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Sample records for additional regulatory genes

  1. Additive Functions in Boolean Models of Gene Regulatory Network Modules

    PubMed Central

    Darabos, Christian; Di Cunto, Ferdinando; Tomassini, Marco; Moore, Jason H.; Provero, Paolo; Giacobini, Mario

    2011-01-01

    Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome's evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in Boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a Boolean model. We use two sub-networks of biological organisms, the yeast cell-cycle and the mouse embryonic stem cell, as topological support for our system. On these structures, we substitute the original random update functions by a novel threshold-based dynamic function in which the promoting and repressing effect of each interaction is considered. We use a third real-life regulatory network, along with its inferred Boolean update functions to validate the proposed update function. Results of this validation hint to increased biological plausibility of the threshold-based function. To investigate the dynamical behavior of this new model, we visualized the phase transition between order and chaos into the critical regime using Derrida plots. We complement the qualitative nature of Derrida plots with an alternative measure, the criticality distance, that also allows to discriminate between regimes in a quantitative way. Simulation on both real-life genetic regulatory networks show that there exists a set of parameters that allows the systems to operate in the critical region. This new model includes experimentally derived biological information and recent discoveries, which makes it potentially useful to guide experimental research. The update function confers additional realism to the model, while reducing the complexity

  2. Additive functions in boolean models of gene regulatory network modules.

    PubMed

    Darabos, Christian; Di Cunto, Ferdinando; Tomassini, Marco; Moore, Jason H; Provero, Paolo; Giacobini, Mario

    2011-01-01

    Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome's evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a boolean model. We use two sub-networks of biological organisms, the yeast cell-cycle and the mouse embryonic stem cell, as topological support for our system. On these structures, we substitute the original random update functions by a novel threshold-based dynamic function in which the promoting and repressing effect of each interaction is considered. We use a third real-life regulatory network, along with its inferred boolean update functions to validate the proposed update function. Results of this validation hint to increased biological plausibility of the threshold-based function. To investigate the dynamical behavior of this new model, we visualized the phase transition between order and chaos into the critical regime using Derrida plots. We complement the qualitative nature of Derrida plots with an alternative measure, the criticality distance, that also allows to discriminate between regimes in a quantitative way. Simulation on both real-life genetic regulatory networks show that there exists a set of parameters that allows the systems to operate in the critical region. This new model includes experimentally derived biological information and recent discoveries, which makes it potentially useful to guide experimental research. The update function confers additional realism to the model, while reducing the complexity

  3. Sparse Additive Ordinary Differential Equations for Dynamic Gene Regulatory Network Modeling.

    PubMed

    Wu, Hulin; Lu, Tao; Xue, Hongqi; Liang, Hua

    2014-04-02

    The gene regulation network (GRN) is a high-dimensional complex system, which can be represented by various mathematical or statistical models. The ordinary differential equation (ODE) model is one of the popular dynamic GRN models. High-dimensional linear ODE models have been proposed to identify GRNs, but with a limitation of the linear regulation effect assumption. In this article, we propose a sparse additive ODE (SA-ODE) model, coupled with ODE estimation methods and adaptive group LASSO techniques, to model dynamic GRNs that could flexibly deal with nonlinear regulation effects. The asymptotic properties of the proposed method are established and simulation studies are performed to validate the proposed approach. An application example for identifying the nonlinear dynamic GRN of T-cell activation is used to illustrate the usefulness of the proposed method.

  4. Sparse Additive Ordinary Differential Equations for Dynamic Gene Regulatory Network Modeling

    PubMed Central

    Wu, Hulin; Lu, Tao; Xue, Hongqi; Liang, Hua

    2014-01-01

    Summary The gene regulation network (GRN) is a high-dimensional complex system, which can be represented by various mathematical or statistical models. The ordinary differential equation (ODE) model is one of the popular dynamic GRN models. High-dimensional linear ODE models have been proposed to identify GRNs, but with a limitation of the linear regulation effect assumption. In this article, we propose a sparse additive ODE (SA-ODE) model, coupled with ODE estimation methods and adaptive group LASSO techniques, to model dynamic GRNs that could flexibly deal with nonlinear regulation effects. The asymptotic properties of the proposed method are established and simulation studies are performed to validate the proposed approach. An application example for identifying the nonlinear dynamic GRN of T-cell activation is used to illustrate the usefulness of the proposed method. PMID:25061254

  5. Additional regulatory activities of MrkH for the transcriptional expression of the Klebsiella pneumoniae mrk genes: Antagonist of H-NS and repressor

    PubMed Central

    Ares, Miguel A.; Fernández-Vázquez, José L.; Pacheco, Sabino; Martínez-Santos, Verónica I.; Jarillo-Quijada, Ma. Dolores; Torres, Javier; Alcántar-Curiel, María D.; González-y-Merchand, Jorge A.; De la Cruz, Miguel A.

    2017-01-01

    Klebsiella pneumoniae is a common opportunistic pathogen causing nosocomial infections. One of the main virulence determinants of K. pneumoniae is the type 3 pilus (T3P). T3P helps the bacterial interaction to both abiotic and biotic surfaces and it is crucial for the biofilm formation. T3P is genetically organized in three transcriptional units: the mrkABCDF polycistronic operon, the mrkHI bicistronic operon and the mrkJ gene. MrkH is a regulatory protein encoded in the mrkHI operon, which positively regulates the mrkA pilin gene and its own expression. In contrast, the H-NS nucleoid protein represses the transcriptional expression of T3P. Here we reported that MrkH and H-NS positively and negatively regulate mrkJ expression, respectively, by binding to the promoter of mrkJ. MrkH protein recognized a sequence located at position -63.5 relative to the transcriptional start site of mrkJ gene. Interestingly, our results show that, in addition to its known function as classic transcriptional activator, MrkH also positively controls the expression of mrk genes by acting as an anti-repressor of H-NS; moreover, our results support the notion that high levels of MrkH repress T3P expression. Our data provide new insights about the complex regulatory role of the MrkH protein on the transcriptional control of T3P in K. pneumoniae. PMID:28278272

  6. Additional regulatory activities of MrkH for the transcriptional expression of the Klebsiella pneumoniae mrk genes: Antagonist of H-NS and repressor.

    PubMed

    Ares, Miguel A; Fernández-Vázquez, José L; Pacheco, Sabino; Martínez-Santos, Verónica I; Jarillo-Quijada, Ma Dolores; Torres, Javier; Alcántar-Curiel, María D; González-Y-Merchand, Jorge A; De la Cruz, Miguel A

    2017-01-01

    Klebsiella pneumoniae is a common opportunistic pathogen causing nosocomial infections. One of the main virulence determinants of K. pneumoniae is the type 3 pilus (T3P). T3P helps the bacterial interaction to both abiotic and biotic surfaces and it is crucial for the biofilm formation. T3P is genetically organized in three transcriptional units: the mrkABCDF polycistronic operon, the mrkHI bicistronic operon and the mrkJ gene. MrkH is a regulatory protein encoded in the mrkHI operon, which positively regulates the mrkA pilin gene and its own expression. In contrast, the H-NS nucleoid protein represses the transcriptional expression of T3P. Here we reported that MrkH and H-NS positively and negatively regulate mrkJ expression, respectively, by binding to the promoter of mrkJ. MrkH protein recognized a sequence located at position -63.5 relative to the transcriptional start site of mrkJ gene. Interestingly, our results show that, in addition to its known function as classic transcriptional activator, MrkH also positively controls the expression of mrk genes by acting as an anti-repressor of H-NS; moreover, our results support the notion that high levels of MrkH repress T3P expression. Our data provide new insights about the complex regulatory role of the MrkH protein on the transcriptional control of T3P in K. pneumoniae.

  7. Identification of an additional ferric-siderophore uptake gene clustered with receptor, biosynthesis, and fur-like regulatory genes in fluorescent Pseudomonas sp. strain M114.

    PubMed Central

    O'Sullivan, D J; Morris, J; O'Gara, F

    1990-01-01

    Five cosmid clones with insert sizes averaging 22.6 kilobases (kb) were isolated after complementation of 22 Tn5-induced Sid- mutants of Pseudomonas sp. strain M114. One of these plasmids (pMS639) was also shown to encode ferric-siderophore receptor and dissociation functions. The receptor gene was located on this plasmid since introduction of the plasmid into three wild-type fluorescent pseudomonads enabled them to utilize the ferric-siderophore from strain M114. The presence of an extra iron-regulated protein in the outer membrane profile of one of these strains was detected by sodium dodecyl sulfate-polyacrylamide gel electrophoresis. A ferric-siderophore dissociation gene was attributed to pMS639 since it complemented the ferric-siderophore uptake mutation in strain M114FR2. This mutant was not defective in the outer membrane receptor for ferric-siderophore but apparently accumulated ferric-siderophore internally. Since ferric-citrate alleviated the iron stress of the mutant, there was no defect in iron metabolism subsequent to release of iron from the ferric-siderophore complex. Consequently, this mutant was defective in ferric-siderophore dissociation. A fur-like regulatory gene also present on pMS639 was subcloned to a 7.0-kb BglII insert of pCUP5 and was located approximately 7.3 kb from the receptor region. These results established that the 27.2-kb insert of pMS639 encoded at least two siderophore biosynthesis genes, ferric-siderophore receptor and dissociation genes, and a fur-like regulatory gene from the biocontrol fluorescent Pseudomonas sp. strain M114. Images PMID:2143887

  8. An Additional Regulatory Gene for Actinorhodin Production in Streptomyces lividans Involves a LysR-Type Transcriptional Regulator

    PubMed Central

    Martínez-Costa, Oscar H.; Martín-Triana, Angel J.; Martínez, Eduardo; Fernández-Moreno, Miguel A.; Malpartida, Francisco

    1999-01-01

    The sequence of a 4.8-kbp DNA fragment adjacent to the right-hand end of the actinorhodin biosynthetic (act) cluster downstream of actVB-orf6 from Streptomyces coelicolor A3(2) reveals six complete open reading frames, named orf7 to orf12. The deduced amino acid sequences from orf7, orf10, and orf11 show significant similarities with the following products in the databases: a putative protein from the S. coelicolor SCP3 plasmid, LysR-type transcriptional regulators, and proteins belonging to the family of short-chain dehydrogenases/reductases, respectively. The deduced product of orf8 reveals low similarities with several methyltransferases from different sources, while orf9 and orf12 products show no similarities with other known proteins. Disruptions of orf10 and orf11 genes in S. coelicolor appear to have no significant effect on the production of actinorhodin. Nevertheless, disruption or deletion of orf10 in Streptomyces lividans causes actinorhodin overproduction. The introduction of extra copies of orf10 and orf11 genes in an S. coelicolor actIII mutant restores the ability to produce actinorhodin. Transcriptional analysis and DNA footprinting indicate that Orf10 represses its own transcription and regulates orf11 transcription, expression of which might require the presence of an unknown inducer. No DNA target for Orf10 protein was found within the act cluster. PMID:10400594

  9. Selection of color additives: a regulatory view.

    PubMed

    Kumar, Anuj; Dureja, Harish; Madan, Anil K

    2012-01-01

    Color additives have a unique place in the categories of the excipients. However, most of the color additives are complex heterogeneous organic compounds. In pharmaceuticals, colors are used in various oral (solid, liquid) and topical dosage form. Different regulatory authorities have their own specific set of regulation for registration, approval, and control of color additives. However, at this time of globalization, selection of appropriate color is not an easy task when a company wants to sale its product in many countries. In this article, the authors have explored various important factors which should be considered in the selection of color additives.

  10. Plant Evolution: Evolving Antagonistic Gene Regulatory Networks.

    PubMed

    Cooper, Endymion D

    2016-06-20

    Developing a structurally complex phenotype requires a complex regulatory network. A new study shows how gene duplication provides a potential source of antagonistic interactions, an important component of gene regulatory networks.

  11. Regulatory genes in the ancestral chordate genomes.

    PubMed

    Satou, Yutaka; Wada, Shuichi; Sasakura, Yasunori; Satoh, Nori

    2008-12-01

    Changes or innovations in gene regulatory networks for the developmental program in the ancestral chordate genome appear to be a major component in the evolutionary process in which tadpole-type larvae, a unique characteristic of chordates, arose. These alterations may include new genetic interactions as well as the acquisition of new regulatory genes. Previous analyses of the Ciona genome revealed that many genes may have emerged after the divergence of the tunicate and vertebrate lineages. In this paper, we examined this possibility by examining a second non-vertebrate chordate genome. We conclude from this analysis that the ancient chordate included almost the same repertory of regulatory genes, but less redundancy than extant vertebrates, and that approximately 10% of vertebrate regulatory genes were innovated after the emergence of vertebrates. Thus, refined regulatory networks arose during vertebrate evolution mainly as preexisting regulatory genes multiplied rather than by generating new regulatory genes. The inferred regulatory gene sets of the ancestral chordate would be an important foundation for understanding how tadpole-type larvae, a unique characteristic of chordates, evolved.

  12. A Rhizobium meliloti symbiotic regulatory gene.

    PubMed

    Szeto, W W; Zimmerman, J L; Sundaresan, V; Ausubel, F M

    1984-04-01

    We have characterized a Rhizobium meliloti regulatory gene required for the expression of two closely linked symbiotic operons, the nitrogenase operon (nifHDK genes) and the "P2" operon. This regulatory gene maps to a 1.8 kb region located 5.5 kb upstream of the nifHDK operon. The regulatory gene is required for the accumulation of nifHDK and P2 mRNA and for the derepression of an R. meliloti nifH-lacZ fusion plasmid during symbiotic growth. The nifH and P2 promoters can be activated in free-living cultures of R. meliloti containing plasmids that produce the Escherichia coli ntrC(glnG) or the Klebsiella pneumoniae nifA regulatory gene products constitutively. The R. meliloti regulatory gene hybridizes to E. coli ntrC(glnG) and, to a lesser extent, to K. pneumoniae nifA DNA. Our results suggest that the R. meliloti regulatory gene acts as a positive transcriptional activator and that it is related to the K. pneumoniae nif regulatory genes.

  13. Modeling of hysteresis in gene regulatory networks.

    PubMed

    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.

  14. Evolving Robust Gene Regulatory Networks

    PubMed Central

    Noman, Nasimul; Monjo, Taku; Moscato, Pablo; Iba, Hitoshi

    2015-01-01

    Design and implementation of robust network modules is essential for construction of complex biological systems through hierarchical assembly of ‘parts’ and ‘devices’. The robustness of gene regulatory networks (GRNs) is ascribed chiefly to the underlying topology. The automatic designing capability of GRN topology that can exhibit robust behavior can dramatically change the current practice in synthetic biology. A recent study shows that Darwinian evolution can gradually develop higher topological robustness. Subsequently, this work presents an evolutionary algorithm that simulates natural evolution in silico, for identifying network topologies that are robust to perturbations. We present a Monte Carlo based method for quantifying topological robustness and designed a fitness approximation approach for efficient calculation of topological robustness which is computationally very intensive. The proposed framework was verified using two classic GRN behaviors: oscillation and bistability, although the framework is generalized for evolving other types of responses. The algorithm identified robust GRN architectures which were verified using different analysis and comparison. Analysis of the results also shed light on the relationship among robustness, cooperativity and complexity. This study also shows that nature has already evolved very robust architectures for its crucial systems; hence simulation of this natural process can be very valuable for designing robust biological systems. PMID:25616055

  15. Identifying genes of gene regulatory networks using formal concept analysis.

    PubMed

    Gebert, Jutta; Motameny, Susanne; Faigle, Ulrich; Forst, Christian V; Schrader, Rainer

    2008-03-01

    In order to understand the behavior of a gene regulatory network, it is essential to know the genes that belong to it. Identifying the correct members (e.g., in order to build a model) is a difficult task even for small subnetworks. Usually only few members of a network are known and one needs to guess the missing members based on experience or informed speculation. It is beneficial if one can additionally rely on experimental data to support this guess. In this work we present a new method based on formal concept analysis to detect unknown members of a gene regulatory network from gene expression time series data. We show that formal concept analysis is able to find a list of candidate genes for inclusion into a partially known basic network. This list can then be reduced by a statistical analysis so that the resulting genes interact strongly with the basic network and therefore should be included when modeling the network. The method has been applied to the DNA repair system of Mycobacterium tuberculosis. In this application, our method produces comparable results to an already existing method of component selection while it is applicable to a broader range of problems.

  16. Phenotype accessibility and noise in random threshold gene regulatory networks.

    PubMed

    Pinho, Ricardo; Garcia, Victor; Feldman, Marcus W

    2014-01-01

    Evolution requires phenotypic variation in a population of organisms for selection to function. Gene regulatory processes involved in organismal development affect the phenotypic diversity of organisms. Since only a fraction of all possible phenotypes are predicted to be accessed by the end of development, organisms may evolve strategies to use environmental cues and noise-like fluctuations to produce additional phenotypic diversity, and hence to enhance the speed of adaptation. We used a generic model of organismal development --gene regulatory networks-- to investigate how different levels of noise on gene expression states (i.e. phenotypes) may affect access to new, unique phenotypes, thereby affecting phenotypic diversity. We studied additional strategies that organisms might adopt to attain larger phenotypic diversity: either by augmenting their genome or the number of gene expression states. This was done for different types of gene regulatory networks that allow for distinct levels of regulatory influence on gene expression or are more likely to give rise to stable phenotypes. We found that if gene expression is binary, increasing noise levels generally decreases phenotype accessibility for all network types studied. If more gene expression states are considered, noise can moderately enhance the speed of discovery if three or four gene expression states are allowed, and if there are enough distinct regulatory networks in the population. These results were independent of the network types analyzed, and were robust to different implementations of noise. Hence, for noise to increase the number of accessible phenotypes in gene regulatory networks, very specific conditions need to be satisfied. If the number of distinct regulatory networks involved in organismal development is large enough, and the acquisition of more genes or fine tuning of their expression states proves costly to the organism, noise can be useful in allowing access to more unique phenotypes.

  17. Comparative studies of gene regulatory mechanisms.

    PubMed

    Pai, Athma A; Gilad, Yoav

    2014-12-01

    It has become increasingly clear that changes in gene regulation have played an important role in adaptive evolution both between and within species. Over the past five years, comparative studies have moved beyond simple characterizations of differences in gene expression levels within and between species to studying variation in regulatory mechanisms. We still know relatively little about the precise chain of events that lead to most regulatory adaptations, but we have taken significant steps towards understanding the relative importance of changes in different mechanisms of gene regulatory evolution. In this review, we first discuss insights from comparative studies in model organisms, where the available experimental toolkit is extensive. We then focus on a few recent comparative studies in primates, where the limited feasibility of experimental manipulation dictates the approaches that can be used to study gene regulatory evolution.

  18. Plant nitrogen regulatory P-PII genes

    DOEpatents

    Coruzzi, Gloria M.; Lam, Hon-Ming; Hsieh, Ming-Hsiun

    2001-01-01

    The present invention generally relates to plant nitrogen regulatory PII gene (hereinafter P-PII gene), a gene involved in regulating plant nitrogen metabolism. The invention provides P-PII nucleotide sequences, expression constructs comprising said nucleotide sequences, and host cells and plants having said constructs and, optionally expressing the P-PII gene from said constructs. The invention also provides substantially pure P-PII proteins. The P-PII nucleotide sequences and constructs of the

  19. Modeling gene regulatory network motifs using statecharts

    PubMed Central

    2012-01-01

    Background Gene regulatory networks are widely used by biologists to describe the interactions among genes, proteins and other components at the intra-cellular level. Recently, a great effort has been devoted to give gene regulatory networks a formal semantics based on existing computational frameworks. For this purpose, we consider Statecharts, which are a modular, hierarchical and executable formal model widely used to represent software systems. We use Statecharts for modeling small and recurring patterns of interactions in gene regulatory networks, called motifs. Results We present an improved method for modeling gene regulatory network motifs using Statecharts and we describe the successful modeling of several motifs, including those which could not be modeled or whose models could not be distinguished using the method of a previous proposal. We model motifs in an easy and intuitive way by taking advantage of the visual features of Statecharts. Our modeling approach is able to simulate some interesting temporal properties of gene regulatory network motifs: the delay in the activation and the deactivation of the "output" gene in the coherent type-1 feedforward loop, the pulse in the incoherent type-1 feedforward loop, the bistability nature of double positive and double negative feedback loops, the oscillatory behavior of the negative feedback loop, and the "lock-in" effect of positive autoregulation. Conclusions We present a Statecharts-based approach for the modeling of gene regulatory network motifs in biological systems. The basic motifs used to build more complex networks (that is, simple regulation, reciprocal regulation, feedback loop, feedforward loop, and autoregulation) can be faithfully described and their temporal dynamics can be analyzed. PMID:22536967

  20. Toward an orofacial gene regulatory network.

    PubMed

    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.

  1. Modeling stochastic noise in gene regulatory systems.

    PubMed

    Meister, Arwen; Du, Chao; Li, Ye Henry; Wong, Wing Hung

    2014-03-01

    The Master equation is considered the gold standard for modeling the stochastic mechanisms of gene regulation in molecular detail, but it is too complex to solve exactly in most cases, so approximation and simulation methods are essential. However, there is still a lack of consensus about the best way to carry these out. To help clarify the situation, we review Master equation models of gene regulation, theoretical approximations based on an expansion method due to N.G. van Kampen and R. Kubo, and simulation algorithms due to D.T. Gillespie and P. Langevin. Expansion of the Master equation shows that for systems with a single stable steady-state, the stochastic model reduces to a deterministic model in a first-order approximation. Additional theory, also due to van Kampen, describes the asymptotic behavior of multistable systems. To support and illustrate the theory and provide further insight into the complex behavior of multistable systems, we perform a detailed simulation study comparing the various approximation and simulation methods applied to synthetic gene regulatory systems with various qualitative characteristics. The simulation studies show that for large stochastic systems with a single steady-state, deterministic models are quite accurate, since the probability distribution of the solution has a single peak tracking the deterministic trajectory whose variance is inversely proportional to the system size. In multistable stochastic systems, large fluctuations can cause individual trajectories to escape from the domain of attraction of one steady-state and be attracted to another, so the system eventually reaches a multimodal probability distribution in which all stable steady-states are represented proportional to their relative stability. However, since the escape time scales exponentially with system size, this process can take a very long time in large systems.

  2. Phenotypic switching in gene regulatory networks.

    PubMed

    Thomas, Philipp; Popović, Nikola; Grima, Ramon

    2014-05-13

    Noise in gene expression can lead to reversible phenotypic switching. Several experimental studies have shown that the abundance distributions of proteins in a population of isogenic cells may display multiple distinct maxima. Each of these maxima may be associated with a subpopulation of a particular phenotype, the quantification of which is important for understanding cellular decision-making. Here, we devise a methodology which allows us to quantify multimodal gene expression distributions and single-cell power spectra in gene regulatory networks. Extending the commonly used linear noise approximation, we rigorously show that, in the limit of slow promoter dynamics, these distributions can be systematically approximated as a mixture of Gaussian components in a wide class of networks. The resulting closed-form approximation provides a practical tool for studying complex nonlinear gene regulatory networks that have thus far been amenable only to stochastic simulation. We demonstrate the applicability of our approach in a number of genetic networks, uncovering previously unidentified dynamical characteristics associated with phenotypic switching. Specifically, we elucidate how the interplay of transcriptional and translational regulation can be exploited to control the multimodality of gene expression distributions in two-promoter networks. We demonstrate how phenotypic switching leads to birhythmical expression in a genetic oscillator, and to hysteresis in phenotypic induction, thus highlighting the ability of regulatory networks to retain memory.

  3. Gene regulatory networks and the underlying biology of developmental toxicity

    EPA Science Inventory

    Embryonic cells are specified by large-scale networks of functionally linked regulatory genes. Knowledge of the relevant gene regulatory networks is essential for understanding phenotypic heterogeneity that emerges from disruption of molecular functions, cellular processes or sig...

  4. Autonomous Boolean modeling of gene regulatory networks

    NASA Astrophysics Data System (ADS)

    Socolar, Joshua; Sun, Mengyang; Cheng, Xianrui

    2014-03-01

    In cases where the dynamical properties of gene regulatory networks are important, a faithful model must include three key features: a network topology; a functional response of each element to its inputs; and timing information about the transmission of signals across network links. Autonomous Boolean network (ABN) models are efficient representations of these elements and are amenable to analysis. We present an ABN model of the gene regulatory network governing cell fate specification in the early sea urchin embryo, which must generate three bands of distinct tissue types after several cell divisions, beginning from an initial condition with only two distinct cell types. Analysis of the spatial patterning problem and the dynamics of a network constructed from available experimental results reveals that a simple mechanism is at work in this case. Supported by NSF Grant DMS-10-68602

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

    PubMed

    Narang, Vipin; Ramli, Muhamad Azfar; Singhal, Amit; Kumar, Pavanish; de Libero, Gennaro; Poidinger, Michael; Monterola, Christopher

    2015-01-01

    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.

  6. Gene regulatory logic of dopaminergic neuron differentiation

    PubMed Central

    Flames, Nuria; Hobert, Oliver

    2009-01-01

    Dopamine signaling regulates a variety of complex behaviors and defects in dopaminergic neuron function or survival result in severe human pathologies, such as Parkinson's disease 1. The common denominator of all dopaminergic neurons is the expression of dopamine pathway genes, which code for a set of phylogenetically conserved proteins involved in dopamine synthesis and transport. Gene regulatory mechanisms that result in the activation of dopamine pathway genes and thereby ultimately determine the identity of dopaminergic neurons are poorly understood in any system studied to date 2. We show here that a simple cis-regulatory element, the DA motif, controls the expression of all dopamine pathway genes in all dopaminergic cell types in C. elegans. The DA motif is activated by the ETS transcription factor, AST-1. Loss of ast-1 results in the failure of all distinct dopaminergic neuronal subtypes to terminally differentiate. Ectopic expression of ast-1 is sufficient to activate the dopamine production pathway in some cellular contexts. Vertebrate dopaminergic pathway genes also contain phylogenetically conserved DA motifs that can be activated by the mouse ETS transcription factor Etv1/ER81 and a specific class of dopaminergic neurons fails to differentiate in mice lacking Etv1/ER81. Moreover, ectopic Etv1/ER81 expression induces dopaminergic fate marker expression in neuronal primary cultures. Mouse Etv1/ER81 can also functionally substitute for ast-1 in C.elegans. Our studies reveal an astoundingly simple and apparently conserved regulatory logic of dopaminergic neuron terminal differentiation and may provide new entry points into the diagnosis or therapy of conditions in which dopamine neurons are defective. PMID:19287374

  7. Angiotensin II-regulated transcription regulatory genes in adrenal steroidogenesis.

    PubMed

    Romero, Damian G; Gomez-Sanchez, Elise P; Gomez-Sanchez, Celso E

    2010-11-29

    Transcription regulatory genes are crucial modulators of cell physiology and metabolism whose intracellular levels are tightly controlled in response to extracellular stimuli. We previously reported a set of 29 transcription regulatory genes modulated by angiotensin II in H295R human adrenocortical cells and their roles in regulating the expression of the last and unique enzymes of the glucocorticoid and mineralocorticoid biosynthetic pathways, 11β-hydroxylase and aldosterone synthase, respectively, using gene expression reporter assays. To study the effect of this set of transcription regulatory genes on adrenal steroidogenesis, H295R cells were transfected by high-efficiency nucleofection and aldosterone and cortisol were measured in cell culture supernatants under basal and angiotensin II-stimulated conditions. BCL11B, BHLHB2, CITED2, ELL2, HMGA1, MAFF, NFIL3, PER1, SERTAD1, and VDR significantly stimulated aldosterone secretion, while EGR1, FOSB, and ZFP295 decreased aldosterone secretion. BTG2, HMGA1, MITF, NR4A1, and ZFP295 significantly increased cortisol secretion, while BCL11B, NFIL3, PER1, and SIX2 decreased cortisol secretion. We also report the effect of some of these regulators on the expression of endogenous aldosterone synthase and 11β-hydroxylase under basal and angiotensin II-stimulated conditions. In summary, this study reports for the first time the effects of a set of angiotensin II-modulated transcription regulatory genes on aldosterone and cortisol secretion and the expression levels of the last and unique enzymes of the mineralocorticoid and glucocorticoid biosynthetic pathways. Abnormal regulation of mineralocorticoid or glucocorticoid secretion is involved in several pathophysiological conditions. These transcription regulatory genes may be involved in adrenal steroidogenesis pathologies; thus they merit additional study as potential candidates for therapeutic intervention.

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

    SciTech Connect

    Fung, Elizabeth-sharon

    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.

  9. EXAMINE: a computational approach to reconstructing gene regulatory networks.

    PubMed

    Deng, Xutao; Geng, Huimin; Ali, Hesham

    2005-08-01

    Reverse-engineering of gene networks using linear models often results in an underdetermined system because of excessive unknown parameters. In addition, the practical utility of linear models has remained unclear. We address these problems by developing an improved method, EXpression Array MINing Engine (EXAMINE), to infer gene regulatory networks from time-series gene expression data sets. EXAMINE takes advantage of sparse graph theory to overcome the excessive-parameter problem with an adaptive-connectivity model and fitting algorithm. EXAMINE also guarantees that the most parsimonious network structure will be found with its incremental adaptive fitting process. Compared to previous linear models, where a fully connected model is used, EXAMINE reduces the number of parameters by O(N), thereby increasing the chance of recovering the underlying regulatory network. The fitting algorithm increments the connectivity during the fitting process until a satisfactory fit is obtained. We performed a systematic study to explore the data mining ability of linear models. A guideline for using linear models is provided: If the system is small (3-20 elements), more than 90% of the regulation pathways can be determined correctly. For a large-scale system, either clustering is needed or it is necessary to integrate information in addition to expression profile. Coupled with the clustering method, we applied EXAMINE to rat central nervous system development (CNS) data with 112 genes. We were able to efficiently generate regulatory networks with statistically significant pathways that have been predicted previously.

  10. Constraint and contingency in multifunctional gene regulatory circuits.

    PubMed

    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.

  11. Mapping gene regulatory circuitry of Pax6 during neurogenesis

    PubMed Central

    Thakurela, Sudhir; Tiwari, Neha; Schick, Sandra; Garding, Angela; Ivanek, Robert; Berninger, Benedikt; Tiwari, Vijay K

    2016-01-01

    Pax6 is a highly conserved transcription factor among vertebrates and is important in various aspects of the central nervous system development. However, the gene regulatory circuitry of Pax6 underlying these functions remains elusive. We find that Pax6 targets a large number of promoters in neural progenitors cells. Intriguingly, many of these sites are also bound by another progenitor factor, Sox2, which cooperates with Pax6 in gene regulation. A combinatorial analysis of Pax6-binding data set with transcriptome changes in Pax6-deficient neural progenitors reveals a dual role for Pax6, in which it activates the neuronal (ectodermal) genes while concurrently represses the mesodermal and endodermal genes, thereby ensuring the unidirectionality of lineage commitment towards neuronal differentiation. Furthermore, Pax6 is critical for inducing activity of transcription factors that elicit neurogenesis and repress others that promote non-neuronal lineages. In addition to many established downstream effectors, Pax6 directly binds and activates a number of genes that are specifically expressed in neural progenitors but have not been previously implicated in neurogenesis. The in utero knockdown of one such gene, Ift74, during brain development impairs polarity and migration of newborn neurons. These findings demonstrate new aspects of the gene regulatory circuitry of Pax6, revealing how it functions to control neuronal development at multiple levels to ensure unidirectionality and proper execution of the neurogenic program. PMID:27462442

  12. Generation of oscillating gene regulatory network motifs

    NASA Astrophysics Data System (ADS)

    van Dorp, M.; Lannoo, B.; Carlon, E.

    2013-07-01

    Using an improved version of an evolutionary algorithm originally proposed by François and Hakim [Proc. Natl. Acad. Sci. USAPNASA60027-842410.1073/pnas.0304532101 101, 580 (2004)], we generated small gene regulatory networks in which the concentration of a target protein oscillates in time. These networks may serve as candidates for oscillatory modules to be found in larger regulatory networks and protein interaction networks. The algorithm was run for 105 times to produce a large set of oscillating modules, which were systematically classified and analyzed. The robustness of the oscillations against variations of the kinetic rates was also determined, to filter out the least robust cases. Furthermore, we show that the set of evolved networks can serve as a database of models whose behavior can be compared to experimentally observed oscillations. The algorithm found three smallest (core) oscillators in which nonlinearities and number of components are minimal. Two of those are two-gene modules: the mixed feedback loop, already discussed in the literature, and an autorepressed gene coupled with a heterodimer. The third one is a single gene module which is competitively regulated by a monomer and a dimer. The evolutionary algorithm also generated larger oscillating networks, which are in part extensions of the three core modules and in part genuinely new modules. The latter includes oscillators which do not rely on feedback induced by transcription factors, but are purely of post-transcriptional type. Analysis of post-transcriptional mechanisms of oscillation may provide useful information for circadian clock research, as recent experiments showed that circadian rhythms are maintained even in the absence of transcription.

  13. Integrated module and gene-specific regulatory inference implicates upstream signaling networks.

    PubMed

    Roy, Sushmita; Lagree, Stephen; Hou, Zhonggang; Thomson, James A; Stewart, Ron; Gasch, Audrey P

    2013-01-01

    Regulatory networks that control gene expression are important in diverse biological contexts including stress response and development. Each gene's regulatory program is determined by module-level regulation (e.g. co-regulation via the same signaling system), as well as gene-specific determinants that can fine-tune expression. We present a novel approach, Modular regulatory network learning with per gene information (MERLIN), that infers regulatory programs for individual genes while probabilistically constraining these programs to reveal module-level organization of regulatory networks. Using edge-, regulator- and module-based comparisons of simulated networks of known ground truth, we find MERLIN reconstructs regulatory programs of individual genes as well or better than existing approaches of network reconstruction, while additionally identifying modular organization of the regulatory networks. We use MERLIN to dissect global transcriptional behavior in two biological contexts: yeast stress response and human embryonic stem cell differentiation. Regulatory modules inferred by MERLIN capture co-regulatory relationships between signaling proteins and downstream transcription factors thereby revealing the upstream signaling systems controlling transcriptional responses. The inferred networks are enriched for regulators with genetic or physical interactions, supporting the inference, and identify modules of functionally related genes bound by the same transcriptional regulators. Our method combines the strengths of per-gene and per-module methods to reveal new insights into transcriptional regulation in stress and development.

  14. Integrated Module and Gene-Specific Regulatory Inference Implicates Upstream Signaling Networks

    PubMed Central

    Roy, Sushmita; Lagree, Stephen; Hou, Zhonggang; Thomson, James A.; Stewart, Ron; Gasch, Audrey P.

    2013-01-01

    Regulatory networks that control gene expression are important in diverse biological contexts including stress response and development. Each gene's regulatory program is determined by module-level regulation (e.g. co-regulation via the same signaling system), as well as gene-specific determinants that can fine-tune expression. We present a novel approach, Modular regulatory network learning with per gene information (MERLIN), that infers regulatory programs for individual genes while probabilistically constraining these programs to reveal module-level organization of regulatory networks. Using edge-, regulator- and module-based comparisons of simulated networks of known ground truth, we find MERLIN reconstructs regulatory programs of individual genes as well or better than existing approaches of network reconstruction, while additionally identifying modular organization of the regulatory networks. We use MERLIN to dissect global transcriptional behavior in two biological contexts: yeast stress response and human embryonic stem cell differentiation. Regulatory modules inferred by MERLIN capture co-regulatory relationships between signaling proteins and downstream transcription factors thereby revealing the upstream signaling systems controlling transcriptional responses. The inferred networks are enriched for regulators with genetic or physical interactions, supporting the inference, and identify modules of functionally related genes bound by the same transcriptional regulators. Our method combines the strengths of per-gene and per-module methods to reveal new insights into transcriptional regulation in stress and development. PMID:24146602

  15. Resolution of gene regulatory conflicts caused by combinations of antibiotics

    PubMed Central

    Bollenbach, Tobias; Kishony, Roy

    2011-01-01

    SUMMARY Regulatory conflicts occur when two signals which individually trigger opposite cellular responses are present simultaneously. Here, we investigate regulatory conflicts in the bacterial response to antibiotic combinations. We use an Escherichia coli promoter-GFP library to study the transcriptional response of many promoters to either additive or antagonistic drug pairs at fine two-dimensional resolution of drug concentration. Surprisingly, we find that this dataset can be characterized as a linear sum of only two principal components. Component one, accounting for over 70% of the response, represents the response to growth inhibition by the drugs. Component two describes how regulatory conflicts are resolved. For the additive drug pair, conflicts are resolved by linearly interpolating the single drug responses, while for the antagonistic drug pair, the growth-limiting drug dominates the response. Importantly, for a given drug pair, the same conflict resolution strategy applies to almost all genes. These results provide a recipe for predicting gene expression responses to antibiotic combinations. PMID:21596308

  16. Regulatory gene networks and the properties of the developmental process

    NASA Technical Reports Server (NTRS)

    Davidson, Eric H.; McClay, David R.; Hood, Leroy

    2003-01-01

    Genomic instructions for development are encoded in arrays of regulatory DNA. These specify large networks of interactions among genes producing transcription factors and signaling components. The architecture of such networks both explains and predicts developmental phenomenology. Although network analysis is yet in its early stages, some fundamental commonalities are already emerging. Two such are the use of multigenic feedback loops to ensure the progressivity of developmental regulatory states and the prevalence of repressive regulatory interactions in spatial control processes. Gene regulatory networks make it possible to explain the process of development in causal terms and eventually will enable the redesign of developmental regulatory circuitry to achieve different outcomes.

  17. Discovering Study-Specific Gene Regulatory Networks

    PubMed Central

    Bo, Valeria; Curtis, Tanya; Lysenko, Artem; Saqi, Mansoor; Swift, Stephen; Tucker, Allan

    2014-01-01

    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 approaches have been recently used that combine multiple microarray studies in order to find networks that are more robust. The purpose of this paper, however, is to combine multiple microarray studies to automatically identify subnetworks that are distinctive to specific experimental conditions rather than common to them all. To better understand key regulatory mechanisms and how they change under different conditions, we derive unique networks from multiple independent networks built using glasso which goes beyond standard correlations. This involves calculating cluster prediction accuracies to detect the most predictive genes for a specific set of conditions. We differentiate between accuracies calculated using cross-validation within a selected cluster of studies (the intra prediction accuracy) and those calculated on a set of independent studies belonging to different study clusters (inter prediction accuracy). Finally, we compare our method's results to related state-of-the art techniques. We explore how the proposed pipeline performs on both synthetic data and real data (wheat and Fusarium). Our results show that subnetworks can be identified reliably that are specific to subsets of studies and that these networks reflect key mechanisms that are fundamental to the experimental conditions in each of those subsets. PMID:25191999

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

    PubMed

    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.

  19. Caenorhabditis elegans metabolic gene regulatory networks govern the cellular economy.

    PubMed

    Watson, Emma; Walhout, Albertha J M

    2014-10-01

    Diet greatly impacts metabolism in health and disease. In response to the presence or absence of specific nutrients, metabolic gene regulatory networks sense the metabolic state of the cell and regulate metabolic flux accordingly, for instance by the transcriptional control of metabolic enzymes. Here, we discuss recent insights regarding metazoan metabolic regulatory networks using the nematode Caenorhabditis elegans as a model, including the modular organization of metabolic gene regulatory networks, the prominent impact of diet on the transcriptome and metabolome, specialized roles of nuclear hormone receptors (NHRs) in responding to dietary conditions, regulation of metabolic genes and metabolic regulators by miRNAs, and feedback between metabolic genes and their regulators.

  20. An internal regulatory element controls troponin I gene expression

    SciTech Connect

    Yutzey, K.E.; Kline, R.L.; Konieczmy, S.F. . Dept. of Biological Sciences)

    1989-04-01

    During skeletal myogenesis, approximately 20 contractile proteins and related gene products temporally accumulate as the cells fuse to form multinucleated muscle fibers. In most instances, the contractile protein genes are regulated transcriptionally, which suggests that a common molecular mechanism may coordinate the expression of this diverse and evolutionarily unrelated gene set. Recent studies have examined the muscle-specific cis-acting elements associated with numerous contractile protein genes. All of the identified regulatory elements are positioned in the 5'-flanking regions, usually within 1,500 base pairs of the transcription start site. Surprisingly, a DNA consensus sequence that is common to each contractile protein gene has not been identified. In contrast to the results of these earlier studies, the authors have found that the 5'-flanking region of the quail troponin I (TnI) gene is not sufficient to permit the normal myofiber transcriptional activation of the gene. Instead, the TnI gene utilizes a unique internal regulatory element that is responsible for the correct myofiber-specific expression pattern associated with the TnI gene. This is the first example in which a contractile protein gene has been shown to rely primarily on an internal regulatory element to elicit transcriptional activation during myogenesis. The diversity of regulatory elements associated with the contractile protein genes suggests that the temporal expression of the genes may involve individual cis-trans regulatory components specific for each gene.

  1. Deciphering RNA Regulatory Elements Involved in the Developmental and Environmental Gene Regulation of Trypanosoma brucei.

    PubMed

    Gazestani, Vahid H; Salavati, Reza

    2015-01-01

    Trypanosoma brucei is a vector-borne parasite with intricate life cycle that can cause serious diseases in humans and animals. This pathogen relies on fine regulation of gene expression to respond and adapt to variable environments, with implications in transmission and infectivity. However, the involved regulatory elements and their mechanisms of actions are largely unknown. Here, benefiting from a new graph-based approach for finding functional regulatory elements in RNA (GRAFFER), we have predicted 88 new RNA regulatory elements that are potentially involved in the gene regulatory network of T. brucei. We show that many of these newly predicted elements are responsive to both transcriptomic and proteomic changes during the life cycle of the parasite. Moreover, we found that 11 of predicted elements strikingly resemble previously identified regulatory elements for the parasite. Additionally, comparison with previously predicted motifs on T. brucei suggested the superior performance of our approach based on the current limited knowledge of regulatory elements in T. brucei.

  2. Computational inference of gene regulatory networks: Approaches, limitations and opportunities.

    PubMed

    Banf, Michael; Rhee, Seung Y

    2017-01-01

    Gene regulatory networks lie at the core of cell function control. In E. coli and S. cerevisiae, the study of gene regulatory networks has led to the discovery of regulatory mechanisms responsible for the control of cell growth, differentiation and responses to environmental stimuli. In plants, computational rendering of gene regulatory networks is gaining momentum, thanks to the recent availability of high-quality genomes and transcriptomes and development of computational network inference approaches. Here, we review current techniques, challenges and trends in gene regulatory network inference and highlight challenges and opportunities for plant science. We provide plant-specific application examples to guide researchers in selecting methodologies that suit their particular research questions. Given the interdisciplinary nature of gene regulatory network inference, we tried to cater to both biologists and computer scientists to help them engage in a dialogue about concepts and caveats in network inference. Specifically, we discuss problems and opportunities in heterogeneous data integration for eukaryotic organisms and common caveats to be considered during network model evaluation. This article is part of a Special Issue entitled: Plant Gene Regulatory Mechanisms and Networks, edited by Dr. Erich Grotewold and Dr. Nathan Springer.

  3. Unraveling gene regulatory networks from time-resolved gene expression data -- a measures comparison study

    PubMed Central

    2011-01-01

    Background Inferring regulatory interactions between genes from transcriptomics time-resolved data, yielding reverse engineered gene regulatory networks, is of paramount importance to systems biology and bioinformatics studies. Accurate methods to address this problem can ultimately provide a deeper insight into the complexity, behavior, and functions of the underlying biological systems. However, the large number of interacting genes coupled with short and often noisy time-resolved read-outs of the system renders the reverse engineering a challenging task. Therefore, the development and assessment of methods which are computationally efficient, robust against noise, applicable to short time series data, and preferably capable of reconstructing the directionality of the regulatory interactions remains a pressing research problem with valuable applications. Results Here we perform the largest systematic analysis of a set of similarity measures and scoring schemes within the scope of the relevance network approach which are commonly used for gene regulatory network reconstruction from time series data. In addition, we define and analyze several novel measures and schemes which are particularly suitable for short transcriptomics time series. We also compare the considered 21 measures and 6 scoring schemes according to their ability to correctly reconstruct such networks from short time series data by calculating summary statistics based on the corresponding specificity and sensitivity. Our results demonstrate that rank and symbol based measures have the highest performance in inferring regulatory interactions. In addition, the proposed scoring scheme by asymmetric weighting has shown to be valuable in reducing the number of false positive interactions. On the other hand, Granger causality as well as information-theoretic measures, frequently used in inference of regulatory networks, show low performance on the short time series analyzed in this study. Conclusions Our

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

    SciTech Connect

    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. Robustness and Accuracy in Sea Urchin Developmental Gene Regulatory Networks.

    PubMed

    Ben-Tabou de-Leon, Smadar

    2016-01-01

    Developmental gene regulatory networks robustly control the timely activation of regulatory and differentiation genes. The structure of these networks underlies their capacity to buffer intrinsic and extrinsic noise and maintain embryonic morphology. Here I illustrate how the use of specific architectures by the sea urchin developmental regulatory networks enables the robust control of cell fate decisions. The Wnt-βcatenin signaling pathway patterns the primary embryonic axis while the BMP signaling pathway patterns the secondary embryonic axis in the sea urchin embryo and across bilateria. Interestingly, in the sea urchin in both cases, the signaling pathway that defines the axis controls directly the expression of a set of downstream regulatory genes. I propose that this direct activation of a set of regulatory genes enables a uniform regulatory response and a clear cut cell fate decision in the endoderm and in the dorsal ectoderm. The specification of the mesodermal pigment cell lineage is activated by Delta signaling that initiates a triple positive feedback loop that locks down the pigment specification state. I propose that the use of compound positive feedback circuitry provides the endodermal cells enough time to turn off mesodermal genes and ensures correct mesoderm vs. endoderm fate decision. Thus, I argue that understanding the control properties of repeatedly used regulatory architectures illuminates their role in embryogenesis and provides possible explanations to their resistance to evolutionary change.

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

    PubMed Central

    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, including ntrB, envZ, virA, phoR, cpxA, and phoM. The N-terminal domains of the products of several regulatory genes thought to be transcriptional activators, including ntrC, ompR, virG, phoB and sfrA. In addition, the central and C-terminal regions of DctD were strongly conserved with the products of ntrC and nifA, transcriptional activators that require the alternate sigma factor rpoN (ntrA) as co-activator. The central region of DctD also contained a potential ATP-binding domain. These results are consistent with recent results that show that rpoN product is required for dctA activation, and suggest that DctB plus DctD-mediated transcriptional activation of dctA may be mechanistically similar to NtrB plus NtrC-mediated activation of glnA in E. coli. PMID:3671068

  7. Evolutionary conservation of regulatory elements in vertebrate Hox gene clusters.

    PubMed

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

    2003-06-01

    Comparisons of DNA sequences among evolutionarily distantly related genomes permit identification of conserved functional regions in noncoding DNA. Hox genes are highly conserved in vertebrates, occur in clusters, and are uninterrupted by other genes. We aligned (PipMaker) the nucleotide sequences of the HoxA clusters of tilapia, pufferfish, striped bass, zebrafish, horn shark, human, and mouse, which are separated by approximately 500 million years of evolution. In support of our approach, several identified putative regulatory elements known to regulate the expression of Hox genes were recovered. The majority of the newly identified putative regulatory elements contain short fragments that are almost completely conserved and are identical to known binding sites for regulatory proteins (Transfac database). The regulatory intergenic regions located between the genes that are expressed most anteriorly in the embryo are longer and apparently more evolutionarily conserved than those at the other end of Hox clusters. Different presumed regulatory sequences are retained in either the Aalpha or Abeta duplicated Hox clusters in the fish lineages. This suggests that the conserved elements are involved in different gene regulatory networks and supports the duplication-deletion-complementation model of functional divergence of duplicated genes.

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

    PubMed

    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 conditions

  9. Reconstruction of the regulatory network for Bacillus subtilis and reconciliation with gene expression data

    DOE PAGES

    Faria, Jose P.; Overbeek, Ross; Taylor, Ronald C.; ...

    2016-03-18

    Here, 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, wemore » 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

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

    PubMed Central

    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. A cis-Regulatory Signature for Chordate Anterior Neuroectodermal Genes

    PubMed Central

    Christiaen, Lionel; Joly, Jean-Stéphane

    2010-01-01

    One of the striking findings of comparative developmental genetics was that expression patterns of core transcription factors are extraordinarily conserved in bilaterians. However, it remains unclear whether cis-regulatory elements of their target genes also exhibit common signatures associated with conserved embryonic fields. To address this question, we focused on genes that are active in the anterior neuroectoderm and non-neural ectoderm of the ascidian Ciona intestinalis. Following the dissection of a prototypic anterior placodal enhancer, we searched all genomic conserved non-coding elements for duplicated motifs around genes showing anterior neuroectodermal expression. Strikingly, we identified an over-represented pentamer motif corresponding to the binding site of the homeodomain protein OTX, which plays a pivotal role in the anterior development of all bilaterian species. Using an in vivo reporter gene assay, we observed that 10 of 23 candidate cis-regulatory elements containing duplicated OTX motifs are active in the anterior neuroectoderm, thus showing that this cis-regulatory signature is predictive of neuroectodermal enhancers. These results show that a common cis-regulatory signature corresponding to K50-Paired homeodomain transcription factors is found in non-coding sequences flanking anterior neuroectodermal genes in chordate embryos. Thus, field-specific selector genes impose architectural constraints in the form of combinations of short tags on their target enhancers. This could account for the strong evolutionary conservation of the regulatory elements controlling field-specific selector genes responsible for body plan formation. PMID:20419150

  12. The companions: regulatory T cells and gene therapy

    PubMed Central

    Eghtesad, Saman; Morel, Penelope A; Clemens, Paula R

    2009-01-01

    Undesired immunological responses to products of therapeutic gene replacement have been obstacles to successful gene therapy. Understanding such responses of the host immune system to achieve immunological tolerance to a transferred gene product is therefore crucial. In this article, we review relevant studies of immunological responses to gene replacement therapy, the role of immunological tolerance mediated by regulatory T cells in down-regulating the unwanted immune responses, and the interrelationship of the two topics. PMID:19368560

  13. Emerging role of regulatory T cells in gene transfer.

    PubMed

    Cao, Ou; Furlan-Freguia, Christian; Arruda, Valder R; Herzog, Roland W

    2007-10-01

    Induction and maintenance of immune tolerance to therapeutic transgene products are key requirements for successful gene replacement therapies. Gene transfer may also be used to specifically induce immune tolerance and thereby augment other types of therapies. Similarly, gene therapies for treatment of autoimmune diseases are being developed in order to restore tolerance to self-antigens. Regulatory T cells have emerged as key players in many aspects of immune tolerance, and a rapidly increasing body of work documents induction and/or activation of regulatory T cells by gene transfer. Regulatory T cells may suppress antibody formation and cytotoxic T cell responses and may be critical for immune tolerance to therapeutic proteins. In this regard, CD4(+)CD25(+) regulatory T cells have been identified as important components of tolerance in several gene transfer protocols, including hepatic in vivo gene transfer. Augmentation of regulatory T cell responses should be a promising new tool to achieve tolerance and avoid immune-mediated rejection of gene therapy. During the past decade, it has become obvious that immune regulation is an important and integral component of tolerance to self-antigens and of many forms of induced tolerance. Gene therapy can only be successful if the immune system does not reject the therapeutic transgene product. Recent studies provide a rapidly growing body of evidence that regulatory T cells (T(reg)) are involved and often play a crucial role in tolerance to proteins expressed by means of gene transfer. This review seeks to provide an overview of these data and their implications for gene therapy.

  14. The molecular and gene regulatory signature of a neuron

    PubMed Central

    Hobert, Oliver; Carrera, Inés; Stefanakis, Nikolaos

    2010-01-01

    Neuron-type specific gene batteries define the morphological and functional diversity of cell types in the nervous system. Here, we discuss the composition of neuron-type specific gene batteries and illustrate gene regulatory strategies employed by distinct organisms from C.elegans to higher vertebrates, which are instrumental in determining the unique gene expression profile and molecular composition of individual neuronal cell types. Based on principles learned from prokaryotic gene regulation, we argue that neuronal, terminal gene batteries are functionally grouped into parallel acting “regulons”. The theoretical concepts discussed here provide testable hypotheses for future experimental analysis into the exact gene regulatory mechanisms that are employed in the generation of neuronal diversity and identity. PMID:20663572

  15. Gene regulatory networks modelling using a dynamic evolutionary hybrid

    PubMed Central

    2010-01-01

    Background Inference of gene regulatory networks is a key goal in the quest for understanding fundamental cellular processes and revealing underlying relations among genes. With the availability of gene expression data, computational methods aiming at regulatory networks reconstruction are facing challenges posed by the data's high dimensionality, temporal dynamics or measurement noise. We propose an approach based on a novel multi-layer evolutionary trained neuro-fuzzy recurrent network (ENFRN) that is able to select potential regulators of target genes and describe their regulation type. Results The recurrent, self-organizing structure and evolutionary training of our network yield an optimized pool of regulatory relations, while its fuzzy nature avoids noise-related problems. Furthermore, we are able to assign scores for each regulation, highlighting the confidence in the retrieved relations. The approach was tested by applying it to several benchmark datasets of yeast, managing to acquire biologically validated relations among genes. Conclusions The results demonstrate the effectiveness of the ENFRN in retrieving biologically valid regulatory relations and providing meaningful insights for better understanding the dynamics of gene regulatory networks. The algorithms and methods described in this paper have been implemented in a Matlab toolbox and are available from: http://bioserver-1.bioacademy.gr/DataRepository/Project_ENFRN_GRN/. PMID:20298548

  16. Time-Delayed Models of Gene Regulatory Networks

    PubMed Central

    Parmar, K.; Blyuss, K. B.; Kyrychko, Y. N.; Hogan, S. J.

    2015-01-01

    We discuss different mathematical models of gene regulatory networks as relevant to the onset and development of cancer. After discussion of alternative modelling approaches, we use a paradigmatic two-gene network to focus on the role played by time delays in the dynamics of gene regulatory networks. We contrast the dynamics of the reduced model arising in the limit of fast mRNA dynamics with that of the full model. The review concludes with the discussion of some open problems. PMID:26576197

  17. Estimating Gene Regulatory Networks with pandaR.

    PubMed

    Schlauch, Daniel; Paulson, Joseph N; Young, Albert; Glass, Kimberly; Quackenbush, John

    2017-03-11

    PANDA (Passing Attributes betweenNetworks forData Assimilation) is a gene regulatory network inference method that begins with amodel of transcription factor-target gene interactions and usesmessage passing to update the network model given available transcriptomic and protein-protein interaction data. PANDA is used to estimate networks for each experimental group and the network models are then compared between groups to explore transcriptional processes that distinguish the groups. We present pandaR (bioconductor.org/packages/pandaR), a Bioconductor package that implements PANDA and provides a framework for exploratory data analysis on gene regulatory networks.

  18. Systems Approaches to Identifying Gene Regulatory Networks in Plants

    PubMed Central

    Long, Terri A.; Brady, Siobhan M.; Benfey, Philip N.

    2009-01-01

    Complex gene regulatory networks are composed of genes, noncoding RNAs, proteins, metabolites, and signaling components. The availability of genome-wide mutagenesis libraries; large-scale transcriptome, proteome, and metabalome data sets; and new high-throughput methods that uncover protein interactions underscores the need for mathematical modeling techniques that better enable scientists to synthesize these large amounts of information and to understand the properties of these biological systems. Systems biology approaches can allow researchers to move beyond a reductionist approach and to both integrate and comprehend the interactions of multiple components within these systems. Descriptive and mathematical models for gene regulatory networks can reveal emergent properties of these plant systems. This review highlights methods that researchers are using to obtain large-scale data sets, and examples of gene regulatory networks modeled with these data. Emergent properties revealed by the use of these network models and perspectives on the future of systems biology are discussed. PMID:18616425

  19. Regulatory Genes Controlling Anthocyanin Pigmentation Are Functionally Conserved among Plant Species and Have Distinct Sets of Target Genes.

    PubMed Central

    Quattrocchio, F; Wing, JF; Leppen, H; Mol, J; Koes, RE

    1993-01-01

    In this study, we demonstrate that in petunia at least four regulatory genes (anthocyanin-1 [an1], an2, an4, and an11) control transcription of a subset of structural genes from the anthocyanin pathway by using a combination of RNA gel blot analysis, transcription run-on assays, and transient expression assays. an2- and an11- mutants could be transiently complemented by the maize regulatory genes Leaf color (Lc) or Colorless-1 (C1), respectively, whereas an1- mutants only by Lc and C1 together. In addition, the combination of Lc and C1 induces pigment accumulation in young leaves. This indicates that Lc and C1 are both necessary and sufficient to produce pigmentation in leaf cells. Regulatory pigmentation genes in maize and petunia control different sets of structural genes. The maize Lc and C1 genes expressed in petunia differentially activate the promoters of the chalcone synthase genes chsA and chsJ in the same way that the homologous petunia genes do. This suggests that the regulatory proteins in both species are functionally similar and that the choice of target genes is determined by their promoter sequences. We present an evolutionary model that explains the differences in regulation of pigmentation pathways of maize, petunia, and snapdragon. PMID:12271045

  20. Initial deployment of the cardiogenic gene regulatory network in the basal chordate, Ciona intestinalis.

    PubMed

    Woznica, Arielle; Haeussler, Maximilian; Starobinska, Ella; Jemmett, Jessica; Li, Younan; Mount, David; Davidson, Brad

    2012-08-01

    The complex, partially redundant gene regulatory architecture underlying vertebrate heart formation has been difficult to characterize. Here, we dissect the primary cardiac gene regulatory network in the invertebrate chordate, Ciona intestinalis. The Ciona heart progenitor lineage is first specified by Fibroblast Growth Factor/Map Kinase (FGF/MapK) activation of the transcription factor Ets1/2 (Ets). Through microarray analysis of sorted heart progenitor cells, we identified the complete set of primary genes upregulated by FGF/Ets shortly after heart progenitor emergence. Combinatorial sequence analysis of these co-regulated genes generated a hypothetical regulatory code consisting of Ets binding sites associated with a specific co-motif, ATTA. Through extensive reporter analysis, we confirmed the functional importance of the ATTA co-motif in primary heart progenitor gene regulation. We then used the Ets/ATTA combination motif to successfully predict a number of additional heart progenitor gene regulatory elements, including an intronic element driving expression of the core conserved cardiac transcription factor, GATAa. This work significantly advances our understanding of the Ciona heart gene network. Furthermore, this work has begun to elucidate the precise regulatory architecture underlying the conserved, primary role of FGF/Ets in chordate heart lineage specification.

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

    PubMed Central

    Benecke, Arndt

    2008-01-01

    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. PMID:19404429

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

    SciTech Connect

    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.

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

    PubMed Central

    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

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

    PubMed

    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.

  5. Portrait of Candida Species Biofilm Regulatory Network Genes.

    PubMed

    Araújo, Daniela; Henriques, Mariana; Silva, Sónia

    2017-01-01

    Most cases of candidiasis have been attributed to Candida albicans, but Candida glabrata, Candida parapsilosis and Candida tropicalis, designated as non-C. albicans Candida (NCAC), have been identified as frequent human pathogens. Moreover, Candida biofilms are an escalating clinical problem associated with significant rates of mortality. Biofilms have distinct developmental phases, including adhesion/colonisation, maturation and dispersal, controlled by complex regulatory networks. This review discusses recent advances regarding Candida species biofilm regulatory network genes, which are key components for candidiasis.

  6. A Maize Gene Regulatory Network for Phenolic Metabolism.

    PubMed

    Yang, Fan; Li, Wei; Jiang, Nan; Yu, Haidong; Morohashi, Kengo; Ouma, Wilberforce Zachary; Morales-Mantilla, Daniel E; Gomez-Cano, Fabio Andres; Mukundi, Eric; Prada-Salcedo, Luis Daniel; Velazquez, Roberto Alers; Valentin, Jasmin; Mejía-Guerra, Maria Katherine; Gray, John; Doseff, Andrea I; Grotewold, Erich

    2017-03-06

    The translation of the genotype into phenotype, represented for example by the expression of genes encoding enzymes required for the biosynthesis of phytochemicals that are important for interaction of plants with the environment, is largely carried out by transcription factors (TFs) that recognize specific cis-regulatory elements in the genes that they control. TFs and their target genes are organized in gene regulatory networks (GRNs), and thus uncovering GRN architecture presents an important biological challenge necessary to explain gene regulation. Linking TFs to the genes they control, central to understanding GRNs, can be carried out using gene- or TF-centered approaches. In this study, we employed a gene-centered approach utilizing the yeast one-hybrid assay to generate a network of protein-DNA interactions that participate in the transcriptional control of genes involved in the biosynthesis of maize phenolic compounds including general phenylpropanoids, lignins, and flavonoids. We identified 1100 protein-DNA interactions involving 54 phenolic gene promoters and 568 TFs. A set of 11 TFs recognized 10 or more promoters, suggesting a role in coordinating pathway gene expression. The integration of the gene-centered network with information derived from TF-centered approaches provides a foundation for a phenolics GRN characterized by interlaced feed-forward loops that link developmental regulators with biosynthetic genes.

  7. A gene regulatory network controlling the embryonic specification of endoderm.

    PubMed

    Peter, Isabelle S; Davidson, Eric H

    2011-05-29

    Specification of endoderm is the prerequisite for gut formation in the embryogenesis of bilaterian organisms. Modern lineage labelling studies have shown that in the sea urchin embryo model system, descendants of the veg1 and veg2 cell lineages produce the endoderm, and that the veg2 lineage also gives rise to mesodermal cell types. It is known that Wnt/β-catenin signalling is required for endoderm specification and Delta/Notch signalling is required for mesoderm specification. Some direct cis-regulatory targets of these signals have been found and various phenomenological patterns of gene expression have been observed in the pre-gastrular endomesoderm. However, no comprehensive, causal explanation of endoderm specification has been conceived for sea urchins, nor for any other deuterostome. Here we propose a model, on the basis of the underlying genomic control system, that provides such an explanation, built at several levels of biological organization. The hardwired core of the control system consists of the cis-regulatory apparatus of endodermal regulatory genes, which determine the relationship between the inputs to which these genes are exposed and their outputs. The architecture of the network circuitry controlling the dynamic process of endoderm specification then explains, at the system level, a sequence of developmental logic operations, which generate the biological process. The control system initiates non-interacting endodermal and mesodermal gene regulatory networks in veg2-derived cells and extinguishes the endodermal gene regulatory network in mesodermal precursors. It also generates a cross-regulatory network that specifies future anterior endoderm in veg2 descendants and institutes a distinct network specifying posterior endoderm in veg1-derived cells. The network model provides an explanatory framework that relates endoderm specification to the genomic regulatory code.

  8. Regulatory links between imprinted genes: evolutionary predictions and consequences.

    PubMed

    Patten, Manus M; Cowley, Michael; Oakey, Rebecca J; Feil, Robert

    2016-02-10

    Genomic imprinting is essential for development and growth and plays diverse roles in physiology and behaviour. Imprinted genes have traditionally been studied in isolation or in clusters with respect to cis-acting modes of gene regulation, both from a mechanistic and evolutionary point of view. Recent studies in mammals, however, reveal that imprinted genes are often co-regulated and are part of a gene network involved in the control of cellular proliferation and differentiation. Moreover, a subset of imprinted genes acts in trans on the expression of other imprinted genes. Numerous studies have modulated levels of imprinted gene expression to explore phenotypic and gene regulatory consequences. Increasingly, the applied genome-wide approaches highlight how perturbation of one imprinted gene may affect other maternally or paternally expressed genes. Here, we discuss these novel findings and consider evolutionary theories that offer a rationale for such intricate interactions among imprinted genes. An evolutionary view of these trans-regulatory effects provides a novel interpretation of the logic of gene networks within species and has implications for the origin of reproductive isolation between species.

  9. Regulatory links between imprinted genes: evolutionary predictions and consequences

    PubMed Central

    Patten, Manus M.; Cowley, Michael; Oakey, Rebecca J.; Feil, Robert

    2016-01-01

    Genomic imprinting is essential for development and growth and plays diverse roles in physiology and behaviour. Imprinted genes have traditionally been studied in isolation or in clusters with respect to cis-acting modes of gene regulation, both from a mechanistic and evolutionary point of view. Recent studies in mammals, however, reveal that imprinted genes are often co-regulated and are part of a gene network involved in the control of cellular proliferation and differentiation. Moreover, a subset of imprinted genes acts in trans on the expression of other imprinted genes. Numerous studies have modulated levels of imprinted gene expression to explore phenotypic and gene regulatory consequences. Increasingly, the applied genome-wide approaches highlight how perturbation of one imprinted gene may affect other maternally or paternally expressed genes. Here, we discuss these novel findings and consider evolutionary theories that offer a rationale for such intricate interactions among imprinted genes. An evolutionary view of these trans-regulatory effects provides a novel interpretation of the logic of gene networks within species and has implications for the origin of reproductive isolation between species. PMID:26842569

  10. Dynamics of gene regulatory networks with cell division cycle

    NASA Astrophysics Data System (ADS)

    Chen, Luonan; Wang, Ruiqi; Kobayashi, Tetsuya J.; Aihara, Kazuyuki

    2004-07-01

    This paper focuses on modeling and analyzing the nonlinear dynamics of gene regulatory networks with the consideration of a cell division cycle with duplication process of DNA , in particular for switches and oscillators of synthetic networks. We derive two models that may correspond to the eukaryotic and prokaryotic cells, respectively. A biologically plausible three-gene model ( lac,tetR , and cI ) and a repressilator as switch and oscillator examples are used to illustrate our theoretical results. We show that the cell cycle may play a significant role in gene regulation due to the nonlinear dynamics of a gene regulatory network although gene expressions are usually tightly controlled by transcriptional factors.

  11. Evolutionary conservation of the eumetazoan gene regulatory landscape

    PubMed Central

    Schwaiger, Michaela; Schönauer, Anna; Rendeiro, André F.; Pribitzer, Carina; Schauer, Alexandra; Gilles, Anna F.; Schinko, Johannes B.; Renfer, Eduard; Fredman, David; Technau, Ulrich

    2014-01-01

    Despite considerable differences in morphology and complexity of body plans among animals, a great part of the gene set is shared among Bilateria and their basally branching sister group, the Cnidaria. This suggests that the common ancestor of eumetazoans already had a highly complex gene repertoire. At present it is therefore unclear how morphological diversification is encoded in the genome. Here we address the possibility that differences in gene regulation could contribute to the large morphological divergence between cnidarians and bilaterians. To this end, we generated the first genome-wide map of gene regulatory elements in a nonbilaterian animal, the sea anemone Nematostella vectensis. Using chromatin immunoprecipitation followed by deep sequencing of five chromatin modifications and a transcriptional cofactor, we identified over 5000 enhancers in the Nematostella genome and could validate 75% of the tested enhancers in vivo. We found that in Nematostella, but not in yeast, enhancers are characterized by the same combination of histone modifications as in bilaterians, and these enhancers preferentially target developmental regulatory genes. Surprisingly, the distribution and abundance of gene regulatory elements relative to these genes are shared between Nematostella and bilaterian model organisms. Our results suggest that complex gene regulation originated at least 600 million yr ago, predating the common ancestor of eumetazoans. PMID:24642862

  12. Variable neighborhood search for reverse engineering of gene regulatory networks.

    PubMed

    Nicholson, Charles; Goodwin, Leslie; Clark, Corey

    2017-01-01

    A new search heuristic, Divided Neighborhood Exploration Search, designed to be used with inference algorithms such as Bayesian networks to improve on the reverse engineering of gene regulatory networks is presented. The approach systematically moves through the search space to find topologies representative of gene regulatory networks that are more likely to explain microarray data. In empirical testing it is demonstrated that the novel method is superior to the widely employed greedy search techniques in both the quality of the inferred networks and computational time.

  13. Computational identification and functional validation of regulatory motifs in cartilage-expressed genes

    PubMed Central

    Davies, Sherri R.; Chang, Li-Wei; Patra, Debabrata; Xing, Xiaoyun; Posey, Karen; Hecht, Jacqueline; Stormo, Gary D.; Sandell, Linda J.

    2007-01-01

    Chondrocyte gene regulation is important for the generation and maintenance of cartilage tissues. Several regulatory factors have been identified that play a role in chondrogenesis, including the positive transacting factors of the SOX family such as SOX9, SOX5, and SOX6, as well as negative transacting factors such as C/EBP and delta EF1. However, a complete understanding of the intricate regulatory network that governs the tissue-specific expression of cartilage genes is not yet available. We have taken a computational approach to identify cis-regulatory, transcription factor (TF) binding motifs in a set of cartilage characteristic genes to better define the transcriptional regulatory networks that regulate chondrogenesis. Our computational methods have identified several TFs, whose binding profiles are available in the TRANSFAC database, as important to chondrogenesis. In addition, a cartilage-specific SOX-binding profile was constructed and used to identify both known, and novel, functional paired SOX-binding motifs in chondrocyte genes. Using DNA pattern-recognition algorithms, we have also identified cis-regulatory elements for unknown TFs. We have validated our computational predictions through mutational analyses in cell transfection experiments. One novel regulatory motif, N1, found at high frequency in the COL2A1 promoter, was found to bind to chondrocyte nuclear proteins. Mutational analyses suggest that this motif binds a repressive factor that regulates basal levels of the COL2A1 promoter. PMID:17785538

  14. Learning gene regulatory networks from next generation sequencing data.

    PubMed

    Jia, Bochao; Xu, Suwa; Xiao, Guanghua; Lamba, Vishal; Liang, Faming

    2017-03-10

    In recent years, next generation sequencing (NGS) has gradually replaced microarray as the major platform in measuring gene expressions. Compared to microarray, NGS has many advantages, such as less noise and higher throughput. However, the discreteness of NGS data also challenges the existing statistical methodology. In particular, there still lacks an appropriate statistical method for reconstructing gene regulatory networks using NGS data in the literature. The existing local Poisson graphical model method is not consistent and can only infer certain local structures of the network. In this article, we propose a random effect model-based transformation to continuize NGS data and then we transform the continuized data to Gaussian via a semiparametric transformation and apply an equivalent partial correlation selection method to reconstruct gene regulatory networks. The proposed method is consistent. The numerical results indicate that the proposed method can lead to much more accurate inference of gene regulatory networks than the local Poisson graphical model and other existing methods. The proposed data-continuized transformation fills the theoretical gap for how to transform discrete data to continuous data and facilitates NGS data analysis. The proposed data-continuized transformation also makes it feasible to integrate different types of data, such as microarray and RNA-seq data, in reconstruction of gene regulatory networks.

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

    PubMed

    Winck, Flavia Vischi; Vischi Winck, Flavia; Arvidsson, Samuel; Riaño-Pachón, Diego Mauricio; Hempel, Sabrina; Koseska, Aneta; Nikoloski, Zoran; Urbina Gomez, David Alejandro; Rupprecht, Jens; Mueller-Roeber, Bernd

    2013-01-01

    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. Our work can

  16. [Regulatory functions of Pax gene family in Drosophila development].

    PubMed

    Li, Li; Yang, Yang; Xue, Lei

    2010-02-01

    The Pax gene family encodes a group of important transcription factors that have been evolutionary conserved from Drosophila to human. Pax genes play pivotal roles in regulating diverse signal transduction pathways and organogenesis during embryonic development through modulating cell proliferation and self-renewal, embryonic precursor cell migration, and the coordination of specific differentiation programs. Ten members of the Pax gene family, which perform crucial regulatory functions during embryonic and postembryonic development, have been identified in Drosophila. In this report, we described the protein structures, expression patterns, and main functions of Drosophila Pax genes.

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

    PubMed

    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.

  18. Combinatorial Gene Regulatory Functions Underlie Ultraconserved Elements in Drosophila.

    PubMed

    Warnefors, Maria; Hartmann, Britta; Thomsen, Stefan; Alonso, Claudio R

    2016-09-01

    Ultraconserved elements (UCEs) are discrete genomic elements conserved across large evolutionary distances. Although UCEs have been linked to multiple facets of mammalian gene regulation their extreme evolutionary conservation remains largely unexplained. Here, we apply a computational approach to investigate this question in Drosophila, exploring the molecular functions of more than 1,500 UCEs shared across the genomes of 12 Drosophila species. Our data indicate that Drosophila UCEs are hubs for gene regulatory functions and suggest that UCE sequence invariance originates from their combinatorial roles in gene control. We also note that the gene regulatory roles of intronic and intergenic UCEs (iUCEs) are distinct from those found in exonic UCEs (eUCEs). In iUCEs, transcription factor (TF) and epigenetic factor binding data strongly support iUCE roles in transcriptional and epigenetic regulation. In contrast, analyses of eUCEs indicate that they are two orders of magnitude more likely than the expected to simultaneously include protein-coding sequence, TF-binding sites, splice sites, and RNA editing sites but have reduced roles in transcriptional or epigenetic regulation. Furthermore, we use a Drosophila cell culture system and transgenic Drosophila embryos to validate the notion of UCE combinatorial regulatory roles using an eUCE within the Hox gene Ultrabithorax and show that its protein-coding region also contains alternative splicing regulatory information. Taken together our experiments indicate that UCEs emerge as a result of combinatorial gene regulatory roles and highlight common features in mammalian and insect UCEs implying that similar processes might underlie ultraconservation in diverse animal taxa.

  19. Combinatorial Gene Regulatory Functions Underlie Ultraconserved Elements in Drosophila

    PubMed Central

    Warnefors, Maria; Hartmann, Britta; Thomsen, Stefan; Alonso, Claudio R.

    2016-01-01

    Ultraconserved elements (UCEs) are discrete genomic elements conserved across large evolutionary distances. Although UCEs have been linked to multiple facets of mammalian gene regulation their extreme evolutionary conservation remains largely unexplained. Here, we apply a computational approach to investigate this question in Drosophila, exploring the molecular functions of more than 1,500 UCEs shared across the genomes of 12 Drosophila species. Our data indicate that Drosophila UCEs are hubs for gene regulatory functions and suggest that UCE sequence invariance originates from their combinatorial roles in gene control. We also note that the gene regulatory roles of intronic and intergenic UCEs (iUCEs) are distinct from those found in exonic UCEs (eUCEs). In iUCEs, transcription factor (TF) and epigenetic factor binding data strongly support iUCE roles in transcriptional and epigenetic regulation. In contrast, analyses of eUCEs indicate that they are two orders of magnitude more likely than the expected to simultaneously include protein-coding sequence, TF-binding sites, splice sites, and RNA editing sites but have reduced roles in transcriptional or epigenetic regulation. Furthermore, we use a Drosophila cell culture system and transgenic Drosophila embryos to validate the notion of UCE combinatorial regulatory roles using an eUCE within the Hox gene Ultrabithorax and show that its protein-coding region also contains alternative splicing regulatory information. Taken together our experiments indicate that UCEs emerge as a result of combinatorial gene regulatory roles and highlight common features in mammalian and insect UCEs implying that similar processes might underlie ultraconservation in diverse animal taxa. PMID:27247329

  20. Efficient reverse-engineering of a developmental gene regulatory network.

    PubMed

    Crombach, Anton; Wotton, Karl R; Cicin-Sain, Damjan; Ashyraliyev, Maksat; Jaeger, Johannes

    2012-01-01

    Understanding the complex regulatory networks underlying development and evolution of multi-cellular organisms is a major problem in biology. Computational models can be used as tools to extract the regulatory structure and dynamics of such networks from gene expression data. This approach is called reverse engineering. It has been successfully applied to many gene networks in various biological systems. However, to reconstitute the structure and non-linear dynamics of a developmental gene network in its spatial context remains a considerable challenge. Here, we address this challenge using a case study: the gap gene network involved in segment determination during early development of Drosophila melanogaster. A major problem for reverse-engineering pattern-forming networks is the significant amount of time and effort required to acquire and quantify spatial gene expression data. We have developed a simplified data processing pipeline that considerably increases the throughput of the method, but results in data of reduced accuracy compared to those previously used for gap gene network inference. We demonstrate that we can infer the correct network structure using our reduced data set, and investigate minimal data requirements for successful reverse engineering. Our results show that timing and position of expression domain boundaries are the crucial features for determining regulatory network structure from data, while it is less important to precisely measure expression levels. Based on this, we define minimal data requirements for gap gene network inference. Our results demonstrate the feasibility of reverse-engineering with much reduced experimental effort. This enables more widespread use of the method in different developmental contexts and organisms. Such systematic application of data-driven models to real-world networks has enormous potential. Only the quantitative investigation of a large number of developmental gene regulatory networks will allow us to

  1. Efficient Reverse-Engineering of a Developmental Gene Regulatory Network

    PubMed Central

    Cicin-Sain, Damjan; Ashyraliyev, Maksat; Jaeger, Johannes

    2012-01-01

    Understanding the complex regulatory networks underlying development and evolution of multi-cellular organisms is a major problem in biology. Computational models can be used as tools to extract the regulatory structure and dynamics of such networks from gene expression data. This approach is called reverse engineering. It has been successfully applied to many gene networks in various biological systems. However, to reconstitute the structure and non-linear dynamics of a developmental gene network in its spatial context remains a considerable challenge. Here, we address this challenge using a case study: the gap gene network involved in segment determination during early development of Drosophila melanogaster. A major problem for reverse-engineering pattern-forming networks is the significant amount of time and effort required to acquire and quantify spatial gene expression data. We have developed a simplified data processing pipeline that considerably increases the throughput of the method, but results in data of reduced accuracy compared to those previously used for gap gene network inference. We demonstrate that we can infer the correct network structure using our reduced data set, and investigate minimal data requirements for successful reverse engineering. Our results show that timing and position of expression domain boundaries are the crucial features for determining regulatory network structure from data, while it is less important to precisely measure expression levels. Based on this, we define minimal data requirements for gap gene network inference. Our results demonstrate the feasibility of reverse-engineering with much reduced experimental effort. This enables more widespread use of the method in different developmental contexts and organisms. Such systematic application of data-driven models to real-world networks has enormous potential. Only the quantitative investigation of a large number of developmental gene regulatory networks will allow us to

  2. New frontiers in the therapy of primary immunodeficiency: From gene addition to gene editing.

    PubMed

    Kohn, Donald B; Kuo, Caroline Y

    2017-03-01

    The most severe primary immune deficiency diseases (PIDs) have been successfully treated with allogeneic hematopoietic stem cell transplantation for more than 4 decades. However, such transplantations have the best outcomes when there is a well-matched donor available because immune complications, such as graft-versus-host disease, are greater without a matched sibling donor. Gene therapy has been developed as a method to perform autologous transplantations of a patient's own stem cells that are genetically corrected. Through an iterative bench-to-bedside-and-back process, methods to efficiently add new copies of the relevant gene to hematopoietic stem cells have led to safe and effective treatments for several PIDs, including forms of severe combined immune deficiency, Wiskott-Aldrich syndrome, and chronic granulomatous disease. New methods for gene editing might allow additional PIDs to be treated by gene therapy because they will allow the endogenous gene to be repaired and expressed under its native regulatory elements, which are essential for genes involved in cell processes of signaling, activation, and proliferation. Gene therapy is providing exciting new treatment options for patients with PIDs, and advances are sure to continue.

  3. Inferring transcription factor collaborations in gene regulatory networks

    PubMed Central

    2014-01-01

    Background Living cells are realized by complex gene expression programs that are moderated by regulatory proteins called transcription factors (TFs). The TFs control the differential expression of target genes in the context of transcriptional regulatory networks (TRNs), either individually or in groups. Deciphering the mechanisms of how the TFs control the expression of target genes is a challenging task, especially when multiple TFs collaboratively participate in the transcriptional regulation. Results We model the underlying regulatory interactions in terms of the directions (activation or repression) and their logical roles (necessary and/or sufficient) with a modified association rule mining approach, called mTRIM. The experiment on Yeast discovered 670 regulatory interactions, in which multiple TFs express their functions on common target genes collaboratively. The evaluation on yeast genetic interactions, TF knockouts and a synthetic dataset shows that our algorithm is significantly better than the existing ones. Conclusions mTRIM is a novel method to infer TF collaborations in transcriptional regulation networks. mTRIM is available at http://www.msu.edu/~jinchen/mTRIM. PMID:24565025

  4. Compartmentalized gene regulatory network of the pathogenic fungus Fusarium graminearum

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Head blight caused by Fusarium graminearum (Fg) is a major limiting factor of wheat production with both yield loss and mycotoxin contamination. Here we report a model for global Fg gene regulatory networks (GRNs) inferred from a large collection of transcriptomic data using a machine-learning appro...

  5. Second order optimization for the inference of gene regulatory pathways.

    PubMed

    Das, Mouli; Murthy, Chivukula A; De, Rajat K

    2014-02-01

    With the increasing availability of experimental data on gene interactions, modeling of gene regulatory pathways has gained special attention. Gradient descent algorithms have been widely used for regression and classification applications. Unfortunately, results obtained after training a model by gradient descent are often highly variable. In this paper, we present a new second order learning rule based on the Newton's method for inferring optimal gene regulatory pathways. Unlike the gradient descent method, the proposed optimization rule is independent of the learning parameter. The flow vectors are estimated based on biomass conservation. A set of constraints is formulated incorporating weighting coefficients. The method calculates the maximal expression of the target gene starting from a given initial gene through these weighting coefficients. Our algorithm has been benchmarked and validated on certain types of functions and on some gene regulatory networks, gathered from literature. The proposed method has been found to perform better than the gradient descent learning. Extensive performance comparison with the extreme pathway analysis method has underlined the effectiveness of our proposed methodology.

  6. Inferring orthologous gene regulatory networks using interspecies data fusion

    PubMed Central

    Penfold, Christopher A.; Millar, Jonathan B. A.; Wild, David L.

    2015-01-01

    Motivation: The ability to jointly learn gene regulatory networks (GRNs) in, or leverage GRNs between related species would allow the vast amount of legacy data obtained in model organisms to inform the GRNs of more complex, or economically or medically relevant counterparts. Examples include transferring information from Arabidopsis thaliana into related crop species for food security purposes, or from mice into humans for medical applications. Here we develop two related Bayesian approaches to network inference that allow GRNs to be jointly inferred in, or leveraged between, several related species: in one framework, network information is directly propagated between species; in the second hierarchical approach, network information is propagated via an unobserved ‘hypernetwork’. In both frameworks, information about network similarity is captured via graph kernels, with the networks additionally informed by species-specific time series gene expression data, when available, using Gaussian processes to model the dynamics of gene expression. Results: Results on in silico benchmarks demonstrate that joint inference, and leveraging of known networks between species, offers better accuracy than standalone inference. The direct propagation of network information via the non-hierarchical framework is more appropriate when there are relatively few species, while the hierarchical approach is better suited when there are many species. Both methods are robust to small amounts of mislabelling of orthologues. Finally, the use of Saccharomyces cerevisiae data and networks to inform inference of networks in the budding yeast Schizosaccharomyces pombe predicts a novel role in cell cycle regulation for Gas1 (SPAC19B12.02c), a 1,3-beta-glucanosyltransferase. Availability and implementation: MATLAB code is available from http://go.warwick.ac.uk/systemsbiology/software/. Contact: d.l.wild@warwick.ac.uk Supplementary information: Supplementary data are available at Bioinformatics

  7. Molecular characterization of a maize regulatory gene

    SciTech Connect

    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.

  8. Inferring slowly-changing dynamic gene-regulatory networks

    PubMed Central

    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. PMID:25917062

  9. Gene regulatory networks elucidating Huanglongbing disease mechanisms

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  10. Topological origin of global attractors in gene regulatory networks

    NASA Astrophysics Data System (ADS)

    Zhang, YunJun; Ouyang, Qi; Geng, Zhi

    2015-02-01

    Fixed-point attractors with global stability manifest themselves in a number of gene regulatory networks. This property indicates the stability of regulatory networks against small state perturbations and is closely related to other complex dynamics. In this paper, we aim to reveal the core modules in regulatory networks that determine their global attractors and the relationship between these core modules and other motifs. This work has been done via three steps. Firstly, inspired by the signal transmission in the regulation process, we extract the model of chain-like network from regulation networks. We propose a module of "ideal transmission chain (ITC)", which is proved sufficient and necessary (under certain condition) to form a global fixed-point in the context of chain-like network. Secondly, by examining two well-studied regulatory networks (i.e., the cell-cycle regulatory networks of Budding yeast and Fission yeast), we identify the ideal modules in true regulation networks and demonstrate that the modules have a superior contribution to network stability (quantified by the relative size of the biggest attraction basin). Thirdly, in these two regulation networks, we find that the double negative feedback loops, which are the key motifs of forming bistability in regulation, are connected to these core modules with high network stability. These results have shed new light on the connection between the topological feature and the dynamic property of regulatory networks.

  11. Modularity and evolutionary constraints in a baculovirus gene regulatory network

    PubMed Central

    2013-01-01

    Background The structure of regulatory networks remains an open question in our understanding of complex biological systems. Interactions during complete viral life cycles present unique opportunities to understand how host-parasite network take shape and behave. The Anticarsia gemmatalis multiple nucleopolyhedrovirus (AgMNPV) is a large double-stranded DNA virus, whose genome may encode for 152 open reading frames (ORFs). Here we present the analysis of the ordered cascade of the AgMNPV gene expression. Results We observed an earlier onset of the expression than previously reported for other baculoviruses, especially for genes involved in DNA replication. Most ORFs were expressed at higher levels in a more permissive host cell line. Genes with more than one copy in the genome had distinct expression profiles, which could indicate the acquisition of new functionalities. The transcription gene regulatory network (GRN) for 149 ORFs had a modular topology comprising five communities of highly interconnected nodes that separated key genes that are functionally related on different communities, possibly maximizing redundancy and GRN robustness by compartmentalization of important functions. Core conserved functions showed expression synchronicity, distinct GRN features and significantly less genetic diversity, consistent with evolutionary constraints imposed in key elements of biological systems. This reduced genetic diversity also had a positive correlation with the importance of the gene in our estimated GRN, supporting a relationship between phylogenetic data of baculovirus genes and network features inferred from expression data. We also observed that gene arrangement in overlapping transcripts was conserved among related baculoviruses, suggesting a principle of genome organization. Conclusions Albeit with a reduced number of nodes (149), the AgMNPV GRN had a topology and key characteristics similar to those observed in complex cellular organisms, which indicates

  12. Gap Gene Regulatory Dynamics Evolve along a Genotype Network

    PubMed Central

    Crombach, Anton; Wotton, Karl R.; Jiménez-Guri, Eva; Jaeger, Johannes

    2016-01-01

    Developmental gene networks implement the dynamic regulatory mechanisms that pattern and shape the organism. Over evolutionary time, the wiring of these networks changes, yet the patterning outcome is often preserved, a phenomenon known as “system drift.” System drift is illustrated by the gap gene network—involved in segmental patterning—in dipteran insects. In the classic model organism Drosophila melanogaster and the nonmodel scuttle fly Megaselia abdita, early activation and placement of gap gene expression domains show significant quantitative differences, yet the final patterning output of the system is essentially identical in both species. In this detailed modeling analysis of system drift, we use gene circuits which are fit to quantitative gap gene expression data in M. abdita and compare them with an equivalent set of models from D. melanogaster. The results of this comparative analysis show precisely how compensatory regulatory mechanisms achieve equivalent final patterns in both species. We discuss the larger implications of the work in terms of “genotype networks” and the ways in which the structure of regulatory networks can influence patterns of evolutionary change (evolvability). PMID:26796549

  13. Identification of cancer-related genes and motifs in the human gene regulatory network.

    PubMed

    Carson, Matthew B; Gu, Jianlei; Yu, Guangjun; Lu, Hui

    2015-08-01

    The authors investigated the regulatory network motifs and corresponding motif positions of cancer-related genes. First, they mapped disease-related genes to a transcription factor regulatory network. Next, they calculated statistically significant motifs and subsequently identified positions within these motifs that were enriched in cancer-related genes. Potential mechanisms of these motifs and positions are discussed. These results could be used to identify other disease- and cancer-related genes and could also suggest mechanisms for how these genes relate to co-occurring diseases.

  14. Genomic imprinting-an epigenetic gene-regulatory model.

    PubMed

    Koerner, Martha V; Barlow, Denise P

    2010-04-01

    Epigenetic mechanisms (Box 1) are considered to play major gene-regulatory roles in development, differentiation and disease. However, the relative importance of epigenetics in defining the mammalian transcriptome in normal and disease states is unknown. The mammalian genome contains only a few model systems where epigenetic gene regulation has been shown to play a major role in transcriptional control. These model systems are important not only to investigate the biological function of known epigenetic modifications but also to identify new and unexpected epigenetic mechanisms in the mammalian genome. Here we review recent progress in understanding how epigenetic mechanisms control imprinted gene expression.

  15. Effects of Four Different Regulatory Mechanisms on the Dynamics of Gene Regulatory Cascades

    PubMed Central

    Hansen, Sabine; Krishna, Sandeep; Semsey, Szabolcs; Lo Svenningsen, Sine

    2015-01-01

    Gene regulatory cascades (GRCs) are common motifs in cellular molecular networks. A given logical function in these cascades, such as the repression of the activity of a transcription factor, can be implemented by a number of different regulatory mechanisms. The potential consequences for the dynamic performance of the GRC of choosing one mechanism over another have not been analysed systematically. Here, we report the construction of a synthetic GRC in Escherichia coli, which allows us for the first time to directly compare and contrast the dynamics of four different regulatory mechanisms, affecting the transcription, translation, stability, or activity of a transcriptional repressor. We developed a biologically motivated mathematical model which is sufficient to reproduce the response dynamics determined by experimental measurements. Using the model, we explored the potential response dynamics that the constructed GRC can perform. We conclude that dynamic differences between regulatory mechanisms at an individual step in a GRC are often concealed in the overall performance of the GRC, and suggest that the presence of a given regulatory mechanism in a certain network environment does not necessarily mean that it represents a single optimal evolutionary solution. PMID:26184971

  16. Characterization of nif regulatory genes in Rhodopseudomonas capsulata using lac gene fusions.

    PubMed

    Kranz, R G; Haselkorn, R

    1985-01-01

    Translational fusions of the Escherichia coli lacZYA operon to Rhodopseudomonas capsulata nif genes were obtained by using mini-MudII1734 [Castilho et al., J. Bacteriol. 158 (1984) 488-495] inserts into cloned fragments of R. capsulata DNA. A lac fusion to the nifH gene, which encodes dinitrogenase reductase, was used to classify Nif- mutations occurring in regulatory genes. Nine mutations were unable to activate nifHDK transcription. The nine mutations define four nif regulatory genes. Three of these genes are located on the same R. capsulata 8.4-kb EcoRI fragment. Each is transcribed independently. One of these (complementing mutant J61) is partially homologous with the ntrC gene of Escherichia coli, based on Southern hybridization. The fourth nif regulatory gene (complementing mutants LJ1, AH1 and AH3) is unlinked to the others. Lac fusions to all four regulatory genes were constructed. Each regulatory gene is weakly expressed compared to derepressed nifH and partially repressed in the presence of ammonia.

  17. Gene Regulatory Network Inference of Immunoresponsive Gene 1 (IRG1) Identifies Interferon Regulatory Factor 1 (IRF1) as Its Transcriptional Regulator in Mammalian Macrophages.

    PubMed

    Tallam, Aravind; Perumal, Thaneer M; Antony, Paul M; Jäger, Christian; Fritz, Joëlle V; Vallar, Laurent; Balling, Rudi; Del Sol, Antonio; Michelucci, Alessandro

    2016-01-01

    Immunoresponsive gene 1 (IRG1) is one of the highest induced genes in macrophages under pro-inflammatory conditions. Its function has been recently described: it codes for immune-responsive gene 1 protein/cis-aconitic acid decarboxylase (IRG1/CAD), an enzyme catalysing the production of itaconic acid from cis-aconitic acid, a tricarboxylic acid (TCA) cycle intermediate. Itaconic acid possesses specific antimicrobial properties inhibiting isocitrate lyase, the first enzyme of the glyoxylate shunt, an anaplerotic pathway that bypasses the TCA cycle and enables bacteria to survive on limited carbon conditions. To elucidate the mechanisms underlying itaconic acid production through IRG1 induction in macrophages, we examined the transcriptional regulation of IRG1. To this end, we studied IRG1 expression in human immune cells under different inflammatory stimuli, such as TNFα and IFNγ, in addition to lipopolysaccharides. Under these conditions, as previously shown in mouse macrophages, IRG1/CAD accumulates in mitochondria. Furthermore, using literature information and transcription factor prediction models, we re-constructed raw gene regulatory networks (GRNs) for IRG1 in mouse and human macrophages. We further implemented a contextualization algorithm that relies on genome-wide gene expression data to infer putative cell type-specific gene regulatory interactions in mouse and human macrophages, which allowed us to predict potential transcriptional regulators of IRG1. Among the computationally identified regulators, siRNA-mediated gene silencing of interferon regulatory factor 1 (IRF1) in macrophages significantly decreased the expression of IRG1/CAD at the gene and protein level, which correlated with a reduced production of itaconic acid. Using a synergistic approach of both computational and experimental methods, we here shed more light on the transcriptional machinery of IRG1 expression and could pave the way to therapeutic approaches targeting itaconic acid levels.

  18. Gene Regulatory Network Inference of Immunoresponsive Gene 1 (IRG1) Identifies Interferon Regulatory Factor 1 (IRF1) as Its Transcriptional Regulator in Mammalian Macrophages

    PubMed Central

    Tallam, Aravind; Perumal, Thaneer M.; Antony, Paul M.; Jäger, Christian; Fritz, Joëlle V.; Vallar, Laurent; Balling, Rudi; del Sol, Antonio; Michelucci, Alessandro

    2016-01-01

    Immunoresponsive gene 1 (IRG1) is one of the highest induced genes in macrophages under pro-inflammatory conditions. Its function has been recently described: it codes for immune-responsive gene 1 protein/cis-aconitic acid decarboxylase (IRG1/CAD), an enzyme catalysing the production of itaconic acid from cis-aconitic acid, a tricarboxylic acid (TCA) cycle intermediate. Itaconic acid possesses specific antimicrobial properties inhibiting isocitrate lyase, the first enzyme of the glyoxylate shunt, an anaplerotic pathway that bypasses the TCA cycle and enables bacteria to survive on limited carbon conditions. To elucidate the mechanisms underlying itaconic acid production through IRG1 induction in macrophages, we examined the transcriptional regulation of IRG1. To this end, we studied IRG1 expression in human immune cells under different inflammatory stimuli, such as TNFα and IFNγ, in addition to lipopolysaccharides. Under these conditions, as previously shown in mouse macrophages, IRG1/CAD accumulates in mitochondria. Furthermore, using literature information and transcription factor prediction models, we re-constructed raw gene regulatory networks (GRNs) for IRG1 in mouse and human macrophages. We further implemented a contextualization algorithm that relies on genome-wide gene expression data to infer putative cell type-specific gene regulatory interactions in mouse and human macrophages, which allowed us to predict potential transcriptional regulators of IRG1. Among the computationally identified regulators, siRNA-mediated gene silencing of interferon regulatory factor 1 (IRF1) in macrophages significantly decreased the expression of IRG1/CAD at the gene and protein level, which correlated with a reduced production of itaconic acid. Using a synergistic approach of both computational and experimental methods, we here shed more light on the transcriptional machinery of IRG1 expression and could pave the way to therapeutic approaches targeting itaconic acid levels

  19. Dynamic Gene Regulatory Networks of Human Myeloid Differentiation.

    PubMed

    Ramirez, Ricardo N; El-Ali, Nicole C; Mager, Mikayla Anne; Wyman, Dana; Conesa, Ana; Mortazavi, Ali

    2017-03-27

    The reconstruction of gene regulatory networks underlying cell differentiation from high-throughput gene expression and chromatin data remains a challenge. Here, we derive dynamic gene regulatory networks for human myeloid differentiation using a 5-day time series of RNA-seq and ATAC-seq data. We profile HL-60 promyelocytes differentiating into macrophages, neutrophils, monocytes, and monocyte-derived macrophages. We find a rapid response in the expression of key transcription factors and lineage markers that only regulate a subset of their targets at a given time, which is followed by chromatin accessibility changes that occur later along with further gene expression changes. We observe differences between promyelocyte- and monocyte-derived macrophages at both the transcriptional and chromatin landscape level, despite using the same differentiation stimulus, which suggest that the path taken by cells in the differentiation landscape defines their end cell state. More generally, our approach of combining neighboring time points and replicates to achieve greater sequencing depth can efficiently infer footprint-based regulatory networks from long series data.

  20. The regulatory compliance plan for the Minimum Additive Waste Stabilization (MAWS) Program

    SciTech Connect

    Akgunduz, N.K.; Gimpel, R.F.; Finger, S.M.

    1993-01-27

    The Fernald Environmental Management Project (FEMP) has initiated the Minimum Additive Waste Stabilization (MAWS) Program to demonstrate and evaluate integrated treatment of the FEMP site`s Operable Unit 1 contaminated soils and sludges. The demonstration will require on-site operation of an integrated treatment system consisting of soil washing, water treatment by ion exchange, and vitrification of all contaminated solid wastes at a rate of 300 kg per day. Compliance with all relevant environmental regulations is a major priority of this program. Relevant regulatory requirements come under the jurisdiction of the US Environmental Protection Agency (US EPA), the Ohio Environmental Protection Agency (Ohio EPA), and the Department of Energy (DOE). The plethora of potentially applicable regulations were reviewed and an efficient regulatory compliance strategy developed. This strategy was documented in the MAWS Regulatory Compliance Plan which was presented to the regulatory agencies as a reasonable working plan. The FEMP has found the development of a comprehensive, organized regulatory plan to be critical to the successful implementation of integrated demonstration projects such as the MAWS Program. This paper discusses the approaches used in the MAWS Regulatory Compliance Plan and highlights which could prove useful for others that want to approach the DOE and/or EPA with technology demonstrations.

  1. Inference of the Xenopus tropicalis embryonic regulatory network and spatial gene expression patterns

    PubMed Central

    2014-01-01

    Background During embryogenesis, signaling molecules produced by one cell population direct gene regulatory changes in neighboring cells and influence their developmental fates and spatial organization. One of the earliest events in the development of the vertebrate embryo is the establishment of three germ layers, consisting of the ectoderm, mesoderm and endoderm. Attempts to measure gene expression in vivo in different germ layers and cell types are typically complicated by the heterogeneity of cell types within biological samples (i.e., embryos), as the responses of individual cell types are intermingled into an aggregate observation of heterogeneous cell types. Here, we propose a novel method to elucidate gene regulatory circuits from these aggregate measurements in embryos of the frog Xenopus tropicalis using gene network inference algorithms and then test the ability of the inferred networks to predict spatial gene expression patterns. Results We use two inference models with different underlying assumptions that incorporate existing network information, an ODE model for steady-state data and a Markov model for time series data, and contrast the performance of the two models. We apply our method to both control and knockdown embryos at multiple time points to reconstruct the core mesoderm and endoderm regulatory circuits. Those inferred networks are then used in combination with known dorsal-ventral spatial expression patterns of a subset of genes to predict spatial expression patterns for other genes. Both models are able to predict spatial expression patterns for some of the core mesoderm and endoderm genes, but interestingly of different gene subsets, suggesting that neither model is sufficient to recapitulate all of the spatial patterns, yet they are complementary for the patterns that they do capture. Conclusion The presented methodology of gene network inference combined with spatial pattern prediction provides an additional layer of validation to

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

    PubMed Central

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

    2014-01-01

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

  3. Enhancers and chromatin structures: regulatory hubs in gene expression and diseases.

    PubMed

    Hu, Zhenhua; Tee, Wee Wei

    2017-03-28

    Gene expression requires successful communication between enhancer and promoter regions, whose activities are regulated by a variety of factors and associated with distinct chromatin structures; in addition, functionally related genes and their regulatory repertoire tend to be arranged in the same sub-chromosomal regulatory domains. In this review, we discuss the importance of enhancers, especially clusters of enhancers (such as super-enhancers), as key regulatory hubs to integrate environmental cues and encode spatiotemporal instructions for genome expression, which are critical for a variety of biological processes governing mammalian development. Furthermore, we emphasize that the enhancer-promoter interaction landscape provides a critical context to understand the etiologies and mechanisms behind numerous complex human diseases, and provides new avenues for effective transcriptional-based interventions.

  4. Beyond antioxidant genes in the ancient NRF2 regulatory network

    PubMed Central

    Lacher, Sarah E.; Lee, Joslynn S.; Wang, Xuting; Campbell, Michelle R.; Bell, Douglas A.; Slattery, Matthew

    2016-01-01

    NRF2, a basic leucine zipper transcription factor encoded by the gene NFE2L2, is a master regulator of the transcriptional response to oxidative stress. NRF2 is structurally and functionally conserved from insects to humans, and it heterodimerizes with the small MAF transcription factors to bind a consensus DNA sequence (the antioxidant response element, or ARE) and regulate gene expression. We have used genome-wide chromatin immunoprecipitation (ChIP-seq) and gene expression data to identify direct NRF2 target genes in Drosophila and humans. These data have allowed us to construct the deeply conserved ancient NRF2 regulatory network – target genes that are conserved from Drosophila to human. The ancient network consists of canonical antioxidant genes, as well as genes related to proteasomal pathways, metabolism, and a number of less expected genes. We have also used enhancer reporter assays and electrophoretic mobility shift assays to confirm NRF2-mediated regulation of ARE (antioxidant response element) activity at a number of these novel target genes. Interestingly, the ancient network also highlights a prominent negative feedback loop; this, combined with the finding that and NRF2-mediated regulatory output is tightly linked to the quality of the ARE it is targeting, suggests that precise regulation of nuclear NRF2 concentration is necessary to achieve proper quantitative regulation of distinct gene sets. Together, these findings highlight the importance of balance in the NRF2-ARE pathway, and indicate that NRF2-mediated regulation of xenobiotic metabolism, glucose metabolism, and proteostasis have been central to this pathway since its inception. PMID:26163000

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

    PubMed

    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.

  6. Analyzing stationary states of gene regulatory network using petri nets.

    PubMed

    Gambin, Anna; Lasota, Sławomir; Rutkowski, Michał

    2006-01-01

    We introduce and formally define the notion of a stationary state for Petri nets. We also propose a fully automatic method for finding such states. The procedure makes use of the Presburger arithmetic to describe all the stationary states. Finally we apply this novel approach to find stationary states of a gene regulatory network describing the flower morphogenesis of A. thaliana. This shows that the proposed method can be successfully applied in the study of biological systems.

  7. Analyzing stationary States of gene regulatory network using petri nets.

    PubMed

    Gambin, Anna; Lasota, Sławomir; Rutkowski, Michał

    2011-01-01

    We introduce and formally define the notion of a stationary state for Petri nets. We also propose a fully automatic method for finding such states. The procedure makes use of the Presburger arithmetic to describe all the stationary states. Finally we apply this novel approach to find stationary states of a gene regulatory network describing the flower morphogenesis of A. thaliana. This shows that the proposed method can be successfully applied in the study of biological systems.

  8. Phase transitions in the evolution of gene regulatory networks

    NASA Astrophysics Data System (ADS)

    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.

  9. Functional studies of regulatory genes in the sea urchin embryo.

    PubMed

    Cavalieri, Vincenzo; Di Bernardo, Maria; Spinelli, Giovanni

    2009-01-01

    Sea urchin embryos are characterized by an extremely simple mode of development, rapid cleavage, high transparency, and well-defined cell lineage. Although they are not suitable for genetic studies, other approaches are successfully used to unravel mechanisms and molecules involved in cell fate specification and morphogenesis. Microinjection is the elective method to study gene function in sea urchin embryos. It is used to deliver precise amounts of DNA, RNA, oligonucleotides, peptides, or antibodies into the eggs or even into blastomeres. Here we describe microinjection as it is currently applied in our laboratory and show how it has been used in gene perturbation analyses and dissection of cis-regulatory DNA elements.

  10. Roles of lignin biosynthesis and regulatory genes in plant development

    PubMed Central

    Yoon, Jinmi; Choi, Heebak

    2015-01-01

    Abstract Lignin is an important factor affecting agricultural traits, biofuel production, and the pulping industry. Most lignin biosynthesis genes and their regulatory genes are expressed mainly in the vascular bundles of stems and leaves, preferentially in tissues undergoing lignification. Other genes are poorly expressed during normal stages of development, but are strongly induced by abiotic or biotic stresses. Some are expressed in non‐lignifying tissues such as the shoot apical meristem. Alterations in lignin levels affect plant development. Suppression of lignin biosynthesis genes causes abnormal phenotypes such as collapsed xylem, bending stems, and growth retardation. The loss of expression by genes that function early in the lignin biosynthesis pathway results in more severe developmental phenotypes when compared with plants that have mutations in later genes. Defective lignin deposition is also associated with phenotypes of seed shattering or brittle culm. MYB and NAC transcriptional factors function as switches, and some homeobox proteins negatively control lignin biosynthesis genes. Ectopic deposition caused by overexpression of lignin biosynthesis genes or master switch genes induces curly leaf formation and dwarfism. PMID:26297385

  11. Roles of lignin biosynthesis and regulatory genes in plant development.

    PubMed

    Yoon, Jinmi; Choi, Heebak; An, Gynheung

    2015-11-01

    Lignin is an important factor affecting agricultural traits, biofuel production, and the pulping industry. Most lignin biosynthesis genes and their regulatory genes are expressed mainly in the vascular bundles of stems and leaves, preferentially in tissues undergoing lignification. Other genes are poorly expressed during normal stages of development, but are strongly induced by abiotic or biotic stresses. Some are expressed in non-lignifying tissues such as the shoot apical meristem. Alterations in lignin levels affect plant development. Suppression of lignin biosynthesis genes causes abnormal phenotypes such as collapsed xylem, bending stems, and growth retardation. The loss of expression by genes that function early in the lignin biosynthesis pathway results in more severe developmental phenotypes when compared with plants that have mutations in later genes. Defective lignin deposition is also associated with phenotypes of seed shattering or brittle culm. MYB and NAC transcriptional factors function as switches, and some homeobox proteins negatively control lignin biosynthesis genes. Ectopic deposition caused by overexpression of lignin biosynthesis genes or master switch genes induces curly leaf formation and dwarfism.

  12. Efficiently finding regulatory elements using correlation with gene expression.

    PubMed

    Bannai, Hideo; Inenaga, Shunsuke; Shinohara, Ayumi; Takeda, Masayuki; Miyano, Satoru

    2004-06-01

    We present an efficient algorithm for detecting putative regulatory elements in the upstream DNA sequences of genes, using gene expression information obtained from microarray experiments. Based on a generalized suffix tree, our algorithm looks for motif patterns whose appearance in the upstream region is most correlated with the expression levels of the genes. We are able to find the optimal pattern, in time linear in the total length of the upstream sequences. We implement and apply our algorithm to publicly available microarray gene expression data, and show that our method is able to discover biologically significant motifs, including various motifs which have been reported previously using the same data set. We further discuss applications for which the efficiency of the method is essential, as well as possible extensions to our algorithm.

  13. An Arabidopsis gene regulatory network for secondary cell wall synthesis

    SciTech Connect

    Taylor-Teeples, M.; Lin, L.; de Lucas, M.; Turco, G.; Toal, T. W.; Gaudinier, A.; Young, N. F.; Trabucco, G. M.; Veling, M. T.; Lamothe, R.; Handakumbura, P. P.; Xiong, G.; Wang, C.; Corwin, J.; Tsoukalas, A.; Zhang, L.; Ware, D.; Pauly, M.; Kliebenstein, D. J.; Dehesh, K.; Tagkopoulos, I.; Breton, G.; Pruneda-Paz, J. L.; Ahnert, S. E.; Kay, S. A.; Hazen, S. P.; Brady, S. M.

    2014-12-24

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

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

    PubMed

    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

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

    PubMed Central

    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. PMID:28270833

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

    PubMed

    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.

  17. Fused Regression for Multi-source Gene Regulatory Network Inference

    PubMed Central

    Lam, Kari Y.; Westrick, Zachary M.; Müller, Christian L.; Christiaen, Lionel; Bonneau, Richard

    2016-01-01

    Understanding gene regulatory networks is critical to understanding cellular differentiation and response to external stimuli. Methods for global network inference have been developed and applied to a variety of species. Most approaches consider the problem of network inference independently in each species, despite evidence that gene regulation can be conserved even in distantly related species. Further, network inference is often confined to single data-types (single platforms) and single cell types. We introduce a method for multi-source network inference that allows simultaneous estimation of gene regulatory networks in multiple species or biological processes through the introduction of priors based on known gene relationships such as orthology incorporated using fused regression. This approach improves network inference performance even when orthology mapping and conservation are incomplete. We refine this method by presenting an algorithm that extracts the true conserved subnetwork from a larger set of potentially conserved interactions and demonstrate the utility of our method in cross species network inference. Last, we demonstrate our method’s utility in learning from data collected on different experimental platforms. PMID:27923054

  18. Regulatory myosin light-chain genes of Caenorhabditis elegans.

    PubMed Central

    Cummins, C; Anderson, P

    1988-01-01

    We have cloned and analyzed the Caenorhabditis elegans regulatory myosin light-chain genes. C. elegans contains two such genes, which we have designated mlc-1 and mlc-2. The two genes are separated by 2.6 kilobases and are divergently transcribed. We determined the complete nucleotide sequences of both mlc-1 and mlc-2. A single, conservative amino acid substitution distinguishes the sequences of the two proteins. The C. elegans proteins are strongly homologous to regulatory myosin light chains of Drosophila melanogaster and vertebrates and weakly homologous to a superfamily of eucaryotic calcium-binding proteins. Both mlc-1 and mlc-2 encode abundant mRNAs. We mapped the 5' termini of these transcripts by using primer extension sequencing of mRNA templates. mlc-1 mRNAs initiate within conserved hexanucleotides at two different positions, located at -28 and -38 relative to the start of translation. The 5' terminus of mlc-2 mRNA is not encoded in the 4.8-kilobase genomic region upstream of mlc-2. Rather, mlc-2 mRNA contains at its 5' end a short, untranslated leader sequence that is identical to the trans-spliced leader sequence of three C. elegans actin genes. Images PMID:3244358

  19. Regulatory aspects for translating gene therapy research into the clinic.

    PubMed

    Laurencot, Carolyn M; Ruppel, Sheryl

    2009-01-01

    Gene therapy products are highly regulated, therefore moving a promising candidate from the laboratory into the clinic can present unique challenges. Success can only be achieved by proper planning and communication within the clinical development team, as well as consultation with the regulatory scientists who will eventually review the clinical plan. Regulators should not be considered as obstacles but rather as collaborators whose advice can significantly expedite the product development. Sound scientific data is required and reviewed by the regulatory agencies to determine whether the potential benefit to the patient population outweighs the risk. Therefore, compliance with Good Manufacturing Practice (GMP) and Good Laboratory Practice (GLP) principles to ensure quality, safety, purity, and potency of the product, and to establish "proof of concept" for efficacy, and for safety information, respectively, is essential. The design and conduct of the clinical trial must adhere to Good Clinical Practice (GCP) principals. The clinical protocol should contain adequate rationale, supported by nonclinical data, to justify the starting dose and regimen, and adequate safety monitoring based on the patient population and the anticipated toxicities. Proper review and approval of gene therapy clinical studies by numerous committees, and regulatory agencies before and throughout the study allows for ongoing risk assessment of these novel and innovative products. The ethical conduct of clinical trials must be a priority for all clinical investigators and sponsors. As history has shown us, only a few fatal mistakes can dramatically alter the regulation of investigational products for all individuals involved in gene therapy clinical research, and further delay the advancement of gene therapy to licensed medicinal products.

  20. The gene regulatory network for breast cancer: integrated regulatory landscape of cancer hallmarks.

    PubMed

    Emmert-Streib, Frank; de Matos Simoes, Ricardo; Mullan, Paul; Haibe-Kains, Benjamin; Dehmer, Matthias

    2014-01-01

    In this study, we infer the breast cancer gene regulatory network from gene expression data. This network is obtained from the application of the BC3Net inference algorithm to a large-scale gene expression data set consisting of 351 patient samples. In order to elucidate the functional relevance of the inferred network, we are performing a Gene Ontology (GO) analysis for its structural components. Our analysis reveals that most significant GO-terms we find for the breast cancer network represent functional modules of biological processes that are described by known cancer hallmarks, including translation, immune response, cell cycle, organelle fission, mitosis, cell adhesion, RNA processing, RNA splicing and response to wounding. Furthermore, by using a curated list of census cancer genes, we find an enrichment in these functional modules. Finally, we study cooperative effects of chromosomes based on information of interacting genes in the beast cancer network. We find that chromosome 21 is most coactive with other chromosomes. To our knowledge this is the first study investigating the genome-scale breast cancer network.

  1. Autonomous Boolean modelling of developmental gene regulatory networks

    PubMed Central

    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

  2. Optimal finite horizon control in gene regulatory networks

    NASA Astrophysics Data System (ADS)

    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.

  3. The structure of the human peripherin gene (PRPH) and identification of potential regulatory elements

    SciTech Connect

    Foley, J.; Ley, C.A.; Parysek, L.M.

    1994-07-15

    The authors determined the complete nucleotide sequence of the coding region of the human peripherin gene (PRPH), as well as 742 bp 5{prime} to the cap site and 584 bp 3{prime} to the stop codon, and compared its structure and sequence to the rat and mouse genes. The overall structure of 9 exons separated by 8 introns is conserved among these three mammalian species. The nucleotide sequences of the human peripherin gene exons were 90% identical to the rat gene sequences, and the predicted human peripherin protein differed from rat peripherin at only 18 of 475 amino acid residues. Comparison of the 5{prime} flanking regions of the human peripherin gene and rodent genes revealed extensive areas of high homology. Additional conserved segments were found in introns 1 and 2. Within the 5{prime} region, potential regulatory sequences, including a nerve growth factor negative regulatory element, a Hox protein binding site, and a heat shock element, were identified in all peripherin genes. The positional conservation of each element suggests that they may be important in the tissue-specific, developmental-specific, and injury-specific expression of the peripherin gene. 24 refs., 2 figs., 1 tab.

  4. Regulatory network analysis of genes and microRNAs in human hepatoblastoma

    PubMed Central

    He, Jimin; Guo, Xiaoxin; Sun, Linlin; Wang, Ning; Bao, Jiwei

    2016-01-01

    Hepatoblastoma (HB) is a common type of primary tumor in children. Previous studies have examined the expression of genes, including transcription factors (TFs), target genes, host genes and microRNAs (miRNAs or miRs) associated with HB. However, the regulatory pathways of miRNAs and genes remain unclear. In the present study, a novel perspective is proposed, which focuses on HB and the associated regulatory pathways, to construct three networks at various levels, including a differentially expressed network, an associated network and a global network. Genes and miRNAs are considered as key factors in the network. In the three networks, the associations between each pair of factors, including TFs that regulate miRNAs, miRNAs that interact with target genes and miRNAs that are located at host genes, were analyzed. The differentially expressed network is considered to be the most crucial of the three networks. All factors in the differentially expressed network were mutated or differentially expressed, which indicated that the majority of the factors were cancerogenic factors that may lead to HB. In addition, the network contained numerous abnormal linkages that may trigger HB. If the expression of each factor was corrected to a normal level, HB may be successfully treated. The associated network included more HB-associated genes and miRNAs, and was useful for analyzing the pathogenesis of HB. By analyzing these close associations, the first and the last factor of the regulatory pathways were revealed to have important roles in HB. For example, v-myc avian myelocytomatosis viral oncogene neuroblastoma derived homolog (MYCN) was observed to regulate Homo sapiens (hsa)-miR-221, hsa-miR-18a and hsa-miR-17-5p, but no miRNAs targeted MYCN. In conclusion, the pathways and mechanisms underlying HB were expounded in the present study, which proposed a fundamental hypothesis for additional studies. PMID:27895778

  5. Reverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression Data.

    PubMed

    Liu, Zhi-Ping

    2015-02-01

    Transcriptional regulation plays vital roles in many fundamental biological processes. Reverse engineering of genome-wide regulatory networks from high-throughput transcriptomic data provides a promising way to characterize the global scenario of regulatory relationships between regulators and their targets. In this review, we summarize and categorize the main frameworks and methods currently available for inferring transcriptional regulatory networks from microarray gene expression profiling data. We overview each of strategies and introduce representative methods respectively. Their assumptions, advantages, shortcomings, and possible improvements and extensions are also clarified and commented.

  6. Reverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression Data

    PubMed Central

    Liu, Zhi-Ping

    2015-01-01

    Transcriptional regulation plays vital roles in many fundamental biological processes. Reverse engineering of genome-wide regulatory networks from high-throughput transcriptomic data provides a promising way to characterize the global scenario of regulatory relationships between regulators and their targets. In this review, we summarize and categorize the main frameworks and methods currently available for inferring transcriptional regulatory networks from microarray gene expression profiling data. We overview each of strategies and introduce representative methods respectively. Their assumptions, advantages, shortcomings, and possible improvements and extensions are also clarified and commented. PMID:25937810

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

    PubMed Central

    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. PMID:25429295

  8. ChIP-Array 2: integrating multiple omics data to construct gene regulatory networks

    PubMed Central

    Wang, Panwen; Qin, Jing; Qin, Yiming; Zhu, Yun; Wang, Lily Yan; Li, Mulin Jun; Zhang, Michael Q.; Wang, Junwen

    2015-01-01

    Transcription factors (TFs) play an important role in gene regulation. The interconnections among TFs, chromatin interactions, epigenetic marks and cis-regulatory elements form a complex gene transcription apparatus. Our previous work, ChIP-Array, combined TF binding and transcriptome data to construct gene regulatory networks (GRNs). Here we present an enhanced version, ChIP-Array 2, to integrate additional types of omics data including long-range chromatin interaction, open chromatin region and histone modification data to dissect more comprehensive GRNs involving diverse regulatory components. Moreover, we substantially extended our motif database for human, mouse, rat, fruit fly, worm, yeast and Arabidopsis, and curated large amount of omics data for users to select as input or backend support. With ChIP-Array 2, we compiled a library containing regulatory networks of 18 TFs/chromatin modifiers in mouse embryonic stem cell (mESC). The web server and the mESC library are publicly free and accessible athttp://jjwanglab.org/chip-array. PMID:25916854

  9. A Provisional Gene Regulatory Atlas for Mouse Heart Development

    PubMed Central

    Chen, Hailin; VanBuren, Vincent

    2014-01-01

    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. PMID:24421884

  10. Innovation and robustness in complex regulatory gene networks

    PubMed Central

    Ciliberti, S.; Martin, O. C.; Wagner, A.

    2007-01-01

    The history of life involves countless evolutionary innovations, a steady stream of ingenuity that has been flowing for more than 3 billion years. Very little is known about the principles of biological organization that allow such innovation. Here, we examine these principles for evolutionary innovation in gene expression patterns. To this end, we study a model for the transcriptional regulation networks that are at the heart of embryonic development. A genotype corresponds to a regulatory network of a given topology, and a phenotype corresponds to a steady-state gene expression pattern. Networks with the same phenotype form a connected graph in genotype space, where two networks are immediate neighbors if they differ by one regulatory interaction. We show that an evolutionary search on this graph can reach genotypes that are as different from each other as if they were chosen at random in genotype space, allowing evolutionary access to different kinds of innovation while staying close to a viable phenotype. Thus, although robustness to mutations may hinder innovation in the short term, we conclude that long-term innovation in gene expression patterns can only emerge in the presence of the robustness caused by connected genotype graphs. PMID:17690244

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

    PubMed Central

    Tian, Dechao; Gu, Quanquan; Ma, Jian

    2016-01-01

    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. PMID:27378774

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

    PubMed

    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.

  13. Engineering nucleases for gene targeting: safety and regulatory considerations.

    PubMed

    Pauwels, Katia; Podevin, Nancy; Breyer, Didier; Carroll, Dana; Herman, Philippe

    2014-01-25

    Nuclease-based gene targeting (NBGT) represents a significant breakthrough in targeted genome editing since it is applicable from single-celled protozoa to human, including several species of economic importance. Along with the fast progress in NBGT and the increasing availability of customized nucleases, more data are available about off-target effects associated with the use of this approach. We discuss how NBGT may offer a new perspective for genetic modification, we address some aspects crucial for a safety improvement of the corresponding techniques and we also briefly relate the use of NBGT applications and products to the regulatory oversight.

  14. Genome-Wide Identification of Regulatory Elements and Reconstruction of Gene Regulatory Networks of the Green Alga Chlamydomonas reinhardtii under Carbon Deprivation

    PubMed Central

    Vischi Winck, Flavia; Arvidsson, Samuel; Riaño-Pachón, Diego Mauricio; Hempel, Sabrina; Koseska, Aneta; Nikoloski, Zoran; Urbina Gomez, David Alejandro; Rupprecht, Jens; Mueller-Roeber, Bernd

    2013-01-01

    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-CO2 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. Our work can

  15. Gene regulatory networks governing haematopoietic stem cell development and identity.

    PubMed

    Pimanda, John E; Göttgens, Berthold

    2010-01-01

    Development can be viewed as a dynamic progression through regulatory states which characterise the various cell types within a given differentiation cascade. To understand the progression of regulatory states that define the origin and subsequent development of haematopoietic stem cells, the first imperative is to understand the ontogeny of haematopoiesis. We are fortunate that the ontogeny of blood development is one of the best characterized mammalian developmental systems. However, the field is still in its infancy with regard to the reconstruction of gene regulatory networks and their interactions with cell signalling cascades that drive a mesodermal progenitor to adopt the identity of a haematopoietic stem cell and beyond. Nevertheless, a framework to dissect these networks and comprehend the logic of its circuitry does exist and although they may not as yet be available, a sense for the tools that will be required to achieve this aim is also emerging. In this review we cover the fundamentals of network architecture, methods used to reconstruct networks, current knowledge of haematopoietic and related transcriptional networks, current challenges and future outlook.

  16. Selection for distinct gene expression properties favours the evolution of mutational robustness in gene regulatory networks.

    PubMed

    Espinosa-Soto, C

    2016-11-01

    Mutational robustness is a genotype's tendency to keep a phenotypic trait with little and few changes in the face of mutations. Mutational robustness is both ubiquitous and evolutionarily important as it affects in different ways the probability that new phenotypic variation arises. Understanding the origins of robustness is specially relevant for systems of development that are phylogenetically widespread and that construct phenotypic traits with a strong impact on fitness. Gene regulatory networks are examples of this class of systems. They comprise sets of genes that, through cross-regulation, build the gene activity patterns that define cellular responses, different tissues or distinct cell types. Several empirical observations, such as a greater robustness of wild-type phenotypes, suggest that stabilizing selection underlies the evolution of mutational robustness. However, the role of selection in the evolution of robustness is still under debate. Computer simulations of the dynamics and evolution of gene regulatory networks have shown that selection for any gene activity pattern that is steady and self-sustaining is sufficient to promote the evolution of mutational robustness. Here, I generalize this scenario using a computational model to show that selection for different aspects of a gene activity phenotype increases mutational robustness. Mutational robustness evolves even when selection favours properties that conflict with the stationarity of a gene activity pattern. The results that I present support an important role for stabilizing selection in the evolution of robustness in gene regulatory networks.

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

    PubMed

    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.

  18. Diverse Gene Expression in Human Regulatory T Cell Subsets Uncovers Connection between Regulatory T Cell Genes and Suppressive Function.

    PubMed

    Hua, Jing; Davis, Scott P; Hill, Jonathan A; Yamagata, Tetsuya

    2015-10-15

    Regulatory T (Treg) cells have a critical role in the control of immunity, and their diverse subpopulations may allow adaptation to different types of immune responses. In this study, we analyzed human Treg cell subpopulations in the peripheral blood by performing genome-wide expression profiling of 40 Treg cell subsets from healthy donors. We found that the human peripheral blood Treg cell population is comprised of five major genomic subgroups, represented by 16 tractable subsets with a particular cell surface phenotype. These subsets possess a range of suppressive function and cytokine secretion and can exert a genomic footprint on target effector T (Teff) cells. Correlation analysis of variability in gene expression in the subsets identified several cell surface molecules associated with Treg suppressive function, and pharmacological interrogation revealed a set of genes having causative effect. The five genomic subgroups of Treg cells imposed a preserved pattern of gene expression on Teff cells, with a varying degree of genes being suppressed or induced. Notably, there was a cluster of genes induced by Treg cells that bolstered an autoinhibitory effect in Teff cells, and this induction appears to be governed by a different set of genes than ones involved in counteracting Teff activation. Our work shows an example of exploiting the diversity within human Treg cell subpopulations to dissect Treg cell biology.

  19. Reverse engineering of gene regulatory networks: a comparative study.

    PubMed

    Hache, Hendrik; Lehrach, Hans; Herwig, Ralf

    2009-01-01

    Reverse engineering of gene regulatory networks has been an intensively studied topic in bioinformatics since it constitutes an intermediate step from explorative to causative gene expression analysis. Many methods have been proposed through recent years leading to a wide range of mathematical approaches. In practice, different mathematical approaches will generate different resulting network structures, thus, it is very important for users to assess the performance of these algorithms. We have conducted a comparative study with six different reverse engineering methods, including relevance networks, neural networks, and Bayesian networks. Our approach consists of the generation of defined benchmark data, the analysis of these data with the different methods, and the assessment of algorithmic performances by statistical analyses. Performance was judged by network size and noise levels. The results of the comparative study highlight the neural network approach as best performing method among those under study.

  20. Genomic Aberrations Frequently Alter Chromatin Regulatory Genes in Chordoma

    PubMed Central

    Wang, Lu; Zehir, Ahmet; Nafa, Khedoudja; Zhou, Nengyi; Berger, Michael F.; Casanova, Jacklyn; Sadowska, Justyna; Lu, Chao; Allis, C. David; Gounder, Mrinal; Chandhanayingyong, Chandhanarat; Ladanyi, Marc; Boland, Patrick J; Hameed, Meera

    2016-01-01

    Chordoma is a rare primary bone neoplasm that is resistant to standard chemotherapies. Despite aggressive surgical management, local recurrence and metastasis is not uncommon. To identify the specific genetic aberrations that play key roles in chordoma pathogenesis, we utilized a genome-wide high-resolution SNP-array and next generation sequencing (NGS)-based molecular profiling platform to study 24 patient samples with typical histopathologic features of chordoma. Matching normal tissues were available for 16 samples. SNP-array analysis revealed nonrandom copy number losses across the genome, frequently involving 3, 9p, 1p, 14, 10, and 13. In contrast, copy number gain is uncommon in chordomas. Two minimum deleted regions were observed on 3p within a ~8 Mb segment at 3p21.1–p21.31, which overlaps SETD2, BAP1 and PBRM1. The minimum deleted region on 9p was mapped to CDKN2A locus at 9p21.3, and homozygous deletion of CDKN2A was detected in 5/22 chordomas (~23%). NGS-based molecular profiling demonstrated an extremely low level of mutation rate in chordomas, with an average of 0.5 mutations per sample for the 16 cases with matched normal. When the mutated genes were grouped based on molecular functions, many of the mutation events (~40%) were found in chromatin regulatory genes. The combined copy number and mutation profiling revealed that SETD2 is the single gene affected most frequently in chordomas, either by deletion or by mutations. Our study demonstrated that chordoma belongs to the C-class (copy number changes) tumors whose oncogenic signature is non-random multiple copy number losses across the genome and genomic aberrations frequently alter chromatin regulatory genes. PMID:27072194

  1. Evolutionary and Topological Properties of Genes and Community Structures in Human Gene Regulatory Networks.

    PubMed

    Szedlak, Anthony; Smith, Nicholas; Liu, Li; Paternostro, Giovanni; Piermarocchi, Carlo

    2016-06-01

    The diverse, specialized genes present in today's lifeforms evolved from a common core of ancient, elementary genes. However, these genes did not evolve individually: gene expression is controlled by a complex network of interactions, and alterations in one gene may drive reciprocal changes in its proteins' binding partners. Like many complex networks, these gene regulatory networks (GRNs) are composed of communities, or clusters of genes with relatively high connectivity. A deep understanding of the relationship between the evolutionary history of single genes and the topological properties of the underlying GRN is integral to evolutionary genetics. Here, we show that the topological properties of an acute myeloid leukemia GRN and a general human GRN are strongly coupled with its genes' evolutionary properties. Slowly evolving ("cold"), old genes tend to interact with each other, as do rapidly evolving ("hot"), young genes. This naturally causes genes to segregate into community structures with relatively homogeneous evolutionary histories. We argue that gene duplication placed old, cold genes and communities at the center of the networks, and young, hot genes and communities at the periphery. We demonstrate this with single-node centrality measures and two new measures of efficiency, the set efficiency and the interset efficiency. We conclude that these methods for studying the relationships between a GRN's community structures and its genes' evolutionary properties provide new perspectives for understanding evolutionary genetics.

  2. Developmental gene regulatory networks in sea urchins and what we can learn from them

    PubMed Central

    Martik, Megan L.; Lyons, Deirdre C.; McClay, David R.

    2016-01-01

    Sea urchin embryos begin zygotic transcription shortly after the egg is fertilized.  Throughout the cleavage stages a series of transcription factors are activated and, along with signaling through a number of pathways, at least 15 different cell types are specified by the beginning of gastrulation.  Experimentally, perturbation of contributing transcription factors, signals and receptors and their molecular consequences enabled the assembly of an extensive gene regulatory network model.  That effort, pioneered and led by Eric Davidson and his laboratory, with many additional insights provided by other laboratories, provided the sea urchin community with a valuable resource.  Here we describe the approaches used to enable the assembly of an advanced gene regulatory network model describing molecular diversification during early development.  We then provide examples to show how a relatively advanced authenticated network can be used as a tool for discovery of how diverse developmental mechanisms are controlled and work. PMID:26962438

  3. Neurogenic gene regulatory pathways in the sea urchin embryo.

    PubMed

    Wei, Zheng; Angerer, Lynne M; Angerer, Robert C

    2016-01-15

    During embryogenesis the sea urchin early pluteus larva differentiates 40-50 neurons marked by expression of the pan-neural marker synaptotagmin B (SynB) that are distributed along the ciliary band, in the apical plate and pharyngeal endoderm, and 4-6 serotonergic neurons that are confined to the apical plate. Development of all neurons has been shown to depend on the function of Six3. Using a combination of molecular screens and tests of gene function by morpholino-mediated knockdown, we identified SoxC and Brn1/2/4, which function sequentially in the neurogenic regulatory pathway and are also required for the differentiation of all neurons. Misexpression of Brn1/2/4 at low dose caused an increase in the number of serotonin-expressing cells and at higher dose converted most of the embryo to a neurogenic epithelial sphere expressing the Hnf6 ciliary band marker. A third factor, Z167, was shown to work downstream of the Six3 and SoxC core factors and to define a branch specific for the differentiation of serotonergic neurons. These results provide a framework for building a gene regulatory network for neurogenesis in the sea urchin embryo.

  4. Evolution of the mammalian embryonic pluripotency gene regulatory network

    PubMed Central

    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

  5. Toxin-mediated gene regulatory mechanism in Staphylococcus aureus

    PubMed Central

    Joo, Hwang-Soo; Otto, Michael

    2016-01-01

    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.

  6. Neurogenic gene regulatory pathways in the sea urchin embryo

    PubMed Central

    Wei, Zheng; Angerer, Lynne M.; Angerer, Robert C.

    2016-01-01

    During embryogenesis the sea urchin early pluteus larva differentiates 40-50 neurons marked by expression of the pan-neural marker synaptotagmin B (SynB) that are distributed along the ciliary band, in the apical plate and pharyngeal endoderm, and 4-6 serotonergic neurons that are confined to the apical plate. Development of all neurons has been shown to depend on the function of Six3. Using a combination of molecular screens and tests of gene function by morpholino-mediated knockdown, we identified SoxC and Brn1/2/4, which function sequentially in the neurogenic regulatory pathway and are also required for the differentiation of all neurons. Misexpression of Brn1/2/4 at low dose caused an increase in the number of serotonin-expressing cells and at higher dose converted most of the embryo to a neurogenic epithelial sphere expressing the Hnf6 ciliary band marker. A third factor, Z167, was shown to work downstream of the Six3 and SoxC core factors and to define a branch specific for the differentiation of serotonergic neurons. These results provide a framework for building a gene regulatory network for neurogenesis in the sea urchin embryo. PMID:26657764

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

    PubMed Central

    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

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

    PubMed

    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).

  9. Implications of Developmental Gene Regulatory Networks Inside and Outside Developmental Biology.

    PubMed

    Peter, Isabelle S; Davidson, Eric H

    2016-01-01

    The insight that the genomic control of developmental process is encoded in the form of gene regulatory networks has profound impacts on many areas of modern bioscience. Most importantly, it affects developmental biology itself, as it means that a causal understanding of development requires knowledge of the architecture of regulatory network interactions. Furthermore, it follows that functional changes in developmental gene regulatory networks have to be considered as a primary mechanism for evolutionary process. We here discuss some of the recent advances in gene regulatory network biology and how they have affected our current understanding of development, evolution, and regulatory genomics.

  10. Replacing and Additive Horizontal Gene Transfer in Streptococcus

    PubMed Central

    Choi, Sang Chul; Rasmussen, Matthew D.; Hubisz, Melissa J.; Gronau, Ilan; Stanhope, Michael J.; Siepel, Adam

    2012-01-01

    The prominent role of Horizontal Gene Transfer (HGT) in the evolution of bacteria is now well documented, but few studies have differentiated between evolutionary events that predominantly cause genes in one lineage to be replaced by homologs from another lineage (“replacing HGT”) and events that result in the addition of substantial new genomic material (“additive HGT”). Here in, we make use of the distinct phylogenetic signatures of replacing and additive HGTs in a genome-wide study of the important human pathogen Streptococcus pyogenes (SPY) and its close relatives S. dysgalactiae subspecies equisimilis (SDE) and S. dysgalactiae subspecies dysgalactiae (SDD). Using recently developed statistical models and computational methods, we find evidence for abundant gene flow of both kinds within each of the SPY and SDE clades and of reduced levels of exchange between SPY and SDD. In addition, our analysis strongly supports a pronounced asymmetry in SPY–SDE gene flow, favoring the SPY-to-SDE direction. This finding is of particular interest in light of the recent increase in virulence of pathogenic SDE. We find much stronger evidence for SPY–SDE gene flow among replacing than among additive transfers, suggesting a primary influence from homologous recombination between co-occurring SPY and SDE cells in human hosts. Putative virulence genes are correlated with transfer events, but this correlation is found to be driven by additive, not replacing, HGTs. The genes affected by additive HGTs are enriched for functions having to do with transposition, recombination, and DNA integration, consistent with previous findings, whereas replacing HGTs seen to influence a more diverse set of genes. Additive transfers are also found to be associated with evidence of positive selection. These findings shed new light on the manner in which HGT has shaped pathogenic bacterial genomes. PMID:22617954

  11. Enhancing gene regulatory network inference through data integration with markov random fields.

    PubMed

    Banf, Michael; Rhee, Seung Y

    2017-02-01

    A gene regulatory network links transcription factors to their target genes and represents a map of transcriptional regulation. Much progress has been made in deciphering gene regulatory networks computationally. However, gene regulatory network inference for most eukaryotic organisms remain challenging. To improve the accuracy of gene regulatory network inference and facilitate candidate selection for experimentation, we developed an algorithm called GRACE (Gene Regulatory network inference ACcuracy Enhancement). GRACE exploits biological a priori and heterogeneous data integration to generate high- confidence network predictions for eukaryotic organisms using Markov Random Fields in a semi-supervised fashion. GRACE uses a novel optimization scheme to integrate regulatory evidence and biological relevance. It is particularly suited for model learning with sparse regulatory gold standard data. We show GRACE's potential to produce high confidence regulatory networks compared to state of the art approaches using Drosophila melanogaster and Arabidopsis thaliana data. In an A. thaliana developmental gene regulatory network, GRACE recovers cell cycle related regulatory mechanisms and further hypothesizes several novel regulatory links, including a putative control mechanism of vascular structure formation due to modifications in cell proliferation.

  12. Enhancing gene regulatory network inference through data integration with markov random fields

    PubMed Central

    Banf, Michael; Rhee, Seung Y.

    2017-01-01

    A gene regulatory network links transcription factors to their target genes and represents a map of transcriptional regulation. Much progress has been made in deciphering gene regulatory networks computationally. However, gene regulatory network inference for most eukaryotic organisms remain challenging. To improve the accuracy of gene regulatory network inference and facilitate candidate selection for experimentation, we developed an algorithm called GRACE (Gene Regulatory network inference ACcuracy Enhancement). GRACE exploits biological a priori and heterogeneous data integration to generate high- confidence network predictions for eukaryotic organisms using Markov Random Fields in a semi-supervised fashion. GRACE uses a novel optimization scheme to integrate regulatory evidence and biological relevance. It is particularly suited for model learning with sparse regulatory gold standard data. We show GRACE’s potential to produce high confidence regulatory networks compared to state of the art approaches using Drosophila melanogaster and Arabidopsis thaliana data. In an A. thaliana developmental gene regulatory network, GRACE recovers cell cycle related regulatory mechanisms and further hypothesizes several novel regulatory links, including a putative control mechanism of vascular structure formation due to modifications in cell proliferation. PMID:28145456

  13. Enhancing gene regulatory network inference through data integration with markov random fields

    DOE PAGES

    Banf, Michael; Rhee, Seung Y.

    2017-02-01

    Here, a gene regulatory network links transcription factors to their target genes and represents a map of transcriptional regulation. Much progress has been made in deciphering gene regulatory networks computationally. However, gene regulatory network inference for most eukaryotic organisms remain challenging. To improve the accuracy of gene regulatory network inference and facilitate candidate selection for experimentation, we developed an algorithm called GRACE (Gene Regulatory network inference ACcuracy Enhancement). GRACE exploits biological a priori and heterogeneous data integration to generate high- confidence network predictions for eukaryotic organisms using Markov Random Fields in a semi-supervised fashion. GRACE uses a novel optimization schememore » to integrate regulatory evidence and biological relevance. It is particularly suited for model learning with sparse regulatory gold standard data. We show GRACE’s potential to produce high confidence regulatory networks compared to state of the art approaches using Drosophila melanogaster and Arabidopsis thaliana data. In an A. thaliana developmental gene regulatory network, GRACE recovers cell cycle related regulatory mechanisms and further hypothesizes several novel regulatory links, including a putative control mechanism of vascular structure formation due to modifications in cell proliferation.« less

  14. Regulatory network of microRNAs and genes in testicular cancer

    PubMed Central

    Zhao, Yansong; Xu, Zhiwen; Wang, Ning; Wang, Shang

    2016-01-01

    Testicular cancer (TC) is the most common cancer in men between 20–40 years of age. A large number of studies have focused on identifying the cause of this disease; however, the underlying regulatory mechanisms have not been thoroughly investigated and the specific cause remains unclear. The present study systematically analyzed the regulatory associations between genes, transcription factors (TFs) and microRNAs (miRNAs), aiming to obtain key information regarding the regulatory processes of TC. Three different networks were derived from the analysis: Global, related and differentially-expressed. These networks may be able to identify the primary causes of TC through gene analysis, which determines underlying regulatory pathways and subsequently discloses information regarding TC pathology. The differentially-expressed network is considered to be the most important. If the differentially-expressed elements in this network were to be manipulated back to normal levels via human intervention, this may prevent the onset of TC. This may be described as suppressing TC at the genetic level. If the abnormal expression of these elements was to be corrected, then preventing TC at the source may be a feasible option. Thus, the present study compared and analyzed the global, related and differentially-expressed networks, from which important genetic pathways in TC were highlighted. In addition, self-adaptation associations, host genes and target genes were analyzed. The upstream and downstream elements were identified, and TFs were predicted using the P-match method. When combined, the results of the current study provide the basic materials for further research on important genes in TC, and provide guidance on the pathological curative method. PMID:27900048

  15. An Arabidopsis gene regulatory network for secondary cell wall synthesis

    DOE PAGES

    Taylor-Teeples, M.; Lin, L.; de Lucas, M.; ...

    2014-12-24

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

  16. Identification of a gene regulatory network associated with prion replication

    PubMed Central

    Marbiah, Masue M; Harvey, Anna; West, Billy T; Louzolo, Anais; Banerjee, Priya; Alden, Jack; Grigoriadis, Anita; Hummerich, Holger; Kan, Ho-Man; Cai, Ying; Bloom, George S; Jat, Parmjit; Collinge, John; Klöhn, Peter-Christian

    2014-01-01

    Prions consist of aggregates of abnormal conformers of the cellular prion protein (PrPC). They propagate by recruiting host-encoded PrPC although the critical interacting proteins and the reasons for the differences in susceptibility of distinct cell lines and populations are unknown. We derived a lineage of cell lines with markedly differing susceptibilities, unexplained by PrPC expression differences, to identify such factors. Transcriptome analysis of prion-resistant revertants, isolated from highly susceptible cells, revealed a gene expression signature associated with susceptibility and modulated by differentiation. Several of these genes encode proteins with a role in extracellular matrix (ECM) remodelling, a compartment in which disease-related PrP is deposited. Silencing nine of these genes significantly increased susceptibility. Silencing of Papss2 led to undersulphated heparan sulphate and increased PrPC deposition at the ECM, concomitantly with increased prion propagation. Moreover, inhibition of fibronectin 1 binding to integrin α8 by RGD peptide inhibited metalloproteinases (MMP)-2/9 whilst increasing prion propagation. In summary, we have identified a gene regulatory network associated with prion propagation at the ECM and governed by the cellular differentiation state. PMID:24843046

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

    PubMed Central

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

    2013-01-01

    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. PMID:23737768

  18. The influence of assortativity on the robustness and evolvability of gene regulatory networks upon gene birth

    PubMed Central

    Pechenick, Dov A.; Moore, Jason H.; Payne, Joshua L.

    2013-01-01

    Gene regulatory networks (GRNs) represent the interactions between genes and gene products, which drive the gene expression patterns that produce cellular phenotypes. GRNs display a number of characteristics that are beneficial for the development and evolution of organisms. For example, they are often robust to genetic perturbation, such as mutations in regulatory regions or loss of gene function. Simultaneously, GRNs are often evolvable as these genetic perturbations are occasionally exploited to innovate novel regulatory programs. Several topological properties, such as degree distribution, are known to influence the robustness and evolvability of GRNs. Assortativity, which measures the propensity of nodes of similar connectivity to connect to one another, is a separate topological property that has recently been shown to influence the robustness of GRNs to point mutations in cis-regulatory regions. However, it remains to be seen how assortativity may influence the robustness and evolvability of GRNs to other forms of genetic perturbation, such as gene birth via duplication or de novo origination. Here, we employ a computational model of genetic regulation to investigate whether the assortativity of a GRN influences its robustness and evolvability upon gene birth. We find that the robustness of a GRN generally increases with increasing assortativity, while its evolvability generally decreases. However, the rate of change in robustness outpaces that of evolvability, resulting in an increased proportion of assortative GRNs that are simultaneously robust and evolvable. By providing a mechanistic explanation for these observations, this work extends our understanding of how the assortativity of a GRN influences its robustness and evolvability upon gene birth. PMID:23542384

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

    PubMed

    Zhang, Qiang; Andersen, Melvin E

    2007-03-02

    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, misfolded proteins, and O2, is first detected by specialized sensor molecules, then the signal is transduced to specific transcription factors. Transcription factors can regulate the expression of a suite of anti-stress genes, many of which encode enzymes functioning to counteract the perturbed variables. The objective of this study was to explore, using control theory and computational approaches, the theoretical basis that underlies the steady-state dose response relationship between cellular stressors and intracellular biochemical species (controlled variables, transcription factors, and gene products) in these gene regulatory networks. Our work indicated that the shape of dose response curves (linear, superlinear, or sublinear) depends on changes in the specific values of local response coefficients (gains) distributed in the feedback loop. Multimerization of anti-stress enzymes and transcription factors into homodimers, homotrimers, or even higher-order multimers, play a significant role in maintaining robust homeostasis. Moreover, our simulation noted that dose response curves for the controlled variables can transition sequentially through four distinct phases as stressor level increases: initial superlinear with lesser control, superlinear more highly controlled, linear uncontrolled, and sublinear catastrophic. Each phase relies on specific gain-changing events that come into play as stressor level increases. The low-dose region is intrinsically nonlinear, and depending on

  20. Gene regulatory network clustering for graph layout based on microarray gene expression data.

    PubMed

    Kojima, Kaname; Imoto, Seiya; Nagasaki, Masao; Miyano, Satoru

    2010-01-01

    We propose a statistical model realizing simultaneous estimation of gene regulatory network and gene module identification from time series gene expression data from microarray experiments. Under the assumption that genes in the same module are densely connected, the proposed method detects gene modules based on the variational Bayesian technique. The model can also incorporate existing biological prior knowledge such as protein subcellular localization. We apply the proposed model to the time series data from a synthetically generated network and verified the effectiveness of the proposed model. The proposed model is also applied the time series microarray data from HeLa cell. Detected gene module information gives the great help on drawing the estimated gene network.

  1. Inheritance of gene expression level and selective constraints on trans- and cis-regulatory changes in yeast.

    PubMed

    Schaefke, Bernhard; Emerson, J J; Wang, Tzi-Yuan; Lu, Mei-Yeh Jade; Hsieh, Li-Ching; Li, Wen-Hsiung

    2013-09-01

    Gene expression evolution can be caused by changes in cis- or trans-regulatory elements or both. As cis and trans regulation operate through different molecular mechanisms, cis and trans mutations may show different inheritance patterns and may be subjected to different selective constraints. To investigate these issues, we obtained and analyzed gene expression data from two Saccharomyces cerevisiae strains and their hybrid, using high-throughput sequencing. Our data indicate that compared with other types of genes, those with antagonistic cis-trans interactions are more likely to exhibit over- or underdominant inheritance of expression level. Moreover, in accordance with previous studies, genes with trans variants tend to have a dominant inheritance pattern, whereas cis variants are enriched for additive inheritance. In addition, cis regulatory differences contribute more to expression differences between species than within species, whereas trans regulatory differences show a stronger association between divergence and polymorphism. Our data indicate that in the trans component of gene expression differences genes subjected to weaker selective constraints tend to have an excess of polymorphism over divergence compared with those subjected to stronger selective constraints. In contrast, in the cis component, this difference between genes under stronger and weaker selective constraint is mostly absent. To explain these observations, we propose that purifying selection more strongly shapes trans changes than cis changes and that positive selection may have significantly contributed to cis regulatory divergence.

  2. Evolutionary and Topological Properties of Genes and Community Structures in Human Gene Regulatory Networks

    PubMed Central

    Szedlak, Anthony; Smith, Nicholas; Liu, Li; Paternostro, Giovanni; Piermarocchi, Carlo

    2016-01-01

    The diverse, specialized genes present in today’s lifeforms evolved from a common core of ancient, elementary genes. However, these genes did not evolve individually: gene expression is controlled by a complex network of interactions, and alterations in one gene may drive reciprocal changes in its proteins’ binding partners. Like many complex networks, these gene regulatory networks (GRNs) are composed of communities, or clusters of genes with relatively high connectivity. A deep understanding of the relationship between the evolutionary history of single genes and the topological properties of the underlying GRN is integral to evolutionary genetics. Here, we show that the topological properties of an acute myeloid leukemia GRN and a general human GRN are strongly coupled with its genes’ evolutionary properties. Slowly evolving (“cold”), old genes tend to interact with each other, as do rapidly evolving (“hot”), young genes. This naturally causes genes to segregate into community structures with relatively homogeneous evolutionary histories. We argue that gene duplication placed old, cold genes and communities at the center of the networks, and young, hot genes and communities at the periphery. We demonstrate this with single-node centrality measures and two new measures of efficiency, the set efficiency and the interset efficiency. We conclude that these methods for studying the relationships between a GRN’s community structures and its genes’ evolutionary properties provide new perspectives for understanding evolutionary genetics. PMID:27359334

  3. Coding and non-coding gene regulatory networks underlie the immune response in liver cirrhosis

    PubMed Central

    Zhang, Xueming; Huang, Yongming; Yang, Zhengpeng; Zhang, Yuguo; Zhang, Weihui; Gao, Zu-hua; Xue, Dongbo

    2017-01-01

    Liver cirrhosis is recognized as being the consequence of immune-mediated hepatocyte damage and repair processes. However, the regulation of these immune responses underlying liver cirrhosis has not been elucidated. In this study, we used GEO datasets and bioinformatics methods to established coding and non-coding gene regulatory networks including transcription factor-/lncRNA-microRNA-mRNA, and competing endogenous RNA interaction networks. Our results identified 2224 mRNAs, 70 lncRNAs and 46 microRNAs were differentially expressed in liver cirrhosis. The transcription factor -/lncRNA- microRNA-mRNA network we uncovered that results in immune-mediated liver cirrhosis is comprised of 5 core microRNAs (e.g., miR-203; miR-219-5p), 3 transcription factors (i.e., FOXP3, ETS1 and FOS) and 7 lncRNAs (e.g., ENTS00000671336, ENST00000575137). The competing endogenous RNA interaction network we identified includes a complex immune response regulatory subnetwork that controls the entire liver cirrhosis network. Additionally, we found 10 overlapping GO terms shared by both liver cirrhosis and hepatocellular carcinoma including “immune response” as well. Interestingly, the overlapping differentially expressed genes in liver cirrhosis and hepatocellular carcinoma were enriched in immune response-related functional terms. In summary, a complex gene regulatory network underlying immune response processes may play an important role in the development and progression of liver cirrhosis, and its development into hepatocellular carcinoma. PMID:28355233

  4. Genetic Analysis of Transvection Effects Involving Cis-Regulatory Elements of the Drosophila Ultrabithorax Gene

    PubMed Central

    Micol, J. L.; Castelli-Gair, J. E.; Garcia-Bellido, A.

    1990-01-01

    The Ultrabithorax (Ubx) gene of Drosophila melanogaster contains two functionally distinguishable regions: the protein-coding Ubx transcription unit and, upstream of it, the transcribed but non-protein-coding bxd region. Numerous recessive, partial loss-of-function mutations which appear to be regulatory mutations map within the bxd region and within the introns of the Ubx transcription unit. In addition, mutations within the Ubx unit exons are known and most of these behave as null alleles. Ubx(1) is one such allele. We have confirmed that, although the Ubx(1) allele does not produce detectable Ubx proteins (UBX), it does retain other genetic functions detectable by their effects on the expression of a paired, homologous Ubx allele, i.e., by transvection. We have extended previous analyses made by E. B. Lewis by mapping the critical elements of the Ubx gene which participate in transvection effects. Our results show that the Ubx(1) allele retains wild-type functions whose effectiveness can be reduced (1) by additional cis mutations in the bxd region or in introns of the Ubx transcription unit, as well as (2) by rearrangements disturbing pairing between homologous Ubx genes. Our results suggest that those remnant functions in Ubx(1) are able to modulate the activity of the allele located in the homologous chromosome. We discuss the normal cis regulatory role of these functions involved in trans interactions between homologous Ubx genes, as well as the implications of our results for the current models on transvection. PMID:2123161

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

    PubMed Central

    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. Topological effects of data incompleteness of gene regulatory networks

    PubMed Central

    2012-01-01

    Background 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. Results 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 levels. Conclusions In doing so, we identify the most relevant factors affecting the validity of previous findings, highlighting important caveats to future prokaryotic TRNs topological analysis. PMID:22920968

  7. Complex Dynamic Behavior in Simple Gene Regulatory Networks

    NASA Astrophysics Data System (ADS)

    Santillán Zerón, Moisés

    2007-02-01

    Knowing the complete genome of a given species is just a piece of the puzzle. To fully unveil the systems behavior of an organism, an organ, or even a single cell, we need to understand the underlying gene regulatory dynamics. Given the complexity of the whole system, the ultimate goal is unattainable for the moment. But perhaps, by analyzing the most simple genetic systems, we may be able to develop the mathematical techniques and procedures required to tackle more complex genetic networks in the near future. In the present work, the techniques for developing mathematical models of simple bacterial gene networks, like the tryptophan and lactose operons are introduced. Despite all of the underlying assumptions, such models can provide valuable information regarding gene regulation dynamics. Here, we pay special attention to robustness as an emergent property. These notes are organized as follows. In the first section, the long historical relation between mathematics, physics, and biology is briefly reviewed. Recently, the multidisciplinary work in biology has received great attention in the form of systems biology. The main concepts of this novel science are discussed in the second section. A very slim introduction to the essential concepts of molecular biology is given in the third section. In the fourth section, a brief introduction to chemical kinetics is presented. Finally, in the fifth section, a mathematical model for the lactose operon is developed and analyzed..

  8. Stochastic S-system modeling of gene regulatory network.

    PubMed

    Chowdhury, Ahsan Raja; Chetty, Madhu; Evans, Rob

    2015-10-01

    Microarray gene expression data can provide insights into biological processes at a system-wide level and is commonly used for reverse engineering gene regulatory networks (GRN). Due to the amalgamation of noise from different sources, microarray expression profiles become inherently noisy leading to significant impact on the GRN reconstruction process. Microarray replicates (both biological and technical), generated to increase the reliability of data obtained under noisy conditions, have limited influence in enhancing the accuracy of reconstruction . Therefore, instead of the conventional GRN modeling approaches which are deterministic, stochastic techniques are becoming increasingly necessary for inferring GRN from noisy microarray data. In this paper, we propose a new stochastic GRN model by investigating incorporation of various standard noise measurements in the deterministic S-system model. Experimental evaluations performed for varying sizes of synthetic network, representing different stochastic processes, demonstrate the effect of noise on the accuracy of genetic network modeling and the significance of stochastic modeling for GRN reconstruction . The proposed stochastic model is subsequently applied to infer the regulations among genes in two real life networks: (1) the well-studied IRMA network, a real-life in-vivo synthetic network constructed within the Saccharomyces cerevisiae yeast, and (2) the SOS DNA repair network in Escherichia coli.

  9. Transactivation of anthocyanin biosynthetic genes following transfer of B regulatory genes into maize tissues.

    PubMed Central

    Goff, S A; Klein, T M; Roth, B A; Fromm, M E; Cone, K C; Radicella, J P; Chandler, V L

    1990-01-01

    The C1, B and R genes regulating the maize anthocyanin biosynthetic pathway encode tissue-specific regulatory proteins with similarities to transcriptional activators. The C1 and R regulatory genes are usually responsible for pigmentation of seed tissues, and the B-Peru allele of B, but not the B-I allele, can substitute for R function in the seed. In this study, members of the B family of regulatory genes were delivered to intact maize tissues by high velocity microprojectiles. In colorless r aleurones or embryos, the introduction of the B-Peru genomic clone or the expressed cDNAs of B-Peru or B-I resulted in anthocyanin-producing cells. Luciferase produced from the Bronze1 anthocyanin structural gene promoter was induced 100-fold when co-introduced with the expressed B-Peru or B-I cDNAs. This quantitative transactivation assay demonstrates that the proteins encoded by these two B alleles are equally able to transactivate the Bronze1 promoter. Analogous results were obtained using embryogenic callus cells. These observations suggest that one major contribution towards tissue-specific anthocyanin synthesis controlled by the various alleles of the B and R genes is the differential expression of functionally similar proteins. Images Fig. 2. PMID:2369901

  10. The Influence of Assortativity on the Robustness of Signal-Integration Logic in Gene Regulatory Networks

    PubMed Central

    Pechenick, Dov A.; Payne, Joshua L.; Moore, Jason H.

    2011-01-01

    Gene regulatory networks (GRNs) drive the cellular processes that sustain life. To do so reliably, GRNs must be robust to perturbations, such as gene deletion and the addition or removal of regulatory interactions. GRNs must also be robust to genetic changes in regulatory regions that define the logic of signal-integration, as these changes can affect how specific combinations of regulatory signals are mapped to particular gene expression states. Previous theoretical analyses have demonstrated that the robustness of a GRN is influenced by its underlying topological properties, such as degree distribution and modularity. Another important topological property is assortativity, which measures the propensity with which nodes of similar connectivity are connected to one another. How assortativity influences the robustness of the signal-integration logic of GRNs remains an open question. Here, we use computational models of GRNs to investigate this relationship. We separately consider each of the three dynamical regimes of this model for a variety of degree distributions. We find that in the chaotic regime, robustness exhibits a pronounced increase as assortativity becomes more positive, while in the critical and ordered regimes, robustness is generally less sensitive to changes in assortativity. We attribute the increased robustness to a decrease in the duration of the gene expression pattern, which is caused by a reduction in the average size of a GRN’s in-components. This study provides the first direct evidence that assortativity influences the robustness of the signal-integration logic of computational models of GRNs, illuminates a mechanistic explanation for this influence, and furthers our understanding of the relationship between topology and robustness in complex biological systems. PMID:22155134

  11. Reverse engineering of gene regulatory network using restricted gene expression programming.

    PubMed

    Yang, Bin; Liu, Sanrong; Zhang, Wei

    2016-10-01

    Inference of gene regulatory networks has been becoming a major area of interest in the field of systems biology over the past decade. In this paper, we present a novel representation of S-system model, named restricted gene expression programming (RGEP), to infer gene regulatory network. A new hybrid evolutionary algorithm based on structure-based evolutionary algorithm and cuckoo search (CS) is proposed to optimize the architecture and corresponding parameters of model, respectively. Two synthetic benchmark datasets and one real biological dataset from SOS DNA repair network in E. coli are used to test the validity of our method. Experimental results demonstrate that our proposed method performs better than previously proposed popular methods.

  12. Algebraic model checking for Boolean gene regulatory networks.

    PubMed

    Tran, Quoc-Nam

    2011-01-01

    We present a computational method in which modular and Groebner bases (GB) computation in Boolean rings are used for solving problems in Boolean gene regulatory networks (BN). In contrast to other known algebraic approaches, the degree of intermediate polynomials during the calculation of Groebner bases using our method will never grow resulting in a significant improvement in running time and memory space consumption. We also show how calculation in temporal logic for model checking can be done by means of our direct and efficient Groebner basis computation in Boolean rings. We present our experimental results in finding attractors and control strategies of Boolean networks to illustrate our theoretical arguments. The results are promising. Our algebraic approach is more efficient than the state-of-the-art model checker NuSMV on BNs. More importantly, our approach finds all solutions for the BN problems.

  13. Modeling gene regulatory networks: A network simplification algorithm

    NASA Astrophysics Data System (ADS)

    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.

  14. Dynamical analysis of regulatory interactions in the gap gene system of Drosophila melanogaster.

    PubMed Central

    Jaeger, Johannes; Blagov, Maxim; Kosman, David; Kozlov, Konstantin N; Manu; Myasnikova, Ekaterina; Surkova, Svetlana; Vanario-Alonso, Carlos E; Samsonova, Maria; Sharp, David H; Reinitz, John

    2004-01-01

    Genetic studies have revealed that segment determination in Drosophila melanogaster is based on hierarchical regulatory interactions among maternal coordinate and zygotic segmentation genes. The gap gene system constitutes the most upstream zygotic layer of this regulatory hierarchy, responsible for the initial interpretation of positional information encoded by maternal gradients. We present a detailed analysis of regulatory interactions involved in gap gene regulation based on gap gene circuits, which are mathematical gene network models used to infer regulatory interactions from quantitative gene expression data. Our models reproduce gap gene expression at high accuracy and temporal resolution. Regulatory interactions found in gap gene circuits provide consistent and sufficient mechanisms for gap gene expression, which largely agree with mechanisms previously inferred from qualitative studies of mutant gene expression patterns. Our models predict activation of Kr by Cad and clarify several other regulatory interactions. Our analysis suggests a central role for repressive feedback loops between complementary gap genes. We observe that repressive interactions among overlapping gap genes show anteroposterior asymmetry with posterior dominance. Finally, our models suggest a correlation between timing of gap domain boundary formation and regulatory contributions from the terminal maternal system. PMID:15342511

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

    PubMed

    Kano, Shungo; Xiao, Jin-Hua; Osório, Joana; Ekker, Marc; Hadzhiev, Yavor; Müller, Ferenc; Casane, Didier; Magdelenat, Ghislaine; Rétaux, Sylvie

    2010-10-13

    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.

  16. Regulation of photoreceptor gene transcription via a highly conserved transcriptional regulatory element by vsx gene products

    PubMed Central

    Pan, Yi; Comiskey, Daniel F.; Kelly, Lisa E.; Chandler, Dawn S.

    2016-01-01

    Purpose The photoreceptor conserved element-1 (PCE-1) sequence is found in the transcriptional regulatory regions of many genes expressed in photoreceptors. The retinal homeobox (Rx or Rax) gene product functions by binding to PCE-1 sites. However, other transcriptional regulators have also been reported to bind to PCE-1. One of these, vsx2, is expressed in retinal progenitor and bipolar cells. The purpose of this study is to identify Xenopus laevis vsx gene products and characterize vsx gene product expression and function with respect to the PCE-1 site. Methods X. laevis vsx gene products were amplified with PCR. Expression patterns were determined with in situ hybridization using whole or sectioned X. laevis embryos and digoxigenin- or fluorescein-labeled antisense riboprobes. DNA binding characteristics of the vsx gene products were analyzed with electrophoretic mobility shift assays (EMSAs) using in vitro translated proteins and radiolabeled oligonucleotide probes. Gene transactivation assays were performed using luciferase-based reporters and in vitro transcribed effector gene products, injected into X. laevis embryos. Results We identified one vsx1 and two vsx2 gene products. The two vsx2 gene products are generated by alternate mRNA splicing. We verified that these gene products are expressed in the developing retina and that expression resolves into distinct cell types in the mature retina. Finally, we found that vsx gene products can bind the PCE-1 site in vitro and that the two vsx2 isoforms have different gene transactivation activities. Conclusions vsx gene products are expressed in the developing and mature neural retina. vsx gene products can bind the PCE-1 site in vitro and influence the expression of a rhodopsin promoter-luciferase reporter gene. The two isoforms of vsx have different gene transactivation activities in this reporter gene system. PMID:28003732

  17. Genome-wide network of regulatory genes for construction of a chordate embryo.

    PubMed

    Shoguchi, Eiichi; Hamaguchi, Makoto; Satoh, Nori

    2008-04-15

    Animal development is controlled by gene regulation networks that are composed of sequence-specific transcription factors (TF) and cell signaling molecules (ST). Although housekeeping genes have been reported to show clustering in the animal genomes, whether the genes comprising a given regulatory network are physically clustered on a chromosome is uncertain. We examined this question in the present study. Ascidians are the closest living relatives of vertebrates, and their tadpole-type larva represents the basic body plan of chordates. The Ciona intestinalis genome contains 390 core TF genes and 119 major ST genes. Previous gene disruption assays led to the formulation of a basic chordate embryonic blueprint, based on over 3000 genetic interactions among 79 zygotic regulatory genes. Here, we mapped the regulatory genes, including all 79 regulatory genes, on the 14 pairs of Ciona chromosomes by fluorescent in situ hybridization (FISH). Chromosomal localization of upstream and downstream regulatory genes demonstrates that the components of coherent developmental gene networks are evenly distributed over the 14 chromosomes. Thus, this study provides the first comprehensive evidence that the physical clustering of regulatory genes, or their target genes, is not relevant for the genome-wide control of gene expression during development.

  18. Regulatory component analysis: a semi-blind extraction approach to infer gene regulatory networks with imperfect biological knowledge

    PubMed Central

    Wang, Chen; Xuan, Jianhua; Shih, Ie-Ming; Clarke, Robert; Wang, Yue

    2011-01-01

    With the advent of high-throughput biotechnology capable of monitoring genomic signals, it becomes increasingly promising to understand molecular cellular mechanisms through systems biology approaches. One of the active research topics in systems biology is to infer gene transcriptional regulatory networks using various genomic data; this inference problem can be formulated as a linear model with latent signals associated with some regulatory proteins called transcription factors (TFs). As common statistical assumptions may not hold for genomic signals, typical latent variable algorithms such as independent component analysis (ICA) are incapable to reveal underlying true regulatory signals. Liao et al. [1] proposed to perform inference using an approach named network component analysis (NCA), the optimization of which is achieved by a least-squares fitting approach with biological knowledge constraints. However, the incompleteness of biological knowledge and its inconsistency with gene expression data are not considered in the original NCA solution, which could greatly affect the inference accuracy. To overcome these limitations, we propose a linear extraction scheme, namely regulatory component analysis (RCA), to infer underlying regulatory signals even with partial biological knowledge. Numerical simulations show a significant improvement of our proposed RCA over NCA, not only when signal-to-noise-ratio (SNR) is low, but also when the given biological knowledge is incomplete and inconsistent to gene expression data. Furthermore, real biological experiments on E. coli are performed for regulatory network inference in comparison with several typical linear latent variable methods, which again demonstrates the effectiveness and improved performance of the proposed algorithm. PMID:22685363

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

    PubMed Central

    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

  20. Coordinated regulation of biosynthetic and regulatory genes coincides with anthocyanin accumulation in developing eggplant fruit

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Violet to black pigmentation of eggplant (Solanum melongena) fruit is attributed to anthocyanin accumulation. Model systems support the interaction of biosynthetic and regulatory genes for anthocyanin biosynthesis. Anthocyanin structural gene transcription requires the expression of at least one m...

  1. Stochastic models and numerical algorithms for a class of regulatory gene networks.

    PubMed

    Fournier, Thomas; Gabriel, Jean-Pierre; Pasquier, Jerôme; Mazza, Christian; Galbete, José; Mermod, Nicolas

    2009-08-01

    Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

  2. Amylase and chitinase genes in Streptomyces lividans are regulated by reg1, a pleiotropic regulatory gene.

    PubMed Central

    Nguyen, J; Francou, F; Virolle, M J; Guérineau, M

    1997-01-01

    A regulatory gene, reg1, was identified in Streptomyces lividans. It encodes a 345-amino-acid protein (Reg1) which contains a helix-turn-helix DNA-binding motif in the N-terminal region. Reg1 exhibits similarity with the LacI/GalR family members over the entire sequence. It displays 95% identity with MalR (the repressor of malE in S. coelicolor), 65% identity with ORF-Sl (a putative regulatory gene of alpha-amylase of S. limosus), and 31% identity with CcpA (the carbon catabolite repressor in Bacillus subtilis). In S. lividans, the chromosomal disruption of reg1 affected the expression of several genes. The production of alpha-amylases of S. lividans and that of the alpha-amylase of S. limosus in S. lividans were enhanced in the reg1 mutant strains and relieved of carbon catabolite repression. As a result, the transcription level of the alpha-amylase of S. limosus was noticeably increased in the reg1 mutant strain. Moreover, the induction of chitinase production in S. lividans was relieved of carbon catabolite repression by glucose in the reg1 mutant strain, while the induction by chitin was lost. Therefore, reg1 can be regarded as a pleiotropic regulatory gene in S. lividans. PMID:9335287

  3. Two different modes of oscillation in a gene transcription regulatory network with interlinked positive and negative feedback loops

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed

    Garfield, David A; Runcie, Daniel E; Babbitt, Courtney C; Haygood, Ralph; Nielsen, William J; Wray, Gregory A

    2013-10-01

    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.

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

    PubMed

    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.

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

    PubMed Central

    2014-01-01

    Background 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. Results 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

  7. Regulatory network reconstruction using an integral additive model with flexible kernel functions

    PubMed Central

    Novikov, Eugene; Barillot, Emmanuel

    2008-01-01

    Background Reconstruction of regulatory networks is one of the most challenging tasks of systems biology. A limited amount of experimental data and little prior knowledge make the problem difficult to solve. Although models that are currently used for inferring regulatory networks are sometimes able to make useful predictions about the structures and mechanisms of molecular interactions, there is still a strong demand to develop increasingly universal and accurate approaches for network reconstruction. Results The additive regulation model is represented by a set of differential equations and is frequently used for network inference from time series data. Here we generalize this model by converting differential equations into integral equations with adjustable kernel functions. These kernel functions can be selected based on prior knowledge or defined through iterative improvement in data analysis. This makes the integral model very flexible and thus capable of covering a broad range of biological systems more adequately and specifically than previous models. Conclusion We reconstructed network structures from artificial and real experimental data using differential and integral inference models. The artificial data were simulated using mathematical models implemented in JDesigner. The real data were publicly available yeast cell cycle microarray time series. The integral model outperformed the differential one for all cases. In the integral model, we tested the zero-degree polynomial and single exponential kernels. Further improvements could be expected if the kernel were selected more specifically depending on the system. PMID:18218091

  8. Regulatory circuit rewiring and functional divergence of the duplicate admp genes in dorsoventral axial patterning.

    PubMed

    Chang, Yi-Cheng; Pai, Chih-Yu; Chen, Yi-Chih; Ting, Hsiu-Chi; Martinez, Pedro; Telford, Maximilian J; Yu, Jr-Kai; Su, Yi-Hsien

    2016-02-01

    The spatially opposed expression of Antidorsalizing morphogenetic protein (Admp) and BMP signals controls dorsoventral (DV) polarity across Bilateria and hence represents an ancient regulatory circuit. Here, we show that in addition to the conserved admp1 that constitutes the ancient circuit, a second admp gene (admp2) is present in Ambulacraria (Echinodermata+Hemichordata) and two marine worms belonging to Xenoturbellida and Acoelomorpha. The phylogenetic distribution implies that the two admp genes were duplicated in the Bilaterian common ancestor and admp2 was subsequently lost in chordates and protostomes. We show that the ambulacrarian admp1 and admp2 are under opposite transcriptional control by BMP signals and knockdown of Admps in sea urchins impaired their DV polarity. Over-expression of either Admps reinforced BMP signaling but resulted in different phenotypes in the sea urchin embryo. Our study provides an excellent example of signaling circuit rewiring and protein functional changes after gene duplications.

  9. A new approach for modelling gene regulatory networks using fuzzy petri nets.

    PubMed

    Hamed, Raed I; Ahson, S I; Parveen, R

    2010-02-04

    Gene Regulatory Networks are models of genes and gene interactions at the expression level. The advent of microarray technology has challenged computer scientists to develop better algorithms for modeling the underlying regulatory relationship in between the genes. Fuzzy system has an ability to search microarray datasets for activator/repressor regulatory relationship. In this paper, we present a fuzzy reasoning model based on the Fuzzy Petri Net. The model considers the regulatory triplets by means of predicting changes in expression level of the target based on input expression level. This method eliminates possible false predictions from the classical fuzzy model thereby allowing a wider search space for inferring regulatory relationship. Through formalization of fuzzy reasoning, we propose an approach to construct a rulebased reasoning system. The experimental results show the proposed approach is feasible and acceptable to predict changes in expression level of the target gene.

  10. Computational tools and resources for prediction and analysis of gene regulatory regions in the chick genome.

    PubMed

    Khan, Mohsin A F; Soto-Jimenez, Luz Mayela; Howe, Timothy; Streit, Andrea; Sosinsky, Alona; Stern, Claudio D

    2013-05-01

    The discovery of cis-regulatory elements is a challenging problem in bioinformatics, owing to distal locations and context-specific roles of these elements in controlling gene regulation. Here we review the current bioinformatics methodologies and resources available for systematic discovery of cis-acting regulatory elements and conserved transcription factor binding sites in the chick genome. In addition, we propose and make available, a novel workflow using computational tools that integrate CTCF analysis to predict putative insulator elements, enhancer prediction, and TFBS analysis. To demonstrate the usefulness of this computational workflow, we then use it to analyze the locus of the gene Sox2 whose developmental expression is known to be controlled by a complex array of cis-acting regulatory elements. The workflow accurately predicts most of the experimentally verified elements along with some that have not yet been discovered. A web version of the CTCF tool, together with instructions for using the workflow can be accessed from http://toolshed.g2.bx.psu.edu/view/mkhan1980/ctcf_analysis. For local installation of the tool, relevant Perl scripts and instructions are provided in the directory named "code" in the supplementary materials.

  11. Regulatory Regions of the Homeotic Gene Proboscipedia Are Sensitive to Chromosomal Pairing

    PubMed Central

    Kapoun, A. M.; Kaufman, T. C.

    1995-01-01

    We have identified regulatory regions of the homeotic gene proboscipedia that are capable of repressing a linked white minigene in a manner that is sensitive to chromosomal pairing. Normally, the eye color of transformants containing white in a P-element vector is affected by the number of copies of the transgene; homozygous flies have darker eyes than heterozygotes. However, we found that flies homozygous for select pb DNA-containing transgenes had lighter eyes than heterozygotes. Several pb DNA fragments are capable of causing this pairing sensitive (PS) negative regulation of white. Two fragments in the upstream DNA of pb, 0.58 and 0.98 kb, are PS; additionally, two PS sites are located in the second intron, including a 0.5-kb region and 49-bp sequence. This phenotype is not observed when two PS sites are located at different chromosomal insertion sites (in trans-heterozygous transgenic animals), indicating that the pb-DNA-mediated repression of white is dependent on the pairing or proximity of the PS regions. The observed phenomenon is similar to transvection in which certain alleles of a gene can complement each other, but only when homologous chromosomes are paired. Interestingly, the intronic PS regions contain positive regulatory sequences for pb, whereas the upstream PS sites contain pb negative regulatory elements. PMID:7498743

  12. Computational tools and resources for prediction and analysis of gene regulatory regions in the chick genome

    PubMed Central

    Khan, Mohsin A. F.; Soto-Jimenez, Luz Mayela; Howe, Timothy; Streit, Andrea; Sosinsky, Alona; Stern, Claudio D.

    2013-01-01

    The discovery of cis-regulatory elements is a challenging problem in bioinformatics, owing to distal locations and context-specific roles of these elements in controlling gene regulation. Here we review the current bioinformatics methodologies and resources available for systematic discovery of cis-acting regulatory elements and conserved transcription factor binding sites in the chick genome. In addition, we propose and make available, a novel workflow using computational tools that integrate CTCF analysis to predict putative insulator elements, enhancer prediction and TFBS analysis. To demonstrate the usefulness of this computational workflow, we then use it to analyze the locus of the gene Sox2 whose developmental expression is known to be controlled by a complex array of cis-acting regulatory elements. The workflow accurately predicts most of the experimentally verified elements along with some that have not yet been discovered. A web version of the CTCF tool, together with instructions for using the workflow can be accessed from http://toolshed.g2.bx.psu.edu/view/mkhan1980/ctcf_analysis. For local installation of the tool, relevant Perl scripts and instructions are provided in the directory named “code” in the supplementary materials. PMID:23355428

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

    PubMed

    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.

  14. Identification and validation of regulatory SNPs that modulate transcription factor chromatin binding and gene expression in prostate cancer

    PubMed Central

    Jin, Hong-Jian; Jung, Segun; DebRoy, Auditi R.; Davuluri, Ramana V.

    2016-01-01

    Prostate cancer (PCa) is the second most common solid tumor for cancer related deaths in American men. Genome wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with the increased risk of PCa. Because most of the susceptibility SNPs are located in noncoding regions, little is known about their functional mechanisms. We hypothesize that functional SNPs reside in cell type-specific regulatory elements that mediate the binding of critical transcription factors (TFs), which in turn result in changes in target gene expression. Using PCa-specific functional genomics data, here we identify 38 regulatory candidate SNPs and their target genes in PCa. Through risk analysis by incorporating gene expression and clinical data, we identify 6 target genes (ZG16B, ANKRD5, RERE, FAM96B, NAALADL2 and GTPBP10) as significant predictors of PCa biochemical recurrence. In addition, 5 SNPs (rs2659051, rs10936845, rs9925556, rs6057110 and rs2742624) are selected for experimental validation using Chromatin immunoprecipitation (ChIP), dual-luciferase reporter assay in LNCaP cells, showing allele-specific enhancer activity. Furthermore, we delete the rs2742624-containing region using CRISPR/Cas9 genome editing and observe the drastic downregulation of its target gene UPK3A. Taken together, our results illustrate that this new methodology can be applied to identify regulatory SNPs and their target genes that likely impact PCa risk. We suggest that similar studies can be performed to characterize regulatory variants in other diseases. PMID:27409348

  15. Plants with genetically modified events combined by conventional breeding: an assessment of the need for additional regulatory data.

    PubMed

    Pilacinski, W; Crawford, A; Downey, R; Harvey, B; Huber, S; Hunst, P; Lahman, L K; MacIntosh, S; Pohl, M; Rickard, C; Tagliani, L; Weber, N

    2011-01-01

    Crop varieties with multiple GM events combined by conventional breeding have become important in global agriculture. The regulatory requirements in different countries for such products vary considerably, placing an additional burden on regulatory agencies in countries where the submission of additional data is required and delaying the introduction of innovative products to meet agricultural needs. The process of conventional plant breeding has predictably provided safe food and feed products both historically and in the modern era of plant breeding. Thus, previously approved GM events that have been combined by conventional plant breeding and contain GM traits that are not likely to interact in a manner affecting safety should be considered to be as safe as their conventional counterparts. Such combined GM event crop varieties should require little, if any, additional regulatory data to meet regulatory requirements.

  16. Evolutionary analysis of the cis-regulatory region of the spicule matrix gene SM50 in strongylocentrotid sea urchins.

    PubMed

    Walters, Jenna; Binkley, Elaine; Haygood, Ralph; Romano, Laura A

    2008-03-15

    An evolutionary analysis of transcriptional regulation is essential to understanding the molecular basis of phenotypic diversity. The sea urchin is an ideal system in which to explore the functional consequence of variation in cis-regulatory sequences. We are particularly interested in the evolution of genes involved in the patterning and synthesis of its larval skeleton. This study focuses on the cis-regulatory region of SM50, which has already been characterized to a considerable extent in the purple sea urchin, Strongylocentrotus purpuratus. We have isolated the cis-regulatory region from 15 individuals of S. purpuratus as well as seven closely related species in the family Strongylocentrotidae. We have performed a variety of statistical tests and present evidence that the cis-regulatory elements upstream of the SM50 gene have been subject to positive selection along the lineage leading to S. purpuratus. In addition, we have performed electrophoretic mobility shift assays (EMSAs) and demonstrate that nucleotide substitutions within Element C affect the ability of nuclear proteins to bind to this cis-regulatory element among members of the family Strongylocentrotidae. We speculate that such changes in SM50 and other genes could accumulate to produce altered patterns of gene expression with functional consequences during skeleton formation.

  17. Applying Attractor Dynamics to Infer Gene Regulatory Interactions Involved in Cellular Differentiation.

    PubMed

    Ghaffarizadeh, Ahmadreza; Podgorski, Gregory J; Flann, Nicholas S

    2017-02-27

    The dynamics of gene regulatory networks (GRNs) guide cellular differentiation. Determining the ways regulatory genes control expression of their targets is essential to understand and control cellular differentiation. The way a regulatory gene controls its target can be expressed as a gene regulatory function. Manual derivation of these regulatory functions is slow, error-prone and difficult to update as new information arises. Automating this process is a significant challenge and the subject of intensive effort. This work presents a novel approach to discovering biologically plausible gene regulatory interactions that control cellular differentiation. This method integrates known cell type expression data, genetic interactions, and knowledge of the effects of gene knockouts to determine likely GRN regulatory functions. We employ a genetic algorithm to search for candidate GRNs that use a set of transcription factors that control differentiation within a lineage. Nested canalyzing functions are used to constrain the search space to biologically plausible networks. The method identifies an ensemble of GRNs whose dynamics reproduce the gene expression pattern for each cell type within a particular lineage. The method's effectiveness was tested by inferring consensus GRNs for myeloid and pancreatic cell differentiation and comparing the predicted gene regulatory interactions to manually derived interactions. We identified many regulatory interactions reported in the literature and also found differences from published reports. These discrepancies suggest areas for biological studies of myeloid and pancreatic differentiation. We also performed a study that used defined synthetic networks to evaluate the accuracy of the automated search method and found that the search algorithm was able to discover the regulatory interactions in these defined networks with high accuracy. We suggest that the GRN functions derived from the methods described here can be used to fill

  18. Large-scale profiling and identification of potential regulatory mechanisms for allelic gene expression in colorectal cancer cells.

    PubMed

    Lee, Robin Dong-Woo; Song, Min-Young; Lee, Jong-Keuk

    2013-01-01

    Allelic variation in gene expression is common in humans and this variation is associated with phenotypic variation. In this study, we employed high-density single nucleotide polymorphism (SNP) chips containing 13,900 exonic SNPs to identify genes with allelic gene expression in cells from colorectal cancer cell lines. We found 2 monoallelically expressed genes (ERAP2 and MYLK4), 32 genes with an allelic imbalance in their expression, and 13 genes showing allele substitution by RNA editing. Among a total of 34 allelically expressed genes in colorectal cancer cells, 15 genes (44.1%) were associated with cis-acting eQTL, indicating that large portions of allelically expressed genes are regulated by cis-acting mechanisms of gene expression. In addition, potential regulatory variants present in the proximal promoter regions of genes showing either monoallelic expression or allelic imbalance were not tightly linked with coding SNPs, which were detected with allelic gene expression. These results suggest that multiple rare variants could be involved in the cis-acting regulatory mechanism of allelic gene expression. In the comparison with allelic gene expression data from Centre d'Etude du Polymorphisme Humain (CEPH) family B cells, 12 genes showed B-cell specific allelic imbalance and 1 noncoding SNP showed colorectal cancer cell-specific allelic imbalance. In addition, different patterns of allele substitution were observed between B cells and colorectal cancer cells. Overall, our study not only indicates that allelic gene expression is common in colorectal cancer cells, but our study also provides a better understanding of allele-specific gene expression in colorectal cancer cells.

  19. Gene regulatory networks and their applications: understanding biological and medical problems in terms of networks

    PubMed Central

    Emmert-Streib, Frank; Dehmer, Matthias; Haibe-Kains, Benjamin

    2014-01-01

    In recent years gene regulatory networks (GRNs) have attracted a lot of interest and many methods have been introduced for their statistical inference from gene expression data. However, despite their popularity, GRNs are widely misunderstood. For this reason, we provide in this paper a general discussion and perspective of gene regulatory networks. Specifically, we discuss their meaning, the consistency among different network inference methods, ensemble methods, the assessment of GRNs, the estimated number of existing GRNs and their usage in different application domains. Furthermore, we discuss open questions and necessary steps in order to utilize gene regulatory networks in a clinical context and for personalized medicine. PMID:25364745

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

    PubMed Central

    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

    2016-01-01

    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 (P<0.0001) and in patients with intermediate cytogenetic risk (P<0.0001) accompanied by a high white blood cell count (P=0.0032). DNA-methylation regulatory gene 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. PMID:27247325

  1. Creating and validating cis-regulatory maps of tissue-specific gene expression regulation.

    PubMed

    O'Connor, Timothy R; Bailey, Timothy L

    2014-01-01

    Predicting which genomic regions control the transcription of a given gene is a challenge. We present a novel computational approach for creating and validating maps that associate genomic regions (cis-regulatory modules-CRMs) with genes. The method infers regulatory relationships that explain gene expression observed in a test tissue using widely available genomic data for 'other' tissues. To predict the regulatory targets of a CRM, we use cross-tissue correlation between histone modifications present at the CRM and expression at genes within 1 Mbp of it. To validate cis-regulatory maps, we show that they yield more accurate models of gene expression than carefully constructed control maps. These gene expression models predict observed gene expression from transcription factor binding in the CRMs linked to that gene. We show that our maps are able to identify long-range regulatory interactions and improve substantially over maps linking genes and CRMs based on either the control maps or a 'nearest neighbor' heuristic. Our results also show that it is essential to include CRMs predicted in multiple tissues during map-building, that H3K27ac is the most informative histone modification, and that CAGE is the most informative measure of gene expression for creating cis-regulatory maps.

  2. The effect of hyperammonemia on myostatin and myogenic regulatory factor gene expression in broiler embryos

    PubMed Central

    Stern, R.A.; Ashwell, C.M.; Dasarathy, S.; Mozdziak, P.E.

    2015-01-01

    Myogenesis is facilitated by four myogenic regulatory factors and is significantly inhibited by myostatin. The objective of the current study was to examine embryonic gene regulation of myostatin/myogenic regulatory factors, and subsequent manipulations of protein synthesis, in broiler embryos under induced hyperammonemia. Broiler eggs were injected with ammonium acetate solution four times over 48 hours beginning on either embryonic day (ED) 15 or 17. Serum ammonia concentration was significantly higher (P < 0.05) in ammonium acetate injected embryos for both ED17 and ED19 collected samples when compared to sham-injected controls. Expression of mRNA, extracted from pectoralis major of experimental and control embryos, was measured using real-time quantitative PCR for myostatin, myogenic regulatory factors myogenic factor 5, myogenic determination factor 1, myogenin, myogenic regulatory factor 4, and paired box 7. A significantly lower (P < 0.01) myostatin expression was accompanied by a higher serum ammonia concentration in both ED17 and ED19 collected samples. Myogenic factor 5 expression was higher (P < 0.05) in ED17 collected samples administered ammonium acetate. In both ED17 and ED19 collected samples, myogenic regulatory factor 4 was lower (P ≤ 0.05) in ammonium acetate injected embryos. No significant difference was seen in myogenic determination factor 1, myogenin, or paired box 7 expression between treatment groups for either age of sample collection. Additionally, there was no significant difference in BrdU staining of histological samples taken from treated and control embryos. Myostatin protein levels were evaluated by Western blot analysis, and also showed lower myostatin expression (P < 0.05). Overall, it appears possible to inhibit myostatin expression through hyperammonemia, which is expected to have a positive effect on embryonic myogenesis and postnatal muscle growth. PMID:25689990

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

    PubMed Central

    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

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

    PubMed

    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

    2017-02-28

    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.

  5. Prior knowledge driven Granger causality analysis on gene regulatory network discovery

    SciTech Connect

    Yao, Shun; Yoo, Shinjae; Yu, Dantong

    2015-08-28

    Our study focuses on discovering gene regulatory networks from time series gene expression data using the Granger causality (GC) model. However, the number of available time points (T) usually is much smaller than the number of target genes (n) in biological datasets. The widely applied pairwise GC model (PGC) and other regularization strategies can lead to a significant number of false identifications when n>>T. In this study, we proposed a new method, viz., CGC-2SPR (CGC using two-step prior Ridge regularization) to resolve the problem by incorporating prior biological knowledge about a target gene data set. In our simulation experiments, the propose new methodology CGC-2SPR showed significant performance improvement in terms of accuracy over other widely used GC modeling (PGC, Ridge and Lasso) and MI-based (MRNET and ARACNE) methods. In addition, we applied CGC-2SPR to a real biological dataset, i.e., the yeast metabolic cycle, and discovered more true positive edges with CGC-2SPR than with the other existing methods. In our research, we noticed a “ 1+1>2” effect when we combined prior knowledge and gene expression data to discover regulatory networks. Based on causality networks, we made a functional prediction that the Abm1 gene (its functions previously were unknown) might be related to the yeast’s responses to different levels of glucose. In conclusion, our research improves causality modeling by combining heterogeneous knowledge, which is well aligned with the future direction in system biology. Furthermore, we proposed a method of Monte Carlo significance estimation (MCSE) to calculate the edge significances which provide statistical meanings to the discovered causality networks. All of our data and source codes will be available under the link https://bitbucket.org/dtyu/granger-causality/wiki/Home.

  6. Prior knowledge driven Granger causality analysis on gene regulatory network discovery

    DOE PAGES

    Yao, Shun; Yoo, Shinjae; Yu, Dantong

    2015-08-28

    Our study focuses on discovering gene regulatory networks from time series gene expression data using the Granger causality (GC) model. However, the number of available time points (T) usually is much smaller than the number of target genes (n) in biological datasets. The widely applied pairwise GC model (PGC) and other regularization strategies can lead to a significant number of false identifications when n>>T. In this study, we proposed a new method, viz., CGC-2SPR (CGC using two-step prior Ridge regularization) to resolve the problem by incorporating prior biological knowledge about a target gene data set. In our simulation experiments, themore » propose new methodology CGC-2SPR showed significant performance improvement in terms of accuracy over other widely used GC modeling (PGC, Ridge and Lasso) and MI-based (MRNET and ARACNE) methods. In addition, we applied CGC-2SPR to a real biological dataset, i.e., the yeast metabolic cycle, and discovered more true positive edges with CGC-2SPR than with the other existing methods. In our research, we noticed a “ 1+1>2” effect when we combined prior knowledge and gene expression data to discover regulatory networks. Based on causality networks, we made a functional prediction that the Abm1 gene (its functions previously were unknown) might be related to the yeast’s responses to different levels of glucose. In conclusion, our research improves causality modeling by combining heterogeneous knowledge, which is well aligned with the future direction in system biology. Furthermore, we proposed a method of Monte Carlo significance estimation (MCSE) to calculate the edge significances which provide statistical meanings to the discovered causality networks. All of our data and source codes will be available under the link https://bitbucket.org/dtyu/granger-causality/wiki/Home.« less

  7. Reconstruction of the regulatory network for Bacillus subtilis and reconciliation with gene expression data

    SciTech Connect

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

    2016-03-18

    Here, 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

  8. Novel insights into the regulatory roles of gene hshB in Xanthomonas oryzae pv. oryzicola.

    PubMed

    Song, Zhiwei; Zhao, Yancun; Qian, Guoliang; Odhiambo, Benard Omondi; Liu, Fengquan

    Xanthomonas oryzae pv. oryzicola causes leaf streak disease of rice. The gene hshB is a newly identified virulence-associated gene that is co-regulated by diffusible signal factor signaling and global regulator Clp in X. oryzae pv. oryzicola. Our previous study showed that mutation of hshB remarkably impaired the virulence, extracellular protease activity, extracellular polysaccharide production and resistance to oxidative stress of X. oryzae pv. oryzicola. In this study, the regulatory role of hshB in X. oryzae pv .oryzicola was expanded. Results showed that hshB was also required for cell swimming motility. Transcriptome analysis showed that 305 genes were significantly differentially expressed after deletion of hshB in X. oryzae pv. oryzicola. Further analysis of transcriptome data indicated that the differentially expressed genes focused on two aspects: namely, cell motility and cell signal transduction. This finding strongly identified the closely related function of hshB to cell motility and signal transduction. In addition, the mutation of hshB of X. oryzae pv. oryzicola enhanced biofilm formation. Collectively, the study showed novel functions of gene hshB in cell motility and biofilm formation by transcriptome analysis, thus expanding our understanding of the roles of gene hshB in the pathogenic X. oryzae pv. oryzicola.

  9. A spatially dynamic cohort of regulatory genes in the endomesodermal gene network of the sea urchin embryo.

    PubMed

    Smith, Joel; Kraemer, Ebba; Liu, Hongdau; Theodoris, Christina; Davidson, Eric

    2008-01-15

    A gene regulatory network subcircuit comprising the otx, wnt8, and blimp1 genes accounts for a moving torus of gene expression that sweeps concentrically across the vegetal domain of the sea urchin embryo. Here we confirm by mutation the inputs into the blimp1cis-regulatory module predicted by network analysis. Its essential design feature is that it includes both activation and autorepression sites. The wnt8 gene is functionally linked into the subcircuit in that cells receiving this ligand generate a beta-catenin/Tcf input required for blimp1 expression, while the wnt8 gene in turn requires a Blimp1 input. Their torus-like spatial expression patterns and gene regulatory analysis indicate that the genes even-skipped and hox11/13b are also entrained by this subcircuit. We verify the cis-regulatory inputs of even-skipped predicted by network analysis. These include activation by beta-catenin/Tcf and Blimp1, repression within the torus by Hox11/13b, and repression outside the torus by Tcf in the absence of Wnt8 signal input. Thus even-skipped and hox11/13b, along with blimp1 and wnt8, are members of a cohort of torus genes with similar regulatory inputs and similar, though slightly out-of-phase, expression patterns, which reflect differences in cis-regulatory design.

  10. Regulatory Divergence between Parental Alleles Determines Gene Expression Patterns in Hybrids

    PubMed Central

    Combes, Marie-Christine; Hueber, Yann; Dereeper, Alexis; Rialle, Stéphanie; Herrera, Juan-Carlos; Lashermes, Philippe

    2015-01-01

    Both hybridization and allopolyploidization generate novel phenotypes by conciliating divergent genomes and regulatory networks in the same cellular context. To understand the rewiring of gene expression in hybrids, the total expression of 21,025 genes and the allele-specific expression of over 11,000 genes were quantified in interspecific hybrids and their parental species, Coffea canephora and Coffea eugenioides using RNA-seq technology. Between parental species, cis- and trans-regulatory divergences affected around 32% and 35% of analyzed genes, respectively, with nearly 17% of them showing both. The relative importance of trans-regulatory divergences between both species could be related to their low genetic divergence and perennial habit. In hybrids, among divergently expressed genes between parental species and hybrids, 77% was expressed like one parent (expression level dominance), including 65% like C. eugenioides. Gene expression was shown to result from the expression of both alleles affected by intertwined parental trans-regulatory factors. A strong impact of C. eugenioides trans-regulatory factors on the upregulation of C. canephora alleles was revealed. The gene expression patterns appeared determined by complex combinations of cis- and trans-regulatory divergences. In particular, the observed biased expression level dominance seemed to be derived from the asymmetric effects of trans-regulatory parental factors on regulation of alleles. More generally, this study illustrates the effects of divergent trans-regulatory parental factors on the gene expression pattern in hybrids. The characteristics of the transcriptional response to hybridization appear to be determined by the compatibility of gene regulatory networks and therefore depend on genetic divergences between the parental species and their evolutionary history. PMID:25819221

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

    PubMed

    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.

  12. A Survey of Statistical Models for Reverse Engineering Gene Regulatory Networks

    PubMed Central

    Huang, Yufei; Tienda-Luna, Isabel M.; Wang, Yufeng

    2009-01-01

    Statistical models for reverse engineering gene regulatory networks are surveyed in this article. To provide readers with a system-level view of the modeling issues in this research, a graphical modeling framework is proposed. This framework serves as the scaffolding on which the review of different models can be systematically assembled. Based on the framework, we review many existing models for many aspects of gene regulation; the pros and cons of each model are discussed. In addition, network inference algorithms are also surveyed under the graphical modeling framework by the categories of point solutions and probabilistic solutions and the connections and differences among the algorithms are provided. This survey has the potential to elucidate the development and future of reverse engineering GRNs and bring statistical signal processing closer to the core of this research. PMID:20046885

  13. Quantitative functional interrelations within the cis-regulatory system of the S. purpuratus Endo16 gene.

    PubMed

    Yuh, C H; Moore, J G; Davidson, E H

    1996-12-01

    similar approach to analyze the repressive activity of the three Endo16 cis-regulatory modules that act negatively in controlling spatial expression. The evidence obtained confirms that the repressive modules act only by affecting the output of module A (C.-H. Yuh and E. Davidson (1996) Development 122, 1069-1082). A new hierarchical model of the cis-regulatory system was formulated in which module A plays a central integrating role, and which also implies specific functions for certain DNA-binding sites within the basal promoter fragment of the gene. Additional kinetic experiments were then carried out, and key aspects of the model were confirmed.

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

    PubMed Central

    Kikuta, Hiroshi; Laplante, Mary; Navratilova, Pavla; Komisarczuk, Anna Z.; Engström, Pär G.; Fredman, David; Akalin, Altuna; Caccamo, Mario; Sealy, Ian; Howe, Kerstin; Ghislain, Julien; Pezeron, Guillaume; Mourrain, Philippe; Ellingsen, Staale; Oates, Andrew C.; Thisse, Christine; Thisse, Bernard; Foucher, Isabelle; Adolf, Birgit; Geling, Andrea; Lenhard, Boris; Becker, Thomas S.

    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 that are different from those of the target genes. Reporter insertions distal to zebrafish developmental regulatory genes pax6.1/2, rx3, id1, and fgf8 and miRNA genes mirn9-1 and mirn9-5 recapitulate the expression patterns of these genes even if located inside or beyond bystander genes, suggesting that the regulatory domain of a developmental regulatory gene can extend into and beyond adjacent transcriptional units. We termed these chromosomal segments genomic regulatory blocks (GRBs). After whole genome duplication in teleosts, GRBs, including HCNEs and target genes, were often maintained in both copies, while bystander genes were typically lost from one GRB, strongly suggesting that evolutionary pressure acts to keep the single-copy GRBs of higher vertebrates intact. We show that loss of bystander genes and other mutational events suffered by duplicated GRBs in teleost genomes permits target gene identification and HCNE/target gene assignment. These findings explain the absence of evolutionary breakpoints from large vertebrate chromosomal segments and will aid in the recognition of position effect mutations within human GRBs. PMID:17387144

  15. Mining Gene Regulatory Networks by Neural Modeling of Expression Time-Series.

    PubMed

    Rubiolo, Mariano; Milone, Diego H; Stegmayer, Georgina

    2015-01-01

    Discovering gene regulatory networks from data is one of the most studied topics in recent years. Neural networks can be successfully used to infer an underlying gene network by modeling expression profiles as times series. This work proposes a novel method based on a pool of neural networks for obtaining a gene regulatory network from a gene expression dataset. They are used for modeling each possible interaction between pairs of genes in the dataset, and a set of mining rules is applied to accurately detect the subjacent relations among genes. The results obtained on artificial and real datasets confirm the method effectiveness for discovering regulatory networks from a proper modeling of the temporal dynamics of gene expression profiles.

  16. [Requirements for drug approval and additional benefits assessment: Regulatory aspects and experiences].

    PubMed

    Broich, K; Löbker, W; Schulte, A; Beinlich, P; Müller, T

    2016-04-01

    The early assessment of benefits of newly approved drugs with novel active substances or new applications, which came into force on 1 January 2011 still represents a challenge to all parties involved. This article highlights the definitions, regulatory requirements and interaction between drug marketing approval and early assessment of benefits in Germany. The constellation of an extensively harmonized European and even international drug authorization process with a predominantly national regulation of drug reimbursement situation inevitably causes friction, which could be markedly reduced through early joint advisory discussions during the planning phase for pivotal clinical trials. During the year 2015 the Federal Institute for Drugs and Medical Devices (BfArM) carried out 300 scientific advice procedures of which 34 were concerned with applications in the field of indications for the central nervous system (CNS). In comparison 98 advisory meetings were held by the Federal Joint Committee (G-BA) of which the BfArM provided advice in 12 instances and in 2 cases on CNS indications. Study design, endpoints and appropriate comparative therapies are the key issues in exchanges and discussions between the BfArM, the G‑BA and applicants. Under these aspects the BfArM and G‑BA promote an early and consistent involvement in early advice procedures regarding the prerequisites for drug approval and assessment of additional benefits.

  17. A Dynamic Gene Regulatory Network Model That Recovers the Cyclic Behavior of Arabidopsis thaliana Cell Cycle.

    PubMed

    Ortiz-Gutiérrez, Elizabeth; García-Cruz, Karla; Azpeitia, Eugenio; Castillo, Aaron; Sánchez, María de la Paz; Álvarez-Buylla, Elena R

    2015-09-01

    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.

  18. Superior Cervical Ganglia Neurons Induce Foxp3+ Regulatory T Cells via Calcitonin Gene-Related Peptide.

    PubMed

    Szklany, Kirsten; Ruiter, Evelyn; Mian, Firoz; Kunze, Wolfgang; Bienenstock, John; Forsythe, Paul; Karimi, Khalil

    2016-01-01

    The nervous and immune systems communicate bidirectionally, utilizing diverse molecular signals including cytokines and neurotransmitters to provide an integrated response to changes in the body's internal and external environment. Although, neuro-immune interactions are becoming better understood under inflammatory circumstances and it has been evidenced that interaction between neurons and T cells results in the conversion of encephalitogenic T cells to T regulatory cells, relatively little is known about the communication between neurons and naïve T cells. Here, we demonstrate that following co-culture of naïve CD4+ T cells with superior cervical ganglion neurons, the percentage of Foxp3 expressing CD4+CD25+ cells significantly increased. This was mediated in part by immune-regulatory cytokines TGF-β and IL-10, as well as the neuropeptide calcitonin gene-related peptide while vasoactive intestinal peptide was shown to play no role in generation of T regulatory cells. Additionally, T cells co-cultured with neurons showed a decrease in the levels of pro-inflammatory cytokine IFN-γ released upon in vitro stimulation. These findings suggest that the generation of Tregs may be promoted by naïve CD4+ T cell: neuron interaction through the release of neuropeptide CGRP.

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

    PubMed Central

    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

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

    ERIC Educational Resources Information Center

    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…

  1. Cell type-selective disease-association of genes under high regulatory load.

    PubMed

    Galhardo, Mafalda; Berninger, Philipp; Nguyen, Thanh-Phuong; Sauter, Thomas; Sinkkonen, Lasse

    2015-10-15

    We previously showed that disease-linked metabolic genes are often under combinatorial regulation. Using the genome-wide ChIP-Seq binding profiles for 93 transcription factors in nine different cell lines, we show that genes under high regulatory load are significantly enriched for disease-association across cell types. We find that transcription factor load correlates with the enhancer load of the genes and thereby allows the identification of genes under high regulatory load by epigenomic mapping of active enhancers. Identification of the high enhancer load genes across 139 samples from 96 different cell and tissue types reveals a consistent enrichment for disease-associated genes in a cell type-selective manner. The underlying genes are not limited to super-enhancer genes and show several types of disease-association evidence beyond genetic variation (such as biomarkers). Interestingly, the high regulatory load genes are involved in more KEGG pathways than expected by chance, exhibit increased betweenness centrality in the interaction network of liver disease genes, and carry longer 3' UTRs with more microRNA (miRNA) binding sites than genes on average, suggesting a role as hubs integrating signals within regulatory networks. In summary, epigenetic mapping of active enhancers presents a promising and unbiased approach for identification of novel disease genes in a cell type-selective manner.

  2. Cell type-selective disease-association of genes under high regulatory load

    PubMed Central

    Galhardo, Mafalda; Berninger, Philipp; Nguyen, Thanh-Phuong; Sauter, Thomas; Sinkkonen, Lasse

    2015-01-01

    We previously showed that disease-linked metabolic genes are often under combinatorial regulation. Using the genome-wide ChIP-Seq binding profiles for 93 transcription factors in nine different cell lines, we show that genes under high regulatory load are significantly enriched for disease-association across cell types. We find that transcription factor load correlates with the enhancer load of the genes and thereby allows the identification of genes under high regulatory load by epigenomic mapping of active enhancers. Identification of the high enhancer load genes across 139 samples from 96 different cell and tissue types reveals a consistent enrichment for disease-associated genes in a cell type-selective manner. The underlying genes are not limited to super-enhancer genes and show several types of disease-association evidence beyond genetic variation (such as biomarkers). Interestingly, the high regulatory load genes are involved in more KEGG pathways than expected by chance, exhibit increased betweenness centrality in the interaction network of liver disease genes, and carry longer 3′ UTRs with more microRNA (miRNA) binding sites than genes on average, suggesting a role as hubs integrating signals within regulatory networks. In summary, epigenetic mapping of active enhancers presents a promising and unbiased approach for identification of novel disease genes in a cell type-selective manner. PMID:26338775

  3. cis regulatory requirements for hypodermal cell-specific expression of the Caenorhabditis elegans cuticle collagen gene dpy-7.

    PubMed Central

    Gilleard, J S; Barry, J D; Johnstone, I L

    1997-01-01

    The Caenorhabditis elegans cuticle collagens are encoded by a multigene family of between 50 and 100 members and are the major component of the nematode cuticular exoskeleton. They are synthesized in the hypodermis prior to secretion and incorporation into the cuticle and exhibit complex patterns of spatial and temporal expression. We have investigated the cis regulatory requirements for tissue- and stage-specific expression of the cuticle collagen gene dpy-7 and have identified a compact regulatory element which is sufficient to specify hypodermal cell reporter gene expression. This element appears to be a true tissue-specific promoter element, since it encompasses the dpy-7 transcription initiation sites and functions in an orientation-dependent manner. We have also shown, by interspecies transformation experiments, that the dpy-7 cis regulatory elements are functionally conserved between C. elegans and C. briggsae, and comparative sequence analysis supports the importance of the regulatory sequence that we have identified by reporter gene analysis. All of our data suggest that the spatial expression of the dpy-7 cuticle collagen gene is established essentially by a small tissue-specific promoter element and does not require upstream activator or repressor elements. In addition, we have found the DPY-7 polypeptide is very highly conserved between the two species and that the C. briggsae polypeptide can function appropriately within the C. elegans cuticle. This finding suggests a remarkably high level of conservation of individual cuticle components, and their interactions, between these two nematode species. PMID:9121480

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

    PubMed

    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.

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

    NASA Technical Reports Server (NTRS)

    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

  6. Reconstructing differentially co-expressed gene modules and regulatory networks of soybean cells

    PubMed Central

    2012-01-01

    Background Current experimental evidence indicates that functionally related genes show coordinated expression in order to perform their cellular functions. In this way, the cell transcriptional machinery can respond optimally to internal or external stimuli. This provides a research opportunity to identify and study co-expressed gene modules whose transcription is controlled by shared gene regulatory networks. Results We developed and integrated a set of computational methods of differential gene expression analysis, gene clustering, gene network inference, gene function prediction, and DNA motif identification to automatically identify differentially co-expressed gene modules, reconstruct their regulatory networks, and validate their correctness. We tested the methods using microarray data derived from soybean cells grown under various stress conditions. Our methods were able to identify 42 coherent gene modules within which average gene expression correlation coefficients are greater than 0.8 and reconstruct their putative regulatory networks. A total of 32 modules and their regulatory networks were further validated by the coherence of predicted gene functions and the consistency of putative transcription factor binding motifs. Approximately half of the 32 modules were partially supported by the literature, which demonstrates that the bioinformatic methods used can help elucidate the molecular responses of soybean cells upon various environmental stresses. Conclusions The bioinformatics methods and genome-wide data sources for gene expression, clustering, regulation, and function analysis were integrated seamlessly into one modular protocol to systematically analyze and infer modules and networks from only differential expression genes in soybean cells grown under stress conditions. Our approach appears to effectively reduce the complexity of the problem, and is sufficiently robust and accurate to generate a rather complete and detailed view of putative soybean

  7. Gene Expression during the Generation and Activation of Mouse Neutrophils: Implication of Novel Functional and Regulatory Pathways

    PubMed Central

    Ericson, Jeffrey A.; Duffau, Pierre; Yasuda, Kei; Ortiz-Lopez, Adriana; Rothamel, Katherine; Rifkin, Ian R.; Monach, Paul A.

    2014-01-01

    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 ImmGen regulatory

  8. Reverse engineering and analysis of genome-wide gene regulatory networks from gene expression profiles using high-performance computing.

    PubMed

    Belcastro, Vincenzo; Gregoretti, Francesco; Siciliano, Velia; Santoro, Michele; D'Angelo, Giovanni; Oliva, Gennaro; di Bernardo, Diego

    2012-01-01

    Regulation of gene expression is a carefully regulated phenomenon in the cell. “Reverse-engineering” algorithms try to reconstruct the regulatory interactions among genes from genome-scale measurements of gene expression profiles (microarrays). Mammalian cells express tens of thousands of genes; hence, hundreds of gene expression profiles are necessary in order to have acceptable statistical evidence of interactions between genes. As the number of profiles to be analyzed increases, so do computational costs and memory requirements. In this work, we designed and developed a parallel computing algorithm to reverse-engineer genome-scale gene regulatory networks from thousands of gene expression profiles. The algorithm is based on computing pairwise Mutual Information between each gene-pair. We successfully tested it to reverse engineer the Mus Musculus (mouse) gene regulatory network in liver from gene expression profiles collected from a public repository. A parallel hierarchical clustering algorithm was implemented to discover “communities” within the gene network. Network communities are enriched for genes involved in the same biological functions. The inferred network was used to identify two mitochondrial proteins.

  9. Combinatorial motif analysis of regulatory gene expression in Mafb deficient macrophages

    PubMed Central

    2011-01-01

    Background Deficiency of the transcription factor MafB, which is normally expressed in macrophages, can underlie cellular dysfunction associated with a range of autoimmune diseases and arteriosclerosis. MafB has important roles in cell differentiation and regulation of target gene expression; however, the mechanisms of this regulation and the identities of other transcription factors with which MafB interacts remain uncertain. Bioinformatics methods provide a valuable approach for elucidating the nature of these interactions with transcriptional regulatory elements from a large number of DNA sequences. In particular, identification of patterns of co-occurrence of regulatory cis-elements (motifs) offers a robust approach. Results Here, the directional relationships among several functional motifs were evaluated using the Log-linear Graphical Model (LGM) after extraction and search for evolutionarily conserved motifs. This analysis highlighted GATA-1 motifs and 5’AT-rich half Maf recognition elements (MAREs) in promoter regions of 18 genes that were down-regulated in Mafb deficient macrophages. GATA-1 motifs and MafB motifs could regulate expression of these genes in both a negative and positive manner, respectively. The validity of this conclusion was tested with data from a luciferase assay that used a C1qa promoter construct carrying both the GATA-1 motifs and MAREs. GATA-1 was found to inhibit the activity of the C1qa promoter with the GATA-1 motifs and MafB motifs. Conclusions These observations suggest that both the GATA-1 motifs and MafB motifs are important for lineage specific expression of C1qa. In addition, these findings show that analysis of combinations of evolutionarily conserved motifs can be successfully used to identify patterns of gene regulation. PMID:22784578

  10. Transfer of a large gene regulatory apparatus to a new developmental address in echinoid evolution.

    PubMed

    Gao, Feng; Davidson, Eric H

    2008-04-22

    Of the five echinoderm classes, only the modern sea urchins (euechinoids) generate a precociously specified embryonic micromere lineage that ingresses before gastrulation and then secretes the biomineral embryonic skeleton. The gene regulatory network (GRN) underlying the specification and differentiation of this lineage is now known. Many of the same differentiation genes as are used in the biomineralization of the embryo skeleton are also used to make the similar biomineral of the spines and test plates of the adult body. Here, we determine the components of the regulatory state upstream of these differentiation genes that are shared between embryonic and adult skeletogenesis. An abrupt "break point" in the micromere GRN is thus revealed, on one side of which most of the regulatory genes are used in both, and on the other side of which the regulatory apparatus is entirely micromere-specific. This reveals the specific linkages of the micromere GRN forged in the evolutionary process by which the skeletogenic gene batteries were caused to be activated in the embryonic micromere lineage. We also show, by comparison with adult skeletogenesis in the sea star, a distant echinoderm outgroup, that the regulatory apparatus responsible for driving the skeletogenic differentiation gene batteries is an ancient pleisiomorphic aspect of the echinoderm-specific regulatory heritage.

  11. CrBPF1 overexpression alters transcript levels of terpenoid indole alkaloid biosynthetic and regulatory genes

    PubMed Central

    Li, Chun Yao; Leopold, Alex L.; Sander, Guy W.; Shanks, Jacqueline V.; Zhao, Le; Gibson, Susan I.

    2015-01-01

    Terpenoid indole alkaloid (TIA) biosynthesis in Catharanthus roseus is a complex and highly regulated process. Understanding the biochemistry and regulation of the TIA pathway is of particular interest as it may allow the engineering of plants to accumulate higher levels of pharmaceutically important alkaloids. Toward this end, we generated a transgenic C. roseus hairy root line that overexpresses the CrBPF1 transcriptional activator under the control of a β-estradiol inducible promoter. CrBPF1 is a MYB-like protein that was previously postulated to help regulate the expression of the TIA biosynthetic gene STR. However, the role of CrBPF1 in regulation of the TIA and related pathways had not been previously characterized. In this study, transcriptional profiling revealed that overexpression of CrBPF1 results in increased transcript levels for genes from both the indole and terpenoid biosynthetic pathways that provide precursors for TIA biosynthesis, as well as for genes in the TIA biosynthetic pathway. In addition, overexpression of CrBPF1 causes increases in the transcript levels for 11 out of 13 genes postulated to act as transcriptional regulators of genes from the TIA and TIA feeder pathways. Interestingly, overexpression of CrBPF1 causes increased transcript levels for both TIA transcriptional activators and repressors. Despite the fact that CrBPF1 overexpression affects transcript levels of a large percentage of TIA biosynthetic and regulatory genes, CrBPF1 overexpression has only very modest effects on the levels of the TIA metabolites analyzed. This finding may be due, at least in part, to the up-regulation of both transcriptional activators and repressors in response to CrBPF1 overexpression, suggesting that CrBPF1 may serve as a “fine-tune” regulator for TIA biosynthesis, acting to help regulate the timing and amplitude of TIA gene expression. PMID:26483828

  12. Use of H19 Gene Regulatory Sequences in DNA-Based Therapy for Pancreatic Cancer

    PubMed Central

    Scaiewicz, V.; Sorin, V.; Fellig, Y.; Birman, T.; Mizrahi, A.; Galula, J.; Abu-lail, R.; Shneider, T.; Ohana, P.; Buscail, L.; Hochberg, A.; Czerniak, A.

    2010-01-01

    Pancreatic cancer is the eighth most common cause of death from cancer in the world, for which palliative treatments are not effective and frequently accompanied by severe side effects. We propose a DNA-based therapy for pancreatic cancer using a nonviral vector, expressing the diphtheria toxin A chain under the control of the H19 gene regulatory sequences. The H19 gene is an oncofetal RNA expressed during embryo development and in several types of cancer. We tested the expression of H19 gene in patients, and found that 65% of human pancreatic tumors analyzed showed moderated to strong expression of the gene. In vitro experiments showed that the vector was effective in reducing Luciferase protein activity on pancreatic carcinoma cell lines. In vivo experiment results revealed tumor growth arrest in different animal models for pancreatic cancer. Differences in tumor size between control and treated groups reached a 75% in the heterotopic model (P = .037) and 50% in the orthotopic model (P = .007). In addition, no visible metastases were found in the treated group of the orthotopic model. These results indicate that the treatment with the vector DTA-H19 might be a viable new therapeutic option for patients with unresectable pancreatic cancer. PMID:21052499

  13. An extended Kalman filtering approach to modeling nonlinear dynamic gene regulatory networks via short gene expression time series.

    PubMed

    Wang, Zidong; Liu, Xiaohui; Liu, Yurong; Liang, Jinling; Vinciotti, Veronica

    2009-01-01

    In this paper, the extended Kalman filter (EKF) algorithm is applied to model the gene regulatory network from gene time series data. The gene regulatory network is considered as a nonlinear dynamic stochastic model that consists of the gene measurement equation and the gene regulation equation. After specifying the model structure, we apply the EKF algorithm for identifying both the model parameters and the actual value of gene expression levels. It is shown that the EKF algorithm is an online estimation algorithm that can identify a large number of parameters (including parameters of nonlinear functions) through iterative procedure by using a small number of observations. Four real-world gene expression data sets are employed to demonstrate the effectiveness of the EKF algorithm, and the obtained models are evaluated from the viewpoint of bioinformatics.

  14. Methods for detecting additional genes underlying Alzheimer disease

    SciTech Connect

    Locke, P.A.; Haines, J.L.; Ter-Minassian, M.

    1994-09-01

    Alzheimer`s disease (AD) is a complex inherited disorder with proven genetic heterogeneity. To date, genes on chromosome 21 (APP) and 14 (not yet identified) are associated with early-onset familial AD, while the APOE gene on chromosome 19 is associated with both late onset familial and sporadic AD and early onset sporadic AD. Although these genes likely account for the majority of AD, many familial cases cannot be traced to any of these genes. From a set of 127 late-onset multiplex families screened for APOE, 43 (34%) families have at least one affected individual with no APOE-4 allele, suggesting an alternative genetic etiology. Simulation studies indicated that additional loci could be identified through a genomic screen with a 10 cM sieve on a subset of 21 well documented, non-APOE-4 families. Given the uncertainties in the mode of inheritance, reliance on a single analytical method could result in a missed linkage. Therefore, we have developed a strategy of using multiple overlapping yet complementary methods to detect linkage. These include sib-pair analysis and affected-pedigree-member analysis, neither of which makes assumptions about mode of inheritance, and lod score analysis (using two predefined genetic models). In order for a marker to qualify for follow-up, it must fit at least two of three criteria. These are nominal P values of 0.05 or less for the non-parametric methods, and/or a lod score greater than 1.0. Adjacent markers each fulfilling a single criterion also warrant follow-up. To date, we have screened 61 markers on chromosomes 1, 2, 3, 18, 19, 21, and 22. One marker, D2S163, generated a lod score of 1.06 ({theta} = 0.15) and an APMT statistic of 3.68 (P < 0.001). This region is currently being investigated in more detail. Updated results of this region plus additional screening data will be presented.

  15. Gene regulatory evolution and the origin of macroevolutionary novelties: insights from the neural crest.

    PubMed

    Van Otterloo, Eric; Cornell, Robert A; Medeiros, Daniel Meulemans; Garnett, Aaron T

    2013-07-01

    The appearance of novel anatomic structures during evolution is driven by changes to the networks of transcription factors, signaling pathways, and downstream effector genes controlling development. The nature of the changes to these developmental gene regulatory networks (GRNs) is poorly understood. A striking test case is the evolution of the GRN controlling development of the neural crest (NC). NC cells emerge from the neural plate border (NPB) and contribute to multiple adult structures. While all chordates have a NPB, only in vertebrates do NPB cells express all the genes constituting the neural crest GRN (NC-GRN). Interestingly, invertebrate chordates express orthologs of NC-GRN components in other tissues, revealing that during vertebrate evolution new regulatory connections emerged between transcription factors primitively expressed in the NPB and genes primitively expressed in other tissues. Such interactions could have evolved by two mechanisms. First, transcription factors primitively expressed in the NPB may have evolved new DNA and/or cofactor binding properties (protein neofunctionalization). Alternately, cis-regulatory elements driving NPB expression may have evolved near genes primitively expressed in other tissues (cis-regulatory neofunctionalization). Here we discuss how gene duplication can, in principle, promote either form of neofunctionalization. We review recent published examples of interspecies gene-swap, or regulatory-element-swap, experiments that test both models. Such experiments have yielded little evidence to support the importance of protein neofunctionalization in the emergence of the NC-GRN, but do support the importance of novel cis-regulatory elements in this process. The NC-GRN is an excellent model for the study of gene regulatory and macroevolutionary innovation.

  16. PTHGRN: unraveling post-translational hierarchical gene regulatory networks using PPI, ChIP-seq and gene expression data.

    PubMed

    Guan, Daogang; Shao, Jiaofang; Zhao, Zhongying; Wang, Panwen; Qin, Jing; Deng, Youping; Boheler, Kenneth R; Wang, Junwen; Yan, Bin

    2014-07-01

    Interactions among transcriptional factors (TFs), cofactors and other proteins or enzymes can affect transcriptional regulatory capabilities of eukaryotic organisms. Post-translational modifications (PTMs) cooperate with TFs and epigenetic alterations to constitute a hierarchical complexity in transcriptional gene regulation. While clearly implicated in biological processes, our understanding of these complex regulatory mechanisms is still limited and incomplete. Various online software have been proposed for uncovering transcriptional and epigenetic regulatory networks, however, there is a lack of effective web-based software capable of constructing underlying interactive organizations between post-translational and transcriptional regulatory components. Here, we present an open web server, post-translational hierarchical gene regulatory network (PTHGRN) to unravel relationships among PTMs, TFs, epigenetic modifications and gene expression. PTHGRN utilizes a graphical Gaussian model with partial least squares regression-based methodology, and is able to integrate protein-protein interactions, ChIP-seq and gene expression data and to capture essential regulation features behind high-throughput data. The server provides an integrative platform for users to analyze ready-to-use public high-throughput Omics resources or upload their own data for systems biology study. Users can choose various parameters in the method, build network topologies of interests and dissect their associations with biological functions. Application of the software to stem cell and breast cancer demonstrates that it is an effective tool for understanding regulatory mechanisms in biological complex systems. PTHGRN web server is publically available at web site http://www.byanbioinfo.org/pthgrn.

  17. BGRMI: A method for inferring gene regulatory networks from time-course gene expression data and its application in breast cancer research

    PubMed Central

    Iglesias-Martinez, Luis F.; Kolch, Walter; Santra, Tapesh

    2016-01-01

    Reconstructing gene regulatory networks (GRNs) from gene expression data is a challenging problem. Existing GRN reconstruction algorithms can be broadly divided into model-free and model–based methods. Typically, model-free methods have high accuracy but are computation intensive whereas model-based methods are fast but less accurate. We propose Bayesian Gene Regulation Model Inference (BGRMI), a model-based method for inferring GRNs from time-course gene expression data. BGRMI uses a Bayesian framework to calculate the probability of different models of GRNs and a heuristic search strategy to scan the model space efficiently. Using benchmark datasets, we show that BGRMI has higher/comparable accuracy at a fraction of the computational cost of competing algorithms. Additionally, it can incorporate prior knowledge of potential gene regulation mechanisms and TF hetero-dimerization processes in the GRN reconstruction process. We incorporated existing ChIP-seq data and known protein interactions between TFs in BGRMI as sources of prior knowledge to reconstruct transcription regulatory networks of proliferating and differentiating breast cancer (BC) cells from time-course gene expression data. The reconstructed networks revealed key driver genes of proliferation and differentiation in BC cells. Some of these genes were not previously studied in the context of BC, but may have clinical relevance in BC treatment. PMID:27876826

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

    PubMed Central

    Zainudin, Suhaila; Arif, Shereena M.

    2017-01-01

    Gene regulatory network (GRN) reconstruction is the process of identifying regulatory gene interactions from experimental data through computational analysis. One of the main reasons for the reduced performance of previous GRN methods had been inaccurate prediction of cascade motifs. Cascade error is defined as the wrong prediction of cascade motifs, where an indirect interaction is misinterpreted as a direct interaction. Despite the active research on various GRN prediction methods, the discussion on specific methods to solve problems related to cascade errors is still lacking. In fact, the experiments conducted by the past studies were not specifically geared towards proving the ability of GRN prediction methods in avoiding the occurrences of cascade errors. Hence, this research aims to propose Multiple Linear Regression (MLR) to infer GRN from gene expression data and to avoid wrongly inferring of an indirect interaction (A → B → C) as a direct interaction (A → C). Since the number of observations of the real experiment datasets was far less than the number of predictors, some predictors were eliminated by extracting the random subnetworks from global interaction networks via an established extraction method. In addition, the experiment was extended to assess the effectiveness of MLR in dealing with cascade error by using a novel experimental procedure that had been proposed in this work. The experiment revealed that the number of cascade errors had been very minimal. Apart from that, the Belsley collinearity test proved that multicollinearity did affect the datasets used in this experiment greatly. All the tested subnetworks obtained satisfactory results, with AUROC values above 0.5. PMID:28250767

  19. Wnt6 activates endoderm in the sea urchin gene regulatory network

    PubMed Central

    Croce, Jenifer; Range, Ryan; Wu, Shu-Yu; Miranda, Esther; Lhomond, Guy; Peng, Jeff Chieh-fu; Lepage, Thierry; McClay, David R.

    2011-01-01

    In the sea urchin, entry of β-catenin into the nuclei of the vegetal cells at 4th and 5th cleavages is necessary for activation of the endomesoderm gene regulatory network. Beyond that, little is known about how the embryo uses maternal information to initiate specification. Here, experiments establish that of the three maternal Wnts in the egg, Wnt6 is necessary for activation of endodermal genes in the endomesoderm GRN. A small region of the vegetal cortex is shown to be necessary for activation of the endomesoderm GRN. If that cortical region of the egg is removed, addition of Wnt6 rescues endoderm. At a molecular level, the vegetal cortex region contains a localized concentration of Dishevelled (Dsh) protein, a transducer of the canonical Wnt pathway; however, Wnt6 mRNA is not similarly localized. Ectopic activation of the Wnt pathway, through the expression of an activated form of β-catenin, of a dominant-negative variant of GSK-3β or of Dsh itself, rescues endomesoderm specification in eggs depleted of the vegetal cortex. Knockdown experiments in whole embryos show that absence of Wnt6 produces embryos that lack endoderm, but those embryos continue to express a number of mesoderm markers. Thus, maternal Wnt6 plus a localized vegetal cortical molecule, possibly Dsh, is necessary for endoderm specification; this has been verified in two species of sea urchin. The data also show that Wnt6 is only one of what are likely to be multiple components that are necessary for activation of the entire endomesoderm gene regulatory network. PMID:21750039

  20. DMRT gene cluster analysis in the platypus: new insights into genomic organization and regulatory regions.

    PubMed

    El-Mogharbel, Nisrine; Wakefield, Matthew; Deakin, Janine E; Tsend-Ayush, Enkhjargal; Grützner, Frank; Alsop, Amber; Ezaz, Tariq; Marshall Graves, Jennifer A

    2007-01-01

    We isolated and characterized a cluster of platypus DMRT genes and compared their arrangement, location, and sequence across vertebrates. The DMRT gene cluster on human 9p24.3 harbors, in order, DMRT1, DMRT3, and DMRT2, which share a DM domain. DMRT1 is highly conserved and involved in sexual development in vertebrates, and deletions in this region cause sex reversal in humans. Sequence comparisons of DMRT genes between species have been valuable in identifying exons, control regions, and conserved nongenic regions (CNGs). The addition of platypus sequences is expected to be particularly valuable, since monotremes fill a gap in the vertebrate genome coverage. We therefore isolated and fully sequenced platypus BAC clones containing DMRT3 and DMRT2 as well as DMRT1 and then generated multispecies alignments and ran prediction programs followed by experimental verification to annotate this gene cluster. We found that the three genes have 58-66% identity to their human orthologues, lie in the same order as in other vertebrates, and colocate on 1 of the 10 platypus sex chromosomes, X5. We also predict that optimal annotation of the newly sequenced platypus genome will be challenging. The analysis of platypus sequence revealed differences in structure and sequence of the DMRT gene cluster. Multispecies comparison was particularly effective for detecting CNGs, revealing several novel potential regulatory regions within DMRT3 and DMRT2 as well as DMRT1. RT-PCR indicated that platypus DMRT1 and DMRT3 are expressed specifically in the adult testis (and not ovary), but DMRT2 has a wider expression profile, as it does for other mammals. The platypus DMRT1 expression pattern, and its location on an X chromosome, suggests an involvement in monotreme sexual development.

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

    PubMed Central

    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

  2. The Gene Regulatory Network of Lens Induction Is Wired through Meis-Dependent Shadow Enhancers of Pax6

    PubMed Central

    Antosova, Barbora; Smolikova, Jana; Klimova, Lucie; Lachova, Jitka; Bendova, Michaela; Kozmikova, Iryna; Machon, Ondrej; Kozmik, Zbynek

    2016-01-01

    Lens induction is a classical developmental model allowing investigation of cell specification, spatiotemporal control of gene expression, as well as how transcription factors are integrated into highly complex gene regulatory networks (GRNs). Pax6 represents a key node in the gene regulatory network governing mammalian lens induction. Meis1 and Meis2 homeoproteins are considered as essential upstream regulators of Pax6 during lens morphogenesis based on their interaction with the ectoderm enhancer (EE) located upstream of Pax6 transcription start site. Despite this generally accepted regulatory pathway, Meis1-, Meis2- and EE-deficient mice have surprisingly mild eye phenotypes at placodal stage of lens development. Here, we show that simultaneous deletion of Meis1 and Meis2 in presumptive lens ectoderm results in arrested lens development in the pre-placodal stage, and neither lens placode nor lens is formed. We found that in the presumptive lens ectoderm of Meis1/Meis2 deficient embryos Pax6 expression is absent. We demonstrate using chromatin immunoprecipitation (ChIP) that in addition to EE, Meis homeoproteins bind to a remote, ultraconserved SIMO enhancer of Pax6. We further show, using in vivo gene reporter analyses, that the lens-specific activity of SIMO enhancer is dependent on the presence of three Meis binding sites, phylogenetically conserved from man to zebrafish. Genetic ablation of EE and SIMO enhancers demostrates their requirement for lens induction and uncovers an apparent redundancy at early stages of lens development. These findings identify a genetic requirement for Meis1 and Meis2 during the early steps of mammalian eye development. Moreover, they reveal an apparent robustness in the gene regulatory mechanism whereby two independent "shadow enhancers" maintain critical levels of a dosage-sensitive gene, Pax6, during lens induction. PMID:27918583

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

    PubMed

    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.

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

    PubMed Central

    Ueki, Toshiyuki; Lovley, Derek R.

    2010-01-01

    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. PMID:20660485

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

    PubMed

    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. Intrinsic noise and deviations from criticality in Boolean gene-regulatory networks

    PubMed Central

    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. Intrinsic noise and deviations from criticality in Boolean gene-regulatory networks.

    PubMed

    Villegas, Pablo; Ruiz-Franco, José; Hidalgo, Jorge; Muñoz, Miguel A

    2016-10-07

    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.

  8. Intrinsic noise and deviations from criticality in Boolean gene-regulatory networks

    NASA Astrophysics Data System (ADS)

    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.

  9. A Bayesian Framework That Integrates Heterogeneous Data for Inferring Gene Regulatory Networks

    PubMed Central

    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. PMID:25152886

  10. The INO2 and INO4 loci of Saccharomyces cerevisiae are pleiotropic regulatory genes.

    PubMed Central

    Loewy, B S; Henry, S A

    1984-01-01

    We isolated a mutant of Saccharomyces cerevisiae defective in the formation of phosphatidylcholine via methylation of phosphatidylethanolamine. The mutant synthesized phosphatidylcholine at a reduced rate and accumulated increased amounts of methylated phospholipid intermediates. It was also found to be auxotrophic for inositol and allelic to an existing series of ino4 mutants. The ino2 and ino4 mutants, originally isolated on the basis of an inositol requirement, are unable to derepress the cytoplasmic enzyme inositol-1-phosphate synthase (myo-inositol-1-phosphate synthase; EC 5.5.1.4). The INO4 and INO2 genes were, thus, previously identified as regulatory genes whose wild-type product is required for expression of the INO1 gene product inositol-1-phosphate synthase (T. Donahue and S. Henry, J. Biol. Chem. 256:7077-7085, 1981). In addition to the identification of a new ino4-allele, further characterization of the existing series of ino4 and ino2 mutants, reported here, demonstrated that they all have a reduced capacity to convert phosphatidylethanolamine to phosphatidylcholine. The pleiotropic phenotype of the ino2 and ino4 mutants described in this paper suggests that the INO2 and INO4 loci are involved in the regulation of phospholipid methylation in the membrane as well as inositol biosynthesis in the cytoplasm. Images PMID:6392853

  11. A Dynamic Gene Regulatory Network Model That Recovers the Cyclic Behavior of Arabidopsis thaliana Cell Cycle

    PubMed Central

    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

  12. The Metarhizium anisopliae trp1 gene: cloning and regulatory analysis.

    PubMed

    Staats, Charley Christian; Silva, Marcia Suzana Nunes; Pinto, Paulo Marcos; Vainstein, Marilene Henning; Schrank, Augusto

    2004-07-01

    The trp1 gene from the entomopathogenic fungus Metarhizium anisopliae, cloned by heterologous hybridization with the plasmid carrying the trpC gene from Aspergillus nidulans, was sequence characterized. The predicted translation product has the conserved catalytic domains of glutamine amidotransferase (G domain), indoleglycerolphosphate synthase (C domain), and phosphoribosyl anthranilate isomerase (F domain) organized as NH2-G-C-F-COOH. The ORF is interrupted by a single intron of 60 nt that is position conserved in relation to trp genes from Ascomycetes and length conserved in relation to Basidiomycetes species. RT-PCR analysis suggests constitutive expression of trp1 gene in M. anisopliae.

  13. Analysis of Gene Sets Based on the Underlying Regulatory Network

    PubMed Central

    Michailidis, George

    2009-01-01

    Abstract Networks are often used to represent the interactions among genes and proteins. These interactions are known to play an important role in vital cell functions and should be included in the analysis of genes that are differentially expressed. Methods of gene set analysis take advantage of external biological information and analyze a priori defined sets of genes. These methods can potentially preserve the correlation among genes; however, they do not directly incorporate the information about the gene network. In this paper, we propose a latent variable model that directly incorporates the network information. We then use the theory of mixed linear models to present a general inference framework for the problem of testing the significance of subnetworks. Several possible test procedures are introduced and a network based method for testing the changes in expression levels of genes as well as the structure of the network is presented. The performance of the proposed method is compared with methods of gene set analysis using both simulation studies, as well as real data on genes related to the galactose utilization pathway in yeast. PMID:19254181

  14. Gene duplication of type-B ARR transcription factors systematically extends transcriptional regulatory structures in Arabidopsis

    PubMed Central

    Choi, Seung Hee; Hyeon, Do Young; Lee, ll Hwan; Park, Su Jin; Han, Seungmin; Lee, In Chul; Hwang, Daehee; Nam, Hong Gil

    2014-01-01

    Many of duplicated genes are enriched in signaling pathways. Recently, gene duplication of kinases has been shown to provide genetic buffering and functional diversification in cellular signaling. Transcription factors (TFs) are also often duplicated. However, how duplication of TFs affects their regulatory structures and functions of target genes has not been explored at the systems level. Here, we examined regulatory and functional roles of duplication of three major ARR TFs (ARR1, 10, and 12) in Arabidopsis cytokinin signaling using wild-type and single, double, and triple deletion mutants of the TFs. Comparative analysis of gene expression profiles obtained from Arabidopsis roots in wild-type and these mutants showed that duplication of ARR TFs systematically extended their transcriptional regulatory structures, leading to enhanced robustness and diversification in functions of target genes, as well as in regulation of cellular networks of target genes. Therefore, our results suggest that duplication of TFs contributes to robustness and diversification in functions of target genes by extending transcriptional regulatory structures. PMID:25425016

  15. Gene Regulatory Network Inferences Using a Maximum-Relevance and Maximum-Significance Strategy

    PubMed Central

    Liu, Wei; Zhu, Wen; Liao, Bo; Chen, Xiangtao

    2016-01-01

    Recovering gene regulatory networks from expression data is a challenging problem in systems biology that provides valuable information on the regulatory mechanisms of cells. A number of algorithms based on computational models are currently used to recover network topology. However, most of these algorithms have limitations. For example, many models tend to be complicated because of the “large p, small n” problem. In this paper, we propose a novel regulatory network inference method called the maximum-relevance and maximum-significance network (MRMSn) method, which converts the problem of recovering networks into a problem of how to select the regulator genes for each gene. To solve the latter problem, we present an algorithm that is based on information theory and selects the regulator genes for a specific gene by maximizing the relevance and significance. A first-order incremental search algorithm is used to search for regulator genes. Eventually, a strict constraint is adopted to adjust all of the regulatory relationships according to the obtained regulator genes and thus obtain the complete network structure. We performed our method on five different datasets and compared our method to five state-of-the-art methods for network inference based on information theory. The results confirm the effectiveness of our method. PMID:27829000

  16. Gene duplication of type-B ARR transcription factors systematically extends transcriptional regulatory structures in Arabidopsis.

    PubMed

    Choi, Seung Hee; Hyeon, Do Young; Lee, Ll Hwan; Park, Su Jin; Han, Seungmin; Lee, In Chul; Hwang, Daehee; Nam, Hong Gil

    2014-11-26

    Many of duplicated genes are enriched in signaling pathways. Recently, gene duplication of kinases has been shown to provide genetic buffering and functional diversification in cellular signaling. Transcription factors (TFs) are also often duplicated. However, how duplication of TFs affects their regulatory structures and functions of target genes has not been explored at the systems level. Here, we examined regulatory and functional roles of duplication of three major ARR TFs (ARR1, 10, and 12) in Arabidopsis cytokinin signaling using wild-type and single, double, and triple deletion mutants of the TFs. Comparative analysis of gene expression profiles obtained from Arabidopsis roots in wild-type and these mutants showed that duplication of ARR TFs systematically extended their transcriptional regulatory structures, leading to enhanced robustness and diversification in functions of target genes, as well as in regulation of cellular networks of target genes. Therefore, our results suggest that duplication of TFs contributes to robustness and diversification in functions of target genes by extending transcriptional regulatory structures.

  17. Stochastic Boolean networks: An efficient approach to modeling gene regulatory networks

    PubMed Central

    2012-01-01

    cell immune response dataset. An SBN can also implement the function of an asynchronous PBN and is potentially useful in a hybrid approach in combination with a continuous or single-molecule level stochastic model. Conclusions Stochastic Boolean networks (SBNs) are proposed as an efficient approach to modelling gene regulatory networks (GRNs). The SBN approach is able to recover biologically-proven regulatory behaviours, such as the oscillatory dynamics of the p53-Mdm2 network and the dynamic attractors in a T cell immune response network. The proposed approach can further predict the network dynamics when the genes are under perturbation, thus providing biologically meaningful insights for a better understanding of the dynamics of GRNs. The algorithms and methods described in this paper have been implemented in Matlab packages, which are attached as Additional files. PMID:22929591

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

    PubMed

    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.

  19. Modeling dynamics of adaptive complex systems: From gene regulatory networks to financial markets

    NASA Astrophysics Data System (ADS)

    Liu, Min

    This dissertation aims to model the dynamics of two types of adaptive complex systems: gene regulatory networks and financial markets. In modeling gene regulatory networks, a dynamics-driven rewiring mechanism is introduced to Boolean networks and it is found that a critical state emerges spontaneously resulting from the interplay between topology and dynamics during evolution. For biologically realized network sizes, significant finite-size effects are observed. In networks of competing Boolean nodes, we find that in small networks, the evolutionary dynamics selects for input inverting functions rather than canalizing functions in infinitely large networks. It is found that finite sizes can cause symmetry breaking in the evolutionary dynamics. Using the Polya theorem, we show the number of the function classes increases to 46, in contrast to 14 in infinitely large networks, due to the reduced symmetry which matches our simulation results well. In addition, we find that an optimum amount of stochastic noise in the signals exchanged between nodes can result in maximum excess canalization. In modeling financial markets, we simulate a double-auction virtual market by utilizing reaction-diffusion processes to describe the dynamics of limit orders. We find that the log-returns produced have a dynamical scaling exponent of 1/4 and nonstationary, negatively autocorrelated increments. By investigating the microstructure of the virtual market, we find that the mean interarrival time between transactions satisfies an increasing power-law function of time. We propose an inhomogeneous compound Poisson process with a decreasing power-law intensity rate function and demonstrate that this purely jump process captures the essential macroscopic dynamics of the virtual market.

  20. The Architecture of Gene Regulatory Variation across Multiple Human Tissues: The MuTHER Study

    PubMed Central

    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

  1. Cis-Regulatory Timers for Developmental Gene Expression

    PubMed Central

    Christiaen, Lionel

    2013-01-01

    How does a fertilized egg decode its own genome to eventually develop into a mature animal? Each developing cell must activate a battery of genes in a timely manner and according to the function it will ultimately perform, but how? During development of the notochord—a structure akin to the vertebrate spine—in a simple marine invertebrate, an essential protein called Brachyury binds to specific sites in its target genes. A study just published in PLOS Biology reports that if the target gene contains multiple Brachyury-binding sites it will be activated early in development but if it contains only one site it will be activated later. Genes that contain no binding site can still be activated by Brachyury, but only indirectly by an earlier Brachyury-dependent gene product, so later than the directly activated genes. Thus, this study shows how several genes can interpret the presence of a single factor differently to become active at distinct times in development. PMID:24204213

  2. [Evolutional principles of homology in regulatory genes of myogenesis].

    PubMed

    Ozerniuk, I D; Miuge, N S

    2012-01-01

    Analysis of early steps in muscular system development of invertebrates and vertebrates shows that early steps of myogenesis are regulated by genes-orthologs mainly belonging to two families, Pax and bHLH. In the majority of the following organisms, muscles formation (steps of determination and the earliest steps of myogenesis) is regulated by genes orthologs Pax3 which belong to the family Pax: nematodes (Caenorhabditis elegans, Pristionchus pacificus), insects (Drosophila melanogaster), echinoderms (Strongylocentrotus purpuratus), sea squirts (Ciona intestinalis, Holocynthia roretzi), fishes (Danio rerio), amphibians (Xenopus laevis), birds, and mammals (mouse, rat). The nematode C. elegans is an exception since formation of its muscles in this period is regulated by homeobox gene Pal-1 belonging to the family Caudal. The sea squirt C. intestinalis is also an exception because the earliest steps of development involved in further muscle formation are accompanied by activation of the gene CiSna (snail) (gene family basic Zinc finger). The next steps of myogenesis in all analyzed species are regulated by genes orthologs belonging to the family of transcriptional factors bHLH. They along with genes Pax3 are characterized by a high extent of homology in all studied groups of animals.

  3. Characterisation of multiple regulatory domains spanning the major transcriptional start site of the FUS gene, a candidate gene for motor neurone disease.

    PubMed

    Khursheed, Kejhal; Wilm, Thomas P; Cashman, Christine; Quinn, John P; Bubb, Vivien J; Moss, Diana J

    2015-01-21

    Fused-In-Sarcoma (FUS) is a candidate gene for neurological disorders including motor neurone disease and Parkinson׳s disease in addition to various types of cancer. Recently it has been reported that over expression of FUS causes motor neurone disease in mouse models hence mutations leading to changes in gene expression may contribute to the development of neurodegenerative disease. Genome evolutionary conservation was used to predict important cis-acting DNA regulators of the FUS gene promoter that direct transcription. The putative regulators identified were analysed in reporter gene assays in cells and in chick embryos. Our analysis indicated in addition to regulatory domains 5' of the transcriptional start site an important regulatory domain resides in intron 1 of the gene itself. This intronic domain functioned both in cell lines and in vivo in the neural tube of the chick embryo including developing motor neurones. Our data suggest the interaction of multiple domains including intronic domains are involved in expression of FUS. A better understanding of the regulation of expression of FUS may give insight into how its stimulus inducible expression may be associated with neurological disorders.

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

    PubMed

    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.

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

    PubMed

    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.

  6. Regulatory Oversight of Gene Therapy and Cell Therapy Products in Korea.

    PubMed

    Choi, Minjoung; Han, Euiri; Lee, Sunmi; Kim, Taegyun; Shin, Won

    2015-01-01

    The Ministry of Food and Drug Safety regulates gene therapy and cell therapy products as biological products under the authority of the Pharmaceutical Affairs Act. As with other medicinal products, gene therapy and cell therapy products are subject to approval for use in clinical trials and for a subsequent marketing authorization and to post-market surveillance. Research and development of gene therapy and cell therapy products have been progressing rapidly in Korea with extensive investment, offering great potential for the treatment of various serious diseases. To facilitate development of safe and effective products and provide more opportunities to patients suffering from severe diseases, several regulatory programs, such as the use of investigational products for emergency situations, fast-track approval, prereview of application packages, and intensive regulatory consultation, can be applied to these products. The regulatory approach for these innovative products is case by case and founded on science-based review that is flexible and balances the risks and benefits.

  7. A positive regulatory element is involved in the induction of the beta-galactosidase gene from Kluyveromyces lactis.

    PubMed Central

    Das, S; Breunig, K D; Hollenberg, C P

    1985-01-01

    The regulation of the LAC4 gene encoding beta-galactosidase in the yeast Kluyveromyces lactis has been studied. The expression of cloned LAC4 gene present on autonomously replicating plasmids was normally regulated by lactose or galactose as inducers. The LAC4 transcription initiation sites were mapped on two plasmids, PTY75-LAC4 and pKL2. The sites were found to be dependent on the level of gene expression and on the plasmid used. Under induced conditions, the normal cluster of initiation sites was used on both plasmids, whereas under non-induced conditions LAC4 on pKL2 showed additional sites. Deletion mapping of the 5' regulatory region of the LAC4 gene revealed a DNA element required for induction, presumably for the binding of a positive regulator. Images Fig. 2. Fig. 3. Fig. 6. PMID:3924596

  8. Control of Hoxd gene transcription in the mammary bud by hijacking a preexisting regulatory landscape

    PubMed Central

    Schep, Ruben; Necsulea, Anamaria; Rodríguez-Carballo, Eddie; Guerreiro, Isabel; Andrey, Guillaume; Nguyen Huynh, Thi Hanh; Marcet, Virginie; Zákány, Jozsef; Duboule, Denis; Beccari, Leonardo

    2016-01-01

    Vertebrate Hox genes encode transcription factors operating during the development of multiple organs and structures. However, the evolutionary mechanism underlying this remarkable pleiotropy remains to be fully understood. Here, we show that Hoxd8 and Hoxd9, two genes of the HoxD complex, are transcribed during mammary bud (MB) development. However, unlike in other developmental contexts, their coexpression does not rely on the same regulatory mechanism. Hoxd8 is regulated by the combined activity of closely located sequences and the most distant telomeric gene desert. On the other hand, Hoxd9 is controlled by an enhancer-rich region that is also located within the telomeric gene desert but has no impact on Hoxd8 transcription, thus constituting an exception to the global regulatory logic systematically observed at this locus. The latter DNA region is also involved in Hoxd gene regulation in other contexts and strongly interacts with Hoxd9 in all tissues analyzed thus far, indicating that its regulatory activity was already operational before the appearance of mammary glands. Within this DNA region and neighboring a strong limb enhancer, we identified a short sequence conserved in therian mammals and capable of enhancer activity in the MBs. We propose that Hoxd gene regulation in embryonic MBs evolved by hijacking a preexisting regulatory landscape that was already at work before the emergence of mammals in structures such as the limbs or the intestinal tract. PMID:27856734

  9. Feather Development Genes and Associated Regulatory Innovation Predate the Origin of Dinosauria

    PubMed Central

    Lowe, Craig B.; Clarke, Julia A.; Baker, Allan J.; Haussler, David; Edwards, Scott V.

    2015-01-01

    The evolution of avian feathers has recently been illuminated by fossils and the identification of genes involved in feather patterning and morphogenesis. However, molecular studies have focused mainly on protein-coding genes. Using comparative genomics and more than 600,000 conserved regulatory elements, we show that patterns of genome evolution in the vicinity of feather genes are consistent with a major role for regulatory innovation in the evolution of feathers. Rates of innovation at feather regulatory elements exhibit an extended period of innovation with peaks in the ancestors of amniotes and archosaurs. We estimate that 86% of such regulatory elements and 100% of the nonkeratin feather gene set were present prior to the origin of Dinosauria. On the branch leading to modern birds, we detect a strong signal of regulatory innovation near insulin-like growth factor binding protein (IGFBP) 2 and IGFBP5, which have roles in body size reduction, and may represent a genomic signature for the miniaturization of dinosaurian body size preceding the origin of flight. PMID:25415961

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

    SciTech Connect

    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.

  11. Feather development genes and associated regulatory innovation predate the origin of Dinosauria.

    PubMed

    Lowe, Craig B; Clarke, Julia A; Baker, Allan J; Haussler, David; Edwards, Scott V

    2015-01-01

    The evolution of avian feathers has recently been illuminated by fossils and the identification of genes involved in feather patterning and morphogenesis. However, molecular studies have focused mainly on protein-coding genes. Using comparative genomics and more than 600,000 conserved regulatory elements, we show that patterns of genome evolution in the vicinity of feather genes are consistent with a major role for regulatory innovation in the evolution of feathers. Rates of innovation at feather regulatory elements exhibit an extended period of innovation with peaks in the ancestors of amniotes and archosaurs. We estimate that 86% of such regulatory elements and 100% of the nonkeratin feather gene set were present prior to the origin of Dinosauria. On the branch leading to modern birds, we detect a strong signal of regulatory innovation near insulin-like growth factor binding protein (IGFBP) 2 and IGFBP5, which have roles in body size reduction, and may represent a genomic signature for the miniaturization of dinosaurian body size preceding the origin of flight.

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

    PubMed

    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.

  13. Identification of Cell Wall Synthesis Regulatory Genes Controlling Biomass Characteristics and Yield in Rice (Oryza Sativa)

    SciTech Connect

    Peng, Zhaohua PEng; Ronald, Palmela; Wang, Guo-Liang

    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

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

    PubMed Central

    Lee, Ho-Joon; Manke, Thomas; Bringas, Ricardo; Vingron, Martin

    2008-01-01

    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 further experimental studies. PMID

  15. Identification of novel regulatory genes in development of the avian reproductive tracts.

    PubMed

    Lim, Whasun; Song, Gwonhwa

    2014-01-01

    The chicken reproductive system is unique in maintaining its functions including production of eggs or sperm, fertilization of the egg by sperm maintained in sperm nests, production of hormones regulating its growth, development and function, and reproduction. Development of the reproductive organs is a highly regulated process that results in differentiation and proliferation of germ cells in response to predominant regulatory factors such as hormones and transcription factors. However, only a few genes are known to determine morphogenesis of the chicken reproductive tract and their mechanisms are unknown. Therefore, in the present study, we investigated the expression patterns of four genes including SNCA, TOM1L1, TTR and ZEB1 in the gonads at embryonic days 14 and 18, and in immature (12-week-old) and mature (50-week-old) chickens, as well as the reproductive tract including ovary, oviduct and testes of the respective sexes by qRT-PCR, in situ hybridization and immunofluorescence analyses. The expression of SNCA, TOM1L1 and ZEB1 genes was higher in immature and mature female reproductive tracts than expression of TTR. In addition, different temporal and spatial patterns of expression of the four genes were observed during maturation of testis in chickens. Specifically, SNCA, TOM1L1 and TTR were highly expressed in testes of 12-week-old chickens. Moreover, several chicken specific microRNAs (miRs) were demonstrated to affect expression of target gene mRNAs by directly binding to the 3'-UTR of their target genes through actions at the post-transcriptional level as follows: miR-153 and miR-1643 for SNCA; miR-1680* for TTR; and miR-200b and miR-1786 for ZEB1. These results suggest that four-selected genes play an important role in development of the male and female reproductive tract in chickens and expression of most candidate genes is regulated at the post-transcriptional level through specific microRNAs.

  16. Identification of Novel Regulatory Genes in Development of the Avian Reproductive Tracts

    PubMed Central

    Lim, Whasun; Song, Gwonhwa

    2014-01-01

    The chicken reproductive system is unique in maintaining its functions including production of eggs or sperm, fertilization of the egg by sperm maintained in sperm nests, production of hormones regulating its growth, development and function, and reproduction. Development of the reproductive organs is a highly regulated process that results in differentiation and proliferation of germ cells in response to predominant regulatory factors such as hormones and transcription factors. However, only a few genes are known to determine morphogenesis of the chicken reproductive tract and their mechanisms are unknown. Therefore, in the present study, we investigated the expression patterns of four genes including SNCA, TOM1L1, TTR and ZEB1 in the gonads at embryonic days 14 and 18, and in immature (12-week-old) and mature (50-week-old) chickens, as well as the reproductive tract including ovary, oviduct and testes of the respective sexes by qRT-PCR, in situ hybridization and immunofluorescence analyses. The expression of SNCA, TOM1L1 and ZEB1 genes was higher in immature and mature female reproductive tracts than expression of TTR. In addition, different temporal and spatial patterns of expression of the four genes were observed during maturation of testis in chickens. Specifically, SNCA, TOM1L1 and TTR were highly expressed in testes of 12-week-old chickens. Moreover, several chicken specific microRNAs (miRs) were demonstrated to affect expression of target gene mRNAs by directly binding to the 3′-UTR of their target genes through actions at the post-transcriptional level as follows: miR-153 and miR-1643 for SNCA; miR-1680* for TTR; and miR-200b and miR-1786 for ZEB1. These results suggest that four-selected genes play an important role in development of the male and female reproductive tract in chickens and expression of most candidate genes is regulated at the post-transcriptional level through specific microRNAs. PMID:24763497

  17. Functional and regulatory interactions between Hox and extradenticle genes

    PubMed Central

    Azpiazu, Natalia; Morata, Ginés

    1998-01-01

    The homeobox gene extradenticle (exd) acts as a cofactor of Hox function both in Drosophila and vertebrates. It has been shown that the distribution of the Exd protein is developmentally regulated at the post-translational level; in the regions where exd is not functional Exd is present only in the cell cytoplasm, whereas it accumulates in the nuclei of cells requiring exd function. We show that the subcellular localization of Exd is regulated by the BX-C genes and that each BX-C gene can prevent or reduce nuclear translocation of Exd to different extents. In spite of this negative regulation, two BX-C genes, Ultrabithorax and abdominal-A, require exd activity for their maintenance and function. We propose that mutual interactions between Exd and BX-C proteins ensure the correct amounts of interacting molecules. As the Hoxd10 gene has the same properties as Drosophila BX-C genes, we suggest that the control mechanism of subcellular distribution of Exd found in Drosophila probably operates in other organisms as well. PMID:9436985

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

    PubMed

    Hase, Takeshi; Ghosh, Samik; Yamanaka, Ryota; Kitano, Hiroaki

    2013-01-01

    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.

  19. A regulatory gene (ECO-orf4) required for ECO-0501 biosynthesis in Amycolatopsis orientalis.

    PubMed

    Shen, Yang; Huang, He; Zhu, Li; Luo, Minyu; Chen, Daijie

    2014-02-01

    ECO-0501 is a novel linear polyene antibiotic, which was discovered from Amycolatopsis orientalis. Recent study of ECO-0501 biosynthesis pathway revealed the presence of regulatory gene: ECO-orf4. The A. orientalis ECO-orf4 gene from the ECO-0501 biosynthesis cluster was analyzed, and its deduced protein (ECO-orf4) was found to have amino acid sequence homology with large ATP-binding regulators of the LuxR (LAL) family regulators. Database comparison revealed two hypothetical domains, a LuxR-type helix-turn-helix (HTH) DNA binding motif near the C-terminal and an N-terminal nucleotide triphosphate (NTP) binding motif included. Deletion of the corresponding gene (ECO-orf4) resulted in complete loss of ECO-0501 production. Complementation by one copy of intact ECO-orf4 restored the polyene biosynthesis demonstrating that ECO-orf4 is required for ECO-0501 biosynthesis. The results of overexpression ECO-orf4 on ECO-0501 production indicated that it is a positive regulatory gene. Gene expression analysis by reverse transcription PCR of the ECO-0501 gene cluster showed that the transcription of ECO-orf4 correlates with that of genes involved in polyketide biosynthesis. These results demonstrated that ECO-orf4 is a pathway-specific positive regulatory gene that is essential for ECO-0501 biosynthesis.

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

    SciTech Connect

    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.

  1. Experimental approaches for gene regulatory network construction: the chick as a model system

    PubMed Central

    Streit, Andrea; Tambalo, Monica; Chen, Jingchen; Grocott, Timothy; Anwar, Maryam; Sosinsky, Alona; Stern, Claudio D.

    2012-01-01

    Setting up the body plan during embryonic development requires the coordinated action of many signals and transcriptional regulators in a precise temporal sequence and spatial pattern. The last decades have seen an explosion of information describing the molecular control of many developmental processes. The next challenge is to integrate this information into logic ‘wiring diagrams’ that visualise gene actions and outputs, have predictive power and point to key control nodes. Here we provide an experimental workflow on how to construct gene regulatory networks using the chick as model system. Keywords: transcription factors, transcriptome analysis, conserved regulatory elements PMID:23174848

  2. Combining Hi-C data with phylogenetic correlation to predict the target genes of distal regulatory elements in human genome.

    PubMed

    Lu, Yulan; Zhou, Yuanpeng; Tian, Weidong

    2013-12-01

    Defining the target genes of distal regulatory elements (DREs), such as enhancer, repressors and insulators, is a challenging task. The recently developed Hi-C technology is designed to capture chromosome conformation structure by high-throughput sequencing, and can be potentially used to determine the target genes of DREs. However, Hi-C data are noisy, making it difficult to directly use Hi-C data to identify DRE-target gene relationships. In this study, we show that DREs-gene pairs that are confirmed by Hi-C data are strongly phylogenetic correlated, and have thus developed a method that combines Hi-C read counts with phylogenetic correlation to predict long-range DRE-target gene relationships. Analysis of predicted DRE-target gene pairs shows that genes regulated by large number of DREs tend to have essential functions, and genes regulated by the same DREs tend to be functionally related and co-expressed. In addition, we show with a couple of examples that the predicted target genes of DREs can help explain the causal roles of disease-associated single-nucleotide polymorphisms located in the DREs. As such, these predictions will be of importance not only for our understanding of the function of DREs but also for elucidating the causal roles of disease-associated noncoding single-nucleotide polymorphisms.

  3. Modelling gene and protein regulatory networks with answer set programming.

    PubMed

    Fayruzov, Timur; Janssen, Jeroen; Vermeir, Dirk; Cornelis, Chris; De Cock, Martine

    2011-01-01

    Recently, many approaches to model regulatory networks have been proposed in the systems biology domain. However, the task is far from being solved. In this paper, we propose an Answer Set Programming (ASP)-based approach to model interaction networks. We build a general ASP framework that describes the network semantics and allows modelling specific networks with little effort. ASP provides a rich and flexible toolbox that allows expanding the framework with desired features. In this paper, we tune our framework to mimic Boolean network behaviour and apply it to model the Budding Yeast and Fission Yeast cell cycle networks. The obtained steady states of these networks correspond to those of the Boolean networks.

  4. PRMT1 mediated methylation of TAF15 is required for its positive gene regulatory function

    SciTech Connect

    Jobert, Laure; Argentini, Manuela; Tora, Laszlo

    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.

  5. Construction of Gene Regulatory Networks Using Recurrent Neural Networks and Swarm Intelligence

    PubMed Central

    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. PMID:27298752

  6. Glucokinase regulatory protein (GCKR) gene polymorphism affects postprandial lipemic response in a dietary intervention study

    PubMed Central

    Shen, Haiqing; Pollin, Toni I.; Damcott, Coleen M.; McLenithan, John C.; Mitchell, Braxton D.; Shuldiner, Alan R.

    2010-01-01

    Postprandial triglyceridemia is an emerging risk factor for cardiovascular disease. However, most of the genes that influence postprandial triglyceridemia are not known. We evaluated whether a common nonsynonymous SNP rs1260326/P446L in the glucokinase regulatory protein (GCKR) gene influenced variation in the postprandial lipid response after a high-fat challenge in seven hundred and seventy participants in the Amish HAPI Heart Study who underwent an oral high-fat challenge and had blood samples taken in the fasting state and during the postprandial phase at 1, 2, 3, 4, and 6 hours. We found that the minor T allele at rs1260326 was associated with significantly higher fasting TG levels after adjusting for age, sex, and family structure (Pa = 0.06 for additive model, and Pr=0.0003 for recessive model). During the fat challenge, the T allele was associated with significantly higher maximum TG level (Pa = 0.006), incremental maximum TG level (Pa = 0.006), TG area under the curve (Pa = 0.02) and incremental TG area under the curve (Pa = 0.03). Our data indicate that the rs1260326 T allele of GCKR is associated with both higher fasting levels of TG as well as the postprandial TG response, which may result in higher atherogenic risk. PMID:19526250

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

    PubMed

    Emmert-Streib, Frank

    2013-01-01

    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.

  8. Inference of gene regulatory networks from genome-wide knockout fitness data

    PubMed Central

    Wang, Liming; Wang, Xiaodong; Arkin, Adam P.; Samoilov, Michael S.

    2013-01-01

    Motivation: Genome-wide fitness is an emerging type of high-throughput biological data generated for individual organisms by creating libraries of knockouts, subjecting them to broad ranges of environmental conditions, and measuring the resulting clone-specific fitnesses. Since fitness is an organism-scale measure of gene regulatory network behaviour, it may offer certain advantages when insights into such phenotypical and functional features are of primary interest over individual gene expression. Previous works have shown that genome-wide fitness data can be used to uncover novel gene regulatory interactions, when compared with results of more conventional gene expression analysis. Yet, to date, few algorithms have been proposed for systematically using genome-wide mutant fitness data for gene regulatory network inference. Results: In this article, we describe a model and propose an inference algorithm for using fitness data from knockout libraries to identify underlying gene regulatory networks. Unlike most prior methods, the presented approach captures not only structural, but also dynamical and non-linear nature of biomolecular systems involved. A state–space model with non-linear basis is used for dynamically describing gene regulatory networks. Network structure is then elucidated by estimating unknown model parameters. Unscented Kalman filter is used to cope with the non-linearities introduced in the model, which also enables the algorithm to run in on-line mode for practical use. Here, we demonstrate that the algorithm provides satisfying results for both synthetic data as well as empirical measurements of GAL network in yeast Saccharomyces cerevisiae and TyrR–LiuR network in bacteria Shewanella oneidensis. Availability: MATLAB code and datasets are available to download at http://www.duke.edu/∼lw174/Fitness.zip and http://genomics.lbl.gov/supplemental/fitness-bioinf/ Contact: wangx@ee.columbia.edu or mssamoilov@lbl.gov Supplementary information

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

    NASA Technical Reports Server (NTRS)

    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.

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

    PubMed

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

    2003-11-11

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  12. Gene regulatory network inference: evaluation and application to ovarian cancer allows the prioritization of drug targets

    PubMed Central

    2012-01-01

    Background Altered networks of gene regulation underlie many complex conditions, including cancer. Inferring gene regulatory networks from high-throughput microarray expression data is a fundamental but challenging task in computational systems biology and its translation to genomic medicine. Although diverse computational and statistical approaches have been brought to bear on the gene regulatory network inference problem, their relative strengths and disadvantages remain poorly understood, largely because comparative analyses usually consider only small subsets of methods, use only synthetic data, and/or fail to adopt a common measure of inference quality. Methods We report a comprehensive comparative evaluation of nine state-of-the art gene regulatory network inference methods encompassing the main algorithmic approaches (mutual information, correlation, partial correlation, random forests, support vector machines) using 38 simulated datasets and empirical serous papillary ovarian adenocarcinoma expression-microarray data. We then apply the best-performing method to infer normal and cancer networks. We assess the druggability of the proteins encoded by our predicted target genes using the CancerResource and PharmGKB webtools and databases. Results We observe large differences in the accuracy with which these methods predict the underlying gene regulatory network depending on features of the data, network size, topology, experiment type, and parameter settings. Applying the best-performing method (the supervised method SIRENE) to the serous papillary ovarian adenocarcinoma dataset, we infer and rank regulatory interactions, some previously reported and others novel. For selected novel interactions we propose testable mechanistic models linking gene regulation to cancer. Using network analysis and visualization, we uncover cross-regulation of angiogenesis-specific genes through three key transcription factors in normal and cancer conditions. Druggabilty analysis

  13. Strong early seed-specific gene regulatory region

    DOEpatents

    Broun, Pierre; Somerville, Chris

    1999-01-01

    Nucleic acid sequences and methods for their use are described which provide for early seed-specific transcription, in order to modulate or modify expression of foreign or endogenous genes in seeds, particularly embryo cells. The method finds particular use in conjunction with modifying fatty acid production in seed tissue.

  14. Strong early seed-specific gene regulatory region

    SciTech Connect

    Broun, Pierre; Somerville, Chris

    2002-01-01

    Nucleic acid sequences and methods for their use are described which provide for early seed-specific transcription, in order to modulate or modify expression of foreign or endogenous genes in seeds, particularly embryo cells. The method finds particular use in conjunction with modifying fatty acid production in seed tissue.

  15. Anthocyanin regulatory/structural gene expression in Phalaenopsis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Partial cDNA fragments of Myb, Myc, Wd, Chs and Dfr genes were generated by Reverse Transcription-PCR using total RNA isolated from flowers of P. amabilis (L.) Blume (anthocyanin-free) and P. schilleriana Rchb. f. (anthocyanin-containing) and cloned into a TOPO vector. RT-PCR revealed that the struc...

  16. Characterization of the Cis-Regulatory Region of the Drosophila Homeotic Gene Sex Combs Reduced

    PubMed Central

    Gindhart-Jr., J. G.; King, A. N.; Kaufman, T. C.

    1995-01-01

    The Drosophila homeotic gene Sex combs reduced (Scr) controls the segmental identity of the labial and prothoracic segments in the embryo and adult. It encodes a sequence-specific transcription factor that controls, in concert with other gene products, differentiative pathways of tissues in which Scr is expressed. During embryogenesis, Scr accumulation is observed in a discrete spatiotemporal pattern that includes the labial and prothoracic ectoderm, the subesophageal ganglion of the ventral nerve cord and the visceral mesoderm of the anterior and posterior midgut. Previous analyses have demonstrated that breakpoint mutations located in a 75-kb interval, including the Scr transcription unit and 50 kb of upstream DNA, cause Scr misexpression during development, presumably because these mutations remove Scr cis-regulatory sequences from the proximity of the Scr promoter. To gain a better understanding of the regulatory interactions necessary for the control of Scr transcription during embryogenesis, we have begun a molecular analysis of the Scr regulatory interval. DNA fragments from this 75-kb region were subcloned into P-element vectors containing either an Scr-lacZ or hsp70-lacZ fusion gene, and patterns of reporter gene expression were assayed in transgenic embryos. Several fragments appear to contain Scr regulatory sequences, as they direct reporter gene expression in patterns similar to those normally observed for Scr, whereas other DNA fragments direct Scr reporter gene expression in developmentally interesting but non-Scr-like patterns during embryogenesis. Scr expression in some tissues appears to be controlled by multiple regulatory elements that are separated, in some cases, by more than 20 kb of intervening DNA. Interestingly, regulatory sequences that direct reporter gene expression in an Scr-like pattern in the anterior and posterior midgut are imbedded in the regulatory region of the segmentation gene fushi tarazu (ftz), which is normally located

  17. Engineering a regulatory region of jadomycin gene cluster to improve jadomycin B production in Streptomyces venezuelae.

    PubMed

    Zheng, Jian-Ting; Wang, Sheng-Lan; Yang, Ke-Qian

    2007-09-01

    Streptomyces venezuelae ISP5230 produces a group of jadomycin congeners with cytotoxic activities. To improve jadomycin fermentation process, a genetic engineering strategy was designed to replace a 3.4-kb regulatory region of jad gene cluster that contains four regulatory genes (3' end 272 bp of jadW2, jadW3, jadR2, and jadR1) and the native promoter upstream of jadJ (P(J)) with the ermEp* promoter sequence so that ermEp* drives the expression of the jadomycin biosynthetic genes from jadJ in the engineered strain. As expected, the mutant strain produced jadomycin B without ethanol treatment, and the yield increased to about twofold that of the stressed wild-type. These results indicated that manipulation of the regulation of a biosynthetic gene cluster is an effective strategy to increase product yield.

  18. Gene regulatory mechanisms orchestrated by p63 in epithelial development and related disorders.

    PubMed

    Kouwenhoven, Evelyn N; van Bokhoven, Hans; Zhou, Huiqing

    2015-06-01

    The transcription factor p63 belongs to the p53 family and is a key regulator in epithelial commitment and development. Mutations in p63 give rise to several epithelial related disorders with defects in skin, limb and orofacial structures. Since the discovery of p63, efforts have been made to identify its target genes using individual gene approaches and to understand p63 function in normal epithelial development and related diseases. Recent genome-wide approaches have identified tens of thousands of potential p63-regulated target genes and regulatory elements, and reshaped the concept of gene regulation orchestrated by p63. These data also provide insights into p63-related disease mechanisms. In this review, we discuss the regulatory role of p63 in normal and diseased epithelial development in light of these novel findings. We also propose future perspectives for dissecting the molecular mechanism of p63-mediated epithelial development and related disorders as well as for potential therapeutic strategies.

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

    PubMed

    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.

  20. Additives

    NASA Technical Reports Server (NTRS)

    Smalheer, C. V.

    1973-01-01

    The chemistry of lubricant additives is discussed to show what the additives are chemically and what functions they perform in the lubrication of various kinds of equipment. Current theories regarding the mode of action of lubricant additives are presented. The additive groups discussed include the following: (1) detergents and dispersants, (2) corrosion inhibitors, (3) antioxidants, (4) viscosity index improvers, (5) pour point depressants, and (6) antifouling agents.

  1. Characterization of the cis-regulatory region of the Drosophila homeotic gene Sex combs reduced

    SciTech Connect

    Gindhart, J.G. Jr.; King, N.A.; Kaufman, T.C.

    1995-02-01

    The Drosophilia homeotic gene Sex combs reduced (Scr) controls the segmental identity of the labial and prothoracic segments in the embryo and adult. It encodes a sequence-specific transcription factor that controls, in concert with other gene products, differentiative pathways of tissues in which Scr is expressed. During embryogenesis, Scr accumulation is observed in a discrete spatiotemporal pattern that includes the labial and prothoracic ectoderm, the subesophageal ganglion of the ventral nerve cord and the visceral mesoderm of the anterior and posterior midgut. Previous analyses have demonstrated that breakpoint mutations located in a 75-kb interval, including the Scr transcription unit and 50 kb of upstream DNA, cause Scr misexpression during development, presumably because these mutations remove Scr cis-regulatory sequences from the proximity of the Scr promoter. To gain a better understanding of the regulatory interactions necessary for the control of Scr transcription during embryogenesis, we have begun a molecular analysis of the Scr regulatory interval. DNA fragments from this 75-kb region were subcloned into P-element vectors containing either an Scr-lacZ or hsp70-lacZ fusion gene, and patterns of reporter gene expression were assayed in transgenic embryos. Several fragments appear to contain Scr regulatory sequences, as they direct reporter gene expression in patterns similar to those normally observed for Scr, whereas other DNA fragments direct Scr reporter gene expression in developmentally interesting but non-Scr-like patterns during embryogenesis. Scr expression in some tissues appears to be controlled by multiple regulatory elements that are separated, in some cases, by more than 20 kb of intervening DNA. This analysis provides an entry point for the study of how Scr transcription is regulated at the molecular level. 60 refs., 7 figs., 1 tab.

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

    NASA Astrophysics Data System (ADS)

    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.

  3. cepip: context-dependent epigenomic weighting for prioritization of regulatory variants and disease-associated genes.

    PubMed

    Li, Mulin Jun; Li, Miaoxin; Liu, Zipeng; Yan, Bin; Pan, Zhicheng; Huang, Dandan; Liang, Qian; Ying, Dingge; Xu, Feng; Yao, Hongcheng; Wang, Panwen; Kocher, Jean-Pierre A; Xia, Zhengyuan; Sham, Pak Chung; Liu, Jun S; Wang, Junwen

    2017-03-16

    It remains challenging to predict regulatory variants in particular tissues or cell types due to highly context-specific gene regulation. By connecting large-scale epigenomic profiles to expression quantitative trait loci (eQTLs) in a wide range of human tissues/cell types, we identify critical chromatin features that predict variant regulatory potential. We present cepip, a joint likelihood framework, for estimating a variant's regulatory probability in a context-dependent manner. Our method exhibits significant GWAS signal enrichment and is superior to existing cell type-specific methods. Furthermore, using phenotypically relevant epigenomes to weight the GWAS single-nucleotide polymorphisms, we improve the statistical power of the gene-based association test.

  4. Cis-regulatory elements are harbored in Intron5 of the RUNX1 gene

    PubMed Central

    2014-01-01

    Background Human RUNX1 gene is one of the most frequent target for chromosomal translocations associated with acute myeloid leukemia (AML) and acute lymphoid leukemia (ALL). The highest prevalence in AML is noted with (8; 21) translocation; which represents 12 to 15% of all AML cases. Interestingly, all the breakpoints mapped to date in t(8;21) are clustered in intron 5 of the RUNX1 gene and intron 1 of the ETO gene. No homologous sequences have been found at the recombination regions; but DNase I hypersensitive sites (DHS) have been mapped to the areas of the genes involved in t(8;21). Presence of DHS sites is commonly associated with regulatory elements such as promoters, enhancers and silencers, among others. Results In this study we used a combination of comparative genomics, cloning and transfection assays to evaluate potential regulatory elements located in intron 5 of the RUNX1 gene. Our genomic analysis identified nine conserved non-coding sequences that are evolutionarily conserved among rat, mouse and human. We cloned two of these regions in pGL-3 Promoter plasmid in order to analyze their transcriptional regulatory activity. Our results demonstrate that the identified regions can indeed regulate transcription of a reporter gene in a distance and position independent manner; moreover, their transcriptional effect is cell type specific. Conclusions We have identified nine conserved non coding sequence that are harbored in intron 5 of the RUNX1 gene. We have also demonstrated that two of these regions can regulate transcriptional activity in vitro. Taken together our results suggest that intron 5 of the RUNX1 gene contains multiple potential cis-regulatory elements. PMID:24655352

  5. Oral streptococci with genetic determinants similar to the glucosyltransferase regulatory gene, rgg.

    PubMed Central

    Vickerman, M M; Sulavik, M C; Clewell, D B

    1995-01-01

    The Streptococcus gordonii Challis glucosyltransferase structural gene, gtfG, is positively regulated by the upstream gene, rgg, the only described gtf regulatory determinant in oral streptococci. Southern hybridization analyses indicated that rgg-like and gtfG-like determinants were present on the same HindIII fragment in strains of S. gordonii, Streptococcus sanguis, and Streptococcus oralis, whereas no rgg-like determinants were detected in mutans streptococci, Streptococcus mitis, and Streptococcus salivarius. PMID:7591096

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

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

    PubMed

    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.

  8. Sterol Regulatory Element Binding Protein Is a Principal Regulator of Anaerobic Gene Expression in Fission Yeast†

    PubMed Central

    Todd, Bridget L.; Stewart, Emerson V.; Burg, John S.; Hughes, Adam L.; Espenshade, Peter J.

    2006-01-01

    Fission yeast sterol regulatory element binding protein (SREBP), called Sre1p, functions in an oxygen-sensing pathway to allow adaptation to fluctuating oxygen concentrations. The Sre1p-Scp1p complex responds to oxygen-dependent sterol synthesis as an indirect measure of oxygen availability. To examine the role of Sre1p in anaerobic gene expression in Schizosaccharomyces pombe, we performed transcriptional profiling experiments after a shift to anaerobic conditions for 1.5 h. Of the 4,940 genes analyzed, expression levels of 521 (10.5%) and 686 (13.9%) genes were significantly increased and decreased, respectively, under anaerobic conditions. Sre1p controlled 68% of genes induced ≥2-fold. Oxygen-requiring biosynthetic pathways for ergosterol, heme, sphingolipid, and ubiquinone were primary targets of Sre1p. Induction of glycolytic genes and repression of mitochondrial oxidative phosphorylation genes largely did not require Sre1p. Using chromatin immunoprecipitation, we demonstrated that Sre1p acts directly at target gene promoters and stimulates its own transcription under anaerobic conditions. sre1+ promoter analysis identified two DNA elements that are both necessary and sufficient for oxygen-dependent, Sre1p-dependent transcription. Interestingly, these elements are homologous to sterol regulatory elements bound by mammalian SREBP, highlighting the evolutionary conservation between Sre1p and SREBP. We conclude that Sre1p is a principal activator of anaerobic gene expression, upregulating genes required for nonrespiratory oxygen consumption. PMID:16537923

  9. Regulatory hotspots are associated with plant gene expression under varying soil phosphorus supply in Brassica rapa.

    PubMed

    Hammond, John P; Mayes, Sean; Bowen, Helen C; Graham, Neil S; Hayden, Rory M; Love, Christopher G; Spracklen, William P; Wang, Jun; Welham, Sue J; White, Philip J; King, Graham J; Broadley, Martin R

    2011-07-01

    Gene expression is a quantitative trait that can be mapped genetically in structured populations to identify expression quantitative trait loci (eQTL). Genes and regulatory networks underlying complex traits can subsequently be inferred. Using a recently released genome sequence, we have defined cis- and trans-eQTL and their environmental response to low phosphorus (P) availability within a complex plant genome and found hotspots of trans-eQTL within the genome. Interval mapping, using P supply as a covariate, revealed 18,876 eQTL. trans-eQTL hotspots occurred on chromosomes A06 and A01 within Brassica rapa; these were enriched with P metabolism-related Gene Ontology terms (A06) as well as chloroplast- and photosynthesis-related terms (A01). We have also attributed heritability components to measures of gene expression across environments, allowing the identification of novel gene expression markers and gene expression changes associated with low P availability. Informative gene expression markers were used to map eQTL and P use efficiency-related QTL. Genes responsive to P supply had large environmental and heritable variance components. Regulatory loci and genes associated with P use efficiency identified through eQTL analysis are potential targets for further characterization and may have potential for crop improvement.

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

    PubMed

    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.

  11. Finding Missing Interactions of the Arabidopsis thaliana Root Stem Cell Niche Gene Regulatory Network

    PubMed Central

    Azpeitia, Eugenio; Weinstein, Nathan; Benítez, Mariana; Mendoza, Luis; Alvarez-Buylla, Elena R.

    2013-01-01

    Over the last few decades, the Arabidopsis thaliana root stem cell niche (RSCN) has become a model system for the study of plant development and stem cell niche dynamics. Currently, many of the molecular mechanisms involved in RSCN maintenance and development have been described. A few years ago, we published a gene regulatory network (GRN) model integrating this information. This model suggested that there were missing components or interactions. Upon updating the model, the observed stable gene configurations of the RSCN could not be recovered, indicating that there are additional missing components or interactions in the model. In fact, due to the lack of experimental data, GRNs inferred from published data are usually incomplete. However, predicting the location and nature of the missing data is a not trivial task. Here, we propose a set of procedures for detecting and predicting missing interactions in Boolean networks. We used these procedures to predict putative missing interactions in the A. thaliana RSCN network model. Using our approach, we identified three necessary interactions to recover the reported gene activation configurations that have been experimentally uncovered for the different cell types within the RSCN: (1) a regulation of PHABULOSA to restrict its expression domain to the vascular cells, (2) a self-regulation of WOX5, possibly by an indirect mechanism through the auxin signaling pathway, and (3) a positive regulation of JACKDAW by MAGPIE. The procedures proposed here greatly reduce the number of possible Boolean functions that are biologically meaningful and experimentally testable and that do not contradict previous data. We believe that these procedures can be used on any Boolean network. However, because the procedures were designed for the specific case of the RSCN, formal demonstrations of the procedures should be shown in future efforts. PMID:23658556

  12. A genome-wide survey of CD4+ lymphocyte regulatory genetic variants identifies novel asthma genes

    PubMed Central

    Sharma, Sunita; Zhou, Xiaobo; Thibault, Derek M.; Himes, Blanca E.; Liu, Andy; Szefler, Stanley J.; Strunk, Robert; Castro, Mario; Hansel, Nadia N.; Diette, Gregory B.; Vonakis, Becky M.; Adkinson, N. Franklin; Avila, Lydiana; Soto-Quiros, Manuel; Barraza-Villareal, Albino; Lemanske, Robert F.; Solway, Julian; Krishnan, Jerry; White, Steven R.; Cheadle, Chris; Berger, Alan E.; Fan, Jinshui; Boorgula, Meher Preethi; Nicolae, Dan; Gilliland, Frank; Barnes, Kathleen; London, Stephanie J.; Martinez, Fernando; Ober, Carole; Celedón, Juan C.; Carey, Vincent J.; Weiss, Scott T.; Raby, Benjamin A.

    2014-01-01

    Background Genome-wide association studies have yet to identify the majority of genetic variants involved in asthma. We hypothesized that expression quantitative trait locus (eQTL) mapping can identify novel asthma genes by enabling prioritization of putative functional variants for association testing. Objective We evaluated 6,706 cis-acting expression-associated variants (eSNP) identified through a genome-wide eQTL survey of CD4+ lymphocytes for association with asthma. Methods eSNP were tested for association with asthma in 359 asthma cases and 846 controls from the Childhood Asthma Management Program, with verification using family-based testing. Significant associations were tested for replication in 579 parent-child trios with asthma from Costa Rica. Further functional validation was performed by Formaldehyde Assisted Isolation of Regulatory Elements (FAIRE)-qPCR and Chromatin-Immunoprecipitation (ChIP)-PCR in lung derived epithelial cell lines (Beas-2B and A549) and Jurkat cells, a leukemia cell line derived from T lymphocytes. Results Cis-acting eSNP demonstrated associations with asthma in both cohorts. We confirmed the previously-reported association of ORMDL3/GSDMB variants with asthma (combined p=2.9 × 108). Reproducible associations were also observed for eSNP in three additional genes: FADS2 (p=0.002), NAGA (p=0.0002), and F13A1 (p=0.0001). We subsequently demonstrated that FADS2 mRNA is increased in CD4+ lymphocytes in asthmatics, and that the associated eSNPs reside within DNA segments with histone modifications that denote open chromatin status and confer enhancer activity. Conclusions Our results demonstrate the utility of eQTL mapping in the identification of novel asthma genes, and provide evidence for the importance of FADS2, NAGA, and F13A1 in the pathogenesis of asthma. PMID:24934276

  13. De-regulation of diabetic regulatory genes in psoriasis: Deciphering the unsolved riddle.

    PubMed

    AlFadhli, Suad; Al-Zufairi, Alaa A M; Nizam, Rasheeba; AlSaffar, Huda A; Al-Mutairi, Nawaf

    2016-11-15

    The purpose of our study was to identify the currently lacking molecular mechanism that accounts for the co-occurrence of two seemingly disparate diseases: psoriasis and type II diabetes. We aimed to investigate a panel of 84 genes related to the diabetic regulatory network in psoriasis (Ps), psoriasis type II diabetes (Ps-T2D), type II diabetes (T2D) and healthy control (HC). We hypothesize that such attempts would provide novel diagnostic markers and/or insights into pathogenesis of the disease. A quantitative Real Time-PCR Human Diabetes RT(2) Profiler PCR Array was chosen to explore the expression profile 84 diabetic genes in study subjects. Statistical analysis was carried out using appropriate software. The analysis revealed three candidate genes GSK3B, PTPN1, STX4 that are differentially expressed in study subjects. GSK3B was highly significant in Ps-T2D (P=0.00018, FR=-26.6), followed by Ps (P=0.0028, FR=-14.5) and T2D groups (P=0.032, FR=-5.9). PTPN1 showed significant association only with PS-T2D (P=0.00027, FR=-8.5). STX4 showed significant association with both Ps (P=0.0002, FR=-20) and Ps-T2D (P=0.0016, FR=-11.2). ACE represents an additional marker that showed suggestive association with Ps (P=0.0079, FR=-9.37). Our study highlights the complex genetics of Ps-T2D and present biomarkers for the development of T2D in Ps cases.

  14. Phylogenetic Relationships and the Evolution of Regulatory Gene Sequences in the Parrotfishes

    PubMed Central

    Smith, Lydia L.; Fessler, Jennifer L.; Alfaro, Michael E.; Streelman, J. Todd; Westneat, Mark W.

    2008-01-01

    Regulatory genes control the expression of other genes and are key components of developmental processes such as segmentation and embryonic construction of the skull in vertebrates. Here we examine the variability and evolution of three vertebrate regulatory genes, addressing issues of their utility for phylogenetics and comparing the rates of genetic change seen in regulatory loci to the rates seen in other genes in the parrotfishes. The parrotfishes are a diverse group of colorful fishes from coral reefs and seagrasses worldwide and have been placed phylogenetically within the family Labridae. We tested phylogenetic hypotheses among the parrotfishes, with a focus on the genera Chlorurus and Scarus, by analyzing eight gene fragments for 42 parrotfishes and eight outgroup species. We sequenced mitochondrial 12s rRNA (967 bp), 16s rRNA (577 bp), and cytochrome b (477 bp). From the nuclear genome, we sequenced part of the protein-coding genes rag2 (715 bp), tmo4c4 (485 bp), and the developmental regulatory genes otx1 (672 bp), bmp4 (488 bp), and dlx2 (522 bp). Bayesian, likelihood, and parsimony analyses on the resulting 4903 bp of DNA sequence produced similar topologies that confirm the monophyly of the scarines and provide a phylogeny at the species level for portions of the genera Scarus and Chlorurus. Four major clades of Scarus were recovered, with three distributed in the Indo-Pacific and one containing Caribbean/Atlantic taxa. Molecular rates suggest a Miocene origin of the parrotfishes (22 mya) and a recent divergence of species within Scarus and Chlorurus, within the past 5 million years. Developmentally important genes made a significant contribution to phylogenetic structure, and rates of genetic evolution were high in bmp4, similar to other coding nuclear genes, but low in otx1 and the dlx2 exons. Synonymous and nonsynonymous substitution patterns in developmental regulatory genes support the hypothesis of stabilizing selection during the history of

  15. Reverse engineering gene regulatory network from microarray data using linear time-variant model

    PubMed Central

    2010-01-01

    Background Gene regulatory network is an abstract mapping of gene regulations in living cells that can help to predict the system behavior of living organisms. Such prediction capability can potentially lead to the development of improved diagnostic tests and therapeutics. DNA microarrays, which measure the expression level of thousands of genes in parallel, constitute the numeric seed for the inference of gene regulatory networks. In this paper, we have proposed a new approach for inferring gene regulatory networks from time-series gene expression data using linear time-variant model. Here, Self-Adaptive Differential Evolution, a versatile and robust Evolutionary Algorithm, is used as the learning paradigm. Results To assess the potency of the proposed work, a well known nonlinear synthetic network has been used. The reconstruction method has inferred this synthetic network topology and the associated regulatory parameters with high accuracy from both the noise-free and noisy time-series data. For validation purposes, the proposed approach is also applied to the simulated expression dataset of cAMP oscillations in Dictyostelium discoideum and has proved it's strength in finding the correct regulations. The strength of this work has also been verified by analyzing the real expression dataset of SOS DNA repair system in Escherichia coli and it has succeeded in finding more correct and reasonable regulations as compared to various existing works. Conclusion By the proposed approach, the gene interaction networks have been inferred in an efficient manner from both the synthetic, simulated cAMP oscillation expression data and real expression data. The computational time of this approach is also considerably smaller, which makes it to be more suitable for larger network reconstruction. Thus the proposed approach can serve as an initiate for the future researches regarding the associated area. PMID:20122231

  16. JNK-dependent gene regulatory circuitry governs mesenchymal fate

    PubMed Central

    Sahu, Sanjeeb Kumar; Garding, Angela; Tiwari, Neha; Thakurela, Sudhir; Toedling, Joern; Gebhard, Susanne; Ortega, Felipe; Schmarowski, Nikolai; Berninger, Benedikt; Nitsch, Robert; Schmidt, Marcus; Tiwari, Vijay K

    2015-01-01

    The epithelial to mesenchymal transition (EMT) is a biological process in which cells lose cell–cell contacts and become motile. EMT is used during development, for example, in triggering neural crest migration, and in cancer metastasis. Despite progress, the dynamics of JNK signaling, its role in genomewide transcriptional reprogramming, and involved downstream effectors during EMT remain largely unknown. Here, we show that JNK is not required for initiation, but progression of phenotypic changes associated with EMT. Such dependency resulted from JNK-driven transcriptional reprogramming of critical EMT genes and involved changes in their chromatin state. Furthermore, we identified eight novel JNK-induced transcription factors that were required for proper EMT. Three of these factors were also highly expressed in invasive cancer cells where they function in gene regulation to maintain mesenchymal identity. These factors were also induced during neuronal development and function in neuronal migration in vivo. These comprehensive findings uncovered a kinetically distinct role for the JNK pathway in defining the transcriptome that underlies mesenchymal identity and revealed novel transcription factors that mediate these responses during development and disease. PMID:26157010

  17. MicroRNA and Transcription Factor Gene Regulatory Network Analysis Reveals Key Regulatory Elements Associated with Prostate Cancer Progression

    PubMed Central

    Sadeghi, Mehdi; Ranjbar, Bijan; Ganjalikhany, Mohamad Reza; M. Khan, Faiz; Schmitz, Ulf; Wolkenhauer, Olaf; Gupta, Shailendra K.

    2016-01-01

    Technological and methodological advances in multi-omics data generation and integration approaches help elucidate genetic features of complex biological traits and diseases such as prostate cancer. Due to its heterogeneity, the identification of key functional components involved in the regulation and progression of prostate cancer is a methodological challenge. In this study, we identified key regulatory interactions responsible for primary to metastasis transitions in prostate cancer using network inference approaches by integrating patient derived transcriptomic and miRomics data into gene/miRNA/transcription factor regulatory networks. One such network was derived for each of the clinical states of prostate cancer based on differentially expressed and significantly correlated gene, miRNA and TF pairs from the patient data. We identified key elements of each network using a network analysis approach and validated our results using patient survival analysis. We observed that HOXD10, BCL2 and PGR are the most important factors affected in primary prostate samples, whereas, in the metastatic state, STAT3, JUN and JUNB are playing a central role. Benefiting integrative networks our analysis suggests that some of these molecules were targeted by several overexpressed miRNAs which may have a major effect on the dysregulation of these molecules. For example, in the metastatic tumors five miRNAs (miR-671-5p, miR-665, miR-663, miR-512-3p and miR-371-5p) are mainly responsible for the dysregulation of STAT3 and hence can provide an opportunity for early detection of metastasis and development of alternative therapeutic approaches. Our findings deliver new details on key functional components in prostate cancer progression and provide opportunities for the development of alternative therapeutic approaches. PMID:28005952

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

    PubMed

    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.

  19. Network component analysis provides quantitative insights on an Arabidopsis transcription factor-gene regulatory network

    PubMed Central

    2013-01-01

    Background Gene regulatory networks (GRNs) are models of molecule-gene interactions instrumental in the coordination of gene expression. Transcription factor (TF)-GRNs are an important subset of GRNs that characterize gene expression as the effect of TFs acting on their target genes. Although such networks can qualitatively summarize TF-gene interactions, it is highly desirable to quantitatively determine the strengths of the interactions in a TF-GRN as well as the magnitudes of TF activities. To our knowledge, such analysis is rare in plant biology. A computational methodology developed for this purpose is network component analysis (NCA), which has been used for studying large-scale microbial TF-GRNs to obtain nontrivial, mechanistic insights. In this work, we employed NCA to quantitatively analyze a plant TF-GRN important in floral development using available regulatory information from AGRIS, by processing previously reported gene expression data from four shoot apical meristem cell types. Results The NCA model satisfactorily accounted for gene expression measurements in a TF-GRN of seven TFs (LFY, AG, SEPALLATA3 [SEP3], AP2, AGL15, HY5 and AP3/PI) and 55 genes. NCA found strong interactions between certain TF-gene pairs including LFY → MYB17, AG → CRC, AP2 → RD20, AGL15 → RAV2 and HY5 → HLH1, and the direction of the interaction (activation or repression) for some AGL15 targets for which this information was not previously available. The activity trends of four TFs - LFY, AG, HY5 and AP3/PI as deduced by NCA correlated well with the changes in expression levels of the genes encoding these TFs across all four cell types; such a correlation was not observed for SEP3, AP2 and AGL15. Conclusions For the first time, we have reported the use of NCA to quantitatively analyze a plant TF-GRN important in floral development for obtaining nontrivial information about connectivity strengths between TFs and their target genes as well as TF

  20. Differentially expressed regulatory genes in honey bee caste development

    NASA Astrophysics Data System (ADS)

    Hepperle, C.; Hartfelder, K.

    2001-03-01

    In the honey bee, an eminently fertile queen with up to 200 ovarioles per ovary monopolizes colony level reproduction. In contrast, worker bees have only few ovarioles and are essentially sterile. This phenotype divergence is a result of caste-specifically modulated juvenile hormone and ecdysteroid titers in larval development. In this study we employed a differential-display reverse transcription (DDRT)-PCR protocol to detect ecdysteroid-regulated gene expression during a critical phase of caste development. We identified a Ftz-F1 homolog and a Cut-like transcript. Ftz-F1 could be a putative element of the metamorphic ecdysone response cascade of bees, whereas Cut-like proteins are described as transcription factors involved in maintaining cellular differentiation states. The downregulation of both factors can be interpreted as steps in the metamorphic degradation of ovarioles in worker-bee ovaries.

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

    PubMed

    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.

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

    PubMed Central

    Menéndez, Patricia; Kourmpetis, Yiannis A. I.; ter Braak, Cajo J. F.; van Eeuwijk, Fred 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 of steady-state levels obtained after applying multifactorial perturbations to the original in silico network. Due to the static character of the challenge data, we tackled the problem via a sparse Gaussian Markov Random Field, which relates network topology with the covariance inverse generated by the gene measurements. As for the computations, we used the Graphical Lasso algorithm which provided a large range of candidate network topologies. The main task was to select the optimal network topology and for that, different model selection criteria were explored. The selected networks were compared with the golden standards and the results ranked using the scoring metrics applied in the challenge, giving a better insight in our submission and the way to improve it. Our approach provides an easy statistical and computational framework to infer gene regulatory networks that is suitable for large networks, even if the number of the observations (perturbations) is greater than the number of variables (genes). PMID:21188141

  3. Causal structure of oscillations in gene regulatory networks: Boolean analysis of ordinary differential equation attractors.

    PubMed

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

    2013-06-01

    A common approach to the modeling of gene regulatory networks is to represent activating or repressing interactions using ordinary differential equations for target gene concentrations that include Hill function dependences on regulator gene concentrations. An alternative formulation represents the same interactions using Boolean logic with time delays associated with each network link. We consider the attractors that emerge from the two types of models in the case of a simple but nontrivial network: a figure-8 network with one positive and one negative feedback loop. We show that the different modeling approaches give rise to the same qualitative set of attractors with the exception of a possible fixed point in the ordinary differential equation model in which concentrations sit at intermediate values. The properties of the attractors are most easily understood from the Boolean perspective, suggesting that time-delay Boolean modeling is a useful tool for understanding the logic of regulatory networks.

  4. Causal structure of oscillations in gene regulatory networks: Boolean analysis of ordinary differential equation attractors

    PubMed Central

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

    2013-01-01

    A common approach to the modeling of gene regulatory networks is to represent activating or repressing interactions using ordinary differential equations for target gene concentrations that include Hill function dependences on regulator gene concentrations. An alternative formulation represents the same interactions using Boolean logic with time delays associated with each network link. We consider the attractors that emerge from the two types of models in the case of a simple but nontrivial network: a figure-8 network with one positive and one negative feedback loop. We show that the different modeling approaches give rise to the same qualitative set of attractors with the exception of a possible fixed point in the ordinary differential equation model in which concentrations sit at intermediate values. The properties of the attractors are most easily understood from the Boolean perspective, suggesting that time-delay Boolean modeling is a useful tool for understanding the logic of regulatory networks. PMID:23822502

  5. High regulatory gene use in sea urchin embryogenesis: Implications for bilaterian development and evolution.

    PubMed

    Howard-Ashby, Meredith; Materna, Stefan C; Brown, C Titus; Tu, Qiang; Oliveri, Paola; Cameron, R Andrew; Davidson, Eric H

    2006-12-01

    A global scan of transcription factor usage in the sea urchin embryo was carried out in the context of the Strongylocentrotus purpuratus genome sequencing project, and results from six individual studies are here considered. Transcript prevalence data were obtained for over 280 regulatory genes encoding sequence-specific transcription factors of every known family, but excluding genes encoding zinc finger proteins. This is a statistically inclusive proxy for the total "regulome" of the sea urchin genome. Close to 80% of the regulome is expressed at significant levels by the late gastrula stage. Most regulatory genes must be used repeatedly for different functions as development progresses. An evolutionary implication is that animal complexity at the stage when the regulome first evolved was far simpler than even the last common bilaterian ancestor, and is thus of deep antiquity.

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

    PubMed

    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.

  7. Data- and knowledge-based modeling of gene regulatory networks: an update

    PubMed Central

    Linde, Jörg; Schulze, Sylvie; Henkel, Sebastian G.; Guthke, Reinhard

    2015-01-01

    Gene regulatory network inference is a systems biology approach which predicts interactions between genes with the help of high-throughput data. In this review, we present current and updated network inference methods focusing on novel techniques for data acquisition, network inference assessment, network inference for interacting species and the integration of prior knowledge. After the advance of Next-Generation-Sequencing of cDNAs derived from RNA samples (RNA-Seq) we discuss in detail its application to network inference. Furthermore, we present progress for large-scale or even full-genomic network inference as well as for small-scale condensed network inference and review advances in the evaluation of network inference methods by crowdsourcing. Finally, we reflect the current availability of data and prior knowledge sources and give an outlook for the inference of gene regulatory networks that reflect interacting species, in particular pathogen-host interactions. PMID:27047314

  8. The Transcriptional and Gene Regulatory Network of Lactococcus lactis MG1363 during Growth in Milk

    PubMed Central

    de Jong, Anne; Hansen, Morten E.; Kuipers, Oscar P.; Kilstrup, Mogens; Kok, Jan

    2013-01-01

    In the present study we examine the changes in the expression of genes of Lactococcus lactis subspecies cremoris MG1363 during growth in milk. To reveal which specific classes of genes (pathways, operons, regulons, COGs) are important, we performed a transcriptome time series experiment. Global analysis of gene expression over time showed that L. lactis adapted quickly to the environmental changes. Using upstream sequences of genes with correlated gene expression profiles, we uncovered a substantial number of putative DNA binding motifs that may be relevant for L. lactis fermentative growth in milk. All available novel and literature-derived data were integrated into network reconstruction building blocks, which were used to reconstruct and visualize the L. lactis gene regulatory network. This network enables easy mining in the chrono-transcriptomics data. A freely available website at http://milkts.molgenrug.nl gives full access to all transcriptome data, to the reconstructed network and to the individual network building blocks. PMID:23349698

  9. A versatile element for gene addition in bacterial chromosomes

    PubMed Central

    Sibley, Marion H.; Raleigh, Elisabeth A.

    2012-01-01

    The increasing interest in genetic manipulation of bacterial host metabolic pathways for protein or small molecule production has led to a need to add new genes to a chromosome quickly and easily without leaving behind a selectable marker. The present report describes a vector and four-day procedure that enable site-specific chromosomal insertion of cloned genes in a context insulated from external transcription, usable once in a construction series. The use of rhamnose-inducible transcription from rhaBp allows regulation of the inserted genes independently of the commonly used IPTG and arabinose strategies. Using lacZ as a reporter, we first show that expression from the rhamnose promoter is tightly regulatable, exhibiting very low leakage of background expression compared with background, and moderate rhamnose-induced expression compared with IPTG-induced expression from lacp. Second, the expression of a DNA methyltransferase was used to show that rhamnose regulation yielded on-off expression of this enzyme, such that a resident high-copy plasmid was either fully sensitive or fully resistant to isoschizomer restriction enzyme cleavage. In both cases, growth medium manipulation allows intermediate levels of expression. The vehicle can also be adapted as an ORF-cloning vector. PMID:22123741

  10. A General Approach for Identifying Distant Regulatory Elements Applied to the Gdf6 Gene

    PubMed Central

    Mortlock, Douglas P.; Guenther, Catherine; Kingsley, David M.

    2003-01-01

    Regulatory sequences in higher genomes can map large distances from gene coding regions, and cannot yet be identified by simple inspection of primary DNA sequence information. Here we describe an efficient method of surveying large genomic regions for gene regulatory information, and subdividing complex sets of distant regulatory elements into smaller intervals for detailed study. The mouse Gdf6 gene is expressed in a number of distinct embryonic locations that are involved in the patterning of skeletal and soft tissues. To identify sequences responsible for Gdf6 regulation, we first isolated a series of overlapping bacterial artificial chromosomes (BACs) that extend varying distances upstream and downstream of the gene. A LacZ reporter cassette was integrated into the Gdf6 transcription unit of each BAC using homologous recombination in bacteria. Each modified BAC was injected into fertilized mouse eggs, and founder transgenic embryos were analyzed for LacZ expression mid-gestation. The overlapping segments defined by the BAC clones revealed five separate regulatory regions that drive LacZ expression in 11 distinct anatomical locations. To further localize sequences that control expression in developing skeletal joints, we created a series of BAC constructs with precise deletions across a putative joint-control region. This approach further narrowed the critical control region to an area containing several stretches of sequence that are highly conserved between mice and humans. A distant 2.9-kilobase fragment containing the highly conserved regions is able to direct very specific expression of a minimal promoter/LacZ reporter in proximal limb joints. These results demonstrate that even distant, complex regulatory sequences can be identified using a combination of BAC scanning, BAC deletion, and comparative sequencing approaches. PMID:12915490

  11. Integrating Quantitative Knowledge into a Qualitative Gene Regulatory Network

    PubMed Central

    Bourdon, Jérémie; Eveillard, Damien; Siegel, Anne

    2011-01-01

    Despite recent improvements in molecular techniques, biological knowledge remains incomplete. Any theorizing about living systems is therefore necessarily based on the use of heterogeneous and partial information. Much current research has focused successfully on the qualitative behaviors of macromolecular networks. Nonetheless, it is not capable of taking into account available quantitative information such as time-series protein concentration variations. The present work proposes a probabilistic modeling framework that integrates both kinds of information. Average case analysis methods are used in combination with Markov chains to link qualitative information about transcriptional regulations to quantitative information about protein concentrations. The approach is illustrated by modeling the carbon starvation response in Escherichia coli. It accurately predicts the quantitative time-series evolution of several protein concentrations using only knowledge of discrete gene interactions and a small number of quantitative observations on a single protein concentration. From this, the modeling technique also derives a ranking of interactions with respect to their importance during the experiment considered. Such a classification is confirmed by the literature. Therefore, our method is principally novel in that it allows (i) a hybrid model that integrates both qualitative discrete model and quantities to be built, even using a small amount of quantitative information, (ii) new quantitative predictions to be derived, (iii) the robustness and relevance of interactions with respect to phenotypic criteria to be precisely quantified, and (iv) the key features of the model to be extracted that can be used as a guidance to design future experiments. PMID:21935350

  12. Hidden Markov induced Dynamic Bayesian Network for recovering time evolving gene regulatory networks

    NASA Astrophysics Data System (ADS)

    Zhu, Shijia; Wang, Yadong

    2015-12-01

    Dynamic Bayesian Networks (DBN) have been widely used to recover gene regulatory relationships from time-series data in computational systems biology. Its standard assumption is ‘stationarity’, and therefore, several research efforts have been recently proposed to relax this restriction. However, those methods suffer from three challenges: long running time, low accuracy and reliance on parameter settings. To address these problems, we propose a novel non-stationary DBN model by extending each hidden node of Hidden Markov Model into a DBN (called HMDBN), which properly handles the underlying time-evolving networks. Correspondingly, an improved structural EM algorithm is proposed to learn the HMDBN. It dramatically reduces searching space, thereby substantially improving computational efficiency. Additionally, we derived a novel generalized Bayesian Information Criterion under the non-stationary assumption (called BWBIC), which can help significantly improve the reconstruction accuracy and largely reduce over-fitting. Moreover, the re-estimation formulas for all parameters of our model are derived, enabling us to avoid reliance on parameter settings. Compared to the state-of-the-art methods, the experimental evaluation of our proposed method on both synthetic and real biological data demonstrates more stably high prediction accuracy and significantly improved computation efficiency, even with no prior knowledge and parameter settings.

  13. MicroRNAs in control of gene regulatory programs in diabetic vasculopathy.

    PubMed

    Pei, Chongzhe; Zhang, Xiaoping; Meng, Shu; Li, Yigang

    2017-01-01

    Diabetes is generally associated with vasculopathy, which contains both microvascular and macrovascular complications, associated with high morbidity and mortality. Currently, despite interventional therapy, the overall prognosis for patients with diabetic vasculopathy remains unsatisfactory. Angiogenesis and vascular injury and repair are associated with a variety of cells. However, the molecular mechanisms of the cells that are involved in pathogenesis of diabetic vasculopathy remain largely unknown. As novel molecules, microRNAs (miRs) take part in regulating protein-coding gene expression at the post-transcriptional level, and contribute to the pathogenesis of various types of chronic metabolism disease, especially diabetic vasculopathy. This allows miRs to have a direct function in regulation of various cellular events. Additionally, circulating miRs have been proposed as biomarkers for a wide range of cardiovascular diseases. This review elucidates miR-mediated regulatory mechanisms in diabetic vasculopathy. Furthermore, we discuss the current understanding of miRs in diabetic vasculopathy. Finally, we summarize the development of novel diagnostic and therapeutic strategies for diabetic vasculopathy related to miRs.

  14. Modulation of neoplastic gene regulatory pathways by the RNA-binding factor AUF1

    PubMed Central

    Zucconi, Beth E.; Wilson, Gerald M.

    2013-01-01

    The mRNA-binding protein AUF1 regulates the expression of many key players in cancer including proto-oncogenes, regulators of apoptosis and the cell cycle, and pro-inflammatory cytokines, principally by directing the decay kinetics of their encoded mRNAs. Most studies support an mRNA-destabilizing role for AUF1, although other findings suggest additional functions for this factor. In this review, we explore how changes in AUF1 isoform distribution, subcellular localization, and post-translational protein modifications can influence the metabolism of targeted mRNAs. However, several lines of evidence also support a role for AUF1 in the initiation and/or development of cancer. Many AUF1-targeted transcripts encode products that control pro- and anti-oncogenic processes. Also, overexpression of AUF1 enhances tumorigenesis in murine models, and AUF1 levels are enhanced in some tumors. Finally, signaling cascades that modulate AUF1 function are deregulated in some cancerous tissues. Together, these features suggest that AUF1 may play a prominent role in regulating the expression of many genes that can contribute to tumorigenic phenotypes, and that this post-transcriptional regulatory control point may be subverted by diverse mechanisms in neoplasia. PMID:21622178

  15. Preservation of Gene Duplication Increases the Regulatory Spectrum of Ribosomal Protein Genes and Enhances Growth under Stress.

    PubMed

    Parenteau, Julie; Lavoie, Mathieu; Catala, Mathieu; Malik-Ghulam, Mustafa; Gagnon, Jules; Abou Elela, Sherif

    2015-12-22

    In baker's yeast, the majority of ribosomal protein genes (RPGs) are duplicated, and it was recently proposed that such duplications are preserved via the functional specialization of the duplicated genes. However, the origin and nature of duplicated RPGs' (dRPGs) functional specificity remain unclear. In this study, we show that differences in dRPG functions are generated by variations in the modality of gene expression and, to a lesser extent, by protein sequence. Analysis of the sequence and expression patterns of non-intron-containing RPGs indicates that each dRPG is controlled by specific regulatory sequences modulating its expression levels in response to changing growth conditions. Homogenization of dRPG sequences reduces cell tolerance to growth under stress without changing the number of expressed genes. Together, the data reveal a model where duplicated genes provide a means for modulating the expression of ribosomal proteins in response to stress.

  16. Congruence of additive and non-additive effects on gene expression estimated from pedigree and SNP data.

    PubMed

    Powell, Joseph E; Henders, Anjali K; McRae, Allan F; Kim, Jinhee; Hemani, Gibran; Martin, Nicholas G; Dermitzakis, Emmanouil T; Gibson, Greg; Montgomery, Grant W; Visscher, Peter M

    2013-05-01

    There is increasing evidence that heritable variation in gene expression underlies genetic variation in susceptibility to disease. Therefore, a comprehensive understanding of the similarity between relatives for transcript variation is warranted--in particular, dissection of phenotypic variation into additive and non-additive genetic factors and shared environmental effects. We conducted a gene expression study in blood samples of 862 individuals from 312 nuclear families containing MZ or DZ twin pairs using both pedigree and genotype information. From a pedigree analysis we show that the vast majority of genetic variation across 17,994 probes is additive, although non-additive genetic variation is identified for 960 transcripts. For 180 of the 960 transcripts with non-additive genetic variation, we identify expression quantitative trait loci (eQTL) with dominance effects in a sample of 339 unrelated individuals and replicate 31% of these associations in an independent sample of 139 unrelated individuals. Over-dominance was detected and replicated for a trans association between rs12313805 and ETV6, located 4MB apart on chromosome 12. Surprisingly, only 17 probes exhibit significant levels of common environmental effects, suggesting that environmental and lifestyle factors common to a family do not affect expression variation for most transcripts, at least those measured in blood. Consistent with the genetic architecture of common diseases, gene expression is predominantly additive, but a minority of transcripts display non-additive effects.

  17. Conservation and Diversification of an Ancestral Chordate Gene Regulatory Network for Dorsoventral Patterning

    PubMed Central

    Kozmikova, Iryna; Smolikova, Jana; Vlcek, Cestmir; Kozmik, Zbynek

    2011-01-01

    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. PMID:21304903

  18. Role of Conserved Non-Coding Regulatory Elements in LMW Glutenin Gene Expression

    PubMed Central

    Juhász, Angéla; Makai, Szabolcs; Sebestyén, Endre; Tamás, László; Balázs, Ervin

    2011-01-01

    Transcriptional regulation of LMW glutenin genes were investigated in-silico, using publicly available gene sequences and expression data. Genes were grouped into different LMW glutenin types and their promoter profiles were determined using cis-acting regulatory elements databases and published results. The various cis-acting elements belong to some conserved non-coding regulatory regions (CREs) and might act in two different ways. There are elements, such as GCN4 motifs found in the long endosperm box that could serve as key factors in tissue-specific expression. Some other elements, such as the AACA/TA motifs or the individual prolamin box variants, might modulate the level of expression. Based on the promoter sequences and expression characteristic LMW glutenin genes might be transcribed following two different mechanisms. Most of the s- and i-type genes show a continuously increasing expression pattern. The m-type genes, however, demonstrate normal distribution in their expression profiles. Differences observed in their expression could be related to the differences found in their promoter sequences. Polymorphisms in the number and combination of cis-acting elements in their promoter regions can be of crucial importance in the diverse levels of production of single LMW glutenin gene types. PMID:22242127

  19. A Genome-Wide Regulatory Framework Identifies Maize Pericarp Color1 Controlled Genes[C][W

    PubMed Central

    Morohashi, Kengo; Casas, María Isabel; Ferreyra, Lorena Falcone; Mejía-Guerra, María Katherine; Pourcel, Lucille; Yilmaz, Alper; Feller, Antje; Carvalho, Bruna; Emiliani, Julia; Rodriguez, Eduardo; Pellegrinet, Silvina; McMullen, Michael; Casati, Paula; Grotewold, Erich

    2012-01-01

    Pericarp Color1 (P1) encodes an R2R3-MYB transcription factor responsible for the accumulation of insecticidal flavones in maize (Zea mays) silks and red phlobaphene pigments in pericarps and other floral tissues, which makes P1 an important visual marker. Using genome-wide expression analyses (RNA sequencing) in pericarps and silks of plants with contrasting P1 alleles combined with chromatin immunoprecipitation coupled with high-throughput sequencing, we show here that the regulatory functions of P1 are much broader than the activation of genes corresponding to enzymes in a branch of flavonoid biosynthesis. P1 modulates the expression of several thousand genes, and ∼1500 of them were identified as putative direct targets of P1. Among them, we identified F2H1, corresponding to a P450 enzyme that converts naringenin into 2-hydroxynaringenin, a key branch point in the P1-controlled pathway and the first step in the formation of insecticidal C-glycosyl flavones. Unexpectedly, the binding of P1 to gene regulatory regions can result in both gene activation and repression. Our results indicate that P1 is the major regulator for a set of genes involved in flavonoid biosynthesis and a minor modulator of the expression of a much larger gene set that includes genes involved in primary metabolism and production of other specialized compounds. PMID:22822204

  20. Understanding microRNA-mediated gene regulatory networks through mathematical modelling

    PubMed Central

    Lai, Xin; Wolkenhauer, Olaf; Vera, Julio

    2016-01-01

    The discovery of microRNAs (miRNAs) has added a new player to the regulation of gene expression. With the increasing number of molecular species involved in gene regulatory networks, it is hard to obtain an intuitive understanding of network dynamics. Mathematical modelling can help dissecting the role of miRNAs in gene regulatory networks, and we shall here review the most recent developments that utilise different mathematical modelling approaches to provide quantitative insights into the function of miRNAs in the regulation of gene expression. Key miRNA regulation features that have been elucidated via modelling include: (i) the role of miRNA-mediated feedback and feedforward loops in fine-tuning of gene expression; (ii) the miRNA–target interaction properties determining the effectiveness of miRNA-mediated gene repression; and (iii) the competition for shared miRNAs leading to the cross-regulation of genes. However, there is still lack of mechanistic understanding of many other properties of miRNA regulation like unconventional miRNA–target interactions, miRNA regulation at different sub-cellular locations and functional miRNA variant, which will need future modelling efforts to deal with. This review provides an overview of recent developments and challenges in this field. PMID:27317695

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

    PubMed Central

    Guzmán-Vargas, Lev; Santillán, Moisés

    2008-01-01

    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 times larger in S

  2. A Machine Learning Approach to Predict Gene Regulatory Networks in Seed Development in Arabidopsis

    PubMed Central

    Ni, Ying; Aghamirzaie, Delasa; Elmarakeby, Haitham; Collakova, Eva; Li, Song; Grene, Ruth; Heath, Lenwood S.

    2016-01-01

    Gene regulatory networks (GRNs) provide a representation of relationships between regulators and their target genes. Several methods for GRN inference, both unsupervised and supervised, have been developed to date. Because regulatory relationships consistently reprogram in diverse tissues or under different conditions, GRNs inferred without specific biological contexts are of limited applicability. In this report, a machine learning approach is presented to predict GRNs specific to developing Arabidopsis thaliana embryos. We developed the Beacon GRN inference tool to predict GRNs occurring during seed development in Arabidopsis based on a support vector machine (SVM) model. We developed both global and local inference models and compared their performance, demonstrating that local models are generally superior for our application. Using both the expression levels of the genes expressed in developing embryos and prior known regulatory relationships, GRNs were predicted for specific embryonic developmental stages. The targets that are strongly positively correlated with their regulators are mostly expressed at the beginning of seed development. Potential direct targets were identified based on a match between the promoter regions of these inferred targets and the cis elements recognized by specific regulators. Our analysis also provides evidence for previously unknown inhibitory effects of three positive regulators of gene expression. The Beacon GRN inference tool provides a valuable model system for context-specific GRN inference and is freely available at https://github.com/BeaconProjectAtVirginiaTech/beacon_network_inference.git. PMID:28066488

  3. A Machine Learning Approach to Predict Gene Regulatory Networks in Seed Development in Arabidopsis.

    PubMed

    Ni, Ying; Aghamirzaie, Delasa; Elmarakeby, Haitham; Collakova, Eva; Li, Song; Grene, Ruth; Heath, Lenwood S

    2016-01-01

    Gene regulatory networks (GRNs) provide a representation of relationships between regulators and their target genes. Several methods for GRN inference, both unsupervised and supervised, have been developed to date. Because regulatory relationships consistently reprogram in diverse tissues or under different conditions, GRNs inferred without specific biological contexts are of limited applicability. In this report, a machine learning approach is presented to predict GRNs specific to developing Arabidopsis thaliana embryos. We developed the Beacon GRN inference tool to predict GRNs occurring during seed development in Arabidopsis based on a support vector machine (SVM) model. We developed both global and local inference models and compared their performance, demonstrating that local models are generally superior for our application. Using both the expression levels of the genes expressed in developing embryos and prior known regulatory relationships, GRNs were predicted for specific embryonic developmental stages. The targets that are strongly positively correlated with their regulators are mostly expressed at the beginning of seed development. Potential direct targets were identified based on a match between the promoter regions of these inferred targets and the cis elements recognized by specific regulators. Our analysis also provides evidence for previously unknown inhibitory effects of three positive regulators of gene expression. The Beacon GRN inference tool provides a valuable model system for context-specific GRN inference and is freely available at https://github.com/BeaconProjectAtVirginiaTech/beacon_network_inference.git.

  4. Reducing the computational complexity of information theoretic approaches for reconstructing gene regulatory networks.

    PubMed

    Qiu, Peng; Gentles, Andrew J; Plevritis, Sylvia K

    2010-02-01

    Information theoretic approaches are increasingly being used for reconstructing regulatory networks from microarray data. These approaches start by computing the pairwise mutual information (MI) between all gene pairs. The resulting MI matrix is then manipulated to identify regulatory relationships. A barrier to these approaches is the time-consuming step of computing the MI matrix. We present a method to reduce this computation time. We apply spectral analysis to re-order the genes, so that genes that share regulatory relationships are more likely to be placed close to each other. Then, using a "sliding window" approach with appropriate window size and step size, we compute the MI for the genes within the sliding window, and the remainder is assumed to be zero. Using both simulated data and microarray data, we demonstrate that our method does not incur performance loss in regions of high-precision and low-recall, while the computational time is significantly lowered. The proposed method can be used with any method that relies on the mutual information to reconstruct networks.

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

    PubMed Central

    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

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

    PubMed

    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.

  7. An efficient data assimilation schema for restoration and extension of gene regulatory networks using time-course observation data.

    PubMed

    Hasegawa, Takanori; Mori, Tomoya; Yamaguchi, Rui; Imoto, Seiya; Miyano, Satoru; Akutsu, Tatsuya

    2014-11-01

    Gene regulatory networks (GRNs) play a central role in sustaining complex biological systems in cells. Although we can construct GRNs by integrating biological interactions that have been recorded in literature, they can include suspicious data and a lack of information. Therefore, there has been an urgent need for an approach by which the validity of constructed networks can be evaluated; simulation-based methods have been applied in which biological observational data are assimilated. However, these methods apply nonlinear models that require high computational power to evaluate even one network consisting of only several genes. Therefore, to explore candidate networks whose simulation models can better predict the data by modifying and extending literature-based GRNs, an efficient and versatile method is urgently required. We applied a combinatorial transcription model, which can represent combinatorial regulatory effects of genes, as a biological simulation model, to reproduce the dynamic behavior of gene expressions within a state space model. Under the model, we applied the unscented Kalman filter to obtain the approximate posterior probability distribution of the hidden state to efficiently estimate parameter values maximizing prediction ability for observational data by the EM-algorithm. Utilizing the method, we propose a novel algorithm to modify GRNs reported in the literature so that their simulation models become consistent with observed data. The effectiveness of our approach was validated through comparison analysis to the previous methods using synthetic networks. Finally, as an application example, a Kyoto Encyclopedia of Genes and Genomes (KEGG)-based yeast cell cycle network was extended with additional candidate genes to better predict the real mRNA expressions data using the proposed method.

  8. Gene-scrambling mutagenesis: generation and analysis of insertional mutations in the alginate regulatory region of Pseudomonas aeruginosa.

    PubMed Central

    Mohr, C D; Deretic, V

    1990-01-01

    A novel method for random mutagenesis of targeted chromosomal regions in Pseudomona aeruginosa was developed. This method can be used with a cloned DNA fragment of indefinite size that contains a putative gene of interest. Cloned DNA is digested to produce small fragments that are then randomly reassembled into long DNA inserts by using cosmid vectors and lambda packaging reaction. This DNA is then transferred into P. aeruginosa and forced into the chromosome via homologous recombination, producing in a single step a random set of insertional mutants along a desired region of the chromosome. Application of this method to extend the analysis of the alginate regulatory region, using a cloned 6.2-kb fragment with the algR gene and the previously uncharacterized flanking regions, produced several insertional mutations. One mutation was obtained in algR, a known transcriptional regulatory of mucoidy in P. aeruginosa. The null mutation of algR was generated in a mucoid derivative of the standard genetic strain PAO responsive to different environmental factors. This mutation was used to demonstrate that the algR gene product was not essential for the regulation of its promoters. Additional insertions were obtained in regions downstream and upstream of algR. A mutation that did not affect mucoidy was generated in a gene located 1 kb upstream of algR. This gene was transcribed in the direction opposite that of algR transcription and encoded a polypeptide of 47 kDa. Partial nucleotide sequence analysis revealed strong homology of its predicted gene product with the human and yeast argininosuccinate lyases. An insertion downstream of algR produced a strain showing reduced induction of mucoidy in response to growth on nitrate as the nitrogen source. Images PMID:2121708

  9. Transcription factors GAF and HSF act at distinct regulatory steps to modulate stress-induced gene activation.

    PubMed

    Duarte, Fabiana M; Fuda, Nicholas J; Mahat, Dig B; Core, Leighton J; Guertin, Michael J; Lis, John T

    2016-08-01

    The coordinated regulation of gene expression at the transcriptional level is fundamental to development and homeostasis. Inducible systems are invaluable when studying transcription because the regulatory process can be triggered instantaneously, allowing the tracking of ordered mechanistic events. Here, we use precision run-on sequencing (PRO-seq) to examine the genome-wide heat shock (HS) response in Drosophila and the function of two key transcription factors on the immediate transcription activation or repression of all genes regulated by HS. We identify the primary HS response genes and the rate-limiting steps in the transcription cycle that GAGA-associated factor (GAF) and HS factor (HSF) regulate. We demonstrate that GAF acts upstream of promoter-proximally paused RNA polymerase II (Pol II) formation (likely at the step of chromatin opening) and that GAF-facilitated Pol II pausing is critical for HS activation. In contrast, HSF is dispensable for establishing or maintaining Pol II pausing but is critical for the release of paused Pol II into the gene body at a subset of highly activated genes. Additionally, HSF has no detectable role in the rapid HS repression of thousands of genes.

  10. A dual cis-regulatory code links IRF8 to constitutive and inducible gene expression in macrophages.

    PubMed

    Mancino, Alessandra; Termanini, Alberto; Barozzi, Iros; Ghisletti, Serena; Ostuni, Renato; Prosperini, Elena; Ozato, Keiko; Natoli, Gioacchino

    2015-02-15

    The transcription factor (TF) interferon regulatory factor 8 (IRF8) controls both developmental and inflammatory stimulus-inducible genes in macrophages, but the mechanisms underlying these two different functions are largely unknown. One possibility is that these different roles are linked to the ability of IRF8 to bind alternative DNA sequences. We found that IRF8 is recruited to distinct sets of DNA consensus sequences before and after lipopolysaccharide (LPS) stimulation. In resting cells, IRF8 was mainly bound to composite sites together with the master regulator of myeloid development PU.1. Basal IRF8-PU.1 binding maintained the expression of a broad panel of genes essential for macrophage functions (such as microbial recognition and response to purines) and contributed to basal expression of many LPS-inducible genes. After LPS stimulation, increased expression of IRF8, other IRFs, and AP-1 family TFs enabled IRF8 binding to thousands of additional regions containing low-affinity multimerized IRF sites and composite IRF-AP-1 sites, which were not premarked by PU.1 and did not contribute to the basal IRF8 cistrome. While constitutively expressed IRF8-dependent genes contained only sites mediating basal IRF8/PU.1 recruitment, inducible IRF8-dependent genes contained variable combinations of constitutive and inducible sites. Overall, these data show at the genome scale how the same TF can be linked to constitutive and inducible gene regulation via distinct combinations of alternative DNA-binding sites.

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

    PubMed Central

    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. PMID:27014338

  12. Conservation and divergence of autonomous pathway genes in the flowering regulatory network of Beta vulgaris.

    PubMed

    Abou-Elwafa, Salah F; Büttner, Bianca; Chia, Tansy; Schulze-Buxloh, Gretel; Hohmann, Uwe; Mutasa-Göttgens, Effie; Jung, Christian; Müller, Andreas E

    2011-06-01

    The transition from vegetative growth to reproductive development is a complex process that requires an integrated response to multiple environmental cues and endogenous signals. In Arabidopsis thaliana, which has a facultative requirement for vernalization and long days, the genes of the autonomous pathway function as floral promoters by repressing the central repressor and vernalization-regulatory gene FLC. Environmental regulation by seasonal changes in daylength is under control of the photoperiod pathway and its key gene CO. The root and leaf crop species Beta vulgaris in the caryophyllid clade of core eudicots, which is only very distantly related to Arabidopsis, is an obligate long-day plant and includes forms with or without vernalization requirement. FLC and CO homologues with related functions in beet have been identified, but the presence of autonomous pathway genes which function in parallel to the vernalization and photoperiod pathways has not yet been reported. Here, this begins to be addressed by the identification and genetic mapping of full-length homologues of the RNA-regulatory gene FLK and the chromatin-regulatory genes FVE, LD, and LDL1. When overexpressed in A. thaliana, BvFLK accelerates bolting in the Col-0 background and fully complements the late-bolting phenotype of an flk mutant through repression of FLC. In contrast, complementation analysis of BvFVE1 and the presence of a putative paralogue in beet suggest evolutionary divergence of FVE homologues. It is further shown that BvFVE1, unlike FVE in Arabidopsis, is under circadian clock control. Together, the data provide first evidence for evolutionary conservation of components of the autonomous pathway in B. vulgaris, while also suggesting divergence or subfunctionalization of one gene. The results are likely to be of broader relevance because B. vulgaris expands the spectrum of evolutionarily diverse species which are subject to differential developmental and/or environmental regulation

  13. The Influence of Promoter Architectures and Regulatory Motifs on Gene Expression in Escherichia coli

    PubMed Central

    Rydenfelt, Mattias; Garcia, Hernan G.; Cox, Robert Sidney; Phillips, Rob

    2014-01-01

    The ability to regulate gene expression is of central importance for the adaptability of living organisms to changes in their external and internal environment. At the transcriptional level, binding of transcription factors (TFs) in the promoter region can modulate the transcription rate, hence making TFs central players in gene regulation. For some model organisms, information about the locations and identities of discovered TF binding sites have been collected in continually updated databases, such as RegulonDB for the well-studied case of E. coli. In order to reveal the general principles behind the binding-site arrangement and function of these regulatory architectures we propose a random promoter architecture model that preserves the overall abundance of binding sites to identify overrepresented binding site configurations. This model is analogous to the random network model used in the study of genetic network motifs, where regulatory motifs are identified through their overrepresentation with respect to a “randomly connected” genetic network. Using our model we identify TF pairs which coregulate operons in an overrepresented fashion, or individual TFs which act at multiple binding sites per promoter by, for example, cooperative binding, DNA looping, or through multiple binding domains. We furthermore explore the relationship between promoter architecture and gene expression, using three different genome-wide protein copy number censuses. Perhaps surprisingly, we find no systematic correlation between the number of activator and repressor binding sites regulating a gene and the level of gene expression. A position-weight-matrix model used to estimate the binding affinity of RNA polymerase (RNAP) to the promoters of activated and repressed genes suggests that this lack of correlation might in part be due to differences in basal transcription levels, with repressed genes having a higher basal activity level. This quantitative catalogue relating promoter

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

    PubMed

    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.

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

    PubMed

    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.

  16. Reconstruction of gene regulatory network related to photosynthesis in Arabidopsis thaliana

    PubMed Central

    Yu, Xianbin; Zheng, Guangyong; Shan, Lanlan; Meng, Guofeng; Vingron, Martin; Liu, Qi; Zhu, Xin-Guang

    2014-01-01

    Photosynthesis is one of the most important biological processes on the earth. So far, though the molecular mechanisms underlying photosynthesis is well understood, however, the regulatory networks of photosynthesis are poorly studied. Given the current interest in improving photosynthetic efficiency for greater crop yield, elucidating the detailed regulatory networks controlling the construction and maintenance of photosynthetic machinery is not only scientifically significant but also holding great potential in agricultural application. In this study, we first identified transcription factors (TFs) related to photosynthesis through the TRAP approach using position weight matrix information. Then, for TFs related to photosynthesis, interactions between them and their targets were also determined by the ARACNE approach. Finally, a gene regulatory network was established by combining TF-targets information generated by these two approaches. Topological analysis of the regulatory network suggested that (a) the regulatory network of photosynthesis has a property of “small world”; (b) there is substantial coordination mediated by transcription factors between different components in photosynthesis. PMID:24982665

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

    PubMed

    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.

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

    PubMed Central

    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

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

    PubMed Central

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

    2013-01-01

    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. PMID:23754813

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

    PubMed

    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.

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

    PubMed

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

    2013-01-01

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

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

    PubMed

    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.

  3. A novel regulatory element (E77) isolated from CHO‐K1 genomic DNA enhances stable gene expression in Chinese hamster ovary cells

    PubMed Central

    Kang, Shin‐Young; Kim, Yeon‐Gu; Kang, Seunghee; Lee, Hong Weon

    2016-01-01

    Abstract Vectors flanked by regulatory DNA elements have been used to generate stable cell lines with high productivity and transgene stability; however, regulatory elements in Chinese hamster ovary (CHO) cells, which are the most widely used mammalian cells in biopharmaceutical production, are still poorly understood. We isolated a novel gene regulatory element from CHO‐K1 cells, designated E77, which was found to enhance the stable expression of a transgene. A genomic library was constructed by combining CHO‐K1 genomic DNA fragments with a CMV promoter‐driven GFP expression vector, and the E77 element was isolated by screening. The incorporation of the E77 regulatory element resulted in the generation of an increased number of clones with high expression, thereby enhancing the expression level of the transgene in the stable transfectant cell pool. Interestingly, the E77 element was found to consist of two distinct fragments derived from different locations in the CHO genome shotgun sequence. High and stable transgene expression was obtained in transfected CHO cells by combining these fragments. Additionally, the function of E77 was found to be dependent on its site of insertion and specific orientation in the vector construct. Our findings demonstrate that stable gene expression mediated by the CMV promoter in CHO cells may be improved by the isolated novel gene regulatory element E77 identified in the present study. PMID:26762773

  4. A novel regulatory element (E77) isolated from CHO-K1 genomic DNA enhances stable gene expression in Chinese hamster ovary cells.

    PubMed

    Kang, Shin-Young; Kim, Yeon-Gu; Kang, Seunghee; Lee, Hong Weon; Lee, Eun Gyo

    2016-05-01

    Vectors flanked by regulatory DNA elements have been used to generate stable cell lines with high productivity and transgene stability; however, regulatory elements in Chinese hamster ovary (CHO) cells, which are the most widely used mammalian cells in biopharmaceutical production, are still poorly understood. We isolated a novel gene regulatory element from CHO-K1 cells, designated E77, which was found to enhance the stable expression of a transgene. A genomic library was constructed by combining CHO-K1 genomic DNA fragments with a CMV promoter-driven GFP expression vector, and the E77 element was isolated by screening. The incorporation of the E77 regulatory element resulted in the generation of an increased number of clones with high expression, thereby enhancing the expression level of the transgene in the stable transfectant cell pool. Interestingly, the E77 element was found to consist of two distinct fragments derived from different locations in the CHO genome shotgun sequence. High and stable transgene expression was obtained in transfected CHO cells by combining these fragments. Additionally, the function of E77 was found to be dependent on its site of insertion and specific orientation in the vector construct. Our findings demonstrate that stable gene expression mediated by the CMV promoter in CHO cells may be improved by the isolated novel gene regulatory element E77 identified in the present study.

  5. Stochastic Analysis of Gene Regulatory Networks using Finite State Projections and Singular Perturbation

    DTIC Science & Technology

    2006-01-01

    Khammash Department of Mechanical Engineering University of California Santa Barbara, CA 93106-5070 Abstract—Considerable recent experimental evidence sug...relevant statistics of the modeled processes. However, the complexity of gene regulatory networks poses serious computational difficulties and makes any...resulting slow manifold FSP algorithm on a simple example arising in the cellular heat shock response mechanism . I. INTRODUCTION Through evolution living

  6. Detecting Functional Divergence after Gene Duplication through Evolutionary Changes in Posttranslational Regulatory Sequences

    PubMed Central

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

    2014-01-01

    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. PMID:25474245

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

    PubMed

    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.

  8. Augmenting Microarray Data with Literature-Based Knowledge to Enhance Gene Regulatory Network Inference

    PubMed Central

    Kilicoglu, Halil; Shin, Dongwook; Rindflesch, Thomas C.

    2014-01-01

    Gene regulatory networks are a crucial aspect of systems biology in describing molecular mechanisms of the cell. Various computational models rely on random gene selection to infer such networks from microarray data. While incorporation of prior knowledge into data analysis has been deemed important, in practice, it has generally been limited to referencing genes in probe sets and using curated knowledge bases. We investigate the impact of augmenting microarray data with semantic relations automatically extracted from the literature, with the view that relations encoding gene/protein interactions eliminate the need for random selection of components in non-exhaustive approaches, producing a more accurate model of cellular behavior. A genetic algorithm is then used to optimize the strength of interactions using microarray data and an artificial neural network fitness function. The result is a directed and weighted network providing the individual contribution of each gene to its target. For testing, we used invasive ductile carcinoma of the breast to query the literature and a microarray set containing gene expression changes in these cells over several time points. Our model demonstrates significantly better fitness than the state-of-the-art model, which relies on an initial random selection of genes. Comparison to the component pathways of the KEGG Pathways in Cancer map reveals that the resulting networks contain both known and novel relationships. The p53 pathway results were manually validated in the literature. 60% of non-KEGG relationships were supported (74% for highly weighted interactions). The method was then applied to yeast data and our model again outperformed the comparison model. Our results demonstrate the advantage of combining gene interactions extracted from the literature in the form of semantic relations with microarray analysis in generating contribution-weighted gene regulatory networks. This methodology can make a significant contribution to

  9. Echinochrome A Increases Mitochondrial Mass and Function by Modulating Mitochondrial Biogenesis Regulatory Genes

    PubMed Central

    Jeong, Seung Hun; Kim, Hyoung Kyu; Song, In-Sung; Noh, Su Jin; Marquez, Jubert; Ko, Kyung Soo; Rhee, Byoung Doo; Kim, Nari; Mishchenko, Natalia P.; Fedoreyev, Sergey A.; Stonik, Valentin A.; Han, Jin

    2014-01-01

    Echinochrome A (Ech A) is a natural pigment from sea urchins that has been reported to have antioxidant properties and a cardio protective effect against ischemia reperfusion injury. In this study, we ascertained whether Ech A enhances the mitochondrial biogenesis and oxidative phosphorylation in rat cardio myoblast H9c2 cells. To study the effects of Ech A on mitochondrial biogenesis, we measured mitochondrial mass, level of oxidative phosphorylation, and mitochondrial biogenesis regulatory gene expression. Ech A treatment did not induce cytotoxicity. However, Ech A treatment enhanced oxygen consumption rate and mitochondrial ATP level. Likewise, Ech A treatment increased mitochondrial contents in H9c2 cells. Furthermore, Ech A treatment up-regulated biogenesis of regulatory transcription genes, including proliferator-activated receptor gamma co-activator (PGC)-1α, estrogen-related receptor (ERR)-α, peroxisome proliferator-activator receptor (PPAR)-γ, and nuclear respiratory factor (NRF)-1 and such mitochondrial transcription regulatory genes as mitochondrial transcriptional factor A (TFAM), mitochondrial transcription factor B2 (TFB2M), mitochondrial DNA direct polymerase (POLMRT), single strand binding protein (SSBP) and Tu translation elongation factor (TUFM). In conclusion, these data suggest that Ech A is a potentiated marine drug which enhances mitochondrial biogenesis. PMID:25196935

  10. Inferring Gene Regulatory Networks by Singular Value Decomposition and Gravitation Field Algorithm

    PubMed Central

    Zheng, Ming; Wu, Jia-nan; Huang, Yan-xin; Liu, Gui-xia; Zhou, You; Zhou, Chun-guang

    2012-01-01

    Reconstruction of gene regulatory networks (GRNs) is of utmost interest and has become a challenge computational problem in system biology. However, every existing inference algorithm from gene expression profiles has its own advantages and disadvantages. In particular, the effectiveness and efficiency of every previous algorithm is not high enough. In this work, we proposed a novel inference algorithm from gene expression data based on differential equation model. In this algorithm, two methods were included for inferring GRNs. Before reconstructing GRNs, singular value decomposition method was used to decompose gene expression data, determine the algorithm solution space, and get all candidate solutions of GRNs. In these generated family of candidate solutions, gravitation field algorithm was modified to infer GRNs, used to optimize the criteria of differential equation model, and search the best network structure result. The proposed algorithm is validated on both the simulated scale-free network and real benchmark gene regulatory network in networks database. Both the Bayesian method and the traditional differential equation model were also used to infer GRNs, and the results were used to compare with the proposed algorithm in our work. And genetic algorithm and simulated annealing were also used to evaluate gravitation field algorithm. The cross-validation results confirmed the effectiveness of our algorithm, which outperforms significantly other previous algorithms. PMID:23226565

  11. Regulatory and ethical issues for phase I in utero gene transfer studies.

    PubMed

    Strong, Carson

    2011-11-01

    Clinical gene transfer research has involved adult and child subjects, and it is expected that gene transfer in fetal subjects will occur in the future. Some genetic diseases have serious adverse effects on the fetus before birth, and there is hope that prenatal gene therapy could prevent such disease progression. Research in animal models of prenatal gene transfer is actively being pursued. The prospect of human phase I in utero gene transfer studies raises important regulatory and ethical issues. One issue not previously addressed arises in applying U.S. research regulations to such studies. Specifically, current regulations state that research involving greater than minimal risk to the fetus and no prospect of direct benefit to the fetus or pregnant woman is not permitted. Phase I studies will involve interventions such as needle insertions through the uterus, which carry risks to the fetus including spontaneous abortion and preterm birth. It is possible that these risks will be regarded as exceeding minimal. Also, some regard the probability of therapeutic benefit in phase I studies to be so low that these studies do not satisfy the regulatory requirement that they "hold out the prospect of direct benefit" to subjects. On the basis of these considerations, investigators and institutional review boards might reasonably conclude that some phase I in utero studies are not to be permitted. This paper identifies considerations that are relevant to such judgments and explores ethically acceptable ways in which phase I studies can be designed so that they are permitted by the regulations.

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

    PubMed

    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.

  13. Inferring gene regulatory networks by singular value decomposition and gravitation field algorithm.

    PubMed

    Zheng, Ming; Wu, Jia-nan; Huang, Yan-xin; Liu, Gui-xia; Zhou, You; Zhou, Chun-guang

    2012-01-01

    Reconstruction of gene regulatory networks (GRNs) is of utmost interest and has become a challenge computational problem in system biology. However, every existing inference algorithm from gene expression profiles has its own advantages and disadvantages. In particular, the effectiveness and efficiency of every previous algorithm is not high enough. In this work, we proposed a novel inference algorithm from gene expression data based on differential equation model. In this algorithm, two methods were included for inferring GRNs. Before reconstructing GRNs, singular value decomposition method was used to decompose gene expression data, determine the algorithm solution space, and get all candidate solutions of GRNs. In these generated family of candidate solutions, gravitation field algorithm was modified to infer GRNs, used to optimize the criteria of differential equation model, and search the best network structure result. The proposed algorithm is validated on both the simulated scale-free network and real benchmark gene regulatory network in networks database. Both the Bayesian method and the traditional differential equation model were also used to infer GRNs, and the results were used to compare with the proposed algorithm in our work. And genetic algorithm and simulated annealing were also used to evaluate gravitation field algorithm. The cross-validation results confirmed the effectiveness of our algorithm, which outperforms significantly other previous algorithms.

  14. Control design for sustained oscillation in a two-gene regulatory network.

    PubMed

    Edwards, Roderick; Kim, Sehjeong; van den Driessche, P

    2011-04-01

    Control strategies for gene regulatory networks have begun to be explored, both experimentally and theoretically, with implications for control of disease as well as for synthetic biology. Recent work has focussed on controls designed to achieve desired stationary states. Another useful objective, however, is the initiation of sustained oscillations in systems where oscillations are normally damped, or even not present. Alternatively, it may be desired to suppress (by damping) oscillations that naturally occur in an uncontrolled network. Here we address these questions in the context of piecewise-affine models of gene regulatory networks with affine controls that match the qualitative nature of the model. In the case of two genes with a single relevant protein concentration threshold per gene, we find that control of production terms (constant control) is effective in generating or suppressing sustained oscillations, while control of decay terms (linear control) is not effective. We derive an easily calculated condition to determine an effective constant control. As an example, we apply our analysis to a model of the carbon response network in Escherichia coli, reduced to the two genes that are essential in understanding its behavior.

  15. NetDiff – Bayesian model selection for differential gene regulatory network inference

    PubMed Central

    Thorne, Thomas

    2016-01-01

    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. PMID:27982083

  16. Regulatory Architecture of Gene Expression Variation in the Threespine Stickleback Gasterosteus aculeatus

    PubMed Central

    Pritchard, Victoria L.; Viitaniemi, Heidi M.; McCairns, R. J. Scott; Merilä, Juha; Nikinmaa, Mikko; Primmer, Craig R.; Leder, Erica H.

    2016-01-01

    Much adaptive evolutionary change is underlain by mutational variation in regions of the genome that regulate gene expression rather than in the coding regions of the genes themselves. An understanding of the role of gene expression variation in facilitating local adaptation will be aided by an understanding of underlying regulatory networks. Here, we characterize the genetic architecture of gene expression variation in the threespine stickleback (Gasterosteus aculeatus), an important model in the study of adaptive evolution. We collected transcriptomic and genomic data from 60 half-sib families using an expression microarray and genotyping-by-sequencing, and located expression quantitative trait loci (eQTL) underlying the variation in gene expression in liver tissue using an interval mapping approach. We identified eQTL for several thousand expression traits. Expression was influenced by polymorphism in both cis- and trans-regulatory regions. Trans-eQTL clustered into hotspots. We did not identify master transcriptional regulators in hotspot locations: rather, the presence of hotspots may be driven by complex interactions between multiple transcription factors. One observed hotspot colocated with a QTL recently found to underlie salinity tolerance in the threespine stickleback. However, most other observed hotspots did not colocate with regions of the genome known to be involved in adaptive divergence between marine and freshwater habitats. PMID:27836907

  17. Integration of metabolic and gene regulatory networks modulates the C. elegans dietary response.

    PubMed

    Watson, Emma; MacNeil, Lesley T; Arda, H Efsun; Zhu, Lihua Julie; Walhout, Albertha J M

    2013-03-28

    Expression profiles are tailored according to dietary input. However, the networks that control dietary responses remain largely uncharacterized. Here, we combine forward and reverse genetic screens to delineate a network of 184 genes that affect the C. elegans dietary response to Comamonas DA1877 bacteria. We find that perturbation of a mitochondrial network composed of enzymes involved in amino acid metabolism and the TCA cycle affects the dietary response. In humans, mutations in the corresponding genes cause inborn diseases of amino acid metabolism, most of which are treated by dietary intervention. We identify several transcription factors (TFs) that mediate the changes in gene expression upon metabolic network perturbations. Altogether, our findings unveil a transcriptional response system that is poised to sense dietary cues and metabolic imbalances, illustrating extensive communication between metabolic networks in the mitochondria and gene regulatory networks in the nucleus.

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

    PubMed Central

    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

  19. Scavenger receptor A gene regulatory elements target gene expression to macrophages and to foam cells of atherosclerotic lesions.

    PubMed Central

    Horvai, A; Palinski, W; Wu, H; Moulton, K S; Kalla, K; Glass, C K

    1995-01-01

    Transcription of the macrophage scavenger receptor A gene is markedly upregulated during monocyte to macrophage differentiation. In these studies, we demonstrate that 291 bp of the proximal scavenger receptor promoter, in concert with a 400-bp upstream enhancer element, is sufficient to direct macrophage-specific expression of a human growth hormone reporter in transgenic mice. These regulatory elements, which contain binding sites for PU.1, AP-1, and cooperating ets-domain transcription factors, are also sufficient to mediate regulation of transgene expression during the in vitro differentiation of bone marrow progenitor cells in response to macrophage colony-stimulating factor. Mutation of the PU.1 binding site within the scavenger receptor promoter severely impairs transgene expression, consistent with a crucial role of PU.1 in regulating the expression of the scavenger receptor gene. The ability of the scavenger receptor promoter and enhancer to target gene expression to macrophages in vivo, including foam cells of atherosclerotic lesions, suggests that these regulatory elements will be of general utility in the study of macrophage differentiation and function by permitting specific modifications of macrophage gene expression. Images Fig. 2 Fig. 3 Fig. 4 Fig. 5 PMID:7777517

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

    PubMed

    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.

  1. Putative cis-regulatory elements in genes highly expressed in rice sperm cells

    PubMed Central

    2011-01-01

    Background The male germ line in flowering plants is initiated within developing pollen grains via asymmetric division. The smaller cell then becomes totally encased within a much larger vegetative cell, forming a unique "cell within a cell structure". The generative cell subsequently divides to give rise to two non-motile diminutive sperm cells, which take part in double fertilization and lead to the seed set. Sperm cells are difficult to investigate because of their presence within the confines of the larger vegetative cell. However, recently developed techniques for the isolation of rice sperm cells and the fully annotated rice genome sequence have allowed for the characterization of the transcriptional repertoire of sperm cells. Microarray gene expression data has identified a subset of rice genes that show unique or highly preferential expression in sperm cells. This information has led to the identification of cis-regulatory elements (CREs), which are conserved in sperm-expressed genes and are putatively associated with the control of cell-specific expression. Findings We aimed to identify the CREs associated with rice sperm cell-specific gene expression data using in silico prediction tools. We analyzed 1-kb upstream regions of the top 40 sperm cell co-expressed genes for over-represented conserved and novel motifs. Analysis of upstream regions with the SIGNALSCAN program with the PLACE database, MEME and the Mclip tool helped to find combinatorial sets of known transcriptional factor-binding sites along with two novel motifs putatively associated with the co-expression of sperm cell-specific genes. Conclusions Our data shows the occurrence of novel motifs, which are putative CREs and are likely targets of transcriptional factors regulating sperm cell gene expression. These motifs can be used to design the experimental verification of regulatory elements and the identification of transcriptional factors that regulate sperm cell-specific gene expression. PMID

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

    DOE PAGES

    Oyserman, Ben O.; Noguera, Daniel R.; del Rio, Tijana Glavina; ...

    2015-11-10

    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 anerobicmore » 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. As a result, this analysis provides a basis and framework for further investigations into Accumulibacter metabolism and the reconstruction of regulatory networks in uncultured organisms.« less

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

    SciTech Connect

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

    2015-11-10

    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. As a result, this analysis provides a basis and framework for further investigations into Accumulibacter metabolism and the reconstruction of regulatory networks in uncultured organisms.

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

    PubMed Central

    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

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

    PubMed Central

    Zhang, Weijia; Le, Thuc Duy; Liu, Lin; Zhou, Zhi-Hua; Li, Jiuyong

    2016-01-01

    Motivation 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. Results 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. PMID:27064982

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

    PubMed

    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.

  7. Gain, Loss and Divergence in Primate Zinc-Finger Genes: A Rich Resource for Evolution of Gene Regulatory Differences between Species

    PubMed Central

    Nowick, Katja; Fields, Christopher; Gernat, Tim; Caetano-Anolles, Derek; Kholina, Nadezda; Stubbs, Lisa

    2011-01-01

    The molecular changes underlying major phenotypic differences between humans and other primates are not well understood, but alterations in gene regulation are likely to play a major role. Here we performed a thorough evolutionary analysis of the largest family of primate transcription factors, the Krüppel-type zinc finger (KZNF) gene family. We identified and curated gene and pseudogene models for KZNFs in three primate species, chimpanzee, orangutan and rhesus macaque, to allow for a comparison with the curated set of human KZNFs. We show that the recent evolutionary history of primate KZNFs has been complex, including many lineage-specific duplications and deletions. We found 213 species-specific KZNFs, among them 7 human-specific and 23 chimpanzee-specific genes. Two human-specific genes were validated experimentally. Ten genes have been lost in humans and 13 in chimpanzees, either through deletion or pseudogenization. We also identified 30 KZNF orthologs with human-specific and 42 with chimpanzee-specific sequence changes that are predicted to affect DNA binding properties of the proteins. Eleven of these genes show signatures of accelerated evolution, suggesting positive selection between humans and chimpanzees. During primate evolution the most extensive re-shaping of the KZNF repertoire, including most gene additions, pseudogenizations, and structural changes occurred within the subfamily homininae. Using zinc finger (ZNF) binding predictions, we suggest potential impact these changes have had on human gene regulatory networks. The large species differences in this family of TFs stands in stark contrast to the overall high conservation of primate genomes and potentially represents a potent driver of primate evolution. PMID:21738707

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

    PubMed

    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.

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

    PubMed Central

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

    2015-01-01

    Abstract 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. PMID:26446758

  10. Expression of flagellin and key regulatory flagellar genes in the non-motile bacterium Piscirickettsia salmonis.

    PubMed

    Carril, Gabriela P; Gómez, Fernando A; Marshall, Sergio H

    2017-02-08

    The Piscirickettsia salmonis genome was screened to evaluate potential flagella-related open reading frames, as well as their genomic organization and eventual expression. A complete and organized set of flagellar genes was found for P. salmonis, although no structural flagellum has ever been reported for this bacterium. To gain further understanding, the hierarchical flagellar cascade described for Legionella pneumophila was used as a reference model for putative analysis in P. salmonis. Specifically, 5 of the most relevant genes from this cascade were chosen, including 3 regulatory genes (fleQ, triggers the cascade; fliA, regulates the σ28-coding gene; and rpoN, an RNA polymerase-dependent gene) and 2 terminal structural genes (flaA and flaB, flagellin and a flagellin-like protein, respectively). Kinetic experiments evaluated gene expressions over time, with P. salmonis assessed in 2 liquid, cell-free media and during infection of the SHK-1 fish cell line. Under all conditions, the 5 target genes were primarily expressed during early growth/infection and were differentially expressed when bacteria encountered environmental stress (i.e. a high-salt concentration). Intriguingly, the flagellin monomer was fully expressed under all growth conditions and was located near the bacterial membrane. While no structural flagellum was detected under any condition, the recombinant flagellin monomer induced a proinflammatory response in SHK-1 cells, suggesting a possible immunomodulatory function. The potential implications of these observations are discussed in the context of P. salmonis biology and pathogenic potential.

  11. A comparative analysis of the evolution, expression, and cis-regulatory element of polygalacturonase genes in grasses and dicots.

    PubMed

    Liang, Ying; Yu, Youjian; Cui, Jinlong; Lyu, Meiling; Xu, Liai; Cao, Jiashu

    2016-11-01

    Cell walls are a distinguishing characteristic of plants essential to their survival. The pectin content of primary cell walls in grasses and dicots is distinctly different. Polygalacturonases (PGs) can degrade pectins and participate in multiple developmental processes of plants. This study comprehensively compared the evolution, expression, and cis-regulatory element of PGs in grasses and dicots. A total of 577 PGs identified from five grasses and five dicots fell into seven clades. Evolutionary analysis demonstrated the distinct differences between grasses and dicots in patterns of gene duplication and loss, and evolutionary rates. Grasses generally contained much fewer clade C and F members than dicots. We found that this disparity was the result of less duplication and more gene losses in grasses. More duplications occurred in clades D and E, and expression analysis showed that most of clade E members were expressed ubiquitously at a high overall level and clade D members were closely related to male reproduction in both grasses and dicots, suggesting their biological functions were highly conserved across species. In addition to the general role in reproductive development, PGs of clades C and F specifically played roles in root development in dicots, shedding light on organ differentiation between the two groups of plants. A regulatory element analysis of clade C and F members implied that possible functions of PGs in specific biological responses contributed to their expansion and preservation. This work can improve the knowledge of PGs in plants generally and in grasses specifically and is beneficial to functional studies.

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

    PubMed

    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.

  13. Proteomics to study DNA-bound and chromatin-associated gene regulatory complexes

    PubMed Central

    Wierer, Michael; Mann, Matthias

    2016-01-01

    High-resolution mass spectrometry (MS)-based proteomics is a powerful method for the identification of soluble protein complexes and large-scale affinity purification screens can decode entire protein interaction networks. In contrast, protein complexes residing on chromatin have been much more challenging, because they are difficult to purify and often of very low abundance. However, this is changing due to recent methodological and technological advances in proteomics. Proteins interacting with chromatin marks can directly be identified by pulldowns with synthesized histone tails containing posttranslational modifications (PTMs). Similarly, pulldowns with DNA baits harbouring single nucleotide polymorphisms or DNA modifications reveal the impact of those DNA alterations on the recruitment of transcription factors. Accurate quantitation – either isotope-based or label free – unambiguously pinpoints proteins that are significantly enriched over control pulldowns. In addition, protocols that combine classical chromatin immunoprecipitation (ChIP) methods with mass spectrometry (ChIP-MS) target gene regulatory complexes in their in-vivo context. Similar to classical ChIP, cells are crosslinked with formaldehyde and chromatin sheared by sonication or nuclease digested. ChIP-MS baits can be proteins in tagged or endogenous form, histone PTMs, or lncRNAs. Locus-specific ChIP-MS methods would allow direct purification of a single genomic locus and the proteins associated with it. There, loci can be targeted either by artificial DNA-binding sites and corresponding binding proteins or via proteins with sequence specificity such as TAL or nuclease deficient Cas9 in combination with a specific guide RNA. We predict that advances in MS technology will soon make such approaches generally applicable tools in epigenetics. PMID:27402878

  14. B-cell lymphoma gene regulatory networks: biological consistency among inference methods.

    PubMed

    de Matos Simoes, Ricardo; Dehmer, Matthias; Emmert-Streib, Frank

    2013-01-01

    Despite the development of numerous gene regulatory network (GRN) inference methods in the last years, their application, usage and the biological significance of the resulting GRN remains unclear for our general understanding of large-scale gene expression data in routine practice. In our study, we conduct a structural and a functional analysis of B-cell lymphoma GRNs that were inferred using 3 mutual information-based GRN inference methods: C3Net, BC3Net and Aracne. From a comparative analysis on the global level, we find that the inferred B-cell lymphoma GRNs show major differences. However, on the edge-level and the functional-level-that are more important for our biological understanding-the B-cell lymphoma GRNs were highly similar among each other. Also, the ranks of the degree centrality values and major hub genes in the inferred networks are highly conserved as well. Interestingly, the major hub genes of all GRNs are associated with the G-protein-coupled receptor pathway, cell-cell signaling and cell cycle. This implies that hub genes of the GRNs can be highly consistently inferred with C3Net, BC3Net, and Aracne, representing prominent targets for signaling pathways. Finally, we describe the functional and structural relationship between C3Net, BC3Net and Aracne gene regulatory networks. Our study shows that these GRNs that are inferred from large-scale gene expression data are promising for the identification of novel candidate interactions and pathways that play a key role in the underlying mechanisms driving cancer hallmarks. Overall, our comparative analysis reveals that these GRNs inferred with considerably different inference methods contain large amounts of consistent, method independent, biological information.

  15. Data-based Reconstruction of Gene Regulatory Networks of Fungal Pathogens

    PubMed Central

    Guthke, Reinhard; Gerber, Silvia; Conrad, Theresia; Vlaic, Sebastian; Durmuş, Saliha; Çakır, Tunahan; Sevilgen, F. E.; Shelest, Ekaterina; Linde, Jörg

    2016-01-01

    In the emerging field of systems biology of fungal infection, one of the central roles belongs to the modeling of gene regulatory networks (GRNs). Utilizing omics-data, GRNs can be predicted by mathematical modeling. Here, we review current advances of data-based reconstruction of both small-scale and large-scale GRNs for human pathogenic fungi. The advantage of large-scale genome-wide modeling is the possibility to predict central (hub) genes and thereby indicate potential biomarkers and drug targets. In contrast, small-scale GRN models provide hypotheses on the mode of gene regulatory interactions, which have to be validated experimentally. Due to the lack of sufficient quantity and quality of both experimental data and prior knowledge about regulator–target gene relations, the genome-wide modeling still remains problematic for fungal pathogens. While a first genome-wide GRN model has already been published for Candida albicans, the feasibility of such modeling for Aspergillus fumigatus is evaluated in the present article. Based on this evaluation, opinions are drawn on future directions of GRN modeling of fungal pathogens. The crucial point of genome-wide GRN modeling is the experimental evidence, both used for inferring the networks (omics ‘first-hand’ data as well as literature data used as prior knowledge) and for validation and evaluation of the inferred network models. PMID:27148247

  16. Directed partial correlation: inferring large-scale gene regulatory network through induced topology disruptions.

    PubMed

    Yuan, Yinyin; Li, Chang-Tsun; Windram, Oliver

    2011-04-06

    Inferring regulatory relationships among many genes based on their temporal variation in transcript abundance has been a popular research topic. Due to the nature of microarray experiments, classical tools for time series analysis lose power since the number of variables far exceeds the number of the samples. In this paper, we describe some of the existing multivariate inference techniques that are applicable to hundreds of variables and show the potential challenges for small-sample, large-scale data. We propose a directed partial correlation (DPC) method as an efficient and effective solution to regulatory network inference using these data. Specifically for genomic data, the proposed method is designed to deal with large-scale datasets. It combines the efficiency of partial correlation for setting up network topology by testing conditional independence, and the concept of Granger causality to assess topology change with induced interruptions. The idea is that when a transcription factor is induced artificially within a gene network, the disruption of the network by the induction signifies a genes role in transcriptional regulation. The benchmarking results using GeneNetWeaver, the simulator for the DREAM challenges, provide strong evidence of the outstanding performance of the proposed DPC method. When applied to real biological data, the inferred starch metabolism network in Arabidopsis reveals many biologically meaningful network modules worthy of further investigation. These results collectively suggest DPC is a versatile tool for genomics research. The R package DPC is available for download (http://code.google.com/p/dpcnet/).

  17. Regulatory elements in the first intron contribute to transcriptional regulation of the beta 3 tubulin gene by 20-hydroxyecdysone in Drosophila Kc cells.

    PubMed Central

    Bruhat, A; Tourmente, S; Chapel, S; Sobrier, M L; Couderc, J L; Dastugue, B

    1990-01-01

    We have studied the transcriptional regulation of the beta 3 tubulin gene by the steroid hormone 20-hydroxyecdysone (20-OH-E) in Drosophila Kc cells. A series of hybrid genes with varying tubulin gene lengths driving the bacterial chloramphenicol acetyl transferase (CAT) gene were constructed. The promoter activity was assayed after transient expression in Kc cells, in the presence or absence of 20-OH-E. We find that 0.91Kb upstream from the transcription start site contain one or several hormone independent positive cis-acting elements, responsible for the constitutive expression of the beta 3 tubulin gene. In the large (4.5 Kb) first intron of this gene, we identified additional hormone dependent negative and positive regulatory elements, which can act in both directions and in a position-independence manner. Then, the negative intron element(s), which repress the transcription in the absence of 20-OH-E has characteristics of silencer. Images PMID:2349088

  18. Association Mapping of Cell Wall Synthesis Regulatory Genes and Cell Wall Quality in Switchgrass

    SciTech Connect

    Bartley, Laura; Wu, Y.; Zhu, L.; Brummer, E. C.; Saha, M.

    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

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

    PubMed Central

    Weston, Cody; 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). PMID:27898674

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

    PubMed

    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).

  1. Integrative Gene Regulatory Network Analysis Reveals Light-Induced Regional Gene Expression Phase Shift Programs in the Mouse Suprachiasmatic Nucleus

    PubMed Central

    Zhu, Haisun; Vadigepalli, Rajanikanth; Rafferty, Rachel; Gonye, Gregory E.; Weaver, David R.; Schwaber, James S.

    2012-01-01

    We use the multigenic pattern of gene expression across suprachiasmatic nuclei (SCN) regions and time to understand the dynamics within the SCN in response to a circadian phase-resetting light pulse. Global gene expression studies of the SCN indicate that circadian functions like phase resetting are complex multigenic processes. While the molecular dynamics of phase resetting are not well understood, it is clear they involve a “functional gene expression program”, e.g., the coordinated behavior of functionally related genes in space and time. In the present study we selected a set of 89 of these functionally related genes in order to further understand this multigenic program. By use of high-throughput qPCR we studied 52 small samples taken by anatomically precise laser capture from within the core and shell SCN regions, and taken at time points with and without phase resetting light exposure. The results show striking regional differences in light response to be present in the mouse SCN. By using network-based analyses, we are able to establish a highly specific multigenic correlation between genes expressed in response to light at night and genes normally activated during the day. The light pulse triggers a complex and highly coordinated network of gene regulation. The largest differences marking neuroanatomical location are in transmitter receptors, and the largest time-dependent differences occur in clock-related genes. Nighttime phase resetting appears to recruit transcriptional regulatory processes normally active in the day. This program, or mechanism, causes the pattern of core region gene expression to transiently shift to become more like that of the shell region. PMID:22662235

  2. Random transposon mutagenesis of the Saccharopolyspora erythraea genome reveals additional genes influencing erythromycin biosynthesis

    PubMed Central

    Fedashchin, Andrij; Cernota, William H.; Gonzalez, Melissa C.; Leach, Benjamin I.; Kwan, Noelle; Wesley, Roy K.; Weber, J. Mark

    2015-01-01

    A single cycle of strain improvement was performed in Saccharopolyspora erythraea mutB and 15 genotypes influencing erythromycin production were found. Genotypes generated by transposon mutagenesis appeared in the screen at a frequency of ∼3%. Mutations affecting central metabolism and regulatory genes were found, as well as hydrolases, peptidases, glycosyl transferases and unknown genes. Only one mutant retained high erythromycin production when scaled-up from micro-agar plug fermentations to shake flasks. This mutant had a knockout of the cwh1 gene (SACE_1598), encoding a cell-wall-associated hydrolase. The cwh1 knockout produced visible growth and morphological defects on solid medium. This study demonstrated that random transposon mutagenesis uncovers strain improvement-related genes potentially useful for strain engineering. PMID:26468041

  3. Dynamic and distinct histone modifications modulate the expression of key adipogenesis regulatory genes.

    PubMed

    Zhang, Qiongyi; Ramlee, Muhammad Khairul; Brunmeir, Reinhard; Villanueva, Claudio J; Halperin, Daniel; Xu, Feng

    2012-12-01

    Histone modifications and their modifying enzymes are fundamentally involved in the epigenetic regulation of adipogenesis. This study aimed to define the roles of various histone modifications and their "division of labor" in fat cell differentiation. To achieve these goals, we examined the distribution patterns of eight core histone modifications at five key adipogenic regulatory genes, Pref-1, C/EBPβ, C/EBPα, PPARγ2 and aP2, during the adipogenesis of C3H 10T1/2 mouse mesenchymal stem cells (MSCs) and 3T3-L1 preadipocytes. We found that the examined histone modifications are globally stable throughout adipogenesis but show distinct and highly dynamic distribution patterns at specific genes. For example, the Pref-1 gene has lower levels of active chromatin markers and significantly higher H3 K27 tri-methylation in MSCs compared with committed preadipocytes; the C/EBPβ gene is enriched in active chromatin markers at its 3'-UTR; the C/EBPα gene is predominantly marked by H3 K27 tri-methylation in adipogenic precursor cells, and this repressive marker decreases dramatically upon induction; the PPARγ2 and aP2 genes show increased histone acetylation on both H3 and H4 tails during adipogenesis. Further functional studies revealed that the decreased level of H3 K27 tri-methylation leads to de-repression of Pref-1 gene, while the increased level of histone acetylation activates the transcription of PPARγ2 and aP2 genes. Moreover, the active histone modification-marked 3'-UTR of C/EBPβ gene was demonstrated as a strong enhancer element by luciferase assay. Our results indicate that histone modifications are gene-specific at adipogenic regulator genes, and they play distinct roles in regulating the transcriptional network during adipogenesis.

  4. Cardiac-targeted delivery of regulatory RNA molecules and genes for the treatment of heart failure

    PubMed Central

    Poller, Wolfgang; Hajjar, Roger; Schultheiss, Heinz-Peter; Fechner, Henry

    2010-01-01

    Ribonucleic acid (RNA) in its many facets of structure and function is becoming more fully understood, and, therefore, it is possible to design and use RNAs as valuable tools in molecular biology and medicine. Understanding of the role of RNAs within the cell has changed dramatically during the past few years. Therapeutic strategies based on non-coding regulatory RNAs include RNA interference (RNAi) for the silencing of specific genes, and microRNA (miRNA) modulations to alter complex gene expression patterns. Recent progress has allowed the targeting of therapeutic RNAi to the heart for the treatment of heart failure, and we discuss current strategies in this field. Owing to the peculiar biochemical properties of small RNA molecules, the actual therapeutic translation of findings in vitro or in cell cultures is more demanding than with small molecule drugs or proteins. The critical requirement for animal studies after pre-testing of RNAi tools in vitro likewise applies for miRNA modulations, which also have complex consequences for the recipient that are dependent on stability and distribution of the RNA tools. Problems in the field that are not yet fully solved are the prediction of targets and specificity of the RNA tools as well as their tissue-specific and regulatable expression. We discuss analogies and differences between regulatory RNA therapy and classical gene therapy, since recent breakthroughs in vector technology are of importance for both. Recent years have witnessed parallel progress in the fields of gene-based and regulatory RNA-based therapies that are likely to significantly expand the cardiovascular therapeutic repertoire within the next decade. PMID:20176815

  5. Allelic polymorphism in transcriptional regulatory regions of HLA-DQB genes

    PubMed Central

    1991-01-01

    Class II genes of the human major histocompatibility complex (MHC) are highly polymorphic. Allelic variation of structural genes provides diversity in immune cell interactions, contributing to the formation of the T cell repertoire and to susceptibility to certain autoimmune diseases. We now report that allelic polymorphism also exists in the promoter and upstream regulatory regions (URR) of human histocompatibility leukocyte antigen (HLA) class II genes. Nucleotide sequencing of these regulatory regions of seven alleles of the DQB locus reveals a number of allele-specific polymorphisms, some of which lie in functionally critical consensus regions thought to be highly conserved in class II promoters. These sequence differences also correspond to allelic differences in binding of nuclear proteins to the URR. Fragments of the URR of two DQB alleles were analyzed for binding to nuclear proteins extracted from human B lymphoblastoid cell lines (B- LCL). Gel retardation assays showed substantially different banding patterns to the two promoters, including prominent variation in nuclear protein binding to the partially conserved X box regions and a novel upstream polymorphic sequence element. Comparison of these two polymorphic alleles in a transient expression system demonstrated a marked difference in their promoter strengths determined by relative abilities to initiate transcription of the chloramphenicol acetyltransferase reporter gene in human B-LCL. Shuttling of URR sequences between alleles showed that functional variation corresponded to both the X box and upstream sequence polymorphic sites. These findings identify an important source of MHC class II diversity, and suggest the possibility that such regulatory region polymorphisms may confer allelic differences in expression, inducibility, and/or tissue specificity of class II molecules. PMID:1985121

  6. Genesis and regulatory wiring of retroelement-derived domesticated genes: a phylogenomic perspective.

    PubMed

    Kokošar, Janez; Kordiš, Dušan

    2013-05-01

    Molecular domestications of transposable elements have occurred repeatedly during the evolution of eukaryotes. Vertebrates, especially mammals, possess numerous single copy domesticated genes (DGs) that have originated from the intronless multicopy transposable elements. However, the origin and evolution of the retroelement-derived DGs (RDDGs) that originated from Metaviridae has been only partially elucidated, due to absence of genome data or to limited analysis of a single family of DGs. We traced the genesis and regulatory wiring of the Metaviridae-derived DGs through phylogenomic analysis, using whole-genome information from more than 90 chordate genomes. Phylogenomic analysis of these DGs in chordate genomes provided direct evidence that major diversification has occurred in the ancestor of placental mammals. Mammalian RDDGs have been shown to originate in several steps by independent domestication events and to diversify later by gene duplications. Analysis of syntenic loci has shown that diverse RDDGs and their chromosomal positions were fully established in the ancestor of placental mammals. By analysis of active Metaviridae lineages in amniotes, we have demonstrated that RDDGs originated from retroelement remains. The chromosomal gene movements of RDDGs were highly dynamic only in the ancestor of placental mammals. During the domestication process, de novo acquisition of regulatory regions is shown to be a prerequisite for the survival of the DGs. The origin and evolution of de novo acquired promoters and untranslated regions in diverse mammalian RDDGs have been explained by comparative analysis of orthologous gene loci. The origin of placental mammal-specific innovations and adaptations, such as placenta and newly evolved brain functions, was most probably connected to the regulatory wiring of DGs and their rapid fixation in the ancestor of placental mammals.

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

    PubMed

    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.

  8. Redox proteins of hydroxylating bacterial dioxygenases establish a regulatory cascade that prevents gratuitous induction of tetralin biodegradation genes.

    PubMed

    Ledesma-García, Laura; Sánchez-Azqueta, Ana; Medina, Milagros; Reyes-Ramírez, Francisca; Santero, Eduardo

    2016-03-31

    Bacterial dioxygenase systems are multicomponent enzymes that catalyze the initial degradation of many environmentally hazardous compounds. In Sphingopyxis granuli strain TFA tetralin dioxygenase hydroxylates tetralin, an organic contaminant. It consists of a ferredoxin reductase (ThnA4), a ferredoxin (ThnA3) and a oxygenase (ThnA1/ThnA2), forming a NAD(P)H-ThnA4-ThnA3-ThnA1/ThnA2 electron transport chain. ThnA3 has also a regulatory function since it prevents expression of tetralin degradation genes (thn) in the presence of non-metabolizable substrates of the catabolic pathway. This role is of physiological relevance since avoids gratuitous and wasteful production of catabolic enzymes. Our hypothesis for thn regulation implies that ThnA3 exerts its action by diverting electrons towards the regulator ThnY, an iron-sulfur flavoprotein that together with the transcriptional activator ThnR is necessary for thn gene expression. Here we analyze electron transfer among ThnA4, ThnA3 and ThnY by using stopped-flow spectrophotometry and determination of midpoint reduction potentials. Our results indicate that when accumulated in its reduced form ThnA3 is able to fully reduce ThnY. In addition, we have reproduced in vitro the regulatory circuit in the proposed physiological direction, NAD(P)H-ThnA4-ThnA3-ThnY. ThnA3 represents an unprecedented way of communication between a catabolic pathway and its regulatory system to prevent gratuitous induction.

  9. Redox proteins of hydroxylating bacterial dioxygenases establish a regulatory cascade that prevents gratuitous induction of tetralin biodegradation genes

    PubMed Central

    Ledesma-García, Laura; Sánchez-Azqueta, Ana; Medina, Milagros; Reyes-Ramírez, Francisca; Santero, Eduardo

    2016-01-01

    Bacterial dioxygenase systems are multicomponent enzymes that catalyze the initial degradation of many environmentally hazardous compounds. In Sphingopyxis granuli strain TFA tetralin dioxygenase hydroxylates tetralin, an organic contaminant. It consists of a ferredoxin reductase (ThnA4), a ferredoxin (ThnA3) and a oxygenase (ThnA1/ThnA2), forming a NAD(P)H–ThnA4–ThnA3–ThnA1/ThnA2 electron transport chain. ThnA3 has also a regulatory function since it prevents expression of tetralin degradation genes (thn) in the presence of non-metabolizable substrates of the catabolic pathway. This role is of physiological relevance since avoids gratuitous and wasteful production of catabolic enzymes. Our hypothesis for thn regulation implies that ThnA3 exerts its action by diverting electrons towards the regulator ThnY, an iron-sulfur flavoprotein that together with the transcriptional activator ThnR is necessary for thn gene expression. Here we analyze electron transfer among ThnA4, ThnA3 and ThnY by using stopped-flow spectrophotometry and determination of midpoint reduction potentials. Our results indicate that when accumulated in its reduced form ThnA3 is able to fully reduce ThnY. In addition, we have reproduced in vitro the regulatory circuit in the proposed physiological direction, NAD(P)H–ThnA4–ThnA3–ThnY. ThnA3 represents an unprecedented way of communication between a catabolic pathway and its regulatory system to prevent gratuitous induction. PMID:27030382

  10. Polymorphism in the upstream regulatory region of DQA1 gene in the Italian population.

    PubMed

    Petronzelli, F; Kimura, A; Ferrante, P; Mazzilli, M C

    1995-04-01

    Polymorphism in the 5'-upstream regulatory region of the DQA1 gene has been recently described. Using PCR-SSO method and SSCP analysis we have investigated this polymorphism in a group of 111 Italian blood donors which had been oligotyped for DRB1, DQA1 and DQB1 genes. Eight allelic variants were detected. Looking at the relationships among QAP sequences and DQA1 and DRB1 genes, three alternative situations were found: 1. a one-to-one relation between QAP and DQA1 alleles, independently of the other class II genes; 2. the same QAP allele in association with different DQA1-DRB1 haplotypes; 3. the same DQA1 allele with different QAP sequences according to the DRB1 specificity. No unexpected associations with DQB1 gene were found. These results must be interpreted considering that DQA1 and DRB1 genes are transcribed in opposite directions so that the promoter region of DQA1 gene lies between DQA1 and DRB1, close to the former but several hundreds kb away from the latter.

  11. Structure and function of gene regulatory networks associated with worker sterility in honeybees.

    PubMed

    Sobotka, Julia A; Daley, Mark; Chandrasekaran, Sriram; Rubin, Benjamin D; Thompson, Graham J

    2016-03-01

    A characteristic of eusocial bees is a reproductive division of labor in which one or a few queens monopolize reproduction, while her worker daughters take on reproductively altruistic roles within the colony. The evolution of worker reproductive altruism involves indirect selection for the coordinated expression of genes that regulate personal reproduction, but evidence for this type of selection remains elusive. In this study, we tested whether genes coexpressed under queen-induced worker sterility show evidence of adaptive organization within a model brain transcriptional regulatory network (TRN). If so, this structured pattern would imply that indirect selection on nonreproductive workers has influenced the functional organization of genes within the network, specifically to regulate the expression of sterility. We found that literature-curated sets of candidate genes for sterility, ranging in size from 18 to 267, show strong evidence of clustering within the three-dimensional space of the TRN. This finding suggests that our candidate sets of genes for sterility form functional modules within the living bee brain's TRN. Moreover, these same gene sets colocate to a single, albeit large, region of the TRN's topology. This spatially organized and convergent pattern contrasts with a null expectation for functionally unrelated genes to be haphazardly distributed throughout the network. Our meta-genomic analysis therefore provides first evidence for a truly "social transcriptome" that may regulate the conditional expression of honeybee worker sterility.

  12. Gene regulatory changes in yeast during life extension by nutrient limitation.

    PubMed

    Wang, Jinqing; Jiang, James C; Jazwinski, S Michal

    2010-08-01

    Genetic analyses aimed at identification of the pathways and downstream effectors of calorie restriction (CR) in the yeast Saccharomyces cerevisiae suggest the importance of central metabolism for the extension of replicative life span by CR. However, the limited gene expression studies to date are not informative, because they have been conducted using cells grown in batch culture which markedly departs from the conditions under which yeasts are grown during life span determinations. In this study, we have examined the gene expression changes that occur during either glucose limitation or elimination of nonessential-amino acids, both of which enhance yeast longevity, culturing cells in a chemostat at equilibrium, which closely mimics conditions they encounter during life span determinations. Expression of 59 genes was examined quantitatively by real-time, reverse transcriptase polymerase chain reaction (qRT-PCR), and the physiological state of the cultures was monitored. Extensive gene expression changes were detected, some of which were common to both CR regimes. The most striking of these was the induction of tricarboxylic acid (TCA) cycle and retrograde response target genes, which appears to be at least partially due to the up-regulation of the HAP4 gene. These gene regulatory events portend an increase in the generation of biosynthetic intermediates necessary for the production of daughter cells, which is the measure of yeast replicative life span.

  13. Identification of co-expression gene networks, regulatory genes and pathways for obesity based on adipose tissue RNA Sequencing in a porcine model

    PubMed Central

    2014-01-01

    Background Obesity is a complex metabolic condition in strong association with various diseases, like type 2 diabetes, resulting in major public health and economic implications. Obesity is the result of environmental and genetic factors and their interactions, including genome-wide genetic interactions. Identification of co-expressed and regulatory genes in RNA extracted from relevant tissues representing lean and obese individuals provides an entry point for the identification of genes and pathways of importance to the development of obesity. The pig, an omnivorous animal, is an excellent model for human obesity, offering the possibility to study in-depth organ-level transcriptomic regulations of obesity, unfeasible in humans. Our aim was to reveal adipose tissue co-expression networks, pathways and transcriptional regulations of obesity using RNA Sequencing based systems biology approaches in a porcine model. Methods We selected 36 animals for RNA Sequencing from a previously created F2 pig population representing three extreme groups based on their predicted genetic risks for obesity. We applied Weighted Gene Co-expression Network Analysis (WGCNA) to detect clusters of highly co-expressed genes (modules). Additionally, regulator genes were detected using Lemon-Tree algorithms. Results WGCNA revealed five modules which were strongly correlated with at least one obesity-related phenotype (correlations ranging from -0.54 to 0.72, P < 0.001). Functional annotation identified pathways enlightening the association between obesity and other diseases, like osteoporosis (osteoclast differentiation, P = 1.4E-7), and immune-related complications (e.g. Natural killer cell mediated cytotoxity, P = 3.8E-5; B cell receptor signaling pathway, P = 7.2E-5). Lemon-Tree identified three potential regulator genes, using confident scores, for the WGCNA module which was associated with osteoclast differentiation: CCR1, MSR1 and SI1 (probability scores respectively 95.30, 62.28, and

  14. Ethanol utilization regulatory protein: profile alignments give no evidence of origin through aldehyde and alcohol dehydrogenase gene fusion.

    PubMed Central

    Nicholas, H. B.; Persson, B.; Jörnvall, H.; Hempel, J.

    1995-01-01

    The suggestion that the ethanol regulatory protein from Aspergillus has its evolutionary origin in a gene fusion between aldehyde and alcohol dehydrogenase genes (Hawkins AR, Lamb HK, Radford A, Moore JD, 1994, Gene 146:145-158) has been tested by profile analysis with aldehyde and alcohol dehydrogenase family profiles. We show that the degree and kind of similarity observed between these profiles and the ethanol regulatory protein sequence is that expected from random sequences of the same composition. This level of similarity fails to support the suggested gene fusion. PMID:8580855

  15. Gene structure, regulatory control, and evolution of black widow venom latrotoxins

    PubMed Central

    Bhere, Kanaka Varun; Haney, Robert A.; Ayoub, Nadia A.; Garb, Jessica E.

    2014-01-01

    Black widow venom contains α-latrotoxin, infamous for causing intense pain. Combining 33 kb of Latrodectus hesperus genomic DNA with RNA-Seq, we characterized the α-latrotoxin gene and discovered a paralog, 4.5 kb downstream. Both paralogs exhibit venom gland specific transcription, and may be regulated post-transcriptionally via musashi-like proteins. A 4 kb intron interrupts the α-latrotoxin coding sequence, while a 10 kb intron in the 3′ UTR of the paralog may cause nonsense-mediated decay. Phylogenetic analysis confirms these divergent latrotoxins diversified through recent tandem gene duplications. Thus, latrotoxin genes have more complex structures, regulatory controls, and sequence diversity than previously proposed. PMID:25217831

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

    PubMed Central

    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

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

    PubMed

    Fan, Yue; Wang, Xiao; Peng, Qinke

    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.

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

    PubMed

    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

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

    PubMed Central

    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

  20. Characterization of the human glycogenin-1 gene: identification of a muscle-specific regulatory domain.

    PubMed

    van Maanen, M H; Fournier, P A; Palmer, T N; Abraham, L J

    1999-07-08

    The de-novo synthesis of glycogen is now known to involve a novel class of self-glucosylating protein primers. In mammalian skeletal muscle, glycogenin-1 is the protein responsible for this initiation step. Northern blot analysis revealed that glycogenin-1 gene transcription is differentially regulated in the C2C12 mouse muscle cell line. To define the regulatory elements that control expression of the glycogenin-1 gene, we have cloned and characterized the genomic structure of the human glycogenin-1 gene and its promoter region. This gene consists of seven exons and six introns, and spans over 13kb. Transcription of human glycogenin-1 is initiated at two major sites, 80 and 86bp upstream from the initiation of translation codon. Nucleotide sequence analysis of 2.1kb of the 5'-flanking region revealed the proximal promoter contains both a TATA box and two putative Sp1 binding sites located in a CpG island. There are numerous binding sites for developmental and cell-type-specific transcription factors, including AP-1, AP-2, GATA, and several potential Oct 1 binding domains. There are also nine consensus E-boxes that bind the basic helix-loop-helix family of muscle-specific transcription factors. The transcriptional activity of the glycogenin-1 gene was investigated by transient transfection of the 5'-flanking region in HepG2 cells and C2C12 myoblasts and myotubes. These results permitted the definition of a minimal 232bp promoter fragment that is responsible for basal level transcription in a cell-type-independent manner. Furthermore, we have identified a regulatory region located between -2076 and -1736 of the 5'-flanking region of the human glycogenin-1 gene that allows myotube-specific expression in C2C12 cells.

  1. Role of Nhp6 and Hmo1 in SWI/SNF occupancy and nucleosome landscape at gene regulatory regions.

    PubMed

    Hepp, Matias I; Smolle, Michaela; Gidi, Cristian; Amigo, Roberto; Valenzuela, Nicole; Arriagada, Axel; Maureira, Alejandro; Gogol, Madelaine M; Torrejón, Marcela; Workman, Jerry L; Gutiérrez, José L

    2017-03-01

    Diverse chromatin modifiers are involved in regulation of gene expression at the level of transcriptional regulation. Among these modifiers are ATP-dependent chromatin remodelers, where the SWI/SNF complex is the founding member. It has been observed that High Mobility Group (HMG) proteins can influence the activity of a number of these chromatin remodelers. In this context, we have previously demonstrated that the yeast HMG proteins Nhp6 and Hmo1 can stimulate SWI/SNF activity. Here, we studied the genome-wide binding patterns of Nhp6, Hmo1 and the SWI/SNF complex, finding that most of gene promoters presenting high occupancy of this complex also display high enrichment of these HMG proteins. Using deletion mutant strains we demonstrate that binding of SWI/SNF is significantly reduced at numerous genomic locations by deletion of NHP6 and/or deletion of HMO1. Moreover, alterations in the nucleosome landscape take place at gene promoters undergoing reduced SWI/SNF binding. Additional analyses show that these effects also correlate with alterations in transcriptional activity. Our results suggest that, besides the ability to stimulate SWI/SNF activity, these HMG proteins are able to assist the loading of this complex onto gene regulatory regions.

  2. A regulatory sequence from the retinoid X receptor γ gene directs expression to horizontal cells and photoreceptors in the embryonic chicken retina

    PubMed Central

    Blixt, Maria K. E.

    2016-01-01

    Purpose Combining techniques of episomal vector gene-specific Cre expression and genomic integration using the piggyBac transposon system enables studies of gene expression–specific cell lineage tracing in the chicken retina. In this work, we aimed to target the retinal horizontal cell progenitors. Methods A 208 bp gene regulatory sequence from the chicken retinoid X receptor γ gene (RXRγ208) was used to drive Cre expression. RXRγ is expressed in progenitors and photoreceptors during development. The vector was combined with a piggyBac “donor” vector containing a floxed STOP sequence followed by enhanced green fluorescent protein (EGFP), as well as a piggyBac helper vector for efficient integration into the host cell genome. The vectors were introduced into the embryonic chicken retina with in ovo electroporation. Tissue electroporation targets specific developmental time points and in specific structures. Results Cells that drove Cre expression from the regulatory RXRγ208 sequence excised the floxed STOP-sequence and expressed GFP. The approach generated a stable lineage with robust expression of GFP in retinal cells that have activated transcription from the RXRγ208 sequence. Furthermore, GFP was expressed in cells that express horizontal or photoreceptor markers when electroporation was performed between developmental stages 22 and 28. Electroporation of a stage 12 optic cup gave multiple cell types in accordance with RXRγ gene expression in the early retina. Conclusions In this study, we describe an easy, cost-effective, and time-efficient method for testing regulatory sequences in general. More specifically, our results open up the possibility for further studies of the RXRγ-gene regulatory network governing the formation of photoreceptor and horizontal cells. In addition, the method presents approaches to target the expression of effector genes, such as regulators of cell fate or cell cycle progression, to these cells and their progenitor. PMID

  3. Identification of positive and negative transcriptional regulatory elements of the rabbit angiotensin-converting enzyme gene.

    PubMed Central

    Goraya, T Y; Kessler, S P; Kumar, R S; Douglas, J; Sen, G C

    1994-01-01

    The two tissue-specific mRNAs encoding the isozymes of rabbit angiotensin-converting enzyme (ACE) are generated from the same gene by alternative choice of two transcription initiation sites 5.7 kb apart. In the current study, we have characterized the regulatory sites controlling the transcription of the larger pulmonary isozyme mRNA. For this purpose, reporter genes driven by varying lengths of upstream region of the ACE gene were transfected into ACE-producing cells. Our results demonstrated that the transcription of this gene is primarily driven by positive elements within the first 274 bp DNA upstream of the transcription initiation site. The reporter gene driven by this region was expressed in two ACE-producing cells but not in two ACE-non-producing cells thereby establishing its tissue specificity. Our experiments also revealed the existence of a strong negative element located between -692 and -610 positions. This element suppressed the expression of the reporter gene in a dose-dependent and position and orientation-independent fashion thus suggesting that it is a true silencer element. It could also repress the expression of a reporter gene driven by the heterologous strong promoter of the beta-actin gene. The repressing effects of the negative element could be partially overcome by cotransfecting the isolated negative element along with the reporter gene containing the negative element. This result was possibly due to the functional removal of a limiting trans-acting factor which binds to this element. Electrophoretic mobility shift assays revealed that the negative element can form several complexes with proteins present in the nuclear extract of an ACE-producing cell line. At least part of the negative element is strongly conserved in the upstream regions of the human and mouse ACE genes. Images PMID:8165133

  4. A comparative analytical assay of gene regulatory networks inferred using microarray and RNA-seq datasets

    PubMed Central

    Izadi, Fereshteh; Zarrini, Hamid Najafi; Kiani, Ghaffar; Jelodar, Nadali Babaeian

    2016-01-01

    A Gene Regulatory Network (GRN) is a collection of interactions between molecular regulators and their targets in cells governing gene expression level. Omics data explosion generated from high-throughput genomic assays such as microarray and RNA-Seq technologies and the emergence of a number of pre-processing methods demands suitable guidelines to determine the impact of transcript data platforms and normalization procedures on describing associations in GRNs. In this study exploiting publically available microarray and RNA-Seq datasets and a gold standard of transcriptional interactions in Arabidopsis, we performed a comparison between six GRNs derived by RNA-Seq and microarray data and different normalization procedures. As a result we observed that compared algorithms were highly data-specific and Networks reconstructed by RNA-Seq data revealed a considerable accuracy against corresponding networks captured by microarrays. Topological analysis showed that GRNs inferred from two platforms were similar in several of topological features although we observed more connectivity in RNA-Seq derived genes network. Taken together transcriptional regulatory networks obtained by Robust Multiarray Averaging (RMA) and Variance-Stabilizing Transformed (VST) normalized data demonstrated predicting higher rate of true edges over the rest of methods used in this comparison. PMID:28293077

  5. Bivalent chromatin marks developmental regulatory genes in the mouse embryonic germline in vivo.

    PubMed

    Sachs, Michael; Onodera, Courtney; Blaschke, Kathryn; Ebata, Kevin T; Song, Jun S; Ramalho-Santos, Miguel

    2013-06-27

    Developmental regulatory genes have both activating (H3K4me3) and repressive (H3K27me3) histone modifications in embryonic stem cells (ESCs). This bivalent configuration is thought to maintain lineage commitment programs in a poised state. However, establishing physiological relevance has been complicated by the high number of cells required for chromatin immunoprecipitation (ChIP). We developed a low-cell-number chromatin immunoprecipitation (low-cell ChIP) protocol to investigate the chromatin of mouse primordial germ cells (PGCs). Genome-wide analysis of embryonic day 11.5 (E11.5) PGCs revealed H3K4me3/H3K27me3 bivalent domains highly enriched at developmental regulatory genes in a manner remarkably similar to ESCs. Developmental regulators remain bivalent and transcriptionally silent through the initiation of sexual differentiation at E13.5. We also identified >2,500 "orphan" bivalent domains that are distal to known genes and expressed in a tissue-specific manner but silent in PGCs. Our results demonstrate the existence of bivalent domains in the germline and raise the possibility that the somatic program is continuously maintained as bivalent, potentially imparting transgenerational epigenetic inheritance.

  6. Relationships between probabilistic Boolean networks and dynamic Bayesian networks as models of gene regulatory networks

    PubMed Central

    Lähdesmäki, Harri; Hautaniemi, Sampsa; Shmulevich, Ilya; Yli-Harja, Olli

    2006-01-01

    A significant amount of attention has recently been focused on modeling of gene regulatory networks. Two frequently used large-scale modeling frameworks are Bayesian networks (BNs) and Boolean networks, the latter one being a special case of its recent stochastic extension, probabilistic Boolean networks (PBNs). PBN is a promising model class that generalizes the standard rule-based interactions of Boolean networks into the stochastic setting. Dynamic Bayesian networks (DBNs) is a general and versatile model class that is able to represent complex temporal stochastic processes and has also been proposed as a model for gene regulatory systems. In this paper, we concentrate on these two model classes and demonstrate that PBNs and a certain subclass of DBNs can represent the same joint probability distribution over their common variables. The major benefit of introducing the relationships between the models is that it opens up the possibility of applying the standard tools of DBNs to PBNs and vice versa. Hence, the standard learning tools of DBNs can be applied in the context of PBNs, and the inference methods give a natural way of handling the missing values in PBNs which are often present in gene expression measurements. Conversely, the tools for controlling the stationary behavior of the networks, tools for projecting networks onto sub-networks, and efficient learning schemes can be used for DBNs. In other words, the introduced relationships between the models extend the collection of analysis tools for both model classes. PMID:17415411

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

    PubMed

    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.

  8. Tumor-suppressor Genes, Cell Cycle Regulatory Checkpoints, and the Skin

    PubMed Central

    Velez, Ana Maria Abreu; Howard, Michael S.

    2015-01-01

    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. PMID:26110128

  9. Supervised, semi-supervised and unsupervised inference of gene regulatory networks.

    PubMed

    Maetschke, Stefan R; Madhamshettiwar, Piyush B; Davis, Melissa J; Ragan, Mark A

    2014-03-01

    Inference of gene regulatory network from expression data is a challenging task. Many methods have been developed to t