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Sample records for regulatory genes urinary

  1. The exocyst and regulatory GTPases in urinary exosomes.

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    Chacon-Heszele, Maria F; Choi, Soo Young; Zuo, Xiaofeng; Baek, Jeong-In; Ward, Chris; Lipschutz, Joshua H

    2014-08-01

    Cilia, organelles that function as cellular antennae, are central to the pathogenesis of "ciliopathies", including various forms of polycystic kidney disease (PKD). To date, however, the molecular mechanisms controlling ciliogenesis and ciliary function remain incompletely understood. A recently proposed model of cell-cell communication, called "urocrine signaling", hypothesizes that a subset of membrane bound vesicles that are secreted into the urinary stream (termed exosome-like vesicles, or ELVs), carry cilia-specific proteins as cargo, interact with primary cilia, and affect downstream cellular functions. This study was undertaken to determine the role of the exocyst, a highly conserved eight-protein trafficking complex, in the secretion and/or retrieval of ELVs. We used Madin-Darby canine kidney (MDCK) cells expressing either Sec10-myc (a central component of the exocyst complex) or Smoothened-YFP (a ciliary protein found in ELVs) in experiments utilizing electron gold microscopy and live fluorescent microscopy, respectively. Additionally, human urinary exosomes were isolated via ultracentrifugation and subjected to mass-spectrometry-based proteomics analysis to determine the composition of ELVs. We found, as determined by EM, that the exocyst localizes to primary cilia, and is present in vesicles attached to the cilium. Furthermore, the entire exocyst complex, as well as most of its known regulatory GTPases, are present in human urinary ELVs. Finally, in living MDCK cells, ELVs appear to interact with primary cilia using spinning disc confocal microscopy. These data suggest that the exocyst complex, in addition to its role in ciliogenesis, is centrally involved in the secretion and/or retrieval of urinary ELVs.

  2. Genetic variation in metallothionein and metal-regulatory transcription factor 1 in relation to urinary cadmium, copper, and zinc

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    Adams, Scott V.; Barrick, Brian; Freney, Emily P.; Shafer, Martin M.; Makar, Karen; Song, Xiaoling; Lampe, Johanna; Vilchis, Hugo; Ulery, April; Newcomb, Polly A.

    2015-01-01

    Background Metallothionein (MT) proteins play critical roles in the physiological handling of both essential (Cu and Zn) and toxic (Cd) metals. MT expression is regulated by metal-regulatory transcription factor 1 (MTF1). Hence, genetic variation in the MT gene family and MTF1 might therefore influence excretion of these metals. Methods 321 women were recruited in Seattle, WA and Las Cruces, NM and provided demographic information, urine samples for measurement of metal concentrations by mass spectrometry and creatinine, and blood or saliva for extraction of DNA. Forty-one single nucleotide polymorphisms (SNPs) within the MTF1 gene region and the region of chromosome 16 encoding the MT gene family were selected for genotyping in addition to an ancestry informative marker panel. Linear regression was used to estimate the association of SNPs with urinary Cd, Cu, and Zn, adjusted for age, urinary creatinine, smoking history, study site, and ancestry. Results Minor alleles of rs28366003 and rs10636 near the MT2A gene were associated with lower urinary Cd, Cu, and Zn. Minor alleles of rs8044719 and rs1599823, near MT1A and MT1B, were associated with lower urinary Cd and Zn, respectively. Minor alleles of rs4653329 in MTF1 was associated with lower urinary Cd. Conclusions These results suggest that genetic variation in the MT gene region and MTF1 influences urinary Cd, Cu, and Zn excretion. PMID:26529669

  3. Modeling of hysteresis in gene regulatory networks.

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    Hu, J; Qin, K R; Xiang, C; Lee, T H

    2012-08-01

    Hysteresis, observed in many gene regulatory networks, has a pivotal impact on biological systems, which enhances the robustness of cell functions. In this paper, a general model is proposed to describe the hysteretic gene regulatory network by combining the hysteresis component and the transient dynamics. The Bouc-Wen hysteresis model is modified to describe the hysteresis component in the mammalian gene regulatory networks. Rigorous mathematical analysis on the dynamical properties of the model is presented to ensure the bounded-input-bounded-output (BIBO) stability and demonstrates that the original Bouc-Wen model can only generate a clockwise hysteresis loop while the modified model can describe both clockwise and counter clockwise hysteresis loops. Simulation studies have shown that the hysteresis loops from our model are consistent with the experimental observations in three mammalian gene regulatory networks and two E.coli gene regulatory networks, which demonstrate the ability and accuracy of the mathematical model to emulate natural gene expression behavior with hysteresis. A comparison study has also been conducted to show that this model fits the experiment data significantly better than previous ones in the literature. The successful modeling of the hysteresis in all the five hysteretic gene regulatory networks suggests that the new model has the potential to be a unified framework for modeling hysteresis in gene regulatory networks and provide better understanding of the general mechanism that drives the hysteretic function.

  4. A study of bacterial gene regulatory mechanisms

    DEFF Research Database (Denmark)

    Hansen, Sabine

    the different regulatory mechanisms affect system dynamics. We have designed a synthetic gene regulatory network (GRN) in bacterial cells that enables us to study the dynamics of GRNs. The results presented in this PhD thesis show that model equations based on the established mechanisms of action of each...... of a particular type of regulatory mechanism. The synthetic system presented in this thesis is, to our knowledge, the first of its kind to allow a direct comparison of the dynamic behaviors of gene regulatory networks that employ different mechanisms of regulation. In addition to studying the dynamic behavior...... of GRNs this thesis also provided the first evidence of the sensor histidine kinase VC1831 being an additional player in the Vibrio cholerae quorum sensing (QS) GRN. Bacteria use a process of cell-cell communication called QS which enable the bacterial cells to collectively control their gene expression...

  5. Inferring latent gene regulatory network kinetics

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    González, Javier; Vujačić, Ivan; Wit, Ernst

    2013-01-01

    Regulatory networks consist of genes encoding transcription factors (TFs) and the genes they activate or repress. Various types of systems of ordinary differential equations (ODE) have been proposed to model these networks, ranging from linear to Michaelis-Menten approaches. In practice, a serious d

  6. Current approaches to gene regulatory network modelling

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    Brazma Alvis

    2007-09-01

    Full Text Available Abstract Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model.

  7. Gene regulatory mechanisms in infected fish

    DEFF Research Database (Denmark)

    Schyth, Brian Dall; Hajiabadi, Seyed Amir Hossein Jalali; Kristensen, Lasse Bøgelund Juel

    2011-01-01

    This talk will highlight the regulatory mechanisms of gene expression especially the programmed form of mRNA decay which is known as RNA interference (RNAi) and how this and other mechanisms contribute to the regulation of genes involved in immunity. In the RNAi mechanism small double stranded RNA...... whole pathways for the fine-tuning of physiological states like immunological reaction. But miRNAs are themselves under control of regulatory sequences for their timed expression. We will give an example of the finding of two rainbow trout microRNAs, which are up-regulated in the liver during infection...

  8. Evolution of evolvability in gene regulatory networks.

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    Anton Crombach

    Full Text Available Gene regulatory networks are perhaps the most important organizational level in the cell where signals from the cell state and the outside environment are integrated in terms of activation and inhibition of genes. For the last decade, the study of such networks has been fueled by large-scale experiments and renewed attention from the theoretical field. Different models have been proposed to, for instance, investigate expression dynamics, explain the network topology we observe in bacteria and yeast, and for the analysis of evolvability and robustness of such networks. Yet how these gene regulatory networks evolve and become evolvable remains an open question. An individual-oriented evolutionary model is used to shed light on this matter. Each individual has a genome from which its gene regulatory network is derived. Mutations, such as gene duplications and deletions, alter the genome, while the resulting network determines the gene expression pattern and hence fitness. With this protocol we let a population of individuals evolve under Darwinian selection in an environment that changes through time. Our work demonstrates that long-term evolution of complex gene regulatory networks in a changing environment can lead to a striking increase in the efficiency of generating beneficial mutations. We show that the population evolves towards genotype-phenotype mappings that allow for an orchestrated network-wide change in the gene expression pattern, requiring only a few specific gene indels. The genes involved are hubs of the networks, or directly influencing the hubs. Moreover, throughout the evolutionary trajectory the networks maintain their mutational robustness. In other words, evolution in an alternating environment leads to a network that is sensitive to a small class of beneficial mutations, while the majority of mutations remain neutral: an example of evolution of evolvability.

  9. Attribute Exploration of Gene Regulatory Processes

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    Wollbold, Johannes

    2012-01-01

    This thesis aims at the logical analysis of discrete processes, in particular of such generated by gene regulatory networks. States, transitions and operators from temporal logics are expressed in the language of Formal Concept Analysis. By the attribute exploration algorithm, an expert or a computer program is enabled to validate a minimal and complete set of implications, e.g. by comparison of predictions derived from literature with observed data. Here, these rules represent temporal dependencies within gene regulatory networks including coexpression of genes, reachability of states, invariants or possible causal relationships. This new approach is embedded into the theory of universal coalgebras, particularly automata, Kripke structures and Labelled Transition Systems. A comparison with the temporal expressivity of Description Logics is made. The main theoretical results concern the integration of background knowledge into the successive exploration of the defined data structures (formal contexts). Applyi...

  10. Gene regulatory networks governing pancreas development.

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    Arda, H Efsun; Benitez, Cecil M; Kim, Seung K

    2013-04-15

    Elucidation of cellular and gene regulatory networks (GRNs) governing organ development will accelerate progress toward tissue replacement. Here, we have compiled reference GRNs underlying pancreas development from data mining that integrates multiple approaches, including mutant analysis, lineage tracing, cell purification, gene expression and enhancer analysis, and biochemical studies of gene regulation. Using established computational tools, we integrated and represented these networks in frameworks that should enhance understanding of the surging output of genomic-scale genetic and epigenetic studies of pancreas development and diseases such as diabetes and pancreatic cancer. We envision similar approaches would be useful for understanding the development of other organs.

  11. Mutational robustness of gene regulatory networks.

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    Aalt D J van Dijk

    Full Text Available Mutational robustness of gene regulatory networks refers to their ability to generate constant biological output upon mutations that change network structure. Such networks contain regulatory interactions (transcription factor-target gene interactions but often also protein-protein interactions between transcription factors. Using computational modeling, we study factors that influence robustness and we infer several network properties governing it. These include the type of mutation, i.e. whether a regulatory interaction or a protein-protein interaction is mutated, and in the case of mutation of a regulatory interaction, the sign of the interaction (activating vs. repressive. In addition, we analyze the effect of combinations of mutations and we compare networks containing monomeric with those containing dimeric transcription factors. Our results are consistent with available data on biological networks, for example based on evolutionary conservation of network features. As a novel and remarkable property, we predict that networks are more robust against mutations in monomer than in dimer transcription factors, a prediction for which analysis of conservation of DNA binding residues in monomeric vs. dimeric transcription factors provides indirect evidence.

  12. Automated Identification of Core Regulatory Genes in Human Gene Regulatory Networks.

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    Vipin Narang

    Full Text Available Human gene regulatory networks (GRN can be difficult to interpret due to a tangle of edges interconnecting thousands of genes. We constructed a general human GRN from extensive transcription factor and microRNA target data obtained from public databases. In a subnetwork of this GRN that is active during estrogen stimulation of MCF-7 breast cancer cells, we benchmarked automated algorithms for identifying core regulatory genes (transcription factors and microRNAs. Among these algorithms, we identified K-core decomposition, pagerank and betweenness centrality algorithms as the most effective for discovering core regulatory genes in the network evaluated based on previously known roles of these genes in MCF-7 biology as well as in their ability to explain the up or down expression status of up to 70% of the remaining genes. Finally, we validated the use of K-core algorithm for organizing the GRN in an easier to interpret layered hierarchy where more influential regulatory genes percolate towards the inner layers. The integrated human gene and miRNA network and software used in this study are provided as supplementary materials (S1 Data accompanying this manuscript.

  13. A study of bacterial gene regulatory mechanisms

    DEFF Research Database (Denmark)

    Hansen, Sabine

    regulator studied accurately reproduced the experimental data. Simulations of system dynamics reveals that even two step regulatory cascades significantly increase response times compared to direct allosteric regulation of a transcription factor. It is observed that while many system behaviors...... of GRNs this thesis also provided the first evidence of the sensor histidine kinase VC1831 being an additional player in the Vibrio cholerae quorum sensing (QS) GRN. Bacteria use a process of cell-cell communication called QS which enable the bacterial cells to collectively control their gene expression...

  14. Selection on Coding and Regulatory Variation Maintains Individuality in Major Urinary Protein Scent Marks in Wild Mice.

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    Michael J Sheehan

    2016-03-01

    Full Text Available Recognition of individuals by scent is widespread across animal taxa. Though animals can often discriminate chemical blends based on many compounds, recent work shows that specific protein pheromones are necessary and sufficient for individual recognition via scent marks in mice. The genetic nature of individuality in scent marks (e.g. coding versus regulatory variation and the evolutionary processes that maintain diversity are poorly understood. The individual signatures in scent marks of house mice are the protein products of a group of highly similar paralogs in the major urinary protein (Mup gene family. Using the offspring of wild-caught mice, we examine individuality in the major urinary protein (MUP scent marks at the DNA, RNA and protein levels. We show that individuality arises through a combination of variation at amino acid coding sites and differential transcription of central Mup genes across individuals, and we identify eSNPs in promoters. There is no evidence of post-transcriptional processes influencing phenotypic diversity as transcripts accurately predict the relative abundance of proteins in urine samples. The match between transcripts and urine samples taken six months earlier also emphasizes that the proportional relationships across central MUP isoforms in urine is stable. Balancing selection maintains coding variants at moderate frequencies, though pheromone diversity appears limited by interactions with vomeronasal receptors. We find that differential transcription of the central Mup paralogs within and between individuals significantly increases the individuality of pheromone blends. Balancing selection on gene regulation allows for increased individuality via combinatorial diversity in a limited number of pheromones.

  15. Simple mathematical models of gene regulatory dynamics

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    Mackey, Michael C; Tyran-Kamińska, Marta; Zeron, Eduardo S

    2016-01-01

    This is a short and self-contained introduction to the field of mathematical modeling of gene-networks in bacteria. As an entry point to the field, we focus on the analysis of simple gene-network dynamics. The notes commence with an introduction to the deterministic modeling of gene-networks, with extensive reference to applicable results coming from dynamical systems theory. The second part of the notes treats extensively several approaches to the study of gene-network dynamics in the presence of noise—either arising from low numbers of molecules involved, or due to noise external to the regulatory process. The third and final part of the notes gives a detailed treatment of three well studied and concrete examples of gene-network dynamics by considering the lactose operon, the tryptophan operon, and the lysis-lysogeny switch. The notes contain an index for easy location of particular topics as well as an extensive bibliography of the current literature. The target audience of these notes are mainly graduat...

  16. Compressed Adjacency Matrices: Untangling Gene Regulatory Networks.

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    Dinkla, K; Westenberg, M A; van Wijk, J J

    2012-12-01

    We present a novel technique-Compressed Adjacency Matrices-for visualizing gene regulatory networks. These directed networks have strong structural characteristics: out-degrees with a scale-free distribution, in-degrees bound by a low maximum, and few and small cycles. Standard visualization techniques, such as node-link diagrams and adjacency matrices, are impeded by these network characteristics. The scale-free distribution of out-degrees causes a high number of intersecting edges in node-link diagrams. Adjacency matrices become space-inefficient due to the low in-degrees and the resulting sparse network. Compressed adjacency matrices, however, exploit these structural characteristics. By cutting open and rearranging an adjacency matrix, we achieve a compact and neatly-arranged visualization. Compressed adjacency matrices allow for easy detection of subnetworks with a specific structure, so-called motifs, which provide important knowledge about gene regulatory networks to domain experts. We summarize motifs commonly referred to in the literature, and relate them to network analysis tasks common to the visualization domain. We show that a user can easily find the important motifs in compressed adjacency matrices, and that this is hard in standard adjacency matrix and node-link diagrams. We also demonstrate that interaction techniques for standard adjacency matrices can be used for our compressed variant. These techniques include rearrangement clustering, highlighting, and filtering.

  17. Measuring Escherichia coli Gene Expression during Human Urinary Tract Infections

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    Mobley, Harry L. T.

    2016-01-01

    Extraintestinal Escherichia coli (E. coli) evolved by acquisition of pathogenicity islands, phage, plasmids, and DNA segments by horizontal gene transfer. Strains are heterogeneous but virulent uropathogenic isolates more often have specific fimbriae, toxins, and iron receptors than commensal strains. One may ask whether it is the virulence factors alone that are required to establish infection. While these virulence factors clearly contribute strongly to pathogenesis, bacteria must survive by metabolizing nutrients available to them. By constructing mutants in all major metabolic pathways and co-challenging mice transurethrally with each mutant and the wild type strain, we identified which major metabolic pathways are required to infect the urinary tract. We must also ask what else is E. coli doing in vivo? To answer this question, we examined the transcriptome of E. coli CFT073 in the murine model of urinary tract infection (UTI) as well as for E. coli strains collected and analyzed directly from the urine of patients attending either a urology clinic or a university health clinic for symptoms of UTI. Using microarrays and RNA-seq, we measured in vivo gene expression for these uropathogenic E. coli strains, identifying genes upregulated during murine and human UTI. Our findings allow us to propose a new definition of bacterial virulence. PMID:26784237

  18. T-Box Genes in the Kidney and Urinary Tract.

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    Kispert, A

    2017-01-01

    T-box (Tbx) genes encode an ancient group of transcription factors that play important roles in patterning, specification, proliferation, and differentiation programs in vertebrate organogenesis. This is testified by severe organ malformation syndromes in mice homozygous for engineered null alleles of specific T-box genes and by the large number of human inherited organ-specific diseases that have been linked to mutations in these genes. One of the organ systems that has not been associated with loss of specific T-box gene function in human disease for long is the excretory system. However, this has changed with the finding that mutations in TBX18, a member of a vertebrate-specific subgroup within the Tbx1-subfamily of T-box transcription factor genes, cause congenital anomalies of the kidney and urinary tract, predominantly hydroureter and ureteropelvic junction obstruction. Gene expression analyses, loss-of-function studies, and lineage tracing in the mouse suggest a primary role for this transcription factor in specifying the ureteric mesenchyme in the common anlage of the kidney, the ureter, and the bladder. We review the function of Tbx18 in ureterogenesis and discuss the body of evidence that Tbx18 and other members of the T-box gene family, namely, Tbx1, Tbx2, Tbx3, and Tbx20, play additional roles in development and homeostasis of other components of the excretory system in vertebrates.

  19. Inferring slowly-changing dynamic gene-regulatory networks

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    Wit, Ernst C.; Abbruzzo, Antonino

    2015-01-01

    Dynamic gene-regulatory networks are complex since the interaction patterns between their components mean that it is impossible to study parts of the network in separation. This holistic character of gene-regulatory networks poses a real challenge to any type of modelling. Graphical models are a cla

  20. Regulatory considerations for translating gene therapy: a European Union perspective.

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    Galli, Maria Cristina

    2009-11-11

    A preclinical study on a gene therapy approach for treatment of the severe muscle weakness associated with a variety of neuromuscular disorders provides a forum to discuss the translational challenges of gene therapy from a regulatory point of view. In this Perspective, the findings are considered from the view of European regulatory requirements for first clinical use.

  1. Chaotic motifs in gene regulatory networks.

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    Zhang, Zhaoyang; Ye, Weiming; Qian, Yu; Zheng, Zhigang; Huang, Xuhui; Hu, Gang

    2012-01-01

    Chaos should occur often in gene regulatory networks (GRNs) which have been widely described by nonlinear coupled ordinary differential equations, if their dimensions are no less than 3. It is therefore puzzling that chaos has never been reported in GRNs in nature and is also extremely rare in models of GRNs. On the other hand, the topic of motifs has attracted great attention in studying biological networks, and network motifs are suggested to be elementary building blocks that carry out some key functions in the network. In this paper, chaotic motifs (subnetworks with chaos) in GRNs are systematically investigated. The conclusion is that: (i) chaos can only appear through competitions between different oscillatory modes with rivaling intensities. Conditions required for chaotic GRNs are found to be very strict, which make chaotic GRNs extremely rare. (ii) Chaotic motifs are explored as the simplest few-node structures capable of producing chaos, and serve as the intrinsic source of chaos of random few-node GRNs. Several optimal motifs causing chaos with atypically high probability are figured out. (iii) Moreover, we discovered that a number of special oscillators can never produce chaos. These structures bring some advantages on rhythmic functions and may help us understand the robustness of diverse biological rhythms. (iv) The methods of dominant phase-advanced driving (DPAD) and DPAD time fraction are proposed to quantitatively identify chaotic motifs and to explain the origin of chaotic behaviors in GRNs.

  2. Toward an orofacial gene regulatory network.

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    Kousa, Youssef A; Schutte, Brian C

    2016-03-01

    Orofacial clefting is a common birth defect with significant morbidity. A panoply of candidate genes have been discovered through synergy of animal models and human genetics. Among these, variants in interferon regulatory factor 6 (IRF6) cause syndromic orofacial clefting and contribute risk toward isolated cleft lip and palate (1/700 live births). Rare variants in IRF6 can lead to Van der Woude syndrome (1/35,000 live births) and popliteal pterygium syndrome (1/300,000 live births). Furthermore, IRF6 regulates GRHL3 and rare variants in this downstream target can also lead to Van der Woude syndrome. In addition, a common variant (rs642961) in the IRF6 locus is found in 30% of the world's population and contributes risk for isolated orofacial clefting. Biochemical studies revealed that rs642961 abrogates one of four AP-2alpha binding sites. Like IRF6 and GRHL3, rare variants in TFAP2A can also lead to syndromic orofacial clefting with lip pits (branchio-oculo-facial syndrome). The literature suggests that AP-2alpha, IRF6 and GRHL3 are part of a pathway that is essential for lip and palate development. In addition to updating the pathways, players and pursuits, this review will highlight some of the current questions in the study of orofacial clefting.

  3. Global properties and functional complexity of human gene regulatory variation.

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    Daniel J Gaffney

    2013-05-01

    Full Text Available Identification and functional interpretation of gene regulatory variants is a major focus of modern genomics. The application of genetic mapping to molecular and cellular traits has enabled the detection of regulatory variation on genome-wide scales and revealed an enormous diversity of regulatory architecture in humans and other species. In this review I summarise the insights gained and questions raised by a decade of genetic mapping of gene expression variation. I discuss recent extensions of this approach using alternative molecular phenotypes that have revealed some of the biological mechanisms that drive gene expression variation between individuals. Finally, I highlight outstanding problems and future directions for development.

  4. Gene regulatory network inference using out of equilibrium statistical mechanics.

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    Benecke, Arndt

    2008-08-01

    Spatiotemporal control of gene expression is fundamental to multicellular life. Despite prodigious efforts, the encoding of gene expression regulation in eukaryotes is not understood. Gene expression analyses nourish the hope to reverse engineer effector-target gene networks using inference techniques. Inference from noisy and circumstantial data relies on using robust models with few parameters for the underlying mechanisms. However, a systematic path to gene regulatory network reverse engineering from functional genomics data is still impeded by fundamental problems. Recently, Johannes Berg from the Theoretical Physics Institute of Cologne University has made two remarkable contributions that significantly advance the gene regulatory network inference problem. Berg, who uses gene expression data from yeast, has demonstrated a nonequilibrium regime for mRNA concentration dynamics and was able to map the gene regulatory process upon simple stochastic systems driven out of equilibrium. The impact of his demonstration is twofold, affecting both the understanding of the operational constraints under which transcription occurs and the capacity to extract relevant information from highly time-resolved expression data. Berg has used his observation to predict target genes of selected transcription factors, and thereby, in principle, demonstrated applicability of his out of equilibrium statistical mechanics approach to the gene network inference problem.

  5. Evolutionary conservation of regulatory elements in vertebrate HOX gene clusters

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    Santini, Simona; Boore, Jeffrey L.; Meyer, Axel

    2003-12-31

    Due to their high degree of conservation, comparisons of DNA sequences among evolutionarily distantly-related genomes permit to identify functional regions in noncoding DNA. Hox genes are optimal candidate sequences for comparative genome analyses, because they are extremely conserved in vertebrates and occur in clusters. We aligned (Pipmaker) the nucleotide sequences of HoxA clusters of tilapia, pufferfish, striped bass, zebrafish, horn shark, human and mouse (over 500 million years of evolutionary distance). We identified several highly conserved intergenic sequences, likely to be important in gene regulation. Only a few of these putative regulatory elements have been previously described as being involved in the regulation of Hox genes, while several others are new elements that might have regulatory functions. The majority of these newly identified putative regulatory elements contain short fragments that are almost completely conserved and are identical to known binding sites for regulatory proteins (Transfac). The conserved intergenic regions located between the most rostrally expressed genes in the developing embryo are longer and better retained through evolution. We document that presumed regulatory sequences are retained differentially in either A or A clusters resulting from a genome duplication in the fish lineage. This observation supports both the hypothesis that the conserved elements are involved in gene regulation and the Duplication-Deletion-Complementation model.

  6. [Enzymatic regulatory processes in gene recombination].

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    Kovarskiĭ, V A; Profir, A V

    1988-01-01

    Recombination bistability in the system of genetic regulation in pro- and eucaryots is analysed on the basis of sigmoid kinetics of regulatory enzymes. It is shown that under an increase of either exogenic factors (temperature) or endogenic factors (concentration of molecules, which activate the enzymes) of crucial values, bistability solutions for recombination frequencies are possible. Histeresic character of the dependence of this value on the external parameters is pointed out. The role of fluctuation processes in distortion of the memory effects is discussed. On the basis of monostable solutions molecular account for the empiric Plau law is given for U-shaped dependence of recombination frequency on temperature.

  7. Regulatory Divergence among Beta-Keratin Genes during Bird Evolution.

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    Bhattacharjee, Maloyjo Joyraj; Yu, Chun-Ping; Lin, Jinn-Jy; Ng, Chen Siang; Wang, Tzi-Yuan; Lin, Hsin-Hung; Li, Wen-Hsiung

    2016-11-01

    Feathers, which are mainly composed of α- and β-keratins, are highly diversified, largely owing to duplication and diversification of β-keratin genes during bird evolution. However, little is known about the regulatory changes that contributed to the expressional diversification of β-keratin genes. To address this issue, we studied transcriptomes from five different parts of chicken contour and flight feathers. From these transcriptomes we inferred β-keratin enriched co-expression modules of genes and predicted transcription factors (TFs) of β-keratin genes. In total, we predicted 262 TF-target gene relationships in which 56 TFs regulate 91 β-keratin genes; we validated 14 of them by in vitro tests. A dual criterion of TF enrichment and "TF-target gene" expression correlation identified 26 TFs as the major regulators of β-keratin genes. According to our predictions, the ancestral scale and claw β-keratin genes have common and unique regulators, whereas most feather β-keratin genes show chromosome-wise regulation, distinct from scale and claw β-keratin genes. Thus, after expansion from the β-keratin gene on Chr7 to other chromosomes, which still shares a TF with scale and claw β-keratin genes, most feather β-keratin genes have recruited distinct or chromosome-specific regulators. Moreover, our data showed correlated gene expression profiles, positive or negative, between predicted TFs and their target genes over the five studied feather regions. Therefore, regulatory divergences among feather β-keratin genes have contributed to structural differences among different parts of feathers. Our study sheds light on how feather β-keratin genes have diverged in regulation from scale and claw β-keratin genes and among themselves. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  8. Gene regulatory mechanisms in infected fish

    DEFF Research Database (Denmark)

    Schyth, Brian Dall; Hajiabadi, Seyed Amir Hossein Jalali; Kristensen, Lasse Bøgelund Juel;

    2011-01-01

    miRNAs) are one class of such small RNAs which are expressed from the genome. The RISC system allows for non-perfect base pairing of miRNAs to their target genes why one small RNA can in theory silence large groups of genes at the same time. It is therefore anticipated that they are able to depress...... seem to show that these microRNAs are only expressed above a certain stage in the development of the fish....

  9. Estrous cycle dependent fluctuations of regulatory neuropeptides in the lower urinary tract of female rats upon colon-bladder cross-sensitization.

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    Xiao-Qing Pan

    Full Text Available Co-morbidity of bladder, bowel, and non-specific pelvic pain symptoms is highly prevalent in women. Little evidence is present on modulation of pelvic pain syndromes by sex hormones, therefore, the objective of this study was to clarify the effects of hormonal fluctuations within the estrous cycle on regulatory neuropeptides in female rats using a model of neurogenic bladder dysfunction. The estrous cycle in female rats (Sprague-Dawley, 230-250 g was assessed by vaginal smears and weight of uterine horns. Neurogenic bladder dysfunction was induced by a single inflammatory insult to the distal colon. Protein expression of calcitonin gene related peptide (CGRP, substance P (SP, nerve growth factor (NGF, and brain derived neurotrophic factor (BDNF in the pelvic organs, sensory ganglia and lumbosacral spinal cord was compared in rats in proestrus (high estrogen vs diestrus (low estrogen. Under normal physiological conditions, concentration of SP and CGRP was similar in the distal colon and urinary bladder during all phases of the estrous cycle, however, acute colitis induced a significant up-regulation of CGRP content in the colon (by 63% and urinary bladder (by 54%, p≤0.05 to control of rats in proestrus. These changes were accompanied by a significant diminution of CGRP content in L6-S2 DRG after colonic treatment, likely associated with its release in the periphery. In rats with high estrogen at the time of testing (proestrus, experimental colitis caused a significant up-regulation of BDNF colonic content from 26.1±8.5 pg/ml to 83.4±32.5 pg/ml (N = 7, p≤0.05 to control and also induced similar effects on BDNF in the urinary bladder which was also up-regulated by 5-fold in rats in proestrus (p≤0.05 to respective control. Our results demonstrate estrous cycle dependent fluctuations of regulatory neuropeptides in the lower urinary tract upon colon-bladder cross-sensitization, which may contribute to pain fluctuations in female patients

  10. Gene regulatory networks elucidating huanglongbing disease mechanisms.

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    Martinelli, Federico; Reagan, Russell L; Uratsu, Sandra L; Phu, My L; Albrecht, Ute; Zhao, Weixiang; Davis, Cristina E; Bowman, Kim D; Dandekar, Abhaya M

    2013-01-01

    Next-generation sequencing was exploited to gain deeper insight into the response to infection by Candidatus liberibacter asiaticus (CaLas), especially the immune disregulation and metabolic dysfunction caused by source-sink disruption. Previous fruit transcriptome data were compared with additional RNA-Seq data in three tissues: immature fruit, and young and mature leaves. Four categories of orchard trees were studied: symptomatic, asymptomatic, apparently healthy, and healthy. Principal component analysis found distinct expression patterns between immature and mature fruits and leaf samples for all four categories of trees. A predicted protein - protein interaction network identified HLB-regulated genes for sugar transporters playing key roles in the overall plant responses. Gene set and pathway enrichment analyses highlight the role of sucrose and starch metabolism in disease symptom development in all tissues. HLB-regulated genes (glucose-phosphate-transporter, invertase, starch-related genes) would likely determine the source-sink relationship disruption. In infected leaves, transcriptomic changes were observed for light reactions genes (downregulation), sucrose metabolism (upregulation), and starch biosynthesis (upregulation). In parallel, symptomatic fruits over-expressed genes involved in photosynthesis, sucrose and raffinose metabolism, and downregulated starch biosynthesis. We visualized gene networks between tissues inducing a source-sink shift. CaLas alters the hormone crosstalk, resulting in weak and ineffective tissue-specific plant immune responses necessary for bacterial clearance. Accordingly, expression of WRKYs (including WRKY70) was higher in fruits than in leaves. Systemic acquired responses were inadequately activated in young leaves, generally considered the sites where most new infections occur.

  11. Research of Gene Regulatory Network with Multi-Time Delay Based on Bayesian Network

    Institute of Scientific and Technical Information of China (English)

    LIU Bei; MENG Fanjiang; LI Yong; LIU Liyan

    2008-01-01

    The gene regulatory network was reconstructed according to time-series microarray data getting from hybridization at different time between gene chips to analyze coordination and restriction between genes. An algorithm for controlling the gene expression regulatory network of the whole cell was designed using Bayesian network which provides an effective aided analysis for gene regulatory network.

  12. Glucocorticoid receptor-dependent gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Phillip Phuc Le

    2005-08-01

    Full Text Available While the molecular mechanisms of glucocorticoid regulation of transcription have been studied in detail, the global networks regulated by the glucocorticoid receptor (GR remain unknown. To address this question, we performed an orthogonal analysis to identify direct targets of the GR. First, we analyzed the expression profile of mouse livers in the presence or absence of exogenous glucocorticoid, resulting in over 1,300 differentially expressed genes. We then executed genome-wide location analysis on chromatin from the same livers, identifying more than 300 promoters that are bound by the GR. Intersecting the two lists yielded 53 genes whose expression is functionally dependent upon the ligand-bound GR. Further network and sequence analysis of the functional targets enabled us to suggest interactions between the GR and other transcription factors at specific target genes. Together, our results further our understanding of the GR and its targets, and provide the basis for more targeted glucocorticoid therapies.

  13. The incorporation of epigenetics in artificial gene regulatory networks.

    Science.gov (United States)

    Turner, Alexander P; Lones, Michael A; Fuente, Luis A; Stepney, Susan; Caves, Leo S D; Tyrrell, Andy M

    2013-05-01

    Artificial gene regulatory networks are computational models that draw inspiration from biological networks of gene regulation. Since their inception they have been used to infer knowledge about gene regulation and as methods of computation. These computational models have been shown to possess properties typically found in the biological world, such as robustness and self organisation. Recently, it has become apparent that epigenetic mechanisms play an important role in gene regulation. This paper describes a new model, the Artificial Epigenetic Regulatory Network (AERN) which builds upon existing models by adding an epigenetic control layer. Our results demonstrate that AERNs are more adept at controlling multiple opposing trajectories when applied to a chaos control task within a conservative dynamical system, suggesting that AERNs are an interesting area for further investigation.

  14. Discovering Study-Specific Gene Regulatory Networks

    OpenAIRE

    2014-01-01

    This article has been made available through the Brunel Open Access Publishing Fund. This article has been made available through the Brunel Open Access Publishing Fund. Microarrays are commonly used in biology because of their ability to simultaneously measure thousands of genes under different conditions. Due to their structure, typically containing a high amount of variables but far fewer samples, scalable network analysis techniques are often employed. In particular, consensus appro...

  15. Noise Control in Gene Regulatory Networks with Negative Feedback.

    Science.gov (United States)

    Hinczewski, Michael; Thirumalai, D

    2016-07-01

    Genes and proteins regulate cellular functions through complex circuits of biochemical reactions. Fluctuations in the components of these regulatory networks result in noise that invariably corrupts the signal, possibly compromising function. Here, we create a practical formalism based on ideas introduced by Wiener and Kolmogorov (WK) for filtering noise in engineered communications systems to quantitatively assess the extent to which noise can be controlled in biological processes involving negative feedback. Application of the theory, which reproduces the previously proven scaling of the lower bound for noise suppression in terms of the number of signaling events, shows that a tetracycline repressor-based negative-regulatory gene circuit behaves as a WK filter. For the class of Hill-like nonlinear regulatory functions, this type of filter provides the optimal reduction in noise. Our theoretical approach can be readily combined with experimental measurements of response functions in a wide variety of genetic circuits, to elucidate the general principles by which biological networks minimize noise.

  16. A gene regulatory network armature for T-lymphocyte specification

    Energy Technology Data Exchange (ETDEWEB)

    Fung, Elizabeth-sharon [Los Alamos National Laboratory

    2008-01-01

    Choice of a T-lymphoid fate by hematopoietic progenitor cells depends on sustained Notch-Delta signaling combined with tightly-regulated activities of multiple transcription factors. To dissect the regulatory network connections that mediate this process, we have used high-resolution analysis of regulatory gene expression trajectories from the beginning to the end of specification; tests of the short-term Notchdependence of these gene expression changes; and perturbation analyses of the effects of overexpression of two essential transcription factors, namely PU.l and GATA-3. Quantitative expression measurements of >50 transcription factor and marker genes have been used to derive the principal components of regulatory change through which T-cell precursors progress from primitive multipotency to T-lineage commitment. Distinct parts of the path reveal separate contributions of Notch signaling, GATA-3 activity, and downregulation of PU.l. Using BioTapestry, the results have been assembled into a draft gene regulatory network for the specification of T-cell precursors and the choice of T as opposed to myeloid dendritic or mast-cell fates. This network also accommodates effects of E proteins and mutual repression circuits of Gfil against Egr-2 and of TCF-l against PU.l as proposed elsewhere, but requires additional functions that remain unidentified. Distinctive features of this network structure include the intense dose-dependence of GATA-3 effects; the gene-specific modulation of PU.l activity based on Notch activity; the lack of direct opposition between PU.l and GATA-3; and the need for a distinct, late-acting repressive function or functions to extinguish stem and progenitor-derived regulatory gene expression.

  17. Gene expression in the urinary bladder: a common carcinoma in situ gene expression signature exists disregarding histopathological classification

    DEFF Research Database (Denmark)

    Andersen, Lars Dyrskjøt; Kruhøffer, Mogens; Andersen, Thomas Thykjær

    2004-01-01

    The presence of carcinoma in situ (CIS) lesions in the urinary bladder is associated with a high risk of disease progression to a muscle invasive stage. In this study, we used microarray expression profiling to examine the gene expression patterns in superficial transitional cell carcinoma (s...... urothelium and urothelium with CIS lesions from the same urinary bladder revealed that the gene expression found in sTCC with surrounding CIS is found also in CIS biopsies as well as in histologically normal samples adjacent to the CIS lesions. Furthermore, we also identified similar gene expression changes...

  18. Molecular characterization of a maize regulatory gene

    Energy Technology Data Exchange (ETDEWEB)

    Wessler, S.R.

    1991-12-01

    Based on initial bombardment studies we have previously concluded that promoter diversity was responsible for the diversity of naturally occurring R alleles. During this period we have found that R is controlled at the level of translation initiation and intron 1 is alternatively spliced. The experiments described in Sections 1 and 2 sought to quantify these effects and to determine whether they contribute to the tissue specific expression of select R alleles. This study was done because very little is understood about the post-transcriptional regulation of plant genes. Section 3 and 4 describe experiments designed to identify important structural components of the R protein.

  19. Blueprinting the regulatory response of Escherichia coli to the urinary tract.

    Science.gov (United States)

    Seed, Patrick C; Hultgren, Scott J

    2005-06-01

    Recent work has shown how comparative genomic and microarray analyses can provide insights into the transcriptional state of uropathogenic Escherichia coli (UPEC) during infection. This study will serve as an important platform from which to identify virulence determinants and the principle mechanisms of adaptation to the urinary tract.

  20. Inferring slowly-changing dynamic gene-regulatory networks.

    Science.gov (United States)

    Wit, Ernst C; Abbruzzo, Antonino

    2015-01-01

    Dynamic gene-regulatory networks are complex since the interaction patterns between their components mean that it is impossible to study parts of the network in separation. This holistic character of gene-regulatory networks poses a real challenge to any type of modelling. Graphical models are a class of models that connect the network with a conditional independence relationships between random variables. By interpreting these random variables as gene activities and the conditional independence relationships as functional non-relatedness, graphical models have been used to describe gene-regulatory networks. Whereas the literature has been focused on static networks, most time-course experiments are designed in order to tease out temporal changes in the underlying network. It is typically reasonable to assume that changes in genomic networks are few, because biological systems tend to be stable. We introduce a new model for estimating slow changes in dynamic gene-regulatory networks, which is suitable for high-dimensional data, e.g. time-course microarray data. Our aim is to estimate a dynamically changing genomic network based on temporal activity measurements of the genes in the network. Our method is based on the penalized likelihood with l1-norm, that penalizes conditional dependencies between genes as well as differences between conditional independence elements across time points. We also present a heuristic search strategy to find optimal tuning parameters. We re-write the penalized maximum likelihood problem into a standard convex optimization problem subject to linear equality constraints. We show that our method performs well in simulation studies. Finally, we apply the proposed model to a time-course T-cell dataset.

  1. Deduced products of C4-dicarboxylate transport regulatory genes of Rhizobium leguminosarum are homologous to nitrogen regulatory gene products.

    OpenAIRE

    Ronson, C W; Astwood, P M; Nixon, B T; Ausubel, F M

    1987-01-01

    We have sequenced two genes dctB and dctD required for the activation of the C4-dicarboxylate transport structural gene dctA in free-living Rhizobium leguminosarum. The hydropathic profile of the dctB gene product (DctB) suggested that its N-terminal region may be located in the periplasm and its C-terminal region in the cytoplasm. The C-terminal region of DctB was strongly conserved with similar regions of the products of several regulatory genes that may act as environmental sensors, includ...

  2. Deduced products of C4-dicarboxylate transport regulatory genes of Rhizobium leguminosarum are homologous to nitrogen regulatory gene products.

    OpenAIRE

    Ronson, C W; Astwood, P M; Nixon, B T; Ausubel, F M

    1987-01-01

    We have sequenced two genes dctB and dctD required for the activation of the C4-dicarboxylate transport structural gene dctA in free-living Rhizobium leguminosarum. The hydropathic profile of the dctB gene product (DctB) suggested that its N-terminal region may be located in the periplasm and its C-terminal region in the cytoplasm. The C-terminal region of DctB was strongly conserved with similar regions of the products of several regulatory genes that may act as environmental sensors, includ...

  3. Gene Regulatory Network Reconstruction Using Conditional Mutual Information

    Directory of Open Access Journals (Sweden)

    Xiaodong Wang

    2008-06-01

    Full Text Available The inference of gene regulatory network from expression data is an important area of research that provides insight to the inner workings of a biological system. The relevance-network-based approaches provide a simple and easily-scalable solution to the understanding of interaction between genes. Up until now, most works based on relevance network focus on the discovery of direct regulation using correlation coefficient or mutual information. However, some of the more complicated interactions such as interactive regulation and coregulation are not easily detected. In this work, we propose a relevance network model for gene regulatory network inference which employs both mutual information and conditional mutual information to determine the interactions between genes. For this purpose, we propose a conditional mutual information estimator based on adaptive partitioning which allows us to condition on both discrete and continuous random variables. We provide experimental results that demonstrate that the proposed regulatory network inference algorithm can provide better performance when the target network contains coregulated and interactively regulated genes.

  4. How difficult is inference of mammalian causal gene regulatory networks?

    Directory of Open Access Journals (Sweden)

    Djordje Djordjevic

    Full Text Available Gene regulatory networks (GRNs play a central role in systems biology, especially in the study of mammalian organ development. One key question remains largely unanswered: Is it possible to infer mammalian causal GRNs using observable gene co-expression patterns alone? We assembled two mouse GRN datasets (embryonic tooth and heart and matching microarray gene expression profiles to systematically investigate the difficulties of mammalian causal GRN inference. The GRNs were assembled based on > 2,000 pieces of experimental genetic perturbation evidence from manually reading > 150 primary research articles. Each piece of perturbation evidence records the qualitative change of the expression of one gene following knock-down or over-expression of another gene. Our data have thorough annotation of tissue types and embryonic stages, as well as the type of regulation (activation, inhibition and no effect, which uniquely allows us to estimate both sensitivity and specificity of the inference of tissue specific causal GRN edges. Using these unprecedented datasets, we found that gene co-expression does not reliably distinguish true positive from false positive interactions, making inference of GRN in mammalian development very difficult. Nonetheless, if we have expression profiling data from genetic or molecular perturbation experiments, such as gene knock-out or signalling stimulation, it is possible to use the set of differentially expressed genes to recover causal regulatory relationships with good sensitivity and specificity. Our result supports the importance of using perturbation experimental data in causal network reconstruction. Furthermore, we showed that causal gene regulatory relationship can be highly cell type or developmental stage specific, suggesting the importance of employing expression profiles from homogeneous cell populations. This study provides essential datasets and empirical evidence to guide the development of new GRN inference

  5. How difficult is inference of mammalian causal gene regulatory networks?

    Science.gov (United States)

    Djordjevic, Djordje; Yang, Andrian; Zadoorian, Armella; Rungrugeecharoen, Kevin; Ho, Joshua W K

    2014-01-01

    Gene regulatory networks (GRNs) play a central role in systems biology, especially in the study of mammalian organ development. One key question remains largely unanswered: Is it possible to infer mammalian causal GRNs using observable gene co-expression patterns alone? We assembled two mouse GRN datasets (embryonic tooth and heart) and matching microarray gene expression profiles to systematically investigate the difficulties of mammalian causal GRN inference. The GRNs were assembled based on > 2,000 pieces of experimental genetic perturbation evidence from manually reading > 150 primary research articles. Each piece of perturbation evidence records the qualitative change of the expression of one gene following knock-down or over-expression of another gene. Our data have thorough annotation of tissue types and embryonic stages, as well as the type of regulation (activation, inhibition and no effect), which uniquely allows us to estimate both sensitivity and specificity of the inference of tissue specific causal GRN edges. Using these unprecedented datasets, we found that gene co-expression does not reliably distinguish true positive from false positive interactions, making inference of GRN in mammalian development very difficult. Nonetheless, if we have expression profiling data from genetic or molecular perturbation experiments, such as gene knock-out or signalling stimulation, it is possible to use the set of differentially expressed genes to recover causal regulatory relationships with good sensitivity and specificity. Our result supports the importance of using perturbation experimental data in causal network reconstruction. Furthermore, we showed that causal gene regulatory relationship can be highly cell type or developmental stage specific, suggesting the importance of employing expression profiles from homogeneous cell populations. This study provides essential datasets and empirical evidence to guide the development of new GRN inference methods for

  6. Dynamic Gene Regulatory Networks Drive Hematopoietic Specification and Differentiation

    Science.gov (United States)

    Goode, Debbie K.; Obier, Nadine; Vijayabaskar, M.S.; Lie-A-Ling, Michael; Lilly, Andrew J.; Hannah, Rebecca; Lichtinger, Monika; Batta, Kiran; Florkowska, Magdalena; Patel, Rahima; Challinor, Mairi; Wallace, Kirstie; Gilmour, Jane; Assi, Salam A.; Cauchy, Pierre; Hoogenkamp, Maarten; Westhead, David R.; Lacaud, Georges; Kouskoff, Valerie; Göttgens, Berthold; Bonifer, Constanze

    2016-01-01

    Summary Metazoan development involves the successive activation and silencing of specific gene expression programs and is driven by tissue-specific transcription factors programming the chromatin landscape. To understand how this process executes an entire developmental pathway, we generated global gene expression, chromatin accessibility, histone modification, and transcription factor binding data from purified embryonic stem cell-derived cells representing six sequential stages of hematopoietic specification and differentiation. Our data reveal the nature of regulatory elements driving differential gene expression and inform how transcription factor binding impacts on promoter activity. We present a dynamic core regulatory network model for hematopoietic specification and demonstrate its utility for the design of reprogramming experiments. Functional studies motivated by our genome-wide data uncovered a stage-specific role for TEAD/YAP factors in mammalian hematopoietic specification. Our study presents a powerful resource for studying hematopoiesis and demonstrates how such data advance our understanding of mammalian development. PMID:26923725

  7. Constraint and contingency in multifunctional gene regulatory circuits.

    Science.gov (United States)

    Payne, Joshua L; Wagner, Andreas

    2013-01-01

    Gene regulatory circuits drive the development, physiology, and behavior of organisms from bacteria to humans. The phenotypes or functions of such circuits are embodied in the gene expression patterns they form. Regulatory circuits are typically multifunctional, forming distinct gene expression patterns in different embryonic stages, tissues, or physiological states. Any one circuit with a single function can be realized by many different regulatory genotypes. Multifunctionality presumably constrains this number, but we do not know to what extent. We here exhaustively characterize a genotype space harboring millions of model regulatory circuits and all their possible functions. As a circuit's number of functions increases, the number of genotypes with a given number of functions decreases exponentially but can remain very large for a modest number of functions. However, the sets of circuits that can form any one set of functions becomes increasingly fragmented. As a result, historical contingency becomes widespread in circuits with many functions. Whether a circuit can acquire an additional function in the course of its evolution becomes increasingly dependent on the function it already has. Circuits with many functions also become increasingly brittle and sensitive to mutation. These observations are generic properties of a broad class of circuits and independent of any one circuit genotype or phenotype.

  8. Urinary Tract Infection and fimH Gene in Escherichia coli

    Directory of Open Access Journals (Sweden)

    Ali Shojaeiani

    2013-07-01

    Full Text Available AbstractBackground and objective: E. coli is considered causes of urinary tract infection (UTI and the majority part of nosocomial infections. This bacterium for having pathogenicity effects is necessary to have virulence factors. One of this factors is fimH (Type I fimbriae. The aim of this research “Study of prevalence of fimH gene in Escherichia coli isolated from patients with and without kidney stone.Materials and methods: A total of 70 urinary samples of stricken with UTI of referred to Ttaleghani Hospital, 42 urinary samples were contaminated with E. coli. Then, is accomplished antibiogram with 9 conventional antibiotics for all of the bacteria. The presence of fimH gene was investigated by PCR. Results: A total of 70 urinary samples were collected, 42 samples (60% were contaminated with Escherichia coli. Of 42 samples, 12 samples (28.6% have had kidney stone & 30 samples (71.4% have not had kidney stone (P<0.05. 24 samples (57.1% have had fimH gene & 18 samples (42.9% have not had fimH gene (P<0.05. Of 12 samples individuals of stricken with kidney stone, 8 samples (66.7% have had fimH gene & 4 samples (33. 3% have not had fimH gene (P<0.05. By doing antibiogram, recommended antibiotics for Urinary Tract Infection were included Imipeneme & Gentamicin. Conclusion: Eschrichia coli with prevalence of 60% were the most common bacteria isolated from the urine of patients with UTI. Individuals with UTI are susceptible for kidney stone formation. fimH gene in patients with UTI is an important pathogenic factor. This gene is involved in advancing kidney stones formation. The identification of microorganisms present in the kidney stone can be treated with appropriate antibiotics to reduce the risk of stone.

  9. Stable Gene Regulatory Network Modeling From Steady-State Data

    Directory of Open Access Journals (Sweden)

    Joy Edward Larvie

    2016-04-01

    Full Text Available Gene regulatory networks represent an abstract mapping of gene regulations in living cells. They aim to capture dependencies among molecular entities such as transcription factors, proteins and metabolites. In most applications, the regulatory network structure is unknown, and has to be reverse engineered from experimental data consisting of expression levels of the genes usually measured as messenger RNA concentrations in microarray experiments. Steady-state gene expression data are obtained from measurements of the variations in expression activity following the application of small perturbations to equilibrium states in genetic perturbation experiments. In this paper, the least absolute shrinkage and selection operator-vector autoregressive (LASSO-VAR originally proposed for the analysis of economic time series data is adapted to include a stability constraint for the recovery of a sparse and stable regulatory network that describes data obtained from noisy perturbation experiments. The approach is applied to real experimental data obtained for the SOS pathway in Escherichia coli and the cell cycle pathway for yeast Saccharomyces cerevisiae. Significant features of this method are the ability to recover networks without inputting prior knowledge of the network topology, and the ability to be efficiently applied to large scale networks due to the convex nature of the method.

  10. Overview of methods of reverse engineering of gene regulatory networks: Boolean and Bayesian networks

    OpenAIRE

    Frolova A. O.

    2012-01-01

    Reverse engineering of gene regulatory networks is an intensively studied topic in Systems Biology as it reconstructs regulatory interactions between all genes in the genome in the most complete form. The extreme computational complexity of this problem and lack of thorough reviews on reconstruction methods of gene regulatory network is a significant obstacle to further development of this area. In this article the two most common methods for modeling gene regulatory networks are surveyed: Bo...

  11. Gene therapy for cancer: regulatory considerations for approval.

    Science.gov (United States)

    Husain, S R; Han, J; Au, P; Shannon, K; Puri, R K

    2015-12-01

    The rapidly changing field of gene therapy promises a number of innovative treatments for cancer patients. Advances in genetic modification of cancer and immune cells and the use of oncolytic viruses and bacteria have led to numerous clinical trials for cancer therapy, with several progressing to late-stage product development. At the time of this writing, no gene therapy product has been approved by the United States Food and Drug Administration (FDA). Some of the key scientific and regulatory issues include understanding of gene transfer vector biology, safety of vectors in vitro and in animal models, optimum gene transfer, long-term persistence or integration in the host, shedding of a virus and ability to maintain transgene expression in vivo for a desired period of time. Because of the biological complexity of these products, the FDA encourages a flexible, data-driven approach for preclinical safety testing programs. The clinical trial design should be based on the unique features of gene therapy products, and should ensure the safety of enrolled subjects. This article focuses on regulatory considerations for gene therapy product development and also discusses guidance documents that have been published by the FDA.

  12. Dose response relationship in anti-stress gene regulatory networks.

    OpenAIRE

    Qiang Zhang; Andersen, Melvin E.

    2007-01-01

    To maintain a stable intracellular environment, cells utilize complex and specialized defense systems against a variety of external perturbations, such as electrophilic stress, heat shock, and hypoxia, etc. Irrespective of the type of stress, many adaptive mechanisms contributing to cellular homeostasis appear to operate through gene regulatory networks that are organized into negative feedback loops. In general, the degree of deviation of the controlled variables, such as electrophiles, misf...

  13. Phase transitions in the evolution of gene regulatory networks

    Science.gov (United States)

    Skanata, Antun; Kussell, Edo

    The role of gene regulatory networks is to respond to environmental conditions and optimize growth of the cell. A typical example is found in bacteria, where metabolic genes are activated in response to nutrient availability, and are subsequently turned off to conserve energy when their specific substrates are depleted. However, in fluctuating environmental conditions, regulatory networks could experience strong evolutionary pressures not only to turn the right genes on and off, but also to respond optimally under a wide spectrum of fluctuation timescales. The outcome of evolution is predicted by the long-term growth rate, which differentiates between optimal strategies. Here we present an analytic computation of the long-term growth rate in randomly fluctuating environments, by using mean-field and higher order expansion in the environmental history. We find that optimal strategies correspond to distinct regions in the phase space of fluctuations, separated by first and second order phase transitions. The statistics of environmental randomness are shown to dictate the possible evolutionary modes, which either change the structure of the regulatory network abruptly, or gradually modify and tune the interactions between its components.

  14. Using gene expression programming to infer gene regulatory networks from time-series data.

    Science.gov (United States)

    Zhang, Yongqing; Pu, Yifei; Zhang, Haisen; Su, Yabo; Zhang, Lifang; Zhou, Jiliu

    2013-12-01

    Gene regulatory networks inference is currently a topic under heavy research in the systems biology field. In this paper, gene regulatory networks are inferred via evolutionary model based on time-series microarray data. A non-linear differential equation model is adopted. Gene expression programming (GEP) is applied to identify the structure of the model and least mean square (LMS) is used to optimize the parameters in ordinary differential equations (ODEs). The proposed work has been first verified by synthetic data with noise-free and noisy time-series data, respectively, and then its effectiveness is confirmed by three real time-series expression datasets. Finally, a gene regulatory network was constructed with 12 Yeast genes. Experimental results demonstrate that our model can improve the prediction accuracy of microarray time-series data effectively. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Comparison of evolutionary algorithms in gene regulatory network model inference.

    LENUS (Irish Health Repository)

    2010-01-01

    ABSTRACT: BACKGROUND: The evolution of high throughput technologies that measure gene expression levels has created a data base for inferring GRNs (a process also known as reverse engineering of GRNs). However, the nature of these data has made this process very difficult. At the moment, several methods of discovering qualitative causal relationships between genes with high accuracy from microarray data exist, but large scale quantitative analysis on real biological datasets cannot be performed, to date, as existing approaches are not suitable for real microarray data which are noisy and insufficient. RESULTS: This paper performs an analysis of several existing evolutionary algorithms for quantitative gene regulatory network modelling. The aim is to present the techniques used and offer a comprehensive comparison of approaches, under a common framework. Algorithms are applied to both synthetic and real gene expression data from DNA microarrays, and ability to reproduce biological behaviour, scalability and robustness to noise are assessed and compared. CONCLUSIONS: Presented is a comparison framework for assessment of evolutionary algorithms, used to infer gene regulatory networks. Promising methods are identified and a platform for development of appropriate model formalisms is established.

  16. Social dominance-related major urinary proteins and the regulatory mechanism in mice.

    Science.gov (United States)

    Guo, Huifen; Fang, Qi; Huo, Ying; Zhang, Yaohua; Zhang, Jianxu

    2015-11-01

    Major urinary proteins (MUPs) have been proven to be non-volatile male pheromones in mice. Here, we aimed to elucidate the relationship between MUPs and dominance hierarchy, and the underlying molecular mechanisms. Dominance-submission relationship was established by chronic dyadic encountering. We found that at the urinary protein level and hepatic mRNA level, the expression of major MUPs, including Mup20, was enhanced in dominant males compared with subordinate males, indicating that MUPs might signal the social status of male mice. Meanwhile, the mRNA level of hepatic corticotropin releasing hormone receptor 2 (CRHR2) was higher in subordinate male mice than in dominant male mice. Castration also enhanced the expression of CRHR2, but suppressed that of MUPs. CRHR2 agonist treatment reduced the expression of MUPs in liver. However, male social status failed to exert significant influence on serum testosterone and corticosterone as well as the mRNA expression of their receptors. These findings reveal that some MUPs, especially Mup20, might constitute potential dominance pheromones and could be downregulated by hepatic CRHR2, which is possibly independent of androgen or corticosterone systems.

  17. Inference of Gene Regulatory Network Based on Local Bayesian Networks.

    Science.gov (United States)

    Liu, Fei; Zhang, Shao-Wu; Guo, Wei-Feng; Wei, Ze-Gang; Chen, Luonan

    2016-08-01

    The inference of gene regulatory networks (GRNs) from expression data can mine the direct regulations among genes and gain deep insights into biological processes at a network level. During past decades, numerous computational approaches have been introduced for inferring the GRNs. However, many of them still suffer from various problems, e.g., Bayesian network (BN) methods cannot handle large-scale networks due to their high computational complexity, while information theory-based methods cannot identify the directions of regulatory interactions and also suffer from false positive/negative problems. To overcome the limitations, in this work we present a novel algorithm, namely local Bayesian network (LBN), to infer GRNs from gene expression data by using the network decomposition strategy and false-positive edge elimination scheme. Specifically, LBN algorithm first uses conditional mutual information (CMI) to construct an initial network or GRN, which is decomposed into a number of local networks or GRNs. Then, BN method is employed to generate a series of local BNs by selecting the k-nearest neighbors of each gene as its candidate regulatory genes, which significantly reduces the exponential search space from all possible GRN structures. Integrating these local BNs forms a tentative network or GRN by performing CMI, which reduces redundant regulations in the GRN and thus alleviates the false positive problem. The final network or GRN can be obtained by iteratively performing CMI and local BN on the tentative network. In the iterative process, the false or redundant regulations are gradually removed. When tested on the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in E.coli, our results suggest that LBN outperforms other state-of-the-art methods (ARACNE, GENIE3 and NARROMI) significantly, with more accurate and robust performance. In particular, the decomposition strategy with local Bayesian networks not only effectively reduce

  18. Urinary Tract Infection and fimH Gene in Escherichia coli

    OpenAIRE

    2013-01-01

    AbstractBackground and objective: E. coli is considered causes of urinary tract infection (UTI) and the majority part of nosocomial infections. This bacterium for having pathogenicity effects is necessary to have virulence factors. One of this factors is fimH (Type I fimbriae). The aim of this research “Study of prevalence of fimH gene in Escherichia coli isolated from patients with and without kidney stone.Materials and methods: A total of 70 urinary samples of stricken with UTI of referred...

  19. Regulatory Features for Odorant Receptor Genes in the Mouse Genome.

    Science.gov (United States)

    Degl'Innocenti, Andrea; D'Errico, Anna

    2017-01-01

    The odorant receptor genes, seven transmembrane receptor genes constituting the vastest mammalian gene multifamily, are expressed monogenically and monoallelicaly in each sensory neuron in the olfactory epithelium. This characteristic, often referred to as the one neuron-one receptor rule, is driven by mostly uncharacterized molecular dynamics, generally named odorant receptor gene choice. Much attention has been paid by the scientific community to the identification of sequences regulating the expression of odorant receptor genes within their loci, where related genes are usually arranged in genomic clusters. A number of studies identified transcription factor binding sites on odorant receptor promoter sequences. Similar binding sites were also found on a number of enhancers that regulate in cis their transcription, but have been proposed to form interchromosomal networks. Odorant receptor gene choice seems to occur via the local removal of strongly repressive epigenetic markings, put in place during the maturation of the sensory neuron on each odorant receptor locus. Here we review the fast-changing state of art for the study of regulatory features for odorant receptor genes.

  20. Propagation of genetic variation in gene regulatory networks.

    Science.gov (United States)

    Plahte, Erik; Gjuvsland, Arne B; Omholt, Stig W

    2013-08-01

    A future quantitative genetics theory should link genetic variation to phenotypic variation in a causally cohesive way based on how genes actually work and interact. We provide a theoretical framework for predicting and understanding the manifestation of genetic variation in haploid and diploid regulatory networks with arbitrary feedback structures and intra-locus and inter-locus functional dependencies. Using results from network and graph theory, we define propagation functions describing how genetic variation in a locus is propagated through the network, and show how their derivatives are related to the network's feedback structure. Similarly, feedback functions describe the effect of genotypic variation of a locus on itself, either directly or mediated by the network. A simple sign rule relates the sign of the derivative of the feedback function of any locus to the feedback loops involving that particular locus. We show that the sign of the phenotypically manifested interaction between alleles at a diploid locus is equal to the sign of the dominant feedback loop involving that particular locus, in accordance with recent results for a single locus system. Our results provide tools by which one can use observable equilibrium concentrations of gene products to disclose structural properties of the network architecture. Our work is a step towards a theory capable of explaining the pleiotropy and epistasis features of genetic variation in complex regulatory networks as functions of regulatory anatomy and functional location of the genetic variation.

  1. Topological effects of data incompleteness of gene regulatory networks

    CERN Document Server

    Sanz, J; Borge-Holthoefer, J; Moreno, Y

    2012-01-01

    The topological analysis of biological networks has been a prolific topic in network science during the last decade. A persistent problem with this approach is the inherent uncertainty and noisy nature of the data. One of the cases in which this situation is more marked is that of transcriptional regulatory networks (TRNs) in bacteria. The datasets are incomplete because regulatory pathways associated to a relevant fraction of bacterial genes remain unknown. Furthermore, direction, strengths and signs of the links are sometimes unknown or simply overlooked. Finally, the experimental approaches to infer the regulations are highly heterogeneous, in a way that induces the appearance of systematic experimental-topological correlations. And yet, the quality of the available data increases constantly. In this work we capitalize on these advances to point out the influence of data (in)completeness and quality on some classical results on topological analysis of TRNs, specially regarding modularity at different level...

  2. Autonomous Boolean modelling of developmental gene regulatory networks

    Science.gov (United States)

    Cheng, Xianrui; Sun, Mengyang; Socolar, Joshua E. S.

    2013-01-01

    During early embryonic development, a network of regulatory interactions among genes dynamically determines a pattern of differentiated tissues. We show that important timing information associated with the interactions can be faithfully represented in autonomous Boolean models in which binary variables representing expression levels are updated in continuous time, and that such models can provide a direct insight into features that are difficult to extract from ordinary differential equation (ODE) models. As an application, we model the experimentally well-studied network controlling fly body segmentation. The Boolean model successfully generates the patterns formed in normal and genetically perturbed fly embryos, permits the derivation of constraints on the time delay parameters, clarifies the logic associated with different ODE parameter sets and provides a platform for studying connectivity and robustness in parameter space. By elucidating the role of regulatory time delays in pattern formation, the results suggest new types of experimental measurements in early embryonic development. PMID:23034351

  3. Optimal finite horizon control in gene regulatory networks

    Science.gov (United States)

    Liu, Qiuli

    2013-06-01

    As a paradigm for modeling gene regulatory networks, probabilistic Boolean networks (PBNs) form a subclass of Markov genetic regulatory networks. To date, many different stochastic optimal control approaches have been developed to find therapeutic intervention strategies for PBNs. A PBN is essentially a collection of constituent Boolean networks via a probability structure. Most of the existing works assume that the probability structure for Boolean networks selection is known. Such an assumption cannot be satisfied in practice since the presence of noise prevents the probability structure from being accurately determined. In this paper, we treat a case in which we lack the governing probability structure for Boolean network selection. Specifically, in the framework of PBNs, the theory of finite horizon Markov decision process is employed to find optimal constituent Boolean networks with respect to the defined objective functions. In order to illustrate the validity of our proposed approach, an example is also displayed.

  4. The distribution of SNPs in human gene regulatory regions

    Directory of Open Access Journals (Sweden)

    Guo Yongjian

    2005-10-01

    Full Text Available Abstract Background As a result of high-throughput genotyping methods, millions of human genetic variants have been reported in recent years. To efficiently identify those with significant biological functions, a practical strategy is to concentrate on variants located in important sequence regions such as gene regulatory regions. Results Analysis of the most common type of variant, single nucleotide polymorphisms (SNPs, shows that in gene promoter regions more SNPs occur in close proximity to transcriptional start sites than in regions further upstream, and a disproportionate number of those SNPs represent nucleotide transversions. Additionally, the number of SNPs found in the predicted transcription factor binding sites is higher than in non-binding site sequences. Conclusion Current information about transcription factor binding site sequence patterns may not be exhaustive, and SNPs may be actively involved in influencing gene expression by affecting the transcription factor binding sites.

  5. A Gene Regulatory Program in Human Breast Cancer.

    Science.gov (United States)

    Li, Renhua; Campos, John; Iida, Joji

    2015-12-01

    Molecular heterogeneity in human breast cancer has challenged diagnosis, prognosis, and clinical treatment. It is well known that molecular subtypes of breast tumors are associated with significant differences in prognosis and survival. Assuming that the differences are attributed to subtype-specific pathways, we then suspect that there might be gene regulatory mechanisms that modulate the behavior of the pathways and their interactions. In this study, we proposed an integrated methodology, including machine learning and information theory, to explore the mechanisms. Using existing data from three large cohorts of human breast cancer populations, we have identified an ensemble of 16 master regulator genes (or MR16) that can discriminate breast tumor samples into four major subtypes. Evidence from gene expression across the three cohorts has consistently indicated that the MR16 can be divided into two groups that demonstrate subtype-specific gene expression patterns. For example, group 1 MRs, including ESR1, FOXA1, and GATA3, are overexpressed in luminal A and luminal B subtypes, but lowly expressed in HER2-enriched and basal-like subtypes. In contrast, group 2 MRs, including FOXM1, EZH2, MYBL2, and ZNF695, display an opposite pattern. Furthermore, evidence from mutual information modeling has congruently indicated that the two groups of MRs either up- or down-regulate cancer driver-related genes in opposite directions. Furthermore, integration of somatic mutations with pathway changes leads to identification of canonical genomic alternations in a subtype-specific fashion. Taken together, these studies have implicated a gene regulatory program for breast tumor progression.

  6. A provisional gene regulatory atlas for mouse heart development.

    Directory of Open Access Journals (Sweden)

    Hailin Chen

    Full Text Available Congenital Heart Disease (CHD is one of the most common birth defects. Elucidating the molecular mechanisms underlying normal cardiac development is an important step towards early identification of abnormalities during the developmental program and towards the creation of early intervention strategies. We developed a novel computational strategy for leveraging high-content data sets, including a large selection of microarray data associated with mouse cardiac development, mouse genome sequence, ChIP-seq data of selected mouse transcription factors and Y2H data of mouse protein-protein interactions, to infer the active transcriptional regulatory network of mouse cardiac development. We identified phase-specific expression activity for 765 overlapping gene co-expression modules that were defined for obtained cardiac lineage microarray data. For each co-expression module, we identified the phase of cardiac development where gene expression for that module was higher than other phases. Co-expression modules were found to be consistent with biological pathway knowledge in Wikipathways, and met expectations for enrichment of pathways involved in heart lineage development. Over 359,000 transcription factor-target relationships were inferred by analyzing the promoter sequences within each gene module for overrepresentation against the JASPAR database of Transcription Factor Binding Site (TFBS motifs. The provisional regulatory network will provide a framework of studying the genetic basis of CHD.

  7. Identifying gene regulatory network rewiring using latent differential graphical models.

    Science.gov (United States)

    Tian, Dechao; Gu, Quanquan; Ma, Jian

    2016-09-30

    Gene regulatory networks (GRNs) are highly dynamic among different tissue types. Identifying tissue-specific gene regulation is critically important to understand gene function in a particular cellular context. Graphical models have been used to estimate GRN from gene expression data to distinguish direct interactions from indirect associations. However, most existing methods estimate GRN for a specific cell/tissue type or in a tissue-naive way, or do not specifically focus on network rewiring between different tissues. Here, we describe a new method called Latent Differential Graphical Model (LDGM). The motivation of our method is to estimate the differential network between two tissue types directly without inferring the network for individual tissues, which has the advantage of utilizing much smaller sample size to achieve reliable differential network estimation. Our simulation results demonstrated that LDGM consistently outperforms other Gaussian graphical model based methods. We further evaluated LDGM by applying to the brain and blood gene expression data from the GTEx consortium. We also applied LDGM to identify network rewiring between cancer subtypes using the TCGA breast cancer samples. Our results suggest that LDGM is an effective method to infer differential network using high-throughput gene expression data to identify GRN dynamics among different cellular conditions.

  8. Regulatory systems for hypoxia-inducible gene expression in ischemic heart disease gene therapy.

    Science.gov (United States)

    Kim, Hyun Ah; Rhim, Taiyoun; Lee, Minhyung

    2011-07-18

    Ischemic heart diseases are caused by narrowed coronary arteries that decrease the blood supply to the myocardium. In the ischemic myocardium, hypoxia-responsive genes are up-regulated by hypoxia-inducible factor-1 (HIF-1). Gene therapy for ischemic heart diseases uses genes encoding angiogenic growth factors and anti-apoptotic proteins as therapeutic genes. These genes increase blood supply into the myocardium by angiogenesis and protect cardiomyocytes from cell death. However, non-specific expression of these genes in normal tissues may be harmful, since growth factors and anti-apoptotic proteins may induce tumor growth. Therefore, tight gene regulation is required to limit gene expression to ischemic tissues, to avoid unwanted side effects. For this purpose, various gene expression strategies have been developed for ischemic-specific gene expression. Transcriptional, post-transcriptional, and post-translational regulatory strategies have been developed and evaluated in ischemic heart disease animal models. The regulatory systems can limit therapeutic gene expression to ischemic tissues and increase the efficiency of gene therapy. In this review, recent progresses in ischemic-specific gene expression systems are presented, and their applications to ischemic heart diseases are discussed.

  9. Ground rules of the pluripotency gene regulatory network.

    KAUST Repository

    Li, Mo

    2017-01-03

    Pluripotency is a state that exists transiently in the early embryo and, remarkably, can be recapitulated in vitro by deriving embryonic stem cells or by reprogramming somatic cells to become induced pluripotent stem cells. The state of pluripotency, which is stabilized by an interconnected network of pluripotency-associated genes, integrates external signals and exerts control over the decision between self-renewal and differentiation at the transcriptional, post-transcriptional and epigenetic levels. Recent evidence of alternative pluripotency states indicates the regulatory flexibility of this network. Insights into the underlying principles of the pluripotency network may provide unprecedented opportunities for studying development and for regenerative medicine.

  10. Superhelical destabilization in regulatory regions of stress response genes.

    Directory of Open Access Journals (Sweden)

    Huiquan Wang

    2008-01-01

    Full Text Available Stress-induced DNA duplex destabilization (SIDD analysis exploits the known structural and energetic properties of DNA to predict sites that are susceptible to strand separation under negative superhelical stress. When this approach was used to calculate the SIDD profile of the entire Escherichia coli K12 genome, it was found that strongly destabilized sites occur preferentially in intergenic regions that are either known or inferred to contain promoters, but rarely occur in coding regions. Here, we investigate whether the genes grouped in different functional categories have characteristic SIDD properties in their upstream flanks. We report that strong SIDD sites in the E. coli K12 genome are statistically significantly overrepresented in the upstream regions of genes encoding transcriptional regulators. In particular, the upstream regions of genes that directly respond to physiological and environmental stimuli are more destabilized than are those regions of genes that are not involved in these responses. Moreover, if a pathway is controlled by a transcriptional regulator whose gene has a destabilized 5' flank, then the genes (operons in that pathway also usually contain strongly destabilized SIDD sites in their 5' flanks. We observe this statistically significant association of SIDD sites with upstream regions of genes functioning in transcription in 38 of 43 genomes of free-living bacteria, but in only four of 18 genomes of endosymbionts or obligate parasitic bacteria. These results suggest that strong SIDD sites 5' to participating genes may be involved in transcriptional responses to environmental changes, which are known to transiently alter superhelicity. We propose that these SIDD sites are active and necessary participants in superhelically mediated regulatory mechanisms governing changes in the global pattern of gene expression in prokaryotes in response to physiological or environmental changes.

  11. Host-specific induction of Escherichia coli fitness genes during human urinary tract infection.

    Science.gov (United States)

    Subashchandrabose, Sargurunathan; Hazen, Tracy H; Brumbaugh, Ariel R; Himpsl, Stephanie D; Smith, Sara N; Ernst, Robert D; Rasko, David A; Mobley, Harry L T

    2014-12-23

    Uropathogenic Escherichia coli (UPEC) is the predominant etiological agent of uncomplicated urinary tract infection (UTI), manifested by inflammation of the urinary bladder, in humans and is a major global public health concern. Molecular pathogenesis of UPEC has been primarily examined using murine models of UTI. Translational research to develop novel therapeutics against this major pathogen, which is becoming increasingly antibiotic resistant, requires a thorough understanding of mechanisms involved in pathogenesis during human UTIs. Total RNA-sequencing (RNA-seq) and comparative transcriptional analysis of UTI samples to the UPEC isolates cultured in human urine and laboratory medium were used to identify novel fitness genes that were specifically expressed during human infection. Evidence for UPEC genes involved in ion transport, including copper efflux, nickel and potassium import systems, as key fitness factors in uropathogenesis were generated using an experimental model of UTI. Translational application of this study was investigated by targeting Cus, a bacterial copper efflux system. Copper supplementation in drinking water reduces E. coli colonization in the urinary bladder of mice. Additionally, our results suggest that anaerobic processes in UPEC are involved in promoting fitness during UTI in humans. In summary, RNA-seq was used to establish the transcriptional signature in UPEC during naturally occurring, community acquired UTI in women and multiple novel fitness genes used by UPEC during human infection were identified. The repertoire of UPEC genes involved in UTI presented here will facilitate further translational studies to develop innovative strategies against UTI caused by UPEC.

  12. Optimal Constrained Stationary Intervention in Gene Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Golnaz Vahedi

    2008-05-01

    Full Text Available A key objective of gene network modeling is to develop intervention strategies to alter regulatory dynamics in such a way as to reduce the likelihood of undesirable phenotypes. Optimal stationary intervention policies have been developed for gene regulation in the framework of probabilistic Boolean networks in a number of settings. To mitigate the possibility of detrimental side effects, for instance, in the treatment of cancer, it may be desirable to limit the expected number of treatments beneath some bound. This paper formulates a general constraint approach for optimal therapeutic intervention by suitably adapting the reward function and then applies this formulation to bound the expected number of treatments. A mutated mammalian cell cycle is considered as a case study.

  13. Optimal Constrained Stationary Intervention in Gene Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Faryabi Babak

    2008-01-01

    Full Text Available A key objective of gene network modeling is to develop intervention strategies to alter regulatory dynamics in such a way as to reduce the likelihood of undesirable phenotypes. Optimal stationary intervention policies have been developed for gene regulation in the framework of probabilistic Boolean networks in a number of settings. To mitigate the possibility of detrimental side effects, for instance, in the treatment of cancer, it may be desirable to limit the expected number of treatments beneath some bound. This paper formulates a general constraint approach for optimal therapeutic intervention by suitably adapting the reward function and then applies this formulation to bound the expected number of treatments. A mutated mammalian cell cycle is considered as a case study.

  14. Bladder inflammatory transcriptome in response to tachykinins: Neurokinin 1 receptor-dependent genes and transcription regulatory elements

    Directory of Open Access Journals (Sweden)

    Dozmorov Igor

    2007-05-01

    Full Text Available Abstract Background Tachykinins (TK, such as substance P, and their neurokinin receptors which are ubiquitously expressed in the human urinary tract, represent an endogenous system regulating bladder inflammatory, immune responses, and visceral hypersensitivity. Increasing evidence correlates alterations in the TK system with urinary tract diseases such as neurogenic bladders, outflow obstruction, idiopathic detrusor instability, and interstitial cystitis. However, despite promising effects in animal models, there seems to be no published clinical study showing that NK-receptor antagonists are an effective treatment of pain in general or urinary tract disorders, such as detrusor overactivity. In order to search for therapeutic targets that could block the tachykinin system, we set forth to determine the regulatory network downstream of NK1 receptor activation. First, NK1R-dependent transcripts were determined and used to query known databases for their respective transcription regulatory elements (TREs. Methods An expression analysis was performed using urinary bladders isolated from sensitized wild type (WT and NK1R-/- mice that were stimulated with saline, LPS, or antigen to provoke inflammation. Based on cDNA array results, NK1R-dependent genes were selected. PAINT software was used to query TRANSFAC database and to retrieve upstream TREs that were confirmed by electrophoretic mobility shift assays. Results The regulatory network of TREs driving NK1R-dependent genes presented cRel in a central position driving 22% of all genes, followed by AP-1, NF-kappaB, v-Myb, CRE-BP1/c-Jun, USF, Pax-6, Efr-1, Egr-3, and AREB6. A comparison between NK1R-dependent and NK1R-independent genes revealed Nkx-2.5 as a unique discriminator. In the presence of NK1R, Nkx2-5 _01 was significantly correlated with 36 transcripts which included several candidates for mediating bladder development (FGF and inflammation (PAR-3, IL-1R, IL-6, α-NGF, TSP2. In the absence of

  15. Inference of Gene Regulatory Network Based on Local Bayesian Networks.

    Directory of Open Access Journals (Sweden)

    Fei Liu

    2016-08-01

    Full Text Available The inference of gene regulatory networks (GRNs from expression data can mine the direct regulations among genes and gain deep insights into biological processes at a network level. During past decades, numerous computational approaches have been introduced for inferring the GRNs. However, many of them still suffer from various problems, e.g., Bayesian network (BN methods cannot handle large-scale networks due to their high computational complexity, while information theory-based methods cannot identify the directions of regulatory interactions and also suffer from false positive/negative problems. To overcome the limitations, in this work we present a novel algorithm, namely local Bayesian network (LBN, to infer GRNs from gene expression data by using the network decomposition strategy and false-positive edge elimination scheme. Specifically, LBN algorithm first uses conditional mutual information (CMI to construct an initial network or GRN, which is decomposed into a number of local networks or GRNs. Then, BN method is employed to generate a series of local BNs by selecting the k-nearest neighbors of each gene as its candidate regulatory genes, which significantly reduces the exponential search space from all possible GRN structures. Integrating these local BNs forms a tentative network or GRN by performing CMI, which reduces redundant regulations in the GRN and thus alleviates the false positive problem. The final network or GRN can be obtained by iteratively performing CMI and local BN on the tentative network. In the iterative process, the false or redundant regulations are gradually removed. When tested on the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in E.coli, our results suggest that LBN outperforms other state-of-the-art methods (ARACNE, GENIE3 and NARROMI significantly, with more accurate and robust performance. In particular, the decomposition strategy with local Bayesian networks not only

  16. The role of master regulators in gene regulatory networks

    Directory of Open Access Journals (Sweden)

    Enrique Hernández Lemus

    2015-05-01

    Full Text Available Gene regulatory networks present a wide variety of dynamical responses to intrinsic and extrinsic perturbations. Arguably, one of the most important of such coordinated responses is the one of amplification cascades, in which activation of a few key-responsive transcription factors (termed master regulators, MRs lead to a large series of transcriptional activation events. This is so since master regulators are transcription factors controlling the expression of other transcription factor molecules and so on. MRs hold a central position related to transcriptional dynamics and control of gene regulatory networks and are often involved in complex feedback and feedforward loops inducing non-trivial dynamics. Recent studies have pointed out to the myocyte enhancing factor 2C (MEF2C, also known as MADS box transcription enhancer factor 2, polypeptide C as being one of such master regulators involved in the pathogenesis of primary breast cancer. In this work, we perform an integrative genomic analysis of the transcriptional regulation activity of MEF2C and its target genes to evaluate to what extent are these molecules inducing collective responses leading to gene expression deregulation and carcinogenesis. We also analyzed a number of induced dynamic responses, in particular those associated with transcriptional bursts, and nonlinear cascading to evaluate the influence they may have in malignant phenotypes and cancer. Received: 20 Novembre 2014, Accepted: 24 June 2015; Edited by: C. A. Condat, G. J. Sibona; DOI: http://dx.doi.org/10.4279/PIP.070011 Cite as: E Hernández-Lemus, K Baca-López, R Lemus, R García-Herrera, Papers in Physics 7, 070011 (2015

  17. Identification of developmental regulatory genes in Aspergillus nidulans by overexpression.

    Science.gov (United States)

    Marhoul, J F; Adams, T H

    1995-02-01

    Overexpression of several Aspergillus nidulans developmental regulatory genes has been shown to cause growth inhibition and development at inappropriate times. We set out to identify previously unknown developmental regulators by constructing a nutritionally inducible A. nidulans expression library containing small, random genomic DNA fragments inserted next to the alcA promoter [alcA(p)] in an A. nidulans transformation vector. Among 20,000 transformants containing random alcA(p) genomic DNA fusion constructs, we identified 66 distinct mutant strains in which alcA(p) induction resulted in growth inhibition as well as causing other detectable phenotypic changes. These growth inhibited mutants were divided into 52 FIG (Forced expression Inhibition of Growth) and 14 FAB (Forced expression Activation of brlA) mutants based on whether or not alcA(p) induction resulted in accumulation of mRNA for the developmental regulatory gene brlA. In four FAB mutants, alcA(p) induction not only activated brlA expression but also caused hyphae to differentiate into reduced conidiophores that produced viable spores from the tips as is observed after alcA(p)::brlA induction. Sequence analyses of the DNA fragments under alcA(p) control in three of these four sporulating strains showed that in two cases developmental activation resulted from overexpression of previously uncharacterized genes, whereas in the third strain, the alcA(p) was fused to brlA. The potential uses for this strategy in identifying genes whose overexpression results in specific phenotypic changes like developmental induction are discussed.

  18. Toxin-mediated gene regulatory mechanism in Staphylococcus aureus

    Directory of Open Access Journals (Sweden)

    Hwang-Soo Joo

    2016-12-01

    Full Text Available The dangerous human pathogen Staphylococcus aureus relies heavily on toxins to cause disease, but toxin production can put a strong burden on the bacteria’s energy balance. Thus, controlling the synthesis of proteins solely needed in times of toxin production represents a way for the bacteria to avoid wasting energy. One hypothetical manner to accomplish this sort of regulation is by gene regulatory functions of the toxins themselves. There have been several reports about gene regulation by toxins in S. aureus, but these were never verified on the molecular level. In our study published in MBio [Joo et al., 7(5. pii: e01579-16], we show that phenol-soluble modulins (PSMs, important peptide toxins of S. aureus, release a repressor from the promoter of the operon encoding the toxin export system, thereby enabling toxin secretion. This study describes the first molecular regulatory mechanism exerted by an S. aureus toxin, setting a paradigmatic example of how S. aureus toxins may influence cell functions to adjust them to times of toxin production.

  19. Evolution of the mammalian embryonic pluripotency gene regulatory network

    Science.gov (United States)

    Fernandez-Tresguerres, Beatriz; Cañon, Susana; Rayon, Teresa; Pernaute, Barbara; Crespo, Miguel; Torroja, Carlos; Manzanares, Miguel

    2010-01-01

    Embryonic pluripotency in the mouse is established and maintained by a gene-regulatory network under the control of a core set of transcription factors that include octamer-binding protein 4 (Oct4; official name POU domain, class 5, transcription factor 1, Pou5f1), sex-determining region Y (SRY)-box containing gene 2 (Sox2), and homeobox protein Nanog. Although this network is largely conserved in eutherian mammals, very little information is available regarding its evolutionary conservation in other vertebrates. We have compared the embryonic pluripotency networks in mouse and chick by means of expression analysis in the pregastrulation chicken embryo, genomic comparisons, and functional assays of pluripotency-related regulatory elements in ES cells and blastocysts. We find that multiple components of the network are either novel to mammals or have acquired novel expression domains in early developmental stages of the mouse. We also find that the downstream action of the mouse core pluripotency factors is mediated largely by genomic sequence elements nonconserved with chick. In the case of Sox2 and Fgf4, we find that elements driving expression in embryonic pluripotent cells have evolved by a small number of nucleotide changes that create novel binding sites for core factors. Our results show that the network in charge of embryonic pluripotency is an evolutionary novelty of mammals that is related to the comparatively extended period during which mammalian embryonic cells need to be maintained in an undetermined state before engaging in early differentiation events. PMID:21048080

  20. Graphlet Based Metrics for the Comparison of Gene Regulatory Networks

    Science.gov (United States)

    Martin, Alberto J. M.; Dominguez, Calixto; Contreras-Riquelme, Sebastián; Holmes, David S.; Perez-Acle, Tomas

    2016-01-01

    Understanding the control of gene expression remains one of the main challenges in the post-genomic era. Accordingly, a plethora of methods exists to identify variations in gene expression levels. These variations underlay almost all relevant biological phenomena, including disease and adaptation to environmental conditions. However, computational tools to identify how regulation changes are scarce. Regulation of gene expression is usually depicted in the form of a gene regulatory network (GRN). Structural changes in a GRN over time and conditions represent variations in the regulation of gene expression. Like other biological networks, GRNs are composed of basic building blocks called graphlets. As a consequence, two new metrics based on graphlets are proposed in this work: REConstruction Rate (REC) and REC Graphlet Degree (RGD). REC determines the rate of graphlet similarity between different states of a network and RGD identifies the subset of nodes with the highest topological variation. In other words, RGD discerns how th GRN was rewired. REC and RGD were used to compare the local structure of nodes in condition-specific GRNs obtained from gene expression data of Escherichia coli, forming biofilms and cultured in suspension. According to our results, most of the network local structure remains unaltered in the two compared conditions. Nevertheless, changes reported by RGD necessarily imply that a different cohort of regulators (i.e. transcription factors (TFs)) appear on the scene, shedding light on how the regulation of gene expression occurs when E. coli transits from suspension to biofilm. Consequently, we propose that both metrics REC and RGD should be adopted as a quantitative approach to conduct differential analyses of GRNs. A tool that implements both metrics is available as an on-line web server (http://dlab.cl/loto). PMID:27695050

  1. Learning gene regulatory networks from gene expression data using weighted consensus

    KAUST Repository

    Fujii, Chisato

    2016-08-25

    An accurate determination of the network structure of gene regulatory systems from high-throughput gene expression data is an essential yet challenging step in studying how the expression of endogenous genes is controlled through a complex interaction of gene products and DNA. While numerous methods have been proposed to infer the structure of gene regulatory networks, none of them seem to work consistently over different data sets with high accuracy. A recent study to compare gene network inference methods showed that an average-ranking-based consensus method consistently performs well under various settings. Here, we propose a linear programming-based consensus method for the inference of gene regulatory networks. Unlike the average-ranking-based one, which treats the contribution of each individual method equally, our new consensus method assigns a weight to each method based on its credibility. As a case study, we applied the proposed consensus method on synthetic and real microarray data sets, and compared its performance to that of the average-ranking-based consensus and individual inference methods. Our results show that our weighted consensus method achieves superior performance over the unweighted one, suggesting that assigning weights to different individual methods rather than giving them equal weights improves the accuracy. © 2016 Elsevier B.V.

  2. Learning Gene Regulatory Networks Computationally from Gene Expression Data Using Weighted Consensus

    KAUST Repository

    Fujii, Chisato

    2015-04-16

    Gene regulatory networks analyze the relationships between genes allowing us to un- derstand the gene regulatory interactions in systems biology. Gene expression data from the microarray experiments is used to obtain the gene regulatory networks. How- ever, the microarray data is discrete, noisy and non-linear which makes learning the networks a challenging problem and existing gene network inference methods do not give consistent results. Current state-of-the-art study uses the average-ranking-based consensus method to combine and average the ranked predictions from individual methods. However each individual method has an equal contribution to the consen- sus prediction. We have developed a linear programming-based consensus approach which uses learned weights from linear programming among individual methods such that the methods have di↵erent weights depending on their performance. Our result reveals that assigning di↵erent weights to individual methods rather than giving them equal weights improves the performance of the consensus. The linear programming- based consensus method is evaluated and it had the best performance on in silico and Saccharomyces cerevisiae networks, and the second best on the Escherichia coli network outperformed by Inferelator Pipeline method which gives inconsistent results across a wide range of microarray data sets.

  3. Gene regulatory network interactions in sea urchin endomesoderm induction.

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    Aditya J Sethi

    2009-02-01

    Full Text Available A major goal of contemporary studies of embryonic development is to understand large sets of regulatory changes that accompany the phenomenon of embryonic induction. The highly resolved sea urchin pregastrular endomesoderm-gene regulatory network (EM-GRN provides a unique framework to study the global regulatory interactions underlying endomesoderm induction. Vegetal micromeres of the sea urchin embryo constitute a classic endomesoderm signaling center, whose potential to induce archenteron formation from presumptive ectoderm was demonstrated almost a century ago. In this work, we ectopically activate the primary mesenchyme cell-GRN (PMC-GRN that operates in micromere progeny by misexpressing the micromere determinant Pmar1 and identify the responding EM-GRN that is induced in animal blastomeres. Using localized loss-of -function analyses in conjunction with expression of endo16, the molecular definition of micromere-dependent endomesoderm specification, we show that the TGFbeta cytokine, ActivinB, is an essential component of this induction in blastomeres that emit this signal, as well as in cells that respond to it. We report that normal pregastrular endomesoderm specification requires activation of the Pmar1-inducible subset of the EM-GRN by the same cytokine, strongly suggesting that early micromere-mediated endomesoderm specification, which regulates timely gastrulation in the sea urchin embryo, is also ActivinB dependent. This study unexpectedly uncovers the existence of an additional uncharacterized micromere signal to endomesoderm progenitors, significantly revising existing models. In one of the first network-level characterizations of an intercellular inductive phenomenon, we describe an important in vivo model of the requirement of ActivinB signaling in the earliest steps of embryonic endomesoderm progenitor specification.

  4. Indeterminacy of reverse engineering of Gene Regulatory Networks: the curse of gene elasticity.

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    Arun Krishnan

    Full Text Available BACKGROUND: Gene Regulatory Networks (GRNs have become a major focus of interest in recent years. A number of reverse engineering approaches have been developed to help uncover the regulatory networks giving rise to the observed gene expression profiles. However, this is an overspecified problem due to the fact that more than one genotype (network wiring can give rise to the same phenotype. We refer to this phenomenon as "gene elasticity." In this work, we study the effect of this particular problem on the pure, data-driven inference of gene regulatory networks. METHODOLOGY: We simulated a four-gene network in order to produce "data" (protein levels that we use in lieu of real experimental data. We then optimized the network connections between the four genes with a view to obtain the original network that gave rise to the data. We did this for two different cases: one in which only the network connections were optimized and the other in which both the network connections as well as the kinetic parameters (given as reaction probabilities in our case were estimated. We observed that multiple genotypes gave rise to very similar protein levels. Statistical experimentation indicates that it is impossible to differentiate between the different networks on the basis of both equilibrium as well as dynamic data. CONCLUSIONS: We show explicitly that reverse engineering of GRNs from pure expression data is an indeterminate problem. Our results suggest the unsuitability of an inferential, purely data-driven approach for the reverse engineering transcriptional networks in the case of gene regulatory networks displaying a certain level of complexity.

  5. Stability Depends on Positive Autoregulation in Boolean Gene Regulatory Networks

    Science.gov (United States)

    Pinho, Ricardo; Garcia, Victor; Irimia, Manuel; Feldman, Marcus W.

    2014-01-01

    Network motifs have been identified as building blocks of regulatory networks, including gene regulatory networks (GRNs). The most basic motif, autoregulation, has been associated with bistability (when positive) and with homeostasis and robustness to noise (when negative), but its general importance in network behavior is poorly understood. Moreover, how specific autoregulatory motifs are selected during evolution and how this relates to robustness is largely unknown. Here, we used a class of GRN models, Boolean networks, to investigate the relationship between autoregulation and network stability and robustness under various conditions. We ran evolutionary simulation experiments for different models of selection, including mutation and recombination. Each generation simulated the development of a population of organisms modeled by GRNs. We found that stability and robustness positively correlate with autoregulation; in all investigated scenarios, stable networks had mostly positive autoregulation. Assuming biological networks correspond to stable networks, these results suggest that biological networks should often be dominated by positive autoregulatory loops. This seems to be the case for most studied eukaryotic transcription factor networks, including those in yeast, flies and mammals. PMID:25375153

  6. Stability depends on positive autoregulation in Boolean gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Ricardo Pinho

    2014-11-01

    Full Text Available Network motifs have been identified as building blocks of regulatory networks, including gene regulatory networks (GRNs. The most basic motif, autoregulation, has been associated with bistability (when positive and with homeostasis and robustness to noise (when negative, but its general importance in network behavior is poorly understood. Moreover, how specific autoregulatory motifs are selected during evolution and how this relates to robustness is largely unknown. Here, we used a class of GRN models, Boolean networks, to investigate the relationship between autoregulation and network stability and robustness under various conditions. We ran evolutionary simulation experiments for different models of selection, including mutation and recombination. Each generation simulated the development of a population of organisms modeled by GRNs. We found that stability and robustness positively correlate with autoregulation; in all investigated scenarios, stable networks had mostly positive autoregulation. Assuming biological networks correspond to stable networks, these results suggest that biological networks should often be dominated by positive autoregulatory loops. This seems to be the case for most studied eukaryotic transcription factor networks, including those in yeast, flies and mammals.

  7. Data Integration for Microarrays: Enhanced Inference for Gene Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Alina Sîrbu

    2015-05-01

    Full Text Available Microarray technologies have been the basis of numerous important findings regarding gene expression in the few last decades. Studies have generated large amounts of data describing various processes, which, due to the existence of public databases, are widely available for further analysis. Given their lower cost and higher maturity compared to newer sequencing technologies, these data continue to be produced, even though data quality has been the subject of some debate. However, given the large volume of data generated, integration can help overcome some issues related, e.g., to noise or reduced time resolution, while providing additional insight on features not directly addressed by sequencing methods. Here, we present an integration test case based on public Drosophila melanogaster datasets (gene expression, binding site affinities, known interactions. Using an evolutionary computation framework, we show how integration can enhance the ability to recover transcriptional gene regulatory networks from these data, as well as indicating which data types are more important for quantitative and qualitative network inference. Our results show a clear improvement in performance when multiple datasets are integrated, indicating that microarray data will remain a valuable and viable resource for some time to come.

  8. Gene-Regulatory Activity of α-Tocopherol

    Directory of Open Access Journals (Sweden)

    John K. Lodge

    2010-03-01

    Full Text Available Vitamin E is an essential vitamin and a lipid soluble antioxidant, at least, under in vitro conditions. The antioxidant properties of vitamin E are exerted through its phenolic hydroxyl group, which donates hydrogen to peroxyl radicals, resulting in the formation of stable lipid species. Beside an antioxidant role, important cell signalling properties of vitamin E have been described. By using gene chip technology we have identified α-tocopherol sensitive molecular targets in vivo including christmas factor (involved in the blood coagulation and 5α-steroid reductase type 1 (catalyzes the conversion of testosterone to 5α-dihydrotestosterone being upregulated and γ-glutamyl-cysteinyl synthetase (the rate limiting enzyme in GSH synthesis being downregulated due to a-tocopherol deficiency. α-Tocopherol regulates signal transduction cascades not only at the mRNA but also at the miRNA level since miRNA 122a (involved in lipid metabolism and miRNA 125b (involved in inflammation are downregulated by α-tocopherol. Genetic polymorphisms may determine the biological and gene-regulatory activity of a-tocopherol. In this context we have recently shown that genes encoding for proteins involved in peripheral α-tocopherol transport and degradation are significantly affected by the apoE genotype.

  9. Modeling gene regulatory networks: A network simplification algorithm

    Science.gov (United States)

    Ferreira, Luiz Henrique O.; de Castro, Maria Clicia S.; da Silva, Fabricio A. B.

    2016-12-01

    Boolean networks have been used for some time to model Gene Regulatory Networks (GRNs), which describe cell functions. Those models can help biologists to make predictions, prognosis and even specialized treatment when some disturb on the GRN lead to a sick condition. However, the amount of information related to a GRN can be huge, making the task of inferring its boolean network representation quite a challenge. The method shown here takes into account information about the interactome to build a network, where each node represents a protein, and uses the entropy of each node as a key to reduce the size of the network, allowing the further inferring process to focus only on the main protein hubs, the ones with most potential to interfere in overall network behavior.

  10. Analysis of deterministic cyclic gene regulatory network models with delays

    CERN Document Server

    Ahsen, Mehmet Eren; Niculescu, Silviu-Iulian

    2015-01-01

    This brief examines a deterministic, ODE-based model for gene regulatory networks (GRN) that incorporates nonlinearities and time-delayed feedback. An introductory chapter provides some insights into molecular biology and GRNs. The mathematical tools necessary for studying the GRN model are then reviewed, in particular Hill functions and Schwarzian derivatives. One chapter is devoted to the analysis of GRNs under negative feedback with time delays and a special case of a homogenous GRN is considered. Asymptotic stability analysis of GRNs under positive feedback is then considered in a separate chapter, in which conditions leading to bi-stability are derived. Graduate and advanced undergraduate students and researchers in control engineering, applied mathematics, systems biology and synthetic biology will find this brief to be a clear and concise introduction to the modeling and analysis of GRNs.

  11. Validation of Gene Regulatory Network Inference Based on Controllability

    Directory of Open Access Journals (Sweden)

    Edward eDougherty

    2013-12-01

    Full Text Available There are two distinct issues regarding network validation: (1 Does an inferred network provide good predictions relative to experimental data? (2 Does a network inference algorithm applied within a certain network model framework yield networks that are accurate relative to some criterion of goodness? The first issue concerns scientific validation and the second concerns algorithm validation. In this paper we consider inferential validation relative to controllability; that is, if an inference procedure is applied to synthetic data generated from a gene regulatory network and an intervention procedure is designed on the inferred network, how well does it perform on the true network? The reasoning behind such a criterion is that, if our purpose is to use gene regulatory networks to design therapeutic intervention strategies, then we are not concerned with network fidelity, per se, but only with our ability to design effective interventions based on the inferred network. We will consider the problem from the perspectives of stationary control, which involves designing a control policy to be applied over time based on the current state of the network, with the decision procedure itself being time independent. {The objective of a control policy is to optimally reduce the total steady-state probability mass of the undesirable states (phenotypes, which is equivalent to optimally increasing the total steady-state mass of the desirable states. Based on this criterion we compare several proposed network inference procedures. We will see that inference procedure psi may perform poorer than inference procedure xi relative to inferring the full network structure but perform better than xi relative to controllability. Hence, when one is aiming at a specific application, it may be wise to use an objective-based measure of inference validity.

  12. Clinical characteristics and prognosis of acute myeloid leukemia associated with DNA-methylation regulatory gene mutations.

    Science.gov (United States)

    Ryotokuji, Takeshi; Yamaguchi, Hiroki; Ueki, Toshimitsu; Usuki, Kensuke; Kurosawa, Saiko; Kobayashi, Yutaka; Kawata, Eri; Tajika, Kenji; Gomi, Seiji; Kanda, Junya; Kobayashi, Anna; Omori, Ikuko; Marumo, Atsushi; Fujiwara, Yusuke; Yui, Shunsuke; Terada, Kazuki; Fukunaga, Keiko; Hirakawa, Tsuneaki; Arai, Kunihito; Kitano, Tomoaki; Kosaka, Fumiko; Tamai, Hayato; Nakayama, Kazutaka; Wakita, Satoshi; Fukuda, Takahiro; Inokuchi, Koiti

    2016-09-01

    In recent years, it has been reported that the frequency of DNA-methylation regulatory gene mutations - mutations of the genes that regulate gene expression through DNA methylation - is high in acute myeloid leukemia. The objective of the present study was to elucidate the clinical characteristics and prognosis of acute myeloid leukemia with associated DNA-methylation regulatory gene mutation. We studied 308 patients with acute myeloid leukemia. DNA-methylation regulatory gene mutations were observed in 135 of the 308 cases (43.8%). Acute myeloid leukemia associated with a DNA-methylation regulatory gene mutation was more frequent in older patients (Pgene mutation was an unfavorable prognostic factor for overall survival in the whole cohort (P=0.0018), in patients aged ≤70 years, in patients with intermediate cytogenetic risk, and in FLT3-ITD-negative patients (P=0.0409). Among the patients with DNA-methylation regulatory gene mutations, 26.7% were found to have two or more such mutations and prognosis worsened with increasing number of mutations. In multivariate analysis DNA-methylation regulatory gene mutation was an independent unfavorable prognostic factor for overall survival (P=0.0424). However, patients with a DNA-methylation regulatory gene mutation who underwent allogeneic stem cell transplantation in first remission had a significantly better prognosis than those who did not undergo such transplantation (P=0.0254). Our study establishes that DNA-methylation regulatory gene mutation is an important unfavorable prognostic factor in acute myeloid leukemia.

  13. Using SCOPE to identify potential regulatory motifs in coregulated genes.

    Science.gov (United States)

    Martyanov, Viktor; Gross, Robert H

    2011-05-31

    SCOPE is an ensemble motif finder that uses three component algorithms in parallel to identify potential regulatory motifs by over-representation and motif position preference. Each component algorithm is optimized to find a different kind of motif. By taking the best of these three approaches, SCOPE performs better than any single algorithm, even in the presence of noisy data. In this article, we utilize a web version of SCOPE to examine genes that are involved in telomere maintenance. SCOPE has been incorporated into at least two other motif finding programs and has been used in other studies. The three algorithms that comprise SCOPE are BEAM, which finds non-degenerate motifs (ACCGGT), PRISM, which finds degenerate motifs (ASCGWT), and SPACER, which finds longer bipartite motifs (ACCnnnnnnnnGGT). These three algorithms have been optimized to find their corresponding type of motif. Together, they allow SCOPE to perform extremely well. Once a gene set has been analyzed and candidate motifs identified, SCOPE can look for other genes that contain the motif which, when added to the original set, will improve the motif score. This can occur through over-representation or motif position preference. Working with partial gene sets that have biologically verified transcription factor binding sites, SCOPE was able to identify most of the rest of the genes also regulated by the given transcription factor. Output from SCOPE shows candidate motifs, their significance, and other information both as a table and as a graphical motif map. FAQs and video tutorials are available at the SCOPE web site which also includes a "Sample Search" button that allows the user to perform a trial run. Scope has a very friendly user interface that enables novice users to access the algorithm's full power without having to become an expert in the bioinformatics of motif finding. As input, SCOPE can take a list of genes, or FASTA sequences. These can be entered in browser text fields, or read from

  14. Evolution of the CNS myelin gene regulatory program.

    Science.gov (United States)

    Li, Huiliang; Richardson, William D

    2016-06-15

    Myelin is a specialized subcellular structure that evolved uniquely in vertebrates. A myelinated axon conducts action potentials many times faster than an unmyelinated axon of the same diameter; for the same conduction speed, the unmyelinated axon would need a much larger diameter and volume than its myelinated counterpart. Hence myelin speeds information transfer and saves space, allowing the evolution of a powerful yet portable brain. Myelination in the central nervous system (CNS) is controlled by a gene regulatory program that features a number of master transcriptional regulators including Olig1, Olig2 and Myrf. Olig family genes evolved from a single ancestral gene in non-chordates. Olig2, which executes multiple functions with regard to oligodendrocyte identity and development in vertebrates, might have evolved functional versatility through post-translational modification, especially phosphorylation, as illustrated by its evolutionarily conserved serine/threonine phospho-acceptor sites and its accumulation of serine residues during more recent stages of vertebrate evolution. Olig1, derived from a duplicated copy of Olig2 in early bony fish, is involved in oligodendrocyte development and is critical to remyelination in bony vertebrates, but is lost in birds. The origin of Myrf orthologs might be the result of DNA integration between an invading phage or bacterium and an early protist, producing a fusion protein capable of self-cleavage and DNA binding. Myrf seems to have adopted new functions in early vertebrates - initiation of the CNS myelination program as well as the maintenance of mature oligodendrocyte identity and myelin structure - by developing new ways to interact with DNA motifs specific to myelin genes. This article is part of a Special Issue entitled SI: Myelin Evolution.

  15. BCIP: a gene-centered platform for identifying potential regulatory genes in breast cancer

    Science.gov (United States)

    Wu, Jiaqi; Hu, Shuofeng; Chen, Yaowen; Li, Zongcheng; Zhang, Jian; Yuan, Hanyu; Shi, Qiang; Shao, Ningsheng; Ying, Xiaomin

    2017-01-01

    Breast cancer is a disease with high heterogeneity. Many issues on tumorigenesis and progression are still elusive. It is critical to identify genes that play important roles in the progression of tumors, especially for tumors with poor prognosis such as basal-like breast cancer and tumors in very young women. To facilitate the identification of potential regulatory or driver genes, we present the Breast Cancer Integrative Platform (BCIP, http://omics.bmi.ac.cn/bcancer/). BCIP maintains multi-omics data selected with strict quality control and processed with uniform normalization methods, including gene expression profiles from 9,005 tumor and 376 normal tissue samples, copy number variation information from 3,035 tumor samples, microRNA-target interactions, co-expressed genes, KEGG pathways, and mammary tissue-specific gene functional networks. This platform provides a user-friendly interface integrating comprehensive and flexible analysis tools on differential gene expression, copy number variation, and survival analysis. The prominent characteristic of BCIP is that users can perform analysis by customizing subgroups with single or combined clinical features, including subtypes, histological grades, pathologic stages, metastasis status, lymph node status, ER/PR/HER2 status, TP53 mutation status, menopause status, age, tumor size, therapy responses, and prognosis. BCIP will help to identify regulatory or driver genes and candidate biomarkers for further research in breast cancer. PMID:28327601

  16. Improving gene regulatory network inference using network topology information.

    Science.gov (United States)

    Nair, Ajay; Chetty, Madhu; Wangikar, Pramod P

    2015-09-01

    Inferring the gene regulatory network (GRN) structure from data is an important problem in computational biology. However, it is a computationally complex problem and approximate methods such as heuristic search techniques, restriction of the maximum-number-of-parents (maxP) for a gene, or an optimal search under special conditions are required. The limitations of a heuristic search are well known but literature on the detailed analysis of the widely used maxP technique is lacking. The optimal search methods require large computational time. We report the theoretical analysis and experimental results of the strengths and limitations of the maxP technique. Further, using an optimal search method, we combine the strengths of the maxP technique and the known GRN topology to propose two novel algorithms. These algorithms are implemented in a Bayesian network framework and tested on biological, realistic, and in silico networks of different sizes and topologies. They overcome the limitations of the maxP technique and show superior computational speed when compared to the current optimal search algorithms.

  17. Automated large-scale control of gene regulatory networks.

    Science.gov (United States)

    Tan, Mehmet; Alhajj, Reda; Polat, Faruk

    2010-04-01

    Controlling gene regulatory networks (GRNs) is an important and hard problem. As it is the case in all control problems, the curse of dimensionality is the main issue in real applications. It is possible that hundreds of genes may regulate one biological activity in an organism; this implies a huge state space, even in the case of Boolean models. This is also evident in the literature that shows that only models of small portions of the genome could be used in control applications. In this paper, we empower our framework for controlling GRNs by eliminating the need for expert knowledge to specify some crucial threshold that is necessary for producing effective results. Our framework is characterized by applying the factored Markov decision problem (FMDP) method to the control problem of GRNs. The FMDP is a suitable framework for large state spaces as it represents the probability distribution of state transitions using compact models so that more space and time efficient algorithms could be devised for solving control problems. We successfully mapped the GRN control problem to an FMDP and propose a model reduction algorithm that helps find approximate solutions for large networks by using existing FMDP solvers. The test results reported in this paper demonstrate the efficiency and effectiveness of the proposed approach.

  18. An algebra-based method for inferring gene regulatory networks.

    Science.gov (United States)

    Vera-Licona, Paola; Jarrah, Abdul; Garcia-Puente, Luis David; McGee, John; Laubenbacher, Reinhard

    2014-03-26

    The inference of gene regulatory networks (GRNs) from experimental observations is at the heart of systems biology. This includes the inference of both the network topology and its dynamics. While there are many algorithms available to infer the network topology from experimental data, less emphasis has been placed on methods that infer network dynamics. Furthermore, since the network inference problem is typically underdetermined, it is essential to have the option of incorporating into the inference process, prior knowledge about the network, along with an effective description of the search space of dynamic models. Finally, it is also important to have an understanding of how a given inference method is affected by experimental and other noise in the data used. This paper contains a novel inference algorithm using the algebraic framework of Boolean polynomial dynamical systems (BPDS), meeting all these requirements. The algorithm takes as input time series data, including those from network perturbations, such as knock-out mutant strains and RNAi experiments. It allows for the incorporation of prior biological knowledge while being robust to significant levels of noise in the data used for inference. It uses an evolutionary algorithm for local optimization with an encoding of the mathematical models as BPDS. The BPDS framework allows an effective representation of the search space for algebraic dynamic models that improves computational performance. The algorithm is validated with both simulated and experimental microarray expression profile data. Robustness to noise is tested using a published mathematical model of the segment polarity gene network in Drosophila melanogaster. Benchmarking of the algorithm is done by comparison with a spectrum of state-of-the-art network inference methods on data from the synthetic IRMA network to demonstrate that our method has good precision and recall for the network reconstruction task, while also predicting several of the

  19. The impact of gene expression variation on the robustness and evolvability of a developmental gene regulatory network.

    Directory of Open Access Journals (Sweden)

    David A Garfield

    2013-10-01

    Full Text Available Regulatory interactions buffer development against genetic and environmental perturbations, but adaptation requires phenotypes to change. We investigated the relationship between robustness and evolvability within the gene regulatory network underlying development of the larval skeleton in the sea urchin Strongylocentrotus purpuratus. We find extensive variation in gene expression in this network throughout development in a natural population, some of which has a heritable genetic basis. Switch-like regulatory interactions predominate during early development, buffer expression variation, and may promote the accumulation of cryptic genetic variation affecting early stages. Regulatory interactions during later development are typically more sensitive (linear, allowing variation in expression to affect downstream target genes. Variation in skeletal morphology is associated primarily with expression variation of a few, primarily structural, genes at terminal positions within the network. These results indicate that the position and properties of gene interactions within a network can have important evolutionary consequences independent of their immediate regulatory role.

  20. Genomic regulatory blocks encompass multiple neighboring genes and maintain conserved synteny in vertebrates

    OpenAIRE

    Kikuta, Hiroshi; Laplante, Mary; Navrátilová, Pavla; Komisarczuk, Anna Zofia; Engström, Pär G.; Fredman, David; Akalin, Altuna; Caccamo, Mario; Sealy, Ian; Howe, Kerstin; Ghislain, Julien; Pezeron, Guillaume; Mourrain, Philippe; Ellingsen, Staale; Oates, Andrew C.

    2007-01-01

    We report evidence for a mechanism for the maintenance of long-range conserved synteny across vertebrate genomes. We found the largest mammal-teleost conserved chromosomal segments to be spanned by highly conserved noncoding elements (HCNEs), their developmental regulatory target genes, and phylogenetically and functionally unrelated “bystander” genes. Bystander genes are not specifically under the control of the regulatory elements that drive the target genes and are expressed in patterns th...

  1. Modular reorganization of the global network of gene regulatory interactions during perinatal human brain development

    OpenAIRE

    Monzón-Sandoval, Jimena; Castillo-Morales, Atahualpa; Urrutia, Araxi O.; Gutierrez, Humberto

    2016-01-01

    Background During early development of the nervous system, gene expression patterns are known to vary widely depending on the specific developmental trajectories of different structures. Observable changes in gene expression profiles throughout development are determined by an underlying network of precise regulatory interactions between individual genes. Elucidating the organizing principles that shape this gene regulatory network is one of the central goals of developmental biology. Whether...

  2. Gene Regulatory Networks from Multifactorial Perturbations Using Graphical Lasso: Application to the DREAM4 Challenge

    NARCIS (Netherlands)

    Menéndez, P.; Kourmpetis, Y.I.A.; Braak, ter C.J.F.; Eeuwijk, van F.A.

    2010-01-01

    A major challenge in the field of systems biology consists of predicting gene regulatory networks based on different training data. Within the DREAM4 initiative, we took part in the multifactorial sub-challenge that aimed to predict gene regulatory networks of size 100 from training data consisting

  3. Inference of Cancer-specific Gene Regulatory Networks Using Soft Computing Rules

    Directory of Open Access Journals (Sweden)

    Xiaosheng Wang

    2010-03-01

    Full Text Available Perturbations of gene regulatory networks are essentially responsible for oncogenesis. Therefore, inferring the gene regulatory networks is a key step to overcoming cancer. In this work, we propose a method for inferring directed gene regulatory networks based on soft computing rules, which can identify important cause-effect regulatory relations of gene expression. First, we identify important genes associated with a specific cancer (colon cancer using a supervised learning approach. Next, we reconstruct the gene regulatory networks by inferring the regulatory relations among the identified genes, and their regulated relations by other genes within the genome. We obtain two meaningful findings. One is that upregulated genes are regulated by more genes than downregulated ones, while downregulated genes regulate more genes than upregulated ones. The other one is that tumor suppressors suppress tumor activators and activate other tumor suppressors strongly, while tumor activators activate other tumor activators and suppress tumor suppressors weakly, indicating the robustness of biological systems. These findings provide valuable insights into the pathogenesis of cancer.

  4. Understanding the Dynamics of Gene Regulatory Systems; Characterisation and Clinical Relevance of cis-Regulatory Polymorphisms

    Directory of Open Access Journals (Sweden)

    Philip Cowie

    2013-01-01

    Full Text Available Modern genetic analysis has shown that most polymorphisms associated with human disease are non-coding. Much of the functional information contained in the non-coding genome consists of cis-regulatory sequences (CRSs that are required to respond to signal transduction cues that direct cell specific gene expression. It has been hypothesised that many diseases may be due to polymorphisms within CRSs that alter their responses to signal transduction cues. However, identification of CRSs, and the effects of allelic variation on their ability to respond to signal transduction cues, is still at an early stage. In the current review we describe the use of comparative genomics and experimental techniques that allow for the identification of CRSs building on recent advances by the ENCODE consortium. In addition we describe techniques that allow for the analysis of the effects of allelic variation and epigenetic modification on CRS responses to signal transduction cues. Using specific examples we show that the interactions driving these elements are highly complex and the effects of disease associated polymorphisms often subtle. It is clear that gaining an understanding of the functions of CRSs, and how they are affected by SNPs and epigenetic modification, is essential to understanding the genetic basis of human disease and stratification whilst providing novel directions for the development of personalised medicine.

  5. Regulatory elements of Caenorhabditis elegans ribosomal protein genes

    Directory of Open Access Journals (Sweden)

    Sleumer Monica C

    2012-08-01

    Full Text Available Abstract Background Ribosomal protein genes (RPGs are essential, tightly regulated, and highly expressed during embryonic development and cell growth. Even though their protein sequences are strongly conserved, their mechanism of regulation is not conserved across yeast, Drosophila, and vertebrates. A recent investigation of genomic sequences conserved across both nematode species and associated with different gene groups indicated the existence of several elements in the upstream regions of C. elegans RPGs, providing a new insight regarding the regulation of these genes in C. elegans. Results In this study, we performed an in-depth examination of C. elegans RPG regulation and found nine highly conserved motifs in the upstream regions of C. elegans RPGs using the motif discovery algorithm DME. Four motifs were partially similar to transcription factor binding sites from C. elegans, Drosophila, yeast, and human. One pair of these motifs was found to co-occur in the upstream regions of 250 transcripts including 22 RPGs. The distance between the two motifs displayed a complex frequency pattern that was related to their relative orientation. We tested the impact of three of these motifs on the expression of rpl-2 using a series of reporter gene constructs and showed that all three motifs are necessary to maintain the high natural expression level of this gene. One of the motifs was similar to the binding site of an orthologue of POP-1, and we showed that RNAi knockdown of pop-1 impacts the expression of rpl-2. We further determined the transcription start site of rpl-2 by 5’ RACE and found that the motifs lie 40–90 bases upstream of the start site. We also found evidence that a noncoding RNA, contained within the outron of rpl-2, is co-transcribed with rpl-2 and cleaved during trans-splicing. Conclusions Our results indicate that C. elegans RPGs are regulated by a complex novel series of regulatory elements that is evolutionarily distinct from

  6. Discovery of time-delayed gene regulatory networks based on temporal gene expression profiling

    Directory of Open Access Journals (Sweden)

    Guo Zheng

    2006-01-01

    Full Text Available Abstract Background It is one of the ultimate goals for modern biological research to fully elucidate the intricate interplays and the regulations of the molecular determinants that propel and characterize the progression of versatile life phenomena, to name a few, cell cycling, developmental biology, aging, and the progressive and recurrent pathogenesis of complex diseases. The vast amount of large-scale and genome-wide time-resolved data is becoming increasing available, which provides the golden opportunity to unravel the challenging reverse-engineering problem of time-delayed gene regulatory networks. Results In particular, this methodological paper aims to reconstruct regulatory networks from temporal gene expression data by using delayed correlations between genes, i.e., pairwise overlaps of expression levels shifted in time relative each other. We have thus developed a novel model-free computational toolbox termed TdGRN (Time-delayed Gene Regulatory Network to address the underlying regulations of genes that can span any unit(s of time intervals. This bioinformatics toolbox has provided a unified approach to uncovering time trends of gene regulations through decision analysis of the newly designed time-delayed gene expression matrix. We have applied the proposed method to yeast cell cycling and human HeLa cell cycling and have discovered most of the underlying time-delayed regulations that are supported by multiple lines of experimental evidence and that are remarkably consistent with the current knowledge on phase characteristics for the cell cyclings. Conclusion We established a usable and powerful model-free approach to dissecting high-order dynamic trends of gene-gene interactions. We have carefully validated the proposed algorithm by applying it to two publicly available cell cycling datasets. In addition to uncovering the time trends of gene regulations for cell cycling, this unified approach can also be used to study the complex

  7. Gene expression in the urinary bladder: a common carcinoma in situ gene expression signature exists disregarding histopathological classification

    DEFF Research Database (Denmark)

    Andersen, Lars Dyrskjøt; Kruhøffer, Mogens; Andersen, Thomas Thykjær

    2004-01-01

    that contained genes with similar expression levels in transitional cell carcinoma (TCC) with surrounding CIS and invasive TCC. However, no close relationship between TCC with adjacent CIS and invasive TCC was observed using hierarchical cluster analysis. Expression profiling of a series of biopsies from normal...... urothelium and urothelium with CIS lesions from the same urinary bladder revealed that the gene expression found in sTCC with surrounding CIS is found also in CIS biopsies as well as in histologically normal samples adjacent to the CIS lesions. Furthermore, we also identified similar gene expression changes...... not only in CIS biopsies but also in sTCC, mTCC, and, remarkably, in histologically normal urothelium from bladders with CIS. Identification of this expression signature could provide guidance for the selection of therapy and follow-up regimen in patients with early stage bladder cancer....

  8. Reconstruction of gene regulatory modules in cancer cell cycle by multi-source data integration.

    Directory of Open Access Journals (Sweden)

    Yuji Zhang

    Full Text Available BACKGROUND: Precise regulation of the cell cycle is crucial to the growth and development of all organisms. Understanding the regulatory mechanism of the cell cycle is crucial to unraveling many complicated diseases, most notably cancer. Multiple sources of biological data are available to study the dynamic interactions among many genes that are related to the cancer cell cycle. Integrating these informative and complementary data sources can help to infer a mutually consistent gene transcriptional regulatory network with strong similarity to the underlying gene regulatory relationships in cancer cells. RESULTS AND PRINCIPAL FINDINGS: We propose an integrative framework that infers gene regulatory modules from the cell cycle of cancer cells by incorporating multiple sources of biological data, including gene expression profiles, gene ontology, and molecular interaction. Among 846 human genes with putative roles in cell cycle regulation, we identified 46 transcription factors and 39 gene ontology groups. We reconstructed regulatory modules to infer the underlying regulatory relationships. Four regulatory network motifs were identified from the interaction network. The relationship between each transcription factor and predicted target gene groups was examined by training a recurrent neural network whose topology mimics the network motif(s to which the transcription factor was assigned. Inferred network motifs related to eight well-known cell cycle genes were confirmed by gene set enrichment analysis, binding site enrichment analysis, and comparison with previously published experimental results. CONCLUSIONS: We established a robust method that can accurately infer underlying relationships between a given transcription factor and its downstream target genes by integrating different layers of biological data. Our method could also be beneficial to biologists for predicting the components of regulatory modules in which any candidate gene is involved

  9. Vitamin D receptor gene Alw I, Fok I, Apa I, and Taq I polymorphisms in patients with urinary stone.

    Science.gov (United States)

    Seo, Ill Young; Kang, In-Hong; Chae, Soo-Cheon; Park, Seung Chol; Lee, Young-Jin; Yang, Yun Sik; Ryu, Soo Bang; Rim, Joung Sik

    2010-04-01

    To evaluate vitamin D receptor (VDR) gene polymorphisms in Korean patients so as to identify the candidate genes associated with urinary stones. Urinary stones are a multifactorial disease that includes various genetic factors. A normal control group of 535 healthy subjects and 278 patients with urinary stones was evaluated. Of 125 patients who presented stone samples, 102 had calcium stones on chemical analysis. The VDR gene Alw I, Fok I, Apa I, and Taq I polymorphisms were evaluated using the polymerase chain reaction-restriction fragment length polymorphism analysis. Allelic and genotypic frequencies were calculated to identify associations in both groups. The haplotype frequencies of the VDR gene polymorphisms for multiple loci were also determined. For the VDR gene Alw I, Fok I, Apa I, and Taq I polymorphisms, there was no statistically significant difference between the patients with urinary stones and the healthy controls. There was also no statistically significant difference between the patients with calcium stones and the healthy controls. A novel haplotype (Ht 4; CTTT) was identified in 13.5% of the patients with urinary stones and in 8.3% of the controls (P = .001). The haplotype frequencies were significantly different between the patients with calcium stones and the controls (P = .004). The VDR gene Alw I, Fok I, Apa I, and Taq I polymorphisms does not seem to be candidate genetic markers for urinary stones in Korean patients. However, 1 novel haplotype of the VDR gene polymorphisms for multiple loci might be a candidate genetic marker. Copyright 2010 Elsevier Inc. All rights reserved.

  10. Motif-guided sparse decomposition of gene expression data for regulatory module identification

    Directory of Open Access Journals (Sweden)

    Hoffman Eric P

    2011-03-01

    Full Text Available Abstract Background Genes work coordinately as gene modules or gene networks. Various computational approaches have been proposed to find gene modules based on gene expression data; for example, gene clustering is a popular method for grouping genes with similar gene expression patterns. However, traditional gene clustering often yields unsatisfactory results for regulatory module identification because the resulting gene clusters are co-expressed but not necessarily co-regulated. Results We propose a novel approach, motif-guided sparse decomposition (mSD, to identify gene regulatory modules by integrating gene expression data and DNA sequence motif information. The mSD approach is implemented as a two-step algorithm comprising estimates of (1 transcription factor activity and (2 the strength of the predicted gene regulation event(s. Specifically, a motif-guided clustering method is first developed to estimate the transcription factor activity of a gene module; sparse component analysis is then applied to estimate the regulation strength, and so predict the target genes of the transcription factors. The mSD approach was first tested for its improved performance in finding regulatory modules using simulated and real yeast data, revealing functionally distinct gene modules enriched with biologically validated transcription factors. We then demonstrated the efficacy of the mSD approach on breast cancer cell line data and uncovered several important gene regulatory modules related to endocrine therapy of breast cancer. Conclusion We have developed a new integrated strategy, namely motif-guided sparse decomposition (mSD of gene expression data, for regulatory module identification. The mSD method features a novel motif-guided clustering method for transcription factor activity estimation by finding a balance between co-regulation and co-expression. The mSD method further utilizes a sparse decomposition method for regulation strength estimation. The

  11. Potential applications of gene therapy/transfer to the treatment of lower urinary tract diseases/disorders.

    Science.gov (United States)

    Christ, George J

    2011-01-01

    Identification of molecular targets for novel therapeutics is a natural consequence of the age of molecular and personalized medicine. How this information is leveraged and applied to the treatment of functional diseases/disorders of the lower urinary tract will determine if this field of medicine can keep pace with technological developments and patient expectations for improved therapies. In this regard, therapeutic improvements for the treatment of lower urinary tract diseases and disorders have been largely incremental over the past 30 years. The goal of this report is to review the evidence pointing toward the enormous potential of gene therapy/transfer to provide a paradigm shift from palliative to curative therapeutic solutions for lower urinary tract diseases/disorders. In fact, it seems clear that gene therapy represents a biotechnology approach particularly suitable to applications in the lower urinary tract. Although much more research is required, ample preclinical evidence already indicates that, for example, gene therapy can favorably impact/alter virtually every aspect of bladder physiology/function. In short, further investigations and continued applications of gene therapy to the treatment of lower urinary tract diseases/disorders seems a prudent step toward potentially marked and more durable therapeutic improvements.

  12. Study on relationship of apolipoprotein E gene polymorphism and genetic susceptibility of stress urinary incontinence

    Institute of Scientific and Technical Information of China (English)

    Tong Jia-li; Lang Jing-he; Zhu lan

    2010-01-01

    Objective: To explore the relationship between apolipoprotein E (ApoE) gene polymorphism and susceptibility of stress urinary incontinence (SUI).Methods: ApoE genotypes were examined by polymerase chain reaction-restricted fragment length polymorphism (PCR-RFLP) technique in 99 patients with SUI and 101 asymptomatic controls. Results: The frequency of allele e3 of ApoE was slightly lower in patients with anatomic SUI than that in controls (79.44% vs. 81.68%), while the frequency of allele e4 of ApoE was slightly higher in patients with anatomic SUI than that in controls (10.00% vs. 9.90%). No significant difference was found in frequency of allele e3 or e4 between SUI patients and controls (χ2=0.523, P=0.770).Conclusion: The gene polymorphism of ApoE is not independently involved in the development of SUI.

  13. Comparative analysis of chromatin landscape in regulatory regions of human housekeeping and tissue specific genes

    Directory of Open Access Journals (Sweden)

    Dasgupta Dipayan

    2005-05-01

    Full Text Available Abstract Background Global regulatory mechanisms involving chromatin assembly and remodelling in the promoter regions of genes is implicated in eukaryotic transcription control especially for genes subjected to spatial and temporal regulation. The potential to utilise global regulatory mechanisms for controlling gene expression might depend upon the architecture of the chromatin in and around the gene. In-silico analysis can yield important insights into this aspect, facilitating comparison of two or more classes of genes comprising of a large number of genes within each group. Results In the present study, we carried out a comparative analysis of chromatin characteristics in terms of the scaffold/matrix attachment regions, nucleosome formation potential and the occurrence of repetitive sequences, in the upstream regulatory regions of housekeeping and tissue specific genes. Our data show that putative scaffold/matrix attachment regions are more abundant and nucleosome formation potential is higher in the 5' regions of tissue specific genes as compared to the housekeeping genes. Conclusion The differences in the chromatin features between the two groups of genes indicate the involvement of chromatin organisation in the control of gene expression. The presence of global regulatory mechanisms mediated through chromatin organisation can decrease the burden of invoking gene specific regulators for maintenance of the active/silenced state of gene expression. This could partially explain the lower number of genes estimated in the human genome.

  14. DMPD: Type I interferon [corrected] gene induction by the interferon regulatory factorfamily of transcription factors. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available 16979567 Type I interferon [corrected] gene induction by the interferon regulatory factorfamily...ng) (.svg) (.html) (.csml) Show Type I interferon [corrected] gene induction by the interferon regulatory factorfamily...orrected] gene induction by the interferon regulatory factorfamily of transcription factors. Authors Honda K

  15. Overview of methods of reverse engineering of gene regulatory networks: Boolean and Bayesian networks

    Directory of Open Access Journals (Sweden)

    Frolova A. O.

    2012-06-01

    Full Text Available Reverse engineering of gene regulatory networks is an intensively studied topic in Systems Biology as it reconstructs regulatory interactions between all genes in the genome in the most complete form. The extreme computational complexity of this problem and lack of thorough reviews on reconstruction methods of gene regulatory network is a significant obstacle to further development of this area. In this article the two most common methods for modeling gene regulatory networks are surveyed: Boolean and Bayesian networks. The mathematical description of each method is given, as well as several algorithmic approaches to modeling gene networks using these methods; the complexity of algorithms and the problems that arise during its implementation are also noted.

  16. Experimental design for parameter estimation of gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Bernhard Steiert

    Full Text Available Systems biology aims for building quantitative models to address unresolved issues in molecular biology. In order to describe the behavior of biological cells adequately, gene regulatory networks (GRNs are intensively investigated. As the validity of models built for GRNs depends crucially on the kinetic rates, various methods have been developed to estimate these parameters from experimental data. For this purpose, it is favorable to choose the experimental conditions yielding maximal information. However, existing experimental design principles often rely on unfulfilled mathematical assumptions or become computationally demanding with growing model complexity. To solve this problem, we combined advanced methods for parameter and uncertainty estimation with experimental design considerations. As a showcase, we optimized three simulated GRNs in one of the challenges from the Dialogue for Reverse Engineering Assessment and Methods (DREAM. This article presents our approach, which was awarded the best performing procedure at the DREAM6 Estimation of Model Parameters challenge. For fast and reliable parameter estimation, local deterministic optimization of the likelihood was applied. We analyzed identifiability and precision of the estimates by calculating the profile likelihood. Furthermore, the profiles provided a way to uncover a selection of most informative experiments, from which the optimal one was chosen using additional criteria at every step of the design process. In conclusion, we provide a strategy for optimal experimental design and show its successful application on three highly nonlinear dynamic models. Although presented in the context of the GRNs to be inferred for the DREAM6 challenge, the approach is generic and applicable to most types of quantitative models in systems biology and other disciplines.

  17. Urinary exosomes: a novel means to non-invasively assess changes in renal gene and protein expression.

    Directory of Open Access Journals (Sweden)

    Silvia Spanu

    Full Text Available BACKGROUND: In clinical practice, there is a lack of markers for the non-invasive diagnosis and follow-up of kidney disease. Exosomes are membrane vesicles, which are secreted from their cells of origin into surrounding body fluids and contain proteins and mRNA which are protected from digestive enzymes by a cell membrane. METHODS: Toxic podocyte damage was induced by puromycin aminonucleoside in rats (PAN. Urinary exosomes were isolated by ultracentrifugation at different time points during the disease. Exosomal mRNA was isolated, amplified, and the mRNA species were globally assessed by gene array analysis. Tissue-specific gene and protein expression was assessed by RT-qPCR analysis and immunohistochemistry. RESULTS: Gene array analysis of mRNA isolated from urinary exosomes revealed cystatin C mRNA as one of the most highly regulated genes. Its gene expression increased 7.5-fold by day 5 and remained high with a 1.9-fold increase until day 10. This was paralleled by a 2-fold increase in cystatin C mRNA expression in the renal cortex. Protein expression in the kidneys also dramatically increased with de novo expression of cystatin C in glomerular podocytes in parts of the proximal tubule and the renal medulla. Urinary excretion of cystatin C increased approximately 2-fold. CONCLUSION: In this proof-of-concept study, we could demonstrate that changes in urinary exosomal cystatin C mRNA expression are representative of changes in renal mRNA and protein expression. Because cells lining the urinary tract produce urinary exosomal cystatin C mRNA, it might be a more specific marker of renal damage than glomerular-filtered free cystatin C.

  18. Characterization of the nifA regulatory gene of Rhizobium leguminosarum PRE.

    NARCIS (Netherlands)

    Roelvink, P.W.

    1989-01-01

    This thesis describes the characterization of the nif A regulatory gene of the pea endosymbiont Rhizobiumleguminosarum PRE.Chapter I gives a general overview on the regulation of nitrogen fixation in diazotrophs, with special focus on the regulatory NifA pr

  19. The Association between Infants' Self-Regulatory Behavior and MAOA Gene Polymorphism

    Science.gov (United States)

    Zhang, Minghao; Chen, Xinyin; Way, Niobe; Yoshikawa, Hirokazu; Deng, Huihua; Ke, Xiaoyan; Yu, Weiwei; Chen, Ping; He, Chuan; Chi, Xia; Lu, Zuhong

    2011-01-01

    Self-regulatory behavior in early childhood is an important characteristic that has considerable implications for the development of adaptive and maladaptive functioning. The present study investigated the relations between a functional polymorphism in the upstream region of monoamine oxidase A gene (MAOA) and self-regulatory behavior in a sample…

  20. From Gene Regulation to Gene Function: Regulatory Networks in Bacillus Subtilis

    Directory of Open Access Journals (Sweden)

    Ivan Moszer

    2006-04-01

    Full Text Available Bacillus subtilis is a sporulating Gram-positive bacterium that lives primarily in the soil and associated water sources. The publication of the B. subtilis genome sequence and subsequent systematic functional analysis and gene regulation programmes, together with an extensive understanding of its biochemistry and physiology, makes this micro-organism a prime candidate in which to model regulatory networks in silico. In this paper we discuss combined molecular biological and bioinformatical approaches that are being developed to model this organism’s responses to changes in its environment.

  1. Large-scale modeling of condition-specific gene regulatory networks by information integration and inference.

    Science.gov (United States)

    Ellwanger, Daniel Christian; Leonhardt, Jörn Florian; Mewes, Hans-Werner

    2014-12-01

    Understanding how regulatory networks globally coordinate the response of a cell to changing conditions, such as perturbations by shifting environments, is an elementary challenge in systems biology which has yet to be met. Genome-wide gene expression measurements are high dimensional as these are reflecting the condition-specific interplay of thousands of cellular components. The integration of prior biological knowledge into the modeling process of systems-wide gene regulation enables the large-scale interpretation of gene expression signals in the context of known regulatory relations. We developed COGERE (http://mips.helmholtz-muenchen.de/cogere), a method for the inference of condition-specific gene regulatory networks in human and mouse. We integrated existing knowledge of regulatory interactions from multiple sources to a comprehensive model of prior information. COGERE infers condition-specific regulation by evaluating the mutual dependency between regulator (transcription factor or miRNA) and target gene expression using prior information. This dependency is scored by the non-parametric, nonlinear correlation coefficient η(2) (eta squared) that is derived by a two-way analysis of variance. We show that COGERE significantly outperforms alternative methods in predicting condition-specific gene regulatory networks on simulated data sets. Furthermore, by inferring the cancer-specific gene regulatory network from the NCI-60 expression study, we demonstrate the utility of COGERE to promote hypothesis-driven clinical research.

  2. Gene regulatory network inference using fused LASSO on multiple data sets.

    Science.gov (United States)

    Omranian, Nooshin; Eloundou-Mbebi, Jeanne M O; Mueller-Roeber, Bernd; Nikoloski, Zoran

    2016-02-11

    Devising computational methods to accurately reconstruct gene regulatory networks given gene expression data is key to systems biology applications. Here we propose a method for reconstructing gene regulatory networks by simultaneous consideration of data sets from different perturbation experiments and corresponding controls. The method imposes three biologically meaningful constraints: (1) expression levels of each gene should be explained by the expression levels of a small number of transcription factor coding genes, (2) networks inferred from different data sets should be similar with respect to the type and number of regulatory interactions, and (3) relationships between genes which exhibit similar differential behavior over the considered perturbations should be favored. We demonstrate that these constraints can be transformed in a fused LASSO formulation for the proposed method. The comparative analysis on transcriptomics time-series data from prokaryotic species, Escherichia coli and Mycobacterium tuberculosis, as well as a eukaryotic species, mouse, demonstrated that the proposed method has the advantages of the most recent approaches for regulatory network inference, while obtaining better performance and assigning higher scores to the true regulatory links. The study indicates that the combination of sparse regression techniques with other biologically meaningful constraints is a promising framework for gene regulatory network reconstructions.

  3. A provisional regulatory gene network for specification of endomesoderm in the sea urchin embryo

    Science.gov (United States)

    Davidson, Eric H.; Rast, Jonathan P.; Oliveri, Paola; Ransick, Andrew; Calestani, Cristina; Yuh, Chiou-Hwa; Minokawa, Takuya; Amore, Gabriele; Hinman, Veronica; Arenas-Mena, Cesar; Otim, Ochan; Brown, C. Titus; Livi, Carolina B.; Lee, Pei Yun; Revilla, Roger; Schilstra, Maria J.; Clarke, Peter J C.; Rust, Alistair G.; Pan, Zhengjun; Arnone, Maria I.; Rowen, Lee; Cameron, R. Andrew; McClay, David R.; Hood, Leroy; Bolouri, Hamid

    2002-01-01

    We present the current form of a provisional DNA sequence-based regulatory gene network that explains in outline how endomesodermal specification in the sea urchin embryo is controlled. The model of the network is in a continuous process of revision and growth as new genes are added and new experimental results become available; see http://www.its.caltech.edu/mirsky/endomeso.htm (End-mes Gene Network Update) for the latest version. The network contains over 40 genes at present, many newly uncovered in the course of this work, and most encoding DNA-binding transcriptional regulatory factors. The architecture of the network was approached initially by construction of a logic model that integrated the extensive experimental evidence now available on endomesoderm specification. The internal linkages between genes in the network have been determined functionally, by measurement of the effects of regulatory perturbations on the expression of all relevant genes in the network. Five kinds of perturbation have been applied: (1) use of morpholino antisense oligonucleotides targeted to many of the key regulatory genes in the network; (2) transformation of other regulatory factors into dominant repressors by construction of Engrailed repressor domain fusions; (3) ectopic expression of given regulatory factors, from genetic expression constructs and from injected mRNAs; (4) blockade of the beta-catenin/Tcf pathway by introduction of mRNA encoding the intracellular domain of cadherin; and (5) blockade of the Notch signaling pathway by introduction of mRNA encoding the extracellular domain of the Notch receptor. The network model predicts the cis-regulatory inputs that link each gene into the network. Therefore, its architecture is testable by cis-regulatory analysis. Strongylocentrotus purpuratus and Lytechinus variegatus genomic BAC recombinants that include a large number of the genes in the network have been sequenced and annotated. Tests of the cis-regulatory predictions of

  4. A saturation screen for cis-acting regulatory DNA in the Hox genes of Ciona intestinalis

    Energy Technology Data Exchange (ETDEWEB)

    Keys, David N.; Lee, Byung-in; Di Gregorio, Anna; Harafuji, Naoe; Detter, Chris; Wang, Mei; Kahsai, Orsalem; Ahn, Sylvia; Arellano, Andre; Zhang, Quin; Trong, Stephan; Doyle, Sharon A.; Satoh, Noriyuki; Satou, Yutaka; Saiga, Hidetoshi; Christian, Allen; Rokhsar, Dan; Hawkins, Trevor L.; Levine, Mike; Richardson, Paul

    2005-01-05

    A screen for the systematic identification of cis-regulatory elements within large (>100 kb) genomic domains containing Hox genes was performed by using the basal chordate Ciona intestinalis. Randomly generated DNA fragments from bacterial artificial chromosomes containing two clusters of Hox genes were inserted into a vector upstream of a minimal promoter and lacZ reporter gene. A total of 222 resultant fusion genes were separately electroporated into fertilized eggs, and their regulatory activities were monitored in larvae. In sum, 21 separable cis-regulatory elements were found. These include eight Hox linked domains that drive expression in nested anterior-posterior domains of ectodermally derived tissues. In addition to vertebrate-like CNS regulation, the discovery of cis-regulatory domains that drive epidermal transcription suggests that C. intestinalis has arthropod-like Hox patterning in the epidermis.

  5. Refining Dynamics of Gene Regulatory Networks in a Stochastic π-Calculus Framework

    OpenAIRE

    Paulevé, Loïc; Magnin, Morgan; Roux, Olivier

    2011-01-01

    International audience; In this paper, we introduce a framework allowing to model and analyse efficiently Gene Regulatory Networks in their temporal and stochastic aspects. The analysis of stable states and inference of René Thomas' discrete parameters derives from this logical formalism. We offer a compositional approach which comes with a natural translation to the Stochastic π-Calculus. The method we propose consists in successive refinements of generalized dynamics of Gene Regulatory Netw...

  6. A novel parametric approach to mine gene regulatory relationship from microarray datasets

    Directory of Open Access Journals (Sweden)

    Zhu Yunping

    2010-12-01

    Full Text Available Abstract Background Microarray has been widely used to measure the gene expression level on the genome scale in the current decade. Many algorithms have been developed to reconstruct gene regulatory networks based on microarray data. Unfortunately, most of these models and algorithms focus on global properties of the expression of genes in regulatory networks. And few of them are able to offer intuitive parameters. We wonder whether some simple but basic characteristics of microarray datasets can be found to identify the potential gene regulatory relationship. Results Based on expression correlation, expression level variation and vectors derived from microarray expression levels, we first introduced several novel parameters to measure the characters of regulating gene pairs. Subsequently, we used the naïve Bayesian network to integrate these features as well as the functional co-annotation between transcription factors and their target genes. Then, based on the character of time-delay from the expression profile, we were able to predict the existence and direction of the regulatory relationship respectively. Conclusions Several novel parameters have been proposed and integrated to identify the regulatory relationship. This new model is proved to be of higher efficacy than that of individual features. It is believed that our parametric approach can serve as a fast approach for regulatory relationship mining.

  7. Inferring gene regulatory networks via nonlinear state-space models and exploiting sparsity.

    Science.gov (United States)

    Noor, Amina; Serpedin, Erchin; Nounou, Mohamed; Nounou, Hazem N

    2012-01-01

    This paper considers the problem of learning the structure of gene regulatory networks from gene expression time series data. A more realistic scenario when the state space model representing a gene network evolves nonlinearly is considered while a linear model is assumed for the microarray data. To capture the nonlinearity, a particle filter-based state estimation algorithm is considered instead of the contemporary linear approximation-based approaches. The parameters characterizing the regulatory relations among various genes are estimated online using a Kalman filter. Since a particular gene interacts with a few other genes only, the parameter vector is expected to be sparse. The state estimates delivered by the particle filter and the observed microarray data are then subjected to a LASSO-based least squares regression operation which yields a parsimonious and efficient description of the regulatory network by setting the irrelevant coefficients to zero. The performance of the aforementioned algorithm is compared with the extended Kalman filter (EKF) and Unscented Kalman Filter (UKF) employing the Mean Square Error (MSE) as the fidelity criterion in recovering the parameters of gene regulatory networks from synthetic data and real biological data. Extensive computer simulations illustrate that the proposed particle filter-based network inference algorithm outperforms EKF and UKF, and therefore, it can serve as a natural framework for modeling gene regulatory networks with nonlinear and sparse structure.

  8. Identifying Gene Regulatory Networks in Arabidopsis by In Silico Prediction, Yeast-1-Hybrid, and Inducible Gene Profiling Assays.

    Science.gov (United States)

    Sparks, Erin E; Benfey, Philip N

    2016-01-01

    A system-wide understanding of gene regulation will provide deep insights into plant development and physiology. In this chapter we describe a threefold approach to identify the gene regulatory networks in Arabidopsis thaliana that function in a specific tissue or biological process. Since no single method is sufficient to establish comprehensive and high-confidence gene regulatory networks, we focus on the integration of three approaches. First, we describe an in silico prediction method of transcription factor-DNA binding, then an in vivo assay of transcription factor-DNA binding by yeast-1-hybrid and lastly the identification of co-expression clusters by transcription factor induction in planta. Each of these methods provides a unique tool to advance our understanding of gene regulation, and together provide a robust model for the generation of gene regulatory networks.

  9. iSLIM: a comprehensive approach to mapping and characterizing gene regulatory networks.

    Science.gov (United States)

    Rockel, Sylvie; Geertz, Marcel; Hens, Korneel; Deplancke, Bart; Maerkl, Sebastian J

    2013-02-01

    Mapping gene regulatory networks is a significant challenge in systems biology, yet only a few methods are currently capable of systems-level identification of transcription factors (TFs) that bind a specific regulatory element. We developed a microfluidic method for integrated systems-level interaction mapping of TF-DNA interactions, generating and interrogating an array of 423 full-length Drosophila TFs. With integrated systems-level interaction mapping, it is now possible to rapidly and quantitatively map gene regulatory networks of higher eukaryotes.

  10. Reconstruction of the Regulatory Network for Bacillus subtilis and Reconciliation with Gene Expression Data

    Science.gov (United States)

    Faria, José P.; Overbeek, Ross; Taylor, Ronald C.; Conrad, Neal; Vonstein, Veronika; Goelzer, Anne; Fromion, Vincent; Rocha, Miguel; Rocha, Isabel; Henry, Christopher S.

    2016-01-01

    We introduce a manually constructed and curated regulatory network model that describes the current state of knowledge of transcriptional regulation of Bacillus subtilis. The model corresponds to an updated and enlarged version of the regulatory model of central metabolism originally proposed in 2008. We extended the original network to the whole genome by integration of information from DBTBS, a compendium of regulatory data that includes promoters, transcription factors (TFs), binding sites, motifs, and regulated operons. Additionally, we consolidated our network with all the information on regulation included in the SporeWeb and Subtiwiki community-curated resources on B. subtilis. Finally, we reconciled our network with data from RegPrecise, which recently released their own less comprehensive reconstruction of the regulatory network for B. subtilis. Our model describes 275 regulators and their target genes, representing 30 different mechanisms of regulation such as TFs, RNA switches, Riboswitches, and small regulatory RNAs. Overall, regulatory information is included in the model for ∼2500 of the ∼4200 genes in B. subtilis 168. In an effort to further expand our knowledge of B. subtilis regulation, we reconciled our model with expression data. For this process, we reconstructed the Atomic Regulons (ARs) for B. subtilis, which are the sets of genes that share the same “ON” and “OFF” gene expression profiles across multiple samples of experimental data. We show how ARs for B. subtilis are able to capture many sets of genes corresponding to regulated operons in our manually curated network. Additionally, we demonstrate how ARs can be used to help expand or validate the knowledge of the regulatory networks by looking at highly correlated genes in the ARs for which regulatory information is lacking. During this process, we were also able to infer novel stimuli for hypothetical genes by exploring the genome expression metadata relating to experimental

  11. Reconstruction of the Regulatory Network for Bacillus subtilis and Reconciliation with Gene Expression Data

    Energy Technology Data Exchange (ETDEWEB)

    Faria, José P.; Overbeek, Ross; Taylor, Ronald C.; Conrad, Neal; Vonstein, Veronika; Goelzer, Anne; Fromion, Vincent; Rocha, Miguel; Rocha, Isabel; Henry, Christopher S.

    2016-03-18

    We introduce a manually constructed and curated regulatory network model that describes the current state of knowledge of transcriptional regulation of B. subtilis. The model corresponds to an updated and enlarged version of the regulatory model of central metabolism originally proposed in 2008. We extended the original network to the whole genome by integration of information from DBTBS, a compendium of regulatory data that includes promoters, transcription factors (TFs), binding sites, motifs and regulated operons. Additionally, we consolidated our network with all the information on regulation included in the SporeWeb and Subtiwiki community-curated resources on B. subtilis. Finally, we reconciled our network with data from RegPrecise, which recently released their own less comprehensive reconstruction of the regulatory network for B. subtilis. Our model describes 275 regulators and their target genes, representing 30 different mechanisms of regulation such as TFs, RNA switches, Riboswitches and small regulatory RNAs. Overall, regulatory information is included in the model for approximately 2500 of the ~4200 genes in B. subtilis 168. In an effort to further expand our knowledge of B. subtilis regulation, we reconciled our model with expression data. For this process, we reconstructed the Atomic Regulons (ARs) for B. subtilis, which are the sets of genes that share the same “ON” and “OFF” gene expression profiles across multiple samples of experimental data. We show how atomic regulons for B. subtilis are able to capture many sets of genes corresponding to regulated operons in our manually curated network. Additionally, we demonstrate how atomic regulons can be used to help expand or validate the knowledge of the regulatory networks by looking at highly correlated genes in the ARs for which regulatory information is lacking. During this process, we were also able to infer novel stimuli for hypothetical genes by exploring the genome expression metadata

  12. Small cell carcinoma of the urinary bladder: KIT and PDGFRA gene mutations

    Directory of Open Access Journals (Sweden)

    Nuket Eliyakin

    2015-12-01

    Full Text Available Primary small cell carcinoma of the urinary bladder is very rare. A 72-year-old was admitted to our hospital because of hematuria and dysuria. Cystoscopy revealed a bladder full of multiple, solid and papillary tumors. Biopsies from the deep and papillary tumors were taken. Histologically, tumor was pure small cell carcinoma. Immunohistochemically, the tumor cells were positive for cytokeratin, chromogranin, synaptophysin, neuron-specific enolase, CD56, CD117 and Ki67 (labeling 70%. The tumor cells were negative for CK7, CK20, CD3, CD20, LCA, CDX2, uroplakin, thyroid transcription factor 1, PSA and p63. Metastatic workup was performed an no primary or metastatic lung lesions were noted. Due to the clinical, radiologic and immunohistochemical findings, the patient was diagnosed as primary small cell carcinoma of bladder. A molecular genetic analysis for KIT (exons 9, 11, 13 and 17 and PDGFRA (exons 12 and 18 genes was performed, in paraffin micro dissection specimens, by the PCR-direct sequencing method. According to the sequencing analyses, two mutations were found at positions 558 (p.K558N and 562 (p.E562D in KIT gene exon 11 in our case. The another hand the same case presented two mutations in PDGFRA gene exon 14 at position 631 (p.P631A and 638 (p.638Q_639AinsC. The disease process was fulminant and the patient was lost due to several complications prior to any chemotherapy.

  13. EWS and FUS bind a subset of transcribed genes encoding proteins enriched in RNA regulatory functions

    DEFF Research Database (Denmark)

    Luo, Yonglun; Friis, Jenny Blechingberg; Fernandes, Ana Miguel

    2015-01-01

    at different levels. Gene Ontology analyses showed that FUS and EWS target genes preferentially encode proteins involved in regulatory processes at the RNA level. Conclusions The presented results yield new insights into gene interactions of EWS and FUS and have identified a set of FUS and EWS target genes...... and involved in the human neurological diseases amyotrophic lateral sclerosis and fronto-temporal lobar degeneration. Results To determine the gene regulatory functions of FUS and EWS at the level of chromatin, we have performed chromatin immunoprecipitation followed by next generation sequencing (Ch......IP-seq). Our results show that FUS and EWS bind to a subset of actively transcribed genes, that binding often is downstream the poly(A)-signal, and that binding overlaps with RNA polymerase II. Functional examinations of selected target genes identified that FUS and EWS can regulate gene expression...

  14. EWS and FUS bind a subset of transcribed genes encoding proteins enriched in RNA regulatory functions

    DEFF Research Database (Denmark)

    Luo, Yonglun; Friis, Jenny Blechingberg; Fernandes, Ana Miguel;

    2015-01-01

    IP-seq). Our results show that FUS and EWS bind to a subset of actively transcribed genes, that binding often is downstream the poly(A)-signal, and that binding overlaps with RNA polymerase II. Functional examinations of selected target genes identified that FUS and EWS can regulate gene expression...... at different levels. Gene Ontology analyses showed that FUS and EWS target genes preferentially encode proteins involved in regulatory processes at the RNA level. Conclusions The presented results yield new insights into gene interactions of EWS and FUS and have identified a set of FUS and EWS target genes...

  15. A boolean model of the cardiac gene regulatory network determining first and second heart field identity.

    Directory of Open Access Journals (Sweden)

    Franziska Herrmann

    Full Text Available Two types of distinct cardiac progenitor cell populations can be identified during early heart development: the first heart field (FHF and second heart field (SHF lineage that later form the mature heart. They can be characterized by differential expression of transcription and signaling factors. These regulatory factors influence each other forming a gene regulatory network. Here, we present a core gene regulatory network for early cardiac development based on published temporal and spatial expression data of genes and their interactions. This gene regulatory network was implemented in a Boolean computational model. Simulations reveal stable states within the network model, which correspond to the regulatory states of the FHF and the SHF lineages. Furthermore, we are able to reproduce the expected temporal expression patterns of early cardiac factors mimicking developmental progression. Additionally, simulations of knock-down experiments within our model resemble published phenotypes of mutant mice. Consequently, this gene regulatory network retraces the early steps and requirements of cardiogenic mesoderm determination in a way appropriate to enhance the understanding of heart development.

  16. A Boolean Model of the Cardiac Gene Regulatory Network Determining First and Second Heart Field Identity

    Science.gov (United States)

    Zhou, Dao; Kestler, Hans A.; Kühl, Michael

    2012-01-01

    Two types of distinct cardiac progenitor cell populations can be identified during early heart development: the first heart field (FHF) and second heart field (SHF) lineage that later form the mature heart. They can be characterized by differential expression of transcription and signaling factors. These regulatory factors influence each other forming a gene regulatory network. Here, we present a core gene regulatory network for early cardiac development based on published temporal and spatial expression data of genes and their interactions. This gene regulatory network was implemented in a Boolean computational model. Simulations reveal stable states within the network model, which correspond to the regulatory states of the FHF and the SHF lineages. Furthermore, we are able to reproduce the expected temporal expression patterns of early cardiac factors mimicking developmental progression. Additionally, simulations of knock-down experiments within our model resemble published phenotypes of mutant mice. Consequently, this gene regulatory network retraces the early steps and requirements of cardiogenic mesoderm determination in a way appropriate to enhance the understanding of heart development. PMID:23056457

  17. Reconstruction of large-scale gene regulatory networks using Bayesian model averaging.

    Science.gov (United States)

    Kim, Haseong; Gelenbe, Erol

    2012-09-01

    Gene regulatory networks provide the systematic view of molecular interactions in a complex living system. However, constructing large-scale gene regulatory networks is one of the most challenging problems in systems biology. Also large burst sets of biological data require a proper integration technique for reliable gene regulatory network construction. Here we present a new reverse engineering approach based on Bayesian model averaging which attempts to combine all the appropriate models describing interactions among genes. This Bayesian approach with a prior based on the Gibbs distribution provides an efficient means to integrate multiple sources of biological data. In a simulation study with maximum of 2000 genes, our method shows better sensitivity than previous elastic-net and Gaussian graphical models, with a fixed specificity of 0.99. The study also shows that the proposed method outperforms the other standard methods for a DREAM dataset generated by nonlinear stochastic models. In brain tumor data analysis, three large-scale networks consisting of 4422 genes were built using the gene expression of non-tumor, low and high grade tumor mRNA expression samples, along with DNA-protein binding affinity information. We found that genes having a large variation of degree distribution among the three tumor networks are the ones that see most involved in regulatory and developmental processes, which possibly gives a novel insight concerning conventional differentially expressed gene analysis.

  18. CoryneRegNet 4.0 – A reference database for corynebacterial gene regulatory networks

    Directory of Open Access Journals (Sweden)

    Baumbach Jan

    2007-11-01

    Full Text Available Abstract Background Detailed information on DNA-binding transcription factors (the key players in the regulation of gene expression and on transcriptional regulatory interactions of microorganisms deduced from literature-derived knowledge, computer predictions and global DNA microarray hybridization experiments, has opened the way for the genome-wide analysis of transcriptional regulatory networks. The large-scale reconstruction of these networks allows the in silico analysis of cell behavior in response to changing environmental conditions. We previously published CoryneRegNet, an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks. Initially, it was designed to provide methods for the analysis and visualization of the gene regulatory network of Corynebacterium glutamicum. Results Now we introduce CoryneRegNet release 4.0, which integrates data on the gene regulatory networks of 4 corynebacteria, 2 mycobacteria and the model organism Escherichia coli K12. As the previous versions, CoryneRegNet provides a web-based user interface to access the database content, to allow various queries, and to support the reconstruction, analysis and visualization of regulatory networks at different hierarchical levels. In this article, we present the further improved database content of CoryneRegNet along with novel analysis features. The network visualization feature GraphVis now allows the inter-species comparisons of reconstructed gene regulatory networks and the projection of gene expression levels onto that networks. Therefore, we added stimulon data directly into the database, but also provide Web Service access to the DNA microarray analysis platform EMMA. Additionally, CoryneRegNet now provides a SOAP based Web Service server, which can easily be consumed by other bioinformatics software systems. Stimulons (imported from the database, or uploaded by the user can be analyzed in the context of known

  19. The gene expression data of Mycobacterium tuberculosis based on Affymetrix gene chips provide insight into regulatory and hypothetical genes

    Directory of Open Access Journals (Sweden)

    Fu-Liu Casey S

    2007-05-01

    Full Text Available Abstract Background Tuberculosis remains a leading infectious disease with global public health threat. Its control and management have been complicated by multi-drug resistance and latent infection, which prompts scientists to find new and more effective drugs. With the completion of the genome sequence of the etiologic bacterium, Mycobacterium tuberculosis, it is now feasible to search for new drug targets by sieving through a large number of gene products and conduct genome-scale experiments based on microarray technology. However, the full potential of genome-wide microarray analysis in configuring interrelationships among all genes in M. tuberculosis has yet to be realized. To date, it is only possible to assign a function to 52% of proteins predicted in the genome. Results We conducted a functional-genomics study using the high-resolution Affymetrix oligonucleotide GeneChip. Approximately one-half of the genes were found to be always expressed, including more than 100 predicted conserved hypotheticals, in the genome of M. tuberculosis during the log phase of in vitro growth. The gene expression profiles were analyzed and visualized through cluster analysis to epitomize the full details of genomic behavior. Broad patterns derived from genome-wide expression experiments in this study have provided insight into the interrelationships among genes in the basic cellular processes of M. tuberculosis. Conclusion Our results have confirmed several known gene clusters in energy production, information pathways, and lipid metabolism, and also hinted at potential roles of hypothetical and regulatory proteins.

  20. Predicting gene regulatory networks of soybean nodulation from RNA-Seq transcriptome data

    Science.gov (United States)

    2013-01-01

    Background High-throughput RNA sequencing (RNA-Seq) is a revolutionary technique to study the transcriptome of a cell under various conditions at a systems level. Despite the wide application of RNA-Seq techniques to generate experimental data in the last few years, few computational methods are available to analyze this huge amount of transcription data. The computational methods for constructing gene regulatory networks from RNA-Seq expression data of hundreds or even thousands of genes are particularly lacking and urgently needed. Results We developed an automated bioinformatics method to predict gene regulatory networks from the quantitative expression values of differentially expressed genes based on RNA-Seq transcriptome data of a cell in different stages and conditions, integrating transcriptional, genomic and gene function data. We applied the method to the RNA-Seq transcriptome data generated for soybean root hair cells in three different development stages of nodulation after rhizobium infection. The method predicted a soybean nodulation-related gene regulatory network consisting of 10 regulatory modules common for all three stages, and 24, 49 and 70 modules separately for the first, second and third stage, each containing both a group of co-expressed genes and several transcription factors collaboratively controlling their expression under different conditions. 8 of 10 common regulatory modules were validated by at least two kinds of validations, such as independent DNA binding motif analysis, gene function enrichment test, and previous experimental data in the literature. Conclusions We developed a computational method to reliably reconstruct gene regulatory networks from RNA-Seq transcriptome data. The method can generate valuable hypotheses for interpreting biological data and designing biological experiments such as ChIP-Seq, RNA interference, and yeast two hybrid experiments. PMID:24053776

  1. Novel regulatory cascades controlling expression of nitrogen-fixation genes in Geobacter sulfurreducens.

    Science.gov (United States)

    Ueki, Toshiyuki; Lovley, Derek R

    2010-11-01

    Geobacter species often play an important role in bioremediation of environments contaminated with metals or organics and show promise for harvesting electricity from waste organic matter in microbial fuel cells. The ability of Geobacter species to fix atmospheric nitrogen is an important metabolic feature for these applications. We identified novel regulatory cascades controlling nitrogen-fixation gene expression in Geobacter sulfurreducens. Unlike the regulatory mechanisms known in other nitrogen-fixing microorganisms, nitrogen-fixation gene regulation in G. sulfurreducens is controlled by two two-component His-Asp phosphorelay systems. One of these systems appears to be the master regulatory system that activates transcription of the majority of nitrogen-fixation genes and represses a gene encoding glutamate dehydrogenase during nitrogen fixation. The other system whose expression is directly activated by the master regulatory system appears to control by antitermination the expression of a subset of the nitrogen-fixation genes whose transcription is activated by the master regulatory system and whose promoter contains transcription termination signals. This study provides a new paradigm for nitrogen-fixation gene regulation.

  2. Rapid male-specific regulatory divergence and down regulation of spermatogenesis genes in Drosophila species hybrids.

    Directory of Open Access Journals (Sweden)

    Jennifer Ferguson

    Full Text Available In most crosses between closely related species of Drosophila, the male hybrids are sterile and show postmeiotic abnormalities. A series of gene expression studies using genomic approaches have found significant down regulation of postmeiotic spermatogenesis genes in sterile male hybrids. These results have led some to suggest a direct relationship between down regulation in gene expression and hybrid sterility. An alternative explanation to a cause-and-effect relationship between misregulation of gene expression and male sterility is rapid divergence of male sex regulatory elements leading to incompatible interactions in an interspecies hybrid genome. To test the effect of regulatory divergence in spermatogenesis gene expression, we isolated 35 fertile D. simulans strains with D. mauritiana introgressions in either the X, second or third chromosome. We analyzed gene expression in these fertile hybrid strains for a subset of spermatogenesis genes previously reported as significantly under expressed in sterile hybrids relative to D. simulans. We found that fertile autosomal introgressions can cause levels of gene down regulation similar to that of sterile hybrids. We also found that X chromosome heterospecific introgressions cause significantly less gene down regulation than autosomal introgressions. Our results provide evidence that rapid male sex gene regulatory divergence can explain misexpression of spermatogenesis genes in hybrids.

  3. Rapid male-specific regulatory divergence and down regulation of spermatogenesis genes in Drosophila species hybrids.

    Science.gov (United States)

    Ferguson, Jennifer; Gomes, Suzanne; Civetta, Alberto

    2013-01-01

    In most crosses between closely related species of Drosophila, the male hybrids are sterile and show postmeiotic abnormalities. A series of gene expression studies using genomic approaches have found significant down regulation of postmeiotic spermatogenesis genes in sterile male hybrids. These results have led some to suggest a direct relationship between down regulation in gene expression and hybrid sterility. An alternative explanation to a cause-and-effect relationship between misregulation of gene expression and male sterility is rapid divergence of male sex regulatory elements leading to incompatible interactions in an interspecies hybrid genome. To test the effect of regulatory divergence in spermatogenesis gene expression, we isolated 35 fertile D. simulans strains with D. mauritiana introgressions in either the X, second or third chromosome. We analyzed gene expression in these fertile hybrid strains for a subset of spermatogenesis genes previously reported as significantly under expressed in sterile hybrids relative to D. simulans. We found that fertile autosomal introgressions can cause levels of gene down regulation similar to that of sterile hybrids. We also found that X chromosome heterospecific introgressions cause significantly less gene down regulation than autosomal introgressions. Our results provide evidence that rapid male sex gene regulatory divergence can explain misexpression of spermatogenesis genes in hybrids.

  4. Large-scale genetic perturbations reveal regulatory networks and an abundance of gene-specific repressors

    NARCIS (Netherlands)

    Kemmeren, P.P.C.W.; Sameith, K.; van de Pasch, L.A.L.; Benschop, J.J.; Lenstra, T.L.; Margaritis, A.; O'Duibhir, E.; Apweiler, E.; van Wageningen, S.; Ko, C.W.; van Heesch, S.A.A.C.; Kashani, M.M.; Ampatziadis-Michailidis, G.; Brok, M.O.; Brabers, N.A.C.H.; Miles, A.J.; Bouwmeester, D.; van Hooff, S.R.; van Bakel, H.H.M.J.; Sluiters, E.C.; Bakker, L.V.; Snel, B.; Lijnzaad, P.; van Leenen, D.; Groot Koerkamp, M.J.A.; Holstege, F.C.P.

    2014-01-01

    To understand regulatory systems, it would be useful to uniformly determine how different components contribute to the expression of all other genes. We therefore monitored mRNA expression genomewide, for individual deletions of one-quarter of yeast genes, focusing on (putative) regulators. The resu

  5. Statistical inference and reverse engineering of gene regulatory networks from observational expression data.

    Science.gov (United States)

    Emmert-Streib, Frank; Glazko, Galina V; Altay, Gökmen; de Matos Simoes, Ricardo

    2012-01-01

    In this paper, we present a systematic and conceptual overview of methods for inferring gene regulatory networks from observational gene expression data. Further, we discuss two classic approaches to infer causal structures and compare them with contemporary methods by providing a conceptual categorization thereof. We complement the above by surveying global and local evaluation measures for assessing the performance of inference algorithms.

  6. On the Interplay between Entropy and Robustness of Gene Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Bor-Sen Chen

    2010-05-01

    Full Text Available The interplay between entropy and robustness of gene network is a core mechanism of systems biology. The entropy is a measure of randomness or disorder of a physical system due to random parameter fluctuation and environmental noises in gene regulatory networks. The robustness of a gene regulatory network, which can be measured as the ability to tolerate the random parameter fluctuation and to attenuate the effect of environmental noise, will be discussed from the robust H∞ stabilization and filtering perspective. In this review, we will also discuss their balancing roles in evolution and potential applications in systems and synthetic biology.

  7. Combination of Neuro-Fuzzy Network Models with Biological Knowledge for Reconstructing Gene Regulatory Networks

    Institute of Scientific and Technical Information of China (English)

    Guixia Liu; Lei Liu; Chunyu Liu; Ming Zheng; Lanying Su; Chunguang Zhou

    2011-01-01

    Inferring gene regulatory networks from large-scale expression data is an important topic in both cellular systems and computational biology. The inference of regulators might be the core factor for understanding actual regulatory conditions in gene regulatory networks, especially when strong regulators do work significantly, in this paper, we propose a novel approach based on combining neuro-fuzzy network models with biological knowledge to infer strong regulators and interrelated fuzzy rules. The hybrid neuro-fuzzy architecture can not only infer the fuzzy rules, which are suitable for describing the regulatory conditions in regulatory networks, but also explain the meaning of nodes and weight value in the neural network. It can get useful rules automatically without factitious judgments. At the same time, it does not add recursive layers to the model, and the model can also strengthen the relationships among genes and reduce calculation. We use the proposed approach to reconstruct a partial gene regulatory network of yeast. The results show that this approach can work effectively.

  8. Cloning and bioinformatic analysis of lovastatin biosynthesis regulatory gene lovE

    Institute of Scientific and Technical Information of China (English)

    HUANG Xin; LI Hao-ming

    2009-01-01

    Background Lovastatin is an effective drug for treatment of hyperlipidemia.This study aimed to clone Iovastatin biosynthesis regulatory gene lovE and analyze the structure and function of its encoding protein.Methods According to the Iovastatin synthase gene sequence from genebank,primers were designed to amplify and clone the Iovastatin biosynthesis regulatory gene lovE from Aspergillus terms genomic DNA.Bioinformatic analysis of lovE and its encoding animo acid sequence was performed through intemet resources and software like DNAMAN.Results Target fragment lovE,almost 1500 bp in length,was amplified from Aspergillus terms genomic DNA and the secondary and three-dimensional structures of LovE protein were predicted.Conclusion In the Iovastatin biosynthesis process lovE is a regulatory gene and LovE protein is a GAL4-1ike transcriptional factor.

  9. CMIP: a software package capable of reconstructing genome-wide regulatory networks using gene expression data.

    Science.gov (United States)

    Zheng, Guangyong; Xu, Yaochen; Zhang, Xiujun; Liu, Zhi-Ping; Wang, Zhuo; Chen, Luonan; Zhu, Xin-Guang

    2016-12-23

    A gene regulatory network (GRN) represents interactions of genes inside a cell or tissue, in which vertexes and edges stand for genes and their regulatory interactions respectively. Reconstruction of gene regulatory networks, in particular, genome-scale networks, is essential for comparative exploration of different species and mechanistic investigation of biological processes. Currently, most of network inference methods are computationally intensive, which are usually effective for small-scale tasks (e.g., networks with a few hundred genes), but are difficult to construct GRNs at genome-scale. Here, we present a software package for gene regulatory network reconstruction at a genomic level, in which gene interaction is measured by the conditional mutual information measurement using a parallel computing framework (so the package is named CMIP). The package is a greatly improved implementation of our previous PCA-CMI algorithm. In CMIP, we provide not only an automatic threshold determination method but also an effective parallel computing framework for network inference. Performance tests on benchmark datasets show that the accuracy of CMIP is comparable to most current network inference methods. Moreover, running tests on synthetic datasets demonstrate that CMIP can handle large datasets especially genome-wide datasets within an acceptable time period. In addition, successful application on a real genomic dataset confirms its practical applicability of the package. This new software package provides a powerful tool for genomic network reconstruction to biological community. The software can be accessed at http://www.picb.ac.cn/CMIP/ .

  10. A Guide to Approaching Regulatory Considerations for Lentiviral-Mediated Gene Therapies.

    Science.gov (United States)

    White, Michael; Whittaker, Roger; Gándara, Carolina; Stoll, Elizabeth A

    2017-08-01

    Lentiviral vectors are increasingly the gene transfer tool of choice for gene or cell therapies, with multiple clinical investigations showing promise for this viral vector in terms of both safety and efficacy. The third-generation vector system is well characterized, effectively delivers genetic material and maintains long-term stable expression in target cells, delivers larger amounts of genetic material than other methods, is nonpathogenic, and does not cause an inflammatory response in the recipient. This report aims to help academic scientists and regulatory managers negotiate the governance framework to achieve successful translation of a lentiviral vector-based gene therapy. The focus is on European regulations and how they are administered in the United Kingdom, although many of the principles will be similar for other regions, including the United States. The report justifies the rationale for using third-generation lentiviral vectors to achieve gene delivery for in vivo and ex vivo applications; briefly summarizes the extant regulatory guidance for gene therapies, categorized as advanced therapeutic medicinal products (ATMPs); provides guidance on specific regulatory issues regarding gene therapies; presents an overview of the key stakeholders to be approached when pursuing clinical trials authorization for an ATMP; and includes a brief catalogue of the documentation required to submit an application for regulatory approval of a new gene therapy.

  11. Clinical development of gene therapy needs a tailored approach: a regulatory perspective from the European Union.

    Science.gov (United States)

    Narayanan, Gopalan; Cossu, Giulio; Galli, Maria Cristina; Flory, Egbert; Ovelgonne, Hans; Salmikangas, Paula; Schneider, Christian K; Trouvin, Jean-Hugues

    2014-03-01

    Gene therapy is a rapidly evolving field that needs an integrated approach, as acknowledged in the concept article on the revision of the guideline on gene transfer medicinal products. The first gene therapy application for marketing authorization was approved in the International Conference on Harmonisation (ICH) region in 2012, the product being Alipogene tiparvovec. The regulatory process for this product has been commented on extensively, highlighting the challenges posed by such a novel technology. Here, as current or previous members of the Committee for Advanced Therapies, we share our perspectives and views on gene therapy as a treatment modality based on current common understanding and regulatory experience of gene therapy products in the European Union to date. It is our view that a tailored approach is needed for a given gene therapy product in order to achieve successful marketing authorization.

  12. CTCF-mediated chromatin loops enclose inducible gene regulatory domains

    NARCIS (Netherlands)

    Oti, M.O.; Falck, J.; Huynen, M.A.; Zhou, Huiqing

    2016-01-01

    BACKGROUND: The CCTC-binding factor (CTCF) protein is involved in genome organization, including mediating three-dimensional chromatin interactions. Human patient lymphocytes with mutations in a single copy of the CTCF gene have reduced expression of enhancer-associated genes involved in response to

  13. Inference of gene regulatory networks with sparse structural equation models exploiting genetic perturbations.

    Directory of Open Access Journals (Sweden)

    Xiaodong Cai

    Full Text Available Integrating genetic perturbations with gene expression data not only improves accuracy of regulatory network topology inference, but also enables learning of causal regulatory relations between genes. Although a number of methods have been developed to integrate both types of data, the desiderata of efficient and powerful algorithms still remains. In this paper, sparse structural equation models (SEMs are employed to integrate both gene expression data and cis-expression quantitative trait loci (cis-eQTL, for modeling gene regulatory networks in accordance with biological evidence about genes regulating or being regulated by a small number of genes. A systematic inference method named sparsity-aware maximum likelihood (SML is developed for SEM estimation. Using simulated directed acyclic or cyclic networks, the SML performance is compared with that of two state-of-the-art algorithms: the adaptive Lasso (AL based scheme, and the QTL-directed dependency graph (QDG method. Computer simulations demonstrate that the novel SML algorithm offers significantly better performance than the AL-based and QDG algorithms across all sample sizes from 100 to 1,000, in terms of detection power and false discovery rate, in all the cases tested that include acyclic or cyclic networks of 10, 30 and 300 genes. The SML method is further applied to infer a network of 39 human genes that are related to the immune function and are chosen to have a reliable eQTL per gene. The resulting network consists of 9 genes and 13 edges. Most of the edges represent interactions reasonably expected from experimental evidence, while the remaining may just indicate the emergence of new interactions. The sparse SEM and efficient SML algorithm provide an effective means of exploiting both gene expression and perturbation data to infer gene regulatory networks. An open-source computer program implementing the SML algorithm is freely available upon request.

  14. In silico evolution of the hunchback gene indicates redundancy in cis-regulatory organization and spatial gene expression.

    Science.gov (United States)

    Zagrijchuk, Elizaveta A; Sabirov, Marat A; Holloway, David M; Spirov, Alexander V

    2014-04-01

    Biological development depends on the coordinated expression of genes in time and space. Developmental genes have extensive cis-regulatory regions which control their expression. These regions are organized in a modular manner, with different modules controlling expression at different times and locations. Both how modularity evolved and what function it serves are open questions. We present a computational model for the cis-regulation of the hunchback (hb) gene in the fruit fly (Drosophila). We simulate evolution (using an evolutionary computation approach from computer science) to find the optimal cis-regulatory arrangements for fitting experimental hb expression patterns. We find that the cis-regulatory region tends to readily evolve modularity. These cis-regulatory modules (CRMs) do not tend to control single spatial domains, but show a multi-CRM/multi-domain correspondence. We find that the CRM-domain correspondence seen in Drosophila evolves with a high probability in our model, supporting the biological relevance of the approach. The partial redundancy resulting from multi-CRM control may confer some biological robustness against corruption of regulatory sequences. The technique developed on hb could readily be applied to other multi-CRM developmental genes.

  15. In silico evolution of the hunchback gene indicates redundancy in cis-regulatory organization and spatial gene expression

    Science.gov (United States)

    Zagrijchuk, Elizaveta A.; Sabirov, Marat A.; Holloway, David M.; Spirov, Alexander V.

    2014-01-01

    Biological development depends on the coordinated expression of genes in time and space. Developmental genes have extensive cis-regulatory regions which control their expression. These regions are organized in a modular manner, with different modules controlling expression at different times and locations. Both how modularity evolved and what function it serves are open questions. We present a computational model for the cis-regulation of the hunchback (hb) gene in the fruit fly (Drosophila). We simulate evolution (using an evolutionary computation approach from computer science) to find the optimal cis-regulatory arrangements for fitting experimental hb expression patterns. We find that the cis-regulatory region tends to readily evolve modularity. These cis-regulatory modules (CRMs) do not tend to control single spatial domains, but show a multi-CRM/multi-domain correspondence. We find that the CRM-domain correspondence seen in Drosophila evolves with a high probability in our model, supporting the biological relevance of the approach. The partial redundancy resulting from multi-CRM control may confer some biological robustness against corruption of regulatory sequences. The technique developed on hb could readily be applied to other multi-CRM developmental genes. PMID:24712536

  16. Multiple Cis-Acting Sequences Contribute to Evolved Regulatory Variation for Drosophila Adh Genes

    Science.gov (United States)

    Fang, X. M.; Brennan, M. D.

    1992-01-01

    Drosophila affinidisjuncta and Drosophila hawaiiensis are closely related species that display distinct tissue-specific expression patterns for their homologous alcohol dehydrogenase genes (Adh genes). In Drosophila melanogaster transformants, both genes are expressed at high levels in the larval and adult fat bodies, but the D. affinidisjuncta gene is expressed 10-50-fold more strongly in the larval and adult midguts and Malpighian tubules. The present study reports the mapping of cis-acting sequences contributing to the regulatory differences between these two genes in transformants. Chimeric genes were constructed and introduced into the germ line of D. melanogaster. Stage- and tissue-specific expression patterns were determined by measuring steady-state RNA levels in larvae and adults. Three portions of the promoter region make distinct contributions to the tissue-specific regulatory differences between the native genes. Sequences immediately upstream of the distal promoter have a strong effect in the adult Malpighian tubules, while sequences between the two promoters are relatively important in the larval Malpighian tubules. A third gene segment, immediately upstream of the proximal promoter, influences levels of the proximal Adh transcript in all tissues and developmental stages examined, and largely accounts for the regulatory difference in the larval and adult midguts. However, these as well as other sequences make smaller contributions to various aspects of the tissue-specific regulatory differences. In addition, some chimeric genes display aberrant RNA levels for the whole organism, suggesting close physical association between sequences involved in tissue-specific regulatory differences and those important for Adh expression in the larval and adult fat bodies. PMID:1644276

  17. Medusa structure of the gene regulatory network: dominance of transcription factors in cancer subtype classification.

    Science.gov (United States)

    Guo, Yuchun; Feng, Ying; Trivedi, Niraj S; Huang, Sui

    2011-05-01

    Gene expression profiles consisting of ten thousands of transcripts are used for clustering of tissue, such as tumors, into subtypes, often without considering the underlying reason that the distinct patterns of expression arise because of constraints in the realization of gene expression profiles imposed by the gene regulatory network. The topology of this network has been suggested to consist of a regulatory core of genes represented most prominently by transcription factors (TFs) and microRNAs, that influence the expression of other genes, and of a periphery of 'enslaved' effector genes that are regulated but not regulating. This 'medusa' architecture implies that the core genes are much stronger determinants of the realized gene expression profiles. To test this hypothesis, we examined the clustering of gene expression profiles into known tumor types to quantitatively demonstrate that TFs, and even more pronounced, microRNAs, are much stronger discriminators of tumor type specific gene expression patterns than a same number of randomly selected or metabolic genes. These findings lend support to the hypothesis of a medusa architecture and of the canalizing nature of regulation by microRNAs. They also reveal the degree of freedom for the expression of peripheral genes that are less stringently associated with a tissue type specific global gene expression profile.

  18. Elevated urinary albumin excretion is not linked to the angiotensin I-converting enzyme gene polymorphism in clinically healthy subjects

    DEFF Research Database (Denmark)

    Clausen, P; Jensen, J S; Borch-Johnsen, K

    2000-01-01

    aged 40-65 years with elevated UAE in a dipstick negative urinary sample (n = 27) from The Copenhagen City Heart Study. Neither the ACE genotype distribution (p = 0.12) nor the D and I allele frequencies (p = 0.69) differed significantly between subjects with elevated UAE and a matched normoalbuminuric......An elevated urinary albumin excretion (UAE) in non-diabetic subjects without renal or cardiovascular disease has been shown to be predictive of ischaemic heart disease. An insertion (I)/deletion (D) polymorphism in the angiotensin I-converting enzyme (ACE) gene has been identified and the D allele...... control group (n = 46). Elevated UAE in clinically healthy subjects is not linked to the ACE gene polymorphism....

  19. Reconstruction of Gene Regulatory Networks Based on Two-Stage Bayesian Network Structure Learning Algorithm

    Institute of Scientific and Technical Information of China (English)

    Gui-xia Liu; Wei Feng; Han Wang; Lei Liu; Chun-guang Zhou

    2009-01-01

    In the post-genomic biology era, the reconstruction of gene regulatory networks from microarray gene expression data is very important to understand the underlying biological system, and it has been a challenging task in bioinformatics. The Bayesian network model has been used in reconstructing the gene regulatory network for its advantages, but how to determine the network structure and parameters is still important to be explored. This paper proposes a two-stage structure learning algorithm which integrates immune evolution algorithm to build a Bayesian network .The new algorithm is evaluated with the use of both simulated and yeast cell cycle data. The experimental results indicate that the proposed algorithm can find many of the known real regulatory relationships from literature and predict the others unknown with high validity and accuracy.

  20. An efficient approach of attractor calculation for large-scale Boolean gene regulatory networks.

    Science.gov (United States)

    He, Qinbin; Xia, Zhile; Lin, Bin

    2016-11-07

    Boolean network models provide an efficient way for studying gene regulatory networks. The main dynamics of a Boolean network is determined by its attractors. Attractor calculation plays a key role for analyzing Boolean gene regulatory networks. An approach of attractor calculation was proposed in this study, which improved the predecessor-based approach. Furthermore, the proposed approach combined with the identification of constant nodes and simplified Boolean networks to accelerate attractor calculation. The proposed algorithm is effective to calculate all attractors for large-scale Boolean gene regulatory networks. If the average degree of the network is not too large, the algorithm can get all attractors of a Boolean network with dozens or even hundreds of nodes.

  1. Biological data warehousing system for identifying transcriptional regulatory sites from gene expressions of microarray data.

    Science.gov (United States)

    Tsou, Ann-Ping; Sun, Yi-Ming; Liu, Chia-Lin; Huang, Hsien-Da; Horng, Jorng-Tzong; Tsai, Meng-Feng; Liu, Baw-Juine

    2006-07-01

    Identification of transcriptional regulatory sites plays an important role in the investigation of gene regulation. For this propose, we designed and implemented a data warehouse to integrate multiple heterogeneous biological data sources with data types such as text-file, XML, image, MySQL database model, and Oracle database model. The utility of the biological data warehouse in predicting transcriptional regulatory sites of coregulated genes was explored using a synexpression group derived from a microarray study. Both of the binding sites of known transcription factors and predicted over-represented (OR) oligonucleotides were demonstrated for the gene group. The potential biological roles of both known nucleotides and one OR nucleotide were demonstrated using bioassays. Therefore, the results from the wet-lab experiments reinforce the power and utility of the data warehouse as an approach to the genome-wide search for important transcription regulatory elements that are the key to many complex biological systems.

  2. Combined effects of urinary phytoestrogens metabolites and polymorphisms in metabolic enzyme gene on idiopathic male infertility.

    Science.gov (United States)

    Qin, Yufeng; Du, Guizhen; Chen, Minjian; Hu, Weiyue; Lu, Chuncheng; Wu, Wei; Hang, Bo; Zhou, Zuomin; Wang, Xinru; Xia, Yankai

    2014-08-01

    Phytoestrogens are plant-derived compounds that may interact with estrogen receptors and mimic estrogenic effects. It remains unclear whether the individual variability in metabolizing phytoestrogens contributes to phytoestrogens-induced beneficial or detrimental effects. Our aim was to determine whether there is any interaction between metabolic rates (MR) of phytoestrogens and genetic polymorphisms in related xenobiotic metabolizing enzyme genes. MR was used to assess phytoestrogen exposure and individual metabolic ability. The amount of phytoestrogens in urine was measured by ultra-high performance liquid chromatography-tandem mass spectrometry in 600 idiopathic infertile male patients and 401 controls. Polymorphisms were genotyped using the SNPstream platform combined with the Taqman method. Prototypes and metabolites of secoisolariciresinol (SEC) have inverse effects on male reproduction. It was found that low MR of SEC increased the risk of male infertility (OR 2.49, 95 % CI 1.78, 3.48, P trend = 8.00 × 10(-8)). Novel interactions were also observed between the MR of SEC and rs1042389 in CYP2B6, rs1048943 in CYP1A1, and rs1799931 in NAT2 on male infertility (P inter = 1.06 × 10(-4), 1.14 × 10(-3), 3.55 × 10(-3), respectively). By analyzing the relationships between urinary phytoestrogen concentrations, their metabolites and male infertility, we found that individual variability in metabolizing SEC contributed to the interpersonal differences in SEC's effects on male reproduction.

  3. Complement regulatory protein genes in channel catfish and their involvement in disease defense response.

    Science.gov (United States)

    Jiang, Chen; Zhang, Jiaren; Yao, Jun; Liu, Shikai; Li, Yun; Song, Lin; Li, Chao; Wang, Xiaozhu; Liu, Zhanjiang

    2015-11-01

    Complement system is one of the most important defense systems of innate immunity, which plays a crucial role in disease defense responses in channel catfish. However, inappropriate and excessive complement activation could lead to potential damage to the host cells. Therefore the complement system is controlled by a set of complement regulatory proteins to allow normal defensive functions, but prevent hazardous complement activation to host tissues. In this study, we identified nine complement regulatory protein genes from the channel catfish genome. Phylogenetic and syntenic analyses were conducted to determine their orthology relationships, supporting their correct annotation and potential functional inferences. The expression profiles of the complement regulatory protein genes were determined in channel catfish healthy tissues and after infection with the two main bacterial pathogens, Edwardsiella ictaluri and Flavobacterium columnare. The vast majority of complement regulatory protein genes were significantly regulated after bacterial infections, but interestingly were generally up-regulated after E. ictaluri infection while mostly down-regulated after F. columnare infection, suggesting a pathogen-specific pattern of regulation. Collectively, these findings suggested that complement regulatory protein genes may play complex roles in the host immune responses to bacterial pathogens in channel catfish.

  4. Regulatory elements of the floral homeotic gene AGAMOUS identified by phylogenetic footprinting and shadowing.

    Energy Technology Data Exchange (ETDEWEB)

    Hong, R. L., Hamaguchi, L., Busch, M. A., and Weigel, D.

    2003-06-01

    OAK-B135 In Arabidopsis thaliana, cis-regulatory sequences of the floral homeotic gene AGAMOUS (AG) are located in the second intron. This 3 kb intron contains binding sites for two direct activators of AG, LEAFY (LFY) and WUSCHEL (WUS), along with other putative regulatory elements. We have used phylogenetic footprinting and the related technique of phylogenetic shadowing to identify putative cis-regulatory elements in this intron. Among 29 Brassicaceae, several other motifs, but not the LFY and WUS binding sites previously identified, are largely invariant. Using reporter gene analyses, we tested six of these motifs and found that they are all functionally important for activity of AG regulatory sequences in A. thaliana. Although there is little obvious sequence similarity outside the Brassicaceae, the intron from cucumber AG has at least partial activity in A. thaliana. Our studies underscore the value of the comparative approach as a tool that complements gene-by-gene promoter dissection, but also highlight that sequence-based studies alone are insufficient for a complete identification of cis-regulatory sites.

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

    Directory of Open Access Journals (Sweden)

    Bringas Ricardo

    2008-01-01

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

  6. Harnessing diversity towards the reconstructing of large scale gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Takeshi Hase

    Full Text Available Elucidating gene regulatory network (GRN from large scale experimental data remains a central challenge in systems biology. Recently, numerous techniques, particularly consensus driven approaches combining different algorithms, have become a potentially promising strategy to infer accurate GRNs. Here, we develop a novel consensus inference algorithm, TopkNet that can integrate multiple algorithms to infer GRNs. Comprehensive performance benchmarking on a cloud computing framework demonstrated that (i a simple strategy to combine many algorithms does not always lead to performance improvement compared to the cost of consensus and (ii TopkNet integrating only high-performance algorithms provide significant performance improvement compared to the best individual algorithms and community prediction. These results suggest that a priori determination of high-performance algorithms is a key to reconstruct an unknown regulatory network. Similarity among gene-expression datasets can be useful to determine potential optimal algorithms for reconstruction of unknown regulatory networks, i.e., if expression-data associated with known regulatory network is similar to that with unknown regulatory network, optimal algorithms determined for the known regulatory network can be repurposed to infer the unknown regulatory network. Based on this observation, we developed a quantitative measure of similarity among gene-expression datasets and demonstrated that, if similarity between the two expression datasets is high, TopkNet integrating algorithms that are optimal for known dataset perform well on the unknown dataset. The consensus framework, TopkNet, together with the similarity measure proposed in this study provides a powerful strategy towards harnessing the wisdom of the crowds in reconstruction of unknown regulatory networks.

  7. Fractal gene regulatory networks for robust locomotion control of modular robots

    DEFF Research Database (Denmark)

    Zahadat, Payam; Christensen, David Johan; Schultz, Ulrik Pagh;

    2010-01-01

    Designing controllers for modular robots is difficult due to the distributed and dynamic nature of the robots. In this paper fractal gene regulatory networks are evolved to control modular robots in a distributed way. Experiments with different morphologies of modular robot are performed and the ......Designing controllers for modular robots is difficult due to the distributed and dynamic nature of the robots. In this paper fractal gene regulatory networks are evolved to control modular robots in a distributed way. Experiments with different morphologies of modular robot are performed...

  8. Molecular characterization of a maize regulatory gene. Progress report, July 1989--March 1990

    Energy Technology Data Exchange (ETDEWEB)

    Wessler, S.

    1990-12-31

    This progress report contains information concerning the characterization of the Maize regulatory gene. The findings of this research program have immediate significance. Firstly, it provides support for the notion that R proteins, produced by the regulatory gene, are functionally equivalent. Secondly, the success of these experiments provides a simple transient assay for either natural or constructed R protein mutations. The relative ease of this assay coupled with overnight results are important prerequisites to the proposed experiments involving a structure-function analysis of the R protein.

  9. Sensor-coupled fractal gene regulatory networks for locomotion control of a modular snake robot

    DEFF Research Database (Denmark)

    Zahadat, Payam; Christensen, David Johan; Katebi, Serajeddin

    2013-01-01

    In this paper we study fractal gene regulatory network (FGRN) controllers based on sensory information. The FGRN controllers are evolved to control a snake robot consisting of seven simulated ATRON modules. Each module contains three tilt sensors which represent the direction of gravity in the co......In this paper we study fractal gene regulatory network (FGRN) controllers based on sensory information. The FGRN controllers are evolved to control a snake robot consisting of seven simulated ATRON modules. Each module contains three tilt sensors which represent the direction of gravity...

  10. Regulatory genes controlling mitosis in the fission yeast Schizosaccharomyces pombe.

    Science.gov (United States)

    Nurse, P; Thuriaux, P

    1980-11-01

    Fifty-two wee mutants that undergo mitosis and cell division at a reduced size compared with wild type have been genetically analyzed. The mutants define two genes, wee1 and cdc2, which control the timing of mitosis. Fifty-one of the mutants map at the wee1 locus, which is unlinked to any known cdc gene. One of the wee1 alleles has been shown to be nonsense suppressible. The 52nd were mutant maps within cdc2. Previously, only temperature-sensitive mutants that become blocked at mitosis have been found at the cdc2 locus. The simplest interpretation of these observations is that wee1+ codes for a negative element or inhibitor, and cdc2+ codes for a positive element or activator in the mitotic control. The gene dosage of wee1+ plays some role in determining the timing of mitosis, but the gene dosage of cdc2+ has little effect. However, some aspect of the cdc2 gene product activity is important for determining when mitosis takes place. The possible roles of wee1 and cdc2 in the mitotic control are discussed, with particular reference to the part they may play in the monitoring of cell growth rate, both of which influence the timing of mitosis.

  11. The Intolerance of Regulatory Sequence to Genetic Variation Predicts Gene Dosage Sensitivity.

    Directory of Open Access Journals (Sweden)

    Slavé Petrovski

    2015-09-01

    Full Text Available Noncoding sequence contains pathogenic mutations. Yet, compared with mutations in protein-coding sequence, pathogenic regulatory mutations are notoriously difficult to recognize. Most fundamentally, we are not yet adept at recognizing the sequence stretches in the human genome that are most important in regulating the expression of genes. For this reason, it is difficult to apply to the regulatory regions the same kinds of analytical paradigms that are being successfully applied to identify mutations among protein-coding regions that influence risk. To determine whether dosage sensitive genes have distinct patterns among their noncoding sequence, we present two primary approaches that focus solely on a gene's proximal noncoding regulatory sequence. The first approach is a regulatory sequence analogue of the recently introduced residual variation intolerance score (RVIS, termed noncoding RVIS, or ncRVIS. The ncRVIS compares observed and predicted levels of standing variation in the regulatory sequence of human genes. The second approach, termed ncGERP, reflects the phylogenetic conservation of a gene's regulatory sequence using GERP++. We assess how well these two approaches correlate with four gene lists that use different ways to identify genes known or likely to cause disease through changes in expression: 1 genes that are known to cause disease through haploinsufficiency, 2 genes curated as dosage sensitive in ClinGen's Genome Dosage Map, 3 genes judged likely to be under purifying selection for mutations that change expression levels because they are statistically depleted of loss-of-function variants in the general population, and 4 genes judged unlikely to cause disease based on the presence of copy number variants in the general population. We find that both noncoding scores are highly predictive of dosage sensitivity using any of these criteria. In a similar way to ncGERP, we assess two ensemble-based predictors of regional noncoding

  12. The Intolerance of Regulatory Sequence to Genetic Variation Predicts Gene Dosage Sensitivity.

    Science.gov (United States)

    Petrovski, Slavé; Gussow, Ayal B; Wang, Quanli; Halvorsen, Matt; Han, Yujun; Weir, William H; Allen, Andrew S; Goldstein, David B

    2015-09-01

    Noncoding sequence contains pathogenic mutations. Yet, compared with mutations in protein-coding sequence, pathogenic regulatory mutations are notoriously difficult to recognize. Most fundamentally, we are not yet adept at recognizing the sequence stretches in the human genome that are most important in regulating the expression of genes. For this reason, it is difficult to apply to the regulatory regions the same kinds of analytical paradigms that are being successfully applied to identify mutations among protein-coding regions that influence risk. To determine whether dosage sensitive genes have distinct patterns among their noncoding sequence, we present two primary approaches that focus solely on a gene's proximal noncoding regulatory sequence. The first approach is a regulatory sequence analogue of the recently introduced residual variation intolerance score (RVIS), termed noncoding RVIS, or ncRVIS. The ncRVIS compares observed and predicted levels of standing variation in the regulatory sequence of human genes. The second approach, termed ncGERP, reflects the phylogenetic conservation of a gene's regulatory sequence using GERP++. We assess how well these two approaches correlate with four gene lists that use different ways to identify genes known or likely to cause disease through changes in expression: 1) genes that are known to cause disease through haploinsufficiency, 2) genes curated as dosage sensitive in ClinGen's Genome Dosage Map, 3) genes judged likely to be under purifying selection for mutations that change expression levels because they are statistically depleted of loss-of-function variants in the general population, and 4) genes judged unlikely to cause disease based on the presence of copy number variants in the general population. We find that both noncoding scores are highly predictive of dosage sensitivity using any of these criteria. In a similar way to ncGERP, we assess two ensemble-based predictors of regional noncoding importance, nc

  13. Analysis of regulatory networks constructed based on gene coexpression in pituitary adenoma.

    Science.gov (United States)

    Gong, Jie; Diao, Bo; Yao, Guo Jie; Liu, Ying; Xu, Guo Zheng

    2013-12-01

    Gene coexpression patterns can reveal gene collections with functional consistency. This study systematically constructs regulatory networks for pituitary tumours by integrating gene coexpression, transcriptional and posttranscriptional regulation. Through network analysis, we elaborate the incidence mechanism of pituitary adenoma. The Pearson's correlation coefficient was utilized to calculate the level of gene coexpression. By comparing pituitary adenoma samples with normal samples, pituitary adenoma-specific gene coexpression patterns were identified. For pituitary adenoma-specific coexpressed genes, we integrated transcription factor (TF) and microRNA (miRNA) regulation to construct a complex regulatory network from the transcriptional and posttranscriptional perspectives. Network module analysis identified the synergistic regulation of genes by miRNAs and TFs in pituitary adenoma. We identified 142 pituitary adenoma-specific active genes, including 43 TFs and 99 target genes of TFs. Functional enrichment of these 142 genes revealed that the occurrence of pituitary adenoma induced abnormalities in intracellular metabolism and angiogenesis process. These 142 genes were also significantly enriched in adenoma pathway. Module analysis of the systematic regulatory network found that three modules contained elements that were closely related to pituitary adenoma, such as FGF2 and SP1, as well as transcription factors and miRNAs involved in the tumourigenesis. These results show that in the occurrence of pituitary adenoma, miRNA, TF and genes interact with each other. Based on gene expression, the proposed method integrates interaction information from different levels and systematically explains the occurrence of pituitary tumours. It facilitates the tracing of the origin of the disease and can provide basis for early diagnosis of complex diseases or cancer without obvious symptoms.

  14. Analysis of regulatory networks constructed based on gene coexpression in pituitary adenoma

    Indian Academy of Sciences (India)

    Jie Gong; Bo Diao; Guo Jie Yao; Ying Liu; Guo Zheng Xu

    2013-12-01

    Gene coexpression patterns can reveal gene collections with functional consistency. This study systematically constructs regulatory networks for pituitary tumours by integrating gene coexpression, transcriptional and posttranscriptional regulation. Through network analysis, we elaborate the incidence mechanism of pituitary adenoma. The Pearson’s correlation coefficient was utilized to calculate the level of gene coexpression. By comparing pituitary adenoma samples with normal samples, pituitary adenoma-specific gene coexpression patterns were identified. For pituitary adenoma-specific coexpressed genes, we integrated transcription factor (TF) and microRNA (miRNA) regulation to construct a complex regulatory network from the transcriptional and posttranscriptional perspectives. Network module analysis identified the synergistic regulation of genes by miRNAs and TFs in pituitary adenoma. We identified 142 pituitary adenoma-specific active genes, including 43 TFs and 99 target genes of TFs. Functional enrichment of these 142 genes revealed that the occurrence of pituitary adenoma induced abnormalities in intracellular metabolism and angiogenesis process. These 142 genes were also significantly enriched in adenoma pathway. Module analysis of the systematic regulatory network found that three modules contained elements that were closely related to pituitary adenoma, such as FGF2 and SP1, as well as transcription factors and miRNAs involved in the tumourigenesis. These results show that in the occurrence of pituitary adenoma, miRNA, TF and genes interact with each other. Based on gene expression, the proposed method integrates interaction information from different levels and systematically explains the occurrence of pituitary tumours. It facilitates the tracing of the origin of the disease and can provide basis for early diagnosis of complex diseases or cancer without obvious symptoms.

  15. Structures and Boolean Dynamics in Gene Regulatory Networks

    Science.gov (United States)

    Szedlak, Anthony

    This dissertation discusses the topological and dynamical properties of GRNs in cancer, and is divided into four main chapters. First, the basic tools of modern complex network theory are introduced. These traditional tools as well as those developed by myself (set efficiency, interset efficiency, and nested communities) are crucial for understanding the intricate topological properties of GRNs, and later chapters recall these concepts. Second, the biology of gene regulation is discussed, and a method for disease-specific GRN reconstruction developed by our collaboration is presented. This complements the traditional exhaustive experimental approach of building GRNs edge-by-edge by quickly inferring the existence of as of yet undiscovered edges using correlations across sets of gene expression data. This method also provides insight into the distribution of common mutations across GRNs. Third, I demonstrate that the structures present in these reconstructed networks are strongly related to the evolutionary histories of their constituent genes. Investigation of how the forces of evolution shaped the topology of GRNs in multicellular organisms by growing outward from a core of ancient, conserved genes can shed light upon the ''reverse evolution'' of normal cells into unicellular-like cancer states. Next, I simulate the dynamics of the GRNs of cancer cells using the Hopfield model, an infinite range spin-glass model designed with the ability to encode Boolean data as attractor states. This attractor-driven approach facilitates the integration of gene expression data into predictive mathematical models. Perturbations representing therapeutic interventions are applied to sets of genes, and the resulting deviations from their attractor states are recorded, suggesting new potential drug targets for experimentation. Finally, I extend the Hopfield model to modular networks, cyclic attractors, and complex attractors, and apply these concepts to simulations of the cell cycle

  16. A method for developing regulatory gene set networks to characterize complex biological systems.

    Science.gov (United States)

    Suphavilai, Chayaporn; Zhu, Liugen; Chen, Jake Y

    2015-01-01

    Traditional approaches to studying molecular networks are based on linking genes or proteins. Higher-level networks linking gene sets or pathways have been proposed recently. Several types of gene set networks have been used to study complex molecular networks such as co-membership gene set networks (M-GSNs) and co-enrichment gene set networks (E-GSNs). Gene set networks are useful for studying biological mechanism of diseases and drug perturbations. In this study, we proposed a new approach for constructing directed, regulatory gene set networks (R-GSNs) to reveal novel relationships among gene sets or pathways. We collected several gene set collections and high-quality gene regulation data in order to construct R-GSNs in a comparative study with co-membership gene set networks (M-GSNs). We described a method for constructing both global and disease-specific R-GSNs and determining their significance. To demonstrate the potential applications to disease biology studies, we constructed and analysed an R-GSN specifically built for Alzheimer's disease. R-GSNs can provide new biological insights complementary to those derived at the protein regulatory network level or M-GSNs. When integrated properly to functional genomics data, R-GSNs can help enable future research on systems biology and translational bioinformatics.

  17. Regulatory Genes Controlling Mitosis in the Fission Yeast SCHIZOSACCHAROMYCES POMBE

    OpenAIRE

    Nurse, Paul; Thuriaux, Pierre

    1980-01-01

    Fifty-two wee mutants that undergo mitosis and cell division at a reduced size compared with wild type have been genetically analyzed. The mutants define two genes, wee1 and cdc2, which control the timing of mitosis. Fifty-one of the mutants map at the wee1 locus, which is unlinked to any known cdc gene. One of the wee1 alleles has been shown to be nonsense suppressible. The 52nd wee mutant maps within cdc2. Previously, only temperature-sensitive mutants that become blocked at mitosis have be...

  18. Developmental gene regulatory network architecture across 500 million years of echinoderm evolution

    Science.gov (United States)

    Hinman, Veronica F.; Nguyen, Albert T.; Cameron, R. Andrew; Davidson, Eric H.

    2003-01-01

    Evolutionary change in morphological features must depend on architectural reorganization of developmental gene regulatory networks (GRNs), just as true conservation of morphological features must imply retention of ancestral developmental GRN features. Key elements of the provisional GRN for embryonic endomesoderm development in the sea urchin are here compared with those operating in embryos of a distantly related echinoderm, a starfish. These animals diverged from their common ancestor 520-480 million years ago. Their endomesodermal fate maps are similar, except that sea urchins generate a skeletogenic cell lineage that produces a prominent skeleton lacking entirely in starfish larvae. A relevant set of regulatory genes was isolated from the starfish Asterina miniata, their expression patterns determined, and effects on the other genes of perturbing the expression of each were demonstrated. A three-gene feedback loop that is a fundamental feature of the sea urchin GRN for endoderm specification is found in almost identical form in the starfish: a detailed element of GRN architecture has been retained since the Cambrian Period in both echinoderm lineages. The significance of this retention is highlighted by the observation of numerous specific differences in the GRN connections as well. A regulatory gene used to drive skeletogenesis in the sea urchin is used entirely differently in the starfish, where it responds to endomesodermal inputs that do not affect it in the sea urchin embryo. Evolutionary changes in the GRNs since divergence are limited sharply to certain cis-regulatory elements, whereas others have persisted unaltered.

  19. Influence of the experimental design of gene expression studies on the inference of gene regulatory networks: environmental factors

    Directory of Open Access Journals (Sweden)

    Frank Emmert-Streib

    2013-02-01

    Full Text Available The inference of gene regulatory networks gained within recent years a considerable interest in the biology and biomedical community. The purpose of this paper is to investigate the influence that environmental conditions can exhibit on the inference performance of network inference algorithms. Specifically, we study five network inference methods, Aracne, BC3NET, CLR, C3NET and MRNET, and compare the results for three different conditions: (I observational gene expression data: normal environmental condition, (II interventional gene expression data: growth in rich media, (III interventional gene expression data: normal environmental condition interrupted by a positive spike-in stimulation. Overall, we find that different statistical inference methods lead to comparable, but condition-specific results. Further, our results suggest that non-steady-state data enhance the inferability of regulatory networks.

  20. Understanding the Role of Housekeeping and Stress-Related Genes in Transcription-Regulatory Networks

    Science.gov (United States)

    Heath, Allison; Kavraki, Lydia; Balázsi, Gábor

    2008-03-01

    Despite the increasing number of completely sequenced genomes, much remains to be learned about how living cells process environmental information and respond to changes in their surroundings. Accumulating evidence indicates that eukaryotic and prokaryotic genes can be classified in two distinct categories that we will call class I and class II. Class I genes are housekeeping genes, often characterized by stable, noise resistant expression levels. In contrast, class II genes are stress-related genes and often have noisy, unstable expression levels. In this work we analyze the large scale transcription-regulatory networks (TRN) of E. coli and S. cerevisiae and preliminary data on H. sapien. We find that stable, housekeeping genes (class I) are preferentially utilized as transcriptional inputs while stress related, unstable genes (class II) are utilized as transcriptional integrators. This might be the result of convergent evolution that placed the appropriate genes in the appropriate locations within transcriptional networks according to some fundamental principles that govern cellular information processing.

  1. A study on the regulatory network with promoter analysis for Arabidopsis DREB-genes

    Science.gov (United States)

    Sazegari, Sima; Niazi, Ali; Ahmadi, Farajolah Shahriary

    2015-01-01

    Dehydration response element binding factors (DREBs) are one of the principal plant transcription factor subfamilies that regulate the expression of many abiotic stress-inducible genes. This sub-family belongs to AP2 transcription factor family and plays a considerable role in improving abiotic stresses tolerance in plants. Therefore, it is of interest to identify critical cis-acting elements involved in abiotic stress responses. In this study, we survey promoter cis-elements for ATDREBs genes (Arabidopsis thaliana DREBs). Regulatory networks based on ATDREB candidate genes were also generated to find other genes that are functionally similar to DREBs. The study was conducted on all 20 Arabidopsis thaliana non redundant DREB genes stored in RefSeq database. Promoter analysis and regulatory network prediction was accomplished by use of Plant CARE program and GeneMANIA web tool, respectively. The results indicated that among all genes, DREB1A, DREB1C, DREB2C, DREB2G and DEAR3 have the most type of diverse motifs involved in abiotic stress responses. It is implied that co-operation of abscisic acid, ethylene, salicylic acid and methyl jasmonate signaling is crucial for the regulation of the expression of drought and cold responses through DREB transcription factors. Gene network analysis showed different co-expressed but functionally similar genes that had physical and functional interactions with candidate DREB genes. PMID:25848171

  2. Large-scale genetic perturbations reveal regulatory networks and an abundance of gene-specific repressors.

    Science.gov (United States)

    Kemmeren, Patrick; Sameith, Katrin; van de Pasch, Loes A L; Benschop, Joris J; Lenstra, Tineke L; Margaritis, Thanasis; O'Duibhir, Eoghan; Apweiler, Eva; van Wageningen, Sake; Ko, Cheuk W; van Heesch, Sebastiaan; Kashani, Mehdi M; Ampatziadis-Michailidis, Giannis; Brok, Mariel O; Brabers, Nathalie A C H; Miles, Anthony J; Bouwmeester, Diane; van Hooff, Sander R; van Bakel, Harm; Sluiters, Erik; Bakker, Linda V; Snel, Berend; Lijnzaad, Philip; van Leenen, Dik; Groot Koerkamp, Marian J A; Holstege, Frank C P

    2014-04-24

    To understand regulatory systems, it would be useful to uniformly determine how different components contribute to the expression of all other genes. We therefore monitored mRNA expression genome-wide, for individual deletions of one-quarter of yeast genes, focusing on (putative) regulators. The resulting genetic perturbation signatures reflect many different properties. These include the architecture of protein complexes and pathways, identification of expression changes compatible with viability, and the varying responsiveness to genetic perturbation. The data are assembled into a genetic perturbation network that shows different connectivities for different classes of regulators. Four feed-forward loop (FFL) types are overrepresented, including incoherent type 2 FFLs that likely represent feedback. Systematic transcription factor classification shows a surprisingly high abundance of gene-specific repressors, suggesting that yeast chromatin is not as generally restrictive to transcription as is often assumed. The data set is useful for studying individual genes and for discovering properties of an entire regulatory system.

  3. Identification of the gene-regulatory landscape in skeletal development and potential links to skeletal regeneration

    Directory of Open Access Journals (Sweden)

    Hironori Hojo

    2017-06-01

    Full Text Available A class of gene-regulatory elements called enhancers are the main mediators controlling quantitative, temporal and spatial gene expressions. In the course of evolution, the enhancer landscape of higher organisms such as mammals has become quite complex, exerting biological functions precisely and coordinately. In mammalian skeletal development, the master transcription factors Sox9, Runx2 and Sp7/Osterix function primarily through enhancers on the genome to achieve specification and differentiation of skeletal cells. Recently developed genome-scale analyses have shed light on multiple layers of gene regulations, uncovering not only the primary mode of actions of these transcription factors on skeletal enhancers, but also the relation of the epigenetic landscape to three-dimensional chromatin architecture. Here, we review findings on the emerging framework of gene-regulatory networks involved in skeletal development. We further discuss the power of genome-scale analyses to provide new insights into genetic diseases and regenerative medicine in skeletal tissues.

  4. Identifying time-delayed gene regulatory networks via an evolvable hierarchical recurrent neural network.

    Science.gov (United States)

    Kordmahalleh, Mina Moradi; Sefidmazgi, Mohammad Gorji; Harrison, Scott H; Homaifar, Abdollah

    2017-01-01

    The modeling of genetic interactions within a cell is crucial for a basic understanding of physiology and for applied areas such as drug design. Interactions in gene regulatory networks (GRNs) include effects of transcription factors, repressors, small metabolites, and microRNA species. In addition, the effects of regulatory interactions are not always simultaneous, but can occur after a finite time delay, or as a combined outcome of simultaneous and time delayed interactions. Powerful biotechnologies have been rapidly and successfully measuring levels of genetic expression to illuminate different states of biological systems. This has led to an ensuing challenge to improve the identification of specific regulatory mechanisms through regulatory network reconstructions. Solutions to this challenge will ultimately help to spur forward efforts based on the usage of regulatory network reconstructions in systems biology applications. We have developed a hierarchical recurrent neural network (HRNN) that identifies time-delayed gene interactions using time-course data. A customized genetic algorithm (GA) was used to optimize hierarchical connectivity of regulatory genes and a target gene. The proposed design provides a non-fully connected network with the flexibility of using recurrent connections inside the network. These features and the non-linearity of the HRNN facilitate the process of identifying temporal patterns of a GRN. Our HRNN method was implemented with the Python language. It was first evaluated on simulated data representing linear and nonlinear time-delayed gene-gene interaction models across a range of network sizes and variances of noise. We then further demonstrated the capability of our method in reconstructing GRNs of the Saccharomyces cerevisiae synthetic network for in vivo benchmarking of reverse-engineering and modeling approaches (IRMA). We compared the performance of our method to TD-ARACNE, HCC-CLINDE, TSNI and ebdbNet across different network

  5. Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function

    Science.gov (United States)

    Martin, O. C.; Krzywicki, A.; Zagorski, M.

    2016-07-01

    Living cells can maintain their internal states, react to changing environments, grow, differentiate, divide, etc. All these processes are tightly controlled by what can be called a regulatory program. The logic of the underlying control can sometimes be guessed at by examining the network of influences amongst genetic components. Some associated gene regulatory networks have been studied in prokaryotes and eukaryotes, unveiling various structural features ranging from broad distributions of out-degrees to recurrent "motifs", that is small subgraphs having a specific pattern of interactions. To understand what factors may be driving such structuring, a number of groups have introduced frameworks to model the dynamics of gene regulatory networks. In that context, we review here such in silico approaches and show how selection for phenotypes, i.e., network function, can shape network structure.

  6. [Role of genes and their cis-regulatory elements during animal morphological evolution].

    Science.gov (United States)

    Sun, Boyuan; Tu, Jianbo; Li, Ying; Yang, Mingyao

    2014-06-01

    Cis-regulatory hypothesis is one of the most important theories in evolutionary developmental biology (evo-devo), which claims that evolution of cis-regulatory elements (CREs) plays a key role during evolution of morphology. However, an increasing number of experimental results show that cis-regulatory hypothesis alone is not far enough to explain the complexity of evo-devo processes. Other modifications, including mutations of protein coding, gene and genome duplications, and flexibility of homeodomains and CREs, also cause the morphological changes in animals. In this review, we retrospect the recent results of evolution of CREs and genes associated with CREs and discuss new methods and trends for research in evo-devo.

  7. Genome-wide prediction of transcriptional regulatory elements of human promoters using gene expression and promoter analysis data

    Directory of Open Access Journals (Sweden)

    Kim Seon-Young

    2006-07-01

    Full Text Available Abstract Background A complete understanding of the regulatory mechanisms of gene expression is the next important issue of genomics. Many bioinformaticians have developed methods and algorithms for predicting transcriptional regulatory mechanisms from sequence, gene expression, and binding data. However, most of these studies involved the use of yeast which has much simpler regulatory networks than human and has many genome wide binding data and gene expression data under diverse conditions. Studies of genome wide transcriptional networks of human genomes currently lag behind those of yeast. Results We report herein a new method that combines gene expression data analysis with promoter analysis to infer transcriptional regulatory elements of human genes. The Z scores from the application of gene set analysis with gene sets of transcription factor binding sites (TFBSs were successfully used to represent the activity of TFBSs in a given microarray data set. A significant correlation between the Z scores of gene sets of TFBSs and individual genes across multiple conditions permitted successful identification of many known human transcriptional regulatory elements of genes as well as the prediction of numerous putative TFBSs of many genes which will constitute a good starting point for further experiments. Using Z scores of gene sets of TFBSs produced better predictions than the use of mRNA levels of a transcription factor itself, suggesting that the Z scores of gene sets of TFBSs better represent diverse mechanisms for changing the activity of transcription factors in the cell. In addition, cis-regulatory modules, combinations of co-acting TFBSs, were readily identified by our analysis. Conclusion By a strategic combination of gene set level analysis of gene expression data sets and promoter analysis, we were able to identify and predict many transcriptional regulatory elements of human genes. We conclude that this approach will aid in decoding

  8. Modelling non-stationary dynamic gene regulatory processes with the BGM model

    NARCIS (Netherlands)

    Grzegorczyk, Marco; Husmeier, Dirk; Rahnenfuehrer, Joerg

    2011-01-01

    Recently, a Bayesian network model for inferring non-stationary regulatory processes from gene expression time series has been proposed. The Bayesian Gaussian Mixture (BGM) Bayesian network model divides the data into disjunct compartments (data subsets) by a free allocation model, and infers networ

  9. Bottom-up GGM algorithm for constructing multiple layered hierarchical gene regulatory networks

    Science.gov (United States)

    Multilayered hierarchical gene regulatory networks (ML-hGRNs) are very important for understanding genetics regulation of biological pathways. However, there are currently no computational algorithms available for directly building ML-hGRNs that regulate biological pathways. A bottom-up graphic Gaus...

  10. Multiple sensors control reciprocal expression of Pseudomonas aeruginosa regulatory RNA and virulence genes

    DEFF Research Database (Denmark)

    Ventre, I.; Goodman, A.L.; Vallet-Gely, I.

    2006-01-01

    by controlling the transcription of a small regulatory RNA, RsmZ. This work identifies a previously undescribed signal transduction network in which the activities of signal-receiving sensor kinases LadS, RetS, and GacS regulate expression of virulence genes associated with acute or chronic infection...

  11. Small RNA-Controlled Gene Regulatory Networks in Pseudomonas putida

    DEFF Research Database (Denmark)

    Bojanovic, Klara

    evolved numerous mechanisms to controlgene expression in response to specific environmental signals. In addition to two-component systems, small regulatory RNAs (sRNAs) have emerged as major regulators of gene expression. The majority of sRNAs bind to mRNA and regulate their expression. They often have...

  12. Regulatory Network Construction in Arabidopsis using genome-wide gene expression QTLs

    NARCIS (Netherlands)

    Keurentjes, J.J.B.; Fu, J.J.; Terpstra, I.R.; Garcia, J.M.; van den Ackerveken, G.; Snoek, L.B.; Peeters, A.J.M.; Vreugdenhil, D.; Koornreef, M.; Jansen, R.C.

    2007-01-01

    Regulatory network construction in Arabidopsis by using genome-wide gene expression quantitative trait loci.Keurentjes JJ, Fu J, Terpstra IR, Garcia JM, van den Ackerveken G, Snoek LB, Peeters AJ, Vreugdenhil D, Koornneef M, Jansen RC. Laboratory of Genetics, Wageningen University, Arboretumlaan 4,

  13. Regulatory gene mutation: a driving force behind group a Streptococcus strain- and serotype-specific variation.

    Science.gov (United States)

    Sarkar, Poulomee; Sumby, Paul

    2017-02-01

    Data from multiple bacterial pathogens are consistent with regulator-encoding genes having higher mutation frequencies than the genome average. Such mutations drive both strain- and type- (e.g., serotype, haplotype) specific phenotypic heterogeneity, and may challenge public health due to the potential of variants to circumvent established treatment and/or preventative regimes. Here, using the human bacterial pathogen the group A Streptococcus (GAS; S. pyogenes) as a model organism, we review the types and regulatory-, phenotypic-, and disease-specific consequences of naturally occurring regulatory gene mutations. Strain-specific regulator mutations that will be discussed include examples that transform isolates into hyper-invasive forms by enhancing expression of immunomodulatory virulence factors, and examples that promote asymptomatic carriage of the organism. The discussion of serotype-specific regulator mutations focuses on serotype M3 GAS isolates, and how the identified rewiring of regulatory networks in this serotype may be contributing to a decades old epidemiological association of M3 isolates with particularly severe invasive infections. We conclude that mutation plays an outsized role in GAS pathogenesis and has clinical relevance. Given the phenotypic variability associated with regulatory gene mutations, the rapid examination of these genes in infecting isolates may inform with respect to potential patient complications and treatment options.

  14. In vivo SPECT reporter gene imaging of regulatory T cells.

    Directory of Open Access Journals (Sweden)

    Ehsan Sharif-Paghaleh

    Full Text Available Regulatory T cells (Tregs were identified several years ago and are key in controlling autoimmune diseases and limiting immune responses to foreign antigens, including alloantigens. In vivo imaging techniques including intravital microscopy as well as whole body imaging using bioluminescence probes have contributed to the understanding of in vivo Treg function, their mechanisms of action and target cells. Imaging of the human sodium/iodide symporter via Single Photon Emission Computed Tomography (SPECT has been used to image various cell types in vivo. It has several advantages over the aforementioned imaging techniques including high sensitivity, it allows non-invasive whole body studies of viable cell migration and localisation of cells over time and lastly it may offer the possibility to be translated to the clinic. This study addresses whether SPECT/CT imaging can be used to visualise the migratory pattern of Tregs in vivo. Treg lines derived from CD4(+CD25(+FoxP3(+ cells were retrovirally transduced with a construct encoding for the human Sodium Iodide Symporter (NIS and the fluorescent protein mCherry and stimulated with autologous DCs. NIS expressing self-specific Tregs were specifically radiolabelled in vitro with Technetium-99m pertechnetate ((99mTcO(4(- and exposure of these cells to radioactivity did not affect cell viability, phenotype or function. In addition adoptively transferred Treg-NIS cells were imaged in vivo in C57BL/6 (BL/6 mice by SPECT/CT using (99mTcO(4(-. After 24 hours NIS expressing Tregs were observed in the spleen and their localisation was further confirmed by organ biodistribution studies and flow cytometry analysis. The data presented here suggests that SPECT/CT imaging can be utilised in preclinical imaging studies of adoptively transferred Tregs without affecting Treg function and viability thereby allowing longitudinal studies within disease models.

  15. A pilot trial assessing urinary gene expression profiling with an mRNA array for diabetic nephropathy.

    Directory of Open Access Journals (Sweden)

    Min Zheng

    Full Text Available BACKGROUND: The initiation and progression of diabetic nephropathy (DN is complex. Quantification of mRNA expression in urinary sediment has emerged as a novel strategy for studying renal diseases. Considering the numerous molecules involved in DN development, a high-throughput platform with parallel detection of multiple mRNAs is needed. In this study, we constructed a self-assembling mRNA array to analyze urinary mRNAs in DN patients with aims to reveal its potential in searching novel biomarkers. METHODS: mRNA array containing 88 genes were fabricated and its performance was evaluated. A pilot study with 9 subjects including 6 DN patients and 3 normal controls were studied with the array. DN patients were assigned into two groups according to their estimate glomerular rate (eGFR: DNI group (eGFR>60 ml/min/1.73 m(2, n = 3 and DNII group (eGFR<60 ml/min/1.73 m(2, n = 3. Urinary cell pellet was collected from each study participant. Relative abundance of these target mRNAs from urinary pellet was quantified with the array. RESULTS: The array we fabricated displayed high sensitivity and specificity. Moreover, the Cts of Positive PCR Controls in our experiments were 24±0.5 which indicated high repeatability of the array. A total of 29 mRNAs were significantly increased in DN patients compared with controls (p<0.05. Among these genes, α-actinin4, CDH2, ACE, FAT1, synaptopodin, COL4α, twist, NOTCH3 mRNA expression were 15-fold higher than those in normal controls. In contrast, urinary TIMP-1 mRNA was significantly decreased in DN patients (p<0.05. It was shown that CTGF, MCP-1, PAI-1, ACE, CDH1, CDH2 mRNA varied significantly among the 3 study groups, and their mRNA levels increased with DN progression (p<0.05. CONCLUSION: Our pilot study demonstrated that mRNA array might serve as a high-throughput and sensitive tool for detecting mRNA expression in urinary sediment. Thus, this primary study indicated that mRNA array probably could be a

  16. Computational design and designability of gene regulatory networks

    OpenAIRE

    Rodrigo Tarrega, Guillermo

    2012-01-01

    Nuestro conocimiento de las interacciones moleculares nos ha conducido hoy hacia una perspectiva ingenieril, donde diseños e implementaciones de sistemas artificiales de regulación intentan proporcionar instrucciones fundamentales para la reprogramación celular. Nosotros aquí abordamos el diseño de redes de genes como una forma de profundizar en la comprensión de las regulaciones naturales. También abordamos el problema de la diseñabilidad dada una genoteca de elementos compatibles. Con este ...

  17. Computational studies of gene regulatory networks: in numero molecular biology.

    Science.gov (United States)

    Hasty, J; McMillen, D; Isaacs, F; Collins, J J

    2001-04-01

    Remarkable progress in genomic research is leading to a complete map of the building blocks of biology. Knowledge of this map is, in turn, setting the stage for a fundamental description of cellular function at the DNA level. Such a description will entail an understanding of gene regulation, in which proteins often regulate their own production or that of other proteins in a complex web of interactions. The implications of the underlying logic of genetic networks are difficult to deduce through experimental techniques alone, and successful approaches will probably involve the union of new experiments and computational modelling techniques.

  18. [Collaborative study on regulatory science for facilitating clinical development of gene therapy products for genetic diseases].

    Science.gov (United States)

    Uchida, Eriko; Igarashi, Yuka; Sato, Yoji

    2014-01-01

    Gene therapy products are expected as innovative medicinal products for intractable diseases such as life-threatening genetic diseases and cancer. Recently, clinical developments by pharmaceutical companies are accelerated in Europe and the United States, and the first gene therapy product in advanced countries was approved for marketing authorization by the European Commission in 2012. On the other hand, more than 40 clinical studies for gene therapy have been completed or ongoing in Japan, most of them are conducted as clinical researches by academic institutes, and few clinical trials have been conducted for approval of gene therapy products. In order to promote the development of gene therapy products, revision of the current guideline and/or preparation of concept paper to address the evaluation of the quality and safety of gene therapy products are necessary and desired to clearly show what data should be submitted before First-in-Human clinical trials of novel gene therapy products. We started collaborative study with academia and regulatory agency to promote regulatory science toward clinical development of gene therapy products for genetic diseases based on lentivirus and adeno-associated virus vectors; National Center for Child Health and Development (NCCHD), Nippon Medical School and PMDA have been joined in the task force. At first, we are preparing pre-draft of the revision of the current gene therapy guidelines in this project.

  19. Cis- and trans-regulatory mechanisms of gene expression in the ASJ sensory neuron of Caenorhabditis elegans

    NARCIS (Netherlands)

    M. González-Barrios (María); J.C. Fierro-González (Juan Carlos); E. Krpelanova (Eva); J.A. Mora-Lorca (José Antonio); J. Rafael Pedrajas (José); X. Peñate (Xenia); S. Chavez (Sebastián); P. Swoboda (Peter); G. Jansen (Gert); A. Miranda-Vizuet (Antonio)

    2015-01-01

    textabstractThe identity of a given cell type is determined by the expression of a set of genes sharing common cis-regulatory motifs and being regulated by shared transcription factors. Here, we identify cis and trans regulatory elements that drive gene expression in the bilateral sensory neuron ASJ

  20. Identification of a cis-regulatory element by transient analysis of co-ordinately regulated genes

    Directory of Open Access Journals (Sweden)

    Allan Andrew C

    2008-07-01

    Full Text Available Abstract Background Transcription factors (TFs co-ordinately regulate target genes that are dispersed throughout the genome. This co-ordinate regulation is achieved, in part, through the interaction of transcription factors with conserved cis-regulatory motifs that are in close proximity to the target genes. While much is known about the families of transcription factors that regulate gene expression in plants, there are few well characterised cis-regulatory motifs. In Arabidopsis, over-expression of the MYB transcription factor PAP1 (PRODUCTION OF ANTHOCYANIN PIGMENT 1 leads to transgenic plants with elevated anthocyanin levels due to the co-ordinated up-regulation of genes in the anthocyanin biosynthetic pathway. In addition to the anthocyanin biosynthetic genes, there are a number of un-associated genes that also change in expression level. This may be a direct or indirect consequence of the over-expression of PAP1. Results Oligo array analysis of PAP1 over-expression Arabidopsis plants identified genes co-ordinately up-regulated in response to the elevated expression of this transcription factor. Transient assays on the promoter regions of 33 of these up-regulated genes identified eight promoter fragments that were transactivated by PAP1. Bioinformatic analysis on these promoters revealed a common cis-regulatory motif that we showed is required for PAP1 dependent transactivation. Conclusion Co-ordinated gene regulation by individual transcription factors is a complex collection of both direct and indirect effects. Transient transactivation assays provide a rapid method to identify direct target genes from indirect target genes. Bioinformatic analysis of the promoters of these direct target genes is able to locate motifs that are common to this sub-set of promoters, which is impossible to identify with the larger set of direct and indirect target genes. While this type of analysis does not prove a direct interaction between protein and DNA

  1. Prevalence of adhesive genes among uropathogenic Escherichia coli strains isolated from patients with urinary tract infection in Mangalore

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    A V Shetty

    2014-01-01

    Full Text Available The study was carried out to detect the adhesive genes pap (pyelonephritis associated pili, sfa (S fimbrial adhesin and afa (afimbrial adhesin from Escherichia coli strains isolated in patients diagnosed with urinary tract infection (UTI. A total of 23% of the isolates were positive for pap, sfa and afa genes with a prevalence of 60.87% (14/23, 39.1% (9/23 and 39.1% (9/23, respectively. Prevalence of multiple adhesive genes was 8.7% (2/23 for pap and afa, 30.43% (7/23 for pap and sfa. Significant numbers of isolates were positive for Congo red binding (80% and haemolysin production 60%. The prevalence of multiple adhesive genes indicate the potential to adhere and subsequently cause a systemic infection among UTI patients.

  2. Reliable transfer of transcriptional gene regulatory networks between taxonomically related organisms

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    Tauch Andreas

    2009-01-01

    Full Text Available Abstract Background Transcriptional regulation of gene activity is essential for any living organism. Transcription factors therefore recognize specific binding sites within the DNA to regulate the expression of particular target genes. The genome-scale reconstruction of the emerging regulatory networks is important for biotechnology and human medicine but cost-intensive, time-consuming, and impossible to perform for any species separately. By using bioinformatics methods one can partially transfer networks from well-studied model organisms to closely related species. However, the prediction quality is limited by the low level of evolutionary conservation of the transcription factor binding sites, even within organisms of the same genus. Results Here we present an integrated bioinformatics workflow that assures the reliability of transferred gene regulatory networks. Our approach combines three methods that can be applied on a large-scale: re-assessment of annotated binding sites, subsequent binding site prediction, and homology detection. A gene regulatory interaction is considered to be conserved if (1 the transcription factor, (2 the adjusted binding site, and (3 the target gene are conserved. The power of the approach is demonstrated by transferring gene regulations from the model organism Corynebacterium glutamicum to the human pathogens C. diphtheriae, C. jeikeium, and the biotechnologically relevant C. efficiens. For these three organisms we identified reliable transcriptional regulations for ~40% of the common transcription factors, compared to ~5% for which knowledge was available before. Conclusion Our results suggest that trustworthy genome-scale transfer of gene regulatory networks between organisms is feasible in general but still limited by the level of evolutionary conservation.

  3. Regulatory gene networks that shape the development of adaptive phenotypic plasticity in a cichlid fish.

    Science.gov (United States)

    Schneider, Ralf F; Li, Yuanhao; Meyer, Axel; Gunter, Helen M

    2014-09-01

    Phenotypic plasticity is the ability of organisms with a given genotype to develop different phenotypes according to environmental stimuli, resulting in individuals that are better adapted to local conditions. In spite of their ecological importance, the developmental regulatory networks underlying plastic phenotypes often remain uncharacterized. We examined the regulatory basis of diet-induced plasticity in the lower pharyngeal jaw (LPJ) of the cichlid fish Astatoreochromis alluaudi, a model species in the study of adaptive plasticity. Through raising juvenile A. alluaudi on either a hard or soft diet (hard-shelled or pulverized snails) for between 1 and 8 months, we gained insight into the temporal regulation of 19 previously identified candidate genes during the early stages of plasticity development. Plasticity in LPJ morphology was first detected between 3 and 5 months of diet treatment. The candidate genes, belonging to various functional categories, displayed dynamic expression patterns that consistently preceded the onset of morphological divergence and putatively contribute to the initiation of the plastic phenotypes. Within functional categories, we observed striking co-expression, and transcription factor binding site analysis was used to examine the prospective basis of their coregulation. We propose a regulatory network of LPJ plasticity in cichlids, presenting evidence for regulatory crosstalk between bone and muscle tissues, which putatively facilitates the development of this highly integrated trait. Through incorporating a developmental time-course into a phenotypic plasticity study, we have identified an interconnected, environmentally responsive regulatory network that shapes the development of plasticity in a key innovation of East African cichlids.

  4. Time delay induced transition of gene switch and stochastic resonance in a genetic transcriptional regulatory model

    Science.gov (United States)

    2012-01-01

    Background Noise, nonlinear interactions, positive and negative feedbacks within signaling pathways, time delays, protein oligomerization, and crosstalk between different pathways are main characters in the regulatory of gene expression. However, only a single noise source or only delay time in the deterministic model is considered in the gene transcriptional regulatory system in previous researches. The combined effects of correlated noise and time delays on the gene regulatory model still remain not to be fully understood. Results The roles of time delay on gene switch and stochastic resonance are systematically explored based on a famous gene transcriptional regulatory model subject to correlated noise. Two cases, including linear time delay appearing in the degradation process (case I) and nonlinear time delay appearing in the synthesis process (case II) are considered, respectively. For case I: Our theoretical results show that time delay can induce gene switch, i.e., the TF-A monomer concentration shifts from the high concentration state to the low concentration state ("on"→"off"). With increasing the time delay, the transition from "on" to "off" state can be further accelerated. Moreover, it is found that the stochastic resonance can be enhanced by both the time delay and correlated noise intensity. However, the additive noise original from the synthesis rate restrains the stochastic resonance. It is also very interesting that a resonance bi-peaks structure appears under large additive noise intensity. The theoretical results by using small-delay time-approximation approach are consistent well with our numerical simulation. For case II: Our numerical simulation results show that time delay can also induce the gene switch, however different with case I, the TF-A monomer concentration shifts from the low concentration state to the high concentration state ("off"→"on"). With increasing time delay, the transition from "on" to "off" state can be further

  5. Deconvoluting lung evolution: from phenotypes to gene regulatory networks

    DEFF Research Database (Denmark)

    Torday, J.S.; Rehan, V.K.; Hicks, J.W.

    2007-01-01

    Speakers in this symposium presented examples of respiratory regulation that broadly illustrate principles of evolution from whole organ to genes. The swim bladder and lungs of aquatic and terrestrial organisms arose independently from a common primordial "respiratory pharynx" but not from each...... other. Pathways of lung evolution are similar between crocodiles and birds but a low compliance of mammalian lung may have driven the development of the diaphragm to permit lung inflation during inspiration. To meet the high oxygen demands of flight, bird lungs have evolved separate gas exchange...... diffusing capacities than required by their oxygen consumption. The "primitive" central admixture of oxygenated and deoxygenated blood in the incompletely divided reptilian heart is actually co-regulated with other autonomic cardiopulmonary responses to provide flexible control of arterial oxygen tension...

  6. Specific regulatory motifs predict glucocorticoid responsiveness of hippocampal gene expression.

    Science.gov (United States)

    Datson, N A; Polman, J A E; de Jonge, R T; van Boheemen, P T M; van Maanen, E M T; Welten, J; McEwen, B S; Meiland, H C; Meijer, O C

    2011-10-01

    The glucocorticoid receptor (GR) is an ubiquitously expressed ligand-activated transcription factor that mediates effects of cortisol in relation to adaptation to stress. In the brain, GR affects the hippocampus to modulate memory processes through direct binding to glucocorticoid response elements (GREs) in the DNA. However, its effects are to a high degree cell specific, and its target genes in different cell types as well as the mechanisms conferring this specificity are largely unknown. To gain insight in hippocampal GR signaling, we characterized to which GRE GR binds in the rat hippocampus. Using a position-specific scoring matrix, we identified evolutionary-conserved putative GREs from a microarray based set of hippocampal target genes. Using chromatin immunoprecipitation, we were able to confirm GR binding to 15 out of a selection of 32 predicted sites (47%). The majority of these 15 GREs are previously undescribed and thus represent novel GREs that bind GR and therefore may be functional in the rat hippocampus. GRE nucleotide composition was not predictive for binding of GR to a GRE. A search for conserved flanking sequences that may predict GR-GRE interaction resulted in the identification of GC-box associated motifs, such as Myc-associated zinc finger protein 1, within 2 kb of GREs with GR binding in the hippocampus. This enrichment was not present around nonbinding GRE sequences nor around proven GR-binding sites from a mesenchymal stem-like cell dataset that we analyzed. GC-binding transcription factors therefore may be unique partners for DNA-bound GR and may in part explain cell-specific transcriptional regulation by glucocorticoids in the context of the hippocampus.

  7. Statistical identification of gene association by CID in application of constructing ER regulatory network

    Directory of Open Access Journals (Sweden)

    Lien Huang-Chun

    2009-03-01

    Full Text Available Abstract Background A variety of high-throughput techniques are now available for constructing comprehensive gene regulatory networks in systems biology. In this study, we report a new statistical approach for facilitating in silico inference of regulatory network structure. The new measure of association, coefficient of intrinsic dependence (CID, is model-free and can be applied to both continuous and categorical distributions. When given two variables X and Y, CID answers whether Y is dependent on X by examining the conditional distribution of Y given X. In this paper, we apply CID to analyze the regulatory relationships between transcription factors (TFs (X and their downstream genes (Y based on clinical data. More specifically, we use estrogen receptor α (ERα as the variable X, and the analyses are based on 48 clinical breast cancer gene expression arrays (48A. Results The analytical utility of CID was evaluated in comparison with four commonly used statistical methods, Galton-Pearson's correlation coefficient (GPCC, Student's t-test (STT, coefficient of determination (CoD, and mutual information (MI. When being compared to GPCC, CoD, and MI, CID reveals its preferential ability to discover the regulatory association where distribution of the mRNA expression levels on X and Y does not fit linear models. On the other hand, when CID is used to measure the association of a continuous variable (Y against a discrete variable (X, it shows similar performance as compared to STT, and appears to outperform CoD and MI. In addition, this study established a two-layer transcriptional regulatory network to exemplify the usage of CID, in combination with GPCC, in deciphering gene networks based on gene expression profiles from patient arrays. Conclusion CID is shown to provide useful information for identifying associations between genes and transcription factors of interest in patient arrays. When coupled with the relationships detected by GPCC, the

  8. Statistical identification of gene association by CID in application of constructing ER regulatory network.

    Science.gov (United States)

    Liu, Li-Yu D; Chen, Chien-Yu; Chen, Mei-Ju M; Tsai, Ming-Shian; Lee, Cho-Han S; Phang, Tzu L; Chang, Li-Yun; Kuo, Wen-Hung; Hwa, Hsiao-Lin; Lien, Huang-Chun; Jung, Shih-Ming; Lin, Yi-Shing; Chang, King-Jen; Hsieh, Fon-Jou

    2009-03-17

    A variety of high-throughput techniques are now available for constructing comprehensive gene regulatory networks in systems biology. In this study, we report a new statistical approach for facilitating in silico inference of regulatory network structure. The new measure of association, coefficient of intrinsic dependence (CID), is model-free and can be applied to both continuous and categorical distributions. When given two variables X and Y, CID answers whether Y is dependent on X by examining the conditional distribution of Y given X. In this paper, we apply CID to analyze the regulatory relationships between transcription factors (TFs) (X) and their downstream genes (Y) based on clinical data. More specifically, we use estrogen receptor alpha (ERalpha) as the variable X, and the analyses are based on 48 clinical breast cancer gene expression arrays (48A). The analytical utility of CID was evaluated in comparison with four commonly used statistical methods, Galton-Pearson's correlation coefficient (GPCC), Student's t-test (STT), coefficient of determination (CoD), and mutual information (MI). When being compared to GPCC, CoD, and MI, CID reveals its preferential ability to discover the regulatory association where distribution of the mRNA expression levels on X and Y does not fit linear models. On the other hand, when CID is used to measure the association of a continuous variable (Y) against a discrete variable (X), it shows similar performance as compared to STT, and appears to outperform CoD and MI. In addition, this study established a two-layer transcriptional regulatory network to exemplify the usage of CID, in combination with GPCC, in deciphering gene networks based on gene expression profiles from patient arrays. CID is shown to provide useful information for identifying associations between genes and transcription factors of interest in patient arrays. When coupled with the relationships detected by GPCC, the association predicted by CID are applicable

  9. Potential transcriptional regulatory regions exist upstream of the human ezrin gene promoter in esophageal carcinoma cells

    Institute of Scientific and Technical Information of China (English)

    Shuying Gao; Yanpeng Dai; Meijun Yin; Jing Ye; Gang Li; Jie Yu

    2011-01-01

    We previously demonstrated that the region -87/+ 134 of the human ezrin gene (VIL2) exhibited promoter activity in human esophageal carcinoma EC109 cells, and a further upstream region -1324/-890 positively regulated transcription.In this study, to identify the transcriptional regulatory regions upstream of the VIL2 promoter, we cloned VIL2 - 1541/- 706 segment containing the -1324/-890, and investigated its transcriptional regulatory properties via luciferase assays in transiently transfected cells.In EC109 cells, it was found that VIL2 -1541/-706 possessed promoter and enhancer activities.We also localized transcriptional regulatory regions by fusing 5′- or 3′-deletion segments of VIL2 -1541/-706 to a luciferase reporter.We found that there were three positive and one negative transcriptional regulatory regions ithin VIL2 -1541/-706 in EC109 cells.When these regions were separately located upstream of the luciferase gene without promoter, or located upstream of the VIL2 promoter or SV40 promoter directing the luciferase gene, only VIL2 -1297/-1186 exhibited considerable promoter and enhancer activities, which were lower than those of -1541/-706.In addition, transient expression of Sp1 increased ezrin expression and the transcriptional activation of VIL2 -1297/-1186.Other three regions,although exhibiting significantly positive or negative transcriptional regulation in deletion experiments, showed a weaker or absent regulation.These data suggested that more than one region upstream of the VIL2 promoter participated in VIL2 transcription, and the VIL2 -1297/-1186, probably as a key transcriptional regulatory region, regulated VIL2 transcription in company with other potential regulatory regions.

  10. Using Xenopus Embryos to Study Transcriptional and Posttranscriptional Gene Regulatory Mechanisms of Intermediate Filaments.

    Science.gov (United States)

    Wang, Chen; Szaro, Ben G

    2016-01-01

    Intermediate filament genes exhibit highly regulated, tissue-specific patterns of expression during development and in response to injury. Identifying the responsible cis-regulatory gene elements thus holds great promise for revealing insights into fundamental gene regulatory mechanisms controlling tissue differentiation and repair. Because much of this regulation occurs in response to signals from surrounding cells, characterizing them requires a model system in which their activity can be tested within the context of an intact organism conveniently. We describe methods for doing so by injecting plasmid DNAs into fertilized Xenopus embryos. A prokaryotic element for site-specific recombination and two dual HS4 insulator elements flanking the reporter gene promote penetrant, promoter-typic expression that persists through early swimming tadpole stages, permitting the observation of fluorescent reporter protein expression in live embryos. In addition to describing cloning strategies for generating these plasmids, we present methods for coinjecting test and reference plasmids to identify the best embryos for analysis, for analyzing reporter protein and RNA expression, and for characterizing the trafficking of expressed reporter RNAs from the nucleus to polysomes. Thus, this system can be used to study the activities of cis-regulatory elements of intermediate filament genes at multiple levels of transcriptional and posttranscriptional control within an intact vertebrate embryo, from early stages of embryogenesis through later stages of organogenesis and tissue differentiation.

  11. Similarity in gene-regulatory networks suggests that cancer cells share characteristics of embryonic neural cells.

    Science.gov (United States)

    Zhang, Zan; Lei, Anhua; Xu, Liyang; Chen, Lu; Chen, Yonglong; Zhang, Xuena; Gao, Yan; Yang, Xiaoli; Zhang, Min; Cao, Ying

    2017-08-04

    Cancer cells are immature cells resulting from cellular reprogramming by gene misregulation, and redifferentiation is expected to reduce malignancy. It is unclear, however, whether cancer cells can undergo terminal differentiation. Here, we show that inhibition of the epigenetic modification enzyme enhancer of zeste homolog 2 (EZH2), histone deacetylases 1 and 3 (HDAC1 and -3), lysine demethylase 1A (LSD1), or DNA methyltransferase 1 (DNMT1), which all promote cancer development and progression, leads to postmitotic neuron-like differentiation with loss of malignant features in distinct solid cancer cell lines. The regulatory effect of these enzymes in neuronal differentiation resided in their intrinsic activity in embryonic neural precursor/progenitor cells. We further found that a major part of pan-cancer-promoting genes and the signal transducers of the pan-cancer-promoting signaling pathways, including the epithelial-to-mesenchymal transition (EMT) mesenchymal marker genes, display neural specific expression during embryonic neurulation. In contrast, many tumor suppressor genes, including the EMT epithelial marker gene that encodes cadherin 1 (CDH1), exhibited non-neural or no expression. This correlation indicated that cancer cells and embryonic neural cells share a regulatory network, mediating both tumorigenesis and neural development. This observed similarity in regulatory mechanisms suggests that cancer cells might share characteristics of embryonic neural cells. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

  12. Improved reconstruction of in silico gene regulatory networks by integrating knockout and perturbation data.

    Directory of Open Access Journals (Sweden)

    Kevin Y Yip

    Full Text Available We performed computational reconstruction of the in silico gene regulatory networks in the DREAM3 Challenges. Our task was to learn the networks from two types of data, namely gene expression profiles in deletion strains (the 'deletion data' and time series trajectories of gene expression after some initial perturbation (the 'perturbation data'. In the course of developing the prediction method, we observed that the two types of data contained different and complementary information about the underlying network. In particular, deletion data allow for the detection of direct regulatory activities with strong responses upon the deletion of the regulator while perturbation data provide richer information for the identification of weaker and more complex types of regulation. We applied different techniques to learn the regulation from the two types of data. For deletion data, we learned a noise model to distinguish real signals from random fluctuations using an iterative method. For perturbation data, we used differential equations to model the change of expression levels of a gene along the trajectories due to the regulation of other genes. We tried different models, and combined their predictions. The final predictions were obtained by merging the results from the two types of data. A comparison with the actual regulatory networks suggests that our approach is effective for networks with a range of different sizes. The success of the approach demonstrates the importance of integrating heterogeneous data in network reconstruction.

  13. A gene regulatory network for root epidermis cell differentiation in Arabidopsis.

    Directory of Open Access Journals (Sweden)

    Angela Bruex

    2012-01-01

    Full Text Available The root epidermis of Arabidopsis provides an exceptional model for studying the molecular basis of cell fate and differentiation. To obtain a systems-level view of root epidermal cell differentiation, we used a genome-wide transcriptome approach to define and organize a large set of genes into a transcriptional regulatory network. Using cell fate mutants that produce only one of the two epidermal cell types, together with fluorescence-activated cell-sorting to preferentially analyze the root epidermis transcriptome, we identified 1,582 genes differentially expressed in the root-hair or non-hair cell types, including a set of 208 "core" root epidermal genes. The organization of the core genes into a network was accomplished by using 17 distinct root epidermis mutants and 2 hormone treatments to perturb the system and assess the effects on each gene's transcript accumulation. In addition, temporal gene expression information from a developmental time series dataset and predicted gene associations derived from a Bayesian modeling approach were used to aid the positioning of genes within the network. Further, a detailed functional analysis of likely bHLH regulatory genes within the network, including MYC1, bHLH54, bHLH66, and bHLH82, showed that three distinct subfamilies of bHLH proteins participate in root epidermis development in a stage-specific manner. The integration of genetic, genomic, and computational analyses provides a new view of the composition, architecture, and logic of the root epidermal transcriptional network, and it demonstrates the utility of a comprehensive systems approach for dissecting a complex regulatory network.

  14. Adaptive modelling of gene regulatory network using Bayesian information criterion-guided sparse regression approach.

    Science.gov (United States)

    Shi, Ming; Shen, Weiming; Wang, Hong-Qiang; Chong, Yanwen

    2016-12-01

    Inferring gene regulatory networks (GRNs) from microarray expression data are an important but challenging issue in systems biology. In this study, the authors propose a Bayesian information criterion (BIC)-guided sparse regression approach for GRN reconstruction. This approach can adaptively model GRNs by optimising the l1-norm regularisation of sparse regression based on a modified version of BIC. The use of the regularisation strategy ensures the inferred GRNs to be as sparse as natural, while the modified BIC allows incorporating prior knowledge on expression regulation and thus avoids the overestimation of expression regulators as usual. Especially, the proposed method provides a clear interpretation of combinatorial regulations of gene expression by optimally extracting regulation coordination for a given target gene. Experimental results on both simulation data and real-world microarray data demonstrate the competent performance of discovering regulatory relationships in GRN reconstruction.

  15. From System-Wide Differential Gene Expression to Perturbed Regulatory Factors: A Combinatorial Approach.

    Directory of Open Access Journals (Sweden)

    Gaurang Mahajan

    Full Text Available High-throughput experiments such as microarrays and deep sequencing provide large scale information on the pattern of gene expression, which undergoes extensive remodeling as the cell dynamically responds to varying environmental cues or has its function disrupted under pathological conditions. An important initial step in the systematic analysis and interpretation of genome-scale expression alteration involves identification of a set of perturbed transcriptional regulators whose differential activity can provide a proximate hypothesis to account for these transcriptomic changes. In the present work, we propose an unbiased and logically natural approach to transcription factor enrichment. It involves overlaying a list of experimentally determined differentially expressed genes on a background regulatory network coming from e.g. literature curation or computational motif scanning, and identifying that subset of regulators whose aggregated target set best discriminates between the altered and the unaffected genes. In other words, our methodology entails testing of all possible regulatory subnetworks, rather than just the target sets of individual regulators as is followed in most standard approaches. We have proposed an iterative search method to efficiently find such a combination, and benchmarked it on E. coli microarray and regulatory network data available in the public domain. Comparative analysis carried out on artificially generated differential expression profiles, as well as empirical factor overexpression data for M. tuberculosis, shows that our methodology provides marked improvement in accuracy of regulatory inference relative to the standard method that involves evaluating factor enrichment in an individual manner.

  16. From System-Wide Differential Gene Expression to Perturbed Regulatory Factors: A Combinatorial Approach.

    Science.gov (United States)

    Mahajan, Gaurang; Mande, Shekhar C

    2015-01-01

    High-throughput experiments such as microarrays and deep sequencing provide large scale information on the pattern of gene expression, which undergoes extensive remodeling as the cell dynamically responds to varying environmental cues or has its function disrupted under pathological conditions. An important initial step in the systematic analysis and interpretation of genome-scale expression alteration involves identification of a set of perturbed transcriptional regulators whose differential activity can provide a proximate hypothesis to account for these transcriptomic changes. In the present work, we propose an unbiased and logically natural approach to transcription factor enrichment. It involves overlaying a list of experimentally determined differentially expressed genes on a background regulatory network coming from e.g. literature curation or computational motif scanning, and identifying that subset of regulators whose aggregated target set best discriminates between the altered and the unaffected genes. In other words, our methodology entails testing of all possible regulatory subnetworks, rather than just the target sets of individual regulators as is followed in most standard approaches. We have proposed an iterative search method to efficiently find such a combination, and benchmarked it on E. coli microarray and regulatory network data available in the public domain. Comparative analysis carried out on artificially generated differential expression profiles, as well as empirical factor overexpression data for M. tuberculosis, shows that our methodology provides marked improvement in accuracy of regulatory inference relative to the standard method that involves evaluating factor enrichment in an individual manner.

  17. Mutual information and the fidelity of response of gene regulatory models

    Science.gov (United States)

    Tabbaa, Omar P.; Jayaprakash, C.

    2014-08-01

    We investigate cellular response to extracellular signals by using information theory techniques motivated by recent experiments. We present results for the steady state of the following gene regulatory models found in both prokaryotic and eukaryotic cells: a linear transcription-translation model and a positive or negative auto-regulatory model. We calculate both the information capacity and the mutual information exactly for simple models and approximately for the full model. We find that (1) small changes in mutual information can lead to potentially important changes in cellular response and (2) there are diminishing returns in the fidelity of response as the mutual information increases. We calculate the information capacity using Gillespie simulations of a model for the TNF-α-NF-κ B network and find good agreement with the measured value for an experimental realization of this network. Our results provide a quantitative understanding of the differences in cellular response when comparing experimentally measured mutual information values of different gene regulatory models. Our calculations demonstrate that Gillespie simulations can be used to compute the mutual information of more complex gene regulatory models, providing a potentially useful tool in synthetic biology.

  18. Dissection of cis-regulatory elements in the C. elegans Hox gene egl-5 promoter.

    Science.gov (United States)

    Teng, Yingqi; Girard, Lisa; Ferreira, Henrique B; Sternberg, Paul W; Emmons, Scott W

    2004-12-15

    Hox genes are highly conserved segmental identity genes well known for their complex expression patterns and divergent targets. Here we present an analysis of cis-regulatory elements in the Caenorhabditis elegans Hox gene egl-5, which is expressed in multiple tissues in the posterior region of the nematode. We have utilized phylogenetic footprinting to efficiently identify cis-regulatory elements and have characterized these with gfp reporters and tissue-specific rescue experiments. We have found that the complex expression pattern of egl-5 is the cumulative result of the activities of multiple tissue or local region-specific activator sequences that are conserved both in sequence and near-perfect order in the related nematode Caenorhabditis briggsae. Two conserved regulatory blocks analyzed in detail contain multiple sites for both positively and negatively acting factors. One of these regions may promote activation of egl-5 in certain cells via the Wnt pathway. Positively acting regions are repressed in inappropriate tissues by additional negative pathways acting at other sites within the promoter. Our analysis has allowed us to implicate several new regulatory factors significant to the control of egl-5 expression.

  19. Construction of an integrated gene regulatory network link to stress-related immune system in cattle.

    Science.gov (United States)

    Behdani, Elham; Bakhtiarizadeh, Mohammad Reza

    2017-08-20

    The immune system is an important biological system that is negatively impacted by stress. This study constructed an integrated regulatory network to enhance our understanding of the regulatory gene network used in the stress-related immune system. Module inference was used to construct modules of co-expressed genes with bovine leukocyte RNA-Seq data. Transcription factors (TFs) were then assigned to these modules using Lemon-Tree algorithms. In addition, the TFs assigned to each module were confirmed using the promoter analysis and protein-protein interactions data. Therefore, our integrated method identified three TFs which include one TF that is previously known to be involved in immune response (MYBL2) and two TFs (E2F8 and FOXS1) that had not been recognized previously and were identified for the first time in this study as novel regulatory candidates in immune response. This study provides valuable insights on the regulatory programs of genes involved in the stress-related immune system.

  20. Mutual information and the fidelity of response of gene regulatory models.

    Science.gov (United States)

    Tabbaa, Omar P; Jayaprakash, C

    2014-08-01

    We investigate cellular response to extracellular signals by using information theory techniques motivated by recent experiments. We present results for the steady state of the following gene regulatory models found in both prokaryotic and eukaryotic cells: a linear transcription-translation model and a positive or negative auto-regulatory model. We calculate both the information capacity and the mutual information exactly for simple models and approximately for the full model. We find that (1) small changes in mutual information can lead to potentially important changes in cellular response and (2) there are diminishing returns in the fidelity of response as the mutual information increases. We calculate the information capacity using Gillespie simulations of a model for the TNF-α-NF-κB network and find good agreement with the measured value for an experimental realization of this network. Our results provide a quantitative understanding of the differences in cellular response when comparing experimentally measured mutual information values of different gene regulatory models. Our calculations demonstrate that Gillespie simulations can be used to compute the mutual information of more complex gene regulatory models, providing a potentially useful tool in synthetic biology.

  1. Multiple sensors control reciprocal expression of Pseudomonas aeruginosa regulatory RNA and virulence genes

    DEFF Research Database (Denmark)

    Ventre, I.; Goodman, A.L.; Vallet-Gely, I.

    2006-01-01

    S, a hybrid sensor kinase that controls the reciprocal expression of genes for type III secretion and biofilm-promoting polysaccharicles. Domain organization of LadS and the range of LadS-controlled genes suggest that it counteracts the activities of another sensor kinase, RetS. These two pathways converge...... by controlling the transcription of a small regulatory RNA, RsmZ. This work identifies a previously undescribed signal transduction network in which the activities of signal-receiving sensor kinases LadS, RetS, and GacS regulate expression of virulence genes associated with acute or chronic infection...

  2. An integer optimization algorithm for robust identification of non-linear gene regulatory networks

    Directory of Open Access Journals (Sweden)

    Chemmangattuvalappil Nishanth

    2012-09-01

    Full Text Available Abstract Background Reverse engineering gene networks and identifying regulatory interactions are integral to understanding cellular decision making processes. Advancement in high throughput experimental techniques has initiated innovative data driven analysis of gene regulatory networks. However, inherent noise associated with biological systems requires numerous experimental replicates for reliable conclusions. Furthermore, evidence of robust algorithms directly exploiting basic biological traits are few. Such algorithms are expected to be efficient in their performance and robust in their prediction. Results We have developed a network identification algorithm to accurately infer both the topology and strength of regulatory interactions from time series gene expression data in the presence of significant experimental noise and non-linear behavior. In this novel formulism, we have addressed data variability in biological systems by integrating network identification with the bootstrap resampling technique, hence predicting robust interactions from limited experimental replicates subjected to noise. Furthermore, we have incorporated non-linearity in gene dynamics using the S-system formulation. The basic network identification formulation exploits the trait of sparsity of biological interactions. Towards that, the identification algorithm is formulated as an integer-programming problem by introducing binary variables for each network component. The objective function is targeted to minimize the network connections subjected to the constraint of maximal agreement between the experimental and predicted gene dynamics. The developed algorithm is validated using both in silico and experimental data-sets. These studies show that the algorithm can accurately predict the topology and connection strength of the in silico networks, as quantified by high precision and recall, and small discrepancy between the actual and predicted kinetic parameters

  3. Microarray and comparative genomics-based identification of genes and gene regulatory regions of the mouse immune system

    Directory of Open Access Journals (Sweden)

    Katz Jonathan D

    2004-10-01

    Full Text Available Abstract Background In this study we have built and mined a gene expression database composed of 65 diverse mouse tissues for genes preferentially expressed in immune tissues and cell types. Using expression pattern criteria, we identified 360 genes with preferential expression in thymus, spleen, peripheral blood mononuclear cells, lymph nodes (unstimulated or stimulated, or in vitro activated T-cells. Results Gene clusters, formed based on similarity of expression-pattern across either all tissues or the immune tissues only, had highly significant associations both with immunological processes such as chemokine-mediated response, antigen processing, receptor-related signal transduction, and transcriptional regulation, and also with more general processes such as replication and cell cycle control. Within-cluster gene correlations implicated known associations of known genes, as well as immune process-related roles for poorly described genes. To characterize regulatory mechanisms and cis-elements of genes with similar patterns of expression, we used a new version of a comparative genomics-based cis-element analysis tool to identify clusters of cis-elements with compositional similarity among multiple genes. Several clusters contained genes that shared 5–6 cis-elements that included ETS and zinc-finger binding sites. cis-Elements AP2 EGRF ETSF MAZF SP1F ZF5F and AREB ETSF MZF1 PAX5 STAT were shared in a thymus-expressed set; AP4R E2FF EBOX ETSF MAZF SP1F ZF5F and CREB E2FF MAZF PCAT SP1F STAT cis-clusters occurred in activated T-cells; CEBP CREB NFKB SORY and GATA NKXH OCT1 RBIT occurred in stimulated lymph nodes. Conclusion This study demonstrates a series of analytic approaches that have allowed the implication of genes and regulatory elements that participate in the differentiation, maintenance, and function of the immune system. Polymorphism or mutation of these could adversely impact immune system functions.

  4. iRegulon: from a gene list to a gene regulatory network using large motif and track collections.

    Directory of Open Access Journals (Sweden)

    Rekin's Janky

    2014-07-01

    Full Text Available Identifying master regulators of biological processes and mapping their downstream gene networks are key challenges in systems biology. We developed a computational method, called iRegulon, to reverse-engineer the transcriptional regulatory network underlying a co-expressed gene set using cis-regulatory sequence analysis. iRegulon implements a genome-wide ranking-and-recovery approach to detect enriched transcription factor motifs and their optimal sets of direct targets. We increase the accuracy of network inference by using very large motif collections of up to ten thousand position weight matrices collected from various species, and linking these to candidate human TFs via a motif2TF procedure. We validate iRegulon on gene sets derived from ENCODE ChIP-seq data with increasing levels of noise, and we compare iRegulon with existing motif discovery methods. Next, we use iRegulon on more challenging types of gene lists, including microRNA target sets, protein-protein interaction networks, and genetic perturbation data. In particular, we over-activate p53 in breast cancer cells, followed by RNA-seq and ChIP-seq, and could identify an extensive up-regulated network controlled directly by p53. Similarly we map a repressive network with no indication of direct p53 regulation but rather an indirect effect via E2F and NFY. Finally, we generalize our computational framework to include regulatory tracks such as ChIP-seq data and show how motif and track discovery can be combined to map functional regulatory interactions among co-expressed genes. iRegulon is available as a Cytoscape plugin from http://iregulon.aertslab.org.

  5. iRegulon: from a gene list to a gene regulatory network using large motif and track collections.

    Directory of Open Access Journals (Sweden)

    Rekin's Janky

    2014-07-01

    Full Text Available Identifying master regulators of biological processes and mapping their downstream gene networks are key challenges in systems biology. We developed a computational method, called iRegulon, to reverse-engineer the transcriptional regulatory network underlying a co-expressed gene set using cis-regulatory sequence analysis. iRegulon implements a genome-wide ranking-and-recovery approach to detect enriched transcription factor motifs and their optimal sets of direct targets. We increase the accuracy of network inference by using very large motif collections of up to ten thousand position weight matrices collected from various species, and linking these to candidate human TFs via a motif2TF procedure. We validate iRegulon on gene sets derived from ENCODE ChIP-seq data with increasing levels of noise, and we compare iRegulon with existing motif discovery methods. Next, we use iRegulon on more challenging types of gene lists, including microRNA target sets, protein-protein interaction networks, and genetic perturbation data. In particular, we over-activate p53 in breast cancer cells, followed by RNA-seq and ChIP-seq, and could identify an extensive up-regulated network controlled directly by p53. Similarly we map a repressive network with no indication of direct p53 regulation but rather an indirect effect via E2F and NFY. Finally, we generalize our computational framework to include regulatory tracks such as ChIP-seq data and show how motif and track discovery can be combined to map functional regulatory interactions among co-expressed genes. iRegulon is available as a Cytoscape plugin from http://iregulon.aertslab.org.

  6. iRegulon: from a gene list to a gene regulatory network using large motif and track collections.

    Science.gov (United States)

    Janky, Rekin's; Verfaillie, Annelien; Imrichová, Hana; Van de Sande, Bram; Standaert, Laura; Christiaens, Valerie; Hulselmans, Gert; Herten, Koen; Naval Sanchez, Marina; Potier, Delphine; Svetlichnyy, Dmitry; Kalender Atak, Zeynep; Fiers, Mark; Marine, Jean-Christophe; Aerts, Stein

    2014-07-01

    Identifying master regulators of biological processes and mapping their downstream gene networks are key challenges in systems biology. We developed a computational method, called iRegulon, to reverse-engineer the transcriptional regulatory network underlying a co-expressed gene set using cis-regulatory sequence analysis. iRegulon implements a genome-wide ranking-and-recovery approach to detect enriched transcription factor motifs and their optimal sets of direct targets. We increase the accuracy of network inference by using very large motif collections of up to ten thousand position weight matrices collected from various species, and linking these to candidate human TFs via a motif2TF procedure. We validate iRegulon on gene sets derived from ENCODE ChIP-seq data with increasing levels of noise, and we compare iRegulon with existing motif discovery methods. Next, we use iRegulon on more challenging types of gene lists, including microRNA target sets, protein-protein interaction networks, and genetic perturbation data. In particular, we over-activate p53 in breast cancer cells, followed by RNA-seq and ChIP-seq, and could identify an extensive up-regulated network controlled directly by p53. Similarly we map a repressive network with no indication of direct p53 regulation but rather an indirect effect via E2F and NFY. Finally, we generalize our computational framework to include regulatory tracks such as ChIP-seq data and show how motif and track discovery can be combined to map functional regulatory interactions among co-expressed genes. iRegulon is available as a Cytoscape plugin from http://iregulon.aertslab.org.

  7. Negative Regulatory Role of TWIST1 on SNAIL Gene Expression.

    Science.gov (United States)

    Forghanifard, Mohammad Mahdi; Ardalan Khales, Sima; Farshchian, Moein; Rad, Abolfazl; Homayouni-Tabrizi, Masoud; Abbaszadegan, Mohammad Reza

    2017-01-01

    Epithelial-mesenchymal transition (EMT) is crucial for specific morphogenetic movements during embryonic development as well as pathological processes of tumor cell invasion and metastasis. TWIST and SNAIL play vital roles in both developmental and pathological EMT. Our aim in this study was to investigate the functional correlation between TWIST1 and SNAIL in human ESCC cell line (KYSE-30). The packaging cell line GP293T was cotransfected with either control retroviral pruf-IRES-GFP plasmid or pruf-IRES-GFP-hTWIST1 and pGP plasmid. The KYSE-30 ESCC cells were transduced with produced viral particles and examined with inverted fluorescence microscope. DNA was extracted from transduced KYSE-30 cells and analyzed for copy number of integrated retroviral sequences in the target cell genome. The concentration of retroviral particles was determined by Real-time PCR. After RNA extraction and cDNA synthesis, the mRNA expression of TWIST1 and SNAIL was assessed by comparative real-time PCR amplification. Ectopic expression of TWIST1 in KYSE-30, dramatically reduces SNAIL expression. Retroviral transduction enforced TWIST1 overexpression in GFP-hTWIST1 nearly 9 folds in comparison with GFP control cells, and interestingly, this TWIST1 enforced expression caused a - 7 fold decrease of SNAIL mRNA expression in GFP-hTWIST1 compared to GFP control cells. Inverse correlation of TWIST1 and SNAIL mRNA levels may introduce novel molecular gene expression pathway controlling EMT process during ESCC aggressiveness and tumorigenesis. Consequently, these data extend the spectrum of biological activities of TWIST1 and propose that therapeutic repression of TWIST1 may be an effective strategy to inhibit cancer cell invasion and metastasis.

  8. In Vivo Gene Expression Analysis Identifies Genes Required for Enhanced Colonization of the Mouse Urinary Tract by Uropathogenic Escherichia coli Strain CFT073 dsdA▿ †

    OpenAIRE

    Haugen, Brian J.; Pellett, Shahaireen; Redford, Peter; Hamilton, Holly L.; Roesch, Paula L.; Welch, Rodney A.

    2006-01-01

    Deletional inactivation of the gene encoding d-serine deaminase, dsdA, in uropathogenic Escherichia coli strain CFT073 results in a hypermotile strain with a hypercolonization phenotype in the bladder and kidneys of mice in a model of urinary tract infection (UTI). The in vivo gene expression profiles of CFT073 and CFT073 dsdA were compared by isolating RNA directly from the urine of mice challenged with each strain individually. Hybridization of cDNAs derived from these samples to CFT073-spe...

  9. Conservation and diversification of an ancestral chordate gene regulatory network for dorsoventral patterning.

    Directory of Open Access Journals (Sweden)

    Iryna Kozmikova

    Full Text Available Formation of a dorsoventral axis is a key event in the early development of most animal embryos. It is well established that bone morphogenetic proteins (Bmps and Wnts are key mediators of dorsoventral patterning in vertebrates. In the cephalochordate amphioxus, genes encoding Bmps and transcription factors downstream of Bmp signaling such as Vent are expressed in patterns reminiscent of those of their vertebrate orthologues. However, the key question is whether the conservation of expression patterns of network constituents implies conservation of functional network interactions, and if so, how an increased functional complexity can evolve. Using heterologous systems, namely by reporter gene assays in mammalian cell lines and by transgenesis in medaka fish, we have compared the gene regulatory network implicated in dorsoventral patterning of the basal chordate amphioxus and vertebrates. We found that Bmp but not canonical Wnt signaling regulates promoters of genes encoding homeodomain proteins AmphiVent1 and AmphiVent2. Furthermore, AmphiVent1 and AmphiVent2 promoters appear to be correctly regulated in the context of a vertebrate embryo. Finally, we show that AmphiVent1 is able to directly repress promoters of AmphiGoosecoid and AmphiChordin genes. Repression of genes encoding dorsal-specific signaling molecule Chordin and transcription factor Goosecoid by Xenopus and zebrafish Vent genes represents a key regulatory interaction during vertebrate axis formation. Our data indicate high evolutionary conservation of a core Bmp-triggered gene regulatory network for dorsoventral patterning in chordates and suggest that co-option of the canonical Wnt signaling pathway for dorsoventral patterning in vertebrates represents one of the innovations through which an increased morphological complexity of vertebrate embryo is achieved.

  10. Identification of C4 photosynthesis metabolism and regulatory-associated genes in Eleocharis vivipara by SSH.

    Science.gov (United States)

    Chen, Taiyu; Ye, Rongjian; Fan, Xiaolei; Li, Xianghua; Lin, Yongjun

    2011-09-01

    This is the first effort to investigate the candidate genes involved in kranz developmental regulation and C(4) metabolic fluxes in Eleocharis vivipara, which is a leafless freshwater amphibious plant and possesses a distinct culms anatomy structure and photosynthetic pattern in contrasting environments. A terrestrial specific SSH library was constructed to investigate the genes involved in kranz anatomy developmental regulation and C(4) metabolic fluxes. A total of 73 ESTs and 56 unigenes in 384 clones were identified by array hybridization and sequencing. In total, 50 unigenes had homologous genes in the databases of rice and Arabidopsis. The real-time quantitative PCR results showed that most of the genes were accumulated in terrestrial culms and ABA-induced culms. The C(4) marker genes were stably accumulated during the culms development process in terrestrial culms. With respect to C(3) culms, C(4) photosynthesis metabolism consumed much more transporters and translocators related to ion metabolism, organic acids and carbohydrate metabolism, phosphate metabolism, amino acids metabolism, and lipids metabolism. Additionally, ten regulatory genes including five transcription factors, four receptor-like proteins, and one BURP protein were identified. These regulatory genes, which co-accumulated with the culms developmental stages, may play important roles in culms structure developmental regulation, bundle sheath chloroplast maturation, and environmental response. These results shed new light on the C(4) metabolic fluxes, environmental response, and anatomy structure developmental regulation in E. vivipara.

  11. Distribution of the trehalase activation response and the regulatory trehalase gene among yeast species.

    Science.gov (United States)

    Soto, T; Fernández, J; Cansado, J; Vicente, J; Gacto, M

    1997-12-01

    In Saccharomyces cerevisiae and other yeasts the activity of regulatory trehalases increases in response to the addition of glucose and to thermal changes in the extracellular medium. We have performed an screening on the extent of this response among different representative yeast species and the results show that this ability is displayed only by a few members of the Saccharomycetaceae family. However, all yeasts examined contain a gene related to that coding for regulatory trehalase in S. cerevisiae. This finding reveals that the operational distinction between regulatory and nonregulatory trehalase in yeasts is not a property of the enzyme by itself but relays on the expression of accompanying mechanisms able to modulate trehalase activity.

  12. Comparative analysis of the transcription-factor gene regulatory networks of E. coli and S. cerevisiae

    Directory of Open Access Journals (Sweden)

    Santillán Moisés

    2008-01-01

    Full Text Available Abstract Background The regulatory interactions between transcription factors (TF and regulated genes (RG in a species genome can be lumped together in a single directed graph. The TF's and RG's conform the nodes of this graph, while links are drawn whenever a transcription factor regulates a gene's expression. Projections onto TF nodes can be constructed by linking every two nodes regulating a common gene. Similarly, projections onto RG nodes can be made by linking every two regulated genes sharing at least one common regulator. Recent studies of the connectivity pattern in the transcription-factor regulatory network of many organisms have revealed some interesting properties. However, the differences between TF and RG nodes have not been widely explored. Results After analysing the RG and TF projections of the transcription-factor gene regulatory networks of Escherichia coli and Saccharomyces cerevisiae, we found several common characteristic as well as some noticeable differences. To better understand these differences, we compared the properties of the E. coli and S. cerevisiae RG- and TF-projected networks with those of the corresponding projections built from randomized versions of the original bipartite networks. These last results indicate that the observed differences are mostly due to the very different ratios of TF to RG counts of the E. coli and S. cerevisiae bipartite networks, rather than to their having different connectivity patterns. Conclusion Since E. coli is a prokaryotic organism while S. cerevisiae is eukaryotic, there are important differences between them concerning processing of mRNA before translation, DNA packing, amount of junk DNA, and gene regulation. From the results in this paper we conclude that the most important effect such differences have had on the development of the corresponding transcription-factor gene regulatory networks is their very different ratios of TF to RG numbers. This ratio is more than three

  13. Polymorphisms in the WNK1 gene are associated with blood pressure variation and urinary potassium excretion.

    Directory of Open Access Journals (Sweden)

    Stephen Newhouse

    Full Text Available WNK1--a serine/threonine kinase involved in electrolyte homeostasis and blood pressure (BP control--is an excellent candidate gene for essential hypertension (EH. We and others have previously reported association between WNK1 and BP variation. Using tag SNPs (tSNPs that capture 100% of common WNK1 variation in HapMap, we aimed to replicate our findings with BP and to test for association with phenotypes relating to WNK1 function in the British Genetics of Hypertension (BRIGHT study case-control resource (1700 hypertensive cases and 1700 normotensive controls. We found multiple variants to be associated with systolic blood pressure, SBP (7/28 tSNPs min-p = 0.0005, diastolic blood pressure, DBP (7/28 tSNPs min-p = 0.002 and 24 hour urinary potassium excretion (10/28 tSNPs min-p = 0.0004. Associations with SBP and urine potassium remained significant after correction for multiple testing (p = 0.02 and p = 0.01 respectively. The major allele (A of rs765250, located in intron 1, demonstrated the strongest evidence for association with SBP, effect size 3.14 mmHg (95%CI:1.23-4.9, DBP 1.9 mmHg (95%CI:0.7-3.2 and hypertension, odds ratio (OR: 1.3 [95%CI: 1.0-1.7].We genotyped this variant in six independent populations (n = 14,451 and replicated the association between rs765250 and SBP in a meta-analysis (p = 7 x 10(-3, combined with BRIGHT data-set p = 2 x 10(-4, n = 17,851. The associations of WNK1 with DBP and EH were not confirmed. Haplotype analysis revealed striking associations with hypertension and BP variation (global permutation p10 mmHg reduction and risk for hypertension (OR<0.60. Our data indicates that multiple rare and common WNK1 variants contribute to BP variation and hypertension, and provide compelling evidence to initiate further genetic and functional studies to explore the role of WNK1 in BP regulation and EH.

  14. Relation between blaTEM, blaSHV and blaCTX-M genes and acute urinary tract infections

    Institute of Scientific and Technical Information of China (English)

    Sima Sadat Seyedjavadi; Mehdi Goudarzi; Fattaneh Sabzehali

    2016-01-01

    Objective: To survey the frequency of blaTEM, blaSHV and blaCTX-M genotypes in extended-spectrum b-lactamase (ESBL)-producing Escherichia coli (E. coli) isolated from hospitalized patients with urinary tract infection and the determination of their antibiotic resistance patterns. Methods: During 11-month study, 100 ESBL-producing E. coli were collected from 330 patients who met the definition of urinary tract infection. The phenotypic identification of ESBL was confirmed by double disk synergy test and combined disk diffusion test. In vitro, susceptibility to ESBL isolates than 14 antimicrobial agents was performed by Kirby-Bauer disk diffusion method. The frequency of blaTEM, blaSHV and blaCTX-M ESBL-producing E. coli was assessed by PCR method. Results: The frequency of ESBL-producing E. coli was 40.8%. In vitro, susceptibility to ESBL-producing E. coli showed that the majority of isolates were highly susceptible to amikacin (74%) and imipenem (91%). The rates of resistance to other antibiotics varied from 33% to 96%. Through 100 tested isolates, the prevalence of blaTEM, blaSHV and blaCTX-M genes was determined to be 67%, 45% and 74% respectively. In comparison with other bla genes, the frequency of blaCTX-M was strikingly high. Conclusions: Due to the increase of E. coli with multiple ESBL genes, continuous sur-veillance in order to use appropriate antibiotics and the control of infections is necessary.

  15. Comparison of gene regulatory networks of benign and malignant breast cancer samples with normal samples.

    Science.gov (United States)

    Chen, D B; Yang, H J

    2014-11-11

    The aim of this study was to explain the pathogenesis and deterioration process of breast cancer. Breast cancer expression profile data GSE27567 was downloaded from the Gene Expression Omnibus (GEO) database, and breast cancer-related genes were extracted from databases, including Cancer-Resource and Online Mendelian Inheritance In Man (OMIM). Next, h17 transcription factor data were obtained from the University of California, Santa Cruz. Database for Annotation, Visualization, and Integrated Discovery (DAVID)-enrichment analysis was applied and gene-regulatory networks were constructed by double-two-way t-tests in 3 states, including normal, benign, and malignant. Furthermore, network topological properties were compared between 2 states, and breast cancer-related bub genes were ranked according to their different degrees between each of the two states. A total of 2380 breast cancer-related genes and 215 transcription factors were screened by exploring databases; the genes were mainly enriched in their functions, such as cell apoptosis and proliferation, and pathways, such as p53 signaling and apoptosis, which were related with carcinogenesis. In addition, gene-regulatory networks in the 3 conditions were constructed. By comparing their network topological properties, we found that there is a larger transition of differences between malignant and benign breast cancer. Moreover, 8 hub genes (YBX1, ZFP36, YY1, XRCC5, XRCC4, ZFHX3, ZMAT3, and XPC) were identified in the top 10 genes ranked by different degrees. Through comparative analysis of gene-regulation networks, we identified the link between related genes and the pathogenesis of breast cancer. However, further experiments are needed to confirm our results.

  16. Cis-regulatory Mutations in the Caenorhabditis elegans Homeobox Gene Locus cog-1 Affect Neuronal Development

    Science.gov (United States)

    O'Meara, M. Maggie; Bigelow, Henry; Flibotte, Stephane; Etchberger, John F.; Moerman, Donald G.; Hobert, Oliver

    2009-01-01

    We apply here comparative genome hybridization as a novel tool to identify the molecular lesion in two Caenorhabditis elegans mutant strains that affect a neuronal cell fate decision. The phenotype of the mutant strains resembles those of the loss-of-function alleles of the cog-1 homeobox gene, an inducer of the fate of the gustatory neuron ASER. We find that both lesions map to the cis-regulatory control region of cog-1 and affect a phylogenetically conserved binding site for the C2H2 zinc-finger transcription factor CHE-1, a previously known regulator of cog-1 expression in ASER. Identification of this CHE-1-binding site as a critical regulator of cog-1 expression in the ASER in vivo represents one of the rare demonstrations of the in vivo relevance of an experimentally determined or predicted transcription-factor-binding site. Aside from the mutationally defined CHE-1-binding site, cog-1 contains a second, functional CHE-1-binding site, which in isolation is sufficient to drive reporter gene expression in the ASER but in an in vivo context is apparently insufficient for promoting appropriate ASER expression. The cis-regulatory control regions of other ASE-expressed genes also contain ASE motifs that can promote ASE neuron expression when isolated from their genomic context, but appear to depend on multiple ASE motifs in their normal genomic context. The multiplicity of cis-regulatory elements may ensure the robustness of gene expression. PMID:19189954

  17. A Catalog of Regulatory Sequences for Trait Gene for the Genome Editing of Wheat

    Science.gov (United States)

    Makai, Szabolcs; Tamás, László; Juhász, Angéla

    2016-01-01

    Wheat has been cultivated for 10000 years and ever since the origin of hexaploid wheat it has been exempt from natural selection. Instead, it was under the constant selective pressure of human agriculture from harvest to sowing during every year, producing a vast array of varieties. Wheat has been adopted globally, accumulating variation for genes involved in yield traits, environmental adaptation and resistance. However, one small but important part of the wheat genome has hardly changed: the regulatory regions of both the x- and y-type high molecular weight glutenin subunit (HMW-GS) genes, which are alone responsible for approximately 12% of the grain protein content. The phylogeny of the HMW-GS regulatory regions of the Triticeae demonstrates that a genetic bottleneck may have led to its decreased diversity during domestication and the subsequent cultivation. It has also highlighted the fact that the wild relatives of wheat may offer an unexploited genetic resource for the regulatory region of these genes. Significant research efforts have been made in the public sector and by international agencies, using wild crosses to exploit the available genetic variation, and as a result synthetic hexaploids are now being utilized by a number of breeding companies. However, a newly emerging tool of genome editing provides significantly improved efficiency in exploiting the natural variation in HMW-GS genes and incorporating this into elite cultivars and breeding lines. Recent advancement in the understanding of the regulation of these genes underlines the needs for an overview of the regulatory elements for genome editing purposes. PMID:27766102

  18. Genome-wide identification of regulatory elements and reconstruction of gene regulatory networks of the green alga Chlamydomonas reinhardtii under carbon deprivation.

    Directory of Open Access Journals (Sweden)

    Flavia Vischi Winck

    Full Text Available The unicellular green alga Chlamydomonas reinhardtii is a long-established model organism for studies on photosynthesis and carbon metabolism-related physiology. Under conditions of air-level carbon dioxide concentration [CO2], a carbon concentrating mechanism (CCM is induced to facilitate cellular carbon uptake. CCM increases the availability of carbon dioxide at the site of cellular carbon fixation. To improve our understanding of the transcriptional control of the CCM, we employed FAIRE-seq (formaldehyde-assisted Isolation of Regulatory Elements, followed by deep sequencing to determine nucleosome-depleted chromatin regions of algal cells subjected to carbon deprivation. Our FAIRE data recapitulated the positions of known regulatory elements in the promoter of the periplasmic carbonic anhydrase (Cah1 gene, which is upregulated during CCM induction, and revealed new candidate regulatory elements at a genome-wide scale. In addition, time series expression patterns of 130 transcription factor (TF and transcription regulator (TR genes were obtained for cells cultured under photoautotrophic condition and subjected to a shift from high to low [CO2]. Groups of co-expressed genes were identified and a putative directed gene-regulatory network underlying the CCM was reconstructed from the gene expression data using the recently developed IOTA (inner composition alignment method. Among the candidate regulatory genes, two members of the MYB-related TF family, Lcr1 (Low-CO 2 response regulator 1 and Lcr2 (Low-CO2 response regulator 2, may play an important role in down-regulating the expression of a particular set of TF and TR genes in response to low [CO2]. The results obtained provide new insights into the transcriptional control of the CCM and revealed more than 60 new candidate regulatory genes. Deep sequencing of nucleosome-depleted genomic regions indicated the presence of new, previously unknown regulatory elements in the C. reinhardtii genome

  19. A consensus network of gene regulatory factors in the human frontal lobe

    Directory of Open Access Journals (Sweden)

    Stefano eBerto

    2016-03-01

    Full Text Available Cognitive abilities, such as memory, learning, language, problem solving, and planning, involve the frontal lobe and other brain areas. Not much is known yet about the molecular basis of cognitive abilities, but it seems clear that cognitive abilities are determined by the interplay of many genes. One approach for analyzing the genetic networks involved in cognitive functions is to study the coexpression networks of genes with known importance for proper cognitive functions, such as genes that have been associated with cognitive disorders like intellectual disability (ID or autism spectrum disorders (ASD. Because many of these genes are gene regulatory factors (GRFs we aimed to provide insights into the gene regulatory networks active in the human frontal lobe. Using genome wide human frontal lobe expression data from 10 independent data sets, we first derived 10 individual coexpression networks for all GRFs including their potential target genes. We observed a high level of variability among these 10 independently derived networks, pointing out that relying on results from a single study can only provide limited biological insights. To instead focus on the most confident information from these 10 networks we developed a method for integrating such independently derived networks into a consensus network. This consensus network revealed robust GRF interactions that are conserved across the frontal lobes of different healthy human individuals. Within this network, we detected a strong central module that is enriched for 166 GRFs known to be involved in brain development and/or cognitive disorders. Interestingly, several hubs of the consensus network encode for GRFs that have not yet been associated with brain functions. Their central role in the network suggests them as excellent new candidates for playing an essential role in the regulatory network of the human frontal lobe, which should be investigated in future studies.

  20. A Consensus Network of Gene Regulatory Factors in the Human Frontal Lobe.

    Science.gov (United States)

    Berto, Stefano; Perdomo-Sabogal, Alvaro; Gerighausen, Daniel; Qin, Jing; Nowick, Katja

    2016-01-01

    Cognitive abilities, such as memory, learning, language, problem solving, and planning, involve the frontal lobe and other brain areas. Not much is known yet about the molecular basis of cognitive abilities, but it seems clear that cognitive abilities are determined by the interplay of many genes. One approach for analyzing the genetic networks involved in cognitive functions is to study the coexpression networks of genes with known importance for proper cognitive functions, such as genes that have been associated with cognitive disorders like intellectual disability (ID) or autism spectrum disorders (ASD). Because many of these genes are gene regulatory factors (GRFs) we aimed to provide insights into the gene regulatory networks active in the human frontal lobe. Using genome wide human frontal lobe expression data from 10 independent data sets, we first derived 10 individual coexpression networks for all GRFs including their potential target genes. We observed a high level of variability among these 10 independently derived networks, pointing out that relying on results from a single study can only provide limited biological insights. To instead focus on the most confident information from these 10 networks we developed a method for integrating such independently derived networks into a consensus network. This consensus network revealed robust GRF interactions that are conserved across the frontal lobes of different healthy human individuals. Within this network, we detected a strong central module that is enriched for 166 GRFs known to be involved in brain development and/or cognitive disorders. Interestingly, several hubs of the consensus network encode for GRFs that have not yet been associated with brain functions. Their central role in the network suggests them as excellent new candidates for playing an essential role in the regulatory network of the human frontal lobe, which should be investigated in future studies.

  1. Regulatory network analysis of microRNAs and genes in imatinib-resistant chronic myeloid leukemia.

    Science.gov (United States)

    Soltani, Ismael; Gharbi, Hanen; Hassine, Islem Ben; Bouguerra, Ghada; Douzi, Kais; Teber, Mouheb; Abbes, Salem; Menif, Samia

    2016-09-16

    Targeted therapy in the form of selective breakpoint cluster region-abelson (BCR/ABL) tyrosine kinase inhibitor (imatinib mesylate) has successfully been introduced in the treatment of the chronic myeloid leukemia (CML). However, acquired resistance against imatinib mesylate (IM) has been reported in nearly half of patients and has been recognized as major issue in clinical practice. Multiple resistance genes and microRNAs (miRNAs) are thought to be involved in the IM resistance process. These resistance genes and miRNAs tend to interact with each other through a regulatory network. Therefore, it is crucial to study the impact of these interactions in the IM resistance process. The present study focused on miRNA and gene network analysis in order to elucidate the role of interacting elements and to understand their functional contribution in therapeutic failure. Unlike previous studies which were centered only on genes or miRNAs, the prime focus of the present study was on relationships. To this end, three regulatory networks including differentially expressed, related, and global networks were constructed and analyzed in search of similarities and differences. Regulatory associations between miRNAs and their target genes, transcription factors and miRNAs, as well as miRNAs and their host genes were also macroscopically investigated. Certain key pathways in the three networks, especially in the differentially expressed network, were featured. The differentially expressed network emerged as a fault map of IM-resistant CML. Theoretically, the IM resistance process could be prevented by correcting the included errors. The present network-based approach to study resistance miRNAs and genes might help in understanding the molecular mechanisms of IM resistance in CML as well as in the improvement of CML therapy.

  2. A scalable algorithm for structure identification of complex gene regulatory network from temporal expression data.

    Science.gov (United States)

    Gui, Shupeng; Rice, Andrew P; Chen, Rui; Wu, Liang; Liu, Ji; Miao, Hongyu

    2017-01-31

    Gene regulatory interactions are of fundamental importance to various biological functions and processes. However, only a few previous computational studies have claimed success in revealing genome-wide regulatory landscapes from temporal gene expression data, especially for complex eukaryotes like human. Moreover, recent work suggests that these methods still suffer from the curse of dimensionality if a network size increases to 100 or higher. Here we present a novel scalable algorithm for identifying genome-wide gene regulatory network (GRN) structures, and we have verified the algorithm performances by extensive simulation studies based on the DREAM challenge benchmark data. The highlight of our method is that its superior performance does not degenerate even for a network size on the order of 10(4), and is thus readily applicable to large-scale complex networks. Such a breakthrough is achieved by considering both prior biological knowledge and multiple topological properties (i.e., sparsity and hub gene structure) of complex networks in the regularized formulation. We also validate and illustrate the application of our algorithm in practice using the time-course gene expression data from a study on human respiratory epithelial cells in response to influenza A virus (IAV) infection, as well as the CHIP-seq data from ENCODE on transcription factor (TF) and target gene interactions. An interesting finding, owing to the proposed algorithm, is that the biggest hub structures (e.g., top ten) in the GRN all center at some transcription factors in the context of epithelial cell infection by IAV. The proposed algorithm is the first scalable method for large complex network structure identification. The GRN structure identified by our algorithm could reveal possible biological links and help researchers to choose which gene functions to investigate in a biological event. The algorithm described in this article is implemented in MATLAB (Ⓡ) , and the source code is

  3. Correlating overrepresented upstream motifs to gene expression a computational approach to regulatory element discovery in eukaryotes

    CERN Document Server

    Caselle, M; Provero, P

    2002-01-01

    Gene regulation in eukaryotes is mainly effected through transcription factors binding to rather short recognition motifs generally located upstream of the coding region. We present a novel computational method to identify regulatory elements in the upstream region of eukaryotic genes. The genes are grouped in sets sharing an overrepresented short motif in their upstream sequence. For each set, the average expression level from a microarray experiment is determined: If this level is significantly higher or lower than the average taken over the whole genome, then the overerpresented motif shared by the genes in the set is likely to play a role in their regulation. The method was tested by applying it to the genome of Saccharomyces cerevisiae, using the publicly available results of a DNA microarray experiment, in which expression levels for virtually all the genes were measured during the diauxic shift from fermentation to respiration. Several known motifs were correctly identified, and a new candidate regulat...

  4. Evolutionary rewiring: a modified prokaryotic gene-regulatory pathway in chloroplasts.

    Science.gov (United States)

    Puthiyaveetil, Sujith; Ibrahim, Iskander M; Allen, John F

    2013-07-19

    Photosynthetic electron transport regulates chloroplast gene transcription through the action of a bacterial-type sensor kinase known as chloroplast sensor kinase (CSK). CSK represses photosystem I (PS I) gene transcription in PS I light and thus initiates photosystem stoichiometry adjustment. In cyanobacteria and in non-green algae, CSK homologues co-exist with their response regulator partners in canonical bacterial two-component systems. In green algae and plants, however, no response regulator partner of CSK is found. Yeast two-hybrid analysis has revealed interaction of CSK with sigma factor 1 (SIG1) of chloroplast RNA polymerase. Here we present further evidence for the interaction between CSK and SIG1. We also show that CSK interacts with quinone. Arabidopsis SIG1 becomes phosphorylated in PS I light, which then specifically represses transcription of PS I genes. In view of the identical signalling properties of CSK and SIG1 and of their interactions, we suggest that CSK is a SIG1 kinase. We propose that the selective repression of PS I genes arises from the operation of a gene-regulatory phosphoswitch in SIG1. The CSK-SIG1 system represents a novel, rewired chloroplast-signalling pathway created by evolutionary tinkering. This regulatory system supports a proposal for the selection pressure behind the evolutionary stasis of chloroplast genes.

  5. Reverse Engineering Sparse Gene Regulatory Networks Using Cubature Kalman Filter and Compressed Sensing

    Directory of Open Access Journals (Sweden)

    Amina Noor

    2013-01-01

    Full Text Available This paper proposes a novel algorithm for inferring gene regulatory networks which makes use of cubature Kalman filter (CKF and Kalman filter (KF techniques in conjunction with compressed sensing methods. The gene network is described using a state-space model. A nonlinear model for the evolution of gene expression is considered, while the gene expression data is assumed to follow a linear Gaussian model. The hidden states are estimated using CKF. The system parameters are modeled as a Gauss-Markov process and are estimated using compressed sensing-based KF. These parameters provide insight into the regulatory relations among the genes. The Cramér-Rao lower bound of the parameter estimates is calculated for the system model and used as a benchmark to assess the estimation accuracy. The proposed algorithm is evaluated rigorously using synthetic data in different scenarios which include different number of genes and varying number of sample points. In addition, the algorithm is tested on the DREAM4 in silico data sets as well as the in vivo data sets from IRMA network. The proposed algorithm shows superior performance in terms of accuracy, robustness, and scalability.

  6. Optimal Control of Gene Regulatory Networks with Effectiveness of Multiple Drugs: A Boolean Network Approach

    Science.gov (United States)

    Kobayashi, Koichi; Hiraishi, Kunihiko

    2013-01-01

    Developing control theory of gene regulatory networks is one of the significant topics in the field of systems biology, and it is expected to apply the obtained results to gene therapy technologies in the future. In this paper, a control method using a Boolean network (BN) is studied. A BN is widely used as a model of gene regulatory networks, and gene expression is expressed by a binary value (0 or 1). In the control problem, we assume that the concentration level of a part of genes is arbitrarily determined as the control input. However, there are cases that no gene satisfying this assumption exists, and it is important to consider structural control via external stimuli. Furthermore, these controls are realized by multiple drugs, and it is also important to consider multiple effects such as duration of effect and side effects. In this paper, we propose a BN model with two types of the control inputs and an optimal control method with duration of drug effectiveness. First, a BN model and duration of drug effectiveness are discussed. Next, the optimal control problem is formulated and is reduced to an integer linear programming problem. Finally, numerical simulations are shown. PMID:24058904

  7. Positional bias of general and tissue-specific regulatory motifs in mouse gene promoters

    Directory of Open Access Journals (Sweden)

    Farré Domènec

    2007-12-01

    Full Text Available Abstract Background The arrangement of regulatory motifs in gene promoters, or promoter architecture, is the result of mutation and selection processes that have operated over many millions of years. In mammals, tissue-specific transcriptional regulation is related to the presence of specific protein-interacting DNA motifs in gene promoters. However, little is known about the relative location and spacing of these motifs. To fill this gap, we have performed a systematic search for motifs that show significant bias at specific promoter locations in a large collection of housekeeping and tissue-specific genes. Results We observe that promoters driving housekeeping gene expression are enriched in particular motifs with strong positional bias, such as YY1, which are of little relevance in promoters driving tissue-specific expression. We also identify a large number of motifs that show positional bias in genes expressed in a highly tissue-specific manner. They include well-known tissue-specific motifs, such as HNF1 and HNF4 motifs in liver, kidney and small intestine, or RFX motifs in testis, as well as many potentially novel regulatory motifs. Based on this analysis, we provide predictions for 559 tissue-specific motifs in mouse gene promoters. Conclusion The study shows that motif positional bias is an important feature of mammalian proximal promoters and that it affects both general and tissue-specific motifs. Motif positional constraints define very distinct promoter architectures depending on breadth of expression and type of tissue.

  8. Partitioning of genetic variation between regulatory and coding gene segments: the predominance of software variation in genes encoding introvert proteins.

    Science.gov (United States)

    Mitchison, A

    1997-01-01

    In considering genetic variation in eukaryotes, a fundamental distinction can be made between variation in regulatory (software) and coding (hardware) gene segments. For quantitative traits the bulk of variation, particularly that near the population mean, appears to reside in regulatory segments. The main exceptions to this rule concern proteins which handle extrinsic substances, here termed extrovert proteins. The immune system includes an unusually large proportion of this exceptional category, but even so its chief source of variation may well be polymorphism in regulatory gene segments. The main evidence for this view emerges from genome scanning for quantitative trait loci (QTL), which in the case of the immune system points to a major contribution of pro-inflammatory cytokine genes. Further support comes from sequencing of major histocompatibility complex (Mhc) class II promoters, where a high level of polymorphism has been detected. These Mhc promoters appear to act, in part at least, by gating the back-signal from T cells into antigen-presenting cells. Both these forms of polymorphism are likely to be sustained by the need for flexibility in the immune response. Future work on promoter polymorphism is likely to benefit from the input from genome informatics.

  9. Study of the association between the BMP4 gene and congenital anomalies of the kidney and urinary tract

    Directory of Open Access Journals (Sweden)

    Geisilaine Soares dos Reis

    2014-01-01

    Full Text Available OBJECTIVE: To determine the frequency of different phenotypes for congenital anomalies of the kidney and urinary tract (CAKUT in a Brazilian sample, and to evaluate the association between the CAKUT phenotypes and the BMP4 gene. METHODS: In this study, 457 Brazilian individuals were analyzed in an attempt to establish the association between the BMP4 gene and the CAKUT diagnosis. A case-control sample was genotyped for three BMP4 gene polymorphisms. RESULTS: Association data was established with CAKUT sample as a whole and with the three most important CAKUT phenotypes: multicystic dysplastic kidney disease (MDK, ureteropelvic junction obstruction (UPJO and vesicoureteral reflux (VUR. When the sample was segregated in these three phenotypes, associations between the BMP4 gene were observed with UPJO and with MDK. Conversely, VUR was not associated to the polymorphisms of the BMP4 gene. CONCLUSIONS: The present data suggest that Brazilian individuals with polymorphisms of the BMP4 gene have a higher risk to develop CAKUT, especially the malformations related to nephrogenesis and initial branching such as MDK and UPJO. Conversely, VUR appeared not to be related to BMP4 gene.

  10. Inference of gene regulatory networks with the strong-inhibition Boolean model

    Energy Technology Data Exchange (ETDEWEB)

    Xia Qinzhi; Liu Lulu; Ye Weiming; Hu Gang, E-mail: ganghu@bnu.edu.cn [Department of Physics, Beijing Normal University, Beijing 100875 (China)

    2011-08-15

    The inference of gene regulatory networks (GRNs) is an important topic in biology. In this paper, a logic-based algorithm that infers the strong-inhibition Boolean genetic regulatory networks (where regulation by any single repressor can definitely suppress the expression of the gene regulated) from time series is discussed. By properly ordering various computation steps, we derive for the first time explicit formulae for the probabilities at which different interactions can be inferred given a certain number of data. With the formulae, we can predict the precision of reconstructions of regulation networks when the data are insufficient. Numerical simulations coincide well with the analytical results. The method and results are expected to be applicable to a wide range of general dynamic networks, where logic algorithms play essential roles in the network dynamics and the probabilities of various logics can be estimated well.

  11. Information theory in systems biology. Part I: Gene regulatory and metabolic networks.

    Science.gov (United States)

    Mousavian, Zaynab; Kavousi, Kaveh; Masoudi-Nejad, Ali

    2016-03-01

    "A Mathematical Theory of Communication", was published in 1948 by Claude Shannon to establish a framework that is now known as information theory. In recent decades, information theory has gained much attention in the area of systems biology. The aim of this paper is to provide a systematic review of those contributions that have applied information theory in inferring or understanding of biological systems. Based on the type of system components and the interactions between them, we classify the biological systems into 4 main classes: gene regulatory, metabolic, protein-protein interaction and signaling networks. In the first part of this review, we attempt to introduce most of the existing studies on two types of biological networks, including gene regulatory and metabolic networks, which are founded on the concepts of information theory. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Regulatory divergence of X-linked genes and hybrid male sterility in mice.

    Science.gov (United States)

    Oka, Ayako; Shiroishi, Toshihiko

    2014-01-01

    Postzygotic reproductive isolation is the reduction of fertility or viability in hybrids between genetically diverged populations. One example of reproductive isolation, hybrid male sterility, may be caused by genetic incompatibility between diverged genetic factors in two distinct populations. Genetic factors involved in hybrid male sterility are disproportionately located on the X chromosome. Recent studies showing the evolutionary divergence in gene regulatory networks or epigenetic effects suggest that the genetic incompatibilities occur at much broader levels than had previously been thought (e.g., incompatibility of protein-protein interactions). The latest studies suggest that evolutionary divergence of transcriptional regulation causes genetic incompatibilities in hybrid animals, and that such incompatibilities preferentially involve X-linked genes. In this review, we focus on recent progress in understanding hybrid sterility in mice, including our studies, and we discuss the evolutionary significance of regulatory divergence for speciation.

  13. Increasing galactose consumption by Saccharomyces cerevisiae through metabolic engineering of the GAL gene regulatory network

    DEFF Research Database (Denmark)

    Østergaard, Simon; Olsson, Lisbeth; Johnston, M.

    2000-01-01

    in the pathway, and ultimately, increasing metabolic flux through the pathway of interest, By manipulating the GAL gene regulatory network of Saccharomyces cerevisiae, which is a tightly regulated system, we produced prototroph mutant strains, which increased the flux through the galactose utilization pathway...... media. The improved galactose consumption of the gal mutants did not favor biomass formation, but rather caused excessive respiro-fermentative metabolism, with the ethanol production rate increasing linearly with glycolytic flux....

  14. PyPanda: a Python package for gene regulatory network reconstruction

    OpenAIRE

    van IJzendoorn, David G. P.; Glass, Kimberly; Quackenbush, John; Kuijjer, Marieke L

    2016-01-01

    Summary: PANDA (Passing Attributes between Networks for Data Assimilation) is a gene regulatory network inference method that uses message-passing to integrate multiple sources of ‘omics data. PANDA was originally coded in C ++. In this application note we describe PyPanda, the Python version of PANDA. PyPanda runs considerably faster than the C ++ version and includes additional features for network analysis. Availability and implementation: The open source PyPanda Python package is freely a...

  15. Interferon regulatory factor 1 is required for mouse Gbp gene activation by gamma interferon.

    OpenAIRE

    1995-01-01

    Full-scale transcriptional activation of the mouse Gbp genes by gamma interferon (IFN-gamma) requires protein synthesis in embryonic fibroblasts. Although the Gbp-1 and Gbp-2 promoters contain binding sites for transcription factors Stat1 and IFN regulatory factor 1 (IRF-1), deletion analysis revealed that the Stat1 binding site is dispensable for IFN-gamma inducibility of Gbp promoter constructs in transfected fibroblasts. However, activation of the mouse Gbp promoter by IFN-gamma requires t...

  16. Methods for Characterizing the Epigenetic Attractors Landscape Associated with Boolean Gene Regulatory Networks

    OpenAIRE

    Davila-Velderrain, Jose; Juarez-Ramiro, Luis; Martinez-Garcia, Juan C.; Alvarez-Buylla, Elena R

    2015-01-01

    Gene regulatory network (GRN) modeling is a well-established theoretical framework for the study of cell-fate specification during developmental processes. Recently, dynamical models of GRNs have been taken as a basis for formalizing the metaphorical model of Waddington's epigenetic landscape, providing a natural extension for the general protocol of GRN modeling. In this contribution we present in a coherent framework a novel implementation of two previously proposed general frameworks for m...

  17. Fanconi anemia core complex gene promoters harbor conserved transcription regulatory elements.

    Directory of Open Access Journals (Sweden)

    Daniel Meier

    Full Text Available The Fanconi anemia (FA gene family is a recent addition to the complex network of proteins that respond to and repair certain types of DNA damage in the human genome. Since little is known about the regulation of this novel group of genes at the DNA level, we characterized the promoters of the eight genes (FANCA, B, C, E, F, G, L and M that compose the FA core complex. The promoters of these genes show the characteristic attributes of housekeeping genes, such as a high GC content and CpG islands, a lack of TATA boxes and a low conservation. The promoters functioned in a monodirectional way and were, in their most active regions, comparable in strength to the SV40 promoter in our reporter plasmids. They were also marked by a distinctive transcriptional start site (TSS. In the 5' region of each promoter, we identified a region that was able to negatively regulate the promoter activity in HeLa and HEK 293 cells in isolation. The central and 3' regions of the promoter sequences harbor binding sites for several common and rare transcription factors, including STAT, SMAD, E2F, AP1 and YY1, which indicates that there may be cross-connections to several established regulatory pathways. Electrophoretic mobility shift assays and siRNA experiments confirmed the shared regulatory responses between the prominent members of the TGF-β and JAK/STAT pathways and members of the FA core complex. Although the promoters are not well conserved, they share region and sequence specific regulatory motifs and transcription factor binding sites (TBFs, and we identified a bi-partite nature to these promoters. These results support a hypothesis based on the co-evolution of the FA core complex genes that was expanded to include their promoters.

  18. Redeployment of a conserved gene regulatory network during Aedes aegypti development.

    Science.gov (United States)

    Suryamohan, Kushal; Hanson, Casey; Andrews, Emily; Sinha, Saurabh; Scheel, Molly Duman; Halfon, Marc S

    2016-08-15

    Changes in gene regulatory networks (GRNs) underlie the evolution of morphological novelty and developmental system drift. The fruitfly Drosophila melanogaster and the dengue and Zika vector mosquito Aedes aegypti have substantially similar nervous system morphology. Nevertheless, they show significant divergence in a set of genes co-expressed in the midline of the Drosophila central nervous system, including the master regulator single minded and downstream genes including short gastrulation, Star, and NetrinA. In contrast to Drosophila, we find that midline expression of these genes is either absent or severely diminished in A. aegypti. Instead, they are co-expressed in the lateral nervous system. This suggests that in A. aegypti this "midline GRN" has been redeployed to a new location while lost from its previous site of activity. In order to characterize the relevant GRNs, we employed the SCRMshaw method we previously developed to identify transcriptional cis-regulatory modules in both species. Analysis of these regulatory sequences in transgenic Drosophila suggests that the altered gene expression observed in A. aegypti is the result of trans-dependent redeployment of the GRN, potentially stemming from cis-mediated changes in the expression of sim and other as-yet unidentified regulators. Our results illustrate a novel "repeal, replace, and redeploy" mode of evolution in which a conserved GRN acquires a different function at a new site while its original function is co-opted by a different GRN. This represents a striking example of developmental system drift in which the dramatic shift in gene expression does not result in gross morphological changes, but in more subtle differences in development and function of the late embryonic nervous system. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. Detecting functional divergence after gene duplication through evolutionary changes in posttranslational regulatory sequences.

    Science.gov (United States)

    Nguyen Ba, Alex N; Strome, Bob; Hua, Jun Jie; Desmond, Jonathan; Gagnon-Arsenault, Isabelle; Weiss, Eric L; Landry, Christian R; Moses, Alan M

    2014-12-01

    Gene duplication is an important evolutionary mechanism that can result in functional divergence in paralogs due to neo-functionalization or sub-functionalization. Consistent with functional divergence after gene duplication, recent studies have shown accelerated evolution in retained paralogs. However, little is known in general about the impact of this accelerated evolution on the molecular functions of retained paralogs. For example, do new functions typically involve changes in enzymatic activities, or changes in protein regulation? Here we study the evolution of posttranslational regulation by examining the evolution of important regulatory sequences (short linear motifs) in retained duplicates created by the whole-genome duplication in budding yeast. To do so, we identified short linear motifs whose evolutionary constraint has relaxed after gene duplication with a likelihood-ratio test that can account for heterogeneity in the evolutionary process by using a non-central chi-squared null distribution. We find that short linear motifs are more likely to show changes in evolutionary constraints in retained duplicates compared to single-copy genes. We examine changes in constraints on known regulatory sequences and show that for the Rck1/Rck2, Fkh1/Fkh2, Ace2/Swi5 paralogs, they are associated with previously characterized differences in posttranslational regulation. Finally, we experimentally confirm our prediction that for the Ace2/Swi5 paralogs, Cbk1 regulated localization was lost along the lineage leading to SWI5 after gene duplication. Our analysis suggests that changes in posttranslational regulation mediated by short regulatory motifs systematically contribute to functional divergence after gene duplication.

  20. The Caenorhabditis elegans vulva: a post-embryonic gene regulatory network controlling organogenesis.

    Science.gov (United States)

    Ririe, Ted O; Fernandes, Jolene S; Sternberg, Paul W

    2008-12-23

    The Caenorhabditis elegans vulva is an elegant model for dissecting a gene regulatory network (GRN) that directs postembryonic organogenesis. The mature vulva comprises seven cell types (vulA, vulB1, vulB2, vulC, vulD, vulE, and vulF), each with its own unique pattern of spatial and temporal gene expression. The mechanisms that specify these cell types in a precise spatial pattern are not well understood. Using reverse genetic screens, we identified novel components of the vulval GRN, including nhr-113 in vulA. Several transcription factors (lin-11, lin-29, cog-1, egl-38, and nhr-67) interact with each other and act in concert to regulate target gene expression in the diverse vulval cell types. For example, egl-38 (Pax2/5/8) stabilizes the vulF fate by positively regulating vulF characteristics and by inhibiting characteristics associated with the neighboring vulE cells. nhr-67 and egl-38 regulate cog-1, helping restrict its expression to vulE. Computational approaches have been successfully used to identify functional cis-regulatory motifs in the zmp-1 (zinc metalloproteinase) promoter. These results provide an overview of the regulatory network architecture for each vulval cell type.

  1. Functional dissection of regulatory models using gene expression data of deletion mutants.

    Directory of Open Access Journals (Sweden)

    Jin'e Li

    Full Text Available Genome-wide gene expression profiles accumulate at an alarming rate, how to integrate these expression profiles generated by different laboratories to reverse engineer the cellular regulatory network has been a major challenge. To automatically infer gene regulatory pathways from genome-wide mRNA expression profiles before and after genetic perturbations, we introduced a new Bayesian network algorithm: Deletion Mutant Bayesian Network (DM_BN. We applied DM_BN to the expression profiles of 544 yeast single or double deletion mutants of transcription factors, chromatin remodeling machinery components, protein kinases and phosphatases in S. cerevisiae. The network inferred by this method identified causal regulatory and non-causal concurrent interactions among these regulators (genetically perturbed genes that are strongly supported by the experimental evidence, and generated many new testable hypotheses. Compared to networks reconstructed by routine similarity measures or by alternative Bayesian network algorithms, the network inferred by DM_BN excels in both precision and recall. To facilitate its application in other systems, we packaged the algorithm into a user-friendly analysis tool that can be downloaded at http://www.picb.ac.cn/hanlab/DM_BN.html.

  2. Multi-target trapping in constrained environments using gene regulatory network-based pattern formation

    Directory of Open Access Journals (Sweden)

    Xingguang Peng

    2016-10-01

    Full Text Available Inspired by the morphogenesis of biological organisms, gene regulatory network-based methods have been used in complex pattern formation of swarm robotic systems. In this article, obstacle information was embedded into the gene regulatory network model to make the robots trap targets with an expected pattern while avoiding obstacles in a distributed manner. Based on the modified gene regulatory network model, an implicit function method was adopted to represent the expected pattern which is easily adjusted by adding extra feature points. Considering environmental constraints (e.g. tunnels or gaps in which robots must adjust their pattern to conduct trapping task, a pattern adaptation strategy was proposed for the pattern modeler to adaptively adjust the expected pattern. Also to trap multiple targets, a splitting pattern adaptation strategy was proposed for diffusively moving targets so that the robots can trap each target separately with split sub-patterns. The proposed model and strategies were verified through a set of simulation with complex environmental constraints and non-consensus movements of targets.

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

    Science.gov (United States)

    Luisier, Raphaëlle; Unterberger, Elif B.; Goodman, Jay I.; Schwarz, Michael; Moggs, Jonathan; Terranova, Rémi; van Nimwegen, Erik

    2014-01-01

    Gene regulatory interactions underlying the early stages of non-genotoxic carcinogenesis are poorly understood. Here, we have identified key candidate regulators of phenobarbital (PB)-mediated mouse liver tumorigenesis, a well-characterized model of non-genotoxic carcinogenesis, by applying a new computational modeling approach to a comprehensive collection of in vivo gene expression studies. We have combined our previously developed motif activity response analysis (MARA), which models gene expression patterns in terms of computationally predicted transcription factor binding sites with singular value decomposition (SVD) of the inferred motif activities, to disentangle the roles that different transcriptional regulators play in specific biological pathways of tumor promotion. Furthermore, transgenic mouse models enabled us to identify which of these regulatory activities was downstream of constitutive androstane receptor and β-catenin signaling, both crucial components of PB-mediated liver tumorigenesis. We propose novel roles for E2F and ZFP161 in PB-mediated hepatocyte proliferation and suggest that PB-mediated suppression of ESR1 activity contributes to the development of a tumor-prone environment. Our study shows that combining MARA with SVD allows for automated identification of independent transcription regulatory programs within a complex in vivo tissue environment and provides novel mechanistic insights into PB-mediated hepatocarcinogenesis. PMID:24464994

  4. Inference of gene regulatory networks from genetic perturbations with linear regression model.

    Directory of Open Access Journals (Sweden)

    Zijian Dong

    Full Text Available It is an effective strategy to use both genetic perturbation data and gene expression data to infer regulatory networks that aims to improve the detection accuracy of the regulatory relationships among genes. Based on both types of data, the genetic regulatory networks can be accurately modeled by Structural Equation Modeling (SEM. In this paper, a linear regression (LR model is formulated based on the SEM, and a novel iterative scheme using Bayesian inference is proposed to estimate the parameters of the LR model (LRBI. Comparative evaluations of LRBI with other two algorithms, the Adaptive Lasso (AL-Based and the Sparsity-aware Maximum Likelihood (SML, are also presented. Simulations show that LRBI has significantly better performance than AL-Based, and overperforms SML in terms of power of detection. Applying the LRBI algorithm to experimental data, we inferred the interactions in a network of 35 yeast genes. An open-source program of the LRBI algorithm is freely available upon request.

  5. Repressive BMP2 gene regulatory elements near the BMP2 promoter

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Shan [Department of Biochemistry and Molecular Biology, University of Medicine and Dentistry (UMDNJ), New Jersey Medical School (NJMS), Newark, NJ (United States); Chandler, Ronald L. [Department of Molecular Physiology and Biophysics, Center for Human Genetics Research, Vanderbilt University School of Medicine, Nashville, TN (United States); Fritz, David T. [Department of Biochemistry and Molecular Biology, University of Medicine and Dentistry (UMDNJ), New Jersey Medical School (NJMS), Newark, NJ (United States); Mortlock, Douglas P. [Department of Molecular Physiology and Biophysics, Center for Human Genetics Research, Vanderbilt University School of Medicine, Nashville, TN (United States); Rogers, Melissa B., E-mail: rogersmb@umdnj.edu [Department of Biochemistry and Molecular Biology, University of Medicine and Dentistry (UMDNJ), New Jersey Medical School (NJMS), Newark, NJ (United States)

    2010-02-05

    The level of bone morphogenetic protein 2 (BMP2) profoundly influences essential cell behaviors such as proliferation, differentiation, apoptosis, and migration. The spatial and temporal pattern of BMP2 synthesis, particular in diverse embryonic cells, is highly varied and dynamic. We have identified GC-rich sequences within the BMP2 promoter region that strongly repress gene expression. These elements block the activity of a highly conserved, osteoblast enhancer in response to FGF2 treatment. Both positive and negative gene regulatory elements control BMP2 synthesis. Detecting and mapping the repressive motifs is essential because they impede the identification of developmentally regulated enhancers necessary for normal BMP2 patterns and concentration.

  6. Modularity of gene-regulatory networks revealed in sea-star development

    Directory of Open Access Journals (Sweden)

    Degnan Bernard M

    2011-01-01

    Full Text Available Abstract Evidence that conserved developmental gene-regulatory networks can change as a unit during deutersostome evolution emerges from a study published in BMC Biology. This shows that genes consistently expressed in anterior brain patterning in hemichordates and chordates are expressed in a similar spatial pattern in another deuterostome, an asteroid echinoderm (sea star, but in a completely different developmental context (the animal-vegetal axis. This observation has implications for hypotheses on the type of development present in the deuterostome common ancestor. See research article: http://www.biomedcentral.com/1741-7007/8/143/abstract

  7. NetDiff - Bayesian model selection for differential gene regulatory network inference.

    Science.gov (United States)

    Thorne, Thomas

    2016-12-16

    Differential networks allow us to better understand the changes in cellular processes that are exhibited in conditions of interest, identifying variations in gene regulation or protein interaction between, for example, cases and controls, or in response to external stimuli. Here we present a novel methodology for the inference of differential gene regulatory networks from gene expression microarray data. Specifically we apply a Bayesian model selection approach to compare models of conserved and varying network structure, and use Gaussian graphical models to represent the network structures. We apply a variational inference approach to the learning of Gaussian graphical models of gene regulatory networks, that enables us to perform Bayesian model selection that is significantly more computationally efficient than Markov Chain Monte Carlo approaches. Our method is demonstrated to be more robust than independent analysis of data from multiple conditions when applied to synthetic network data, generating fewer false positive predictions of differential edges. We demonstrate the utility of our approach on real world gene expression microarray data by applying it to existing data from amyotrophic lateral sclerosis cases with and without mutations in C9orf72, and controls, where we are able to identify differential network interactions for further investigation.

  8. PRODIGEN: visualizing the probability landscape of stochastic gene regulatory networks in state and time space.

    Science.gov (United States)

    Ma, Chihua; Luciani, Timothy; Terebus, Anna; Liang, Jie; Marai, G Elisabeta

    2017-02-15

    Visualizing the complex probability landscape of stochastic gene regulatory networks can further biologists' understanding of phenotypic behavior associated with specific genes. We present PRODIGEN (PRObability DIstribution of GEne Networks), a web-based visual analysis tool for the systematic exploration of probability distributions over simulation time and state space in such networks. PRODIGEN was designed in collaboration with bioinformaticians who research stochastic gene networks. The analysis tool combines in a novel way existing, expanded, and new visual encodings to capture the time-varying characteristics of probability distributions: spaghetti plots over one dimensional projection, heatmaps of distributions over 2D projections, enhanced with overlaid time curves to display temporal changes, and novel individual glyphs of state information corresponding to particular peaks. We demonstrate the effectiveness of the tool through two case studies on the computed probabilistic landscape of a gene regulatory network and of a toggle-switch network. Domain expert feedback indicates that our visual approach can help biologists: 1) visualize probabilities of stable states, 2) explore the temporal probability distributions, and 3) discover small peaks in the probability landscape that have potential relation to specific diseases.

  9. Two lamprey Hedgehog genes share non-coding regulatory sequences and expression patterns with gnathostome Hedgehogs.

    Directory of Open Access Journals (Sweden)

    Shungo Kano

    Full Text Available Hedgehog (Hh genes play major roles in animal development and studies of their evolution, expression and function point to major differences among chordates. Here we focused on Hh genes in lampreys in order to characterize the evolution of Hh signalling at the emergence of vertebrates. Screening of a cosmid library of the river lamprey Lampetra fluviatilis and searching the preliminary genome assembly of the sea lamprey Petromyzon marinus indicate that lampreys have two Hh genes, named Hha and Hhb. Phylogenetic analyses suggest that Hha and Hhb are lamprey-specific paralogs closely related to Sonic/Indian Hh genes. Expression analysis indicates that Hha and Hhb are expressed in a Sonic Hh-like pattern. The two transcripts are expressed in largely overlapping but not identical domains in the lamprey embryonic brain, including a newly-described expression domain in the nasohypophyseal placode. Global alignments of genomic sequences and local alignment with known gnathostome regulatory motifs show that lamprey Hhs share conserved non-coding elements (CNE with gnathostome Hhs albeit with sequences that have significantly diverged and dispersed. Functional assays using zebrafish embryos demonstrate gnathostome-like midline enhancer activity for CNEs contained in intron2. We conclude that lamprey Hh genes are gnathostome Shh-like in terms of expression and regulation. In addition, they show some lamprey-specific features, including duplication and structural (but not functional changes in the intronic/regulatory sequences.

  10. In vitro gene regulatory networks predict in vivo function of liver

    Directory of Open Access Journals (Sweden)

    Ang Choo Y

    2010-11-01

    Full Text Available Abstract Background Evolution of toxicity testing is predicated upon using in vitro cell based systems to rapidly screen and predict how a chemical might cause toxicity to an organ in vivo. However, the degree to which we can extend in vitro results to in vivo activity and possible mechanisms of action remains to be fully addressed. Results Here we use the nitroaromatic 2,4,6-trinitrotoluene (TNT as a model chemical to compare and determine how we might extrapolate from in vitro data to in vivo effects. We found 341 transcripts differentially expressed in common among in vitro and in vivo assays in response to TNT. The major functional term corresponding to these transcripts was cell cycle. Similarly modulated common pathways were identified between in vitro and in vivo. Furthermore, we uncovered the conserved common transcriptional gene regulatory networks between in vitro and in vivo cellular liver systems that responded to TNT exposure, which mainly contain 2 subnetwork modules: PTTG1 and PIR centered networks. Interestingly, all 7 genes in the PTTG1 module were involved in cell cycle and downregulated by TNT both in vitro and in vivo. Conclusions The results of our investigation of TNT effects on gene expression in liver suggest that gene regulatory networks obtained from an in vitro system can predict in vivo function and mechanisms. Inhibiting PTTG1 and its targeted cell cyle related genes could be key machanism for TNT induced liver toxicity.

  11. In vitro gene regulatory networks predict in vivo function of liver

    Science.gov (United States)

    2010-01-01

    Background Evolution of toxicity testing is predicated upon using in vitro cell based systems to rapidly screen and predict how a chemical might cause toxicity to an organ in vivo. However, the degree to which we can extend in vitro results to in vivo activity and possible mechanisms of action remains to be fully addressed. Results Here we use the nitroaromatic 2,4,6-trinitrotoluene (TNT) as a model chemical to compare and determine how we might extrapolate from in vitro data to in vivo effects. We found 341 transcripts differentially expressed in common among in vitro and in vivo assays in response to TNT. The major functional term corresponding to these transcripts was cell cycle. Similarly modulated common pathways were identified between in vitro and in vivo. Furthermore, we uncovered the conserved common transcriptional gene regulatory networks between in vitro and in vivo cellular liver systems that responded to TNT exposure, which mainly contain 2 subnetwork modules: PTTG1 and PIR centered networks. Interestingly, all 7 genes in the PTTG1 module were involved in cell cycle and downregulated by TNT both in vitro and in vivo. Conclusions The results of our investigation of TNT effects on gene expression in liver suggest that gene regulatory networks obtained from an in vitro system can predict in vivo function and mechanisms. Inhibiting PTTG1 and its targeted cell cyle related genes could be key machanism for TNT induced liver toxicity. PMID:21073692

  12. Molecular structural and functional characterization of STAT1 gene regulatory region in teleost Channa argus.

    Science.gov (United States)

    Jia, Weizhang; Zhou, Xiuxia

    2010-05-15

    The transcription factor STAT1 is involved in signal transduction of type I and II interferons (IFNs). However, the molecular characteristics of the STAT1 regulatory region still remain to be elucidated in teleosts. In the present study, the complete cDNA and the regulatory region of the STAT1 gene were isolated from snakehead (Channa argus). More than 2.4kb 5'-flanking region of STAT1 shares the regulatory elements of IFN-stimulated response element (ISRE) and IFN-gamma activation site (GAS). Consensus ISRE and GAS were located from -373 to -361 and -716 to -724 in the promoter region, respectively. Moreover, it is noticeable that the crucial elements of ISRE (+698 to +710) and GAS (+294 and +301) are present in the first intron of snakehead STAT1. Comparisons of six vertebrate STAT1 5'-flanking regions all present the common sequence characteristics of IFN-induced gene promoter, which include ISRE, GAS and Sp1 sites. In order to further characterize the snakehead STAT1 regulatory region, six reporter constructs of snakehead STAT1 promoter and first intron were generated to examine the specificity to human interferon-gamma (hIFN-gamma). Only those constructs containing the ISRE element showed notable reporter activity after stimulation of Hela cells with hIFN-gamma. However, sequential deletions of putative transcription factor binding sites indicated that GAS elements have little effect on the promoter and intronic activity in response to hIFN-gamma. Taken together, these results suggest that the regulatory mechanisms of IFN-signalling appear to be mediated in a similar manner in fish and mammals.

  13. State of the Art of Fuzzy Methods for Gene Regulatory Networks Inference

    Science.gov (United States)

    Al Qazlan, Tuqyah Abdullah; Kara-Mohamed, Chafia

    2015-01-01

    To address one of the most challenging issues at the cellular level, this paper surveys the fuzzy methods used in gene regulatory networks (GRNs) inference. GRNs represent causal relationships between genes that have a direct influence, trough protein production, on the life and the development of living organisms and provide a useful contribution to the understanding of the cellular functions as well as the mechanisms of diseases. Fuzzy systems are based on handling imprecise knowledge, such as biological information. They provide viable computational tools for inferring GRNs from gene expression data, thus contributing to the discovery of gene interactions responsible for specific diseases and/or ad hoc correcting therapies. Increasing computational power and high throughput technologies have provided powerful means to manage these challenging digital ecosystems at different levels from cell to society globally. The main aim of this paper is to report, present, and discuss the main contributions of this multidisciplinary field in a coherent and structured framework. PMID:25879048

  14. State of the Art of Fuzzy Methods for Gene Regulatory Networks Inference

    Directory of Open Access Journals (Sweden)

    Tuqyah Abdullah Al Qazlan

    2015-01-01

    Full Text Available To address one of the most challenging issues at the cellular level, this paper surveys the fuzzy methods used in gene regulatory networks (GRNs inference. GRNs represent causal relationships between genes that have a direct influence, trough protein production, on the life and the development of living organisms and provide a useful contribution to the understanding of the cellular functions as well as the mechanisms of diseases. Fuzzy systems are based on handling imprecise knowledge, such as biological information. They provide viable computational tools for inferring GRNs from gene expression data, thus contributing to the discovery of gene interactions responsible for specific diseases and/or ad hoc correcting therapies. Increasing computational power and high throughput technologies have provided powerful means to manage these challenging digital ecosystems at different levels from cell to society globally. The main aim of this paper is to report, present, and discuss the main contributions of this multidisciplinary field in a coherent and structured framework.

  15. Urinary Incontinence

    Science.gov (United States)

    ... It may begin around the time of menopause. Urgency urinary incontinence happens when people have a sudden need ... urinary incontinence is a mix of stress and urgency urinary incontinence. You may leak urine with a laugh ...

  16. Mapping regulatory genes as candidates for cold and drought stress tolerance in barley.

    Science.gov (United States)

    Tondelli, A; Francia, E; Barabaschi, D; Aprile, A; Skinner, J S; Stockinger, E J; Stanca, A M; Pecchioni, N

    2006-02-01

    Cereal crop yield is greatly affected in many growing areas by abiotic stresses, mainly low temperature and drought. In order to find candidates for the tolerance genes for these stresses, 13 genes encoding for transcription factors and upstream regulators were screened by amplification and SSCP on six parental genotypes of three barley mapping populations ('Nure' x 'Tremois', 'Proctor' x 'Nudinka', and 'Steptoe' x 'Morex'), and mapped as newly developed STS, SNP, and SSCP markers. A new consensus function map was then drawn using the three maps above, including 16 regulatory candidate genes (CGs). The positions of barley cold and drought tolerance quantitative trait loci (QTLs) presently described in the literature were added to the consensus map to find positional candidates from among the mapped genes. A cluster of six HvCBF genes co-mapped with the Fr-H2 cold tolerance QTL, while no QTLs for the same trait were positioned on chromosome 7H, where two putative barley regulators of CBF expression, ICE1 and FRY1, found by homology search, were mapped in this work. These observations suggest that CBF gene(s) themselves, rather than their two regulators, are at present the best candidates for cold tolerance. Four out of 12 drought tolerance QTLs of the consensus map are associated with regulatory CGs, on chromosomes 2H, 5H, and 7H, and two QTLs with effector genes, on chromosomes 5H and 6H. The results obtained could be used to guide MAS applications, allowing introduction into an ideal genotype of favourable alleles of tolerance QTLs.

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

    Science.gov (United States)

    Ruyssinck, Joeri; Huynh-Thu, Vân Anh; Geurts, Pierre; Dhaene, Tom; Demeester, Piet; Saeys, Yvan

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Joeri Ruyssinck

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

  19. Regulatory RNAs in Bacillus subtilis : a Gram-Positive Perspective on Bacterial RNA-Mediated Regulation of Gene Expression

    NARCIS (Netherlands)

    Mars, Ruben A. T.; Nicolas, Pierre; Denham, Emma L.; van Dijl, Jan Maarten

    2016-01-01

    Bacteria can employ widely diverse RNA molecules to regulate their gene expression. Such molecules include trans-acting small regulatory RNAs, antisense RNAs, and a variety of transcriptional attenuation mechanisms in the 5= untranslated region. Thus far, most regulatory RNA research has focused on

  20. Metatranscriptomic insights on gene expression and regulatory controls in Candidatus Accumulibacter phosphatis

    Science.gov (United States)

    Oyserman, Ben O; Noguera, Daniel R; del Rio, Tijana Glavina; Tringe, Susannah G; McMahon, Katherine D

    2016-01-01

    Previous studies on enhanced biological phosphorus removal (EBPR) have focused on reconstructing genomic blueprints for the model polyphosphate-accumulating organism Candidatus Accumulibacter phosphatis. Here, a time series metatranscriptome generated from enrichment cultures of Accumulibacter was used to gain insight into anerobic/aerobic metabolism and regulatory mechanisms within an EBPR cycle. Co-expressed gene clusters were identified displaying ecologically relevant trends consistent with batch cycle phases. Transcripts displaying increased abundance during anerobic acetate contact were functionally enriched in energy production and conversion, including upregulation of both cytoplasmic and membrane-bound hydrogenases demonstrating the importance of transcriptional regulation to manage energy and electron flux during anerobic acetate contact. We hypothesized and demonstrated hydrogen production after anerobic acetate contact, a previously unknown strategy for Accumulibacter to maintain redox balance. Genes involved in anerobic glycine utilization were identified and phosphorus release after anerobic glycine contact demonstrated, suggesting that Accumulibacter routes diverse carbon sources to acetyl-CoA formation via previously unrecognized pathways. A comparative genomics analysis of sequences upstream of co-expressed genes identified two statistically significant putative regulatory motifs. One palindromic motif was identified upstream of genes involved in PHA synthesis and acetate activation and is hypothesized to be a phaR binding site, hence representing a hypothetical PHA modulon. A second motif was identified ~35 base pairs (bp) upstream of a large and diverse array of genes and hence may represent a sigma factor binding site. This analysis provides a basis and framework for further investigations into Accumulibacter metabolism and the reconstruction of regulatory networks in uncultured organisms. PMID:26555245

  1. Associations of Filaggrin Gene Loss-of-Function Variants with Urinary Phthalate Metabolites and Testicular Function in Young Danish Men

    Science.gov (United States)

    Jørgensen, Niels; Meldgaard, Michael; Frederiksen, Hanne; Andersson, Anna-Maria; Menné, Torkil; Johansen, Jeanne Duus; Carlsen, Berit Christina; Stender, Steen; Szecsi, Pal Bela; Skakkebæk, Niels Erik; De Meyts, Ewa Rajpert; Thyssen, Jacob P.

    2014-01-01

    Background: Filaggrin is an epidermal protein that is crucial for skin barrier function. Up to 10% of Europeans and 5% of Asians carry at least one null allele in the filaggrin gene (FLG). Reduced expression of filaggrin in carriers of the null allele is associated with facilitated transfer of allergens across the epidermis. We hypothesized that these individuals may have increased transdermal uptake of endocrine disruptors, including phthalates. Objectives: We investigated urinary excretion of phthalate metabolites and testicular function in young men with and without FLG loss-of-function variants in a cross-sectional study of 861 young men from the general Danish population. Methods: All men were genotyped for FLG R501X, 2282del4, and R2447X loss-of-function variants. We measured urinary concentrations of 14 phthalate metabolites and serum levels of reproductive hormones. We also evaluated semen quality. Results: Sixty-five men (7.5%) carried at least one FLG-null allele. FLG-null carriers had significantly higher urinary concentrations of several phthalate metabolites, including a 33% higher concentration of MnBP (mono-n-butyl phthalate; 95% CI: 16, 51%). FLG-null variants were not significantly associated with reproductive hormones or semen quality parameters. Conclusion: This study provides evidence that carriers of FLG loss-of-function alleles may have higher internal exposure to phthalates, possibly due to increased transepidermal absorption. FLG loss-of-function variants may indicate susceptible populations for which special attention to transepidermal absorption of chemicals and medication may be warranted. Citation: Joensen UN, Jørgensen N, Meldgaard M, Frederiksen H, Andersson AM, Menné T, Johansen JD, Carlsen BC, Stender S, Szecsi PB, Skakkebæk NE, Rajpert-De Meyts E, Thyssen JP. 2014. Associations of filaggrin gene loss-of-function variants with urinary phthalate metabolites and testicular function in young Danish men. Environ Health Perspect 122

  2. Developmental gene regulatory network evolution: insights from comparative studies in echinoderms.

    Science.gov (United States)

    Hinman, Veronica F; Cheatle Jarvela, Alys M

    2014-03-01

    One of the central concerns of Evolutionary Developmental biology is to understand how the specification of cell types can change during evolution. In the last decade, developmental biology has progressed toward a systems level understanding of cell specification processes. In particular, the focus has been on determining the regulatory interactions of the repertoire of genes that make up gene regulatory networks (GRNs). Echinoderms provide an extraordinary model system for determining how GRNs evolve. This review highlights the comparative GRN analyses arising from the echinoderm system. This work shows that certain types of GRN subcircuits or motifs, i.e., those involving positive feedback, tend to be conserved and may provide a constraint on development. This conservation may be due to a required arrangement of transcription factor binding sites in cis regulatory modules. The review will also discuss ways in which novelty may arise, in particular through the co-option of regulatory genes and subcircuits. The development of the sea urchin larval skeleton, a novel feature that arose in echinoderms, has provided a model for study of co-option mechanisms. Finally, the types of GRNs that can permit the great diversity in the patterns of ciliary bands and their associated neurons found among these taxa are discussed. The availability of genomic resources is rapidly expanding for echinoderms, including genome sequences not only for multiple species of sea urchins but also a species of sea star, sea cucumber, and brittle star. This will enable echinoderms to become a particularly powerful system for understanding how developmental GRNs evolve.

  3. Predicting miRNA Targets by Integrating Gene Regulatory Knowledge with Expression Profiles.

    Directory of Open Access Journals (Sweden)

    Weijia Zhang

    Full Text Available microRNAs (miRNAs play crucial roles in post-transcriptional gene regulation of both plants and mammals, and dysfunctions of miRNAs are often associated with tumorigenesis and development through the effects on their target messenger RNAs (mRNAs. Identifying miRNA functions is critical for understanding cancer mechanisms and determining the efficacy of drugs. Computational methods analyzing high-throughput data offer great assistance in understanding the diverse and complex relationships between miRNAs and mRNAs. However, most of the existing methods do not fully utilise the available knowledge in biology to reduce the uncertainty in the modeling process. Therefore it is desirable to develop a method that can seamlessly integrate existing biological knowledge and high-throughput data into the process of discovering miRNA regulation mechanisms.In this article we present an integrative framework, CIDER (Causal miRNA target Discovery with Expression profile and Regulatory knowledge, to predict miRNA targets. CIDER is able to utilise a variety of gene regulation knowledge, including transcriptional and post-transcriptional knowledge, and to exploit gene expression data for the discovery of miRNA-mRNA regulatory relationships. The benefits of our framework is demonstrated by both simulation study and the analysis of the epithelial-to-mesenchymal transition (EMT and the breast cancer (BRCA datasets. Our results reveal that even a limited amount of either Transcription Factor (TF-miRNA or miRNA-mRNA regulatory knowledge improves the performance of miRNA target prediction, and the combination of the two types of knowledge enhances the improvement further. Another useful property of the framework is that its performance increases monotonically with the increase of regulatory knowledge.

  4. Direct and indirect control of oral ectoderm regulatory gene expression by Nodal signaling in the sea urchin embryo.

    Science.gov (United States)

    Li, Enhu; Materna, Stefan C; Davidson, Eric H

    2012-09-15

    The Nodal signaling pathway is known from earlier work to be an essential mediator of oral ectoderm specification in the sea urchin embryo, and indirectly, of aboral ectoderm specification as well. Following expression of the Nodal ligand in the future oral ectoderm during cleavage, a sequence of regulatory gene activations occur within this territory which depend directly or indirectly on nodal gene expression. Here we describe additional regulatory genes that contribute to the oral ectoderm regulatory state during specification in Strongylocentrotus purpuratus, and show how their spatial expression changes dynamically during development. By means of system wide perturbation analyses we have significantly improved current knowledge of the epistatic relations among the regulatory genes of the oral ectoderm. From these studies there emerge diverse circuitries relating downstream regulatory genes directly and indirectly to Nodal signaling. A key intermediary regulator, the role of which had not previously been discerned, is the not gene. In addition to activating several genes earlier described as targets of Nodal signaling, the not gene product acts to repress other oral ectoderm genes, contributing crucially to the bilateral spatial organization of the embryonic oral ectoderm. Copyright © 2012 Elsevier Inc. All rights reserved.

  5. Potential gene regulatory role for cyclin D3 in muscle cells

    Indian Academy of Sciences (India)

    Fathima Athar; Veena K Parnaik

    2015-09-01

    Cyclin D3 is important for muscle development and regeneration, and is involved in post-mitotic arrest of muscle cells. Cyclin D3 also has cell-cycle-independent functions such as regulation of specific genes in other tissues. Ectopic expression of cyclin D3 in myoblasts, where it is normally undetectable, promotes muscle gene expression and faster differentiation kinetics upon serum depletion. In the present study, we investigated the mechanistic role of cyclin D3 in muscle gene regulation. We initially showed by mutational analysis that a stable and functional cyclin D3 was required for promoting muscle differentiation. Using chromatin immunoprecipitation assays, we demonstrated that expression of cyclin D3 in undifferentiated myoblasts altered histone epigenetic marks at promoters of muscle-specific genes like MyoD, Pax7, myogenin and muscle creatine kinase but not non-muscle genes. Cyclin D3 expression also reduced the mRNA levels of certain epigenetic modifier genes. Our data suggest that epigenetic modulation of muscle-specific genes in cyclin-D3-expressing myoblasts may be responsible for faster differentiation kinetics upon serum depletion. Our results have implications for a regulatory role for cyclin D3 in muscle-specific gene activation.

  6. Demystifying the secret mission of enhancers: linking distal regulatory elements to target genes.

    Science.gov (United States)

    Yao, Lijing; Berman, Benjamin P; Farnham, Peggy J

    2015-01-01

    Enhancers are short regulatory sequences bound by sequence-specific transcription factors and play a major role in the spatiotemporal specificity of gene expression patterns in development and disease. While it is now possible to identify enhancer regions genomewide in both cultured cells and primary tissues using epigenomic approaches, it has been more challenging to develop methods to understand the function of individual enhancers because enhancers are located far from the gene(s) that they regulate. However, it is essential to identify target genes of enhancers not only so that we can understand the role of enhancers in disease but also because this information will assist in the development of future therapeutic options. After reviewing models of enhancer function, we discuss recent methods for identifying target genes of enhancers. First, we describe chromatin structure-based approaches for directly mapping interactions between enhancers and promoters. Second, we describe the use of correlation-based approaches to link enhancer state with the activity of nearby promoters and/or gene expression. Third, we describe how to test the function of specific enhancers experimentally by perturbing enhancer-target relationships using high-throughput reporter assays and genome editing. Finally, we conclude by discussing as yet unanswered questions concerning how enhancers function, how target genes can be identified, and how to distinguish direct from indirect changes in gene expression mediated by individual enhancers.

  7. A model of gene expression based on random dynamical systems reveals modularity properties of gene regulatory networks.

    Science.gov (United States)

    Antoneli, Fernando; Ferreira, Renata C; Briones, Marcelo R S

    2016-06-01

    Here we propose a new approach to modeling gene expression based on the theory of random dynamical systems (RDS) that provides a general coupling prescription between the nodes of any given regulatory network given the dynamics of each node is modeled by a RDS. The main virtues of this approach are the following: (i) it provides a natural way to obtain arbitrarily large networks by coupling together simple basic pieces, thus revealing the modularity of regulatory networks; (ii) the assumptions about the stochastic processes used in the modeling are fairly general, in the sense that the only requirement is stationarity; (iii) there is a well developed mathematical theory, which is a blend of smooth dynamical systems theory, ergodic theory and stochastic analysis that allows one to extract relevant dynamical and statistical information without solving the system; (iv) one may obtain the classical rate equations form the corresponding stochastic version by averaging the dynamic random variables (small noise limit). It is important to emphasize that unlike the deterministic case, where coupling two equations is a trivial matter, coupling two RDS is non-trivial, specially in our case, where the coupling is performed between a state variable of one gene and the switching stochastic process of another gene and, hence, it is not a priori true that the resulting coupled system will satisfy the definition of a random dynamical system. We shall provide the necessary arguments that ensure that our coupling prescription does indeed furnish a coupled regulatory network of random dynamical systems. Finally, the fact that classical rate equations are the small noise limit of our stochastic model ensures that any validation or prediction made on the basis of the classical theory is also a validation or prediction of our model. We illustrate our framework with some simple examples of single-gene system and network motifs.

  8. Evolution of gene regulatory network architectures: examples of subcircuit conservation and plasticity between classes of echinoderms.

    Science.gov (United States)

    Hinman, Veronica F; Yankura, Kristen A; McCauley, Brenna S

    2009-04-01

    Developmental gene regulatory networks (GRNs) explain how regulatory states are established in particular cells during development and how these states then determine the final form of the embryo. Evolutionary changes to the sequence of the genome will direct reorganization of GRN architectures, which in turn will lead to the alteration of developmental programs. A comparison of GRN architectures must consequently reveal the molecular basis for the evolution of developmental programs among different organisms. This review highlights some of the important findings that have emerged from the most extensive direct comparison of GRN architectures to date. Comparison of the orthologous GRNs for endomesodermal specification in the sea urchin and sea star, provides examples of several discrete, functional GRN subcircuits and shows that they are subject to diverse selective pressures. This demonstrates that different regulatory linkages may be more or less amenable to evolutionary change. One of the more surprising findings from this comparison is that GRN-level functions may be maintained while the factors performing the functions have changed, suggesting that GRNs have a high capacity for compensatory changes involving transcription factor binding to cis regulatory modules.

  9. Efflux pump regulatory genes mutations in multidrug resistance Pseudomonas aeruginosa isolated from wound infections in Isfahan hospitals

    Directory of Open Access Journals (Sweden)

    Hamid Vaez

    2014-01-01

    Conclusions: P. aeruginosa isolates with mutation in efflux pump regulatory genes such as mexR and nfxB could be a main factor contributed to antibiotic resistance and must be considered in antibiotic treatment.

  10. Robustness and state-space structure of Boolean gene regulatory models.

    Science.gov (United States)

    Willadsen, Kai; Wiles, Janet

    2007-12-21

    Robustness to perturbation is an important characteristic of genetic regulatory systems, but the relationship between robustness and model dynamics has not been clearly quantified. We propose a method for quantifying both robustness and dynamics in terms of state-space structures, for Boolean models of genetic regulatory systems. By investigating existing models of the Drosophila melanogaster segment polarity network and the Saccharomyces cerevisiae cell-cycle network, we show that the structure of attractor basins can yield insight into the underlying decision making required of the system, and also the way in which the system maximises its robustness. In particular, gene networks implementing decisions based on a few genes have simple state-space structures, and their attractors are robust by virtue of their simplicity. Gene networks with decisions that involve many interacting genes have correspondingly more complicated state-space structures, and robustness cannot be achieved through the structure of the attractor basins, but is achieved by larger attractor basins that dominate the state space. These different types of robustness are demonstrated by the two models: the D. melanogaster segment polarity network is robust due to simple attractor basins that implement decisions based on spatial signals; the S. cerevisiae cell-cycle network has a complicated state-space structure, and is robust only due to a giant attractor basin that dominates the state space.

  11. Characterization of Putative cis-Regulatory Elements in Genes Preferentially Expressed in Arabidopsis Male Meiocytes

    Directory of Open Access Journals (Sweden)

    Junhua Li

    2014-01-01

    Full Text Available Meiosis is essential for plant reproduction because it is the process during which homologous chromosome pairing, synapsis, and meiotic recombination occur. The meiotic transcriptome is difficult to investigate because of the size of meiocytes and the confines of anther lobes. The recent development of isolation techniques has enabled the characterization of transcriptional profiles in male meiocytes of Arabidopsis. Gene expression in male meiocytes shows unique features. The direct interaction of transcription factors (TFs with DNA regulatory sequences forms the basis for the specificity of transcriptional regulation. Here, we identified putative cis-regulatory elements (CREs associated with male meiocyte-expressed genes using in silico tools. The upstream regions (1 kb of the top 50 genes preferentially expressed in Arabidopsis meiocytes possessed conserved motifs. These motifs are putative binding sites of TFs, some of which share common functions, such as roles in cell division. In combination with cell-type-specific analysis, our findings could be a substantial aid for the identification and experimental verification of the protein-DNA interactions for the specific TFs that drive gene expression in meiocytes.

  12. A recursive network approach can identify constitutive regulatory circuits in gene expression data

    Science.gov (United States)

    Blasi, Monica Francesca; Casorelli, Ida; Colosimo, Alfredo; Blasi, Francesco Simone; Bignami, Margherita; Giuliani, Alessandro

    2005-03-01

    The activity of the cell is often coordinated by the organisation of proteins into regulatory circuits that share a common function. Genome-wide expression profiles might contain important information on these circuits. Current approaches for the analysis of gene expression data include clustering the individual expression measurements and relating them to biological functions as well as modelling and simulation of gene regulation processes by additional computer tools. The identification of the regulative programmes from microarray experiments is limited, however, by the intrinsic difficulty of linear methods to detect low-variance signals and by the sensitivity of the different approaches. Here we face the problem of recognising invariant patterns of correlations among gene expression reminiscent of regulation circuits. We demonstrate that a recursive neural network approach can identify genetic regulation circuits from expression data for ribosomal and genome stability genes. The proposed method, by greatly enhancing the sensitivity of microarray studies, allows the identification of important aspects of genetic regulation networks and might be useful for the discrimination of the different players involved in regulation circuits. Our results suggest that the constitutive regulatory networks involved in the generic organisation of the cell display a high degree of clustering depending on a modular architecture.

  13. Boolean networks using the chi-square test for inferring large-scale gene regulatory networks

    Directory of Open Access Journals (Sweden)

    Lee Jae K

    2007-02-01

    Full Text Available Abstract Background Boolean network (BN modeling is a commonly used method for constructing gene regulatory networks from time series microarray data. However, its major drawback is that its computation time is very high or often impractical to construct large-scale gene networks. We propose a variable selection method that are not only reduces BN computation times significantly but also obtains optimal network constructions by using chi-square statistics for testing the independence in contingency tables. Results Both the computation time and accuracy of the network structures estimated by the proposed method are compared with those of the original BN methods on simulated and real yeast cell cycle microarray gene expression data sets. Our results reveal that the proposed chi-square testing (CST-based BN method significantly improves the computation time, while its ability to identify all the true network mechanisms was effectively the same as that of full-search BN methods. The proposed BN algorithm is approximately 70.8 and 7.6 times faster than the original BN algorithm when the error sizes of the Best-Fit Extension problem are 0 and 1, respectively. Further, the false positive error rate of the proposed CST-based BN algorithm tends to be less than that of the original BN. Conclusion The CST-based BN method dramatically improves the computation time of the original BN algorithm. Therefore, it can efficiently infer large-scale gene regulatory network mechanisms.

  14. New regulatory circuit controlling spatial and temporal gene expression in the sea urchin embryo oral ectoderm GRN.

    Science.gov (United States)

    Li, Enhu; Materna, Stefan C; Davidson, Eric H

    2013-10-01

    The sea urchin oral ectoderm gene regulatory network (GRN) model has increased in complexity as additional genes are added to it, revealing its multiple spatial regulatory state domains. The formation of the oral ectoderm begins with an oral-aboral redox gradient, which is interpreted by the cis-regulatory system of the nodal gene to cause its expression on the oral side of the embryo. Nodal signaling drives cohorts of regulatory genes within the oral ectoderm and its derived subdomains. Activation of these genes occurs sequentially, spanning the entire blastula stage. During this process the stomodeal subdomain emerges inside of the oral ectoderm, and bilateral subdomains defining the lateral portions of the future ciliary band emerge adjacent to the central oral ectoderm. Here we examine two regulatory genes encoding repressors, sip1 and ets4, which selectively prevent transcription of oral ectoderm genes until their expression is cleared from the oral ectoderm as an indirect consequence of Nodal signaling. We show that the timing of transcriptional de-repression of sip1 and ets4 targets which occurs upon their clearance explains the dynamics of oral ectoderm gene expression. In addition two other repressors, the direct Nodal target not, and the feed forward Nodal target goosecoid, repress expression of regulatory genes in the central animal oral ectoderm thereby confining their expression to the lateral domains of the animal ectoderm. These results have permitted construction of an enhanced animal ectoderm GRN model highlighting the repressive interactions providing precise temporal and spatial control of regulatory gene expression. © 2013 Elsevier Inc. All rights reserved.

  15. Expression pattern and transcriptional regulatory mechanism of noxa gene in grass carp (Ctenopharyngodon idella).

    Science.gov (United States)

    Pei, Yongyan; Lu, Xiaonan; He, Libo; Wang, Hao; Zhang, Aidi; Li, Yongming; Huang, Rong; Liao, Lanjie; Zhu, Zuoyan; Wang, Yaping

    2015-12-01

    Noxa, a pro-apoptotic protein, plays an important role in cell apoptosis. The researches about noxa gene were concentrated in mammalians, whereas the role and transcriptional regulatory mechanism of noxa in fish were still unclear. In this study, the expression pattern and transcriptional regulatory mechanism of noxa gene in grass carp were analyzed. Noxa was constitutively expressed in all the examined tissues but the relative expression level differed. After exposure to grass carp reovirus (GCRV), mRNA expression level of noxa was down-regulated at the early phase whereas up-regulated at the late phase of infection. Luciferase assays showed that the promoter region -867 ∼ +107 of noxa had high activity and the region -678 ∼ -603 was important in the response to GCRV infection. By deleting the predicted transcription factor binding sites, transcription factors FOXO1 and CEBPβ were found important for noxa in response to GCRV infection. Moreover, the noxa promoter was biotin-labeled and incubated with nuclear extracts from GCRV infected cells. Mass spectrometry analysis showed that transcription factors FOXO1 and CEBPβ were also enriched in the combined proteins. Therefore, the results suggested that transcription factors FOXO1 and CEBPβ may play an important role in the regulation of noxa. Our study would provide new insight into the transcriptional regulatory mechanism of noxa in teleost fish.

  16. A Systems’ Biology Approach to Study MicroRNA-Mediated Gene Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Xin Lai

    2013-01-01

    Full Text Available MicroRNAs (miRNAs are potent effectors in gene regulatory networks where aberrant miRNA expression can contribute to human diseases such as cancer. For a better understanding of the regulatory role of miRNAs in coordinating gene expression, we here present a systems biology approach combining data-driven modeling and model-driven experiments. Such an approach is characterized by an iterative process, including biological data acquisition and integration, network construction, mathematical modeling and experimental validation. To demonstrate the application of this approach, we adopt it to investigate mechanisms of collective repression on p21 by multiple miRNAs. We first construct a p21 regulatory network based on data from the literature and further expand it using algorithms that predict molecular interactions. Based on the network structure, a detailed mechanistic model is established and its parameter values are determined using data. Finally, the calibrated model is used to study the effect of different miRNA expression profiles and cooperative target regulation on p21 expression levels in different biological contexts.

  17. Aberrations in the Iron Regulatory Gene Signature Are Associated with Decreased Survival in Diffuse Infiltrating Gliomas.

    Science.gov (United States)

    Weston, Cody; Klobusicky, Joe; Weston, Jennifer; Connor, James; Toms, Steven A; Marko, Nicholas F

    2016-01-01

    Iron is a tightly regulated micronutrient with no physiologic means of elimination and is necessary for cell division in normal tissue. Recent evidence suggests that dysregulation of iron regulatory proteins may play a role in cancer pathophysiology. We use public data from The Cancer Genome Atlas (TCGA) to study the association between survival and expression levels of 61 genes coding for iron regulatory proteins in patients with World Health Organization Grade II-III gliomas. Using a feature selection algorithm we identified a novel, optimized subset of eight iron regulatory genes (STEAP3, HFE, TMPRSS6, SFXN1, TFRC, UROS, SLC11A2, and STEAP4) whose differential expression defines two phenotypic groups with median survival differences of 52.3 months for patients with grade II gliomas (25.9 vs. 78.2 months, p< 10-3), 43.5 months for patients with grade III gliomas (43.9 vs. 87.4 months, p = 0.025), and 54.0 months when considering both grade II and III gliomas (79.9 vs. 25.9 months, p < 10-5).

  18. Dissecting early regulatory relationships in the lamprey neural crest gene network.

    Science.gov (United States)

    Nikitina, Natalya; Sauka-Spengler, Tatjana; Bronner-Fraser, Marianne

    2008-12-23

    The neural crest, a multipotent embryonic cell type, originates at the border between neural and nonneural ectoderm. After neural tube closure, these cells undergo an epithelial-mesenchymal transition, migrate to precise, often distant locations, and differentiate into diverse derivatives. Analyses of expression and function of signaling and transcription factors in higher vertebrates has led to the proposal that a neural crest gene regulatory network (NC-GRN) orchestrates neural crest formation. Here, we interrogate the NC-GRN in the lamprey, taking advantage of its slow development and basal phylogenetic position to resolve early inductive events, 1 regulatory step at the time. To establish regulatory relationships at the neural plate border, we assess relative expression of 6 neural crest network genes and effects of individually perturbing each on the remaining 5. The results refine an upstream portion of the NC-GRN and reveal unexpected order and linkages therein; e.g., lamprey AP-2 appears to function early as a neural plate border rather than a neural crest specifier and in a pathway linked to MsxA but independent of ZicA. These findings provide an ancestral framework for performing comparative tests in higher vertebrates in which network linkages may be more difficult to resolve because of their rapid development.

  19. Evaluation of combinatorial cis-regulatory elements for stable gene expression in chicken cells

    Directory of Open Access Journals (Sweden)

    Seo Hee W

    2010-09-01

    Full Text Available Abstract Background Recent successes in biotechnological application of birds are based on their unique physiological traits such as unlimited manipulability onto developing embryos and simple protein constituents of the eggs. However it is not likely that target protein is produced as kinetically expected because various factors affect target gene expression. Although there have been various attempts to minimize the silencing of transgenes, a generalized study that uses multiple cis-acting elements in chicken has not been made. The aim of the present study was to analyze whether various cis-acting elements can help to sustain transgene expression in chicken fibroblasts. Results We investigated the optimal transcriptional regulatory elements for enhancing stable transgene expression in chicken cells. We generated eight constructs that encode enhanced green fluorescent protein (eGFP driven by either CMV or CAG promoters (including the control, containing three types of key regulatory elements: a chicken lysozyme matrix attachment region (cMAR, 5'-DNase I-hypersensitive sites 4 (cHS4, and the woodchuck hepatitis virus posttranscriptional regulatory element (WPRE. Then we transformed immortalized chicken embryonic fibroblasts with these constructs by electroporation, and after cells were expanded under G418 selection, analyzed mRNA levels and mean fluorescence intensity (MFI by quantitative real-time PCR and flow cytometry, respectively. We found that the copy number of each construct significantly decreased as the size of the construct increased (R2 = 0.701. A significant model effect was found in the expression level among various constructs in both mRNA and protein (P cis-acting elements decreased the level of gene silencing as well as the coefficient of variance of eGFP-expressing cells (P Conclusions Our current data show that an optimal combination of cis-acting elements and promoters/enhancers for sustaining gene expression in chicken cells

  20. Regulatory structures for gene therapy medicinal products in the European Union.

    Science.gov (United States)

    Klug, Bettina; Celis, Patrick; Carr, Melanie; Reinhardt, Jens

    2012-01-01

    Taking into account the complexity and technical specificity of advanced therapy medicinal products: (gene and cell therapy medicinal products and tissue engineered products), a dedicated European regulatory framework was needed. Regulation (EC) No. 1394/2007, the "ATMP Regulation" provides tailored regulatory principles for the evaluation and authorization of these innovative medicines. The majority of gene or cell therapy product development is carried out by academia, hospitals, and small- and medium-sized enterprises (SMEs). Thus, acknowledging the particular needs of these types of sponsors, the legislation also provides incentives for product development tailored to them. The European Medicines Agency (EMA) and, in particular, its Committee for Advanced Therapies (CAT) provide a variety of opportunities for early interaction with developers of ATMPs to enable them to have early regulatory and scientific input. An important tool to promote innovation and the development of new medicinal products by micro-, small-, and medium-sized enterprises is the EMA's SME initiative launched in December 2005 to offer financial and administrative assistance to smaller companies. The European legislation also foresees the involvement of stakeholders, such as patient organizations, in the development of new medicines. Considering that gene therapy medicinal products are developed in many cases for treatment of rare diseases often of monogenic origin, the involvement of patient organizations, which focus on rare diseases and genetic and congenital disorders, is fruitful. Two such organizations are represented in the CAT. Research networks play another important role in the development of gene therapy medicinal products. The European Commission is funding such networks through the EU Sixth Framework Program.

  1. Few regulatory metabolites coordinate expression of central metabolic genes in Escherichia coli.

    Science.gov (United States)

    Kochanowski, Karl; Gerosa, Luca; Brunner, Simon F; Christodoulou, Dimitris; Nikolaev, Yaroslav V; Sauer, Uwe

    2017-01-03

    Transcription networks consist of hundreds of transcription factors with thousands of often overlapping target genes. While we can reliably measure gene expression changes, we still understand relatively little why expression changes the way it does. How does a coordinated response emerge in such complex networks and how many input signals are necessary to achieve it? Here, we unravel the regulatory program of gene expression in Escherichia coli central carbon metabolism with more than 30 known transcription factors. Using a library of fluorescent transcriptional reporters, we comprehensively quantify the activity of central metabolic promoters in 26 environmental conditions. The expression patterns were dominated by growth rate-dependent global regulation for most central metabolic promoters in concert with highly condition-specific activation for only few promoters. Using an approximate mathematical description of promoter activity, we dissect the contribution of global and specific transcriptional regulation. About 70% of the total variance in promoter activity across conditions was explained by global transcriptional regulation. Correlating the remaining specific transcriptional regulation of each promoter with the cell's metabolome response across the same conditions identified potential regulatory metabolites. Remarkably, cyclic AMP, fructose-1,6-bisphosphate, and fructose-1-phosphate alone explained most of the specific transcriptional regulation through their interaction with the two major transcription factors Crp and Cra. Thus, a surprisingly simple regulatory program that relies on global transcriptional regulation and input from few intracellular metabolites appears to be sufficient to coordinate E. coli central metabolism and explain about 90% of the experimentally observed transcription changes in 100 genes. © 2017 The Authors. Published under the terms of the CC BY 4.0 license.

  2. Learning a Markov Logic network for supervised gene regulatory network inference.

    Science.gov (United States)

    Brouard, Céline; Vrain, Christel; Dubois, Julie; Castel, David; Debily, Marie-Anne; d'Alché-Buc, Florence

    2013-09-12

    Gene regulatory network inference remains a challenging problem in systems biology despite the numerous approaches that have been proposed. When substantial knowledge on a gene regulatory network is already available, supervised network inference is appropriate. Such a method builds a binary classifier able to assign a class (Regulation/No regulation) to an ordered pair of genes. Once learnt, the pairwise classifier can be used to predict new regulations. In this work, we explore the framework of Markov Logic Networks (MLN) that combine features of probabilistic graphical models with the expressivity of first-order logic rules. We propose to learn a Markov Logic network, e.g. a set of weighted rules that conclude on the predicate "regulates", starting from a known gene regulatory network involved in the switch proliferation/differentiation of keratinocyte cells, a set of experimental transcriptomic data and various descriptions of genes all encoded into first-order logic. As training data are unbalanced, we use asymmetric bagging to learn a set of MLNs. The prediction of a new regulation can then be obtained by averaging predictions of individual MLNs. As a side contribution, we propose three in silico tests to assess the performance of any pairwise classifier in various network inference tasks on real datasets. A first test consists of measuring the average performance on balanced edge prediction problem; a second one deals with the ability of the classifier, once enhanced by asymmetric bagging, to update a given network. Finally our main result concerns a third test that measures the ability of the method to predict regulations with a new set of genes. As expected, MLN, when provided with only numerical discretized gene expression data, does not perform as well as a pairwise SVM in terms of AUPR. However, when a more complete description of gene properties is provided by heterogeneous sources, MLN achieves the same performance as a black-box model such as a

  3. Genome-wide analyses for dissecting gene regulatory networks in the shoot apical meristem.

    Science.gov (United States)

    Bustamante, Mariana; Matus, José Tomás; Riechmann, José Luis

    2016-03-01

    Shoot apical meristem activity is controlled by complex regulatory networks in which components such as transcription factors, miRNAs, small peptides, hormones, enzymes and epigenetic marks all participate. Many key genes that determine the inherent characteristics of the shoot apical meristem have been identified through genetic approaches. Recent advances in genome-wide studies generating extensive transcriptomic and DNA-binding datasets have increased our understanding of the interactions within the regulatory networks that control the activity of the meristem, identifying new regulators and uncovering connections between previously unlinked network components. In this review, we focus on recent studies that illustrate the contribution of whole genome analyses to understand meristem function. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  4. Inference of Gene Regulatory Networks Using Bayesian Nonparametric Regression and Topology Information

    Science.gov (United States)

    2017-01-01

    Gene regulatory networks (GRNs) play an important role in cellular systems and are important for understanding biological processes. Many algorithms have been developed to infer the GRNs. However, most algorithms only pay attention to the gene expression data but do not consider the topology information in their inference process, while incorporating this information can partially compensate for the lack of reliable expression data. Here we develop a Bayesian group lasso with spike and slab priors to perform gene selection and estimation for nonparametric models. B-spline basis functions are used to capture the nonlinear relationships flexibly and penalties are used to avoid overfitting. Further, we incorporate the topology information into the Bayesian method as a prior. We present the application of our method on DREAM3 and DREAM4 datasets and two real biological datasets. The results show that our method performs better than existing methods and the topology information prior can improve the result. PMID:28133490

  5. Inference of Gene Regulatory Networks Using Bayesian Nonparametric Regression and Topology Information

    Directory of Open Access Journals (Sweden)

    Yue Fan

    2017-01-01

    Full Text Available Gene regulatory networks (GRNs play an important role in cellular systems and are important for understanding biological processes. Many algorithms have been developed to infer the GRNs. However, most algorithms only pay attention to the gene expression data but do not consider the topology information in their inference process, while incorporating this information can partially compensate for the lack of reliable expression data. Here we develop a Bayesian group lasso with spike and slab priors to perform gene selection and estimation for nonparametric models. B-spline basis functions are used to capture the nonlinear relationships flexibly and penalties are used to avoid overfitting. Further, we incorporate the topology information into the Bayesian method as a prior. We present the application of our method on DREAM3 and DREAM4 datasets and two real biological datasets. The results show that our method performs better than existing methods and the topology information prior can improve the result.

  6. Evaluation of potential regulatory elements identified as DNase I hypersensitive sites in the CFTR gene

    DEFF Research Database (Denmark)

    Phylactides, M.; Rowntree, R.; Nuthall, H.

    2002-01-01

    The cystic fibrosis transmembrane conductance regulator (CFTR) gene shows a complex pattern of expression, with temporal and spatial regulation that is not accounted for by elements in the promoter. One approach to identifying the regulatory elements for CFTR is the mapping of DNase I...... hypersensitive sites (DHS) within the locus. We previously identified at least 12 clusters of DHS across the CFTR gene and here further evaluate DHS in introns 2,3,10,16,17a, 18, 20 and 21 to assess their functional importance in regulation of CFTR gene expression. Transient transfections of enhancer....../reporter constructs containing the DHS regions showed that those in introns 20 and 21 augmented the activity of the CFTR promoter. Structural analysis of the DNA sequence at the DHS suggested that only the one intron 21 might be caused by inherent DNA structures. Cell specificity of the DHS suggested a role...

  7. Constant expression of cyclooxygenase-2 gene in prostate and the lower urinary tract of estrogen-treated male rats.

    Science.gov (United States)

    Luo, C; Strauss, L; Ristimäki, A; Streng, T; Santti, R

    2001-01-01

    Expression of cyclooxygenase-2 (E. C. 1.14.99.1) in prostate and the lower urinary tract (LUT) of the neonatally estrogenized male rat has been studied by using a COX-2's PCR fragment of 724 nt spanning 3 introns and a 478nt internal standard for quantitative RT-PCR. The same fragment of 724 nt was used for RNA probe in Northern hybridization. Neonatal estrogenization (10 microg/day of diethylstilbestrol on days 1-5) had no effect on COX-2 expression in prostatic urethra, prostatic lobes, or bladder. Acute estrogen treatment of castrated animals did not induce COX-2 expression, either. In addition the differential expression of basal level of COX-2 in the different lobes of prostate in normal rat was demonstrated. Our results suggest a constant expression of COX-2 gene in prostate and the lower urinary tract of the neonatally estrogenized (neoDES) rats. The present study indicates that the increased expression of COX-2 is probably not essential for the estrogen-driven development of stromal inflammation or hyperplastic and dysplastic alterations in the prostate of neoDES rats.

  8. Genetic regulatory signatures underlying islet gene expression and type 2 diabetes

    Science.gov (United States)

    Varshney, Arushi; Scott, Laura J.; Welch, Ryan P.; Erdos, Michael R.; Chines, Peter S.; Narisu, Narisu; Albanus, Ricardo D’O.; Orchard, Peter; Wolford, Brooke N.; Kursawe, Romy; Vadlamudi, Swarooparani; Cannon, Maren E.; Didion, John P.; Hensley, John; Kirilusha, Anthony; Bonnycastle, Lori L.; Taylor, D. Leland; Watanabe, Richard; Mohlke, Karen L.; Boehnke, Michael; Collins, Francis S.; Parker, Stephen C. J.; Stitzel, Michael L.

    2017-01-01

    Genome-wide association studies (GWAS) have identified >100 independent SNPs that modulate the risk of type 2 diabetes (T2D) and related traits. However, the pathogenic mechanisms of most of these SNPs remain elusive. Here, we examined genomic, epigenomic, and transcriptomic profiles in human pancreatic islets to understand the links between genetic variation, chromatin landscape, and gene expression in the context of T2D. We first integrated genome and transcriptome variation across 112 islet samples to produce dense cis-expression quantitative trait loci (cis-eQTL) maps. Additional integration with chromatin-state maps for islets and other diverse tissue types revealed that cis-eQTLs for islet-specific genes are specifically and significantly enriched in islet stretch enhancers. High-resolution chromatin accessibility profiling using assay for transposase-accessible chromatin sequencing (ATAC-seq) in two islet samples enabled us to identify specific transcription factor (TF) footprints embedded in active regulatory elements, which are highly enriched for islet cis-eQTL. Aggregate allelic bias signatures in TF footprints enabled us de novo to reconstruct TF binding affinities genetically, which support the high-quality nature of the TF footprint predictions. Interestingly, we found that T2D GWAS loci were strikingly and specifically enriched in islet Regulatory Factor X (RFX) footprints. Remarkably, within and across independent loci, T2D risk alleles that overlap with RFX footprints uniformly disrupt the RFX motifs at high-information content positions. Together, these results suggest that common regulatory variations have shaped islet TF footprints and the transcriptome and that a confluent RFX regulatory grammar plays a significant role in the genetic component of T2D predisposition. PMID:28193859

  9. Mosaic gene network modelling identified new regulatory mechanisms in HCV infection.

    Science.gov (United States)

    Popik, Olga V; Petrovskiy, Evgeny D; Mishchenko, Elena L; Lavrik, Inna N; Ivanisenko, Vladimir A

    2016-06-15

    Modelling of gene networks is widely used in systems biology to study the functioning of complex biological systems. Most of the existing mathematical modelling techniques are useful for analysis of well-studied biological processes, for which information on rates of reactions is available. However, complex biological processes such as those determining the phenotypic traits of organisms or pathological disease processes, including pathogen-host interactions, involve complicated cross-talk between interacting networks. Furthermore, the intrinsic details of the interactions between these networks are often missing. In this study, we developed an approach, which we call mosaic network modelling, that allows the combination of independent mathematical models of gene regulatory networks and, thereby, description of complex biological systems. The advantage of this approach is that it allows us to generate the integrated model despite the fact that information on molecular interactions between parts of the model (so-called mosaic fragments) might be missing. To generate a mosaic mathematical model, we used control theory and mathematical models, written in the form of a system of ordinary differential equations (ODEs). In the present study, we investigated the efficiency of this method in modelling the dynamics of more than 10,000 simulated mosaic regulatory networks consisting of two pieces. Analysis revealed that this approach was highly efficient, as the mean deviation of the dynamics of mosaic network elements from the behaviour of the initial parts of the model was less than 10%. It turned out that for construction of the control functional, data on perturbation of one or two vertices of the mosaic piece are sufficient. Further, we used the developed method to construct a mosaic gene regulatory network including hepatitis C virus (HCV) as the first piece and the tumour necrosis factor (TNF)-induced apoptosis and NF-κB induction pathways as the second piece. Thus

  10. Recursive random forest algorithm for constructing multilayered hierarchical gene regulatory networks that govern biological pathways

    Science.gov (United States)

    Zhang, Kui; Busov, Victor; Wei, Hairong

    2017-01-01

    Background Present knowledge indicates a multilayered hierarchical gene regulatory network (ML-hGRN) often operates above a biological pathway. Although the ML-hGRN is very important for understanding how a pathway is regulated, there is almost no computational algorithm for directly constructing ML-hGRNs. Results A backward elimination random forest (BWERF) algorithm was developed for constructing the ML-hGRN operating above a biological pathway. For each pathway gene, the BWERF used a random forest model to calculate the importance values of all transcription factors (TFs) to this pathway gene recursively with a portion (e.g. 1/10) of least important TFs being excluded in each round of modeling, during which, the importance values of all TFs to the pathway gene were updated and ranked until only one TF was remained in the list. The above procedure, termed BWERF. After that, the importance values of a TF to all pathway genes were aggregated and fitted to a Gaussian mixture model to determine the TF retention for the regulatory layer immediately above the pathway layer. The acquired TFs at the secondary layer were then set to be the new bottom layer to infer the next upper layer, and this process was repeated until a ML-hGRN with the expected layers was obtained. Conclusions BWERF improved the accuracy for constructing ML-hGRNs because it used backward elimination to exclude the noise genes, and aggregated the individual importance values for determining the TFs retention. We validated the BWERF by using it for constructing ML-hGRNs operating above mouse pluripotency maintenance pathway and Arabidopsis lignocellulosic pathway. Compared to GENIE3, BWERF showed an improvement in recognizing authentic TFs regulating a pathway. Compared to the bottom-up Gaussian graphical model algorithm we developed for constructing ML-hGRNs, the BWERF can construct ML-hGRNs with significantly reduced edges that enable biologists to choose the implicit edges for experimental

  11. A relative variation-based method to unraveling gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Yali Wang

    Full Text Available Gene regulatory network (GRN reconstruction is essential in understanding the functioning and pathology of a biological system. Extensive models and algorithms have been developed to unravel a GRN. The DREAM project aims to clarify both advantages and disadvantages of these methods from an application viewpoint. An interesting yet surprising observation is that compared with complicated methods like those based on nonlinear differential equations, etc., methods based on a simple statistics, such as the so-called Z-score, usually perform better. A fundamental problem with the Z-score, however, is that direct and indirect regulations can not be easily distinguished. To overcome this drawback, a relative expression level variation (RELV based GRN inference algorithm is suggested in this paper, which consists of three major steps. Firstly, on the basis of wild type and single gene knockout/knockdown experimental data, the magnitude of RELV of a gene is estimated. Secondly, probability for the existence of a direct regulation from a perturbed gene to a measured gene is estimated, which is further utilized to estimate whether a gene can be regulated by other genes. Finally, the normalized RELVs are modified to make genes with an estimated zero in-degree have smaller RELVs in magnitude than the other genes, which is used afterwards in queuing possibilities of the existence of direct regulations among genes and therefore leads to an estimate on the GRN topology. This method can in principle avoid the so-called cascade errors under certain situations. Computational results with the Size 100 sub-challenges of DREAM3 and DREAM4 show that, compared with the Z-score based method, prediction performances can be substantially improved, especially the AUPR specification. Moreover, it can even outperform the best team of both DREAM3 and DREAM4. Furthermore, the high precision of the obtained most reliable predictions shows that the suggested algorithm may be

  12. The MYB98 subcircuit of the synergid gene regulatory network includes genes directly and indirectly regulated by MYB98.

    Science.gov (United States)

    Punwani, Jayson A; Rabiger, David S; Lloyd, Alan; Drews, Gary N

    2008-08-01

    The female gametophyte contains two synergid cells that play a role in many steps of the angiosperm reproductive process, including pollen tube guidance. At their micropylar poles, the synergid cells have a thickened and elaborated cell wall: the filiform apparatus that is thought to play a role in the secretion of the pollen tube attractant(s). MYB98 regulates an important subcircuit of the synergid gene regulatory network (GRN) that functions to activate the expression of genes required for pollen tube guidance and filiform apparatus formation. The MYB98 subcircuit comprises at least 83 downstream genes, including 48 genes within four gene families (CRP810, CRP3700, CRP3730 and CRP3740) that encode Cys-rich proteins. We show that the 11 CRP3700 genes, which include DD11 and DD18, are regulated by a common cis-element, GTAACNT, and that a multimer of this sequence confers MYB98-dependent synergid expression. The GTAACNT element contains the MYB98-binding site identified in vitro, suggesting that the 11 CRP3700 genes are direct targets of MYB98. We also show that five of the CRP810 genes, which include DD2, lack a functional GTAACNT element, suggesting that they are not directly regulated by MYB98. In addition, we show that the five CRP810 genes are regulated by the cis-element AACGT, and that a multimer of this sequence confers synergid expression. Together, these results suggest that the MYB98 branch of the synergid GRN is multi-tiered and, therefore, contains at least one additional downstream transcription factor.

  13. Comparative analysis of RNA regulatory elements of amino acid metabolism genes in Actinobacteria

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    Gelfand Mikhail S

    2005-10-01

    Full Text Available Abstract Background Formation of alternative structures in mRNA in response to external stimuli, either direct or mediated by proteins or other RNAs, is a major mechanism of regulation of gene expression in bacteria. This mechanism has been studied in detail using experimental and computational approaches in proteobacteria and Firmicutes, but not in other groups of bacteria. Results Comparative analysis of amino acid biosynthesis operons in Actinobacteria resulted in identification of conserved regions upstream of several operons. Classical attenuators were predicted upstream of trp operons in Corynebacterium spp. and Streptomyces spp., and trpS and leuS genes in some Streptomyces spp. Candidate leader peptides with terminators were observed upstream of ilvB genes in Corynebacterium spp., Mycobacterium spp. and Streptomyces spp. Candidate leader peptides without obvious terminators were found upstream of cys operons in Mycobacterium spp. and several other species. A conserved pseudoknot (named LEU element was identified upstream of leuA operons in most Actinobacteria. Finally, T-boxes likely involved in the regulation of translation initiation were observed upstream of ileS genes from several Actinobacteria. Conclusion The metabolism of tryptophan, cysteine and leucine in Actinobacteria seems to be regulated on the RNA level. In some cases the mechanism is classical attenuation, but in many cases some components of attenuators are missing. The most interesting case seems to be the leuA operon preceded by the LEU element that may fold into a conserved pseudoknot or an alternative structure. A LEU element has been observed in a transposase gene from Bifidobacterium longum, but it is not conserved in genes encoding closely related transposases despite a very high level of protein similarity. One possibility is that the regulatory region of the leuA has been co-opted from some element involved in transposition. Analysis of phylogenetic patterns

  14. Divergence in cis-regulatory sequences surrounding the opsin gene arrays of African cichlid fishes

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    Streelman J Todd

    2011-05-01

    Full Text Available Abstract Background Divergence within cis-regulatory sequences may contribute to the adaptive evolution of gene expression, but functional alleles in these regions are difficult to identify without abundant genomic resources. Among African cichlid fishes, the differential expression of seven opsin genes has produced adaptive differences in visual sensitivity. Quantitative genetic analysis suggests that cis-regulatory alleles near the SWS2-LWS opsins may contribute to this variation. Here, we sequence BACs containing the opsin genes of two cichlids, Oreochromis niloticus and Metriaclima zebra. We use phylogenetic footprinting and shadowing to examine divergence in conserved non-coding elements, promoter sequences, and 3'-UTRs surrounding each opsin in search of candidate cis-regulatory sequences that influence cichlid opsin expression. Results We identified 20 conserved non-coding elements surrounding the opsins of cichlids and other teleosts, including one known enhancer and a retinal microRNA. Most conserved elements contained computationally-predicted binding sites that correspond to transcription factors that function in vertebrate opsin expression; O. niloticus and M. zebra were significantly divergent in two of these. Similarly, we found a large number of relevant transcription factor binding sites within each opsin's proximal promoter, and identified five opsins that were considerably divergent in both expression and the number of transcription factor binding sites shared between O. niloticus and M. zebra. We also found several microRNA target sites within the 3'-UTR of each opsin, including two 3'-UTRs that differ significantly between O. niloticus and M. zebra. Finally, we examined interspecific divergence among 18 phenotypically diverse cichlids from Lake Malawi for one conserved non-coding element, two 3'-UTRs, and five opsin proximal promoters. We found that all regions were highly conserved with some evidence of CRX transcription

  15. Use of lactobacilli and their pheromone-based regulatory mechanism in gene expression and drug delivery.

    Science.gov (United States)

    Diep, D B; Mathiesen, G; Eijsink, V G H; Nes, I F

    2009-01-01

    Lactobacilli are common microorganisms in diverse vegetables and meat products and several of these are also indigenous inhabitants in the gastro-intestinal (GI) tract of humans and animals where they are believed to have health promoting effects on the host. One of the highly appreciated probiotic effects is their ability to inhibit the growth of pathogens by producing antimicrobial peptides, so-called bacteriocins. Production of some bacteriocins has been shown to be strictly regulated through a quorum-sensing based mechanism mediated by a secreted peptide-pheromone (also called induction peptide; IP), a membrane-located sensor (histidine protein kinase; HPK) and a cytoplasmic response regulator (RR). The interaction between an IP and its sensor, which is highly specific, leads to activation of the cognate RR which in turn binds to regulated promoters and activates gene expression. The HPKs and RRs are built up by conserved modules, and the signalling between them within a network is efficient and directional, and can easily be activated by exogenously added synthetic IPs. Consequently, components from such regulatory networks have successfully been exploited in construction of a number of inducible gene expression systems. In this review, we discuss some well-characterised quorum sensing networks involved in bacteriocin production in lactobacilli, with special focus on the use of the regulatory components in gene expression and on lactobacilli as potential delivery vehicle for therapeutic and vaccine purposes.

  16. The underlying molecular and network level mechanisms in the evolution of robustness in gene regulatory networks.

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    Mario Pujato

    Full Text Available Gene regulatory networks show robustness to perturbations. Previous works identified robustness as an emergent property of gene network evolution but the underlying molecular mechanisms are poorly understood. We used a multi-tier modeling approach that integrates molecular sequence and structure information with network architecture and population dynamics. Structural models of transcription factor-DNA complexes are used to estimate relative binding specificities. In this model, mutations in the DNA cause changes on two levels: (a at the sequence level in individual binding sites (modulating binding specificity, and (b at the network level (creating and destroying binding sites. We used this model to dissect the underlying mechanisms responsible for the evolution of robustness in gene regulatory networks. Results suggest that in sparse architectures (represented by short promoters, a mixture of local-sequence and network-architecture level changes are exploited. At the local-sequence level, robustness evolves by decreasing the probabilities of both the destruction of existent and generation of new binding sites. Meanwhile, in highly interconnected architectures (represented by long promoters, robustness evolves almost entirely via network level changes, deleting and creating binding sites that modify the network architecture.

  17. Patterns of Positive Selection of the Myogenic Regulatory Factor Gene Family in Vertebrates

    Science.gov (United States)

    Zhao, Xiao; Yu, Qi; Huang, Ling; Liu, Qing-Xin

    2014-01-01

    The functional divergence of transcriptional factors is critical in the evolution of transcriptional regulation. However, the mechanism of functional divergence among these factors remains unclear. Here, we performed an evolutionary analysis for positive selection in members of the myogenic regulatory factor (MRF) gene family of vertebrates. We selected 153 complete vertebrate MRF nucleotide sequences from our analyses, which revealed substantial evidence of positive selection. Here, we show that sites under positive selection were more frequently detected and identified from the genes encoding the myogenic differentiation factors (MyoG and Myf6) than the genes encoding myogenic determination factors (Myf5 and MyoD). Additionally, the functional divergence within the myogenic determination factors or differentiation factors was also under positive selection pressure. The positive selection sites were more frequently detected from MyoG and MyoD than Myf6 and Myf5, respectively. Amino acid residues under positive selection were identified mainly in their transcription activation domains and on the surface of protein three-dimensional structures. These data suggest that the functional gain and divergence of myogenic regulatory factors were driven by distinct positive selection of their transcription activation domains, whereas the function of the DNA binding domains was conserved in evolution. Our study evaluated the mechanism of functional divergence of the transcriptional regulation factors within a family, whereby the functions of their transcription activation domains diverged under positive selection during evolution. PMID:24651579

  18. Shaping skeletal growth by modular regulatory elements in the Bmp5 gene.

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    Catherine Guenther

    2008-12-01

    Full Text Available Cartilage and bone are formed into a remarkable range of shapes and sizes that underlie many anatomical adaptations to different lifestyles in vertebrates. Although the morphological blueprints for individual cartilage and bony structures must somehow be encoded in the genome, we currently know little about the detailed genomic mechanisms that direct precise growth patterns for particular bones. We have carried out large-scale enhancer surveys to identify the regulatory architecture controlling developmental expression of the mouse Bmp5 gene, which encodes a secreted signaling molecule required for normal morphology of specific skeletal features. Although Bmp5 is expressed in many skeletal precursors, different enhancers control expression in individual bones. Remarkably, we show here that different enhancers also exist for highly restricted spatial subdomains along the surface of individual skeletal structures, including ribs and nasal cartilages. Transgenic, null, and regulatory mutations confirm that these anatomy-specific sequences are sufficient to trigger local changes in skeletal morphology and are required for establishing normal growth rates on separate bone surfaces. Our findings suggest that individual bones are composite structures whose detailed growth patterns are built from many smaller lineage and gene expression domains. Individual enhancers in BMP genes provide a genomic mechanism for controlling precise growth domains in particular cartilages and bones, making it possible to separately regulate skeletal anatomy at highly specific locations in the body.

  19. Glutathione S-transferase Ya subunit gene: identification of regulatory elements required for basal level and inducible expression.

    OpenAIRE

    Telakowski-Hopkins, C A; King, R. G.; Pickett, C B

    1988-01-01

    The function of the 5'-flanking region of a rat glutathione S-transferase Ya subunit structural gene has been examined in homologous and heterologous cells. By using the 5'-flanking region of the Ya subunit gene fused to the structural gene encoding chloramphenicol acetyltransferase, we have identified two cis-acting regulatory elements in the upstream region of the Ya gene. One element is required for maximum basal level expression in homologous cells, whereas maximum basal level expression ...

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

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    Min Kyung Sung

    2014-12-01

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

  1. Tumor-suppressor genes, cell cycle regulatory checkpoints, and the skin

    Directory of Open Access Journals (Sweden)

    Ana Maria Abreu Velez

    2015-01-01

    Full Text Available The cell cycle (or cell-division cycle is a series of events that take place in a cell, leading to its division and duplication. Cell division requires cell cycle checkpoints (CPs that are used by the cell to both monitor and regulate the progress of the cell cycle. Tumor-suppressor genes (TSGs or antioncogenes are genes that protect the cell from a single event or multiple events leading to cancer. When these genes mutate, the cell can progress to a cancerous state. We aimed to perform a narrative review, based on evaluation of the manuscripts published in MEDLINE-indexed journals using the Medical Subject Headings (MeSH terms "tumor suppressor′s genes," "skin," and "cell cycle regulatory checkpoints." We aimed to review the current concepts regarding TSGs, CPs, and their association with selected cutaneous diseases. It is important to take into account that in some cell cycle disorders, multiple genetic abnormalities may occur simultaneously. These abnormalities may include intrachromosomal insertions, unbalanced division products, recombinations, reciprocal deletions, and/or duplication of the inserted segments or genes; thus, these presentations usually involve several genes. Due to their complexity, these disorders require specialized expertise for proper diagnosis, counseling, personal and family support, and genetic studies. Alterations in the TSGs or CP regulators may occur in many benign skin proliferative disorders, neoplastic processes, and genodermatoses.

  2. A novel regulatory element between the human FGA and FGG genes.

    Science.gov (United States)

    Fish, Richard J; Neerman-Arbez, Marguerite

    2012-09-01

    High circulating fibrinogen levels correlate with cardiovascular disease (CVD) risk. Fibrinogen levels vary between people and also change in response to physiological and environmental stimuli. A modest proportion of the variation in fibrinogen levels can be explained by genotype, inferring that variation in genomic sequences that regulate the fibrinogen genes ( FGA , FGB and FGG ) may affect hepatic fibrinogen production and perhaps CVD risk. We previously identified a conserved liver enhancer in the fibrinogen gene cluster (CNC12), between FGB and FGA . Genome-wide Chromatin immunoprecipitation-sequencing (ChIP-seq) demonstrated that transcription factors which bind fibrinogen gene promoters also interact with CNC12, as well as two potential fibrinogen enhancers (PFE), between FGA and FGG . Here we show that one of the PFE sequences has potent hepatocyte enhancer activity. Using a luciferase reporter gene system, we found that PFE2 enhances minimal promoter- and FGA promoter-driven gene expression in hepatoma cells, regardless of its orientation with respect to the promoters. A region within PFE2 bears a short series of conserved nucleotides which maintain enhancer activity without flanking sequence. We also demonstrate that PFE2 is a liver enhancer in vivo, driving enhanced green fluorescent protein expression in transgenic zebrafish larval livers. Our study shows that combining public domain ChIP-seq data with in vitro and in vivo functional tests can identify novel fibrinogen gene cluster regulatory sequences. Variation in such elements could affect fibrinogen production and influence CVD risk.

  3. Refining ensembles of predicted gene regulatory networks based on characteristic interaction sets.

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    Lukas Windhager

    Full Text Available Different ensemble voting approaches have been successfully applied for reverse-engineering of gene regulatory networks. They are based on the assumption that a good approximation of true network structure can be derived by considering the frequencies of individual interactions in a large number of predicted networks. Such approximations are typically superior in terms of prediction quality and robustness as compared to considering a single best scoring network only. Nevertheless, ensemble approaches only work well if the predicted gene regulatory networks are sufficiently similar to each other. If the topologies of predicted networks are considerably different, an ensemble of all networks obscures interesting individual characteristics. Instead, networks should be grouped according to local topological similarities and ensemble voting performed for each group separately. We argue that the presence of sets of co-occurring interactions is a suitable indicator for grouping predicted networks. A stepwise bottom-up procedure is proposed, where first mutual dependencies between pairs of interactions are derived from predicted networks. Pairs of co-occurring interactions are subsequently extended to derive characteristic interaction sets that distinguish groups of networks. Finally, ensemble voting is applied separately to the resulting topologically similar groups of networks to create distinct group-ensembles. Ensembles of topologically similar networks constitute distinct hypotheses about the reference network structure. Such group-ensembles are easier to interpret as their characteristic topology becomes clear and dependencies between interactions are known. The availability of distinct hypotheses facilitates the design of further experiments to distinguish between plausible network structures. The proposed procedure is a reasonable refinement step for non-deterministic reverse-engineering applications that produce a large number of candidate

  4. Mutations of the SLIT2–ROBO2 pathway genes SLIT2 and SRGAP1 confer risk for congenital anomalies of the kidney and urinary tract

    NARCIS (Netherlands)

    Hwang, Daw Yang; Kohl, Stefan; Fan, Xueping; Vivante, Asaf; Chan, Stefanie; Dworschak, Gabriel C.; Schulz, Julian; van Eerde, Albertien M.; Hilger, Alina C.; Gee, Heon Yung; Pennimpede, Tracie; Herrmann, Bernhard G.; van de Hoek, Glenn; Renkema, Kirsten Y.; Schell, Christoph; Huber, Tobias B.; Reutter, Heiko M.; Soliman, Neveen A.; Stajic, Natasa; Bogdanovic, Radovan; Kehinde, Elijah O.; Lifton, Richard P.; Tasic, Velibor; Lu, Weining; Hildebrandt, Friedhelm

    2015-01-01

    Congenital anomalies of the kidney and urinary tract (CAKUT) account for 40–50 % of chronic kidney disease that manifests in the first two decades of life. Thus far, 31 monogenic causes of isolated CAKUT have been described, explaining ~12 % of cases. To identify additional CAKUT-causing genes, we p

  5. Systematic Approach to Computational Design of Gene Regulatory Networks with Information Processing Capabilities.

    Science.gov (United States)

    Moskon, Miha; Mraz, Miha

    2014-01-01

    We present several measures that can be used in de novo computational design of biological systems with information processing capabilities. Their main purpose is to objectively evaluate the behavior and identify the biological information processing structures with the best dynamical properties. They can be used to define constraints that allow one to simplify the design of more complex biological systems. These measures can be applied to existent computational design approaches in synthetic biology, i.e., rational and automatic design approaches. We demonstrate their use on a) the computational models of several basic information processing structures implemented with gene regulatory networks and b) on a modular design of a synchronous toggle switch.

  6. MicroRNA Gene Regulatory Networks in Peripheral Nerve Sheath Tumors

    Science.gov (United States)

    2012-09-01

    NUMBER (include area code) Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std . Z39.18 MicroRNA Gene Regulatory Networks in Peripheral Nerve...Department of Surgery, University of Minnesota, 11-212 Moos Tower (Mail Code: MMC 195), 515 Delaware St, S.E, Minneapolis, MN 55455, USA e-mail...malignant bone tumor with an incidence of 4–5 cases per million. It arises from the metaphysis of the long bones of adolescents and young adults. Two

  7. PyPanda: a Python package for gene regulatory network reconstruction

    Science.gov (United States)

    van IJzendoorn, David G.P.; Glass, Kimberly; Quackenbush, John; Kuijjer, Marieke L.

    2016-01-01

    Summary: PANDA (Passing Attributes between Networks for Data Assimilation) is a gene regulatory network inference method that uses message-passing to integrate multiple sources of ‘omics data. PANDA was originally coded in C ++. In this application note we describe PyPanda, the Python version of PANDA. PyPanda runs considerably faster than the C ++ version and includes additional features for network analysis. Availability and implementation: The open source PyPanda Python package is freely available at http://github.com/davidvi/pypanda. Contact: mkuijjer@jimmy.harvard.edu or d.g.p.van_ijzendoorn@lumc.nl PMID:27402905

  8. Overproduction of lactimidomycin by cross-overexpression of genes encoding Streptomyces antibiotic regulatory proteins.

    Science.gov (United States)

    Zhang, Bo; Yang, Dong; Yan, Yijun; Pan, Guohui; Xiang, Wensheng; Shen, Ben

    2016-03-01

    The glutarimide-containing polyketides represent a fascinating class of natural products that exhibit a multitude of biological activities. We have recently cloned and sequenced the biosynthetic gene clusters for three members of the glutarimide-containing polyketides-iso-migrastatin (iso-MGS) from Streptomyces platensis NRRL 18993, lactimidomycin (LTM) from Streptomyces amphibiosporus ATCC 53964, and cycloheximide (CHX) from Streptomyces sp. YIM56141. Comparative analysis of the three clusters identified mgsA and chxA, from the mgs and chx gene clusters, respectively, that were predicted to encode the PimR-like Streptomyces antibiotic regulatory proteins (SARPs) but failed to reveal any regulatory gene from the ltm gene cluster. Overexpression of mgsA or chxA in S. platensis NRRL 18993, Streptomyces sp. YIM56141 or SB11024, and a recombinant strain of Streptomyces coelicolor M145 carrying the intact mgs gene cluster has no significant effect on iso-MGS or CHX production, suggesting that MgsA or ChxA regulation may not be rate-limiting for iso-MGS and CHX production in these producers. In contrast, overexpression of mgsA or chxA in S. amphibiosporus ATCC 53964 resulted in a significant increase in LTM production, with LTM titer reaching 106 mg/L, which is five-fold higher than that of the wild-type strain. These results support MgsA and ChxA as members of the SARP family of positive regulators for the iso-MGS and CHX biosynthetic machinery and demonstrate the feasibility to improve glutarimide-containing polyketide production in Streptomyces strains by exploiting common regulators.

  9. Association between polymorphisms in arsenic metabolism genes and urinary arsenic methylation profiles in girls and boys chronically exposed to arsenic.

    Science.gov (United States)

    Recio-Vega, Rogelio; González-Cortes, Tania; Olivas-Calderón, Edgar; Clark Lantz, R; Jay Gandolfi, A; Michel-Ramirez, Gladis

    2016-08-01

    Disease manifestations or susceptibilities often differ among individuals exposed to the same concentrations of arsenic (As). These differences have been associated with several factors including As metabolism, sex, age, genetic variants, nutritional status, smoking, and others. This study evaluated the associations between four As metabolism-related gene polymorphisms/null genotypes with urinary As methylation profiles in girls and boys chronically exposed to As. In a total of 332 children aged 6-12 years, the frequency of AS3MT, GSTO1, GSTT1, and GSTM1 polymorphisms/null genotypes and As urinary metabolites were measured. The results revealed that total As and monomethyl metabolites of As (MMA) levels were higher in boys than in girls. No differences in the frequency of the evaluated polymorphisms were found between girls and boys. In AS3MT-Met287Thr carriers, %MMA levels were higher and second methylation levels (defined as dimethylarsinic acid divided by MMA) were lower. In children with the GSTM1 null genotype, second methylation levels were higher. In boys, a positive association between the AS3MT-Met287Thr polymorphism with %MMA and between the GSTO1-Glu155del and As(v) was found; whereas, a negative relationship was identified between AS3MT-Met287Thr and second methylation profiles. In girls, a positive association was found between the GSTO1-Ala140Asp polymorphism with second methylation levels. In conclusion, our data indicate that gender, high As exposure levels, and polymorphisms in the evaluated genes negatively influenced As metabolism. Environ. Mol. Mutagen. 57:516-525, 2016. © 2016 Wiley Periodicals, Inc.

  10. Conserved cis-regulatory modules in promoters of genes encoding wheat high-molecular-weight glutenin subunits.

    Science.gov (United States)

    Ravel, Catherine; Fiquet, Samuel; Boudet, Julie; Dardevet, Mireille; Vincent, Jonathan; Merlino, Marielle; Michard, Robin; Martre, Pierre

    2014-01-01

    The concentration and composition of the gliadin and glutenin seed storage proteins (SSPs) in wheat flour are the most important determinants of its end-use value. In cereals, the synthesis of SSPs is predominantly regulated at the transcriptional level by a complex network involving at least five cis-elements in gene promoters. The high-molecular-weight glutenin subunits (HMW-GS) are encoded by two tightly linked genes located on the long arms of group 1 chromosomes. Here, we sequenced and annotated the HMW-GS gene promoters of 22 electrophoretic wheat alleles to identify putative cis-regulatory motifs. We focused on 24 motifs known to be involved in SSP gene regulation. Most of them were identified in at least one HMW-GS gene promoter sequence. A common regulatory framework was observed in all the HMW-GS gene promoters, as they shared conserved cis-regulatory modules (CCRMs) including all the five motifs known to regulate the transcription of SSP genes. This common regulatory framework comprises a composite box made of the GATA motifs and GCN4-like Motifs (GLMs) and was shown to be functional as the GLMs are able to bind a bZIP transcriptional factor SPA (Storage Protein Activator). In addition to this regulatory framework, each HMW-GS gene promoter had additional motifs organized differently. The promoters of most highly expressed x-type HMW-GS genes contain an additional box predicted to bind R2R3-MYB transcriptional factors. However, the differences in annotation between promoter alleles could not be related to their level of expression. In summary, we identified a common modular organization of HMW-GS gene promoters but the lack of correlation between the cis-motifs of each HMW-GS gene promoter and their level of expression suggests that other cis-elements or other mechanisms regulate HMW-GS gene expression.

  11. Dynamic regulatory interactions of Polycomb group genes: MEDEA autoregulation is required for imprinted gene expression in Arabidopsis.

    Science.gov (United States)

    Baroux, Célia; Gagliardini, Valeria; Page, Damian R; Grossniklaus, Ueli

    2006-05-01

    The imprinted Arabidopsis Polycomb group (PcG) gene MEDEA (MEA), which is homologous to Enhancer of Zeste [E(Z)], is maternally required for normal seed development. Here we show that, unlike known mammalian imprinted genes, MEA regulates its own imprinted expression: It down-regulates the maternal allele around fertilization and maintains the paternal allele silent later during seed development. Autorepression of the maternal MEA allele is direct and independent of the MEA-FIE (FERTILIZATION-INDEPENDENT ENDOSPERM) PcG complex, which is similar to the E(Z)-ESC (Extra sex combs) complex of animals, suggesting a novel mechanism. A complex network of cross-regulatory interactions among the other known members of the MEA-FIE PcG complex implies distinct functions that are dynamically regulated during reproduction.

  12. Ancestral regulatory circuits governing ectoderm patterning downstream of Nodal and BMP2/4 revealed by gene regulatory network analysis in an echinoderm.

    Directory of Open Access Journals (Sweden)

    Alexandra Saudemont

    Full Text Available Echinoderms, which are phylogenetically related to vertebrates and produce large numbers of transparent embryos that can be experimentally manipulated, offer many advantages for the analysis of the gene regulatory networks (GRN regulating germ layer formation. During development of the sea urchin embryo, the ectoderm is the source of signals that pattern all three germ layers along the dorsal-ventral axis. How this signaling center controls patterning and morphogenesis of the embryo is not understood. Here, we report a large-scale analysis of the GRN deployed in response to the activity of this signaling center in the embryos of the Mediterranean sea urchin Paracentrotus lividus, in which studies with high spatial resolution are possible. By using a combination of in situ hybridization screening, overexpression of mRNA, recombinant ligand treatments, and morpholino-based loss-of-function studies, we identified a cohort of transcription factors and signaling molecules expressed in the ventral ectoderm, dorsal ectoderm, and interposed neurogenic ("ciliary band" region in response to the known key signaling molecules Nodal and BMP2/4 and defined the epistatic relationships between the most important genes. The resultant GRN showed a number of striking features. First, Nodal was found to be essential for the expression of all ventral and dorsal marker genes, and BMP2/4 for all dorsal genes. Second, goosecoid was identified as a central player in a regulatory sub-circuit controlling mouth formation, while tbx2/3 emerged as a critical factor for differentiation of the dorsal ectoderm. Finally, and unexpectedly, a neurogenic ectoderm regulatory circuit characterized by expression of "ciliary band" genes was triggered in the absence of TGF beta signaling. We propose a novel model for ectoderm regionalization, in which neural ectoderm is the default fate in the absence of TGF beta signaling, and suggest that the stomodeal and neural subcircuits that we

  13. Enriching regulatory networks by bootstrap learning using optimised GO-based gene similarity and gene links mined from PubMed abstracts

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, Ronald C.; Sanfilippo, Antonio P.; McDermott, Jason E.; Baddeley, Robert L.; Riensche, Roderick M.; Jensen, Russell S.; Verhagen, Marc; Pustejovsky, James

    2011-02-18

    Transcriptional regulatory networks are being determined using “reverse engineering” methods that infer connections based on correlations in gene state. Corroboration of such networks through independent means such as evidence from the biomedical literature is desirable. Here, we explore a novel approach, a bootstrapping version of our previous Cross-Ontological Analytic method (XOA) that can be used for semi-automated annotation and verification of inferred regulatory connections, as well as for discovery of additional functional relationships between the genes. First, we use our annotation and network expansion method on a biological network learned entirely from the literature. We show how new relevant links between genes can be iteratively derived using a gene similarity measure based on the Gene Ontology that is optimized on the input network at each iteration. Second, we apply our method to annotation, verification, and expansion of a set of regulatory connections found by the Context Likelihood of Relatedness algorithm.

  14. Regulatory Factor X (RFX)-mediated transcriptional rewiring of ciliary genes in animals.

    Science.gov (United States)

    Piasecki, Brian P; Burghoorn, Jan; Swoboda, Peter

    2010-07-20

    Cilia were present in the last eukaryotic common ancestor (LECA) and were retained by most organisms spanning all extant eukaryotic lineages, including organisms in the Unikonta (Amoebozoa, fungi, choanoflagellates, and animals), Archaeplastida, Excavata, Chromalveolata, and Rhizaria. In certain animals, including humans, ciliary gene regulation is mediated by Regulatory Factor X (RFX) transcription factors (TFs). RFX TFs bind X-box promoter motifs and thereby positively regulate >50 ciliary genes. Though RFX-mediated ciliary gene regulation has been studied in several bilaterian animals, little is known about the evolutionary conservation of ciliary gene regulation. Here, we explore the evolutionary relationships between RFX TFs and cilia. By sampling the genome sequences of >120 eukaryotic organisms, we show that RFX TFs are exclusively found in unikont organisms (whether ciliated or not), but are completely absent from the genome sequences of all nonunikont organisms (again, whether ciliated or not). Sampling the promoter sequences of 12 highly conserved ciliary genes from 23 diverse unikont and nonunikont organisms further revealed that phylogenetic footprints of X-box promoter motif sequences are found exclusively in ciliary genes of certain animals. Thus, there is no correlation between cilia/ciliary genes and the presence or absence of RFX TFs and X-box promoter motifs in nonanimal unikont and in nonunikont organisms. These data suggest that RFX TFs originated early in the unikont lineage, distinctly after cilia evolved. The evolutionary model that best explains these observations indicates that the transcriptional rewiring of many ciliary genes by RFX TFs occurred early in the animal lineage.

  15. Characterization of a regulatory gene, aveR, for the biosynthesis of avermectin in Streptomyces avermitilis.

    Science.gov (United States)

    Kitani, Shigeru; Ikeda, Haruo; Sakamoto, Takako; Noguchi, Satoru; Nihira, Takuya

    2009-04-01

    Avermectin is an important macrocyclic polyketide produced by Streptomyces avermitilis and widely used as an anthelmintic agent in the medical, veterinary, and agricultural fields. The avermectin biosynthetic gene cluster contains aveR, which belongs to the LAL-family of regulatory genes. In this study, aveR was inactivated by gene replacement in the chromosome of S. avermitilis, resulting in the complete loss of avermectin production. The aveR mutant was unable to convert an avermectin intermediate to any avermectin derivatives, and complementation by intact aveR and its proper upstream region restored avermectin production in the mutant, suggesting that AveR is a positive regulator controlling the expression of both polyketide biosynthetic genes and postpolyketide modification genes in avermectin biosynthesis. Despite the general concept that an increased amount of a positive pathway-specific regulator leads to higher production, a higher amount of aveR resulted in complete loss of avermectin, indicating that there is a maximum threshold concentration of aveR for the production of avermectin.

  16. Majority Rules with Random Tie-Breaking in Boolean Gene Regulatory Networks

    Science.gov (United States)

    Chaouiya, Claudine; Ourrad, Ouerdia; Lima, Ricardo

    2013-01-01

    We consider threshold Boolean gene regulatory networks, where the update function of each gene is described as a majority rule evaluated among the regulators of that gene: it is turned ON when the sum of its regulator contributions is positive (activators contribute positively whereas repressors contribute negatively) and turned OFF when this sum is negative. In case of a tie (when contributions cancel each other out), it is often assumed that the gene keeps it current state. This framework has been successfully used to model cell cycle control in yeast. Moreover, several studies consider stochastic extensions to assess the robustness of such a model. Here, we introduce a novel, natural stochastic extension of the majority rule. It consists in randomly choosing the next value of a gene only in case of a tie. Hence, the resulting model includes deterministic and probabilistic updates. We present variants of the majority rule, including alternate treatments of the tie situation. Impact of these variants on the corresponding dynamical behaviours is discussed. After a thorough study of a class of two-node networks, we illustrate the interest of our stochastic extension using a published cell cycle model. In particular, we demonstrate that steady state analysis can be rigorously performed and can lead to effective predictions; these relate for example to the identification of interactions whose addition would ensure that a specific state is absorbing. PMID:23922761

  17. Majority rules with random tie-breaking in Boolean gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Claudine Chaouiya

    Full Text Available We consider threshold boolean gene regulatory networks, where the update function of each gene is described as a majority rule evaluated among the regulators of that gene: it is turned ON when the sum of its regulator contributions is positive (activators contribute positively whereas repressors contribute negatively and turned OFF when this sum is negative. In case of a tie (when contributions cancel each other out, it is often assumed that the gene keeps it current state. This framework has been successfully used to model cell cycle control in yeast. Moreover, several studies consider stochastic extensions to assess the robustness of such a model. Here, we introduce a novel, natural stochastic extension of the majority rule. It consists in randomly choosing the next value of a gene only in case of a tie. Hence, the resulting model includes deterministic and probabilistic updates. We present variants of the majority rule, including alternate treatments of the tie situation. Impact of these variants on the corresponding dynamical behaviours is discussed. After a thorough study of a class of two-node networks, we illustrate the interest of our stochastic extension using a published cell cycle model. In particular, we demonstrate that steady state analysis can be rigorously performed and can lead to effective predictions; these relate for example to the identification of interactions whose addition would ensure that a specific state is absorbing.

  18. Gene expression profiling reveals large regulatory switches between succeeding stipe stages in Volvariella volvacea.

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    Yongxin Tao

    Full Text Available The edible mushroom Volvariella volvacea is an important crop in Southeast Asia and is predominantly harvested in the egg stage. One of the main factors that negatively affect its yield and value is the rapid transition from the egg to the elongation stage, which has a decreased commodity value and shelf life. To improve our understanding of the changes during stipe development and the transition from egg to elongation stage in particular, we analyzed gene transcription in stipe tissue of V. volvacea using 3'-tag based digital expression profiling. Stipe development turned out to be fairly complex with high numbers of expressed genes, and regulation of stage differences is mediated mainly by changes in expression levels of genes, rather than on/off modulation. Most explicit is the strong up-regulation of cell division from button to egg, and the very strong down-regulation hereof from egg to elongation, that continues in the maturation stage. Button and egg share cell division as means of growth, followed by a major developmental shift towards rapid stipe elongation based on cell extension as demonstrated by inactivation of cell division throughout elongation and maturation. Examination of regulatory genes up-regulated from egg to elongation identified three potential high upstream regulators for this switch. The new insights in stipe dynamics, together with a series of new target genes, will provide a sound base for further studies on the developmental mechanisms of mushroom stipes and the switch from egg to elongation in V. volvacea in particular.

  19. High Prevalence of Iron Acquisition Genes Among Acinetobacter baumannii Strains Isolated From Patients With Urinary Tract Infections in Southeast of Iran

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    Ali Abdi

    2015-11-01

    Full Text Available Background Acinetobacter baumannii is the most clinically prominent species of the Acinetobacter genus and is commonly found in hospital environments. In mammals, the iron element is virtually unavailable to invading bacteria, being mainly incorporated into iron transport and storage proteins. Therefore, iron acquisition systems are important factors for the pathogenicity of A. baumannii strains. Objectives The aim of this study was to determine the frequency of iron acquisition genes among A. baumannii isolates, collected from patients with urinary tract infections, for the first time in Iran. Patients and Methods A total of 100 A. baumannii isolates were collected from patients with urinary tract infections in Zabol, southeast of Iran. All isolates were evaluated to determine the prevalence of iron acquisition genes, including tonB (TonB-dependent receptor, barA (acinetobactin ABC transporter, feoB (ferrous iron transport protein B, entA (acinetobactin siderophore precursor, A1S_2563 (siderophore-interacting protein, and hemO (heme oxygenase using the multiplex polymerase chain reaction (PCR method. Results A high prevalence of genes encoding iron acquisition systems were observed in A. baumannii isolates. The frequency of tonB, barA, feoB, entA, A1S_2563, and hemO genes were 85, 97, 99, 98, 99, and 95%, respectively. Based on the distribution of the various iron acquisition genes, all the studied isolates exhibited seven gene profile patterns. Conclusions This is the first report on the prevalence of iron acquisition genes among A. baumannii isolates collected from patients with urinary tract infections. The high prevalence of iron acquisition genes in A. baumannii isolates suggests that these virulence factors play an important role in the development of urinary tract infections.

  20. What makes the lac-pathway switch : identifying the fluctuations that trigger phenotype switching in gene regulatory systems

    NARCIS (Netherlands)

    Bhogale, Prasanna M; Sorg, Robin A; Veening, Jan-Willem; Berg, Johannes

    2014-01-01

    Multistable gene regulatory systems sustain different levels of gene expression under identical external conditions. Such multistability is used to encode phenotypic states in processes including nutrient uptake and persistence in bacteria, fate selection in viral infection, cell-cycle control and d

  1. Gene Regulatory Mechanisms Underlying the Spatial and Temporal Regulation of Target-Dependent Gene Expression in Drosophila Neurons.

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    Anthony J E Berndt

    2015-12-01

    Full Text Available Neuronal differentiation often requires target-derived signals from the cells they innervate. These signals typically activate neural subtype-specific genes, but the gene regulatory mechanisms remain largely unknown. Highly restricted expression of the FMRFa neuropeptide in Drosophila Tv4 neurons requires target-derived BMP signaling and a transcription factor code that includes Apterous. Using integrase transgenesis of enhancer reporters, we functionally dissected the Tv4-enhancer of FMRFa within its native cellular context. We identified two essential but discrete cis-elements, a BMP-response element (BMP-RE that binds BMP-activated pMad, and a homeodomain-response element (HD-RE that binds Apterous. These cis-elements have low activity and must be combined for Tv4-enhancer activity. Such combinatorial activity is often a mechanism for restricting expression to the intersection of cis-element spatiotemporal activities. However, concatemers of the HD-RE and BMP-RE cis-elements were found to independently generate the same spatiotemporal expression as the Tv4-enhancer. Thus, the Tv4-enhancer atypically combines two low-activity cis-elements that confer the same output from distinct inputs. The activation of target-dependent genes is assumed to 'wait' for target contact. We tested this directly, and unexpectedly found that premature BMP activity could not induce early FMRFa expression; also, we show that the BMP-insensitive HD-RE cis-element is activated at the time of target contact. This led us to uncover a role for the nuclear receptor, seven up (svp, as a repressor of FMRFa induction prior to target contact. Svp is normally downregulated immediately prior to target contact, and we found that maintaining Svp expression prevents cis-element activation, whereas reducing svp gene dosage prematurely activates cis-element activity. We conclude that the target-dependent FMRFa gene is repressed prior to target contact, and that target-derived BMP

  2. Constructing a Knowledge Base for Gene Regulatory Dynamics by Formal Concept Analysis Methods

    CERN Document Server

    Wollbold, Johannes; Ganter, Bernhard

    2008-01-01

    Our aim is to build a set of rules, such that reasoning over temporal dependencies within gene regulatory networks is possible. The underlying transitions may be obtained by discretizing observed time series, or they are generated based on existing knowledge, e.g. by Boolean networks or their nondeterministic generalization. We use the mathematical discipline of formal concept analysis (FCA), which has been applied successfully in domains as knowledge representation, data mining or software engineering. By the attribute exploration algorithm, an expert or a supporting computer program is enabled to decide about the validity of a minimal set of implications and thus to construct a sound and complete knowledge base. From this all valid implications are derivable that relate to the selected properties of a set of genes. We present results of our method for the initiation of sporulation in Bacillus subtilis. However the formal structures are exhibited in a most general manner. Therefore the approach may be adapte...

  3. Manipulation of regulatory genes reveals complexity and fidelity in hormaomycin biosynthesis.

    Science.gov (United States)

    Cai, Xiaofeng; Teta, Roberta; Kohlhaas, Christoph; Crüsemann, Max; Ueoka, Reiko; Mangoni, Alfonso; Freeman, Michael F; Piel, Jörn

    2013-06-20

    Hormaomycin (HRM) is a structurally remarkable peptide produced by Streptomyces griseoflavus W-384 that acts as a Streptomyces signaling metabolite and exhibits potent antibiotic activity against coryneform actinomycetes. HRM biosynthetic studies have been hampered by inconsistent and low production. To enhance fermentation titers, the role of its cluster-encoded regulatory genes was investigated. Extra copies of the putative regulators hrmA and hrmB were introduced into the wild-type strain, resulting in an increase of HRM production and its analogs up to 135-fold. For the HrmB overproducer, six bioactive analogs were isolated and characterized. This study demonstrates that HrmA and HrmB are positive regulators in HRM biosynthesis. A third gene, hrmH, was identified as encoding a protein capable of shifting the metabolic profile of HRM and its derivatives. Its manipulation resulted in the generation of an additional HRM analog.

  4. Developmental evolution in social insects: regulatory networks from genes to societies.

    Science.gov (United States)

    Linksvayer, Timothy A; Fewell, Jennifer H; Gadau, Jürgen; Laubichler, Manfred D

    2012-05-01

    The evolution and development of complex phenotypes in social insect colonies, such as queen-worker dimorphism or division of labor, can, in our opinion, only be fully understood within an expanded mechanistic framework of Developmental Evolution. Conversely, social insects offer a fertile research area in which fundamental questions of Developmental Evolution can be addressed empirically. We review the concept of gene regulatory networks (GRNs) that aims to fully describe the battery of interacting genomic modules that are differentially expressed during the development of individual organisms. We discuss how distinct types of network models have been used to study different levels of biological organization in social insects, from GRNs to social networks. We propose that these hierarchical networks spanning different organizational levels from genes to societies should be integrated and incorporated into full GRN models to elucidate the evolutionary and developmental mechanisms underlying social insect phenotypes. Finally, we discuss prospects and approaches to achieve such an integration.

  5. Reverse engineering gene regulatory networks related to quorum sensing in the plant pathogen Pectobacterium atrosepticum.

    Science.gov (United States)

    Lin, Kuang; Husmeier, Dirk; Dondelinger, Frank; Mayer, Claus D; Liu, Hui; Prichard, Leighton; Salmond, George P C; Toth, Ian K; Birch, Paul R J

    2010-01-01

    The objective of the project reported in the present chapter was the reverse engineering of gene regulatory networks related to quorum sensing in the plant pathogen Pectobacterium atrosepticum from micorarray gene expression profiles, obtained from the wild-type and eight knockout strains. To this end, we have applied various recent methods from multivariate statistics and machine learning: graphical Gaussian models, sparse Bayesian regression, LASSO (least absolute shrinkage and selection operator), Bayesian networks, and nested effects models. We have investigated the degree of similarity between the predictions obtained with the different approaches, and we have assessed the consistency of the reconstructed networks in terms of global topological network properties, based on the node degree distribution. The chapter concludes with a biological evaluation of the predicted network structures.

  6. Establishment of the methods for searching eukaryotic gene cis-regulatory modules.

    Science.gov (United States)

    Zhong, Dong; Zhang, Zhen-shu; Liu, Yu-hu; Zheng, Guo-qing; Liu, Xiao-yi; Lu, Yang; Zhao, Gui-jun; Xu, An-long

    2004-02-01

    On the basis of the knowledge of eukaryotic gene regulation, we modified the method in three aspects: (1) Searching the cis-regulatory modules (CRM) according Fasta or Blast sequence with multiple sequence and low E value, followed by mutual scoring of these sequence with Smith-Waterman algorithms and finally by clustering analysis; (2) Searching the transcription factor-binding site using International Union of Pure and Applied Chemistry, Position-Weight Matrix(PWM) and Dyed method; (3) Designing and implementation of data analysis based on the software in Windows 2000 and UNIX using object-oriented technology. The results of analysis of the major histocompatibility complex gene family show that this procedure may accurately locate the regions that contain some of the CRMs.

  7. [ Super-enhancers. Are they regulators of regulatory genes of development and cancer?].

    Science.gov (United States)

    Didych, D A; Tyulkina, D V; Pleshkan, V V; Alekseenko, I V; Sverdlov, E D

    2015-01-01

    Enhancers make up a huge class of genome regulatory elements that play an important role in the formation and maintenance of specific patterns of gene transcriptional activity in all types of cells. In recent years, high-throughput methods for the genome-wide epigenetic analysis of chromatin have made it possible to identify structural and functional features of enhancers and their role in the spatial and functional organization of the genome and in the formation and maintenance of cell identity, as well as in the pathogenesis of certain diseases. Special attention has been focused on genome regions called super-enhancers, or stretch enhancers, which consist of clusters of elements with properties of classic enhancers. This review considers current data on specific properties of super-enhancers and their role in the formation of interconnected autoregulatory circuits with positive feedback that regulates the most important genes, the activity of which underlies the formation and maintenance of specialized cellular functions.

  8. Robust and regulatory expression of defensin A gene driven by vitellogenin promoter in transgenic Anopheles stephensi

    Institute of Scientific and Technical Information of China (English)

    CHEN XiaoGuang; ZHANG YaJing; ZHENG XueLi; WANG ChunMei

    2007-01-01

    The use of genetically modified mosquitoes to reduce or replace field populations is a new strategy to control mosquito-borne diseases. The precondition of the implementation of this strategy is the ability to manipulate the genome of mosquitoes and to induce specific expression of the effector molecules driven by a suitable promoter. The objective of this study is to evaluate the expression of defensin A gene of Anopheles sinensis under the control of a vitellogenin promoter in transgenic Anopheles stephensi. The regulatory region of Anopheles gambiae vitellogenin was cloned and subcloned into transfer vector pSLFa consisting of an expression cassette with defensin A coding sequence. Then, the expression cassette was transferred into transformation vector pBac[3xP3-DsRedafm] using Asc I digestion. The recombinant plasmid DNA of pBac[3xP3DsRed-AgVgT2-DefA] and helper plasmid DNA of phsp-pBac were micro-injected into embryos of An. stephensi. The positive transgenic mosquitoes were screened by observing specific red fluorescence in the eyes of G1 larvae. Southern blot analysis showed that a single-copy transgene integrated into the genome of An. stephensi. RT-PCR analysis showed that the defensin A gene expressed specifically in fat bodies of female mosquitoes after a blood meal. Interestingly, the mRNA of defensin A is more stable compared with that of the endogenous vitellogenin gene. After multiple blood meals, the expression of defensin A appeared as a reducible and non-cycling type, a crucial feature for its anti-pathogen effect. From data above, we concluded that the regulatory function of the Vg promoter and the expression of defensin A gene were relatively conserved in different species of anopheles mosquitoes. These molecules could be used as candidates in the development of genetically modified mosquitoes.

  9. Putative cis-regulatory elements associated with heat shock genes activated during excystation of Cryptosporidium parvum.

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    Benjamin Cohn

    Full Text Available BACKGROUND: Cryptosporidiosis is a ubiquitous infectious disease, caused by the protozoan parasites Cryptosporidium hominis and C. parvum, leading to acute, persistent and chronic diarrhea worldwide. Although the complications of this disease can be serious, even fatal, in immunocompromised patients of any age, they have also been found to lead to long term effects, including growth inhibition and impaired cognitive development, in infected immunocompetent children. The Cryptosporidium life cycle alternates between a dormant stage, the oocyst, and a highly replicative phase that includes both asexual vegetative stages as well as sexual stages, implying fine genetic regulatory mechanisms. The parasite is extremely difficult to study because it cannot be cultured in vitro and animal models are equally challenging. The recent publication of the genome sequence of C. hominis and C. parvum has, however, significantly advanced our understanding of the biology and pathogenesis of this parasite. METHODOLOGY/PRINCIPAL FINDINGS: Herein, our goal was to identify cis-regulatory elements associated with heat shock response in Cryptosporidium using a combination of in silico and real time RT-PCR strategies. Analysis with Gibbs-Sampling algorithms of upstream non-translated regions of twelve genes annotated as heat shock proteins in the Cryptosporidium genome identified a highly conserved over-represented sequence motif in eleven of them. RT-PCR analyses, described herein and also by others, show that these eleven genes bearing the putative element are induced concurrent with excystation of parasite oocysts via heat shock. CONCLUSIONS/SIGNIFICANCE: Our analyses suggest that occurrences of a motif identified in the upstream regions of the Cryptosporidium heat shock genes represent parts of the transcriptional apparatus and function as stress response elements that activate expression of these genes during excystation, and possibly at other stages in the life

  10. Cloning and characterization of nif structural and regulatory genes in the purple sulfur bacterium, Halorhodospira halophila.

    Science.gov (United States)

    Tsuihiji, Hisayoshi; Yamazaki, Yoichi; Kamikubo, Hironari; Imamoto, Yasushi; Kataoka, Mikio

    2006-03-01

    Halorhodospira halophila is a halophilic photosynthetic bacterium classified as a purple sulfur bacterium. We found that H. halophila generates hydrogen gas during photoautotrophic growth as a byproduct of a nitrogenase reaction. In order to consider the applied possibilities of this photobiological hydrogen generation, we cloned and characterized the structural and regulatory genes encoding the nitrogenase, nifH, nifD and nifA, from H. halophila. This is the first description of the nif genes for a purple sulfur bacterium. The amino-acid sequences of NifH and NifD indicated that these proteins are an Fe protein and a part of a MoFe protein, respectively. The important residues are conserved completely. The sequence upstream from the nifH region and sequence similarities of nifH and nifD with those of the other organisms suggest that the regulatory system might be a NifL-NifA system; however, H. halophila lacks nifL. The amino-acid sequence of H. halophila NifA is closer to that of the NifA of the NifL-NifA system than to that of NifA without NifL. H. halophila NifA does not conserve either the residue that interacts with NifL or the important residues involved in NifL-independent regulation. These results suggest the existence of yet another regulatory system, and that the development of functional systems and their molecular counterparts are not necessarily correlated throughout evolution. All of these Nif proteins of H. halophila possess an excess of acidic residues, which acts as a salt-resistant mechanism.

  11. Gene Regulatory Network Analysis Reveals Differences in Site-specific Cell Fate Determination in Mammalian Brain

    Directory of Open Access Journals (Sweden)

    Gokhan eErtaylan

    2014-12-01

    Full Text Available Neurogenesis - the generation of new neurons - is an ongoing process that persists in the adult mammalian brain of several species, including humans. In this work we analyze two discrete brain regions: the subventricular zone (SVZ lining the walls of the lateral ventricles; and the subgranular zone (SGZ of the dentate gyrus of the hippocampus in mice and shed light on the SVZ and SGZ specific neurogenesis. We propose a computational model that relies on the construction and analysis of region specific gene regulatory networks from the publicly available data on these two regions. Using this model a number of putative factors involved in neuronal stem cell (NSC identity and maintenance were identified. We also demonstrate potential gender and niche-derived differences based on cell surface and nuclear receptors via Ar, Hif1a and Nr3c1.We have also conducted cell fate determinant analysis for SVZ NSC populations to Olfactory Bulb interneurons and SGZ NSC populations to the granule cells of the Granular Cell Layer. We report thirty-one candidate cell fate determinant gene pairs, ready to be validated. We focus on Ar - Pax6 in SVZ and Sox2 - Ncor1 in SGZ. Both pairs are expressed and localized in the suggested anatomical structures as shown by in situ hybridization and found to physically interact.Finally, we conclude that there are fundamental differences between SGZ and SVZ neurogenesis. We argue that these regulatory mechanisms are linked to the observed differential neurogenic potential of these regions. The presence of nuclear and cell surface receptors in the region specific regulatory circuits indicate the significance of niche derived extracellular factors, hormones and region specific factors such as the oxygen sensitivity, dictating SGZ and SVZ specific neurogenesis.

  12. Plasticity of the cis-regulatory input function of a gene.

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    Avraham E Mayo

    2006-04-01

    Full Text Available The transcription rate of a gene is often controlled by several regulators that bind specific sites in the gene's cis-regulatory region. The combined effect of these regulators is described by a cis-regulatory input function. What determines the form of an input function, and how variable is it with respect to mutations? To address this, we employ the well-characterized lac operon of Escherichia coli, which has an elaborate input function, intermediate between Boolean AND-gate and OR-gate logic. We mapped in detail the input function of 12 variants of the lac promoter, each with different point mutations in the regulator binding sites, by means of accurate expression measurements from living cells. We find that even a few mutations can significantly change the input function, resulting in functions that resemble Pure AND gates, OR gates, or single-input switches. Other types of gates were not found. The variant input functions can be described in a unified manner by a mathematical model. The model also lets us predict which functions cannot be reached by point mutations. The input function that we studied thus appears to be plastic, in the sense that many of the mutations do not ruin the regulation completely but rather result in new ways to integrate the inputs.

  13. Neural model of gene regulatory network: a survey on supportive meta-heuristics.

    Science.gov (United States)

    Biswas, Surama; Acharyya, Sriyankar

    2016-06-01

    Gene regulatory network (GRN) is produced as a result of regulatory interactions between different genes through their coded proteins in cellular context. Having immense importance in disease detection and drug finding, GRN has been modelled through various mathematical and computational schemes and reported in survey articles. Neural and neuro-fuzzy models have been the focus of attraction in bioinformatics. Predominant use of meta-heuristic algorithms in training neural models has proved its excellence. Considering these facts, this paper is organized to survey neural modelling schemes of GRN and the efficacy of meta-heuristic algorithms towards parameter learning (i.e. weighting connections) within the model. This survey paper renders two different structure-related approaches to infer GRN which are global structure approach and substructure approach. It also describes two neural modelling schemes, such as artificial neural network/recurrent neural network based modelling and neuro-fuzzy modelling. The meta-heuristic algorithms applied so far to learn the structure and parameters of neutrally modelled GRN have been reviewed here.

  14. Conservation-based prediction of the transcription regulatory region of the SCN1A gene

    Institute of Scientific and Technical Information of China (English)

    Yue-Sheng Long; Yi-Wu Shi; Wei-Ping Liao

    2009-01-01

    A challenge in identifying the transcription regulatory region is that the locations of eukaryotic transcriptional elements are often diverse among different genes.SCN1A,a disease-related sodium channel gene,has a complex 5'-untranslated region and diverse mRNA transcripts,which might be driven by different promoters.By cross-species sequence comparison and bioinformatics analysis,human 5'-untranslated exons were found to be conserved within the region of 200 kb upstream of the 5' flanking regions of SCN1A in higher mammals,but not in lower mammals and non-mammals.The core promoter elements (INR,DPE,and TATA) were found in the regions flanking different 5'-untranslated exons,suggesting that these sequences (from-45 to+35) might be targeted as core promoters.The nucleotide identity rate of these core promoter sequences are different,and the conservation level of the upstream region of each core promoter varies distinctly,implicating different regulatory mechanisms of the four promoters which exist in the nervous system.

  15. Polymorphisms in the surfactant protein a gene are associated with the susceptibility to recurrent urinary tract infection in chinese women.

    Science.gov (United States)

    Liu, Jiao; Hu, Fengqi; Liang, Wei; Wang, Guirong; Singhal, Pravin C; Ding, Guohua

    2010-05-01

    Some risk factors for susceptibility to recurrent urinary tract infection (r-UTI) are well known, but the genetic role in acquiring the disease is poorly understood. Surfactant protein A and D (SP-A and SP-D) play an important role in modulation of lung inflammatory processes. The SP-A1 and SP-A2 genes encoding SP-A and the SP-D gene are highly polymorphic, and some of polymorphisms are associated with several infective diseases, including pyelonephritis. In the present study, we investigated whether some of these polymorphisms are associated with the risk of r-UTI in Chinese population. Genomic DNA was extracted from blood samples of 32 female patients with r-UTI and 30 age-matched, unrelated healthy female subjects. Genotyping of gene polymorphisms was analyzed by PCR. Among 11 single nucleotide polymorphisms (SNPs) (five of SP-A1, four of SP-A2 and two of SP-D) observed in the enrolled subjects, Ala19Val of SP-A1 and Lys223Gln of SP-A2 were associated with susceptibility to r-UTI. The frequencies of 19Ala allele of SP-A1 gene (p = 0.038) and 223Gln allele of SP-A2 gene (p = 0.012) in the patients were significantly higher than those in healthy subjects. The serum SP-A and SP-D levels were increased and the urine SP-A and SP-D levels were decreased in r-UTI patients compared with control subjects (p UTI patients with 19Ala/Ala or 223Gln/Gln genotype were associated with high serum and low urine SP-A levels (p UTI.

  16. In vivo gene expression analysis identifies genes required for enhanced colonization of the mouse urinary tract by uropathogenic Escherichia coli strain CFT073 dsdA.

    Science.gov (United States)

    Haugen, Brian J; Pellett, Shahaireen; Redford, Peter; Hamilton, Holly L; Roesch, Paula L; Welch, Rodney A

    2007-01-01

    Deletional inactivation of the gene encoding d-serine deaminase, dsdA, in uropathogenic Escherichia coli strain CFT073 results in a hypermotile strain with a hypercolonization phenotype in the bladder and kidneys of mice in a model of urinary tract infection (UTI). The in vivo gene expression profiles of CFT073 and CFT073 dsdA were compared by isolating RNA directly from the urine of mice challenged with each strain individually. Hybridization of cDNAs derived from these samples to CFT073-specific microarrays allowed identification of genes that were up- or down-regulated in the dsdA deletion strain during UTI. Up-regulated genes included the known d-serine-responsive gene dsdX, suggesting in vivo intracellular accumulation of d-serine by CFT073 dsdA. Genes encoding F1C fimbriae, both copies of P fimbriae, hemolysin, OmpF, a dipeptide transporter DppA, a heat shock chaperone IbpB, and clusters of open reading frames with unknown functions were also up-regulated. To determine the role of these genes as well as motility in the hypercolonization phenotype, mutants were constructed in the CFT073 dsdA background and tested in competition against the wild type in the murine model of UTI. Strains with deletions of one or both of the two P fimbrial operons, hlyA, fliC, ibpB, c0468, locus c3566 to c3568, or c2485 to c2490 colonized mouse bladders and kidneys at levels indistinguishable from wild type. CFT073 dsdA c2398 and CFT073 dsdA focA maintained a hypercolonization phenotype. A CFT073 dsdA dppA mutant was attenuated 10- to 50-fold in its colonization ability compared to CFT073. Our results support a role for d-serine catabolism and signaling in global virulence gene regulation of uropathogenic E. coli.

  17. Gene Regulatory Scenarios of Primary 1,25-Dihydroxyvitamin D3 Target Genes in a Human Myeloid Leukemia Cell Line

    Directory of Open Access Journals (Sweden)

    Moray J. Campbell

    2013-10-01

    Full Text Available Genome- and transcriptome-wide data has significantly increased the amount of available information about primary 1,25-dihydroxyvitamin D3 (1,25(OH2D3 target genes in cancer cell models, such as human THP-1 myelomonocytic leukemia cells. In this study, we investigated the genes G0S2, CDKN1A and MYC as master examples of primary vitamin D receptor (VDR targets being involved in the control of cellular proliferation. The chromosomal domains of G0S2 and CDKN1A are 140–170 kb in size and contain one and three VDR binding sites, respectively. This is rather compact compared to the MYC locus that is 15 times larger and accommodates four VDR binding sites. All eight VDR binding sites were studied by chromatin immunoprecipitation in THP-1 cells. Interestingly, the site closest to the transcription start site of the down-regulated MYC gene showed 1,25(OH2D3-dependent reduction of VDR binding and is not associated with open chromatin. Four of the other seven VDR binding regions contain a typical DR3-type VDR binding sequence, three of which are also occupied with VDR in macrophage-like cells. In conclusion, the three examples suggest that each VDR target gene has an individual regulatory scenario. However, some general components of these scenarios may be useful for the development of new therapy regimens.

  18. Ectopic expression of MYB46 identifies transcriptional regulatory genes involved in secondary wall biosynthesis in Arabidopsis.

    Science.gov (United States)

    Ko, Jae-Heung; Kim, Won-Chan; Han, Kyung-Hwan

    2009-11-01

    MYB46 functions as a transcriptional switch that turns on the genes necessary for secondary wall biosynthesis. Elucidating the transcriptional regulatory network immediately downstream of MYB46 is crucial to our understanding of the molecular and biochemical processes involved in the biosynthesis and deposition of secondary walls in plants. To gain insights into MYB46-mediated transcriptional regulation, we first established an inducible secondary wall thickening system in Arabidopsis by expressing MYB46 under the control of dexamethasone-inducible promoter. Then, we used an ATH1 GeneChip microarray and Illumina digital gene expression system to obtain a series of transcriptome profiles with regard to the induction of secondary wall development. These analyses allowed us to identify a group of transcription factors whose expression coincided with or preceded the induction of secondary wall biosynthetic genes. A transient transcriptional activation assay was used to confirm the hierarchical relationships among the transcription factors in the network. The in vivo assay showed that MYB46 transcriptionally activates downstream target transcription factors, three of which (AtC3H14, MYB52 and MYB63) were shown to be able to activate secondary wall biosynthesis genes. AtC3H14 activated the transcription of all of the secondary wall biosynthesis genes tested, suggesting that AtC3H14 may be another master regulator of secondary wall biosynthesis. The transcription factors identified here may include direct activators of secondary wall biosynthesis genes. The present study discovered novel hierarchical relationships among the transcription factors involved in the transcriptional regulation of secondary wall biosynthesis, and generated several testable hypotheses.

  19. Deciphering ascorbic acid regulatory pathways in ripening tomato fruit using a weighted gene correlation network analysis approach.

    Science.gov (United States)

    Gao, Chao; Ju, Zheng; Li, Shan; Zuo, Jinhua; Fu, Daqi; Tian, Huiqin; Luo, Yunbo; Zhu, Benzhong

    2013-11-01

    Genotype is generally determined by the co-expression of diverse genes and multiple regulatory pathways in plants. Gene co-expression analysis combining with physiological trait data provides very important information about the gene function and regulatory mechanism. L-Ascorbic acid (AsA), which is an essential nutrient component for human health and plant metabolism, plays key roles in diverse biological processes such as cell cycle, cell expansion, stress resistance, hormone synthesis, and signaling. Here, we applied a weighted gene correlation network analysis approach based on gene expression values and AsA content data in ripening tomato (Solanum lycopersicum L.) fruit with different AsA content levels, which leads to identification of AsA relevant modules and vital genes in AsA regulatory pathways. Twenty-four modules were compartmentalized according to gene expression profiling. Among these modules, one negatively related module containing genes involved in redox processes and one positively related module enriched with genes involved in AsA biosynthetic and recycling pathways were further analyzed. The present work herein indicates that redox pathways as well as hormone-signal pathways are closely correlated with AsA accumulation in ripening tomato fruit, and allowed us to prioritize candidate genes for follow-up studies to dissect this interplay at the biochemical and molecular level.

  20. Deciphering Ascorbic Acid Regulatory Pathways in Ripening Tomato Fruit Using a Weighted Gene Correlation Network Analysis Approach

    Institute of Scientific and Technical Information of China (English)

    Chao Gao; Zheng Ju; Shan Li; Jinhua Zuo; Daqi Fu; Huiqin Tian; Yunbo Luo; Benzhong Zhu

    2013-01-01

    Genotype is generally determined by the co-expression of diverse genes and multiple regulatory pathways in plants. Gene co-expression analysis combining with physiological trait data provides very important information about the gene function and regulatory mechanism. L-Ascorbic acid (AsA), which is an essential nutrient component for human health and plant metabolism, plays key roles in diverse biological processes such as cell cycle, cell expansion, stress resistance, hormone synthesis, and signaling. Here, we applied a weighted gene correlation network analysis approach based on gene expression values and AsA content data in ripening tomato (Solanum lycopersicum L.) fruit with different AsA content levels, which leads to identification of AsA relevant modules and vital genes in AsA regulatory pathways. Twenty-four modules were compartmentalized according to gene expression profiling. Among these modules, one negatively related module containing genes involved in redox processes and one positively related module enriched with genes involved in AsA biosynthetic and recycling pathways were further analyzed. The present work herein indicates that redox pathways as well as hormone-signal pathways are closely correlated with AsA accumulation in ripening tomato fruit, and allowed us to prioritize candidate genes for follow-up studies to dissect this interplay at the biochemical and molecular level.

  1. A meta-analysis of multiple matched copy number and transcriptomics data sets for inferring gene regulatory relationships.

    Directory of Open Access Journals (Sweden)

    Richard Newton

    Full Text Available Inferring gene regulatory relationships from observational data is challenging. Manipulation and intervention is often required to unravel causal relationships unambiguously. However, gene copy number changes, as they frequently occur in cancer cells, might be considered natural manipulation experiments on gene expression. An increasing number of data sets on matched array comparative genomic hybridisation and transcriptomics experiments from a variety of cancer pathologies are becoming publicly available. Here we explore the potential of a meta-analysis of thirty such data sets. The aim of our analysis was to assess the potential of in silico inference of trans-acting gene regulatory relationships from this type of data. We found sufficient correlation signal in the data to infer gene regulatory relationships, with interesting similarities between data sets. A number of genes had highly correlated copy number and expression changes in many of the data sets and we present predicted potential trans-acted regulatory relationships for each of these genes. The study also investigates to what extent heterogeneity between cell types and between pathologies determines the number of statistically significant predictions available from a meta-analysis of experiments.

  2. Identifying Regulatory Patterns at the 3'end Regions of Over-expressed and Under-expressed Genes

    KAUST Repository

    Othoum, Ghofran K

    2013-05-01

    Promoters, neighboring regulatory regions and those extending further upstream of the 5’end of genes, are considered one of the main components affecting the expression status of genes in a specific phenotype. More recently research by Chen et al. (2006, 2012) and Mapendano et al. (2010) demonstrated that the 3’end regulatory regions of genes also influence gene expression. However, the association between the regulatory regions surrounding 3’end of genes and their over- or under-expression status in a particular phenotype has not been systematically studied. The aim of this study is to ascertain if regulatory regions surrounding the 3’end of genes contain sufficient regulatory information to correlate genes with their expression status in a particular phenotype. Over- and under-expressed ovarian cancer (OC) genes were used as a model. Exploratory analysis of the 3’end regions were performed by transforming the annotated regions using principal component analysis (PCA), followed by clustering the transformed data thereby achieving a clear separation of genes with different expression status. Additionally, several classification algorithms such as Naïve Bayes, Random Forest and Support Vector Machine (SVM) were tested with different parameter settings to analyze the discriminatory capacity of the 3’end regions of genes related to their gene expression status. The best performance was achieved using the SVM classification model with 10-fold cross-validation that yielded an accuracy of 98.4%, sensitivity of 99.5% and specificity of 92.5%. For gene expression status for newly available instances, based on information derived from the 3’end regions, an SVM predictive model was developed with 10-fold cross-validation that yielded an accuracy of 67.0%, sensitivity of 73.2% and specificity of 61.0%. Moreover, building an SVM with polynomial kernel model to PCA transformed data yielded an accuracy of 83.1%, sensitivity of 92.5% and specificity of 74.8% using

  3. Nucleotide sequence conservation of novel and established cis-regulatory sites within the tyrosine hydroxylase gene promoter.

    Science.gov (United States)

    Wang, Meng; Banerjee, Kasturi; Baker, Harriet; Cave, John W

    2015-02-01

    Tyrosine hydroxylase (TH) is the rate-limiting enzyme in catecholamine biosynthesis and its gene proximal promoter ( electromobility shift assays showed that brain-region specific complexes assemble on these motifs. These studies also identified a non-canonical CRE binding (CREB) protein recognition element in the proximal promoter. Together, these studies provide a detailed analysis of evolutionary conservation within the TH promoter and identify potential cis-regulatory motifs that underlie a core set of regulatory mechanisms in mammals.

  4. Vagaries of fluorochrome reporter gene expression in Foxp3+ regulatory T cells.

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    Sonja Schallenberg

    Full Text Available CD4(+CD25(+ regulatory T (Treg cell lineage commitment and expression of the transcription factor Foxp3 can be induced at the CD4(+CD8(+ double-positive (DP and CD4(+CD8(? single-positive stages of thymic development, as well as in postthymic CD4(+ T cells in peripheral lymphoid tissues. The availability of transgenic mice with Foxp3-dependent fluorochrome reporter gene expression has greatly facilitated studies on the intra- and extrathymic generation of murine Foxp3(+ Treg cells. Here, we performed a comparative analysis of thymic Treg cell development and peripheral compartments of mature Treg cells in various transgenic strains with gene targeted and bacterial artificial chromosome (BAC-driven Foxp3-fluorochrome expression. These studies revealed a relative deficiency of Foxp3(+ DP thymocytes selectively in mice with targeted insertion of the fluorochrome reporter gene coding sequence into the endogenous Foxp3 gene. While Foxp3 BAC-driven fluorochrome expression in ex vivo CD4(+ T cells was found to faithfully reflect Foxp3 protein expression, we provide evidence that Foxp3 BAC transgenesis can result in sizable populations of Foxp3(+ Treg cells that lack fluorochrome reporter expression. This could be attributed to both timely delayed up-regulation of BAC expression in developing Treg cells and the accumulation of peripheral Foxp3(+ Treg cells with continuous transcriptional inactivity of the Foxp3 BAC transgene.

  5. MicroRNA-24/MODY gene regulatory pathway mediates pancreatic β-cell dysfunction.

    Science.gov (United States)

    Zhu, Yunxia; You, Weiyan; Wang, Hongdong; Li, Yating; Qiao, Nan; Shi, Yuguang; Zhang, Chenyu; Bleich, David; Han, Xiao

    2013-09-01

    Overnutrition and genetics both contribute separately to pancreatic β-cell dysfunction, but how these factors interact is unclear. This study was aimed at determining whether microRNAs (miRNAs) provide a link between these factors. In this study, miRNA-24 (miR-24) was highly expressed in pancreatic β-cells and further upregulated in islets from genetic fatty (db/db) or mice fed a high-fat diet, and islets subject to oxidative stress. Overexpression of miR-24 inhibited insulin secretion and β-cell proliferation, potentially involving 351 downregulated genes. By using bioinformatic analysis combined with luciferase-based promoter activity assays and quantitative real-time PCR assays, we identified two maturity-onset diabetes of the young (MODY) genes as direct targets of miR-24. Silencing either of these MODY genes (Hnf1a and Neurod1) mimicked the cellular phenotype caused by miR-24 overexpression, whereas restoring their expression rescued β-cell function. Our findings functionally link the miR-24/MODY gene regulatory pathway to the onset of type 2 diabetes and create a novel network between nutrient overload and genetic diabetes via miR-24.

  6. Regulatory elements controlling pituitary-specific expression of the human prolactin gene.

    Science.gov (United States)

    Peers, B; Voz, M L; Monget, P; Mathy-Hartert, M; Berwaer, M; Belayew, A; Martial, J A

    1990-09-01

    We have performed transfection and DNase I footprinting experiments to investigate pituitary-specific expression of the human prolactin (hPRL) gene. When fused to the chloramphenicol acetyltransferase (CAT) reporter gene, 5,000 base pairs of the 5'-flanking sequences of the hPRL gene were able to drive high cat gene expression in prolactin-expressing GH3B6 cells specifically. Deletion analysis indicated that this pituitary-specific expression was controlled by three main positive regulatory regions. The first was located just upstream from the TATA box between coordinates -40 and -250 (proximal region). We have previously shown that three motifs of this region bind the pituitary-specific Pit-1 factor. The second positive region was located in the vicinity of coordinates -1300 to -1750 (distal region). DNase I footprinting assays revealed that eight DNA motifs of this distal region bound protein Pit-1 and that two other motifs were recognized by ubiquitous factors, one of which seems to belong to the AP-1 (jun) family. The third positive region was located further upstream, between -3500 and -5000 (superdistal region). This region appears to enhance transcription only in the presence of the distal region.

  7. Mean field analysis of a spatial stochastic model of a gene regulatory network.

    Science.gov (United States)

    Sturrock, M; Murray, P J; Matzavinos, A; Chaplain, M A J

    2015-10-01

    A gene regulatory network may be defined as a collection of DNA segments which interact with each other indirectly through their RNA and protein products. Such a network is said to contain a negative feedback loop if its products inhibit gene transcription, and a positive feedback loop if a gene product promotes its own production. Negative feedback loops can create oscillations in mRNA and protein levels while positive feedback loops are primarily responsible for signal amplification. It is often the case in real biological systems that both negative and positive feedback loops operate in parameter regimes that result in low copy numbers of gene products. In this paper we investigate the spatio-temporal dynamics of a single feedback loop in a eukaryotic cell. We first develop a simplified spatial stochastic model of a canonical feedback system (either positive or negative). Using a Gillespie's algorithm, we compute sample trajectories and analyse their corresponding statistics. We then derive a system of equations that describe the spatio-temporal evolution of the stochastic means. Subsequently, we examine the spatially homogeneous case and compare the results of numerical simulations with the spatially explicit case. Finally, using a combination of steady-state analysis and data clustering techniques, we explore model behaviour across a subregion of the parameter space that is difficult to access experimentally and compare the parameter landscape of our spatio-temporal and spatially-homogeneous models.

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

    Directory of Open Access Journals (Sweden)

    Faridah Hani Mohamed Salleh

    2017-01-01

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

  9. Urothelial cancer gene regulatory networks inferred from large-scale RNAseq, Bead and Oligo gene expression data.

    Science.gov (United States)

    de Matos Simoes, Ricardo; Dalleau, Sabine; Williamson, Kate E; Emmert-Streib, Frank

    2015-05-14

    Urothelial pathogenesis is a complex process driven by an underlying network of interconnected genes. The identification of novel genomic target regions and gene targets that drive urothelial carcinogenesis is crucial in order to improve our current limited understanding of urothelial cancer (UC) on the molecular level. The inference of genome-wide gene regulatory networks (GRN) from large-scale gene expression data provides a promising approach for a detailed investigation of the underlying network structure associated to urothelial carcinogenesis. In our study we inferred and compared three GRNs by the application of the BC3Net inference algorithm to large-scale transitional cell carcinoma gene expression data sets from Illumina RNAseq (179 samples), Illumina Bead arrays (165 samples) and Affymetrix Oligo microarrays (188 samples). We investigated the structural and functional properties of GRNs for the identification of molecular targets associated to urothelial cancer. We found that the urothelial cancer (UC) GRNs show a significant enrichment of subnetworks that are associated with known cancer hallmarks including cell cycle, immune response, signaling, differentiation and translation. Interestingly, the most prominent subnetworks of co-located genes were found on chromosome regions 5q31.3 (RNAseq), 8q24.3 (Oligo) and 1q23.3 (Bead), which all represent known genomic regions frequently deregulated or aberated in urothelial cancer and other cancer types. Furthermore, the identified hub genes of the individual GRNs, e.g., HID1/DMC1 (tumor development), RNF17/TDRD4 (cancer antigen) and CYP4A11 (angiogenesis/ metastasis) are known cancer associated markers. The GRNs were highly dataset specific on the interaction level between individual genes, but showed large similarities on the biological function level represented by subnetworks. Remarkably, the RNAseq UC GRN showed twice the proportion of significant functional subnetworks. Based on our analysis of inferential

  10. Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and information theory

    Science.gov (United States)

    Sayyed-Ahmad, Abdallah; Tuncay, Kagan; Ortoleva, Peter J

    2007-01-01

    Background Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targeted treatments. A new approach to the construction and quantification of transcriptional regulatory networks (TRNs) is presented that integrates gene expression microarray data and cell modeling through information theory. Given a partial TRN and time series data, a probability density is constructed that is a functional of the time course of transcription factor (TF) thermodynamic activities at the site of gene control, and is a function of mRNA degradation and transcription rate coefficients, and equilibrium constants for TF/gene binding. Results Our approach yields more physicochemical information that compliments the results of network structure delineation methods, and thereby can serve as an element of a comprehensive TRN discovery/quantification system. The most probable TF time courses and values of the aforementioned parameters are obtained by maximizing the probability obtained through entropy maximization. Observed time delays between mRNA expression and activity are accounted for implicitly since the time course of the activity of a TF is coupled by probability functional maximization, and is not assumed to be proportional to expression level of the mRNA type that translates into the TF. This allows one to investigate post-translational and TF activation mechanisms of gene regulation. Accuracy and robustness of the method are evaluated. A kinetic formulation is used to facilitate the analysis of phenomena with a strongly dynamical character while a physically-motivated regularization of the TF time course is found to overcome difficulties due to omnipresent noise and data sparsity that plague other methods of gene expression data analysis. An application to Escherichia coli is presented. Conclusion Multiplex time series data can be used for the construction of the network of

  11. Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and information theory

    Directory of Open Access Journals (Sweden)

    Tuncay Kagan

    2007-01-01

    Full Text Available Abstract Background Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targeted treatments. A new approach to the construction and quantification of transcriptional regulatory networks (TRNs is presented that integrates gene expression microarray data and cell modeling through information theory. Given a partial TRN and time series data, a probability density is constructed that is a functional of the time course of transcription factor (TF thermodynamic activities at the site of gene control, and is a function of mRNA degradation and transcription rate coefficients, and equilibrium constants for TF/gene binding. Results Our approach yields more physicochemical information that compliments the results of network structure delineation methods, and thereby can serve as an element of a comprehensive TRN discovery/quantification system. The most probable TF time courses and values of the aforementioned parameters are obtained by maximizing the probability obtained through entropy maximization. Observed time delays between mRNA expression and activity are accounted for implicitly since the time course of the activity of a TF is coupled by probability functional maximization, and is not assumed to be proportional to expression level of the mRNA type that translates into the TF. This allows one to investigate post-translational and TF activation mechanisms of gene regulation. Accuracy and robustness of the method are evaluated. A kinetic formulation is used to facilitate the analysis of phenomena with a strongly dynamical character while a physically-motivated regularization of the TF time course is found to overcome difficulties due to omnipresent noise and data sparsity that plague other methods of gene expression data analysis. An application to Escherichia coli is presented. Conclusion Multiplex time series data can be used for the

  12. High Dimensional ODEs Coupled with Mixed-Effects Modeling Techniques for Dynamic Gene Regulatory Network Identification.

    Science.gov (United States)

    Lu, Tao; Liang, Hua; Li, Hongzhe; Wu, Hulin

    2011-01-01

    Gene regulation is a complicated process. The interaction of many genes and their products forms an intricate biological network. Identification of this dynamic network will help us understand the biological process in a systematic way. However, the construction of such a dynamic network is very challenging for a high-dimensional system. In this article we propose to use a set of ordinary differential equations (ODE), coupled with dimensional reduction by clustering and mixed-effects modeling techniques, to model the dynamic gene regulatory network (GRN). The ODE models allow us to quantify both positive and negative gene regulations as well as feedback effects of one set of genes in a functional module on the dynamic expression changes of the genes in another functional module, which results in a directed graph network. A five-step procedure, Clustering, Smoothing, regulation Identification, parameter Estimates refining and Function enrichment analysis (CSIEF) is developed to identify the ODE-based dynamic GRN. In the proposed CSIEF procedure, a series of cutting-edge statistical methods and techniques are employed, that include non-parametric mixed-effects models with a mixture distribution for clustering, nonparametric mixed-effects smoothing-based methods for ODE models, the smoothly clipped absolute deviation (SCAD)-based variable selection, and stochastic approximation EM (SAEM) approach for mixed-effects ODE model parameter estimation. The key step, the SCAD-based variable selection of the proposed procedure is justified by investigating its asymptotic properties and validated by Monte Carlo simulations. We apply the proposed method to identify the dynamic GRN for yeast cell cycle progression data. We are able to annotate the identified modules through function enrichment analyses. Some interesting biological findings are discussed. The proposed procedure is a promising tool for constructing a general dynamic GRN and more complicated dynamic networks.

  13. Multiple Herbicide Resistance in Lolium multiflorum and Identification of Conserved Regulatory Elements of Herbicide Resistance Genes

    Science.gov (United States)

    Mahmood, Khalid; Mathiassen, Solvejg K.; Kristensen, Michael; Kudsk, Per

    2016-01-01

    Herbicide resistance is a ubiquitous challenge to herbicide sustainability and a looming threat to control weeds in crops. Recently four genes were found constituently over-expressed in herbicide resistant individuals of Lolium rigidum, a close relative of Lolium multiflorum. These include two cytochrome P450s, one nitronate monooxygenase and one glycosyl-transferase. Higher expressions of these four herbicide metabolism related (HMR) genes were also observed after herbicides exposure in the gene expression databases, indicating them as reliable markers. In order to get an overview of herbicidal resistance status of L. multiflorum L, 19 field populations were collected. Among these populations, four populations were found to be resistant to acetolactate synthase (ALS) inhibitors while three exhibited resistance to acetyl-CoA carboxylase (ACCase) inhibitors in our initial screening and dose response study. The genotyping showed the presence of mutations Trp-574-Leu and Ile-2041-Asn in ALS and ACCase, respectively, and qPCR experiments revealed the enhanced expression of HMR genes in individuals of certain resistant populations. Moreover, co-expression networks and promoter analyses of HMR genes in O. sativa and A. thaliana resulted in the identification of a cis-regulatory motif and zinc finger transcription factors. The identified transcription factors were highly expressed similar to HMR genes in response to xenobiotics whereas the identified motif is known to play a vital role in coping with environmental stresses and maintaining genome stability. Overall, our findings provide an important step forward toward a better understanding of metabolism-based herbicide resistance that can be utilized to devise novel strategies of weed management. PMID:27547209

  14. Multiple Herbicide Resistance in Lolium multiflorum and Identification of Conserved Regulatory Elements of Herbicide Resistance Genes.

    Science.gov (United States)

    Mahmood, Khalid; Mathiassen, Solvejg K; Kristensen, Michael; Kudsk, Per

    2016-01-01

    Herbicide resistance is a ubiquitous challenge to herbicide sustainability and a looming threat to control weeds in crops. Recently four genes were found constituently over-expressed in herbicide resistant individuals of Lolium rigidum, a close relative of Lolium multiflorum. These include two cytochrome P450s, one nitronate monooxygenase and one glycosyl-transferase. Higher expressions of these four herbicide metabolism related (HMR) genes were also observed after herbicides exposure in the gene expression databases, indicating them as reliable markers. In order to get an overview of herbicidal resistance status of L. multiflorum L, 19 field populations were collected. Among these populations, four populations were found to be resistant to acetolactate synthase (ALS) inhibitors while three exhibited resistance to acetyl-CoA carboxylase (ACCase) inhibitors in our initial screening and dose response study. The genotyping showed the presence of mutations Trp-574-Leu and Ile-2041-Asn in ALS and ACCase, respectively, and qPCR experiments revealed the enhanced expression of HMR genes in individuals of certain resistant populations. Moreover, co-expression networks and promoter analyses of HMR genes in O. sativa and A. thaliana resulted in the identification of a cis-regulatory motif and zinc finger transcription factors. The identified transcription factors were highly expressed similar to HMR genes in response to xenobiotics whereas the identified motif is known to play a vital role in coping with environmental stresses and maintaining genome stability. Overall, our findings provide an important step forward toward a better understanding of metabolism-based herbicide resistance that can be utilized to devise novel strategies of weed management.

  15. Multiple herbicide resistance in Lolium multiflorum and identification of conserved regulatory elements of herbicide resistance genes

    Directory of Open Access Journals (Sweden)

    Khalid Mahmood

    2016-08-01

    Full Text Available Herbicide resistance is a ubiquitous challenge to herbicide sustainability and a looming threat to control weeds in crops. Recently four genes were found constituently over-expressed in herbicide resistant individuals of Lolium rigidum, a close relative of L. multiflorum. These include two cytochrome P450s, one nitronate monooxygenase and one glycosyl-transferase. Higher expressions of these four herbicide metabolism related (HMR genes were also observed after herbicides exposure in the gene expression databases, indicating them a reliable marker. In order to get an overview of herbicidal resistance status of Lolium multiflorum L, 19 field populations were collected. Among these populations, four populations were found to be resistant to acetolactate synthase (ALS inhibitors while three exhibited resistance to acetyl-CoA carboxylase (ACCase inhibitors in our initial screening and dose response study. The genotyping showed the presence of mutations Trp-574-Leu and Ile-2041-Asn in ALS and ACCase, respectively and qPCR experiments revealed the enhanced expression of HMR genes in individuals of certain resistant populations. Moreover, co-expression networks and promoter analyses of HMR genes in O.sativa and A.thaliana resulted in the identification of a cis-regulatory motif and zinc finger transcription factors. The identified transcription factors were highly expressed similar to HMR genes in response to xenobiotics whereas the identified motif known to play a vital role in coping with environmental stresses and maintaining genome stability. Overall, our findings provide an important step forward towards a better understanding of metabolism-based herbicide resistance that can be utilized to devise novel strategies of weed management.

  16. Stochastic Boolean networks: An efficient approach to modeling gene regulatory networks

    Directory of Open Access Journals (Sweden)

    Liang Jinghang

    2012-08-01

    Full Text Available Abstract Background Various computational models have been of interest due to their use in the modelling of gene regulatory networks (GRNs. As a logical model, probabilistic Boolean networks (PBNs consider molecular and genetic noise, so the study of PBNs provides significant insights into the understanding of the dynamics of GRNs. This will ultimately lead to advances in developing therapeutic methods that intervene in the process of disease development and progression. The applications of PBNs, however, are hindered by the complexities involved in the computation of the state transition matrix and the steady-state distribution of a PBN. For a PBN with n genes and N Boolean networks, the complexity to compute the state transition matrix is O(nN22n or O(nN2n for a sparse matrix. Results This paper presents a novel implementation of PBNs based on the notions of stochastic logic and stochastic computation. This stochastic implementation of a PBN is referred to as a stochastic Boolean network (SBN. An SBN provides an accurate and efficient simulation of a PBN without and with random gene perturbation. The state transition matrix is computed in an SBN with a complexity of O(nL2n, where L is a factor related to the stochastic sequence length. Since the minimum sequence length required for obtaining an evaluation accuracy approximately increases in a polynomial order with the number of genes, n, and the number of Boolean networks, N, usually increases exponentially with n, L is typically smaller than N, especially in a network with a large number of genes. Hence, the computational efficiency of an SBN is primarily limited by the number of genes, but not directly by the total possible number of Boolean networks. Furthermore, a time-frame expanded SBN enables an efficient analysis of the steady-state distribution of a PBN. These findings are supported by the simulation results of a simplified p53 network, several randomly generated networks and a

  17. Two different modes of oscillation in a gene transcription regulatory network with interlinked positive and negative feedback loops

    Science.gov (United States)

    Karmakar, Rajesh

    2016-12-01

    We study the oscillatory behavior of a gene regulatory network with interlinked positive and negative feedback loop. The frequency and amplitude are two important properties of oscillation. The studied network produces two different modes of oscillation. In one mode (mode-I), frequency of oscillation remains constant over a wide range of amplitude and in the other mode (mode-II) the amplitude of oscillation remains constant over a wide range of frequency. Our study reproduces both features of oscillations in a single gene regulatory network and shows that the negative plus positive feedback loops in gene regulatory network offer additional advantage. We identified the key parameters/variables responsible for different modes of oscillation. The network is flexible in switching between different modes by choosing appropriately the required parameters/variables.

  18. Extensive evolutionary changes in regulatory element activity during human origins are associated with altered gene expression and positive selection.

    Directory of Open Access Journals (Sweden)

    Yoichiro Shibata

    2012-06-01

    Full Text Available Understanding the molecular basis for phenotypic differences between humans and other primates remains an outstanding challenge. Mutations in non-coding regulatory DNA that alter gene expression have been hypothesized as a key driver of these phenotypic differences. This has been supported by differential gene expression analyses in general, but not by the identification of specific regulatory elements responsible for changes in transcription and phenotype. To identify the genetic source of regulatory differences, we mapped DNaseI hypersensitive (DHS sites, which mark all types of active gene regulatory elements, genome-wide in the same cell type isolated from human, chimpanzee, and macaque. Most DHS sites were conserved among all three species, as expected based on their central role in regulating transcription. However, we found evidence that several hundred DHS sites were gained or lost on the lineages leading to modern human and chimpanzee. Species-specific DHS site gains are enriched near differentially expressed genes, are positively correlated with increased transcription, show evidence of branch-specific positive selection, and overlap with active chromatin marks. Species-specific sequence differences in transcription factor motifs found within these DHS sites are linked with species-specific changes in chromatin accessibility. Together, these indicate that the regulatory elements identified here are genetic contributors to transcriptional and phenotypic differences among primate species.

  19. A classification-based framework for predicting and analyzing gene regulatory response.

    Science.gov (United States)

    Kundaje, Anshul; Middendorf, Manuel; Shah, Mihir; Wiggins, Chris H; Freund, Yoav; Leslie, Christina

    2006-03-20

    We have recently introduced a predictive framework for studying gene transcriptional regulation in simpler organisms using a novel supervised learning algorithm called GeneClass. GeneClass is motivated by the hypothesis that in model organisms such as Saccharomyces cerevisiae, we can learn a decision rule for predicting whether a gene is up- or down-regulated in a particular microarray experiment based on the presence of binding site subsequences ("motifs") in the gene's regulatory region and the expression levels of regulators such as transcription factors in the experiment ("parents"). GeneClass formulates the learning task as a classification problem--predicting +1 and -1 labels corresponding to up- and down-regulation beyond the levels of biological and measurement noise in microarray measurements. Using the Adaboost algorithm, GeneClass learns a prediction function in the form of an alternating decision tree, a margin-based generalization of a decision tree. In the current work, we introduce a new, robust version of the GeneClass algorithm that increases stability and computational efficiency, yielding a more scalable and reliable predictive model. The improved stability of the prediction tree enables us to introduce a detailed post-processing framework for biological interpretation, including individual and group target gene analysis to reveal condition-specific regulation programs and to suggest signaling pathways. Robust GeneClass uses a novel stabilized variant of boosting that allows a set of correlated features, rather than single features, to be included at nodes of the tree; in this way, biologically important features that are correlated with the single best feature are retained rather than decorrelated and lost in the next round of boosting. Other computational developments include fast matrix computation of the loss function for all features, allowing scalability to large datasets, and the use of abstaining weak rules, which results in a more

  20. Gene and metabolite regulatory network analysis of early developing fruit tissues highlights new candidate genes for the control of tomato fruit composition and development.

    Science.gov (United States)

    Mounet, Fabien; Moing, Annick; Garcia, Virginie; Petit, Johann; Maucourt, Michael; Deborde, Catherine; Bernillon, Stéphane; Le Gall, Gwénaëlle; Colquhoun, Ian; Defernez, Marianne; Giraudel, Jean-Luc; Rolin, Dominique; Rothan, Christophe; Lemaire-Chamley, Martine

    2009-03-01

    Variations in early fruit development and composition may have major impacts on the taste and the overall quality of ripe tomato (Solanum lycopersicum) fruit. To get insights into the networks involved in these coordinated processes and to identify key regulatory genes, we explored the transcriptional and metabolic changes in expanding tomato fruit tissues using multivariate analysis and gene-metabolite correlation networks. To this end, we demonstrated and took advantage of the existence of clear structural and compositional differences between expanding mesocarp and locular tissue during fruit development (12-35 d postanthesis). Transcriptome and metabolome analyses were carried out with tomato microarrays and analytical methods including proton nuclear magnetic resonance and liquid chromatography-mass spectrometry, respectively. Pairwise comparisons of metabolite contents and gene expression profiles detected up to 37 direct gene-metabolite correlations involving regulatory genes (e.g. the correlations between glutamine, bZIP, and MYB transcription factors). Correlation network analyses revealed the existence of major hub genes correlated with 10 or more regulatory transcripts and embedded in a large regulatory network. This approach proved to be a valuable strategy for identifying specific subsets of genes implicated in key processes of fruit development and metabolism, which are therefore potential targets for genetic improvement of tomato fruit quality.

  1. Sub-circuits of a gene regulatory network control a developmental epithelial-mesenchymal transition.

    Science.gov (United States)

    Saunders, Lindsay R; McClay, David R

    2014-04-01

    Epithelial-mesenchymal transition (EMT) is a fundamental cell state change that transforms epithelial to mesenchymal cells during embryonic development, adult tissue repair and cancer metastasis. EMT includes a complex series of intermediate cell state changes including remodeling of the basement membrane, apical constriction, epithelial de-adhesion, directed motility, loss of apical-basal polarity, and acquisition of mesenchymal adhesion and polarity. Transcriptional regulatory state changes must ultimately coordinate the timing and execution of these cell biological processes. A well-characterized gene regulatory network (GRN) in the sea urchin embryo was used to identify the transcription factors that control five distinct cell changes during EMT. Single transcription factors were perturbed and the consequences followed with in vivo time-lapse imaging or immunostaining assays. The data show that five different sub-circuits of the GRN control five distinct cell biological activities, each part of the complex EMT process. Thirteen transcription factors (TFs) expressed specifically in pre-EMT cells were required for EMT. Three TFs highest in the GRN specified and activated EMT (alx1, ets1, tbr) and the 10 TFs downstream of those (tel, erg, hex, tgif, snail, twist, foxn2/3, dri, foxb, foxo) were also required for EMT. No single TF functioned in all five sub-circuits, indicating that there is no EMT master regulator. Instead, the resulting sub-circuit topologies suggest EMT requires multiple simultaneous regulatory mechanisms: forward cascades, parallel inputs and positive-feedback lock downs. The interconnected and overlapping nature of the sub-circuits provides one explanation for the seamless orchestration by the embryo of cell state changes leading to successful EMT.

  2. A Dynamic Gene Regulatory Network Model That Recovers the Cyclic Behavior of Arabidopsis thaliana Cell Cycle

    Science.gov (United States)

    Ortiz-Gutiérrez, Elizabeth; García-Cruz, Karla; Azpeitia, Eugenio; Castillo, Aaron; Sánchez, María de la Paz; Álvarez-Buylla, Elena R.

    2015-01-01

    Cell cycle control is fundamental in eukaryotic development. Several modeling efforts have been used to integrate the complex network of interacting molecular components involved in cell cycle dynamics. In this paper, we aimed at recovering the regulatory logic upstream of previously known components of cell cycle control, with the aim of understanding the mechanisms underlying the emergence of the cyclic behavior of such components. We focus on Arabidopsis thaliana, but given that many components of cell cycle regulation are conserved among eukaryotes, when experimental data for this system was not available, we considered experimental results from yeast and animal systems. We are proposing a Boolean gene regulatory network (GRN) that converges into only one robust limit cycle attractor that closely resembles the cyclic behavior of the key cell-cycle molecular components and other regulators considered here. We validate the model by comparing our in silico configurations with data from loss- and gain-of-function mutants, where the endocyclic behavior also was recovered. Additionally, we approximate a continuous model and recovered the temporal periodic expression profiles of the cell-cycle molecular components involved, thus suggesting that the single limit cycle attractor recovered with the Boolean model is not an artifact of its discrete and synchronous nature, but rather an emergent consequence of the inherent characteristics of the regulatory logic proposed here. This dynamical model, hence provides a novel theoretical framework to address cell cycle regulation in plants, and it can also be used to propose novel predictions regarding cell cycle regulation in other eukaryotes. PMID:26340681

  3. Identification of Cell Wall Synthesis Regulatory Genes Controlling Biomass Characteristics and Yield in Rice (Oryza Sativa)

    Energy Technology Data Exchange (ETDEWEB)

    Peng, Zhaohua PEng [Mississippi State University; Ronald, Palmela [UC-Davis; Wang, Guo-Liang [The Ohio State University

    2013-04-26

    This project aims to identify the regulatory genes of rice cell wall synthesis pathways using a cell wall removal and regeneration system. We completed the gene expression profiling studies following the time course from cell wall removal to cell wall regeneration in rice suspension cells. We also completed, total proteome, nuclear subproteome and histone modification studies following the course from cell wall removal and cell wall regeneration process. A large number of differentially expressed regulatory genes and proteins were identified. Meanwhile, we generated RNAi and over-expression transgenic rice for 45 genes with at least 10 independent transgenic lines for each gene. In addition, we ordered T-DNA and transposon insertion mutants for 60 genes from Korea, Japan, and France and characterized the mutants. Overall, we have mutants and transgenic lines for over 90 genes, exceeded our proposed goal of generating mutants for 50 genes. Interesting Discoveries a) Cell wall re-synthesis in protoplasts may involve a novel cell wall synthesis mechanism. The synthesis of the primary cell wall is initiated in late cytokinesis with further modification during cell expansion. Phragmoplast plays an essential role in cell wall synthesis. It services as a scaffold for building the cell plate and formation of a new cell wall. Only one phragmoplast and one new cell wall is produced for each dividing cell. When the cell wall was removed enzymatically, we found that cell wall re-synthesis started from multiple locations simultaneously, suggesting that a novel mechanism is involved in cell wall re-synthesis. This observation raised many interesting questions, such as how the starting sites of cell wall synthesis are determined, whether phragmoplast and cell plate like structures are involved in cell wall re-synthesis, and more importantly whether the same set of enzymes and apparatus are used in cell wall re-synthesis as during cytokinesis. Given that many known cell wall

  4. Evidence of the regulatory effect of Ginkgo biloba extract on skin blood flow and study of its effects on urinary metabolites in healthy humans

    NARCIS (Netherlands)

    Boelsma, E.; Lamers, R.-J.A.N.; Hendriks, H.F.J.; Nesselrooij, J.H.J. van; Roza, L.

    2004-01-01

    Ginkgo biloba extract has been advocated for the improvement of blood circulation in circulatory disorders. This study investigated the effect of the Gingko biloba extract EGb 761 on skin blood flow in healthy volunteers and accompanying changes in urinary metabolites. Twenty-seven healthy middle-ag

  5. Intrinsic noise and deviations from criticality in Boolean gene-regulatory networks

    Science.gov (United States)

    Villegas, Pablo; Ruiz-Franco, José; Hidalgo, Jorge; Muñoz, Miguel A.

    2016-10-01

    Gene regulatory networks can be successfully modeled as Boolean networks. A much discussed hypothesis says that such model networks reproduce empirical findings the best if they are tuned to operate at criticality, i.e. at the borderline between their ordered and disordered phases. Critical networks have been argued to lead to a number of functional advantages such as maximal dynamical range, maximal sensitivity to environmental changes, as well as to an excellent tradeoff between stability and flexibility. Here, we study the effect of noise within the context of Boolean networks trained to learn complex tasks under supervision. We verify that quasi-critical networks are the ones learning in the fastest possible way –even for asynchronous updating rules– and that the larger the task complexity the smaller the distance to criticality. On the other hand, when additional sources of intrinsic noise in the network states and/or in its wiring pattern are introduced, the optimally performing networks become clearly subcritical. These results suggest that in order to compensate for inherent stochasticity, regulatory and other type of biological networks might become subcritical rather than being critical, all the most if the task to be performed has limited complexity.

  6. Intrinsic noise and deviations from criticality in Boolean gene-regulatory networks

    Science.gov (United States)

    Villegas, Pablo; Ruiz-Franco, José; Hidalgo, Jorge; Muñoz, Miguel A.

    2016-01-01

    Gene regulatory networks can be successfully modeled as Boolean networks. A much discussed hypothesis says that such model networks reproduce empirical findings the best if they are tuned to operate at criticality, i.e. at the borderline between their ordered and disordered phases. Critical networks have been argued to lead to a number of functional advantages such as maximal dynamical range, maximal sensitivity to environmental changes, as well as to an excellent tradeoff between stability and flexibility. Here, we study the effect of noise within the context of Boolean networks trained to learn complex tasks under supervision. We verify that quasi-critical networks are the ones learning in the fastest possible way –even for asynchronous updating rules– and that the larger the task complexity the smaller the distance to criticality. On the other hand, when additional sources of intrinsic noise in the network states and/or in its wiring pattern are introduced, the optimally performing networks become clearly subcritical. These results suggest that in order to compensate for inherent stochasticity, regulatory and other type of biological networks might become subcritical rather than being critical, all the most if the task to be performed has limited complexity. PMID:27713479

  7. Localizing potentially active post-transcriptional regulations in the Ewing's sarcoma gene regulatory network

    Directory of Open Access Journals (Sweden)

    Delyon Bernard

    2010-11-01

    Full Text Available Abstract Background A wide range of techniques is now available for analyzing regulatory networks. Nonetheless, most of these techniques fail to interpret large-scale transcriptional data at the post-translational level. Results We address the question of using large-scale transcriptomic observation of a system perturbation to analyze a regulatory network which contained several types of interactions - transcriptional and post-translational. Our method consisted of post-processing the outputs of an open-source tool named BioQuali - an automatic constraint-based analysis mimicking biologist's local reasoning on a large scale. The post-processing relied on differences in the behavior of the transcriptional and post-translational levels in the network. As a case study, we analyzed a network representation of the genes and proteins controlled by an oncogene in the context of Ewing's sarcoma. The analysis allowed us to pinpoint active interactions specific to this cancer. We also identified the parts of the network which were incomplete and should be submitted for further investigation. Conclusions The proposed approach is effective for the qualitative analysis of cancer networks. It allows the integrative use of experimental data of various types in order to identify the specific information that should be considered a priority in the initial - and possibly very large - experimental dataset. Iteratively, new dataset can be introduced into the analysis to improve the network representation and make it more specific.

  8. A negative regulatory loop between microRNA and Hox gene controls posterior identities in Caenorhabditis elegans.

    Directory of Open Access Journals (Sweden)

    Zhongying Zhao

    2010-09-01

    Full Text Available MicroRNAs (miRNAs have been found to regulate gene expression across eukaryotic species, but the function of most miRNA genes remains unknown. Here we describe how the analysis of the expression patterns of a well-conserved miRNA gene, mir-57, at cellular resolution for every minute during early development of Caenorhabditis elegans provided key insights in understanding its function. Remarkably, mir-57 expression shows strong positional bias but little tissue specificity, a pattern reminiscent of Hox gene function. Despite the minor defects produced by a loss of function mutation, overexpression of mir-57 causes dramatic posterior defects, which also mimic the phenotypes of mutant alleles of a posterior Hox gene, nob-1, an Abd homolog. More importantly, nob-1 expression is found in the same two posterior AB sublineages as those expressing mir-57 but with an earlier onset. Intriguingly, nob-1 functions as an activator for mir-57 expression; it is also a direct target of mir-57. In agreement with this, loss of mir-57 function partially rescues the nob-1 allele defects, indicating a negative feedback regulatory loop between the miRNA and Hox gene to provide positional cues. Given the conservation of the miRNA and Hox gene, the regulatory mechanism might be broadly used across species. The strategy used here to explore mir-57 function provides a path to dissect the regulatory relationship between genes.

  9. Evolutionary analysis and lateral gene transfer of two-component regulatory systems associated with heavy-metal tolerance in bacteria.

    Science.gov (United States)

    Bouzat, Juan L; Hoostal, Matthew J

    2013-05-01

    Microorganisms have adapted intricate signal transduction mechanisms to coordinate tolerance to toxic levels of metals, including two-component regulatory systems (TCRS). In particular, both cop and czc operons are regulated by TCRS; the cop operon plays a key role in bacterial tolerance to copper, whereas the czc operon is involved in the efflux of cadmium, zinc, and cobalt from the cell. Although the molecular physiology of heavy metal tolerance genes has been extensively studied, their evolutionary relationships are not well-understood. Phylogenetic relationships among heavy-metal efflux proteins and their corresponding two-component regulatory proteins revealed orthologous and paralogous relationships from species divergences and ancient gene duplications. The presence of heavy metal tolerance genes on bacterial plasmids suggests these genes may be prone to spread through horizontal gene transfer. Phylogenetic inferences revealed nine potential examples of lateral gene transfer associated with metal efflux proteins and two examples for regulatory proteins. Notably, four of the examples suggest lateral transfer across major evolutionary domains. In most cases, differences in GC content in metal tolerance genes and their corresponding host genomes confirmed lateral gene transfer events. Three-dimensional protein structures predicted for the response regulators encoded by cop and czc operons showed a high degree of structural similarity with other known proteins involved in TCRS signal transduction, which suggests common evolutionary origins of functional phenotypes and similar mechanisms of action for these response regulators.

  10. Prioritizing predicted cis-regulatory elements for co-expressed gene sets based on Lasso regression models.

    Science.gov (United States)

    Hu, Hong; Roqueiro, Damian; Dai, Yang

    2011-01-01

    Computational prediction of cis-regulatory elements for a set of co-expressed genes based on sequence analysis provides an overwhelming volume of potential transcription factor binding sites. It presents a challenge to prioritize transcription factors for regulatory functional studies. A novel approach based on the use of Lasso regression models is proposed to address this problem. We examine the ability of the Lasso model using time-course microarray data obtained from a comprehensive study of gene expression profiles in skin and mucosal wounds in mouse over all stages of wound healing.

  11. Regulatory Volume Decrease in Neural Precursor Cells: Taurine Efflux and Gene Microarray Analysis

    Directory of Open Access Journals (Sweden)

    Reyna Hernández-Benítez

    2014-11-01

    Full Text Available Background/Aims: Neural stem/ progenitor cells (NPCs endure important changes in cell volume during growth, proliferation and migration. As a first approach to know about NPC response to cell volume changes, the Regulatory Volume Decrease (RVD subsequent to hypotonic swelling was investigated. Methods: NPCs obtained from the mesencephalon and the subventricular zone of embryonic and adult mice, respectively, were grown and cultured as neurospheres. Cell volume changes were measured by large-angle light-scattering and taurine efflux by [3H]-taurine. Expression of genes encoding molecules related to RVD was analysed using a DNA microarray obtained from NPC samples. Results: Embryonic and adult NPCs exposed to osmolarity reduction (H15, H30, H40 exhibited rapid swelling followed by RVD. The magnitude, efficiency and pharmacological profile, of RVD and of [3H]-taurine osmosensitive efflux were comparable to those found in cultured brain cells, astrocytes and neurons. The relative expression of genes encoding molecules related to volume regulation, i.e. K+ and Cl- channels, cotransporters, exchangers and aquaporins were identified in NPCs. Conclusion: NPCs show the ability to respond to hypotonic-evoked volume changes by adaptative recovery processes, similar to those found in other cultured brain cells. Genes related to molecules involved in RVD were found expressed in NPCs.

  12. The HY5-PIF regulatory module coordinates light and temperature control of photosynthetic gene transcription.

    Directory of Open Access Journals (Sweden)

    Gabriela Toledo-Ortiz

    2014-06-01

    Full Text Available The ability to interpret daily and seasonal alterations in light and temperature signals is essential for plant survival. This is particularly important during seedling establishment when the phytochrome photoreceptors activate photosynthetic pigment production for photoautotrophic growth. Phytochromes accomplish this partly through the suppression of phytochrome interacting factors (PIFs, negative regulators of chlorophyll and carotenoid biosynthesis. While the bZIP transcription factor long hypocotyl 5 (HY5, a potent PIF antagonist, promotes photosynthetic pigment accumulation in response to light. Here we demonstrate that by directly targeting a common promoter cis-element (G-box, HY5 and PIFs form a dynamic activation-suppression transcriptional module responsive to light and temperature cues. This antagonistic regulatory module provides a simple, direct mechanism through which environmental change can redirect transcriptional control of genes required for photosynthesis and photoprotection. In the regulation of photopigment biosynthesis genes, HY5 and PIFs do not operate alone, but with the circadian clock. However, sudden changes in light or temperature conditions can trigger changes in HY5 and PIFs abundance that adjust the expression of common target genes to optimise photosynthetic performance and growth.

  13. Rearrangement of Upstream Regulatory Elements Leads to Ectopic Expression of the Drosophila Mulleri Adh-2 Gene

    Science.gov (United States)

    Falb, D.; Fischer, J.; Maniatis, T.

    1992-01-01

    The Adh-2 gene of Drosophila mulleri is expressed in the larval fat body and the adult fat body and hindgut, and a 1500-bp element located 2-3 kb upstream of the Adh-2 promoter is necessary for maximal levels of transcription. Previous work demonstrated that deletion of sequences between this upstream element and the Adh-2 promoter results in Adh-2 gene expression in a novel larval tissue, the middle midgut. In this study we show that the upstream element possesses all of the characteristics of a transcriptional enhancer: its activity is independent of orientation, it acts on a heterologous promoter, and it functions at various positions both 5' and 3' to the Adh-2 gene. Full enhancer function can be localized to a 750-bp element, although other regions possess some redundant activity. The ectopic expression pattern is dependent on the proximity of at least two sequence elements. Thus, tissue-specific transcription can involve complex proximity-dependent interactions among combinations of regulatory elements. PMID:1459428

  14. Gene regulatory network modeling via global optimization of high-order dynamic Bayesian network

    Directory of Open Access Journals (Sweden)

    Xuan Nguyen

    2012-06-01

    Full Text Available Abstract Background Dynamic Bayesian network (DBN is among the mainstream approaches for modeling various biological networks, including the gene regulatory network (GRN. Most current methods for learning DBN employ either local search such as hill-climbing, or a meta stochastic global optimization framework such as genetic algorithm or simulated annealing, which are only able to locate sub-optimal solutions. Further, current DBN applications have essentially been limited to small sized networks. Results To overcome the above difficulties, we introduce here a deterministic global optimization based DBN approach for reverse engineering genetic networks from time course gene expression data. For such DBN models that consist only of inter time slice arcs, we show that there exists a polynomial time algorithm for learning the globally optimal network structure. The proposed approach, named GlobalMIT+, employs the recently proposed information theoretic scoring metric named mutual information test (MIT. GlobalMIT+ is able to learn high-order time delayed genetic interactions, which are common to most biological systems. Evaluation of the approach using both synthetic and real data sets, including a 733 cyanobacterial gene expression data set, shows significantly improved performance over other techniques. Conclusions Our studies demonstrate that deterministic global optimization approaches can infer large scale genetic networks.

  15. A bayesian framework that integrates heterogeneous data for inferring gene regulatory networks.

    Science.gov (United States)

    Santra, Tapesh

    2014-01-01

    Reconstruction of gene regulatory networks (GRNs) from experimental data is a fundamental challenge in systems biology. A number of computational approaches have been developed to infer GRNs from mRNA expression profiles. However, expression profiles alone are proving to be insufficient for inferring GRN topologies with reasonable accuracy. Recently, it has been shown that integration of external data sources (such as gene and protein sequence information, gene ontology data, protein-protein interactions) with mRNA expression profiles may increase the reliability of the inference process. Here, I propose a new approach that incorporates transcription factor binding sites (TFBS) and physical protein interactions (PPI) among transcription factors (TFs) in a Bayesian variable selection (BVS) algorithm which can infer GRNs from mRNA expression profiles subjected to genetic perturbations. Using real experimental data, I show that the integration of TFBS and PPI data with mRNA expression profiles leads to significantly more accurate networks than those inferred from expression profiles alone. Additionally, the performance of the proposed algorithm is compared with a series of least absolute shrinkage and selection operator (LASSO) regression-based network inference methods that can also incorporate prior knowledge in the inference framework. The results of this comparison suggest that BVS can outperform LASSO regression-based method in some circumstances.

  16. A Bayesian Framework that integrates heterogeneous data for inferring gene regulatory networks

    Directory of Open Access Journals (Sweden)

    Tapesh eSantra

    2014-05-01

    Full Text Available Reconstruction of gene regulatory networks (GRNs from experimental data is a fundamental challenge in systems biology. A number of computational approaches have been developed to infer GRNs from mRNA expression profiles. However, expression profiles alone are proving to be insufficient for inferring GRN topologies with reasonable accuracy. Recently, it has been shown that integration of external data sources (such as gene and protein sequence information, gene ontology data, protein protein interactions with mRNA expression profiles may increase the reliability of the inference process. Here, I propose a new approach that incorporates transcription factor binding sites (TFBS and physical protein interactions (PPI among transcription factors (TFs in a Bayesian Variable Selection (BVS algorithm which can infer GRNs from mRNA expression profiles subjected to genetic perturbations. Using real experimental data, I show that the integration of TFBS and PPI data with mRNA expression profiles leads to significantly more accurate networks than those inferred from expression profiles alone. Additionally, the performance of the proposed algorithm is compared with a series of LASSO regression based network inference methods that can also incorporate prior knowledge in the inference framework. The results of this comparison suggest that BVS can outperform LASSO regression based method in some circumstances.

  17. Semi-supervised prediction of gene regulatory networks using machine learning algorithms

    Indian Academy of Sciences (India)

    Nihir Patel; T L Wang

    2015-10-01

    Use of computational methods to predict gene regulatory networks (GRNs) from gene expression data is a challenging task. Many studies have been conducted using unsupervised methods to fulfill the task; however, such methods usually yield low prediction accuracies due to the lack of training data. In this article, we propose semi-supervised methods for GRN prediction by utilizing two machine learning algorithms, namely, support vector machines (SVM) and random forests (RF). The semi-supervised methods make use of unlabelled data for training. We investigated inductive and transductive learning approaches, both of which adopt an iterative procedure to obtain reliable negative training data from the unlabelled data. We then applied our semi-supervised methods to gene expression data of Escherichia coli and Saccharomyces cerevisiae, and evaluated the performance of our methods using the expression data. Our analysis indicated that the transductive learning approach outperformed the inductive learning approach for both organisms. However, there was no conclusive difference identified in the performance of SVM and RF. Experimental results also showed that the proposed semi-supervised methods performed better than existing supervised methods for both organisms.

  18. Prolactin regulatory element-binding protein is involved in suppression of the adiponectin gene in vivo.

    Science.gov (United States)

    Zhang, X Z; Imachi, H; Lyu, J Y; Fukunaga, K; Sato, S; Ibata, T; Kobayashi, T; Yoshimoto, T; Kikuchi, F; Dong, T; Murao, K

    2017-04-01

    Prolactin regulatory element-binding protein (PREB), a member of the WD-repeat protein family, has been recognized as a transcriptional factor that regulates prolactin promoter activity in the anterior pituitary of rats. PREB is expressed not only in the pituitary but also in various other tissues, including the adipose tissue. Previous studies have shown that PREB acts as a transcriptional regulator and suppresses the expression of the adiponectin gene in cultured 3T3L1 preadipocytes. The aim of this study was to further examine the potential role of PREB in adipose tissue in vivo. Transgenic mice that overexpressing PREB (PREB transgenic mice) were generated. Insulin resistance was evaluated in PREB transgenic mice using glucose and insulin tolerance tests. Adiponectin expression in the adipose tissue was examined by western blot analysis and quantitative polymerase chain reaction (qPCR). The expression levels of stearoyl-CoA desaturase (Scd) and adiponectin receptor 2(ADIPOR2) were quantified by qPCR. Glucose and insulin tolerance tests revealed insulin resistance in PREB transgenic mice. Serum adiponectin and leptin concentrations were decreased. Adiponectin gene expression was decreased in the adipose tissue, which was confirmed by the downregulation of the adiponectin-dependent hepatic Scd gene and upregulation of the ADIPOR2 gene in the liver of PREB transgenic mice. We also found that pioglitazone, an agonist for the peroxisome proliferator-activated receptor-r, improved the insulin resistance in the PREB transgenic mice after a 10-day feeding period. These results demonstrated that PREB might contribute to the regulation of adiponectin gene expression in vivo.

  19. Gene environment interaction in urinary bladder cancer with special reference to organochlorine pesticide: a case control study.

    Science.gov (United States)

    Sharma, Tusha; Jain, Smita; Verma, Ankur; Sharma, Nivedita; Gupta, Sanjay; Arora, Vinod Kumar; Dev Banerjee, Basu

    2013-01-01

    Urinary bladder cancer (UBC) is a common disease worldwide with a higher incidence rate in developed countries. Organochlorine pesticides (OCPs), potent endocrine disrupters, are found to be associated with several cancers such as prostate, breast, bladder, etc. Glutathione S-transferase (GST) is a polymorphic supergene family involved in the detoxification of numerous environmental toxins including OCPs. The present study was carried out in UBC subjects (n=50) and healthy control subjects (n=50) with an aim to determine the role of GSTM1 and GSTT1 polymorphism and its implication on the OCP detoxification or bioaccumulation which may increase the risk of UBC in humans. This study was also designed to identify the "gene-environment interaction" specifically between gene polymorphism in xenobiotic metabolizing genetic enzyme(s) and blood OCP levels. GSTM1/GSTT1 gene polymorphism was analysed by using multiplex PCR. OCPs levels in whole blood were estimated by Gas chromatography equipped with electron capture detector. The results demonstrated a significant (p^{-}/GSTT1^{-} (null) genotype in UBC cases without interfering the distribution of other GSTT1/GSTM1 genotypes. The blood levels of alpha (α), Beta (β), Gamma (γ), total - Hexachlorcyclohexane (HCH) and para-para - dichlorodiphenyltrichloroetane (p,p'-DDT) were found to be significantly (pcases as compared to controls. Multiple regression analysis revealed a significant interaction between β-HCH and GSTM1^{-} genotype (p^{-} genotype (penvironment interaction" may play a key role in increasing the risk for UBC in individuals who are genetically more susceptible due to presence of GSTM1/GSTT1 null deletion during their routine encounter with or exposure to OCPs.

  20. A regulatory network modeled from wild-type gene expression data guides functional predictions in Caenorhabditis elegans development

    Directory of Open Access Journals (Sweden)

    Stigler Brandilyn

    2012-06-01

    Full Text Available Abstract Background Complex gene regulatory networks underlie many cellular and developmental processes. While a variety of experimental approaches can be used to discover how genes interact, few biological systems have been systematically evaluated to the extent required for an experimental definition of the underlying network. Therefore, the development of computational methods that can use limited experimental data to define and model a gene regulatory network would provide a useful tool to evaluate many important but incompletely understood biological processes. Such methods can assist in extracting all relevant information from data that are available, identify unexpected regulatory relationships and prioritize future experiments. Results To facilitate the analysis of gene regulatory networks, we have developed a computational modeling pipeline method that complements traditional evaluation of experimental data. For a proof-of-concept example, we have focused on the gene regulatory network in the nematode C. elegans that mediates the developmental choice between mesodermal (muscle and ectodermal (skin cell fates in the embryonic C lineage. We have used gene expression data to build two models: a knowledge-driven model based on gene expression changes following gene perturbation experiments, and a data-driven mathematical model derived from time-course gene expression data recovered from wild-type animals. We show that both models can identify a rich set of network gene interactions. Importantly, the mathematical model built only from wild-type data can predict interactions demonstrated by the perturbation experiments better than chance, and better than an existing knowledge-driven model built from the same data set. The mathematical model also provides new biological insight, including a dissection of zygotic from maternal functions of a key transcriptional regulator, PAL-1, and identification of non-redundant activities of the T-box genes

  1. A regulatory network modeled from wild-type gene expression data guides functional predictions in Caenorhabditis elegans development.

    Science.gov (United States)

    Stigler, Brandilyn; Chamberlin, Helen M

    2012-06-26

    Complex gene regulatory networks underlie many cellular and developmental processes. While a variety of experimental approaches can be used to discover how genes interact, few biological systems have been systematically evaluated to the extent required for an experimental definition of the underlying network. Therefore, the development of computational methods that can use limited experimental data to define and model a gene regulatory network would provide a useful tool to evaluate many important but incompletely understood biological processes. Such methods can assist in extracting all relevant information from data that are available, identify unexpected regulatory relationships and prioritize future experiments. To facilitate the analysis of gene regulatory networks, we have developed a computational modeling pipeline method that complements traditional evaluation of experimental data. For a proof-of-concept example, we have focused on the gene regulatory network in the nematode C. elegans that mediates the developmental choice between mesodermal (muscle) and ectodermal (skin) cell fates in the embryonic C lineage. We have used gene expression data to build two models: a knowledge-driven model based on gene expression changes following gene perturbation experiments, and a data-driven mathematical model derived from time-course gene expression data recovered from wild-type animals. We show that both models can identify a rich set of network gene interactions. Importantly, the mathematical model built only from wild-type data can predict interactions demonstrated by the perturbation experiments better than chance, and better than an existing knowledge-driven model built from the same data set. The mathematical model also provides new biological insight, including a dissection of zygotic from maternal functions of a key transcriptional regulator, PAL-1, and identification of non-redundant activities of the T-box genes tbx-8 and tbx-9. This work provides a strong

  2. A review of integration strategies to support gene regulatory network construction.

    Science.gov (United States)

    Chen, Hailin; VanBuren, Vincent

    2012-01-01

    Gene regulatory network (GRN) construction is a central task of systems biology. Integration of different data sources to infer and construct GRNs is an important consideration for the success of this effort. In this paper, we will discuss distinctive strategies of data integration for GRN construction. Basically, the process of integration of different data sources is divided into two phases: the first phase is collection of the required data and the second phase is data processing with advanced algorithms to infer the GRNs. In this paper these two phases are called "structural integration" and "analytic integration," respectively. Compared with the nonintegration strategies, the integration strategies perform quite well and have better agreement with the experimental evidence.

  3. A Review of Integration Strategies to Support Gene Regulatory Network Construction

    Directory of Open Access Journals (Sweden)

    Hailin Chen

    2012-01-01

    Full Text Available Gene regulatory network (GRN construction is a central task of systems biology. Integration of different data sources to infer and construct GRNs is an important consideration for the success of this effort. In this paper, we will discuss distinctive strategies of data integration for GRN construction. Basically, the process of integration of different data sources is divided into two phases: the first phase is collection of the required data and the second phase is data processing with advanced algorithms to infer the GRNs. In this paper these two phases are called “structural integration” and “analytic integration,” respectively. Compared with the nonintegration strategies, the integration strategies perform quite well and have better agreement with the experimental evidence.

  4. Cloning of a regulatory gene from Streptomyces cattleya and study on its cis-acting element.

    Science.gov (United States)

    Shang, G; Wang, Y

    2000-08-01

    Primers were designed from the highly conserved protein regions of luxl, one of the two component regulatory genes in prokaryotic, and an about 180 bp DNA from Streptomyces cattleya was amplified by PCR. Using this fragment as a probe, Southern hybridization was accomplished with chromosome DNA of S. cattleya, leading to the cloning of the foreign DNA into pBluescript (SK-). DNA sequencing and frame analysis showed an intact ORF consisting of 1800 bp; the G+C composition was 69.3%. Upstream from the ORF was a 249 bp AT rich region, downstream of the ORF several complicated secondary structures were found. DNA-binding assay by gel retardation demonstrated the presence of a protein that specifically bound to the 249 bp AT rich region. The region also showed anomalous electrophoretic mobility at low temperature, like that of a bent DNA molecule, indicating that the region contains a cis-acting element.

  5. Cloning of a regulatory gene from Streptomyces cattleya and study on its cis-acting element

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Primers were designed from the highly conserved protein regions of luxI, one of the two component regulatory genes in prokaryotic, and an about 180 bp DNA from Streptomyces cattleya was amplified by PCR. Using this fragment as a probe, Southern hybridization was accomplished with chromosome DNA of S. cattleya, leading to the cloning of the foreign DNA into pBluescript (SK-). DNA sequencing and frame analysis showed an intact ORF consisting of 1 800 bp; the G+C composition was 69.3%. Upstream from the ORF was a 249 bp AT rich region, downstream of the ORF several complicated secondary structures were found. DNA-binding assay by gel retardation demonstrated the presence of a protein that specifically bound to the 249 bp AT rich region. The region also showed anomalous electrophoretic mobility at low temperature, like that of a bent DNA molecule, indicating that the region contains a cis-acting element.

  6. Stochastic Resonance in a Gene Transcriptional Regulatory System with Time Delay

    Institute of Scientific and Technical Information of China (English)

    ZENG Chun-Hua; XIE Chong-Wei

    2008-01-01

    We study the stochastic resonance (SR) phenomenon in a time-delayed gene transcriptional regulatory system under the simultaneous action of a multiplicative noise and an additive noise and a weak periodic signal.The expression of the signal-to-noise ratio RSNR is obtained by applying the two-state theory in adiabatic limit under the condition of small delay time.The effects of delay time and intensity of the correlation between multiplicative and additive noise on RSNR are discussed.It is found that the delay time (T) enhances the SR of the system.The correlation intensity λ enhances the SR in the RSNR - D plot (D denotes the multiplicative noise intensity),but weakens the SR in the RSNR - α plot (α denotes the additive noise intensity).

  7. Cloning of a regulatory gene from Streptomyces cattleya and study on its cis-acting element

    Institute of Scientific and Technical Information of China (English)

    尚广东; 王以光

    2000-01-01

    Primers were designed from the highly conserved protein regions of luxl, one of the two component regulatory genes in prokaryotic, and an about 180 bp DNA from Streptomyces cattleya was amplified by PCR. Using this fragment as a probe, Southern hybridization was accomplished with chromosome DNA of S. cattleya, leading to the cloning of the foreign DNA into pBluescript (SK-). DNA sequencing and frame analysis showed an intact ORF consisting of 1 800 bp; the G+C composition was 69.3%. Upstream from the ORF was a 249 bp AT rich region, downstream of the ORF several complicated secondary structures were found. DNA-binding assay by gel retardation demonstrated the presence of a protein that specifically bound to the 249 bp AT rich region. The region also showed anomalous electrophoretic mobility at low temperature, like that of a bent DNA molecule, indicating that the region contains a c/s-acting element.

  8. The architecture of gene regulatory variation across multiple human tissues: the MuTHER study.

    Directory of Open Access Journals (Sweden)

    Alexandra C Nica

    Full Text Available While there have been studies exploring regulatory variation in one or more tissues, the complexity of tissue-specificity in multiple primary tissues is not yet well understood. We explore in depth the role of cis-regulatory variation in three human tissues: lymphoblastoid cell lines (LCL, skin, and fat. The samples (156 LCL, 160 skin, 166 fat were derived simultaneously from a subset of well-phenotyped healthy female twins of the MuTHER resource. We discover an abundance of cis-eQTLs in each tissue similar to previous estimates (858 or 4.7% of genes. In addition, we apply factor analysis (FA to remove effects of latent variables, thus more than doubling the number of our discoveries (1,822 eQTL genes. The unique study design (Matched Co-Twin Analysis--MCTA permits immediate replication of eQTLs using co-twins (93%-98% and validation of the considerable gain in eQTL discovery after FA correction. We highlight the challenges of comparing eQTLs between tissues. After verifying previous significance threshold-based estimates of tissue-specificity, we show their limitations given their dependency on statistical power. We propose that continuous estimates of the proportion of tissue-shared signals and direct comparison of the magnitude of effect on the fold change in expression are essential properties that jointly provide a biologically realistic view of tissue-specificity. Under this framework we demonstrate that 30% of eQTLs are shared among the three tissues studied, while another 29% appear exclusively tissue-specific. However, even among the shared eQTLs, a substantial proportion (10%-20% have significant differences in the magnitude of fold change between genotypic classes across tissues. Our results underline the need to account for the complexity of eQTL tissue-specificity in an effort to assess consequences of such variants for complex traits.

  9. The Architecture of Gene Regulatory Variation across Multiple Human Tissues: The MuTHER Study

    Science.gov (United States)

    Nica, Alexandra C.; Parts, Leopold; Glass, Daniel; Nisbet, James; Barrett, Amy; Sekowska, Magdalena; Travers, Mary; Potter, Simon; Grundberg, Elin; Small, Kerrin; Hedman, Åsa K.; Bataille, Veronique; Tzenova Bell, Jordana; Surdulescu, Gabriela; Dimas, Antigone S.; Ingle, Catherine; Nestle, Frank O.; di Meglio, Paola; Min, Josine L.; Wilk, Alicja; Hammond, Christopher J.; Hassanali, Neelam; Yang, Tsun-Po; Montgomery, Stephen B.; O'Rahilly, Steve; Lindgren, Cecilia M.; Zondervan, Krina T.; Soranzo, Nicole; Barroso, Inês; Durbin, Richard; Ahmadi, Kourosh; Deloukas, Panos; McCarthy, Mark I.; Dermitzakis, Emmanouil T.; Spector, Timothy D.

    2011-01-01

    While there have been studies exploring regulatory variation in one or more tissues, the complexity of tissue-specificity in multiple primary tissues is not yet well understood. We explore in depth the role of cis-regulatory variation in three human tissues: lymphoblastoid cell lines (LCL), skin, and fat. The samples (156 LCL, 160 skin, 166 fat) were derived simultaneously from a subset of well-phenotyped healthy female twins of the MuTHER resource. We discover an abundance of cis-eQTLs in each tissue similar to previous estimates (858 or 4.7% of genes). In addition, we apply factor analysis (FA) to remove effects of latent variables, thus more than doubling the number of our discoveries (1,822 eQTL genes). The unique study design (Matched Co-Twin Analysis—MCTA) permits immediate replication of eQTLs using co-twins (93%–98%) and validation of the considerable gain in eQTL discovery after FA correction. We highlight the challenges of comparing eQTLs between tissues. After verifying previous significance threshold-based estimates of tissue-specificity, we show their limitations given their dependency on statistical power. We propose that continuous estimates of the proportion of tissue-shared signals and direct comparison of the magnitude of effect on the fold change in expression are essential properties that jointly provide a biologically realistic view of tissue-specificity. Under this framework we demonstrate that 30% of eQTLs are shared among the three tissues studied, while another 29% appear exclusively tissue-specific. However, even among the shared eQTLs, a substantial proportion (10%–20%) have significant differences in the magnitude of fold change between genotypic classes across tissues. Our results underline the need to account for the complexity of eQTL tissue-specificity in an effort to assess consequences of such variants for complex traits. PMID:21304890

  10. Interferon regulatory factor 5 gene polymorphism in Egyptian children with systemic lupus erythematosus.

    Science.gov (United States)

    Hammad, A; Mossad, Y M; Nasef, N; Eid, R

    2017-01-01

    Background Increased expression of interferon-inducible genes is implicated in the pathogenesis of systemic lupus erythematosus (SLE). Interferon regulatory factor 5 (IRF5) is one of the transcription factors regulating interferon and was proved to be implicated in the pathogenesis of SLE in different populations. Objectives The objective of this study was to investigate the correlation between polymorphisms of the IRF5 gene and SLE susceptibility in a cohort of Egyptian children and to investigate their association with clinico-pathological features, especially lupus nephritis. Subjects and methods Typing of interferon regulatory factor 5 rs10954213, rs2004640 and rs2280714 polymorphisms were done using polymerase chain reaction-restriction fragment length polymorphism for 100 children with SLE and 100 matched healthy controls. Results Children with SLE had more frequent T allele and TT genotype of rs2004640 ( Pc = 0.003 and 0.024, respectively) compared to controls. Patients with nephritis had more frequent T allele of rs2004640 compared to controls ( Pc = 0.003). However the allele and genotype frequencies of the three studied polymorphisms did not show any difference in patients with nephritis in comparison to those without nephritis. Haplotype GTA of rs10954213, rs2004640 and rs2280714, respectively, was more frequent in lupus patients in comparison to controls ( p = 0.01) while the haplotype GGG was more frequent in controls than lupus patients ( p = 0.011). Conclusion The rs2004640 T allele and TT genotype and GTA haplotype of rs rs10954213, rs2004640, and rs2280714, respectively, can be considered as risk factors for the development of SLE. The presence of the rs2004640 T allele increases the risk of nephritis development in Egyptian children with SLE.

  11. Evolution of New cis-Regulatory Motifs Required for Cell-Specific Gene Expression in Caenorhabditis.

    Directory of Open Access Journals (Sweden)

    Michalis Barkoulas

    2016-09-01

    Full Text Available Patterning of C. elegans vulval cell fates relies on inductive signaling. In this induction event, a single cell, the gonadal anchor cell, secretes LIN-3/EGF and induces three out of six competent precursor cells to acquire a vulval fate. We previously showed that this developmental system is robust to a four-fold variation in lin-3/EGF genetic dose. Here using single-molecule FISH, we find that the mean level of expression of lin-3 in the anchor cell is remarkably conserved. No change in lin-3 expression level could be detected among C. elegans wild isolates and only a low level of change-less than 30%-in the Caenorhabditis genus and in Oscheius tipulae. In C. elegans, lin-3 expression in the anchor cell is known to require three transcription factor binding sites, specifically two E-boxes and a nuclear-hormone-receptor (NHR binding site. Mutation of any of these three elements in C. elegans results in a dramatic decrease in lin-3 expression. Yet only a single E-box is found in the Drosophilae supergroup of Caenorhabditis species, including C. angaria, while the NHR-binding site likely only evolved at the base of the Elegans group. We find that a transgene from C. angaria bearing a single E-box is sufficient for normal expression in C. elegans. Even a short 58 bp cis-regulatory fragment from C. angaria with this single E-box is able to replace the three transcription factor binding sites at the endogenous C. elegans lin-3 locus, resulting in the wild-type expression level. Thus, regulatory evolution occurring in cis within a 58 bp lin-3 fragment, results in a strict requirement for the NHR binding site and a second E-box in C. elegans. This single-cell, single-molecule, quantitative and functional evo-devo study demonstrates that conserved expression levels can hide extensive change in cis-regulatory site requirements and highlights the evolution of new cis-regulatory elements required for cell-specific gene expression.

  12. Genes unlinked to the leptin receptor influence urinary albumin excretion in obese Zucker rats

    NARCIS (Netherlands)

    Kim, K.; Warden, C.H.; Griffey, S.M.; Vilches-Moure, J.G.; Hansen, S.; Cuppen, E.; Nijman, I.J.; Chiu, S.; Stern, J.S.

    2010-01-01

    We have previously shown that 90% of outbred obese Zucker Lepr(fa/fa) rats die prematurely of renal disease. Thus, renal disease in obese Zucker Lepr(fa/fa) rats may be caused by the LEPR mutation on chromosome 5, by the obesity, or it may be influenced by Zucker susceptibility alleles of genes on o

  13. A STAT6 gene polymorphism is associated with high infection levels in urinary schistosomiasis.

    Science.gov (United States)

    He, H; Isnard, A; Kouriba, B; Cabantous, S; Dessein, A; Doumbo, O; Chevillard, C

    2008-04-01

    Th2-mediated immunity is critical for human defence against schistosome, and susceptibility to infection is controlled by a major genetic locus, mapped on the 5q31-q33 region comprising the genes IL4, IL5 and IL13. We have reported an association between the rs1800925 polymorphism in the IL13 promoter and infection levels in a Dogon population (693 subjects in Ségué and 148 in Boul), where Schistosoma haematobium is endemic. In the same population, we investigated whether other polymorphisms in genes involved in type 2 cytokine immune response could affect susceptibility to schistosome infection. By logistic regression analysis, we found an association between a single-nucleotide polymorphism (SNP) in the STAT6 gene (rs324013) and infection levels (P=0.04). We confirmed this association in analyses restricted to subjects under 20 years age and living in Boul, the village with the highest levels of infection (P=0.005). We detected an additive effect of the rs324013 and rs1800925 polymorphisms (P=0.011). These SNPs were not strongly correlated with any other tested markers surrounding the two genes. Furthermore, electrophoretic mobility shift assay has shown that both polymorphisms affect transcription factor binding. These results are consistent with the Th2 cytokine pathway enhancing resistance to schistosome infection in humans.

  14. Expression of FGFR3 Protein and Gene Amplification in Urinary Bladder Lesions in Relation to Schistosomiasis

    Directory of Open Access Journals (Sweden)

    Olfat Hammam

    2017-04-01

    CONCLUSIONS: FGFR3 overexpression in malignant cases was significantly higher than in chronic cystitis. FGFR3 gene amplification was reported mainly in low grade and NNMBIC tumours. FGFR3 may be further studied as a subject for target therapy of bladder cancer.

  15. Prediction of Cis-Regulatory Elements Controlling Genes Differentially Expressed by Retinal and Choroidal Vascular Endothelial Cells.

    Science.gov (United States)

    Choi, Dongseok; Appukuttan, Binoy; Binek, Sierra J; Planck, Stephen R; Stout, J Timothy; Rosenbaum, James T; Smith, Justine R

    2008-01-01

    Cultured endothelial cells of the human retina and choroid demonstrate distinct patterns of gene expression. We hypothesized that differential gene expression reflected differences in the interactions of transcription factors and respective cis-regulatory motifs(s) in these two emdothelial cell subpopulations, recognizing that motifs often exist as modules. We tested this hypothesis in silico by using TRANSFAC Professional and CisModule to identify cis-regulatory motifs and modules in genes that were differentially expressed by human retinal versus choroidal endothelial cells, as identified by analysis of a microarray data set. Motifs corresponding to eight transcription factors were significantly (p < 0.05) differentially abundant in genes that were relatively highly expressed in retinal (i.e., GCCR, HMGIY, HSF1, p53, VDR) or choroidal (i.e., E2F, YY1, ZF5) endothelial cells. Predicted cis-regulatory modules were quite different for these two groups of genes. Our findings raise the possibility of exploiting specific cis-regulatory motifs to target therapy at the ocular endothelial cells subtypes responsible for neovascular age-related macular degeneration or proliferative diabetic retinopathy.

  16. Regulatory RNAs in Bacillus subtilis: a Gram-Positive Perspective on Bacterial RNA-Mediated Regulation of Gene Expression.

    Science.gov (United States)

    Mars, Ruben A T; Nicolas, Pierre; Denham, Emma L; van Dijl, Jan Maarten

    2016-12-01

    Bacteria can employ widely diverse RNA molecules to regulate their gene expression. Such molecules include trans-acting small regulatory RNAs, antisense RNAs, and a variety of transcriptional attenuation mechanisms in the 5' untranslated region. Thus far, most regulatory RNA research has focused on Gram-negative bacteria, such as Escherichia coli and Salmonella. Hence, there is uncertainty about whether the resulting insights can be extrapolated directly to other bacteria, such as the Gram-positive soil bacterium Bacillus subtilis. A recent study identified 1,583 putative regulatory RNAs in B. subtilis, whose expression was assessed across 104 conditions. Here, we review the current understanding of RNA-based regulation in B. subtilis, and we categorize the newly identified putative regulatory RNAs on the basis of their conservation in other bacilli and the stability of their predicted secondary structures. Our present evaluation of the publicly available data indicates that RNA-mediated gene regulation in B. subtilis mostly involves elements at the 5' ends of mRNA molecules. These can include 5' secondary structure elements and metabolite-, tRNA-, or protein-binding sites. Importantly, sense-independent segments are identified as the most conserved and structured potential regulatory RNAs in B. subtilis. Altogether, the present survey provides many leads for the identification of new regulatory RNA functions in B. subtilis. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

  17. Regulatory puzzle of xyn1 gene (xylanase1) expression in Trichoderma reesei

    Institute of Scientific and Technical Information of China (English)

    Robert L Mach; Elisabeth Würleitner; Astrid R Stricker; Roman Rauscher; Christian Wacenovsky

    2004-01-01

    @@ Xylanase 1 (Xyn1) is one of the two major representatives of the xylanase system of T. reesei; the mechanisms governing its expression were analysed throughout this study. All factors and regulatory motifs responsible for transcriptional regulation and the model of their interplay in induction and repression will be presented. Using in vivo foot printing analysis of xylan-induced and glucose repressed mycelia, we detected three adjacent nucleotide sequences contacted by DNA-binding proteins. Protection within the inverted repeat of the Cre1 (SYGGRG) consensus sequence on the non coding strand under repressing conditions is in perfect agreement with the previously reported Cre1dependent glucose repression of xyn1. Constitutive protein binding could be observed to a CCAAT-box and an inverted repeat of a 5′ GGCTAA 3′ sequence. EMSA with crude extracts from induced and repressed mycelia revealed that the latter motifs are sufficient for formation of the basal transcriptional complex under all conditions. The inverted repeat of GGCTAA closely resembles the consensus sequences of the cellulase and xylanase regulators Ace1, Ace2 and, Xyr1 (encoded by xyr1, cloned and characterised in this study) EMSA with heterologously expressed components of each factor and of the T. reesei Hap2/3/5 protein complex revealed that the basal transcriptional complex is formed by Xyr1and the Hap2/3/5. Additionally to the Cre1 mediated carbon catabolite repression a yet unknown mechanism antagonizing induction of xyn1 expression could be elucidated. Latter occurs through competition of the repressor Ace1 and Xyr1 for the GGCTAA motif. In vivo proof for the relevance of identified motifs could be given through analysis of T. reesei transformants containing correspondingly mutated versions of the xyn1 promoter fused to the A. niger goxA gene. The results indicated that the basal as well as the induction level of xyn1 gene transcription is dependent on an interaction of Xyr1with the

  18. Global gene expression profiling of the asymptomatic bacteriuria Escherichia coli strain 83972 in the human urinary tract

    DEFF Research Database (Denmark)

    Hancock, Viktoria; Klemm, Per

    2006-01-01

    Urinary tract infections (UTIs) are an important health problem worldwide, with many million cases each year. Escherichia coli is the most common organism causing UTIs in humans. The asymptomatic bacteriuria E. coli strain 83972 is an excellent colonizer of the human urinary tract, where it causes...

  19. European genome-wide association study identifies SLC14A1 as a new urinary bladder cancer susceptibility gene.

    Science.gov (United States)

    Rafnar, Thorunn; Vermeulen, Sita H; Sulem, Patrick; Thorleifsson, Gudmar; Aben, Katja K; Witjes, J Alfred; Grotenhuis, Anne J; Verhaegh, Gerald W; Hulsbergen-van de Kaa, Christina A; Besenbacher, Soren; Gudbjartsson, Daniel; Stacey, Simon N; Gudmundsson, Julius; Johannsdottir, Hrefna; Bjarnason, Hjordis; Zanon, Carlo; Helgadottir, Hafdis; Jonasson, Jon Gunnlaugur; Tryggvadottir, Laufey; Jonsson, Eirikur; Geirsson, Gudmundur; Nikulasson, Sigfus; Petursdottir, Vigdis; Bishop, D Timothy; Chung-Sak, Sei; Choudhury, Ananya; Elliott, Faye; Barrett, Jennifer H; Knowles, Margaret A; de Verdier, Petra J; Ryk, Charlotta; Lindblom, Annika; Rudnai, Peter; Gurzau, Eugene; Koppova, Kvetoslava; Vineis, Paolo; Polidoro, Silvia; Guarrera, Simonetta; Sacerdote, Carlotta; Panadero, Angeles; Sanz-Velez, José I; Sanchez, Manuel; Valdivia, Gabriel; Garcia-Prats, Maria D; Hengstler, Jan G; Selinski, Silvia; Gerullis, Holger; Ovsiannikov, Daniel; Khezri, Abdolaziz; Aminsharifi, Alireza; Malekzadeh, Mahyar; van den Berg, Leonard H; Ophoff, Roel A; Veldink, Jan H; Zeegers, Maurice P; Kellen, Eliane; Fostinelli, Jacopo; Andreoli, Daniele; Arici, Cecilia; Porru, Stefano; Buntinx, Frank; Ghaderi, Abbas; Golka, Klaus; Mayordomo, José I; Matullo, Giuseppe; Kumar, Rajiv; Steineck, Gunnar; Kiltie, Anne E; Kong, Augustine; Thorsteinsdottir, Unnur; Stefansson, Kari; Kiemeney, Lambertus A

    2011-11-01

    Three genome-wide association studies in Europe and the USA have reported eight urinary bladder cancer (UBC) susceptibility loci. Using extended case and control series and 1000 Genomes imputations of 5 340 737 single-nucleotide polymorphisms (SNPs), we searched for additional loci in the European GWAS. The discovery sample set consisted of 1631 cases and 3822 controls from the Netherlands and 603 cases and 37 781 controls from Iceland. For follow-up, we used 3790 cases and 7507 controls from 13 sample sets of European and Iranian ancestry. Based on the discovery analysis, we followed up signals in the urea transporter (UT) gene SLC14A. The strongest signal at this locus was represented by a SNP in intron 3, rs17674580, that reached genome-wide significance in the overall analysis of the discovery and follow-up groups: odds ratio = 1.17, P = 7.6 × 10(-11). SLC14A1 codes for UTs that define the Kidd blood group and are crucial for the maintenance of a constant urea concentration gradient in the renal medulla and, through this, the kidney's ability to concentrate urine. It is speculated that rs17674580, or other sequence variants in LD with it, indirectly modifies UBC risk by affecting urine production. If confirmed, this would support the 'urogenous contact hypothesis' that urine production and voiding frequency modify the risk of UBC.

  20. Association of Toll-Like Receptor 4 Gene Polymorphism and Expression with Urinary Tract Infection Types in Adults

    Science.gov (United States)

    Yin, Xiaolin; Hou, Tianwen; Liu, Ying; Chen, Jing; Yao, Zhiyan; Ma, Cuiqing; Yang, Lijuan; Wei, Lin

    2010-01-01

    Background Innate immunity of which Toll-like receptor (TLR) 4 and CXCR1 are key elements plays a central role in the development of urinary tract infection (UTI). Although the relation between the genetics of TLR4 and CXCR1 and UTI is investigated partly, the polymorphisms and expression of TLR4 and CXCR1 in different types of UTI in adults are not extremely clear. Methodology/Principal Findings This study investigates the presence of TLR4 A (896) G and CXCR1 G (2608) C polymorphisms in 129 UTI patients using RFLP-PCR. Gene and allelic prevalence were compared with 248 healthy controls. Flow cytometry was used to detect TLR4 and CXCR1 expression in the monocytes of UTI patients and healthy controls. TLR4 (896) AG genotype and TLR4 (896) G allele had higher prevalence in UTI (especially in acute cystitis and urethritis) patients, whereas CXCR1 (2608) GC genotype and CXCR1 (2608) C allele had lower prevalence in UTI patients than controls. TLR4 expression was significantly lower in chronic UTI patients than in acute pyelonephritis or healthy controls. CXCR1 expression was similar in both controls and patients. TLR4 expression in chronic UTI patients after astragalus treatment was higher than pre-treatment. Conclusions The results indicate the relationship between the carrier status of TLR4 (896) G alleles and the development of UTI, especially acute cystitis and urethritis, in adults. TLR4 expression levels are correlated with chronic UTI. PMID:21151974

  1. Dynamic chromatin states in human ES cells reveal potential regulatory sequences and genes involved in pluripotency

    Institute of Scientific and Technical Information of China (English)

    R David Hawkins; Zhen Ye; Samantha Kuan; Pengzhi Yu; Hui Liu; Xinmin Zhang; Roland D Green; Victor V Lobanenkov; Ron Stewart; James A Thomson; Bing Ren; Gary C Hon; Chuhu Yang; Jessica E Antosiewicz-Bourget; LeonardKLee; Que-Minh Ngo; Sarit Klugman; Keith A Ching; Lee E Edsall

    2011-01-01

    Pluripotency,the ability of a cell to differentiate and give rise to all embryonic lineages,defines a small number of mammalian cell types such as embryonic stem (ES) cells.While it has been generally held that pluripotency is the product of a transcriptional regulatory network that activates and maintains the expression of key stem cell genes,accumulating evidence is pointing to a critical role for epigenetic processes in establishing and safeguarding the pluripotency of ES cells,as well as maintaining the identity of differentiated cell types.In order to better understand the role of epigenetic mechanisms in pluripotency,we have examined the dynamics of chromatin modifications genomewide in human ES cells (hESCs) undergoing differentiation into a mesendodermal lineage.We found that chromatin modifications at promoters remain largely invariant during differentiation,except at a small number of promoters where a dynamic switch between acetylation and methylation at H3K27 marks the transition between activation and silencing of gene expression,suggesting a hierarchy in cell fate commitment over most differentially expressed genes.We also mapped over 50 000 potential enhancers,and observed much greater dynamics in chromatin modifications,especially H3K4mel and H3K27ac,which correlate with expression of their potential target genes.Further analysis of these enhancers revealed potentially key transcriptional regulators of pluripotency and a chromatin signature indicative of a poised state that may confer developmental competence in hESCs.Our results provide new evidence supporting the role of chromatin modifications in defining enhancers and pluripotency.

  2. Human Sterol Regulatory Element-Binding Protein 1a Contributes Significantly to Hepatic Lipogenic Gene Expression

    Directory of Open Access Journals (Sweden)

    Andreas Bitter

    2015-01-01

    Full Text Available Background/Aims: Sterol regulatory element-binding protein (SREBP 1, the master regulator of lipogenesis, was shown to be associated with non-alcoholic fatty liver disease, which is attributed to its major isoform SREBP1c. Based on studies in mice, the minor isoform SREBP1a is regarded as negligible for hepatic lipogenesis. This study aims to elucidate the expression and functional role of SREBP1a in human liver. Methods: mRNA expression of both isoforms was quantified in cohorts of human livers and primary human hepatocytes. Hepatocytes were treated with PF-429242 to inhibit the proteolytic activation of SREBP precursor protein. SREBP1a-specifc and pan-SREBP1 knock-down were performed by transfection of respective siRNAs. Lipogenic SREBP-target gene expression was analyzed by real-time RT-PCR. Results: In human liver, SREBP1a accounts for up to half of the total SREBP1 pool. Treatment with PF-429242 indicated SREBP-dependent auto-regulation of SREBP1a, which however was much weaker than of SREBP1c. SREBP1a-specifc knock-down also reduced significantly the expression of SREBP1c and of SREBP-target genes. Regarding most SREBP-target genes, simultaneous knock-down of both isoforms resulted in effects of only similar extent as SREBP1a-specific knock-down. Conclusion: We here showed that SREBP1a is significantly contributing to the human hepatic SREBP1 pool and has a share in human hepatic lipogenic gene expression.

  3. The contribution of cis-regulatory elements to head-to-head gene pairs’ co-expression pattern

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Transcription regulation is one of the most critical pipelines in biological process,in which cis-elements play the role as gene expression regulators.We attempt to deduce the principles underlying the co-expression of "head-to-head" gene pairs by analyzing activities or behaviors of the shared cis-elements.A network component analysis was performed to estimate the impact of cis-elements on gene promoters and their activities under different conditions.Our discoveries reveal how biological system uses those regulatory elements to control the expression pattern of "head-to-head" gene pairs and the whole transcription regulation system.

  4. Identification of New Genes Positively Regulated by Tri10 and a Regulatory Network for Trichothecene Mycotoxin Production

    OpenAIRE

    Peplow, Andrew W.; Tag, Andrew G.; Garifullina, Gulnara F.; Beremand, Marian N.

    2003-01-01

    Tri10, a regulatory gene in trichothecene mycotoxin-producing Fusarium species, is required for trichothecene biosynthesis and the coordinated expression of four trichothecene pathway-specific genes (Tri4, Tri5, Tri6, and Tri101) and the isoprenoid biosynthetic gene for farnesyl pyrophosphate synthetase (FPPS). We showed that six more trichothecene genes (Tri3, Tri7, Tri8, Tri9, Tri11, and Tri12) are regulated by Tri10. We also constructed a cDNA library from a strain of Fusarium sporotrichio...

  5. Gene expression during the generation and activation of mouse neutrophils: implication of novel functional and regulatory pathways.

    Directory of Open Access Journals (Sweden)

    Jeffrey A Ericson

    Full Text Available As part of the Immunological Genome Project (ImmGen, gene expression was determined in unstimulated (circulating mouse neutrophils and three populations of neutrophils activated in vivo, with comparison among these populations and to other leukocytes. Activation conditions included serum-transfer arthritis (mediated by immune complexes, thioglycollate-induced peritonitis, and uric acid-induced peritonitis. Neutrophils expressed fewer genes than any other leukocyte population studied in ImmGen, and down-regulation of genes related to translation was particularly striking. However, genes with expression relatively specific to neutrophils were also identified, particularly three genes of unknown function: Stfa2l1, Mrgpr2a and Mrgpr2b. Comparison of genes up-regulated in activated neutrophils led to several novel findings: increased expression of genes related to synthesis and use of glutathione and of genes related to uptake and metabolism of modified lipoproteins, particularly in neutrophils elicited by thioglycollate; increased expression of genes for transcription factors in the Nr4a family, only in neutrophils elicited by serum-transfer arthritis; and increased expression of genes important in synthesis of prostaglandins and response to leukotrienes, particularly in neutrophils elicited by uric acid. Up-regulation of genes related to apoptosis, response to microbial products, NFkB family members and their regulators, and MHC class II expression was also seen, in agreement with previous studies. A regulatory model developed from the ImmGen data was used to infer regulatory genes involved in the changes in gene expression during neutrophil activation. Among 64, mostly novel, regulatory genes predicted to influence these changes in gene expression, Irf5 was shown to be important for optimal secretion of IL-10, IP-10, MIP-1α, MIP-1β, and TNF-α by mouse neutrophils in vitro after stimulation through TLR9. This data-set and its analysis using the

  6. [Improvement of natamycin production in an industrial strain by heterologous expression of the afsRS(cla) global regulatory genes].

    Science.gov (United States)

    Tao, Zhengsheng; Wang, Yemin; Zheng, Hualiang; Tao, Meifeng

    2015-05-01

    The afsRS(cla) global regulatory genes from Streptomyces clavuligerus activate the production of two antibiotics in Streptomyces lividans. In this study, we gained an increase of 38% in the production of natamycin (3.56 g/L) in an industrial strain Streptomyces gilvosporeus TZ1401 through the integration of pHL851 that bears the afsRS(cla) global regulatory genes into its genome. We discovered by quantitive real-time reverse transcription PCR (qRT-PCR) that the expression of 6 genes of the natamycin biosynthetic gene cluster were improved from 1.9 to 2.7 times. This suggests that afsRS(cla) improve the production of natamycin through increased transcription. This study provides a good example for applying afsRS(cla) in high yield breeding of industrial antibiotic producers.

  7. A systems biology approach to construct the gene regulatory network of systemic inflammation via microarray and databases mining

    Directory of Open Access Journals (Sweden)

    Lan Chung-Yu

    2008-09-01

    Full Text Available Abstract Background Inflammation is a hallmark of many human diseases. Elucidating the mechanisms underlying systemic inflammation has long been an important topic in basic and clinical research. When primary pathogenetic events remains unclear due to its immense complexity, construction and analysis of the gene regulatory network of inflammation at times becomes the best way to understand the detrimental effects of disease. However, it is difficult to recognize and evaluate relevant biological processes from the huge quantities of experimental data. It is hence appealing to find an algorithm which can generate a gene regulatory network of systemic inflammation from high-throughput genomic studies of human diseases. Such network will be essential for us to extract valuable information from the complex and chaotic network under diseased conditions. Results In this study, we construct a gene regulatory network of inflammation using data extracted from the Ensembl and JASPAR databases. We also integrate and apply a number of systematic algorithms like cross correlation threshold, maximum likelihood estimation method and Akaike Information Criterion (AIC on time-lapsed microarray data to refine the genome-wide transcriptional regulatory network in response to bacterial endotoxins in the context of dynamic activated genes, which are regulated by transcription factors (TFs such as NF-κB. This systematic approach is used to investigate the stochastic interaction represented by the dynamic leukocyte gene expression profiles of human subject exposed to an inflammatory stimulus (bacterial endotoxin. Based on the kinetic parameters of the dynamic gene regulatory network, we identify important properties (such as susceptibility to infection of the immune system, which may be useful for translational research. Finally, robustness of the inflammatory gene network is also inferred by analyzing the hubs and "weak ties" structures of the gene network

  8. Conserved-peptide upstream open reading frames (CPuORFs are associated with regulatory genes in angiosperms

    Directory of Open Access Journals (Sweden)

    Richard A Jorgensen

    2012-08-01

    Full Text Available Upstream open reading frames (uORFs are common in eukaryotic transcripts, but those that encode conserved peptides (CPuORFs occur in less than 1% of transcripts. The peptides encoded by three plant CPuORF families are known to control translation of the downstream ORF in response to a small signal molecule (sucrose, polyamines and phosphocholine. In flowering plants, transcription factors are statistically over-represented among genes that possess CPuORFs, and in general it appeared that many CPuORF genes also had other regulatory functions, though the significance of this suggestion was uncertain (Hayden and Jorgensen, 2007. Five years later the literature provides much more information on the functions of many CPuORF genes. Here we reassess the functions of 27 known CPuORF gene families and find that 22 of these families play a variety of different regulatory roles, from transcriptional control to protein turnover, and from small signal molecules to signal transduction kinases. Clearly then, there is indeed a strong association of CPuORFs with regulatory genes. In addition, 16 of these families play key roles in a variety of different biological processes. Most strikingly, the core sucrose response network includes three different CPuORFs, creating the potential for sophisticated balancing of the network in response to three different molecular inputs. We propose that the function of most CPuORFs is to modulate translation of a downstream major ORF (mORF in response to a signal molecule recognized by the conserved peptide and that because the mORFs of CPuORF genes generally encode regulatory proteins, many of them centrally important in the biology of plants, CPuORFs play key roles in balancing such regulatory networks.

  9. In Vivo Gene Expression Analysis Identifies Genes Required for Enhanced Colonization of the Mouse Urinary Tract by Uropathogenic Escherichia coli Strain CFT073 dsdA▿ †

    Science.gov (United States)

    Haugen, Brian J.; Pellett, Shahaireen; Redford, Peter; Hamilton, Holly L.; Roesch, Paula L.; Welch, Rodney A.

    2007-01-01

    Deletional inactivation of the gene encoding d-serine deaminase, dsdA, in uropathogenic Escherichia coli strain CFT073 results in a hypermotile strain with a hypercolonization phenotype in the bladder and kidneys of mice in a model of urinary tract infection (UTI). The in vivo gene expression profiles of CFT073 and CFT073 dsdA were compared by isolating RNA directly from the urine of mice challenged with each strain individually. Hybridization of cDNAs derived from these samples to CFT073-specific microarrays allowed identification of genes that were up- or down-regulated in the dsdA deletion strain during UTI. Up-regulated genes included the known d-serine-responsive gene dsdX, suggesting in vivo intracellular accumulation of d-serine by CFT073 dsdA. Genes encoding F1C fimbriae, both copies of P fimbriae, hemolysin, OmpF, a dipeptide transporter DppA, a heat shock chaperone IbpB, and clusters of open reading frames with unknown functions were also up-regulated. To determine the role of these genes as well as motility in the hypercolonization phenotype, mutants were constructed in the CFT073 dsdA background and tested in competition against the wild type in the murine model of UTI. Strains with deletions of one or both of the two P fimbrial operons, hlyA, fliC, ibpB, c0468, locus c3566 to c3568, or c2485 to c2490 colonized mouse bladders and kidneys at levels indistinguishable from wild type. CFT073 dsdA c2398 and CFT073 dsdA focA maintained a hypercolonization phenotype. A CFT073 dsdA dppA mutant was attenuated 10- to 50-fold in its colonization ability compared to CFT073. Our results support a role for d-serine catabolism and signaling in global virulence gene regulation of uropathogenic E. coli. PMID:17074858

  10. Association Mapping of Cell Wall Synthesis Regulatory Genes and Cell Wall Quality in Switchgrass

    Energy Technology Data Exchange (ETDEWEB)

    Bartley, Laura [Univ. of Oklahoma, Norman, OK (United States). Dept. of Microbiology and Plant Biology; Wu, Y. [Oklahoma State Univ., Stillwater, OK (United States); Zhu, L. [Oklahoma State Univ., Stillwater, OK (United States); Brummer, E. C. [Noble Foundation, Ardmore, OK (United States); Saha, M. [Noble Foundation, Ardmore, OK (United States)

    2016-05-31

    markers might be used to select switchgrass genotypes with improved composition in breeding programs for biofuel and forage production. Because the SSAC continues to be characterized by collaborators in the bioenergy community, the data generated will be used to identify additional markers in higher resolution genotyping data to approach identifying the genes and alleles that cause natural variation in switchgrass cell wall quality. For example, these markers can be surveyed in the 2100-member Oklahoma Southern and Northern Lowland switchgrass collections that this project also characterized. An orthogonal approach to biodiversity studies, using comparative functional genomics permits systematic querying of how much regulatory information is likely to be transferable from dicots to grasses and use of accumulated functional genomics resources for better-characterized grass species, such as rice, itself a biomass source in global agriculture and in certain regions. The project generated and tested a number of specific hypotheses regarding cell wall transcription factors and enzymes of grasses. To aid identification of cell wall regulators, the project assembled a novel, highdepth and -quality gene association network using a general linearized model scoring system to combine rice gene network data. Using known or putative orthologs of Arabidopsis cell wall biosynthesis genes and regulators, the project pulled from this network a cell wall sub-network that includes 96 transcription factors. Reverse genetics of a co-ortholog of the Arabidopsis MYB61 transcription factor in rice revealed that this regulatory node has evolved the ability to regulate grass-specific cell wall synthesis enzymes. A transcription factor with such activity has not been previously characterized to our knowledge, representing a major conclusion of this work. Changes in gene expression in a protoplast-based assay demonstrated positive or negative roles in cell wall regulation for eleven other

  11. Interactions between urinary 4-tert-octylphenol levels and metabolism enzyme gene variants on idiopathic male infertility.

    Directory of Open Access Journals (Sweden)

    Yufeng Qin

    Full Text Available Octylphenol (OP and Trichlorophenol (TCP act as endocrine disruptors and have effects on male reproductive function. We studied the interactions between 4-tert-Octylphenol (4-t-OP, 4-n- Octylphenol (4-n-OP, 2,3,4-Trichlorophenol (2,3,4-TCP, 2,4,5-Trichlorophenol (2,4,5-TCP urinary exposure levels and polymorphisms in selected xenobiotic metabolism enzyme genes among 589 idiopathic male infertile patients and 396 controls in a Han-Chinese population. Ultra high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS was used to measure alkylphenols and chlorophenols in urine. Polymorphisms were genotyped using the SNPstream platform and the Taqman method. Among four phenols that were detected, we found that only exposure to 4-t-OP increased the risk of male infertility (P(trend = 1.70×10(-7. The strongest interaction was between 4-t-OP and rs4918758 in CYP2C9 (P(inter = 6.05×10(-7. It presented a significant monotonic increase in risk estimates for male infertility with increasing 4-t-OP exposure levels among men with TC/CC genotype (low level compared with non-exposed, odds ratio (OR = 2.26, 95% confidence intervals (CI = 1.06, 4.83; high level compared with non-exposed, OR = 9.22, 95% CI = 2.78, 30.59, but no associations observed among men with TT genotype. We also found interactions between 4-t-OP and rs4986894 in CYP2C19, and between rs1048943 in CYP1A1, on male infertile risk (P(inter = 8.09×10(-7, P(inter = 3.73×10(-4, respectively.We observed notable interactions between 4-t-OP exposure and metabolism enzyme gene polymorphisms on idiopathic infertility in Han-Chinese men.

  12. A Gene Regulatory Network Cooperatively Controlled by Pdx1 and Sox9 Governs Lineage Allocation of Foregut Progenitor Cells

    DEFF Research Database (Denmark)

    Shih, Hung Ping; Seymour, Philip A; Patel, Nisha A;

    2015-01-01

    The generation of pancreas, liver, and intestine from a common pool of progenitors in the foregut endoderm requires the establishment of organ boundaries. How dorsal foregut progenitors activate pancreatic genes and evade the intestinal lineage choice remains unclear. Here, we identify Pdx1 and Sox...... pancreatic fate and sheds light on the gene regulatory circuitry that governs the development of distinct organs from multi-lineage-competent foregut progenitors....

  13. Microarray analyses of SREBP-1a and SREBP-1c target genes identify new regulatory pathways in muscle.

    OpenAIRE

    Rome, Sophie; Lecomte, Virginie; Meugnier, Emmanuelle; Rieusset, Jennifer; Debard, Cyrille; Euthine, Vanessa; Vidal, Hubert; Lefai, Etienne

    2008-01-01

    International audience; In this study we have identified the target genes of sterol regulatory element binding protein (SREBP)-1a and SREBP-1c in primary cultures of human skeletal muscle cells, using adenoviral vectors expressing the mature nuclear form of human SREBP-1a or SREBP-1c combined with oligonucleotide microarrays. Overexpression of SREBP-1a led to significant changes in the expression of 1,315 genes (655 upregulated and 660 downregulated), whereas overexpression of SREBP-1c modifi...

  14. Screening in silico predicted remotely acting NF1 gene regulatory elements for mutations in patients with neurofibromatosis type 1.

    Science.gov (United States)

    Hamby, Stephen E; Reviriego, Pablo; Cooper, David N; Upadhyaya, Meena; Chuzhanova, Nadia

    2013-08-15

    Neurofibromatosis type 1 (NF1), a neuroectodermal disorder, is caused by germline mutations in the NF1 gene. NF1 affects approximately 1/3,000 individuals worldwide, with about 50% of cases representing de novo mutations. Although the NF1 gene was identified in 1990, the underlying gene mutations still remain undetected in a small but obdurate minority of NF1 patients. We postulated that in these patients, hitherto undetected pathogenic mutations might occur in regulatory elements far upstream of the NF1 gene. In an attempt to identify such remotely acting regulatory elements, we reasoned that some of them might reside within DNA sequences that (1) have the potential to interact at distance with the NF1 gene and (2) lie within a histone H3K27ac-enriched region, a characteristic of active enhancers. Combining Hi-C data, obtained by means of the chromosome conformation capture technique, with data on the location and level of histone H3K27ac enrichment upstream of the NF1 gene, we predicted in silico the presence of two remotely acting regulatory regions, located, respectively, approximately 600 kb and approximately 42 kb upstream of the NF1 gene. These regions were then sequenced in 47 NF1 patients in whom no mutations had been found in either the NF1 or SPRED1 gene regions. Five patients were found to harbour DNA sequence variants in the distal H3K27ac-enriched region. Although these variants are of uncertain pathological significance and still remain to be functionally characterized, this approach promises to be of general utility for the detection of mutations underlying other inherited disorders that may be caused by mutations in remotely acting regulatory elements.

  15. Regulatory single nucleotide polymorphisms at the beginning of intron 2 of the human gene

    Indian Academy of Sciences (India)

    Elena V Antontseva; Marina Yu Matveeva; Natalia P Bondar; Elena V Kashina; Elena Yu Leberfarb; Leonid O Bryzgalov; Polina A Gervas; Anastasia A Ponomareva; Nadezhda V Cherdyntseva; Yury L Orlov; Tatiana I Merkulova

    2015-12-01

    There are two regulatory single nucleotide polymorphisms (rSNPs) at the beginning of the second intron of the mouse - gene that are strongly associated with lung cancer susceptibility. We performed functional analysis of three SNPs (rs12228277: T>A, rs12226937: G>A, and rs61761074: T>G) located in the same region of human . We found that rs12228277 and rs61761074 result in differential binding patterns of lung nuclear proteins to oligonucleotide probes corresponding two alternative alleles; in both cases, the transcription factor NF-Y is involved. G>A substitution (rs12226937) had no effect on the binding of lung nuclear proteins. However, all the nucleotide substitutions under study showed functional effects in a luciferase reporter assay. Among them, rs61761074 demonstrated a significant correlation with allele frequency in non-small-cell lung cancer (NSCLC). Taken together, the results of our study suggest that a T>G substitution at nucleotide position 615 in the second intron of the KRAS gene (rs61761074) may represent a promising genetic marker of NSCLC.

  16. PRMT1 mediated methylation of TAF15 is required for its positive gene regulatory function

    Energy Technology Data Exchange (ETDEWEB)

    Jobert, Laure; Argentini, Manuela [Institut de Genetique et de Biologie Moleculaire et Cellulaire (IGBMC), CNRS UMR 7104, INSERM U 596, Universite Louis Pasteur de Strasbourg, BP 10142 - 67404 Illkirch Cedex, CU de Strasbourg (France); Tora, Laszlo, E-mail: laszlo@igbmc.u-strasbg.fr [Institut de Genetique et de Biologie Moleculaire et Cellulaire (IGBMC), CNRS UMR 7104, INSERM U 596, Universite Louis Pasteur de Strasbourg, BP 10142 - 67404 Illkirch Cedex, CU de Strasbourg (France)

    2009-04-15

    TAF15 (formerly TAF{sub II}68) is a nuclear RNA-binding protein that is associated with a distinct population of TFIID and RNA polymerase II complexes. TAF15 harbours an N-terminal activation domain, an RNA recognition motif (RRM) and many Arg-Gly-Gly (RGG) repeats at its C-terminal end. The N-terminus of TAF15 serves as an essential transforming domain in the fusion oncoprotein created by chromosomal translocation in certain human chondrosarcomas. Post-transcriptional modifications (PTMs) of proteins are known to regulate their activity, however, nothing is known on how PTMs affect TAF15 function. Here we demonstrate that endogenous human TAF15 is methylated in vivo at its numerous RGG repeats. Furthermore, we identify protein arginine N-methyltransferase 1 (PRMT1) as a TAF15 interactor and the major PRMT responsible for its methylation. In addition, the RGG repeat-containing C-terminus of TAF15 is responsible for the shuttling between the nucleus and the cytoplasm and the methylation of RGG repeats affects the subcellular localization of TAF15. The methylation of TAF15 by PRMT1 is required for the ability of TAF15 to positively regulate the expression of the studied endogenous TAF15-target genes. Our findings demonstrate that arginine methylation of TAF15 by PRMT1 is a crucial event determining its proper localization and gene regulatory function.

  17. Signaling and Gene Regulatory Networks Governing Definitive Endoderm Derivation From Pluripotent Stem Cells.

    Science.gov (United States)

    Mohammadnia, Abdulshakour; Yaqubi, Moein; Pourasgari, Farzaneh; Neely, Eric; Fallahi, Hossein; Massumi, Mohammad

    2016-09-01

    The generation of definitive endoderm (DE) from pluripotent stem cells (PSCs) is a fundamental stage in the formation of highly organized visceral organs, such as the liver and pancreas. Currently, there is a need for a comprehensive study that illustrates the involvement of different signaling pathways and their interactions in the derivation of DE cells from PSCs. This study aimed to identify signaling pathways that have the greatest influence on DE formation using analyses of transcriptional profiles, protein-protein interactions, protein-DNA interactions, and protein localization data. Using this approach, signaling networks involved in DE formation were constructed using systems biology and data mining tools, and the validity of the predicted networks was confirmed experimentally by measuring the mRNA levels of hub genes in several PSCs-derived DE cell lines. Based on our analyses, seven signaling pathways, including the BMP, ERK1-ERK2, FGF, TGF-beta, MAPK, Wnt, and PIP signaling pathways and their interactions, were found to play a role in the derivation of DE cells from PSCs. Lastly, the core gene regulatory network governing this differentiation process was constructed. The results of this study could improve our understanding surrounding the efficient generation of DE cells for the regeneration of visceral organs. J. Cell. Physiol. 231: 1994-2006, 2016. © 2016 Wiley Periodicals, Inc.

  18. Construction of Gene Regulatory Networks Using Recurrent Neural Networks and Swarm Intelligence.

    Science.gov (United States)

    Khan, Abhinandan; Mandal, Sudip; Pal, Rajat Kumar; Saha, Goutam

    2016-01-01

    We have proposed a methodology for the reverse engineering of biologically plausible gene regulatory networks from temporal genetic expression data. We have used established information and the fundamental mathematical theory for this purpose. We have employed the Recurrent Neural Network formalism to extract the underlying dynamics present in the time series expression data accurately. We have introduced a new hybrid swarm intelligence framework for the accurate training of the model parameters. The proposed methodology has been first applied to a small artificial network, and the results obtained suggest that it can produce the best results available in the contemporary literature, to the best of our knowledge. Subsequently, we have implemented our proposed framework on experimental (in vivo) datasets. Finally, we have investigated two medium sized genetic networks (in silico) extracted from GeneNetWeaver, to understand how the proposed algorithm scales up with network size. Additionally, we have implemented our proposed algorithm with half the number of time points. The results indicate that a reduction of 50% in the number of time points does not have an effect on the accuracy of the proposed methodology significantly, with a maximum of just over 15% deterioration in the worst case.

  19. Robust dynamic balance of AP-1 transcription factors in a neuronal gene regulatory network

    Directory of Open Access Journals (Sweden)

    Schwaber James S

    2010-12-01

    Full Text Available Abstract Background The octapeptide Angiotensin II is a key hormone that acts via its receptor AT1R in the brainstem to modulate the blood pressure control circuits and thus plays a central role in the cardiac and respiratory homeostasis. This modulation occurs via activation of a complex network of signaling proteins and transcription factors, leading to changes in levels of key genes and proteins. AT1R initiated activity in the nucleus tractus solitarius (NTS, which regulates blood pressure, has been the subject of extensive molecular analysis. But the adaptive network interactions in the NTS response to AT1R, plausibly related to the development of hypertension, are not understood. Results We developed and analyzed a mathematical model of AT1R-activated signaling kinases and a downstream gene regulatory network, with structural basis in our transcriptomic data analysis and literature. To our knowledge, our report presents the first computational model of this key regulatory network. Our simulations and analysis reveal a dynamic balance among distinct dimers of the AP-1 family of transcription factors. We investigated the robustness of this behavior to simultaneous perturbations in the network parameters using a novel multivariate approach that integrates global sensitivity analysis with decision-tree methods. Our analysis implicates a subset of Fos and Jun dependent mechanisms, with dynamic sensitivities shifting from Fos-regulating kinase (FRK-mediated processes to those downstream of c-Jun N-terminal kinase (JNK. Decision-tree analysis indicated that while there may be a large combinatorial functional space feasible for neuronal states and parameters, the network behavior is constrained to a small set of AP-1 response profiles. Many of the paths through the combinatorial parameter space lead to a dynamic balance of AP-1 dimer forms, yielding a robust AP-1 response counteracting the biological variability. Conclusions Based on the simulation

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

    Science.gov (United States)

    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.

  1. Reduced FOXP3(+) regulatory T cells in patients with primary sclerosing cholangitis are associated with IL2RA gene polymorphisms

    NARCIS (Netherlands)

    Sebode, M.; Peiseler, M.; Franke, B.; Schwinge, D.; Schoknecht, T.; Wortmann, F.; Quaas, A.; Petersen, B.S.; Ellinghaus, E.; Baron, U.; Olek, S.; Wiegard, C.; Weiler-Normann, C.; Lohse, A.W.; Herkel, J.; Schramm, C.

    2014-01-01

    BACKGROUND & AIMS: Recently, genome wide association studies in primary sclerosing cholangitis (PSC) revealed associations with gene polymorphisms that potentially could affect the function of regulatory T cells (Treg). The aim of this study was to investigate Treg in patients with PSC and to associ

  2. Modelling non-stationary gene regulatory processes with a non-homogeneous Bayesian network and the allocation sampler

    NARCIS (Netherlands)

    Grzegorczyk, Marco; Husmeier, Dirk; Edwards, Kieron D.; Ghazal, Peter; Millar, Andrew J.

    2008-01-01

    Method: The objective of the present article is to propose and evaluate a probabilistic approach based on Bayesian networks for modelling non-homogeneous and non-linear gene regulatory processes. The method is based on a mixture model, using latent variables to assign individual measurements to diff

  3. Structural basis for regulation of rhizobial nodulation and symbiosis gene expression by the regulatory NolR

    Science.gov (United States)

    The symbiosis between rhizobial microbes and host plants involves the coordinated expression of multiple genes, which leads to nodule formation and nitrogen fixation. As part of the transcriptional machinery for nodulation and symbiosis across a range of Rhizobium, NolR serves as a global regulatory...

  4. Modelling non-stationary gene regulatory processes with a non-homogeneous Bayesian network and the allocation sampler

    NARCIS (Netherlands)

    Grzegorczyk, Marco; Husmeier, Dirk; Edwards, Kieron D.; Ghazal, Peter; Millar, Andrew J.

    2008-01-01

    Method: The objective of the present article is to propose and evaluate a probabilistic approach based on Bayesian networks for modelling non-homogeneous and non-linear gene regulatory processes. The method is based on a mixture model, using latent variables to assign individual measurements to

  5. Arabidopsis CPR5 is a senescence-regulatory gene with pleiotropic functions as predicted by the evolutionary theory of senescence

    NARCIS (Netherlands)

    Jing, Hai-Chun; Anderson, Lisa; Sturre, Marcel J. G.; Hille, Jacques; Dijkwel, Paul P.

    2007-01-01

    Arabidopsis CPR5 is a senescence-regulatory gene with pleiotropic functions as predicted by the evolutionary theory of senescence Hai-Chun Jing1,2, Lisa Anderson3, Marcel J.G. Sturre1, Jacques Hille1 and Paul P. Dijkwel1,* 1Molecular Biology of Plants, Groningen Biomolecular Sciences and Biotechnolo

  6. Arabidopsis CPR5 is a senescence-regulatory gene with pleiotropic functions as predicted by the evolutionary theory of senescence

    NARCIS (Netherlands)

    Jing, Hai-Chun; Anderson, Lisa; Sturre, Marcel J. G.; Hille, Jacques; Dijkwel, Paul P.

    2007-01-01

    Arabidopsis CPR5 is a senescence-regulatory gene with pleiotropic functions as predicted by the evolutionary theory of senescence Hai-Chun Jing1,2, Lisa Anderson3, Marcel J.G. Sturre1, Jacques Hille1 and Paul P. Dijkwel1,* 1Molecular Biology of Plants, Groningen Biomolecular Sciences and

  7. Global characterization of interferon regulatory factor (IRF genes in vertebrates: Glimpse of the diversification in evolution

    Directory of Open Access Journals (Sweden)

    Xu Zhen

    2010-05-01

    Full Text Available Abstract Background Interferon regulatory factors (IRFs, which can be identified based on a unique helix-turn-helix DNA-binding domain (DBD are a large family of transcription factors involved in host immune response, haemotopoietic differentiation and immunomodulation. Despite the identification of ten IRF family members in mammals, and some recent effort to identify these members in fish, relatively little is known in the composition of these members in other classes of vertebrates, and the evolution and probably the origin of the IRF family have not been investigated in vertebrates. Results Genome data mining has been performed to identify any possible IRF family members in human, mouse, dog, chicken, anole lizard, frog, and some teleost fish, mainly zebrafish and stickleback, and also in non-vertebrate deuterostomes including the hemichordate, cephalochordate, urochordate and echinoderm. In vertebrates, all ten IRF family members, i.e. IRF-1 to IRF-10 were identified, with two genes of IRF-4 and IRF-6 identified in fish and frog, respectively, except that in zebrafish exist three IRF-4 genes. Surprisingly, an additional member in the IRF family, IRF-11 was found in teleost fish. A range of two to ten IRF-like genes were detected in the non-vertebrate deuterostomes, and they had little similarity to those IRF family members in vertebrates as revealed in genomic structure and in phylogenetic analysis. However, the ten IRF family members, IRF-1 to IRF-10 showed certain degrees of conservation in terms of genomic structure and gene synteny. In particular, IRF-1, IRF-2, IRF-6, IRF-8 are quite conserved in their genomic structure in all vertebrates, and to a less degree, some IRF family members, such as IRF-5 and IRF-9 are comparable in the structure. Synteny analysis revealed that the gene loci for the ten IRF family members in vertebrates were also quite conservative, but in zebrafish conserved genes were distributed in a much longer distance in

  8. Global characterization of interferon regulatory factor (IRF) genes in vertebrates: glimpse of the diversification in evolution.

    Science.gov (United States)

    Huang, Bei; Qi, Zhi T; Xu, Zhen; Nie, Pin

    2010-05-05

    Interferon regulatory factors (IRFs), which can be identified based on a unique helix-turn-helix DNA-binding domain (DBD) are a large family of transcription factors involved in host immune response, haemotopoietic differentiation and immunomodulation. Despite the identification of ten IRF family members in mammals, and some recent effort to identify these members in fish, relatively little is known in the composition of these members in other classes of vertebrates, and the evolution and probably the origin of the IRF family have not been investigated in vertebrates. Genome data mining has been performed to identify any possible IRF family members in human, mouse, dog, chicken, anole lizard, frog, and some teleost fish, mainly zebrafish and stickleback, and also in non-vertebrate deuterostomes including the hemichordate, cephalochordate, urochordate and echinoderm. In vertebrates, all ten IRF family members, i.e. IRF-1 to IRF-10 were identified, with two genes of IRF-4 and IRF-6 identified in fish and frog, respectively, except that in zebrafish exist three IRF-4 genes. Surprisingly, an additional member in the IRF family, IRF-11 was found in teleost fish. A range of two to ten IRF-like genes were detected in the non-vertebrate deuterostomes, and they had little similarity to those IRF family members in vertebrates as revealed in genomic structure and in phylogenetic analysis. However, the ten IRF family members, IRF-1 to IRF-10 showed certain degrees of conservation in terms of genomic structure and gene synteny. In particular, IRF-1, IRF-2, IRF-6, IRF-8 are quite conserved in their genomic structure in all vertebrates, and to a less degree, some IRF family members, such as IRF-5 and IRF-9 are comparable in the structure. Synteny analysis revealed that the gene loci for the ten IRF family members in vertebrates were also quite conservative, but in zebrafish conserved genes were distributed in a much longer distance in chromosomes. Furthermore, all ten different

  9. Characterization of the bovine pregnancy-associated glycoprotein gene family – analysis of gene sequences, regulatory regions within the promoter and expression of selected genes

    Directory of Open Access Journals (Sweden)

    Walker Angela M

    2009-04-01

    Full Text Available Abstract Background The Pregnancy-associated glycoproteins (PAGs belong to a large family of aspartic peptidases expressed exclusively in the placenta of species in the Artiodactyla order. In cattle, the PAG gene family is comprised of at least 22 transcribed genes, as well as some variants. Phylogenetic analyses have shown that the PAG family segregates into 'ancient' and 'modern' groupings. Along with sequence differences between family members, there are clear distinctions in their spatio-temporal distribution and in their relative level of expression. In this report, 1 we performed an in silico analysis of the bovine genome to further characterize the PAG gene family, 2 we scrutinized proximal promoter sequences of the PAG genes to evaluate the evolution pressures operating on them and to identify putative regulatory regions, 3 we determined relative transcript abundance of selected PAGs during pregnancy and, 4 we performed preliminary characterization of the putative regulatory elements for one of the candidate PAGs, bovine (bo PAG-2. Results From our analysis of the bovine genome, we identified 18 distinct PAG genes and 14 pseudogenes. We observed that the first 500 base pairs upstream of the translational start site contained multiple regions that are conserved among all boPAGs. However, a preponderance of conserved regions, that harbor recognition sites for putative transcriptional factors (TFs, were found to be unique to the modern boPAG grouping, but not the ancient boPAGs. We gathered evidence by means of Q-PCR and screening of EST databases to show that boPAG-2 is the most abundant of all boPAG transcripts. Finally, we provided preliminary evidence for the role of ETS- and DDVL-related TFs in the regulation of the boPAG-2 gene. Conclusion PAGs represent a relatively large gene family in the bovine genome. The proximal promoter regions of these genes display differences in putative TF binding sites, likely contributing to observed

  10. Life without oxygen: gene regulatory responses of the crucian carp (Carassius carassius heart subjected to chronic anoxia.

    Directory of Open Access Journals (Sweden)

    Kåre-Olav Stensløkken

    Full Text Available Crucian carp are unusual among vertebrates in surviving extended periods in the complete absence of molecular oxygen. During this time cardiac output is maintained though these mechanisms are not well understood. Using a high-density cDNA microarray, we have defined the genome-wide gene expression responses of cardiac tissue after exposing the fish at two temperatures (8 and 13 °C to one and seven days of anoxia, followed by seven days after restoration to normoxia. At 8 °C, using a false discovery rate of 5%, neither anoxia nor re-oxygenation elicited appreciable changes in gene expression. By contrast, at 13 °C, 777 unique genes responded strongly. Up-regulated genes included those involved in protein turnover, the pentose phosphate pathway and cell morphogenesis while down-regulated gene categories included RNA splicing and transcription. Most genes were affected between one and seven days of anoxia, indicating gene regulation over the medium term but with few early response genes. Re-oxygenation for 7 days was sufficient to completely reverse these responses. Glycolysis displayed more complex responses with anoxia up-regulated transcripts for the key regulatory enzymes, hexokinase and phosphofructokinase, but with down-regulation of most of the non-regulatory genes. This complex pattern of responses in genomic transcription patterns indicates divergent cardiac responses to anoxia, with the transcriptionally driven reprogramming of cardiac function seen at 13 °C being largely completed at 8 °C.

  11. Global gene expression profiling of the asymptomatic bacteriuria Escherichia coli strain 83972 in the human urinary tract

    DEFF Research Database (Denmark)

    Hancock, Viktoria; Klemm, Per

    2006-01-01

    long-term bladder colonization. The strain has been used for prophylactic purposes in patients prone to more severe and recurrent UTIs. For this study, we used DNA microarrays to monitor the expression profile of strain 83972 in the human urinary tract. Significant differences in expression levels were......Urinary tract infections (UTIs) are an important health problem worldwide, with many million cases each year. Escherichia coli is the most common organism causing UTIs in humans. The asymptomatic bacteriuria E. coli strain 83972 is an excellent colonizer of the human urinary tract, where it causes...

  12. Phosphatidylinositol 3-kinase p85 regulatory subunit gene and spinal muscular atrophy disease

    Directory of Open Access Journals (Sweden)

    Monica STAVARACHI

    2009-11-01

    Full Text Available Spinal muscular atrophy (SMA is a frequent neuromuscular disorder caused by motoneuronal apoptosis, as a result of SMN (Survival Motor Neuron protein deficiency. Although the SMA determining gene was identified, the molecular mechanism of the disease is not clearly understood, due to the heterogeneity of clinical manifestations. Trying to complete the molecular describing SMA picture, by identifying potential modulators factors, we investigated the relationship between phosphatidylinositol 3-kinase p85 regulatory subunit gene (PIK3R1 and SMA pathology. As IGF signaling pathway has been reported to play an important role in motoneurons survival and PIK3 is a key element of this cascade signaling, we focused on the relationship between PIK3R1 gene Met326Ile polymorphism and SMA type I, the most severe form of the disease. A total of 80 subjects (40 SMA type I patients and 40 unrelated healthy controls were included in the study. The statistical analyzes performed consequently to the genotyping by mismatch PCR-RFLP method, revealed that Met326Ile polymorphism is not associated with SMA type I disease: ORMet/Met = 0.398 with a p = 0.072 meanwhile ORMet = 0.495, p = 0.063. However, the Cochrane – Armitage test indicated that there is a statistically association trend between the analyzed polymorphism and SMA type I pathology: ORMet = 0.438, p = 0.032. We concluded that additional researches with an increased subjects number and replicates studies in other populations will clarify the investigated relationship and it may contribute to the SMA molecular mechanism understanding.

  13. Novel mutations in the GH gene (GH1) uncover putative splicing regulatory elements.

    Science.gov (United States)

    Babu, Deepak; Mellone, Simona; Fusco, Ileana; Petri, Antonella; Walker, Gillian E; Bellone, Simonetta; Prodam, Flavia; Momigliano-Richiardi, Patricia; Bona, Gianni; Giordano, Mara

    2014-05-01

    Mutations affecting exon 3 splicing are the main cause of autosomal dominant Isolated GH Deficiency II (IGHDII) by increasing the level of exon 3-skipped mRNA encoding the functionally inactive dominant-negative 17.5-kDa isoform. The exons and introns of the gene encoding GH (GH1) were screened for the presence of mutations in 103 sporadic isolated GH deficiency cases. Four different variations within exon 3 were identified in 3 patients. One carried c.261C>T (p.Pro87Pro) and c.272A>T (p.Glu91Val), the second c.255G>A (p.Pro85Pro) and c.261 C>T, and the third c.246G>C (p.Glu82Asp). All the variants were likel