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

PubMed

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

2017-09-05

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

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

PubMed Central

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

2014-01-01

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

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

PubMed

Larson, Nicholas B; Schaid, Daniel J

2013-11-01

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

Global Mapping of the Yeast Genetic Interaction Network

NASA Astrophysics Data System (ADS)

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

2004-02-01

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

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…

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

PubMed

Amato, Roberto; Pinelli, Michele; D'Andrea, Daniel; Miele, Gennaro; Nicodemi, Mario; Raiconi, Giancarlo; Cocozza, Sergio

2010-01-05

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

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

PubMed

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

2007-10-04

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

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

PubMed Central

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

2000-01-01

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

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

DOE PAGES

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

2016-01-19

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

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

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

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

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

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

PubMed Central

2010-01-01

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

Combining research approaches to advance our understanding of drug addiction.

PubMed

van den Bree, Marianne B M

2005-04-01

Drug addiction is a complex behavior, likely to be influenced by various genes, environmental factors, and gene-gene and gene-environment interactions. Various aspects of addiction are studied by different disciplines. Animal studies are increasing insight into brain regions and genes associated with addiction. Epidemiologic studies are establishing the factors increasing risk for initiation and continuation of substance use. Twin and adoption studies are increasing our understanding of the complex mechanisms involved in substance use, including comorbidity and gene environment interaction. Finally, molecular genetic studies in humans are starting to yield some converging findings. It is argued and illustrated with examples that greater awareness of progress in other disciplines can speed up our understanding of the complex processes involved in addiction. This should help our ability to identify who is at increased risk of becoming addicted and the development of prevention and intervention strategies targeted at an individual's specific needs.

Juxtaposed Polycomb complexes co-regulate vertebral identity.

PubMed

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

2006-12-01

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

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.

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

PubMed Central

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

2014-01-01

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

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

PubMed Central

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

2014-01-01

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

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-06-04

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

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

PubMed

Lee, Woojoo; Sjölander, Arvid; Pawitan, Yudi

2016-07-01

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

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

PubMed

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

2013-01-01

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

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

PubMed Central

Witzmann, Frank A.; Rhodes, Simon J.

2013-01-01

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

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.

Learning contextual gene set interaction networks of cancer with condition specificity

PubMed Central

2013-01-01

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

Gene-gene and gene-environment interactions defining lipid-related traits.

PubMed

Ordovás, José M; Robertson, Ruairi; Cléirigh, Ellen Ní

2011-04-01

Steps towards reducing chronic disease progression are continuously being taken through the form of genomic research. Studies over the last year have highlighted more and more polymorphisms, pathways and interactions responsible for metabolic disorders such as cardiovascular disease, obesity and dyslipidemia. Many of these chronic illnesses can be partially blamed by altered lipid metabolism, combined with individual genetic components. Critical evaluation and comparison of these recent studies is essential in order to comprehend the results, conclusions and future prospects in the field of genomics as a whole. Recent literature elucidates significant gene--diet and gene--environment interactions resulting in altered lipid metabolism, inflammation and other metabolic imbalances leading to cardiovascular disease and obesity. Epigenetic and epistatic interactions are now becoming more significantly associated with such disorders, as genomic research digs deeper into the complex nature of genetic individuality and heritability. The vast array of data collected from genome-wide association studies must now be empowered and explored through more complex interaction studies, using standardized methods and larger sample sizes. In doing so the etiology of chronic disease progression will be further understood.

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

PubMed Central

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

2014-01-01

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

Epistasis-list.org: A Curated Database of Gene-Gene and Gene-Environment Interactions in Human Epidemiology

EPA Science Inventory

The field of human genetics has experienced a paradigm shift in that common diseases are now thought to be due to the complex interactions among numerous genetic and environmental factors. This paradigm shift has prompted the development of myriad novel methods to detect such int...

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

ERIC Educational Resources Information Center

Winham, Stacey J.; Biernacka, Joanna M.

2013-01-01

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

Quantitative genetic-interaction mapping in mammalian cells

PubMed Central

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

2013-01-01

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

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.

A divalent interaction between HPS1 and HPS4 is required for the formation of the biogenesis of lysosome-related organelle complex-3 (BLOC-3).

PubMed

Carmona-Rivera, Carmelo; Simeonov, Dimitre R; Cardillo, Nicholas D; Gahl, William A; Cadilla, Carmen L

2013-03-01

Hermansky-Pudlak syndrome (HPS) is a group of rare autosomal recessive disorders characterized by oculocutaneous albinism, a bleeding tendency, and sporadic pulmonary fibrosis, granulomatous colitis or infections. Nine HPS-causing genes have been identified in humans. HPS-1 is the most severe subtype with a prevalence of ~1/1800 in northwest Puerto Rico due to a founder mutation in the HPS1 gene. Mutations in HPS genes affect the biogenesis of lysosome-related organelles such as melanosomes in melanocytes and platelet dense granules. Two of these genes (HPS1 and HPS4) encode the HPS1 and HPS4 proteins, which assemble to form a complex known as Biogenesis of Lysosome-related Organelle Complex 3 (BLOC-3). We report the identification of the interacting regions in HPS1 and HPS4 required for the formation of this complex. Two regions in HPS1, spanning amino acids 1-249 and 506-700 are required for binding to HPS4; the middle portion of HPS1 (residues 250-505) is not required for this interaction. Further interaction studies showed that the N-termini of HPS1 and HPS4 interact with each other and that a discrete region of HPS4 (residues 340-528) interacts with both the N- and C-termini of the HPS1 protein. Several missense mutations found in HPS-1 patients did not affect interaction with HPS4, but some mutations involving regions interacting with HPS4 caused instability of HPS1. These observations extend our understanding of BLOC-3 assembly and represent an important first step in the identification of domains responsible for the biogenesis of lysosome-related organelles. Copyright © 2012 Elsevier B.V. All rights reserved.

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.

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

PubMed

Özgür, Arzucan; Hur, Junguk; He, Yongqun

2016-01-01

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

Adenovirus Small E1A Employs the Lysine Acetylases p300/CBP and Tumor Suppressor Rb to Repress Select Host Genes and Promote Productive Virus Infection

PubMed Central

Ferrari, Roberto; Gou, Dawei; Jawdekar, Gauri; Johnson, Sarah A.; Nava, Miguel; Su, Trent; Yousef, Ahmed F.; Zemke, Nathan R.; Pellegrini, Matteo; Kurdistani, Siavash K.; Berk, Arnold J.

2015-01-01

SUMMARY Oncogenic transformation by adenovirus small e1a depends on simultaneous interactions with the host lysine acetylases p300/CBP and the tumor suppressor RB. How these interactions influence cellular gene expression remains unclear. We find that e1a displaces RBs from E2F transcription factors and promotes p300 acetylation of RB1 K873/K874 to lock it into a repressing conformation that interacts with repressive chromatin-modifying enzymes. These repressing p300-e1a-RB1 complexes specifically interact with host genes that have unusually high p300 association within the gene body. The TGFβ-, TNF-, and interleukin-signaling pathway components are enriched among such p300-targeted genes. The p300-e1a-RB1 complex condenses chromatin in a manner dependent on HDAC activity, p300 lysine acetylase activity, the p300 bromodomain, and RB K873/K874 and e1a K239 acetylation to repress host genes that would otherwise inhibit productive virus infection. Thus, adenovirus employs e1a to repress host genes that interfere with viral replication. PMID:25525796

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.

A novel gene, MdSSK1, as a component of the SCF complex rather than MdSBP1 can mediate the ubiquitination of S-RNase in apple.

PubMed

Yuan, Hui; Meng, Dong; Gu, Zhaoyu; Li, Wei; Wang, Aide; Yang, Qing; Zhu, Yuandi; Li, Tianzhong

2014-07-01

As a core factor in S-RNase-based gametophytic self-incompatibility (GSI), the SCF (SKP1-Cullin1-F-box-Rbx1) complex (including pollen determinant SLF, S-locus-F-box) functions as an E3 ubiquitin ligase on non-self S-RNase. The SCF complex is formed by SKP1 bridging between SLF, CUL1, and Rbx1; however, it is not known whether an SCF complex lacking SKP1 can mediate the ubiquitination of S-RNase. Three SKP1-like genes from pollen were cloned based on the structural features of the SLF-interacting-SKP1-like (SSK) gene and the 'Golden Delicious' apple genome. These genes have a motif of five amino acids following the standard 'WAFE' at the C terminal and, in addition, contain eight sheets and two helices. All three genes were expressed exclusively in pollen. In the yeast two-hybrid and pull-down assays only one was found to interact with MdSFBB and MdCUL1, suggesting it is the SLF-interacting SKP1-like gene in apple which was named MdSSK1. In vitro experiments using MdSSK1, S2-MdSFBB1 (S2-Malus domestica S-locus-F-box brother) and MdCUL1 proteins incubated with S 2-RNase and ubiquitin revealed that the SCF complex ubiquitinylates S-RNase in vitro, while MdSBP1 (Malus domestica S-RNase binding protein 1) could not functionally replace MdSSK1 in the SCF complex in ubiquitinylating S-RNase. According to the above experiments, MdSBP1 is probably the only factor responsible for recognition with S-RNase, while not a component of the SCF complex, and an SCF complex containing MdSSK1 is required for mediating the ubiquitination of S-RNase. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Nutrigenetics and prostate cancer: 2011 and beyond.

PubMed

Yuan, Yinan; Ferguson, Lynnette R

2011-01-01

Prostate cancer runs in families and shows a clear dietary involvement. Until recently, the key risk gene(s) have proved elusive. We summarise current understandings of nutrient-gene interactions in prostate cancer risk and progression. A MEDLINE-based literature search was conducted. Hypothesis-directed candidate gene approaches provide plausible, albeit statistically weak, nutrient-gene interactions. These are based on early understandings of factors likely to impact on carcinogenesis, including both nutrient and genetic effects on androgen biosynthesis and action, xenobiotic metabolism, DNA damage and DNA repair. Non-hypothesis-directed genome-wide association studies provide much stronger evidence for other genes, not hitherto suspected for involvement. Although only a few of these have been formally tested for dietary associations in well-designed epidemiologic studies, the nature of many of the genes suggests that their activity may be regulated by nutrients. These effects may not only be relevant to prostate cancer susceptibility, but also to disease progression. It will be important to move beyond studying single nucleotide polymorphisms, into more complex chromosomal rearrangements and to epigenetic changes. For future progress, large international cohorts will not only need to provide proof of individual nutrient-gene interactions, but also to relate these to more complex nutrient-gene-gene interactions, as parts of pathways. Bioinformatics and biostatistics will be increasingly important tools in nutrigenetic studies beyond 2011. Copyright © 2011 S. Karger AG, Basel.

Markov Logic Networks in the Analysis of Genetic Data

PubMed Central

Sakhanenko, Nikita A.

2010-01-01

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

Transitions from mono- to co- to tri-culture uniquely affect gene expression in breast cancer, stromal, and immune compartments.

PubMed

Regier, Mary C; Maccoux, Lindsey J; Weinberger, Emma M; Regehr, Keil J; Berry, Scott M; Beebe, David J; Alarid, Elaine T

2016-08-01

Heterotypic interactions in cancer microenvironments play important roles in disease initiation, progression, and spread. Co-culture is the predominant approach used in dissecting paracrine interactions between tumor and stromal cells, but functional results from simple co-cultures frequently fail to correlate to in vivo conditions. Though complex heterotypic in vitro models have improved functional relevance, there is little systematic knowledge of how multi-culture parameters influence this recapitulation. We therefore have employed a more iterative approach to investigate the influence of increasing model complexity; increased heterotypic complexity specifically. Here we describe how the compartmentalized and microscale elements of our multi-culture device allowed us to obtain gene expression data from one cell type at a time in a heterotypic culture where cells communicated through paracrine interactions. With our device we generated a large dataset comprised of cell type specific gene-expression patterns for cultures of increasing complexity (three cell types in mono-, co-, or tri-culture) not readily accessible in other systems. Principal component analysis indicated that gene expression was changed in co-culture but was often more strongly altered in tri-culture as compared to mono-culture. Our analysis revealed that cell type identity and the complexity around it (mono-, co-, or tri-culture) influence gene regulation. We also observed evidence of complementary regulation between cell types in the same heterotypic culture. Here we demonstrate the utility of our platform in providing insight into how tumor and stromal cells respond to microenvironments of varying complexities highlighting the expanding importance of heterotypic cultures that go beyond conventional co-culture.

Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

PubMed

Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia

2015-06-01

To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modeling transcriptional networks regulating secondary growth and wood formation in forest trees

Treesearch

Lijun Liu; Vladimir Filkov; Andrew Groover

2013-01-01

The complex interactions among the genes that underlie a biological process can be modeled and presented as a transcriptional network, in which genes (nodes) and their interactions (edges) are shown in a graphical form similar to a wiring diagram. A large number of genes have been identified that are expressed during the radial woody growth of tree stems (secondary...

MEDIATOR25 Acts as an Integrative Hub for the Regulation of Jasmonate-Responsive Gene Expression in Arabidopsis1[C][W

PubMed Central

Çevik, Volkan; Kidd, Brendan N.; Zhang, Peijun; Hill, Claire; Kiddle, Steve; Denby, Katherine J.; Holub, Eric B.; Cahill, David M.; Manners, John M.; Schenk, Peer M.; Beynon, Jim; Kazan, Kemal

2012-01-01

The PHYTOCHROME AND FLOWERING TIME1 gene encoding the MEDIATOR25 (MED25) subunit of the eukaryotic Mediator complex is a positive regulator of jasmonate (JA)-responsive gene expression in Arabidopsis (Arabidopsis thaliana). Based on the function of the Mediator complex as a bridge between DNA-bound transcriptional activators and the RNA polymerase II complex, MED25 has been hypothesized to function in association with transcriptional regulators of the JA pathway. However, it is currently not known mechanistically how MED25 functions to regulate JA-responsive gene expression. In this study, we show that MED25 physically interacts with several key transcriptional regulators of the JA signaling pathway, including the APETALA2 (AP2)/ETHYLENE RESPONSE FACTOR (ERF) transcription factors OCTADECANOID-RESPONSIVE ARABIDOPSIS AP2/ERF59 and ERF1 as well as the master regulator MYC2. Physical interaction detected between MED25 and four group IX AP2/ERF transcription factors was shown to require the activator interaction domain of MED25 as well as the recently discovered Conserved Motif IX-1/EDLL transcription activation motif of MED25-interacting AP2/ERFs. Using transcriptional activation experiments, we also show that OCTADECANOID-RESPONSIVE ARABIDOPSIS AP2/ERF59- and ERF1-dependent activation of PLANT DEFENSIN1.2 as well as MYC2-dependent activation of VEGETATIVE STORAGE PROTEIN1 requires a functional MED25. In addition, MED25 is required for MYC2-dependent repression of pathogen defense genes. These results suggest an important role for MED25 as an integrative hub within the Mediator complex during the regulation of JA-associated gene expression. PMID:22822211

From Genes to Networks: Characterizing Gene-Regulatory Interactions in Plants.

PubMed

Kaufmann, Kerstin; Chen, Dijun

2017-01-01

Plants, like other eukaryotes, have evolved complex mechanisms to coordinate gene expression during development, environmental response, and cellular homeostasis. Transcription factors (TFs), accompanied by basic cofactors and posttranscriptional regulators, are key players in gene-regulatory networks (GRNs). The coordinated control of gene activity is achieved by the interplay of these factors and by physical interactions between TFs and DNA. Here, we will briefly outline recent technological progress made to elucidate GRNs in plants. We will focus on techniques that allow us to characterize physical interactions in GRNs in plants and to analyze their regulatory consequences. Targeted manipulation allows us to test the relevance of specific gene-regulatory interactions. The combination of genome-wide experimental approaches with mathematical modeling allows us to get deeper insights into key-regulatory interactions and combinatorial control of important processes in plants.

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

PubMed

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

2018-05-28

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

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

PubMed Central

Malashchuk, Igor; Lajoie, Brian R.; Mardaryev, Andrei N.; Gdula, Michal R.; Sharov, Andrey A.; Kohwi-Shigematsu, Terumi; Fessing, Michael Y.

2017-01-01

Mammalian genomes contain several dozens of large (>0.5 Mbp) lineage-specific gene loci harbouring functionally related genes. However, spatial chromatin folding, organization of the enhancer-promoter networks and their relevance to Topologically Associating Domains (TADs) in these loci remain poorly understood. TADs are principle units of the genome folding and represents the DNA regions within which DNA interacts more frequently and less frequently across the TAD boundary. Here, we used Chromatin Conformation Capture Carbon Copy (5C) technology to characterize spatial chromatin interaction network in the 3.1 Mb Epidermal Differentiation Complex (EDC) locus harbouring 61 functionally related genes that show lineage-specific activation during terminal keratinocyte differentiation in the epidermis. 5C data validated by 3D-FISH demonstrate that the EDC locus is organized into several TADs showing distinct lineage-specific chromatin interaction networks based on their transcription activity and the gene-rich or gene-poor status. Correlation of the 5C results with genome-wide studies for enhancer-specific histone modifications (H3K4me1 and H3K27ac) revealed that the majority of spatial chromatin interactions that involves the gene-rich TADs at the EDC locus in keratinocytes include both intra- and inter-TAD interaction networks, connecting gene promoters and enhancers. Compared to thymocytes in which the EDC locus is mostly transcriptionally inactive, these interactions were found to be keratinocyte-specific. In keratinocytes, the promoter-enhancer anchoring regions in the gene-rich transcriptionally active TADs are enriched for the binding of chromatin architectural proteins CTCF, Rad21 and chromatin remodeler Brg1. In contrast to gene-rich TADs, gene-poor TADs show preferential spatial contacts with each other, do not contain active enhancers and show decreased binding of CTCF, Rad21 and Brg1 in keratinocytes. Thus, spatial interactions between gene promoters and enhancers at the multi-TAD EDC locus in skin epithelial cells are cell type-specific and involve extensive contacts within TADs as well as between different gene-rich TADs, forming the framework for lineage-specific transcription. PMID:28863138

Adenovirus small E1A employs the lysine acetylases p300/CBP and tumor suppressor Rb to repress select host genes and promote productive virus infection.

PubMed

Ferrari, Roberto; Gou, Dawei; Jawdekar, Gauri; Johnson, Sarah A; Nava, Miguel; Su, Trent; Yousef, Ahmed F; Zemke, Nathan R; Pellegrini, Matteo; Kurdistani, Siavash K; Berk, Arnold J

2014-11-12

Oncogenic transformation by adenovirus small e1a depends on simultaneous interactions with the host lysine acetylases p300/CBP and the tumor suppressor RB. How these interactions influence cellular gene expression remains unclear. We find that e1a displaces RBs from E2F transcription factors and promotes p300 acetylation of RB1 K873/K874 to lock it into a repressing conformation that interacts with repressive chromatin-modifying enzymes. These repressing p300-e1a-RB1 complexes specifically interact with host genes that have unusually high p300 association within the gene body. The TGF-β, TNF-, and interleukin-signaling pathway components are enriched among such p300-targeted genes. The p300-e1a-RB1 complex condenses chromatin in a manner dependent on HDAC activity, p300 lysine acetylase activity, the p300 bromodomain, and RB K873/K874 and e1a K239 acetylation to repress host genes that would otherwise inhibit productive virus infection. Thus, adenovirus employs e1a to repress host genes that interfere with viral replication. Copyright © 2014 Elsevier Inc. All rights reserved.

Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns.

PubMed

Lezon, Timothy R; Banavar, Jayanth R; Cieplak, Marek; Maritan, Amos; Fedoroff, Nina V

2006-12-12

We describe a method based on the principle of entropy maximization to identify the gene interaction network with the highest probability of giving rise to experimentally observed transcript profiles. In its simplest form, the method yields the pairwise gene interaction network, but it can also be extended to deduce higher-order interactions. Analysis of microarray data from genes in Saccharomyces cerevisiae chemostat cultures exhibiting energy metabolic oscillations identifies a gene interaction network that reflects the intracellular communication pathways that adjust cellular metabolic activity and cell division to the limiting nutrient conditions that trigger metabolic oscillations. The success of the present approach in extracting meaningful genetic connections suggests that the maximum entropy principle is a useful concept for understanding living systems, as it is for other complex, nonequilibrium systems.

Genetic interactions within inositol-related pathways are associated with longitudinal changes in ventricle size

PubMed Central

Koran, Mary Ellen I.; Hohman, Timothy J.; Meda, Shashwath A.; Thornton-Wells, Tricia A.

2013-01-01

The genetic etiology of late onset Alzheimer disease (LOAD) has proven complex, involving clinical and genetic heterogeneity and gene-gene interactions. Recent genome wide association studies (GWAS) in LOAD have led to the discovery of novel genetic risk factors; however, the investigation of gene-gene interactions has been limited. Conventional genetic studies often use binary disease status as the primary phenotype, but for complex brain-based diseases, neuroimaging data can serve as quantitative endophenotypes that correlate with disease status and closely reflect pathological changes. In the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, we tested for association of genetic interactions with longitudinal MRI measurements of the inferior lateral ventricles (ILVs), which have repeatedly shown a relationship to LOAD status and progression. We performed linear regression to evaluate the ability of pathway-derived SNP-SNP pairs to predict the slope of change in volume of the ILVs. After Bonferroni correction, we identified four significant interactions in the right ILV (RILV) corresponding to gene-gene pairs SYNJ2-PI4KA, PARD3-MYH2, PDE3A-ABHD12B and OR2L13-PRKG1 and one significant interaction in the left ILV (LILV) corresponding to SYNJ2-PI4KA. The SNP-SNP interaction corresponding to SYNJ2-PI4KA was identical in the RILV and LILV and was the most significant interaction in each (RILV: p=9.10×10−12; LILV: p=8.20×10−13). Both genes belong to the inositol phosphate signaling pathway which has been previously associated with neurodegeneration in AD and we discuss the possibility that perturbation of this pathway results in a down-regulation of the Akt cell survival pathway and, thereby, decreased neuronal survival, as reflected by increased volume of the ventricles. PMID:24077433

Structural dissection of an interaction between transcription initiation and termination factors implicated in promoter-terminator cross-talk.

PubMed

Bratkowski, Matthew; Unarta, Ilona Christy; Zhu, Lizhe; Shubbar, Murtada; Huang, Xuhui; Liu, Xin

2018-02-02

Functional cross-talk between the promoter and terminator of a gene has long been noted. Promoters and terminators are juxtaposed to form gene loops in several organisms, and gene looping is thought to be involved in transcriptional regulation. The general transcription factor IIB (TFIIB) and the C-terminal domain phosphatase Ssu72, essential factors of the transcription preinitiation complex and the mRNA processing and polyadenylation complex, respectively, are important for gene loop formation. TFIIB and Ssu72 interact both genetically and physically, but the molecular basis of this interaction is not known. Here we present a crystal structure of the core domain of TFIIB in two new conformations that differ in the relative distance and orientation of the two cyclin-like domains. The observed extraordinary conformational plasticity may underlie the binding of TFIIB to multiple transcription factors and promoter DNAs that occurs in distinct stages of transcription, including initiation, reinitiation, and gene looping. We mapped the binding interface of the TFIIB-Ssu72 complex using a series of systematic, structure-guided in vitro binding and site-specific photocross-linking assays. Our results indicate that Ssu72 competes with acidic activators for TFIIB binding and that Ssu72 disrupts an intramolecular TFIIB complex known to impede transcription initiation. We also show that the TFIIB-binding site on Ssu72 overlaps with the binding site of symplekin, a component of the mRNA processing and polyadenylation complex. We propose a hand-off model in which Ssu72 mediates a conformational transition in TFIIB, accounting for the role of Ssu72 in transcription reinitiation, gene looping, and promoter-terminator cross-talk. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

Genome-Wide Localization Study of Yeast Pex11 Identifies Peroxisome–Mitochondria Interactions through the ERMES Complex

PubMed Central

Mattiazzi Ušaj, M.; Brložnik, M.; Kaferle, P.; Žitnik, M.; Wolinski, H.; Leitner, F.; Kohlwein, S.D.; Zupan, B.; Petrovič, U.

2015-01-01

Pex11 is a peroxin that regulates the number of peroxisomes in eukaryotic cells. Recently, it was found that a mutation in one of the three mammalian paralogs, PEX11β, results in a neurological disorder. The molecular function of Pex11, however, is not known. Saccharomyces cerevisiae Pex11 has been shown to recruit to peroxisomes the mitochondrial fission machinery, thus enabling proliferation of peroxisomes. This process is essential for efficient fatty acid β-oxidation. In this study, we used high-content microscopy on a genome-wide scale to determine the subcellular localization pattern of yeast Pex11 in all non-essential gene deletion mutants, as well as in temperature-sensitive essential gene mutants. Pex11 localization and morphology of peroxisomes was profoundly affected by mutations in 104 different genes that were functionally classified. A group of genes encompassing MDM10, MDM12 and MDM34 that encode the mitochondrial and cytosolic components of the ERMES complex was analyzed in greater detail. Deletion of these genes caused a specifically altered Pex11 localization pattern, whereas deletion of MMM1, the gene encoding the fourth, endoplasmic-reticulum-associated component of the complex, did not result in an altered Pex11 localization or peroxisome morphology phenotype. Moreover, we found that Pex11 and Mdm34 physically interact and that Pex11 plays a role in establishing the contact sites between peroxisomes and mitochondria through the ERMES complex. Based on these results, we propose that the mitochondrial/cytosolic components of the ERMES complex establish a direct interaction between mitochondria and peroxisomes through Pex11. PMID:25769804

Transitions from mono- to co- to tri-culture uniquely affect gene expression in breast cancer, stromal, and immune compartments

PubMed Central

Weinberger, Emma M.; Regehr, Keil J.; Berry, Scott M.; Beebe, David J.; Alarid, Elaine T.

2016-01-01

Heterotypic interactions in cancer microenvironments play important roles in disease initiation, progression, and spread. Co-culture is the predominant approach used in dissecting paracrine interactions between tumor and stromal cells, but functional results from simple co-cultures frequently fail to correlate to in vivo conditions. Though complex heterotypic in vitro models have improved functional relevance, there is little systematic knowledge of how multi-culture parameters influence this recapitulation. We therefore have employed a more iterative approach to investigate the influence of increasing model complexity; increased heterotypic complexity specifically. Here we describe how the compartmentalized and microscale elements of our multi-culture device allowed us to obtain gene expression data from one cell type at a time in a heterotypic culture where cells communicated through paracrine interactions. With our device we generated a large dataset comprised of cell type specific gene-expression patterns for cultures of increasing complexity (three cell types in mono-, co-, or tri-culture) not readily accessible in other systems. Principal component analysis indicated that gene expression was changed in co-culture but was often more strongly altered in tri-culture as compared to mono-culture. Our analysis revealed that cell type identity and the complexity around it (mono-, co-, or tri-culture) influence gene regulation. We also observed evidence of complementary regulation between cell types in the same heterotypic culture. Here we demonstrate the utility of our platform in providing insight into how tumor and stromal cells respond to microenvironments of varying complexities highlighting the expanding importance of heterotypic cultures that go beyond conventional co-culture. PMID:27432323

Mediator complex cooperatively regulates transcription of retinoic acid target genes with Polycomb Repressive Complex 2 during neuronal differentiation.

PubMed

Fukasawa, Rikiya; Iida, Satoshi; Tsutsui, Taiki; Hirose, Yutaka; Ohkuma, Yoshiaki

2015-11-01

The Mediator complex (Mediator) plays key roles in transcription and functions as the nexus for integration of various transcriptional signals. Previously, we screened for Mediator cyclin-dependent kinase (CDK)-interacting factors and identified three proteins related to chromatin regulation. One of them, SUZ12 is required for both stability and activity of Polycomb Repressive Complex 2 (PRC2). PRC2 primarily suppresses gene expression through histone H3 lysine 27 trimethylation, resulting in stem cell maintenance and differentiation; perturbation of this process leads to oncogenesis. Recent work showed that Mediator contributes to the embryonic stem cell state through DNA loop formation, which is strongly associated with chromatin architecture; however, it remains unclear how Mediator regulates gene expression in cooperation with chromatin regulators (i.e. writers, readers and remodelers). We found that Mediator CDKs interact directly with the PRC2 subunit EZH2, as well as SUZ12. Known PRC2 target genes were deregulated by Mediator CDK knockdown during neuronal differentiation, and both Mediator and PRC2 complexes co-occupied the promoters of developmental genes regulated by retinoic acid. Our results provide a mechanistic link between Mediator and PRC2 during neuronal differentiation. © The Authors 2015. Published by Oxford University Press on behalf of the Japanese Biochemical Society. All rights reserved.

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

PubMed

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

2017-05-01

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

NRIP enhances HPV gene expression via interaction with either GR or E2

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

Chang, Szu-Wei; Lu, Pei-Yu; Guo, Jih-Huong

We previously identified a gene, nuclear receptor-interaction protein (NRIP), which functions as a transcription cofactor in glucocorticoid receptor (GR) and human papillomavirus E2 (HPV E2)-driven gene expression. Here, we comprehensively evaluated the role of NRIP in HPV-16 gene expression. NRIP acts as a transcription cofactor to enhance GR-regulated HPV-16 gene expression in the presence of hormone. NRIP also can form complex with E2 that caused NRIP-induced HPV gene expression via E2-binding sites in a hormone-independent manner. Furthermore, NRIP can associate with GR and E2 to form tri-protein complex to activate HPV gene expression via GRE, not the E2-binding site, inmore » a hormone-dependent manner. These results indicate that NRIP and GR are viral E2-binding proteins and that NRIP regulates HPV gene expression via GRE and/or E2 binding site in the HPV promoter in a hormone-dependent or independent manner, respectively.« less

Transcription factor 19 interacts with histone 3 lysine 4 trimethylation and controls gluconeogenesis via the nucleosome-remodeling-deacetylase complex.

PubMed

Sen, Sabyasachi; Sanyal, Sulagna; Srivastava, Dushyant Kumar; Dasgupta, Dipak; Roy, Siddhartha; Das, Chandrima

2017-12-15

Transcription factor 19 (TCF19) has been reported as a type 1 diabetes-associated locus involved in maintenance of pancreatic β cells through a fine-tuned regulation of cell proliferation and apoptosis. TCF19 also exhibits genomic association with type 2 diabetes, although the precise molecular mechanism remains unknown. It harbors both a plant homeodomain and a forkhead-associated domain implicated in epigenetic recognition and gene regulation, a phenomenon that has remained unexplored. Here, we show that TCF19 selectively interacts with histone 3 lysine 4 trimethylation through its plant homeodomain finger. Knocking down TCF19 under high-glucose conditions affected many metabolic processes, including gluconeogenesis. We found that TCF19 overexpression represses de novo glucose production in HepG2 cells. The transcriptional repression of key genes, induced by TCF19, coincided with NuRD (nucleosome-remodeling-deacetylase) complex recruitment to the promoters of these genes. TCF19 interacted with CHD4 (chromodomain helicase DNA-binding protein 4), which is a part of the NuRD complex, in a glucose concentration-independent manner. In summary, our results show that TCF19 interacts with an active transcription mark and recruits a co-repressor complex to regulate gluconeogenic gene expression in HepG2 cells. Our study offers critical insights into the molecular mechanisms of transcriptional regulation of gluconeogenesis and into the roles of chromatin readers in metabolic homeostasis. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Modeling synthetic lethality

PubMed Central

Le Meur, Nolwenn; Gentleman, Robert

2008-01-01

Background Synthetic lethality defines a genetic interaction where the combination of mutations in two or more genes leads to cell death. The implications of synthetic lethal screens have been discussed in the context of drug development as synthetic lethal pairs could be used to selectively kill cancer cells, but leave normal cells relatively unharmed. A challenge is to assess genome-wide experimental data and integrate the results to better understand the underlying biological processes. We propose statistical and computational tools that can be used to find relationships between synthetic lethality and cellular organizational units. Results In Saccharomyces cerevisiae, we identified multi-protein complexes and pairs of multi-protein complexes that share an unusually high number of synthetic genetic interactions. As previously predicted, we found that synthetic lethality can arise from subunits of an essential multi-protein complex or between pairs of multi-protein complexes. Finally, using multi-protein complexes allowed us to take into account the pleiotropic nature of the gene products. Conclusions Modeling synthetic lethality using current estimates of the yeast interactome is an efficient approach to disentangle some of the complex molecular interactions that drive a cell. Our model in conjunction with applied statistical methods and computational methods provides new tools to better characterize synthetic genetic interactions. PMID:18789146

Multifactor-Dimensionality Reduction Reveals High-Order Interactions among Estrogen-Metabolism Genes in Sporadic Breast Cancer

PubMed Central

Ritchie, Marylyn D.; Hahn, Lance W.; Roodi, Nady; Bailey, L. Renee; Dupont, William D.; Parl, Fritz F.; Moore, Jason H.

2001-01-01

One of the greatest challenges facing human geneticists is the identification and characterization of susceptibility genes for common complex multifactorial human diseases. This challenge is partly due to the limitations of parametric-statistical methods for detection of gene effects that are dependent solely or partially on interactions with other genes and with environmental exposures. We introduce multifactor-dimensionality reduction (MDR) as a method for reducing the dimensionality of multilocus information, to improve the identification of polymorphism combinations associated with disease risk. The MDR method is nonparametric (i.e., no hypothesis about the value of a statistical parameter is made), is model-free (i.e., it assumes no particular inheritance model), and is directly applicable to case-control and discordant-sib-pair studies. Using simulated case-control data, we demonstrate that MDR has reasonable power to identify interactions among two or more loci in relatively small samples. When it was applied to a sporadic breast cancer case-control data set, in the absence of any statistically significant independent main effects, MDR identified a statistically significant high-order interaction among four polymorphisms from three different estrogen-metabolism genes. To our knowledge, this is the first report of a four-locus interaction associated with a common complex multifactorial disease. PMID:11404819

A Method for Predicting Protein Complexes from Dynamic Weighted Protein-Protein Interaction Networks.

PubMed

Liu, Lizhen; Sun, Xiaowu; Song, Wei; Du, Chao

2018-06-01

Predicting protein complexes from protein-protein interaction (PPI) network is of great significance to recognize the structure and function of cells. A protein may interact with different proteins under different time or conditions. Existing approaches only utilize static PPI network data that may lose much temporal biological information. First, this article proposed a novel method that combines gene expression data at different time points with traditional static PPI network to construct different dynamic subnetworks. Second, to further filter out the data noise, the semantic similarity based on gene ontology is regarded as the network weight together with the principal component analysis, which is introduced to deal with the weight computing by three traditional methods. Third, after building a dynamic PPI network, a predicting protein complexes algorithm based on "core-attachment" structural feature is applied to detect complexes from each dynamic subnetworks. Finally, it is revealed from the experimental results that our method proposed in this article performs well on detecting protein complexes from dynamic weighted PPI networks.

Mitochondrial-Nuclear Epistasis: Implications for Human Aging and Longevity

PubMed Central

Tranah, Gregory

2010-01-01

There is substantial evidence that mitochondria are involved in the aging process. Mitochondrial function requires the coordinated expression of hundreds of nuclear genes and a few dozen mitochondrial genes, many of which have been associated with either extended or shortened life span. Impaired mitochondrial function resulting from mtDNA and nuclear DNA variation is likely to contribute to an imbalance in cellular energy homeostasis, increased vulnerability to oxidative stress, and an increased rate of cellular senescence and aging. The complex genetic architecture of mitochondria suggests that there may be an equally complex set of gene interactions (epistases) involving genetic variation in the nuclear and mitochondrial genomes. Results from Drosophila suggest that the effects of mtDNA haplotypes on longevity vary among different nuclear allelic backgrounds, which could account for the inconsistent associations that have been observed between mitochondrial DNA (mtDNA) haplogroups and survival in humans. A diversity of pathways may influence the way mitochondria and nuclear – mitochondrial interactions modulate longevity, including: oxidative phosphorylation; mitochondrial uncoupling; antioxidant defenses; mitochondrial fission and fusion; and sirtuin regulation of mitochondrial genes. We hypothesize that aging and longevity, as complex traits having a significant genetic component, are likely to be controlled by nuclear gene variants interacting with both inherited and somatic mtDNA variability. PMID:20601194

High Fractional Occupancy of a Tandem Maf Recognition Element and Its Role in Long-Range β-Globin Gene Regulation

PubMed Central

Stees, Jared R.; Hossain, Mir A.; Sunose, Tomoki; Kudo, Yasushi; Pardo, Carolina E.; Nabilsi, Nancy H.; Darst, Russell P.; Poudyal, Rosha; Igarashi, Kazuhiko; Kladde, Michael P.

2015-01-01

Enhancers and promoters assemble protein complexes that ultimately regulate the recruitment and activity of RNA polymerases. Previous work has shown that at least some enhancers form stable protein complexes, leading to the formation of enhanceosomes. We analyzed protein-DNA interactions in the murine β-globin gene locus using the methyltransferase accessibility protocol for individual templates (MAPit). The data show that a tandem Maf recognition element (MARE) in locus control region (LCR) hypersensitive site 2 (HS2) reveals a remarkably high degree of occupancy during differentiation of mouse erythroleukemia cells. Most of the other transcription factor binding sites in LCR HS2 or in the adult β-globin gene promoter regions exhibit low fractional occupancy, suggesting highly dynamic protein-DNA interactions. Targeting of an artificial zinc finger DNA-binding domain (ZF-DBD) to the HS2 tandem MARE caused a reduction in the association of MARE-binding proteins and transcription complexes at LCR HS2 and the adult βmajor-globin gene promoter but did not affect expression of the βminor-globin gene. The data demonstrate that a stable MARE-associated footprint in LCR HS2 is important for the recruitment of transcription complexes to the adult βmajor-globin gene promoter during erythroid cell differentiation. PMID:26503787

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm.

PubMed

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene x gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene x gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms.

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm

PubMed Central

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene × gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene × gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms. PMID:18466570

Visualization of the Drosophila dKeap1-CncC interaction on chromatin illumines cooperative, xenobiotic-specific gene activation

PubMed Central

Deng, Huai; Kerppola, Tom K.

2014-01-01

Interactions among transcription factors control their physiological functions by regulating their binding specificities and transcriptional activities. We implement a strategy to visualize directly the genomic loci that are bound by multi-protein complexes in single cells in Drosophila. This method is based on bimolecular fluorescence complementation (BiFC) analysis of protein interactions on polytene chromosomes. Drosophila Keap1 (dKeap1)-CncC complexes localized to the nucleus and bound chromatin loci that were not bound preferentially by dKeap1 or CncC when they were expressed separately. dKeap1 and CncC binding at these loci was enhanced by phenobarbital, but not by tert-butylhydroquinone (tBHQ) or paraquat. Endogenous dKeap1 and CncC activated transcription of the Jheh (Jheh1, Jheh2, Jheh3) and dKeap1 genes at these loci, whereas CncC alone activated other xenobiotic response genes. Ectopic dKeap1 expression increased CncC binding at the Jheh and dKeap1 gene loci and activated their transcription, whereas dKeap1 inhibited CncC binding at other xenobiotic response gene loci and suppressed their transcription. The combinatorial chromatin-binding specificities and transcriptional activities of dKeap1-CncC complexes mediated the selective activation of different sets of genes by different xenobiotic compounds, in part through feed-forward activation of dKeap1 transcription. PMID:25063457

Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns

PubMed Central

Lezon, Timothy R.; Banavar, Jayanth R.; Cieplak, Marek; Maritan, Amos; Fedoroff, Nina V.

2006-01-01

We describe a method based on the principle of entropy maximization to identify the gene interaction network with the highest probability of giving rise to experimentally observed transcript profiles. In its simplest form, the method yields the pairwise gene interaction network, but it can also be extended to deduce higher-order interactions. Analysis of microarray data from genes in Saccharomyces cerevisiae chemostat cultures exhibiting energy metabolic oscillations identifies a gene interaction network that reflects the intracellular communication pathways that adjust cellular metabolic activity and cell division to the limiting nutrient conditions that trigger metabolic oscillations. The success of the present approach in extracting meaningful genetic connections suggests that the maximum entropy principle is a useful concept for understanding living systems, as it is for other complex, nonequilibrium systems. PMID:17138668

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

USDA-ARS?s Scientific Manuscript database

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

Unveiling network-based functional features through integration of gene expression into protein networks.

PubMed

Jalili, Mahdi; Gebhardt, Tom; Wolkenhauer, Olaf; Salehzadeh-Yazdi, Ali

2018-06-01

Decoding health and disease phenotypes is one of the fundamental objectives in biomedicine. Whereas high-throughput omics approaches are available, it is evident that any single omics approach might not be adequate to capture the complexity of phenotypes. Therefore, integrated multi-omics approaches have been used to unravel genotype-phenotype relationships such as global regulatory mechanisms and complex metabolic networks in different eukaryotic organisms. Some of the progress and challenges associated with integrated omics studies have been reviewed previously in comprehensive studies. In this work, we highlight and review the progress, challenges and advantages associated with emerging approaches, integrating gene expression and protein-protein interaction networks to unravel network-based functional features. This includes identifying disease related genes, gene prioritization, clustering protein interactions, developing the modules, extract active subnetworks and static protein complexes or dynamic/temporal protein complexes. We also discuss how these approaches contribute to our understanding of the biology of complex traits and diseases. This article is part of a Special Issue entitled: Cardiac adaptations to obesity, diabetes and insulin resistance, edited by Professors Jan F.C. Glatz, Jason R.B. Dyck and Christine Des Rosiers. Copyright © 2018 Elsevier B.V. All rights reserved.

Deciphering the Interdependence between Ecological and Evolutionary Networks.

PubMed

Melián, Carlos J; Matthews, Blake; de Andreazzi, Cecilia S; Rodríguez, Jorge P; Harmon, Luke J; Fortuna, Miguel A

2018-05-24

Biological systems consist of elements that interact within and across hierarchical levels. For example, interactions among genes determine traits of individuals, competitive and cooperative interactions among individuals influence population dynamics, and interactions among species affect the dynamics of communities and ecosystem processes. Such systems can be represented as hierarchical networks, but can have complex dynamics when interdependencies among levels of the hierarchy occur. We propose integrating ecological and evolutionary processes in hierarchical networks to explore interdependencies in biological systems. We connect gene networks underlying predator-prey trait distributions to food webs. Our approach addresses longstanding questions about how complex traits and intraspecific trait variation affect the interdependencies among biological levels and the stability of meta-ecosystems. Copyright © 2018 Elsevier Ltd. All rights reserved.

The long noncoding RNA Chaer defines an epigenetic checkpoint in cardiac hypertrophy.

PubMed

Wang, Zhihua; Zhang, Xiao-Jing; Ji, Yan-Xiao; Zhang, Peng; Deng, Ke-Qiong; Gong, Jun; Ren, Shuxun; Wang, Xinghua; Chen, Iris; Wang, He; Gao, Chen; Yokota, Tomohiro; Ang, Yen Sin; Li, Shen; Cass, Ashley; Vondriska, Thomas M; Li, Guangping; Deb, Arjun; Srivastava, Deepak; Yang, Huang-Tian; Xiao, Xinshu; Li, Hongliang; Wang, Yibin

2016-10-01

Epigenetic reprogramming is a critical process of pathological gene induction during cardiac hypertrophy and remodeling, but the underlying regulatory mechanisms remain to be elucidated. Here we identified a heart-enriched long noncoding (lnc)RNA, named cardiac-hypertrophy-associated epigenetic regulator (Chaer), which is necessary for the development of cardiac hypertrophy. Mechanistically, Chaer directly interacts with the catalytic subunit of polycomb repressor complex 2 (PRC2). This interaction, which is mediated by a 66-mer motif in Chaer, interferes with PRC2 targeting to genomic loci, thereby inhibiting histone H3 lysine 27 methylation at the promoter regions of genes involved in cardiac hypertrophy. The interaction between Chaer and PRC2 is transiently induced after hormone or stress stimulation in a process involving mammalian target of rapamycin complex 1, and this interaction is a prerequisite for epigenetic reprogramming and induction of genes involved in hypertrophy. Inhibition of Chaer expression in the heart before, but not after, the onset of pressure overload substantially attenuates cardiac hypertrophy and dysfunction. Our study reveals that stress-induced pathological gene activation in the heart requires a previously uncharacterized lncRNA-dependent epigenetic checkpoint.

Specific gene transfer mediated by galactosylated poly-L-lysine into hepatoma cells.

PubMed

Han, J; Il Yeom, Y

2000-07-20

Plasmid DNA/galactosylated poly-L-lysine(GalPLL) complex was used to transfer luciferase reporter gene in vitro into human hepatoma cells by a receptor-mediated endocytosis process. DNA was combined with galPLL via charge interaction (DNA:GalPLL:fusogenic peptide, 1:0.4:5, w/w/w) and the resulting complex was characterized by dynamic light scattering, gel retardation assay and zeta potential analyzer to determine the particle size, electrostatic charge interaction, and apparent surface charge. The complex was tested for the efficiency of gene transfer in cultured human hepatoblastoma cell line Hep G2 and fibroblast cells NIH/3T3 in vitro. The mean diameter of the complex (DNA:GalPLL=1:0.4, w/w) was 256+/-34.8 nm, and at this ratio, it was positively charged (zeta potential of this complex was 10.1 mV). Hep G2 cells, which express a galactose specific membrane lectin, were efficiently and selectively transfected with the RSV Luc/GalPLL complex in a sugar-dependent manner. NIH/3T3 cells, which do not express the galactose-specific membrane lectin, showed only a marginal level of gene expression. The transfection efficiency of GalPLL-conjugated DNA complex into Hep G2 cells was greatly enhanced in the presence of fusogenic peptide that can disrupt endosomes, where the GalPLL-DNA complex is entrapped with the fusogenic peptide. With the fusogenic peptide KALA, the luciferase activity in Hep G2 cells was ten-fold higher than that of cells transfected in the absence of the fusogenic peptide. Our gene transfer formulation may find potential application for the gene therapy of liver diseases.

Super-Enhancers and Broad H3K4me3 Domains Form Complex Gene Regulatory Circuits Involving Chromatin Interactions.

PubMed

Cao, Fan; Fang, Yiwen; Tan, Hong Kee; Goh, Yufen; Choy, Jocelyn Yeen Hui; Koh, Bryan Thean Howe; Hao Tan, Jiong; Bertin, Nicolas; Ramadass, Aroul; Hunter, Ewan; Green, Jayne; Salter, Matthew; Akoulitchev, Alexandre; Wang, Wilson; Chng, Wee Joo; Tenen, Daniel G; Fullwood, Melissa J

2017-05-19

Stretched histone regions, such as super-enhancers and broad H3K4me3 domains, are associated with maintenance of cell identity and cancer. We connected super-enhancers and broad H3K4me3 domains in the K562 chronic myelogenous leukemia cell line as well as the MCF-7 breast cancer cell line with chromatin interactions. Super-enhancers and broad H3K4me3 domains showed higher association with chromatin interactions than their typical counterparts. Interestingly, we identified a subset of super-enhancers that overlap with broad H3K4me3 domains and show high association with cancer-associated genes including tumor suppressor genes. Besides cell lines, we could observe chromatin interactions by a Chromosome Conformation Capture (3C)-based method, in primary human samples. Several chromatin interactions involving super-enhancers and broad H3K4me3 domains are constitutive and can be found in both cancer and normal samples. Taken together, these results reveal a new layer of complexity in gene regulation by super-enhancers and broad H3K4me3 domains.

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

PubMed

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

2012-06-28

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

Epistasis interaction of QTL effects as a genetic parameter influencing estimation of the genetic additive effect.

PubMed

Bocianowski, Jan

2013-03-01

Epistasis, an additive-by-additive interaction between quantitative trait loci, has been defined as a deviation from the sum of independent effects of individual genes. Epistasis between QTLs assayed in populations segregating for an entire genome has been found at a frequency close to that expected by chance alone. Recently, epistatic effects have been considered by many researchers as important for complex traits. In order to understand the genetic control of complex traits, it is necessary to clarify additive-by-additive interactions among genes. Herein we compare estimates of a parameter connected with the additive gene action calculated on the basis of two models: a model excluding epistasis and a model with additive-by-additive interaction effects. In this paper two data sets were analysed: 1) 150 barley doubled haploid lines derived from the Steptoe × Morex cross, and 2) 145 DH lines of barley obtained from the Harrington × TR306 cross. The results showed that in cases when the effect of epistasis was different from zero, the coefficient of determination was larger for the model with epistasis than for the one excluding epistasis. These results indicate that epistatic interaction plays an important role in controlling the expression of complex traits.

A functionally conserved Polycomb response element from mouse HoxD complex responds to heterochromatin factors

NASA Astrophysics Data System (ADS)

Vasanthi, Dasari; Nagabhushan, A.; Matharu, Navneet Kaur; Mishra, Rakesh K.

2013-10-01

Anterior-posterior body axis in all bilaterians is determined by the Hox gene clusters that are activated in a spatio-temporal order. This expression pattern of Hox genes is established and maintained by regulatory mechanisms that involve higher order chromatin structure and Polycomb group (PcG) and trithorax group (trxG) proteins. We identified earlier a Polycomb response element (PRE) in the mouse HoxD complex that is functionally conserved in flies. We analyzed the molecular and genetic interactions of mouse PRE using Drosophila melanogaster and vertebrate cell culture as the model systems. We demonstrate that the repressive activity of this PRE depends on PcG/trxG genes as well as the heterochromatin components. Our findings indicate that a wide range of factors interact with the HoxD PRE that can contribute to establishing the expression pattern of homeotic genes in the complex early during development and maintain that pattern at subsequent stages.

Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases

PubMed Central

Ritchie, Marylyn D; White, Bill C; Parker, Joel S; Hahn, Lance W; Moore, Jason H

2003-01-01

Background Appropriate definition of neural network architecture prior to data analysis is crucial for successful data mining. This can be challenging when the underlying model of the data is unknown. The goal of this study was to determine whether optimizing neural network architecture using genetic programming as a machine learning strategy would improve the ability of neural networks to model and detect nonlinear interactions among genes in studies of common human diseases. Results Using simulated data, we show that a genetic programming optimized neural network approach is able to model gene-gene interactions as well as a traditional back propagation neural network. Furthermore, the genetic programming optimized neural network is better than the traditional back propagation neural network approach in terms of predictive ability and power to detect gene-gene interactions when non-functional polymorphisms are present. Conclusion This study suggests that a machine learning strategy for optimizing neural network architecture may be preferable to traditional trial-and-error approaches for the identification and characterization of gene-gene interactions in common, complex human diseases. PMID:12846935

Whirlin and PDZ domain-containing 7 (PDZD7) proteins are both required to form the quaternary protein complex associated with Usher syndrome type 2.

PubMed

Chen, Qian; Zou, Junhuang; Shen, Zuolian; Zhang, Weiping; Yang, Jun

2014-12-26

Usher syndrome (USH) is the leading genetic cause of combined hearing and vision loss. Among the three USH clinical types, type 2 (USH2) occurs most commonly. USH2A, GPR98, and WHRN are three known causative genes of USH2, whereas PDZD7 is a modifier gene found in USH2 patients. The proteins encoded by these four USH genes have been proposed to form a multiprotein complex, the USH2 complex, due to interactions found among some of these proteins in vitro, their colocalization in vivo, and mutual dependence of some of these proteins for their normal in vivo localizations. However, evidence showing the formation of the USH2 complex is missing, and details on how this complex is formed remain elusive. Here, we systematically investigated interactions among the intracellular regions of the four USH proteins using colocalization, yeast two-hybrid, and pull-down assays. We show that multiple domains of the four USH proteins interact among one another. Importantly, both WHRN and PDZD7 are required for the complex formation with USH2A and GPR98. In this USH2 quaternary complex, WHRN prefers to bind to USH2A, whereas PDZD7 prefers to bind to GPR98. Interaction between WHRN and PDZD7 is the bridge between USH2A and GPR98. Additionally, the USH2 quaternary complex has a variable stoichiometry. These findings suggest that a non-obligate, short term, and dynamic USH2 quaternary protein complex may exist in vivo. Our work provides valuable insight into the physiological role of the USH2 complex in vivo and informs possible reconstruction of the USH2 complex for future therapy. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

The hematopoietic regulator TAL1 is required for chromatin looping between the β-globin LCR and human γ-globin genes to activate transcription

PubMed Central

Yun, Won Ju; Kim, Yea Woon; Kang, Yujin; Lee, Jungbae; Dean, Ann; Kim, AeRi

2014-01-01

TAL1 is a key hematopoietic transcription factor that binds to regulatory regions of a large cohort of erythroid genes as part of a complex with GATA-1, LMO2 and Ldb1. The complex mediates long-range interaction between the β-globin locus control region (LCR) and active globin genes, and although TAL1 is one of the two DNA-binding complex members, its role is unclear. To explore the role of TAL1 in transcription activation of the human γ-globin genes, we reduced the expression of TAL1 in erythroid K562 cells using lentiviral short hairpin RNA, compromising its association in the β-globin locus. In the TAL1 knockdown cells, the γ-globin transcription was reduced to 35% and chromatin looping of the Gγ-globin gene with the LCR was disrupted with decreased occupancy of the complex member Ldb1 and LMO2 in the locus. However, GATA-1 binding, DNase I hypersensitive site formation and several histone modifications were largely maintained across the β-globin locus. In addition, overexpression of TAL1 increased the γ-globin transcription and increased interaction frequency between the Gγ-globin gene and LCR. These results indicate that TAL1 plays a critical role in chromatin loop formation between the γ-globin genes and LCR, which is a critical step for the transcription of the γ-globin genes. PMID:24470145

The hematopoietic regulator TAL1 is required for chromatin looping between the β-globin LCR and human γ-globin genes to activate transcription.

PubMed

Yun, Won Ju; Kim, Yea Woon; Kang, Yujin; Lee, Jungbae; Dean, Ann; Kim, AeRi

2014-04-01

TAL1 is a key hematopoietic transcription factor that binds to regulatory regions of a large cohort of erythroid genes as part of a complex with GATA-1, LMO2 and Ldb1. The complex mediates long-range interaction between the β-globin locus control region (LCR) and active globin genes, and although TAL1 is one of the two DNA-binding complex members, its role is unclear. To explore the role of TAL1 in transcription activation of the human γ-globin genes, we reduced the expression of TAL1 in erythroid K562 cells using lentiviral short hairpin RNA, compromising its association in the β-globin locus. In the TAL1 knockdown cells, the γ-globin transcription was reduced to 35% and chromatin looping of the (G)γ-globin gene with the LCR was disrupted with decreased occupancy of the complex member Ldb1 and LMO2 in the locus. However, GATA-1 binding, DNase I hypersensitive site formation and several histone modifications were largely maintained across the β-globin locus. In addition, overexpression of TAL1 increased the γ-globin transcription and increased interaction frequency between the (G)γ-globin gene and LCR. These results indicate that TAL1 plays a critical role in chromatin loop formation between the γ-globin genes and LCR, which is a critical step for the transcription of the γ-globin genes.

[Identification of C(2)M interacting proteins by yeast two-hybrid screening].

PubMed

Yue, Shan-shan; Xia, Lai-xin

2015-11-01

The synaptonemal complex (SC) is a huge structure which assembles between the homologous chromosomes during meiotic prophase I. Drosophila germ cell-specific nucleoprotein C(2)M clustering at chromosomes can induce SC formation. To further study the molecular function and mechanism of C(2)M in meiosis, we constructed a bait vector for C(2)M and used the yeast two-hybrid system to identify C(2)M interacting proteins. Forty interacting proteins were obtained, including many DNA and histone binding proteins, ATP synthases and transcription factors. Gene silencing assays in Drosophila showed that two genes, wech and Psf1, may delay the disappearance of SC. These results indicate that Wech and Psf1 may form a complex with C(2)M to participate in the formation or stabilization of the SC complex.

The proto-oncoprotein FBI-1 interacts with MBD3 to recruit the Mi-2/NuRD-HDAC complex and BCoR and to silence p21WAF/CDKN1A by DNA methylation.

PubMed

Choi, Won-Il; Jeon, Bu-Nam; Yoon, Jae-Hyeon; Koh, Dong-In; Kim, Myung-Hwa; Yu, Mi-Young; Lee, Kyung-Mi; Kim, Youngsoo; Kim, Kyunggon; Hur, Sujin Susanne; Lee, Choong-Eun; Kim, Kyung-Sup; Hur, Man-Wook

2013-07-01

The tumour-suppressor gene CDKN1A (encoding p21Waf/Cip1) is thought to be epigenetically repressed in cancer cells. FBI-1 (ZBTB7A) is a proto-oncogenic transcription factor repressing the alternative reading frame and p21WAF/CDKN1A genes of the p53 pathway. FBI-1 interacts directly with MBD3 (methyl-CpG-binding domain protein 3) in the nucleus. We demonstrated that FBI-1 binds both non-methylated and methylated DNA and that MBD3 is recruited to the CDKN1A promoter through its interaction with FBI-1, where it enhances transcriptional repression by FBI-1. FBI-1 also interacts with the co-repressors nuclear receptor corepressor (NCoR), silencing mediator for retinoid and thyroid receptors (SMRT) and BCL-6 corepressor (BCoR) to repress transcription. MBD3 regulates a molecular interaction between the co-repressor and FBI-1. MBD3 decreases the interaction between FBI-1 and NCoR/SMRT but increases the interaction between FBI-1 and BCoR. Because MBD3 is a subunit of the Mi-2 autoantigen (Mi-2)/nucleosome remodelling and histone deacetylase (NuRD)-HDAC complex, FBI-1 recruits the Mi-2/NuRD-HDAC complex via MBD3. BCoR interacts with the Mi-2/NuRD-HDAC complex, DNMTs and HP1. MBD3 and BCoR play a significant role in the recruitment of the Mi-2/NuRD-HDAC complex- and the NuRD complex-associated proteins, DNMTs and HP. By recruiting DNMTs and HP1, Mi-2/NuRD-HDAC complex appears to play key roles in epigenetic repression of CDKN1A by DNA methylation.

Gene-Gene-Environment Interactions of Serotonin Transporter, Monoamine Oxidase A and Childhood Maltreatment Predict Aggressive Behavior in Chinese Adolescents

PubMed Central

Zhang, Yun; Ming, Qing-sen; Yi, Jin-yao; Wang, Xiang; Chai, Qiao-lian; Yao, Shu-qiao

2017-01-01

Gene-environment interactions that moderate aggressive behavior have been identified independently in the serotonin transporter (5-HTT) gene and monoamine oxidase A gene (MAOA). The aim of the present study was to investigate epistasis interactions between MAOA-variable number tandem repeat (VNTR), 5-HTTlinked polymorphism (LPR) and child abuse and the effects of these on aggressive tendencies in a group of otherwise healthy adolescents. A group of 546 Chinese male adolescents completed the Child Trauma Questionnaire and Youth self-report of the Child Behavior Checklist. Buccal cells were collected for DNA analysis. The effects of childhood abuse, MAOA-VNTR, 5-HTTLPR genotypes and their interactive gene-gene-environmental effects on aggressive behavior were analyzed using a linear regression model. The effect of child maltreatment was significant, and a three-way interaction among MAOA-VNTR, 5-HTTLPR and sexual abuse (SA) relating to aggressive behaviors was identified. Chinese male adolescents with high expression of the MAOA-VNTR allele and 5-HTTLPR “SS” genotype exhibited the highest aggression tendencies with an increase in SA during childhood. The findings reported support aggression being a complex behavior involving the synergistic effects of gene-gene-environment interactions. PMID:28203149

Imaging dynamic and selective low-complexity domain interactions that control gene transcription.

PubMed

Chong, Shasha; Dugast-Darzacq, Claire; Liu, Zhe; Dong, Peng; Dailey, Gina M; Cattoglio, Claudia; Heckert, Alec; Banala, Sambashiva; Lavis, Luke; Darzacq, Xavier; Tjian, Robert

2018-06-21

Many eukaryotic transcription factors (TFs) contain intrinsically disordered low-complexity domains (LCDs), but how they drive transactivation remains unclear. Here, live-cell single-molecule imaging reveals that TF-LCDs form local high-concentration interaction hubs at synthetic and endogenous genomic loci. TF-LCD hubs stabilize DNA binding, recruit RNA polymerase II (Pol II), and activate transcription. LCD-LCD interactions within hubs are highly dynamic, display selectivity with binding partners, and are differentially sensitive to disruption by hexanediols. Under physiological conditions, rapid and reversible LCD-LCD interactions occur between TFs and the Pol II machinery without detectable phase separation. Our findings reveal fundamental mechanisms underpinning transcriptional control and suggest a framework for developing single-molecule imaging screens for novel drugs targeting gene regulatory interactions implicated in disease. Copyright © 2018, American Association for the Advancement of Science.

Primary Sex Determination in Drosophila melanogaster Does Not Rely on the Male-Specific Lethal Complex.

PubMed

Erickson, James W

2016-02-01

It has been proposed that the Male Specific Lethal (MSL) complex is active in Drosophila melanogaster embryos of both sexes prior to the maternal-to-zygotic transition. Elevated gene expression from the two X chromosomes of female embryos is proposed to facilitate the stable establishment of Sex-lethal (Sxl) expression, which determines sex and represses further activity of the MSL complex, leaving it active only in males. Important supporting data included female-lethal genetic interactions between the seven msl genes and either Sxl or scute and sisterlessA, two of the X-signal elements (XSE) that regulate early Sxl expression. Here I report contrary findings that there are no female-lethal genetic interactions between the msl genes and Sxl or its XSE regulators. Fly stocks containing the msl3(1) allele were found to exhibit a maternal-effect interaction with Sxl, scute, and sisterlessA mutations, but genetic complementation experiments showed that msl3 is neither necessary nor sufficient for the female-lethal interactions, which appear to be due to an unidentified maternal regulator of Sxl. Published data cited as evidence for an early function of the MSL complex in females, including a maternal effect of msl2, have been reevaluated and found not to support a maternal, or other effect, of the MSL complex in sex determination. These findings suggest that the MSL complex is not involved in primary sex determination or in X chromosome dosage compensation prior to the maternal-to-zygotic transition. Copyright © 2016 by the Genetics Society of America.

The Importance of Normalization on Large and Heterogeneous Microarray Datasets

EPA Science Inventory

DNA microarray technology is a powerful functional genomics tool increasingly used for investigating global gene expression in environmental studies. Microarrays can also be used in identifying biological networks, as they give insight on the complex gene-to-gene interactions, ne...

Architecture of the human interactome defines protein communities and disease networks

PubMed Central

Huttlin, Edward L.; Bruckner, Raphael J.; Paulo, Joao A.; Cannon, Joe R.; Ting, Lily; Baltier, Kurt; Colby, Greg; Gebreab, Fana; Gygi, Melanie P.; Parzen, Hannah; Szpyt, John; Tam, Stanley; Zarraga, Gabriela; Pontano-Vaites, Laura; Swarup, Sharan; White, Anne E.; Schweppe, Devin K.; Rad, Ramin; Erickson, Brian K.; Obar, Robert A.; Guruharsha, K.G.; Li, Kejie; Artavanis-Tsakonas, Spyros; Gygi, Steven P.; Harper, J. Wade

2017-01-01

The physiology of a cell can be viewed as the product of thousands of proteins acting in concert to shape the cellular response. Coordination is achieved in part through networks of protein-protein interactions that assemble functionally related proteins into complexes, organelles, and signal transduction pathways. Understanding the architecture of the human proteome has the potential to inform cellular, structural, and evolutionary mechanisms and is critical to elucidation of how genome variation contributes to disease1–3. Here, we present BioPlex 2.0 (Biophysical Interactions of ORFEOME-derived complexes), which employs robust affinity purification-mass spectrometry (AP-MS) methodology4 to elucidate protein interaction networks and co-complexes nucleated by more than 25% of protein coding genes from the human genome, and constitutes the largest such network to date. With >56,000 candidate interactions, BioPlex 2.0 contains >29,000 previously unknown co-associations and provides functional insights into hundreds of poorly characterized proteins while enhancing network-based analyses of domain associations, subcellular localization, and co-complex formation. Unsupervised Markov clustering (MCL)5 of interacting proteins identified more than 1300 protein communities representing diverse cellular activities. Genes essential for cell fitness6,7 are enriched within 53 communities representing central cellular functions. Moreover, we identified 442 communities associated with more than 2000 disease annotations, placing numerous candidate disease genes into a cellular framework. BioPlex 2.0 exceeds previous experimentally derived interaction networks in depth and breadth, and will be a valuable resource for exploring the biology of incompletely characterized proteins and for elucidating larger-scale patterns of proteome organization. PMID:28514442

Wongabel rhabdovirus accessory protein U3 targets the SWI/SNF chromatin remodeling complex.

PubMed

Joubert, D Albert; Rodriguez-Andres, Julio; Monaghan, Paul; Cummins, Michelle; McKinstry, William J; Paradkar, Prasad N; Moseley, Gregory W; Walker, Peter J

2015-01-15

Wongabel virus (WONV) is an arthropod-borne rhabdovirus that infects birds. It is one of the growing array of rhabdoviruses with complex genomes that encode multiple accessory proteins of unknown function. In addition to the five canonical rhabdovirus structural protein genes (N, P, M, G, and L), the 13.2-kb negative-sense single-stranded RNA (ssRNA) WONV genome contains five uncharacterized accessory genes, one overlapping the N gene (Nx or U4), three located between the P and M genes (U1 to U3), and a fifth one overlapping the G gene (Gx or U5). Here we show that WONV U3 is expressed during infection in insect and mammalian cells and is required for efficient viral replication. A yeast two-hybrid screen against a mosquito cell cDNA library identified that WONV U3 interacts with the 83-amino-acid (aa) C-terminal domain of SNF5, a component of the SWI/SNF chromatin remodeling complex. The interaction was confirmed by affinity chromatography, and nuclear colocalization was established by confocal microscopy. Gene expression studies showed that SNF5 transcripts are upregulated during infection of mosquito cells with WONV, as well as West Nile virus (Flaviviridae) and bovine ephemeral fever virus (Rhabdoviridae), and that SNF5 knockdown results in increased WONV replication. WONV U3 also inhibits SNF5-regulated expression of the cytokine gene CSF1. The data suggest that WONV U3 targets the SWI/SNF complex to block the host response to infection. The rhabdoviruses comprise a large family of RNA viruses infecting plants, vertebrates, and invertebrates. In addition to the major structural proteins (N, P, M, G, and L), many rhabdoviruses encode a diverse array of accessory proteins of largely unknown function. Understanding the role of these proteins may reveal much about host-pathogen interactions in infected cells. Here we examine accessory protein U3 of Wongabel virus, an arthropod-borne rhabdovirus that infects birds. We show that U3 enters the nucleus and interacts with SNF5, a component of the chromatin remodeling complex that is upregulated in response to infection and restricts viral replication. We also show that U3 inhibits SNF5-regulated expression of the cytokine colony-stimulating factor 1 (CSF1), suggesting that it targets the chromatin remodeling complex to block the host response to infection. This study appears to provide the first evidence of a virus targeting SNF5 to inhibit host gene expression. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Wongabel Rhabdovirus Accessory Protein U3 Targets the SWI/SNF Chromatin Remodeling Complex

PubMed Central

Joubert, D. Albert; Rodriguez-Andres, Julio; Monaghan, Paul; Cummins, Michelle; McKinstry, William J.; Paradkar, Prasad N.; Moseley, Gregory W.

2014-01-01

ABSTRACT Wongabel virus (WONV) is an arthropod-borne rhabdovirus that infects birds. It is one of the growing array of rhabdoviruses with complex genomes that encode multiple accessory proteins of unknown function. In addition to the five canonical rhabdovirus structural protein genes (N, P, M, G, and L), the 13.2-kb negative-sense single-stranded RNA (ssRNA) WONV genome contains five uncharacterized accessory genes, one overlapping the N gene (Nx or U4), three located between the P and M genes (U1 to U3), and a fifth one overlapping the G gene (Gx or U5). Here we show that WONV U3 is expressed during infection in insect and mammalian cells and is required for efficient viral replication. A yeast two-hybrid screen against a mosquito cell cDNA library identified that WONV U3 interacts with the 83-amino-acid (aa) C-terminal domain of SNF5, a component of the SWI/SNF chromatin remodeling complex. The interaction was confirmed by affinity chromatography, and nuclear colocalization was established by confocal microscopy. Gene expression studies showed that SNF5 transcripts are upregulated during infection of mosquito cells with WONV, as well as West Nile virus (Flaviviridae) and bovine ephemeral fever virus (Rhabdoviridae), and that SNF5 knockdown results in increased WONV replication. WONV U3 also inhibits SNF5-regulated expression of the cytokine gene CSF1. The data suggest that WONV U3 targets the SWI/SNF complex to block the host response to infection. IMPORTANCE The rhabdoviruses comprise a large family of RNA viruses infecting plants, vertebrates, and invertebrates. In addition to the major structural proteins (N, P, M, G, and L), many rhabdoviruses encode a diverse array of accessory proteins of largely unknown function. Understanding the role of these proteins may reveal much about host-pathogen interactions in infected cells. Here we examine accessory protein U3 of Wongabel virus, an arthropod-borne rhabdovirus that infects birds. We show that U3 enters the nucleus and interacts with SNF5, a component of the chromatin remodeling complex that is upregulated in response to infection and restricts viral replication. We also show that U3 inhibits SNF5-regulated expression of the cytokine colony-stimulating factor 1 (CSF1), suggesting that it targets the chromatin remodeling complex to block the host response to infection. This study appears to provide the first evidence of a virus targeting SNF5 to inhibit host gene expression. PMID:25392228

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

Bis-quaternary gemini surfactants as components of nonviral gene delivery systems: a comprehensive study from physicochemical properties to membrane interactions.

PubMed

Cardoso, Ana M; Morais, Catarina M; Silva, Sandra G; Marques, Eduardo F; de Lima, Maria C Pedroso; Jurado, Maria Amália S

2014-10-20

Gemini surfactants have been successfully used as components of gene delivery systems. In the present work, a family of gemini surfactants, represented by the general structure [CmH2m+1(CH3)2N(+)(CH2)sN(+)(CH3)2CmH2m+1]2Br(-), or simply m-s-m, was used to prepare cationic gene carriers, aiming at their application in transfection studies. An extensive characterization of the gemini surfactant-based complexes, produced with and without the helper lipids cholesterol and DOPE, was carried out in order to correlate their physico-chemical properties with transfection efficiency. The most efficient complexes were those containing helper lipids, which, combining amphiphiles with propensity to form structures with different intrinsic curvatures, displayed a morphologically labile architecture, putatively implicated in the efficient DNA release upon complex interaction with membranes. While complexes lacking helper lipids were translocated directly across the lipid bilayer, complexes containing helper lipids were taken up by cells also by macropinocytosis. This study contributes to shed light on the relationship between important physico-chemical properties of surfactant-based DNA vectors and their efficiency to promote gene transfer, which may represent a step forward to the rational design of gene delivery systems. Copyright © 2014 Elsevier B.V. All rights reserved.

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

PubMed

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

2011-07-01

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

Altered interactions within FY/AtCPSF complexes required for Arabidopsis FCA-mediated chromatin silencing

PubMed Central

Manzano, David; Marquardt, Sebastian; Jones, Alexandra M. E.; Bäurle, Isabel; Liu, Fuquan; Dean, Caroline

2009-01-01

The role of RNA metabolism in chromatin silencing is now widely recognized. We have studied the Arabidopsis RNA-binding protein FCA that down-regulates an endogenous floral repressor gene through a chromatin mechanism involving histone demethylase activity. This mechanism needs FCA to interact with an RNA 3′ processing/polyadenylation factor (FY/Pfs2p), but the subsequent events leading to chromatin changes are unknown. Here, we show that this FCA–FY interaction is required for general chromatin silencing roles where hairpin transgenes induce DNA methylation of an endogenous gene. We also show 2 conserved RNA processing factors, AtCPSF100 and AtCPSF160, but not FCA, are stably associated with FY in vivo and form a range of different-sized complexes. A hypomorphic fy allele producing a shorter protein, able to provide some FY functions but unable to interact with FCA, reduces abundance of some of the larger MW complexes. Suppressor mutants, which specifically disrupt the FY motif through which FCA interacts, also lacked these larger complexes. Our data support a model whereby FCA, perhaps after recognition of a specific RNA feature, transiently interacts with FY, an integral component of the canonical RNA 3′ processing machinery, changing the interactions of the different RNA processing components. These altered interactions would appear to be a necessary step in this RNA-mediated chromatin silencing. PMID:19439664

Altered interactions within FY/AtCPSF complexes required for Arabidopsis FCA-mediated chromatin silencing.

PubMed

Manzano, David; Marquardt, Sebastian; Jones, Alexandra M E; Bäurle, Isabel; Liu, Fuquan; Dean, Caroline

2009-05-26

The role of RNA metabolism in chromatin silencing is now widely recognized. We have studied the Arabidopsis RNA-binding protein FCA that down-regulates an endogenous floral repressor gene through a chromatin mechanism involving histone demethylase activity. This mechanism needs FCA to interact with an RNA 3' processing/polyadenylation factor (FY/Pfs2p), but the subsequent events leading to chromatin changes are unknown. Here, we show that this FCA-FY interaction is required for general chromatin silencing roles where hairpin transgenes induce DNA methylation of an endogenous gene. We also show 2 conserved RNA processing factors, AtCPSF100 and AtCPSF160, but not FCA, are stably associated with FY in vivo and form a range of different-sized complexes. A hypomorphic fy allele producing a shorter protein, able to provide some FY functions but unable to interact with FCA, reduces abundance of some of the larger MW complexes. Suppressor mutants, which specifically disrupt the FY motif through which FCA interacts, also lacked these larger complexes. Our data support a model whereby FCA, perhaps after recognition of a specific RNA feature, transiently interacts with FY, an integral component of the canonical RNA 3' processing machinery, changing the interactions of the different RNA processing components. These altered interactions would appear to be a necessary step in this RNA-mediated chromatin silencing.

Nutrigenomics and nutrigenetics in inflammatory bowel diseases.

PubMed

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

2012-10-01

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

Gemini surfactants mediate efficient mitochondrial gene delivery and expression.

PubMed

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

2015-03-02

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

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.

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

PubMed

Abe, Koichiro; Yu, Philipp

2009-02-01

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

Levels of behavioral organization and the evolution of division of labor

NASA Astrophysics Data System (ADS)

Page, Robert E.; Erber, Joachim

2002-03-01

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

Mediator-dependent Nuclear Receptor Functions

PubMed Central

Chen, Wei; Roeder, Robert

2011-01-01

As gene-specific transcription factors, nuclear hormone receptors are broadly involved in many important biological processes. Their function on target genes requires the stepwise assembly of different coactivator complexes that facilitate chromatin remodeling and subsequent preinitiation complex (PIC) formation and function. Mediator has proved to be a crucial, and general, nuclear receptor-interacting coactivator, with demonstrated functions in transcription steps ranging from chromatin remodeling to subsequent PIC formation and function. Here we discuss (i) our current understanding of pathways that nuclear receptors and other interacting cofactors employ to recruit Mediator to target gene enhancers and promoters, including conditional requirements for the strong NR-Mediator interactions mediated by the NR AF2 domain and the MED1 LXXLLL motifs and (ii) mechanisms by which Mediator acts to transmit signals from enhancer-bound nuclear receptors to the general transcription machinery at core promoters to effect PIC formation and function. PMID:21854863

Gene-Diet Interactions in Childhood Obesity

PubMed Central

Garver, William S

2011-01-01

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

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

USDA-ARS?s Scientific Manuscript database

Leaf shape traits have long been a focus of many disciplines, but searching for complex genetic and environmental interactive mechanisms regulating leaf shape variation has not yet been well developed. The question of the respective roles of gene and environment and how they interplay to modulate l...

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.

Semantics based approach for analyzing disease-target associations.

PubMed

Kaalia, Rama; Ghosh, Indira

2016-08-01

A complex disease is caused by heterogeneous biological interactions between genes and their products along with the influence of environmental factors. There have been many attempts for understanding the cause of these diseases using experimental, statistical and computational methods. In the present work the objective is to address the challenge of representation and integration of information from heterogeneous biomedical aspects of a complex disease using semantics based approach. Semantic web technology is used to design Disease Association Ontology (DAO-db) for representation and integration of disease associated information with diabetes as the case study. The functional associations of disease genes are integrated using RDF graphs of DAO-db. Three semantic web based scoring algorithms (PageRank, HITS (Hyperlink Induced Topic Search) and HITS with semantic weights) are used to score the gene nodes on the basis of their functional interactions in the graph. Disease Association Ontology for Diabetes (DAO-db) provides a standard ontology-driven platform for describing genes, proteins, pathways involved in diabetes and for integrating functional associations from various interaction levels (gene-disease, gene-pathway, gene-function, gene-cellular component and protein-protein interactions). An automatic instance loader module is also developed in present work that helps in adding instances to DAO-db on a large scale. Our ontology provides a framework for querying and analyzing the disease associated information in the form of RDF graphs. The above developed methodology is used to predict novel potential targets involved in diabetes disease from the long list of loose (statistically associated) gene-disease associations. Copyright © 2016 Elsevier Inc. All rights reserved.

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

Cyclin A and the retinoblastoma gene product complex with a common transcription factor.

PubMed

Bandara, L R; Adamczewski, J P; Hunt, T; La Thangue, N B

1991-07-18

The retinoblastoma gene (Rb) product is a negative regulator of cellular proliferation, an effect that could be mediated in part at the transcriptional level through its ability to complex with the sequence-specific transcription factor DRTF1. This interaction is modulated by adenovirus E1a, which sequesters the Rb protein and several other cellular proteins, including cyclin A, a molecule that undergoes cyclical accumulation and destruction during each cell cycle and which is required for cell cycle progression. Cyclin A, which also complexes with DRTF1, facilitates the efficient assembly of the Rb protein into the complex. This suggests a role for cyclin A in regulating transcription and defines a transcription factor through which molecules that regulate the cell cycle in a negative fashion, such as Rb, and in a positive fashion, such as cyclin A, interact. Mutant loss-of-function Rb alleles, which occur in a variety of tumour cells, also fail to complex with E1a and large T antigen. Here we report on a naturally occurring loss-of-function Rb allele encoding a protein that fails to complex with DRTF1. This might explain how mutation in the Rb gene prevents negative growth control.

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.

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

Core Histones and HIRIP3, a Novel Histone-Binding Protein, Directly Interact with WD Repeat Protein HIRA

PubMed Central

Lorain, Stéphanie; Quivy, Jean-Pierre; Monier-Gavelle, Frédérique; Scamps, Christine; Lécluse, Yann; Almouzni, Geneviève; Lipinski, Marc

1998-01-01

The human HIRA gene has been named after Hir1p and Hir2p, two corepressors which together appear to act on chromatin structure to control gene transcription in Saccharomyces cerevisiae. HIRA homologs are expressed in a regulated fashion during mouse and chicken embryogenesis, and the human gene is a major candidate for the DiGeorge syndrome and related developmental disorders caused by a reduction to single dose of a fragment of chromosome 22q. Western blot analysis and double-immunofluorescence experiments using a specific antiserum revealed a primary nuclear localization of HIRA. Similar to Hir1p, HIRA contains seven amino-terminal WD repeats and probably functions as part of a multiprotein complex. HIRA and core histone H2B were found to physically interact in a yeast double-hybrid protein interaction trap, in GST pull-down assays, and in coimmunoprecipitation experiments performed from cellular extracts. In vitro, HIRA also interacted with core histone H4. H2B- and H4-binding domains were overlapping but distinguishable in the carboxy-terminal region of HIRA, and the region for HIRA interaction was mapped to the amino-terminal tail of H2B and the second α helix of H4. HIRIP3 (HIRA-interacting protein 3) is a novel gene product that was identified from its HIRA-binding properties in the yeast protein interaction trap. In vitro, HIRIP3 directly interacted with HIRA but also with core histones H2B and H3, suggesting that a HIRA-HIRIP3-containing complex could function in some aspects of chromatin and histone metabolism. Insufficient production of HIRA, which we report elsewhere interacts with homeodomain-containing DNA-binding factors during mammalian embryogenesis, could perturb the stoichiometric assembly of multimolecular complexes required for normal embryonic development. PMID:9710638

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

PubMed Central

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

2017-01-01

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

Simian Virus 40 Large T Antigen Interacts with Human TFIIB-Related Factor and Small Nuclear RNA-Activating Protein Complex for Transcriptional Activation of TATA-Containing Polymerase III Promoters

PubMed Central

Damania, Blossom; Mital, Renu; Alwine, James C.

1998-01-01

The TATA-binding protein (TBP) is common to the basal transcription factors of all three RNA polymerases, being associated with polymerase-specific TBP-associated factors (TAFs). Simian virus 40 large T antigen has previously been shown to interact with the TBP-TAFII complexes, TFIID (B. Damania and J. C. Alwine, Genes Dev. 10:1369–1381, 1996), and the TBP-TAFI complex, SL1 (W. Zhai, J. Tuan, and L. Comai, Genes Dev. 11:1605–1617, 1997), and in both cases these interactions are critical for transcriptional activation. We show a similar mechanism for activation of the class 3 polymerase III (pol III) promoter for the U6 RNA gene. Large T antigen can activate this promoter, which contains a TATA box and an upstream proximal sequence element but cannot activate the TATA-less, intragenic VAI promoter (a class 2, pol III promoter). Mutants of large T antigen that cannot activate pol II promoters also fail to activate the U6 promoter. We provide evidence that large T antigen can interact with the TBP-containing pol III transcription factor human TFIIB-related factor (hBRF), as well as with at least two of the three TAFs in the pol III-specific small nuclear RNA-activating protein complex (SNAPc). In addition, we demonstrate that large T antigen can cofractionate and coimmunoprecipitate with the hBRF-containing complex TFIIIB derived from HeLa cells infected with a recombinant adenovirus which expresses large T antigen. Hence, similar to its function with pol I and pol II promoters, large T antigen interacts with TBP-containing, basal pol III transcription factors and appears to perform a TAF-like function. PMID:9488448

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.

Design and analysis issues in gene and environment studies

PubMed Central

2012-01-01

Both nurture (environmental) and nature (genetic factors) play an important role in human disease etiology. Traditionally, these effects have been thought of as independent. This perspective is ill informed for non-mendelian complex disorders which result as an interaction between genetics and environment. To understand health and disease we must study how nature and nurture interact. Recent advances in human genomics and high-throughput biotechnology make it possible to study large numbers of genetic markers and gene products simultaneously to explore their interactions with environment. The purpose of this review is to discuss design and analytic issues for gene-environment interaction studies in the “-omics” era, with a focus on environmental and genetic epidemiological studies. We present an expanded environmental genomic disease paradigm. We discuss several study design issues for gene-environmental interaction studies, including confounding and selection bias, measurement of exposures and genotypes. We discuss statistical issues in studying gene-environment interactions in different study designs, such as choices of statistical models, assumptions regarding biological factors, and power and sample size considerations, especially in genome-wide gene-environment studies. Future research directions are also discussed. PMID:23253229

Design and analysis issues in gene and environment studies.

PubMed

Liu, Chen-yu; Maity, Arnab; Lin, Xihong; Wright, Robert O; Christiani, David C

2012-12-19

Both nurture (environmental) and nature (genetic factors) play an important role in human disease etiology. Traditionally, these effects have been thought of as independent. This perspective is ill informed for non-mendelian complex disorders which result as an interaction between genetics and environment. To understand health and disease we must study how nature and nurture interact. Recent advances in human genomics and high-throughput biotechnology make it possible to study large numbers of genetic markers and gene products simultaneously to explore their interactions with environment. The purpose of this review is to discuss design and analytic issues for gene-environment interaction studies in the "-omics" era, with a focus on environmental and genetic epidemiological studies. We present an expanded environmental genomic disease paradigm. We discuss several study design issues for gene-environmental interaction studies, including confounding and selection bias, measurement of exposures and genotypes. We discuss statistical issues in studying gene-environment interactions in different study designs, such as choices of statistical models, assumptions regarding biological factors, and power and sample size considerations, especially in genome-wide gene-environment studies. Future research directions are also discussed.

A systems biology model of the regulatory network in Populus leaves reveals interacting regulators and conserved regulation

PubMed Central

2011-01-01

Background Green plant leaves have always fascinated biologists as hosts for photosynthesis and providers of basic energy to many food webs. Today, comprehensive databases of gene expression data enable us to apply increasingly more advanced computational methods for reverse-engineering the regulatory network of leaves, and to begin to understand the gene interactions underlying complex emergent properties related to stress-response and development. These new systems biology methods are now also being applied to organisms such as Populus, a woody perennial tree, in order to understand the specific characteristics of these species. Results We present a systems biology model of the regulatory network of Populus leaves. The network is reverse-engineered from promoter information and expression profiles of leaf-specific genes measured over a large set of conditions related to stress and developmental. The network model incorporates interactions between regulators, such as synergistic and competitive relationships, by evaluating increasingly more complex regulatory mechanisms, and is therefore able to identify new regulators of leaf development not found by traditional genomics methods based on pair-wise expression similarity. The approach is shown to explain available gene function information and to provide robust prediction of expression levels in new data. We also use the predictive capability of the model to identify condition-specific regulation as well as conserved regulation between Populus and Arabidopsis. Conclusions We outline a computationally inferred model of the regulatory network of Populus leaves, and show how treating genes as interacting, rather than individual, entities identifies new regulators compared to traditional genomics analysis. Although systems biology models should be used with care considering the complexity of regulatory programs and the limitations of current genomics data, methods describing interactions can provide hypotheses about the underlying cause of emergent properties and are needed if we are to identify target genes other than those constituting the "low hanging fruit" of genomic analysis. PMID:21232107

A random set scoring model for prioritization of disease candidate genes using protein complexes and data-mining of GeneRIF, OMIM and PubMed records.

PubMed

Jiang, Li; Edwards, Stefan M; Thomsen, Bo; Workman, Christopher T; Guldbrandtsen, Bernt; Sørensen, Peter

2014-09-24

Prioritizing genetic variants is a challenge because disease susceptibility loci are often located in genes of unknown function or the relationship with the corresponding phenotype is unclear. A global data-mining exercise on the biomedical literature can establish the phenotypic profile of genes with respect to their connection to disease phenotypes. The importance of protein-protein interaction networks in the genetic heterogeneity of common diseases or complex traits is becoming increasingly recognized. Thus, the development of a network-based approach combined with phenotypic profiling would be useful for disease gene prioritization. We developed a random-set scoring model and implemented it to quantify phenotype relevance in a network-based disease gene-prioritization approach. We validated our approach based on different gene phenotypic profiles, which were generated from PubMed abstracts, OMIM, and GeneRIF records. We also investigated the validity of several vocabulary filters and different likelihood thresholds for predicted protein-protein interactions in terms of their effect on the network-based gene-prioritization approach, which relies on text-mining of the phenotype data. Our method demonstrated good precision and sensitivity compared with those of two alternative complex-based prioritization approaches. We then conducted a global ranking of all human genes according to their relevance to a range of human diseases. The resulting accurate ranking of known causal genes supported the reliability of our approach. Moreover, these data suggest many promising novel candidate genes for human disorders that have a complex mode of inheritance. We have implemented and validated a network-based approach to prioritize genes for human diseases based on their phenotypic profile. We have devised a powerful and transparent tool to identify and rank candidate genes. Our global gene prioritization provides a unique resource for the biological interpretation of data from genome-wide association studies, and will help in the understanding of how the associated genetic variants influence disease or quantitative phenotypes.

Decoding the complex genetic causes of heart diseases using systems biology.

PubMed

Djordjevic, Djordje; Deshpande, Vinita; Szczesnik, Tomasz; Yang, Andrian; Humphreys, David T; Giannoulatou, Eleni; Ho, Joshua W K

2015-03-01

The pace of disease gene discovery is still much slower than expected, even with the use of cost-effective DNA sequencing and genotyping technologies. It is increasingly clear that many inherited heart diseases have a more complex polygenic aetiology than previously thought. Understanding the role of gene-gene interactions, epigenetics, and non-coding regulatory regions is becoming increasingly critical in predicting the functional consequences of genetic mutations identified by genome-wide association studies and whole-genome or exome sequencing. A systems biology approach is now being widely employed to systematically discover genes that are involved in heart diseases in humans or relevant animal models through bioinformatics. The overarching premise is that the integration of high-quality causal gene regulatory networks (GRNs), genomics, epigenomics, transcriptomics and other genome-wide data will greatly accelerate the discovery of the complex genetic causes of congenital and complex heart diseases. This review summarises state-of-the-art genomic and bioinformatics techniques that are used in accelerating the pace of disease gene discovery in heart diseases. Accompanying this review, we provide an interactive web-resource for systems biology analysis of mammalian heart development and diseases, CardiacCode ( http://CardiacCode.victorchang.edu.au/ ). CardiacCode features a dataset of over 700 pieces of manually curated genetic or molecular perturbation data, which enables the inference of a cardiac-specific GRN of 280 regulatory relationships between 33 regulator genes and 129 target genes. We believe this growing resource will fill an urgent unmet need to fully realise the true potential of predictive and personalised genomic medicine in tackling human heart disease.

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

PubMed Central

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

2016-01-01

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

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

PubMed

Lobach, Iryna; Fan, Ruzong; Manga, Prashiela

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

TTT and PIKK Complex Genes Reverted to Single Copy Following Polyploidization and Retain Function Despite Massive Retrotransposition in Maize.

PubMed

Garcia, Nelson; Messing, Joachim

2017-01-01

The TEL2, TTI1, and TTI2 proteins are co-chaperones for heat shock protein 90 (HSP90) to regulate the protein folding and maturation of phosphatidylinositol 3-kinase-related kinases (PIKKs). Referred to as the TTT complex, the genes that encode them are highly conserved from man to maize. TTT complex and PIKK genes exist mostly as single copy genes in organisms where they have been characterized. Members of this interacting protein network in maize were identified and synteny analyses were performed to study their evolution. Similar to other species, there is only one copy of each of these genes in maize which was due to a loss of the duplicated copy created by ancient allotetraploidy. Moreover, the retained copies of the TTT complex and the PIKK genes tolerated extensive retrotransposon insertion in their introns that resulted in increased gene lengths and gene body methylation, without apparent effect in normal gene expression and function. The results raise an interesting question on whether the reversion to single copy was due to selection against deleterious unbalanced gene duplications between members of the complex as predicted by the gene balance hypothesis, or due to neutral loss of extra copies. Uneven alteration of dosage either by adding extra copies or modulating gene expression of complex members is being proposed as a means to investigate whether the data supports the gene balance hypothesis or not.

Tetratricopeptide-motif-mediated interaction of FANCG with recombination proteins XRCC3 and BRCA2.

PubMed

Hussain, Shobbir; Wilson, James B; Blom, Eric; Thompson, Larry H; Sung, Patrick; Gordon, Susan M; Kupfer, Gary M; Joenje, Hans; Mathew, Christopher G; Jones, Nigel J

2006-05-10

Fanconi anaemia is an inherited chromosomal instability disorder characterised by cellular sensitivity to DNA interstrand crosslinkers, bone-marrow failure and a high risk of cancer. Eleven FA genes have been identified, one of which, FANCD1, is the breast cancer susceptibility gene BRCA2. At least eight FA proteins form a nuclear core complex required for monoubiquitination of FANCD2. The BRCA2/FANCD1 protein is connected to the FA pathway by interactions with the FANCG and FANCD2 proteins, both of which co-localise with the RAD51 recombinase, which is regulated by BRCA2. These connections raise the question of whether any of the FANC proteins of the core complex might also participate in other complexes involved in homologous recombination repair. We therefore tested known FA proteins for direct interaction with RAD51 and its paralogs XRCC2 and XRCC3. FANCG was found to interact with XRCC3, and this interaction was disrupted by the FA-G patient derived mutation L71P. FANCG was co-immunoprecipitated with both XRCC3 and BRCA2 from extracts of human and hamster cells. The FANCG-XRCC3 and FANCG-BRCA2 interactions did not require the presence of other FA proteins from the core complex, suggesting that FANCG also participates in a DNA repair complex that is downstream and independent of FANCD2 monoubiquitination. Additionally, XRCC3 and BRCA2 proteins co-precipitate in both human and hamster cells and this interaction requires FANCG. The FANCG protein contains multiple tetratricopeptide repeat motifs (TPRs), which function as scaffolds to mediate protein-protein interactions. Mutation of one or more of these motifs disrupted all of the known interactions of FANCG. We propose that FANCG, in addition to stabilising the FA core complex, may have a role in building multiprotein complexes that facilitate homologous recombination repair.

Short cell-penetrating peptides: a model of interactions with gene promoter sites.

PubMed

Khavinson, V Kh; Tarnovskaya, S I; Linkova, N S; Pronyaeva, V E; Shataeva, L K; Yakutseni, P P

2013-01-01

Analysis of the main parameters of molecular mechanics (number of hydrogen bonds, hydrophobic and electrostatic interactions, DNA-peptide complex minimization energy) provided the data to validate the previously proposed qualitative models of peptide-DNA interactions and to evaluate their quantitative characteristics. Based on these estimations, a three-dimensional model of Lys-Glu and Ala-Glu-Asp-Gly peptide interactions with DNA sites (GCAG and ATTTC) located in the promoter zones of genes encoding CD5, IL-2, MMP2, and Tram1 signal molecules.

Reconstructing gene regulatory networks from knock-out data using Gaussian Noise Model and Pearson Correlation Coefficient.

PubMed

Mohamed Salleh, Faridah Hani; Arif, Shereena Mohd; Zainudin, Suhaila; Firdaus-Raih, Mohd

2015-12-01

A gene regulatory network (GRN) is a large and complex network consisting of interacting elements that, over time, affect each other's state. The dynamics of complex gene regulatory processes are difficult to understand using intuitive approaches alone. To overcome this problem, we propose an algorithm for inferring the regulatory interactions from knock-out data using a Gaussian model combines with Pearson Correlation Coefficient (PCC). There are several problems relating to GRN construction that have been outlined in this paper. We demonstrated the ability of our proposed method to (1) predict the presence of regulatory interactions between genes, (2) their directionality and (3) their states (activation or suppression). The algorithm was applied to network sizes of 10 and 50 genes from DREAM3 datasets and network sizes of 10 from DREAM4 datasets. The predicted networks were evaluated based on AUROC and AUPR. We discovered that high false positive values were generated by our GRN prediction methods because the indirect regulations have been wrongly predicted as true relationships. We achieved satisfactory results as the majority of sub-networks achieved AUROC values above 0.5. Copyright © 2015 Elsevier Ltd. All rights reserved.

The binary protein-protein interaction landscape of Escherichia coli

PubMed Central

Rajagopala, Seesandra V.; Vlasblom, James; Arnold, Roland; Franca-Koh, Jonathan; Pakala, Suman B.; Phanse, Sadhna; Ceol, Arnaud; Häuser, Roman; Siszler, Gabriella; Wuchty, Stefan; Emili, Andrew; Babu, Mohan; Aloy, Patrick; Pieper, Rembert; Uetz, Peter

2014-01-01

Efforts to map the Escherichia coli interactome have identified several hundred macromolecular complexes, but direct binary protein-protein interactions (PPIs) have not been surveyed on a large scale. Here we performed yeast two-hybrid screens of 3,305 baits against 3,606 preys (~70% of the E. coli proteome) in duplicate to generate a map of 2,234 interactions, approximately doubling the number of known binary PPIs in E. coli. Integration of binary PPIs and genetic interactions revealed functional dependencies among components involved in cellular processes, including envelope integrity, flagellum assembly and protein quality control. Many of the binary interactions that could be mapped within multi-protein complexes were informative regarding internal topology and indicated that interactions within complexes are significantly more conserved than those interactions connecting different complexes. This resource will be useful for inferring bacterial gene function and provides a draft reference of the basic physical wiring network of this evolutionarily significant model microbe. PMID:24561554

A strategy to apply quantitative epistasis analysis on developmental traits.

PubMed

Labocha, Marta K; Yuan, Wang; Aleman-Meza, Boanerges; Zhong, Weiwei

2017-05-15

Genetic interactions are keys to understand complex traits and evolution. Epistasis analysis is an effective method to map genetic interactions. Large-scale quantitative epistasis analysis has been well established for single cells. However, there is a substantial lack of such studies in multicellular organisms and their complex phenotypes such as development. Here we present a method to extend quantitative epistasis analysis to developmental traits. In the nematode Caenorhabditis elegans, we applied RNA interference on mutants to inactivate two genes, used an imaging system to quantitatively measure phenotypes, and developed a set of statistical methods to extract genetic interactions from phenotypic measurement. Using two different C. elegans developmental phenotypes, body length and sex ratio, as examples, we showed that this method could accommodate various metazoan phenotypes with performances comparable to those methods in single cell growth studies. Comparing with qualitative observations, this method of quantitative epistasis enabled detection of new interactions involving subtle phenotypes. For example, several sex-ratio genes were found to interact with brc-1 and brd-1, the orthologs of the human breast cancer genes BRCA1 and BARD1, respectively. We confirmed the brc-1 interactions with the following genes in DNA damage response: C34F6.1, him-3 (ortholog of HORMAD1, HORMAD2), sdc-1, and set-2 (ortholog of SETD1A, SETD1B, KMT2C, KMT2D), validating the effectiveness of our method in detecting genetic interactions. We developed a reliable, high-throughput method for quantitative epistasis analysis of developmental phenotypes.

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

Connecting the Human Variome Project to nutrigenomics.

PubMed

Kaput, Jim; Evelo, Chris T; Perozzi, Giuditta; van Ommen, Ben; Cotton, Richard

2010-12-01

Nutrigenomics is the science of analyzing and understanding gene-nutrient interactions, which because of the genetic heterogeneity, varying degrees of interaction among gene products, and the environmental diversity is a complex science. Although much knowledge of human diversity has been accumulated, estimates suggest that ~90% of genetic variation has not yet been characterized. Identification of the DNA sequence variants that contribute to nutrition-related disease risk is essential for developing a better understanding of the complex causes of disease in humans, including nutrition-related disease. The Human Variome Project (HVP; http://www.humanvariomeproject.org/) is an international effort to systematically identify genes, their mutations, and their variants associated with phenotypic variability and indications of human disease or phenotype. Since nutrigenomic research uses genetic information in the design and analysis of experiments, the HVP is an essential collaborator for ongoing studies of gene-nutrient interactions. With the advent of next generation sequencing methodologies and the understanding of the undiscovered variation in human genomes, the nutrigenomic community will be generating novel sequence data and results. The guidelines and practices of the HVP can guide and harmonize these efforts.

Planting increases the abundance and structure complexity of soil core functional genes relevant to carbon and nitrogen cycling

PubMed Central

Wang, Feng; Liang, Yuting; Jiang, Yuji; Yang, Yunfeng; Xue, Kai; Xiong, Jinbo; Zhou, Jizhong; Sun, Bo

2015-01-01

Plants have an important impact on soil microbial communities and their functions. However, how plants determine the microbial composition and network interactions is still poorly understood. During a four-year field experiment, we investigated the functional gene composition of three types of soils (Phaeozem, Cambisols and Acrisol) under maize planting and bare fallow regimes located in cold temperate, warm temperate and subtropical regions, respectively. The core genes were identified using high-throughput functional gene microarray (GeoChip 3.0), and functional molecular ecological networks (fMENs) were subsequently developed with the random matrix theory (RMT)-based conceptual framework. Our results demonstrated that planting significantly (P < 0.05) increased the gene alpha-diversity in terms of richness and Shannon – Simpson’s indexes for all three types of soils and 83.5% of microbial alpha-diversity can be explained by the plant factor. Moreover, planting had significant impacts on the microbial community structure and the network interactions of the microbial communities. The calculated network complexity was higher under maize planting than under bare fallow regimes. The increase of the functional genes led to an increase in both soil respiration and nitrification potential with maize planting, indicating that changes in the soil microbial communities and network interactions influenced ecological functioning. PMID:26396042

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

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

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Genes for normal sleep and sleep disorders.

PubMed

Tafti, Mehdi; Maret, Stéphanie; Dauvilliers, Yves

2005-01-01

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

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

PubMed

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

2005-03-30

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

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

PubMed

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

2014-06-01

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

Assessing information content and interactive relationships of subgenomic DNA sequences of the MHC using complexity theory approaches based on the non-extensive statistical mechanics

NASA Astrophysics Data System (ADS)

Karakatsanis, L. P.; Pavlos, G. P.; Iliopoulos, A. C.; Pavlos, E. G.; Clark, P. M.; Duke, J. L.; Monos, D. S.

2018-09-01

This study combines two independent domains of science, the high throughput DNA sequencing capabilities of Genomics and complexity theory from Physics, to assess the information encoded by the different genomic segments of exonic, intronic and intergenic regions of the Major Histocompatibility Complex (MHC) and identify possible interactive relationships. The dynamic and non-extensive statistical characteristics of two well characterized MHC sequences from the homozygous cell lines, PGF and COX, in addition to two other genomic regions of comparable size, used as controls, have been studied using the reconstructed phase space theorem and the non-extensive statistical theory of Tsallis. The results reveal similar non-linear dynamical behavior as far as complexity and self-organization features. In particular, the low-dimensional deterministic nonlinear chaotic and non-extensive statistical character of the DNA sequences was verified with strong multifractal characteristics and long-range correlations. The nonlinear indices repeatedly verified that MHC sequences, whether exonic, intronic or intergenic include varying levels of information and reveal an interaction of the genes with intergenic regions, whereby the lower the number of genes in a region, the less the complexity and information content of the intergenic region. Finally we showed the significance of the intergenic region in the production of the DNA dynamics. The findings reveal interesting content information in all three genomic elements and interactive relationships of the genes with the intergenic regions. The results most likely are relevant to the whole genome and not only to the MHC. These findings are consistent with the ENCODE project, which has now established that the non-coding regions of the genome remain to be of relevance, as they are functionally important and play a significant role in the regulation of expression of genes and coordination of the many biological processes of the cell.

Systems-level analysis of risk genes reveals the modular nature of schizophrenia.

PubMed

Liu, Jiewei; Li, Ming; Luo, Xiong-Jian; Su, Bing

2018-05-19

Schizophrenia (SCZ) is a complex mental disorder with high heritability. Genetic studies (especially recent genome-wide association studies) have identified many risk genes for schizophrenia. However, the physical interactions among the proteins encoded by schizophrenia risk genes remain elusive and it is not known whether the identified risk genes converge on common molecular networks or pathways. Here we systematically investigated the network characteristics of schizophrenia risk genes using the high-confidence protein-protein interactions (PPI) from the human interactome. We found that schizophrenia risk genes encode a densely interconnected PPI network (P = 4.15 × 10 -31 ). Compared with the background genes, the schizophrenia risk genes in the interactome have significantly higher degree (P = 5.39 × 10 -11 ), closeness centrality (P = 7.56 × 10 -11 ), betweeness centrality (P = 1.29 × 10 -11 ), clustering coefficient (P = 2.22 × 10 -2 ), and shorter average shortest path length (P = 7.56 × 10 -11 ). Based on the densely interconnected PPI network, we identified 48 hub genes and 4 modules formed by highly interconnected schizophrenia genes. We showed that the proteins encoded by schizophrenia hub genes have significantly more direct physical interactions. Gene ontology (GO) analysis revealed that cell adhesion, cell cycle, immune system response, and GABR-receptor complex categories were enriched in the modules formed by highly interconnected schizophrenia risk genes. Our study reveals that schizophrenia risk genes encode a densely interconnected molecular network and demonstrates the modular nature of schizophrenia. Copyright © 2018 Elsevier B.V. All rights reserved.

Identification and comprehensive analyses of the CBL and CIPK gene families in wheat (Triticum aestivum L.).

PubMed

Sun, Tao; Wang, Yan; Wang, Meng; Li, Tingting; Zhou, Yi; Wang, Xiatian; Wei, Shuya; He, Guangyuan; Yang, Guangxiao

2015-11-04

Calcineurin B-like (CBL) proteins belong to a unique group of calcium sensors in plant that decode the Ca(2+) signature by interacting with CBL-interacting protein kinases (CIPKs). Although CBL-CIPK complexes have been shown to play important roles in the responses to various stresses in plants, little is known about their functions in wheat. A total of seven TaCBL and 20 TaCIPK genes were amplified from bread wheat, Triticum aestivum cv. Chinese Spring. Reverse-transcriptase-polymerase chain reaction (RT-PCR) and in silico expression analyses showed that TaCBL and TaCIPK genes were expressed at different levels in different tissues, or maintained at nearly constant expression levels during the whole life cycle of the wheat plant. Some TaCBL and TaCIPK genes showed up- or down-regulated expressions during seed germination. Preferential interactions between TaCBLs and TaCIPKs were observed in yeast two-hybrid and bimolecular fluorescence complementation experiments. Analyses of a deletion series of TaCIPK proteins with amino acid variations at the C-terminus provided new insights into the specificity of the interactions between TaCIPKs and TaCBLs, and indicated that the TaCBL-TaCIPK signaling pathway is very complex in wheat because of its hexaploid genome. The expressions of many TaCBLs and TaCIPKs were responsive to abiotic stresses (salt, cold, and simulated drought) and abscisic acid treatment. Transgenic Arabidopsis plants overexpressing TaCIPK24 exhibited improved salt tolerance through increased Na(+) efflux and an enhanced reactive oxygen species scavenging capacity. These results contribute to our understanding of the functions of CBL-CIPK complexes and provide the basis for selecting appropriate genes for in-depth functional studies of CBL-CIPK in wheat.

Extensive cross-regulation of post-transcriptional regulatory networks in Drosophila

DOE PAGES

Stoiber, Marcus H.; Olson, Sara; May, Gemma E.; ...

2015-08-20

In eukaryotic cells, RNAs exist as ribonucleoprotein particles (RNPs). Despite the importance of these complexes in many biological processes, including splicing, polyadenylation, stability, transportation, localization, and translation, their compositions are largely unknown. We affinity-purified 20 distinct RNA-binding proteins (RBPs) from cultured Drosophila melanogaster cells under native conditions and identified both the RNA and protein compositions of these RNP complexes. We identified “high occupancy target” (HOT) RNAs that interact with the majority of the RBPs we surveyed. HOT RNAs encode components of the nonsense-mediated decay and splicing machinery, as well as RNA-binding and translation initiation proteins. The RNP complexes contain proteinsmore » and mRNAs involved in RNA binding and post-transcriptional regulation. Genes with the capacity to produce hundreds of mRNA isoforms, ultracomplex genes, interact extensively with heterogeneous nuclear ribonuclear proteins (hnRNPs). Our data are consistent with a model in which subsets of RNPs include mRNA and protein products from the same gene, indicating the widespread existence of auto-regulatory RNPs. Lastly, from the simultaneous acquisition and integrative analysis of protein and RNA constituents of RNPs, we identify extensive cross-regulatory and hierarchical interactions in post-transcriptional control.« less

Extensive cross-regulation of post-transcriptional regulatory networks in Drosophila

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

Stoiber, Marcus H.; Olson, Sara; May, Gemma E.

In eukaryotic cells, RNAs exist as ribonucleoprotein particles (RNPs). Despite the importance of these complexes in many biological processes, including splicing, polyadenylation, stability, transportation, localization, and translation, their compositions are largely unknown. We affinity-purified 20 distinct RNA-binding proteins (RBPs) from cultured Drosophila melanogaster cells under native conditions and identified both the RNA and protein compositions of these RNP complexes. We identified “high occupancy target” (HOT) RNAs that interact with the majority of the RBPs we surveyed. HOT RNAs encode components of the nonsense-mediated decay and splicing machinery, as well as RNA-binding and translation initiation proteins. The RNP complexes contain proteinsmore » and mRNAs involved in RNA binding and post-transcriptional regulation. Genes with the capacity to produce hundreds of mRNA isoforms, ultracomplex genes, interact extensively with heterogeneous nuclear ribonuclear proteins (hnRNPs). Our data are consistent with a model in which subsets of RNPs include mRNA and protein products from the same gene, indicating the widespread existence of auto-regulatory RNPs. Lastly, from the simultaneous acquisition and integrative analysis of protein and RNA constituents of RNPs, we identify extensive cross-regulatory and hierarchical interactions in post-transcriptional control.« less

Cationic Lipid-Nucleic Acid Complexes for Gene Delivery And Silencing: Pathways And Mechanisms for Plasmid Dna And Sirna

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

Ewert, K.K.; Zidovska, A.; Ahmad, A.

2012-07-17

Motivated by the promises of gene therapy, there is great interest in developing non-viral lipid-based vectors for therapeutic applications due to their low immunogenicity, low toxicity, ease of production, and the potential of transferring large pieces of DNA into cells. In fact, cationic liposome (CL) based vectors are among the prevalent synthetic carriers of nucleic acids (NAs) currently used in gene therapy clinical trials worldwide. These vectors are studied both for gene delivery with CL-DNA complexes and gene silencing with CL-siRNA (short interfering RNA) complexes. However, their transfection efficiencies and silencing efficiencies remain low compared to those of engineered viralmore » vectors. This reflects the currently poor understanding of transfection-related mechanisms at the molecular and self-assembled levels, including a lack of knowledge about interactions between membranes and double stranded NAs and between CL-NA complexes and cellular components. In this review we describe our recent efforts to improve the mechanistic understanding of transfection by CL-NA complexes, which will help to design optimal lipid-based carriers of DNA and siRNA for therapeutic gene delivery and gene silencing.« less

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.

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

Strickland, Madeleine; Stanley, Ann Marie; Wang, Guangshun

Paralogous enzymes arise from gene duplication events that confer a novel function, although it is unclear how cross-reaction between the original and duplicate protein interaction network is minimized. We investigated HPr:EIsugar and NPr:EINtr, the initial complexes of paralogous phosphorylation cascades involved in sugar import and nitrogen regulation in bacteria, respectively. Although the HPr:EIsugar interaction has been well characterized, involving multiple complexes and transient interactions, the exact nature of the NPr:EINtr complex was unknown. We set out to identify the key features of the interaction by performing binding assays and elucidating the structure of NPr in complex with the phosphorylation domainmore » of EINtr (EINNtr), using a hybrid approach involving X-ray, homology, and sparse nuclear magnetic resonance. We found that the overall fold and active-site structure of the two complexes are conserved in order to maintain productive phosphorylation, however, the interface surface potential differs between the two complexes, which prevents cross-reaction.« less

APG: an Active Protein-Gene network model to quantify regulatory signals in complex biological systems.

PubMed

Wang, Jiguang; Sun, Yidan; Zheng, Si; Zhang, Xiang-Sun; Zhou, Huarong; Chen, Luonan

2013-01-01

Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF upstream-regulation and downstream-regulation high-throughput data. Firstly, we theoretically and computationally demonstrate the effectiveness of APG by comparing with the traditional strategy based only on TF downstream-regulation information. We then apply this model to study spontaneous type 2 diabetic Goto-Kakizaki (GK) and Wistar control rats. Our biological experiments validate the theoretical results. In particular, SP1 is found to be a hidden TF with changed regulatory activity, and the loss of SP1 activity contributes to the increased glucose production during diabetes development. APG model provides theoretical basis to quantitatively elucidate transcriptional regulation by modelling TF combinatorial interactions and exploiting multilevel high-throughput information.

APG: an Active Protein-Gene Network Model to Quantify Regulatory Signals in Complex Biological Systems

PubMed Central

Wang, Jiguang; Sun, Yidan; Zheng, Si; Zhang, Xiang-Sun; Zhou, Huarong; Chen, Luonan

2013-01-01

Synergistic interactions among transcription factors (TFs) and their cofactors collectively determine gene expression in complex biological systems. In this work, we develop a novel graphical model, called Active Protein-Gene (APG) network model, to quantify regulatory signals of transcription in complex biomolecular networks through integrating both TF upstream-regulation and downstream-regulation high-throughput data. Firstly, we theoretically and computationally demonstrate the effectiveness of APG by comparing with the traditional strategy based only on TF downstream-regulation information. We then apply this model to study spontaneous type 2 diabetic Goto-Kakizaki (GK) and Wistar control rats. Our biological experiments validate the theoretical results. In particular, SP1 is found to be a hidden TF with changed regulatory activity, and the loss of SP1 activity contributes to the increased glucose production during diabetes development. APG model provides theoretical basis to quantitatively elucidate transcriptional regulation by modelling TF combinatorial interactions and exploiting multilevel high-throughput information. PMID:23346354

Complex Interdependence Regulates Heterotypic Transcription Factor Distribution and Coordinates Cardiogenesis.

PubMed

Luna-Zurita, Luis; Stirnimann, Christian U; Glatt, Sebastian; Kaynak, Bogac L; Thomas, Sean; Baudin, Florence; Samee, Md Abul Hassan; He, Daniel; Small, Eric M; Mileikovsky, Maria; Nagy, Andras; Holloway, Alisha K; Pollard, Katherine S; Müller, Christoph W; Bruneau, Benoit G

2016-02-25

Transcription factors (TFs) are thought to function with partners to achieve specificity and precise quantitative outputs. In the developing heart, heterotypic TF interactions, such as between the T-box TF TBX5 and the homeodomain TF NKX2-5, have been proposed as a mechanism for human congenital heart defects. We report extensive and complex interdependent genomic occupancy of TBX5, NKX2-5, and the zinc finger TF GATA4 coordinately controlling cardiac gene expression, differentiation, and morphogenesis. Interdependent binding serves not only to co-regulate gene expression but also to prevent TFs from distributing to ectopic loci and activate lineage-inappropriate genes. We define preferential motif arrangements for TBX5 and NKX2-5 cooperative binding sites, supported at the atomic level by their co-crystal structure bound to DNA, revealing a direct interaction between the two factors and induced DNA bending. Complex interdependent binding mechanisms reveal tightly regulated TF genomic distribution and define a combinatorial logic for heterotypic TF regulation of differentiation. Copyright © 2016 Elsevier Inc. All rights reserved.

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

PubMed

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

2017-06-23

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

The aryl hydrocarbon receptor and glucocorticoid receptor interact to activate human metallothionein 2A

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

Sato, Shoko, E-mail: satosho@rs.tus.ac.jp; Shirakawa, Hitoshi, E-mail: shirakah@m.tohoku.ac.jp; Tomita, Shuhei, E-mail: tomita@med.tottori-u.ac.jp

2013-11-15

Although the aryl hydrocarbon receptor (AHR) and glucocorticoid receptor (GR) play essential roles in mammalian development, stress responses, and other physiological events, crosstalk between these receptors has been the subject of much debate. Metallothioneins are classic glucocorticoid-inducible genes that were reported to increase upon treatment with AHR agonists in rodent tissues and cultured human cells. In this study, the mechanism of human metallothionein 2A (MT2A) gene transcription activation by AHR was investigated. Cotreatment with 3-methylcholanthrene and dexamethasone, agonists of AHR and GR respectively, synergistically increased MT2A mRNA levels in HepG2 cells. MT2A induction was suppressed by RNA interference against AHRmore » or GR. Coimmunoprecipitation experiments revealed a physical interaction between AHR and GR proteins. Moreover, chromatin immunoprecipitation assays indicated that AHR was recruited to the glucocorticoid response element in the MT2A promoter. Thus, we provide a novel mechanism whereby AHR modulates expression of human MT2A via the glucocorticoid response element and protein–protein interactions with GR. - Highlights: • Aryl hydrocarbon receptor forms a complex with glucocorticoid receptor in cells. • Human metallothionein gene is regulated by the AHR and GR interaction. • AHR–GR complex binds to glucocorticoid response element in metallothionein gene. • We demonstrated a novel transcriptional mechanism via AHR and GR interaction.« less

SWI/SNF interacts with cleavage and polyadenylation factors and facilitates pre-mRNA 3' end processing.

PubMed

Yu, Simei; Jordán-Pla, Antonio; Gañez-Zapater, Antoni; Jain, Shruti; Rolicka, Anna; Östlund Farrants, Ann-Kristin; Visa, Neus

2018-05-31

SWI/SNF complexes associate with genes and regulate transcription by altering the chromatin at the promoter. It has recently been shown that these complexes play a role in pre-mRNA processing by associating at alternative splice sites. Here, we show that SWI/SNF complexes are involved also in pre-mRNA 3' end maturation by facilitating 3' end cleavage of specific pre-mRNAs. Comparative proteomics show that SWI/SNF ATPases interact physically with subunits of the cleavage and polyadenylation complexes in fly and human cells. In Drosophila melanogaster, the SWI/SNF ATPase Brahma (dBRM) interacts with the CPSF6 subunit of cleavage factor I. We have investigated the function of dBRM in 3' end formation in S2 cells by RNA interference, single-gene analysis and RNA sequencing. Our data show that dBRM facilitates pre-mRNA cleavage in two different ways: by promoting the association of CPSF6 to the cleavage region and by stabilizing positioned nucleosomes downstream of the cleavage site. These findings show that SWI/SNF complexes play a role also in the cleavage of specific pre-mRNAs in animal cells.

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

Bioinformatic prediction of leader genes in human periodontitis.

PubMed

Covani, Ugo; Marconcini, Simone; Giacomelli, Luca; Sivozhelevov, Victor; Barone, Antonio; Nicolini, Claudio

2008-10-01

Genes involved in different biologic processes form complex interaction networks. However, only a few have a high number of interactions with the other genes in the network. In previous bioinformatics and experimental studies concerning the T lymphocyte cell cycle, these genes were identified and termed "leader genes." In this work, genes involved in human periodontitis were tentatively identified and ranked according to their number of interactions to obtain a preliminary, broader view of molecular mechanisms of periodontitis and plan targeted experimentation. Genes were identified with interrelated queries of several databases. The interactions among these genes were mapped and given a significance score. The weighted number of links (weighted sum of scores for every interaction in which the given gene is involved) was calculated for each gene. Genes were clustered according to this parameter. The genes in the highest cluster were termed leader genes. Sixty-one genes involved or potentially involved in periodontitis were identified. Only five were identified as leader genes, whereas 12 others were ranked in an immediately lower cluster. For 10 of 17 genes there is evidence of involvement in periodontitis; seven new genes that are potentially involved in this disease were identified. The involvement in periodontitis has been completely established for only two leader genes. We applied a validated bioinformatics algorithm to increase our knowledge of molecular mechanisms of periodontitis. Even with the limitations of this ab initio analysis, this theoretical study can suggest ad hoc experimentation targeted on significant genes and, therefore, simpler than mass-scale molecular genomics. Moreover, the identification of leader genes might suggest new potential risk factors and therapeutic targets.

From Interaction to Co-Association —A Fisher r-To-z Transformation-Based Simple Statistic for Real World Genome-Wide Association Study

PubMed Central

Yuan, Zhongshang; Liu, Hong; Zhang, Xiaoshuai; Li, Fangyu; Zhao, Jinghua; Zhang, Furen; Xue, Fuzhong

2013-01-01

Currently, the genetic variants identified by genome wide association study (GWAS) generally only account for a small proportion of the total heritability for complex disease. One crucial reason is the underutilization of gene-gene joint effects commonly encountered in GWAS, which includes their main effects and co-association. However, gene-gene co-association is often customarily put into the framework of gene-gene interaction vaguely. From the causal graph perspective, we elucidate in detail the concept and rationality of gene-gene co-association as well as its relationship with traditional gene-gene interaction, and propose two Fisher r-to-z transformation-based simple statistics to detect it. Three series of simulations further highlight that gene-gene co-association refers to the extent to which the joint effects of two genes differs from the main effects, not only due to the traditional interaction under the nearly independent condition but the correlation between two genes. The proposed statistics are more powerful than logistic regression under various situations, cannot be affected by linkage disequilibrium and can have acceptable false positive rate as long as strictly following the reasonable GWAS data analysis roadmap. Furthermore, an application to gene pathway analysis associated with leprosy confirms in practice that our proposed gene-gene co-association concepts as well as the correspondingly proposed statistics are strongly in line with reality. PMID:23923021

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 stable transcription factor complex nucleated by oligomeric AML1–ETO controls leukaemogenesis

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

Sun, Xiao-Jian; Wang, Zhanxin; Wang, Lan

2013-06-30

Transcription factors are frequently altered in leukaemia through chromosomal translocation, mutation or aberrant expression. AML1–ETO, a fusion protein generated by the t(8;21) translocation in acute myeloid leukaemia, is a transcription factor implicated in both gene repression and activation. AML1–ETO oligomerization, mediated by the NHR2 domain, is critical for leukaemogenesis, making it important to identify co-regulatory factors that ‘read’ the NHR2 oligomerization and contribute to leukaemogenesis. Here we show that, in human leukaemic cells, AML1–ETO resides in and functions through a stable AML1–ETO-containing transcription factor complex (AETFC) that contains several haematopoietic transcription (co)factors. These AETFC components stabilize the complex through multivalentmore » interactions, provide multiple DNA-binding domains for diverse target genes, co-localize genome wide, cooperatively regulate gene expression, and contribute to leukaemogenesis. Within the AETFC complex, AML1–ETO oligomerization is required for a specific interaction between the oligomerized NHR2 domain and a novel NHR2-binding (N2B) motif in E proteins. Crystallographic analysis of the NHR2–N2B complex reveals a unique interaction pattern in which an N2B peptide makes direct contact with side chains of two NHR2 domains as a dimer, providing a novel model of how dimeric/oligomeric transcription factors create a new protein-binding interface through dimerization/oligomerization. Intriguingly, disruption of this interaction by point mutations abrogates AML1–ETO-induced haematopoietic stem/progenitor cell self-renewal and leukaemogenesis. These results reveal new mechanisms of action of AML1–ETO, and provide a potential therapeutic target in t(8;21)-positive acute myeloid leukaemia.« less

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

GeneNetFinder2: Improved Inference of Dynamic Gene Regulatory Relations with Multiple Regulators.

PubMed

Han, Kyungsook; Lee, Jeonghoon

2016-01-01

A gene involved in complex regulatory interactions may have multiple regulators since gene expression in such interactions is often controlled by more than one gene. Another thing that makes gene regulatory interactions complicated is that regulatory interactions are not static, but change over time during the cell cycle. Most research so far has focused on identifying gene regulatory relations between individual genes in a particular stage of the cell cycle. In this study we developed a method for identifying dynamic gene regulations of several types from the time-series gene expression data. The method can find gene regulations with multiple regulators that work in combination or individually as well as those with single regulators. The method has been implemented as the second version of GeneNetFinder (hereafter called GeneNetFinder2) and tested on several gene expression datasets. Experimental results with gene expression data revealed the existence of genes that are not regulated by individual genes but rather by a combination of several genes. Such gene regulatory relations cannot be found by conventional methods. Our method finds such regulatory relations as well as those with multiple, independent regulators or single regulators, and represents gene regulatory relations as a dynamic network in which different gene regulatory relations are shown in different stages of the cell cycle. GeneNetFinder2 is available at http://bclab.inha.ac.kr/GeneNetFinder and will be useful for modeling dynamic gene regulations with multiple regulators.

Activation-dependent intrachromosomal interactions formed by the TNF gene promoter and two distal enhancers

PubMed Central

Tsytsykova, Alla V.; Rajsbaum, Ricardo; Falvo, James V.; Ligeiro, Filipa; Neely, Simon R.; Goldfeld, Anne E.

2007-01-01

Here we provide a mechanism for specific, efficient transcription of the TNF gene and, potentially, other genes residing within multigene loci. We identify and characterize highly conserved noncoding elements flanking the TNF gene, which undergo activation-dependent intrachromosomal interactions. These elements, hypersensitive site (HSS)−9 and HSS+3 (9 kb upstream and 3 kb downstream of the TNF gene, respectively), contain DNase I hypersensitive sites in naive, T helper 1, and T helper 2 primary T cells. Both HSS-9 and HSS+3 inducibly associate with acetylated histones, indicative of chromatin remodeling, bind the transcription factor nuclear factor of activated T cells (NFAT)p in vitro and in vivo, and function as enhancers of NFAT-dependent transactivation mediated by the TNF promoter. Using the chromosome conformation capture assay, we demonstrate that upon T cell activation intrachromosomal looping occurs in the TNF locus. HSS-9 and HSS+3 each associate with the TNF promoter and with each other, circularizing the TNF gene and bringing NFAT-containing nucleoprotein complexes into close proximity. TNF gene regulation thus reveals a mode of intrachromosomal interaction that combines a looped gene topology with interactions between enhancers and a gene promoter. PMID:17940009

Nuclear import of transcription factor BR-C is mediated by its interaction with RACK1.

PubMed

Cheng, Daojun; Qian, Wenliang; Wang, Yonghu; Meng, Meng; Wei, Ling; Li, Zhiqing; Kang, Lixia; Peng, Jian; Xia, Qingyou

2014-01-01

The transcription factor Broad Complex (BR-C) is an early ecdysone response gene in insects and contains two types of domains: two zinc finger domains for the activation of gene transcription and a Bric-a-brac/Tramtrack/Broad complex (BTB) domain for protein-protein interaction. Although the mechanism of zinc finger-mediated gene transcription is well studied, the partners interacting with the BTB domain of BR-C has not been elucidated until now. Here, we performed a yeast two-hybrid screen using the BTB domain of silkworm BR-C as bait and identified the receptor for activated C-kinase 1 (RACK1), a scaffolding/anchoring protein, as the novel partner capable of interacting with BR-C. The interaction between BR-C and RACK1 was further confirmed by far-western blotting and pull-down assays. Importantly, the disruption of this interaction, via RNAi against the endogenous RACK1 gene or deletion of the BTB domain, abolished the nuclear import of BR-C in BmN4 cells. In addition, RNAi against the endogenous PKC gene as well as phosphorylation-deficient mutation of the predicted PKC phosphorylation sites at either Ser373 or Thr406 in BR-C phenocopied RACK1 RNAi and altered the nuclear localization of BR-C. However, when BTB domain was deleted, phosphorylation mimics of either Ser373 or Thr406 had no effect on the nuclear import of BR-C. Moreover, mutating the PKC phosphorylation sites at Ser373 and Thr406 or deleting the BTB domain significantly decreased the transcriptional activation of a BR-C target gene. Given that RACK1 is necessary for recruiting PKC to close and phosphorylate target proteins, we suggest that the PKC-mediated phosphorylation and nuclear import of BR-C is determined by its interaction with RACK1. This novel finding will be helpful for further deciphering the mechanism underlying the role of BR-C proteins during insect development.

Nuclear Import of Transcription Factor BR-C Is Mediated by Its Interaction with RACK1

PubMed Central

Wang, Yonghu; Meng, Meng; Wei, Ling; Li, Zhiqing; Kang, Lixia; Peng, Jian; Xia, Qingyou

2014-01-01

The transcription factor Broad Complex (BR-C) is an early ecdysone response gene in insects and contains two types of domains: two zinc finger domains for the activation of gene transcription and a Bric-a-brac/Tramtrack/Broad complex (BTB) domain for protein-protein interaction. Although the mechanism of zinc finger-mediated gene transcription is well studied, the partners interacting with the BTB domain of BR-C has not been elucidated until now. Here, we performed a yeast two-hybrid screen using the BTB domain of silkworm BR-C as bait and identified the receptor for activated C-kinase 1 (RACK1), a scaffolding/anchoring protein, as the novel partner capable of interacting with BR-C. The interaction between BR-C and RACK1 was further confirmed by far-western blotting and pull-down assays. Importantly, the disruption of this interaction, via RNAi against the endogenous RACK1 gene or deletion of the BTB domain, abolished the nuclear import of BR-C in BmN4 cells. In addition, RNAi against the endogenous PKC gene as well as phosphorylation-deficient mutation of the predicted PKC phosphorylation sites at either Ser373 or Thr406 in BR-C phenocopied RACK1 RNAi and altered the nuclear localization of BR-C. However, when BTB domain was deleted, phosphorylation mimics of either Ser373 or Thr406 had no effect on the nuclear import of BR-C. Moreover, mutating the PKC phosphorylation sites at Ser373 and Thr406 or deleting the BTB domain significantly decreased the transcriptional activation of a BR-C target gene. Given that RACK1 is necessary for recruiting PKC to close and phosphorylate target proteins, we suggest that the PKC-mediated phosphorylation and nuclear import of BR-C is determined by its interaction with RACK1. This novel finding will be helpful for further deciphering the mechanism underlying the role of BR-C proteins during insect development. PMID:25280016

Long Non-Coding RNAs (lncRNAs) of Sea Cucumber: Large-Scale Prediction, Expression Profiling, Non-Coding Network Construction, and lncRNA-microRNA-Gene Interaction Analysis of lncRNAs in Apostichopus japonicus and Holothuria glaberrima During LPS Challenge and Radial Organ Complex Regeneration.

PubMed

Mu, Chuang; Wang, Ruijia; Li, Tianqi; Li, Yuqiang; Tian, Meilin; Jiao, Wenqian; Huang, Xiaoting; Zhang, Lingling; Hu, Xiaoli; Wang, Shi; Bao, Zhenmin

2016-08-01

Long non-coding RNA (lncRNA) structurally resembles mRNA but cannot be translated into protein. Although the systematic identification and characterization of lncRNAs have been increasingly reported in model species, information concerning non-model species is still lacking. Here, we report the first systematic identification and characterization of lncRNAs in two sea cucumber species: (1) Apostichopus japonicus during lipopolysaccharide (LPS) challenge and in heathy tissues and (2) Holothuria glaberrima during radial organ complex regeneration, using RNA-seq datasets and bioinformatics analysis. We identified A. japonicus and H. glaberrima lncRNAs that were differentially expressed during LPS challenge and radial organ complex regeneration, respectively. Notably, the predicted lncRNA-microRNA-gene trinities revealed that, in addition to targeting protein-coding transcripts, miRNAs might also target lncRNAs, thereby participating in a potential novel layer of regulatory interactions among non-coding RNA classes in echinoderms. Furthermore, the constructed coding-non-coding network implied the potential involvement of lncRNA-gene interactions during the regulation of several important genes (e.g., Toll-like receptor 1 [TLR1] and transglutaminase-1 [TGM1]) in response to LPS challenge and radial organ complex regeneration in sea cucumbers. Overall, this pioneer systematic identification, annotation, and characterization of lncRNAs in echinoderm pave the way for similar studies and future genetic, genomic, and evolutionary research in non-model species.

Dissecting the Calcium-Induced Differentiation of Human Primary Keratinocytes Stem Cells by Integrative and Structural Network Analyses

PubMed Central

Toufighi, Kiana; Yang, Jae-Seong; Luis, Nuno Miguel; Aznar Benitah, Salvador; Lehner, Ben; Serrano, Luis; Kiel, Christina

2015-01-01

The molecular details underlying the time-dependent assembly of protein complexes in cellular networks, such as those that occur during differentiation, are largely unexplored. Focusing on the calcium-induced differentiation of primary human keratinocytes as a model system for a major cellular reorganization process, we look at the expression of genes whose products are involved in manually-annotated protein complexes. Clustering analyses revealed only moderate co-expression of functionally related proteins during differentiation. However, when we looked at protein complexes, we found that the majority (55%) are composed of non-dynamic and dynamic gene products (‘di-chromatic’), 19% are non-dynamic, and 26% only dynamic. Considering three-dimensional protein structures to predict steric interactions, we found that proteins encoded by dynamic genes frequently interact with a common non-dynamic protein in a mutually exclusive fashion. This suggests that during differentiation, complex assemblies may also change through variation in the abundance of proteins that compete for binding to common proteins as found in some cases for paralogous proteins. Considering the example of the TNF-α/NFκB signaling complex, we suggest that the same core complex can guide signals into diverse context-specific outputs by addition of time specific expressed subunits, while keeping other cellular functions constant. Thus, our analysis provides evidence that complex assembly with stable core components and competition could contribute to cell differentiation. PMID:25946651

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

PubMed Central

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

2015-01-01

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

Integration of biological networks and gene expression data using Cytoscape

PubMed Central

Cline, Melissa S; Smoot, Michael; Cerami, Ethan; Kuchinsky, Allan; Landys, Nerius; Workman, Chris; Christmas, Rowan; Avila-Campilo, Iliana; Creech, Michael; Gross, Benjamin; Hanspers, Kristina; Isserlin, Ruth; Kelley, Ryan; Killcoyne, Sarah; Lotia, Samad; Maere, Steven; Morris, John; Ono, Keiichiro; Pavlovic, Vuk; Pico, Alexander R; Vailaya, Aditya; Wang, Peng-Liang; Adler, Annette; Conklin, Bruce R; Hood, Leroy; Kuiper, Martin; Sander, Chris; Schmulevich, Ilya; Schwikowski, Benno; Warner, Guy J; Ideker, Trey; Bader, Gary D

2013-01-01

Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape. PMID:17947979

Control of developmentally primed erythroid genes by combinatorial co-repressor actions

PubMed Central

Stadhouders, Ralph; Cico, Alba; Stephen, Tharshana; Thongjuea, Supat; Kolovos, Petros; Baymaz, H. Irem; Yu, Xiao; Demmers, Jeroen; Bezstarosti, Karel; Maas, Alex; Barroca, Vilma; Kockx, Christel; Ozgur, Zeliha; van Ijcken, Wilfred; Arcangeli, Marie-Laure; Andrieu-Soler, Charlotte; Lenhard, Boris; Grosveld, Frank; Soler, Eric

2015-01-01

How transcription factors (TFs) cooperate within large protein complexes to allow rapid modulation of gene expression during development is still largely unknown. Here we show that the key haematopoietic LIM-domain-binding protein-1 (LDB1) TF complex contains several activator and repressor components that together maintain an erythroid-specific gene expression programme primed for rapid activation until differentiation is induced. A combination of proteomics, functional genomics and in vivo studies presented here identifies known and novel co-repressors, most notably the ETO2 and IRF2BP2 proteins, involved in maintaining this primed state. The ETO2–IRF2BP2 axis, interacting with the NCOR1/SMRT co-repressor complex, suppresses the expression of the vast majority of archetypical erythroid genes and pathways until its decommissioning at the onset of terminal erythroid differentiation. Our experiments demonstrate that multimeric regulatory complexes feature a dynamic interplay between activating and repressing components that determines lineage-specific gene expression and cellular differentiation. PMID:26593974

The RavA-ViaA Chaperone-Like System Interacts with and Modulates the Activity of the Fumarate Reductase Respiratory Complex.

PubMed

Wong, Keith S; Bhandari, Vaibhav; Janga, Sarath Chandra; Houry, Walid A

2017-01-20

Regulatory ATPase variant A (RavA) is a MoxR AAA+ protein that functions together with a partner protein that we termed VWA interacting with AAA+ ATPase (ViaA) containing a von Willebrand Factor A domain. However, the functional role of RavA-ViaA in the cell is not yet well established. Here, we show that RavA-ViaA are functionally associated with anaerobic respiration in Escherichia coli through interactions with the fumarate reductase (Frd) electron transport complex. Expression analysis of ravA and viaA genes showed that both proteins are co-expressed with multiple anaerobic respiratory genes, many of which are regulated by the anaerobic transcriptional regulator Fnr. Consistently, the expression of both ravA and viaA was found to be dependent on Fnr in cells grown under oxygen-limiting condition. ViaA was found to physically interact with FrdA, the flavin-containing subunit of the Frd complex. Both RavA and the Fe-S-containing subunit of the Frd complex, FrdB, regulate this interaction. Importantly, Frd activity was observed to increase in the absence of RavA and ViaA. This indicates that RavA and ViaA modulate the activity of the Frd complex, signifying a potential regulatory chaperone-like function for RavA-ViaA during bacterial anaerobic respiration with fumarate as the terminal electron acceptor. Copyright © 2016 Elsevier Ltd. All rights reserved.

Construction of the model for the Genetic Analysis Workshop 14 simulated data: genotype-phenotype relationships, gene interaction, linkage, association, disequilibrium, and ascertainment effects for a complex phenotype.

PubMed

Greenberg, David A; Zhang, Junying; Shmulewitz, Dvora; Strug, Lisa J; Zimmerman, Regina; Singh, Veena; Marathe, Sudhir

2005-12-30

The Genetic Analysis Workshop 14 simulated dataset was designed 1) To test the ability to find genes related to a complex disease (such as alcoholism). Such a disease may be given a variety of definitions by different investigators, have associated endophenotypes that are common in the general population, and is likely to be not one disease but a heterogeneous collection of clinically similar, but genetically distinct, entities. 2) To observe the effect on genetic analysis and gene discovery of a complex set of gene x gene interactions. 3) To allow comparison of microsatellite vs. large-scale single-nucleotide polymorphism (SNP) data. 4) To allow testing of association to identify the disease gene and the effect of moderate marker x marker linkage disequilibrium. 5) To observe the effect of different ascertainment/disease definition schemes on the analysis. Data was distributed in two forms. Data distributed to participants contained about 1,000 SNPs and 400 microsatellite markers. Internet-obtainable data consisted of a finer 10,000 SNP map, which also contained data on controls. While disease characteristics and parameters were constant, four "studies" used varying ascertainment schemes based on differing beliefs about disease characteristics. One of the studies contained multiplex two- and three-generation pedigrees with at least four affected members. The simulated disease was a psychiatric condition with many associated behaviors (endophenotypes), almost all of which were genetic in origin. The underlying disease model contained four major genes and two modifier genes. The four major genes interacted with each other to produce three different phenotypes, which were themselves heterogeneous. The population parameters were calibrated so that the major genes could be discovered by linkage analysis in most datasets. The association evidence was more difficult to calibrate but was designed to find statistically significant association in 50% of datasets. We also simulated some marker x marker linkage disequilibrium around some of the genes and also in areas without disease genes. We tried two different methods to simulate the linkage disequilibrium.

An integrative approach to inferring biologically meaningful gene modules.

PubMed

Cho, Ji-Hoon; Wang, Kai; Galas, David J

2011-07-26

The ability to construct biologically meaningful gene networks and modules is critical for contemporary systems biology. Though recent studies have demonstrated the power of using gene modules to shed light on the functioning of complex biological systems, most modules in these networks have shown little association with meaningful biological function. We have devised a method which directly incorporates gene ontology (GO) annotation in construction of gene modules in order to gain better functional association. We have devised a method, Semantic Similarity-Integrated approach for Modularization (SSIM) that integrates various gene-gene pairwise similarity values, including information obtained from gene expression, protein-protein interactions and GO annotations, in the construction of modules using affinity propagation clustering. We demonstrated the performance of the proposed method using data from two complex biological responses: 1. the osmotic shock response in Saccharomyces cerevisiae, and 2. the prion-induced pathogenic mouse model. In comparison with two previously reported algorithms, modules identified by SSIM showed significantly stronger association with biological functions. The incorporation of semantic similarity based on GO annotation with gene expression and protein-protein interaction data can greatly enhance the functional relevance of inferred gene modules. In addition, the SSIM approach can also reveal the hierarchical structure of gene modules to gain a broader functional view of the biological system. Hence, the proposed method can facilitate comprehensive and in-depth analysis of high throughput experimental data at the gene network level.

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

PubMed

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

2017-01-01

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

Application of network methods for understanding evolutionary dynamics in discrete habitats.

PubMed

Greenbaum, Gili; Fefferman, Nina H

2017-06-01

In populations occupying discrete habitat patches, gene flow between habitat patches may form an intricate population structure. In such structures, the evolutionary dynamics resulting from interaction of gene-flow patterns with other evolutionary forces may be exceedingly complex. Several models describing gene flow between discrete habitat patches have been presented in the population-genetics literature; however, these models have usually addressed relatively simple settings of habitable patches and have stopped short of providing general methodologies for addressing nontrivial gene-flow patterns. In the last decades, network theory - a branch of discrete mathematics concerned with complex interactions between discrete elements - has been applied to address several problems in population genetics by modelling gene flow between habitat patches using networks. Here, we present the idea and concepts of modelling complex gene flows in discrete habitats using networks. Our goal is to raise awareness to existing network theory applications in molecular ecology studies, as well as to outline the current and potential contribution of network methods to the understanding of evolutionary dynamics in discrete habitats. We review the main branches of network theory that have been, or that we believe potentially could be, applied to population genetics and molecular ecology research. We address applications to theoretical modelling and to empirical population-genetic studies, and we highlight future directions for extending the integration of network science with molecular ecology. © 2017 John Wiley & Sons Ltd.

The QQS orphan gene regulates carbon and nitrogen partitioning across species via NF-YC interactions

USDA-ARS?s Scientific Manuscript database

The allocation of carbon and nitrogen resources to the synthesis of plant proteins, carbohydrates, and lipids is complex and under the control of many genes; much remains to be understood about this process. QQS (Qua Quine Starch, At3g30720), an orphan gene unique to Arabidopsis thaliana, regulates...

Gene Expression Profiling in Rodent Models for Schizophrenia

PubMed Central

Schijndel, Jessica E. Van; Martens, Gerard J.M

2010-01-01

The complex neurodevelopmental disorder schizophrenia is thought to be induced by an interaction between predisposing genes and environmental stressors. In order to get a better insight into the aetiology of this complex disorder, animal models have been developed. In this review, we summarize mRNA expression profiling studies on neurodevelopmental, pharmacological and genetic animal models for schizophrenia. We discuss parallels and contradictions among these studies, and propose strategies for future research. PMID:21629445

Degrees of separation as a statistical tool for evaluating candidate genes.

PubMed

Nelson, Ronald M; Pettersson, Mats E

2014-12-01

Selection of candidate genes is an important step in the exploration of complex genetic architecture. The number of gene networks available is increasing and these can provide information to help with candidate gene selection. It is currently common to use the degree of connectedness in gene networks as validation in Genome Wide Association (GWA) and Quantitative Trait Locus (QTL) mapping studies. However, it can cause misleading results if not validated properly. Here we present a method and tool for validating the gene pairs from GWA studies given the context of the network they co-occur in. It ensures that proposed interactions and gene associations are not statistical artefacts inherent to the specific gene network architecture. The CandidateBacon package provides an easy and efficient method to calculate the average degree of separation (DoS) between pairs of genes to currently available gene networks. We show how these empirical estimates of average connectedness are used to validate candidate gene pairs. Validation of interacting genes by comparing their connectedness with the average connectedness in the gene network will provide support for said interactions by utilising the growing amount of gene network information available. Copyright © 2014 Elsevier Ltd. All rights reserved.

Host cell interactome of PA protein of H5N1 influenza A virus in chicken cells.

PubMed

Wang, Qiao; Li, Qinghe; Liu, Ranran; Zheng, Maiqing; Wen, Jie; Zhao, Guiping

2016-03-16

Influenza A virus (IAV) heavily depends on viral-host protein interactions in order to replicate and spread. Identification of host factors that interact with viral proteins plays crucial roles in understanding the mechanism of IAV infection. Here we report the interaction landscape of H5N1 IAV PA protein in chicken cells through the use of affinity purification and mass spectrometry. PA protein was expressed in chicken cells and PA interacting complexes were captured by co-immunoprecipitation and analyzed by mass spectrometry. A total of 134 proteins were identified as PA-host interacting factors. Protein complexes including the minichromosome maintenance complex (MCM), 26S proteasome and the coat protein I (COPI) complex associated with PA in chicken cells, indicating the essential roles of these functional protein complexes during the course of IAV infection. Gene Ontology and pathway enrichment analysis both showed strong enrichment of PA interacting proteins in the category of DNA replication, covering genes such as PCNA, MCM2, MCM3, MCM4, MCM5 and MCM7. This study has uncovered the comprehensive interactome of H5N1 IAV PA protein in its chicken host and helps to establish the foundation for further investigation into the newly identified viral-host interactions. Influenza A virus (IAV) is a great threat to public health and avian production. However, the manner in which avian IAV recruits the host cellular machinery for replication and how the host antagonizes the IAV infection was previously poorly understood. Here we present the viral-host interactome of the H5N1 IAV PA protein and reveal the comprehensive association of host factors with PA. Copyright © 2016 Elsevier B.V. All rights reserved.

Inherited variation in immune response genes in follicular lymphoma and diffuse large B-cell lymphoma.

PubMed

Nielsen, Kaspar Rene; Steffensen, Rudi; Haunstrup, Thure Mors; Bødker, Julie Støve; Dybkær, Karen; Baech, John; Bøgsted, Martin; Johnsen, Hans Erik

2015-01-01

Diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL) both depend on immune-mediated survival and proliferation signals from the tumor microenvironment. Inherited genetic variation influences this complex interaction. A total of 89 studies investigating immune-response genes in DLBCL and FL were critically reviewed. Relatively consistent association exists for variation in the tumor necrosis factor alpha (TNFA) and interleukin-10 loci and DLBCL risk; for DLBCL outcome association with the TNFA locus exists. Variations at chromosome 6p31-32 were associated with FL risk. Importantly, individual risk alleles have been shown to interact with each other. We suggest that the pathogenetic impact of polymorphic genes should include gene-gene interaction analysis and should be validated in preclinical model systems of normal B lymphopoiesis and B-cell malignancies. In the future, large cohort studies of interactions and genome-wide association studies are needed to extend the present findings and explore new risk alleles to be studied in preclinical models.

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

PubMed

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

2017-01-01

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

Revealing complex function, process and pathway interactions with high-throughput expression and biological annotation data.

PubMed

Singh, Nitesh Kumar; Ernst, Mathias; Liebscher, Volkmar; Fuellen, Georg; Taher, Leila

2016-10-20

The biological relationships both between and within the functions, processes and pathways that operate within complex biological systems are only poorly characterized, making the interpretation of large scale gene expression datasets extremely challenging. Here, we present an approach that integrates gene expression and biological annotation data to identify and describe the interactions between biological functions, processes and pathways that govern a phenotype of interest. The product is a global, interconnected network, not of genes but of functions, processes and pathways, that represents the biological relationships within the system. We validated our approach on two high-throughput expression datasets describing organismal and organ development. Our findings are well supported by the available literature, confirming that developmental processes and apoptosis play key roles in cell differentiation. Furthermore, our results suggest that processes related to pluripotency and lineage commitment, which are known to be critical for development, interact mainly indirectly, through genes implicated in more general biological processes. Moreover, we provide evidence that supports the relevance of cell spatial organization in the developing liver for proper liver function. Our strategy can be viewed as an abstraction that is useful to interpret high-throughput data and devise further experiments.

Pleiotropic and Epistatic Network-Based Discovery: Integrated Networks for Target Gene Discovery

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

Weighill, Deborah; Jones, Piet; Shah, Manesh

Biological organisms are complex systems that are composed of functional networks of interacting molecules and macro-molecules. Complex phenotypes are the result of orchestrated, hierarchical, heterogeneous collections of expressed genomic variants. However, the effects of these variants are the result of historic selective pressure and current environmental and epigenetic signals, and, as such, their co-occurrence can be seen as genome-wide correlations in a number of different manners. Biomass recalcitrance (i.e., the resistance of plants to degradation or deconstruction, which ultimately enables access to a plant's sugars) is a complex polygenic phenotype of high importance to biofuels initiatives. This study makes usemore » of data derived from the re-sequenced genomes from over 800 different Populus trichocarpa genotypes in combination with metabolomic and pyMBMS data across this population, as well as co-expression and co-methylation networks in order to better understand the molecular interactions involved in recalcitrance, and identify target genes involved in lignin biosynthesis/degradation. A Lines Of Evidence (LOE) scoring system is developed to integrate the information in the different layers and quantify the number of lines of evidence linking genes to target functions. This new scoring system was applied to quantify the lines of evidence linking genes to lignin-related genes and phenotypes across the network layers, and allowed for the generation of new hypotheses surrounding potential new candidate genes involved in lignin biosynthesis in P. trichocarpa, including various AGAMOUS-LIKE genes. Lastly, the resulting Genome Wide Association Study networks, integrated with Single Nucleotide Polymorphism (SNP) correlation, co-methylation, and co-expression networks through the LOE scores are proving to be a powerful approach to determine the pleiotropic and epistatic relationships underlying cellular functions and, as such, the molecular basis for complex phenotypes, such as recalcitrance.« less

Pleiotropic and Epistatic Network-Based Discovery: Integrated Networks for Target Gene Discovery

DOE PAGES

Weighill, Deborah; Jones, Piet; Shah, Manesh; ...

2018-05-11

Biological organisms are complex systems that are composed of functional networks of interacting molecules and macro-molecules. Complex phenotypes are the result of orchestrated, hierarchical, heterogeneous collections of expressed genomic variants. However, the effects of these variants are the result of historic selective pressure and current environmental and epigenetic signals, and, as such, their co-occurrence can be seen as genome-wide correlations in a number of different manners. Biomass recalcitrance (i.e., the resistance of plants to degradation or deconstruction, which ultimately enables access to a plant's sugars) is a complex polygenic phenotype of high importance to biofuels initiatives. This study makes usemore » of data derived from the re-sequenced genomes from over 800 different Populus trichocarpa genotypes in combination with metabolomic and pyMBMS data across this population, as well as co-expression and co-methylation networks in order to better understand the molecular interactions involved in recalcitrance, and identify target genes involved in lignin biosynthesis/degradation. A Lines Of Evidence (LOE) scoring system is developed to integrate the information in the different layers and quantify the number of lines of evidence linking genes to target functions. This new scoring system was applied to quantify the lines of evidence linking genes to lignin-related genes and phenotypes across the network layers, and allowed for the generation of new hypotheses surrounding potential new candidate genes involved in lignin biosynthesis in P. trichocarpa, including various AGAMOUS-LIKE genes. Lastly, the resulting Genome Wide Association Study networks, integrated with Single Nucleotide Polymorphism (SNP) correlation, co-methylation, and co-expression networks through the LOE scores are proving to be a powerful approach to determine the pleiotropic and epistatic relationships underlying cellular functions and, as such, the molecular basis for complex phenotypes, such as recalcitrance.« less

The IKAROS interaction with a complex including chromatin remodeling and transcription elongation activities is required for hematopoiesis.

PubMed

Bottardi, Stefania; Mavoungou, Lionel; Pak, Helen; Daou, Salima; Bourgoin, Vincent; Lakehal, Yahia A; Affar, El Bachir; Milot, Eric

2014-12-01

IKAROS is a critical regulator of hematopoietic cell fate and its dynamic expression pattern is required for proper hematopoiesis. In collaboration with the Nucleosome Remodeling and Deacetylase (NuRD) complex, it promotes gene repression and activation. It remains to be clarified how IKAROS can support transcription activation while being associated with the HDAC-containing complex NuRD. IKAROS also binds to the Positive-Transcription Elongation Factor b (P-TEFb) at gene promoters. Here, we demonstrate that NuRD and P-TEFb are assembled in a complex that can be recruited to specific genes by IKAROS. The expression level of IKAROS influences the recruitment of the NuRD-P-TEFb complex to gene regulatory regions and facilitates transcription elongation by transferring the Protein Phosphatase 1α (PP1α), an IKAROS-binding protein and P-TEFb activator, to CDK9. We show that an IKAROS mutant that is unable to bind PP1α cannot sustain gene expression and impedes normal differentiation of Ik(NULL) hematopoietic progenitors. Finally, the knock-down of the NuRD subunit Mi2 reveals that the occupancy of the NuRD complex at transcribed regions of genes favors the relief of POL II promoter-proximal pausing and thereby, promotes transcription elongation.

The IKAROS Interaction with a Complex Including Chromatin Remodeling and Transcription Elongation Activities Is Required for Hematopoiesis

PubMed Central

Bottardi, Stefania; Mavoungou, Lionel; Pak, Helen; Daou, Salima; Bourgoin, Vincent; Lakehal, Yahia A.; Affar, El Bachir; Milot, Eric

2014-01-01

IKAROS is a critical regulator of hematopoietic cell fate and its dynamic expression pattern is required for proper hematopoiesis. In collaboration with the Nucleosome Remodeling and Deacetylase (NuRD) complex, it promotes gene repression and activation. It remains to be clarified how IKAROS can support transcription activation while being associated with the HDAC-containing complex NuRD. IKAROS also binds to the Positive-Transcription Elongation Factor b (P-TEFb) at gene promoters. Here, we demonstrate that NuRD and P-TEFb are assembled in a complex that can be recruited to specific genes by IKAROS. The expression level of IKAROS influences the recruitment of the NuRD-P-TEFb complex to gene regulatory regions and facilitates transcription elongation by transferring the Protein Phosphatase 1α (PP1α), an IKAROS-binding protein and P-TEFb activator, to CDK9. We show that an IKAROS mutant that is unable to bind PP1α cannot sustain gene expression and impedes normal differentiation of IkNULL hematopoietic progenitors. Finally, the knock-down of the NuRD subunit Mi2 reveals that the occupancy of the NuRD complex at transcribed regions of genes favors the relief of POL II promoter-proximal pausing and thereby, promotes transcription elongation. PMID:25474253

A Simple and Computationally Efficient Sampling Approach to Covariate Adjustment for Multifactor Dimensionality Reduction Analysis of Epistasis

PubMed Central

Gui, Jiang; Andrew, Angeline S.; Andrews, Peter; Nelson, Heather M.; Kelsey, Karl T.; Karagas, Margaret R.; Moore, Jason H.

2010-01-01

Epistasis or gene-gene interaction is a fundamental component of the genetic architecture of complex traits such as disease susceptibility. Multifactor dimensionality reduction (MDR) was developed as a nonparametric and model-free method to detect epistasis when there are no significant marginal genetic effects. However, in many studies of complex disease, other covariates like age of onset and smoking status could have a strong main effect and may potentially interfere with MDR's ability to achieve its goal. In this paper, we present a simple and computationally efficient sampling method to adjust for covariate effects in MDR. We use simulation to show that after adjustment, MDR has sufficient power to detect true gene-gene interactions. We also compare our method with the state-of-art technique in covariate adjustment. The results suggest that our proposed method performs similarly, but is more computationally efficient. We then apply this new method to an analysis of a population-based bladder cancer study in New Hampshire. PMID:20924193

Functional signaling and gene regulatory networks between the oocyte and the surrounding cumulus cells.

PubMed

Biase, Fernando H; Kimble, Katelyn M

2018-05-10

The maturation and successful acquisition of developmental competence by an oocyte, the female gamete, during folliculogenesis is highly dependent on molecular interactions with somatic cells. Most of the cellular interactions identified, thus far, are modulated by growth factors, ions or metabolites. We hypothesized that this interaction is also modulated at the transcriptional level, which leads to the formation of gene regulatory networks between the oocyte and cumulus cells. We tested this hypothesis by analyzing transcriptome data from single oocytes and the surrounding cumulus cells collected from antral follicles employing an analytical framework to determine interdependencies at the transcript level. We overlapped our transcriptome data with putative protein-protein interactions and identified hundreds of ligand-receptor pairs that can transduce paracrine signaling between an oocyte and cumulus cells. We determined that 499 ligand-encoding genes expressed in oocytes and cumulus cells are functionally associated with transcription regulation (FDR < 0.05). Ligand-encoding genes with specific expression in oocytes or cumulus cells were enriched for biological functions that are likely associated with the coordinated formation of transzonal projections from cumulus cells that reach the oocyte's membrane. Thousands of gene pairs exhibit significant linear co-expression (absolute correlation > 0.85, FDR < 1.8 × 10 - 5 ) patterns between oocytes and cumulus cells. Hundreds of co-expressing genes showed clustering patterns associated with biological functions (FDR < 0.5) necessary for a coordinated function between the oocyte and cumulus cells during folliculogenesis (i.e. regulation of transcription, translation, apoptosis, cell differentiation and transport). Our analyses revealed a complex and functional gene regulatory circuit between the oocyte and surrounding cumulus cells. The regulatory profile of each cumulus-oocyte complex is likely associated with the oocytes' developmental potential to derive an embryo.

Current Understanding of Usher Syndrome Type II

PubMed Central

Yang, Jun; Wang, Le; Song, Hongman; Sokolov, Maxim

2012-01-01

Usher syndrome is the most common deafness-blindness caused by genetic mutations. To date, three genes have been identified underlying the most prevalent form of Usher syndrome, the type II form (USH2). The proteins encoded by these genes are demonstrated to form a complex in vivo. This complex is localized mainly at the periciliary membrane complex in photoreceptors and the ankle-link of the stereocilia in hair cells. Many proteins have been found to interact with USH2 proteins in vitro, suggesting that they are potential additional components of this USH2 complex and that the genes encoding these proteins may be the candidate USH2 genes. However, further investigations are critical to establish their existence in the USH2 complex in vivo. Based on the predicted functional domains in USH2 proteins, their cellular localizations in photoreceptors and hair cells, the observed phenotypes in USH2 mutant mice, and the known knowledge about diseases similar to USH2, putative biological functions of the USH2 complex have been proposed. Finally, therapeutic approaches for this group of diseases are now being actively explored. PMID:22201796

Electrostatically assembled dendrimer complex with a high-affinity protein binder for targeted gene delivery.

PubMed

Kim, Jong-Won; Lee, Joong-Jae; Choi, Joon Sig; Kim, Hak-Sung

2018-06-10

Although a variety of non-viral gene delivery systems have been developed, they still suffer from low efficiency and specificity. Herein, we present the assembly of a dendrimer complex comprising a DNA cargo and a targeting moiety as a new format for targeted gene delivery. A PAMAM dendrimer modified with histidine and arginine (HR-dendrimer) was used to enhance the endosomal escape and transfection efficiency. An EGFR-specific repebody, composed of leucine-rich repeat (LRR) modules, was employed as a targeting moiety. A polyanionic peptide was genetically fused to the repebody, followed by incubation with an HR-dendrimer and a DNA cargo to assemble the dendrimer complex through an electrostatic interaction. The resulting dendrimer complex was shown to deliver a DNA cargo with high efficiency in a receptor-specific manner. An analysis using a confocal microscope confirmed the internalization of the dendrimer complex and subsequent dissociation of a DNA cargo from the complex. The present approach can be broadly used in a targeted gene delivery in many areas. Copyright © 2018 Elsevier B.V. All rights reserved.

PRDM16 enhances nuclear receptor-dependent transcription of the brown fat-specific Ucp1 gene through interactions with Mediator subunit MED1.

PubMed

Iida, Satoshi; Chen, Wei; Nakadai, Tomoyoshi; Ohkuma, Yoshiaki; Roeder, Robert G

2015-02-01

PR domain-containing 16 (PRDM16) induces expression of brown fat-specific genes in brown and beige adipocytes, although the underlying transcription-related mechanisms remain largely unknown. Here, in vitro studies show that PRDM16, through its zinc finger domains, directly interacts with the MED1 subunit of the Mediator complex, is recruited to the enhancer of the brown fat-specific uncoupling protein 1 (Ucp1) gene through this interaction, and enhances thyroid hormone receptor (TR)-driven transcription in a biochemically defined system in a Mediator-dependent manner, thus providing a direct link to the general transcription machinery. Complementary cell-based studies show that upon forskolin treatment, PRDM16 induces Ucp1 expression in undifferentiated murine embryonic fibroblasts, that this induction depends on MED1 and TR, and, consistent with a direct effect, that PRDM16 is recruited to the Ucp1 enhancer. Related studies have defined MED1 and PRDM16 interaction domains important for Ucp1 versus Ppargc1a induction by PRDM16. These results reveal novel mechanisms for PRDM16 function through the Mediator complex. © 2015 Iida et al.; Published by Cold Spring Harbor Laboratory Press.

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

The Genome-Wide Interaction Network of Nutrient Stress Genes in Escherichia coli.

PubMed

Côté, Jean-Philippe; French, Shawn; Gehrke, Sebastian S; MacNair, Craig R; Mangat, Chand S; Bharat, Amrita; Brown, Eric D

2016-11-22

Conventional efforts to describe essential genes in bacteria have typically emphasized nutrient-rich growth conditions. Of note, however, are the set of genes that become essential when bacteria are grown under nutrient stress. For example, more than 100 genes become indispensable when the model bacterium Escherichia coli is grown on nutrient-limited media, and many of these nutrient stress genes have also been shown to be important for the growth of various bacterial pathogens in vivo To better understand the genetic network that underpins nutrient stress in E. coli, we performed a genome-scale cross of strains harboring deletions in some 82 nutrient stress genes with the entire E. coli gene deletion collection (Keio) to create 315,400 double deletion mutants. An analysis of the growth of the resulting strains on rich microbiological media revealed an average of 23 synthetic sick or lethal genetic interactions for each nutrient stress gene, suggesting that the network defining nutrient stress is surprisingly complex. A vast majority of these interactions involved genes of unknown function or genes of unrelated pathways. The most profound synthetic lethal interactions were between nutrient acquisition and biosynthesis. Further, the interaction map reveals remarkable metabolic robustness in E. coli through pathway redundancies. In all, the genetic interaction network provides a powerful tool to mine and identify missing links in nutrient synthesis and to further characterize genes of unknown function in E. coli Moreover, understanding of bacterial growth under nutrient stress could aid in the development of novel antibiotic discovery platforms. With the rise of antibiotic drug resistance, there is an urgent need for new antibacterial drugs. Here, we studied a group of genes that are essential for the growth of Escherichia coli under nutrient limitation, culture conditions that arguably better represent nutrient availability during an infection than rich microbiological media. Indeed, many such nutrient stress genes are essential for infection in a variety of pathogens. Thus, the respective proteins represent a pool of potential new targets for antibacterial drugs that have been largely unexplored. We have created all possible double deletion mutants through a genetic cross of nutrient stress genes and the E. coli deletion collection. An analysis of the growth of the resulting clones on rich media revealed a robust, dense, and complex network for nutrient acquisition and biosynthesis. Importantly, our data reveal new genetic connections to guide innovative approaches for the development of new antibacterial compounds targeting bacteria under nutrient stress. Copyright © 2016 Côté et al.

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao

2016-04-01

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks.

PubMed

Li, Min; Li, Dongyan; Tang, Yu; Wu, Fangxiang; Wang, Jianxin

2017-08-31

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster.

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks

PubMed Central

Li, Min; Li, Dongyan; Tang, Yu; Wang, Jianxin

2017-01-01

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster. PMID:28858211

GENIUS: web server to predict local gene networks and key genes for biological functions.

PubMed

Puelma, Tomas; Araus, Viviana; Canales, Javier; Vidal, Elena A; Cabello, Juan M; Soto, Alvaro; Gutiérrez, Rodrigo A

2017-03-01

GENIUS is a user-friendly web server that uses a novel machine learning algorithm to infer functional gene networks focused on specific genes and experimental conditions that are relevant to biological functions of interest. These functions may have different levels of complexity, from specific biological processes to complex traits that involve several interacting processes. GENIUS also enriches the network with new genes related to the biological function of interest, with accuracies comparable to highly discriminative Support Vector Machine methods. GENIUS currently supports eight model organisms and is freely available for public use at http://networks.bio.puc.cl/genius . genius.psbl@gmail.com. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Commentary: Fundamental problems with candidate gene-by-environment interaction studies - reflections on Moore and Thoemmes (2016).

PubMed

Border, Richard; Keller, Matthew C

2017-03-01

Moore and Thoemmes elaborate on one particular source of difficulty in the study of candidate gene-by-environment interactions (cG × E): how different biologically plausible configurations of gene-environment covariation can bias estimates of cG × E when not explicitly modeled. However, even if cG × E investigators were able to account for the sources of bias Moore and Thoemmes elaborate, it is unlikely that conventional approaches would yield reliable results. Published cG × E findings to date have generally employed inadequate analytic procedures, have relied on samples orders of magnitude too small to detect plausible effects, and have relied on a particular candidate gene approach that has been unfruitful and largely jettisoned in mainstream genetic analyses of complex traits. Analytic procedures for the study of gene-environment interplay must evolve to meet the challenges that the genetic architecture of complex traits presents, and investigators must collaborate on grander scales if we hope to begin to understand how specific genes and environments combine to affect behavior. © 2017 Association for Child and Adolescent Mental Health.

Complex multi-enhancer contacts captured by Genome Architecture Mapping (GAM)

PubMed Central

Beagrie, Robert A.; Scialdone, Antonio; Schueler, Markus; Kraemer, Dorothee C.A.; Chotalia, Mita; Xie, Sheila Q.; Barbieri, Mariano; de Santiago, Inês; Lavitas, Liron-Mark; Branco, Miguel R.; Fraser, James; Dostie, Josée; Game, Laurence; Dillon, Niall; Edwards, Paul A.W.; Nicodemi, Mario; Pombo, Ana

2017-01-01

Summary The organization of the genome in the nucleus and the interactions of genes with their regulatory elements are key features of transcriptional control and their disruption can cause disease. We developed a novel genome-wide method, Genome Architecture Mapping (GAM), for measuring chromatin contacts, and other features of three-dimensional chromatin topology, based on sequencing DNA from a large collection of thin nuclear sections. We apply GAM to mouse embryonic stem cells and identify an enrichment for specific interactions between active genes and enhancers across very large genomic distances, using a mathematical model ‘SLICE’ (Statistical Inference of Co-segregation). GAM also reveals an abundance of three-way contacts genome-wide, especially between regions that are highly transcribed or contain super-enhancers, highlighting a previously inaccessible complexity in genome architecture and a major role for gene-expression specific contacts in organizing the genome in mammalian nuclei. PMID:28273065

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

PubMed

Miraldi Utz, Virginia

2017-01-01

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

Identifying Dynamic Protein Complexes Based on Gene Expression Profiles and PPI Networks

PubMed Central

Li, Min; Chen, Weijie; Wang, Jianxin; Pan, Yi

2014-01-01

Identification of protein complexes from protein-protein interaction networks has become a key problem for understanding cellular life in postgenomic era. Many computational methods have been proposed for identifying protein complexes. Up to now, the existing computational methods are mostly applied on static PPI networks. However, proteins and their interactions are dynamic in reality. Identifying dynamic protein complexes is more meaningful and challenging. In this paper, a novel algorithm, named DPC, is proposed to identify dynamic protein complexes by integrating PPI data and gene expression profiles. According to Core-Attachment assumption, these proteins which are always active in the molecular cycle are regarded as core proteins. The protein-complex cores are identified from these always active proteins by detecting dense subgraphs. Final protein complexes are extended from the protein-complex cores by adding attachments based on a topological character of “closeness” and dynamic meaning. The protein complexes produced by our algorithm DPC contain two parts: static core expressed in all the molecular cycle and dynamic attachments short-lived. The proposed algorithm DPC was applied on the data of Saccharomyces cerevisiae and the experimental results show that DPC outperforms CMC, MCL, SPICi, HC-PIN, COACH, and Core-Attachment based on the validation of matching with known complexes and hF-measures. PMID:24963481

A data-mining approach to rank candidate protein-binding partners-The case of biogenesis of lysosome-related organelles complex-1 (BLOC-1).

PubMed

Rodriguez-Fernandez, I A; Dell'Angelica, E C

2009-04-01

The study of protein-protein interactions is a powerful approach to uncovering the molecular function of gene products associated with human disease. Protein-protein interaction data are accumulating at an unprecedented pace owing to interactomics projects, although it has been recognized that a significant fraction of these data likely represents false positives. During our studies of biogenesis of lysosome-related organelles complex-1 (BLOC-1), a protein complex involved in protein trafficking and containing the products of genes mutated in Hermansky-Pudlak syndrome, we faced the problem of having too many candidate binding partners to pursue experimentally. In this work, we have explored ways of efficiently gathering high-quality information about candidate binding partners and presenting the information in a visually friendly manner. We applied the approach to rank 70 candidate binding partners of human BLOC-1 and 102 candidates of its counterpart from Drosophila melanogaster. The top candidate for human BLOC-1 was the small GTPase encoded by the RAB11A gene, which is a paralogue of the Rab38 and Rab32 proteins in mammals and the lightoid gene product in flies. Interestingly, genetic analyses in D. melanogaster uncovered a synthetic sick/lethal interaction between Rab11 and lightoid. The data-mining approach described herein can be customized to study candidate binding partners for other proteins or possibly candidates derived from other types of 'omics' data.

LIM-domain proteins, LIMD1, Ajuba, and WTIP are required for microRNA-mediated gene silencing

PubMed Central

James, Victoria; Zhang, Yining; Foxler, Daniel E.; de Moor, Cornelia H.; Kong, Yi Wen; Webb, Thomas M.; Self, Tim J.; Feng, Yungfeng; Lagos, Dimitrios; Chu, Chia-Ying; Rana, Tariq M.; Morley, Simon J.; Longmore, Gregory D.; Bushell, Martin; Sharp, Tyson V.

2010-01-01

In recent years there have been major advances with respect to the identification of the protein components and mechanisms of microRNA (miRNA) mediated silencing. However, the complete and precise repertoire of components and mechanism(s) of action remain to be fully elucidated. Herein we reveal the identification of a family of three LIM domain-containing proteins, LIMD1, Ajuba and WTIP (Ajuba LIM proteins) as novel mammalian processing body (P-body) components, which highlight a novel mechanism of miRNA-mediated gene silencing. Furthermore, we reveal that LIMD1, Ajuba, and WTIP bind to Ago1/2, RCK, Dcp2, and eIF4E in vivo, that they are required for miRNA-mediated, but not siRNA-mediated gene silencing and that all three proteins bind to the mRNA 5′ m7GTP cap–protein complex. Mechanistically, we propose the Ajuba LIM proteins interact with the m7GTP cap structure via a specific interaction with eIF4E that prevents 4EBP1 and eIF4G interaction. In addition, these LIM-domain proteins facilitate miRNA-mediated gene silencing by acting as an essential molecular link between the translationally inhibited eIF4E-m7GTP-5′cap and Ago1/2 within the miRISC complex attached to the 3′-UTR of mRNA, creating an inhibitory closed-loop complex. PMID:20616046

Genes and environment in neonatal intraventricular hemorrhage.

PubMed

Ment, Laura R; Ådén, Ulrika; Bauer, Charles R; Bada, Henrietta S; Carlo, Waldemar A; Kaiser, Jeffrey R; Lin, Aiping; Cotten, Charles Michael; Murray, Jeffrey; Page, Grier; Hallman, Mikko; Lifton, Richard P; Zhang, Heping

2015-12-01

Emerging data suggest intraventricular hemorrhage (IVH) of the preterm neonate is a complex disorder with contributions from both the environment and the genome. Environmental analyses suggest factors mediating both cerebral blood flow and angiogenesis contribute to IVH, while candidate gene studies report variants in angiogenesis, inflammation, and vascular pathways. Gene-by-environment interactions demonstrate the interaction between the environment and the genome, and a non-replicated genome-wide association study suggests that both environmental and genetic factors contribute to the risk for severe IVH in very low-birth weight preterm neonates. Copyright © 2015 Elsevier Inc. All rights reserved.

3D RNA and functional interactions from evolutionary couplings

PubMed Central

Weinreb, Caleb; Riesselman, Adam; Ingraham, John B.; Gross, Torsten; Sander, Chris; Marks, Debora S.

2016-01-01

Summary Non-coding RNAs are ubiquitous, but the discovery of new RNA gene sequences far outpaces research on their structure and functional interactions. We mine the evolutionary sequence record to derive precise information about function and structure of RNAs and RNA-protein complexes. As in protein structure prediction, we use maximum entropy global probability models of sequence co-variation to infer evolutionarily constrained nucleotide-nucleotide interactions within RNA molecules, and nucleotide-amino acid interactions in RNA-protein complexes. The predicted contacts allow all-atom blinded 3D structure prediction at good accuracy for several known RNA structures and RNA-protein complexes. For unknown structures, we predict contacts in 160 non-coding RNA families. Beyond 3D structure prediction, evolutionary couplings help identify important functional interactions, e.g., at switch points in riboswitches and at a complex nucleation site in HIV. Aided by accelerating sequence accumulation, evolutionary coupling analysis can accelerate the discovery of functional interactions and 3D structures involving RNA. PMID:27087444

Noninvasive imaging of protein-protein interactions in living organisms.

PubMed

Haberkorn, Uwe; Altmann, Annette

2003-06-01

Genomic research is expected to generate new types of complex observational data, changing the types of experiments as well as our understanding of biological processes. The investigation and definition of relationships among proteins is essential for understanding the function of each gene and the mechanisms of biological processes that specific genes are involved in. Recently, a study by Paulmurugan et al. demonstrated a tool for in vivo noninvasive imaging of protein-protein interactions and intracellular networks.

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

PubMed Central

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

2008-01-01

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

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 of a common painkiller piroxicam and copper-piroxicam with chromatin causes structural alterations accompanied by modulation at the epigenomic/genomic level.

PubMed

Goswami, Sathi; Sanyal, Sulagna; Chakraborty, Payal; Das, Chandrima; Sarkar, Munna

2017-08-01

NSAIDs are the most common class of painkillers and anti-inflammatory agents. They also show other functions like chemoprevention and chemosuppression for which they act at the protein but not at the genome level since they are mostly anions at physiological pH, which prohibit their approach to the poly-anionic DNA. Complexing the drugs with bioactive metal obliterate their negative charge and allow them to bind to the DNA, thereby, opening the possibility of genome level interaction. To test this hypothesis, we present the interaction of a traditional NSAID, Piroxicam and its copper complex with core histone and chromatin. Spectroscopy, DLS, and SEM studies were applied to see the effect of the interaction on the structure of histone/chromatin. This was coupled with MTT assay, immunoblot analysis, confocal microscopy, micro array analysis and qRT-PCR. The interaction of Piroxicam and its copper complex with histone/chromatin results in structural alterations. Such structural alterations can have different biological manifestations, but to test our hypothesis, we have focused only on the accompanied modulations at the epigenomic/genomic level. The complex, showed alteration of key epigenetic signatures implicated in transcription in the global context, although Piroxicam caused no significant changes. We have correlated such alterations caused by the complex with the changes in global gene expression and validated the candidate gene expression alterations. Our results provide the proof of concept that DNA binding ability of the copper complexes of a traditional NSAID, opens up the possibility of modulations at the epigenomic/genomic level. Copyright © 2017 Elsevier B.V. All rights reserved.

A Comparative Study on Multifactor Dimensionality Reduction Methods for Detecting Gene-Gene Interactions with the Survival Phenotype

PubMed Central

Lee, Seungyeoun; Kim, Yongkang; Kwon, Min-Seok; Park, Taesung

2015-01-01

Genome-wide association studies (GWAS) have extensively analyzed single SNP effects on a wide variety of common and complex diseases and found many genetic variants associated with diseases. However, there is still a large portion of the genetic variants left unexplained. This missing heritability problem might be due to the analytical strategy that limits analyses to only single SNPs. One of possible approaches to the missing heritability problem is to consider identifying multi-SNP effects or gene-gene interactions. The multifactor dimensionality reduction method has been widely used to detect gene-gene interactions based on the constructive induction by classifying high-dimensional genotype combinations into one-dimensional variable with two attributes of high risk and low risk for the case-control study. Many modifications of MDR have been proposed and also extended to the survival phenotype. In this study, we propose several extensions of MDR for the survival phenotype and compare the proposed extensions with earlier MDR through comprehensive simulation studies. PMID:26339630

Proteomic and Genomic Analyses of the Rvb1 and Rvb2 Interaction Network upon Deletion of R2TP Complex Components*

PubMed Central

Lakshminarasimhan, Mahadevan; Boanca, Gina; Banks, Charles A. S.; Hattem, Gaye L.; Gabriel, Ana E.; Groppe, Brad D.; Smoyer, Christine; Malanowski, Kate E.; Peak, Allison; Florens, Laurence; Washburn, Michael P.

2016-01-01

The highly conserved yeast R2TP complex, consisting of Rvb1, Rvb2, Pih1, and Tah1, participates in diverse cellular processes ranging from assembly of protein complexes to apoptosis. Rvb1 and Rvb2 are closely related proteins belonging to the AAA+ superfamily and are essential for cell survival. Although Rvbs have been shown to be associated with various protein complexes including the Ino80 and Swr1chromatin remodeling complexes, we performed a systematic quantitative proteomic analysis of their associated proteins and identified two additional complexes that associate with Rvb1 and Rvb2: the chaperonin-containing T-complex and the 19S regulatory particle of the proteasome complex. We also analyzed Rvb1 and Rvb2 purified from yeast strains devoid of PIH1 and TAH1. These analyses revealed that both Rvb1 and Rvb2 still associated with Hsp90 and were highly enriched with RNA polymerase II complex components. Our analyses also revealed that both Rvb1 and Rvb2 were recruited to the Ino80 and Swr1 chromatin remodeling complexes even in the absence of Pih1 and Tah1 proteins. Using further biochemical analysis, we showed that Rvb1 and Rvb2 directly interacted with Hsp90 as well as with the RNA polymerase II complex. RNA-Seq analysis of the deletion strains compared with the wild-type strains revealed an up-regulation of ribosome biogenesis and ribonucleoprotein complex biogenesis genes, down-regulation of response to abiotic stimulus genes, and down-regulation of response to temperature stimulus genes. A Gene Ontology analysis of the 80 proteins whose protein associations were altered in the PIH1 or TAH1 deletion strains found ribonucleoprotein complex proteins to be the most enriched category. This suggests an important function of the R2TP complex in ribonucleoprotein complex biogenesis at both the proteomic and genomic levels. Finally, these results demonstrate that deletion network analyses can provide novel insights into cellular systems. PMID:26831523

An integrative approach to inferring biologically meaningful gene modules

PubMed Central

2011-01-01

Background The ability to construct biologically meaningful gene networks and modules is critical for contemporary systems biology. Though recent studies have demonstrated the power of using gene modules to shed light on the functioning of complex biological systems, most modules in these networks have shown little association with meaningful biological function. We have devised a method which directly incorporates gene ontology (GO) annotation in construction of gene modules in order to gain better functional association. Results We have devised a method, Semantic Similarity-Integrated approach for Modularization (SSIM) that integrates various gene-gene pairwise similarity values, including information obtained from gene expression, protein-protein interactions and GO annotations, in the construction of modules using affinity propagation clustering. We demonstrated the performance of the proposed method using data from two complex biological responses: 1. the osmotic shock response in Saccharomyces cerevisiae, and 2. the prion-induced pathogenic mouse model. In comparison with two previously reported algorithms, modules identified by SSIM showed significantly stronger association with biological functions. Conclusions The incorporation of semantic similarity based on GO annotation with gene expression and protein-protein interaction data can greatly enhance the functional relevance of inferred gene modules. In addition, the SSIM approach can also reveal the hierarchical structure of gene modules to gain a broader functional view of the biological system. Hence, the proposed method can facilitate comprehensive and in-depth analysis of high throughput experimental data at the gene network level. PMID:21791051

The mediator complex in genomic and non-genomic signaling in cancer.

PubMed

Weber, Hannah; Garabedian, Michael J

2018-05-01

Mediator is a conserved, multi-subunit macromolecular machine divided structurally into head, middle, and tail modules, along with a transiently associating kinase module. Mediator functions as an integrator of transcriptional regulatory activity by interacting with DNA-bound transcription factors and with RNA polymerase II (Pol II) to both activate and repress gene expression. Mediator has been shown to affect multiple steps in transcription, including chromatin looping between enhancers and promoters, pre-initiation complex formation, transcriptional elongation, and mRNA splicing. Individual Mediator subunits participate in regulation of gene expression by the estrogen and androgen receptors and are altered in a number of endocrine cancers, including breast and prostate cancer. In addition to its role in genomic signaling, MED12 has been implicated in non-genomic signaling by interacting with and activating TGF-beta receptor 2 in the cytoplasm. Recent structural studies have revealed extensive inter-domain interactions and complex architecture of the Mediator-Pol II complex, suggesting that Mediator is capable of reorganizing its conformation and composition to fit cellular needs. We propose that alterations in Mediator subunit expression that occur in various cancers could impact the organization and function of Mediator, resulting in changes in gene expression that promote malignancy. A better understanding of the role of Mediator in cancer could reveal new approaches to the diagnosis and treatment of Mediator-dependent endocrine cancers, especially in settings of therapy resistance. Copyright © 2017 Elsevier Inc. All rights reserved.

iLOCi: a SNP interaction prioritization technique for detecting epistasis in genome-wide association studies

PubMed Central

2012-01-01

Background Genome-wide association studies (GWAS) do not provide a full account of the heritability of genetic diseases since gene-gene interactions, also known as epistasis are not considered in single locus GWAS. To address this problem, a considerable number of methods have been developed for identifying disease-associated gene-gene interactions. However, these methods typically fail to identify interacting markers explaining more of the disease heritability over single locus GWAS, since many of the interactions significant for disease are obscured by uninformative marker interactions e.g., linkage disequilibrium (LD). Results In this study, we present a novel SNP interaction prioritization algorithm, named iLOCi (Interacting Loci). This algorithm accounts for marker dependencies separately in case and control groups. Disease-associated interactions are then prioritized according to a novel ranking score calculated from the difference in marker dependencies for every possible pair between case and control groups. The analysis of a typical GWAS dataset can be completed in less than a day on a standard workstation with parallel processing capability. The proposed framework was validated using simulated data and applied to real GWAS datasets using the Wellcome Trust Case Control Consortium (WTCCC) data. The results from simulated data showed the ability of iLOCi to identify various types of gene-gene interactions, especially for high-order interaction. From the WTCCC data, we found that among the top ranked interacting SNP pairs, several mapped to genes previously known to be associated with disease, and interestingly, other previously unreported genes with biologically related roles. Conclusion iLOCi is a powerful tool for uncovering true disease interacting markers and thus can provide a more complete understanding of the genetic basis underlying complex disease. The program is available for download at http://www4a.biotec.or.th/GI/tools/iloci. PMID:23281813

GA binding protein augments autophagy via transcriptional activation of BECN1-PIK3C3 complex genes

PubMed Central

Zhu, Wan; Swaminathan, Gayathri; Plowey, Edward D

2014-01-01

Macroautophagy is a vesicular catabolic trafficking pathway that is thought to protect cells from diverse stressors and to promote longevity. Recent studies have revealed that transcription factors play important roles in the regulation of autophagy. In this study, we have identified GA binding protein (GABP) as a transcriptional regulator of the combinatorial expression of BECN1-PIK3C3 complex genes involved in autophagosome initiation. We performed bioinformatics analyses that demonstrated highly conserved putative GABP sites in genes that encode BECN1/Beclin 1, several BECN1 interacting proteins, and downstream autophagy proteins including the ATG12–ATG5-ATG16L1 complex. We demonstrate that GABP binds to the promoter regions of BECN1-PIK3C3 complex genes and activates their transcriptional activities. Knockdown of GABP reduced BECN1-PIK3C3 complex transcripts, BECN1-PIK3C3 complex protein levels and autophagy in cultured cells. Conversely, overexpression of GABP increased autophagy. Nutrient starvation increased GABP-dependent transcriptional activity of BECN1-PIK3C3 complex gene promoters and increased the recruitment of GABP to the BECN1 promoter. Our data reveal a novel function of GABP in the regulation of autophagy via transcriptional activation of the BECN1-PIK3C3 complex. PMID:25046113

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

Synthesis: Ecological Impacts of Forest Vegetation Management

Treesearch

Jerry L. Michael; M. Hermy

2002-01-01

Ecological impacts of forest vegetation management are highly complex with many interactions. Interactions are bounded on the one hand by hierarchical levels from genes to species to ecosystems and on the other hand by the tools used and the intensity of management applied to each level of possible interactions. Some impacts are easy to measure, but impacts become more...

Roles of mono-ubiquitinated Smad4 in the formation of Smad transcriptional complexes

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

Wang Bei; Suzuki, Hiroyuki; Kato, Mitsuyasu

2008-11-14

TGF-{beta} activates receptor-regulated Smad (R-Smad) through phosphorylation by type I receptors. Activated R-Smad binds to Smad4 and the complex translocates into the nucleus and stimulates the transcription of target genes through association with co-activators including p300. It is not clear, however, how activated Smad complexes are removed from target genes. In this study, we show that TGF-{beta} enhances the mono-ubiquitination of Smad4. Smad4 mono-ubiquitination was promoted by p300 and suppressed by the c-Ski co-repressor. Smad4 mono-ubiquitination disrupted the interaction with Smad2 in the presence of constitutively active TGF-{beta} type I receptor. Furthermore, mono-ubiquitinated Smad4 was not found in DNA-binding Smadmore » complexes. A Smad4-Ubiquitin fusion protein, which mimics mono-ubiquitinated Smad4, enhanced localization to the cytoplasm. These results suggest that mono-ubiquitination of Smad4 occurs in the transcriptional activator complex and facilitates the turnover of Smad complexes at target genes.« less

Roles of mono-ubiquitinated Smad4 in the formation of Smad transcriptional complexes.

PubMed

Wang, Bei; Suzuki, Hiroyuki; Kato, Mitsuyasu

2008-11-14

TGF-beta activates receptor-regulated Smad (R-Smad) through phosphorylation by type I receptors. Activated R-Smad binds to Smad4 and the complex translocates into the nucleus and stimulates the transcription of target genes through association with co-activators including p300. It is not clear, however, how activated Smad complexes are removed from target genes. In this study, we show that TGF-beta enhances the mono-ubiquitination of Smad4. Smad4 mono-ubiquitination was promoted by p300 and suppressed by the c-Ski co-repressor. Smad4 mono-ubiquitination disrupted the interaction with Smad2 in the presence of constitutively active TGF-beta type I receptor. Furthermore, mono-ubiquitinated Smad4 was not found in DNA-binding Smad complexes. A Smad4-Ubiquitin fusion protein, which mimics mono-ubiquitinated Smad4, enhanced localization to the cytoplasm. These results suggest that mono-ubiquitination of Smad4 occurs in the transcriptional activator complex and facilitates the turnover of Smad complexes at target genes.

A Pathway for the Control of Anoikis Sensitivity by E-Cadherin and Epithelial-to-Mesenchymal Transition▿‡

PubMed Central

Kumar, Sanjeev; Park, Sun Hee; Cieply, Benjamin; Schupp, Jane; Killiam, Elizabeth; Zhang, Fan; Rimm, David L.; Frisch, Steven M.

2011-01-01

Detachment of epithelial cells from matrix or attachment to an inappropriate matrix engages an apoptotic response known as anoikis, which prevents metastasis. Cellular sensitivity to anoikis is compromised during the oncogenic epithelial-to-mesenchymal transition (EMT), through unknown mechanisms. We report here a pathway through which EMT confers anoikis resistance. NRAGE (neurotrophin receptor-interacting melanoma antigen) interacted with a component of the E-cadherin complex, ankyrin-G, maintaining NRAGE in the cytoplasm. Oncogenic EMT downregulated ankyrin-G, enhancing the nuclear localization of NRAGE. The oncogenic transcriptional repressor protein TBX2 interacted with NRAGE, repressing the tumor suppressor gene p14ARF. P14ARF sensitized cells to anoikis; conversely, the TBX2/NRAGE complex protected cells against anoikis by downregulating this gene. This represents a novel pathway for the regulation of anoikis by EMT and E-cadherin. PMID:21746881

Direct Imaging of Gene-Carrier Complexes in Animal Cells

NASA Astrophysics Data System (ADS)

Lin, Alison J.; Slack, Nelle L.; Ahmad, Ayesha; Matsumoto, Brian; Safinya, Cyrus R.

1998-03-01

Cationic lipids are promising gene carriers for DNA transfection. Establishing the correlations between structures of cationic lipid/DNA complexes (CL-DNA) and pathways of transfection will greatly aid us in achieving the optimal CL-DNA transfections. Our first step is to determine the uptake mechanism of DNA by studying the interactions and structures of DNA and cationic lipids. X-ray diffraction shows that the CL-DNA undergoes structural phase transitions from lamellar( J. Raedler, I. Koltover, T. Salditt, C. R. Safinya, Science 275, 810 (1997).) to inverted hexagonal self-assemblies as we change the lipid composition. X-ray diffraction and optical microscopy techniques are used to directly image the progress of the CL-DNA in mouse L-cells and unravel the complex structure in-situ. Fluorescence and confocal optical microscopy techniques allow us to monitor the interactions between the complexes and different organelles in the cell cytoplasm. Current results indicate that once inside cells, complexes containing DOPE follow a different pathway from those containing DOPC. This research is funded by NSF-DMR-9624091, PRF-31352-AC7, and Los Alamos-STB/UC:96-108.

SON and its alternatively spliced isoforms control MLL complex-mediated H3K4me3 and transcription of leukemia-associated genes

PubMed Central

Kim, Jung-Hyun; Baddoo, Melody C.; Park, Eun Young; Stone, Joshua K.; Park, Hyeonsoo; Butler, Thomas W.; Huang, Gang; Yan, Xiaomei; Pauli-Behn, Florencia; Myers, Richard M.; Tan, Ming; Flemington, Erik K.; Lim, Ssang-Taek; Erin Ahn, Eun-Young

2016-01-01

SUMMARY Dysregulation of MLL complex-mediated histone methylation plays a pivotal role in gene expression associated with diseases, but little is known about cellular factors modulating MLL complex activity. Here, we report that SON, previously known as an RNA splicing factor, controls MLL complex-mediated transcriptional initiation. SON binds to DNA near transcription start sites, interacts with menin, and inhibits MLL complex assembly, resulting in decreased H3K4me3 and transcriptional repression. Importantly, alternatively spliced short isoforms of SON are markedly upregulated in acute myeloid leukemia. The short isoforms compete with full-length SON for chromatin occupancy, but lack the menin-binding ability, thereby antagonizing full-length SON function in transcriptional repression while not impairing full-length SON-mediated RNA splicing. Furthermore, overexpression of a short isoform of SON enhances replating potential of hematopoietic progenitors. Our findings define SON as a fine-tuner of the MLL-menin interaction and reveal short SON overexpression as a marker indicating aberrant transcriptional initiation in leukemia. PMID:26990989

The herpes simplex virus 1 UL51 protein interacts with the UL7 protein and plays a role in its recruitment into the virion.

PubMed

Roller, Richard J; Fetters, Rachel

2015-03-01

The alphaherpesvirus UL51 protein is a tegument component that interacts with the viral glycoprotein E and functions at multiple steps in virus assembly and spread in epithelial cells. We show here that pUL51 forms a complex in infected cells with another conserved tegument protein, pUL7. This complex can form in the absence of other viral proteins and is largely responsible for recruitment of pUL7 to cytoplasmic membranes and into the virion tegument. Incomplete colocalization of pUL51 and pUL7 in infected cells, however, suggests that a significant fraction of the population of each protein is not complexed with the other and that they may accomplish independent functions. The ability of herpesviruses to spread from cell to cell in the face of an immune response is critical for disease and shedding following reactivation from latency. Cell-to-cell spread is a conserved ability of herpesviruses, and the identification of conserved viral genes that mediate this process will aid in the design of attenuated vaccines and of novel therapeutics. The conserved UL51 gene of herpes simplex virus 1 plays important roles in cell-to-cell spread and in virus assembly in the cytoplasm, both of which likely depend on specific interactions with other viral and cellular proteins. Here we identify one of those interactions with the product of another conserved herpesvirus gene, UL7, and show that formation of this complex mediates recruitment of UL7 to membranes and to the virion. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Controlled Chaos of Polymorphic Mucins in a Metazoan Parasite (Schistosoma mansoni) Interacting with Its Invertebrate Host (Biomphalaria glabrata)

PubMed Central

Roger, Emmanuel; Grunau, Christoph; Pierce, Raymond J.; Hirai, Hirohisa; Gourbal, Benjamin; Galinier, Richard; Emans, Rémi; Cesari, Italo M.; Cosseau, Céline; Mitta, Guillaume

2008-01-01

Invertebrates were long thought to possess only a simple, effective and hence non-adaptive defence system against microbial and parasitic attacks. However, recent studies have shown that invertebrate immunity also relies on immune receptors that diversify (e.g. in echinoderms, insects and mollusks (Biomphalaria glabrata)). Apparently, individual or population-based polymorphism-generating mechanisms exists that permit the survival of invertebrate species exposed to parasites. Consequently, the generally accepted arms race hypothesis predicts that molecular diversity and polymorphism also exist in parasites of invertebrates. We investigated the diversity and polymorphism of parasite molecules (Schistosoma mansoni Polymorphic Mucins, SmPoMucs) that are key factors for the compatibility of schistosomes interacting with their host, the mollusc Biomphalaria glabrata. We have elucidated the complex cascade of mechanisms acting both at the genomic level and during expression that confer polymorphism to SmPoMuc. We show that SmPoMuc is coded by a multi-gene family whose members frequently recombine. We show that these genes are transcribed in an individual-specific manner, and that for each gene, multiple splice variants exist. Finally, we reveal the impact of this polymorphism on the SmPoMuc glycosylation status. Our data support the view that S. mansoni has evolved a complex hierarchical system that efficiently generates a high degree of polymorphism—a “controlled chaos”—based on a relatively low number of genes. This contrasts with protozoan parasites that generate antigenic variation from large sets of genes such as Trypanosoma cruzi, Trypanosoma brucei and Plasmodium falciparum. Our data support the view that the interaction between parasites and their invertebrate hosts are far more complex than previously thought. While most studies in this matter have focused on invertebrate host diversification, we clearly show that diversifying mechanisms also exist on the parasite side of the interaction. Our findings shed new light on how and why invertebrate immunity develops. PMID:19002242

Analysis of the SWI/SNF chromatin-remodeling complex during early heart development and BAF250a repression cardiac gene transcription during P19 cell differentiation

PubMed Central

Singh, Ajeet Pratap; Archer, Trevor K.

2014-01-01

The regulatory networks of differentiation programs and the molecular mechanisms of lineage-specific gene regulation in mammalian embryos remain only partially defined. We document differential expression and temporal switching of BRG1-associated factor (BAF) subunits, core pluripotency factors and cardiac-specific genes during post-implantation development and subsequent early organogenesis. Using affinity purification of BRG1 ATPase coupled to mass spectrometry, we characterized the cardiac-enriched remodeling complexes present in E8.5 mouse embryos. The relative abundance and combinatorial assembly of the BAF subunits provides functional specificity to Switch/Sucrose NonFermentable (SWI/SNF) complexes resulting in a unique gene expression profile in the developing heart. Remarkably, the specific depletion of the BAF250a subunit demonstrated differential effects on cardiac-specific gene expression and resulted in arrhythmic contracting cardiomyocytes in vitro. Indeed, the BAF250a physically interacts and functionally cooperates with Nucleosome Remodeling and Histone Deacetylase (NURD) complex subunits to repressively regulate chromatin structure of the cardiac genes by switching open and poised chromatin marks associated with active and repressed gene expression. Finally, BAF250a expression modulates BRG1 occupancy at the loci of cardiac genes regulatory regions in P19 cell differentiation. These findings reveal specialized and novel cardiac-enriched SWI/SNF chromatin-remodeling complexes, which are required for heart formation and critical for cardiac gene expression regulation at the early stages of heart development. PMID:24335282

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

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

PubMed

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

2017-07-01

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

Differential C3NET reveals disease networks of direct physical interactions

PubMed Central

2011-01-01

Background Genes might have different gene interactions in different cell conditions, which might be mapped into different networks. Differential analysis of gene networks allows spotting condition-specific interactions that, for instance, form disease networks if the conditions are a disease, such as cancer, and normal. This could potentially allow developing better and subtly targeted drugs to cure cancer. Differential network analysis with direct physical gene interactions needs to be explored in this endeavour. Results C3NET is a recently introduced information theory based gene network inference algorithm that infers direct physical gene interactions from expression data, which was shown to give consistently higher inference performances over various networks than its competitors. In this paper, we present, DC3net, an approach to employ C3NET in inferring disease networks. We apply DC3net on a synthetic and real prostate cancer datasets, which show promising results. With loose cutoffs, we predicted 18583 interactions from tumor and normal samples in total. Although there are no reference interactions databases for the specific conditions of our samples in the literature, we found verifications for 54 of our predicted direct physical interactions from only four of the biological interaction databases. As an example, we predicted that RAD50 with TRF2 have prostate cancer specific interaction that turned out to be having validation from the literature. It is known that RAD50 complex associates with TRF2 in the S phase of cell cycle, which suggests that this predicted interaction may promote telomere maintenance in tumor cells in order to allow tumor cells to divide indefinitely. Our enrichment analysis suggests that the identified tumor specific gene interactions may be potentially important in driving the growth in prostate cancer. Additionally, we found that the highest connected subnetwork of our predicted tumor specific network is enriched for all proliferation genes, which further suggests that the genes in this network may serve in the process of oncogenesis. Conclusions Our approach reveals disease specific interactions. It may help to make experimental follow-up studies more cost and time efficient by prioritizing disease relevant parts of the global gene network. PMID:21777411

The proto-oncoprotein FBI-1 interacts with MBD3 to recruit the Mi-2/NuRD-HDAC complex and BCoR and to silence p21WAF/CDKN1A by DNA methylation

PubMed Central

Choi, Won-Il; Jeon, Bu-Nam; Yoon, Jae-Hyeon; Koh, Dong-In; Kim, Myung-Hwa; Yu, Mi-Young; Lee, Kyung-Mi; Kim, Youngsoo; Kim, Kyunggon; Hur, Sujin Susanne; Lee, Choong-Eun; Kim, Kyung-Sup; Hur, Man-Wook

2013-01-01

The tumour-suppressor gene CDKN1A (encoding p21Waf/Cip1) is thought to be epigenetically repressed in cancer cells. FBI-1 (ZBTB7A) is a proto-oncogenic transcription factor repressing the alternative reading frame and p21WAF/CDKN1A genes of the p53 pathway. FBI-1 interacts directly with MBD3 (methyl-CpG–binding domain protein 3) in the nucleus. We demonstrated that FBI-1 binds both non-methylated and methylated DNA and that MBD3 is recruited to the CDKN1A promoter through its interaction with FBI-1, where it enhances transcriptional repression by FBI-1. FBI-1 also interacts with the co-repressors nuclear receptor corepressor (NCoR), silencing mediator for retinoid and thyroid receptors (SMRT) and BCL-6 corepressor (BCoR) to repress transcription. MBD3 regulates a molecular interaction between the co-repressor and FBI-1. MBD3 decreases the interaction between FBI-1 and NCoR/SMRT but increases the interaction between FBI-1 and BCoR. Because MBD3 is a subunit of the Mi-2 autoantigen (Mi-2)/nucleosome remodelling and histone deacetylase (NuRD)-HDAC complex, FBI-1 recruits the Mi-2/NuRD-HDAC complex via MBD3. BCoR interacts with the Mi-2/NuRD-HDAC complex, DNMTs and HP1. MBD3 and BCoR play a significant role in the recruitment of the Mi-2/NuRD-HDAC complex– and the NuRD complex–associated proteins, DNMTs and HP. By recruiting DNMTs and HP1, Mi-2/NuRD-HDAC complex appears to play key roles in epigenetic repression of CDKN1A by DNA methylation. PMID:23658227

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

PubMed Central

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

2016-01-01

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

Multiscale Embedded Gene Co-expression Network Analysis

PubMed Central

Song, Won-Min; Zhang, Bin

2015-01-01

Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma. PMID:26618778

Multiscale Embedded Gene Co-expression Network Analysis.

PubMed

Song, Won-Min; Zhang, Bin

2015-11-01

Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and gene expression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the gene expression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressed gene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

SAP30L interacts with members of the Sin3A corepressor complex and targets Sin3A to the nucleolus

PubMed Central

Viiri, K. M.; Korkeamäki, H.; Kukkonen, M. K.; Nieminen, L. K.; Lindfors, K.; Peterson, P.; Mäki, M.; Kainulainen, H.; Lohi, O.

2006-01-01

Histone acetylation plays a key role in the regulation of gene expression. The chromatin structure and accessibility of genes to transcription factors is regulated by enzymes that acetylate and deacetylate histones. The Sin3A corepressor complex recruits histone deacetylases and in many cases represses transcription. Here, we report that SAP30L, a close homolog of Sin3-associated protein 30 (SAP30), interacts with several components of the Sin3A corepressor complex. We show that it binds to the PAH3/HID (Paired Amphipathic Helix 3/Histone deacetylase Interacting Domain) region of mouse Sin3A with residues 120–140 in the C-terminal part of the protein. We provide evidence that SAP30L induces transcriptional repression, possibly via recruitment of Sin3A and histone deacetylases. Finally, we characterize a functional nucleolar localization signal in SAP30L and show that SAP30L and SAP30 are able to target Sin3A to the nucleolus. PMID:16820529

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

Control of human adenovirus type 5 gene expression by cellular Daxx/ATRX chromatin-associated complexes

PubMed Central

Schreiner, Sabrina; Bürck, Carolin; Glass, Mandy; Groitl, Peter; Wimmer, Peter; Kinkley, Sarah; Mund, Andreas; Everett, Roger D.; Dobner, Thomas

2013-01-01

Death domain–associated protein (Daxx) cooperates with X-linked α-thalassaemia retardation syndrome protein (ATRX), a putative member of the sucrose non-fermentable 2 family of ATP-dependent chromatin-remodelling proteins, acting as the core ATPase subunit in this complex, whereas Daxx is the targeting factor, leading to histone deacetylase recruitment, H3.3 deposition and transcriptional repression of cellular promoters. Despite recent findings on the fundamental importance of chromatin modification in host-cell gene regulation, it remains unclear whether adenovirus type 5 (Ad5) transcription is regulated by cellular chromatin remodelling to allow efficient virus gene expression. Here, we focus on the repressive role of the Daxx/ATRX complex during Ad5 replication, which depends on intact protein–protein interaction, as negative regulation could be relieved with a Daxx mutant that is unable to interact with ATRX. To ensure efficient viral replication, Ad5 E1B-55K protein inhibits Daxx and targets ATRX for proteasomal degradation in cooperation with early region 4 open reading frame protein 6 and cellular components of a cullin-dependent E3-ubiquitin ligase. Our studies illustrate the importance and diversity of viral factors antagonizing Daxx/ATRX-mediated repression of viral gene expression and shed new light on the modulation of cellular chromatin remodelling factors by Ad5. We show for the first time that cellular Daxx/ATRX chromatin remodelling complexes play essential roles in Ad gene expression and illustrate the importance of early viral proteins to counteract cellular chromatin remodelling. PMID:23396441

Network representations of immune system complexity

PubMed Central

Subramanian, Naeha; Torabi-Parizi, Parizad; Gottschalk, Rachel A.; Germain, Ronald N.; Dutta, Bhaskar

2015-01-01

The mammalian immune system is a dynamic multi-scale system composed of a hierarchically organized set of molecular, cellular and organismal networks that act in concert to promote effective host defense. These networks range from those involving gene regulatory and protein-protein interactions underlying intracellular signaling pathways and single cell responses to increasingly complex networks of in vivo cellular interaction, positioning and migration that determine the overall immune response of an organism. Immunity is thus not the product of simple signaling events but rather non-linear behaviors arising from dynamic, feedback-regulated interactions among many components. One of the major goals of systems immunology is to quantitatively measure these complex multi-scale spatial and temporal interactions, permitting development of computational models that can be used to predict responses to perturbation. Recent technological advances permit collection of comprehensive datasets at multiple molecular and cellular levels while advances in network biology support representation of the relationships of components at each level as physical or functional interaction networks. The latter facilitate effective visualization of patterns and recognition of emergent properties arising from the many interactions of genes, molecules, and cells of the immune system. We illustrate the power of integrating ‘omics’ and network modeling approaches for unbiased reconstruction of signaling and transcriptional networks with a focus on applications involving the innate immune system. We further discuss future possibilities for reconstruction of increasingly complex cellular and organism-level networks and development of sophisticated computational tools for prediction of emergent immune behavior arising from the concerted action of these networks. PMID:25625853

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

PubMed

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

2003-02-01

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

batman Interacts with Polycomb and trithorax Group Genes and Encodes a BTB/POZ Protein That Is Included in a Complex Containing GAGA Factor

PubMed Central

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

2003-01-01

Polycomb and trithorax group genes maintain the appropriate repressed or activated state of homeotic gene expression throughout Drosophila melanogaster development. We have previously identified the batman gene as a Polycomb group candidate since its function is necessary for the repression of Sex combs reduced. However, our present genetic analysis indicates functions of batman in both activation and repression of homeotic genes. The 127-amino-acid Batman protein is almost reduced to a BTB/POZ domain, an evolutionary conserved protein-protein interaction domain found in a large protein family. We show that this domain is involved in the interaction between Batman and the DNA binding GAGA factor encoded by the Trithorax-like gene. The GAGA factor and Batman codistribute on polytene chromosomes, coimmunoprecipitate from nuclear embryonic and larval extracts, and interact in the yeast two-hybrid assay. Batman, together with the GAGA factor, binds to MHS-70, a 70-bp fragment of the bithoraxoid Polycomb response element. This binding, like that of the GAGA factor, requires the presence of d(GA)n sequences. Together, our results suggest that batman belongs to a subset of the Polycomb/trithorax group of genes that includes Trithorax-like, whose products are involved in both activation and repression of homeotic genes. PMID:12556479

The evolution of resistance genes in multi-protein plant resistance systems.

PubMed

Friedman, Aaron R; Baker, Barbara J

2007-12-01

The genomic perspective aids in integrating the analysis of single resistance (R-) genes into a higher order model of complex plant resistance systems. The majority of R-genes encode a class of proteins with nucleotide binding (NB) and leucine-rich repeat (LRR) domains. Several R-proteins act in multi-protein R-complexes that mediate interaction with pathogen effectors to induce resistance signaling. The complexity of these systems seems to have resulted from multiple rounds of plant-pathogen co-evolution. R-gene evolution is thought to be facilitated by the formation of R-gene clusters, which permit sequence exchanges via recombinatorial mispairing and generate high haplotypic diversity. This pattern of evolution may also generate diversity at other loci that contribute to the R-complex. The rate of recombination at R-clusters is not necessarily homogeneous or consistent over evolutionary time: recent evidence suggests that recombination at R-clusters is increased following pathogen infection, suggesting a mechanism that induces temporary genome instability in response to extreme stress. DNA methylation and chromatin modifications may allow this instability to be conditionally regulated and targeted to specific genome regions. Knowledge of natural R-gene evolution may contribute to strategies for artificial evolution of novel resistance specificities.

Cooperation and coexpression: How coexpression networks shift in response to multiple mutualists.

PubMed

Palakurty, Sathvik X; Stinchcombe, John R; Afkhami, Michelle E

2018-04-01

A mechanistic understanding of community ecology requires tackling the nonadditive effects of multispecies interactions, a challenge that necessitates integration of ecological and molecular complexity-namely moving beyond pairwise ecological interaction studies and the "gene at a time" approach to mechanism. Here, we investigate the consequences of multispecies mutualisms for the structure and function of genomewide differential coexpression networks for the first time, using the tractable and ecologically important interaction between legume Medicago truncatula, rhizobia and mycorrhizal fungi. First, we found that genes whose expression is affected nonadditively by multiple mutualists are more highly connected in gene networks than expected by chance and had 94% greater network centrality than genes showing additive effects, suggesting that nonadditive genes may be key players in the widespread transcriptomic responses to multispecies symbioses. Second, multispecies mutualisms substantially changed coexpression network structure of 18 modules of host plant genes and 22 modules of the fungal symbionts' genes, indicating that third-party mutualists can cause significant rewiring of plant and fungal molecular networks. Third, we found that 60% of the coexpressed gene sets that explained variation in plant performance had coexpression structures that were altered by interactive effects of rhizobia and fungi. Finally, an "across-symbiosis" approach identified sets of plant and mycorrhizal genes whose coexpression structure was unique to the multiple mutualist context and suggested coupled responses across the plant-mycorrhizal interaction to rhizobial mutualists. Taken together, these results show multispecies mutualisms have substantial effects on the molecular interactions in host plants, microbes and across symbiotic boundaries. © 2018 John Wiley & Sons Ltd.

Arabidopsis Ensemble Reverse-Engineered Gene Regulatory Network Discloses Interconnected Transcription Factors in Oxidative Stress[W

PubMed Central

Vermeirssen, Vanessa; De Clercq, Inge; Van Parys, Thomas; Van Breusegem, Frank; Van de Peer, Yves

2014-01-01

The abiotic stress response in plants is complex and tightly controlled by gene regulation. We present an abiotic stress gene regulatory network of 200,014 interactions for 11,938 target genes by integrating four complementary reverse-engineering solutions through average rank aggregation on an Arabidopsis thaliana microarray expression compendium. This ensemble performed the most robustly in benchmarking and greatly expands upon the availability of interactions currently reported. Besides recovering 1182 known regulatory interactions, cis-regulatory motifs and coherent functionalities of target genes corresponded with the predicted transcription factors. We provide a valuable resource of 572 abiotic stress modules of coregulated genes with functional and regulatory information, from which we deduced functional relationships for 1966 uncharacterized genes and many regulators. Using gain- and loss-of-function mutants of seven transcription factors grown under control and salt stress conditions, we experimentally validated 141 out of 271 predictions (52% precision) for 102 selected genes and mapped 148 additional transcription factor-gene regulatory interactions (49% recall). We identified an intricate core oxidative stress regulatory network where NAC13, NAC053, ERF6, WRKY6, and NAC032 transcription factors interconnect and function in detoxification. Our work shows that ensemble reverse-engineering can generate robust biological hypotheses of gene regulation in a multicellular eukaryote that can be tested by medium-throughput experimental validation. PMID:25549671

Arabidopsis ensemble reverse-engineered gene regulatory network discloses interconnected transcription factors in oxidative stress.

PubMed

Vermeirssen, Vanessa; De Clercq, Inge; Van Parys, Thomas; Van Breusegem, Frank; Van de Peer, Yves

2014-12-01

The abiotic stress response in plants is complex and tightly controlled by gene regulation. We present an abiotic stress gene regulatory network of 200,014 interactions for 11,938 target genes by integrating four complementary reverse-engineering solutions through average rank aggregation on an Arabidopsis thaliana microarray expression compendium. This ensemble performed the most robustly in benchmarking and greatly expands upon the availability of interactions currently reported. Besides recovering 1182 known regulatory interactions, cis-regulatory motifs and coherent functionalities of target genes corresponded with the predicted transcription factors. We provide a valuable resource of 572 abiotic stress modules of coregulated genes with functional and regulatory information, from which we deduced functional relationships for 1966 uncharacterized genes and many regulators. Using gain- and loss-of-function mutants of seven transcription factors grown under control and salt stress conditions, we experimentally validated 141 out of 271 predictions (52% precision) for 102 selected genes and mapped 148 additional transcription factor-gene regulatory interactions (49% recall). We identified an intricate core oxidative stress regulatory network where NAC13, NAC053, ERF6, WRKY6, and NAC032 transcription factors interconnect and function in detoxification. Our work shows that ensemble reverse-engineering can generate robust biological hypotheses of gene regulation in a multicellular eukaryote that can be tested by medium-throughput experimental validation. © 2014 American Society of Plant Biologists. All rights reserved.

Disentangling the many layers of eukaryotic transcriptional regulation.

PubMed

Lelli, Katherine M; Slattery, Matthew; Mann, Richard S

2012-01-01

Regulation of gene expression in eukaryotes is an extremely complex process. In this review, we break down several critical steps, emphasizing new data and techniques that have expanded current gene regulatory models. We begin at the level of DNA sequence where cis-regulatory modules (CRMs) provide important regulatory information in the form of transcription factor (TF) binding sites. In this respect, CRMs function as instructional platforms for the assembly of gene regulatory complexes. We discuss multiple mechanisms controlling complex assembly, including cooperative DNA binding, combinatorial codes, and CRM architecture. The second section of this review places CRM assembly in the context of nucleosomes and condensed chromatin. We discuss how DNA accessibility and histone modifications contribute to TF function. Lastly, new advances in chromosomal mapping techniques have provided increased understanding of intra- and interchromosomal interactions. We discuss how these topological maps influence gene regulatory models.

Animal-specific C-terminal domain links myeloblastosis oncoprotein (Myb) to an ancient repressor complex

PubMed Central

Andrejka, Laura; Wen, Hong; Ashton, Jonathan; Grant, Megan; Iori, Kevin; Wang, Amy; Manak, J. Robert; Lipsick, Joseph S.

2011-01-01

Members of the Myb oncoprotein and E2F-Rb tumor suppressor protein families are present within the same highly conserved multiprotein transcriptional repressor complex, named either as Myb and synthetic multivuval class B (Myb-MuvB) or as Drosophila Rb E2F and Myb-interacting proteins (dREAM). We now report that the animal-specific C terminus of Drosophila Myb but not the more highly conserved N-terminal DNA-binding domain is necessary and sufficient for (i) adult viability, (ii) proper localization to chromosomes in vivo, (iii) regulation of gene expression in vivo, and (iv) interaction with the highly conserved core of the MuvB/dREAM transcriptional repressor complex. In addition, we have identified a conserved peptide motif that is required for this interaction. Our results imply that an ancient function of Myb in regulating G2/M genes in both plants and animals appears to have been transferred from the DNA-binding domain to the animal-specific C-terminal domain. Increased expression of B-MYB/MYBL2, the human ortholog of Drosophila Myb, correlates with poor prognosis in human patients with breast cancer. Therefore, our results imply that the specific interaction of the C terminus of Myb with the MuvB/dREAM core complex may provide an attractive target for the development of cancer therapeutics. PMID:21969598

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.

Learning directed acyclic graphs from large-scale genomics data.

PubMed

Nikolay, Fabio; Pesavento, Marius; Kritikos, George; Typas, Nassos

2017-09-20

In this paper, we consider the problem of learning the genetic interaction map, i.e., the topology of a directed acyclic graph (DAG) of genetic interactions from noisy double-knockout (DK) data. Based on a set of well-established biological interaction models, we detect and classify the interactions between genes. We propose a novel linear integer optimization program called the Genetic-Interactions-Detector (GENIE) to identify the complex biological dependencies among genes and to compute the DAG topology that matches the DK measurements best. Furthermore, we extend the GENIE program by incorporating genetic interaction profile (GI-profile) data to further enhance the detection performance. In addition, we propose a sequential scalability technique for large sets of genes under study, in order to provide statistically significant results for real measurement data. Finally, we show via numeric simulations that the GENIE program and the GI-profile data extended GENIE (GI-GENIE) program clearly outperform the conventional techniques and present real data results for our proposed sequential scalability technique.

[Fanconi anemia: genes and function(s) revisited].

PubMed

Papadopoulo, Dora; Moustacchi, Ethel

2005-01-01

Fanconi anemia (FA), a rare inherited disorder, exhibits a complex phenotype including progressive bone marrow failure, congenital malformations and increased risk of cancers, mainly acute myeloid leukaemia. At the cellular level, FA is characterized by hypersensitivity to DNA cross-linking agents and by high frequencies of induced chromosomal aberrations, a property used for diagnosis. FA results from mutations in one of the eleven FANC (FANCA to FANCJ) genes. Nine of them have been identified. In addition, FANCD1 gene has been shown to be identical to BRCA2, one of the two breast cancer susceptibility genes. Seven of the FANC proteins form a complex, which exists in four different forms depending of its subcellular localisation. Four FANC proteins (D1(BRCA2), D2, I and J) are not associated to the complex. The presence of the nuclear form of the FA core complex is necessary for the mono-ubiquitinylation of FANCD2 protein, a modification required for its re-localization to nuclear foci, likely to be sites of DNA repair. A clue towards understanding the molecular function of the FANC genes comes from the recently identified connection of FANC to the BRCA1, ATM, NBS1 and ATR genes. Two of the FANC proteins (A and D2) directly interact with BRCA1, which in turn interacts with the MRE11/RAD50/NBS1 complex, which is one of the key components in the mechanisms involved in the cellular response to DNA double strand breaks (DSB). Moreover, ATM, a protein kinase that plays a central role in the network of DSB signalling, phosphorylates in vitro and in vivo FANCD2 in response to ionising radiations. Moreover, the NBS1 protein and the monoubiquitinated form of FANCD2 seem to act together in response to DNA crosslinking agents. Taken together with the previously reported impaired DSB and DNA interstrand crosslinks repair in FA cells, the connection of FANC genes to the ATM, ATR, NBS1 and BRCA1 links the FANC genes function to the finely orchestrated network involved in the sensing, signalling and repair of DNA replication-blocking lesions.

A Study on the Interaction of Rhodamine B with Methylthioadenosine Phosphorylase Protein Sourced from an Antarctic Soil Metagenomic Library

PubMed Central

Bujacz, Anna; Wierzbicka-Woś, Anna; Kur, Józef

2013-01-01

The presented study examines the phenomenon of the fluorescence under UV light excitation (312 nm) of E. coli cells expressing a novel metagenomic-derived putative methylthioadenosine phosphorylase gene, called rsfp, grown on LB agar supplemented with a fluorescent dye rhodamine B. For this purpose, an rsfp gene was cloned and expressed in an LMG194 E. coli strain using an arabinose promoter. The resulting RSFP protein was purified and its UV-VIS absorbance spectrum and emission spectrum were assayed. Simultaneously, the same spectroscopic studies were carried out for rhodamine B in the absence or presence of RSFP protein or native E. coli proteins, respectively. The results of the spectroscopic studies suggested that the fluorescence of E. coli cells expressing rsfp gene under UV illumination is due to the interaction of rhodamine B molecules with the RSFP protein. Finally, this interaction was proved by a crystallographic study and then by site-directed mutagenesis of rsfp gene sequence. The crystal structures of RSFP apo form (1.98 Å) and complex RSFP/RB (1.90 Å) show a trimer of RSFP molecules located on the crystallographic six fold screw axis. The RSFP complex with rhodamine B revealed the binding site for RB, in the pocket located on the interface between symmetry related monomers. PMID:23383268

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

PubMed

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

2017-04-11

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

Intrinsic limits to gene regulation by global crosstalk

NASA Astrophysics Data System (ADS)

Friedlander, Tamar; Prizak, Roshan; Guet, Calin; Barton, Nicholas H.; Tkacik, Gasper

Gene activity is mediated by the specificity of binding interactions between special proteins, called transcription factors, and short regulatory sequences on the DNA, where different protein species preferentially bind different DNA targets. Limited interaction specificity may lead to crosstalk: a regulatory state in which a gene is either incorrectly activated due to spurious interactions or remains erroneously inactive. Since each protein can potentially interact with numerous DNA targets, crosstalk is inherently a global problem, yet has previously not been studied as such. We construct a theoretical framework to analyze the effects of global crosstalk on gene regulation, using statistical mechanics. We find that crosstalk in regulatory interactions puts fundamental limits on the reliability of gene regulation that are not easily mitigated by tuning proteins concentrations or by complex regulatory schemes proposed in the literature. Our results suggest that crosstalk imposes a previously unexplored global constraint on the functioning and evolution of regulatory networks, which is qualitatively distinct from the known constraints that act at the level of individual gene regulatory elements. The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007-2013) under REA Grant agreement Nr. 291734 (T.F.) and ERC Grant Nr. 250152 (N.B.).

PAMPs, PRRs, effectors and R-genes associated with citrus–pathogen interactions

PubMed Central

Dalio, Ronaldo J. D.; Magalhães, Diogo M.; Rodrigues, Carolina M.; Arena, Gabriella D.; Oliveira, Tiago S.; Souza-Neto, Reinaldo R.; Picchi, Simone C.; Martins, Paula M. M.; Santos, Paulo J. C.; Maximo, Heros J.; Pacheco, Inaiara S.; De Souza, Alessandra A.

2017-01-01

Abstract Background Recent application of molecular-based technologies has considerably advanced our understanding of complex processes in plant–pathogen interactions and their key components such as PAMPs, PRRs, effectors and R-genes. To develop novel control strategies for disease prevention in citrus, it is essential to expand and consolidate our knowledge of the molecular interaction of citrus plants with their pathogens. Scope This review provides an overview of our understanding of citrus plant immunity, focusing on the molecular mechanisms involved in the interactions with viruses, bacteria, fungi, oomycetes and vectors related to the following diseases: tristeza, psorosis, citrus variegated chlorosis, citrus canker, huanglongbing, brown spot, post-bloom, anthracnose, gummosis and citrus root rot. PMID:28065920

Reconstruction of a Functional Human Gene Network, with an Application for Prioritizing Positional Candidate Genes

PubMed Central

Franke, Lude; Bakel, Harm van; Fokkens, Like; de Jong, Edwin D.; Egmont-Petersen, Michael; Wijmenga, Cisca

2006-01-01

Most common genetic disorders have a complex inheritance and may result from variants in many genes, each contributing only weak effects to the disease. Pinpointing these disease genes within the myriad of susceptibility loci identified in linkage studies is difficult because these loci may contain hundreds of genes. However, in any disorder, most of the disease genes will be involved in only a few different molecular pathways. If we know something about the relationships between the genes, we can assess whether some genes (which may reside in different loci) functionally interact with each other, indicating a joint basis for the disease etiology. There are various repositories of information on pathway relationships. To consolidate this information, we developed a functional human gene network that integrates information on genes and the functional relationships between genes, based on data from the Kyoto Encyclopedia of Genes and Genomes, the Biomolecular Interaction Network Database, Reactome, the Human Protein Reference Database, the Gene Ontology database, predicted protein-protein interactions, human yeast two-hybrid interactions, and microarray coexpressions. We applied this network to interrelate positional candidate genes from different disease loci and then tested 96 heritable disorders for which the Online Mendelian Inheritance in Man database reported at least three disease genes. Artificial susceptibility loci, each containing 100 genes, were constructed around each disease gene, and we used the network to rank these genes on the basis of their functional interactions. By following up the top five genes per artificial locus, we were able to detect at least one known disease gene in 54% of the loci studied, representing a 2.8-fold increase over random selection. This suggests that our method can significantly reduce the cost and effort of pinpointing true disease genes in analyses of disorders for which numerous loci have been reported but for which most of the genes are unknown. PMID:16685651

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.

The Robustness of a Signaling Complex to Domain Rearrangements Facilitates Network Evolution

PubMed Central

Sato, Paloma M.; Yoganathan, Kogulan; Jung, Jae H.; Peisajovich, Sergio G.

2014-01-01

The rearrangement of protein domains is known to have key roles in the evolution of signaling networks and, consequently, is a major tool used to synthetically rewire networks. However, natural mutational events leading to the creation of proteins with novel domain combinations, such as in frame fusions followed by domain loss, retrotranspositions, or translocations, to name a few, often simultaneously replace pre-existing genes. Thus, while proteins with new domain combinations may establish novel network connections, it is not clear how the concomitant deletions are tolerated. We investigated the mechanisms that enable signaling networks to tolerate domain rearrangement-mediated gene replacements. Using as a model system the yeast mitogen activated protein kinase (MAPK)-mediated mating pathway, we analyzed 92 domain-rearrangement events affecting 11 genes. Our results indicate that, while domain rearrangement events that result in the loss of catalytic activities within the signaling complex are not tolerated, domain rearrangements can drastically alter protein interactions without impairing function. This suggests that signaling complexes can maintain function even when some components are recruited to alternative sites within the complex. Furthermore, we also found that the ability of the complex to tolerate changes in interaction partners does not depend on long disordered linkers that often connect domains. Taken together, our results suggest that some signaling complexes are dynamic ensembles with loose spatial constraints that could be easily re-shaped by evolution and, therefore, are ideal targets for cellular engineering. PMID:25490747

The role of TREX in gene expression and disease

PubMed Central

Heath, Catherine G.; Viphakone, Nicolas; Wilson, Stuart A.

2016-01-01

TRanscription and EXport (TREX) is a conserved multisubunit complex essential for embryogenesis, organogenesis and cellular differentiation throughout life. By linking transcription, mRNA processing and export together, it exerts a physiologically vital role in the gene expression pathway. In addition, this complex prevents DNA damage and regulates the cell cycle by ensuring optimal gene expression. As the extent of TREX activity in viral infections, amyotrophic lateral sclerosis and cancer emerges, the need for a greater understanding of TREX function becomes evident. A complete elucidation of the composition, function and interactions of the complex will provide the framework for understanding the molecular basis for a variety of diseases. This review details the known composition of TREX, how it is regulated and its cellular functions with an emphasis on mammalian systems. PMID:27679854

The N-CoR complex enables chromatin remodeler SNF2H to enhance repression by thyroid hormone receptor

PubMed Central

Alenghat, Theresa; Yu, Jiujiu; Lazar, Mitchell A

2006-01-01

Unliganded thyroid hormone receptor (TR) actively represses transcription via the nuclear receptor corepressor (N-CoR)/histone deacetylase 3 (HDAC3) complex. Although transcriptional activation by liganded receptors involves chromatin remodeling, the role of ATP-dependent remodeling in receptor-mediated repression is unknown. Here we report that SNF2H, the mammalian ISWI chromatin remodeling ATPase, is critical for repression of a genomically integrated, TR-regulated reporter gene. N-CoR and HDAC3 are both required for recruitment of SNF2H to the repressed gene. SNF2H does not interact directly with the N-CoR/HDAC3 complex, but binds to unacetylated histone H4 tails, suggesting that deacetylase activity of the corepressor complex is critical to SNF2H function. Indeed, HDAC3 as well as SNF2H are required for nucleosomal organization on the TR target gene. Consistent with these findings, reduction of SNF2H induces expression of an endogenous TR-regulated gene, dio1, in liver cells. Thus, although not apparent from studies of transiently transfected reporter genes, gene repression by TR involves the targeting of chromatin remodeling factors to repressed genes by the HDAC activity of nuclear receptor corepressors. PMID:16917504

RPA Interacts with HIRA and Regulates H3.3 Deposition at Gene Regulatory Elements in Mammalian Cells.

PubMed

Zhang, Honglian; Gan, Haiyun; Wang, Zhiquan; Lee, Jeong-Heon; Zhou, Hui; Ordog, Tamas; Wold, Marc S; Ljungman, Mats; Zhang, Zhiguo

2017-01-19

The histone chaperone HIRA is involved in depositing histone variant H3.3 into distinct genic regions, including promoters, enhancers, and gene bodies. However, how HIRA deposits H3.3 to these regions remains elusive. Through a short hairpin RNA (shRNA) screening, we identified single-stranded DNA binding protein replication protein A (RPA) as a regulator of the deposition of newly synthesized H3.3 into chromatin. We show that RPA physically interacts with HIRA to form RPA-HIRA-H3.3 complexes, and it co-localizes with HIRA and H3.3 at gene promoters and enhancers. Depletion of RPA1, the largest subunit of the RPA complex, dramatically reduces both HIRA association with chromatin and the deposition of newly synthesized H3.3 at promoters and enhancers and leads to altered transcription at gene promoters. These results support a model whereby RPA, best known for its role in DNA replication and repair, recruits HIRA to promoters and enhancers and regulates deposition of newly synthesized H3.3 to these regulatory elements for gene regulation. Copyright © 2017 Elsevier Inc. All rights reserved.

Induction of apoptosis in cells expressing exogenous Hippi, a molecular partner of huntingtin-interacting protein Hip1.

PubMed

Majumder, Pritha; Chattopadhyay, Biswanath; Mazumder, Arindam; Das, Pradeep; Bhattacharyya, Nitai P

2006-05-01

To decipher the pathway of apoptosis induction downstream to caspase-8 activation by exogenous expression of Hippi, an interactor of huntingtin-interacting protein Hip1, we studied apoptosis in HeLa and Neuro2A cells expressing GFP-tagged Hippi. Nuclear fragmentation, caspase-1, caspase-8, caspase-9/caspase-6 and caspase-3 activation were increased significantly in Hippi expressing cells. Cleavage of Bid, release of cytochrome c and apoptosis inducing factor (AIF) from mitochondria were also increased in GFP-Hippi expressing cells. It was observed that caspase-1 and caspase-8 activation was earlier than caspase-3 activation and nuclear fragmentation. Expression of caspase-1, caspase-3 and caspase-7 was increased while anti-apoptotic gene Bcl-2 and mitochondrial genes ND1 and ND4 were reduced in Hippi expressing cells. Besides, the expression SDHA and SDHB, nuclear genes, subunits of mitochondrial complex II were decreased in GFP-Hippi expressing cells. Taken together, we concluded that Hippi expression induced apoptosis by releasing AIF and cytochrome c from mitochondria, activation of caspase-1 and caspase-3, and altering the expression of apoptotic genes and genes involved in mitochondrial complex I and II.

The knottin-like Blufensin family regulates genes involved in nuclear import and the secretory pathway in barley-powdery mildew interactions

USDA-ARS?s Scientific Manuscript database

Plants have evolved complex regulatory mechanisms to control a multi-layered defense response to microbial attack. Both temporal and spatial gene expression are tightly regulated in response to pathogen ingress, modulating both positive and negative control of defense. BLUFENSINs, small knottin-like...

fabp4 is central to eight obesity associated genes: a functional gene network-based polymorphic study.

PubMed

Bag, Susmita; Ramaiah, Sudha; Anbarasu, Anand

2015-01-07

Network study on genes and proteins offers functional basics of the complexity of gene and protein, and its interacting partners. The gene fatty acid-binding protein 4 (fabp4) is found to be highly expressed in adipose tissue, and is one of the most abundant proteins in mature adipocytes. Our investigations on functional modules of fabp4 provide useful information on the functional genes interacting with fabp4, their biochemical properties and their regulatory functions. The present study shows that there are eight set of candidate genes: acp1, ext2, insr, lipe, ostf1, sncg, usp15, and vim that are strongly and functionally linked up with fabp4. Gene ontological analysis of network modules of fabp4 provides an explicit idea on the functional aspect of fabp4 and its interacting nodes. The hierarchal mapping on gene ontology indicates gene specific processes and functions as well as their compartmentalization in tissues. The fabp4 along with its interacting genes are involved in lipid metabolic activity and are integrated in multi-cellular processes of tissues and organs. They also have important protein/enzyme binding activity. Our study elucidated disease-associated nsSNP prediction for fabp4 and it is interesting to note that there are four rsID׳s (rs1051231, rs3204631, rs140925685 and rs141169989) with disease allelic variation (T104P, T126P, G27D and G90V respectively). On the whole, our gene network analysis presents a clear insight about the interactions and functions associated with fabp4 gene network. Copyright © 2014 Elsevier Ltd. All rights reserved.

A bioinformatics analysis of Lamin-A regulatory network: a perspective on epigenetic involvement in Hutchinson-Gilford progeria syndrome.

PubMed

Arancio, Walter

2012-04-01

Hutchinson-Gilford progeria syndrome (HGPS) is a rare human genetic disease that leads to premature aging. HGPS is caused by mutation in the Lamin-A (LMNA) gene that leads, in affected young individuals, to the accumulation of the progerin protein, usually present only in aging differentiated cells. Bioinformatics analyses of the network of interactions of the LMNA gene and transcripts are presented. The LMNA gene network has been analyzed using the BioGRID database (http://thebiogrid.org/) and related analysis tools such as Osprey (http://biodata.mshri.on.ca/osprey/servlet/Index) and GeneMANIA ( http://genemania.org/). The network of interaction of LMNA transcripts has been further analyzed following the competing endogenous (ceRNA) hypotheses (RNA cross-talk via microRNAs [miRNAs]) and using the miRWalk database and tools (www.ma.uni-heidelberg.de/apps/zmf/mirwalk/). These analyses suggest particular relevance of epigenetic modifiers (via acetylase complexes and specifically HTATIP histone acetylase) and adenosine triphosphate (ATP)-dependent chromatin remodelers (via pBAF, BAF, and SWI/SNF complexes).

Biomechanical cell regulatory networks as complex adaptive systems in relation to cancer.

PubMed

Feller, Liviu; Khammissa, Razia Abdool Gafaar; Lemmer, Johan

2017-01-01

Physiological structure and function of cells are maintained by ongoing complex dynamic adaptive processes in the intracellular molecular pathways controlling the overall profile of gene expression, and by genes in cellular gene regulatory circuits. Cytogenetic mutations and non-genetic factors such as chronic inflammation or repetitive trauma, intrinsic mechanical stresses within extracellular matrix may induce redirection of gene regulatory circuits with abnormal reactivation of embryonic developmental programmes which can now drive cell transformation and cancer initiation, and later cancer progression and metastasis. Some of the non-genetic factors that may also favour cancerization are dysregulation in epithelial-mesenchymal interactions, in cell-to-cell communication, in extracellular matrix turnover, in extracellular matrix-to-cell interactions and in mechanotransduction pathways. Persistent increase in extracellular matrix stiffness, for whatever reason, has been shown to play an important role in cell transformation, and later in cancer cell invasion. In this article we review certain cell regulatory networks driving carcinogenesis, focussing on the role of mechanical stresses modulating structure and function of cells and their extracellular matrices.

Gene-gene interactions among genetic variants from obesity candidate genes for nonobese and obese populations in type 2 diabetes.

PubMed

Lin, Eugene; Pei, Dee; Huang, Yi-Jen; Hsieh, Chang-Hsun; Wu, Lawrence Shih-Hsin

2009-08-01

Recent studies indicate that obesity may play a key role in modulating genetic predispositions to type 2 diabetes (T2D). This study examines the main effects of both single-locus and multilocus interactions among genetic variants in Taiwanese obese and nonobese individuals to test the hypothesis that obesity-related genes may contribute to the etiology of T2D independently and/or through such complex interactions. We genotyped 11 single nucleotide polymorphisms for 10 obesity candidate genes including adrenergic beta-2-receptor surface, adrenergic beta-3-receptor surface, angiotensinogen, fat mass and obesity associated gene, guanine nucleotide binding protein beta polypeptide 3 (GNB3), interleukin 6 receptor, proprotein convertase subtilisin/kexin type 1 (PCSK1), uncoupling protein 1, uncoupling protein 2, and uncoupling protein 3. There were 389 patients diagnosed with T2D and 186 age- and sex-matched controls. Single-locus analyses showed significant main effects of the GNB3 and PCSK1 genes on the risk of T2D among the nonobese group (p = 0.002 and 0.047, respectively). Further, interactions involving GNB3 and PCSK1 were suggested among the nonobese population using the generalized multifactor dimensionality reduction method (p = 0.001). In addition, interactions among angiotensinogen, fat mass and obesity associated gene, GNB3, and uncoupling protein 3 genes were found in a significant four-locus generalized multifactor dimensionality reduction model among the obese population (p = 0.001). The results suggest that the single nucleotide polymorphisms from the obesity candidate genes may contribute to the risk of T2D independently and/or in an interactive manner according to the presence or absence of obesity.

Auxin-dependent compositional change in Mediator in ARF7- and ARF19-mediated transcription.

PubMed

Ito, Jun; Fukaki, Hidehiro; Onoda, Makoto; Li, Lin; Li, Chuanyou; Tasaka, Masao; Furutani, Masahiko

2016-06-07

Mediator is a multiprotein complex that integrates the signals from transcription factors binding to the promoter and transmits them to achieve gene transcription. The subunits of Mediator complex reside in four modules: the head, middle, tail, and dissociable CDK8 kinase module (CKM). The head, middle, and tail modules form the core Mediator complex, and the association of CKM can modify the function of Mediator in transcription. Here, we show genetic and biochemical evidence that CKM-associated Mediator transmits auxin-dependent transcriptional repression in lateral root (LR) formation. The AUXIN/INDOLE 3-ACETIC ACID 14 (Aux/IAA14) transcriptional repressor inhibits the transcriptional activity of its binding partners AUXIN RESPONSE FACTOR 7 (ARF7) and ARF19 by making a complex with the CKM-associated Mediator. In addition, TOPLESS (TPL), a transcriptional corepressor, forms a bridge between IAA14 and the CKM component MED13 through the physical interaction. ChIP assays show that auxin induces the dissociation of MED13 but not the tail module component MED25 from the ARF7 binding region upstream of its target gene. These findings indicate that auxin-induced degradation of IAA14 changes the module composition of Mediator interacting with ARF7 and ARF19 in the upstream region of their target genes involved in LR formation. We suggest that this regulation leads to a quick switch of signal transmission from ARFs to target gene expression in response to auxin.

A CRISPR Cas9-based gene drive platform for genetic interaction analysis in Candida albicans

PubMed Central

Shapiro, Rebecca S.; Chavez, Alejandro; Porter, Caroline B. M.; Hamblin, Meagan; Kaas, Christian S.; DiCarlo, James E.; Zeng, Guisheng; Xu, Xiaoli; Revtovich, Alexey V.; Kirienko, Natalia V.; Wang, Yue; Church, George M.; Collins, James J.

2018-01-01

Candida albicans is the leading cause of fungal infections; yet, complex genetic interaction analysis remains cumbersome in this diploid pathogen. Here, we developed a CRISPR-Cas9-based ‘gene drive array’ (GDA) platform to facilitate efficient genetic analysis in C. albicans. In our system, a modified DNA donor molecule acts as a selfish genetic element, replaces the targeted site, and propagates to replace additional wild-type loci. Using mating-competent C. albicans haploids, each carrying a different gene drive disabling a gene of interest, we are able to create diploid strains that are homozygous double-deletion mutants. We generate double-gene deletion libraries to demonstrate this technology, targeting antifungal efflux and biofilm adhesion factors. We screen these libraries to identify virulence regulators and determine how genetic networks shift under diverse conditions. This platform transforms our ability to perform genetic interaction analysis in C. albicans and is readily extended to other fungal pathogens. PMID:29062088

EDdb: a web resource for eating disorder and its application to identify an extended adipocytokine signaling pathway related to eating disorder.

PubMed

Zhao, Min; Li, XiaoMo; Qu, Hong

2013-12-01

Eating disorder is a group of physiological and psychological disorders affecting approximately 1% of the female population worldwide. Although the genetic epidemiology of eating disorder is becoming increasingly clear with accumulated studies, the underlying molecular mechanisms are still unclear. Recently, integration of various high-throughput data expanded the range of candidate genes and started to generate hypotheses for understanding potential pathogenesis in complex diseases. This article presents EDdb (Eating Disorder database), the first evidence-based gene resource for eating disorder. Fifty-nine experimentally validated genes from the literature in relation to eating disorder were collected as the core dataset. Another four datasets with 2824 candidate genes across 601 genome regions were expanded based on the core dataset using different criteria (e.g., protein-protein interactions, shared cytobands, and related complex diseases). Based on human protein-protein interaction data, we reconstructed a potential molecular sub-network related to eating disorder. Furthermore, with an integrative pathway enrichment analysis of genes in EDdb, we identified an extended adipocytokine signaling pathway in eating disorder. Three genes in EDdb (ADIPO (adiponectin), TNF (tumor necrosis factor) and NR3C1 (nuclear receptor subfamily 3, group C, member 1)) link the KEGG (Kyoto Encyclopedia of Genes and Genomes) "adipocytokine signaling pathway" with the BioCarta "visceral fat deposits and the metabolic syndrome" pathway to form a joint pathway. In total, the joint pathway contains 43 genes, among which 39 genes are related to eating disorder. As the first comprehensive gene resource for eating disorder, EDdb ( http://eddb.cbi.pku.edu.cn ) enables the exploration of gene-disease relationships and cross-talk mechanisms between related disorders. Through pathway statistical studies, we revealed that abnormal body weight caused by eating disorder and obesity may both be related to dysregulation of the novel joint pathway of adipocytokine signaling. In addition, this joint pathway may be the common pathway for body weight regulation in complex human diseases related to unhealthy lifestyle.

Specific interactions between DNA and regulatory protein controlled by ligand-binding: Ab initio molecular simulation

NASA Astrophysics Data System (ADS)

Matsushita, Y.; Murakawa, T.; Shimamura, K.; Oishi, M.; Ohyama, T.; Kurita, N.

2015-02-01

The catabolite activator protein (CAP) is one of the regulatory proteins controlling the transcription mechanism of gene. Biochemical experiments elucidated that the complex of CAP with cyclic AMP (cAMP) is indispensable for controlling the mechanism, while previous molecular simulations for the monomer of CAP+cAMP complex revealed the specific interactions between CAP and cAMP. However, the effect of cAMP-binding to CAP on the specific interactions between CAP and DNA is not elucidated at atomic and electronic levels. We here considered the ternary complex of CAP, cAMP and DNA in solvating water molecules and investigated the specific interactions between them at atomic and electronic levels using ab initio molecular simulations based on classical molecular dynamics and ab initio fragment molecular orbital methods. The results highlight the important amino acid residues of CAP for the interactions between CAP and cAMP and between CAP and DNA.

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

PubMed Central

Brorsson, C.; Hansen, N. T.; Lage, K.; Bergholdt, R.; Brunak, S.; Pociot, F.

2009-01-01

Aim To develop novel methods for identifying new genes that contribute to the risk of developing type 1 diabetes within the Major Histocompatibility Complex (MHC) region on chromosome 6, independently of the known linkage disequilibrium (LD) between human leucocyte antigen (HLA)-DRB1, -DQA1, -DQB1 genes. Methods We have developed a novel method that combines single nucleotide polymorphism (SNP) genotyping data with protein–protein interaction (ppi) networks to identify disease-associated network modules enriched for proteins encoded from the MHC region. Approximately 2500 SNPs located in the 4 Mb MHC region were analysed in 1000 affected offspring trios generated by the Type 1 Diabetes Genetics Consortium (T1DGC). The most associated SNP in each gene was chosen and genes were mapped to ppi networks for identification of interaction partners. The association testing and resulting interacting protein modules were statistically evaluated using permutation. Results A total of 151 genes could be mapped to nodes within the protein interaction network and their interaction partners were identified. Five protein interaction modules reached statistical significance using this approach. The identified proteins are well known in the pathogenesis of T1D, but the modules also contain additional candidates that have been implicated in β-cell development and diabetic complications. Conclusions The extensive LD within the MHC region makes it important to develop new methods for analysing genotyping data for identification of additional risk genes for T1D. Combining genetic data with knowledge about functional pathways provides new insight into mechanisms underlying T1D. PMID:19143816

Direct interaction between the tobacco mosaic virus helicase domain and the ATP-bound resistance protein, N factor during the hypersensitive response in tobacco plants.

PubMed

Ueda, Hirokazu; Yamaguchi, Yube; Sano, Hiroshi

2006-05-01

Plants cope with pathogens with distinct mechanisms. One example is a gene-for-gene system, in which plants recognize the pathogen molecule by specified protein(s), this being called the R factor. However, mechanisms of interaction between proteins from the host and the pathogen are not completely understood. Here, we analyzed the mode of interaction between the N factor, a tobacco R factor, and the helicase domain (p50) of tobacco mosaic virus (TMV). To this end, domain dissected proteins were prepared and subjected to Agroinfiltration into intact leaves, followed by yeast two hybrid and pull-down assays. The results pointed to three novel features. First, the N factor was found to directly bind to the p50 of TMV, second, ATP was pre-requisite for this interaction, with formation of an ATP/N factor complex, and third, the N factor was shown to possess ATPase activity, which is enhanced by the p50. Moreover, we found that intra- and/or inter-molecular interactions take place in the N factor molecule. This interaction required ATP, and was disrupted by the p50. Based on these results, we propose a following model for the TMV recognition mechanism in tobacco plants. The N factor forms a complex with ATP, to which the helicase domain interacts, and enhances ATP hydrolysis. The resulting ADP/N factor complex then changes its conformation, thereby facilitating further interaction with the down-stream signaling factor(s). This model is consistent with the idea of 'protein machine'.

Hidden state prediction: a modification of classic ancestral state reconstruction algorithms helps unravel complex symbioses.

PubMed

Zaneveld, Jesse R R; Thurber, Rebecca L V

2014-01-01

Complex symbioses between animal or plant hosts and their associated microbiotas can involve thousands of species and millions of genes. Because of the number of interacting partners, it is often impractical to study all organisms or genes in these host-microbe symbioses individually. Yet new phylogenetic predictive methods can use the wealth of accumulated data on diverse model organisms to make inferences into the properties of less well-studied species and gene families. Predictive functional profiling methods use evolutionary models based on the properties of studied relatives to put bounds on the likely characteristics of an organism or gene that has not yet been studied in detail. These techniques have been applied to predict diverse features of host-associated microbial communities ranging from the enzymatic function of uncharacterized genes to the gene content of uncultured microorganisms. We consider these phylogenetically informed predictive techniques from disparate fields as examples of a general class of algorithms for Hidden State Prediction (HSP), and argue that HSP methods have broad value in predicting organismal traits in a variety of contexts, including the study of complex host-microbe symbioses.

Heuristic Identification of Biological Architectures for Simulating Complex Hierarchical Genetic Interactions

PubMed Central

Moore, Jason H; Amos, Ryan; Kiralis, Jeff; Andrews, Peter C

2015-01-01

Simulation plays an essential role in the development of new computational and statistical methods for the genetic analysis of complex traits. Most simulations start with a statistical model using methods such as linear or logistic regression that specify the relationship between genotype and phenotype. This is appealing due to its simplicity and because these statistical methods are commonly used in genetic analysis. It is our working hypothesis that simulations need to move beyond simple statistical models to more realistically represent the biological complexity of genetic architecture. The goal of the present study was to develop a prototype genotype–phenotype simulation method and software that are capable of simulating complex genetic effects within the context of a hierarchical biology-based framework. Specifically, our goal is to simulate multilocus epistasis or gene–gene interaction where the genetic variants are organized within the framework of one or more genes, their regulatory regions and other regulatory loci. We introduce here the Heuristic Identification of Biological Architectures for simulating Complex Hierarchical Interactions (HIBACHI) method and prototype software for simulating data in this manner. This approach combines a biological hierarchy, a flexible mathematical framework, a liability threshold model for defining disease endpoints, and a heuristic search strategy for identifying high-order epistatic models of disease susceptibility. We provide several simulation examples using genetic models exhibiting independent main effects and three-way epistatic effects. PMID:25395175

Multi-Enzyme Complexes in the Thermophilic Archaea: The Effects of Temperature on Stability, Catalysis and Enzyme Interactions in a Multi-Component System

DTIC Science & Technology

2012-01-01

COVERED (From - To) 4. TITLE AND SUBTITLE Multi- enzyme complexes in the thermophilic archaea: The effects of temperature on stability, catalysis and... enzyme interactions in a multi- component system 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-07-1-0058 5c. PROGRAM ELEMENT NUMBER 61102F 6...involves cloning of the genes for the relevant lipoylation enzymes , and characterisation of the protein products 15. SUBJECT TERMS 16. SECURITY

Sub-Cellular Localization and Complex Formation by Aminoacyl-tRNA Synthetases in Cyanobacteria: Evidence for Interaction of Membrane-Anchored ValRS with ATP Synthase.

PubMed

Santamaría-Gómez, Javier; Ochoa de Alda, Jesús A G; Olmedo-Verd, Elvira; Bru-Martínez, Roque; Luque, Ignacio

2016-01-01

tRNAs are charged with cognate amino acids by aminoacyl-tRNA synthetases (aaRSs) and subsequently delivered to the ribosome to be used as substrates for gene translation. Whether aminoacyl-tRNAs are channeled to the ribosome by transit within translational complexes that avoid their diffusion in the cytoplasm is a matter of intense investigation in organisms of the three domains of life. In the cyanobacterium Anabaena sp. PCC 7120, the valyl-tRNA synthetase (ValRS) is anchored to thylakoid membranes by means of the CAAD domain. We have investigated whether in this organism ValRS could act as a hub for the nucleation of a translational complex by attracting other aaRSs to the membranes. Out of the 20 aaRSs, only ValRS was found to localize in thylakoid membranes whereas the other enzymes occupied the soluble portion of the cytoplasm. To investigate the basis for this asymmetric distribution of aaRSs, a global search for proteins interacting with the 20 aaRSs was conducted. The interaction between ValRS and the FoF1 ATP synthase complex here reported is of utmost interest and suggests a functional link between elements of the gene translation and energy production machineries.

From pull-down data to protein interaction networks and complexes with biological relevance.

PubMed

Zhang, Bing; Park, Byung-Hoon; Karpinets, Tatiana; Samatova, Nagiza F

2008-04-01

Recent improvements in high-throughput Mass Spectrometry (MS) technology have expedited genome-wide discovery of protein-protein interactions by providing a capability of detecting protein complexes in a physiological setting. Computational inference of protein interaction networks and protein complexes from MS data are challenging. Advances are required in developing robust and seamlessly integrated procedures for assessment of protein-protein interaction affinities, mathematical representation of protein interaction networks, discovery of protein complexes and evaluation of their biological relevance. A multi-step but easy-to-follow framework for identifying protein complexes from MS pull-down data is introduced. It assesses interaction affinity between two proteins based on similarity of their co-purification patterns derived from MS data. It constructs a protein interaction network by adopting a knowledge-guided threshold selection method. Based on the network, it identifies protein complexes and infers their core components using a graph-theoretical approach. It deploys a statistical evaluation procedure to assess biological relevance of each found complex. On Saccharomyces cerevisiae pull-down data, the framework outperformed other more complicated schemes by at least 10% in F(1)-measure and identified 610 protein complexes with high-functional homogeneity based on the enrichment in Gene Ontology (GO) annotation. Manual examination of the complexes brought forward the hypotheses on cause of false identifications. Namely, co-purification of different protein complexes as mediated by a common non-protein molecule, such as DNA, might be a source of false positives. Protein identification bias in pull-down technology, such as the hydrophilic bias could result in false negatives.

The genetic landscape of a physical interaction

PubMed Central

Diss, Guillaume

2018-01-01

A key question in human genetics and evolutionary biology is how mutations in different genes combine to alter phenotypes. Efforts to systematically map genetic interactions have mostly made use of gene deletions. However, most genetic variation consists of point mutations of diverse and difficult to predict effects. Here, by developing a new sequencing-based protein interaction assay – deepPCA – we quantified the effects of >120,000 pairs of point mutations on the formation of the AP-1 transcription factor complex between the products of the FOS and JUN proto-oncogenes. Genetic interactions are abundant both in cis (within one protein) and trans (between the two molecules) and consist of two classes – interactions driven by thermodynamics that can be predicted using a three-parameter global model, and structural interactions between proximally located residues. These results reveal how physical interactions generate quantitatively predictable genetic interactions. PMID:29638215

Complex modulation of androgen responsive gene expression by methoxyacetic acid

PubMed Central

2011-01-01

Background Optimal androgen signaling is critical for testicular development and spermatogenesis. Methoxyacetic acid (MAA), the primary active metabolite of the industrial chemical ethylene glycol monomethyl ether, disrupts spermatogenesis and causes testicular atrophy. Transcriptional trans-activation studies have indicated that MAA can enhance androgen receptor activity, however, whether MAA actually impacts the expression of androgen-responsive genes in vivo, and which genes might be affected is not known. Methods A mouse TM3 Leydig cell line that stably expresses androgen receptor (TM3-AR) was prepared and analyzed by transcriptional profiling to identify target gene interactions between MAA and testosterone on a global scale. Results MAA is shown to have widespread effects on androgen-responsive genes, affecting processes ranging from apoptosis to ion transport, cell adhesion, phosphorylation and transcription, with MAA able to enhance, as well as antagonize, androgenic responses. Moreover, testosterone is shown to exert both positive and negative effects on MAA gene responses. Motif analysis indicated that binding sites for FOX, HOX, LEF/TCF, STAT5 and MEF2 family transcription factors are among the most highly enriched in genes regulated by testosterone and MAA. Notably, 65 FOXO targets were repressed by testosterone or showed repression enhanced by MAA with testosterone; these include 16 genes associated with developmental processes, six of which are Hox genes. Conclusions These findings highlight the complex interactions between testosterone and MAA, and provide insight into the effects of MAA exposure on androgen-dependent processes in a Leydig cell model. PMID:21453523

Interaction between the bacterial nucleoid associated proteins Hha and H-NS involves a conformational change of Hha.

PubMed

García, Jesús; Cordeiro, Tiago N; Nieto, José M; Pons, Ignacio; Juárez, Antonio; Pons, Miquel

2005-06-15

The H-NS family of proteins has been shown to participate in the regulation of a large number of genes in Gram-negative bacteria in response to environmental factors. In recent years, it has become apparent that proteins of the Hha family are essential elements for H-NS-regulated gene expression. Hha has been shown to bind H-NS, although the details for this interaction are still unknown. In the present paper, we report fluorescence anisotropy and NMR studies of the interaction between Hha and H-NS64, a truncated form of H-NS containing only its N-terminal dimerization domain. We demonstrate the initial formation of a complex between one Hha and two H-NS64 monomers in 150 mM NaCl. This complex seems to act as a nucleation unit for higher-molecular-mass complexes. NMR studies suggest that Hha is in equilibrium between two different conformations, one of which is stabilized by binding to H-NS64. A similar exchange is also observed for Hha in the absence of H-NS when temperature is increased to 37 degrees C, suggesting a key role for intrinsic conformational changes of Hha in modulating its interaction with H-NS.

Interaction between the bacterial nucleoid associated proteins Hha and H-NS involves a conformational change of Hha

PubMed Central

2005-01-01

The H-NS family of proteins has been shown to participate in the regulation of a large number of genes in Gram-negative bacteria in response to environmental factors. In recent years, it has become apparent that proteins of the Hha family are essential elements for H-NS-regulated gene expression. Hha has been shown to bind H-NS, although the details for this interaction are still unknown. In the present paper, we report fluorescence anisotropy and NMR studies of the interaction between Hha and H-NS64, a truncated form of H-NS containing only its N-terminal dimerization domain. We demonstrate the initial formation of a complex between one Hha and two H-NS64 monomers in 150 mM NaCl. This complex seems to act as a nucleation unit for higher-molecular-mass complexes. NMR studies suggest that Hha is in equilibrium between two different conformations, one of which is stabilized by binding to H-NS64. A similar exchange is also observed for Hha in the absence of H-NS when temperature is increased to 37 °C, suggesting a key role for intrinsic conformational changes of Hha in modulating its interaction with H-NS. PMID:15720293

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

PubMed

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

2016-07-01

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

A ruthenium anticancer compound interacts with histones and impacts differently on epigenetic and death pathways compared to cisplatin

PubMed Central

Capuozzo, Antonelle; Ali, Moussa; Santamaria, Rita; Armant, Olivier; Delalande, Francois; Dorsselaer, Alain Van; Cianferani, Sarah; Spencer, John; Pfeffer, Michel; Mellitzer, Georg; Gaiddon, Christian

2017-01-01

Ruthenium complexes are considered as potential replacements for platinum compounds in oncotherapy. Their clinical development is handicapped by a lack of consensus on their mode of action. In this study, we identify three histones (H3.1, H2A, H2B) as possible targets for an anticancer redox organoruthenium compound (RDC11). Using purified histones, we confirmed an interaction between the ruthenium complex and histones that impacted on histone complex formation. A comparative study of the ruthenium complex versus cisplatin showed differential epigenetic modifications on histone H3 that correlated with differential expression of histone deacetylase (HDAC) genes. We then characterized the impact of these epigenetic modifications on signaling pathways employing a transcriptomic approach. Clustering analyses showed gene expression signatures specific for cisplatin (42%) and for the ruthenium complex (30%). Signaling pathway analyses pointed to specificities distinguishing the ruthenium complex from cisplatin. For instance, cisplatin triggered preferentially p53 and folate biosynthesis while the ruthenium complex induced endoplasmic reticulum stress and trans-sulfuration pathways. To further understand the role of HDACs in these regulations, we used suberanilohydroxamic acid (SAHA) and showed that it synergized with cisplatin cytotoxicity while antagonizing the ruthenium complex activity. This study provides critical information for the characterization of signaling pathways differentiating both compounds, in particular, by the identification of a non-DNA direct target for an organoruthenium complex. PMID:27935863

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

PubMed

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

2018-02-02

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

INCURVATA2 Encodes the Catalytic Subunit of DNA Polymerase α and Interacts with Genes Involved in Chromatin-Mediated Cellular Memory in Arabidopsis thaliana

PubMed Central

Barrero, José María; González-Bayón, Rebeca; del Pozo, Juan Carlos; Ponce, María Rosa; Micol, José Luis

2007-01-01

Cell type–specific gene expression patterns are maintained by the stable inheritance of transcriptional states through mitosis, requiring the action of multiprotein complexes that remodel chromatin structure. Genetic and molecular interactions between chromatin remodeling factors and components of the DNA replication machinery have been identified in Schizosaccharomyces pombe, indicating that some epigenetic marks are replicated simultaneously to DNA with the participation of the DNA replication complexes. This model of epigenetic inheritance might be extended to the plant kingdom, as we report here with the positional cloning and characterization of INCURVATA2 (ICU2), which encodes the putative catalytic subunit of the DNA polymerase α of Arabidopsis thaliana. The strong icu2-2 and icu2-3 insertional alleles caused fully penetrant zygotic lethality when homozygous and incompletely penetrant gametophytic lethality, probably because of loss of DNA polymerase activity. The weak icu2-1 allele carried a point mutation and caused early flowering, leaf incurvature, and homeotic transformations of sepals into carpels and of petals into stamens. Further genetic analyses indicated that ICU2 interacts with TERMINAL FLOWER2, the ortholog of HETEROCHROMATIN PROTEIN1 of animals and yeasts, and with the Polycomb group (PcG) gene CURLY LEAF. Another PcG gene, EMBRYONIC FLOWER2, was found to be epistatic to ICU2. Quantitative RT-PCR analyses indicated that a number of regulatory genes were derepressed in the icu2-1 mutant, including genes associated with flowering time, floral meristem, and floral organ identity. PMID:17873092

The cardiac TBX5 interactome reveals a chromatin remodeling network essential for cardiac septation

PubMed Central

Waldron, Lauren; Steimle, Jeffrey D.; Greco, Todd M.; Gomez, Nicholas C.; Dorr, Kerry M.; Kweon, Junghun; Temple, Brenda; Yang, Xinan Holly; Wilczewski, Caralynn M.; Davis, Ian J.; Cristea, Ileana M.; Moskowitz, Ivan P.; Conlon, Frank L.

2016-01-01

SUMMARY Human mutations in the cardiac transcription factor gene TBX5 cause Congenital Heart Disease (CHD), however the underlying mechanism is unknown. We report characterization of the endogenous TBX5 cardiac interactome and demonstrate that TBX5, long considered a transcriptional activator, interacts biochemically and genetically with the Nucleosome Remodeling and Deacetylase (NuRD) repressor complex. Incompatible gene programs are repressed by TBX5 in the developing heart. CHD missense mutations that disrupt the TBX5-NuRD interaction cause depression of a subset of repressed genes. Furthermore, the TBX5-NuRD interaction is required for heart development. Phylogenetic analysis showed that the TBX5-NuRD interaction domain evolved during early diversification of vertebrates, simultaneous with the evolution of cardiac septation. Collectively, this work defines a TBX5-NuRD interaction essential to cardiac development and the evolution of the mammalian heart, and when altered may contribute to human CHD. PMID:26859351

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

Graph Curvature for Differentiating Cancer Networks

PubMed Central

Sandhu, Romeil; Georgiou, Tryphon; Reznik, Ed; Zhu, Liangjia; Kolesov, Ivan; Senbabaoglu, Yasin; Tannenbaum, Allen

2015-01-01

Cellular interactions can be modeled as complex dynamical systems represented by weighted graphs. The functionality of such networks, including measures of robustness, reliability, performance, and efficiency, are intrinsically tied to the topology and geometry of the underlying graph. Utilizing recently proposed geometric notions of curvature on weighted graphs, we investigate the features of gene co-expression networks derived from large-scale genomic studies of cancer. We find that the curvature of these networks reliably distinguishes between cancer and normal samples, with cancer networks exhibiting higher curvature than their normal counterparts. We establish a quantitative relationship between our findings and prior investigations of network entropy. Furthermore, we demonstrate how our approach yields additional, non-trivial pair-wise (i.e. gene-gene) interactions which may be disrupted in cancer samples. The mathematical formulation of our approach yields an exact solution to calculating pair-wise changes in curvature which was computationally infeasible using prior methods. As such, our findings lay the foundation for an analytical approach to studying complex biological networks. PMID:26169480

Mutations in Protein-Binding Hot-Spots on the Hub Protein Smad3 Differentially Affect Its Protein Interactions and Smad3-Regulated Gene Expression

PubMed Central

Schiro, Michelle M.; Stauber, Sara E.; Peterson, Tami L.; Krueger, Chateen; Darnell, Steven J.; Satyshur, Kenneth A.; Drinkwater, Norman R.; Newton, Michael A.; Hoffmann, F. Michael

2011-01-01

Background Hub proteins are connected through binding interactions to many other proteins. Smad3, a mediator of signal transduction induced by transforming growth factor beta (TGF-β), serves as a hub protein for over 50 protein-protein interactions. Different cellular responses mediated by Smad3 are the product of cell-type and context dependent Smad3-nucleated protein complexes acting in concert. Our hypothesis is that perturbation of this spectrum of protein complexes by mutation of single protein-binding hot-spots on Smad3 will have distinct consequences on Smad3-mediated responses. Methodology/Principal Findings We mutated 28 amino acids on the surface of the Smad3 MH2 domain and identified 22 Smad3 variants with reduced binding to subsets of 17 Smad3-binding proteins including Smad4, SARA, Ski, Smurf2 and SIP1. Mutations defective in binding to Smad4, e.g., D408H, or defective in nucleocytoplasmic shuttling, e.g., W406A, were compromised in modulating the expression levels of a Smad3-dependent reporter gene or six endogenous Smad3-responsive genes: Mmp9, IL11, Tnfaip6, Fermt1, Olfm2 and Wnt11. However, the Smad3 mutants Y226A, Y297A, W326A, K341A, and E267A had distinct differences on TGF-β signaling. For example, K341A and Y226A both reduced the Smad3-mediated activation of the reporter gene by ∼50% but K341A only reduced the TGF-β inducibilty of Olfm2 in contrast to Y226A which reduced the TGF-β inducibility of all six endogenous genes as severely as the W406A mutation. E267A had increased protein binding but reduced TGF-β inducibility because it caused higher basal levels of expression. Y297A had increased TGF-β inducibility because it caused lower Smad3-induced basal levels of gene expression. Conclusions/Significance Mutations in protein binding hot-spots on Smad3 reduced the binding to different subsets of interacting proteins and caused a range of quantitative changes in the expression of genes induced by Smad3. This approach should be useful for unraveling which Smad3 protein complexes are critical for specific biological responses. PMID:21949838

Mutations in protein-binding hot-spots on the hub protein Smad3 differentially affect its protein interactions and Smad3-regulated gene expression.

PubMed

Schiro, Michelle M; Stauber, Sara E; Peterson, Tami L; Krueger, Chateen; Darnell, Steven J; Satyshur, Kenneth A; Drinkwater, Norman R; Newton, Michael A; Hoffmann, F Michael

2011-01-01

Hub proteins are connected through binding interactions to many other proteins. Smad3, a mediator of signal transduction induced by transforming growth factor beta (TGF-β), serves as a hub protein for over 50 protein-protein interactions. Different cellular responses mediated by Smad3 are the product of cell-type and context dependent Smad3-nucleated protein complexes acting in concert. Our hypothesis is that perturbation of this spectrum of protein complexes by mutation of single protein-binding hot-spots on Smad3 will have distinct consequences on Smad3-mediated responses. We mutated 28 amino acids on the surface of the Smad3 MH2 domain and identified 22 Smad3 variants with reduced binding to subsets of 17 Smad3-binding proteins including Smad4, SARA, Ski, Smurf2 and SIP1. Mutations defective in binding to Smad4, e.g., D408H, or defective in nucleocytoplasmic shuttling, e.g., W406A, were compromised in modulating the expression levels of a Smad3-dependent reporter gene or six endogenous Smad3-responsive genes: Mmp9, IL11, Tnfaip6, Fermt1, Olfm2 and Wnt11. However, the Smad3 mutants Y226A, Y297A, W326A, K341A, and E267A had distinct differences on TGF-β signaling. For example, K341A and Y226A both reduced the Smad3-mediated activation of the reporter gene by ∼50% but K341A only reduced the TGF-β inducibilty of Olfm2 in contrast to Y226A which reduced the TGF-β inducibility of all six endogenous genes as severely as the W406A mutation. E267A had increased protein binding but reduced TGF-β inducibility because it caused higher basal levels of expression. Y297A had increased TGF-β inducibility because it caused lower Smad3-induced basal levels of gene expression. Mutations in protein binding hot-spots on Smad3 reduced the binding to different subsets of interacting proteins and caused a range of quantitative changes in the expression of genes induced by Smad3. This approach should be useful for unraveling which Smad3 protein complexes are critical for specific biological responses.

Menin regulates Inhbb expression through an Akt/Ezh2-mediated H3K27 histone modification.

PubMed

Gherardi, Samuele; Ripoche, Doriane; Mikaelian, Ivan; Chanal, Marie; Teinturier, Romain; Goehrig, Delphine; Cordier-Bussat, Martine; Zhang, Chang X; Hennino, Ana; Bertolino, Philippe

2017-04-01

Although Men1 is a well-known tumour suppressor gene, little is known about the functions of Menin, the protein it encodes for. Since few years, numerous publications support a major role of Menin in the control of epigenetics gene regulation. While Menin interaction with MLL complex favours transcriptional activation of target genes through H3K4me3 marks, Menin also represses gene expression via mechanisms involving the Polycomb repressing complex (PRC). Interestingly, Ezh2, the PRC-methyltransferase that catalyses H3K27me3 repressive marks and Menin have been shown to co-occupy a large number of promoters. However, lack of binding between Menin and Ezh2 suggests that another member of the PRC complex is mediating this indirect interaction. Having found that ActivinB - a TGFβ superfamily member encoded by the Inhbb gene - is upregulated in insulinoma tumours caused by Men1 invalidation, we hypothesize that Menin could directly participate in the epigenetic-repression of Inhbb gene expression. Using Animal model and cell lines, we report that loss of Menin is directly associated with ActivinB-induced expression both in vivo and in vitro. Our work further reveals that ActivinB expression is mediated through a direct modulation of H3K27me3 marks on the Inhbb locus in Menin-KO cell lines. More importantly, we show that Menin binds on the promoter of Inhbb gene where it favours the recruitment of Ezh2 via an indirect mechanism involving Akt-phosphorylation. Our data suggests therefore that Menin could take an important part to the Ezh2-epigenetic repressive landscape in many cells and tissues through its capacity to modulate Akt phosphorylation. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

A comparative study of disease genes and drug targets in the human protein interactome

PubMed Central

2015-01-01

Background Disease genes cause or contribute genetically to the development of the most complex diseases. Drugs are the major approaches to treat the complex disease through interacting with their targets. Thus, drug targets are critical for treatment efficacy. However, the interrelationship between the disease genes and drug targets is not clear. Results In this study, we comprehensively compared the network properties of disease genes and drug targets for five major disease categories (cancer, cardiovascular disease, immune system disease, metabolic disease, and nervous system disease). We first collected disease genes from genome-wide association studies (GWAS) for five disease categories and collected their corresponding drugs based on drugs' Anatomical Therapeutic Chemical (ATC) classification. Then, we obtained the drug targets for these five different disease categories. We found that, though the intersections between disease genes and drug targets were small, disease genes were significantly enriched in targets compared to their enrichment in human protein-coding genes. We further compared network properties of the proteins encoded by disease genes and drug targets in human protein-protein interaction networks (interactome). The results showed that the drug targets tended to have higher degree, higher betweenness, and lower clustering coefficient in cancer Furthermore, we observed a clear fraction increase of disease proteins or drug targets in the near neighborhood compared with the randomized genes. Conclusions The study presents the first comprehensive comparison of the disease genes and drug targets in the context of interactome. The results provide some foundational network characteristics for further designing computational strategies to predict novel drug targets and drug repurposing. PMID:25861037

A comparative study of disease genes and drug targets in the human protein interactome.

PubMed

Sun, Jingchun; Zhu, Kevin; Zheng, W; Xu, Hua

2015-01-01

Disease genes cause or contribute genetically to the development of the most complex diseases. Drugs are the major approaches to treat the complex disease through interacting with their targets. Thus, drug targets are critical for treatment efficacy. However, the interrelationship between the disease genes and drug targets is not clear. In this study, we comprehensively compared the network properties of disease genes and drug targets for five major disease categories (cancer, cardiovascular disease, immune system disease, metabolic disease, and nervous system disease). We first collected disease genes from genome-wide association studies (GWAS) for five disease categories and collected their corresponding drugs based on drugs' Anatomical Therapeutic Chemical (ATC) classification. Then, we obtained the drug targets for these five different disease categories. We found that, though the intersections between disease genes and drug targets were small, disease genes were significantly enriched in targets compared to their enrichment in human protein-coding genes. We further compared network properties of the proteins encoded by disease genes and drug targets in human protein-protein interaction networks (interactome). The results showed that the drug targets tended to have higher degree, higher betweenness, and lower clustering coefficient in cancer Furthermore, we observed a clear fraction increase of disease proteins or drug targets in the near neighborhood compared with the randomized genes. The study presents the first comprehensive comparison of the disease genes and drug targets in the context of interactome. The results provide some foundational network characteristics for further designing computational strategies to predict novel drug targets and drug repurposing.

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

PubMed

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

2017-08-01

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

The Caenorhabditis elegans RDE-10/RDE-11 complex regulates RNAi by promoting secondary siRNA amplification.

PubMed

Zhang, Chi; Montgomery, Taiowa A; Fischer, Sylvia E J; Garcia, Susana M D A; Riedel, Christian G; Fahlgren, Noah; Sullivan, Christopher M; Carrington, James C; Ruvkun, Gary

2012-05-22

In nematodes, plants, and fungi, RNAi is remarkably potent and persistent due to the amplification of initial silencing signals by RNA-dependent RNA polymerases (RdRPs). In Caenorhabditis elegans (C. elegans), the interaction between the RNA-induced silencing complex (RISC) loaded with primary small interfering RNAs (siRNAs) and the target messenger RNA (mRNA) leads to the recruitment of RdRPs and synthesis of secondary siRNAs using the target mRNA as the template. The mechanism and genetic requirements for secondary siRNA accumulation are not well understood. From a forward genetic screen for C. elegans genes required for RNAi, we identified rde-10, and through proteomic analysis of RDE-10-interacting proteins, we identified a protein complex containing the new RNAi factor RDE-11, the known RNAi factors RSD-2 and ERGO-1, and other candidate RNAi factors. The RNAi defective genes rde-10 and rde-11 encode a novel protein and a RING-type zinc finger domain protein, respectively. Mutations in rde-10 and rde-11 genes cause dosage-sensitive RNAi deficiencies: these mutants are resistant to low dosage but sensitive to high dosage of double-stranded RNAs. We assessed the roles of rde-10, rde-11, and other dosage-sensitive RNAi-defective genes rsd-2, rsd-6, and haf-6 in both exogenous and endogenous small RNA pathways using high-throughput sequencing and qRT-PCR. These genes are required for the accumulation of secondary siRNAs in both exogenous and endogenous RNAi pathways. The RDE-10/RDE-11 complex is essential for the amplification of RNAi in C. elegans by promoting secondary siRNA accumulation. Copyright © 2012 Elsevier Ltd. All rights reserved.

The Caenorhabditis elegans RDE-10/RDE-11 complex regulates RNAi by promoting secondary siRNA amplification

PubMed Central

Zhang, Chi; Montgomery, Taiowa A.; Fischer, Sylvia E. J.; Garcia, Susana M. D. A.; Riedel, Christian G.; Fahlgren, Noah; Sullivan, Christopher M.; Carrington, James C.; Ruvkun, Gary

2012-01-01

SUMMARY Background In nematodes, plants and fungi, RNAi is remarkably potent and persistent due to the amplification of initial silencing signals by RNA-dependent RNA polymerases (RdRPs). In Caenorhabditis elegans (C. elegans), the interaction between the RNA-induced silencing complex (RISC) loaded with primary siRNAs and the target mRNA leads to the recruitment of RdRPs and synthesis of secondary siRNAs using the target mRNA as the template. The mechanism and genetic requirements for secondary siRNA accumulation are not well understood. Results From a forward genetic screen for C. elegans genes required for RNAi, we identified rde-10 and through proteomic analysis of RDE-10-interacting proteins, we identified a protein complex containing the new RNAi factor RDE-11, the known RNAi factors RSD-2 and ERGO-1, as well as other candidate RNAi factors. The RNAi defective genes rde-10 and rde-11 encode a novel protein and a RING-type zinc finger domain protein, respectively. Mutations in rde-10 and rde-11 genes cause dosage-sensitive RNAi deficiencies: these mutants are resistant to low dosage, but sensitive to high dosage of double-stranded RNAs (dsRNAs). We assessed the roles of rde-10, rde-11, and other dosage-sensitive RNAi-defective genes rsd-2, rsd-6 and haf-6 in both exogenous and endogenous small RNA pathways using high-throughput sequencing and qRT-PCR. These genes are required for the accumulation of secondary siRNAs in both exogenous and endogenous RNAi pathways. Conclusions The RDE-10/RDE-11 complex is essential for the amplification of RNAi in C. elegans by promoting secondary siRNA accumulation. PMID:22542102

Competitive Endogenous RNAs in Prostate Cancer

DTIC Science & Technology

2015-01-01

that there is a negative correlation between GAS5 and miR-21, and microRNAs silence target genes via RISC complex carrying AGO2, next we asked whether...GAS5 directly interacts with miR-12 in the RISC complex. Thus, we synthesized GAS5 RNA probe and labeled with biotin and then mixed with cellular

Insight into genome variability in the Fusarium Incarnatum-equiseti species complex through comparative analysis of secondary metabolic biosynthetic gene clusters

USDA-ARS?s Scientific Manuscript database

The genus Fusarium comprises 22 species complexes that together include approximately 300 phylogenetically distinct species. A major focus in Fusarium literature is to understand the genetic basis of niche specialization, secondary metabolites (SM) production, and host interactions in closely relate...

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

PubMed Central

2011-01-01

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

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.

Polyamidoamine-Decorated Nanodiamonds as a Hybrid Gene Delivery Vector and siRNA Structural Characterization at the Charged Interfaces.

PubMed

Lim, Dae Gon; Rajasekaran, Nirmal; Lee, Dukhee; Kim, Nam Ah; Jung, Hun Soon; Hong, Sungyoul; Shin, Young Kee; Kang, Eunah; Jeong, Seong Hoon

2017-09-20

Nanodiamonds have been discovered as a new exogenous material source in biomedical applications. As a new potent form of nanodiamond (ND), polyamidoamine-decorated nanodiamonds (PAMAM-NDs) were prepared for E7 or E6 oncoprotein-suppressing siRNA gene delivery for high risk human papillomavirus-induced cervical cancer, such as types 16 and 18. It is critical to understand the physicochemical properties of siRNA complexes immobilized on cationic solid ND surfaces in the aspect of biomolecular structural and conformational changes, as the new inert carbon material can be extended into the application of a gene delivery vector. A spectral study of siRNA/PAMAM-ND complexes using differential scanning calorimetry and circular dichroism spectroscopy proved that the hydrogen bonding and electrostatic interactions between siRNA and PAMAM-NDs decreased endothermic heat capacity. Moreover, siRNA/PAMAM-ND complexes showed low cell cytotoxicity and significant suppressing effects for forward target E6 and E7 oncogenic genes, proving functional and therapeutic efficacy. The cellular uptake of siRNA/PAMAM-ND complexes at 8 h was visualized by macropinocytes and direct endosomal escape of the siRNA/PAMAM-ND complexes. It is presumed that PAMAM-NDs provided a buffering cushion to adjust the pH and hard mechanical stress to escape endosomes. siRNA/PAMAM-ND complexes provide a potential organic/inorganic hybrid material source for gene delivery carriers.

Recovering Protein-Protein and Domain-Domain Interactions from Aggregation of IP-MS Proteomics of Coregulator Complexes

PubMed Central

Mazloom, Amin R.; Dannenfelser, Ruth; Clark, Neil R.; Grigoryan, Arsen V.; Linder, Kathryn M.; Cardozo, Timothy J.; Bond, Julia C.; Boran, Aislyn D. W.; Iyengar, Ravi; Malovannaya, Anna; Lanz, Rainer B.; Ma'ayan, Avi

2011-01-01

Coregulator proteins (CoRegs) are part of multi-protein complexes that transiently assemble with transcription factors and chromatin modifiers to regulate gene expression. In this study we analyzed data from 3,290 immuno-precipitations (IP) followed by mass spectrometry (MS) applied to human cell lines aimed at identifying CoRegs complexes. Using the semi-quantitative spectral counts, we scored binary protein-protein and domain-domain associations with several equations. Unlike previous applications, our methods scored prey-prey protein-protein interactions regardless of the baits used. We also predicted domain-domain interactions underlying predicted protein-protein interactions. The quality of predicted protein-protein and domain-domain interactions was evaluated using known binary interactions from the literature, whereas one protein-protein interaction, between STRN and CTTNBP2NL, was validated experimentally; and one domain-domain interaction, between the HEAT domain of PPP2R1A and the Pkinase domain of STK25, was validated using molecular docking simulations. The scoring schemes presented here recovered known, and predicted many new, complexes, protein-protein, and domain-domain interactions. The networks that resulted from the predictions are provided as a web-based interactive application at http://maayanlab.net/HT-IP-MS-2-PPI-DDI/. PMID:22219718

Characterization and modification of phage T7 DNA polymerase for use in DNA sequencing; Progress report, June 1, 1990--May 31, 1993

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

Richardson, C.C.

1993-12-31

This project focuses on the DNA polymerase (gene 5 protein) of phage T7 for use in DNA sequence analysis. Gene 5 protein interacts with accessory proteins to acquire properties essential for DNA replication. One goal is to understand these interactions in order to modify the proteins for use in DNA sequencing. E. coli thioredoxin, binds to gene 5 protein and clamps it to a primer-template. They have analyzed the binding of gene 5 protein-thioredoxin to primer-templates and have defined the optimal conditions to form an extremely stable complex with a dNTP in the polymerase catalytic site. The spatial proximity ofmore » these components has been determined using fluorescence emission anisotropy. The T7 DNA binding protein, the gene 2.5 protein, interacts with gene 5 protein and gene 4 protein to increase processivity and primer synthesis, respectively. Mutant gene 2.5 proteins have been isolated that do not interact with T7 DNA polymerase and can not support T7 growth. The nucleotide binding site of the T7 helicase has been identified and mutations affecting the site provide information on how the hydrolysis of NTPs fuel its unidirectional translocation. The sequence, GTC, has been shown to be necessary and sufficient for recognition by the T7 primase. The T7 gene 5.5 protein interacts with the E. coli nucleoid protein, H-NS, and also overcomes the phage {lambda} rex restriction system.« less

Systems genetics: a paradigm to improve discovery of candidate genes and mechanisms underlying complex traits.

PubMed

Feltus, F Alex

2014-06-01

Understanding the control of any trait optimally requires the detection of causal genes, gene interaction, and mechanism of action to discover and model the biochemical pathways underlying the expressed phenotype. Functional genomics techniques, including RNA expression profiling via microarray and high-throughput DNA sequencing, allow for the precise genome localization of biological information. Powerful genetic approaches, including quantitative trait locus (QTL) and genome-wide association study mapping, link phenotype with genome positions, yet genetics is less precise in localizing the relevant mechanistic information encoded in DNA. The coupling of salient functional genomic signals with genetically mapped positions is an appealing approach to discover meaningful gene-phenotype relationships. Techniques used to define this genetic-genomic convergence comprise the field of systems genetics. This short review will address an application of systems genetics where RNA profiles are associated with genetically mapped genome positions of individual genes (eQTL mapping) or as gene sets (co-expression network modules). Both approaches can be applied for knowledge independent selection of candidate genes (and possible control mechanisms) underlying complex traits where multiple, likely unlinked, genomic regions might control specific complex traits. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

RNA editing of microRNA prevents RNA-induced silencing complex recognition of target mRNA

PubMed Central

Cui, Yalei; Huang, Tianzhi; Zhang, Xiaobo

2015-01-01

MicroRNAs (miRNAs) integrate with Argonaut (Ago) to create the RNA-induced silencing complex, and regulate gene expression by silencing target mRNAs. RNA editing of miRNA may affect miRNA processing, assembly of the Ago complex and target mRNA binding. However, the function of edited miRNA, assembled within the Ago complex, has not been extensively investigated. In this study, sequence analysis of the Ago complex of Marsupenaeus japonicus shrimp infected with white spot syndrome virus (WSSV) revealed that host ADAR (adenosine deaminase acting on RNA) catalysed A-to-I RNA editing of a viral miRNA (WSSV-miR-N12) at the +16 site. This editing of the non-seed sequence did not affect association of the edited miRNA with the Ago protein, but inhibited interaction between the miRNA and its target gene (wsv399). The WSSV early gene wsv399 inhibited WSSV infection. As a result, the RNA editing of miRNA caused virus latency. Our results highlight a novel example of miRNA editing in the miRNA-induced silencing complex. PMID:26674414

Annual Research Review: Developmental Considerations of Gene by Environment Interactions

ERIC Educational Resources Information Center

Lenroot, Rhoshel K.; Giedd, Jay N.

2011-01-01

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

The Expression of Caspases Is Enhanced in Peripheral Blood Mononuclear Cells of Autism Spectrum Disorder Patients

ERIC Educational Resources Information Center

Siniscalco, Dario; Sapone, Anna; Giordano, Catia; Cirillo, Alessandra; de Novellis, Vito; de Magistris, Laura; Rossi, Francesco; Fasano, Alessio; Maione, Sabatino; Antonucci, Nicola

2012-01-01

Autism and autism spectrum disorders (ASDs) are heterogeneous complex neuro-developmental disorders characterized by dysfunctions in social interaction and communication skills. Their pathogenesis has been linked to interactions between genes and environmental factors. Consistent with the evidence of certain similarities between immune cells and…

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

ERIC Educational Resources Information Center

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

2012-01-01

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

Yeast transcriptional activator INO2 interacts as an Ino2p/Ino4p basic helix-loop-helix heteromeric complex with the inositol/choline-responsive element necessary for expression of phospholipid biosynthetic genes in Saccharomyces cerevisiae.

PubMed Central

Schwank, S; Ebbert, R; Rautenstrauss, K; Schweizer, E; Schüller, H J

1995-01-01

Coordinate transcriptional control of yeast genes involved in phospholipid biosynthesis is mediated by the inositol/choline-responsive element (ICRE) contained in the respective promoter regions. Regulatory genes INO2 and INO4, both encoding basic helix-loop-helix (bHLH) proteins, are necessary for ICRE-dependent gene activation. By the use of size variants and by heterologous expression in E. coli we demonstrate that Ino2p and Ino4p are both necessary and sufficient for the formation of the previously described FAS binding factor 1, Fbf1, interacting with the ICRE. Formation of a heteromeric complex between Ino2p and Ino4p by means of the respective bHLH domains was demonstrated in vivo by the interaction of appropriate two-hybrid constructs and in vitro by Far-Western analyses. Neither Ino2p nor Ino4p binds to the ICRE as a homodimer. When fused to the DNA-binding domain of Gal4p, Ino2p but not Ino4p was able to activate a UASGAL-containing reporter gene even in the absence of the heterologous Fbf1 subunit. By deletion studies, two separate transcriptional activation domains were identified in the N-terminal part of Ino2p. Thus, the bHLH domains of Ino2p and Ino4p constitute the dimerization/DNA-binding module of Fbf1 mediating its interaction with the ICRE, while transcriptional activation is effected exclusively by Ino2p. Images PMID:7862526

Identification and functional analysis of a core gene module associated with hepatitis C virus-induced human hepatocellular carcinoma progression.

PubMed

Bai, Gaobo; Zheng, Wenling; Ma, Wenli

2018-05-01

Hepatitis C virus (HCV)-induced human hepatocellular carcinoma (HCC) progression may be due to a complex multi-step processes. The developmental mechanism of these processes is worth investigating for the prevention, diagnosis and therapy of HCC. The aim of the present study was to investigate the molecular mechanism underlying the progression of HCV-induced hepatocarcinogenesis. First, the dynamic gene module, consisting of key genes associated with progression between the normal stage and HCC, was identified using the Weighted Gene Co-expression Network Analysis tool from R language. By defining those genes in the module as seeds, the change of co-expression in differentially expressed gene sets in two consecutive stages of pathological progression was examined. Finally, interaction pairs of HCV viral proteins and their directly targeted proteins in the identified module were extracted from the literature and a comprehensive interaction dataset from yeast two-hybrid experiments. By combining the interactions between HCV and their targets, and protein-protein interactions in the Search Tool for the Retrieval of Interacting Genes database (STRING), the HCV-key genes interaction network was constructed and visualized using Cytoscape software 3.2. As a result, a module containing 44 key genes was identified to be associated with HCC progression, due to the dynamic features and functions of those genes in the module. Several important differentially co-expressed gene pairs were identified between non-HCC and HCC stages. In the key genes, cyclin dependent kinase 1 (CDK1), NDC80, cyclin A2 (CCNA2) and rac GTPase activating protein 1 (RACGAP1) were shown to be targeted by the HCV nonstructural proteins NS5A, NS3 and NS5B, respectively. The four genes perform an intermediary role between the HCV viral proteins and the dysfunctional module in the HCV key genes interaction network. These findings provided valuable information for understanding the mechanism of HCV-induced HCC progression and for seeking drug targets for the therapy and prevention of HCC.

Mutations in extracellular matrix genes NID1 and LAMC1 cause autosomal dominant Dandy-Walker malformation and occipital cephaloceles

PubMed Central

Darbro, Benjamin W.; Mahajan, Vinit B.; Gakhar, Lokesh; Skeie, Jessica M.; Campbell, Elizabeth; Wu, Shu; Bing, Xinyu; Millen, Kathleen J.; Dobyns, William B.; Kessler, John A.; Jalali, Ali; Cremer, James; Segre, Alberto; Manak, J. Robert; Aldinger, Kimerbly A.; Suzuki, Satoshi; Natsume, Nagato; Ono, Maya; Hai, Huynh Dai; Viet, Le Thi; Loddo, Sara; Valente, Enza M.; Bernardini, Laura; Ghonge, Nitin; Ferguson, Polly J.; Bassuk, Alexander G.

2013-01-01

We performed whole-exome sequencing of a family with autosomal dominant Dandy-Walker malformation and occipital cephaloceles (ADDWOC) and detected a mutation in the extracellular matrix protein encoding gene NID1. In a second family, protein interaction network analysis identified a mutation in LAMC1, which encodes a NID1 binding partner. Structural modeling the NID1-LAMC1 complex demonstrated that each mutation disrupts the interaction. These findings implicate the extracellular matrix in the pathogenesis of Dandy-Walker spectrum disorders. PMID:23674478

A network approach to predict pathogenic genes for Fusarium graminearum.

PubMed

Liu, Xiaoping; Tang, Wei-Hua; Zhao, Xing-Ming; Chen, Luonan

2010-10-04

Fusarium graminearum is the pathogenic agent of Fusarium head blight (FHB), which is a destructive disease on wheat and barley, thereby causing huge economic loss and health problems to human by contaminating foods. Identifying pathogenic genes can shed light on pathogenesis underlying the interaction between F. graminearum and its plant host. However, it is difficult to detect pathogenic genes for this destructive pathogen by time-consuming and expensive molecular biological experiments in lab. On the other hand, computational methods provide an alternative way to solve this problem. Since pathogenesis is a complicated procedure that involves complex regulations and interactions, the molecular interaction network of F. graminearum can give clues to potential pathogenic genes. Furthermore, the gene expression data of F. graminearum before and after its invasion into plant host can also provide useful information. In this paper, a novel systems biology approach is presented to predict pathogenic genes of F. graminearum based on molecular interaction network and gene expression data. With a small number of known pathogenic genes as seed genes, a subnetwork that consists of potential pathogenic genes is identified from the protein-protein interaction network (PPIN) of F. graminearum, where the genes in the subnetwork are further required to be differentially expressed before and after the invasion of the pathogenic fungus. Therefore, the candidate genes in the subnetwork are expected to be involved in the same biological processes as seed genes, which imply that they are potential pathogenic genes. The prediction results show that most of the pathogenic genes of F. graminearum are enriched in two important signal transduction pathways, including G protein coupled receptor pathway and MAPK signaling pathway, which are known related to pathogenesis in other fungi. In addition, several pathogenic genes predicted by our method are verified in other pathogenic fungi, which demonstrate the effectiveness of the proposed method. The results presented in this paper not only can provide guidelines for future experimental verification, but also shed light on the pathogenesis of the destructive fungus F. graminearum.

Mito-Nuclear Interactions Affecting Lifespan and Neurodegeneration in a Drosophila Model of Leigh Syndrome.

PubMed

Loewen, Carin A; Ganetzky, Barry

2018-04-01

Proper mitochondrial activity depends upon proteins encoded by genes in the nuclear and mitochondrial genomes that must interact functionally and physically in a precisely coordinated manner. Consequently, mito-nuclear allelic interactions are thought to be of crucial importance on an evolutionary scale, as well as for manifestation of essential biological phenotypes, including those directly relevant to human disease. Nonetheless, detailed molecular understanding of mito-nuclear interactions is still lacking, and definitive examples of such interactions in vivo are sparse. Here we describe the characterization of a mutation in Drosophila ND23 , a nuclear gene encoding a highly conserved subunit of mitochondrial complex 1. This characterization led to the discovery of a mito-nuclear interaction that affects the ND23 mutant phenotype. ND23 mutants exhibit reduced lifespan, neurodegeneration, abnormal mitochondrial morphology, and decreased ATP levels. These phenotypes are similar to those observed in patients with Leigh syndrome, which is caused by mutations in a number of nuclear genes that encode mitochondrial proteins, including the human ortholog of ND23 A key feature of Leigh syndrome, and other mitochondrial disorders, is unexpected and unexplained phenotypic variability. We discovered that the phenotypic severity of ND23 mutations varies depending on the maternally inherited mitochondrial background. Sequence analysis of the relevant mitochondrial genomes identified several variants that are likely candidates for the phenotypic interaction with mutant ND23 , including a variant affecting a mitochondrially encoded component of complex I. Thus, our work provides an in vivo demonstration of the phenotypic importance of mito-nuclear interactions in the context of mitochondrial disease. Copyright © 2018 by the Genetics Society of America.

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

PubMed

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

2012-08-01

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

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

Genetic interactions underlying hybrid male sterility in the Drosophila bipectinata species complex.

PubMed

Mishra, Paras Kumar; Singh, Bashisth Narayan

2006-06-01

Understanding genetic mechanisms underlying hybrid male sterility is one of the most challenging problems in evolutionary biology especially speciation. By using the interspecific hybridization method roles of Y chromosome, Major Hybrid Sterility (MHS) genes and cytoplasm in sterility of hybrid males have been investigated in a promising group, the Drosophila bipectinata species complex that consists of four closely related species: D. pseudoananassae, D. bipectinata, D. parabipectinata and D. malerkotliana. The interspecific introgression analyses show that neither cytoplasm nor MHS genes are involved but X-Y interactions may be playing major role in hybrid male sterility between D. pseudoananassae and the other three species. The results of interspecific introgression analyses also show considerable decrease in the number of males in the backcross offspring and all males have atrophied testes. There is a significant positive correlation between sex - ratio distortion and severity of sterility in backcross males. These findings provide evidence that D. pseudoananassae is remotely related with other three species of the D. bipectinata species complex.

c-Ski inhibits the TGF-beta signaling pathway through stabilization of inactive Smad complexes on Smad-binding elements.

PubMed

Suzuki, Hiroyuki; Yagi, Ken; Kondo, Miki; Kato, Mitsuyasu; Miyazono, Kohei; Miyazawa, Keiji

2004-06-24

c-Ski inhibits transforming growth factor-beta (TGF-beta) signaling through interaction with Smad proteins. c-Ski represses Smad-mediated transcriptional activation, probably through its action as a transcriptional co-repressor. c-Ski also inhibits TGF-beta-induced downregulation of genes such as c-myc. However, mechanisms for transcriptional regulation of target genes by c-Ski have not been fully determined. In this study, we examined how c-Ski inhibits both TGF-beta-induced transcriptional activation and repression. DNA-affinity precipitation analysis revealed that c-Ski enhances the binding of Smad2 and 4, and to a lesser extent Smad3, to both CAGA and TGF-beta1 inhibitory element probes. A c-Ski mutant, which is unable to interact with Smad4, failed to enhance the binding of Smad complex on these probes and to inhibit the Smad-responsive promoter. These results suggest that stabilization of inactive Smad complexes on DNA is a critical event in c-Ski-mediated inhibition of TGF-beta signaling.

The light gene of Drosophila melanogaster encodes a homologue of VPS41, a yeast gene involved in cellular-protein trafficking.

PubMed

Warner, T S; Sinclair, D A; Fitzpatrick, K A; Singh, M; Devlin, R H; Honda, B M

1998-04-01

Mutations in a number of genes affect eye colour in Drosophila melanogaster; some of these "eye-colour" genes have been shown to be involved in various aspects of cellular transport processes. In addition, combinations of viable mutant alleles of some of these genes, such as carnation (car) combined with either light (lt) or deep-orange (dor) mutants, show lethal interactions. Recently, dor was shown to be homologous to the yeast gene PEP3 (VPS18), which is known to be involved in intracellular trafficking. We have undertaken to extend our earlier work on the lt gene, in order to examine in more detail its expression pattern and to characterize its gene product via sequencing of a cloned cDNA. The gene appears to be expressed at relatively high levels in all stages and tissues examined, and shows strong homology to VPS41, a gene involved in cellular-protein trafficking in yeast and higher eukaryotes. Further genetic experiments also point to a role for lt in transport processes: we describe lethal interactions between viable alleles of lt and dor, as well as phenotypic interactions (reductions in eye pigment) between allels of lt and another eye-colour gene, garnet (g), whose gene product has close homology to a subunit of the human adaptor complex, AP-3.

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

Interfacing cellular networks of S. cerevisiae and E. coli: Connecting dynamic and genetic information

PubMed Central

2013-01-01

Background In recent years, various types of cellular networks have penetrated biology and are nowadays used omnipresently for studying eukaryote and prokaryote organisms. Still, the relation and the biological overlap among phenomenological and inferential gene networks, e.g., between the protein interaction network and the gene regulatory network inferred from large-scale transcriptomic data, is largely unexplored. Results We provide in this study an in-depth analysis of the structural, functional and chromosomal relationship between a protein-protein network, a transcriptional regulatory network and an inferred gene regulatory network, for S. cerevisiae and E. coli. Further, we study global and local aspects of these networks and their biological information overlap by comparing, e.g., the functional co-occurrence of Gene Ontology terms by exploiting the available interaction structure among the genes. Conclusions Although the individual networks represent different levels of cellular interactions with global structural and functional dissimilarities, we observe crucial functions of their network interfaces for the assembly of protein complexes, proteolysis, transcription, translation, metabolic and regulatory interactions. Overall, our results shed light on the integrability of these networks and their interfacing biological processes. PMID:23663484

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

PubMed

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

2015-11-01

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

Structural Insights into the Regulation of Foreign Genes in Salmonella by the Hha/H-NS Complex*

PubMed Central

Ali, Sabrina S.; Whitney, John C.; Stevenson, James; Robinson, Howard; Howell, P. Lynne; Navarre, William Wiley

2013-01-01

The bacterial nucleoid-associated proteins Hha and H-NS jointly repress horizontally acquired genes in Salmonella, including essential virulence loci encoded within Salmonella pathogenicity islands. Hha is known to interact with the N-terminal dimerization domain of H-NS; however, the manner in which this interaction enhances transcriptional silencing is not understood. To further understand this process, we solved the x-ray crystal structure of Hha in complex with the N-terminal dimerization domain of H-NS (H-NS(1–46)) to 3.2 Å resolution. Two monomers of Hha bind to symmetrical sites on either side of the H-NS(1–46) dimer. Disruption of the Hha/H-NS interaction by the H-NS site-specific mutation I11A results in increased expression of the Hha/H-NS co-regulated gene hilA without affecting the expression levels of proV, a target gene repressed by H-NS in an Hha-independent fashion. Examination of the structure revealed a cluster of conserved basic amino acids that protrude from the surface of Hha on the opposite side of the Hha/H-NS(1–46) interface. Hha mutants with a diminished positively charged surface maintain the ability to interact with H-NS but can no longer regulate hilA. Increased expression of the hilA locus did not correspond to significant depletion of H-NS at the promoter region in chromatin immunoprecipitation assays. However, in vitro, we find Hha improves H-NS binding to target DNA fragments. Taken together, our results show for the first time how Hha and H-NS interact to direct transcriptional repression and reveal that a positively charged surface of Hha enhances the silencing activity of H-NS nucleoprotein filaments. PMID:23515315

Recruitment by the Repressor Freud-1 of Histone Deacetylase-Brg1 Chromatin Remodeling Complexes to Strengthen HTR1A Gene Repression.

PubMed

Souslova, Tatiana; Mirédin, Kim; Millar, Anne M; Albert, Paul R

2017-12-01

Five-prime repressor element under dual repression binding protein-1 (Freud-1)/CC2D1A is genetically linked to intellectual disability and implicated in neuronal development. Freud-1 represses the serotonin-1A (5-HT1A) receptor gene HTR1A by histone deacetylase (HDAC)-dependent or HDAC-independent mechanisms in 5-HT1A-negative (e.g., HEK-293) or 5-HT1A-expressing cells (SK-N-SH), respectively. To identify the underlying mechanisms, Freud-1-associated proteins were affinity-purified from HEK-293 nuclear extracts and members of the Brg1/SMARCCA chromatin remodeling and Sin3A-HDAC corepressor complexes were identified. Pull-down assays using recombinant proteins showed that Freud-1 interacts directly with the Brg1 carboxyl-terminal domain; interaction with Brg1 required the carboxyl-terminal of Freud-1. Freud-1 complexes in HEK-293 and SK-N-SH cells differed, with low levels of BAF170/SMARCC2 and BAF57/SMARCE1 in HEK-293 cells and low-undetectable BAF155/SMARCC1, Sin3A, and HDAC1/2 in SK-N-SH cells. Similarly, by quantitative chromatin immunoprecipitation, Brg1-BAF170/57 and Sin3A-HDAC complexes were observed at the HTR1A promoter in HEK-293 cells, whereas in SK-N-SH cells, Sin3A-HDAC proteins were not detected. Quantifying 5-HT1A receptor mRNA levels in cells treated with siRNA to Freud-1, Brg1, or both RNAs addressed the functional role of the Freud-1-Brg1 complex. In HEK-293 cells, 5-HT1A receptor mRNA levels were increased only when both Freud-1 and Brg1 were depleted, but in SK-N-SH cells, depletion of either protein upregulated 5-HT1A receptor RNA. Thus, recruitment by Freud-1 of Brg1, BAF155, and Sin3A-HDAC complexes appears to strengthen repression of the HTR1A gene to prevent its expression inappropriate cell types, while recruitment of the Brg1-BAF170/57 complex is permissive to 5-HT1A receptor expression. Alterations in Freud-1-Brg1 interactions in mutants associated with intellectual disability could impair gene repression leading to altered neuronal development.

Recruitment by the Repressor Freud-1 of Histone Deacetylase-Brg1 Chromatin Remodeling Complexes to Strengthen HTR1A Gene Repression

PubMed Central

Souslova, Tatiana; Mirédin, Kim; Millar, Anne M.

2017-01-01

Five-prime repressor element under dual repression binding protein-1 (Freud-1)/CC2D1A is genetically linked to intellectual disability and implicated in neuronal development. Freud-1 represses the serotonin-1A (5-HT1A) receptor gene HTR1A by histone deacetylase (HDAC)-dependent or HDAC-independent mechanisms in 5-HT1A-negative (e.g., HEK-293) or 5-HT1A-expressing cells (SK-N-SH), respectively. To identify the underlying mechanisms, Freud-1-associated proteins were affinity-purified from HEK-293 nuclear extracts and members of the Brg1/SMARCCA chromatin remodeling and Sin3A-HDAC corepressor complexes were identified. Pull-down assays using recombinant proteins showed that Freud-1 interacts directly with the Brg1 carboxyl-terminal domain; interaction with Brg1 required the carboxyl-terminal of Freud-1. Freud-1 complexes in HEK-293 and SK-N-SH cells differed, with low levels of BAF170/SMARCC2 and BAF57/SMARCE1 in HEK-293 cells and low-undetectable BAF155/SMARCC1, Sin3A, and HDAC1/2 in SK-N-SH cells. Similarly, by quantitative chromatin immuno-precipitation, Brg1-BAF170/57 and Sin3A-HDAC complexes were observed at the HTR1A promoter in HEK-293 cells, whereas in SK-N-SH cells, Sin3A-HDAC proteins were not detected. Quantifying 5-HT1A receptor mRNA levels in cells treated with siRNA to Freud-1, Brg1, or both RNAs addressed the functional role of the Freud-1-Brg1 complex. In HEK-293 cells, 5-HT1A receptor mRNA levels were increased only when both Freud-1 and Brg1 were depleted, but in SK-N-SH cells, depletion of either protein upregulated 5-HT1A receptor RNA. Thus, recruitment by Freud-1 of Brg1, BAF155, and Sin3A-HDAC complexes appears to strengthen repression of the HTR1A gene to prevent its expression inappropriate cell types, while recruitment of the Brg1-BAF170/57 complex is permissive to 5-HT1A receptor expression. Alterations in Freud-1-Brg1 interactions in mutants associated with intellectual disability could impair gene repression leading to altered neuronal development. PMID:27914010

Interaction of the iron–sulfur cluster assembly protein IscU with the Hsc66/Hsc20 molecular chaperone system of Escherichia coli

PubMed Central

Hoff, Kevin G.; Silberg, Jonathan J.; Vickery, Larry E.

2000-01-01

The iscU gene in bacteria is located in a gene cluster encoding proteins implicated in iron–sulfur cluster assembly and an hsc70-type (heat shock cognate) molecular chaperone system, iscSUA-hscBA. To investigate possible interactions between these systems, we have overproduced and purified the IscU protein from Escherichia coli and have studied its interactions with the hscA and hscB gene products Hsc66 and Hsc20. IscU and its iron–sulfur complex (IscU–Fe/S) stimulated the basal steady-state ATPase activity of Hsc66 weakly in the absence of Hsc20 but, in the presence of Hsc20, increased the ATPase activity up to 480-fold. Hsc20 also decreased the apparent Km for IscU stimulation of Hsc66 ATPase activity, and surface plasmon resonance studies revealed that Hsc20 enhances binding of IscU to Hsc66. Surface plasmon resonance and isothermal titration calorimetry further showed that IscU and Hsc20 form a complex, and Hsc20 may thereby aid in the targeting of IscU to Hsc66. These results establish a direct and specific role for the Hsc66/Hsc20 chaperone system in functioning with isc gene components for the assembly of iron–sulfur cluster proteins. PMID:10869428

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.

Chronic obstructive pulmonary disease: nature-nurture interactions.

PubMed

Clancy, John; Nobes, Maggie

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

Predicting the Impact of Alternative Splicing on Plant MADS Domain Protein Function

PubMed Central

Severing, Edouard I.; van Dijk, Aalt D. J.; Morabito, Giuseppa; Busscher-Lange, Jacqueline; Immink, Richard G. H.; van Ham, Roeland C. H. J.

2012-01-01

Several genome-wide studies demonstrated that alternative splicing (AS) significantly increases the transcriptome complexity in plants. However, the impact of AS on the functional diversity of proteins is difficult to assess using genome-wide approaches. The availability of detailed sequence annotations for specific genes and gene families allows for a more detailed assessment of the potential effect of AS on their function. One example is the plant MADS-domain transcription factor family, members of which interact to form protein complexes that function in transcription regulation. Here, we perform an in silico analysis of the potential impact of AS on the protein-protein interaction capabilities of MIKC-type MADS-domain proteins. We first confirmed the expression of transcript isoforms resulting from predicted AS events. Expressed transcript isoforms were considered functional if they were likely to be translated and if their corresponding AS events either had an effect on predicted dimerisation motifs or occurred in regions known to be involved in multimeric complex formation, or otherwise, if their effect was conserved in different species. Nine out of twelve MIKC MADS-box genes predicted to produce multiple protein isoforms harbored putative functional AS events according to those criteria. AS events with conserved effects were only found at the borders of or within the K-box domain. We illustrate how AS can contribute to the evolution of interaction networks through an example of selective inclusion of a recently evolved interaction motif in the MADS AFFECTING FLOWERING1-3 (MAF1–3) subclade. Furthermore, we demonstrate the potential effect of an AS event in SHORT VEGETATIVE PHASE (SVP), resulting in the deletion of a short sequence stretch including a predicted interaction motif, by overexpression of the fully spliced and the alternatively spliced SVP transcripts. For most of the AS events we were able to formulate hypotheses about the potential impact on the interaction capabilities of the encoded MIKC proteins. PMID:22295091

USP15 regulates dynamic protein–protein interactions of the spliceosome through deubiquitination of PRP31

PubMed Central

Das, Tanuza; Park, Joon Kyu; Park, Jinyoung; Kim, Eunji; Rape, Michael

2017-01-01

Abstract Post-translational modifications contribute to the spliceosome dynamics by facilitating the physical rearrangements of the spliceosome. Here, we report USP15, a deubiquitinating enzyme, as a regulator of protein–protein interactions for the spliceosome dynamics. We show that PRP31, a component of U4 snRNP, is modified with K63-linked ubiquitin chains by the PRP19 complex and deubiquitinated by USP15 and its substrate targeting factor SART3. USP15SART3 makes a complex with USP4 and this ternary complex serves as a platform to deubiquitinate PRP31 and PRP3. The ubiquitination and deubiquitination status of PRP31 regulates its interaction with the U5 snRNP component PRP8, which is required for the efficient splicing of chromosome segregation related genes, probably by stabilizing the U4/U6.U5 tri-snRNP complex. Collectively, our data suggest that USP15 plays a key role in the regulation of dynamic protein–protein interactions of the spliceosome. PMID:28088760

The butterfly plant arms-race escalated by gene and genome duplications

PubMed Central

Edger, Patrick P.; Heidel-Fischer, Hanna M.; Bekaert, Michaël; Rota, Jadranka; Glöckner, Gernot; Platts, Adrian E.; Heckel, David G.; Der, Joshua P.; Wafula, Eric K.; Tang, Michelle; Hofberger, Johannes A.; Smithson, Ann; Hall, Jocelyn C.; Blanchette, Matthieu; Bureau, Thomas E.; Wright, Stephen I.; dePamphilis, Claude W.; Eric Schranz, M.; Barker, Michael S.; Conant, Gavin C.; Wahlberg, Niklas; Vogel, Heiko; Pires, J. Chris; Wheat, Christopher W.

2015-01-01

Coevolutionary interactions are thought to have spurred the evolution of key innovations and driven the diversification of much of life on Earth. However, the genetic and evolutionary basis of the innovations that facilitate such interactions remains poorly understood. We examined the coevolutionary interactions between plants (Brassicales) and butterflies (Pieridae), and uncovered evidence for an escalating evolutionary arms-race. Although gradual changes in trait complexity appear to have been facilitated by allelic turnover, key innovations are associated with gene and genome duplications. Furthermore, we show that the origins of both chemical defenses and of molecular counter adaptations were associated with shifts in diversification rates during the arms-race. These findings provide an important connection between the origins of biodiversity, coevolution, and the role of gene and genome duplications as a substrate for novel traits. PMID:26100883

The butterfly plant arms-race escalated by gene and genome duplications.

PubMed

Edger, Patrick P; Heidel-Fischer, Hanna M; Bekaert, Michaël; Rota, Jadranka; Glöckner, Gernot; Platts, Adrian E; Heckel, David G; Der, Joshua P; Wafula, Eric K; Tang, Michelle; Hofberger, Johannes A; Smithson, Ann; Hall, Jocelyn C; Blanchette, Matthieu; Bureau, Thomas E; Wright, Stephen I; dePamphilis, Claude W; Eric Schranz, M; Barker, Michael S; Conant, Gavin C; Wahlberg, Niklas; Vogel, Heiko; Pires, J Chris; Wheat, Christopher W

2015-07-07

Coevolutionary interactions are thought to have spurred the evolution of key innovations and driven the diversification of much of life on Earth. However, the genetic and evolutionary basis of the innovations that facilitate such interactions remains poorly understood. We examined the coevolutionary interactions between plants (Brassicales) and butterflies (Pieridae), and uncovered evidence for an escalating evolutionary arms-race. Although gradual changes in trait complexity appear to have been facilitated by allelic turnover, key innovations are associated with gene and genome duplications. Furthermore, we show that the origins of both chemical defenses and of molecular counter adaptations were associated with shifts in diversification rates during the arms-race. These findings provide an important connection between the origins of biodiversity, coevolution, and the role of gene and genome duplications as a substrate for novel traits.

β-Globin locus control region HS2 and HS3 interact structurally and functionally

PubMed Central

Jackson, David A.; McDowell, Jennifer C.; Dean, Ann

2003-01-01

The overall structure of the DNase I hypersensitive sites (HSs) that comprise the β-globin locus control region (LCR) is highly conserved among mammals, implying that the HSs have conserved functions. However, it is not well understood how the LCR HSs, either individually or collectively, activate transcription. We analyzed the interactions of HS2, HS3 and HS4 with the human ε- and β-globin genes in chromatinized episomes in fetal/embryonic K562 cells. Only HS2 activates transcription of the ε-globin gene, while all three HSs activate the β-globin gene. HS3 stimulates the β-globin gene constitutively, but HS2 and HS4 transactivation requires expression of the transcription factor EKLF, which is not present in K562 cells but is required for β-globin expression in vivo. To begin addressing how the individual HSs may interact with one another in a complex, we linked the β-globin gene to both the HS2 and HS3. HS2 and HS3 together resulted in synergistic stimulation of β-globin transcription. Unexpectedly, mutated, inactive forms of HS2 impeded the activation of the β-globin gene by HS3. Thus, there appear to be distinct interactions among the HSs and between the HSs and the globin genes. These preferential, non-exclusive interactions may underlie an important structural and functional cooperativity among the regulatory sequences of the β-globin locus in vivo. PMID:12582237

Latent feature decompositions for integrative analysis of multi-platform genomic data

PubMed Central

Gregory, Karl B.; Momin, Amin A.; Coombes, Kevin R.; Baladandayuthapani, Veerabhadran

2015-01-01

Increased availability of multi-platform genomics data on matched samples has sparked research efforts to discover how diverse molecular features interact both within and between platforms. In addition, simultaneous measurements of genetic and epigenetic characteristics illuminate the roles their complex relationships play in disease progression and outcomes. However, integrative methods for diverse genomics data are faced with the challenges of ultra-high dimensionality and the existence of complex interactions both within and between platforms. We propose a novel modeling framework for integrative analysis based on decompositions of the large number of platform-specific features into a smaller number of latent features. Subsequently we build a predictive model for clinical outcomes accounting for both within- and between-platform interactions based on Bayesian model averaging procedures. Principal components, partial least squares and non-negative matrix factorization as well as sparse counterparts of each are used to define the latent features, and the performance of these decompositions is compared both on real and simulated data. The latent feature interactions are shown to preserve interactions between the original features and not only aid prediction but also allow explicit selection of outcome-related features. The methods are motivated by and applied to, a glioblastoma multiforme dataset from The Cancer Genome Atlas to predict patient survival times integrating gene expression, microRNA, copy number and methylation data. For the glioblastoma data, we find a high concordance between our selected prognostic genes and genes with known associations with glioblastoma. In addition, our model discovers several relevant cross-platform interactions such as copy number variation associated gene dosing and epigenetic regulation through promoter methylation. On simulated data, we show that our proposed method successfully incorporates interactions within and between genomic platforms to aid accurate prediction and variable selection. Our methods perform best when principal components are used to define the latent features. PMID:26146492

Functional genomics platform for pooled screening and mammalian genetic interaction maps

PubMed Central

Kampmann, Martin; Bassik, Michael C.; Weissman, Jonathan S.

2014-01-01

Systematic genetic interaction maps in microorganisms are powerful tools for identifying functional relationships between genes and defining the function of uncharacterized genes. We have recently implemented this strategy in mammalian cells as a two-stage approach. First, genes of interest are robustly identified in a pooled genome-wide screen using complex shRNA libraries. Second, phenotypes for all pairwise combinations of hit genes are measured in a double-shRNA screen and used to construct a genetic interaction map. Our protocol allows for rapid pooled screening under various conditions without a requirement for robotics, in contrast to arrayed approaches. Each stage of the protocol can be implemented in ~2 weeks, with additional time for analysis and generation of reagents. We discuss considerations for screen design, and present complete experimental procedures as well as a full computational analysis suite for identification of hits in pooled screens and generation of genetic interaction maps. While the protocols outlined here were developed for our original shRNA-based approach, they can be applied more generally, including to CRISPR-based approaches. PMID:24992097

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

PubMed Central

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

2017-01-01

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

Structural and Functional Assessment of APOBEC3G Macromolecular Complexes

PubMed Central

Polevoda, Bogdan; McDougall, William M.; Bennett, Ryan P.; Salter, Jason D.; Smith, Harold C.

2016-01-01

There are eleven members in the human APOBEC family of proteins that are evolutionarily related through their zinc-dependent cytidine deaminase domains. The human APOBEC gene clusters arose on chromosome 6 and 22 through gene duplication and divergence to where current day APOBEC proteins are functionally diverse and broadly expressed in tissues. APOBEC serve enzymatic and non enzymatic functions in cells. In both cases, formation of higher-order structures driven by APOBEC protein-protein interactions and binding to RNA and/or single stranded DNA are integral to their function. In some circumstances, these interactions are regulatory and modulate APOBEC activities. We are just beginning to understand how macromolecular interactions drive processes such as APOBEC subcellular compartmentalization, formation of holoenzyme complexes, gene targeting, foreign DNA restriction, anti-retroviral activity, formation of ribonucleoprotein particles and APOBEC degradation. Protein-protein and protein-nucleic acid cross-linking methods coupled with mass spectrometry, electrophoretic mobility shift assays, glycerol gradient sedimentation, fluorescence anisotropy and APOBEC deaminase assays are enabling mapping of interacting surfaces that are essential for these functions. The goal of this methods review is through example of our research on APOBEC3G, describe the application of cross-linking methods to characterize and quantify macromolecular interactions and their functional implications. Given the homology in structure and function, it is proposed that these methods will be generally applicable to the discovery process for other APOBEC and RNA and DNA editing and modifying proteins. PMID:26988126

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.

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.

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

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

Condensin-driven remodelling of X chromosome topology during dosage compensation

NASA Astrophysics Data System (ADS)

Crane, Emily; Bian, Qian; McCord, Rachel Patton; Lajoie, Bryan R.; Wheeler, Bayly S.; Ralston, Edward J.; Uzawa, Satoru; Dekker, Job; Meyer, Barbara J.

2015-07-01

The three-dimensional organization of a genome plays a critical role in regulating gene expression, yet little is known about the machinery and mechanisms that determine higher-order chromosome structure. Here we perform genome-wide chromosome conformation capture analysis, fluorescent in situ hybridization (FISH), and RNA-seq to obtain comprehensive three-dimensional (3D) maps of the Caenorhabditis elegans genome and to dissect X chromosome dosage compensation, which balances gene expression between XX hermaphrodites and XO males. The dosage compensation complex (DCC), a condensin complex, binds to both hermaphrodite X chromosomes via sequence-specific recruitment elements on X (rex sites) to reduce chromosome-wide gene expression by half. Most DCC condensin subunits also act in other condensin complexes to control the compaction and resolution of all mitotic and meiotic chromosomes. By comparing chromosome structure in wild-type and DCC-defective embryos, we show that the DCC remodels hermaphrodite X chromosomes into a sex-specific spatial conformation distinct from autosomes. Dosage-compensated X chromosomes consist of self-interacting domains (~1 Mb) resembling mammalian topologically associating domains (TADs). TADs on X chromosomes have stronger boundaries and more regular spacing than on autosomes. Many TAD boundaries on X chromosomes coincide with the highest-affinity rex sites and become diminished or lost in DCC-defective mutants, thereby converting the topology of X to a conformation resembling autosomes. rex sites engage in DCC-dependent long-range interactions, with the most frequent interactions occurring between rex sites at DCC-dependent TAD boundaries. These results imply that the DCC reshapes the topology of X chromosomes by forming new TAD boundaries and reinforcing weak boundaries through interactions between its highest-affinity binding sites. As this model predicts, deletion of an endogenous rex site at a DCC-dependent TAD boundary using CRISPR/Cas9 greatly diminished the boundary. Thus, the DCC imposes a distinct higher-order structure onto X chromosomes while regulating gene expression chromosome-wide.

Condensin-Driven Remodeling of X-Chromosome Topology during Dosage Compensation

PubMed Central

Crane, Emily; Bian, Qian; McCord, Rachel Patton; Lajoie, Bryan R.; Wheeler, Bayly S.; Ralston, Edward J.; Uzawa, Satoru; Dekker, Job; Meyer, Barbara J.

2015-01-01

The three-dimensional organization of a genome plays a critical role in regulating gene expression, yet little is known about the machinery and mechanisms that determine higher-order chromosome structure1,2. Here we perform genome-wide chromosome conformation capture analysis, FISH, and RNA-seq to obtain comprehensive 3D maps of the Caenorhabditis elegans genome and to dissect X-chromosome dosage compensation, which balances gene expression between XX hermaphrodites and XO males. The dosage compensation complex (DCC), a condensin complex, binds to both hermaphrodite X chromosomes via sequence-specific recruitment elements on X (rex sites) to reduce chromosome-wide gene expression by half3–7. Most DCC condensin subunits also act in other condensin complexes to control the compaction and resolution of all mitotic and meiotic chromosomes5,6. By comparing chromosome structure in wild-type and DCC-defective embryos, we show that the DCC remodels hermaphrodite X chromosomes into a sex-specific spatial conformation distinct from autosomes. Dosage-compensated X chromosomes consist of self-interacting domains (~1 Mb) resembling mammalian Topologically Associating Domains (TADs)8,9. TADs on X have stronger boundaries and more regular spacing than on autosomes. Many TAD boundaries on X coincide with the highest-affinity rex sites and become diminished or lost in DCC-defective mutants, thereby converting the topology of X to a conformation resembling autosomes. rex sites engage in DCC-dependent long-range interactions, with the most frequent interactions occurring between rex sites at DCC-dependent TAD boundaries. These results imply that the DCC reshapes the topology of X by forming new TAD boundaries and reinforcing weak boundaries through interactions between its highest-affinity binding sites. As this model predicts, deletion of an endogenous rex site at a DCC-dependent TAD boundary using CRISPR/Cas9 greatly diminished the boundary. Thus, the DCC imposes a distinct higher-order structure onto X while regulating gene expression chromosome wide. PMID:26030525

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

Gene Transfer in Eukaryotic Cells Using Activated Dendrimers

NASA Astrophysics Data System (ADS)

Dennig, Jörg

Gene transfer into eukaryotic cells plays an important role in cell biology. Over the last 30 years a number of transfection methods have been developed to mediate gene transfer into eukaryotic cells. Classical methods include co-precipitation of DNA with calcium phosphate, charge-dependent precipitation of DNA with DEAE-dextran, electroporation of nucleic acids, and formation of transfection complexes between DNA and cationic liposomes. Gene transfer technologies based on activated PAMAM-dendrimers provide another class of transfection reagents. PAMAM-dendrimers are highly branched, spherical molecules. Activation of newly synthesized dendrimers involves hydrolytic removal of some of the branches, and results in a molecule with a higher degree of flexibility. Activated dendrimers assemble DNA into compact structures via charge interactions. Activated dendrimer - DNA complexes bind to the cell membrane of eukaryotic cells, and are transported into the cell by non-specific endocytosis. A structural model of the activated dendrimer - DNA complex and a potential mechanism for its uptake into cells will be discussed.

An Arabidopsis Gene Regulatory Network for Secondary Cell Wall Synthesis

PubMed Central

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

2014-01-01

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

Mediator and Cohesin Connect Gene Expression and Chromatin Architecture

PubMed Central

Kagey, Michael H.; Newman, Jamie J.; Bilodeau, Steve; Zhan, Ye; Orlando, David A.; van Berkum, Nynke L.; Ebmeier, Christopher C.; Goossens, Jesse; Rahl, Peter B.; Levine, Stuart S.; Taatjes, Dylan J.; Dekker, Job; Young, Richard A.

2010-01-01

Summary Transcription factors control cell specific gene expression programs through interactions with diverse coactivators and the transcription apparatus. Gene activation may involve DNA loop formation between enhancer-bound transcription factors and the transcription apparatus at the core promoter, but this process is not well understood. We report here that Mediator and Cohesin physically and functionally connect the enhancers and core promoters of active genes in embryonic stem cells. Mediator, a transcriptional coactivator, forms a complex with Cohesin, which can form rings that connect two DNA segments. The Cohesin loading factor Nipbl is associated with Mediator/Cohesin complexes, providing a means to load Cohesin at promoters. DNA looping is observed between the enhancers and promoters occupied by Mediator and Cohesin. Mediator and Cohesin occupy different promoters in different cells, thus generating cell-type specific DNA loops linked to the gene expression program of each cell. PMID:20720539

Genetics of preeclampsia: what are the challenges?

PubMed

Bernard, Nathalie; Giguère, Yves

2003-07-01

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

Kicking against the PRCs – A Domesticated Transposase Antagonises Silencing Mediated by Polycomb Group Proteins and Is an Accessory Component of Polycomb Repressive Complex 2

PubMed Central

Perera, Pumi; Mora-García, Santiago; de Leau, Erica; Thornton, Harry; de Alves, Flavia Lima; Rapsilber, Juri; Yang, Suxin; James, Geo Velikkakam; Schneeberger, Korbinian; Finnegan, E. Jean; Turck, Franziska; Goodrich, Justin

2015-01-01

The Polycomb group (PcG) and trithorax group (trxG) genes play crucial roles in development by regulating expression of homeotic and other genes controlling cell fate. Both groups catalyse modifications of chromatin, particularly histone methylation, leading to epigenetic changes that affect gene activity. The trxG antagonizes the function of PcG genes by activating PcG target genes, and consequently trxG mutants suppress PcG mutant phenotypes. We previously identified the ANTAGONIST OF LIKE HETEROCHROMATIN PROTEIN1 (ALP1) gene as a genetic suppressor of mutants in the Arabidopsis PcG gene LIKE HETEROCHROMATIN PROTEIN1 (LHP1). Here, we show that ALP1 interacts genetically with several other PcG and trxG components and that it antagonizes PcG silencing. Transcriptional profiling reveals that when PcG activity is compromised numerous target genes are hyper-activated in seedlings and that in most cases this requires ALP1. Furthermore, when PcG activity is present ALP1 is needed for full activation of several floral homeotic genes that are repressed by the PcG. Strikingly, ALP1 does not encode a known chromatin protein but rather a protein related to PIF/Harbinger class transposases. Phylogenetic analysis indicates that ALP1 is broadly conserved in land plants and likely lost transposase activity and acquired a novel function during angiosperm evolution. Consistent with this, immunoprecipitation and mass spectrometry (IP-MS) show that ALP1 associates, in vivo, with core components of POLYCOMB REPRESSIVE COMPLEX 2 (PRC2), a widely conserved PcG protein complex which functions as a H3K27me3 histone methyltransferase. Furthermore, in reciprocal pulldowns using the histone methyltransferase CURLY LEAF (CLF), we identify not only ALP1 and the core PRC2 components but also plant-specific accessory components including EMBRYONIC FLOWER 1 (EMF1), a transcriptional repressor previously associated with PRC1-like complexes. Taken together our data suggest that ALP1 inhibits PcG silencing by blocking the interaction of the core PRC2 with accessory components that promote its HMTase activity or its role in inhibiting transcription. ALP1 is the first example of a domesticated transposase acquiring a novel function as a PcG component. The antagonistic interaction of a modified transposase with the PcG machinery is novel and may have arisen as a means for the cognate transposon to evade host surveillance or for the host to exploit features of the transposition machinery beneficial for epigenetic regulation of gene activity. PMID:26642436

The Mediator Complex MED15 Subunit Mediates Activation of Downstream Lipid-Related Genes by the WRINKLED1 Transcription Factor.

PubMed

Kim, Mi Jung; Jang, In-Cheol; Chua, Nam-Hai

2016-07-01

The Mediator complex is known to be a master coordinator of transcription by RNA polymerase II, and this complex is recruited by transcription factors (TFs) to target promoters for gene activation or repression. The plant-specific TF WRINKLED1 (WRI1) activates glycolysis-related and fatty acid biosynthetic genes during embryogenesis. However, no Mediator subunit has yet been identified that mediates WRI1 transcriptional activity. Promoter-β-glucuronidase fusion experiments showed that MEDIATOR15 (MED15) is expressed in the same cells in the embryo as WRI1. We found that the Arabidopsis (Arabidopsis thaliana) MED15 subunit of the Mediator complex interacts directly with WRI1 in the nucleus. Overexpression of MED15 or WRI1 increased transcript levels of WRI1 target genes involved in glycolysis and fatty acid biosynthesis; these genes were down-regulated in wild-type or WRI1-overexpressing plants by silencing of MED15 However, overexpression of MED15 in the wri1 mutant also increased transcript levels of WRI1 target genes, suggesting that MED15 also may act with other TFs to activate downstream lipid-related genes. Chromatin immunoprecipitation assays confirmed the association of MED15 with six WRI1 target gene promoters. Additionally, silencing of MED15 resulted in reduced fatty acid content in seedlings and mature seeds, whereas MED15 overexpression increased fatty acid content in both developmental stages. Similar results were found in wri1 mutant and WRI1 overexpression lines. Together, our results indicate that the WRI1/MED15 complex transcriptionally regulates glycolysis-related and fatty acid biosynthetic genes during embryogenesis. © 2016 American Society of Plant Biologists. All Rights Reserved.

Equilibrium location for spherical DNA and toroidal cyclodextrin

NASA Astrophysics Data System (ADS)

Sarapat, Pakhapoom; Baowan, Duangkamon; Hill, James M.

2018-05-01

Cyclodextrin comprises a ring structure composed of glucose molecules with an ability to form complexes of certain substances within its central cavity. The compound can be utilised for various applications including food, textiles, cosmetics, pharmaceutics, and gene delivery. In gene transfer, the possibility of forming complexes depends upon the interaction energy between cyclodextrin and DNA molecules which here are modelled as a torus and a sphere, respectively. Our proposed model is derived using the continuum approximation together with the Lennard-Jones potential, and the total interaction energy is obtained by integrating over both the spherical and toroidal surfaces. The results suggest that the DNA prefers to be symmetrically situated about 1.2 Å above the centre of the cyclodextrin to minimise its energy. Furthermore, an optimal configuration can be determined for any given size of torus and sphere.

Characterization of the Porphyromonas gingivalis Type IX Secretion Trans-envelope PorKLMNP Core Complex*

PubMed Central

Vincent, Maxence S.; Canestrari, Mickaël J.; Leone, Philippe; Stathopulos, Julien; Ize, Bérengère; Zoued, Abdelrahim; Cambillau, Christian; Kellenberger, Christine; Roussel, Alain

2017-01-01

The transport of proteins at the cell surface of Bacteroidetes depends on a secretory apparatus known as type IX secretion system (T9SS). This machine is responsible for the cell surface exposition of various proteins, such as adhesins, required for gliding motility in Flavobacterium, S-layer components in Tannerella forsythia, and tooth tissue-degrading enzymes in the oral pathogen Porphyromonas gingivalis. Although a number of subunits of the T9SS have been identified, we lack details on the architecture of this secretion apparatus. Here we provide evidence that five of the genes encoding the core complex of the T9SS are co-transcribed and that the gene products are distributed in the cell envelope. Protein-protein interaction studies then revealed that these proteins oligomerize and interact through a dense network of contacts. PMID:28057754

A Protein Encoded by the Latency-Related Gene of Bovine Herpesvirus 1 Is Expressed in Trigeminal Ganglionic Neurons of Latently Infected Cattle and Interacts with Cyclin-Dependent Kinase 2 during Productive Infection

PubMed Central

Jiang, Yunquan; Hossain, Ashfaque; Winkler, Maria Teresa; Holt, Todd; Doster, Alan; Jones, Clinton

1998-01-01

Despite productive viral gene expression in the peripheral nervous system during acute infection, the bovine herpesvirus 1 (BHV-1) infection cycle is blocked in sensory ganglionic neurons and consequently latency is established. The only abundant viral transcript expressed during latency is the latency-related (LR) RNA. LR gene products inhibit S-phase entry, and binding of the LR protein (LRP) to cyclin A was hypothesized to block cell cycle progression. This study demonstrates LRP is a nuclear protein which is expressed in neurons of latently infected cattle. Affinity chromatography indicated that LRP interacts with cyclin-dependent kinase 2 (cdk2)-cyclin complexes or cdc2-cyclin complexes in transfected human cells or infected bovine cells. After partial purification using three different columns (DEAE-Sepharose, Econo S, and heparin-agarose), LRP was primarily associated with cdk2-cyclin E complexes, an enzyme which is necessary for G1-to-S-phase cell cycle progression. During acute infection of trigeminal ganglia or following dexamethasone-induced reactivation, BHV-1 induces expression of cyclin A in neurons (L. M. Schang, A. Hossain, and C. Jones, J. Virol. 70:3807–3814, 1996). Expression of S-phase regulatory proteins (cyclin A, for example) leads to neuronal apoptosis. Consequently, we hypothesize that interactions between LRP and cell cycle regulatory proteins promote survival of postmitotic neurons during acute infection and/or reactivation. PMID:9733854

A protein encoded by the latency-related gene of bovine herpesvirus 1 is expressed in trigeminal ganglionic neurons of latently infected cattle and interacts with cyclin-dependent kinase 2 during productive infection.

PubMed

Jiang, Y; Hossain, A; Winkler, M T; Holt, T; Doster, A; Jones, C

1998-10-01

Despite productive viral gene expression in the peripheral nervous system during acute infection, the bovine herpesvirus 1 (BHV-1) infection cycle is blocked in sensory ganglionic neurons and consequently latency is established. The only abundant viral transcript expressed during latency is the latency-related (LR) RNA. LR gene products inhibit S-phase entry, and binding of the LR protein (LRP) to cyclin A was hypothesized to block cell cycle progression. This study demonstrates LRP is a nuclear protein which is expressed in neurons of latently infected cattle. Affinity chromatography indicated that LRP interacts with cyclin-dependent kinase 2 (cdk2)-cyclin complexes or cdc2-cyclin complexes in transfected human cells or infected bovine cells. After partial purification using three different columns (DEAE-Sepharose, Econo S, and heparin-agarose), LRP was primarily associated with cdk2-cyclin E complexes, an enzyme which is necessary for G1-to-S-phase cell cycle progression. During acute infection of trigeminal ganglia or following dexamethasone-induced reactivation, BHV-1 induces expression of cyclin A in neurons (L. M. Schang, A. Hossain, and C. Jones, J. Virol. 70:3807-3814, 1996). Expression of S-phase regulatory proteins (cyclin A, for example) leads to neuronal apoptosis. Consequently, we hypothesize that interactions between LRP and cell cycle regulatory proteins promote survival of postmitotic neurons during acute infection and/or reactivation.

Power of data mining methods to detect genetic associations and interactions.

PubMed

Molinaro, Annette M; Carriero, Nicholas; Bjornson, Robert; Hartge, Patricia; Rothman, Nathaniel; Chatterjee, Nilanjan

2011-01-01

Genetic association studies, thus far, have focused on the analysis of individual main effects of SNP markers. Nonetheless, there is a clear need for modeling epistasis or gene-gene interactions to better understand the biologic basis of existing associations. Tree-based methods have been widely studied as tools for building prediction models based on complex variable interactions. An understanding of the power of such methods for the discovery of genetic associations in the presence of complex interactions is of great importance. Here, we systematically evaluate the power of three leading algorithms: random forests (RF), Monte Carlo logic regression (MCLR), and multifactor dimensionality reduction (MDR). We use the algorithm-specific variable importance measures (VIMs) as statistics and employ permutation-based resampling to generate the null distribution and associated p values. The power of the three is assessed via simulation studies. Additionally, in a data analysis, we evaluate the associations between individual SNPs in pro-inflammatory and immunoregulatory genes and the risk of non-Hodgkin lymphoma. The power of RF is highest in all simulation models, that of MCLR is similar to RF in half, and that of MDR is consistently the lowest. Our study indicates that the power of RF VIMs is most reliable. However, in addition to tuning parameters, the power of RF is notably influenced by the type of variable (continuous vs. categorical) and the chosen VIM. Copyright © 2011 S. Karger AG, Basel.

Genetic Interaction of Centrosomin and Bazooka in Apical Domain Regulation in Drosophila Photoreceptor

PubMed Central

Chen, Geng; Rogers, Alicia K.; League, Garrett P.; Nam, Sang-Chul

2011-01-01

Background Cell polarity genes including Crumbs (Crb) and Par complexes are essential for controlling photoreceptor morphogenesis. Among the Crb and Par complexes, Bazooka (Baz, Par-3 homolog) acts as a nodal component for other cell polarity proteins. Therefore, finding other genes interacting with Baz will help us to understand the cell polarity genes' role in photoreceptor morphogenesis. Methodology/Principal Findings Here, we have found a genetic interaction between baz and centrosomin (cnn). Cnn is a core protein for centrosome which is a major microtubule-organizing center. We analyzed the effect of the cnn mutation on developing eyes to determine its role in photoreceptor morphogenesis. We found that Cnn is dispensable for retinal differentiation in eye imaginal discs during the larval stage. However, photoreceptors deficient in Cnn display dramatic morphogenesis defects including the mislocalization of Crumbs (Crb) and Bazooka (Baz) during mid-stage pupal eye development, suggesting that Cnn is specifically required for photoreceptor morphogenesis during pupal eye development. This role of Cnn in apical domain modulation was further supported by Cnn's gain-of-function phenotype. Cnn overexpression in photoreceptors caused the expansion of the apical Crb membrane domain, Baz and adherens junctions (AJs). Conclusions/Significance These results strongly suggest that the interaction of Baz and Cnn is essential for apical domain and AJ modulation during photoreceptor morphogenesis, but not for the initial photoreceptor differentiation in the Drosophila photoreceptor. PMID:21253601

Molecular pathways to parallel evolution: I. Gene nexuses and their morphological correlates.

PubMed

Zuckerkandl, E

1994-12-01

Aspects of the regulatory interactions among genes are probably as old as most genes are themselves. Correspondingly, similar predispositions to changes in such interactions must have existed for long evolutionary periods. Features of the structure and the evolution of the system of gene regulation furnish the background necessary for a molecular understanding of parallel evolution. Patently "unrelated" organs, such as the fat body of a fly and the liver of a mammal, can exhibit fractional homology, a fraction expected to become subject to quantitation. This also seems to hold for different organs in the same organism, such as wings and legs of a fly. In informational macromolecules, on the other hand, homology is indeed all or none. In the quite different case of organs, analogy is expected usually to represent attenuated homology. Many instances of putative convergence are likely to turn out to be predominantly parallel evolution, presumably including the case of the vertebrate and cephalopod eyes. Homology in morphological features reflects a similarity in networks of active genes. Similar nexuses of active genes can be established in cells of different embryological origins. Thus, parallel development can be considered a counterpart to parallel evolution. Specific macromolecular interactions leading to the regulation of the c-fos gene are given as an example of a "controller node" defined as a regulatory unit. Quantitative changes in gene control are distinguished from relational changes, and frequent parallelism in quantitative changes is noted in Drosophila enzymes. Evolutionary reversions in quantitative gene expression are also expected. The evolution of relational patterns is attributed to several distinct mechanisms, notably the shuffling of protein domains. The growth of such patterns may in part be brought about by a particular process of compensation for "controller gene diseases," a process that would spontaneously tend to lead to increased regulatory and organismal complexity. Despite the inferred increase in gene interaction complexity, whose course over evolutionary time is unknown, the number of homology groups for the functional and structural protein units designated as domains has probably remained rather constant, even as, in some of its branches, evolution moved toward "higher" organisms. In connection with this process, the question is raised of parallel evolution within the purview of activating and repressing master switches and in regard to the number of levels into which the hierarchies of genic master switches will eventually be resolved.

A robust multifactor dimensionality reduction method for detecting gene-gene interactions with application to the genetic analysis of bladder cancer susceptibility

PubMed Central

Gui, Jiang; Andrew, Angeline S.; Andrews, Peter; Nelson, Heather M.; Kelsey, Karl T.; Karagas, Margaret R.; Moore, Jason H.

2010-01-01

A central goal of human genetics is to identify and characterize susceptibility genes for common complex human diseases. An important challenge in this endeavor is the modeling of gene-gene interaction or epistasis that can result in non-additivity of genetic effects. The multifactor dimensionality reduction (MDR) method was developed as machine learning alternative to parametric logistic regression for detecting interactions in absence of significant marginal effects. The goal of MDR is to reduce the dimensionality inherent in modeling combinations of polymorphisms using a computational approach called constructive induction. Here, we propose a Robust Multifactor Dimensionality Reduction (RMDR) method that performs constructive induction using a Fisher’s Exact Test rather than a predetermined threshold. The advantage of this approach is that only those genotype combinations that are determined to be statistically significant are considered in the MDR analysis. We use two simulation studies to demonstrate that this approach will increase the success rate of MDR when there are only a few genotype combinations that are significantly associated with case-control status. We show that there is no loss of success rate when this is not the case. We then apply the RMDR method to the detection of gene-gene interactions in genotype data from a population-based study of bladder cancer in New Hampshire. PMID:21091664

COMMD1 is linked to the WASH complex and regulates endosomal trafficking of the copper transporter ATP7A

PubMed Central

Phillips-Krawczak, Christine A.; Singla, Amika; Starokadomskyy, Petro; Deng, Zhihui; Osborne, Douglas G.; Li, Haiying; Dick, Christopher J.; Gomez, Timothy S.; Koenecke, Megan; Zhang, Jin-San; Dai, Haiming; Sifuentes-Dominguez, Luis F.; Geng, Linda N.; Kaufmann, Scott H.; Hein, Marco Y.; Wallis, Mathew; McGaughran, Julie; Gecz, Jozef; van de Sluis, Bart; Billadeau, Daniel D.; Burstein, Ezra

2015-01-01

COMMD1 deficiency results in defective copper homeostasis, but the mechanism for this has remained elusive. Here we report that COMMD1 is directly linked to early endosomes through its interaction with a protein complex containing CCDC22, CCDC93, and C16orf62. This COMMD/CCDC22/CCDC93 (CCC) complex interacts with the multisubunit WASH complex, an evolutionarily conserved system, which is required for endosomal deposition of F-actin and cargo trafficking in conjunction with the retromer. Interactions between the WASH complex subunit FAM21, and the carboxyl-terminal ends of CCDC22 and CCDC93 are responsible for CCC complex recruitment to endosomes. We show that depletion of CCC complex components leads to lack of copper-dependent movement of the copper transporter ATP7A from endosomes, resulting in intracellular copper accumulation and modest alterations in copper homeostasis in humans with CCDC22 mutations. This work provides a mechanistic explanation for the role of COMMD1 in copper homeostasis and uncovers additional genes involved in the regulation of copper transporter recycling. PMID:25355947

Oxidative stress/damage induces multimerization and interaction of Fanconi anemia proteins.

PubMed

Park, Su-Jung; Ciccone, Samantha L M; Beck, Brian D; Hwang, Byounghoon; Freie, Brian; Clapp, D Wade; Lee, Suk-Hee

2004-07-16

Fanconi anemia (FANC) is a heterogeneous genetic disorder characterized by a hypersensitivity to DNA-damaging agents, chromosomal instability, and defective DNA repair. Eight FANC genes have been identified so far, and five of them (FANCA, -C, -E, -F, and -G) assemble in a multinuclear complex and function at least in part in a complex to activate FANCD2 by monoubiquitination. Here we show that FANCA and FANCG are redox-sensitive proteins that are multimerized and/or form a nuclear complex in response to oxidative stress/damage. Both FANCA and FANCG proteins exist as monomers under non-oxidizing conditions, whereas they become multimers following H2O2 treatment. Treatment of cells with oxidizing agent not only triggers the multimeric complex of FANCA and FANCG in vivo but also induces the interaction between FANCA and FANCG. N-Ethylmaleimide treatment abolishes multimerization and interaction of FANCA and FANCG in vitro. Taken together, our results lead us to conclude that FANCA and FANCG uniquely respond to oxidative damage by forming complex(es) via intermolecular disulfide linkage(s), which may be crucial in forming such complexes and in determining their function.

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.

Trichodiene production in a Trichoderma harzianum erg1-silenced strain provides evidence of the importance of the sterol biosynthetic pathway in inducing plant defense-related gene expression

USDA-ARS?s Scientific Manuscript database

Trichoderma species are often used as biocontrol agents against plant-pathogenic fungi. A complex molecular interaction occurs among the biocontrol agent, the antagonistic fungus, and the plant. Terpenes and sterols produced by the biocontrol fungus have been found to affect gene expression in both ...

AP1 Keeps Chromatin Poised for Action | Center for Cancer Research

Cancer.gov

The human genome harbors gene-encoding DNA, the blueprint for building proteins that regulate cellular function. Embedded across the genome, in non-coding regions, are DNA elements to which regulatory factors bind. The interaction of regulatory factors with DNA at these sites modifies gene expression to modulate cell activity. In cells, DNA exists in a complex with proteins

Glucosylated polyethylenimine as a tumor-targeting gene carrier.

PubMed

Park, In-Kyu; Cook, Seung-Eun; Kim, You-Kyoung; Kim, Hyun-Woo; Cho, Myung-Haing; Jeong, Hwan-Jeong; Kim, Eun-Mi; Nah, Jae-Woon; Bom, Hee-Seung; Cho, Chong-Su

2005-11-01

Glucosylated polyethylenimine (GPEI) was synthesized as a tumor-targeting gene carrier through facilitative glucose metabolism by tumor glucose transporter. Particle sizes of GPEI/DNA complex increased in proportion to glucose content of GPEI, whereas surface charge of the complex was not dependent on glucosylation, partially due to inefficient shielding of the short hydrophilic group introduced. GPEI with higher glucosylation (36 mol-%) had no cytotoxic effect on cells even at polymer concentrations higher than 200 microg/mL. Compared to unglucosylated PEI, glucosylation induced less than one-order decrease of transfection efficiency. Transfection of GPEI/DNA complex into tumor cells possibly occurred through specific interaction between glucose-related cell receptors and glucose moiety of GPEI. Gamma imaging technique revealed GPEI/DNA complex was distributed in liver, spleen, and tumors.

Transcriptional and posttranscriptional regulation of Bacillus sp. CDB3 arsenic-resistance operon ars1

PubMed Central

Yu, Xuefei; Zheng, Wei; Bhat, Somanath; Aquilina, J. Andrew

2015-01-01

Bacillus sp. CDB3 possesses a novel eight-gene ars cluster (ars1, arsRYCDATorf7orf8) with some unusual features in regard to expression regulation. This study demonstrated that the cluster is a single operon but can also produce a short three-gene arsRYC transcript. A hairpin structure formed by internal inverted repeats between arsC and arsD was shown to diminish the expression of the full operon, thereby probably acting as a transcription attenuator. A degradation product of the arsRYC transcript was also identified. Electrophoretic mobility shift analysis demonstrated that ArsR interacts with the ars1 promoter forming a protein-DNA complex that could be impaired by arsenite. However, no interaction was detected between ArsD and the ars1 promoter, suggesting that the CDB3 ArsD protein may not play a regulatory role. Compared to other ars gene clusters, regulation of the Bacillus sp. CDB3 ars1 operon is more complex. It represents another example of specific mRNA degradation in the transporter gene region and possibly the first case of attenuator-mediated regulation of ars operons. PMID:26355338

Chromatin Insulators: A Role in Nuclear Organization and Gene Expression

PubMed Central

Yang, Jingping; Corces, Victor G.

2011-01-01

Chromatin insulators are DNA-protein complexes with broad functions in nuclear biology. Based on the ability of insulator proteins to interact with each other, it was originally thought that insulators form loops that could constitute functional domains of co-regulated gene expression. Nevertheless, data from genome-wide localization studies indicate that insulator proteins can be present in intergenic regions as well as at the 5′, introns or 3′ of genes, suggesting a broader role in chromosome biology. Cells have developed mechanisms to control insulator activity by recruiting specialized proteins or by covalent modification of core components. Recent results suggest that insulators mediate intra- and inter-chromosomal interactions to affect transcription, imprinting and recombination. It is possible that these interactions set up cell-specific blueprints of nuclear organization that may contribute to the establishment of different patterns of gene expression during cell differentiation. As a consequence, disruption of insulator activity could result in the development of cancer or other disease states. PMID:21704228

The Fanconi anemia protein FANCF forms a nuclear complex with FANCA, FANCC and FANCG.

PubMed

de Winter, J P; van der Weel, L; de Groot, J; Stone, S; Waisfisz, Q; Arwert, F; Scheper, R J; Kruyt, F A; Hoatlin, M E; Joenje, H

2000-11-01

Fanconi anemia (FA) is a chromosomal instability syndrome associated with a strong predisposition to cancer, particularly acute myeloid leukemia and squamous cell carcinoma. At the cellular level, FA is characterized by spontaneous chromosomal breakage and a unique hypersensitivity to DNA cross-linking agents. Complementation analysis has indicated that at least seven distinct genes are involved in the pathogenesis of FA. Despite the identification of four of these genes (FANCA, FANCC, FANCF and FANCG), the nature of the 'FA pathway' has remained enigmatic, as the FA proteins lack sequence homologies or motifs that could point to a molecular function. To further define this pathway, we studied the subcellular localizations and mutual interactions of the FA proteins, including the recently identified FANCF protein, in human lymphoblasts. FANCF was found predominantly in the nucleus, where it complexes with FANCA, FANCC and FANCG. These interactions were detected in wild-type and FA-D lymphoblasts, but not in lymphoblasts of other FA complementation groups. This implies that each of the FA proteins, except FANCD, is required for these complexes to form. Similarly, we show that the interaction between FANCA and FANCC is restricted to wild-type and FA-D cells. Furthermore, we document the subcellular localization of FANCA and the FANCA/FANCG complex in all FA complementation groups. Our results, along with published data, culminate in a model in which a multi-protein FA complex serves a nuclear function to maintain genomic integrity.

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.

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

The egasyn gene affects the processing of oligosaccharides of lysosomal beta-glucuronidase in liver.

PubMed Central

Swank, R T; Pfister, K; Miller, D; Chapman, V

1986-01-01

The accumulation of the relatively large amounts of beta-glucuronidase in microsomal fractions of normal mice depends on formation of complexes with the protein egasyn. Unexpectedly, it was found that the egasyn gene also affects the processing of beta-glucuronidase, which is segregated to lysosomes. In egasyn-positive mice lysosomal beta-glucuronidase from liver has a mean pI of 5.9 with a minor proportion at pI 5.4, whereas in egasyn-negative mice the proportion of the two lysosomal forms is reversed. Combined experiments measuring susceptibility to neuraminidase and to endoglycosidase H and specific binding to Ricinus communis lectin-agarose columns showed that the alterations in isoelectric point were associated with a decrease in complex oligosaccharides of lysosomal beta-glucuronidase in egasyn-positive mice. Since this alteration occurs not only in a congenic strain carrying the Eg0 gene but also in several other inbred strains that are homozygous for this gene, it is considered to be a genuine effect of the Eg gene rather than other genes that might regulate oligosaccharide processing. Also, the alteration is likely to be a result of direct physical interaction of the egasyn protein and lysosomal beta-glucuronidase, since a second lysosomal enzyme, beta-galactosidase, which does not form complexes with egasyn, is unaffected. The results suggest a model in which egasyn not only causes accumulation of beta-glucuronidase in the microsomal compartment but also acts upon the precursor to lysosomal beta-glucuronidase to alter its interaction with trans-Golgi-apparatus processing enzymes. Images Fig. 1. Fig. 2. Fig. 3. Fig. 4. Fig. 6. Fig. 7. Fig. 8. PMID:3101673

Hidden state prediction: a modification of classic ancestral state reconstruction algorithms helps unravel complex symbioses

PubMed Central

Zaneveld, Jesse R. R.; Thurber, Rebecca L. V.

2014-01-01

Complex symbioses between animal or plant hosts and their associated microbiotas can involve thousands of species and millions of genes. Because of the number of interacting partners, it is often impractical to study all organisms or genes in these host-microbe symbioses individually. Yet new phylogenetic predictive methods can use the wealth of accumulated data on diverse model organisms to make inferences into the properties of less well-studied species and gene families. Predictive functional profiling methods use evolutionary models based on the properties of studied relatives to put bounds on the likely characteristics of an organism or gene that has not yet been studied in detail. These techniques have been applied to predict diverse features of host-associated microbial communities ranging from the enzymatic function of uncharacterized genes to the gene content of uncultured microorganisms. We consider these phylogenetically informed predictive techniques from disparate fields as examples of a general class of algorithms for Hidden State Prediction (HSP), and argue that HSP methods have broad value in predicting organismal traits in a variety of contexts, including the study of complex host-microbe symbioses. PMID:25202302

Bacillus subtilis glutamine synthetase regulates its own synthesis by acting as a chaperone to stabilize GlnR-DNA complexes.

PubMed

Fisher, Susan H; Wray, Lewis V

2008-01-22

The Bacillus subtilis GlnR repressor controls gene expression in response to nitrogen availability. Because all GlnR-regulated genes are expressed constitutively in mutants lacking glutamine synthetase (GS), GS is required for repression by GlnR. Feedback-inhibited GS (FBI-GS) was shown to activate GlnR DNA binding with an in vitro electophoretic mobility shift assay (EMSA). The activation of GlnR DNA binding by GS in these experiments depended on the feedback inhibitor glutamine and did not occur with mutant GS proteins defective in regulating GlnR activity in vivo. Although stable GS-GlnR-DNA ternary complexes were not observed in the EMSA experiments, cross-linking experiments showed that a protein-protein interaction occurs between GlnR and FBI-GS. This interaction was reduced in the absence of the feedback inhibitor glutamine and with mutant GS proteins. Because FBI-GS significantly reduced the dissociation rate of the GlnR-DNA complexes, the stability of these complexes is enhanced by FBI-GS. These results argue that FBI-GS acts as a chaperone that activates GlnR DNA binding through a transient protein-protein interaction that stabilizes GlnR-DNA complexes. GS was shown to control the activity of the B. subtilis nitrogen transcription factor TnrA by forming a stable complex between FBI-GS and TnrA that inhibits TnrA DNA binding. Thus, B. subtilis GS is an enzyme with dual catalytic and regulatory functions that uses distinct mechanisms to control the activity of two different transcription factors.

The nuclear lamina and heterochromatin: a complex relationship.

PubMed

Bank, Erin M; Gruenbaum, Yosef

2011-12-01

In metazoan cells, the heterochromatin is generally localized at the nuclear periphery, whereas active genes are preferentially found in the nuclear interior. In the present paper, we review current evidence showing that components of the nuclear lamina interact directly with heterochromatin, which implicates the nuclear lamina in a mechanism of specific gene retention at the nuclear periphery and release to the nuclear interior upon gene activation. We also discuss recent data showing that mutations in lamin proteins affect gene positioning and expression, providing a potential mechanism for how these mutations lead to tissue-specific diseases.

Xanthomonas TAL effectors hijack host basal transcription factor IIA α and γ subunits for invasion.

PubMed

Ma, Ling; Wang, Qiang; Yuan, Meng; Zou, Tingting; Yin, Ping; Wang, Shiping

2018-02-05

The Xanthomonas genus includes Gram-negative plant-pathogenic bacteria, which infect a broad range of crops and wild plant species, cause symptoms with leaf blights, streaks, spots, stripes, necrosis, wilt, cankers and gummosis on leaves, stems and fruits in a wide variety of plants via injecting their effector proteins into the host cell during infection. Among these virulent effectors, transcription activator-like effectors (TALEs) interact with the γ subunit of host transcription factor IIA (TFIIAγ) to activate the transcription of host disease susceptibility genes. Functional TFIIA is a ternary complex comprising α, β and γ subunits. However, whether TALEs recruit TFIIAα, TFIIAβ, or both remains unknown. The underlying molecular mechanisms by which TALEs mediate host susceptibility gene activation require full elucidation. Here, we show that TALEs interact with the α+γ binary subcomplex but not the α+β+γ ternary complex of rice TFIIA (holo-OsTFIIA). The transcription factor binding (TFB) regions of TALEs, which are highly conserved in Xanthomonas species, have a dominant role in these interactions. Furthermore, the interaction between TALEs and the α+γ complex exhibits robust DNA binding activity in vitro. These results collectively demonstrate that TALE-carrying pathogens hijack the host basal transcription factors TFIIAα and TFIIAγ, but not TFIIAβ, to enhance host susceptibility during pathogen infection. The uncovered mechanism widens new insights on host-microbe interaction and provide an applicable strategy to breed high-resistance crop varieties. Copyright © 2018 Elsevier Inc. All rights reserved.

Complex network theory for the identification and assessment of candidate protein targets.

PubMed

McGarry, Ken; McDonald, Sharon

2018-06-01

In this work we use complex network theory to provide a statistical model of the connectivity patterns of human proteins and their interaction partners. Our intention is to identify important proteins that may be predisposed to be potential candidates as drug targets for therapeutic interventions. Target proteins usually have more interaction partners than non-target proteins, but there are no hard-and-fast rules for defining the actual number of interactions. We devise a statistical measure for identifying hub proteins, we score our target proteins with gene ontology annotations. The important druggable protein targets are likely to have similar biological functions that can be assessed for their potential therapeutic value. Our system provides a statistical analysis of the local and distant neighborhood protein interactions of the potential targets using complex network measures. This approach builds a more accurate model of drug-to-target activity and therefore the likely impact on treating diseases. We integrate high quality protein interaction data from the HINT database and disease associated proteins from the DrugTarget database. Other sources include biological knowledge from Gene Ontology and drug information from DrugBank. The problem is a very challenging one since the data is highly imbalanced between target proteins and the more numerous nontargets. We use undersampling on the training data and build Random Forest classifier models which are used to identify previously unclassified target proteins. We validate and corroborate these findings from the available literature. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

PubMed

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

2015-11-01

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

Analysis of gene expression profile microarray data in complex regional pain syndrome.

PubMed

Tan, Wulin; Song, Yiyan; Mo, Chengqiang; Jiang, Shuangjian; Wang, Zhongxing

2017-09-01

The aim of the present study was to predict key genes and proteins associated with complex regional pain syndrome (CRPS) using bioinformatics analysis. The gene expression profiling microarray data, GSE47603, which included peripheral blood samples from 4 patients with CRPS and 5 healthy controls, was obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in CRPS patients compared with healthy controls were identified using the GEO2R online tool. Functional enrichment analysis was then performed using The Database for Annotation Visualization and Integrated Discovery online tool. Protein‑protein interaction (PPI) network analysis was subsequently performed using Search Tool for the Retrieval of Interaction Genes database and analyzed with Cytoscape software. A total of 257 DEGs were identified, including 243 upregulated genes and 14 downregulated ones. Genes in the human leukocyte antigen (HLA) family were most significantly differentially expressed. Enrichment analysis demonstrated that signaling pathways, including immune response, cell motion, adhesion and angiogenesis were associated with CRPS. PPI network analysis revealed that key genes, including early region 1A binding protein p300 (EP300), CREB‑binding protein (CREBBP), signal transducer and activator of transcription (STAT)3, STAT5A and integrin α M were associated with CRPS. The results suggest that the immune response may therefore serve an important role in CRPS development. In addition, genes in the HLA family, such as HLA‑DQB1 and HLA‑DRB1, may present potential biomarkers for the diagnosis of CRPS. Furthermore, EP300, its paralog CREBBP, and the STAT family genes, STAT3 and STAT5 may be important in the development of CRPS.

Prioritization of Epilepsy Associated Candidate Genes by Convergent Analysis

PubMed Central

Jia, Peilin; Ewers, Jeffrey M.; Zhao, Zhongming

2011-01-01

Background Epilepsy is a severe neurological disorder affecting a large number of individuals, yet the underlying genetic risk factors for epilepsy remain unclear. Recent studies have revealed several recurrent copy number variations (CNVs) that are more likely to be associated with epilepsy. The responsible gene(s) within these regions have yet to be definitively linked to the disorder, and the implications of their interactions are not fully understood. Identification of these genes may contribute to a better pathological understanding of epilepsy, and serve to implicate novel therapeutic targets for further research. Methodology/Principal Findings In this study, we examined genes within heterozygous deletion regions identified in a recent large-scale study, encompassing a diverse spectrum of epileptic syndromes. By integrating additional protein-protein interaction data, we constructed subnetworks for these CNV-region genes and also those previously studied for epilepsy. We observed 20 genes common to both networks, primarily concentrated within a small molecular network populated by GABA receptor, BDNF/MAPK signaling, and estrogen receptor genes. From among the hundreds of genes in the initial networks, these were designated by convergent evidence for their likely association with epilepsy. Importantly, the identified molecular network was found to contain complex interrelationships, providing further insight into epilepsy's underlying pathology. We further performed pathway enrichment and crosstalk analysis and revealed a functional map which indicates the significant enrichment of closely related neurological, immune, and kinase regulatory pathways. Conclusions/Significance The convergent framework we proposed here provides a unique and powerful approach to screening and identifying promising disease genes out of typically hundreds to thousands of genes in disease-related CNV-regions. Our network and pathway analysis provides important implications for the underlying molecular mechanisms for epilepsy. The strategy can be applied for the study of other complex diseases. PMID:21390307

Prioritization of epilepsy associated candidate genes by convergent analysis.

PubMed

Jia, Peilin; Ewers, Jeffrey M; Zhao, Zhongming

2011-02-24

Epilepsy is a severe neurological disorder affecting a large number of individuals, yet the underlying genetic risk factors for epilepsy remain unclear. Recent studies have revealed several recurrent copy number variations (CNVs) that are more likely to be associated with epilepsy. The responsible gene(s) within these regions have yet to be definitively linked to the disorder, and the implications of their interactions are not fully understood. Identification of these genes may contribute to a better pathological understanding of epilepsy, and serve to implicate novel therapeutic targets for further research. In this study, we examined genes within heterozygous deletion regions identified in a recent large-scale study, encompassing a diverse spectrum of epileptic syndromes. By integrating additional protein-protein interaction data, we constructed subnetworks for these CNV-region genes and also those previously studied for epilepsy. We observed 20 genes common to both networks, primarily concentrated within a small molecular network populated by GABA receptor, BDNF/MAPK signaling, and estrogen receptor genes. From among the hundreds of genes in the initial networks, these were designated by convergent evidence for their likely association with epilepsy. Importantly, the identified molecular network was found to contain complex interrelationships, providing further insight into epilepsy's underlying pathology. We further performed pathway enrichment and crosstalk analysis and revealed a functional map which indicates the significant enrichment of closely related neurological, immune, and kinase regulatory pathways. The convergent framework we proposed here provides a unique and powerful approach to screening and identifying promising disease genes out of typically hundreds to thousands of genes in disease-related CNV-regions. Our network and pathway analysis provides important implications for the underlying molecular mechanisms for epilepsy. The strategy can be applied for the study of other complex diseases.

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

PubMed

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

2009-09-01

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

General and craniofacial development are complex adaptive processes influenced by diversity.

PubMed

Brook, A H; O'Donnell, M Brook; Hone, A; Hart, E; Hughes, T E; Smith, R N; Townsend, G C

2014-06-01

Complex systems are present in such diverse areas as social systems, economies, ecosystems and biology and, therefore, are highly relevant to dental research, education and practice. A Complex Adaptive System in biological development is a dynamic process in which, from interacting components at a lower level, higher level phenomena and structures emerge. Diversity makes substantial contributions to the performance of complex adaptive systems. It enhances the robustness of the process, allowing multiple responses to external stimuli as well as internal changes. From diversity comes variation in outcome and the possibility of major change; outliers in the distribution enhance the tipping points. The development of the dentition is a valuable, accessible model with extensive and reliable databases for investigating the role of complex adaptive systems in craniofacial and general development. The general characteristics of such systems are seen during tooth development: self-organization; bottom-up emergence; multitasking; self-adaptation; variation; tipping points; critical phases; and robustness. Dental findings are compatible with the Random Network Model, the Threshold Model and also with the Scale Free Network Model which has a Power Law distribution. In addition, dental development shows the characteristics of Modularity and Clustering to form Hierarchical Networks. The interactions between the genes (nodes) demonstrate Small World phenomena, Subgraph Motifs and Gene Regulatory Networks. Genetic mechanisms are involved in the creation and evolution of variation during development. The genetic factors interact with epigenetic and environmental factors at the molecular level and form complex networks within the cells. From these interactions emerge the higher level tissues, tooth germs and mineralized teeth. Approaching development in this way allows investigation of why there can be variations in phenotypes from identical genotypes; the phenotype is the outcome of perturbations in the cellular systems and networks, as well as of the genotype. Understanding and applying complexity theory will bring about substantial advances not only in dental research and education but also in the organization and delivery of oral health care. © 2014 Australian Dental Association.

Dissecting social cell biology and tumors using Drosophila genetics.

PubMed

Pastor-Pareja, José Carlos; Xu, Tian

2013-01-01

Cancer was seen for a long time as a strictly cell-autonomous process in which oncogenes and tumor-suppressor mutations drive clonal cell expansions. Research in the past decade, however, paints a more integrative picture of communication and interplay between neighboring cells in tissues. It is increasingly clear as well that tumors, far from being homogenous lumps of cells, consist of different cell types that function together as complex tissue-level communities. The repertoire of interactive cell behaviors and the quantity of cellular players involved call for a social cell biology that investigates these interactions. Research into this social cell biology is critical for understanding development of normal and tumoral tissues. Such complex social cell biology interactions can be parsed in Drosophila. Techniques in Drosophila for analysis of gene function and clonal behavior allow us to generate tumors and dissect their complex interactive biology with cellular resolution. Here, we review recent Drosophila research aimed at understanding tissue-level biology and social cell interactions in tumors, highlighting the principles these studies reveal.

TTG2 controls the developmental regulation of seed coat tannins in Arabidopsis by regulating vacuolar transport steps in the proanthocyanidin pathway.

PubMed

Gonzalez, Antonio; Brown, Matthew; Hatlestad, Greg; Akhavan, Neda; Smith, Tyler; Hembd, Austin; Moore, Joshua; Montes, David; Mosley, Trenell; Resendez, Juan; Nguyen, Huy; Wilson, Lyndsey; Campbell, Annabelle; Sudarshan, Duncan; Lloyd, Alan

2016-11-01

The brown color of Arabidopsis seeds is caused by the deposition of proanthocyanidins (PAs or condensed tannins) in their inner testa layer. A transcription factor complex consisting of TT2, TT8 and TTG1 controls expression of PA biosynthetic genes, just as similar TTG1-dependent complexes have been shown to control flavonoid pigment pathway gene expression in general. However, PA synthesis is controlled by at least one other gene. TTG2 mutants lack the pigmentation found in wild-type seeds, but produce other flavonoid compounds, such as anthocyanins in the shoot, suggesting that TTG2 regulates genes in the PA biosynthetic branch of the flavonoid pathway. We analyzed the expression of PA biosynthetic genes within the developing seeds of ttg2-1 and wild-type plants for potential TTG2 regulatory targets. We found that expression of TT12, encoding a MATE type transporter, is dependent on TTG2 and that TTG2 can bind to the upstream regulatory region of TT12 suggesting that TTG2 directly regulates TT12. Ectopic expression of TT12 in ttg2-1 plants partially restores seed coat pigmentation. Moreover, we show that TTG2 regulation of TT12 is dependent on TTG1 and that TTG1 and TTG2 physically interact. The observation that TTG1 interacts with TTG2, a WRKY type transcription factor, proposes the existence of a novel TTG1-containing complex, and an addendum to the existing paradigm of flavonoid pathway regulation. Copyright © 2016 Elsevier Inc. All rights reserved.

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

Testing for gene-environment interaction under exposure misspecification.

PubMed

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

2017-11-09

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

ATAD3 proteins: brokers of a mitochondria-endoplasmic reticulum connection in mammalian cells.

PubMed

Baudier, Jacques

2018-05-01

In yeast, a sequence of physical and genetic interactions termed the endoplasmic reticulum (ER)-mitochondria organizing network (ERMIONE) controls mitochondria-ER interactions and mitochondrial biogenesis. Several functions that characterize ERMIONE complexes are conserved in mammalian cells, suggesting that a similar tethering complex must exist in metazoans. Recent studies have identified a new family of nuclear-encoded ATPases associated with diverse cellular activities (AAA+-ATPase) mitochondrial membrane proteins specific to multicellular eukaryotes, called the ATPase family AAA domain-containing protein 3 (ATAD3) proteins (ATAD3A and ATAD3B). These proteins are crucial for normal mitochondrial-ER interactions and lie at the heart of processes underlying mitochondrial biogenesis. ATAD3A orthologues have been studied in flies, worms, and mammals, highlighting the widespread importance of this gene during embryonic development and in adulthood. ATAD3A is a downstream effector of target of rapamycin (TOR) signalling in Drosophila and exhibits typical features of proteins from the ERMIONE-like complex in metazoans. In humans, mutations in the ATAD3A gene represent a new link between altered mitochondrial-ER interaction and recognizable neurological syndromes. The primate-specific ATAD3B protein is a biomarker of pluripotent embryonic stem cells. Through negative regulation of ATAD3A function, ATAD3B supports mitochondrial stemness properties. © 2017 Cambridge Philosophical Society.

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

PubMed

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

2017-07-28

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

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

PubMed

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

2018-02-10

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

The molecular dynamics of long noncoding RNA control of transcription in PTEN and its pseudogene

PubMed Central

Lister, Nicholas; Shevchenko, Galina; Walshe, James L.; Groen, Jessica; Johnsson, Per; Vidarsdóttir, Linda; Grander, Dan; Ataide, Sandro F.; Morris, Kevin V.

2017-01-01

RNA has been found to interact with chromatin and modulate gene transcription. In human cells, little is known about how long noncoding RNAs (lncRNAs) interact with target loci in the context of chromatin. We find here, using the phosphatase and tensin homolog (PTEN) pseudogene as a model system, that antisense lncRNAs interact first with a 5′ UTR-containing promoter-spanning transcript, which is then followed by the recruitment of DNA methyltransferase 3a (DNMT3a), ultimately resulting in the transcriptional and epigenetic control of gene expression. Moreover, we find that the lncRNA and promoter-spanning transcript interaction are based on a combination of structural and sequence components of the antisense lncRNA. These observations suggest, on the basis of this one example, that evolutionary pressures may be placed on RNA structure more so than sequence conservation. Collectively, the observations presented here suggest a much more complex and vibrant RNA regulatory world may be operative in the regulation of gene expression. PMID:28847966

Convergent roles of de novo mutations and common variants in schizophrenia in tissue-specific and spatiotemporal co-expression network.

PubMed

Jia, Peilin; Chen, Xiangning; Fanous, Ayman H; Zhao, Zhongming

2018-05-24

Genetic components susceptible to complex disease such as schizophrenia include a wide spectrum of variants, including common variants (CVs) and de novo mutations (DNMs). Although CVs and DNMs differ by origin, it remains elusive whether and how they interact at the gene, pathway, and network levels that leads to the disease. In this work, we characterized the genes harboring schizophrenia-associated CVs (CVgenes) and the genes harboring DNMs (DNMgenes) using measures from network, tissue-specific expression profile, and spatiotemporal brain expression profile. We developed an algorithm to link the DNMgenes and CVgenes in spatiotemporal brain co-expression networks. DNMgenes tended to have central roles in the human protein-protein interaction (PPI) network, evidenced in their high degree and high betweenness values. DNMgenes and CVgenes connected with each other significantly more often than with other genes in the networks. However, only CVgenes remained significantly connected after adjusting for their degree. In our gene co-expression PPI network, we found DNMgenes and CVgenes connected in a tissue-specific fashion, and such a pattern was similar to that in GTEx brain but not in other GTEx tissues. Importantly, DNMgene-CVgene subnetworks were enriched with pathways of chromatin remodeling, MHC protein complex binding, and neurotransmitter activities. In summary, our results unveiled that both DNMgenes and CVgenes contributed to a core set of biologically important pathways and networks, and their interactions may attribute to the risk for schizophrenia. Our results also suggested a stronger biological effect of DNMgenes than CVgenes in schizophrenia.

WRI1-1, ABI5, NF-YA3 and NF-YC2 increase oil biosynthesis in coordination with hormonal signaling during fruit development in oil palm.

PubMed

Yeap, Wan-Chin; Lee, Fong-Chin; Shabari Shan, Dilip Kumar; Musa, Hamidah; Appleton, David Ross; Kulaveerasingam, Harikrishna

2017-07-01

The oil biosynthesis pathway must be tightly controlled to maximize oil yield. Oil palm accumulates exceptionally high oil content in its mesocarp, suggesting the existence of a unique fruit-specific fatty acid metabolism transcriptional network. We report the complex fruit-specific network of transcription factors responsible for modulation of oil biosynthesis genes in oil palm mesocarp. Transcriptional activation of EgWRI1-1 encoding a key master regulator that activates expression of oil biosynthesis genes, is activated by three ABA-responsive transcription factors, EgNF-YA3, EgNF-YC2 and EgABI5. Overexpression of EgWRI1-1 and its activators in Arabidopsis accelerated flowering, increased seed size and oil content, and altered expression levels of oil biosynthesis genes. Protein-protein interaction experiments demonstrated that EgNF-YA3 interacts directly with EgWRI1-1, forming a transcription complex with EgNF-YC2 and EgABI5 to modulate transcription of oil biosynthesis pathway genes. Furthermore, EgABI5 acts downstream of EgWRKY40, a repressor that interacts with EgWRKY2 to inhibit the transcription of oil biosynthesis genes. We showed that expression of these activators and repressors in oil biosynthesis can be induced by phytohormones coordinating fruit development in oil palm. We propose a model highlighting a hormone signaling network coordinating fruit development and fatty acid biosynthesis. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Combining Shapley value and statistics to the analysis of gene expression data in children exposed to air pollution

PubMed Central

Moretti, Stefano; van Leeuwen, Danitsja; Gmuender, Hans; Bonassi, Stefano; van Delft, Joost; Kleinjans, Jos; Patrone, Fioravante; Merlo, Domenico Franco

2008-01-01

Background In gene expression analysis, statistical tests for differential gene expression provide lists of candidate genes having, individually, a sufficiently low p-value. However, the interpretation of each single p-value within complex systems involving several interacting genes is problematic. In parallel, in the last sixty years, game theory has been applied to political and social problems to assess the power of interacting agents in forcing a decision and, more recently, to represent the relevance of genes in response to certain conditions. Results In this paper we introduce a Bootstrap procedure to test the null hypothesis that each gene has the same relevance between two conditions, where the relevance is represented by the Shapley value of a particular coalitional game defined on a microarray data-set. This method, which is called Comparative Analysis of Shapley value (shortly, CASh), is applied to data concerning the gene expression in children differentially exposed to air pollution. The results provided by CASh are compared with the results from a parametric statistical test for testing differential gene expression. Both lists of genes provided by CASh and t-test are informative enough to discriminate exposed subjects on the basis of their gene expression profiles. While many genes are selected in common by CASh and the parametric test, it turns out that the biological interpretation of the differences between these two selections is more interesting, suggesting a different interpretation of the main biological pathways in gene expression regulation for exposed individuals. A simulation study suggests that CASh offers more power than t-test for the detection of differential gene expression variability. Conclusion CASh is successfully applied to gene expression analysis of a data-set where the joint expression behavior of genes may be critical to characterize the expression response to air pollution. We demonstrate a synergistic effect between coalitional games and statistics that resulted in a selection of genes with a potential impact in the regulation of complex pathways. PMID:18764936

Symbiosis within Symbiosis: Evolving Nitrogen-Fixing Legume Symbionts.

PubMed

Remigi, Philippe; Zhu, Jun; Young, J Peter W; Masson-Boivin, Catherine

2016-01-01

Bacterial accessory genes are genomic symbionts with an evolutionary history and future that is different from that of their hosts. Packages of accessory genes move from strain to strain and confer important adaptations, such as interaction with eukaryotes. The ability to fix nitrogen with legumes is a remarkable example of a complex trait spread by horizontal transfer of a few key symbiotic genes, converting soil bacteria into legume symbionts. Rhizobia belong to hundreds of species restricted to a dozen genera of the Alphaproteobacteria and Betaproteobacteria, suggesting infrequent successful transfer between genera but frequent successful transfer within genera. Here we review the genetic and environmental conditions and selective forces that have shaped evolution of this complex symbiotic trait. Copyright © 2015 Elsevier Ltd. All rights reserved.

Nonviral Vectors for Gene Delivery

NASA Astrophysics Data System (ADS)

Baoum, Abdulgader Ahmed

2011-12-01

The development of nonviral vectors for safe and efficient gene delivery has been gaining considerable attention recently. An ideal nonviral vector must protect the gene against degradation by nuclease in the extracellular matrix, internalize the plasma membrane, escape from the endosomal compartment, unpackage the gene at some point and have no detrimental effects. In comparison to viruses, nonviral vectors are relatively easy to synthesize, less immunogenic, low in cost, and have no limitation in the size of a gene that can be delivered. Significant progress has been made in the basic science and applications of various nonviral gene delivery vectors; however, the majority of nonviral approaches are still inefficient and often toxic. To this end, two nonviral gene delivery systems using either biodegradable poly(D,L-lactide- co-glycolide) (PLG) nanoparticles or cell penetrating peptide (CPP) complexes have been designed and studied using A549 human lung epithelial cells. PLG nanoparticles were optimized for gene delivery by varying particle surface chemistry using different coating materials that adsorb to the particle surface during formation. A variety of cationic coating materials were studied and compared to more conventional surfactants used for PLG nanoparticle fabrication. Nanoparticles (˜200 nm) efficiently encapsulated plasmids encoding for luciferase (80-90%) and slowly released the same for two weeks. After a delay, moderate levels of gene expression appeared at day 5 for certain positively charged PLG particles and gene expression was maintained for at least two weeks. In contrast, gene expression mediated by polyethyleneimine (PEI) ended at day 5. PLG particles were also significantly less cytotoxic than PEI suggesting the use of these vehicles for localized, sustained gene delivery to the pulmonary epithelium. On the other hand, a more simple method to synthesize 50-200 nm complexes capable of high transfection efficiency or high gene knockdown was also explored. Positively charged CPPs were complexed with pDNA or siRNA, which resulted in 'loose' (˜1 micron) particles. These were then condensed into small nanoparticles by using calcium, which formed "soft" crosslinks by interacting with both phosphates on nucleic acids and amines on CPPs. An optimal amount of CaCl2 produced stable, ˜100 nm complexes that exhibited higher transfection efficiency and gene silencing than PEI polyplexes. CPPs also displayed negligible cytotoxicity up to 5 mg/mL. Biophysical studies of the pDNA structure within complexes suggested that pDNA within CPP complexes (condensed with calcium) had similar structure, but enhanced thermal stability compared to PEI complexes. Thus, CPP complexes emerged as simple, attractive candidates for future studies on nonviral gene delivery in vivo.

Transcriptional Regulatory Network Analysis of MYB Transcription Factor Family Genes in Rice.

PubMed

Smita, Shuchi; Katiyar, Amit; Chinnusamy, Viswanathan; Pandey, Dev M; Bansal, Kailash C

2015-01-01

MYB transcription factor (TF) is one of the largest TF families and regulates defense responses to various stresses, hormone signaling as well as many metabolic and developmental processes in plants. Understanding these regulatory hierarchies of gene expression networks in response to developmental and environmental cues is a major challenge due to the complex interactions between the genetic elements. Correlation analyses are useful to unravel co-regulated gene pairs governing biological process as well as identification of new candidate hub genes in response to these complex processes. High throughput expression profiling data are highly useful for construction of co-expression networks. In the present study, we utilized transcriptome data for comprehensive regulatory network studies of MYB TFs by "top-down" and "guide-gene" approaches. More than 50% of OsMYBs were strongly correlated under 50 experimental conditions with 51 hub genes via "top-down" approach. Further, clusters were identified using Markov Clustering (MCL). To maximize the clustering performance, parameter evaluation of the MCL inflation score (I) was performed in terms of enriched GO categories by measuring F-score. Comparison of co-expressed cluster and clads analyzed from phylogenetic analysis signifies their evolutionarily conserved co-regulatory role. We utilized compendium of known interaction and biological role with Gene Ontology enrichment analysis to hypothesize function of coexpressed OsMYBs. In the other part, the transcriptional regulatory network analysis by "guide-gene" approach revealed 40 putative targets of 26 OsMYB TF hubs with high correlation value utilizing 815 microarray data. The putative targets with MYB-binding cis-elements enrichment in their promoter region, functional co-occurrence as well as nuclear localization supports our finding. Specially, enrichment of MYB binding regions involved in drought-inducibility implying their regulatory role in drought response in rice. Thus, the co-regulatory network analysis facilitated the identification of complex OsMYB regulatory networks, and candidate target regulon genes of selected guide MYB genes. The results contribute to the candidate gene screening, and experimentally testable hypotheses for potential regulatory MYB TFs, and their targets under stress conditions.

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

PubMed

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

2018-06-13

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

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

Natural changes in light interact with circadian regulation at promoters to control gene expression in cyanobacteria

PubMed Central

2017-01-01

The circadian clock interacts with other regulatory pathways to tune physiology to predictable daily changes and unexpected environmental fluctuations. However, the complexity of circadian clocks in higher organisms has prevented a clear understanding of how natural environmental conditions affect circadian clocks and their physiological outputs. Here, we dissect the interaction between circadian regulation and responses to fluctuating light in the cyanobacterium Synechococcus elongatus. We demonstrate that natural changes in light intensity substantially affect the expression of hundreds of circadian-clock-controlled genes, many of which are involved in key steps of metabolism. These changes in expression arise from circadian and light-responsive control of RNA polymerase recruitment to promoters by a network of transcription factors including RpaA and RpaB. Using phenomenological modeling constrained by our data, we reveal simple principles that underlie the small number of stereotyped responses of dusk circadian genes to changes in light. PMID:29239721

Chelerythrine down regulates expression of VEGFA, BCL2 and KRAS by arresting G-Quadruplex structures at their promoter regions.

PubMed

Jana, Jagannath; Mondal, Soma; Bhattacharjee, Payel; Sengupta, Pallabi; Roychowdhury, Tanaya; Saha, Pranay; Kundu, Pallob; Chatterjee, Subhrangsu

2017-01-19

A putative anticancer plant alkaloid, Chelerythrine binds to G-quadruplexes at promoters of VEGFA, BCL2 and KRAS genes and down regulates their expression. The association of Chelerythrine to G-quadruplex at the promoters of these oncogenes were monitored using UV absorption spectroscopy, fluorescence anisotropy, circular dichroism spectroscopy, CD melting, isothermal titration calorimetry, molecular dynamics simulation and quantitative RT-PCR technique. The pronounced hypochromism accompanied by red shifts in UV absorption spectroscopy in conjunction with ethidium bromide displacement assay indicates end stacking mode of interaction of Chelerythrine with the corresponding G-quadruplex structures. An increase in fluorescence anisotropy and CD melting temperature of Chelerythrine-quadruplex complex revealed the formation of stable Chelerythrine-quadruplex complex. Isothermal titration calorimetry data confirmed that Chelerythrine-quadruplex complex formation is thermodynamically favourable. Results of quantative RT-PCR experiment in combination with luciferase assay showed that Chelerythrine treatment to MCF7 breast cancer cells effectively down regulated transcript level of all three genes, suggesting that Chelerythrine efficiently binds to in cellulo quadruplex motifs. MD simulation provides the molecular picture showing interaction between Chelerythrine and G-quadruplex. Binding of Chelerythrine with BCL2, VEGFA and KRAS genes involved in evasion, angiogenesis and self sufficiency of cancer cells provides a new insight for the development of future therapeutics against cancer.

A potential targeting gene vector based on biotinylated polyethyleneimine/avidin bioconjugates.

PubMed

Zeng, Xuan; Sun, Yun-Xia; Zhang, Xian-Zheng; Cheng, Si-Xue; Zhuo, Ren-Xi

2009-08-01

To improve the gene delivery efficiency and safety of non-viral vector in liver cells, avidin, which exhibited good biocompatibility and remarkable accumulation in liver, was bioconjugated with biotinylated polyethylenimine to obtain a novel gene vector. Biotinylated polyethyleneimine/avidin bioconjugate (ABP) was synthesized through grafting biotin to high molecular weight branched polyethylenimine (PEI, 25 kDa) and then bioconjugating with avidin by the biotin-avidin interaction. Physiochemical characteristics of ABP/pDNA complexes were analyzed, and in vitro cytotoxicity and transfection of ABP were also evaluated in HepG2, Hela and 293 T cells by using 25 kDa PEI as the control. It was found that ABP was able to condense pDNA efficiently at N/P ratio of 4. The particle sizes of ABP/pDNA complexes were less than 220 nm, and the average surface charges were around 27 mV at the N/P ratio ranging from 2 to 60. Among three different cell lines, ABP and its DNA complexes demonstrated much lower cytotoxicity and higher transfection efficacy in HepG2 cells as compared with 25 kDa PEI. ABP presented higher transfection efficacy and safety in HepG2 cells due to the biocompatibility of avidin and the specific interactions between avidin and HepG2 cells.

Chelerythrine down regulates expression of VEGFA, BCL2 and KRAS by arresting G-Quadruplex structures at their promoter regions

NASA Astrophysics Data System (ADS)

Jana, Jagannath; Mondal, Soma; Bhattacharjee, Payel; Sengupta, Pallabi; Roychowdhury, Tanaya; Saha, Pranay; Kundu, Pallob; Chatterjee, Subhrangsu

2017-01-01

A putative anticancer plant alkaloid, Chelerythrine binds to G-quadruplexes at promoters of VEGFA, BCL2 and KRAS genes and down regulates their expression. The association of Chelerythrine to G-quadruplex at the promoters of these oncogenes were monitored using UV absorption spectroscopy, fluorescence anisotropy, circular dichroism spectroscopy, CD melting, isothermal titration calorimetry, molecular dynamics simulation and quantitative RT-PCR technique. The pronounced hypochromism accompanied by red shifts in UV absorption spectroscopy in conjunction with ethidium bromide displacement assay indicates end stacking mode of interaction of Chelerythrine with the corresponding G-quadruplex structures. An increase in fluorescence anisotropy and CD melting temperature of Chelerythrine-quadruplex complex revealed the formation of stable Chelerythrine-quadruplex complex. Isothermal titration calorimetry data confirmed that Chelerythrine-quadruplex complex formation is thermodynamically favourable. Results of quantative RT-PCR experiment in combination with luciferase assay showed that Chelerythrine treatment to MCF7 breast cancer cells effectively down regulated transcript level of all three genes, suggesting that Chelerythrine efficiently binds to in cellulo quadruplex motifs. MD simulation provides the molecular picture showing interaction between Chelerythrine and G-quadruplex. Binding of Chelerythrine with BCL2, VEGFA and KRAS genes involved in evasion, angiogenesis and self sufficiency of cancer cells provides a new insight for the development of future therapeutics against cancer.

Differential network entropy reveals cancer system hallmarks

PubMed Central

West, James; Bianconi, Ginestra; Severini, Simone; Teschendorff, Andrew E.

2012-01-01

The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network we here demonstrate that cancer cells are characterised by an increase in network entropy. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local network entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local correlation patterns. In particular, we find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in network entropy. These findings may have potential implications for identifying novel drug targets. PMID:23150773

AP1 Keeps Chromatin Poised for Action | Center for Cancer Research

Cancer.gov

The human genome harbors gene-encoding DNA, the blueprint for building proteins that regulate cellular function. Embedded across the genome, in non-coding regions, are DNA elements to which regulatory factors bind. The interaction of regulatory factors with DNA at these sites modifies gene expression to modulate cell activity. In cells, DNA exists in a complex with proteins called chromatin that compacts the DNA in the nucleus, strongly restricting access to DNA sequences. As a result, regulatory factors only interact with a small subset of their potential binding elements in a given cell to regulate genes. How factors recognize and select sites in chromatin across the genome is not well understood -- but several discoveries in CCR’s Laboratory of Receptor Biology and Gene Expression (LRBGE) have shed light on the mechanisms that direct factors to DNA.

RISC-Target Interaction: Cleavage and Translational Suppression

PubMed Central

van den Berg, Arjen; Mols, Johann; Han, Jiahuai

2008-01-01

Summary Small RNA molecules have been known and utilized to suppress gene expression for more than a decade. The discovery that these small RNA molecules are endogenously expressed in many organisms and have a critical role in controlling gene expression have led to the arising of a whole new field of research. Termed small interfering RNA (siRNA) or microRNA (miRNA) these ~22 nt RNA molecules have the capability to suppress gene expression through various mechanisms once they are incorporated in the multi-protein RNA-Induced Silencing Complex (RISC) and interact with their target mRNA. This review introduces siRNAs and microRNAs in a historical perspective and focuses on the key molecules in RISC, structural properties and mechanisms underlying the process of small RNA regulated post-transcriptional suppression of gene expression. PMID:18692607

Mutations in extracellular matrix genes NID1 and LAMC1 cause autosomal dominant Dandy-Walker malformation and occipital cephaloceles.

PubMed

Darbro, Benjamin W; Mahajan, Vinit B; Gakhar, Lokesh; Skeie, Jessica M; Campbell, Elizabeth; Wu, Shu; Bing, Xinyu; Millen, Kathleen J; Dobyns, William B; Kessler, John A; Jalali, Ali; Cremer, James; Segre, Alberto; Manak, J Robert; Aldinger, Kimerbly A; Suzuki, Satoshi; Natsume, Nagato; Ono, Maya; Hai, Huynh Dai; Viet, Le Thi; Loddo, Sara; Valente, Enza M; Bernardini, Laura; Ghonge, Nitin; Ferguson, Polly J; Bassuk, Alexander G

2013-08-01

We performed whole-exome sequencing of a family with autosomal dominant Dandy-Walker malformation and occipital cephaloceles and detected a mutation in the extracellular matrix (ECM) protein-encoding gene NID1. In a second family, protein interaction network analysis identified a mutation in LAMC1, which encodes a NID1-binding partner. Structural modeling of the NID1-LAMC1 complex demonstrated that each mutation disrupts the interaction. These findings implicate the ECM in the pathogenesis of Dandy-Walker spectrum disorders. © 2013 WILEY PERIODICALS, INC.

Finding gene-environment interactions for phobias.

PubMed

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

2008-03-01

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

Myogenin Recruits the Histone Chaperone Facilitates Chromatin Transcription (FACT) to Promote Nucleosome Disassembly at Muscle-specific Genes*

PubMed Central

Lolis, Alexandra A.; Londhe, Priya; Beggs, Benjamin C.; Byrum, Stephanie D.; Tackett, Alan J.; Davie, Judith K.

2013-01-01

Facilitates chromatin transcription (FACT) functions to reorganize nucleosomes by acting as a histone chaperone that destabilizes and restores nucleosomal structure. The FACT complex is composed of two subunits: SSRP1 and SPT16. We have discovered that myogenin interacts with the FACT complex. Transfection of FACT subunits with myogenin is highly stimulatory for endogenous muscle gene expression in 10T1/2 cells. We have also found that FACT subunits do not associate with differentiation-specific genes while C2C12 cells are proliferating but are recruited to muscle-specific genes as differentiation initiates and then dissociate as differentiation proceeds. The recruitment is dependent on myogenin, as knockdowns of myogenin show no recruitment of the FACT complex. These data suggest that FACT is involved in the early steps of gene activation through its histone chaperone activities that serve to open the chromatin structure and facilitate transcription. Consistent with this hypothesis, we find that nucleosomes are depleted at muscle-specific promoters upon differentiation and that this activity is dependent on the presence of FACT. Our results show that the FACT complex promotes myogenin-dependent transcription and suggest that FACT plays an important role in the establishment of the appropriate transcription profile in a differentiated muscle cell. PMID:23364797

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

NASA Astrophysics Data System (ADS)

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

2010-06-01

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

Astrocyte Elevated Gene 1 Interacts with Acetyltransferase p300 and c-Jun To Promote Tumor Aggressiveness

PubMed Central

Liu, Liping; Guan, Hongyu; Li, Yun; Ying, Zhe; Wu, Jueheng; Zhu, Xun; Song, Libing

2016-01-01

ABSTRACT Astrocyte elevated gene 1 (AEG-1) is an oncoprotein that strongly promotes the development and progression of cancers. However, the detailed underlying mechanisms through which AEG-1 enhances tumor development and progression remain to be determined. In this study, we identified c-Jun and p300 to be novel interacting partners of AEG-1 in gliomas. AEG-1 promoted c-Jun transcriptional activity by interacting with the c-Jun/p300 complex and inducing c-Jun acetylation. Furthermore, the AEG-1/c-Jun/p300 complex was found to bind the promoter of c-Jun downstream targeted genes, consequently establishing an acetylated chromatin state that favors transcriptional activation. Importantly, AEG-1/p300-mediated c-Jun acetylation resulted in the development of a more aggressive malignant phenotype in gliomas through a drastic increase in glioma cell proliferation and angiogenesis in vitro and in vivo. Consistently, the AEG-1 expression levels in clinical glioma specimens correlated with the status of c-Jun activation. Taken together, our results suggest that AEG-1 mediates a novel epigenetic mechanism that enhances c-Jun transcriptional activity to induce glioma progression and that AEG-1 might be a novel, potential target for the treatment of gliomas. PMID:27956703

Pathway analyses and understanding disease associations

PubMed Central

Liu, Yu; Chance, Mark R

2013-01-01

High throughput technologies have been applied to investigate the underlying mechanisms of complex diseases, identify disease-associations and help to improve treatment. However it is challenging to derive biological insight from conventional single gene based analysis of “omics” data from high throughput experiments due to sample and patient heterogeneity. To address these challenges, many novel pathway and network based approaches were developed to integrate various “omics” data, such as gene expression, copy number alteration, Genome Wide Association Studies, and interaction data. This review will cover recent methodological developments in pathway analysis for the detection of dysregulated interactions and disease-associated subnetworks, prioritization of candidate disease genes, and disease classifications. For each application, we will also discuss the associated challenges and potential future directions. PMID:24319650

Advances in asthma and allergy genetics in 2007.

PubMed

Vercelli, Donata

2008-08-01

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

Systems Biophysics of Gene Expression

PubMed Central

Vilar, Jose M.G.; Saiz, Leonor

2013-01-01

Gene expression is a process central to any form of life. It involves multiple temporal and functional scales that extend from specific protein-DNA interactions to the coordinated regulation of multiple genes in response to intracellular and extracellular changes. This diversity in scales poses fundamental challenges to the use of traditional approaches to fully understand even the simplest gene expression systems. Recent advances in computational systems biophysics have provided promising avenues to reliably integrate the molecular detail of biophysical process into the system behavior. Here, we review recent advances in the description of gene regulation as a system of biophysical processes that extend from specific protein-DNA interactions to the combinatorial assembly of nucleoprotein complexes. There is now basic mechanistic understanding on how promoters controlled by multiple, local and distal, DNA binding sites for transcription factors can actively control transcriptional noise, cell-to-cell variability, and other properties of gene regulation, including precision and flexibility of the transcriptional responses. PMID:23790365

Dynamic network reconstruction from gene expression data applied to immune response during bacterial infection.

PubMed

Guthke, Reinhard; Möller, Ulrich; Hoffmann, Martin; Thies, Frank; Töpfer, Susanne

2005-04-15

The immune response to bacterial infection represents a complex network of dynamic gene and protein interactions. We present an optimized reverse engineering strategy aimed at a reconstruction of this kind of interaction networks. The proposed approach is based on both microarray data and available biological knowledge. The main kinetics of the immune response were identified by fuzzy clustering of gene expression profiles (time series). The number of clusters was optimized using various evaluation criteria. For each cluster a representative gene with a high fuzzy-membership was chosen in accordance with available physiological knowledge. Then hypothetical network structures were identified by seeking systems of ordinary differential equations, whose simulated kinetics could fit the gene expression profiles of the cluster-representative genes. For the construction of hypothetical network structures singular value decomposition (SVD) based methods and a newly introduced heuristic Network Generation Method here were compared. It turned out that the proposed novel method could find sparser networks and gave better fits to the experimental data. Reinhard.Guthke@hki-jena.de.

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.

Molecular interactions of orthologues of floral homeotic proteins from the gymnosperm Gnetum gnemon provide a clue to the evolutionary origin of 'floral quartets'.

PubMed

Wang, Yong-Qiang; Melzer, Rainer; Theissen, Günter

2010-10-01

Several lines of evidence suggest that the identity of floral organs in angiosperms is specified by multimeric transcription factor complexes composed of MADS-domain proteins. These bind to specific cis-regulatory elements ('CArG-boxes') of their target genes involving DNA-loop formation, thus constituting 'floral quartets'. Gymnosperms, angiosperms' closest relatives, contain orthologues of floral homeotic genes, but when and how the interactions constituting floral quartets were established during evolution has remained unknown. We have comprehensively studied the dimerization and DNA-binding of several classes of MADS-domain proteins from the gymnosperm Gnetum gnemon. Determination of protein-protein and protein-DNA interactions by yeast two-hybrid, in vitro pull-down and electrophoretic mobility shift assays revealed complex patterns of homo- and heterodimerization among orthologues of floral homeotic class B, class C and class E proteins and B(sister) proteins. Using DNase I footprint assays we demonstrate that both orthologues of class B with C proteins, and orthologues of class C proteins alone, but not orthologues of class B proteins alone can loop DNA in floral quartet-like complexes. This is in contrast to class B and class C proteins from angiosperms, which require other factors such as class E floral homeotic proteins to 'glue' them together in multimeric complexes. Our findings suggest that the evolutionary origin of floral quartet formation is based on the interaction of different DNA-bound homodimers, does not depend on class E proteins, and predates the origin of angiosperms. © 2010 The Authors. Journal compilation © 2010 Blackwell Publishing Ltd.

From Biophysics to Evolutionary Genetics: Statistical Aspects of Gene Regulation

NASA Astrophysics Data System (ADS)

Lässig, Michael

Genomic functions often cannot be understood at the level of single genes but require the study of gene networks. This systems biology credo is nearly commonplace by now. Evidence comes from the comparative analysis of entire genomes: current estimates put, for example, the number of human genes at around 22,000, hardly more than the 14,000 of the fruit fly, and not even an order of magnitude higher than the 6,000 of baker's yeast. The complexity and diversity of higher animals, therefore, cannot be explained in terms of their gene numbers. If, however, a biological function requires the concerted action of several genes, and conversely, a gene takes part in several functional contexts, an organism may be defined less by its individual genes but by their interactions. The emerging picture of the genome as a strongly interacting system with many degrees of freedom brings new challenges for experiment and theory, many of which are of a statistical nature. And indeed, this picture continues to make the subject attractive to a growing number of statistical physicists.

RNA editing of microRNA prevents RNA-induced silencing complex recognition of target mRNA.

PubMed

Cui, Yalei; Huang, Tianzhi; Zhang, Xiaobo

2015-12-01

MicroRNAs (miRNAs) integrate with Argonaut (Ago) to create the RNA-induced silencing complex, and regulate gene expression by silencing target mRNAs. RNA editing of miRNA may affect miRNA processing, assembly of the Ago complex and target mRNA binding. However, the function of edited miRNA, assembled within the Ago complex, has not been extensively investigated. In this study, sequence analysis of the Ago complex of Marsupenaeus japonicus shrimp infected with white spot syndrome virus (WSSV) revealed that host ADAR (adenosine deaminase acting on RNA) catalysed A-to-I RNA editing of a viral miRNA (WSSV-miR-N12) at the +16 site. This editing of the non-seed sequence did not affect association of the edited miRNA with the Ago protein, but inhibited interaction between the miRNA and its target gene (wsv399). The WSSV early gene wsv399 inhibited WSSV infection. As a result, the RNA editing of miRNA caused virus latency. Our results highlight a novel example of miRNA editing in the miRNA-induced silencing complex. © 2015 The Authors.

Homo sapiens exhibit a distinct pattern of CNV genes regulation: an important role of miRNAs and SNPs in expression plasticity.

PubMed

Dweep, Harsh; Kubikova, Nada; Gretz, Norbert; Voskarides, Konstantinos; Felekkis, Kyriacos

2015-07-16

Gene expression regulation is a complex and highly organized process involving a variety of genomic factors. It is widely accepted that differences in gene expression can contribute to the phenotypic variability between species, and that their interpretation can aid in the understanding of the physiologic variability. CNVs and miRNAs are two major players in the regulation of expression plasticity and may be responsible for the unique phenotypic characteristics observed in different lineages. We have previously demonstrated that a close interaction between these two genomic elements may have contributed to the regulation of gene expression during evolution. This work presents the molecular interactions between CNV and non CNV genes with miRNAs and other genomic elements in eight different species. A comprehensive analysis of these interactions indicates a unique nature of human CNV genes regulation as compared to other species. By using genes with short 3' UTR that abolish the "canonical" miRNA-dependent regulation, as a model, we demonstrate a distinct and tight regulation of human genes that might explain some of the unique features of human physiology. In addition, comparison of gene expression regulation between species indicated that there is a significant difference between humans and mice possibly questioning the effectiveness of the latest as experimental models of human diseases.

Homo sapiens exhibit a distinct pattern of CNV genes regulation: an important role of miRNAs and SNPs in expression plasticity

PubMed Central

Dweep, Harsh; Kubikova, Nada; Gretz, Norbert; Voskarides, Konstantinos; Felekkis, Kyriacos

2015-01-01

Gene expression regulation is a complex and highly organized process involving a variety of genomic factors. It is widely accepted that differences in gene expression can contribute to the phenotypic variability between species, and that their interpretation can aid in the understanding of the physiologic variability. CNVs and miRNAs are two major players in the regulation of expression plasticity and may be responsible for the unique phenotypic characteristics observed in different lineages. We have previously demonstrated that a close interaction between these two genomic elements may have contributed to the regulation of gene expression during evolution. This work presents the molecular interactions between CNV and non CNV genes with miRNAs and other genomic elements in eight different species. A comprehensive analysis of these interactions indicates a unique nature of human CNV genes regulation as compared to other species. By using genes with short 3′ UTR that abolish the “canonical” miRNA-dependent regulation, as a model, we demonstrate a distinct and tight regulation of human genes that might explain some of the unique features of human physiology. In addition, comparison of gene expression regulation between species indicated that there is a significant difference between humans and mice possibly questioning the effectiveness of the latest as experimental models of human diseases. PMID:26178010

Epistasis and Its Implications for Personal Genetics

PubMed Central

Moore, Jason H.; Williams, Scott M.

2009-01-01

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

Epistasis and its implications for personal genetics.

PubMed

Moore, Jason H; Williams, Scott M

2009-09-01

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

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

Transcription regulation by the Mediator complex.

PubMed

Soutourina, Julie

2018-04-01

Alterations in the regulation of gene expression are frequently associated with developmental diseases or cancer. Transcription activation is a key phenomenon in the regulation of gene expression. In all eukaryotes, mediator of RNA polymerase II transcription (Mediator), a large complex with modular organization, is generally required for transcription by RNA polymerase II, and it regulates various steps of this process. The main function of Mediator is to transduce signals from the transcription activators bound to enhancer regions to the transcription machinery, which is assembled at promoters as the preinitiation complex (PIC) to control transcription initiation. Recent functional studies of Mediator with the use of structural biology approaches and functional genomics have revealed new insights into Mediator activity and its regulation during transcription initiation, including how Mediator is recruited to transcription regulatory regions and how it interacts and cooperates with PIC components to assist in PIC assembly. Novel roles of Mediator in the control of gene expression have also been revealed by showing its connection to the nuclear pore and linking Mediator to the regulation of gene positioning in the nuclear space. Clear links between Mediator subunits and disease have also encouraged studies to explore targeting of this complex as a potential therapeutic approach in cancer and fungal infections.

Dystrophic Cardiomyopathy: Complex Pathobiological Processes to Generate Clinical Phenotype

PubMed Central

Tsuda, Takeshi; Fitzgerald, Kristi K.

2017-01-01

Duchenne muscular dystrophy (DMD), Becker muscular dystrophy (BMD), and X-linked dilated cardiomyopathy (XL-DCM) consist of a unique clinical entity, the dystrophinopathies, which are due to variable mutations in the dystrophin gene. Dilated cardiomyopathy (DCM) is a common complication of dystrophinopathies, but the onset, progression, and severity of heart disease differ among these subgroups. Extensive molecular genetic studies have been conducted to assess genotype-phenotype correlation in DMD, BMD, and XL-DCM to understand the underlying mechanisms of these diseases, but the results are not always conclusive, suggesting the involvement of complex multi-layers of pathological processes that generate the final clinical phenotype. Dystrophin protein is a part of dystrophin-glycoprotein complex (DGC) that is localized in skeletal muscles, myocardium, smooth muscles, and neuronal tissues. Diversity of cardiac phenotype in dystrophinopathies suggests multiple layers of pathogenetic mechanisms in forming dystrophic cardiomyopathy. In this review article, we review the complex molecular interactions involving the pathogenesis of dystrophic cardiomyopathy, including primary gene mutations and loss of structural integrity, secondary cellular responses, and certain epigenetic and other factors that modulate gene expressions. Involvement of epigenetic gene regulation appears to lead to specific cardiac phenotypes in dystrophic hearts. PMID:29367543

SAD-3, a Putative Helicase Required for Meiotic Silencing by Unpaired DNA, Interacts with Other Components of the Silencing Machinery

PubMed Central

Hammond, Thomas M.; Xiao, Hua; Boone, Erin C.; Perdue, Tony D.; Pukkila, Patricia J.; Shiu, Patrick K. T.

2011-01-01

In Neurospora crassa, genes lacking a pairing partner during meiosis are suppressed by a process known as meiotic silencing by unpaired DNA (MSUD). To identify novel MSUD components, we have developed a high-throughput reverse-genetic screen for use with the N. crassa knockout library. Here we describe the screening method and the characterization of a gene (sad-3) subsequently discovered. SAD-3 is a putative helicase required for MSUD and sexual spore production. It exists in a complex with other known MSUD proteins in the perinuclear region, a center for meiotic silencing activity. Orthologs of SAD-3 include Schizosaccharomyces pombe Hrr1, a helicase required for RNAi-induced heterochromatin formation. Both SAD-3 and Hrr1 interact with an RNA-directed RNA polymerase and an Argonaute, suggesting that certain aspects of silencing complex formation may be conserved between the two fungal species. PMID:22384347

Leucine-Rich Repeat Kinase 2 interacts with Parkin, DJ-1 and PINK-1 in a Drosophila melanogaster model of Parkinson's disease.

PubMed

Venderova, Katerina; Kabbach, Ghassan; Abdel-Messih, Elizabeth; Zhang, Yi; Parks, Robin J; Imai, Yuzuru; Gehrke, Stephan; Ngsee, Johnny; Lavoie, Matthew J; Slack, Ruth S; Rao, Yong; Zhang, Zhuohua; Lu, Bingwei; Haque, M Emdadul; Park, David S

2009-11-15

Mutations in the LRRK2 gene are the most common genetic cause of familial Parkinson's disease (PD). However, its physiological and pathological functions are unknown. Therefore, we generated several independent Drosophila lines carrying WT or mutant human LRRK2 (mutations in kinase, COR or LRR domains, resp.). Ectopic expression of WT or mutant LRRK2 in dopaminergic neurons caused their significant loss accompanied by complex age-dependent changes in locomotor activity. Overall, the ubiquitous expression of LRRK2 increased lifespan and fertility of the flies. However, these flies were more sensitive to rotenone. LRRK2 expression in the eye exacerbated retinal degeneration. Importantly, in double transgenic flies, various indices of the eye and dopaminergic survival were modified in a complex fashion by a concomitant expression of PINK1, DJ-1 or Parkin. This evidence suggests a genetic interaction between these PD-relevant genes.

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

PubMed

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

2006-07-01

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

The genetics of childhood obesity and interaction with dietary macronutrients.

PubMed

Garver, William S; Newman, Sara B; Gonzales-Pacheco, Diana M; Castillo, Joseph J; Jelinek, David; Heidenreich, Randall A; Orlando, Robert A

2013-05-01

The genes contributing to childhood obesity are categorized into three different types based on distinct genetic and phenotypic characteristics. These types of childhood obesity are represented by rare monogenic forms of syndromic or non-syndromic childhood obesity, and common polygenic childhood obesity. In some cases, genetic susceptibility to these forms of childhood obesity may result from different variations of the same gene. Although the prevalence for rare monogenic forms of childhood obesity has not increased in recent times, the prevalence of common childhood obesity has increased in the United States and developing countries throughout the world during the past few decades. A number of recent genome-wide association studies and mouse model studies have established the identification of susceptibility genes contributing to common childhood obesity. Accumulating evidence suggests that this type of childhood obesity represents a complex metabolic disease resulting from an interaction with environmental factors, including dietary macronutrients. The objective of this article is to provide a review on the origins, mechanisms, and health consequences of obesity susceptibility genes and interaction with dietary macronutrients that predispose to childhood obesity. It is proposed that increased knowledge of these obesity susceptibility genes and interaction with dietary macronutrients will provide valuable insight for individual, family, and community preventative lifestyle intervention, and eventually targeted nutritional and medicinal therapies.

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

PubMed

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

2017-09-27

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

Spatial enhancer clustering and regulation of enhancer-proximal genes by cohesin

PubMed Central

Ing-Simmons, Elizabeth; Seitan, Vlad C.; Faure, Andre J.; Flicek, Paul; Carroll, Thomas; Dekker, Job; Fisher, Amanda G.; Lenhard, Boris

2015-01-01

In addition to mediating sister chromatid cohesion during the cell cycle, the cohesin complex associates with CTCF and with active gene regulatory elements to form long-range interactions between its binding sites. Genome-wide chromosome conformation capture had shown that cohesin's main role in interphase genome organization is in mediating interactions within architectural chromosome compartments, rather than specifying compartments per se. However, it remains unclear how cohesin-mediated interactions contribute to the regulation of gene expression. We have found that the binding of CTCF and cohesin is highly enriched at enhancers and in particular at enhancer arrays or “super-enhancers” in mouse thymocytes. Using local and global chromosome conformation capture, we demonstrate that enhancer elements associate not just in linear sequence, but also in 3D, and that spatial enhancer clustering is facilitated by cohesin. The conditional deletion of cohesin from noncycling thymocytes preserved enhancer position, H3K27ac, H4K4me1, and enhancer transcription, but weakened interactions between enhancers. Interestingly, ∼50% of deregulated genes reside in the vicinity of enhancer elements, suggesting that cohesin regulates gene expression through spatial clustering of enhancer elements. We propose a model for cohesin-dependent gene regulation in which spatial clustering of enhancer elements acts as a unified mechanism for both enhancer-promoter “connections” and “insulation.” PMID:25677180

A systems-genetics approach and data mining tool to assist in the discovery of genes underlying complex traits in Oryza sativa.

PubMed

Ficklin, Stephen P; Feltus, Frank Alex

2013-01-01

Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify co-localized genetic and gene expression signals that implicate complex genotype-phenotype relationships. In this work, we used a knowledge-independent, systems genetics approach, to discover a high-quality set of co-expression networks, termed Gene Interaction Layers (GILs). Twenty-two GILs were constructed from 1,306 Affymetrix microarray rice expression profiles that were pre-clustered to allow for improved capture of gene co-expression relationships. Functional genomic and genetic data, including over 8,000 QTLs and 766 phenotype-tagged SNPs (p-value < = 0.001) from genome-wide association studies, both covering over 230 different rice traits were integrated with the GILs. An online systems genetics data-mining resource, the GeneNet Engine, was constructed to enable dynamic discovery of gene sets (i.e. network modules) that overlap with genetic traits. GeneNet Engine does not provide the exact set of genes underlying a given complex trait, but through the evidence of gene-marker correspondence, co-expression, and functional enrichment, site visitors can identify genes with potential shared causality for a trait which could then be used for experimental validation. A set of 2 million SNPs was incorporated into the database and serve as a potential set of testable biomarkers for genes in modules that overlap with genetic traits. Herein, we describe two modules found using GeneNet Engine, one with significant overlap with the trait amylose content and another with significant overlap with blast disease resistance.

A Systems-Genetics Approach and Data Mining Tool to Assist in the Discovery of Genes Underlying Complex Traits in Oryza sativa

PubMed Central

Ficklin, Stephen P.; Feltus, Frank Alex

2013-01-01

Many traits of biological and agronomic significance in plants are controlled in a complex manner where multiple genes and environmental signals affect the expression of the phenotype. In Oryza sativa (rice), thousands of quantitative genetic signals have been mapped to the rice genome. In parallel, thousands of gene expression profiles have been generated across many experimental conditions. Through the discovery of networks with real gene co-expression relationships, it is possible to identify co-localized genetic and gene expression signals that implicate complex genotype-phenotype relationships. In this work, we used a knowledge-independent, systems genetics approach, to discover a high-quality set of co-expression networks, termed Gene Interaction Layers (GILs). Twenty-two GILs were constructed from 1,306 Affymetrix microarray rice expression profiles that were pre-clustered to allow for improved capture of gene co-expression relationships. Functional genomic and genetic data, including over 8,000 QTLs and 766 phenotype-tagged SNPs (p-value < = 0.001) from genome-wide association studies, both covering over 230 different rice traits were integrated with the GILs. An online systems genetics data-mining resource, the GeneNet Engine, was constructed to enable dynamic discovery of gene sets (i.e. network modules) that overlap with genetic traits. GeneNet Engine does not provide the exact set of genes underlying a given complex trait, but through the evidence of gene-marker correspondence, co-expression, and functional enrichment, site visitors can identify genes with potential shared causality for a trait which could then be used for experimental validation. A set of 2 million SNPs was incorporated into the database and serve as a potential set of testable biomarkers for genes in modules that overlap with genetic traits. Herein, we describe two modules found using GeneNet Engine, one with significant overlap with the trait amylose content and another with significant overlap with blast disease resistance. PMID:23874666

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).

Co-complex protein membership evaluation using Maximum Entropy on GO ontology and InterPro annotation.

PubMed

Armean, Irina M; Lilley, Kathryn S; Trotter, Matthew W B; Pilkington, Nicholas C V; Holden, Sean B

2018-06-01

Protein-protein interactions (PPI) play a crucial role in our understanding of protein function and biological processes. The standardization and recording of experimental findings is increasingly stored in ontologies, with the Gene Ontology (GO) being one of the most successful projects. Several PPI evaluation algorithms have been based on the application of probabilistic frameworks or machine learning algorithms to GO properties. Here, we introduce a new training set design and machine learning based approach that combines dependent heterogeneous protein annotations from the entire ontology to evaluate putative co-complex protein interactions determined by empirical studies. PPI annotations are built combinatorically using corresponding GO terms and InterPro annotation. We use a S.cerevisiae high-confidence complex dataset as a positive training set. A series of classifiers based on Maximum Entropy and support vector machines (SVMs), each with a composite counterpart algorithm, are trained on a series of training sets. These achieve a high performance area under the ROC curve of ≤0.97, outperforming go2ppi-a previously established prediction tool for protein-protein interactions (PPI) based on Gene Ontology (GO) annotations. https://github.com/ima23/maxent-ppi. sbh11@cl.cam.ac.uk. Supplementary data are available at Bioinformatics online.

Interactions between the promoter and first intron are involved in transcriptional control of alpha 1(I) collagen gene expression.

PubMed Central

Bornstein, P; McKay, J; Liska, D J; Apone, S; Devarayalu, S

1988-01-01

The first intron of the human collagen alpha 1(I) gene contains several positively and negatively acting elements. We have studied the transcription of collagen-human growth hormone fusion genes, containing deletions and rearrangements of collagen intronic sequences, by transient transfection of chick tendon fibroblasts and NIH 3T3 cells. In chick tendon fibroblasts, but not in 3T3 cells, inversion of intronic sequences containing a previously studied 274-base-pair segment, A274, resulted in markedly reduced human growth hormone mRNA levels as determined by an RNase protection assay. This inhibitory effect was largely alleviated when deletions were introduced in the collagen promoter of plasmids containing negatively oriented intronic sequences. Evidence for interaction of the promoter with the intronic segment, A274, was obtained by gel mobility shift assays. We suggest that promoter-intron interactions, mediated by DNA-binding proteins, regulate collagen gene transcription. Inversion of intronic segments containing critical interactive elements might then lead to an altered geometry and reduced activity of a transcriptional complex in those cells with sufficiently high levels of appropriate transcription factors. We further suggest that the deleted promoter segment plays a key role in directing DNA interactions involved in transcriptional control. Images PMID:3211130

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

PubMed Central

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

2017-01-01

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

Determination of nonlinear genetic architecture using compressed sensing.

PubMed

Ho, Chiu Man; Hsu, Stephen D H

2015-01-01

One of the fundamental problems of modern genomics is to extract the genetic architecture of a complex trait from a data set of individual genotypes and trait values. Establishing this important connection between genotype and phenotype is complicated by the large number of candidate genes, the potentially large number of causal loci, and the likely presence of some nonlinear interactions between different genes. Compressed Sensing methods obtain solutions to under-constrained systems of linear equations. These methods can be applied to the problem of determining the best model relating genotype to phenotype, and generally deliver better performance than simply regressing the phenotype against each genetic variant, one at a time. We introduce a Compressed Sensing method that can reconstruct nonlinear genetic models (i.e., including epistasis, or gene-gene interactions) from phenotype-genotype (GWAS) data. Our method uses L1-penalized regression applied to nonlinear functions of the sensing matrix. The computational and data resource requirements for our method are similar to those necessary for reconstruction of linear genetic models (or identification of gene-trait associations), assuming a condition of generalized sparsity, which limits the total number of gene-gene interactions. An example of a sparse nonlinear model is one in which a typical locus interacts with several or even many others, but only a small subset of all possible interactions exist. It seems plausible that most genetic architectures fall in this category. We give theoretical arguments suggesting that the method is nearly optimal in performance, and demonstrate its effectiveness on broad classes of nonlinear genetic models using simulated human genomes and the small amount of currently available real data. A phase transition (i.e., dramatic and qualitative change) in the behavior of the algorithm indicates when sufficient data is available for its successful application. Our results indicate that predictive models for many complex traits, including a variety of human disease susceptibilities (e.g., with additive heritability h (2)∼0.5), can be extracted from data sets comprised of n ⋆∼100s individuals, where s is the number of distinct causal variants influencing the trait. For example, given a trait controlled by ∼10 k loci, roughly a million individuals would be sufficient for application of the method.

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

PubMed Central

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

2008-01-01

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

Discovery of new candidate genes related to brain development using protein interaction information.

PubMed

Chen, Lei; Chu, Chen; Kong, Xiangyin; Huang, Tao; Cai, Yu-Dong

2015-01-01

Human brain development is a dramatic process composed of a series of complex and fine-tuned spatiotemporal gene expressions. A good comprehension of this process can assist us in developing the potential of our brain. However, we have only limited knowledge about the genes and gene functions that are involved in this biological process. Therefore, a substantial demand remains to discover new brain development-related genes and identify their biological functions. In this study, we aimed to discover new brain-development related genes by building a computational method. We referred to a series of computational methods used to discover new disease-related genes and developed a similar method. In this method, the shortest path algorithm was executed on a weighted graph that was constructed using protein-protein interactions. New candidate genes fell on at least one of the shortest paths connecting two known genes that are related to brain development. A randomization test was then adopted to filter positive discoveries. Of the final identified genes, several have been reported to be associated with brain development, indicating the effectiveness of the method, whereas several of the others may have potential roles in brain development.

An Lnc RNA (GAS5)/SnoRNA-derived piRNA induces activation of TRAIL gene by site-specifically recruiting MLL/COMPASS-like complexes

PubMed Central

He, Xin; Chen, Xinxin; Zhang, Xue; Duan, Xiaobing; Pan, Ting; Hu, Qifei; Zhang, Yijun; Zhong, Fudi; Liu, Jun; Zhang, Hong; Luo, Juan; Wu, Kang; Peng, Gao; Luo, Haihua; Zhang, Lehong; Li, Xiaoxi; Zhang, Hui

2015-01-01

PIWI-interacting RNA (piRNA) silences the transposons in germlines or induces epigenetic modifications in the invertebrates. However, its function in the mammalian somatic cells remains unknown. Here we demonstrate that a piRNA derived from Growth Arrest Specific 5, a tumor-suppressive long non-coding RNA, potently upregulates the transcription of tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL), a proapoptotic protein, by inducing H3K4 methylation/H3K27 demethylation. Interestingly, the PIWIL1/4 proteins, which bind with this piRNA, directly interact with WDR5, resulting in a site-specific recruitment of the hCOMPASS-like complexes containing at least MLL3 and UTX (KDM6A). We have indicated a novel pathway for piRNAs to specially activate gene expression. Given that MLL3 or UTX are frequently mutated in various tumors, the piRNA/MLL3/UTX complex mediates the induction of TRAIL, and consequently leads to the inhibition of tumor growth. PMID:25779046

A study of structural properties of gene network graphs for mathematical modeling of integrated mosaic gene networks.

PubMed

Petrovskaya, Olga V; Petrovskiy, Evgeny D; Lavrik, Inna N; Ivanisenko, Vladimir A

2017-04-01

Gene network modeling is one of the widely used approaches in systems biology. It allows for the study of complex genetic systems function, including so-called mosaic gene networks, which consist of functionally interacting subnetworks. We conducted a study of a mosaic gene networks modeling method based on integration of models of gene subnetworks by linear control functionals. An automatic modeling of 10,000 synthetic mosaic gene regulatory networks was carried out using computer experiments on gene knockdowns/knockouts. Structural analysis of graphs of generated mosaic gene regulatory networks has revealed that the most important factor for building accurate integrated mathematical models, among those analyzed in the study, is data on expression of genes corresponding to the vertices with high properties of centrality.

Cell surface retention sequence binding protein-1 interacts with the v-sis gene product and platelet-derived growth factor beta-type receptor in simian sarcoma virus-transformed cells.

PubMed

Boensch, C; Huang, S S; Connolly, D T; Huang, J S

1999-04-09

The cell surface retention sequence (CRS) binding protein-1 (CRSBP-1) is a newly identified membrane glycoprotein which is hypothesized to be responsible for cell surface retention of the oncogene v-sis and c-sis gene products and other secretory proteins containing CRSs. In simian sarcoma virus-transformed NIH 3T3 cells (SSV-NIH 3T3 cells), a fraction of CRSBP-1 was demonstrated at the cell surface and underwent internalization/recycling as revealed by cell surface 125I labeling and its resistance/sensitivity to trypsin digestion. However, the majority of CRSBP-1 was localized in intracellular compartments as evidenced by the resistance of most of the 35S-metabolically labeled CRSBP-1 to trypsin digestion, and by indirect immunofluorescent staining. CRSBP-1 appeared to form complexes with proteolytically processed forms (generated at and/or after the trans-Golgi network) of the v-sis gene product and with a approximately 140-kDa proteolytically cleaved form of the platelet-derived growth factor (PDGF) beta-type receptor, as demonstrated by metabolic labeling and co-immunoprecipitation. CRSBP-1, like the v-sis gene product and PDGF beta-type receptor, underwent rapid turnover which was blocked in the presence of 100 microM suramin. In normal and other transformed NIH 3T3 cells, CRSBP-1 was relatively stable and did not undergo rapid turnover and internalization/recycling at the cell surface. These results suggest that in SSV-NIH 3T3 cells, CRSBP-1 interacts with and forms ternary and binary complexes with the newly synthesized v-sis gene product and PDGF beta-type receptor at the trans-Golgi network and that the stable binary (CRSBP-1.v-sis gene product) complex is transported to the cell surface where it presents the v-sis gene product to unoccupied PDGF beta-type receptors during internalization/recycling.

Interspecies Systems Biology Uncovers Metabolites Affecting C. elegans Gene Expression and Life History Traits

PubMed Central

Watson, Emma; MacNeil, Lesley T.; Ritter, Ashlyn D.; Yilmaz, L. Safak; Rosebrock, Adam P.; Caudy, Amy A.; Walhout, Albertha J. M.

2014-01-01

SUMMARY Diet greatly influences gene expression and physiology. In mammals, elucidating the effects and mechanisms of individual nutrients is challenging due to the complexity of both the animal and its diet. Here we used an interspecies systems biology approach with Caenorhabditis elegans and two if its bacterial diets, Escherichia coli and Comamonas aquatica, to identify metabolites that affect the animal’s gene expression and physiology. We identify vitamin B12 as the major dilutable metabolite provided by Comamonas aq. that regulates gene expression, accelerates development and reduces fertility, but does not affect lifespan. We find that vitamin B12 has a dual role in the animal: it affects development and fertility via the methionine/S-Adenosylmethionine (SAM) cycle and breaks down the short-chain fatty acid propionic acid preventing its toxic buildup. Our interspecies systems biology approach provides a paradigm for understanding complex interactions between diet and physiology. PMID:24529378

Shadows of complexity: what biological networks reveal about epistasis and pleiotropy

PubMed Central

Tyler, Anna L.; Asselbergs, Folkert W.; Williams, Scott M.; Moore, Jason H.

2011-01-01

Pleiotropy, in which one mutation causes multiple phenotypes, has traditionally been seen as a deviation from the conventional observation in which one gene affects one phenotype. Epistasis, or gene-gene interaction, has also been treated as an exception to the Mendelian one gene-one phenotype paradigm. This simplified perspective belies the pervasive complexity of biology and hinders progress toward a deeper understanding of biological systems. We assert that epistasis and pleiotropy are not isolated occurrences, but ubiquitous and inherent properties of biomolecular networks. These phenomena should not be treated as exceptions, but rather as fundamental components of genetic analyses. A systems level understanding of epistasis and pleiotropy is, therefore, critical to furthering our understanding of human genetics and its contribution to common human disease. Finally, graph theory offers an intuitive and powerful set of tools with which to study the network bases of these important genetic phenomena. PMID:19204994

Elongator promotes germination and early post-germination growth.

PubMed

Woloszynska, Magdalena; Gagliardi, Olimpia; Vandenbussche, Filip; Van Lijsebettens, Mieke

2018-01-02

The Elongator complex interacts with RNA polymerase II and via histone acetylation and DNA demethylation facilitates epigenetically the transcription of genes involved in diverse processes in plants, including growth, development, and immune response. Recently, we have shown that the Elongator complex promotes hypocotyl elongation and photomorphogenesis in Arabidopsis thaliana by regulating the photomorphogenesis and growth-related gene network that converges on genes implicated in cell wall biogenesis and hormone signaling. Here, we report that germination in the elo mutant was delayed by 6 h in the dark when compared to the wild type in a time lapse and germination assay. A number of germination-correlated genes were down-regulated in the elo transcriptome, suggesting a transcriptional regulation by Elongator. We also show that the hypocotyl elongation defect observed in the elo mutants in darkness originates very early in the post-germination development and is independent from the germination delay.

MTA family of coregulators in nuclear receptor biology and pathology

PubMed Central

Manavathi, Bramanandam; Singh, Kamini; Kumar, Rakesh

2007-01-01

Nuclear receptors (NRs) rely on coregulators (coactivators and corepressors) to modulate the transcription of target genes. By interacting with nucleosome remodeling complexes, NR coactivators potentiate transcription, whereas corepressors inhibit transcription of the target genes. Metastasis-associated proteins (MTA) represent an emerging family of novel NR coregulators. In general, MTA family members form independent nucleosome remodeling and deacetylation (NuRD) complexes and repress the transcription of different genes by recruiting histone deacetylases onto their target genes. However, MTA1 also acts as a coactivator in a promoter-context dependent manner. Recent findings that repression of estrogen receptor transactivation functions by MTA1, MTA1s, and MTA2 and regulation of MTA3 by estrogen signaling have indicated the significance of these proteins in NR signaling. Here, we highlight the action of MTA proteins on NR signaling and their roles in pathophysiological conditions. PMID:18174918

PAMPs, PRRs, effectors and R-genes associated with citrus-pathogen interactions.

PubMed

Dalio, Ronaldo J D; Magalhães, Diogo M; Rodrigues, Carolina M; Arena, Gabriella D; Oliveira, Tiago S; Souza-Neto, Reinaldo R; Picchi, Simone C; Martins, Paula M M; Santos, Paulo J C; Maximo, Heros J; Pacheco, Inaiara S; De Souza, Alessandra A; Machado, Marcos A

2017-03-01

Recent application of molecular-based technologies has considerably advanced our understanding of complex processes in plant-pathogen interactions and their key components such as PAMPs, PRRs, effectors and R-genes. To develop novel control strategies for disease prevention in citrus, it is essential to expand and consolidate our knowledge of the molecular interaction of citrus plants with their pathogens. This review provides an overview of our understanding of citrus plant immunity, focusing on the molecular mechanisms involved in the interactions with viruses, bacteria, fungi, oomycetes and vectors related to the following diseases: tristeza, psorosis, citrus variegated chlorosis, citrus canker, huanglongbing, brown spot, post-bloom, anthracnose, gummosis and citrus root rot. © The Author 2017. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Using the clustered circular layout as an informative method for visualizing protein-protein interaction networks.

PubMed

Fung, David C Y; Wilkins, Marc R; Hart, David; Hong, Seok-Hee

2010-07-01

The force-directed layout is commonly used in computer-generated visualizations of protein-protein interaction networks. While it is good for providing a visual outline of the protein complexes and their interactions, it has two limitations when used as a visual analysis method. The first is poor reproducibility. Repeated running of the algorithm does not necessarily generate the same layout, therefore, demanding cognitive readaptation on the investigator's part. The second limitation is that it does not explicitly display complementary biological information, e.g. Gene Ontology, other than the protein names or gene symbols. Here, we present an alternative layout called the clustered circular layout. Using the human DNA replication protein-protein interaction network as a case study, we compared the two network layouts for their merits and limitations in supporting visual analysis.

Connecting the Human Variome Project to nutrigenomics

PubMed Central

Evelo, Chris T.; Perozzi, Giuditta; van Ommen, Ben; Cotton, Richard

2010-01-01

Nutrigenomics is the science of analyzing and understanding gene–nutrient interactions, which because of the genetic heterogeneity, varying degrees of interaction among gene products, and the environmental diversity is a complex science. Although much knowledge of human diversity has been accumulated, estimates suggest that ~90% of genetic variation has not yet been characterized. Identification of the DNA sequence variants that contribute to nutrition-related disease risk is essential for developing a better understanding of the complex causes of disease in humans, including nutrition-related disease. The Human Variome Project (HVP; http://www.humanvariomeproject.org/) is an international effort to systematically identify genes, their mutations, and their variants associated with phenotypic variability and indications of human disease or phenotype. Since nutrigenomic research uses genetic information in the design and analysis of experiments, the HVP is an essential collaborator for ongoing studies of gene–nutrient interactions. With the advent of next generation sequencing methodologies and the understanding of the undiscovered variation in human genomes, the nutrigenomic community will be generating novel sequence data and results. The guidelines and practices of the HVP can guide and harmonize these efforts. PMID:28300226

IC97 Is a Novel Intermediate Chain of I1 Dynein That Interacts with Tubulin and Regulates Interdoublet Sliding

PubMed Central

Wirschell, Maureen; Yang, Chun; Yang, Pinfen; Fox, Laura; Yanagisawa, Haru-aki; Kamiya, Ritsu; Witman, George B.; Porter, Mary E.

2009-01-01

Our goal is to understand the assembly and regulation of flagellar dyneins, particularly the Chlamydomonas inner arm dynein called I1 dynein. Here, we focus on the uncharacterized I1-dynein IC IC97. The IC97 gene encodes a novel IC without notable structural domains. IC97 shares homology with the murine lung adenoma susceptibility 1 (Las1) protein—a candidate tumor suppressor gene implicated in lung tumorigenesis. Multiple, independent biochemical assays determined that IC97 interacts with both α- and β-tubulin subunits within the axoneme. I1-dynein assembly mutants suggest that IC97 interacts with both the IC138 and IC140 subunits within the I1-dynein motor complex and that IC97 is part of a regulatory complex that contains IC138. Microtubule sliding assays, using axonemes containing I1 dynein but devoid of IC97, show reduced microtubule sliding velocities that are not rescued by kinase inhibitors, revealing a critical role for IC97 in I1-dynein function and control of dynein-driven motility. PMID:19420136

Assessing the utility of gene co-expression stability in combination with correlation in the analysis of protein-protein interaction networks

PubMed Central

2011-01-01

Background Gene co-expression, in the form of a correlation coefficient, has been valuable in the analysis, classification and prediction of protein-protein interactions. However, it is susceptible to bias from a few samples having a large effect on the correlation coefficient. Gene co-expression stability is a means of quantifying this bias, with high stability indicating robust, unbiased co-expression correlation coefficients. We assess the utility of gene co-expression stability as an additional measure to support the co-expression correlation in the analysis of protein-protein interaction networks. Results We studied the patterns of co-expression correlation and stability in interacting proteins with respect to their interaction promiscuity, levels of intrinsic disorder, and essentiality or disease-relatedness. Co-expression stability, along with co-expression correlation, acts as a better classifier of hub proteins in interaction networks, than co-expression correlation alone, enabling the identification of a class of hubs that are functionally distinct from the widely accepted transient (date) and obligate (party) hubs. Proteins with high levels of intrinsic disorder have low co-expression correlation and high stability with their interaction partners suggesting their involvement in transient interactions, except for a small group that have high co-expression correlation and are typically subunits of stable complexes. Similar behavior was seen for disease-related and essential genes. Interacting proteins that are both disordered have higher co-expression stability than ordered protein pairs. Using co-expression correlation and stability, we found that transient interactions are more likely to occur between an ordered and a disordered protein while obligate interactions primarily occur between proteins that are either both ordered, or disordered. Conclusions We observe that co-expression stability shows distinct patterns in structurally and functionally different groups of proteins and interactions. We conclude that it is a useful and important measure to be used in concert with gene co-expression correlation for further insights into the characteristics of proteins in the context of their interaction network. PMID:22369639

Bcl11b, a novel GATA3-interacting protein, suppresses Th1 while limiting Th2 cell differentiation.

PubMed

Fang, Difeng; Cui, Kairong; Hu, Gangqing; Gurram, Rama Krishna; Zhong, Chao; Oler, Andrew J; Yagi, Ryoji; Zhao, Ming; Sharma, Suveena; Liu, Pentao; Sun, Bing; Zhao, Keji; Zhu, Jinfang

2018-05-07

GATA-binding protein 3 (GATA3) acts as the master transcription factor for type 2 T helper (Th2) cell differentiation and function. However, it is still elusive how GATA3 function is precisely regulated in Th2 cells. Here, we show that the transcription factor B cell lymphoma 11b (Bcl11b), a previously unknown component of GATA3 transcriptional complex, is involved in GATA3-mediated gene regulation. Bcl11b binds to GATA3 through protein-protein interaction, and they colocalize at many important cis-regulatory elements in Th2 cells. The expression of type 2 cytokines, including IL-4, IL-5, and IL-13, is up-regulated in Bcl11b -deficient Th2 cells both in vitro and in vivo; such up-regulation is completely GATA3 dependent. Genome-wide analyses of Bcl11b- and GATA3-regulated genes (from RNA sequencing), cobinding patterns (from chromatin immunoprecipitation sequencing), and Bcl11b-modulated epigenetic modification and gene accessibility suggest that GATA3/Bcl11b complex is involved in limiting Th2 gene expression, as well as in inhibiting non-Th2 gene expression. Thus, Bcl11b controls both GATA3-mediated gene activation and repression in Th2 cells. This is a work of the U.S. Government and is not subject to copyright protection in the United States. Foreign copyrights may apply.

Identification of SFBB-containing canonical and noncanonical SCF complexes in pollen of apple (Malus × domestica).

PubMed

Minamikawa, Mai F; Koyano, Ruriko; Kikuchi, Shinji; Koba, Takato; Sassa, Hidenori

2014-01-01

Gametophytic self-incompatibility (GSI) of Rosaceae, Solanaceae and Plantaginaceae is controlled by a single polymorphic S locus. The S locus contains at least two genes, S-RNase and F-box protein encoding gene SLF/SFB/SFBB that control pistil and pollen specificity, respectively. Generally, the F-box protein forms an E3 ligase complex, SCF complex with Skp1, Cullin1 (CUL1) and Rbx1, however, in Petunia inflata, SBP1 (S-RNase binding protein1) was reported to play the role of Skp1 and Rbx1, and form an SCFSLF-like complex for ubiquitination of non-self S-RNases. On the other hand, in Petunia hybrida and Petunia inflata of Solanaceae, Prunus avium and Pyrus bretschneideri of Rosaceae, SSK1 (SLF-interacting Skp1-like protein1) is considered to form the SCFSLF/SFB complex. Here, we isolated pollen-expressed apple homologs of SSK1 and CUL1, and named MdSSK1, MdCUL1A and MdCUL1B. MdSSK1 was preferentially expressed in pollen, but weakly in other organs analyzed, while, MdCUL1A and MdCUL1B were almost equally expressed in all the organs analyzed. MdSSK1 transcript abundance was significantly (>100 times) higher than that of MdSBP1. In vitro binding assays showed that MdSSK1 and MdSBP1 interacted with MdSFBB1-S9 and MdCUL1, and MdSFBB1-S9 interacted more strongly with MdSSK1 than with MdSBP1. The results suggest that both MdSSK1-containing SCFSFBB1 and MdSBP1-containing SCFSFBB1-like complexes function in pollen of apple, and the former plays a major role.

Characterization of stem cells and cancer cells on the basis of gene expression profile stability, plasticity, and robustness: dynamical systems theory of gene expressions under cell-cell interaction explains mutational robustness of differentiated cells and suggests how cancer cells emerge.

PubMed

Kaneko, Kunihiko

2011-06-01

Here I present and discuss a model that, among other things, appears able to describe the dynamics of cancer cell origin from the perspective of stable and unstable gene expression profiles. In identifying such aberrant gene expression profiles as lying outside the normal stable states attracted through development and normal cell differentiation, the hypothesis explains why cancer cells accumulate mutations, to which they are not robust, and why these mutations create a new stable state far from the normal gene expression profile space. Such cells are in strong contrast with normal cell types that appeared as an attractor state in the gene expression dynamical system under cell-cell interaction and achieved robustness to noise through evolution, which in turn also conferred robustness to mutation. In complex gene regulation networks, other aberrant cellular states lacking such high robustness are expected to remain, which would correspond to cancer cells. Copyright © 2011 WILEY Periodicals, Inc.

Key role of LaeA and velvet complex proteins on expression of β-lactam and PR-toxin genes in Penicillium chrysogenum: cross-talk regulation of secondary metabolite pathways.

PubMed

Martín, Juan F

2017-05-01

Penicillium chrysogenum is an excellent model fungus to study the molecular mechanisms of control of expression of secondary metabolite genes. A key global regulator of the biosynthesis of secondary metabolites is the LaeA protein that interacts with other components of the velvet complex (VelA, VelB, VelC, VosA). These components interact with LaeA and regulate expression of penicillin and PR-toxin biosynthetic genes in P. chrysogenum. Both LaeA and VelA are positive regulators of the penicillin and PR-toxin biosynthesis, whereas VelB acts as antagonist of the effect of LaeA and VelA. Silencing or deletion of the laeA gene has a strong negative effect on penicillin biosynthesis and overexpression of laeA increases penicillin production. Expression of the laeA gene is enhanced by the P. chrysogenum autoinducers 1,3 diaminopropane and spermidine. The PR-toxin gene cluster is very poorly expressed in P. chrysogenum under penicillin-production conditions (i.e. it is a near-silent gene cluster). Interestingly, the downregulation of expression of the PR-toxin gene cluster in the high producing strain P. chrysogenum DS17690 was associated with mutations in both the laeA and velA genes. Analysis of the laeA and velA encoding genes in this high penicillin producing strain revealed that both laeA and velA acquired important mutations during the strain improvement programs thus altering the ratio of different secondary metabolites (e.g. pigments, PR-toxin) synthesized in the high penicillin producing mutants when compared to the parental wild type strain. Cross-talk of different secondary metabolite pathways has also been found in various Penicillium spp.: P. chrysogenum mutants lacking the penicillin gene cluster produce increasing amounts of PR-toxin, and mutants of P. roqueforti silenced in the PR-toxin genes produce large amounts of mycophenolic acid. The LaeA-velvet complex mediated regulation and the pathway cross-talk phenomenon has great relevance for improving the production of novel secondary metabolites, particularly of those secondary metabolites which are produced in trace amounts encoded by silent or near-silent gene clusters.

An N-terminal region of a Myb-like protein is involved in its intracellular localization and activation of a gibberellin-inducible proteinase gene in germinated rice seeds.

PubMed

Sutoh, Keita; Washio, Kenji; Imai, Ryozo; Wada, Masamitsu; Nakai, Tomonori; Yamauchi, Daisuke

2015-01-01

The expression of the gene for a proteinase (Rep1) is upregulated by gibberellins. The CAACTC regulatory element (CARE) of the Rep1 promoter is involved in the gibberellin response. We isolated a cDNA for a CARE-binding protein containing a Myb domain in its carboxyl-terminal region and designated the gene Carboxyl-terminal Myb1 (CTMyb1). This gene encodes two polypeptides of two distinctive lengths, CTMyb1L and CTMyb1S, which include or exclude 213 N-terminal amino acid residues, respectively. CTMyb1S transactivated the Rep1 promoter in the presence of OsGAMyb, but not CTMyb1L. We observed an interaction between CTMyb1S and the rice prolamin box-binding factor (RPBF). A bimolecular fluorescence complex analysis detected the CTMyb1S and RPBF complex in the nucleus, but not the CTMyb1L and RPBF complex. The results suggest that the arrangement of the transfactors is involved in gibberellin-inducible expression of Rep1.

Glycosaminoglycan-resistant and pH-sensitive lipid-coated DNA complexes produced by detergent removal method.

PubMed

Lehtinen, Julia; Hyvönen, Zanna; Subrizi, Astrid; Bunjes, Heike; Urtti, Arto

2008-10-21

Cationic polymers are efficient gene delivery vectors in in vitro conditions, but these carriers can fail in vivo due to interactions with extracellular polyanions, i.e. glycosaminoglycans (GAG). The aim of this study was to develop a stable gene delivery vector that is activated at the acidic endosomal pH. Cationic DNA/PEI complexes were coated by 1,2-dioleylphosphatidylethanolamine (DOPE) and cholesteryl hemisuccinate (CHEMS) (3:2 mol/mol) using two coating methods: detergent removal and mixing with liposomes prepared by ethanol injection. Only detergent removal produced lipid-coated DNA complexes that were stable against GAGs, but were membrane active at low pH towards endosome mimicking liposomes. In relation to the low cellular uptake of the coated complexes, their transfection efficacy was relatively high. PEGylation of the coated complexes increased their cellular uptake but reduced the pH-sensitivity. Detergent removal was thus a superior method for the production of stable, but acid activatable, lipid-coated DNA complexes.

Coordinating Regulation of Gene Expression in Cardiovascular Disease: Interactions between Chromatin Modifiers and Transcription Factors

PubMed Central

Bauer, Ashley J.; Martin, Kathleen A.

2017-01-01

Cardiovascular disease is a leading cause of death with increasing economic burden. The pathogenesis of cardiovascular diseases is complex, but can arise from genetic and/or environmental risk factors. This can lead to dysregulated gene expression in numerous cell types including cardiomyocytes, endothelial cells, vascular smooth muscle cells, and inflammatory cells. While initial studies addressed transcriptional control of gene expression, epigenetics has been increasingly appreciated to also play an important role in this process through alterations in chromatin structure and gene accessibility. Chromatin-modifying proteins including enzymes that modulate DNA methylation, histone methylation, and histone acetylation can influence gene expression in numerous ways. These chromatin modifiers and their marks can promote or prevent transcription factor recruitment to regulatory regions of genes through modifications to DNA, histones, or the transcription factors themselves. This review will focus on the emerging question of how epigenetic modifiers and transcription factors interact to coordinately regulate gene expression in cardiovascular disease. While most studies have addressed the roles of either epigenetic or transcriptional control, our understanding of the integration of these processes is only just beginning. Interrogating these interactions is challenging, and improved technical approaches will be needed to fully dissect the temporal and spatial relationships between transcription factors, chromatin modifiers, and gene expression in cardiovascular disease. We summarize the current state of the field and provide perspectives on limitations and future directions. Through studies of epigenetic and transcriptional interactions, we can advance our understanding of the basic mechanisms of cardiovascular disease pathogenesis to develop novel therapeutics. PMID:28428957

IQCJ-SCHIP1, a novel fusion transcript encoding a calmodulin-binding IQ motif protein

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

Kwasnicka-Crawford, Dorota A.; Carson, Andrew R.; Scherer, Stephen W.

The existence of transcripts that span two adjacent, independent genes is considered rare in the human genome. This study characterizes a novel human fusion gene named IQCJ-SCHIP1. IQCJ-SCHIP1 is the longest isoform of a complex transcriptional unit that bridges two separate genes that encode distinct proteins, IQCJ, a novel IQ motif containing protein and SCHIP1, a schwannomin interacting protein that has been previously shown to interact with the Neurofibromatosis type 2 (NF2) protein. IQCJ-SCHIP1 is located on the chromosome 3q25 and comprises a 1692-bp transcript encompassing 11 exons spanning 828 kb of the genomic DNA. We show that IQCJ-SCHIP1 mRNAmore » is highly expressed in the brain. Protein encoded by the IQCJ-SCHIP1 gene was localized to cytoplasm and actin-rich regions and in differentiated PC12 cells was also seen in neurite extensions.« less

Using Gene Ontology to describe the role of the neurexin-neuroligin-SHANK complex in human, mouse and rat and its relevance to autism.

PubMed

Patel, Sejal; Roncaglia, Paola; Lovering, Ruth C

2015-06-06

People with an autistic spectrum disorder (ASD) display a variety of characteristic behavioral traits, including impaired social interaction, communication difficulties and repetitive behavior. This complex neurodevelopment disorder is known to be associated with a combination of genetic and environmental factors. Neurexins and neuroligins play a key role in synaptogenesis and neurexin-neuroligin adhesion is one of several processes that have been implicated in autism spectrum disorders. In this report we describe the manual annotation of a selection of gene products known to be associated with autism and/or the neurexin-neuroligin-SHANK complex and demonstrate how a focused annotation approach leads to the creation of more descriptive Gene Ontology (GO) terms, as well as an increase in both the number of gene product annotations and their granularity, thus improving the data available in the GO database. The manual annotations we describe will impact on the functional analysis of a variety of future autism-relevant datasets. Comprehensive gene annotation is an essential aspect of genomic and proteomic studies, as the quality of gene annotations incorporated into statistical analysis tools affects the effective interpretation of data obtained through genome wide association studies, next generation sequencing, proteomic and transcriptomic datasets.

Augmenting Microarray Data with Literature-Based Knowledge to Enhance Gene Regulatory Network Inference

PubMed Central

Kilicoglu, Halil; Shin, Dongwook; Rindflesch, Thomas C.

2014-01-01

Gene regulatory networks are a crucial aspect of systems biology in describing molecular mechanisms of the cell. Various computational models rely on random gene selection to infer such networks from microarray data. While incorporation of prior knowledge into data analysis has been deemed important, in practice, it has generally been limited to referencing genes in probe sets and using curated knowledge bases. We investigate the impact of augmenting microarray data with semantic relations automatically extracted from the literature, with the view that relations encoding gene/protein interactions eliminate the need for random selection of components in non-exhaustive approaches, producing a more accurate model of cellular behavior. A genetic algorithm is then used to optimize the strength of interactions using microarray data and an artificial neural network fitness function. The result is a directed and weighted network providing the individual contribution of each gene to its target. For testing, we used invasive ductile carcinoma of the breast to query the literature and a microarray set containing gene expression changes in these cells over several time points. Our model demonstrates significantly better fitness than the state-of-the-art model, which relies on an initial random selection of genes. Comparison to the component pathways of the KEGG Pathways in Cancer map reveals that the resulting networks contain both known and novel relationships. The p53 pathway results were manually validated in the literature. 60% of non-KEGG relationships were supported (74% for highly weighted interactions). The method was then applied to yeast data and our model again outperformed the comparison model. Our results demonstrate the advantage of combining gene interactions extracted from the literature in the form of semantic relations with microarray analysis in generating contribution-weighted gene regulatory networks. This methodology can make a significant contribution to understanding the complex interactions involved in cellular behavior and molecular physiology. PMID:24921649

Augmenting microarray data with literature-based knowledge to enhance gene regulatory network inference.

PubMed

Chen, Guocai; Cairelli, Michael J; Kilicoglu, Halil; Shin, Dongwook; Rindflesch, Thomas C

2014-06-01

Gene regulatory networks are a crucial aspect of systems biology in describing molecular mechanisms of the cell. Various computational models rely on random gene selection to infer such networks from microarray data. While incorporation of prior knowledge into data analysis has been deemed important, in practice, it has generally been limited to referencing genes in probe sets and using curated knowledge bases. We investigate the impact of augmenting microarray data with semantic relations automatically extracted from the literature, with the view that relations encoding gene/protein interactions eliminate the need for random selection of components in non-exhaustive approaches, producing a more accurate model of cellular behavior. A genetic algorithm is then used to optimize the strength of interactions using microarray data and an artificial neural network fitness function. The result is a directed and weighted network providing the individual contribution of each gene to its target. For testing, we used invasive ductile carcinoma of the breast to query the literature and a microarray set containing gene expression changes in these cells over several time points. Our model demonstrates significantly better fitness than the state-of-the-art model, which relies on an initial random selection of genes. Comparison to the component pathways of the KEGG Pathways in Cancer map reveals that the resulting networks contain both known and novel relationships. The p53 pathway results were manually validated in the literature. 60% of non-KEGG relationships were supported (74% for highly weighted interactions). The method was then applied to yeast data and our model again outperformed the comparison model. Our results demonstrate the advantage of combining gene interactions extracted from the literature in the form of semantic relations with microarray analysis in generating contribution-weighted gene regulatory networks. This methodology can make a significant contribution to understanding the complex interactions involved in cellular behavior and molecular physiology.

Mediator links transcription and DNA repair by facilitating Rad2/XPG recruitment.

PubMed

Eyboulet, Fanny; Cibot, Camille; Eychenne, Thomas; Neil, Helen; Alibert, Olivier; Werner, Michel; Soutourina, Julie

2013-12-01

Mediator is a large multiprotein complex conserved in all eukaryotes. The crucial function of Mediator in transcription is now largely established. However, we found that this complex also plays an important role by connecting transcription with DNA repair. We identified a functional contact between the Med17 Mediator subunit and Rad2/XPG, the 3' endonuclease involved in nucleotide excision DNA repair. Genome-wide location analyses revealed that Rad2 is associated with RNA polymerase II (Pol II)- and Pol III-transcribed genes and telomeric regions in the absence of exogenous genotoxic stress. Rad2 occupancy of Pol II-transcribed genes is transcription-dependent. Genome-wide Rad2 occupancy of class II gene promoters is well correlated with that of Mediator. Furthermore, UV sensitivity of med17 mutants is correlated with reduced Rad2 occupancy of class II genes and concomitant decrease of Mediator interaction with Rad2 protein. Our results suggest that Mediator is involved in DNA repair by facilitating Rad2 recruitment to transcribed genes.

Mediator links transcription and DNA repair by facilitating Rad2/XPG recruitment

PubMed Central

Eyboulet, Fanny; Cibot, Camille; Eychenne, Thomas; Neil, Helen; Alibert, Olivier; Werner, Michel; Soutourina, Julie

2013-01-01

Mediator is a large multiprotein complex conserved in all eukaryotes. The crucial function of Mediator in transcription is now largely established. However, we found that this complex also plays an important role by connecting transcription with DNA repair. We identified a functional contact between the Med17 Mediator subunit and Rad2/XPG, the 3′ endonuclease involved in nucleotide excision DNA repair. Genome-wide location analyses revealed that Rad2 is associated with RNA polymerase II (Pol II)- and Pol III-transcribed genes and telomeric regions in the absence of exogenous genotoxic stress. Rad2 occupancy of Pol II-transcribed genes is transcription-dependent. Genome-wide Rad2 occupancy of class II gene promoters is well correlated with that of Mediator. Furthermore, UV sensitivity of med17 mutants is correlated with reduced Rad2 occupancy of class II genes and concomitant decrease of Mediator interaction with Rad2 protein. Our results suggest that Mediator is involved in DNA repair by facilitating Rad2 recruitment to transcribed genes. PMID:24298055

An Arabidopsis gene regulatory network for secondary cell wall synthesis

DOE PAGES

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

2014-12-24

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

Expression of a DNA Replication Gene Cluster in Bacteriophage T4: Genetic Linkage and the Control of Gene Product Interactions

PubMed Central

Gerald, W. L.; Karam, J. D.

1984-01-01

The results of this study bear on the relationship between genetic linkage and control of interactions between the protein products of different cistrons. In T4 bacteriophage, genes 45 and 44 encode essential components of the phage DNA replication multiprotein complex. T4 gene 45 maps directly upstream of gene 44 relative to the overall direction of reading of this region of the phage chromosome, but it is not known whether these two genes are cotranscribed. It has been shown that a nonsense lesion of T4 gene 45 exerts a cis-dominant inhibitory effect on growth of a missense mutant of gene 44 but not on growth of phage carrying the wild-type gene 44 allele. In previous work, we confirmed these observations on polarity of the gene 45 mutation but detected no polar effects by this lesion on synthesis of either mutant or wild-type gene 44 protein. In the present study, we demonstrate that mRNA for gene 44 protein is separable by gel electrophoresis from gene 45-protein-encoding mRNA. That is, the two proteins are not synthesized from one polycistronic message, and the cis-dominant inhibitory effect of the gene 45 mutation on gene 44 function is probably expressed at a posttranslational stage. We propose that close genetic linkage, whether or not it provides shared transcriptional and translational regulatory signals for certain clusters of functionally related cistrons, may determine the intracellular compartmentalization for synthesis of proteins encoded by these clusters. In prokaryotes, such linkage-dependent compartmentation may minimize the diffusion distances between gene products that are synthesized at low levels and are destined to interact. PMID:6745641

An epigenetic switch regulates de novo DNA methylation at a subset of pluripotency gene enhancers during embryonic stem cell differentiation.

PubMed

Petell, Christopher J; Alabdi, Lama; He, Ming; San Miguel, Phillip; Rose, Richard; Gowher, Humaira

2016-09-19

Coordinated regulation of gene expression that involves activation of lineage specific genes and repression of pluripotency genes drives differentiation of embryonic stem cells (ESC). For complete repression of pluripotency genes during ESC differentiation, chromatin at their enhancers is silenced by the activity of the Lsd1-Mi2/NuRD complex. The mechanism/s that regulate DNA methylation at these enhancers are largely unknown. Here, we investigated the affect of the Lsd1-Mi2/NuRD complex on the dynamic regulatory switch that induces the local interaction of histone tails with the Dnmt3 ATRX-DNMT3-DNMT3L (ADD) domain, thus promoting DNA methylation at the enhancers of a subset of pluripotency genes. This is supported by previous structural studies showing a specific interaction between Dnmt3-ADD domain with H3K4 unmethylated histone tails that is disrupted by histone H3K4 methylation and histone acetylation. Our data suggest that Dnmt3a activity is triggered by Lsd1-Mi2/NuRD-mediated histone deacetylation and demethylation at these pluripotency gene enhancers when they are inactivated during mouse ESC differentiation. Using Dnmt3 knockout ESCs and the inhibitors of Lsd1 and p300 histone modifying enzymes during differentiation of E14Tg2A and ZHBTc4 ESCs, our study systematically reveals this mechanism and establishes that Dnmt3a is both reader and effector of the epigenetic state at these target sites. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

An epigenetic switch regulates de novo DNA methylation at a subset of pluripotency gene enhancers during embryonic stem cell differentiation

PubMed Central

Petell, Christopher J.; Alabdi, Lama; He, Ming; San Miguel, Phillip; Rose, Richard; Gowher, Humaira

2016-01-01

Coordinated regulation of gene expression that involves activation of lineage specific genes and repression of pluripotency genes drives differentiation of embryonic stem cells (ESC). For complete repression of pluripotency genes during ESC differentiation, chromatin at their enhancers is silenced by the activity of the Lsd1-Mi2/NuRD complex. The mechanism/s that regulate DNA methylation at these enhancers are largely unknown. Here, we investigated the affect of the Lsd1-Mi2/NuRD complex on the dynamic regulatory switch that induces the local interaction of histone tails with the Dnmt3 ATRX-DNMT3-DNMT3L (ADD) domain, thus promoting DNA methylation at the enhancers of a subset of pluripotency genes. This is supported by previous structural studies showing a specific interaction between Dnmt3-ADD domain with H3K4 unmethylated histone tails that is disrupted by histone H3K4 methylation and histone acetylation. Our data suggest that Dnmt3a activity is triggered by Lsd1-Mi2/NuRD-mediated histone deacetylation and demethylation at these pluripotency gene enhancers when they are inactivated during mouse ESC differentiation. Using Dnmt3 knockout ESCs and the inhibitors of Lsd1 and p300 histone modifying enzymes during differentiation of E14Tg2A and ZHBTc4 ESCs, our study systematically reveals this mechanism and establishes that Dnmt3a is both reader and effector of the epigenetic state at these target sites. PMID:27179026

An information-gain approach to detecting three-way epistatic interactions in genetic association studies

PubMed Central

Hu, Ting; Chen, Yuanzhu; Kiralis, Jeff W; Collins, Ryan L; Wejse, Christian; Sirugo, Giorgio; Williams, Scott M; Moore, Jason H

2013-01-01

Background Epistasis has been historically used to describe the phenomenon that the effect of a given gene on a phenotype can be dependent on one or more other genes, and is an essential element for understanding the association between genetic and phenotypic variations. Quantifying epistasis of orders higher than two is very challenging due to both the computational complexity of enumerating all possible combinations in genome-wide data and the lack of efficient and effective methodologies. Objectives In this study, we propose a fast, non-parametric, and model-free measure for three-way epistasis. Methods Such a measure is based on information gain, and is able to separate all lower order effects from pure three-way epistasis. Results Our method was verified on synthetic data and applied to real data from a candidate-gene study of tuberculosis in a West African population. In the tuberculosis data, we found a statistically significant pure three-way epistatic interaction effect that was stronger than any lower-order associations. Conclusion Our study provides a methodological basis for detecting and characterizing high-order gene-gene interactions in genetic association studies. PMID:23396514

Systems biology approach to transplant tolerance: proof of concept experiments using RNA interference (RNAi) to knock down hub genes in Jurkat and HeLa cells in vitro.

PubMed

Lwin, Wint Wah; Park, Ken; Wauson, Matthew; Gao, Qin; Finn, Patricia W; Perkins, David; Khanna, Ajai

2012-07-01

Systems biology is gaining importance in studying complex systems such as the functional interconnections of human genes [1]. To investigate the molecular interactions involved in T cell immune responses, we used databases of physical gene-gene interactions to constructed molecular interaction networks (interconnections) with R language algorithms. This helped to identify highly interconnected "hub" genes AT(1)P5C1, IL6ST, PRKCZ, MYC, FOS, JUN, and MAPK1. We hypothesized that suppression of these hub genes in the gene network would result in significant phenotypic effects on T cells and examined this in vitro. The molecular interaction networks were then analyzed and visualized with Cytoscape. Jurkat and HeLa cells were transfected with siRNA for the selected hub genes. Cell proliferation was measured using ATP luminescence and BrdU labeling, which were measured 36, 72, and 96 h after activation. Following T cell stimulation, we found a significant decrease in ATP production (P < 0.05) when the hub genes ATP5C1 and PRKCZ were knocked down using siRNA transfection, whereas no difference in ATP production was observed in siRNA transfected HeLa cells. However, HeLa cells showed a significant (P < 0.05) decrease in cell proliferation when the genes MAPK1, IL6ST, ATP5C1, JUN, and FOS were knocked down. In both Jurkat and HeLa cells, targeted gene knockdown using siRNA showed decreased cell proliferation and ATP production in both Jurkat and HeLa cells. However, Jurkat T cells and HELA cells use different hub genes to regulate activation responses. This experiment provides proof of principle of applying siRNA knockdown of T cell hub genes to evaluate their proliferative capacity and ATP production. This novel concept outlines a systems biology approach to identify hub genes for targeted therapeutics. Published by Elsevier Inc.

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.

Analysis of trehalose-6-phosphate synthase (TPS) gene family suggests the formation of TPS complexes in rice.

PubMed

Zang, Baisheng; Li, Haowen; Li, Wenjun; Deng, Xing Wang; Wang, Xiping

2011-08-01

Trehalose-6-phosphate (T6P), an intermediate in the trehalose biosynthesis pathway, is emerging as an important regulator of plant metabolism and development. T6P levels are potentially modulated by a group of trehalose-6-phosphate synthase (TPS) and trehalose-6-phosphate phosphatase (TPP) homologues. In this study, we have isolated 11 TPS genes encoding proteins with both TPS and TPP domains, from rice. Functional complement assays performed in yeast tps1 and tps2 mutants, revealed that only OsTPS1 encodes an active TPS enzyme and no OsTPS protein possesses TPP activity. By using a yeast two-hybrid analysis, a complicated interaction network occurred among OsTPS proteins, and the TPS domain might be essential for this interaction to occur. The interaction between OsTPS1 and OsTPS8 in vivo was confirmed by bimolecular fluorescence complementation and coimmunoprecipitation assays. Furthermore, our gel filtration assay showed that there may exist two forms of OsTPS1 (OsTPS1a and OsTPS1b) with different elution profiles in rice. OsTPS1b was particularly cofractionated with OsTPS5 and OsTPS8 in the 360 kDa complex, while OsTPS1a was predominantly incorporated into the complexes larger than 360 kDa. Collectively, these results suggest that OsTPS family members may form trehalose-6-phosphate synthase complexes and therefore potentially modify T6P levels to regulate plant development.

A model for family-based case-control studies of genetic imprinting and epistasis.

PubMed

Li, Xin; Sui, Yihan; Liu, Tian; Wang, Jianxin; Li, Yongci; Lin, Zhenwu; Hegarty, John; Koltun, Walter A; Wang, Zuoheng; Wu, Rongling

2014-11-01

Genetic imprinting, or called the parent-of-origin effect, has been recognized to play an important role in the formation and pathogenesis of human diseases. Although the epigenetic mechanisms that establish genetic imprinting have been a focus of many genetic studies, our knowledge about the number of imprinting genes and their chromosomal locations and interactions with other genes is still scarce, limiting precise inference of the genetic architecture of complex diseases. In this article, we present a statistical model for testing and estimating the effects of genetic imprinting on complex diseases using a commonly used case-control design with family structure. For each subject sampled from a case and control population, we not only genotype its own single nucleotide polymorphisms (SNPs) but also collect its parents' genotypes. By tracing the transmission pattern of SNP alleles from parental to offspring generation, the model allows the characterization of genetic imprinting effects based on Pearson tests of a 2 × 2 contingency table. The model is expanded to test the interactions between imprinting effects and additive, dominant and epistatic effects in a complex web of genetic interactions. Statistical properties of the model are investigated, and its practical usefulness is validated by a real data analysis. The model will provide a useful tool for genome-wide association studies aimed to elucidate the picture of genetic control over complex human diseases. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

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

PubMed

Fletcher, Jason M; Conley, Dalton

2013-10-01

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

Budding Yeast Silencing Complexes and Regulation of Sir2 Activity by Protein-Protein Interactions

PubMed Central

Tanny, Jason C.; Kirkpatrick, Donald S.; Gerber, Scott A.; Gygi, Steven P.; Moazed, Danesh

2004-01-01

Gene silencing in the budding yeast Saccharomyces cerevisiae requires the enzymatic activity of the Sir2 protein, a highly conserved NAD-dependent deacetylase. In order to study the activity of native Sir2, we purified and characterized two budding yeast Sir2 complexes: the Sir2/Sir4 complex, which mediates silencing at mating-type loci and at telomeres, and the RENT complex, which mediates silencing at the ribosomal DNA repeats. Analyses of the protein compositions of these complexes confirmed previously described interactions. We show that the assembly of Sir2 into native silencing complexes does not alter its selectivity for acetylated substrates, nor does it allow the deacetylation of nucleosomal histones. The inability of Sir2 complexes to deacetylate nucleosomes suggests that additional factors influence Sir2 activity in vivo. In contrast, Sir2 complexes show significant enhancement in their affinities for acetylated substrates and their sensitivities to the physiological inhibitor nicotinamide relative to recombinant Sir2. Reconstitution experiments showed that, for the Sir2/Sir4 complex, these differences stem from the physical interaction of Sir2 with Sir4. Finally, we provide evidence that the different nicotinamide sensitivities of Sir2/Sir4 and RENT in vitro could contribute to locus-specific differences in how Sir2 activity is regulated in vivo. PMID:15282295

The interplay of post-translational modification and gene therapy.

PubMed

Osamor, Victor Chukwudi; Chinedu, Shalom N; Azuh, Dominic E; Iweala, Emeka Joshua; Ogunlana, Olubanke Olujoke

2016-01-01

Several proteins interact either to activate or repress the expression of other genes during transcription. Based on the impact of these activities, the proteins can be classified into readers, modifier writers, and modifier erasers depending on whether histone marks are read, added, or removed, respectively, from a specific amino acid. Transcription is controlled by dynamic epigenetic marks with serious health implications in certain complex diseases, whose understanding may be useful in gene therapy. This work highlights traditional and current advances in post-translational modifications with relevance to gene therapy delivery. We report that enhanced understanding of epigenetic machinery provides clues to functional implication of certain genes/gene products and may facilitate transition toward revision of our clinical treatment procedure with effective fortification of gene therapy delivery.

Inference on the Strength of Balancing Selection for Epistatically Interacting Loci

PubMed Central

Buzbas, Erkan Ozge; Joyce, Paul; Rosenberg, Noah A.

2011-01-01

Existing inference methods for estimating the strength of balancing selection in multi-locus genotypes rely on the assumption that there are no epistatic interactions between loci. Complex systems in which balancing selection is prevalent, such as sets of human immune system genes, are known to contain components that interact epistatically. Therefore, current methods may not produce reliable inference on the strength of selection at these loci. In this paper, we address this problem by presenting statistical methods that can account for epistatic interactions in making inference about balancing selection. A theoretical result due to Fearnhead (2006) is used to build a multi-locus Wright-Fisher model of balancing selection, allowing for epistatic interactions among loci. Antagonistic and synergistic types of interactions are examined. The joint posterior distribution of the selection and mutation parameters is sampled by Markov chain Monte Carlo methods, and the plausibility of models is assessed via Bayes factors. As a component of the inference process, an algorithm to generate multi-locus allele frequencies under balancing selection models with epistasis is also presented. Recent evidence on interactions among a set of human immune system genes is introduced as a motivating biological system for the epistatic model, and data on these genes are used to demonstrate the methods. PMID:21277883

Ecogeographic Genetic Epidemiology

PubMed Central

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

2009-01-01

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

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.

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

PubMed

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

2014-10-14

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

Nucleoporins and chromatin metabolism.

PubMed

Ptak, Christopher; Wozniak, Richard W

2016-06-01

Mounting evidence has implicated a group of proteins termed nucleoporins, or Nups, in various processes that regulate chromatin structure and function. Nups were first recognized as building blocks for nuclear pore complexes, but several members of this group of proteins also reside in the cytoplasm and within the nucleus. Moreover, many are dynamic and move between these various locations. Both at the nuclear envelope, as part of nuclear pore complexes, and within the nucleoplasm, Nups interact with protein complexes that function in gene transcription, chromatin remodeling, DNA repair, and DNA replication. Here, we review recent studies that provide further insight into the molecular details of these interactions and their role in regulating the activity of chromatin modifying factors. Copyright © 2016. Published by Elsevier Ltd.

Defining the human deubiquitinating enzyme interaction landscape.

PubMed

Sowa, Mathew E; Bennett, Eric J; Gygi, Steven P; Harper, J Wade

2009-07-23

Deubiquitinating enzymes (Dubs) function to remove covalently attached ubiquitin from proteins, thereby controlling substrate activity and/or abundance. For most Dubs, their functions, targets, and regulation are poorly understood. To systematically investigate Dub function, we initiated a global proteomic analysis of Dubs and their associated protein complexes. This was accomplished through the development of a software platform called CompPASS, which uses unbiased metrics to assign confidence measurements to interactions from parallel nonreciprocal proteomic data sets. We identified 774 candidate interacting proteins associated with 75 Dubs. Using Gene Ontology, interactome topology classification, subcellular localization, and functional studies, we link Dubs to diverse processes, including protein turnover, transcription, RNA processing, DNA damage, and endoplasmic reticulum-associated degradation. This work provides the first glimpse into the Dub interaction landscape, places previously unstudied Dubs within putative biological pathways, and identifies previously unknown interactions and protein complexes involved in this increasingly important arm of the ubiquitin-proteasome pathway.

Defining the Human Deubiquitinating Enzyme Interaction Landscape

PubMed Central

Sowa, Mathew E.; Bennett, Eric J.; Gygi, Steven P.; Harper, J. Wade

2009-01-01

Summary Deubiquitinating enzymes (Dubs) function to remove covalently attached ubiquitin from proteins, thereby controlling substrate activity and/or abundance. For most Dubs, their functions, targets, and regulation are poorly understood. To systematically investigate Dub function, we initiated a global proteomic analysis of Dubs and their associated protein complexes. This was accomplished through the development of a software platform, called CompPASS, which uses unbiased metrics to assign confidence measurements to interactions from parallel non-reciprocal proteomic datasets. We identified 774 candidate interacting proteins associated with 75 Dubs. Using Gene Ontology, interactome topology classification, sub-cellular localization and functional studies, we link Dubs to diverse processes, including protein turnover, transcription, RNA processing, DNA damage, and endoplasmic reticulum-associated degradation. This work provides the first glimpse into the Dub interaction landscape, places previously unstudied Dubs within putative biological pathways, and identifies previously unknown interactions and protein complexes involved in this increasingly important arm of the ubiquitin-proteasome pathway. PMID:19615732

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

PubMed

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

2003-11-01

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

A Julia set model of field-directed morphogenesis: developmental biology and artificial life.

PubMed

Levin, M

1994-04-01

One paradigm used in understanding the control of morphogenetic events is the concept of positional information, where sub-organismic components (such as cells) act in response to positional cues. It is important to determine what kinds of spatiotemporal patterns may be obtained by such a method, and what the characteristics of such a morphogenetic process might be. This paper presents a computer model of morphogenesis based on gene activity driven by interpreting a positional information field. In this model, the interactions of mutually regulating developmental genes are viewed as a map from R2 to R2, and are modeled by the complex number algebra. Functions in complex variables are used to simulate genetic interactions resulting in position-dependent differentiation. This is shown to be equivalent to computing modified Julia sets, and is seen to be sufficient to produce a very rich set of morphologies which are similar in appearance and several important characteristics to those of real organisms. The properties of this model can be used to study the potential role of fields and positional information as guiding factors in morphogenesis, as the model facilitates the study of static images, time-series (movies) and experimental alterations of the developmental process. It is thus shown that gene interactions can be modeled as a multi-dimensional algebra, and that only two interacting genes are sufficient for (i) complex pattern formation, (ii) chaotic differentiation behavior, and (iii) production of sharp edges from a continuous positional information field. This model is meant to elucidate the properties of the process of positional information-guided biomorphogenesis, not to serve as a simulation of any particular organism's development. Good quantitative data are not currently available on the interplay of gene products in morphogenesis. Thus, no attempt is made to link the images produced with actual pictures of any particular real organism. A brief introduction to top-down models and positional information is followed by the formal definition of the model. Then, the implications of the resulting morphologies to biological development are discussed, in terms of static shapes, parametrization studies, time series (movies made from individual frames), and behavior of the model in light of experimental perturbations. All figures (in grayscale), formulas and parameter values needed to re-create the figures and movies are included.

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

Revealing the potential pathogenesis of glioma by utilizing a glioma associated protein-protein interaction network.

PubMed

Pan, Weiran; Li, Gang; Yang, Xiaoxiao; Miao, Jinming

2015-04-01

This study aims to explore the potential mechanism of glioma through bioinformatic approaches. The gene expression profile (GSE4290) of glioma tumor and non-tumor samples was downloaded from Gene Expression Omnibus database. A total of 180 samples were available, including 23 non-tumor and 157 tumor samples. Then the raw data were preprocessed using robust multiarray analysis, and 8,890 differentially expressed genes (DEGs) were identified by using t-test (false discovery rate < 0.0005). Furthermore, 16 known glioma related genes were abstracted from Genetic Association Database. After mapping 8,890 DEGs and 16 known glioma related genes to Human Protein Reference Database, a glioma associated protein-protein interaction network (GAPN) was constructed. In addition, 51 sub-networks in GAPN were screened out through Molecular Complex Detection (score ≥ 1), and sub-network 1 was found to have the closest interaction (score = 3). What' more, for the top 10 sub-networks, Gene Ontology (GO) enrichment analysis (p value < 0.05) was performed, and DEGs involved in sub-network 1 and 2, such as BRMS1L and CCNA1, were predicted to regulate cell growth, cell cycle, and DNA replication via interacting with known glioma related genes. Finally, the overlaps of DEGs and human essential, housekeeping, tissue-specific genes were calculated (p value = 1.0, 1.0, and 0.00014, respectively) and visualized by Venn Diagram package in R. About 61% of human tissue-specific genes were DEGs as well. This research shed new light on the pathogenesis of glioma based on DEGs and GAPN, and our findings might provide potential targets for clinical glioma treatment.

Whole-Exome Sequencing Identifies Novel Variants for Tooth Agenesis.

PubMed

Dinckan, N; Du, R; Petty, L E; Coban-Akdemir, Z; Jhangiani, S N; Paine, I; Baugh, E H; Erdem, A P; Kayserili, H; Doddapaneni, H; Hu, J; Muzny, D M; Boerwinkle, E; Gibbs, R A; Lupski, J R; Uyguner, Z O; Below, J E; Letra, A

2018-01-01

Tooth agenesis is a common craniofacial abnormality in humans and represents failure to develop 1 or more permanent teeth. Tooth agenesis is complex, and variations in about a dozen genes have been reported as contributing to the etiology. Here, we combined whole-exome sequencing, array-based genotyping, and linkage analysis to identify putative pathogenic variants in candidate disease genes for tooth agenesis in 10 multiplex Turkish families. Novel homozygous and heterozygous variants in LRP6, DKK1, LAMA3, and COL17A1 genes, as well as known variants in WNT10A, were identified as likely pathogenic in isolated tooth agenesis. Novel variants in KREMEN1 were identified as likely pathogenic in 2 families with suspected syndromic tooth agenesis. Variants in more than 1 gene were identified segregating with tooth agenesis in 2 families, suggesting oligogenic inheritance. Structural modeling of missense variants suggests deleterious effects to the encoded proteins. Functional analysis of an indel variant (c.3607+3_6del) in LRP6 suggested that the predicted resulting mRNA is subject to nonsense-mediated decay. Our results support a major role for WNT pathways genes in the etiology of tooth agenesis while revealing new candidate genes. Moreover, oligogenic cosegregation was suggestive for complex inheritance and potentially complex gene product interactions during development, contributing to improved understanding of the genetic etiology of familial tooth agenesis.

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.