three biology themes: synaptic function, morphology, and plasticity.

Transcriptional Dysregulation of MYC Reveals Common Enhancer-Docking Mechanism.

PubMed

Schuijers, Jurian; Manteiga, John Colonnese; Weintraub, Abraham Selby; Day, Daniel Sindt; Zamudio, Alicia Viridiana; Hnisz, Denes; Lee, Tong Ihn; Young, Richard Allen

2018-04-10

Transcriptional dysregulation of the MYC oncogene is among the most frequent events in aggressive tumor cells, and this is generally accomplished by acquisition of a super-enhancer somewhere within the 2.8 Mb TAD where MYC resides. We find that these diverse cancer-specific super-enhancers, differing in size and location, interact with the MYC gene through a common and conserved CTCF binding site located 2 kb upstream of the MYC promoter. Genetic perturbation of this enhancer-docking site in tumor cells reduces CTCF binding, super-enhancer interaction, MYC gene expression, and cell proliferation. CTCF binding is highly sensitive to DNA methylation, and this enhancer-docking site, which is hypomethylated in diverse cancers, can be inactivated through epigenetic editing with dCas9-DNMT. Similar enhancer-docking sites occur at other genes, including genes with prominent roles in multiple cancers, suggesting a mechanism by which tumor cell oncogenes can generally hijack enhancers. These results provide insights into mechanisms that allow a single target gene to be regulated by diverse enhancer elements in different cell types. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Phytoplankton-bacterial interactions mediate micronutrient colimitation at the coastal Antarctic sea ice edge.

PubMed

Bertrand, Erin M; McCrow, John P; Moustafa, Ahmed; Zheng, Hong; McQuaid, Jeffrey B; Delmont, Tom O; Post, Anton F; Sipler, Rachel E; Spackeen, Jenna L; Xu, Kai; Bronk, Deborah A; Hutchins, David A; Allen, Andrew E

2015-08-11

Southern Ocean primary productivity plays a key role in global ocean biogeochemistry and climate. At the Southern Ocean sea ice edge in coastal McMurdo Sound, we observed simultaneous cobalamin and iron limitation of surface water phytoplankton communities in late Austral summer. Cobalamin is produced only by bacteria and archaea, suggesting phytoplankton-bacterial interactions must play a role in this limitation. To characterize these interactions and investigate the molecular basis of multiple nutrient limitation, we examined transitions in global gene expression over short time scales, induced by shifts in micronutrient availability. Diatoms, the dominant primary producers, exhibited transcriptional patterns indicative of co-occurring iron and cobalamin deprivation. The major contributor to cobalamin biosynthesis gene expression was a gammaproteobacterial population, Oceanospirillaceae ASP10-02a. This group also contributed significantly to metagenomic cobalamin biosynthesis gene abundance throughout Southern Ocean surface waters. Oceanospirillaceae ASP10-02a displayed elevated expression of organic matter acquisition and cell surface attachment-related genes, consistent with a mutualistic relationship in which they are dependent on phytoplankton growth to fuel cobalamin production. Separate bacterial groups, including Methylophaga, appeared to rely on phytoplankton for carbon and energy sources, but displayed gene expression patterns consistent with iron and cobalamin deprivation. This suggests they also compete with phytoplankton and are important cobalamin consumers. Expression patterns of siderophore- related genes offer evidence for bacterial influences on iron availability as well. The nature and degree of this episodic colimitation appear to be mediated by a series of phytoplankton-bacterial interactions in both positive and negative feedback loops.

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

PubMed

Enoch, Mary-Anne

2006-12-01

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

Phytoplankton–bacterial interactions mediate micronutrient colimitation at the coastal Antarctic sea ice edge

PubMed Central

Bertrand, Erin M.; McCrow, John P.; Moustafa, Ahmed; Zheng, Hong; McQuaid, Jeffrey B.; Delmont, Tom O.; Post, Anton F.; Sipler, Rachel E.; Spackeen, Jenna L.; Xu, Kai; Bronk, Deborah A.; Hutchins, David A.; Allen, Andrew E.

2015-01-01

Southern Ocean primary productivity plays a key role in global ocean biogeochemistry and climate. At the Southern Ocean sea ice edge in coastal McMurdo Sound, we observed simultaneous cobalamin and iron limitation of surface water phytoplankton communities in late Austral summer. Cobalamin is produced only by bacteria and archaea, suggesting phytoplankton–bacterial interactions must play a role in this limitation. To characterize these interactions and investigate the molecular basis of multiple nutrient limitation, we examined transitions in global gene expression over short time scales, induced by shifts in micronutrient availability. Diatoms, the dominant primary producers, exhibited transcriptional patterns indicative of co-occurring iron and cobalamin deprivation. The major contributor to cobalamin biosynthesis gene expression was a gammaproteobacterial population, Oceanospirillaceae ASP10-02a. This group also contributed significantly to metagenomic cobalamin biosynthesis gene abundance throughout Southern Ocean surface waters. Oceanospirillaceae ASP10-02a displayed elevated expression of organic matter acquisition and cell surface attachment-related genes, consistent with a mutualistic relationship in which they are dependent on phytoplankton growth to fuel cobalamin production. Separate bacterial groups, including Methylophaga, appeared to rely on phytoplankton for carbon and energy sources, but displayed gene expression patterns consistent with iron and cobalamin deprivation. This suggests they also compete with phytoplankton and are important cobalamin consumers. Expression patterns of siderophore- related genes offer evidence for bacterial influences on iron availability as well. The nature and degree of this episodic colimitation appear to be mediated by a series of phytoplankton–bacterial interactions in both positive and negative feedback loops. PMID:26221022

Distinct self-interaction domains promote Multi Sex Combs accumulation in and formation of the Drosophila histone locus body

PubMed Central

Terzo, Esteban A.; Lyons, Shawn M.; Poulton, John S.; Temple, Brenda R. S.; Marzluff, William F.; Duronio, Robert J.

2015-01-01

Nuclear bodies (NBs) are structures that concentrate proteins, RNAs, and ribonucleoproteins that perform functions essential to gene expression. How NBs assemble is not well understood. We studied the Drosophila histone locus body (HLB), a NB that concentrates factors required for histone mRNA biosynthesis at the replication-dependent histone gene locus. We coupled biochemical analysis with confocal imaging of both fixed and live tissues to demonstrate that the Drosophila Multi Sex Combs (Mxc) protein contains multiple domains necessary for HLB assembly. An important feature of this assembly process is the self-interaction of Mxc via two conserved N-terminal domains: a LisH domain and a novel self-interaction facilitator (SIF) domain immediately downstream of the LisH domain. Molecular modeling suggests that the LisH and SIF domains directly interact, and mutation of either the LisH or the SIF domain severely impairs Mxc function in vivo, resulting in reduced histone mRNA accumulation. A region of Mxc between amino acids 721 and 1481 is also necessary for HLB assembly independent of the LisH and SIF domains. Finally, the C-terminal 195 amino acids of Mxc are required for recruiting FLASH, an essential histone mRNA-processing factor, to the HLB. We conclude that multiple domains of the Mxc protein promote HLB assembly in order to concentrate factors required for histone mRNA biosynthesis. PMID:25694448

References for Haplotype Imputation in the Big Data Era

PubMed Central

Li, Wenzhi; Xu, Wei; Li, Qiling; Ma, Li; Song, Qing

2016-01-01

Imputation is a powerful in silico approach to fill in those missing values in the big datasets. This process requires a reference panel, which is a collection of big data from which the missing information can be extracted and imputed. Haplotype imputation requires ethnicity-matched references; a mismatched reference panel will significantly reduce the quality of imputation. However, currently existing big datasets cover only a small number of ethnicities, there is a lack of ethnicity-matched references for many ethnic populations in the world, which has hampered the data imputation of haplotypes and its downstream applications. To solve this issue, several approaches have been proposed and explored, including the mixed reference panel, the internal reference panel and genotype-converted reference panel. This review article provides the information and comparison between these approaches. Increasing evidence showed that not just one or two genetic elements dictate the gene activity and functions; instead, cis-interactions of multiple elements dictate gene activity. Cis-interactions require the interacting elements to be on the same chromosome molecule, therefore, haplotype analysis is essential for the investigation of cis-interactions among multiple genetic variants at different loci, and appears to be especially important for studying the common diseases. It will be valuable in a wide spectrum of applications from academic research, to clinical diagnosis, prevention, treatment, and pharmaceutical industry. PMID:27274952

Genome-wide mapping in a house mouse hybrid zone reveals hybrid sterility loci and Dobzhansky-Muller interactions

PubMed Central

Turner, Leslie M; Harr, Bettina

2014-01-01

Mapping hybrid defects in contact zones between incipient species can identify genomic regions contributing to reproductive isolation and reveal genetic mechanisms of speciation. The house mouse features a rare combination of sophisticated genetic tools and natural hybrid zones between subspecies. Male hybrids often show reduced fertility, a common reproductive barrier between incipient species. Laboratory crosses have identified sterility loci, but each encompasses hundreds of genes. We map genetic determinants of testis weight and testis gene expression using offspring of mice captured in a hybrid zone between M. musculus musculus and M. m. domesticus. Many generations of admixture enables high-resolution mapping of loci contributing to these sterility-related phenotypes. We identify complex interactions among sterility loci, suggesting multiple, non-independent genetic incompatibilities contribute to barriers to gene flow in the hybrid zone. DOI: http://dx.doi.org/10.7554/eLife.02504.001 PMID:25487987

Wisdom of crowds for robust gene network inference

PubMed Central

Marbach, Daniel; Costello, James C.; Küffner, Robert; Vega, Nicci; Prill, Robert J.; Camacho, Diogo M.; Allison, Kyle R.; Kellis, Manolis; Collins, James J.; Stolovitzky, Gustavo

2012-01-01

Reconstructing gene regulatory networks from high-throughput data is a long-standing problem. Through the DREAM project (Dialogue on Reverse Engineering Assessment and Methods), we performed a comprehensive blind assessment of over thirty network inference methods on Escherichia coli, Staphylococcus aureus, Saccharomyces cerevisiae, and in silico microarray data. We characterize performance, data requirements, and inherent biases of different inference approaches offering guidelines for both algorithm application and development. We observe that no single inference method performs optimally across all datasets. In contrast, integration of predictions from multiple inference methods shows robust and high performance across diverse datasets. Thereby, we construct high-confidence networks for E. coli and S. aureus, each comprising ~1700 transcriptional interactions at an estimated precision of 50%. We experimentally test 53 novel interactions in E. coli, of which 23 were supported (43%). Our results establish community-based methods as a powerful and robust tool for the inference of transcriptional gene regulatory networks. PMID:22796662

Androgen Receptor Gene Polymorphisms and Alterations in Prostate Cancer: Of Humanized Mice and Men

PubMed Central

Robins, Diane M.

2011-01-01

Germline polymorphisms and somatic mutations of the androgen receptor (AR) have been intensely investigated in prostate cancer but even with genomic approaches their impact remains controversial. To assess the functional significance of AR genetic variation, we converted the mouse gene to the human sequence by germline recombination and engineered alleles to query the role of a polymorphic glutamine (Q) tract implicated in cancer risk. In a prostate cancer model, AR Q tract length influences progression and castration response. Mutation profiling in mice provides direct evidence that somatic AR variants are selected by therapy, a finding validated in human metastases from distinct treatment groups. Mutant ARs exploit multiple mechanisms to resist hormone ablation, including alterations in ligand specificity, target gene selectivity, chaperone interaction and nuclear localization. Regardless of their frequency, these variants permute normal function to reveal novel means to target wild type AR and its key interacting partners. PMID:21689727

iCOSSY: An Online Tool for Context-Specific Subnetwork Discovery from Gene Expression Data

PubMed Central

Saha, Ashis; Jeon, Minji; Tan, Aik Choon; Kang, Jaewoo

2015-01-01

Pathway analyses help reveal underlying molecular mechanisms of complex biological phenotypes. Biologists tend to perform multiple pathway analyses on the same dataset, as there is no single answer. It is often inefficient for them to implement and/or install all the algorithms by themselves. Online tools can help the community in this regard. Here we present an online gene expression analytical tool called iCOSSY which implements a novel pathway-based COntext-specific Subnetwork discoverY (COSSY) algorithm. iCOSSY also includes a few modifications of COSSY to increase its reliability and interpretability. Users can upload their gene expression datasets, and discover important subnetworks of closely interacting molecules to differentiate between two phenotypes (context). They can also interactively visualize the resulting subnetworks. iCOSSY is a web server that finds subnetworks that are differentially expressed in two phenotypes. Users can visualize the subnetworks to understand the biology of the difference. PMID:26147457

Nuclear envelope and genome interactions in cell fate

PubMed Central

Talamas, Jessica A.; Capelson, Maya

2015-01-01

The eukaryotic cell nucleus houses an organism’s genome and is the location within the cell where all signaling induced and development-driven gene expression programs are ultimately specified. The genome is enclosed and separated from the cytoplasm by the nuclear envelope (NE), a double-lipid membrane bilayer, which contains a large variety of trans-membrane and associated protein complexes. In recent years, research regarding multiple aspects of the cell nucleus points to a highly dynamic and coordinated concert of efforts between chromatin and the NE in regulation of gene expression. Details of how this concert is orchestrated and how it directs cell differentiation and disease are coming to light at a rapid pace. Here we review existing and emerging concepts of how interactions between the genome and the NE may contribute to tissue specific gene expression programs to determine cell fate. PMID:25852741

RNA-Seq Meta-analysis identifies genes in skeletal muscle associated with gain and intake across a multi-season study of crossbred beef steers.

PubMed

Keel, Brittney N; Zarek, Christina M; Keele, John W; Kuehn, Larry A; Snelling, Warren M; Oliver, William T; Freetly, Harvey C; Lindholm-Perry, Amanda K

2018-06-04

Feed intake and body weight gain are economically important inputs and outputs of beef production systems. The purpose of this study was to discover differentially expressed genes that will be robust for feed intake and gain across a large segment of the cattle industry. Transcriptomic studies often suffer from issues with reproducibility and cross-validation. One way to improve reproducibility is by integrating multiple datasets via meta-analysis. RNA sequencing (RNA-Seq) was performed on longissimus dorsi muscle from 80 steers (5 cohorts, each with 16 animals) selected from the outside fringe of a bivariate gain and feed intake distribution to understand the genes and pathways involved in feed efficiency. In each cohort, 16 steers were selected from one of four gain and feed intake phenotypes (n = 4 per phenotype) in a 2 × 2 factorial arrangement with gain and feed intake as main effect variables. Each cohort was analyzed as a single experiment using a generalized linear model and results from the 5 cohort analyses were combined in a meta-analysis to identify differentially expressed genes (DEG) across the cohorts. A total of 51 genes were differentially expressed for the main effect of gain, 109 genes for the intake main effect, and 11 genes for the gain x intake interaction (P corrected  < 0.05). A jackknife sensitivity analysis showed that, in general, the meta-analysis produced robust DEGs for the two main effects and their interaction. Pathways identified from over-represented genes included mitochondrial energy production and oxidative stress pathways for the main effect of gain due to DEG including GPD1, NDUFA6, UQCRQ, ACTC1, and MGST3. For intake, metabolic pathways including amino acid biosynthesis and degradation were identified, and for the interaction analysis the pathways identified included GADD45, pyridoxal 5'phosphate salvage, and caveolar mediated endocytosis signaling. Variation among DEG identified by cohort suggests that environment and breed may play large roles in the expression of genes associated with feed efficiency in the muscle of beef cattle. Meta-analyses of transcriptome data from groups of animals over multiple cohorts may be necessary to elucidate the genetics contributing these types of biological phenotypes.

Transcriptome analysis of Pinus monticola primary needles by RNA-seq provides novel insight into host resistance to Cronartium ribicola

PubMed Central

2013-01-01

Background Five-needle pines are important forest species that have been devastated by white pine blister rust (WPBR, caused by Cronartium ribicola) across North America. Currently little transcriptomic and genomic data are available to understand molecular interactions in the WPBR pathosystem. Results We report here RNA-seq analysis results using Illumina deep sequencing of primary needles of western white pine (Pinus monticola) infected with WPBR. De novo gene assembly was used to generate the first P. monticola consensus transcriptome, which contained 39,439 unique transcripts with an average length of 1,303 bp and a total length of 51.4 Mb. About 23,000 P. monticola unigenes produced orthologous hits in the Pinus gene index (PGI) database (BLASTn with E values < e-100) and 6,300 genes were expressed actively (at RPKM ≥ 10) in the healthy tissues. Comparison of transcriptomes from WPBR-susceptible and -resistant genotypes revealed a total of 979 differentially expressed genes (DEGs) with a significant fold change > 1.5 during P. monticola- C. ribicola interactions. Three hundred and ten DEGs were regulated similarly in both susceptible and resistant seedlings and 275 DEGs showed regulatory differences between susceptible and resistant seedlings post infection by C. ribicola. The DEGs up-regulated in resistant seedlings included a set of putative signal receptor genes encoding disease resistance protein homologs, calcineurin B-like (CBL)-interacting protein kinases (CIPK), F-box family proteins (FBP), and abscisic acid (ABA) receptor; transcriptional factor (TF) genes of multiple families; genes homologous to apoptosis-inducing factor (AIF), flowering locus T-like protein (FT), and subtilisin-like protease. DEGs up-regulated in resistant seedlings also included a wide diversity of down-stream genes (encoding enzymes involved in different metabolic pathways, pathogenesis-related -PR proteins of multiple families, and anti-microbial proteins). A large proportion of the down-regulated DEGs were related to photosystems, the metabolic pathways of carbon fixation and flavonoid biosynthesis. Conclusions The novel P. monticola transcriptome data provide a basis for future studies of genetic resistance in a non-model, coniferous species. Our global gene expression profiling presents a comprehensive view of transcriptomic regulation in the WPBR pathosystem and yields novel insights on molecular and biochemical mechanisms of disease resistance in conifers. PMID:24341615

Pharmacogenomic Approaches for Automated Medication Risk Assessment in People with Polypharmacy

PubMed Central

Liu, Jiazhen; Friedman, Carol; Finkelstein, Joseph

2018-01-01

Abstract Medication regimen may be optimized based on individual drug efficacy identified by pharmacogenomic testing. However, majority of current pharmacogenomic decision support tools provide assessment only of single drug-gene interactions without taking into account complex drug-drug and drug-drug-gene interactions which are prevalent in people with polypharmacy and can result in adverse drug events or insufficient drug efficacy. The main objective of this project was to develop comprehensive pharmacogenomic decision support for medication risk assessment in people with polypharmacy that simultaneously accounts for multiple drug and gene effects. To achieve this goal, the project addressed two aims: (1) development of comprehensive knowledge repository of actionable pharmacogenes; (2) introduction of scoring approaches reflecting potential adverse effect risk levels of complex medication regimens accounting for pharmacogenomic polymorphisms and multiple drug metabolizing pathways. After pharmacogenomic knowledge repository was introduced, a scoring algorithm has been built and pilot-tested using a limited data set. The resulting total risk score for frequently hospitalized older adults with polypharmacy (72.04±17.84) was statistically significantly different (p<0.05) from the total risk score for older adults with polypharmacy with low hospitalization rate (8.98±2.37). An initial prototype assessment demonstrated feasibility of our approach and identified steps for improving risk scoring algorithms.

Trainable Gene Regulation Networks with Applications to Drosophila Pattern Formation

NASA Technical Reports Server (NTRS)

Mjolsness, Eric

2000-01-01

This chapter will very briefly introduce and review some computational experiments in using trainable gene regulation network models to simulate and understand selected episodes in the development of the fruit fly, Drosophila melanogaster. For details the reader is referred to the papers introduced below. It will then introduce a new gene regulation network model which can describe promoter-level substructure in gene regulation. As described in chapter 2, gene regulation may be thought of as a combination of cis-acting regulation by the extended promoter of a gene (including all regulatory sequences) by way of the transcription complex, and of trans-acting regulation by the transcription factor products of other genes. If we simplify the cis-action by using a phenomenological model which can be tuned to data, such as a unit or other small portion of an artificial neural network, then the full transacting interaction between multiple genes during development can be modelled as a larger network which can again be tuned or trained to data. The larger network will in general need to have recurrent (feedback) connections since at least some real gene regulation networks do. This is the basic modeling approach taken, which describes how a set of recurrent neural networks can be used as a modeling language for multiple developmental processes including gene regulation within a single cell, cell-cell communication, and cell division. Such network models have been called "gene circuits", "gene regulation networks", or "genetic regulatory networks", sometimes without distinguishing the models from the actual modeled systems.

Detecting gene subnetworks under selection in biological pathways.

PubMed

Gouy, Alexandre; Daub, Joséphine T; Excoffier, Laurent

2017-09-19

Advances in high throughput sequencing technologies have created a gap between data production and functional data analysis. Indeed, phenotypes result from interactions between numerous genes, but traditional methods treat loci independently, missing important knowledge brought by network-level emerging properties. Therefore, detecting selection acting on multiple genes affecting the evolution of complex traits remains challenging. In this context, gene network analysis provides a powerful framework to study the evolution of adaptive traits and facilitates the interpretation of genome-wide data. We developed a method to analyse gene networks that is suitable to evidence polygenic selection. The general idea is to search biological pathways for subnetworks of genes that directly interact with each other and that present unusual evolutionary features. Subnetwork search is a typical combinatorial optimization problem that we solve using a simulated annealing approach. We have applied our methodology to find signals of adaptation to high-altitude in human populations. We show that this adaptation has a clear polygenic basis and is influenced by many genetic components. Our approach, implemented in the R package signet, improves on gene-level classical tests for selection by identifying both new candidate genes and new biological processes involved in adaptation to altitude. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Genetic Variants in the Bone Morphogenic Protein Gene Family Modify the Association between Residential Exposure to Traffic and Peripheral Arterial Disease

PubMed Central

Ward-Caviness, Cavin K.; Neas, Lucas M.; Blach, Colette; Haynes, Carol S.; LaRocque-Abramson, Karen; Grass, Elizabeth; Dowdy, Elaine; Devlin, Robert B.; Diaz-Sanchez, David; Cascio, Wayne E.; Lynn Miranda, Marie; Gregory, Simon G.; Shah, Svati H.; Kraus, William E.; Hauser, Elizabeth R.

2016-01-01

There is a growing literature indicating that genetic variants modify many of the associations between environmental exposures and clinical outcomes, potentially by increasing susceptibility to these exposures. However, genome-scale investigations of these interactions have been rarely performed particularly in the case of air pollution exposures. We performed race-stratified genome-wide gene-environment interaction association studies on European-American (EA, N = 1623) and African-American (AA, N = 554) cohorts to investigate the joint influence of common single nucleotide polymorphisms (SNPs) and residential exposure to traffic (“traffic exposure”)—a recognized vascular disease risk factor—on peripheral arterial disease (PAD). Traffic exposure was estimated via the distance from the primary residence to the nearest major roadway, defined as the nearest limited access highways or major arterial. The rs755249-traffic exposure interaction was associated with PAD at a genome-wide significant level (P = 2.29x10-8) in European-Americans. Rs755249 is located in the 3’ untranslated region of BMP8A, a member of the bone morphogenic protein (BMP) gene family. Further investigation revealed several variants in BMP genes associated with PAD via an interaction with traffic exposure in both the EA and AA cohorts; this included interactions with non-synonymous variants in BMP2, which is regulated by air pollution exposure. The BMP family of genes is linked to vascular growth and calcification and is a novel gene family for the study of PAD pathophysiology. Further investigation of BMP8A using the Genotype Tissue Expression Database revealed multiple variants with nominally significant (P < 0.05) interaction P-values in our EA cohort were significant BMP8A eQTLs in tissue types highlight relevant for PAD such as rs755249 (tibial nerve, eQTL P = 3.6x10-6) and rs1180341 (tibial artery, eQTL P = 5.3x10-6). Together these results reveal a novel gene, and possibly gene family, associated with PAD via an interaction with traffic air pollution exposure. These results also highlight the potential for interactions studies, particularly at the genome scale, to reveal novel biology linking environmental exposures to clinical outcomes. PMID:27082954

Toxoplasmosis and Polygenic Disease Susceptibility Genes: Extensive Toxoplasma gondii Host/Pathogen Interactome Enrichment in Nine Psychiatric or Neurological Disorders.

PubMed

Carter, C J

2013-01-01

Toxoplasma gondii is not only implicated in schizophrenia and related disorders, but also in Alzheimer's or Parkinson's disease, cancer, cardiac myopathies, and autoimmune disorders. During its life cycle, the pathogen interacts with ~3000 host genes or proteins. Susceptibility genes for multiple sclerosis, Alzheimer's disease, schizophrenia, bipolar disorder, depression, childhood obesity, Parkinson's disease, attention deficit hyperactivity disorder (P  from  8.01E - 05  (ADHD)  to  1.22E - 71) (multiple sclerosis), and autism (P = 0.013), but not anorexia or chronic fatigue are highly enriched in the human arm of this interactome and 18 (ADHD) to 33% (MS) of the susceptibility genes relate to it. The signalling pathways involved in the susceptibility gene/interactome overlaps are relatively specific and relevant to each disease suggesting a means whereby susceptibility genes could orient the attentions of a single pathogen towards disruption of the specific pathways that together contribute (positively or negatively) to the endophenotypes of different diseases. Conditional protein knockdown, orchestrated by T. gondii proteins or antibodies binding to those of the host (pathogen derived autoimmunity) and metabolite exchange, may contribute to this disruption. Susceptibility genes may thus be related to the causes and influencers of disease, rather than (and as well as) to the disease itself.

Gene-by-environment effect of house dust mite on purinergic receptor P2Y12 (P2RY12) and lung function in children with asthma.

PubMed

Bunyavanich, S; Boyce, J A; Raby, B A; Weiss, S T

2012-02-01

Distinct receptors likely exist for leukotriene (LT)E(4), a potent mediator of airway inflammation. Purinergic receptor P2Y12 is needed for LTE(4)-induced airways inflammation, and P2Y12 antagonism attenuates house dust mite-induced pulmonary eosinophilia in mice. Although experimental data support a role for P2Y12 in airway inflammation, its role in human asthma has never been studied. To test for association between variants in the P2Y12 gene (P2RY12) and lung function in human subjects with asthma, and to examine for gene-by-environment interaction with house dust mite exposure. Nineteen single nucleotide polymorphisms (SNPs) in P2RY12 were genotyped in 422 children with asthma and their parents (n = 1266). Using family based methods, we tested for associations between these SNPs and five lung function measures. We performed haplotype association analyses and tested for gene-by-environment interactions using house dust mite exposure. We used the false discovery rate to account for multiple comparisons. Five SNPs in P2RY12 were associated with multiple lung function measures (P-values 0.006–0.025). Haplotypes in P2RY12 were also associated with lung function (P-values 0.0055–0.046). House dust mite exposure modulated associations between P2RY12 and lung function, with minor allele homozygotes exposed to house dust mite demonstrating worse lung function than those unexposed (significant interaction P-values 0.0028–0.040). The P2RY12 variants were associated with lung function in a large family-based asthma cohort. House dust mite exposure caused significant gene-by-environment effects. Our findings add the first human evidence to experimental data supporting a role for P2Y12 in lung function. P2Y12 could represent a novel target for asthma treatment.

Identifying Drug-Target Interactions with Decision Templates.

PubMed

Yan, Xiao-Ying; Zhang, Shao-Wu

2018-01-01

During the development process of new drugs, identification of the drug-target interactions wins primary concerns. However, the chemical or biological experiments bear the limitation in coverage as well as the huge cost of both time and money. Based on drug similarity and target similarity, chemogenomic methods can be able to predict potential drug-target interactions (DTIs) on a large scale and have no luxurious need about target structures or ligand entries. In order to reflect the cases that the drugs having variant structures interact with common targets and the targets having dissimilar sequences interact with same drugs. In addition, though several other similarity metrics have been developed to predict DTIs, the combination of multiple similarity metrics (especially heterogeneous similarities) is too naïve to sufficiently explore the multiple similarities. In this paper, based on Gene Ontology and pathway annotation, we introduce two novel target similarity metrics to address above issues. More importantly, we propose a more effective strategy via decision template to integrate multiple classifiers designed with multiple similarity metrics. In the scenarios that predict existing targets for new drugs and predict approved drugs for new protein targets, the results on the DTI benchmark datasets show that our target similarity metrics are able to enhance the predictive accuracies in two scenarios. And the elaborate fusion strategy of multiple classifiers has better predictive power than the naïve combination of multiple similarity metrics. Compared with other two state-of-the-art approaches on the four popular benchmark datasets of binary drug-target interactions, our method achieves the best results in terms of AUC and AUPR for predicting available targets for new drugs (S2), and predicting approved drugs for new protein targets (S3).These results demonstrate that our method can effectively predict the drug-target interactions. The software package can freely available at https://github.com/NwpuSY/DT_all.git for academic users. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Detection of epistatic effects with logic regression and a classical linear regression model.

PubMed

Malina, Magdalena; Ickstadt, Katja; Schwender, Holger; Posch, Martin; Bogdan, Małgorzata

2014-02-01

To locate multiple interacting quantitative trait loci (QTL) influencing a trait of interest within experimental populations, usually methods as the Cockerham's model are applied. Within this framework, interactions are understood as the part of the joined effect of several genes which cannot be explained as the sum of their additive effects. However, if a change in the phenotype (as disease) is caused by Boolean combinations of genotypes of several QTLs, this Cockerham's approach is often not capable to identify them properly. To detect such interactions more efficiently, we propose a logic regression framework. Even though with the logic regression approach a larger number of models has to be considered (requiring more stringent multiple testing correction) the efficient representation of higher order logic interactions in logic regression models leads to a significant increase of power to detect such interactions as compared to a Cockerham's approach. The increase in power is demonstrated analytically for a simple two-way interaction model and illustrated in more complex settings with simulation study and real data analysis.

Heart morphogenesis gene regulatory networks revealed by temporal expression analysis.

PubMed

Hill, Jonathon T; Demarest, Bradley; Gorsi, Bushra; Smith, Megan; Yost, H Joseph

2017-10-01

During embryogenesis the heart forms as a linear tube that then undergoes multiple simultaneous morphogenetic events to obtain its mature shape. To understand the gene regulatory networks (GRNs) driving this phase of heart development, during which many congenital heart disease malformations likely arise, we conducted an RNA-seq timecourse in zebrafish from 30 hpf to 72 hpf and identified 5861 genes with altered expression. We clustered the genes by temporal expression pattern, identified transcription factor binding motifs enriched in each cluster, and generated a model GRN for the major gene batteries in heart morphogenesis. This approach predicted hundreds of regulatory interactions and found batteries enriched in specific cell and tissue types, indicating that the approach can be used to narrow the search for novel genetic markers and regulatory interactions. Subsequent analyses confirmed the GRN using two mutants, Tbx5 and nkx2-5 , and identified sets of duplicated zebrafish genes that do not show temporal subfunctionalization. This dataset provides an essential resource for future studies on the genetic/epigenetic pathways implicated in congenital heart defects and the mechanisms of cardiac transcriptional regulation. © 2017. Published by The Company of Biologists Ltd.

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

PubMed Central

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

2013-01-01

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

Generation of HIV-1 based bi-cistronic lentiviral vectors for stable gene expression and live cell imaging.

PubMed

Sehgal, Lalit; Budnar, Srikanth; Bhatt, Khyati; Sansare, Sneha; Mukhopadhaya, Amitabha; Kalraiya, Rajiv D; Dalal, Sorab N

2012-10-01

The study of protein-protein interactions, protein localization, protein organization into higher order structures and organelle dynamics in live cells, has greatly enhanced the understanding of various cellular processes. Live cell imaging experiments employ plasmid or viral vectors to express the protein/proteins of interest fused to a fluorescent protein. Unlike plasmid vectors, lentiviral vectors can be introduced into both dividing and non dividing cells, can be pseudotyped to infect a broad or narrow range of cells, and can be used to generate transgenic animals. However, the currently available lentiviral vectors are limited by the choice of fluorescent protein tag, choice of restriction enzyme sites in the Multiple Cloning Sites (MCS) and promoter choice for gene expression. In this report, HIV-1 based bi-cistronic lentiviral vectors have been generated that drive the expression of multiple fluorescent tags (EGFP, mCherry, ECFP, EYFP and dsRed), using two different promoters. The presence of a unique MCS with multiple restriction sites allows the generation of fusion proteins with the fluorescent tag of choice, allowing analysis of multiple fusion proteins in live cell imaging experiments. These novel lentiviral vectors are improved delivery vehicles for gene transfer applications and are important tools for live cell imaging in vivo.

SOX9 regulates multiple genes in chondrocytes, including genes encoding ECM proteins, ECM modification enzymes, receptors, and transporters.

PubMed

Oh, Chun-do; Lu, Yue; Liang, Shoudan; Mori-Akiyama, Yuko; Chen, Di; de Crombrugghe, Benoit; Yasuda, Hideyo

2014-01-01

The transcription factor SOX9 plays an essential role in determining the fate of several cell types and is a master factor in regulation of chondrocyte development. Our aim was to determine which genes in the genome of chondrocytes are either directly or indirectly controlled by SOX9. We used RNA-Seq to identify genes whose expression levels were affected by SOX9 and used SOX9 ChIP-Seq to identify those genes that harbor SOX9-interaction sites. For RNA-Seq, the RNA expression profile of primary Sox9flox/flox mouse chondrocytes infected with Ad-CMV-Cre was compared with that of the same cells infected with a control adenovirus. Analysis of RNA-Seq data indicated that, when the levels of Sox9 mRNA were decreased more than 8-fold by infection with Ad-CMV-Cre, 196 genes showed a decrease in expression of at least 4-fold. These included many cartilage extracellular matrix (ECM) genes and a number of genes for ECM modification enzymes (transferases), membrane receptors, transporters, and others. In ChIP-Seq, 75% of the SOX9-interaction sites had a canonical inverted repeat motif within 100 bp of the top of the peak. SOX9-interaction sites were found in 55% of the genes whose expression was decreased more than 8-fold in SOX9-depleted cells and in somewhat fewer of the genes whose expression was reduced more than 4-fold, suggesting that these are direct targets of SOX9. The combination of RNA-Seq and ChIP-Seq has provided a fuller understanding of the SOX9-controlled genetic program of chondrocytes.

A Grammatical Approach to RNA-RNA Interaction Prediction

NASA Astrophysics Data System (ADS)

Kato, Yuki; Akutsu, Tatsuya; Seki, Hiroyuki

2007-11-01

Much attention has been paid to two interacting RNA molecules involved in post-transcriptional control of gene expression. Although there have been a few studies on RNA-RNA interaction prediction based on dynamic programming algorithm, no grammar-based approach has been proposed. The purpose of this paper is to provide a new modeling for RNA-RNA interaction based on multiple context-free grammar (MCFG). We present a polynomial time parsing algorithm for finding the most likely derivation tree for the stochastic version of MCFG, which is applicable to RNA joint secondary structure prediction including kissing hairpin loops. Also, elementary tests on RNA-RNA interaction prediction have shown that the proposed method is comparable to Alkan et al.'s method.

Recent molecular genetic studies and methodological issues in suicide research.

PubMed

Tsai, Shih-Jen; Hong, Chen-Jee; Liou, Ying-Jay

2011-06-01

Suicide behavior (SB) spans a spectrum ranging from suicidal ideation to suicide attempts and completed suicide. Strong evidence suggests a genetic susceptibility to SB, including familial heritability and common occurrence in twins. This review addresses recent molecular genetic studies in SB that include case-control association, genome gene-expression microarray, and genome-wide association (GWA). This work also reviews epigenetics in SB and pharmacogenetic studies of antidepressant-induced suicide. SB fulfills criteria for a complex genetic phenotype in which environmental factors interact with multiple genes to influence susceptibility. So far, case-control association approaches are still the mainstream in SB genetic studies, although whole genome gene-expression microarray and GWA studies have begun to emerge in recent years. Genetic association studies have suggested several genes (e.g., serotonin transporter, tryptophan hydroxylase 2, and brain-derived neurotrophic factor) related to SB, but not all reports support these findings. The case-control approach while useful is limited by present knowledge of disease pathophysiology. Genome-wide studies of gene expression and genetic variation are not constrained by our limited knowledge. However, the explanatory power and path to clinical translation of risk estimates for common variants reported in genome-wide association studies remain unclear because of the presence of rare and structural genetic variation. As whole genome sequencing becomes increasingly widespread, available genomic information will no longer be the limiting factor in applying genetics to clinical medicine. These approaches provide exciting new avenues to identify new candidate genes for SB genetic studies. The other limitation of genetic association is the lack of a consistent definition of the SB phenotype among studies, an inconsistency that hampers the comparability of the studies and data pooling. In summary, SB involves multiple genes interacting with non-genetic factors. A better understanding of the SB genes by combining whole genome approaches with case-control association studies, may potentially lead to developing effective screening, prevention, and management of SB. Copyright © 2010 Elsevier Inc. All rights reserved.

Effects of enamel matrix genes on dental caries are moderated by fluoride exposures

PubMed Central

Shaffer, John R.; Carlson, Jenna C.; Stanley, Brooklyn O. C.; Feingold, Eleanor; Cooper, Margaret; Vanyukov, Michael M.; Maher, Brion S.; Slayton, Rebecca L.; Willing, Marcia C.; Reis, Steven E.; McNeil, Daniel W.; Crout, Richard J.; Weyant, Robert J.; Levy, Steven M.; Vieira, Alexandre R.; Marazita, Mary L.

2014-01-01

Dental caries (tooth decay) is the most common chronic disease, worldwide, affecting most children and adults. Though dental caries is highly heritable, few caries-related genes have been discovered. We investigated whether 18 genetic variants in the group of nonamelogenin enamel matrix genes (AMBN, ENAM, TUFT1, and TFIP11) were associated with dental caries experience in 13 age- and race-stratified samples from six parent studies (N=3,600). Linear regression was used to model genetic associations and test gene-byfluoride interaction effects for two sources of fluoride: daily tooth brushing and home water fluoride concentration. Meta-analysis was used to combine results across five child and eight adult samples. We observed the statistically significant association of rs2337359 upstream of TUFT1 with dental caries experience via meta-analysis across adult samples (p<0.002) and the suggestive association for multiple variants in TFIP11 across child samples (p<0.05). Moreover, we discovered two genetic variants (rs2337359 upstream of TUFT1 and missense rs7439186 in AMBN) involved in gene-by-fluoride interactions. For each interaction, participants with the risk allele/genotype exhibited greater dental caries experience only if they were not exposed to the source of fluoride. Altogether, these results confirm that variation in enamel matrix genes contributes to individual differences in dental caries liability, and demonstrate that the effects of these genes may be moderated by protective fluoride exposures. In short, genes may exert greater influence on dental caries in unprotected environments, or equivalently, the protective effects of fluoride may obviate the effects of genetic risk alleles. PMID:25373699

Identification of additive, dominant, and epistatic variation conferred by key genes in cellulose biosynthesis pathway in Populus tomentosa†

PubMed Central

Du, Qingzhang; Tian, Jiaxing; Yang, Xiaohui; Pan, Wei; Xu, Baohua; Li, Bailian; Ingvarsson, Pär K.; Zhang, Deqiang

2015-01-01

Economically important traits in many species generally show polygenic, quantitative inheritance. The components of genetic variation (additive, dominant and epistatic effects) of these traits conferred by multiple genes in shared biological pathways remain to be defined. Here, we investigated 11 full-length genes in cellulose biosynthesis, on 10 growth and wood-property traits, within a population of 460 unrelated Populus tomentosa individuals, via multi-gene association. To validate positive associations, we conducted single-marker analysis in a linkage population of 1,200 individuals. We identified 118, 121, and 43 associations (P< 0.01) corresponding to additive, dominant, and epistatic effects, respectively, with low to moderate proportions of phenotypic variance (R2). Epistatic interaction models uncovered a combination of three non-synonymous sites from three unique genes, representing a significant epistasis for diameter at breast height and stem volume. Single-marker analysis validated 61 associations (false discovery rate, Q ≤ 0.10), representing 38 SNPs from nine genes, and its average effect (R2 = 3.8%) nearly 2-fold higher than that identified with multi-gene association, suggesting that multi-gene association can capture smaller individual variants. Moreover, a structural gene–gene network based on tissue-specific transcript abundances provides a better understanding of the multi-gene pathway affecting tree growth and lignocellulose biosynthesis. Our study highlights the importance of pathway-based multiple gene associations to uncover the nature of genetic variance for quantitative traits and may drive novel progress in molecular breeding. PMID:25428896

Tissue-Specific Chromatin Modifications at a Multigene Locus Generate Asymmetric Transcriptional Interactions

PubMed Central

Yoo, Eung Jae; Cajiao, Isabela; Kim, Jeong-Seon; Kimura, Atsushi P.; Zhang, Aiwen; Cooke, Nancy E.; Liebhaber, Stephen A.

2006-01-01

Random assortment within mammalian genomes juxtaposes genes with distinct expression profiles. This organization, along with the prevalence of long-range regulatory controls, generates a potential for aberrant transcriptional interactions. The human CD79b/GH locus contains six tightly linked genes with three mutually exclusive tissue specificities and interdigitated control elements. One consequence of this compact organization is that the pituitarycell-specific transcriptional events that activate hGH-N also trigger ectopic activation of CD79b. However, the B-cell-specific events that activate CD79b do not trigger reciprocal activation of hGH-N. Here we utilized DNase I hypersensitive site mapping, chromatin immunoprecipitation, and transgenic models to explore the basis for this asymmetric relationship. The results reveal tissue-specific patterns of chromatin structures and transcriptional controls at the CD79b/GH locus in B cells distinct from those in the pituitary gland and placenta. These three unique transcriptional environments suggest a set of corresponding gene expression pathways and transcriptional interactions that are likely to be found juxtaposed at multiple sites within the eukaryotic genome. PMID:16847312

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

PubMed

Propp, Phaedra; Becker, Allan

2013-12-01

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

Global Profiling of hnRNP A2/B1-RNA Binding on Chromatin Highlights LncRNA Interactions.

PubMed

Nguyen, Eric D; Balas, Maggie M; Griffin, April M; Roberts, Justin T; Johnson, Aaron M

2018-06-23

Long noncoding RNAs (lncRNAs) often carry out their functions through associations with adaptor proteins. We recently identified heterogeneous ribonucleoprotein (hnRNP) A2/B1 as an adaptor of the human HOTAIR lncRNA. hnRNP A2 and B1 are splice isoforms of the same gene. The spliced version of HOTAIR preferentially associates with the B1 isoform, which we hypothesize contributes to RNA-RNA matching between HOTAIR and transcripts of target genes in breast cancer. Here we used enhanced cross-linking immunoprecipitation (eCLIP) to map the direct interactions between A2/B1 and RNA in breast cancer cells. Despite differing by only twelve amino acids, the A2 and B1 splice isoforms associate preferentially with distinct populations of RNA in vivo. Through cellular fractionation experiments we characterize the pattern of RNA association in chromatin, nucleoplasm, and cytoplasm. We find that a majority of interactions occur on chromatin, even those that do not contribute to co-transcriptional splicing. A2/B1 binding site locations on multiple RNAs hint at a contribution to the regulation and function of lncRNAs. Surprisingly, the strongest A2/B1 binding site occurs in a retained intron of HOTAIR, which interrupts an RNA-RNA interaction hotspot. In vitro eCLIP experiments highlight additional exonic B1 binding sites in HOTAIR which also surround the RNA-RNA interaction hotspot. Interestingly, a version of HOTAIR with the intron retained is still capable of making RNA-RNA interactions in vitro through the hotspot region. Our data further characterize the multiple functions of a repurposed splicing factor with isoform-biased interactions, and highlight that the majority of these functions occur on chromatin-associated RNA.

BRD4 assists elongation of both coding and enhancer RNAs guided by histone acetylation

PubMed Central

Kanno, Tomohiko; Kanno, Yuka; LeRoy, Gary; Campos, Eric; Sun, Hong-Wei; Brooks, Stephen R; Vahedi, Golnaz; Heightman, Tom D; Garcia, Benjamin A; Reinberg, Danny; Siebenlist, Ulrich; O’Shea, John J; Ozato, Keiko

2016-01-01

Small-molecule BET inhibitors interfere with the epigenetic interactions between acetylated histones and the bromodomains of the BET family proteins, including BRD4, and they potently inhibit growth of malignant cells by targeting cancer-promoting genes. BRD4 interacts with the pause-release factor P-TEFb, and has been proposed to release Pol II from promoter-proximal pausing. We show that BRD4 occupied widespread genomic regions in mouse cells, and directly stimulated elongation of both protein-coding transcripts and non-coding enhancer RNAs (eRNAs), dependent on the function of bromodomains. BRD4 interacted physically with elongating Pol II complexes, and assisted Pol II progression through hyper-acetylated nucleosomes by interacting with acetylated histones via bromodomains. On active enhancers, the BET inhibitor JQ1 antagonized BRD4-associated eRNA synthesis. Thus, BRD4 is involved in multiple steps of the transcription hierarchy, primarily by assisting transcript elongation both at enhancers and on gene bodies. PMID:25383670

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

PubMed

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

2016-08-01

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

Generation of gene-targeted mice using embryonic stem cells derived from a transgenic mouse model of Alzheimer's disease.

PubMed

Yamamoto, Satoshi; Ooshima, Yuki; Nakata, Mitsugu; Yano, Takashi; Matsuoka, Kunio; Watanabe, Sayuri; Maeda, Ryouta; Takahashi, Hideki; Takeyama, Michiyasu; Matsumoto, Yoshio; Hashimoto, Tadatoshi

2013-06-01

Gene-targeting technology using mouse embryonic stem (ES) cells has become the "gold standard" for analyzing gene functions and producing disease models. Recently, genetically modified mice with multiple mutations have increasingly been produced to study the interaction between proteins and polygenic diseases. However, introduction of an additional mutation into mice already harboring several mutations by conventional natural crossbreeding is an extremely time- and labor-intensive process. Moreover, to do so in mice with a complex genetic background, several years may be required if the genetic background is to be retained. Establishing ES cells from multiple-mutant mice, or disease-model mice with a complex genetic background, would offer a possible solution. Here, we report the establishment and characterization of novel ES cell lines from a mouse model of Alzheimer's disease (3xTg-AD mouse, Oddo et al. in Neuron 39:409-421, 2003) harboring 3 mutated genes (APPswe, TauP301L, and PS1M146V) and a complex genetic background. Thirty blastocysts were cultured and 15 stable ES cell lines (male: 11; female: 4) obtained. By injecting these ES cells into diploid or tetraploid blastocysts, we generated germline-competent chimeras. Subsequently, we confirmed that F1 mice derived from these animals showed similar biochemical and behavioral characteristics to the original 3xTg-AD mice. Furthermore, we introduced a gene-targeting vector into the ES cells and successfully obtained gene-targeted ES cells, which were then used to generate knockout mice for the targeted gene. These results suggest that the present methodology is effective for introducing an additional mutation into mice already harboring multiple mutated genes and/or a complex genetic background.

A flexible ontology for inference of emergent whole cell function from relationships between subcellular processes.

PubMed

Hansen, Jens; Meretzky, David; Woldesenbet, Simeneh; Stolovitzky, Gustavo; Iyengar, Ravi

2017-12-18

Whole cell responses arise from coordinated interactions between diverse human gene products functioning within various pathways underlying sub-cellular processes (SCP). Lower level SCPs interact to form higher level SCPs, often in a context specific manner to give rise to whole cell function. We sought to determine if capturing such relationships enables us to describe the emergence of whole cell functions from interacting SCPs. We developed the Molecular Biology of the Cell Ontology based on standard cell biology and biochemistry textbooks and review articles. Currently, our ontology contains 5,384 genes, 753 SCPs and 19,180 expertly curated gene-SCP associations. Our algorithm to populate the SCPs with genes enables extension of the ontology on demand and the adaption of the ontology to the continuously growing cell biological knowledge. Since whole cell responses most often arise from the coordinated activity of multiple SCPs, we developed a dynamic enrichment algorithm that flexibly predicts SCP-SCP relationships beyond the current taxonomy. This algorithm enables us to identify interactions between SCPs as a basis for higher order function in a context dependent manner, allowing us to provide a detailed description of how SCPs together can give rise to whole cell functions. We conclude that this ontology can, from omics data sets, enable the development of detailed SCP networks for predictive modeling of emergent whole cell functions.

THE PEAKS AND GEOMETRY OF FITNESS LANDSCAPES

PubMed Central

CRONA, KRISTINA; GREENE, DEVIN; BARLOW, MIRIAM

2012-01-01

Fitness landscapes are central in the theory of adaptation. Recent work compares global and local properties of fitness landscapes. It has been shown that multi-peaked fitness landscapes have a local property called reciprocal sign epistasis interactions. The converse is not true. We show that no condition phrased in terms of reciprocal sign epistasis interactions only, implies multiple peaks. We give a sufficient condition for multiple peaks phrased in terms of two-way interactions. This result is surprising since it has been claimed that no sufficient local condition for multiple peaks exist. We show that our result cannot be generalized to sufficient conditions for three or more peaks. Our proof depends on fitness graphs, where nodes represent genotypes and where arrows point toward more fit genotypes. We also use fitness graphs in order to give a new brief proof of the equivalent characterizations of fitness landscapes lacking genetic constraints on accessible mutational trajectories. We compare a recent geometric classification of fitness landscape based on triangulations of polytopes with qualitative aspects of gene interactions. One observation is that fitness graphs provide information not contained in the geometric classification. We argue that a qualitative perspective may help relating theory of fitness landscapes and empirical observations. PMID:23036916

MAOA-uVNTR and Early Physical Discipline Interact to Influence Delinquent Behavior

ERIC Educational Resources Information Center

Edwards, Alexis C.; Dodge, Kenneth A.; Latendresse, Shawn J.; Lansford, Jennifer E.; Bates, John E.; Pettit, Gregory S.; Budde, John P.; Goate, Alison M.; Dick, Danielle M.

2010-01-01

Background: A functional polymorphism in the promoter region of the monoamine oxidizing gene "monoamine oxidase A" ("MAOA") has been associated with behavioral sensitivity to adverse environmental conditions in multiple studies (e.g., Caspi et al. 2002; Kim-Cohen et al., 2006). The present study investigates the effects of…

Saturated fat intake modulates the association between an obesity genetic risk score and body mass index in two U.S. populations

USDA-ARS?s Scientific Manuscript database

Combining multiple genetic variants related to obesity into a genetic risk score (GRS) might improve identification of individuals at risk of developing obesity. Moreover, characterizing gene-diet interactions is a research challenge to establish dietary recommendations to individuals with higher pr...

Selection and Validation of Reference Genes for Accurate RT-qPCR Data Normalization in Coffea spp. under a Climate Changes Context of Interacting Elevated [CO2] and Temperature

PubMed Central

Martins, Madlles Q.; Fortunato, Ana S.; Rodrigues, Weverton P.; Partelli, Fábio L.; Campostrini, Eliemar; Lidon, Fernando C.; DaMatta, Fábio M.; Ramalho, José C.; Ribeiro-Barros, Ana I.

2017-01-01

World coffee production has faced increasing challenges associated with ongoing climatic changes. Several studies, which have been almost exclusively based on temperature increase, have predicted extensive reductions (higher than half by 2,050) of actual coffee cropped areas. However, recent studies showed that elevated [CO2] can strongly mitigate the negative impacts of heat stress at the physiological and biochemical levels in coffee leaves. In addition, it has also been shown that coffee genotypes can successfully cope with temperatures above what has been traditionally accepted. Altogether, this information suggests that the real impact of climate changes on coffee growth and production could be significantly lower than previously estimated. Gene expression studies are an important tool to unravel crop acclimation ability, demanding the use of adequate reference genes. We have examined the transcript stability of 10 candidate reference genes to normalize RT-qPCR expression studies using a set of 24 cDNAs from leaves of three coffee genotypes (CL153, Icatu, and IPR108), grown under 380 or 700 μL CO2 L−1, and submitted to increasing temperatures from 25/20°C (day/night) to 42/34°C. Samples were analyzed according to genotype, [CO2], temperature, multiple stress interaction ([CO2], temperature) and total stress interaction (genotype, [CO2], and temperature). The transcript stability of each gene was assessed through a multiple analytical approach combining the Coeficient of Variation method and three algorithms (geNorm, BestKeeper, NormFinder). The transcript stability varied according to the type of stress for most genes, but the consensus ranking obtained with RefFinder, classified MDH as the gene with the highest mRNA stability to a global use, followed by ACT and S15, whereas α-TUB and CYCL showed the least stable mRNA contents. Using the coffee expression profiles of the gene encoding the large-subunit of ribulose-1,5-bisphosphate carboxylase/oxygenase (RLS), results from the in silico aggregation and experimental validation of the best number of reference genes showed that two reference genes are adequate to normalize RT-qPCR data. Altogether, this work highlights the importance of an adequate selection of reference genes for each single or combined experimental condition and constitutes the basis to accurately study molecular responses of Coffea spp. in a context of climate changes and global warming. PMID:28326094

Selection and Validation of Reference Genes for Accurate RT-qPCR Data Normalization in Coffea spp. under a Climate Changes Context of Interacting Elevated [CO2] and Temperature.

PubMed

Martins, Madlles Q; Fortunato, Ana S; Rodrigues, Weverton P; Partelli, Fábio L; Campostrini, Eliemar; Lidon, Fernando C; DaMatta, Fábio M; Ramalho, José C; Ribeiro-Barros, Ana I

2017-01-01

World coffee production has faced increasing challenges associated with ongoing climatic changes. Several studies, which have been almost exclusively based on temperature increase, have predicted extensive reductions (higher than half by 2,050) of actual coffee cropped areas. However, recent studies showed that elevated [CO 2 ] can strongly mitigate the negative impacts of heat stress at the physiological and biochemical levels in coffee leaves. In addition, it has also been shown that coffee genotypes can successfully cope with temperatures above what has been traditionally accepted. Altogether, this information suggests that the real impact of climate changes on coffee growth and production could be significantly lower than previously estimated. Gene expression studies are an important tool to unravel crop acclimation ability, demanding the use of adequate reference genes. We have examined the transcript stability of 10 candidate reference genes to normalize RT-qPCR expression studies using a set of 24 cDNAs from leaves of three coffee genotypes (CL153, Icatu, and IPR108), grown under 380 or 700 μL CO 2 L -1 , and submitted to increasing temperatures from 25/20°C (day/night) to 42/34°C. Samples were analyzed according to genotype, [CO 2 ], temperature, multiple stress interaction ([CO 2 ], temperature) and total stress interaction (genotype, [CO 2 ], and temperature). The transcript stability of each gene was assessed through a multiple analytical approach combining the Coeficient of Variation method and three algorithms (geNorm, BestKeeper, NormFinder). The transcript stability varied according to the type of stress for most genes, but the consensus ranking obtained with RefFinder, classified MDH as the gene with the highest mRNA stability to a global use, followed by ACT and S15 , whereas α -TUB and CYCL showed the least stable mRNA contents. Using the coffee expression profiles of the gene encoding the large-subunit of ribulose-1,5-bisphosphate carboxylase/oxygenase ( RLS ), results from the in silico aggregation and experimental validation of the best number of reference genes showed that two reference genes are adequate to normalize RT-qPCR data. Altogether, this work highlights the importance of an adequate selection of reference genes for each single or combined experimental condition and constitutes the basis to accurately study molecular responses of Coffea spp. in a context of climate changes and global warming.

PanACEA: a bioinformatics tool for the exploration and visualization of bacterial pan-chromosomes.

PubMed

Clarke, Thomas H; Brinkac, Lauren M; Inman, Jason M; Sutton, Granger; Fouts, Derrick E

2018-06-27

Bacterial pan-genomes, comprised of conserved and variable genes across multiple sequenced bacterial genomes, allow for identification of genomic regions that are phylogenetically discriminating or functionally important. Pan-genomes consist of large amounts of data, which can restrict researchers ability to locate and analyze these regions. Multiple software packages are available to visualize pan-genomes, but currently their ability to address these concerns are limited by using only pre-computed data sets, prioritizing core over variable gene clusters, or by not accounting for pan-chromosome positioning in the viewer. We introduce PanACEA (Pan-genome Atlas with Chromosome Explorer and Analyzer), which utilizes locally-computed interactive web-pages to view ordered pan-genome data. It consists of multi-tiered, hierarchical display pages that extend from pan-chromosomes to both core and variable regions to single genes. Regions and genes are functionally annotated to allow for rapid searching and visual identification of regions of interest with the option that user-supplied genomic phylogenies and metadata can be incorporated. PanACEA's memory and time requirements are within the capacities of standard laptops. The capability of PanACEA as a research tool is demonstrated by highlighting a variable region important in differentiating strains of Enterobacter hormaechei. PanACEA can rapidly translate the results of pan-chromosome programs into an intuitive and interactive visual representation. It will empower researchers to visually explore and identify regions of the pan-chromosome that are most biologically interesting, and to obtain publication quality images of these regions.

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

PubMed Central

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

2011-01-01

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

Novel polymorphism in FADS1 gene and fish consumption on risk of oral cancer: A case-control study in southeast China.

PubMed

Chen, Fa; Lin, Tao; Yan, Lingjun; Liu, Fengqiong; Huang, Jiangfeng; Liu, Fangping; Wu, Junfeng; Qiu, Yu; Lin, Lisong; Cai, Lin; He, Baochang

2017-02-28

The aim of this study was to investigate the independent and combined effects of fatty acid desaturase 1 (FADS1) gene polymorphism and fish consumption on oral cancer. A hospital-based case-control study was performed including 305 oral cancer patients and 579 cancer-free controls. The genotypes were determined by TaqMan genotyping assay. Non-conditional logistic regression model was used to assess the effects of FADS1 rs174549 polymorphism and fish intake. Subjects carrying A allele of rs174549 significantly reduced the risk of oral cancer (AA VS GG, OR: 0.65, 95% CI: 0.42-0.99; AA VS AG+GG, OR: 0.67, 95% CI: 0.46-0.98). Moreover, the statistically significant reverse associations were especially evident in men, smokers, alcohol drinkers and those age ≤ 60 years. Additionally, fish intake ≥7 times/week showed a 73% reduction in risk for oral cancer compared to those who ate fish less than 2 times/week (OR: 0.27, 95% CI: 0.18-0.42). Furthermore, a significant gene-diet multiplicative interaction was observed between FADS1 rs174549 polymorphism and fish intake for oral cancer (P=0.028). This preliminary study suggests that FADS1 rs174549 polymorphism and fish consumption may be protective factors for oral cancer, with a gene-diet multiplicative interaction. Functional studies with larger samples are required to confirm our findings.

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

PubMed

Walker, Jeffrey A

2010-12-01

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

ePlant and the 3D data display initiative: integrative systems biology on the world wide web.

PubMed

Fucile, Geoffrey; Di Biase, David; Nahal, Hardeep; La, Garon; Khodabandeh, Shokoufeh; Chen, Yani; Easley, Kante; Christendat, Dinesh; Kelley, Lawrence; Provart, Nicholas J

2011-01-10

Visualization tools for biological data are often limited in their ability to interactively integrate data at multiple scales. These computational tools are also typically limited by two-dimensional displays and programmatic implementations that require separate configurations for each of the user's computing devices and recompilation for functional expansion. Towards overcoming these limitations we have developed "ePlant" (http://bar.utoronto.ca/eplant) - a suite of open-source world wide web-based tools for the visualization of large-scale data sets from the model organism Arabidopsis thaliana. These tools display data spanning multiple biological scales on interactive three-dimensional models. Currently, ePlant consists of the following modules: a sequence conservation explorer that includes homology relationships and single nucleotide polymorphism data, a protein structure model explorer, a molecular interaction network explorer, a gene product subcellular localization explorer, and a gene expression pattern explorer. The ePlant's protein structure explorer module represents experimentally determined and theoretical structures covering >70% of the Arabidopsis proteome. The ePlant framework is accessed entirely through a web browser, and is therefore platform-independent. It can be applied to any model organism. To facilitate the development of three-dimensional displays of biological data on the world wide web we have established the "3D Data Display Initiative" (http://3ddi.org).

Interaction of Hb Grey Lynn (Vientiane) [α91(FG3)Leu>Phe (α1)] with Hb E [β26(B8) Glu>Lys] and α(+)-thalassemia: Molecular and Hematological Analysis.

PubMed

Singha, Kritsada; Fucharoen, Goonnapa; Fucharoen, Supan

2015-01-01

Hemoglobin (Hb) Grey Lynn is a Hb variant caused by a mutation at codon 91 of α1-globin gene whereas Hb E is a common β-globin chain variant among Southeast Asian population. We report two hitherto undescribed conditions of Hb Grey Lynn found in Thai individuals. The study was done on two unrelated Thai subjects. Hematological parameters were recorded and Hb analysis was carried out using automated Hb analyzers. Mutations were identified by DNA analysis. Hematological features of the patients were compared with those of various forms of Hb Grey Lynn documented previously. Hb and DNA analyses identified a heterozygous Hb Grey Lynn in one patient and a double heterozygous Hb Grey Lynn and Hb E with α(+)-thalassemia in another. Interaction of α(Grey Lynn) with β(E) chains leads to the formation of a new Hb variant, namely the Hb Grey Lynn E (α(GL)2β(E)2), detectable by liquid chromatography (10.3%) but masked by Hb E on capillary electrophoresis. Interaction of these multiple globin gene defects could lead to complex hemoglobinopathies requiring combined analysis with multiple Hb analyzers followed by DNA testing to provide accurate diagnosis of the cases.

Deep conservation of cis-regulatory elements in metazoans

PubMed Central

Maeso, Ignacio; Irimia, Manuel; Tena, Juan J.; Casares, Fernando; Gómez-Skarmeta, José Luis

2013-01-01

Despite the vast morphological variation observed across phyla, animals share multiple basic developmental processes orchestrated by a common ancestral gene toolkit. These genes interact with each other building complex gene regulatory networks (GRNs), which are encoded in the genome by cis-regulatory elements (CREs) that serve as computational units of the network. Although GRN subcircuits involved in ancient developmental processes are expected to be at least partially conserved, identification of CREs that are conserved across phyla has remained elusive. Here, we review recent studies that revealed such deeply conserved CREs do exist, discuss the difficulties associated with their identification and describe new approaches that will facilitate this search. PMID:24218633

Tumor necrosis is an important hallmark of aggressive endometrial cancer and associates with hypoxia, angiogenesis and inflammation responses

PubMed Central

Stefansson, Ingunn M.; Birkeland, Even; Bø, Trond Hellem; Øyan, Anne M.; Trovik, Jone; Kalland, Karl-Henning; Jonassen, Inge; Salvesen, Helga B.; Wik, Elisabeth; Akslen, Lars A.

2015-01-01

Aims Tumor necrosis is associated with aggressive features of endometrial cancer and poor prognosis. Here, we investigated gene expression patterns and potential treatment targets related to presence of tumor necrosis in primary endometrial cancer lesions. Methods and Results By DNA microarray analysis, expression of genes related to tumor necrosis reflected multiple tumor-microenvironment interactions like tissue hypoxia, angiogenesis and inflammation pathways. A tumor necrosis signature of 38 genes and a related patient cluster (Cluster I, 67% of the cases) were associated with features of aggressive tumors such as type II cancers, estrogen receptor negative tumors and vascular invasion. Further, the tumor necrosis signature was increased in tumor cells grown in hypoxic conditions in vitro. Multiple genes with increased expression are known to be activated by HIF1A and NF-kB. Conclusions Our findings indicate that the presence of tumor necrosis within primary tumors is associated with hypoxia, angiogenesis and inflammation responses. HIF1A, NF-kB and PI3K/mTOR might be potential treatment targets in aggressive endometrial cancers with presence of tumor necrosis. PMID:26485755

Tumor necrosis is an important hallmark of aggressive endometrial cancer and associates with hypoxia, angiogenesis and inflammation responses.

PubMed

Bredholt, Geir; Mannelqvist, Monica; Stefansson, Ingunn M; Birkeland, Even; Bø, Trond Hellem; Øyan, Anne M; Trovik, Jone; Kalland, Karl-Henning; Jonassen, Inge; Salvesen, Helga B; Wik, Elisabeth; Akslen, Lars A

2015-11-24

Tumor necrosis is associated with aggressive features of endometrial cancer and poor prognosis. Here, we investigated gene expression patterns and potential treatment targets related to presence of tumor necrosis in primary endometrial cancer lesions. By DNA microarray analysis, expression of genes related to tumor necrosis reflected multiple tumor-microenvironment interactions like tissue hypoxia, angiogenesis and inflammation pathways. A tumor necrosis signature of 38 genes and a related patient cluster (Cluster I, 67% of the cases) were associated with features of aggressive tumors such as type II cancers, estrogen receptor negative tumors and vascular invasion. Further, the tumor necrosis signature was increased in tumor cells grown in hypoxic conditions in vitro. Multiple genes with increased expression are known to be activated by HIF1A and NF-kB. Our findings indicate that the presence of tumor necrosis within primary tumors is associated with hypoxia, angiogenesis and inflammation responses. HIF1A, NF-kB and PI3K/mTOR might be potential treatment targets in aggressive endometrial cancers with presence of tumor necrosis.

Genome-Wide Analysis of Polymorphisms Associated with Cytokine Responses in Smallpox Vaccine Recipients

PubMed Central

Kennedy, Richard B.; Ovsyannikova, Inna G.; Pankratz, V. Shane; Haralambieva, Iana H.; Vierkant, Robert A.; Poland, Gregory A.

2014-01-01

The role that genetics plays in response to infection or disease is becoming increasingly clear as we learn more about immunogenetics and host-pathogen interactions. Here we report a genome-wide analysis of the effects of host genetic variation on cytokine responses to vaccinia virus stimulation in smallpox vaccine recipients. Our data show that vaccinia stimulation of immune individuals results in secretion of inflammatory and Th1 cytokines. We identified multiple SNPs significantly associated with variations in cytokine secretion. These SNPs are found in genes with known immune function, as well as in genes encoding for proteins involved in signal transduction, cytoskeleton, membrane channels and ion transport, as well as others with no previously identified connection to immune responses. The large number of significant SNP associations implies that cytokine secretion in response to vaccinia virus is a complex process controlled by multiple genes and gene families. Follow-up studies to replicate these findings and then pursue mechanistic studies will provide a greater understanding of how genetic variation influences vaccine responses. PMID:22610502

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

PubMed

Kadupitige, Sidath Randeni; Leung, Kin Chun; Sellmeier, Julia; Sivieng, Jane; Catchpoole, Daniel R; Bain, Michael E; Gaëta, Bruno A

2009-12-03

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. 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. 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.

Practical applications of the bioinformatics toolbox for narrowing quantitative trait loci.

PubMed

Burgess-Herbert, Sarah L; Cox, Allison; Tsaih, Shirng-Wern; Paigen, Beverly

2008-12-01

Dissecting the genes involved in complex traits can be confounded by multiple factors, including extensive epistatic interactions among genes, the involvement of epigenetic regulators, and the variable expressivity of traits. Although quantitative trait locus (QTL) analysis has been a powerful tool for localizing the chromosomal regions underlying complex traits, systematically identifying the causal genes remains challenging. Here, through its application to plasma levels of high-density lipoprotein cholesterol (HDL) in mice, we demonstrate a strategy for narrowing QTL that utilizes comparative genomics and bioinformatics techniques. We show how QTL detected in multiple crosses are subjected to both combined cross analysis and haplotype block analysis; how QTL from one species are mapped to the concordant regions in another species; and how genomewide scans associating haplotype groups with their phenotypes can be used to prioritize the narrowed regions. Then we illustrate how these individual methods for narrowing QTL can be systematically integrated for mouse chromosomes 12 and 15, resulting in a significantly reduced number of candidate genes, often from hundreds to <10. Finally, we give an example of how additional bioinformatics resources can be combined with experiments to determine the most likely quantitative trait genes.

Transcription factor MBF-I interacts with metal regulatory elements of higher eucaryotic metallothionein genes.

PubMed Central

Imbert, J; Zafarullah, M; Culotta, V C; Gedamu, L; Hamer, D

1989-01-01

Metallothionein (MT) gene promoters in higher eucaryotes contain multiple metal regulatory elements (MREs) that are responsible for the metal induction of MT gene transcription. We identified and purified to near homogeneity a 74-kilodalton mouse nuclear protein that specifically binds to certain MRE sequences. This protein, MBF-I, was purified employing as an affinity reagent a trout MRE that is shown to be functional in mouse cells but which lacks the G+C-rich and SP1-like sequences found in many mammalian MT gene promoters. Using point-mutated MREs, we showed that there is a strong correlation between DNA binding in vitro and MT gene regulation in vivo, suggesting a direct role of MBF-I in MT gene transcription. We also showed that MBF-I can induce MT gene transcription in vitro in a mouse extract and that this stimulation requires zinc. Images PMID:2586522

Development, Prevention, and Treatment of Alcohol-Induced Organ Injury: The Role of Nutrition

PubMed Central

Barve, Shirish; Chen, Shao-Yu; Kirpich, Irina; Watson, Walter H.; McClain, Craig

2017-01-01

Alcohol and nutrition have the potential to interact at multiple levels. For example, heavy alcohol consumption can interfere with normal nutrition, resulting in overall malnutrition or in deficiencies of important micronutrients, such as zinc, by reducing their absorption or increasing their loss. Interactions between alcohol consumption and nutrition also can affect epigenetic regulation of gene expression by influencing multiple regulatory mechanisms, including methylation and acetylation of histone proteins and DNA. These effects may contribute to alcohol-related organ or tissue injury. The impact of alcohol–nutrition interactions has been assessed for several organs and tissues, including the intestine, where heavy alcohol use can increase intestinal permeability, and the liver, where the degree of malnutrition can be associated with the severity of liver injury and liver disease. Alcohol–nutrition interactions also play a role in alcohol-related lung injury, brain injury, and immune dysfunction. Therefore, treatment involving nutrient supplementation (e.g., with zinc or S-adenosylmethionine) may help prevent or attenuate some types of alcohol-induced organ damage. PMID:28988580

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

PubMed

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.

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

PubMed Central

Kubo, Takahiko; Yoshimura, Atsushi; Kurata, Nori

2016-01-01

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. PMID:27172610

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

PubMed Central

Kitchen, James L.; Allaby, Robin G.

2013-01-01

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

APOE Modulates the Correlation Between Triglycerides, Cholesterol, and CHD Through Pleiotropy, and Gene-by-Gene Interactions

PubMed Central

Maxwell, Taylor J.; Ballantyne, Christie M.; Cheverud, James M.; Guild, Cameron S.; Ndumele, Chiadi E.; Boerwinkle, Eric

2013-01-01

Relationship loci (rQTL) exist when the correlation between multiple traits varies by genotype. rQTL often occur due to gene-by-gene (G × G) or gene-by-environmental interactions, making them a powerful tool for detecting G × G. Here we present an empirical analysis of apolipoprotein E (APOE) with respect to lipid traits and incident CHD leading to the discovery of loci that interact with APOE to affect these traits. We found that the relationship between total cholesterol (TC) and triglycerides (ln TG) varies by APOE isoform genotype in African-American (AA) and European-American (EA) populations. The e2 allele is associated with strong correlation between ln TG and TC while the e4 allele leads to little or no correlation. This led to a priori hypotheses that APOE genotypes affect the relationship of TC and/or ln TG with incident CHD. We found that APOE*TC was significant (P = 0.016) for AA but not EA while APOE*ln TG was significant for EA (P = 0.027) but not AA. In both cases, e2e2 and e2e3 had strong relationships between TC and ln TG with CHD while e2e4 and e4e4 results in little or no relationship between TC and ln TG with CHD. Using ARIC GWAS data, scans for loci that significantly interact with APOE produced four loci for African Americans (one CHD, one TC, and two HDL). These interactions contribute to the rQTL pattern. rQTL are a powerful tool to identify loci that modify the relationship between risk factors and disease and substantially increase statistical power for detecting G × G. PMID:24097412

Effect of occupational exposures on lung cancer susceptibility: a study of gene-environment interaction analysis.

PubMed

Malhotra, Jyoti; Sartori, Samantha; Brennan, Paul; Zaridze, David; Szeszenia-Dabrowska, Neonila; Świątkowska, Beata; Rudnai, Peter; Lissowska, Jolanta; Fabianova, Eleonora; Mates, Dana; Bencko, Vladimir; Gaborieau, Valerie; Stücker, Isabelle; Foretova, Lenka; Janout, Vladimir; Boffetta, Paolo

2015-03-01

Occupational exposures are known risk factors for lung cancer. Role of genetically determined host factors in occupational exposure-related lung cancer is unclear. We used genome-wide association (GWA) data from a case-control study conducted in 6 European countries from 1998 to 2002 to identify gene-occupation interactions and related pathways for lung cancer risk. GWA analysis was performed for each exposure using logistic regression and interaction term for genotypes, and exposure was included in this model. Both SNP-based and gene-based interaction P values were calculated. Pathway analysis was performed using three complementary methods, and analyses were adjusted for multiple comparisons. We analyzed 312,605 SNPs and occupational exposure to 70 agents from 1,802 lung cancer cases and 1,725 cancer-free controls. Mean age of study participants was 60.1 ± 9.1 years and 75% were male. Largest number of significant associations (P ≤ 1 × 10(-5)) at SNP level was demonstrated for nickel, brick dust, concrete dust, and cement dust, and for brick dust and cement dust at the gene-level (P ≤ 1 × 10(-4)). Approximately 14 occupational exposures showed significant gene-occupation interactions with pathways related to response to environmental information processing via signal transduction (P < 0.001 and FDR < 0.05). Other pathways that showed significant enrichment were related to immune processes and xenobiotic metabolism. Our findings suggest that pathways related to signal transduction, immune process, and xenobiotic metabolism may be involved in occupational exposure-related lung carcinogenesis. Our study exemplifies an integrative approach using pathway-based analysis to demonstrate the role of genetic variants in occupational exposure-related lung cancer susceptibility. Cancer Epidemiol Biomarkers Prev; 24(3); 570-9. ©2015 AACR. ©2015 American Association for Cancer Research.

The Proteomic Profile of Deleted in Breast Cancer 1 (DBC1) Interactions Points to a Multifaceted Regulation of Gene Expression*

PubMed Central

Giguère, Sophie S. B.; Guise, Amanda J.; Jean Beltran, Pierre M.; Joshi, Preeti M.; Greco, Todd M.; Quach, Olivia L.; Kong, Jeffery; Cristea, Ileana M.

2016-01-01

Deleted in breast cancer 1 (DBC1) has emerged as an important regulator of multiple cellular processes, ranging from gene expression to cell cycle progression. DBC1 has been linked to tumorigenesis both as an inhibitor of histone deacetylases, HDAC3 and sirtuin 1, and as a transcriptional cofactor for nuclear hormone receptors. However, despite mounting interest in DBC1, relatively little is known about the range of its interacting partners and the scope of its functions. Here, we carried out a functional proteomics-based investigation of DBC1 interactions in two relevant cell types, T cells and kidney cells. Microscopy, molecular biology, biochemistry, and mass spectrometry studies allowed us to assess DBC1 mRNA and protein levels, localization, phosphorylation status, and protein interaction networks. The comparison of DBC1 interactions in these cell types revealed conserved regulatory roles for DBC1 in gene expression, chromatin organization and modification, and cell cycle progression. Interestingly, we observe previously unrecognized DBC1 interactions with proteins encoded by cancer-associated genes. Among these interactions are five components of the SWI/SNF complex, the most frequently mutated chromatin remodeling complex in human cancers. Additionally, we identified a DBC1 interaction with TBL1XR1, a component of the NCoR complex, which we validated by reciprocal isolation. Strikingly, we discovered that DBC1 associates with proteins that regulate the circadian cycle, including DDX5, DHX9, and SFPQ. We validated this interaction by colocalization and reciprocal isolation. Functional assessment of this association demonstrated that DBC1 protein levels are important for regulating CLOCK and BMAL1 protein oscillations in synchronized T cells. Our results suggest that DBC1 is integral to the maintenance of the circadian molecular clock. Furthermore, the identified interactions provide a valuable resource for the exploration of pathways involved in DBC1-associated tumorigenesis. PMID:26657080

Xenobiotic metabolizing gene variants, pesticide use, and risk of prostate cancer

PubMed Central

Koutros, Stella; Andreotti, Gabriella; Berndt, Sonja I.; Barry, Kathryn Hughes; Lubin, Jay H.; Hoppin, Jane A.; Kamel, Freya; Sandler, Dale P.; Burdette, Laurie A.; Yuenger, Jeffrey; Yeager, Meredith; Alavanja, Michael C.R.; Beane Freeman, Laura E.

2011-01-01

Background To explore associations with prostate cancer and farming, it is important to investigate the relationship between pesticide use and single nucleotide polymorphisms (SNPs) in xenobiotic metabolic enzyme (XME) genes. Objectives We evaluated pesticide-SNP interactions between 45 pesticides and 1,913 XME SNPs with respect to prostate cancer among 776 cases and 1,444 controls in the Agricultural Health Study. Methods We used unconditional logistic regression to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Multiplicative SNP-pesticide interactions were calculated using a likelihood ratio test. Results A positive monotonic interaction was observed between petroleum oil/petroleum distillate use and rs1883633 in the oxidative stress gene glutamate-cysteine ligase (GCLC) (p-interaction=1.0×10−4); men carrying at least one variant allele (minor allele) experienced an increased prostate cancer risk (OR=3.7, 95% CI: 1.9–7.3). Among men carrying the variant allele for thioredoxin reductase 2 (TXNRD2) rs4485648, microsomal epoxide hyrdolase 1 (EPHX1) rs17309872, or myeloperoxidase (MPO) rs11079344, increased prostate cancer risk was observed with high compared to no petroleum oil/petroleum distillate (OR=1.9, 95% CI: 1.1–3.2, p-interaction=0.01), (OR=2.1, 95% CI: 1.1–4.0, p-interaction=0.01), or terbufos (OR=3.0, 95% CI: 1.5–6.0 p-interaction=2.0×10−3) use, respectively. No interactions were deemed noteworthy at the false discovery rate = 0.20 level; the number of observed interactions in XMEs was comparable to the number expected by chance alone. Conclusions We observed several pesticide-SNP interactions in oxidative stress and phase I/phase II enzyme genes and risk of prostate cancer. Additional work is needed to explain the joint contribution of genetic variation in XMEs, pesticide use, and prostate cancer risk. PMID:21716162

Developmental Patterning as a Quantitative Trait: Genetic Modulation of the Hoxb6 Mutant Skeletal Phenotype

PubMed Central

Kappen, Claudia

2016-01-01

The process of patterning along the anterior-posterior axis in vertebrates is highly conserved. The function of Hox genes in the axis patterning process is particularly well documented for bone development in the vertebral column and the limbs. We here show that Hoxb6, in skeletal elements at the cervico-thoracic junction, controls multiple independent aspects of skeletal pattern, implicating discrete developmental pathways as substrates for this transcription factor. In addition, we demonstrate that Hoxb6 function is subject to modulation by genetic factors. These results establish Hox-controlled skeletal pattern as a quantitative trait modulated by gene-gene interactions, and provide evidence that distinct modifiers influence the function of conserved developmental genes in fundamental patterning processes. PMID:26800342

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

PubMed Central

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

2011-01-01

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

Studies of genes involved in craniofacial development and tumorigenesis: FGF3 contributes to isolated oral clefts and may interact with PAX9.

PubMed

Küchler, Erika C; Sabóia, Ticiana M; Vieira, Thays C; Lips, Andrea; Tannure, Patricia N; Deeley, Kathleen; Reis, Maria F; Ho, Bao; Rey, Ana C; Costa, Marcelo C; Granjeiro, José M; Vieira, Alexandre R

2014-11-01

Previous studies suggest individuals born with oral clefts and their families have a higher susceptibility for cancer, which raises the hypothesis that these two conditions share common molecular pathways. This study evaluated the association between oral clefts and polymorphisms in genes that play a role in craniofacial and tumor development. Four hundred and ninety-seven subjects born with oral clefts and 823 unaffected subjects were recruited. Twenty-nine markers in 13 genes were genotyped by the Taqman method. Chi-square was used to compare allele and genotype frequencies. Bonferroni correction for multiple testing was used and the established alpha was 0.0003. This study also used logistic regression to test if genetic variants were associated with oral clefts using positive family history of cancer and age as covariates. There was no association between family history of cancer and oral clefts (p = 0.51). None of the 1320 study participants had a diagnosis of cancer at the time of participation in the study. The marker rs4980700 in FGF3 was associated with oral clefts (p = 0.0002). Logistic regression analysis also provided evidence for gene-gene interaction between FGF3 (rs4980700) and PAX9 (rs2073242), increasing the risk for isolated oral clefts (p = 0.0003). FGF3 is associated with oral clefts and may interact with PAX9.

Plant hormones in defense response of Brassica napus to Sclerotinia sclerotiorum - reassessing the role of salicylic acid in the interaction with a necrotroph.

PubMed

Nováková, Miroslava; Sašek, Vladimír; Dobrev, Petre I; Valentová, Olga; Burketová, Lenka

2014-07-01

According to general model, jasmonic acid (JA) and ethylene (ET) signaling pathways are induced in Arabidopsis after an attack of necrotroph, Sclerotinia sclerotiorum (Lib.) de Bary. However, abscisic acid (ABA) and salicylic acid (SA) also seem to play a role. While signaling events in Arabidopsis have been intensively studied recently, information for the natural host Brassica napus is limited. In this study, multiple plant hormone quantification and expression analysis of marker genes of the signaling pathways was used to gain a complete view of the interaction of B. napus with S. sclerotiorum. Strong response of ET biosynthetic gene ACS2 was observed, accompanied by increases of SA and JA levels that correspond to the elevated expression of marker genes PR1 and LOX3. Interestingly, the level of ABA and the expression of its marker gene RD26 were also elevated. Furthermore, induction of the SA-dependent defense decreased disease symptoms. In addition, SA signaling is suggested as a possible target for manipulation by S. sclerotiorum. A gene for putative chorismate mutase SS1G_14320 was identified that is highly expressed during infection but not in vitro. Our results bring the evidence of SA involvement in the interaction of plant with the necrotroph that conflict with the current model. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Constructing an integrated gene similarity network for the identification of disease genes.

PubMed

Tian, Zhen; Guo, Maozu; Wang, Chunyu; Xing, LinLin; Wang, Lei; Zhang, Yin

2017-09-20

Discovering novel genes that are involved human diseases is a challenging task in biomedical research. In recent years, several computational approaches have been proposed to prioritize candidate disease genes. Most of these methods are mainly based on protein-protein interaction (PPI) networks. However, since these PPI networks contain false positives and only cover less half of known human genes, their reliability and coverage are very low. Therefore, it is highly necessary to fuse multiple genomic data to construct a credible gene similarity network and then infer disease genes on the whole genomic scale. We proposed a novel method, named RWRB, to infer causal genes of interested diseases. First, we construct five individual gene (protein) similarity networks based on multiple genomic data of human genes. Then, an integrated gene similarity network (IGSN) is reconstructed based on similarity network fusion (SNF) method. Finally, we employee the random walk with restart algorithm on the phenotype-gene bilayer network, which combines phenotype similarity network, IGSN as well as phenotype-gene association network, to prioritize candidate disease genes. We investigate the effectiveness of RWRB through leave-one-out cross-validation methods in inferring phenotype-gene relationships. Results show that RWRB is more accurate than state-of-the-art methods on most evaluation metrics. Further analysis shows that the success of RWRB is benefited from IGSN which has a wider coverage and higher reliability comparing with current PPI networks. Moreover, we conduct a comprehensive case study for Alzheimer's disease and predict some novel disease genes that supported by literature. RWRB is an effective and reliable algorithm in prioritizing candidate disease genes on the genomic scale. Software and supplementary information are available at http://nclab.hit.edu.cn/~tianzhen/RWRB/ .

Genetic Variation in Selenoprotein Genes, Lifestyle, and Risk of Colon and Rectal Cancer

PubMed Central

Slattery, Martha L.; Lundgreen, Abbie; Welbourn, Bill; Corcoran, Christopher; Wolff, Roger K.

2012-01-01

Background Associations between selenium and cancer have directed attention to role of selenoproteins in the carcinogenic process. Methods We used data from two population-based case-control studies of colon (n = 1555 cases, 1956 controls) and rectal (n = 754 cases, 959 controls) cancer. We evaluated the association between genetic variation in TXNRD1, TXNRD2, TXNRD3, C11orf31 (SelH), SelW, SelN1, SelS, SepX, and SeP15 with colorectal cancer risk. Results After adjustment for multiple comparisons, several associations were observed. Two SNPs in TXNRD3 were associated with rectal cancer (rs11718498 dominant OR 1.42 95% CI 1.16,1.74 pACT 0.0036 and rs9637365 recessive 0.70 95% CI 0.55,0.90 pACT 0.0208). Four SNPs in SepN1 were associated with rectal cancer (rs11247735 recessive OR 1.30 95% CI 1.04,1.63 pACT 0.0410; rs2072749 GGvsAA OR 0.53 95% CI 0.36,0.80 pACT 0.0159; rs4659382 recessive OR 0.58 95% CI 0.39,0.86 pACT 0.0247; rs718391 dominant OR 0.76 95% CI 0.62,0.94 pACT 0.0300). Interaction between these genes and exposures that could influence these genes showed numerous significant associations after adjustment for multiple comparisons. Two SNPs in TXNRD1 and four SNPs in TXNRD2 interacted with aspirin/NSAID to influence colon cancer; one SNP in TXNRD1, two SNPs in TXNRD2, and one SNP in TXNRD3 interacted with aspirin/NSAIDs to influence rectal cancer. Five SNPs in TXNRD2 and one in SelS, SeP15, and SelW1 interacted with estrogen to modify colon cancer risk; one SNP in SelW1 interacted with estrogen to alter rectal cancer risk. Several SNPs in this candidate pathway influenced survival after diagnosis with colon cancer (SeP15 and SepX1 increased HRR) and rectal cancer (SepX1 increased HRR). Conclusions Findings support an association between selenoprotein genes and colon and rectal cancer development and survival after diagnosis. Given the interactions observed, it is likely that the impact of cancer susceptibility from genotype is modified by lifestyle. PMID:22615972

Transcriptional Responses of Candida albicans to Epithelial and Endothelial Cells▿ †

PubMed Central

Park, Hyunsook; Liu, Yaoping; Solis, Norma; Spotkov, Joshua; Hamaker, Jessica; Blankenship, Jill R.; Yeaman, Michael R.; Mitchell, Aaron P.; Liu, Haoping; Filler, Scott G.

2009-01-01

Candida albicans interacts with oral epithelial cells during oropharyngeal candidiasis and with vascular endothelial cells when it disseminates hematogenously. We set out to identify C. albicans genes that govern interactions with these host cells in vitro. The transcriptional response of C. albicans to the FaDu oral epithelial cell line and primary endothelial cells was determined by microarray analysis. Contact with epithelial cells caused a decrease in transcript levels of genes related to protein synthesis and adhesion, whereas contact with endothelial cells did not significantly influence any specific functional category of genes. Many genes whose transcripts were increased in response to either host cell had not been previously characterized. We constructed mutants with homozygous insertions in 22 of these uncharacterized genes to investigate their function during host-pathogen interaction. By this approach, we found that YCK2, VPS51, and UEC1 are required for C. albicans to cause normal damage to epithelial cells and resist antimicrobial peptides. YCK2 is also necessary for maintenance of cell polarity. VPS51 is necessary for normal vacuole formation, resistance to multiple stressors, and induction of maximal endothelial cell damage. UEC1 encodes a unique protein that is required for resistance to cell membrane stress. Therefore, some C. albicans genes whose transcripts are increased upon contact with epithelial or endothelial cells are required for the organism to damage these cells and withstand the stresses that it likely encounters during growth in the oropharynx and bloodstream. PMID:19700637

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

PubMed Central

2012-01-01

Background Cowpea, Vigna unguiculata L. Walp., is one of the most important food and forage legumes in the semi-arid tropics. While most domesticated forms of cowpea are susceptible to the root parasitic weed Striga gesnerioides, several cultivars have been identified that show race-specific resistance. Cowpea cultivar B301 contains the RSG3-301 gene for resistance to S. gesnerioides race SG3, but is susceptible to race SG4z. When challenged by SG3, roots of cultivar B301 develop a strong resistance response characterized by a hypersensitive reaction and cell death at the site of parasite attachment. In contrast, no visible response occurs in B301 roots parasitized by SG4z. Results Gene expression in the roots of the cowpea cultivar B301 during compatible (susceptible) and incompatible (resistant) interactions with S. gesnerioides races SG4z and SG3, respectively, were investigated at the early (6 days post-inoculation (dpi)) and late (13 dpi) stages of the resistance response using a Nimblegen custom design cowpea microarray. A total of 111 genes were differentially expressed in B301 roots at 6 dpi; this number increased to 2102 genes at 13 dpi. At 13 dpi, a total of 1944 genes were differentially expressed during compatible (susceptible) interactions of B301 with SG4z. Genes and pathways involved in signal transduction, programmed cell death and apoptosis, and defense response to biotic and abiotic stress were differentially expressed in the early resistance response; at the later time point, enrichment was primarily for defense-related gene expression, and genes encoding components of lignifications and secondary wall formation. In compatible interactions (B301 – SG4z), multiple defense pathways were repressed, including those involved in lignin biosynthesis and secondary cell wall modifications, while cellular transport processes for nitrogen and sulfur were increased. Conclusion Distinct changes in global gene expression profiles occur in host roots following successful and unsuccessful attempted parasitism by Striga. Induction of specific defense related genes and pathways defines components of a unique resistance mechanism. Some genes and pathways up-regulated in the host resistance response to SG3 are repressed in the susceptible interactions, suggesting that the parasite is targeting specific components of the host’s defense. These results add to our understanding of plant-parasite interactions and the evolution of resistance to parasitic weeds. PMID:22900582

Genome-wide copy number variation study associates metabotropic glutamate receptor gene networks with attention deficit hyperactivity disorder

PubMed Central

Elia, Josephine; Glessner, Joseph T; Wang, Kai; Takahashi, Nagahide; Shtir, Corina J; Hadley, Dexter; Sleiman, Patrick M A; Zhang, Haitao; Kim, Cecilia E; Robison, Reid; Lyon, Gholson J; Flory, James H; Bradfield, Jonathan P; Imielinski, Marcin; Hou, Cuiping; Frackelton, Edward C; Chiavacci, Rosetta M; Sakurai, Takeshi; Rabin, Cara; Middleton, Frank A; Thomas, Kelly A; Garris, Maria; Mentch, Frank; Freitag, Christine M; Steinhausen, Hans-Christoph; Todorov, Alexandre A; Reif, Andreas; Rothenberger, Aribert; Franke, Barbara; Mick, Eric O; Roeyers, Herbert; Buitelaar, Jan; Lesch, Klaus-Peter; Banaschewski, Tobias; Ebstein, Richard P; Mulas, Fernando; Oades, Robert D; Sergeant, Joseph; Sonuga-Barke, Edmund; Renner, Tobias J; Romanos, Marcel; Romanos, Jasmin; Warnke, Andreas; Walitza, Susanne; Meyer, Jobst; Pálmason, Haukur; Seitz, Christiane; Loo, Sandra K; Smalley, Susan L; Biederman, Joseph; Kent, Lindsey; Asherson, Philip; Anney, Richard J L; Gaynor, J William; Shaw, Philip; Devoto, Marcella; White, Peter S; Grant, Struan F A; Buxbaum, Joseph D; Rapoport, Judith L; Williams, Nigel M; Nelson, Stanley F; Faraone, Stephen V; Hakonarson, Hakon

2014-01-01

Attention deficit hyperactivity disorder (ADHD) is a common, heritable neuropsychiatric disorder of unknown etiology. We performed a whole-genome copy number variation (CNV) study on 1,013 cases with ADHD and 4,105 healthy children of European ancestry using 550,000 SNPs. We evaluated statistically significant findings in multiple independent cohorts, with a total of 2,493 cases with ADHD and 9,222 controls of European ancestry, using matched platforms. CNVs affecting metabotropic glutamate receptor genes were enriched across all cohorts (P = 2.1 × 10−9). We saw GRM5 (encoding glutamate receptor, metabotropic 5) deletions in ten cases and one control (P = 1.36 × 10−6). We saw GRM7 deletions in six cases, and we saw GRM8 deletions in eight cases and no controls. GRM1 was duplicated in eight cases. We experimentally validated the observed variants using quantitative RT-PCR. A gene network analysis showed that genes interacting with the genes in the GRM family are enriched for CNVs in ~10% of the cases (P = 4.38 × 10−10) after correction for occurrence in the controls. We identified rare recurrent CNVs affecting glutamatergic neurotransmission genes that were overrepresented in multiple ADHD cohorts. PMID:22138692

Amino acid transporter expansions associated with the evolution of obligate endosymbiosis in sap-feeding insects (Hemiptera: sternorrhyncha).

PubMed

Dahan, Romain A; Duncan, Rebecca P; Wilson, Alex C C; Dávalos, Liliana M

2015-03-25

Mutualistic obligate endosymbioses shape the evolution of endosymbiont genomes, but their impact on host genomes remains unclear. Insects of the sub-order Sternorrhyncha (Hemiptera) depend on bacterial endosymbionts for essential amino acids present at low abundances in their phloem-based diet. This obligate dependency has been proposed to explain why multiple amino acid transporter genes are maintained in the genomes of the insect hosts. We implemented phylogenetic comparative methods to test whether amino acid transporters have proliferated in sternorrhynchan genomes at rates grater than expected by chance. By applying a series of methods to reconcile gene and species trees, inferring the size of gene families in ancestral lineages, and simulating the null process of birth and death in multi-gene families, we uncovered a 10-fold increase in duplication rate in the AAAP family of amino acid transporters within Sternorrhyncha. This gene family expansion was unmatched in other closely related clades lacking endosymbionts that provide essential amino acids. Our findings support the influence of obligate endosymbioses on host genome evolution by both inferring significant expansions of gene families involved in symbiotic interactions, and discovering increases in the rate of duplication associated with multiple emergences of obligate symbiosis in Sternorrhyncha.

Multiple Interactions between Glucose and Brassinosteroid Signal Transduction Pathways in Arabidopsis Are Uncovered by Whole-Genome Transcriptional Profiling1

PubMed Central

2015-01-01

Brassinosteroid (BR) and glucose (Glc) regulate many common responses in plants. Here, we demonstrate that under etiolated growth conditions, extensive interdependence/overlap occurs between BR- and Glc-regulated gene expression as well as physiological responses. Glc could regulate the transcript level of 72% of BR-regulated genes at the whole-genome level, of which 58% of genes were affected synergistically and 42% of genes were regulated antagonistically. Presence of Glc along with BR in medium could affect BR induction/repression of 85% of BR-regulated genes. Glc could also regulate several genes involved in BR metabolism and signaling. Both BR and Glc coregulate a large number of genes involved in abiotic/biotic stress responses and growth and development. Physiologically, Glc and BR interact to regulate hypocotyl elongation growth of etiolated Arabidopsis (Arabidopsis thaliana) seedlings in a dose-dependent manner. Glc may interact with BR via a HEXOKINASE1 (HXK1)-mediated pathway to regulate etiolated hypocotyl elongation. BRASSINOSTEROID INSENSITIVE1 (BRI1) is epistatic to HXK1, as the Glc insensitive2bri1-6 double mutant displayed severe defects in hypocotyl elongation growth similar to its bri1-6 parent. Analysis of Glc and BR sensitivity in mutants defective in auxin response/signaling further suggested that Glc and BR signals may converge at S-phase kinase-associated protein1-Cullin-F-box-TRANSPORT INHIBITOR RESPONSE1/AUXIN-RELATED F-BOX-AUXIN/INDOLE-3-ACETIC ACID-mediated auxin-signaling machinery to regulate etiolated hypocotyl elongation growth in Arabidopsis. PMID:26034265

Genetic polymorphisms in nitric oxide synthase genes modify the relationship between vegetable and fruit intake and risk of non-Hodgkin lymphoma

PubMed Central

Han, Xuesong; Zheng, Tongzhang; Lan, Qing; Zhang, Yaqun; Kilfoy, Briseis A.; Qin, Qin; Rothman, Nathaniel; Zahm, Shelia H.; Holford, Theodore R.; Leaderer, Brian; Zhang, Yawei

2010-01-01

Oxidative damage caused by reactive oxygen species (ROS) and other free radicals is involved in carcinogenesis. It has been suggested that high vegetable and fruit intake may reduce the risk of non-Hodgkin lymphoma (NHL) as vegetables and fruit are rich in antioxidants. The aim of this study is to evaluate the interaction of vegetable and fruit intake with genetic polymorphisms in oxidative stress pathway genes and NHL risk. This hypothesis was investigated in a population-based case-control study of NHL and NHL histological subtype in Connecticut women including 513 histologically confirmed incident cases and 591 randomly selected controls. Gene-vegetable/fruit joint effects were estimated using unconditional logistic regression model. The false discovery rate method was applied to adjust for multiple comparisons. Significant interactions with vegetable and fruit intake were mainly found for genetic polymorphisms on nitric oxide synthase (NOS) genes among those with diffuse large B-cell lymphoma (DLBCL) and Follicular lymphoma (FL). Two single nucleotide polymorphisms (SNPs) in the NOS1 gene were found to significantly modify the association between total vegetable and fruit intake and risk of NHL overall, as well as the risk of follicular lymphoma (FL). When vegetables, bean vegetables, cruciferous vegetables, green leafy vegetables, red vegetables, yellow/orange vegetables, fruit, and citrus fruit were examined separately, strong interaction effects were narrowed to vegetable intake among DLBCL patients. Our results suggest that genetic polymorphisms in oxidative stress pathway genes, especially in the nitric oxide synthase genes, modify the association between vegetable and fruit intake and risk of NHL. PMID:19423521

Transcription co-activator SAYP mediates the action of STAT activator.

PubMed

Panov, Vladislav V; Kuzmina, Julia L; Doronin, Semen A; Kopantseva, Marina R; Nabirochkina, Elena N; Georgieva, Sofia G; Vorobyeva, Nadezhda E; Shidlovskii, Yulii V

2012-03-01

Jak/STAT is an important signaling pathway mediating multiple events in development. We describe participation of metazoan co-activator SAYP/PHF10 in this pathway downstream of STAT. The latter, via its activation domain, interacts with the conserved core of SAYP. STAT is associated with the SAYP-containing co-activator complex BTFly and recruits BTFly onto genes. SAYP is necessary for stimulating STAT-driven transcription of numerous genes. Mutation of SAYP leads to maldevelopments similar to those observed in STAT mutants. Thus, SAYP is a novel co-activator mediating the action of STAT.

Entropy Based Genetic Association Tests and Gene-Gene Interaction Tests

PubMed Central

de Andrade, Mariza; Wang, Xin

2011-01-01

In the past few years, several entropy-based tests have been proposed for testing either single SNP association or gene-gene interaction. These tests are mainly based on Shannon entropy and have higher statistical power when compared to standard χ2 tests. In this paper, we extend some of these tests using a more generalized entropy definition, Rényi entropy, where Shannon entropy is a special case of order 1. The order λ (>0) of Rényi entropy weights the events (genotype/haplotype) according to their probabilities (frequencies). Higher λ places more emphasis on higher probability events while smaller λ (close to 0) tends to assign weights more equally. Thus, by properly choosing the λ, one can potentially increase the power of the tests or the p-value level of significance. We conducted simulation as well as real data analyses to assess the impact of the order λ and the performance of these generalized tests. The results showed that for dominant model the order 2 test was more powerful and for multiplicative model the order 1 or 2 had similar power. The analyses indicate that the choice of λ depends on the underlying genetic model and Shannon entropy is not necessarily the most powerful entropy measure for constructing genetic association or interaction tests. PMID:23089811

Natural allelic variation of the AZI1 gene controls root growth under zinc-limiting condition

PubMed Central

Bouain, Nadia; Saenchai, Chorpet

2018-01-01

Zinc is an essential micronutrient for all living organisms and is involved in a plethora of processes including growth and development, and immunity. However, it is unknown if there is a common genetic and molecular basis underlying multiple facets of zinc function. Here we used natural variation in Arabidopsis thaliana to study the role of zinc in regulating growth. We identify allelic variation of the systemic immunity gene AZI1 as a key for determining root growth responses to low zinc conditions. We further demonstrate that this gene is important for modulating primary root length depending on the zinc and defence status. Finally, we show that the interaction of the immunity signal azelaic acid and zinc level to regulate root growth is conserved in rice. This work demonstrates that there is a common genetic and molecular basis for multiple zinc dependent processes and that nutrient cues can determine the balance of growth and immune responses in plants. PMID:29608565

The 32-Kilodalton Subunit of Replication Protein A Interacts with Menin, the Product of the MEN1 Tumor Suppressor Gene

PubMed Central

Sukhodolets, Karen E.; Hickman, Alison B.; Agarwal, Sunita K.; Sukhodolets, Maxim V.; Obungu, Victor H.; Novotny, Elizabeth A.; Crabtree, Judy S.; Chandrasekharappa, Settara C.; Collins, Francis S.; Spiegel, Allen M.; Burns, A. Lee; Marx, Stephen J.

2003-01-01

Menin is a 70-kDa protein encoded by MEN1, the tumor suppressor gene disrupted in multiple endocrine neoplasia type 1. In a yeast two-hybrid system based on reconstitution of Ras signaling, menin was found to interact with the 32-kDa subunit (RPA2) of replication protein A (RPA), a heterotrimeric protein required for DNA replication, recombination, and repair. The menin-RPA2 interaction was confirmed in a conventional yeast two-hybrid system and by direct interaction between purified proteins. Menin-RPA2 binding was inhibited by a number of menin missense mutations found in individuals with multiple endocrine neoplasia type 1, and the interacting regions were mapped to the N-terminal portion of menin and amino acids 43 to 171 of RPA2. This region of RPA2 contains a weak single-stranded DNA-binding domain, but menin had no detectable effect on RPA-DNA binding in vitro. Menin bound preferentially in vitro to free RPA2 rather than the RPA heterotrimer or a subcomplex consisting of RPA2 bound to the 14-kDa subunit (RPA3). However, the 70-kDa subunit (RPA1) was coprecipitated from HeLa cell extracts along with RPA2 by menin-specific antibodies, suggesting that menin binds to the RPA heterotrimer or a novel RPA1-RPA2-containing complex in vivo. This finding was consistent with the extensive overlap in the nuclear localization patterns of endogenous menin, RPA2, and RPA1 observed by immunofluorescence. PMID:12509449

The "11K" gene family members sf68, sf95 and sf138 modulate transmissibility and insecticidal properties of Spodoptera frugiperda multiple nucleopolyhedrovirus.

PubMed

Beperet, Inés; Simón, Oihane; Williams, Trevor; López-Ferber, Miguel; Caballero, Primitivo

2015-05-01

The "11K" gene family is notable for having homologs in both baculoviruses and entomopoxviruses and is classified as either type 145 or type 150, according to their similarity with the ac145 or ac150 genes of Autographa californica multiple nucleopolyhedrovirus (AcMNPV). One homolog of ac145 (sf138) and two homologs of ac150 (sf68 and sf95) are present in Spodoptera frugiperda multiple nucleopolyhedrovirus (SfMNPV). Recombinant bacmids lacking sf68, sf95 or sf138 (Sf68null, Sf95null and Sf138null, respectively) and the respective repair bacmids were generated from a bacmid comprising the complete virus genome. Occlusion bodies (OBs) of the Sf138null virus were ∼15-fold less orally infective to insects, which was attributed to a 100-fold reduction in ODV infectious titer. Inoculation of insects with Sf138null OBs in mixtures with an optical brightener failed to restore the pathogenicity of Sf138null OBs to that of the parental virus, indicating that the effects of sf138 deletion on OB pathogenicity were unlikely to involve an interaction with the gut peritrophic matrix. In contrast, deletion of sf68 and sf95 resulted in a slower speed-of-kill by 9h, and a concurrent increase in the yield of OBs. Phylogenetic analysis indicated that sf68 and sf95 were not generated after a duplication event of an ancestral gene homologous to the ac150 gene. We conclude that type 145 genes modulate the primary infection process of the virus, whereas type 150 genes appear to have a role in spreading systemic infection within the insect. Copyright © 2015 Elsevier Inc. All rights reserved.

Matrix metalloproteinases and educational attainment in refractive error: evidence of gene-environment interactions in the AREDS study

PubMed Central

Wojciechowski, Robert; Yee, Stephanie S.; Simpson, Claire L.; Bailey-Wilson, Joan E.; Stambolian, Dwight

2012-01-01

Purpose A previous study of Old Order Amish families has shown association of ocular refraction with markers proximal to matrix metalloproteinase (MMP) genes MMP1 and MMP10 and intragenic to MMP2. We conducted a candidate gene replication study of association between refraction and single nucleotide polymorphisms (SNPs) within these genomic regions. Design Candidate gene genetic association study. Participants 2,000 participants drawn from the Age Related Eye Disease Study (AREDS) were chosen for genotyping. After quality control filtering, 1912 individuals were available for analysis. Methods Microarray genotyping was performed using the HumanOmni 2.5 bead array. SNPs originally typed in the previous Amish association study were extracted for analysis. In addition, haplotype tagging SNPs were genotyped using TaqMan assays. Quantitative trait association analyses of mean spherical equivalent refraction (MSE) were performed on 30 markers using linear regression models and an additive genetic risk model, while adjusting for age, sex, education, and population substructure. Post-hoc analyses were performed after stratifying on a dichotomous education variable. Pointwise (P-emp) and multiple-test study-wise (P-multi) significance levels were calculated empirically through permutation. Main outcome measures MSE was used as a quantitative measure of ocular refraction. Results The mean age and ocular refraction were 68 years (SD=4.7) and +0.55 D (SD=2.14), respectively. Pointwise statistical significance was obtained for rs1939008 (P-emp=0.0326). No SNP attained statistical significance after correcting for multiple testing. In stratified analyses, multiple SNPs reached pointwise significance in the lower-education group: 2 of these were statistically significant after multiple testing correction. The two highest-ranking SNPs in Amish families (rs1939008 and rs9928731) showed pointwise P-emp<0.01 in the lower-education stratum of AREDS participants. Conclusions We show suggestive evidence of replication of an association signal for ocular refraction to a marker between MMP1 and MMP10. We also provide evidence of a gene-environment interaction between previously-reported markers and education on refractive error. Variants in MMP1- MMP10 and MMP2 regions appear to affect population variation in ocular refraction in environmental conditions less favorable for myopia development. PMID:23098370

A perspective on interaction effects in genetic association studies

PubMed Central

2016-01-01

ABSTRACT The identification of gene–gene and gene–environment interaction in human traits and diseases is an active area of research that generates high expectation, and most often lead to high disappointment. This is partly explained by a misunderstanding of the inherent characteristics of standard regression‐based interaction analyses. Here, I revisit and untangle major theoretical aspects of interaction tests in the special case of linear regression; in particular, I discuss variables coding scheme, interpretation of effect estimate, statistical power, and estimation of variance explained in regard of various hypothetical interaction patterns. Linking this components it appears first that the simplest biological interaction models—in which the magnitude of a genetic effect depends on a common exposure—are among the most difficult to identify. Second, I highlight the demerit of the current strategy to evaluate the contribution of interaction effects to the variance of quantitative outcomes and argue for the use of new approaches to overcome this issue. Finally, I explore the advantages and limitations of multivariate interaction models, when testing for interaction between multiple SNPs and/or multiple exposures, over univariate approaches. Together, these new insights can be leveraged for future method development and to improve our understanding of the genetic architecture of multifactorial traits. PMID:27390122

Genetics of human neural tube defects

PubMed Central

Greene, Nicholas D.E.; Stanier, Philip; Copp, Andrew J.

2009-01-01

Neural tube defects (NTDs) are common, severe congenital malformations whose causation involves multiple genes and environmental factors. Although more than 200 genes are known to cause NTDs in mice, there has been rather limited progress in delineating the molecular basis underlying most human NTDs. Numerous genetic studies have been carried out to investigate candidate genes in cohorts of patients, with particular reference to those that participate in folate one-carbon metabolism. Although the homocysteine remethylation gene MTHFR has emerged as a risk factor in some human populations, few other consistent findings have resulted from this approach. Similarly, attention focused on the human homologues of mouse NTD genes has contributed only limited positive findings to date, although an emerging association between genes of the non-canonical Wnt (planar cell polarity) pathway and NTDs provides candidates for future studies. Priorities for the next phase of this research include: (i) larger studies that are sufficiently powered to detect significant associations with relatively minor risk factors; (ii) analysis of multiple candidate genes in groups of well-genotyped individuals to detect possible gene–gene interactions; (iii) use of high throughput genomic technology to evaluate the role of copy number variants and to detect ‘private’ and regulatory mutations, neither of which have been studied to date; (iv) detailed analysis of patient samples stratified by phenotype to enable, for example, hypothesis-driven testing of candidates genes in groups of NTDs with specific defects of folate metabolism, or in groups of fetuses with well-defined phenotypes such as craniorachischisis. PMID:19808787

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

PubMed

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.

The Impact of Familial Autism Diagnoses on Autism Symptomatology in Infants and Toddlers

ERIC Educational Resources Information Center

Kozlowski, Alison M.; Matson, Johnny L.; Worley, Julie A.

2012-01-01

Debate regarding the etiology of Autism Spectrum Disorders (ASD) is on the rise with numerous theories being put forth. Currently, the theory with the most empirical support is the interaction of multiple genes. Many studies have provided evidence that as the incidence of ASD increases so do genetic similarities. However, very little research has…

Nutrigenomics, the microbiome, and gene environment interactions: new directions in cardiovascular disease research, prevention, and treatment. A scientific statement From the American Heart Association

USDA-ARS?s Scientific Manuscript database

Cardiometabolic diseases are the leading cause of death worldwide and are strongly linked to both genetic and nutritional factors. The field of nutrigenomics encompasses multiple approaches aimed at understanding the effects of diet on health or disease development, including nutrigenetic studies in...

Paraspeckles: Where Long Noncoding RNA Meets Phase Separation.

PubMed

Fox, Archa H; Nakagawa, Shinichi; Hirose, Tetsuro; Bond, Charles S

2018-02-01

Long noncoding RNA (lncRNA) molecules are some of the newest and least understood players in gene regulation. Hence, we need good model systems with well-defined RNA and protein components. One such system is paraspeckles - protein-rich nuclear organelles built around a specific lncRNA scaffold. New discoveries show how paraspeckles are formed through multiple RNA-protein and protein-protein interactions, some of which involve extensive polymerization, and others with multivalent interactions driving phase separation. Once formed, paraspeckles influence gene regulation through sequestration of component proteins and RNAs, with subsequent depletion in other compartments. Here we focus on the dual aspects of paraspeckle structure and function, revealing an emerging role for these dynamic bodies in a multitude of cellular settings. Copyright © 2017 Elsevier Ltd. All rights reserved.

Incorporating interaction networks into the determination of functionally related hit genes in genomic experiments with Markov random fields

PubMed Central

Robinson, Sean; Nevalainen, Jaakko; Pinna, Guillaume; Campalans, Anna; Radicella, J. Pablo; Guyon, Laurent

2017-01-01

Abstract Motivation: Incorporating gene interaction data into the identification of ‘hit’ genes in genomic experiments is a well-established approach leveraging the ‘guilt by association’ assumption to obtain a network based hit list of functionally related genes. We aim to develop a method to allow for multivariate gene scores and multiple hit labels in order to extend the analysis of genomic screening data within such an approach. Results: We propose a Markov random field-based method to achieve our aim and show that the particular advantages of our method compared with those currently used lead to new insights in previously analysed data as well as for our own motivating data. Our method additionally achieves the best performance in an independent simulation experiment. The real data applications we consider comprise of a survival analysis and differential expression experiment and a cell-based RNA interference functional screen. Availability and implementation: We provide all of the data and code related to the results in the paper. Contact: sean.j.robinson@utu.fi or laurent.guyon@cea.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28881978

Enhancement of efficiency of chitosan-based complexes for gene transfection with poly(γ-glutamic acid) by augmenting their cellular uptake and intracellular unpackage.

PubMed

Liao, Zi-Xian; Peng, Shu-Fen; Chiu, Ya-Ling; Hsiao, Chun-Wen; Liu, Hung-Yi; Lim, Woon-Hui; Lu, Hsiang-Ming; Sung, Hsing-Wen

2014-11-10

As a cationic polysaccharide, chitosan (CS) has been identified for its potential use as a non-viral vector for exogenous gene transfection. However, owing to their electrostatic interactions, CS complexes may cause difficulties in gene release upon their arrival at the site of action, thus limiting their transfection efficiency. In this work, an attempt is made to facilitate the release of a gene by incorporating a negatively-charged poly(γ-glutamic acid) (γPGA) into CS complexes in order to diminish their attractive interactions. The mechanisms of exploiting γPGA to enhance the transfection efficiency of CS complexes are elucidated. The feasibility of using this CS/γPGA-based system for DNA or siRNA transfer is explored as well. Additionally, potential of the CS/γPGA formulation to deliver disulfide bond-conjugated dual PEGylated siRNAs for multiple gene silencing is also examined. Moreover, the genetic use of pKillerRed-mem, delivered using complexes of CS and γPGA, to express a membrane-targeted KillerRed as an intrinsically generated photosensitizer for photodynamic therapy is described. Copyright © 2014 Elsevier B.V. All rights reserved.

[Influences of environmental factors and interaction of several chemokines gene-environmental on systemic lupus erythematosus].

PubMed

Ye, Dong-qing; Hu, Yi-song; Li, Xiang-pei; Huang, Fen; Yang, Shi-gui; Hao, Jia-hu; Yin, Jing; Zhang, Guo-qing; Liu, Hui-hui

2004-11-01

To explore the impact of environmental factors, daily lifestyle, psycho-social factors and the interactions between environmental factors and chemokines genes on systemic lupus erythematosus (SLE). Case-control study was carried out and environmental factors for SLE were analyzed by univariate and multivariate unconditional logistic regression. Interactions between environmental factors and chemokines polymorphism contributing to systemic lupus erythematosus were also analyzed by logistic regression model. There were nineteen factors associated with SLE when univariate unconditional logistic regression was used. However, when multivariate unconditional logistic regression was used, only five factors showed having impacts on the disease, in which drinking well water (OR=0.099) was protective factor for SLE, and multiple drug allergy (OR=8.174), over-exposure to sunshine (OR=18.339), taking antibiotics (OR=9.630) and oral contraceptives were risk factors for SLE. When unconditional logistic regression model was used, results showed that there was interaction between eating irritable food and -2518MCP-1G/G genotype (OR=4.387). No interaction between environmental factors was found that contributing to SLE in this study. Many environmental factors were related to SLE, and there was an interaction between -2518MCP-1G/G genotype and eating irritable food.

Rin4 Causes Hybrid Necrosis and Race-Specific Resistance in an Interspecific Lettuce Hybrid[W

PubMed Central

Jeuken, Marieke J.W.; Zhang, Ningwen W.; McHale, Leah K.; Pelgrom, Koen; den Boer, Erik; Lindhout, Pim; Michelmore, Richard W.; Visser, Richard G.F.; Niks, Rients E.

2009-01-01

Some inter- and intraspecific crosses may result in reduced viability or sterility in the offspring, often due to genetic incompatibilities resulting from interactions between two or more loci. Hybrid necrosis is a postzygotic genetic incompatibility that is phenotypically manifested as necrotic lesions on the plant. We observed hybrid necrosis in interspecific lettuce (Lactuca sativa and Lactuca saligna) hybrids that correlated with resistance to downy mildew. Segregation analysis revealed a specific allelic combination at two interacting loci to be responsible. The allelic interaction had two consequences: (1) a quantitative temperature-dependent autoimmunity reaction leading to necrotic lesions, lethality, and quantitative resistance to an otherwise virulent race of Bremia lactucae; and (2) a qualitative temperature-independent race-specific resistance to an avirulent race of B. lactucae. We demonstrated by transient expression and silencing experiments that one of the two interacting genes was Rin4. In Arabidopsis thaliana, RIN4 is known to interact with multiple R gene products, and their interactions result in hypersensitive resistance to Pseudomonas syringae. Site-directed mutation studies on the necrosis-eliciting allele of Rin4 in lettuce showed that three residues were critical for hybrid necrosis. PMID:19855048

Rin4 causes hybrid necrosis and race-specific resistance in an interspecific lettuce hybrid.

PubMed

Jeuken, Marieke J W; Zhang, Ningwen W; McHale, Leah K; Pelgrom, Koen; den Boer, Erik; Lindhout, Pim; Michelmore, Richard W; Visser, Richard G F; Niks, Rients E

2009-10-01

Some inter- and intraspecific crosses may result in reduced viability or sterility in the offspring, often due to genetic incompatibilities resulting from interactions between two or more loci. Hybrid necrosis is a postzygotic genetic incompatibility that is phenotypically manifested as necrotic lesions on the plant. We observed hybrid necrosis in interspecific lettuce (Lactuca sativa and Lactuca saligna) hybrids that correlated with resistance to downy mildew. Segregation analysis revealed a specific allelic combination at two interacting loci to be responsible. The allelic interaction had two consequences: (1) a quantitative temperature-dependent autoimmunity reaction leading to necrotic lesions, lethality, and quantitative resistance to an otherwise virulent race of Bremia lactucae; and (2) a qualitative temperature-independent race-specific resistance to an avirulent race of B. lactucae. We demonstrated by transient expression and silencing experiments that one of the two interacting genes was Rin4. In Arabidopsis thaliana, RIN4 is known to interact with multiple R gene products, and their interactions result in hypersensitive resistance to Pseudomonas syringae. Site-directed mutation studies on the necrosis-eliciting allele of Rin4 in lettuce showed that three residues were critical for hybrid necrosis.

Toxoplasmosis and Polygenic Disease Susceptibility Genes: Extensive Toxoplasma gondii Host/Pathogen Interactome Enrichment in Nine Psychiatric or Neurological Disorders

PubMed Central

Carter, C. J.

2013-01-01

Toxoplasma gondii is not only implicated in schizophrenia and related disorders, but also in Alzheimer's or Parkinson's disease, cancer, cardiac myopathies, and autoimmune disorders. During its life cycle, the pathogen interacts with ~3000 host genes or proteins. Susceptibility genes for multiple sclerosis, Alzheimer's disease, schizophrenia, bipolar disorder, depression, childhood obesity, Parkinson's disease, attention deficit hyperactivity disorder (P  from  8.01E − 05  (ADHD)  to  1.22E − 71) (multiple sclerosis), and autism (P = 0.013), but not anorexia or chronic fatigue are highly enriched in the human arm of this interactome and 18 (ADHD) to 33% (MS) of the susceptibility genes relate to it. The signalling pathways involved in the susceptibility gene/interactome overlaps are relatively specific and relevant to each disease suggesting a means whereby susceptibility genes could orient the attentions of a single pathogen towards disruption of the specific pathways that together contribute (positively or negatively) to the endophenotypes of different diseases. Conditional protein knockdown, orchestrated by T. gondii proteins or antibodies binding to those of the host (pathogen derived autoimmunity) and metabolite exchange, may contribute to this disruption. Susceptibility genes may thus be related to the causes and influencers of disease, rather than (and as well as) to the disease itself. PMID:23533776

Nature plus nurture: the triggering of multiple sclerosis.

PubMed

Wekerle, Hartmut

2015-01-01

Recent clinical and experimental studies indicate that multiple sclerosis develops as consequence of a failed interplay between genetic ("nature") and environmental ("nurture") factors. A large number of risk genes favour an autoimmune response against the body's own brain matter. New experimental data indicate that the actual trigger of this attack is however provided by an interaction of brain-specific immune cells with components of the regular commensal gut flora, the intestinal microbiota. This concept opens the way for new therapeutic approaches involving modulation of the microbiota by dietary or antibiotic regimens.

PSAT: A web tool to compare genomic neighborhoods of multiple prokaryotic genomes

PubMed Central

Fong, Christine; Rohmer, Laurence; Radey, Matthew; Wasnick, Michael; Brittnacher, Mitchell J

2008-01-01

Background The conservation of gene order among prokaryotic genomes can provide valuable insight into gene function, protein interactions, or events by which genomes have evolved. Although some tools are available for visualizing and comparing the order of genes between genomes of study, few support an efficient and organized analysis between large numbers of genomes. The Prokaryotic Sequence homology Analysis Tool (PSAT) is a web tool for comparing gene neighborhoods among multiple prokaryotic genomes. Results PSAT utilizes a database that is preloaded with gene annotation, BLAST hit results, and gene-clustering scores designed to help identify regions of conserved gene order. Researchers use the PSAT web interface to find a gene of interest in a reference genome and efficiently retrieve the sequence homologs found in other bacterial genomes. The tool generates a graphic of the genomic neighborhood surrounding the selected gene and the corresponding regions for its homologs in each comparison genome. Homologs in each region are color coded to assist users with analyzing gene order among various genomes. In contrast to common comparative analysis methods that filter sequence homolog data based on alignment score cutoffs, PSAT leverages gene context information for homologs, including those with weak alignment scores, enabling a more sensitive analysis. Features for constraining or ordering results are designed to help researchers browse results from large numbers of comparison genomes in an organized manner. PSAT has been demonstrated to be useful for helping to identify gene orthologs and potential functional gene clusters, and detecting genome modifications that may result in loss of function. Conclusion PSAT allows researchers to investigate the order of genes within local genomic neighborhoods of multiple genomes. A PSAT web server for public use is available for performing analyses on a growing set of reference genomes through any web browser with no client side software setup or installation required. Source code is freely available to researchers interested in setting up a local version of PSAT for analysis of genomes not available through the public server. Access to the public web server and instructions for obtaining source code can be found at . PMID:18366802

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

PubMed

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

2017-02-03

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

Genome-wide identification, classification and expression analysis in fungal-plant interactions of cutinase gene family and functional analysis of a putative ClCUT7 in Curvularia lunata.

PubMed

Liu, Tong; Hou, Jumei; Wang, Yuying; Jin, Yazhong; Borth, Wayne; Zhao, Fengzhou; Liu, Zheng; Hu, John; Zuo, Yuhu

2016-06-01

Cutinase is described as playing various roles in fungal-plant pathogen interactions, such as eliciting host-derived signals, fungal spore attachment and carbon acquisition during saprophytic growth. However, the characteristics of the cutinase genes, their expression in compatible interactions and their roles in pathogenesis have not been reported in Curvularia lunata, an important leaf spot pathogen of maize in China. Therefore, a cutinase gene family analysis could have profound significance. In this study, we identified 13 cutinase genes (ClCUT1 to ClCUT13) in the C. lunata genome. Multiple sequence alignment showed that most fungal cutinase proteins had one highly conserved GYSQG motif and a similar DxVCxG[ST]-[LIVMF](3)-x(3)H motif. Gene structure analyses of the cutinases revealed a complex intron-exon pattern with differences in the position and number of introns and exons. Based on phylogenetic relationship analysis, C. lunata cutinases and 78 known cutinase proteins from other fungi were classified into four groups with subgroups, but the C. lunata cutinases clustered in only three of the four groups. Motif analyses showed that each group of cutinases from C. lunata had a common motif. Real-time PCR indicated that transcript levels of the cutinase genes in a compatible interaction between pathogen and host had varied expression patterns. Interestingly, the transcript levels of ClCUT7 gradually increased during early pathogenesis with the most significant up-regulation at 3 h post-inoculation. When ClCUT7 was deleted, pathogenicity of the mutant decreased on unwounded maize (Zea mays) leaves. On wounded maize leaves, however, the mutant caused symptoms similar to the wild-type strain. Moreover, the ClCUT7 mutant had an approximately 10 % reduction in growth rate when cutin was the sole carbon source. In conclusion, we identified and characterized the cutinase family genes of C. lunata, analyzed their expression patterns in a compatible host-pathogen interaction, and explored the role of ClCUT7 in pathogenicity. This work will increase our understanding of cutinase genes in other fungal-plant pathogens.

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

PubMed Central

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

2012-01-01

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

SNP-by-fitness and SNP-by-BMI interactions from seven candidate genes and incident hypertension after 20 years of follow-up: the CARDIA Fitness Study.

PubMed

Sarzynski, M A; Rankinen, T; Sternfeld, B; Fornage, M; Sidney, S; Bouchard, C

2011-08-01

The association of single nucleotide polymorphisms (SNPs) from seven candidate genes, including genotype-by-baseline fitness and genotype-by-baseline body mass index (BMI) interactions, with incident hypertension over 20 years was investigated in 2663 participants (1301 blacks, 1362 whites) of the Coronary Artery Risk Development in Young Adults Study (CARDIA). Baseline cardiorespiratory fitness was determined from duration of a modified Balke treadmill test. A total of 98 SNPs in blacks and 89 SNPs in whites from seven candidate genes were genotyped. Participants that became hypertensive (295 blacks and 146 whites) had significantly higher blood pressure and BMI (both races), and lower fitness (blacks only) at baseline than those who remained normotensive. Markers at the peroxisome proliferative activated receptor gamma coactivator 1α (PPARGC1A) and bradykinin β2 receptor (BDKRB2) genes were nominally associated with greater risk of hypertension, although one marker each at the BDKRB2 and endothelial nitric oxide synthase-3 (NOS3) genes were nominally associated with lower risk. The association of baseline fitness with risk of hypertension was nominally modified by genotype at markers within the angiotensin converting enzyme, angiotensinogen, BDKRB2 and NOS3 genes in blacks and the BDKRB2, endothelin-1 and PPARGC1A genes in whites. BDKRB2 rs4900318 showed nominal interactions with baseline fitness on the risk of hypertension in both races. The association of baseline BMI with risk of hypertension was nominally modified by GNB3 rs2301339 genotype in whites. None of the above associations were statistically significant after correcting for multiple testing. We found that SNPs in these candidate genes did not modify the association between baseline fitness or BMI and risk of hypertension in CARDIA participants.

Interactions between genetic polymorphisms of glucose metabolizing genes and smoking and alcohol consumption in the risk of type 2 diabetes mellitus.

PubMed

Gao, Kaiping; Ren, Yongcheng; Wang, Jinjin; Liu, Zichen; Li, Jianna; Li, Linlin; Wang, Bingyuan; Li, Hong; Wang, Yaxi; Cao, Yunkai; Ohno, Kinji; Zhai, Rihong; Liang, Zhen

2017-12-01

The impact of gene-environment interaction on diabetes remains largely unknown. We aimed to investigate if interaction between glucose metabolizing genes and lifestyle factors is associated with type 2 diabetes mellitus (T2DM). Interactions between genotypes of 4 glucose metabolizing genes (MTNR1B, KCNQ1, KLF14, and GCKR) and lifestyle factors were estimated in 722 T2DM patients and 759 controls, using multiple logistic regression. No significant associations with T2DM were detected for the single nucleotide polymorphisms of MTNR1B, KLF14 and GCKR. However, rs151290 (KCNQ1) polymorphisms were found to be associated with risk of T2DM. Compared with AA, the odds ratios (ORs) of AC or CC genotypes for developing T2DM were 1.545 (P = 0.0489) and 1.603 (P = 0.0383), respectively. In stratified analyses, the associations were stronger in smokers with CC than smokers with AA (OR = 3.668, P = 0.013); drinkers with AC (OR = 5.518, P = 0.036), CC (OR = 8.691, P = 0.0095), and AC+CC (OR = 6.764, P = 0.016) than drinkers with AA. Compared with nondrinkers with AA, drinkers who carry AC and CC had 12.072-fold (P = 0.0007) and 8.147-fold (P = 0.0052) higher risk of developing T2DM. In conclusions, rs151290 (KCNQ1) polymorphisms are associated with increased risk of T2DM, alone and especially in interaction with smoking and alcohol.

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

PubMed

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.

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

PubMed Central

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

2008-01-01

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. PMID:19033192

Proteome-wide Prediction of Self-interacting Proteins Based on Multiple Properties*

PubMed Central

Liu, Zhongyang; Guo, Feifei; Zhang, Jiyang; Wang, Jian; Lu, Liang; Li, Dong; He, Fuchu

2013-01-01

Self-interacting proteins, whose two or more copies can interact with each other, play important roles in cellular functions and the evolution of protein interaction networks (PINs). Knowing whether a protein can self-interact can contribute to and sometimes is crucial for the elucidation of its functions. Previous related research has mainly focused on the structures and functions of specific self-interacting proteins, whereas knowledge on their overall properties is limited. Meanwhile, the two current most common high throughput protein interaction assays have limited ability to detect self-interactions because of biological artifacts and design limitations, whereas the bioinformatic prediction method of self-interacting proteins is lacking. This study aims to systematically study and predict self-interacting proteins from an overall perspective. We find that compared with other proteins the self-interacting proteins in the structural aspect contain more domains; in the evolutionary aspect they tend to be conserved and ancient; in the functional aspect they are significantly enriched with enzyme genes, housekeeping genes, and drug targets, and in the topological aspect tend to occupy important positions in PINs. Furthermore, based on these features, after feature selection, we use logistic regression to integrate six representative features, including Gene Ontology term, domain, paralogous interactor, enzyme, model organism self-interacting protein, and betweenness centrality in the PIN, to develop a proteome-wide prediction model of self-interacting proteins. Using 5-fold cross-validation and an independent test, this model shows good performance. Finally, the prediction model is developed into a user-friendly web service SLIPPER (SeLf-Interacting Protein PrEdictoR). Users may submit a list of proteins, and then SLIPPER will return the probability_scores measuring their possibility to be self-interacting proteins and various related annotation information. This work helps us understand the role self-interacting proteins play in cellular functions from an overall perspective, and the constructed prediction model may contribute to the high throughput finding of self-interacting proteins and provide clues for elucidating their functions. PMID:23422585

Transcriptomic profile induced in bone marrow mesenchymal stromal cells after interaction with multiple myeloma cells: implications in myeloma progression and myeloma bone disease

PubMed Central

Garcia-Gomez, Antonio; Las Rivas, Javier De; Ocio, Enrique M.; Díaz-Rodríguez, Elena; Montero, Juan C.; Martín, Montserrat; Blanco, Juan F.; Sanchez-Guijo, Fermín M.; Pandiella, Atanasio; San Miguel, Jesús F.; Garayoa, Mercedes

2014-01-01

Despite evidence about the implication of the bone marrow (BM) stromal microenvironment in multiple myeloma (MM) cell growth and survival, little is known about the effects of myelomatous cells on BM stromal cells. Mesenchymal stromal cells (MSCs) from healthy donors (dMSCs) or myeloma patients (pMSCs) were co-cultured with the myeloma cell line MM.1S, and the transcriptomic profile of MSCs induced by this interaction was analyzed. Deregulated genes after co-culture common to both d/pMSCs revealed functional involvement in tumor microenvironment cross-talk, myeloma growth induction and drug resistance, angiogenesis and signals for osteoclast activation and osteoblast inhibition. Additional genes induced by co-culture were exclusively deregulated in pMSCs and predominantly associated to RNA processing, the ubiquitine-proteasome pathway, cell cycle regulation, cellular stress and non-canonical Wnt signaling. The upregulated expression of five genes after co-culture (CXCL1, CXCL5 and CXCL6 in d/pMSCs, and Neuregulin 3 and Norrie disease protein exclusively in pMSCs) was confirmed, and functional in vitro assays revealed putative roles in MM pathophysiology. The transcriptomic profile of pMSCs co-cultured with myeloma cells may better reflect that of MSCs in the BM of myeloma patients, and provides new molecular insights to the contribution of these cells to MM pathophysiology and to myeloma bone disease. PMID:25268740

Simultaneous Identification of Multiple Driver Pathways in Cancer

PubMed Central

Leiserson, Mark D. M.; Blokh, Dima

2013-01-01

Distinguishing the somatic mutations responsible for cancer (driver mutations) from random, passenger mutations is a key challenge in cancer genomics. Driver mutations generally target cellular signaling and regulatory pathways consisting of multiple genes. This heterogeneity complicates the identification of driver mutations by their recurrence across samples, as different combinations of mutations in driver pathways are observed in different samples. We introduce the Multi-Dendrix algorithm for the simultaneous identification of multiple driver pathways de novo in somatic mutation data from a cohort of cancer samples. The algorithm relies on two combinatorial properties of mutations in a driver pathway: high coverage and mutual exclusivity. We derive an integer linear program that finds set of mutations exhibiting these properties. We apply Multi-Dendrix to somatic mutations from glioblastoma, breast cancer, and lung cancer samples. Multi-Dendrix identifies sets of mutations in genes that overlap with known pathways – including Rb, p53, PI(3)K, and cell cycle pathways – and also novel sets of mutually exclusive mutations, including mutations in several transcription factors or other genes involved in transcriptional regulation. These sets are discovered directly from mutation data with no prior knowledge of pathways or gene interactions. We show that Multi-Dendrix outperforms other algorithms for identifying combinations of mutations and is also orders of magnitude faster on genome-scale data. Software available at: http://compbio.cs.brown.edu/software. PMID:23717195

The combined effects of genetic risk and perceived discrimination on blood pressure among African Americans in the Jackson Heart Study

PubMed Central

Taylor, Jacquelyn Y.; Sun, Yan V.; Barcelona de Mendoza, Veronica; Ifatunji, Mosi; Rafferty, Jane; Fox, Ervin R.; Musani, Solomon K.; Sims, Mario; Jackson, James S.

2017-01-01

Abstract Both genomics and environmental stressors play a significant role in increases in blood pressure (BP). In an attempt to further explain the hypertension (HTN) disparity among African Americans (AA), both genetic underpinnings (selected candidate genes) and stress due to perceived racial discrimination (as reported in the literature) have independently been linked to increased BP among AAs. Although Gene x Environment interactions on BP have been examined, the environmental component of these investigations has focused more on lifestyle behaviors such as smoking, diet, and physical activity, and less on psychosocial stressors such as perceived discrimination. The present study uses candidate gene analyses to identify the relationship between Everyday Discrimination (ED) and Major Life Discrimination (MLD) with increases in systolic BP (SBP) and diastolic BP (DBP) among AA in the Jackson Heart Study. Multiple linear regression models reveal no association between discrimination and BP after adjusting for age, sex, body mass index (BMI), antihypertensive medication use, and current smoking status. Subsequent candidate gene analysis identified 5 SNPs (rs7602215, rs3771724, rs1006502, rs1791926, and rs2258119) that interacted with perceived discrimination and SBP, and 3 SNPs (rs2034454, rs7602215, and rs3771724) that interacted with perceived discrimination and DBP. Most notably, there was a significant SNP × discrimination interaction for 2 SNPs on the SLC4A5 gene: rs3771724 (MLD: SBP P = .034, DBP P = .031; ED: DBP: P = .016) and rs1006502 (MLD: SBP P = .034, DBP P = .030; ED: DBP P = .015). This study supports the idea that SNP × discrimination interactions combine to influence clinically relevant traits such as BP. Replication with similar epidemiological samples is required to ascertain the role of genes and psychosocial stressors in the development and expression of high BP in this understudied population. PMID:29069027

A Graphical Model of Smoking-Induced Global Instability in Lung Cancer.

PubMed

Wang, Yanbo; Qian, Weikang; Yuan, Bo

2018-01-01

Smoking is the major cause of lung cancer and the leading cause of cancer-related death in the world. The most current view about lung cancer is no longer limited to individual genes being mutated by any carcinogenic insults from smoking. Instead, tumorigenesis is a phenotype conferred by many systematic and global alterations, leading to extensive heterogeneity and variation for both the genotypes and phenotypes of individual cancer cells. Thus, strategically it is foremost important to develop a methodology to capture any consistent and global alterations presumably shared by most of the cancerous cells for a given population. This is particularly true that almost all of the data collected from solid cancers (including lung cancers) are usually distant apart over a large span of temporal or even spatial contexts. Here, we report a multiple non-Gaussian graphical model to reconstruct the gene interaction network using two previously published gene expression datasets. Our graphical model aims to selectively detect gross structural changes at the level of gene interaction networks. Our methodology is extensively validated, demonstrating good robustness, as well as the selectivity and specificity expected based on our biological insights. In summary, gene regulatory networks are still relatively stable during presumably the early stage of neoplastic transformation. But drastic structural differences can be found between lung cancer and its normal control, including the gain of functional modules for cellular proliferations such as EGFR and PDGFRA, as well as the lost of the important IL6 module, supporting their roles as potential drug targets. Interestingly, our method can also detect early modular changes, with the ALDH3A1 and its associated interactions being strongly implicated as a potential early marker, whose activations appear to alter LCN2 module as well as its interactions with the important TP53-MDM2 circuitry. Our strategy using the graphical model to reconstruct gene interaction work with biologically-inspired constraints exemplifies the importance and beauty of biology in developing any bio-computational approach.

The combined effects of genetic risk and perceived discrimination on blood pressure among African Americans in the Jackson Heart Study.

PubMed

Taylor, Jacquelyn Y; Sun, Yan V; Barcelona de Mendoza, Veronica; Ifatunji, Mosi; Rafferty, Jane; Fox, Ervin R; Musani, Solomon K; Sims, Mario; Jackson, James S

2017-10-01

Both genomics and environmental stressors play a significant role in increases in blood pressure (BP). In an attempt to further explain the hypertension (HTN) disparity among African Americans (AA), both genetic underpinnings (selected candidate genes) and stress due to perceived racial discrimination (as reported in the literature) have independently been linked to increased BP among AAs. Although Gene x Environment interactions on BP have been examined, the environmental component of these investigations has focused more on lifestyle behaviors such as smoking, diet, and physical activity, and less on psychosocial stressors such as perceived discrimination.The present study uses candidate gene analyses to identify the relationship between Everyday Discrimination (ED) and Major Life Discrimination (MLD) with increases in systolic BP (SBP) and diastolic BP (DBP) among AA in the Jackson Heart Study. Multiple linear regression models reveal no association between discrimination and BP after adjusting for age, sex, body mass index (BMI), antihypertensive medication use, and current smoking status.Subsequent candidate gene analysis identified 5 SNPs (rs7602215, rs3771724, rs1006502, rs1791926, and rs2258119) that interacted with perceived discrimination and SBP, and 3 SNPs (rs2034454, rs7602215, and rs3771724) that interacted with perceived discrimination and DBP. Most notably, there was a significant SNP × discrimination interaction for 2 SNPs on the SLC4A5 gene: rs3771724 (MLD: SBP P = .034, DBP P = .031; ED: DBP: P = .016) and rs1006502 (MLD: SBP P = .034, DBP P = .030; ED: DBP P = .015).This study supports the idea that SNP × discrimination interactions combine to influence clinically relevant traits such as BP. Replication with similar epidemiological samples is required to ascertain the role of genes and psychosocial stressors in the development and expression of high BP in this understudied population.

Renin-Angiotensin System Gene Variants and Type 2 Diabetes Mellitus: Influence of Angiotensinogen

PubMed Central

Joyce-Tan, Siew Mei; Zain, Shamsul Mohd; Abdul Sattar, Munavvar Zubaid; Abdullah, Nor Azizan

2016-01-01

Genome-wide association studies (GWAS) have been successfully used to call for variants associated with diseases including type 2 diabetes mellitus (T2DM). However, some variants are not included in the GWAS to avoid penalty in multiple hypothetic testing. Thus, candidate gene approach is still useful even at GWAS era. This study attempted to assess whether genetic variations in the renin-angiotensin system (RAS) and their gene interactions are associated with T2DM risk. We genotyped 290 T2DM patients and 267 controls using three genes of the RAS, namely, angiotensin converting enzyme (ACE), angiotensinogen (AGT), and angiotensin II type 1 receptor (AGTR1). There were significant differences in allele frequencies between cases and controls for AGT variants (P = 0.05) but not for ACE and AGTR1. Haplotype TCG of the AGT was associated with increased risk of T2DM (OR 1.92, 95% CI 1.15–3.20, permuted P = 0.012); however, no evidence of significant gene-gene interactions was seen. Nonetheless, our analysis revealed that the associations of the AGT variants with T2DM were independently associated. Thus, this study suggests that genetic variants of the RAS can modestly influence the T2DM risk. PMID:26682227

Associations of multiple trauma types and MAOA with severe aggressive behavior and MAOA effects on training outcome.

PubMed

Smeijers, Danique; Bulten, Erik; Franke, Barbara; Buitelaar, Jan; Verkes, Robbert-Jan

2017-07-01

Previous research showed that the disposition to react with disproportionate aggression in adults is influenced by an interaction between a variant in the X-chromosomal monoamine oxidase A gene (MAOA) and early traumatic events. Such studies have often focused on a single type of trauma, whereas we know that experiencing multiple trauma types is associated with more detrimental consequences. The differential susceptibility hypothesis suggests that individuals who are most susceptible to adversity, are also most likely to benefit from supportive experiences in childhood. Differences in susceptibility are thought to be partly genetically driven. In the present study we explored whether a genotype of MAOA linked to lower expression of the gene (MAOA-L) modified the effect of multiple types of trauma on aggression and/or altered responsiveness to treatment among adults with severe aggression. Forensic psychiatric outpatients (FPOs) (N=150) receiving treatment for aggression regulation problems were recruited. Traumatic events and aggression were measured using self-report. FPOs with multiple trauma types and those with the MAOA-L allele reported more severe levels of aggression. No interaction effects between MAOA genotype and trauma emerged. There were no differences in response to the intervention between FPOs with and without the MAOA-L variant, whereas FPOs with a single type of trauma showed the slowest reduction of aggression. FPOs with multiple types of trauma reported the highest levels of aggression over the course of treatment. Future research is needed to elucidate this association in further detail. The current study emphasized the importance of early recognition of early traumatic events. Copyright © 2017 Elsevier B.V. and ECNP. All rights reserved.

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

PubMed

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.

The Transcription Factors TBX2 and TBX3 Interact with Human Papillomavirus 16 (HPV16) L2 and Repress the Long Control Region of HPVs

PubMed Central

Schneider, Marc A.; Scheffer, Konstanze D.; Bund, Timo; Boukhallouk, Fatima; Lambert, Carsten; Cotarelo, Cristina; Pflugfelder, Gert O.

2013-01-01

The minor capsid protein L2 of human papillomaviruses (HPVs) has multiple functions during the viral life cycle. Although L2 is required for effective invasion and morphogenesis, only a few cellular interaction partners are known so far. Using yeast two-hybrid screening, we identified the transcription factor TBX2 as a novel interaction partner of HPV type 16 (HPV16) L2. Coimmunoprecipitations and immunofluorescence analyses confirmed the L2-TBX2 interaction and revealed that L2 also interacts with TBX3, another member of the T-box family. Transcription of the early genes during HPV infection is under the control of an upstream enhancer and early promoter region, the long control region (LCR). In promoter-reporter gene assays, we observed that TBX2 and TBX3 repress transcription from the LCR and that this effect is enhanced by L2. Repression of the HPV LCR by TBX2/3 seems to be a conserved mechanism, as it was also observed with the LCRs of different HPV types. Finally, interaction of TBX2 with the LCR was detected by chromatin immunoprecipitation, and we found a strong colocalization of L2 and TBX2 in HPV16-positive cervical intraepithelial neoplasia (CIN) I-II tissue sections. These results suggest that TBX2/3 might play a role in the regulation of HPV gene expression during the viral life cycle. PMID:23388722

Gene-environment interaction involving recently identified colorectal cancer susceptibility loci

PubMed Central

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

Biomine: predicting links between biological entities using network models of heterogeneous databases.

PubMed

Eronen, Lauri; Toivonen, Hannu

2012-06-06

Biological databases contain large amounts of data concerning the functions and associations of genes and proteins. Integration of data from several such databases into a single repository can aid the discovery of previously unknown connections spanning multiple types of relationships and databases. Biomine is a system that integrates cross-references from several biological databases into a graph model with multiple types of edges, such as protein interactions, gene-disease associations and gene ontology annotations. Edges are weighted based on their type, reliability, and informativeness. We present Biomine and evaluate its performance in link prediction, where the goal is to predict pairs of nodes that will be connected in the future, based on current data. In particular, we formulate protein interaction prediction and disease gene prioritization tasks as instances of link prediction. The predictions are based on a proximity measure computed on the integrated graph. We consider and experiment with several such measures, and perform a parameter optimization procedure where different edge types are weighted to optimize link prediction accuracy. We also propose a novel method for disease-gene prioritization, defined as finding a subset of candidate genes that cluster together in the graph. We experimentally evaluate Biomine by predicting future annotations in the source databases and prioritizing lists of putative disease genes. The experimental results show that Biomine has strong potential for predicting links when a set of selected candidate links is available. The predictions obtained using the entire Biomine dataset are shown to clearly outperform ones obtained using any single source of data alone, when different types of links are suitably weighted. In the gene prioritization task, an established reference set of disease-associated genes is useful, but the results show that under favorable conditions, Biomine can also perform well when no such information is available.The Biomine system is a proof of concept. Its current version contains 1.1 million entities and 8.1 million relations between them, with focus on human genetics. Some of its functionalities are available in a public query interface at http://biomine.cs.helsinki.fi, allowing searching for and visualizing connections between given biological entities.

Transcription Factor Information System (TFIS): A Tool for Detection of Transcription Factor Binding Sites.

PubMed

Narad, Priyanka; Kumar, Abhishek; Chakraborty, Amlan; Patni, Pranav; Sengupta, Abhishek; Wadhwa, Gulshan; Upadhyaya, K C

2017-09-01

Transcription factors are trans-acting proteins that interact with specific nucleotide sequences known as transcription factor binding site (TFBS), and these interactions are implicated in regulation of the gene expression. Regulation of transcriptional activation of a gene often involves multiple interactions of transcription factors with various sequence elements. Identification of these sequence elements is the first step in understanding the underlying molecular mechanism(s) that regulate the gene expression. For in silico identification of these sequence elements, we have developed an online computational tool named transcription factor information system (TFIS) for detecting TFBS for the first time using a collection of JAVA programs and is mainly based on TFBS detection using position weight matrix (PWM). The database used for obtaining position frequency matrices (PFM) is JASPAR and HOCOMOCO, which is an open-access database of transcription factor binding profiles. Pseudo-counts are used while converting PFM to PWM, and TFBS detection is carried out on the basis of percent score taken as threshold value. TFIS is equipped with advanced features such as direct sequence retrieving from NCBI database using gene identification number and accession number, detecting binding site for common TF in a batch of gene sequences, and TFBS detection after generating PWM from known raw binding sequences in addition to general detection methods. TFIS can detect the presence of potential TFBSs in both the directions at the same time. This feature increases its efficiency. And the results for this dual detection are presented in different colors specific to the orientation of the binding site. Results obtained by the TFIS are more detailed and specific to the detected TFs as integration of more informative links from various related web servers are added in the result pages like Gene Ontology, PAZAR database and Transcription Factor Encyclopedia in addition to NCBI and UniProt. Common TFs like SP1, AP1 and NF-KB of the Amyloid beta precursor gene is easily detected using TFIS along with multiple binding sites. In another scenario of embryonic developmental process, TFs of the FOX family (FOXL1 and FOXC1) were also identified. TFIS is platform-independent which is publicly available along with its support and documentation at http://tfistool.appspot.com and http://www.bioinfoplus.com/tfis/ . TFIS is licensed under the GNU General Public License, version 3 (GPL-3.0).

A Guide to the PLAZA 3.0 Plant Comparative Genomic Database.

PubMed

Vandepoele, Klaas

2017-01-01

PLAZA 3.0 is an online resource for comparative genomics and offers a versatile platform to study gene functions and gene families or to analyze genome organization and evolution in the green plant lineage. Starting from genome sequence information for over 35 plant species, precomputed comparative genomic data sets cover homologous gene families, multiple sequence alignments, phylogenetic trees, and genomic colinearity information within and between species. Complementary functional data sets, a Workbench, and interactive visualization tools are available through a user-friendly web interface, making PLAZA an excellent starting point to translate sequence or omics data sets into biological knowledge. PLAZA is available at http://bioinformatics.psb.ugent.be/plaza/ .

Gene Presence-Absence Polymorphism in Castrating Anther-Smut Fungi: Recent Gene Gains and Phylogeographic Structure.

PubMed

Hartmann, Fanny E; Rodríguez de la Vega, Ricardo C; Brandenburg, Jean-Tristan; Carpentier, Fantin; Giraud, Tatiana

2018-04-01

Gene presence-absence polymorphisms segregating within species are a significant source of genetic variation but have been little investigated to date in natural populations. In plant pathogens, the gain or loss of genes encoding proteins interacting directly with the host, such as secreted proteins, probably plays an important role in coevolution and local adaptation. We investigated gene presence-absence polymorphism in populations of two closely related species of castrating anther-smut fungi, Microbotryum lychnidis-dioicae (MvSl) and M. silenes-dioicae (MvSd), from across Europe, on the basis of Illumina genome sequencing data and high-quality genome references. We observed presence-absence polymorphism for 186 autosomal genes (2% of all genes) in MvSl, and only 51 autosomal genes in MvSd. Distinct genes displayed presence-absence polymorphism in the two species. Genes displaying presence-absence polymorphism were frequently located in subtelomeric and centromeric regions and close to repetitive elements, and comparison with outgroups indicated that most were present in a single species, being recently acquired through duplications in multiple-gene families. Gene presence-absence polymorphism in MvSl showed a phylogeographic structure corresponding to clusters detected based on SNPs. In addition, gene absence alleles were rare within species and skewed toward low-frequency variants. These findings are consistent with a deleterious or neutral effect for most gene presence-absence polymorphism. Some of the observed gene loss and gain events may however be adaptive, as suggested by the putative functions of the corresponding encoded proteins (e.g., secreted proteins) or their localization within previously identified selective sweeps. The adaptive roles in plant and anther-smut fungi interactions of candidate genes however need to be experimentally tested in future studies.

Gene Presence–Absence Polymorphism in Castrating Anther-Smut Fungi: Recent Gene Gains and Phylogeographic Structure

PubMed Central

Rodríguez de la Vega, Ricardo C; Brandenburg, Jean-Tristan; Carpentier, Fantin; Giraud, Tatiana

2018-01-01

Abstract Gene presence–absence polymorphisms segregating within species are a significant source of genetic variation but have been little investigated to date in natural populations. In plant pathogens, the gain or loss of genes encoding proteins interacting directly with the host, such as secreted proteins, probably plays an important role in coevolution and local adaptation. We investigated gene presence–absence polymorphism in populations of two closely related species of castrating anther-smut fungi, Microbotryum lychnidis-dioicae (MvSl) and M. silenes-dioicae (MvSd), from across Europe, on the basis of Illumina genome sequencing data and high-quality genome references. We observed presence–absence polymorphism for 186 autosomal genes (2% of all genes) in MvSl, and only 51 autosomal genes in MvSd. Distinct genes displayed presence–absence polymorphism in the two species. Genes displaying presence–absence polymorphism were frequently located in subtelomeric and centromeric regions and close to repetitive elements, and comparison with outgroups indicated that most were present in a single species, being recently acquired through duplications in multiple-gene families. Gene presence–absence polymorphism in MvSl showed a phylogeographic structure corresponding to clusters detected based on SNPs. In addition, gene absence alleles were rare within species and skewed toward low-frequency variants. These findings are consistent with a deleterious or neutral effect for most gene presence–absence polymorphism. Some of the observed gene loss and gain events may however be adaptive, as suggested by the putative functions of the corresponding encoded proteins (e.g., secreted proteins) or their localization within previously identified selective sweeps. The adaptive roles in plant and anther-smut fungi interactions of candidate genes however need to be experimentally tested in future studies. PMID:29722826

Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach

PubMed Central

Ye, Yusen; Gao, Lin; Zhang, Shihua

2017-01-01

Transcription factors play a key role in transcriptional regulation of genes and determination of cellular identity through combinatorial interactions. However, current studies about combinatorial regulation is deficient due to lack of experimental data in the same cellular environment and extensive existence of data noise. Here, we adopt a Bayesian CANDECOMP/PARAFAC (CP) factorization approach (BCPF) to integrate multiple datasets in a network paradigm for determining precise TF interaction landscapes. In our first application, we apply BCPF to integrate three networks built based on diverse datasets of multiple cell lines from ENCODE respectively to predict a global and precise TF interaction network. This network gives 38 novel TF interactions with distinct biological functions. In our second application, we apply BCPF to seven types of cell type TF regulatory networks and predict seven cell lineage TF interaction networks, respectively. By further exploring the dynamics and modularity of them, we find cell lineage-specific hub TFs participate in cell type or lineage-specific regulation by interacting with non-specific TFs. Furthermore, we illustrate the biological function of hub TFs by taking those of cancer lineage and blood lineage as examples. Taken together, our integrative analysis can reveal more precise and extensive description about human TF combinatorial interactions. PMID:29033978

Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach.

PubMed

Ye, Yusen; Gao, Lin; Zhang, Shihua

2017-01-01

Transcription factors play a key role in transcriptional regulation of genes and determination of cellular identity through combinatorial interactions. However, current studies about combinatorial regulation is deficient due to lack of experimental data in the same cellular environment and extensive existence of data noise. Here, we adopt a Bayesian CANDECOMP/PARAFAC (CP) factorization approach (BCPF) to integrate multiple datasets in a network paradigm for determining precise TF interaction landscapes. In our first application, we apply BCPF to integrate three networks built based on diverse datasets of multiple cell lines from ENCODE respectively to predict a global and precise TF interaction network. This network gives 38 novel TF interactions with distinct biological functions. In our second application, we apply BCPF to seven types of cell type TF regulatory networks and predict seven cell lineage TF interaction networks, respectively. By further exploring the dynamics and modularity of them, we find cell lineage-specific hub TFs participate in cell type or lineage-specific regulation by interacting with non-specific TFs. Furthermore, we illustrate the biological function of hub TFs by taking those of cancer lineage and blood lineage as examples. Taken together, our integrative analysis can reveal more precise and extensive description about human TF combinatorial interactions.

Host genetic determinants of microbiota-dependent nutrition revealed by genome-wide analysis of Drosophila melanogaster

PubMed Central

Dobson, Adam J.; Chaston, John M.; Newell, Peter D.; Donahue, Leanne; Hermann, Sara L.; Sannino, David R.; Westmiller, Stephanie; Wong, Adam C.-N.; Clark, Andrew G.; Lazzaro, Brian P.; Douglas, Angela E.

2015-01-01

Animals bear communities of gut microorganisms with substantial effects on animal nutrition, but the host genetic basis of these effects is unknown. Here, we use Drosophila to demonstrate substantial among-genotype variation in the effects of eliminating the gut microbiota on five host nutritional indices (weight, and protein, lipid, glucose and glycogen contents); this includes variation in both the magnitude and direction of microbiota-dependent effects. Genome-wide associations to identify the genetic basis of the microbiota-dependent variation reveal polymorphisms in largely non-overlapping sets of genes associated with variation in the nutritional traits, including strong representation of conserved genes functioning in signaling. Key genes identified by the GWA study are validated by loss-of-function mutations that altered microbiota-dependent nutritional effects. We conclude that the microbiota interacts with the animal at multiple points in the signaling and regulatory networks that determine animal nutrition. These interactions with the microbiota are likely conserved across animals, including humans. PMID:25692519

Menin-MLL inhibitors reverse oncogenic activity of MLL fusion proteins in leukemia.

PubMed

Grembecka, Jolanta; He, Shihan; Shi, Aibin; Purohit, Trupta; Muntean, Andrew G; Sorenson, Roderick J; Showalter, Hollis D; Murai, Marcelo J; Belcher, Amalia M; Hartley, Thomas; Hess, Jay L; Cierpicki, Tomasz

2012-01-29

Translocations involving the mixed lineage leukemia (MLL) gene result in human acute leukemias with very poor prognosis. The leukemogenic activity of MLL fusion proteins is critically dependent on their direct interaction with menin, a product of the multiple endocrine neoplasia (MEN1) gene. Here we present what are to our knowledge the first small-molecule inhibitors of the menin-MLL fusion protein interaction that specifically bind menin with nanomolar affinities. These compounds effectively reverse MLL fusion protein-mediated leukemic transformation by downregulating the expression of target genes required for MLL fusion protein oncogenic activity. They also selectively block proliferation and induce both apoptosis and differentiation of leukemia cells harboring MLL translocations. Identification of these compounds provides a new tool for better understanding MLL-mediated leukemogenesis and represents a new approach for studying the role of menin as an oncogenic cofactor of MLL fusion proteins. Our findings also highlight a new therapeutic strategy for aggressive leukemias with MLL rearrangements.

Genetics of schizophrenia from a clinicial perspective

PubMed Central

Kukshal, Prachi; Thelma, B. K.; Nimgaonkar, Vishwajit L.; Deshpande, Smita N.

2017-01-01

Schizophrenia (SZ) is a common disorder that runs in families. It has a relatively high heritability, i.e. inherited factors account for the major proportion of its etiology. The high heritability has motivated gene mapping studies that have improved in sophistication through the past two decades. Belying earlier expectations, it is now becoming increasingly clear that the cause of SZ does not reside in a single mutation, or even in a single gene. Rather, there are multiple DNA variants, not all of which have been identified. Additional risk may be conferred by interactions between individual DNA variants, as well as ‘gene-environment’ interactions. We review studies that have accounted for a fraction of the heritability. Their relevance to the practising clinician is discussed. We propose that continuing research in DNA variation, in conjunction with rapid ongoing advances in allied fields, will yield dividends from the perspective of diagnosis, treatment prediction through pharmacogenetics, and rational treatment through discoveries in pathogenesis. PMID:23057976

Retroviruses Hijack Chromatin Loops to Drive Oncogene Expression and Highlight the Chromatin Architecture around Proto-Oncogenic Loci

PubMed Central

Pattison, Jillian M.; Wright, Jason B.; Cole, Michael D.

2015-01-01

The majority of the genome consists of intergenic and non-coding DNA sequences shown to play a major role in different gene regulatory networks. However, the specific potency of these distal elements as well as how these regions exert function across large genomic distances remains unclear. To address these unresolved issues, we closely examined the chromatin architecture around proto-oncogenic loci in the mouse and human genomes to demonstrate a functional role for chromatin looping in distal gene regulation. Using cell culture models, we show that tumorigenic retroviral integration sites within the mouse genome occur near existing large chromatin loops and that this chromatin architecture is maintained within the human genome as well. Significantly, as mutagenesis screens are not feasible in humans, we demonstrate a way to leverage existing screens in mice to identify disease relevant human enhancers and expose novel disease mechanisms. For instance, we characterize the epigenetic landscape upstream of the human Cyclin D1 locus to find multiple distal interactions that contribute to the complex cis-regulation of this cell cycle gene. Furthermore, we characterize a novel distal interaction upstream of the Cyclin D1 gene which provides mechanistic evidence for the abundant overexpression of Cyclin D1 occurring in multiple myeloma cells harboring a pathogenic translocation event. Through use of mapped retroviral integrations and translocation breakpoints, our studies highlight the importance of chromatin looping in oncogene expression, elucidate the epigenetic mechanisms crucial for distal cis-regulation, and in one particular instance, explain how a translocation event drives tumorigenesis through upregulation of a proto-oncogene. PMID:25799187

Obstructive heart defects associated with candidate genes, maternal obesity, and folic acid supplementation.

PubMed

Tang, Xinyu; Cleves, Mario A; Nick, Todd G; Li, Ming; MacLeod, Stewart L; Erickson, Stephen W; Li, Jingyun; Shaw, Gary M; Mosley, Bridget S; Hobbs, Charlotte A

2015-06-01

Right-sided and left-sided obstructive heart defects (OHDs) are subtypes of congenital heart defects, in which the heart valves, arteries, or veins are abnormally narrow or blocked. Previous studies have suggested that the development of OHDs involved a complex interplay between genetic variants and maternal factors. Using the data from 569 OHD case families and 1,644 control families enrolled in the National Birth Defects Prevention Study (NBDPS) between 1997 and 2008, we conducted an analysis to investigate the genetic effects of 877 single nucleotide polymorphisms (SNPs) in 60 candidate genes for association with the risk of OHDs, and their interactions with maternal use of folic acid supplements, and pre-pregnancy obesity. Applying log-linear models based on the hybrid design, we identified a SNP in methylenetetrahydrofolate reductase (MTHFR) gene (C677T polymorphism) with a main genetic effect on the occurrence of OHDs. In addition, multiple SNPs in betaine-homocysteine methyltransferase (BHMT and BHMT2) were also identified to be associated with the occurrence of OHDs through significant main infant genetic effects and interaction effects with maternal use of folic acid supplements. We also identified multiple SNPs in glutamate-cysteine ligase, catalytic subunit (GCLC) and DNA (cytosine-5-)-methyltransferase 3 beta (DNMT3B) that were associated with elevated risk of OHDs among obese women. Our findings suggested that the risk of OHDs was closely related to a combined effect of variations in genes in the folate, homocysteine, or glutathione/transsulfuration pathways, maternal use of folic acid supplements and pre-pregnancy obesity. © 2015 Wiley Periodicals, Inc.

Vitamin D3 Receptor ( VDR ) Gene rs2228570 (Fok1) and rs731236 (Taq1) Variants Are Not Associated with the Risk for Multiple Sclerosis: Results of a New Study and a Meta-Analysis

PubMed Central

García-Martín, Elena; Agúndez, José A. G.; Martínez, Carmen; Benito-León, Julián; Millán-Pascual, Jorge; Calleja, Patricia; Díaz-Sánchez, María; Pisa, Diana; Turpín-Fenoll, Laura; Alonso-Navarro, Hortensia; Ayuso-Peralta, Lucía; Torrecillas, Dolores; Plaza-Nieto, José Francisco; Jiménez-Jiménez, Félix Javier

2013-01-01

Background Some epidemiological, genetic, and experimental data suggest a possible role of vitamin D in the pathogenesis of multiple sclerosis (MS) and in experimental autoimmune encephalomyelitis. Data on the possible contribution of several single nucleotide polymorphisms (SNP) in the vitamin D receptor (VDR) gene to the risk for MS are controversial. Several studies suggested an interaction between some SNPs in the VDR gene and HLADRB1*1501 in the risk for MS. Objectives The aim of this study was to investigate a possible influence of the SNPs rs2228570 and rs731236 in the VDR gene in the risk for MS. A secondary objective was to address the possible interactions between VDR genes and HLADRB1*1501. Methods We analyzed the allelic and genotype frequency of VDR rs2228570, rs731236, and HLADRB1*1501 (rs3135388) in 303 patients with MS and 310 healthy controls, using TaqMan Assays. We also conducted a meta-analysis, that was carried out by using the software Meta-Disc 1.1.1 (http://www.hrc.es/investigacion/metadisc.html; Unit of Clinical Statistics, Hospital Ramón y Cajal, Madrid, Spain). Heterogeneity between studies in terms of degree of association was tested using the Q-statistic. Results VDR rs2228570 and rs731236 allelic and genotype frequencies did not differ significantly between MS patients and controls, and were unrelated with the age of onset of MS, gender, and course of MS. HLADRB1*1501 showed a high association with the risk of developing MS 4.76(95% C.I.  = 3.14–7.27; p<0.0001). The meta-analysis, after excluding data of one study that was responsible of heterogeneity for rs731236 polymorphism, showed lack of relation of both SNPs with the risk for MS. HLADRB1*1501 showed lack of interaction with VDR rs2228570 and rs731236 in increasing MS risk. Conclusions These results suggest that VDR rs2228570 and rs731236 polymorphisms are not related with the risk for MS, and did not confirm interaction between these VDR SNPs and HLADRB1 in the risk for MS. PMID:23840333

bHLH106 Integrates Functions of Multiple Genes through Their G-Box to Confer Salt Tolerance on Arabidopsis.

PubMed

Ahmad, Aftab; Niwa, Yasuo; Goto, Shingo; Ogawa, Takeshi; Shimizu, Masanori; Suzuki, Akane; Kobayashi, Kyoko; Kobayashi, Hirokazu

2015-01-01

An activation-tagging methodology was applied to dedifferentiated calli of Arabidopsis to identify new genes involved in salt tolerance. This identified salt tolerant callus 8 (stc8) as a gene encoding the basic helix-loop-helix transcription factor bHLH106. bHLH106-knockout (KO) lines were more sensitive to NaCl, KCl, LiCl, ABA, and low temperatures than the wild-type. Back-transformation of the KO line rescued its phenotype, and over-expression (OX) of bHLH106 in differentiated plants exhibited tolerance to NaCl. Green fluorescent protein (GFP) fused with bHLH106 revealed that it was localized to the nucleus. Prepared bHLH106 protein was subjected to electrophoresis mobility shift assays against E-box sequences (5'-CANNTG-3'). The G-box sequence 5'-CACGTG-3' had the strongest interaction with bHLH106. bHLH106-OX lines were transcriptomically analyzed, and resultant up- and down-regulated genes selected on the criterion of presence of a G-box sequence. There were 198 genes positively regulated by bHLH106 and 36 genes negatively regulated; these genes possessed one or more G-box sequences in their promoter regions. Many of these genes are known to be involved in abiotic stress response. It is concluded that bHLH106 locates at a branching point in the abiotic stress response network by interacting directly to the G-box in genes conferring salt tolerance on plants.

Detection of changes in gene regulatory patterns, elicited by perturbations of the Hsp90 molecular chaperone complex, by visualizing multiple experiments with an animation

PubMed Central

2011-01-01

Background To make sense out of gene expression profiles, such analyses must be pushed beyond the mere listing of affected genes. For example, if a group of genes persistently display similar changes in expression levels under particular experimental conditions, and the proteins encoded by these genes interact and function in the same cellular compartments, this could be taken as very strong indicators for co-regulated protein complexes. One of the key requirements is having appropriate tools to detect such regulatory patterns. Results We have analyzed the global adaptations in gene expression patterns in the budding yeast when the Hsp90 molecular chaperone complex is perturbed either pharmacologically or genetically. We integrated these results with publicly accessible expression, protein-protein interaction and intracellular localization data. But most importantly, all experimental conditions were simultaneously and dynamically visualized with an animation. This critically facilitated the detection of patterns of gene expression changes that suggested underlying regulatory networks that a standard analysis by pairwise comparison and clustering could not have revealed. Conclusions The results of the animation-assisted detection of changes in gene regulatory patterns make predictions about the potential roles of Hsp90 and its co-chaperone p23 in regulating whole sets of genes. The simultaneous dynamic visualization of microarray experiments, represented in networks built by integrating one's own experimental with publicly accessible data, represents a powerful discovery tool that allows the generation of new interpretations and hypotheses. PMID:21672238

Interaction of Osmotic Stress, Temperature, and Abscisic Acid in the Regulation of Gene Expression in Arabidopsis

PubMed Central

Xiong, Liming; Ishitani, Manabu; Zhu, Jian-Kang

1999-01-01

The impact of simultaneous environmental stresses on plants and how they respond to combined stresses compared with single stresses is largely unclear. By using a transgene (RD29A-LUC) consisting of the firefly luciferase coding sequence (LUC) driven by the stress-responsive RD29A promoter, we investigated the interactive effects of temperature, osmotic stress, and the phytohormone abscisic acid (ABA) in the regulation of gene expression in Arabidopsis seedlings. Results indicated that both positive and negative interactions exist among the studied stress factors in regulating gene expression. At a normal growth temperature (22°C), osmotic stress and ABA act synergistically to induce the transgene expression. Low temperature inhibits the response to osmotic stress or to combined treatment of osmotic stress and ABA, whereas low temperature and ABA treatments are additive in inducing transgene expression. Although high temperature alone does not activate the transgene, it significantly amplifies the effects of ABA and osmotic stress. The effect of multiple stresses in the regulation of RD29A-LUC expression in signal transduction mutants was also studied. The results are discussed in the context of cold and osmotic stress signal transduction pathways. PMID:9880362

The interplay of genetic and environmental factors in shaping well-being across the lifespan: Evidence from the serotonin transporter gene.

PubMed

Gärtner, Matti; Grimm, Simone; Aust, Sabine; Fan, Yan; von Scheve, Christian; Bajbouj, Malek

2017-07-07

Converging evidence suggests that well-being plays an important role in promoting and maintaining mental health across the life span. It has been shown that well-being has a considerable heritable component, but little is known about the specific genes involved. In this study, we investigated a healthy sample (N = 298) that was genotyped for the serotonin transporter-linked polymorphic region (5-HTTLPR). We hypothesized that 5-HTTLPR gene variation would influence well-being, and additionally investigated interaction effects with age and the environmental influence of early life stress (ELS). Using multiple regression, our results showed a significant three-way interaction between genotype, ELS, and age. Exploration of this interaction showed that young subjects had decreased levels of well-being if they were exposed to ELS and homozygous for the short variant of 5-HTTLPR. This relationship was reversed in old age: subjects that were exposed to ELS and carried the long variant of 5-HTTLPR had decreased levels of well-being. Our results indicate that genetic and environmental factors have joint effects on well-being that are susceptible to profound changes across the life span.

FOG-2, a Heart- and Brain-Enriched Cofactor for GATA Transcription Factors

PubMed Central

Lu, Jian-rong; McKinsey, Timothy A.; Xu, Hongtao; Wang, Da-zhi; Richardson, James A.; Olson, Eric N.

1999-01-01

Members of the GATA family of zinc finger transcription factors have been shown to play important roles in the control of gene expression in a variety of cell types. GATA-1, -2, and -3 are expressed primarily in hematopoietic cell lineages and are required for proliferation and differentiation of multiple hematopoietic cell types, whereas GATA-4, -5, and -6 are expressed in the heart, where they activate cardiac muscle structural genes. Friend of GATA-1 (FOG) is a multitype zinc finger protein that interacts with GATA-1 and serves as a cofactor for GATA-1-mediated transcription. FOG is coexpressed with GATA-1 in developing erythroid and megakaryocyte cell lineages and cooperates with GATA-1 to control erythropoiesis. We describe a novel FOG-related factor, FOG-2, that is expressed predominantly in the developing and adult heart, brain, and testis. FOG-2 interacts with GATA factors, and interaction of GATA-4 and FOG-2 results in either synergistic activation or repression of GATA-dependent cardiac promoters, depending on the specific promoter and the cell type in which they are tested. The properties of FOG-2 suggest its involvement in the control of cardiac and neural gene expression by GATA transcription factors. PMID:10330188

Genetic Modification of the Relationship between Parental Rejection and Adolescent Alcohol Use.

PubMed

Stogner, John M; Gibson, Chris L

2016-07-01

Parenting practices are associated with adolescents' alcohol consumption, however not all youth respond similarly to challenging family situations and harsh environments. This study examines the relationship between perceived parental rejection and adolescent alcohol use, and specifically evaluates whether youth who possess greater genetic sensitivity to their environment are more susceptible to negative parental relationships. Analyzing data from the National Longitudinal Study of Adolescent Health, we estimated a series of regression models predicting alcohol use during adolescence. A multiplicative interaction term between parental rejection and a genetic index was constructed to evaluate this potential gene-environment interaction. Results from logistic regression analyses show a statistically significant gene-environment interaction predicting alcohol use. The relationship between parental rejection and alcohol use was moderated by the genetic index, indicating that adolescents possessing more 'risk alleles' for five candidate genes were affected more by stressful parental relationships. Feelings of parental rejection appear to influence the alcohol use decisions of youth, but they do not do so equally for all. Higher scores on the constructed genetic sensitivity measure are related to increased susceptibility to negative parental relationships. © The Author 2016. Medical Council on Alcohol and Oxford University Press. All rights reserved.

Anxiety and affective disorder comorbidity related to serotonin and other neurotransmitter systems: obsessive–compulsive disorder as an example of overlapping clinical and genetic heterogeneity

PubMed Central

Murphy, Dennis L.; Moya, Pablo R.; Fox, Meredith A.; Rubenstein, Liza M.; Wendland, Jens R.; Timpano, Kiara R.

2013-01-01

Individuals with obsessive–compulsive disorder (OCD) have also been shown to have comorbid lifetime diagnoses of major depressive disorder (MDD; rates greater than 70%), bipolar disorder (rates greater than 10%) and other anxiety disorders (e.g. panic disorder, post-traumatic stress disorder (PTSD)). In addition, overlap exists in some common genetic variants (e.g. the serotonin transporter gene (SLC6A4), the brain-derived neurotrophic factor (BDNF) gene), and rare variants in genes/chromosomal abnormalities (e.g. the 22q11 microdeletion syndrome) found across the affective/anxiety disorder spectrums. OCD has been proposed as a possible independent entity for DSM-5, but by others thought best retained as an anxiety disorder subtype (its current designation in DSM-IV), and yet by others considered best in the affective disorder spectrum. This review focuses on OCD, a well-studied but still puzzling heterogeneous disorder, regarding alterations in serotonergic, dopaminergic and glutamatergic neurotransmission in addition to other systems involved, and how related genes may be involved in the comorbidity of anxiety and affective disorders. OCD resembles disorders such as depression, in which gene × gene interactions, gene × environment interactions and stress elements coalesce to yield OC symptoms and, in some individuals, full-blown OCD with multiple comorbid disorders. PMID:23440468

Balancing Selection at the Tomato RCR3 Guardee Gene Family Maintains Variation in Strength of Pathogen Defense

PubMed Central

Hörger, Anja C.; Ilyas, Muhammad; Stephan, Wolfgang; Tellier, Aurélien; van der Hoorn, Renier A. L.; Rose, Laura E.

2012-01-01

Coevolution between hosts and pathogens is thought to occur between interacting molecules of both species. This results in the maintenance of genetic diversity at pathogen antigens (or so-called effectors) and host resistance genes such as the major histocompatibility complex (MHC) in mammals or resistance (R) genes in plants. In plant–pathogen interactions, the current paradigm posits that a specific defense response is activated upon recognition of pathogen effectors via interaction with their corresponding R proteins. According to the “Guard-Hypothesis,” R proteins (the “guards”) can sense modification of target molecules in the host (the “guardees”) by pathogen effectors and subsequently trigger the defense response. Multiple studies have reported high genetic diversity at R genes maintained by balancing selection. In contrast, little is known about the evolutionary mechanisms shaping the guardee, which may be subject to contrasting evolutionary forces. Here we show that the evolution of the guardee RCR3 is characterized by gene duplication, frequent gene conversion, and balancing selection in the wild tomato species Solanum peruvianum. Investigating the functional characteristics of 54 natural variants through in vitro and in planta assays, we detected differences in recognition of the pathogen effector through interaction with the guardee, as well as substantial variation in the strength of the defense response. This variation is maintained by balancing selection at each copy of the RCR3 gene. Our analyses pinpoint three amino acid polymorphisms with key functional consequences for the coevolution between the guardee (RCR3) and its guard (Cf-2). We conclude that, in addition to coevolution at the “guardee-effector” interface for pathogen recognition, natural selection acts on the “guard-guardee” interface. Guardee evolution may be governed by a counterbalance between improved activation in the presence and prevention of auto-immune responses in the absence of the corresponding pathogen. PMID:22829777

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

PubMed

Carvalho, Claudia M B; Vasanth, Shivakumar; Shinawi, Marwan; Russell, Chad; Ramocki, Melissa B; Brown, Chester W; Graakjaer, Jesper; Skytte, Anne-Bine; Vianna-Morgante, Angela M; Krepischi, Ana C V; Patel, Gayle S; Immken, LaDonna; Aleck, Kyrieckos; Lim, Cynthia; Cheung, Sau Wai; Rosenberg, Carla; Katsanis, Nicholas; Lupski, James R

2014-11-06

The 17p13.1 microdeletion syndrome is a recently described genomic disorder with a core clinical phenotype of intellectual disability, poor to absent speech, dysmorphic features, and a constellation of more variable clinical features, most prominently microcephaly. We identified five subjects 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 in zebrafish embryos revealed a complex genetic architecture: dosage perturbation of four genes (ASGR1, ACADVL, DVL2, and GABARAP) impeded neurodevelopment and decreased dosage of the same loci caused a reduced mitotic index in vitro. Moreover, epistatic analyses in vivo showed that dosage perturbations of discrete gene pairings induce microcephaly. Taken together, these studies support a model in which concomitant dosage perturbation of multiple genes within the CNV drive the microcephaly and possibly other neurodevelopmental phenotypes associated with rearrangements in the 17p13.1 SRO. Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Discovering perturbation of modular structure in HIV progression by integrating multiple data sources through non-negative matrix factorization.

PubMed

Ray, Sumanta; Maulik, Ujjwal

2016-12-20

Detecting perturbation in modular structure during HIV-1 disease progression is an important step to understand stage specific infection pattern of HIV-1 virus in human cell. In this article, we proposed a novel methodology on integration of multiple biological information to identify such disruption in human gene module during different stages of HIV-1 infection. We integrate three different biological information: gene expression information, protein-protein interaction information and gene ontology information in single gene meta-module, through non negative matrix factorization (NMF). As the identified metamodules inherit those information so, detecting perturbation of these, reflects the changes in expression pattern, in PPI structure and in functional similarity of genes during the infection progression. To integrate modules of different data sources into strong meta-modules, NMF based clustering is utilized here. Perturbation in meta-modular structure is identified by investigating the topological and intramodular properties and putting rank to those meta-modules using a rank aggregation algorithm. We have also analyzed the preservation structure of significant GO terms in which the human proteins of the meta-modules participate. Moreover, we have performed an analysis to show the change of coregulation pattern of identified transcription factors (TFs) over the HIV progression stages.

Quantitative trait locus mapping of drought and salt tolerance in as introgressed recombinant inbred line population of upland cotton under the greenhouse and feild conditions

USDA-ARS?s Scientific Manuscript database

Drought and salt tolerances are complex traits and controlled by multiple genes, environmental factors and their interactions. Drought and salt stresses can result in more than 50% yield loss in Upland cotton (Gossypium hirsutum L.). G. barbadense L. (the source of Pima cotton) carries desirable tra...

A reproducible approach to high-throughput biological data acquisition and integration

PubMed Central

Rahnavard, Gholamali; Waldron, Levi; McIver, Lauren; Shafquat, Afrah; Franzosa, Eric A.; Miropolsky, Larissa; Sweeney, Christopher

2015-01-01

Modern biological research requires rapid, complex, and reproducible integration of multiple experimental results generated both internally and externally (e.g., from public repositories). Although large systematic meta-analyses are among the most effective approaches both for clinical biomarker discovery and for computational inference of biomolecular mechanisms, identifying, acquiring, and integrating relevant experimental results from multiple sources for a given study can be time-consuming and error-prone. To enable efficient and reproducible integration of diverse experimental results, we developed a novel approach for standardized acquisition and analysis of high-throughput and heterogeneous biological data. This allowed, first, novel biomolecular network reconstruction in human prostate cancer, which correctly recovered and extended the NFκB signaling pathway. Next, we investigated host-microbiome interactions. In less than an hour of analysis time, the system retrieved data and integrated six germ-free murine intestinal gene expression datasets to identify the genes most influenced by the gut microbiota, which comprised a set of immune-response and carbohydrate metabolism processes. Finally, we constructed integrated functional interaction networks to compare connectivity of peptide secretion pathways in the model organisms Escherichia coli, Bacillus subtilis, and Pseudomonas aeruginosa. PMID:26157642

Systems Level Analysis of Systemic Sclerosis Shows a Network of Immune and Profibrotic Pathways Connected with Genetic Polymorphisms

PubMed Central

Mahoney, J. Matthew; Taroni, Jaclyn; Martyanov, Viktor; Wood, Tammara A.; Greene, Casey S.; Pioli, Patricia A.; Hinchcliff, Monique E.; Whitfield, Michael L.

2015-01-01

Systemic sclerosis (SSc) is a rare systemic autoimmune disease characterized by skin and organ fibrosis. The pathogenesis of SSc and its progression are poorly understood. The SSc intrinsic gene expression subsets (inflammatory, fibroproliferative, normal-like, and limited) are observed in multiple clinical cohorts of patients with SSc. Analysis of longitudinal skin biopsies suggests that a patient's subset assignment is stable over 6–12 months. Genetically, SSc is multi-factorial with many genetic risk loci for SSc generally and for specific clinical manifestations. Here we identify the genes consistently associated with the intrinsic subsets across three independent cohorts, show the relationship between these genes using a gene-gene interaction network, and place the genetic risk loci in the context of the intrinsic subsets. To identify gene expression modules common to three independent datasets from three different clinical centers, we developed a consensus clustering procedure based on mutual information of partitions, an information theory concept, and performed a meta-analysis of these genome-wide gene expression datasets. We created a gene-gene interaction network of the conserved molecular features across the intrinsic subsets and analyzed their connections with SSc-associated genetic polymorphisms. The network is composed of distinct, but interconnected, components related to interferon activation, M2 macrophages, adaptive immunity, extracellular matrix remodeling, and cell proliferation. The network shows extensive connections between the inflammatory- and fibroproliferative-specific genes. The network also shows connections between these subset-specific genes and 30 SSc-associated polymorphic genes including STAT4, BLK, IRF7, NOTCH4, PLAUR, CSK, IRAK1, and several human leukocyte antigen (HLA) genes. Our analyses suggest that the gene expression changes underlying the SSc subsets may be long-lived, but mechanistically interconnected and related to a patients underlying genetic risk. PMID:25569146

Kcne2 Deletion Creates a Multisystem Syndrome Predisposing to Sudden Cardiac Death

PubMed Central

Hu, Zhaoyang; Kant, Ritu; Anand, Marie; King, Elizabeth C.; Krogh-Madsen, Trine; Christini, David J.; Abbott, Geoffrey W.

2014-01-01

Background Sudden cardiac death (SCD) is the leading global cause of mortality, exhibiting increased incidence in diabetics. Ion channel gene perturbations provide a well-established ventricular arrhythmogenic substrate for SCD. However, most arrhythmia susceptibility genes - including the KCNE2 K+ channel β subunit - are expressed in multiple tissues, suggesting potential multiplex SCD substrates. Methods and Results Using “whole transcript” transcriptomics, we uncovered cardiac angiotensinogen upregulation and remodeling of cardiac angiotensinogen interaction networks in P21 Kcne2−/− mouse pups, and adrenal remodeling consistent with metabolic syndrome in adult Kcne2−/− mice. This led to the discovery that Kcne2 disruption causes multiple acknowledged SCD substrates of extracardiac origin: diabetes, hypercholesterolemia, hyperkalemia, anemia and elevated angiotensin II. Kcne2 deletion was also prerequisite for aging-dependent QT prolongation, ventricular fibrillation and SCD immediately following transient ischemia, and fasting-dependent hypoglycemia, myocardial ischemia and atrioventricular block. Conclusions Disruption of a single, widely expressed arrhythmia susceptibility gene can generate a multisystem syndrome comprising manifold electrical and systemic substrates and triggers of SCD. This paradigm is expected to apply to other arrhythmia susceptibility genes, the majority of which encode ubiquitously expressed ion channel subunits or regulatory proteins. PMID:24403551

Differentiation and injury-repair signals modulate the interaction of E2F and pRB proteins with novel target genes in keratinocytes.

PubMed

Chang, Wing Y; Andrews, Joseph; Carter, David E; Dagnino, Lina

2006-08-01

E2F transcription factors are central to epidermal morphogenesis and regeneration after injury. The precise nature of E2F target genes involved in epidermal formation and repair has yet to be determined. Identification of these genes is essential to understand how E2F proteins regulate fundamental aspects of epidermal homeostasis and transformation. We have conducted a genome-wide screen using CpG island microarray analysis to identify novel promoters bound by E2F3 and E2F5 in human keratinocytes. We further characterized several of these genes, and determined that multiple E2F and retinoblastoma (pRb) family proteins associate with them in exponentially proliferating cells. We also assessed the effect on E2F and pRb binding to those genes in response to differentiation induced by bone morphogenetic protein-6 (BMP-6), or to activation of repair mechanisms induced by transforming growth factor-beta (TGF-beta). These studies demonstrate promoter- and cytokine-specific changes in binding profiles of E2F and/or pRb family proteins. For example, E2F1, 3, 4 and p107 were recruited to the N-myc promoter in cells treated with BMP-6, whereas E2F1, 3, 4, 5, p107 and p130 were bound to this promoter in the presence of TGF-beta. Functionally, these different interactions resulted in transcriptional repression by BMP-6 and TGF-beta of the N-myc gene, via mechanisms that involved E2F binding to the promoter and association with pRb-family proteins. Thus, multiple combinations of E2F and pRb family proteins may associate with and transcriptionally regulate a given target promoter in response to differentiation and injury-repair stimuli in epidermal keratinocytes.

The E3 ligase Ubr3 regulates Usher syndrome and MYH9 disorder proteins in the auditory organs of Drosophila and mammals.

PubMed

Li, Tongchao; Giagtzoglou, Nikolaos; Eberl, Daniel F; Jaiswal, Sonal Nagarkar; Cai, Tiantian; Godt, Dorothea; Groves, Andrew K; Bellen, Hugo J

2016-06-22

Myosins play essential roles in the development and function of auditory organs and multiple myosin genes are associated with hereditary forms of deafness. Using a forward genetic screen in Drosophila, we identified an E3 ligase, Ubr3, as an essential gene for auditory organ development. Ubr3 negatively regulates the mono-ubiquitination of non-muscle Myosin II, a protein associated with hearing loss in humans. The mono-ubiquitination of Myosin II promotes its physical interaction with Myosin VIIa, a protein responsible for Usher syndrome type IB. We show that ubr3 mutants phenocopy pathogenic variants of Myosin II and that Ubr3 interacts genetically and physically with three Usher syndrome proteins. The interactions between Myosin VIIa and Myosin IIa are conserved in the mammalian cochlea and in human retinal pigment epithelium cells. Our work reveals a novel mechanism that regulates protein complexes affected in two forms of syndromic deafness and suggests a molecular function for Myosin IIa in auditory organs.

Co-transcriptional nuclear actin dynamics

PubMed Central

Percipalle, Piergiorgio

2013-01-01

Actin is a key player for nuclear structure and function regulating both chromosome organization and gene activity. In the cell nucleus actin interacts with many different proteins. Among these proteins several studies have identified classical nuclear factors involved in chromatin structure and function, transcription and RNA processing as well as proteins that are normally involved in controlling the actin cytoskeleton. These discoveries have raised the possibility that nuclear actin performs its multi task activities through tight interactions with different sets of proteins. This high degree of promiscuity in the spectrum of protein-to-protein interactions correlates well with the conformational plasticity of actin and the ability to undergo regulated changes in its polymerization states. Several of the factors involved in controlling head-to-tail actin polymerization have been shown to be in the nucleus where they seem to regulate gene activity. By focusing on the multiple tasks performed by actin and actin-binding proteins, possible models of how actin dynamics controls the different phases of the RNA polymerase II transcription cycle are being identified. PMID:23138849

Tumor Cell Gene Expression Changes Following Short-term In vivo Exposure to Single Agent Chemotherapeutics are Related to Survival in Multiple Myeloma

PubMed Central

Burington, Bart; Barlogie, Bart; Zhan, Fenghuang; Crowley, John; Shaughnessy, John D.

2013-01-01

Changes in global gene expression patterns in tumor cells following in vivo therapy may vary by treatment and provide added or synergistic prognostic power over pretherapy gene expression profiles (GEP). This molecular readout of drug-cell interaction may also point to mechanisms of action/resistance. In newly diagnosed patients with multiple myeloma (MM), microarray data were obtained on tumor cells prior to and 48 hours after in vivo treatment using dexamethasone (n = 45) or thalidomide (n = 42); in the case of relapsed MM, microarray data were obtained prior to (n = 36) and after (n = 19) lenalidomide administration. Dexamethasone and thalidomide induced both common and unique GEP changes in tumor cells. Combined baseline and 48-hour changes in GEP in a subset of genes, many related to oxidative stress and cytoskeletal dynamics, were predictive of outcome in newly diagnosed MM patients receiving tandem transplants. Thalidomide-altered genes also changed following lenalidomide exposure and predicted event-free and overall survival in relapsed patients receiving lenalidomide as a single agent. Combined with baseline molecular features, changes in GEP following short-term single-agent exposure may help guide treatment decisions for patients with MM. Genes whose drug-altered expression were found to be related to survival may point to molecular switches related to response and/or resistance to different classes of drugs. PMID:18676754

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

PubMed

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

2018-04-01

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

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

PubMed

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.

Genetic variability of VEGF pathway genes in six randomized phase III trials assessing the addition of bevacizumab to standard therapy.

PubMed

de Haas, Sanne; Delmar, Paul; Bansal, Aruna T; Moisse, Matthieu; Miles, David W; Leighl, Natasha; Escudier, Bernard; Van Cutsem, Eric; Carmeliet, Peter; Scherer, Stefan J; Pallaud, Celine; Lambrechts, Diether

2014-10-01

Despite extensive translational research, no validated biomarkers predictive of bevacizumab treatment outcome have been identified. We performed a meta-analysis of individual patient data from six randomized phase III trials in colorectal, pancreatic, lung, renal, breast, and gastric cancer to explore the potential relationships between 195 common genetic variants in the vascular endothelial growth factor (VEGF) pathway and bevacizumab treatment outcome. The analysis included 1,402 patients (716 bevacizumab-treated and 686 placebo-treated). Twenty variants were associated (P < 0.05) with progression-free survival (PFS) in bevacizumab-treated patients. Of these, 4 variants in EPAS1 survived correction for multiple testing (q < 0.05). Genotype-by-treatment interaction tests revealed that, across these 20 variants, 3 variants in VEGF-C (rs12510099), EPAS1 (rs4953344), and IL8RA (rs2234671) were potentially predictive (P < 0.05), but not resistant to multiple testing (q > 0.05). A weak genotype-by-treatment interaction effect was also observed for rs699946 in VEGF-A, whereas Bayesian genewise analysis revealed that genetic variability in VHL was associated with PFS in the bevacizumab arm (q < 0.05). Variants in VEGF-A, EPAS1, and VHL were located in expression quantitative loci derived from lymphoblastoid cell lines, indicating that they affect the expression levels of their respective gene. This large genetic analysis suggests that variants in VEGF-A, EPAS1, IL8RA, VHL, and VEGF-C have potential value in predicting bevacizumab treatment outcome across tumor types. Although these associations did not survive correction for multiple testing in a genotype-by-interaction analysis, they are among the strongest predictive effects reported to date for genetic variants and bevacizumab efficacy.

Systematic analysis of molecular mechanisms for HCC metastasis via text mining approach.

PubMed

Zhen, Cheng; Zhu, Caizhong; Chen, Haoyang; Xiong, Yiru; Tan, Junyuan; Chen, Dong; Li, Jin

2017-02-21

To systematically explore the molecular mechanism for hepatocellular carcinoma (HCC) metastasis and identify regulatory genes with text mining methods. Genes with highest frequencies and significant pathways related to HCC metastasis were listed. A handful of proteins such as EGFR, MDM2, TP53 and APP, were identified as hub nodes in PPI (protein-protein interaction) network. Compared with unique genes for HBV-HCCs, genes particular to HCV-HCCs were less, but may participate in more extensive signaling processes. VEGFA, PI3KCA, MAPK1, MMP9 and other genes may play important roles in multiple phenotypes of metastasis. Genes in abstracts of HCC-metastasis literatures were identified. Word frequency analysis, KEGG pathway and PPI network analysis were performed. Then co-occurrence analysis between genes and metastasis-related phenotypes were carried out. Text mining is effective for revealing potential regulators or pathways, but the purpose of it should be specific, and the combination of various methods will be more useful.

Ankyrin-repeat containing proteins of microbes: a conserved structure with functional diversity

PubMed Central

Al-Khodor, Souhaila; Price, Christopher T.; Kalia, Awdhesh; Kwaik, Yousef Abu

2009-01-01

Summary The ankyrin repeat (ANK) is the most common protein-protein interaction motif in nature and predominantly found in eukaryotic proteins. The genome sequencing of various pathogenic or symbiotic bacteria and eukaryotic viruses identified numerous genes encoding ANK-containing proteins that were proposed to have been acquired from eukaryotes by horizontal gene transfer. However, the recent discovery of additional ANK-containing proteins encoded in the genomes of archaea and free-living bacteria suggests either a more ancient origin of the ANK motif or multiple convergent evolution events. Many bacterial pathogens employ various types of secretion systems to deliver ANK-containing proteins into eukaryotic cells where they mimic or manipulate various host functions. Understanding the molecular and biochemical functions of this family of proteins will enhance our understanding of important host-microbe interactions. PMID:19962898

Genes Interacting with Occupational Exposures to Low Molecular Weight Agents and Irritants on Adult-Onset Asthma in Three European Studies

PubMed Central

Rava, Marta; Ahmed, Ismail; Kogevinas, Manolis; Le Moual, Nicole; Bouzigon, Emmanuelle; Curjuric, Ivan; Dizier, Marie-Hélène; Dumas, Orianne; Gonzalez, Juan R.; Imboden, Medea; Mehta, Amar J.; Tubert-Bitter, Pascale; Zock, Jan-Paul; Jarvis, Deborah; Probst-Hensch, Nicole M.; Demenais, Florence; Nadif, Rachel

2016-01-01

Background: The biological mechanisms by which cleaning products and disinfectants—an emerging risk factor—affect respiratory health remain incompletely evaluated. Studying genes by environment interactions (G × E) may help identify new genes related to adult-onset asthma. Objectives: We identified interactions between genetic polymorphisms of a large set of genes involved in the response to oxidative stress and occupational exposures to low molecular weight (LMW) agents or irritants on adult-onset asthma. Methods: Our data came from three large European cohorts: Epidemiological Family-based Study of the Genetics and Environment of Asthma (EGEA), Swiss Cohort Study on Air Pollution and Lung and Heart Disease in Adults (SAPALDIA), and European Community Respiratory Health Survey in Adults (ECRHS). A candidate pathway–based strategy identified 163 genes involved in the response to oxidative stress and potentially related to exposures to LMW agents/irritants. Occupational exposures were evaluated using an asthma job-exposure matrix and job-specific questionnaires for cleaners and healthcare workers. Logistic regression models were used to detect G × E interactions, adjusted for age, sex, and population ancestry, in 2,599 adults (mean age, 47 years; 60% women, 36% exposed, 18% asthmatics). p-Values were corrected for multiple comparisons. Results: Ever exposure to LMW agents/irritants was associated with current adult-onset asthma [OR = 1.28 (95% CI: 1.04, 1.58)]. Eight single nucleotide polymorphism (SNP) by exposure interactions at five loci were found at p < 0.005: PLA2G4A (rs932476, chromosome 1), near PLA2R1 (rs2667026, chromosome 2), near RELA (rs931127, rs7949980, chromosome 11), PRKD1 (rs1958980, rs11847351, rs1958987, chromosome 14), and PRKCA (rs6504453, chromosome 17). Results were consistent across the three studies and after accounting for smoking. Conclusions: Using a pathway-based selection process, we identified novel genes potentially involved in adult asthma by interaction with occupational exposure. These genes play a role in the NF-κB pathway, which is involved in inflammation. Citation: Rava M, Ahmed I, Kogevinas M, Le Moual N, Bouzigon E, Curjuric I, Dizier MH, Dumas O, Gonzalez JR, Imboden M, Mehta AJ, Tubert-Bitter P, Zock JP, Jarvis D, Probst-Hensch NM, Demenais F, Nadif R. 2017. Genes interacting with occupational exposures to low molecular weight agents and irritants on adult-onset asthma in three European studies. Environ Health Perspect 125:207–214; http://dx.doi.org/10.1289/EHP376 PMID:27504716

Genome-wide analysis of the interaction between the endosymbiotic bacterium Wolbachia and its Drosophila host.

PubMed

Xi, Zhiyong; Gavotte, Laurent; Xie, Yan; Dobson, Stephen L

2008-01-02

Intracellular Wolbachia bacteria are obligate, maternally-inherited, endosymbionts found frequently in insects and other invertebrates. The success of Wolbachia can be attributed in part to an ability to alter host reproduction via mechanisms including cytoplasmic incompatibility (CI), parthenogenesis, feminization and male killing. Despite substantial scientific effort, the molecular mechanisms underlying the Wolbachia/host interaction are unknown. Here, an in vitro Wolbachia infection was generated in the Drosophila S2 cell line, and transcription profiles of infected and uninfected cells were compared by microarray. Differentially-expressed patterns related to reproduction, immune response and heat stress response are observed, including multiple genes that have been previously reported to be involved in the Wolbachia/host interaction. Subsequent in vivo characterization of differentially-expressed products in gonads demonstrates that Angiotensin Converting Enzyme (Ance) varies between Wolbachia infected and uninfected flies and that the variation occurs in a sex-specific manner. Consistent with expectations for the conserved CI mechanism, the observed Ance expression pattern is repeatable in different Drosophila species and with different Wolbachia types. To examine Ance involvement in the CI phenotype, compatible and incompatible crosses of Ance mutant flies were conducted. Significant differences are observed in the egg hatch rate resulting from incompatible crosses, providing support for additional experiments examining for an interaction of Ance with the CI mechanism. Wolbachia infection is shown to affect the expression of multiple host genes, including Ance. Evidence for potential Ance involvement in the CI mechanism is described, including the prior report of Ance in spermatid differentiation, Wolbachia-induced sex-specific effects on Ance expression and an Ance mutation effect on CI levels. The results support the use of Wolbachia infected cell cultures as an appropriate model for predicting in vivo host/Wolbachia interactions.

Genome-wide analysis of the interaction between the endosymbiotic bacterium Wolbachia and its Drosophila host

PubMed Central

Xi, Zhiyong; Gavotte, Laurent; Xie, Yan; Dobson, Stephen L

2008-01-01

Background Intracellular Wolbachia bacteria are obligate, maternally-inherited, endosymbionts found frequently in insects and other invertebrates. The success of Wolbachia can be attributed in part to an ability to alter host reproduction via mechanisms including cytoplasmic incompatibility (CI), parthenogenesis, feminization and male killing. Despite substantial scientific effort, the molecular mechanisms underlying the Wolbachia/host interaction are unknown. Results Here, an in vitro Wolbachia infection was generated in the Drosophila S2 cell line, and transcription profiles of infected and uninfected cells were compared by microarray. Differentially-expressed patterns related to reproduction, immune response and heat stress response are observed, including multiple genes that have been previously reported to be involved in the Wolbachia/host interaction. Subsequent in vivo characterization of differentially-expressed products in gonads demonstrates that Angiotensin Converting Enzyme (Ance) varies between Wolbachia infected and uninfected flies and that the variation occurs in a sex-specific manner. Consistent with expectations for the conserved CI mechanism, the observed Ance expression pattern is repeatable in different Drosophila species and with different Wolbachia types. To examine Ance involvement in the CI phenotype, compatible and incompatible crosses of Ance mutant flies were conducted. Significant differences are observed in the egg hatch rate resulting from incompatible crosses, providing support for additional experiments examining for an interaction of Ance with the CI mechanism. Conclusion Wolbachia infection is shown to affect the expression of multiple host genes, including Ance. Evidence for potential Ance involvement in the CI mechanism is described, including the prior report of Ance in spermatid differentiation, Wolbachia-induced sex-specific effects on Ance expression and an Ance mutation effect on CI levels. The results support the use of Wolbachia infected cell cultures as an appropriate model for predicting in vivo host/Wolbachia interactions. PMID:18171476

Transcription co-activator SAYP mediates the action of STAT activator

PubMed Central

Panov, Vladislav V.; Kuzmina, Julia L.; Doronin, Semen A.; Kopantseva, Marina R.; Nabirochkina, Elena N.; Georgieva, Sofia G.; Vorobyeva, Nadezhda E.; Shidlovskii, Yulii V.

2012-01-01

Jak/STAT is an important signaling pathway mediating multiple events in development. We describe participation of metazoan co-activator SAYP/PHF10 in this pathway downstream of STAT. The latter, via its activation domain, interacts with the conserved core of SAYP. STAT is associated with the SAYP-containing co-activator complex BTFly and recruits BTFly onto genes. SAYP is necessary for stimulating STAT-driven transcription of numerous genes. Mutation of SAYP leads to maldevelopments similar to those observed in STAT mutants. Thus, SAYP is a novel co-activator mediating the action of STAT. PMID:22123744

Polo boxes and Cut23 (Apc8) mediate an interaction between polo kinase and the anaphase-promoting complex for fission yeast mitosis

PubMed Central

May, Karen M.; Reynolds, Nicola; Cullen, C. Fiona; Yanagida, Mitsuhiro; Ohkura, Hiroyuki

2002-01-01

The fission yeast plo1 + gene encodes a polo-like kinase, a member of a conserved family of kinases which play multiple roles during the cell cycle. We show that Plo1 kinase physically interacts with the anaphase-promoting complex (APC)/cyclosome through the noncatalytic domain of Plo1 and the tetratricopeptide repeat domain of the subunit, Cut23. A new cut23 mutation, which specifically disrupts the interaction with Plo1, results in a metaphase arrest. This arrest can be rescued by high expression of Plo1 kinase. We suggest that this physical interaction is crucial for mitotic progression by targeting polo kinase activity toward the APC. PMID:11777938

-A curated transcriptomic dataset collection relevant to embryonic development associated with in vitro fertilization in healthy individuals and patients with polycystic ovary syndrome.

PubMed

Mackeh, Rafah; Boughorbel, Sabri; Chaussabel, Damien; Kino, Tomoshige

2017-01-01

The collection of large-scale datasets available in public repositories is rapidly growing and providing opportunities to identify and fill gaps in different fields of biomedical research. However, users of these datasets should be able to selectively browse datasets related to their field of interest. Here we made available a collection of transcriptome datasets related to human follicular cells from normal individuals or patients with polycystic ovary syndrome, in the process of their development, during in vitro fertilization. After RNA-seq dataset exclusion and careful selection based on study description and sample information, 12 datasets, encompassing a total of 85 unique transcriptome profiles, were identified in NCBI Gene Expression Omnibus and uploaded to the Gene Expression Browser (GXB), a web application specifically designed for interactive query and visualization of integrated large-scale data. Once annotated in GXB, multiple sample grouping has been made in order to create rank lists to allow easy data interpretation and comparison. The GXB tool also allows the users to browse a single gene across multiple projects to evaluate its expression profiles in multiple biological systems/conditions in a web-based customized graphical views. The curated dataset is accessible at the following link: http://ivf.gxbsidra.org/dm3/landing.gsp.

­A curated transcriptomic dataset collection relevant to embryonic development associated with in vitro fertilization in healthy individuals and patients with polycystic ovary syndrome

PubMed Central

Mackeh, Rafah; Boughorbel, Sabri; Chaussabel, Damien; Kino, Tomoshige

2017-01-01

The collection of large-scale datasets available in public repositories is rapidly growing and providing opportunities to identify and fill gaps in different fields of biomedical research. However, users of these datasets should be able to selectively browse datasets related to their field of interest. Here we made available a collection of transcriptome datasets related to human follicular cells from normal individuals or patients with polycystic ovary syndrome, in the process of their development, during in vitro fertilization. After RNA-seq dataset exclusion and careful selection based on study description and sample information, 12 datasets, encompassing a total of 85 unique transcriptome profiles, were identified in NCBI Gene Expression Omnibus and uploaded to the Gene Expression Browser (GXB), a web application specifically designed for interactive query and visualization of integrated large-scale data. Once annotated in GXB, multiple sample grouping has been made in order to create rank lists to allow easy data interpretation and comparison. The GXB tool also allows the users to browse a single gene across multiple projects to evaluate its expression profiles in multiple biological systems/conditions in a web-based customized graphical views. The curated dataset is accessible at the following link: http://ivf.gxbsidra.org/dm3/landing.gsp. PMID:28413616

Functional analysis of U1-70K interacting SR proteins in pre-mRNA splicing in Arabidopsis

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

A.S.N. Reddy

Proteins of a serine/arginine-rich (SR) family are part of the spliceosome and are implicated in both constitutive and alternative splicing of pre-mRNAs. With the funding from DOE we have been studying alternative of splicing of genes encoding serine/arginine-rich (SR) proteins and the roles of SR proteins that interact with U1-70K in regulating basic and alternative splicing. Alternative splicing of pre-mRNAs of Arabidopsis serine/arginine-rich proteins and its regulation by hormones and stresses: We analyzed the splicing of all 19 Arabidopsis genes in different tissues, during different seedling stages and in response to various hormonal and stress treatments. Remarkably, about 90 differentmore » transcripts are produced from 15 SR genes, thereby increasing the transcriptome complexity of SR genes by about five fold. Using the RNA isolated from polysomes we have shown that most of the splice variants are recruited for translation. Alternative splicing of some SR genes is controlled in a developmental and tissue-specific manner (Palusa et al., 2007). Interestingly, among the various hormones and abiotic stresses tested, temperature stress (cold and heat) and ultraviolet light dramatically altered alternative splicing of pre-mRNAs of several SR genes whereas hormones altered the splicing of only two SR genes (Palusa et al., 2007). Localization and dynamics of a novel serine/arginine-rich protein that interacts with U1-70K: We analyzed the intranuclear movement of SR45 fused to GFP by fluorescence recovery after photobleaching (FRAP) and fluorescence loss in photobleaching (FLIP). We demonstrate that the movement of GFP-SR45 is ATP-dependent. Interestingly, inhibition of transcription or phosphorylation slowed the mobility of GFP-SR45 (Ali et al., 2006). Our studies have revealed that the nuclear localization signals are located in arg/ser-rich domains (RS) 1 and 2, whereas the speckle targeting signals are exclusively present in RS2 (Ali et al., 2006). The regulation of SR45 mobility by ATP and a transcriptional inhibitor is in contrast to the mobility of SR family splicing factors in animals and suggests fundamental differences in the movement of plant and animals splicing factors. In vivo interaction of U170K with SR45: To analyze the interaction of U170K with SR45, we expressed these proteins fused to RFP and GFP respectively, in protoplasts. Both the reporters co-localized to the same subnuclear domains. To determine direct interaction of these proteins, we fused full-length U170K to one part of split YFP and full-length or truncated version of SR45 to the second half of split YFP. Coexpession of these split YFP constructs resulted in reconstitution of YFP in speckles, suggesting direction interaction of these proteins in vivo (Ali et al., 2008). SR45 is a Novel Plant-Specific Splicing Factor and is Involved in Regulating Multiple Developmental Processes: Using an in vitro splicing complementation assay, we showed that SR45 is an essential splicing factor. The sr45-1 mutant exhibited a number of developmental abnormalities. Further analysis of flowering time has shown that the autonomous pathway of flowering is affected in the mutant. Expression analysis of several flowering genes has revealed that FLC, a key flowering repressor, is up-regulated in the SR45 mutant. Further, alternative splicing pattern of several other SR genes was altered in the sr45-1 mutant in a tissue-specific manner. Hence, the observed pleiotropic effects on various aspects of development are likely due to altered level of SR protein isoforms, which in turn regulate the splicing of other pre-mRNAs. Expression of wild-type SR45 in the mutant complemented the phenotypic defects and changes in alternative splicing of SR genes. SR45 thus is a novel plant-specific splicing factor and plays a crucial role in multiple developmental processes.« less

KAP1 promotes proliferation and metastatic progression of breast cancer cells.

PubMed

Addison, Joseph B; Koontz, Colton; Fugett, James H; Creighton, Chad J; Chen, Dongquan; Farrugia, Mark K; Padon, Renata R; Voronkova, Maria A; McLaughlin, Sarah L; Livengood, Ryan H; Lin, Chen-Chung; Ruppert, J Michael; Pugacheva, Elena N; Ivanov, Alexey V

2015-01-15

KAP1 (TRIM28) is a transcriptional regulator in embryonic development that controls stem cell self-renewal, chromatin organization, and the DNA damage response, acting as an essential corepressor for KRAB family zinc finger proteins (KRAB-ZNF). To gain insight into the function of this large gene family, we developed an antibody that recognizes the conserved zinc fingers linker region (ZnFL) in multiple KRAB-ZNF. Here, we report that the expression of many KRAB-ZNF along with active SUMOlyated KAP1 is elevated widely in human breast cancers. KAP1 silencing in breast cancer cells reduced proliferation and inhibited the growth and metastasis of tumor xenografts. Conversely, KAP1 overexpression stimulated cell proliferation and tumor growth. In cells where KAP1 was silenced, we identified multiple downregulated genes linked to tumor progression and metastasis, including EREG/epiregulin, PTGS2/COX2, MMP1, MMP2, and CD44, along with downregulation of multiple KRAB-ZNF proteins. KAP1-dependent stabilization of KRAB-ZNF required direct interactions with KAP1. Together, our results show that KAP1-mediated stimulation of multiple KRAB-ZNF contributes to the growth and metastasis of breast cancer. ©2014 American Association for Cancer Research.

Identification of SNPs associated with variola virus virulence.

PubMed

Hoen, Anne Gatewood; Gardner, Shea N; Moore, Jason H

2013-02-14

Decades after the eradication of smallpox, its etiological agent, variola virus (VARV), remains a threat as a potential bioweapon. Outbreaks of smallpox around the time of the global eradication effort exhibited variable case fatality rates (CFRs), likely attributable in part to complex viral genetic determinants of smallpox virulence. We aimed to identify genome-wide single nucleotide polymorphisms associated with CFR. We evaluated unadjusted and outbreak geographic location-adjusted models of single SNPs and two- and three-way interactions between SNPs. Using the data mining approach multifactor dimensionality reduction (MDR), we identified five VARV SNPs in models significantly associated with CFR. The top performing unadjusted model and adjusted models both revealed the same two-way gene-gene interaction. We discuss the biological plausibility of the influence of the SNPs identified these and other significant models on the strain-specific virulence of VARV. We have identified genetic loci in the VARV genome that are statistically associated with VARV virulence as measured by CFR. While our ability to infer a causal relationship between the specific SNPs identified in our analysis and VARV virulence is limited, our results suggest that smallpox severity is in part associated with VARV strain variation and that VARV virulence may be determined by multiple genetic loci. This study represents the first application of MDR to the identification of pathogen gene-gene interactions for predicting infectious disease outbreak severity.

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

PubMed

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

2018-03-01

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

Identification of SNPs associated with variola virus virulence

PubMed Central

2013-01-01

Background Decades after the eradication of smallpox, its etiological agent, variola virus (VARV), remains a threat as a potential bioweapon. Outbreaks of smallpox around the time of the global eradication effort exhibited variable case fatality rates (CFRs), likely attributable in part to complex viral genetic determinants of smallpox virulence. We aimed to identify genome-wide single nucleotide polymorphisms associated with CFR. We evaluated unadjusted and outbreak geographic location-adjusted models of single SNPs and two- and three-way interactions between SNPs. Findings Using the data mining approach multifactor dimensionality reduction (MDR), we identified five VARV SNPs in models significantly associated with CFR. The top performing unadjusted model and adjusted models both revealed the same two-way gene-gene interaction. We discuss the biological plausibility of the influence of the SNPs identified these and other significant models on the strain-specific virulence of VARV. Conclusions We have identified genetic loci in the VARV genome that are statistically associated with VARV virulence as measured by CFR. While our ability to infer a causal relationship between the specific SNPs identified in our analysis and VARV virulence is limited, our results suggest that smallpox severity is in part associated with VARV strain variation and that VARV virulence may be determined by multiple genetic loci. This study represents the first application of MDR to the identification of pathogen gene-gene interactions for predicting infectious disease outbreak severity. PMID:23410064

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

PubMed

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

2015-01-01

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

Passing messages between biological networks to refine predicted interactions.

PubMed

Glass, Kimberly; Huttenhower, Curtis; Quackenbush, John; Yuan, Guo-Cheng

2013-01-01

Regulatory network reconstruction is a fundamental problem in computational biology. There are significant limitations to such reconstruction using individual datasets, and increasingly people attempt to construct networks using multiple, independent datasets obtained from complementary sources, but methods for this integration are lacking. We developed PANDA (Passing Attributes between Networks for Data Assimilation), a message-passing model using multiple sources of information to predict regulatory relationships, and used it to integrate protein-protein interaction, gene expression, and sequence motif data to reconstruct genome-wide, condition-specific regulatory networks in yeast as a model. The resulting networks were not only more accurate than those produced using individual data sets and other existing methods, but they also captured information regarding specific biological mechanisms and pathways that were missed using other methodologies. PANDA is scalable to higher eukaryotes, applicable to specific tissue or cell type data and conceptually generalizable to include a variety of regulatory, interaction, expression, and other genome-scale data. An implementation of the PANDA algorithm is available at www.sourceforge.net/projects/panda-net.

Cytochrome P450s--Their expression, regulation, and role in insecticide resistance.

PubMed

Liu, Nannan; Li, Ming; Gong, Youhui; Liu, Feng; Li, Ting

2015-05-01

P450s are known to be critical for the detoxification and/or activation of xenobiotics such as drugs and pesticides and overexpression of P450 genes can significantly affect the disposition of xenobiotics in the tissues of organisms, altering their pharmacological/toxicological effects. In insects, P450s play an important role in detoxifying exogenous compounds such as insecticides and plant toxins and their overexpression can result in increased levels of P450 proteins and P450 activities. This has been associated with enhanced metabolic detoxification of insecticides and has been implicated in the development of insecticide resistance in insects. Multiple P450 genes have been found to be co-overexpressed in individual insect species via several constitutive overexpression and induction mechanisms, which in turn are co-responsible for high levels of insecticide resistance. Many studies have also demonstrated that the transcriptional overexpression of P450 genes in resistant insects is regulated by trans and/or cis regulatory genes/factors. Taken together, these earlier findings suggest not only that insecticide resistance is conferred via multi-resistance P450 genes, but also that it is mediated through the interaction of regulatory genes/factors and resistance genes. This chapter reviews our current understanding of how the molecular mechanisms of P450 interaction/gene regulation govern the development of insecticide resistance in insects and our progress along the road to a comprehensive characterization of P450 detoxification-mediated insecticide resistance. Copyright © 2015 Elsevier Inc. All rights reserved.

Multiple histone deacetylases are recruited by corepressor Sin3 and contribute to gene repression mediated by Opi1 regulator of phospholipid biosynthesis in the yeast Saccharomyces cerevisiae.

PubMed

Grigat, Mathias; Jäschke, Yvonne; Kliewe, Felix; Pfeifer, Matthias; Walz, Susanne; Schüller, Hans-Joachim

2012-06-01

Yeast genes of phospholipid biosynthesis are negatively regulated by repressor protein Opi1 when precursor molecules inositol and choline (IC) are available. Opi1-triggered gene repression is mediated by recruitment of the Sin3 corepressor complex. In this study, we systematically investigated the regulatory contribution of subunits of Sin3 complexes and identified Pho23 as important for IC-dependent gene repression. Two non-overlapping regions within Pho23 mediate its direct interaction with Sin3. Previous work has shown that Sin3 recruits the histone deacetylase (HDAC) Rpd3 to execute gene repression. While deletion of SIN3 strongly alleviates gene repression by IC, an rpd3 null mutant shows almost normal regulation. We thus hypothesized that various HDACs may contribute to Sin3-mediated repression of IC-regulated genes. Indeed, a triple mutant lacking HDACs, Rpd3, Hda1 and Hos1, could phenocopy a sin3 single mutant. We show that these proteins are able to contact Sin3 in vitro and in vivo and mapped three distinct HDAC interaction domains, designated HID1, HID2 and HID3. HID3, which is identical to the previously described structural motif PAH4 (paired amphipathic helix), can bind all HDACs tested. Chromatin immunoprecipitation studies finally confirmed that Hda1 and Hos1 are recruited to promoters of phospholipid biosynthetic genes INO1 and CHO2.

ABCB1 genetic polymorphism and risk of upper aerodigestive tract cancers among smokers, tobacco chewers and alcoholics in an Indian population.

PubMed

Sam, Soya Sisy; Thomas, Vinod; Sivagnanam, Kumaran; Reddy, Kanipakapatanam Sathyanarayana; Surianarayanan, Gopalakrishnan; Chandrasekaran, Adithan

2007-10-01

Upper aerodigestive tract (UADT) cancers are associated with the tobacco use and alcohol consumption. Certain toxins and carcinogens causing UADT cancers are found to be substrates of polymorphic ABCB1 gene encoded P-glycoprotein efflux pump. This study investigates the association between ABCB1 gene polymorphism at exon 26 (3435C>T) and risk to UADT cancers in Tamilians, a population of south India. The study included 219 unrelated histopathologically confirmed cases and 210 population-based controls. Genomic DNA was extracted from peripheral leukocytes and genotyped for ABCB1 3435C>T polymorphism by PCR-restriction fragment length polymorphism method. The multivariate logistic regression analyses demonstrated that the homozygous ABCB1 TT genotype was significantly associated with an overall increased risk for developing UADT cancers [odds ratio (OR): 2.53; 95% confidence interval (CI): 1.28-5.02]. Further, the determination of gene-environment interaction by stratified analyses have revealed a significant interaction between the smoking and homozygous TT genotype [(OR: 7.52; CI: 1.50-37.70) and (OR: 16.89; CI: 3.87-73.79) for 11-20 and >20 pack-years, respectively]. The strongest interaction was observed among the regular tobacco chewers (OR: 45.29; CI: 8.94-130.56) homozygous for TT genotype. No suggestion, however, of an interaction between the genotypes and the alcohol consumption on the multiplicative scale was made. The ABCB1 gene polymorphism at exon 26 (3435C>T) may be one of the risk factors for susceptibility to UADT cancers. Furthermore, the significant interaction among habitual smokers and tobacco chewers, homozygous for TT genotype modulates the risk to UADT cancers in the Tamilian population of south India.

From perception to activation: the molecular-genetic and biochemical landscape of disease resistance signaling in plants.

PubMed

Knepper, Caleb; Day, Brad

2010-01-01

More than 60 years ago, H.H. Flor proposed the "Gene-for-Gene" hypothesis, which described the genetic relationship between host plants and pathogens. In the decades that followed Flor's seminal work, our understanding of the plant-pathogen interaction has evolved into a sophisticated model, detailing the molecular genetic and biochemical processes that control host-range, disease resistance signaling and susceptibility. The interaction between plants and microbes is an intimate exchange of signals that has evolved for millennia, resulting in the modification and adaptation of pathogen virulence strategies and host recognition elements. In total, plants have evolved mechanisms to combat the ever-changing landscape of biotic interactions bombarding their environment, while in parallel, plant pathogens have co-evolved mechanisms to sense and adapt to these changes. On average, the typical plant is susceptible to attack by dozens of microbial pathogens, yet in most cases, remains resistant to many of these challenges. The sum of research in our field has revealed that these interactions are regulated by multiple layers of intimately linked signaling networks. As an evolved model of Flor's initial observations, the current paradigm in host-pathogen interactions is that pathogen effector molecules, in large part, drive the recognition, activation and subsequent physiological responses in plants that give rise to resistance and susceptibility. In this Chapter, we will discuss our current understanding of the association between plants and microbial pathogens, detailing the pressures placed on both host and microbe to either maintain disease resistance, or induce susceptibility and disease. From recognition to transcriptional reprogramming, we will review current data and literature that has advanced the classical model of the Gene-for-Gene hypothesis to our current understanding of basal and effector triggered immunity.

NOS2A, TLR4, and IFNGR1 interactions influence pulmonary tuberculosis susceptibility in African-Americans

PubMed Central

Velez, Digna Rosa; Hulme, William F.; Myers, Jamie L.; Weinberg, J. Brice; Levesque, Marc C.; Stryjewski, Martin E.; Abbate, Eduardo; Estevan, Rosa; Patillo, Sara G.; Gilbert, John R; Hamilton, Carol D.; Scott, William K.

2010-01-01

Tuberculosis (TB) has substantial mortality worldwide with 5-10% of those exposed progressing to active TB disease. Studies in mice and humans indicate that the inducible nitric oxide synthase (iNOS) molecule plays an important role in immune response to TB. A mixed case-control association study of individuals with TB, relatives, or close contact controls was performed in 726 individuals (279 case and 166 control African-Americans; 198 case and 123 control Caucasians). Thirty-nine single nucleotide polymorphisms (SNPs) were selected from the NOS2A gene for single SNP, haplotype, and multilocus interaction analyses with other typed candidate genes using generalized estimating equations. In African-Americans, ten NOS2A SNPs were associated with TB. The strongest associations were observed at rs2274894 (odds ratio (OR) = 1.84, 95% confidence interval (CI) [1.23-2.77], p = 0.003) and rs7215373 (OR 1.67, 95% CI [1.17-2.37], p = 0.004), both of which passed a false discovery rate (FDR) correction for multiple comparisons (q*=0.20). The strongest gene-gene interactions were observed between NOS2A rs2248814 and IFNGR1 rs1327474 (p = 0.0004) and NOS2A rs944722 and IFNGR1 rs1327474 (p = 0.0006). Three other SNPs in NOS2A interacted with TLR4 rs5030729 and five other NOS2A SNPs interacted with IFNGR1 rs1327474. No significant associations were observed in Caucasians. These results suggest that NOS2A variants may contribute to TB susceptibility, particularly in individuals of African descent, and may act synergistically with SNPs in TLR4 and IFNGR1. PMID:19575238

A Network Approach of Gene Co-expression in the Zea mays/Aspergillus flavus Pathosystem to Map Host/Pathogen Interaction Pathways.

PubMed

Musungu, Bryan M; Bhatnagar, Deepak; Brown, Robert L; Payne, Gary A; OBrian, Greg; Fakhoury, Ahmad M; Geisler, Matt

2016-01-01

A gene co-expression network (GEN) was generated using a dual RNA-seq study with the fungal pathogen Aspergillus flavus and its plant host Zea mays during the initial 3 days of infection. The analysis deciphered novel pathways and mapped genes of interest in both organisms during the infection. This network revealed a high degree of connectivity in many of the previously recognized pathways in Z. mays such as jasmonic acid, ethylene, and reactive oxygen species (ROS). For the pathogen A. flavus , a link between aflatoxin production and vesicular transport was identified within the network. There was significant interspecies correlation of expression between Z. mays and A. flavus for a subset of 104 Z. mays , and 1942 A. flavus genes. This resulted in an interspecies subnetwork enriched in multiple Z. mays genes involved in the production of ROS. In addition to the ROS from Z. mays , there was enrichment in the vesicular transport pathways and the aflatoxin pathway for A. flavus . Included in these genes, a key aflatoxin cluster regulator, AflS, was found to be co-regulated with multiple Z. mays ROS producing genes within the network, suggesting AflS may be monitoring host ROS levels. The entire GEN for both host and pathogen, and the subset of interspecies correlations, is presented as a tool for hypothesis generation and discovery for events in the early stages of fungal infection of Z. mays by A. flavus .

A Network Approach of Gene Co-expression in the Zea mays/Aspergillus flavus Pathosystem to Map Host/Pathogen Interaction Pathways

PubMed Central

Musungu, Bryan M.; Bhatnagar, Deepak; Brown, Robert L.; Payne, Gary A.; OBrian, Greg; Fakhoury, Ahmad M.; Geisler, Matt

2016-01-01

A gene co-expression network (GEN) was generated using a dual RNA-seq study with the fungal pathogen Aspergillus flavus and its plant host Zea mays during the initial 3 days of infection. The analysis deciphered novel pathways and mapped genes of interest in both organisms during the infection. This network revealed a high degree of connectivity in many of the previously recognized pathways in Z. mays such as jasmonic acid, ethylene, and reactive oxygen species (ROS). For the pathogen A. flavus, a link between aflatoxin production and vesicular transport was identified within the network. There was significant interspecies correlation of expression between Z. mays and A. flavus for a subset of 104 Z. mays, and 1942 A. flavus genes. This resulted in an interspecies subnetwork enriched in multiple Z. mays genes involved in the production of ROS. In addition to the ROS from Z. mays, there was enrichment in the vesicular transport pathways and the aflatoxin pathway for A. flavus. Included in these genes, a key aflatoxin cluster regulator, AflS, was found to be co-regulated with multiple Z. mays ROS producing genes within the network, suggesting AflS may be monitoring host ROS levels. The entire GEN for both host and pathogen, and the subset of interspecies correlations, is presented as a tool for hypothesis generation and discovery for events in the early stages of fungal infection of Z. mays by A. flavus. PMID:27917194

Pathway-based analyses.

PubMed

Kent, Jack W

2016-02-03

New technologies for acquisition of genomic data, while offering unprecedented opportunities for genetic discovery, also impose severe burdens of interpretation and penalties for multiple testing. The Pathway-based Analyses Group of the Genetic Analysis Workshop 19 (GAW19) sought reduction of multiple-testing burden through various approaches to aggregation of highdimensional data in pathways informed by prior biological knowledge. Experimental methods testedincluded the use of "synthetic pathways" (random sets of genes) to estimate power and false-positive error rate of methods applied to simulated data; data reduction via independent components analysis, single-nucleotide polymorphism (SNP)-SNP interaction, and use of gene sets to estimate genetic similarity; and general assessment of the efficacy of prior biological knowledge to reduce the dimensionality of complex genomic data. The work of this group explored several promising approaches to managing high-dimensional data, with the caveat that these methods are necessarily constrained by the quality of external bioinformatic annotation.

MGDB: a comprehensive database of genes involved in melanoma.

PubMed

Zhang, Di; Zhu, Rongrong; Zhang, Hanqian; Zheng, Chun-Hou; Xia, Junfeng

2015-01-01

The Melanoma Gene Database (MGDB) is a manually curated catalog of molecular genetic data relating to genes involved in melanoma. The main purpose of this database is to establish a network of melanoma related genes and to facilitate the mechanistic study of melanoma tumorigenesis. The entries describing the relationships between melanoma and genes in the current release were manually extracted from PubMed abstracts, which contains cumulative to date 527 human melanoma genes (422 protein-coding and 105 non-coding genes). Each melanoma gene was annotated in seven different aspects (General Information, Expression, Methylation, Mutation, Interaction, Pathway and Drug). In addition, manually curated literature references have also been provided to support the inclusion of the gene in MGDB and establish its association with melanoma. MGDB has a user-friendly web interface with multiple browse and search functions. We hoped MGDB will enrich our knowledge about melanoma genetics and serve as a useful complement to the existing public resources. Database URL: http://bioinfo.ahu.edu.cn:8080/Melanoma/index.jsp. © The Author(s) 2015. Published by Oxford University Press.

Network-based analysis of genotype-phenotype correlations between different inheritance modes.

PubMed

Hao, Dapeng; Li, Chuanxing; Zhang, Shaojun; Lu, Jianping; Jiang, Yongshuai; Wang, Shiyuan; Zhou, Meng

2014-11-15

Recent studies on human disease have revealed that aberrant interaction between proteins probably underlies a substantial number of human genetic diseases. This suggests a need to investigate disease inheritance mode using interaction, and based on which to refresh our conceptual understanding of a series of properties regarding inheritance mode of human disease. We observed a strong correlation between the number of protein interactions and the likelihood of a gene causing any dominant diseases or multiple dominant diseases, whereas no correlation was observed between protein interaction and the likelihood of a gene causing recessive diseases. We found that dominant diseases are more likely to be associated with disruption of important interactions. These suggest inheritance mode should be understood using protein interaction. We therefore reviewed the previous studies and refined an interaction model of inheritance mode, and then confirmed that this model is largely reasonable using new evidences. With these findings, we found that the inheritance mode of human genetic diseases can be predicted using protein interaction. By integrating the systems biology perspectives with the classical disease genetics paradigm, our study provides some new insights into genotype-phenotype correlations. haodapeng@ems.hrbmu.edu.cn or biofomeng@hotmail.com Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A powerful approach reveals numerous expression quantitative trait haplotypes in multiple tissues.

PubMed

Ying, Dingge; Li, Mulin Jun; Sham, Pak Chung; Li, Miaoxin

2018-04-26

Recently many studies showed single nucleotide polymorphisms (SNPs) affect gene expression and contribute to development of complex traits/diseases in a tissue context-dependent manner. However, little is known about haplotype's influence on gene expression and complex traits, which reflects the interaction effect between SNPs. In the present study, we firstly proposed a regulatory region guided eQTL haplotype association analysis approach, and then systematically investigate the expression quantitative trait loci (eQTL) haplotypes in 20 different tissues by the approach. The approach has a powerful design of reducing computational burden by the utilization of regulatory predictions for candidate SNP selection and multiple testing corrections on non-independent haplotypes. The application results in multiple tissues showed that haplotype-based eQTLs not only increased the number of eQTL genes in a tissue specific manner, but were also enriched in loci that associated with complex traits in a tissue-matched manner. In addition, we found that tag SNPs of eQTL haplotypes from whole blood were selectively enriched in certain combination of regulatory elements (e.g. promoters and enhancers) according to predicted chromatin states. In summary, this eQTL haplotype detection approach, together with the application results, shed insights into synergistic effect of sequence variants on gene expression and their susceptibility to complex diseases. The executable application "eHaplo" is implemented in Java and is publicly available at http://grass.cgs.hku.hk/limx/ehaplo/. jonsonfox@gmail.com, limiaoxin@mail.sysu.edu.cn. Supplementary data are available at Bioinformatics online.

Identification of novel mutational drivers reveals oncogene dependencies in multiple myeloma.

PubMed

Walker, Brian A; Mavrommatis, Konstantinos; Wardell, Christopher P; Ashby, T Cody; Bauer, Michael; Davies, Faith E; Rosenthal, Adam; Wang, Hongwei; Qu, Pingping; Hoering, Antje; Samur, Mehmet; Towfic, Fadi; Ortiz, Maria; Flynt, Erin; Yu, Zhinuan; Yang, Zhihong; Rozelle, Dan; Obenauer, John; Trotter, Matthew; Auclair, Daniel; Keats, Jonathan; Bolli, Niccolo; Fulciniti, Mariateresa; Szalat, Raphael; Moreau, Philippe; Durie, Brian; Stewart, A Keith; Goldschmidt, Hartmut; Raab, Marc S; Einsele, Hermann; Sonneveld, Pieter; San Miguel, Jesus; Lonial, Sagar; Jackson, Graham H; Anderson, Kenneth C; Avet-Loiseau, Herve; Munshi, Nikhil; Thakurta, Anjan; Morgan, Gareth J

2018-06-08

Understanding the profile of oncogene and tumor suppressor gene mutations with their interactions and impact on the prognosis of multiple myeloma (MM) can improve the definition of disease subsets and identify pathways important in disease pathobiology. Using integrated genomics of 1,273 newly diagnosed patients with multiple myeloma we identify 63 driver genes, some of which are novel including IDH1 , IDH2 , HUWE1 , KLHL6 , and PTPN11 Oncogene mutations are significantly more clonal than tumor suppressor mutations, indicating they may exert a bigger selective pressure. Patients with more mutations in driver genes are associated with a worse outcome, as are those with identified mechanisms of genomic instability. Oncogenic dependencies were identified between mutations in driver genes, common regions of copy number change, and primary translocation and hyperdiploidy events. These dependencies included associations with t(4;14) and mutations in FGFR3 , DIS3 and PRKD2 ; t(11;14) with mutations in CCND1 and IRF4 ; t(14;16) with mutations in MAF , BRAF , DIS3 and ATM ; and hyperdiploidy with gain 11q, mutations in FAM46C and MYC rearrangements. These associations indicate that the genomic landscape of myeloma is pre-determined by the primary events upon which further dependencies are built, giving rise to a non-random accumulation of genetic hits. Understanding these dependencies may elucidate potential evolutionary patterns and lead to better treatment regimens. Copyright © 2018 American Society of Hematology.

Analysis of papaya cell wall-related genes during fruit ripening indicates a central role of polygalacturonases during pulp softening.

PubMed

Fabi, João Paulo; Broetto, Sabrina Garcia; da Silva, Sarah Lígia Garcia Leme; Zhong, Silin; Lajolo, Franco Maria; do Nascimento, João Roberto Oliveira

2014-01-01

Papaya (Carica papaya L.) is a climacteric fleshy fruit that undergoes dramatic changes during ripening, most noticeably a severe pulp softening. However, little is known regarding the genetics of the cell wall metabolism in papayas. The present work describes the identification and characterization of genes related to pulp softening. We used gene expression profiling to analyze the correlations and co-expression networks of cell wall-related genes, and the results suggest that papaya pulp softening is accomplished by the interactions of multiple glycoside hydrolases. The polygalacturonase cpPG1 appeared to play a central role in the network and was further studied. The transient expression of cpPG1 in papaya results in pulp softening and leaf necrosis in the absence of ethylene action and confirms its role in papaya fruit ripening.

Improved genome-scale multi-target virtual screening via a novel collaborative filtering approach to cold-start problem

PubMed Central

Lim, Hansaim; Gray, Paul; Xie, Lei; Poleksic, Aleksandar

2016-01-01

Conventional one-drug-one-gene approach has been of limited success in modern drug discovery. Polypharmacology, which focuses on searching for multi-targeted drugs to perturb disease-causing networks instead of designing selective ligands to target individual proteins, has emerged as a new drug discovery paradigm. Although many methods for single-target virtual screening have been developed to improve the efficiency of drug discovery, few of these algorithms are designed for polypharmacology. Here, we present a novel theoretical framework and a corresponding algorithm for genome-scale multi-target virtual screening based on the one-class collaborative filtering technique. Our method overcomes the sparseness of the protein-chemical interaction data by means of interaction matrix weighting and dual regularization from both chemicals and proteins. While the statistical foundation behind our method is general enough to encompass genome-wide drug off-target prediction, the program is specifically tailored to find protein targets for new chemicals with little to no available interaction data. We extensively evaluate our method using a number of the most widely accepted gene-specific and cross-gene family benchmarks and demonstrate that our method outperforms other state-of-the-art algorithms for predicting the interaction of new chemicals with multiple proteins. Thus, the proposed algorithm may provide a powerful tool for multi-target drug design. PMID:27958331

Improved genome-scale multi-target virtual screening via a novel collaborative filtering approach to cold-start problem.

PubMed

Lim, Hansaim; Gray, Paul; Xie, Lei; Poleksic, Aleksandar

2016-12-13

Conventional one-drug-one-gene approach has been of limited success in modern drug discovery. Polypharmacology, which focuses on searching for multi-targeted drugs to perturb disease-causing networks instead of designing selective ligands to target individual proteins, has emerged as a new drug discovery paradigm. Although many methods for single-target virtual screening have been developed to improve the efficiency of drug discovery, few of these algorithms are designed for polypharmacology. Here, we present a novel theoretical framework and a corresponding algorithm for genome-scale multi-target virtual screening based on the one-class collaborative filtering technique. Our method overcomes the sparseness of the protein-chemical interaction data by means of interaction matrix weighting and dual regularization from both chemicals and proteins. While the statistical foundation behind our method is general enough to encompass genome-wide drug off-target prediction, the program is specifically tailored to find protein targets for new chemicals with little to no available interaction data. We extensively evaluate our method using a number of the most widely accepted gene-specific and cross-gene family benchmarks and demonstrate that our method outperforms other state-of-the-art algorithms for predicting the interaction of new chemicals with multiple proteins. Thus, the proposed algorithm may provide a powerful tool for multi-target drug design.

Boosting for detection of gene-environment interactions.

PubMed

Pashova, H; LeBlanc, M; Kooperberg, C

2013-01-30

In genetic association studies, it is typically thought that genetic variants and environmental variables jointly will explain more of the inheritance of a phenotype than either of these two components separately. Traditional methods to identify gene-environment interactions typically consider only one measured environmental variable at a time. However, in practice, multiple environmental factors may each be imprecise surrogates for the underlying physiological process that actually interacts with the genetic factors. In this paper, we develop a variant of L(2) boosting that is specifically designed to identify combinations of environmental variables that jointly modify the effect of a gene on a phenotype. Because the effect modifiers might have a small signal compared with the main effects, working in a space that is orthogonal to the main predictors allows us to focus on the interaction space. In a simulation study that investigates some plausible underlying model assumptions, our method outperforms the least absolute shrinkage and selection and Akaike Information Criterion and Bayesian Information Criterion model selection procedures as having the lowest test error. In an example for the Women's Health Initiative-Population Architecture using Genomics and Epidemiology study, the dedicated boosting method was able to pick out two single-nucleotide polymorphisms for which effect modification appears present. The performance was evaluated on an independent test set, and the results are promising. Copyright © 2012 John Wiley & Sons, Ltd.

Small-molecule MDM2 antagonists reveal aberrant p53 signaling in cancer: Implications for therapy

PubMed Central

Tovar, Christian; Rosinski, James; Filipovic, Zoran; Higgins, Brian; Kolinsky, Kenneth; Hilton, Holly; Zhao, Xiaolan; Vu, Binh T.; Qing, Weiguo; Packman, Kathryn; Myklebost, Ola; Heimbrook, David C.; Vassilev, Lyubomir T.

2006-01-01

The p53 tumor suppressor retains its wild-type conformation and transcriptional activity in half of all human tumors, and its activation may offer a therapeutic benefit. However, p53 function could be compromised by defective signaling in the p53 pathway. Using a small-molecule MDM2 antagonist, nutlin-3, to probe downstream p53 signaling we find that the cell-cycle arrest function of the p53 pathway is preserved in multiple tumor-derived cell lines expressing wild-type p53, but many have a reduced ability to undergo p53-dependent apoptosis. Gene array analysis revealed attenuated expression of multiple apoptosis-related genes. Cancer cells with mdm2 gene amplification were most sensitive to nutlin-3 in vitro and in vivo, suggesting that MDM2 overexpression may be the only abnormality in the p53 pathway of these cells. Nutlin-3 also showed good efficacy against tumors with normal MDM2 expression, suggesting that many of the patients with wild-type p53 tumors may benefit from antagonists of the p53–MDM2 interaction. PMID:16443686

The epigenetic basis of memory formation and storage.

PubMed

Jarome, Timothy J; Thomas, Jasmyne S; Lubin, Farah D

2014-01-01

The formation of long-term memory requires a series of cellular and molecular changes that involve transcriptional regulation of gene expression. While these changes in gene transcription were initially thought to be largely regulated by the activation of transcription factors by intracellular signaling molecules, epigenetic mechanisms have emerged as an important regulator of transcriptional processes across multiple brain regions to form a memory circuit for a learned event or experience. Due to their self-perpetuating nature and ability to bidirectionally control gene expression, these epigenetic mechanisms have the potential to not only regulate initial memory formation but also modify and update memory over time. This chapter focuses on the established, but poorly understood, role for epigenetic mechanisms such as posttranslational modifications of histone proteins and DNA methylation at the different stages of memory storage. Additionally, this chapter emphasizes how these mechanisms interact to control the ideal epigenetic environment for memory formation and modification in neurons. The reader will gain insights into the limitations in our current understanding of epigenetic regulation of memory storage, especially in terms of their cell-type specificity and the lack of understanding in the interactions of various epigenetic modifiers to one another to impact gene expression changes during memory formation.

KCNJ11: Genetic Polymorphisms and Risk of Diabetes Mellitus

PubMed Central

Mohamed, Zahurin; Abdullah, Nor Azizan; Haghvirdizadeh, Pantea; Haerian, Monir Sadat

2015-01-01

Diabetes mellitus (DM) is a major worldwide health problem and its prevalence has been rapidly increasing in the last century. It is caused by defects in insulin secretion or insulin action or both, leading to hyperglycemia. Of the various types of DM, type 2 occurs most frequently. Multiple genes and their interactions are involved in the insulin secretion pathway. Insulin secretion is mediated through the ATP-sensitive potassium (KATP) channel in pancreatic beta cells. This channel is a heteromeric protein, composed of four inward-rectifier potassium ion channel (Kir6.2) tetramers, which form the pore of the KATP channel, as well as sulfonylurea receptor 1 subunits surrounding the pore. Kir6.2 is encoded by the potassium inwardly rectifying channel, subfamily J, member 11 (KCNJ11) gene, a member of the potassium channel genes. Numerous studies have reported the involvement of single nucleotide polymorphisms of the KCNJ11 gene and their interactions in the susceptibility to DM. This review discusses the current evidence for the contribution of common KCNJ11 genetic variants to the development of DM. Future studies should concentrate on understanding the exact role played by these risk variants in the development of DM. PMID:26448950

Evolution of Salmonella-Host Cell Interactions through a Dynamic Bacterial Genome

PubMed Central

Ilyas, Bushra; Tsai, Caressa N.; Coombes, Brian K.

2017-01-01

Salmonella Typhimurium has a broad arsenal of genes that are tightly regulated and coordinated to facilitate adaptation to the various host environments it colonizes. The genome of Salmonella Typhimurium has undergone multiple gene acquisition events and has accrued changes in non-coding DNA that have undergone selection by regulatory evolution. Together, at least 17 horizontally acquired pathogenicity islands (SPIs), prophage-associated genes, and changes in core genome regulation contribute to the virulence program of Salmonella. Here, we review the latest understanding of these elements and their contributions to pathogenesis, emphasizing the regulatory circuitry that controls niche-specific gene expression. In addition to an overview of the importance of SPI-1 and SPI-2 to host invasion and colonization, we describe the recently characterized contributions of other SPIs, including the antibacterial activity of SPI-6 and adhesion and invasion mediated by SPI-4. We further discuss how these fitness traits have been integrated into the regulatory circuitry of the bacterial cell through cis-regulatory evolution and by a careful balance of silencing and counter-silencing by regulatory proteins. Detailed understanding of regulatory evolution within Salmonella is uncovering novel aspects of infection biology that relate to host-pathogen interactions and evasion of host immunity. PMID:29034217

Multivariate inference of pathway activity in host immunity and response to therapeutics

PubMed Central

Goel, Gautam; Conway, Kara L.; Jaeger, Martin; Netea, Mihai G.; Xavier, Ramnik J.

2014-01-01

Developing a quantitative view of how biological pathways are regulated in response to environmental factors is central for understanding of disease phenotypes. We present a computational framework, named Multivariate Inference of Pathway Activity (MIPA), which quantifies degree of activity induced in a biological pathway by computing five distinct measures from transcriptomic profiles of its member genes. Statistical significance of inferred activity is examined using multiple independent self-contained tests followed by a competitive analysis. The method incorporates a new algorithm to identify a subset of genes that may regulate the extent of activity induced in a pathway. We present an in-depth evaluation of specificity, robustness, and reproducibility of our method. We benchmarked MIPA's false positive rate at less than 1%. Using transcriptomic profiles representing distinct physiological and disease states, we illustrate applicability of our method in (i) identifying gene–gene interactions in autophagy-dependent response to Salmonella infection, (ii) uncovering gene–environment interactions in host response to bacterial and viral pathogens and (iii) identifying driver genes and processes that contribute to wound healing and response to anti-TNFα therapy. We provide relevant experimental validation that corroborates the accuracy and advantage of our method. PMID:25147207

Interactions between genetic variation and cellular environment in skeletal muscle gene expression.

PubMed

Taylor, D Leland; Knowles, David A; Scott, Laura J; Ramirez, Andrea H; Casale, Francesco Paolo; Wolford, Brooke N; Guan, Li; Varshney, Arushi; Albanus, Ricardo D'Oliveira; Parker, Stephen C J; Narisu, Narisu; Chines, Peter S; Erdos, Michael R; Welch, Ryan P; Kinnunen, Leena; Saramies, Jouko; Sundvall, Jouko; Lakka, Timo A; Laakso, Markku; Tuomilehto, Jaakko; Koistinen, Heikki A; Stegle, Oliver; Boehnke, Michael; Birney, Ewan; Collins, Francis S

2018-01-01

From whole organisms to individual cells, responses to environmental conditions are influenced by genetic makeup, where the effect of genetic variation on a trait depends on the environmental context. RNA-sequencing quantifies gene expression as a molecular trait, and is capable of capturing both genetic and environmental effects. In this study, we explore opportunities of using allele-specific expression (ASE) to discover cis-acting genotype-environment interactions (GxE)-genetic effects on gene expression that depend on an environmental condition. Treating 17 common, clinical traits as approximations of the cellular environment of 267 skeletal muscle biopsies, we identify 10 candidate environmental response expression quantitative trait loci (reQTLs) across 6 traits (12 unique gene-environment trait pairs; 10% FDR per trait) including sex, systolic blood pressure, and low-density lipoprotein cholesterol. Although using ASE is in principle a promising approach to detect GxE effects, replication of such signals can be challenging as validation requires harmonization of environmental traits across cohorts and a sufficient sampling of heterozygotes for a transcribed SNP. Comprehensive discovery and replication will require large human transcriptome datasets, or the integration of multiple transcribed SNPs, coupled with standardized clinical phenotyping.

GeneSeqToFamily: a Galaxy workflow to find gene families based on the Ensembl Compara GeneTrees pipeline.

PubMed

Thanki, Anil S; Soranzo, Nicola; Haerty, Wilfried; Davey, Robert P

2018-03-01

Gene duplication is a major factor contributing to evolutionary novelty, and the contraction or expansion of gene families has often been associated with morphological, physiological, and environmental adaptations. The study of homologous genes helps us to understand the evolution of gene families. It plays a vital role in finding ancestral gene duplication events as well as identifying genes that have diverged from a common ancestor under positive selection. There are various tools available, such as MSOAR, OrthoMCL, and HomoloGene, to identify gene families and visualize syntenic information between species, providing an overview of syntenic regions evolution at the family level. Unfortunately, none of them provide information about structural changes within genes, such as the conservation of ancestral exon boundaries among multiple genomes. The Ensembl GeneTrees computational pipeline generates gene trees based on coding sequences, provides details about exon conservation, and is used in the Ensembl Compara project to discover gene families. A certain amount of expertise is required to configure and run the Ensembl Compara GeneTrees pipeline via command line. Therefore, we converted this pipeline into a Galaxy workflow, called GeneSeqToFamily, and provided additional functionality. This workflow uses existing tools from the Galaxy ToolShed, as well as providing additional wrappers and tools that are required to run the workflow. GeneSeqToFamily represents the Ensembl GeneTrees pipeline as a set of interconnected Galaxy tools, so they can be run interactively within the Galaxy's user-friendly workflow environment while still providing the flexibility to tailor the analysis by changing configurations and tools if necessary. Additional tools allow users to subsequently visualize the gene families produced by the workflow, using the Aequatus.js interactive tool, which has been developed as part of the Aequatus software project.

Proteins Encoded in Genomic Regions Associated with Immune-Mediated Disease Physically Interact and Suggest Underlying Biology

PubMed Central

Rossin, Elizabeth J.; Lage, Kasper; Raychaudhuri, Soumya; Xavier, Ramnik J.; Tatar, Diana; Benita, Yair

2011-01-01

Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed by these risk variants. It has previously been observed that different genes harboring causal mutations for the same Mendelian disease often physically interact. We sought to evaluate the degree to which this is true of genes within strongly associated loci in complex disease. Using sets of loci defined in rheumatoid arthritis (RA) and Crohn's disease (CD) GWAS, we build protein–protein interaction (PPI) networks for genes within associated loci and find abundant physical interactions between protein products of associated genes. We apply multiple permutation approaches to show that these networks are more densely connected than chance expectation. To confirm biological relevance, we show that the components of the networks tend to be expressed in similar tissues relevant to the phenotypes in question, suggesting the network indicates common underlying processes perturbed by risk loci. Furthermore, we show that the RA and CD networks have predictive power by demonstrating that proteins in these networks, not encoded in the confirmed list of disease associated loci, are significantly enriched for association to the phenotypes in question in extended GWAS analysis. Finally, we test our method in 3 non-immune traits to assess its applicability to complex traits in general. We find that genes in loci associated to height and lipid levels assemble into significantly connected networks but did not detect excess connectivity among Type 2 Diabetes (T2D) loci beyond chance. Taken together, our results constitute evidence that, for many of the complex diseases studied here, common genetic associations implicate regions encoding proteins that physically interact in a preferential manner, in line with observations in Mendelian disease. PMID:21249183

From gene networks to drugs: systems pharmacology approaches for AUD.

PubMed

Ferguson, Laura B; Harris, R Adron; Mayfield, Roy Dayne

2018-06-01

The alcohol research field has amassed an impressive number of gene expression datasets spanning key brain areas for addiction, species (humans as well as multiple animal models), and stages in the addiction cycle (binge/intoxication, withdrawal/negative effect, and preoccupation/anticipation). These data have improved our understanding of the molecular adaptations that eventually lead to dysregulation of brain function and the chronic, relapsing disorder of addiction. Identification of new medications to treat alcohol use disorder (AUD) will likely benefit from the integration of genetic, genomic, and behavioral information included in these important datasets. Systems pharmacology considers drug effects as the outcome of the complex network of interactions a drug has rather than a single drug-molecule interaction. Computational strategies based on this principle that integrate gene expression signatures of pharmaceuticals and disease states have shown promise for identifying treatments that ameliorate disease symptoms (called in silico gene mapping or connectivity mapping). In this review, we suggest that gene expression profiling for in silico mapping is critical to improve drug repurposing and discovery for AUD and other psychiatric illnesses. We highlight studies that successfully apply gene mapping computational approaches to identify or repurpose pharmaceutical treatments for psychiatric illnesses. Furthermore, we address important challenges that must be overcome to maximize the potential of these strategies to translate to the clinic and improve healthcare outcomes.

Identification of aberrant gene expression associated with aberrant promoter methylation in primordial germ cells between E13 and E16 rat F3 generation vinclozolin lineage.

PubMed

Taguchi, Y-h

2015-01-01

Transgenerational epigenetics (TGE) are currently considered important in disease, but the mechanisms involved are not yet fully understood. TGE abnormalities expected to cause disease are likely to be initiated during development and to be mediated by aberrant gene expression associated with aberrant promoter methylation that is heritable between generations. However, because methylation is removed and then re-established during development, it is not easy to identify promoter methylation abnormalities by comparing normal lineages with those expected to exhibit TGE abnormalities. This study applied the recently proposed principal component analysis (PCA)-based unsupervised feature extraction to previously reported and publically available gene expression/promoter methylation profiles of rat primordial germ cells, between E13 and E16 of the F3 generation vinclozolin lineage that are expected to exhibit TGE abnormalities, to identify multiple genes that exhibited aberrant gene expression/promoter methylation during development. The biological feasibility of the identified genes were tested via enrichment analyses of various biological concepts including pathway analysis, gene ontology terms and protein-protein interactions. All validations suggested superiority of the proposed method over three conventional and popular supervised methods that employed t test, limma and significance analysis of microarrays, respectively. The identified genes were globally related to tumors, the prostate, kidney, testis and the immune system and were previously reported to be related to various diseases caused by TGE. Among the genes reported by PCA-based unsupervised feature extraction, we propose that chemokine signaling pathways and leucine rich repeat proteins are key factors that initiate transgenerational epigenetic-mediated diseases, because multiple genes included in these two categories were identified in this study.

Identification of aberrant gene expression associated with aberrant promoter methylation in primordial germ cells between E13 and E16 rat F3 generation vinclozolin lineage

PubMed Central

2015-01-01

Background Transgenerational epigenetics (TGE) are currently considered important in disease, but the mechanisms involved are not yet fully understood. TGE abnormalities expected to cause disease are likely to be initiated during development and to be mediated by aberrant gene expression associated with aberrant promoter methylation that is heritable between generations. However, because methylation is removed and then re-established during development, it is not easy to identify promoter methylation abnormalities by comparing normal lineages with those expected to exhibit TGE abnormalities. Methods This study applied the recently proposed principal component analysis (PCA)-based unsupervised feature extraction to previously reported and publically available gene expression/promoter methylation profiles of rat primordial germ cells, between E13 and E16 of the F3 generation vinclozolin lineage that are expected to exhibit TGE abnormalities, to identify multiple genes that exhibited aberrant gene expression/promoter methylation during development. Results The biological feasibility of the identified genes were tested via enrichment analyses of various biological concepts including pathway analysis, gene ontology terms and protein-protein interactions. All validations suggested superiority of the proposed method over three conventional and popular supervised methods that employed t test, limma and significance analysis of microarrays, respectively. The identified genes were globally related to tumors, the prostate, kidney, testis and the immune system and were previously reported to be related to various diseases caused by TGE. Conclusions Among the genes reported by PCA-based unsupervised feature extraction, we propose that chemokine signaling pathways and leucine rich repeat proteins are key factors that initiate transgenerational epigenetic-mediated diseases, because multiple genes included in these two categories were identified in this study. PMID:26677731

Virulence gene regulation by CvfA, a putative RNase: the CvfA-enolase complex in Streptococcus pyogenes links nutritional stress, growth-phase control, and virulence gene expression.

PubMed

Kang, Song Ok; Caparon, Michael G; Cho, Kyu Hong

2010-06-01

Streptococcus pyogenes, a multiple-auxotrophic human pathogen, regulates virulence gene expression according to nutritional availability during various stages in the infection process or in different infection sites. We discovered that CvfA influenced the expression of virulence genes according to growth phase and nutritional status. The influence of CvfA in C medium, rich in peptides and poor in carbohydrates, was most pronounced at the stationary phase. Under these conditions, up to 30% of the transcriptome exhibited altered expression; the levels of expression of multiple virulence genes were altered, including the genes encoding streptokinase, CAMP factor, streptolysin O, M protein (more abundant in the CvfA(-) mutant), SpeB, mitogenic factor, and streptolysin S (less abundant). The increase of carbohydrates or peptides in media restored the levels of expression of the virulence genes in the CvfA(-) mutant to wild-type levels (emm, ska, and cfa by carbohydrates; speB by peptides). Even though the regulation of gene expression dependent on nutritional stress is commonly linked to the stringent response, the levels of ppGpp were not altered by deletion of cvfA. Instead, CvfA interacted with enolase, implying that CvfA, a putative RNase, controls the transcript decay rates of virulence factors or their regulators according to nutritional status. The virulence of CvfA(-) mutants was highly attenuated in murine models, indicating that CvfA-mediated gene regulation is necessary for the pathogenesis of S. pyogenes. Taken together, the CvfA-enolase complex in S. pyogenes is involved in the regulation of virulence gene expression by controlling RNA degradation according to nutritional stress.

Prediction of Oncogenic Interactions and Cancer-Related Signaling Networks Based on Network Topology

PubMed Central

Acencio, Marcio Luis; Bovolenta, Luiz Augusto; Camilo, Esther; Lemke, Ney

2013-01-01

Cancer has been increasingly recognized as a systems biology disease since many investigators have demonstrated that this malignant phenotype emerges from abnormal protein-protein, regulatory and metabolic interactions induced by simultaneous structural and regulatory changes in multiple genes and pathways. Therefore, the identification of oncogenic interactions and cancer-related signaling networks is crucial for better understanding cancer. As experimental techniques for determining such interactions and signaling networks are labor-intensive and time-consuming, the development of a computational approach capable to accomplish this task would be of great value. For this purpose, we present here a novel computational approach based on network topology and machine learning capable to predict oncogenic interactions and extract relevant cancer-related signaling subnetworks from an integrated network of human genes interactions (INHGI). This approach, called graph2sig, is twofold: first, it assigns oncogenic scores to all interactions in the INHGI and then these oncogenic scores are used as edge weights to extract oncogenic signaling subnetworks from INHGI. Regarding the prediction of oncogenic interactions, we showed that graph2sig is able to recover 89% of known oncogenic interactions with a precision of 77%. Moreover, the interactions that received high oncogenic scores are enriched in genes for which mutations have been causally implicated in cancer. We also demonstrated that graph2sig is potentially useful in extracting oncogenic signaling subnetworks: more than 80% of constructed subnetworks contain more than 50% of original interactions in their corresponding oncogenic linear pathways present in the KEGG PATHWAY database. In addition, the potential oncogenic signaling subnetworks discovered by graph2sig are supported by experimental evidence. Taken together, these results suggest that graph2sig can be a useful tool for investigators involved in cancer research interested in detecting signaling networks most prone to contribute with the emergence of malignant phenotype. PMID:24204854

Semi-Supervised Multi-View Learning for Gene Network Reconstruction

PubMed Central

Ceci, Michelangelo; Pio, Gianvito; Kuzmanovski, Vladimir; Džeroski, Sašo

2015-01-01

The task of gene regulatory network reconstruction from high-throughput data is receiving increasing attention in recent years. As a consequence, many inference methods for solving this task have been proposed in the literature. It has been recently observed, however, that no single inference method performs optimally across all datasets. It has also been shown that the integration of predictions from multiple inference methods is more robust and shows high performance across diverse datasets. Inspired by this research, in this paper, we propose a machine learning solution which learns to combine predictions from multiple inference methods. While this approach adds additional complexity to the inference process, we expect it would also carry substantial benefits. These would come from the automatic adaptation to patterns on the outputs of individual inference methods, so that it is possible to identify regulatory interactions more reliably when these patterns occur. This article demonstrates the benefits (in terms of accuracy of the reconstructed networks) of the proposed method, which exploits an iterative, semi-supervised ensemble-based algorithm. The algorithm learns to combine the interactions predicted by many different inference methods in the multi-view learning setting. The empirical evaluation of the proposed algorithm on a prokaryotic model organism (E. coli) and on a eukaryotic model organism (S. cerevisiae) clearly shows improved performance over the state of the art methods. The results indicate that gene regulatory network reconstruction for the real datasets is more difficult for S. cerevisiae than for E. coli. The software, all the datasets used in the experiments and all the results are available for download at the following link: http://figshare.com/articles/Semi_supervised_Multi_View_Learning_for_Gene_Network_Reconstruction/1604827. PMID:26641091

Bayesian state space models for dynamic genetic network construction across multiple tissues.

PubMed

Liang, Yulan; Kelemen, Arpad

2016-08-01

Construction of gene-gene interaction networks and potential pathways is a challenging and important problem in genomic research for complex diseases while estimating the dynamic changes of the temporal correlations and non-stationarity are the keys in this process. In this paper, we develop dynamic state space models with hierarchical Bayesian settings to tackle this challenge for inferring the dynamic profiles and genetic networks associated with disease treatments. We treat both the stochastic transition matrix and the observation matrix time-variant and include temporal correlation structures in the covariance matrix estimations in the multivariate Bayesian state space models. The unevenly spaced short time courses with unseen time points are treated as hidden state variables. Hierarchical Bayesian approaches with various prior and hyper-prior models with Monte Carlo Markov Chain and Gibbs sampling algorithms are used to estimate the model parameters and the hidden state variables. We apply the proposed Hierarchical Bayesian state space models to multiple tissues (liver, skeletal muscle, and kidney) Affymetrix time course data sets following corticosteroid (CS) drug administration. Both simulation and real data analysis results show that the genomic changes over time and gene-gene interaction in response to CS treatment can be well captured by the proposed models. The proposed dynamic Hierarchical Bayesian state space modeling approaches could be expanded and applied to other large scale genomic data, such as next generation sequence (NGS) combined with real time and time varying electronic health record (EHR) for more comprehensive and robust systematic and network based analysis in order to transform big biomedical data into predictions and diagnostics for precision medicine and personalized healthcare with better decision making and patient outcomes.

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

PubMed Central

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

2001-01-01

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. PMID:11606538

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

PubMed

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.

151. Bromocriptine Challenge Affects Working Memory Processing in Humans Depending on DRD2-Related Genes

PubMed Central

Pergola, Giulio; Selvaggi, Pierluigi; Gelao, Barbara; Di Carlo, Pasquale; Nettis, Maria Antonietta; Amico, Graziella; Felici, Valentina; Fazio, Leonardo; Rampino, Antonio; Sambataro, Fabio; Blasi, Giuseppe; Bertolino, Alessandro

2017-01-01

Abstract Background: Dopamine D2 receptors (D2R) contribute to the inverted-U shaped relationship between dopamine dorsolateral prefrontal cortex (DLPFC) and working memory (WM). Genetic variation in DRD2 coding for D2Rs modulates D2 signaling, but other genes in its pathway may be involved. In a previous work, using gene co-expression networks we identified 84 partner genes coregulated with DRD2 and eight single nucleotide polymorphisms (SNPs) predicting coexpression of the whole gene set in the human DLPFC [1]. These SNPs combined into a polygenic coexpression index (PCI) predicted WM performance and DLPFC activity in two independent samples of living healthy humans [1]. Here, we asked whether response to D2R targeting drugs is associated with this PCI. Thus, we investigated the interaction between WM behavioral/brain response to the D2R agonist Bromocriptine (BRO) and the PCI. [1] Pergola G, Di Carlo P, et al. (In press). Translational Psychiatry. Methods: Fifty healthy volunteers entered a double-blind, crossover, randomized, placebo-controlled fMRI study with BRO 1.25 mg and performed the N-Back WM task during the fMRI scanning session. We computed the PCI for all participants and investigated its association with WM-related behavior and brain activity using general linear models. Results: A PCI by drug interaction was significant on both DLPFC signal (right BA46, 242 voxels, F(1, 48) = 24; right BA9, 177 voxels, F(1, 48) = 19; P < .05 cluster-level FWE corrected) and behavioral scores, F(1, 46) = 4.6, P = .045, using a U-shaped quadratic model. The U-shaped relationship between the PCI and WM processing found on placebo was reversed on BRO. Furthermore, the increase in behavioral performance on BRO correlated with a decrease in BA46 activity, t(48) = −2.0, P = .049). Conclusion: The combined effect of multiple alleles on DRD2 coexpression covaried with drug response such that different allelic patterns were associated with similar responses, as in the inverted U-shaped model of WM. Thus, multiple genes and multiple allelic patterns are implicated in the inverted U-shaped dopamine/WM relationship. This relationship is reversed when individuals are administered BRO, suggesting that brain and behavioral response to this pharmacological challenge depends on a pleiotropic individual genetic background. Hence, pharmacogenomics in schizophrenia should take into account allelic patterns associated with molecular phenomena such as gene expression to predict drug response.

Transcriptome Profiling Reveals the Negative Regulation of Multiple Plant Hormone Signaling Pathways Elicited by Overexpression of C-Repeat Binding Factors.

PubMed

Li, Aixin; Zhou, Mingqi; Wei, Donghui; Chen, Hu; You, Chenjiang; Lin, Juan

2017-01-01

C-repeat binding factors (CBF) are a subfamily of AP2 transcription factors that play critical roles in the regulation of plant cold tolerance and growth in low temperature. In the present work, we sought to perform a detailed investigation into global transcriptional regulation of plant hormone signaling associated genes in transgenic plants engineered with CBF genes. RNA samples from Arabidopsis thaliana plants overexpressing two CBF genes, CBF2 and CBF3 , were subjected to Illumina HiSeq 2000 RNA sequencing (RNA-Seq). Our results showed that more than half of the hormone associated genes that were differentially expressed in CBF2 or CBF3 transgenic plants were related to auxin signal transduction and metabolism. Most of these alterations in gene expression could lead to repression of auxin signaling. Accordingly, the IAA content was significantly decreased in young tissues of plants overexpressing CBF2 and CBF3 compared with wild type. In addition, genes associated with the biosynthesis of Jasmonate (JA) and Salicylic acid (SA), as well as the signal sensing of Brassinolide (BR) and SA, were down-regulated, while genes associated with Gibberellin (GA) deactivation were up-regulated. In general, overexpression of CBF2 and CBF3 negatively affects multiple plant hormone signaling pathways in Arabidopsis . The transcriptome analysis using CBF2 and CBF3 transgenic plants provides novel and integrated insights into the interaction between CBFs and plant hormones, particularly the modulation of auxin signaling, which may contribute to the improvement of crop yields under abiotic stress via molecular engineering using CBF genes.

Transcriptome Profiling Reveals the Negative Regulation of Multiple Plant Hormone Signaling Pathways Elicited by Overexpression of C-Repeat Binding Factors

PubMed Central

Li, Aixin; Zhou, Mingqi; Wei, Donghui; Chen, Hu; You, Chenjiang; Lin, Juan

2017-01-01

C-repeat binding factors (CBF) are a subfamily of AP2 transcription factors that play critical roles in the regulation of plant cold tolerance and growth in low temperature. In the present work, we sought to perform a detailed investigation into global transcriptional regulation of plant hormone signaling associated genes in transgenic plants engineered with CBF genes. RNA samples from Arabidopsis thaliana plants overexpressing two CBF genes, CBF2 and CBF3, were subjected to Illumina HiSeq 2000 RNA sequencing (RNA-Seq). Our results showed that more than half of the hormone associated genes that were differentially expressed in CBF2 or CBF3 transgenic plants were related to auxin signal transduction and metabolism. Most of these alterations in gene expression could lead to repression of auxin signaling. Accordingly, the IAA content was significantly decreased in young tissues of plants overexpressing CBF2 and CBF3 compared with wild type. In addition, genes associated with the biosynthesis of Jasmonate (JA) and Salicylic acid (SA), as well as the signal sensing of Brassinolide (BR) and SA, were down-regulated, while genes associated with Gibberellin (GA) deactivation were up-regulated. In general, overexpression of CBF2 and CBF3 negatively affects multiple plant hormone signaling pathways in Arabidopsis. The transcriptome analysis using CBF2 and CBF3 transgenic plants provides novel and integrated insights into the interaction between CBFs and plant hormones, particularly the modulation of auxin signaling, which may contribute to the improvement of crop yields under abiotic stress via molecular engineering using CBF genes. PMID:28983312

Multivariate generalized multifactor dimensionality reduction to detect gene-gene interactions

PubMed Central

2013-01-01

Background Recently, one of the greatest challenges in genome-wide association studies is to detect gene-gene and/or gene-environment interactions for common complex human diseases. Ritchie et al. (2001) proposed multifactor dimensionality reduction (MDR) method for interaction analysis. MDR is a combinatorial approach to reduce multi-locus genotypes into high-risk and low-risk groups. Although MDR has been widely used for case-control studies with binary phenotypes, several extensions have been proposed. One of these methods, a generalized MDR (GMDR) proposed by Lou et al. (2007), allows adjusting for covariates and applying to both dichotomous and continuous phenotypes. GMDR uses the residual score of a generalized linear model of phenotypes to assign either high-risk or low-risk group, while MDR uses the ratio of cases to controls. Methods In this study, we propose multivariate GMDR, an extension of GMDR for multivariate phenotypes. Jointly analysing correlated multivariate phenotypes may have more power to detect susceptible genes and gene-gene interactions. We construct generalized estimating equations (GEE) with multivariate phenotypes to extend generalized linear models. Using the score vectors from GEE we discriminate high-risk from low-risk groups. We applied the multivariate GMDR method to the blood pressure data of the 7,546 subjects from the Korean Association Resource study: systolic blood pressure (SBP) and diastolic blood pressure (DBP). We compare the results of multivariate GMDR for SBP and DBP to the results from separate univariate GMDR for SBP and DBP, respectively. We also applied the multivariate GMDR method to the repeatedly measured hypertension status from 5,466 subjects and compared its result with those of univariate GMDR at each time point. Results Results from the univariate GMDR and multivariate GMDR in two-locus model with both blood pressures and hypertension phenotypes indicate best combinations of SNPs whose interaction has significant association with risk for high blood pressures or hypertension. Although the test balanced accuracy (BA) of multivariate analysis was not always greater than that of univariate analysis, the multivariate BAs were more stable with smaller standard deviations. Conclusions In this study, we have developed multivariate GMDR method using GEE approach. It is useful to use multivariate GMDR with correlated multiple phenotypes of interests. PMID:24565370

Interactions among genetic variants in apoptosis pathway genes, reflux symptoms, body mass index, and smoking indicate two distinct etiologic patterns of esophageal adenocarcinoma.

PubMed

Zhai, Rihong; Chen, Feng; Liu, Geoffrey; Su, Li; Kulke, Matthew H; Asomaning, Kofi; Lin, Xihong; Heist, Rebecca S; Nishioka, Norman S; Sheu, Chau-Chyun; Wain, John C; Christiani, David C

2010-05-10

Apoptosis pathway, gastroesophageal reflux symptoms (reflux), higher body mass index (BMI), and tobacco smoking have been individually associated with esophageal adenocarcinoma (EA) development. However, how multiple factors jointly affect EA risk remains unclear. In total, 305 patients with EA and 339 age- and sex-matched controls were studied. High-order interactions among reflux, BMI, smoking, and functional polymorphisms in five apoptotic genes (FAS, FASL, IL1B, TP53BP, and BAT3) were investigated by entropy-based multifactor dimensionality reduction (MDR), classification and regression tree (CART), and traditional logistic regression (LR) models. In LR analysis, reflux, BMI, and smoking were significantly associated with EA risk, with reflux as the strongest individual factor. No individual single nucleotide polymorphism was associated with EA susceptibility. However, there was a two-way interaction between IL1B + 3954C>T and reflux (P = .008). In both CART and MDR analyses, reflux was also the strongest individual factor for EA risk. In individuals with reflux symptoms, CART analysis indicated that strongest interaction was among variant genotypes of IL1B + 3954C>T and BAT3S625P, higher BMI, and smoking (odds ratio [OR], 5.76; 95% CI, 2.48 to 13.38), a finding independently found using MDR analysis. In contrast, for participants without reflux symptoms, the strongest interaction was found between higher BMI and smoking (OR, 3.27; 95% CI, 1.88 to 5.68), also echoed by entropy-based MDR analysis. Although a history of reflux is an important risk for EA, multifactor interactions also play important roles in EA risk. Gene-environment interaction patterns differ between patients with and without reflux symptoms.

Properties of genes essential for mouse development

PubMed Central

Kabir, Mitra; Barradas, Ana; Tzotzos, George T.; Hentges, Kathryn E.

2017-01-01

Essential genes are those that are critical for life. In the specific case of the mouse, they are the set of genes whose deletion means that a mouse is unable to survive after birth. As such, they are the key minimal set of genes needed for all the steps of development to produce an organism capable of life ex utero. We explored a wide range of sequence and functional features to characterise essential (lethal) and non-essential (viable) genes in mice. Experimental data curated manually identified 1301 essential genes and 3451 viable genes. Very many sequence features show highly significant differences between essential and viable mouse genes. Essential genes generally encode complex proteins, with multiple domains and many introns. These genes tend to be: long, highly expressed, old and evolutionarily conserved. These genes tend to encode ligases, transferases, phosphorylated proteins, intracellular proteins, nuclear proteins, and hubs in protein-protein interaction networks. They are involved with regulating protein-protein interactions, gene expression and metabolic processes, cell morphogenesis, cell division, cell proliferation, DNA replication, cell differentiation, DNA repair and transcription, cell differentiation and embryonic development. Viable genes tend to encode: membrane proteins or secreted proteins, and are associated with functions such as cellular communication, apoptosis, behaviour and immune response, as well as housekeeping and tissue specific functions. Viable genes are linked to transport, ion channels, signal transduction, calcium binding and lipid binding, consistent with their location in membranes and involvement with cell-cell communication. From the analysis of the composite features of essential and viable genes, we conclude that essential genes tend to be required for intracellular functions, and viable genes tend to be involved with extracellular functions and cell-cell communication. Knowledge of the features that are over-represented in essential genes allows for a deeper understanding of the functions and processes implemented during mammalian development. PMID:28562614

Structural dissection of an interaction between transcription initiation and termination factors implicated in promoter-terminator cross-talk.

PubMed

Bratkowski, Matthew; Unarta, Ilona Christy; Zhu, Lizhe; Shubbar, Murtada; Huang, Xuhui; Liu, Xin

2018-02-02

Functional cross-talk between the promoter and terminator of a gene has long been noted. Promoters and terminators are juxtaposed to form gene loops in several organisms, and gene looping is thought to be involved in transcriptional regulation. The general transcription factor IIB (TFIIB) and the C-terminal domain phosphatase Ssu72, essential factors of the transcription preinitiation complex and the mRNA processing and polyadenylation complex, respectively, are important for gene loop formation. TFIIB and Ssu72 interact both genetically and physically, but the molecular basis of this interaction is not known. Here we present a crystal structure of the core domain of TFIIB in two new conformations that differ in the relative distance and orientation of the two cyclin-like domains. The observed extraordinary conformational plasticity may underlie the binding of TFIIB to multiple transcription factors and promoter DNAs that occurs in distinct stages of transcription, including initiation, reinitiation, and gene looping. We mapped the binding interface of the TFIIB-Ssu72 complex using a series of systematic, structure-guided in vitro binding and site-specific photocross-linking assays. Our results indicate that Ssu72 competes with acidic activators for TFIIB binding and that Ssu72 disrupts an intramolecular TFIIB complex known to impede transcription initiation. We also show that the TFIIB-binding site on Ssu72 overlaps with the binding site of symplekin, a component of the mRNA processing and polyadenylation complex. We propose a hand-off model in which Ssu72 mediates a conformational transition in TFIIB, accounting for the role of Ssu72 in transcription reinitiation, gene looping, and promoter-terminator cross-talk. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Candidate-gene association study of mothers with pre-eclampsia, and their infants, analyzing 775 SNPs in 190 genes.

PubMed

Goddard, Katrina A B; Tromp, Gerard; Romero, Roberto; Olson, Jane M; Lu, Qing; Xu, Zhiying; Parimi, Neeta; Nien, Jyh Kae; Gomez, Ricardo; Behnke, Ernesto; Solari, Margarita; Espinoza, Jimmy; Santolaya, Joaquin; Chaiworapongsa, Tinnakorn; Lenk, Guy M; Volkenant, Kimberly; Anant, Madan Kumar; Salisbury, Benjamin A; Carr, Janet; Lee, Min Soeb; Vovis, Gerald F; Kuivaniemi, Helena

2007-01-01

Pre-eclampsia (PE) affects 5-7% of pregnancies in the US, and is a leading cause of maternal death and perinatal morbidity and mortality worldwide. To identify genes with a role in PE, we conducted a large-scale association study evaluating 775 SNPs in 190 candidate genes selected for a potential role in obstetrical complications. SNP discovery was performed by DNA sequencing, and genotyping was carried out in a high-throughput facility using the MassARRAY(TM) System. Women with PE (n = 394) and their offspring (n = 324) were compared with control women (n = 602) and their offspring (n = 631) from the same hospital-based population. Haplotypes were estimated for each gene using the EM algorithm, and empirical p values were obtained for a logistic regression-based score test, adjusted for significant covariates. An interaction model between maternal and offspring genotypes was also evaluated. The most significant findings for association with PE were COL1A1 (p = 0.0011) and IL1A (p = 0.0014) for the maternal genotype, and PLAUR (p = 0.0008) for the offspring genotype. Common candidate genes for PE, including MTHFR and NOS3, were not significantly associated with PE. For the interaction model, SNPs within IGF1 (p = 0.0035) and IL4R (p = 0.0036) gave the most significant results. This study is one of the most comprehensive genetic association studies of PE to date, including an evaluation of offspring genotypes that have rarely been considered in previous studies. Although we did not identify statistically significant evidence of association for any of the candidate loci evaluated here after adjusting for multiple testing using the false discovery rate, additional compelling evidence exists, including multiple SNPs with nominally significant p values in COL1A1 and the IL1A region, and previous reports of association for IL1A, to support continued interest in these genes as candidates for PE. Identification of the genetic regulators of PE may have broader implications, since women with PE are at increased risk of death from cardiovascular diseases later in life.

In Silico Enhancing M. tuberculosis Protein Interaction Networks in STRING To Predict Drug-Resistance Pathways and Pharmacological Risks.

PubMed

Mei, Suyu

2018-05-04

Bacterial protein-protein interaction (PPI) networks are significant to reveal the machinery of signal transduction and drug resistance within bacterial cells. The database STRING has collected a large number of bacterial pathogen PPI networks, but most of the data are of low quality without being experimentally or computationally validated, thus restricting its further biomedical applications. We exploit the experimental data via four solutions to enhance the quality of M. tuberculosis H37Rv (MTB) PPI networks in STRING. Computational results show that the experimental data derived jointly by two-hybrid and copurification approaches are the most reliable to train an L 2 -regularized logistic regression model for MTB PPI network validation. On the basis of the validated MTB PPI networks, we further study the three problems via breadth-first graph search algorithm: (1) discovery of MTB drug-resistance pathways through searching for the paths between known drug-target genes and drug-resistance genes, (2) choosing potential cotarget genes via searching for the critical genes located on multiple pathways, and (3) choosing essential drug-target genes via analysis of network degree distribution. In addition, we further combine the validated MTB PPI networks with human PPI networks to analyze the potential pharmacological risks of known and candidate drug-target genes from the point of view of system pharmacology. The evidence from protein structure alignment demonstrates that the drugs that act on MTB target genes could also adversely act on human signaling pathways.

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

PubMed Central

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

CHiCP: a web-based tool for the integrative and interactive visualization of promoter capture Hi-C datasets.

PubMed

Schofield, E C; Carver, T; Achuthan, P; Freire-Pritchett, P; Spivakov, M; Todd, J A; Burren, O S

2016-08-15

Promoter capture Hi-C (PCHi-C) allows the genome-wide interrogation of physical interactions between distal DNA regulatory elements and gene promoters in multiple tissue contexts. Visual integration of the resultant chromosome interaction maps with other sources of genomic annotations can provide insight into underlying regulatory mechanisms. We have developed Capture HiC Plotter (CHiCP), a web-based tool that allows interactive exploration of PCHi-C interaction maps and integration with both public and user-defined genomic datasets. CHiCP is freely accessible from www.chicp.org and supports most major HTML5 compliant web browsers. Full source code and installation instructions are available from http://github.com/D-I-L/django-chicp ob219@cam.ac.uk. © The Author 2016. Published by Oxford University Press. All rights reserved.

Phycomyces MADB interacts with MADA to form the primary photoreceptor complex for fungal phototropism.

PubMed

Sanz, Catalina; Rodríguez-Romero, Julio; Idnurm, Alexander; Christie, John M; Heitman, Joseph; Corrochano, Luis M; Eslava, Arturo P

2009-04-28

The fungus Phycomyces blakesleeanus reacts to environmental signals, including light, gravity, touch, and the presence of nearby objects, by changing the speed and direction of growth of its fruiting body (sporangiophore). Phototropism, growth toward light, shares many features in fungi and plants but the molecular mechanisms remain to be fully elucidated. Phycomyces mutants with altered phototropism were isolated approximately 40 years ago and found to have mutations in the mad genes. All of the responses to light in Phycomyces require the products of the madA and madB genes. We showed that madA encodes a protein similar to the Neurospora blue-light photoreceptor, zinc-finger protein WC-1. We show here that madB encodes a protein similar to the Neurospora zinc-finger protein WC-2. MADA and MADB interact to form a complex in yeast 2-hybrid assays and when coexpressed in E. coli, providing evidence that phototropism and other responses to light are mediated by a photoresponsive transcription factor complex. The Phycomyces genome contains 3 genes similar to wc-1, and 4 genes similar to wc-2, many of which are regulated by light in a madA or madB dependent manner. We did not detect any interactions between additional WC proteins in yeast 2-hybrid assays, which suggest that MADA and MADB form the major photoreceptor complex in Phycomyces. However, the presence of multiple wc genes in Phycomyces may enable perception across a broad range of light intensities, and may provide specialized photoreceptors for distinct photoresponses.

Enhancing crop resilience to combined abiotic and biotic stress through the dissection of physiological and molecular crosstalk

PubMed Central

Kissoudis, Christos; van de Wiel, Clemens; Visser, Richard G. F.; van der Linden, Gerard

2014-01-01

Plants growing in their natural habitats are often challenged simultaneously by multiple stress factors, both abiotic and biotic. Research has so far been limited to responses to individual stresses, and understanding of adaptation to combinatorial stress is limited, but indicative of non-additive interactions. Omics data analysis and functional characterization of individual genes has revealed a convergence of signaling pathways for abiotic and biotic stress adaptation. Taking into account that most data originate from imposition of individual stress factors, this review summarizes these findings in a physiological context, following the pathogenesis timeline and highlighting potential differential interactions occurring between abiotic and biotic stress signaling across the different cellular compartments and at the whole plant level. Potential effects of abiotic stress on resistance components such as extracellular receptor proteins, R-genes and systemic acquired resistance will be elaborated, as well as crosstalk at the levels of hormone, reactive oxygen species, and redox signaling. Breeding targets and strategies are proposed focusing on either manipulation and deployment of individual common regulators such as transcription factors or pyramiding of non- (negatively) interacting components such as R-genes with abiotic stress resistance genes. We propose that dissection of broad spectrum stress tolerance conferred by priming chemicals may provide an insight on stress cross regulation and additional candidate genes for improving crop performance under combined stress. Validation of the proposed strategies in lab and field experiments is a first step toward the goal of achieving tolerance to combinatorial stress in crops. PMID:24904607

Phycomyces MADB interacts with MADA to form the primary photoreceptor complex for fungal phototropism

PubMed Central

Sanz, Catalina; Rodríguez-Romero, Julio; Idnurm, Alexander; Christie, John M.; Heitman, Joseph; Corrochano, Luis M.; Eslava, Arturo P.

2009-01-01

The fungus Phycomyces blakesleeanus reacts to environmental signals, including light, gravity, touch, and the presence of nearby objects, by changing the speed and direction of growth of its fruiting body (sporangiophore). Phototropism, growth toward light, shares many features in fungi and plants but the molecular mechanisms remain to be fully elucidated. Phycomyces mutants with altered phototropism were isolated ≈40 years ago and found to have mutations in the mad genes. All of the responses to light in Phycomyces require the products of the madA and madB genes. We showed that madA encodes a protein similar to the Neurospora blue-light photoreceptor, zinc-finger protein WC-1. We show here that madB encodes a protein similar to the Neurospora zinc-finger protein WC-2. MADA and MADB interact to form a complex in yeast 2-hybrid assays and when coexpressed in E. coli, providing evidence that phototropism and other responses to light are mediated by a photoresponsive transcription factor complex. The Phycomyces genome contains 3 genes similar to wc-1, and 4 genes similar to wc-2, many of which are regulated by light in a madA or madB dependent manner. We did not detect any interactions between additional WC proteins in yeast 2-hybrid assays, which suggest that MADA and MADB form the major photoreceptor complex in Phycomyces. However, the presence of multiple wc genes in Phycomyces may enable perception across a broad range of light intensities, and may provide specialized photoreceptors for distinct photoresponses. PMID:19380729

Evidence for Transcript Networks Composed of Chimeric RNAs in Human Cells

PubMed Central

Borel, Christelle; Mudge, Jonathan M.; Howald, Cédric; Foissac, Sylvain; Ucla, Catherine; Chrast, Jacqueline; Ribeca, Paolo; Martin, David; Murray, Ryan R.; Yang, Xinping; Ghamsari, Lila; Lin, Chenwei; Bell, Ian; Dumais, Erica; Drenkow, Jorg; Tress, Michael L.; Gelpí, Josep Lluís; Orozco, Modesto; Valencia, Alfonso; van Berkum, Nynke L.; Lajoie, Bryan R.; Vidal, Marc; Stamatoyannopoulos, John; Batut, Philippe; Dobin, Alex; Harrow, Jennifer; Hubbard, Tim; Dekker, Job; Frankish, Adam; Salehi-Ashtiani, Kourosh; Reymond, Alexandre; Antonarakis, Stylianos E.; Guigó, Roderic; Gingeras, Thomas R.

2012-01-01

The classic organization of a gene structure has followed the Jacob and Monod bacterial gene model proposed more than 50 years ago. Since then, empirical determinations of the complexity of the transcriptomes found in yeast to human has blurred the definition and physical boundaries of genes. Using multiple analysis approaches we have characterized individual gene boundaries mapping on human chromosomes 21 and 22. Analyses of the locations of the 5′ and 3′ transcriptional termini of 492 protein coding genes revealed that for 85% of these genes the boundaries extend beyond the current annotated termini, most often connecting with exons of transcripts from other well annotated genes. The biological and evolutionary importance of these chimeric transcripts is underscored by (1) the non-random interconnections of genes involved, (2) the greater phylogenetic depth of the genes involved in many chimeric interactions, (3) the coordination of the expression of connected genes and (4) the close in vivo and three dimensional proximity of the genomic regions being transcribed and contributing to parts of the chimeric RNAs. The non-random nature of the connection of the genes involved suggest that chimeric transcripts should not be studied in isolation, but together, as an RNA network. PMID:22238572

Multiple interval QTL mapping and searching for PSTOL1 homologs associated with root morphology, biomass accumulation and phosphorus content in maize seedlings under low-P.

PubMed

Azevedo, Gabriel C; Cheavegatti-Gianotto, Adriana; Negri, Bárbara F; Hufnagel, Bárbara; E Silva, Luciano da Costa; Magalhaes, Jurandir V; Garcia, Antonio Augusto F; Lana, Ubiraci G P; de Sousa, Sylvia M; Guimaraes, Claudia T

2015-07-07

Modifications in root morphology are important strategies to maximize soil exploitation under phosphorus starvation in plants. Here, we used two multiple interval models to map QTLs related to root traits, biomass accumulation and P content in a maize RIL population cultivated in nutrient solution. In addition, we searched for putative maize homologs to PSTOL1, a gene responsible to enhance early root growth, P uptake and grain yield in rice and sorghum. Based on path analysis, root surface area was the root morphology component that most strongly contributed to total dry weight and to P content in maize seedling under low-P availability. Multiple interval mapping models for single (MIM) and multiple traits (MT-MIM) were combined and revealed 13 genomic regions significantly associated with the target traits in a complementary way. The phenotypic variances explained by all QTLs and their epistatic interactions using MT-MIM (23.4 to 35.5 %) were higher than in previous studies, and presented superior statistical power. Some of these QTLs were coincident with QTLs for root morphology traits and grain yield previously mapped, whereas others harbored ZmPSTOL candidate genes, which shared more than 55 % of amino acid sequence identity and a conserved serine/threonine kinase domain with OsPSTOL1. Additionally, four ZmPSTOL candidate genes co-localized with QTLs for root morphology, biomass accumulation and/or P content were preferentially expressed in roots of the parental lines that contributed the alleles enhancing the respective phenotypes. QTL mapping strategies adopted in this study revealed complementary results for single and multiple traits with high accuracy. Some QTLs, mainly the ones that were also associated with yield performance in other studies, can be good targets for marker-assisted selection to improve P-use efficiency in maize. Based on the co-localization with QTLs, the protein domain conservation and the coincidence of gene expression, we selected novel maize genes as putative homologs to PSTOL1 that will require further validation studies.

Identification and Correction of Additive and Multiplicative Spatial Biases in Experimental High-Throughput Screening.

PubMed

Mazoure, Bogdan; Caraus, Iurie; Nadon, Robert; Makarenkov, Vladimir

2018-06-01

Data generated by high-throughput screening (HTS) technologies are prone to spatial bias. Traditionally, bias correction methods used in HTS assume either a simple additive or, more recently, a simple multiplicative spatial bias model. These models do not, however, always provide an accurate correction of measurements in wells located at the intersection of rows and columns affected by spatial bias. The measurements in these wells depend on the nature of interaction between the involved biases. Here, we propose two novel additive and two novel multiplicative spatial bias models accounting for different types of bias interactions. We describe a statistical procedure that allows for detecting and removing different types of additive and multiplicative spatial biases from multiwell plates. We show how this procedure can be applied by analyzing data generated by the four HTS technologies (homogeneous, microorganism, cell-based, and gene expression HTS), the three high-content screening (HCS) technologies (area, intensity, and cell-count HCS), and the only small-molecule microarray technology available in the ChemBank small-molecule screening database. The proposed methods are included in the AssayCorrector program, implemented in R, and available on CRAN.

Common and specific signatures of gene expression and protein-protein interactions in autoimmune diseases.

PubMed

Tuller, T; Atar, S; Ruppin, E; Gurevich, M; Achiron, A

2013-03-01

The aim of this study is to understand intracellular regulatory mechanisms in peripheral blood mononuclear cells (PBMCs), which are either common to many autoimmune diseases or specific to some of them. We incorporated large-scale data such as protein-protein interactions, gene expression and demographical information of hundreds of patients and healthy subjects, related to six autoimmune diseases with available large-scale gene expression measurements: multiple sclerosis (MS), systemic lupus erythematosus (SLE), juvenile rheumatoid arthritis (JRA), Crohn's disease (CD), ulcerative colitis (UC) and type 1 diabetes (T1D). These data were analyzed concurrently by statistical and systems biology approaches tailored for this purpose. We found that chemokines such as CXCL1-3, 5, 6 and the interleukin (IL) IL8 tend to be differentially expressed in PBMCs of patients with the analyzed autoimmune diseases. In addition, the anti-apoptotic gene BCL3, interferon-γ (IFNG), and the vitamin D receptor (VDR) gene physically interact with significantly many genes that tend to be differentially expressed in PBMCs of patients with the analyzed autoimmune diseases. In general, similar cellular processes tend to be differentially expressed in PBMC in the analyzed autoimmune diseases. Specifically, the cellular processes related to cell proliferation (for example, epidermal growth factor, platelet-derived growth factor, nuclear factor-κB, Wnt/β-catenin signaling, stress-activated protein kinase c-Jun NH2-terminal kinase), inflammatory response (for example, interleukins IL2 and IL6, the cytokine granulocyte-macrophage colony-stimulating factor and the B-cell receptor), general signaling cascades (for example, mitogen-activated protein kinase, extracellular signal-regulated kinase, p38 and TRK) and apoptosis are activated in most of the analyzed autoimmune diseases. However, our results suggest that in each of the analyzed diseases, apoptosis and chemotaxis are activated via different subsignaling pathways. Analyses of the expression levels of dozens of genes and the protein-protein interactions among them demonstrated that CD and UC have relatively similar gene expression signatures, whereas the gene expression signatures of T1D and JRA relatively differ from the signatures of the other autoimmune diseases. These diseases are the only ones activated via the Fcɛ pathway. The relevant genes and pathways reported in this study are discussed at length, and may be helpful in the diagnoses and understanding of autoimmunity and/or specific autoimmune diseases.

Uptake, Results, and Outcomes of Germline Multiple-Gene Sequencing After Diagnosis of Breast Cancer.

PubMed

Kurian, Allison W; Ward, Kevin C; Hamilton, Ann S; Deapen, Dennis M; Abrahamse, Paul; Bondarenko, Irina; Li, Yun; Hawley, Sarah T; Morrow, Monica; Jagsi, Reshma; Katz, Steven J

2018-05-10

Low-cost sequencing of multiple genes is increasingly available for cancer risk assessment. Little is known about uptake or outcomes of multiple-gene sequencing after breast cancer diagnosis in community practice. To examine the effect of multiple-gene sequencing on the experience and treatment outcomes for patients with breast cancer. For this population-based retrospective cohort study, patients with breast cancer diagnosed from January 2013 to December 2015 and accrued from SEER registries across Georgia and in Los Angeles, California, were surveyed (n = 5080, response rate = 70%). Responses were merged with SEER data and results of clinical genetic tests, either BRCA1 and BRCA2 (BRCA1/2) sequencing only or including additional other genes (multiple-gene sequencing), provided by 4 laboratories. Type of testing (multiple-gene sequencing vs BRCA1/2-only sequencing), test results (negative, variant of unknown significance, or pathogenic variant), patient experiences with testing (timing of testing, who discussed results), and treatment (strength of patient consideration of, and surgeon recommendation for, prophylactic mastectomy), and prophylactic mastectomy receipt. We defined a patient subgroup with higher pretest risk of carrying a pathogenic variant according to practice guidelines. Among 5026 patients (mean [SD] age, 59.9 [10.7]), 1316 (26.2%) were linked to genetic results from any laboratory. Multiple-gene sequencing increasingly replaced BRCA1/2-only testing over time: in 2013, the rate of multiple-gene sequencing was 25.6% and BRCA1/2-only testing, 74.4%;in 2015 the rate of multiple-gene sequencing was 66.5% and BRCA1/2-only testing, 33.5%. Multiple-gene sequencing was more often ordered by genetic counselors (multiple-gene sequencing, 25.5% and BRCA1/2-only testing, 15.3%) and delayed until after surgery (multiple-gene sequencing, 32.5% and BRCA1/2-only testing, 19.9%). Multiple-gene sequencing substantially increased rate of detection of any pathogenic variant (multiple-gene sequencing: higher-risk patients, 12%; average-risk patients, 4.2% and BRCA1/2-only testing: higher-risk patients, 7.8%; average-risk patients, 2.2%) and variants of uncertain significance, especially in minorities (multiple-gene sequencing: white patients, 23.7%; black patients, 44.5%; and Asian patients, 50.9% and BRCA1/2-only testing: white patients, 2.2%; black patients, 5.6%; and Asian patients, 0%). Multiple-gene sequencing was not associated with an increase in the rate of prophylactic mastectomy use, which was highest with pathogenic variants in BRCA1/2 (BRCA1/2, 79.0%; other pathogenic variant, 37.6%; variant of uncertain significance, 30.2%; negative, 35.3%). Multiple-gene sequencing rapidly replaced BRCA1/2-only testing for patients with breast cancer in the community and enabled 2-fold higher detection of clinically relevant pathogenic variants without an associated increase in prophylactic mastectomy. However, important targets for improvement in the clinical utility of multiple-gene sequencing include postsurgical delay and racial/ethnic disparity in variants of uncertain significance.

Massive reshaping of genome-nuclear lamina interactions during oncogene-induced senescence.

PubMed

Lenain, Christelle; de Graaf, Carolyn A; Pagie, Ludo; Visser, Nils L; de Haas, Marcel; de Vries, Sandra S; Peric-Hupkes, Daniel; van Steensel, Bas; Peeper, Daniel S

2017-10-01

Cellular senescence is a mechanism that virtually irreversibly suppresses the proliferative capacity of cells in response to various stress signals. This includes the expression of activated oncogenes, which causes Oncogene-Induced Senescence (OIS). A body of evidence points to the involvement in OIS of chromatin reorganization, including the formation of senescence-associated heterochromatic foci (SAHF). The nuclear lamina (NL) is an important contributor to genome organization and has been implicated in cellular senescence and organismal aging. It interacts with multiple regions of the genome called lamina-associated domains (LADs). Some LADs are cell-type specific, whereas others are conserved between cell types and are referred to as constitutive LADs (cLADs). Here, we used DamID to investigate the changes in genome-NL interactions in a model of OIS triggered by the expression of the common BRAF V600E oncogene. We found that OIS cells lose most of their cLADS, suggesting the loss of a specific mechanism that targets cLADs to the NL. In addition, multiple genes relocated to the NL. Unexpectedly, they were not repressed, implying the abrogation of the repressive activity of the NL during OIS. Finally, OIS cells displayed an increased association of telomeres with the NL. Our study reveals that senescent cells acquire a new type of LAD organization and suggests the existence of as yet unknown mechanisms that tether cLADs to the NL and repress gene expression at the NL. © 2017 Lenain et al.; Published by Cold Spring Harbor Laboratory Press.

From neurodevelopment to neurodegeneration: the interaction of neurofibromin and valosin-containing protein/p97 in regulation of dendritic spine formation.

PubMed

Hsueh, Yi-Ping

2012-03-26

Both Neurofibromatosis type I (NF1) and inclusion body myopathy with Paget's disease of bone and frontotemporal dementia (IBMPFD) are autosomal dominant genetic disorders. These two diseases are fully penetrant but with high heterogeneity in phenotypes, suggesting the involvement of genetic modifiers in modulating patients' phenotypes. Although NF1 is recognized as a developmental disorder and IBMPFD is associated with degeneration of multiple tissues, a recent study discovered the direct protein interaction between neurofibromin, the protein product of the NF1 gene, and VCP/p97, encoded by the causative gene of IBMPFD. Both NF1 and VCP/p97 are critical for dendritic spine formation, which provides the cellular mechanism explaining the cognitive deficits and dementia found in patients. Moreover, disruption of the interaction between neurofibromin and VCP impairs dendritic spinogenesis. Neurofibromin likely influences multiple downstream pathways to control dendritic spinogenesis. One is to activate the protein kinase A pathway to initiate dendritic spine formation; another is to regulate the synaptic distribution of VCP and control the activity of VCP in dendritic spinogenesis. Since neurofibromin and VCP/p97 also regulate cell growth and bone metabolism, the understanding of neurofibromin and VCP/p97 in neurons may be applied to study of cancer and bone. Statin treatment rescues the spine defects caused by VCP deficiency, suggesting the potential role of statin in clinical treatment for these two diseases.